Housing Choice Voucher Program;Patterns and Factors of Spatial Concentration in Cleveland

Housing Choice Voucher Program is the single largest housing subsidy program in the USA with the goal of poverty deconcentration and race desegregation. This study aims to identify the presence and locations of voucher holders\u27 spatial concentration, and to investigate the factors associated with the location outcomes of voucher recipients in Cleveland from 2005 to 2009. Analyzing voucher recipients\u27 information from Cuyahoga Metropolitan Housing Authority, this dissertation found meaningful results for the voucher program performances. Hotspot analysis indicated that location patterns of voucher recipients do not show even distribution over the study area. Additionally, voucher holders have clustered together and their concentrations have changed during the five years. Voucher recipients were highly concentrated in the east part of Cuyahoga County, and over time, concentration patterns spread out from the central city to suburbs. Spatial concentrations were significantly different by race and ethnicity, but not by income. Regression analysis identified several factors associated with voucher recipients\u27 concentration, which include race, availability of affordable housing, poverty rates, vacancy rates, and accessibility to public transportation. The spatial error model estimation and Geographically Weighted Regression (GWR) account for spatial autocorrelation and spatial heterogeneity. The GWR model substantially improved the explanatory power compared to the OLS and spatial models, and revealed spatial variation of estimated coefficients. Factors showing a spatial non-stationarity were confirmed by Monte Carlo tests. Results from the dissertation presented the limited potential of the voucher program since voucher holders are still clustered in specific neighborhoods, even though they tend to move in less poor neighborhoods over time. However, in terms of poverty deconcentration, the voucher program has been successful to disperse low-income households in suburbs. On the other hand, desegregating minority pop

Housing Choice Voucher Program;Patterns and Factors of Spatial Concentration in Cleveland

Housing Choice Voucher Program is the single largest housing subsidy program in the USA with the goal of poverty deconcentration and race desegregation. This study aims to identify the presence and locations of voucher holders\u27 spatial concentration, and to investigate the factors associated with the location outcomes of voucher recipients in Cleveland from 2005 to 2009. Analyzing voucher recipients\u27 information from Cuyahoga Metropolitan Housing Authority, this dissertation found meaningful results for the voucher program performances. Hotspot analysis indicated that location patterns of voucher recipients do not show even distribution over the study area. Additionally, voucher holders have clustered together and their concentrations have changed during the five years. Voucher recipients were highly concentrated in the east part of Cuyahoga County, and over time, concentration patterns spread out from the central city to suburbs. Spatial concentrations were significantly different by race and ethnicity, but not by income. Regression analysis identified several factors associated with voucher recipients\u27 concentration, which include race, availability of affordable housing, poverty rates, vacancy rates, and accessibility to public transportation. The spatial error model estimation and Geographically Weighted Regression (GWR) account for spatial autocorrelation and spatial heterogeneity. The GWR model substantially improved the explanatory power compared to the OLS and spatial models, and revealed spatial variation of estimated coefficients. Factors showing a spatial non-stationarity were confirmed by Monte Carlo tests. Results from the dissertation presented the limited potential of the voucher program since voucher holders are still clustered in specific neighborhoods, even though they tend to move in less poor neighborhoods over time. However, in terms of poverty deconcentration, the voucher program has been successful to disperse low-income households in suburbs. On the other hand, desegregating minority pop

Housing policy

노트 : The full name of PKPP series is A Primer on Korea Planning and Policy

Effect of trehalose and trehalose transport on the tolerance of clostridium perfringens to environmental stress in a wild type strain and its fluoroquinolone-resistant mutant

Trehalose has been shown to protect bacterial cells from environmental stress. Its uptake and osmoprotective effect in Clostridium perfringens were investigated by comparing wild type C. perfringens ATCC 13124 with a fluoroquinolone- (gatifloxacin-) resistant mutant. In a chemically defined medium, trehalose and sucrose supported the growth of the wild type but not that of the mutant. Microarray data and qRT-PCR showed that putative genes for the phosphorylation and transport of sucrose and trehalose (via phosphoenolpyruvate-dependent phosphotransferase systems, PTS) and some regulatory genes were downregulated in the mutant. The wild type had greater tolerance than the mutant to salts and low pH; trehalose and sucrose further enhanced the osmotolerance of the wild type to NaCl. Expression of the trehalose-specific PTS was lower in the fluoroquinolone-resistant mutant. Protection of C. perfringens from environmental stress could therefore be correlated with the ability to take up trehalose

Effects of Bile Acids and Nisin on the Production of Enterotoxin by Clostridium perfringens

Clostridium perfringens is the second most common cause of bacterial foodborne illness in the United States, with nearly a million cases each year. C. perfringens enterotoxin (CPE), produced during sporulation, damages intestinal epithelial cells by pore formation, which results in watery diarrhea. The effects of low concentrations of nisin and bile acids on sporulation and toxin production were investigated in C. perfringens SM101, which carries an enterotoxin gene on the chromosome, in a nutrient-rich medium. Bile acids and nisin increased production of enterotoxin in cultures; bile acids had the highest effect. Both compounds stimulated the transcription of enterotoxin and sporulation-related genes and production of spores during the early growth phase. They also delayed spore outgrowth and nisin was more inhibitory. Bile acids and nisin enhanced enterotoxin production in some but not all other C. perfringens isolates tested. Low concentrations of bile acids and nisin may act as a stress signal for the initiation of sporulation and the early transcription of sporulation-related genes in some strains of C. perfringens, which may result in increased strain-specific production of enterotoxin in those strains. This is the first report showing that nisin and bile acids stimulated the transcription of enterotoxin and sporulation-related genes in a nutrient-rich bacterial culture medium

Cinchonine Prevents High-Fat-Diet-Induced Obesity through Downregulation of Adipogenesis and Adipose Inflammation

Cinchonine (C19H22N2O) is a natural compound of Cinchona bark. Although cinchonine's antiplatelet effect has been reported in the previous study, antiobesity effect of cinchonine has never been studied. The main objective of this study was to investigate whether cinchonine reduces high-fat-diet- (HFD-) induced adipogenesis and inflammation in the epididymal fat tissues of mice and to explore the underlying mechanisms involved in these reductions. HFD-fed mice treated with 0.05% dietary cinchonine for 10 weeks had reduced body weight gain (−38%), visceral fat-pad weights (−26%), and plasma levels of triglyceride, free fatty acids, total cholesterol, and glucose compared with mice fed with the HFD. Moreover, cinchonine significantly reversed HFD-induced downregulations of WNT10b and galanin-mediated signaling molecules and key adipogenic genes in the epididymal adipose tissues of mice. Cinchonine also attenuated the HFD-induced upregulation of proinflammatory cytokines by inhibiting toll-like-receptor-2- (TLR2-) and TLR4-mediated signaling cascades in the adipose tissue of mice. Our findings suggest that dietary cinchonine with its effects on adipogenesis and inflammation may have a potential benefit in preventing obesity

Hierarchical Joint Graph Learning and Multivariate Time Series Forecasting

Multivariate time series is prevalent in many scientific and industrial domains. Modeling multivariate signals is challenging due to their long-range temporal dependencies and intricate interactions--both direct and indirect. To confront these complexities, we introduce a method of representing multivariate signals as nodes in a graph with edges indicating interdependency between them. Specifically, we leverage graph neural networks (GNN) and attention mechanisms to efficiently learn the underlying relationships within the time series data. Moreover, we suggest employing hierarchical signal decompositions running over the graphs to capture multiple spatial dependencies. The effectiveness of our proposed model is evaluated across various real-world benchmark datasets designed for long-term forecasting tasks. The results consistently showcase the superiority of our model, achieving an average 23\% reduction in mean squared error (MSE) compared to existing models.Comment: Temporal Graph Learning Workshop @ NeurIPS 2023, New Orleans, United State

FlowQoS: Per-Flow Quality of Service for Broadband Access Networks

Research areas: Computer NetworksIn broadband access networks, one application may compete for the bandwidth of other applications, thus degrading overall performance. One solution to this problem is to allocate bandwidth to competing flows based on the application type at the gateway of the home network. Unfortunately, application-based quality of service (QoS) on a home network gateway faces significant constraints, as commodity home routers are not typically powerful enough to perform application classification, and many home users are not savvy enough to configure QoS parameters. This paper describes FlowQoS, an SDN-based approach for application-based bandwidth allocation where users can allocate upstream and downstream bandwidths for different applications at a high level, offloading application identification to an SDN controller that dynamically installs traffic shaping rules for application flows. FlowQoS has two modules: a flow classifier and an SDNbased rate limiter. We design a custom DNS-based classifier to identify different applications that run over common web ports; a second classifier performs lightweight packet inspection to classify non-HTTP traffic flows. We implement FlowQoS on OpenWrt and demonstrate that it can improve the performance of both adaptive video streaming and VoIP in the presence of active competing traffic

Association between p53 Expression and Amount of Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer

Background Most triple-negative breast cancers (TNBCs) have a high histologic grade, are associated with high endoplasmic stress, and possess a high frequency of TP53 mutations. TP53 missense mutations lead to the production of mutant p53 protein and usually show high levels of p53 protein expression. Tumor-infiltrating lymphocytes (TILs) accumulate as part of the anti-tumor immune response and have a strong prognostic and predictive significance in TNBC. We aimed to elucidate the association between p53 expression and the amount of TILs in TNBC. Methods In 678 TNBC patients, we evaluated TIL levels and expression of endoplasmic stress molecules. Immunohistochemical examination of p53 protein expression was categorized into three groups: no, low, and high expression. Results No, low, and high p53 expression was identified in 44.1% (n = 299), 20.1% (n = 136), and 35.8% (n = 243) of patients, respectively. Patients with high p53 expression showed high histologic grade (p < .001), high TIL levels (p = .009), and high expression of endoplasmic reticulum stress-associated molecules (p-eIF2a, p = .013; XBP1, p = .007), compared to patients with low p53 expression. There was no significant difference in disease-free (p = .406) or overall survival rates (p = .444) among the three p53 expression groups. Conclusions High p53 expression is associated with increased expression of endoplasmic reticulum stress molecules and TIL influx