Anomaly Detection in Network Traffic via Cross-Domain Federated Graph Representation Learning by Yanli Zhao, Zongduo Liu, Junjie Pang

“…Traditional detection approaches typically rely on statistical features while overlooking the interaction patterns and structural dependencies among traffic flows. …”
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Dorsal epidural disc migration—MRI characteristics and surgical microdiscectomy treatment: Case report and review of the literature by Antonios Michailidis, MD, Ioannis Tsifountoudis, MD, PhD, Dimitrios Kitridis, MD, FEBOT, MSc, PhDc, Konstantinos Tasoulis, MD, Kostas Charatsis, MD, Giannetopoulos Dimitrios, MD

“…Surgical intervention, particularly microdiscectomy, has shown favorable outcomes in resolving symptoms associated with nerve compression and minimizing recurrence rates. This report presents a case of DEDM in a 39-year-old male with persistent sciatica, analyzing MRI characteristics and surgical treatment.…”
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Deep Temporal and Structural Embeddings for Robust Unsupervised Anomaly Detection in Dynamic Graphs by Samir Abdaljalil, Hasan Kurban, Rachad Atat, Erchin Serpedin, Khalid Qaraqe

“…We introduce Temporal Structural Graph Anomaly Detection (<sc>T-StructGAD</sc>), an unsupervised framework that leverages Graph Convolutional Gated Recurrent Units (<monospace>GConvGRU</monospace>s) and Long Short-Term Memory networks (<monospace>LSTM</monospace>s) to jointly model both structural and temporal dynamics in graph node embeddings. …”
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Seasonal population dynamics and dietary switching of Vulpes spp. amplify Echinococcus spp. transmission in the Eastern Tibetan plateau: implications for wildlife-mediated zoonotic... by Xu Wang, Chuizhao Xue, Xueying Deng, Qilu Chen, Chunyang Li, Baixue Liu, Ying Wang, Yan Kui, Qingqiu Zuo, Jianhai Yin, Shuai Han, Yujuan Shen, Jianping Cao

“…This dietary diversification correlated with seasonal resource scarcity, driving foxes to exploit alternative prey. The infection rates of Echinococcus in V. ferrilata displayed the U-shaped seasonal patterns. …”
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Toward AI-Augmented Formal Verification: A Preliminary Investigation of ENGRU and Its Challenges by Chanon Dechsupa, Teerapong Panboonyuen, Wiwat Vatanawood, Praisan Padungweang, Chakchai So-In

“…In this paper, we present ENGRU (Enhanced Gated Recurrent Units), a novel deep learning-based approach for formal verification. …”
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Optimization of Electric Transformer Operation Through Load Estimation Based on the K-Means Algorithm by Pedro Torres-Bermeo, José Varela-Aldás, Kevin López-Eugenio, Nancy Velasco, Guillermo Palacios-Navarro

“…These estimated curves are integrated into a process that calculates technical losses, both no-load and load losses, for different transformer sizes, selecting the optimal rating that minimizes losses without compromising demand. …”
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Dramatic Decoupling Between Population and Construction Land in Rural China by Jiatong Han, Minghong Tan

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Risk factor, diagnosis, and current treatment of H. pylori Infection in Indonesia: A Literature Review by Rizani Putri Iman, Tiroy Junita, Rinaldo Indra Rachman, Ari Fahrial Syam

“…Several findings revealed high rates of antibiotic resistance varying among Indonesian regions and ethnicities, suggesting that triple therapy regimen may not be suitable for all population. …”
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CRYPTOCURRENCY TIME SERIES FORECASTING MODEL USING GRU ALGORITHM BASED ON MACHINE LEARNING by Melina Melina, Sukono Sukono, Herlina Napitupulu, Norizan Mohamed, Yulison Herry Chrisnanto, Asep ID Hadiana, Valentina Adimurti Kusumaningtyas

“…This research aims to build a cryptocurrency forecasting model with a machine learning-based time series approach using the gated recurrent units (GRU) algorithm. The dataset used is historical Bitcoin closing price data from January 1, 2017, to July 31, 2024. …”
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Improving cancer detection through computer-aided diagnosis: A comprehensive analysis of nonlinear and texture features in breast thermograms. by Hamed Khodadadi, Shima Nazem

“…Breast cancer is a significant health issue for women, characterized by its high rates of mortality and sickness. However, its early detection is crucial for improving patient outcomes. …”
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Deep Learning Based Breast Cancer Detection Using Decision Fusion by Doğu Manalı, Hasan Demirel, Alaa Eleyan

“…Breast cancer, which has the highest mortality and morbidity rates among diseases affecting women, poses a significant threat to their lives and health. …”
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Numerical Determination Of Cooling Performance On Heat Sink Using Impingement Jet by Rami Abdulraheem Abdulrezzaq Al-anı, Altuğ Karabey

“…In this method, significant heat transfer rates are achieved. The present study examined the cooling performance of the fin pairs, which are aligned in a consecutively enlarging-contracting pattern and have a rectangular geometry, on a heat sink. …”
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A Novel Approach for Tomato Leaf Disease Classification with Deep Convolutional Neural Networks by Gizem Irmak, Ahmet Saygılı

“…The findings indicate that the CNN model consistently outperformed classical learning methods, achieving accuracy rates of 99.5%, 98.50%, and 97.0% for 2-class, 6-class, and 10-class classifications, respectively. …”
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MULTINATIONAL COMPANIES FOR BUSINESS INTERNATIONALIZATION THROUGH FOREIGN DIRECT INVESTMENT (FDI) IN GLOBALIZATION: TRENDS FOR VALUES by Anis BENABED

“…Multinational companies that go for foreign direct investment have an economic impact and can affect a country's economy in various ways, for example, in the balance of payments, in growth rates and in job creation. The effect of foreign direct investment by multinational companies can be negative or positive depending on certain factors. …”
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The role of the ventral striatum in the relationship between impulsive decision-making and emotional self-regulation by cognitive reappraisal by Youngwoo Bryan Yoon, Wi Hoon Jung

“…Our data revealed that greater use of cognitive reappraisal as an emotion regulation strategy was significantly associated with lower DD rates (i.e., reduced temporal impulsivity). No such relationship was found for expressive suppression. …”
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Group attention for collaborative filtering with sequential feedback and context aware attributes by Hadise Vaghari, Mehdi Hosseinzadeh Aghdam, Hojjat Emami

“…However, due to individual variations in rating patterns and dynamic interplays of item attributes, it becomes challenging to model user preferences accurately. …”
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Measurement of food sensitivity with special reference to food properties in children with autism spectrum disorder by Rameen Sameer, Beenish Israr, Aqsa Inam, Hafiza Kinza Javed

“…The Childhood Autism Rating Scale (CARS) was used to assess behavioral responses and food acceptance. …”
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Presentation time shapes perceived room size in visual and auditory modalities by Johanna Bogon, Cindy Jagorska, Ella Maria Heinz, Martin Riemer

“…As time judgments were consistently rated as more difficult relative to space judgments, this pattern of interference cannot be explained on the basis of task difficulty. …”
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Nursing Value Analysis and Risk Assessment of Acute Gastrointestinal Bleeding Using Multiagent Reinforcement Learning Algorithm by Fang Liu, Xiaoli Liu, Changyou Yin, Hongrong Wang

“…As a result, we present а unique machine learning-based nursing value analysis and risk assessment framework in this research to construct a model to evaluate the risk of hospital-based interventions or mortality in individuals with GIB and make a comparison to that of other rating systems. Initially, the dataset is collected, and preprocessing is done. …”
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Color characteristics and psychological healing effects in Rokuon-ji Temple Garden: a quantitative analysis by Jinyang Wang, Yoichi Kunii

“…From an initial collection of 150 photographs documenting the garden’s complete visitor experience, 42 landscape photographs were systematically selected based on healing quality ratings (mean ≥5.0, median ≥5.0, standard deviation &lt;1.2) and analyzed for six color categories (red, yellow, brown, gray, white, green) using three quantitative metrics: fractal dimension, diversity index, and concentration index. …”
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