The Immunophenotyping Changes of Peripheral CD4+ T Lymphocytes and Inflammatory Markers of Class III Obesity Subjects After Laparoscopic Gastric Sleeve Surgery – A Follow-Up Study... by Nasser M Rizk (18810328)

“…</p><h3>Results </h3><p dir="ltr">The means (SD) of age and BMI of class III obesity subjects was 32.32 (8.36) years and 49.02 (6.28) kg/m², respectively. LGS caused a significant reduction in BMI by 32%, p< 0.0001. LGS intervention significantly decreased CD4+ T-lymphocytes and effector memory (TEM) cells but increased T-regulatory (Treg), naïve, and central memory (TCM) cells, with all p values < 0.05. …”

The Effect of Treated Waste-Water on Compaction and Compression of Fine Soil by Attom, Mousa

“…The significant effect was observed in swell index and swelling pressure of the soils. …”
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Measuring Sustainability in Design for Hospitality by Zimmer, Teresa Marie

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Modeling electricity consumption patterns during the COVID-19 pandemic across six socioeconomic sectors in the State of Qatar by Ammar, Abulibdeh

“…The propagation of the COVID-19 pandemic, and the associated measures taken by many countries to slow down the spread of the disease, has significantly affected all aspects of people's lives, including the global energy sector. …”
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Modeling electricity consumption patterns during the COVID-19 pandemic across six socioeconomic sectors in the State of Qatar by Ammar Abulibdeh (15785928)

“…<p dir="ltr">The propagation of the COVID-19 pandemic, and the associated measures taken by many countries to slow down the spread of the disease, has significantly affected all aspects of people's lives, including the global energy sector. …”

Past, present and future global mangrove primary productivity by Mark Chatting (5728340)

“…However, significant regional changes were identified, including substantial increases in NPP in the Southwest Australian Shelf (60.58 ± 97.9 %), the Warm Temperate Northeast Pacific (43.75 ± 65.7 %), and the Warm Temperate Northwest Pacific (31.55 ± 55.7 %), as well as decreases in <u>Southeast Asian </u>provinces like the Java Transitional (11.45 ± 6.2 %) and Western Coral Triangle (7.61 ± 9.6 %). …”

Investigation of Groundwater Depletion in the State of Qatar and Its Implication to Energy Water and Food Nexus by Hazrat Bilal (7367477)

“…Long-term temperature data indicates that the annual mean temperature increased significantly by 1.02 °C between 1987 and 2016, while total rainfall exhibited a slight decreasing trend. …”

Hydrogen energy systems: Technologies, trends, and future prospects by Abdellatif M. Sadeq (16931841)

“…Adoption at scale could decrease global <i>CO</i>_<em>2</em>emissions by up to 830 million tonnes annually. …”

A Multidecadal Assessment of Haze Development and Fluctuations in Visibility for Arabian Peninsula by Luqman Atique (16036586)

Multi-IsnadSet MIS for Sahih Muslim Hadith with chain of narrators, based on multiple ISNAD by Aziz Mehmood Farooqi (20748788)

MCDFN: supply chain demand forecasting via an explainable multi-channel data fusion network model by Md Abrar Jahin (20108252)

“…MCDFN utilizes Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), and Gated Recurrent Units (GRUs) to extract spatial and temporal features from time series data. Comparative benchmarking against seven other deep-learning models validates MCDFN’s efficacy, showing it outperforms its counterparts across key metrics with a mean squared error (MSE) of 23.5738, root mean squared error (RMSE) of 4.8553, mean absolute error (MAE) of 3.9991, and mean absolute percentage error (MAPE) of 20.1575%. …”

PredictPTB: an interpretable preterm birth prediction model using attention-based recurrent neural networks by Rawan AlSaad (14159019)

“…<h3>Background</h3><p dir="ltr">Early identification of pregnant women at risk for preterm birth (PTB), a major cause of infant mortality and morbidity, has a significant potential to improve prenatal care. However, we lack effective predictive models which can accurately forecast PTB and complement these predictions with appropriate interpretations for clinicians. …”

Hyperspectral-physiological based predictive model for transpiration in greenhouses under CO₂ enrichment by Ikhlas Ghiat (16932564)

“…These predictive models assimilate microclimate, physiological and hyperspectral features with high temporal and spatial resolutions. …”

A Diffusion-Based Probabilistic Ultra-Short-Term Solar Power Prediction Using the Sky Image Sequences by Razieh Rastgoo (22457767)

“…Central to this framework is the Cross Branch Visual Informer (CB-ViInf), the first model to integrate multi-resolution patches into the Vision Informer architecture, improving feature extraction and temporal modeling for solar forecasting. …”

Assessment of High-resolution Local Emissions and Land-use in Air Quality Forecasting at an Urban, Coastal, Desert Environment by Christos Fountoukis (4722963)

Characterizing the dynamics of climate and native desert plants in Qatar by Meshal Abdullah (17746950)

“…<p>This study aims to measure changes in climatic factors and their relationship to vegetation growth in Qatar to develop a plant-climate characterization for native desert plants. …”

Characteristics of aerosols and planetary boundary layer dynamics during biomass burning season by Muhammad Zeeshaan Shahid (18131689)

Effects of ethanol addition to diesel–biodiesel blends on the CI engine characteristics by Fakher Hamdi (21225134)

Crystallization properties of arsenic doped GST alloys by Vinod E. Madhavan (8136774)

“…Optical band gap (E_opt) values of the as-deposited films show a clear increasing trend; 0.6 eV for GST to 0.76 eV for (GST)_0.85As_0.15. The decreases in E_opt for the samples annealed at higher temperatures shows significant optical contrast between the as-deposited and annealed samples. …”

Binary-NeRV: Hybrid-Precision Weights Binarization for Efficient Neural Video Representation by Shanableh, Tamer

“…In this work, we propose Binary-NeRV, a hybrid-precision extension of NeRV that integrates XNOR-based binary convolutions into the decoding pipeline to significantly reduce model size, bitrate, and computational complexity while reasonably preserving reconstruction fidelity. …”
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