From immune evasion to broad in silico binding: computational optimization of SARS-CoV-2 RBD-targeting nanobody by Shuyuan Cao, Bo Sun, Feng Gao, Feng Gao, Feng Gao

“…By enhancing nanobody efficacy, our method provides a viable framework for developing targeted countermeasures against evolving SARS-CoV-2 variants and other pathogens.…”
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Building for the mind a neuro-architectural approach of spatial experience for sustainable mental health and wellbeing by Alaa Akmal Elghor, Zeinab Shafik, Atef Abdel-Moneim Ali, Mennat-Allah Elhusseiny

“…<strong></strong></p><p><strong>Practical implications</strong></p><p>         This research sheds light on the multidisciplinary approach of architecture and urban design. The science-based method adopted clarifies that architects and urban designers can seek evidence using scientific tools and including scientific approaches in design decisions. …”
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Indirect sliding mode adaptive fractional order nonlinear observer based controller with fractional order single-ended primary inductor converter by Sena Alemu Wondimu, Desalegn Tsega Dagne, Kinde Anlay Fante

“…The Mittag-Leffler function, along with Lyapunov methods, are used to analyze the system’s dynamic stability. …”
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Multi-environmental evaluation of barley core collection against spot blotch for genetic variability and identification of promising genotypes exhibiting resistance by Shiv Shankar Patel, Shyam Saran Vaish, Sherry Rachel Jacob, Gyanendra Pratap Singh, Vikender Kaur

“…Host resistance presents a sustainable, cost-effective, and eco-friendly method for disease management. The extent of resistance and the number of resistant accessions are limited within barley genetic resources. …”
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Statistical - Synoptic Analysis of the Extreme Precipitation in Western Iran by Mehrdad Kiani, Hasan Lashkari, Houshang Ghaemi

“…This climate parameter in mountainous areas such as Zagros in western Iran has wide variations.­ Diversity of topography is one of the factors leading to these changes. …”
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Enhanced FCS-MPC for DFIG Under Non-Ideal Grid Conditions by Yuri O. YuriCota, Jefferson S. Costa, Angelo Lunardi, Igor Oliani, Ekom E. Okpo, Alfeu J. Sguarezi Filho

“…Experimental tests on a 3 kW/220 V DFIG bench setup demonstrated that the proposed enhancements deliver superior performance to conventional MPC-FCS, SRF-PLL, Deadbeat, and classical PI controllers. The proposed method, integrated with DDSRF-PLL, exhibited superior performance compared to the other strategies, standing out in waveform quality and dynamic response. …”
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Features of Changes of Main Indices in Acne Patients Systemic Immunity and Their Dependence on Clinical Forms of Dermatosis Course by Syzon O., Dashko M.

“…Hence, the establishment of the nature of changes in individual indicators of systemic immunity in acne patients as well as their dependence on the clinical variations of common acne forms is a topical task of modern dermatology since this will allow to clarify their basic pathogenetic mechanisms and develop differentiated treatment methods. …”
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Life’s Essential 8 cardiovascular health, cardiovascular-kidney-metabolic syndrome stages, and incident cardiovascular events: a nationwide 10-year prospective cohort study in Chin... by Mian Li, Min Xu, Yi Ding, Hong Lin, Guijun Qin, Tiange Wang, Yu Xu, Yuhong Chen, Shuangyuan Wang, Zhiyun Zhao, Jie Zheng, Li Yan, Lixin Shi, Zhengnan Gao, Lulu Chen, Tianshu Zeng, Ruying Hu, Zhen Ye, Xuefeng Yu, Gang Chen, Qing Su, Yiming Mu, Xulei Tang, Qin Wan, Guixia Wang, Feixia Shen, Xuejiang Gu, Zuojie Luo, Yingfen Qin, Li Chen, Xinguo Hou, Yanan Huo, Qiang Li, Hong Qiao, Yinfei Zhang, Chao Liu, Youmin Wang, Shengli Wu, Tao Yang, Huacong Deng, Jiajun Zhao, Guang Ning, Jieli Lu, Weiqing Wang, Yufang Bi

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Calculation of COVID-19 disease burden using Monte Carlo simulation with dynamic disability weights and analysis of transmission characteristics by Wenxiu Chen, Wei An, Qun Gao, Ji Bai, Hua Li, Song Tang, Wenhui Gao, Zhe Tian, Yu Zhang, Min Yang

“…These distributions were integrated into Monte Carlo simulations to model real-time disease burden, offering robust data to support evidence-based policy decisions and optimize resource allocation. …”
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Gut microbiota influence on lung cancer risk through blood metabolite mediation: from a comprehensive Mendelian randomization analysis and genetic analysis by Yizhao Du, Qin Wang, Zongmei Zheng, Hailun Zhou, Yang Han, Ao Qi, Lijing Jiao, Lijing Jiao, Yabin Gong

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Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference by Fateme Fotouhi, Fateme Fotouhi, Kevin Menke, Aaron Prestholt, Ashish Gupta, Matthew E. Carroll, Hsin-Jung Yang, Edwin J. Skidmore, Matthew O’Neal, Nirav Merchant, Sajal K. Das, Peter Kyveryga, Baskar Ganapathysubramanian, Baskar Ganapathysubramanian, Asheesh K. Singh, Arti Singh, Soumik Sarkar, Soumik Sarkar

“…However, this task is fraught with complexities, encompassing challenges such as, laborious dataset annotation, recognizing small insect-pests in low-resolution or distant images, and the intricate variations across insect-pests life stages and species classes.MethodsTo tackle these obstacles, this work investigates combining two solutions, Hierarchical Transfer Learning (HTL) and Slicing-Aided Hyper Inference (SAHI), along with applying a detection model. …”
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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…Using long short-term memory (LSTM) neural networks as predictive models, the results yield coefficient of determination (R2) values of 0.81 and 0.96, root mean square error (RMSE) values of 5.91 mm/min and 3.09 mm, and average bias factor values of 0.99 and 0.88 for the P and S predictive models, respectively, based on validation datasets. This integrated framework, which combines the non-dominated sorting genetic algorithm (NSGA-II) with LSTM neural networks, is applied to MOO to identify the optimal SOPs, while accounting for their influence on S variation as a time-series over 11 timesteps, as considered in this study. …”
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Impact of stratiform liquid water clouds on vegetation albedo quantified by coupling an atmosphere and a vegetation radiative transfer model by K. Wolf, E. Jäkel, A. Ehrlich, M. Schäfer, H. Feilhauer, H. Feilhauer, H. Feilhauer, A. Huth, A. Huth, A. Huth, A. Weigelt, M. Wendisch

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Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…The Random forest-based Boruta method was used to examine the importance of multiple factors contributing to the prediction’s accuracy. …”
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Optimal Protection Coordination for Grid-Connected and Islanded Microgrids Assisted by the Crow Search Algorithm: Application of Dual-Setting Overcurrent Relays and Fault Current L... by Hossien Shad, Hamid Amini Khanavandi, Saeed Abrisham Foroushan Asl, Ali Aranizadeh, Behrooz Vahidi, Mirpouya Mirmozaffari

“…This paper introduces a two-stage protection coordination framework designed for grid-connected and islanded microgrids (MGs) that integrate distributed generations (DGs) and energy storage systems (ESSs). …”
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Core outcomes for the evaluation of new healthcare programmes – a modified Delphi study by Benjamin P. Harvey, Emmelie Barenfeld, Joakim Öhlén, Jana Bergholtz, Carl Johan Orre, Tomas Lindroth, Hanna Gyllensten

“…The outcomes underwent a two-round modified Delphi method with representative groups including managerial decision-makers, researchers, health workers, and patients/patient representatives. …”
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Multilevel determinants of physical activity in children and adolescents: a meta-analysis guided by social ecological model by Chun Zhao, Jing Yuan, Wen Wen Huang

“…Meta-analysis confirmed multilevel SEM influences (SMD = 0.443,95%CI [0.784,0.885]), Due to variations in statistical methods (I 2  = 45.9–99.8%), survey setting scope (I 2  = 0–99.6%), geography (I 2  = 0.86–99.7%), and Research design (I 2  = 67.5–99.8%), there was a considerable degree of heterogeneity among the included studies. …”
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Global transcriptome modulation by xenobiotics: the role of alternative splicing in adaptive responses to chemical exposures by Andrew J. Annalora, Jacki L. Coburn, Antony Jozic, Patrick L. Iversen, Craig B. Marcus

“…C6-MDB reduced this ratio to ~ 50% by PCR and ~ 39% by RNA-seq, showing slight method-dependent variations yet consistent trends. …”
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Construction of an evaluation indicator system for the emergency management capability of major infectious diseases in urban communities by Xiuying Guan, Wentao Li, Nan Cui, Jiacen Yu, Libin An

“…The modified Delphi method was applied to refine the third-level indicators for the evaluation system. …”
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Urban malaria and population mobility in sub-Saharan Africa: systematic review and meta-analysis by Hailu Merga, Teshome Degefa, Zewdie Birhanu, Ming-Chieh Lee, Guiyun Yan, Delenasaw Yewhalaw

“…While country-level differences contributed to this variability, other important sources of heterogeneity included variations in population included, method employed and population characteristics. …”
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