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Beliefs About Emotions and Positive Emotion Regulation: Do Fears of Social Evaluation Moderate the Relationship?
No full textIndividuals hold a variety of beliefs about emotions, which can influence how they regulate specific emotions. Additionally, concerns about social evaluations can shape how people's beliefs about emotions are associated with the way they manage their feelings. In this study, we investigate the beliefs about undesirability of positive emotions and controllability of feeling good in relation to positive emotion regulation strategies (i.e., positive rumination vs. dampening). Within the scope of this study, the concepts of fear of happiness and discomfort with positive emotions were examined in relation to beliefs about undesirability. Moreover, we considered the moderating roles of both fears of positive and negative evaluation in the relationships between those beliefs and the regulation strategies. Our findings (N = 411) indicated that both fear of happiness and discomfort with positive emotions were associated with lower positive rumination but were associated with higher dampening. On the contrary, beliefs about the controllability of feeling good were associated with higher positive rumination but with lower dampening. However, neither of the fears of social evaluation moderated the relationship between emotion beliefs and positive emotion regulation strategies. Our findings highlight the role of emotional beliefs in positive emotion regulation and suggest that interventions targeting these beliefs can improve emotion regulation skills
Feasibility of Artificial Intelligence-Based Image Enhancement Program for Anatomical Dissection Photographs
No full textAnatomical photographs are essential in medical education and research as they document fine details of human anatomy. which may support visualization of dissection material. This study investigated the feasibility of an artificial intelligence (AI)-based image enhancement system for anatomical dissection photographs and explored whether subtle visual differences could be detected under magnification. A dataset of 50 anatomical photographs taken between 2001 and 2024 with four different digital cameras was processed using Upscayl (v2.11.5) with the preset “16× REAL-ESRGAN.” Processing was performed on a Casper Excalibur G770 laptop, requiring approximately 3–5 min per image. Original and enhanced images were compared at magnifications of 1×, 5×, 10×, 15×, and 20× on a 55-in. Full HD display. Forty experts, including neuroanatomists and neurosurgeons, qualitatively assessed the images with respect to anatomical accuracy, noise reduction, edge definition, and training value. The visual differences between the original and enhanced images were generally subtle. However, subtle improvements in edge definition and noise reduction became more apparent in deep anatomical regions, such as ventricular cavities, particularly at higher magnification levels. High-resolution images showed limited observable differences, whereas lower-resolution images exhibited slightly more noticeable changes under magnification. The enhancement process did not introduce distortions of anatomical structures. A key limitation was the substantial increase in file size after enhancement. AI-based image enhancement appears feasible for anatomical dissection photographs and may provide modest visual benefits in selected settings, especially for older or lower-resolution images viewed at higher magnification. Further optimization is required to reduce file size and processing time before routine educational or publication use
Intrusion Detection Using TabNet with Recursive Feature Elimination and Deep Supervision
No full textIntrusion Detection Systems (IDS) are essential for safeguarding modern network infrastructures against an ever-evolving spectrum of cyberattacks. However, the high dimensionality and imbalance of network traffic data often hinder the performance and scalability of conventional deep learning models. This paper proposes a novel IDS framework that integrates Recursive Feature Elimination (RFE), the TabNet deep neural network, and deep supervision to enhance both accuracy and interpretability. The RFE module effectively reduces feature redundancy, while TabNet utilizes sequential attention to dynamically prioritize the most relevant attributes during classification. Deep supervision further improves convergence and stability by applying auxiliary loss functions to intermediate layers. The model was evaluated on the CIC-IDS2017 dataset and achieved outstanding results, with 98.7% accuracy, 98.5% precision, 98.2% recall, 98.4% F1 score, and an AUC of 0.979. Comparative analysis with recent studies confirms the superiority of the proposed approach in terms of performance, efficiency, and feature transparency. This framework offers a robust and scalable solution for real-world network intrusion detection applications
Exploring the Interictal Neuropsychological Burden of Pediatric Migraine
No full textBackground: Migraine in childhood and adolescence is a common neurological disorder extending beyond headache attacks, often affecting cognitive, emotional, and behavioral functioning during the interictal phase. Although migraine-related disability and school absenteeism are well recognized, comprehensive multidimensional assessments are limited, especially in non-Western populations. To examine the interictal burden of pediatric migraine by evaluating executive functions, emotional-behavioral symptoms, and attention-deficit/hyperactivity disorder (ADHD)-related features using standardized psychometric tools. Methods: This cross-sectional study included 71 adolescents (mean age 14.6 ± 1.9 years; 70.4% female) diagnosed with migraine based on International Classification of Headache Disorders, 3rd edition criteria. Migraine-related disability and impact were measured with the Pediatric Migraine Disability Assessment (PedMIDAS) and Headache Impact Test (HIT-6). Executive functions were assessed using the Teenage Executive Functioning Inventory (TEXI), emotional-behavioral symptoms with the Strengths and Difficulties Questionnaire (SDQ), and ADHD-related features with the Conners Parent Rating Scale–Short Form. Correlation, group comparison, and multiple regression analyses explored associations between migraine severity, headache frequency, and psychometric outcomes. Results: PedMIDAS and HIT-6 indicated moderate-to-severe migraine burden. HIT-6 correlated with TEXI inhibition, Conners total, ADHD index, and SDQ emotional symptoms. PedMIDAS correlated with SDQ emotional and hyperactivity subscales. Headache frequency was associated with TEXI total and SDQ total scores. Girls had higher PedMIDAS and TEXI inhibition, while boys scored higher on Conners hyperactivity. Regression analyses revealed directional but nonsignificant relationships after adjusting for confounders. Conclusions: Pediatric migraine imposes a considerable interictal burden, influencing executive, emotional, and behavioral domains. Multidimensional evaluation and integrated management approaches are essential to address both medical and psychosocial impacts
INVESTIGATION OF FLUID FLOW BEHAVIOR IN FIXED AND ADJUSTABLE HYDRAULIC CHANNELS
No full textChallenges of open-channel flow are discussed, with emphasis on energy dissipation and the difficulties brought by channel design for hydraulic pressure and velocity measure. The influence of the rheology of the slurry on channel design is also complicated. The objective of this work is to study the flow behavior in open channels of different shapes and with variable wall stability (fixed and movable). ANSYS Fluent (Release 2, 2021) Computational Fluit Dynamic (CFD) simulations were performed for the velocity distribution and pressure profiles in four configurations of channels: parallel, zigzag, wavy and curved. The study examines the effects of channel height variations and various inlet velocity (6, 3, and 0.3 m/s) on flow behavior. Findings indicate that increasing channel height reduces internal pressure, while lowering the height increases it, with pressure also varying by channel geometry. The curved channel shows the maximum pressure at a height of 0.5 m, and the channel with wavy shape exhibits the maximum pressure at 2831.92 MPa, with the curved channel reaching 3384.85 MPa under fixed-wall conditions
Spooks
No full textThis article considers the double meaning of ‘spook’ as both ghost and spy. Building on but moving beyond the hauntological or spectral turn in the recent humanities, the article explores this double meaning of ‘spook’ and what it might tell us about security politics. In so doing, the article moves through a diverse range of topics: from Hamlet to Bentham, from undercover cops to the anxieties of security intellectuals, and from moles to the ghostly powers of police, the article lays bare the haunted nature of contemporary security
In vitro assessment of cytotoxic, genotoxic, and antimicrobial properties of pediatric restorative dental materials
Full text linkBackground: This study aimed to comparatively evaluate the cytotoxic and genotoxic effects of three glass ionomer-based restorative materials and one alkasite material on murine fibroblast cells (L929). Additionally, their antibacterial activities against two prominent oral pathogens were investigated. Methods: The tested materials included ChemFil Rock (Dentsply Sirona, Germany), EQUIA Forte HT Fil (GC, Japan), Ruby Liner (Rubydent, Turkey), and the alkasite material Cention Forte (Ivoclar Vivadent, Switzerland). Cytotoxicity and genotoxicity were assessed using the L929 fibroblast cell line through MTT and comet assays. Antibacterial properties against Streptococcus mutans and Enterococcus faecalis were determined using the agar diffusion method. Data were analyzed with one-way ANOVA and Tukey’s HSD post hoc test (GraphPad Prism v5.03). Statistical significance was set at p < 0.0001 for cytotoxicity and p < 0.05 for genotoxicity. Results: All tested materials exhibited cytotoxic and genotoxic effects on L929 cells, with no statistically significant differences among the groups. None of the materials demonstrated antibacterial activity, as indicated by the absence of inhibition zones against both S. mutans and E. faecalis. Conclusions: The evaluated glass ionomer-based and alkasite restorative materials induced significant cytotoxic and genotoxic responses in vitro but showed no antibacterial efficacy. These findings underline the necessity for further in vivo investigations to determine their clinical safety and long-term biocompatibility
Correction: Ketamine versus morphine for musculoskeletal trauma pain: a meta-analysis of randomized controlled trials
No full textIn the original version of this article, the last line in Methods and materials section under abstract which previously read as Heterogeneity was evaluated with Cochrane’s Q statistic and Hedges’ g I2 estimation. But now it should read as Heterogeneity was evaluated with Cochrane’s Q statistic and I2 estimation. And the line in data analysis under methods section which previously appeared as The between-study heterogeneity was assessed using Cochrane’s Q statistic and Hedges’ g I2 estimation. But now it should appear as shown below Effect size was expressed as Hedges’ g with 95% confidence interval. The between-study heterogeneity was assessed using Cochrane’s Q statistic I2 estimation
A Distributed Approach for Frequency Stabilization in Grid-Connected Oil Facilities Using Metaheuristics and Fuzzy Logic
No full textWith oil fields expressing an increasing need for dependable and renewably powered systems, considerable attention is being directed towards hybrid renewably integrated grid-connected microgrids. This work implements the assimilation of the Hawkfish Optimization Algorithm coupled with fuzzy logic for a hybrid microgrid metaheuristic approach to control frequency stabilization. This research focuses on a hybrid unit which consists of wind turbines, solar photovoltaics, and conventional fuel subsystems. This approach deals explicitly with the intrinsic instability of the intermittent renewable resources as they pose serious challenges to the frequency stability of the microgrid. For the proposed method, the hybrid system is first modeled, followed by system design of three control schemes which include classical PI, fuzzy PI, and an HFOA-optimized fuzzy PI control scheme. Simulation results demonstrate the dominance of HFOA-optimized fuzzy control in terms of system dynamic response control, parameter variation and load disturbance disturbance robustness, and in control of disturbance rejection among the three. Additionally, to complete the proposed control architecture on the control hierarchy, a set of Distributed Energy Resources (DERs) which include Fuel Cells, Battery Energy Storage Systems (BESS), and Flywheel Energy Storage Systems (FESS) is controlled on different subsystems of control hierarchy. The application of intelligent control methods, particularly the combination of fuzzy logic and HFOA, enhances the reliability, competence, and frequency control of advanced microgrid systems. This research advances the implementation of intelligent control methods in renewable energy dominant microgrids and aids the transition towards more intelligent resilient power systems
Modified YOLOv8x model for coronary stenosis detection and troponin risk stratification
Full text linkDetection of coronary artery stenosis and risk stratification of troponin plays a pivotal role in offering early diagnosis and treatment of cardiovascular diseases. In this paper, an improved deep learning framework that allows using both spatial and frequency-based attention mechanisms will be proposed using a modified YOLOv8x framework. Upon benchmarking YOLOv8, YOLOv9 and YOLOv10 models, YOLOv8x was chosen due to its excellent baseline and the enhancement was done to make it more clinical relevant. The proposed model was found to have a precision of 0.991, a recall value of 0.960, F1-score of 0.980, and a mAP of 0.976. These findings show significant possibilities of real world applications. The effectiveness of the improvements is in addition validated by large-scale ablation studies, and the results overcome the problem of detecting fine lesions and disparate clinical information. The work has added value in the form of a reliable end-to-end diagnostic cardiovascular imaging and biomarker-based risk analysis