Navigating Nepal's health financing system: A road to universal health coverage amid epidemiological and demographic transitions. by Resham B Khatri, Pratik Khanal, Dipendra Singh Thakuri, Prabesh Ghimire, Mihajlo Jakovljevic

“…Key reforms  include: (1) merging or harmonizing existing social health protection schemes for efficient pooling and purchasing; (2) enhancing domestic health financing through increased health funding (≥5% of GDP) via payroll contributions, progressive taxation, and earmarked sin taxes; (3) reforming NHIP to mandatory enrollment starting from formal sector, subsidizing premium for informal sector and free coverage for disadvantaged groups, alongside strengthening policy implementation including accrediting of health facilities, ensuring service quality, prioritising and expanding coverage packages with strategic purchasing from all public and private health facilities; and (4) equitable public financing to ensure needs-based allocation across government levels that respond to demographic and epidemiological patterns. …”
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Geographic variation in the determinants of ectoparasite faunas’ species richness: fleas and gamasid mites parasitic on small mammals from 6 biogeographic realms by Boris R. Krasnov, Vasily I. Grabovsky, Natalia Korallo-Vinarskaya, Maxim V. Vinarski, Angel Luis Robles Fernandez, Irina Khokhlova

“…We conclude that caution is needed in making judgements about the generality of macroecological patterns related to parasites based on the investigations of these patterns in limited numbers of localities and when pooling data on various taxa.…”
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Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

“…Fault detection in photovoltaic (PV) panels using thermal images remains a significant challenge due to the complexity of thermal patterns, environmental noise, and the subtle nature of anomalies. …”
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Research on Electric Vehicle Charging Load Prediction Methods Combining Signal Noise Reduction and Time Series Modeling by Liyun Liu, Xiaomei Xu, Jinsong Zhang, Dong Li

“…This study introduces a hybrid deep learning model combining Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Networks (CNN), Bi-directional Gated Recurrent Units (BiGRU), and Attention Mechanism (AM) to address the volatility in charging load patterns. The proposed method begins with the application of CEEMDAN to decompose the data into intrinsic mode functions (IMFs) and residuals. …”
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ECG-GraphNet: Advanced arrhythmia classification based on graph convolutional networks by Myeonghun Lee, BS, Jiwoo Lim, MS, JinKook Kim, MS

“…A unique QRS-centered weighted average pooling method is employed to enhance beat-specific feature extraction. …”
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Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

“…Our framework incorporates dimension alignment strategies and attention mechanisms to capture temporal–spatial complementarity between acoustic feeding signals and visual behavioral patterns. Extensive experiments demonstrate superior performance compared to single-modal and conventional fusion approaches, with 6.4% accuracy improvement. …”
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Predicting changes in agricultural yields under climate change scenarios and their implications for global food security by Christine Li, James Camac, Andrew Robinson, Tom Kompas

“…We present updates to published estimates of crop yield responses to projected temperature, precipitation, and CO2 patterns and show that mixed effects models perform better than pooled OLS models on root mean squared error (RMSE) and explained deviance, despite the common usage of pooled OLS in previous meta-analyses. …”
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SAGEFusionNet: An Auxiliary Supervised Graph Neural Network for Brain Age Prediction as a Neurodegenerative Biomarker by Suraj Kumar, Suman Hazarika, Cota Navin Gupta

“…<b>Methods:</b> In this study, we propose SAGEFusionNet, a GNN architecture specifically designed to enhance brain age prediction and assess PD-related brain ageing patterns using T1-weighted structural MRI (sMRI). SAGEFusionNet learns important ROIs for brain age prediction by incorporating ROI-aware pooling at every layer to overcome the above challenges. …”
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Estimating Trends in Cardiovascular Disease Risk for the EXPOSE (Explaining Population Trends in Cardiovascular Risk: A Comparative Analysis of Health Transitions in South Africa a... by Shaun Scholes, Jennifer S Mindell, Mari Toomse-Smith, Annibale Cois, Kafui Adjaye-Gbewonyo

“…Predicted CVD risk using the Globorisk algorithms was lower on average in absolute terms, but the pattern of change was very similar. Trends in the individual risk components showed a complex pattern. …”
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Multimodal imaging biomarkers of subretinal hyperreflective material accumulation in central serous chorioretinopathy by Jiaxin Pu, Guiqin He, Xiongze Zhang, Miaoling Li, Xinlei Hao, Xuenan Zhuang, Yongyue Su, Feng Wen

“…Differences were also discovered in serous retinal detachment (SRD) dimensions, presence of pigment epithelial detachment (PED) and retinal pigment epithelium (RPE) defects in OCT, gravitational tracks and hyperautofluorescence contours in FAF, leakage patterns and dye pooling area in FFA, and focal choroidal vascular hyperpermeability (CVH) area in ICGA (P < 0.05 for all). …”
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Accurate Indoor Home Location Classification through Sound Analysis: The 1D-ILQP Approach by Umut Erman, Türker Tuncer, Nura Abdullahi, Sengul Dogan, Erhan Akbal

“…At the core of our approach is the introduction of a local feature generator, referred to as the one-dimensional Improved Local Quadruple Pattern (1D-ILQP). This novel 1D-ILQP plays a central role in the feature extraction process, generating textural features from the acoustic signals. …”
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ID3RSNet: cross-subject driver drowsiness detection from raw single-channel EEG with an interpretable residual shrinkage network by Xiao Feng, Xiao Feng, Zhongyuan Guo, Zhongyuan Guo, Sam Kwong

“…With the global average pooling (GAP) layer incorporated in the residual shrinkage network structure, we introduce an EEG-based Class Activation Map (ECAM) interpretable method to enable visualization analysis of sample-wise learned patterns to effectively explain the model decision. …”
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LMSOE-Net: lightweight multi-scale small object enhancement network for UAV aerial images by Zhixing Ma, Peidong Luo, Xiaole Shen

“…This upgrade strengthens the network’s ability to capture fine details and complex patterns, improving multi-scale feature extraction without a significant increase in parameters. …”
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MB-MSTFNet: A Multi-Band Spatio-Temporal Attention Network for EEG Sensor-Based Emotion Recognition by Cheng Fang, Sitong Liu, Bing Gao

“…Bi-directional GRUs (BiGRUs) model temporal dependencies in sensor time-series, adept at capturing long-range dynamic patterns. Multi-head self-attention highlights critical time windows and brain regions by assigning adaptive weights to relevant sensor channels, suppressing noise from non-contributory electrodes. …”
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Key features of observational research data preparation for evidence synthesis by A. A. Lazarev, K. V. Sapozhnikov, D. G. Tolkacheva, N. A. Sableva

“…This work was conducted within a review of asymptomatic hyperuricemia (AH) and was intended to lead to the consensus among rheumatologists on the management patterns of patients with AH in the Russian Federation.Materials and methods. …”
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DSAT: a dynamic sparse attention transformer for steel surface defect detection with hierarchical feature fusion by Shouluan Wu, Hui Yang, Liefa Liao, Chao Song, Yating Fang, Jianglong Fu, Tan Li

“…These defects exhibit diverse morphological characteristics and complex patterns, which pose substantial challenges to traditional detection models, particularly regarding multi-scale feature extraction and information retention across network depths. …”
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Graph Neural Network Learning on the Pediatric Structural Connectome by Anand Srinivasan, Rajikha Raja, John O. Glass, Melissa M. Hudson, Noah D. Sabin, Kevin R. Krull, Wilburn E. Reddick

“…Architecture exploration experiments were conducted to evaluate the impact of network depth, pooling techniques, and skip connections on the ability of GNN models to capture connectomic patterns. …”
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Duration of protection against malaria and anaemia provided by intermittent preventive treatment in infants in Navrongo, Ghana. by Matthew Cairns, Ilona Carneiro, Paul Milligan, Seth Owusu-Agyei, Timothy Awine, Roly Gosling, Brian Greenwood, Daniel Chandramohan

“…Analysis of first-or-only clinical malaria episode following the individual IPTi doses showed that some protection against malaria lasted between 4 to 6 weeks. A similar pattern was seen when the incidence of all malaria episodes up to 2 years of age was analysed in relation to the most recent IPT, by pooling the incidence of malaria after the individual IPTi doses. …”
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Clinical and Diagnostic Significance of Lactate Dehydrogenase and Its Isoenzymes in Animals by Robert Klein, Oskar Nagy, Csilla Tóthová, Frederika Chovanová

“…The activity of LDH and its serum and tissue patterns and composition show great variations between the species. …”
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A Comprehensive Review on the Application of 3D Convolutional Neural Networks in Medical Imaging by Satyam Tiwari, Goutam Jain, Dasharathraj K. Shetty, Manu Sudhi, Jayaraj Mymbilly Balakrishnan, Shreepathy Ranga Bhatta

“…CNNs are particularly adept in automatically identifying complex patterns and features in pictures like X-rays, CT scans, and MRIs. …”
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