Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Skin Substitutes—Potential of Tissue Engineered Skin for Facilitating Anti-Fibrotic Healing

Skin protects the body from exogenous substances and functions as a barrier to fluid loss and trauma. The skin comprises of epidermal, dermal and hypodermal layers, which mainly contain keratinocytes, fibroblasts and adipocytes, respectively, typically embedded on extracellular matrix made up of glycosaminoglycans and fibrous proteins. When the integrity of skin is compromised due to injury as in burns the coverage of skin has to be restored to facilitate repair and regeneration. Skin substitutes are preferred for wound coverage when the loss of skin is extensive especially in the case of second or third degree burns. Different kinds of skin substitutes with different features are commercially available; they can be classified into acellular skin substitutes, those with cultured epidermal cells and no dermal components, those with only dermal components, and tissue engineered substitutes that contain both epidermal and dermal components. Typically, adult wounds heal by fibrosis. Most organs are affected by fibrosis, with chronic fibrotic diseases estimated to be a leading cause of morbidity and mortality. In the skin, fibroproliferative disorders such as hypertrophic scars and keloid formation cause cosmetic and functional problems. Dermal fibroblasts are understood to be heterogeneous; this may have implications on post-burn wound healing since studies have shown that superficial and deep dermal fibroblasts are anti-fibrotic and pro-fibrotic, respectively. Selective use of superficial dermal fibroblasts rather than the conventional heterogeneous dermal fibroblasts may prove beneficial for post-burn wound healing.
Salsolinol modulation of dopamine neurons

Salsolinol, a tetrahydroisoquinoline present in the human and rat brains, is the condensation product of dopamine and acetaldehyde, the first metabolite of ethanol. Previous evidence obtained in vivo links salsolinol with the mesolimbic dopaminergic (DA) system: salsolinol is self-administered into the posterior of the ventral tegmental area (pVTA) of rats; intra-VTA administration of salsolinol induces a strong conditional place preference and increases dopamine release in the nucleus accumbens (NAc). However, the underlying neuronal mechanisms are unclear. Here we present an overview of some of the recent research on this topic. Electrophysiological studies reveal that DA neurons in the pVTA are a target of salsolinol. In acute brain slices from rats, salsolinol increases the excitability and accelerates the ongoing firing of dopamine neurons in the pVTA. Intriguingly, this action of salsolinol involves multiple pre- and post-synaptic mechanisms, including: (1) depolarizing dopamine neurons; (2) by activating μ opioid receptors on the GABAergic inputs to dopamine neurons – which decreases GABAergic activity – dopamine neurons are disinhibited; and (3) enhancing presynaptic glutamatergic transmission onto dopamine neurons via activation of dopamine type 1 receptors, probably situated on the glutamatergic terminals. These novel mechanisms may contribute to the rewarding/reinforcing properties of salsolinol observed in vivo.
Is Populism an Ideology? A Refutation and a New Perspective

The dominant theoretical paradigm originating in the work of Cas Mudde conceives of populism as a thin-centered ideology that focuses on the antagonism between people and elites against the backdrop of popular sovereignty. While this framework has contributed signiﬁcantly to an improved scientiﬁc analysis of populism, it is argued in this article that its ideological connotations are ill-conceived both conceptually and methodologically, and that its normative implications and failure to acknowledge the graded nature of populist behavior hinder the further evolution of the ﬁeld of populism studies. Combining insights from the work of Ernesto Laclau and the proponents of frame theory, the article suggests dropping the ideological clause and simply conceiving populism as a discursive frame. The article contends that frame analysis reveals a strong ﬁt between discursive elements and cognitive features of populism, furnishing solid methodological foundations to conduct empirical research and encouraging cooperation with neighboring ﬁelds of social science.
A Spiral of Cynicism for Some: The Contingent Effects of Campaign News Frames on Participation and Confidence in Government

This article explores the impact of strategy-based campaign coverage on turnout and confidence in government. Recent theoretical advances suggest that variables such as sophistication and involvement frequently moderate media exposure effects. We hypothesize that the impact of strategy frames will be moderated by political involvement and sophistication. In an experiment, we precisely isolate and manipulate particular story elements that have been said to foster public cynicism: the strategic interpretation of candidate motives, the presence of polling results, and the use of war or game metaphors to describe the campaign. Relative to the issue-oriented coverage, strategy frames boost the number of strategy-based comments people offer when describing the campaign and depress issue-based commentary. As expected, framing effects on turnout, trust in government, civic duty, and the perceived meaningfulness of elections are moderated by involvement and sophistication. Nonpartisans and those with less than a college degree are significantly demobilized and alienated by strategy-based coverage, while partisans and the highly educated are mostly unaffected.
The Metaphor TIME AS SPACE across Languages

1 The domains of space and time The impact of spatial orientation on human thought and, in particular, our understanding of time has often been noted. 1 Lakoff (1993: 218) assumes that our metaphorical understanding of time in terms of space is biologically determined: " In our visual systems, we have detectors for motion and detectors for objects/locations. We do not have detectors for time (whatever that could mean). Thus, it makes good biological sense that time should be understood in terms of things and motion. " This explanation is not fully convincing because there is empirical evidence that humans directly perceive and " feel " the passage of time (see Evans, in print). Our direct experience of time is subjective and may, therefore, be strikingly different from objective time. Thus, a given duration of time is experienced as lasting longer or shorter depending on our state of awareness and the amount of information registered. For example, the duration of time in situations of heightened awareness and high information processing such as during times of suffering or danger is experienced as passing more slowly, while in situations of low information processing, such as during routine activities, time appears to pass more quickly. Evans convincingly argues that our experience of time results from internal, subjective responses to external sensory stimuli and that by imparting spatio-physical " image content " to a subjective response concept we are able to " objectify " our temporal experience. According to this view of time, our spatial understanding of time is not determined by biological needs, but by intersubjective, or communicative, needs. We need spatio-physical metaphors to speak about time in the same way that we need concrete metaphors to speak about other internal states such as emotions or thoughts. We may, however, consider a third reason why the metaphor TIME AS SPACE is so pervasive. In Metaphors We Live by, Lakoff and Johnson (1980: Ch. 21) draw attention to the power of metaphor to create new meaning. Our veridical experience of time is restricted to only a few of its aspects: simultaneity and duration, and the awareness of the present as the time experienced at each moment, the past as the time related to remembered events, and the future as time related to predicted events. In metaphorizing time as space, these notions are typically seen with respect to a one-dimensional line, the time axis. But …
Concurrency Bug Detection and Avoidance Through Continuous Learning of Invariants Using Neural Networks in Hardware

As parallel architectures become mainstream, the issue of writing and debugging parallel programs becomes a major concern for today’s computing world. Researchers have shown that diﬀerent types of concurrency bugs can be eﬀec-tively detected by checking the validity of various invariants (e.g. inter-thread communication invariants). Existing invariant based proposals collect a large number of execution traces by using various test inputs available from the developers. Then, they analyze those traces and extract the required invariants. As a result, these proposals suﬀer from a number of limitations arising from this invariant extraction process. First, they cannot test all possible thread interleavings and hence, miss many invariants. Second, often times these proposals cannot replicate the production run environments and inputs during the extraction process. This re-sults in missing and sometimes incorrect invariants. Third, as a program is extended and ﬁxed over its lifetime, many invariants might become invalid and new invariants might arise. These proposals cannot cope up with this situation properly. Finally, existing invariant based proposals cannot check the correctness of an invariant if it is not found during the extraction process. Therefore, these proposals allow (or disallow) any new invariant blindly. These limitations severely hampers the applicability of any invariant based approach. In order to remedy this situation, we propose a novel scheme that uses hardware based neural networks to continuously learn and verify invariants dynamically during production runs. This alleviates all of the above mentioned limitations, thereby making any invariant based approach more applicable and eﬀective. In this paper, we present our initial design and some preliminary results of our proposed scheme.
Impact of data collection on interpretation and evaluation of student models

Student modeling techniques are evaluated mostly using historical data. Researchers typically do not pay attention to details of the origin of the used data sets. However, the way data are collected can have important impact on evaluation and interpretation of student models. We discuss in detail two ways how data collection in educational systems can influence results: mastery attrition bias and adaptive choice of items. We systematically discuss previous work related to these biases and illustrate the main points using both simulated and real data. We summarize specific consequences for practice -- not just for doing evaluation of student models, but also for data collection and publication of data sets.
GaInSb/AlInSb Multi-Quantum-Wells for Mid-Infrared Lasers

Photoluminescence (PL) from GaInSb/AlInSb type I multi-quantum-wells, grown on GaAs, has been investigated as a function of strain in the quantum wells. Luminescence, between 3 and 4 μm, was observed for all samples, with good agreement between the measured and calculated peak emission energies. Analysis of the temperature dependence of the luminescence suggests that population of excited quantum well hole subbands occurs at high temperature, leading to a reduction in the PL signal. Room temperature luminescence was obtained from a sample with ∼0.8% strain in the quantum wells. Preliminary results from laser diodes fabricated from companion wafers indicate lasing up to 220 K.
Recommendation of software technologies based on collaborative filtering

Software engineers have to select some appropriate development technologies to use in the work; however, engineers sometimes cannot find the appropriate technologies because there are vast amount of options today. To solve this problem, we propose a software technology recommendation method based on collaborative filtering (CF). In the proposed method, at first, questionnaires are collected from concerned engineers about their technical interest. Next, similarities between an active engineer who gets recommendation and the other engineers are calculated according to the technical interests. Then, some similar engineers are selected for the active engineer. At last, some technologies are recommended which attract the similar engineers. An experimental evaluation showed that the proposed method can make accurate recommendations than that of a naive (non-CF) method.
The Changing Experience of Australian Female Entrepreneurs

The study of female entrepreneurship is a dynamic field, with more women than men engaging in self-employment in Australia, the United Kingdom and the United States. Prior research in this field has identified a series of factors which characterize entrepreneurs. This paper examines the extent to which the experiences of Australian women entrepreneurs are reflected in the prior research. In particular, emphasis is placed on whether the personal characteristics, educational levels, motivations for starting business and resource acquisition behaviour of contemporary Australian women entrepreneurs are reflected in the prior research. While many of the key findings of prior research were found to describe accurately the experience of Australian women entrepreneurs, three new factors have been identified. First, Australian women entrepreneurs have increasingly come from business education backgrounds compared to the predominantly liberal arts backgrounds reported elsewhere. Second, the reasons for establishing small business differ insofar as they represent a greater proportion of general business needs as well as personal internal needs. Third, Australian women entrepreneurs are moving away from traditional "female industries" into sectors identified as "male industries" such as manufacturing. Overall, Australian women entrepreneurs demonstrate similarities in their identifying characteristics; however, significant shifts are occurring in their behaviours.
Individual differences in perceptual abilities predict target visibility during masking

Many studies have shown that the visual system can implicitly process a single stimulus under conditions of low visibility. However, it remains unknown whether this ability extends when viewing conditions become more difficult, and whether differences in early perceptual abilities modulate masking sensitivity. To address these issues, participants enumerated a variable number of target elements among distracters in two electroencephalography experiments. Either one (Experiment 1) or all targets (Experiment 2) were masked through object‐substitution. Results showed that an event‐related potential measure of selective individuation, the N2pc component, was modulated by target numerosity in both masked and unmasked trials, suggesting that multiple object individuation can operate in conditions of limited visibility. However, this effect was present mainly for participants with low masking effects, who overall showed more pronounced N2pc modulations as a function of target numerosity. Finally, oscillatory activity analyses revealed that early segmentation mechanisms, as reflected by lateralized gamma synchronization, were more active in participants with low sensitivity to masking, suggesting that individual variation in early perceptual functions is associated with susceptibility to masking such that more efficient segmentation and individuation mechanisms reduce the effects of masking. These findings cast doubt on the claim that effectively masked stimuli can be individuated.
Come/Came Variation In English Dialects

L'alternance come/came dans les contextes a reference passee constitue l'un des traits les plus familiers des dialectes anglais. L'A. examine ici de maniere systematique le comportement de come dans un large corpus oral linguistique et sociolinguistique provenant de l'Angleterre du nord. Ces donnees sont comparees a celles provenant, d'une part, d'autres dialectes anglais presentant une variabilite similaire (tel que la variante de York) et, d'autre part, des premiers stades de l'anglais
A Cross-media Model for Automatic Image Annotation

Automatic image annotation is still an important open problem in multimedia and computer vision. The success of media sharing websites has led to the availability of large collections of images tagged with human-provided labels. Many approaches previously proposed in the literature do not accurately capture the intricate dependencies between image content and annotations. We propose a learning procedure based on Kernel Canonical Correlation Analysis which finds a mapping between visual and textual words by projecting them into a latent meaning space. The learned mapping is then used to annotate new images using advanced nearest-neighbor voting methods. We evaluate our approach on three popular datasets, and show clear improvements over several approaches relying on more standard representations.
But I did not Mean It!—Intent Classification of Racist Posts on Tumblr

Research shows that many like-minded people use popular microblogging websites for posting hateful speech against various religions and race. Automatic identification of racist and hate promoting posts is required for building social media intelligence and security informatics based solutions. However, just keyword spotting based techniques cannot be used to accurately identify the intent of a post. In this paper, we address the challenge of the presence of ambiguity in such posts. We conduct our study on Tumblr microblogging website and develop a cascaded ensemble learning classifier for identifying the posts having racist or radicalized intent. We train our model by identifying various semantic, sentiment and linguistic features from free-form text. Our experimental results shows that the proposed approach is effective and the social tendencies, language cues and personality traits of a narrative are discriminatory features for classifying the posts with racist intent.
Demonstration of p-type In0.7Ga0.3As/GaAs0.35Sb0.65 and n-type GaAs0.4Sb0.6/In0.65Ga0.35As complimentary Heterojunction Vertical Tunnel FETs for ultra-low power logic

Extremely scaled high-k gate dielectrics with high quality electrical interfaces with arsenide (As) and antimonide (Sb) channels are used to demonstrate complimentary `all III-V' Heterojunction Vertical Tunnel FET (HVTFET) with record performance at |V<sub>DS</sub>|=0.5V. The p-type TFET (PTFET) has I<sub>ON</sub> =30μA/μm and I<sub>ON</sub>/I<sub>OFF</sub> =10<sup>5</sup>, whereas the n-type TFET (NTFET) has I<sub>ON</sub> =275μA/μm and I<sub>ON</sub>/I<sub>OFF</sub>=3×10<sup>5</sup>, respectively. NTFET shows 55mV/decade switching slope (SS) while PTFET shows 115mV/decade SS in pulsed mode measurement. Vertical TFET offers 77% higher effective drive strength than Si-FinFET for given inverter standard cell area. Energy-delay performance of TFET shows gain over CMOS for low V<sub>DD</sub> logic applications.
Information-Theoretic Active Perception for Multi-Robot Teams

INFORMATION-THEORETIC ACTIVE PERCEPTION FOR MULTI-ROBOT TEAMS Benjamin Charrow Vijay Kumar Nathan Michael Multi-robot teams that intelligently gather information have the potential to transform industries as diverse as agriculture, space exploration, mining, environmental monitoring, search and rescue, and construction. Despite large amounts of research effort on active perception problems, there still remain significant challenges. In this thesis, we present a variety of information-theoretic control policies that enable teams of robots to efficiently estimate different quantities of interest. Although these policies are intractable in general, we develop a series of approximations that make them suitable for real time use. We begin by presenting a unified estimation and control scheme based on Shannon’s mutual information that lets small teams of robots equipped with range-only sensors track a single static target. By creating approximate representations, we substantially reduce the complexity of this approach, letting the team track a mobile target. We then scale this approach to larger teams that need to localize a large and unknown number of targets. We also examine information-theoretic control policies to autonomously construct 3D maps with ground and aerial robots. By using Cauchy-Schwarz quadratic mutual information, we show substantial computational improvements over similar information-theoretic measures. To map environments faster, we adopt a hierarchical planning approach which incorporates trajectory optimization so that robots can quickly determine feasible and locally optimal trajectories. Finally, we present a high-level planning algorithm that enables heterogeneous robots to cooperatively construct maps.
The effects of a life skills program on the social and academic performance of freshman student-athletes

The purpose of this study was to examine the effects of participation in a Life Skills program for freshman student-athletes on academic and social performance. Subjects (n = 38) were freshman student-athletes participating in varsity athletics at Western Washington University during Fall Quarter 2010. The treatment group (n = 21) met for one hour, twice a week and completed a Life Skills Seminar Course (LSSC) designed and taught by the researcher. Subjects completed both the Student Adaptation to College Questionnaire (SACQ) and the College Self-Efficacy Inventory (CSEI) at the beginning and conclusion of the course. A two-way ANOVA between-within was used to analyze adjustment and selfefficacy outcomes and means of the fall quarter grade point average were calculated and compared for both the treatment and the control group. No statistically significant interactions were found between time (preor post-measures) or groups (treatment and control) of student-athlete adaptation to college as measured by the SACQ or student-athlete college self-efficacy as measured by the College Self-Efficacy Inventory CSEI. No significant relationship between the grade point average (GPA) of the two groups was found although the GPA for seminar participants was 2.98, which was . 35 points higher than the GPA for the control group participants. Despite no significant relationships in the measures, student-athletes reported on the effectiveness of participation in the LSSC through evaluations and described the course content as being beneficial to their general knowledge.
Protein S Deficiency: A Database of Mutations – Summary of the First Update

Protein S is a vitamin K dependent protein whose inherited deficiency is a well recognized risk factor for venous thrombosis. Its role is to act as activated protein C cofactor in factor Va and VIIIa proteolysis, thus restricting thrombin generation. Its gene lies on chromosome 3, at position 3p11.1-q11.2, and its structural organization has been described. Elucidation of the gene defects responsible for protein S deficiency is proceeding rapidly. A first record of identified mutations was undertaken in 1996 under the auspices of the International Society on Thrombosis and Haemostasis Scientific and Standardization Committee (ISTH SSC) and was published in 1997 (Thromb Haemost 1997; 77: 1201-14). This first database reported mutations identified in 126 protein S-deficient subjects postulated to be detrimental, and 19 mutations that were considered as neutral polymorphisms. The classification proposed by Bertina at the subcommittee meeting in 1991 was used to classify the mutations according to the phenotype observed in deficient subjects, that is type I when both free and total PS antigen levels were decreased, type III when free PS levels were decreased with normal total PS antigen levels, and type II when cofactor activity of PS was decreased while total and free antigen levels were within the normal ranges.