Biodiversity characteristics of large forest plots in Qinghai area of Qilian Mountain National Park by WANG Dinghui, SUONAN Cairang, YU Hongyan, DU Yangong

“…The coefficients of determination for the training and testing sets of the machine learning model were 0.95 and 0.93, respectively, with root mean square errors of only 0.06 and 0.08. …”
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In pursuit of evidence: A need to transform Ayurvedic education by Sruthi G, Megha

“…We argue that this arises in part from an outdated curriculum, poorly trained teachers, insufficient investment in research infrastructure at teaching colleges, and a paucity of policies to encourage cross-disciplinary learning. To address these gaps, we propose a comprehensive transformation of Ayurvedic education by including biomedical credit courses into the curriculum, practical internships to provide hands-on-experience, recruitment of teachers with biomedical expertise and funds to upgrade Ayurveda colleges. …”
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Smart Filter Performance Monitoring System by Chenxing Pei, Weiqi Chen, Qisheng Ou, David Y. H. Pui

“…Moreover, filter monitoring data can establish a database for researchers to validate the filter models or train a machine learning model for filter performance prediction. Filter or air-cleaning device manufacturers can improve their products or recommend suitable products to their customers based on big data contributed by this filter monitoring system.…”
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Enhanced education on geology by 3D interactive virtual geological scenes by Yuan Fang, Yuxin Li, Lei Fan

“…Their feedback served to validate the effectiveness of the virtual geology site in providing an interactive and enhanced learning experience. Additionally, the study explores the potential for VR to overcome practical challenges associated with traditional field trips, such as accessibility and safety concerns, making it a versatile tool for ongoing and future educational applications in geology and beyond.…”
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Properties of the new N $$ \mathcal{N} $$ = 1 AdS4 vacuum of maximal supergravity by Nikolay Bobev, Thomas Fischbacher, Krzysztof Pilch

“…Abstract The recent comprehensive numerical study of critical points of the scalar potential of four-dimensional N $$ \mathcal{N} $$ = 8, SO(8) gauged supergravity using Machine Learning software in [1] has led to a discovery of a new N $$ \mathcal{N} $$ = 1 vacuum with a triality-invariant SO(3) symmetry. …”
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An estimation method of sound speed profile based on grouped dilated convolution informer model by Siyuan Qin, Yi Zhang, Zhou Chen

“…Traditional methods for acquiring SSP data are often time-consuming and costly. Machine learning techniques provide a more efficient alternative for SSP inversion, effectively addressing the limitations of conventional approaches.MethodsThis study proposes a novel SSP inversion model based on a grouped dilated convolution (GDC) Informer architecture. …”
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Progress on responsive neurostimulation in treatment of drug⁃resistant epilepsy by FAN Xiu⁃liang, BAI Yu⁃tong, YANG An⁃chao, ZHANG Kai

“…This paper aims to review the composition of the RNS, optimization and dyanmic adjustment of stimulation parameters, long⁃term data recording and analysis, fusion with machine learning, clinical efficacy, and comparison with vagus nerve stimulation (VNS). …”
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Awareness and attitudes of pregnant women concerning genetic disorders and pregnancy termination in northeastern Iran by Nafiseh Todarbary, Abouzar Irandegani, Mojtaba Meshkat, Aida Gholoobi, Tayebeh Hamzehloei

“…Additionally, the number of children was correlated with congenital blindness, Duchenne muscular dystrophy, autism, Proteus syndrome, Klinefelter syndrome, anencephaly, mental retardation (MR), quadriplegia, and severe learning disability and mental health (LDMH). Age was associated with conditions such as epilepsy, congenital blindness, schizophrenia, and severe LDMH. …”
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A Watershed Approach to Co-Creating Just Sustainabilities: Reflections from the Lake Superior Living Labs Network by Charles Z. Levkoe, Nairne Cameron, Lindsay P. Galway, Rachel L. W. Portinga, Randy Hanson, Kathryn Milun, Erika Vye

“…Living labs aim to co-create innovative solutions to complex challenges through interdisciplinary, placed-based experiential learning and community-engaged action in the built and natural environments. …”
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Data on battery health and performance: Analysing Samsung INR21700-50E cells with advanced feature engineering by Sahar Qaadan, Aiman Alshare, Alexander Popp, Myrel Tiemann, Utz Spaeth, Benedikt Schmuelling

“…This dataset is particularly valuable for advanced machine learning applications, enabling accurate battery state-of-health estimation and predictive maintenance. …”
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Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL by WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui

“…Based on this，a comprehensive energy system short-term load forecasting model is proposed，which combines complete ensemble empirical mode decomposition with adaptive noise （CEEMDAN），cross optimization algorithm （CSO），long short term memory （LSTM） network，and multi task learning （MTL）. Firstly，preprocess the collected raw load data and calculate the actual load value considering system energy loss； Secondly，the maximum information coefficient （MIC） is used to analyze the correlation between multiple loads and between multiple loads and weather factors，and to extract strongly correlated variables of multiple loads； Once again，the strongly correlated variables of multiple loads are substituted into CEEMDAN，and the load data is decomposed into stationary subsequences； Then，the feature sequence is substituted into the LSTM-MTL shared layer and the CSO algorithm is used to optimize the prediction model，achieving collaborative prediction of multiple loads； Finally，the performance of the constructed model was validated using a multivariate load dataset from a chemical park in Jilin City，Jilin Province，China. …”
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A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits. by Dennis Khodasevich, Nina Holland, Lars van der Laan, Andres Cardenas

“…<h4>Conclusions</h4>We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.…”
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Improvement of reading platforms assisted by the spring framework: A recommendation technique integrating the KGMRA algorithm and BERT model by Yawen Su

“…Concurrently, the BERT model uses deep learning to generate robust semantic representations of article content, enhancing the system's capacity to understand and predict user interests with greater precision. …”
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Grade students attending classes in primary schools and at gymnasiums at national mathematics competitions by Vulović Nenad R., Milenković Aleksandar Z., Milikić Milan P.

“…For decades, mathematics education researchers have been focusing on students with special abilities in mathematics and mathematics competitions, and examining the impact of various organizational forms of work, such as grouping students and enriching teaching and learning programs, on students' success in competitions. …”
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A 20 m spatial resolution peatland extent map of Alaska by Mark J. Lara, Roger Michaelides, Duncan Anderson, Wenqu Chen, Emma C. Hall, Caroline Ludden, Aiden I. G. Schore, Umakant Mishra, Sarah N. Scott

“…Ground-data were used to train machine learning classifiers to detect peatlands using a fusion of Sentinel-1 (Dual-polarized Synthetic Aperture Radar), Sentinel-2 (Multi-Spectral Imager), and derivatives from the Arctic Digital Elevation Model (ArcticDEM), that were spatially constrained by a peatland suitability model. …”
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Decoding Sentiment in Online Communication: A Social Media Analysis of Fashion Companies by Karolina Mania, Monika Jedynak, Aneta Kuźniarska, Karolina Woszczyna

“…Analysis was performed at sentence, document, and aspect levels, employing both lexicon-based methods and machine learning. Findings: The results showed a preponderance of strong positive sentiment among the messages seen on the social media channels of the companies analyzed. …”
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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

“…Medical image analysis methods and computer-aided diagnosis can enhance this process, providing training and assistance to less experienced clinicians. Deep Learning (DL) models play a great role in accurately detecting and classifying cancer in the huge dataset, especially when dealing with large medical images. …”
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Indigenous Environmental Activism and Media Depiction by Raphaela G O Pavlakos

“…The purpose of this article is to elucidate media bias as a way of informing our individual teaching and learning practice, as well as shaping how we engage with and talk about Indigenous issues. …”
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Self-driving lab for the photochemical synthesis of plasmonic nanoparticles with targeted structural and optical properties by Tianyi Wu, Sina Kheiri, Riley J. Hickman, Huachen Tao, Tony C. Wu, Zhi-Bo Yang, Xin Ge, Wei Zhang, Milad Abolhasani, Kun Liu, Alan Aspuru-Guzik, Eugenia Kumacheva

“…Here, we introduce the Autonomous Fluidic Identification and Optimization Nanochemistry (AFION) self-driving lab that integrates a microfluidic reactor, in-flow spectroscopic nanoparticle characterization, and machine learning for the exploration and optimization of the multidimensional chemical space for the photochemical synthesis of plasmonic nanoparticles. …”
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Convolutional Neural Networks for Direction of Arrival Estimation Compared to Classical Estimators and Bounds by Christopher J. Bell, Kaushallya Adhikari, Andrew Brown

“…Recently, there has been a proliferation of applied machine learning (ML) research, including the use of convolutional neural networks (CNNs) for direction of arrival (DoA) estimation. …”
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