Development, implementation and evaluation of consultation case-based learning course to improve the interdisciplinary clinical reasoning ability-a pilot study from nephrology by Weiwei Kong, Ying Huang, Yingying Lu, Xiaoqi Shen, Chong Luo, Biyu Zhang, Yu Lin, Shaohua Chen, Xiayu Li, Fei Han, Jianghua Chen, Ying Xu

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Prevalence of specific learning disability in children and its association with somatic symptom disorder – data from a tertiary care centre of South India by Nishanth Rajan, Priya Jose, Peter Prasanth Kumar Kommu, Shanthi Kannan

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Does age still matter? An age-group comparison of self-efficacy, initial interest and performance when learning bystander resuscitation in secondary schools

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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

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PENGEMBANGAN LKPD BERBASIS DISCOVERY LEARNING BERBANTUAN SOFTWARE TRACKER PADA MATERI GERAK MELINGKAR UNTUK MENINGKATKAN PEMAHAMAN KONSEP PESERTA DIDIK by Sindi Permata Sari, Patricia H M Lubis, Sugiarti Sugiarti

“…Keywords: LKPD, Discovery Learning, Software Tracker, Concept Understanding. …”
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Ab-initio trained machine learning potential for MAX compound Ti2AlC: construction, validation, and study of non linear elasticity by Aishwaryo Ghosh, Amitava Moitra, Tanusri Saha-Dasgupta

Subjects: “…machine learning…”
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VisualCodeMOOC: A course platform for algorithms and data structures integrating a conversational agent for enhanced learning through dynamic visualizations by Mingyuan Li, Duan Wang, Erick Purwanto, Thomas Selig, Qing Zhang, Hai-Ning Liang

“…With instructions structuring, novel response-based algorithm visualization, exercise design, VisualCodeMOOC provides a cohesive and supportive learning environment that promotes active learning. …”
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An integrated evaluation framework – smartness, well-being, e-maturity – for participatory evaluation of learning ecosystems: first application to two Italian high schools by Carlo Giovannella

“… In this contribution, after a brief analysis of the critical issues associated with learning ecosystem evaluation frameworks, a participatory evaluation approach is proposed that aims to: (a) be people-centered and bring out the perceptions of all categories involved in educational processes – with particular reference to students, teachers and parents; this is in order to mitigate the objectivity bias associated with self-evaluations conducted by internal evaluation teams by means of top-down evaluation models; b) base the evaluation on an integrable set of multidimensional constructs such as smartness – capable of capturing both the “external” well-being associated with the quality of the context and the well-being perceived at an individual level – and e-maturity, i.e. the digital maturity of the context that defines its positioning (vision, plans and actions) with respect to the potential and opportunities offered by the digital transition; c) provide reference values with the intention of making evaluations of educational ecosystems both synchronically and diachronically comparable, as well as allowing for the elaboration of an adequate base of knowledge to facilitate the elaboration of improvement plans and to support evidence-based decision-making. …”
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HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ Mapping in the Knee Joint by Dilbag Singh, Ravinder R. Regatte, Marcelo V. W. Zibetti

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What makes health systems resilient? An analytical framework drawing on European learnings from the COVID-19 pandemic based on a multitiered approach by Thomas Czypionka, Markus Kraus, Miriam Reiss, Monika Riedel

“…In the face of a shock, adequate response strategies need to be developed. An essential learning from the COVID-19 pandemic has been that contextual factors of societies and subgroups play a major role in the ability of health systems to overcome a shock, as they impact the implementation and effectiveness of crisis management policies.…”
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Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients by Chaoqun Huang, Shangzhi Shu, Miaomiao Zhou, Zhenming Sun, Shuyan Li

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RUS DİLİNDEKİ İFADE ZENGİNLİĞİNİN ÇEVİRİ BİLİMİNE VE RUSÇA ÖĞRENİMİNE KATKISI / CONTRIBUTION OF THE ABUNDANCE OF EXPRESSIONS IN RUSSIAN LANGUAGE TO TRANSLATING AND LEARNING RUSSIAN by Leyla DALKILIÇ

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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification. by Saleem Mustafa, Arfan Jaffar, Muhammad Rashid, Sheeraz Akram, Sohail Masood Bhatti

“…This paper offers a cutting-edge hybrid deep learning approach of better segmentation and classification of skin lesions. …”
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Metacognition & learning process: Using think-aloud protocol (TAP) to understand students and their teacher’s reflection processes during a problem-solving situation by O. Bouiri, S. Lotfi, M. Talbi

Subjects: “…learning process…”
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Rational emotive behavior therapy for reducing adolescent anxiety in post-covid-19 pandemic online learning: group approach and single case design by I Dewa Ayu Eka Purba Dharma Tari, I Made Mahaardhika

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Building a near-infrared (NIR) soil spectral dataset and predictive machine learning models using a handheld NIR spectrophotometerZenodo by Colleen Partida, Jose Lucas Safanelli, Sadia Mannan Mitu, Mohammad Omar Faruk Murad, Yufeng Ge, Richard Ferguson, Keith Shepherd, Jonathan Sanderman

“…All scanning was performed on dried and sieved (<2 mm) soil samples. Machine learning predictive models were developed for soil organic carbon (SOC), pH, bulk density (BD), carbonate (CaCO3), exchangeable potassium (Ex. …”
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Prediction of microvascular obstruction from angio-based microvascular resistance and available clinical data in percutaneous coronary intervention: an explainable machine learning model by Zhe Zhang, Yang Dai, Peng Xue, Xue Bao, Xinbo Bai, Shiyang Qiao, Yuan Gao, Xuemei Guo, Yanan Xue, Qing Dai, Biao Xu, Lina Kang

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Prediction and unsupervised clustering of fertility intention among migrant workers based on machine learning: a cross-sectional survey from Henan, China by Xinghong Guo, Mingze Ma, Yiyang Chen, Zhaoyang Fang, Jingru Liu, Shuming Yan, Yifei Feng, Xinya Cheng, Jian Wu, Beizhu Ye

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What We Didn’t Know a Recipe Could Be: Political Commentary, Machine Learning Models, and the Fluidity of Form in Nineteenth-Century Newspaper Recipes by Avery Blankenship

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A simple model for Behavioral Time Scale Synaptic Plasticity (BTSP) provides content addressable memory with binary synapses and one-shot learning by Yujie Wu, Wolfgang Maass

“…We introduce a transparent model for the core function of this learning rule and establish a theory that enables a principled understanding of the system of memory traces that it creates. …”
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