Data on highway maintenance, rehabilitation, and mobility projects for integrated planning in Texas.
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ABSTRACT:
SUBMITTER: France-Mensah J
PROVIDER: S-EPMC6717169 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Although a wide range of literature has investigated the network-level highway maintenance plans and policies, few of them focused on the maintenance scheduling problem. This study proposes a methodology framework to model and compare two different maintenance scheduling strategies for highway networks, i.e., minimal makespan strategy (MMS) and minimal increased travel delay strategy (MITDS). We formulate MMS as a mixed integer linear programming model subject to the constraints of the quantity of manpower and the worst-first maintenance sequence. A bi-level programming model is proposed to quantify and optimize MITDS. The upper level model determines the optimal scheduling to minimize the increased traffic delays during the maintenance makespan. In the lower level, a modified day-to-day traffic assignment model is put forward to reflect the traffic evolution dynamics by simulating travelers' route choice behaviors. A simulated annealing algorithm and augmented Lagrange algorithm are employed to solve the two proposed models, respectively. Finally, a numerical example using a highway network is developed. The two proposed strategies are tested considering different traffic demands, numbers of engineering teams, and travelers' sensitivities to traffic congestion. The experiment results reveal that compared with MMS, MITDS extends makespan by 2 days though, it reduces the total increased travel delays by 4% and both MMS and MITDS can obtain the minimum total increased travel delays when the number of engineering teams is 6. The sensitivity analysis indicates that both the two strategies have the maximum and minimum total increased travel delays when the weight of prediction in travelers' perception is 0.3 and 0.7, respectively. The proposed framework has the potential to provide reference in implementing highway maintenance activities reasonably.
| S-EPMC9176791 | biostudies-literature
Project description:BackgroundPatients undergoing hemodialysis have a high mortality rate and yet underutilize palliative care and hospice resources. The Shared Decision Making-Renal Supportive Care (SDM-RSC) intervention focused on goals of care conversations between patients and family members with the nephrologist and social worker. The intervention targeted deficiencies in communication, estimating prognosis, and transition planning for seriously ill dialysis patients. The intervention showed capacity to increase substantially completion of advance care directives. The HIGHway Project, adapted from the previous SDM-RSC, scale up training social workers or nurses in dialysis center in advance care planning (ACP), and then support them for a subsequent 9-month action period, to engage in ACP conversations with patients at their dialysis center regarding their preferences for end-of-life care.MethodsWe will train between 50-60 dialysis teams, led by social workers or nurses, to engage in ACP conversations with patients at their dialysis center regarding their preferences for end-of-life care. This implementation project uses the Knowledge to Action (KTA) Framework within the Consolidated Framework for Implementation Research (CFIR) to increase adoption and sustainability in the participating dialysis centers. This includes a curriculum about how to hold ACP conversation and coaching with monthly teleconferences through case discussion and mentoring. An application software will guide on the process and provide resources for holding ACP conversations. Our project will focus on implementation outcomes. Success will be determined by adoption and effective use of the ACP approach. Patient and provider outcomes will be measured by the number of ACP conversations held and documented; the quality and fidelity of ACP conversations to the HIGHway process as taught during education sessions; impact on knowledge and skills; content, relevance, and significance of ACP intervention for patients, and Supportive Kidney Care (SKC) App usage. Currently HIGHway is in the recruitment stage.DiscussionEffective changes to advance care planning processes in dialysis centers can lead to institutional policy and protocol changes, providing a model for patients receiving dialysis treatment in the US. The result will be a widespread improvement in advance care planning, thereby remedying one of the current barriers to patient-centered, goal-concordant care for dialysis patients.Trial registrationThe George Washington University Protocol Record NCR213481, Honoring Individual Goals and Hopes: Implementing Advance Care Planning for Persons with Kidney Disease on Dialysis, is registered in ClinicalTrials.gov Identifier: NCT05324878 on April 11th, 2022.
| S-EPMC9286956 | biostudies-literature
Project description:The datasets and tool presented in this article are related to the research article entitled "Improving crash predictability of the Highway Safety Manual through optimizing local calibration process" (Dadvar et al., 2020) [1], in which these datasets were used to investigate alternative local calibration methods for the Highway Safety Manual (HSM) [2] local application. The datasets are integrated Highway Safety Information System (HSIS) [3] state-wide rural two-lane, two-way roads (R2U) data from states of Illinois and Washington. The HSIS is a database that maintains motor vehicle crash data, roadway inventory, and traffic volume data for several US states. It is an excellent source of data to highway safety research and can be used to investigate many research questions. However, to prepare an analysis-ready roadway safety dataset based on the HSIS or any databases that store the relevant data in multiple different datasets, the researchers should integrate multiple datasets, merge or unmerge and remove certain inconsistent records, and finally clean the integrated dataset. The HSIS staff is usually accommodating and eager to help, but sometimes the nature of data needs is complicated and laborious. A tool named Roadway Safety Data Integrator (RSDI) was developed for combining, segmenting, and selecting homogeneous (unchanged during the study period for certain variables of interest) HSIS roadway segments and also crash assignment by desired crash attributes (e.g., crash severity or type). The RSDI tool can be helpful for integrating different safety-related datasets such as roadway inventory (including grade, curve, and other subsets), traffic volume, and motor vehicle crash data; also, it can do required segmentation and identify the homogeneous roadway segments over the desired years of study that are the basis for development and calibration of the HSM predictive models. The shared datasets contain homogeneous roadway segments, geometric details, and crash data for six years from Illinois (2005-10) and Washington (2010-15). The datasets and RSDI tool would be important sources generally for investigating highway safety research questions and in particular, for HSM-related analyses. The RSDI tool can be used for similar purposes and it is not limited to the HSIS data. It can be used for segmentation and finding homogeneous segments of any datasets that follow linear referencing. The datasets and RSDI tool are hosted in the Mendeley Data repository [4].
| S-EPMC7452693 | biostudies-literature
Project description:BackgroundIntegrated knowledge translation (IKT) can optimize the uptake of research evidence into clinical practice by incorporating knowledge users as equal partners in the entire research process. Although several studies have investigated stakeholder involvement in research, the literature on partnerships between researchers and clinicians in rehabilitation and their impact on clinical practice is scarce. This study described the individual research projects, the outcomes of these projects on clinical practice and the partnership experiences of an initiative that funds IKT projects co-led by a rehabilitation clinician and a researcher.MethodsThis was a sequential explanatory mixed methods study where quantitative data (document reviews and surveys) informed the qualitative phase (focus groups with researchers and interviews with clinicians). Descriptive analysis was completed for the quantitative data and thematic analysis was used for the qualitative data.Results53 projects were classified within multiple steps of the KTA framework. Descriptive information on the projects and outcomes were obtained through the survey for 37 of the 53 funded projects (70%). Half of the respondents (n = 18) were very satisfied or satisfied with their project's impact. Only two (6%) projects reported having measured sustainability of their projects and four (11%) measured long-term impact. A focus group with six researchers and individual interviews with nine clinicians highlighted the benefits (e.g. acquired collaborative skills, stronger networks between clinicians and academia) and challenges (e.g. measuring KT outcomes, lack of planning for sustainability, barriers related to clinician involvement in research) of participating in this initiative. Considerations when partnering on IKT projects included: the importance of having a supportive organization culture and physical proximity between collaborators, sharing motives for participating, leveraging everyone's expertise, grounding projects in KT models, discussing feasibility of projects on a restricted timeline, and incorporating the necessary knowledge users. Clinicians discussed the main outputs (scientific contribution, training and development, increased awareness of best practice, step in a larger effort) as project outcomes, but highlighted the complexity of measuring outcomes on clinical practice.ConclusionThe study provides a portrait of an IKT funding model, sheds light on past IKT projects' strengths and weaknesses and provides strategies for promoting positive partnership experiences between researchers and rehabilitation clinicians.
| S-EPMC6469130 | biostudies-literature
Project description:There have been growing research interests in finding a suitable work zone layout to improve work zone safety and traffic efficiency. This paper contains data supporting the research article entitled: Effects of work zone configurations and traffic density on performance variables and subjective workload (Shakouri et al., 2014 [1]). A full factorial experiment was conducted to compare the efficiency of two work zone configurations by using a driving simulator with two levels of work zone configuration, two levels of traffic density and three levels of sign placement as fixed factors. Seven female and 23 male participants completed the experiment. In this paper we present the data relating to demographic information of participants, driving simulator data and subjective workload evaluation of participants for each work zone.
| S-EPMC4749935 | biostudies-literature
Project description:The unpredictable elements involved in a vehicular traffic system, like human interaction and weather, lead to a very complicated, high-dimensional, nonlinear dynamical system. Therefore, it is difficult to develop a mathematical or artificial intelligence model that describes the time evolution of traffic systems. All the while, the ever-increasing demands on transportation systems has left traffic agencies in dire need of a robust method for analyzing and forecasting traffic. Here we demonstrate how the Koopman mode decomposition can offer a model-free, data-driven approach for analyzing and forecasting traffic dynamics. By obtaining a decomposition of data sets collected by the Federal Highway Administration and the California Department of Transportation, we are able to reconstruct observed data, distinguish any growing or decaying patterns, and obtain a hierarchy of previously identified and never before identified spatiotemporal patterns. Furthermore, it is demonstrated how this methodology can be utilized to forecast highway network conditions.
| S-EPMC7190853 | biostudies-literature
Project description:Reinforcement learning (RL) is a promising direction in automated parking systems (APSs), as integrating planning and tracking control using RL can potentially maximize the overall performance. However, commonly used model-free RL requires many interactions to achieve acceptable performance, and model-based RL in APS cannot continuously learn. In this paper, a data-efficient RL method is constructed to learn from data by use of a model-based method. The proposed method uses a truncated Monte Carlo tree search to evaluate parking states and select moves. Two artificial neural networks are trained to provide the search probability of each tree branch and the final reward for each state using self-trained data. The data efficiency is enhanced by weighting exploration with parking trajectory returns, an adaptive exploration scheme, and experience augmentation with imaginary rollouts. Without human demonstrations, a novel training pipeline is also used to train the initial action guidance network and the state value network. Compared with path planning and path-following methods, the proposed integrated method can flexibly co-ordinate the longitudinal and lateral motion to park a smaller parking space in one maneuver. Its adaptability to changes in the vehicle model is verified by joint Carsim and MATLAB simulation, demonstrating that the algorithm converges within a few iterations. Finally, experiments using a real vehicle platform are used to further verify the effectiveness of the proposed method. Compared with obtaining rewards using simulation, the proposed method achieves a better final parking attitude and success rate.
| S-EPMC7766926 | biostudies-literature
Project description:The red palm weevil Rhynchophorus ferrugineus is an invasive pest from southeastern Asia and Melanesia that has spread widely across the Middle East and the Mediterranean Basin over the last 30 years. Its endophagous larvae cause huge amounts of damage to several palm tree species from the Arecaceae family. Many of these palms are economically important for agricultural and ornamental purposes. Therefore, a lot of attention has recently been focused on studying this species with the aim of identifying sustainable and effective eradication strategies. Sterile insect techniques are biological control strategies that are currently being investigated for their potential to eradicate this pest in selected invasion areas. Mating system features (e.g., polyandry and related features) can affect the success and suitability of these approaches. The main goal of this research was to assess the performance of a previously developed microsatellite panel in terms of the paternity assignment of progeny from laboratory mating experiments. Using a simulation approach, we evaluated the reliability of the microsatellite markers in the paternity tests both in complex laboratory experiment scenarios and on the progeny of wild-caught gravid females to help future studies on the RPW mating system. As a case study of the simulation results, we performed two double-mating experiments, genotyped the progeny and estimated the P2 values to compare to the expected progeny genotypes according to the crossing scheme of each experiment. The results of our simulations on laboratory experiments showed that it was possible to carry out paternity assignments for all progeny with reliable statistical confidence using our 13 microsatellites set. On the contrary the low genetic variability measured in red palm weevil populations in invaded areas made the resolution power of our loci too low to carry out paternity analyses on natural populations. Results of laboratory crossing were completely congruent with the expectations from the Mendelian laws.
| S-EPMC10144754 | biostudies-literature
Project description:Against a backdrop of continued gender challenges within the European manufacturing and technology domains, and wider society in general, such as gender balance and inequality, the gender pay gap, the glass ceiling/sticky floor, the glass cliff, the invisible woman and the under-representation of women in STEM careers and senior positions, and framed within the latest European Commission guidelines and requirements on equality, diversity and inclusion, this paper will report on the actions and research undertaken by the voluntary Gender Action Planning (GAP) team within a large, multinational, complex Industry4.0 Horizon2020 research and innovation project to try to address gender inequalities and gender balance, as well as to provide safe spaces, supportive communities and raised awareness of gender issues over the four year lifespan of the project. It is hoped that the learning from the GAP team may provide a good exemplar for future Horizon programme proposal submissions where a Gender Plan is now a mandated requirement.
| S-EPMC10632589 | biostudies-literature
Project description:ObjectiveTo determine the effectiveness of Fragility Fracture Integrated Rehabilitation Management (FIRM) on mobility, activity of daily living and cognitive functioning in elderly with hip fracture.MethodsA randomized control trial was conducted at Seoul National University Bundang Hospital, South Korea from August 2017 to January 2018. Patients of both genders with the age 65-95 years, diagnosed cases of hip fracture specifically fractures neck of femur, intertrochanteric, subtrochantric, patients who got bipolar hemiarthroplasty, total hip replacement arthroplasty, reduction and internal fixation were included in this study. A total of n=39 sample was collected through non probability convenience sampling technique and randomly divided into Fragility Integrated Rehabilitation Management (FIRM) group (n=20) and Conventional Physical therapy (CPT) group (n=19). The data was collected through KOVAL for walking ability, modified barthal index (MBI) for behaviors related to activities of daily living (ADLS) and mini mental status examination (MMSE) for cognitive functions at baseline on 2nd postoperative day and after 10th FIRM session on 15th postoperative day.ResultsThe mean age of study participants was 82.07±6.00 years. The post intervention comparison did not show any significant difference (p>0.05) in walking ability, overall ADLs and cognitive functioning. But FIRM group showed significant improvement in stair climbing {0(5) ver. 2(7.5), p=0.049} and ambulation or walker use {8(5) ver. 2(4), p=0.037}, as compared to CPT group.ConclusionBoth groups improved in indoor mobility with walker and crutches as well as activities of daily living. But FIRM showed more improving ambulation with walker and stair climbing. While cognitive functioning was observed only in FIRM group.
| S-EPMC7372678 | biostudies-literature