Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the impact of submarine frontal melting and ice mélange on glacier dynamics

Abstract. Submarine melting of the calving face of tidewater glaciers and the mechanical back force applied by the ice melange layer are two mechanisms generally proposed to explain seasonal variations at the calving front of tidewater glaciers. However, the way these processes affect the calving rate and glacier dynamics remains uncertain. In this study, we used a finite element-based model that solves the full Stokes equations to simulate the impact of these forcings on two-dimensional theoretical flow line glacier configurations. The model, which includes calving processes, suggests that frontal melting affects the position of the terminus only slightly (less than a few hundred metres) and does not affect the multiannual glacier mass balance at all. However, the ice melange has a greater impact on the advance and retreat cycles of the glacier front (more than several kilometres) and its consequences for the mass balance are not completely negligible, stressing the need for better characterization of forcing properties. We also show that ice melange forcing against the calving face can mechanically prevent crevasse propagation at sea level and hence prevent calving. Results also reveal different behaviours in grounded and floating glaciers: in the case of a floating extension, the strongest forcings can disrupt the glacier equilibrium by modifying its buttressing and ice flux at the grounding line.
Political Extremity, Social Media Use, Social Support, and Well-Being for Emerging Adults During the 2016 Presidential Election Campaign

The 2016 U.S. presidential election was marked by hostile political discourse, often on social media, where users were exposed to divergent, and potentially distressing, political discourse. This research explores the effects of this election on the well-being of emerging adults who receive the majority of their news via social media. Using data from the Emerging Adulthood Measured at Multiple Institutions 2 Study, we expected greater social media use to be associated with greater perceived stress, and lower well-being, among emerging adults who are more politically extreme, and expected these relationships would be moderated by social support and social media use. Our preregistered analysis did not support our hypotheses. Although there were some effects of extremity on stress and well-being, overall the direction of the effects were inconsistent and neither social media use nor social support was found to moderate the effects of extremity on stress and well-being.
Assessment of Surface Water Quality Using Principle Component Analysis and Factor Analysis

This research was carried out using multivariate statistical techniques for analyzing the quality of water and monitoring the variables affecting its quality in Gharasou river, in Ardabil province in northwest of Iran. During a year, 28 physical and chemical parameters were sampled in 11 stations. Results of these measurements were analyzed by multivariate procedures such as Principal Component Analysis (PCA), Factor Analysis (FA) and Discriminant Analysis (DA). The amount of pollutants resulting from the PCA showed that the three first components accounted for %78 percent of differences altogether, the first component accounting for 51.6, the second for 14.2 and the third for 12.2 percent of contribution, respectively. The values of coefficients calculated for the first and second components show the degree to which the places are susceptible to pollution. These values also showed that the main reason for the differences among stations’ pollution level, in different periods, is the amount of parameters like NO , NH , Na, TDS, EC, Mg , 3 3 2+ Turb. , PO , WT, COD, BOD, SO , Fe, Ca and diazinon pesticide compared to other parameters. The results 4 4 322+ of this analysis distinguished the stations as did CA. DA showed that NH Ca , Mg , EC parameters and 3, 2+ 2+ diazinon had the utmost importance in grouping the stations. The first two functions of DA accounted for 100% of changes. Therefore, DA allowed a reduction in the dimensionality of large data set, delineating a few indicator parameters responsible for large variation in water quality. This, in addition, confirmed that the model resulting from multi-linear regression analysis of the main component is a good indicator of each source or factor’s loading in the distribution of pollution in the river. Thus, this study illustrated the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets and in water quality assessment, identification of pollution sources/factors and understanding spatial variations in water quality for effective river water quality management. This study also showed the effectiveness of these techniques for getting better information about the water quality and design of monitoring network for effective management of water resources.
Pilot Study of Urinary Biomarkers of Phytoestrogens, Phthalates, and Phenols in Girls

Background Hormonally active environmental agents have been measured among U.S. children using exposure biomarkers in urine. However, little is known about their variation by race, age, sex, and geography, and no data exist for newly developed biomarkers. Objective Our goal was to characterize relevant, prevalent exposures for a study of female pubertal development. Methods In a pilot study among 90 girls from New York City, New York, Cincinnati, Ohio, and northern California, we measured 25 urinary analytes representing 22 separate agents from three chemical families: phytoestrogens, phthalates, and phenols. Exposures occur chiefly from the diet and from household or personal care products. Results Participants represented four racial/ethnic groups (Asian, black, Hispanic, white), with mean age of 7.77 years. Most analytes were detectable in > 94% of samples. The highest median concentrations for individual analytes in each family were for enterolactone (298 μg/L), monoethylphthalate (MEP; 83.2 μg/L), and benzophenone-3 (BP3; 14.7 μg/L). Few or no data have been reported previously for four metabolites: mono(2-ethyl-5-carboxypentyl) phthalate, triclosan, bisphenol A (BPA), and BP3; these were detected in 67–100% of samples with medians of 1.8–53.2 μg/L. After multivariate adjustment, two analytes, enterolactone and BPA, were higher among girls with body mass index < 85th reference percentile than those at or above the 85th percentile. Three phthalate metabolites differed by race/ethnicity [MEP, mono(2-ethylhexyl) phthalate, and mono-3-carboxypropylphthalate]. Conclusions A wide spectrum of hormonally active exposure biomarkers were detectable and variable among young girls, with high maximal concentrations (> 1,000 μg/L) found for several analytes. They varied by characteristics that may be relevant to development.
The Production of Fungal Mannanase, Cellulase and Xylanase Using Palm Kernel Meal as a Substrate

Extracellular enzymes including mannanase, cellulase and xylanase from Aspergillus wentii TISTR 3075, Aspergillus niger, Aspergillus oryzae, Trichoderma reesei TISTR 3080 and Penicillium sp. were investigated. The enzymes were produced in solid-state fermentation using palm kernel meal (PKM) as a substrate. All fungal strains produced mainly mannanase. A maximum activity of 24.9 U/g koji was observed in A. wentii TISTR 3075 with a specific activity of 1.5 U/mg protein. During PKM fermentation, there was also found low concomitantly of cellulase and xylanase activities with high mannanase activity in all strains. The degradation of non-starch polysaccharides (NSPs) in PKM by these fungal strains was indicated by the increased mannanase, cellulase and xylanase activities which correlated with the increase in reducing sugar content and pH profiles during PKM fermentation. PKM was shown to be more suitable for production of mannanase than cellulase and xylanase for all strains because of the high content of mannan as an inducer in PKM. Increases in enzyme yield might be obtained by optimizing the culture conditions.
Pruning of Random Forest classifiers: A survey and future directions

Random Forest is an ensemble supervised machine learning technique. Based on bagging and random feature selection, number of decision trees (base classifiers) is generated and majority voting is taken for classification. For effective learning and classification of Random Forest, there is need for reducing number of trees (Pruning) in Random Forest. We have presented here systematic survey of pruning efforts of Random Forest classifier along with the required theoretical background. Most of the work for pruning takes static approach while recently dynamic pruning is being targeted. We have also generated a Comparison Chart by taking relevant parameters. There is research scope for analyzing behavior of Random forest, generating accurate and diverse base decision trees, truly dynamic pruning algorithm for Random Forest classifier, and generating optimal subset of Random forest.
The role of cardiac registries in evidence-based medicine.

Cardiovascular disease remains the primary cause of mortality, and a major cause of disability in the developed world.1 This significant burden necessitates ongoing improvements in patient management, to minimize the impact of cardiovascular conditions on both patients and healthcare systems. These improvements in cardiovascular care are promoted by an evidence-based approach, shaped by comprehensive clinical guidelines. The scientific basis of recommendations is an important feature of clinical guidelines, and influences the degree to which they are followed in clinical practice.2 Recent studies have assigned the highest evidence grading to randomized controlled trials (RCTs) that are clinically important, and representative of the clinical population covered by the guideline recommendation.3 For example, this highest grading was assigned to a recommendation based on a meta-analysis of RCTs showing low-dose diuretics to be the most effective first-line treatment for cardiovascular event prevention in hypertensive patients. This study reviewed data from 42 RCTs which were, crucially, representative of the population that the recommendation was made for (i.e. hypertensive patients). 3,4 The importance of the applicability of evidence to recommendations highlights the need to consider evidence from clinically relevant situations, not all of which have been assessed by RCTs. This evidence can originate from expert consensus, as well as non-randomized prospective studies. Although generally providing a lower evidence-level than RCTs,3,5 observational studies can make an important contribution to the evidence base when the study outcomes are clinically important, and the populations involved are representative. Indeed, information from several registries was considered in the recent American Heart Association Acute Coronary Care in the Elderly Scientific Statement.6 Non-randomized prospective registries document the treatment and outcomes for consecutive patients in clinical practice. Therefore, data are gained from a ‘real-world’ selection of patients, many of whom would be excluded from RCTs, …
The Influence of Big Five Personality Traits on Dual-Process Cognitive Information Processing Styles in Medical Decision-Making

We all make decisions, but when medical professionals do it, it can literally mean life or death. Decisions are influenced by many factors. The aim of the present study was to investigate if personality traits as proposed by the Big Five Model influence the Rational and Experiential cognitive information processing styles as proposed by the dual-process Cognitive-Experiential Self-Theory theory in medical decision-making. A sample of doctors and nurses (N=102) from various medical institutions in Macedonia was presented with an online survey containing Big Five Factors Inventory (Goldberg, 1992) and REI-40 (Paccini & Epstain, 1999). The results showed significant relation for Openness and Conscientiousness with Rationality and Agreeableness with Experientiality. Neuroticism showed significant positive influence on one of the sub-dimensions of Rationality, the Rational Ability, but not on Rationality in total. The medical professionals demonstrated clear preference towards Rationality over Experientiality. The importance of these results is further discussed in context of somewhat similar research.
Dynamics of neuronal firing correlation: modulation of "effective connectivity".

1. We reexamine the possibilities for analyzing and interpreting the time course of correlation in spike trains simultaneously and separably recorded from two neurons. 2. We develop procedures to quantify and properly normalize the classical joint peristimulus time scatter diagram. These allow separation of the "raw" correlation into components caused by direct stimulus modulations of the single-neuron firing rates and those caused by various types of interaction between the two neurons. 3. A newly developed significance test ("surprise") is applied to evaluate such inferences. 4. Application of the new procedures to simulated spike trains allowed the recovery of the known circuitry. In particular, it proved possible to recover fast stimulus-locked modulations of "effective connectivity," even if they were masked by strong direct stimulus modulations of individual firing rates. These procedures thus present a clearly superior alternative to the commonly used "shift predictor. " 5. Adopting a model-based approach, we generalize the classical measures for quantifying a direct interneuronal connection ("efficacy" and "contribution") to include possible stimulus-locked time variations. 6. Application of the new procedures to real spike trains from several different preparations showed that fast stimulus-locked modulations of "effective connectivity" also occur for real neurons.
Response-Based Approachability and its Application to Generalized No-Regret Algorithms

Approachability theory, introduced by Blackwell (1956), provides fundamental results on repeated games with vector-valued payoffs, and has been usefully applied since in the theory of learning in games and to learning algorithms in the online adversarial setup. Given a repeated game with vector payoffs, a target set $S$ is approachable by a certain player (the agent) if he can ensure that the average payoff vector converges to that set no matter what his adversary opponent does. Blackwell provided two equivalent sets of conditions for a convex set to be approachable. The first (primary) condition is a geometric separation condition, while the second (dual) condition requires that the set be {\em non-excludable}, namely that for every mixed action of the opponent there exists a mixed action of the agent (a {\em response}) such that the resulting payoff vector belongs to $S$. Existing approachability algorithms rely on the primal condition and essentially require to compute at each stage a projection direction from a given point to $S$. In this paper, we introduce an approachability algorithm that relies on Blackwell's {\em dual} condition. Thus, rather than projection, the algorithm relies on computation of the response to a certain action of the opponent at each stage. The utility of the proposed algorithm is demonstrated by applying it to certain generalizations of the classical regret minimization problem, which include regret minimization with side constraints and regret minimization for global cost functions. In these problems, computation of the required projections is generally complex but a response is readily obtainable.
Shine on Me: Industry Coherence and Policy Support for Emerging Industries

Although the emergence of new industries is often attributed to state support, little is known about the conditions under which an emergent category of organizations comes to receive state support in the first place. We theorize how government support for a nascent industry is jointly determined by the industry’s internal features and external forces and test our arguments by analyzing feed-in tariff policies for the emergent solar photovoltaics (PV) industry in 28 European countries from 1987 to 2012. We find that feed-in tariffs—policies that incentivize renewable energy—were more likely in countries with greater numbers of solar PV producers and where the industry was more coherent, containing fewer producers coming from industries with a contrasting identity, such as fossil fuels. Further, we find that the concentration of the incumbent (rival) energy sector in a given country enhances the effect of the number of PV producers on government policy support, but only when the emerging industry has a coherent identity. Our results shed new light on the relationship between public policy and the emergence of an industry category, and they extend our understanding of how new industries can attain valuable state support while operating in seemingly hostile environments.
Event-by-Event Fluctuations of Azimuthal Particle Anisotropy in Au+Au Collisions at {radical}(s{sub NN})=200 GeV

This Letter presents the first measurement of event-by-event fluctuations of the elliptic flow parameter v{sub 2} in Au+Au collisions at {radical}(s{sub NN})=200 GeV as a function of collision centrality. The relative nonstatistical fluctuations of the v{sub 2} parameter are found to be approximately 40%. The results, including contributions from event-by-event elliptic flow fluctuations and from azimuthal correlations that are unrelated to the reaction plane (nonflow correlations), establish an upper limit on the magnitude of underlying elliptic flow fluctuations. This limit is consistent with predictions based on spatial fluctuations of the participating nucleons in the initial nuclear overlap region. These results provide important constraints on models of the initial state and hydrodynamic evolution of relativistic heavy ion collisions.
Exploring veganism through serious leisure and liquid modernity

ABSTRACT Understandings of leisure have progressed into a deep comprehension of the importance of intrinsic qualities that leisure creates for an individual choice and expression of self through food support the ‘modern’ paramount of personal choice and individuality. Food and dietary choices connecting to leisure and lifestyle mirror the conceptual framework of liquid modernity. The clarification of lifestyle offers an approach to explore veganism as a leisure lifestyle providing the foundation for this paper where veganism is explored using the dimensions of serious leisure. In this exploratory paper, the serious leisure perspective will be critiqued as a framework to explore veganism, as it moves from a diet and lifestyle to a form of individual expression of identity and self, culture and leisure.
IR meets NLP: On the Semantic Similarity between Subject-Verb-Object Phrases

Measuring the semantic similarity between phrases and sentences is an important task in natural language processing (NLP) and information retrieval (IR). We compare the quality of the distributional semantic NLP models against phrase-based semantic IR. The evaluation is based on the correlation between human judgements and model scores on a distributional phrase similarity task. We experiment with four NLP and two IR model variants. On the NLP side, models vary over normalization schemes and composition operators. On the IR side, models vary with respect to estimation of the probability of a term being in a document, namely P(t|d) where only term co-occurrence information is used and P(t|d, sim) which incorporates term distributional similarity. A mixture of the two methods is presented and evaluated. For both methods, word meanings are derived from large corpora of data: the BNC and ukWaC. One of the main findings is that grammatical distributional models give better scores than the IR models. This suggests that an IR model enriched with distributional linguistic information performs better in the long standing problem in IR of document retrieval where there is no direct symbolic relationship between query and document concepts.
The Rosa chinensis cv. Viridiflora Phyllody Phenotype Is Associated with Misexpression of Flower Organ Identity Genes

Phyllody is a flower abnormality in which leaf-like structures replace flower organs in all whorls. Here, we investigated the origin and the molecular mechanism of phyllody phenotype in Rosa chinensis cv. Viridiflora, an ancient naturally occurring Chinese mutant cultivar. Reciprocal grafting experiments and microscopy analyses, demonstrated that the phyllody phenotype in Viridiflora is not associated with phytoplasmas infection. Transcriptome comparisons by the mean of RNA-Seq identified 672 up-regulated and 666 down-regulated genes in Viridiflora compared to its closely related genotype R. chinensis cv. Old Blush. A fraction of these genes are putative homologs of genes known to be involved in flower initiation and development. We show that in flower whorl 2 of Viridiflora, a down-regulation of the floral organ identity genes RcPISTILLATA (RcPI), RcAPETALA3 (RcAP3) and RcSEPALLATA3 (RcSEP3), together with an up-regulation of the putative homolog of the gene SUPPRESSOR of OVEREXPRESSION of CONSTANS1 (RcSOC1) are likely at the origin of the loss of petal identity and leaf-like structures formation. In whorl 3 of Viridiflora, ectopic expression of RcAPETALA2 (RcAP2) along with the down regulation of RcPI, RcAP3, and RcSEP3 is associated with loss of stamens identity and leaf-like structures formation. In whorl 4, the ectopic expression of RcAP2 associated with a down-regulation of RcSEP3 and of the C-class gene RcAGAMOUS correlate with loss of pistil identity. The latter also suggested the antagonist effect between the A and C class genes in the rose. Together, these data suggest that modified expression of the ABCE flower organ identity genes is associated with the phyllody phenotype in the rose Viridiflora and that these genes are important for normal flower organs development.
Characterization of Dystroglycan‐Laminin Interaction in Peripheral Nerve

Abstract: Dystroglycan is encoded by a single gene and cleaved into two proteins, α‐ and β‐dystroglycan, by posttranslational processing. The 120‐kDa peripheral nerve isoform of α‐dystroglycan binds laminin‐2 comprised of the α2, β1, and γ1 chains. In congenital muscular dystrophy and dy mice deficient in laminin α2 chain, peripheral myelination is disturbed, suggesting a role for the dystroglycan‐laminin interaction in peripheral myelinogenesis. To begin to test this hypothesis, we have characterized the dystroglycan‐laminin interaction in peripheral nerve. We demonstrate that (1) α‐dystroglycan is an extracellular peripheral membrane glycoprotein that links β‐dystroglycan in the Schwann cell outer membrane with laminin‐2 in the endoneurial basal lamina, and (2) dystrophin homologues Dp116 and utrophin are cytoskeletal proteins of the Schwann cell cytoplasm. We also present data that suggest a role for glycosylation of α‐dystroglycan in the interaction with laminin.
Optimization and Application of Reflective LSPR Optical Fiber Biosensors Based on Silver Nanoparticles

In this study, we developed a reflective localized surface plasmon resonance (LSPR) optical fiber sensor, based on silver nanoparticles (Ag NPs). To enhance the sensitivity of the LSPR optical sensor, two key parameters were optimized, the length of the sensing area and the coating time of the Ag NPs. A sensing length of 1.5 cm and a 1-h coating time proved to be suitable conditions to produce highly sensitive sensors for biosensing. The optimized sensor has a high refractive index sensitivity of 387 nm/RIU, which is much higher than that of other reported individual silver nanoparticles in solutions. Moreover, the sensor was further modified with antigen to act as a biosensor. Distinctive wavelength shifts were found after each surface modification step. In addition, the reflective LSPR optical fiber sensor has high reproducibility and stability.