Mesocosm‐based simulations to optimize a bioremediation strategy for the effective restoration of wildfire‐impacted soils contaminated with high‐molecular‐weight hydrocarbons

Aims: We obtained four microbial isolates from soil exposed to forest fire and evaluated their potential bioremediation activity when combined with a biosurfactant-producing bacterial strain for the decontamination of wildfire-impacted soil polluted with high-molecular-weight (HMW) hydrocarbons. Methods and Results: We established mesocosm trials to compare three bioremediation strategies: natural attenuation, bioaugmentation and biostimulation. Chemical analysis, culture-dependent and culture-independent methods were used to evaluate the bioremediation efficiency and speciation of the microbial cenoses based on these approaches. After treatment for 90 days, bioaugmentation removed 75·2–75·9% of the HMW hydrocarbons, biostimulation removed 63·2–69·5% and natural attenuation removed ~22·5%. Hydrocarbon degradation was significantly enhanced in the mesocosm supplemented with the biosurfactant-producing bacterial strain after 20 and 50 days of treatment compared to the other bioremediation strategies. Conclusions: We found that the bioaugmentation approach was more effective than biostimulation and natural attenuation for the removal of HMW hydrocarbons from fire-impacted soil. Significance and Impact of the Study: Our study showed that micro-organisms from wildfire-impacted soil show significant potential for bioremediation, and that biosurfactant-producing bacterial strains can be combined with them as part of an effective bioremediation strategy

Combining exposure indicators and predictive analytics for threats detection in real industrial IoT sensor networks

We present a framework able to combine exposure indicators and predictive analytics using AI-tools and big data architectures for threats detection inside a real industrial IoT sensors network. The described framework, able to fill the gaps between these two worlds, provides mechanisms to internally assess and evaluate products, services and share results without disclosing any sensitive and private information. We analyze the actual state of the art and a possible future research on top of a real case scenario implemented into a technological platform being developed under the H2020 ECHO project, for sharing and evaluating cybersecurity relevant informations, increasing trust and transparency among different stakeholders

Gaugino Mass Nonuniversality and Dark Matter in SUGRA, Strings and D Brane Models

The effects of nonuniversality of gaugino masses on dark matter are examined within supersymmetric grand unification, and in string and D brane models with R parity invariance. In SU(5) unified models nonuniversality in the gaugino sector can be generated via the gauge kinetic energy function which may depend on the 24, 75 and 200 dimensional Higgs representations. We also consider string models which allow for nonuniversality of gaugino masses and D brane models where nonuniversality arises from embeddings of the Standard Model gauge group on five branes and nine branes. It is found that with gaugino mass nonuniversality the range of the LSP mass can be extended much beyond the range allowed in the universal SUGRA case, up to about 600 GeV even without coannihilation effects in some regions of the parameter space. The effects of coannihilation are not considered and inclusion of these effects may further increase the allowed neutralino mass range. Similarly with the inclusion of gaugino mass nonuniversality, the neutralino-proton ($\chi -p$) cross-section can increase by as much as a factor of 10 in some of regions of the parameter space. An analysis of the uncertainties in the quark density content of the nucleon is given and their effects on $\chi -p$ cross-section are discussed. The predictions of our analysis including nonuniversality is compared with the current limits from dark matter detectors and implications for future dark matter searches are discussed.Comment: Revised version, 23 pages, Latex, and 7 figure

Italian network for obesity and cardiovascular disease surveillance: A pilot project

<p>Abstract</p> <p>Background</p> <p>Also in Mediterranean countries, which are considered a low risk population for cardiovascular disease (CVD), the increase in body mass index (BMI) has become a public health priority. To evaluate the feasibility of a CVD and obesity surveillance network, forty General Practitioners (GPs) were engaged to perform a screening to assess obesity, cardiovascular risk, lifestyle habits and medication use.</p> <p>Methods</p> <p>A total of 1,046 women and 1,044 men aged 35–74 years were randomly selected from GPs' lists stratifying by age decade and gender. Anthropometric and blood pressure measurements were performed by GPs using standardized methodologies. BMI was computed and categorized in normal weight (BMI 18.5–24.9 kg/m²), overweight (BMI 25.0–29.9 kg/m²) and obese (BMI ≥ 30 kg/m²). Food frequency (per day: fruits and vegetables; per week: meat, cheese, fish, pulses, chocolate, fried food, sweet, wholemeal food, rotisserie food and sugar drink) and physical activity (at work and during leisure time) were investigated through a questionnaire. CVD risk was assessed using the Italian CUORE Project risk function.</p> <p>Results</p> <p>The percentage of missing values was very low. Prevalence of overweight was 34% in women and 50% in men; prevalence of obesity was 23% in both men and women. Level of physical activity was mostly low or very low. BMI was inversely associated with consumption of pulses, rotisserie food, chocolate, sweets and physical activity during leisure time and directly associated with consumption of meat. Mean value of total cardiovascular risk was 4% in women and 11% in men. One percent of women and 16% of men were at high cardiovascular risk (≥ 20% in 10 years). Normal weight persons were four times more likely to be at low risk than obese persons.</p> <p>Conclusion</p> <p>This study demonstrated the feasibility of a surveillance network of GPs in Italy focusing on obesity and other CVD risk factors. It also provided information on lifestyle habits, such as diet and physical activity.</p

Track reconstruction and matching between emulsion and silicon pixel detectors for the SHiP-charm experiment

In July 2018 an optimization run for the proposed charm cross section measurement for SHiP was performed at the CERN SPS. A heavy, moving target instrumented with nuclear emulsion films followed by a silicon pixel tracker was installed in front of the Goliath magnet at the H4 proton beam-line. Behind the magnet, scintillating-fibre, drift-tube and RPC detectors were placed. The purpose of this run was to validate the measurement's feasibility, to develop the required analysis tools and fine-tune the detector layout. In this paper, we present the track reconstruction in the pixel tracker and the track matching with the moving emulsion detector. The pixel detector performed as expected and it is shown that, after proper alignment, a vertex matching rate of 87% is achieved.Peer Reviewe

The SHiP experiment at the proposed CERN SPS Beam Dump Facility

The Search for Hidden Particles (SHiP) Collaboration has proposed a general-purpose experimental facility operating in beam-dump mode at the CERN SPS accelerator to search for light, feebly interacting particles. In the baseline configuration, the SHiP experiment incorporates two complementary detectors. The upstream detector is designed for recoil signatures of light dark matter (LDM) scattering and for neutrino physics, in particular with tau neutrinos. It consists of a spectrometer magnet housing a layered detector system with high-density LDM/neutrino target plates, emulsion-film technology and electronic high-precision tracking. The total detector target mass amounts to about eight tonnes. The downstream detector system aims at measuring visible decays of feebly interacting particles to both fully reconstructed final states and to partially reconstructed final states with neutrinos, in a nearly background-free environment. The detector consists of a 50 m long decay volume under vacuum followed by a spectrometer and particle identification system with a rectangular acceptance of 5 m in width and 10 m in height. Using the high-intensity beam of 400 GeV protons, the experiment aims at profiting from the 4 x 10(19) protons per year that are currently unexploited at the SPS, over a period of 5-10 years. This allows probing dark photons, dark scalars and pseudo-scalars, and heavy neutral leptons with GeV-scale masses in the direct searches at sensitivities that largely exceed those of existing and projected experiments. The sensitivity to light dark matter through scattering reaches well below the dark matter relic density limits in the range from a few MeV/c(2) up to 100 MeV-scale masses, and it will be possible to study tau neutrino interactions with unprecedented statistics. This paper describes the SHiP experiment baseline setup and the detector systems, together with performance results from prototypes in test beams, as it was prepared for the 2020 Update of the European Strategy for Particle Physics. The expected detector performance from simulation is summarised at the end