Experimental investigation of solar PVT collector with the dryer on mass and temperature of dried red chili with Machine Learning Models by Miroslav Mahdal, K. Rajathi, Muniyandy Elangovan, Prabhukumar Sellamuthu, Amit Verma

“…The drying process was stop at 11 % moisture content after 6-day testing round of red chilies drying. Machine learning (ML) models, namely the Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Decision Tree (DT), were used to forecast the temperature and mass dryness variables.The RBF model showed the best performance with 0.98, 0.95, and 0.92 for temperature dryness, above MLP and DM. …”
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Multi-Scale Long- and Short-Range Structure Aggregation Learning for Low-Illumination Remote Sensing Imagery Enhancement by Yu Cao, Yuyuan Tian, Xiuqin Su, Meilin Xie, Wei Hao, Haitao Wang, Fan Wang

“…It features flexible architecture for exploiting features at different scales of the input low illumination (LI) image, with branches including a short-range structure learning module and a long-range structure learning module. …”
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Tackling the Optimal Phasor Measurement Unit Placement and Attack Detection Problems in Smart Grids by Incorporating Machine Learning by Ramzi Al-Sharawi, Abdelfatah Ali, Mostafa Shaaban, Nasser Qaddoumi, Mohamed S. Abdalzaher

“…Thus, this paper proposes a novel approach by formulating this issue as a tri-objective functions optimization problem. The proposed approach optimizes PMU allocation to maximize topological observability and minimize system cost while improving the FDIA detection performance using machine learning. …”
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XGBoost-based machine learning model combining clinical and ultrasound data for personalized prediction of thyroid nodule malignancy by Wenhan Li, Wenhan Li, Yajing Zhou, Ziyu Luo, Ziyu Luo, Miao Tan, Miao Tan, Rui Yin, Jianhui Li, Jianhui Li

“…Features included demographic, ultrasound, and thyroid function indices. Random Forest (RF) and Lasso regression were used for feature selection. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. …”
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Can sign-naïve adults learn about the phonological regularities of an unfamiliar sign language from minimal exposure? by Chloe Marshall, Julia Hofweber, Lizzy Aumônier, Marianne Gullberg, Vikki Janke

“…In this study, we examined whether such implicit statistical learning mechanisms operate in the visual modality. …”
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Identification of biomarkers for the diagnosis of chronic kidney disease (CKD) with dilated cardiomyopathy (DCM) by bioinformatics analysis and machine learning by Yuhang Liu, Yuhang Liu, Yong Wang, Wenyang Nie, Wenyang Nie, Zhen Wang

“…MNS1 and HERC6 are implicated in metabolism, inflammation, immunity, and heart function. Immune cell infiltration analysis indicated dysregulation in DCM, with MNS1 and HERC6 correlating with immune cells. …”
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Machine Learning Based Localization of LoRa Mobile Wireless Nodes Using a Novel Sectorization Method by Madiyar Nurgaliyev, Askhat Bolatbek, Batyrbek Zholamanov, Ahmet Saymbetov, Kymbat Kopbay, Evan Yershov, Sayat Orynbassar, Gulbakhar Dosymbetova, Ainur Kapparova, Nurzhigit Kuttybay, Nursultan Koshkarbay

“…Analysis of the cumulative error distribution function revealed the average localization error of 0.384 m, while the mean absolute error reached 0.246 m. …”
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A deep learning-based detection model and illumination-adaptive behavioral analysis for soldier crabs in the intertidal zone by Liangjun Li, Zhihao Ren, Cheng Tang, Shengning Lu, Yong Liang

“…The model integrates an SPD-Conv module for efficient downsampling, a fine-grained channel attention mechanism for enhanced feature representation, and a robust SIoU loss function to improve the localization of small targets. …”
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A New Immersion and Invariance Control and Stable Deep Learning Fuzzy Approach for Power/Voltage Control Problem by Mohammad Hosein Sabzalian, Khalid A. Alattas, Mauricio Aredes, Abdullah K. Alanazi, Hala M. Abo-Dief, Ardashir Mohammadzadeh, Saleh Mobayen, Bruno Wanderley Franca, Afef Fekih

“…The uncertainties are compensated by the new optimization rules based on Immersion and Invariance (I&I) theorem and proposed deep learning type-2 fuzzy logic compensator (T2FLC). The objective function of T2FLC is to minimize the tracking error in presence of perturbations. …”
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Fish keypoint detection for offshore aquaculture: a robust deep learning approach with PCA-based shape constraint by Gen Li, Gen Li, Anji Lian, Zidan Yao, Yu Hu, Yu Hu, Guoliang Pang, Guoliang Pang, Taiping Yuan, Taiping Yuan, Zhenhua Li, Xiaohua Huang, Xiaohua Huang, Gang Wang

“…As a result, output keypoints of such networks do not always conform to the shape of a fish and the training process can be affected by incorrect labels, leading to errors in subsequent tasks.MethodsTo address these issues, this paper proposes a robust deep learning approach characterized by three improvements. 1) A shape model of fish that includes the average shape of fish, principal components of fish keypoints, and corresponding eigenvalues is constructed using principal component analysis (PCA) and unscented transform. 2) A customized version of anchor boxes is introduced and referred to as “anchor fish”, which along with the shape model, can be used to encode and decode fish keypoints. 3) Shape variation loss, calculated based on the eigenvalues in the shape model, is added as part of the loss function to constrain the output of the regression head. …”
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Evaluation of vascular cognitive impairment and identification of imaging markers using machine learning: a multimodal MRI study by Haoying He, Dongwei Lu, Sisi Peng, Jiu Jiang, Fan Fan, Dong Sun, Tianqi Sun, Zhipeng Xu, Ping Zhang, Xiaoxiang Peng, Ming Lei, Junjian Zhang

“…BackgroundVascular cognitive impairment (VCI) is prevalent but underdiagnosed due to its heterogeneous nature and the lack of reliable diagnostic tools. Machine learning (ML) enhances disease evaluation by enabling accurate prediction and early detection from complex data. …”
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Deep-learning-based sub-seasonal precipitation and streamflow ensemble forecasting over the source region of the Yangtze River by N. Dong, H. Hao, H. Hao, M. Yang, J. Wei, S. Xu, H. Kunstmann, H. Kunstmann, H. Kunstmann

“…At sub-seasonal scales, readily available hydrometeorological forecast products often exhibit large uncertainties and insufficient accuracies to support decision-making. We propose a deep-learning-based modelling framework for sub-seasonal joint precipitation and streamflow ensemble forecasts for a lead time of up to 30 d. …”
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Investigation of a chest radiograph-based deep learning model to identify an imaging biomarker for malnutrition in older adults by Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, Takahito Nishihara, Masafumi Haraguchi, Masanori Fukushima, Ryu Sasaki, Satoshi Miuma, Hisamitsu Miyaaki, Kazuhiko Nakao

“…Summary: Background & Aims: In recent years, artificial intelligence (AI) models based on chest radiography have gained attention in various fields, including cardiac function, age estimation, and clinical assessment during hospitalization. …”
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Low-carbohydrate diet score and chronic obstructive pulmonary disease: a machine learning analysis of NHANES data by Xin Zhang, Jipeng Mo, Kaiyu Yang, Tiewu Tan, Cuiping Zhao, Hui Qin

“…BackgroundRecent research has identified the Low-Carbohydrate Diet (LCD) score as a novel biomarker, with studies showing that LCDs can reduce carbon dioxide retention, potentially improving lung function. While the link between the LCD score and chronic obstructive pulmonary disease (COPD) has been explored, its relevance in the US population remains uncertain. …”
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Machine learning integration of single-cell and bulk transcriptomics identifies fibroblast-driven prognostic markers in colorectal cancer by Ning Zhang, Ruiyan Liu, Siya Wu, Chenxi Feng, Boxiang Wang, Qiaoqiao Zheng, Linru Jie, Ruihua Kang, Xiaoli Guo, Xiaoyang Wang, Shaokai Zhang, Jiangong Zhang

“…Functional enrichment analyses revealed that this signature is involved in immune regulation and multiple tumor-associated cellular pathways. …”
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Skin hyperspectral imaging and machine learning to accurately predict the muscular poly-unsaturated fatty acids contents in fish by Yi-Ming Cao, Yan Zhang, Qi Wang, Ran Zhao, Mingxi Hou, Shuang-Ting Yu, Kai-Kuo Wang, Ying-Jie Chen, Xiao-Qing Sun, Shijing Liu, Jiong-Tang Li

“…With the skin spectra of fish, five ML methods, including the extreme learning machine (ELM), random forest (RF), radial basis function (RBF), back propagation (BP), and least squares support vector machine (LS-SVM) methods, were used to predict the PUFAs and EPA + DHA contents. …”
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Instrumente digitale și abordări noi în lucrul profesorului modern la organizarea învățământului mixt by Iuliana Vladimirovna BOBROVA

“… The article discusses modern digital tools and services designed for a variety of purposes. The functionality of some educational platforms and sites is listed. …”
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Fosab, but not fosaa, plays important role in learning and memory in fish—insights from zebrafish gene knockout study by Qiuling Wang, Qiuling Wang, Qiuling Wang, Lixin Zhang, Lixin Zhang, Lixin Zhang, Chenyuan Zhu, Chenyuan Zhu, Chenyuan Zhu, Ke Lu, Ke Lu, Ke Lu, Jiaqi Wu, Jiaqi Wu, Jiaqi Wu, Xu-Fang Liang, Xu-Fang Liang, Xu-Fang Liang

“…Additionally, the phylogenetic and multiple amino acid alignment results indicated that fish fosab has a higher identity with mammals Fos.Discussion: By integrating the above results, we found that fosab, but not fosaa, may possess a learning and memory function in fish. For the first time, we illustrated the role of fosaa and fosab in learning and memory via c-fos knockout in fish, which can provide new insights into environmental adaptation.…”
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THE EFFECT OF PROJECT-BASED LEARNING (PJBL) USING PIZZALUV-MATHEMATICS MEDIA ON SELF-EFFICACY AND 4C SKILLS by Akhsanul In'am, Moh. Mahfud Effendi, Rani Darmayanti

“…This study was conducted on twelfth-grade students at MAN 2 Malang, Indonesia, in the context of algebraic function limits. Pizzaluv-Mathematics media is designed to help students complete learning projects through communication, collaboration, and critical and creative thinking in making a "Love" shaped math pizza using visual media. …”
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