Transportation Costs Research Articles

The content optimization of supplementary cementitious materials in coral sand-seawater cement mortar: A focus on mechanical properties and transportation costs

This study examines how supplementary cementitious materials (SCMs) such as fly ash (FA), blast furnace slag (BFS), and metakaolin (MK) affect the mechanical properties and transportation costs of coral sand-seawater cement mortar (CSSC). The Dinger-Funk equation was used to obtain the most densely packed design and preparation of coral sand and cementitious materials. The mechanical properties of CSSC were assessed utilizing the RMT testing apparatus. A thorough examination of the mechanical properties and transportation costs of CSSC was undertaken using the principle of value engineering and the effectiveness coefficient approach. Research results show that BFS10 has outstanding mechanical qualities in the binary cementitious system. Within the ternary cementitious system, the mechanical qualities typically exceed those of the binary system, with FA15BFS15 demonstrating the highest performance. The best appropriate mix ratio is FA15BFS15, as determined by a thorough examination and cost-benefit analysis. This ratio offers temporal sensitivity and maximized transit capacity. The SVR model is highly proficient in forecasting the compressive strength of CSSC, showcasing accurate prediction and data interpretation abilities. The research findings provide practical evidence for optimizing the proportion of CSSC in calcium sulfoaluminate cement, considering transportation expenses and algorithm prediction needs.

If it is adequate, it is not affordable: stakeholder perceptions on opportunities and constraints for pension reform in Indonesia

PurposeThe purpose of the study is to emphasise the urgent need for pension policy reform within Indonesia’s social security system.Design/methodology/approachThe methodology employed in this research includes qualitative techniques such as in-depth interviews and thematic content analysis.FindingsThe findings suggest various measures for pension reform, including revising eligibility criteria, adjusting benefit designs to cover housing and transportation costs, promoting Defined Benefit Plans, enforcing compliance, addressing insufficient contributions, advocating for transparency, and aligning social assistance programs with pension system enhancements. However, there is a trade-off between the adequacy of pension benefits and the amount of resources required.Research limitations/implicationsThis study is limited by the need for more individuals knowledgeable about pension issues in Indonesia, primarily due to their high-ranking positions, making access challenging and potentially compromising the small sample size in research.Practical implicationsThe research underscores the importance of maintaining policy consistency. It proposes a gradual increase in pension contributions as a pivotal strategy to ensure sustained financial security for retirees, particularly in the face of fiscal constraints. Also, the government should undertake comprehensive reforms, encompassing the revision of eligibility criteria, adjustment of minimum benefit designs, encouragement of employer contributions and effective management of compliance issues.Social implicationsSocial implications emphasise the importance of enhancing the financial security of retirees within Indonesia’s ageing population.Originality/valueThe originality and value of the research lie in guiding pension reform from the viewpoint of key policymakers involved in Indonesia’s pension system.

Sustainable gains from inland waterway investments at port-city interface

The objective of this research is to identify and quantify the sustainable impacts resulting from transportation investments at the port-city interface. These investments encompass two main components: 1) restoring the local inland waterway fairway for navigation, and 2) constructing a new railway bridge that traverses the primary waterway at the entrance of the seaport. The study is centered on the local transportation system in the northwestern region of Poland. Sustainability is assessed using an analytical tool derived from societal cost-benefit analysis and simulation in the relevant market transport performance in options with and without investment. Economic effects are evaluated in terms of savings in generalized transportation costs, which include transport operating expenses and travel durations. Environmental considerations encompass transport-related air pollution, greenhouse gas emissions, and well-to-tank emissions. Social aspects focus on issues like transport congestion, traffic noise, and transport-related accidents. Each type of investment yields distinct sustainable gains and distributes them among stakeholders differently. Additionally, the enhanced capacity of the rail bridge reveals the potential for a modal shift in the local passenger transport system, wherein passengers may transition from buses/cars to a fast railway. Tangible gains expressed in monetary terms allow for a sustainable assessment of transport investments. The elaborated research scheme can be employed to assess the sustainable ramifications arising from investments in intermodal transport at any port-city interface. It provides decision-makers with comprehensive insights into the economic, environmental, and social implications of various transport policies and interventions.

Heuristic-Based Hybrid Algorithm for Value Stream Design with Milk-Run Approach

In this study, a heuristic algorithm has been developed for the Milk-Run related to the vehicle routing problem. It aimed to supply in the right place and at the right time in a short time with the internal logistics system approach. Since the proposed problem formulation is NP-hard, we suggested a heuristic-based hybrid genetic algorithm method to solve the problem. Real life problem is solved with a milk run approach inspired by vehicle routing problems. Firstly the model was developed with mixed integer linear programming then the problem was solved with the proposed hybrid genetic algorithm. The aim reduce the total transportation cost in the network and the number of vehicles required by using an efficient vehicle routing strategy. It explains the change in the existing distribution and collection systems of a logistics service company. The response of variables such as time, weight, volume, and pallet was measured under various scenarios with cost and time savings by applying Milk-Run optimization. The deterministic model and the proposed heuristic algorithm compared the previews and outputs of the paths. Accordingly, 30% and 50% discounts were made on restrictions for six different scenarios.

Choice or Constraint? A Locally Tailored Assessment of Housing and Transportation Costs in Central Texas

Transportation costs are a key component of an overall household budget. These costs are determined in part by residential location—housing and transportation costs are inextricably linked. The burden of high housing and transportation costs must be understood in context. High costs on their own are not necessarily a problem if a household freely chooses their location. Although several national-level tools (including the Center for Neighborhood Technology’s H+T Index and the U.S. Department of Housing and Urban Development’s Location Affordability Index) are now available to improve transparency about combined housing and transportation costs, their ability to reflect local conditions and to understand relative burdens is limited. In this paper, we create a combined housing and transportation cost index tailored to the realities of the Austin metropolitan area in Central Texas, with most data sources coming from state and local government or pertinent transportation agencies. We identify households allocating large shares of their budgets to housing and transportation costs and differentiate between those that have the ability to mode switch to reduce costs in principle and those that do not. Black and Hispanic/Latino households were disproportionately burdened by high costs. But across the entire population, overall cost burdens were low. This result means that fostering nonautomobile travel or denser residential living will be challenging using cost arguments alone.

Cost-competitive decentralized ammonia fertilizer production can increase food security.

The current centralized configuration of the ammonia industry makes the production of nitrogen fertilizers susceptible to the volatility of fossil fuel prices and involves complex supply chains with long-distance transport costs. An alternative consists of on-site decentralized ammonia production using small modular technologies, such as electric Haber-Bosch or electrocatalytic reduction. Here we evaluate the cost-competitiveness of producing low-carbon ammonia at the farm scale, from a solar agrivoltaic system, or using electricity from the grid, within a novel global fertilizer industry. Projected costs for decentralized ammonia production are compared with historical market prices from centralized production. We find that the cost-competitiveness of decentralized production relies on transport costs and supply chain disruptions. Taking both factors into account, decentralized production could achieve cost-competitiveness for up to 96% of the global ammonia demand by 2030. These results show the potential of decentralized ammonia technologies in revolutionizing the fertilizer industry, particularly in regions facing food insecurity.

Joint optimization of the inventory routing problem considering the recycling of broken bikes in the bike-sharing system

Bike-sharing system has become an indispensable element of sustainable urban transportation, effectively resolving the "last mile" transportation challenge for city dwellers. A major daily operational task in these systems is planning a fleet to rebalance the bikes over time, ensuring the optimal availability of bikes and docks to users. Recycling is also a daily work with the an increase in the number of broken bikes. However, rebalancing or recycling operation is always regarded as an independent tasks. They are separately studied in existing papers. Thus, this paper develops an operational strategy for recycling broken bikes during the rebalancing process, and studies the combination of the station inventory and vehicle routing problems. First, an inventory routing model is constructed with the aim of minimizing the total costs including procurement, expected user loss, inventory and transportation costs. Then, a two-stage iterative algorithm is developed with both exact and heuristic algorithms. We use real-world data from Capital Bikeshare to test our proposed model and approach, which shows the two-stage iterative algorithm is efficient and outperforms existing solutions in reducing total costs. Finally, the sensitivity analysis is performed on key parameters such as the vehicle’s capacity, unit penalty costs for customer dissatisfaction events, unit inventory holding costs and the observation period of rebalancing. It shows that enterprises can reduce the total cost by altering vehicle’s capacity, reducing the unit inventory holding costs or changing the observation period of rebalancing.

A Systematic Formulation into Neutrosophic Z Methodologies for Symmetrical and Asymmetrical Transportation Problem Challenges

This study formulates a multi-objective, multi-item solid transportation issue with parameters that are neutrosophic Z-number fuzzy variables such as transportation costs, supplies, and demands. This work covers two scenarios where uncertainty in the problem can arise: the fuzzy solid transportation problem and the interval solid transportation problem. The first scenario arises when we represent data problems as intervals instead of exact values, while the second scenario arises when the information is not entirely clear. We address both models when the uncertainty alone impacts the constraint set. In order to find a solution for the interval case, we generate an additional problem. Since this auxiliary problem is typical of solid transportation, we can resolve it using the effective techniques currently in use. In the fuzzy scenario, a parametric method is used to discover a fuzzy solution to the earlier issue. Parametric analysis identifies that the best parameterized approaches to complementary problems are characterized by the application of parametric analysis. We present a suggested algorithm for determining the stability set. Finally, we provide a numerical example and sensitivity analysis for the transportation problem, which is both symmetrical and asymmetrical.

Pine needle gasification-based electricity production: Understanding the effect of supply chain.

Pine needles (pine tree leaves), found abundantly across continents such as North America, Asia, Europe, South America, Africa, and parts of the Southern Hemisphere, are a significant global concern due to their high susceptibility to catching fire, especially in dry and hot climates. The same issue persists in the Uttarakhand state of India, which boasts ample pine forests, yielding a substantial 1.67 × 109kg of pine needles annually. In the present study, the annual potential emissions from forest fires in Uttarakhand were estimated to be 58.37 × 109kg of CO2 equivalent. Therefore, the present research aims to unlock pine needles' potential via gasification for green electricity and biochar production, offering an alternative to coal-based plants while reducing forest fire frequencies. Nevertheless, obstacles hindering pine needle gasification include an unsteady supply chain, limited collection windows (100days), and plant expenses, including transportation and operational costs. The primary focus of the research is to design and assess the performance of a gasification-based supply chain for pine needles in the Almora District of Uttarakhand. Ten plant capacity scenarios were considered, ranging from 25 to 250kW. The study incorporated critical factors, encompassing diverse losses within the supply chain, selecting potential plant sites, minimizing transportation distance, and evaluating the supply chain's economic and environmental performance. The economic analysis revealed that the 250-kW plant scenario exhibited a minimum discounted payback period (DPP) of 3.93years, alongside an internal rate of return (IRR) of 19% and a net present value (NPV) of 653.32 million INR without government subsidies. With subsidies included, the DPP decreased to 1.30years, improving the IRR to 69% with an NPV of 916.17 million INR. The emission analysis indicated that gasification plant capacity scenarios could potentially reduce 44.63 × 106 to 46.16 × 106kg of CO2 equivalent emissions annually compared to grid electricity while meeting nearly 5.5% of the electricity demand of Almora district. The present study aligns with SDG-7 (Affordable and Clean Energy), SDG-13 (Climate Action), SDG-9 (Industry, Innovation, and Infrastructure), SDG-11 (Sustainable Cities and Communities), SDG-3 (Good Health and Well-being), and SDG-15 (Life on Land).

GARBAGE COLLECTOR USING ARDUINO

The amount of Solid waste that is being produced through our everyday activities is huge and is getting unmanageable day by day. This is mainly due to increasing population leading to haphazard dumping and increasing transportation costs with already few cost-effective methods to treat the solid waste. According to an estimate in 2016, 277 million tons of solid waste is produced by India every year. It is also projected to increase to 387 million tons by 2030 and 543 million tons by 2050. The very first method involved in the Solid Waste Management is sorting of waste which simplifies the further procedure as to what to do with the waste i.e., should it be treated thermally, biologically or dumped. Improper segregation of solid waste and segregation at secondary levels of waste management is only going to delay the waste management process and sometimes even lead to inappropriate dumping. This project suggests a way to deal with segregation process so as to make the whole solid waste management easier and more efficient. Automatic Waste Segregation system provides a practical segregation process of solid waste into metal waste, dry waste and wet waste at the primary level right where the waste is being generated. An Automatic Waste Segregator with simpler mechanism than that of previous models is designed and a detailed methodology of the working of the segregation process is provided. Selection of the required equipment has been mentioned. This project aims at segregating the waste produced at the primary level and reducing the burden at secondary levels and cost of transportation of the waste. The results obtained after testing the Automatic Waste Segregator with wastes proved to be functional and can be comfortably relied upon to segregate the wastes.

Logistics distribution route optimization of electric vehicles based on distributed intelligent system

Abstract The data management system of health cloud authentication plays an important role in the optimization of logistics vehicle routing. It can not only help logistics vehicles choose the best distribution path, but also save time and cost and improve economic efficiency. At present, logistics has not yet formed a complete service system. High distribution costs and low distribution efficiency limit the development of the entire logistics. The reduction of logistics costs and the improvement of distribution efficiency have become the top priorities of the society. The optimization of the distribution route is the key to cost saving and distribution logistics. It is particularly important to study and optimize the distribution route, because the distribution route affects the logistics transportation efficiency and the loss cost during transportation. Therefore, this paper adjusted the scheduling system of logistics vehicles through a distributed intelligent system, and optimized the path of logistics vehicles according to the improved genetic algorithm, thereby reducing the transportation cost of logistics and improving the efficiency of logistics distribution. This article first explains the definition, classification, and main components of the delivery vehicle routing problem. Then, using cloud authentication path optimization, a distributed intelligent system is constructed. Finally, an improved ant colony algorithm is used to analyze and study the distance constraints of vehicles. By improving the ant colony algorithm, it can be seen that the optimized path pheromone concentration and the optimized sub-function have gradually increased with time. The mean pheromone concentration was 40 %, and the seventh day was 15 % higher than the first. The mean value of the optimized subfunction was 0.34 %, and the seventh day was 20 % higher than the first. The distribution cost and distribution efficiency of the optimized logistics vehicle distribution path were much higher than those of the traditional logistics distribution path. Moreover, the distribution cost of the logistics distribution path was 9 % lower than the traditional one, and the distribution efficiency was 13 % higher. The average smoothness of the optimized logistics path is about 90 %, and the seventh day is 11 % higher than the first day. The average fitness of the optimized logistics path is 88 %, and the seventh day is 14 % higher than the first day. In a word, the data management system can uniformly schedule logistics vehicles and improve the efficiency of distribution.

Sustainability Assessment of 2G Bioethanol Production from Residual Lignocellulosic Biomass

The development of sustainable biofuels can help to reduce the reliance on fossil fuels and mitigate the impact of climate change. This study analyzes bioethanol production from agro-forestry residual biomass, namely eucalyptus residues and corn stover. The study includes process simulation using Aspen Plus software, followed by economic analysis and life cycle assessment (LCA) with the help of SimaPro software and by applying the environmental footprint (EF) 3.0 method. The economic analysis on the biorefinery’s economic viability, equipment, and production costs reveals a positive decision for bioethanol production from eucalyptus residues due to logistical and transportation costs. The minimum ethanol selling price (MESP) obtained was 2.19 €/L and 2.45 €/L for eucalyptus residues and corn stover, respectively. From the LCA with a functional unit of 1 MJ of ethanol, bioethanol production from eucalyptus residues results in a single score impact of 37.86 µPt, whereas for corn stover, it is 33.47 µPt. In the climate change impact category, the eucalyptus residues scenario has an impact of 0.264 kg CO2 eq/MJ ethanol while corn stover leads to 0.254 kg CO2 eq/MJ ethanol. In-situ enzyme production, heat integration, and the use of renewable energy sources were also analyzed. Combining in situ enzyme production with renewable energy sources lowers CO2 equivalent emissions by 89% for both feedstocks, in comparison to the base-case scenario.

The impact of credit accessibility and information communication technology on the income of small-scale sugarcane farmers in Ndwedwe Local Municipality, KwaZulu-Natal Province, South Africa

IntroductionAccess to credit and information and communication technology (ICT) plays a pivotal role in enhancing the practices of small-scale sugarcane farmers, impacting their financial, social, and economic wellbeing. However, many small-scale farmers need help accessing these resources, thereby affecting their ability to generate sustainable income. This study aimed to assess the factors influencing the adoption of ICT and access to credit and their subsequent impact on small-scale farmers' income.MethodsEmploying a multistage sampling technique, 300 small-scale farmers were selected as participants in the study. The recursive bivariate probit regression model was used to assess the factors affecting adoption ICT and a selectivity-corrected ordinary least square regression model was utilized to estimate the synergistic effect of ICT adoption and access to credit on the income of small-scale sugarcane farmers.Results and discussionThe findings revealed that approximately 77% of small-scale farmers had access to credit, while more than 80% had adopted ICT. The results derived from the recursive bivariate probit (RBP) regression model indicated that access to credit, education, and extension support positively and significantly influenced the adoption of ICT. Conversely, marital status and non-farm income exhibited a negative and significant influence on the adoption of ICT. Gender and marital status were positively and significantly associated with access to credit, whereas age, education, and non-farm income showed a negative and significant relationship on access to credit. Subsequently, a selectivity-corrected ordinary least square regression model analysis revealed that factors such as gender, marital status, extension, government support, and transportation costs positively and significantly influenced farmer's income. In contrast, education, employment status, and non-farm income exhibited a negative and significant influence on income.Conclusion and recommendationsThe study concludes that socio-demographic factors, such as gender, marital status, extension support, government support, and transportation costs, positively contribute to farmers' income. Small-scale sugarcane farmer involvement in other non-farm activities is associated with reduced farm income. This implies that farmers' livelihoods options are reduced as they can only focus on sugarcane development as a source of income. There is a pressing need to educate small-scale farmers on ICT and provide them with access to agricultural credit. Additionally, extension workers should offer advisory support to small-scale farmers requiring assistance in accessing agricultural credit. There is a need to train sugarcane farmers on different agricultural income generating activities to reduce their over-reliance on sugarcane development. By addressing the identified socio-demographic factors and implementing targeted policy interventions, stakeholders can foster an enabling environment for small-scale farmers to thrive, ultimately contributing to the sustainable development of the sugarcane sector and the broader agricultural landscape in South Africa.

A novel development of a new single switch inductor coupled DC-DC converter for PV system with two-leg inverter

From the power generation history, the nonrenewable power sources utilization is falling extremely because of their demerits are high atmospheric pollution, more expensive, more catchment area for development, high fossil fuel transportation cost, less flexibility, and reliability. So, the sunlight systems are utilized in this work for feeding the power to the central grid. On the earth, the sunlight energy availability is more and it is more flexible for the installation. However, the sunlight photovoltaic (PV) module’s power production is very low. To improve the power generation of the PV network, a modified slider maximum power point tracking (MPPT) controller is proposed in the first objective and it is interfaced with the sunlight system for capturing more sunlight insolation thereby moving the functioning point of the solar system from local MPP place to required global MPP place. The features of this sliding controller are continuous peak power production, easy development, less power dissipation losses, plus good dynamic system response. In the second objective, the available voltage of the PV is low which improved from low level to high level by utilizing the Wide voltage supply-inductor coupled converter. The development of this circuit needed very less inductive, plus capacitive components. Also, it is developed by selecting a single switch. As a result, the entire network power production cost is reduced. In the third objective, a two-leg inverter is proposed for the transformation of the DC voltage supply into three-phase powers. The MATLAB/Simulink tool is used to investigate the overall system.

Can toll prices changes affect the housing market? The case of the Severn crossing toll removal

PurposeSince 1966, the Severn crossing has been connecting England and Wales. In January 2018, its ownership returned to the UK Government, and this marked the start of a toll-free journey across the two countries and made commuting between the regions more affordable. In this paper, we examine the impact of the toll removal on the property market.Design/methodology/approachWe employ property-level data from the Land Registry and a difference-in-differences (DiD) empirical model for the periods 2016–2018 and 2019–2021 to capture the pre- and post-toll removal dynamics. The DiD estimation allows us to examine the causal relationship between policy changes and property prices.FindingsOur findings suggest that property prices in Newport and Monmouthshire (South East Wales) are positively affected by the policy, which results in a statistically significant increase of 5.8% more than those located in the South West England (Bristol and South Gloucestershire) region in the period 2019–2021. The impact can reach up to 13.1% for properties located in a 10 km radius of the bridge. The results indicate that the toll removal enables the ripple effect across the two markets by reducing commuting costs.Originality/valueThis is the first paper that examines the Severn Crossing case study. Its contribution is significant since we provide empirical evidence on how reduced transportation costs increase property prices in the lowest income region and have the opposite effect on the area with higher incomes and economic activity levels.

OPTIMIZATION OF ORGANIZATIONAL PROCESSES IN CIVIL ENGINEERING USING LOGISTICS MODELS

Purpose. In accordance with the analyzed problem, there is a need for a more detailed study and justification of the benefits of implementing logistics models to optimize organizational processes in civil engineering. Methodology. To achieve this goal, the article conducts a systematic analysis of organizational processes in civil engineering in terms of logistics approaches. Current trends in the industry, regulations and scientific developments are considered, risks and barriers that may arise when implementing logistics models in the construction industry are analyzed, practical examples of possible use of logistics concepts in civil engineering at different stages of work and when using specific building materials are offered, ways to overcome barriers and stimulate the implementation of logistics models are provided, and an integrated approach to optimizing organizational processes in civil engineering is proposed. Findings. The study has shown that the introduction of logistics models in civil engineering can lead to: significant efficiency improvements, shorter construction time, reduced costs for materials and transportation, improved quality of construction work, reduced environmental impact, rational use of resources, reduced construction waste, increased competitiveness, improved safety, and increased project profitability. Originality. The key principles of development and functioning of logistics models in the context of civil construction are identified: the principle of integration: combining all stages of the construction process into a single logistics system, the principle of resource optimization: minimizing the cost of materials, transport, labor, the principle of flexibility and adaptability: the ability to adapt the logistics model to changing construction conditions. Practical value. The results of the study indicate that the introduction of logistics models in civil engineering is a relevant and promising area for optimizing processes in this sector. The use of logistics can contribute to effective resource management, increase productivity and reduce costs, which is noted by the practical importance of this study.

Scheduling of Container Transportation Vehicles in Surface Coal Mines Based on the GA–GWO Hybrid Algorithm

The coal loading operation of the coal preparation plant of an open pit coal mine causes chaos in coal mine vehicle scheduling due to the unreasonable arrival times of outgoing and container transportation vehicles. To further reduce the length of time that vehicle transportation equipment waits for each other and to reduce the total cost of container transportation, the optimisation model of container transportation vehicle scheduling in an open pit coal mine is constructed to minimise the minimum sum of the shortest time of container reversal and the lowest cost of container transportation. To accurately measure the total cost of container backward transportation, waiting time and unit waiting time cost parameters are introduced, and the total cost of container transportation is measured using the transportation cost and the waiting time cost transformation method. An improved grey wolf algorithm is proposed to speed up the convergence of the algorithm and improve the quality of the solution. When employing the genetic algorithm (GA) and grey wolf optimisation algorithm (GWO) for optimising the scheduling of container transport vehicles in coal mines, it is noted that while the GA can achieve the global optimum, its convergence speed is relatively slow. Conversely, the GWO converges more quickly, but it tends to be trapped in local optima. To accelerate the convergence speed of the algorithm and improve the solution quality, a hybrid GA−GWO algorithm is proposed, which introduces three genetic operations of selection, crossover, and mutation of GA into the GWO algorithm to prevent the algorithm from falling into the local optimum due to the fall; at the same time, it introduces hunting and attacking operations into the elite retention strategy of GA, which improves the stability of the algorithm’s global convergence. Analysis indicates that, compared to SA, GWO, and GA, the hybrid algorithm enhances optimisation speed by 43.1%, 46.2%, and 43.7%, increases optimisation accuracy by 4.12%, 6.1%, and 3.2%, respectively, and reduces the total container reversal time by 35.46, 22, and 31 h. The total cost of container transportation is reduced by 2437 RMB, 3512 RMB, and 1334 RMB, respectively.

The Impact of Climate Change on Tourism Demand in China

This study quantified the impact of climate on the international tourism demand in China. Due to rising awareness and urgency to combat climate change, there is a growing need to better grasp the possible implications and the risk of climate change to the tourism industry. The tourists’ travel decision can be influenced by both climatic and non-climatic factors, and thus this study has integrated both factors into the models. The climatic variable is represented by Tourism Climate Index (TCI) and Holiday Climate Index (HCI) while the selected non-climatic determinants are tourists’ income, tourism price, exchange rate and transportation cost. The empirical findings showed that climate conditions significantly and adversely affect China’s tourism demand. Tourists’ income level, as expected, positively affects their decision to travel to China. Meanwhile, the tourism price, exchange rate, and transportation cost negatively impact China’s tourism industry. Although some valuable results have been found, more works are required to understand its long-haul significance to the tourism industry, especially during extreme events such as extreme weathers, pandemics, financial crises and etc.

A wireless controlled robotic insect with ultrafast untethered running speeds

Running speed degradation of insect-scale (less than 5 cm) legged microrobots after carrying payloads has become a bottleneck for microrobots to achieve high untethered locomotion performance. In this work, we present a 2-cm legged microrobot (BHMbot, BeiHang Microrobot) with ultrafast untethered running speeds, which is facilitated by the complementary combination of bouncing length and bouncing frequency in the microrobot’s running gait. The untethered BHMbot (2-cm-long, 1760 mg) can achieve a running speed of 17.5 BL s−1 and a turning centripetal acceleration of 65.4 BL s−2 at a Cost of Transport of 303.7 and a power consumption of 1.77 W. By controlling its two front legs independently, the BHMbot demonstrates various locomotion trajectories including circles, rectangles, letters and irregular paths across obstacles through a wireless control module. Such advancements enable the BHMbot to carry out application attempts including sound signal detection, locomotion inside a turbofan engine and transportation via a quadrotor.

Routine 2-Week Postoperative Radiographs After Geriatric Hip Fracture Fixation: Low Utility and High Cost

Background: Geriatric hip fractures are associated with a large financial burden on both patients and payors, yet minimal data exist regarding postoperative cost optimization and guidelines for delivering high-value care. We assessed the utility and cost of routine radiographs at the first postoperative visit (FPOV) after fixation of geriatric hip fractures. Methods: We retrospectively evaluated patients with isolated geriatric hip fractures treated with internal fixation between January 2018 and September 2020. Medical records were reviewed to assess whether radiographs at the FPOV changed management. Direct costs of radiographs at the FPOV were estimated using Medicare Fee Schedule data. Indirect costs were estimated by assessing transportation costs. National costs were estimated by extrapolating institutional and Medicare data to the estimated 300,000 to 500,000 annual hip fractures in the United States. Results: Two hundred forty-one patients were included. A majority had intertrochanteric fractures (80%), were injured because of a ground-level fall (94%), and received long intramedullary nails (73%). One patient (1/241, 0.41%) had their postoperative management changed by FPOV radiographs, and that patient had an acute reinjury before their FPOV. Patients discharged home (50/241, 21%) traveled mean 51.3 miles each way, and those discharged to another facility (191/241, 79%) traveled mean 24.1 miles each way. The national estimated direct cost of routine radiographs at the FPOV totaled $10.9 to $18.2 m annually. The national indirect costs are estimated to be $1.2 to $1.9 m annually for patients discharged home and $63.4 to $105.7 m annually for patients discharged to a facility. Conclusions: Routine radiographs at the FPOV after internal fixation of geriatric hip fractures may not change management and should only be obtained when specifically indicated. Elimination of routine radiographs and conduction of the FPOV virtually by telemedicine could result in national cost savings of estimated $75.5 to $125.8 m annually without compromising quality of care.