Unlocking potent anti-tuberculosis natural products through structure–activity relationship analysis by Delfly Booby Abdjul, Fitri Budiyanto, Joko Tri Wibowo, Tutik Murniasih, Siti Irma Rahmawati, Dwi Wahyu Indriani, Masteria Yunovilsa Putra, Asep Bayu

“…Abstract Tuberculosis (TB) remains a world health problem due to the high number of affected individuals, high mortality rates, prolonged treatment durations, and the increasing prevalence of resistance to commercial TB drugs. …”
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Comparative Analysis of Attention Mechanisms in Densely Connected Network for Network Traffic Prediction by Myeongjun Oh, Sung Oh, Jongkyung Im, Myungho Kim, Joung-Sik Kim, Ji-Yeon Park, Na-Rae Yi, Sung-Ho Bae

“…Our key findings are as follows: i) attention modules are very effective when positioned between the last dense module and the final feature fusion module, meaning that the attention module plays a key role in aggregating low-level local features with long-term dependency. …”
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Development of the program for sustainability of technological development of an industrial enterprise by A. E. Miller, D. O. Drozdov

“…The concept under consideration clarifies the key principles of the classical theory of sustainability of development, which make it possible to explore problem areas that hinder technological development. …”
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Noble Metal Complexes in Cancer Therapy: Unlocking Redox Potential for Next-Gen Treatments by Alina Stefanache, Alina Monica Miftode, Marcu Constantin, Roxana Elena Bogdan Goroftei, Iulia Olaru, Cristian Gutu, Alexandra Vornicu, Ionut Iulian Lungu

“…<b>(1) Context</b>: Cancer is still a major problem worldwide, and traditional therapies like radiation and chemotherapy often fail to alleviate symptoms because of side effects, systemic toxicity, and mechanisms of resistance. …”
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F. C. La Harpe’s report on the education of the grand dukes Alexander and Konstantin during the year 1791 by Andrei Andreev, Vera Mil'china

“…This report has a direct link to the series of the similar documents, which were already known by historians and dedicated to the education of the elder grandsons of Catherine II; thus this publication fills a lacuna in the existing row of revealed sources on this problem. The text of the report can make us follow the characteristic features of the education process held under the La Harpe’s guidance. …”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…This approach is particularly attractive due to the absence of the barren plateau problem, a fundamental challenge in training quantum neural networks (QNNs), and its feasibility. …”
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Enhanced Prediction of the Remaining Useful Life of Rolling Bearings Under Cross-Working Conditions via an Initial Degradation Detection-Enabled Joint Transfer Metric Network by Lingfeng Qi, Jiafang Pan, Tianping Huang, Zhenfeng Zhou, Faguo Huang

“…Remaining useful life (RUL) prediction of rolling bearings is of significance for improving the reliability and durability of rotating machinery. Aiming at the problem of suboptimal RUL prediction precision under cross-working conditions due to distribution discrepancies between training and testing data, enhanced cross-working condition RUL prediction for rolling bearings via an initial degradation detection-enabled joint transfer metric network is proposed. …”
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Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative by Hong-Seng Gan, Tan Tian Swee, Ahmad Helmy Abdul Karim, Khairil Amir Sayuti, Mohammed Rafiq Abdul Kadir, Weng-Kit Tham, Liang-Xuan Wong, Kashif T. Chaudhary, Jalil Ali, Preecha P. Yupapin

“…The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. …”
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GYS-RT-DETR: A Lightweight Citrus Disease Detection Model Based on Integrated Adaptive Pruning and Dynamic Knowledge Distillation by Linlin Yang, Zhonghao Huang, Yi Huangfu, Rui Liu, Xuerui Wang, Zhiwei Pan, Jie Shi

“…First, this paper introduces the following innovations in model structure: (1) A Gather-and-Distribute Mechanism is introduced in the Neck section, which effectively enhances the model’s ability to detect medium to large targets through global feature fusion and high-level information injection.(2) Scale Sequence Feature Fusion (SSFF) is used to optimize the Neck structure to improve the detection performance of the model for small targets in complex environments. (3) The Focaler-ShapeIoU loss function is used to solve the problems of unbalanced training samples and inaccurate positioning. …”
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Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

“…Deep learning algorithms have shown remarkable capabilities in pattern recognition, feature extraction, and predictive modeling, enabling researchers to uncover hidden relationships within microbial ecosystems. …”
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An Insight on the Timely Diagnosis of Diabetic Retinopathy Using Traditional and AI-Driven Approaches by Malaika Asif, Fasih Ur Rehman, Zoya Rashid, Altaf Hussain, Alina Mirza, Waqar Shahid Qureshi

“…Artificial intelligence is transforming the detection of diabetic retinopathy, moving away from traditional machine learning models that rely on manually created features to deep learning methods that allow for automatic feature extraction from retinal images. …”
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Modular Neural Network Model for Biometric Authentication of Personnel in Critical Infrastructure Facilities Based on Facial Images by Oleksandr Korchenko, Ihor Tereikovskyi, Ruslana Ziubina, Liudmyla Tereikovska, Oleksandr Korystin, Oleh Tereikovskyi, Volodymyr Karpinskyi

“…Innovative features of the developed modular model include the ability to recognize spoofing attacks based on environmental artifacts and the naturalness of emotions, as well as an increase in the accuracy of person recognition due to the use of a U-Net neural network to highlight natural facial contours in occlusions. …”
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Joint Class and Domain Continual Learning for Decentralized Federated Processes by Chiara Lanza, Tinne Tuytelaars, Marco Miozzo, Eduard Angelats, Paolo Dini

“…In this work, we formulate a joint Class and Domain Continual Learning problem, where local data at the nodes might include multiple classes belonging to different domains. …”
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Intrusion Detection in IoT Networks Using Dynamic Graph Modeling and Graph-Based Neural Networks by William Villegas-Ch, Jaime Govea, Alexandra Maldonado Navarro, Pablo Palacios Jativa

“…In this model, devices are represented as nodes and communications as weighted edges, integrating features such as communication frequency, transmitted data volume, and protocol type. …”
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SDMSEAF-YOLOv8: a framework to significantly improve the detection performance of unmanned aerial vehicle images by Linxuan Li, Xiaoyu Liu, Xuan Chen, Fengjuan Yin, Bin Chen, Yufeng Wang, Fanbin Meng

“…A Space-to-depth layer replaces the traditional strided convolution layer to enhance the extraction of fine-grained information and small-sized target features. A Multi-Separated and Enhancement Attention module enhances the feature learning ability of the occluded target region, thus reducing missed and false detections. …”
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Semi-MeshSeg: A semi-supervised semantic segmentation network for large-scale urban textured meshes using all pseudo-labels by Wenjie Zi, Jun Li, Hao Chen, Qingren Jia

“…To address this issue, we propose a novel semi-supervised learning approach, Semi-MeshSeg, to tackle the problem of insufficiently labeled data. Urban meshes are irregular and susceptible to distortion, leading to blurred boundaries and surface features. …”
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Distributed Denial of Service Attack Detection in Software-Defined Networks Using Decision Tree Algorithms by Ali Zaman, Salman A. Khan, Nazeeruddin Mohammad, Abdelhamied A. Ateya, Sadique Ahmad, Mohammed A. ElAffendi

“…These attack paralyze networks by flooding the controller with bogus requests. The answer to this problem is to ignore machines in the network sending these requests. …”
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Indirect charitable assistance to Russia from American and Russian organisations and individuals by Vladislav Tarelko

“…Consequently, the author has identified the following purpose of this article – to summarize and expand the available material about the American and Russian relief and humanitarian assistance, to identify the features, forms and instruments of its activities, as well as to draw a general conclusion about the scale and benefits of the aforementioned assistance to Russia during the European war. …”
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Reasoning like a doctor or like a nurse? An integrative review protocol by Rashmi A Kusurkar, Jos Dobber, Jettie Vreugdenhil, Sunia Somra, Hans Ket, Eugène J F M Custers, Marcel E Reinders

“…We will extract the data of the included studies conforming these layers and features, to capture the multifaceted nature of clinical reasoning in both professions. …”
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Fine-Grained Extraction of Coastal Aquaculture Ponds From Remote Sensing Images Using an Edge-Supervised Multi-task Neural Network by Jian Qi, Min Ji, Fengxiang Jin, Jianran Xu, Hanyu Ji, Juan Wang

“…Then, a selective task fusion module was developed to optimize the allocation of shared feature space, effectively alleviating the negative transfer problem of multitask architecture. …”
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