Environmental Assessment of the Agricultural Sector

One of the main problems recognized in sustainable development goals and sustainable agricultural objectives is Climate change. Farming contributes significantly to the overall Greenhouse gases (GHG) in the atmosphere, which is approximately 10-12 percent of total GHG emissions, but when taking in consideration also land-use change, including deforestation driven by agricultural expansion for food, fiber and fuel the number rises to approximately 30 percent (Smith et. al., 2007). There are two distinct methodological approaches for environmental impact assessment; Life Cycle Assessment (a bottom up approach) and Input-Output Analysis (a top down approach). The two methodologies differ significantly but there is not an immediate choice between them if the scope of the study is on a sectorial level. Instead, as an alternative, hybrid approaches which combine these two approaches have emerged. The aim of this study is to analyze in a greater detail the agricultural sectors contribution to Climate change caused by the consumption of food products. Hence, to identify the food products that have the greatest impact through their life cycle, identifying their hotspots and evaluating the mitigation possibilities for the same. At the same time evaluating methodological possibilities and models to be applied for this purpose both on a EU level and on a country level (Italy).

Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

Statistical analysis of the error associated with the simplification of the stratigraphy in geotechnical models

The uncertainties in the determination of the stratigraphic profile of natural soils is one of the main problems in geotechnics, in particular for landslide characterization and modeling. The study deals with a new approach in geotechnical modeling which relays on a stochastic generation of different soil layers distributions, following a boolean logic – the method has been thus called BoSG (Boolean Stochastic Generation). In this way, it is possible to randomize the presence of a specific material interdigitated in a uniform matrix. In the building of a geotechnical model it is generally common to discard some stratigraphic data in order to simplify the model itself, assuming that the significance of the results of the modeling procedure would not be affected. With the proposed technique it is possible to quantify the error associated with this simplification. Moreover, it could be used to determine the most significant zones where eventual further investigations and surveys would be more effective to build the geotechnical model of the slope. The commercial software FLAC was used for the 2D and 3D geotechnical model. The distribution of the materials was randomized through a specifically coded MatLab program that automatically generates text files, each of them representing a specific soil configuration. Besides, a routine was designed to automate the computation of FLAC with the different data files in order to maximize the sample number. The methodology is applied with reference to a simplified slope in 2D, a simplified slope in 3D and an actual landslide, namely the Mortisa mudslide (Cortina d’Ampezzo, BL, Italy). However, it could be extended to numerous different cases, especially for hydrogeological analysis and landslide stability assessment, in different geological and geomorphological contexts.

A Web GIS Decision Support System For Coastal Risk Assessment and Mitigation Planning

Coastal flooding poses serious threats to coastal areas around the world, billions of dollars in damage to property and infrastructure, and threatens the lives of millions of people. Therefore, disaster management and risk assessment aims at detecting vulnerability and capacities in order to reduce coastal flood disaster risk. In particular, non-specialized researchers, emergency management personnel, and land use planners require an accurate, inexpensive method to determine and map risk associated with storm surge events and long-term sea level rise associated with climate change. This study contributes to the spatially evaluation and mapping of social-economic-environmental vulnerability and risk at sub-national scale through the development of appropriate tools and methods successfully embedded in a Web-GIS Decision Support System. A new set of raster-based models were studied and developed in order to be easily implemented in the Web-GIS framework with the purpose to quickly assess and map flood hazards characteristics, damage and vulnerability in a Multi-criteria approach. The Web-GIS DSS is developed recurring to open source software and programming language and its main peculiarity is to be available and usable by coastal managers and land use planners without requiring high scientific background in hydraulic engineering. The effectiveness of the system in the coastal risk assessment is evaluated trough its application to a real case study.

Rapid assessment of internodal myelin integrity in central nervous system tissue

Monitoring pathology/regeneration in experimental models of de-/remyelination requires an accurate measure not only of functional changes but also of the amount of myelin. We tested whether X-ray diffraction (XRD), which measures periodicity in unfixed myelin, can assess the structural integrity of myelin in fixed tissue. From laboratories involved in spinal cord injury research and in studying the aging primate brain, we solicited "blind" samples and used an electronic detector to record rapidly the diffraction patterns (30 min each pattern) from them. We assessed myelin integrity by measuring its periodicity and relative amount. Fixation of tissue itself introduced +/-10% variation in periodicity and +/-40% variation in relative amount of myelin. For samples having the most native-like periods, the relative amounts of myelin detected allowed distinctions to be made between normal and demyelinating segments, between motor and sensory tracts within the spinal cord, and between aged and young primate CNS. Different periodicities also allowed distinctions to be made between samples from spinal cord and nerve roots and between well-fixed and poorly fixed samples. Our findings suggest that, in addition to evaluating the effectiveness of different fixatives, XRD could also be used as a robust and rapid technique for quantitating the relative amount of myelin among spinal cords and other CNS tissue samples from experimental models of de- and remyelination.

Numerical assessment on the effective mechanical stimuli for matrix-associated metabolism in chondrocyte-seeded constructs

The self-regeneration capacity of articular cartilage is limited, due to its avascular and aneural nature. Loaded explants and cell cultures demonstrated that chondrocyte metabolism can be regulated via physiologic loading. However, the explicit ranges of mechanical stimuli that correspond to favourable metabolic response associated with extracellular matrix (ECM) synthesis are elusive. Unsystematic protocols lacking this knowledge produce inconsistent results. This study aims to determine the intrinsic ranges of physical stimuli that increase ECM synthesis and simultaneously inhibit nitric oxide (NO) production in chondrocyte-agarose constructs, by numerically re-evaluating the experiments performed by Tsuang et al. (2008). Twelve loading patterns were simulated with poro-elastic finite element models in ABAQUS. Pressure on solid matrix, von Mises stress, maximum principle stress and pore pressure were selected as intrinsic mechanical stimuli. Their development rates and magnitudes at the steady state of cyclic loading were calculated with MATLAB at the construct level. Concurrent increase in glycosaminoglycan and collagen was observed at 2300 Pa pressure and 40 Pa/s pressure rate. Between 0-1500 Pa and 0-40 Pa/s, NO production was consistently positive with respect to controls, whereas ECM synthesis was negative in the same range. A linear correlation was found between pressure rate and NO production (R = 0.77). Stress states identified in this study are generic and could be used to develop predictive algorithms for matrix production in agarose-chondrocyte constructs of arbitrary shape, size and agarose concentration. They could also be helpful to increase the efficacy of loading protocols for avascular tissue engineering. Copyright (c) 2010 John Wiley \& Sons, Ltd.

Assessment Of Dynamic Properties Of A Crowd Model For Human-Structure Interaction Modeling

As lightweight and slender structural elements are more frequently used in the design, large scale structures become more flexible and susceptible to excessive vibrations. To ensure the functionality of the structure, dynamic properties of the occupied structure need to be estimated during the design phase. Traditional analysis method models occupants simply as an additional mass; however, research has shown that human occupants could be better modeled as an additional degree-of- freedom. In the United Kingdom, active and passive crowd models are proposed by the Joint Working Group as a result of a series of analytical and experimental research. It is expected that the crowd models would yield a more accurate estimation to the dynamic response of the occupied structure. However, experimental testing recently conducted through a graduate student project at Bucknell University indicated that the proposed passive crowd model might be inaccurate in representing the impact on the structure from the occupants. The objective of this study is to provide an assessment of the validity of the crowd models proposed by JWG through comparing the dynamic properties obtained from experimental testing data and analytical modeling results. The experimental data used in this study was collected by Firman in 2010. The analytical results were obtained by performing a time-history analysis on a finite element model of the occupied structure. The crowd models were created based on the recommendations from the JWG combined with the physical properties of the occupants during the experimental study. During this study, SAP2000 was used to create the finite element models and to implement the analysis; Matlab and ME¿scope were used to obtain the dynamic properties of the structure through processing the time-history analysis results from SAP2000. The result of this study indicates that the active crowd model could quite accurately represent the impact on the structure from occupants standing with bent knees while the passive crowd model could not properly simulate the dynamic response of the structure when occupants were standing straight or sitting on the structure. Future work related to this study involves improving the passive crowd model and evaluating the crowd models with full-scale structure models and operating data.

Simulator training on pulsatile vascular models significantly improves surgical skills and the quality of carotid patch plasty

Vascular surgeons perform numerous highly sophisticated and delicate procedures. Due to restrictions in training time and the advent of endovascular techniques, new concepts including alternative environments for training and assessment of surgical skills are required. Over the past decade, training on simulators and synthetic models has become more sophisticated and lifelike. This study was designed to evaluate the impact of a 3-day intense training course in open vascular surgery on both specific and global vascular surgical skills.

In Vitro and In Vivo Imaging Characteristics Assessment of Polymeric Coils Compared with Standard Platinum Coils for the Treatment of Intracranial Aneurysms

BACKGROUND AND PURPOSE:Conventional platinum coils cause imaging artifacts that reduce imaging quality and therefore impair imaging interpretation on intraprocedural or noninvasive follow-up imaging. The purpose of this study was to evaluate imaging characteristics and artifact production of polymeric coils compared with standard platinum coils in vitro and in vivo.MATERIALS AND METHODS:Polymeric coils and standard platinum coils were evaluated in vitro with the use of 2 identical silicon aneurysm models coiled with a packing attenuation of 20% each. DSA, flat panel CT, CT, and MR imaging were performed. In vivo evaluation of imaging characteristics of polymeric coils was performed in experimentally created rabbit carotid bifurcation aneurysms. DSA, CT/CTA, and MR imaging were performed after endovascular treatment of the aneurysms. Images were evaluated regarding visibility of individual coils, coil mass, artifact production, and visibility of residual flow within the aneurysm.RESULTS:Overall, in vitro and in vivo imaging showed relevantly reduced artifact production of polymeric coils in all imaging modalities compared with standard platinum coils. Image quality of CT and MR imaging was improved with the use of polymeric coils, which permitted enhanced depiction of individual coil loops and residual aneurysm lumen as well as the peri-aneurysmal area. Remarkably, CT images demonstrated considerably improved image quality with only minor artifacts compared with standard coils. On DSA, polymeric coils showed transparency and allowed visualization of superimposed vessel structures.CONCLUSIONS:This initial experimental study showed improved imaging quality with the use of polymeric coils compared with standard platinum coils in all imaging modalities. This might be advantageous for improved intraprocedural imaging for the detection of complications and posttreatment noninvasive follow-up imaging.

Assessment of Alcohol Reward in Prairie Voles (Microtus ochrogaster)

The purpose of our study was to assess whether prairie voles find alcohol rewarding. Prairie voles have recently become a species of interest for alcohol studies, which have traditionally used other rodent model species including several different strains of mice and rats. The prairie vole is one of only two known rodent species that readily administers high levels of unsweetened alcohol, implicating it as a potentially effective animal model for studying alcohol abuse. However, voluntary consumption does not necessarily imply that prairie voles find it rewarding. Therefore the purpose of our study was to investigate if alcohol has rewarding properties for prairie voles using three different approaches: place conditioning, flavor conditioning, and immunohistochemistry. Furthermore, we sought to characterize their reward profile and compare it to other commonly used rodent models ¿ C57BL/6 mice, DBA/2J mice, and Sprague-Dawley rats. Place and flavor conditioning are behavioral methods that rely on the learned association between a stimulus and the effects of a drug; the drug of interest in these studies is alcohol. To assess whether prairie voles will demonstrate a conditioned preference for alcohol-paired stimuli, seven place conditioning studies were run that investigated a range of different doses, individual conditioning session durations, and trial durations. Video analysis revealed no difference in the amount of time spent on the alcohol-paired floor, suggesting no conditioned place preference for alcohol. Two flavor conditioning tests were conducted to assess whether voles would demonstrate a preference for an alcohol-paired flavored saccharin solution. Voles demonstrated reduced consumption of the alcohol-paired flavored saccharin solution, regardless of dose or flavor, when alcohol administration occurred after conditioning sessions (p=<0.001). When alcohol was administered before conditioning sessions, no difference in consumption of the alcohol-paired and saline-paired flavored saccharin solutions was seen (p=0.545). Previous studies that have documented similar behavior have hypothesized that this is an example of an anticipatory contrast effect. This theory proposes that prairie voles reduce their intake of a hedonic solution (flavored saccharin solution) in anticipation of later drug administration (alcohol). However, conditioning-based behavioral methods of studying alcohol reward are highly sensitive to the parameters of the conditioned stimulus, thus it is possible that voles will not show preference for alcohol-related stimuli, even if they do find alcohol rewarding. Immunohistochemical analysis supplemented this behavioral data by allowing us to identify specific neural regions that were directly activated in response to the acute administration of alcohol. No difference in the number of activated c-Fos neurons in the Nucleus Accumbens (NAc) core or shell was seen (p=0.3364; p=0.6698) in animals that received an acute injection of alcohol or saline. There was a significant increase in the number of activated c-Fos neurons in the Paraventricular Nucleus of the Hypothalamus (PVN) in alcohol-treated animals compared to saline-treated animals (p=0.0034). There was no difference in the pixel count of activated c-Fos neurons or in the % area activated in the Arcuate Nucleus between alcohol and saline-treated animals (p=0.4523; p=0.3304). In conclusion, the place conditioning studies that were conducted in this thesis suggest that prairie voles do not demonstrate preference or aversion towards alcohol-paired stimuli. The flavor conditioning studies suggest that prairie voles do not demonstrate aversion but rather avoidance of the alcohol-paired flavor in anticipation of future alcohol administration. The preliminary immunohistochemical data collected is inconclusive but cannot rule out the possibility of neuronal activation patterns indicative of reward. Taken together, our data indicate that prairie voles hav

Sensitivity Analysis for the Assessment of Causal Vaccine Effects on Viral Load in HIV Vaccine Trials

Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias.

Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.