Truncated differential analysis of reduced-round LBlock

In this paper we present truncated differential analysis of reduced-round LBlock by computing the differential distribution of every nibble of the state. LLR statistical test is used as a tool to apply the distinguishing and key-recovery attacks. To build the distinguisher, all possible differences are traced through the cipher and the truncated differential probability distribution is determined for every output nibble. We concatenate additional rounds to the beginning and end of the truncated differential distribution to apply the key-recovery attack. By exploiting properties of the key schedule, we obtain a large overlap of key bits used in the beginning and final rounds. This allows us to significantly increase the differential probabilities and hence reduce the attack complexity. We validate the analysis by implementing the attack on LBlock reduced to 12 rounds. Finally, we apply single-key and related-key attacks on 18 and 21-round LBlock, respectively.

Studies on decomposed crop residues by FTIR differential analysis

The decomposing process of corn leaf residues (CLR) was studied by FTIR differential analysis,and the differential spectra were compared with normal spectra. The result showed that the purification process to remove inorganic matters from decomposed CLR could be omitted when differential analysis is used, and the differential spectra were cleat and distinct. As far as the studies of decomposed crop residues, the FTIR differential analysis was a convenient and forthright method.

Motivational profiles Spanish students of Compulsory Secondary Education: Differential analysis of academic self-attributions

Academic goals and academic self-attributions are relevant variables in school settings. The objective of this study is to identify whether there are combinations of multiple goals that lead to different motivational profiles and to determine whether there are significant differences between the groups obtained regarding causal attributions of success and failure (ability, effort, or external causes) in Mathematics and Language and Literature, and in overall academic performance. The Goal Achievement Tendencies Questionnaire (AGTQ) and the Sydney Attribution Scale (SAS) were administered to a sample of 2022 students of compulsory secondary education, ranging in age from 12 to 16 years (M = 13.81, SD = 1.35). Cluster analysis identified four motivational profiles: a group of students with a high generalized motivation profile, a group of students with low generalized motivation profile, a group of students with predominance of learning goals and achievement goals, and a final group of students with predominance of social reinforcement goals. Results revealed statistically significant differences between the profiles obtained in academic self-attributions.

Analysis of differential gene expression based on Bayesian estimation of variance

Gene expression is arguably the most important indicator of biological function. Thus identifying differentially expressed genes is one of the main aims of high throughout studies that use microarray and RNAseq platforms to study deregulated cellular pathways. There are many tools for analysing differentia gene expression from transciptomic datasets. The major challenge of this topic is to estimate gene expression variance due to the high amount of ‘background noise’ that is generated from biological equipment and the lack of biological replicates. Bayesian inference has been widely used in the bioinformatics field. In this work, we reveal that the prior knowledge employed in the Bayesian framework also helps to improve the accuracy of differential gene expression analysis when using a small number of replicates. We have developed a differential analysis tool that uses Bayesian estimation of the variance of gene expression for use with small numbers of biological replicates. Our method is more consistent when compared to the widely used cyber-t tool that successfully introduced the Bayesian framework to differential analysis. We also provide a user-friendly web based Graphic User Interface for biologists to use with microarray and RNAseq data. Bayesian inference can compensate for the instability of variance caused when using a small number of biological replicates by using pseudo replicates as prior knowledge. We also show that our new strategy to select pseudo replicates will improve the performance of the analysis. - See more at: http://www.eurekaselect.com/node/138761/article#sthash.VeK9xl5k.dpuf

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

Proteomic Analysis of Chloroplast-to-Chromoplast Transition in Tomato Reveals Metabolic Shifts Coupled with Disrupted Thylakoid Biogenesis Machinery and Elevated Energy-Production Components

A comparative proteomic approach was performed to identify differentially expressed proteins in plastids at three stages of tomato (Solanum lycopersicum) fruit ripening (mature-green, breaker, red). Stringent curation and processing of the data from three independent replicates identified 1,932 proteins among which 1,529 were quantified by spectral counting. The quantification procedures have been subsequently validated by immunoblot analysis of six proteins representative of distinct metabolic or regulatory pathways. Among the main features of the chloroplast-to-chromoplast transition revealed by the study, chromoplastogenesis appears to be associated with major metabolic shifts: (1) strong decrease in abundance of proteins of light reactions (photosynthesis, Calvin cycle, photorespiration) and carbohydrate metabolism (starch synthesis/degradation), mostly between breaker and red stages and (2) increase in terpenoid biosynthesis (including carotenoids) and stress-response proteins (ascorbate-glutathione cycle, abiotic stress, redox, heat shock). These metabolic shifts are preceded by the accumulation of plastid-encoded acetyl Coenzyme A carboxylase D proteins accounting for the generation of a storage matrix that will accumulate carotenoids. Of particular note is the high abundance of proteins involved in providing energy and in metabolites import. Structural differentiation of the chromoplast is characterized by a sharp and continuous decrease of thylakoid proteins whereas envelope and stroma proteins remain remarkably stable. This is coincident with the disruption of the machinery for thylakoids and photosystem biogenesis (vesicular trafficking, provision of material for thylakoid biosynthesis, photosystems assembly) and the loss of the plastid division machinery. Altogether, the data provide new insights on the chromoplast differentiation process while enriching our knowledge of the plant plastid proteome.

Proteomic analysis of banana fruit reveals proteins that are differentially accumulated during ripening

Bananas (Musa spp.) are highly perishable fruit of notable economic and nutritional relevance. Because the identification of proteins involved in metabolic pathways could help to extend green-life and improve the quality of the fruit, this study aimed to compare the proteins of banana pulp at the pre-climacteric and climacteric stages. The use of two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) revealed 50 differentially expressed proteins, and comparing those proteins to the Mass Spectrometry Protein Sequence Database (MSDB) identified 26 known proteins. Chitinases were the most abundant types of proteins in unripe bananas, and two isoforms in the ripe fruit have been implicated in the stress/defense response. In this regard, three heat shock proteins and isoflavone reductase were also abundant at the climacteric stage. Concerning fruit quality, pectate lyase, malate dehydrogenase, and starch phosphorylase accumulated during ripening. In addition to the ethylene formation enzyme amino cyclo carboxylic acid oxidase, the accumulation of S-adenosyl-L-homocysteine hydrolase was needed because of the increased ethylene synthesis and DNA methylation that occurred in ripening bananas. Differential analysis provided information on the ripening-associated changes that occurred in proteins involved in banana flavor, texture, defense, synthesis of ethylene, regulation of expression, and protein folding, and this analysis validated previous data on the transcripts during ripening. In this regard, the differential proteomics of fruit pulp enlarged our understanding of the process of banana ripening. (C) 2012 Elsevier B.V. All rights reserved.

Kinetic study of the pyrolysis of miscanthus and its acid hydrolysis residue by thermogravimetric analysis

The kinetic parameters of the pyrolysis of miscanthus and its acid hydrolysis residue (AHR) were determined using thermogravimetric analysis (TGA). The AHR was produced at the University of Limerick by treating miscanthus with 5 wt.% sulphuric acid at 175 °C as representative of a lignocellulosic acid hydrolysis product. For the TGA experiments, 3 to 6 g of sample, milled and sieved to a particle size below 250 μm, were placed in the TGA ceramic crucible. The experiments were carried out under non-isothermal conditions heating the samples from 50 to 900 °C at heating rates of 2.5, 5, 10, 17 and 25 °C/min. The activation energy (EA) of the decomposition process was determined from the TGA data by differential analysis (Friedman) and three isoconversional methods of integral analysis (Kissinger–Akahira–Sunose, Ozawa–Flynn–Wall, Vyazovkin). The activation energy ranged from 129 to 156 kJ/mol for miscanthus and from 200 to 376 kJ/mol for AHR increasing with increasing conversion. The reaction model was selected using the non-linear least squares method and the pre-exponential factor was calculated from the Arrhenius approximation. The results showed that the best fitting reaction model was the third order reaction for both feedstocks. The pre-exponential factor was in the range of 5.6 × 1010 to 3.9 × 10+ 13 min− 1 for miscanthus and 2.1 × 1016 to 7.7 × 1025 min− 1 for AHR.

Low probability differentials and the cryptanalysis of full-round CLEFIA-128

So far, low probability differentials for the key schedule of block ciphers have been used as a straightforward proof of security against related-key differential analysis. To achieve resistance, it is believed that for cipher with k-bit key it suffices the upper bound on the probability to be 2− k . Surprisingly, we show that this reasonable assumption is incorrect, and the probability should be (much) lower than 2− k . Our counter example is a related-key differential analysis of the well established block cipher CLEFIA-128. We show that although the key schedule of CLEFIA-128 prevents differentials with a probability higher than 2− 128, the linear part of the key schedule that produces the round keys, and the Feistel structure of the cipher, allow to exploit particularly chosen differentials with a probability as low as 2− 128. CLEFIA-128 has 214 such differentials, which translate to 214 pairs of weak keys. The probability of each differential is too low, but the weak keys have a special structure which allows with a divide-and-conquer approach to gain an advantage of 27 over generic analysis. We exploit the advantage and give a membership test for the weak-key class and provide analysis of the hashing modes. The proposed analysis has been tested with computer experiments on small-scale variants of CLEFIA-128. Our results do not threaten the practical use of CLEFIA.

Reconstruction of surfaces of revolution from single uncalibrated views

This paper addresses the problem of recovering the 3D shape of a surface of revolution from a single uncalibrated perspective view. The algorithm introduced here makes use of the invariant properties of a surface of revolution and its silhouette to locate the image of the revolution axis, and to calibrate the focal length of the camera. The image is then normalized and rectified such that the resulting silhouette exhibits bilateral symmetry. Such a rectification leads to a simpler differential analysis of the silhouette, and yields a simple equation for depth recovery. It is shown that under a general camera configuration, there will be a 2-parameter family of solutions for the reconstruction. The first parameter corresponds to an unknown scale, whereas the second one corresponds to an unknown attitude of the object. By identifying the image of a latitude circle, the ambiguity due to the unknown attitude can be resolved. Experimental results on real images are presented, which demonstrate the quality of the reconstruction. © 2004 Elsevier B.V. All rights reserved.

SMS4密码算法的差分故障攻击

SMS4是用于WAPI的分组密码算法,是国内官方公布的第一个商用密码算法.由于公布时间不长,关于它的安全性研究尚没有公开结果发表.该文研究SMS4密码算法对差分故障攻击的安全性.攻击采用面向字节的随机故障模型,并且结合了差分分析技术.该攻击方法理论上仅需要32个错误密文就可以完全恢复出SMS4的128比特种子密钥.因为实际中故障发生的字节位置是不可能完全平均的,所以实际攻击所需错误密文数将略大于理论值;文中的实验结果也验证了这一事实,恢复SMS4的128bit种子密钥平均大约需要47个错误密文.文章结果显示SMS4对差分故障攻击是脆弱的.为了避免这类攻击,建议用户对加密设备进行保护,阻止攻击者对其进行故障诱导.

Impacto das variáveis sociodemográficas no potencial dos jovens com formação superior em Portugal

Dissertação apresentada à Universidade Fernando Pessoa, como parte dos requisitos para a obtenção do grau de Mestre em Psicologia, ramo de Psicologia do Trabalho e das Organizações

The present-day chemical composition of the SMC from UVES spectra of the sharp-lined, B-type dwarf AV 304

High-resolution spectroscopic VLT/UVES observations are presented for the B-type main-sequence star, AV 304, in the Small Magellanic Cloud (SMC). These spectra have been analysed using LTE model-atmosphere techniques, to derive stellar atmospheric parameters and chemical compositions. As AV 304 is located within the hydrogen burning main-sequence band, its chemical composition should reflect that of the SMC interstellar medium (ISM). A detailed line-by-line differential analysis has been undertaken relative to a Galactic comparison star. A general metal deficiency for the a-process elements O, Si & S of -0.43 +/- 0.05 dex is found for AV 304, with iron having a similar underabundance. Oxygen may be relatively over- abundant by similar to0.1 dex and carbon and aluminium underabundant by similar to0.2 dex. A large nitrogen underabundance (of -1.2 dex relative to hydrogen and -0.7 dex relative to iron) is found. This is interpreted in terms of the CNO bi-cycle having been suppressed in the SMC. Furthermore, the large nitrogen deficiency is in excellent agreement with that found for SMC H II regions. Indeed, this represents a first for stellar astrophysics - confirming the low base-line nitrogen composition of the SMC ISM (viz. 12+log(N/H) similar to 6.66 +/- 0.10 dex).

The chemical composition towards the galactic anti-centre .1. Observations and model atmosphere analyses

High resolution spectra of six early B-type main-sequence stars having galactocentric distances of between 10 and 18 kpc are presented. We List the equivalent widths for the metal lines and illustrate their hydrogen and helium line profiles. The stars are analysed using LTE line-blanketed model atmosphere techniques to derive atmospheric parameters and surface chemical compositions. All six stars have similar effective temperatures and surface gravities, allowing a reliable comparison of their metal abundances and distances. Significant variations in the photospheric abundances are evident and are discuss the need for a more detailed line-by-line differential analysis to exactly quantify the differences. This will be presented in a companion paper (Smartt et al. 1996).

Burnout e engagement nos médicos dos Hospitais do grande Porto

Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo de Gestão de Empresas Orientada por: Prof. Doutor Eduardo Manuel Lopes de Sá e Silva Coorientada por: Mestre Adalmiro Álvaro Malheiro de Castro Andrade Pereira Esta dissertação inclui as críticas e sugestões feitas pelo júri.