272 results on '"Kumar, Harish"'
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2. Crafting Inclusive Marketing Campaigns: Insights and Influential Factors in the Indian Context.
- Author
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Upadhyay, Saurabh, Tuli, Nikhita, and Kumar, Harish
- Abstract
With increasing diversity of consumers in the marketplace, marketers have begun to embrace inclusive marketing practices. However, there is still a lack of research on the topic, making it difficult for managers to understand how to design and execute effective campaigns. This study aims to fill this gap by identifying the key factors that contribute toward an impactful inclusive marketing campaign. The study used a sequential mixed-methods approach and first conducted interviews with 29 LGBTQIA+ and non-LGBTQ consumers to gain insights into their perceptions of effective inclusive campaigns. In the study's second phase, ten industry experts provided inputs for the Fuzzy DEMATEL method to identify critical factors for an effective campaign. The findings revealed seven essential factors: social acceptance of the community, use of community-specific symbols, authentic communication about community issues, top management's approach, inclusive hiring practices, brand history, and legal market structure, which were then grouped into social, communication-related, brand-related, organization-specific, and other macro-level categories. The study fills an important gap in the inclusive marketing literature and can serve as a practical guide for marketers to design and implement inclusive campaigns. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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3. Efficient Finite Difference WENO Scheme for Hyperbolic Systems with Non-conservative Products
- Author
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Balsara, Dinshaw S., Bhoriya, Deepak, Shu, Chi-Wang, and Kumar, Harish
- Abstract
Higher order finite difference weighted essentially non-oscillatory (WENO) schemes have been constructed for conservation laws. For multidimensional problems, they offer a high order accuracy at a fraction of the cost of a finite volume WENO or DG scheme of the comparable accuracy. This makes them quite attractive for several science and engineering applications. But, to the best of our knowledge, such schemes have not been extended to non-linear hyperbolic systems with non-conservative products. In this paper, we perform such an extension which improves the domain of the applicability of such schemes. The extension is carried out by writing the scheme in fluctuation form. We use the HLLI Riemann solver of Dumbser and Balsara (J. Comput. Phys. 304: 275–319, 2016) as a building block for carrying out this extension. Because of the use of an HLL building block, the resulting scheme has a proper supersonic limit. The use of anti-diffusive fluxes ensures that stationary discontinuities can be preserved by the scheme, thus expanding its domain of the applicability. Our new finite difference WENO formulation uses the same WENO reconstruction that was used in classical versions, making it very easy for users to transition over to the present formulation. For conservation laws, the new finite difference WENO is shown to perform as well as the classical version of finite difference WENO, with two major advantages: (i) It can capture jumps in stationary linearly degenerate wave families exactly. (ii) It only requires the reconstruction to be applied once. Several examples from hyperbolic PDE systems with non-conservative products are shown which indicate that the scheme works and achieves its design order of the accuracy for smooth multidimensional flows. Stringent Riemann problems and several novel multidimensional problems that are drawn from compressible Baer-Nunziato multiphase flow, multiphase debris flow and two-layer shallow water equations are also shown to document the robustness of the method. For some test problems that require well-balancing we have even been able to apply the scheme without any modification and obtain good results. Many useful PDEs may have stiff relaxation source terms for which the finite difference formulation of WENO is shown to provide some genuine advantages.
- Published
- 2024
- Full Text
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4. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
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Schumacher, Austin E, Kyu, Hmwe Hmwe, Aali, Amirali, Abbafati, Cristiana, Abbas, Jaffar, Abbasgholizadeh, Rouzbeh, Abbasi, Madineh Akram, Abbasian, Mohammadreza, Abd ElHafeez, Samar, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdelwahab, Ahmed, Abdollahi, Mohammad, Abdoun, Meriem, Abdullahi, Auwal, Abdurehman, Ame Mehadi, Abebe, Mesfin, Abedi, Aidin, Abedi, Armita, Abegaz, Tadesse M, Abeldaño Zuñiga, Roberto Ariel, Abhilash, E S, Abiodun, Olugbenga Olusola, Aboagye, Richard Gyan, Abolhassani, Hassan, Abouzid, Mohamed, Abreu, Lucas Guimarães, Abrha, Woldu Aberhe, Abrigo, Michael R M, Abtahi, Dariush, Abu Rumeileh, Samir, Abu-Rmeileh, Niveen ME, Aburuz, Salahdein, Abu-Zaid, Ahmed, Acuna, Juan Manuel, Adair, Tim, Addo, Isaac Yeboah, Adebayo, Oladimeji M, Adegboye, Oyelola A, Adekanmbi, Victor, Aden, Bashir, Adepoju, Abiola Victor, Adetunji, Charles Oluwaseun, Adeyeoluwa, Temitayo Esther, Adeyomoye, Olorunsola Israel, Adha, Rishan, Adibi, Amin, Adikusuma, Wirawan, Adnani, Qorinah Estiningtyas Sakilah, Adra, Saryia, Afework, Abel, Afolabi, Aanuoluwapo Adeyimika, Afraz, Ali, Afyouni, Shadi, Afzal, Saira, Agasthi, Pradyumna, Aghamiri, Shahin, Agodi, Antonella, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahmad, Aqeel, Ahmad, Danish, Ahmad, Firdos, Ahmad, Muayyad M, Ahmad, Tauseef, Ahmadi, Keivan, Ahmadzade, Amir Mahmoud, Ahmadzade, Mohadese, Ahmed, Ayman, Ahmed, Haroon, Ahmed, Luai A, Ahmed, Muktar Beshir, Ahmed, Syed Anees, Ajami, Marjan, Aji, Budi, Ajumobi, Olufemi, Akalu, Gizachew Taddesse, Akara, Essona Matatom, Akinosoglou, Karolina, Akkala, Sreelatha, Akyirem, Samuel, Al Hamad, Hanadi, Al Hasan, Syed Mahfuz, Al Homsi, Ammar, Al Qadire, Mohammad, Ala, Moein, Aladelusi, Timothy Olukunle, AL-Ahdal, Tareq Mohammed Ali, Alalalmeh, Samer O, Al-Aly, Ziyad, Alam, Khurshid, Alam, Manjurul, Alam, Zufishan, Al-amer, Rasmieh Mustafa, Alanezi, Fahad Mashhour, Alanzi, Turki M, Albashtawy, Mohammed, AlBataineh, Mohammad T, Aldridge, Robert W, Alemi, Sharifullah, Al-Eyadhy, Ayman, Al-Gheethi, Adel Ali Saeed, Alhabib, Khalid F, Alhalaiqa, Fadwa Alhalaiqa Naji, Al-Hanawi, Mohammed Khaled, Ali, Abid, Ali, Akhtar, Ali, Beriwan Abdulqadir, Ali, Hassam, Ali, Mohammed Usman, Ali, Rafat, Ali, Syed Shujait Shujait, Ali, Zahid, Alian Samakkhah, Shohreh, Alicandro, Gianfranco, Alif, Sheikh Mohammad, Aligol, Mohammad, Alimi, Rasoul, Aliyi, Ahmednur Adem, Al-Jumaily, Adel, Aljunid, Syed Mohamed, Almahmeed, Wael, Al-Marwani, Sabah, Al-Maweri, Sadeq Ali Ali, Almazan, Joseph Uy, Al-Mekhlafi, Hesham M, Almidani, Omar, Alomari, Mahmoud A, Alonso, Nivaldo, Alqahtani, Jaber S, Alqutaibi, Ahmed Yaseen, Al-Sabah, Salman Khalifah, Altaf, Awais, Al-Tawfiq, Jaffar A, Altirkawi, Khalid A, Alvi, Farrukh Jawad, Alwafi, Hassan, Al-Worafi, Yaser Mohammed, Aly, Hany, Alzoubi, Karem H, Amare, Azmeraw T, Ameyaw, Edward Kwabena, Amhare, Abebe Feyissa, Amin, Tarek Tawfik, Amindarolzarbi, Alireza, Aminian Dehkordi, Javad, Amiri, Sohrab, Amu, Hubert, Amugsi, Dickson A, Amzat, Jimoh, Ancuceanu, Robert, Anderlini, Deanna, Andrade, Pedro Prata, Andrei, Catalina Liliana, Andrei, Tudorel, Angappan, Dhanalakshmi, Anil, Abhishek, Anjum, Afifa, Antony, Catherine M, Antriyandarti, Ernoiz, Anuoluwa, Iyadunni Adesola, Anwar, Sumadi Lukman, Anyasodor, Anayochukwu Edward, Appiah, Seth Christopher Yaw, Aqeel, Muhammad, Arabloo, Jalal, Arabzadeh Bahri, Razman, Arab-Zozani, Morteza, Arafat, Mosab, Araújo, Ana Margarida, Aravkin, Aleksandr Y, Aremu, Abdulfatai, Ariffin, Hany, Aripov, Timur, Armocida, Benedetta, Arooj, Mahwish, Artamonov, Anton A, Artanti, Kurnia Dwi, Arulappan, Judie, Aruleba, Idowu Thomas, Aruleba, Raphael Taiwo, Arumugam, Ashokan, Asaad, Malke, Asgary, Saeed, Ashemo, Mubarek Yesse, Ashraf, Muhammad, Asika, Marvellous O, Athari, Seyyed Shamsadin, Atout, Maha Moh'd Wahbi, Atreya, Alok, Attia, Sameh, Aujayeb, Avinash, Avan, Abolfazl, Awotidebe, Adedapo Wasiu, Ayala Quintanilla, Beatriz Paulina, Ayanore, Martin Amogre, Ayele, Getnet Melaku, Ayuso-Mateos, Jose L, Ayyoubzadeh, Seyed Mohammad, Azadnajafabad, Sina, Azhar, Gulrez Shah, Aziz, Shahkaar, Azzam, Ahmed Y, Babashahi, Mina, Babu, Abraham Samuel, Badar, Muhammad, Badawi, Alaa, Badiye, Ashish D, Baghdadi, Soroush, Bagheri, Nasser, Bagherieh, Sara, Bah, Sulaiman, Bahadorikhalili, Saeed, Bai, Jianjun, Bai, Ruhai, Baker, Jennifer L, Bakkannavar, Shankar M, Bako, Abdulaziz T, Balakrishnan, Senthilkumar, Balogun, Saliu A, Baltatu, Ovidiu Constantin, Bam, Kiran, Banach, Maciej, Bandyopadhyay, Soham, Banik, Biswajit, Banik, Palash Chandra, Bansal, Hansi, Barati, Shirin, Barchitta, Martina, Bardhan, Mainak, Barker-Collo, Suzanne Lyn, Barone-Adesi, Francesco, Barqawi, Hiba Jawdat, Barr, Ronald D, Barrero, Lope H, Basharat, Zarrin, Bashir, Asma'u I J, Bashiru, Hameed Akande, Baskaran, Pritish, Basnyat, Buddha, Bassat, Quique, Basso, João Diogo, Basu, Saurav, Batra, Kavita, Batra, Ravi, Baune, Bernhard T, Bayati, Mohsen, Bayileyegn, Nebiyou Simegnew, Beaney, Thomas, Bedi, Neeraj, Begum, Tahmina, Behboudi, Emad, Behnoush, Amir Hossein, Beiranvand, Maryam, Bejarano Ramirez, Diana Fernanda, Belgaumi, Uzma Iqbal, Bell, Michelle L, Bello, Aminu K, Bello, Muhammad Bashir, Bello, Olorunjuwon Omolaja, Belo, Luis, Beloukas, Apostolos, Bendak, Salaheddine, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berezvai, Zombor, Berman, Adam E, Bermudez, Amiel Nazer C, Bettencourt, Paulo J G, Beyene, Habtamu B, Beyene, Kebede A, Bhagat, Devidas S, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhalla, Ashish, Bhandari, Dinesh, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhardwaj, Prarthna V, Bhargava, Ashish, Bhaskar, Sonu, Bhat, Vivek, Bhatti, Gurjit Kaur, Bhatti, Jasvinder Singh, Bhatti, Manpreet S, Bhatti, Rajbir, Bhutta, Zulfiqar A, Bikbov, Boris, Binmadi, Nada, Bintoro, Bagas Suryo, Biondi, Antonio, Bisignano, Catherine, Bisulli, Francesca, Biswas, Atanu, Biswas, Raaj Kishore, Bitaraf, Saeid, Bjørge, Tone, Bleyer, Archie, Boampong, Mary Sefa, Bodolica, Virginia, Bodunrin, Aadam Olalekan, Bolarinwa, Obasanjo Afolabi, Bonakdar Hashemi, Milad, Bonny, Aime, Bora, Kaustubh, Bora Basara, Berrak, Borodo, Safiya Bala, Borschmann, Rohan, Botero Carvajal, Alejandro, Bouaoud, Souad, Boudalia, Sofiane, Boyko, Edward J, Bragazzi, Nicola Luigi, Braithwaite, Dejana, Brenner, Hermann, Britton, Gabrielle, Browne, Annie J, Brunoni, Andre R, Bulamu, Norma B, Bulto, Lemma N, Buonsenso, Danilo, Burkart, Katrin, Burns, Richard A, Burugina Nagaraja, Sharath, Busse, Reinhard, Bustanji, Yasser, Butt, Zahid A, Caetano dos Santos, Florentino Luciano, Cai, Tianji, Calina, Daniela, Cámera, Luis Alberto, Campos, Luciana Aparecida, Campos-Nonato, Ismael R, Cao, Chao, Cardenas, Carlos Alberto, Cárdenas, Rosario, Carr, Sinclair, Carreras, Giulia, Carrero, Juan J, Carugno, Andrea, Carvalho, Felix, Carvalho, Márcia, Castaldelli-Maia, Joao Mauricio, Castañeda-Orjuela, Carlos A, Castelpietra, Giulio, Catalá-López, Ferrán, Catapano, Alberico L, Cattaruzza, Maria Sofia, Caye, Arthur, Cederroth, Christopher R, Cembranel, Francieli, Cenderadewi, Muthia, Cercy, Kelly M, Cerin, Ester, Cevik, Muge, Chacón-Uscamaita, Pamela R Uscamaita, Chahine, Yaacoub, Chakraborty, Chiranjib, Chan, Jeffrey Shi Kai, Chang, Chin-Kuo, Charalampous, Periklis, Charan, Jaykaran, Chattu, Vijay Kumar, Chatzimavridou-Grigoriadou, Victoria, Chavula, Malizgani Paul, Cheema, Huzaifa Ahmad, Chen, An-Tian, Chen, Haowei, Chen, Lingxiao, Chen, Meng Xuan, Chen, Simiao, Cherbuin, Nicolas, Chew, Derek S, Chi, Gerald, Chirinos-Caceres, Jesus Lorenzo, Chitheer, Abdulaal, Cho, So Mi Jemma, Cho, William C S, Chong, Bryan, Chopra, Hitesh, Choudhary, Rahul, Chowdhury, Rajiv, Chu, Dinh-Toi, Chukwu, Isaac Sunday, Chung, Eric, Chung, Eunice, Chung, Sheng-Chia, Cini, Karly I, Clark, Cain C T, Coberly, Kaleb, Columbus, Alyssa, Comfort, Haley, Conde, Joao, Conti, Sara, Cortesi, Paolo Angelo, Costa, Vera Marisa, Cousin, Ewerton, Cowden, Richard G, Criqui, Michael H, Cruz-Martins, Natália, Culbreth, Garland T, Cullen, Patricia, Cunningham, Matthew, da Silva e Silva, Daniel, Dadana, Sriharsha, Dadras, Omid, Dai, Zhaoli, Dalal, Koustuv, Dalli, Lachlan L, Damiani, Giovanni, D'Amico, Emanuele, Daneshvar, Sara, Darwesh, Aso Mohammad, Das, Jai K, Das, Saswati, Dash, Nihar Ranjan, Dashti, Mohsen, Dávila-Cervantes, Claudio Alberto, Davis Weaver, Nicole, Davletov, Kairat, De Leo, Diego, Debele, Aklilu Tamire, Degenhardt, Louisa, Dehbandi, Reza, Deitesfeld, Lee, Delgado-Enciso, Ivan, Delgado-Ortiz, Laura, Demant, Daniel, Demessa, Berecha Hundessa, Demetriades, Andreas K, Deng, Xinlei, Denova-Gutiérrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Des Jarlais, Don C, Desai, Hardik Dineshbhai, Desai, Rupak, Deuba, Keshab, Devanbu, Vinoth Gnana Chellaiyan, Dey, Sourav, Dhali, Arkadeep, Dhama, Kuldeep, Dhimal, Mandira Lamichhane, Dhimal, Meghnath, Dhingra, Sameer, Dias da Silva, Diana, Diaz, Daniel, Dima, Adriana, Ding, Delaney D, Dirac, M Ashworth, Dixit, Abhinav, Dixit, Shilpi Gupta, Do, Thanh Chi, Do, Thao Huynh Phuong, do Prado, Camila Bruneli, Dodangeh, Masoud, Dokova, Klara Georgieva, Dolecek, Christiane, Dorsey, E Ray, dos Santos, Wendel Mombaque, Doshi, Rajkumar, Doshmangir, Leila, Douiri, Abdel, Dowou, Robert Kokou, Driscoll, Tim Robert, Dsouza, Haneil Larson, Dube, John, Dumith, Samuel C, Dunachie, Susanna J, Duncan, Bruce B, Duraes, Andre Rodrigues, Duraisamy, Senbagam, Durojaiye, Oyewole Christopher, Dutta, Sulagna, Dzianach, Paulina Agnieszka, Dziedzic, Arkadiusz Marian, Ebenezer, Oluwakemi, Eboreime, Ejemai, Ebrahimi, Alireza, Echieh, Chidiebere Peter, Ed-Dra, Abdelaziz, Edinur, Hisham Atan, Edvardsson, David, Edvardsson, Kristina, Efendi, Defi, Efendi, Ferry, Eghdami, Shayan, Eikemo, Terje Andreas, Eini, Ebrahim, Ekholuenetale, Michael, Ekpor, Emmanuel, Ekundayo, Temitope Cyrus, El Arab, Rabie Adel, El Morsi, Doaa Abdel Wahab, El Sayed Zaki, Maysaa, El Tantawi, Maha, Elbarazi, Iffat, Elemam, Noha Mousaad, Elgar, Frank J, Elgendy, Islam Y, ElGohary, Ghada Metwally Tawfik, Elhabashy, Hala Rashad, Elhadi, Muhammed, Elmeligy, Omar Abdelsadek Abdou, Elshaer, Mohammed, Elsohaby, Ibrahim, Emami Zeydi, Amir, Emamverdi, Mehdi, Emeto, Theophilus I, Engelbert Bain, Luchuo, Erkhembayar, Ryenchindorj, Eshetie, Tesfahun C, Eskandarieh, Sharareh, Espinosa-Montero, Juan, Estep, Kara, Etaee, Farshid, Eze, Ugochukwu Anthony, Fabin, Natalia, Fadaka, Adewale Oluwaseun, Fagbamigbe, Adeniyi Francis, Fahimi, Saman, Falzone, Luca, Farinha, Carla Sofia e Sá, Faris, MoezAlIslam Ezzat Mahmoud, Farjoud Kouhanjani, Mohsen, Faro, Andre, Farrokhpour, Hossein, Fatehizadeh, Ali, Fattahi, Hamed, Fauk, Nelsensius Klau, Fazeli, Pooria, Feigin, Valery L, Fekadu, Ginenus, Fereshtehnejad, Seyed-Mohammad, Feroze, Abdullah Hamid, Ferrante, Daniela, Ferrara, Pietro, Ferreira, Nuno, Fetensa, Getahun, Filip, Irina, Fischer, Florian, Flavel, Joanne, Flaxman, Abraham D, Flor, Luisa S, Florin, Bobirca Teodor, Folayan, Morenike Oluwatoyin, Foley, Kristen Marie, Fomenkov, Artem Alekseevich, Force, Lisa M, Fornari, Carla, Foroutan, Behzad, Foschi, Matteo, Francis, Kate Louise, Franklin, Richard Charles, Freitas, Alberto, Friedman, Joseph, Friedman, Sara D, Fukumoto, Takeshi, Fuller, John E, Gaal, Peter Andras, Gadanya, Muktar A, Gaihre, Santosh, Gaipov, Abduzhappar, Gakidou, Emmanuela, Galali, Yaseen, Galehdar, Nasrin, Gallus, Silvano, Gan, Quan, Gandhi, Aravind P, Ganesan, Balasankar, Garg, Jalaj, Gau, Shuo-Yan, Gautam, Prem, Gautam, Rupesh K, Gazzelloni, Federica, Gebregergis, Miglas W, Gebrehiwot, Mesfin, Gebremariam, Tesfay Brhane, Gerema, Urge, Getachew, Motuma Erena, Getachew, Tamirat, Gething, Peter W, Ghafourifard, Mansour, Ghahramani, Sulmaz, Ghailan, Khalid Yaser, Ghajar, Alireza, Ghanbarnia, Mohammad Javad, Ghasemi, MohammadReza, Ghasemzadeh, Afsaneh, Ghassemi, Fariba, Ghazy, Ramy Mohamed, Ghimire, Sailaja, Gholamian, Asadollah, Gholamrezanezhad, Ali, Ghorbani Vajargah, Pooyan, Ghozali, Ghozali, Ghozy, Sherief, Ghuge, Arun Digambarrao, Gialluisi, Alessandro, Gibson, Ruth Margaret, Gil, Artyom Urievich, Gill, Paramjit Singh, Gill, Tiffany K, Gillum, Richard F, Ginindza, Themba G, Girmay, Alem, Glasbey, James C, Gnedovskaya, Elena V, Göbölös, Laszlo, Goel, Amit, Goldust, Mohamad, Golechha, Mahaveer, Goleij, Pouya, Golestanfar, Arefeh, Golinelli, Davide, Gona, Philimon N, Goudarzi, Houman, Goudarzian, Amir Hossein, Goyal, Anmol, Greenhalgh, Scott, Grivna, Michal, Guarducci, Giovanni, Gubari, Mohammed Ibrahim Mohialdeen, Gudeta, Mesay Dechasa, Guha, Avirup, Guicciardi, Stefano, Gunawardane, Damitha Asanga, Gunturu, Sasidhar, Guo, Cui, Gupta, Anish Kumar, Gupta, Bhawna, Gupta, Indarchand Ratanlal, Gupta, Rajat Das, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vijai Kumar, Gupta, Vivek Kumar, Gutiérrez, Reyna Alma, Habibzadeh, Farrokh, Habibzadeh, Parham, Hachinski, Vladimir, Haddadi, Mohammad, Haddadi, Rasool, Haep, Nils, Hajj Ali, Adel, Halboub, Esam S, Halim, Sobia Ahsan, Hall, Brian J, Haller, Sebastian, Halwani, Rabih, Hamadeh, Randah R, Hamagharib Abdullah, Kanaan, Hamidi, Samer, Hamiduzzaman, Mohammad, Hammoud, Ahmad, Hanifi, Nasrin, Hankey, Graeme J, Hannan, Md Abdul, Haque, Md Nuruzzaman, Harapan, Harapan, Haro, Josep Maria, Hasaballah, Ahmed I, Hasan, Faizul, Hasan, Ikramul, Hasan, M Tasdik, Hasani, Hamidreza, Hasanian, Mohammad, Hasanpour- Dehkordi, Ali, Hassan, Abbas M, Hassan, Amr, Hassanian-Moghaddam, Hossein, Hassanipour, Soheil, Haubold, Johannes, Havmoeller, Rasmus J, Hay, Simon I, Hbid, Youssef, Hebert, Jeffrey J, Hegazi, Omar E, Heidari, Golnaz, Heidari, Mohammad, Heidari-Foroozan, Mahsa, Heidari-Soureshjani, Reza, Helfer, Bartosz, Herteliu, Claudiu, Hesami, Hamed, Hettiarachchi, Dineshani, Heyi, Demisu Zenbaba, Hezam, Kamal, Hiraike, Yuta, Hoffman, Howard J, Holla, Ramesh, Horita, Nobuyuki, Hossain, Md Belal, Hossain, Md Mahbub, Hossain, Sahadat, Hosseini, Mohammad-Salar, Hosseinzadeh, Hassan, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hsairi, Mohamed, Hsieh, Vivian Chia-rong, Hu, Chengxi, Huang, Junjie, Huda, Md Nazmul, Hugo, Fernando N, Hultström, Michael, Hussain, Javid, Hussain, Salman, Hussein, Nawfal R, Huy, Le Duc, Huynh, Hong-Han, Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Idowu, Oluwatope Olaniyi, Ijo, Desta, Ikuta, Kevin S, Ilaghi, Mehran, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Immurana, Mustapha, Inbaraj, Leeberk Raja, Iradukunda, Arnaud, Iravanpour, Farideh, Iregbu, Kenneth Chukwuemeka, Islam, Md Rabiul, Islam, Mohammad Mainul, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Ismail, Nahlah Elkudssiah, Isola, Gaetano, Iwagami, Masao, Iwu, Chidozie C D, Iwu-Jaja, Chinwe Juliana, Iyer, Mahalaxmi, J, Linda Merin, Jaafari, Jalil, Jacob, Louis, Jacobsen, Kathryn H, Jadidi-Niaragh, Farhad, Jafarinia, Morteza, Jaggi, Khushleen, Jahankhani, Kasra, Jahanmehr, Nader, Jahrami, Haitham, Jain, Akhil, Jain, Nityanand, Jairoun, Ammar Abdulrahman, Jakovljevic, Mihajlo, Jalilzadeh Yengejeh, Reza, Jamshidi, Elham, Jani, Chinmay T, Janko, Mark M, Jatau, Abubakar Ibrahim, Jayapal, Sathish Kumar, Jayaram, Shubha, Jeganathan, Jayakumar, Jema, Alelign Tasew, Jemere, Digisie Mequanint, Jeong, Wonjeong, Jha, Anil K, Jha, Ravi Prakash, Ji, John S, Jiang, Heng, Jin, Yingzhao, Jin, Yinzi, Johnson, Olatunji, Jomehzadeh, Nabi, Jones, Darwin Phan, Joo, Tamas, Joseph, Abel, Joseph, Nitin, Joshua, Charity Ehimwenma, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kaambwa, Billingsley, Kabir, Ali, Kabir, Hannaneh, Kabir, Zubair, Kadashetti, Vidya, Kahe, Farima, Kakodkar, Pradnya Vishal, Kalani, Rizwan, Kalankesh, Leila R, Kaliyadan, Feroze, Kalra, Sanjay, Kamath, Ashwin, Kamireddy, Arun, Kanagasabai, Thanigaivelan, Kandel, Himal, Kanmiki, Edmund Wedam, Kanmodi, Kehinde Kazeem, Kantar, Rami S, Kapoor, Neeti, Karajizadeh, Mehrdad, Karami Matin, Behzad, Karanth, Shama D, Karaye, Ibraheem M, Karim, Asima, Karimi, Hanie, Karimi, Salah Eddin, Karimi Behnagh, Arman, Karkhah, Samad, Karna, Ajit K, Kashoo, Faizan Zaffar, Kasraei, Hengameh, Kassaw, Nigussie Assefa, Kassebaum, Nicholas J, Kassel, Molly B, Katamreddy, Adarsh, Katikireddi, Srinivasa Vittal, Katoto, Patrick DMC, Kauppila, Joonas H, Kaur, Navjot, Kaydi, Neda, Kayibanda, Jeanne Françoise, Kayode, Gbenga A, Kazemi, Foad, Kazemian, Sina, Kazeminia, sara, Keikavoosi-Arani, Leila, Keller, Cathleen, Kempen, John H, Kerr, Jessica A, Kesse-Guyot, Emmanuelle, Keykhaei, Mohammad, Khadembashiri, Mohamad Mehdi, Khadembashiri, Mohammad Amin, Khafaie, Morteza Abdullatif, Khajuria, Himanshu, Khalafi, Mohammad, Khalaji, Amirmohammad, Khalid, Nauman, Khalil, Ibrahim A, Khamesipour, Faham, Khan, Asaduzzaman, Khan, Gulfaraz, Khan, Ikramullah, Khan, Imteyaz A, Khan, Maseer, Khan, Moien AB, Khan, Taimoor, Khan suheb, Mahammed Ziauddin, Khanmohammadi, Shaghayegh, Khatab, Khaled, Khatami, Fatemeh, Khavandegar, Armin, Khayat Kashani, Hamid Reza, Kheirallah, Khalid A, Khidri, Feriha Fatima, Khodadoust, Elaheh, Khormali, Moein, Khosrowjerdi, Mahmood, Khubchandani, Jagdish, Khusun, Helda, Kifle, Zemene Demelash, Kim, Grace, Kim, Jihee, Kimokoti, Ruth W, Kinzel, 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Lin, Yano, Yuichiro, Yao, Yao, Ye, Pengpeng, Yesera, Gesila Endashaw, Yesodharan, Renjulal, Yesuf, Subah Abderehim, Yiğit, Arzu, Yiğit, Vahit, Yip, Paul, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yu, Chuanhua, Zadey, Siddhesh, Zadnik, Vesna, Zafari, Nima, Zahedi, Mohammad, Zahid, Muhammad Nauman, Zahir, Mazyar, Zakham, Fathiah, Zaki, Nazar, Zakzuk, Josefina, Zamagni, Giulia, Zaman, Burhan Abdullah, Zaman, Sojib Bin, Zamora, Nelson, Zand, Ramin, Zandi, Milad, Zandieh, Ghazal G Z, Zanghì, Aurora, Zare, Iman, Zastrozhin, Mikhail Sergeevich, Zeariya, Mohammed G M, Zeng, Youjie, Zhai, Chunxia, Zhang, Chen, Zhang, Haijun, Zhang, Hongwei, Zhang, Yunquan, Zhang, Zhaofeng, Zhang, Zhenyu, Zhao, Hanqing, Zhao, Yang, Zhao, Yong, Zheng, Peng, Zhong, Chenwen, Zhou, Juexiao, Zhu, Bin, Zhu, Zhaohua, Ziaeefar, Pardis, Zielińska, Magdalena, Zou, Zhiyong, Zumla, Alimuddin, Zweck, Elric, Zyoud, Samer H, Lim, Stephen S, and Murray, Christopher J L
- Abstract
Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.
- Published
- 2024
- Full Text
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5. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021
- Author
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Vollset, Stein Emil, Ababneh, Hazim S, Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbasgholizadeh, Rouzbeh, Abbasian, Mohammadreza, Abbastabar, Hedayat, Abd Al Magied, Abdallah H A, Abd ElHafeez, Samar, Abdelkader, Atef, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdi, Parsa, Abdollahi, Mohammad, Abdoun, Meriem, Abdullahi, Auwal, Abebe, Mesfin, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Abouzid, Mohamed, Aboye, Girma Beressa, Abreu, Lucas Guimarães, Absalan, Abdorrahim, Abualruz, Hasan, Abubakar, Bilyaminu, Abukhadijah, Hana Jihad Jihad, Addolorato, Giovanni, Adekanmbi, Victor, Adetunji, Charles Oluwaseun, Adetunji, Juliana Bunmi, Adeyeoluwa, Temitayo Esther, Adha, Rishan, Adhikary, Ripon Kumar, Adnani, Qorinah Estiningtyas Sakilah, Adzigbli, Leticia Akua, Afrashteh, Fatemeh, Afzal, Muhammad Sohail, Afzal, Saira, Agbozo, Faith, Agodi, Antonella, Agrawal, Anurag, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahlstrom, Austin J, Ahmad, Aqeel, Ahmad, 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- Abstract
Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050.
- Published
- 2024
- Full Text
- View/download PDF
6. Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
- Author
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- Abstract
Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios.
- Published
- 2024
- Full Text
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7. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Naghavi, Mohsen, Ong, Kanyin Liane, Aali, Amirali, Ababneh, Hazim S, Abate, Yohannes Habtegiorgis, Abbafati, Cristiana, Abbasgholizadeh, Rouzbeh, Abbasian, Mohammadreza, Abbasi-Kangevari, Mohsen, Abbastabar, Hedayat, Abd ElHafeez, Samar, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdelwahab, Ahmed, Abdollahi, Mohammad, Abdollahifar, Mohammad-Amin, Abdoun, Meriem, Abdulah, Deldar Morad, Abdullahi, Auwal, Abebe, Mesfin, Abebe, Samrawit Shawel, Abedi, Aidin, Abegaz, Kedir Hussein, Abhilash, E S, Abidi, Hassan, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Abolmaali, Meysam, Abouzid, Mohamed, Aboye, Girma Beressa, Abreu, Lucas Guimarães, Abrha, Woldu Aberhe, Abtahi, Dariush, Abu Rumeileh, Samir, Abualruz, Hasan, Abubakar, Bilyaminu, Abu-Gharbieh, Eman, Abu-Rmeileh, Niveen ME, Aburuz, Salahdein, Abu-Zaid, Ahmed, Accrombessi, Manfred Mario Kokou, Adal, Tadele Girum, Adamu, Abdu A, Addo, Isaac Yeboah, Addolorato, Giovanni, Adebiyi, Akindele Olupelumi, Adekanmbi, Victor, 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Erkhembayar, Ryenchindorj, Esezobor, Christopher Imokhuede, Eshrati, Babak, Eskandarieh, Sharareh, Espinosa-Montero, Juan, Esubalew, Habtamu, Etaee, Farshid, Fabin, Natalia, Fadaka, Adewale Oluwaseun, Fagbamigbe, Adeniyi Francis, Fahim, Ayesha, Fahimi, Saman, Fakhri-Demeshghieh, Aliasghar, Falzone, Luca, Fareed, Mohammad, Farinha, Carla Sofia e Sá, Faris, MoezAlIslam Ezzat Mahmoud, Faris, Pawan Sirwan, Faro, Andre, Fasanmi, Abidemi Omolara, Fatehizadeh, Ali, Fattahi, Hamed, Fauk, Nelsensius Klau, Fazeli, Pooria, Feigin, Valery L, Feizkhah, Alireza, Fekadu, Ginenus, Feng, Xiaoru, Fereshtehnejad, Seyed-Mohammad, Feroze, Abdullah Hamid, Ferrante, Daniela, Ferrari, Alize J, Ferreira, Nuno, Fetensa, Getahun, Feyisa, Bikila Regassa, Filip, Irina, Fischer, Florian, Flavel, Joanne, Flood, David, Florin, Bobirca Teodor, Foigt, Nataliya A, Folayan, Morenike Oluwatoyin, Fomenkov, Artem Alekseevich, Foroutan, Behzad, Foroutan, Masoud, Forthun, Ingeborg, Fortuna, Daniela, Foschi, Matteo, Fowobaje, 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Patoulias, Dimitrios, Patthipati, Venkata Suresh, Paudel, Uttam, Pazoki Toroudi, Hamidreza, Pease, Spencer A, Peden, Amy E, Pedersini, Paolo, Pensato, Umberto, Pepito, Veincent Christian Filipino, Peprah, Emmanuel K, Peprah, Prince, Perdigão, João, Pereira, Marcos, Peres, Mario F P, Perianayagam, Arokiasamy, Perico, Norberto, Pestell, Richard G, Pesudovs, Konrad, Petermann-Rocha, Fanny Emily, Petri, William A, Pham, Hoang Tran, Philip, Anil K, Phillips, Michael R, Pierannunzio, Daniela, Pigeolet, Manon, Pigott, David M, Pilgrim, Thomas, Piracha, Zahra Zahid, Piradov, Michael A, Pirouzpanah, Saeed, Plakkal, Nishad, Plotnikov, Evgenii, Podder, Vivek, Poddighe, Dimitri, Polinder, Suzanne, Polkinghorne, Kevan R, Poluru, Ramesh, Ponkilainen, Ville T, Porru, Fabio, Postma, Maarten J, Poudel, Govinda Raj, Pourshams, Akram, Pourtaheri, Naeimeh, Prada, Sergio I, Pradhan, Pranil Man Singh, Prakasham, Thejeswar N, Prasad, Manya, Prashant, Akila, Prates, Elton Junio Sady, Prieto Alhambra, Daniel, PRISCILLA, TINA, Pritchett, Natalie, Purohit, Bharathi M, Puvvula, Jagadeesh, Qasim, Nameer Hashim, Qattea, Ibrahim, Qazi, Asma Saleem, Qian, Gangzhen, Qiu, Suli, Qureshi, Maryam Faiz, Rabiee Rad, Mehrdad, Radfar, Amir, Radhakrishnan, Raghu Anekal, Radhakrishnan, Venkatraman, Raeisi Shahraki, Hadi, Rafferty, Quinn, Raggi, Alberto, Raghav, Pankaja Raghav, Raheem, Nasiru, Rahim, Fakher, Rahim, Md Jillur, Rahimi-Movaghar, Vafa, Rahman, Md Mosfequr, Rahman, Mohammad Hifz Ur, Rahman, Mosiur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Shayan, Rahmanian, Vahid, Rajaa, Sathish, Rajput, Prashant, Rakovac, Ivo, Ramasamy, Shakthi Kumaran, Ramazanu, Sheena, Rana, Kritika, Ranabhat, Chhabi Lal, Rancic, Nemanja, Rane, Amey, Rao, Chythra R, Rao, Indu Ramachandra, Rao, Mithun, Rao, Sowmya J, Rasali, Drona Prakash, Rasella, Davide, Rashedi, Sina, Rashedi, Vahid, Rashidi, Mohammad-Mahdi, Rasouli-Saravani, Ashkan, Rasul, Azad, Rathnaiah Babu, Giridhara, Rauniyar, Santosh Kumar, Ravangard, Ramin, Ravikumar, Nakul, Rawaf, David Laith, Rawaf, Salman, Rawal, Lal, Rawassizadeh, Reza, Rawlley, Bharat, Raza, Rabail Zehra, Razo, Christian, Redwan, Elrashdy Moustafa Mohamed, Rehman, Faizan Ur, Reifels, Lennart, Reiner Jr, Robert C, Remuzzi, Giuseppe, Reyes, Luis Felipe, Rezaei, Maryam, Rezaei, Nazila, Rezaei, Negar, Rezaeian, Mohsen, Rhee, Taeho Gregory, Riaz, Mavra A, Ribeiro, Antonio Luiz P, Rickard, Jennifer, Riva, Hannah R, Robinson-Oden, Hannah Elizabeth, Rodrigues, Célia Fortuna, Rodrigues, Mónica, Roever, Leonardo, Rogowski, Emma Lynn Best, Rohloff, Peter, Romadlon, Debby Syahru, Romero-Rodríguez, Esperanza, Romoli, Michele, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rout, Himanshu Sekhar, Roy, Nitai, Roy, Priyanka, Rubagotti, Enrico, Ruela, Guilherme de Andrade, Rumisha, Susan Fred, Runghien, Tilleye, Rwegerera, Godfrey M, Rynkiewicz, Andrzej, S N, Chandan, Saad, Aly M A, Saadatian, Zahra, Saber, Korosh, Saber-Ayad, Maha Mohamed, SaberiKamarposhti, Morteza, Sabour, Siamak, Sacco, Simona, Sachdev, Perminder S, Sachdeva, Rajesh, Saddik, Basema, Saddler, Adam, Sadee, Bashdar Abuzed, Sadeghi, Ehsan, Sadeghi, Erfan, Sadeghian, Farideh, Saeb, Mohammad Reza, Saeed, Umar, Safaeinejad, Fahimeh, Safi, Sher Zaman, Sagar, Rajesh, Saghazadeh, Amene, Sagoe, Dominic, Saheb Sharif-Askari, Fatemeh, Saheb Sharif-Askari, Narjes, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahoo, Umakanta, Sahu, Monalisha, Saif, Zahra, Sajid, Mirza Rizwan, Sakshaug, Joseph W, Salam, Nasir, Salamati, Payman, Salami, Afeez Abolarinwa, Salaroli, Luciane B, Saleh, Mohamed A, Salehi, Sana, Salem, Marwa Rashad, Salem, Mohammed Z Y, Salimi, Sohrab, Samadi Kafil, Hossein, Samadzadeh, Sara, Samargandy, Saad, Samodra, Yoseph Leonardo, Samy, Abdallah M, Sanabria, Juan, Sanna, Francesca, Santomauro, Damian Francesco, Santos, Itamar S, Santric-Milicevic, Milena M, Sao Jose, Bruno Piassi, Sarasmita, Made Ary, Saraswathy, Sivan Yegnanarayana Iyer, Saravanan, Aswini, Saravi, Babak, Sarikhani, Yaser, Sarkar, Tanmay, Sarmiento-Suárez, Rodrigo, Sarode, Gargi Sachin, Sarode, Sachin C, Sarveazad, Arash, Sathian, Brijesh, Sathish, Thirunavukkarasu, Satpathy, Maheswar, Sayeed, Abu, Sayeed, Md Abu, Saylan, Mete, Sayyah, Mehdi, Scarmeas, Nikolaos, Schaarschmidt, Benedikt Michael, Schlaich, Markus P, Schlee, Winfried, Schmidt, Maria Inês, Schneider, Ione Jayce Ceola, Schuermans, Art, Schumacher, Austin E, Schutte, Aletta Elisabeth, Schwarzinger, Michaël, Schwebel, David C, Schwendicke, Falk, Šekerija, Mario, Selvaraj, Siddharthan, Senapati, Sabyasachi, Senthilkumaran, Subramanian, Sepanlou, Sadaf G, Serban, Dragos, Sethi, Yashendra, Sha, Feng, Shabany, Maryam, Shafaat, Amir, Shafie, Mahan, Shah, Nilay S, Shah, Pritik A, Shah, Syed Mahboob, Shahabi, Saeed, Shahbandi, Ataollah, Shahid, Izza, Shahid, Samiah, Shahid, Wajeehah, Shahsavari, Hamid R, Shahwan, Moyad Jamal, Shaikh, Ahmed, Shaikh, Masood Ali, Shakeri, Alireza, Shalash, Ali S, Sham, Sunder, Shamim, Muhammad Aaqib, Shams-Beyranvand, Mehran, Shamshad, Hina, Shamsi, Mohammad Anas, Shanawaz, Mohd, Shankar, Abhishek, Sharfaei, Sadaf, Sharifan, Amin, Sharifi-Rad, Javad, Sharma, Rajesh, Sharma, Saurab, Sharma, Ujjawal, Sharma, Vishal, Shastry, Rajesh P, Shavandi, Amin, Shayan, Maryam, Shehabeldine, Amr Mohamed Elsayed, Sheikh, Aziz, Sheikhi, Rahim Ali, Shen, Jiabin, Shetty, Adithi, Shetty, B Suresh Kumar, Shetty, Pavanchand H, Shi, Peilin, Shibuya, Kenji, Shiferaw, Desalegn, Shigematsu, Mika, Shin, Min-Jeong, Shin, Youn Ho, Shiri, Rahman, Shirkoohi, Reza, Shitaye, Nebiyu Aniley, Shittu, Aminu, Shiue, Ivy, Shivakumar, K M, Shivarov, Velizar, Shokraneh, Farhad, Shokri, Azad, Shool, Sina, Shorofi, Seyed Afshin, Shrestha, Sunil, Shuval, Kerem, Siddig, Emmanuel Edwar, Silva, João Pedro, Silva, Luís Manuel Lopes Rodrigues, Silva, Soraia, Simpson, Colin R, Singal, Anjali, Singh, Abhinav, Singh, Balbir Bagicha, Singh, Garima, Singh, Jasbir, Singh, Narinder Pal, Singh, Paramdeep, Singh, Surjit, Sinha, Dhirendra Narain, Sinto, Robert, Siraj, Md Shahjahan, Sirota, Sarah Brooke, Sitas, Freddy, Sivakumar, Shravan, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Sleet, David A, Socea, Bogdan, Sokhan, Anton, Solanki, Ranjan, Solanki, Shipra, Soleimani, Hamidreza, Soliman, Sameh S M, Song, Suhang, Song, Yimeng, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Spartalis, Michael, Spearman, Sandra, Sreeramareddy, Chandrashekhar T, Srivastava, Vijay Kumar, Stanaway, Jeffrey D, Stanikzai, Muhammad Haroon, Stark, Benjamin A, Starnes, Joseph R, Starodubova, Antonina V, Stein, Caroline, Stein, Dan J, Steinbeis, Fridolin, Steiner, Caitlyn, Steinmetz, Jaimie D, Steiropoulos, Paschalis, Stevanović, Aleksandar, Stockfelt, Leo, Stokes, Mark A, Stortecky, Stefan, Subramaniyan, Vetriselvan, Suleman, Muhammad, Suliankatchi Abdulkader, Rizwan, Sultana, Abida, Sun, Haitong Zhe, Sun, Jing, Sundström, Johan, Sunkersing, David, Sunnerhagen, Katharina S, Swain, Chandan Kumar, Szarpak, Lukasz, Szeto, Mindy D, Szócska, Miklós, Tabaee Damavandi, Payam, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabatabaei Malazy, Ozra, Tabatabaeizadeh, Seyed-Amir, Tabatabai, Shima, Tabish, Mohammad, TADAKAMADLA, JYOTHI, Tadakamadla, Santosh Kumar, Taheri Abkenar, Yasaman, Taheri Soodejani, Moslem, Taiba, Jabeen, Takahashi, Ken, Talaat, Iman M, Talukder, Ashis, Tampa, Mircea, Tamuzi, Jacques Lukenze, Tan, Ker-Kan, Tandukar, Sarmila, Tang, Haosu, Tang, Hong K, Tarigan, Ingan Ukur, Tariku, Mengistie Kassahun, Tariqujjaman, Md, Tarkang, Elvis Enowbeyang, Tavakoli Oliaee, Razieh, Tavangar, Seyed Mohammad, Taveira, Nuno, Tefera, Yibekal Manaye, Temsah, Mohamad-Hani, Temsah, Reem Mohamad Hani, Teramoto, Masayuki, Tesler, Riki, Teye-Kwadjo, Enoch, Thakur, Rishu, Thangaraju, Pugazhenthan, Thankappan, Kavumpurathu Raman, Tharwat, Samar, Thayakaran, Rasiah, Thomas, Nihal, Thomas, Nikhil Kenny, Thomson, Azalea M, Thrift, Amanda G, Thum, Chern Choong Chern, Thygesen, Lau Caspar, Tian, Jing, Tichopad, Ales, Ticoalu, Jansje Henny Vera, Tillawi, Tala, Tiruye, Tenaw Yimer, Titova, Mariya Vladimirovna, Tonelli, Marcello, Topor-Madry, Roman, Toriola, Adetunji T, Torre, Anna E, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Tran, Jasmine T, Tran, Nghia Minh, Trico, Domenico, Tromans, Samuel Joseph, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsegay, Guesh Mebrahtom, Tsermpini, Evangelia Eirini, Tumurkhuu, Munkhtuya, Tung, Kang, Tyrovolas, Stefanos, Uddin, Sayed Mohammad Nazim, Udoakang, Aniefiok John, Udoh, Arit, Ullah, Atta, Ullah, Irfan, Ullah, Saeed, Ullah, Sana, Umakanthan, Srikanth, Umeokonkwo, Chukwuma David, Unim, Brigid, Unnikrishnan, Bhaskaran, Unsworth, Carolyn Anne, Upadhyay, Era, Urso, Daniele, Usman, Jibrin Sammani, Vahabi, Seyed Mohammad, Vaithinathan, Asokan Govindaraj, Valizadeh, Rohollah, Van de Velde, Sarah M, Van den Eynde, Jef, Varga, Orsolya, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vasic, Milena, Vaziri, Siavash, Vellingiri, Balachandar, Venketasubramanian, Narayanaswamy, Verghese, Nicholas Alexander, Verma, Madhur, Veroux, Massimiliano, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafañe, Jorge Hugo, Villanueva, Gabriela Ines, Vinayak, Manish, Violante, Francesco S, Viskadourou, Maria, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vo, Bay, Vollset, Stein Emil, Vongpradith, Avina, Vos, Theo, Vujcic, Isidora S, Vukovic, Rade, Wafa, Hatem A, Waheed, Yasir, Wamai, Richard G, Wang, Cong, Wang, Ning, Wang, Shu, Wang, Song, Wang, Yanzhong, Wang, Yuan-Pang, Waqas, Muhammad, Ward, Paul, Wassie, Emebet Gashaw, Watson, Stefanie, Watson, Stephanie Louise Watson, Weerakoon, Kosala Gayan, Wei, Melissa Y, Weintraub, Robert G, Weiss, Daniel J, Westerman, Ronny, Whisnant, Joanna L, Wiangkham, Taweewat, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Wilandika, Angga, Wilkerson, Caroline, Willeit, Peter, Wilson, Shadrach, Wojewodzic, Marcin W, Woldegebreal, Demewoz H, Wolf, Axel Walter, Wolfe, Charles D A, Wondimagegene, Yohannes Addisu, Wong, Yen Jun, Wongsin, Utoomporn, Wu, Ai-Min, Wu, Chenkai, Wu, Felicia, Wu, Xinsheng, Wu, Zenghong, Xia, Juan, Xiao, Hong, Xie, Yang, Xu, Suowen, Xu, Wang-Dong, Xu, Xiaoyue, Xu, Yvonne Yiru, Yadollahpour, Ali, Yamagishi, Kazumasa, Yang, Danting, Yang, Lin, Yano, Yuichiro, Yao, Yao, Yaribeygi, Habib, Ye, Pengpeng, Yehualashet, Sisay Shewasinad, Yesiltepe, Metin, Yesuf, Subah Abderehim, Yezli, Saber, Yi, Siyan, Yigezu, Amanuel, Yiğit, Arzu, Yiğit, Vahit, Yip, Paul, Yismaw, Malede Berihun, Yismaw, Yazachew, Yon, Dong Keon, Yonemoto, Naohiro, Yoon, Seok-Jun, You, Yuyi, Younis, Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Yuh, Faith H, Zadey, Siddhesh, Zadnik, Vesna, Zafari, Nima, Zakham, Fathiah, Zaki, Nazar, Zaman, Sojib Bin, Zamora, Nelson, Zand, Ramin, Zangiabadian, Moein, Zar, Heather J, Zare, Iman, Zarrintan, Armin, Zeariya, Mohammed G M, Zeinali, Zahra, Zhang, Haijun, Zhang, Jianrong, Zhang, Jingya, Zhang, Liqun, Zhang, Yunquan, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhong, Chenwen, Zhou, Juexiao, Zhu, Bin, Zhu, Lei, Ziafati, Makan, Zielińska, Magdalena, Zitoun, Osama A, Zoladl, Mohammad, Zou, Zhiyong, Zuhlke, Liesl J, Zumla, Alimuddin, Zweck, Elric, Zyoud, Samer H, Wool, Eve E, and Murray, Christopher J L
- Abstract
Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.
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- 2024
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8. Preparation and studying some physical properties of copper oxide nanoparticles
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Salem, Karrar Hazim, Al Hasan, Nuha Hadi Jasim, Alebadi, Shireen N., Alkhafaji, Mohammed Ayad, Zabibah, Rahman S., Judi, Hawraa K., Abdul-Zahra, Dalael Saad, Mohammed, Kahtan A., Kumar, Harish, Prakash, Chander, and Saxena, Kuldeep Kumar
- Abstract
ABSTRACTIn this study, we report the structural, optical, and surface properties of copper oxide (CuO) nanostructures that were produced using the chemical co-precipitation process at various specified pH values ranging from 8 to 12. X-ray diffraction, scanning electron microscopy, and elemental analysis (EDX) were used to describe the structural properties of the produced nanostructures, while UV–visible spectroscopy was used to examine their optical properties. The study of X-ray diffractometer patterns indicates the pure phase formation of CuO and this purity loses when pH reach to 13 where the impurities presented in the CuO. scanning electron microscopy images show the structural changes from nanoparticles shape at (pH 8) to nanoflowers shape (pH 10). The absorption band of CuO nanoparticles shows a blue shift with increase of pH.
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- 2024
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9. Preparation and characterisation of pure and Ni doped ZnO nanorods
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Abdulameer, Zahraa Thabet, Hasan, Nuha Hadi Jasim Al, Jarad, Amer N., Salem, Karrar Hazim, Alkhafaji, Mohammed Ayad, Zabibah, Rahman S., Mohammed, Kahtan A., Saxena, Kuldeep K, Kumar, Harish, Prakash, Chander, and Agrawal, Manoj Kumar
- Abstract
ABSTRACTOne-dimensional pure and Ni-doped zinc oxide nanorods (NRs) were prepared by chemical bath technique. Some physical properties like optical, morphological and structural were examined for prepared NRs. The result of X-ray diffraction XRD was exposed that the crystal structure was hexagonal for both pure and Ni-doped NRs where there is no change in the crystal system but some small shifting in diffraction angle appeared. The chemical composition and the presence of Ni atoms in the ZnO were approved by EDX test. Additionally, morphology investigation of the scanning electron microscopy (SEM) is conducted and showed that the shape of prepared materials was NRs. A red shift in the absorption spectrum and band gap happened after doping with Ni where the energy gap dropped from 3.72 for ZnO to 3.5 eV for ZnO:Ni.
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- 2024
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10. Efficient-VGG16: A Novel Ensemble Method for the Classification of COVID-19 X-ray Images in Contrast to Machine and Transfer Learning.
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Kumar, Sunil and Kumar, Harish
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X-ray imaging ,X-rays ,MACHINE tools ,COVID-19 ,CONVOLUTIONAL neural networks ,COMMUNICABLE diseases - Abstract
Corona Virus Disease 2019 (COVID-19) is a contagious respiratory disease characterized by its high transmissibility and exponential spread, presenting persistent difficulties. This investigation sought to incorporate machine learning (ML) and transfer learning (TL) and introduced Efficient-VGG16, a novel ensemble approach that integrated the EfficientNet-B0 and VGG16 architectures to classify chest X-ray images as either COVID-19 positive or non-COVID. The COVID-Xray-5k dataset used in the research was split into different training and testing sets (with ratios of 80:20, 75:25, and 70:30), preprocessed, and then used to evaluate the approach's effectiveness. Throughout the investigation, all procedures operated effectively at the same selected image size, 224*224. Preprocessing included Gaussian blur to remove noise and relics, while Contrast Limited Adaptive Histogram Equalization (CLAHE) adjusted contrast. Among the employed ML classifiers, XgBoost attained the highest accuracy, with F1 scores of 95.78% and 71.56%, respectively. In addition, the research investigated the effectiveness of TL using pre-trained convolutional neural networks (CNNs) such as VGG16, MobileNetV3, ResNet101, Densenet201, and EfficientNet-B0. EfficientNet-B0 achieved the highest levels of accuracy and F1 score, 99.31% and 93.72%, respectively. Furthermore, the proposed Efficient-VGG16 achieved accuracy and an F1 score of 99.46% and 98.41%, respectively, and outperformed TL with EfficientNet-B0 and XgBoost. The investigation demonstrated the effectiveness of the Efficient-VGG16 for accurately classifying COVID-19. [ABSTRACT FROM AUTHOR]
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- 2024
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11. Biomarkers for Early Detection of Charcot Arthropathy: A Prospective Study on Type 2 Diabetes Patients with Severe Neuropathy.
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Dharmadas, Salini, Kumar, Harish, Pillay, Minnie, Sukumaran Mangalanandan, Thacho, Vivek, Lakshmanan, Praveen, Valiyaparambil Pavithran, and Bal, Arun
- Abstract
Background: Charcot arthropathy (CA) is a progressive noninfectious inflammatory disease that causes irreversible destruction to pedal architecture in diabetic neuropathy (DN) patients. The debilitating prognosis demands early detection to prevent the development and progression of this disorder. Dysregulated and persistent production of inflammatory cytokines is reported as the key element in initiating osteoclastogenesis in CA. The study analyzed the potential association of markers of inflammation and bone turnover of prediagnostic serum samples on CA. Methods: Seventy-one type 2 severe DN patients were selected based on inclusion-exclusion criteria. Serum samples of interleukin 6 (IL-6), osteoprotegerin (OPG), bone alkaline phosphatase (BALP), and C-reactive protein (CRP) were analyzed. These patients were followed for the development of symptoms of CA for 12 months. In the year of monitoring, 7 patients developed CA (group 1), whereas the remaining 64 patients did not develop CA (group 2). Results: The rate of development of CA in patients with severe DN was 9.8%. In this group, significantly increased median values of Hb
A1c (group 2: 8.00 [7.00-9.00], group 1: 10.00 [9.25-11.50], P =.013); IL-6 (group 2: 1.21 [0.72-2.16], group 1: 11.08 [6.65-63.64], P =.008); and CRP (group 2: 1.25 [0.78-3.20], group 1: 3.31 [1.18-41.33], P =.041) were found. The receiver operating characteristic analysis showed that IL-6 was more strongly associated with the onset of CA (IL-6: area under the curve = 0.808; P =.008) than CRP. Cut-off values of ≥6.6 for IL-6 show potential to rule out CA in high-risk patients, with a positive predictive value of 26.1%, a negative predictive value of 97.9%, a sensitivity of 85.7%, and a specificity of 73.4%. Conclusion: In our study population, we found that an exacerbated inflammatory state, reflected by IL-6 values, generally occurred in DN patients before the clinical detection of CA. Level of Evidence: Level II, prospective comparative study. [ABSTRACT FROM AUTHOR]- Published
- 2024
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12. Implications of Additive Manufacturing on Supply Chain Management
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Bhasin, Shallu, Singari, Ranganath M., Arora, Pawan Kumar, and Kumar, Harish
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Additive manufacturing is emerging as one of the manufacturing technologies, which affect the traditional supply chain management. The traditional supply chain is based on a push system, whereas an additional supply chain is based on a pull system. In this work we have found the impact of 3D printing on supply chain management, what the risks and opportunities of 3D printing on the supply chain are and, also what the companies are doing to leverages these opportunities and risks. It has been concluded that the additive supply chain has drastically changed the traditional supply chain in four key ways i.e. time, quality, speed, and environmental impact. It will result in the effective management of resources, which is of immense importance, keeping in mind the sustainable development goals of a blue-chip organization. It will be cost-effective and will reduce the lead-time of the supply chain. It will result in increased customer satisfaction, as the product will be produced by mass customization and improved quality. Moreover, this will lead to flexibility in the manufacturing process, which will enhance industrial efficiency. Therefore, we can say that this research will give us the vision of different industries in India in the coming years.
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- 2024
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13. Biomarkers for Early Detection of Charcot Arthropathy: A Prospective Study on Type 2 Diabetes Patients with Severe Neuropathy
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Dharmadas, Salini, Kumar, Harish, Pillay, Minnie, Sukumaran Mangalanandan, Thacho, Vivek, Lakshmanan, Praveen, Valiyaparambil Pavithran, and Bal, Arun
- Abstract
Background: Charcot arthropathy (CA) is a progressive noninfectious inflammatory disease that causes irreversible destruction to pedal architecture in diabetic neuropathy (DN) patients. The debilitating prognosis demands early detection to prevent the development and progression of this disorder. Dysregulated and persistent production of inflammatory cytokines is reported as the key element in initiating osteoclastogenesis in CA. The study analyzed the potential association of markers of inflammation and bone turnover of prediagnostic serum samples on CA.Methods: Seventy-one type 2 severe DN patients were selected based on inclusion-exclusion criteria. Serum samples of interleukin 6 (IL-6), osteoprotegerin (OPG), bone alkaline phosphatase (BALP), and C-reactive protein (CRP) were analyzed. These patients were followed for the development of symptoms of CA for 12 months. In the year of monitoring, 7 patients developed CA (group 1), whereas the remaining 64 patients did not develop CA (group 2).Results: The rate of development of CA in patients with severe DN was 9.8%. In this group, significantly increased median values of HbA1c(group 2: 8.00 [7.00-9.00], group 1: 10.00 [9.25-11.50], P= .013); IL-6 (group 2: 1.21 [0.72-2.16], group 1: 11.08 [6.65-63.64], P= .008); and CRP (group 2: 1.25 [0.78-3.20], group 1: 3.31 [1.18-41.33], P= .041) were found. The receiver operating characteristic analysis showed that IL-6 was more strongly associated with the onset of CA (IL-6: area under the curve = 0.808; P= .008) than CRP. Cut-off values of ≥6.6 for IL-6 show potential to rule out CA in high-risk patients, with a positive predictive value of 26.1%, a negative predictive value of 97.9%, a sensitivity of 85.7%, and a specificity of 73.4%.Conclusion: In our study population, we found that an exacerbated inflammatory state, reflected by IL-6 values, generally occurred in DN patients before the clinical detection of CA.Level of Evidence: Level II, prospective comparative study.
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- 2024
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14. Crystal growth and magnetic properties of pyrochlore iridate Bi2Ir2O7
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Kumar, Harish, Klinger, M., Jesche, A., and Kuntscher, C. A.
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- 2024
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15. Deciphering the Therapeutic Applications of Nanomedicine in Ovarian Cancer Therapy: An Overview
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Mathur, Pooja, Bhatt, Shailendra, Kumar, Suresh, Kamboj, Sweta, Kamboj, Rohit, Rana, Arpana, Kumar, Harish, and Verma, Ravinder
- Abstract
The majority of deadly cancers that afflict the female reproductive system occur in the ovary. Around 1,40,000 women worldwide die from ovarian cancer each year, making it the sixth most common cancer-associated deceases among females in the United States. Modern, cutting-edge treatments like chemotherapy and surgery frequently produce full remissions, but the recurrence rate is still very high. When this crippling condition is diagnosed, there are frequently few therapeutic choices available because of how quietly it manifests.Healthcare practitioners must have a fundamental grasp of the warning signs and symptoms of ovarian cancer, as well as the imaging techniques and treatment choices available, to give the patient the best care possible. The discipline of medical nanotechnology has gained a lot of momentum in recent years in resolving issues and enhancing the detection and treatment of different illnesses, including cancer.This article gives a brief summary of types, risk factors and approaches to ovarian cancer treatment. We subsequently discussed the pathophysiology of ovarian cancer with the risk factors. This review also emphasizes the various signalling pathways involved in ovarian cancer. Our comprehensive integration of recent findings in fundamental research in the nano arena reveals the strong interest in these nanomedicines in ovarian cancer treatment. However, these nanomedicines still require more research, as indicated by the comparatively small number of clinical trials ongoing. This article will provide a reference for ovarian cancer treatment.
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- 2024
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16. Efficient Alternative Finite Difference WENO Schemes for Hyperbolic Systems with Non-conservative Products
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Balsara, Dinshaw S., Bhoriya, Deepak, Shu, Chi-Wang, and Kumar, Harish
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Higher order finite difference Weighted Essentially Non-oscillatory (WENO) schemes for conservation laws represent a technology that has been reasonably consolidated. They are extremely popular because, when applied to multidimensional problems, they offer high order accuracy at a fraction of the cost of finite volume WENO or DG schemes. They come in two flavors. There is the classical finite difference WENO (FD-WENO) method (Shu and Osher in J. Comput. Phys. 83: 32–78, 1989). However, in recent years there is also an alternative finite difference WENO (AFD-WENO) method which has recently been formalized into a very useful general-purpose algorithm for conservation laws (Balsara et al. in Efficient alternative finite difference WENO schemes for hyperbolic conservation laws, submitted to CAMC, 2023). However, the FD-WENO algorithm has only very recently been formulated for hyperbolic systems with non-conservative products (Balsara et al. in Efficient finite difference WENO scheme for hyperbolic systems with non-conservative products, to appear CAMC, 2023). In this paper, we show that there are substantial advantages in obtaining an AFD-WENO algorithm for hyperbolic systems with non-conservative products. Such an algorithm is documented in this paper. We present an AFD-WENO formulation in a fluctuation form that is carefully engineered to retrieve the flux form when that is warranted and nevertheless extends to non-conservative products. The method is flexible because it allows any Riemann solver to be used. The formulation we arrive at is such that when non-conservative products are absent it reverts exactly to the formulation in the second citation above which is in the exact flux conservation form. The ability to transition to a precise conservation form when non-conservative products are absent ensures, via the Lax-Wendroff theorem, that shock locations will be exactly captured by the method. We present two formulations of AFD-WENO that can be used with hyperbolic systems with non-conservative products and stiff source terms with slightly differing computational complexities. The speeds of our new AFD-WENO schemes are compared to the speed of the classical FD-WENO algorithm from the first of the above-cited papers. At all orders, AFD-WENO outperforms FD-WENO. We also show a very desirable result that higher order variants of AFD-WENO schemes do not cost that much more than their lower order variants. This is because the larger number of floating point operations associated with larger stencils is almost very efficiently amortized by the CPU when the AFD-WENO code is designed to be cache friendly. This should have great, and very beneficial, implications for the role of our AFD-WENO schemes in the Peta- and Exascale computing. We apply the method to several stringent test problems drawn from the Baer-Nunziato system, two-layer shallow water equations, and the multicomponent debris flow. The method meets its design accuracy for the smooth flow and can handle stringent problems in one and multiple dimensions. Because of the pointwise nature of its update, AFD-WENO for hyperbolic systems with non-conservative products is also shown to be a very efficient performer on problems with stiff source terms.
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- 2024
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17. NiO@PANI based Nanocomposites as an Advanced Functional Material: Experimental and Computational Approach
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Kumar, Harish and Luthra, Manisha
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Background: Individually, metal nanoparticles (NPs) and conducting polymers show unique properties due to small size, large surface area, and high order of conductivity. But their combination may result in a synergistic effect in properties.Methods: The NiO NPs and conducting polymer Polyaniline were prepared by modified Sol-gel and chemical oxidative methods, respectively. Powder XRD, FTIR, TEM, and UV-visible methods were used for the structural evaluation. The computational (DFT) study was performed to support experimental results. The NiO/Polyaniline (PANI) nanocomposites (NCs) were explored as corrosion inhibitors, electrical conductors, and photocatalytic agents.Results: The NiO/Polyaniline NCs showed 91.52% corrosion inhibition efficiency at 1000 ppm concentration. The photocatalytic activity was investigated against methylene blue dye under ultraviolet light. The NiO/Polyaniline NCs decompose 90% of organic dye. The NCs exhibit good conducting, corrosion inhibition, and photocatalytic activity.Conclusion: The metal oxide (NiO NPs) and PANI-based NCs can be used as corrosion inhibitors, conducting material, and for the degradation of organic compounds (dyes) in impure water.
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- 2024
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18. Blended Tele-mentoring Support for Strengthening Antenatal Care by Private Health care Facilities: FOGSI VISTRIT INITIATIVE
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Kumar, Priti, Gandhi, Alpesh, Tank, Jaydeep, Gupta, Sachin, Bajpayee, Devina, Kumar, Harish, Datta, Nivedita, Sharma, K. Aparna, Rana, Anubhuti, and Pandey, Anamika
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Introduction: The objective of the present initiative was to build capacity of health care providers in private sector along with standardisation of care during antenatal period for common antenatal problems of GDM and iron deficiency anaemia in private sector. Methods: A pilot project for all levels of health care providers including doctors, nurses, counsellors and laboratory technicians of 34 private facilities in six districts of Jharkhand was planned. Training modules for GDM and anaemia based on government of India guidelines were developed. End line evaluation included data collection and descriptive analysis of quantitative data quality scores from assessment standards on GDM and anaemia in pregnancy. Results: Knowledge assessment of health care providers and doctors through baseline and end line knowledge assessment survey questionnaire showed that 100% health care providers who were trained scored 85% or more in knowledge assessment questionnaires as seen by baseline and end line questionnaire results. All project hospitals (n= 34) in Jharkhand achieved quality standards of care in intervention period for gestational diabetes mellitus and anaemia in pregnancy. They achieved total score more than 80% and exceeded target of 80% of the quality standards. Conclusion: A systematic strengthening of private health care facilities through a blended tele-mentoring and onsite support is possible.
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- 2024
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19. Efficient Alternative Finite Difference WENO Schemes for Hyperbolic Conservation Laws
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Balsara, Dinshaw S., Bhoriya, Deepak, Shu, Chi-Wang, and Kumar, Harish
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Higher order finite difference Weighted Essentially Non-Oscillatory (FD-WENO) schemes for conservation laws are extremely popular because, for multidimensional problems, they offer high order accuracy at a fraction of the cost of finite volume WENO or DG schemes. Such schemes come in two formulations. The very popular classical FD-WENO method (Shu and Osher J Comput Phys 83: 32–78, 1989) relies on two reconstruction steps applied to two split fluxes. However, the method cannot accommodate different types of Riemann solvers and cannot preserve free stream boundary conditions on curvilinear meshes. This limits its utility. The alternative FD-WENO (AFD-WENO) method can overcome these deficiencies, however, much less work has been done on this method. The reasons are three-fold. First, it is difficult for the casual reader to understand the intricate logic that requires higher order derivatives of the fluxes to be evaluated at zone boundaries. The analytical methods for deriving the update equation for AFD-WENO schemes are somewhat recondite. To overcome that difficulty, we provide an easily accessible script that is based on a computer algebra system in Appendix A of this paper. Second, the method relies on interpolation rather than reconstruction, and WENO interpolation formulae have not been documented in the literature as thoroughly as WENO reconstruction formulae. In this paper, we explicitly provide all necessary WENO interpolation formulae that are needed for implementing the AFD-WENO up to the ninth order. The third reason is that the AFD-WENO requires higher order derivatives of the fluxes to be available at zone boundaries. Since those derivatives are usually obtained by finite differencing the zone-centered fluxes, they become susceptible to a Gibbs phenomenon when the solution is non-smooth. The inclusion of those fluxes is also crucially important for preserving the order property when the solution is smooth. This has limited the utility of the AFD-WENO in the past even though the method per se has many desirable features. Some efforts to mitigate the effect of finite differencing of the fluxes have been tried, but so far they have been done on a case by case basis for the PDE being considered. In this paper we find a general-purpose strategy that is based on a different type of the WENO interpolation. This new WENO interpolation takes the first derivatives of the fluxes at zone centers as its inputs and returns the requisite non-linearly hybridized higher order derivatives of flux-like terms at the zone boundaries as its output. With these three advances, we find that the AFD-WENO becomes a robust and general-purpose solution strategy for large classes of conservation laws. It allows any Riemann solver to be used. The AFD-WENO has a computational complexity that is entirely comparable to the classical FD-WENO, because it relies on two interpolation steps which cost the same as the two reconstruction steps in the classical FD-WENO. We apply the method to several stringent test problems drawn from Euler flow, relativistic hydrodynamics (RHD), and ten-moment equations. The method meets its design accuracy for smooth flow and can handle stringent problems in one and multiple dimensions.
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- 2024
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20. Enablers Driving Success of Artificial Intelligence in Business Performance: A TISM-MICMAC Approach
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Sharma, Vijay Kumar and Kumar, Harish
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Organizations have recently seen a significant transition from implementing technologies in business processes. The cutting-edge technology, such as artificial intelligence (AI), makes business firms more competitive in a dynamic world. This study aims to investigate key variables that drive success of AI to improve financial performance and values of a firm. The inter-relationships among variables are established to explain the emergence of AI in a novel hierarchical model. The study deployed “Total Interpretive Structural Modeling” and “Cross-Impact Matrix Multiplication Applied to Classification” for developing a hierarchical model to analyze inter-relationships among identified key variables. The results hold important insights for strategic decisions and are useful for business firms to invest in advanced technology, such as AI, to enhance business performance and revenue in domestic as well as in global markets. Insights drawn from analysis will help business firms to grow in a competitive landscape. The decision makers can utilize the proposed hierarchical model to enhance the performance of business along with process automation. The found interactions among the key variables can be utilized to understand the ecosystem that drives business performance.
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- 2024
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21. Analysing consumer behaviour by integrating digital payment awareness into the UTAUT model
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Kumar, Harish and Sofat, Rajni
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Currently, the market is flooded with internet-based services, including digital payment. The study examines the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, and digital payment awareness on behavioural intention and consumer buying behaviour. It also investigates mediating role of behavioural intention between independent and dependent variables. Surveys were used to learn about digital payment patterns in Uttarakhand, India. We used SmartPLS-3.0 to test hypotheses. Overall, performance expectancy, effort expectancy, social influence, facilitating conditions, and digital payment awareness favourably affected customer buying behaviour. However, behavioural intention partially mediated the link between performance expectancy, social influence, facilitating conditions, and consumer buying behaviour, and fully mediated the relationship between effort expectancies, digital payment awareness, and consumer buying behaviour. The results of this study could help fintech companies, banks, payment gateways, and governments build user-friendly technological improvements, regulatory rules, and frameworks to make digital payments better and more accessible for everyone.
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- 2024
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22. Analysing antecedent and consequences of trust in m-commerce for sustainability in tourism industry in Uttarakhand
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Anuj, Chauhan, Jitendra Singh, Agarwal, Pankaj, Kumar, Harish, Sharma, Megha, and Thapliyal, Madhur
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This study aims to apply a hypothesised model to better understand the phenomenon of m-commerce in the tourism sector and recognise the mediating role of trust (TST) in relation to contextual factors of perceived security (PSEC), electronic word-of-mouth (eWOM), and perceived quality (PQ) to purchase intention (IB). A total of 417 travellers from northern Indian tourist destinations took part in the questionnaire-based study. SEM was applied to analyse the measurement model and hypothesis. It was found that TST mediates the associations between PSEC and IB, eWOM and IB, and PQ and IB. Findings also confirm the positive connotation between PSEC and TST, eWOM and trust, PQ and TST. The findings of this study will assist the tourism sector in realising the importance of trust in visitors' purchasing intentions. This study draws attention to the tourism sector's need to improve PSEC, eWOM, and PQ to build visitor confidence.
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- 2024
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23. Outcomes of a hypertension care program based on task-sharing with private pharmacies: a retrospective study from two blocks in rural India
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Das, Hemanshu, Sachdeva, Ashish, Kumar, Harish, Krishna, Ashish, Moran, Andrew E., Pathni, Anupam K., Sharma, Bhawna, Singh, Bhanu P., Ranjan, Manish, and Deo, Sarang
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Low density of formal care providers in rural India results in restricted and delayed access to standardized management of hypertension. Task-sharing with pharmacies, typically the first point of contact for rural populations, can bridge the gap in access to formal care and improve health outcomes. In this study, we implemented a hypertension care program involving task-sharing with twenty private pharmacies between November 2020 and April 2021 in two blocks of Bihar, India. Pharmacists conducted free hypertension screening, and a trained physician offered free consultations at the pharmacy. We calculated the number of subjects screened, initiated on treatment (enrolled) and the change in blood pressure using the data collected through the program application. Of the 3403 subjects screened at pharmacies, 1415 either reported having a history of hypertension or had elevated blood pressure during screening. Of these, 371 (26.22%) were enrolled in the program. Of these, 129 (34.8%) made at least one follow-up visit. For these subjects, the adjusted average difference in systolic and diastolic blood pressure between the screening and follow-up visits was −11.53 (−16.95 to −6.11, 95% CI) and −4.68 (−8.53 to −0.82, 95% CI) mmHg, respectively. The adjusted odds of blood pressure being under control in this group during follow-up visits compared to screening visit was 7.07 (1.29 to 12.85, 95% CI). Task-sharing with private pharmacies can lead to early detection and improved control of blood pressure in a resource-constrained setting. Additional strategies to increase patient screening and retention rates are needed to ensure sustained health benefits.
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- 2023
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24. Identification of prospective covalent inhibitors for SARS-CoV-2 main protease using structure-based approach
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Gayatri, Shenvi Kudchadker, Chhabra, Vaishnavi, Kumar, Harish, and Sobhia, M. Elizabeth
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AbstractThe rapid global spread of SARS-CoV-2 has recently caused havoc and forced the world into a state of the pandemic causing respiratory, gastrointestinal, hepatic, and neurologic diseases. It persistently, through mutation, develops into new variants of the virus that have appeared over time. As main protease (Mpro) is involved in proteolysis of two overlapping polyproteins pp1aand pp1abto produce 16 non-structural proteins having a paramount factor in the virus replication that have a cysteine–histidine catalytic dyad. A computational approach, guiding a covalent docking as it offers higher potency, long duration of action and decreased drug resistance advantages over the conventional docking of the ligands on a catalytic dyad, is applied for SARS-CoV-2 main protease (Mpro) in this manuscript to divulge better molecules. Mproactive site contains Cys145 residue which act as a nucleophile and can donate its electron to an electrophilic molecule by interacting covalently. Furthermore, the ligand–protein complexes are allowed to simulate their dynamic studies to look into their time-based interaction stability and also, a parallel study of ADME properties for the hit molecules is also performed. Important insights from the studies revealed that the interactions are persistent and molecules may be considered for further optimization in clinical investigation.Communicated by Ramaswamy H. Sarma.
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- 2023
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25. Correlation Between Synovial Fluid Levels of Matrix Metalloproteinase’s (MMP-1, MMP-3, and MMP-9) and TNF-α with the Severity of Osteoarthritis Knee in Rural Indian Population
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Kumar, Sunil, Kumar, Harish, Mittal, Ankit, Singh, Prashant Pratap, Yadav, Vikas, Kumar, Dinesh, Ahmad, Ishan, and Mishra, Vyutpanna
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Background: In India, 22% to 39% of the ageing population suffers from degenerative knee osteoarthritis (OA), making it the most prevalent joint disorder in the knee. MMP-1, MMP-3, and MMP-9 protein expression levels have all been associated with OA. The aim of the present study was to establish a relationship between synovial fluid levels of matrix metalloproteinases (MMP-1, MMP-3, and MMP-9), and tumour necrosis factor-alpha (TNF-α) with different Kellgren–Lawrence Grading scale as per the severity of knee osteoarthritis (OA). Methods: This hospital-based observational study included 87 individuals with knee osteoarthritis examined at the orthopaedics department outpatient clinic at the tertiary care teaching hospital in rural area of north India. In-person interviews were conducted to gather data, through a semi-structured, pretested interview schedule. To determine the degree and severity of OA, the levels of the enzymes matrix metalloproteinase MMP-1, MMP-3, and MMP-9 as well as tumour necrosis factor (TNF–α) were assessed in the synovial fluid of knee of each study participant. Results: The levels of MMP-1, MMP-3, MMP-9, and TNF-α in synovial fluid were significantly correlated with the severity of osteoarthritis as determined by the Kellgren–Lawrence Grading Scale. Age, duration of symptoms and BMI showed a strong positive and significant correlation with biochemical markers (MMP-1, MMP-3, MMP-9, and TNF-α) in synovial fluid of Knee. Conclusion: Level of biochemical markers (MMP-1, -3, -9, and TNF-α) in synovial fluid act as diagnostic markers and have a positive correlation with the severity of osteoarthritis knee, age, weight/BMI and duration of disease. However, no significant correlation was found between the level of aforementioned biochemical markers with sex, height, inflammation of the knee, morning stiffness, and age of onset of disease.
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- 2023
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26. Spin–Phonon and Electron–Phonon Coupling in Pyrochlore Iridates (Y1–xPrx)2Ir2O7: An Investigation with Raman Spectroscopy.
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Kumar, Harish, Sathe, V G, and Pramanik, A K
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- 2023
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27. Delayed diagnosis of plasma cell disorder related Fanconi syndrome in young adults presenting as osteomalacia: report of two cases with normokalemia and normal haematological parameters at the time of presentation.
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Franklin, Joel, Pavithran, Praveen Valliyaparambil, Sidharthan, Neeraj, Vijayan, Seethalekshmy Nalumackal, Abraham, Nithya, Bhavani, Nisha, Menon, Vadayath Usha, Nair, Vasantha, and Kumar, Harish
- Abstract
Adult-onset hypophosphatemic osteomalacia is rare and diagnosis is frequently delayed. Fanconi syndrome (FS) due to monoclonal gammopathy is a well-recognized, but rare cause of hypophosphatemia. The relatively young age of patients and normal routine hematological parameters often results in late recognition of this treatable disease entity. Low phosphorus, elevated alkaline phosphatase, mildly impaired renal function and hypokalemia are often the only abnormalities on routine evaluation. We summarize the clinico-pathological features of two cases who initially presented with fractures and proximal myopathy and were subsequently found to have FS secondary to light chain proximal tubulopathy. Atypical features like absence of hypokalemia at presentation and elevated fibroblast growth factor 23 (FGF 23), a marker of oncogenic osteomalacia were noted. Marked clinical improvement and recovery of renal parameters were evident with phosphate supplements and chemotherapy for the plasma cell disorder. FS due to monoclonal gammopathy may present with atypical features and diagnosis may be challenging. [ABSTRACT FROM AUTHOR]
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- 2023
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28. Delayed diagnosis of plasma cell disorder related Fanconi syndrome in young adults presenting as osteomalacia: report of two cases with normokalemia and normal haematological parameters at the time of presentation.
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Franklin, Joel, Pavithran, Praveen Valliyaparambil, Sidharthan, Neeraj, Vijayan, Seethalekshmy Nalumackal, Abraham, Nithya, Bhavani, Nisha, Menon, Vadayath Usha, Nair, Vasantha, and Kumar, Harish
- Abstract
Adult-onset hypophosphatemic osteomalacia is rare and diagnosis is frequently delayed. Fanconi syndrome (FS) due to monoclonal gammopathy is a well-recognized, but rare cause of hypophosphatemia. The relatively young age of patients and normal routine hematological parameters often results in late recognition of this treatable disease entity. Low phosphorus, elevated alkaline phosphatase, mildly impaired renal function and hypokalemia are often the only abnormalities on routine evaluation. We summarize the clinico-pathological features of two cases who initially presented with fractures and proximal myopathy and were subsequently found to have FS secondary to light chain proximal tubulopathy. Atypical features like absence of hypokalemia at presentation and elevated fibroblast growth factor 23 (FGF 23), a marker of oncogenic osteomalacia were noted. Marked clinical improvement and recovery of renal parameters were evident with phosphate supplements and chemotherapy for the plasma cell disorder. FS due to monoclonal gammopathy may present with atypical features and diagnosis may be challenging. [ABSTRACT FROM AUTHOR]
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- 2023
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29. Performance-based natural rubber composites reinforced with jute fibers and nano-silica: thermal, morphological, and mechanical studies with statistical optimization.
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Kumar, Sumit, Lal, Sohan, Jagdeva, Geetanjali, Arora, Sanjiv, Kumar, Parvin, Soni, R. K., Kumar, Harish, Kumar, Sunil, and Panchal, Suresh
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- 2023
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30. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021
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Ong, Kanyin Liane, Stafford, Lauryn K, McLaughlin, Susan A, Boyko, Edward J, Vollset, Stein Emil, Smith, Amanda E, Dalton, Bronte E, Duprey, Joe, Cruz, Jessica A, Hagins, Hailey, Lindstedt, Paulina A, Aali, Amirali, Abate, Yohannes Habtegiorgis, Abate, Melsew Dagne, Abbasian, Mohammadreza, Abbasi-Kangevari, Zeinab, Abbasi-Kangevari, Mohsen, Abd ElHafeez, Samar, Abd-Rabu, Rami, Abdulah, Deldar Morad, Abdullah, Abu Yousuf Md, Abedi, Vida, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Abu-Gharbieh, Eman, Abu-Zaid, Ahmed, Adane, Tigist Demssew, Adane, Denberu Eshetie, Addo, Isaac Yeboah, Adegboye, Oyelola A, Adekanmbi, Victor, Adepoju, Abiola Victor, Adnani, Qorinah Estiningtyas Sakilah, Afolabi, Rotimi Felix, Agarwal, Gina, Aghdam, Zahra Babaei, Agudelo-Botero, Marcela, Aguilera Arriagada, Constanza Elizabeth, Agyemang-Duah, Williams, Ahinkorah, Bright Opoku, Ahmad, Danish, Ahmad, Rizwan, Ahmad, Sajjad, Ahmad, Aqeel, Ahmadi, Ali, Ahmadi, Keivan, Ahmed, Ayman, Ahmed, Ali, Ahmed, Luai A, Ahmed, Syed Anees, Ajami, Marjan, Akinyemi, Rufus Olusola, Al Hamad, Hanadi, Al Hasan, Syed Mahfuz, AL-Ahdal, Tareq Mohammed Ali, Alalwan, Tariq A, Al-Aly, Ziyad, AlBataineh, Mohammad T, Alcalde-Rabanal, Jacqueline Elizabeth, Alemi, Sharifullah, Ali, Hassam, Alinia, Tahereh, Aljunid, Syed Mohamed, Almustanyir, Sami, Al-Raddadi, Rajaa M, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Amiri, Sohrab, Amusa, Ganiyu Adeniyi, Andrei, Catalina Liliana, Anjana, Ranjit Mohan, Ansar, Adnan, Ansari, Golnoosh, Ansari-Moghaddam, Alireza, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Aravkin, Aleksandr Y, Areda, Demelash, Arifin, Hidayat, Arkew, Mesay, Armocida, Benedetta, Ärnlöv, Johan, Artamonov, Anton A, Arulappan, Judie, Aruleba, Raphael Taiwo, Arumugam, Ashokan, Aryan, Zahra, Asemu, Mulu Tiruneh, Asghari-Jafarabadi, Mohammad, Askari, Elaheh, Asmelash, Daniel, Astell-Burt, Thomas, Athar, Mohammad, Athari, Seyyed Shamsadin, Atout, Maha Moh'd Wahbi, Avila-Burgos, Leticia, Awaisu, Ahmed, Azadnajafabad, Sina, B, Darshan B, Babamohamadi, Hassan, Badar, Muhammad, Badawi, Alaa, Badiye, Ashish D, Baghcheghi, Nayereh, Bagheri, Nasser, Bagherieh, Sara, Bah, Sulaiman, Bahadory, Saeed, Bai, Ruhai, Baig, Atif Amin, Baltatu, Ovidiu Constantin, Baradaran, Hamid Reza, Barchitta, Martina, Bardhan, Mainak, Barengo, Noel C, Bärnighausen, Till Winfried, Barone, Mark Thomaz Ugliara, Barone-Adesi, Francesco, Barrow, Amadou, Bashiri, Hamideh, Basiru, Afisu, Basu, Sanjay, Basu, Saurav, Batiha, Abdul-Monim Mohammad, Batra, Kavita, Bayih, Mulat Tirfie, Bayileyegn, Nebiyou Simegnew, Behnoush, Amir Hossein, Bekele, Alehegn Bekele, Belete, Melaku Ashagrie, Belgaumi, Uzma Iqbal, Belo, Luis, Bennett, Derrick A, Bensenor, Isabela M, Berhe, Kidanemaryam, Berhie, Alemshet Yirga, Bhaskar, Sonu, Bhat, Ajay Nagesh, Bhatti, Jasvinder Singh, Bikbov, Boris, Bilal, Faiq, Bintoro, Bagas Suryo, Bitaraf, Saeid, Bitra, Veera R, Bjegovic-Mikanovic, Vesna, Bodolica, Virginia, Boloor, Archith, Brauer, Michael, Brazo-Sayavera, Javier, Brenner, Hermann, Butt, Zahid A, Calina, Daniela, Campos, Luciana Aparecida, Campos-Nonato, Ismael R, Cao, Yin, Cao, Chao, Car, Josip, Carvalho, Márcia, Castañeda-Orjuela, Carlos A, Catalá-López, Ferrán, Cerin, Ester, Chadwick, Joshua, Chandrasekar, Eeshwar K, Chanie, Gashaw Sisay, Charan, Jaykaran, Chattu, Vijay Kumar, Chauhan, Kirti, Cheema, Huzaifa Ahmad, Chekol Abebe, Endeshaw, Chen, Simiao, Cherbuin, Nicolas, Chichagi, Fatemeh, Chidambaram, Saravana Babu, Cho, William C S, Choudhari, Sonali Gajanan, Chowdhury, Rajiv, Chowdhury, Enayet Karim, Chu, Dinh-Toi, Chukwu, Isaac Sunday, Chung, Sheng-Chia, Coberly, Kaleb, Columbus, Alyssa, Contreras, Daniela, Cousin, Ewerton, Criqui, Michael H, Cruz-Martins, Natália, Cuschieri, Sarah, Dabo, Bashir, Dadras, Omid, Dai, Xiaochen, Damasceno, Albertino Antonio Moura, Dandona, Rakhi, Dandona, Lalit, Das, Saswati, Dascalu, Ana Maria, Dash, Nihar Ranjan, Dashti, Mohsen, Dávila-Cervantes, Claudio Alberto, De la Cruz-Góngora, Vanessa, Debele, Gebiso Roba, Delpasand, Kourosh, Demisse, Fitsum Wolde, Demissie, Getu Debalkie, Deng, Xinlei, Denova-Gutiérrez, Edgar, Deo, Salil V, Dervišević, Emina, Desai, Hardik Dineshbhai, Desale, Aragaw Tesfaw, Dessie, Anteneh Mengist, Desta, Fikreab, Dewan, Syed Masudur Rahman, Dey, Sourav, Dhama, Kuldeep, Dhimal, Meghnath, Diao, Nancy, Diaz, Daniel, Dinu, Monica, Diress, Mengistie, Djalalinia, Shirin, Doan, Linh Phuong, Dongarwar, Deepa, dos Santos Figueiredo, Francisco Winter, Duncan, Bruce B, Dutta, Siddhartha, Dziedzic, Arkadiusz Marian, Edinur, Hisham Atan, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Elgendy, Islam Y, Elhadi, Muhammed, El-Huneidi, Waseem, Elmeligy, Omar Abdelsadek Abdou, Elmonem, Mohamed A, Endeshaw, Destaw, Esayas, Hawi Leul, Eshetu, Habitu Birhan, Etaee, Farshid, Fadhil, Ibtihal, Fagbamigbe, Adeniyi Francis, Fahim, Ayesha, Falahi, Shahab, Faris, MoezAlIslam Ezzat Mahmoud, Farrokhpour, Hossein, Farzadfar, Farshad, Fatehizadeh, Ali, Fazli, Ghazal, Feng, Xiaoqi, Ferede, Tomas Y, Fischer, Florian, Flood, David, Forouhari, Ali, Foroumadi, Roham, Foroutan Koudehi, Masoumeh, Gaidhane, Abhay Motiramji, Gaihre, Santosh, Gaipov, Abduzhappar, Galali, Yaseen, Ganesan, Balasankar, Garcia-Gordillo, MA, Gautam, Rupesh K, Gebrehiwot, Mesfin, Gebrekidan, Kahsu Gebrekirstos, Gebremeskel, Teferi Gebru, Getacher, Lemma, Ghadirian, Fataneh, Ghamari, Seyyed-Hadi, Ghasemi Nour, Mohammad, Ghassemi, Fariba, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Gopalani, Sameer Vali, Guadie, Habtamu Alganeh, Guan, Shi-Yang, Gudayu, Temesgen Worku, Guimarães, Rafael Alves, Guled, Rashid Abdi, Gupta, Rajeev, Gupta, Kartik, Gupta, Veer Bala, Gupta, Vivek Kumar, Gyawali, Bishal, Haddadi, Rasool, Hadi, Najah R, Haile, Teklehaimanot Gereziher, Hajibeygi, Ramtin, Haj-Mirzaian, Arvin, Halwani, Rabih, Hamidi, Samer, Hankey, Graeme J, Hannan, Md Abdul, Haque, Shafiul, Harandi, Hamid, Harlianto, Netanja I, Hasan, S M Mahmudul, Hasan, Syed Shahzad, Hasani, Hamidreza, Hassanipour, Soheil, Hassen, Mohammed Bheser, Haubold, Johannes, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Hessami, Kamran, Hiraike, Yuta, Holla, Ramesh, Hossain, Sahadat, Hossain, Md Shakhaoat, Hosseini, Mohammad-Salar, Hosseinzadeh, Mehdi, Hosseinzadeh, Hassan, Huang, Junjie, Huda, Md Nazmul, Hussain, Salman, Huynh, Hong-Han, Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Ikeda, Nayu, Ilic, Irena M, Ilic, Milena D, Inbaraj, Leeberk Raja, Iqbal, Afrin, Islam, Sheikh Mohammed Shariful, Islam, Rakibul M, Ismail, Nahlah Elkudssiah, Iso, Hiroyasu, Isola, Gaetano, Itumalla, Ramaiah, Iwagami, Masao, Iwu, Chidozie C D, Iyamu, Ihoghosa Osamuyi, Iyasu, Assefa N, Jacob, Louis, Jafarzadeh, Abdollah, Jahrami, Haitham, Jain, Rajesh, Jaja, Chinwe, Jamalpoor, Zahra, Jamshidi, Elham, Janakiraman, Balamurugan, Jayanna, Krishnamurthy, Jayapal, Sathish Kumar, Jayaram, Shubha, Jayawardena, Ranil, Jebai, Rime, Jeong, Wonjeong, Jin, Yinzi, Jokar, Mohammad, Jonas, Jost B, Joseph, Nitin, Joseph, Abel, Joshua, Charity Ehimwenma, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Kaambwa, Billingsley, Kabir, Ali, Kabthymer, Robel Hussen, Kadashetti, Vidya, Kahe, Farima, Kalhor, Rohollah, Kandel, Himal, Karanth, Shama D, Karaye, Ibraheem M, Karkhah, Samad, Katoto, Patrick DMC, Kaur, Navjot, Kazemian, Sina, Kebede, Sewnet Adem, Khader, Yousef Saleh, Khajuria, Himanshu, Khalaji, Amirmohammad, Khan, Moien AB, Khan, Maseer, Khan, Ajmal, Khanal, Saval, Khatatbeh, Moawiah Mohammad, Khater, Amir M, Khateri, Sorour, khorashadizadeh, Fatemeh, Khubchandani, Jagdish, Kibret, Biruk Getahun, Kim, Min Seo, Kimokoti, Ruth W, Kisa, Adnan, Kivimäki, Mika, Kolahi, Ali-Asghar, Komaki, Somayeh, Kompani, Farzad, Koohestani, Hamid Reza, Korzh, Oleksii, Kostev, Karel, Kothari, Nikhil, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Yuvaraj, Kuate Defo, Barthelemy, Kuddus, Mohammed, Kuddus, Md Abdul, Kumar, Rakesh, Kumar, Harish, Kundu, Satyajit, Kurniasari, Maria Dyah, Kuttikkattu, Ambily, La Vecchia, Carlo, Lallukka, Tea, Larijani, Bagher, Larsson, Anders O, Latief, Kamaluddin, Lawal, Basira Kankia, Le, Thao Thi Thu, Le, Trang Thi Bich, Lee, Shaun Wen Huey, Lee, Munjae, Lee, Wei-Chen, Lee, Paul H, Lee, Sang-woong, Lee, Seung Won, Legesse, Samson Mideksa, Lenzi, Jacopo, Li, Yongze, Li, Ming-Chieh, Lim, Stephen S, Lim, Lee-Ling, Liu, Xuefeng, Liu, Chaojie, Lo, Chun-Han, Lopes, Graciliana, Lorkowski, Stefan, Lozano, Rafael, Lucchetti, Giancarlo, Maghazachi, Azzam A, Mahasha, Phetole Walter, Mahjoub, Soleiman, Mahmoud, Mansour Adam, Mahmoudi, Razzagh, Mahmoudimanesh, Marzieh, Mai, Anh Tuan, Majeed, Azeem, Majma Sanaye, Pantea, Makris, Konstantinos Christos, Malhotra, Kashish, Malik, Ahmad Azam, Malik, Iram, Mallhi, Tauqeer Hussain, Malta, Deborah Carvalho, Mamun, Abdullah A, Mansouri, Borhan, Marateb, Hamid Reza, Mardi, Parham, Martini, Santi, Martorell, Miquel, Marzo, Roy Rillera, Masoudi, Reza, Masoudi, Sahar, Mathews, Elezebeth, Maugeri, Andrea, Mazzaglia, Giampiero, Mekonnen, Teferi, Meshkat, Mahboobeh, Mestrovic, Tomislav, Miao Jonasson, Junmei, Miazgowski, Tomasz, Michalek, Irmina Maria, Minh, Le Huu Nhat, Mini, GK, Miranda, J Jaime, Mirfakhraie, Reza, Mirrakhimov, Erkin M, Mirza-Aghazadeh-Attari, Mohammad, Misganaw, Awoke, Misgina, Kebede Haile, Mishra, Manish, Moazen, Babak, Mohamed, Nouh Saad, Mohammadi, Esmaeil, Mohammadi, Mohsen, Mohammadian-Hafshejani, Abdollah, Mohammadshahi, Marita, Mohseni, Alireza, Mojiri-forushani, Hoda, Mokdad, Ali H, Momtazmanesh, Sara, Monasta, Lorenzo, Moniruzzaman, Md, Mons, Ute, Montazeri, Fateme, Moodi Ghalibaf, AmirAli, Moradi, Yousef, Moradi, Maryam, Moradi Sarabi, Mostafa, Morovatdar, Negar, Morrison, Shane Douglas, Morze, Jakub, Mossialos, Elias, Mostafavi, Ebrahim, Mueller, Ulrich Otto, Mulita, Francesk, Mulita, Admir, Murillo-Zamora, Efrén, Musa, Kamarul Imran, Mwita, Julius C, Nagaraju, Shankar Prasad, Naghavi, Mohsen, Nainu, Firzan, Nair, Tapas Sadasivan, Najmuldeen, Hastyar Hama Rashid, Nangia, Vinay, Nargus, Shumaila, Naser, Abdallah Y, Nassereldine, Hasan, Natto, Zuhair S, Nauman, Javaid, Nayak, Biswa Prakash, Ndejjo, Rawlance, Negash, Hadush, Negoi, Ruxandra Irina, Nguyen, Hau Thi Hien, Nguyen, Dang H, Nguyen, Phat Tuan, Nguyen, Van Thanh, Nguyen, Hien Quang, Niazi, Robina Khan, Nigatu, Yeshambel T, Ningrum, Dina Nur Anggraini, Nizam, Muhammad A, Nnyanzi, Lawrence Achilles, Noreen, Mamoona, Noubiap, Jean Jacques, Nzoputam, Ogochukwu Janet, Nzoputam, Chimezie Igwegbe, Oancea, Bogdan, Odogwu, Nkechi Martina, Odukoya, Oluwakemi Ololade, Ojha, Vivek Anand, Okati-Aliabad, Hassan, Okekunle, Akinkunmi Paul, Okonji, Osaretin Christabel, Okwute, Patrick Godwin, Olufadewa, Isaac Iyinoluwa, Onwujekwe, Obinna E, Ordak, Michal, Ortiz, Alberto, Osuagwu, Uchechukwu Levi, Oulhaj, Abderrahim, Owolabi, Mayowa O, Padron-Monedero, Alicia, Padubidri, Jagadish Rao, Palladino, Raffaele, Panagiotakos, Demosthenes, Panda-Jonas, Songhomitra, Pandey, Ashok, Pandey, Anamika, Pandi-Perumal, Seithikurippu R, Pantea Stoian, Anca Mihaela, Pardhan, Shahina, Parekh, Tarang, Parekh, Utsav, Pasovic, Maja, Patel, Jay, Patel, Jenil R, Paudel, Uttam, Pepito, Veincent Christian Filipino, Pereira, Marcos, Perico, Norberto, Perna, Simone, Petcu, Ionela-Roxana, Petermann-Rocha, Fanny Emily, Podder, Vivek, Postma, Maarten J, Pourali, Ghazaleh, Pourtaheri, Naeimeh, Prates, Elton Junio Sady, Qadir, Mirza Muhammad Fahd, Qattea, Ibrahim, Raee, Pourya, Rafique, Ibrar, Rahimi, Mehran, Rahimifard, Mahban, Rahimi-Movaghar, Vafa, Rahman, Md Obaidur, Rahman, Muhammad Aziz, Rahman, Mohammad Hifz Ur, Rahman, Mosiur, Rahman, Md Mosfequr, Rahmani, Mohamed, Rahmani, Shayan, Rahmanian, Vahid, Rahmawaty, Setyaningrum, Rahnavard, Niloufar, Rajbhandari, Bibek, Ram, Pradhum, Ramazanu, Sheena, Rana, Juwel, Rancic, Nemanja, Ranjha, Muhammad Modassar Ali Nawaz, Rao, Chythra R, Rapaka, Deepthi, Rasali, Drona Prakash, Rashedi, Sina, Rashedi, Vahid, Rashid, Ahmed Mustafa, Rashidi, Mohammad-Mahdi, Ratan, Zubair Ahmed, Rawaf, Salman, Rawal, Lal, Redwan, Elrashdy Moustafa Mohamed, Remuzzi, Giuseppe, Rengasamy, Kannan RR, Renzaho, Andre M N, Reyes, Luis Felipe, Rezaei, Nima, Rezaei, Nazila, Rezaeian, Mohsen, Rezazadeh, Hossein, Riahi, Seyed Mohammad, Rias, Yohanes Andy, Riaz, Muhammad, Ribeiro, Daniela, Rodrigues, Mónica, Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Rohloff, Peter, Roshandel, Gholamreza, Roustazadeh, Abazar, Rwegerera, Godfrey M, Saad, Aly M A, Saber-Ayad, Maha Mohamed, Sabour, Siamak, Sabzmakan, Leila, Saddik, Basema, Sadeghi, Erfan, Saeed, Umar, Saeedi Moghaddam, Sahar, Safi, Sare, Safi, Sher Zaman, Saghazadeh, Amene, Saheb Sharif-Askari, Narjes, Saheb Sharif-Askari, Fatemeh, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahoo, Harihar, Saif-Ur-Rahman, KM, Sajid, Mirza Rizwan, Salahi, Sarvenaz, Salahi, Saina, Saleh, Mohamed A, Salehi, Mohammad Amin, Salomon, Joshua A, Sanabria, Juan, Sanjeev, Rama Krishna, Sanmarchi, Francesco, Santric-Milicevic, Milena M, Sarasmita, Made Ary, Sargazi, Saman, Sathian, Brijesh, Sathish, Thirunavukkarasu, Sawhney, Monika, Schlaich, Markus P, Schmidt, Maria Inês, Schuermans, Art, Seidu, Abdul-Aziz, Senthil Kumar, Nachimuthu, Sepanlou, Sadaf G, Sethi, Yashendra, Seylani, Allen, Shabany, Maryam, Shafaghat, Tahereh, Shafeghat, Melika, Shafie, Mahan, Shah, Nilay S, Shahid, Samiah, Shaikh, Masood Ali, Shanawaz, Mohd, Shannawaz, Mohammed, Sharfaei, Sadaf, Shashamo, Bereket Beyene, Shiri, Rahman, Shittu, Aminu, Shivakumar, K M, Shivalli, Siddharudha, Shobeiri, Parnian, Shokri, Fereshteh, Shuval, Kerem, Sibhat, Migbar Mekonnen, Silva, Luís Manuel Lopes Rodrigues, Simpson, Colin R, Singh, Jasvinder A, Singh, Paramdeep, Singh, Surjit, Siraj, Md Shahjahan, Skryabina, Anna Aleksandrovna, Sohag, Abdullah Al Mamun, Soleimani, Hamidreza, Solikhah, Solikhah, Soltani-Zangbar, Mohammad Sadegh, Somayaji, Ranjani, Sorensen, Reed J D, Starodubova, Antonina V, Sujata, Sujata, Suleman, Muhammad, Sun, Jing, Sundström, Johan, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabatabaeizadeh, Seyed-Amir, Tabish, Mohammad, Taheri, Majid, Taheri, Ensiyeh, Taki, Elahe, Tamuzi, Jacques JL Lukenze, Tan, Ker-Kan, Tat, Nathan Y, Taye, Birhan Tsegaw, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Tesler, Riki, Thangaraju, Pugazhenthan, Thankappan, Kavumpurathu Raman, Thapa, Rajshree, Tharwat, Samar, Thomas, Nihal, Ticoalu, Jansje Henny Vera, Tiyuri, Amir, Tonelli, Marcello, Tovani-Palone, Marcos Roberto, Trico, Domenico, Trihandini, Indang, Tripathy, Jaya Prasad, Tromans, Samuel Joseph, Tsegay, Guesh Mebrahtom, Tualeka, Abdul Rohim, Tufa, Derara Girma, Tyrovolas, Stefanos, Ullah, Sana, Upadhyay, Era, Vahabi, Seyed Mohammad, Vaithinathan, Asokan Govindaraj, Valizadeh, Rohollah, van Daalen, Kim Robin, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vaziri, Siavash, Verma, Madhur verma, Verras, Georgios-Ioannis, Vo, Danh Cao, Wagaye, Birhanu, Waheed, Yasir, Wang, Ziyue, Wang, Yanqing, Wang, Cong, Wang, Fang, Wassie, Gizachew Tadesse, Wei, Melissa Y Wei, Weldemariam, Abrha Hailay, Westerman, Ronny, Wickramasinghe, Nuwan Darshana, Wu, YiFan, Wulandari, Ratna DWI, Xia, Juan, Xiao, Hong, Xu, Suowen, Xu, Xiaoyue, Yada, Dereje Y, Yang, Lin, Yatsuya, Hiroshi, Yesiltepe, Metin, Yi, Siyan, Yohannis, Hunachew Kibret, Yonemoto, Naohiro, You, Yuyi, Zaman, Sojib Bin, Zamora, Nelson, Zare, Iman, Zarea, Kourosh, Zarrintan, Armin, Zastrozhin, Mikhail Sergeevich, Zeru, Naod Gebrekrstos, Zhang, Zhi-Jiang, Zhong, Chenwen, Zhou, Jingjing, Zielińska, Magdalena, Zikarg, Yossef Teshome, Zodpey, Sanjay, Zoladl, Mohammad, Zou, Zhiyong, Zumla, Alimuddin, Zuniga, Yves Miel H, Magliano, Dianna J, Murray, Christopher J L, Hay, Simon I, and Vos, Theo
- Abstract
Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050.
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- 2023
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31. Spin–Phonon and Electron–Phonon Coupling in Pyrochlore Iridates (Y1–xPrx)2Ir2O7: An Investigation with Raman Spectroscopy
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Kumar, Harish, Sathe, V G, and Pramanik, A K
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The complex interplay between the lattice geometry and spin–orbit coupling in pyrochlore iridates is shown to give rise to many intriguing phenomena. Here, we report a temperature-dependent Raman scattering study in a series of pyrochlore iridate materials (Y1–xPrx)2Ir2O7which shows magnetic and electronic transition with variation of both temperature as well as composition. Our Raman studies reveal an anomalous change in frequency and line width of F2gand A1gmodes across its transition temperatures while the data in high temperatures mostly follow the anharmonic model. The variation of A1gmode associated with
bending vibrations indicates prominent spin-phonon coupling which is mostly induced by a Dzyaloshinskii-Moriya interaction rather than exchange interaction. On the other hand, the signature of electron–phonon interaction is also found to be prominent from stretching F2gmode and opposite line width variation for sample with metallic transition. Thus, our study establishes prominent spin–phonon and electron–phonon coupling and its connection with A-site atoms in pyrochlore iridates. - Published
- 2023
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32. Quality Enhancement of Recommendation using Improved Triangle Ratings.
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Gautam, Devendra, Dixit, Anurag, Banda, Latha, Kumar, Harish, Sharma, Purushottam, and Verma, Chaman
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RECOMMENDER systems ,ONLINE social networks ,TRIANGLES ,TAGS (Metadata) - Abstract
Recommender Systems are a potent technology used in many social networking sites. Personalized recommender systems are an added method for improving the quality of recommendation and customer’s requirements. There are many kinds of techniques available to get personalised recommendations such as Content based, Collaborative filtering and Hybrid filtering. In these mentioned techniques, the most popular CF technique is used to enhance the accuracy of RS with some shortcomings such as sparsity, scalability and cold start user problems. To enhance the quality of collaborative filtering using tagging, the proposed approach IUGT-Jaccard-ITR used may target the issue of cold start user or item problems in recommendation. [ABSTRACT FROM AUTHOR]
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- 2023
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33. A parametric analysis of AVA to optimise Netflix performance
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Rastogi, Divya, Parihar, Tasha Singh, and Kumar, Harish
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In this research study, researcher tries to understand how Over-the-top platforms like Netflix categorically utilize aesthetic visual analysis (AVA); an image selection tool to reduce time and increase efficacy, through a parametric analysis of AVA to optimise Netflix performance. This research paper tries to answer all the questions related to the how the database of aesthetic visual analysis (AVA), an image selection tool works better or more like humans. To further substantiate the popularity of Netflix, a real time data of 307 respondents who use OTT platforms in Delhi was collected to determine whether Netflix in fact is or not the market leader. 63.8% of them selected Netflix as their top option.
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- 2023
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34. Development of adaptive headlight system for automobile
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Gowri Shankar, M., Bharathiraja, M., Kumar, Harish, Yokeshwaran, R. K., Pradeep Kumar, T., Chethan, R., and Satyanarayana Gupta, M.
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- 2023
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35. Synthesis of biodegradable carboxymethyl cellulose film-loaded magnesium nanoparticles
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Kumar, Harish, Gaur, Ankur, and Karuna, M. S.
- Abstract
Graphical abstract:
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- 2023
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36. Tribological behaviour of stir casted hybrid-Al metal matrix composites using Taguchi technique
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Ranjan, Alok, Nagdeve, Leeladhar, Kumar, Harish, Mishra, Abhishek, and Katiyar, Jitendra Kumar
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A hybrid Al6061 composite material was fabricated with various weight percentage of different reinforcing material such as SiC, Al2O3, RHA and ZrSiO4by liquid metallurgy route via. Stir casting method. The tribological properties were tested and carried out on pin-on-disc tribometers by considering various parameters like, mixture weight percentage of reinforcing materials, sliding distance, speed and applied load to study the tribological characteristics. Taguchi technique was used to analyse the wear rate of hybrid composites. Different experiments were conducted using Taguchi technique and the regression equations were developed through Analysis of Variance (ANOVA) to investigate the influence of various test parameters such as sliding distance, materials parameters (such as weight percentage of reinforcement), sliding distance and applied load. Finally, Taguchi results were used to train the Artificial Neural Network (ANN) model. The input parameters assigned to develop an ANN model are mixture weight percent of reinforcement, sliding distance, sliding speed and applied load. Finally confirmation test was done to verify the predictive model with the experimental results of the wear pin sample. The weight percentage of reinforcement had the greatest influence on statistical and physical properties of hybrid composites while the sliding speed exercised its impact on the Coefficient of Frication (COF) of hybrid composites on dry sliding wear and also on the optimal parameters for less wear rate and low COF. The results indicated that combination of 4.5 wt.% of reinforcement, 30 N load, 0.9 m/s sliding velocity and 3600 m sliding distance was the optimum blend for minimum wear rate and 4.5 wt.% of reinforcement, 3.4 m/s sliding velocity, 3600 m sliding distance and 40 N load was identified as the optimum blend for minimum COF using the main effect plot.
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- 2023
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37. Development of a Systematic Strategy toward Promotion of α‑Synuclein Aggregation Using 2‑Hydroxyisophthalamide-Based Systems.
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Uddin, Aslam, Malla, Javid Ahmad, Kumar, Harish, Kumari, Manisha, Sinha, Suman, Sharma, Virender Kumar, Kumar, Yashwant, Talukdar, Pinaki, Lahiri, Mayurika, Maiti, Tushar Kanti, and Hazra, Partha
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- 2022
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38. Microenvironmental CXCL12 deletion enhances Flt3-ITD acute myeloid leukemia stem cell response to therapy by reducing p38 MAPK signaling
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Anderson, Nicholas R., Sheth, Vipul, Li, Hui, Harris, Mason W., Qiu, Shaowei, Crossman, David K., Kumar, Harish, Agarwal, Puneet, Nagasawa, Takashi, Paterson, Andrew J., Welner, Robert S., and Bhatia, Ravi
- Abstract
Fms-like tyrosine kinase 3 (Flt3) tyrosine kinase inhibitors (Flt3-TKI) have improved outcomes for patients with Flt3-mutated acute myeloid leukemia (AML) but are limited by resistance and relapse, indicating persistence of leukemia stem cells (LSC). Here utilizing a Flt3-internal tandem duplication (Flt3-ITD) and Tet2-deleted AML genetic mouse model we determined that FLT3-ITD AML LSC were enriched within the primitive ST-HSC population. FLT3-ITD LSC showed increased expression of the CXCL12 receptor CXCR4. CXCL12-abundant reticular (CAR) cells were increased in Flt3-ITD AML marrow. CXCL12 deletion from the microenvironment enhanced targeting of AML cells by Flt3-TKI plus chemotherapy treatment, including enhanced LSC targeting. Both treatment and CXCL12 deletion partially reduced p38 mitogen-activated protein kinase (p38) signaling in AML cells and further reduction was seen after treatment in CXCL12 deleted mice. p38 inhibition reduced CXCL12-dependent and -independent maintenance of both murine and human Flt3-ITD AML LSC by MSC and enhanced their sensitivity to treatment. p38 inhibition in combination with chemotherapy plus TKI treatment leads to greater depletion of Flt3-ITD AML LSC compared with CXCL12 deletion. Our studies support roles for CXCL12 and p38 signaling in microenvironmental protection of AML LSC and provide a rationale for inhibiting p38 signaling to enhance Flt3-ITD AML targeting.
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- 2023
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39. Technological Solutions for Digital Identity: A Computer Vision-Based Approach to Mitigate Imaging Errors
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Kumar, Harish, Ture, Rameshwar, Gupta, M., and Sharma, R.
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Digital transformation of enterprises is driving the need for a digital identity to recognize people for delivering services. The implementation of digital identity is complex, requiring several technological solutions and much coordination. Capturing and processing data is challenging because biometric issues may arise due to imaging errors. This article addresses this issue and proposes a computer vision-based framework for contactless recognition process using a focus group discussion approach for inputs from experts. The proposed framework enhances image capturing process, extraction of high-quality features from captured images, image processing, contactless face detection, and authentication. The study also derives lessons for other biometric-based identity projects based on image analysis. The proposed framework can be used as a reference for understanding multidimensional perspectives, scalability, and adoption of technological solutions in other similar projects in developing countries in future.
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- 2023
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40. AFP-SPTS: An Accurate Prediction of Antifreeze Proteins Using Sequential and Pseudo-Tri-Slicing Evolutionary Features with an Extremely Randomized Tree
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Khan, Adnan, Uddin, Jamal, Ali, Farman, Kumar, Harish, Alghamdi, Wajdi, and Ahmad, Aftab
- Abstract
The development of intracellular ice in the bodies of cold-blooded living organisms may cause them to die. These species yield antifreeze proteins (AFPs) to live in subzero temperature environments. Additionally, AFPs are implemented in biotechnological, industrial, agricultural, and medical fields. Machine learning-based predictors were presented for AFP identification. However, more accurate predictors are still highly desirable for boosting the AFP prediction. This work presents a novel approach, named AFP-SPTS, for the correct prediction of AFPs. We explored the discriminative features with four schemes, namely, dipeptide deviation from the expected mean (DDE), reduced amino acid alphabet (RAAA), grouped dipeptide composition (GDPC), and a novel representative method, called pseudo-position-specific scoring matrix tri-slicing (PseTS-PSSM). Considering the advantages of ensemble learning strategy, we fused each feature vector into different combinations and trained the models with five machine learning algorithms, i.e., multilayer perceptron (MLP), extremely randomized tree (ERT), decision tree (DT), random forest (RF), and AdaBoost. Among all models, PseTS-PSSM + RAAA with an extremely randomized tree attained the best outcomes. The proposed predictor (AFP-SPTS) boosted the accuracies of AFPs in the literature by 1.82 and 4.1%.
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- 2023
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41. Advancements in welding of austenitic stainless steel
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Kumar, Harish and Singh, Harmeet
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- 2023
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42. Optimization of surface finishing and material removal of boron based HMMCs applying magnetic abrasive flow machining process
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Singh, Vijay and Kumar, Harish
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- 2023
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43. Development of Highly Efficient Dual-Purpose Gas Hydrate and Corrosion Inhibitors for Flow Assurance Application: An Experimental and Computational Study.
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Omidvar, Maryam, Cheng, Liwei, Farhadian, Abdolreza, Berisha, Avni, Rahimi, Alireza, Ning, Fulong, Kumar, Harish, Peyvandi, Kiana, and Nabid, Mohammad Reza
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- 2023
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44. Enablers to intensify OTT streaming services among consumers: a study using TISM-MICMAC approach
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Sharma, Vijay Kumar, Kumar, Harish, and Mahobia, Himanshu
- Abstract
Over-the-top (OTT) is an application, content and services created for consumers which are accessible through internet. There are many challenges for OTT entertainment industry like understanding the audience choices, irrelevant or inappropriate contents, poor service experience, cost of services, etc. The growth and development of an OTT platform depends on multiple factors. Therefore, the study focuses on identifying various factors from literature which influence consumers' desire to subscribe an OTT service platform. The study deployed multi-criteria decision-making (MCDM) techniques, namely 'total interpretive structural modelling' (TISM) and 'cross-impact matrix multiplication applied to classification' (MICMAC) to study cross-inter-relationship among factors. The study proposes a unique model that recommends developing strategies along two pathways as 'service quality' and 'consumers' affordability'. This study will help the OTT service providers to execute their services offerings to target new consumers as well as retaining their existing consumers.
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- 2023
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45. Performance-based natural rubber composites reinforced with jute fibers and nano-silica: thermal, morphological, and mechanical studies with statistical optimization
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Kumar, Sumit, Lal, Sohan, Jagdeva, Geetanjali, Arora, Sanjiv, Kumar, Parvin, Soni, R. K., Kumar, Harish, Kumar, Sunil, and Panchal, Suresh
- Abstract
Graphical abstract:
- Published
- 2023
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46. Techniques, Tricks, and Algorithms for Efficient GPU-Based Processing of Higher Order Hyperbolic PDEs
- Author
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Subramanian, Sethupathy, Balsara, Dinshaw S., Bhoriya, Deepak, and Kumar, Harish
- Abstract
GPU computing is expected to play an integral part in all modern Exascale supercomputers. It is also expected that higher order Godunov schemes will make up about a significant fraction of the application mix on such supercomputers. It is, therefore, very important to prepare the community of users of higher order schemes for hyperbolic PDEs for this emerging opportunity.
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- 2023
- Full Text
- View/download PDF
47. Utilization of Maltodextrin and Whey Protein Concentrate for Microencapsulation of Kinnow Peel Extract in Breadsticks
- Author
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Rafiq, Shafiya, Ahmad Nayik, Gulzar, Kaul, Rajkumari, Kumar, Harish, and Ruiz Rodríguez, Alfonso
- Abstract
Aims: This work aimed to develop a functional powder from kinnow peel extract, which could be proposed as a novel ingredient in the formulation of functional foods. Methods: The extract was spray-dried using different proportions (0, 15, 30 and 45 %) of encapsulating agents (maltodextrin and whey protein concentrate (WPC) at two different inlet air temperatures of 145 and 155 °C). The developed powder was examined for process yield, microencapsulation efficiency, colour, moisture content, water activity, hygroscopicity, solubility and antioxidant properties. Results: The study showed the excellent potential of WPC as a drying aid in the production of quality powder terms of better yield (77.76-82.87%), higher microencapsulation efficiency (69.07-80.36 %), better phenolic content (18.04-13.37 mg/g GAE) and higher antioxidant activity (63.80-74.20 %), as compared to maltodextein. Polyphenol retention was also investigated under controlled conditions, and results demonstrated an excellent stability of polyphenols at higher concentrations of encapsulating agent. Microencapsulated powder in breadsticks significantly affected the proximate composition and viscoelastic properties. Conclusion: This study can be recommended for the conversion of plant extracts into encapsulated powders with reduced volume and better physical and rehydration properties to fortify different cereal products, thus producing new and functional foods.
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- 2023
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48. Research on computer 3D image encryption processing based on the nonlinear algorithm
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Bian, Longlong, Chen, Jianwei, Soni, Mukesh, Bhola, Jyoti, Kumar, Harish, and Jawarneh, Malik
- Abstract
This article uses the nonlinear digital chaos theory algorithm to generate the corresponding encryption system initial parameters, by analysing the correlation degree of image elements from the angles of horizontal, vertical, and diagonal direction, in order to study computer three-dimensional (3D) image encryption processing. The correlation degree of the cypher text obtained by the nonlinear algorithm is weak in the image's adjacent pixels, and the adjacent pixels are not related at all, horizontal angle: 0.915989, vertical angle: 0.968184, diagonal angle: 0.913533. The nonlinear algorithm distributes the image's statistical features into the random cypher text. By applying permutations and replacements in 3D space, the proposed approach improves performance parameters and widens key space in comparison to previous image cryptography investigations. The important qualities of such a secure system are its simplicity and efficacy. Simulations and analysis show that the proposed method can produce a large key space while also surviving standard cipher attacks. Because of its powerful cryptographic properties, it is suited for image applications. The nonlinear algorithm has very high sensitivity to the secret key and plaintext, as well as better statistical performance, higher security, and higher efficiency in the operation of the algorithm.
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- 2022
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49. Proficient exclusion of pesticide using humic acid-modified magnetite nanoparticles from aqueous solution
- Author
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Jangra, Arti, Kumar, Jai, Singh, Devender, Kumar, Harish, Kumar, Parvin, Kumar, Suresh, and Kumar, Ramesh
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- 2022
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50. Development of a Systematic Strategy toward Promotion of α-Synuclein Aggregation Using 2-Hydroxyisophthalamide-Based Systems
- Author
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Uddin, Aslam, Malla, Javid Ahmad, Kumar, Harish, Kumari, Manisha, Sinha, Suman, Sharma, Virender Kumar, Kumar, Yashwant, Talukdar, Pinaki, Lahiri, Mayurika, Maiti, Tushar Kanti, and Hazra, Partha
- Abstract
Establishing a potent scheme against α-synuclein aggregation involved in Parkinson’s disease has been evaluated as a promising route to identify compounds that either inhibit or promote the aggregation process of α-synuclein. In the last two decades, this perspective has guided a dramatic increase in the efforts, focused on developing potent drugs either for retardation or promotion of the self-assembly process of α-synuclein. To address this issue, using a chemical kinetics platform, we developed a strategy that enabled a progressively detailed analysis of the molecular events leading to protein aggregation at the microscopic level in the presence of a recently synthesized 2-hydroxyisophthalamide class of small organic molecules based on their binding affinity. Furthermore, qualitatively, we have developed a strategy of disintegration of α-synuclein fibrils in the presence of these organic molecules. Finally, we have shown that these organic molecules effectively suppress the toxicity of α-synuclein oligomers in neuron cells.
- Published
- 2022
- Full Text
- View/download PDF
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