Spatial performance of skewed continuous rigid-frame bridges based on finite element analysis

Continuous rigid-frame bridges are usually symmetrically designed along the bridge center line for simplicity and clarity purposes. However, the skewed bridges are necessary in case of complex intersections with space constraint in highways. Previous research mainly focuses on the discussion of skewed angle and the interaction between girders and cross frames on I shape section. Box sections are also used for skewed bridge due to large torsion stiffness, which have many problems during service time. This paper analyzed coupled skew and bending effect for the bridge which combines the continuous rigid-frame system and skewed system. For skewed bridges, significant out-of-lane effect occurs in bridges, which is hard to be predicted through linear analysis. For continuous bridges, at the interior supports, negative bending moments exist. In addition, a part of each diaphragm of the bridge is connected to the main girder, and the rest part only carries its self-weight, which makes the girder behavior more complex in the transverse direction. Therefore, the spatial performance of the bridge is very complex. The design cannot only use simple two dimension analysis. In the paper the three dimensional finite element analysis was conducted to find the effect due to dead load, live load, temperature, and brake force to find critical position for monitoring and maintainance. Primary bending normal stress, warping normal stress, coefficient of shearing force lag and stress distribution of consolidation pier were analyzed and output. The behavior of both superstructure and sub structure were investigated. The effect of coupled bending and torsion is significant to the behavior of the bridge. Finally the design recommendations about the skew bridge are given. The critical positions for the further test and monitoring are found

Genre analysis of research grant proposals.

This paper examines nine successful SSHRC (Social Sciences and Humanities Research Council of Canada) standard research grant proposals written by nine professors in the field of education at a Canadian university. The study follows the tradition of move analysis developed by Swales (1990) and Bhatia (1993) to describe the generic structures of the summary (one page) and main text (six pages) of the sample proposals. Findings suggest a three-move scheme of the summary and a ten-move scheme of the main text. Compared with a comparatively sequential move structure in the summary, the rhetorical structure of the main text with move recurrences and move mixing appears to be quite complex. The study addresses the issues of move recurrence and move mixing by revealing the grant writers’ rationale behind their discursive act. Based on the analyses of both textual and interview data, the study also describes and explains the rhetorical strategies the writers employed in achieving the promotional purposes and addressing the reviewer committee. Implications for move analysts and suggestions for grant proposal learner writers are also included

Dietary Flaxseed Oil Prevents Western-Type Diet-Induced Nonalcoholic Fatty Liver Disease in Apolipoprotein-E Knockout Mice

The prevalence of nonalcoholic fatty liver disease (NAFLD) has dramatically increased globally during recent decades. Intake of n-3 polyunsaturated fatty acids (PUFAs), mainly eicosapentaenoic acid (EPA, C20:5n-3) and docosahexaenoic acid (DHA, C22:6n-3), is believed to be beneficial to the development of NAFLD. However, little information is available with regard to the effect of flaxseed oil rich in α-linolenic acid (ALA, C18:3n-3), a plant-derived n-3 PUFA, in improving NAFLD. This study was to gain the effect of flaxseed oil on NAFLD and further investigate the underlying mechanisms. Apolipoprotein-E knockout (apoE-KO) mice were given a normal chow diet, a western-type high-fat and high-cholesterol diet (WTD), or a WTD diet containing 10% flaxseed oil (WTD + FO) for 12 weeks. Our data showed that consumption of flaxseed oil significantly improved WTD-induced NAFLD, as well as ameliorated impaired lipid homeostasis, attenuated oxidative stress, and inhibited inflammation. These data were associated with the modification effects on expression levels of genes involved in de novo fat synthesis (SREBP-1c, ACC), triacylglycerol catabolism (PPARα, CPT1A, and ACOX1), inflammation (NF-κB, IL-6, TNF-α, and MCP-1), and oxidative stress (ROS, MDA, GSH, and SOD)

Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers

Fog and Cloud Computing Assisted IoT Model Based Personal Emergency Monitoring and Diseases Prediction Services

Along with the rapid development of modern high-tech and the change of people's awareness of healthy life, the demand for personal healthcare services is gradually increasing. The rapid progress of information and communication technology and medical and bio technology not only improves personal healthcare services, but also brings the fact that the human being has entered the era of longevity. At present, there are many researches focused on various wearable sensing devices and implant devices and Internet of Things in order to capture personal daily life health information more conveniently and effectively, and significant results have been obtained, such as fog computing. To provide personal healthcare services, the fog and cloud computing is an effective solution for sharing health information. The health big data analysis model can provide personal health situation reports on a daily basis, and the gene sequencing can provide hereditary disease prediction. However, the injury mortality and emergency diseases since long ago caused death and great pain for the family. And there are no effective rescue methods to save precious lives and no methods to predict the disease morbidity likelihood. The purpose of this research is to capture personal daily health information based on sensors and monitoring emergency situations with the help of fog computing and mobile applications, and disease prediction based on cloud computing and big data analysis. Through the comparison of test results it was proved that the proposed emergency monitoring based on fog and cloud computing and the diseases prediction model based on big data analysis not only gain more of the rescue time than the traditional emergency treatment method, but they also accumulate lots of different personal healthcare related experience. The Taian 960 hospital of PLA and the Yanbian Hospital as IM testbed were joined to provide emergency monitoring tests, and to ensure the CVD and CVA morbidity likelihood medical big data analysis, the people around Taian city participated in personal health tests. Through the project, the five network layers architecture and integrated MAPE-K Model based EMDPS platform not only made the cooperation between hospitals feasible to deal with emergency situations, but also the Internet medicine for the disease prediction was built

Cell-free measurements of brightness of fluorescently labeled antibodies

Validation of imaging contrast agents, such as fluorescently labeled imaging antibodies, has been recognized as a critical challenge in clinical and preclinical studies. As the number of applications for imaging antibodies grows, these materials are increasingly being subjected to careful scrutiny. Antibody fluorescent brightness is one of the key parameters that is of critical importance. Direct measurements of the brightness with common spectroscopy methods are challenging, because the fluorescent properties of the imaging antibodies are highly sensitive to the methods of conjugation, degree of labeling, and contamination with free dyes. Traditional methods rely on cell-based assays that lack reproducibility and accuracy. In this manuscript, we present a novel and general approach for measuring the brightness using antibody-avid polystyrene beads and flow cytometry. As compared to a cell-based method, the described technique is rapid, quantitative, and highly reproducible. The proposed method requires less than ten microgram of sample and is applicable for optimizing synthetic conjugation procedures, testing commercial imaging antibodies, and performing high-throughput validation of conjugation procedures

Experimental and numerical study on column-foundation connection through external socket

In practice, bridge foundations and pier columns are usually constructed with cast-in-place concrete. Precast columns are currently widely used in highway bridges in China, which can save construction time and improve concrete quality. The connection between precast bridge columns and the foundation can affect how forces transfer from one to the other. This paper investigates using external sockets to form a connection between the bridge column and foundation. This method can accelerate the bridge construction time with the additional advantages of improving the orientation and creating a large erection tolerance. Two types of connections are presented and tested to investigate the behavior of the column-foundation connections and find a more suitable way to use external socket connections. The experimental results show that the column-foundation connection design satisfies the design requirements. The results also show that roughening the column surface within the external socket is more effective at connecting the column to the foundation when using an external socket compared to attaching a steel plate on the column. The experimental results are validated with a finite element analysis, resulting in a proposal regarding the column-foundation connection behavior as well as design recommendations for the external socket connection

Material extrusion filament width and height prediction via design of experiment and machine learning

The dimensions of material extrusion 3D printing filaments play a pivotal role in determining processing resolution and efficiency and are influenced by processing parameters. This study focuses on four key process parameters, namely, nozzle diameter, nondimensional nozzle height, extrusion pressure, and printing speed. The design of experiment was carried out to determine the impact of various factors and interaction effects on filament width and height through variance analysis. Five machine learning models (support vector regression, backpropagation neural network, decision tree, random forest, and K-nearest neighbor) were built to predict the geometric dimension of filaments. The models exhibited good predictive performance. The coefficients of determination of the backpropagation neural network model for predicting line width and line height were 0.9025 and 0.9604, respectively. The effect of various process parameters on the geometric morphology based on the established prediction model was also studied. The order of influence on line width and height, ranked from highest to lowest, was as follows: nozzle diameter, printing speed, extrusion pressure, and nondimensional nozzle height. Different nondimensional nozzle height settings may cause the extruded material to be stretched or squeezed. The material being in a stretched state leads to a thin filament, and the regularity of processing parameters on the geometric size is not strong. Meanwhile, the nozzle diameter exhibits a significant impact on dimensions when the material is in a squeezing state. Thus, this study can be used to predict the size of printing filament structures, guide the selection of printing parameters, and determine the size of 3D printing layers