Search Results (352)

In high-dynamic bipedal locomotion control, robotic systems are often constrained by motor torque limitations, particularly during explosive tasks such as jumping. One of the key challenges in reinforcement learning lies in bridging the sim-to-real gap, which mainly stems from both inaccuracies in simulation models and the limitations of motor torque output, ultimately leading to the failure of deploying learned policies in real-world systems. Traditional RL methods usually focus on peak torque limits but ignore that motor torque changes with speed. By only limiting peak torque, they prevent the torque from adjusting dynamically based on velocity, which can reduce the system’s efficiency and performance in high-speed tasks. To address these issues, this paper proposes a reinforcement learning jump-control framework tailored for tendon-driven bipedal robots, which integrates dynamic torque boundary constraints and torque error-compensation modeling. First, we developed a torque transmission coefficient model based on the tendon-driven mechanism, taking into account tendon elasticity and motor-control errors, which significantly improves the modeling accuracy. Building on this, we derived a dynamic joint torque limit that adapts to joint velocity, and designed a torque-aware reward function within the reinforcement learning environment, aimed at encouraging the policy to implicitly learn and comply with physical constraints during training, effectively bridging the gap between simulation and real-world performance. Hardware experimental results demonstrate that the proposed method effectively satisfies actuator safety limits while achieving more efficient and stable jumping behavior. This work provides a general and scalable modeling and control framework for learning high-dynamic bipedal motion under complex physical constraints. Full article

The use of the Soil and Water Assessment Tool (SWAT) model driven by China Meteorological Assimilation Driving Datasets (CMADS) for runoff simulation research is of great significance for regional flood prevention and control. Therefore, from the perspective of production-living-ecological space, this article combined multi-source data such as DEM, soil texture and land use type, in order to construct scenarios of territorial spatial change (TSC) across distinct periods. Based on the CMADS-L40 data and the SWAT model, it simulated the runoff dynamics in the Xitiaoxi River Basin, and analyzed the hydrological response characteristics under different TSCs. The results showed that The SWAT model, driven by CMADS-L40 data, demonstrated robust performance in monthly runoff simulation. The coefficient of determination (R²), Nash–Sutcliffe efficiency coefficient (NSE), and the absolute value of percentage bias (|PBIAS|) during the calibration and validation period all met the accuracy requirements of the model, which validated the applicability of CMADS-L40 data and the SWAT model for runoff simulation at the watershed scale. Changes in territorial spatial patterns are closely correlated with runoff variation. Changes in agricultural production space and forest ecological space show statistically significant negative correlation with runoff change, while industrial production space change exhibits a significant positive correlation with runoff change. The expansion of production space, particularly industrial production space, leads to increased runoff, whereas the enlargement of agricultural production space and forest ecological space can reduce runoff. This article contributes to highlighting the role of land use policy in hydrological regulation, providing a scientific basis for optimizing territorial spatial planning to mitigate flood risks and protect water resources. Full article

Background/Objectives: Vaccine hesitancy is becoming an increasing concern, leading to preventable outbreaks of infectious diseases. During the COVID-19 pandemic, the United States served as an intriguing case study for exploring how risk perception and trust in health authorities, including scientists, are influenced by government policies and how these factors affect vaccine hesitancy. Methods: We conducted a secondary analysis using the MIT COVID-19 Survey dataset to investigate whether risk perception and trust differ between states governed by Democratic or Republican governors. Results: Our analysis (n = 6119) found that participants did not vary significantly by state political affiliation in terms of their sociodemographic factors (such as age, gender, self-rated health, education, and whether they live in a city, town, or rural area), their perceived risk for the community, or their ability to control whether they become infected. However, there was a difference in the perceived risk of infection, which was higher in states governed by Republicans. Trust also varied by gubernatorial affiliation, with higher levels of trust reported among residents of Democratic-leaning states. We also found a strong mediation effect of trust on vaccine hesitancy, but this was not the case for risk perception. Conclusion: Therefore, it appears that vaccine acceptance relies on trust in health authorities, which is influenced by governmental policies. State officials should work with local health officials to build trust and increase timely responses to public health crises. Full article

Particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and heavy metals (HMs) present in polluted air are strongly associated with an increased risk of respiratory diseases. In our study, we grouped cities based on their pollution levels using a method called Ward’s cluster analysis and looked at the increased cancer risk from PM₁₀-bound harmful substances for adult men and women living in Polish cities. The analysis was based on data from 8 monitoring stations where concentrations of PM₁₀, PAHs, and HMs were measured simultaneously between 2018 and 2022. The cluster analysis made it possible to distinguish three separate agglomeration clusters: cluster I (Upper Silesia, Wroclaw) with the highest concentrations of heavy metals and PAHs, with mean levels of lead 14.97 ± 7.27 ng·m⁻³, arsenic 1.73 ± 0.60 ng·m⁻³, nickel 1.77 ± 0.95 ng·m⁻³, cadmium 0.49 ± 0.28 ng·m⁻³, and ∑PAHs 15.53 ± 6.44 ng·m⁻³, cluster II (Warsaw, Łódź, Lublin, Cracow) with dominant road traffic emissions and low emissions, with average levels of lead 8.00 ± 3.14 ng·m⁻³, arsenic 0.70 ± 0.17 ng·m⁻³, nickel 1.64 ± 0.96 ng·m⁻³, and cadmium 0.49 ± 0.28 ng·m⁻³, and cluster III (Szczecin, Tricity) with the lowest concentration levels with favourable ventilation conditions. All calculated ILCR values were in the range of 1.20 × 10⁻⁶ to 1.11 × 10⁻⁵, indicating a potential cancer risk associated with long-term exposure. The highest ILCR values were reached in Upper Silesia and Wroclaw (cluster I), and the lowest in Tricity, which was classified in cluster III. Our findings suggest that there are continued preventive actions and stricter air quality control. The results confirm that PM₁₀ is a significant carrier of airborne carcinogens and should remain a priority in both environmental and public health policy. Full article

Background: Trauma-related injuries are among the most common reasons for paediatric hospital presentations and represent a substantial component of orthopaedic care. Their management poses unique challenges due to ongoing skeletal development in children. While most reported fractures occur at home or during sports, prior studies have primarily used data from urban European populations, limiting the relevance of their findings for rural and regional settings. Urban-centred research often informs public healthcare guidelines, treatment algorithms, and infrastructure planning, introducing a bias when findings are generalised outside of metropolitan populations. This study addresses that gap by analysing fracture data from two rural trauma centres in New South Wales, Australia. This study assesses paediatric fractures resulting from severe injury mechanisms in rural areas, identifying common fracture types, underlying mechanisms, and treatment approaches to highlight differences in demographics. These findings aim to cast a light on healthcare challenges that regional areas face and to improve the overall cultural safety of children who live and grow up outside of the metropolitan trauma networks. Methods: We analysed data from two major rural referral hospitals in New South Wales (NSW) for paediatric injuries presenting between 1 January 2018 and 31 December 2022. This study included 150 patients presenting with fractures following severe mechanisms of injury, triaged into Australasian Triage Scale (ATS) categories 1 and 2 upon initial presentation. Results: A total of 150 severe fractures were identified, primarily affecting the upper and lower limbs. Males presented more frequently than females, and children aged 10–14 years old were most commonly affected. High-energy trauma from motorcycle (dirt bike) accidents was the leading mechanism of injury among all patients, and accounted for >50% of injuries among 10–14-year-old patients. The most common fractures sustained in these events were upper limb fractures, notably of the clavicle (n = 26, 17.3%) and combined radius/ulna fractures (n = 26, 17.3%). Conclusions: Paediatric trauma in regional Australia presents a unique and under-reported challenge, with high-energy injuries frequently linked to unregulated underage dirt bike use. Unlike urban centres where low-energy mechanisms dominate, rural areas require targeted prevention strategies. While most cases were appropriately managed locally, some were transferred to tertiary centres. These findings lay the groundwork for multi-centre research, and support the need for region-specific policy reform in the form of improved formal injury surveillance, injury prevention initiatives, and the regulation of under-aged off-road vehicular usage. Full article

Workplace violence (WPV) is a prevailing global concern among healthcare providers (HCPs). Pharmacists may be more vulnerable to WPV than other HCPs due to being the most trusted, approachable, and accessible healthcare workers. However, in Saudi Arabia, there is little research on violence in the workplace among pharmacists working in different sectors. This is a cross-sectional survey study. An online survey was adopted from previous studies and distributed to a convenience sample of pharmacists by email and social media using a link to a web-based survey platform in QuestionPro. SPSS 28 was used for analysis. Logistic regression was employed to assess the association between WPV exposure and the participants’ characteristics. Three hundred and nineteen pharmacists participated in the study. A total of 156 (48.9%) reported exposure to workplace violence. Most participants had experienced verbal abuse (39.7%). Most offenders were male (84.6%), and aged 21–45 years (66.7%). Common causes included lack of a penalty (13.3%), and absence of reporting systems (11.4%). Seventy-eight percent of participants reported that the violence affected them negatively, leading to hopelessness (19.7%), and decreased work performance and productivity (15.1%). Logistic regression indicated that working as a staff (OR: 3.165; 95% CI 1.118–8.96, p = 0.030), working evening or night shift (OR: 2.4456; 95% CI 1.340–4.503, p = 0.004), and lacking procedure for reporting the violence (OR: 0.412; 95% CI 0.236–0.717, p = 0.002) were more likely to be victim of workplace violence than their counterparts. In Saudi Arabia, the risk of WPV events occurrence among pharmacists is high. The findings can guide the creation of appropriate policies, actions, and safety procedures to prevent and address WPV against pharmacists. Full article

Harmful Algal Blooms (HABs) are a growing environmental concern due to their adverse impacts on aquatic ecosystems, human health, and economic activities. These blooms are driven by a combination of factors, including nutrient enrichment, environmental factors, and hydrological conditions, leading to the excessive growth of algae. HABs produce toxins that threaten aquatic biodiversity, contaminate drinking water, and cause economic losses in fisheries and tourism. The causes of HABs are multifaceted, involving interactions between environmental factors such as temperature, light availability, and nutrient levels. Agricultural runoff, wastewater discharge, and industrial pollution introduce excessive nitrogen and phosphorus into water bodies, fueling bloom formation. Climate change further exacerbates the problem by altering precipitation patterns, increasing water temperatures, and intensifying coastal upwelling events, all of which create favorable conditions for HAB proliferation. This review explores the causes, ecological consequences, and potential mitigation strategies for HABs. Effective monitoring and detection methods, including satellite remote sensing, molecular biotechnology, and artificial intelligence-driven predictive models, offer promising avenues for early intervention. Sustainable management strategies such as nutrient load reductions, bioremediation, and regulatory policies can help mitigate the adverse effects of HABs. Public awareness and community involvement also play a crucial role in preventing and managing HAB events by promoting responsible agricultural practices, reducing waste discharge, and supporting conservation efforts. By examining existing literature and case studies, this study underscores the urgent need for comprehensive and interdisciplinary approaches to regulate HABs. Full article

The global increase in early-onset cancers among adolescents and young adults has happened at the same time as the rise in the consumption of ultra-processed foods (UPFs). Far beyond their poor nutritional quality, UPFs are increasingly seen as Trojan horses, complex biological agents that interfere with many functions of the human organism. In this review, we utilise the Trojan horse model to explain the quiet and building health risks from UPFs as foods that seem harmless, convenient, and affordable while secretly delivering endocrine-disrupting chemicals (EDCs), causing chronic low-grade inflammation, altering the microbiome, and producing epigenetic alterations. We bring together new proof showing that UPFs mess up hormonal signals, harm the body’s ability to fight off harmful germs, lead to an imbalance of microbes, and cause detrimental changes linked to cancer. Important components, such as bisphenols and phthalates, can migrate from containers into food, while additional ingredients and effects from cooking disrupt the normal balance of cells. These exposures are especially harmful during vulnerable developmental periods and may lay the groundwork for disease many years later. The Trojan horse model illustrates the hidden nature of UPF-related damage, not through a sudden toxin but via chronic dysregulation of metabolic, hormonal, and genetic control. This model changes focus from usual diet worries to a bigger-picture view of UPFs as causes of life-disrupting damage. Ultimately, this review aims to identify gaps in current knowledge and epidemiological approaches and highlight the need for multi-omics, long-term studies and personalised nutrition plans to assess and reduce the cancer risk associated with UPFs. Recognising UPFs as a silent disruptor is crucial in shaping public health policies and cancer prevention programs targeting younger people. Full article

Background: Cardiovascular disease remains a leading cause of preventable mortality in the United States, with rural counties in the Deep South experiencing disproportionately high burdens. Grounded in the Andersen healthcare utilization model, this study examined how enabling resources, predisposing characteristics, and access-related barriers relate to coronary heart disease (CHD) prevalence and mortality. Methods: This ecological analysis included 418 counties across Alabama, Georgia, Louisiana, Mississippi, and South Carolina. Using Local Indicators of Spatial Association (LISA) and multivariable linear regression, we tested three theory-based hypotheses and assessed the spatial clustering of CHD outcomes, while identifying key structural and sociodemographic predictors. Results: Counties with greater rurality and fewer healthcare providers exhibited significantly higher rates of CHD prevalence and mortality. Primary care provider availability and higher household income were protective factors. Digital exclusion, measured by lack of access to computers or mobile devices, was significantly associated with higher CHD prevalence and mortality. Spatial analysis identified the counties with better-than-expected cardiovascular outcomes despite structural disadvantages, suggesting the potential role of localized resilience factors and unmeasured community-level interventions. Conclusions: The findings affirm the relevance of the Andersen model for understanding rural health disparities and highlight the importance of investing in both digital infrastructure and healthcare capacity. Expanding telehealth without addressing provider shortages and social determinants may be insufficient. Local policy innovations and community resilience mechanisms may offer scalable models for improving cardiovascular health in disadvantaged areas. Full article

This study aims to predict and discover important factors for the learning performance of students belonging to two ethnic groups—Khmer and Chinese (Hoa) students—in Soc Trang with the use of random forest (RF) and Gaussian Naïve Bayes (GNB) classifiers based on students’ demographics and grade point average (GPA) scores. The study involved 174 Khmer and Chinese (Hoa) students in Grade 10 in a high school in Soc Trang Province, Vietnam. The results showed that, for Khmer students, GNB was better than RF, with an F1 score of 100%. Mathematics was the most important subject leading Khmer students to very good or poor performance. For Chinese (Hoa) students, both classifiers showed the same accuracy performance. Scores in Literature and English in Semester 1 impacted Chinese (Hoa) students’ performance. The results of this study provide a reference for formulating a policy to improve the learning performance of minority students to prevent dropouts. Full article

Background/Objectives: Maintaining high childhood vaccination coverage is essential to prevent outbreaks of vaccine-preventable diseases. In Italy, Law No. 119/2017 introduced mandatory childhood immunizations, leading to significant improvements. However, the COVID-19 pandemic disrupted routine services, potentially jeopardizing these gains. This study aimed to evaluate national and regional trends in vaccine coverage across three phases: post-mandate (2015–2016 vs. 2017–2019), pandemic (2017–2019 vs. 2020–2021), and post-pandemic recovery (2020–2021 vs. 2022–2023). Methods: National and regional administrative data on vaccination coverage at 24 months of age were obtained from the Italian Ministry of Health. Temporal trends were analyzed using Joinpoint regression to estimate annual percent changes (APCs), and absolute changes in coverage (Δ) were calculated across defined periods. Pearson correlation coefficients were used to assess associations between baseline coverage and subsequent changes. Results: After the 2017 mandate, coverage increased significantly for varicella (APC = +28.6%), MenB (+22.6%), and measles (+3.4%). Regionally, varicella coverage rose by up to +58.4% in Emilia-Romagna and measles by +11.1% in Campania. During the pandemic, coverage declined for polio (−2.4% in the South) and measles (−6.2% in Abruzzo), while MenB increased in regions with lower initial uptake (r = −0.918, p < 0.001). Post-pandemic, coverage rebounded, with varicella improving by +20.1% in central regions and measles by +13.9% in Abruzzo. A strong inverse correlation between baseline coverage and improvement was observed for varicella across all periods (r from −0.877 to −0.915). Conclusions: Mandatory vaccination policies led to substantial coverage improvements, and despite the disruption caused by the pandemic, recovery trends were observed for most vaccines. The consistent association between low baseline coverage and stronger gains highlights the resilience of the system, but also the ongoing need for regionally tailored strategies to reduce geographic disparities and ensure equitable immunization across Italy. Full article

Plateau hypoxia represents a type of hypobaric hypoxia caused by reduced atmospheric pressure at high altitudes. Pressurization therapy is one of the most effective methods for alleviating acute high-altitude sickness. This study focuses on the development of an advanced control system for a vehicle-mounted mild hyperbaric chamber (MHBC) designed for the prevention and treatment of plateau hypoxia. Conventional control methods struggle to cope with the high complexity and inherent uncertainties associated with MHBC control tasks, thereby motivating the exploration of sequential decision-making approaches such as reinforcement learning. Nevertheless, the application of sequential decision-making in MHBC control encounters several challenges, including data inefficiency and non-stationary dynamics. The system’s low tolerance for trial-and-error may lead to component damage or unsafe operating conditions, and anomalies such as valve failure can emerge during long-term operation, compromising system stability. To address these challenges, this study proposes a decision-time learning and planning integrated framework for MHBC control. Specifically, an innovative latent model embedding decision-time learning is designed for system identification, separately managing system uncertainties to fine-tune the model output. Furthermore, a decision-time planning algorithm is developed and the planning process is further guided by incorporating a value network and an enhanced online policy. Experimental results demonstrate that the proposed decision-time learning and planning integrated approaches achieve notable performance in MHBC control. Full article

Placenta accreta spectrum (PAS) refers to a group of abnormal placental attachments in which the placenta adheres too deeply to the uterine wall, with varying degrees of invasion classified as accreta, increta, or percreta. Increased rates of uterine surgeries, advanced maternal age, and cesarean deliveries have all contributed to an increase in the incidence of PAS. Complications associated with PAS can lead to severe intrapartum or postpartum hemorrhage, hysterectomy, and significant maternal morbidity, making early diagnosis and management crucial for improving outcomes. Understanding the epidemiology and risk factors of PAS is crucial for developing early detection protocols and preventive strategies. Localized data, particularly from Bahrain, can inform targeted care approaches and optimize resource allocation, ultimately leading to improved clinical guidelines, enhanced patient education, and better healthcare outcomes for affected women. There are growing concerns about the impact of PAS on maternal health and healthcare resources in Bahrain, similar to trends observed in other regions. To improve patient education and management strategies, it is essential to comprehend the regional patterns, characteristics, and outcomes associated with PAS. However, the absence of comprehensive data specific to Bahrain hinders effective clinical decision-making and policy development. Addressing this gap is imperative for advancing maternal healthcare in the region. Full article

Background/Objectives: Child abuse is a pervasive global issue with significant implications for the physical, emotional, and psychological well-being of victims. This review highlights the clinical, molecular, and therapeutic dimensions of child abuse, emphasizing its long-term impact and the need for interdisciplinary approaches. Early exposure to abuse activates the hypothalamic-pituitary-adrenal (HPA) axis, leading to chronic cortisol release and subsequent neuroplastic changes in brain regions such as the hippocampus, amygdala, and prefrontal cortex. These molecular alterations, including epigenetic modifications and inflammatory responses, contribute to the heightened risk of psychiatric disorders and chronic illnesses in survivors. Clinically, child abuse presents with diverse manifestations ranging from physical injuries to psychological and developmental disorders, making timely diagnosis challenging. Methods: A multidisciplinary approach involving thorough clinical evaluation, detailed histories, and collaboration with child protection services is essential for accurate diagnosis and effective intervention. Results: Recent advances in molecular biology have identified biomarkers, such as stress-related hormones and epigenetic changes, which provide novel insights into the physiological impact of abuse and potential targets for therapeutic intervention. Current treatment strategies prioritize the child’s safety, psychological well-being, and prevention of further abuse. Trauma-focused cognitive behavioral therapy and family-centered interventions are pivotal in promoting recovery and resilience. Conclusions: Emerging research focuses on integrating molecular findings with clinical practice, utilizing digital health tools, and leveraging big data to develop predictive models and personalized treatments. Interdisciplinary collaboration remains crucial to translating research into policy and practice, ultimately aiming to mitigate the impact of child abuse and improve outcomes for survivors. Full article

The Internet of Things (IoT) aims to wirelessly connect billions of physical things to the IT infrastructure. Although there are several radio access technologies available, few of them meet the needs of Internet of Things applications, such as long range, low cost, and low energy consumption. The low data rate of low-power wide-area network (LPWAN) technologies, particularly SigFox, makes them appropriate for Internet of Things applications since the longer the radio link’s useable distance, the lower the data rate. Network reliability is the primary goal of SigFox technology, which aims to deliver data messages successfully through redundancy. This raises concerns about SigFox’s scalability and leads to one of its flaws, namely the high collision rate. In this paper, the goal is to prevent collisions by switching to time division multiple access (TDMA) from SigFox’s Aloha-based medium access protocol, utilizing only orthogonal channels, and eliminating redundancy. Consequently, during a designated time slot, each node transmits a single copy of the data message over a particular orthogonal channel. To achieve this, a multi-agent, off-policy reinforcement learning (RL) Q-Learning technique will be used on top of SigFox. In other words, the objective is to increase SigFox’s scalability through the use of Reinforcement Learning based time slot allocation (RL-SCAP). The findings show that, especially in situations with high node densities or constrained communication slots, the proposed protocol performs better than the basic SCAP (Slot and Channel Allocation Protocol) by obtaining a higher Packet Delivery Ratio (PDR) in average of 60.58%, greater throughput in average of 60.90%, and a notable decrease in collisions up to 79.37%. Full article