Multi-source localization with binary sensor networks by CHENG Long1, WU Cheng-dong1, ZHANG Yun-zhou1, JIA Zi-xi1, JI Peng1

“…A new multi-source detection model was proposed based on Neyman-Pearson criterion to reduce the computa-tional complexity caused in the multi-source localization.The Fisher criterion was employed to divide sensors into two parts,where two sources were present and each part corresponds to one of the sources.The WSNAP（weighted subtract on negative add on positive） multi-source location algorithm was applied to localize the multiple sources.The simulation results show that Fisher criterion is able to divide the alarmed sensor into two parts with relatively higher accuracy.The proposed WSNAP has better estimation accuracy than AP（add positive） algorithm and CE（centroid estimator） algorithm under the circumstance of lower computation complexity.Finally,the results are verified using the database of distributed wireless sensor networks.…”
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Modeling residue formation from crude oil oxidation using tree-based machine learning approaches by Mohammad-Reza Mohammadi, Seyyed-Mohammad-Mehdi Hosseini, Behnam Amiri-Ramsheh, Saptarshi Kar, Ali Abedi, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour

“…Furthermore, temperature was identified as the most influential factor affecting residual crude oil content, exhibiting a significant negative correlation, while API gravity also showed a negative impact. …”
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Preeclampsia pathogenesis and prediction - where are we now: the focus on the role of galectins and miRNAs by Natasa Karadzov Orlic, Ivana Joksić

“…Preeclampsia is a complex, progressive multisystem hypertensive disorder during pregnancy that significantly contributes to increased maternal and perinatal morbidity and mortality. Two screening algorithms are in clinical use for detecting preeclampsia: first-trimester screening, which has been developed and validated for predicting early-onset preeclampsia but is less effective for late-onset disease; and the sFlt-1:PlGF biomarker ratio (soluble tyrosine kinase and placental growth factor) used in suspected cases of preeclampsia. …”
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The role of magnetic resonance imaging in radiation Diagnosis of abdominal aortic aneurysm by S. S. Saidov, S. K. Skul'skiy, N. P. Morozova, Ya. A. Lubashev, V. A. Ratnikov

“…At the same time, the existing algorithms for examining patients with AAA, aimed at the timely detection of preand postoperative complications, require significant correction [6, 7]. …”
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The Utility of Follow-up Transthoracic Echocardiogram to Screen for Severe Portopulmonary Hypertension (POPH) in Patients Granted POPH Model for End-stage Liver Disease (MELD) Exce... by Kathryn T. del Valle, MD, Dana Kay, MD, Michael J. Krowka, MD, James R. Runo, MD, Corey Sadd, MD, Julie K. Heimbach, MD, Rodrigo Cartin-Ceba, MD, Hector R. Cajigas, MD, Charles D. Burger, MD, John E. Moss, MD, Hilary M. DuBrock, MD

“…In external validation of 13 paired echocardiograms and RHCs, our algorithm had 64% specificity and 100% negative predictive value. …”
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Cost-effectiveness of different tuberculosis diagnostic approaches in Nigeria based on decision analytical modelling by Muktar H Aliyu, Hafsat U Ibrahim, Rayyan M Garba, Jameel I Ahmad, Kabiru Abdulsalam, Yasir N Jibril, Faisal S Dankishiya, Abdullahi Ibrahim, Ibrahim U Garzali, Aisha A Galadanci, Abdullahi K Suleiman, Abdulgafar L Olawumi, Umar F Abdullahi, Fatima M Mahmud, Amina A Umar, Olive Asafu- Adjaye, Lukman F Owolabi, Baba M Musa

“…Conventional diagnostic methods such as sputum smear microscopy and chest radiography often fail to detect TB accurately in this population due to smear-negative presentations and atypical radiographic findings. …”
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Exploring the role of mitochondrial metabolism and immune infiltration in myocardial infarction: novel insights from bioinformatics and experimental validation by Jingyi Hou, Jingyi Hou, Jingyi Hou, Lihan Wang, Lihan Wang, Naiqiang Zhu, Xueli Li

“…A protein-protein interaction (PPI) network of mitoDEGs was constructed, and hub mitoDEGs associated with MI were identified using CytoHubba and molecular complex detection (MCODE) algorithms. Transcription factor (TF) and microRNA (miRNA) targets of hub mitoDEGs were predicted using iRegulon and miRWalk plug-ins, respectively, and a regulatory network involving TFs, hub mitoDEGs, and miRNA was established. …”
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Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018 by Xiangling Deng, Lifei Ma, Pin Li, Mengyang He, Ruyue Jin, Yuandong Tao, Hualin Cao, Hengyu Gao, Wenquan Zhou, Kuan Lu, Xiaoye Chen, Wenchao Li, Huixia Zhou

“…Furthermore, an optimal predictive model was developed for CKD using ten machine learning algorithms and enhanced model interpretability with the Shapley Additive Explanations (SHAP) method. …”
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A mobile app to improve adherence to colorectal cancer screening and post polypectomy surveillance guidelines by María A. Casas, Francisco Schlottmann, Leandro Steinberg, Xavier Bessa, Anna Serradesanferm, Angels Pozo, Sonia Torres, Antoni Castells, Francesc Balaguer, Jaume Grau, Lisandro Pereyra, María Pellisé

“…Abstract Background Despite significant advances in prevention and early detection, colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. …”
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A Portable UV-LED/RGB Sensor for Real-Time Bacteriological Water Quality Monitoring Using ML-Based MPN Estimation by Andrés Saavedra-Ruiz, Pedro J. Resto-Irizarry

“…Fluorescence signals from individual wells are captured by the RGB sensors and analyzed using Multilayer Perceptron Neural Network (MLPNN) and Support Vector Machine (SVM) algorithms, which can quickly determine if individual wells will be positive or negative by the end of a 24 h period. …”
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Construction method of attack scenario in cloud environment based on dynamic probabilistic attack graph by Wenjuan WANG, Xuehui DU, Dibin SHAN

“…Aiming at the problem of complex multi-step attack detection, the method of attack scenario construction oriented to cloud computing environment was studied.Firstly, a dynamic probabilistic attack graph model was constructed, and a probabilistic attack graph updating algorithm was designed to make it update periodically with the passage of time and space, so as to adapt to the elastic and dynamic cloud computing environment.Secondly, an attack intention inference algorithm and a maximum probability attack path inference algorithm were designed to solve the uncertain problems such as error and fracture of attack scenarios caused by false positive or false negative, and ensure the accuracy of attack scenario.Meanwhile, the attack scenario was dynamically evolved along with the dynamic probability attack graph to ensure the completeness and freshness of the attack scenario.Experimental results show that the proposed method can adapt to the elastic and dynamic cloud environment, restore the penetration process of attacker’s and reconstruct high-level attack scenario, and so provide certain references for building supervised and accountable cloud environment.…”
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Classification of Phishing Email Using Random Forest Machine Learning Technique by Andronicus A. Akinyelu, Aderemi O. Adewumi

“…From a dataset consisting of 2000 phishing and ham emails, a set of prominent phishing email features (identified from the literature) were extracted and used by the machine learning algorithm with a resulting classification accuracy of 99.7% and low false negative (FN) and false positive (FP) rates.…”
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UHVDC Transmission Line Fault Identification Method Based on Generalized Regression Neural Network by XIE Jia, LIU Feng, KE Yanguo, YIN Zhen, RUAN Wei, YAO Jinming

“…A protection method for ultra-high voltage direct current transmission lines based on generalized regression neural network (GRNN) is proposed to address the issues of easy rejection and long fault detection time in ultra-high voltage direct current protection. …”
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Clinical performance validation and four diagnostic strategy assessments of high-sensitivity troponin I assays by Junyi Wu, Yaotong Hua, Yilin Ge, Ke Chen, Siyu Chen, Jiashu Yang, Hui Yuan

“…However, there is no consensus on the optimal diagnostic strategy for early NSTEMI detection. This study aims to evaluate the diagnostic performance of four hs-cTnI-based strategies for suspected NSTEMI: Limit of Detection (LoB), Single Cut-off, hs-cTnI 0/1 h Algorithm, and hs-cTnI 0/2 h Algorithm, in a Chinese cohort and compare the performance of assays from different manufacturers. …”
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Utilizing bioinformatics to identify biomarkers and analyze their expression in relation to immune cell ratios in femoral head necrosis by Dongchen Li, Dongchen Li, Zhilong Huang, Teng Ma, Yu Su, Yu Su, Zhao Li, Zhao Li, Liang Sun, Ming Li, Zhong Li, Yao Li, Qian Wang, Yao Lu

“…BackgroundNecrosis of the Femoral Head (NFH) represents a challenging orthopedic condition, characterized by elusive early detection and rapid progression, predominantly in the middle-aged demographic. …”
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Constitutional-Legal Aspect of Creating Large Language Models: the Problem of Digital Inequality and Linguistic Discrimination by I. G. Ilin

“…While direct forms of discrimination can be detected in predictive algorithms, generative models create more subtle but no less significant cumulative effects. …”
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A Federated Learning-Based Framework for Accurately Identifying Human Activity in the Environment by Nwadher Suliman Al-Blihed, Dina M. Ibrahim

“…Human Activity Recognition (HAR) refers to the detection of people’s activities during daily life using various types of sensors. …”
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An ImmunoSignature test distinguishes Trypanosoma cruzi, hepatitis B, hepatitis C and West Nile virus seropositivity among asymptomatic blood donors. by Michael Rowe, Jonathan Melnick, Robert Gerwien, Joseph B Legutki, Jessica Pfeilsticker, Theodore M Tarasow, Kathryn F Sykes

“…<h4>Principal findings</h4>Initially, samples from two Chagas cohorts declared positive or negative by bank testing were studied. With the first cohort, library-peptides displaying differential binding signals between T. cruzi sero-states were used to train an algorithm. …”
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Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson’s Disease: A Systematic Review and Meta-Analysis by Feng Zhang, Liangqing Guo, Lin Liu, Xiaochun Han

“…To evaluate the diagnostic accuracy of machine learning-assisted magnetic resonance imaging (MRI) in detecting cognitive impairment among Parkinson’s disease (PD) patients through a systematic review and meta-analysis. …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Notably, among different BRCA molecular sub-types, Hormone Receptor negative (HR-) BRCA cases, especially Basal-like BRCA sub-types, lack estrogen and progesterone hormone receptors and they exhibit a higher tumor growth rate compared to HR+ cases. …”
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