Models for MAGDM with dual hesitant q-rung orthopair fuzzy 2-tuple linguistic MSM operators and their application to COVID-19 pandemic.

In this article, we introduce dual hesitant q -rung orthopair fuzzy 2-tuple linguistic set (DHq-ROFTLS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into dual hesitant q -rung orthopair fuzzy set (DHq-ROFS). DHq-ROFTLS is a better way to deal with uncertain and imprecise information in the decision-making environment. We elaborate the operational rules, based on which, the DHq-ROFTL weighted averaging (DHq-ROFTLWA) operator and the DHq-ROFTL weighted geometric (DHq-ROFTLWG) operator are presented to fuse the DHq-ROFTL numbers (DHq-ROFTLNs). As Maclaurin symmetric mean (MSM) aggregation operator is a useful tool to model the interrelationship between multi-input arguments, we generalize the traditional MSM to aggregate DHq-ROFTL information. Firstly, the DHq-ROFTL Maclaurin symmetric mean (DHq-ROFTLMSM) and the DHq-ROFTL weighted Maclaurin symmetric mean (DHq-ROFTLWMSM) operators are proposed along with some of their desirable properties and some special cases. Further, the DHq-ROFTL dual Maclaurin symmetric mean (DHq-ROFTLDMSM) and weighted dual Maclaurin symmetric mean (DHq-ROFTLWDMSM) operators with some properties and cases are presented. Moreover, the assessment and prioritizing of the most important aspects in multiple attribute group decision-making (MAGDM) problems is analysed by an extended novel approach based on the proposed aggregation operators under DHq-ROFTL framework. At long last, a numerical model is provided for the selection of adequate medication to control COVID-19 outbreaks to demonstrate the use of the generated technique and exhibit its adequacy. Finally, to analyse the advantages of the proposed method, a comparison analysis is conducted and the superiorities are illustrated.

Comparison of Tobacco Consumption among Adults in SAARC Countries (Pakistan, India and Bangladesh).

OBJECTIVE: To compare the findings of Global adult tobacco surveys (GATS) conducted in SAARC Countries. METHODS: The national representative data from Pakistan, India, and Bangladesh was used as GATS was done in these three countries of SAARC. The key variables were selected where information was consistently taken like current smokers, smokeless tobacco users, exposure to second-hand smoke, advise by health care provider to quit, monthly expenditure and noticing of health warning label and other information related to daily tobacco users (smoke, smokeless) mean age of initiation and mean number of cigarettes consumed per day were also collected. Chi-square test was applied and p-value was considered significant at <0.05. RESULTS: Overall tobacco consumption was significantly high (43.3%) in Bangladesh (Pakistan 19.1% and India 34.6%). Similarly, current smokers were significantly more in Bangladesh 23% (India 14% and Pakistan 12%) and smokeless tobacco was significantly more in Bangladesh 27.2% (India 25.9% and Pakistan 7.7%). Exposure to second-hand smoke at work was 69.1% in Pakistan (63% in Bangladesh and 29.9% in India). Monthly expenditure on cigarettes was also high in Pakistan 7.51 USD (India 6.26 USD and Bangladesh 4.57USD). Mean age of initiation was 18.8 years in Bangladesh, (17.8 India and 18.7 Pakistan). Mean number of cigarettes consumed was significantly high in Pakistan i.e. 13.6 (6.2 in India and 5.1 Bangladesh). CONCLUSIONS: All the three South Asian countries have a high prevalence of tobacco consumption. Tobacco use was high in Bangladesh but smokeless tobacco among males was high in India and mean number of cigarettes daily was high in Pakistan.

Prevalence of Smokeless Tobacco Use in Pakistan: Insight from the Global Adult Tobacco Survey Pakistan (GATS Pakistan-2014).

OBJECTIVE: Prevalence of tobacco consumption is increasing including both smoked and smokeless tobacco. The objective of this paper is to highlight the prevalence of smokeless tobacco use, its demographic trends as well as socioeconomic determinants based on Global Adult Tobacco Survey 2014 (GATS) -Pakistan. METHODS: Secondary analysis of GATS data was done which was a nationally representative survey, conducted among non-institutionalized males and females aged 15 years and above. The survey included a total of 9,856 households which were selected using multistage stratified cluster sampling technique. RESULTS: Secondary analysis of GATS data revealed that 8.6% of the Pakistani population was current users of smokeless tobacco; among them, 8.0% were daily users and 0.6% were less than daily users. Prevalence of SLT use was higher in males (13.7%) compared to females (3.9%) (p = 0.000). Mean age of male users was 39.96±14.43 years and of females was 47.71±16.21 (p=0.000). Males (3.959 95% CI = 3.291-4.764) and respondents with primary or less education (2.216 95%CI = 1.841-2.668) were at higher odds of SLT use prevalence. Among daily users, Naswar was the preferred (71.8%) SLT product in males, compared to females (p = 0.000). Whereas, in females, use of Paan with tobacco (26.4%) (P = 0.000) and Naas (20.9%) (P = 0.000) was more common compared to males. Among SLT users, 71.1% participants used to spend 1-100 Rs (0.0095-0.95USD) per week on purchase of SLT products. However 28.9% were spending more than one dollar on the purchase of SLT products including 19.1% who were spending Rs 101-200 (0.96-1.9USD) followed by 7.2% spending Rs 201-300 (1.91-2.85 USD) and 2.6% spending Rs. >300 (>2.85 USD). CONCLUSIONS: Males and less educated individuals should be targeted with behavioral interventions for control of SLT use. Males started SLT use at an earlier age compared to females which can result in premature morbidity and mortality in males. SLT products are cheaper compared to cigarettes, therefore, taxes need to be levied on SLT products.

Exposure of the Adult Pakistani Population to Second-Hand Smoke - An insight from Global Adult Tobacco Survey of Pakistan 2014.

OBJECTIVE: About one-third of the world population is exposed to second hand smoke (SHS) with estimated 600,000 annual deaths. The objective of this article is to determine the exposure of adult Pakistani population to SHS and its association with different demographic variables based on data of Global Adult Tobacco Survey (GATS) conducted in 2014 in Pakistan. METHODS: Secondary analysis of Global Adult Tobacco Survey (GATS) data was done which is a global standard used for systematically monitoring use of both smoked and smokeless tobacco products. GATS Pakistan was a nationally representative survey, conducted in all four provinces among adult males and females aged15 years and above. Using multistage stratified cluster sampling technique a total of 9,856 households were selected and finally 7,831 individuals were enrolled. RESULTS: At homes around 43.3% individuals were exposed to SHS. Univariate analysis revealed that overall males (Odds Ratio, OR: 1.17 CI: 1.04-1.30, p=0.006) and less educated (OR: 1.30, CI: 1.16-1.46, p=0.000) group were at higher odds of being exposed to SHS at homes. Over all exposure to second hand smoke at home was also significantly high among urban residents (p = 0.000). Among nonsmokers age group 15 -35 years (odds ratio, 1.24 CI:1.09-1.04, P=0.01) and less educated group (OR 1.24, CI: 1.09-1.40, p=0.001) were at higher odds of being exposed to SHS at home At indoor workplaces, overall 69.1% and among non-smokers, 65.3% individuals were exposed to SHS. Univariate analysis has shown that less educated group (OR: 1.525, CI: 1.012-2.298, p=0.043) was at higher odds of being exposed to SHS at indoor workplaces. Among various public places exposure of participants to SHS was highest (86%) at restaurants, followed by public transport (74%), marriage halls (65%), universities (46%), health care facilities (35%) and least at schools (20%).. CONCLUSIONS: Less educated males were more exposed to second-hand smoke both at work places and public places; therefore to start with interventions, work places and public places should be a priority as at home results could be confounded by self-smoking as well.

Determinants of Smoked Tobacco Consumption among Pakistani Adults: An Analysis from GATS Pakistan 2014.

OBJECTIVE: An in-depth analysis of GATS 2014 is performed to study the various demographic determinants of smoked tobacco consumption among Pakistani adults. METHODS: The Global Adult Tobacco Survey (GATS) is a standardized surveillance mechanism regarding monitoring of tobacco consumption globally, that uses three stage cluster random sampling technique to have a representative data. We performed the complex data set analysis using SPSS V 15. The associations were determined by carrying out univariate analysis, and determining chi squares for categorical variables. RESULTS: Overall current smoking prevalence was found to be 12.4%. The univariate analysis revealed male gender (OR: 14.1 CI= 11.2-17.7, p value 0.000), little or no education (OR: 1.4 CI=1.2-1.6, p-value 0.000), living in urban areas (OR: 0.7 CI= 0.6-0.8, p-value 0.000) and avoiding smoking attempts in young age till 25 years (OR: 0.2 CI= 0.1-0.2, p value 0.000) were determinants. Assosiation of demographic determinants with cessation behaviour showed that the health concern was the primary reason to ever stop smoking among both urban rural dwellers, educated and uneducated and respondents aged 25 years and above. Educational status, age of respondent and residence had almost no significant effect on cessation behaviour of smoked tobacco users. CONCLUSIONS: Males having low education and living in rural area puts an adult Pakistani at high risk of becoming the user of smoked tobacco. Health education involving primary health care providers particularly focusing on rural areas will reduce the prevalence of smoking.

Effective multi-attribute group decision-making approach to study astronomy in the probabilistic linguistic q-rung orthopair fuzzy VIKOR framework.

This study employs a novel fuzzy logic-based framework to address multi-attribute group decision-making problems commonly encountered in modern astronomy. Our approach utilizes the probabilistic linguistic q-rung orthopair fuzzy set (PLq-ROFS) to handle the inherent uncertainties associated with astronomical data. The PLq-ROFS offers significant advantages over existing fuzzy sets like probabilistic hesitant, linguistic intuitionistic, and linguistic Pythagorean fuzzy sets, which comprise both stochastic and non-stochastic uncertainties simultaneously. To aggregate the probabilistic linguistic decision information effectively, we propose two novel operators: the PLq-ROF weighted power average (PLq-ROFWPA) and the PLq-ROF weighted power geometric (PLq-ROFWPG). These operators form the foundation of a novel method within the PLq-ROF environment. Furthermore, this study integrates the PLq-ROF framework with the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model, a widely used decision-making (DM) tool known for its ability to balance group utility maximization with individual regret minimization. This integration leads to the PLq-ROF-VIKOR model, a novel approach for ranking alternative solutions based on the subjective preferences of decision-makers. The effectiveness of the proposed method is demonstrated through a real-world case study in astronomy, accompanied by both parameter and comparative analyses. These analyses highlight the efficiency and accuracy of the PLq-ROF-VIKOR model, ultimately leading to the conclusion that cosmology is the most optimal key finding in this case study.

Decision analysis with IDOCRIW-QUALIFLEX approach in the 2TLq-ROF environment: An application of accident prediction models in Pakistan.

In Pakistan, the assessment of road safety measures within road safety management systems is commonly seen as the most deficient part. Accident prediction models are essential for road authorities, road designers, and road safety specialists. These models facilitate the examination of safety concerns, the identification of safety improvements, and the projection of the potential impact of these modifications in terms of collision reduction. In the context described above, the goal of this paper is to utilize the 2-tuple linguistic q-rung orthopair fuzzy set (2TLq-ROFS), a new and useful decision tool with a strong ability to address uncertain or imprecise information in practical decision-making processes. In addition, for dealing with the multi-attribute group decision-making problems in road safety management, this paper proposes a new 2TLq-ROF integrated determination of objective criteria weights (IDOCRIW)-the qualitative flexible multiple criteria (QUALIFLEX) decision analysis method with a weighted power average (WPA) operator based on the 2TLq-ROF numbers. The IDOCRIW method is used to calculate the weight of attributes and the QUALIFLEX method is used to rank the options. To show the viability and superiority of the proposed approach, we also perform a case study on the evaluation of accident prediction models in road safety management. Finally, the results of the experiments and comparisons with existing methods are used to explain the benefits and superiority of the suggested approach. The findings of this study show that the proposed approach is more practical and compatible with other existing approaches.

Semi-supervised ensemble learning for human activity recognition in casas Kyoto dataset.

-The automatic identification of human physical activities, commonly referred to as Human Activity Recognition (HAR), has garnered significant interest and application across various sectors, including entertainment, sports, and notably health. Within the realm of health, a myriad of applications exists, contingent upon the nature of experimentation, the activities under scrutiny, and the methodology employed for data and information acquisition. This diversity opens doors to multifaceted applications, including support for the well-being and safeguarding of elderly individuals afflicted with neurodegenerative diseases, especially in the context of smart homes. Within the existing literature, a multitude of datasets from both indoor and outdoor environments have surfaced, significantly contributing to the activity identification processes. One prominent dataset, the CASAS project developed by Washington State University (WSU) University, encompasses experiments conducted in indoor settings. This dataset facilitates the identification of a range of activities, such as cleaning, cooking, eating, washing hands, and even making phone calls. This article introduces a model founded on the principles of Semi-supervised Ensemble Learning, enabling the harnessing of the potential inherent in distance-based clustering analysis. This technique aids in the identification of distinct clusters, each encapsulating unique activity characteristics. These clusters serve as pivotal inputs for the subsequent classification process, which leverages supervised techniques. The outcomes of this approach exhibit great promise, as evidenced by the quality metrics' analysis, showcasing favorable results compared to the existing state-of-the-art methods. This integrated framework not only contributes to the field of HAR but also holds immense potential for enhancing the capabilities of smart homes and related applications.

Situation analysis of research ethics governance in Pakistan.

Background: Mapping of ethical governance structures is very useful in identifying strengths and weaknesses in order to uphold integrity and ensure standardization. However, reliable countrywide data about ethical review committees (ERCs) is unavailable in Pakistan. Aims: To evaluate the research ethics governance mechanisms at national level and at key healthcare institutions in Pakistan. Methods: This pilot mapping exercise used a mixed-methods approach, involving a cross-sectional survey of 19 key healthcare research institutions, and structured in-depth interviews with the chairs of the National Bioethics Committee and the Drug Regulatory Authority of Pakistan. Results: Eighteen institutions responded to the ethics mapping survey. Twelve public sector ERCs had a permanent structure and 17 had formal terms of reference. Seven ERCs claimed accreditation, although no central accreditation agency exists in Pakistan. Eight ERCs were chaired by the heads of the institutions. There was no fixed tenure for the heads in 13 committees, and 14 committees allowed multiple terms. Six ERCs had follow-up mechanisms for ethical approvals, and 6 took punitive actions in response to any deviation from an approved protocol, or to a scientific misconduct. Two respondents recalled situations where applicants pressured committee members for favourable approvals. Survey respondents mentioned the lack of central research ethics guidelines as a weakness of the national governance system. Structured interviews revealed the need for formal training of committee members and capacity strengthening, particularly for administrative staff. Conclusion: There is a need to develop guidelines for local ethics governance in Pakistan, and ensure accreditation of ERCs through the National Bioethics Committee to uphold the integrity of the ethics governance structure.

A new MAGDM method with 2-tuple linguistic bipolar fuzzy Heronian mean operators.

In this article, we introduce the 2-tuple linguistic bipolar fuzzy set (2TLBFS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into bipolar fuzzy set. The 2TLBFS is a better way to deal with uncertain and imprecise information in the decision-making environment. We elaborate the operational rules, based on which, the 2-tuple linguistic bipolar fuzzy weighted averaging (2TLBFWA) operator and the 2-tuple linguistic bipolar fuzzy weighted geometric (2TLBFWG) operator are presented to fuse the 2TLBF numbers (2TLBFNs). The Heronian mean (HM) operator, which can reflect the internal correlation between attributes and their influence on decision results, is integrated into the 2TLBF environment to analyze the effect of the correlation between decision factors on decision results. Initially, the generalized 2-tuple linguistic bipolar fuzzy Heronian mean (G2TLBFHM) operator and generalized 2-tuple linguistic bipolar fuzzy weighted Heronian mean (G2TLBFWHM) operator are proposed and properties are explained. Further, 2-tuple linguistic bipolar fuzzy geometric Heronian mean (2TLBFGHM) operator and 2-tuple linguistic bipolar weighted geometric Heronian mean (2TLBFWGHM) operator are proposed along with some of their desirable properties. Then, an approach to multi-attribute group decision-making (MAGDM) based on the proposed aggregation operators under the 2TLBF framework is developed. At last, a numerical illustration is provided for the selection of the best photovoltaic cell to demonstrate the use of the generated technique and exhibit its adequacy.

Evaluation of divergent yeast genera for fermentation-associated stresses and identification of a robust sugarcane distillery waste isolate Saccharomyces cerevisiae NGY10 for lignocellulosic ethanol production in SHF and SSF.

BACKGROUND: Lignocellulosic hydrolysates contain a mixture of hexose (C6)/pentose (C5) sugars and pretreatment-generated inhibitors (furans, weak acids and phenolics). Therefore, robust yeast isolates with characteristics of C6/C5 fermentation and tolerance to pretreatment-derived inhibitors are pre-requisite for efficient lignocellulosic material based biorefineries. Moreover, use of thermotolerant yeast isolates will further reduce cooling cost, contamination during fermentation, and required for developing simultaneous saccharification and fermentation (SSF), simultaneous saccharification and co-fermentation (SScF), and consolidated bio-processing (CBP) strategies. RESULTS: In this study, we evaluated thirty-five yeast isolates (belonging to six genera including Saccharomyces, Kluyveromyces, Candida, Scheffersomyces, Ogatea and Wickerhamomyces) for pretreatment-generated inhibitors {furfural, 5-hydroxymethyl furfural (5-HMF) and acetic acid} and thermotolerant phenotypes along with the fermentation performances at 40 °C. Among them, a sugarcane distillery waste isolate, Saccharomyces cerevisiae NGY10 produced maximum 49.77 ± 0.34 g/l and 46.81 ± 21.98 g/l ethanol with the efficiency of 97.39% and 93.54% at 30 °C and 40 °C, respectively, in 24 h using glucose as a carbon source. Furthermore, isolate NGY10 produced 12.25 ± 0.09 g/l and 7.18 ± 0.14 g/l of ethanol with 92.81% and 91.58% efficiency via SHF, and 30.22 g/l and 25.77 g/l ethanol with 86.43% and 73.29% efficiency via SSF using acid- and alkali-pretreated rice straw as carbon sources, respectively, at 40 °C. In addition, isolate NGY10 also produced 92.31 ± 3.39 g/l (11.7% v/v) and 33.66 ± 1.04 g/l (4.26% v/v) ethanol at 40 °C with the yields of 81.49% and 73.87% in the presence of 30% w/v glucose or 4× concentrated acid-pretreated rice straw hydrolysate, respectively. Moreover, isolate NGY10 displayed furfural- (1.5 g/l), 5-HMF (3.0 g/l), acetic acid- (0.2% v/v) and ethanol-(10.0% v/v) tolerant phenotypes. CONCLUSION: A sugarcane distillery waste isolate NGY10 demonstrated high potential for ethanol production, C5 metabolic engineering and developing strategies for SSF, SScF and CBP.

Emerging concepts of quality assurance in clinical laboratories.

Quality Assurance is a management system designed to achieve an acceptable level of quality services, prevent poor quality and in laboratories is intended to ensure reliability of results. It comprehensively includes controlling the quality of procedures at each and every step including Pre-analytical (specimen collection and transport), Analytical (specimen processing in the lab) and Post-analytical (reporting and interpretation of results). Concept of total quality management (TQM) is closely interlinked with good laboratory practices and goes far beyond the widely practiced conventional Quality Control (QC) procedures. TQM includes Technical accuracy and precision, equipment and supplies, staff training and skill, financial management (cost effectiveness), lab safety, communication etc. Recent pressures on pathology laboratories have meant that laboratories no longer have the numbers of scientists and pathologists they had in the past. This has resulted in more questions being asked of the QA staff with a steady increase in the number of scientists employed to address this demand. Quality improvement in the modern clinical laboratory environment entails the continuous inspection and refinement of processes to ensure the efficient delivery of services that meet the needs and expectations of those who use them.