133 research outputs found

    An Inverse Method for Policy-Iteration Based Algorithms

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    We present an extension of two policy-iteration based algorithms on weighted graphs (viz., Markov Decision Problems and Max-Plus Algebras). This extension allows us to solve the following inverse problem: considering the weights of the graph to be unknown constants or parameters, we suppose that a reference instantiation of those weights is given, and we aim at computing a constraint on the parameters under which an optimal policy for the reference instantiation is still optimal. The original algorithm is thus guaranteed to behave well around the reference instantiation, which provides us with some criteria of robustness. We present an application of both methods to simple examples. A prototype implementation has been done

    Upper limb work-related musculoskeletal disorders in operating room nurses: A multicenter cross-sectional study

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    This study aimed to evaluate the association between personal and job characteristics and the risk of upper limb work-related musculoskeletal disorders (WMSDs) among operating room nurses (ORNs). To this end, we collected data from 148 ORNs working at 8 Italian hospitals and measured any upper limb disabilities experienced in the previous year using the Italian version of the disabilities of the arm, shoulder and hand (DASH) questionnaire. The associations between personal and job characteristics and risk of upper limb WMSDs were estimated by unconditional logistic regression models. The prevalence of upper limb WMSDs was 45.9%. Multivariate analysis showed the \u201cfemale gender\u201d and \u201cmonthly hours spent working as a scrub nurse\u201d to be directly associated with a higher DASH score (adjusted OR for gender = 5.37, 95% CI: 1.65\u201317.51, p < 0.01; adjusted OR for monthly hours as scrub nurse = 3.09, 95% CI: 1.33\u20137.19, p < 0.01). Overall, our findings indicate that a full-time job (>120 h/month) as a scrub nurse significantly increases the risk of developing upper limb WMSDs among female ORNs. Thus, to reduce such risk in this particularly sensitive population, we recommend urgent implementation of ergonomic interventions on surgical equipment alongside job rotation and medical surveillance programs

    Providing freedom or financial remuneration? A cross-sectional study on the role of monetary and legal incentives on COVID-19 further booster vaccination intention in the Italian context

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    Vaccine hesitancy became a more and more important issue during the COVID-19 pandemic. Due to the emergence of new variants, many international health agencies have already begun administering booster doses of the vaccine in response to these threats. Studies have emphasized the effectiveness of different types of incentive-based strategies to increase vaccination behaviors. The purpose of the present study was to identify the correlation between different types of incentives (legal or financial) with people's intentions to get a COVID-19 booster vaccine. We conducted a cross-sectional study between 29 January 2022 and 03 February 2022. An online quantitative survey was carried out in Italy. One thousand and twenty-two Italian adults were recruited by a professional panel provider. Descriptive statistics were computed for the five variables concerning the incentives (monetary, tax, fee, health certification, travel) toward vaccination. A general linear model (GLM) was then computed to compare the scores of the five different variables within the subjects. The general linear model showed a significant within-subjects main effect. Post-hoc comparisons showed that among the financial incentive, the monetary reward is rated lower than all the others. Tax and fees both resulted lower than both the legal incentives. Finally, COVID-19 health certification and travel did not result significantly different from each other. This study offers an important contribution to public policy literature and to policymakers in their efforts to explain and steer booster vaccination acceptance while facing an ongoing pandemic

    Policy Optimization for Dynamic Power Management

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    Dynamic power management schemes (also called policies) reduce the power consumption of complex electronic systems by trading off performance for power in a controlled fashion, taking system workload into account. In a power-managed system it is possible to set components into different states, each characterized by performance and power consumption levels. The main function of a power management policy is to decide when to perform component state transitions and which transition should be performed, depending on system history, workload, and performance constraints. In the past, power management policies have been formulated heuristically. The main contribution of this paper is to introduce a finite-state, abstract system model for power-managed systems based on Markov decision processes. Under this model, the problem of finding policies that optimally tradeoff performance for power can be cast as a stochastic optimization problem and solved exactly and efficiently. The applicability and generality of the approach are assessed by formulating Markov model and optimizing power management policies for several systems

    Policy Optimization for Dynamic Power Management

    No full text
    Dynamic power management schemes (also called policies) reduce the power consumption of complex electronic systems by trading off performance for power in a controlled fashion, taking system workload into account. In a power-managed system it is possible to set components into different states, each characterized by performance and power consumption levels. The main function of a power management policy is to decide when to perform component state transitions and which transition should be performed, depending on system history, workload and performance constraints. In the pas

    Living Kidney Transplantation: Evaluation of Renal Function and Morphology of Potential Donors

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    The evaluation of potential living kidney donors requires an accurate study of renal function and morphology. The gold standard to assess renal function is the measurement of glomerular filtration rate (GFR). However, GFR is often estimated from serum creatinine (SCr), cystatin C (SCys), or creatinine clearance (CCr). Otherwise, GFR is predicted using formulas based on SCr or SCys. Ultrasound scanning evaluates morphology and dimensions, while scintigraphy provides information on morphofunctional symmetry of kidneys. The aim of this study in 79 potential donors was to assess the accuracy of the tests employed to estimate GFR and the utility of renal ultrasound and scintigraphy for morphofunctional evaluation of potential donors. GFR (clearance of (99m)Tc-DTPA) was compared with estimates obtained with Cockcroft and Gault (CG-CCr) and Modification of Diet in Renal Disease (MDRD-GFR) formulas, and from SCys (Cys-GFR). The correlation with GFR was statistically significant for SCys and for all estimates, but not for SCr. CCr showed a poor agreement with GFR, with a large range of agreement and a marked and significant overestimation of GFR (33.8 mL/min). The accuracy of CG-CCr and MDRD-GFR as indicators of a GFR < 80 mL/min was better than that of Cys-GFR and CCr. However, their mean prediction errors versus GFR were relevant. Renal dimensions, particularly renal volume, showed a good correlation with GFR. The correlation was higher than that of all prediction equations. The direct measurement of GFR remains the reference method to assess renal function in potential kidney donors. The measurement of renal dimensions can provide useful information also on renal function

    IgA nephropathy: preliminary results of low-antigen-content diet treatment

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    IgA nephropathy is recognized as the most common form of glomerulonephritis. Circulating IgA-IC, found in one third of the patients, seems to play a relevant role. On this bases, we applied a dietetic regimen in five patients with IgA nephropathy to reduce the input of potential nephritogenic dietary antigen
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