Optimised protocols for time-critical applications and internetworking in wehicular ad-hoc networks

Vehicular ad-hoc networks (VANETs) that enable communication among vehicles and between vehicles and unmanned aerial vehicles (UAVs) and cellular base stations have recently attracted significant interest from the research community, due to the wide range of practical applications they can facilitate (e.g., road safety, traffic management and rescue missions). Despite this increased research activity, the high vehicle mobility in a VANET raises concerns regarding the robustness and adaptiveness of such networks to support time-critical applications and internetworking. In this thesis, as a first step toward the design of efficient MAC protocol to support time-critical applications and internetworking, we show that it is indeed possible to follow the dynamics of a network and consequently adapt the transmission probability of the Aloha protocol to reduce the interference and maximise the single-hop throughput between adjacent nodes. Extensive simulation validates the proposed analytical model, which thus can serve as a promising tool to improve VANETs performance. By exploiting the parallel between the CSMA/CA and Aloha performance models, the optimal transmission probability for the Aloha protocol as a function of estimated vehicular density is derived. This probability is then used to obtain the optimal maximum CW that can be integrated in an amended CSMA/CA protocol to maximise the single-hop throughput among adjacent vehicles. We show by means of simulation that the beneficial impact the proposed protocol is increased channel throughput and reduced transmission delay when compared with the standardised protocol CSMA/CA in IEEE 802.11p. These results reveal the applicability of the new, optimised protocol to safety applications and clustering techniques with stringent performance requirements. Lastly, we propose a Stable Clustering Algorithm for vehicular ad-hoc networks (SCalE) internetworking. The exchange of the necessary status information to support the efficient clusters formation can firmly relay on the support of our optimised CSMA/CA protocol. The SCalE algorithm makes use of the knowledge of the vehicles behaviour (explained in Chapter 5) for efficient selection of CHs, and selects a backup CH on top of the CH to maintain the stability of cluster structures. The increased stability and improved performance of the SCalE algorithm is studied and compared with existing clustering algorithms.Open Acces

Study of the beam-cavity interaction in the PS 10 MHz RF system

The eleven main accelerating cavities of the Proton Synchrotron (PS) at CERN consist of two ferrite-loaded coaxial lambda/4 resonators each. Both resonators oscillate in phase, as their gaps are electrically connected by short bars. They are in addition magnetically coupled via the bias loop used for cavity tuning. The cavities are equipped with a wide-band feedback system, limiting the beam loading, and a further reduction of the beam induced voltage is achieved by relays which short-circuit each half-resonator gap when the cavity is not in use. Asymmetries of the beam induced voltage observed in the two half-cavities indicate that the coupling between the two resonators is not as tight as expected. The total cavity impedance coupling to the beam may be affected differently by the contributions of both resonators. A dedicated measurement campaign with high-intensity proton beam and numerical simulation have been performed to investigate the beam-cavity interaction. This paper reports the result of the study and the work aiming at the development of a model of the system, including the wide-band feedback, which reproduces this interaction

Host-probiotic interaction: new insight into the role of the endocannabinoid system by in vivo and ex vivo approaches

The endocannabinoid system plays an important role in regulating inflammation in several chronic or anomalous gut inflammatory diseases. In vivo and ex vivo studies showed that 30 days treatment with a probiotic mix activated the endocannabinoid system in zebrafish. These results highlight the potential of this probiotic mixture to regulate immune cell function, by inducing gene expression of toll-like receptors and other immune related molecules. Furthermore, TUNEL assay showed a decrease in the number of apoptotic cells, and this finding was supported by a reduction in pro-apoptotic factors and an increase in anti-apoptotic molecules. The results presented here strengthen the molecular mechanisms activated by probiotic mix controlling immune response and inflammation

The PS 10 MHz High Level RF System Upgrade

In view of the upgrade of the injectors for the High Luminosity LHC, significantly higher bunch intensity is required for LHC-type beams. In this context an upgrade of the main accelerating RF system of the Proton Synchrotron (PS) is necessary, aiming at reducing the cavity impedance which is the source of longitudinal coupled-bunch oscillations. These instabilities pose as a major limitation for the increase of the beam intensity as planned after LS2. The 10 MHz RF system consists in 11 ferrite loaded cavities, driven by tube-based power amplifiers for reasons of radiation hardness. The cavity-amplifier system is equipped with a wide-band feedback that reduces the beam induced voltage. A further reduction of the beam loading is foreseen by upgrading the feedback system, which can be reasonably achieved by increasing the loop gain of the existing amplification chain. This paper describes the progress of the design of the upgraded feedback system and shows the results of the tests on the new amplifier prototype, installed in the PS during the 2015-16 technical stop. It also reports the first results of its performance with beam, observed in the beginning of the 2016 run

Effect of HXT1 and HXT7 hexose transporter overexpression on wild-type and lactic acid producing Saccharomyces cerevisiae cells

<p>Abstract</p> <p>Background</p> <p>Since about three decades, <it>Saccharomyces cerevisiae </it>can be engineered to efficiently produce proteins and metabolites. Even recognizing that in baker's yeast one determining step for the glucose consumption rate is the sugar uptake, this fact has never been conceived to improve the metabolite(s) productivity.</p> <p>In this work we compared the ethanol and/or the lactic acid production from wild type and metabolically engineered <it>S. cerevisiae </it>cells expressing an additional copy of one hexose transporter.</p> <p>Results</p> <p>Different <it>S. cerevisiae </it>strains (wild type and metabolically engineered for lactic acid production) were transformed with the <it>HXT</it>1 or the <it>HXT</it>7 gene encoding for hexose transporters.</p> <p>Data obtained suggest that the overexpression of an Hxt transporter may lead to an increase in glucose uptake that could result in an increased ethanol and/or lactic acid productivities. As a consequence of the increased productivity and of the reduced process timing, a higher production was measured.</p> <p>Conclusion</p> <p>Metabolic pathway manipulation for improving the properties and the productivity of microorganisms is a well established concept. A high production relies on a multi-factorial system. We showed that by modulating the first step of the pathway leading to lactic acid accumulation an improvement of about 15% in lactic acid production can be obtained in a yeast strain already developed for industrial application.</p

Biohydrogen production from food waste: Influence of the inoculum-to-substrate ratio

In this study, the influence of the inoculum-to-substrate ratio (ISR) on dark fermentative hydrogen production from food waste (FW) was evaluated. ISR values ranging from 0.05 to 0.25 g VSinoculum/g VSsubstrate were investigated by performing batch tests at T = 39 °C and pH = 6.5, the latter being the optimal value identified based on a previous study. The ISR was found to affect the fermentation process, clearly showing that an adequate ISR is essential in order to optimise the process kinetics and the H2 yield. An ISR of 0.14 proved to optimum, leading to a maximum H2 yield of 88.8 L H2/kg VSFW and a maximum production rate of 10.8 L H2/kg VSFW∙h. The analysis of the fermentation products indicated that the observed highest H2 production mostly derived from the typical acetate/butyrate-type fermentation

Quantification of Botrytis cinerea in Grapevine Bunch Trash by Real-Time PCR

Quantification of colonization of grape bunch trash by Botrytis cinerea is crucial for Botrytis bunch rot (BBR) control. A previously developed quantitative polymerase chain reaction (qPCR) method was adapted to quantify B. cinerea DNA in grape bunch trash, and a colonization coefficient (CC) was calculated as the ratio between the DNA concentrations of B. cinerea and of Vitis vinifera. CC values increased linearly with the number of conidia of B. cinerea or the quantity of mycelium of B. cinerea added to the bunch trash increased. CC values also increased linearly in bunch trash samples containing increasing percentages of B. cinerea-colonized bunch trash; in the latter samples, CC values were correlated with subsequent assessments of B. cinerea colonization of trash (as determined by plating on agar) and sporulation on the trash (as determined by spore counts after incubation in humid chambers). The qPCR assay was also validated using trash collected from bunches treated or not treated with fungicides in three vineyards in two seasons. CC values reflected the reduction in sporulation and in latent infections of mature berries caused by fungicide application. The qPCR assay enables rapid, specific, sensitive, and reliable quantification of the degree of colonization of bunch trash by B. cinerea, which makes it a useful tool for studies of the epidemiology and management of BBR

Dermacentor marginatus and Dermacentor reticulatus, and Their Infection by SFG Rickettsiae and Francisella-Like Endosymbionts, in Mountain and Periurban Habitats of Northwestern Italy

We investigated the distribution of Dermacentor spp. and their infection by zoonotic bacteria causing SENLAT (scalp eschar neck lymphadenopathy) in Turin province, northwestern Italy. We collected ticks in a mountain and in a periurban park, from vegetation and different animal sources, and we sampled tissues from wild boar. Dermacentor marginatus (n = 121) was collected in both study areas, on vegetation, humans, and animals, while D. reticulatus (n = 13) was exclusively collected on wild boar from the periurban area. Rickettsia slovaca and Candidatus Rickettsia rioja infected 53.1% of the ticks, and R. slovaca was also identified in 11.3% of wild boar tissues. Bartonella spp. and Francisella tularensis were not detected, however, Francisella-like endosymbionts infected both tick species (9.2%). Our findings provide new insights on the current distribution of Dermacentor spp. and their infection with a spotted-fever group rickettsiae in the Alps region. Wild boar seem to play a major role in their eco-epidemiology and dispersion in the study area. Although further studies are needed to assess the burden of rickettsial diseases, our results highlight the risk of contracting SENLAT infection through Dermacentor spp. bites in the region

Screening of environmental yeasts for the fermentative production of arabitol from lactose and glycerol

Arabitol is a sugar alcohol, stereoisomer to xylitol, which is enlisted among the main target for biorefineries. It can serve as low calorie sweetener and as building block in the enantiopure synthesis of immunosuppressive glycolipids, herbicides, and drugs. Several studies described the fermentative production of arabitol by osmophilic yeasts, cultured with high concentrations of D-glucose. The utilization of cheaper carbon sources, such as glycerol or lactose, is of great interest for biorefinery implementation, but information on exploitation to arabitol production is still scarce. In the present study 50 yeasts belonging to 24 ascomycetous species were screened for the ability to grow and produce arabitol in presence of 80 g/L lactose or glycerol. Production from lactose was generally unsuccessful, the best producer being Kluyveromyces lactis WC 1401 with 0.94 g/L in 160 h. Production from glycerol was promising, with Zygosaccharomyces rouxii WC 1206, Pichia guilliermondii CBS 566, Hansenula anomala WC 1501, and Candida freyschussii ATCC 18737 yielding 3 to 4.5 g/L arabitol, with conversion yield (YP/S) ranging from 11 to 21.7%. Batch growth with high initial glycerol amount (160 g/L) resulted in higher production, with H. anomala WC 1501 yielding 10.0 g/L arabitol (YP/S = 12%) in 160 h. Preliminary bioreactor fermentations with H. anomala WC 1501 indicated that production is not growth associated and revealed some major parameters affecting production, such as the pH and the C:N ratio, that will be the target of following studies aiming at process optimization. Cultivation under controlled oxygenation (DOT = 20%) and pH (= 3.0) resulted in improvement in the performance of H. anomala WC 1501, yielding 16.1 g/L arabitol. Cultivation in a medium with high C:N ratio, lacking inorganic nitrogen yielded 17.1 g/L arabitol. Therefore, this strain was selected for the development of a fed-batch process, aiming to improve the efficiency of the biomass, generated in the growth phase, and increasing the production in the stationary phase

analysis of brain nmr images for age estimation with deep learning

Abstract During the last decade, deep learning and Convolutional Neural Networks (CNNs) have produced a devastating impact on computer vision, yielding exceptional results on a variety of problems, including analysis of medical images. Recently, these techniques have been extended to 3D images with the downside of a large increase in the computational load. In particular, state-of-the-art CNNs have been used for brain Nuclear Magnetic Resonance (NMR) imaging, with the aim of estimating the patients' age. In fact, a large discrepancy between the real and the estimated age is a clear alarm for the onset of neurodegenerative diseases, such as some types of early dementia and Alzheimer's disease. In this paper, we propose an effective alternative to 3D convolutions that guarantees a significant reduction of the computational requirements for this kind of analysis. The proposed architectures achieve comparable results with the competitor 3D methods, requiring only a fraction of the training time and GPU memory