Miracle-dz/UniFAR-FTUs huggingface dataset:
A factor analysis of tic symptoms in Gilles de la Tourette's syndrome.

OBJECTIVE Gilles de la Tourette's syndrome is a well-characterized disorder with clear DSM-IV criteria. However, the great deal of clinical variability across patients may represent an underlying etiologic complexity. Issues of phenotypic heterogeneity are particularly critical to current efforts at mapping genes involved in this syndrome. METHOD Lifetime tic symptom data were obtained from direct structured interviews of 85 Tourette's disorder probands. Information on 29 tic symptoms was elicited. The probands' tic symptoms were grouped by using agglomerative hierarchical clustering, with no a priori assumptions concerning the relatedness of symptoms. Scores for the probands' symptom clusters were used as variables in a principal-component factor analysis. The relationships of the resulting factor scores to comorbidity in probands and recurrence risks in relatives were examined. In addition, intraclass correlations were calculated for within-family factor scores of 36 families. RESULTS Four significant factors were identified: 1) aggressive phenomena (e.g., kicking, temper fits, argumentativeness), 2) purely motor and phonic tic symptoms, 3) compulsive phenomena (e.g., touching of others or objects, repetitive speech, throat clearing), and 4) tapping and absence of grunting. Analysis of the symptom loadings, comorbidity, recurrence risks, and within-family correlations indicate that these factors represent a valid structure with clinical and biological relevance. CONCLUSIONS In this symptom-based factor analysis of Tourette's disorder, four factors accounted for 61% of the phenotypic symptom variance in Tourette's disorder probands and their first-degree relatives. Three of these factors may indicate the presence of heritable components of the Tourette's disorder phenotype.
Exponentially slow mixing in the mean-field Swendsen-Wang dynamics

Swendsen-Wang dynamics for the Potts model was proposed in the late 1980's as an alternative to single-site heat-bath dynamics, in which global updates allow this MCMC sampler to switch between metastable states and ideally mix faster. Gore and Jerrum (1999) found that this dynamics may in fact exhibit slow mixing: they showed that, for the Potts model with $q\geq 3$ colors on the complete graph on $n$ vertices at the critical point $\beta_c(q)$, Swendsen-Wang dynamics has $t_{\mathrm{mix}}\geq \exp(c\sqrt n)$. The same lower bound was extended to the critical window $(\beta_s,\beta_S)$ around $\beta_c$ by Galanis et al. (2015), as well as to the corresponding mean-field FK model by Blanca and Sinclair (2015). In both cases, an upper bound of $t_{\mathrm{mix}} \leq \exp(c' n)$ was known. Here we show that the mixing time is truly exponential in $n$: namely, $t_{\mathrm{mix}} \geq \exp (cn)$ for Swendsen-Wang dynamics when $q\geq 3$ and $\beta\in(\beta_s,\beta_S)$, and the same bound holds for the related MCMC samplers for the mean-field FK model when $q>2$.
Pruning and summarizing the discovered associations

Association rules are a fundamental class of patterns that exist in data. The key strength of association rule mining is its completeness. It finds all associations in the data that satisfy the user specified minimum support and minimum confidence constraints. This strength, however, comes with a major drawback. It often produces a huge number of associations. This is particularly true for data sets whose attributes are highly correlated. The huge number of associations makes it very diff icult, if not impossible, for a human user to analyze in order to identify those interesting/useful ones. In this paper, we propose a novel technique to overcome this problem. The technique first prunes the discovered associations to remove those insignificant associations, and then finds a special subset of the unpruned associations to form a summary of the discovered associations. We call this subset of associations the direction setting (DS) rules as they set the directions that are followed by the rest of the associations. Using this summary, the user can focus on the essential aspects (or relationships) of the domain and selectively view the relevant details. The approach is effective because experiment results show that the set of DS rules is typically very small . They can be analyzed manually by a human user. The proposed technique has also been applied successfully to a number of real-li fe applications.
MLCK regulates Schwann cell cytoskeletal organization, differentiation and myelination

Signaling through cyclic AMP (cAMP) has been implicated in the regulation of Schwann cell (SC) proliferation and differentiation. In quiescent SCs, elevation of cAMP promotes the expression of proteins associated with myelination such as Krox-20 and P0, and downregulation of markers associated with the non-myelinating SC phenotype. We have previously shown that the motor protein myosin II is required for the establishment of normal SC–axon interactions, differentiation and myelination, however, the mechanisms behind these effects are unknown. Here we report that the levels and activity of myosin light chain kinase (MLCK), an enzyme that regulates MLC phosphorylation in non-muscle cells, are dramatically downregulated in SCs after cAMP treatment, in a similar pattern to that of c-Jun, a known inhibitor of myelination. Knockdown of MLCK in SCs mimics the effect of cAMP elevation, inducing plasma membrane expansion and expression of Krox-20 and myelin proteins. Despite activation of myelin gene transcription these cells fail to make compact myelin when placed in contact with axons. Our data indicate that myosin II activity is differentially regulated at various stages during myelination and that in the absence of MLCK the processes of SC differentiation and compact myelin assembly are uncoupled.
Learning sensory maps with real-world stimuli in real time using a biophysically realistic learning rule

We present a real-time model of learning in the auditory cortex that is trained using real-world stimuli. The system consists of a peripheral and a central cortical network of spiking neurons. The synapses formed by peripheral neurons on the central ones are subject to synaptic plasticity. We implemented a biophysically realistic learning rule that depends on the precise temporal relation of pre- and postsynaptic action potentials. We demonstrate that this biologically realistic real-time neuronal system forms stable receptive fields that accurately reflect the spectral content of the input signals and that the size of these representations can be biased by global signals acting on the local learning mechanism. In addition, we show that this learning mechanism shows fast acquisition and is robust in the presence of large imbalances in the probability of occurrence of individual stimuli and noise.
CaV3.2 Channels and the Induction of Negative Feedback in Cerebral Arteries

Rationale: T-type (CaV3.1/CaV3.2) Ca2+ channels are expressed in rat cerebral arterial smooth muscle. Although present, their functional significance remains uncertain with findings pointing to a variety of roles. Objective: This study tested whether CaV3.2 channels mediate a negative feedback response by triggering Ca2+ sparks, discrete events that initiate arterial hyperpolarization by activating large-conductance Ca2+-activated K+ channels. Methods and Results: Micromolar Ni2+, an agent that selectively blocks CaV3.2 but not CaV1.2/CaV3.1, was first shown to depolarize/constrict pressurized rat cerebral arteries; no effect was observed in CaV3.2−/− arteries. Structural analysis using 3-dimensional tomography, immunolabeling, and a proximity ligation assay next revealed the existence of microdomains in cerebral arterial smooth muscle which comprised sarcoplasmic reticulum and caveolae. Within these discrete structures, CaV3.2 and ryanodine receptor resided in close apposition to one another. Computational modeling revealed that Ca2+ influx through CaV3.2 could repetitively activate ryanodine receptor, inducing discrete Ca2+-induced Ca2+ release events in a voltage-dependent manner. In keeping with theoretical observations, rapid Ca2+ imaging and perforated patch clamp electrophysiology demonstrated that Ni2+ suppressed Ca2+ sparks and consequently spontaneous transient outward K+ currents, large-conductance Ca2+-activated K+ channel mediated events. Additional functional work on pressurized arteries noted that paxilline, a large-conductance Ca2+-activated K+ channel inhibitor, elicited arterial constriction equivalent, and not additive, to Ni2+. Key experiments on human cerebral arteries indicate that CaV3.2 is present and drives a comparable response to moderate constriction. Conclusions: These findings indicate for the first time that CaV3.2 channels localize to discrete microdomains and drive ryanodine receptor–mediated Ca2+ sparks, enabling large-conductance Ca2+-activated K+ channel activation, hyperpolarization, and attenuation of cerebral arterial constriction.
Gastrointestinal Parasites in Mammals of Two Italian Zoological Gardens

Abstract The prevalence of gastrointestinal parasites was investigated in mammals housed in two of the main Italian zoological gardens: the Zoo Safari of Fasano (province of Bindisi, Apulia, Italy) and the Giardino Zoologico of Pistoia (Tuscany, Italy). In November 2007, fecal samples were collected at the Zoo Safari of Fasano (n = 96) and at the Giardino Zoologico of Pistoia (n = 60), from primates, carnivores, perissodactyls, artiodactyls and proboscideans. In most of the cases, the same animal species or genera were considered in both the zoos. One or more intestinal parasites were detected in 61.5% of the examined samples. However, very different percentages of protozoa- and helminth-positive samples were obtained in the animals from the two zoos, with an overall gastrointestinal parasitic infection of 77.1% in the Zoo Safari of Fasano and 36.7% in the Giardino Zoologico of Pistoia. Overall, 10% (Cryptosporidium sp.) and 43.3% (Toxocara cati, Strongyloides stercoralis, Toxascaris leonina, and hookworms) of carnivores, 66.7% (Cryptosporidium spp.) and 100% (Trichuris spp. and Strongyloides fülleborni) of primates, 25.0% (Eimeria spp., Cryptosporidium spp.), and 57.1% (Trichuris sp., Toxocara [Neoascaris] vitulorum, gastrointestinal strongyles, and Paramphistomidae) of artiodactyls were infected with protozoa and helminthes parasites, respectively. Only gastrointestinal strongyles were diagnosed in 16.7% of proboscideans and in 50.0% of perissodactyls examined. The results of this study suggest that zoonotic protozoans and gastrointestinal helminths are common in zoo mammals and that these animals may serve as a potential reservoir and transmit these parasites to humans. The different animal management in the two zoos indicates that the regular monitoring of parasitic diseases and the use of selective treatments can represent effective measures for the control of several gastrointestinal infections in zoological gardens.
Cooperative Network Coding Strategies for Wireless Relay Networks with Backhaul

We investigate cooperative network coding strategies for relay-aided two-source two-destination wireless networks with a backhaul connection between the source nodes. Each source multicasts information to all destinations using a shared relay. We study cooperative strategies based on different network coding schemes, namely, finite field and linear network coding, and lattice coding. To further exploit the backhaul connection, we also propose network coding based beamforming. We measure the performance in term of achievable rates over Gaussian channels, and observe significant gains over benchmark schemes. We derive the achievable rate regions for these schemes and find the cut-set bound for our system. We also show that the cut-set bound can be achieved by network coding based beamforming when the signal-to-noise ratios lie in the sphere defined by the source-relay and relay-destination channel gains.
Fifteen new T dwarfs discovered in the UKIDSS Large Area Survey

We present the discovery of fifteen new T2.5-T7.5 dwarfs (with estimated distances between �24–93pc), identified in the first three main data releases of the UKIRT Infrared Deep Sky Survey. This brings the total number of T dwarfs discovered in the Large Area Survey (to date) to 28. These discoveries are confirmed by near infrared spectroscopy, from which we derive spectral types on the unified scheme of Burgasser et al. (2006). Seven of the new T dwarfs have spectral types of T2.5-T4.5, five have spectral types of T5-T5.5, one is a T6.5p, and two are T7-7.5. We assess spectral morphology and colours to identify T dwarfs in our sample that may have non-typical physical properties (by comparison to solar neighbourhood populations), and find that one of these new T dwarfs may be metal poor, three may have low surface gravity, and one may have high surface gravity. The colours of the full sample of LAS T dwarfs show a possible trend to bluer Y J with decreasing effective temperature, and some interesting colour changes in J H and z J (deserving further investigation) beyond T8. The LAS T dwarf sample from the first and second main data releases show good evidence for a consistent level of completion to J=19. By accounting for the main sources of incompleteness (selection, follow-up and spatial) as well as the effects of unresolved binarity and Malmquist bias, we estimate that there are 17±4 >T4 dwarfs in the J 619 volume of the LAS second data release. Comparing this to theoretical predictions is most consistent with a sub-stellar mass function exponent α between -1.0 and 0. This is consistent with the latest 2MASS/SDSS constraint (which is based on lower number statistics), and is significantly lower than the α � 1.0 suggested by L dwarf field populations, possibly a result of the lower mass range probed by the T dwarf class.
Bifurcation of a Modified BVP Circuit Model for Neurons Generating Rectangular Waves (Special Section on Nonlinear Theory and Its Applications)

We investigate bifurcations of burst oscillations with rectangular waveform observed in a modified Bonhöffer-van der Pol equation, which is considered as a circuit model for neurons of a feeding rhythm generator. In particular, we clarify a mechanism of properties in a one-parameter graph on the period of oscillations, showing a staircase with hysteresis jumps, by studying a successive bifurcation process including a chain of homoclinic bifurcations. The occurrence of homoclinic bifurcations is confirmed by using the linking number of limit cycles related with the stable manifold through an equilibrium. key words: modified BVP equation, bifurcation, homoclinic orbit, chaos, neuronal model
Are You a Racist or Am I Seeing Things? Annotator Influence on Hate Speech Detection on Twitter

Hate speech in the form of racism and sexism is commonplace on the internet (Waseem and Hovy, 2016). For this reason, there has been both an academic and an industry interest in detection of hate speech. The volume of data to be reviewed for creating data sets encourages a use of crowd sourcing for the annotation efforts. In this paper, we provide an examination of the inﬂuence of annotator knowledge of hate speech on classiﬁcation models by comparing classiﬁcation results obtained from training on expert and amateur annotations. We provide an evaluation on our own data set and run our models on the data set released by Waseem and Hovy (2016). We ﬁnd that amateur annotators are more likely than expert annotators to label items as hate speech, and that systems trained on expert annotations outperform systems trained on amateur annotations.
On the Krull Dimension of the deformation ring of curves with automorphisms

We reduce the study of the Krull dimension d of the deformation ring of the functor of deformations of curves with automorphisms to the study of the tangent space of the deformation functor of a class of matrix representations of the p-part of the decomposition groups at wild ramified points, and we give a method in order to compute d.
Direct Isosurface Ray Casting of NURBS-Based Isogeometric Analysis

In NURBS-based isogeometric analysis, the basis functions of a 3D model's geometric description also form the basis for the solution space of variational formulations of partial differential equations. In order to visualize the results of a NURBS-based isogeometric analysis, we developed a novel GPU-based multi-pass isosurface visualization technique which performs directly on an equivalent rational Bézier representation without the need for discretization or approximation. Our approach utilizes rasterization to generate a list of intervals along the ray that each potentially contain boundary or isosurface intersections. Depth-sorting this list for each ray allows us to proceed in front-to-back order and enables early ray termination. We detect multiple intersections of a ray with the higher-order surface of the model using a sampling-based root-isolation method. The model's surfaces and the isosurfaces always appear smooth, independent of the zoom level due to our pixel-precise processing scheme. Our adaptive sampling strategy minimizes costs for point evaluations and intersection computations. The implementation shows that the proposed approach interactively visualizes volume meshes containing hundreds of thousands of Bézier elements on current graphics hardware. A comparison to a GPU-based ray casting implementation using spatial data structures indicates that our approach generally performs significantly faster while being more accurate.
Comparative analysis of methods for genome-wide nucleosome cartography

Nucleosomes contribute to compacting the genome into the nucleus and regulate the physical access of regulatory proteins to DNA either directly or through the epigenetic modifications of the histone tails. Precise mapping of nucleosome positioning across the genome is, therefore, essential to understanding the genome regulation. In recent years, several experimental protocols have been developed for this purpose that include the enzymatic digestion, chemical cleavage or immunoprecipitation of chromatin followed by next-generation sequencing of the resulting DNA fragments. Here, we compare the performance and resolution of these methods from the initial biochemical steps through the alignment of the millions of short-sequence reads to a reference genome to the final computational analysis to generate genome-wide maps of nucleosome occupancy. Because of the lack of a unified protocol to process data sets obtained through the different approaches, we have developed a new computational tool (NUCwave), which facilitates their analysis, comparison and assessment and will enable researchers to choose the most suitable method for any particular purpose. NUCwave is freely available at http://nucleosome.usal. es/nucwave along with a step-by-step protocol for its use.
Maximum Radiated Emissions of Printed Circuit Board Using Analytical Methods

The rapid progress of technology has imposed significant challenges on Printed Circuit Boards (PCB) designers. Once of those challenges is to satisfy the electromagnetic compatibility (EMC) compliance requirements. For that reason, EMC compliance must be considered earlier at the design stage for time and cost savings. Conventionally, full wave simulation is employed to check whether the designed PCB meets EMC standards or not. However, this method is not a suitable option since it requires intensive computational time and thus increasing the unit cost. This paper describes novel analytical models for estimating the radiated emissions (RE) of PCB. These models can be used to help the circuit designer to modify their circuit based on the maximum allowable RE comparing to the relevant EMC-RE standard limit. Although there are many RE sources on PCB, this paper focuses on the significant source of RE on PCB; namely PCB-traces. The trace geometry, termination impedance, dielectric type, etc. can be specified based on the maximum allowable emissions. The proposed models were verified by comparing the results of the proposed models with both simulation and experimental results. Good agreements were obtained between the analytically computed results and simulation/measurement results with accuracy of ±3dB.
The effect of social content on deductive reasoning: An fMRI study

Psychological studies of deductive reasoning have shown that subjects' performance is affected significantly by the content of the presented stimuli. Specifically, subjects find it easier to reason about contexts and situations with a social content. In the present study, the effect of content on brain activation was investigated with functional magnetic resonance imaging (fMRI) while subjects were solving two versions of the Wason selection task, which previous behavioral studies have shown to elicit a significant content effect. One version described an arbitrary relation between two actions (Descriptive: “If someone does …, then he does …”), whereas the other described an exchange of goods between two persons (Social‐Exchange: “If you give me …, then I give you …”). Random‐effect statistical analyses showed that compared to baseline, both tasks activated frontal medial cortex and left dorsolateral frontal and parietal regions, confirming the major role of the left hemisphere in deductive reasoning. In addition, although the two reasoning conditions were identical in logical form, the social‐exchange task was also associated with right frontal and parietal activations, mirroring the left‐sided activations common to both reasoning tasks. These results suggest that the recruitment of the right hemisphere is dependent on the content of the stimuli presented. Hum Brain Mapp, 2005. © 2005 Wiley‐Liss, Inc.
Positive Relationship between Aboveground Carbon Stocks and Structural Diversity in Spruce-Dominated Forest Stands in New Brunswick, Canada

Maintaining both the structure and functionality of forest ecosystems is a primary goal of forest management. In this study, relationships between structural diversity and aboveground stand carbon (C) stocks were examined in spruce-dominated forests in New Brunswick, Canada. Tree species, size, and height diversity indices as well as a combination of these diversity indices were used to correlate aboveground C stocks. Multiple linear regressions were subsequently used to quantify the relationships between these indices and aboveground C stocks, and partial correlation analysis was also adopted to remove the effects of other explanatory variables. Results show that stand structural diversity has a significant positive effect on aboveground C stocks even though the relationship is weak overall. Positive relationships observed between the diversity indices and aboveground C stocks support the hypothesis that increased structural diversity enhances aboveground C storage capacity. This occurs because complex forest structures allow for greater light infiltration and promote a more efficient resource use by trees, leading to an increase in biomass and C production. Mixed tolerant species composition and uneven-aged stand management in conjunction with selection or partial cutting to maintain high structural diversity is therefore recommended to preserve biodiversity and C stocks in spruce-dominated forests. FOR . S CI. 57(6):506-515.