Nanoproducts represent a potential growing sector and nanofibrous materials are widely requested in industrial, medical, and environmental applications. Unfortunately, the production processes at the nanoscale are difficult to control and nanoproducts often exhibit localized defects that impair their functional properties. Therefore, defect detection is a particularly important feature in smart-manufacturing systems to raise alerts as soon as defects exceed a given tolerance level and to design production processes that both optimize the physical properties and control the defectiveness of the produced materials. Here, we present a novel solution to detect defects in nanofibrous materials by analyzing scanning electron microscope images. We employ an algorithm that learns, during a training phase, a model yielding sparse representations of the structures that characterize correctly produced nanofiborus materials. Defects are then detected by analyzing each patch of an input image and extracting features that quantitatively assess whether the patch conforms or not to the learned model. The proposed solution has been successfully validated over 45 images acquired from samples produced by a prototype electrospinning machine. The low computational times indicate that the proposed solution can be effectively adopted in a monitoring system for industrial productio

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Home Care (HC) providers are complex organizations that manage a large number of patients, different categories of operators, support staff and material resources in a context affected by high variability. Hence, robust resource planning is crucial for operations in HC organizations, in order to avoid process inefficiencies, treatment delays, and low quality of service. Under continuity of care, one of the main issues in HC planning is the assignment of a reference nurse to each assisted patient, because this decision has an impact on the workload assigned to the nurse for the entire patient's length of stay. In this paper, we derive an analytical structural policy for solving the nurse-to-patient assignment problem in the HC context under continuity of care. This policy accounts for the randomness that is related to the demands from patients already assigned to nurses and to the demands from new patients who need assignments. The policy is compared to other previously developed approaches, and applied to a relevant real case.

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A pulsatile mock loop system was designed and tested. This prototype represents a versatile, adjustable, and controllable experimental apparatus for in vitro studies of devices meant to interface with the human circulatory system. The pumping system consisted of a ventricular chamber featuring two biomorphic silicone valves as the inlet and outlet valves. The chamber volume is forced by a piston pump moved by a computer-controlled, low-inertia motor. Fluid dynamic tests with the device were performed to simulate physiological conditions in terms of cardiac output (mean flow of 5 and 6 L/min, with beat rates from 60 to 80 bpm), of rheological properties of the processed fluid, and of systemic circulation impedance. The pulsating actuator performed a good replication of the physiological ventricular behavior and was able to guarantee easy control of the waveform parameters. Experimental pressure and flow tracings reliably simulated the physiological profiles, and no hemolytic subatmospheric pressures were revealed. The performance of the prototype valves was also studied in terms of dynamic and static backflow, effective orifice area, and pressure loss, resulting in their applicability for this device. Mechanical reliability was also tested over 8 h. The device proved to be a reliable lab apparatus for in vitro tests; the pumping system also represents a first step toward a possible future application of pulsating perfusion in the clinic arena, such as in short-term cardiac assist and pulsatile cardiopulmonary bypass.

Peripheral vasomotion, interstitial liquid exchange, and cardiovascular system behaviour are investigated by means of a lumped parameter model of the systemic and peripheral circulation, from the aortic valve to the venules. This modelling work aims at combining arterial tree hemodynamics description, active peripheral flow regulation, and fluid exchange. The arterial compartment is constructed with 63 RCL segments and 30 peripheral districts including myogenic control on arterioles, metabolic control on venules, and Starling filtration through capillary membrane. The arterial behaviour is characterised as to the long term stability of pressure/flow waves in the different segments. Peripheral districts show autoregulatory capabilities against pressure changes over a wide range and also self-sustained oscillations mimicking vasomotor activity. A preliminary study was carried out as to the model response to changes induced by cardiopulmonary bypass (CPB). Among the induced alterations, the system responds mainly to hemodilution, which increased peripheral fluid loss and oedema beyond the compensatory capabilities of local regulation mechanisms. This resulted in an overall increase total arterial resistance. Local transport deficits were assessed for each district according to the different metabolic demand. This study shows the requirement of a suitable description of both arteries and peripheral mechanisms in order to describe cardiovascular response non-physiological conditions, as well as assisted circulation or other pathological conditions.

The great influence of uncertainties on the behavior of physical systems has always drawn attention to the importance of a stochastic approach to engineering problems. Accordingly, in this paper, we address the problem of solving a Finite Element analysis in the presence of uncertain parameters. We consider an approach in which several solutions of the problem are obtained in correspondence of parameters samples, and propose a novel non-intrusive method, which exploits the functional principal component analysis, to get acceptable computational efforts. Indeed, the proposed approach allows constructing an optimal basis of the solutions space and projecting the full Finite Element problem into a smaller space spanned by this basis. Even if solving the problem in this reduced space is computationally convenient, very good approximations are obtained by upper bounding the error between the full Finite Element solution and the reduced one. Finally, we assess the applicability of the proposed approach through different test cases, obtaining satisfactory results