Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonnegative sparse representation based on the determinant measure

Recently, sparse representations via an overcomplete dictionary has become a major field of researches in signal processing. This paper focuses on sparse representation of nonnegative signals since signals and corresponding dictionary have nonnegativity limitations in some applications, e.g., multispectral data analysis. We present a novel sparsity measure based on a kind of determinant of matrix. Unlike the conventional sparsity measures, the proposed measure is differentiable and easy to optimize. Based on this measure, a new sparse model is derived, and an iterative sparseness minimization approach is proposed to solve this model. In the approach, the nonnegative sparse representation problem can be cast into row-to-row optimizations with respect to the sparse coefficient matrix, and then the quadratic programming (QP) is used to optimize each row. Numerical experiments on recovery of the sparse coefficient and synthesis dictionary show the effectiveness of the proposed algorithm.
The Price Consideration Model of Brand Choice

The workhorse brand choice models in marketing are the multinomial logit (MNL) and nested multinomial logit (NMNL). These models place strong restrictions on how brand share and purchase incidence price elasticities are related. In this paper, we propose a new model of brand choice, the “price consideration” (PC) model, that allows more flexibility in this relationship. In the PC model, consumers do not observe prices in each period. Every week, a consumer decides whether to consider a category. Only then does he/she look at prices and decide whether and what to buy. Using scanner data, we show the PC model fits much better than MNL or NMNL. Simulations reveal the reason: the PC model provides a vastly superior fit to inter-purchase spells.
ARF Noncoding RNA Whose Expression Coclusters with , an Antisense ANRIL Tumor Family : Identification of Locus , in a Melanoma-Neural System INK 4 / ARF Entire Characterization of a GermLine Deletion

We have previously detected a large germ-line deletion, which included the entire p15/CDKN2B-p16/CDKN2A-p14/ARF gene cluster, in the largest melanoma-neural system tumor (NST) syndrome family known to date by means of heterozygosity mapping based on microsatellite markers. Here, we used gene dose mapping with sequence-tagged site real-time PCR to locate the deletion end points, which were then precisely characterized by means of long-range PCR and nucleotide sequencing. The deletion was exactly 403,231 bp long and included the entire p15/CDKN2B, p16/CDKN2A , and p14/ARF genes. We then developed a simple and rapid assay to detect the junction fragment and to serve as a direct predictive DNA test for this large French family. We identified a new large antisense noncoding RNA (named ANRIL) within the 403-kb germ-line deletion, with a first exon located in the promoter of the p14/ARF gene and overlapping the two exons of p15/CDKN2B . Expression of ANRIL mainly coclustered with p14/ARF both in physiologic (various normal human tissues) and in pathologic conditions (human breast tumors). This study points to the existence of a new gene within the p15/ CDKN2B-p16/CDKN2A-p14/ARF locus putatively involved in melanoma-NST syndrome families and in melanoma-prone families with no identified p16/CDKN2A mutations as well as in somatic tumors. [Cancer Res 2007;67(8):3963–9]
Serotonin-1A Autoreceptors Are Necessary and Sufficient for the Normal Formation of Circuits Underlying Innate Anxiety

Identifying the factors contributing to the etiology of anxiety and depression is critical for the development of more efficacious therapies. Serotonin (5-HT) is intimately linked to both disorders. The inhibitory serotonin-1A (5-HT1A) receptor exists in two separate populations with distinct effects on serotonergic signaling: (1) an autoreceptor that limits 5-HT release throughout the brain and (2) a heteroreceptor that mediates inhibitory responses to released 5-HT. Traditional pharmacologic and transgenic strategies have not addressed the distinct roles of these two receptor populations. Here we use a recently developed genetic mouse system to independently manipulate 5-HT1A autoreceptor and heteroreceptor populations. We show that 5-HT1A autoreceptors act to affect anxiety-like behavior. In contrast, 5-HT1A heteroreceptors affect responses to forced swim stress, without effects on anxiety-like behavior. Together with our previously reported work, these results establish distinct roles for the two receptor populations, providing evidence that signaling through endogenous 5-HT1A autoreceptors is necessary and sufficient for the establishment of normal anxiety-like behavior.
Differential Noise Figure De-Embedding: A Comparison of Available Approaches

A new matrix-based approach for de-embedding the noise figure of a differential device has been recently presented. In this paper, an enhancement to this method will be provided. The new method will be compared to state-of-the-art approaches. For comparison, measurements have been performed on an amplifier with distinct transfer characteristics. The respective integrated circuit is composed of two single-ended amplifiers placed in close proximity within the layout. Due to capacitive cross-couplings arising from this arrangement, the differential noise figure is degraded compared to the single-ended one, which indicates the requirement of differential excitation. For completion, measurements have also been performed on a differential device. A commercially available evaluation board has been used for this purpose and measurement results agree well with those specified by the manufacturer.
Graphical-Information Central of Composite Analysis on Big Sensor-Data of Engineering Inspection

The amounts of data volume are escalated in the scientific and engineering fields by the improvement of instruments as higher resolution or rates commence more precise or accurate analyses. The aim of this work is to comprise an information system for maintenance of one physical system, a train consist. The information of the entity is provided by collecting, managing and analyzing the sensor data along the part's lifetime. The data gathered at local storages is staged as time goes on and the data volume overwhelms the processing capacity of an ordinary computing system. The big data processing would be constituted with desktop PCs and a few server machines.
AKAMAS: Mining association rules using a new algorithm for the assessment of the risk of coronary heart events

Many algorithms have been developed for rule mining in large transaction databases. Discovery of some important association rules is a main database mining problem. The objective of this study was to develop a new data mining algorithm named AKAMAS using different measures to extract the most important association rules for the assessment of heart event related risk factors. The implemented measures were: support, confidence, p-value, chi square, coverage, prevalence, recall, specificity, accuracy, lift, leverage, added value, relative risk, odds ratio, and conviction. The AKAMAS algorithm is a variant of the Apriori algorithm, the main difference is that it does not use the iterative technique of k-itemset to build the (k +1)- itemsets. It needs only one pass for extracting frequent itemsets. Although AKAMAS gave similar rules to Apriori it offers a wide selection of measures for filtering the best rules, including the computation of the chi square test, and its associated probability value (i.e. if a rule is statistically significant or not). Moreover, the rules are more comprehensively represented and are more easily to interpret.
Building Rich User Profiles for Personalized News Recommendation

Nowadays, more and more people are using online news platforms as their main source of information about daily life events. Users of such platforms have access to an increasing amount of articles of different topics, stories, and view points. Thus, a news personalization service is needed to filter the flow of available information and satisfy users needs. To this end, it is crucial to understand and build accurate profiles for both users and news articles. In this paper, we propose a new approach that exploits users comments to recommend articles. We build the profile of each user based on (1) the set of entities he talked about it in his comments, (2) and the set of aspects related to those entities. The same information is extracted from the content of each news article to create its profile. These profiles are then matched for the purpose of recommendation. We have used a collection based on real users activities in four news web sites, namely The Independent, The Telegraph, CNN and ALJazeera. The first results show that our approach outperforms baseline approaches achieving high accuracy.
Multiview Metric Learning with Global Consistency and Local Smoothness

In many real-world applications, the same object may have different observations (or descriptions) from multiview observation spaces, which are highly related but sometimes look different from each other. Conventional metric-learning methods achieve satisfactory performance on distance metric computation of data in a single-view observation space, but fail to handle well data sampled from multiview observation spaces, especially those with highly nonlinear structure. To tackle this problem, we propose a new method called Multiview Metric Learning with Global consistency and Local smoothness (MVML-GL) under a semisupervised learning setting, which jointly considers global consistency and local smoothness. The basic idea is to reveal the shared latent feature space of the multiview observations by embodying global consistency constraints and preserving local geometric structures. Specifically, this framework is composed of two main steps. In the first step, we seek a global consistent shared latent feature space, which not only preserves the local geometric structure in each space but also makes those labeled corresponding instances as close as possible. In the second step, the explicit mapping functions between the input spaces and the shared latent space are learned via regularized locally linear regression. Furthermore, these two steps both can be solved by convex optimizations in closed form. Experimental results with application to manifold alignment on real-world datasets of pose and facial expression demonstrate the effectiveness of the proposed method.
The Interferon-Induced Gene Ifi27l2a is Active in Lung Macrophages and Lymphocytes After Influenza A Infection but Deletion of Ifi27l2a in Mice Does Not Increase Susceptibility to Infection

Interferons represent one of the first and essential host defense mechanisms after infection, and the activation of the IFN-pathway results in the transcriptional activation of hundreds of interferon-stimulated genes. The alpha-inducible protein 27 like 2A (Ifi27l2a) gene (human synonym: ISG12) is strongly up-regulated in the lung after influenza A infection in mice and has been shown in gene expression studies to be highly correlated to other activated genes. Therefore, we investigated the role of Ifi27l2a for the host defense to influenza A infections in more detail. RT-PCR analyses in non-infected mice demonstrated that Ifi27l2a was expressed in several tissues, including the lung. Detailed analyses of reporter gene expression in lungs from Ifi27l2a-LacZ mice revealed that Ifi27l2a was expressed in macrophages and lymphocytes but not in alveolar cells or bronchiolar epithelium cells. The number of macrophages and lymphocyte strongly increased in the lung after infection, but no significant increase in expression levels of the LacZ reporter gene was found within individual immune cells. Also, no reporter gene expression was found in bronchiolar epithelial cells, alveolar cells or infiltrating neutrophils after infection. Thus, up-regulation of Ifi27l2a in infected lungs is mainly due to the infiltration of macrophages and lymphocytes. Most surprisingly, deletion of Ifi27l2a in mouse knock-out lines did not result in increased susceptibility to infections with H1N1 or H7N7 influenza A virus compared to wild type C57BL/6N mice, suggesting a less important role of the gene for the host response to influenza infections than for bacterial infections.
Agile Principles and Ethical Conduct

Software practitioners experience pressure to compromise their work and their reasonable care for others. Even as software becomes more beneficial, pervasive, and interconnected, the potential for unintended harm grows. Agile Software Development is an approach to building software systems that embodies a set of declared core principles. How do these principles align to an ethical standard of conduct? This paper attempts from an Agile Practitioner's perspective to compare and contrast Agile Principles with other approaches to Software Ethics. It identifies areas of strong resonance and gaps that exist between the stated Agile Principles and an explicit software code of ethical conduct.
Measuring the Response of Macroeconomic Uncertainty to Shocks

Recent research documents the importance of uncertainty in determining macroeconomic outcomes, but little is known about the transmission of uncertainty across such outcomes. This paper examines the response of uncertainty about inflation and output growth to shocks documenting statistically significant size and sign bias and spillover effects. Uncertainty about inflation is a determinant of output uncertainty, whereas higher growth volatility tends to raise inflation volatility. Both inflation and growth volatility respond asymmetrically to positive and negative shocks. Negative growth and inflation shocks lead to higher and more persistent uncertainty than shocks of equal magnitude but opposite sign.
Student Success Does Not Arise By Chance

Vincent Tinto is a national expert on student persistence and success whose book Leaving College, Rethinking the Causes and Cures of Student Attrition (University of Chicago Press, 1987) established the first widely adopted model of student departure. His most recent book, Completing College: Rethinking Institutional Action (University of Chicago Press, 2012) lays out a framework for institutional action for student success, describes the range of programs that have been effective in enhancing student success, and the types of policies institutions should adopt to successfully implement programs in ways that endure and scale-up over time. In this seminar, Dr.Tinto will provide a commentary on MSU’s efforts to increase student success based on the frameworks he has developed, and will place our efforts in a national perspective. *In addition to the morning LEAD session, Dr. Tinto will be speaking to additional groups throughout the day. For a full schedule, please visit: http://fod.msu. edu/Tinto [1].
Broadband 65nm CMOS SOI LNA for a 100Gbit/s fiber-optic SCM transceiver

The suitability of the ST Microelectronics 65nm CMOS LP SOI process on HR substrate for a 100Gbit/s fiber-optic SCM transceiver LNA is examined in this paper. A broadband single stage and three stage LNA, using requirements derived from system simulations, were designed with bandwidths from 2GHz to 40GHz and 2GHz to 26GHz at gains of 5dB and 15dB respectively. A noise figure of ~5-7dB was obtained. Although the LNA noise figure is not as good, when compared to LNAs designed using other semiconductor technologies, it is still sufficient to be considered for the application, and has the advantage that it can be integrated with complex digital and analog baseband CMOS circuits.
Youth Web Spaces: Design Requirements, Framework, and Architecture of Wikis to Promote youth Well Being

Youth is a period of rapid emotional, physical and intellectual change, where young people progress from being dependent children to independent adults. Young people who are unable to make this transition smoothly can face significant difficulties in both the short and long term. Although the vast majority of young people are able to find all the resources they need for their health, well-being and development within their families and living environments, some young people have difficulty in locating resources that can help them and moreover, difficulty in integrating into society. One way to support this transition is to create an environment that enables youth to be well supported through the provision of information and the creation of a community where youth feel empowered to collaborate with their peers as well as decision makers and legislators. This article focuses on the exploring the use of the Internet by youth and how youth well-being can be improved through the design of a youth-friendly web space. This article begins with a definition of youth well-being and what this means in the context of the Web. We propose key requirements for the design of youth web spaces that will result in their well-being. We use these requirements to analyse existing web spaces and conclude with the problems and issues that need to be addressed. These problems, issues and requirements then motivate us to propose a framework and architecture for the design and implementation of Wikis for enhancing youth well-being.
A new model of QIM data hiding for quality access control of digital image

This paper proposes a data-hiding scheme for quality access control of digital images using a new model of quantization index modulation (QIM). An encoded binary watermark is embedded over N-mutually orthogonal signal points using QIM but without complete self-noise suppression. It is well known that due to insertion of external information, there will be degradation in visual quality of the host image (cover) that plays the key role in access control through reversible process. Decision variable for each bit of watermark decoding is formed from the weighted average of N-decision statistics that increases the correctness of extracted watermark bits. The self-noise is suppressed by authorized user to provide better quality image. The simulation results have shown the validity of those claims.
Time-dependent correlations in quantum magnets at finite temperature

In this Rapid Communication we investigate the time dependence of the gap mode of copper nitrate at various temperatures. We combine state-of-the-art theoretical calculations with high precision neutron resonance spin-echo measurements to understand the anomalous decoherence effects found previously in this material. It is shown that the time domain offers a complementary view on this phenomenon, which allows us to directly compare experimental data and theoretical predictions without the need of further intensive data analysis, such as (de)convolution.
Consistent Model Selection Criteria on High Dimensions

Asymptotic properties of model selection criteria for high-dimensional regression models are studied where the dimension of covariates is much larger than the sample size. Several sufficient conditions for model selection consistency are provided. Non-Gaussian error distributions are considered and it is shown that the maximal number of covariates for model selection consistency depends on the tail behavior of the error distribution. Also, sufficient conditions for model selection consistency are given when the variance of the noise is neither known nor estimated consistently. Results of simulation studies as well as real data analysis are given to illustrate that finite sample performances of consistent model selection criteria can be quite different.
Resisting Global Toxics: Transnational Movements for Environmental Justice

Every year, nations and corporations in the "global North" produce millions of tons of toxic waste. Too often this hazardous material -- inked to high rates of illness and death and widespread ecosystem damage -- is exported to poor communities of color around the world. In Resisting Global Toxics, David Naguib Pellow examines this practice and charts the emergence of transnational environmental justice movements to challenge and reverse it. Pellow argues that waste dumping across national boundaries from rich to poor communities is a form of transnational environmental inequality that reflects North/South divisions in a globalized world, and that it must be theorized in the context of race, class, nation, and environment. Building on environmental justice studies, environmental sociology, social movement theory, and race theory, and drawing on his own research, interviews, and participant observations, Pellow investigates the phenomenon of global environmental inequality and considers the work of activists, organizations, and networks resisting it. He traces the transnational waste trade from its beginnings in the 1980s to the present day, examining global garbage dumping, the toxic pesticides that are the legacy of the Green Revolution in agriculture, and today's scourge of dumping and remanufacturing high tech and electronics products. The rise of the transnational environmental movements described in Resisting Global Toxics charts a pragmatic path toward environmental justice, human rights, and sustainability.
Redes Complexas Aplicadas no Reconhecimento de Faces

Este artigo apresenta uma nova metodologia para o reconhecimento de faces, um importante e difícil problema que tem sido estudado pela comunidade de visão computacional e reconhecimento de padrões. A metodologia utilizada modela a imagem de uma face através de uma rede complexa e medidas são extraídas sobre essas redes para a composição do vetor de característica. Os experimentos foram conduzidos usando diferentes configurações, incluindo modificações no limiar para a modelagem da rede. A metodologia com redes foi comparada com a técnica eigenfaces, obtendo resultados promissores.
Degeneracy enriches artificial chemistry binding systems

We hypothesise that degeneracy in the components of an artificial chemistry (AChem) facilitates the complexity of the system as a whole. We introduce definitions of degeneracy and redundancy, and show how these quantities can be calculated for the binding system of an AChem. We present a case study using the AChem Stringmol, in order to support our hypothesis. We demonstrate that the binding system in Stringmol has degeneracy and we create a deliberately poor variant: ‘sticky-Stringmol’, that has a binding system with no degeneracy. Comparing sticky-Stringmol to Stringmol, we note the loss of many simulation artifacts that have been used as evidence of the complexity of Stringmol, including: emergent macro-mutations, hypercycles, sweeps and parasite evasion. These results are evidence that degeneracy in the components of an AChem facilitates the complexity of the system as a whole.
Using machine learning algorithms to find patterns in stock prices

This paper analyzes the regulation of access to, and activity of, the legal and medical professions. A critical assessment is offered of the economic theory of the regulation of professions in relation to the key issues of: (a) Why regulate, (b) How to regulate, and (c) What to regulate. We suggest a set of indicators to measure the quality of regulatory restrictions, and thereby expose comparative inefficiencies, in the medical and legal professional activities. We conclude that generally speaking the USA followed by Norway, the UK [England and Wales] and Belgium perform better in terms of efficient regulation, whereas Germany, Austria and Portugal perform badly for both legal and medical professionals. Other countries (including the Netherlands, Spain, France) vary. Our results are partly, but not entirely, consistent with previous findings.