Miracle-dz/UniFAR-FTUs huggingface dataset:
Pathogenesis and molecular targeted therapy of spinal and bulbar muscular atrophy

Spinal and bulbar muscular atrophy (SBMA) or Kennedy's disease is a motor neurone disease characterized by muscle atrophy, weakness, contraction fasciculations and bulbar involvement. SBMA mainly affects males, while females are usually asymptomatic. SBMA is caused by expansion of a polyglutamine (polyQ)‐encoding CAG trinucleotide repeat in the androgen receptor (AR) gene. AR belongs to the heat shock protein 90 (Hsp90) client protein family. The histopathologic hallmarks of SBMA are diffuse nuclear accumulation and nuclear inclusions of the mutant AR with expanded polyQ in residual motor neurones in the brainstem and spinal cord as well as in some other visceral organs. There is increasing evidence that the ligand of AR and molecular chaperones play a crucial role in the pathogenesis of SBMA. The success of androgen deprivation therapy in SBMA mouse models has been translated into clinical trials. In addition, elucidation of its pathophysiology using animal models has led to the development of disease‐modifying drugs, that is, Hsp90 inhibitor and Hsp inducer, which inhibit the pathogenic process of neuronal degeneration. SBMA is a slowly progressive disease by nature. The degree of nuclear accumulation of mutant AR in scrotal skin epithelial cells was correlated with that in spinal motor neurones in autopsy specimens; therefore, the results of scrotal skin biopsy may be used to assess the efficacy of therapeutic trials. Clinical and pathological parameters that reflect the pathogenic process of SBMA should be extensively investigated.
The Indian Spontaneous Expression Database for Emotion Recognition

Automatic recognition of spontaneous facial expressions is a major challenge in the field of affective computing. Head rotation, face pose, illumination variation, occlusion etc. are the attributes that increase the complexity of recognition of spontaneous expressions in practical applications. Effective recognition of expressions depends significantly on the quality of the database used. Most well-known facial expression databases consist of posed expressions. However, currently there is a huge demand for spontaneous expression databases for the pragmatic implementation of the facial expression recognition algorithms. In this paper, we propose and establish a new facial expression database containing spontaneous expressions of both male and female participants of Indian origin. The database consists of 428 segmented video clips of the spontaneous facial expressions of 50 participants. In our experiment, emotions were induced among the participants by using emotional videos and simultaneously their self-ratings were collected for each experienced emotion. Facial expression clips were annotated carefully by four trained decoders, which were further validated by the nature of stimuli used and self-report of emotions. An extensive analysis was carried out on the database using several machine learning algorithms and the results are provided for future reference. Such a spontaneous database will help in the development and validation of algorithms for recognition of spontaneous expressions.
Multi-objective learning and mask-based post-processing for deep neural network based speech enhancement

We propose a multi-objective framework to learn both secondary targets not directly related to the intended task of speech enhancement (SE) and the primary target of the clean log-power spectra (LPS) features to be used directly for constructing the enhanced speech signals. In deep neural network (DNN) based SE we introduce an auxiliary structure to learn secondary continuous features, such as mel-frequency cepstral coefficients (MFCCs), and categorical information, such as the ideal binary mask (IBM), and integrate it into the original DNN architecture for joint optimization of all the parameters. This joint estimation scheme imposes additional constraints not available in the direct prediction of LPS, and potentially improves the learning of the primary target. Furthermore, the learned secondary information as a byproduct can be used for other purposes, e.g., the IBM-based post-processing in this work. A series of experiments show that joint LPS and MFCC learning improves the SE performance, and IBM-based post-processing further enhances listening quality of the reconstructed speech.
Methylphenidate for attention deficit hyperactivity disorder and drug relapse in criminal offenders with substance dependence: a 24-week randomized placebo-controlled trial

Aim To test the efficacy and safety of osmotic release oral system (OROS) methylphenidate (MPH) in doses up to 180 mg/day to treat attention deficit hyperactivity disorder (ADHD) and prevent any drug relapse in individuals with a co-diagnosis of ADHD and amphetamine dependence. Design Randomized placebo-controlled 24-week double-blind trial with parallel groups design. Setting Participants were recruited from medium security prisons in Sweden. The medication started within 2 weeks before release from prison and continued in out-patient care with twice-weekly visits, including once-weekly cognitive behavioural therapy. Participants Fifty-four men with a mean age of 42 years, currently incarcerated, meeting DSM-IV criteria for ADHD and amphetamine dependence. Measurements Change in self-reported ADHD symptoms, relapse to any drug use (amphetamine and other drugs) measured by urine toxicology, retention to treatment, craving and time to relapse. Findings The MPH-treated group reduced their ADHD symptoms during the trial (P = 0.011) and had a significantly higher proportion of drug-negative urines compared with the placebo group (P = 0.047), including more amphetamine-negative urines (P = 0.019) and better retention to treatment (P = 0.032). Conclusions Methylphenidate treatment reduces attention deficit hyperactivity disorder symptoms and the risk for relapse to substance use in criminal offenders with attention deficit hyperactivity disorder and substance dependence.
Using Domain-specific and Collaborative Resources for Term Translation

In this article we investigate the translation of terms from English into German and vice versa in the isolation of an ontology vocabulary. For this study we built new domain-specific resources from the translation search engine Linguee and from the online encyclopedia Wikipedia. We learned that a domain-specific resource produces better results than a bigger, but more general one. The first finding of our research is that the vocabulary and the structure of the parallel corpus are important. By integrating the multilingual knowledge base Wikipedia, we further improved the translation wrt. the domain-specific resources, whereby some translation evaluation metrics outperformed the results of Google Translate. This finding leads us to the conclusion that a hybrid translation system, a combination of bilingual terminological resources and statistical machine translation can help to improve translation of domain-specific terms.
Bacteria‐Phage Coevolution and the Emergence of Generalist Pathogens

Understanding the genetic constraints on pathogen evolution will help to predict the emergence of generalist pathogens that can infect a range of different host genotypes. Here we show that generalist viral pathogens are more likely to emerge during coevolution between the bacterium Pseudomonas fluorescens and the lytic phage SBW25Φ2 than when the same pathogen is challenged to adapt to a nonevolving population of novel hosts. When phages were able to adapt to nonevolving novel hosts, the resulting phenotypes had relatively narrow host ranges compared with coevolved phages. Evolved (rather than coevolved) phages also had lower virulence, although they attained virulence similar to that of coevolved phages after continued adaptation to a nonevolving population of the same host. We explain these results by using sequence data showing that the evolution of broad host range is associated with several different amino acid substitutions and therefore occurs only through repeated rounds of selection for novel infectivity alleles. These findings suggest that generalist bacteriophages are more likely to emerge through long‐term coevolution with their hosts than through spontaneous adaptation to a single novel host. These results are likely to be relevant to host‐parasite systems where parasite generalism can evolve through the acquisition of multiple mutations or alleles, as appears to be the case for many plant‐bacteria and bacteria‐virus interactions.
P2Y2 Receptor Transcription Is Increased by NF-κB and Stimulates Cyclooxygenase-2 Expression and PGE2 Released by Intestinal Epithelial Cells1

Inflammatory stresses associated with inflammatory bowel diseases up-regulate P2Y2 mRNA receptor expression in the human colon adenocarcinoma cell line Caco-2, the noncancerous IEC-6 cells and in colonic tissues of patient suffering from Crohn’s disease and ulcerative colitis. However, the transcriptional events regulating P2Y2 receptor (P2Y2R) expression are not known. We have identified a putative transcription start site in the P2Y2R gene and demonstrated acetylation of Lys14 on histone H3 and Lys8 on histone H4, thus suggesting that the chromatin associated with the P2Y2 promoter is accessible to transcription factors. We also showed that the transcription factor NF-κB p65 regulates P2Y2R transcription under both proinflammatory and basal conditions. A NF-κB-responsive element was identified at −181 to −172 bp in the promoter region of P2Y2. Hence, activation of P2Y2R by ATP and UTP stimulated cyclooxygenase-2 expression and PGE2 secretion by intestinal epithelial cells. These findings demonstrate that P2Y2R expression is regulated during intestinal inflammation through an NF-κB p65-dependent mechanism and could contribute not only to inflammatory bowel disease but also to other inflammatory diseases by regulating PG release.
Size, strength and allometry of joints in the articulated coralline Calliarthron

SUMMARY Articulated coralline algae (Corallinales, Rhodophyta) dominate low-intertidal, wave-exposed habitats around the world, yet the mechanics of this diverse group of organisms has been almost completely unexplored. In contrast to fleshy seaweeds, articulated corallines consist of calcified segments (intergenicula) separated by uncalcified joints (genicula). This jointed construction makes calcified fronds as flexible as fleshy seaweeds, allowing them to `go with the flow' when struck by breaking waves. In addition to functioning as joints, genicula act as breakage points along articulated fronds. Here, I describe the allometric scaling of geniculum size, breaking force and tissue strength along articulated fronds in two species of Calliarthron. Genicular material is much stronger than tissue from fleshy macroalgae. Moreover, as fronds grow, genicula get bigger and their tissue strengthens, two processes that help them resist breakage. Within individual fronds, larger branches, which presumably experience greater drag force, are supported by bigger, stronger genicula. However, frond growth greatly outpaces genicular strengthening. As a result, Calliarthron fronds most likely break at their bases when critically stressed by incoming waves. Shedding fronds probably reduces the drag force that threatens to dislodge coralline crusts and may constitute a reproductive strategy.
Capacity gain of MIMO systems with micro-structured antenna arrays

This paper aims to evaluate the contribution of micro-structured antennas in MIMO communication systems. This antenna technology is based on hybridization band gaps and presents at the same time a very small form factor and very low correlation coefficients. In order to evaluate this new type of antenna, a comparison of performance with patch antenna type was performed. Both prototypes were used in an indoor measurement campaign in a residential environment. An analysis of the MIMO matrix measurement has been carried out focusing on the MIMO gain capacity of the two types of antennas.
Amino acid sequence of mouse tenascin and differential expression of two tenascin isoforms during embryogenesis

We have isolated cDNA clones for mouse tenascin and analyzed expression of tenascin mRNAs during embryonic development of the kidney and gut. The deduced amino acid sequence of the mouse tenascin cDNAs shows a modular structure of repeats similar to chicken and human tenascin. In mouse there are 14.5 cysteine-rich repeats with similarity to the EGF repeat, followed by several repeats with similarity to the type III repeat of fibronectin. A longer variant contains 13 fibronectin type III repeats, whereas a shorter splice variant of mouse tenascin lacks the 5 type III repeats that occur directly after the fifth repeat in the longer variant. Contrary to the chicken and human sequences, mouse tenascin does not contain an RGD sequence in the third type III repeat implicated in cell attachment, or in any other positions. In Northern hybridizations to RNA from primary embryonic fibroblasts, the cDNA clone M 20/1 detects two mRNAs with sizes close to 6 and 8 kb. This, and the other data presented here suggest that the two major mouse tenascin polypeptides arise through an alternative RNA splicing. The two major mRNAs are differentially expressed during development. The 8- kb mRNA is more prominent than the 6-kb mRNA throughout prenatal kidney development, but during postnatal development the ratio of the two mRNAs changes. A different expression pattern is seen in the developing gut where the 6-kb mRNA predominates during embryogenesis with the 8-kb mRNA appearing later. The mRNA data of the developing gut correspond with previous protein data, which showed that the shorter Mr 210,000 polypeptide predominates during earlier developmental stages and the larger Mr 260,000 polypeptide appears later in the embryonic gut (Aufderheide, E., and P. Ekblom. 1988. J. Cell Biol. 107:2341-2349).
Public acceptability of financial incentives for smoking cessation in pregnancy and breast feeding: a survey of the British public

Objective To survey public attitudes about incentives for smoking cessation in pregnancy and for breast feeding to inform trial design. Design Cross-sectional survey. Setting and participants British general public. Methods Seven promising incentive strategies had been identified from evidence syntheses and qualitative interview data from service users and providers. These were shopping vouchers for: (1) validated smoking cessation in pregnancy and (2) after birth; (3) for a smoke-free home; (4) for proven breast feeding; (5) a free breast pump; (6) payments to health services for reaching smoking cessation in pregnancy targets and (7) breastfeeding targets. Ipsos MORI used area quota sampling and home-administered computer-assisted questionnaires, with randomised question order to assess agreement with different incentives (measured on a five-point scale). Demographic data and target behaviour experience were recorded. Analysis used multivariable ordered logit models. Results Agreement with incentives was mixed (ranging from 34% to 46%) among a representative sample of 1144 British adults. Mean agreement score was highest for a free breast pump, and lowest for incentives for smoking abstinence after birth. More women disagreed with shopping vouchers than men. Those with lower levels of education disagreed more with smoking cessation incentives and a breast pump. Those aged 44 or under agreed more with all incentive strategies compared with those aged 65 and over, particularly provider targets for smoking cessation. Non-white ethnic groups agreed particularly with breastfeeding incentives. Current smokers with previous stop attempts and respondents who had breast fed children agreed with providing vouchers for the respective behaviours. Up to £40/month vouchers for behaviour change were acceptable (>85%). Conclusions Women and the less educated were more likely to disagree, but men and women of childbearing age to agree, with incentives designed for their benefit. Trials evaluating reach, impact on health inequalities and ethnic groups are required prior to implementing incentive interventions. Trial registration number CRD42012001980.
Permissive Controller Synthesis for Probabilistic Systems

We propose novel controller synthesis techniques for probabilistic systems modelled using stochastic two-player games: one player acts as a controller, the second represents its environment, and probability is used to capture uncertainty arising due to, for example, unreliable sensors or faulty system components. Our aim is to generate robust controllers that are resilient to unexpected system changes at runtime, and flexible enough to be adapted if additional constraints need to be imposed. We develop a permissive controller synthesis framework, which generates multi-strategies for the controller, offering a choice of control actions to take at each time step. We formalise the notion of permissiveness using penalties, which are incurred each time a possible control action is blocked by a multi-strategy. Permissive controller synthesis aims to generate a multi-strategy that minimises these penalties, whilst guaranteeing the satisfaction of a specified system property. We establish several key results about the optimality of multi-strategies and the complexity of synthesising them. Then, we develop methods to perform permissive controller synthesis using mixed integer linear programming and illustrate their effectiveness on a selection of case studies.
Effects of a default on the reflectivity of plane periodic media

The influence of defect layers in a fluid-loaded plane multilayer composed of N periods is highlighted by analyzing the stop bands and pass bands of the reflection coefficient. The period is composed of two plates exhibiting a high impedance contrast, in aluminum and polyethylene for instance. No attenuation is taken into account Two types of defect layers are considered: either the thickness of a plate in one period is varied, or a layer made up of another material is inserted between two adjacent periods. The transmission coefficient is obtained with a numerically stable transfer matrix method. The study consists in comparing the plots of the transmission coefficient of a structure with no defect to the ones of structures with defects inserted at different locations. The variations of the resonance frequencies in the pass bands according to the defect position, as well as the width of the stop bands, are studied. A particular attention has been paid to the resonances at low frequency, linked with the so-called vertical modes. In the case of a defect included between two periods, it may appear very narrow pass bands in the stop bands.
Mobile capture for wearable computer usability testing

The-mobility of wearable computers makes usability-testing; difficult. In order to fully understand how a user interacts with the wearable, the researcher must examine, both the user's direct interactions, with the, computer, as well as the external context the user perceives during their interaction. We present, a tool that augments a wearable computer with additional hardware and software to capture the information needed to perform a usability study in the field under realistic conditions. We examine the challenges in doing the capture and present our implementation. We also describe VizWear a tool for examining the captured data. Finally, we present our experiences using the system for a sample user study.
Training Context-Sensitive Neural Networks with Few Relevant Examples for the TREC-9 Routing

The present paper describes our second participation to the routing task; it features improvements over our previous approach [Stricker et al., 2000]. Our former model used a "bag of words" for text representation with a feature selection, and a neural network without hidden neuron (i.e. a logistic regression), to estimate the probability of relevance of each document. This approach was close to the ones proposed by [Schutze et al., 1995] or [Wiener et al., 1995] but its original feature was the use of very few relevant features for text representation (25 features per topic on the average for the TREC-8 Routing). In this paper, two main improvements are proposed: • The feature selection defines target words for which vectors of local contexts are subsequently defined. These vectors help disambiguate the target words and are defined by an analysis of both the relevant and the irrelevant documents of the training set. • This new representation requires large neural networks, which are therefore prone to overfitting. A regularization technique is applied during training to favor smoother network mappings, thereby avoiding overfitting. This was achieved by adding a weight decay term to the usual cost function. This approach led to good results on the MeSH Sample topics (S2RNsamp) and on the OHSUMED topics (S2RNr1 and S2RNr2).
Homotopical Patch Theory ( Expanded Version )

Homotopy type theory is an extension of Martin-Löf type theory, based on a correspondence with homotopy theory and higher category theory. In homotopy type theory, the propositional equality type becomes proof-relevant, and corresponds to paths in a space. This allows for a new class of datatypes, called higher inductive types, which are specified by constructors not only for points but also for paths. In this paper, we consider a programming application of higher inductive types. Version control systems such as Darcs are based on the notion of patches—syntactic representations of edits to a repository. We show how patch theory can be developed in homotopy type theory. Our formulation separates formal theories of patches from their interpretation as edits to repositories. A patch theory is presented as a higher inductive type. Models of a patch theory are given by maps out of that type, which, being functors, automatically preserve the structure of patches. Several standard tools of homotopy theory come into play, demonstrating the use of these methods in a practical programming context.
The Impact of Goal Specificity on Strategy Use and the Acquisition of Problem Structure

Theories of skill acquisition have made radically different predictions about the role of general problem-solving methods in acquiring rules that promote effective transfer to new problems. Under one view, methods that focus on reaching specific goals, such as means-ends analysis, are assumed to provide the basis for efficient knowledge compilation (Anderson, 1987). whereas under an alternative view such methods are believed to disrupt rule induction (Sweller, 1988). We suggest that the role of general methods in learning varies with both the specificity of the problem solver’s goal and the systematicity of the strategies used for testing hypotheses about rules. In the absence of a specific goal people are more likely to use a rule-induction learning strategy, whereas provision of a specific goal fosters use of difference reduction, which tends to be a non-rule-induction strategy. We performed two experiments to investigate the impact of goal specificity and systematicity of rule-induction strategies in learning and transfer within a complex dynamic system. The results of Experiment 1 indicated that during free exploration of a problem space, greater learning occurred if participants adopted more systematic strategies for rule induction, and that participants come to favor such strategies. Experiment 2 revealed that participants who were provided with a specific goal performed well on the initial problem but were impaired on a transfer test using a similar problem with a different goal. Instruction on a systematic rule-induction strategy facilitated solution for both the initial and transfer problems, but participants’ use of this strategy declined if they had a specific goal. Our results support Sweller’s (1988) proposal that general problemsolving methods applied to a specific goal foster acquisition of knowledge about an isolated solution path but da not provide an effective way of learning the overall structure of a problem space. We interpret these results in terms of dualspace theories of search through problem space.