Multitask Learning-Based Pipeline-Parallel Computation Offloading Architecture for Deep Face Analysis by Faris S. Alghareb, Balqees Talal Hasan

“…To train the proposed deep face analysis network architecture, two custom datasets (HDDB and FRAED) were created for head detection and face-age recognition. …”
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Impact of different car-following models on estimating safety and emissions on signal-controlled intersections using microscopic simulations by Konrad Biszko, Jacek Oskarbski, Karol Żarski

“…The proposed method aims to evaluate the precision of the microscopic model in replicating real road networks and traffic based on available datasets. Two car-following models (CFM), Wiedemann 74 (W74), and Wiedemann 99 (W99) are chosen for further analysis. …”
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Caregivers’ experiences of being asked about adverse childhood experiences and receiving support from an integrated health and social care hub: a qualitative study by Ashraful Kabir, Harriet Hiscock, Hueiming Liu, Lingling Chen, Rebecca Bosward, Natalie White, Sarah Loveday, Wilhelmina Ebbett

“…NVivo (V.12) was used to organise, index and retrieve data.Settings This study was conducted in two Child and Family Hubs (CFHs) in Australia—IPC Health, Wyndham Vale, Melbourne, and Marrickville Health Centre, Sydney, between May and October 2023.Participants Participants (n=29) were the caregivers of children living with adverse childhood experiences (ACEs).Results Four themes were identified which reflected the caregivers’ experiences of being asked about adversities and how they linked to the support and services both in the CFHs and outside the CFH. …”
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Leveraging machine learning for enhanced reservoir permeability estimation in geothermal hotspots: a case study of the Williston Basin by Abdul-Muaizz Koray, Emmanuel Gyimah, Mohamed Metwally, Hamid Rahnema, Olusegun Tomomewo

“…Overall, the SVM and GPR regression methods were observed to show consistent results with the training and testing datasets, with the SVM regression technique yielding higher R-squared values through regression across the different clustering techniques. …”
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An Approach to Refining MODIS LAI Data Using a Fitting Scale Factor Time Series by Junxian Tang, Peijuan Wang, Rui Feng, Yang Li, Qing Li

“…Although the remote sensing LAI data provide a critical foundation for monitoring crop growth and estimating yields, the existing datasets often exhibit notable errors due to the pixel-level heterogeneity. …”
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Exploring the predictive power of antinuclear antibodies and Rheumatoid factor correlations in anticipating therapeutic outcomes for female patients with coexisting Sjögren's syndr... by Anitha Krishnan Pandarathodiyil, Hema Shree K, Pratibha Ramani, B. Sivapathasundharam, Ramya Ramadoss

“…These findings suggest that machine learning models could enhance personalized treatment strategies for patients with SS and RA, but additional validation with larger datasets is required.…”
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Precise and interpretable neural networks reveal epigenetic signatures of aging across youth in health and disease by David Martínez-Enguita, Thomas Hillerton, Julia Åkesson, Daniel Kling, Maria Lerm, Mika Gustafsson

“…We showcased the practical applicability of this approach by identifying candidate mechanisms underlying the altered pace of aging observed in pediatric Crohn’s disease.DiscussionIn this study, we present a deep neural network epigenetic clock, named NCAE-CombClock, that improves age prediction accuracy in large datasets, and a suite of explainable neural network clocks for robust age classification across youth. …”
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A comparative analysis of sequence composition in different lots of a phage display peptide library during amplification by Anders Wilgaard Sinkjaer, Ane Beth Sloth, Amanda Oester Andersen, Malte Jensen, Babak Bakhshinejad, Andreas Kjaer

“…DNA from the samples was subjected to Next-Generation Sequencing (NGS) using an Illumina platform. The NGS datasets underwent a variety of bioinformatic analyses using Python and MATLAB scripts. …”
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Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders by Muhammad Sajid, Kaleem Razzaq Malik, Ateeq Ur Rehman, Tauqeer Safdar Malik, Masoud Alajmi, Ali Haider Khan, Amir Haider, Seada Hussen

“…On the other hand, the low availability of 3D datasets significantly impedes learning high-quality 3D features because of the high data processing cost. …”
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Seasonal and Regional Variability of Long-Wave Effective Radiation in China and Associated Modulating Factors by Qianrong Ma, Jie Zhang, Yu Gu, Yujun Ma, Yu Cao

“…Variations in all-sky and clear-sky long-wave effective radiation (LER) in China during the period 2001–2016 were determined using monthly radiative datasets from the Clouds and the Earth’s Radiant Energy System (CERES). …”
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FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution by Hefei Wang, Ruichun Gu, Jingyu Wang, Xiaolin Zhang, Hui Wei

“…The FedBFGCN was evaluated on standard reference network datasets (Cora, Citeseer, Polblogs), and experimental results showed that it has lower losses and higher performance in multiple aspects. …”
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Progressive Self-Prompting Segment Anything Model for Salient Object Detection in Optical Remote Sensing Images by Xiaoning Zhang, Yi Yu, Daqun Li, Yuqing Wang

“…Extensive experiments on three benchmark ORSI-SOD datasets demonstrate that our proposed network achieves state-of-the-art performance.…”
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Payment Reforms for Prehospital Care Services in a Middle Income Country: Assessing Implementation and Patient Outcomes Using a Mixed-Methods Approach by Paibul Suriyawongpaisal, Samrit Srithamrongsawad, Pongsakorn Atiksawedparit, Khanisthar Phooseemungkun, Krongkan Bunchaiyai, Thanita Thongtan

“…Using a mixed-methods approach, retrospective datasets of 3,769,399 individual records of call responses from 2015 to 2017 were analyzed which compared EMS units with the direct-pay system against those without in terms of time flow of claim data and patient outcomes. …”
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Changes in incidence and epidemiology of antimicrobial resistant pathogens before and during the COVID-19 pandemic in Germany, 2015–2022 by Jonathan H. J. Baum, Achim Dörre, Felix Reichert, Ines Noll, Marcel Feig, Tim Eckmanns, Mirco Sandfort, Sebastian Haller

“…Methods We used two independent datasets, statutory surveillance and laboratory-based Antibiotic Resistance Surveillance (ARS). …”
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Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review by Md Mohshin Ali, Md. Arif Hossen, Azrina Abd Aziz

“…These models can handle extensive experimental datasets, optimize operational parameters, and provide insights into CO2 reduction (CO2R) mechanisms. …”
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Influence of type traits on stayability in the Ital- ian Mediterranean buffalo by Damiano Altieri, Stefano Biffani, Mayra Gómez, Yuri Gombia, Dario Rossi, Luca Gubitosi, Nadia Piscopo, Francesca Carnovale, Rossella Di Palo

“…Data from 276.415 buffalo cows registered in the ANASB studbook starting from 1989 were extracted and merged with the official milk test-day recording datasets from the Italian Breeder’s Association (AIA). …”
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Iron and folic acid supplementation compliance during pregnancy and its effect on post-pregnancy anaemia among reproductive-age women in East Africa by Melaku Tadege Engidaw, Patricia Lee, Faruk Ahmed

“…Methods: This study used data from 43,200 reproductive-age women from 2015 to 2022 demographic and health survey datasets. We used multilevel mixed-effect logistic regression analysis to identify associated factors with IFA supplementation compliance during pregnancy. …”
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Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein A. M. Hussein, Sharafiz B. Abdul Rahim, Faizal B. Mustapha, Prajindra S. Krishnan, Nawal Aswan B. Abdul Jalil

“…The proposed methodology demonstrated exceptional performance, with the ANN model achieving consistently high overall accuracy (above 99.7%) and remarkably low mean squared error (in the range of 0.0088 × 10−3 to 0.3062 × 10−3) across multiple iterations and sensor datasets. The detailed class-specific metrics, including accuracy, precision, sensitivity, and F1-score, further substantiated the model’s effectiveness in identifying the individual fault types with near-perfect or perfect results for the majority of the fault scenarios. …”
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Challenges and opportunities for assessing trends of amphibians with heterogeneous data – a call for better metadata reporting by Klaus Henle, Reinhard A. Klenke, M. Benjamin Barth, Annegret Grimm-Seyfarth, Diana E. Bowler

“…Instead, there are many heterogeneous datasets that contain observations of amphibians from professional surveys as well as diverse citizen science and other voluntary surveys. …”
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Correction of CAMS PM₁₀ Reanalysis Improves AI-Based Dust Event Forecast by Ron Sarafian, Sagi Nathan, Dori Nissenbaum, Salman Khan, Yinon Rudich

“…The Copernicus Atmosphere Monitoring Service (CAMS) offers global reanalysis datasets and forecasts of particulate matter with a diameter of under 10 μm (PM₁₀), which approximate dust, but recent studies highlight discrepancies between CAMS data and ground <i>in-situ</i> measurements. …”
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