Miracle-dz/UniFAR-FTUs huggingface dataset:
MINDFULNESS, SELF-COMPASSION AND THREAT RELATED ATTENTIONAL BIAS: IMPLICATIONS FOR SOCIAL ANXIETY AND LONELINESS IN LATE ADOLESCENT COLLEGE STUDENTS.

The present study examined associations among mindfulness, self-compassion, social anxiety, loneliness and attention bias toward threat in a community sample of undergraduate university students (n = 176). Of interest was whether threat bias would mediate the independent effects of mindfulness and self-compassion on social anxiety and loneliness. Threat bias is characterized by the display of exaggerated attention toward threatening cues in the environment and has been repeatedly linked to the origin and continuation of anxious symptoms. Given the focus of contemplative practices on attentional awareness and control, this study examined whether mindfulness and self-compassion may contribute to decreased levels of anxiety and loneliness, in part, by influencing attentional mechanisms that may lower threat bias. The specificity of individual facets of mindfulness and self-compassion were also examined in relation to threat bias, social anxiety and loneliness. Overall, findings confirm previous studies, demonstrating strong predictive associations between mindfulness, self-compassion, social anxiety and loneliness in college students. Results also highlight the indirect effect of attention bias in the relationship between self-compassion, loneliness and social anxiety. The implications of these findings are discussed in relation to contemplative intervention programs to promote healthy social adjustment and relations in late adolescent college students.
Community Violence and Trauma: The Influence of Child Abuse, Bullying, and Intimate Partner Violence

Community violence exposure is associated with a myriad of physical and mental health problems and adjustment difficulties (Fowler, Tompsett, Braciszewski, Jacques-Tiura & Baltes, 2009; Senn, Walsh & Carey, 2016 ; Voisin, Chen, Fullilove & Jacobson, 2015). However, the research that investigates the adult mental health consequences of community violence exposure within the context of other potentially traumatic events is still emerging (Walling, Eriksson, Putman & Foy, 2011; Kennedy, Bybee & Greeson, 2014 ). This dissertation responds to this gap in the literature. This study investigated the interrelationships among violence exposures in community, school, family and intimate relationships and PTSD symptoms. The study also examined whether child abuse, intimate partner violence and school bullying moderated the relationship between community violence exposure and PTSD. The researcher collected data from 499 undergraduate students using a demographic questionnaire, the Trauma Symptom Checklist -40 (Briere & Runtz, 1989), the Survey of Exposure to Community Violence (SECV; Richters & Saltzman, 1990), the Retrospective Bully Questionnaire (RBQ; Schäfer, et al,2004), the Composite Abuse Scale (Hegarty, Bush, Sheehan, 2005) and the Early Trauma InventorySelf Report (ETI-SR; Bremner, Bolus & Mayer, 2007). Bivariate correlations revealed significant, positive correlations between PTSD and community violence exposure (r =.264, p < .01), school bullying (r = .242, p < .01), intimate partner violence (r = .327, p < .01) and child abuse (r = .292, p < .01). Community violence, child abuse, intimate partner violence and school bully significantly predicted the variance in PTSD symptoms. The study found that child abuse, intimate partner violence and school bullying scores were (β = -.000, t (216) = -. 027, p >. 01) not substantial moderators for the relationship between community violence and PTSD with this sample F(211) = 8.067, p < . 01, R = . 192 ) . Demographic differences in PTSD symptoms and community violence exposure were observed. INDEX WORDS: Community Violence, PTSD, Intimate Partner Violence, Child Abuse COMMUNITY VIOLENCE AND TRAUMA: THE INFLUENCE OF CHILD ABUSE, BULLYING AND INTIMATE PARTNER VIOLENCE By CLAUDINE O. ANDERSON-ATKINSON, MS.
Brazilian Road Traffic Fatalities: A Spatial and Environmental Analysis

Background Road traffic injuries (RTI) are a major public health epidemic killing thousands of people daily. Low and middle-income countries, such as Brazil, have the highest annual rates of road traffic fatalities. In order to improve road safety, this study mapped road traffic fatalities on a Brazilian highway to determine the main environmental factors affecting road traffic fatalities. Methods and Findings Four techniques were utilized to identify and analyze RTI hotspots. We used spatial analysis by points by applying kernel density estimator, and wavelet analysis to identify the main hot regions. Additionally, built environment analysis, and principal component analysis were conducted to verify patterns contributing to crash occurrence in the hotspots. Between 2007 and 2009, 379 crashes were notified, with 466 fatalities on BR277. Higher incidence of crashes occurred on sections of highway with double lanes (ratio 2∶1). The hotspot analysis demonstrated that both the eastern and western regions had higher incidences of crashes when compared to the central region. Through the built environment analysis, we have identified five different patterns, demonstrating that specific environmental characteristics are associated with different types of fatal crashes. Patterns 2 and 4 are constituted mainly by predominantly urban characteristics and have frequent fatal pedestrian crashes. Patterns 1, 3 and 5 display mainly rural characteristics and have higher prevalence of vehicular collisions. In the built environment analysis, the variables length of road in urban area, limited lighting, double lanes roadways, and less auxiliary lanes were associated with a higher incidence of fatal crashes. Conclusions By combining different techniques of analyses, we have identified numerous hotspots and environmental characteristics, which governmental or regulatory agencies could make use to plan strategies to reduce RTI and support life-saving policies.
STROBE-compliant article

AbstractContinuity of care (COC) has a proven relationship with health care outcomes. However, evidence regarding an association between COC and avoidable hospitalization for elderly patients with asthma is insufficient.A retrospective cohort study was performed using Taiwanese National Health Insurance claim data from 2004 to 2013. Patients were retrospectively followed for 2 years; the COC index (COCI) for asthma was measured in the 1st year, and avoidable hospitalization for asthma and follow-up time were determined in the subsequent year. Cox proportional hazards regression was employed to examine hazard ratios (HRs) between COC and avoidable hospitalization for asthma after adjustment for confounding factors. Adjusted HR (aHR) was also calculated by stratifying each variable to investigate whether the effect of COC on hospitalization for asthma was avoidable and how this varied across levels of COCI.Of 3356 patients included in this study, 1648 patients (49%) had a COCI of 1, and the average COCI was 0.73. Compared with patients with high COC (COCI = 1), those with low COC (COCI < 0.5) had a significantly higher risk of avoidable hospitalization for asthma (aHR = 2.68; 95% confidence interval [CI]: 1.55–4.63). In addition, after stratified analysis, we determined that COC plays a much more important role for patients who were women, had low insurance premiums, and had no comorbidities.High continuity of ambulatory asthma care is linked to a reduced risk of avoidable hospitalization for asthma in elderly asthmatic patients.
Minimalist Regression Network with Reinforced Gradients and Weighted Estimates: a Case Study on Parameters Estimation in Automated Welding

This paper presents a minimalist neural regression network as an aggregate of independent identical regression blocks that are trained simultaneously. Moreover, it introduces a new multiplicative parameter, shared by all the neural units of a given layer, to maintain the quality of its gradients. Furthermore, it increases its estimation accuracy via learning a weight factor whose quantity captures the redundancy between the estimated and actual values at each training iteration. We choose the estimation of the direct weld parameters of different welding techniques to show a significant improvement in calculation of these parameters by our model in contrast to state-of-the-arts techniques in the literature. Furthermore, we demonstrate the ability of our model to retain its performance when presented with combined data of different welding techniques. This is a nontrivial result in attaining an scalable model whose quality of estimation is independent of adopted welding techniques.
Automatically Identifying Morphological Relations in = Machine-Readable Dictionaries

We describe an automated method for identifying classes of morphologically related words in an on-line dictionary, and for linking individual senses in the derived form to one or more senses in the base form by means of morphological relation attributes. We also present an algorithm for computing a score reflecting the system=92s certainty in these derivational links; this computation relies on the content of semantic relations associated with each sense, which are extracted automatically by parsing each sense definition and subjecting the parse structure to automated semantic analysis. By processing the entire set of headwords in the dictionary in this fashion we create a large set of directed derivational graphs, which can then be accessed by other components in our broad-coverage NLP system. Spurious or unlikely derivations are not discarded, but are rather added to the dictionary and assigned a negative score; this allows the system to handle non-standard uses of these forms.
Bank Capital Requirements and Managerial Self-Interest

We analyze the effect of capital adequacy requirements on bank risk policy when managers and shareholders have different information about the quality of the loan portfolio. In a two-period model in which shareholders implement the optimal contract with managers, we show that the level of managerial effort (and therefore the quality of the loan portfolio) is higher when shareholders cannot observe the manager's action. When information regarding the bank loan portfolio is symmetric, capital requirements help reduce the excess risk-taking problem that deposit insurance creates. Taking as given optimal regulation on capital requirements and deposit insurance, we show that the moral hazard problem in banks leads to a reduction in the banks' loan portfolio through an increase in the managerial effort in loan supervision. Only high-quality loans are accepted by the bank, but some profitable investments are bypassed because managers are more interested in maximizing their compensation (diluting the stock value) than in maximizing the shareholders' wealth. Thus we conclude that the riskiness of banks may be suboptimally low under
A data-driven spoken language understanding system

The paper presents a purely data-driven spoken language understanding (SLU) system. It consists of three major components, a speech recognizer, a semantic parser, and a dialog act decoder. A novel feature of the system is that the understanding components are trained directly from data without using explicit semantic grammar rules or fully-annotated corpus data. Despite this, the system is nevertheless able to capture hierarchical structure in user utterances and handle long range dependencies. Experiments have been conducted on the ATIS corpus and 16.1% and 12.6% utterance understanding error rates were obtained for spoken input using the ATIS-3 1993 and 1994 test sets. These results show that our system is comparable to existing SLU systems which rely on either handcrafted semantic grammar rules or statistical models trained on fully-annotated training corpora, but it has greatly reduced build cost.
Aging of Al thin film extreme ultraviolet filters

Thin film Al filters, very popular for their high transmittance in the wavelength range 17 to 67 nm and simultaneously low transmittance in the visible and near UV region, are prone to oxidation. The amorphous Al2O3 layers on the Al surfaces have much smaller transmittance than the bulk Al material, and, therefore, they strongly influence the total transmittance of the filter. This paper gives not only the transmittance of very old Al filters, but also maps the transmittance development of Al filters in two years span since their delivery in not controlled atmosphere. Surprisingly, it turned out that while the transmission of surface layers (present on filters since the very beginning) slightly increases with time, the average attenuation rate per unit filter thickness of the bulk material (Al) with time dramatically rises.
Innovative Activity in Rural Areas : The Importance of Local and Regional Characteristics

I nnovation, supported by a developed and active entrepreneurial system, long has been recognized as critical to regional economic competitiveness. regional competitiveness is driven by gains in productivity, and advances in productivity result from sustained innovative activity. Innovation also plays an essential role for rural economic development as these regions respond to the challenges of competing in the global economy. Specifically, Drabenstott and Henderson (2006) propose two key ingredients to a rural development strategy: (1) the twin force of innovation and entrepreneurs, and (2) a critical mass of human, financial, and social capital to support the evolving innovative and entrepreneurial activity. 2 Empirical support for the role of innovation in regional economic growth is provided in a study of county-level differences in 2002 per capita incomes and 1997 to 2002 per capita income growth (Schunk, Woodward, and Hefner, 2005). The authors used county-level utility patents and university research and development expenditures as measures of local innovation and innovative capacity. Their findings indicate that " roughly two-thirds of the variation in county-level per capita income across the U.S. can be explained by variations in these measures of innovation and innovative capacity " (9), and " counties with higher levels of patents and university research and development also appear to see faster rates of growth " (11). The innovation–economic development relationship is good economic news for regions with significant innovative capacity (such as the Research Triangle in North Carolina) or the resources to attract a major research and development center (Florida and the Scripps Institute, for example). Unfortunately for many local economies, however, innovative capacity and activity are distributed very unevenly across the country. For example, among the 1,343 counties in the thirteen southern states, twenty-six counties averaged 100 or more utility patents a year from 1990 to 1999, while 681 counties averaged less than one utility patent per year for the same period. A clustering of patenting activity would not necessarily be detrimental to the economic development prospects of areas with little innovative activity if there exists the spillovers of jobs and income from the innovation centers to other areas. Evidence of such spillovers is relatively limited. Acs (2002, 165) concluded that " we have established a striking correlation between local R&D and subsequent high-technology employment in the same MSA (metropolitan statistical area) and three-digit industry cluster. There is apparently no spillover relationship from R&D in other industry groups. " These …
Early reionization by the first galaxies

Large-scale polarization of the cosmic microwave background measured by the WMAP satellite requires a mean optical depth to Thomson scattering, τ e ∼ 0.17. The reionization of the Universe must therefore have begun at relatively high redshift. We have studied the reionization process using supercomputer simulations of a large and representative region of a universe which has cosmological parameters consistent with the WMAP results (Ω m = 0.3, Ω Λ = 0.7, h = 0.7, Ω b = 0.04, n = 1 and σ 8 = 0.9). Our simulations follow both the radiative transfer of ionizing photons and the formation and evolution of the galaxy population which produces them. A previously published model with ionizing photon production as expected for zero-metallicity stars distributed according to a standard stellar initial mass function (IMF) (10 6 1 photons per unit solar mass of formed stars) and with a moderate photon escape fraction from galaxies (5 per cent), produces τ e = 0.104, which is within 1.0 to 1. 5σ of the 'best' WMAP value. Values of up to 0.16 can be produced by taking larger escape fractions or a top-heavy IMF. The data do not require a separate populations of 'miniquasars' or of stars forming in objects with total masses below 10 9 M O . Reconciling such early reionization with the observed Gunn-Peterson troughs in z > 6 quasars may be challenging. Possible resolutions of this problem are discussed.
On the Formal Specification of Group Membership Services

The problem of group membership has been the focus of much theoretical and experimental work on fault-tolerant distributed systems. This has resulted in a voluminous literature and several formal specifications of this problem have been given. In this paper, we examine the two most referenced formal specifications of group membership and show that they are unsatisfactory: One has flaws in the formalism and allows undesirable executions, and the other can be satisfied by useless protocols.
Brain Penetration of the Oral Immunomodulatory Drug FTY720 and Its Phosphorylation in the Central Nervous System during Experimental Autoimmune Encephalomyelitis: Consequences for Mode of Action in Multiple Sclerosis

FTY720 [2-amino-2-[2-(4-octylphenyl) ethyl]propane-1,3-diol hydrochloride] is an oral sphingosine-1-phosphate receptor modulator under development for the treatment of multiple sclerosis (MS). The drug is phosphorylated in vivo by sphingosine kinase 2 to its bioactive form, FTY720-P. Although treatment with FTY720 is accompanied by a reduction of the peripheral lymphocyte count, its efficacy in MS and experimental autoimmune encephalomyelitis (EAE) may be due to additional, direct effects in the central nervous system (CNS). We now show that FTY720 localizes to the CNS white matter, preferentially along myelin sheaths. Brain trough levels of FTY720 and FTY720-P in rat EAE are of the same magnitude and dose dependently increase; they are in the range of 40 to 540 ng/g in the brain tissue at efficacious doses and exceed blood concentrations severalfold. In a rat model of chronic EAE, prolonged treatment with 0.03 mg/kg was efficacious, but limiting the dosing period failed to prevent EAE despite a significant decrease in blood lymphocytes. FTY720 effectiveness is likely due to a culmination of mechanisms involving reduction of autoreactive T cells, neuroprotective influence of FTY720-P in the CNS, and inhibition of inflammatory mediators in the brain.
Canine pyometra: a model for the analysis of serum CXCL8 in inflammation

Interleukin-8 (IL-8 or CXCL8) is a highly selective pro-inflammatory chemokine, that is elevated in sera of humans and animals with various inflammatory diseases. CXCL8 is possibly involved in uncontrolled inflammation and the development of a systemic inflammatory response syndrome (SIRS) and sepsis. Nevertheless, its behavior and precise properties in the course of inflammation are not fully understood. Thus, we used naturally occurring canine pyometra as a model of inflammation, in order to examine the behavior of serum CXCL8 in relation to the disease intensity and commonly analyzed inflammatory mediators. Using a commercially available canine ELISA kit, a significant increase of CXCL8 was determined in the serum of 23 dogs with pyometra compared with 35 healthy dogs. Interestingly, serum CXCL8 did not increase in severely diseased patients and behaved contrary to white blood cells (WBC), neutrophils and C-reactive protein (CRP). The measurement of serum CXCL8 may provide valuable information about the extent of ongoing lesions and could be a useful complement for existing laboratory tests.
Arc-Faults Detection in PV Systems by Measuring Pink Noise With Magnetic Sensors

The dc-arc detection is essential for dc systems to operate reliably and safely. Due to the randomness of dc-arc faults, it is difficult to define their characteristics for detection. The magnetic-sensing-based methodology using tunnel magnetoresistance (TMR) sensor was developed to distinguish the dc arc accurately. However, the noise from the power electronics such as maximum power pointing tracking (MPPT) controllers could affect the dc-arc detection in a photovoltaic (PV) system. In this paper, the arc faults which may occur in PV systems under various conditions were emulated in the dc system of 9 kW. It was verified that the proposed methodology of measuring pink noise can distinguish the dc arc accurately for PV systems from 48 to 300 V and current up to 30 A. An off-grid PV system was established to experimentally demonstrate the arc-detection method in the practical system. The experimental results confirmed that the technique could identify the dc arc correctly with an extended working region despite the noise of power electronics in MPPT. It was verified that the arc-detection system is capable of discriminating the normal operation and arc fault in the PV system. This technique is applicable and promising for arc-faults detection in PV systems.
Multivariate Normal Distributions Parametrized as a Riemannian Symmetric Space

The construction of a distance function between probability distributions is of importance in mathematical statistics and its applications. The distance function based on the Fisher information metric has been studied by a number of statisticians, especially in the case of the multivariate normal distribution (Gaussian) on Rn. It turns out that, except in the case n=1, where the Fisher metric describes the hyperbolic plane, it is difficult to obtain an exact formula for the distance function (although this can be achieved for special families with fixed mean or fixed covariance). We propose to study a slightly different metric on the space of multivariate normal distributions on Rn. Our metric is based on the fundamental idea of parametrizing this space as the Riemannian symmetric space SL(n+1)/SO(n+1). Symmetric spaces are well understood in Riemannian geometry, allowing us to compute distance functions and other relevant geometric data.
Tyrosine Phosphatases ε and α Perform Specific and Overlapping Functions in Regulation of Voltage-gated Potassium Channels in Schwann Cells

Tyrosine phosphatases (PTPs) epsilon and alpha are closely related and share several molecular functions, such as regulation of Src family kinases and voltage-gated potassium (Kv) channels. Functional interrelationships between PTPepsilon and PTPalpha and the mechanisms by which they regulate K+ channels and Src were analyzed in vivo in mice lacking either or both PTPs. Lack of either PTP increases Kv channel activity and phosphorylation in Schwann cells, indicating these PTPs inhibit Kv current amplitude in vivo. Open probability and unitary conductance of Kv channels are unchanged, suggesting an effect on channel number or organization. PTPalpha inhibits Kv channels more strongly than PTPepsilon; this correlates with constitutive association of PTPalpha with Kv2.1, driven by membranal localization of PTPalpha. PTPalpha, but not PTPepsilon, activates Src in sciatic nerve extracts, suggesting Src deregulation is not responsible exclusively for the observed phenotypes and highlighting an unexpected difference between both PTPs. Developmentally, sciatic nerve myelination is reduced transiently in mice lacking either PTP and more so in mice lacking both PTPs, suggesting both PTPs support myelination but are not fully redundant. We conclude that PTPepsilon and PTPalpha differ significantly in their regulation of Kv channels and Src in the system examined and that similarity between PTPs does not necessarily result in full functional redundancy in vivo.