The unseen effect of pesticides: The impact on phytobiota structure and functions

In the last years, the diffusion and implementation of next-generation sequencing and the reduction of costs raised the interest in phytyobiome studies allowing to dissect the ecological interactions regulating the holobiont. Indeed, crop plants are associated with a wide diversity of microorganisms in all their parts. Crop microbiota influences plant phenotype, growth, yield and quality by contributing to plant resistance toward diseases, plant adaptation to abiotic stresses, and plant nutrition. The association between terrestrial plants and microbes developed at least 460 million years ago, as suggested by the fossil evidence of the earliest land plants, indicating the essential role of microbes for plants. Recent studies indicate that plants actively recruit beneficial microorganisms to facilitate their adaptation to environmental conditions. Cultivation methods and disease control measures can influence plant microbiome structure and functions. Both pesticide and biological control agent applications may alter the biodiversity inside the phytobiota and suppress beneficial functions. Nonetheless, to date, the effects of disease control measures on phytobiota and their possible side consequences on plant growth, crop productivity and quality remain a neglected field of study. The present work summarizes the known effects on phytobiota providing evidence about the role of plant microbial community in determining the overall efficacy of the applied control measure and suggests that future studies on plant disease control consider also the microbe-mediated effects on plant fitness

Fatigue behavior of friction stir spot welding and riveted joints in an Al alloy

AbstractThe main aim of this study was to compare the fatigue resistance of welded joints produced by FSSW process and riveted joints of AA2024 alloy. The specimens welded with the best preliminary parameters determined by previous tensile shear tests were tested in fatigue under load control, R=0.1, at room temperature. Two welding parameter sets were used, and P-N curves (load versus cycles) were plotted, using 2×106 cycles as the fatigue life limit. A similar curve was obtained for riveted specimens. The FSSW welding procedures were carried out in a CNC milling machining and the riveted specimens were produced in accordance with aircraft industry parameters. Although the welded specimens presented almost the same results in the tensile shear tests, the results were fairly lower than those observed for riveted joints in fatigue. The main failure mode observed in the welded joints was shearing, besides some cases of crack propagation in the perpendicular load direction, while for riveted specimens occurred mainly fretting nucleation followed by crack propagation in the perpendicular load direction. The evidences of shearing and lower fatigue lives for welded specimens indicate that the joint geometry highly affects the joint properties, due probably to stress concentrators presented locally

Predicting individual differences in reading, spelling and maths in a sample of typically developing children: A study in the perspective of comorbidity

none4noopenZoccolotti P., De Luca M., Marinelli C.V., Spinelli D.Zoccolotti, P.; De Luca, M.; Marinelli, C. V.; Spinelli, D

Two Dimensional Quantum Mechanical Modeling of Nanotransistors

Quantization in the inversion layer and phase coherent transport are anticipated to have significant impact on device performance in 'ballistic' nanoscale transistors. While the role of some quantum effects have been analyzed qualitatively using simple one dimensional ballistic models, two dimensional (2D) quantum mechanical simulation is important for quantitative results. In this paper, we present a framework for 2D quantum mechanical simulation of a nanotransistor / Metal Oxide Field Effect Transistor (MOSFET). This framework consists of the non equilibrium Green's function equations solved self-consistently with Poisson's equation. Solution of this set of equations is computationally intensive. An efficient algorithm to calculate the quantum mechanical 2D electron density has been developed. The method presented is comprehensive in that treatment includes the three open boundary conditions, where the narrow channel region opens into physically broad source, drain and gate regions. Results are presented for (i) drain current versus drain and gate voltages, (ii) comparison to results from Medici, and (iii) gate tunneling current, using 2D potential profiles. Methods to reduce the gate leakage current are also discussed based on simulation results.Comment: 12 figures. Journal of Applied Physics (to appear

Conservazione e sicurezza strutturale di colonne in ghisa prodotte e montate in opera nel XIX secolo

riassunto esteso e presentazione orale al convegno Workshop IGF - Problematiche di Frattura nei Materiali per l'Ingegneria, Forni di Sopra (UD), 7/1/2010 - 9/1/201

Respiratory drive in the acute respiratory distress syndrome: pathophysiology, monitoring, and therapeutic interventions

Neural respiratory drive, i.e., the activity of respiratory centres controlling breathing, is an overlooked physiologic variable which affects the pathophysiology and the clinical outcome of acute respiratory distress syndrome (ARDS). Spontaneous breathing may offer multiple physiologic benefits in these patients, including decreased need for sedation, preserved diaphragm activity and improved cardiovascular function. However, excessive effort to breathe due to high respiratory drive may lead to patient self-inflicted lung injury (P-SILI), even in the absence of mechanical ventilation. In the present review, we focus on the physiological and clinical implications of control of respiratory drive in ARDS patients. We summarize the main determinants of neural respiratory drive and the mechanisms involved in its potentiation, in health and ARDS. We also describe potential and pitfalls of the available bedside methods for drive assessment and explore classical and more \u201cfuturistic\u201d interventions to control drive in ARDS patients

Testing the specificity of predictors of reading, spelling and maths: a new model of the association among learning skills based on competence, performance and acquisition

In a previous study (Zoccolotti et al., 2020) we examined reading, spelling, and maths skills in an unselected group of 129 Italian children attending fifth grade by testing various cognitive predictors; results showed a high degree of predictors’ selectivity for each of these three behaviors. In the present study, we focused on the specificity of the predictors by performing cross-analyses on the same dataset; i.e., we predicted spelling and maths skills based on reading predictors, reading based on maths predictors and so on. Results indicated that some predictors, such as the Orthographic Decision and the Arithmetic Facts tests, predicted reading, spelling and maths skills in similar ways, while others predicted different behaviors but only for a specific parameter, such as fluency but not accuracy (as in the case of RAN), and still others were specific for a single behavior (e.g., Visual-auditory Pseudo-word Matching test predicted only spelling skills). To interpret these results, we propose a novel model of learning skills separately considering factors in terms of competence, performance and acquisition (automatization). Reading, spelling and calculation skills would depend on the development of discrete and different abstract competences (accounting for the partial dissociations among learning disorders reported in the literature). By contrast, overlap among behaviors would be accounted for by defective acquisition in automatized responses to individual “instances”; this latter skill is item specific but domain independent. Finally, performance factors implied in task’s characteristics (such as time pressure) may contribute to the partial association among learning skills. It is proposed that this new model may provide a useful base for interpreting the diffuse presence of comorbidities among learning disorders

Green Hydrogen Production from Raw Biogas: A Techno-Economic Investigation of Conventional Processes Using Pressure Swing Adsorption Unit

This paper discusses the techno-economic assessment of hydrogen production from biogas with conventional systems. The work is part of the European project BIONICO, whose purpose is to develop and test a membrane reactor (MR) for hydrogen production from biogas. Within the BIONICO project, steam reforming (SR) and autothermal reforming (ATR), have been identified as well-known technologies for hydrogen production from biogas. Two biogases were examined: one produced by landfill and the other one by anaerobic digester. The purification unit required in the conventional plants has been studied and modeled in detail, using Aspen Adsorption. A pressure swing adsorption system (PSA) with two and four beds and a vacuum PSA (VPSA) made of four beds are compared. VPSA operates at sub-atmospheric pressure, thus increasing the recovery: results of the simulations show that the performances strongly depend on the design choices and on the gas feeding the purification unit. The best purity and recovery values were obtained with the VPSA system, which achieves a recovery between 50% and 60% at a vacuum pressure of 0.1 bar and a hydrogen purity of 99.999%. The SR and ATR plants were designed in Aspen Plus, integrating the studied VPSA model, and analyzing the behavior of the systems at the variation of the pressure and the type of input biogas. The SR system achieves a maximum efficiency, calculated on the LHV, of 52% at 12 bar, while the ATR of 28% at 18 bar. The economic analysis determined a hydrogen production cost of around 5 €/kg of hydrogen for the SR case