Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender issues in the research environment

Recruiting and retaining females within science, engineering and technology continues to challenge many European Higher Education Institutions. This study looks at female self-perceptions relating to effective research work and career progression. Focus groups are used to examine the attitudes and experiences of females, and a questionnaire used to explore perceptions in four main skills areas: group work; communication; personal awareness; and project planning and management. The study indicates consistent female concerns on issues pertaining to effective female role models, negative work-role stereotypes and the work-life balance of an academic career. For all four skills areas, the average confidence scores of the female participants fell below that of males, but these differences were only statistically significant for perceptions on group work and communication skills, and prior to an intense skills development course. Based on these findings, a student workshop on gender issues has been developed, an outline of which is presented.
Individual Distinctiveness in Call Types of Wild Western Female Gorillas

Individually distinct vocalizations play an important role in animal communication, allowing call recipients to respond differentially based on caller identity. However, which of the many calls in a species' repertoire should have more acoustic variability and be more recognizable is less apparent. One proposed hypothesis is that calls used over long distances should be more distinct because visual cues are not available to identify the caller. An alternative hypothesis proposes that close calls should be more recognizable because of their importance in social interactions. To examine which hypothesis garners more support, the acoustic variation and individual distinctiveness of eight call types of six wild western gorilla (Gorilla gorilla) females were investigated. Acoustic recordings of gorilla calls were collected at the Mondika Research Center (Republic of Congo). Acoustic variability was high in all gorilla calls. Similar high inter-individual variation and potential for identity coding (PIC) was found for all call types. Discriminant function analyses confirmed that all call types were individually distinct (although for call types with lowest sample size - hum, grumble and scream - this result cannot be generalized), suggesting that neither the distance at which communication occurs nor the call social function alone can explain the evolution of identity signaling in western gorilla communication.
Efficient Induction and Expansion of Human Alloantigen-Specific CD8 Regulatory T Cells from Naive Precursors by CD40-Activated B Cells1

Although recent studies have focused on CD4+ regulatory T cells (Treg), CD8+ Treg have also been reported to play important roles in the induction and maintenance of immune tolerance. Adoptive transfer of CD8+ Treg in rodents or induction of CD8+ Treg in humans can prevent or treat allograft rejection and autoimmune diseases. However, no approaches have been reported for the generation of human Ag-specific CD8+ Treg at a practical scale for clinical use. Here, we found that two novel CD8+ T cell subsets with different levels of CD8 surface expression, CD8high and CD8low, could be induced from naive CD8+ precursors in vitro by allogeneic CD40-activated B cells, whereas only CD8high T cells were alloantigen-specific Treg with relatively poor alloantigen-specific cytotoxicity. Importantly, alloantigen-specific CD8high Treg could be induced and expanded from naive CD8+CD25− T cells at a large scale after 3 wk of culture without exogenous cytokines. These induced alloantigen-specific Treg were CD45RO+ and CCR7− memory cells, and they expressed Foxp3, CD25, CD27, CD28, and CD62L. The induction and expansion of CD8high Treg by CD40-activated B cells were dependent on endogenously expressed IFN-γ, IL-2, IL-4, and CTLA-4. This approach may facilitate the clinical application of CD8+ Treg-based immunotherapy in transplantation and autoimmune diseases.
Language abilities in Williams syndrome: A critical review

Williams syndrome is a rare genetic disorder in which, it is claimed, language abilities are relatively strong despite mild to moderate mental retardation. Such claims have, in turn, been interpreted as evidence either for modular preservation of language or for atypical constraints on cognitive development. However, this review demonstrates that there is, in fact, little evidence that syntax, morphology, phonology, or pragmatics are any better than predicted by nonverbal ability, although performance on receptive vocabulary tests is relatively good. Similarly, claims of an imbalance between good phonology and impaired or atypical lexical semantics are without strong support. There is, nevertheless, consistent evidence for specific deficits in spatial language that mirror difficulties in nonverbal spatial cognition, as well as some tentative evidence that early language acquisition proceeds atypically. Implications for modular and neuroconstructivist accounts of language development are discussed.The preparation of this paper was supported by the Williams Syndrome Foundation (United Kingdom) and the Medical Research Council. I thank Courtenay Norbury and Kate Nation for comments on the manuscript and Chris Jarrold, Jill Boucher, and Teresa McCormack for many useful discussions.
Translation-Equivariant Matchings of Coin Flips on ℤ d

Consider independent fair coin flips at each site of the lattice ℤ d . A translation-equivariant matching rule is a perfect matching of heads to tails that commutes with translations of ℤ d and is given by a deterministic function of the coin flips. Let Z Φ be the distance from the origin to its partner, under the translation-equivariant matching rule Φ. Holroyd and Peres (2005) asked, what is the optimal tail behaviour of Z Φ for translation-equivariant perfect matching rules? We prove that, for every d ≥ 2, there exists a translation-equivariant perfect matching rule Φ such that EZ Φ 2/3-ε < ∞ for every ε > 0.
Survey of Keyword Extraction Techniques

Keywords are commonly used for search engines and document databases to locate information and determine if two pieces of test are related to each other. Reading and summarizing the contents of large entries of text into a small set of topics is difficult and time consuming for a human, so much so that it becomes nearly impossible to accomplish with limited manpower as the size of the information grows. As a result, automated systems are being more commonly used to do this task. This problem is challenging due to the intricate complexities of natural language , as well as the inherent difficulty in determining if a word or set of words accurately represent topics present within the text. With the advent of the internet, there is now both a massive amount of information available, as well as a demand to be able to search through all of this information. Keyword extraction from text data is a common tool used by search engines and indexes alike to quickly categorize and locate specific data based on explicitly or implicitly supplied keywords. Motivation Many different methods have been used over the years, and new solutions are constantly being proposed to solve this complex problem. A broad overview of the common techniques and algorithms has not yet been explored. Methods Various methods of locating and defining keywords have been used, both individually and in concert. Despite their differences, most methods have the same purpose and attempt to do the same thing: using some heuristic (such as distance between words, frequency of word use, or predetermined word relationships), locate and define a set of words that accurately convey themes or describe information contained in the text. Much early work concerned the frequency of term usage in the text, but most of this work focused on defining keywords in relation to a single document. In 1972, the idea of statistically analyzing the frequency of keyword usage within a document in relation to multiple other documents became more common. [4] This technique, known as Term Frequency-Inverse Document Frequency or simply TF-IDF, weights a given term to determine how well the term describes an individual document within a corpus. It does this by weight-ing the term positively for the number of times the term occurs within the specific document, while also weighting the term negatively relative to the number of documents which contain the term. Consider term t …
Spans of Delta Lenses

As part of an ongoing project to unify the treatment of symmetric lenses (of various kinds) as equivalence classes of spans of asymmetric lenses (of corresponding kinds) we relate the symmetric delta lenses of Diskin et al, with spans of asymmetric delta lenses. Because delta lenses are based on state spaces which are categories rather than sets there is further structure that needs to be accounted for and one of the main findings in this paper is that the required equivalence relation among spans is compatible with, but coarser than, the one expected. The main result is an isomorphism of categories between a category whose morphisms are equivalence classes of symmetric delta lenses (here called fb-lenses) and the category of spans of delta lenses modulo the new equivalence.
Generic role assignment: A uniform middleware abstraction for configuration of pervasive systems

Pervasive computing envisions distraction-free support for user tasks by means of cooperating devices that are invisibly integrated into the environment. Due to device mobility and continuous changes in context, pervasive systems need to be adaptive to realize this vision. To simplify their development, pervasive computing middleware ease the resulting configuration tasks. In the past, middleware developers have used independent abstractions to support different task. In this paper, we argue that support for the configuration should be built on top of one generic abstraction. For this, we introduce the abstraction of a role and we outline how role assignment can be used to support configuration. Finally, we also show that our approach has additional benefits such as improved reuse of configuration logic and increased flexibility to support novel configuration tasks.
Alternative Strategies for Variable Selection in Linear Regression Models for Incomplete Multivariate Normal Data

1. INTRODUCTION 1.1. 1. Variable Selection for Incomplete Data sets In statistical practice, many real-life data sets are incomplete for reasons like non-responses or drop-outs. When a data set is incomplete, practitioners frequently resort to a " case-deletion " strategy within which the incomplete cases are excluded from analysis and the complete cases are formed into a reduced rectangular complete-data format. Then traditional variable selection approaches such as stepwise or criterion-based ones can be applied to such a reduced data matrix. The problem with case-deletion is that too much statistical power may be lost and unbiased estimate is obtained only when the missingness mechanism is missing completely at random (MCAR) (Little and Rubin 1987). A more satisfying strategy for handling general missing data problems is via imputation methods, where the missing data are replaced by some plausible values. In order to retain the original " uncertainty " due to missing data, Rubin (1987) developed a strategy named multiple imputation, within which missing data are imputed several times. Then, the multiple imputed complete data sets are analyzed and the multiple parameter estimates are combined into one that incorporates the between-imputation variance, which can be viewed as the measure of the above uncertainty. Using a Markov chain Monte Carlo imputation approach, Schafer (1997) has developed a program to handle incomplete multivariate normal data with unbiased parameter estimation being achieved when missingness mechanism is " ignorable " in the sense defined by Rubin (1976), where missing values are missing at random (MAR) and the parameters of missingness mechanism and the model parameters are distinct. Ignorability is a less stringent case than MCAR and missingness mechanisms of many practical incomplete data can be well approximated by it. For the purpose of variable selection, however, traditional non-Bayesian approaches cannot be easily applied within the framework of multiple imputation. The difficulty lies in how to combine the selection results corresponding to the multiple imputed data sets, because these Non-Bayesian approaches sometimes describe different " best " linear regression models for different imputed data sets. With different predictors included in these " best " models, regression coefficients cannot just be simply averaged since their explanations vary across models.
Diagnosing Psoriatic Arthritis from the Dermatologist’s View

Psoriatic arthritis is a chronic inflammatory arthropathy associated with skin psoriasis. It is considered a unique arthropathy with distinct clinical and radiologic features. Up to 40% of patients with psoriasis may develop psoriatic arthritis. Psoriasis usually precedes psoriatic arthritis, so dermatologists are in a critical position for screening patients of psoriatic arthritis early in the disease course. Psoriatic arthritis may be challenging to diagnose, especially for dermatologists, because it has an insidious disease course, non-specific symptoms, and no specific biomarkers. Psoriatic arthritis is a polygenic autoimmune disorder of unknown etiology, but immunologic roles have recently been validated. In recent years, treatment modalities have rapidly advanced in the fields of psoriasis and psoriatic arthritis. Biologic agents, including TNF-α inhibitors and anti-IL12/23 agents, have shown dramatic improvement.
Suppression of Facial Mimicry of Negative Facial Expressions in an Incongruent Context

People react with Rapid Facial Reactions (RFRs) when presented with human facial emotional expressions. Recent studies show that RFRs are not always congruent with emotional cues. The processes underlying RFRs are still being debated. In our study described herein, we manipulate the context of perception and its influence on RFRs. We use a subliminal affective priming task with emotional labels. Facial electromyography (EMG) (frontalis, corrugator, zygomaticus, and depressor) was recorded while participants observed static facial expressions (joy, fear, anger, sadness, and neutral expression) preceded/not preceded by a subliminal word (JOY, FEAR, ANGER, SADNESS, or NEUTRAL). For the negative facial expressions, when the priming word was congruent with the facial expression, participants displayed congruent RFRs (mimicry). When the priming word was incongruent, we observed a suppression of mimicry. Happiness was not affected by the priming word. RFRs thus appear to be modulated by the context and type of emotion that is presented via facial expressions.
GOLAM: A Framework for Analyzing Genomic Data

The emerging medical models aim at leveraging on high-throughput genome sequencing technologies to better target drugs to patients' personal profiles so as to increase their effectiveness. However, the huge amount of data made available by these technologies calls for sophisticated and automated analysis techniques. In this direction we present GOLAM, a framework for OLAP analysis and mining of matches between genomic regions extracted from ENCODE, a worldwide-available collection of shared genomic data. The goal of GOLAM is to overcome the current limitations of genome analysis methods, that are normally based on browsing. This is done by partially automating and speeding-up the analysis process on the one hand, by making it more flexible and introducing a multi-resolution view of data on the other. The framework has been partially implemented so far; in this paper we focus on conveying its potential and on describing its functional architecture and the underlying data models.
System Identiication 1 the Basic Ideas 1.1 10 Basic Questions about System Identiication 1. What Is System Identiication?

System Identiication allows you to build mathematical models of a dynamic system based on measured data. 2. How is that done? Essentially by adjusting parameters within a given model until its output coincides as well as possible with the measured output. 3. How do you know if the model is any good? A good test is to take a close look at the model's output compared to the measurements on a data set that wasn't used for the t (\Validation Data"). 4. Can the quality of the model be tested in other ways? It is also valuable to look at what the model couldn't reproduce in the data (\the residuals"). There should be no correlation with other available information, such as the system's input.
The motivational arc of massive virtual collaboration 1

Massive virtual collaborations (MVC) involve large numbers of mostly unpaid contributors collectively creating various kinds of new content. We propose a model of motivations for contribution to MVC that uses helping behaviour as a framework to integrate various theoretical perspectives, namely work motivation and social movement theory. We argue that what was previous considered a single, static and individual phenomenon, namely motivation for contribution to a virtual work setting, is in fact at least three separate but interrelated phenomena, with organizational and dynamic aspects. The model distinguishes motivations for three levels of contribution (initial, sustained and meta) and captures the dynamic and recursive effects of contributions on emergent individual and project states.
Hyaluronic acid fat graft myringoplasty: how we do it

Dear Editor, Tympanic membrane (TM) perforation is most commonly a result of infection, trauma, or the sequelae of tympanostomy tube insertion. Although 88% of traumatic perforations of any size heal without intervention, the remainders become chronic and require treatment.1 Without closure, morbidity may include hearing loss, chronic otorrhea and cholesteatoma formation.2 These tympanic membrane perforations can be repaired surgically; however, doing so requires a general anesthesia which is often protracted and/or hypotensive, and which can represent an unacceptable risk in older patients.3 Day-stay surgery has become an integral part of modern otolaryngology. Myringoplasty under local anesthesia is a short, simple, cost-effective and minimally invasive technique compared with traditional myringoplasty.4 The purpose of this prospective clinical trial was to evaluate the success rate of the Hyaluronic Acid Fat Graft Myringoplasty (HAFGM) performed under local anesthesia as an outpatient clinic procedure and to discuss the utilities and advantages of this new procedure described by the author.
Self-Definition for Software Development

Satisfactory communication between developers and stake holders during system development is important to ensure satisfactory outcomes for those investing in the system. Unfortunately, communication is hampered when the two parties do not speak in the same language. Here, we identify and advocate the use of self-definition to alleviate some of these problems in certain types of systems where a formal or semiformal language is provided by the system for the user. Selfdefinition will be defined as describing the user's system in the language intended for use by the user. This will require effort by the developer to use the user's language but we will hypothesise that the systems so specified have advantages of otherwise specified systems, for both the developer and the user. To support our hypotheses we will draw on well-known examples of what we call “self-definition” from mathematics, computer science and other areas.
Impact of Body Mass Index and the Metabolic Syndrome on the Risk of Cardiovascular Disease and Death in Middle-Aged Men

Background— The purpose of this study was to investigate associations between combinations of body mass index (BMI) categories and metabolic syndrome (MetS) and the risk of cardiovascular disease and death in middle-aged men. Methods and Results— At age 50 years, cardiovascular risk factors were assessed in 1758 participants without diabetes in the community-based Uppsala Longitudinal Study of Adult Men (ULSAM). According to BMI-MetS status, they were categorized as normal weight (BMI <25 kg/m2) without MetS (National Cholesterol Education Program criteria; n=891), normal weight with MetS (n=64), overweight (BMI 25 to 30 kg/m2) without MetS (n=582), overweight with MetS (n=125), obese (BMI >30 kg/m2) without MetS (n=30), or obese with MetS (n=66). During follow-up (median 30 years), 788 participants died, and 681 developed cardiovascular disease (composite of cardiovascular death or hospitalization for myocardial infarction, stroke, or heart failure). In Cox proportional-hazards models that adjusted for age, smoking, and low-density lipoprotein cholesterol, an increased risk for cardiovascular disease was observed in normal-weight participants with MetS (hazard ratio 1.63, 95% confidence interval 1.11 to 2.37), overweight participants without MetS (hazard ratio 1.52, 95% confidence interval 1.28 to 1.80), overweight participants with MetS (hazard ratio 1.74, 95% confidence interval 1.32 to 2.30), obese participants without MetS (hazard ratio 1.95, 95% confidence interval 1.14 to 3.34), and obese participants with MetS (hazard ratio 2.55, 95% confidence interval 1.81 to 3.58) compared with normal-weight individuals without MetS. These BMI-MetS categories significantly predicted total mortality rate in a similar pattern. Conclusions— Middle-aged men with MetS had increased risk for cardiovascular events and total death regardless of BMI status during more than 30 years of follow-up. In contrast to previous reports, overweight and obese individuals without MetS also had an increased risk. The present data refute the notion that overweight and obesity without MetS are benign conditions.
SWIFT X-RAY TELESCOPE STUDY OF THE BLACK HOLE BINARY MAXI J1659–152: VARIABILITY FROM A TWO COMPONENT ACCRETION FLOW

We present an energy dependent X-ray variability study of the 2010 outburst of the black hole X-ray binary MAXI J1659–152 with the Swift X-ray Telescope (XRT). The broadband noise components and the quasi-periodic oscillations (QPO) observed in the power spectra show a strong and varied energy dependence. Combining Swift XRT data with data from the Rossi X-ray Timing Explorer, we report, for the first time, an rms spectrum (fractional rms amplitude as a function of energy) of these components in the 0.5–30 keV energy range. We find that the strength of the low-frequency component (<0.1 Hz) decreases with energy, contrary to the higher frequency components (>0.1 Hz) whose strengths increase with energy. In the context of the propagating fluctuations model for X-ray variability, we suggest that the low-frequency component originates in the accretion disk (which dominates emission below ∼2 keV) and the higher frequency components are formed in the hot flow (which dominates emission above ∼2 keV). As the properties of the QPO suggest that it may have a different driving mechanism, we investigate the Lense–Thirring precession of the hot flow as a candidate model. We also report on the QPO coherence evolution for the first time in the energy band below 2 keV. While there are strong indications that the QPO is less coherent at energies below 2 keV than above 2 keV, the coherence increases with intensity similar to what is observed at energies above 2 keV in other black hole X-ray binaries.