Proton-proton, anti-proton-anti-proton, proton-anti-proton correlations in Au + Au collisions measured by STAR at RHIC

The analysis of two-particle correlations provides a powerful tool to study the properties of hot and dense matter created in heavy-ion collisions at ultra-relativistic energies. Applied to identical and non-identical hadron pairs, it makes the study of space-time evolution of the source in femtoscopic scale possible. Baryon femtoscopy allows extraction of the radii of produced sources which can be compared to those deduced from identical pion studies, providing complete information about the source characteristics. In this paper we present the correlation functions obtained for identical and non-identical baryon pairs of protons and anti-protons. The data were collected recently in Au+Au collisions at $\sqrt{s_{NN}}$ =62 GeV and $\sqrt{s_{NN}}$ =200 GeV by the STAR detector at the RHIC accelerator. We introduce corrections to the baryon-baryon correlations taking into account: residual correlations from weak decays, particle identification probability and the fraction of primary baryons. Finally we compare our results to theoretical prediction

Entrepreneurship in the Wine Industry. A matter of Risk and Reward

This thesis concerns two lines of research that can be considered relevant for wine SMEs located in Italy.The first one concentrates on the moderating role of agglomeration and network and the relationship between Entrepreneurial Orientation (EO) and firms performance. The second line proposes a framework to compare the web quality to costumers\u2019 perceptions and preference

SQLformer: Deep Auto-Regressive Query Graph Generation for Text-to-SQL Translation

In recent years, there has been growing interest in text-to-SQL translation, which is the task of converting natural language questions into executable SQL queries. This technology is important for its potential to democratize data extraction from databases. However, some of its key hurdles include domain generalisation, which is the ability to adapt to previously unseen databases, and alignment of natural language questions with the corresponding SQL queries. To overcome these challenges, we introduce SQLformer, a novel Transformer architecture specifically crafted to perform text-to-SQL translation tasks. Our model predicts SQL queries as abstract syntax trees (ASTs) in an autoregressive way, incorporating structural inductive bias in the encoder and decoder layers. This bias, guided by database table and column selection, aids the decoder in generating SQL query ASTs represented as graphs in a Breadth-First Search canonical order. Comprehensive experiments illustrate the state-of-the-art performance of SQLformer in the challenging text-to-SQL Spider benchmark. Our implementation is available at https://github.com/AdrianBZG/SQLformerComment: 11 pages, 4 figure

Unsupervised Fact Verification by Language Model Distillation

Unsupervised fact verification aims to verify a claim using evidence from a trustworthy knowledge base without any kind of data annotation. To address this challenge, algorithms must produce features for every claim that are both semantically meaningful, and compact enough to find a semantic alignment with the source information. In contrast to previous work, which tackled the alignment problem by learning over annotated corpora of claims and their corresponding labels, we propose SFAVEL (Self-supervised Fact Verification via Language Model Distillation), a novel unsupervised framework that leverages pre-trained language models to distil self-supervised features into high-quality claim-fact alignments without the need for annotations. This is enabled by a novel contrastive loss function that encourages features to attain high-quality claim and evidence alignments whilst preserving the semantic relationships across the corpora. Notably, we present results that achieve a new state-of-the-art on the standard FEVER fact verification benchmark (+8% accuracy) with linear evaluation

Motivations, perceived risk and behavioural intentions in hard adventure tourism. A natural park case study1

Purpose of the paper: This study on consumer behaviour intends to combine two lines of investigation. First, we examine how different motivation factors in adventure tourism affect behavioural intentions. Secondly, in order to provide a better understanding of behavioural intentions we further explore the differences between the groups of individuals\u2019 subjective perception of risk. Design/methodology/approach: A visitor survey was conducted on a sample of hard adventure tourists at the Friuli Dolomiti Alps Natural Park. Factor analysis of motivational items resulted in four dimensions (i.e. nature, risk, contemplation and socialization). In order to discover a relationship between the four motivational factors and the adventure tourists\u2019 behavioural intention, a stepwise regression analysis was conducted. Then, using ANOVA and post hoc analysis (Scheffe\u2019s test), the existing differences between various levels of risk perception of adventure tourists and their response to behavioural intentions were analysed. Findings: The analysis of motivational factors indicates that \u201cactivity related motivations\u201d include four dimensions: nature, risk, contemplation and socialization. The stepwise regression results show that nature is the only motivational factor that affects tourists\u2019 behavioural intention. Originality/value: This paper shows that \u201cnature\u201d is the key motivational factor for adventure tourists to revisit a park. Practical implications: The analysis provides a framework suggesting how organizations might usefully implement a marketing strategy. This study encompasses the risk perception as a motivational factor and tries to discuss how this concept can be operationalized in tourism marketing. Limitations: This paper presents two main limitations. Firstly, the cross sectional nature of the data, and secondly, the hypotheses were tested using a sample from a limited area

Expression of multiple horizontally acquired genes is a hallmark of both vertebrate and invertebrate genomes.

BACKGROUND: A fundamental concept in biology is that heritable material, DNA, is passed from parent to offspring, a process called vertical gene transfer. An alternative mechanism of gene acquisition is through horizontal gene transfer (HGT), which involves movement of genetic material between different species. HGT is well-known in single-celled organisms such as bacteria, but its existence in higher organisms, including animals, is less well established, and is controversial in humans. RESULTS: We have taken advantage of the recent availability of a sufficient number of high-quality genomes and associated transcriptomes to carry out a detailed examination of HGT in 26 animal species (10 primates, 12 flies and four nematodes) and a simplified analysis in a further 14 vertebrates. Genome-wide comparative and phylogenetic analyses show that HGT in animals typically gives rise to tens or hundreds of active 'foreign' genes, largely concerned with metabolism. Our analyses suggest that while fruit flies and nematodes have continued to acquire foreign genes throughout their evolution, humans and other primates have gained relatively few since their common ancestor. We also resolve the controversy surrounding previous evidence of HGT in humans and provide at least 33 new examples of horizontally acquired genes. CONCLUSIONS: We argue that HGT has occurred, and continues to occur, on a previously unsuspected scale in metazoans and is likely to have contributed to biochemical diversification during animal evolution.This work was supported by the European Research Council (AdG233232).This is the final published version. It first appeared at http://genomebiology.com/2015/16/1/50