Multi-Channel Underwater Acoustic Signal Analysis Using Improved Multivariate Multiscale Sample Entropy by Jing Zhou, Yaan Li, Mingzhou Wang

“…When processing real-world underwater acoustic signals, traditional multivariate entropy algorithms often struggle to simultaneously ensure stability and extract cross-channel information. To address these issues, the improved multivariate multiscale sample entropy (IMMSE) algorithm is proposed, which extracts the complexity of multi-channel data, enabling a more comprehensive and stable representation of the dynamic characteristics of complex nonlinear systems. …”
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Emotional distress during the first year of the COVID-19 pandemic-large sample serbian study by Bojana Dunjic-Kostic, Marija Mitkovic-Voncina, Jelena Jovic, Emilija Eric, Marta Gostiljac, Stefan Jerotic, Nikola Lalovic, Milan Latas, Maja Pantovic-Stefanovic

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Small sample smart contract vulnerability detection method based on multi-layer feature fusion by Jinlin Fan, Yaqiong He, Huaiguang Wu

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Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling by Eliott Park, Saeed Izadi

“…Based on our benchmarking analysis, we propose six in silico developability risk flags and assess their effectiveness in predicting potential developability issues for a set of case study molecules.…”
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AMCL: supervised contrastive learning with hard sample mining for multi-functional therapeutic peptide prediction by Jiwei Fang, Henghui Fan, Jintao Zhao, Jianping Zhao, Junfeng Xia

“…AMCL incorporates a semantic-preserving data augmentation strategy, a multi-label supervised contrastive learning mechanism with hard sample mining, and a weighted combined loss combining Focal Dice Loss (FDL) and Distribution-Balanced Loss (DBL) to alleviate class imbalance issues. …”
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The Accuracy of the Step Point Vegetation Sampling Method for Herbaceous Layer Monitoring in South African Savannas by Armand A. Biko’o, Willem J. Myburgh, Brian K. Reilly

“…However, it is often considered inaccurate in describing vegetation dynamics in the savanna herbaceous layer due primarily to issues with sample sizes and cover estimates, its inability to capture the spatial heterogeneity and patchy distribution typical of these ecosystems, sensitivity to observer bias, reliance on relative values and poor inclusion of sparse or less common species. …”
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Automatic generation of high-quality building samples using OpenStreetMap and deep learning by Ming Zhao, Chenxiao Zhang, Zhen Gu, Zhipeng Cao, Chuanwei Cai, Zhaoyan Wu, Lianlian He

“…Crowdsourced OpenStreetMap (OSM) data, with its extensive volume and openness, is widely used for annotation purposes. However, issues such as missing quality information and poor data completeness have hindered its potential to generate deep-learning samples. …”
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Southern Vietnamese women’s views on HPV vaccination, cervical cancer screening, and HPV self-sampling by Minh Tung Phung, Pham Le An, Lilah Khoja, Alice W. Lee, Celeste Leigh Pearce

“…Three main themes emerged: (1) barriers to prevention included low knowledge, logistical and psychological challenges, and issues related to healthcare providers; (2) participants viewed HPV self-sampling positively, although concerns about incorrect self-sampling and mailing logistics were noted; (3) participants generally accepted cervical cancer prevention and drew parallels to COVID-19 prevention, suggesting similar public health approaches. …”
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DSGAU: Dual-Scale Graph Attention U-Nets for Hyperspectral Image Classification With Limited Samples by Hongzhuang Ji, Leying Song, Zhaohui Xue, Hongjun Su

“…Nevertheless, prevalent graph pooling techniques often employ single-scale strategies that inadequately capture multiscale features, potentially leading to information loss or redundancy. To address this issue, we propose a dual-scale graph attention U-Nets for HSI classification with limited samples. …”
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Validation of two swabbing methods to sample DNA for genotyping Atlantic bluefin tuna (Thunnus thynnus) by D. Righton, F. Garzon, L. A. Hawkes, R. Hicks, T. Horton, M. Ives, I. Katsiadaki, S. R. McCully Phillips, S. Roslyn, M. Sebire, D. Stone, M. J. Witt, S. Wright, N. J. McKeown

“…All six microsatellites were successfully amplified including a largest allele size of 291 bp. mtDNA and microsatellite genotypes for the skin swabs matched with the corresponding fin clip samples. Although no tissue replicates were available for the pole swab samples the genotypes obtained were unambiguous, consistent across repeated PCRs, and reported no evidence of PCR issues such as large allele drop out. …”
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Socioeconomic and Health Impacts of Dust Storms in Southwest Iran by Neamat MalAmiri, Alireza Rashki, Ali Al-Dousari, Dimitris G. Kaskaoutis

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A review of deep learning-based few sample fault diagnosis method for rotating machinery by Ke WU, Jun WU, Qiming SHU, Weiming SHEN, Wenbin SONG

“…Domain generalization can enhance the model performance in unknown domains but may suffer from overfitting issues. Data augmentation can increase dataset diversity but may generate inconsistent samples. …”
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A sensitive sample preparation pipeline for adventitious virus detection using Oxford Nanopore sequencing by Emmanuel K. Tsinda, Charles A. Swofford, James P.B. Strutt, José Sangerman, Raeuf Roushangar, Alexander Li, Lara M. Gomez, Aidan N. Bousquet, Caleb Neufeld, Jacqueline M. Wolfrum, Jongyoon Han, Rohan B.H. Williams, Anthony J. Sinskey, Paul W. Barone, Stacy L. Springs

“…Oxford Nanopore sequencing can address these issues, as it provides real-time basecalling and sequence alignment, which can reduce the overall assay time. …”
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Increasing belief but issue fatigue: Changes in Australian Household Climate Change Segments between 2011 and 2016. by Mark Morrison, Kevin Parton, Donald W Hine

“…We found that a greater proportion of households have personally experienced climate change, and were more likely to believe in human causation and believe that there is a scientific consensus about the issue. However, there was evidence of issue fatigue. …”
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ELO-Mask: Effective and Layerwise Optimization of Mask for Sparse LLMs by Bingjie Xiang, Jiarui Wu, Xiaoying Han, Qian Gu, Fei Chao, Xiao Yang, Fan Wu, Xin Fu

“…To address the issue of the substantial computational resource consumption during the inference phase of large language models due to their vast number of parameters, model sparsification is an effective solution. …”
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Enhancing Cropland Mapping with Spatial Super-Resolution Reconstruction by Optimizing Training Samples for Image Super-Resolution Models by Xiaofeng Jia, Xinyan Li, Zirui Wang, Zhen Hao, Dong Ren, Hui Liu, Yun Du, Feng Ling

“…The results indicate that the samples acquired by the histogram-matched GF-2 and degraded GF-2 images can resolve spectral band mismatches when simulating training samples from fine spatial resolution imagery, while the other three methods have limitations in their inability to fully address spectral and spatial mismatches. …”
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Betacyanins, nitrates and the issue of standardization in red beetroot (Beta vulgaris L.) extracts and powders sold online by Marco Gozzi, Guillem Campmajó, Chiara Dall’Asta, Laura Righetti, Martina Cirlini, Marco Biagi, Renato Bruni

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Fostering Critical Thinking through Socio-Scientific Issue-Based Problem-Based Learning in Stoichiometry Instruction by Aida Hajijah, Mariam Nasution, Nur Azizah Putri Hasibuan, Lelya Hilda, Najah Yousef Baroud

“…Understanding stoichiometry remains a significant challenge for many secondary school students, primarily due to traditional instructional approaches that emphasize memorization rather than analytical reasoning. To address this issue, this study examines the effectiveness of a socio-scientific issue (SSI)-based problem-based learning (PBL) model in fostering students’ critical thinking skills in stoichiometry instruction. …”
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Detection of Dairy Herd Management Issues Using Fatty Acid Profiles Predicted by Mid-Infrared Spectrometry by Sébastien Franceschini, Claire Fastré, Charles Nickmilder, Débora E. Santschi, Daniel Warner, Mazen Bahadi, Carlo Bertozzi, Didier Veselko, Frédéric Dehareng, Nicolas Gengler, Hélène Soyeurt

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Meta-analysis of supervisor support and postgraduate creativity: evidence from a sample of Chinese students by Qiaoli Chang, Hui Han, Dexin Hu

“…IntroductionWith the growing number of Chinese postgraduate students, enhancing their creativity has become a pressing issue in Chinese higher education. This meta-analysis aimed to investigate the relationship between supervisor support and postgraduate creativity using a sample of Chinese students and to explore potential moderating variables.MethodThe study incorporated 62 primary studies involving 51,640 Chinese graduate students.ResultsThe results revealed that supervisor support was significantly and positively associated with postgraduate creativity. …”
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