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35. Deep Learning Techniques for Future Intelligent Cross-Media Retrieval

Author

Rehman, Sadaqat ur, Waqas, Muhammad, Tu, Shanshan, Koubaa, Anis, Rehman, Obaid ur, Ahmad, Jawad, Hanif, Muhammad, and Han, Zhu

Subjects
Computer Science - Information Retrieval, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

With the advancement in technology and the expansion of broadcasting, cross-media retrieval has gained much attention. It plays a significant role in big data applications and consists in searching and finding data from different types of media. In this paper, we provide a novel taxonomy according to the challenges faced by multi-modal deep learning approaches in solving cross-media retrieval, namely: representation, alignment, and translation. These challenges are evaluated on deep learning (DL) based methods, which are categorized into four main groups: 1) unsupervised methods, 2) supervised methods, 3) pairwise based methods, and 4) rank based methods. Then, we present some well-known cross-media datasets used for retrieval, considering the importance of these datasets in the context in of deep learning based cross-media retrieval approaches. Moreover, we also present an extensive review of the state-of-the-art problems and its corresponding solutions for encouraging deep learning in cross-media retrieval. The fundamental objective of this work is to exploit Deep Neural Networks (DNNs) for bridging the "media gap", and provide researchers and developers with a better understanding of the underlying problems and the potential solutions of deep learning assisted cross-media retrieval. To the best of our knowledge, this is the first comprehensive survey to address cross-media retrieval under deep learning methods., Comment: arXiv admin note: text overlap with arXiv:1804.09539 by other authors

Published
2020

40. Water Preservation in Soan River Basin using Deep Learning Techniques

Author

Rehman, Sadaqat ur, Yang, Zhongliang, Shahid, Muhammad, Wei, Nan, Huang, Yongfeng, Waqas, Muhammad, Tu, Shanshan, and Rehman, Obaid ur

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

Water supplies are crucial for the development of living beings. However, change in the hydrological process i.e. climate and land usage are the key issues. Sustaining water level and accurate estimating for dynamic conditions is a critical job for hydrologists, but predicting hydrological extremes is an open issue. In this paper, we proposed two deep learning techniques and three machine learning algorithms to predict stream flow, given the present climate conditions. The results showed that the Recurrent Neural Network (RNN) or Long Short-term Memory (LSTM), an artificial neural network based method, outperform other conventional and machine-learning algorithms for predicting stream flow. Furthermore, we analyzed that stream flow is directly affected by precipitation, land usage, and temperature. These indexes are critical, which can be used by hydrologists to identify the potential for stream flow. We make the dataset publicly available (https://github.com/sadaqat007/Dataset) so that others should be able to replicate and build upon the results published., Comment: 14 pages

Published
2019

45. Casemix, management, and mortality of patients receiving emergency neurosurgery for traumatic brain injury in the Global Neurotrauma Outcomes Study: a prospective observational cohort study

Author

Abbas, Ghayur, Abdallah, Omar Ibrahim, Abdel-Lateef, Ahmed, Abdifatah, Khalif, Abdullateef, Awfa, Abeygunaratne, Ruvini, Aboellil, Mostafa, Adam, Abass, Adams, Robert, Adeleye, Amos, Adeolu, Augustine, Adji, Novan Krisno, Afianti, Nur, Agarwal, Sudarsan, Aghadi, Ifeanyi Kene, Aguilar, Paúl Martín Méndez, Ahmad, Syeda Rida, Ahmed, Daniyal, Ahmed, Nafees, Aizaz, Haider, Aji, Yunus Kuntawi, Alamri, Alex, Alberto, Augusto Jacinto Mussindo, Alcocer, Luis Alcocer, Alfaro, Lesly Gonzales, Al-Habib, Amro, Alhourani, Ahmad, Ali, Syed Muhammad Rafay, Alkherayf, Fahad, AlMenabbawy, Ahmed, Alshareef, Aliyah, Aminullah, Muhammad Adil s/o, Amjad, Madeha, Amorim, Robson Luis Oliveira de, Anbazhagan, Sathiaprabhu, Andrade, Almir, Antar, Waleed, Anyomih, Theophilus T.K., Aoun, Salah, Apriawan, Tedy, Armocida, Daniele, Arnold, Paul, Arraez, Miguel, Assefa, Temesgen, Asser, Andres, Athiththan, S.P., Attanayake, Deepal, Aung, Maung Maung, Avi, Allan, Ayala, Victor Enrique Antolinez, Azab, Mohammed, Azam, Gaousul, Azharuddin, Mohd, Badejo, Olukemi, Badran, Mohamed, Baig, Azam Ali, Baig, Rehman Ali, Bajaj, Ankur, Baker, Paul, Bala, Renu, Balasa, Artur, Balchin, Ross, Balogun, James, Ban, Vin Shen, Bandi, Bharath Kumar Reddy, Bandyopadhyay, Soham, Bank, Matthew, Barthelemy, Ernest, Bashir, Mohammed Talha, Basso, Luciano Silveira, Basu, Surajit, Batista, Auricelio, Bauer, Marlies, Bavishi, Devi, Beane, Abi, Bejell, Shmuel, Belachew, Anteneh, Belli, Antonio, Belouaer, Amani, Bendahane, Najia El Abbadi, Benjamin, Okanga, Benslimane, Youssef, Benyaiche, Chaymae, Bernucci, Claudio, Berra, Luigi Valentino, Bhebe, Arnold, Bimpis, Alexios, Blanaru, Diana, Bonfim, Jean Claude, Borba, Luis A B, Borcek, Alp Ozgun, Borotto, Erika, Bouhuwaish, Ahmad Elmabri Mohammad, Bourilhon, Facundo, Brachini, Gioia, Breedon, Joshua, Broger, Maximilian, Brunetto, Giacoma Maria Floriana, Bruzzaniti, Placido, Budohoska, Natalia, Burhan, Hira, Calatroni, Maximiliano Luis, Camargo, Catherine, Cappai, Pier Francesco, Cardali, Salvatore Massimiliano, Castaño-Leon, Ana M, Cederberg, David, Celaya, Mikel, Cenzato, Marco, Challa, Lakshmi Madhavi, Charest, Dhanny, Chaurasia, Bipin, Chenna, Rabah, Cherian, Iype, Ching'o, Juliana Henry, Chotai, Tejas, Choudhary, Ajay, Choudhary, Nabeel, Choumin, Florence, Cigic, Tomislav, Ciro, Juan, Conti, Carlo, Corrêa, Antônio Carlos de Souza, Cossu, Giulia, Couto, Maíra Piani, Cruz, Aurora, D'Silva, Divya, D'Aliberti, Giuseppe Antonio, Dampha, Lamin, Daniel, Roy Thomas, Dapaah, Andrew, Darbar, Aneela, Dascalu, Gabriel, Dauda, Happy Amos, Davies, Owain, Delgado-Babiano, Andrea, Dengl, Markus, Despotovic, Marko, Devi, Indira, Dias, Celeste, Dirar, Mohamed, Dissanayake, Melina, Djimbaye, Hananiah, Dockrell, Simon, Dolachee, Ali, Dolgopolova, Julija, Dolgun, Muge, Dow, Abdalrouf, Drusiani, Davide, Dugan, Artjom, Duong, Dinh Tuan, Duong, Trung Kien, Dziedzic, Tomasz, Ebrahim, Ali, El Fatemi, Nizar, El Helou, Antonios El, El Maaqili, Rachid El, El Mostarchid, Brahim El, El Ouahabi, Abdessamad El, Elbaroody, Mohammad, El-Fiki, Ahmed, El-Garci, Ahmed, El-Ghandour, Nasser M.F., Elhadi, Muhammed, Elleder, Vanessa, Elrais, Safa, El-shazly, Mohamed, Elshenawy, Mohamed, Elshitany, Hesham, El-Sobky, Omar, Emhamed, Marwa, Enicker, Basil, Erdogan, Onur, Ertl, Sebastian, Esene, Ignatius, Espinosa, Omar Ocampo, Fadalla, Tarig, Fadelalla, Mohammed, Faleiro, Rodrigo Moreira, Fatima, Nida, Fawaz, Charbel, Fentaw, Assefa, Fernandez, Carla Eiriz, Ferreira, Ana, Ferri, Francesco, Figaji, Tony, Filho, Emerson L B, Fin, Loic, Fisher, Benjamin, Fitra, Fitra, Flores, Alexis Palpan, Florian, Ioan Stefan, Fontana, Vincenzo, Ford, Lauren, Fountain, Daniel, Frade, Jose Maria Roda, Fratto, Antonio, Freyschlag, Christian, Gabin, Aranzazu Sánchez, Gallagher, Clare, Ganau, Mario, Gandia-Gonzalez, Maria Luisa, Garcia, Andoni, Garcia, Borja Hernandez, Garusinghe, Sanjeewa, Gebreegziabher, Biniam, Gelb, Adrian, George, Jerome St, Germanò, Antonino Francesco, Ghetti, Ilaria, Ghimire, Prajwal, Giammarusti, Alessandro, Gil, Jose Luis, Gkolia, Panagiota, Godebo, Yoseph, Gollapudi, Prakash Rao, Golubovic, Jagos, Gomes, Jeremias Fernando, Gonzales, Javier, Gormley, William, Gots, Alexander, Gribaudi, Giulia Letizia, Griswold, Dylan, Gritti, Paolo, Grobler, Ruan, Gunawan, Rudy, Hailemichael, Birhanu, Hakkou, Elmehdi, Haley, Mark, Hamdan, Alhafidz, Hammed, Ali, Hamouda, Waeel, Hamzah, Nurul Ashikin, Han, Nyein Latt, Hanalioglu, Sahin, Haniffa, Rashan, Hanko, Martin, Hanrahan, John, Hardcastle, Timothy, Hassani, Fahd Derkaoui, Heidecke, Volkmar, Helseth, Eirik, Hernández-Hernández, Miguel Ángel, Hickman, Zachary, Hoang, Le Minh Chau, Hollinger, Alexa, Horakova, Lenka, Hossain-Ibrahim, Kismet, Hou, Boru, Hoz, Samer, Hsu, Janine, Hunn, Martin, Hussain, Madiha, Iacopino, Giorgia, Ideta, Mylena Miki Lopes, Iglesias, Irene, Ilunga, Ali, Imtiaz, Nafiz, Islam, Rafiza, Ivashchenko, Serge, Izirouel, Karim, Jabal, Mohamed Sobhi, Jabal, Soubhi, Jabang, John Nute, Jamjoom, Aimun, Jan, Irfan, Jarju, Landing BM, Javed, Saad, Jelaca, Bojan, Jhawar, Sukhdeep Singh, Jiang, Ting Ting, Jimenez, Fernando, Jiris, Jorge, Jithoo, Ron, Johnson, Walt, Joseph, Mathew, Joshi, Rameshman, Junttila, Eija, Jusabani, Mubashir, Kache, Stephen Akau, Kadali, Satyavara Prasad, Kalkmann, Gabriela F, Kamboh, Usman, Kandel, Hitham, Karakus, Ahmet Kamil, Kassa, Mengistu, Katila, Ari, Kato, Yoko, Keba, Martin, Kehoe, Kristy, Kertmen, Huseyin Hayri, Khafaji, Soha, Khajanchi, Monty, Khan, Mohammed, Khan, Muhammad Mukhtar, Khan, Sohail Daud, Khizar, Ahtesham, Khriesh, Amir, Kierońska, Sara, Kisanga, Paul, Kivevele, Boniface, Koczyk, Kacper, Koerling, Anna-Lucia, Koffenberger, Danielle, Kõiv, Kennet, Kõiv, Leho, Kolarovszki, Branislav, König, Marton, Könü-Leblebicioglu, Dilek, Koppala, Santhoshi Devi, Korhonen, Tommi, Kostkiewicz, Boguslaw, Kostyra, Kacper, Kotakadira, Srinivas, Kotha, Arjun Reddy, Kottakki, Madhu Narayana Rao, Krajcinovic, Nenad, Krakowiak, Michal, Kramer, Andreas, Krishnamoorthy, Selvamuthukumaran, Kumar, Ashok, Kumar, Pankaj, Kumar, Pradhumna, Kumarasinghe, Nilaksha, Kuncha, Gowtham, Kutty, Raja K., Laeke, Tsegazeab, Lafta, Ghazwan, Lammy, Simon, Lapolla, Pierfrancesco, Lardani, Jacopo, Lasica, Nebojsa, Lastrucci, Giancarlo, Launey, Yoann, Lavalle, Laura, Lawrence, Tim, Lazaro, Albert, Lebed, Vitalii, Leinonen, Ville, Lemeri, Lawrence, Levi, Leon, Lim, Jia Yi, Lim, Xiao Yi, Linares-Torres, Jorge, Lippa, Laura, Lisboa, Lurdes, Liu, Jinfang, Liu, Ziyuan, Lo, William B, Lodin, Jan, Loi, Federico, Londono, Daniella, Lopez, Pedro Antonio Gomez, López, Cristina Barceló, Lotbiniere-Bassett, Madeleine De, Lulens, Rihards, Luna, Facundo Hector, Luoto, Teemu, M.V., Vijaya Sekhar, Mabovula, Ndyebo, MacAllister, Matthew, Macie, Alcina Americo, Maduri, Rodolfo, Mahfoud, Moufid, Mahmood, Ashraf, Mahmoud, Fathia, Mahoney, Dominic, Makhlouf, Wissam, Malcolm, George, Malomo, Adefolarin, Malomo, Toluyemi, Mani, Manoranjitha Kumari, Marçal, Tomás Gazzinelli, Marchello, Jacopo, Marchesini, Nicolò, Marhold, Franz, Marklund, Niklas, Martín-Láez, Rubén, Mathaneswaran, Vickneswaran, Mato-Mañas, David José, Maye, Helen, McLean, Aaron Lawson, McMahon, Catherine, Mediratta, Saniya, Mehboob, Mehreen, Meneses, Alisson, Mentri, Nesrine, Mersha, Hagos, Mesa, Ana Milena, Meyer, Cristy, Millward, Christopher, Mimbir, Salomao Amone, Mingoli, Andrea, Mishra, Parashruram, Mishra, Tejesh, Misra, Basant, Mittal, Siddharth, Mohammed, Imran, Moldovan, Ioana, Molefe, Masechaba, Moles, Alexis, Moodley, Preston, Morales, Mario Augusto Narváez, Morgan, Lucy, Morillo, German Del Castillo, Moustafa, Wahab, Moustakis, Nikolaos, Mrichi, Salma, Munjal, Satya Shiva, Muntaka, Abdul-Jalilu Mohammed, Naicker, Denver, Nakashima, Paulo E H, Nandigama, Pratap Kumar, Nash, Samantha, Negoi, Ionut, Negoita, Valetina, Neupane, Samundra, Nguyen, Manh Hung, Niantiarno, Fajar Herbowo, Noble, Abbi, Nor, Mohd Arman Muhamad, Nowak, Blazej, Oancea, Andrei, O'Brien, Frazer, Okere, Oghenekevwe, Olaya, Sandra, Oliveira, Leandro, Oliveira, Louise Makarem, Omar, Fatma, Ononeme, Okezi, Opšenák, René, Orlandini, Simone, Osama, Alrobah, Osei-Poku, Dorcas, Osman, Haytham, Otero, Alvaro, Ottenhausen, Malte, Otzri, Shuli, Outani, Oumaima, Owusu, Emmanuel Abem, Owusu-Agyemang, Kevin, Ozair, Ahmad, Ozoner, Baris, Paal, Elli, Paiva, Mauro Sérgio, Paiva, Wellingson, Pandey, Sharad, Pansini, Gastone, Pansini, Luigi, Pantel, Tobias, Pantelas, Nikolaos, Papadopoulos, Konstantinos, Papic, Vladimir, Park, Kee, Park, Nick, Paschoal, Eric Homero Albuquerque, Paschoalino, Mylla Christie de Oliveira, Pathi, Rajesh, Peethambaran, Anilkumar, Pereira, Thiago Andrade, Perez, Irene Panero, Pérez, Claudio José Piqueras, Periyasamy, Tamilanandh, Peron, Stefano, Phillips, Michael, Picazo, Sofía Sotos, Pinar, Ertugrul, Pinggera, Daniel, Piper, Rory, Pirakash, Pathmanesan, Popadic, Branko, Posti, Jussi P., Prabhakar, Rajmohan Bhanu, Pradeepan, Sivanesalingam, Prasad, Manjunath, Prieto, Paola Calvachi, Prince, Ron, Prontera, Andrea, Provaznikova, Eva, Quadros, Danilo, Quintero, Nezly Jadid Romero, Qureshi, Mahmood, Rabiel, Happiness, Rada, Gabriel, Ragavan, Sivagnanam, Rahman, Jueria, Ramadhan, Omar, Ramaswamy, Padma, Rashid, Sakina, Rathugamage, Jagath, Rätsep, Tõnu, Rauhala, Minna, Raza, Asif, Reddycherla, Naga Raju, Reen, Linus, Refaat, Mohamed, Regli, Luca, Ren, Haijun, Ria, Antonio, Ribeiro, Thales Francisco, Ricci, Alessandro, Richterová, Romana, Ringel, Florian, Robertson, Faith, Rocha, Catarina Mayrink Siqueira Cabral, Rogério, Juvenal de Souza, Romano, Adan Anibal, Rothemeyer, Sally, Rousseau, Gail Rousseau Gail, Roza, Ranette, Rueda, Kevin David Farelo, Ruiz, Raiza, Rundgren, Malin, Rzeplinski, Radoslaw, S.Chandran, Raj, Sadayandi, Ramesh Andi, Sage, William, Sagerer, André Norbert Josef, Sakar, Mustafa, Salami, Mohcine, Sale, Danjuma, Saleh, Youssuf, Sánchez-Viguera, Cristina, Sandila, Saning'o, Sanli, Ahmet Metin, Santi, Laura, Santoro, Antonio, Santos, Aieska Kellen Dantas Dos, Santos, Samir Cezimbra dos, Sanz, Borja, Sapkota, Shabal, Sasidharan, Gopalakrishnan, Sasillo, Ibrahim, Satoskar, Rajeev, Sayar, Ali Caner, Sayee, Vignesh, Scheichel, Florian, Schiavo, Felipe Lourenzon, Schupper, Alexander, Schwarz, Andreas, Scott, Teresa, Seeberger, Esther, Segundo, Claudionor Nogueira Costa, Seidu, Anwar Sadat, Selfa, Antonio, Selmi, Nazan Has, Selvarajah, Claudiya, Şengel, Necmiye, Seule, Martin, Severo, Luiz, Shah, Purva, Shahzad, Muhammad, Shangase, Thobekile, Sharma, Mayur, Shiban, Ehab, Shimber, Emnet, Shokunbi, Temitayo, Siddiqui, Kaynat, Sieg, Emily, Siegemund, Martin, Sikder, Shahidur Rahman, Silva, Ana Cristina Veiga, Silva, Ana, Silva, Pedro Alberto, Singh, Deepinder, Skadden, Carly, Skola, Josef, Skouteli, Eirini, Słoniewski, Pawel, Smith, Brandon, Solanki, Guirish, Solla, Davi Fontoura, Solla, Davi, Sonmez, Ozcan, Sönmez, Müge, Soon, Wai Cheong, Stefini, Roberto, Stienen, Martin Nikolaus, Stoica, Bogdan, Stovell, Matthew, Suarez, Maria Natalia, Sulaiman, Alaa, Suliman, Mazin, Sulistyanto, Adi, Sulubulut, Şeniz, Sungailaite, Sandra, Surbeck, Madlen, Szmuda, Tomasz, Taddei, Graziano, Tadele, Abraham, Taher, Ahmed Saleh Ahmed, Takala, Riikka, Talari, Krishna Murthy, Tan, Bih Huei, Tariciotti, Leonardo, Tarmohamed, Murad, Taroua, Oumayma, Tatti, Emiliano, Tenovuo, Olli, Tetri, Sami, Thakkar, Poojan, Thango, Nqobile, Thatikonda, Satish Kumar, Thesleff, Tuomo, Thomé, Claudius, Thornton, Owen, Timmons, Shelly, Timoteo, Eva Ercilio, Tingate, Campbell, Tliba, Souhil, Tolias, Christos, Toman, Emma, Torres, Ivan, Torres, Luis, Touissi, Youness, Touray, Musa, Tropeano, Maria Pia, Tsermoulas, Georgios, Tsitsipanis, Christos, Turkoglu, Mehmet Erhan, Uçkun, Özhan Merzuk, Ullman, Jamie, Ungureanu, Gheorghe, Urasa, Sarah, Ur-Rehman, Obaid, Uysal, Muhammed, Vakis, Antonios, Valeinis, Egils, Valluru, Vaishali, Vannoy, Debby, Vargas, Pablo, Varotsis, Phillipos, Varshney, Rahul, Vats, Atul, Veljanoski, Damjan, Venturini, Sara, Verma, Abhijit, Villa, Clara, Villa, Genaro, Villar, Sofia, Villard, Erin, Viruez, Antonio, Voglis, Stefanos, Vulekovic, Petar, Wadanamby, Saman, Wagner, Katherine, Walshe, Rebecca, Walter, Jan, Waseem, Marriam, Whitworth, Tony, Wijeyekoon, Ruwani, Williams, Adam, Wilson, Mark, Win, Sein, Winarso, Achmad Wahib Wahju, Ximenes, Abraão Wagner Pessoa, Yadav, Anurag, Yadav, Dipak, Yakoub, Kamal Makram, Yalcinkaya, Ali, Yan, Guizhong, Yaqoob, Eesha, Yepes, Carlos, Yılmaz, Ayfer Nazmiye, Yishak, Betelehem, Yousuf, Farhat Basheer, Zahari, Muhammad Zamzuri, Zakaria, Hussein, Zambonin, Diego, Zavatto, Luca, Zebian, Bassel, Zeitlberger, Anna Maria, Zhang, Furong, Zheng, Fengwei, Ziga, Michal, Clark, David, Joannides, Alexis, Adeleye, Amos Olufemi, Bajamal, Abdul Hafid, Bashford, Tom, Biluts, Hagos, Budohoski, Karol, Ercole, Ari, Fernández-Méndez, Rocío, Figaji, Anthony, Gupta, Deepak Kumar, Härtl, Roger, Iaccarino, Corrado, Khan, Tariq, Rubiano, Andrés, Shabani, Hamisi K, Sichizya, Kachinga, Tewari, Manoj, Tirsit, Abenezer, Thu, Myat, Tripathi, Manjul, Trivedi, Rikin, Devi, Bhagavatula Indira, Servadei, Franco, Menon, David, Kolias, Angelos, and Hutchinson, Peter

Published
2022
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46. Nationwide Cross-Sectional Analysis of Mortality Trends in Patients with Sarcoidosis and Non-Ischemic Cardiovascular Disease—The Impact of Gender, Ethnicity, Geographical Location, and COVID-19 Pandemic.

Author

Ahmed, Raheel, Ahmed, Mushood, Khlidj, Yehya, Rehman, Obaid Ur, Al-Mukhtar, Laith, Abou Khater, Noha, Khurram Mustaq Gardezi, Syed, Rashid, Muhammad, Collins, Peter, Jain, Hritvik, Ramphul, Kamleshun, Baig, Mudassar, Chahal, Anwar, Kouranos, Vasilis, Behary Paray, Nitish, and Sharma, Rakesh

Abstract

Background and Objectives: The epidemiological data regarding mortality rates of adults with sarcoidosis and non-ischemic cardiovascular disease (CVD) are limited. A retrospective observational analysis was conducted to identify trends and disparities related to sarcoidosis and non-ischemic cardiovascular disease mortality among the adult US population from 1999 to 2022. Methods: We used the Centers for Disease Control and Prevention (CDC) WONDER database to extract death certificate data for the adult US population (≥25 years). The age-adjusted mortality rates (AAMRs) per 100,000 persons were calculated, and annual percent changes (APCs) were determined using Joinpoint. Results: Between 1999 and 2022, 23,642 deaths were identified related to non-ischemic CVD + sarcoidosis. The overall AAMR increased from 0.2 (95% CI, 0.2 to 0.3) in 1999 to 0.5 (95% CI, 0.5 to 0.6) in 2022. Females had a higher AAMR than males (0.6 vs. 0.5). Non-Hispanic (NH) blacks had the highest AAMR, followed by NH whites and Hispanic or Latinos. The southern region had the highest AAMR (0.7: 95% CI, 0.6–0.7), followed by the Midwest (0.6, 95% CI, 0.54–0.669), the Northeast (0.5, 95% CI, 0.5 to 0.6), and the West (0.4; 95% CI, 0.3–0.4). Urban and rural areas had comparable mortality rates (0.5 vs. 0.6). People aged 65+ had the highest AAMRs. Conclusions: The overall mortality rates for non-ischemic CVD and sarcoidosis have increased in the US from 1999 to 2022. Females and NH blacks had higher AAMRs, while a minimal variation was observed based on geographical regions. Early diagnosis and prompt management are the keys to reducing the mortality burden of non-ischemic CVD plus sarcoidosis. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Identification and Expression Analysis of TCP Transcription Factors Under Abiotic Stress in Phoebe bournei.

Author

Lv, Wenzhuo, Yang, Hao, Zheng, Qiumian, Liao, Wenhai, Chen, Li, Lian, Yiran, Lin, Qinmin, Huo, Shuhao, Rehman, Obaid Ur, Liu, Wei, Zheng, Kehui, Zhang, Yanzi, and Cao, Shijiang

Subjects
GENE families, TRANSCRIPTION factors, ABIOTIC stress, X chromosome, SOMATOTROPIN
Abstract

The TCP gene family encodes plant transcription factors crucial for regulating growth and development. While TCP genes have been identified in various species, they have not been studied in Phoebe bournei (Hemsl.). This study identified 29 TCP genes in the P. bournei genome, categorizing them into Class I (PCF) and Class II (CYC/TB1 and CIN). We conducted analyses on the PbTCP gene at both the protein level (physicochemical properties) and the gene sequence level (subcellular localization, chromosomal distribution, phylogenetic relationships, conserved motifs, and gene structure). Most P. bournei TCP genes are localized in the nucleus, except PbTCP9 in the mitochondria and PbTCP8 in both the chloroplast and nucleus. Chromosomal mapping showed 29 TCP genes unevenly distributed across 10 chromosomes, except chromosome 8 and 9. We also analyzed the promoter cis-regulatory elements, which are mainly involved in plant growth and development and hormone responses. Notably, most PbTCP transcription factors respond highly to light. Further analysis revealed three subfamily genes expressed in five P. bournei tissues: leaves, root bark, root xylem, stem xylem, and stem bark, with predominant PCF genes. Using qRT-PCR, we examined six representative genes—PbTCP16, PbTCP23, PbTCP7, PbTCP29, PbTCP14, and PbTCP15—under stress conditions such as high temperature, drought, light exposure, and dark. PbTCP14 and PbTCP15 showed significantly higher expression under heat, drought, light and dark stress. We hypothesize that TCP transcription factors play a key role in growth under varying light conditions, possibly mediated by auxin hormones. This work provides insights into the TCP gene family's functional characteristics and stress resistance regulation in P. bournei. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Identification and Characterization of the DOF Gene Family in Phoebe bournei and Its Role in Abiotic Stress—Drought, Heat and Light Stress.

Author

Zheng, Kehui, Lv, Mengmeng, Qian, Jiaying, Lian, Yiran, Liu, Ronglin, Huo, Shuhao, Rehman, Obaid Ur, Lin, Qinmin, Zhou, Zhongyang, Liu, Xiaomin, and Cao, Shijiang

Subjects
GENE families, ZINC-finger proteins, ABIOTIC stress, ARABIDOPSIS thaliana, TRANSCRIPTION factors
Abstract

Phoebe bournei is a second-class endangered and protected species unique to China, and it holds significant ecological and economic value. DNA binding one zinc finger (Dof) transcription factors are plant-specific regulators. Numerous studies have demonstrated that Dof genes are involved in plant growth, development and responses to abiotic stress. In this study, we identified and analyzed 34 PbDof gene members at the whole-genome level. The results indicated that the 34 PbDof genes were unevenly distributed across 12 chromosomes. We utilized the Dof genes from Arabidopsis thaliana and P. bournei to construct a phylogenetic tree and categorized these genes into eight subgroups. In the collinearity analysis, there were 16 homologous gene pairs between AtDof and PbDof and nine homologous gene pairs between ZmDof and PbDof. We conducted a cis-acting element analysis and found that cis-acting elements involved in light response were the most abundant in PbDof genes. Through SSR site prediction, we analyzed that the evolution level of Dof genes is low. Additionally, we assessed the expression profiles of eight PbDof genes under high temperature, drought, and light stress using qRT-PCR. In particular, PbDof08 and PbDof16 are significantly upregulated under the three stresses. This study provides foundational information for PbDof genes and offers new insights for further research on the mechanism of Dof transcription factors responding to stress, as well as the adaptation of P. bournei to environmental changes. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Gamifying Green: Does Gamified Advertisement Affect Consumer Intentions to Use Green Gamified Banking – The Moderating Role of Environmental Concerns.

Author

Rehman, Obaid ul and Jun, Tang Zhong

Abstract

This paper examines the impact of Gamified advertisement (G.A) on the intention to use green gamified banking (IUGGB) in mainland China. A survey of 264 e-banking consumers was conducted, and the data was analyzed using linear regression, path analysis, and PLS-SEM. It is observed that GA has a significant positive effect on IUGGB, β = 0.342, p < 0.001, while its influence has been outperformed by environmental concern (ENV), β = 0.59, p < 0.001. The interaction effect of GA-ENV was statistically significant, with a β-value of 0.11 and p = 0.025, suggesting interactions between the variables. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Recent Development, Trends and Challenges in IoT Security

Author

Talezari, Morteza, Tu, Shanshan, Rehman, Sadaqat ur, Chuangbai, Xiao, Ahmad, Basharat, Waqas, Muhammad, Rehman, Obaid ur, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sun, Xingming, editor, Zhang, Xiaorui, editor, and Xia, Zhihua, editor

Published
2021
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