Manufactured Housing Appreciation: Stereotypes and Data

Consumers Union assessed the financial appreciation of manufactured- housing units, by examining the relative appreciation rates of manufactured housing and site-built housing, as well as the factors affecting the appreciation rate of manufactured housing. Our analysis includes an extensive literature review of previous work in the field, as well as primary research using data from the 1985–1999 American Housing Survey Panel and county appraisal data from several counties in Texas. The stereotypes of manufactured housing are built upon very real differences in appreciation experienced by the people who own them. The large proportion of manufactured homes in rental parks contributes greatly to the lower appreciation experienced by manufactured home owners as a whole, as land ownership is an important driver of appreciation. High variation in the individual appreciation rates of manufactured homes also causes a higher proportion of manufactured homes, even packaged with land, to lose value over time. Even so, average appreciation rates of manufactured homes packaged with owned land are statistically in line with the site built market, and there are few inherent reasons that a home built in a factory should perform differently than one built on site. Our analysis suggests that consumers can make decisions which can improve the appreciation of a manufactured home. Land ownership, location, purchase price and maintenance expenditures are among the factors that predict appreciation, and should be considered when attempting to increase appreciation in a particular unit.manufactured housing mobile home appreciation

Manipulated, Misled, Ignored, Abused: Residential Consumer Experience with Electric Deregulation in the United Kingdom

The United Kingdom began deregulating its electric market years before the U.S. Thus, the UK provides the best example of what can be expected in the deregulated residential retail electric market in the United States. . An extensive review of the evidence found: Questionable price savings: Large drops in wholesale market prices were not fully passed on to residential consumers in the deregulated marketplace. Increase in complaints: The volume of complaints about energy companies jumped after deregulation, and new types of complaints such as unauthorized switching of service (“slamming”) arose. Failure of Competition to Develop: Rather than compete for new customers, companies are relying on customer inertia to keep their existing customer base. Higher prices for low- income consumers: Since deregulation begain in 1990, there has been a marked increase in the use of prepayment meters, resulting in low-income customers paying more for their electricity. These findings lead us to recommend against implementing plans to replace traditional regulation with “retail competition” for consumers. Where a state or country has already enacted such a plan, it should be prepared to address and remedy each of the problems identified above.Electricity Markets, Deregulation, United Kingdom, Energy Markets, privitization, privitisation, low-income consumers

The Poverty Concentration Implications of Housing Subsidies: A Cellular Automata Thought Experiment

Looking at data from HUD’s low income housing tax credit database from 1987 to 2001, we examine how the US tax credit program has concentrated poverty in neighborhoods by offering advantages to developing low income housing projects in low income census tracts. We then use a simple Cellular Automata model to explore how alternative programs structures could impact economic diversity and poverty concentration. This model suggests that many widely dispersed fixed location affordable housing projects increase local economic diversity over alternative housing allocation rules. If policymakers wish align the Low Income Housing Tax Credit program with the goal of promoting economic diversity in our neighborhoods, they should restructure the bonus to reward to projects in areas without a concentration of subsidized housing.low income housing tax credit; Residential Location; Simulation; segregation; cellular automata

Psychosocial Interventions for Emergent Adults With Type 1 Diabetes: Near-Empty Systematic Review and Exploratory Meta-Analysis

Risk for developing mental health concerns is increased for people with diabetes. Coupled with stressors related to the transition from adolescence to adulthood, emergent adults may be in greater need of psychosocial interventions to help them cope. This review summarizes the literature on interventions used with people with diabetes aged 15–30 years on psychosocial and biological (A1C) outcomes. Core databases were searched for both published and grey research. Studies completed between January 1985 and October 2018 using any psychosocial intervention and meeting age and diabetes type requirements were selected if they included a control or comparison group and findings reported in such a way that effect size was calculable. Two authors independently extracted relevant data using standard data extraction templates. Six studies with 450 participants met the broad inclusion criteria. Sample-weighted pooling of 12 outcomes, six each on glycemic control and psychosocial status, suggested the preventive potential (d = 0.31, 95% CI 0.17–0.45) and homogeneity (χ2 [11] = 11.15, P = 0.43) of studied interventions. This preliminary meta-analysis provides some suggestion that psychosocial interventions, including telephone-based case management, individualized treatment modules, and small-group counseling interventions, may diminish burden, depression, and anxiety and enhance glycemic control among emerging adults with type 1 diabetes as they transition from adolescence to adulthood

Measuring Air Quality for Advocacy in Africa (MA3): Feasibility and Practicality of Longitudinal Ambient PM2.5 Measurement Using Low-Cost Sensors.

Ambient air pollution in urban cities in sub-Saharan Africa (SSA) is an important public health problem with models and limited monitoring data indicating high concentrations of pollutants such as fine particulate matter (PM2.5). On most global air quality index maps, however, information about ambient pollution from SSA is scarce. We evaluated the feasibility and practicality of longitudinal measurements of ambient PM2.5 using low-cost air quality sensors (Purple Air-II-SD) across thirteen locations in seven countries in SSA. Devices were used to gather data over a 30-day period with the aim of assessing the efficiency of its data recovery rate and identifying challenges experienced by users in each location. The median data recovery rate was 94% (range: 72% to 100%). The mean 24 h concentration measured across all sites was 38 µg/m3 with the highest PM2.5 period average concentration of 91 µg/m3 measured in Kampala, Uganda and lowest concentrations of 15 µg/m3 measured in Faraja, The Gambia. Kampala in Uganda and Nnewi in Nigeria recorded the longest periods with concentrations >250µg/m3. Power outages, SD memory card issues, internet connectivity problems and device safety concerns were important challenges experienced when using Purple Air-II-SD sensors. Despite some operational challenges, this study demonstrated that it is reasonably practicable and feasible to establish a network of low-cost devices to provide data on local PM2.5 concentrations in SSA countries. Such data are crucially needed to raise public, societal and policymaker awareness about air pollution across SSA

Testing SOAR Tools in Use

Modern security operation centers (SOCs) rely on operators and a tapestry of logging and alerting tools with large scale collection and query abilities. SOC investigations are tedious as they rely on manual efforts to query diverse data sources, overlay related logs, and correlate the data into information and then document results in a ticketing system. Security orchestration, automation, and response (SOAR) tools are a new technology that promise to collect, filter, and display needed data; automate common tasks that require SOC analysts' time; facilitate SOC collaboration; and, improve both efficiency and consistency of SOCs. SOAR tools have never been tested in practice to evaluate their effect and understand them in use. In this paper, we design and administer the first hands-on user study of SOAR tools, involving 24 participants and 6 commercial SOAR tools. Our contributions include the experimental design, itemizing six characteristics of SOAR tools and a methodology for testing them. We describe configuration of the test environment in a cyber range, including network, user, and threat emulation; a full SOC tool suite; and creation of artifacts allowing multiple representative investigation scenarios to permit testing. We present the first research results on SOAR tools. We found that SOAR configuration is critical, as it involves creative design for data display and automation. We found that SOAR tools increased efficiency and reduced context switching during investigations, although ticket accuracy and completeness (indicating investigation quality) decreased with SOAR use. Our findings indicated that user preferences are slightly negatively correlated with their performance with the tool; overautomation was a concern of senior analysts, and SOAR tools that balanced automation with assisting a user to make decisions were preferred

The Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP): Enabling Open Science for the Global Aboveground Terrestrial Carbon Dynamics Research Community

No abstract availabl

AI ATAC 1: An Evaluation of Prominent Commercial Malware Detectors

This work presents an evaluation of six prominent commercial endpoint malware detectors, a network malware detector, and a file-conviction algorithm from a cyber technology vendor. The evaluation was administered as the first of the Artificial Intelligence Applications to Autonomous Cybersecurity (AI ATAC) prize challenges, funded by / completed in service of the US Navy. The experiment employed 100K files (50/50% benign/malicious) with a stratified distribution of file types, including ~1K zero-day program executables (increasing experiment size two orders of magnitude over previous work). We present an evaluation process of delivering a file to a fresh virtual machine donning the detection technology, waiting 90s to allow static detection, then executing the file and waiting another period for dynamic detection; this allows greater fidelity in the observational data than previous experiments, in particular, resource and time-to-detection statistics. To execute all 800K trials (100K files $\times$ 8 tools), a software framework is designed to choreographed the experiment into a completely automated, time-synced, and reproducible workflow with substantial parallelization. A cost-benefit model was configured to integrate the tools' recall, precision, time to detection, and resource requirements into a single comparable quantity by simulating costs of use. This provides a ranking methodology for cyber competitions and a lens through which to reason about the varied statistical viewpoints of the results. These statistical and cost-model results provide insights on state of commercial malware detection

HMDB: the Human Metabolome Database

The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at