Miracle-dz/UniFAR-FTUs huggingface dataset:
LOCALITY OF MHD TURBULENCE IN ISOTHERMAL DISKS

We numerically evolve turbulence driven by the magnetorotational instability (MRI) in a three-dimensional, unstratified shearing box and study its structure using two-point correlation functions. We confirm Fromang and Papaloizou's result that shearing box models with zero net magnetic flux are not converged; the dimensionless shear stress α is proportional to the grid scale. We find that the two-point correlation of shows that it is composed of narrow filaments that are swept back by differential rotation into a trailing spiral. The correlation lengths along each of the correlation function principal axes decrease monotonically with the grid scale. For mean azimuthal field models, which we argue are more relevant to astrophysical disks than the zero net field models, we find that: α increases weakly with increasing resolution at fixed box size; α increases slightly as the box size is increased; α increases linearly with net field strength, confirming earlier results; the two-point correlation function of the magnetic field is resolved and converged, and is composed of narrow filaments swept back by the shear; the major axis of the two-point increases slightly as the box size is increased; these results are code independent, based on a comparison of ATHENA and ZEUS runs. The velocity, density, and magnetic fields decorrelate over scales larger than ∼H, as do the dynamical terms in the magnetic energy evolution equations. We conclude that MHD turbulence in disks is localized, subject to the limitations imposed by the absence of vertical stratification, the use of an isothermal equation of state, finite box size, finite run time, and finite resolution.
The Theoretical Principles of the Body-Centered Therapy to Promote Affective Attunement in Children with Autism Spectrum Disorder

Background: The roots of autism spectrum disorders become evident in first attunement mechanisms between mother and child that allow a first level of mentalizing. Neurosciences and current developmental theories confirm the existence of defensive mechanisms related to body and affectivity that psychodynamic theories had already highlighted. Reading child’s behavior not only by administering tests but also through careful clinical observations allows a better understanding of the communication and social difficulties present in autistic children. The identification of the zone of proximal development can promote a therapeutic intervention that respects the individuality of the child and the specificity of his relational approach to the world. Conclusion: The paper presents the theoretical principles of a body-centered therapy to promote the attunement processes necessary to activate cognitive resources.
Passive cooling design options to improve thermal comfort in an Urban District of Rome, under hot summer conditions

The aim of this study is to investigate how the air temperature is affected by the urban design and how it can be modified to improve the thermal comfort in the city of Rome. The physical and geometrical properties of the buildings and the presence of green areas have a large impact on the urban climate and on thermal conditions of the people who use open spaces; it is obvious how the role of a urban planner is important to reduce the thermal stress and to design comfortable outdoor spaces for humans. In this study, several numerical simulations using ENVI-met have been performed to evaluate the impact of urban morphology on the microclimate within a city center in summer. Although some very hot conditions were recorded, there were evident examples of more acceptable comfort conditions and cooling potential for some orientations and degrees of urban compactness due to the clustered form with green cool islands and wind flow through the main canyons. Some design guidance on how to form urban passive cooling systems is presented.
Barrier Option Hedging under Constraints: A Viscosity Approach

We study the problem of finding the minimal initial capital needed in order to hedge without risk a barrier option when the vector of proportions of wealth invested in each risky asset is constrained to lie in a closed convex domain. In the context of a Brownian diffusion model, we provide a PDE characterization of the superhedging price. This extends the result of Broadie, Cvitanicg, and Soner [Rev. Financial Stud. , 11 (1998), pp. 59-79] and Cvitanicg, Pham, and Touzi [J. Appl. Probab. , 36 (1999), pp. 523-545] which was obtained for plain vanilla options and provides a natural numerical procedure for computing the corresponding superhedging price. As a by-product, we obtain a comparison theorem for a class of parabolic PDEs with relaxed Dirichlet conditions involving a constraint on the gradient.
Untargeted Metabolomic Analysis of Amniotic Fluid in the Prediction of Preterm Delivery and Bronchopulmonary Dysplasia

Objective Bronchopulmonary dysplasia (BPD) is a serious complication associated with preterm birth. A growing body of evidence suggests a role for prenatal factors in its pathogenesis. Metabolomics allows simultaneous characterization of low molecular weight compounds and may provide a picture of such a complex condition. The aim of this study was to evaluate whether an unbiased metabolomic analysis of amniotic fluid (AF) can be used to investigate the risk of spontaneous preterm delivery (PTD) and BPD development in the offspring. Study design We conducted an exploratory study on 32 infants born from mothers who had undergone an amniocentesis between 21 and 28 gestational weeks because of spontaneous preterm labor with intact membranes. The AF samples underwent untargeted metabolomic analysis using mass spectrometry combined with ultra-performance liquid chromatography. The data obtained were analyzed using multivariate and univariate statistical data analysis tools. Results Orthogonally Constrained Projection to Latent Structures-Discriminant Analysis (oCPLS2-DA) excluded effects on data modelling of crucial clinical variables. oCPLS2-DA was able to find unique differences in select metabolites between term (n = 11) and preterm (n = 13) deliveries (negative ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.65; positive ionization data set: R2 = 0.47, mean AUC ROC in prediction = 0.70), and between PTD followed by the development of BPD (n = 10), and PTD without BPD (n = 11) (negative data set: R2 = 0.48, mean AUC ROC in prediction = 0.73; positive data set: R2 = 0.55, mean AUC ROC in prediction = 0.71). Conclusions This study suggests that amniotic fluid metabolic profiling may be promising for identifying spontaneous preterm birth and fetuses at risk for developing BPD. These findings support the hypothesis that some prenatal metabolic dysregulations may play a key role in the pathogenesis of PTD and the development of BPD.
Chromosomal Genotype in Breast Cancer Progression: Comparison of Primary and Secondary Manifestations

The purpose of this study was to compare the chromosomal genotype between breast cancers with and without secondary manifestations and between primary tumors and their secondary manifestations. Eighty six breast cancers, twenty lymph node metastases, ten distant metastases and ten local recurrences were analyzed by comparative genomic hybridization. Tumors with local recurrences showed significant more frequent losses at 2q32 than the tumors without recurrences. Lymph node positive cases showed significant more frequent losses at 9p21 than node negative cases. Lymph node metastases exhibited significant more frequent losses at 7q11, 14q24.3–q31 and 17q22–q24 than their primary tumors. In cases with distant metastases, losses at 5q23 were more frequent than in those without, but not reaching the significance level. The distant metastases showed significant more frequent losses at 5p15, 12q24 and 17q22–q24 than the primary tumors. These results reveal strong evidence that the potential for progression is determined in the primary tumor and that different ways of the development of local recurrences, lymph node and distant metastases exist. After confirmation of the results by interphase FISH on tissue micro arrays, the detection of these specific chromosomal imbalances may contribute to a more individual prediction of prognosis in breast cancer.
University of Huddersfield Repository A comparison between the use of straight and curved beam elements for modelling curved railway tracks

A major environmental concern related to railway trafﬁc is vibration. A lot of research has been carried out to understand vibration of straight tracks, with less attention been paid to curved tracks. Modelling the dynamic behaviour of a curved railway track is important to understand the physics of generation and propagation of vibration from trains at non-straight sections of tracks. Modelling is also important to assess the current and any alternative track designs from an environmental point of view. In this paper a curved track is modelled and the effect of curvature is investigated. Two models have been developed and their results have been compared. In the ﬁrst, the curved track is modelled using straight beam elements. In the second curved beam elements are used. For both, the Euler-Bernoulli beam theory has been adopted to describe their bending behaviour. The elements have 12 degrees of freedom accounting for displacements and rotations in the lateral, transverse and longitudinal directions. The excitation comes from an axle traversing the rails with subcritical velocity, accounting for the wheel-rail contact forces. The described models are solved using the Finite Element Method. The time domain response of the versine of the curved track due to the passage of the axle is computed. A comparison is made on the efﬁciency of the two models for different curve radii and frequencies. The two models provide very similar results showing that the piecewise straight beam approximation represents the behaviour of the curved track accurately. Also the curved beam model used in this study shows some limitations for the speciﬁc
Potential biases in bug localization: do they matter?

Issue tracking systems are valuable resources during software maintenance activities and contain information about the issues faced during the development of a project as well as after its release. Many projects receive many reports of bugs and it is challenging for developers to manually debug and fix them. To mitigate this problem, past studies have proposed information retrieval (IR)-based bug localization techniques, which takes as input a textual description of a bug stored in an issue tracking system, and returns a list of potentially buggy source code files. These studies often evaluate their effectiveness on issue reports marked as bugs in issue tracking systems, using as ground truth the set of files that are modified in commits that fix each bug. However, there are a number of potential biases that can impact the validity of the results reported in these studies. First, issue reports marked as bugs might not be reports of bugs due to error in the reporting and classification process. Many issue reports are about documentation update, request for improvement, refactoring, code cleanups, etc. Second, bug reports might already explicitly specify the buggy program files and for these reports bug localization techniques are not needed. Third, files that get modified in commits that fix the bugs might not contain the bug. This study investigates the extent these potential biases affect the results of a bug localization technique and whether bug localization researchers need to consider these potential biases when evaluating their solutions. In this paper, we analyse issue reports from three different projects: HTTPClient, Jackrabbit, and Lucene-Java to examine the impact of above three biases on bug localization. Our results show that one of these biases significantly and substantially impacts bug localization results, while the other two biases have negligible or minor impact.
Commensal or pathogen – a challenge to fulfil Koch’s Postulates

ABSTRACT 1. Infectious diseases have a large impact on poultry health and economics. Elucidating the pathogenesis of a certain disease is crucial to implement control strategies. 2. Multiplication of a pathogen and its characterisation in vitro are basic requirements to perform experimental studies. However, passaging of the pathogen in vitro can influence the pathogenicity, a process targeted for live vaccine development, but limits the reproduction of clinical signs. 3. Numerous factors can influence the outcome of experimental infections with some importance on the pathogen, application route and host as exemplarily outlined for Histomonas meleagridis, Gallibacterium anatis and fowl aviadenoviruses (FAdVs). 4. In future, more comprehensive and detailed settings are needed to obtain as much information as possible from animal experiments. Processing of samples with modern diagnostic tools provides the option to closely monitor the host–pathogen interaction.
Ambient Air Pollutants Have Adverse Effects on Insulin and Glucose Homeostasis in Mexican Americans

OBJECTIVE Recent studies suggest that air pollution plays a role in type 2 diabetes (T2D) incidence and mortality. The underlying physiological mechanisms have yet to be established. We hypothesized that air pollution adversely affects insulin sensitivity and secretion and serum lipid levels. RESEARCH DESIGN AND METHODS Participants were selected from BetaGene (n = 1,023), a study of insulin resistance and pancreatic β-cell function in Mexican Americans. All participants underwent DXA and oral and intravenous glucose tolerance tests and completed dietary and physical activity questionnaires. Ambient air pollutant concentrations (NO2, O3, and PM2.5) for short- and long-term periods were assigned by spatial interpolation (maximum interpolation radius of 50 km) of data from air quality monitors. Traffic-related air pollution from freeways (TRAP) was estimated using the dispersion model as NOx. Variance component models were used to analyze individual and multiple air pollutant associations with metabolic traits. RESULTS Short-term (up to 58 days cumulative lagged averages) exposure to PM2.5 was associated with lower insulin sensitivity and HDL-to-LDL cholesterol ratio and higher fasting glucose and insulin, HOMA-IR, total cholesterol, and LDL cholesterol (LDL-C) (all P ≤ 0.036). Annual average PM2.5 was associated with higher fasting glucose, HOMA-IR, and LDL-C (P ≤ 0.043). The effects of short-term PM2.5 exposure on insulin sensitivity were largest among obese participants. No statistically significant associations were found between TRAP and metabolic outcomes. CONCLUSIONS Exposure to ambient air pollutants adversely affects glucose tolerance, insulin sensitivity, and blood lipid concentrations. Our findings suggest that ambient air pollutants may contribute to the pathophysiology in the development of T2D and related sequelae.
Association Mapping of Biomass Yield and Stem Composition in a Tetraploid Alfalfa Breeding Population

Alfalfa (Medicago sativa L.), an important forage crop that is also a potential biofuel crop, has advantages of high yield, high lignocellulose concentration in stems, and has low input costs. In this study, we investigated population structure and linkage disequilibrium (LD) patterns in a tetraploid alfalfa breeding population using genome‐wide simple sequence repeat (SSR) markers and identified markers related to yield and cell wall composition by association mapping. No obvious population structure was found in our alfalfa breeding population, which could be due to the relatively narrow genetic base of the founders and/or due to two generations of random mating. We found significant LD (p < 0.001) between 61.5% of SSR marker pairs separated by less than 1 Mbp. The observed large extent of LD could be explained by the effect of bottlenecking and selection or the high mutation rates of SSR markers. Total marker heterozygosity was positively related to biomass yield in each of five environments, but no relationship was noted for stem composition traits. Of a total of 312 nonrare (frequency >10%) alleles across the 71 SSR markers, 15 showed strong association (p < 0.005) with yield in at least one of five environments, and most of the 15 alleles were identified in multiple environments. Only one allele showed strong association with acid detergent fiber (ADF) and one allele with acid detergent lignin (ADL). Alleles associated with traits could be directly applied in a breeding program using marker‐assisted selection. However, based on our estimated LD level, we would need about 1000 markers to explore the whole alfalfa genome for association between markers and traits.
EWOM and brand awareness impact on consumer purchase intention: mediating role of brand image

: The basic purpose of this research is to analyze the impact of electronic word of mouth (eWOM) and brand awareness on customer purchase intention with the mediating role of brand image. The research is conducted to analyze the full or partial role of mediator on the said relationship. This research is basically conducted on customers of mobile users of Rawalpindi and Islamabad. To check this relationship a total of 300 questionnaires were floated in four universities of twin cities, of which 262 questionnaires with a response rate of 87.33% were received back on which mediation analysis has been performed. The results show full mediating impact of brand image on Electronic Word of Mouth (eWOM) and customer purchase intention relationship, while partial mediating role of brand image on relationship of brand awareness and customer purchase intention has been observed. This research will help marketers in implementing better marketing techniques for boosting customers purchase intention.
Protective and Harmful Effects of Religious Practice on Depression Among Jewish Individuals With Mood Disorders

Research suggests that religious practice has a small but consistent inverse relationship with depression, but recent work within the Jewish population has been equivocal. Following the behavioral model of depression, one explanation is that religious activity may provide positive reinforcement. We hypothesized that this would be true only for those who intrinsically value religion, and conversely, religious practice may be depressogenic for individuals lacking intrinsic motivation. We tested this possibility in a longitudinal sample of 160 Jewish individuals meeting DSM–IV criteria for a mood disorder. Multilevel autoregressive growth modeling suggested that controlling for past depressive symptoms, past intrinsic religiosity, and religious practice jointly predicted future depression. Individuals with high religious practice and high intrinsic religiosity reported lower future depressive symptoms, whereas those with high practice and low intrinsic religiosity reported higher depressive symptoms. These findings suggest that religious practice can have both protective and harmful effects, depending on internal values.
2 Evidence-Based Complementary and Alternative Medicine a key

1 Department of Physical Medicine and Rehabilitation, China Medical University Hospital, Taichung 40447, Taiwan 2 School of Chinese Medicine, College of Chinese Medicine, China Medical University, No. 91 Hsueh-Shih Road, Taichung 40402, Taiwan 3 Department of Physical Medicine and Rehabilitation, Yangming Branch, Taipei City Hospital, Taipei 11146, Taiwan 4 Department of Physical Therapy and Assistive Technology, National Yang-Ming University, Taipei 11221, Taiwan
Study on interaction between entropy pruning and kneser-ney smoothing

The paper presents an in-depth analysis of a less known interaction between Kneser-Ney smoothing and entropy pruning that leads to severe degradation in language model performance under aggressive pruning regimes. Experiments in a data-rich setup such as google.com voice search show a significant impact in WER as well: pruning Kneser-Ney and Katz models to 0.1% of their original impacts speech recognition accuracy significantly, approx. 10% relative.
Airborne observations of IEPOX-derived isoprene SOA in the Amazon during SAMBBA

Abstract. Isoprene is a potentially highly significant but currently poorly quantified source of secondary organic aerosols (SOA). This is especially important in the tropics, where large rainforests act as significant sources of isoprene. Methylfuran, produced through thermal decomposition during analysis, has recently been suggested as a marker for isoprene SOA formation through the isoprene epoxydiol (IEPOX) route, which mostly occurs under low NOx conditions. This is manifested as a peak at m/z=82 in Aerodyne Aerosol Mass Spectrometer (AMS) data. Here we present a study of this marker measured during five flights over the Amazon rainforest on board the UK Facility for Airborne Atmospheric Measurement (FAAM) BAe-146 research aircraft during the South American Biomass Burning Analysis (SAMBBA) campaign. Cases where this marker is and is not present are contrasted and linked to the presence of acidic seed particles, lower NOx concentrations and higher humidities. There are also data to suggest a role of organic nitrogen in the particulate composition. Furthermore, an inspection of the vertical trends of the marker indicates that concentrations are highest at the top of the boundary layer (possibly due to semivolatile repartitioning) and that upwards through the free troposphere, the mass spectral profile evolves towards that of low volatility oxygenated aerosol. These observations offer insights into the behaviour of IEPOX-derived SOA formation above the Amazon rainforest and the suitability of methylfuran as a marker for this process.
Development of a systematic methodology of fuzzy logic modeling

This paper proposes a systematic methodology of fuzzy logic modeling for complex system modeling. It has a unified parameterized reasoning formulation, an improved fuzzy clustering algorithm, and an efficient strategy of selecting significant system inputs and their membership functions. The reasoning mechanism introduces 4 parameters whose variation provides a continuous range of inference operation. As a result, we are no longer restricted to standard extremes in any step of reasoning. The fuzzy model itself can then adjust the reasoning process by optimizing the inference parameters based on input-output data. The fuzzy rules are generated through fuzzy c-means (FCM) clustering. Major bottlenecks are addressed and analytical solutions are suggested. We also address the classification process to extend the derived fuzzy partition to the entire output space. In order to select suitable input variables among a finite number of candidates (unlike traditional approaches) we suggest a new strategy through which dominant input parameters are assigned in one step and no iteration process is required. Furthermore, a clustering technique called fuzzy fine clustering is introduced to assign the input membership functions. In order to evaluate the proposed methodology, two examples-a nonlinear function and a gas furnace dynamic procedure-are investigated in detail. The significant improvement of the model is concluded compared to other fuzzy modeling approaches.