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Electric vehicles (EVs) have shown promise in providing ancillary services, e.g., frequency regulation. This is mainly due to their capacities and fast response. On the contrary, the rapid integration of EVs in the grid poses challenges, such as frequency and voltage stability. In order to mitigate the above-mentioned issues, several dispatching strategies have been introduced in the recent literature to optimize the charging/discharging rates of EVs. In this paper, a comparative study of power management strategies for secondary frequency regulation (SFR) employing a fleet of EVs is presented. A hierarchical control scheme is employed to compare two cases, namely control at the charging station (CS) level and novel control at the EVs level. Under both cases, a multi-objective optimization approach is utilized to define the optimal charging and discharging rates of EVs using a pattern search algorithm. Furthermore, the performance of the two models is experimented under contingency cases, a notable contribution of this study. Finally, simulations are carried out using OPAL-RT real time simulator to validate the performance of the two models based on real-time traces obtained from Pennsylvania, New Jersey, and Maryland (PJM) interconnection and California independent system operator (CAISO). To further validate the proposed model, a comparison with a mixed-integer linear programming (MILP) based model is presented. [ABSTRACT FROM AUTHOR]

Highlights • The flux of multivalent cations across non-selective CMX membranes was 1.4 times > sodium. • A CMX-S membrane at the cathode boundary reduced the flux of Ca, Mg, and Ba into the electrode rinse. • Ca, Mg and Ba interfered by blocking transfer sites on the CMX-S membrane at the cathode barrier. • Overall flux was improved by unblocking the CMX-S membrane with periodic polarity reversal. • Soluble Fe precipitated throughout the stack and within the diluate and concentrate tanks. Abstract Electrodialysis is an electrochemically driven membrane technology usually used for treating feed water containing several thousand mg/l total dissolved solids (TDS). This research investigated the use of conventional ED for the treatment of flowback water from shale gas hydraulic fracturing that contains up to tens of thousands of mg/l TDS and contain a mixture of multivalent cations. This paper discusses efforts to treat concentrated brines with electrodialysis and focuses on the mitigation of the detrimental effects of multivalent cations such as calcium, magnesium, barium, iron, and in the feedstock. A previous paper detailed the effects of calcium under defined lab conditions. The apparent calcium fouling (in and around) the electrode cells was mitigated by changing the single cathode chamber boundary membrane to a (CMX-S) that was more selective for monovalent cations. This paper covers efforts undertaken to mitigate problems associated with high concentrations of calcium, barium, iron, and magnesium. Four field samples of produced water from oil and gas operations in from the Marcellus shale formation (generally Pennsylvania, USA) and the Barnett shale formation (generally north central Texas, USA) were also tested. These results from field samples were similar to the results from lab defined tests. Mechanisms of process interference by the different multivalent cations appear different for each species. Calcium, magnesium, barium, and iron were preferentially transported from the diluate to the concentrate compared to sodium by a factor of about 1.4:1 on a charge basis resulting in a suppression of the flux of sodium to the concentrate. A single CMX-S membrane selective for monovalent cations was placed at the cathode barrier resulting in a reduced flux of calcium, magnesium and barium into the electrode rinse. However total ion flux was inhibited caused by apparent blockage of the cation transfer sites on the CMX-S membrane by the stagnant multivalent cations. A series of tests with periodic pulse polarity-reversal (anode and cathode reversed for a brief time) indicted the blockage by calcium and barium was immediately reversable, however, iron was more problematic and may have precipitated on membrane surfaces other than the cathode barrier. [ABSTRACT FROM AUTHOR]

Coal mine methane (CMM) and abandoned mine methane (AMM) are by-products of underground mining of gassy coal beds. The quantity and the emission rate of CMM and AMM may vary depending on the type of mine, gas content of the mined coal bed, and gas sourced from strata and coal beds in overlying and underlying formations affected by mining. Therefore, if a mine has the potential of accumulating gas after being abandoned and sealed properly, that methane may be produced and used as an energy source to serve local communities in the area. Producing AMM also prevents methane, which is a potent greenhouse gas, from leaking to the atmosphere through seals, shaft plugs or surface cracks. A technical barrier to economical utilization of CMM and AMM is the uncertainty about how much methane may be available in the gas emission zone (GEZ) as a resource during mining, as well as after the panels are sealed and the mine is abandoned. Another difficulty is estimating how much of the potential methane resource can be produced from gob gas ventholes (GGV) converted to capture AMM. In this study, a comparative assessment is presented to address the issues stated above. The assessment was conducted on two adjacent panels of a longwall mine that operated in Pennsylvania until 2016 in the Northern Appalachian Basin. The study is based on two approaches that might be used depending on the availability of data. The first approach uses an extensive geological data set, geostatistics, and measured shaft gas emission and GGV production values that were collected while the panel (s) were active to assess the AMM resource. The second approach uses a minimal amount of geologic data, uncertainty of the data as probabilistic distributions, and the use of publicly available software to predict during-mining emissions. Results showed that both approaches provide relatively comparable estimates of AMM resources and AMM recovery potential using wellbores. The differences in assessed quantities are mostly due to the characteristics of the two methods. In that regard, this paper can be considered as guidance to choose the assessment approach based on data availability. • A comparative assessment procedure for CMM and AMM resource potential is presented. • The assessment was conducted on two adjacent panels of a longwall mine that operated in in the Northern Appalachian basin. • Results showed that both approaches provide relatively comparable estimates. • The differences in assessed quantities are mostly due to the characteristics of the two methods. • This paper can be considered as guidance in the choice of assessment approaches based on data availability. [ABSTRACT FROM AUTHOR]

• Paper estimates a CMF for high friction surface treatment (HFST) applied to horizontal curves on undivided two-lane roads. • Propensity score matching is incorporated into EB before-after methodology to select more appropriate reference group. • Results indicate significant reductions in crash frequency (of all types considered) when applying HFST. Horizontal curves are locations that, as a result of the changing alignment, may be a contributing factor in roadway departure crashes. One low-cost countermeasure to mitigate crashes at these locations is the installation of the high friction surface treatment (HFST), which increases roadway friction and is intended to help keep drivers on the roadway when traversing a horizontal curve. This treatment has been implemented at numerous curves in Pennsylvania, but the overall safety effectiveness is not known. The purpose of this study is to estimate a suite of Crash Modification Factors (CMFs) for HFST applied to curve sections of undivided two-lane roadways. A novel combination of the empirical Bayes observational before-after study design and propensity score matching was used to estimate CMFs for multiple crash types, crash severities, and roadway settings (urban and rural). Propensity score matching was implemented to identify the most appropriate reference group to use within the empirical Bayes methodology. The results indicate that the installation of HFST is associated with a statistically significant decrease in all crash types and severities considered. [ABSTRACT FROM AUTHOR]

Despite significant efforts to improve access to medications for opioid use disorder (MOUD), uptake remains low relative to the scope of the problem in the United States. A growing body of quantitative and qualitative research has documented consistent barriers to MOUD treatment access and retention, at the level of individuals, institutions, and society at large. Stigma - surrounding both people who use opioids (PWUO) and treatment using MOUD – is among the most-cited barriers by patients and providers alike, yet few studies have examined provider-based stigma specifically, or considered its interaction with other impediments to OUD care. This paper employs a qualitative approach to the analysis of provider-based stigma among professionals involved in the treatment or supervision of individuals with OUD. We conducted and analyzed interviews with 19 professionals as part of a larger mixed methods study on stigma among substance use treatment providers and court personnel in Pennsylvania. Beyond capturing providers' perceptions of PWUO and MOUD, the authors asked participants to describe barriers to recovery, and the effective delivery of care within this population. Interviewees enumerated multiple entrenched barriers that sometimes operated at different levels, such as criminal-legal involvement, which weakened PWUO's social networks and employment prospects, while undermining providers' attempts at continuity of care; moreover, participants cited the "War on Drugs" as an overarching impediment to effective substance use treatment, not least for its role in perpetuating stigma against PWUO. Interestingly, while an overwhelming majority of participants named stigma as a barrier to treatment at every level, most also articulated stigmatizing beliefs around PWUO. Namely, providers evoked one element of stigma – blameworthiness – in their contention that many PWUO are inadequately motivated to recover. In addition to adding further complexity to MOUD barriers research, this study troubles the notion that professional training and education on the disease model of addiction serve to eradicate stigma. • Uptake of medications for opioid use disorder remains low despite efforts to expand access. • Individual, institutional, and systemic barriers to MOUD interact to reduce usage. • Treatment providers identify stigma as a primary barrier to MOUD effectiveness at all levels. • Many treatment providers also express conceptions of people who use opioids as "blameworthy." [ABSTRACT FROM AUTHOR]

Stormwater green infrastructure (GI) has been applied as a method to address urban flooding for over forty years. However, GI has not yet been widely utilized across the US. Prior studies identified some challenges with technical, engineering, and socioeconomic aspects of GI, but detailed examination of non-scientific papers to identify and analyze real-world barriers that may hinder the implementation of GI has not yet been done. To achieve this goal, we conducted a meta-analysis of 351 public documents from federal, state, and 62 municipalities in Eastern Pennsylvania to systematically review the support of different levels of government for implementing GI. We summarized barriers in three categories: 1) governance and policy: failure to integrate GI into existing stormwater management policies due to unclearly defined responsibility and infrequent policy updates, 2) stormwater fees and credits: inequity in stormwater fee structures and debate of stormwater credits connected to GI, and 3) public education and outreach: most municipal governments provide little or no stormwater and GI-related information to their residents, but some municipalities with higher population density have tried to offer more. These barriers will restrain the original intention and vision of GI implementation and cause difficulties in effectively conveying GI's information from the federal and state levels to municipalities and residents. Our discussion highlights these difficulties of GI implementation at all governmental levels and shed light on potential solutions to address these barriers. • Barriers to Green Infrastructure (GI) adoption in the US context are identified. • Qualitative and quantitative methods are conducted to identify GI barriers. • Three categories of GI barriers are summarized at different levels of government. [ABSTRACT FROM AUTHOR]

The main challenge in addressing constrained multi-objective optimization problems (CMOPs) lies in achieving a balance among convergence, diversity, and feasibility. To address this issue, this paper proposes a constrained multi-objective evolutionary algorithm with Pareto estimation via neural network named CMOEA-PeNN. In order to exploit and explore the decision space, the proposed algorithm employs a dual-population mechanism, which is trained with a self-organizing map (SOM). Firstly, the population distribution structure in decision space is mapped to objective space while preserving neighborhood information, and then the neuron weight is utilized to estimate the Pareto front (PF). Secondly, a novel approach is devised to preserve the feasibility of the population and enhance the estimation of the Pareto front by SOM. The achievement scalarizing function (ASF) is employed to choose promising solutions. This strategy could guide the population toward the optimal solution while exploring the small feasible regions. Finally, the performance of CMOEA-PeNN is compared with five state-of-the-art constrained multi-objective evolutionary algorithms (CMOEAs) on three widely used benchmark problems and a real-world problem. The experimental results show that CMOEA-PeNN could archive competitive performance in solving CMOPs. [ABSTRACT FROM AUTHOR]

As the extraction of shale gas and oil transforms localities, these places emerge as important, if understudied, sites of contemporary carbon politics. In this paper, we develop a new approach for examining lived connections between fossil fuel extraction and climate change. We propose the concept of carbon mobilization to describe the multiple stages of fossil fuel extraction and combustion that may be experienced independently (as an economic boom, climate disaster, or air pollution, for example) or simultaneously, in locally distinctive combinations – but until now have been considered separately in most scholarship and public policy. We explore lived experiences of carbon mobilization in Bradford County, Pennsylvania, a community that, in the last decade, has gone through a shale gas boom and bust and has suffered from severe flooding. Interviews with social service providers and county leaders indicated that connections between the fossil fuel industry and climate disaster manifested most saliently around housing security—particularly the loss of housing due to floods and economic insecurity related to boom-bust cycles. Economic changes that gas development brought to the community made flood resilience more challenging for some, and easier for others. Perhaps surprisingly, the natural gas industry was a "double winner," benefitting from climate disaster by gaining a reputation for helping with flood recovery. We suggest that while global climate discourse may not resonate locally in communities that host fossil fuel extraction, people make locally-salient connections between different stages of carbon mobilization, and these connections have important public policy and social justice implications. [ABSTRACT FROM AUTHOR]

Heroin overdose, more accurately termed ‘heroin-related overdose’ due to the frequent involvement of other drugs, is the leading cause of mortality among regular heroin users. (Degenhardt et al., 2010) Heroin injectors are at greater risk of hospital admission for heroin-related overdose (HOD) in the eastern United States where Colombian-sourced powder heroin is sold than in the western US where black ‘tar’ heroin predominates. (Unick et al., 2014) This paper examines under-researched influences on HOD, both fatal and non-fatal, using data from a qualitative study of injecting drug users of black tar heroin in San Francisco and powder heroin in Philadelphia Data were collected through in-depth, semi-structured interviews carried out in 2012 that were conducted against a background of longer-term participant-observation, ethnographic studies of drug users and dealers in Philadelphia (2007–12) and of users in San Francisco (1994–2007, 2012). Our findings suggest three types of previously unconsidered influences on overdose risk that arise both from structural socio-economic factors and from the physical properties of the heroin source-types: 1) retail market structure including information flow between users; 2) marketing techniques such as branding, free samples and pricing and 3) differences in the physical characteristics of the two major heroin source forms and how they affect injecting techniques and vascular health. Although chosen for their contrasting source-forms, we found that the two cities have contrasting dominant models of drug retailing: San Francisco respondents tended to buy through private dealers and Philadelphia respondents frequented an open-air street market where heroin is branded and free samples are distributed, although each city included both types of drug sales. These market structures and marketing techniques shape the availability of information regarding heroin potency and its dissemination among users who tend to seek out the strongest heroin available on a given day. The physical characteristics of these two source-types, the way they are prepared for injecting and their effects on vein health also differ markedly. The purpose of this paper is to examine some of the unexplored factors that may lead to heroin-related overdose in the United States and to generate hypotheses for further study. [ABSTRACT FROM AUTHOR]

Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies. The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs). Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs. Up to 3 attempts were made to obtain each ASA24 recall. Participants were administered doubly-labeled water to provide a measure of total energy expenditure and collected two 24-hour urine samples to assess concentrations of nitrogen, sodium, and potassium. From January through September 2012, 1,110 adult members of AARP, 50 to 74 years of age, were recruited from the Pittsburgh, PA, area to participate in the Interactive Diet and Activity Tracking in AARP (IDATA) study. After excluding 33 participants who had not completed any dietary assessments, 531 men and 546 women remained. Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. Ninety-one percent of men and 86% of women completed 3 ASA24 recalls. Approximately three-quarters completed 5 or more, higher than the completion rates for 2 4DFRs and 2 FFQs. Approximately, three-quarters of men and 70% of women completed ASA24 on the first attempt; 1 in 5 completed it on the second. Completion rates varied slightly by age and body mass index. Median time to complete ASA24-2011 (current version: ASA24-2020) declined with subsequent recalls from 55 to 41 minutes in men and from 58 to 42 minutes in women and was lowest in those younger than 60 years. Mean nutrient intakes were similar across recalls. For each recording day, energy intakes estimated by ASA24 were lower than energy expenditure. Reported intakes for protein, potassium, and sodium were closer to recovery biomarkers for women, but not for men. Geometric means of reported intakes of these nutrients did not systematically vary across ASA24 administrations, but differences between reported intakes and biomarkers differed by nutrient. Of 100 possible points, HEI-2015 total scores were nearly identical for 4DFRs and ASA24 recalls and higher for FFQs (men: 61, 60, and 68; women: 64, 64, and 72, respectively). ASA24, a freely available dietary assessment tool for use in large-scale nutrition research, was found to be highly feasible. Similar to previously reported data for nutrient intakes, HEI-2015 total and component scores for ASA24 recalls were comparable to those for 4DFRs, but not FFQs. ClinicalTrials.gov identifier: NCT03268577 (http://www.clinicaltrials.gov). [ABSTRACT FROM AUTHOR]

Millions of American adults do not receive the recommended vaccinations each year. Community pharmacies are well positioned to help fill this gap through easy access and innovative patient-centered interventions. The primary goal of this demonstration project was to implement new notification and motivational interviewing processes at a regional supermarket chain pharmacy to increase the number of influenza, pertussis, pneumococcal, and herpes zoster vaccines provided to adults. This prospective, observational project utilized a pre-post design. Algorithms were developed with pharmacy dispensing data to identify vaccine-eligible patients. Pharmacy staff then received automated notifications through one of the following: (1) a vaccine message printed on the prescription receipt or on paper attached to the prescription bag when patients came to the pharmacy; or (2) a patient list generated through commercially-available software listing patient contact information and which vaccine they were eligible to receive. Irrespective of the notification process, pharmacy staff employed motivational interviewing techniques either face-to-face or telephonic to engage patients in conversation about getting vaccinated. Finally, an interface to the statewide vaccination registry was developed and tested to transmit vaccination information from all pharmacy locations. Ninety-nine pharmacies participated in the demonstration project across western Pennsylvania. A 33% increase in vaccinations was recorded over the prior year. Increases in vaccines were demonstrated in three of the four vaccine types: 45% for influenza, 31% for pertussis, and 7% for pneumococcal vaccinations. A decrease of 5% was observed for herpes zoster vaccinations. A successful connection to the statewide vaccine registry was established and 100% of all vaccines administered were transmitted to the registry. A combination of face-to-face and telephonic interventions with motivational interviewing were successful at increasing adult vaccinations in a regional supermarket chain pharmacy. Equal and sustained prioritization for all vaccines is necessary to achieve increases across all vaccine types. [ABSTRACT FROM AUTHOR]

Although water and energy systems are interdependent, they are still designed individually due to their complexity. This paper proposes a multiple input multiple output (MIMO) model predictive control (MPC) for demand management of an integrated water distribution system (WDS) supplied by an islanded microgrid (MG) system, offering an additional opportunity for energy-saving at the WDS. This strategy benefits the island and remote communities, which have limited access to the centralized electric grid. The existing literature either used an open-loop approach for energy management of water-energy microgrids or ignored the interconnected nature and MIMO nature of these systems. Compared to that, the proposed closed-loop energy management system is developed to address the detailed dynamics of assets, the inherent interconnections between water and energy networks, and to provide resilience as well as energy saving and demand management capabilities. The integrated MPC algorithm is designed in discrete time, utilizing a state-space model and sequential quadratic programming (SQP) as the solution method. Considering the intensive use of electricity by the pumps in WDS, their energy consumption is accommodated by an islanded microgrid system that incorporates a diesel generator, renewable energy sources (wind and solar), and a battery bank that serves as an energy source and a storage device. The proposed approach is investigated using base water demand from a real-world community, Telford, in Pennsylvania. Several case studies, such as variations in renewable energy contributions and increments of the control actions, are carried out to demonstrate the feasibility and reliability of the integrated MPC to provide efficient water and energy demand management concurrently. • Model predictive control algorithm of the interconnected water-energy is developed. • The full dynamics of energy-consuming assets in the water system are considered, including quadratic pump relations. • Effect of the renewable energy variations on the 24-hr energy dispatch is studied. • Multiple optimal configurations result in up to $360k/year savings, reduced carbon footprint, and smoother control. • The developed framework is applied in a Telford, PA case study, showcasing its real-world implementation. [ABSTRACT FROM AUTHOR]

• Aggregation and cooperation among peers will expand beyond prosumers in microgrids. • Growth in IoT and metering infrastructure is empowering end-use consumers. • Methodology allows aggregated consumers to schedule load and share energy. • Application demonstrates a significant cost reduction while assuring fairness. • Offers a novel cost-sharing strategy guided by cost minimization and Nash bargaining. End-use consumers (peers) are being empowered to aggregate for direct demand-side participation through load scheduling and energy sharing. This is the result of the growth of Internet of Things (IoT) enabled loads, availability of advanced metering infrastructure, and the move towards real-time (RT) pricing of electricity. Peer-to-peer (P2P) cooperation has received significant interest in recent years, though the focus of this growing body of research is on modeling prosumer behavior in microgrids. Hence, there is a need for new methodologies to examine empowerment of all end-use consumers (not limited to prosumers) to form aggregations and develop fair rules of cooperation to reduce cost. This paper offers an optimization based methodology to address the above need for power systems. It minimizes the total cost and considers fairness using a Nash bargaining approach. Since cost and fairness are often in conflict, trade-off strategies are also presented. The model to asses fairness is nonlinear. Hence, it is transformed into a second order cone program (SOCP) and solved using GUROBI software version 7.5.2. The methodology is implemented on a sample 5-bus network, built using price and demand data from one of the load zones of Pennsylvania, New Jersey, and Maryland (PJM) power network in the United States. It is shown that two aggregations of peers participating in the sample network can reduce their total cost by 14.17% and 22.7%, while maintaining fairness. Concluding remarks highlight some of the limitations of the methodology. [ABSTRACT FROM AUTHOR]

Exclusionary discipline practices have made schools among the primary referral sources to the juvenile justice system, helping create and perpetuate the school-to-prison pipeline. To dismantle the school-to-prison pipeline in Philadelphia, the City's police department initiated the Philadelphia Police School Diversion Program and collaborated with the City's school district, Department of Human Services (DHS), and other child-serving agencies to design and implement the program. This program diverts at-risk youth from school-based arrest and into community-based services to address identified needs. All students, ages 10 and older, without prior adjudications or open cases, who have committed designated summary or misdemeanor offenses on school grounds, are enrolled in this program and connected with a DHS-sponsored service provider—rather than facing arrest and automatic removal from school through suspension, expulsion, or disciplinary transfer. The Philadelphia Police School Diversion Program has been cited as a model of collaborative partnerships to address the school-to-prison pipeline. This paper describes the school-to-prison pipeline's creation; established diversionary efforts to keep students out of the justice system; and the development, procedures, implications, and limitations of the Philadelphia Police School Diversion Program. [ABSTRACT FROM AUTHOR]

Highlights • Examine the effectiveness of environmental enforcement in the Marcellus Shale. • Employ a three-level Hierarchical Linear Model to analyze gas wells' environmental non-compliance behaviors. • Previous inspection and punishment significantly affect current compliance of shale gas wells. • Inspection frequency and punishment severity could be increased. Abstract The rapid development of shale gas in the United States raises potential concerns about environmental impacts. This paper examines how environmental regulations are enforced in shale gas development in Pennsylvania's Marcellus Shale development and the resulting compliance behaviors, employing the economic literature of crime and punishment as the analytical framework. A three-level hierarchical linear model (HLM) is used to analyze the enforcement and compliance performance of regulators and shale gas operators, respectively, employing data spanning from 2011 to 2017. Significant variation in the environmental non-compliance exists between both wells and operators. The empirical results suggest progressive directions for adjusting environmental enforcement strategies in Pennsylvania and provide implications and references for other regions with similar shale gas ambitions. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The energy performance of a solar-powered VMD plant was evaluated. • The effect of the applied vacuum pressure on the specific energy consumption was demonstrated. • The effect of solar radiation on the energy performance of the installation was analyzed. • The impact of recycling hot cooling water used for steam condensation on SEC, GOR and daily production was discussed. Abstract In this paper, a study of the energy performance of a solar powered vacuum membrane distillation was investigated on four typical days that represent the four seasons of the year namely: the equinoxes (March 21st and September 21st) and the solstices (June 21st and December 21st), through the widely used energy criteria such as specific energy consumption, gained output ratio and heat recovery factor. The results indicate that the energy performance of the process is strongly linked to the solar irradiation and as long as the VMD is coupled with solar energy, the process could be competitive with industrialized desalination technologies such as RO, MSF and MED. Besides, the effect of the applied vacuum level on the specific energy consumption was examined. Obviously, the results reveal that for minimum SEEC an optimal vacuum pressure is between 5000 and 10000 Pa. As well a technique to optimize the energy performance by recycling hot cooling water, used for steam condensation, was discussed. An amelioration of about 35%, 26% and 31%, during the hottest day (June 21st) and of about 22%, 19% and 21%, during the coldest (December 21st) in the GOR, the SEC and the daily production could be achieved. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Copaifera reticulata oleoresin showed antigenotoxic effect on colon. • Pre-neoplastic lesions of the colon were reduced by treatment with Copaiba oleoresin. • The oleoresin reduced the progression of carcinogenesis. • Major chemical constituent of the oleoresin showed anti-inflammatory activity. • The anti-inflammatory activity of oleoresin is involved in its chemopreventive effect. Abstract In Brazilian folk medicine, copaiba oleoresin is widely known for its therapeutic activity, especially its wound healing and anti-inflammatory actions. Considering the relationship between inflammatory processes and carcinogenesis, this paper reports on the Copaifera reticulata Ducke oleoresin (CRO) chemopreventive potential in the colon carcinogenesis model in rats. To understand the mechanisms involved in this effect, the anti-inflammatory activity of CRO and its major chemical constituent, the diterpene ent -polyalthic acid (PA), were evaluated on the production of nitric oxide (NO) and prostaglandin E2 (PGE2) in mouse macrophages. For the chemoprevention assessment, the effect of CRO administered by gavage was investigated on DNA damage, pre-neoplastic lesions and mitotic frequencies induced by the 1,2-dimethylhydrazine (DMH; intraperitoneal injection) carcinogen by comet, aberrant crypt focus (ACF) and long-term assays, respectively. CRO reduced DNA damage (average 31.5%) and pre-neoplastic lesions (average 64.5%) induced by DMH, which revealed that CRO has antigenotoxic and anticarcinogenic effects. In the long-term assay, treatment with CRO significantly decreased mitoses in the tumor tissue, which suggested that CRO influenced carcinogenesis progression. PA reduced NO levels induced by lipopolysaccharides in macrophages. However, this diterpene showed no effect on PGE2. Taken together, our results suggest that PA exerts anti-inflammatory action via the NO pathway. The CRO chemopreventive effect may be partly due to the anti-inflammatory property of its major chemical constituent, PA. Our findings indicate that CRO is a promising agent to suppress colon carcinogenesis. [ABSTRACT FROM AUTHOR]

This paper focuses on improving equity in a well-known stochastic facility location problem (FLP). Specifically, given sets of potential facility locations and customers with random demand, traditional stochastic optimization models for the FLP seek to determine the number and location of facilities to open that minimize the total cost, including the fixed cost of opening facilities, expected transportation cost from customers to facilities, and expected unmet demand cost. We show that such models lead to inequitable distribution of facilities across different regions and disparities in transportation distance needed to reach those facilities. To mitigate such disparities, we first analyze a set of measures to gauge the level of equity of location decisions. Then, to investigate the impact of the method of modeling uncertainty on equity, we formulate and analyze stochastic programming (SP) and distributionally robust optimization (DRO) models that employ these measures to minimize disparities in transportation distance needed to access open facilities, assuming known and unknown distributions of the demand. Finally, we use a case study based on the Lehigh region in Pennsylvania to compare the impact of location decisions obtained using the traditional and the proposed models on equity and efficiency. Our results demonstrate how different methods of modeling equity under uncertainty can result in different location decisions with varying impacts on equity and efficiency. Notably, while prior literature shows that equity-neutral DRO models for the FLP yield robust location decisions, our results additionally demonstrate that the proposed DRO models produce equitable distributions of facilities and more effectively mitigate disparities in transportation distance than their SP and equity-neutral counterparts. • Reducing disparities in accessibility to service-providing facilities is important. • We aim to mitigate such disparities in a stochastic facility location problem (FLP). • We propose several equity-promoting stochastic optimization models for the FLP. • We derive insights using a case study based on the Lehigh region in Pennsylvania. • We show the impacts of methods of modeling equity and uncertainty on equity. [ABSTRACT FROM AUTHOR]

Scholars and activists have called for a recognition of a "third way" of farming which is beyond the binary between organic and conventional agriculture and instead represents a spectrum of practices. In this paper, we ask if the way Plain (conservative Amish and Mennonite) farmers manage antibiotic use and natural remedies is an example of these middle paths. Antibiotic use in managing herd health is a practice with significant environmental and health implications. Regulations and use patterns may enhance potential bifurcation between conventional and organic production in the US compared to the European context. The data for this study were collected through semi-structured interviews with 29 Plain dairy producers and nine veterinary health professionals in Michigan and Pennsylvania. Interviews focused on attitudes and behavior around herd health and possible connections to family healthcare management. Overall, our results indicate that the Plain farmers, especially the Amish, combined minimal antibiotics with a mixture of natural remedies. This indicates that delineations between organic and conventional agriculture and natural healthcare and mainstream healthcare may be more nuanced and complex than has been characterized in previous literature. • Amish and Mennonite dairy farmers offer an example of "middle paths" in managing antibiotic use. • Amish and Mennonite dairy farmers use a "third way" between organic and conventional management. • Amish and Mennonite dairy farmers combine antibiotics and natural remedies for animal health. [ABSTRACT FROM AUTHOR]

In many parts of the world nursing home residents have experienced a disproportionate risk of exposure to COVID-19 and have died at much higher rates than other groups. There is a critical need to identify the factors driving COVID-19 risk in nursing homes to better understand and address the conditions contributing to their vulnerability during public health crises. This study investigates the characteristics associated with COVID-19 cases and deaths among residents in U.S. nursing homes from 2020 to 2021, with a focus on geospatial and racial inequalities. Using data from the Centers for Medicare and Medicaid Services and LTCFocus, this paper uses zero-inflated negative binomial regression models, Kruskal-Wallis tests, and Local Moran's I to generate statistical and geospatial results. Our analysis reveals that majority Hispanic facilities have alarmingly high COVID-19 cases and deaths, suggesting that these facilities have the greatest need for policy improvements in staffing and financing to reduce racial inequalities in nursing home care. At the same time we also detect COVID-19 hot spots in rural areas with predominately White residents, indicating a need to rethink public messaging strategies in these areas. The top states with COVID-19 hot spots are Kentucky, Pennsylvania, Illinois, and Oklahoma. This research provides new insights into the socio-spatial contexts and inequities that contribute to the vulnerability of nursing home residents during a pandemic. • Geographic and racial inequalities are important indicators of covid-19 risk. • Covid-19 cases & deaths are high among facilities with majority Hispanic residents. • Facilities with majority Hispanic residents have high covid-19 vaccination rates. • Most covid-19 hot spots of cases & deaths are in predominantly White, rural areas. • The top states with covid-19 hot spots of cases & deaths are KY, PA, IL, and OK. [ABSTRACT FROM AUTHOR]

• Simultaneous estimation of crash frequency by either type or severity considered. • Univariate and bivariate (without and with copulas) negative binomial regression models compared. • Bivariate models with copulas shown to outperform traditional bivariate and univariate models. • Bivariate model with normal copulas outperforms other copulas tested. Statistical models of crash frequency typically apply univariate regression models to estimate total crash frequency or crash counts by various categories. However, a possible correlation between the dependent variables or unobserved variables associated with the dependent variables is not considered when univariate models are used to estimate categorized crash counts—such as different severity levels or numbers of vehicles involved. This may lead to inefficient parameter estimates compared to multivariate models that directly consider these correlations. This paper compares the results obtained from univariate negative binomial regression models of property-damage only (PDO) and fatal plus injury (FI) crash frequencies to models using traditional bivariate and copula-based bivariate negative binomial regression models. A similar comparison was made using models for the expected crash frequency of single- (SV) and multi-vehicle (MV) crashes. The models were estimated using two-lane, two-way rural highway segment-level data from an engineering district in Pennsylvania. The results show that all bivariate negative binomial models (with or without copulas) outperformed the corresponding univariate negative binomial models for PDO and FI, as well as SV and MV, crashes. Second, the statistical association of various traffic and roadway/roadside features with PDO and FI, as well as SV and MV crashes, were not the same relative to their corresponding relationships in the univariate models. The bivariate negative binomial model with normal copula outperformed all other models based on the goodness-of-fit statistics. The results suggest that copula-based bivariate negative binomial regression models may be a valuable alternative for univariate models when simultaneously modeling two disaggregate levels of crash counts. [ABSTRACT FROM AUTHOR]

• Model-based recursive partitioning (MOB) produces similar crash frequency model estimation compared to heterogeneity model. • MOB algorithm improves predictive power relative to traditional safety and heterogeneity models based on hold-out sample. • MOB is promising alternative to traditional count regression models to identify covariate subgroup patterns in safety data. • The posted speed limit and the presence of a passing zone were key splitting variables in the MOB algorithm. • Traffic volume and horizontal curve density were identified as random parameters in heterogeneity model. Count regression models have been applied widely in traffic safety research to estimate expected crash frequencies on road segments. Data mining algorithms, such as classification and regression trees, have recently been introduced into the field to overcome some of the assumptions associated with statistical models. However, these data-driven algorithms usually provide non-parametric output, making it difficult to draw statistical inference or to evaluate how independent variables are associated with expected crash frequencies. In this paper, the model-based recursive partitioning (MOB) algorithm is applied in a crash frequency application. The algorithm incorporates the concept of recursive partitioning data in tree models and develops user-defined statistical models as outputs. The objective of this paper is to explore the potential of the MOB algorithm as a methodological alternative to parametric modeling methods in crash frequency analysis. To accomplish the objective, a standard negative binomial (NB) regression model, a NB model developed using the MOB algorithm, adjusted NB models which incorporate variables identified by the MOB algorithm, and a random parameters NB model are compared using 8 years of data collected from two-lane rural highways in Pennsylvania. The models are compared in terms of data fitness, sign and magnitude of statistical association between the independent and dependent variables, and predictive power. The results show that the MOB-NB model yields better data fitness than other NB models, and provides similar performance to the RPNB model, suggesting that the MOB-NB model may be capturing unobserved heterogeneity by dividing the data into subgroups. The presence of a passing zone and posted speed limit are two covariates identified by the MOB algorithm that differentiate variable effects among subgroups. In addition, the MOB-NB model provides the highest prediction accuracy based on the training and test data sets, although the difference among models is small. The comparison results reveal that the MOB algorithm is a promising alternative to identify covariates, evaluate variable associations and instability, and make predictions in a crash frequency context. [ABSTRACT FROM AUTHOR]

• SPFs developed using negative binomial (NB) and random parameters negative binomial (RPNB) modeling frameworks. • Fit and predictive power compared on both within sample and out-of-sample observations. • RPNB model provides better predictions than NB model when applied to within sample observations. • NB model provides better predictions than RPNB model when applied to out-of-sample observations. Negative binomial (NB) regression is among the most common statistical modeling methods used to model crash frequencies due to its simple functional form and ability to handle over-dispersion commonly found in crash data. However, a drawback of this approach is that regression parameters are assumed to be the same across observations, which could contribute to biased parameter estimates. To alleviate this concern, the random parameters negative binomial (RPNB) model was recently proposed, which allows regression parameters to differ across observations following some known distribution. The resulting coefficients should be less biased, and thus the RPNB approach is believed to provide a more accurate relationship between independent variables and expected crash frequency. However, the prediction accuracy of the RPNB model relative to the standard NB model has not been thoroughly evaluated, particularly with respect to out-of-sample observations for which unique random parameters cannot be estimated. In this paper, the predictive power of the RPNB and NB models are examined using two-lane rural highway data from three engineering Districts in Pennsylvania. Multiple evaluation metrics are applied—root-mean-square error (RMSE) and mean absolute error (MAE), coefficients from calibration functions and cumulative residual (CURE) plots—to assess each model type. The results show that the RPNB model outperforms the NB model when applied to within sample observations (i.e., those used to estimate the model) by making use of the observation-specific coefficients. However, the predictive power of the RPNB model appears to be similar to or slightly less precise than the traditional NB model when applied to out-of-sample observations. Since the RPNB model is estimated using a simulation-based approach, sensitivity tests were also performed to see how the parameter estimates change with the number of Halton draws used to perform the simulation. For the sample sizes used in this paper, the estimates were fairly insensitive when more than 50 Halton draws were used. The findings suggest that the RPNB model is more reliable when applied to the same set of sites that were used to estimate the model but might not be as robust as the traditional NB model when applied to other sites. [ABSTRACT FROM AUTHOR]

• The Just Beginning parenting intervention combined instructional videos and father-child play sessions with the aim of improving the quality of father-child interactions. • Using video-recordings of 152 father-child play sessions, we find a pattern of improvement across Just Beginning sessions on one indicator of positive father-child interaction quality, but we did not find statistically significant changes on several other indicators. • For non-resident fathers, the intervention was associated with growth in three indicators of parenting behaviors that are associated with healthy child development. The Just Beginning intervention aims to improve the quality of interactions between fathers with low income and their young children. This intervention was implemented at a fatherhood program site in Philadelphia, Pennsylvania. Fathers participated in up to five sessions of the Just Beginning program, which included unstructured play sessions with their young child. In this paper, we use growth curve models to estimate patterns of change across the five sessions in the quality of the father-child interactions, drawing on 152 video observations from 53 father-child dyads. We find that fathers' positive regard toward their children increased across JB sessions, but do not find statistically significant changes in other indicators of fathers' positive parenting behaviors or in fathers' negative parenting behaviors. Estimating results for non-resident and resident fathers, we find that improvements in positive parenting behaviors appeared to be larger and more widespread for non-resident fathers than they were for fathers who lived with their focal children. [ABSTRACT FROM AUTHOR]

How are new speakers of an endangered language created? In this paper we draw on a three-year ethnographic case study to explore the processes through which a group of learners at a Pennsylvania college came to be identified as speakers of Lenape, a language indigenous to the eastern United States. Using a communities of practice framework, we analyze how language learning was facilitated and how the identities of community members were negotiated and contested through processes of authentication. A community of practice lens affords a useful framework for understanding how this successful learning community functioned, and for identifying factors that may benefit other language revitalization initiatives. [ABSTRACT FROM AUTHOR]

Dense phase pneumatic conveying of pulverized fuel particles under high pressure is one of the key techniques in large scale gasification of coal and petroleum coke. The real time and continuous measurement of dense phase gas–solid flow parameters such as particle velocity, concentration and mass flow rate has great significance for the in-depth understanding of particle flow dynamic behaviors and the optimized design of the conveying system. In this paper, an integrated electrostatic sensor is designed and used to explore the flow characteristics of anthracite and petroleum coke particles on a dense phase pneumatic conveyor. The ring electrodes in the integrated sensor are capable of measuring the “mean” velocity of solid particles over the whole cross-section of the pipeline, while the arc electrodes are employed to determine the local velocity of particles near them. The experimental results on a dense phase pneumatic conveyor under high pressure demonstrate that the flow characteristics depend on the physical properties of solid particles and carrying gas. Petroleum coke particles are much easier to be suspended in the gas flow than the anthracite particles, but its flow stability is worse. The local velocities from the arc electrode pairs mounted on the top of the pipeline are usually higher than those from the arc electrodes on the bottom for a stratified flow. The velocity from the ring electrode pair, indicating the mean velocity of particles over the whole cross-section, is usually higher than the local velocities from the arc electrode pairs for a suspension flow. In addition, the relationship between the mass flow rate and charge level of dense phase pneumatically conveyed solid particles is very complicated due to the complexity of the particle flow and the charge level cannot be used to measure particle concentration or mass flow rate. [ABSTRACT FROM AUTHOR]

The IPCC recommends keeping the global average temperature increase well below 2 °C, if not below 1.5 °C, by 2100 to avoid the worst effects of climate change. This requires achieving carbon neutrality shortly after 2050. In the United States, industrial emissions represent 22% of greenhouse gas emissions and are particularly hard to decarbonize, because (1) the processes emit CO 2 as a byproduct of chemical reactions and (2) these industries require high-grade heat input. This study focuses on some of these industries, namely cement, lime, glass, and steelmaking. This work details the incumbent kiln and furnace technologies and explores the developing processes with examples of existing projects that aim to reduce carbon emissions, such as carbon capture and storage (CCS), fuel switching, and other technological changes. We provide tools to evaluate the most appropriate low-carbon solutions at existing facilities and on new-build infrastructure while taking into account the local context and resources. This paper highlights two states within the U.S. with a high concentration of cement, lime, glass, and steelmaking facilities, California and Pennsylvania. The emissions from cement, lime, and glass facilities in California total 8.5 MtCO 2 eq/yr. About 6.3 MtCO 2 /yr (7.1% of in-state industrial emissions) could be captured from cement and lime facilities, transported, and stored in sedimentary basins below the Central Valley. Replacing 20% of coal by biomass could also reduce the fossil emissions by 0.5 MtCO 2 /yr (6.2% of in-state industrial emissions) without making changes to the facilities. In Pennsylvania, heavy industry (cement, lime, glass, and steelmaking) emits about 9.4 MtCO 2 eq/yr. Most of the facilities are located near sedimentary basins, facilitating the development of CCS. In addition, the presence of low-carbon energy sources can help in the deployment of electrified processes. Also, industrial byproducts such as steel slag and fly ash can be reused in low-carbon concrete mix. As shown with these two examples, there are many strategies leading to the deep decarbonization of the economy and they need to be adapted to the local context. [ABSTRACT FROM AUTHOR]

This paper revisits the question of why more open countries tend to have bigger governments. We replicate successfully the main results of Ram (2009), who rejects the role of country size as an omitted variable. However, several extensions advise against a hasty conclusion: The results differ substantially depending on the data source used, the timeframe considered, the countries selected, and the way variables are measured. Specifically, we employ newer versions of the Penn World Table (PWT 7.1 and 8.0), allowing us to both extend the number of observations and the timeframe. We find evidence for the claim that smaller countries do indeed have bigger governments, especially when using the PWT 8.0 data, and Ram (2009) findings might be driven by the specific dataset used (PWT 6.1) and the countries included in that sample. Finally, we also conduct quantile regression analyses to pin down at which point of the distribution the suggested relationships come out. [ABSTRACT FROM AUTHOR]

To respond to the high prevalence of obesity and its associated health consequences, recent food research and policy have focused on neighborhood food environments, especially the links between health and retail mix, proximity of food outlets, and types of foods available. In addition, the social environment exerts important influences on food-related behaviors, through mechanisms like role-modeling, social support, and social norms. This study examined the social dynamics of residents' health-related food-shopping behaviors in 2010–11 in urban Philadelphia, where we conducted 25 semi-structured resident interviews—the foundation for this paper—in addition to 514 structured interviews and a food environment audit. In interviews, participants demonstrated adaptability and resourcefulness in their food shopping; they chose to shop at stores that met a range of social needs. Those needs ranged from practical financial considerations, to fundamental issues of safety, to mundane concerns about convenience, and juggling multiple work and family responsibilities. The majority of participants were highly motivated to adapt their shopping patterns to accommodate personal financial constraints. In addition, they selectively shopped at stores frequented by people who shared their race/ethnicity, income and education, and they sought stores where they had positive interactions with personnel and proprietors. In deciding where to shop in this urban context, participants adapted their routines to avoid unsafe places and the threat of violence. Participants also discussed the importance of convenient stores that allowed for easy parking, accommodation of physical disabilities or special needs, and integration of food shopping into other daily activities like meeting children at school. Food research and policies should explicitly attend to the social dynamics that influence food-shopping behavior. In our social relationships, interactions, and responsibilities, there are countless opportunities to influence—and also to improve—health. [ABSTRACT FROM AUTHOR]

Law enforcement officers continue to serve on the front lines as mental health interventionists, and as such have been subject to a wave of "first generation" reform designed to enhance their crisis response capabilities. Yet, this focus on crisis intervention has not answered recent calls to move "upstream" and bolster early intervention in the name of long-term recovery. This paper reports on findings from an action research project in Philadelphia aimed at exploring opportunities for enhanced upstream engagement. Study methods include spatial analyses of police mental health transportations from an eight year period (2004-2011) and qualitative data from twenty-three "framing conversations" with partners and other stakeholders, seven focus groups with police and outreach workers, five key informant interviews as well as document reviews of the service delivery system in Philadelphia. Recommendations include the need to move beyond a focus on what police can do to a wider conception of city agencies and business stakeholders who can influence vulnerable people and vulnerable spaces of the city. We argue for the need to develop shared principles and rules of engagement that clarify roles and stipulate how best to enlist city resources in a range of circumstances. Since issues of mental health, substance use and disorder are so tightly coupled, we stress the importance of establishing a data-driven approach to crime and disorder reduction in areas of the city we term "hotspots of vulnerability". In line with a recovery philosophy, such an approach should reduce opportunities for anti-social behavior among the "dually labeled" in ways consistent with "procedural justice". Furthermore, crime and disorder data flowing from police and security to behavioral health analysts could contribute to a more focused case management of "repeat utilizers" across the two systems. Our central argument is that a twin emphasis on "case management" and "place management" may provide the pillars needed to move upstream and strengthen interventions along a continuum of engagement. [ABSTRACT FROM AUTHOR]

In recent years, a large number of building energy consumption prediction models, with various intended uses, have been proposed. The majority of these models have either taken a data-driven or a physical modeling approach, with each approach having its own strengths and limitations. Towards leveraging the strengths and reducing the limitations of each approach for improved prediction performance, this paper presents a hybrid machine-learning approach for occupant-behavior-sensitive energy consumption prediction. The proposed approach is composed of three constituent models: (1) a machine-learning model that learns the impact of outdoor weather conditions from simulation-generated data, (2) a machine-learning model that learns the impact of occupant behavior from real data, and (3) an ensemble model that predicts cooling energy consumption based on the outputs of the first two models. The simulation-generated data were created through simulating a set of reference buildings in EnergyPlus. The real data were collected from an office building in Pennsylvania. The proposed hybrid model was validated on an unseen real dataset. It achieved 0.73 kWh RMSE and 9.07% CV in hourly cooling energy consumption prediction, which indicates that the proposed approach is promising. [ABSTRACT FROM AUTHOR]

• The problem of historical steel truss bridges preservation is presented. • A novel hybrid deductive failure analysis approach (Analytical Fault Tree - AFT) is developed. • Numerical models investigate fault scenarios including fatigue and concurring causes. • AFT and fault scenarios are applied to a historical bridge located in the East of Spain. • Guidelines and conservation strategies are obtained for the investigated bridge. Historical steel bridges represent an important construction typology integrating the constructive heritage of the past century that needs to be preserved. Exposure to fatigue phenomenon, aging, improper design or execution, extreme events, and other aggressive environmental agents can seriously compromise the conservation and performance of these structures as some recent catastrophic collapses have shown (Mississippi River bridge, Minneapolis, Minnesota 2007; Kinzua Bridge State Park, Pennsylvania 2003). In this context, the diagnostic of historical steel bridges becomes of basic importance to identify and implement maintenance, monitoring and conservation strategies. Fault Trees are useful tools for practitioners that provide a complete overview of possible failures. In the related literature, this instrument is mainly applied with approaches that are based on previous experience or failures detected in similar structures, and so the Fault Tree can only provide qualitative support. This paper proposes a new method to achieve an "Analytical" Bridge Fault Tree linking the technician's experience and the numerical simulations of different fault scenarios. The latter are achieved by a numerical model able to consider fatigue failure and different concurring causes in the analysis (e.g., and aggressive phenomena, corrosion, defects, lack of maintenance). The proposed approach was applied to a historical railway steel truss bridge located in the East of Spain (Valencia Region) in order to show its applicability and potential. [ABSTRACT FROM AUTHOR]

Since the Pennsylvania oil rush of 1859, petroleum has quickly become the dominant fuel of industrial society. The "Peak Oil" debate focused on whether or not there was an impending production crunch of cheap oil, and whilst there have been no shortages across the globe, a shift from conventional to unconventional oil liquids has occurred. One aspect of this shift was not fully explored in previous discussions–although of some importance in a low-carbon energy transition context: the extent to which the net-energy supply of oil products is affected by the use of lower quality energy sources. To fill this gap, this paper incorporates standard EROI (energy-return-on-investment) estimates and dynamic decline functions in the GlobalShift all-liquids bottom-up model on a global scale. We determine the energy necessary for the production of oil liquids (including direct and indirect energy costs) to represent today 15.5% of the energy production of oil liquids, and growing at an exponential rate: by 2050, a proportion equivalent to half of the gross energy output will be engulfed in its own production. Our findings thus question the feasibility of a global and fast low-carbon energy transition. We therefore suggest an urgent return of the peak oil debate, but including net-energy issues and avoiding a narrow focus on 'peak supply' vs 'peak demand'. [Display omitted] • Global gross and net-energy of oil liquids production is determined from 1950 to 2050. • Energy required for production is estimated to be 15.5% of the actual gross energy. • Oil liquids become a limit to a rapid and global low-carbon energy transition. • The peak supply vs. peak demand dispute needs to be re-examined. • Focus should be put instead on net-energy transition and wise energy consumption. [ABSTRACT FROM AUTHOR]

• Probabilistic life-cycle cost analysis for concrete bridge decks under corrosion. • Agency and user cost quantification for decks with different reinforcement types. • Detailed traffic delay estimation based on vehicle queuing and traffic control procedures. • Analyze effect of concrete cover, bridge location, traffic volume, and number of lanes. • Optimum deck reinforcement selection based on bridge attributes and life-cycle cost. Reinforced concrete bridge decks with conventional reinforcement may experience deterioration due to deicing salts or marine environmental conditions. Routine maintenance, rehabilitation, and repair activities are implemented to maintain an acceptable performance level. In addition to the significant financial resources required to conduct these activities, traffic congestions at work zones can lead to an increase in delays and crash risk for road network users, as well as other environmental and social impacts. These user costs arising from traffic congestions can be significantly higher than the cost of maintenance, rehabilitation, and repair activities. Despite the higher initial unit cost, bridge decks constructed with corrosion resistant reinforcement can provide a longer service life and require less maintenance activities. Accordingly, from a life-cycle cost perspective, corrosion resistant reinforcement could be a better alternative compared to conventional reinforcement for bridge decks. This paper presents a probabilistic framework to estimate the life-cycle cost associated with bridge decks constructed with different reinforcement alternatives. The framework accounts for reinforcement deterioration to evaluate the maintenance activity timeline considering influential corrosion-related parameters (e.g., reinforcement type, concrete cover, and bridge location, among others). Key attributes affecting traffic delays, including traffic volume, number of lanes, and vehicular queuing, are also included in the framework. Monte Carlo simulation is used to predict the corrosion-induced cracking time, service life of the bridge deck, and the life-cycle cost under uncertainty. A bridge located in Pennsylvania is used as an illustrative example to demonstrate the application of the proposed framework. The results show that the concrete cover, chloride exposure condition, average daily traffic, and number of traffic lanes have a significant effect on the life-cycle cost of reinforced concrete bridge decks; especially for those constructed with conventional reinforcement. The presented framework can be beneficial in selecting the optimum bridge deck reinforcement type from a life-cycle cost perspective. [ABSTRACT FROM AUTHOR]

• New SPF functional form proposed that allows traffic volume to have different elasticities in different ranges. • Proposed form allows for continuous relationship between predicted crash frequency and traffic volume. • Proposed models shown to better fit observed data that traditional and other forms. Statistical models of expected crash frequency are referred to as Safety Performance Functions (SPFs) in the first edition of the American Association of State Highway and Transportation Officials' Highway Safety Manual (HSM). The SPFs in the HSM specify expected annual crash frequencies as a function of various roadway and roadside features, with the most important predictor variable being traffic volume, which serves as a measure of vehicle exposure to crashes. Traffic volumes are typically measured using the average annual daily traffic and are incorporated into the SPFs using a natural logarithm transformation. This specification suggests that the relationship between expected crash frequency and traffic volume increases non-linearly with a constant elasticity over the range of observed values. While researchers concur that the relationship between expected crash frequencies and traffic volume is non-linear, further exploration of the functional form of this relationship may offer additional insights concerning the association between safety performance and vehicle exposure. This paper proposes an alternative functional form for the traffic volume variable in SPFs that allows for different elasticities between traffic volume and expected crash frequency within different traffic volume ranges, while preserving the same general non-linear relationship in existing HSM SPFs. Although other forms—like the Hoerl function—have been proposed in the literature, the proposed model allows for natural breakpoints in the traffic volume for which roadway or geometric features might have varying effects on low- or high-volume roads. The proposed functional form was applied to SPFs developed for two-lane rural roadways in Pennsylvania. Comparisons with SPFs developed using the traditional and Hoerl functional forms suggest that this proposed functional form offers an improved fit and predictive performance, and thus might be considered for the development of future SPFs. [ABSTRACT FROM AUTHOR]

Background: Opioid overdoses are primarily discussed by the pharmacological properties of the drugs used. Research shows that other factors such as the social/physical environment and the mental/emotional states can have an impact on overdose events. Ataiants and colleagues (2020) used Zinberg's "drug, set, and setting" framework to identify circumstances surrounding overdose experiences of street-involved women in Philadelphia. The aim of this paper is to extend their analysis to a diverse sample of suburban women who experienced overdoses.Methods: The mixed-methods design consisted of ethnographic fieldwork, in-depth interviews, and brief surveys with 32 suburban women who use opioids. Inductive theoretical reasoning and constant comparative analysis facilitated themes emerging within the "drug, set, and setting" framework.Results: Eighteen out of 32 women identified "drug" as the primary factor involved in their overdose events. Major themes were an inability to identify the synthetic opioid fentanyl, lack of knowledge or control over how much to use, poly-substance use, and an insufficient understanding of risks. Eleven out of 32 women linked "set" to their overdose experiences. Themes included emotional trauma, such as death of a child, child custody issues, and mental health conditions, such as depression. Six out of 32 women associated "setting" with one of their overdose experiences. Themes were related to being with friends or partners that used, and having recently been released from treatment or incarceration.Conclusion: Findings show similar themes found among an urban sample, adding insight on the need for effective overdose interventions targeted for suburban populations. The opioid crisis is not confined to the cities, and neither should services aimed at addressing opioid overdose. The knowledge provided here can help policy makers support female-centered harm reduction services not only in urban areas but also in the suburbs. [ABSTRACT FROM AUTHOR]

Around the globe, governments are experimenting with lowering the voting age to 16-years-old as a way to turn around recent declines in civic participation. However, one concern is that younger voters will be more susceptible to parental and community influence. We used voter records from two U.S. states to explore stability and change in partisan identifications as a function of age in order to assess the likelihood that younger voters are more susceptible to social influences. In general, little evidence was found to suggest that teenagers' partisan identifications are substantially more influenced by families, communities, and historical events than older adults. In a final set of analyses, we examined partisan identification from voter records in Takoma Park, Maryland after it lowered the voting age to 16. To test for an effect of lowered voting age, we compared household voting patterns over time in Takoma Park to those in Maryland and Pennsylvania. A time series analysis did not show any difference between patterns in Takoma Park and patterns in Maryland and Pennsylvania, suggesting that lowering the voting age had no discernable impact on partisan identifications. The paper contributes to the expanding research base indicating that lowering the voting age has no apparent ill-effects on young people or their communities and will increase the political representation of an age cohort that can vote responsibly. • Identification with a political party is highly stable, even in adolescence. • Change in party identification is largely unaffected by moving away from family, community partisanship, and discrete historical events. • Lowering the voting age to 16 does not intensify parental influence on their children's partisan identifications. [ABSTRACT FROM AUTHOR]

Introduction: Drug overdose is a significant public health problem, yet little is known about racial/ethnic differences in drug overdose rates and/or in responses to a drug overdose following naloxone administration. This paper examines differences in rates of survivorship, response, revival and administration of naloxone by race and ethnicity among those who experienced a drug overdose in Pennsylvania between January 1, 2018 and December 31, 2019. Spatio-temporal variations in drug overdose locations were examined to facilitate understanding of service development, planning, and delivery of effective treatment need.Methods: Ten thousand two hundred and ninety drug overdose incidents were analyzed from the Pennsylvania Overdose Information Network (ODIN). The ODIN is a centralized repository that contains information on drug overdoses victims including age, gender and race/ethnicity, naloxone administrations and survivorship, drug(s) suspected of causing the overdose, victim outcomes (e.g. hospitalizations and arrests) and average naloxone dosage per victim. Between group differences were tested using χ2 -tests of independence. Multivariate logistic regression was used to estimate the predicted probability of survivorship according to victim characteristics. All statistical analyses and mapping were performed using the R statistical programming environment.Results: About eighty-seven percent of drug overdose response victims were white, and seventy-one percent were between the ages of 20-39. White females were more likely to receive an overdose response compared to black or Hispanic females. A non-opioid was indicated more frequently in overdoses involving black victims compared to either whites or Latinos. Latinos and blacks were more likely to survive a drug overdose. However, following naloxone administration, no racial or ethnic differences in survivorship were noted. Differences in responsiveness to naloxone and transitions to care following the drug overdose event were also found. Finally, overdoses among Blacks and Latinos demonstrated a stronger spatial patterning across counties compared to whites.Conclusions: This study found a significant, disparate impact of race/ethnicity on fatal drug overdoses when naloxone is not administered. Further, individuals who were administered naloxone and subsequently received medical care in a hospital experienced lower drug-related mortality, suggesting that first responders are critical intervention points for individuals in need of medical treatment following a drug overdose. However, while naloxone administration is a necessary first step in the recovery process, longitudinal pathways towards treatment are critical to stem the drug overdose crisis. [ABSTRACT FROM AUTHOR]

• Background is provided about the need for tools to support regional energy baselining and efficiency planning. • 296 homes in Pennsylvania are simulated in EnergyPlus using a batch simulation tool and energy audit records. • Simulation results are scaled and compared to building level electricity use data and utility sales data. • Analysis reveals discrepancies between simulated and actual energy use that varies by utility. • The role of building simulation tools for energy baselining and efficiency planning is discussed. Building simulation tools are seeing growing use in the residential sector due to a combination of increased interest in building energy performance, more user-friendly software packages, and decreasing computing power requirements. These tools are now being applied in batch simulations, where large numbers of homes are simulated at once to understand existing building stock energy consumption and potential energy efficiency improvements to make to those stocks. As these types of applications grow, attention is needed to ensure that simulation inputs and outputs are handled with an appropriate understanding of the uncertainties involved. In this paper, we use a batch simulation tool to translate energy audit records of 296 existing single-family homes in Pennsylvania into EnergyPlus building simulation models. We compare the results of these simulations to actual metered electricity use data from these homes, representative device-level data, and local utility data to better understand the abilities and limits of such modeling practices. Results show that while batch simulations are capable of producing accurate estimates of the energy consumption of a large number of homes, many more homes had their energy consumption overestimated than underestimated, resulting in a significant net overestimate for the sample as a whole. When results are scaled up to the utility level, simulation accuracy varies by utility with net overestimates ranging from around 15% to 25%. Comparisons of individual simulation results to metered consumption identify electric space heating systems as the source of much of this error. This highlights the importance of gathering accurate, detailed information on these systems to generate reliable simulation results. NREL has recently released a batch simulation tool called ResStock that takes a more statistically robust approach to simulating representative archetype homes as opposed to actual existing homes. The results of this study suggest that the type of probabilistic treatment of building characteristics underlying that tool will provide more meaningful results than trying to simulate actual buildings. With additional validation measures similar to those used in this study, ResStock can likely be used to reliably estimate baseline energy consumption and quantify efficiency savings opportunities and can serve as a valuable decision-making tool for state, local, and utility efficiency program designers. [ABSTRACT FROM AUTHOR]

In this paper, we examine the attitudes, experiences, and perceptions of health care among unauthorized immigrant women in Philadelphia, Pennsylvania. Research on health care utilization among undocumented immigrants usually focuses on barriers to securing health care access, but little attention has been paid to how these barriers shape patients' experiences. Patients' experiences are important because they affect persistence in care seeking, adherence to treatment regimens, and self-reported health. Drawing from interviews with undocumented Mexican women, we find that receptionists, staff, and social workers play an important role in shaping women's perceptions of health care. In contrast to previous research which finds that negative experiences with providers lead undocumented immigrants to withdraw from seeking medical services, without fail, our respondents persisted and sought care elsewhere. This strategy ensured that all women eventually found care with which they were satisfied, but sometimes after significant delays. • Unique focus on health care experiences of undocumented Mexican immigrant women. • Considers how barriers to health care affect perceptions of care. • Argues that perceptions of care are shaped by non-medical staff, such as receptionists and social workers. [ABSTRACT FROM AUTHOR]

Background: Malnutrition screening is an important first step in identifying hospitalized inpatients at risk for increased lengths of stay, mortality, and morbidity. Methods: The dietetic intern completed the MST using a paper form one day per week for 7 weeks. A list of newly admitted adult patients was gathered from the electronic medical report inpatient length of stay at UVAHS within 1 hour of the dietetic intern conducting MST screenings. A total of 85 patients were screened by the dietetic intern. After the MST was conducted, information was gathered from patients medical records: age, sex, admission date and time, unit, primary diagnosis, nursing completion of the MST, and nursing MST score (if applicable). A Weighted Cohens Kappa test was used to assess interrater reliability between the dietetic intern and nursing, including the probability that the scores were the same by chance. Results / Outcomes: Nursing screened 67 out of the 85 patients (78.8%) seen by the dietetic intern. The Weighted Cohens Kappa test showed moderate interrater reliability between dietetic intern and nursing scores (Kappa score = 0.498). Out of a total of 85 patients screened for malnutrition by the dietetic intern, 20 out of the 85 (24%) were not triggered to see a registered dietitian nutritionist (RDN) due to nursing either not filling out the MST or filling it out incorrectly. Twelve out of the 67 (18%) patients screened by RNs as not being at risk were at risk for malnutrition based on dietetic intern screening. Eight out of 18 (44%) patients that nursing did not screen were at risk for malnutrition based on dietetic intern screening. Conclusions: Nursing screened 78.8% of patients for malnutrition using the MST. This is slightly higher than 75% that was seen in recent small random audits completed at UVAHS. Twenty out of 85 (24%) patients were missed due to nursing either not filling out the MST or filling it out incorrectly. Results indicate a potential knowledge deficit amongst nursing regarding how to conduct malnutrition screening. Results also indicate a need for improved compliance with use of the MST to ensure at-risk patients are referred to RDNs. [ABSTRACT FROM AUTHOR]

Research outcome: Excessive sodium consumption is a worldwide public health concern. The purpose of this study was to evaluate a Sodium Reduction Initiative (SRI) at hospital cafeterias. Methods: A comprehensive nutrient analysis was conducted before and after the SRI to calculate average sodium offered on menus from six hospital cafeterias. The Food Satisfaction Survey, a 10-item paper questionnaire, was used to assess food satisfaction among cafeteria customers (n=l,678) before and at six-month intervals after sodium reduction up to 18 months. Analysis: Foods were classified as low sodium (<350 mg for entrees, <235 mg for sides) and by category: broth/soups, dairy, meat/main entree, sauces/ condiments, seasonings, grains/desserts, vegetables, and combination foods. Food satisfaction data was analyzed using ANOVA to compare satisfaction across time points. Results: A total of 66 foods were impacted resulting in a reduction of 145 mg average sodium offered on the menus. Low sodium foods increased by 16% and the majority of foods offered (>70%) were low sodium. Targeted foods were primarily sauces/condiments (n=17), meat/main entrees (n=13), vegetables (n=12), and seasoning (n=12). Most foods were reduced by <200 mg of sodium (n=34). Foods reduced by >500 mg (n=12) of sodium were sauces/ condiments (n=4), broths/soups (n=3), vegetables. (n=3) and seasonings (n=2). Food satisfaction did not differ among targeted foods from baseline to follow-up. One target item increased from baseline (M=3.4, SD=1.3) to follow-up (M=4.0, SD=1.3, F (3,409)=2.709, p=0.45). Conclusions: The SRI successfully lowered sodium, increased the number of low sodium options, and did not negatively affect food satisfaction at hospitals. [ABSTRACT FROM AUTHOR]

Introduction: Per the Academy and the US Breastfeeding Committee (USBC), practicing RDNs should have a minimum level of breastfeeding (BF) competency to provide patient care. The objective of this cross-sectional study was to assess RDN knowledge of BF core competencies (CC). Methods: A random sample of RDNs, provided by CDR, were invited to complete an online survey examining their knowledge of the CCs outlined in the Academy's practice paper and USBC standards, yielding a total CC knowledge score (maximum score=16). Demographics and knowledge were examined using descriptive statistics. RDNs were grouped as either currently working with pregnant or BF mothers (RDN-CW) or not (RDN-NC). Results: Participants (n=434, 99.1% female, 18-66+y) scored an average of 12.1 ±3.5. Scores of RDN-CW (n=72,13.5±2.7) were significantly higher than RDN-NC (n=362, 11.9±3.5, p=0.001). Compared to RDN-NC, a greater percentage of RDN-CW “strongly agreed" that they had adequate knowledge about breast anatomy and physiology (25% vs 11%, p=0.001) and were adequately prepared to obtain infant nutrition histories (39 % vs. 12%, p<0.001). While more than half of all RDNs indicated their BF knowledge came from personal experience, RDN-CW reported it came from on the job training most often. Conclusions: Immersion in this practice area increases perceived competency, which may lead to RDNs providing effective, comprehensive services to mothers, children and families. Advanced efforts should be made to increase exposure of RDNs to pregnant and BF mothers in both the preparation of future RDNs and through professional development. [ABSTRACT FROM AUTHOR]

Food insecurity, a major health crisis, is defined as the lack of consistent access to enough food for an active, healthy life, Hunger among undergraduates has been associated with additional missed classes, increased course drop rates, and the inability to afford textbooks. This study examined rates and perceptions of food insecurity among undergraduates at South Carolina 2- and 4-year higher education public institutions. The USDA’s 10- item Food Security Model Survey, food insecurity perception items, and demographics were included in a 2018 online and paper/pencil survey [N= 1088; Female-78.57%; White-60.65%; 4-year students-68.3%; 18-29 years old-90.18%) which was disseminated at ten 4-year and three 2-year public institutions. Significant differences were found for students scoring as having low/very low food security by institution type (2-year: 16.92%; 4-year: 11.06%, X2 (1, N=1087)=5.26, p<,05], T-tests revealed significant differences in food insecurity perceptions (1: strongly agree; 5: strongly disagree) for 'only people in poverty experience food insecurity” (2-year: M=3.61, SD=1.09); (4-year: M=3.77, SD=.87, p<.05), “there are plenty of resources available for healthy food" (2-year: M=3.19, SD=1.26); (4-year: M=2.92, SD=1.16, pc.Ol), and "food insecurity is due to high groceiy store prices on healthy foods" (2-year: M=2.12, SD=1.03); (4-year: M=2.42, SD=,98, p<.0001). Low/very low food secure students had significant differences in Government loan [Loan: 14.50%; No loan: 10.52%, X2 (1, N=1068)=3.87, p<,05] and Pell grant participation (Pell Grant: 17.24%; No Pell Grant: 8.0%, X2 (1, N=1068)CT1.06, p<.0001]. Evaluating food insecurity on college campuses is critical to successfully implement educational initiatives and improve campus resources to promote academic success. [ABSTRACT FROM AUTHOR]

Background/Objective: To transition clinical preceptors of the Rutgers University Dietetic Internship (DI) into the online learning environments. Methods: For the 2018-2019 academic year, we provided students with iPads and clinical preceptors with access to the online learning platform to access all pre-rotation reading materials, schedules, and assignments for all clinical rotations used by the DI faculty and students. We converted pre-rotation assignments to self-scoring via the learning platform and also transitioned from paper to electronic evaluations of interns' performance via an electronic survey. Access to the online learning platform allowed preceptors to have electronic access to all programmatic learning materials, reduced academic burden of grading pre-rotation assignments, and improved compilation of clinical performance scores and feedback for interns and DI faculty. Interns submitted key rotation assignments and self, site and preceptor evaluations online. Shared drives were used to consolidate individual intern's products and evaluations. Conclusions: Incorporating clinical preceptors into the online learning environment used by the DI faculty and students was successful and early feedback suggests this was considered a favorable benefit. Intern support assisted with transition. The transitions required dedicated time by program personnel upfront however resulted in quicker and easier compilation of preceptor evaluations. Preceptor feedback will be collected at the end of the academic year and challenges and obstacles will be shared. [ABSTRACT FROM AUTHOR]

Residents' participation is key to the success of urban tree planting programs, yet a gap between resident intentions and participation actions may limit the benefits provided by such programs. Philadelphia Parks and Recreation (Pennsylvania, US) has conducted tree giveaway events for residents since 2012 with the goal of increasing tree canopy. But some residents who register for giveaway events do not follow through and attend the event, creating logistical and planning difficulties that increase program costs. We tested whether phone call reminders could narrow the intention-action gap and increase the likelihood that registered residents attend a yard tree giveaway event. A total of 251 people registered for a spring 2018 giveaway event. Registered participants were randomly assigned to receive either a standard set of email and paper reminders representing normal program operations (126 participants), or to receive up to two phone call reminder attempts in addition to the standard reminders (125 participants). The follow-through (attendance) rate among registered participants who received phone calls was compared to those who did not receive phone calls. The phone calls increased attendance by 16 percentage points, a statistically significant increase. Based on this effect size and time spent making phone calls, staff spent an average of 12.4 min making phone calls per additional attendee. This study demonstrates the feasibility of using an experimental approach to facilitate evidence-based decisions in an urban tree planting context. Further research is needed to evaluate the impacts of communication strategies on resident behavior in tree planting and distribution programs. [ABSTRACT FROM AUTHOR]

Background The Philadelphia Ujima Coalition for a Healthier Community (Philadelphia Ujima) promotes health improvement of girls, women, and their families using a gender framework and community-based participatory research approach to addressing gender-based disparities. Institutional policies developed through community-based participatory research approaches are integral to sustaining gender-integrated health-promotion programs and necessary for reducing gender health inequities. This paper describes the results of a policy analysis of the Philadelphia Ujima coalition partner sites and highlights two case studies. Methods The policy analysis used a document review and key informant interview transcripts to explore 1) processes that community, faith, and academic organizations engaged in a community participatory process used to develop policies or institutional changes, 2) types of policy changes developed, and 3) initial outcomes and impact of the policy changes on the target population. Results Fifteen policies were developed as a result of the funding from the U.S. Department of Health and Human Services Office on Women's Health. Policy changes included 1) healthy food options guidance, 2) leadership training on sexual and relationship violence, and 3) curricula and programming inclusion and expansion of a sex and gender focus in high school and medical school. Conclusions Organizational practice changes and policies can be activated through individual-level interventions using a community participatory approach. This approach empowers communities to play an integral role in creating health-promoting policies. [ABSTRACT FROM AUTHOR]