Search Results (1,445)

Background/Objectives: Idiopathic Toe Walking (ITW) is a pediatric gait disorder characterized by persistent toe-to-heel ambulation in the absence of neurological, orthopedic, or developmental abnormalities. While spatio-temporal parameters often remain within normal ranges, subtle but clinically significant kinematic deviations may underlie compensatory mechanisms that sustain gait functionality. This study aims to evaluate spatio-temporal and sagittal plane kinematic differences between children with ITW and typically developing peers using Statistical Parametric Mapping (SPM). Methods: A cohort of 30 children with ITW and 30 typically developing peers aged 6–12 years participated in this study. Spatio-temporal variables, including step length, cadence, stride length, walking speed, single support phase, and swing phase, were analyzed using a three-dimensional motion capture system. Sagittal plane kinematics of the pelvis, hip, knee, and ankle were compared between groups using SPM to identify significant deviations across the gait cycle. Results: Significant differences were identified in the single support and swing phases, with higher values observed in the ITW group (p < 0.05). Sagittal plane kinematics revealed a consistent reduction in anterior pelvic tilt (p = 0.002), reduced hip and knee flexion during stance and swing phases (p < 0.001), and excessive ankle plantarflexion during early stance and terminal swing phases (p < 0.001). The plantarflexion observed at the end of the gait cycle corresponded to early gait phases due to methodological considerations of the coordinate-based event detection algorithm. Conclusions: Children with ITW demonstrate distinct spatio-temporal adaptations, including increased single support and swing phases, along with reduced walking velocity compared to typically developing peers. These findings, coupled with significant sagittal plane kinematic deviations, suggest altered neuromuscular control and joint mechanics. These insights highlight the importance of detailed kinematic analyses to identify biomechanical deficits and inform targeted interventions. Future research should explore the long-term musculoskeletal consequences of these deviations and optimize therapeutic strategies, such as physical therapy and orthotic interventions, to improve gait functionality and quality of life. Full article

Background: The Bayesian mapping approach has not been used to identify head and neck cancer hotspots in Australia previously. This study aims to identify rural communities at risk of head and neck cancer (HNC) for targeted prevention programs. Methods: This study included data from 23,853 cases recorded in the Queensland Cancer Register between 1982 and 2018. Outcomes for mapping included incidence, overall mortality, 3-year mortality, and 5-year mortality. Local government areas (LGAs) with a general population aged 15 years and above (according to 2016 census data from the Australian Bureau of Statistics) were utilized for mapping. Results: Of the 59 LGAs with higher-than-average risk, 22 predominantly rural and remote LGAs showed statistically significant higher risks of head and neck cancer occurrence. Estimated median standardized mortality ratios (SMRs) ranged from 0.57 to 3.44 and were higher than the state average in 38 LGAs. Four LGAs had the highest mortality—the Shires of Quilpie, Yarrabah, Murweh, and Hinchinbrook. Conclusions: Whilst reasons for some LGAs exhibiting higher HNC are unknown, Bayesian mapping highlights these rural and remote regions as worthy of further investigation. In conclusion, the Bayesian disease mapping approach is effective in identifying high-risk communities for HNC. Findings from this study will aid in designing targeted screening and interventions for the prevention and management of head and neck cancer in regional and remote communities through support services such as a cancer navigator. Full article

Japan is facing challenges associated with its super-aging society, including increased social security burdens and a rise in the elderly workforce due to a declining younger labor force. Extending the healthy life expectancy is one countermeasure, necessitating lifestyle improvements such as frailty prevention and ensuring adequate sleep duration. This study investigated the relationship between heart rate variability (HRV) and sleep duration among older adults (aged ≥ 65) using electrocardiogram (ECG) and three-axis accelerometer data from the Allostatic State Mapping by the Ambulatory ECG Repository (ALLSTAR) database, recorded between January 2019 and March 2021. Inclusion criteria required a sinus rhythm and recording durations ≥80%. Continuous 24 h ECG and accelerometer data were analyzed for 55,154 participants (mean age 76 ± 6). The results consistently showed significant differences in HRV metrics, including MRRI, SDRR, ULF, LF, HF, and LF/HF, across sleep duration groups (G1–G4). Short-sleep groups (G4) exhibited decreased MRRI and SDRR and increased LF/HF, suggesting active lifestyles but reduced HRV. Conversely, long-sleep groups (G1) showed increased MRRI and reduced LF/HF but exhibited age-related declines in SDRR and ULF. These findings indicate that both insufficient and excessive sleep may contribute to HRV reduction in older adults. This study provides critical insights for improving elderly lifestyles through tailored interventions in exercise and sleep management. Full article

Flood risks are escalating globally due to unplanned urban expansion and the impacts of climate change, posing significant challenges for urban areas and necessitating effective mitigation strategies. Nature-based solutions (NBSs) have emerged as innovative and sustainable approaches for managing flood risks. The International Union for Conservation of Nature (IUCN) defines NBSs as actions that conserve, manage, and restore natural and modified ecosystems to address societal concerns while benefiting both people and the environment. This research focuses on developing NBS strategies for the most flood-prone area within Kochi, a city highly vulnerable to flooding. The study begins with a comprehensive site examination to identify flood sources and causes in Kochi, aiding in selecting flood vulnerability indicators. An analytical framework incorporating flood risk assessment and exposure studies using physical and social indicators, alongside GIS mapping techniques, revealed that approximately half of Kochi is affected. The study identified key vulnerability hotspots, particularly within the Central Business District (CBD), where high population density and inadequate infrastructure exacerbate flood risks. Proposed NBS interventions include restoring natural floodplains, enhancing canal capacities, creating urban forests, and establishing green infrastructure like permeable pavements and rainwater harvesting systems. Key findings emphasize the effectiveness of integrating NBSs with traditional flood management strategies, forming a mixed flood control system. These interventions mitigate flood risks, improve biodiversity, reduce the urban heat island effect, and enhance community well-being. Importantly, the research underscores the role of public participation and community-driven maintenance plans in ensuring the sustainability of NBS interventions. Aligning these strategies with Kochi’s Master Plan 2040 ensures coherence with broader urban planning and climate resilience goals. The research anticipates changes in climate, land use patterns, and urban dynamics to inform NBS suitability in Kochi. Ultimately, the research demonstrates how implementing NBSs can deliver a range of socio-environmental benefits, significantly influencing urban development in vulnerable zones. By advocating for the integration of NBSs into urban infrastructure planning, this study offers a blueprint for resilient and sustainable flood management strategies that are applicable to other coastal cities facing similar challenges. Full article

Children’s playgrounds are an important component providing opportunities for children’s play. Few studies, however, have explored the unequal geographic provision of these valuable spaces. This work addressed this research gap by identifying the key data and methods required to analyse children’s playground provision at both global and national geographic scales. The aims of the paper were twofold: It firstly explored the potential for mapping children’s playground provision at a global scale and validated such an approach using finer spatial scales. Secondly, the unequal provision of playgrounds was investigated at a national scale in England, UK using open data sources. Relationships with the size of the settlement and deprivation were also explored. The work used a range of secondary datasets through applying quantitative GIS and statistical approaches. The results demonstrated that, due to data quality issues, a world approach to map playground provision was not currently viable. At a national scale, results highlighted substantial inequality in provision, with some settlements in England experiencing five times the number of children per playground, despite being broadly comparable in terms of population. Deprived settlements in England tended to have fewer, smaller, and further-away playgrounds. The patterns were most stark in the largest settlements. London, however, was consistently an exception to these patterns, where deprived areas tended to have more and closer playgrounds. Acknowledging the numerous competing different metrics to measure provision of children’s playgrounds, the research generated a framework for bringing together a wide range of interrelated data into a condensed form for comparison. Thus, the approach facilitated the identification of interventions within different contexts in order to reduce inequalities in playground provision and bolster children’s democratic right to the city for play. Full article

In Asia, Apis cerana (native) and Apis mellifera (introduced) are the primary managed honeybee species, vital for pollination and honey production. However, climate change and other threats are driving pollinator declines, while research on their ecology in Asia remains limited. Bridging these knowledge gaps is crucial for developing conservation strategies to sustain pollination services and agricultural systems in the region. In this study, we evaluated the potential impacts of climate change on the spatial interactions between two honeybee species (A. cerana and A. mellifera) and 20 pollinator-dependent crops across 23 countries in Asia. We used species distribution models (SDMs) to generate habitat suitability maps for both honeybees and crops under current and future climate scenarios (SSP585 for 2070). Schoener’s D statistic was employed to quantify the spatial overlap, and a novel spatial approach was applied to create mismatch maps that identified areas of increased or decreased interactions. We found that, on average, A. cerana demonstrated higher overlap with 12 crops compared to 8 for A. mellifera in future projections. Key crops like sesame, eggplant, and mango retained strong overlaps with both pollinators, while mismatches were more pronounced for A. cerana, particularly with watermelon, strawberry, and buckwheat. In contrast, A. mellifera showed greater stability and resilience in spatial overlaps with crops such as soybean and sunflower. Overall, A. cerana is expected to face more significant spatial mismatches, highlighting its vulnerability to climate-induced changes and the critical need for targeted conservation efforts. This study highlights the urgent need for region-specific conservation strategies by identifying areas at risk of losing critical pollination services. Our results provide a crucial framework for informed management and policy interventions to safeguard pollination-dependent agricultural systems and biodiversity in Asia amidst accelerating environmental challenges. Full article

This narrative review provides an overview of the various diagnostic tools used to assess cartilage health, with a focus on early detection, nutrition intervention, and management of osteoarthritis. Early detection of cartilage damage is crucial for effective patient management. Traditional diagnostic tools like radiography and conventional magnetic resonance imaging (MRI) sequences are more suited to detecting late-stage structural changes. This paper highlights advanced imaging techniques, including sodium MRI, T2 mapping, T1ρ imaging, and delayed gadolinium-enhanced MRI of cartilage, which provide valuable biochemical information about cartilage composition, particularly the glycosaminoglycan content and its potential links to nutrition-related factors influencing cartilage health. Cartilage degradation is often linked with inflammation and measurable via markers like CRP and IL-6 which, although not specific to cartilage breakdown, offer insights into the inflammation affecting cartilage. In addition to imaging techniques, biochemical markers, such as collagen breakdown products and aggrecan fragments, which reflect metabolic changes in cartilage, are discussed. Emerging tools like optical coherence tomography and hybrid positron emission tomography–magnetic resonance imaging (PET-MRI) are also explored, offering high-resolution imaging and combined metabolic and structural insights, respectively. Finally, wearable technology and biosensors for real-time monitoring of osteoarthritis progression, as well as the role of artificial intelligence in enhancing diagnostic accuracy through pattern recognition in imaging data are addressed. While these advanced diagnostic tools hold great potential for early detection and monitoring of osteoarthritis, challenges remain in clinical translation, including validation in larger populations and integration into existing clinical workflows and personalized treatment strategies for cartilage-related diseases. Full article

Introduction: Autism and ADHD shape behaviours related to food, exercise, and body image, potentially influencing obesity treatment outcomes, as seen in eating disorder research. Resultantly, autistic and ADHD patients with obesity may have distinct experiences and differences compared to non-autistic and non-ADHD patients. This review maps existing literature on autism and ADHD in adults with obesity. Methods: Following PRISMA guidelines, six databases (Embase, MEDLINE, PsycINFO, Web of Science, CENTRAL, and Scopus) were searched for studies on autism and/or ADHD (diagnosed, probable, or traits) in adults with obesity. Screening and data extraction were conducted twice independently for each record. Results: Thirty-one studies were included, with 1,027,773 participants. Two case reports described successful use of weight loss drugs in autistic people with obesity. Eight prevalence studies suggested ADHD is overrepresented in obesity, regardless of binge eating status. Nineteen studies examined clinical profiles: ADHD patients had lower socioeconomic status, poorer health-related quality of life, increased impulsivity, cognitive inflexibility, and neuroticism, alongside lower agreeableness, conscientiousness, self-directedness, and cooperativeness. ADHD patients also exhibited higher psychopathology, problematic alcohol use, and disordered eating. Eight studies assessed treatment responses, noting poorer outcomes from behavioural programs and obesity pharmacotherapy, but similar post-surgical weight outcomes, despite increased complications. Two studies considered ADHD-specific treatment adaptions, one reporting a successful trial of ADHD medication for weight loss and the other reporting on switching to transdermal ADHD medications after bariatric surgery. Conclusions: This review underscores the need for more research on autism and obesity. For ADHD, findings suggest frequent co-occurrence with obesity, but lived experiences and tailored interventions remain underexplored. Full article

Urban parks are vital public spaces that provide cultural ecosystem services (CESs) that enhance the well-being of city dwellers. As the demand for CESs has greatly increased, the imbalance between CES supply and demand has become prominent. Accurately identifying whether the supply of CESs meets the demand supports urban park planning and management. However, the CES supply–demand gap lies not only in the quantitative resource deficits, but also in the spatial mismatch between supply and demand. At present, scientific quantification methods for urban park CES supply and demand that comprehensively consider both quantitative and spatial relationships remain inadequate. To fill this gap, we propose an integrated framework that combines spatial and quantitative analysis to identify the supply and demand of urban park CESs, using Shanghai as the study area. The framework consists of three major steps: (1) mapping the CES supply and demand of urban parks; (2) identifying the CES supply–demand relationship by combining quantitative analysis through bivariate mapping with spatial analysis using spatial statistics; (3) categorizing the supply–demand relationship into four scenarios based on quantity balance and spatial matching, with three corresponding planning proposals. The results show that 136 sub-districts belong to the quantity balance and space matching type, while 79 sub-districts belonging to the imbalanced quantities type, including 41 belonging to the quantity imbalance and space mismatching type. Notably, only 15 sub-districts face a situation where supply is less than demand. Our findings provide a solid basis for identifying key areas of CES supply–demand conflict and prioritizing targeted planning interventions. This approach not only improves the efficiency of CES provision, but also addresses the growing demand for high-quality CESs in rapidly urbanizing regions. Full article

Background: There has been a substantial increase in research on the new 24-hour movement paradigm, emphasizing the importance of considering the “whole day” and investigating integrated movement behaviors (physical activity, sedentary behavior, and sleep). This scoping review aims to map the evidence from reviews that have summarized information on integrated 24-hour movement behaviors in children and adolescents. Methods: Eight databases were searched in May 2023, with an update in October 2024. The review followed the PRISMA-ScR framework and the guidelines of the Joanna Briggs Institute Reviewer’s Manual. Results: National 24-hour movement guidelines for children and adolescents exist in only a few countries (Australia, Canada, New Zealand, and South Africa). There is a lack of valid and reliable measurement tools for assessing 24-hour movement. Globally, children and adolescents, with and without disabilities, show low adherence to these guidelines. Reallocating time to moderate-to-vigorous physical activity was beneficial, while other reallocations had mixed results to health. COVID-19 reduced physical activity and increased screen time and sleep. Healthy movement behaviors are positively associated with better health outcomes in children and adolescents. There is a possible relationship between adherence to 24-hour movement behaviors and cognitive function, pollution measures, and eHealth interventions. Inconsistencies were identified in the terms used. Conclusions: High-quality research is needed to develop measurement tools that assess the long-term health impact of 24-hour movement and to create solutions for improving adherence, mainly in countries lacking specific guidelines. Full article

Background/Objectives: Accurate and efficient segmentation of cervical cells is crucial for the early detection of cervical cancer, enabling timely intervention and treatment. Existing segmentation models face challenges with complex cellular arrangements, such as overlapping cells and indistinct boundaries, and are often computationally intensive, which limits their deployment in resource-constrained settings. Methods: In this study, we introduce a lightweight and efficient segmentation model specifically designed for cervical cell analysis. The model employs a MobileNetV2 architecture for feature extraction, ensuring a minimal parameter count conducive to real-time processing. To enhance boundary delineation, we propose a novel force map approach that drives pixel adjustments inward toward the centers of cells, thus improving cell separation in densely packed areas. Additionally, we integrate extreme point supervision to refine segmentation outcomes using minimal boundary annotations, rather than full pixel-wise labels. Results: Our model was rigorously trained and evaluated on a comprehensive dataset of cervical cell images. It achieved a Dice Coefficient of 0.87 and a Boundary F1 Score of 0.84, performances that are comparable to those of advanced models but with considerably lower inference times. The optimized model operates at approximately 50 frames per second on standard low-power hardware. Conclusions: By effectively balancing segmentation accuracy with computational efficiency, our model addresses critical barriers to the widespread adoption of automated cervical cell segmentation tools. Its ability to perform in real time on low-cost devices makes it an ideal candidate for clinical applications and deployment in low-resource environments. This advancement holds significant potential for enhancing access to cervical cancer screening and diagnostics worldwide, thereby supporting broader healthcare initiatives. Full article

Background/Objectives: Chronic pain is common following a stroke and is associated with increased disability. Yet, little is known about the chronic pain experience in the stroke population. This study aimed to identify and explore the features and neuropathic symptoms of chronic pain in individuals with longstanding stroke. Methods: This observational study utilized an online survey that was developed for individuals who have had a stroke (>3 months). Data sought included participant demographics, medical history, and details of the stroke(s). Participants who reported experiencing chronic pain completed the Numerical Rating Scale for Pain, the Neuropathic Pain Symptom Inventory, and body maps to indicate region(s) of pain. Results: A total of 533 individuals with longstanding stroke participated. Chronic pain was reported as being experienced by 60% of participants and was more frequently experienced by individuals who reported being female (p = 0.002). Moderate or severe pain intensity was commonly reported (mean = 5.98, SD = 1.89). Individuals with chronic pain post-stroke reported a range of neuropathic symptoms rather than a common pain experience, with combinations of spontaneous, paroxysmal, and evoked pains in addition to pain associated with paraesthesia/dysaesthesia. Pain involving the upper limb was the most common region (shoulder 39%, hand and forearm 38%), followed by the lower limb (foot 30%, leg 29%). Having multiple strokes was associated with a higher frequency of chronic pain (p = 0.01), as was peripheral vascular disease (p < 0.001) and lipid disorders (p = 0.001). Conclusions: These findings highlight the varied nature of chronic pain experienced by individuals following a stroke, while also detailing stroke and medical history associated with chronic pain. It builds on existing knowledge of chronic pain post-stroke and provides new insight into the neuropathic symptoms experienced. This knowledge has the potential to assist in the development of tailored interventions based on addressing pain symptomatology and health literacy. Full article

This study evaluates the combined use of mobile transects and fixed stations to analyze atmospheric urban heat islands (UHIs’a) in Temuco, Chile. Data were collected using 23 fixed stations and 3 mobile transects traversing predefined city routes, capturing temperature records at one-minute intervals. Results revealed moderate correlations between methodologies (coefficients: 0.55–0.62) and average temperature differences of 0.72 °C to 1.6 °C, confirming their compatibility for integrated use. UHI intensities ranged from weak (0.5 °C) to extremely strong (13 °C), with the highest urban temperature (33.1 °C) observed in Zone Z-3, contrasting with 25.4 °C at the rural Maquehue station. Simulations and isothermal maps identified four UHI zones, highlighting the influence of impervious surfaces, traffic density, and limited vegetation on temperature distribution. Fluctuation plots revealed rapid cooling in vegetated areas and high heat retention in dense urban zones. These findings validate the methodologies for spatial and temporal UHI analysis and provide actionable insights for urban planning. Targeted interventions, such as increasing vegetation in high-risk zones, are recommended to mitigate extreme heat and enhance thermal comfort in urban areas. Full article

Geospatial tools and geocoding systems play an increasingly significant role in the modernization and operation of municipal water utility networks. This research explored how geocoding systems could improve network management, facilitate leak detection, and enhance hydraulic modeling accuracy. Various geocoding services, including Google, Bing Maps, and OpenStreetMap APIs were analyzed using address data from a small Central European municipality. The analysis was performed in February and March of 2024. The accuracy and efficiency of these systems in handling spatial data for domestic water networks were assessed and results showed that geocoding accuracy depended on the quality of the service provider databases and the formatting of input data. Google proved the most reliable, while Bing and OpenStreetMap were less accurate. Additionally, the Location Database developed by Lechner Knowledge Center was used as a reliable local reference for comparison with global services. Geocoding results were integrated into GIS softwares (Google Earth ver. 7.3.6.9796, QGIS ver. 3.36, ArcGIS ver 10.8.2) to enable spatial analysis and comparison of geographic coordinates. The findings highlight geocoding’s critical role in efficient water network management, particularly for mapping consumer data and rapidly localizing leaks and breaks. Our findings directly support hydraulic modeling tasks, contributing to sustainable operations and cost-effective interventions. Full article

The aim of the present research is to validate the combined use, through data fusion, of a Laser Induced Fluorescence (LIF) scanning system and a radar scanner (RGB-ITR, Red Green Blue Imaging Topological Radar system), as a unique tool to address the need for non-invasive, rapid, and low-cost techniques for both diagnostic and operational needs. The integrated system has been applied to the House of Diana complex in Ostia Antica. The main diagnostic objective of this research was to trace the materials used in different phases of restoration, from antiquity to modernity, on both masonry and pictorial surfaces, to reconstruct the history of the building. Due to the significant interest in this insula, other studies have been recently carried out on the House of Diana, but they once again highlighted the necessity of multiple approaches and non-invasive methods capable of providing quasi-real-time answers, delivering point-by-point information on very large surfaces to overcome the limits related to representativeness of sampling. The data acquired by the RGB-ITR system are quantitative, allowing for morphological and 3-colour analysis of the investigated artwork. In this work, the sensor has been used to create coloured 3D models useful for structural assessments and for locating different classes of materials. In fact, the LIF maps, which integrate knowledge about the original constituent materials and previous conservation interventions, have been used as additional layers of the tridimensional models. Therefore, the method can direct possible new investigations and restoration actions, piecing together the history of the House of Diana to build for it a safer future. Full article