Pattern recognition of acoustic emission signal during the mode I fracture mechanisms in carbon- epoxy composite

The aim of the paper is to use Acoustic Emission technique to distinguish the micro/macro failure mechanisms of carbon-epoxy composite laminates during Double Cantilever Beam (DCB) tests. In order to recognize and detect different damage mechanisms, Self-Organizing Map (SOM) method has been used to cluster the AE signals according with the fracture mode that originated them. In addition, most significate Learning vector quantization (LVQ) program has been applied to verify the signals. Five AE features were selected as main parameters: Rise-time, Counts, Energy, Duration and Amplitude. The results highlighted that different signals can be recognized and classified related to their origin. The failure mechanisms detected are Matrix cracking, delamination, and fiber breakage. Scanning Electron Microscopy (SEM) images validate the results. Mathematics data and experimental results confirmed a good converging of AE dat

Supervised and non-supervised AE data classification of nanomodified CFRP during DCB tests

Aim of the paper is to use acoustic emissions to study the effect of electrospun nylon 6,6 Nanofibrous mat on carbon-epoxy composites during Double Cantilever beam (DCB) tests. In order to recognize the effect of the nanofibres and to detect different damage mechanisms, k-means clustering of acoustic emission signals applied to rise time, count, energy, duration and amplitude of the events is used. Supervised neural network (NN) is then applied to verify clustered signals. Results showed that clustered acoustic emission signals are a reliable tool to detect different damage mechanisms; neural network showed the method has a 99% of accuracy

A retrospective molecular study of select intestinal protozoa in healthy pet cats from Italy

The feline gut can harbour a number of protozoan parasites. Recent genetic studies have highlighted new epidemiological findings about species of Cryptosporidium, assemblages of Giardia duodenalis and Toxoplasma gondii. Furthermore, epidemiological studies suggest the occurrence of Tritrichomonas foetus in cats is on the increase worldwide. The prevalence of selected intestinal protozoa was determined by PCR using DNA previously extracted from the faeces of 146 privately owned healthy cats from Italy. Molecular genotyping on T gondii, G duodenalis and Cryptosporidium DNA was achieved. PCR assays were positive in 32 (22.9%) samples. Three animals (2.0%) were positive for T foetus and Cryptosporidium DNA, 15 specimens (10.3%) were positive for T gondii and 11 (7.5%) for G duodenalis. Co-infections were never observed. Results of the typing analysis allowed the identification of Cryptosporidium felis in all cases. The specimens positive for T gondii hinted at clonal genotype I (n = 7), genotype II (n = 1) and genotype III (n = 7). The G duodenalis isolates were referable to assemblages F (n = 9) and C (n = 2). In conclusion, the results obtained in this study add to the literature regarding the epidemiology of these parasites by confirming their presence in the faeces of healthy pet cats

Postmortem CT pulmonary findings in SARS-CoV-2-positive cases: correlation with lung histopathological findings and autopsy results

Introduction/purpose Postmortem computed tomography (PMCT) is a valuable tool for analyzing the death of patients with SARS-CoV-2 infection. The purpose of this study was to investigate the correlation between PMCT lung findings in autopsy cadavers positive for SARS-CoV-2 infection and the severity of COVID-19 lung disease by histopathological analysis.Materials and methods We reviewed chest PMCT findings, paying particular attention to the lung parenchyma, in 8 autopsy cases positive for SARS-CoV-2. Correlations between chest PMCT and histopathological findings were assessed. Clinical conditions and comorbidities were also recorded and discussed. The primary cause of death was finally considered.Results In 6/8 cases, pulmonary PMCT findings were massive consolidation (4/8) and bilateral diffuse mixed densities with a crazy-paving pattern (2/8). These cases showed severe pulmonary signs of COVID-19 at histopathological analysis. In the remaining 2/8 cases, pulmonary PMCT findings were scant antideclive ground-glass opacities in prevalent gradient densities attributed to hypostasis. In 4/8 cases with massive consolidations, important comorbidities were noted. In 6/8 cases with severe pulmonary histopathological signs of lung COVID-19, autopsy found that the cause of death was cardiorespiratory failure. In the remaining 2/8 cases, histopathological analysis revealed lung alterations due to edema and some signs of SARS-CoV-2 infection; the cause of death was not attributed to SARS-CoV-2 infection (Table 1).Discussion and conclusion Chest PMCT findings correlate with the severity of COVID-19 lung disease at histopathology examination. According to our results, there may also be a relationship between cause of death and PMCT findings in COVID-19, which must be critically analyzed considering clinical antemortem data

Postmortem CT pulmonary findings in SARS-CoV-2-positive cases: correlation with lung histopathological findings and autopsy results

Introduction/purpose: Postmortem computed tomography (PMCT) is a valuable tool for analyzing the death of patients with SARS-CoV-2 infection. The purpose of this study was to investigate the correlation between PMCT lung findings in autopsy cadavers positive for SARS-CoV-2 infection and the severity of COVID-19 lung disease by histopathological analysis. Materials and methods: We reviewed chest PMCT findings, paying particular attention to the lung parenchyma, in 8 autopsy cases positive for SARS-CoV-2. Correlations between chest PMCT and histopathological findings were assessed. Clinical conditions and comorbidities were also recorded and discussed. The primary cause of death was finally considered. Results: In 6/8 cases, pulmonary PMCT findings were massive consolidation (4/8) and bilateral diffuse mixed densities with a crazy-paving pattern (2/8). These cases showed severe pulmonary signs of COVID-19 at histopathological analysis. In the remaining 2/8 cases, pulmonary PMCT findings were scant antideclive ground-glass opacities in prevalent gradient densities attributed to hypostasis. In 4/8 cases with massive consolidations, important comorbidities were noted. In 6/8 cases with severe pulmonary histopathological signs of lung COVID-19, autopsy found that the cause of death was cardiorespiratory failure. In the remaining 2/8 cases, histopathological analysis revealed lung alterations due to edema and some signs of SARS-CoV-2 infection; the cause of death was not attributed to SARS-CoV-2 infection (Table 1). Discussion and conclusion: Chest PMCT findings correlate with the severity of COVID-19 lung disease at histopathology examination. According to our results, there may also be a relationship between cause of death and PMCT findings in COVID-19, which must be critically analyzed considering clinical antemortem data

From health-related Corporate Welfare initiatives to Employee Engagement: unveiling the role of Employee Legitimization

The present study aims at unveiling the determinants of the process which leads an employee to legitimize a health-related Corporate Welfare (CW) initiative, thus increasing his or her work engagement. The work is based on 276 answers coming from a survey to test the proposed model. The results obtained demonstrate that different sets of health-related CW initiatives favor employee engagement if they meet the legitimization of the employees. Thus, employers willing to promote initiatives of CW targeting the health of their employees should adopt an employee-centric approach that considers their perceptions and interests, as such factors significantly affect the success of the initiatives themselves. Overall, the results sustain the high potentiality of these kinds of initiatives given the great commitment people show towards health and the positive opinion they have about CW, especially in the light of the impact of the Covid- 19 pandemic