Search results

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

In service, the periodic clashes of wheel flat against the rail result in large wheel/rail impact force and high-frequency vibration, leading to severe damage on the wheelset, rail and track structure. This study aims to analyze characteristics and dynamic impact law of wheel and rail caused by wheel flat of high-speed trains.

A full-scale high-speed wheel/rail interface test rig was used for the test of the dynamic impact of wheel/rail caused by wheel flat of high-speed train. With wheel flats of different lengths, widths and depths manually set around the rolling circle of the wheel tread, and wheel/rail dynamic impact tests to the flats in the speed range of 0–400 km/h on the rig were conducted.

As the speed goes up, the flat induced the maximum of the wheel/rail dynamic impact force increases rapidly before it reaches its limit at the speed of around 35 km/h. It then goes down gradually as the speed continues to grow. The impact of flat wheel on rail leads to 100–500 Hz middle-frequency vibration, and around 2,000 Hz and 6,000 Hz high-frequency vibration. In case of any wheel flat found during operation, the train speed shall be controlled according to the status of the flat and avoid the running speed of 20 km/h–80 km/h as much as possible.

The research can provide a new method to obtain the dynamic impact of wheel/rail caused by wheel flat by a full-scale high-speed wheel/rail interface test rig. The relations among the flat size, the running speed and the dynamic impact are hopefully of reference to the building of speed limits for HSR wheel flat of different degrees.

The main aim of this study is to investigate the impact of climate change and water salinity on farmer’s income risk with future outlook mitigation. Salinity and climate change are a threat to agricultural productivity worldwide. However, the combined effects of climate change and salinity impacts on farmers' income are not well understood, particularly in developing countries.

The response-yield function and general maximum entropy methods were used to predict the impact of temperature, precipitation and salinity on crop yield. The target minimization of total absolute deviations (MOTAD)-positive mathematical programming model was used to simulate the impact of climate change and salinity on socioeconomic and environmental indicators. In the end, a multicriteria decision-making model was used, aiming at the selection of suitable climate scenarios.

The results revealed that precipitation shows a significantly decreasing trend, while temperature and groundwater salinity (EC) illustrate a significantly increasing trend. Climate change and EC negatively impact the farmer's income and water shadow prices. Maximum reduction in income and water shadow prices was observed for A2 scenario (−12.4% and 19.4%) during 2050. The environmental index was the most important, with priority of 43.4% compared to socioeconomic indicators. Subindex amount of water used was also significant in study area, with 28.1% priority. The technique for order preference by similarity to ideal solution ranking system found that B1 was the best climatic scenario for adopting climate change adaptation in the research region.

In this study, farmers' income threats were assessed with the aspects of different climate scenario (A1, A1B and B1) over the horizons of 2030, 2040 and 2050 and three different indicators (economic, social and environmental) in Northwestern region of Pakistan. Only in arid and semiarid regions has climate change raised temperature and reduced rainfall, which are preliminary symptoms of growing salinity.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.

This paper aims to identify the risk factors that affect depression in students who sought psychological consultation during lockdown period in the health department at a university in Colombia.

The sample consisted of 33 students (12 men and 21 women) with a mean age of 21 ± 2.5 years during the COVID-19 lockdown in 2020. Convenience sampling was used. The beck depression inventory-II instrument and a sociodemographic questionnaire were used to determine levels of depression and associated risk factors. A Google Form was designed with the respective instruments and sent along with the informed consent by email.

The results indicated that the population is characterized by presenting a level of mild (24.2%), moderate (15.2%) and severe (21.2%) depression. Concerning the levels of depression and risk factors, a significant difference was found with a history of violence (p-value = 0.000), mainly during childhood and adolescence, as well as objection to psychological therapy, belonging to a medium–high socioeconomic stratum, lack of family support and recent significant losses coupled with the lockdown because of the pandemic, which increased symptoms of depression and suicidal ideation.

This research was conducted using Google Forms, which meant that some questionnaires were incomplete. In addition, this study did not count with the full participation of patients who attended psychological consultation.

Universities should generate programs for early detection of risk factors and prevention of depression in students, which could affect academic performance, school dropout, interpersonal relationships and trigger suicidal ideation. These results can also be applied to reducing family violence, which has increased since the pandemic, by improving students' family dynamics.

Because of the scarce research on this topic in Latin America, this study contributes to mental health in this population. The university becomes a fundamental scenario in which the ability to help students develop an adequate expression of emotions, positive coping strategies and sense of life as protective factors against depression can be enhanced.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

In the construction industry, an under researched area of study is how main contractor (MC) sub-contract design responsibilities to sub-contractor (SC). This lack of knowledge is particularly serious in the context of delivery methods such as design and construct where design responsibilities are pushed down the supply chain. In this study, it is aimed to explore which level of design responsibility MCs sub-contract to SCs, for what reasons, and what the impact of sub-contracting decisions is on projects.

A qualitative in-depth multiple case study was conducted. Six sub-contracting cases were examined in two civil engineering projects. In each project, the MCs sub-contracted pre-fabricated beams, reinforcement and railing to SCs. Data collection included document analysis and interviews. A within-case and cross-case analysis was conducted to examine emerging empirical patterns. These patterns were used to elaborate theory and develop propositions.

MCs sub-contracted design responsibilities to SCs as suggested by literature. However, despite that sub-contracting was in keeping with literature, several problems were reported in the cases where MCs involved SCs no earlier than in the construction stage. This is not to be expected according to theory.

This study adds value to the sub-contracting field as it provides new insights in relationships between the level of design responsibilities sub-contracted and the impact of that on projects. The study also revealed new factors such as building information modelling (BIM) interoperability that should get more attention in sub-contracting.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

This paper aims to propose an enhanced densely dehazing network to suit railway scenes’ features and improve the visual quality degraded by haze and fog.

It is an end-to-end network based on DenseNet. The authors design enhanced dense blocks and fuse them in a pyramid pooling module for visual data’s local and global features. Multiple ablation studies have been conducted to show the effects of each module proposed in this paper.

The authors have compared dehazed results on real hazy images and railway hazy images of state-of-the-art dehazing networks with the dehazed results in data quality. Finally, an object-detection test is taken to judge the edge information preservation after haze removal. All results demonstrate that the proposed dehazing network performs better under railway scenes in detail.

This study provides a new method for image enhancing in the railway monitoring system.

Additive manufacturing (AM) technologies, also known as three-dimensional printing (3DP), is a technological breakthrough that have the potential to disrupt the traditional operations of supply chains. They open the way to a supply chains innovation that can significantly benefit hospitals and health-related organizations in dealing with crises or unexpected events in a faster and more flexible way. In this study the authors identify the boundary of this potential support.

The authors adopt a case study approach to understand the dynamics behind a well-known best practice to identify the main opportunities and the main pitfalls that AM may pose to health-related organizations wanting to leverage them.

The case highlights that it is possible to increase hospital flexibility using AM and that by leveraging the Internet it is possible to spread the benefits faster than what it would be normally possible using traditional supply chain processes. At the same time the case highlights that leveraging these technologies needs buy-in from all the relevant stakeholders.

The paper is one of the first, to the best of the authors' knowledge, to highlight the main opportunities and difficulties of implementing 3DP technologies in hospital supply chain management.