An AI-Based Open-Source Software for <i>Varroa</i> Mite Fall Analysis in Honeybee Colonies by Jesús Yániz, Matías Casalongue, Francisco Javier Martinez-de-Pison, Miguel Angel Silvestre, Beeguards Consortium, Pilar Santolaria, Jose Divasón

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Bias‐Independent True Random Number Generator Circuit using Memristor Noise Signals as Entropy Source by Jinwoo Park, Hyunjoong Kim, Hyungjin Kim

“…Finally, the performance of the designed TRNG circuit is evaluated using autocorrelation functions and National Institute of Standards and Technology tests, confirming its capability to produce random number bitstreams.…”
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Multiepoch Observations of the Nearby Spiral Galaxy NGC 3938 with the Chandra X-Ray Observatory by Siddhi Raut, Eric M. Schlegel, Thomas G. Pannuti, Brannon W. Jones, Jacobo Matallana

“…A total of 47 discrete merged sources from both epochs were detected at the ≈3 σ level or greater with the D25 radius. …”
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Potential Source Regions and Transportation Pathways of Reactive Gases at a Regional Background Site in Northwestern China by Quanwei Zhao, Qing He, Lili Jin, Jianlin Wang

“…Wind rose, cluster analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) methods were adopted for identifying the transport pathways and potential source regions of these atmosphere components at Akedala. …”
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Statistically Optimized Near-Field Acoustic Holography Using Prolate Spheroidal Wave Functions by Xuxin Zhang, Jingjun Lou, Jinfang Lu, Ronghua Li, Shijian Zhu

“…Near-field acoustic holography (NAH) is an effective tool for realizing accurate sound field reconstruction in three-dimensional space on the prerequisite that appropriate elementary wave functions are selected or constructed to match the characteristics of the sound sources. …”
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Features of Bearing on Underwater Object Using Phase Information of a Differential Stereo Sensor by V. A. Shirokov, A. I. Bazhenova, V. N. Milich

“…Taking into account the factor of smoothness and continuity of the object's trajectory makes it possible to qualitatively correct the selection of the maximum of the cross-correlation function of the stereo sensor signals. …”
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Enhancing Antioxidant Benefits of Kombucha Through Optimized Glucuronic Acid by Selected Symbiotic Fermentation Culture by Yu-Chieh Chou, Hui-Wen Lin, Chung-Yi Wang, Chen-Che Hsieh, Shella Permatasari Santoso, Shin-Ping Lin, Kuan-Chen Cheng

“…To optimize the glucuronic acid content in kombucha, various strain combinations by selecting fermented sources were accomplished. According to the experimental results, kombucha produced through co-fermentation with <i>Pichia anomala</i> and <i>Komagataeibacter hansenii</i>, with glucose-added black tea as the carbon source, exhibited the highest glucuronic acid production. …”
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RpiBeh offers a versatile open source solution for rodent behavior tracking and closed loop interventions by Yiqi Sun, Jie Zhang, Qianyun Wang, Jianguang Ni

“…Existing commercial systems are costly and inflexible for customization, while current open-source tools are often lack of real-time functionality and suffer from steep learning curve. …”
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Scientific rationale of ingredients choice for functional fish pastes by A. S. Kupriy, N. I. Dunchenko, E. S. Voloshina

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Forecasting springtime rainfall in southeastern Australia using empirical orthogonal functions and neural networks by S. Marčelja

“…In addition to standard ocean climate indicators such as El Niño or the Indian Ocean Dipole, other typical patterns of variation are captured in terms of the temperatures of selected ocean areas. When characteristic patterns of correlation are discovered, they are included in the predictor selection in the form of expansion in terms of the empirical orthogonal functions (EOFs). …”
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A Self-Adaptive Particle Swarm Optimization Based Multiple Source Localization Algorithm in Binary Sensor Networks by Long Cheng, Yan Wang, Shuai Li

“…Then the maximum likelihood estimator is employed to establish the objective function which is used to estimate the location of sources. …”
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Fast detection method for radionuclides based on Sequential Bayesian approach by WAN Linjian, ZHANG Xuan, ZHANG Chunlei, HUANG Jianwei, LIU Jiacheng, ZHANG Xiaole, LI Dehong, YANG Zhijun

“…Finally, experimental verifications were conducted on the feasibility, detection performance, and universality of the method by placing a set of standard point sources at different distances from the front of a LaBr3(Ce) detection system in both low and natural radiation background environments. …”
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Introduction of AI Technology for Objective Physical Function Assessment by Nobuji Kouno, Satoshi Takahashi, Masaaki Komatsu, Yusuke Sakaguchi, Naoaki Ishiguro, Katsuji Takeda, Kyoko Fujioka, Ayumu Matsuoka, Maiko Fujimori, Ryuji Hamamoto

“…This paper explored how artificial intelligence (AI) could predict physical function scores from various patient data sources and reviewed methods to measure objective physical function using this technology. …”
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Assessment of the capacity of health facilities in preventing and managing non-communicable diseases in selected regions of Somaliland by Opeolu O. Ojo, Omar O Hersi, Ayodele A Falobi, Nura Ali, Lawrence Tan, Yusuf A. Ali

“…The survey focused on assessing the capacity of selected hospitals in detecting and managing NCDs by collecting data on the availability of health workers, equipment, screening and management services, medications, and laboratory tests. …”
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Selection of Suitable Sites for Small Ruminant Production Using Remote Sensing and the Geographic Information System by Halil Baki Ünal, Esin Deri

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Joint Multifractal Analysis and Source Testing of River Level Records Based on Multifractal Detrended Cross-Correlation Analysis by Liang Wu, Manling Wang, Tongzhou Zhao

“…It is important for the detection of change in multifractality in space. Besides, the cross-correlations in two analyzed series make the analysis of sources of joint multifractality difficult. …”
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Data‐Driven Materials Research and Development for Functional Coatings by Kai Xu, Xuelian Xiao, Linjing Wang, Ming Lou, Fangming Wang, Changheng Li, Hui Ren, Xue Wang, Keke Chang

“…In this paper, recent advances in data‐driven materials research and development (R&D) for functional coatings, highlighting the importance, data sources, working processes, and applications of this paradigm are summarized. …”
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First Principles Calculation Guided Material Selection of Poly(propylenemonothiocarbonate) for High-Performance Triboelectric Nanogenerators by Muhammad Naeem Shah, Jiaqi Lu, Dinku Hazarika, Munir Ullah Khan, Srinivasa Rao Pathipati, Kaihang Zhang, Liangquan Xu, Jie Li, Xiaozhi Wang, Shurong Dong, Jikui Luo

“…The advancement of the information era has raised growing interest in triboelectric nanogenerators (TENGs) as environmentally friendly micropower sources. However, most developments to increase the power outputs of TENGs have focused on tribo-negative materials, with limited exploration of tribo-positive materials. …”
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Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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A METHOD FOR INVESTIGATING MACHINE LEARNING ATTACKS ON ARBITER-TYPE PHYSICALLY UNCLONABLE FUNCTIONS by Yuri A. Korotaev

“…This approach allows for a preliminary evaluation of the effectiveness of different algorithms for attacking APUFs without access to challenge-response datasets from real instances of physically unclonable functions. Attacks were conducted on models of basic and modified variants of APUFs from the open-source library "pypuf", using classical logistic regression and artificial neural networks (ANNs). …”
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