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The purpose of this paper is to investigate electronic benefits transfer (EBT) card reforms in California’s Food Stamp Program, and its impact on food insecurity.

The authors test the hypothesis that EBT cards reduce food insecurity by reducing the food costs associated with loss and theft of benefits, as well as by decreasing fraudulent sales of benefits. The authors use a natural experiment in the form of the time-varying roll-out of EBT card reforms across California counties in conjunction with the California Health Interview Survey, to conduct an event study.

The findings suggest no evidence for a decrease in food insecurity. The authors do, however, find evidence of a transitory increase in food insecurity immediately following implementation of EBT reforms. Reforms increase the likelihood of food insecurity by about 3 percent for up to two months. The result is distinguishable from zero, and robust to changes in specification, inclusion of controls, and measurement choices. The authors posit the increase was due to frictions in the transition to EBT card systems.

Although a considerable literature with regard to the FSP exists, very little has been written investigating a specific linkage between EBT cards and food security. The findings are not supportive of policy makers’ hypothesis that a positive externality of EBT benefits delivery is a lasting reduction in food insecurity.

Specific types of Hispanic-owned banks (HOBs), including those related to Brazilian, Cuban, Mexican or Puerto Rican heritage, have not be analyzed to date. There are important differences between the relevant communities, including geographic location, language barriers, population size and the importance of remittances to foreign nations. The analysis here sheds light on these differences.

HOBs with the Federal Deposit Insurance Corporation (FDIC)-designated minority-owned depository institution (MDI) designation are identified, along with bank ownership heritage. Financial data, a measure of market competition, and demographics of depositors from 2003 to 2017 are utilized in an exploratory analysis comparing banks by HOB type, with random effects regressions for the pre-collapse (2003–2006) and post-collapse (2009–2017) periods.

Although each of the four types of HOBs serve Hispanic and poor communities, there are substantial differences. For example, Brazilian and Puerto Rican banks on the island held high levels of nonperforming loans (NPLs) post-collapse, with the Brazilian and Mexican banks expanding levels of risky commercial real estate (CRE) lending post-collapse, while the Cuban banks contracted CRE lending. Differences in terms of return on assets (ROAs), the cost of borrowed funds and the tier-1 risk-based capital ratio are also identified.

HOBs, like Latinos in the USA, are culturally heterogeneous and likely operate in different ways depending upon the culture and economic circumstances of the communities where they operate.

Although there is substantial research on MDIs, this is the first analysis which treats HOBs as culturally heterogeneous. Further research of this type is warranted.

The practice of facility management (FM) has been evolving with the rapid development of pervasive sensing technologies (PSTs) such as sensors, automatic identification (auto-ID), laser scanning and photogrammetry. Despite the proliferation of research on the use of PSTs for FM, a comprehensive review of such research is missing from the literature. This study aims to cover the knowledge void by examining the status quo and challenges of the selected PSTs with a focus on FM.

This paper reviewed 204 journal papers recounting cases of using PSTs for FM. The reviewed papers were extracted from Elsevier Scopus database using the advanced search.

Findings of this study revealed that PSTs and FM applications form a many-to-many mapping, i.e. one PST could facilitate many FM applications, and one application can also be supported by various PSTs. It is also found that energy modeling and management is the most referred purpose in FM to adopt PSTs, while space management, albeit important, received the least attention. Five challenges are identified, which include high investment on PSTs, data storage problem, absence of proper data exchange protocols for data interoperability, a lack of mature data processing methods for data utilization and privacy of users.

This paper paints a full picture of PSTs adoption for FM. It pinpoints the promising explorations for tackling the key challenges to future development.

The purpose of this paper is to make an overview of 474 publications and 512 patents of FTL from 1987 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of FTL for interested researchers.

Firstly, the FTL algorithms are classified and its functions are introduced in detail. Secondly, the structures of the publications are analyzed in terms of the fundamental information and the publication of the most productive countries/regions, institutions and authors. After that, co-citation networks of institutions, authors and papers illustrated by VOS Viewer are given to show the relationship among those and the most influential of them is further analyzed. Then, the characteristics of the patent are analyzed based on the basic information and classification of the patent and the most productive inventors. In order to obtain research hotspots and trends in this field, the time-line review and citation burst detection of keywords carried out by Cite Space are made to be visual. Finally, based on the above analysis, it draws some other important conclusions and the development trend of this field.

The research on FTL algorithm is still the top priority in the future, and how to improve the performance of SSD in the era of big data is one of the research hotspots.

This paper makes a comprehensive analysis of FTL with the method of bibliometrics, and it is valuable for researchers can quickly grasp the hotspots in this area.

This article draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to inspire new ideas for researchers.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

Network coverage is crucial for the adoption of advanced Smart Home applications. The commonly used log-based path loss model is not able to accurately estimate WiFi signal strength in different houses, as it does not fully consider the impact of building morphology. To better describe the propagation of WiFi signals and achieve higher estimation accuracy, this paper studies the basic building morphology characteristics of houses.

A new path loss model based on a decision tree was proposed after measuring the WiFi signal strength passing through multiple housing units. Three types of regression models were tested and compared.

The findings demonstrate that the log-based path loss model fits small houses well, while the newly proposed nonlinear path loss model performs better in large houses (area larger than 125 m2 and area-to-perimeter ratio larger than 2.5). The impact of building design on path loss has been proven and specifically quantified in the model.

Proposed an improved model to estimate indoor network coverage. Quantify the impacts of building morphology on indoor WiFi signal strength. Improve WiFi signal strength estimation to support Smart Home applications.