On the range of validity of perturbative models for galaxy clustering and its uncertainty

We explore the reach of analytical models at one-loop in Perturbation Theory (PT) to accurately describe measurements of the galaxy power spectrum from numerical simulations in redshift space. We consider the validity range in terms of three different diagnostics: 1) the goodness of fit; 2) a figure-of-bias quantifying the error in recovering the fiducial value of a cosmological parameter; 3) an internal consistency check of the theoretical model quantifying the running of the model parameters with the scale cut. We consider different sets of measurements corresponding to an increasing cumulative simulation volume in redshift space. For each volume we define a median value and the associated scatter for the largest wavenumber where the model is valid (the $k$-reach of the model). We find, as a rather general result, that the median value of the reach decreases with the simulation volume, as expected since the smaller statistical errors provide a more stringent test for the model. This is true for all the three definitions considered, with the one given in terms of the figure-of-bias providing the most stringent scale cut. More interestingly, we find as well that the error associated with the $k$-reach value is quite large, with a significant probability of being as low as 0.1$\, h \, {\rm Mpc}^{-1}$ (or, more generally, up to 40% smaller than the median) for all the simulation volumes considered. We explore as well the additional information on the growth rate parameter encoded in the power spectrum hexadecapole, compared to the analysis of monopole and quadrupole, as a function of simulation volume. While our analysis is, in many ways, rather simplified, we find that the gain in the determination of the growth rate is quite small in absolute value and well within the statistical error on the corresponding figure of merit.Comment: 7 pages, 3 figure

La pubblicazione dei dati sui beneficiari dei Fondi Strutturali: quali strategie per le regioni europee?

European Cohesion Policy and its Structural Funds, involving all EU Regions and Member States, are a well-suited context to verify the presence of different approaches to the publication of Open Government Data, a crucial tool to foster governmental transparency and accountability. Following the theoretical framework introduced by Dawes (2010), this paper is aimed at exploring how national and regional managing authorities of Structural Funds are making available the data on the use of the funding, in terms of both data stewardship (quality, format, accessibility, detail, etc.) and usefulness (availability of tools to interact with the data). The analysis takes into consideration 15 indicators aggregating 63 characteristics of the data published by each EU 2007-13 Programme in December 2013. Results show that only a fraction of the administrations is investing in advanced tools for data visualization and citizen engagement. Those authorities rely on good quality and high detail of the information, thus confirming the interdependence of the stewardship and usefulness principles, as highlighted in the literature

Marker-assisted selection of dairy cows for β-casein gene A2 variant

Many studies highlighted potential associations of β-casein A1 with specific human diseases and a minor digestibility of milk, due to the bioactive peptide β-casomorphin 7 (BCM-7) release during digestion. Conversely, the ancestral β-casein A2 variant seems to be a favorable trait because it is not associated with BMC-7 release. The aim of this work was to evaluate frequencies of β-casein variants in offspring of previously genotyped cows inseminated with A2 homozygous semen. The frequency of the A2/A2 animals has almost doubled from 37 to 69%. These are encouraging results with the perspective of reaching the goal of producing A2 milk

SARS-CoV-2 multi-variant rapid detector based on graphene transistor functionalized with an engineered dimeric ACE2 receptor

Reliable point-of-care (POC) rapid tests are crucial to detect infection and contain the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The emergence of several variants of concern (VOC) can reduce binding affinity to diagnostic antibodies, limiting the efficacy of the currently adopted tests, while showing unaltered or increased affinity for the host receptor, angiotensin converting enzyme 2 (ACE2). We present a graphene field-effect transistor (gFET) biosensor design, which exploits the Spike-ACE2 interaction, the crucial step for SARS-CoV-2 infection. Extensive computational analyses show that a chimeric ACE2-Fragment crystallizable (ACE2-Fc) construct mimics the native receptor dimeric conformation. ACE2-Fc functionalized gFET allows in vitro detection of the trimeric Spike protein, outperforming functionalization with a diagnostic antibody or with the soluble ACE2 portion, resulting in a sensitivity of 20 pg/mL. Our miniaturized POC biosensor successfully detects B.1.610 (pre-VOC), Alpha, Beta, Gamma, Delta, Omicron (i.e., BA.1, BA.2, BA.4, BA.5, BA.2.75 and BQ.1) variants in isolated viruses and patient's clinical nasopharyngeal swabs. The biosensor reached a Limit Of Detection (LOD) of 65 cps/mL in swab specimens of Omicron BA.5. Our approach paves the way for a new and reusable class of highly sensitive, rapid and variant-robust SARS-CoV-2 detection systems

Science with the space-based interferometer LISA. IV: probing inflation with gravitational waves

We investigate the potential for the LISA space-based interferometer to detect the stochastic gravitational wave background produced from different mechanisms during inflation. Focusing on well-motivated scenarios, we study the resulting contributions from particle production during inflation, inflationary spectator fields with varying speed of sound, effective field theories of inflation with specific patterns of symmetry breaking and models leading to the formation of primordial black holes. The projected sensitivities of LISA are used in a model-independent way for various detector designs and configurations. We demonstrate that LISA is able to probe these well-motivated inflationary scenarios beyond the irreducible vacuum tensor modes expected from any inflationary background.Comment: 53 pages, 18 figures; v2: minor changes to match published versio

Building new resources for historical linguistics

This volume collects the papers originally presented at the workshop Building New Resources for Historical Linguistics, held at the University of Pavia in November 2020. The purpose of this workshop was to provide an opportunity for researchers engaged in the development of linguistic resources for historical linguistics to share their experience and knowledge. Sharing is crucial in computational linguistics in order to avoid multiplying efforts and encourage the use of compatible tools, formats, and formalisms to increase the interoperability. Reflecting the purpose of the original workshop, this book introduces the reader to different projects aimed at creating, developing and linking linguistic resources for historical linguistics. While some of the papers in the volume describe mature resources and discuss their possible application, others introduce resources that are still in progress, presenting their aims, the challenges faced in their construction, and the methodologies employed to tackle them. The different types of resources described in the volume include syntactically annotated corpora (treebanks), dependency lexica, as well as lexical and typological databases. Furthermore, some of the papers are concerned with the thriving field of Linguistic Linked Open Data, the current up-to-date standard to link linguistic resources

Linking the Ancient Greek WordNet to the Homeric Dependency Lexicon

The Ancient Greek WordNet is a new resource that is being developed at the Universities of Pavia and Exeter, based on the Princeton WordNet. The Princeton WordNet provides sentence frames for verb senses, but this type of information is lacking in most WordNets of other languages. In fact, exporting sentence frames from English to other languages is not a trivial task, as sentence frames depend on the syntax of individual languages. In addition, the information provided by the Princeton WordNet is not corpus-based but relies on native speakers’ knowledge. This type of information is not available for dead languages, which are by definition corpus languages. In this paper, we show how sentence frames can be extracted from morpho-syntactically parsed corpora by linking an existing depend- ency lexicon of Homeric verbs (HoDeL) to verbs in the Ancient Greek WordNet. Given its features, HoDeL allows automatically extracting all subcategorization frames available for each verb along with information concerning their frequency as well as semantic information regarding the possible arguments occurring in specific frames. In the paper, we show our method to automatically link the two resources and compare some of the resulting sentence frames with the English sentence frames in the Princeton WordNet

Linking the Sanskrit WordNet to the Vedic Dependency Treebank: a pilot study

The Sanskrit WordNet is a resource currently under development, whose core was induced from a Vedic text sample semantically annotated by means of an ontology mapped on the Princeton WordNet synsets. Building on a previous case study on Ancient Greek (Zanchi et al. 2021), we show how sentence frames can be extracted from morphosyntactically parsed corpora by linking an existing dependency treebank of Vedic Sanskrit to verbal synsets in the Sanskrit WordNet. Our case study focuses on two verbs of asking, y{\=a}c- and prach-, featuring a high degree of variability in sentence frames. Treebanks enhanced with WordNet-based semantic information revealed to be of crucial help in motivating sentence frame alternations