Mapping the Intercounty Transmission Risk of COVID-19 in New York State

Social Science Research Network published a piece over COVID-19 and includes three UT Affiliates that is published on May 1, 2020.Office of the VP for Researc

Rapid and simultaneous detection of human hepatitis B virus and hepatitis C virus antibodies based on a protein chip assay using nano-gold immunological amplification and silver staining method

BACKGROUND: Viral hepatitis due to hepatitis B virus and hepatitis C virus are major public health problems all over the world. Traditional detection methods including polymerase chain reaction (PCR)-based assays and enzyme-linked immunosorbent assays (ELISA) are expensive and time-consuming. In our assay, a protein chip assay using Nano-gold Immunological Amplification and Silver Staining (NIASS) method was applied to detect HBV and HCV antibodies rapidly and simultaneously. METHODS: Chemically modified glass slides were used as solid supports (named chip), on which several antigens, including HBsAg, HBeAg, HBcAg and HCVAg (a mixture of NS3, NS5 and core antigens) were immobilized respectively. Colloidal nano-gold labelled staphylococcal protein A (SPA) was used as an indicator and immunogold silver staining enhancement technique was applied to amplify the detection signals, producing black image on array spots, which were visible with naked eyes. To determine the detection limit of the protein chip assay, a set of model arrays in which human IgG was spotted were structured and the model arrays were incubated with different concentrations of anti-IgG. A total of 305 serum samples previously characterized with commercial ELISA were divided into 4 groups and tested in this assay. RESULTS: We prepared mono-dispersed, spherical nano-gold particles with an average diameter of 15 ± 2 nm. Colloidal nano-gold-SPA particles observed by TEM were well-distributed, maintaining uniform and stable. The optimum silver enhancement time ranged from 8 to 12 minutes. In our assay, the protein chips could detect serum antibodies against HBsAg, HBeAg, HBcAg and HCVAg with the absence of the cross reaction. In the model arrays, the anti-IgG as low as 3 ng/ml could be detected. The data for comparing the protein chip assay with ELISA indicated that no distinct difference (P > 0.05) existed between the results determined by our assay and ELISA respectively. CONCLUSION: Results showed that our assay can be applied with serology for the detection of HBV and HCV antibodies rapidly and simultaneously in clinical detection

Relationship between Socio-Demographics and COVID-19: A Case Study in Three Texas Regions

This is an article published from SSRN that was in the Good Systems Network Digest in June 2020.Office of the VP for Researc

The impact of peer-to-peer ridesharing on travel mode: Empirical study of Uber effects on travel mode in Seattle

Thesis (Master's)--University of Washington, 2018Peer-to-peer ridesharing, as a new travel mode, could be a potential solution to two major transportation issues: congestion and air pollution by reducing inefficient driving and promoting public transit ridership. Uber, as one of the leader transport network company, launched in San Francisco in 2010 and expanded around the world. This new travel mode could affect transportation situation, however, its impact is still not clear. The results from this study are based on current research to test the impact of this new travel mode in Seattle through the difference-in-differences analysis. This thesis could help policymakers to forecast the future transportation demand by estimating the commuters of different commute mode choice within the effects of this new travel option on commuting. According to past studies, peer-to-peer ridesharing could reduce driving alone demand but its impact on public transit is not clear. This thesis analyzes the impacts of peer-to-peer ridesharing on driving alone and public transit to commuting controlling for socio-demographic factors. In addition, it studies the different impact of peer-to-peer ridesharing within the different socio-demographic factors through Cluster analysis. This thesis collects 143 census tract data of Seattle from 2010-2016 as the study sample. Through the difference-in-differences analysis and the dynamic coefficient robustness test, this thesis measures the impacts of peer-to-peer ridesharing in Seattle. Then, this thesis divides 143 census tracts into three clusters through the K-mean Cluster analysis and studies the different impact of peer-to-peer ridesharing on commute mode across these clusters

Is the relationship between bus and light rail transit a competition substitution or a congestion substitution? An empirical study in Seattle

Public transit in Seattle has achieved success, with increases in transit ridership during these years, while most U.S. cities face a decline in transit ridership. It is worth learning the experience from Seattle\u27s transit success, but the causes remain unclear. This study hypothetically attributes this success to a good cooperation between public transit modes and uses quantile regressions to prove this hypothesis. Based on a bus stop ridership of 2988 in 2017, results indicate that the differences between bus stops within light rail transit catchments and outside catchments are significant and prove the relationship as the substitution of light rail transit for bus services. We further identify the situations when substitution happens and find it only happens in areas with high bus ridership, as congestion substitution. Besides, bus rapid ride lines and land-use factors are significantly associated with bus ridership. Conclusively, our study proves that the good cooperation between light-rail transit and bus service and transferring facilities could be a success story in the Seattle public transit service. This study can contribute to policymakers allocating public transit budgets wisely and suggest that a good cooperation between public transit modes can be a potent way to promote public transit ridership

Are There Transit Deserts in Europe? A Study Focusing on Four European Cases through Publicly Available Data

Public transit has been proven as an affordable travel method, while the inequitable distribution is a rising concern among practitioners and researchers. A transit desert, based on the demand and supply concept in measuring the mismatch in allocating the level of public transit service, has proved its ability to be applied in cases across countries. According to this concept, this study investigated transit deserts in four cases in Europe. Results indicate that the public transit system in Grand Paris and Madrid are superior due to a smaller population living in areas where public transit cannot meet the demand. Moreover, we noticed that the spatial distributions of transit deserts were significantly different, and the public transit accessibility of green spaces in Greater London and Madrid requires attention. These findings prove the potentials of the transit desert concept in generally evaluating and comparing the performance of different regional public transit systems which can guide the public transit investments by regional/cross-national agencies

What Are the Relationships between Public Transit and Gentrification Progress? An Empirical Study in the New York–Northern New Jersey–Long Island Areas

Transit-oriented development has been a widely accepted tool among transportation planning practitioners; however, there are concerns about the risk of increasing residential property values leading to gentrification or displacements. Therefore, it is critical to provide precise investigations of the relationships between public transit and gentrification. Although numerous studies have explored this topic, few have discussed these relationships based on detailed measurements of gentrification from a regional perspective. This study aims to fill the research gap by measuring the gentrification subcategories through a hierarchical definition based on data in the New York–Northern New Jersey–Long Island areas and applying the transit desert concept as the measurement of transit services. Through multinomial logistic regression and machine-learning approaches, findings indicate that the rate of transit deserts in economically disadvantaged neighborhoods is higher than the others. In addition, the impacts of transit services are significant in gentrification but insignificant in super-gentrification. These findings can advance the knowledge of the role of the transit service in different gentrification progresses. Based on these findings, policymakers need to be careful when allocating public transit budgets and note the effects of these investments on neighborhoods with different socioeconomic statuses

TOPSIS-based entropy measure for intuitionistic trapezoidal fuzzy sets and application to multi-attribute decision making

As an extension of intuitionistic fuzzy numbers, intuitionistic trapezoidal fuzzy numbers (ITrFNs) are useful in expressing complex fuzzy information with an 'interval value'. This study focuses on multi-attribute decision-making (MADM) problems with unknown attribute weights under an ITrFN environment. We initially present an entropy measure for ITrFNs by using the relative closeness of technique for order preference by similarity to an ideal solution. From the view of the reliability and certainty of decision data, we present an approach to determine the attribute weights. Subsequently, a new method to solve intuitionistic trapezoidal fuzzy MADM problems with unknown attribute weight information is proposed. A numerical example is provided to verify the practicality and effectiveness of the proposed method

Power-Efficient Response Time Guarantees for Virtualized Enterprise Servers

Both power and performance are important concerns for enterprise data centers. While various management strategies have been developed to effectively reduce server power consumption by transitioning hardware components to lower-power states, they cannot be directly applied to today’s data centers that rely on virtualization technologies. Virtual machines running on the same physical server are correlated, because the state transition of any hardware component will affect the application performance of all the virtual machines. As a result, reducing power solely based on the performance level of one virtual machine may cause another to violate its performance specification. This paper proposes a two-layer control architecture based on well-established control theory. The primary control loop adopts a multi-input-multi-output control approach to maintain load balancing among all virtual machines so that they can have approximately the same performance level relative to their allowed peak values. The secondary performance control loop then manipulates CPU frequency for power efficiency based on the uniform performance level achieved by the primary loop. Empirical results demonstrate that our control solution can effectively reduce server power consumption while achieving required application-level performance for virtualized enterprise servers