Surrogate metamodels from digital image correlation for testing high-performance composite vessels

In this work, a workflow has been developed for the generation of surrogate metamodels to predict and evaluate failure with a confidence above 95 % in initial service conditions of high-performance cylindrical vessels manufactured in composites by Roll Wrapping technology. Currently, there is no specific testing standardization for this type of vessel and to fill this gap probabilistic numerical models were developed, performed by the Finite Element Method, fed with the material characteristics obtained experimentally by 2D digital image correlation from flat specimens. From the initial numerical model, a surrogate metamodel was generated by stochastic approximations. Once the metamodels were obtained by robust engineering, an experimental ring-ring tensile test was developed under service conditions and deformations were measured by high-precision 3D digital image correlation. Parametric and robust tests showed that the results of the metamodel did not show statistically significant differences, with errors in the rupture part of less than 2 % with respect to the results obtained in the test, being proposed as a basis for new test procedures.

Smartvessel: A New Extinguisher Prototype Based on New Materials and IoT Sensors

Smartvessel is an innovative fire extinguisher prototype supported by new materials and IoT technology that seeks to improve the functionality and efficiency of conventional fire extinguishers. Storage containers for gases and liquids are essential for industrial activity as they enable higher energy density. The main contributions of this new prototype are (i) innovation in the use of new materials that provide lighter and more resistant extinguishers, both mechanically and against corrosion in aggressive environments. For this purpose, these characteristics are directly compared in vessels made of steel, aramid fiber and carbon fiber with the filament winding technique. (ii) The integration of sensors that allow its monitoring and provide the possibility of predictive maintenance. The prototype is tested and validated on a ship, where accessibility is complicated and critical. For this purpose, different data transmission parameters are defined, verifying that no data are lost. Finally, a noise study of these measurements is carried out to verify the quality of each data. Acceptable coverage values are achieved with very low read noise, on average less than 1%, and a weight reduction of 30% is obtained.

Predictive Models for the Characterization of Internal Defects in Additive Materials from Active Thermography Sequences Supported by Machine Learning Methods

The present article addresses a generation of predictive models that assesses the thickness and length of internal defects in additive manufacturing materials. These modes use data from the application of active transient thermography numerical simulation. In this manner, the raised procedure is an ad-hoc hybrid method that integrates finite element simulation and machine learning models using different predictive feature sets and characteristics (i.e., regression, Gaussian regression, support vector machines, multilayer perceptron, and random forest). The performance results for each model were statistically analyzed, evaluated, and compared in terms of predictive performance, processing time, and outlier sensibility to facilitate the choice of a predictive method to obtain the thickness and length of an internal defect from thermographic monitoring. The best model to predictdefect thickness with six thermal features was interaction linear regression. To make predictive models for defect length and thickness, the best model was Gaussian process regression. However, models such as support vector machines also had significative advantages in terms of processing time and adequate performance for certain feature sets. In this way, the results showed that the predictive capability of some types of algorithms could allow for the detection and measurement of internal defects in materials produced by additive manufacturing using active thermography as a non-destructive test.

Retrospective study of 149 cases of salivary gland carcinoma in a Spanish hospital population

Background

The clinical and histological characteristics of salivary gland tumors vary widely, complicating their diagnosis and management, and major differences have been recorded in the distribution of histopathological diagnoses among different countries.

Material and Methods

This retrospective study reviewed the demographic (age, sex) and clinicopathological (pathology diagnosis and localization) characteristics of cases diagnosed with primary SGC between June 1992 and May 2014 in the Pathology Department of the 12 de Octubre Hospital of Madrid. Diagnoses were recorded according to the 2005 WHO classification.

Results

The study included 149 SCG patients, aged between 11 and 94 yrs, with mean age at onset of 55.56 yrs and peak incidence in the eighth decade of life. The male:female ratio was 1.01. The parotid gland was the most frequently involved (75.2%). The most frequent carcinoma was mucoepidermoid carcinoma (24.2%), followed by acinic cell carcinoma (15.4%).

Conclusions

The demographic and histopathological characteristics of patients with salivary gland carcinomas in Spain, reported here for the first time, are broadly similar to those found in other countries.

Key words:Salivary gland carcinomas, descriptive, salivary glands, salivary gland tumors, head and neck cancer, oral cancer, Spain.

Validation in colorectal procedures of a useful novel approach for the use of C-reactive protein in postoperative infectious complications

AIM

Our aim was to validate a novel use of C-reactive protein (CRP) measurement to identify postoperative infectious complications in patients undergoing colorectal surgery, and to compare the predictive value in this setting against white blood cell (WBC) count and neutrophil-to-lymphocyte ratio (NLR).

METHOD

This was a retrospective study of CRP, NLR and WBC measurements in patients undergoing colorectal surgery. CRP, NLR and WBC were recorded on the second postoperative day and on the day of infectious complication (patients who developed infectious complications) or within 3 days prior to discharge (subjects with no complications). The test for detecting infectious complications consisted of comparing the value of the inflammatory marker on the day on which a complication was suspected against the value recorded on the second postoperative day. The test was considered positive if a given value was higher than the registered peak at postoperative day 2. Factors influencing the postoperative peak CRP were also studied.

RESULTS

A total of 254 patients were retrospectively studied. Patients whose CRP value was higher than on the second postoperative day had a diagnostic accuracy for infectious complications of up to 94.4% and sensitivity, specificity, positive predictive value and negative predictive value of up to 97.4%, 93.4%, 85.7% and 99.1%, respectively. Poorer results were observed when WBC count and NLR were used rather than CRP measurement. Multiple linear regression analysis showed that surgical procedure and approach, as well as additional resections, were independent factors for 48 h peak CRP.

CONCLUSION

C-reactive protein is a better parameter than WBC count and NLR for detecting infectious complications. Our proposed methodology presents good diagnostic accuracy and performance and could potentially be used for any surgical procedure.

Precise determination of the f0(600) and f0(980) pole parameters from a dispersive data analysis

We use our latest dispersive analysis of ππ scattering data and the very recent K(ℓ4) experimental results to obtain the mass, width, and couplings of the two lightest scalar-isoscalar resonances. These parameters are defined from their associated poles in the complex plane. The analytic continuation to the complex plane is made in a model-independent way by means of once- and twice-subtracted dispersion relations for the partial waves, without any other theoretical assumption. We find the f(0)(600) pole at (457(-13))+14))-i(279(-7)(+11)) MeV and that of the f(0)(980) at (996 ± 7)-i(25(-6)(+10)) MeV, whereas their respective couplings to two pions are 3.59(-0.13)(+0.11) and 2.3 ± 0.2 GeV.

Correlation between c-erb-B2 overexpression with disease-free survival and rate of pelvic relapse in patients with advanced cervical cancer treated with chemo-radiotherapy

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Aims: To determine the impact of the c-erb-B2 overexpression receptor on pelvic relapse and on disease-free survival (DFS) in patients with advanced cervical cancer receiving concurrent chemo-radiotherapy. Methods: One hundred thirty six patients with advanced cervical cancer (stage: 12 IB2-IIA, 34 IIB, 71 IIIB, 19 IVA); histology: 86 epidermoid and 14 adenocarcinoma) were analyzed to detect c-erbB-2 level using an immunohistochemical method (Herceptest Dako). Cases c-erbB-2 (+3) were considered positive. All patients received pelvic radiotherapy, brachitherapy and concurrent chemotherapy with two schedules: 48 patients with tegafur (800 mg/day via oral) and 88 with tegafur (same doses) plus five cycles of weekly cisplatin 40 mg/m2/week iv. Results: Of the 136 biopsies, 32 (23.5%) were c- erbB-2 positive. The disease free survival to 3 and 5 years of the patients were 61% and 58% for c-erb-B2 negative and 36% and 36% for c-erb- B2 positive (p=0.02), respectively.We divided our patients in four groups: c-erb-B2 positive treated with cisplatin; c-erb-B2 positive without cisplatin, c-erb-b2 negative treated with cisplatin and c-erb-b2 negative without cisplatin. The group of patients with c-erb-B2 overexpression that did not received platinum treatment had a higher rate of pelvis relapse (p<0.0001) and with a decreased DFS (p=0.0014). Conclusions: c-erbB-2 overexpression may imply a poor prognosis for patients with advanced cervix cancer, especially if they did not receive concurrent radiochemotherapy with cisplatin.

No significant financial relationships to disclose.