Search Results (9,935)

Particle Swarm Optimization (PSO) is a widespread evolutionary technique that has successfully solved diverse optimization problems across various application fields. However, when dealing with more complex optimization problems, PSO can suffer from premature convergence and may become stuck in local optima. The primary goal is accelerating convergence and preventing solutions from falling into these local optima. This paper introduces a new approach to address these shortcomings and improve overall performance: utilizing a reinforcement deep learning method to carry out online adjustments of parameters in a homogeneous Particle Swarm Optimization, where all particles exhibit identical search behaviors inspired by models of social influence among uniform individuals. The present method utilizes an online parameter control to analyze and adjust each primary PSO parameter, particularly the acceleration factors and the inertia weight. Initially, a partially observed Markov decision process model at the PSO level is used to model the online parameter adaptation. Subsequently, a Hidden Markov Model classification, combined with a Deep Q-Network, is implemented to create a novel Particle Swarm Optimization named DPQ-PSO, and its parameters are adjusted according to deep reinforcement learning. Experiments on different benchmark unimodal and multimodal functions demonstrate superior results over most state-of-the-art methods regarding solution accuracy and convergence speed. Full article

Self-paced exercise protocols have gained attention for their potential to optimize performance and manage fatigue by allowing individuals to regulate their efforts based on perceived exertion. This pilot study aimed to investigate the neural and physiological responses during a self-paced V̇O₂max (SPV) and incremental exercise tests (IET). Six trained male cyclists (mean age 39.2 ± 13.3 years; V̇O₂max 54.3 ± 8.2 mL·kg⁻¹·min⁻¹) performed both tests while recording their brain activity using electroencephalography (EEG). The IET protocol involved increasing the power every 3 min relative to body weight, while the SPV allowed participants to self-regulate the intensity using ratings of perceived exertion (RPE). Gas exchange, EEG, heart rate (HR), stroke volume (SV), and power output were continuously monitored. Statistical analyses included a two-way repeated measures ANOVA and Wilcoxon signed-rank tests to assess differences in alpha and beta power spectral densities (PSDs) and the EEG/V̇O₂ ratio. Our results showed that during the SPV test, the beta PSD initially increased but stabilized at around 80% of the test duration, suggesting effective management of effort without further neural strain. In contrast, the IET showed a continuous increase in beta activity, indicating greater neural demand and potentially leading to an earlier onset of fatigue. Additionally, participants maintained similar cardiorespiratory parameters (V̇O₂, HR, SV, respiratory frequency, etc.) across both protocols, reinforcing the reliability of the RPE scale in guiding exercise intensity. These findings suggest that SPV better optimizes neural efficiency and delays fatigue compared to fixed protocols and that individuals can accurately control exercise intensity based on perceived exertion. Despite the small sample size, the results provide valuable insights into the potential benefits of self-paced exercise for improving adherence to exercise programs and optimizing performance across different populations. Full article

Borderline personality disorder (BPD) is a complex psychiatric disorder characterized by an unstable sense of self and identity, emotional dysregulation, impulsivity, and disturbed interpersonal relationships. This narrative review examines the interplay between dysregulation of the autonomic nervous system, metabolic changes, and cardiovascular risk in BPD. Altered heart rate variability (HRV), reflecting the dysregulation of the autonomic nervous system, is associated with some BPD core symptoms, such as emotional instability and impulsivity. Dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis, often stemming from early trauma, contributes to chronic inflammation and elevated allostatic load, which further increases cardiovascular risk. Metabolic dysfunctions in BPD, such as elevated body mass index (BMI), high blood pressure, and inflammatory markers like C-reactive protein (CRP), exacerbate these risks. Speckle-tracking echocardiography, particularly global longitudinal strain (GLS) and biomarkers such as homocysteine and epicardial fat, could be considered early predictors of cardiovascular events in individuals with BPD. Chronic stress, inflammation, and maladaptive stress responses further heighten cardiovascular vulnerability, potentially accelerating biological aging and cognitive decline. A literature search covering the period from 2014 to 2024 on PubMed identified 189 studies on this topic, of which 37 articles were deemed eligible for this review. These included cross-sectional, longitudinal, case–control, randomised controlled trials (RCTs) , reviews, and meta-analysis designs, with sample sizes ranging from 14 to 5969 participants. The main limitations were that only one database was searched, the time of publications was limited, non-English manuscripts were excluded, and the quality of each paper was not commented on. This narrative review aims to provide an overview of recent evidence obtained on this topic, pointing out a direction for future research. Full article

Background and objectives: Drunkorexia is a novel alcohol-related disorder prevalent among adolescents and young adults. Extensive research on the causes and their relationship is lacking. Identifying these aspects could improve early detection and management by healthcare professionals. The aim of this review was to identify the influencing factors of drunkorexia in adolescents and young adults, as well as the main opportunities for action by health professionals. Methods: A scoping review was conducted in June and July 2024 using three databases (Pubmed, Scopus, and Web of Science). A search and review protocol were established and registered in PROSPERO. The research questions were formulated in Patient, Concept, Context (PCC) formats for an adequate literature review. Original articles from January 2008 to July 2024 were included. Reviews, meta-analyses, and doctoral theses or academic texts were excluded. In the screening phase, a methodological assessment was conducted using the Joanna Briggs Institute’s (JBI) critical appraisal tools to support study eligibility. Depending on the study design, different checklists were used, and cross-sectional studies that received scores of 4/8 or higher, quasi-experimental designs that obtained 5/9 or higher, and qualitative research that obtained 5/10 or higher were accepted. Results: A total of 1502 studies were initially found. After applying the inclusion/exclusion criteria, 20 studies were selected. Complications of emotion regulation, both positive and negative metacognitive beliefs, inability to effectively manage stress and anxiety, symptoms of post-traumatic stress disorder, self-discipline and self-control, or differences in social expectations are predisposing factors for drunkorexia. The management of malnutrition and dehydration is an opportunity for clinical professionals to address this problem. In addition, mental health issues can provide another opportunity to manage heavy alcohol consumption. Conclusions: Drunkorexia must be recognized as a new disease to be addressed from a multidisciplinary perspective. In this way, increasing research on this trend would support prevention and intervention strategies. The use of digital platforms is essential for raising social awareness of this negative habit. Full article

Thermal management presents a significant challenge in electric design, particularly in densely packed electronic systems. This study proposes a theoretical model for radiative bionic skin that emulates human skin, enabling the self-adaptive modulation of the thermal exhaustion rate to maintain homeostasis for objects covered by the skin in fluctuating thermal environments. The proposed artificial skin consists of phase change material (VO₂) nanoparticles embedded in a low-loss matrix situated on a metallic substrate with a minimal thickness of several micrometers. The findings from our theoretical analyses indicate that substantial alterations in thermal radiation power around the phase transition temperature of 340 K enable a silicone substrate to sustain a relatively stable temperature, with variations confined to ±6 K, despite external heat fluxes ranging from 150 to 450 W/m². Furthermore, to improve the spectral resemblance to natural skin, a plasmonic surface composed of self-assembled silver nanocubes is incorporated, allowing for modifications to the visible light properties of the bionic skin while maintaining its infrared characteristics. This theoretical investigation offers a cost-effective and conformal approach to the design of ultra-compact, fully passive, and versatile thermal management solutions for robotic systems and related technologies. Full article

With the deep integration of psychology and artificial intelligence technology and other related technologies, eye control technology has achieved certain results at the practical application level. However, it is found that the accuracy of the current single-modal eye control technology is still not high, which is mainly caused by the inaccurate eye movement detection caused by the high randomness of eye movements in the process of human–computer interaction. Therefore, this study will propose an intent recognition method that fuses facial expressions and eye movement information and expects to complete an eye control method based on the fusion of facial expression and eye movement information based on the multimodal intent recognition dataset, including facial expressions and eye movement information constructed in this study. Based on the self-attention fusion strategy, the fused features are calculated, and the multi-layer perceptron is used to classify the fused features, so as to realize the mutual attention between different features, and improve the accuracy of intention recognition by enhancing the weight of effective features in a targeted manner. In order to solve the problem of inaccurate eye movement detection, an improved YOLOv5 model was proposed, and the accuracy of the model detection was improved by adding two strategies: a small target layer and a CA attention mechanism. At the same time, the corresponding eye movement behavior discrimination algorithm was combined for each eye movement action to realize the output of eye behavior instructions. Finally, the experimental verification of the eye–computer interaction scheme combining the intention recognition model and the eye movement detection model showed that the accuracy of the eye-controlled manipulator to perform various tasks could reach more than 95 percent based on this scheme. Full article

Field positioning (FP) is a key technique in the digitalization of agriculture. By integrating sensors and mapping techniques, FP can convey critical information such as soil quality, plant distribution, and topography. Utilizing vehicles for field applications provides precise control and scientific management for agricultural production. Compared to conventional methods, which often struggle with the complexities of field conditions and suffer from insufficient accuracy, this study employs a novel approach using self-developed multi-sensor array hardware as a portable field topographic surveying device. This innovative setup effectively navigates challenging field conditions to collect raw data. Data fusion is carried out using the Unscented Kalman Filter (UKF) algorithm. Building on this, this study combines the good point set and Opposition-based Differential Evolution for a joint improvement of the Slime Mould Algorithm. This is linked with the UKF algorithm to establish loss value feedback, realizing the adaptive parameter adjustment of the UKF algorithm. This reduces the workload of parameter setting and enhances the precision of data fusion. The improved algorithm optimizes parameters with an efficiency increase of 40.43%. Combining professional, mapping-grade total stations for accuracy comparison, the final test results show an absolute error of less than 0.3857 m, achieving decimeter-level precision in field positioning. This provides a new application technology for better implementation of agricultural digitalization. Full article

This study proposes a deep learning-based method for monitoring the growth of Botrytis cinerea and evaluating the effectiveness of control measures. It aims to address the limitations of traditional statistical analysis methods in capturing non-linear relationships and multi-factor synergistic effects. The method integrates colony growth environment data and images as network inputs, achieving real-time prediction of colony area through an improved RepVGG network. The innovations include (1) combining channel attention mechanism, multi-head self-attention mechanism, and multi-scale feature extractor to improve prediction accuracy and (2) introducing the Shapley value algorithm to achieve a precise quantitative analysis of environmental variables’ contribution to colony growth. Experimental results show that the validation loss of this method reaches 0.007, with a mean absolute error of 0.0148, outperforming other comparative models. This study enriches the theory of gray mold control and provides information technology for optimizing and selecting its inhibitors. Full article

Background/Objectives: Numerous risk factors of cardiac diseases are influenced by health behaviours. An individual’s health behaviours, somatic symptoms and even cardiac outcomes can be influenced by their personality. The aim of this study was to analyse the influence of personality traits on the knowledge and health behaviour of cardiac patients. Methods: The study was conducted at the Independent Public Voivodship Hospital in Szczecin on 180 patients in the invasive cardiology wards and the intensive cardiac care unit between July and September 2019. A self-developed questionnaire and the NEO-Five-Factor Inventory-3 (NEO-FFI) and Health Behaviour Inventory (HBI) standardised tools were used. Results: Respondents mostly linked the occurrence of cardiovascular disease with smoking (87.22%) and hypertension (85.56%). A large majority of the respondents (68.44%) knew the correct recommended values for blood pressure. This was also the case for total cholesterol—only 20.56% of the patients did not know the correct levels. Respondents experienced more difficulty in adhering to preventive measures—only 27.22% followed a low-fat diet and only half controlled their weight. The overall HBI scale score was 5.93 sten, which indicates an average score. The most intense personality trait among the respondents was extraversion (5.79), while the least intense was agreeableness (4.12). Neuroticism was found to be negatively correlated (p < 0.05) with healthy eating habits and a positive mental attitude. Extroverts, on the other hand, are more likely to take preventive action. Older and non-working individuals are more likely to exhibit health-promoting behaviours in all HBI categories (p < 0.05). Conclusions: The personality traits that have the greatest impact on health behaviour are extraversion, agreeableness and conscientiousness. Health practises also depend on gender, age and work activity. Further research on more diverse groups is needed. Full article

Background: To provide more effective pregraduate patient safety education, understanding medical students’ perceptions of patient safety before pregraduate patient safety education is necessary. Therefore, we conducted this study to examine patient safety awareness among medical students at the time of admission and compare it with that among controls. Methods: In the 2019 academic year, 132 medical school freshmen enrolled at Teikyo University and 166 age-matched, non-medical students enrolled at an affiliated institution within the Teikyo University organization were surveyed using an anonymous and self-administered questionnaire. The questionnaire divided patient safety awareness into three categories: perception, knowledge, and attitude, which were evaluated on a 5-point Likert scale (Cronbach’s alpha coefficient was 0.77). To assess overall patient safety awareness, the total scores were calculated for the item groups on “perception”, “knowledge”, and “attitude” and compared these scores between the two groups. Results: The total scores (mean ± SD) were 104.2 ± 10.2 for medical students and 88.8 ± 9.6 for controls (p < 0.001). In the “perception” and “attitude” item groups, a higher proportion of medical students provided a positive response than controls. In particular, medical students were more motivated to learn about patient safety than the controls. In the “knowledge” item group, neither medical students nor controls provided a high proportion of positive responses. Conclusions: Medical students demonstrated a higher awareness of patient safety than controls and showed a strong sensitivity to patient safety from the time of enrollment. Full article

Waste rock backfilled into a goaf can function as the main load-bearing carrier to support the overlying strata, so the compressive behavior of backfill materials plays a critical role in the effectiveness of strata control. However, in the laboratory, the specimen size also significantly influences on the accurate prediction of compressive deformation in waste rock backfill materials. To assess the influence of the specimen size on compressive behavior in waste rock backfill materials, a WAW-1000D (Changchun Xinte Testing Machine Co., Ltd., Changchun, Jilin Province, China) electric servo-motor testing machine and self-made compressors of different sizes were used to characterize the compressive deformation of waste rock backfill materials with different specimen sizes. The stress–strain relationships and changes in the void ratio of specimens were analyzed, revealing the influence of the specimen size on the compressive behavior. The research found that when the ratio of the inner diameter of compressors to the maximum particle size of specimens is 15:1 and above, the inner diameter of compressors only has a slight influence. Taking a backfill panel in Xinjulong Coal Mine as the engineering context, waste rock with particle sizes in the range of 0~20 mm was backfilled. The measured roof subsidence was 568 mm, matching the measured experimental value. The results provide data to support roof subsidence predictions following waste rock backfill mining. Full article

Background: Hepatitis C virus (HCV) infection presents a significant public health challenge globally, particularly in high-burden countries like Nigeria, where an estimated 2.4 million individuals are living with HCV. HCV self-testing (HCVST) can potentially bridge the significant diagnosis gap and help individuals to determine their HCV status in the privacy of their homes. It offers a solution to overcome barriers related to stigma and limited access to healthcare. In Nigeria, Self-testing for hepatitis C has only been implemented in a pilot research context. This study aimed to assess stakeholder and community awareness and perceptions of HCVST in Nigeria. The findings will provide insights that could inform effective policies and future scale-up programs for HCV control. Methods: A cross-sectional descriptive study was conducted using an online social media survey administered through SurveyMonkey. The survey was disseminated across social media platforms and groups between October–November 2023. Participants included Nigerians (both health professionals and non-health professionals) aged 18 years or older residing in any of the 36 states and the Federal Capital Territory (FCT). Data collected include sociodemographic characteristics, awareness and perceptions of HCVST, and perceived benefits and barriers. Results: Of 321 respondents, 94% perceived HCVST as highly important. While 77% of respondents knew about HIVST, only 58% had prior knowledge of HCVST. The analysis also showed that healthcare workers had greater awareness of HIV self-testing (82.3%) compared to non-healthcare workers (50.0%). Most respondents (88%) were highly likely to recommend HCVST and perceived it as a cost-effective alternative to traditional testing. Key perceived benefits included increased disease detection and control (67%), improved access to testing (21%), and reduced stigma (11%). In the unadjusted model, geographical zone (Southern Nigeria: cOR = 0.49, 95% CI: 0.30–0.77, p = 0.002), work experience (more than 20 years: cOR = 2.79, 95% CI: 1.11–8.07, p = 0.039), and prior awareness of HIV self-testing (cOR = 5.24, 95% CI: 3.00–9.43, p < 0.001) were significant predictors of HCVST awareness. However, in the adjusted model, only prior awareness of HIV self-testing remained significant (aOR = 4.77, 95% CI: 2.62–8.94, p < 0.001). Conclusions: The strong support for HCVST among stakeholders in Nigeria highlights its potential to enhance HCV control, especially within the broader context of infectious diseases like STIs. The greater awareness of HIV self-testing among healthcare workers compared to non-healthcare workers indicates the need for targeted awareness campaigns for non-healthcare populations. Addressing these awareness gaps, leveraging lessons from HIVST, and using existing infrastructure will be crucial. Prioritizing public education, outreach, and effective linkage to care will drive the impact of HCVST in achieving HCV elimination goals and position it as a model for expanding similar STI interventions in Nigeria. Full article

Objectives: This systematic review evaluates the anti-suicidal properties of Lithium in children and adolescents with Bipolar Disorder (BD), addressing gaps in evidence regarding its efficacy and safety in reducing suicidality and self-harming behaviors. Methods: A comprehensive literature search was conducted across PubMed, Web of Science, and Scopus up to February 2024. Eligible studies were those focusing on patients aged 25 years or younger, examining Lithium therapy and its impact on suicidal ideation and behaviors. The review included randomized controlled trials, longitudinal prospective and retrospective studies, and cross-sectional studies, while excluding expert opinions and case reports. Results: Evidence generally supports the efficacy of Lithium in reducing suicidal ideation and self-harming behaviors in youth with BD, though results are mixed. Randomized controlled trials demonstrated its effectiveness in mitigating suicidal thoughts during acute manic episodes, with effects persisting post-treatment. Longitudinal studies suggested that Lithium might offer superior outcomes compared to other mood stabilizers, although its specific impact on suicidality remains inconclusive. Cross-sectional studies and retrospective analyses reveal associations between Lithium use and reduced self-harming behaviors, but causality remains uncertain. While mood-stabilizing effects of Lithium offer potential benefits for reducing suicidality in youth, evidence on its direct impact on emotional dysregulation (ED) and long-term efficacy is limited. Variability in individual responses and adherence issues underscore the need for further research. Future studies should include larger, diverse samples, focus on ED symptoms, and explore Lithium mechanisms in suicidality prevention. Conclusions: Lithium remains a promising treatment for mood stabilization and reduction in suicidality in youth with BD. Full article

This paper presents a programmable digital filtering unit dedicated to operating with signals from infrared (IR) detection modules. The designed device is quite useful for increasing the signal-to-noise ratio due to the reduction in noise and interference from detector–amplifier circuits or external radiation sources. Moreover, the developed device is flexible due to the possibility of programming the desired filter types and their responses. In the circuit, an advanced field-programmable gate array FPGA chip was used to ensure an adequate number of resources that are necessary to implement an effective filtration process. The proposed circuity was assisted by a 32-bit microcontroller to perform controlling functions and could operate at frequency sampling of up to 40 MSa/s with 16-bit resolution. In addition, in our application, the sampling frequency decimation enabled obtaining relatively narrow passband characteristics also in the low frequency range. The filtered signal was available in real time at the digital-to-analog converter output. In the paper, we showed results of simulations and real measurements of filters implementation in the FPGA device. Moreover, we also presented a practical application of the proposed circuit in cooperation with an InAsSb mid-IR detector module, where its self-noise was effectively reduced. The presented device can be regarded as an attractive alternative to the lock-in technique, artificial intelligence algorithms, or wavelet transform in applications where their use is impossible or problematic. Comparing the presented device with the previous proposal, a higher signal-to-noise ratio improvement and wider bandwidth of operation were obtained. Full article

Background: Kidney transplantation is an effective treatment for patients with kidney failure. Despite the advances in technology, a certain number of patients still deteriorate due to improper management. The purpose of this study was to identify the promoting and inhibitory factors that influence recipients’ self-management behaviors after a kidney transplant. Methods: We enrolled participants who had kidney transplants for more than one year, aged ≥20 years from outpatient clinics in Japan. Face-to-face interviews were conducted between April and December 2016. Results: Nine participants were included in this study. By qualitative content analysis, 115 codes and 8 categories were extracted for the factors resulting in maintenance and the promotion of self-management behaviors; those were [attentiveness to changes in one’s own body], [good partnership with medical care providers], [past painful experiences], [establishment of lifestyle habits], [autonomy to protect one’s own body], [support from family and others], [gratitude for kidney donation], and [increased self-efficacy]. We also extracted three categories that inhibited self-management behavior: [fading threat of worsening disease], [shifting priorities], and [decreased motivation to control the disease]. Conclusions: The passage of time after transplant became a barrier to continue self-management. Providing knowledge about the importance of self-management can prevent the deterioration of kidney function over time after a transplant. Full article