Tailored plasma sprayed MCrAlY coatings for aircraft gas turbine applications

Eighteen plasma sprayed coating systems, nine based on the NiCoCrAly chemistry and nine based on the CoCrAly composition, were evaluated to identify coating systems which provide equivalent or superior life to that shown by the electron beam physical vapor deposited NiCoCrAly and CoCrAly coatings respectively. NiCoCrAly type coatings were examined on a single crystal alloy and the CoCrAly based coatings were optimized on the B1900+ Hf alloy. Cyclic burner rig oxidation and hot corrosion and tensile ductility tests used to evaluate the various coating candidates. For the single crystal alloy, a low pressure chamber plasma sprayed NiCoCrAly + Si coating exhibited a 2x oxidation life improvement at 1394 K (2050 F) over the vapor deposited NiCoCrAly material while showing equivalent tensile ductility. A silicon modified low pressure chamber plasma sprayed CoCrAly coating was found to be more durable than the baseline vapor deposited CoCrAly coating on the B1900+ Hf alloy

Enhanced Recovery after Bariatric Surgery: 202 Consecutive Patients in an Italian Bariatric Center

Background: Enhanced Recovery After Surgery (ERAS) pathways have been shown to improve postoperative outcomes. However, its application in bariatric surgery is still limited. The aim of the study was to define the safety of ERAS in bariatric patients with regard to postoperative complications, length of hospital stay (LOS), and readmission rates within 30\ua0days from surgery. Methods: The effectiveness and safety of an ERAS protocol was prospectively investigated in morbidly obese patients who underwent bariatric surgery in a single-institute experience over a 2-year period. Results: Between June 2016 and September 2018, a total of 89 laparoscopic sleeve gastrectomy (SG), 105 Roux-en-Y gastric bypass (RYGB), and 8 one-anastomosis gastric bypass (OAGB) were performed. Twenty patients (9.9%) were revisional cases. Mean (standard deviation, SD) BMI and age at time of surgery were 43.2 (\ub1 6.2)\ua0kg/m2 and 46 (\ub1 11.3)\ua0years, respectively. Median (range) surgical time was 118 (45\u2013255) minutes. Overall postoperative complication rate was 7.4%, with 6 (3.0%) patients developing grade III\u2013IV complications according to the Clavien-Dindo classification. Median (range) LOS was 2 (1\u201350)\ua0days, with mean (SD) LOS of 2.3 (\ub1 3.6)\ua0days. Overall, 36.6% of patients were discharged by first postoperative day and 77.7% by second postoperative day. Readmission rate was 4.5%. No mortality was observed during the study period. Conclusions: According to the results of the present study, ERAS in primary and revisional bariatric surgery is safe and feasible, with short LOS, low morbidity and readmission rates, and no mortality. A significant reduction of mean LOS was progressively noted over the study period

Angular correlation of scattered annihilation photons, to test the possibility of hidden variables in quantum theory

Angular correlations of the annihilation photons, Compton scattered by plastic scintillators and detected by means of NaI (T1) crystals, have been measured in order to test the possibility of deviations of the experimental results from the predictions of the quantum theory

Genetic drift at expanding frontiers promotes gene segregation

Competition between random genetic drift and natural selection plays a central role in evolution: Whereas non-beneficial mutations often prevail in small populations by chance, mutations that sweep through large populations typically confer a selective advantage. Here, however, we observe chance effects during range expansions that dramatically alter the gene pool even in large microbial populations. Initially well-mixed populations of two fluorescently labeled strains of Escherichia coli develop well-defined, sector-like regions with fractal boundaries in expanding colonies. The formation of these regions is driven by random fluctuations that originate in a thin band of pioneers at the expanding frontier. A comparison of bacterial and yeast colonies (Saccharomyces cerevisiae) suggests that this large-scale genetic sectoring is a generic phenomenon that may provide a detectable footprint of past range expansions.Comment: Please visit http://www.pnas.org/content/104/50/19926.abstract for published articl

Comparison of contact parameters measured with two different friction rigs for nonlinear dynamic analysis

The accurate measurement of contact interface parameters is of great importance for nonlinear dynamic response computations since there is a lack of predictive capabilities for such input parameters. Several test rigs have been developed at different institutions, and a series of measurements published, but their reliability remains unknown due to a lack of direct comparisons. To somehow address this issue, a Round-Robin test campaign was performed including the high frequency friction rigs of Imperial College London and Politecnico di Torino. Comparable hysteresis loops were recorded on specimen pairs manufactured from the same batch of raw stainless steel, for a wide range of test conditions, including varying normal loads, sliding distances and nominal areas of contact. Measurements from the two rigs were compared to quantify the level of agreement between the two very different experimental setup, showing a reasonably good matching in the results, but also highlighting some differences. Results also demonstrated that loading conditions can strongly affect the contact parameters, and consequently their effect must be included in future nonlinear dynamic simulations for more reliable predictions

Deep learning-based pixel-wise lesion segmentation on oral squamous cell carcinoma images

Oral squamous cell carcinoma is the most common oral cancer. In this paper, we present a performance analysis of four different deep learning-based pixel-wise methods for lesion segmentation on oral carcinoma images. Two diverse image datasets, one for training and another one for testing, are used to generate and evaluate the models used for segmenting the images, thus allowing to assess the generalization capability of the considered deep network architectures. An important contribution of this work is the creation of the Oral Cancer Annotated (ORCA) dataset, containing ground-truth data derived from the well-known Cancer Genome Atlas (TCGA) dataset

Teaching mathematics at distance: A challenge for universities

The focus of this research is how Sicilian state university mathematics professors faced the challenge of teaching via distance education during the first wave of the COVID-19 pandemic. Since the pandemic entered our lives suddenly, the professors found themselves having to lecture using an e-learning platform that they had never used before, and for which they could not receive training due to the health emergency. In addition to the emotional aspects related to the particular situation of the pandemic, there are two aspects to consider when teaching mathematics at a distance. The first is related to the fact that at university level, lecturers generally teach mathematics in a formal way, using many symbols and formulas that they are used to writing. The second aspect is that the way mathematics is taught is also related to the students to whom the teaching is addressed. In fact, not only online, but also in face-to-face modality, the teaching of mathematics to students on the mathematics degree course involves a different approach to lessons (as well as to the choice of topics to explain) than teaching mathematics in another degree course. In order to investigate how the Sicilian State university mathematics professors taught mathematics at distance, a questionnaire was prepared and administered one month after the beginning of the lockdown in Italy. Both quantitative and qualitative analyses were made, which allowed us to observe the way that university professors have adapted to the new teaching modality: they started to appropriate new artifacts (writing tablets, mathematical software, e-learning platform) to replicate their face-to-face teaching modality, mostly maintaining their blackboard teacher status. Their answers also reveal their beliefs related to teaching mathematics at university level, noting what has been an advantageous or disadvantageous for them in distance teaching

Skin Lesion Area Segmentation Using Attention Squeeze U-Net for Embedded Devices

Melanoma is the deadliest form of skin cancer. Early diagnosis of malignant lesions is crucial for reducing mortality. The use of deep learning techniques on dermoscopic images can help in keeping track of the change over time in the appearance of the lesion, which is an important factor for detecting malignant lesions. In this paper, we present a deep learning architecture called Attention Squeeze U-Net for skin lesion area segmentation specifically designed for embedded devices. The main goal is to increase the patient empowerment through the adoption of deep learning algorithms that can run locally on smartphones or low cost embedded devices. This can be the basis to (1) create a history of the lesion, (2) reduce patient visits to the hospital, and (3) protect the privacy of the users. Quantitative results on publicly available data demonstrate that it is possible to achieve good segmentation results even with a compact model