Effect of duplex treatments by plasma nitriding and triode sputtering on corrosion behaviour of 32CDV13 low alloy steel

This paper presents corrosion behaviour of duplex treated low alloy steel. Different kinds of samples were tested: non-treated, plasma nitrided, ZrBN-triode sputtered and ZrBN-duplex treated samples. The corrosion behaviour was evaluated by electrochemical techniques (corrosion potential and polarisation resistance evolutions versus immersion time, potentiodynamic curves). The corrosion tests were carried out in neutral aqueous saline solution (NaCl 30 g L−1), naturally aerated. The composition and the structure of layers were determined by EDS and XRD, respectively, while the morphology was observed by SEM. Experimental results showed that the corrosion current density Icorr increased with decreasing white layer thickness in plasma nitrided specimens. The nitrides ε-Fe2 − 3N and γ′-Fe4N present in the white layer are nobler than the substrate but may promote, by galvanic effect, a localised corrosion through open porosity. The duplex treated specimens (nitriding+ZrBN coating) present better corrosion protection and enable to overcome the drawbacks of both techniques, mainly the porosity of the deposited films

THE EFFECT OF ANNEALING ON THE PROPERTIES OF ZNO:AL FILMS GROWN BY RF MAGNETRON SPUTTERING

The effect of annealing temperature ranged from 200 to 600 °C on the structural, optical and electrical properties of aluminum doped zinc oxide (ZnO:Al) films was reported. The thin films were deposited on glass and silicon substrates by rf magnetron sputtering method using ZnO target (diameter 7,5 cm) mixed with 2 wt.% Al2O3. It has been found that the crystal structure of ZnO:Al films is hexagonal with c-axis preferential orientation. With an increase in the annealing temperature the intrinsic compressive stress was found to decrease, and near stress-free film was obtained after annealing at 600 °C. A resistivity of 1.25x10-3 cm and an average transmittance above 90 % in visible range were obtained for films prepared at room temperature. 

Using a three-isotope Bayesian mixing model to assess the contribution of refuse dumps in the diet of the yellow-legged gull Larus michahellis

SUMMARY.¿ The yellow-legged gull Larus michahellis is usually considered as an opportunistic species that depends on food derived from anthropogenic activity, such as garbage and fishery discards. However, although it has become a problematic species in many Mediterranean countries, there is stillno information about its status in Tunisia. The aim of this work was to assess the differential use of marine and terrestrial resources by the yellow-legged gulls breeding in an urban area on Chikly Island. Dietary reconstructions were performed through the analysis of regurgitates and δ13C, δ34S and δ15N of feathers of fledglings. Contrary to most Mediterranean breeding colonies, and to our expectations, the mixing model showed that yellow-legged gulls from Chikly are above all marine foragers. Whereas the Lake of Tunis was the principal source of food in 2005 and 2007, chicks from 2006 were fed mainly with prey from the Gulf of Tunis. Although the Gulf is located further from the breeding colony and has less fishing activity than the Lake, our study demonstrated that it is used as an alternative foraging habitat. The Bayesian mixing model approach proved to be a useful tool for evaluating temporal variations in the feeding ecology of the colony, which is relevant information in the management of a wild species. This study also demonstrated the importance of isotopic variability among years for inferring diet diversity and food availability for the colony, thereby allowing demographic forecasts when trophic resources vary in abundance or the foraging habitat is disturbed

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

NO2 Selective Sensor Based on α-Fe2O3 Nanoparticles Synthesized via Hydrothermal Technique

In the present work, hematite (&alpha;-Fe2O3) nanopowders were successfully prepared via a hydrothermal route. The morphology and microstructure of the synthesized nanopowders were analyzed by using scanning and transmission electron microscopy (SEM and TEM, respectively) analysis and X-ray diffraction. Gas sensing devices were fabricated by printing &alpha;-Fe2O3 nanopowders on alumina substrates provided with an interdigitated platinum electrode. To determine the sensor sensitivity toward NO2, one of the main environmental pollutants, tests with low concentrations of NO2 in air were carried out. The results of sensing tests performed at the operating temperature of 200 &deg;C have shown that the &alpha;-Fe2O3 sensor exhibits p-type semiconductor behavior and high sensitivity. Further, the dynamics exhibited by the sensor are also very fast. Lastly, to determine the selectivity of the &alpha;-Fe2O3 sensor, it was tested toward different gases. The sensor displayed large selectivity to nitrogen dioxide, which can be attributed to larger affinity towards NO2 in comparison to other pollutant gases present in the environment, such as CO and CO2

Effects of thickness variation on properties of ZnO:Al thin films grown by RF magnetron sputtering deposition

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Indirect Quantitative Analysis of Biochemical Parameters in Banana Using Spectral Reflectance Indices Combined with Machine Learning Modeling

The primary issues in collecting biochemical information in a large area using chemical laboratory procedures are low throughput, hard work, time-consuming, and requiring several samples. Thus, real-time and precise estimation of biochemical variables of various fruits using a proximal remote sensing based on spectral reflectance is critical for harvest time, artificial ripening, and food processing, which might be beneficial economically and ecologically. The main goal of this study was to assess the biochemical parameters of banana fruits such as chlorophyll a (Chl a), chlorophyll b (Chl b), respiration rate, total soluble solids (TSS), and firmness using published and newly developed spectral reflectance indices (SRIs), integrated with machine learning modeling (Artificial Neural Networks; ANN and support vector machine regression; SVMR) at different ripening degrees. The results demonstrated that there were evident and significant differences in values of SRIs at different ripening degrees, which may be attributed to the large variations in values of biochemical parameters. The newly developed two-band SRIs are more effective at measuring different biochemical parameters. The SRIs that were extracted from the visible (VIS), near-infrared (NIR), and their combination showed better R2 with biochemical parameters. SRIs combined with ANN and SVMR would be an effective method for estimating five biochemical parameters in the calibration (Cal.) and validation (Val.) datasets with acceptable accuracy. The ANN-TSS-SRI-13 model was built to determine TSS with greater performance expectations (R2 = 1.00 and 0.97 for Cal. and Val., respectively). Furthermore, the model ANN-Firmness-SRI-15 was developed for determining firmness, and it performed better (R2 = 1.00 and 0.98 for Cal. and Val., respectively). In conclusion, this study revealed that SRIs and a combination approach of ANN and SVMR models would be a useful and excellent tool for estimating the biochemical characteristics of banana fruits