Search

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum. Supplementary information: you can download the chains here or create your own chains with CosmoSIS here.

We address the problem of optimally identifying all kilonovae detected via gravitational-wave emission in the upcoming LIGO/Virgo/KAGRA observing run, O4, which is expected to be sensitive to a factor of ∼7 more binary neutron star (BNS) alerts than previously. Electromagnetic follow-up of all but the brightest of these new events will require >1 m telescopes, for which limited time is available. We present an optimized observing strategy for the DECam during O4. We base our study on simulations of gravitational-wave events expected for O4 and wide-prior kilonova simulations. We derive the detectabilities of events for realistic observing conditions. We optimize our strategy for confirming a kilonova while minimizing telescope time. For a wide range of kilonova parameters, corresponding to a fainter kilonova compared to GW170817/AT 2017gfo, we find that, with this optimal strategy, the discovery probability for electromagnetic counterparts with the DECam is ∼80% at the nominal BNS gravitational-wave detection limit for O4 (190 Mpc), which corresponds to an ∼30% improvement compared to the strategy adopted during the previous observing run. For more distant events (∼330 Mpc), we reach an ∼60% probability of detection, a factor of ∼2 increase. For a brighter kilonova model dominated by the blue component that reproduces the observations of GW170817/AT 2017gfo, we find that we can reach ∼90% probability of detection out to 330 Mpc, representing an increase of ∼20%, while also reducing the total telescope time required to follow up events by ∼20%.

The ultra-faint dwarf galaxy Reticulum II (Ret II) exhibits a unique chemical evolution history, with ${72}_{-12}^{+10}$ % of its stars strongly enhanced in r -process elements. We present deep Hubble Space Telescope photometry of Ret II and analyze its star formation history. As in other ultra-faint dwarfs, the color–magnitude diagram is best fit by a model consisting of two bursts of star formation. If we assume that the bursts were instantaneous, then the older burst occurred around the epoch of reionization, forming ∼80% of the stars in the galaxy, while the remainder of the stars formed ∼3 Gyr later. When the bursts are allowed to have nonzero durations, we obtain slightly better fits. The best-fitting model in this case consists of two bursts beginning before reionization, with approximately half the stars formed in a short (100 Myr) burst and the other half in a more extended period lasting 2.6 Gyr. Considering the full set of viable star formation history models, we find that 28% of the stars formed within 500 ± 200 Myr of the onset of star formation. The combination of the star formation history and the prevalence of r -process-enhanced stars demonstrates that the r -process elements in Ret II must have been synthesized early in its initial star-forming phase. We therefore constrain the delay time between the formation of the first stars in Ret II and the r -process nucleosynthesis to be less than 500 Myr. This measurement rules out an r -process source with a delay time of several Gyr or more, such as GW170817.

The nucleolus is a dynamic non-membrane-bound nuclear organelle, which plays key roles not only in ribosome biogenesis but also in many other cellular processes. Consistent with its multiple functions, the nucleolus has been implicated in many human diseases, including cancer and degenerative pathologies of the nervous system and heart. Here, we report the characterization of the Drosophila Non3 (Novel nucleolar protein 3) gene, which encodes a protein homologous to the human Brix domain-containing Rpf2 that has been shown to control ribosomal RNA (rRNA) processing. We used imprecise P-element excision to generate four new mutant alleles in the Non3 gene. Complementation and phenotypic analyses showed that these Non3 mutations can be arranged in an allelic series that includes both viable and lethal alleles. The strongest lethal allele (Non3∆600) is a genetically null allele that carries a large deletion of the gene and exhibits early lethality when homozygous. Flies heterozygous for Non3∆600 occasionally exhibit a mild reduction in the bristle size, but develop normally and are fertile. However, heteroallelic combinations of viable Non3 mutations (Non3197, Non3310 and Non3259) display a Minute-like phenotype, consisting in delayed development and short and thin bristles, suggesting that they are defective in ribosome biogenesis. We also demonstrate that the Non3 protein localizes to the nucleolus of larval brain cells and it is required for proper nucleolar localization of Fibrillarin, a protein important for post-translational modification and processing of rRNAs. In summary, we generated a number of genetic and biochemical tools that were exploited for an initial characterization of Non3, and will be instrumental for future functional studies on this gene and its protein product.

Abstract The present study compares the physiological and cropping response of the new fungi-resistant grapevine Accession 72–096 (‘Sangiovese’ x ‘Bianca’ hybrid) against a susceptible ‘Sangiovese’ clone which was either fully (FS-SG) or partially sprayed (PS-SG). Data logged on Accession 72–096 indicate that while two early season sprays were enough to avoid major downy mildew (DM) and powdery mildew (PM) outbreaks, Accession 72–096 also showed concurrent desirable features such as moderate cropping, loose clusters, fast sugar accumulation coupled with sufficient acidity even at peak total soluble solids (TSS) concentration (around 24 °Brix), good color and higher flavonols prompting co-pigmentation. Conversely, FS-SG showed final lower acidity despite the notably lower sugar concentration (≅18 °Brix), as well as larger clusters and berries that resulted in more compact bunches. From a methodological viewpoint, end of season single-leaf readings appeared to overestimate the limitation of leaf function due to PM and DM infections in SG-PS vines which, when assessed via a whole-canopy approach, did not show significant differences vs. Accession 72–096, a result likely due to counteracting effects linked to a compensation mechanism by healthy tissues. Our data also suggest that a PM infection can lead to a decoupling in sugar-color accumulation patterns.

The implementation of Information and Communication Technologies (ICT) in business education appears to be influenced by a number of organizational issues, such as culture and technological sophistication. However, extant research has had very little to say about the antecedents that shape the adoption and diffusion of ICT across companies. In order to shed light on the phenomenon under investigation, this paper presents a comparative case study between five Italian companies that have instituted a corporate university. By distinguishing companies in typical cases and deviant cases with regard to the extensive use of e-learning technologies, our findings provide some useful insights about the antecedents that make companies more or less prone to employ the new frontiers of technology in their CUs.

Often left in the background by media, biogas is a renewable energy source with a great potential for development. Its production is based on the anaerobic digestion of organic waste materials, which are usually livestock effluents, municipal and industrial sewage sludge, energy crops, agro-industrial wastes, MSW landfills, etc. To date, biogas is mainly used for the production of electrical energy, thanks to a more favorable regulatory and incentive framework. Installations may adopt a cogeneration arrangement, that allows to recover the heat produced by gas-fired engines for home or industrial reuse. In the near future, however, the biogas properly upgraded to biomethane will be used for transportation or fed into the natural gas grid directly reaching end consumers, both solutions adding value to biogas. The utilization of biogas is in line with the “20- 20-20” targets to be met by the Member States of the European Union by 2020, which provide that 20 % of EU energy consumption will have to come from renewable resources and that the share of energy from renewable sources in the transport sector in 2020 will be at least 10 %. Biomethane is obtained from properly treated biogas. Biogas is a mixture of mainly methane and CO2 with other contaminants (such as H2S, nitrogen and oxygen), whose type and amount depend upon the biogas source and determine which cleaning technique (and, to some extent, also upgrading technique) is the most suitable for gas purification. ”Cleaning” is referred to the pretreatment that allows the removal of all pollutants but carbon dioxide, while “upgrading” consists of CO2 removal. There are no clear guidelines for choosing among the different techniques, mainly in relation with the biomass source which affects the biogas composition. This work performs a techno-economic analysis of the biogas-to-biomethane process using three different biogases produced from sewage sludge, agro-industrial wastes and landfills, using water scrubbing and amine washing for the upgrading process. By means of process simulation with commercial software (such as Aspen Plus®), a comparison among performances, energy requirements and solvent type is carried out. In the end, an economic assessment of the two upgrading techniques for the three considered biogas sources is performed, taking into account the flow rate of the biogas to be treated.

This paper evaluates the thermodynamic performance and costs of biomethane production plants tailored to the Italian scenario, by comparing the competitiveness of a water wash based biogas upgrading plant against a conventional biogas-to-electricity facility. The main goals of the article are the following: Report an updated picture of the state-of-the-art of the Italian biogas plants fleet, taking advantage from a database of existing plants collected by LEAP (Laboratorio Energia e Ambiente Piacenza) in the framework of its techno-economic assessment activity performed over the last years; Review and compare the strengths and drawbacks of the commercially available upgrading processes, both from a technical and economic point of view; Identify and model a case study, based on water wash upgrading, which is suitable for the Italian context, simulating heat and mass balances; Carry out a preliminary economic assessment of the biomethane production chain, i.e. from cradle to pipeline, in order to determine biogas upgrading competitiveness. A typical agricultural feedstock, made of a mixture of corn silage and cattle manure is considered as reference. Moreover, concerning the plant size, two scenarios are analysed, respectively, (i) featuring themost common biogas production rate of the Italian plants (500 Sm3biogas/h, which corresponds to roughly 250 Sm3biomethane/h) and (ii) entailing a biogas production rate more suitable for a biomethane plant (1,000Sm3biogas/h, roughly 500 Sm3biomethane/h).

This paper analyses the thermodynamic performance and proposes different energy integration schemes for a methanol absorption based acid gas removal process, namely the Rectisol® process specifically designed for the selective removal of H2S and CO2 from coal derived syngas. The study consists of three major tasks:Calibrating the PC-SAFT equation of state for MEOH-CO2-H2S-H2-CO mixtures at conditions relevant for the Rectisol® process. Evaluating the thermodynamic performances and optimising the energy integration of the “Reference” scheme by means of “heat-cascade” based optimisation methodology. Identifying attractive process modifications on the basis of Process Integration principles.

We report that somatostain receptor (SSTR) 1,2 and 5 activation by selective agonista, cause C6 cell growth arrest through PTPn-dependent dephosphorylation of ERK1/2 in vitro and after xenografting in nude mice. Individual SSTR agonist desplayed different efficacy and potecy showing partial synergism by combined treatment. Since most tumor cells express multiple SSTRs, the activtion of all the subtypes may grant a better control of cancer growth.

The roasting process allows complex chemical reactions in foods leading the formation of the Maillard-related compounds, which are of fundamental importance for colour and aroma development in hazelnuts (Corylus avellana L.). Colour is a charming characteristic of roasted foods; despite of their fundamental role in organoleptic properties, the roasting allows accumulation of some potentially toxic technological contaminants, as showed in other matrices (e.g. acrylamide, furan and D-amino acids). Free and protein-bound D-amino acids (D-aa) in foods can origin by technological processing (their formation is pH, time, and temperature-dependent), and also from bacterial racemases in fermented foods, as recently showed in cocoa ( FRIEDMAN 1999; CALIGIANI et al. 2007) So, these compounds can be used as thermal and bacterial markers. Racemisation impairs digestibility/nutritional quality of foods; some D-aa acids are both beneficial and deleterious (DA-WEN SUN 2008). The L*a*b* (international standard for colour measurements adopted by the Commission Internationale d'Eclairage, CIE, 1976) and Red Green Blue (RGB) systems are the most employed methods for colour analysis. Computer Vision Image Analysis (CVIA) coupled with Artificial Intelligence (AI) and related tools (Principal Component Analysis, Artificial Neural Networks, Self Organising Maps) should be considered a powerful approach for evaluating colour development in foods (PATZOLD & BRUCKNER 2006). First aim of our study was to monitor via GC-MS the D-aa formation in hazelnuts during different conditions of roasting. Second aim was to develop a CVIA/AI method to study the colour development in roasted hazelnut, considering the correlation between colour and D-aa too. The racemisation of L-aa (particularly D-aspartic acid plus D-asparagine, D-asx) in hazelnut was time-temperature dependent. Protein-bound D-asx (expressed as D/(L+D); 1.49%) and free D-ala (5.87%) were predominant in Infra-Red roasted samples. Hot-air flow process leads the formation of free-D-aa (D-ala: 6.77%; D-asx: 3.47%; D-glu: 4.50%). Using Back Propagation Neural Network on the Discrete Fourier Transform output (whole surface colour), the identification of hazelnuts samples roasted in different condition was achieved. Red colour decreased according to the correspondent increase of D-amino acids content. Concluding, CVIA/AI is a promising complex tool useful to simplify the comprehension of a complex model system, as colour development in roasted hazelnuts. Keywor