Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding Family Meanings: A Reflective Text

Jane Ribbens McCarthy, Megan Doolittle and Shelley Day Sclater. Understanding Family Meanings: A Reflective Text. Bristol, UK: The Policy Press, University of Bristol (2012). 287 pages, ISBN 9781447301134. First published in 2008 by The Open University.The goal of this book, which is clearly aimed toward graduate and undergraduate students and interested public who are just beginning to investigate the meaning of family, is to offer a comprehensive and challenging look at the subject of family. The book is ideally suited to undergraduate sociology, anthropology and family studies students. The authors look at the social, cultural, political and personal meanings of family and at some of the controversies surrounding how to define family for census purposes. This book seeks to look at family meanings in many different contexts and examines issues of power, inequality and values. It is clearly a text designed to explore family studies for the edification of individuals, researchers, public policymakers and professionals as they grapple with the notion of what constitutes a family. The book also emphasizes the idea that family is a fluid and dynamic concept, whose meanings can shift depending upon the context under discussion.The book is divided into three parts. Part 1 looks at Research [why family meanings; family meanings in contemporary contexts; teasing threads apart; understanding family and household through quantitative evidence]. Part 2 looks at Theories and Concepts [family discourses and family practices; intimacy and personal life]. Part 3 looks at Contexts [family meanings across time and place; family meanings in social policies and professional practices; family meanings and family values]. Chapters include plenty of discussion, as well as activities, reflections, real-life examples, comments, supplemental readings, visual graphs, models [e.g., the ecological model shown on p. 238 and the ecological model describing the risk factors for child maltreatment on p. 241], charts, diagrams, hand-written and even historical census data, helpful exercises and thorough references and citations to assist readers. There is also an important section on reading statistics with a critical eye [p. 101 -102], excellent given the student audience to which the book is addressed. Chapters also include helpful summaries to help students remember and reinforce concepts.The authors point out that family life is often portrayed in the media as having "gone wrong" or "gone bad" compared to the halcyon olden golden days. I remember vividly getting a call from a respected journalist for National Public Radio who said she wanted to do a piece on the disintegration of the American family and could she quote me as saying as much; despite spending several hours with her going over the history and current statistics and all the subtleties about families in America, she chose to ignore the complexities and go for one quote that seemed to buttress her argument. …
Crowdsourcing the Creation of a Word – Emotion Association Lexicon

Even though considerable attention has been given to semantic orientation of words and the creation of large polarity lexicons, research in emotion analysis has had to rely on limited and small emotion lexicons. In this paper we show how the combined strength and wisdom of the crowds can be used to generate a large, high-quality, word–emotion association lexicon quickly and inexpensively. We flesh out various challenges in emotion annotation in a crowdsourcing scenario and propose solutions to address them. Most notably, in addition to questions about emotions associated with terms, we show how the inclusion of a word choice question can discourage malicious data entry, help identify instances where the annotator may not be familiar with the target term (allowing us to reject such annotations), and help obtain annotations at sense level (rather than at word level). We perform an extensive analysis of the annotations to better understand the distribution of emotions evoked by terms of different parts of speech. We identify which emotions tend to be evoked simultaneously by the same term and show that certain emotions indeed go hand in hand. We also analyze the polarity of terms (positive and negative), as well as what colors are associated with words. We find that associations with colors is directly correlated with the order that colors terms first came into existence in language. Also, red and black are strongly associated with negative emotion terms, whereas white and green are strongly associated with positive terms. The lexicon with close to 10,000 entries (one entry for each word–sense pair) will be made freely available.
Radiative transfer of ultrasound

A radiative transfer equation is used to model the diffuse multiple scattering of ultrasound in a medium containing discrete random scatterers. An assumption of uncorrelated phases allows one to write an equation of energy balance for the diffuse intensity. This ultrasonic radiative transfer equation contains single‐scattering and propagation parameters that are calculated using the elastic wave equation. Polarization effects are included through the introduction of an elastodynamic Stokes vector which contains a longitudinal Stokes parameter and four shear Stokes parameters similar to the four Stokes parameters used in optical radiative transfer theory. The theory is applied to a statistically homogeneous, isotropic elastic half‐space containing randomly distributed spherical voids illuminated by a harmonic plane wave. Results on the angular dependence of backscattered intensity are presented. It is anticipated that this approach may be applicable to materials characterization through the study of the ti.
Bi-level Relative Information Analysis for Multiple-Shot Person Re-Identification

Multiple-shot person re-identification, which is valuable for application in visual surveillance, tackles the problem of building the correspondence between images of the same person from different cameras. It is challenging because of the large within-class variations due to the changeable body appearance and environment and the small between-class differences arising from the possibly similar body shape and clothes style. A novel method named “Bi-level Relative Information Analysis” is proposed in this paper for the issue by treating it as a set-based ranking problem. It creatively designs a relative dissimilarity using set-level neighborhood information, called “Set-level Common-Near-Neighbor Modeling”, complementary to the sample-level relative feature “Third-Party Collaborative Representation” which has recently been proven to be quite effective for multiple-shot person re-identification. Experiments implemented on several public benchmark datasets show significant improvements over state-of-the-art methods. key words: Bi-level relative information analysis; multiple-shot person re-identification; visual surveillance
Distributed under Creative Commons Cc-by 4.0 Obesity-induced Diet Leads to Weight Gain, Systemic Metabolic Alterations, Adipose Tissue Inflammation, Hepatic Steatosis, and Oxidative Stress in Gerbils (meriones Unguiculatus)

Background. Nowadays, the number of obese people in the world has reached alarming proportions. During the expansion of adipose tissue, a number of functions such as activation and release of cytokines and hormones may be affected. This leads the body to a pro-inflammatory pattern, which may affect the proper functioning of many tissues. Thus, studying the mechanisms by which obesity induces physiological disorders is necessary, and may be facilitated by the use of animal models, in particular rodents. We sought to characterize the metabolic and adipose tissue changes resulting from a diet rich in fats and simple sugars in gerbils. Methods. We divided 14 gerbils into two experimental groups that received a diet rich in simple carbohydrates and fats with 5,86 kcal/g (OB, n = 7) or a standard diet with 4.15 kcal/g (CT; n = 7) for 11 weeks. The animals had free access to water and food. The animal weight and food consumption were measured weekly. Blood, adipose tissue and liver of each animal were collected at the end of experiment. The following parameters were determined: cholesterol (COL), triglycerides (TGL) and glycemia (GLI) in the plasma; cytokines (IL-6, IL-10 and TNF-α) and hormones (adiponectin and leptin) in adipose tissue; activity of superoxide dismutase (SOD) and catalase (CAT), extraction and differentiation of fat and histology in liver. Results. The consumption of a diet rich in simple carbohydrates and fats led to increased total body weight and increased relative weights of liver and adipose tissue. In addition, we observed increased fasting glucose levels and circulating triglycerides, along with high TNF-α production in adipose tissue and increased total fat, cholesterol and triglyceride contents in the liver, contributing to higher intensity of hepatic steatosis. On the other hand, the animals of this group showed depletion in the enzyme activity of SOD and CAT in the liver, as well as reduction of IL-10 and adiponectin levels in adipose tissue.
User profiling with geo-located posts and demographic data

This paper presents a novel method for user proﬁling in social media that makes use of geo-location information associated with social media posts to avoid the need for self-reported data. These posts are combined with two publicly available sources of demographic information to automatically create data sets in which posts are labelled with socio-economic status. The data sets are linked by identifying each user’s ‘home loca-tion’. Analysis indicates that the nature of the demographic information is an important factor in performance of this approach.
HELPING STUDENTS ENHANCE THEIR GRIT AND GROWTH MINDSETS

their ideas make sense, students who are resilient and who work hard tend to do better than students who are not resilient and who give up easily. Both authors tell us that this kind of perseverance seems to be more important than are natural abilities and intelligence. Analysts of brain research (e.g. Caine & Caine, 2011; Sousa, 2011; Johnson, Johnson & Holubec, 2008) now believe that intelligence is not a static commodity. The more we learn, the more we can learn (Sousa, 2011). Those who end up being the best or the smartest are not always those who start out that way (Duckworth, 2013). Johnson and Johnson (2013) tell us that students who work together in positive and promotive ways persevere longer, work harder, and learn more in general than do students who work alone or who compete against their peers. Dweck (2006) believes that students can be taught the skills to persevere, to believe that their efforts and attitudes make a difference. Hattie (2009) has described teacher initiatives that make a difference for students. In this essay we will discuss ways that teachers can and do make a positive difference for their students.
Characterization of monoclonal antibodies against the human immunodeficiency virus (HIV) gag products and their use in monitoring HIV isolate variation.

Monoclonal antibodies were raised against the gag proteins of a British isolate of the human immunodeficiency virus (HIV), CBL-1. Seven of the monoclonal antibodies recognized HIV gag-coded proteins of 55,000 mol. wt. (p55) and 24,000 mol. wt. (p24), three recognized p55/p18 and three p18 alone. Cross-competition assays suggested that at least two independent epitopes exist on the p24 cleaved from the p55 precursor, whereas a cluster of closely related epitopes was recognized by the p55/p18 and p18 antibodies. The panel of monoclonal antibodies was then used to compare by immunofluorescence the expression of gag-encoded antigenic determinants on HIV isolates from different geographical locations. Minor changes in epitope expression were observed in isolates from the U.S.A. and Haiti with the most notable changes being detected in isolates from Zaire, Tanzania and Uganda.
“What the hell was in that wine?”: Entitlement to launch and develop stories within a multiparty context

We consider a corpus of conversational narratives which arise in the complex, multiparty setting of pre- and post-game stretching sessions of a women’s elite basketball team. Our focus is on the characteristics of story openings within this corpus, and we consider how stories are launched; how roles of story opener and teller are distributed within the group, reflecting both entitlement to tell stories and social relationships between the participants; and what strategies are used to introduce different kinds of stories into the interaction. We suggest that the team from which the stories derive represents a modern-day ‘society of intimates’, and show that patterns of story opening and telling reflect this — and correlate with institutional and social roles and relationships.
Specific Binding of Tombusvirus Replication Protein p33 to an Internal Replication Element in the Viral RNA Is Essential for Replication

ABSTRACT The mechanism of template selection for genome replication in plus-strand RNA viruses is poorly understood. Using the prototypical tombusvirus, Tomato bushy stunt virus (TBSV), we show that recombinant p33 replicase protein binds specifically to an internal replication element (IRE) located within the p92 RNA-dependent RNA polymerase coding region of the viral genome. Specific binding of p33 to the IRE in vitro depends on the presence of a C · C mismatch within a conserved RNA helix. Interestingly, the absence of the p33:p33/p92 interaction domain in p33 prevented specific but allowed nonspecific RNA binding, suggesting that a multimeric form of this protein is involved in the IRE-specific interaction. Further support for the selectivity of p33 binding in vitro was provided by the inability of the replicase proteins of the closely related Turnip crinkle virus and distantly related Hepatitis C virus to specifically recognize the TBSV IRE. Importantly, there was also a strong correlation between p33:IRE complex formation in vitro and viral replication in vivo, where mutations in the IRE that disrupted selective p33 binding in vitro also abolished TBSV RNA replication both in plant and in Saccharomyces cerevisiae cells. Based on these findings and the other known properties of p33 and the IRE, it is proposed that the p33:IRE interaction provides a mechanism to selectively recruit viral RNAs into cognate viral replicase complexes. Since all genera in Tombusviridae encode comparable replicase proteins, these results may be relevant to other members of this large virus family.
Host ecology determines the relative fitness of virus genotypes in mixed‐genotype nucleopolyhedrovirus infections

Mixed‐genotype infections are common in many natural host–parasite interactions. Classical kin‐selection models predict that single‐genotype infections can exploit host resources prudently to maximize fitness, but that selection favours rapid exploitation when co‐infecting genotypes share limited host resources. However, theory has outpaced evidence: we require empirical studies of pathogen genotypes that naturally co‐infect hosts. Do genotypes actually compete within hosts? Can host ecology affect the outcome of co‐infection? We posed both questions by comparing traits of infections in which two baculovirus genotypes were fed to hosts alongside inocula of the same or a different genotype. The host, Panolis flammea, is a herbivore of Pinus sylvestris and Pi. contorta. The pathogen, PfNPV (a nucleopolyhedrovirus), occurs naturally as mixtures of genotypes that differ, when isolated, in pathogenicity, speed of kill and yield. Single‐genotype infection traits failed to predict the ‘winning’ genotypes in co‐infections. Co‐infections infected and caused lethal disease in more hosts, and produced high yields, relative to single‐genotype infections. The need to share with nonkin did not cause fitness costs to either genotype. In fact, in hosts feeding on Pi. sylvestris, one genotype gained increased yields in mixed‐genotype infections. These results are discussed in relation to theory surrounding adaptive responses to competition with nonkin for limited resources.
Metrics for formal methods : The ATC case study

As quality and reliability become even more important factors in software development due to increased business competition and different regulatory requirements, many organizations are considering the use of formal methods as part of their development process. Using formal methods, a software implementation can rigorously be shown to satisfy its specification. These methods can be used to varying degree on a software development project. An initial specification can be developed formally using precise mathematical and logical notation, and this specification is then shown to be consistent by performing correctness proofs. The software system might then be developed using conventional methods, or alternatively a complete formal development is carried out (that is, the specification is gradually transformed into the final implementation by using so called refinement techniques, with correctness proofs performed to show that each step is a valid refinement of the original specification). In this report we investigate the issues involved in applying formal methods to the development of an Air-Traffic Control Information System (ATC) [1]. We analyze the project from a metrics and measurement perspective, to investigate questions such as whether formal methods have an affect on the quality of the final product, and whether these methods could actually save development costs compared to a traditional development. We look at whether
Forecasting Volatility of Stock Market Using Adaptive Fuzzy-GARCH Model

In this paper, we study the problem of volatility forecasting of financial stock market. In general, stock market volatility is time-varying and nonlinear, and exhibits properties of clustering. This paper shows results from using the method of fuzzy systems to analyze the nonlinear in the case of generalized autoregressive conditional heteroskedasticity (GARCH) models and using the adaptive method of recursive least-squares (RLS) to forecast the stock market volatility. The joint the parameters of membership functions and GARCH model is a rather high nonlinear and complicated problem. This study presents an iterative algorithm based on genetic ones to estimate parameters of the membership functions and GARCH model. The genetic algorithm (GA) method aims to achieve a global optimal solution with a fast convergence rate for this Fuzzy-GARCH model estimation problem. From the simulation results, we have determined that the both estimation of in-sample and forecasting of out-of-sample volatility performance are significantly improved, if the both of leverage effect and adaptive forecast are considered in the GARCH model.
TransCONFIRM: Identification of a Genetic Signature of Response to Fulvestrant in Advanced Hormone Receptor–Positive Breast Cancer

Purpose: Fulvestrant is an estrogen receptor (ER) antagonist and an approved treatment for metastatic estrogen receptor–positive (ER+) breast cancer. With the exception of ER levels, there are no established predictive biomarkers of response to single-agent fulvestrant. We attempted to identify a gene signature of response to fulvestrant in advanced breast cancer. Experimental Design: Primary tumor samples from 134 patients enrolled in the phase III CONFIRM study of patients with metastatic ER+ breast cancer comparing treatment with either 250 mg or 500 mg fulvestrant were collected for genome-wide transcriptomic analysis. Gene expression profiling was performed using Affymetrix microarrays. An exploratory analysis was performed to identify biologic pathways and new signatures associated with response to fulvestrant. Results: Pathway analysis demonstrated that increased EGF pathway and FOXA1 transcriptional signaling is associated with decreased response to fulvestrant. Using a multivariate Cox model, we identified a novel set of 37 genes with an expression that is independently associated with progression-free survival (PFS). TFAP2C, a known regulator of ER activity, was ranked second in this gene set, and high expression was associated with a decreased response to fulvestrant. The negative predictive value of TFAP2C expression at the protein level was confirmed by IHC. Conclusions: We identified biologic pathways and a novel gene signature in primary ER+ breast cancers that predicts for response to treatment in the CONFIRM study. These results suggest potential new therapeutic targets and warrant further validation as predictive biomarkers of fulvestrant treatment in metastatic breast cancer. Clin Cancer Res; 22(23); 5755–64. ©2016 AACR.
Learning a Specialization for Face Recognition : The E ect ofSpatial

The double dissociation between prosopagnosia, a face recognition deecit occurring after brain damage, and visual object agnosia, diiculty recognizing other kinds of complex objects, indicates that face and non-face object recognition may be served by partially independent mechanisms in the brain. Such a dissociation could be the result of a competitive learning mechanism that, during development, devotes neural resources to the tasks they are best at performing. Studies of normal adult performance on face and object recognition tasks seem to indicate that face recognition is primarily conngural, involving the low spatial frequency information present in a stimulus over relatively large distances, whereas object recognition is primarily featural, involving analysis of the object's parts using local, high spatial frequency information. In a feed-forward computational model of visual processing, two modules compete to classify input stimuli; when one module receives low spatial frequency information and the other receives high spatial frequency information, the low-frequency module shows a strong specialization for face recognition in a combined face identiication/object classiication task. The series of experiments shows that the ne discrimination necessary for distinguishing members of a visually homogeneous class such as faces relies heavily on the low spatial frequencies present in a stimulus. 1 Background Studies of the preserved and impaired abilities in brain damaged patients provide important clues on how the brain is organized. Cases of prosopagnosia, a face recognition deecit often sparing recognition of non-face objects, provide some evidence that face recognition is served by a \special" mechanism. What might the basis for this dissociation be? The fact that visual object agnosia, an object recognition deecit, can occur without appreciable impairment of face recognition 1] precludes the possibility that face recognition is simply harder than object recognition but is served by the same mechanism. Another possibility, that prosopagnosics have impaired within-category discrimination but intact superordinate classiication, can be rejected on the basis of studies of extreme prosopagnosic patients such as W.J., who learned a diicult sheep discrimination task remarkably well but could not learn new faces 11]. In previous work, we proposed that a neural mechanism allocating resources according to their ability to perform a given task could explain the apparent specialization for face recognition evi-denced by prosopagnosia 4]. We showed that a model based on the mixture of experts architecture 10], in which a gating network implements competitive learning between two simple homogeneous modules, could develop a specialization such that damage …