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

Outcome of competition between Monkhead and 92-46.

<p>(a) Seed biomass per pot of Monkhead and 92-46 along the de Wit series. Error bars denote 95% confidence intervals for the mean. (b) The input–output ratio diagram, in which the output proportion of 92-46 at harvest is plotted against the input proportion of 92-46 at sowing. The dotted line is the 45° equilibrium line on which the output proportion equals the input proportion. Error bars denote 95% confidence intervals for the mean.</p

Root biomass per plant

<p>(a), seed biomass per plant (b), total biomass per plant (c), and root allocation (d) of Monkhead and 92-46 along the de Wit series. Error bars denote 95% confidence intervals for the mean. We used different English letters to indicate significant difference between different mixtures for Monkhead, and Latin letters for 92-46 (<i>S-N-K</i> test was used if variances were homogeneous; otherwise, Tamhane <i>t</i>-test was used).</p

Data for two spring wheat varieties in a de Wit series of competition

Pot experiment conducted in the Botanical Garden of Beijing Normal University

De Wit replacement series.

<p>92-46 and Monkhead were mixed in ratios of 0: 4 (pure Monkhead), 1:3, 2:2, 3:1 and 4: 0 (pure 92-46), with four plants in each pot. The dotted line represented segregation by nylon bags.</p

Accelerating Structural Optimization through Fingerprinting Space Integration on the Potential Energy Surface

Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique, in particular. In this study, we introduce a novel method that enhances the efficiency of local optimization by integrating extra fingerprint space into the optimization process. Our approach utilizes a mixed energy concept in the hyper potential energy surface (PES), combining real energy and a newly introduced fingerprint energy derived from the symmetry of the local atomic environment. This method strategically guides the optimization process toward high-symmetry, low-energy structures by leveraging the intrinsic symmetry of the atomic configurations. The effectiveness of our approach was demonstrated through structural optimizations of silicon, silicon carbide, and Lennard-Jones cluster systems. Our results show that the fingerprint space biasing technique significantly enhances the performance and probability of discovering energetically favorable, high-symmetry structures as compared to conventional optimizations. The proposed method is anticipated to streamline the search for new materials and facilitate the discovery of novel energetically favorable configurations

The Correlation Analysis of Two Common Polymorphisms in <i>STAT6</i> Gene and the Risk of Asthma: A Meta-Analysis

<div><p>Background</p><p>Several studies have reported that the <i>GT</i> dinucleotide repeat length polymorphism and the <i>G2964A</i> polymorphism in <i>signal transducer and activator of transcriptional factor 6</i> gene are associated with asthma susceptibility, but others have conflicting results. Our meta-analysis aimed to elucidate the emerging paradigms.</p><p>Methods</p><p>We searched PUBMED, EMBASE, ISI web of knowledge, Chinese National Knowledge Infrastructure, and Wanfang databases. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to evaluate the strength of association. We applied Bonferroni step-down and Benjamini-Hochberg step-up methods to adjust the values for multiple comparisons.</p><p>Results</p><p>A total of 12 individual studies in 11 articles were included in the meta-analysis. For <i>GT</i> repeat polymorphism, the <i>S</i> allele had approximately 45% increased risk of asthma (<i>S</i> vs. <i>L</i>: OR = 1.45, 95% CI = 1.22–1.71, <i>P</i>_UNCORRECTED <0.001, <i>P_Bon</i> <0.001, <i>P_FDR</i> <0.001). Further analysis indicated that <i>GT₁₃</i> and <i>GT₁₄</i> contributed to asthma risk, whereas <i>GT₁₅</i> and <i>GT₁₆</i> were protective (<i>GT₁₃</i> vs. <i>GT₁₅</i>: OR = 1.38, 95% CI = 1.16–1.65, <i>P</i>_{UNCORRECTED =}0.001, <i>P_Bon =</i>0.005, <i>P_FDR =</i>0.002). Similar results were obtained in the subgroup analysis of Asian population. <i>G2964A</i> polymorphism analysis showed that the <i>AA</i> genotype moderately increased the risk of asthma by 47% compared with the <i>GG</i> genotype (OR = 1.47, p = 0.068) in Chinese population, whereas the <i>2964A</i> allele moderately increased the risk of asthma in Chinese population by 18% (<i>2964A</i> vs. <i>2964G</i>: OR = 1.18, p = 0.08). However, none of the associations reached statistically significant levels particularly after correction for multiple testing.</p><p>Conclusions</p><p>This meta-analysis suggests that <i>S</i> allele (<i>GT₁₃</i> and <i>GT₁₄</i>) of the <i>GT</i> repeat polymorphism confers significant risks to asthma. However, the <i>G2964A</i> polymorphism does not have an association with the susceptibility to asthma.</p></div

A D-Optimal Design for Estimation of Parameters of an Exponential-Linear Growth Curve of Nanostructures

<div><p>We consider the problem of determining an optimal experimental design for estimation of parameters of a class of complex curves characterizing nanowire growth that is partially exponential and partially linear. Locally D-optimal designs for some of the models belonging to this class are obtained by using a geometric approach. Further, a Bayesian sequential algorithm is proposed for obtaining D-optimal designs for models with a closed-form solution, and for obtaining efficient designs in situations where theoretical results cannot be obtained. The advantages of the proposed algorithm over traditional approaches adopted in recently reported nanoexperiments are demonstrated using Monte Carlo simulations. The computer code implementing the sequential algorithm is available as supplementary materials.</p></div

Descriptions of studies included in the meta-analysis.

<p><b>Abbreviations:</b> NA: not available; PCR: Polymerase Chain Reaction; SSCP: Single Strand Conformation Polymorphism; RFLP: Restriction Fragment Length Polymorphism; CE: Capillary Electrophoresis; STR: Short Tandem Repeat.</p

Association between <i>GT</i> repeat length polymorphism in <i>STAT6</i> with the risk of asthma.

<p>The results were shown by forest plots, each study is shown by the first author name, year of publication, individual and overall ORs (odds ratio) and 95% CI (confidence intervals). Box and horizontal line represent OR and 95% CI of the corresponding study, and the diamond represents the overall OR and 95% CI. Alleles ≤14 were defined as short alleles (<i>S</i>), and alleles ≥15 were regarded as long alleles (<i>L</i>). (A) <i>S</i> vs. <i>L</i> in all the populations, fixed-effects model; (B) <i>GT₁₃</i> vs. <i>GT₁₅</i> in all the populations, fixed-effects model; (C) <i>GT₁₃</i> vs. <i>GT₁₄</i> in all the populations, fixed-effects model; (D) <i>GT₁₅</i> vs. <i>GT₁₆</i> in all the populations, random-effects model.</p