bluuebunny/crossref_metadata_2025_split huggingface dataset:
Satisfaction With Telephone Versus In-Person Interpretation Services in Limited English-Proficient Urogynecology Patients: A Randomized Controlled Trial
Authors: Taylor Danielle Lynn , Sierra Tania , Maheshwari Deepali , Hall Cynthia , Leung Katherine , Flynn Michael 
Published: July 2020

Objective
The objective of this study was to determine if in-person interpreters improve patient satisfaction scores compared with phone interpreters for urogynecology office visits in limited English proficient (LEP) patients.

Methods
Portuguese and Spanish LEP subjects were randomized to phone or in-person interpreter, and a 14-item questionnaire was administered with 3 subscales assessing the primary outcome of patient satisfaction with the interpreter, physician, and nursing. Subject demographics, English proficiency, overall health status, and yearly household income were recorded. Sample size calculations indicated that a mean difference of 12 in satisfaction scores could be detected with 44 subjects per arm. Analysis was conducted using descriptive statistics, and comparisons between the intervention versus control group were analyzed using Fisher exact test, Wilcoxon rank sum test, and linear regression.

Results
We enrolled and randomized 106 subjects, and 82 subjects completed the study. There was a statistically significant difference in subject satisfaction between randomization groups, favoring in-person interpreters. In the as-treated analysis, the median satisfaction score for the phone interpreter group was 92.9 and 100 for in-person interpreter group (P < 0.001). Linear regression adjusted for English proficiency showed that there was a difference between median scores of 7.14 (P = 0.002).

Conclusions
Portuguese and Spanish LEP patients experienced higher satisfaction scores for urogynecology office visits when in-person interpreters are used compared with a phone interpreter. Although we found a statistically significant difference between these groups, the clinical significance of our finding is less clear. This topic should continue to be investigated for the field of urogynecology and further studies are needed.
The association between level of trauma care and clinical outcome measures: A systematic review and meta-analysis
Authors: Van Ditshuizen Jan C. , Van Den Driessche Claire R.L. , Sewalt Charlie A. , Van Lieshout Esther M.M. , Verhofstad Michiel H.J. , Den Hartog Dennis 
Published: July 2020

BACKGROUND
With implementation of trauma systems, a level of trauma care classification was introduced. Use of such a system has been linked to significant improvements in survival and other outcomes.

OBJECTIVES
The aim of this study was assessing the association between level of trauma care and fatal and nonfatal outcome measures for general and major trauma (MT) populations.

METHODS
A systematic literature search was conducted using six electronic databases up to December 18, 2019. Studies comparing mortality or nonfatal outcomes between different levels of trauma care in general and MT populations (preferably Injury Severity Score of >15) were included. Two independent reviewers performed selection of relevant studies, data extraction, and a quality assessment of included articles. With a random-effects meta-analysis, adjusted and unadjusted pooled effect sizes were calculated for level I versus non–level I trauma centers.

RESULTS
Twenty-two studies were included. Quality of the included studies was good; however, adjustment for comorbidity (32%) and interhospital transfer (38%) was performed less frequently. Nine (60%) of the 15 studies analyzing in-hospital mortality in general trauma populations reported a survival benefit for level I trauma centers. Level I trauma centers were not associated with higher mortality than non–level I trauma centers (adjusted odd ratio, 0.97; 95% confidence interval, 0.61–1.52). Of the 11 studies reporting in-hospital mortality in MT populations, 10 (91%) reported a survival benefit for level I trauma centers. Level I trauma centers were associated with lower mortality than non–level I trauma centers (adjusted odd ratio, 0.77; 95% confidence interval, 0.69–0.87).

CONCLUSION
The association between level of trauma care and in-hospital mortality is evident for MT populations; however, this does not hold for general trauma populations. Level I trauma centers produce improved survival in MT populations. This association could not be proven for nonfatal outcomes in general and MT populations because of inconsistencies in the body of evidence.

LEVEL OF EVIDENCE
Systematic review and meta-analysis, level III.
Impact of helmet laws on motorcycle crash mortality rates
Authors: Notrica David M. , Sayrs Lois W. , Krishna Nidhi , Davenport Katherine P. , Jamshidi Ramin , McMahon Lisa 
Published: July 2020

BACKGROUND
Helmets are effective in reducing traumatic brain injury. However, population effects of helmet laws have not been well described. This study assesses the impact of helmet laws on the motorcycle (MC) fatality rate in the United States from 1999 to 2015.

METHODS
Fatality Analysis Reporting System MC fatalities (aged ≥16 years), crash characteristics, and MC-related laws were collected by year for all 50 states from 1999 to 2015 to create a pooled time series. Generalized linear autoregressive modeling was applied to assess the relative contribution of helmet laws to the MC fatality rate while controlling for other major driver laws and crash characteristics.

RESULTS
Universal helmet laws were associated with a 36% to 45% decline in the motorcycle crash mortality rate during the study period across all age cohorts (unstandardized regression coefficients are reported): 16 to 20 years, B = −0.45 (p < 0.05); 21 to 55 years, B = −0.42 (p < 0.001); 56 to 65 years, B = −0.38 (p < 0.04); and older than 65 years, B = −0.36 (p < 0.02). Partial helmet laws were associated with a 1% to 81% increase in the fatality rate compared with states with no helmet laws and a 22% to 45% increase compared with universal laws. Helmet usage did not attenuate the countervailing effect of weaker partial laws for 16 to 20 years (B = 0.01 [p < 0.001]). Other laws associated with a declining motorcycle crash mortality rate included the following: social host/overservice laws, 21 to 55 years (B = −0.38 [p < 0.001]); 56 to 65 years (B = −0.16 [p < 0.002]), and older than 65 years (B = −0.12 [p < 0.003]); laws reducing allowable blood alcohol content, 21 to 55 years (B = −4.9 [p < 0.02]); and laws limiting passengers for new drivers 16 to 20 years (B = −0.06 [p < 0.01]).

CONCLUSION
During the period of the study, universal helmet laws were associated with a declining mortality rate, while partial helmet laws were associated with an increasing mortality rate. Other state driver laws were also associated with a declining rate. In addition to universal helmet laws, advocating for strict alcohol control legislation and reevaluation of licenses in older riders could also result in significant reduction in MC-related mortality.

LEVEL OF EVIDENCE
Prognostic and epidemiological, level III.
Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging
Authors: Ning Kaida , Duffy Ben A. , Franklin Meredith , Matloff Will , Zhao Lu , Arzouni Nibal , Sun Fengzhu , Toga Arthur W. 
Published: July 2020

AbstractBrain aging trajectories among those of the same chronological age can vary significantly. Statistical models have been created for estimating the apparent age of the brain, or predicted brain age, with imaging data. Recently, convolutional neural networks (CNNs) have shown the potential to more accurately predict brain age. We trained a CNN on 16,998 UK Biobank subjects, and in validation tests found that it was more accurate than a regression model for predicting brain age. A genome-wide association study was conducted on CNN-derived predicted brain age whereby we identified single nucleotide polymorphisms from four independent loci significantly associated with brain aging. One locus has been previously reported to be associated with brain aging. The three other loci were novel. Our results suggest that a more accurate brain age prediction enables the discovery of novel genetic associations, which may be valuable for identifying other lifestyle factors associated with brain aging.
Outbreak of Covid-19 worldwide is on the decline -----Recurrent Neural Reinforcement Learning and Health Interventions to Curb the Spread of Covid-19 in the world
Authors: Ge Qiyang , Hu Zixin , Zhang Kai , Li Shudi , Lin Wei , Jin Li , Xiong Momiao 
Published: July 2020

AbstractAs the Covid-19 pandemic soars around the world, there is urgent need to forecast the expected number of cases worldwide and the length of the pandemic before receding and implement public health interventions for significantly stopping the spread of Covid-19. Widely used statistical and computer methods for modeling and forecasting the trajectory of Covid-19 are epidemiological models. Although these epidemiological models are useful for estimating the dynamics of transmission of epidemics, their prediction accuracies are quite low. Alternative to the epidemiological models, the reinforcement learning (RL) and causal inference emerge as a powerful tool to select optimal interventions for worldwide containment of Covid-19. Therefore, we formulated real-time forecasting and evaluation of multiple public health intervention problems into off-policy evaluation (OPE) and counterfactual outcome forecasting problems and integrated RL and recurrent neural network (RNN) for exploring public health intervention strategies to slow down the spread of Covid-19 worldwide, given the historical data that may have been generated by different public health intervention policies. We applied the developed methods to real data collected from January 22, 2020 to July 30, 2020 for real-time forecasting the confirmed cases of Covid-19 across the world. We observed that the number of new cases of Covid-19 worldwide reached a peak (407,205) on July 24, 2020 and forecasted that the number of laboratory-confirmed cumulative cases of Covid-19 will pass 20 million as of August 22, 2020. The results showed that outbreak of Covid-19 worldwide has peaked and is on the decline
Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction
Authors: Castro André Ferreira , Baltruschat Lothar , Stürner Tomke , Bahrami Amirhoushang , Jedlicka Peter , Tavosanis Gaia , Cuntz Hermann 
Published: July 2020

AbstractClass I ventral posterior dendritic arborisation (c1vpda) proprioceptive sensory neurons respond to contractions in theDrosophilalarval body wall during crawling. Their dendritic branches run along the direction of contraction, possibly a functional requirement to maximise membrane curvature during crawling contractions. Although the molecular machinery of dendritic patterning in c1vpda has been extensively studied, the process leading to the precise elaboration of their comb-like shapes remains elusive. Here, to link dendrite shape with its proprioceptive role, we performed long-term, non-invasive,in vivotime-lapse imaging of c1vpda embryonic and larval morphogenesis to reveal a sequence of differentiation stages. We combined computer models and dendritic branch dynamics tracking to propose that distinct sequential phases of targeted growth and stochastic retraction achieve efficient dendritic trees both in terms of wire and function. Our study shows how dendrite growth balances structure–function requirements, shedding new light on general principles of self-organisation in functionally specialised dendrites.In briefAn optimal wire and function trade-off emerges from noisy growth and stochastic retraction duringDrosophilaclass I ventral posterior dendritic arborisation (c1vpda) dendrite development.HighlightsC1vpda dendrite outgrowth follows wire constraints.Stochastic retraction of functionally suboptimal branches in a subsequent growth phase.C1vpda growth rules favour branches running parallel to larval body wall contraction.Comprehensive growth model reproduces c1vpda developmentin silico.
Disentangling Increased Testing from Covid-19 Epidemic Spread
Authors: Lengerich Benjamin , Neiswanger Willie , Lengerich Eugene J. , Xing Eric P. 
Published: July 2020

AbstractTo design effective disease control strategies, it is critical to understand the incidence of diseases. In the Covid-19 epidemic in the United States (caused by outbreak of the SARS-CoV-2 virus), testing capacity was initially very limited and has been increasing at the same time as the virus has been spreading. When estimating the incidence, it can be difficult to distinguish whether increased numbers of positive tests stem from increases in the spread of the virus or increases in testing. This has made it very difficult to identify locations in which the epidemic poses the largest public health risks. Here, we use a probabilistic model to quantify beliefs about testing strategies and understand implications regarding incidence. We apply this model to estimate the incidence in each state of the United States, and find that: (1) the Covid-19 epidemic is likely to be more widespread than reported by limited testing, (2) the Covid-19 epidemic growth in the summer months is likely smaller than it was during the spring months, and (3) the regions which are at highest risk of Covid-19 epidemic outbreaks are not always those with the largest number of positive test results.
Design of the rainfall index annual forage program
Authors: ShalekBriski Abby , Brorsen Wade , Rogers James K. , Biermacher Jon T. , Marburger David , Edwards Jeff 
Published: July 2020

PurposeThe authors determine the effectiveness of the Rainfall Index Annual Forage Program (RIAFP) in offsetting yield risk of winter annual forage growers. The authors also evaluate the effectiveness in reducing risk of potential alternative weather indices.Design/methodology/approachThe RIAFP is designed to compensate forage producers when yield losses occur. Prior research found weak correlation between the rainfall index and actual winter annual forage yields. The authors use long-term small-plot variety trials of rye, ryegrass, wheat, triticale and oats with rainfall recorded on site and measure the correlation of the index with actual rainfall and actual yields. The alternative indices include frequency of precipitation events and of days with temperature below freezing.FindingsThe correlation between actual rainfall and the current RMA index was strongly positive as in previous research. Correlations between forage yields and monthly intervals of the current RMA index were mostly statistically insignificant, and many had an unexpected sign. All indices had some correlations that were inconsistent across time intervals and forage variety. The inconsistent signs suggest a nonlinear relationship with weather and forage yield, indicating that rainfall can be too much or too little. The number of days below freezing has the most potential of the three measures examined.Practical implicationsProducers should view the winter forage RIAFP as a risk-increasing income-transfer farm program. A product to reduce the risk for forage producers may need to use a crop growth simulation model or another approach that can capture the nonlinearity.Originality/valueConsiderably more data were considered than in past research. Past research did not consider alternative weather indices. The program should be continued if its goal is to serve as disguised income transfer, but it should be discontinued if its goal is to reduce risk.
Mediated effect of export assistance on export performance of Serbian manufacturing SMEs
Authors: Njegić Katarina , Damnjanović Jelena , Komnenić Biserka 
Published: July 2020

PurposeThe purpose of this paper was to examine the intervening role of export-related resources in the relationship between export assistance (EA) and export performance (EP) as well as the role of competitive intensity as a driver for the adoption of EA programmes by small and medium-sized enterprises (SMEs).Design/methodology/approachThe proposed model was tested on the sample of 119 SMEs that export from the Republic of Serbia. The data were gathered through an online survey. In order to test the hypotheses, partial least squares structural equation modelling (PLS-SEM) was used.FindingsThe results revealed that export-related resources (intellectual, relational and managerial resources) fully mediate the relationship between EA and EP. It was shown that competitive intensity in export markets had a positive effect on the amount of EA that SMEs receive from the government, EU and other organisations.Research limitations/implicationsThe number of firms that participated in the survey is small. Furthermore, the responses may be biased due to the auto-selection of SMEs. The research included only SMEs from different manufacturing industries. Thus, the implications of the research cannot be applied to the service sector.Practical implicationsThe findings of the conducted research are relevant for the managers of SMEs since they show the importance of using EA as an external resource. The use of EA improves EP through the enhancement of intellectual, relational and managerial resources. The results of this study also support further government investment in EA as it was found that EA is an effective tool for the improvement of EP of SMEs.Originality/valueThe effect of EA on EP was tested in Serbia, the research context in which this effect was not tested before. Besides, the proposed model gives insights into the factors that affect engagement in EA programmes, which is a topic rarely examined in the literature.
Evaluation of the future adaptive reuse of Mashrooteh house using the adaptSTAR model
Authors: Sharifi Ali Asghar , Farahinia Amir Hossein 
Published: July 2020

PurposeThe concept of adaptive reuse is an effective strategy in enhancing the heritage assets economic, cultural and social values. The main purpose of this research is to determine how to increase the life of the heritage buildings thereby improving their sustainability and reducing energy consumption and waste, while preserving them from the risk of obsolescence.Design/methodology/approachThe qualitative method has been used in this research to evaluate the functional quality and sustainability of Mashrooteh house by using the adaptSTAR model with its scoring sheet with respective design criteria. Predicting and evaluating the sustainability and adaptability of the historic Mashrooteh house in Tabriz will ensure its reuse and increase its adaptability and future life.FindingsFindings have shown that to increase the adaptability and future life of Mashrooteh house, it requires the improvement of the physical, legal, technological and functional criteria in order to provide suitable conditions for increasing the environmental and functional sustainability of this heritage building, while improving the quality of its spaces.Originality/valueWith the emphasis on conservation of national heritage as well as promoting sustainable development, the overall service life of these structures can be extended. The significance of this study lies in recognizing the incompatibilities and potential of viable approaches to rehabilitate the volatile condition of Mashrooteh house. The result of this study will add value to existing sustainable reuse database in Tabriz and other countries in the Middle East region.
Entrepreneurial collaboration for R&D alliance performance: a role of social capital configuration
Authors: Seo Ribin 
Published: July 2020

PurposeDespite increasing research on the social nature of entrepreneurial collaboration in the context of alliances, its performance implication has been under debate. The present study tests a theoretical framework to elucidate the mediated relationship between social capital (SC) and research and development (R&D) alliance performance through the entrepreneurial orientation (EO) of alliance firms.Design/methodology/approachBased on the authors’ literature review, SC is conceptualized as the sum of actual and potential assets, including structural, relational and cognitive capital, embedded within the networks of alliance partners. Alliance performance is regarded as a combination of technological performance and business performance, corresponding to the mutual and private benefits of R&D alliances, respectively. This study hypothesizes the potential impact of SC on alliance performance and the mediating role of EO in the relationship.FindingsThe results from an analysis of 218 Korean ventures that participated in R&D alliance projects as focal alliance partners show that each SC dimension drives alliance firms to enact EO, which eventually leads to increased performance in technology and business. Specifically, EO contributes to translating the implications of SC for technological performance partially and for business performance completely.Originality/valueThis study links fragmented theoretical perspectives in research, shedding new light on the importance of social nature in the context of R&D alliances, which conditions entrepreneurial collaboration for better alliance performance. The findings suggest that practitioners should adopt an ambidextrous approach to the SC–EO interface at the alliance level, which opens a gateway to achieve greater performance by alliance.
Prioritizing distribution centers in humanitarian logistics using type-2 fuzzy MCDM approach
Authors: Yılmaz Hafize , Kabak Özgür 
Published: July 2020

PurposeLocating disaster response centers is one of the key elements of efficient relief operations. The location and infrastructure of the candidate facilities usually conform to the required criteria at different levels. This study aims to identify the criteria for the main and local distribution center location problem separately and prioritize each candidate distribution center using a hybrid multiple criteria decision-making approach.Design/methodology/approachThe proposed model incorporates analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) under interval type-2 fuzzy sets (IT2FSs) to overcome the uncertainty of experts` judgments and expressions in the evaluations of candidate distribution centers. In the proposed approach, weights of the criteria are determined using type-2 fuzzy AHP and the candidate distribution centers are prioritized using type-2 fuzzy TOPSIS.FindingsTransportation, cost, infrastructure and security are determined as the main criteria for the main distribution center location criteria. Cost, warehouse facilities and security are the main criteria for local distribution center location selection. Prioritization enables decision-makers to assess each alternative accordingly to be able to select the best locations/facilities for efficient disaster response operations.Originality/valueThis study proposes new multi-criteria decision support models for prioritizing disaster response distribution centers. IT2FSs are used to be able to reflect both the complexity and vagueness of disaster environment and expert opinions. Different support models are suggested for main and local distribution centers considering their different missions. The proposed methodology is applied in Istanbul city, Turkey, where a high-magnitude earthquake is expected.