Topic Modeling based text classification regarding Islamophobia using Word Embedding and Transformers Techniques

Islamophobia is a rising area of concern in the current era where Muslims face discrimination and receive negative perspectives towards their religion, Islam. Islamophobia is a type of racism that is being practiced by individuals, groups, and organizations worldwide. Moreover, the ease of access to social media platforms and their augmented usage has also contributed to spreading hate speech, false information, and negative opinions about Islam. In this research study, we focused to detect Islamophobic textual content shared on various social media platforms. We explored the state-of-the-art techniques being followed in text data mining and Natural Language Processing (NLP). Topic modelling algorithm Latent Dirichlet Allocation is used to find top topics. Then, word embedding approaches such as Word2Vec and Global Vectors for word representation (GloVe) are used as feature extraction techniques. For text classification, we utilized modern text analysis techniques of transformers-based Deep Learning algorithms named Bidirectional Encoders Representation from Transformers (BERT) and Generative Pre-Trained Transformer (GPT). For results comparison, we conducted an extensive empirical analysis of Machine Learning algorithms and Deep Learning using conventional textual features such as the Term Frequency-Inverse Document Frequency, N-gram, and Bag of words (BoW). The empirical based results evaluated using standard performance evaluation measures show that the proposed approach effectively detects the textual content related to Islamophobia. In the corpus of the study under Machine Learning models Support Vector Machine (SVM) performed best with an F1 score of 91%. The Transformer based core NLP models and the Deep Learning model Convolutional Neural Network (CNN) when combined with GloVe performed best among all the techniques except SVM with BoW. GPT, SVM when combined with BoW and BERT yielded the best F1 score of 92%, 92% and 91.9% respectively, while CNN performed slightly poor with an F1 score of 91%

Impact of Graphic Warning Labels on Cigarette Packs in Changing Smokers' Views and Habits: An Opinion Survey

Background: Smoking has become a major issue worldwide. With the advancement in technology, morevulnerable populations, such as teenagers, are also being harmed. One deterrent is the presence of graphiclabels on cigarette packs. With this rationale in mind, the objective of our study is to assess the impact ofthese warning labels on the habits and opinions of smokers.Methods: A cross-sectional study was conducted by distributing a validated paper-based questionnaire.The sample size was calculated to be 200 using statistical software. The study targeted students ofIslamabad, Pakistan, who were studying in twelfth grade and were smokers. The sampling method usedwas ‘snowball sampling’.Findings: 128 (64%) males and 72 (36%) females participated in the study. The mean age of the participantswas 17.59 ± 0.51 years. 40 participants reported choosing local brands for cigarettes due to cigarette‘freshness’, regardless of presence or absence of a graphic label, which was a new concept. 94% ofparticipants believed that presence of a visual label helped with understanding the harm and 78% believedthat the side effects were accurately portrayed. Participants who were more than 17 years of age believed thatthe graphic label provided a clear description of the consequences of smoking. Similar results were seen inthe female participants of the study.Conclusion: There is a general consensus on graphic labels altering the opinions of smokers. The presenceof these labels is, however, targeting only a specific type of audience and hence, should be expanded for alarger audienc

Honey Composition, Therapeutic Potential and Authentication through Novel Technologies: An Overview

Honey is acknowledged as a natural functional food with additional health benefits. Due to its medicinal and therapeutic properties, honey is being used in both pharmaceutical and food industries to develop products as a remedy against various types of ailments. Honey contains polyphenols, flavonoids, and other key compounds that play an important role in human health. Honey possesses anticancer and antimicrobial properties as well as contains antioxidant and anti-inflammatory substance. Some studies also highlighted the antidiabetic properties of honey. It supports the respiratory system and contributes beneficial effects to the cardiovascular system. As a functional and nutraceutical food, honey plays a significant role. Due to the modernization and digitalization in this era, the role of novel technologies for characterization and authentication of honey cannot be ignored. Hence, the main purpose of this chapter is to review the latest studies related to honey’s advantageous effects on human health and to highlight the novel technologies to detect the impurities in honey

Classification of adaptation measures and criteria for evaluation Case studies in the Indus River-Basin

This work was carried out by the Himalayan Adaptation, Water and Resilience (HI-AWARE) consortium under the Collaborative Adaptation Research Initiative in Africa and Asia (CARIAA) with financial support from the UK Government’s Department for International Development and the International Development Research Centre, Ottawa, Canada.This working paper is aimed at finding out the climate change adaptations going on across the three HI-AWARE Project Sites in Indus Basin, namely Hunza (High mountains), Soan Basin (Mid hill) and Chaj Doab ( Flood plains). Both autonomous and planned adaptations have been enlisted after thoroughly reviewing published and grey literature. Some focus group discus-sions and key informant interviews were also held in order to know about people experiences, perceptions and existing practices that they are carrying out to sustain their livelihood

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

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Comparative Analysis for Machine-Learning-Based Optimal Control of Upper Extremity Rehabilitation Robots

It has been observed from many pieces of research and through applications that robotic movements using human interaction are considered dangerous, tiresome and require extraordinary precision and smooth control. Specifically, medical and healthcare applications have been the highest priority in recent years. The concept of rehabilitation using robotics was introduced during the 1980s with the motive of freeing therapists from repetitive work while treating an increasing elderly population requiring physiotherapy. Furthermore, the consistency of the robot’s operation and the volume of repetitions has increased. They can assist therapists in performing tedious tasks and let them concentrate on several patients simultaneously. Several types of rehabilitation robot devices have been produced in recent years with different modes of training and control strategies using various control algorithms. In this research paper, a comprehensive overview of rehabilitation in relation to robotics is presented. The main aim is to determine robust controlling optimization for the smooth control of robotic movement, as these movements require a lot of precision and accuracy. The analysis showed that M-PSO was found to be very effective and robust in finding the best optimal values, as the Modified PSO achieved the minimum root mean square value and a best fit of 98.7

Removal of Chromium (VI) from the Steel Mill Effluents Using the Chemically Modified Leaves of <i>Pteris vittata</i> as Adsorbent

Chromium (Cr), a metal that is released in appreciable amounts from the steel industry into water bodies, is not only the main causative agent of lung cancer in human but also negatively affects the metabolic activities of plants. Keeping in view the hazardous effects of Cr(VI), the present study was aimed to eliminate it from industrial effluents of steel mills installed in Dargai District Malakand, Pakistan, using chemically modified Pteris vittata plant leaves as an adsorbent. The instrumental techniques such as FTIR, surface area analysis, SEM, TGA and EDX were used to evaluate surface functionality, morphology, thermal stability and elemental composition of the modified leaves. To identify the ideal conditions for the biosorption process, batch adsorption tests were carried out under varied conditions of pH, contact time, initial metal concentration, biosorbent dose, as well as temperature. Various models, such as those of Freundlich, Jovanovich, Temkin, Langmuir, and Harkins–Jura, were utilized to explain the isothermal experimental data. The high value of R2 (0.991) was exhibited by the Langmuir model. Pseudo-first-order, power function, pseudo-second-order, intraparticle diffusion, and Natarajan–Khalaf models were employed to obtain an insight into kinetics of the process. The highest R2 value, close to unity was recorded with pseudo-second order. At pH = 2, the best elimination of Cr was observed with maximum uptake capacity qmax(66.6 mg/g) as calculated from the Langmuir isotherm. The thermodynamic analysis, which was conducted at different temperatures, showed that the nature of this sorption process was exothermic and spontaneous. The modified leaves-based biosorbent could be used as an alternative adsorbent for effective Cr elimination from water, and its use could be extended to other heavy metals and organic pollutants as well, and further experimentation are needed in this regard

What is Core and What Future Holds for Blockchain Technologies and Cryptocurrencies: A Bibliometric Analysis

A new era awaits the development of cryptocurrency and blockchain technologies. This study highlights the influential and conceptual aspects of blockchain and cryptocurrency literature with bibliometric analysis. There are 1965 related documents from 2015 and 2020, represent various structures and technologies, cryptocurrencies, and blockchain applications. We have deployed “bibliometrix 3.0”, the r-package, and VOS viewer to analyze key literature aspects. IEEE Access is the core journal for cryptocurrency and blockchain publications. The University of Cagliari, Notreported, and Peking University are key affiliations, and the USA, China, and India are core countries for literary research. H. Wang is the core author with the central theme of security of blockchain technologies. It is a set basis for conceptual aspects, core, and future research streams and themes. The study proposes three research streams: the structure of cryptocurrencies and implications of blockchain technologies, privacy, security management of data and information, and development of optimal information systems. The study further segregates themes into highly centralized and motor themes that are also core themes. Topics related to Consensus protocols, proof of work, distribution ledger technology, blockchain, and cryptocurrency procedures and structure comes under core themes. Highly developed and emerging themes are considered as a stepping stone for future directions. Underlying topics are related to fintech, Islamic finance, valuations, and dynamics of cryptocurrencies