Use of a gray level co-occurrence matrix to characterize duplex stainless steel phases microstructure

Duplex stainless steels are widely used in industry. This is due to their higher strength compared to austenitic steels and to their higher toughness than ferritic steels. They also have good weldability and high resistance to stress corrosion cracking. These steels are characterized by two-phase microstructures composed by almost the same level of ferrite and austenite. Duplex steel 2205 samples evaluated are: as received, cold rolled (33%) and heat-treated at 800°C for 10 hours. A metallographic etching with 10% oxalic acid has been carried out to highlight the phases morphology. Some photos have been taken by SEM microscope and submitted to image analysis. The analysis carried out is based on the determination of co-occurrence matrix and on the following interpretation of appropriate indicators. Through these indicators is possible to estimate the features of images objectively

High-temperature oxidation behaviour of a TiAl-based alloy subjected to aluminium hot-dipping

In this research the oxidation resistance at high temperature of a TiAl-based alloy has been improved by hot-dipping the alloy in molten aluminium and by performing an interdiffusion process. After selecting the best process parameters, a compact TiAl3 coating characterized by an almost constant thickness was formed on the surface. Isothermal oxidation tests, carried out at 900, 950 and 1000 °C, showed that the coated alloy is able to form a continuous and thin alumina layer that is very protective. Microstructural investigations highlighted that, above 900 °C, long residence times at high temperature determine the diffusion through the TiAl3 layer of Cr that favours migration toward the outer surface of Al and thus the formation of a self-healing alumina layer

Corrosion behavior of Shape Memory Alloy in NaCl environment and deformation recovery maintenance in Cu-Zn-Al system

Shape memory effect (SME) and the relation with corrosion behavior of Cu-Zn-Al Smart Memory Alloys (SMAs) were investigated using different techniques: Scanning Electron Microscopy equipped with an Energy Dispersive System, X-Ray Diffraction analysis, Electrochemical Test in NaCl solutions with different concentrations (0.035%, 0.35% and 3.5%), which simulate coastal conditions, mechanical characterization through tensile test and guided bend test. SMAs are an important class of smart materials able to recover after deformation a pre-imposed shape through a temperature modification. These alloys show great potential, finding several applications in medicine and in different types of industry sectors (aerospace, architecture, automotive etc.). Cu-based SMAs, including Cu-Zn-Al alloys, have lower production costs with respect to Ni-Ti alloys as well as good possibility in seismic and architectural applications. A Cu-Zn-Al alloy with a theoretical composition of 25 wt.% Zn and 4 wt.% Al was produced by casting method. The aim of this study is to characterize the microstructure, the mechanical properties and the corrosion behavior through different kind of standard corrosion tests of this alloy and to evaluate the effect of corrosion damage on the shape memory recovery capability through a combination of corrosion and thermo-mechanical cyclic test and SEM observations

Skin Lesion Segmentation Ensemble with Diverse Training Strategies

This paper presents a novel strategy to perform skin lesion segmentation from dermoscopic images. We design an effective segmentation pipeline, and explore several pre-training methods to initialize the features extractor, highlighting how different procedures lead the Convolutional Neural Network (CNN) to focus on different features. An encoder-decoder segmentation CNN is employed to take advantage of each pre-trained features extractor. Experimental results reveal how multiple initialization strategies can be exploited, by means of an ensemble method, to obtain state-of-the-art skin lesion segmentation accuracy

Mental health and well-being during the second wave of COVID-19: longitudinal analyses of the UK COVID-19 Mental Health and Wellbeing study (UK COVID-MH)

Background Waves 1 to 3 (March 2020 to May 2020) of the UK COVID-19 Mental Health and Wellbeing study suggested an improvement in some indicators of mental health across the first 6 weeks of the UK lockdown; however, suicidal ideation increased. Aims To report the prevalence of mental health and well-being of adults in the UK from March/April 2020 to February 2021. Method Quota sampling was employed at wave 1 (March/April 2020), and online surveys were conducted at seven time points. Primary analyses cover waves 4 (May/June 2020), 5 (July/August 2020), 6 (October 2020) and 7 (February 2021), including a period of increased restrictions in the UK. Mental health indicators were suicidal ideation, self-harm, suicide attempt, depression, anxiety, defeat, entrapment, loneliness and well-being. Results A total of 2691 (87.5% of wave 1) individuals participated in at least one survey between waves 4 and 7. Depressive symptoms and loneliness increased from October 2020 to February 2021. Defeat and entrapment increased from July/August 2020 to October 2020, and remained elevated in February 2021. Well-being decreased from July/August 2020 to October 2020. Anxiety symptoms and suicidal ideation did not change. Young adults, women, those who were socially disadvantaged and those with a pre-existing mental health condition reported worse mental health. Conclusions The mental health and well-being of the UK population deteriorated from July/August 2020 to October 2020 and February 2021, which coincided with the second wave of COVID-19. Suicidal thoughts did not decrease significantly, suggesting a need for continued vigilance as we recover from the pandemic

Development of intermediate layer systems for direct deposition of thin film solar cells onto low cost steel substrates

The functionalisation of low-cost steel over large areas with low cost intermediate layers (ILs) for utilisation as substrates in thin film solar modules is reported. Three approaches for the deposition of ILs are demonstrated and evaluated; a thick SiOx sol–gel based on a one-step acidic catalysis applied by spray technique, a commercial screen-printable dielectric ink, and an epoxy-based material (SU8) deposited by screen printing or bar coating. These ILs demonstrated the properties of surface levelling (quantified by mechanical profilometry), electric insulation (tested using breakdown voltage and leakage current) and acted as an anti-diffusion barrier (demonstrated with glow discharge mass spectrometry). Moreover, the performances of amorphous silicon (a-Si:H) and organic photovoltaic (OPV) thin film solar cells grown on carbon and stainless steels (a-Si:H: 5.53% and OPV: 2.40%) show similar performances as those obtained using a reference glass substrate (a-Si:H: 5.51% and OPV: 2.90%). Finally, a cost analysis taking into account both the SiOx sol–gel and the dielectric ink IL was reported to demonstrate the economic feasibility of the steel/IL prototypes

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Computational Methods for Pigmented Skin Lesion Classification in Images: Review and Future Trends

Skin cancer is considered as one of the most common types of cancer in several countries, and its incidence rate has increased in recent years. Melanoma cases have caused an increasing number of deaths worldwide, since this type of skin cancer is the most aggressive compared to other types. Computational methods have been developed to assist dermatologists in early diagnosis of skin cancer. An overview of the main and current computational methods that have been proposed for pattern analysis and pigmented skin lesion classification is addressed in this review. In addition, a discussion about the application of such methods, as well as future trends, is also provided. Several methods for feature extraction from both macroscopic and dermoscopic images and models for feature selection are introduced and discussed. Furthermore, classification algorithms and evaluation procedures are described, and performance results for lesion classification and pattern analysis are given