A possible solution for dinamically managing virtual environments

In modern distributed computer systems (clusters and computing GRIDs) a new class of problems, due to the increasing heterogeneity of users’ needs, have to be tackled by the administrators. One possible solution is to create ondemand virtual working environments tailored on the user’s requirements. Hence the need for an architecture to manage dynamically such environments. In this work we propose a possible solution based on the use of Virtual Machines (Xen), the implementation of a Virtual Machine Manager, capable of creation, destruction and migration of the virtualized working environments. The information will be collected using a client-server mechanism, to allow the manager to deploy preconfigured Virtual Machines on the available hardware resources. When a new execution environment became active, it is automatically recognized by the Batch System Manager and is then ready to be used

On Designing a Time Sensitive Interaction Graph to Identify Twitter Opinion Leaders

What happened on social media during the recent pandemic? Who was the opinion leader of the conversations? Who influenced whom? Were they medical doctors, ordinary people, scientific experts? Did health institutions play an important role in informing and updating citizens? Identifying opinion leaders within social platforms is of particular importance and, in this paper, we introduce the idea of a time sensitive interaction graph to identify opinion leaders within Twitter conversations. To evaluate our proposal, we focused on all the tweets posted on Twitter in the period 2020-21 and we considered just the ones that were Italian-written and were related to COVID-19. After mapping these tweets into the graph, we applied the PageRank algorithm to extract the opinion leaders of these conversations. Results show that our approach is effective in identifying opinion leaders and therefore it might be used to monitor the role that specific accounts (i.e., health authorities, politicians, city administrators) have within specific conversations

Durum wheat grain yield and quality as affected by S rate under Mediterranean conditions

The decreased inputs of S from atmospheric acidic deposition, the use of low S-containing fertilisers, and the decrease of organic matter content in soil resulted in S deficiency in many agricultural regions of the world. Sulphur fertilisation significantly affects grain yield and protein composition of cereals, thus altering the technological quality of grain. Field experiments were conducted in central Italy in two subsequent seasons to investigate the effects ofNand S application on five commercial wheat cultivarsknownto differ in yield potential and grain N content. Fertiliser treatments were two levels of N fertiliser (120 kgNha−1 and 180 kgNha−1) and three levels of S fertiliser (not applied, 60 kg S ha−1, and 120 kg S ha−1). Analyzed characters were dry weight and N and S uptake of grain and vegetative plant part, and grain quality characters. Variations in weather pattern – and especially in rainfall – between years significantly influenced grain yield and N and S content of grain, but did not affect quality parameters. Nitrogen and S application also significantly affected grain yield and the quality characteristicsW, P/L, dry gluten and SDS, although no interactive effect between treatments was observed. The highest protein content and W in grain was obtained with the combination of the highest fertiliser rates: 180 kgNha−1 and 120 kg S ha−1. Genotypes differed for yield stability between years, in that grain production was decreased in the driest year only in the varieties Claudio and Creso, but they responded similarly to N and S fertilisation. Genotypes differed also for protein concentration and quality parameters, and, on average, the varieties Duilio, Simeto and Svevo gave better performances. Differences in grain quality parameters were maintained through years, indicating that these traits are under strong genetic control

Development of a tool to optimize the performance of a Maui Cluster Scheduler

The use of Linux cluster computing in a scientific and heterogeneous environment has been growing very fast in the past years. The often conflicting user’s requests of shared resources are quite difficult to satisfy for the administrators, and, usually, lower the overall system efficiency. In this scenario a new tool to study and optimize the Maui Cluster Scheduler has been developed together with a new set of metrics to evaluate any given configuration. The main idea is to use the Maui internal simulator, fed by workloads produced either by a real cluster than by an ad hoc one, to test several scheduler configurations and then, using a genetic algorithm, to choose the best solution. In this work the architecture of the proposed tool is described together with the first results

Including an ocean carbon cycle model into iLOVECLIM (v1.0)

The atmospheric carbon dioxide concentration plays a crucial role in the radiative balance and as such has a strong influence on the evolution of climate. Because of the numerous interactions between climate and the carbon cycle, it is necessary to include a model of the carbon cycle within a climate model to understand and simulate past and future changes of the carbon cycle. In particular, natural variations of atmospheric CO2 have happened in the past, while anthropogenic carbon emissions are likely to continue in the future. To study changes of the carbon cycle and climate on timescales of a few hundred to a few thousand years, we have included a simple carbon cycle model into the iLOVECLIM Earth System Model. In this study, we describe the ocean and terrestrial biosphere carbon cycle models and their performance relative to observational data. We focus on the main carbon cycle variables including the carbon isotope ratios δ13C and the Δ14C. We show that the model results are in good agreement with modern observations both at the surface and in the deep ocean for the main variables, in particular phosphates, dissolved inorganic carbon and the carbon isotopes

Post-anthesis dry matter and nitrogen dynamics in durum wheat as affected by nitrogen supply and soil water availability.

Durum wheat (Triticum durum Desf.) is commonly grown in dryland conditions, where environmental stress during grain filling can limit productivity and increase the dependency on stored assimilate.We investigated current assimilation and remobilization of dry matter and nitrogen during grain filling in N fertilized and unfertilized durum wheat subjected to different levels of water deficit during grain filling. Two durum wheat varieties, Appio and Creso, were grown in open-air containers with three rates of nitrogen fertilizer (not applied, N0; normal amount, NN; high amount, NH) and four water regimes during grain filling (fully irrigated treatment, FI; low, LWS, moderate, MWS and high water stress, HWS) across 2 years. Grain yield and dry matter and N accumulation and remobilization were positively affected by N availability and negatively by water stress during grain filling. The reduction of grain yield by severe post-anthesis water stress amounted to 27 and 37% for N0 and NN, respectively, and was associated with a decrease in kernel weight. There was also a small negative effect on the number of kernels per spike. Conversely, the duration of grain filling was not modified either by water stress or by nitrogen treatments. Severe water stress also reduced dry matter accumulation and remobilization by 36 and 14% in N0 plants and by 48 and 25% in NH plants. Similarly, N accumulation and N remobilization was reduced by 43% and by 16% in N0 plants and by 51% and by 15% in NH plants. Conversely, low and moderate water stress did not substantially modify the patterns of dry matter and nitrogen deposition in grain. Although remobilization of dry matter and N was less affected by water stress than accumulation, it was not able to counterbalance the reduction of assimilation and consequently it was not able to stabilize grain yield under drought

Performance evaluation of Border irrigation method for cotton field

Performance evaluation of Border irrigation method was carried out for cotton field in village Kirarkot, Sirsa (Haryana). Water application, storage and distribution efficiency were estimated using measurements of soil moisture (%), infiltration rate (cm/hr), water advance and recession time (minute) during different irrigation events. The advance time increased during the growing season due to increased infiltration rate and increased resistance to flow by the growing crops. The water application efficiency of cotton field was 100 per cent as average applied depth (8.26 cm for canal irrigation and 9.06 cm for tubewell irrigation) of irrigation was less than the average required depth (10.30 cm for canal irrigation and 10.98 cm for tubewell irrigation) throughout the field plots. The observed water storage efficiency in different cotton fields varied from 72.92 - 90.08 per cent indicating under irrigation. Water distribution efficiency of cotton fields (97.8 -99.2per cent) indicated a relatively high degree of uniformity of water application. Stratified soil profile (sandy loam: 0-30 cm and sandy clay loam: 30-120 cm) of the selected fields reduced the infiltration rate to relatively very low value after 10-15 minutes creating favourable condition for uniformity of water application under border irrigation