A Copula-Based Joint Model of Commute Mode Choice and Number of Non-Work Stops during the Commute

At the time of publication A. Portoghese, E. Spissu, and I. Meloni were at University of Cagliari, and C.R. Bhat and N. Eluru were at the University of Texas at Austin.In this paper, in the spirit of a tour-based frame of analysis, we examine the commute mode choice and the number of non-work stops during the commute. Understanding the mode and activity stop dimensions of weekday commute travel is important since the highest level of weekday traffic congestion in urban areas occurs during the commute periods. The paper employs a copula-based joint multinomial logit – ordered modeling framework in which commute mode choice is modeled using a multinomial logit formulation and the number of commute stops is modeled using an ordered response formulation. The data used in this study are drawn from the “Time use” multipurpose survey conducted between 2002 and 2003 by the Turin Town Council and the Italian National Institute of Statistics (ISTAT) in the Greater Turin metropolitan area of Italy. The results highlight the importance of accommodating the inter-relationship between commute mode choice and commute stops behavior. The results also point to the stronger effect of household responsibilities and demographic characteristics in the Italian context compared to the US context.Civil, Architectural, and Environmental Engineerin

Modeling the impacts of volumetric water pricing in irrigation districts with conjunctive use of surface and groundwater resources

Water pricing has been identified as a generally valid water supply policy to help solve problems of water scarcity and competition. As for the non-agricultural sectors, in the last three decades water pricing has been widely discussed in and promoted with regard to the irrigation management, though in the actual practice its effectiveness is quite controversial. This is particularly true in semi-arid regions, where conjunctive use of collective facilities and on-farm groundwater pumps may cause conflicts and mismanagement of water resources. Under such circumstances, irrigation water pricing policies are not easy to deploy and implement effectively, due to potential occurrence of side and unintended effects. In this framework, the present work aims at investigating the impact at the district scale of water pricing policies, on both surface water (SW) and groundwater (GW) resources. In this regard, a model which deals with the analysis of farmers' decision concerning water source selection is proposed. The analysis is carried out keeping capital asset as given, also with the aim to elicit the relevance of on-farm irrigation water cost on resources use during the irrigation season. Reference is made to an intensive agricultural district in Southern Italy, conjunctively supplied by collective schemes managed by the local irrigation board and on-farm individual groundwater pumping systems. The proposed model was built along with local stakeholders, in order to (i) underline the relationship between the water tariff applied for collective supply service and the irrigation source selection during the irrigation season; and (ii) the relevance of the conjunctive use of GW based on pumping cost convenience and service standards needed to fulfill the irrigation requirements. The results have been then integrated into a quantitative water balance model, and a scenario analysis used to show the potential side impacts that a restrictive SW tariff policy applied during drought periods may have on the GW state, in different hydrological conditions

Radiation Tolerance of Nanocrystal-Based Flash Memory Arrays Against Heavy Ion Irradiation

We present new results on heavy-ion irradiation of nanocrystal non-volatile addressable memory arrays. We show that the effects of a single ion hit are negligible on these devices due to the discrete nature of the storage sites. We estimate that, in order to observe an appreciable threshold voltage shift, at least three-four ion hit are needed. Despite several cells experienced multiple hits they are still functional after the irradiation, showing no changes on the retention characteristics. These results highlights an outstanding improvement of the nanocrystal technology over the conventional floating gate memories in terms of radiation tolerance, which are encouraging for a potential application in radiation-harsh environments

Appraising water and nutrient recovery for perennial crops irrigated with reclaimed water in Mediterranean areas through an index-based approach

The use of reclaimed water for agricultural irrigation is among the agronomic practices being increasingly valued by policy-makers, water planners, and regulators to pursue more sustainable resource management in many arid and semi-arid agricultural production areas worldwide. This practice can make additional supply available in water-scarce areas, provide crop nutrients, and reduce the disposal of wastewater to the environment, thus providing considerable agronomic and environmental benefits. However, the process for treated wastewater reuse is complex because of multiple interactions among technical, economic, environmental, and public health related aspects. In this context, the application of quantitative indices capturing agronomic, engineering, and environmental factors and their possible inter-relations enable to appraise the potential benefits and risks of treated wastewater reuse at individual project¿s scale and for regional policies. The present article describes a quantitative approach that utilizes a set of proposed indices to characterize various aspects affecting water and nutrient recovery for specific combinations between the characteristics of the treatment facility and the attributes of the irrigation district supplied with reclaimed water. The proposed index-based approach was tested on datasets collected for 11 pilot reuse schemes located in the Apulia region of southern Italy with the aim to evaluate the potential for water and nutrient recovery resulting from irrigation with reclaimed water. Results from the data analysis and interpretation showed that the proposed indices enabled to quantify the environmental benefits of irrigation with RW that leads to divert less freshwater from conventional sources and dispose less reclaimed water into natural water receptors, as well as the agronomic advantages of using RW, which can partially fulfill the irrigation and nutrient requirements for the supplied districts' service areas. Overall, the proposed set of indices can provide valuable information for the successful implementation of water reuse policies for irrigated agriculture.This research was co-funded by the Regione Puglia as the project “Sistema innovativo di monitoraggio e trattamento delle acque reflue per il miglioramento della compatibilità ambientale ai fini di un'agricoltura sostenibile” - SMART WATER (No. 5ABY6P0) through the INNONETWORK CALL 201

Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardware availability while still achieving accurate segmentation. We apply these models to a limited set of 85 manual prostate segmentations using the k-fold validation strategy and the Tversky loss function and we compare their results. We find that ENet and UNet are more accurate than ERFNet, with ENet much faster than UNet. Specifically, ENet obtains a dice similarity coefficient of 90.89% and a segmentation time of about 6 s using central processing unit (CPU) hardware to simulate real clinical conditions where graphics processing unit (GPU) is not always available. In conclusion, ENet could be efficiently applied for prostate delineation even in small image training datasets with potential benefit for patient management personalization

An Insight into the Emergency Preparedness and Coping Capacity of Italian Water Utilities

The present work provides an insight into the emergency preparedness and coping capacity of Italian water utilities, based on the results of two ongoing research projects. Specific attention is given to the role that Water Safety Plans (WSPs) may have in this framework. The results of an online survey completed with a wide sample of Italian water utilities have been integrated with the evidence from targeted in-depth interviews, with the aim of: (i) characterizing the state of implementation of WSPs in Italy; (ii) identifying the main challenges, barriers and opportunities; (iii) describing the key issues related to the interactions among different institutions. A critical summary of the main evidence was structured in the form of a SWOT analysis