A Practice-Oriented Procedure for Seismic Reliability Assessment of RC Structures Affected by Carbonation-Induced Degradation

Existing reinforced concrete (RC) buildings in Europe have generally been designed without proper consideration of seismic actions and capacity design principles, and thus they tend to be vulnerable to earthquakes. Moreover, since a significant proportion of the aforementioned buildings were developed during the 1950s and 1960s, they are currently close to the end of their service life. Therefore, seismic assessment of existing RC building is a major issue in structural engineering and construction management, and the related seismic analyses should take into account the effect of material ageing and degradation. This paper proposes a practice-oriented procedure for quantifying seismic reliability, taking into account the main effects of carbonation-induced degradation phenomena. It summarizes the main aspects of the most up-to-date models for the seismic degradation of concrete and RC members and shows how nonlinear static (pushover) analyses can be utilized (in lieu of the most time-consuming non-linear time history analyses) in quantifying seismic reliability with respect to the performance levels of relevance in seismic engineering. A relevant case study is finally considered with the aim to showing how some parameters, such as exposure class and cover thickness, affect the resulting seismic reliability of existing RC buildings

Collaboration as a route to SME competitiveness

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collaboration as a route to sme competitiveness

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Relationship between device acceptance and patient-reported outcomes in left ventricular assist device (LVAD) recipients

The number of Left Ventricular Assist Devices (LVADs) implanted each year is rising. Nevertheless, there are minimal data on device acceptance after LVAD implant, and on its relationship with patient-reported outcomes. We designed a cross-sectional study to address this knowledge gap and test the hypothesis that low device acceptance is associated with poorer quality of life, depression and anxiety. Self-report questionnaires were administered to assess quality of life (12-item Kansas City Cardiomyopathy Questionnaire quality of life subscale), level of anxiety (7-item Generalized Anxiety Disorder; GAD-7), level of depression (9-item Patient Health Questionnaire; PHQ-9) and device acceptance (Florida Patient Acceptance Survey; FPAS) to 101 consecutive patients presenting to LVAD clinic. Regression analysis showed a strong correlation between device acceptance and both psychological distress (p\u2009<\u20090.001) and quality of life (p\u2009<\u20090.001). Analysis of the sub-scales of the FPAS showed that patients had significant body image concerns, but return to function and device-related distress were the main drivers of the observed correlation between device acceptance and patient well-being. Younger age was associated with lower device acceptance (r\u2009=\u20090.36, p\u2009<\u20090.001) and lower quality of life (r\u2009=\u20090.54, p\u2009<\u20090.001). These findings suggest that interventions targeting device acceptance should be explored to improve outcomes in LVAD recipients

Targeting tumour-reprogrammed myeloid cells: the new battleground in cancer immunotherapy

Tumour microenvironment is a complex ecosystem in which myeloid cells are the most abundant immune elements. This cell compartment is composed by different cell types, including neutrophils, macrophages, dendritic cells, and monocytes but also unexpected cell populations with immunosuppressive and pro-tumour roles. Indeed, the release of tumour-derived factors influences physiological haematopoiesis producing unconventional cells with immunosuppressive and tolerogenic functions such as myeloid-derived suppressor cells. These pro-tumour myeloid cell populations not only support immune escape directly but also assist tumour invasion trough non-immunological activities. It is therefore not surprising that these cell subsets considerably impact in tumour progression and cancer therapy resistance, including immunotherapy, and are being investigated as potential targets for developing a new era of cancer therapy. In this review, we discuss emerging strategies able to modulate the functional activity of these tumour-supporting myeloid cells subverting their accumulation, recruitment, survival, and functions. These innovative approaches will help develop innovative, or improve existing, cancer treatments

Sentinel-2 Remote Sensed Image Classification with Patchwise Trained ConvNets for Grassland Habitat Discrimination

The present study focuses on the use of Convolutional Neural Networks (CNN or ConvNet) to classify a multi-seasonal dataset of Sentinel-2 images to discriminate four grassland habitats in the “Murgia Alta” protected site. To this end, we compared two approaches differing only by the first layer machinery, which, in one case, is instantiated as a fully-connected layer and, in the other case, results in a ConvNet equipped with kernels covering the whole input (wide-kernel ConvNet). A patchwise approach, tessellating training reference data in square patches, was adopted. Besides assessing the effectiveness of ConvNets with patched multispectral data, we analyzed how the information needed for classification spreads to patterns over convex sets of pixels. Our results show that: (a) with an F1-score of around 97% (5 x 5 patch size), ConvNets provides an excellent tool for patch-based pattern recognition with multispectral input data without requiring special feature extraction; (b) the information spreads over the limit of a single pixel: the performance of the network increases until 5 x 5 patch sizes are used and then ConvNet performance starts decreasing