Exploring Traffic Speed Patterns for the Implementation of Variable Speed Limit (VSL) Signs

Traffic congestion is a prevalent issue during peak travel hours on roads in the United States. This study focuses on identifying suitable road links in Charlotte, North Carolina, for implementing variable speed limit (VSL) signs. Real-world traffic speed data collected over one year was analyzed to identify specific road links with favorable characteristics for VSL sign installations. The analysis considered weekdays, weekends, and specific times of the day to capture variations in speed patterns. The results revealed that roads with lower speed limits consistently experienced speeds exceeding the posted speed limits, suggesting additional enforcement or safety measures. For roads with higher speed limits, mean speeds were generally close to the speed limits, but the 85th percentile speeds exceeded them, indicating a potential need for speed management measures. Road links with a 45/50 mph speed limit display a unique pattern compared to other clusters. The mean speed on these roads decreases as the standard deviation increases. The findings contribute to understanding traffic speed patterns and provide valuable insights for transportation planning and management

Deep Learning, Machine Learning, or Statistical Models for Weather-related Crash Severity Prediction

Nearly 5,000 people are killed and more than 418,000 are injured in weather-related traffic incidents each year. Assessments of the effectiveness of statistical models applied to crash severity prediction compared to machine learning (ML) and deep learning techniques (DL) help researchers and practitioners know what models are most effective under specific conditions. Given the class imbalance in crash data, the synthetic minority over-sampling technique for nominal (SMOTE-N) data was employed to generate synthetic samples for the minority class. The ordered logit model (OLM) and the ordered probit model (OPM) were evaluated as statistical models, while random forest (RF) and XGBoost were evaluated as ML models. For DL, multi-layer perceptron (MLP) and TabNet were evaluated. The performance of these models varied across severity levels, with property damage only (PDO) predictions performing the best and severe injury predictions performing the worst. The TabNet model performed best in predicting severe injury and PDO crashes, while RF was the most effective in predicting moderate injury crashes. However, all models struggled with severe injury classification, indicating the potential need for model refinement and exploration of other techniques. Hence, the choice of model depends on the specific application and the relative costs of false negatives and false positives. This conclusion underscores the need for further research in this area to improve the prediction accuracy of severe and moderate injury incidents, ultimately improving available data that can be used to increase road safety

Low-Temperature and High-Pressure Induced Swelling of a Hydrophobic Polymer-Chain in Aqueous Solution

We report molecular dynamics simulations of a hydrophobic polymer-chain in aqueous solution between $260 {K}$ and $420 {K}$ at pressures of $1 {bar}$, $3000 {bar}$, and $4500 {bar}$. The simulations reveal a hydrophobically collapsed state at low pressures and high temperatures. At $3000 {bar}$ and about $260 {K}$ and at $4500 {bar}$ and about $260 {K}$, however, a transition to a swelled state is observed. The transition is driven by a smaller volume and a remarkably strong lower enthalpy of the swelled state, indicating a steep positive slope of the corresponding transition line. The swelling is stabilized almost completely by the energetically favorable state of water in the polymers hydrophobic first hydration shell at low temperatures. Although surprising, this finding is consistent with the observation of a positive heat capacity of hydrophobic solvation. Moreover, the slope and location of the observed swelling transition for the collapsed hydrophobic chain coincides remarkably well with the cold denaturation transition of proteins.Comment: 9 pages, 9 figures, twocolumn revte

A possible mechanism for cold denaturation of proteins at high pressure

We study cold denaturation of proteins at high pressures. Using multicanonical Monte Carlo simulations of a model protein in a water bath, we investigate the effect of water density fluctuations on protein stability. We find that above the pressure where water freezes to the dense ice phase ($\approx2$ kbar), the mechanism for cold denaturation with decreasing temperature is the loss of local low-density water structure. We find our results in agreement with data of bovine pancreatic ribonuclease A.Comment: 4 pages for double column and single space. 3 figures Added references Changed conten

TESTING AND MODELING HIGH STRAIN RATE FAILURE IN COMPOSITE MATERIALS

The use of fiber-matrix composite materials in military ordnance casings is of increasing interest to the U.S. Navy due to the potential for such casings to reduce collateral structure damage. In order to use fiber-matrix composite materials in such an application, the high strain rate failure characteristics of said materials must be well understood and capable of finite element (FE) implementation. This study evaluated the high strain rate behavior in relation to quasi-static behavior of a supplied carbon fiber material. Material samples were provided in three distinct composite layup orientations. High strain rate testing utilized a Charpy impact tester, and slow strain rate testing used a standard tensile tester. Experimental data revealed a rate-dependent failure strain in the composite matrix material and a rate-invariant failure strain in the carbon fiber. Material property data (including high strain rate effects) were passed into an impact specimen and tensile specimen ABAQUS FE model that used a pre-defined user subroutine capable of performing damage calculations on fiber-matrix composite materials. Additional impact tests used a load cell in order to create a time-dependent input force for the FE model (unique to each composite layup). The ABAQUS FE model produced results that were in agreement with the experimentally observed changes in composite layup material properties as functions of the applied strain rate.Office of Naval Researchhttp://archive.org/details/testingandmodeli1094562710Ensign, United States NavyApproved for public release; distribution is unlimited

Der Beitrag von Erfahrungen an den Entwicklungsprozessen zur Selbständigkeit

Mit der Arbeit wird der Versuch unternommen, den Zusammenhängen von Biographie- und individuellen Lernprozessen nachzugehen. Dies erfolgt am Beispiel von acht ostdeutschen ExistenzgründerInnen, die sich nach der Wende in den neuen Bundesländern im Lebensmitteleinzelhandel selbständig gemacht haben. Hierbei interessiert die Frage, inwieweit Erfahrungen den Lernprozeß behindert oder gefördert haben. Die Ergebnisse der Arbeit bestätigen die hohe Relevanz von Erfahrungen, Handlungsmustern und Verhaltensweisen und weisen auf die Bedeutung emotionaler Faktoren im Lernprozeß hin, die den Lernprozeß sowohl behindert, als auch gefördert haben. Die Autorin zieht hieraus den Schluß, daß individuelle Lernprozesse durch Lernberater zu begleiten und durch den Aufbau von Netzwerken zu unterstützen seien. Voraussetzung hierfür ist eine neue Lernkultur, die an den Biographie- und Kompetenzressourcen der Lerner ansetzt und dem Lehrenden eine beratende und moderierende Rolle im Lernprozeß zuweist. Wesentliche Grundlage sind kooperative und reflexive Kompetenzen und die Fähigkeit, eine vertrauensvolle Atmosphäre zu schaffen, in der sich beide Seiten öffnen können.This paper attempts to look into the interrelationships between biographical and individual learning processes. The work is based on the example of eight female persons who, following German reunification, became self-employed within the food retail trade in the former East German states. The question of interest here is, in how far past experiences have promoted or impeded the learning process. The results of this work confirm the high relevance of experiences, action patterns and behaviour, and point out the significance of emotional factors within the learning process, through which this process was both impeded as well as promoted. The author comes to the conclusion that individual learning processes should be accompanied by educational consultants and supported through the establishment of networks. A pre-requirement for this is a new learning culture that starts out with the biographical and competence resources of the learning person and assigns to the teaching person a counselling and presenting role within the process of learning. The essential fundamentals are co-operative and reflexive competencies and the ability to create a trusting atmosphere within which both sides can open themselves up

R-Nasalization in Hoocąk: a Diachronic and Synchronic Perspective

This thesis examines an understudied nasalization rule in Hoocąk, an endangered Siouan language, whereby the alveolar flap becomes nasalized after nasal vowels. Impressionistic descriptions suggest that this has developed in two ways over time: (1) the output was [ɾ͂] but is not [n] and (2) this nasalized flap previously did not feed a vowel nasalization rule wherein nasal consonants nasalize the following vowels, but now it does. These impressions are tested by a phonetic examination of two recordings. While there are phonological analyses of Hoocąk, no acoustic studies have yet been published. These acoustic description results are then discussed through the lens of exemplar theory as described in Bybee (2001) and Bermúdez-Otero’s life cycle of phonological sound change (2007, 2019) to understand historical sound change better