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The accuracy and reliability of upper limb motion assessment have received great attention in the field of rehabilitation. Grasping test is widely carried out for motion assessment, which requires patients to grasp objects and move them to target place. The traditional assessments test the upper limb motion ability by therapists, which mainly relies on experience and lacks quantitative indicators. This paper aims to propose a deep learning method based on the vision system of our upper limb rehabilitation robot to recognize the motion trajectory of rehabilitation target objects automatically and quantitatively assess the upper limb motion in the grasping test.

To begin with, an SRF network is designed to recognize rehabilitation target objects grasped in assessment tests. Moreover, the upper limb motion trajectory is calculated through the motion of objects’ central positions. After that, a GAE network is designed to analyze the motion trajectory which reflects the motion of upper limb. Finally, based on the upper limb rehabilitation exoskeleton platform, the upper limb motion assessment tests are carried out to show the accuracy of both object recognition of SRF network and motion assessment of GAE network. The results including object recognition, trajectory calculation and deviation assessment are given with details.

The performance of the proposed networks is validated by experiments that are developed on the upper limb rehabilitation robot. It is implemented by recognizing rehabilitation target objects, calculating the motion trajectory and grading the upper limb motion performance. It illustrates that the networks, including both object recognition and trajectory evaluation, can grade the upper limb motion functionn accurately, where the accuracy is above 95.0% in different grasping tests.

A novel assessment method of upper limb motion is proposed and verified. According to the experimental results, the accuracy can be remarkably enhanced, and the stability of the results can be improved, which provide more quantitative indicators for further application of upper limb motion assessment.

A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution.

A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI.

Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality.

This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

The purpose of this systematic literature review is to identify which soft skills are developed during work-based learning (WBL) programmes in higher education contexts. Additionally, the study sought to identify strategies used to promote soft skills development within work-based learning programmes.

The authors used the PRISMA-P protocol to guide the methodology and ensure the transparency and reproducibility of the paper. In total, 36 papers were considered eligible from the search conducted in two databases between 2013 and 2024.

Findings indicate that while there is some overlap in the soft skills mentioned, great variety exists due to the complexity of soft skills frameworks. The soft skills most frequently referenced were communication and teamwork skills. Regarding strategies, a few articles mention reflection and personal connections for enhancing soft skills development; however, further research is needed in this area.

A clearer understanding of skill development could significantly benefit higher education institutions, students and related organisations. This understanding may enhance programme quality and better prepare students for their future.

Although research on the development of soft skills in the context of WBL programmes is still limited, there is increasing evidence suggesting they may be an effective means of fostering these skills. This paper presents an overview of the research conducted to date and outlines potential avenues for further investigation.

This study aims to comprehensively explore households’ residential search process by examining various decision dimensions – search tenure, housing typology, search criteria, information sources, search extent and search duration – and identifying factors influencing each.

The study area includes Bidhannagar Municipal Corporation and Rajarhat Newtown. A retrospective survey was conducted with recently relocated households to investigate their search process. Based on a search process framework from literature, separate logit models were developed to analyse decision dimensions.

The study identifies the influence of household typology, size, income, car ownership, origin and education, including travel attitudes, relocation reasons and urgency on decision dimensions. Key findings indicate that households use five dominant search criteria to orient themselves spatially, also affecting the search extent. Moreover, some households enter the housing market without housing typology preferences, exploring all options.

Choice set development – a critical stage in residential location choice modelling – represents the outcome of household’s search process: the collection of potential locations considered before making a final selection. Traditionally, entire urban area is considered as choice set, but the study’s findings can inform screening rules to tailor choice set to household preferences.

To the best of the authors’ knowledge, this is the first study to comprehensively explore the housing search process in India, introducing novel factors like travel attitudes, relocation motivations and urgency. Instead of focusing on specific housing typologies, the authors investigate whether households enter the market with established preferences or not. The authors also examined search criteria households consider to define search space and its impact on search extent.

This study aims to identify the significant exit barriers encountered by tenants in public rental housing and analyze the moderating effects of sociodemographic factors on tenants’ decisions to leave public rental housing.

This study applied a quantitative methodology. Questionnaire survey was used as its main instrument for data collection. Responses were gathered from 328 tenants in the Program Perumahan Rakyat (PPR) through stratified random sampling. Data were analyzed using structural equation modeling partial least square (SEM-PLS).

The findings reveal that housing availability and the exit programs by DBKL are the most significant factors influencing exit barriers. Tenant income also impacts their decision to remain, as available housing often does not match their income levels. Policymakers and relevant agencies should collaborate to help tenants increase their income, facilitating their transition out of public rental housing.

This study is limited to the factors influencing the tenant from exiting PRH. Furthermore, the study specifically targeted those who rent public housing under DBKL administration may neglect the perspectives of other stakeholders, such as DBKL management, property owners and policymakers. Therefore, the findings are insufficient in representing tenants other than those under the DBKL’s administration. While the causes may be similar, the opinions and consequences would vary among other tenants depending on their socio-demographic profiles.

This research offers a more comprehensive understanding of the exit barriers tenants’ encounter in PRH. The results gained from this study will assist policymakers in developing a more comprehensive initiative that will assist tenants in exiting PRH. DBKL can effectively engage PRH tenants to provide a strategic departure mechanism for better solutions. Furthermore, DBKL can offer aid in locating cheap housing options for tenants who may have limited access to information on the availability of such homes.

This discovery will also be advantageous for prospective tenants who have been on the waiting list for several years, eagerly awaiting the vacancy of units previously occupied by other tenants. Furthermore, residents who successfully vacate public rental housing (PRH) will need to be considered for incentives to promote the success of the housing pathway. This will lead to the attainment of the equitable allocation that has been identified as the primary concern of PRH.

This study seeks to clarify the exit barriers encountered by tenants in PRH and identifies the significant factors contributing to the low turnover rate of tenants. The study is relevant for DBKL and policymakers in promoting the success of housing pathways to ensure fairness and efficiency in the principles of public housing.