Search Results (41)

Autonomous drones may be called on to perform search-and-rescue operations in environments without access to signals from the global navigation satellite system (GNSS), such as underground mines, subterranean caverns, or confined tunnels. While technology to perform such missions has been demonstrated at events such as DARPA’s Subterranean (Sub-T) Challenge, the hardware deployed for these missions relies on heavy and expensive sensors, such as LiDAR, carried by costly mobile platforms, such as legged robots and heavy-lift multicopters, creating barriers for deployment and training with this technology for all but the wealthiest search-and-rescue organizations. To address this issue, we have developed a custom four-rotor aerial drone platform specifically built around low-cost low-weight sensors in order to minimize costs and maximize flight time for search-and-rescue operations in GNSS-denied environments. We document the various issues we encountered during the building and testing of the vehicle and how they were solved, for instance a novel redesign of the airframe to handle the aggressive yaw maneuvers commanded by the FUEL exploration framework running onboard the drone. The resulting system is successfully validated through a hardware autonomous flight experiment performed in an underground environment without access to GNSS signals. The contribution of the article is to share our experiences with other groups interested in low-cost search-and-rescue drones to help them advance their own programs. Full article

This study investigates an aerodynamic optimization framework inspired by marine biological morphology, utilizing the sailfish profile as a basis for airfoil configuration. Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. Parametric studies revealed that pivotal factors including installation angle significantly influenced the fluid dynamic performance metrics of lift generation and pressure drag. Response surface methodology was employed to establish predictive models for these critical performance indicators, effectively reducing computational resource consumption and experimental validation costs. The refined bio-inspired configuration demonstrated multi-objective performance improvements compared to the baseline configuration, validating the computational framework’s effectiveness for hydrodynamic profile optimization studies. Furthermore, a coaxial dual-rotor vertical axis turbine configuration was developed, integrating centrifugal and axial-flow energy conversion mechanisms through a shared drivetrain system. The centrifugal rotor component harnessed tidal current kinetic energy while the axial-flow rotor module captured wave-induced potential energy. Transient numerical simulations employing dynamic mesh techniques and user-defined functions within the Fluent environment were conducted to analyze rotor interactions. Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. Parametric optimization revealed maximum energy extraction efficiency for the centrifugal rotor occurs at λ = 1.25 tip-speed ratio under Re = 1.3 × 10⁵ flow conditions, while the axial-flow counterpart attained optimal performance at λ = 1.5 with Re = 5.5 × 10⁴. This synergistic configuration demonstrated complementary operational characteristics under marine energy conversion scenarios. Full article

Industrial workers often engage in repetitive lifting tasks. This type of continual loading on their arms throughout the workday can lead to muscle or tendon injuries. A non-intrusive system designed to assist a worker’s arms would help alleviate strain on their muscles, thereby preventing injury and minimizing productivity losses. The goal of this project is to develop a wearable soft robotic arm enhancement device that supports a worker’s muscles by sharing the load during lifting tasks, thereby increasing their lifting capacity, reducing fatigue, and improving their endurance to help prevent injury. The device should be easy to use and wear, functioning in relative harmony with the user’s own muscles. It should not restrict the user’s range of motion or flexibility. The human arm consists of numerous muscles that work together to enable its movement. However, as a proof of concept, this project focuses on developing a prototype to enhance the biceps brachii muscle, the primary muscle involved in pulling movements during lifting. Key components of the prototype include a soft robotic muscle or actuator analogous to the biceps, a control system for the pneumatic muscle actuator, and a method for securing the soft muscle to the user’s arm. The McKibben-inspired pneumatic muscle was chosen as the soft actuator for the prototype. A hybrid control algorithm, incorporating PID and model-based control methods, was developed. Electromyography (EMG) and pressure sensors were utilized as inputs for the control algorithms. This paper discusses the design strategies for the device and the preliminary results of the feasibility testing. Based on the results, a wearable EMG-controlled soft robotic arm augmentation could effectively enhance the endurance of industrial workers engaged in repetitive lifting tasks. Full article

Canada’s heritage sites, while fewer in number compared to Europe, face significant challenges in accessibility due to strict preservation laws. Many were built before social inclusion became a priority, making them difficult to navigate for individuals with disabilities. For example, cobbled streets with uneven surfaces or significant level differences create obstacles for wheelchair users and others with mobility challenges. This qualitative action research aimed to develop guidelines for shared street designs and innovative solutions that balance heritage preservation with inclusive accessibility. The study involved go along interviews with 21 participants with disabilities in Quebec City’s Petit-Champlain and Place-Royale areas, as well as the Old-Seminary. Insights from these interviews informed a co-design methodology involving three sessions with participants with disabilities, family caregivers, and experts in accessibility and heritage. The co-design sessions generated practical solutions such as lift platforms, accessible signage, and guided handrails, addressing both outdoor and indoor accessibility barriers. For indoor spaces, solutions included integrating acoustic panels and foldable seating, while outdoor recommendations emphasized autonomous access solutions like non-slip coatings and accessible elevators for winter conditions. It was concluded that achieving a balance between preservation and accessibility requires collaboration among architects, designers, heritage experts, and individuals with disabilities. This research highlights the importance of co-design as a method to ensure heritage sites remain culturally significant and universally accessible. Full article

Symmetric lateral inlet pumping stations are commonly utilized for water lifting in agricultural multi-crop irrigation districts, but they often share non-ideal flow patterns, which can easily cause pump vibration and sediment deposition. In this paper, a symmetrical lateral pumping station in an irrigation district is taken as the research object, and CFD (Computational Fluid Dynamics) technology is used to study it. The model test used a model scale ratio of ${\lambda }_L$ = 1:18. Results: By comparing the CFD data and test data, the average relative error for the left station is found to be 3.213%, while that for the right station is 5.107%, indicating that the numerical simulation method is reliable. Six different rectification measures are proposed, the cross sectional flow pattern of the pumping station is observed, and the longitudinal profile of axial velocity distribution in the sump is analyzed. The velocity-weighted average angle and hydraulic loss of each case study are also analyzed. The flow operates smoothly in case study 7. The vortex in the approach channel disappears when the columns and bottom sill are finally installed. Compared to the original case study, the velocity-weighted average angle at the 5# station in case study 7 increased by 14%, and it increased by 13.9% at station #9. The flow became more stable, and hydraulic losses were minimized. The simulated hydraulic loss in case study 7 decreased by 14.2%. These findings can serve as a reference for similar pump station projects. Full article

Can the backward endowments of rural areas support digital village construction to attain the expected results? If the answer is yes, what are the mechanisms involved? Answering these questions is related to common prosperity. Counties are China’s frontline commanders, and the urban–rural income gap is a suitable entry point for observing the urban–rural digital divide; however, there is limited research assessing the effectiveness of digital village construction from the perspective of the urban–rural income gap at the county level. In addition, counties lifted out of poverty, as counties with worse initial endowments and as counties that should be most concerned with common wealth, are more typical for examining the effectiveness of digital rural construction; however, there are few studies on counties lifted out of poverty. Based on cross-sectional data from 865 counties in China in 2020, this study empirically analyzes the impact of digital village construction on the urban–rural income gap using an OLS model. This study also conducts mechanism tests and poverty benefit tests in addition to heterogeneity and robustness tests. The findings indicate that the development of digital villages lowers the income difference between urban and rural areas, and that the shift in the industrial structure is a key driver of this effect. Different construction dimensions have varying degrees of impact, with digital infrastructure and the digitalization of the economy having the most significant impact, the digitalization of countryside governance coming second, and the digitalization of countryside life having the most negligible impact. The impact is more pronounced in the central-eastern region of China and counties that have just been lifted out of poverty than in the western region and counties that have never been in poverty. The government will benefit greatly from this study’s understanding of the main themes, areas, and scope of digital rural construction, which will help to expand and further integrate the outcomes of reducing poverty and fostering shared prosperity. Full article

At the beginning of July 2022, when public health restrictions were lifted, we deployed a country-wide e-survey about how older people were managing now after COVID-19 pandemic-related anxiety. Our responder sample was stratified by age, sex, and education to approximate the Canadian population. E-survey responders were asked to share open-text messages about what contemporaries could do to live less socially isolated lives at this tenuous turning point following the pandemic as the COVID-19 virus still lingered. Contracting COVID-19 enhanced older Canadians’ risk for being hospitalized and/or mortality risk. Messages were shared by 1189 of our 1327 e-survey responders. Content analysis revealed the following four calls to action: (1) cultivating community; (2) making room for what is good; (3) not letting your guard down; and (4) voicing out challenges. Responders with no chronic illnesses were more likely to endorse making room for what is good. Those with no diploma, degree, or certificate least frequently instructed others to not let their guard down. While COVID-19 is no longer a major public health risk, a worrisome proportion of older people across the globe are still living socially isolated. We encourage health and social care practitioners and older people to share messages identified in this study with more isolated persons. Full article

As ESG (environmental, social, and corporate governance) is consistent with the spirit of sustainable development, it is useful to elevate ESG performance to realize the sustainable development of enterprise and society. Using the data of Chinese A-share listed firms in the period of 2011 to 2019, this paper takes the National Big Data Comprehensive Pilot Zone policy as a quasi-natural experiment and uses the difference-in-differences method to assess the effect of digital economy development on ESG performance. This paper reveals the following: (1) the digital economy can facilitate ESG performance; (2) digitalization of the economy helps enterprises to propel digital transformation, which in turn lifts ESG performance; (3) digital economy development has a deeper impact on private enterprises, especially for those in China’s capital cities; and (4) digital economy development moderates the inhibiting effect of ESG performance on corporate financial constraints. The findings of this paper indicate that digitalization of the economy can help to achieve sustainable development. Full article

Conventional methods for solving Navier–Stokes (NS) equations to analyze flow fields and aerodynamic forces of airfoils with trailing edge flaps (TEFs) are known for their significant time cost. This study presents a Multi-Task Swin Transformer (MT-Swin-T) deep learning framework tailored for swift prediction of velocity fields and aerodynamic coefficients of TEF-equipped airfoils. The proposed model combines a Swin Transformer (Swin-T) for flow field prediction with a multi-layer perceptron (MLP) dedicated to lift coefficient prediction. Both networks undergo gradient updates through the shared encoder component of the Swin Transformer. Such a trained network model for computational fluid dynamics simulations is both effective and robust, significantly improving the efficiency of complex aerodynamic shape design optimization and flow control. The study further investigates the impact of integrating multi-task learning loss functions, skip connections, and the network’s structural design on prediction accuracy. Additionally, the effectiveness of deep learning in improving the aerodynamic simulation efficiency of airfoils with TEF is examined. Results demonstrate that the multi-task deep learning approach provides accurate predictions for TEF airfoil flow fields and lift coefficients. The strategic combination of these tasks during network training, along with the optimal selection of loss functions, significantly enhances prediction accuracy compared with the single-task network. In a specific case study, the MT-Swin-T model demonstrated a prediction time that was 1/7214 of the time necessitated by CFD simulation. Full article

Research Problem: Families with children travel by car more frequently than any other household type and hence significantly contribute to transport externalities. Lift-sharing is a potential time-effective and convenient means of mitigating these effects. Whilst some research has been conducted on lift-sharing for the school run, there is little research beyond this context, particularly around lift-sharing for children’s activities (e.g., sport). Study Aim: Consequently, the aim of this study was to assess the current prevalence of lift-sharing (for children’s activities and other types of trips) in families with young children, the factors influencing its uptake, the experiences and attitudes of regular lift-sharers, and whether previous literature findings on reciprocity applied in this context to gain a deeper understanding of how and why families participate in activity lift-sharing. Research Design: A mixed-methods approach was applied, comprising (1) a travel survey of 474 families to establish socio-demographic and activity factors that influence lift-share prevalence for activity trips; and (2) 15 semi-structured interviews with parents to further explore how and why families participate in activity lift-sharing. Results: Factors influencing lift-sharing decisions for activity travel were number of cars owned, number of seats in the car, settlement type, income, time of day and location of the activity, number of children attending, parking availability, whether the activity is a sporting activity or not, and number of close friends of the child at the same activity. Salient motivating factors triggering lift-sharing included intentions to reduce chauffeuring and parents wanting their children to socialise. Trust was an initial imperative component of lift-share formation, and attitudes towards reciprocity supported previous literature findings relating to the variability of acceptable reciprocation and the role of fairness. Full article

Introduction: Due to the lack of labeled data, applying predictive maintenance algorithms for facility management is cumbersome. Most companies are unwilling to share data or do not have time for annotation. In addition, most available facility management data are text data. Thus, there is a need for an unsupervised predictive maintenance algorithm that is capable of handling textual data. Methodology: This paper proposes applying association rule mining on maintenance requests to identify upcoming needs in facility management. By coupling temporal association rule mining with the concept of semantic similarity derived from large language models, the proposed methodology can discover meaningful knowledge in the form of rules suitable for decision-making. Results: Relying on the large German language models works best for the presented case study. Introducing a temporal lift filter allows for reducing the created rules to the most important ones. Conclusions: Only a few maintenance requests are sufficient to mine association rules that show links between different infrastructural failures. Due to the unsupervised manner of the proposed algorithm, domain experts need to evaluate the relevance of the specific rules. Nevertheless, the algorithm enables companies to efficiently utilize their data stored in databases to create interpretable rules supporting decision-making. Full article

The purpose of this study was to compare electromyographic (EMG) with mechanomyographic (MMG) recordings during isometric conditions, and during a simulated load-lifting task. Twenty-two males (age: 25.5 ± 5.3 years) first performed maximal voluntary contractions (MVC) and submaximal isometric contractions of upper limb muscles at 25%, 50% and 75% MVC. Participants then executed repetitions of a functional activity simulating a load-lifting task above shoulder level, at 25%, 50% and 75% of their maximum activity (based on MVC). The low-frequency part of the accelerometer signal (<5 Hz) was used to segment the six phases of the motion. EMG and MMG were both recorded during the entire experimental procedure. Root mean square (RMS) and mean power frequency (MPF) were selected as signal extraction features. During isometric contractions, EMG and MMG exhibited similar repeatability scores. They also shared similar RMS vs. force relationship, with RMS increasing to 75% MVC and plateauing to 100%. MPF decreased with increasing force to 75% MVC. In dynamic condition, $RM{S}_{MMG}$ exhibited higher sensitivity to changes in load than $RM{S}_{EMG}$. These results confirm the feasibility of MMG measurements to be used during functional activities outside the laboratory. It opens new perspectives for future applications in sports science, ergonomics and human–machine interface conception. Full article

Two methods for multistage adaptive robust binary optimization are investigated in this work. These methods referred to as binary decision rule and finite adaptability inherently share similarities in dividing the uncertainty set into subsets. In the binary decision rule method, the uncertainty is lifted using indicator functions which result in a nonconvex lifted uncertainty set. The linear decision rule is further applied to a convexified version of the lifted uncertainty set. In the finite adaptability method, the uncertainty set is divided into partitions and a constant decision is applied for each partition. In both methods, breakpoints are utilized either to define the indicator functions in the lifting method or to partition the uncertainty set in the finite adaptability method. In this work, we propose variable breakpoint location optimization for both methods. Extensive computational study on an illustrating example and a larger size case study is conducted. The performance of binary decision rule and finite adaptability methods under fixed and variable breakpoint approaches is compared. Full article

The displacement and resettlement-associated poverty caused by water conservancy projects (WCP) is a worldwide issue. Re-settlers are often impoverished for extended periods due to loss, difficult re-establishment, and insufficient compensation. Addressing poverty has become a worldwide concern, and accurate measurements of poverty remain a fundamental issue. Before 2020, the Chinese government used the absolute income method to measure re-settler poverty. However, this method reflected neither the overall income gap nor potential benefits of social development and poverty alleviation policies. Therefore, we used the relative income and multidimensional methods alongside the absolute income poverty method to measure the poverty in recently resettled households. Based on survey data from over resettled 1000 households we conclude that: (1) The remaining poor measured by the absolute poverty line were mainly caused by serious diseases, disabilities and loss of labor ability, which means they have no ability to be lifted out of poverty except through the bottom line of local governments. As a result, the absolute poverty line loses its distinction to poverty. (2) Rural re-settlers were more resilient to forced majeure because land guarantees employment and food supply, allowing households to avoid secondary livelihood destruction. (3) Income derived measurement of re-settler poverty masks the benefits of poverty alleviation and other socioeconomic aid programs. A few households showed improvements in child school attendance, child mortality, nutrition, cooking fuel, asset ownership, and social insurance following resettlement. (4) To reduce the multidimensional gap, government aid programs should focus on years of schooling (including training), nutrition, household savings, and household labor force rather than simply providing monetary assistance. At the same time, we suggest that the government adopt a variety of compensation methods, such as: sharing the benefits of water conservancy projects, industrial support and improving the bottom line guarantee. Full article

The current study involves an experimental as well as numerical study on the aerodynamic behavior of a flapping-wing rotor (FWR) with different feathering amplitudes (−20°–50°, −50°–20°, and −35°–35°). In order to fulfil the experimental test, an FWR which weighs 18.7 g is designed in this manuscript. According to the experimental and numerical results, it was observed that, compared with the cases under a zero average stroke angle, the cases under a positive average stroke angle or negative average stroke angle share a higher rotary speed given the same input voltage. Despite the fact that the negative average stroke angle would facilitate the generation of a higher rotary speed, the negative average stroke angle cases tend to generate the smallest lift-to-power ratio. On the other hand, the cases with a positive average stroke angle tend to share the largest lift-to-power ratio (about 1.25 times those of zero average stroke angle cases and about 1.6 times those of negative average stroke angle cases). The above study indicates that the application of a positive average stroke angle can provide an effective solution to further increase the aerodynamic performance of a bio-inspired FWR. Full article