Search Results (70)

This review explores the multifaceted roles of the amygdala, focusing on its structural components, projections, physiological aspects, and key functions in emotional processing and fear conditioning. Beyond traditional roles, it examines the amygdala’s involvement in sleep architecture during the NREM and REM phases. In NREM sleep, the amygdala is involved in memory replay and encoding. During REM sleep, it is highly active, contributing to the emotional content of dreams. This state is characterized by increased cerebral blood flow to the amygdaloid complexes and the generation of Ponto–Geniculo–Occipital (PGO) waves, which are linked to vivid visual imagery and emotional experiences. The review establishes a critical link between the amygdala and the cycle of anxiety disorders and sleep disturbances. It explores anxiety disorders’ specific impact on the amygdala and their influence on sleep patterns. Additionally, the review discusses how medications for anxiety disorders and sleep disturbances act on the amygdala. Selective serotonin reuptake inhibitors (SSRIs) regulate amygdala function, affecting emotional responses and connectivity patterns, improving anxiety, and potentially enhancing sleep quality over time. Trazodone, a serotonin antagonist and reuptake inhibitor (SARI), improves sleep by blocking serotonin receptors and is effective in treating post-traumatic stress disorder (PTSD) related sleep disturbances. Benzodiazepines and zolpidem affect sleep architecture and anxiety by selectively enhancing the actions of both endogenous and exogenous GABA through GABA-A receptors. At the same time, agomelatine, an antidepressant with anxiolytic properties, improves sleep quality without disrupting REM sleep and treats insomnia associated with various conditions, including alcohol dependence. The aim of this review is to summarize amygdala functions, with a focus on their role in regulating sleep and affective responses. Moreover, it discusses possible therapeutic targets in the amygdala for anxiety and sleep disorders. Full article

Traditional signal processing methods for rotating machinery fault diagnosis rely heavily on human experience, while deep learning models often suffer from unstable classification boundaries and poor generalization under complex operating conditions. To address these issues, this paper proposes a hybrid fault diagnosis method based on CWT and CNN-DOA-LSSVM. Firstly, CWT is employed to convert one-dimensional vibration signals into high-resolution time-frequency maps, fully highlighting the transient impact features of faults. Secondly, CNNs automatically extract deep discriminative features, avoiding the cumbersome process of manual feature engineering. Thirdly, LSSVM replaces the Softmax classification layer in traditional CNNs to overcome the deficiency of the Softmax classifier in nonlinear classification. Finally, by leveraging the two-stage separation mechanism of exploration and exploitation in DOA, along with its unique forgetting-supplement and dream-sharing strategies, an adaptive optimal configuration of the key parameters of LSSVM is achieved. Validation results on the Southeast University gearbox dataset and the Huazhong University of Science and Technology bearing dataset show that the proposed method achieves average classification accuracies of 99.59% and 99.50%, respectively, demonstrating good performance in both classification accuracy and stability. Full article

This study introduces a novel fusion deep learning framework that integrates a convolutional neural network (CNN), a bidirectional gated recurrent unit (BiGRU), and a self-attention (SA) mechanism to address the shortcomings of conventional linear models in modeling and predicting nonlinear dynamics of sea level changes. To further enhance model adaptability and performance, the Dream Optimization Algorithm (DOA) is incorporated to enable hyperparameter tuning, resulting in the DOA-CNN-BiGRU-SA framework, which significantly improves the model’s ability to predict nonlinear sea level time series. To mitigate the impact of randomness in neural network initialization, we initially employed a default random seed and conducted experiments with data from five tidal stations in Japan. The DOA-CNN-BiGRU-SA framework outperformed seven other relevant models. Subsequently, an extended evaluation was carried out using data from six additional tidal stations, with predictions generated across 30 different random seeds, confirming the model’s competitive accuracy and robustness. Finally, the proposed framework was applied to satellite altimetry data over the entire East and South China Sea region. Two distinct processing strategies yielded regional sea level rise trends of 3.96 ± 0.47 mm/year and 4.02 ± 0.47 mm/year, respectively, over the 1993–2023 period, and these results closely agree with those reported in the China Sea Level Bulletin report in 2023. This paper presents an integrated approach that enables joint optimization of deep learning architectures and investigates the effects of initialization randomness in neural networks, offering a robust technical solution for predicting short-term regional sea level changes. Full article

Controller performance is strongly influenced by its parameters. Estimating these parameters requires an effective estimation approach for obtaining the best possible response. This study proposes a novel methodology for the estimation of controller parameters, utilizing the dream optimization algorithm (DOA) and a new objective function. The proposed method is employed to determine the optimal parameters of various PID controllers used in the automatic voltage regulator (AVR) system. Thus, the suggested objective function consists of transient response metrics and the stability index “integral of time-weighted absolute error ($ITAE$)”. Three different PID controllers are used, which are cascaded PIPD with filter (CPIPDF), cascaded fractional-order PI fractional-order PDF (CFOPIFOPDF), and PIDF. The DOA’s performance is compared with famous and recent optimizers and shows more reliable performance. For example, based on the statistical analysis, the DOA obtained a standard deviation of 0.0042, while the closest competitor obtained 0.0089. Furthermore, the CPIPDF, CFOPIFOPDF, and PIDF controllers are compared under a wide variety of operating conditions. Based on ITAE, the CPIPDF controller achieved lower values than the CFOPIFOPDF and PIDF controllers. Also, the results show that the CPIPDF controller achieves better performance than other published controllers. For instance, the CPIPDF controller improves AVR performance by approximately 45.3% compared to the fireworks whale optimization algorithm-based PIDD² controller in the case of varying load condition impact. Moreover, scenarios that remain insufficiently addressed in the literature, such as communication delays, restricted excitation voltages, and external disturbances, are considered. Full article

The transition toward a circular economy has made industrial symbiosis an important approach for improving resource efficiency and reducing environmental impact, especially for small- and medium-sized enterprises (SMEs). However, the extent to which SMEs can adopt these practices differs across countries. This study aims to explore the readiness of SMEs for industrial symbiosis in Türkiye, Jordan, Portugal, and Croatia, and to propose a digital model that can support this transition. The research is based on a qualitative, literature-driven comparative analysis examining institutional structures, technological capacity, sectoral characteristics, and collaboration networks in each country. The findings indicate that, despite contextual differences, all four countries face similar challenges, such as limited data sharing, insufficient digital infrastructure, and weak inter-firm cooperation. While EU member states demonstrate more developed policy frameworks, implementation gaps remain evident across cases. Building on these insights, the study introduces the Digital Recycling and Material Network (DREAM) model, a digital platform that connects waste-generating firms, recycling companies, and businesses that use secondary raw materials. The model enables real-time data sharing and supports sustainability-oriented matching mechanisms. Overall, the study suggests that digital platforms like DREAM can play a key role in strengthening industrial symbiosis practices and supporting SMEs in their transition toward circular production systems. Full article

This article explores Daniel Kahneman’s concept of system thinking from his book Thinking Fast and Slow (2013) in the context of contemporary spiritual and theological reflection. The question studied here is: What does the intentional use of emotions, dreams and intuition described by Daniel Kahneman as System 1 thinking look like in contemporary spiritual and theological reflection? According to Kanheman, System 1 thinking includes emotions, dreams and intuition. The method for answering the research question is hermeneutical. This means gathering texts that fit Kahneman’s description of System 1 thinking and integrating these concepts into some form of spiritual and theological reflection. Hermeneutical research is text-based. Fifty-three (53) texts were found in a search of various databases. These texts are analyzed noting the impact of System 1 thinking on spiritual and theological reflection. Findings include the following: First, there is a rise in the number of texts using System 1 thinking in spiritual and theological reflection. Second, disciplines outside of theology are practicing spiritual reflection as part of their spiritual care. Third, these non-theological disciplines are also using System 1 thinking in their spiritual reflections. Fourth, there is an awareness and utilization of diverse cultures and faith experiences in spiritual reflection. Fifth, these texts indicate the growth of the demographic of people who are spiritual but not religious and a connection to dreams, emotions and intuition in spiritual and theological reflection. Sixth, there is also a developing overlap between spiritual and theological reflection. Cautions and gaps in the textual analysis are noted as well as future applications. Full article

SWMM (Stormwater Management Model) is one of the most widely used computation tools in urban water resources management. Traditionally, the choice of rainfall data for calibrating the SWMM model has been arbitrary, lacking clarity on the most suitable rainfall types. In addition, the simplification in the SWMM hydrological module of the rainfall–runoff process, coupled with measurement errors, introduces a high level of uncertainty in the calibration. This study investigates the influences of rainfall types on the highly uncertain SWMM model calibration by implementing the Bayesian inference theory. A Bayesian SWMM calibration framework was established, in which an advanced DREAM(zs) (Differential Evolution Adaptive Metropolis, Version ZS) sampling method was used. The investigation focused on eight key hydrological parameters of SWMM. The impact of rainfall types was analyzed using nine rainfall intensities and three rainfall patterns. Results show that rainfall events equivalent to a one-year return period (R5, 42.70 mm total depth) or higher generally yield the most accurate parameters, with posterior distribution standard deviations reduced by 40–60% compared to low-intensity rainfalls. Notably, three parameters (impervious area percentage [Imperv], storage depth of impervious area [S-imperv], and Manning’s coefficient of impervious area [N-imperv]) demonstrated consistent accuracy irrespective of rainfall intensity, with a coefficient of variation below 0.05 for Imperv and S-imperv across all rainfall intensities. Furthermore, it was found that rainfall events with double peaks resulted in more satisfactory calibration compared to single or triple peaks, reducing the standard deviation of the Width parameter from 168.647 (single-peak) to 110.789 (double-peak). The findings from this study could offer valuable insights for selecting appropriate rainfall events before SWMM model calibration for more accurate predictions when it comes to urban non-point pollution control strategies and watershed management. Full article

The proliferation of artificial intelligence (AI) and online services has significantly escalated the demand for computing and storage resources, which are fundamentally enabled by cloud computing infrastructure. As the backbone of cloud computing services, data centers have undergone continuous expansion in scale, consequently leading to significant energy consumption and a significant carbon footprint. To effectively mitigate the environmental impact, the strategy should prioritize the integration of renewable energy, while simultaneously minimizing other contributing factors such as energy consumption. Achieving both objectives simultaneously requires a fine-grained, dynamic approach to workload management. To this end, this study proposes a comprehensive container placement strategy that integrates a dynamic priority-based container selection algorithm with a multi-factor single-objective container placement algorithm based on the Dream Optimization Algorithm (DOA). The placement algorithm converts multiple factors—including load balancing in multi-data center environments, energy consumption, renewable energy utilization rate, carbon emissions, Service Level Agreement Violation (SLAV), and container migration costs—into a comprehensive fitness metric. Experimental results on Google and Alibaba datasets show our method consistently achieves the highest renewable energy utilization rates (up to 92.08%) and the lowest carbon emissions. Furthermore, our integrated strategy demonstrates a superior trade-off, reducing migration counts by up to 16.3% and SLAV by 12.4% compared to baselines, while maintaining excellent green performance. This establishes our method as a practical and effective solution for sustainable cloud computing. Full article

Background: Nightmares are a type of sleep disorder characterised by vivid and distressing dreams that cause abrupt awakenings, leading to significant discomfort. In adults, recurrent nightmares can negatively impact quality of life, daytime functioning, and overall mental health. In this context, it is essential to have valid, reliable, and culturally appropriate psychological instruments that allow for an accurate assessment of this phenomenon. The aim of the present study was to translate and validate the Nightmare Disorder Index (NDI) into Spanish for use with Peruvian adults. Methods: A total of 507 adults (66.7% women) participated by completing a sociodemographic questionnaire and psychological instruments. Statistical analyses were conducted using structural equation modelling and item response theory. Results: The NDI demonstrated adequate content validity (V > 0.70), a unidimensional structure (CFI = 0.99, RMSEA = 0.06 [90% CI: 0.030, 0.102], SRMR = 0.03), and reliability (ω = 0.84, H = 0.94, r_xx = 0.79). In addition, invariance was observed across sex, and significant associations were found with depressive symptoms, generalised anxiety, and suicidal ideation. Item 3 showed the highest discrimination and information, and the scale proved to be accurate at higher levels of nightmare severity. Conclusions: The NDI presents adequate psychometric properties for the inference and interpretation of scores in the assessment of nightmares. Its use is recommended in both professional practice and research with the adult general population. Full article

Background: Bruxism is defined as repetitive activity of the masticatory muscles characterized by clenching or grinding of the teeth and/or stiffening or protrusion of the mandible, referred to as sleep bruxism or awake bruxism. It is believed that in generally healthy individuals, bruxism should not be considered a disorder, but rather a behavior that may be a risk factor (and/or protective factor) for certain clinical consequences. The aim of the study was to assess the occurrence and strength of the correlation between bruxism and sleep disorders (parasomnias and insomnia), as well as to evaluate the correlation between bruxism and the nature of dreams. Methods: The study involved 276 people aged 18–55. The research was conducted using an online survey in the period from January to March 2022. The author’s own questionnaire was composed of five segments of test questions (basic questions, bruxism severity test, Athens Insomnia Scale, parasomnia test, sleep evaluation test). The respondents were divided into groups based on the severity of bruxism, insomnia, parasomnias and the occurrence of dreams related to the oral cavity and teeth. Statistical analysis included Spearman’s correlation coefficients, chi-square test, Kruskal–Wallis ANOVA, and Mann–Whitney U test. Results: The analysis revealed a significant correlation between the severity of bruxism and insomnia symptoms. Participants with moderate and severe bruxism reported insomnia more frequently and with greater intensity. Similar correlations were observed with parasomnias and the frequency of dreams concerning the oral cavity and teeth. The strongest association with bruxism was found for physical dreams. Moreover, correlations were also noted between insomnia and parasomnias. Conclusions: These findings suggest that individuals experiencing bruxism, particularly sleep bruxism, may be more vulnerable to other sleep disturbances. Addressing one of these conditions could potentially have a beneficial impact on the others. Full article

Unmanned aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) systems have developed rapidly in the sixth generation (6G) era. However, factors such as the mobility of ground users and malicious jamming pose significant challenges to systems’ performance and reliability. Against this backdrop, this paper designs a multi-UAV-assisted ISAC system model under malicious jamming environments. Under the constraint of sensing accuracy, the total communication rate of the system is maximized through joint optimization of user association, UAV trajectory, and transmit power. The problem is then decomposed into three subproblems, which are solved using the improved auction algorithm (IAA), dream optimization algorithm (DOA), and rapidly-exploring random trees-based optimizer algorithm (RRTOA). The global optimal solution is approached through the alternating optimization-based predictive scheduling algorithm (AOPSA). Meanwhile, this paper also introduces a long short-term memory (LSTM) network to predict users’ dynamic positions, addressing the impact of user mobility and enhancing the system’s real-time performance. Simulation results show that compared with the baseline scheme, the proposed algorithm achieves a 188% improvement in communication rate, which verifies its effectiveness and superiority. Full article

Background/Objectives: Little is known about experiences of sleep disturbance in dementia amongst South Asian families, the UK’s biggest minority ethnic group. We aimed to explore their experiences of these alongside translation and preliminary cultural adaptation of an existing effective multicomponent intervention, DREAMS-START. Methods: We interviewed family carers of people living with dementia who had participated in the DREAMS-START (n = 7) trial or other dementia studies (n = 4), conducting reflective thematic analysis. We translated DREAMS-START into Hindi and consulted with Hindi speakers with experience in dementia care, revising iteratively. Results: We identified two overarching themes: (i) the experience of dementia-related sleep disturbance in South Asian families, including the impact of multigenerational living, cultural expectations and practices, and existing relationships; and (ii) considerations for culturally adapting DREAMS-START, including language barriers, linguistic and other changes to peripheral elements to increase engagement and relevance, and culturally competent facilitation of the intervention. Conclusions: Consideration of multigenerational family structures, within-member dynamics, culturally appropriate activities and lack of access to support are important during consultation and intervention. It was thought that cultural adaptation of the intervention in language and facilitator cultural competence, including consideration of the schedule of prayer, would increase relevance and thus community access. We will use this preliminary work to inform future cultural adaptation and testing of the intervention with the intention to widen access for UK-based South Asian families. Full article

Background: Namibia is experiencing a generalized HIV epidemic, with 7.5% of the population living with HIV. Adolescent girls and young women (AGYW) aged 15–24 account for 28.6% of new infections annually. Various factors increase AGYW’s vulnerability to HIV. To address this, Project HOPE Namibia (PHN)-led consortium implemented the PEPFAR/USAID-funded DREAMS project in Khomas, Oshikoto, and Zambezi regions from 2018 to 2023. This study estimated the AGYW population most in need of HIV prevention and assessed geographic and age-specific gaps to improve program effectiveness and efficiency. Methods: This secondary data analysis utilized the Namibia Population-Based HIV Impact Assessment (NamPHIA) 2017, the Namibia census, and service data from the DREAMS project, which includes entry points for recruitment, screening, and enrolment. We used Python to conduct unadjusted and adjusted Poisson regression and UpSet plots for data visualization. Results: Analysis of NamPHIA data revealed low HIV prevalence in 10–14-year-olds, with only Oshikoto showing a detectable rate of 2.76%, mostly attributed to perinatal HIV transmission. Of the 12 DREAMS eligibility criteria, three could be mapped to 10–14-year-olds, while all except sexually transmitted infections could be mapped for 15–19 and 20–24-year-olds. Nationally, 17.3% of 10–14-year-old AGYW, 48.0% of 15–19-year-olds, and 50% of 20–24-year-olds met at least one DREAMS eligibility criterion. Among 15–19-year-olds, a history of pregnancy, no/irregular condom use, and out-of-school status were positively associated with HIV status. For 20–24-year-olds, transactional sex was positively associated with HIV status. Overall, 62% of screened individuals were eligible, and 62% of eligible individuals enrolled. PHN screened 134% of the estimated 37,965 10–14-year-olds, 95% of the estimated 35,585 15–19-year-olds, and 57% of the 24,011 20–24-year-olds residing in the five districts where DREAMS was implemented. Conclusions: We recommend the refinement of the DREAMS eligibility criteria, particularly for AGYW 10–14, to better identify and engage those at risk of HIV acquisition through sexual transmission. For 15–19-year-olds, PHN efforts should interrogate geographic variability in entry points for recruitment and screening practices. PHN should enhance the recruitment and engagement of AGYW 20–24, with a particular focus on those engaged in transactional sex. Full article

Background/Objectives: Pathology is often perceived as a technical medical specialty that lacks direct contact with the patient. However, oncological histopathological diagnosis requires a high degree of moral and emotional responsibility. The objective of this study was to investigate how empathy is manifested toward the “invisible” patient, the emotional impact on pathology staff, and potential repercussions in their personal lives. Method: We conducted a descriptive, cross-sectional study with a quantitative component, using an anonymous 22-item questionnaire among Romanian pathologists and medical personnel working in pathology services. The questionnaire was focused on three research directions: professional empathy in the absence of direct patient contact, the emotional impact of oncologic diagnosis on medical personnel in pathology departments, and the carryover of emotions from professional to personal life. A total of 165 respondents were included in the study (physicians, technicians, registrars). Results: Most of the respondents consider that the absence of the patient’s direct contact does not cancel the empathy, this being felt in a cognitive and more natural way. Over 60% of the respondents see oncologic histopathological diagnosis as an emphatic medical act. Over 80% of the respondents experience a sense of emotional responsibility and 70% consider that professional training does not include adequate emotional support. There is a high interest in empathy and psychological support. The professional activity of a pathologist may influence sleep, dreams, and the perception on their own health status. Diagnosing pediatric or young patients is perceived as particularly emotionally challenging. Collegial support is moderate and discussion about professional stress is rare. Conclusions: Empathy is present and relevant in pathology, despite the absence of direct patient interaction. Oncological diagnostics has a significant emotional impact on pathology department personnel, with the need to acknowledge the emotional dimension of the profession and to integrate psychological support mechanisms into pathology practice. Full article

By focussing on the emotional and affective dimensions of borders, this article suggests integrating the negative emotions that the European Union (EU) states’ border politics aim to instil—including fear, anxiety and trauma—with the positive emotions that the dream of a life in Europe encourages. Drawing upon the psychological and philosophical approaches to hope, this article highlights the centrality of hope in shaping agency, stimulating alternative visions, and overcoming difficulties. What is the impact of hope and daydreams in shaping migrants’ decision to engage with risky journeys? To what extent might the dream of Europe counterbalance the EU’s securitarian technologies? This article introduces and explores the processes of b/ordering and the role that emotions, as spatially grounded, play in it. This article will ultimately contend that, once confronted with the uncertainties of long and risky journeys and the prospect of a bright and dreamed future, the latter often prevails. Under this scenario, states’ deterrent systems might not be as effective as hoped, as the dream of Europe overrides the fear and anxiety that EU states’ border security aims to generate. Full article