Development of a Human-Centric Autonomous Heating, Ventilation, and Air Conditioning Control System Enhanced for Industry 5.0 Chemical Fiber Manufacturing by Madankumar Balasubramani, Jerry Chen, Rick Chang, Jiann-Shing Shieh

“…This research presents an advanced autonomous HVAC control system tailored for a chemical fiber factory, emphasizing the human-centric principles and collaborative potential of Industry 5.0. …”
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Ventral hippocampus to nucleus accumbens shell circuit regulates approach decisions during motivational conflict. by Dylan Patterson, Nisma Khan, Emily A Collins, Norman R Stewart, Kian Sassaninejad, Dylan Yeates, Andy C H Lee, Rutsuko Ito

“…Converging human and animal research has implicated the anterior/ventral hippocampus (vHPC) as a key node in arbitrating AAC in a region-specific manner. …”
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Human Sensitivity to Community Structure Is Robust to Topological Variation by Elisabeth A. Karuza, Ari E. Kahn, Danielle S. Bassett

“…The extent to which behavioral signatures of learning are robust to changes in community size and number is the focus of the present work. …”
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Dynamic equivalent modelling for active distributed network considering adjustable loads charging characteristics by Jingwen Wang, Jiehui Zheng, Zhigang Li, Qing‐Hua Wu

“…From the simulation results, the present method is effective.…”
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Drawing a Scientific Map and Analyzing the Co-occurrence Network of Master's Dissertations and Doctoral Theses in Mathematics Education at Iranian Universities by Vahideh Soleymani Rad, Younes Karimi Fardinpour, Mohammad Hassan Behzadi, Ahmad Shahvarani Semnani

“…One of the most important indicators in social network analysis is centrality, which comes in various forms and indicates the positions of specific nodes within the network. In the present study, three types of centrality indicators, namely degree centrality, betweenness centrality, and closeness centrality, were utilized. …”
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An assessment of applications of digital health in Iran: A scientometric study by Abdolahad Nabiolahi, Hassan Shojaee-Mend, Abdoljavad Khajavi, Mohsen Sahebanmaleki

“…In addition, the scientific map showed that out of 198 nodes, the four main clusters in the field of digital health in Iran, including deep learning, mobile-based programs, humans, virtual reality and artificial intelligence, have been considered more, and in areas such as COVID-19, pregnancy and other subcategories, mobile phone-based programs have been developed. …”
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A novel end-to-end privacy preserving deep Aquila feed forward networks on healthcare 4.0 environment by Ponugoti Kalpana, Sunitha Tappari, L. Smitha, Dasari Madhavi, K. Naresh, Maddala Vijayalakshmi

“…This evokes a need for designing intelligent systems to eradicate data breaches and privacy problems. This research presents a groundbreaking framework that uniquely combines privacy-preserving optimized deep learning to effectively diagnose cardiac troubles utilizing edge and fog computing devices. …”
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Passive localization based on radio tomography images with CNN model utilizing WIFI RSSI by Muhammad Jabbar, Umar Shoaib

“…We have developed and thoroughly examined the working of radio tomography generation algorithms and present a deep learning approach using a convolutional neural network (CNN) to address the inverse problem. …”
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Radiomics in the Diagnosis of Thyroid Nodules by A. A. Tokmacheva, D. S. Vyalkin, A. A. Trots, E. E. Tarakanova, Yu. I. Davletova, E. L. Abdullina, V. B. Stepnadze, A. I. Akhmetova, N. E. Shagieva, V. D. Uskova, V. S. Konovalova, A. R. Magdanova

“…The article summarizes the application of various imaging techniques to identify benign and malignant TNs, determine invasiveness and metastases to lymph nodes, as well as some new advances in the field of molecular level and deep learning. …”
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Using text-mining to measure the scientific impact and legacy of ELIXIR, a distributed research infrastructure for life science data [version 3; peer review: 2 approved] by Erika Balsyte, Corinne S. Martin, Ivan Mičetić, Martin Cook, Marilena D’Ambrosio, Robert Petryszak, Francesca De Leo, Chiara Bruno

“…Methods To overcome challenges inherent in ELIXIR’s distributed structure, and the fact that those publishing ELIXIR-supported work are typically working part-time on ELIXIR matters, a semi-automated approach, consisting of text-mining followed by manual curation, is presented. A country-level case study (ELIXIR Italy) refines and expands the methods, notably by introducing more granularity in the curation process (e.g. considering all national-level grants, examining affiliations to report publication per institute) and by additionally looking at the scientific impact of the resources developed and operated by the Italian Node of ELIXIR. …”
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Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology by Olga Fourkioti, Matt De Vries, Reed Naidoo, Chris Bakal

“…The model learns from these broad labels to extract more detailed, instance-level insights. …”
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Latent Graph Attention for Spatial Context in Light-Weight Networks: Multi-Domain Applications in Visual Perception Tasks by Ayush Singh, Yash Bhambhu, Himanshu Buckchash, Deepak K. Gupta, Dilip K. Prasad

“…In this paper, we present Latent Graph Attention (LGA), a computationally inexpensive (linear to the number of nodes) and stable modular framework for incorporating the global context in existing architectures. …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…The proposed AKW-MRPK framework achieves up to 92 % accuracy, reduces computational time to as low as 0.875 ms for 25 patients, and demonstrates superior speedup efficiency with a value of 1.9 ms using two computational nodes, consistently outperforming supervised machine learning algorithms and Hadoop-based clusters across these critical metrics. • The AKW-MRPK method selects attributes and accelerates computations for predictions. • Parallelizing polynomial kernels improves accuracy and speed in healthcare data analysis.…”
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Financial risk forecasting with RGCT-prerisk: a relational graph and cross-temporal contrastive pretraining framework by Liyu Chen, Xiangwei Fan

“…Our approach achieves state-of-the-art predictive performance while providing human-interpretable insights into why a firm is predicted to be at risk. This work presents a new direction for interpretable financial risk forecasting by integrating graph-based representation learning, contrastive pretraining, and case-based reasoning.…”
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SMILES all around: structure to SMILES conversion for transition metal complexes by Maria H. Rasmussen, Magnus Strandgaard, Julius Seumer, Laura K. Hemmingsen, Angelo Frei, David Balcells, Jan H. Jensen

“…We utilize these SMILES to make simple molecular fingerprint (FP) and graph-based representations of the molecules to be used in the context of machine learning. Comparing with the graphs made by Kneiding et al. where nodes and edges are featurized with DFT properties, we find that depending on the target property (polarizability, HOMO-LUMO gap or dipole moment) the SMILES based representations can perform equally well. …”
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3D MC. I. X-Ray Tomography Begins to Unravel the 3D Structure of a Molecular Cloud in our Galaxy’s Center by Samantha W. Brunker, Cara Battersby, Danya Alboslani, Maïca Clavel, Daniel L. Walker, Dani Lipman, H Perry Hatchfield, Régis Terrier

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Slowness and sparseness lead to place, head-direction, and spatial-view cells. by Mathias Franzius, Henning Sprekeler, Laurenz Wiskott

“…We present a model for the self-organized formation of place cells, head-direction cells, and spatial-view cells in the hippocampal formation based on unsupervised learning on quasi-natural visual stimuli. …”
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Low‐dimensional neural ordinary differential equations accounting for inter‐individual variability implemented in Monolix and NONMEM by Dominic Stefan Bräm, Bernhard Steiert, Marc Pfister, Britta Steffens, Gilbert Koch

“…Abstract Neural ordinary differential equations (NODEs) are an emerging machine learning (ML) method to model pharmacometric (PMX) data. …”
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GPU-accelerated simulated annealing based on p-bits with real-world device-variability modeling by Naoya Onizawa, Takahiro Hanyu

“…Abstract Probabilistic computing using probabilistic bits (p-bits) presents an efficient alternative to traditional CMOS logic for complex problem-solving, including simulated annealing and machine learning. …”
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“Tumour sink effect” on the diagnostic or posttreatment radioiodine scan due to sequestration into large-volume functioning metastasis of differentiated thyroid carcinoma influenci... by Sandip Basu, Rohit Ranade, Amit Abhyankar

“…In both the situations, large-volume highly functioning skeletal metastasis was the cause for the observed “sink effect” and is presented as learning illustrations to the attending physicians. …”
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