Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling Analysis of the Galaxy Distribution in the SSRS Catalog

A detailed analysis of the galaxy distribution in the Southern Sky Redshift Survey (SSRS) by means of the multifractal or scaling formalism is presented. It is shown that galaxies cluster in different ways according to their morphological type as well as their size. Ellipticals are more clustered than spirals, even at scales up to 15 h$^{-1}$ Mpc, whereas no clear segregation between early and late spirals is found. It is also shown that smaller galaxies distribute more homogeneously than larger galaxies.
Long Term Effect of Curcumin in Restoration of Tumour Suppressor p53 and Phase-II Antioxidant Enzymes via Activation of Nrf2 Signalling and Modulation of Inflammation in Prevention of Cancer

Inhibition of carcinogenesis may be a consequence of attenuation of oxidative stress via activation of antioxidant defence system, restoration and stabilization of tumour suppressor proteins along with modulation of inflammatory mediators. Previously we have delineated significant role of curcumin during its long term effect in regulation of glycolytic pathway and angiogenesis, which in turn results in prevention of cancer via modulation of stress activated genes. Present study was designed to investigate long term effect of curcumin in regulation of Nrf2 mediated phase-II antioxidant enzymes, tumour suppressor p53 and inflammation under oxidative tumour microenvironment in liver of T-cell lymphoma bearing mice. Inhibition of Nrf2 signalling observed during lymphoma progression, resulted in down regulation of phase II antioxidant enzymes, p53 as well as activation of inflammatory signals. Curcumin potentiated significant increase in Nrf2 activation. It restored activity of phase-II antioxidant enzymes like GST, GR, NQO1, and tumour suppressor p53 level. In addition, curcumin modulated inflammation via upregulation of TGF-β and reciprocal regulation of iNOS and COX2. The study suggests that during long term effect, curcumin leads to prevention of cancer by inducing phase-II antioxidant enzymes via activation of Nrf2 signalling, restoration of tumour suppressor p53 and modulation of inflammatory mediators like iNOS and COX2 in liver of lymphoma bearing mice.
Combining local‐structure, fold‐recognition, and new fold methods for protein structure prediction

This article presents an overview of the SAM‐T02 method for protein fold recognition and the UNDERTAKER program for ab initio predictions. The SAM‐T02 server is an automatic method that uses two‐track hidden Markov models (HMMS) to find and align template proteins from PDB to the target protein. The two‐track HMMs use an amino acid alphabet and one of several different local structure alphabets. The UNDERTAKER program is a new fragment‐packing program that can use short or long fragments and alignments to create protein conformations. The HMMs and fold‐recognition alignments from the SAM‐T02 method were used to generate the fragment and alignment libraries used by UNDERTAKER. We present results on a few selected targets for which this combined method worked particularly well: T0129, T0181, T0135, T0130, and T0139. Proteins 2003;53:491–496. © 2003 Wiley‐Liss, Inc.
A FRET-Based Real-Time PCR Assay to Identify the Main Causal Agents of New World Tegumentary Leishmaniasis

In South America, various species of Leishmania are endemic and cause New World tegumentary leishmaniasis (NWTL). The correct identification of these species is critical for adequate clinical management and surveillance activities. We developed a real-time polymerase chain reaction (PCR) assay and evaluated its diagnostic performance using 64 archived parasite isolates and 192 prospectively identified samples collected from individuals with suspected leishmaniasis enrolled at two reference clinics in Lima, Peru. The real-time PCR assay was able to detect a single parasite and provided unambiguous melting peaks for five Leishmania species of the Viannia subgenus that are highly prevalent in South America: L. (V.) braziliensis, L. (V.) panamensis, L. (V.) guyanensis, L. (V.) peruviana and L. (V.) lainsoni. Using kinetoplastid DNA-based PCR as a gold standard, the real-time PCR had sensitivity and specificity values of 92% and 77%, respectively, which were significantly higher than those of conventional tests such as microscopy, culture and the leishmanin skin test (LST). In addition, the real-time PCR identified 147 different clinical samples at the species level, providing an overall agreement of 100% when compared to multilocus sequence typing (MLST) data performed on a subset of these samples. Furthermore, the real-time PCR was three times faster and five times less expensive when compared to PCR - MLST for species identification from clinical specimens. In summary, this new assay represents a cost-effective and reliable alternative for the identification of the main species causing NWTL in South America.
PolicyGlobe: a framework for integrating network and operating system security policies

In modern networked systems with many machines and traffic control devices (such as firewalls), it is difficult to determine the overall effect of the security policies and configurations implemented inside the operating system and network devices. This paper describes PolicyGlobe, a framework to integrate operating system and network security policies. Using the idea of accessibility sets, PolicyGlobe integrates the Security Enhanced Linux (SE-Linux) access control policies with firewall configurations and traffic control policies. Using this framework, it is possible to construct a global accessibility set for each process in the system. PolicyGlobe makes it possible to determine the global effect of the local security policies and firewall configurations and answer the basic questions "can a subject in one machine access an object in another machine? " We have developed the integration algorithms, optimized the algorithms, implemented the entire framework, and conducted empirical studies on it. The studies show that in a network of 10 densely connected machines each with a large SE-Linux policy (~275,000 lines of rules), PolicyGlobe can build the global accessibility sets in about 10 minutes. In a system with a more limited connectivity, the analysis takes a much shorter amount of time.
Dye solar cell design parameter optimization using Silvaco ATHENA and ATLAS

Dye Solar Cell (DSC) is one of the third generation solar cell. It uses nontoxic material and relatively easy to fabricate. However, its conversion efficiency still needs to be improved. In this paper, DSC is simulated using Silvaco ATHENA and ATLAS. Parameters such as TiO2 layer thickness and electrolyte concentration are investigated. Effect of TiO2 morphology and additional TiO2 passivation layer are also studied. Properties of the parameters are extracted from literatures as the input for the simulation. Validation with published experimental works by other group is also performed. Results showed that by optimizing TiO2 thickness, TiO2 composite, electrolyte concentration and TiO2 passivation layer, DSC conversion efficiency can be improved up to 4.592%.
A Next-Generation Sequencing Method for Genotyping-by-Sequencing of Highly Heterozygous Autotetraploid Potato

Assessment of genomic DNA sequence variation and genotype calling in autotetraploids implies the ability to distinguish among five possible alternative allele copy number states. This study demonstrates the accuracy of genotyping-by-sequencing (GBS) of a large collection of autotetraploid potato cultivars using next-generation sequencing. It is still costly to reach sufficient read depths on a genome wide scale, across the cultivated gene pool. Therefore, we enriched cultivar-specific DNA sequencing libraries using an in-solution hybridisation method (SureSelect). This complexity reduction allowed to confine our study to 807 target genes distributed across the genomes of 83 tetraploid cultivars and one reference (DM 1–3 511). Indexed sequencing libraries were paired-end sequenced in 7 pools of 12 samples using Illumina HiSeq2000. After filtering and processing the raw sequence data, 12.4 Gigabases of high-quality sequence data was obtained, which mapped to 2.1 Mb of the potato reference genome, with a median average read depth of 63× per cultivar. We detected 129,156 sequence variants and genotyped the allele copy number of each variant for every cultivar. In this cultivar panel a variant density of 1 SNP/24 bp in exons and 1 SNP/15 bp in introns was obtained. The average minor allele frequency (MAF) of a variant was 0.14. Potato germplasm displayed a large number of relatively rare variants and/or haplotypes, with 61% of the variants having a MAF below 0.05. A very high average nucleotide diversity (π = 0.0107) was observed. Nucleotide diversity varied among potato chromosomes. Several genes under selection were identified. Genotyping-by-sequencing results, with allele copy number estimates, were validated with a KASP genotyping assay. This validation showed that read depths of ∼60–80× can be used as a lower boundary for reliable assessment of allele copy number of sequence variants in autotetraploids. Genotypic data were associated with traits, and alleles strongly influencing maturity and flesh colour were identified.
ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management

This paper describes our system, called ITC-UT, for the task-2 (on-line reputation management task) in WePS-3. Our idea is to categorize each query into 3 or 4 classes according to how much the tweets retrieved by the query contain the “true” entity names that refer to the target entity, and then categorize each tweet by the rules defined for each class of queries. We show the evaluation results for our system along with the details of results of query categorization.
A novel image splicing detection method based on the inconsistency of image noise

Aiming at localizing tampered image regions, a novel detection method is proposed. Based on the statistical properties of image features, we expose the tampered parts by dividing image into some sub-blocks and computing the noise variance of each ones. Then we choose Laplace fitting based on the maximal likelihood estimation method to decide the boundary between tampered regions and the original. Several examples are shown to demonstrate the proposed method's output. We also demonstrate the efficiency of our method in paper.
A Compact DC-30 GHz 0.13-um CMOS SP4T Switch

This paper presents a DC−30 GHz single-pole- four-throw (SP4T) CMOS switch using 0.13 μ mC MOS process. The CMOS transistor layout is done to minimize the substrate network resistance. The on-chip matching inductors and routing are designed for a very small die area (250 × 180 μm 2 ), and modeled using full-wave EM simulations. The SP4T CMOS switch result in an insertion loss of 1.8 dB and 2.7 dB at 5 GHz and 24 GHz, respectively. The isolation is > 25 dB up to 30 GHz and achieved using a series-shunt switch configuration. The measured input P1dB and IIP3 of the SP4T switch are 9 dBm and 21 dBm, respectively. To our knowledge, this is the first ultra wideband CMOS SP4T switch and with a very small chip area. Index Terms— microwave switch, CMOS switch, SP4T, T/R switch, substrate resistance, RFIC
A Hashtag Worth a Thousand Words: Discursive Strategies Around #JeNeSuisPasCharlie After the 2015 Charlie Hebdo Shooting

Following a shooting attack by two self-proclaimed Islamist gunmen at the offices of French satirical weekly Charlie Hebdo on 7 January 2015, there emerged the hashtag #JeSuisCharlie on Twitter as an expression of solidarity and support for the magazine’s right to free speech. Almost simultaneously, however, there was also #JeNeSuisPasCharlie explicitly countering the former, affirmative hashtag. Based on a multimethod analysis of 74,047 tweets containing #JeNeSuisPasCharlie posted between 7 and 11 January, this article reveals that users of the hashtag under study employed various discursive strategies and tactics to challenge the mainstream framing of the shooting as the universal value of freedom of expression being threatened by religious extremism, while protecting themselves from the risk of being viewed as disrespecting victims or endorsing the violence committed. The significance of this study is twofold. First, it extends the literature on strategic speech acts by examining how such acts take place in a social media context. Second, it highlights the need for a multidimensional and reflective methodology when dealing with data mined from social media.
Spatiotemporal Sparsity Induced Similarity Measure for Human Action Recognition

In this paper, we propose a model-free method for human action recognition via sparse spatiotemporal representation. Similar to the template matching method, the philosophy of the proposed method is to decompose each video sample containing one kind of human actions as a 1 sparse linear combination of several video samples containing multiple kinds of human actions. To realize this goal, we mainly focus on three problems, feature point detection and description for human action, spatiotemporal feature construction for action video representation, and action video decomposition via sparse representation. The contributions of this method lies in three-folds: 1) the proposed method does not depend on complicated model selection and learning; 2) it can handle the action recognition under difference scenarios by multiple persons; 3) the generalization ability of the method can be easily extended by simply adding bases, the new labeled action video. To demonstrate the superiority of the proposed method, we evaluate it on KTH dataset, the well known dataset for human action recognition. Large scale experiment shows the accuracy and robustness of the method. Moreover, the proposed method outperforms most of the state-of-art methods for human behavior recognition.
Genetic and Endocrine Tools for Carnivore Surveys

ahead of science in imagining the information that could be obtained from single hairs or feces. Indeed, from Aldous Huxley’s Brave New World (1932) to the cult movie GATTACA (Columbia Pictures Corporation 1997), writers and producers foreshadowed the scientific value of noninvasive samples. In the 1990s, with the advance of both molecular genetics and endocrine biology, forensic scientists developed tools to determine the identity, sex, health, and social status of humans from samples left at crime scenes (e.g., hair, scat, urine, saliva). As with many technological advances in human biology, these developments soon transferred to other disciplines—including wildlife biology. In this chapter, we review the state-of-the-art tools that molecular and endocrine biologists employ to learn about carnivores and other wildlife through noninvasive means. The chapter is divided into three sections, with the first describing advances in molecular ecology, the second recounting advances in endocrinology, and the final section briefly discussing the synergy obtained by combining DNA and endocrine tools for understanding carnivore ecology. The primary objectives of this chapter are to (1) provide a general overview of laboratory methods and demonstrate their application via examples; Chapter 9
Multiprocessor scheduling and rescheduling with use of cellular automata and artificial immune system support

The paper presents cellular automata (CA)-based multiprocessor scheduling system, in which an extraction of knowledge about scheduling process occurs and this knowledge is used while solving new instances of the scheduling problem. There are three modes of the scheduler: learning, normal operating, and reusing. In the learning mode, a genetic algorithm is used to discover CA rules suitable for solving instances of a scheduling problem. In the normal operating mode, discovered rules are able to find automatically, without a calculation of a cost function, an optimal or suboptimal solution of the scheduling problem for any initial allocation of program tasks in a multiprocessor system. In the third mode, previously discovered rules are reused with support of an artificial immune system (AIS) to solve new instances of the problem. We present a number of experimental results showing the performance of the CA-based scheduler.
Participation Costs, Trend Chasing, and Volatility of Stock Prices

We analyze an overlapping generations model with fixed costs of stock market participation. Participation in the stock market is determined endogenously and covaries positively with preceding innovations in dividends. The equilibrium share price is positively related to market participation of the same period and to information about future dividends. There is "rational trend chasing" in the sense that, although all agents are rational, market participation rises after an increase of the share price and falls after a decrease. Finally, we show that the endogenous fluctuations of market participation lead to increased volatility of the share price. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.
Usability measurement in context

Abstract Different approaches to the measurement of usability are reviewed and related to definitions of usability in international standards. It is concluded that reliable measures of overall usability can only be obtained by assessing the effectiveness, efficiency and satisfaction with which representative users carry out representative tasks in representative environments.This requires a detailed understanding of the context of use of a product. The ESPRIT MUSiC project has developed tools which can be used to measure usability in the laboratory and the field. An overview is given of the methods and tools for measuring user performance, cognitive workload, and user perceived quality.
Plain cigarette packs do not exert Pavlovian to instrumental transfer of control over tobacco-seeking

Aims To gain insight into the potential impact of plain tobacco packaging policy, two experiments were undertaken to test whether ‘prototype’ plain compared with branded UK cigarette pack stimuli would differentially elicit instrumental tobacco-seeking in a nominal Pavlovian to instrumental transfer (PIT) procedure. Design, Setting and Participants Two experiments were undertaken at the University of Bristol UK, with a convenience sample of adult smokers (experiment 1, n = 23, experiment 2, n = 121). Measurement In both experiments, smokers were trained on a concurrent choice procedure in which two responses earned points for cigarettes and chocolate, respectively, before images of branded and plain packs were tested for capacity to elicit the tobacco-seeking response in extinction. The primary outcome was percentage choice of the tobacco- over the chocolate-seeking response in plain pack, branded pack and no-stimulus conditions. Findings Both experiments found that branded packs primed a greater percentage of tobacco-seeking (overall mean = 62%) than plain packs (overall mean = 53%) and the no-stimulus condition (overall mean = 52%; Ps ≤ 0.01, ŋp2s ≥ 0.16), and that there was no difference in percentage tobacco-seeking between plain packs and the no-stimulus condition (Ps ≥ 0.17, ŋp2s ≤ 0.04). Plain tobacco packs showed an overall 9% reduction in the priming of a tobacco choice response compared to branded tobacco packs. Conclusions Plain packaging may reduce smoking in current smokers by degrading cue-elicited tobacco-seeking.
3D Object Model Fitting to Still Images Using Linear Combination Method of 2D Aspect Images

This paper describes a method for fitting 3D object model to still (single) 2D observed image by searching for the model's optimum posture parameters in the parameter space through LMM iteration method (a stabilized Gauss-Newton method). In the method, we propose a new approach to feeding an excellent initial parameter value to the iteration method via aspect identification by applying linear combination method of 2D aspect imaged[l], and via restricting the feature correspondence between the 2D image and the model's projection image to their circumferential features. Due to these schemes, the method gives a simple, fast and robust procedure. Numerical simulation using 500 randomly postured synthetic images of an irregular pentagonal prism shows 100% correct match only in 2.98 average iteration counts of the LMM method.
A primer on the theory of frames

This report aims to give an overview of frame theory in order to gain insight in the use of the frame framework as a unifying layer in the Large Time-Frequency Analysis Toolbox (LTFAT). In the first section the general concept of a frame is introduced and some of its properties are defined. In the second section some linear operators associated with frames are introduced and their use for the construction of canonical frames and the computation of the frame bounds are stated. In these first sections frames are notated as general collections or families and the operators associated with frames as mappings since this is also the way they are presented in the LTFAT. In the third section frames and their associated operators are described in terms of matrices in order to gain insight in the computational aspects of frames. The concept of a frame was first introduced in [5] in the context of nonharmonic Fourier series. In this context the frame forms a system of complex exponentials. Frames were studied in the same context further in [9]. In [4] the concept of a frame was generalized to other contexts than nonharmonic Fourier series which leads to general nonorthogonal expansions in a Hilbert space. In the meantime frame theory became a relevant subject in several disciplines and is studied in several contexts. 1 Frames A frame of a Hilbert space H is a collection of elements {fk}k∈I⊆Z ⊆ H that spans H. Formally, a collection of elements {fk}k∈I ⊆ H is a frame for H if there exist two constants 0 < A ≤ B <∞ for which ∀f ∈ H, A ||f || ≤ ∑ k ∈ I | 〈f, fk〉 | ≤ B ||f || (1) The statement expressed in (1) is in general called the frame condition and it guarantees that any f ∈ H can be constructed from the frame {fk}k∈I .
The dangers of relentless pursuit: teaching, personal health, and the symbolic/real violence of Teach For America

ABSTRACT This paper examines the pressures experienced by teachers as they strive to embody the Teach For America (TFA) motif of ‘relentless pursuit’. It draws on interviews conducted with 36 teachers and uses a Bourdieuian analysis to consider the mechanisms of control manifested through socialization and corps member habituation. The findings suggest that corps members experience both symbolic and self-imposed overt violence as they aim to meet the demands of TFA. This has implications for the increasing number of teachers in programs around like TFA as well as the broader discourses of teacher accountability and the teaching profession.
Seismic interpretation using global image segmentation

Summary A rst step in seismic interpretation is seismic image segmentation. For most seismic images, with incompletely or poorly imaged faults and horizons, global methods for segmentation are more robust than local event tracking or region growing methods commonly used today. The disadvantage of global image segmentation methods has been their relatively high computational cost. We reduce this cost by applying these methods to a space-lling mesh aligned automatically with features in seismic images. The mesh makes global segmentation of 3-D seismic images feasible.
Indoor Positioning Using Fingerprinting With Locata Signals

This research studies indoor positioning using power-level-fingerprinting with a time-synchronised Locata network. We compare our results to another fingerprinting-based positioning method using WiFi access points. With an accuracy of 1.2 - 1.5 metres, our technique can be a powerful fall-back option when regular Locata positioning fails due to difficult signal conditions. Moreover, our results serve as a benchmark for future research on indoor positioning with Locata.