Push & Pull: autonomous deployment of mobile sensors for a complete coverage

Mobile sensor networks are important for several strategic applications devoted to monitoring critical areas. In such hostile scenarios, sensors cannot be deployed manually and are either sent from a safe location or dropped from an aircraft. Mobile devices permit a dynamic deployment reconfiguration that improves the coverage in terms of completeness and uniformity. In this paper we propose a distributed algorithm for the autonomous deployment of mobile sensors called Push&Pull. According to our proposal, movement decisions are made by each sensor on the basis of locally available information and do not require any prior knowledge of the operating conditions or any manual tuning of key parameters. We formally prove that, when a sufficient number of sensors are available, our approach guarantees a complete and uniform coverage. Furthermore, we demonstrate that the algorithm execution always terminates preventing movement oscillations. Numerous simulations show that our algorithm reaches a complete coverage within reasonable time with moderate energy consumption, even when the target area has irregular shapes. Performance comparisons between Push&Pull and one of the most acknowledged algorithms show how the former one can efficiently reach a more uniform and complete coverage under a wide range of working scenarios.Comment: Technical Report. This paper has been published on Wireless Networks, Springer. Animations and the complete code of the proposed algorithm are available for download at the address: http://www.dsi.uniroma1.it/~novella/mobile_sensors

GRBs with optical afterglow and known redshift: a statistical study

We present a correlation between two intrinsic parameters of GRB optical afterglows. These are the isotropic luminosity at the maximum of the light curve (Lpeak) and the time-integrated isotropic energy (Eiso) radiated after the observed maximum. We test the correlation between the logarithms of (Eiso) and (Lpeak) and finally we value the effect of the different samples of GRBs in according with the first optical observation reduced to proper time.Comment: To be published in the proceedings of the conference "SWIFT and GRBs: Unveiling the Relativistic Universe", Venice, June 5-9, 200

Rooting and carbohydrate availability in Vitis 140 Ruggeri stem cuttings

Rooting in Vitis 140 Ruggeri rootstock appears to be correlated to the availability of soluble carbohydrates in the cuttings. This relationship was verified using stem cuttings collected from December to April by comparing those propagated after cold storage (C) with those collected directly in the field (F). The basal end of some of the cuttings of both groups (C and F) were dipped into deionized water before propagation (CW and FW). The mobilization of soluble carbohydrates paralleled with the pattern of the rooting process. In the cold stored material, rooting took place earlier than in the field material. The mobilization of soluble carbohydrates occurred at two stages: during the storage period at 2 °C (50% if compared with the cuttings collected in the field) and during the first 20 d of rooting. On day 20, the carbohydrate content was reduced by 80%. Rooting and carbohydrate availability appear to be associated

Egg quality from nera atriana, a local poultry breed of the Abruzzo region (Italy), and isa brown hens reared under free range conditions

The selection and diffusion in the poultry sector of hybrid breeds able to produce higher amount of meat and eggs, led over time to the erosion of genetic resources. One of the strategies that can be applied in order to stem such phenomenon, concerns the valorization of the animal products, meat or eggs, obtained from indigenous poultry breeds. Therefore, the aim of this study is to characterize the qualitative aspects of eggs obtained from the Nera Atriana hen, an Italian indigenous laying hen characteristic of the Abruzzo region, making a direct comparison with a commercial hybrid reared in the same environment and applying the same feeding protocol. The trial was conducted for a period of 5 months (from March to July 2019), in which 6 egg samplings were performed (one at the beginning and additional 5 on a monthly basis); each sampling involved the collection of 15 eggs per group of animals for a total of 90 eggs per genotype. Eggs were specifically subjected to evaluations of the physical parameters, including the yolk color, and analyses aimed at determining the content of total lipids, cholesterol, and β-carotene. In addition to this, the fatty acids profile and the electrophoretic pattern of the globular proteins of the yolk were characterized. Eggs from hybrid hens were characterized by higher total weight with significantly higher values specifically associated to albumen and yolk weight and to the albumen percentage. In the eggs obtained from the local hen, higher relative percentages were instead found in the quantity of shell and yolk; furthermore, in the same samples was observed a higher yolk redness, a cholesterol concentration tending to be lower although not significant (p = 0.0521), and a greater amount of saturated fatty acids which could justify a lower susceptibility of the food to oxidative processes following transformation with heat treatments. With regard to the fatty acid composition, differences were specifically observed for palmitic (C16:0) and palmitoleic (C16:1 cis-9) acids that showed higher relative percentages in eggs from local breed, and for the oleic acid (C18:1 cis-9) which was more represented in eggs from commercial hens. In conclusion, some interesting nutritional features, in a preliminary way, have been highlighted that could lead the consumer to prefer these “niche” products over those obtained from commercial hybrids

Polymorphisms of seed storage proteins in Olea europaea L. cultivars

The use of Olea europaea globulins as genetic markers for the identification of the cultivars was perfomed in the laboratory of Genetics of Department of Agriculture, Food and Environment, University of Pisa. The major component of Olea europaea L. seed storage proteins is represented by globulins. These fractions were characterised by electrophoresis and compared with the proteins extracted from protein bodies. The biochemical analysis of the olive seed globulins was carried out in sixteen different cultivars coming from several geographical areas of Italy. The electrophoretic patterns in polyacrylamide gels electrophoresis in denaturing conditions (SDS-PAGE) evidenced both qualitative and quantitative differences. It was possible to identify all the cultivars by their electrophoretic spectra. Number and position of the electrophoretic bands allowed the construction of a similarity matrix and of a dendrogram that allowed the separation into groups, according to their phylogenetic relationships. The several clusters seem to be related with agronomic traits such as fruit size or oil production; no relationships were found with the geographical cultivation area

Esca symptoms appearance in Vitis vinifera L.: influence of climate, pedo-climatic conditions and rootstock/cultivar combination

This study investigated the appearance of esca symptoms in relation to environmental factors and the rootstock/cultivar combination in an experimental setting between 2004 and 2009. Among the common genotypes showing susceptibility to the esca disease, four cultivars were considered: ‘Cabernet Sauvignon’, ‘Sangiovese’, ‘Trebbiano Toscano’ and ‘Chardonnay’. These cultivars were studied own-rooted and in combination with two rootstocks: Kober 5BB and 1103 Paulsen. The difference in susceptibility of cultivars to esca appeared negatively related to the graft. No clear relation was found between esca appearance and environmental factors. Moreover, an unexpected discordance between esca incidence percentage and mortality rate was observed.

Source Code Classification for Energy Efficiency in Parallel Ultra Low-Power Microcontrollers

The analysis of source code through machine learning techniques is an increasingly explored research topic aiming at increasing smartness in the software toolchain to exploit modern architectures in the best possible way. In the case of low-power, parallel embedded architectures, this means finding the configuration, for instance in terms of the number of cores, leading to minimum energy consumption. Depending on the kernel to be executed, the energy optimal scaling configuration is not trivial. While recent work has focused on general-purpose systems to learn and predict the best execution target in terms of the execution time of a snippet of code or kernel (e.g. offload OpenCL kernel on multicore CPU or GPU), in this work we focus on static compile-time features to assess if they can be successfully used to predict the minimum energy configuration on PULP, an ultra-low-power architecture featuring an on-chip cluster of RISC-V processors. Experiments show that using machine learning models on the source code to select the best energy scaling configuration automatically is viable and has the potential to be used in the context of automatic system configuration for energy minimisation