Assessment of optimal design methods of viscous dampers

Viscous dampers are often used for seismic protection and performance enhancement of building frames. The optimal design of such devices requires the modelling and propagation of the uncertainties related to the earthquake hazard. Different approaches are available for the seismic input characterisation and for the probabilistic response evaluation. This work analyzes the effect of different characterizations of the seismic input and of the response evaluation on the design of dampers for building frames. The seismic input is represented as a stochastic process and the optimal damper properties are found via a reliability-based design procedure aiming at controlling the frame performance while limiting the damper cost. Two simplified approaches are used to design the viscous damper of a multi-storey steel frame and the design results are compared with those obtained by considering a rigorous design approach resorting to advanced simulations for the response assessment. The first methodology evaluates the response through a prefixed probabilistic demand model, while the second approach considers the average response for a given hazard level only. The comparison allows to evaluate and quantify the effect of the seismic input uncertainty treatment on the system and damper performances

Analysis of the interaction of calcitriol with the disulfide isomerase ERp57

Calcitriol, the active form of vitamin D3, can regulate the gene expression through the binding to the nuclear receptor VDR, but it can also display nongenomic actions, acting through a membrane- associated receptor, which has been discovered as the disul de isomerase ERp57. The aim of our research is to identify the binding sites for calcitriol in ERp57 and to analyze their interaction. We rst studied the interaction through bioinformatics and uorimetric analyses. Subsequently, we focused on two protein mutants containing the predicted interaction domains with calcitriol: abb’- ERp57, containing the rst three domains, and a’-ERp57, the fourth domain only. To consolidate the achievements we used the calorimetric approach to the whole protein and its mutants. Our results allow us to hypothesize that the interaction with the a’ domain contributes to a greater extent than the other potential binding sites to the dissociation constant, calculated as a Kd of about 10−9 M

An efficient approach for computing analytical non-parametric fragility curves

Fragility curves are used in earthquake engineering for assessing the seismic vulnerability of structures or systems. Direct estimations of fragility curves by means of simulation-based approaches lead generally to relevant computational costs, especially when the failure region is characterized by small probabilities of occurrence. Simplified hypotheses are therefore introduced in the common practice to approximate the dependency between the structural response and the associated seismic intensity level. The study proposes a non-parametric methodology to estimate analytical fragility curves without specific assumptions on their final shape. The approach starts by identifying all the subsets characterized by the same values of the chosen seismic intensity measure parameter. Then, the failure region is mapped by means of a classification algorithm coupled with a polynomial kernel. Finally, the conditional failure probability is computed by associating the samples generated in each subset to the corresponding classification score. A stochastic earthquake model is employed to define the seismic dataset and the uncertainty associated with the ground motion records. Two case studies are analyzed in which the non-parametric methodology is compared against three popular parametric approaches and a reference solution. The proposed approach shows an overall higher accuracy and efficiency, especially in case of rare failure domains

An efficient method for estimating conditional failure probabilities

Conditional reliability measures provide a more detailed description of the performance of a system, being representative of different initial configurations. Commonly, since the failure region is characterized by a small probability of occurrence, advanced sampling techniques are required to reduce the computational effort of a simulation based approach. These techniques if on one hand decrease the number of samples needed to identify the failure domain, on the other hand do not generally allow a direct estimation of the conditional failure probability for different given inputs. This study aims at providing an efficient and simple methodology to evaluate the conditional failure probability in the case of a static reliability analysis. In particular, under the assumption of probability density functions (PDFs) with a finite support, the failure region mapping process is carried out using surrogate PDFs associated with Sobol’ sequences in order to reduce as much as possible the model evaluations. Finally, the integration of the failure region in the standard normal space employs probabilistic weights instead of a classic indicator function to account for the uncertainty associated with the failure region definition. The approach is verified by comparing the results against those obtained from a Latin Hypercube Sampling. The performance of the proposed method is evaluated in terms of computational costs and accurac

Reliability-based optimal design of nonlinear viscous dampers for the seismic protection of structural systems

Viscous dampers are widely employed for enhancing the seismic performance of structural systems, and their design is often carried out using simplified approaches to account for the uncertainty in the seismic input. This paper introduces a novel and rigorous approach that allows to explicitly consider the variability of the intensity and characteristics of the seismic input in designing the optimal viscous constant and velocity exponent of the dampers based on performance-based criteria. The optimal solution permits controlling the probability of structural failure, while minimizing the damper cost, related to the sum of the damper forces. The solution to the optimization problem is efficiently sought via the constrained optimization by linear approximation (COBYLA) method, while Subset simulation together with auxiliary response method are employed for the performance assessment at each iteration of the optimization process. A 3-storey steel moment-resisting building frame is considered to illustrate the application of the proposed design methodology and to evaluate and compare the performances that can be achieved with different damper nonlinearity levels. Comparisons are also made with the results obtained by applying simplifying approaches, often employed in design practice, as those aiming to minimize the sum of the viscous damping constant and/or considering a single hazard level for the performance assessment

Non-dimensional probabilistic analysis of seismic pounding between flexible structures and rigid boundaries

Pounding between adjacent structures subjected to earthquake actions can cause significant damage. Due to the many uncertainties inherent to the seismic input and the impact phenomenon, a probabilistic assessment of the occurrence of seismic pounding and of its consequences on the structural performance is necessary. This work analyzes the problem of pounding by considering a single-degree-of-freedom benchmark system surrounded by rigid boundaries and subjected to a stochastic earthquake input. Although simplified, the model is representative of several realistic configurations, such as base-isolated systems surrounded by moat walls or bridge decks near the bridge abutments. The problem is cast in non-dimensional form and a parametric study is carried out to evaluate the influence of the identified non-dimensional input parameters on the statistics of the response. A probabilistic demand model is developed for the impact forces via non-linear regression, with the demand expressed as a function of the identified non-dimensional parameters. This model provides an estimate of median pounding force and of its dispersion given the seismic intensity of the input. Finally, global sensitivity analysis is used to rank the model parameters in terms of their influence on the system performance

Longitudinal study on low-dose aspirin versus placebo administration in silent brain infarcts: the silence study

Background. We investigated low-dose aspirin (ASA) efficacy and safety in subjects with silent brain infarcts (SBIs) in preventing new cerebrovascular (CVD) events as well as cognitive impairment. Methods. We included subjects aged ≥45 years, with at least one SBI and no previous CVD. Subjects were followed up to 4 years assessing CVD and SBI incidence as primary endpoint and as secondary endpoints: (a) cardiovascular and adverse events and (b) cognitive impairment. Results. Thirty-six subjects received ASA while 47 were untreated. Primary endpoint occurred in 9 controls (19.1%) versus 2 (5.6%) in the ASA group (p=0.10). Secondary endpoints did not differ in the two groups. Only baseline leukoaraiosis predicts primary [OR 5.4 (95%CI 1.3-22.9, p=0.022)] and secondary endpoint-A [3.2 (95%CI 1.1-9.6, p=0.040)] occurrence. Conclusions. These data show an increase of new CVD events in the untreated group. Despite the study limitations, SBI seems to be a negative prognostic factor and ASA preventive treatment might improve SBI prognosis. EU Clinical trial is registered with EudraCT Number: 2005-000996-16; Sponsor Protocol Number: 694/30.06.04

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients