Investigation of photon, neutron and proton shielding features of H3BO3–ZnO–Na2O–BaO glass system

The current study aims to explore the shielding properties of multi-component borate-based glass series. Seven glass-samples with composition of (80-y)H3BO3–10ZnO–10Na2O–yBaO where (y = 0, 5, 10, 15, 20, 25 and 30 mol.%) were synthesized by melt-quench method. Various shielding features for photons, neutrons, and protons were determined for all prepared samples. XCOM, Phy-X program, and SRIM code were performed to determine and explain several shielding properties such as equivalent atomic number, exposure build-up factor, specific gamma-ray constants, effective removal cross-section (SR), neutron scattering and absorption, Mass Stopping Power (MSP) and projected range. The energy ranges for photons and protons were 0.015–15 MeV and 0.01–10 MeV, respectively. The mass attenuation coefficient (µ/?) was also determined experimentally by utilizing two radioactive sources (166Ho and 137Cs). Consistent results were obtained between experimental and XCOM values in determining µ/? of the new glasses. The addition of BaO to the glass matrix led to enhance the µ/? and specific gamma-ray constants of glasses. Whereas the remarkable reductions in SR, MSP, and projected range values were reported with increasing BaO concentrations. The acquired results nominate the use of these glasses in different radiation shielding purposes

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

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

Spectrophotometric Analysis of Dental Enamel Staining to Antiseptic and Dietary Agents: In Vitro Study

Background/Objectives. Use of antiseptics as an adjunct to a traditional mechanical tooth brushing method has limited their application for long duration because of their side effects such as staining and calculus formation. The objective of this in vitro study is to analyse the staining effects of antiseptic mouthwashes on dental enamel and compare it with those containing nanoparticles, dietary agents, and distilled water (control). Material and Methods. 105 intact premolars extracted for orthodontic reasons and without any caries or anatomical defects were selected for analysis. The samples were randomly divided into 7 different groups of fifteen teeth each for different solutions. A spectrophotometer was used to assess the colorimeter analysis of buccal dental enamel surface at R1 (baseline examination), R2 (24 hours after immersion in different solutions), and R3 (after brushing). Statistical analysis was done using the Kolmogorov–Smirnov test and Levene’s test (p<0.05), respectively. One-way ANOVA was used to compare the difference in color (∆E) between the readings, R1, R2, and R3. Results. The mouthwash containing titanium dioxide (TiO2) nanoparticles produced the greater enamel discoloration compared to that of chlorhexidine. Brushing had little effect on removal of stains induced by all mouthwashes except for dietary solutions (lemon with sodium bicarbonate and olive with laurel) and distilled water (control). Conclusion. The results from this study show that mouthwashes containing TiO2 nanoparticles and other antiseptic mouthwashes cause change in color of the teeth and lead to poor esthetic appearance when compared to dietary and control solutions. Thus, future in vivo studies have to be conducted to confirm these findings as in vitro studies may not provide a reliable simulation of the clinical situations

Intelligent Deep Machine Learning Cyber Phishing URL Detection Based on BERT Features Extraction

Recently, phishing attacks have been a crucial threat to cyberspace security. Phishing is a form of fraud that attracts people and businesses to access malicious uniform resource locators (URLs) and submit their sensitive information such as passwords, credit card ids, and personal information. Enormous intelligent attacks are launched dynamically with the aim of tricking users into thinking they are accessing a reliable website or online application to acquire account information. Researchers in cyberspace are motivated to create intelligent models and offer secure services on the web as phishing grows more intelligent and malicious every day. In this paper, a novel URL phishing detection technique based on BERT feature extraction and a deep learning method is introduced. BERT was used to extract the URLs&rsquo; text from the Phishing Site Predict dataset. Then, the natural language processing (NLP) algorithm was applied to the unique data column and extracted a huge number of useful data features in terms of meaningful text information. Next, a deep convolutional neural network method was utilised to detect phishing URLs. It was used to constitute words or n-grams in order to extract higher-level features. Then, the data were classified into legitimate and phishing URLs. To evaluate the proposed method, a famous public phishing website URLs dataset was used, with a total of 549,346 entries. However, three scenarios were developed to compare the outcomes of the proposed method by using similar datasets. The feature extraction process depends on natural language processing techniques. The experiments showed that the proposed method had achieved 96.66% accuracy in the results, and then the obtained results were compared to other literature review works. The results showed that the proposed method was efficient and valid in detecting phishing websites&rsquo; URLs

Intelligent deep machine learning cyber phishing URL detection based on BERT features extraction

Recently, phishing attacks have been a crucial threat to cyberspace security. Phishing is a form of fraud that attracts people and businesses to access malicious uniform resource locators (URLs) and submit their sensitive information such as passwords, credit card ids, and personal information. Enormous intelligent attacks are launched dynamically with the aim of tricking users into thinking they are accessing a reliable website or online application to acquire account information. Researchers in cyberspace are motivated to create intelligent models and offer secure services on the web as phishing grows more intelligent and malicious every day. In this paper, a novel URL phishing detection technique based on BERT feature extraction and a deep learning method is introduced. BERT was used to extract the URLs’ text from the Phishing Site Predict dataset. Then, the natural language processing (NLP) algorithm was applied to the unique data column and extracted a huge number of useful data features in terms of meaningful text information. Next, a deep convolutional neural network method was utilised to detect phishing URLs. It was used to constitute words or n-grams in order to extract higher-level features. Then, the data were classified into legitimate and phishing URLs. To evaluate the proposed method, a famous public phishing website URLs dataset was used, with a total of 549,346 entries. However, three scenarios were developed to compare the outcomes of the proposed method by using similar datasets. The feature extraction process depends on natural language processing techniques. The experiments showed that the proposed method had achieved 96.66% accuracy in the results, and then the obtained results were compared to other literature review works. The results showed that the proposed method was efficient and valid in detecting phishing websites’ URLs

Our Experience of Using Thermally Recycled Silica Gel in a Teaching and Small Research Laboratory Setting

Organic synthetic research laboratories generate a large amount of waste. Some of the waste is the silica gel used as the stationary phase in column chromatographic separations. Here, the authors discuss the possibility of recycling silica gel wastes thermally at 600 &deg;C, at which temperature the remnant adsorbed organic material combusts. It could be shown that the recycled silica gel maintains its adsorption characteristics. The process could be repeated 10 times with any discernable deterioration of the separation properties of the silica gel for the product mixture of the reactions used in this research. In those cases where triphenyl oxide remained on the silica gel after the separation of the reaction mixture, such as after Wittig olefination and Appel-type reactions, an increase of phosphorus content was noted in the silica gel after thermal treatment. The original and recycled silica gel was partly analyzed by Brunauer-Emmett-Teller (BET) surface measurements, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and in inductively coupled plasma optical emission spectroscopy (ICP-OES). The process significantly reduced waste production in our laboratory and also led to a reduction in costs associated with acquiring new silica gel and with the management and the disposal of spent silica gel. A simple environmental impact assessment has been carried out

Biological Potentials and Phytochemical Constituents of Raw and Roasted <i>Nigella arvensis</i> and <i>Nigella sativa</i>

Nigella species are widely used to cure various ailments. Their health benefits, particularly from the seed oils, could be attributed to the presence of a variety of bioactive components. Roasting is a critical process that has historically been used to facilitate oil extraction and enhance flavor; it may also alter the chemical composition and biological properties of the Nigella seed. The aim of this study was to investigate the effect of the roasting process on the composition of the bioactive components and the biological activities of Nigella arvensis and Nigella sativa seed extracts. Our preliminary study showed that seeds roasted at 50 °C exhibited potent antimicrobial activities; therefore, this temperature was selected for roasting Nigella seeds. For extraction, raw and roasted seed samples were macerated in methanol. The antimicrobial activities against Streptococcus agalactiae, Streptococcus epidermidis, Streptococcus pyogenes, Candida albicans, Escherichia coli, Enterobacter aerogenes, Klebsiella pneumoniae, and Klebsiella oxytoca were determined by measuring the diameter of the zone of inhibition. The cell viability of extracts was tested in a colon carcinoma cell line, HCT-116, by using a microculture tetrazolium technique (MTT) assay. Amino acids were extracted and quantified using an automatic amino acid analyzer. Then, gas chromatography–mass spectrometry (GC–MS) analysis was performed to identify the chemical constituents and fatty acids. As a result, the extracts of raw and roasted seeds in both Nigella species showed strong inhibition against Klebsiella oxytoca, and the raw seed extract of N.arvensis demonstrated moderate inhibition against S. pyogenes. The findings of the MTT assay indicated that all the extracts significantly decreased cancer cell viability. Moreover, N. sativa species possessed higher contents of the measured amino acids, except tyrosine, cystine, and methionine. The GC–MS analysis of extracts showed the presence of 22 and 13 compounds in raw and roasted N. arvensis, respectively, and 9 and 11 compounds in raw and roasted N. sativa, respectively. However, heat treatment decreased the detectable components to 13 compounds in roasted N. arvensis and increased them in roasted N. sativa. These findings indicate that N. arvensis and N. sativa could be potential sources of anticancer and antimicrobials, where the bioactive compounds play a pivotal role as functional components