Microbial diversity in innovative mesophilic/thermophilic temperature-phased anaerobic digestion of sludge

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Rainfall-induced differential settlements of foundations on heterogeneous unsaturated soils

This study stochastically investigates the rainfall-induced differential settlement of a centrally loaded, rigid strip foundation on an unsaturated soil with spatially varying values of either preconsolidation stress or porosity. The differential settlement (between the two foundation ends) is calculated at various times during rainfall by way of a coupled, hydro-mechanical, finite-element analysis. The Barcelona basic model describes the mechanical behaviour of the soil, and the van Genuchten relationships describe water retention and permeability. The variability of soil properties is modelled by means of random fields with spatial correlation in the framework of a Monte Carlo simulation. The study demonstrates that the occurrence of rainfall-induced differential settlements can be consistently analysed using concepts of unsaturated soil mechanics and random field theory. Results show that differential settlements can be vastly underpredicted (or even completely missed) if random heterogeneity and partial saturation are not simultaneously considered. The variation of differential settlements and their statistics during the rainfall depend on the magnitude of the applied load and the statistics of soil variability. Moreover, the transient phase of infiltration and a spatial correlation length equal to the width of the foundation pose the highest risk of differential settlement

Genetic Diversity of Pseudomonas syringae pv. actinidiae Strains from Different Geographic Regions in China

Pseudomonas syringae pv. actinidiae causes kiwifruit bacterial canker, with severe infection of the kiwifruit plant resulting in heavy economic losses. Little is known regarding the biodiversity and genetic variation of populations of P. syringae pv. actinidiae in China. A collection of 269 strains of P. syringae pv. actinidiae was identified from 300 isolates obtained from eight sampling sites in five provinces in China. The profiles of 50 strains of P. syringae pv. actinidiae and one strain of P. syringae pv. actinidifoliorum were characterized by Rep-, insertion sequences 50, and randomly amplified polymorphic DNA polymerase chain reaction (PCR). Discriminant analysis of principal coordinates, principal component analysis, and hierarchical cluster analysis were used to analyze the combined fingerprints of the different PCR assays. The results revealed that all isolates belonged to the Psa3 group, that strains of P. syringae pv. actinidiae from China have broad genetic variability that was related to source geographic region, and that Chinese strains can be readily differentiated from strains from France but are very similar to those from Italy. Multilocus sequence typing of 24 representative isolates using the concatenated sequences of five housekeeping genes (cts, gapA, gyrB, pfk, and rpoD) demonstrated that strain Jzhy2 from China formed an independent clade compared with the other biovars, which possessed the hopH1 effector gene but lacked the hopA1 effector gene. A constellation analysis based on the presence or absence of the four loci coding for phytotoxins and a cluster analysis based on the 11 effector genes showed that strains from China formed two distinct clades. All of the strains, including K3 isolated in 1997 from Jeju, Korea, lacked the cfl gene coding for coronatine. In contrast, the tox-argK gene cluster coding for phaseolotoxin was detected in K3 and in the biovar 1 strains (K3, Kw30, and Psa92), and produced a false-positive amplicon for the hopAM1-like gene in this study. To date, only one biovar (biovar 3) is represented by the strains of P. syringae pv. actinidiae from China, despite China being the center of origin for kiwifruit

Towards specific T–H relationships: FRIBAS database for better characterization of RC and URM buildings

FRIBAS database is an open access database composed of the characteristics of 312 buildings (71 masonry, 237 reinforced concrete and 4 mixed types). It collects and harmonizes data from different surveys performed on buildings in the Basilicata and Friuli Venezia Giulia regions (Southern and Northeastern Italy, respectively). Each building is defined by 37 parameters related to the building and foundation soil characteristics. The building and soil fundamental periods were experimentally estimated based on ambient noise measurements. FRIBAS gave us the opportunity to study the influence of the main characteristics of buildings and the soil-building interaction effect to their structural response. In this study, we have used the FRIBAS dataset to investigate how the building period varies as a function of construction materials and soil types. Our results motivate the need of going beyond a 'one-fits-all' numerical period-height (T-H) relationship for generic building typologies provided by seismic codes, towards specific T-H relationships that account for both soil and building typologies

Geological and geophysical characterization of the southeastern side of the High Agri Valley (southern Apennines, Italy)

Abstract. In the frame of a national project funded by Eni S.p.A. and developed by three institutes of the National Research Council (the Institute of Methodologies for Environmental Analysis, the Institute of Research for Hydrogeological Protection and the Institute for Electromagnetic Sensing of the Environment), a multidisciplinary approach based on the integration of satellite, aero-photogrammetric and in situ geophysical techniques was applied to investigate an area located in the Montemurro territory in the southeastern sector of the High Agri Valley (Basilicata Region, southern Italy). This paper reports the results obtained by the joint analysis of in situ geophysical surveys, aerial photos interpretation, morphotectonic investigation, geological field survey and borehole data. The joint analysis of different data allowed us (1) to show the shallow geological and structural setting, (2) to detect the geometry of the different lithological units and their mechanical and dynamical properties, (3) to image a previously unmapped fault beneath suspected scarps/warps and (4) to characterize the geometry of an active landslide affecting the study area

Corrigendum to "Geological and geophysical characterization of the southeastern side of the High Agri Valley (southern Apennines, Italy)" published in Nat. Hazards Earth Syst. Sci., 15, 315–323, 2015

No abstract available

Using Social Networks to Estimate the Number of COVID-19 Cases: The Incident (Hidden COVID-19 Cases Network Estimation) Study Protocol

Recent literature has reported a high percentage of asymptomatic or paucisymptomatic cases in subjects with COVID-19 infection. This proportion can be difficult to quantify; therefore, it constitutes a hidden population. This study aims to develop a proof-of-concept method for estimating the number of undocumented infections of COVID-19. This is the protocol for the INCIDENT (Hidden COVID-19 Cases Network Estimation) study, an online, cross-sectional survey with snowball sampling based on the network scale-up method (NSUM). The original personal network size estimation method was based on a fixed-effects maximum likelihood estimator. We propose an extension of previous Bayesian estimation methods to estimate the unknown network size using the Markov chain Monte Carlo algorithm. On 6 May 2020, 1963 questionnaires were collected, 1703 were completed except for the random questions, and 1652 were completed in all three sections. The algorithm was initialized at the first iteration and applied to the whole dataset. Knowing the number of asymptomatic COVID-19 cases is extremely important for reducing the spread of the virus. Our approach reduces the number of questions posed. This allows us to speed up the completion of the questionnaire with a subsequent reduction in the nonresponse rate