A Transportation Performance Measurement System with a Mississippi Case Study

In current literature and practices, there are no systematic and user-oriented intermodal transportation performance measures. After identifying customer needs and transportation goals, this paper proposes a set of system-level performance measures for intermodal transportation that are user-oriented, scalable, systematic, and scientific. The measures can be used to compare intermodal design alternatives or to evaluate existing transportation systems with any size and any mode. The highway system in Mississippi is analyzed as a case study. The case study demonstrates the existing data sources, the methods of calculating the measures, and the means of evaluating transportation systems with the measures

A Transportation Performance Measurement System with a Mississippi Case Study

In current literature and practices, there are no systematic and user-oriented intermodal transportation performance measures. After identifying customer needs and transportation goals, this paper proposes a set of system-level performance measures for intermodal transportation that are user-oriented, scalable, systematic, and scientific. The measures can be used to compare intermodal design alternatives or to evaluate existing transportation systems with any size and any mode. The highway system in Mississippi is analyzed as a case study. The case study demonstrates the existing data sources, the methods of calculating the measures, and the means of evaluating transportation systems with the measures

High sensitivity infrared nano-spectroscopy in ambient and water environment

Mid-infrared (mid-IR) vibrational spectroscopy is a universal label–free tool for identifying molecular compounds via their ‘fingerprint’ vibrational absorption lines. Infrared nano-spectroscopies with nanoscale spatial resolution can reveal the chemical and physical properties at a few nanometers, and several scanning probe techniques¹⁻⁹ have been developed to address this need. Among these methods, AFM-IR and scattering nearfield scanning microscopy (s-NSOM) have produced outstanding results in mid-IR and far-IR spectral range. In this thesis, a set of experiments are presented, which have substantially improved AFM-IR in terms of the sensitivity and resolution, and have implemented the system for operation under different conditions. We demonstrated high-sensitivity AFM-IR on monolayer molecules via molecular expansion force. AFM-IR microscopy and spectroscopy is also demonstrated on thin films in aqueous environment, which offers the possibility of in vivo studies of biological samples using IR nanospectroscopies¹⁰. Apart from AFM-IR, s-NSOM imaging using the self-mixing detection in mid-IR quantum cascade lasers (QCL) is also presented in this dissertation. The phase and amplitude of the scattered light field can be analyzed from the voltage signal on the QCL, without the need of external-cavity interferometric optical setup.Electrical and Computer Engineerin

Co-methylated Genes in Different Adipose Depots of Pig are Associated with Metabolic, Inflammatory and Immune Processes

It is well established that the metabolic risk factors of obesity and its comorbidities are more attributed to adipose tissue distribution rather than total adipose mass. Since emerging evidence suggests that epigenetic regulation plays an important role in the aetiology of obesity, we conducted a genome-wide methylation analysis on eight different adipose depots of three pig breeds living within comparable environments but displaying distinct fat level using methylated DNA immunoprecipitation sequencing. We aimed to investigate the systematic association between anatomical location-specific DNA methylation status of different adipose depots and obesity-related phenotypes. We show here that compared to subcutaneous adipose tissues which primarily modulate metabolic indicators, visceral adipose tissues and intermuscular adipose tissue, which are the metabolic risk factors of obesity, are primarily associated with impaired inflammatory and immune responses. This study presents epigenetic evidence for functionally relevant methylation differences between different adipose depots

FERSC Data Management Plan

FERSC is a Tier 1 University Transportation Center consortium led by the University of Tennessee, Knoxville. Its focus is the Infrastructure Investment and Jobs Act (IIJA)\u2019s research priority, Improving Mobility of People and Goods as its primary area. The consortium supports the DOT Strategic Goals of Economic Strength and Global Competitiveness as the primary focus and Equity and Transformation as the secondaries

Identification of exosome-like nanoparticle-derived microRNAs from 11 edible fruits and vegetables

Edible plant-derived exosome-like nanoparticles (EPDELNs) are novel naturally occurring plant ultrastructures that are structurally similar to exosomes. Many EPDELNs have anti-inflammatory properties. MicroRNAs (miRNAs) play a critical role in mediating physiological and pathological processes in animals and plants. Although miRNAs can be selectively encapsulated in extracellular vesicles, little is known about their expression and function in EPDELNs. In this study, we isolated nanovesicles from 11 edible fruits and vegetables and subjected the corresponding EPDELN small RNA libraries to Illumina sequencing. We identified a total of 418 miRNAs—32 to 127 per species—from the 11 EPDELN samples. Target prediction and functional analyses revealed that highly expressed miRNAs were closely associated with the inflammatory response and cancer-related pathways. The 418 miRNAs could be divided into three classes according to their EPDELN distributions: 26 “frequent” miRNAs (FMs), 39 “moderately present” miRNAs (MPMs), and 353 “rare” miRNAs (RMs). FMs were represented by fewer miRNA species than RMs but had a significantly higher cumulative expression level. Taken together, our in vitro results indicate that miRNAs in EPDELNs have the potential to regulate human mRNA

Optimal In Silico Target Gene Deletion through Nonlinear Programming for Genetic Engineering

Optimal selection of multiple regulatory genes, known as targets, for deletion to enhance or suppress the activities of downstream genes or metabolites is an important problem in genetic engineering. Such problems become more feasible to address in silico due to the availability of more realistic dynamical system models of gene regulatory and metabolic networks. The goal of the computational problem is to search for a subset of genes to knock out so that the activity of a downstream gene or a metabolite is optimized.Based on discrete dynamical system modeling of gene regulatory networks, an integer programming problem is formulated for the optimal in silico target gene deletion problem. In the first result, the integer programming problem is proved to be NP-hard and equivalent to a nonlinear programming problem. In the second result, a heuristic algorithm, called GKONP, is designed to approximate the optimal solution, involving an approach to prune insignificant terms in the objective function, and the parallel differential evolution algorithm. In the third result, the effectiveness of the GKONP algorithm is demonstrated by applying it to a discrete dynamical system model of the yeast pheromone pathways. The empirical accuracy and time efficiency are assessed in comparison to an optimal, but exhaustive search strategy.Although the in silico target gene deletion problem has enormous potential applications in genetic engineering, one must overcome the computational challenge due to its NP-hardness. The presented solution, which has been demonstrated to approximate the optimal solution in a practical amount of time, is among the few that address the computational challenge. In the experiment on the yeast pheromone pathways, the identified best subset of genes for deletion showed advantage over genes that were selected empirically. Once validated in vivo, the optimal target genes are expected to achieve higher genetic engineering effectiveness than a trial-and-error procedure

Individual Professional Practice in the Company

Import 23/08/2017Cílem této bakalářské práce je popsat absolvování odborné praxe ve firmě HS Interactive s.r.o. Praxe byla zaměřena na vývoj mobilní aplikace pro operační systém Android. Aplikace je mobilním klientem pro sociální síť MatchToMe. V úvodu popisuji důvody, které vedly k výběru odborné praxe. Dále se věnuji úkolům, které mi byly zadány s jejich implementací a postupem řešení problémů, které se objevily při vývoji. Závěr práce je věnován zhodnocení získaných zkušeností a dosažených výsledků.Purpose of this bachelor thesis is to describe a professional practice in company HS Interactive s.r.o. Practice was focused on the development of mobile application for the operating system Android. The application is a mobile client for social network MatchToMe. In the introduction I describe reasons that led to the selection of professional practice. Then I describe tasks that I have been awarded with their implementations and process of solution issues that have emerged during development. The conclusion of thesis is dedicated to the evaluation of the experience gained and the results achieved.440 - Katedra telekomunikační technikyvýborn

Genomic data for 78 chickens from 14 populations

Background: Since the domestication of the red jungle fowls (Gallus gallus; dating back to~10 000 B.P.) in Asia, domestic chickens (Gallus gallus domesticus) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production, and skin color. Population genomic variations through diversifying selection have not been fully investigated. Findings: The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of five wild red jungle fowls and eight Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ~21.30 gigabases (Gb) of high-quality data from each individual to the reference chicken genome, we identified ~6.44 million (M) single nucleotide polymorphisms (SNPs) for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. Conclusions: The current data is important for population genetics and further studies in chickens and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chickens.Peer reviewedAnimal Scienc