Safety and Cost Performance of Intersection Lighting

It has been reported that nationwide, about one quarter of the roadway travel commonly occurs after dark and half of the roadway traffic fatalities occurred at night. The nighttime traffic crash fatality rate is about three times the daytime traffic crash fatality rate. The problem may become worse at unlit or poorly lit critical roadway safety spots such as interchange, intersections, and railroad and highway crossing, particularly in adverse weather conditions. This study was conducted to investigate the lighting effects on crashes at Indiana intersections. The analysis of Indiana nighttime crash data to identify the contributing factors was conducted. The study intersection sites were selected based on crash frequencies and crash severities. Before and after field light tests were conducted to verify in-service light performance, including illuminance distribution and uniformity ratio. AGi32 simulation was also performed for three selected intersections to compare with field test results. In addition, the long term performance of demonstration luminaires at the I-74 & US 231 interchange was tracked and documented. This activity provides a better understanding of maintenance issues, cycles, and costs. Surveys to both State Highway Agencies (SHAs) and communities were conducted in order to identify perceptions from SHAs and the public toward lighting improvement. The community survey included questions such as the public attitudes to intersection lighting, effectiveness of lighting, visibility improvement, and safety improvement. To quantify safety effects of lighting at intersections, crash modification factors (CMFs) were developed by using two methodologies: before-and-after analysis and cross-sectional statistical analysis. The developed CMFs could be used to justify roadway lighting projects. Life Cycle Cost Analysis (LCCA) was conducted to determine the best lighting solution given a real project scenario. The analysis considered initial (luminaire and installation) cost, operation and maintenance cost, and energy cost

High-performance real-world optical computing trained by in situ model-free optimization

Optical computing systems can provide high-speed and low-energy data processing but face deficiencies in computationally demanding training and simulation-to-reality gap. We propose a model-free solution for lightweight in situ optimization of optical computing systems based on the score gradient estimation algorithm. This approach treats the system as a black box and back-propagates loss directly to the optical weights' probabilistic distributions, hence circumventing the need for computation-heavy and biased system simulation. We demonstrate a superior classification accuracy on the MNIST and FMNIST datasets through experiments on a single-layer diffractive optical computing system. Furthermore, we show its potential for image-free and high-speed cell analysis. The inherent simplicity of our proposed method, combined with its low demand for computational resources, expedites the transition of optical computing from laboratory demonstrations to real-world applications

Making Multimodal Generation Easier: When Diffusion Models Meet LLMs

We present EasyGen, an efficient model designed to enhance multimodal understanding and generation by harnessing the capabilities of diffusion models and large language models (LLMs). Unlike existing multimodal models that predominately depend on encoders like CLIP or ImageBind and need ample amounts of training data to bridge the gap between modalities, EasyGen is built upon a bidirectional conditional diffusion model named BiDiffuser, which promotes more efficient interactions between modalities. EasyGen handles image-to-text generation by integrating BiDiffuser and an LLM via a simple projection layer. Unlike most existing multimodal models that are limited to generating text responses, EasyGen can also facilitate text-to-image generation by leveraging the LLM to create textual descriptions, which can be interpreted by BiDiffuser to generate appropriate visual responses. Extensive quantitative and qualitative experiments demonstrate the effectiveness of EasyGen, whose training can be easily achieved in a lab setting. The source code is available at https://github.com/zxy556677/EasyGen

A modified perioperative regimen for deceased donor kidney transplantation in presensitized recipients without prior desensitization therapy

BackgroundRenal transplantation in HLA-presensitized recipients entails an increased risk of antibody-mediated rejection (AMR) and graft loss. There is currently no accepted standard treatment protocol that can help transplant surgeons safely perform deceased donor (DD) kidney transplantation in presensitized patients without pretransplant desensitization.MethodsFifty-one panel-reactive antibody (PRA)-positive recipients and 62 PRA-negative retransplant recipients (control) who received DD renal transplantation were included. Patients in the presensitized group (donor-specific antibody [DSA]-positive, n=25; DSA-negative, n=26) without desensitization received a modified perioperative treatment starting on day 0 or -1 with rituximab, thymoglobulin, and low daily doses of intravenous immunoglobulin (IVIG, 10-20 g/d, for 14 days). Plasmapheresis was performed once before surgery in DSA-positive recipients.ResultsThe median follow-up time was 51 months in the presensitized group and 41 months in the control group. The incidence of early acute rejection (AR) and AMR (including mixed rejection) was 35.3% and 13.7% in the presensitized group, respectively, significantly higher than in the control group (14.5% and 1.6%, respectively). Within the presensitized group, the DSA-positive subgroup had more AMR than the DSA-negative subgroup (24.0% vs. 3.8%), but the incidence of T cell-mediated rejection was comparable (20.0% vs. 23.4%). In the presensitized group, all rejections were successfully reversed, and graft function remained stable during follow-up. The 1-year and 3-year survival rates of the grafts and recipients in this group were 98.0%.ConclusionWith a modified IVIG-based perioperative regimen, excellent intermediate-term graft and recipient survival outcomes can be achieved in presensitized patients who received DD kidney transplantation without prior desensitization

Friction Surface Treatment Selection: Aggregate Properties, Surface Characteristics, Alternative Treatments, and Safety Effects

This study aimed to evaluate the long term performance of the selected surface friction treatments, including high friction surface treatment (HFST) using calcined bauxite and steel slag, and conventional friction surfacing, in particular pavement preservation treatments such as chip seal, microsurfacing, ultrathin bonded wearing course (UBWC), and diamond grinding. This study also attempted to determine the correlation between vehicle crash and pavement surface friction, which makes it possible to quantitatively establish the so-called crash modification factors (CMFs) that are extremely useful in selecting a cost-effective solution to reduce wet pavement vehicle crashes. In-depth reviews were conducted to identify the aspects of the properties for aggregates used in HFST, including aggregate abrasion value (AAV), Los Angeles abrasion (LAA), Micro-Deval abrasion, and polished stone value (PSV). Extensive laboratory testing was conducted to examine the LAA, Micro-Deval abrasion, and PSV, and to provide first-hand data on the calcined bauxite and steel slag that may be used for HFST and friction surfacing in Indiana. Laboratory accelerating polishing was carried out to evaluate the effect of aggregate gradation and identify the HFST systems with satisfactory friction performance with respect to surface macro-texture and friction. Test strips were installed in the pavement on a real-world road to further evaluate the friction performances of the promising HFST systems under the true traffic polishing and assess the potential effect of winter and snow plough. Pull-off testing was also conducted to examine the bonding between the proposed HFST systems and the substrate surface. Field friction test data was utilized to evaluate the long-term friction performances of pavement preservation treatments, including chip seal, microsurfacing, UBWC, and diamond grinding. Statewide vehicle crash data between 2010 and 2014 was examined to determine the crash statistics associated with pavement friction. The crash data was also matched to the annual pavement inventory friction data to quantify the probabilistic association between vehicle crash and pavement friction with respect to interstate, US, and state highways, respectively. Specification requirements were established for the properties of calcined bauxite and steel slag for HFST and friction surfacing with respect to LAA, Micro-Deval abrasion, PSV, Al2O3 content, and fine aggregate angularity (FAA). Specification requirements were also developed for HFST aggregate gradation and surface friction performance. Regression models were developed for predicting the friction numbers of chip seal, microsurfacing, UBWC, and diamond grinding over their service lives. Regression models were also provided to quantify the effectiveness of friction surfacing for interstate, US, and state highways, respectively

Single-Trial EEG-fMRI Reveals the Generation Process of the Mismatch Negativity

Although research on the mismatch negativity (MMN) has been ongoing for 40 years, the generation process of the MMN remains largely unknown. In this study, we used a single-trial electro-encephalography (EEG)-functional magnetic resonance imaging (fMRI) coupling method which can analyze neural activity with both high temporal and high spatial resolution and thus assess the generation process of the MMN. We elicited the MMN with an auditory oddball paradigm while recording simultaneous EEG and fMRI. We divided the MMN into five equal-durational phases. Utilizing the single-trial variability of the MMN, we analyzed the neural generators of the five phases, thereby determining the spatiotemporal generation process of the MMN. We found two distinct bottom-up prediction error propagations: first from the auditory cortex to the motor areas and then from the auditory cortex to the inferior frontal gyrus (IFG). Our results support the regularity-violation hypothesis of MMN generation

Usefulness of soluble endothelial protein C receptor combined with left ventricular global longitudinal strain for predicting slow coronary flow: A case-control study

Background: Slow coronary flow (SCF) is an angiographic entity characterized by delayed coronary opacification without an evident obstructive lesion in the epicardial coronary artery. However, patients with SCF have decreased left ventricular (LV) global longitudinal strain (GLS). SCF is associated with inflammation, and soluble endothelial protein C receptor (sEPCR) is a potential biomarker of inflammation. Therefore, under evaluation herein, was the relationship between SCF and sEPCR and the predictive value of sEPCR and LV GLS for SCF was investigated. Methods: Twenty-eight patients with SCF and 34 controls were enrolled. SCF was diagnosed by the thrombolysis in myocardial infarction frame count (TFC). The plasma level of sEPCR was quantified using enzyme-linked immunosorbent assay. LV GLS was measured by two-dimensional speckle-tracking echocardiography. Results: Plasma sEPCR was significantly higher in patients with SCF than in controls and was positively correlated with the mean TFC (r = 0.67, p < 0.001) and number of involved vessels (r = 0.61, p < 0.001). LV GLS was decreased in patients with SCF compared to that in controls. sEPCR level (OR = 3.14, 95% CI 1.55–6.36, p = 0.001) and LV GLS (OR = 1.44, 95% CI 1.02–2.04, p = 0.04) were independent predictors of SCF. sEPCR predicted SCF (area under curve [AUC]: 0.83); however, sEPCR > 9.63 ng/mL combined with LV GLS > −14.36% demonstrated better predictive power (AUC: 0.89; sensitivity: 75%; specificity: 91%). Conclusions: Patients with SCF have increased plasma sEPCR and decreased LV GLS. sEPCR may be a useful potential biomarker for SCF, and sEPCR combined with LV GLS can better predict SCF