Incorporating weather into regionwide safety planning prediction models

Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity

Modelling Severity Level in Multi-vehicle Collision on Indian Highways

AbstractCrash injury severities are recorded in ordinal scales with fatal crashes ranking highest in the scale and property damage minor crashes ranking lowest in the scale. Various researchers have attempted to model injury severity outcomes by taking injury severity levels as either simple categorical variables or ordered categorical variables. The severity level of crashes vary with the collision partners, crash time, roadside activity characteristics and road inventory characteristics. Collision partner is the key attribute in determining the severity outcome of crashes, but severity of crashes vary even if the collision partners remain same. The influence of other factors on severity outcome may be fixed or random. This study makes an attempt to model the crash severity outcome for vulnerable road user involving crashes, crashes involving passenger cars and crashes involving only heavy vehicles using multinomial and ordered models. The model is developed using data from National Highway-6 (NH-6,West Bengal, India), considering crash time, roadside activity characteristics and road inventory details as contributing factors. The crash severity outcomes are categorized into three categories viz. minor injury crashes, major injury crashes and fatal crashes. The study also attempts to identify factors influencing higher severity crashes

Liberalization and Welfare Conditions of a Developing Economy: A General Equilibrium Analysis

The paper attempts to analyze the impact of trade liberalization policy, in terms of FDI, on the level of informal competitive wage rate as well as on the size of the informal sectors of a developing economy with dualistic economic structure in a general equilibrium framework. The wage rate earned by the informal workers has been considered here as a proxy for their living standard. In this paper it is found that FDI raises the level of wage rate of the informal workers and consequently raises their standard of living. It is also found in this paper that FDI expands both formal and informal manufacturing sectors in the urban areas whereas it contracts the rural agricultural informal sector. In this structure an attempt has also been made to analyze the effects on the welfare level of the economy for a drive towards liberalization through FDI by assuming Sen (1974) type social welfare function which considers inequality in income distribution

Liberalization and Welfare Conditions of a Developing Economy: A General Equilibrium Analysis

The paper attempts to analyze the impact of trade liberalization policy, in terms of FDI, on the level of informal competitive wage rate as well as on the size of the informal sectors of a developing economy with dualistic economic structure in a general equilibrium framework. The wage rate earned by the informal workers has been considered here as a proxy for their living standard. In this paper it is found that FDI raises the level of wage rate of the informal workers and consequently raises their standard of living. It is also found in this paper that FDI expands both formal and informal manufacturing sectors in the urban areas whereas it contracts the rural agricultural informal sector. In this structure an attempt has also been made to analyze the effects on the welfare level of the economy for a drive towards liberalization through FDI by assuming Sen (1974) type social welfare function which considers inequality in income distribution

Amino Acid Compositions of 27 Food Fishes and Their Importance in Clinical Nutrition

Proteins and amino acids are important biomolecules which regulate key metabolic pathways and serve as precursors for synthesis of biologically important substances; moreover, amino acids are building blocks of proteins. Fish is an important dietary source of quality animal proteins and amino acids and play important role in human nutrition. In the present investigation, crude protein content and amino acid compositions of important food fishes from different habitats have been studied. Crude protein content was determined by Kjeldahl method and amino acid composition was analyzed by high performance liquid chromatography and information on 27 food fishes was generated. The analysis showed that the cold water species are rich in lysine and aspartic acid, marine fishes in leucine, small indigenous fishes in histidine, and the carps and catfishes in glutamic acid and glycine. The enriched nutrition knowledge base would enhance the utility of fish as a source of quality animal proteins and amino acids and aid in their inclusion in dietary counseling and patient guidance for specific nutritional needs

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| < 0.03 at 95% confidence level. [Figure not available: see fulltext.