39,362 results on '"Memon, A."'
Search Results
52. Povidone-iodine in vitro antiseptic efficacy as a function of exposure duration, concentration, preparation, and length of storage
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Ambrosino, Christina M., Shen, Leo L., Mahjoub, Heba, Memon, Warda, Zhang, Sean X., and Breazzano, Mark P.
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- 2024
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53. Heavy Metal Concentrations in Water, Sediment, and Fish Species in Chashma Barrage, Indus River: A Comprehensive Health Risk Assessment
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Rind, Khalid Hussain, Aslam, Sonia, Memon, Nazakat Hussain, Raza, Asif, Saeed, Muhammad Qamar, Mushtaq, Alia, Ujan, Javed Ahmed, Habib, Syed Fahad, Al-Rejaie, Salim S., and Mohany, Mohamed
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- 2024
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54. Curriculum, democracy and pedagogies for justice: a collective futures dialogue
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Maher, Katie, Rigney, Lester-Irabinna, King, Mikayla, Garrett, Robyne, Windle, Joel, Memon, Nadeem, Wrench, Alison, Carter, Jenni, Paige, Kathryn, O’Keeffe, Lisa, Lovell, Margaret, Schulz, Samantha, Soong, Hannah, Colton, Jill, McDonald, Sarah, and Hattam, Robert
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- 2024
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55. Characterization and value-added addition of biomass for the reduction of emissions using coal as co-feed
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Usto, Muhammad Azam, Solangi, Zulfiqar, Shah, Abdul Kareem, Qureshi, Khan Muhammad, Sultan, Syed Hasseb, Rajput, Muhammad Irfan, Jatoi, Abdul Sattar, Shah, Ayaz Ali, Memon, Shahrukh, Channa, Fida Hussain, Siyal, Sajid Hussain, and jarwar, Arshad Iqbal
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- 2024
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56. Gender disparities in gastroenterology and hepatology conferences: The journey towards equality
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Devi, Jalpa, Butt, Amna Subhan, Rai, Lajpat, Kumar, Jatin, and Memon, Sadik
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- 2024
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57. Investigating the Relationship Between Relational Leadership and Employees’ Promotive Voice Behavior
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Memon, Khalid Rasheed and Ooi, Say Keat
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- 2024
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58. Effects of performance appraisal on employees’ extra-role behaviors and turnover intentions – A parallel mediation model
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Ghani, Bilqees, Malik, Muhammad Abdur Rahman, and Memon, Khalid Rasheed
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- 2024
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59. Strategic planning, budget monitoring and growth optimism: evidence from Australian SMEs
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Rice, John, Martin, Nigel, Raziq, Muhammad Mustafa, Memon, Mumtaz Ali, and Fieger, Peter
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- 2024
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60. Exploring the drivers of residents’ identification and green citizenship behavior in green cities: a multicountry study
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Raji, Ridwan Adetunji, Mohamad, Bahtiar, and Memon, Sumera
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- 2024
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61. Pizza Town Sukkur: sustaining in the current competitive environment
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Memon, Ubedullah, Lanjo, Asghar Ali, Shaikh, Javeria, Khan, Mahnoor, and Ali, Masroor
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- 2024
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62. Turning crisis into opportunity: the emergence of cyber risk takaful in the digital world
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Memon, Ubedullah, Waseem, Muhammad, Zain ul Abidin, Muhammad, Junejo, Zeeshan, and Ali, Masroor
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- 2024
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63. Alpha-wolves and Alpha-mammals: Exploring Dictionary Attacks on Iris Recognition Systems
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Banerjee, Sudipta, Jain, Anubhav, Jiang, Zehua, Memon, Nasir, Togelius, Julian, and Ross, Arun
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Computer Science - Computer Vision and Pattern Recognition - Abstract
A dictionary attack in a biometric system entails the use of a small number of strategically generated images or templates to successfully match with a large number of identities, thereby compromising security. We focus on dictionary attacks at the template level, specifically the IrisCodes used in iris recognition systems. We present an hitherto unknown vulnerability wherein we mix IrisCodes using simple bitwise operators to generate alpha-mixtures - alpha-wolves (combining a set of "wolf" samples) and alpha-mammals (combining a set of users selected via search optimization) that increase false matches. We evaluate this vulnerability using the IITD, CASIA-IrisV4-Thousand and Synthetic datasets, and observe that an alpha-wolf (from two wolves) can match upto 71 identities @FMR=0.001%, while an alpha-mammal (from two identities) can match upto 133 other identities @FMR=0.01% on the IITD dataset., Comment: 8 pages, 5 figures, 13 tables, Workshop on Manipulation, Adversarial, and Presentation Attacks in Biometrics, Winter Conference on Applications of Computer Vision
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- 2023
64. AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons
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Murugesan, Gowtham Krishnan, McCrumb, Diana, Aboian, Mariam, Verma, Tej, Soni, Rahul, Memon, Fatima, Farahani, Keyvan, Pei, Linmin, Wagner, Ulrike, Fedorov, Andrey Y., Clunie, David, Moore, Stephen, and Van Oss, Jeff
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Electrical Engineering and Systems Science - Image and Video Processing - Abstract
The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging tools and algorithms. Despite their potential, these collections are minimally annotated; only 4% of DICOM studies in collections considered in the project had existing segmentation annotations. This project increases the quantity of segmentations in various IDC collections. We produced high-quality, AI-generated imaging annotations dataset of tissues, organs, and/or cancers for 11 distinct IDC image collections. These collections contain images from a variety of modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). The collections cover various body parts, such as the chest, breast, kidneys, prostate, and liver. A portion of the AI annotations were reviewed and corrected by a radiologist to assess the performance of the AI models. Both the AI's and the radiologist's annotations were encoded in conformance to the Digital Imaging and Communications in Medicine (DICOM) standard, allowing for seamless integration into the IDC collections as third-party analysis collections. All the models, images and annotations are publicly accessible., Comment: 24 pages; 20 figures
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- 2023
65. Information Forensics and Security: A quarter-century-long journey
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Barni, Mauro, Campisi, Patrizio, Delp, Edward J., Doërr, Gwenael, Fridrich, Jessica, Memon, Nasir, Pérez-González, Fernando, Rocha, Anderson, Verdoliva, Luisa, and Wu, Min
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Computer Science - Cryptography and Security ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Information Forensics and Security (IFS) is an active R&D area whose goal is to ensure that people use devices, data, and intellectual properties for authorized purposes and to facilitate the gathering of solid evidence to hold perpetrators accountable. For over a quarter century since the 1990s, the IFS research area has grown tremendously to address the societal needs of the digital information era. The IEEE Signal Processing Society (SPS) has emerged as an important hub and leader in this area, and the article below celebrates some landmark technical contributions. In particular, we highlight the major technological advances on some selected focus areas in the field developed in the last 25 years from the research community and present future trends.
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- 2023
66. A Large Open Access Dataset of Brain Metastasis 3D Segmentations with Clinical and Imaging Feature Information
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Ramakrishnan, Divya, Jekel, Leon, Chadha, Saahil, Janas, Anastasia, Moy, Harrison, Maleki, Nazanin, Sala, Matthew, Kaur, Manpreet, Petersen, Gabriel Cassinelli, Merkaj, Sara, von Reppert, Marc, Baid, Ujjwal, Bakas, Spyridon, Kirsch, Claudia, Davis, Melissa, Bousabarah, Khaled, Holler, Wolfgang, Lin, MingDe, Westerhoff, Malte, Aneja, Sanjay, Memon, Fatima, and Aboian, Mariam S.
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Quantitative Biology - Quantitative Methods - Abstract
Resection and whole brain radiotherapy (WBRT) are the standards of care for the treatment of patients with brain metastases (BM) but are often associated with cognitive side effects. Stereotactic radiosurgery (SRS) involves a more targeted treatment approach and has been shown to avoid the side effects associated with WBRT. However, SRS requires precise identification and delineation of BM. While many AI algorithms have been developed for this purpose, their clinical adoption has been limited due to poor model performance in the clinical setting. Major reasons for non-generalizable algorithms are the limitations in the datasets used for training the AI network. The purpose of this study was to create a large, heterogenous, annotated BM dataset for training and validation of AI models to improve generalizability. We present a BM dataset of 200 patients with pretreatment T1, T1 post-contrast, T2, and FLAIR MR images. The dataset includes contrast-enhancing and necrotic 3D segmentations on T1 post-contrast and whole tumor (including peritumoral edema) 3D segmentations on FLAIR. Our dataset contains 975 contrast-enhancing lesions, many of which are sub centimeter, along with clinical and imaging feature information. We used a streamlined approach to database-building leveraging a PACS-integrated segmentation workflow., Comment: 12 pages, 2 figures, 1 table
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- 2023
67. Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon
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Memon, Halar, Gjerde, Eskil, Lynam, Alex, Chowdhury, Amiya, De Maere, Geert, Figueredo, Grazziela, and Hussain, Tanvir
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Physics - Plasma Physics - Abstract
In this study, the first-of-its-kind use of active learning (AL) framework in thermal spray is adapted to improve the prediction accuracy of the in-flight particle characteristics and uses Gaussian Process (GP) ML model as a surrogate that generalises a global solution without necessarily involving physical mechanisms. The AL framework via the Bayesian Optimisation was utilised to: (a) reduce the maximum uncertainty in the given database and (b) reduce local uncertainty around a contrived test point. The initial dataset consists of 26 atmospheric plasma spray (APS) parameters of silicon, aimed at ceramic matrix composites (CMCs) for the next generation of aerospace applications. The maximum uncertainty in the initial dataset was reduced by AL-driven identification of search spaces and conducting six guided spray trails in the identified search spaces. On average, a 52.9% improvement (error reduction) of RMSE and an R2 increase of 8.5% were reported on the predicted in-flight particle velocities and temperatures after the AL-driven optimisation. Furthermore, the Bayesian Optimisation around a contrived test point to predict the best possible characteristics resulted in a three-fold increase in prediction accuracy as compared to the non-optimised prediction. These AL-guided experimental validations not only increase the informativeness of the limited dataset but is adaptable for other thermal spraying methods without necessarily involving physical mechanisms and underlying mechanisms. The use of AL-driven optimisation may drive the thermal spraying towards resource-efficiency and may serve as the first step towards fully digital thermal spraying environments.
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- 2023
68. Phytochemical and antibacterial assessment of essential oils extracted from aerial parts of cordia dichotoma G. Forst
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Saddam Hussain Bughio, Saba Bhatti, Shahabuddin Memon, Ayaz Ali Memon, Muhammad Qasim Samejo, Roomia Memon, Mohsin Kazi, and Khalid Hussain Thebo
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Cordia dichotoma ,essential oils ,chemical composition ,GC-MS ,antibacterial activity ,Nutrition. Foods and food supply ,TX341-641 ,Food processing and manufacture ,TP368-456 - Abstract
ABSTRACTThis study involved the exploration of hydro-distilled essential oil (EsO) from the aerial parts of Cordia dichotoma fruits, stems, seeds and leaves via gas chromatography‒mass spectrometry. Approximately 33 volatile components were detected throughout the study. Almost 27 and 23 compounds (comprising 64.83% and 31.55%, respectively, of the total components) were detected in the fruits and stems, whereas 25 compounds (57.12% of the total components) were detected in the seeds, and 25 compounds (52.48% of the total components) were found in the leaves. The main components of the fruit oil were Nonanal (5.77%), Oleic acid (4.30%), β-Damascenone (4.12%), 3, 4-Dehydro-β-ionone (4.06%), Methyl jasmonate (3.32%), Sabinene (3.31%), Phytol (3.22%) and Vitispirane (3.11%). From stem oil, the major components were Nonanal (6.52%), Nonadecane (3.22%) and 2, 3-Octanedione (2.16%). Whereas, the major components of the seed oils were Nonanal (12.14%), Oleic acid (5.13%), Dihydroactindiolide (3.35%), 2-Methoxy-4-vinylphenol (3.18%), Dodecanoic acid (3.16%) and Methyl jasmonate (3.11%). Similarly, the major components of the leaf oils were 2, 4-di-t-Butylphenol (10.25%), 3-Methylnonane (4.73%), 2-Undecanol (4.64%), 3, 4-Dehydro-β-ionone (3.52%) and Nonanal (3.16%). These EsO were used for antibacterial activity against two bacteria i.e. E. coli (G-ve) and the S. aureus (G+ve) by disc diffusion method to determine the MIC (minimum inhibitory concentration) and MBC (maximum bactericidal concentration). However, among the four parts of C. dichotoma, fruit and seed EsO were highly effective against E. coli (MIC and MBC were 125 μg/mL, 1000 μg/mL respectively) compared to S. aureus (MICs of 250 and 500 μg/mL with an MBC of 1000 μg/mL)
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- 2024
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69. Supramolecular structural-based fabrication of silver nanoparticles using diamide derivative of calix[4]arene: an efficient antimicrobial agent
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Chandio, Anwar Ali, Memon, Shahabuddin, Otho, Aijaz, Khalid, Awais, Alotaibi, Bader S., Balouch, Amna, Brohi, Nazir Ahmed, Memon, Fakhar N., Memon, Ayaz Ali, and Thebo, Khalid Hussain
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- 2024
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70. SEMAGLUTIDE: Weight loss, glycaemic control and safety profile in obese patients with and without type-II diabetes-An experience from Karachi, Pakistan
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Muhammad Y. Memon, Tasnim Ahsan, Rukhshanda Jabeen, Saba Latif, Saeeda F. Qasim, and Paras Imran
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alanine aminotransferase ,blood pressure ,diabetes mellitus ,dyslipidemia ,glycemic control ,hba1c ,obesity ,semaglutide ,Medicine - Abstract
Objective To assess the efficacy and safety of Semaglutide (a GLP-1 receptor agonist) in obese patients with and without Type-II Diabetes Mellitus. Methods This observational analytic cohort study was conducted in a private medical institute in Karachi Pakistan; from August 2022 to January 2023. A total of 65 obese individuals >18 years of age, with or without T2D were included. Semaglutide was started with an initial dose of 0.25 mg with an increase in dose to 0.5 mg, 1 mg and 2 mg with gap of 4 weeks between each dose escalation. Patients were kept on the maximally tolerated dose, not exceeding 2 mg/week. Patients were evaluated on the first and second follow-up at 3 and 6 months respectively, for the same parameters as noted at the initial visit, along with documentation of any adverse effect. Results Out of 65 patients, 49.2% were female and 50.8% were male. Mean age was 49.16 ± 14.20 years. 47.7% of the patients had hypertension, 46.2% had diabetes mellitus, 35.4% had dyslipidemia and 13.8% had ischemic heart disease. All patients were using 0.5 mg of semaglutide after three months, however by six months 33.8% were using 1 mg, and 24.6% were on 2 mg, whereas 40% decided to adhere to 0.5 mg and only 1.5% decided to reduce the dose to 0.25 mg due to adverse effects. Patients reported start of the first adverse effect by 3.44 ± 2.27 weeks of starting the drug. By the end of three months, 55.4% of patients in our study reported adverse effect, which declined to 34.5% by the end of six months, and the majority being mild to moderate and the most frequent side effects were gastrointestinal in origin. There was no significant difference in side effect profile in between those with and without diabetes mellitus. The average weight loss was 5.81 ± 2.64 kg and 9.86 ± 3.54 kg after three and six months respectively and the amount of weight loss was almost equal in those with and without T2D. A significant decline was observed in the average HbA1c levels, body mass index (p =
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- 2024
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71. Generalized tetanus complicated with Takotsubo-cardiomyopathy in a septuagenarian following a laceration injury with soil contamination – a case report
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Sareesh Bandapaati, Rayno Navinan Mitrakrishnan, Mazharul Islam, and Usman Memon
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Tetanus ,Elderly ,Vaccination ,Post exposure prophylaxis ,Cardiac complications ,Takotsubo-cardiomyopathy ,Medical emergencies. Critical care. Intensive care. First aid ,RC86-88.9 - Abstract
Abstract Background Tetanus is a clinical rarity due to the successful globally adopted childhood vaccination programme. The rising elderly population in the United Kingdom creates a subset of individuals whom are prone to develop Tetanus as they preceded this vaccination drive. Case summary A 76 year old Caucasian lady presented with a soil contaminated laceration injury on her knee following a fall. Though she received urgent assessment and wound care, the relevance of the injury in the backdrop of her age was not appreciated and her tetanus post exposure prophylaxis was overlooked. She readmitted seeking further management 1 week later with an infected wound with Trismus and clinical features favoring Generalized tetanus. During her stay she developed Takotsubo-cardiomyopathy with congestive cardiac failure and required prolonged care in the intensive unit with mechanical ventilation and rehabilitation before being discharged home. Conclusion First contact physicians should have a greater appreciation of the types of injuries and at-risk individuals who are more prone to develop tetanus upon exposure to ensure early and appropriate identification. There should be greater situational awareness with regard to the elderly in view of their heightened risk of development of tetanus specially those born before the vaccination drive. Knowledge regarding post exposure prophylaxis measures for tetanus should be regularly updated using local guidance to ensure awareness, so as to despite its rarity Tetanus remains an adequately appreciated disease.
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- 2024
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72. AI-Generated Annotations Dataset for Diverse Cancer Radiology Collections in NCI Image Data Commons
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Gowtham Krishnan Murugesan, Diana McCrumb, Mariam Aboian, Tej Verma, Rahul Soni, Fatima Memon, Keyvan Farahani, Linmin Pei, Ulrike Wagner, Andrey Y. Fedorov, David Clunie, Stephen Moore, and Jeff Van Oss
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Science - Abstract
Abstract The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging tools and algorithms. Despite their potential, these collections are minimally annotated; only 4% of DICOM studies in collections considered in the project had existing segmentation annotations. This project increases the quantity of segmentations in various IDC collections. We produced high-quality, AI-generated imaging annotations dataset of tissues, organs, and/or cancers for 11 distinct IDC image collections. These collections contain images from a variety of modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). The collections cover various body parts, such as the chest, breast, kidneys, prostate, and liver. A portion of the AI annotations were reviewed and corrected by a radiologist to assess the performance of the AI models. Both the AI’s and the radiologist’s annotations were encoded in conformance to the Digital Imaging and Communications in Medicine (DICOM) standard, allowing for seamless integration into the IDC collections as third-party analysis collections. All the models, images and annotations are publicly accessible.
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- 2024
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73. Comparison of active release technique and post-isometric relaxation in treatment of plantar fasciitis among traffic police wardens: a quasi-experimental study
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Muniba Afzal Dar, Kinza Noor, Sajjan Iqbal Memon, Roha Safdar, Zainab Rafique, Aftab Mehar, and Fatima Saddiqua
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Active release technique ,Post-isometric relaxation ,Plantar fasciitis ,Traffic wardens ,Miscellaneous systems and treatments ,RZ409.7-999 - Abstract
Abstract Background Plantar fasciitis (PF) is a common cause of chronic foot pain that leads to functional limitations in individuals. There has been recent research on plantar fasciitis, but no studies have compared the effects of the active release technique and post-isometric relaxation in patients to determine which manual therapy technique improves foot pain and function. Objective This study aimed to compare the effectiveness of the active release technique and post-isometric relaxation on proximal foot pain and functional status and to assess muscular tightness among patients with traffic police wards and plantar fasciitis. Methods A quasi-experimental study (pre-test, post-test) was conducted in the Physiotherapy Department of Police Hospital, Gujranwala, Pakistan, between October 2022 and April 2023. We included 30 consecutively aged 25- to 60-year-old symptomatic police wardens diagnosed with planter fasciitis, who complained of pain on walking and standing for more than 3 months and met the inclusion criteria. They were equally assorted into two groups (n = 15 in each group) using convenient sampling. Group A received an active release exercise technique, group B received a post-isometric relaxation technique, and the participants in both groups received a similar baseline treatment protocol that consisted of calf stretching and stretching of the plantar fascia (5 repetitions and holding for 15 s). In the outcome measures, we included the Foot Function Index to assess the function of the foot and the Visual Analog Scale to examine the pain intensity measured during rest. The participants in both groups performed the selective protocol 3 days per week for 3 weeks, and we calculated the results at baseline and on the third day of the third week. We analyzed the data using SPSS software version 24 (IBM Corp., Armonk, NY). We compared within-group differences in the VAS score and FFI using paired t tests and analyzed between-group differences in the VAS score and FFI before and after performing the ART and PIR using independent t tests. Results The 8-week intervention therapy revealed a demographic age mean and standard deviation of 36.60 ± 6.11 for group A and 35.60 ± 4.85 for group B. Within-group analysis demonstrated a significant decrease in VAS (pain) score following ART intervention (1.80 ± 0.862, p 0.05), suggesting non-significant differences. Conclusion The active release exercise intervention is more effective than post-isometric relaxation in improving pain and foot function disability in patients with plantar fasciitis. The present study aimed to help physical therapists choose the most efficient manual therapy exercise intervention to improve functional limitations.
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- 2024
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74. A 360-degree evaluation of the professionalism and communication skills of technologists working in the radiology department of a public sector tertiary care hospital in Karachi, Pakistan
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N. Rafiq, N. Naz, R. Memon, J. Shoukat, K. Kumari, H. Shaikh, and F. Akram
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Radiological technologist ,Professionalism ,Communication skills ,Evaluation ,Special aspects of education ,LC8-6691 ,Medicine - Abstract
Abstract Background Radiologic technologists (RTs) are at the forefront of radiology departments and require optimal skills to demonstrate professionalism and effective provider–patient communication. Hence, the objective of this study was to determine the reliability of 360-degree evaluation as a feedback tool to improve competencies in this crucial workforce. Methods A planned 360-degree evaluation was conducted using a 10-item tool to evaluate communication skills and professionalism among radiological technologists working at Dow University Hospital, Karachi. In total, 311 evaluations of fifteen radiological technologists were conducted while performing various diagnostic radiology procedures at the radiology department of Dow University Hospital. The data were analysed using SPSS version 26 to compute the evaluation scores and the reliability of 360-degree evaluation. Results A total of 311 RT-patient interactions were recorded over 48 days, with scores from all three raters. The evaluation tool was found to have good internal consistency for patients, faculty, and RT, with Cronbach’s alpha values of 0.89, 087, and 0.74, respectively. The study found an intraclass correlation of 0.66 (95% CI; 0.58–0.72), showing moderate reliability of the 360-degree evaluation across different raters. Conclusion We conclude that 360-degree evaluation is a valid and reliable tool for determining the professionalism and communication skills of radiologic technologists and should be incorporated into training programs for formative and summative assessments. However, large-scale multicenter studies are crucial for generalizing these findings and incorporating 360 evaluations in radiological technologist training programs for formative and summative assessments.
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- 2024
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75. Effect of recycled aggregates with different parent strength and fly ash on flexural strength of recycled aggregate concrete prisms
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Ghulam Shabir Bhatti, Bashir Ahmed Memon, Muhammad Aachar Zardari, Mahboob Oad, Riaz Bhambhro, and Amjad Hussain Bhutto
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Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Science - Abstract
Fast consumption of conventional ingredients of concrete and waste generated due to demolishing old buildings is a multi-fold problem in the concrete industry. Hence the sustainable alternative of it is the need of the day. In this research work effect of binary blending of demolished waste and fly ash on the flexural strength of plain concrete prism is presented. The properties of aggregates and cement are evaluated. The physical and chemical properties of fly ash were determined. Recycled aggregates from demolished waste with different mix ratios (1:2:4 and 1:1.5:3) were used. Optimization of recycled aggregates; by evaluating concrete cylinders in 12 batches; showed 35% as optimum. At the optimum dosage of recycled aggregates fly ash was used from 2.5% to 15% with an increment of 2.5% to optimize its dosage. Compressive strength test of the standard-size cylinders and their comparison with control concrete showed a 10% dosage of a fly as the optimum percentage to replace the cement in the concrete matrix. Using both optimized dosages of recycled aggregates and fly ash prism specimens of 900mmx150mmx300mm were cast in four batches. The beam specimens were cured for 28 days followed by an evaluation of flexural strength and deflection under centric load in the universal testing machine. Test results of flexural strength (only 15% loss) showed good potential for both waste materials in the concrete matrix. Recycled aggregate with higher parent strength showed better performance than its other counterparts. With higher-strength recycled aggregates residual flexural strength was recorded as equal to 93%. For all specimens recorded deflection was within the allowable limits of ACI-318.
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- 2024
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76. Exploring the adaptive mechanisms and strategies of various populations of Sporobolus ioclados in response to arid conditions in Cholistan desert
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Abdul Rehman, Rabia Asma Memon, Mansoor Hameed, Nargis Naz, Anis Ali Shah, Ihab Mohamed Moussa, Eman A. Mahmoud, Toqeer Abbas, and Shifa Shaffique
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Cholistan desert ,Drought adaptation ,Plant physiology ,Ecological features ,Water scarcity ,Proline contents ,Botany ,QK1-989 - Abstract
Abstract This study explored the drought resistance mechanisms of different populations of Sporobolus ioclados (Poaceae), locally known as “Sawri,” “Drabhri” and “Dhrbholi” native to Africa and the Indian Subcontinent. These populations were grown in conventional nursery practices at Khawaja Fareed Government College in Rahim Yar Khan, Pakistan, and subsequently subjected to four distinct levels of drought within carefully monitored experimental settings. The experiment was conducted in a two-factorial design involving populations and drought treatments and was repeated three times. The physiological and morphological responses of S. ioclados, including plant height, number of roots, root length, flag leaf area, stomatal features, proline concentration and nitrogen content, displayed significant variability in response to the imposed drought stress. Drought resulted in increases in proline concentration and nitrogen content. The number of roots decreased, while the length and width of the stomata increased in various populations. A combination of advanced statistical techniques, such as ANOVA, PCA, HCA, and DFA, provided a comprehensive understanding of the mechanism of plant adaptation and the extent of population diversity within the species. The Yazman and Nwab Wala populations exhibited the highest rates of photosynthesis and stomatal conductance, while S. ioclados demonstrated notable drought tolerance at the T4 level of drought stress. A negative correlation was found between proline levels, nitrogen contents, and photosynthesis, suggesting that proline has a protective role in drought. The diverse adaptation strategies indicated by S. ioclados populations have revealed the potential of this species for afforestation and climate change mitigation in dry environments.
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- 2024
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77. LHCGR inactivating variants: single center experience and systematic review of phenotype-genotype of 46,XY and 46,XX patients
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Rohit Barnabas, Swati Jadhav, Anurag Ranjan Lila, Sirisha Kusuma Boddu, Saba Samad Memon, Sneha Arya, Samiksha Chandrashekhar Hegishte, Manjiri Karlekar, Virendra A Patil, Vijaya Sarathi, Nalini S Shah, and Tushar Bandgar
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hypogonadism ,leydig cell hypoplasia ,lhcgr ,Diseases of the endocrine glands. Clinical endocrinology ,RC648-665 - Abstract
Background: The data on Leydig cell hypoplasia (LCH) resulting from biallelic Luteinizing hormone/chorionic gonadotropin receptor (LHCGR) inactivating variants is limited to case series. Methods: We aim to describe our patients and perform systematic review of the patients with LHCGR inactivating variants in the literature. Detailed phenotype and genotype data of three patients from our centre and 85 (46,XY: 67; 46,XX: 18) patients from 59 families with LHCGR-inactivating variants from literature were described. Results: Three 46,XY patients (age 6–18 years) from our center, with two reared as females, had two novel variants in LHCGR. Systematic review (including our patients) revealed 72 variants in 88 patients. 46,XY patients (n = 70, 56 raised as females) presented with pubertal delay (n = 41) or atypical genitalia (n = 17). Sinnecker score ≥3 (suggesting antenatal human chorionic gonadotropin (hCG) inaction) was seen in 80% (56/70), and hCG-stimulated testosterone was low (
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- 2024
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78. Evaluation of antioxidant, antibacterial, and anti-inflammatory activities of deodorizer distillate-derived silver nanoparticles
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Hadia Shoaib, Sarfaraz Ahmed Mahesar, Syed Tufail Hussain Sherazi, Saba Naz, Hamide Filiz Ayyildiz, Sirajuddin, Hina Daud Memon, and Ahmed Raza Sidhu
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Silver nanoparticles ,Green synthesis ,Deodorizer distillate ,Anti-inflammatory activity ,Antibacterial activity ,Chemical engineering ,TP155-156 - Abstract
Silver nanoparticles (AgNPs) were synthesized using a sustainable green approach utilizing deodorizer distillates of canola (CODD) and soybean oil (SODD) as both reducing and capping agents. This synthesis approach resulted in the formation of pale-yellow colored CODD-AgNPs and SODD-AgNPs, which was confirmed by distinctive absorption peaks at 420 nm and 408 nm, respectively via Ultraviolet-Visible (UV–Vis) spectroscopy. Fourier Transform Infrared (FTIR) analysis provided insights into the functional group interactions between CODD and SODD with their AgNPs. X-ray diffraction (XRD) confirmed the face-centered cubic lattice structure of both CODD-AgNPs and SODD-AgNPs. Further characterization via Atomic Force Microscopy (AFM), Transmission Electron Microscopy (TEM), and Scanning Electron Microscopy (SEM) revealed the sizes, shapes, and surface morphologies of CODD-AgNPs and SODD-AgNPs. Assessment of antioxidant activity using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) method demonstrated superior radical scavenging efficacy by CODD-AgNPs (IC50 value 1.07±0.04 µg/mL) and SODD-AgNPs (IC50 value 1.14±0.23 µg/mL) compared to CODD and SODD. Evaluation of antibacterial properties against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) via disc diffusion method revealed potent antibacterial activities of CODD-AgNPs and SODD-AgNPs at 100 µg/mL concentration, surpassing the antibacterial efficacy of CODD and SODD. Furthermore, CODD-AgNPs and SODD-AgNPs exhibited significant anti-inflammatory potential at 500 µg/mL concentration, with IC50 values of 187.2 ± 1.28 µg/mL and 203.9 ± 2.08 µg/mL, respectively, highlighting their potential therapeutic applications. In conclusion, this study demonstrates the effective utilization of CODD and SODD in synthesizing AgNPs with enhanced biological functionalities, making them promising candidates for various biomedical applications.
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- 2024
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79. Nature-inspired swarm intelligence algorithms for optimal distributed generation allocation: A comprehensive review for minimizing power losses in distribution networks
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Qirat Nizamani, Ashfaque Ahmed Hashmani, Zohaib Hussain Leghari, Zeeshan Anjum Memon, Hafiz Mudassir Munir, Tomas Novak, and Michal Jasinski
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Distributed generation ,Distribution networks ,Nature-inspired ,Power loss minimization ,Swarm-intelligence ,Optimization algorithms ,Engineering (General). Civil engineering (General) ,TA1-2040 - Abstract
The continuous increase in energy demand strains distribution networks, resulting in heightened power losses and a decline in overall performance. This negatively impacts distribution companies' profits and increases consumer electricity costs. Optimal distributed generation (DG) allocation in distribution networks can mitigate these issues by enhancing power supply capabilities and improving network performance. However, achieving optimal DG allocation is a complex optimization problem that requires advanced mathematical techniques. Nature-inspired (NI) swarm intelligence (SI)-based optimization techniques offer potential solutions by emulating the natural collective behaviors of animals. This paper reviews the application of NI-SI algorithms for optimal DG allocation, specifically focusing on reducing power losses as a key objective function. The review analyzes a significant body of literature demonstrating the effectiveness of NI-SI techniques in addressing power loss challenges in distribution networks. Additionally, future research directions are provided to guide further exploration in this field.
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- 2024
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80. 24-H movement behaviours research in Chinese population: A scoping review
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Jiafu Huang, Aamir Raoof Memon, Ran Bao, Huiying Fan, Lijuan Wang, Yang Liu, Sitong Chen, and Chunxiao Li
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24-H movement guidelines ,Physical activity ,Sedentary behaviour ,Sleep ,China ,Sports ,GV557-1198.995 - Abstract
Background: Numerous studies examining 24-h movement behaviours have been exponentially published globally. However, no comprehensive reviews summarized and synthesized the evidence on the Chinese population. This review aimed to map the most recent research state and fill the gaps related to 24-h movement behaviours in the Chinese population. Methods: Five electronic databases (Web of Science, PubMed, Scopus, EBSCOhost, and CNKI (Chinese database)) were searched from their inceptions through October 2023. Quantitative studies published in English and/or Chinese were included if they were related to 24-h movement behaviours in the Chinese population. Results: From 9431 documents screened, 53 met the inclusion criteria. All the included studies were published between 2019 and 2023, showing a notable increasing trend over the years. Most studies used cross-sectional designs (96.2 %) and self-reported measures (56.6 %). Nearly all the studies targeted general healthy population (96.2 %), especially children and adolescents (64.2 %). The main three research topics observed were health outcomes (81.1 %), prevalence (66.0 %), and correlates (15.1 %) of 24-h movement behaviours. Conclusion: 24-h movement behaviours in the Chinese population has been an increasingly important research topic in the literature, with predominant focus on children and adolescents (study population), self-report measure (measurement), cross-sectional design (study design), guidelines adherence (study topic), and health outcomes examination (study topic). These findings delineate a research landscape in the Chinese population, and highlight the research gaps needed to be addressed. Future studies are suggested to target these research gaps, expanding evidence base for the Chinese populations. For instance, more studies using device-based measures, longitudinal or interventional designs, as well as qualitative and mixed-methods approaches are required.
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- 2024
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81. Association of the c.75C>A Variant in CLCC1 with Autosomal Recessive Retinitis Pigmentosa in Pakistan
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Yar Muhammad Waryah, Feriha Fatima Khidri, Amir Ansari, Samia Mehmood, Sumera Abbasi, and Shabahat Memon
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clcc1 gene ,night blindness ,endogamous pedigree ,genetic counseling ,sanger sequencing ,phenotype-genotype correlation ,Medicine - Abstract
OBJECTIVE: To identify the disease-causing allele of retinitis pigmentosa, a heterogeneous genetic disorder in a single affected family. METHODOLOGY: A cross-sectional descriptive study was conducted at the Sindh Institute of Ophthalmology & Visual Sciences Hyderabad from December 2022 to December 2023, with approval from the SIOVS ethical committee. A consanguineous pedigree with multiple affected members was included, while pedigrees with only one affected member or secondary causes of vision loss were excluded. After getting informed consent, each enrolled participant's blood samples (10 cc) were collected, and DNA was extracted. The family was subjected to Sanger sequencing for the CLCC1 gene. RESULTS: In this study, one reported c.C75A, p.Asp25Glu allele in the CLCC1 gene was identified from an endogamous pedigree in Sindh, Pakistan. The identified c.C75A, p.Asp25Glu allele is a common cause of autosomal recessive retinitis pigmentosa (arRP) in Pakistani-affected individuals. This allele is estimated to have occurred 2000-5000 years ago and has been transmitted to affected individuals of Pakistani origin and global descent across various geographical regions. All the affected patients underwent detailed clinical investigations, including fundus photography and optical coherence tomography, to confirm the retinitis pigmentosa symptoms. The Sanger sequencing method was used to detect pathogenic variants, and bioinformatics tools were utilized to investigate the pathogenesis of identified alleles and compare phenotype-genotype correlations. CONCLUSION: The finding of frequent disease-causing alleles from Pakistani-affected patients will significantly improve existing genetic databases and facilitate more accurately the affected diagnosis of gene testing.
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- 2024
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82. Hepatoprotective role of unacylated ghrelin in different doses: an experimental study
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Kumayl Abbas Meghji, Tariq Feroz Memon, Muhammad Shahab Hanif, Muhammad Saqib Baloch, Ali Abbas Thalho, and Naila Noor
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ghrelin ,oxidative stress ,liver diseases ,carbon tetrachloride ,alanine transaminase ,aspartate aminotransferases ,malondialdehyde ,interleukin-6 ,tumor necrosis factor-alpha ,superoxide dismutase ,histology ,necroinflammation ,ghrelin, oxidative stress, liver diseases, necroinflammation ,Medicine - Abstract
OBJECTIVE: To investigate the hepatoprotective effects of Unacylated Ghrelin (UAG) at varying doses in the management of acute liver injury in Wistar albino rats. METHODS: This quasi-experimental study was conducted at Department of Physiology, Isra University, Hyderabad, Pakistan from March to August 2023. Thirty Wistar albino rats (200-250 grams) were randomly divided into five groups (n=6). Group A served as the control, while liver injury was induced in Groups B, C, D, and E via intraperitoneal injection of 0.1% CCl₄. Groups C, D, and E were subsequently treated with low, medium, and high doses of UAG, respectively. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), malondialdehyde, interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and superoxide dismutase (SOD) levels were assessed, along with liver histopathology. RESULTS: Pre-experimental body weights (Mean±SD) for groups A, B, C, D, and E were 227.33±7.75 g, 229.80±2.08 g, 228.70±5.34 g, 231.33±8.69 g, and 236.38±10.63 g, respectively. The liver index was 4.36±0.28, 6.65±0.37, 5.80±0.17, 5.70±0.08, and 5.06±0.23, respectively, across the groups. A statistically significant (p
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- 2024
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83. Uncovering the hidden health burden: a systematic review and meta-analysis of iron deficiency anemia among adolescents, and pregnant women in Pakistan
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Benazir Mahar, Tazeen Shah, Khalida shaikh, Saima Naz shaikh, Arsalan Ahmed Uqaili, Khalida Naz Memon, Jamshed Warsi, Rozina Mangi, Sani Aliyu, Qamar Abbas, and Farheen Shaikh
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Iron deficiency ,Pregnancy ,Adolescent females ,Anemia ,Pakistan ,Nutritional diseases. Deficiency diseases ,RC620-627 ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Introduction Iron deficiency anemia (IDA) is the most prevalent diet-related disorder and mainly affects women and children. To determine the trend of anemia incidence in Pakistan, a current review was carried out. This review aimed to estimate the prevalence of anemia among pregnant women and adult/adolescent nonpregnant women in Pakistan and to provide a 15-year trend analysis. Materials and methods Studies were identified by searching PubMed, Google Scholar, Scopus, and Science Direct, complementing this digital exploration, and a manual review of reference lists from previously published prevalence studies was performed to enhance the scope of relevant articles. A total of twenty-seven population-based anemia studies on adolescent/adult females and pregnant women published in Pakistan from January 1st-2007 until December 2021 were included. Systematic data extraction was facilitated through the implementation of a standardized and rigorously pretested data extraction checklist. For the subsequent analysis, the sophisticated capabilities of R statistical software were harnessed. The I2 test was used to assess heterogeneity among studies, and the pooled prevalence of anemia was calculated. Results The final analysis included 27 research articles as well as two extensive National Nutrition survey reports, NNS 2011 and NNS 2018. The forest plot of sixteen studies on pregnant women revealed that the overall pooled prevalence of anemia among pregnant females in Pakistan was 70.4% (95% CI: 0.619, 0.789), and the forest plot of eleven studies on non-pregnant adolescent and adult females reported the pooled prevalence was 54.6% (95% CI: 0.422, 0.669). Subgroup analysis among pregnant women based on region, trimester and socioeconomic status revealed that the highest anemia incidence was observed in Punjab (77.4%). Similarly, females in the second trimester reported a higher prevalence of anemia 78% (95% CI, 0.556 1.015), and the status-wise group with a mixed background reported a higher prevalence 72.8% (95% CI, 0.620 0.835). According to the subgroup analysis, eleven studies of adult nonpregnant groups of mixed socioeconomic status reported a higher prevalence of 56.9% (95% CI, 0.292 0.845). Conclusion In Pakistan, anemia, is widespread among pregnant women and nonpregnant adolescent/adult females. A deeper understanding of anemia in Pakistani women is necessary for targeted interventions and policy decisions to predict demographic shifts.
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- 2024
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84. ENHANCED DEEP LEARNING BASED PRECISION AGRICULTURE: A DECISION SUPPORT SYSTEM FOR ENHANCING CROP RECOMMENDATION ACCURACY USING CONVOLUTIONAL NEURAL NETWORKS (CNN)
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Muhammad Nabeel Amin, Shreeraz Memon, Arshad Ali, Hamayun Khan, Roshan Joshi, Muhammad Tausif Afzal Ran, and Yazed ALsaawy
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accuracy rates ,agricultural parameters ,convolutional neural network (cnn) ,crop recommendation systems ,precision agriculture ,Mathematics ,QA1-939 - Abstract
Machine learning-based crop recommendation models are invaluable tools for enhancing modern AI-based farming, assisting in decisions about the selection of crops to optimize yield performance and growth. This research introduces an intelligent strategy and explainable artificial intelligence (XAI) principles based on the Convolutional Neural Network (CNN) method due to the growing demand for interpretability in modern farming decision-making, Utilizing the "Smart Agricultural Production Optimizing Engine” dataset procured from Kaggle. The proposed CNN model gives remarkable results through a comprehensive examination of soil and environmental boundaries like Nitrogen (N), Phosphorus (P), Potassium (K) levels, temperature, moistness, pH, and precipitation. Our results illustrate that the proposed framework essentially moves forward the precision of trim suggestions, advertising a promising arrangement for modernizing agricultural practices and guaranteeing maintainable crop yields.
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- 2024
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85. Effects of a Paleolithic diet compared to a diabetes diet on leptin binding inhibition in secondary analysis of a randomised cross-over study
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Maelán Fontes-Villalba, Yvonne Granfeldt, Kristina Sundquist, Ashfaque A. Memon, Anna Hedelius, Pedro Carrera-Bastos, and Tommy Jönsson
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Paleolithic diet ,Type 2 diabetes ,Leptin ,Leptin resistance ,Wheat gluten ,BioLep ,Diseases of the endocrine glands. Clinical endocrinology ,RC648-665 - Abstract
Abstract Background Beneficial effects from practising a Paleolithic diet as compared to a diabetes diet on weight, waist circumference, satiety, leptin, HbA1c and glucose control in randomised controlled trial participants with type 2 diabetes could be due to lower leptin resistance. Support for this hypothesis comes from an in vitro experiment that showed that digested wheat gluten, which is excluded from a Paleolithic diet, inhibits leptin from binding to its receptor, thus indicating a possible dietary cause of leptin resistance. However, the clinical relevance of the latter finding is unclear since removal of enzyme activity from the gluten digest by heat treatment also abolished leptin binding inhibition. Assessment of leptin binding inhibition in vivo is possible by comparison of total leptin levels with those of ‘biologically active’ leptin bound to its receptor (bioLep). Objectives To assess the effects of a Paleolithic diet compared to a diabetes diet on leptin binding inhibition and to replicate our in vitro study. Methods BioLep and total leptin levels were measured in secondary analysis of fasting plasma samples from our open label random order three plus three-month long cross-over trial performed in 2005–2007, that compared a Paleolithic diet with a diabetes diet in participants with type 2 diabetes without insulin treatment (per protocol). BioLep was also measured in vitro for known recombinant leptin concentrations incubated with a series of concentrations of 10 kDa spin-filtered digested wheat gluten, with or without prior heat treatment, at 100ºC for 30 min and centrifugation. Results There was no difference between diets when comparing differences between bioLep and total leptin levels and their ratio in the 13 participants, three women and 10 men, aged 52–74 years with a mean BMI of 30 kg/m2 and a mean diabetes duration of eight years. We found no carry-over or period effect for bioLep and total leptin. In vitro, wheat gluten digest inhibited leptin binding in a dose-dependent manner but not after heat treatment. Conclusions We found no leptin binding inhibition after the Paleolithic or diabetes diet, possibly due to its abolishment from cooking-related heat treatment of wheat gluten. Trial registration Registered on 14/02/2007 at ClinicalTrials.gov Identifier: NCT00435240.
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- 2024
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86. Affect and the Force of Counter Stories: Learning Racial Literacy through Thinking and Feeling
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Samantha Schulz, Lester-Irabinna Rigney, Michalinos Zembylas, Robert Hattam, and Nadeem Memon
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This paper contributes to international scholarship on racial literacy in teacher education. Specifically, we consider filmic counter stories as bodies that carry an affective charge with the potential to ignite dialogic and embodied/emotional learning. The football documentary The Final Quarter is our case study. This film traces the racially explosive final years of First Nations Australian, Adam Goodes' elite playing career. The film floodlights football as a site for public pedagogy where people learn racism, with the film offering means of developing racial literacy through examining its encounters. The paper describes racial literacy and establishes affect/embodiment as a contribution to the field. We analyse the film using an affective-discursive lens and genealogical methodology and consider implications for teacher education. We argue that language is insufficient for understanding racism and that the affective intensities activated by film may help to pedagogically illuminate the role of emotions in reproducing racism.
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- 2024
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87. When Religion Intersects Equity and Inclusion: Muslim Educator Affective Responses in Ontario Public Schools
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Nadeem A. Memon and jeewan chanicka
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Ontario education policy articulates an explicit commitment to equity and inclusion for increasingly diverse classrooms. Despite policy commitments, when equity and inclusion intersect with religion, enactments remain underwhelming. This paper draws on the voices of 30 Ontario public school educators, all of whom self-identify as Muslim, to share the ways they affect and have been affected in attempting to enact a responsive pedagogy for faith-centred learners. Through the use of dialogic portraits in two different school boards, the voices of Muslim educators express consistent sentiments of responsibility to advocate for basic religious accommodations while at the same time needing to tread carefully with anything to do with religion in order to not be marginalised by colleagues. Participants in this study reinforce the need for more robust conceptions of equity and inclusion that consider the complexities of the religious identities of learners and educators in public education.
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- 2024
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88. Casteism and Career Change in India: A Gender-Based Explanation of Retention
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Dina Banerjee, Nazia Zabin Memon, and Alka Sharma
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"Dalits" are a historically marginalized caste group in India. In this study, we examine the impact that the institution of caste has on career change. Focusing on the shift from science, technology, engineering, and mathematics (STEM) to non-STEM careers, we ask why members of the Dalit communities in India leave their STEM careers. To present a comprehensive understanding of this career change, we also examine the factors that facilitate their retention in STEM careers. Deriving data from in-depth interviews with 42 STEM scholars from the Dalit communities in India, we illustrate their organizational experiences that are based on casteism. Qualitative data analyses were done using the grounded theory method. Results suggest that while caste operates in a unique way to drive away Dalit scholars from their STEM careers, doing gender plays an important role in their retention within the same careers.
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- 2024
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89. Breast cancer risk factors based on reproductive and non-reproductive profiling of Pakistani women : A hospital based case control study
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Rani, Keenjhar, Laghari, Zulfiqar A., Shaikh, Khalida, Memon, Khalida N., Bhatti, Urooj, and Memon, Zoheb R.
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- 2023
90. Consanguinity as a predictor of premature births reported in maternity wards of teaching hospitals in Sindh Pakistan
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Memon, Khalida N., Rajar, Allah Bachayo, Usman, Gulzar, Zaman, Nimra, Soomro, Fatima, and Memon, Zoheb R.
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- 2023
91. Correction to: The relationship between psychological contract and voice behavior—a social exchange perspective
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Memon, Khalid Rasheed and Ghani, Bilqees
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- 2024
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92. MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
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Li, Jianning, Zhou, Zongwei, Yang, Jiancheng, Pepe, Antonio, Gsaxner, Christina, Luijten, Gijs, Qu, Chongyu, Zhang, Tiezheng, Chen, Xiaoxi, Li, Wenxuan, Wodzinski, Marek, Friedrich, Paul, Xie, Kangxian, Jin, Yuan, Ambigapathy, Narmada, Nasca, Enrico, Solak, Naida, Melito, Gian Marco, Vu, Viet Duc, Memon, Afaque R., Schlachta, Christopher, De Ribaupierre, Sandrine, Patel, Rajnikant, Eagleson, Roy, Chen, Xiaojun, Mächler, Heinrich, Kirschke, Jan Stefan, de la Rosa, Ezequiel, Christ, Patrick Ferdinand, Li, Hongwei Bran, Ellis, David G., Aizenberg, Michele R., Gatidis, Sergios, Küstner, Thomas, Shusharina, Nadya, Heller, Nicholas, Andrearczyk, Vincent, Depeursinge, Adrien, Hatt, Mathieu, Sekuboyina, Anjany, Löffler, Maximilian, Liebl, Hans, Dorent, Reuben, Vercauteren, Tom, Shapey, Jonathan, Kujawa, Aaron, Cornelissen, Stefan, Langenhuizen, Patrick, Ben-Hamadou, Achraf, Rekik, Ahmed, Pujades, Sergi, Boyer, Edmond, Bolelli, Federico, Grana, Costantino, Lumetti, Luca, Salehi, Hamidreza, Ma, Jun, Zhang, Yao, Gharleghi, Ramtin, Beier, Susann, Sowmya, Arcot, Garza-Villarreal, Eduardo A., Balducci, Thania, Angeles-Valdez, Diego, Souza, Roberto, Rittner, Leticia, Frayne, Richard, Ji, Yuanfeng, Ferrari, Vincenzo, Chatterjee, Soumick, Dubost, Florian, Schreiber, Stefanie, Mattern, Hendrik, Speck, Oliver, Haehn, Daniel, John, Christoph, Nürnberger, Andreas, Pedrosa, João, Ferreira, Carlos, Aresta, Guilherme, Cunha, António, Campilho, Aurélio, Suter, Yannick, Garcia, Jose, Lalande, Alain, Vandenbossche, Vicky, Van Oevelen, Aline, Duquesne, Kate, Mekhzoum, Hamza, Vandemeulebroucke, Jef, Audenaert, Emmanuel, Krebs, Claudia, van Leeuwen, Timo, Vereecke, Evie, Heidemeyer, Hauke, Röhrig, Rainer, Hölzle, Frank, Badeli, Vahid, Krieger, Kathrin, Gunzer, Matthias, Chen, Jianxu, van Meegdenburg, Timo, Dada, Amin, Balzer, Miriam, Fragemann, Jana, Jonske, Frederic, Rempe, Moritz, Malorodov, Stanislav, Bahnsen, Fin H., Seibold, Constantin, Jaus, Alexander, Marinov, Zdravko, Jaeger, Paul F., Stiefelhagen, Rainer, Santos, Ana Sofia, Lindo, Mariana, Ferreira, André, Alves, Victor, Kamp, Michael, Abourayya, Amr, Nensa, Felix, Hörst, Fabian, Brehmer, Alexander, Heine, Lukas, Hanusrichter, Yannik, Weßling, Martin, Dudda, Marcel, Podleska, Lars E., Fink, Matthias A., Keyl, Julius, Tserpes, Konstantinos, Kim, Moon-Sung, Elhabian, Shireen, Lamecker, Hans, Zukić, Dženan, Paniagua, Beatriz, Wachinger, Christian, Urschler, Martin, Duong, Luc, Wasserthal, Jakob, Hoyer, Peter F., Basu, Oliver, Maal, Thomas, Witjes, Max J. H., Schiele, Gregor, Chang, Ti-chiun, Ahmadi, Seyed-Ahmad, Luo, Ping, Menze, Bjoern, Reyes, Mauricio, Deserno, Thomas M., Davatzikos, Christos, Puladi, Behrus, Fua, Pascal, Yuille, Alan L., Kleesiek, Jens, and Egger, Jan
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Databases ,Computer Science - Machine Learning ,68T01 - Abstract
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 dataset with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, facial and skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://medshapenet.ikim.nrw/ and https://github.com/Jianningli/medshapenet-feedback, Comment: 16 pages
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- 2023
93. Fair GANs through model rebalancing for extremely imbalanced class distributions
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Jain, Anubhav, Memon, Nasir, and Togelius, Julian
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Computers and Society ,Computer Science - Machine Learning - Abstract
Deep generative models require large amounts of training data. This often poses a problem as the collection of datasets can be expensive and difficult, in particular datasets that are representative of the appropriate underlying distribution (e.g. demographic). This introduces biases in datasets which are further propagated in the models. We present an approach to construct an unbiased generative adversarial network (GAN) from an existing biased GAN by rebalancing the model distribution. We do so by generating balanced data from an existing imbalanced deep generative model using an evolutionary algorithm and then using this data to train a balanced generative model. Additionally, we propose a bias mitigation loss function that minimizes the deviation of the learned class distribution from being equiprobable. We show results for the StyleGAN2 models while training on the Flickr Faces High Quality (FFHQ) dataset for racial fairness and see that the proposed approach improves on the fairness metric by almost 5 times, whilst maintaining image quality. We further validate our approach by applying it to an imbalanced CIFAR10 dataset where we show that we can obtain comparable fairness and image quality as when training on a balanced CIFAR10 dataset which is also twice as large. Lastly, we argue that the traditionally used image quality metrics such as Frechet inception distance (FID) are unsuitable for scenarios where the class distributions are imbalanced and a balanced reference set is not available.
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- 2023
94. Identity-Preserving Aging of Face Images via Latent Diffusion Models
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Banerjee, Sudipta, Mittal, Govind, Joshi, Ameya, Hegde, Chinmay, and Memon, Nasir
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Computer Science - Computer Vision and Pattern Recognition - Abstract
The performance of automated face recognition systems is inevitably impacted by the facial aging process. However, high quality datasets of individuals collected over several years are typically small in scale. In this work, we propose, train, and validate the use of latent text-to-image diffusion models for synthetically aging and de-aging face images. Our models succeed with few-shot training, and have the added benefit of being controllable via intuitive textual prompting. We observe high degrees of visual realism in the generated images while maintaining biometric fidelity measured by commonly used metrics. We evaluate our method on two benchmark datasets (CelebA and AgeDB) and observe significant reduction (~44%) in the False Non-Match Rate compared to existing state-of the-art baselines., Comment: Accepted to appear in International Joint Conference in Biometrics (IJCB) 2023
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- 2023
95. Characterizing the effect of retractions on scientific careers
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Memon, Shahan Ali, Makovi, Kinga, and AlShebli, Bedoor
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Computer Science - Social and Information Networks ,Computer Science - Computers and Society - Abstract
Retracting academic papers is a fundamental tool of quality control when the validity of papers or the integrity of authors is questioned post-publication. While retractions do not eliminate papers from the record, they have far-reaching consequences for retracted authors and their careers, serving as a visible and permanent signal of potential transgressions. Previous studies have highlighted the adverse effects of retractions on citation counts and coauthors' citations; however, the broader impacts beyond these have not been fully explored. We address this gap leveraging Retraction Watch, the most extensive data set on retractions and link it to Microsoft Academic Graph, a comprehensive data set of scientific publications and their citation networks, and Altmetric that monitors online attention to scientific output. Our investigation focuses on: 1) the likelihood of authors exiting scientific publishing following a retraction, and 2) the evolution of collaboration networks among authors who continue publishing after a retraction. Our empirical analysis reveals that retracted authors, particularly those with less experience, tend to leave scientific publishing in the aftermath of retraction, particularly if their retractions attract widespread attention. We also uncover that retracted authors who remain active in publishing maintain and establish more collaborations compared to their similar non-retracted counterparts. Nevertheless, retracted authors with less than a decade of publishing experience retain less senior, less productive and less impactful coauthors, and gain less senior coauthors post-retraction. Taken together, notwithstanding the indispensable role of retractions in upholding the integrity of the academic community, our findings shed light on the disproportionate impact that retractions impose on early-career authors., Comment: 49 pages, 13 figures, 19 tables
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- 2023
96. The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
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Moawad, Ahmed W., Janas, Anastasia, Baid, Ujjwal, Ramakrishnan, Divya, Saluja, Rachit, Ashraf, Nader, Jekel, Leon, Amiruddin, Raisa, Adewole, Maruf, Albrecht, Jake, Anazodo, Udunna, Aneja, Sanjay, Anwar, Syed Muhammad, Bergquist, Timothy, Calabrese, Evan, Chiang, Veronica, Chung, Verena, Conte, Gian Marco Marco, Dako, Farouk, Eddy, James, Ezhov, Ivan, Familiar, Ariana, Farahani, Keyvan, Iglesias, Juan Eugenio, Jiang, Zhifan, Johanson, Elaine, Kazerooni, Anahita Fathi, Kofler, Florian, Krantchev, Kiril, LaBella, Dominic, Van Leemput, Koen, Li, Hongwei Bran, Linguraru, Marius George, Link, Katherine E., Liu, Xinyang, Maleki, Nazanin, Meier, Zeke, Menze, Bjoern H, Moy, Harrison, Osenberg, Klara, Piraud, Marie, Reitman, Zachary, Shinohara, Russel Takeshi, Tahon, Nourel hoda, Nada, Ayman, Velichko, Yuri S., Wang, Chunhao, Wiestler, Benedikt, Wiggins, Walter, Shafique, Umber, Willms, Klara, Avesta, Arman, Bousabarah, Khaled, Chakrabarty, Satrajit, Gennaro, Nicolo, Holler, Wolfgang, Kaur, Manpreet, LaMontagne, Pamela, Lin, MingDe, Lost, Jan, Marcus, Daniel S., Maresca, Ryan, Merkaj, Sarah, Nada, Ayaman, Pedersen, Gabriel Cassinelli, von Reppert, Marc, Sotiras, Aristeidis, Teytelboym, Oleg, Tillmans, Niklas, Westerhoff, Malte, Youssef, Ayda, Godfrey, Devon, Floyd, Scott, Rauschecker, Andreas, Villanueva-Meyer, Javier, Pflüger, Irada, Cho, Jaeyoung, Bendszus, Martin, Brugnara, Gianluca, Cramer, Justin, Perez-Carillo, Gloria J. Guzman, Johnson, Derek R., Kam, Anthony, Kwan, Benjamin Yin Ming, Lai, Lillian, Lall, Neil U., Memon, Fatima, Patro, Satya Narayana, Petrovic, Bojan, So, Tiffany Y., Thompson, Gerard, Wu, Lei, Schrickel, E. Brooke, Bansal, Anu, Barkhof, Frederik, Besada, Cristina, Chu, Sammy, Druzgal, Jason, Dusoi, Alexandru, Farage, Luciano, Feltrin, Fabricio, Fong, Amy, Fung, Steve H., Gray, R. Ian, Ikuta, Ichiro, Iv, Michael, Postma, Alida A., Mahajan, Amit, Joyner, David, Krumpelman, Chase, Letourneau-Guillon, Laurent, Lincoln, Christie M., Maros, Mate E., Miller, Elka, Morón, Fanny, Nimchinsky, Esther A., Ozsarlak, Ozkan, Patel, Uresh, Rohatgi, Saurabh, Saha, Atin, Sayah, Anousheh, Schwartz, Eric D., Shih, Robert, Shiroishi, Mark S., Small, Juan E., Tanwar, Manoj, Valerie, Jewels, Weinberg, Brent D., White, Matthew L., Young, Robert, Zohrabian, Vahe M., Azizova, Aynur, Brüßeler, Melanie Maria Theresa, Fehringer, Pascal, Ghonim, Mohanad, Ghonim, Mohamed, Gkampenis, Athanasios, Okar, Abdullah, Pasquini, Luca, Sharifi, Yasaman, Singh, Gagandeep, Sollmann, Nico, Soumala, Theodora, Taherzadeh, Mahsa, Yordanov, Nikolay, Vollmuth, Philipp, Foltyn-Dumitru, Martha, Malhotra, Ajay, Abayazeed, Aly H., Dellepiane, Francesco, Lohmann, Philipp, Pérez-García, Víctor M., Elhalawani, Hesham, Al-Rubaiey, Sanaria, Armindo, Rui Duarte, Ashraf, Kholod, Asla, Moamen M., Badawy, Mohamed, Bisschop, Jeroen, Lomer, Nima Broomand, Bukatz, Jan, Chen, Jim, Cimflova, Petra, Corr, Felix, Crawley, Alexis, Deptula, Lisa, Elakhdar, Tasneem, Shawali, Islam H., Faghani, Shahriar, Frick, Alexandra, Gulati, Vaibhav, Haider, Muhammad Ammar, Hierro, Fátima, Dahl, Rasmus Holmboe, Jacobs, Sarah Maria, Hsieh, Kuang-chun Jim, Kandemirli, Sedat G., Kersting, Katharina, Kida, Laura, Kollia, Sofia, Koukoulithras, Ioannis, Li, Xiao, Abouelatta, Ahmed, Mansour, Aya, Maria-Zamfirescu, Ruxandra-Catrinel, Marsiglia, Marcela, Mateo-Camacho, Yohana Sarahi, McArthur, Mark, McDonnell, Olivia, McHugh, Maire, Moassefi, Mana, Morsi, Samah Mostafa, Muntenu, Alexander, Nandolia, Khanak K., Naqvi, Syed Raza, Nikanpour, Yalda, Alnoury, Mostafa, Nouh, Abdullah Mohamed Aly, Pappafava, Francesca, Patel, Markand D., Petrucci, Samantha, Rawie, Eric, Raymond, Scott, Roohani, Borna, Sabouhi, Sadeq, Sanchez-Garcia, Laura M., Shaked, Zoe, Suthar, Pokhraj P., Altes, Talissa, Isufi, Edvin, Dhermesh, Yaseen, Gass, Jaime, Thacker, Jonathan, Tarabishy, Abdul Rahman, Turner, Benjamin, Vacca, Sebastiano, Vilanilam, George K., Warren, Daniel, Weiss, David, Worede, Fikadu, Yousry, Sara, Lerebo, Wondwossen, Aristizabal, Alejandro, Karargyris, Alexandros, Kassem, Hasan, Pati, Sarthak, Sheller, Micah, Bakas, Spyridon, Rudie, Jeffrey D., and Aboian, Mariam
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Quantitative Biology - Other Quantitative Biology ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space.The BraTS-METS 2023 challenge successfully curated well-annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied clinical environments and providing personalized volumetric reports to patients undergoing BM treatment.
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- 2023
97. Comparative Analysis of Pre-trained based CNN-RNN Deep Learning Models on Anomaly-5 Dataset for Action Recognition
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Fayaz Ahmed Memon, Umair Ali Khan, Pardeep Kumar, Imtiaz Ali Halepoto, and Farida Memon
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Computer engineering. Computer hardware ,TK7885-7895 ,Mathematics ,QA1-939 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Action recognition in videos is one of the essential, challenging and active area of research in the field of computer vision that adopted in various applications including automated surveillance systems, security systems and human computer interaction. In this paper, we present an in-depth comparative analysis of five CNN-RNN models based on pre-trained networks such as InceptionV3, VGG16, MobileNetV2, ResNet152V2 and InceptionResNetV2 with recurrent LSTM units for action recognition on Anomaly-5 dataset. The performance of these models is analyzed and compared in terms of accuracy, precision, recall & F1-scores and computational efficiency. The CNN-RNN architectures we considered for analysis in this paper, the ResNet152V2 based CNN-RNN model exhibits better performance and achieved highest accuracy, precision, recall and F1-score equal to 92.20% due to its ability to capture more complex spatial features. This comparative analysis may guide the researchers in selecting appropriate models for real-world applications for action recognition. In addition of this, a new dataset is developed called Anomaly-5 that can helps as a valuable resource for training and evaluating action recognition algorithms.
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- 2024
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98. Risk Factors of Crimean-Congo Haemorrhagic Fever in Sindh Province, Pakistan
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Muhammad Asif Syed, Muhammad Ilyas Siddiqui, Ishfaque Hussain Memon, Kishwar Jehandad, Nayyar Nawaz Baloch, Hamza Jamal, Aamir Hussain, Naveed Masood Memon, Masroor Hussain Syed, Zeeshan Ansar Ahmed, Robert E. Fontaine, and Paola Rullán-Oliver
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Crimean-Congo haemorrhagic fever ,Risk factors ,Public health surveillance ,Occupational exposure ,Livestock ,Urban population ,Infectious and parasitic diseases ,RC109-216 - Abstract
Objectives: In Sindh Province, Pakistan, confirmed Crimean-Congo haemorrhagic fever (CCHF) increased from zero in 2008 to 16 in 2015-2016. To counter this increase, in 2016, we initiated structured CCHF surveillance to improve estimates of risk factors for CCHF in Sindh and to identify potential interventions. Methods: Beginning in 2016, all referral hospitals in Sindh reported all CCHF cases to surveillance agents. We used laboratory-confirmed cases from CCHF surveillance from 2016 to 2020 to compute incidence rates and in a case–control study to quantify risk factors for CCHF. Results: For the 5 years, CCHF incidence was 4.2 per million for the Sindh capital, Karachi, (68 cases) and 0.4 per million elsewhere. Each year, the onset of new cases peaked during the 13 days during and after the 3-day Eid-al-Adha festival, when Muslims sacrificed livestock, accounting for 38% of cases. In Karachi, livestock for Eid were purchased at a seasonal livestock market that concentrated up to 700,000 livestock. CCHF cases were most common (44%) among the general population that had visited livestock markets (odds ratio = 102). Conclusions: Urban CCHF in Sindh province is associated with the general public's exposure to livestock markets in addition to high-risk occupations.
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- 2024
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99. Biochar-Based Catalyst for Degradation of Organic Pollutants
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Memon, Saima Q., Khan, Sidra, Yurekli, Yilmaz, Memon, Najma, Hussain, Fayyaz Salih, Akitsu, Takashiro, Jawaid, Mohammad, Series Editor, Khan, Anish, Series Editor, Bhawani, Showkat Ahmad, editor, Umar, Khalid, editor, Mohamad Ibrahim, Mohamad Nasir, editor, and Alotaibi, Khalid M., editor
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- 2024
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100. Sustainability and Manufacturing Practices in China: A Global Perspective
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Memon, Hafeezullah, Chen, Lihong, Yan, Xinfeng, Mokanaasri, E, Sadhna, Memon, Hafeezullah, Series Editor, Sadhna, editor, Kumar, Rajesh, editor, and Greeshma, S., editor
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- 2024
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