Miracle-dz/UniFAR-FTUs huggingface dataset:
Will Morality or Political Ideology Determine Attitudes to Climate Change

Climate change is a major moral and political challenge facing Australia. Public attitudes to the issue influence public policy in respect of responding to climate change. Using Moral Foundations theory, this study investigated the relationship between attitudes to climate change, individuals’ moral intuitions and political affinity, using a sample of 487 Australian adults between the ages of 18 and 86 years. Patterns of moral intuitions scores which are higher for harm and fairness and lower for in-group, authority or purity, correlated with liberalism and self-reported left-wing political orientation, and predicted a preference for a strong response to climate change irrespective of self-interest. Patterns of moral intuitions scores, which focus more equally on all five foundations, correlated with conservatism and self-reported rightwing political orientation, and predicted a preference for a reduced response. Specifically, intuitions concerned with harm and fairness were predictive of preference for stronger responses, whereas those concerned with loyalty to in-group were the opposite. Overall, moral intuitions predicted attitudes to response to climate change, but the relationship was partially mediated by political affinity. The study is further evidence of the relevance of Moral Foundations Theory to moral issues, particularly those requiring a political response. Climate change is currently prominent
YMD: a microarray database for large-scale gene expression analysis

The use of microarray technology to perform parallel analysis of the expression pattern of a large number of genes in a single experiment has created a new frontier of medical research. The vast amount of gene expression data generated from multiple microarray experiments requires a robust database system that allows efficient data storage, retrieval, secure access, data dissemination, and integrated data analyses. To address the growing needs of microarray researchers at Yale and their collaborators, we have built the Yale Microarray Database (YMD). YMD is Web-accessible with the following features: (i) a Web program that tracks DNA samples between source plates and arrays, (ii) the capability of finding common genes/clones across different array platforms, (iii) an image file server, (iv) laboratory-based user management and access privileges, (v) project management, (vi) template data entry, (vii) linking gene expression data to annotation databases for functional analysis. YMD is currently being used on a pilot basis by several laboratories for different organisms and array platforms.
Noncommutative Electrodynamics

In this paper we deﬁne a causal Lorentz covariant noncommutative (NC) classical Electrodynamics. We obtain an explicit realization of the NC theory by solving perturbatively the Seiberg-Witten map. The action is polynomial in the ﬁeld strenght F , allowing to preserve both causality and Lorentz covariance. The general structure of the Lagrangian is studied, to all orders in the perturbative expansion in the NC parameter θ . We show that monochromatic plane waves are solutions of the equations of motion to all orders. An iterative method has been developed to solve the equations of motion and has been applied to the study of the corrections to the superposition law and to the Coulomb law.
Perfusion index derived from a pulse oximeter can predict the incidence of hypotension during spinal anaesthesia for Caesarean delivery.

BACKGROUND Hypotension during spinal anaesthesia for Caesarean delivery is a result of decreased vascular resistance due to sympathetic blockade and decreased cardiac output due to blood pooling in blocked areas of the body. Change in baseline peripheral vascular tone due to pregnancy may affect the degree of such hypotension. The perfusion index (PI) derived from a pulse oximeter has been used for assessing peripheral perfusion dynamics due to changes in peripheral vascular tone. The aim of this study was to examine whether baseline PI could predict the incidence of spinal anaesthesia-induced hypotension during Caesarean delivery. METHODS Parturients undergoing elective Caesarean delivery under spinal anaesthesia with hyperbaric bupivacaine 10 mg and fentanyl 20 μg were enrolled in this prospective study. The correlation between baseline PI and the degree of hypotension during spinal anaesthesia and also the predictability of spinal anaesthesia-induced hypotension during Caesarean delivery by PI were investigated. RESULTS Baseline PI correlated with the degree of decreases in systolic and mean arterial pressure (r=0.664, P<0.0001 and r=0.491, P=0.0029, respectively). The cut-off PI value of 3.5 identified parturients at risk for spinal anaesthesia-induced hypotension with a sensitivity of 81% and a specificity of 86% (P<0.001). The change of PI in parturients with baseline PI ≤ 3.5 was not significant during the observational period, while PI in parturients with baseline PI>3.5 demonstrated marked decreases after spinal injection. CONCLUSIONS We demonstrated that higher baseline PI was associated with profound hypotension and that baseline PI could predict the incidence of spinal anaesthesia-induced hypotension during Caesarean delivery.
Quinolone resistance and ornithine decarboxylation activity in lactose-negative Escherichia coli

Quinolones and fluoroquinolones are widely used to treat uropathogenic Escherichia coli infections. Bacterial resistance to these antimicrobials primarily involves mutations in gyrA and parC genes. To date, no studies have examined the potential relationship between biochemical characteristics and quinolone resistance in uropathogenic E. coli strains. The present work analyzed the quinolone sensitivity and biochemical activities of fifty-eight lactose-negative uropathogenic E. coli strains. A high percentage of the isolates (48.3%) was found to be resistant to at least one of the tested quinolones, and DNA sequencing revealed quinolone resistant determining region gyrA and parC mutations in the multi-resistant isolates. Statistical analyses suggested that the lack of ornithine decarboxylase (ODC) activity is correlated with quinolone resistance. Despite the low number of isolates examined, this is the first study correlating these characteristics in lactose-negative E. coli isolates.
Effects of Gadolinium Contrast Agent Administration on Automatic Brain Tissue Classification of Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE: The administration of gadolinium contrast agent is a common part of MR imaging examinations in patients with MS. The presence of gadolinium may affect the outcome of automated tissue classification. The purpose of this study was to investigate the effects of the presence of gadolinium on the automatic segmentation in patients with MS by using the synthetic tissue-mapping method. MATERIALS AND METHODS: A cohort of 20 patients with clinically definite multiple sclerosis were recruited, and the T1 and T2 relaxation times and proton density were simultaneously quantified before and after the administration of gadolinium. Synthetic tissue-mapping was used to measure white matter, gray matter, CSF, brain parenchymal, and intracranial volumes. For comparison, 20 matched controls were measured twice, without gadolinium. RESULTS: No differences were observed for the control group between the 2 measurements. For the MS group, significant changes were observed pre- and post-gadolinium in intracranial volume (−13 mL, P < .005) and cerebrospinal fluid volume (−16 mL, P < .005) and the remaining, unclassified non-WM/GM/CSF tissue volume within the intracranial volume (+8 mL, P < .05). The changes in the patient group were much smaller than the differences, compared with the controls, which were −129 mL for WM volume, −22 mL for GM volume, +91 mL for CSF volume, 24 mL for the remaining, unclassified non-WM/GM/CSF tissue volume within the intracranial volume, and −126 mL for brain parenchymal volume. No significant differences were observed for linear regression values against age and Expanded Disability Status Scale. CONCLUSIONS: The administration of gadolinium contrast agent had a significant effect on automatic brain-tissue classification in patients with MS by using synthetic tissue-mapping. The observed differences, however, were much smaller than the group differences between MS and controls.
A Multi-Element Approach to Location Inference of Twitter: A Case for Emergency Response

Since its inception, Twitter has played a major role in real-world events—especially in the aftermath of disasters and catastrophic incidents, and has been increasingly becoming the first point of contact for users wishing to provide or seek information about such situations. The use of Twitter in emergency response and disaster management opens up avenues of research concerning different aspects of Twitter data quality, usefulness and credibility. A real challenge that has attracted substantial attention in the Twitter research community exists in the location inference of twitter data. Considering that less than 2% of tweets are geotagged, finding location inference methods that can go beyond the geotagging capability is undoubtedly the priority research area. This is especially true in terms of emergency response, where spatial aspects of information play an important role. This paper introduces a multi-elemental location inference method that puts the geotagging aside and tries to predict the location of tweets by exploiting the other inherently attached data elements. In this regard, textual content, users’ profile location and place labelling, as the main location-related elements, are taken into account. Location-name classes in three granularity levels are defined and employed to look up the location references from the location-associated elements. The inferred location of the finest granular level is assigned to a tweet, based on a novel location assignment rule. The location assigned by the location inference process is considered to be the inferred location of a tweet, and is compared with the geotagged coordinates as the ground truth of the study. The results show that this method is able to successfully infer the location of 87% of the tweets at the average distance error of 12.2 km and the median distance error of 4.5 km, which is a significant improvement compared with that of the current methods that can predict the location with much larger distance errors or at a city-level resolution at best.
Differences in Job Satisfaction Between General Education and Special Education Teachers

The occupational field of special education has been particularly vulnerable to losing its well-trained professional staff. Academic preparation and training of these teachers is costly and time-consuming, and replacing them is difficult. The present study compared the satisfactions and dissatisfactions of teachers of emotionally/behaviorally impaired students in special education, teachers of students in general education, and teachers responsible for both groups of students. Teachers of students in special education programs were found to be the most dissatisfied. Specific stresses and frustrations, both from within and from outside the classroom, were found to be associated with the dissatisfaction. The difficulties were particularly common in younger, less experienced special education teachers. The implications of these findings are discussed, and recommendations aimed at improving job satisfaction for special education teachers are presented.
Impact of two sessions of mindfulness training on attention

of a dissertation at the University of Miami. The effect on two sessions of mindfulness training on attentional efficiency was examined. 150 novice meditators were randomly assigned to mindfulness training, relaxation training, or a neutral task and were tested before and after participation. They were evaluated with performance measures of attentional efficiency and short-term memory as well as self-report measures of mindfulness and affect. Results indicated that mindfulness training was not related to better performance on any attention measure or a verbal memory measure as compared to relaxation and control groups. Possible reasons for the failure to find attentional benefits are explored and directions for future research are discussed.
Waddlia chondrophila induces systemic infection, organ pathology, and elicits Th1-associated humoral immunity in a murine model of genital infection

Waddlia chondrophila is a known bovine abortigenic Chlamydia-related bacterium that has been associated with adverse pregnancy outcomes in human. However, there is a lack of knowledge regarding how W. chondrophila infection spreads, its ability to elicit an immune response and induce pathology. A murine model of genital infection was developed to investigate the pathogenicity and immune response associated with a W. chondrophila infection. Genital inoculation of the bacterial agent resulted in a dose-dependent infection that spread to lumbar lymph nodes and successively to spleen and liver. Bacterial-induced pathology peaked on day 14, characterized by leukocyte infiltration (uterine horn, liver, and spleen), necrosis (liver) and extramedullary hematopoiesis (spleen). Immunohistochemistry demonstrated the presence of a large number of W. chondrophila in the spleen on day 14. Robust IgG titers were detected by day 14 and remained high until day 52. IgG isotypes consisted of high IgG2a, moderate IgG3 and no detectable IgG1, indicating a Th1-associated immune response. This study provides the first evidence that W. chondrophila genital infection is capable of inducing a systemic infection that spreads to major organs, induces uterus, spleen, and liver pathology and elicits a Th1-skewed humoral response. This new animal model will help our understanding of the mechanisms related to intracellular bacteria-induced miscarriages, the most frequent complication of pregnancy that affects one in four women.
BNT STRUCTURE LEARNING PACKAGE : Documentation and Experiments

Bayesian networks are a formalism for probabilistic reasoning that have grown increasingly popular for tasks such as classification in data-mining. In some situations, the structure of the Bayesian network can be given by an expert. If not, retrieving it automatically from a database of cases is a NP-hard problem; notably because of the complexity of the search space. In the last decade, numerous methods have been introduced to learn the network’s structure automatically, by simplifying the search space or by using an heuristic in the search space. Most methods deal with completely observed data, but some can deal with incomplete data. The Bayes Net Toolbox for Matlab, introduced by Murphy (2004), offers functions for both using and learning Bayesian Networks. But this toolbox is not ’state of the art’ as regards structural learning methods. This is why we propose the SLP package.
β-Catenin Regulates Acetylcholine Receptor Clustering in Muscle Cells through Interaction with Rapsyn

Agrin is believed to be a factor used by motoneurons to direct acetylcholine receptor (AChR) clustering at the neuromuscular junction. However, exactly how agrin mediates this effect remains unclear. Here we demonstrate that the β-catenin interacts with rapsyn, a molecule key for AChR clustering. Agrin stimulation increases the association of β-catenin with surface AChRs. Suppression of β-catenin expression inhibited agrin-induced AChR clustering, suggesting a necessary role of β-catenin in this event. The β-catenin action did not appear to require the function of T-cell factors (TCFs), suggesting a mechanism independent of TCF-mediated transcription. In contrast, prevention of β-catenin from interacting with α-catenin attenuated agrin-induced AChR clustering. These results suggest that β-catenin may serve as a link between AChRs and α-catenin-associated cytoskeleton, revealing a novel function of β-catenin in synaptogenesis.
Biodiversity and ecosystem functioning

This chapter examines the relationship between biodiversity (most often measured as species richness) and the functioning of ecosystems. Examined in detail are the effects of biodiversity on: ecosystem productivity, nutrient use and nutrient retention, community and ecosystem stability, and invasibility by exotic species. A careful look, over two decades, at experimental results and meta-analyses confirms the positive impact of species richness on productivity, ecosystem stability, and nutrient retention. Thus, we can confidently conclude that biodiversity matters to the healthy functioning of ecosystems, although we do not yet know how many species are needed to ensure the successful functioning of any given ecosystem. The chapter concludes with a discussion of six important, but unanswered question in the study of biodiversity and ecosystem functioning.
Building bridges

This article explores how universities and industry can work together to improve access to graduate opportunities for disadvantaged students. Focusing on an initiative which involved students from a ‘post-1992’ UK university experiencing London’s legal sector, the article analyses the factors that contributed to the students’ perceptions of their increased self-efficacy as a result of participating in the event. Using a focus group methodology, the authors critically examine the barriers that can be imposed by students’ socio-economic backgrounds, which may prevent such initiatives from having a meaningful impact on diverse recruitment and fair access to the higher professional occupations. Concentrating on two strands of the Triple Helix model, the authors also make recommendations for building more effective bridges between universities and industry to improve access to the elite professions.
Ethanol modulation of mammalian BK channels in excitable tissues: molecular targets and their possible contribution to alcohol-induced altered behavior

In most tissues, the function of Ca2+- and voltage-gated K+ (BK) channels is modified in response to ethanol concentrations reached in human blood during alcohol intoxication. In general, modification of BK current from ethanol-naïve preparations in response to brief ethanol exposure results from changes in channel open probability without modification of unitary conductance or change in BK protein levels in the membrane. Protracted and/or repeated ethanol exposure, however, may evoke changes in BK expression. The final ethanol effect on BK open probability leading to either BK current potentiation or BK current reduction is determined by an orchestration of molecular factors, including levels of activating ligand (Ca2+i), BK subunit composition and post-translational modifications, and the channel's lipid microenvironment. These factors seem to allosterically regulate a direct interaction between ethanol and a recognition pocket of discrete dimensions recently mapped to the channel-forming (slo1) subunit. Type of ethanol exposure also plays a role in the final BK response to the drug: in several central nervous system regions (e.g., striatum, primary sensory neurons, and supraoptic nucleus), acute exposure to ethanol reduces neuronal excitability by enhancing BK activity. In contrast, protracted or repetitive ethanol administration may alter BK subunit composition and membrane expression, rendering the BK complex insensitive to further ethanol exposure. In neurohypophyseal axon terminals, ethanol potentiation of BK channel activity leads to a reduction in neuropeptide release. In vascular smooth muscle, however, ethanol inhibition of BK current leads to cell contraction and vascular constriction.
Portable Execution Time Analysis for RISC Processors

The knowledge of a task’s worst case execution time (WCET) is required for scheduling real-time tasks. Existing execution time analyzers are machine dependent and this is a serious problem as architectures evolve rapidly. In this paper, we present a tool for portable execution time analysis for RISC processors. This tool generates an execution time analyzer for any RISC processor. The analyzer takes into account the effect of the hardware’s pipeline when calculating the execution time, thereby making possible accurate results, depending on the precision with which developers model the underlying architecture.
Genetic Relationship of Productive Life, Production and Type Traits of Korean Holsteins at Early Lactations

The present study was performed to study the genetic relationship of productive life with production and type traits of Korean Holsteins at first three lactations. The data for the analysis from 56,054, 28,997, and 11,816 animals of first, second and third parity cows which were born from 2006 to 2011 were collected by Dairy Cattle Improvement Center, National Agricultural Co-operative Federation. Milk, protein and fat yields adjusted for 305 days and average somatic cell score considered as production traits and analyzed type traits were stature, strength, body depth, dairy form, rump angle, rump width, rear leg side view, foot angle, front attachment placement, rear attachment height, rear attachment width, udder cleft, udder depth, front teat placement and front teat length. A multi trait genetic analysis was performed using Wombat program with restricted maximum likelihood animal model composed of fixed effect of birth year, farm and the random effect of animal and random residual effect according to the traits. Heritability estimates of productive life were between 0.06 and 0.13. Genetic and phenotypic correlations between production and productive life traits ranged from 0.35 to 0.04 for milk, 0.16 to 0.05 for protein and 0.18 to 0.02 f 15-0034 (2nd) 150520 or fat. Somatic cells score showed a negative genetic and phenotypic correlation with productive life and also udder type traits, indicating that the selection for higher udder traits will likely to improve resistance to mastitis and persistence in the herd. Among all dairy form type traits, udder characters such as udder cleft showed a significant relationship with productive life. However, a specific change of heritabilities or correlations were not observed with the change of parity. Moreover, further studies are needed to further confirm the significance of the above traits and the effect of parity on above relationships in order to minimize both voluntary and involuntary culling rates while improving herd health and maintaining high yielding dairy cows.
Up Against The Wall: The Effects of Climate Warming on Soil Microbial Diversity and The Potential for Feedbacks to The Carbon Cycle

Earth’s climate is warming, and there is evidence that increased temperature alters soil C cycling, which may result in a self-reinforcing (positive), microbial mediated feedback to the climate system. Though soil microbes are major drivers of soil C cycling, we lack an understanding of how temperature affects SOM decomposition. Numerous studies have explored, to differing degrees, the extent to which climate change may affect biodiversity. While there is ample evidence that community diversity begets ecosystem stability and resilience, we know of keystone species that perform functions whose effects far outweigh their relative abundance. In this paper, we first review the meaning of microbial diversity and how it relates to ecosystem function, then conduct a literature review of field-based climate warming studies that have made some measure of microbial diversity. Finally, we explore how measures of diversity may yield a larger, more complete picture of climate warming effects on microbial communities, and how this may translate to altered carbon cycling and greenhouse gas emissions. While warming effects seem to be ecosystem-specific, the lack of observable consistency between measures is due in some part to the diversity in measures of microbial diversity.