Source faulting properties of the 2021 MS 6.4 Yangbi, China, earthquake sequence by Xiangyun Guo, Xu Zhang, Lihua Fang, Dahu Li, Lei Yi

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Predicting anemia management in dialysis patients using open-source machine learning libraries by Takahiro Inoue, Norio Hanafusa, Yuki Kawaguchi, Ken Tsuchiya

“…ML models were developed using PyCaret, an open-source Python library. Performance metrics were compared across models, including XGBoost and LightGBM, to identify the most accurate algorithms. …”
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PyAMARES, an Open-Source Python Library for Fitting Magnetic Resonance Spectroscopy Data by Jia Xu, Michael Vaeggemose, Rolf F. Schulte, Baolian Yang, Chu-Yu Lee, Christoffer Laustsen, Vincent A. Magnotta

“…This study introduces pyAMARES, an open-source Python implementation of AMARES, addressing the need for a flexible, user-friendly, and versatile MRS quantification tool within the Python ecosystem. …”
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K-means and agglomerative clustering for source-load mapping in distributed district heating planning by Amir Shahcheraghian, Adrian Ilinca, Nelson Sommerfeldt

“…This study introduces a high-resolution, data-driven approach for optimizing district heating networks using source-load mapping, focusing on Stockholm as a case study. …”
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Variational autoencoders for at-source data reduction and anomaly detection in high energy particle detectors by Alexander Yue, Haoyi Jia, Julia Gonski

“…To address these challenges, machine learning in readout electronics can be leveraged for smart detector designs, enabling intelligent inference and data reduction at-source. Variational autoencoders (VAEs) offer a variety of benefits for front-end readout; an on-sensor encoder can perform efficient lossy data compression while simultaneously providing a latent space representation that can be used for anomaly detection. …”
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TOA-Based Source Localization: A Linearization Approach Adopting Coordinate System Translation by Shunyuan Sun, Shouhong Zhu, Zhiguo Ding, Baoguo Xu

“…Generally speaking, for such TOA-based source localization, the corresponding observation equations contain nonlinear relationship between measurements and unknown parameters, which normally results in the nonexistence of any efficient unbiased estimator that attains the Cramer-Rao lower bound (CRLB). …”
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Analytical Simulations for Spill Point Source Localization Using Inverse Problems in Closed Form by Vinicius Ribeiro, Jorge Zabadal, Ederson Staudt, Josenilson Marinho, André Silveira, Sidnei Silveira

“…This analytical method offers a valuable tool for efficient and accurate leak source localization, enhancing environmental protection efforts.…”
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City-scale industrial tank detection using multi-source spatial data fusion by Zhibao Wang, Mingyuan Zhu, Lu Bai, Jinhua Tao, Mei Wang, Xiaoqing He, Anna Jurek-Loughrey, Liangfu Chen

“…The integration from multiple data sources provides an accurate and efficient solution for the identification of industrial storage tanks within urban areas.…”
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Advancing the accuracy of clathrin protein prediction through multi-source protein language models by Watshara Shoombuatong, Nalini Schaduangrat, Pakpoom Mookdarsanit, Jaru Nikom, Lawankorn Mookdarsanit

“…In PLM-CLA, we leveraged multi-source pre-trained protein language models (PLMs), which were trained on large-scale protein sequences from multiple database sources, including ProtT5-BFD, ProtT5-UR50, ProstT5, and ESM-2. …”
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ETQ-Matcher: Efficient Quadtree-Attention-Guided Transformer for Detector-Free Aerial–Ground Image Matching by Chuan Xu, Beikang Wang, Zhiwei Ye, Liye Mei

“…We collect 12 pairs of UAV remote sensing images using drones and handheld devices, and we further utilize representative multi-source remote sensing images along with MegaDepth datasets to demonstrate their strong generalization ability. …”
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Energy Audit for Complex Energy System Simulated Using TRNSYS Software by Volodymyr Bezhan, Volodymyr Zhytarenko, Olga Yakovleva, Oleksii Ostapenko, Mykhailo Khmelniuk

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A Cost-Effective and High-Efficiency Novel 15-Level Hybrid MLI Topology for Renewable Energy Systems by Murat Karakılıç, Hasan Hataş

“…In this paper, a new hybrid model for single DC source multilevel inverters (MLIs) is proposed. The proposed switched diode (SD) and high frequency link (HFL) hybrid structure utilizes a single DC source voltage and supplies multiple DC voltages to the PUC circuit. …”
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Waste heat harness in a thermal energy system using TEGs, and SCO2 brayton cycle driven by renewable sources for electricity and liquid hydrogen Production: Thermo-Economic optimiz... by Amr S. Abouzied, Sarminah Samad, Pradeep Kumar Singh, Ahmed H. Janabi, Mohamed Shaban, Asma Ahmed A. Mohammed, Shoira Formanova, H. Elhosiny Ali, Samah G. Babiker, Abdulrahman M. Alansari

“…A detailed techno-economic and environmental model is utilized to assess the system's performance, concentrating on critical indicators such as second law efficiency, total cost rate, hydrogen production rate, net power output, levelized costs, and the rate of CO2 emission reduction. …”
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Transboundary Dispersal Dynamics of <i>Ceracris kiangsu</i>: From Source Regions to Migration Corridors by Yangyang Li, Ting Du, Jun Yao, Yunsen Chen, Lei Shi, Sangzi Ze

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Stress Tolerance and Organic Acid Productivity of Fungal Strains Isolated from Local Agricultural Sources by Christopher Osazuwa

“…Abstract Fungal diversity enhances industrial bioprocess efficiency and innovation. This study was aimed at isolating stress-tolerant fungal strains from local agricultural sources and evaluating their organic acid productivity. …”
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Economic efficiency of energy storage systems for renewable energy power plants integration in the energy system by E. A. Tregubova, M. A. Gorodilov, L. S. Lyushnin

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Determining the efficiency of local heat recycling wastewater based on a heat exchanger by V. A. Kunitskiy, S. V. Lukin

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Gas source and contribution identification for coal measure gas commingled production in Wulihou mining area by NI Xiaoming, FENG Dong, HAO Shaowei, WANG Kai, SU Erlei

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Multi-Source Rainfall Data Assimilation based on Broad Learning System over Yunnan Province by Yuanyuan ZHOU, Xiaohui YANG, Tiangui XIAO

“…The accurate estimation of rainfall is always a topic of concern， given its pivotal role in accurately predicting rainfall-related disasters.This study proposed a multi-source rainfall assimilation technology based on a broad learning system （BLS） to improve the accuracy of rainfall estimation.Yunnan Province， located in China's low-latitude plateau， was chosen as the geographical area of interest to establish a multi-source rainfall assimilation model within this region.In particular， the model utilizes five satellite-derived rainfall datasets （3B42V7， IMERG， GSMaP， CMORPH， PERSIANN） and the latitude and longitude information as the source data， and the ground-based rainfall gauge data serves as the reference data.The time span of all the datasets is from April 2014 to December 2017.A leave-one-year-out cross-validation （LOYOCV） method was applied to verify the performance of the established assimilation model， where statistical indicators including Pearson’s correlation coefficient （CC）， root-mean square error （RMSE）， mean absolute error （MAE）， Nash efficiency coefficient （NSE） and Kling-Gupta efficiency （KGE） were used to quantify the accuracy of assimilation rainfall at different spatiotemporal scales.Concurrently， assimilation models based on support vector machine （SVM） and deep neural network （DNN） were established to highlight the accuracy and efficiency of the BLS， respectively.Additionally， the effectiveness of the latitude and longitude information within the proposed assimilation model was examined.The results show that the daily average statistical index of assimilation rainfall based on BLS is better than that of the other five satellite-based products in LOYOCV.At the temporal scale， the proposed assimilation technique effectively reflects the temporal variations observed in gauge-recorded rainfall.Moreover， it can accurately estimate the rainfall amounts during rainstorms in Yunnan Province throughout 2017.It is worth noting that the rainfall data generated through the BLS method outperforms the CMORPH product （the most accurate one among the five satellite-derived rainfall products） in both rainy and dry seasons （May to October and November to April of next year， respectively）.At the spatial scale， BLS-based rainfall results in most areas of Yunnan Province showed higher CC and NSE as well as smaller RMSE and MAE than the satellite-based products.The evaluation of the assimilation models based on BLS， SVM， and DNN highlights that the BLS exhibits superior functional mapping capabilities compared to SVM and demands fewer computational resources than DNN.It is reasonable to conclude that the multi-source rainfall assimilation approach utilizing the BLS while incorporating latitude and longitude information can enhance the precision of rainfall estimates in Yunnan Province.The proposed method presents practical significance in multi-source rainfall data assimilation.…”
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Transforming waste into value: Advancements in protein recovery and functional product development from wastewater sources by Thirugnanasambandham Karchiyappan, Parameswari Ettiyagounder, Paul Sebastian Selvaraj, Krishnan Ramanujam

“…Other sources, including mung bean, tannery, soybean, silk degumming, dairy, and potato starch wastewater, report recovery exceeding 90 %. …”
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