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Background: The gut microbiome is an important determinant of health and disease in preterm infants. Objectives: The objective of this article was to share our current protocol for other neonatal intensive care units to potentially expand their existing protocols, aiming to characterize the relationship between the intestinal microbiome and health outcomes in preterm infants. Methods : This prospective, longitudinal study planned to recruit 160 preterm infants born <32 weeks gestational age or weighing <1,500 g and admitted to one of two Level III/IV neonatal intensive care units. During the neonatal intensive care unit period, the primary measures included events of early life pain/stress, gut microbiome, host genetic variations, and neurobehavioral assessment. During follow-up visits, gut microbiome; pain sensitivity; and medical, growth, and developmental outcomes at 4, 8-12, and 18-24 months corrected age were measured. Discussion : As of February 14, 2020, 214 preterm infants have been recruited. We hypothesize that infants who experience greater levels of pain/stress will have altered gut microbiome, including potential adverse outcomes such as necrotizing enterocolitis and host genetic variations, feeding intolerance, and/or neurodevelopmental impairments. These will differ from the intestinal microbiome of preterm infants who do not develop these adverse outcomes. To test this hypothesis, we will determine how alterations in the intestinal microbiome affect the risk of developing necrotizing enterocolitis, feeding intolerance, and neurodevelopmental impairments in preterm infants. In addition, we will examine the interaction between the intestinal microbiome and host genetics in the regulation of intestinal health and neurodevelopmental outcomes. [ABSTRACT FROM AUTHOR]

Working waterfront space is limited, leading to competition for coastal space among different waterfront‐dependent industries as well as non‐waterfront dependent users. Coastal margins will be shrinking as sea levels rise due to climate change, squeezing already scarce port resources, exacerbating competition for these spaces, and generating conflicts. This paper focuses on the competition for waterfront space on the Thames River of Connecticut bordered by the municipalities of New London, Groton, Norwich, Ledyard, and Montville. Emerging wind power in the new Blue Economy looks to reshape port usage in the Thames River. The recent focus on wind generation by the State of Connecticut, coupled with several competitive bidding events for wind‐generated electricity, has augmented demand for port space that will serve as a staging area for this offshore development. Although the development of wind power will occur offshore, Connecticut ports are anticipating port use by wind companies with winning bids. This paper explores the processes by which port space has been (re)allocated and contested, and examines the nature of the ensuing conflicts and outcomes. [ABSTRACT FROM AUTHOR]

This paper describes a human-centered design approach to investigate unmet adolescent sexual health wants and needs among youth of color in low-income and rural communities in Texas, North Carolina, and Connecticut (n = 149). The approach involved gathering qualitative data through in-depth interviews and other human-centered design activities between April 2016 and August 2016. Data were analyzed using thematic content analysis after each round of data collection. Themes were triangulated across multiple data sources to identify key insights. Results highlighted several important unmet wants and needs. Participants shared that schools were not the preferred place to learn about sexual health and healthy relationships, due to uncomfortable and sometimes even hostile environments. When discussing the potential to use internet- and technology-based sexual health resources, participants expressed concerns over privacy, safety, and credibility of information available. Similarly, participants preferred mobile apps over websites due to the privacy of the experience. Most importantly, key emotions impacting adolescents' access to and use of sexual health resources were identified. Results indicated a preference for consuming story-based information in a text message format that described diverse experiences related to sexual health topics. Together, these findings led to the development of an innovative, mobile health intervention for adolescents, the Real Talk mobile app. This human-centered approach can support researchers and practitioners in strengthening intervention development efforts to improve the reach, adoption, and implementation of sexual health interventions. [ABSTRACT FROM AUTHOR]

Palliative care and medical-legal partnership are complementary disciplines dedicated to integrating care to treat the whole patient and intervening before a legal or medical issue is at a crisis point. In this paper, we discuss the founding and operations of the Yale Palliative Medical Legal Partnership, give examples of typical cases, explain special considerations in this area of law, and propose areas for further research. [ABSTRACT FROM AUTHOR]

Provides information on the British and American Art at Yale, a symposium held in Hew Haven in October 1995, with reference to a tribute paid to Jules David Prown, professor of art history and material culture at Yale University. Contributions made by Prown to the college; Information on the participants of the symposium; When Prown began teaching at Yale.

Presents an inventory on three volumes of the archives of Renaissance painter Giorgio Vasari at the Beinecke Rare Book and Manuscript Library at Yale University, New Haven, Connecticut. Highlights of the archives; Document on the work of Vasari on the decoration of the cupola of Florence Cathedral in Italy; Insights on account books in the archives.

Child protective services (CPS) case records contain a vast amount of narrative information that is underutilized for estimating risk, conceptualizing family needs, and planning for services. The current study applied a novel method for quantifying family-level severity of maltreatment and non-maltreatment-related adversity types to narrative information reflecting a family's full CPS history. Cases were randomly sampled (N = 100) from two regions of Connecticut that were referred over a specified 6-month period. De-identified data were extracted through comprehensive chart review of electronic and paper case records. The Yale-Vermont Adversity in Childhood Scale (Y-VACS; Holbrook et al., 2015) was used to quantify adversity severity across a range of intrafamilial and extrafamilial experiences. Several family-level adversity severity ratings were associated with administrative data on allegations and investigative outcomes. Poly-victimization (β =.47, p <.001) and poly-deprivation (β =.25, p =.005) significantly predicted total allegation types and total substantiation types (β =.30, p =.002; β =.26, p =.008, respectively) across the case history. Poly-victimization significantly predicted the presence of a new allegation within 12 months of the index report, OR = 1.72, SE =.25, p =.027. Findings support the feasibility of a novel method that uses narrative case record information to quantify severity of maltreatment and non-maltreatment-related adversity types, as well as cumulative measures of threat- and deprivation-based adversities at the family level. Implications for utilizing case record data to inform CPS intervention are discussed. [ABSTRACT FROM AUTHOR]

As the COVID-19 pandemic unfolds, every aspect of daily life is being altered in response to the virus. The pandemic has altered secondary education. Classes online, teachers struggling to learn Zoom and make lessons meaningful and relevant to students. Students struggling to make sense of this moment, struggling with mental health issues due to the loss of routine and in many cases contact with adult role models. Unfortunately, in times of crisis such as these some of the most disenfranchized people in society are completely overlooked and forgotten, such as refugees. However, if more teachers were to leverage the social studies potential of current events such as the Coronavirus, greater empathy would be felt for marginalized people more starkly impacted by the pandemic, leading ultimately to a heightened sense of civic engagement among the next generation. The purpose of this paper is to assist teachers in guiding their students through analyzing current events, such as COVID-19's impact on refugees, toward developing civic mindedness. In addition to this, the paper will discuss some of the broader societal impacts the virus is having within the United States, as well as ways in which this event may be viewed as a historical subject in the future. The paper will begin by building the content knowledge of high school social studies teachers through addressing the following question: "What is the difference between a refugee entering the United States now versus one year ago before the COVID-19 pandemic?" Following this, the authors will present an inquiry-based learning segment designed to teach the History correlated to the COVID-19 pandemic to a classroom of secondary education students. The inquiry template follows the standard C3 format utilized by the State of Connecticut. [ABSTRACT FROM AUTHOR]

Fostering collaboration and instilling core competencies across the diverse Infant Mental Health systems and understanding their training needs are crucial endeavors to support the delivery of evidence‐based care and treatment continuity for infants and their families. This paper details the Connecticut Association for Infant Mental Health's use of a comprehensive infant mental health training series as a vehicle to achieve these aims. The training series, and the steps taken to execute and evaluate it are described to provide a framework for future collaborative training initiatives. Evaluation efforts were designed to address knowledge sought and gained and included pre and posttraining tests, participant reports of their training goals and needs, and interviews with trainers regarding the series' strengths and limitations. Findings suggest significant improvements in participants' knowledge of training content across trainings. Participants indicated a desire for trainings on working with the whole family and their plan to integrate skills from the training into their work. Recommendations from trainers and evaluators are provided to spark future trainings and collaborative efforts. [ABSTRACT FROM AUTHOR]

The search for reliable tools to assess potential deleterious reactions in sulfide-bearing aggregates, is driven by recent field structure damage involving such types of aggregates. The paper presents a new test scheme with detailed procedures and limit criteria. Five aggregates, including pyrrhotite-bearing reactive ones (Connecticut and MSK 0.9), an alkali-silica reactive low-sulfur limestone (Spratt), a non-reactive control (PKA), and a low-sulfide aggregate (MSK 0.2), were used to manufacture concrete specimens that were subjected to the proposed test. The limit criterion, based on modulus of elasticity loss (RMoE), effectively distinguishes non-reactive, reactive, and potentially reactive aggregates. The scheme's reliability is validated against an existing protocol involving sulfur determination and mortar bar expansion testing. Four of five aggregates exhibit similar potential sulfide reactivity. Despite excessive mortar bar expansion, MSK 0.2, with traces of pyrrhotite, shows non-reactive behavior in concrete specimens after electrochemical treatment. The proposed test scheme offers a practical and timely tool for assessing sulfide-bearing aggregate reactivity before concrete production. [ABSTRACT FROM AUTHOR]

Background: Although Good Samaritan laws (GSLs) have been widely adopted throughout the United States, their efficacy in individual states is often unknown. This paper offers an approach for assessing the impact of GSLs and insight for policy-makers and public health officials who wish to know whether they should expect to see outcomes from similar policy interventions.Methods: Utilizing a system dynamics (SD) modeling approach, the research team conducted a policy evaluation to determine the impact of GSLs on opioid use disorder (OUD) in Connecticut and evaluated the GSL based upon the following health outcomes: (1) emergency department (ED) visits for overdose, (2) behavioral changes of bystanders, and (3) overdose deaths.Results: The simulation model suggests that Connecticut's GSL has not yet affected overdose deaths but has resulted in bystander behavioral changes, such as increased 911 calls for overdose. ED visits have increased as the number of opioid users has increased.Conclusions: The simulation results indicate that the number of opioid-related deaths will continue to increase and that the GSL alone cannot effectively control the crisis. However, the SD approach that was used will allow policymakers to evaluate the effectiveness of the GSL over time using a simulation framework. This SD model demonstrates great potential by producing simulations that allow policymakers to assess multiple strategies for combating the opioid crisis and select optimal public health interventions. [ABSTRACT FROM AUTHOR]

• Planning an effective network of fuel stations is a multi-scale location problem. • The method integrates operations research and GIS network analysis techniques. • Optimization models maximize coverage of local, metropolitan, and intercity trips. • GIS tool assesses accessibility of local street intersections from/to freeways. • Scenario planning approach converges on robust set of stations for Hartford CT, USA. Electric drive vehicles (plug-in electric vehicle or hydrogen fuel cell vehicles) have been promoted by governments to foster a more sustainable transportation future. Wider adoption of these vehicles, however, depends on the availability of a convenient and reliable refueling/recharging infrastructure. This paper introduces a path-based, multi-scale, scenario-planning modeling framework for locating a system of alternative-fuel stations. The approach builds on (1) the Flow Refueling Location Model (FRLM), which assumes that drivers stop along their origin-destination routes to refuel, and checks explicitly whether round trips can be completed without running out of fuel, and (2) the Freeway Traffic Capture Method (FTCM), which assesses the degree to which drivers can conveniently reach sites on the local street network near freeway intersections. This paper extends the FTCM to handle cases involving clusters of nearby freeway intersections, which is a limitation of its previous specification. Then, the cluster-based FTCM (CFTCM) is integrated with the FRLM and the DFRLM (FRLM with Deviations) to better conduct detailed geographic optimization of this multi-scale location planning problem. The main contribution of this research is the introduction of a framework that combines multi-scale planning methods to more effectively inform the early development stage of hydrogen refueling infrastructure planning. The proposed multi-scale modeling framework is applied to the Hartford, Connecticut region, which is one of the next areas targeted for fuel-cell vehicle (FCV) market and infrastructure expansion in the United States. This method is generalizable to other regions or other types of fast-fueling alternative fuel vehicles. [ABSTRACT FROM AUTHOR]

Demand response (DR) program empowers the dynamic prices to actively optimize the consumption. This optimized consumption plays a vital role in resolving the complex operation and reliability issues in the electricity market. The human behavior aspect of consumers explained by several models that have been reported in the literature. These models depend on the classical utility factor. The effect of price on the consumer's decision in the field of energy efficiency and reduction of consumption based on behavioral characteristics are two important aspects of DR programs. In absence of such characteristics, results become non‐viable. In this paper, the footprint of two time‐based DR programs is explored on the peak reduction namely; Real‐Time Pricing (RTP) and Peak Time Rebate (PTR). Artificial Neural Network (ANN) based topologies for two DR programs are proposed. The proposed topologies employ variation in demand and price, subsequently for simulating an online DR simulator. Demand before and after the RTP and PTR was calculated and compared with four ANN‐based DR topologies namely; Radial Basis Function Neural Network‐Demand Response (RBFN‐DR), Feedforward Backprop‐Demand Response (FFBP‐DR), Layer Recurrent‐Demand Response (LR‐DR), and Generalized Regression‐Demand Response (GR‐DR). The proposed models are tested on three test cases. The first case tested on hourly data of New England ISO of Connecticut on August 18, 2014, the second case tested on hourly data of the same system on August 18, 2020, and the third case tested on hourly residential data of test smart grid. By assessing the results from all three test cases, depicted that RBFN‐DR proved its efficacy by giving better results for both price‐based programs namely; RTP and PTR. [ABSTRACT FROM AUTHOR]

In this paper we propose a statistical modeling framework that contributes to advancing methods for modeling insurance policy premium in the actuarial literature. Specification of separate frequency and severity models, accounting for territorial risk and performing accurate inference, are some of the challenges an actuary faces while modeling policy premium. Policy premiums are characterized to follow a semi-continuous probability distribution, featuring a non-zero probability at zero along with a positive continuous support. Interpretability is a concern when quantifying unobserved risks premiums face from spatial variation. Commonly used strategies in the literature are known to successfully quantify this risk, but do not necessarily produce interpretable estimates. Resorting to frequency-severity models leaves the actuary indecisive about the specification of covariates and spatial effects. The novelty of our proposed approach lies in the development of a parsimonious and interpretable zero-adjusted modeling framework that allows for joint estimation of the effect of policy and individual characteristics on the mean premium and dispersion, while quantifying spatial variability in the mean model. The developed methods are applied to a database featuring premiums arising from the collision coverage in insurance policies for motor vehicles within the state of Connecticut, USA, for the year 2008. [ABSTRACT FROM AUTHOR]

To support public health policymakers in Connecticut, we developed a flexible county-structured compartmental SEIR-type model of SARS-CoV-2 transmission and COVID-19 disease progression. Our goals were to provide projections of infections, hospitalizations, and deaths, and estimates of important features of disease transmission and clinical progression. In this paper, we outline the model design, implementation and calibration, and describe how projections and estimates were used to meet the changing requirements of policymakers and officials in Connecticut from March 2020 to February 2021. The approach takes advantage of our unique access to Connecticut public health surveillance and hospital data and our direct connection to state officials and policymakers. We calibrated this model to data on deaths and hospitalizations and developed a novel measure of close interpersonal contact frequency to capture changes in transmission risk over time and used multiple local data sources to infer dynamics of time-varying model inputs. Estimated epidemiologic features of the COVID-19 epidemic in Connecticut include the effective reproduction number, cumulative incidence of infection, infection hospitalization and fatality ratios, and the case detection ratio. We conclude with a discussion of the limitations inherent in predicting uncertain epidemic trajectories and lessons learned from one year of providing COVID-19 projections in Connecticut. [ABSTRACT FROM AUTHOR]

Objective: To compare the efficacy of gentamicin and steroids in patients with Meniere's disease (MD). Methods: The study protocol was structured in accordance with the Population, Intervention, Comparison and Outcome (PICO) framework. We used "Endnote" (Thomson ResearchSoft; Stanford, Connecticut, the United States) to retrieve database documents. A systematic literature search of Web of Science and PubMed Database through May 2020 was conducted using specific search terms. Inclusion criteria, exclusion criteria, vertigo improvement, and exact hearing changes were defined. Review Manager 5.3 (Cochrane) was used for data analysis. Results: A total of 80 articles were searched from Web of Science and 23 articles were searched from PubMed database. After further reviewing the specific points of the inclusion criteria and exclusion criteria, 9 papers were finally selected. Intratympanic gentamicin (ITG) was superior to intratympanic steroid (ITS) in reducing the number of vertigo attacks (odds ratio (OR) 3.08, 95% confidence intervals (CI) [2.05–3.65]), probability (P) < 0.01). As for hearing improvement, we did the analysis twice. With all the studies included, the odds of hearing improvement (by "x") was 0.31 among patients receiving gentamicin compared to those treated by steroids (OR 0.31, 95% CI [0.16–0.61]). But after removing one study with outlying results from the analysis, this effect disappeared. Hearing loss of ITG and ITS was not statistically significant (P = 0.29). Conclusions: ITG is superior to ITS in reducing the number of vertigo attacks in the treatment of MD (P < 0.01); the impact on hearing is more heterogeneous in the studies. Overall, there was no clear difference between ITG and ITS on hearing improvement and on hearing loss. [ABSTRACT FROM AUTHOR]

• Using probe data, we estimated the traffic density information on limited access highways. • We used a mixed effect binomial model to link the odds of speeding to traffic density, roadway characteristics, and COVID-19 phases. • We analyzed and compared speeding in two U.S. states, Maine, and Connecticut. • We found that a better level of service such as A, or B (low density) results in higher odds of speeding. • We found that speeding substantially increased during COVID-19 stay-at-home orders and continued to happen even one year after the orders. Stay-at-home orders - imposed to prevent the spread of COVID-19 - drastically changed the way highways operate. Despite lower traffic volumes during these times, the rate of fatal and serious injury crashes increased significantly across the United States due to increased speeding on roads with less traffic congestion and lower levels of speed enforcement. This paper uses a mixed effect binomial regression model to investigate the impact of stay-at-home orders on odds of speeding on urban limited access highway segments in Maine and Connecticut. This paper also establishes a link between traffic density and the odds of speeding. For this purpose, hourly speed and volume probe data were collected on limited access highway segments for the U.S. states of Maine and Connecticut to estimate the traffic density. The traffic density was then combined with the roadway geometric characteristics, speed limit, as well as dummy variables denoting the time of the week, time of the day, COVID-19 phases (before, during and after stay-at-home order), and the interactions between them. Density, represented in the model as Level of Service, was found to be associated with the odds of speeding, with better levels of service such as A, or B (low density) resulting in the higher odds that drivers would speed. We also found that narrower shoulder width could result in lower odds of speeding. Furthermore, we found that during the stay-at-home order, the odds of speeding by more than 10, 15, and 20 mph increased respectively by 54%, 71% and 85% in Connecticut, and by 15%, 36%, and 65% in Maine during evening peak hours. Additionally, one year after the onset of the pandemic, during evening peak hours, the odds of speeding greater than 10, 15, and 20 mph were still 35%, 29%, and 19% greater in Connecticut and 35% 35% and 20% greater in Maine compared to before pandemic. [ABSTRACT FROM AUTHOR]

Provides information on school-based crisis intervention services for adolescents endorsed by the Committees on Adolescence and School Health of the American Academy of Pediatrics chapter in Connecticut. Requirements for the crisis intervention plan; Staff training and education; Liaisons with community resources; Need for follow-up services and services for related problems.

The article reports that for many years Laura Manuelidis, a neuropathologist from Yale University has been arguing that the Creutzfeldt-Jakob disease is caused by virus. A recent paper by Manuelidis at the National Academy of Sciences shows that the debate is not over. The paper displays virus-like particles in infected cells and does not deny the prion hypothesis, it only shows that identification of disease source is difficult. Comments of many neurologists on this issue are also presented.

While researchers have examined the economic effects of sport franchise relocation on cities and municipalities, little research has explored the social psychological effects of relocation on the fans from the cities being abandoned. Through the use of "Virtual Participant Observation" and "Inter(net)viewing," this paper examines the meanings fans attach to franchise relocation decisions and how they make sense of and adjust to the impending loss of a civic institution such as a sport franchise. The paper also examines the root metaphors created and used by fans in the expression of their feelings, experiences, and interpretations of (a) the relocation decision, (b) the relationship of the owners and team, and (c) the relationship of the fans and team. These metaphors enable funs to make sense of a particularly disruptive situation (i.e., franchise relocation)--a decision which violates normative American cultural assumptions, core tenets, and values. [ABSTRACT FROM AUTHOR]

• Despite reform efforts, the juvenile justice system is permeated with inequities. • Partnering with stakeholders, we developed an integrated model of juvenile justice. • The model layers public health, socioecological and restorative justice frameworks. • Applied examples illustrate how this approach can benefit youth and communities. • Recommendations for engaging in community-driven reform efforts are provided. Approaches to juvenile justice have undergone significant change in recent years, shifting away from retributive models and toward greater focus on rehabilitation and recognition of the unique developmental needs of youth. However, the juvenile justice system is still permeated with significant challenges, including the overrepresentation of vulnerable youth, particularly youth of color, and limited community-based interventions for youth at risk for justice involvement. Current models of juvenile justice do not fully address the needs of at-risk and justice involved youth, and have struggled to effectively reduce racial and ethnic disparities within the system, suggesting there is a need for a model that is better able to conceptualize and respond to youths' needs. The purpose of this paper is to describe the Integrated Model of Juvenile Justice (IMJJ), a novel conceptual approach to juvenile justice reform, which integrates the public health, social-ecological, and restorative justice models. We worked collaboratively with justice system stakeholders in Connecticut to develop the IMJJ, which proposes that juvenile justice practice must take into account and provide for youths' multi-level needs. Through an applied example, this paper describes how the IMJJ can be utilized to target youth offending and promote equitable treatment of youth in the juvenile justice system. Recommendations for justice system stakeholders are provided and implications for policy and practice are discussed. [ABSTRACT FROM AUTHOR]

Background: Dementia, depression, and delirium alone or in combination (3Ds) can threaten independence among older adults, and polypharmacy may further accelerate decline. Clinical pharmacists can play an important role on multidisciplinary home-based care teams by identifying medication therapy problems (MTPs) involving cognition. Within a larger ongoing clinical trial, this paper describes cognition-related MTPs and pharmacist recommendations among older adults with 3Ds followed by a home-based care team. Methods: We conducted a retrospective analysis of medication data among Medicare Advantage members aged ≥ 65 years living at home in Connecticut with International Statistical Classification of Diseases and Related Health Problems, 10th Revision codes related to 3Ds; analyses include the first 105 subjects randomized to the home-based care team from March 2017 to January 2019. Advanced practice registered nurses conducted in-home medication reconciliations along with medical and cognitive assessments. Clinical pharmacists then conducted medication reviews centered on agents treating or exacerbating 3Ds. After review by the study advanced practice registered nurse, geriatrician, and psychiatrist, salient recommendations were forwarded to primary care providers for consideration. Medication therapy problems related to cognition were retrospectively abstracted and classified as: (1) indication: underuse or overuse; (2) effectiveness: ineffective agent or low dose (mainly for antidepressants); and (3) safety: undesirable effect (e.g., impaired cognition, dementia treatment side effects), unsafe medication (e.g., potentially inappropriate medications that can harm cognition), drug interaction, or high dose. Results: Pharmacists identified 166 cognitive MTPs, with a mean (standard deviation) of 1.58 (1.35) [range 0–6] MTPs per subject. Indication MTPs represented 34% of total MTPs, of which 79% involved underuse and 21% overuse; effectiveness represented 13% of total MTPs; and safety represented over half (52%) of all MTPs, with benzodiazepines and anticholinergics frequently implicated. Recommendations commonly included medication reduction (discontinuation 23% and dose reduction 19%). We found MTPs involving cognition among most (79%) patients. Conclusions: Our study findings support the role of pharmacists on multidisciplinary teams to identify cognitively harmful medications, dementia treatment side effects, and untreated cognitive conditions. Clinical Trial Registration: ClinicalTrials.gov NCT02945085. [ABSTRACT FROM AUTHOR]

• Crash prediction by injury severity and vehicle damage was conducted and compared. • Multivariate Poisson-Lognormal (MVPLN) models were estimated. • Joint Negative Binomial-Generalized Ordered Probit Fractional Split (NB-GOPFS) models were estimated. • Unobserved heterogeneity was accommodated by both models. • A surrogate measure for injury severity was evaluated. Introduction: Predicting crash counts by severity plays a dominant role in identifying roadway sites that experience overrepresented crashes, or an increase in the potential for crashes with higher severity levels. Valid and reliable methodologies for predicting highway accidents by severity are necessary in assessing contributing factors to severe highway crashes, and assisting the practitioners in allocating safety improvement resources. Methods: This paper uses urban and suburban intersection data in Connecticut, along with two sophisticated modeling approaches, i.e. a Multivariate Poisson-Lognormal (MVPLN) model and a Joint Negative Binomial-Generalized Ordered Probit Fractional Split (NB-GOPFS) model to assess the methodological rationality and accuracy by accommodating for the unobserved factors in predicting crash counts by severity level. Furthermore, crash prediction models based on vehicle damage level are estimated using the same two methodologies to supplement the injury severity in estimating crashes by severity when the sample mean of severe injury crashes (e.g., fatal crashes) is very low. Results: The model estimation results highlight the presence of correlations of crash counts among severity levels, as well as the crash counts in total and crash proportions by different severity levels. A comparison of results indicates that injury severity and vehicle damage are highly consistent. Conclusions: Crash severity counts are significantly correlated and should be accommodated in crash prediction models. Practical application: The findings of this research could help select sound and reliable methodologies for predicting highway accidents by injury severity. When crash data samples have challenges associated with the low observed sampling rates for severe injury crashes, this research also confirmed that vehicle damage can be appropriate as an alternative to injury severity in crash prediction by severity. [ABSTRACT FROM AUTHOR]

• A framework for characterizing inundation depth (ID) during compound events is presented. • Relative importance of surge and inland flows in controlling flood ID is quantified. • A new topographic index is introduced to capture the variability of flood ID from river to coast. • With the index areas are identified where compound events are more prominent. Storm surge and river runoff can result in compound flooding in coastal areas. The impact of these events can be more significant than that generated by each component individually. This paper describes a framework for characterizing flooding during compound events and quantifying the relative importance of surge and river flows in controlling inundation depth (ID). For the analysis, we considered 1051 simulations of historical flood events covering about 40 years in Connecticut (CT), USA, and several simulated storms associated with synthetic climate scenarios. We simulated river discharge time series for each event using a physically based distributed hydrological model and retrieved the storm surge from tidal stations. These time series are used as upstream and downstream boundary conditions in 2D hydrodynamic simulation. We focused the analysis on seven locations along the coast of Connecticut covered by LiDAR-derived 1 m DEM. To capture the variability of inundation characteristics over the full-scale gradient from river to coast, we introduced a new topographic index, D-Index, that distinguishes topologic variabilities. Results from this study highlight that there is a correlation of ID to different drivers in distinct categories of the D-Index, which can correctly label the main source of hazard, either coast, river, or compound. We identified thresholds of standard deviation (σ) of the D-Index to identify areas where ID strongly correlates with either flow peak and volume, surge peak, or a combination of both. The study also shows that it is possible to use the results obtained from the 1 m analysis to generalize the findings for the entire CT coast to derive zones dominated by surge, river flow, or the compound effect of the two. This study can help coastal communities better understand the risk of the compound impacts of coastal storms, which is essential for increasing climate resilience. [ABSTRACT FROM AUTHOR]

Objectives: This paper investigates a community-based intervention for young fathers, FatherWorks, compared to care-as-usual, 24/7 Dads. We hypothesized that utilizing the FatherWorks intervention (a 15 session parenting intervention, 13 session employment class, paid internship, case management, and access to behavioral health services) will assist in readiness to use condoms and increase condom usage, which may differ by race/ethnicity. Methods: Eligible males (n = 328) were enrolled into a Randomized Control Trial. Participants were 15–24 years old and had fathered one or more children with a female under the age of 21. A survey was taken at baseline and at 15 weeks following the intervention. Results: Analyses of changes indicated that intervention participants improved from the pre-contemplation stage of condom usage towards contemplation, and from preparation to action. The pattern of improvement in the condom use stage of change was different in African-American versus Hispanic participants. Changes in condom use during last intercourse were not significant. Conclusions: Study findings indicate that FatherWorks is successful in increasing the intent to use condoms, with the effect manifesting differently in African-American and Hispanic young fathers. Future work with minority fathers indicates a need for cultural adaptation of the intervention. [ABSTRACT FROM AUTHOR]

Epidemiologic studies have established associations between various air pollutants and adverse health outcomes for adults and children. Due to high costs of monitoring air pollutant concentrations for subjects enrolled in a study, statisticians predict exposure concentrations from spatial models that are developed using concentrations monitored at a few sites. In the absence of detailed information on when and where subjects move during the study window, researchers typically assume that the subjects spend their entire day at home, school, or work. This assumption can potentially lead to large exposure assignment bias. In this study, we aim to determine the distribution of the exposure assignment bias for an air pollutant (ozone) when subjects are assumed to be static as compared to accounting for individual mobility. To achieve this goal, we use cell-phone mobility data on approximately 400,000 users in the state of Connecticut, USA during a week in July 2016, in conjunction with an ozone pollution model, and compare individual ozone exposure assuming static versus mobile scenarios. Our results show that exposure models not taking mobility into account often provide poor estimates of individuals commuting into and out of urban areas: the average 8-h maximum difference between these estimates can exceed 80 parts per billion (ppb). However, for most of the population, the difference in exposure assignment between the two models is small, thereby validating many current epidemiologic studies focusing on exposure to ozone. Supplementary materials accompanying this paper appear online. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to understand landlords' attitudes toward applicants with histories of sex offenses and landlords' willingness to broaden eligibility criteria for tenancy. Design/methodology/approach: A convenience sample of 50 landlords in Connecticut were interviewed. The content of interviews was analyzed to examine how often a landlord would be open to renting to individuals on the sex offender registry and what conditions affect their decisions. Findings: In total, 44% of landlords would not rent to adults with histories of sex offenses under any circumstance, but 8% of landlords reported they would rent to such individuals and an additional 36% of landlords were open to it with a high threshold for other indicators of good tenancy such as stable housing history, good credit and timely rental payments. Practical implications: These findings not only illustrate the real-world challenges in finding housing for adults with histories of sex offenses but also highlight opportunities in working with landlords. Originality/value: There has been little examination of housing adults with sex offenders from the perspective of landlords, which is important to understand to address this difficult and sensitive issue. [ABSTRACT FROM AUTHOR]

There is an ongoing argument about the potency of chrysotile asbestos to cause malignant mesothelioma. Authors of chrysotile risk assessments have relied upon the results of an epidemiologic study, published in 1984, to state that there were no mesotheliomas found among workers at a Connecticut friction products plant. McDonald reported the first two cases in 1986. In 2010, we reported the work histories and pathologic reports of five individuals from the Connecticut plant who were diagnosed with mesothelioma. Despite this, a review of the health effects of chrysotile published in 2018 continued to state that there were no cases of mesothelioma from this plant. We report here two new cases that were diagnosed after the publication of our previous report, bringing the current total to nine cases. We also discuss the results of previously unpublished air sampling data from the plant. Chrysotile, mainly from Canada, was the only asbestos fiber type used until 1957 when some anthophyllite was added in making paper discs and bands. Beyond this original description of the anthophyllite usage from McDonald, there is a dearth of information about the amount of anthophyllite used in the plant, the frequency of its use, and the specific departments where it was used. For over 30 years in the published literature, this factory has alternatively been described as a 'chrysotile' or 'predominantly chrysotile' factory. While it is clear that some anthophyllite was used in the factory (in addition to 400 pounds of crocidolite in the laboratory), given the volume, frequency, and processes using chrysotile, it still seems satisfactory to describe this cohort as a predominantly, but not exclusively, chrysotile-exposed cohort. [ABSTRACT FROM AUTHOR]

Aim: This article considers the systems leadership doctor of nursing practice degree as an option to increase nursing leadership roles and heighten presence at policy tables globally, particularly in low‐ and middle‐income countries. Recent global reports emphasize core competencies needed for nursing leadership, particularly systems leadership and health policy, to successfully move the global health agenda forward. Using the Yale University School of Nursing programme as an exemplar, this paper is focused on the elements directly linked to leadership competencies and relevance of a systems leadership doctor of nursing practice programme globally. Background/Introduction: The dramatic growth and wide variability of doctor of nursing practice programmes offered in all 50 US States have generated questions and debate. According to the American Association of Colleges of Nursing as of May 2018, there are 121 schools that reported having a leadership focus in postmaster's doctor of nursing practice degree offering. Yet there has not been the same enthusiasm for development and implementation for a practice doctorate in nursing across the globe. Sources of evidence: A narrative literature review was conducted aimed at addressing the relevance of a practice doctorate globally. This analysis of the literature included a search of peer‐reviewed and grey literature. Nursing school websites were visited, and opinions of nurse leaders and students were sought. In addition, global reports that supported nursing leadership and their role in policy development were reviewed. Discussion/Conclusion: Globally, nurses have a critical role in leading health systems. Developing a cadre of nurse leaders educated at the doctoral level who can communicate with policymakers and develop strategies to meet health systems' goals is necessary. Implications for nursing, health and education policy: In recent global health reports and campaigns, strengthening nursing leadership and presence at policymaking tables are recurring themes. Offering a systems leadership doctor of nursing practice degree is one viable option to increase doctorally prepared nurse leaders for nursing policy and practice engagement. This calls for work with country and regional governments, regulatory bodies and nursing associations to empower nursing to contribute fully. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to describe a best practice model of care for children's mobile crisis services in Connecticut: Emergency Mobile Psychiatric Services (EMPS). EMPS responds to homes, schools, emergency departments and other community locations to provide children and their families with mobile crisis stabilization, assessment and brief intervention, and referral and linkage to ongoing care. The system is comprised of a statewide network of contracted providers, a statewide Call Center to manage and triage incoming referrals, and a Performance Improvement Center to provide data analysis, reporting, quality improvement, and standardized training. Data collected since 2009 demonstrate high service utilization, consistently high mobility rates, and rapid response times as well as statistically significant improvements in child outcomes. The paper discusses the role of mobile crisis services within a comprehensive continuum of behavioral health care for children and families. [ABSTRACT FROM AUTHOR]

Abstract The involvement of consumers in the planning and development of health services has been encouraged and, in some cases, mandated. This involvement is viewed by many as a democratic or ethical requirement in that consumers have a right to influence services. Connecticut has been working toward the full implementation of a children's behavioral health system of care since 1997 but has lacked the mechanisms needed for family members to have their voices heard or to be full partners at decision-making tables. This paper is a case study that highlights work that has been done to 1) gather systematic feedback from families through the use of participatory research methods; 2) increase family access to data; and, 3) build the capacity of caregivers with the goal of increasing their involvement and leadership at all levels of the system of care. Highlights • The involvement of consumers in the planning and development of health services is encouraged. • Involvement of consumers is viewed by many ethical as consumers have a right to influence services they receive. • Connecticut has been working to engage family members as full partners at children's behavioral health decision-making tables. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to describe a public, open‐access, computed tomography (CT) phantom image set acquired at three centers and collected especially for radiomics reproducibility research. The dataset is useful to test radiomic features reproducibility with respect to various parameters, such as acquisition settings, scanners, and reconstruction algorithms. Acquisition and validation methods: Three phantoms were scanned in three independent institutions. Images of the following phantoms were acquired: Catphan 700 and COPDGene Phantom II (Phantom Laboratory, Greenwich, NY, USA), and the Triple modality 3D Abdominal Phantom (CIRS, Norfolk, VA, USA). Data were collected at three Dutch medical centers: MAASTRO Clinic (Maastricht, NL), Radboud University Medical Center (Nijmegen, NL), and University Medical Center Groningen (Groningen, NL) with scanners from two different manufacturers Siemens Healthcare and Philips Healthcare. The following acquisition parameter were varied in the phantom scans: slice thickness, reconstruction kernels, and tube current. Data format and usage notes: We made the dataset publically available on the Dutch instance of "Extensible Neuroimaging Archive Toolkit‐XNAT" (https://xnat.bmia.nl). The dataset is freely available and reusable with attribution (Creative Commons 3.0 license). Potential applications: Our goal was to provide a findable, open‐access, annotated, and reusable CT phantom dataset for radiomics reproducibility studies. Reproducibility testing and harmonization are fundamental requirements for wide generalizability of radiomics‐based clinical prediction models. It is highly desirable to include only reproducible features into models, to be more assured of external validity across hitherto unseen contexts. In this view, phantom data from different centers represent a valuable source of information to exclude CT radiomic features that may already be unstable with respect to simplified structures and tightly controlled scan settings. The intended extension of our shared dataset is to include other modalities and phantoms with more realistic lesion simulations. [ABSTRACT FROM AUTHOR]

Perturbations to acoustic speech feedback have been typically localized to specific phonetic characteristics, for example, fundamental frequency (F0) or the first two formants (F1/F2), or affect all aspects of the speech signal equally, for example, via the addition of background noise. This paper examines the consequences of a more selective global perturbation: real-time cochlear implant (CI) simulation of acoustic speech feedback. Specifically, we examine the potential similarity between speakers’ response to noise vocoding and the characteristics of Lombard speech. An acoustic analysis of supra-segmental characteristics in speaking rate, F0 production, and voice amplitude revealed changes that paralleled the Lombard effect in some domains but not others. Two studies of speech intelligibility complemented the acoustic analysis, finding that intelligibility significantly decreased as a result of CI simulation of speaker feedback. Together, the results point to differences in speakers’ responses to these two superficially similar feedback manipulations. In both cases we see a complex, multi-faceted behavior on the part of talkers. We argue that more instances of global perturbation and broader response assessment are needed to determine whether such complexity is present in other feedback manipulations or if it represents a relatively rare exception to the typical compensatory feedback response. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: The cost of diapering an infant can place a significant financial strain on families living in poverty. Partnerships between diaper banks and home visiting programs for young families may offer an innovative solution to expanding the reach and impact of diaper banks in low‐income communities. The purpose of this pilot study was to uncover preliminary information about the functions of diaper distribution through home visiting programs, and to inform future research and policy questions regarding diaper distribution to families in need. Design and Sample: In this descriptive qualitative pilot study, semi‐structured interviews were conducted with 6 home visitors from Minding the Baby® (MTB), a home visiting intervention for young parents. MTB clinicians routinely distribute diapers in partnership with The Diaper Bank in Connecticut. We used directed content analysis to code and analyze interview transcripts. Results/Conclusion: These preliminary findings indicate that partnerships between home visiting programs and diaper banks may benefit families by improving diaper access, reducing stigma, and fostering trusting relationships with home visitors. Home visiting program benefits including engagement or re‐engagement with families may need to be balanced with potential effects on clinical and therapeutic relationships. Recommendations for next steps in research and related policy questions are discussed. [ABSTRACT FROM AUTHOR]

This paper improves upon an existing extreme precipitation monitoring system that is based on the Tropical Rainfall Measuring Mission (TRMM)daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach in which data from similar locations are pooled to increase the quality of the resulting model parameter estimates to compensate for the short data record. The regional analysis is divided into two stages. First, the region defined by the TRMM measurements is partitioned into approximately 28 000 nonoverlapping clusters using a recursive k-means clustering scheme. Next, a statistical model is used characterize the extreme precipitation events occurring in each cluster. Instead of applying the block maxima approach used in the existing system, in which the generalized extreme value probability distribution is fit to the annual precipitation maxima at each site separately, the present work adopts the peak-over-threshold method of classifying points as extreme if they exceed a prespecified threshold. Theoretical considerations motivate using the point process framework for modeling extremes. The fitted parameters are used to estimate trends and to construct simple and intuitive average recurrence interval (ARI) maps that reveal how rare a particular precipitation event is. This information could be used by policy makers for disaster monitoring and prevention. The new method eliminates much of the noise that was produced by the existing models because of a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center ground-based observations. Furthermore, the proposed method can be applied to other extreme climate records. [ABSTRACT FROM AUTHOR]

Hurricane Sandy (2012, referred to as Current Sandy) was among the most devastating storms to impact Connecticut's overhead electric distribution network, resulting in over 15 000 outage locations that affected more than 500 000 customers. In this paper, the severity of tree-caused outages in Connecticut is estimated under future-climate Hurricane Sandy simulations, each exhibiting strengthened winds and heavier rain accumulation over the study area from large-scale thermodynamic changes in the atmosphere and track changes in the year~2100 (referred to as Future Sandy). Three machine-learning models used five weather simulations and the ensemble mean of Current and Future Sandy, along with land-use and overhead utility infrastructure data, to predict the severity and spatial distribution of outages across the Eversource Energy service territory in Connecticut. To assess the influence of increased precipitation from Future Sandy, two approaches were compared: an outage model fit with a full set of variables accounting for both wind and precipitation, and a reduced set with only wind. Future Sandy displayed an outage increase of 42%-64% when using the ensemble of WRF simulations fit with three different outage prediction models. This study is a proof of concept for the assessment of increased outage risk resulting from potential changes in tropical cyclone intensity associated with late-century thermodynamic changes driven by the IPCC AR4 A2 emissions scenario. [ABSTRACT FROM AUTHOR]

This paper aims to understand whether outbreaks of Covid-19 cases may increase after major storms due to the displacement and movement of a large number of people affected by fallen trees, power lines, and resultant power outages. After Tropical Storm Isais caused widespread power outages in Connecticut (CT), we compiled hourly power outage data, and daily COVID-19 cases for 21 days before and after the storm. First, we identified towns with statistically significant increasing trends of daily COVID-19 cases before and after the storm using time series functions. Using a retrospective space-time scan statistic, we further identified COVID-19 space-time clusters that were active (i.e., more observed than expected cases) before and after the storm. Second, we measured the movement of people from cell phone data aggregated by Safegraph. Third, we measured statistical associations between power outages and movement of people with the increase in COVID-19 cases. Results showed positive associations between power outages and COVTD-19 cases increase. It may be possible to predict the location of future outbreaks after major storms using power outage information. We can estimate times to power restoration by locations using outage predictions and then direct appropriate public health interventions such as increased testing and contact tracing when people return to their homes and businesses to prevent future disease outbreaks. This paper has the potential for advancing the understanding of coupled human-environment systems through an investigation of the relationships between extreme weather events, environmental management, and human health. [ABSTRACT FROM AUTHOR]

Background: Although studies show that genomics and environmental stressors affect blood pressure, few studies have examined their combined effects, especially in African Americans. Objective: We present the recruitment methods and psychological measures of the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure (InterGEN) study, which seeks to investigate the individual and combined effects of genetic (G) and environmental (E) (psychological) stressors on blood pressure in African American mother-child dyads. Genetic methods are presented elsewhere, but here we present the recruitment methods, psychological measures, and analysis plan for these environmental stressors. Methods: This longitudinal study will enroll 250 mother-child dyads (N = 500). Study participation is restricted to women who (a) are ≤21 years of age, (b) self-identify as African American or Black, (c) speak English, (d) do not have an identified mental illness or cognitive impairment, and (e) have a biological child between 3 and 5 years old. The primary environmental stressors assessed are parenting stress, perceived racism and discrimination, and maternal mental health. Covariates include age, cigarette smoking (for mothers), and gender (for children). The study outcome variables are systolic and diastolic blood pressure. Analysis: The main analytic outcome is genetic-by-environment interaction analyses (G x E); however, main effects (G) and (E) will be individually assessed first. Genetic (G) and interaction analyses (G x E) are described in a companion paper and will include laboratory procedures. Statistical modeling of environmental stressors on blood pressure will be done using descriptive statistics and generalized estimating equation models. Implications: The methodology presented here includes the study rationale, community engagement and recruitment protocol, psychological variable measurement, and analysis plan for assessing the association of environmental stressors and blood pressure. This study may provide the foundation for other studies and development of interventions to reduce the risk for hypertension and to propose targeted health promotion programs for this high-risk population. [ABSTRACT FROM AUTHOR]

Due to the variability of working conditions and the scarcity of fault samples, the existing diagnosis models still have a big gap under the condition of covering more practical application scenarios. Therefore, it is of great significance to study an intelligent diagnosis scheme that takes few samples in the training source domain and zero samples in the test target domain (FST-ZST) into account. A Brownian correlation metric prototypical network (BCMPN) algorithm based on a multi-scale mask preprocessing mechanism is proposed for the above problem. First, this paper constructs a multi-scale mask preprocessing mechanism (MMP) to improve the optimization starting point. Second, the multi-scale feature embedding is realized through the dilation convolution module and the effective light channel attention (ELCA) module. Third, based on the Brownian distance similarity measurement, we learn the feature representation by measuring the difference between the joint feature function and the edge product in the field of diagnosis. Finally, based on the gear data set of the Connecticut university (UConn) and the data collected in the laboratory, it is proved that the BCMPN has better performance in the problem of FST-ZST. [ABSTRACT FROM AUTHOR]

This paper explores an emerging pattern of migration currently being written by the new wave of Mexican migrants in New Haven, Connecticut, a city with little to no history of Mexican migration. Using New Haven as a case study, this paper argues that local conditions shape immigrant experiences and thus frame the process of social and economic incorporation. By contrasting first-wave Italian migration and contemporary Mexican migration, we demonstrate that urban conditions both foster and impede the social and political integration of immigrant groups. Our analyses demonstrate that the presence of established ethnic communities pose challenges and benefits to the political and social incorporation of Italians and Mexicans in their respective urban eras. Moreover, we find that contemporary immigrants are entering settings that are more racialized and economically distinct than that of their first-wave immigrant predecessors. [ABSTRACT FROM AUTHOR]

This paper explicates the elements of several policy instruments used in Connecticut, the political conditions under which they were chosen, and their intended targets and expected effects on teacher quality and student learning. The purpose of the paper is to explain how the Connecticut General Assembly (CGA) and the Connecticut State Department of Education (CSDE) were able to implement and sustain a set of integrated policies related to teaching and learning over a 20-year period from 1985 to 2005. We argue that this occurred for three primary reasons. First, the state legislature combined changes in teacher certification requirements in the 1980s with significant increases in teacher salaries in order to build strong political support among teachers and teacher union leaders for the new requirements. Second, in the 1980s and 1990s, CGA and CSDE repeatedly combined policy instruments in ways that involved multiple stakeholders and strong elements of capacity-building, thereby increasing their likelihood of success. Third, several policies enacted in Connecticut in the 1990s were directly connected to and strongly reinforced each other. [ABSTRACT FROM AUTHOR]