Urban Expansion and Land Use Transformations in Midnapore City (2003–2024): Implications for Sustainable Development by Rakesh Ranjan Thakur, Debabrata Nandi, Anoop Kumar Shukla, Subhasmita Das, Sasmita Chand, Pankaj Singha, Roshan Beuria, Chetan Sharma

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STRATEGIC COMPETENCE AS A GUARANTEE OF PROFESSIONAL ACTIVITY OF A MODERN IT SPECIALIST by Volkova Nataliia, Oliinyk Iryna, Karpova Maryna

“…It has been established that strategic competence of an IT specialist is a personal integrative creation. This represents the unity of professionally significant qualities, knowledge and skills, with the help of which specialists formulate the strategic goal of work, show a value-motivational attitude to strategic changes and flexibility in behaviour depending on the factors of the external environment, make a reasonable choice and implement strategies depending on the situation, while achieving the effectiveness of the professional activity. …”
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Improving EEG based brain computer interface emotion detection with EKO ALSTM model by R. Kishore Kanna, Preety Shoran, Meenakshi Yadav, Mohammad Nadeem Ahmed, Shrikant Burje, Garima Shukla, Anurag Sinha, Mohammad Rashid Hussain, Saifullah Khalid

“…The proposed system and existing algorithms are compared using a variety of evaluation criteria, including specificity, F1 score, accuracy, recall or sensitivity, and positive predictive values or precision. …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. …”
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Research Progress on Identification and Extraction Methods of Soil and Water Conservation Measures by TIAN Pei, REN Yiling, CHEN Yan

“…[Results] In semantic segmentation, future feature fusion and multimodal learning, weak supervision and semi-supervised learning, integrated learning and meta-learning can be applied to the extraction of soil and water conservation measures. …”
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Appropriateness of NHS 111 Wales outcomes—using the Call Prioritisation Streaming System: a RAND/UCLA modified Delphi method by Craig Brown, Conrad Fivaz, Rebecca Malin, Mike Brady, Rhiannon Elizabeth Roynon, Peter Noblett

“…It achieves this by integrating individual patient data with a comprehensive computerised knowledge base, employing advanced software algorithms to produce recommendations and dispositions.Objectives While CPSS offers many advantages, its introduction marked a major shift in clinical digital processes. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…This study introduces innovative ensemble learning models that integrate the randomizable filter classifier (RFC), regression by discretization (RBD), and attribute-selected classifier (ASC) with the random forest (RF) algorithm, resulting in hybrid models (RFC-RF, RBD-RF, and ASC-RF). …”
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Single-cell transcriptomics and machine learning unveil ferroptosis features in tumor-associated macrophages: Prognostic model and therapeutic strategies for lung adenocarcinoma by Ting Ji, Ting Ji, Juanli Jiang, Juanli Jiang, Xin Wang, Xin Wang, Kai Yang, Kai Yang, Shaojin Wang, Shaojin Wang, Bin Pan, Bin Pan

“…Eight machine learning algorithms (LASSO, SVM, XGBoost, etc.) were leveraged to identify prognostic genes and build a Cox regression risk model. …”
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Influence of micro-topography on the spatial heterogeneity of above-ground biomass: Lessons from the Qinglan Port Mangrove Nature Reserve, China by Meihuijuan Jiang, Penghua Qiu, Dezhi Wang, Minghui Wu, Ruiquan Lai, Xinqing Zou, Tingting Si, Hui Li, Qidong Shi, Yi Lin, Genzong Xie, Yanli Yang, Siang Wan

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Intelligent Prediction Platform for Sepsis Risk Based on Real-Time Dynamic Temporal Features: Design Study by Mingwei Zhang, Ming Zhong, Yunzhang Cheng, Tianyi Zhang

“…Three linear parameters (mean, SD, and endpoint value) were calculated to construct the prediction model using multiple ML algorithms. …”
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Diagnostics-linked Antimicrobial Surveillance: A Route to Patient-Centred Microbiology Diagnostics? by Dr Alex Howard, Dr Charlotte Brookfield, Dr Conor Rosato, Dr Anoop Velluva, Dr Alessandro Gerada, Professor William Hope

“…Conclusion: A diagnostic-linked algorithmic approach to antimicrobial surveillance using linked, pseudonymised prescribing and diagnostic data could help clinicians, laboratory managers, and service commissioners better quantify the clinical impact, value, and required resourcing of diagnostic services to help maximise their effect on antimicrobial stewardship.…”
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Genetic analysis of non-syndromic peg lateralis using whole-exome sequencing by Junglim Choi, Junglim Choi, Sungnam Kim, Hyunsoo Ahn, Donghyo Kim, Sung-Won Cho, Sanguk Kim, Sanguk Kim, Sanguk Kim, Jae Hoon Lee

“…In-silico mutation impact analysis was performed using Polymorphism Phenotyping v2, sorting intolerant from the tolerant, and integrated score of co-evolution and conservation algorithms.ResultsWe identified a heterozygous allele for RP11-131H24.4 and OTOP1, which encodes the otopetrin-1 protein, a proton channel, in all 20 individuals. …”
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Applying machine learning to assist in the morphometric assessment of brain arteriolosclerosis through automation by Jerry J. Lou, Peter Chang, Kiana D. Nava, Chanon Chantaduly, Hsin-Pei Wang, William H. Yong, Viharkumar Patel, Ajinkya J. Chaudhari, La Rissa Vasquez, Edwin Monuki, Elizabeth Head, Harry V. Vinters, Shino Magaki, Danielle J. Harvey, Chen-Nee Chuah, Charles S. DeCarli, Christopher K. Williams, Michael Keiser, Brittany N. Dugger

“…To address this gap, we present a prototype end-to-end machine learning (ML)-based algorithm, Arteriolosclerosis Segmentation (ArtSeg), followed by Vascular Morphometry (VasMorph) – to assist persons in the morphometric analysis of arteriolosclerotic vessels on whole slide images (WSIs). …”
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Combination of ultrasound-based radiomics and deep learning with clinical data to predict response in breast cancer patients treated with neoadjuvant chemotherapy by Wu Tenghui, Liu Xinyi, Si Ziyi, Zhang Yanting, Ma Ziqian, Zhu Yiwen, Gan Ling

“…This integrated approach highlights the value of combining diverse data types to improve prediction, offering a promising tool for guiding NAC response assessment and personalized treatment planning.…”
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A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…At the same time, in each detection layer, a lightweight CRE module was integrated, leveraging attention mechanisms and detection heads to enhance precision for small object detection. …”
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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach by Mar Roca, Chengfa Benjamin Lee, Avi Putri Pertiwi, Alina Blume, Isabel Caballero, Gabriel Navarro, Dimosthenis Traganos

“…Using existing in situ soil carbon stock (Cstock) data, we estimated a mean Cstock value of 12.27 ± 2.1 million megagram (Mg) Corg, while mapping a total annual C fixation (Cfix) and C sequestration (Cseq) rates of P. oceanica of 1,116.3 Mg Corg and 227 Mg Corg, according to depth. …”
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GAB-YOLO: a lightweight deep learning model for real-time detection of abnormal behaviors in juvenile greater amberjack fish by Mingxin Liu, Mingxin Liu, Chun Zhang, Cong Lin, Cong Lin

“…Meanwhile, existing automated detection algorithms often struggle with a trade-off between detection accuracy and model size. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Results demonstrate three key findings: (1) By introducing prototype learning, a meta-learning approach, to guide model updates, we achieved precise assessments with small training samples, attaining an MAE of 1.02, representing 58.5–76.1% error reduction compared to conventional machine learning algorithms. This reveals that implicitly classifying typhoon disaster loss types through prototype learning can significantly improve assessment accuracy in data-scarce scenarios. (2) By designing a dual-path uncertainty quantification mechanism, we realized high-reliability risk assessment, with 95.45% of actual loss values falling within predicted confidence intervals (theoretical expectation: 95%). …”
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Analysis and validation of novel biomarkers related to palmitoylation in adenomyosis by Hongyu Zhang, Yufeng Li, Huijuan Cao, Yiling Zhao, Hongwen Zhu, Tiansheng Qin

“…Meanwhile, the diagnostic value of each biomarker was assessed using the receiver operating characteristic curve analysis in the remaining three datasets. …”
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