Search Results (1,712)

In recent years, computational intelligence techniques have significantly contributed to the automation and optimization of trading strategies. Despite the increasing sophistication of predictive models, classical technical indicators such as dual Simple Moving Averages (2-SMA) remain popular due to their simplicity and interpretability. This work proposes an adaptive trading system that combines the 2-SMA strategy with a learning-based metaheuristic optimizer known as the Learning-Based Linear Balancer ($L{B}^2$). The objective is to dynamically adjust the strategy’s parameters to maximize returns in the highly volatile cryptocurrency market. The proposed system is evaluated through simulations using historical data of the BTCUSDT futures contract from the Binance platform, incorporating real-world trading constraints such as transaction fees. The optimization process is validated over 34 training/test splits using overlapping 60-day windows. Results show that the $L{B}^2$-optimized strategy achieves an average return on investment (ROI) of 7.9% in unseen test periods, with a maximum ROI of 17.2% in the best case. Statistical analysis using the Wilcoxon Signed-Rank Test confirms that our approach significantly outperforms classical benchmarks, including Buy and Hold, Random Walk, and non-optimized 2-SMA. This study demonstrates that hybrid strategies combining classical indicators with adaptive optimization can achieve robust and consistent returns, making them a viable alternative to more complex predictive models in crypto-based financial environments. Full article

This study examines the variation and trends in wave parameters across the Arctic, including the marginal ice zone (MIZ), by comparing historical data (1980–2009) with projections for a future climate scenario (2070–2099) as outlined by the IPCC. Utilizing the WAVEWATCH III (WW3) numerical wave prediction model, we simulate the wave climate for these periods, incorporating advanced parameterizations to account for wave-ice interactions within the MIZ. Our analysis focuses on the extreme values of significant wave heights (Hs), mean wave periods (T0), and dominant mean wave direction (MWD), calculated for both winter and summer seasons. To assess changes in wave climate under future climate scenarios, we first use a similarity matrix, applying the kappa variable and cell-by-cell numerical comparison methods to assess model congruence across different conditions. We also follow a standard approach, by assessing the extreme wave conditions for 20 and 100-year return periods using standard stochastic models, including Gumbel, exponential, and Weibull distributions. Full article

The digitalization of financial systems has intensified risks such as cyber fraud, data breaches, and financial exclusion, particularly for individuals with low digital financial literacy (DFL). As digital finance becomes ubiquitous, DFL has emerged as a critical competency. However, the determinants of DFL remain insufficiently explored. This study aims to validate a comprehensive, theory-driven model that identifies the key sociodemographic, economic, and psychological factors that influence DFL acquisition among investors. Drawing on six established learning and behavioral theories—we analyze data from 158,169 active account holders in Japan through ordinary least squares regression. The results show that higher levels of DFL are associated with being male, younger or middle-aged, highly educated, and unemployed and having greater household income and assets. In contrast, being married, having children, holding a myopic view of the future, and high risk aversion are linked to lower DFL. Interaction effects show a stronger income–DFL association for males and a diminishing return for reduced education with age. Robustness checks using a probit model with a binary DFL measure confirmed the OLS results. These findings highlight digital inequalities and behavioral barriers that shape DFL acquisition. This study contributes a validated framework for identifying at-risk groups and supports future interventions to enhance inclusive digital financial capabilities in increasingly digital economies. Full article

Background: Understanding the mechanisms underlying dental pain caused by pulpitis in humans has led to the development of animal models, such as the rat, which enable the study of the mechanisms underlying inflammation; the use of these models is considered ethically justified when the anticipated scientific benefits outweigh the potential impacts on animals in the harm/benefit balance. Objective: To develop a rat model of mechanically induced pulpitis and to evaluate the potential impact on animal well-being. Methods: Pulpitis was mechanically induced in male Lewis rats (13–16 weeks, 350–400 g) which were anesthetized and endotracheally intubated. Following pulp exposure, the cavity was sealed with either amalgam (n = 10) or zinc phosphate cement (n = 10). Following recovery and return to their housing, behavioral assessments and histological evaluations using Hematoxylin and Eosin (H&E) staining were conducted in separate cohorts at two time points: 3 h and 5 days following the procedure. Results: A standardized model of mechanically induced pulpitis was established and verified clinically and by histopathological analysis, which showed evidence of the inflammatory process and revealed no statistically significant differences in the scoring of pain, discomfort, or distress, nor in the measurements of food and water consumption or body weight. Conclusions: The behavioral assessments conducted in this study supported the implementation of a safe and easily reproducible model for future research aimed at elucidating the mechanisms underlying pulp inflammation. Full article

The purpose of this study is to investigate the factors that influence tourist behavior and revisit intentions in the context of halal tourism. The antecedent variables in this study included religiosity, digital halal literacy, halal destination features, contentment, and trust. This is a quantitative study that used travelers that visited halal tourism attractions in West Sumatra, Indonesia, as the sample population. The sample size was 400 respondents. The data were analyzed using the partial least squares–structural equation model (PLS-SEM). We discovered that religiosity is an important predictor of contentment and trust. Satisfaction was achieved through digital halal literacy and halal destination qualities and was found to have a significant influence on trust, tourist behavior, and revisit intentions. Finally, trust was found to have a significant association with intention to revisit and behavior. The results of this research are insightful for managers and policymakers on how to provide halal tourism attributes and analyze tourists’ digital halal literacy that lead to tourist satisfaction. This study also provides further knowledge to policymakers and local authorities on how to promote future tourist participation in halal tourism development in Indonesia; thus, it can help create more tourist returns for further visits to the same location in the future. Full article

Background/Objectives: The COVID-19 pandemic caused pronounced disorder in healthcare delivery globally, including ophthalmology. Our study explores how ophthalmologists in Puerto Rico (PR) altered their practices during the pandemic, confronting obstacles such as resource shortages, evolving public health mandates, and unique socio-economic and geographic constraints. The study aims to enhance preparedness for future public health crises. Methods: We conducted descriptive analyses on four online surveys distributed at crucial time points of the pandemic (March 2020, May 2020, August 2020, August 2021) to all practicing ophthalmologists in PR (N ≈ 200), capturing data on closures, patient volume, personal protective equipment (PPE) access, telemedicine use, and financial relief. Results: Survey responses ranged from 41% (n = 81) to 56% (n = 111). By March 2020, 22% (24/111) of respondents closed their offices. By May 2020, 20% (19/93) of respondents maintained a closed office, while 89% (64/72) of open offices reported seeing less than 25% of their usual patient volume. Access to PPE was a challenge, with 59% (65/111) reporting difficulty obtaining N95 masks in March 2020. Telemedicine usage increased initially, peaking in May 2020 and declining in July 2020. By August 2021, all respondents were fully vaccinated and most practices returned to pre-pandemic levels. Overall, 86% (70/81) of respondents found the surveys to be useful for navigating practice changes during the pandemic. Conclusions: PR ophthalmologists showed adaptability during the COVID-19 pandemic to maintain care given limited resources. Guidelines from professional organizations and real time surveys play an important role in future crisis preparedness. Full article

This study investigates the predictive performance of financial indicators in forecasting stock prices within the automotive sector using an adaptive neuro-fuzzy inference system (ANFIS). In light of the growing complexity of global financial markets and the increasing demand for automated, data-driven forecasting models, this research aims to identify those financial ratios that most accurately reflect price dynamics in this specific industry. The model incorporates four widely used financial indicators, return on assets (ROA), return on equity (ROE), earnings per share (EPS), and profit margin (PM), as inputs. The analysis is based on real financial and market data from automotive companies, and model performance was assessed using RMSE, nRMSE, and confidence intervals. The results indicate that the full model, including all four indicators, achieved the highest accuracy and prediction stability, while the exclusion of ROA or ROE significantly deteriorated model performance. These findings challenge the weak-form efficiency hypothesis and underscore the relevance of firm-level fundamentals in stock price formation. This study’s sector-specific approach highlights the importance of tailoring predictive models to industry characteristics, offering implications for both financial modeling and investment strategies. Future research directions include expanding the indicator set, increasing the sample size, and testing the model across additional industry domains. Full article

Implementing nature-based solutions (NbSs) for wildfire risk management and other hazards has been challenging in emerging economies due to the high costs, the lack of immediate returns on investment, and stringent inclusion criteria set by organizations like the IUCN and domain experts. To address these challenges, this exploratory study proposes a new concept: green/blue initiatives. These initiatives represent intermediate steps, encompassing small-scale, community-driven activities that can evolve into recognized NbSs over time. To explore this concept, experiences related to wildfire prevention in the Biobío region of Chile were analyzed through primary and secondary source reviews. The analysis identified three initiatives qualifying as green/blue initiatives: (1) goat grazing in Santa Juana to reduce fuel loads, (2) a restoration prevention farm model in Florida called Faro de Restauración Mahuidanche and (3) the Conservation Landscape Strategy in Nonguén. They were examined in detail using data collected from site visits and interviews. In contrast to Chile’s prevailing wildfire policies, which focus on costly, large-scale fire suppression efforts, these initiatives emphasize the importance of reframing wildfire as a manageable ecological process. Lastly, the challenges and enabling factors for adopting green/blue initiatives are discussed, highlighting their potential to pave the way for future NbS implementation in central Chile. Full article

Current rehabilitation protocols for transitioning patients to late-stage recovery, evaluating return-to-play (RTP) clearance, and assessing tendon characteristics exhibit significant heterogeneity. Clinicians frequently interpret and apply research findings based on individual philosophies, resulting in varied RTP criteria and performance expectations. Despite medical clearance, patients recovering from Achilles tendon (AT) injuries often exhibit persistent impairments in muscle volume, tendon structure, and force-generating capacity. Inconsistencies in assessment frameworks, compounded by a lack of quantitative data and the utilization of specific metrics to quantify certain strength characteristics (endurance, maximal, explosive, etc.) and standardized protocols, hinder optimal functional recovery of the plantar flexors during the final stages of rehabilitation and RTP. With this in mind, the aim of this integrative review was to provide an overview of AT rehabilitation, with particular critique around mid-stage strengthening and the use of the heel-raise assessment in milestoning rehabilitation progress. From this critique, new perspectives in mid-stage strengthening are suggested and future research directions identified. Full article

Augmented reality (AR), which overlays digital content within the user’s view, is gaining traction across domains such as education, healthcare, manufacturing, and entertainment. The hardware constraints of commercially available HMDs are well acknowledged, but little work addresses what design or interactions techniques developers can employ or build into experiences to work around these limitations. We conducted a scoping literature review, with the aim of mapping the current landscape of design principles and interaction techniques employed in near-field AR environments. We searched for literature published between 2016 and 2025 across major databases, including the ACM Digital Library and IEEE Xplore. Studies were included if they explicitly employed design or interaction techniques with a commercially available HMD for near-field AR experiences. A total of 780 articles were returned by the search, but just 7 articles met the inclusion criteria. Our review identifies key themes around how existing techniques are employed and the two competing goals of AR experiences, and we highlight the importance of embodiment in interaction efficacy. We present directions for future research based on and justified by our review. The findings offer a comprehensive overview for researchers, designers, and developers aiming to create more intuitive, effective, and context-aware near-field AR experiences. This review also provides a foundation for future research by outlining underexplored areas and recommending research directions for near-field AR interaction design. Full article

The integration of renewable energy into power grids is imperative for reducing carbon emissions and mitigating reliance on depleting fossil fuels. In this paper, we develop symmetric and asymmetric evolutionary game-theoretic models to analyze how user–grid cooperation in peak shaving can be enhanced by incorporating whole-process democracy (deliberative governance) into decision-making. Our framework captures excess returns, cooperation-driven profits, energy pricing, participation costs, and benefit-sharing coefficients to identify equilibrium conditions under varied subsidy, cost, and market scenarios. Furthermore, this study integrates the theory, path, and mechanism of deliberative procedures under the perspective of whole-process democracy, exploring how inclusive and participatory decision-making processes can enhance cooperation in renewable energy systems. We simulate seven scenarios that systematically adjust subsidy rates, cost–benefit structures, dynamic pricing, and renewable-versus-conventional competitiveness, revealing that robust cooperation emerges only under well-aligned incentives, equitable profit sharing, and targeted financial policies. These scenarios systematically vary these key parameters to assess the robustness of cooperative equilibria under diverse economic and policy conditions. Our findings indicate that policy efficacy hinges on deliberative stakeholder engagement, fair profit allocation, and adaptive subsidy mechanisms. These results furnish actionable guidelines for regulators and grid operators to foster sustainable, low-carbon energy systems and inform future research on demand response and multi-source integration. Full article

Osteochondritis Dissecans (OCD) is a joint condition characterized by damage to the surface of the joint and the underlying subchondral bone, leading to early-onset osteoarthritis. It predominantly affects the knee, elbow, and ankle, with higher prevalence in juveniles actively participating in sports, which complicates the condition due to slow healing processes and prolonged restrictions on physical activities. This review aims to summarize current knowledge on OCD in athletes, with emphasis on sport-specific risk factors, diagnosis, and treatment, to support clinical decision-making and future research. We conducted searches in the PubMed and Embase databases, covering the period from 2014 to 2024. The keywords used in the search covered most common sports in combination with term osteochondritis dissecans. This review examines the impacts of various sports on the development of OCD, analyzing prevalence and risk factors, with a focus on sports-specific risks across athletic disciplines like football, basketball, baseball, and gymnastics. The significance of early detection, intervention, and sport-specific conditioning is underscored to prevent the condition and manage it effectively. Moreover, the review highlights the positive prognosis for athletes, particularly adolescents, recovering from OCD, with a high rate of return to sport. Understanding the sports-specific risks, ensuring early intervention, and adopting a cautious, stepwise return to sport are critical for managing OCD effectively, thereby safeguarding the health and careers of athletes. Full article

Background/Objectives: In late 2019, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a pandemic called the ‘coronavirus disease 2019’ (COVID-19). After the acute SARS-CoV-2 infection, many individuals (up to 33%) complained of unexplained symptoms involving multiple organ systems and were diagnosed as having Long COVID-19 (LC-19). Currently, LC-19 is inadequately defined, requiring the formation of consistent diagnostic parameters to provide a foundation for ongoing and future studies of epidemiology, risk factors, clinical characteristics, and therapy. LC-19 represents a significant burden on multiple levels. The reduced ability of workers to return to work or compromised work efficiency has led to consequences at national, economic, and societal levels by increasing dependence on community services. On a personal scale, the isolation and helplessness caused by the disease and its subsequent impact on the patient’s mental health and quality of life are incalculable. Methods: In this paper, we used Walker and Avants’ eight-step approach to perform a concept analysis of the term “Long COVID-19” and define its impact across these parameters. Results: Using this methodology, we provide an improved definition of LC-19 by connecting the clinical symptomology with previously under-addressed factors, such as mental, psychological, economic, and social effects. This definition of LC-19 features can help improve diagnostic procedures and help plan relevant healthcare services. Conclusions: LC-19 represents a complex and pressing public health challenge with diverse symptomology, an unpredictable timeline, and complex pathophysiology. This concept analysis serves as a tool for improving LC-19 definition, but it remains a dynamic disease with evolving diagnostic and therapeutic approaches, requiring deeper investigation and understanding of its long-term effects. Full article

The likely increase in the frequency and severity of droughts with climate warming will pose an enormous challenge for the conservation of forest biodiversity. Documenting the response of species to recent droughts can inform future conservation actions. Mammals that breed and mature slowly may be especially vulnerable to drought-induced disruption to breeding. The yellow-bellied glider (Petaurus australis, Shaw) is a threatened low-density, arboreal marsupial of eastern Australia. Following a severe drought in 2019, one population had declined by 48% by 2021. The present study investigated whether this population had recovered 3–4 years (2022 and 2023) after that drought. Audio surveys of this highly vocal species were conducted at 42 sites, sampling > 1000 h per year, and producing recordings of 2038–2856 call sequences. The probability of occupancy varied little across the two survey years (0.92–0.97). Local abundance in 2023 had returned to pre-drought levels (45% of occupied sites had ≥3 individuals compared to 6% in 2021). These findings show a recovery from a drought-induced decline required at least 3 years, in keeping with the slow life history traits of this species. This study highlights the importance of considering a species’ life history strategy when evaluating its sensitivity to drought. Full article

Straw-returning is an effective way to improve straw utilization efficiency and reduce environmental pollution. Various straw-returning methods exist; however, their effects on soil microbial diversity and community composition in cool regions have been little studied. This study investigated the changes of soil microbial diversity and community composition under three straw-returning methods, i.e., straw mulching, straw mulching and overturning, straw crushed and mixed, as compared to straw removal as control. The results showed that straw-returning could alter the soil microbial community composition and abundance compared with straw removal. Alpha diversity analysis showed that straw mulching treatment, and straw crushed and mixed treatment significantly increased the diversity of both soil bacteria and fungi compared with straw mulching and overturning treatment. Moreover, this study preliminarily screened Trichoderma, Chaetomium and Streptomyces as potential straw-degrading microorganisms. This study provides basis for further enhancement of straw degradation by using soil microorganisms and sheds light on future work for improving straw degradation efficiency. Full article