Search Results (311)

Accurate and scalable gait assessment is essential for clinical and research applications, including fall risk evaluation, rehabilitation monitoring, and early detection of neurodegenerative diseases. While electronic walkways remain the clinical gold standard, their high cost and limited portability restrict widespread use. Wearable inertial measurement units (IMUs) and markerless depth cameras have emerged as promising alternatives; however, prior studies have typically assessed these systems under tightly controlled conditions, with single participants in view, limited marker sets, and without direct cross-technology comparisons. This study addresses these gaps by simultaneously evaluating three sensing technologies—APDM wearable IMUs (tested in two separate configurations: foot-mounted and lumbar-mounted) and the Azure Kinect depth camera—against ProtoKinetics Zeno™ Walkway Gait Analysis System in a realistic clinical environment where multiple individuals were present in the camera’s field of view. Gait data from 20 older adults (mean age $70.06\pm 9.45$ years) performing Single-Task and Dual-Task walking trials were synchronously captured using custom hardware for precise temporal alignment. Eleven gait markers spanning macro, micro-temporal, micro-spatial, and spatiotemporal domains were compared using mean absolute error (MAE), Pearson correlation (r), and Bland–Altman analysis. Foot-mounted IMUs demonstrated the highest accuracy (MAE $=0.00$–$6.12$, $r=0.92$–$1.00$), followed closely by the Azure Kinect (MAE $=0.01$–$6.07$, $r=0.68$–0.98). Lumbar-mounted IMUs showed consistently lower agreement with the reference system. These findings provide the first comprehensive comparison of wearable and depth-sensing technologies with a clinical gold standard under real-world conditions and across an extensive set of gait markers. The results establish a foundation for deploying scalable, low-cost gait assessment systems in diverse healthcare contexts, supporting early detection, mobility monitoring, and rehabilitation outcomes across multiple patient populations. Full article

High strength and high ductility concrete (HSHDC) exhibit exceptional compressive strength (up to 90 MPa) and remarkable tensile ductility (ultimate tensile strain reaching 6%), making them highly resilient under impact loading. To elucidate the influence of strain rate and wet–dry cycling of salt spray on the dynamic compressive response of HSHDC, a series of tests was conducted using a 75 mm split Hopkinson pressure bar (SHPB) system on specimens exposed to cyclic corrosion for periods ranging from 0 to 180 days. The alternating seasonal corrosion environment was reproduced by using a programmable walk-in environmental chamber. Subsequently, both uniaxial compression and SHPB tests were employed to evaluate the post-corrosion dynamic compressive properties of HSHDC. Experimental findings reveal that corrosive exposure significantly alters both the static and dynamic compressive mechanical behavior and constitutive characteristics of HSHDC, warranting careful consideration in long-term structural integrity assessments. As corrosion duration increases, the quasi-static and dynamic compressive strengths of HSHDC exhibit an initial enhancement followed by a gradual decline, with stress reaching its peak at 120 days of corrosion under all strain rates. All specimens demonstrated pronounced strain-rate sensitivity, with the dynamic increase factor (DIF) being minimally influenced by the extent of corrosion under dynamic strain rates (112.6–272.0 s⁻¹). Furthermore, the peak energy-consumption capacity of HSHDC was modulated by both the duration of corrosion and the applied strain rate. Full article

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

Tourism’s rapid growth has significant and negative effects on the environment, society, and economy. Sustainable tourism practices are essential in order to mitigate these effects. Virtual reality (VR) technologies offer the possibility of implementing sustainable tourism policies by providing immersive experiences that replace real ones. Moreover, VR can be a useful tool for the protection and promotion of cultural and natural heritage. The article discusses the potential directions for sustainable tourism using VR. This technology can reduce the burden on popular tourist sites without losing their value to visitors. Additionally, it can promote less popular destinations in the wider public awareness. A case study of the implementation of a virtual tour at the Pahlavon Mahmud Mausoleum in Khiva (Uzbekistan) is presented. The research method was designed to evaluate the acceptability of VR technology among a convenience sampling of n = 57 Gen Z consumers (university students 20–24 years of age), who completed interviews following their participation in a voluntary virtual walking tour. The research results suggest that VR can be an acceptable and useful tool for implementing sustainable tourism policies in the near future. Another conclusion is that virtual sightseeing should not fully replace onsite tourism. Full article

Legged rovers are gaining interest for planetary exploration due to their high mobility. However, loose regolith on celestial surfaces like the Moon and Mars often leads to slippage as legs disturb the soil. To address this, a walking technique has been proposed that enhances soil support by transmitting vibrations from the robot’s legs. This approach aims to improve mobility by increasing the ground’s bearing capacity. To evaluate its effectiveness in space-like environments, this study experimentally investigates the effect of vibration on bearing capacity under low atmospheric pressure, which can influence soil behavior due to reduced air resistance. Using Silica No. 5 and Toyoura sand as test materials, experiments were conducted to compare bearing capacities under standard and low pressure. The results demonstrate that applying vibration significantly improves bearing capacity and that the influence of atmospheric pressure is minimal. These findings support the viability of vibration-assisted locomotion for planetary rovers operating in low-pressure extraterrestrial environments. Full article

Wellington, New Zealand, is highly vulnerable to disaster-induced food security crises due to its geography and geological characteristics, which can disrupt transportation and isolate the city following disasters. Urban agriculture (UA) has been proposed as a potential alternative food source for post-disaster scenarios. This study examined the potential of urban agriculture for enhancing post-disaster food security by calculating vegetable self-sufficiency rates. Specifically, it evaluated the capacity of current Wellington’s community gardens to meet post-disaster vegetable demand in terms of both weight and nutrient content. Data collection employed mixed methods with questionnaires, on-site observations and mapping, and collecting high-resolution aerial imagery. Garden yields were estimated using self-reported data supported by literature benchmarks, while cultivated areas were quantified through on-site mapping and aerial imagery analysis. Six post-disaster food demand scenarios were used based on different target populations to develop an understanding of the range of potential produce yields. Weight-based results show that community gardens currently supply only 0.42% of the vegetable demand for residents living within a five-minute walk. This rate increased to 2.07% when specifically targeting only vulnerable populations, and up to 10.41% when focusing on gardeners’ own households. However, at the city-wide level, the current capacity of community gardens to provide enough produce to feed people remained limited. Nutrient-based self-sufficiency was lower than weight-based results; however, nutrient intake is particularly critical for vulnerable populations after disasters, underscoring the greater challenge of ensuring adequate nutrition through current urban food production. Beyond self-sufficiency, this study also addressed the role of UA in promoting food diversity and acceptability, as well as its social and psychological benefits based on the questionnaires and on-site observations. The findings indicate that community gardens contribute meaningfully to post-disaster food security for gardeners and nearby residents, particularly for vulnerable groups with elevated nutritional needs. Despite the current limited capacity of community gardens to provide enough produce to feed residents, findings suggest that Wellington could enhance post-disaster food self-reliance by diversifying UA types and optimizing land-use to increase food production during and after a disaster. Realizing this potential will require strategic interventions, including supportive policies, a conducive social environment, and diversification—such as the including private yards—all aimed at improving food access, availability, and nutritional quality during crises. The primary limitation of this study is the lack of comprehensive data on urban agriculture in Wellington and the wider New Zealand context. Addressing this data gap should be a key focus for future research to enable more robust assessments and evidence-based planning. Full article

Background: Gait kinematics address the analysis of joint angles and segment movements during walking. Although there is work in the literature to solve the problems of forward (FK) and inverse kinematics (IK), there are still problems related to the accuracy of the estimation of Cartesian and joint variables, singularities, and modeling complexity on gait analysis approaches. Objective: In this work, we propose a framework for two-dimensional gait analysis addressing the singularities in the estimation of the joint variables using quaternion-based kinematic modeling. Methods: To solve the forward and inverse kinematics problems we use the dual quaternions’ composition and Damped Least Square (DLS) Jacobian method, respectively. We assess the performance of the proposed methods with three gait patterns including normal, toe-walking, and heel-walking using the RMSE value in both Cartesian and joint spaces. Results: The main results demonstrate that the forward and inverse kinematics methods are capable of calculating the posture and the joint angles of the three-DoF kinematic chain representing a lower limb. Conclusions: This framework could be extended for modeling the full or partial human body as a kinematic chain with more degrees of freedom and multiple end-effectors. Finally, these methods are useful for both diagnostic disease and performance evaluation in clinical gait analysis environments. Full article

Background/Objectives: Obesity in adolescence is associated with a deterioration in cognitive functions, with significant implications for psychophysical well-being and academic performance. Recent studies highlight the importance of integrated interventions that combine nutrition education and physical activity to promote the overall health of students. The present study aims to evaluate the efficacy of an integrated intervention based on nutritional education and conscious body movement in improving cognitive functions, perceived well-being and nutritional knowledge in lower secondary school students with indicators of overweight and obesity. Methods: A quasi-experimental design with randomization at the class level was adopted, involving 60 students divided into an experimental group and control group. The intervention was divided into twelve weeks of activities, divided between nutritional education modules and physical activity courses. Standardized tests for the assessment of cognitive functions (Digit Span Forward, Digit Span Backward, Stroop Test, Trail Making Test B), motor tests (6-Minute Walk Test, Sit and Reach Test) and a food knowledge questionnaire were administered before and after the intervention. Results: The experimental group showed significant improvements compared to the control group in all cognitive, motor, and nutritional knowledge measures, indicating the effectiveness of the integrated intervention in promoting cognitive and physical well-being. Conclusions: The findings support the role of school as a generative environment of integrated well-being, suggesting the need to develop and implement curricular programs that integrate nutrition education and physical activity to counteract the negative effects of obesity on cognitive function in adolescents. Full article

This study evaluates the potential health risks posed by geogenic arsenic in environments suitable for leisure activities, such as walking, bathing, and playing, for adults and children alike, as well as in neighbouring agricultural areas. The study includes an analysis of environmental characteristics and the main stream originating in the adjacent mining area, with water and sediment samples taken. The study area is representative of other areas in the vicinity of the Mar Menor Lagoon, which is one of the largest and most biodiverse coastal lagoons in the Mediterranean Sea. The general characteristics of the soil and water were determined for this study, as was the concentration of As in the soil and water samples. A granulometric separation was carried out into four different fractions (<2 mm, <250 µm, <100 µm, and <65 µm). The mineralogical composition, total As content, and bioaccessible As content are analysed in each of these fractions. This provides data with which to calculate the danger of arsenic (As) to human health by ingestion and to contribute to As bioaccessibility studies and the role played by the mineralogical composition and particle size of soil ingestion. The conclusions rule out residential use of this environment, although they allow for eventual tourist use and traditional agricultural use of the surrounding soils. Full article

Falls are a major safety concern in physically demanding occupations such as roofing, where workers operate on inclined surfaces under unstable postures. While inertial measurement units (IMUs) are widely used in wearable fall detection systems, they often fail to capture early indicators of instability related to foot–ground interactions. This study evaluates the effectiveness of plantar pressure sensors, alone and combined with IMUs, for fall detection on sloped surfaces. We collected data in a controlled laboratory environment using a custom-built roof mockup with incline angles of 0°, 15°, and 30°. Participants performed roofing-relevant activities, including standing, walking, stooping, kneeling, and simulated fall events. Statistical features were extracted from synchronized IMU and plantar pressure data, and multiple machine learning models were trained and evaluated, including traditional classifiers and deep learning architectures, such as MLP and CNN. Our results show that integrating plantar pressure sensors significantly improves fall detection. A CNN using just three IMUs and two plantar pressure sensors achieved the highest F1 score of 0.88, outperforming the full 17-sensor IMU setup. These findings support the use of multimodal sensor fusion for developing efficient and accurate wearable systems for fall detection and physical health monitoring. Full article

According to the World Health Organization (WHO), indoor air quality (IAQ) is becoming a serious global concern due to its significant impact on human health. However, not all relevant health parameters are currently regulated. For example, particle number concentration (PNC) and its associated carbonaceous species, such as black carbon (BC), which are classified as carcinogenic by the International Agency for Research on Cancer (IARC), are not currently regulated. Compared with IAQ studies in other types of buildings, studies focusing on IAQ in hospitals or other healthcare facilities are scarce. Therefore, this study aims to evaluate the impact of these outdoor pollutants, among others, on the indoor environment of a hospital under different atmospheric conditions. To identify the seasonal influence, two different periods of two consecutive seasons (summer 2020 and winter 2021) were selected for the measurements. Regulated pollutants (NO, NO₂, O₃, PM₁₀, and PM_2.5) and nonregulated pollutants (PM₁, PNC, and equivalent BC (eBC)) in outdoor air were simultaneously measured indoor and outdoor. This study also investigated the impact of indoor activities on indoor air quality. In the absence of indoor activities, outdoor sources significantly contribute to indoor traffic-related pollutants. Indoor and outdoor (I-O) measurements showed similar behavior, but indoor concentrations were lower, with peak levels delayed by up to two hours. Seasonal variations in indoor/outdoor ($\mathrm{I}/\mathrm{O}$) ratios were lower for particles than for associated gaseous pollutants. Particle infiltration depended on particle size, with it being higher the smaller the particle size. Indoor activities also significantly affected indoor pollutants. PM_x (especially PM₁₀ and PM_2.5) concentrations were mainly modulated by walking-induced particle resuspension. Vertical eBC profiles indicated a relatively well-mixed environment. Ventilation through open windows rapidly altered indoor air quality. Outdoor-dominant pollutants (PNC, eBC, and NO_X) had $\mathrm{I}/\mathrm{O}$ ratios ≥ 1. Staying in the room with an open window had a synergistic effect, increasing the $\mathrm{I}/\mathrm{O}$ ratios for all pollutants. Higher I/O ratios were associated with turbulent outdoor conditions in both unoccupied and occupied conditions. Statistically significant differences were observed between stable (TKE ≤ 1 m² s⁻²) and unstable (TKE > 1 m² s⁻²) conditions, except for NO₂ in summer. This finding was particularly significant when the wind direction was westerly or easterly during unstable conditions. The results of this study highlight the importance of understanding the behavior of indoor particulate matter and related pollutants. These pollutants are highly variable, and knowledge about them is crucial for determining their health effects, particularly in public buildings such as hospitals, where information on IAQ is often limited. More measurement data is particularly important for further research into I-O transport mechanisms, which are essential for developing preventive measures and improving IAQ. Full article

This paper presents a novel, four-port, rectangular microstrip, inset-feed multiple-input and multiple-output (MIMO) antenna array, enhanced with metamaterials for improved gain and isolation, specifically designed for multi-operator 5G open radio access network (ORAN)-based indoor software-defined radio (SDR) applications. ORAN is an open-source interoperable framework for radio access networks (RANs), while SDR refers to a radio communication system where functions are implemented via software on a programmable platform. A 3 × 3 metamaterial (MTM) superstrate is placed above the MIMO antenna array to improve gain and reduce the mutual coupling of MIMO. The proposed MIMO antenna operates over a 300 MHz bandwidth (3.5–3.8 GHz), enabling shared infrastructure for multiple operators. The antenna’s dimensions are 75 × 75 × 18.2 mm³. The antenna possesses a reduced mutual coupling less than −30 dB and a 3.5 dB enhancement in gain with the help of a novel 3 × 3 MTM superstrate 15 mm above the radiating MIMO elements. A performance evaluation based on simulated results and lab measurements demonstrates the promising value of key MIMO metrics such as a low envelope correlation coefficient (ECC) < 0.002, diversity gain (DG) ~10 dB, total active reflection coefficient (TARC) < −10 dB, and channel capacity loss (CCL) < 0.2 bits/sec/Hz. Real-world testing of the proposed antenna for ORAN-based sub-6 GHz indoor wireless systems demonstrates a downlink throughput of approximately 200 Mbps, uplink throughput of 80 Mbps, and transmission delays below 80 ms. Additionally, a walk test in an indoor environment with a corresponding floor plan and reference signal received power (RSRP) measurements indicates that most of the coverage area achieves RSRP values exceeding −75 dBm, confirming its suitability for indoor applications. Full article

Urban public toilets are essential for improving urban and rural living environments. Traditional evaluations have relied on statistical indicators such as total numbers and network coverage, but have overlooked population demand, limiting their ability to reflect actual service levels and optimize spatial allocation. This study assesses the public toilet service capacity according to spatial accessibility and offers insights into layout optimization. The main urban area of Kunming was considered as the case study. First, the Gaussian two-step floating catchment area (G2SFCA) method was used to calculate public toilet accessibility. The service level of public toilets at the community scale was assessed based on the calculation results. Finally, recommendations for the optimization of the spatial layout of public toilet provision are proposed based on the evaluation findings. Results indicate that (1) 57 communities lacked access to public toilets within a 5 min walk, while only two lacked access within 20 min; all communities had access within 30 min; (2) increasing stalls in old public toilets by 50% would meet the policy requirements for most residents; (3) transportation accessibility has a significant impact on residents’ convenience in accessing public toilets. Areas with lower transportation connectivity tend to have poorer toilet accessibility. The construction of new public toilets near road networks can effectively enhance overall restroom convenience for residents in the study area. By integrating public toilet accessibility with resident restroom demand, this study proposes targeted strategies for optimizing the spatial layout of urban public toilets, offering valuable insights and feasible solutions for improving the scientific and rational allocation of urban public resources. Full article

Sewing is the major contributor to the manufacturing of protection wear for the survival of early human civilization against extreme weather conditions. Mechanized sewing witnessed developments during the middle of the 19th century, and tedious handwork was replaced by sewing machines. Despite the modernization of sewing machine technologies, speed, material thicknesses, automation, and the introduction of AI in sewing, there is a longstanding problem of heat loss along stitch lines. The sewing material is compressed by the sewing thread, and this compression results in a bridge between the human body and the external cold environment. Garment technologists identify this problem and due to the lack of any technological solution, the problem is solved through complex material handling methods. A new sewing technological solution has been developed to solve this problem, called spacer stitching, which addresses the problem of compression along stitch lines. Two baffled jackets with sewn-through methods are prepared, one with the spacer stitching technology and the other with conventional sewing. Thermal resistance and insulation efficiency are evaluated using the Thermetrics thermal manikin “Sonny” under dynamic (walking) conditions to analyze the thermal resistance difference between the two types of sewing methods as well as the effects of motion on insulation. The results reveal that the jacket made with spacer stitching demonstrates significantly higher thermal resistance and enhanced wearer comfort compared to that produced using conventional methods. Additionally, variations in thermal resistance are observed across different zones of the thermal manikin. These findings highlight the potential of spacer stitching to improve thermal insulation and revolutionize high-performance outerwear design. Full article

Traditional force plate-based systems offer high measurement precision but are limited to laboratory settings, restricting their use in real-world environments. To address this, we propose a method for estimating a three-axis ground reaction force (GRF) and two-axis center of pressure (CoP) using a shoe embedded with three uniaxial load cells. The estimation was conducted under five gait conditions: straight walking, turning, uphill, downhill, and running. Data were collected from 40 healthy young adults. Four deep-learning models—Fully Connected Neural Network (FCNN), Convolutional Neural Network (CNN), Sequence-to-Sequence Long Short-Term Memory (Seq2Seq-LSTM), and Transformer—were evaluated. Among them, Seq2Seq-LSTM and CNN achieved the highest performance in predicting both GRF and CoP. However, the medio-lateral (ML) components showed lower accuracy than the vertical and anterior–posterior directions. In slope conditions, particularly for vertical GRF, relatively higher root mean-square error (RMSE) values were observed. Despite some variation across gait types, predicted values showed high agreement with measurements. Compared with previous studies, the proposed method achieved comparable or better performance with a minimal sensor setup. These findings highlight the feasibility of accurate GRF and CoP estimation in diverse gait scenarios and support the potential for real-world applications. Future work will focus on sensor optimization and broader population validation. Full article