Design and Implementation of a Physically Secure Open-Source FPGA and Toolchain by Sergej Meschkov, Daniel Lammers, Mehdi B. Tahoori, Amir Moradi

“…A practical security evaluation of our securefabric implementation on a real FPGA target board, using Test Vector LeakageAssessment (TVLA), demonstrated no SCA leakage over 100 million traces. …”
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Insertional mutagenesis and deep profiling reveals gene hierarchies and a Myc/p53-dependent bottleneck in lymphomagenesis. by Camille A Huser, Kathryn L Gilroy, Jeroen de Ridder, Anna Kilbey, Gillian Borland, Nancy Mackay, Alma Jenkins, Margaret Bell, Pawel Herzyk, Louise van der Weyden, David J Adams, Alistair G Rust, Ewan Cameron, James C Neil

“…These findings provide insights into retroviral biology, human cancer genetics and the safety of vector-mediated gene therapy.…”
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K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

“…In the second phase, the best set of features in each group is identified through the Genetic algorithm to enhance the classification process. Finally, a voting ensemble technique is applied, in which the Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Adaptive boosting (AdaBoost) models are combined. …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…Therefore, Na+, Cl+, Na%, CO3 −, and SO4 2− were used as input variables (independent variables), and EC, TDS, and SAR were used as output variables (dependent variables). Support vector machine (SVM) with various kernel functions, multilayer perceptron artificial neural network (MLP-ANN) with various training algorithms, random forest algorithm (RFA), Gaussian process regression (GPR), and statistical analysis methods were used for modeling. …”
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Range Space and Similarity Transformation Using Symbolic Mathematics in Python by Chainarong Wisassakwichai, Prasert Phaochoo

“…It covers important theorems, including vector space basis, range space, null space, rank and nullity, eigenvalues, generalized eigenvectors, eigenspaces, and diagonal-Jordan canonical form transformations. …”
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Development and validation of a machine learning‐based model of ischemic stroke risk in the Chinese elderly hypertensive population by Xiaoyue Lyu, Jie Liu, Yingying Gou, Shengli Sun, Jing Hao, Yali Cui

“…The final model, eXtreme gradient boosting, was identified as having superior performance than the other 9 classifers (random forest, Gaussian process, multilayer perceptron, logistic regression, support vector machine, K‐nearest neighbor, decision tree, Gaussian naive bayes, and ensemble model), with area under the receiver‐operating characteristic curves of 0.97 and 0.94 for the test and external validation sets, respectively. …”
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Towards an intelligent integrated methodology for accurate determination of volume percentages in three-phase flow systems by Abdullah M. Iliyasu, Mohammad Sh. Daoud, Ahmed Sayed Salama, John William Grimaldo Guerrero, Kaoru Hirota

“…Abstract Accurate determination of volume percentages in three-phase fluids is paramount for the success of various industrial processes, ranging from oil and gas production to chemical engineering. …”
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A Set of Proximal Regulatory Elements Contribute to the Transcriptional Activity of the Human Lipoprotein Lipase Promoter by Nasmah K. Bastaki, Taybha A. Albarjes, Afnan K. Mohamed, Noorhan H. Sabri, Suzanne A. Al-Bustan

“…The transcription of <i>LPL</i> in response to cell types and regulatory factors is a complex process that starts with its promoter. In previous studies, several proximal regulatory elements within the human <i>LPL</i> promoter were individually characterized. …”
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Detection of Escherichia coli Using Bacteriophage T7 and Analysis of Excitation‑Emission Matrix Fluorescence Spectroscopy by Nicharee Wisuthiphaet, Huanle Zhang, Xin Liu, Nitin Nitin

“…For example, the Gaussian Process model achieved an accuracy of 92% in detecting different concentration levels of live E. coli. …”
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History Matching of a Channelized Reservoir Using a Serial Denoising Autoencoder Integrated with ES-MDA by Sungil Kim, Baehyun Min, Seoyoon Kwon, Min-gon Chu

“…It does this through encoding and decoding processes using the noise realizations as inputs and the original realizations as outputs of the SDAE. …”
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Extraction Method of Coronary Artery Blood Vessel Centerline in CT Coronary Angiography by Xiaodong Sheng, Tao Fan, Xiaoqi Jin, Jing Jin, Zhixian Chen, Guanqun Zheng, Min Lu, Zongcheng Zhu

“…The experimental results show that the method can accurately extract the blood vessel center line, direction vector and other information in the coronary angiography image without manual intervention, and can be used in the computer-assisted diagnosis and treatment process of clinical cardiovascular disease.…”
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Predictors of length of hospital stay in patients with acute COVID-19 by E. S. Pan’ko, S. V. Zhavoronok, A. M. Solovchuk, S. S. Pan’ko, S. V. Pan’ko

“…Conclusion: The proposed model for determining of the hypoxia vector by assessing the severity of ventilation-perfusion dissociation with indicators of oxygenation and ventilation showed that the MVV/MV ratio and SpO2/FiO2 ratio can be used alone and especially in combination, as effective outcome predictors of the acute phase of the infectious process caused by SARS-CoV-2.…”
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Prognosis of air quality index and air pollution using machine learning techniques by Mostafa M. Abdelmalek, Hatem Mahmoud, Hassan Shokry

“…This study utilizes five machine learning (ML) models, which are Gaussian Process Regression (GPR), Ensemble Regression (ER), Support Vector Machine (SVM), Regression Tree (RT), and Kernel Approximation Regression (KAR), which are developed and compared to predict the Air Quality Index (AQI). …”
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Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection by Ali Nizam, Ertugrul Islamoglu, Omer Kerem Adali, Musa Aydin

“…Code embedding represents code semantics in vector form. Although code embedding-based systems have been successfully applied to various source code analysis tasks, further research is required to enhance code embedding for better code analysis capabilities, aiming to surpass the performance and functionality of static code analysis tools. …”
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PAR-3 knockdown enhances adhesion rate of PANC-1 cells via increased expression of integrinαv and E-cadherin. by Liora Segal, Liora S Katz, Hagit Shapira, Judith Sandbank, Elizabeth Geras-Raaka, Marvin C Gershengorn, Yoram Oron

“…Since thrombin has been implicated in cancer progression, we studied the role(s) of thrombin-activated receptors in the adhesion process. We stably knocked down proteinase-activated receptors (PARs) -1, or -3 in human pancreatic adenocarcinoma PANC-1 cells. …”
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A novel attention-based deep learning model for improving sentiment classification after the case of the 2023 Kahramanmaras/Turkey earthquake on Twitter by Serpil Aslan, Muhammed Yildirim

“…The model employs the FastText word embedding technique to convert tweets into vector representations. These vectorized inputs are then processed by a hybrid model integrating convolutional neural networks (CNNs) and recurrent neural networks (RNNs) with a global attention mechanism. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…The nonlinear Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel achieve the best performance for MCI classification, with an accuracy of 69%, an AUC of 0.75, and a Matthews Correlation Coefficient (MCC) of 0.43. …”
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Temperature affects the sorption of trace metals by macro- and microplastics within marine intertidal sediments: insights from a long-term laboratory-based study by Tamara N. Kazmiruk, Juan José Alava, Juan José Alava, Eirikur Palsson, Leah I. Bendell

“…Macro- and microplastics and trace metals are significant pollutants in the marine environment and have been reported in all ecosystems around the world. The process of sorption/desorption of trace metals by macro- and microplastics is influenced by various factors, including the morphological characteristics of macro- and microplastics, their adsorption capacity, and environmental conditions. …”
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First report of plastic biomedia contamination in Brazilian beaches - evidence from the Paraná coast by Renata Hanae Nagai, Yan Weber Mesquita, Aislyn Alvarenga, Cecília C.V.N. Massignani, Ana Barbara T. Nascimento

“…Highlighting the potential role of the PEC as a substantial vector for marine debris to the Paraná coastline. …”
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A Novel Adaptive Cuboid Regional Growth Algorithm for Trunk–Branch Segmentation of Point Clouds from Two Fruit Tree Species by Yuheng Cao, Ning Wang, Bin Wu, Xin Zhang, Yaxiong Wang, Shuting Xu, Man Zhang, Yanlong Miao, Feng Kang

“…This method integrates a growth vector that is adaptively adjusted based on the growth trend of branches and a growth cuboid that is dynamically regulated according to branch diameters. …”
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