Detection of Bipolar Disorder and Schizophrenia Employing Bayesian-Optimized Grad-CAM-Driven Deep Learning by Osman Tayfun Bişkin, Cemre Candemir, Mustafa Alper Selver

“…Deep learning (DL) has emerged as a transformative tool in neuroimaging analysis, offering the ability to automatically extract intricate features from large datasets. …”
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A Comprehensive Framework for Out-of-Distribution Detection and Open-Set Recognition in SAR Targets by Fei Gao, Heqing Huang, Jun Wang, Jinping Sun, Amir Hussain, Huiyu Zhou

“…The rejection of outlier data in synthetic aperture radar (SAR) image analysis presents a significant challenge, particularly in the scenarios of out-of-distribution (OOD) detection and open set recognition (OSR). …”
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Serious game to promote socioemotional learning and mental health (emoTIC): a study protocol for randomised controlled trial by Usue De la Barrera, Silvia Postigo-Zegarra, Estefanía Mónaco, José-Antonio Gil-Gómez, Inmaculada Montoya-Castilla

“…The purpose of the study is to design a serious game based on the Mayer et al’s emotional intelligence ability model and analyse the effectiveness of the emoTIC programme to develop emotional competences, well-being, mental health, and personal strengths immediately after completion and at 12 months.Methods and analysis The new version of emoTIC will be designed following the suggestions of the adolescents who participated in the pilot study and the results obtained from the statistical analysis. …”
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Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction by Amun Jarzembski, Siddharth Nair, Wyatt Hodges, Matthew Jordan, Anthony McDonald, Logan Antiporda, Greg W. Pickrell, Timothy Walsh, Fabio Semperlotti, Jason Neely, Luke Yates

“…Abstract Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. …”
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Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches by Mohsin Akram, Muhammad Adnan, Syed Farooq Ali, Jameel Ahmad, Amr Yousef, Tagrid Abdullah N. Alshalali, Zaffar Ahmed Shaikh

“…Abstract Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. …”
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Wolbachia elevates host methyltransferase expression and alters the m6A methylation landscape in Aedes aegypti mosquito cells by Michael Leitner, Valentine Murigneux, Kayvan Etebari, Sassan Asgari

“…Our study revealed that Wolbachia infection elevates the expression of genes involved in the mosquito’s m6A methyltransferase complex. However, knocking down these m6A-related genes did not affect Wolbachia density. …”
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Vision Transformer-Based Unhealthy Tree Crown Detection in Mixed Northeastern US Forests and Evaluation of Annotation Uncertainty by Durga Joshi, Chandi Witharana

“…These findings highlight SegFormer’s superior ability to capture complex spatial patterns, even in relatively low-resolution (60 cm) datasets. …”
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Shared realities, therapeutic settings, and countertransference in times of crisis: a multinational qualitative study of psychotherapists’ experiences by Rose Marie Nassif, Rahmeth Radjack, Nour Beaini, Tonnie Choueiri, Gabriel Binkowski, Elisabetta Dozio, Mathilde Laroche Joubert, Marie-Rose Moro, Layla Tarazi-Sahab, Mayssa’ El Husseini

“…Results The analysis of the data revealed three superordinate themes that are best presented by following the journey of the mental health professional as he or she navigates from external reality (1) to virtual reality (remote therapy) (2), ultimately plunging into the internal reality (internal reorganization linked to his or her ability to create novelty within these complex situations) (3). …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…Abstract The growing number of patients and the emergence of new symptoms and diseases make health monitoring and assessment increasingly complex for medical staff and hospitals. The execution of big and heterogeneous data gathered by medical sensors and the necessity of patient classification and disease analysis have become serious problems for various health-based sensing applications. …”
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Ethical Aspects of the Influence of Neural Networks on the Lives of Students in the Context of a Sociological Approach (using the Example of Students of the IT Department of ETU) by A. S. Kurapova, S. V. Kurapov, A. D. Derzhavina, N. V. Shatilo

“…A significant portion of the respondents expressed concerns about ethical issues related to the use of neural networks, including loss of autonomy in decision-making and lack of human interaction. The analysis of the responses of the ChatGPT-3.5 neural network to questions related to solving ethical dilemmas was carried out, which confirmed the ability of the neural network to emotionally analyze and take into account ethical aspects.Conclusion. …”
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EVALUATION OF THE EFFECTIVENESS OF BIOFEEDBACK TECHNOLOGY FOR LOCOMOTIVE CREW WORKERS by Ирина Алексеевна Несина, Ольга Андреевна Джафарова, Елена Леонидовна Потеряева, Елена Леонидовна Смирнова, Тамара Викторовна Кулишова

“…Results. The analysis of the self-assessment survey of the results of the BOS training allowed us to identify 3 groups: group 1 – 194 people (56%) – indicated the ability to manage their emotional state as the main result; group 2 – 114 people (33%) – noted the improvement/development of self-regulation skills; group 3 – 38 people (11%) – they did not feel any changes in their emotional state, could not formulate the result of the training, i.e. this group can be described as «unchanged». …”
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Peculiarities of clinical course and diagnostics of calculous cholecystitis in children by A. G. Zaporozhchenko, Y. P. Gerasimenko, O. V. Spakhi

“…In all the children anamnesis was studied, evaluation of objective data and complex clinical, laboratory, ultrasound and x-ray examination were carried out. …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…The significance of this research lies in its ability to automate and accelerate complex structural analysis using Adaptive Neuro-Fuzzy Inference Systems (ANFISs), achieving an average error of less than 2% in multi-variable prediction scenarios. …”
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Metabolic Influence of <i>S. boulardii</i> and <i>S. cerevisiae</i> in Cross-Kingdom Models of <i>S. mutans</i> and <i>C. albicans</i> by Ting Li, Xingyi Lu, Yan Wu, Tongtong Wu, Jin Xiao

“…Untargeted LC-MS/MS analysis was conducted to assess metabolites in a planktonic model, followed by metabolomic profiling and pathway analysis to identify key metabolic alterations. …”
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Challenges in Thirst Management for Intubated Patients in the ICU: A Qualitative Study of Healthcare Provider and Patient Perspectives by Yuan Y, He LF, Luo Q, Zhang X, Chen F, Hu RJ

“…These findings underscore the multifaceted nature of thirst management in tracheal intubation.Conclusion: Thirst management for patients undergoing tracheal intubation in the ICU involves complex, multidimensional challenges. The findings offer clinically relevant insights that may enhance the ability of healthcare providers to recognize and assess thirst, support the development of targeted communication strategies and interventions, and facilitate greater patient involvement in care decisions, thereby contributing to improved treatment adherence and nursing quality.Keywords: clinical challenges, cognitive differences, communication barriers, intubated patients, thirst management…”
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COPD-MMDDxNet: a multimodal deep learning framework for accurate COPD diagnosis using electronic medical records by Yuanyuan Yi, Lei Shi, Haoran Liu, Mingyu Wang, Min Feng, Yanxia Li

“…These innovations significantly enhance the model's ability to capture complex cross-modal relationships, thereby improving diagnostic accuracy.The dataset used in this study comprises 800 COPD patients, with a balanced age and sex distribution, and data were collected over a 24-month period. …”
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Mechanisms of Ocean Acidification in Massachusetts Bay: Insights from Modeling and Observations by Lu Wang, Changsheng Chen, Joseph Salisbury, Siqi Li, Robert C. Beardsley, Jackie Motyka

“…These patterns arise from complex nonlinear interactions between physical and biogeochemical processes. …”
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A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus by Levin John, Leona Dcunha, Mukhtar Ahmed, Sonet Daniel Thomas, Rajesh Raju, Abhithaj Jayanandan

“…With no antiviral drugs or vaccines available, exploring the complex machinery involved in viral RNA synthesis presents a promising target for therapy. …”
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A study exploring predictors of cell phone use while walking among adolescents based on theory of planned behavior by Biaoqian Tang, Jun Ren, Yiyang Li, Koustuv Dalal, Fenfen Li, Xiaoya Yin, Bohao Chen, Wenbiao Zhao, Shumei Wang

“…Abstract Background Walking is a complex activity that requires high levels of perception and cognitive abilities. …”
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Molecular dynamic simulation studies of hemidesmus indicus-derived oleanen-3-yl acetate in stat3 based tumor signaling by J Renukadevi, V S Karthikha, J Sam Helinto, D. Prena, Arockiya Rabin A

“…It sheds light on the conformational changes induced by Oleanen derivatives during binding, demonstrating its ability to destabilize the complex and enhance p53's apoptotic activity. …”
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