Intraspecific and Intracolonial Variation in the Profile of Venom Alkaloids and Cuticular Hydrocarbons of the Fire Ant Solenopsis saevissima Smith (Hymenoptera: Formicidae) by Eduardo Gonçalves Paterson Fox, Adriana Pianaro, Daniel Russ Solis, Jacques Hubert Charles Delabie, Bruno Cunha Vairo, Ednildo de Alcântara Machado, Odair Correa Bueno

“…Some fire ant species are top-rated pests spreading throughout the world by trade vessels. …”
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SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu, Chongbin Sun

“…Next, a SOH estimation framework based on the CGKAN model is developed, where 1-Dimensional-Convolutional Neural Networks (1D-CNN) are used to extract deep features from the original data, Bidirectional Gated Recurrent Unit (BiGRU) captures the bidirectional dependencies of the time series, and Kolmogorov–Arnold Networks (KAN) enhances the modeling of complex nonlinear features through its nonlinear mapping capabilities, thereby improving the accuracy of SOH estimation. …”
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AEMS: Adaptive Ensemble GNNs for Multibehavior Stream Recommendation by Ritchie Natuan Caibigan, Punyaphol Horata, Pusadee Seresangtakul

“…The AEMS synergizes long-term preference patterns (derived from historical interactions) with real-time user intents and item attributes (captured through multibehavior signals), integrating them via an adaptive ensemble neural gating mechanism. …”
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Forecasting Sales in Live-Streaming Cross-Border E-Commerce in the UK Using the Temporal Fusion Transformer Model by Qi Zhang, Xue Li, Pengbin Gao

“…Our multimodal approach integrates diverse time series data, including historical sales, key opinion leader (KOL) influence, and seasonal patterns. The Temporal Fusion Transformer (TFT) model demonstrated consistently lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Squared Error (MSE) across all forecasting horizons compared to other machine learning approaches, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Gated Recurrent Unit(GPU)-accelerated architectures. …”
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A clustering-based federated deep learning approach for enhancing diabetes management with privacy-preserving edge artificial intelligence by Xinyi Yang, Juan Li

“…We develop tailored models that enhance prediction accuracy by clustering patients based on carbohydrate (CHO) intake patterns. Utilizing Simple Recurrent Neural Network (SimpleRNN) and Gated Recurrent Unit (GRU) methods, the study evaluates the performance of local patients who contribute to training the cluster and global (non-cluster) models. …”
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fNIRS evidence of abnormal frontotemporal cortex activation and functional connectivity in depressed patients after stroke: neuromodulatory mechanisms from mild to moderate depress... by Shanshan Zhou, Xiaodie Liu, Mengyuan Chen, Wenyi Chen, Yawen Pan, Yinghao Zhi

“…In contrast, the mild-PSD group displayed no notable connectivity differences between the two groups.ConclusionThis study presents distinct patterns of frontotemporal cortex activation and functional connectivity alterations associated with varying severity levels of PSD. …”
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A Cross-Sectional Analysis of Oil Pulling on YouTube Shorts by Jun Yaung, Sun Ha Park, Shahed Al Khalifah

“…., dentist, hygienist, influencer), engagement metrics, stated benefits, oil type and regimen, the use of disclaimers or citations, and stance toward oil pulling rated on a 5-point Likert scale. Speaker background and nationality were determined through publicly available channel descriptions or linked websites, with user identities anonymized and ethical approval deemed unnecessary due to the use of publicly available content. …”
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The Ethical Significance of Brain-Computer Interfaces as Enablers of Communication by Toma Gruica

“…Intracortical BCIs, by contrast, can restore communicative capacity by directly decoding neural signals associated with intended speech or movement.[5] One landmark study documented an amyotrophic lateral sclerosis (ALS) patient who, after entering CLIS, learned to use an implanted BCI speller to construct sentences at a rate of approximately one character per minute. The patient’s communications ranged from the mundane, such as requesting music, to expressions of existential significance involving care preferences.[6] Importantly, when researchers were asked how they would respond if the patient spelled “unplug my ventilator,” they emphatically stated that BCI output would not determine decisions regarding life support withdrawal. …”
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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

“…The high fluctuation and volatility of cryptocurrency prices and the complexity of non-linear relationships in data patterns attract investors and researchers who want to develop accurate cryptocurrency price forecasting models. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…Three sequential deep learning models—Recurrent Neural Network and Gated Recurrent Unit—were developed and optimized using the Adam algorithm. …”
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Content-Based Brain Magnetic Resonance Image Retrieval and Classification With the Proposed Deep Learning and Tissue-Based System by Bedriye Dogan, Hursit Burak Mutlu, Muhammed Yildirim, Sercan Yalcin, Serpil Aslan, Niranjana Sampathila, Ozal Yildirim, Edward J. Ciaccio, Ru-San Tan, U. Rajendra Acharya

“…Notably, existing machine architectures already published in the literature have struggled to achieve comparable success rates in discerning such closely related yet distinct disease groups. …”
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A Long-Term Overview of Elasmobranch Fisheries in an Oceanic Archipelago: A Case Study of the Madeira Archipelago by Mafalda Freitas, Filipa Pinho-Duarte, Madalena Gaspar, Pedro Ideia, João Delgado, Sara C. Cerqueira, Ricardo Sousa

“…Management measures currently in place need to be updated and ought to be based on studies on the type and size of hooks for each fishery, to ultimately infer about species-specific survival rates, as well as the fishing gears’ soak time. Moreover, studies on the enhancement of food supply through fisheries discards are still missing, even though it is highly likely that this input may alter the dynamics of marine food webs.…”
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The large and central Caligo martia eyespot may reduce fatal attacks by birds: a case study supports the deflection hypothesis in nature by Iserhard, Cristiano Agra, Malta, Shimene, Penz, Carla, Fraga, Brenda Barbon, Costa, Camila Abel, Schwantz, Taiane, Bordin, Kauane Maiara

“…Eyespots did not appear to reduce attack rates, suggesting that local bird species were not intimidated. …”
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MSA-GCN: Exploiting Multi-Scale Temporal Dynamics With Adaptive Graph Convolution for Skeleton-Based Action Recognition by Kowovi Comivi Alowonou, Ji-Hyeong Han

“…On the other hand, the TMST module integrates a Gated Multi-stage Temporal Convolution (GMSTC) with a Temporal Multi-Head Self-Attention (TMHSA) to capture global temporal features and accommodate both long-term and short-term dependencies within action sequences. …”
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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

“…These components are then modeled independently: long short-term memory (LSTM) and convolutional neural networks (CNN) handle trend and seasonal patterns, while gated recurrent units (GRU) and Transformer process residual fluctuations. …”
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Multiscale Convolutional Fusion Network for Efficient Monaural Speech Separation by Rui Yang, Shanliang Pan

“…MSCF first employs dynamic convolution-based downsampling to enhance the multiscale feature representation. Adaptive gating and multiscale convolutions are then utilized to capture complex acoustic patterns. …”
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Collective and individual adaptation of rice farmers to climatic variability in the Vietnamese Mekong Delta by Hieu Hong Hua, Minh Anh Nguyen, Thuy Thanh Thi Ngo

“…It systematically explores the patterns of climate variability and their profound impacts on rice production across diverse areas within the delta. …”
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Stem introducer designs and surgical technique play a significant role in achieving the optimal implant-cement interface by Bernard H. van Duren, Kevin Ilo, Sophie Walker, Mark Higgins, Benjamin V. Bloch, Andrew R. Manktelow, Hemant G. Pandit

“…A significant variation exists between PTS stem designs, associated fractured rates among them, and the design of introducers used. …”
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Impact of oral hygiene on the development of oropharyngeal neoplasms by D. G. Kiparisova, Yu. S. Kiparisov, N. S. Nurieva

“…The patient hygiene performance (PHP) index (Podshadley, Haley, 1968) was used to estimate his/her baseline ability. The rates of initial visits made by patients with oropharyngeal tumors to physicians of different specialties were also analyzed.Results. …”
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Meningitis caused by Aspergillus fumigatus: a case report by Yifei Zhang, Yu Ma, Rushuang Yue, Yuan Meng, Yue Jin, Chengwei Yin, Qianmei Zhou, Rong Shi

“…Conclusion A. fumigatus meningitis represents a rare but life-threatening infection characterized by diagnostic challenges and alarmingly high mortality rates. Stringent diagnostic vigilance is essential to avoid diagnostic errors in these cases. …”
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