Deep Learning-Based MRI Brain Tumor Segmentation With EfficientNet-Enhanced UNet by Pradeep Kumar Tiwary, Prashant Johri, Alok Katiyar, Mayur Kumar Chhipa

“…Precisely delineating brain tumor areas from multimodal MRI scans is crucial for clinical diagnosis and predicting patient outcomes. However, challenges arise from similar intensity patterns, varying tumor shapes, and indistinct boundaries, which complicate brain tumor segmentation. …”
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Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning by In-Seop Na, Vani Rajasekar, Velliangiri Sarveshwaran

“…A key innovation is the use of digital twin technology, which dynamically integrates real-time data from IoT sensors and simulation models to predict fire disaster scenarios accurately. …”
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Estimating corn leaf chlorophyll content using airborne multispectral imagery and machine learning by Fengkai Tian, Jianfeng Zhou, Curtis J. Ransom, Noel Aloysius, Kenneth A. Sudduth

“…A UAV-based multispectral camera collected imagery at the same time as manual readings. Machine learning models developed based on image features derived from UAV images were used to predict leaf chlorophyll content. …”
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Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States by Meredith M. Brehob, Michael J. Pennino, Amalia M. Handler, Jana E. Compton, Sylvia S. Lee, Robert D. Sabo

“…We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐a for ∼112,000 lakes across the CONUS. …”
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Generative Design-Driven Optimization for Effective Concrete Structural Systems by Hossam Wefki, Mona Salah, Emad Elbeltagi, Majed Alinizzi

“…The model automates and optimizes the layout process, yielding measurable improvements in spatial efficiency while maintaining compliance with structural performance criteria. …”
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Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…This novel approach represents a step forward in hydrological applications, potentially improving the way we predict and manage water-related events by increasing the accuracy and reliability of precipitation data analysis.…”
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Incorporating long-term numerical weather forecasts to quantify dynamic vulnerability of irrigation supply system: A case study of Shihmen Reservoir in Taiwan by Chia-Chuan Hsu, Yu-Pin Lin

“…The simulation of historical conditions shows successful predictions of 6 out of 7 historical drought-induced irrigation stoppages during 2000–2021. …”
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Basin-wide and coastal modes of north tropical Atlantic variability have distinct impacts on hurricanes by Yi Liu, Michael J. McPhaden, Wenju Cai, Yu Zhang, Jiuwei Zhao, Hyacinth C. Nnamchi, Xiaopei Lin, Ziguang Li, Jun-Chao Yang

“…Here we use observations and model outputs over the past several decades to determine whether there exists inherent diversity in north tropical Atlantic surface temperature spatial structures and impacts. …”
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Boundary-Aware Transformer for Optic Cup and Disc Segmentation in Fundus Images by Soohyun Wang, Byoungkug Kim, Doo-Seop Eom

“…Furthermore, the proposed model more accurately captures the relative size and spatial alignment of the OD and OC and produces smooth and consistent boundary predictions in clinically significant regions such as the region of interest (ROI). …”
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A method to quantify jump dispersal of invasive species from occurrence data: the case of the spotted lanternfly, Lycorma delicatula by Nadège Belouard, Sebastiano De Bona, Matthew R. Helmus, Isabella G. Smith, Jocelyn E. Behm

“…The accuracy of predicting the spread of biological invasions is improved if models explicitly incorporate the two main dispersal mechanisms: diffusive spread and jump dispersal. …”
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Role of Cairns–Gurevich ion distribution on nonlinear wave propagation in negatively charged dusty plasma by N.S. Alharthi

“…The results demonstrated that soliton waves, explosive waves, and kink waves exhibit distinct behaviors depending on these parameters and the spatial context of Earth's magnetosphere. These findings provide new insights compared to previous studies into the conditions under which these waveforms emerge and evolve, especially in magnetized environments where earlier models were less effective at accurately characterizing or predicting wave behavior. …”
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Micro, Small or Medium, New or Old—Are There Differences? Testing Business-Specific Difficulties by Mihaela Brîndușa Tudose, Savin Dorin Ionesi, Ionuț Dulgheriu, Liliana Buhu, Valentina Diana Rusu

“…To formulate general conclusions or predictions, in economic research, large databases are often used, related to more or less homogeneous samples, without taking into account the spatial or structural differences of the analysed processes or phenomena. …”
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Joint Inversion of InSAR and GNSS for surface subsidence and terrestrial water storage anomalies of small-area in west-central Yunnan Province, China by Ming Shangguan, Jingyi Guo, Shuguang Wu, Xu Zhou, Rong Zou, Xin Zhang

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Land Use and Climate Change Accelerate the Loss of Habitat and Ecological Corridor to Reeves's Pheasant (Syrmaticus reevesii) in China by Qingqing He, Shan Tian, Junqin Hua, Zhengxiao Liu, Yating Liu, Ting Jin, Jiliang Xu

“…However, determining the causal factors of their extinction and carrying out protection measures appear to be challenging owing to a lack of long‐term data with high spatial and temporal resolutions. Here, based on a national field survey, we used habitat suitability models and integrated data on geographical environment, road development, land use, and climate change to predict the potential changes in the distribution and connectivity of the habitat of Reeves's pheasant from 1995 to 2050. …”
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Unsupervised semantic label generation in agricultural fields by Gianmarco Roggiolani, Julius Rückin, Marija Popović, Jens Behley, Cyrill Stachniss, Cyrill Stachniss

“…Using our generated labels to train deep learning models boosts our prediction performance on previously unseen fields with respect to unseen crop species, growth stages, or different lighting conditions. …”
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A long neglected world malaria map: Plasmodium vivax endemicity in 2010. by Peter W Gething, Iqbal R F Elyazar, Catherine L Moyes, David L Smith, Katherine E Battle, Carlos A Guerra, Anand P Patil, Andrew J Tatem, Rosalind E Howes, Monica F Myers, Dylan B George, Peter Horby, Heiman F L Wertheim, Ric N Price, Ivo Müeller, J Kevin Baird, Simon I Hay

“…The model incorporated data on Duffy negative phenotype frequency to suppress endemicity predictions, particularly in Africa. …”
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Multi-objective Optimization of Window and Shading Systems for Enhanced Office Building Performance: A Case Study in Qom, Iran by Mohammad Hassan Abedini, Hanieh Gholami, Hamed Sangin

“…Conducted in the hot desert climate of Qom, the research employs advanced simulation tools, including Rhino 8 integrated with Grasshopper, Honeybee, and Ladybug, to model and evaluate shading strategies. A multi-objective optimization (MOO) approach was applied to enhance four key metrics: Thermal Comfort Percent (TCP), Energy Use Intensity (EUI), Annual Sunlight Exposure (ASE), and Spatial Daylight Autonomy (sDA). …”
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Driving towards net-zero: the impact of electric vehicle flexibility participation on a future Norwegian electricity system by Tobias Verheugen Hvidsten, Maximilian Roithner, Fred Espen Benth, Marianne Zeyringer

“…This work presents a modelling study of the Norwegian electricity system using the high spatial and temporal resolution electricity system model (highRES). …”
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Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles by Pengcheng Ma, Shuai Zhang, Bin Zhou, Wenqi Shao, Haowen Li, Tengfei Ma, Dong Guo

“…The article proposes a vehicle power exchange demand-oriented power exchange station siting planning scheme to meet the rapid replenishment demand of operating vehicles in urban areas. The spatial and temporal distribution of power exchange demand is predicted by considering the operation law, driving law, and charging decision of drivers; the candidate sites of power exchange stations are determined based on the data of power exchange demand; the optimization model of the site selection of power exchange stations with the lowest loss time of vehicle power exchange and the lowest cost of the planning and construction of power exchange stations is established and solved by using the joint algorithm of MLP-NSGA-II; and the optimization model is compared with the traditional genetic algorithm (GA) and the Density Peak. …”
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Association of Antibiotic Resistance Traits in Uropathogenic Escherichia coli (UPEC) Isolates by Md. Mostafizer Rahman, Mridha Md. Kamal Hossain, Rubaya Rubaya, Joyanta Halder, Md. Ekramul Karim, Anjuman Ara Bhuiya, Anwara Khatun, Jahangir Alam

“…However, these findings might have important implications for the development of an AMR prediction model to tackle future AMR outbreaks.…”
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