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Structural topology optimization (STO) is usually treated as a constrained minimization problem, which is iteratively addressed by solving the equilibrium equations for the problem under consideration. To reduce the computational effort, several reduced basis approaches that solve the equilibrium equations in a reduced space have been proposed. In this work, we apply functional principal component analysis (FPCA) to generate the reduced basis, and we couple FPCA with a gradient-based optimization method for the first time in the literature. The proposed algorithm has been tested on a large STO problem with 4.8 million degrees of freedom. Results show that the proposed algorithm achieves significant computational time savings with negligible loss of accuracy. Indeed, the density maps obtained with the proposed algorithm capture the larger features of maps obtained without reduced basis, but in significantly lower computational times, and are associated with similar values of the minimized compliance.

Intimate partner violence against women (IPVAW) is the most pervasive violation of women’s rights worldwide, causing devastating lifelong damage. Victims can suffer physical, emotional or mental health problems, and experience detrimental effects in social, psychological and relational health with their families, especially children. Due to the complexity regarding violence against women in heterosexual couples, it is important to make a clear distinction between psychological and physical mistreatment, which also includes psychological violence. This differentiation is important in determining different emotional and psychological aspects of mistreatment in order to understand the reasons why some women stay in such relationships and to explain the personality profiles of victims and perpetrators. In this short narrative review, we have combined perspectives of depth psychology and attachment theory from studies on trauma, traumatic bonds and the perpetrator/victim complex in gender violence. We have also considered the growing literature on IPVAW as it relates to the medico-legal field. Our search strategy included intimate partner violence, attachment styles, risk factors and the victim/perpetrator relationship. Distinguishing the different types of IPVAW is a necessary step in understanding the complexity, causes, correlations and consequences of this issue. Above all, it enables the implementation of effective prevention and intervention strategies.

International audience; We revisit a classical method for ecological risk assessment, the Species Sensitivity Distribution (SSD) approach, in a Bayesian nonparamet-ric framework. SSD is a mandatory diagnostic required by environmental regulatory bodies from the European Union, the United States, Australia, China etc. Yet, it is subject to much scientific criticism, notably concerning a historically debated parametric assumption for modelling species variability. Tackling the problem using nonparametric mixture models, it is possible to shed this parametric assumption and build a statistically sounder basis for SSD. We use Normalized Random Measures with Independent Increments (NRMI) as the mixing measure because they offer a greater flexibility than the Dirichlet process. Indeed, NRMI can induce a prior on the number of components in the mixture model that is less informative than the Dirichlet process. This feature is consistent with the fact that SSD practitioners do not usually have a strong prior belief on the number of components. In this short paper, we illustrate the advantage of the nonparametric SSD over the classical normal SSD and a kernel density estimate SSD on several real datasets. We summarise the results of the complete study in Kon Kam King et al. (2016), where the method is generalised to censored data and a systematic comparison on simulated data is also presented, along with a study of the clustering induced by the mixture model to examine patterns in species sensitivity.

Blood is fundamental in several care treatments and surgeries, and plays a crucial role in the health care system. It is a limited resource, as it can be produced only by donors and its shelf life is short; thus, the blood donation (BD) system aims at providing adequate supply of blood units to transfusion centers and hospitals. An effective collection of blood units from donors is fundamental for adequately feeding the entire BD system and optimizing blood usage. However, despite its relevance, donation scheduling is only marginally addressed in the literature. In this paper we consider the Blood Donation Appointment Scheduling (BDAS) problem, aiming at balancing the production of the different blood types among days in order to provide a quite constant feeding of blood units to the BD system. We propose a framework for the appointment reservation that accounts for both booked donors and donors arriving without a reservation. It consists of an offline Mixed Integer Linear Programming (MILP) model for preallocating time slots to blood types, and an online prioritization policy to assign a preallocated slot when the donor calls to make the reservation. © 2017 Elsevier B.V.

Electrospinning is affected by high variability, and an accurate setting of process parameters is fundamental for producing high quality nanofibers. This work aims at determining the optimal values of the main process parameters (polymer concentration, polymer feed rate, and voltage) as a function of the environmental factors (temperature and humidity), in order to obtain nanofibrous materials within a specific range of fiber diameter and porosity, and at the same time to minimize production defects. The response surfaces of diameter, porosity, and defects are first determined with a central composite design. These surfaces are then employed as an input for the optimization problem: diameter and porosity surfaces are used to constrain an admissible region, where the minimum of the defect surface is searched. The approach is tested on a prototype electrospinning machine. The estimated response surfaces capture the variability of the process with respect to both production parameters and environmental factors, and are capable of getting the optimal values of the process parameters. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44740.

Home Health Care (HHC) is a relatively new service that plays an important role to reduce hospitalization costs and improve the life quality for patients. Human resource planning is one of the most important processes in HHC systems, for which service providers have to deal with several operational problems, e.g., the assignment of operators to patients together with their routing process. In the literature, either these problems have been simultaneously solved, or decomposed by first solving the assignment problem and then the routing problem. In this work, we propose an alternative approach, where the decomposition is based on the First Route and Second Assign (FRSA) approach. An instance generation mechanism is developed as well, which generates instances inspired from real HHC providers, to test the proposed FRSA approach under different circumstances. Preliminary experiments show the effectiveness of the approach. © Springer International Publishing AG 2017. 3rd International Conference on Health Care Systems Engineering, HCSE 2017 -- 29 May 2017 through 31 May 2017 -- -- 210379

Studies of climate change rely on numerical outputs simulated from Global Climate Models coupling the dynamics of ocean and atmosphere (GCMs). GCMs are, however, notoriously affected by substantial systematic errors (biases), whose assessment is essential to assert the accuracy and robustness of simulated climate features. This contribution focuses on constructing a Bayesian hierarchical model for the quantification of climate model biases in a multi-model framework. The method combines information from a multi-model ensemble of GCM simulations to provide a unified assessment of the bias. It further individuates different bias components that are characterized as non-stationary spatial fields accounting for spatial dependence. The approach is illustrated based on the case of near-surface air temperature bias over the tropical Atlantic and bordering regions from a multi-model ensemble of historical simulations from the fifth phase of the Coupled Model Intercomparison Project.

Applying optimization methods to healthcare management and logistics is a developing research area with numerous studies. Specifically, facility location, staff rostering, patient allocation, and medical supply transportation are the main themes analysed. Optimization approaches have been developed for several healthcare related problems, ranging from the resource management in hospitals to the delivery of care services in a territory. However, optimization approaches can also improve other services in the health system that have been only marginally addressed, yet. One of them is the Blood Donation (BD) system, aiming at providing an adequate supply of blood to Transfusion Centres (TCs) and hospitals.

Recently, the interest of many environmental agencies is on short-term air pollution predictions referred at high spatial resolution. This permits citizens and public health decision-makers to be informed with visual and easy access to air-quality assessment. We propose a hierarchical spatiotemporal model to enable use of different sources of information to provide short-term air pollution forecasting. In particular, we combine monitoring data and numerical model output in order to obtain short-term ozone forecasts over the Emilia Romagna region where the orography plays an important role on the air pollution; thus, the elevation is also included in the model. We provide high-resolution spatial forecast maps and uncertainty associated with these predictions. The assessment of the predictive performance of the model is based upon a site-one-out cross-validation experiment.

Writing papers is an essential part of the research process. Researchers have a professional obligation of disseminating their results, making them available for others to use to enhance common scientific knowledge. Besides the fun of sharing their own ideas and views, to publish is essential in order to actually have a scientific career. Although scientific writing certainly has its own conventions and standards, I suspect there is no a unique true recipe making the trick. As a matter of fact I do not have any. However my quite long time in the academic arena has given me a pretty clear idea about how I do and do not like things done. In this paper I will be giving my personal view and rules, in the hope that sharing my own experience would do some good to others as it did for me.

A correlation between perfusion modality and vascular dilation induced by endothelial nitric oxide (NO) release has been pointed out in the literature; nevertheless, only a few studies deal with the analysis of patients treated by cardiac surgery. The aim of this work is to analyze endothelial NO release in patients undergoing cardiac surgery under continuous flow cardiopulmonary bypass (CPB) or pulsatile perfusion. Pulsatile devices approved for clinical CPB do not accurately reproduce the physiological flow waveform provided by the left ventricle while, on the other hand, it is important to analyze pulsatile perfusion under both physiological flow waveform and pulsatile flow CPB. Physiological pulsatile perfusion (supplied by the left ventricle) was examined in this study. A total of 16 patients undergoing cardiac surgery were enrolled in the study and divided into two groups: 8 patients were put on continuous flow CPB while the others underwent beating heart surgery. Venous blood samples were withdrawn to quantify endothelial NO release through its bioactive forms in blood. Plasma was used for the chemiluminescent detection of nitrite (NO2—) and nitrate (NO3—), and the cellular component for electron spin resonance detection of nitrosylhemoglobin. Significant reduction in the intraoperative concentration with respect to the preoperative was observed only in the continuous group for both NO2— and NOx (NO2— + NO3—) concentration (p=0.003 and p=0.016, respectively). A significant difference in the intraoperative nitrite concentration was also observed between the groups (p=0.006). Nitrosylhemoglobin concentration, although not instrumentally detectable, resulted as negligible with respect to the other NO metabolites. Despite the small number of patients belonging to each group, this significant reduction of NO2— concentration under continuous flow CPB revealed a strong dependence on endothelial NO release and plasma nitrite concentration on perfusion modality.