Miracle-dz/UniFAR-FTUs huggingface dataset:
Breakfast consumption is inversely associated with metabolic syndrome in a sample of Iranian adults

Background: Central obesity, insulin resistance, dyslipidemia and hypertension are the core components of metabolic syndrome (MetS) which is coincident with unhealthy dietary habits in the Middle-Eastern countries. The aim of this study was to explore the association between dietary habits and metabolic syndrome of adult population living in Yazd Greater Area, Iran. Methods: This is a cross-sectional study which uses the data of a population-based cohort study on Iranian adults, known as Yazd Health Study (YaHS). The relationship between dietary habits and metabolic syndrome among adults (n= 2896) were analyzed using multiple logistic regression method. Results: Outcomes from logistic regression examining show that breakfast consumption has a significant inverse effect on the occurrence of metabolic syndrome after adjustment for age, education level, physical activity statue, history of chronic diseases and smoking (odds ratio (OR)= 0.38, 95% confidence interval (CI)= 0.14, 0.97). This effect remains significant even after adjustment for body mass index (BMI) and reveals that odds of having MetS is 69 % lower in breakfast consumers in contrast to non-consumers (OR=0.31, 95% CI= 0.11, 0.87). However, no significant relationship was observed between other dietary habits and MetS after adjustment for all potential confounders Conclusions: This study revealed that eating breakfast has an inverse relationship with metabolic syndrome. Finding out stronger evidence in relation between dietary habits and metabolic syndrome, more researches especially population-based cohort studies are needed to be conducted.
Influence Of SINx: H And SIOx Films On Optical And Electrical Properties Of Antireflective Coatings For Silicon Solar Cells

ABSRTACT: To increase the photon transmission in solar cells based on multicrystalline silicon, two different double layer antireflections (DARC1 and DARC2) were optimized and simulated, to optimize the antireflection double layer, we have developed a numerical simulation code with Matlab software package where we have used the method of transfer matrix to solve the optical equation. These solutions permit us to plot the optical reflectivity and the absorption versus wavelengths and layer thicknesses. The optical refractive index and thicknesses of considered materials which allowed us to have the best results of reflection were used to simulate the electrical properties of the cell with PC1D software. Thus, our results showed that the average reflectivity of 5.4 % and 6.4 % is obtained with a DARC2composed of two different layers of hydrogenated silicon nitride (SiNx: H) and silicon oxide (SiO2) and DARC1 composed of two layers of silicon nitride hydrogenated SiNx: H with optical indexes and thicknesses different, respectively. These optimized structures have the potential to increase the short-circuit current by more than 1.8% with a DARC1 and up 3.3 % with a DARC2 for non-encapsulated cells, in comparison with the standard single SiNx:H ARC.
LIFE CYCLE ANALYSIS FOR INVESTMENT DECISION-MAKING TO REVIVE ANCIENT SILK ROAD AND ENHANCE THE ECONOMIES OF CENTRAL ASIAN COUNTRIES

Presented is a project-level highway design application of user and agency life cycle cost and benefit analysis for preservation and upgrade of the famous ancient Silk Road infrastructure. Presented are some results of the World Bank's HDM III program as well as the USER software for the highway section of the road in mountainous terrain and in the harsh winter environment. The design of tunnels and covered bridges will make it possible to keep the highway open throughout the year instead of service period of only three months of summer in its existing condition, and the initial investment is expected to provide a high rate of return over the 20-year analysis period. The paper also shows that life cycle analysis over longer performance periods can lead to an improved and cost effective investment planning and decision making process.
Age-Related Performance in Using a Fully Immersive and Automated Virtual Reality System to Assess Cognitive Function

Introduction Cognition generally declines gradually over time due to progressive degeneration of the brain, leading to dementia and eventual loss of independent functions. The rate of regression varies among the six cognitive domains (perceptual motor, executive function, complex attention, learning and memory, social cognition and language). Current modality of cognitive assessment using neuropsychological paper-and-pencil screening tools for cognitive impairment such as the Montreal Cognitive Assessment (MoCA) has limitations and is influenced by age. Virtual reality (VR) is considered as a potential alternative tool to assess cognition. A novel, fully immersive automated VR system (Cognitive Assessment using Virtual Reality, CAVIRE) has been developed to assess the six cognitive domains. As cognition is associated with age, VR performance is postulated to vary with age using this system. Aims This is a feasibility study to evaluate the VR performance of cognitively healthy adults aged between 35 and 74 years old, based on the performance score and completion time using the CAVIRE system. Methods Conducted in a public primary care clinic in Singapore, 25 multi-ethnic Asian adults were recruited in each of the four age groups in years: (1) 35–44; (2) 45–54; (3) 55–64, and (4) 65–74. The eligibility criteria included a MoCA score of 26 or higher to reflect normal cognition and understanding English instructions. They completed common daily activities ranging from brushing teething to shopping, across 13 VR segments. Their performances scores and completion time were automatically computed by the CAVIRE system. These VR performance indices were compared across the four age groups using one-way ANOVA, F-test of the hypothesis, followed by pair-wise comparisons in the event of a significant F-test (p < 0.05). Results One participant dropped out from Group 1. The demographic characteristics of 99 participants were similar across the 4 age groups. Overall, younger participants in Groups 1 and 2 attained higher VR performance scores and shorter completion time, compared to those in Groups 3 and 4, in all six cognitive domains (all p < 0.05). Conclusion The CAVIRE VR performance scores and completion time significantly differ between the younger and older Asian participants with normal cognition. Enhancements to the system are needed to establish the age-group specific normal performance indices.
A Predictive Model and Evaluation Framework for Smart Parking: The Case of ParkPGH

ParkPGH is a smart parking system that uses historical parking and event data in a prediction model to provide real-time information on the availability of parking in eight parking facilities within the Pittsburgh Cultural District. The project’s unique characteristics include the collaborative efforts of funders, academia, nonprofit and for-profit entities that are involved in the project, the environment in which the product is deployed and the richness of the data from which the prediction model and the robust evaluation strategy draw upon. The paper describes the pilot phase of the project along with preliminary results, as well as the next steps to be taken for a full project implementation.
COMPUTATION OF THE TRANSMISSION OF WAVES FROM PILE DRIVING

Installation of pre-formed piles is normally achieved by impact hammer into cohesive and mixed soils, and by vibrodriver into granular soils. Both systems are high energy devices, and part of the energy imposed on to the pile is transmitted outwards into the soil from the pile shaft and the pile toe. Surface waves from an impact hammer have been observed as a single pulse similar to a single sine wave of short duration (typically, 0.05-0.05 s) with minor vibrations before and after. Surface waves from a vibrodriver have been recorded as pure sinusoidal vibrations at the vibrodriver frequency. Essentially, both types of disturbance comprise primary or dilational P waves, shear S waves and surface or Rayleigh R waves, emanating from the shaft and the toe. While empirical equations have been derived for estimation of peak surface vibrations, detailed computation of the ground waves is lacking. This paper describes a computational system based upon finite elements and infinite elements using the ABAQUS package. The system is capable of modelling the three wave components, and can include infinite elements which are essential for eliminating wave reflection at finite boundaries. (A) For the covering abstract see IRRD 493147.
Development and control of a 3-axis stabilised platform

The successful control of a three-degree-of-freedom gyroscope is presented for the application of steering and stabilising a platform mounted underneath an airship. The end goal is to stabilise a camera for earth observation purposes. The development of the necessary electronics, sensors and actuators along with the hardware and software to interface these components are presented. This include DC drives, torque control systems for the gimbal motors and a speed control system for the gyroscope as well as platform angle and angular rate sensors. A mathematical model for the gyroscope, based on Euler's equations of motion, is presented. Non-linear simulations are performed and compared to measurements of the plant's behaviour to step torque commands to determine the parameters of the gyroscope. Pole placement and LQR optimal control methods are considered in the design of a MIMO controller to steer the platform in the elevation plane, along with a PI controller to steer the platform in the azimuth plane. Ground tests display the success of the steering controllers.
Integrated Cardiac Electromechanics: Modeling and Personalization

Cardiac disease remains the leading cause of morbidity and mortality in the world. A variety of heart diagnosis techniques have been developed during the last century, and generally fall into two groups. The first group evaluates the electrical function of the heart using electrophysiological data such as electrocardiogram (ECG), while the second group aims to assess the mechanical function of the heart through medical imaging data. Nevertheless, the heart is an integrated electromechanical organ, where its cyclic pumping arises from the synergy of its electrical and mechanical function which requires first to be electrically excited in order to contract. At the same time, cardiac electrical function experiences feedback from mechanical contraction. This inter-dependent relationship determines that neither electrical function nor mechanical function alone can completely reflect the pathophysiological conditions of the heart. The aim of this thesis is working towards building an integrated framework for heart diagnosis through evaluation of electrical and mechanical functions simultaneously. The basic rational is to obtain quantitative interpretation of a subject-specific heart system by combining an electromechanical heart model and individual clinical measurements of the heart. To this end, we first develop a biologically-inspired mathematical model of the heart that provides a general, macroscopic description of
Designs for increasing reliability while reducing energy and increasing lifetime

In the last decades, the computing technology experienced tremendous developments. For instance, transistors' feature size shrank to half at every two years as consistently from the first time Moore stated his law. Consequently, number of transistors and core count per chip doubles at each generation. Similarly, petascale systems that have the capability of processing more than one billion calculation per second have been developed. As a matter of fact, exascale systems are predicted to be available at year 2020. However, these developments in computer systems face a reliability wall. For instance, transistor feature sizes are getting so small that it becomes easier for high-energy particles to temporarily flip the state of a memory cell from 1-to-0 or 0-to-1. Also, even if we assume that fault-rate per transistor stays constant with scaling, the increase in total transistor and core count per chip will significantly increase the number of faults for future desktop and exascale systems. Moreover, circuit ageing is exacerbated due to increased manufacturing variability and thermal stresses, therefore, lifetime of processor structures are becoming shorter. On the other side, due to the limited power budget of the computer systems such that mobile devices, it is attractive to scale down the voltage. However, when the voltage level scales to beyond the safe margin especially to the ultra-low level, the error rate increases drastically. Nevertheless, new memory technologies such as NAND flashes present only limited amount of nominal lifetime, and when they exceed this lifetime, they can not guarantee storing of the data correctly leading to data retention problems. Due to these issues, reliability became a first-class design constraint for contemporary computing in addition to power and performance. Moreover, reliability even plays increasingly important role when computer systems process sensitive and life-critical information such as health records, financial information, power regulation, transportation, etc. In this thesis, we present several different reliability designs for detecting and correcting errors occurring in processor pipelines, L1 caches and non-volatile NAND flash memories due to various reasons. We design reliability solutions in order to serve three main purposes. Our first goal is to improve the reliability of computer systems by detecting and correcting random and non-predictable errors such as bit flips or ageing errors. Second, we aim to reduce the energy consumption of the computer systems by allowing them to operate reliably at ultra-low voltage level. Third, we target to increase the lifetime of new memory technologies by implementing efficient and low-cost reliability schemes.
A Fuzzy Decision Variables Framework for Large-Scale Multiobjective Optimization

In large-scale multiobjective optimization, too many decision variables hinder the convergence search of evolutionary algorithms. Reducing the search range of the decision space will significantly alleviate this puzzle. With this in mind, this article proposes a fuzzy decision variables framework for large-scale multiobjective optimization. The framework divides the entire evolutionary process into two main stages: 1) fuzzy evolution and 2) precise evolution. In fuzzy evolution, we blur the decision variables of the original solution to reduce the search range of the evolutionary algorithm in the decision space so that the evolutionary population can quickly converge. The degree of fuzzification gradually decreases with the evolutionary process. Once the population approximately converges, the framework will turn to precise evolution. In precise evolution, the actual decision variables of the solution are directly optimized to increase the diversity of the population so as to be closer to the true Pareto optimal front. Finally, this article embeds some representative algorithms into the proposed framework and verifies the framework’s effectiveness through comparative experiments on various large-scale multiobjective problems with 500 to 5000 decision variables. The experimental results show that in large-scale multiobjective optimization, the framework proposed in this article can significantly improve the performance and computational efficiency of multiobjective optimization algorithms.
Estimation of the safety benefits of a vehicle replacement program in Victoria

Australia is facing an ageing and polarising-market passenger vehicle fleet. This study focuses on Victoria, and assesses the current and past passenger fleet composition in terms of vehicle age by market group. Based on current trends, such as population rates, new vehicle sales and market group trends, a scrappage function by age of vehicle is estimated to project the vehicle fleet to 2012. By manipulating key inputs and outputs to the system, deviations from this baseline projection are estimated from a range of scenarios, to examine changes in vehicle fleet composition from various external influences to the system. The overall purpose of this estimation procedure will be in estimating the crashworthiness, and intrinsically aggressivity, of those projected fleets to give an overall estimation of fleet crashworthiness under the various scenarios. This will help to determine the effect of a particular change to the system, for example a policy change, and to measure the effect on the overall safety of the vehicle fleet over time. (a) For the covering entry of this conference, please see ITRD abstract no. E210298.
A Comprehensive Structural Dynamic Analysis Approach for Multi Mission Earth Entry Vehicle (MMEEV) Development

The anticipated NASA Mars Sample Return Mission (MSR) requires a simple and reliable method in which to return collected Martian samples back to earth for scientific analysis. The Multi-Mission Earth Entry Vehicle (MMEEV) is NASA's proposed solution to this MSR requirement. Key aspects of the MMEEV are its reliable and passive operation, energy absorbing foam-composite structure, and modular impact sphere (IS) design. To aid in the development of an EEV design that can be modified for various missions requirements, two fully parametric finite element models were developed. The first model was developed in an explicit finite element code and was designed to evaluate the impact response of the vehicle and payload during the final stage of the vehicle's return to earth. The second model was developed in an explicit code and was designed to evaluate the static and dynamic structural response of the vehicle during launch and reentry. In contrast to most other FE models, built through a Graphical User Interface (GUI) pre-processor, the current model was developed using a coding technique that allows the analyst to quickly change nearly all aspects of the model including: geometric dimensions, material properties, load and boundary conditions, mesh properties, and analysis controls. Using the developed design tool, a full range of proposed designs can quickly be analyzed numerically and thus the design trade space for the EEV can be fully understood. An engineer can then quickly reach the best design for a specific mission and also adapt and optimize the general design for different missions.
Models and Algorithms of Real-Time Vehicle Rescheduling Problems under Schedule Disruptions

A vehicle-based service system might be susceptible to unexpected costs and delays due to unforeseen events, such as a vehicle breakdown, a traffic accident, a medical emergency, depot overload, road work, etc. In such situations, a priori algorithmic solution may be deteriorated and fleet plans may need to be adjusted in real-time as a function of the dynamic system state. I consider real-time logistics management problems where a vehicle breaks down in the midst of operation. First, a backup vehicle needs to be determined to pick up the passengers/cargo from the breakdown vehicle, and from the breakdown point completing the remaining portion of the planned trip. This backup vehicle can be dispatched from the depot or from the vehicles currently in service. In the former case, it may impose a significant delay if the depot is far away from the breakdown location. In the latter case, the vehicle used as backup may have to change its own schedule. Trips uncompleted by this backup vehicle may have to be further covered by other vehicles. Thus, a good solution should be acquired in conjunction with the status of all other vehicles in the entire network. Yet, the new schedule may be considerably different from the original one after rescheduling is done. These changes may make the crew-rescheduling problem challenging, since it is essential to ensure that all crews know the itinerary of their new trips. Furthermore, the vehicle breakdown may not only delay the current trip that is directly affected by the disruption but also other trips that the breakdown vehicle has to cover in the network. As a result, some of the delayed trips may have to be cancelled. A good approach should consider operating cost, fixed vehicle cost, delay cost, schedule disruption cost as well as trip cancellation cost simultaneously. This real-time logistics management problem has not been properly addressed in the literature.
Evaluation of warm mix asphalt using the Mechanistic-Empirical Pavement Design Guide

This paper summarizes a recently completed field and laboratory evaluation of warm mix asphalt based on performance testing results. The field study incorporated asphalt mixture samples procured from four different Iowa Department of Transportation (IDOT) projects for a total of eight different field produced mixes, four WMA mixes and four HMA mixes. There was one HMA control mix and one WMA mix for each project. Dynamic modulus tests were performed on these samples and a statistical analysis showed differences when comparing WMA and HMA. The main objective of this paper is to investigate how the differences found in the dynamic modulus tests correlate to actual field performance using the Mechanistic-Empirical Pavement Design Guide (MEPDG). The MEPDG is a pavement design software that utilizes dynamic modulus laboratory data to predict performance in the field, at a user specified design reliability, based on traffic, climate and material inputs. The dynamic modulus data is used as an input to the MEPDG model in order to calculate predicted pavement performance. The results show that for certain mixes, there may be statistical evidence of a difference in long term pavement performance based on the HMA MEPDG output compared with the WMA MEPDG output. The analysis shows statistical differences in the laboratory dynamic modulus data and these differences correspond well with the MEPDG analysis.
AUTOMATED COLLISION NOTIFICATION (ACN) FIELD OPERATIONAL TEST (FOT) EVALUATION REPORT

The Johns Hopkins University Applied Physics Laboratory conducted the Independent Evaluation of the Automated Collision Notification (ACN) Field Operational Test (FOT) for the National Highway Traffic Safety Administration. The goal of ACN is to use technology to provide faster and smarter emergency medical responses in an attempt to save lives and reduce disabilities from injuries. To attain this goal an ACN system should automatically determine that a motor vehicle has been in a collision, notify emergency response personnel of the collision and the vehicle location, provide information concerning the crash, and establish a voice link between the vehicle and emergency response personnel. Information that might be provided about the crash includes estimates of crash severity and the probability of serious injury. The purpose of the ACN FOT was to demonstrate the feasibility of fielding an ACN system and the benefits of an ACN system to victims of motor vehicle crashes. The ACN FOT was initiated in October 1995 with the first installations of ACN systems in vehicles starting in June of 1997. This report evaluates the results of the ACN FOT using data collected through the end of the test period in August of 2000. The ACN FOT and current activity in the commercial marketplace have demonstrated that the development and deployment of ACN systems is technically feasible. The potential benefits of an ACN system result from reduced public safety answering point (PSAP) notification times, improved knowledge of the vehicle location, and estimates of crash severity and the probability of serious injury.