A federated LSTM network for load forecasting using multi-source data with homomorphic encryption by Mengdi Wang, Rui Xin, Mingrui Xia, Zhifeng Zuo, Yinyin Ge, Pengfei Zhang, Hongxing Ye

“…To further enhance security, the homomorphic encryption (HE) using Paillier algorithm was introduced during the federated process. …”
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Transabdominal ultrasound for the characterization and follow-up of cystic pancreatic lesions by Julian Seelig, Maria Heni, Max Seitzinger, Kien Vu Trung, Jürgen Feisthammel, Marcus Hollenbach, Robert Henker, Albrecht Hoffmeister, Jonas Rosendahl, Valentin Blank, Thomas Karlas

“…Cross-method morphological assessments were analysed, and a patient-specific algorithm for selecting the appropriate monitoring method was developed. …”
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Filamentary Hierarchies and Superbubbles. I. Characterizing Filament Properties across a Simulated Spiral Galaxy by Rachel Pillsworth, Erica Roscoe, Ralph E. Pudritz, Eric W. Koch

“…By adapting the FilFinder algorithm of E. W. Koch & E. W. Rosolowsky, we extract over 500 filaments ranging up to 10 kpc in scale, to derive the probability distribution functions for filament masses and lengths, magnetic field orientations, and the gravitational stability and fragmentation patterns of filaments. …”
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A Clinical Validation of a Diagnostic Test for Esophageal Adenocarcinoma Based on a Novel Serum Glycoprotein Biomarker Panel: PromarkerEso by Jordana Sheahan, Iris Wang, Peter Galettis, David I. Watson, Virendra Joshi, Michelle M. Hill, Richard Lipscombe, Kirsten Peters, Scott Bringans

“…A panel of glycoproteins: alpha-1-antitrypsin, alpha-1-antichymotrypsin, complement C9 and plasma kallikrein, were combined with clinical factors (age, sex and BMI) in an algorithm to categorize the samples by the risk of EAC. …”
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Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model by Bo Hu, Yue Sun, Wei Huang, Changzheng Shao, Tao Niu, Xin Cheng, Kaigui Xie

“…Finally, a reliability assessment framework for a composite power system is developed considering the uncertain price-based DR model and a k-means algorithm is used to accelerate the assessment process. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…By analysing data from sensors and system logs, ML algorithms can identify patterns indicative of faults or inefficiencies, such as shading, soiling, or equipment malfunctions, often before they become serious issues. …”
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Climatic suitability and potential distribution of earleaf acacia and its candidate biological control agent Trichilogaster sp by Sara S. MacDonald, Emily J. Le Falchier, Lindsay P. Campbell, Ryan Zonneveld, Carey R. Minteer

“…Ecological niche models were created using the ‘maxnet’ algorithm in the ‘ENMEval’ R package with appropriate environmental variables. …”
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Prognosticating salvage stereotactic radiosurgery outcomes in relapsed primary central nervous system lymphoma: A machine learning-driven decision tree analysis by Huili Zhao, Shenao Zhang, Lang Chen, Xin Liu, Aihong Cao, Peng Du

“…The cohort was randomly divided into training and validation sets (7:3 ratio). The C5.0 algorithm was employed to develop a decision tree model for predicting treatment response. …”
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Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions by Xuan Yu, Jing Zhou, Yaping Wu, Yan Bai, Nan Meng, Qingxia Wu, Shuting Jin, Huanhuan Liu, Panlong Li, Meiyun Wang

“…The area under the receiver operating characteristic curve (AUC) was employed to assess predictive performance. Results The ROI-based models of intratumoral and peritumoral regions, utilizing deep learning algorithms on multi-sequence MRI, were capable of predicting MGMT promoter methylation status in glioblastoma patients. …”
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Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharma... by Auwal Salisu Isa, Adamu Uzairu, Umar Mele Umar, Muhammad Tukur Ibrahim, David Ebuka Arthur, Samuel Ndaghiya Adawara

“…The present research was centered on the development of a predictive model aimed at assessing the responses of prostate tumors to a range of compounds within the scope of the pIC50 project. …”
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Passive Microwave Imagers, Their Applications, and Benefits: A Review by Nazak Rouzegari, Mohammad Bolboli Zadeh, Claudia Jimenez Arellano, Vesta Afzali Gorooh, Phu Nguyen, Huan Meng, Ralph R. Ferraro, Satya Kalluri, Soroosh Sorooshian, Kuolin Hsu

“…This review examines the relevance, applications, and benefits of PMWI data, focusing on their practical use and benefits to society rather than the specific techniques or algorithms involved in data processing. Specifically, it assesses the impact of PMWI data on Tropical Cyclone (TC) intensity and structure, global precipitation and extreme events, flood prediction, the effectiveness of tropical storm and hurricane watches, fire severity and carbon emissions, weather forecasting, and drought mitigation. …”
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Critical review of patient outcome study in head and neck cancer radiotherapy by Jingyuan Chen, Yunze Yang, Chenbin Liu, Hongying Feng, Jason M. Holmes, Lian Zhang, Steven J. Frank, Charles B. Simone, II, Daniel J. Ma, Samir H. Patel, Wei Liu

“…This review critically evaluates the evolution of data-driven approaches in predicting patient outcomes in head and neck cancer patients treated with radiation therapy. …”
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Draft genome dataset of Streptomyces griseoincarnatus strain R-35 isolated from tidal pool sedimentsMendeley DataNCBI by Danielle Dana Mitchell, Jo-Marie Vreulink, Alaric Prins, Marilize Le Roes-Hill

“…The phylogenomic positioning of S. griseoincarnatus strain R-35 was determined using the Type Strain Genome Server (TYGS) and was found to be related to S. griseoincarnatus JCM 4381T, with a digital DNA-DNA hybridisation (dDDH) value of 84.1%, and an OrthoANIu value of 98.22%. The CARD RGI algorithm on Proksee predicted the presence of 6,107 antimicrobial resistance (AMR) features, 27 biosynthetic gene clusters (BGCs) were predicted using antiSMASH, while 189 carbohydrate-active enzymes (CAZymes) were predicted using dbCAN3. …”
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An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments by Zhenling Dai, Ziqun Gu, Rongrong Shen, Jingshuai Wang

“…Notably, this 11-gene signature also predicted the sensitivity of breast cancer to both conventional and immune therapies, aligning closely with predictions from the OncoPredict algorithm. …”
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Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study by Xiaojiang Zhao, Yuhang Wang, Mengli Xue, Yun Ding, Han Zhang, Kai Wang, Jie Ren, Xin Li, Meilin Xu, Jun Lv, Zixiao Wang, Daqiang Sun

“…Tumor segmentation was achieved using an automatic virtual adversarial training segmentation algorithm based on a three-dimensional U-shape convolutional neural network (3D U-Net). …”
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The association between inflammatory, metabolic, and hepatic fibrosis-related biomarkers and atrial fibrillation in older patients with metabolic dysfunction-associated steatotic l... by Shuai Zhang, Hao Liang, Jun Liu, Zhipeng Huang, Xijing Shi, Ye Zhu

“…The variable importance ranking results based on the Boruta algorithm, as well as the Receiver Operating Characteristic (ROC) curve and Decision Curve Analysis (DCA), all indicate that NFS and ALBI have high predictive performance and clinical benefits. …”
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Unlocking potent anti-tuberculosis natural products through structure–activity relationship analysis by Delfly Booby Abdjul, Fitri Budiyanto, Joko Tri Wibowo, Tutik Murniasih, Siti Irma Rahmawati, Dwi Wahyu Indriani, Masteria Yunovilsa Putra, Asep Bayu

“…Significant characteristics and relevant biological properties of each compound were analysed using a Random Forest, machine learning algorithm, to explore SAR. Using molecular docking, AutoDock Vina was utilised to assess molecular interactions with protein targets, and predictive accuracy was enhanced using the XGBoost machine learning model. …”
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Modeling Canopy Height of Forest–Savanna Mosaics in Togo Using ICESat-2 and GEDI Spaceborne LiDAR and Multisource Satellite Data by Arifou Kombate, Guy Armel Fotso Kamga, Kalifa Goïta

“…We tested four methods: Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN). The RF algorithm obtained the best predictions using 98% relative height (RH98). …”
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Strategic Implementation of Super-Agents in Heterogeneous Multi-Agent Training for Advanced Military Simulation Adaptability by Huseyin Oktay Altun, Huseyin Furkan Ceran, Korkut Kutay Metin, Tolga Erol, Emre Fisne

“…Optimizing Heterogeneous Multi-Agent Training (HMAT) through scenario-specific adjustments to the Proximal Policy Optimization (PPO) algorithm, we tackle the complexity of tactical simulations. …”
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Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System by Hongseok Jang, Yeonho Lee, Hongseok Lee, Youngtaek Cha, Sungjoon Choi, Jongkyu Park

“…Furthermore, it uses a ground stability determination algorithm that qualitatively assesses soft ground conditions, which are the primary cause of ground subsidence. …”
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