A meta-analysis of the effect of protein synthesis inhibitors on rodent fear conditioning by Carneiro, Clarissa F. D., Amorim, Felippe E., Amaral, Olavo B.

“…In this work, we studied protein synthesis inhibition, a classic intervention used to disrupt fear learning, reconsolidation, and extinction in rodents, to explore how meta-analyses can identify potential moderators of its effect. …”
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MLDFNet: A Multilabel Dual-Flow Network for Change Detection in Bitemporal Remote Sensing Images by Daniyaer Sidekejiang, Panpan Zheng, Liejun Wang

“…With the development of deep learning (DL) in recent years, numerous remote sensing image change detection (CD) networks have emerged. …”
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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“…We argue that this arises in part from an outdated curriculum, poorly trained teachers, insufficient investment in research infrastructure at teaching colleges, and a paucity of policies to encourage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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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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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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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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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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The Importance of Breakfast in Enhancing Students' Focus at School by Nurul Widad Fitri Muhammad, Nur Aina Mardhiah Che Rahim, Amrina Rasyada Kamaruzaman, Noor Fatimah Mujahid, Khairulnazrin Nasir

“…Students who skip breakfast will become hungry, which can disrupt their learning. Islam, as a complete faith, emphasises eating healthy meals. …”
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Synchronization-based graph spatio-temporal attention network for seizure prediction by Jie Xiang, Yanan Li, Xubin Wu, Yanqing Dong, Xin Wen, Yan Niu

“…In recent years, a large number of studies have been conducted using deep learning models on epileptic open electroencephalogram (EEG) datasets with good results, but due to individual differences there are still some subjects whose seizure features cannot be accurately captured and are more difficult to differentiate, with poor prediction results. …”
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Living Group Mosaic Family: participation of people with disabilities in the community by Marta Aoki, Fátima Correa Oliver, Ariane Bazarin de Campos Cancegliero, Júlia Colussi

“…Joining the group promoted emotional changes, discoveries of skills, promotion of care and learning, self-esteem and communication improvement among participants. …”
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