A fluorescence-enhanced inverse opal sensing film for multi-sources detection of formaldehyde by Xiaokang Lu, Bo Han, Deyilei Wei, Mingzhu Chu, Haojie Ma, Ran Li, Xueyan Hou, Yuqi Zhang, Jijiang Wang

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New source of cellulase production using a metagenomic technique by Safaa M. Ali, Nadia A. Soliman

“…In the outlook, the metagenomic guide approachs may be functional to the elevated selection of novel cellulase from the environment.…”
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Development of an effectiveness evaluation model of the security management function of radiological facilities by Alexandre Roza de Lima, Francisco Cesar Augusto Da Silva, Thiago Pereira Germano

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Development of Time-Reversal Method for Impact Source Identification on Plate Structures by Chunlin Chen, Yulong Li, Fuh-Gwo Yuan

“…A number of parameters selected for determining the impact location, approximated transfer functions and steps taken for reconstructing the impact loading time-history are also examined. …”
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Applicability and Design Considerations of Chaotic and Quantum Entropy Sources for Random Number Generation in IoT Devices by Wieslaw Marszalek, Michał Melosik, Mariusz Naumowicz, Przemysław Głowacki

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Grape Seed Powders as a Source of Phenolic Compounds: UHPLC Orbitrap MS4 Characterization by Danijel D. Milinčić, Uroš Gašić, Aleksandar Ž. Kostić, Slađana P. Stanojević, Živoslav Lj. Tešić, Mirjana B. Pešić

“…Grape seeds represent a rich source of phenolic compounds that exhibit various health benefits. …”
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Municipal secondary-treated effluent data seem to be a suitable source of information for human viral trends by Elsa T. Rodrigues, Joana M. Oliveira, Anália Carmo, Miguel A. Pardal, Ana M. Matos

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Potential Source Density Function: A New Tool for Identifying Air Pollution Sources by In Sun Kim, Yong Pyo Kim, Daehyun Wee

“…Abstract Potential source density function (PSDF) is developed to identify, that is, locate and quantify, source areas of ambient trace species based on Gaussian process regression (GPR), a machine-learning technique. …”
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Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features by Daniel Hilário da Silva, Caio Tonus Ribeiro, Leandro Rodrigues da Silva Souza, Adriano Alves Pereira

“…Seventeen ML algorithms were applied to a dataset of voice recordings from Healthy Control and PD individuals, sourced from a publicly available repository. We leveraged the PyCaret Python library's ML algorithms and functions, which were introduced in this article, to demonstrate their simplicity and effectiveness in dealing with real-world data. …”
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Near-source wastewater surveillance of SARS-CoV-2, norovirus, influenza virus and RSV across five different sites in the UK. by Jay C Bullen, Mina Mohaghegh, Fatima Tahir, Charlotte Hammer, Jacob Sims, Frederico Myers, Lucas Eisinger, Ali Reza Kasmati, Claire F Trant

“…The key findings are (1) near-source wastewater detections were linked to local events (staff sickness, enhanced cleaning, changing populations); (2) wastewater detections decreased in the order norovirus GII > norovirus GI > SARS-CoV-2 ≈ influenza A ≈ RSV A > influenza B ≈ RSV B; (3) correlation between near-source wastewater data and national surveillance data increases as a function of catchment size and viral prevalence (examples include the SARS-CoV-2 BA.4/BA.5 variant peak at a museum and wastewater tracking the winter norovirus season); (4) strong weekday periodicity in near-source wastewater SARS-CoV-2 detections, with the correlation against COVID-19 case numbers increasing when modelling variable lag times between faecal shedding onset and clinical diagnosis (R2 = 0.45 increases to 0.84-0.86); (5) a log-linear relationship between the frequency of wastewater SARS-CoV-2 detection and log(catchment size⋅viral prevalence) (R2 = 0.6914-0.9066). …”
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On Data Selection and Regularization for Underdetermined Vibro-Acoustic Source Identification by Laixu Jiang, Jingqiao Liu, Xin Jiang, Yuezhao Pang

“…The number of hologram points in near-field acoustical holography (NAH) for a vibro-acoustic system plays a vital role in conditioning the transfer function between the source and measuring points. The requirement for many overdetermined hologram points for extended sources to obtain high accuracy poses a problem for the practical applications of NAH. …”
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SELECTION FEATURES OF THE FIELDS REPRESENTATION FOR THE ADDITIONAL SOURCES OF THE PARTIAL DOMAINS by A.P. ZVEREV

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Development and validation of microwave-assisted extraction for phenolic compound profiling in diverse oyster mushrooms (Pleurotus spp.) sourced from various geographical regions by M Umar Harun, Miguel Palma, Widiastuti Setyaningsih

“…This study aimed to develop and validate a microwave-assisted extraction (MAE) method for profiling phenolic compounds in a diverse selection of oyster mushrooms (Pleurotus spp.) sourced from multiple geographical regions. …”
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A Decision Support System for Optimal Building Cold Source Selection by Qing Li, Yan Dong, Rong-Guang Cao, Le Li, Zhi-Bin Chen

“…Based on existing approaches to construction project evaluation and the selection of cold source systems, we establish an evaluation index for building cold source system functional models and network structures. …”
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ABDviaMSIFAT: Abnormal Crowd Behavior Detection Utilizing a Multi-Source Information Fusion Technique by Ali Ahmad Hamid, S. Amirhassan Monadjemi, Bijan Shoushtarian

“…To solve this issue, we suggest a new method that combines data from various sources with different characteristics to enhance the precision of detecting human behavior in crowds. …”
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Flickers, Bursts, and Dips: Detecting Rapid Variability with the g(2) Autocorrelation Function by Brian C. Lacki

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Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
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Feature dependence graph based source code loophole detection method by Hongyu YANG, Haiyun YANG, Liang ZHANG, Xiang CHENG

“…Given the problem that the existing source code loophole detection methods did not explicitly maintain the semantic information related to the loophole in the source code, which led to the difficulty of feature extraction of loo-phole statements and the high false positive rate of loophole detection, a source code loophole detection method based on feature dependency graph was proposed.First, extracted the candidate loophole statements in the function slice, and gen-erated the feature dependency graph by analyzing the control dependency chain and data dependency chain of the candi-date loophole statements.Secondly, the word vector model was used to generate the initial node representation vector of the feature dependency graph.Finally, a loophole detection neural network oriented to feature dependence graph was constructed, in which the graph learning network learned the heterogeneous neighbor node information of the feature de-pendency graph and the detection network extracted global features and performed loophole detection.The experimental results show that the recall rate and F1 score of the proposed method are improved by 1.50%～22.32% and 1.86%～16.69% respectively, which is superior to the existing method.…”
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Selenium Accumulating Leafy Vegetables Are a Potential Source of Functional Foods by Petro E. Mabeyo, Mkabwa L. K. Manoko, Amra Gruhonjic, Paul A. Fitzpatrick, Göran Landberg, Máté Erdélyi, Stephen S. Nyandoro

“…., Cucurbita maxima, Ipomoea batatas, Solanum villosum, Solanum scabrum, and Vigna unguiculata were explored for their capabilities to accumulate selenium when grown on selenium enriched soil and for use as a potential source of selenium enriched functional foods. Their selenium contents were determined by spectrophotometry using the complex of 3,3′-diaminobenzidine hydrochloride (DABH) as a chromogen. …”
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Derivation of pressure distribution models for horizontal well using source function by J.O. Oloro, E.S. Adewole

“…In this work, ten (10) models for pressure distribution for horizontal well under different boundary variation were derived following these steps for each of the models:(i) choosing a boundary condition for each axis (ii) selecting the appropriate source function for each axis and (iii)applying Newman product rule to arrive at the pressure expression. …”
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