Refined-scale panel data crash rate analysis using random-effects tobit model

Random effects tobit models are developed in predicting hourly crash rates with refined-scale panel data structure in both temporal and spatial domains. The proposed models address left-censoring effects of crash rates data while accounting for unobserved heterogeneity across groups and serial correlations within group in the meantime. The utilization of panel data in both refined temporal and spatial scales (hourly record and 1-mile roadway segments on average) exhibits strong potential on capturing the nature of time-varying and spatially varying contributing variables that is usually ignored in traditional aggregated traffic accident modeling. 1-year accident data and detailed traffic, environment, road geometry and surface condition data from a segment of I-25 in Colorado are adopted to demonstrate the proposed methodology. To better understand significantly different characteristics of crashes, two separate models, one for daytime and another for nighttime, have been developed. The results show major difference in contributing factors towards crash rate between daytime and nighttime models, implying considerable needs to investigate daytime and nighttime crashes separately using refined-scale data. After the models are developed, a comprehensive review of various contributing factors is made, followed by discussions on some interesting findings.     

Investigation of seasonal variations of Beijing pavement condition data using unevenly spaced dynamic panel data model

Beijing municipal highway administration started to collect pavement condition data on its major expressways since 2006. It is advised in the Chinese practice standard that data collection shall be conducted on annual basis. However, pavement data are usually collected at different seasons of the year, which may cause significant seasonal variations in the observed condition. Moreover, for some reasons, data are missing for some of the pavement sections at certain years, which could bring up difficulties in performance model estimation and inference. These concerns have been simply neglected in past practice. This study proposed an unevenly spaced dynamic panel data model to investigate the seasonal patterns of a performance indicator called Ride Quality Index (RQI). A quasi-differencing approach was adopted for the estimation. Data collected from the 5th Ring Road of Beijing were used in the case study. It was found that RQI data collected during the fall season are expected to be lower than that collected during the spring or summer seasons. Findings from this research would be helpful to pavement engineers in using unevenly spaced pavement condition data for future condition estimation.     

The efficiency analysis of container port production using DEA panel data approaches

Applications of Data Envelopment Analysis (DEA) to container port production have been largely restricted to standard DEA models using cross-sectional data. The efficiency results derived may be biased; for instance, as the result of random effects or a recent investment in future production. In overcoming this problem, panel data on container port production may be more suitable for medium- to long-term efficiency analysis. This paper evaluates available DEA panel data approaches by applying them to a sample of 25 leading container ports. Empirical results validate the necessity of utilizing panel data and reveal that considerable waste exists in container port production. It also provides a basis for assessing the competitiveness of container ports, for benchmarking best practice and identifying specific sources or causes of inefficiency.     

A state-based peridynamic model for quantitative fracture analysis

A new state-based peridynamic model is proposed to quantitatively analyze fracture behavior (crack initiation and propagation) of materials. In this model, the general relationship of the critical stretch and the critical energy release rate is for the first time obtained for the state-based peridynamic model of linear elastic brittle materials, and the released energy density is defined to quantitatively track the energy released during crack propagation. The three-dimensional (3D) and two-dimensional (2D) (for both plane stress and plane strain) cases are all considered. As illustrations, the compact tension and double cantilever beam tests are analyzed using the proposed model, which is capable of successfully capturing fracture behaviors (e.g., crack path and concentration of strain energy density) of the considered fracture tests. The characteristic parameters (i.e., critical load, critical energy release rate, etc.) are calculated and compared with available experimental and numerical data in the literature to demonstrate validity of the proposed model.     

A dynamic analysis of motorcycle ownership and usage: A panel data modeling approach

This study aims to develop motorcycle ownership and usage models with consideration of the state dependence and heterogeneity effects based on a large-scale questionnaire panel survey on vehicle owners. To account for the independence among alternatives and heterogeneity among individuals, the modeling structure of motorcycle ownership adopts disaggregate choice models considering the multinomial, nested, and mixed logit formulations. Three types of panel data regression models – ordinary, fixed, and random effects – are developed and compared for motorcycle usage. The estimation results show that motorcycle ownership in the previous year does exercise a significantly positive effect on the number of motorcycles owned by households in the current year, suggesting that the state dependence effect does exist in motorcycle ownership decisions. In addition, the fixed effects model is the preferred specification for modeling motorcycle usage, indicating strong evidence for existence of heterogeneity. Among various management strategies evaluated under different scenarios, increasing gas prices and parking fees will lead to larger reductions in total kilometers traveled.     

Motivating business towards innovation: A panel data study using dynamic capability framework

National strategic dynamic capabilities refer to the nations' ability to acquire, develop, and transfer national resources into innovation. This would help provoke firms and individuals’ capabilities to sense and seize to expedite innovative performance transformation. This study suggests that through the dynamic capabilities (DC) framework, the government can increase Innovation by channelizing the economic innovation system indicators. Macroeconomic indicators from 62 countries were taken to assess the significance of indicator-based dynamic capabilities model. The results confirm that sensing and seizing indices motivate Innovation, while the cost of business negatively moderates sensing. This model suggests that governments can motivate Innovation by exploring the indicators which are determining the sensing and seizing environment of decision-makers in businesses.     

Software for quantitative proteomic analysis using stable isotope labeling and data independent acquisition

Many software tools have been developed for analyzing stable isotope labeling (SIL)-based quantitative proteomic data using data dependent acquisition (DDA). However, programs for analyzing SIL-based quantitative proteomics data obtained with data independent acquisition (DIA) have yet to be reported. Here, we demonstrated the development of a new software for analyzing SIL data using the DIA method. Performance of the DIA on SYNAPT G2MS was evaluated using SIL-labeled complex proteome mixtures with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10) and compared with the DDA on linear ion trap (LTQ)-Orbitrap MS. The DIA displays relatively high quantitation accuracy for peptides cross all intensity regions, while the DDA shows an intensity dependent distribution of H/L ratios. For the three proteome mixtures, the number of detected SIL-peptide pairs and dynamic range of protein intensities using DIA drop stepwise, whereas no significant changes in these aspects using DDA were observed. The new software was applied to investigate the proteome difference between mouse embryonic fibroblasts (MEFs) and MEF-derived induced pluripotent stem cells (iPSCs) using (16)O/(18)O labeling. Our study expanded the capacities of our UNiquant software pipeline and provided valuable insight into the performance of the two cutting-edge MS platforms for SIL-based quantitative proteomic analysis today.     

Nonlinear hygro-thermo-elastic vibration analysis of doubly curved composite shell panel using finite element micromechanical model

Nonlinear free vibration behavior of laminated composite curved panel under hygrothermal environment is investigated in this article. The mathematical model of the laminated panel is developed using Green–Lagrange-type geometrical nonlinearity in the framework of higher-order mid-plane kinematics. The corrugated composite properties are evaluated through the micromechanical model and all the nonlinear higher-order terms are included in the present model for the sake of generality. The equation of vibrated panel is obtained using Hamilton's principle and discretized with the help of the finite element steps. The solutions are computed numerically using the direct iterative method. The effect of parameters on the nonlinear vibration responses is examined thoroughly by solving the wide variety of numerical examples.     

Performance modelling of a solar road panel prototype using finite element analysis

Performance prediction is a critical step towards the acceptance of a new pavement structure. This is true for both conventional and innovative designs; however, it is particularly important for innovative designs that attempt to redefine pavement design practices. One such innovative design concept is the solar road panel; a road panel with a transparent surface that generates electricity through embedded solar cells. Despite the work completed by multiple organisations towards the development of this concept, questions exist about the viability of these panels as a structural pavement surface. This paper investigates these questions through a finite element modelling approach that assesses a prototype panel's performance on a variety of structural bases. Overall, this paper finds that it is possible to design a solar road panel to withstand traffic loading and that a concrete structural base allows for substantial optimisation to the analysed prototype design.     

A correlation algorithm for the automated quantitative analysis of shotgun proteomics data

Quantitative shotgun proteomic analyses are facilitated using chemical tags such as ICAT and metabolic labeling strategies with stable isotopes. The rapid high-throughput production of quantitative "shotgun" proteomic data necessitates the development of software to automatically convert mass spectrometry-derived data of peptides into relative protein abundances. We describe a computer program called RelEx, which uses a least-squares regression for the calculation of the peptide ion current ratios from the mass spectrometry-derived ion chromatograms. RelEx is tolerant of poor signal-to-noise data and can automatically discard nonusable chromatograms and outlier ratios. We apply a simple correction for systematic errors that improves the accuracy of the quantitative measurement by 32 +/- 4%. Our automated approach was validated using labeled mixtures composed of known molar ratios and demonstrated in a real sample by measuring the effect of osmotic stress on protein expression in Saccharomyces cerevisiae.     

A finite element analysis of rubber coextrusion using a power-law model

A finite element method to simulate coupled thermal viscous coextrusion is presented, with a power-law viscosity function obtained from viscometric data on rubber composites. It combines, by successive substitution iterations, some well-known schemes, such as streamline integration for updating interfaces and Lagrange-Galerkin treatment of the energy equation. Some details of the implementation are discussed. The method is then applied to a comparison of two pre-forming plates for the dual tuber head extruder of Farrel Corporation. Both the normal stress and the temperature at the interface suggest that the presence of a deflector deteriorates the adherence properties. This prediction is in agreement with operational experience.     

Component reliability assessment using quantitative and qualitative data

The estimation of a component failure rate depends on the availability of plant specific numerical data. The purpose of this study was development of a new method that explicitly includes numerical and linguistic information into the assessment of a specific failure rate. The basis of the method is the Bayesian updating approach. A prior distribution is selected from a generic database, whereas likelihood is assessed using the principles of fuzzy set theory. The influence of component operating conditions on component failure rate is modeled using a fuzzy inference system. Results of fuzzy reasoning are then used for building an appropriate likelihood function for the Bayesian inference.The method was applied on a high voltage transformer. Results show that with the proposed method, one can estimate the specific failure rate and analyze possible measures to improve component reliability. The method can be used for specific applications including components for which there is not enough numerical data for specific evaluation.     

Investment appraisal using quantitative risk analysis

Investment appraisal concerned with investments in fire safety systems is discussed. Particular attention is directed at evaluating, in terms of the Bayesian decision theory, the risk reduction that investment in a fire safety system involves. It is shown how the monetary value of the change from a building design without any specific fire protection system to one including such a system can be estimated by use of quantitative risk analysis, the results of which are expressed in terms of a Risk-adjusted net present value. This represents the intrinsic monetary value of investing in the fire safety system. The method suggested is exemplified by a case study performed in an Avesta Sheffield factory.     

加筋板总体失稳分析的等效层合板模型

基于等效刚度的思想,通过设定层合板的属性参数模拟了加筋板结构的力学特性,提出了一种适用于不同截面形状以及布局形式的加筋板总体失稳分析的等效层合板建模方法。利用PATRAN/NASTRAN 软件比较了反映实际壁板形状的高精度有限元模型与对应的赋有层合板属性的等效刚度简化模型。对于工程中常见形状的加强筋以及不同布局形式的壁板,2种模型的一阶线性失稳因子基本一致,从而验证了将等效层合板模型用于加筋壁板结构的稳定性分析可以满足工程精度要求,并显著提高了计算效率。     

A CERIF data model extension for evaluation and quantitative expression of scientific research results

This paper presents a proposal of CERIF data model extension for evaluation of scientific research results. The data model extension is based on the CERIF semantic layer which enables classification of entities and relations between entities according to some classification scheme. The proposed data model was created using PowerDesigner CASE tool. The model is represented using a physical data model in the conceptual notation that is adopted in literature for representing the CERIF data model. This model is verified using the rule book for evaluation and quantitative expression of scientific research results of researchers employed at University of Novi Sad.     

High-throughput comparative proteome analysis using a quantitative cysteinyl-peptide enrichment technology

A new quantitative cysteinyl-peptide enrichment technology (QCET) was developed to achieve higher efficiency, greater dynamic range, and higher throughput in quantitative proteomics that use stable-isotope labeling techniques combined with high-resolution liquid chromatography (LC)-mass spectrometry (MS). This approach involves (18)O labeling of tryptic peptides, high-efficiency enrichment of cysteine-containing peptides, and confident protein identification and quantification using the accurate mass and time tag strategy. Proteome profiling of na?ve and in vitro-differentiated human mammary epithelial cells using QCET resulted in the identification and quantification of 603 proteins in a single LC-Fourier transform ion cyclotron resonance MS analysis. Advantages of this technology include the following: (1) a simple, highly efficient method for enriching cysteinyl-peptides; (2) a high-throughput strategy suitable for extensive proteome analysis; and (3) improved labeling efficiency for better quantitative measurements. This technology enhances both the functional analysis of biological systems and the detection of potential clinical biomarkers.     

Wing-body interference using a hybrid panel method

Summary The problem of determining the pressures acting on bodies in the region of wing-body interference in subsonic, inviscid flows is dealt with in detail in the current paper in the framework of a hybrid vortex lattice/first order panel method. Here the lift carryover and the wing-body interference effects are accounted for by the use of interpenetrating singularity panels. The non-lifting components are modeled by constant source panels and lifting elements by horse shoe vortices. Several alternative models have been programmed to study their effects on the pressure distribution in the wing-body interference region. The final procedure has been validated by comparing the pressures from experiments for several wing-body combinations.Notation AR Wing aspect ratio - b Wing span - B Body - C _p ,C _p Pressure coefficient,P-P /1/2 U ² - ,n Unit normal to panel; also direction of normal - r(p, q) Distance between two points in three dimensional space; especially between a point where a source is located and a point where the velocities are computed - U ,V _FS Free stream velocity - V _B Velocity due to body sources - V _D Velocity due to distributed vortices - V _T Velocity due to wing thickness sources - V _P Total velocity at pointP - V _c+ Velocity due to camber and incidence - W Wing - X _B Distance along length of body - Angle of attack - , Vortex strength - Air density - Azimuthal distribution of panels on fuselage - Non-dimensional spanwise station - Source density - Free stream conditions     

Data-reduction method for spatial data using a structured wavelet model

Recent advances in sensor instrumentation have provided opportunities for process engineers to collect data at various process steps in order to detect process problems and develop remedial procedures. This article presents a structured wavelet model for the reduction of two-dimensional data having distinct structures. The wavelet component of our model can handle irregular data patterns exhibiting many peaks and valleys, while the existence of a distinct data structure prompts the use of polynomial functions on wavelet coefficients. The two-dimensional antenna data is reduced with a structured wavelet model followed by some procedures for the detection of process defects based on the reduced-size data. A real-life example is presented to illustrate the usefulness of the proposed tools in detecting process problems from a potentially large volume of data exhibiting many peaks and valleys.     

The relationship between technological innovation and green transformation efficiency in China: An empirical analysis using spatial panel data

Challenged by climate change and severe damage of the ecological environment caused by carbon emissions, the process of green transformation in the world has to be urgently accelerated. This study adopted the super-efficiency DEA method to calculate the green transformation efficiency (GTE) of 30 provinces of China (except for Tibet) from 2009 to 2018. From the perspective of the technological innovation process, a spatial Durbin model is further proposed to investigate the impacts of technology research and development (TERD) and technology commercialization (TECO) on GTEs. The results showed that: (1) both TERD and TECO exerted significant positive effects on GTEs in local provinces, while the TERD coefficient was higher than that of TECO. (2) The spillover effect of TERD on GTEs in neighboring provinces was significantly negative, while the spillover effect of TERD was significantly positive. (3) Although the interaction between TERD and TECO positively affected GTEs, it also exerted a negative spillover effect on GTE. These findings indicate that the government should include the spatial spillover effects of TERD and TECO on GTEs when designing policies in support of technological innovation activities that contribute to green transformation.