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Abstract Background The Manhattan Lupus Surveillance Program (MLSP), a population-based retrospective registry of patients with systemic lupus erythematosus (SLE), was used to investigate the prevalence of cardiovascular disease events (CVE) and compare rates among sex, age and race/ethnicity to population-based controls. Methods Patients with prevalent SLE in 2007 aged ≥ 20 years in the MLSP were included. CVE required documentation of a myocardial infarction or cerebrovascular accident. We calculated crude risk ratios and adjusted risk ratios (ARR) controlling for sex, age group, race and ethnicity, and years since diagnosis. Data from the 2009–2010 National Health and Nutrition Examination Survey (NHANES) and the 2013–2014 NYC Health and Nutrition Examination Survey (NYC HANES) were used to calculate expected CVE prevalence by multiplying NHANES and NYC HANES estimates by strata-specific counts of patients with SLE. Crude prevalence ratios (PRs) using national and NYC estimates and age standardized prevalence ratios (ASPRs) using national estimates were calculated. Results CVE occurred in 13.9% of 1,285 MLSP patients with SLE, and risk was increased among men (ARR:1.7, 95%CI:1.2–2.5) and older adults (age > 60 ARR:2.5, 95%CI:1.7–3.8). Compared with non-Hispanic Asian patients, CVE risk was elevated among Hispanic/Latino (ARR:3.1, 95%CI:1.4-7.0) and non-Hispanic Black (ARR:3.5, 95%CI1.6-7.9) patients as well as those identified as non-Hispanic and in another or multiple racial groups (ARR:4.2, 95%CI:1.1–15.8). Overall, CVE prevalence was higher among patients with SLE than nationally (ASPR:3.1, 95%CI:3.0-3.1) but did not differ by sex. Compared with national race and ethnicity-stratified estimates, CVE among patients with SLE was highest among Hispanics/Latinos (ASPR:4.3, 95%CI:4.2–4.4). CVE was also elevated among SLE registry patients compared with all NYC residents. Comparisons with age-stratified national estimates revealed PRs of 6.4 (95%CI:6.2–6.5) among patients aged 20–49 years and 2.2 (95%CI:2.1–2.2) among those ≥ 50 years. Male (11.3, 95%CI:10.5–12.1), Hispanic/Latino (10.9, 95%CI:10.5–11.4) and non-Hispanic Black (6.2, 95%CI:6.0-6.4) SLE patients aged 20–49 had the highest CVE prevalence ratios. Conclusions These population-based estimates of CVE in a diverse registry of patients with SLE revealed increased rates among younger male, Hispanic/Latino and non-Hispanic Black patients. These findings reinforce the need to appropriately screen for CVD among all SLE patients but particularly among these high-risk patients.

Excessive dependence on fossil fuels has precipitated various challenges, including Greenhouse Gas (GHG) emissions, health hazards, and the depletion of natural resources. Such perils underscore the importance of conducting requisite risk assessments for alternative fuel sources like Compressed Natural Gas (CNG) to ensure their safe utilization. This study undertakes a quantitative risk assessment encompassing diverse facets of the CNG sector holistically, aiming to pinpoint, analyze, and appraise risks, thus empowering policymakers to devise targeted mitigation strategies. To achieve this goal, the collected data undergoes analysis via an integrated approach combining the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Technique of Order Preference by Similarity to Ideal Solution (F-TOPSIS). The study's findings reveal a heightened risk of explosion within the CNG sector owing to its highly combustible nature. Additionally, it computes an overall risk index of 0.266 for the CNG sector in a developing nation like Pakistan, indicating a relatively lower risk level compared to other fuel sources. Policymakers are thus advised to undertake requisite measures concerning infrastructure, customer safety, and environmental and economic stability to accrue both immediate and long-term benefits. The application of hybrid techniques for the risk assessment of the CNG sector in the case of a developing country marks the novelty of this study and a study of the first of its kind.

Abstract In South Asia, Pakistan has a long and deadly history of floods that cause losses to various infrastructures, lives, and industries. This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt. The assessment of flood risk mitigation strategies in this study is based on certain criteria, which are analyzed using the fuzzy full consistency method. Moreover, flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment (WASPAS) method, considering previously prioritized criteria. According to the results, lack of governance, lack of funding and resources, and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan. Adopting hard engineering strategies (e.g., dams, reservoirs, river straightening and dredging, embankments, and flood relief channels), maintaining existing infrastructure, and adopting soft engineering strategies (flood plain zoning, comprehensive flood risk assessment, and sophisticated flood modeling) are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method. The highest weight (0.98) was assigned to the adoption of hard engineering strategies to mitigate flood risks. The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods, during which approximately one-third of the nation was submerged. This focus on a recent and highly significant event enhances the study’s relevance and contributes a unique perspective to the existing literature on flood risk management. The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation. It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future.

Genetic Algorithm is an optimization technique inspired by nature. The technique has been used by scientists and engineers for real-life search and optimization problems. This work makes use of the genetic algorithm for the solution of the traveling salesman problem. This work focuses on real-time problems; the algorithm is used to find the optimum path for sales travelers inside the Khyber Pakhtunkhwa Province of Pakistan. The solution provides the shortest distance between the cities to be traveled and gives the optimal route. The coding is done in Python-3 and software is developed for the traveling salesmen, where the salesmen can select the cities, they want to travel, and the software will provide the optimal path and the distance.

Objective: To analyze the role of ASA status in carrying out laparoscopic cholecystectomies by evaluating the perioperative findings of patients. Study Design: Cross-sectional study. Place and Duration of Study: Combined Military Hospital, Rawalpindi Pakistan, from Jan 2019 to Jan 2021. Methodology: Laparoscopic cholecystectomies were performed on 385 patients with symptomatic gallstones. The inclusion criteria comprised of symptomatic cholelithiasis, acute cholecystitis and chronic cholecystitis. Data for the perioperative findings such as gallbladder grades, bile, cystic duct, cystic artery and Common Bile Duct were recorded during the study. Results: The study included 226(59%) female patients and 159(41%) males. The mean age was 48.15±15.5 years. There were 145(37.66%) patients in American Society of Anesthesiologists Classification ASA-I, 174(45.20%) patients in ASA-II and 66(17.14%) in ASA-III. Results showed that the abnormalities of cystic duct were 34(23.4%) in ASA-I, 68(39.1%) in ASA-II and 43(65.2%) in ASA-III. For CBD, they were 7(4.8%) in ASA-I, 49(28.2%) in ASA-II and 44(66.2%) in ASA-III. The complications of cystic artery and bile were 34(23.4%) in ASA-I, 60(34.5%) in ASA-II, 46(69.7%) in ASA-III and 82(56.6%) in ASA-I, 119(68.4%) in ASA-II, 50(75.8%) in ASA-III respectively. The gallbladder grades I were 27(18.6%) in ASA-I and (4.5%) in ASA-III whereas, grades V were 7(4.8%) in ASA-I and 20(30.3%) in ASA-III. Conclusion: Peri-operative morbidity increased with increasing ASA status, therefore, there is a significant relationship between ASA Status and peri-operative findings.

OBJECTIVE: To estimate the proportion of electronic media usage among teenagers and identify the association between behavior and the use of electronic media. METHODOLOGY: An analytical cross-sectional study conducted from December 2021 to February 2022. A sample of teenagers (n=340) were selected from primary care clinics of Chanesar Goth and Hijrat Colony, Karachi. Participants were questioned regarding their daily usage of media. Strengths and Difficulties Questionnaire was administered to assess the behavior. Data was analyzed using SPSS 23. RESULTS: 350 teenagers were enrolled in the study, and the gender distribution was almost equal. Daily usage of media included Television(88.9%), videogames(47.4%), computer/laptop(79%), mobile phone (90.3%) and tablet(20.9%). The content viewed were movies (68.9%), Facebook (72%) and Chats/ WhatsApp (76.6%). The mean of total difficulty score in our study population was 19.1 (SD: 4.8). On multivariate analysis, higher difficulty score was positively associated with increasing age (Beta: 0.428, 95% Cis: 0.070 -0.785, p-value: 0.019) and total screen time (Beta: 0.003, 95% Cis: 0.001 -0.005, p-value: 0.036) while difficulty score was negatively associated with male gender (Beta: -1.223, 95% Cis: -2.441 -- -0.005, p-value: 0.049). CONCLUSION: Our population's media exposure and difficulty scores are higher than those of other populations. Media exposure needs to be reduced to control psychosocial problems

In a global context, the development of new technologies and becomes an entrepreneurial challenge for the near future. One of the most promising phenomena of this new way are startups. This phenomenon is also emerging in developing countries like Pakistan. However, the success rate of startups is prone to several micro and macro environmental challenges and if these challenges not addressed properly, cause failure of startups. This study intends to contribute to research by proposing a methodological approach to find out the macro-environmental factors and their impact on startups from the perspective of developing countries. Firstly, the PESTEL (Political, Economic, Social, Technological, Environmental, and Legal) analysis is conducted to identify macro-environmental factors displayed in the Cause and effect diagram. Secondly, the Fuzzy Failure Mode and Effect Analysis (FFMEA) is applied to prioritize the risks to devise strategies. Thirdly, to formulate a risk mitigation strategies and policies to support startup ecosystem. The results show that inflation rates, currency depreciation, and corruption are significant challenges for startups. Therefore, this paper aims to help policy makers, entrepreneurs and business schools to work in join collaboration to devise risk mitigation strategies for startups in emerging economies.

This research aims to develop an intelligent framework for quality control and fault detection in pre-production and post-production systems in Industry 4.0. In the pre-production system, the health of the manufacturing machine is monitored. In this study, we examine the gear system of induction motors used in industries. In post-production, the product is tested for quality using a machine vision system. Gears are fundamental components in countless mechanical systems, ranging from automotive transmissions to industrial machinery, where their reliable operation is vital for overall system efficiency. A faulty gear system in the induction motor directly affects the quality of the manufactured product. Vibration data, collected from the gear system of the induction motor using vibration sensors, are used to predict the motor’s health condition. The gear system is monitored for six different fault conditions. In the second part, the quality of the final product is inspected with the machine vision system. Faults on the surface of manufactured products are detected, and the product is classified as a good or bad product. The quality control system is developed with different deep learning models. Finally, the quality control framework is validated and tested with the evaluation metrics.

ObjectiveLeveraging the Manhattan Lupus Surveillance Program (MLSP), a population-based registry of cases of systemic lupus erythematosus (SLE) and related diseases, we investigated the proportion of SLE with concomitant rheumatic diseases, including Sjögren’s disease (SjD), antiphospholipid syndrome (APLS), and fibromyalgia (FM), as well as the prevalence of autoantibodies in SLE by sex and race/ethnicity.MethodsPrevalent SLE cases fulfilled one of three sets of classification criteria. Additional rheumatic diseases were defined using modified criteria based on data available in the MLSP: SjD (anti-SSA/Ro positive and evidence of keratoconjunctivitis sicca and/or xerostomia), APLS (antiphospholipid antibody positive and evidence of a blood clot), and FM (diagnosis in the chart).Results1,342 patients fulfilled SLE classification criteria. Of these, SjD was identified in 147 (11.0%, 95% CI 9.2–12.7%) patients with women and non-Latino Asian patients being the most highly represented. APLS was diagnosed in 119 (8.9%, 95% CI 7.3–10.5%) patients with the highest frequency in Latino patients. FM was present in 120 (8.9%, 95% CI 7.3–10.5) patients with non-Latino White and Latino patients having the highest frequency. Anti-dsDNA antibodies were most prevalent in non-Latino Asian, Black, and Latino patients while anti-Sm antibodies showed the highest proportion in non-Latino Black and Asian patients. Anti-SSA/Ro and anti-SSB/La antibodies were most prevalent in non-Latino Asian patients and least prevalent in non-Latino White patients. Men were more likely to be anti-Sm positive.ConclusionData from the MLSP revealed differences among patients classified as SLE in the prevalence of concomitant rheumatic diseases and autoantibody profiles by sex and race/ethnicity underscoring comorbidities associated with SLE.

Mouhammad J Alawad,1 Mohammad Abu-Tineh,2 Awni Alshurafa,2 Alaa Al-Taie,3 Anil Yousaf,2 Mohamed A Yassin2 1Department of Medical Education, Internal Medicine Residency Program, Hamad Medical Corporation, Doha, Qatar; 2Department of Medical Oncology, Hematology and BMT Section, National Center for Hamad Medical Corporation, Doha, Qatar; 3Clinical Imaging Department, Hamad Medical Corporation, Doha, QatarCorrespondence: Mouhammad J Alawad, Department of Medical Education, Internal Medicine Residency Program, Hamad Medical Corporation, PO Box 3050, Doha, Qatar, Tel +974 33078745, Fax +97444397857, Email www.wad7a123@gmail.comAbstract: Glanzmann thrombasthenia is a bleeding disorder with a low incidence. It typically manifests as superficial bleeding episodes, which tend to be mild. Deep organ involvement is not uncommon but remains rare due to the rarity of the disease itself and the unusual association between platelet disorders and deep organ implications. A 17-year-old boy with Glanzmann thrombasthenia since infancy developed ankle pain after a minor trauma. His initial workup was negative, but he continued to experience ankle pain. A magnetic resonance imaging (MRI) done after four weeks suggested siderotic synovitis. The patient was lost to follow-up after that and returned after two years with recurrent left ankle pain. Imaging and studies have shown evidence of chronic arthropathy. A specialized orthopedic team assessed the patient. The patient underwent intra-articular steroid injection for pain relief and was referred to continue physical therapy. In conclusion, hemarthrosis is more common in hemophilia than in platelet disorders and has potential morbidity and quality-of-life implications.Keywords: Glanzmann thrombasthenia, hemarthrosis, synovitis

Advancement in technologies such as robotic industries and artificial intelligence bring fear among human being that jobs will be substituted by robots. Base on the panel data of 28 China's manufacturing industries, this research analyzed the impact of technical progress bias on employment. First, we calculate the technical progress bias index of 28 industries base on the stochastic frontier model with transcendental logarithm function found 16 industries were toward the skilled labor while the remaining 12 industries were toward the unskilled labor. Second, the empirical results show that technical progress bias has a positive impact on the total manufacturing employment and significant positive effect on the unskilled labor, while no significant impact on skilled labor employment. Third, the threshold effect test proves that if taking industry value-added per capita or R&D capital stock as threshold variable, the threshold about the impact exist, making the impact on skilled labor was insignificant.

Purpose – Social development is the ultimate goal of every nation, and climate change is a major stumbling block. Climate Risk Index has documented several climate change events with their devastations in terms of lives lost and economic cost. This study aims to link the climate change and renewable energy with the social progress of extreme climate affected countries. Design/methodology/approach – This research used the top 50 most climate-affected countries of the decade and estimated the impact of climate risk on social progress with moderation effects of renewable energy and technology. Several competing panel data models such as quantile regression, bootstrap quantile regression and feasible generalized least square are used to generate robust estimates. Findings – The results confirm that climate hazards obstruct socioeconomic progress, but renewable energy and technology can help to mitigate the repercussion. Moreover, improved institutions enhance the social progress of nations. Research limitations/implications – Government should improve the institutional quality that enhances their performance in terms of Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption to increase social progress. In addition, society should use renewable energy instead of fossil fuels to avoid environmental degradation and health hazards. Innovation and technology also play an important role in social progress and living standards, so there should be free hand to private business research and development, encouraging research institutes and universities to come forward for innovation and research. Practical implications – The ultimate goal of all human struggle is to have progress that facilitates human beings to uplift their living standard. One of the best measures that can tell us about a nation’s progress is Social Progress Index (SPI), and one of many factors that can abruptly change it is the climate; so this study is an attempt to link the relationship among these variables and also discuss the situation where the impact of climate can be reduced. Social implications – Although social progress is an important concept of today’s economics discussion, relatively few studies are using the SPI to measure social well-being. Similarly, there is consensus about the impact of climate on people, government and crops but relatively less study about its overall impact on social progress, so this study attempts to fill the gap about the relationship between social progress and climate change. Originality/value – The main contribution of this study is the solution for the impact of climate risk. Climate risk is not in human control, and we cannot eliminate it, but we can reduce the negative impacts of climate change. Moderator impact of renewable energy decreases the negative impact of climate change, so there is a need to use more renewable energy to mitigate the bad consequences of climate on social progress. Another moderator is technology; using technology will also mitigate the negative consequences of the climate, so there is a need to facilitate technological advancement.

Trading companies of used product market are struggling to gain customers attentaion and to sell the products. The aim of this research is to develop a mechanism that can maximize the sale of products while considering profit implications. The literature review classifies the procurement mechanism. Given the limited-supply nature, that also includes unpredictable quality levels and a procurement mechanism that perceives the company offering prices to suppliers on a single-item basis. The academic literature has not covered such a mechanism. Techniques like those that improve the required bidding strategy are reviewed and considered fit to be included in the support tool as the procedures intention to maximize an objective function depending on the bidding price and contain the probability of winning the auction and the profit made from the proceeding, the motivation laid on the approach that predicts the probability. It is determined that this assembles a Response to Reverse Request for Quotation that meets the assumptions of a First-Price Sealed-Bid(FPSD) auction that potentially includes a hidden reservation price.

Previous studies ignore the geospatial dynamics effects between renewable energy (RE) and CO2 while assessing such impacts in European countries. Further, most studies wrongfully use RE in its aggregated format rather than decomposing RE by its components. This is important as not all the RE sources share the same characteristics. We fill these gaps in the literature by investigating the effects of various forms of RE on CO2 emissions in 36 European countries from 2000 to 2018. Spatial econometric models have been used to better understand the results. A series of indicative tests confirmed the use of the Durbin panel model and the inclusion of spatial interaction of CO2 emissions in models. Our results confirm the Environmental Kuznets Curve hypothesis in our sample. We identify a positive and significant effect of economic growth (captured through GDP per capita), foreign direct investment, urbanization, and energy intensity on CO2 emissions. Our findings indicate that increasing well-established RE technologies such as geothermal and hydropower lower CO2 emissions. However, increasing RE sources with more advanced technologies such as solar, wind, and bioenergy either increase or have no impact on CO2 emissions. Increasing RE sources as a whole result in a reduction of CO2 emissions in our sample of countries. Moreover, our spatial models suggest that foreign direct investment lowers local CO2 emissions, while neighboring countries’ energy intensity and trade openness increase local CO2 emissions. Lastly, we find solar and bioenergy generation in adjacent countries increase local CO2 emissions, whilst geothermal generation in adjacent countries lowers local CO2 marginally.

The main objective of this research is to develop a sustainable stock quantitative investing model based on Machine Learning and Economic Value-Added techniques for optimizing investment strategies. Quantitative stock selection and algorithmic trading are the two features of the model. Principal component analysis and economic value-added criteria are used in quantitative stock model for efficiently stocks selection, which may repeatedly select valuable stocks. Machine learning techniques such as Moving Average Convergence, Stochastic Indicators and Long-Short Term Memory are used in algorithmic trading. One of the first attempts, the Economic Value-Added indicators are used to appraise stocks in this study. Furthermore, the application of EVA in stock selection is exposed. Illustration of the proposed model has been done on United States stock market and finding shows that Long-Short Term Memory (LSTM) networks can more accurately forecast future stock values. The proposed strategy is feasible in all market situations, with a return that is significantly larger than the market return. As a result, the proposed approach can not only assist the market in returning to rational investing, but also assist investors in obtaining significant returns that are both realistic and valuable.

Naveed Ahmed,1 Mohmed Isaqali Karobari,2– 4 Anam Yousaf,5 Roshan Noor Mohamed,6 Sohaib Arshad,7 Syed Nahid Basheer,8 Syed Wali Peeran,9 Tahir Yusuf Noorani,4 Ali A Assiry,10 Abdulaziz S Alharbi,11 Chan Yean Yean1 1Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, 16150, Malaysia; 2Department of Restorative Dentistry & Endodontics, Faculty of Dentistry, University of Puthisastra, Phnom Penh, 12211, Cambodia; 3Center for Transdisciplinary Research (CFTR), Saveetha Dental College & Hospitals, Saveetha Institute of Medical and Technical Sciences University, Chennai, Tamil Nadu, 600077, India; 4Conservative Dentistry Unit, School of Dental Sciences, Universiti Sains Malaysia, Health Campus, Kota Bharu, Kelantan, 16150, Malaysia; 5Department of Pathology Laboratory, Pakistan Kidney and Liver Institute & Research Center, Lahore, Pakistan; 6Department of Pediatric Dentistry, Faculty of Dentistry, Taif University, Taif, 21944, Saudi Arabia; 7Periodontics Unit, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian, Kelantan, 16150, Malaysia; 8Division of Operative Dentistry, Department of Restorative Dental Sciences, College of Dentistry, Jazan University, Jazan, Saudi Arabia; 9Department of Periodontics, Armed Forces Hospital Jizan, Jizan, Kingdom of Saudi Arabia; 10Preventive Dental Science Department, Faculty of Dentistry, Najran University, Najran, Kingdom of Saudi Arabia; 11Saudi Board of Pediatric Dentistry (SB-PD), King Fahad Military Medical Complex – KFMMC, Dammam, Saudi ArabiaCorrespondence: Mohmed Isaqali Karobari, Department of Restorative Dentistry & Endodontics, Faculty of Dentistry, University of Puthisastra, Phnom Penh, 12211, Cambodia, Email dr.isaq@gmail.com Chan Yean Yean, Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, 16150, Malaysia, Email yychan@usm.myAbstract: Introduction: Ginger (Zingiber officinale) has been one of the most commonly consumed herbal medicines for a long time to treat several common diseases. Antibacterial activity, antioxidant properties and many bioactive compounds in ginger have been identified previously, which could be used as an alternative method to treat many infectious diseases.Methods: The current study evaluates ginger’s biochemical profile using qualitative and quantitative analysis and its bioactive potentials using antioxidant and antimicrobial assays against Streptococcus mutans and selective oral microbes. HPLC analysis was performed for the quantitative analysis. DPPH and disc diffusion assays were used for antioxidant and antimicrobial activities. The antimicrobial activity was checked against Streptococcus mutans, Enterococcus faecalis, Staphylococcus spp., and Lactobacillus spp. All solvents were removed by rotary evaporation before testing the dried extracts.Results: The observed IC50 value showed that distilled water extract exhibited the highest antioxidant activity (43.9), followed by ethanol extract (52.4), and the lowest activity was observed in n-butanol extract (91.2) and n-hexane (90.6). Different plant extracts have shown significant antibacterial activity (p = 0.001) against each bacterium. The highest antibacterial activity against tested bacteria was observed in n-hexane, chloroform and ethanol extracts. In comparison, the ethyl acetate, n-butanol and water extracts showed low antibacterial activity.Conclusion: This study emphasizes that Zingiber officinale (Z. officinale) against Gram-positive bacteria is an effective antimicrobial herb. Furthermore, it can be used as a potential natural source of antioxidants. Further studies on the toxicity analysis of ginger are recommended.Keywords: Streptococcus mutans, ginger, dental, oral microbes, herbal medicine, medicinal plants, healthy food

This study examines the relationship between globalization, ecological footprint, innovation, and subjective wellbeing in the form of happiness, using a comprehensive assessment of OECD countries from 2008 to 2020. The study employs FGLS, Quantile, and Bootstrap Quantile regression estimation to investigate the quadratic effects of globalization, ecological footprint, and the moderating effect of innovation while controlling for renewable energy and population density. Happiness is a multidisciplinary subject, and this study focuses on the economic dimensions of happiness. The findings reveal a nonlinear relationship between ecological footprint and globalization, with negative effects on subjective wellbeing at high levels of ecological footprint and globalization. However, the moderating effect of innovation mitigates these adverse effects, indicating that innovation can help to offset the detrimental impacts of ecological footprint and globalization on subjective wellbeing. The study's implications are significant for policymakers promoting sustainable economic growth while enhancing subjective wellbeing. The findings highlight the importance of investing in innovation and sustainable development to promote subjective wellbeing in the face of increasing ecological footprint and globalization. Additionally, this research contributes to the multidisciplinary understanding of happiness and provides valuable insights for future research in this area.

The aim of this article is to explore the impact of housing investment on household entrepreneurship. Using survey data from China and employing a Probit model, we examine three aspects of housing status and innovatively subdivide household entrepreneurship into agricultural entrepreneurship and business entrepreneurship. The results show that households with higher housing investment are less likely to become agricultural entrepreneurs, but more likely to start a new business. Households with full-owned housing enjoy a higher likelihood to become business entrepreneurs. However, other ownerships have no relation with the choice of entrepreneurship. More housing loans discourage entrepreneurial activities. One exception is that bank loan raises the chance of being agricultural entrepreneurs. Households who build their own houses have a higher agricultural entrepreneurship. Buying market price houses encourages households to be business entrepreneurs. Low-price house and inherited house prevent households from being business entrepreneurs.

A two-stage planning form of multi-energy supply optimization such as power, cooling, and heating is presented in this paper as a micro energy grid (MEG) To cover the effect of uncertainty in renewable energy sources (RES), the scheduling cycle is considered in this paper. Next, the results of the day-ahead prediction are considered as random variables for the upper-layer model. To realize the random variables at the lower layer, the revised model of energy storage and the demand response (DR) planning model are considered. Finally, the modified version of the artificial bee colony (ABC) algorithm is utilized to find the optimal solution. The improved ABC algorithm is a shape-memory method based on the collective intelligence and behavior of bees in a colony for finding the best nutrition source. In the improved ABC algorithm, with information exchange between the bees, based on Newton’s law of universal gravitation, the full potential of this algorithm is used to find the optimal solution given the constraints applied to the system. The proposed method is applied to a real system and the results show that the two-stage optimization algorithm and the proposed intelligent algorithm obtained the simultaneous optimization of different energy forms. The obtained numerical analysis results in test cases prove the following points: (1) The optimal synergistic supply of multiple energy forms has been provided based on the two-stage optimization algorithm and solution approach. (2) The surplus energy can be converted to natural gas by the power-to-gas converter (P2G) based on power cascade conversion in a multi-directional mode. (3) To get some revenue, the MEG is flexible enough to cooperate with the upper-grade energy network. (4) The DR-based price can smooth the load shape and increase the MEG operation revenue using some supplementary features. Also, P2G can sequentially develop the flexible multidirectional energy conversion in energy - gas - energy - cooling as a cascade. When the evaluated P2G energy rises by 450 kW, the total GST output raises by 1244 kWh. For more economic benefits, MEG can be connected to the upstream energy grid. Load management also increases the net revenue of the system.

The objective of this study is to explore the contributory factors responsible for road accidents and identifies the black spots on the three motorways; M1 (Peshawar-Islamabad), M2 (Islamabad-Lahore), and M3 (Pindi BhattianFaisalabad) in Pakistan. Five years’ road accident data was obtained from the National Highways and Motorway Police (NHMP), Pakistan. The database of this study included six hundred road accidents on a total of 574 kilometers long routes of M1, M2 and M3. The reliability analysis approach was used to locate black spot locations on each motorway. For the visualization and mapping of black spots on each motorway, a Geographic Information System (GIS) was used. The results explored that vehicle condition was the significant contributory factor responsible for the maximum number of road accidents on M1 and M3, while for M2, it was drowsy driving. It is also found that a maximum number of road accidents on M2 and M3 occurred in late-night, while for M1, it was day timing. Furthermore, road accidents were relatively higher in May-July and December on M1 and M2, which shows that extreme weather influences the occurrence of road accidents. On the contrary, no substantial variation of road accidents was examined for M3 month-wise. Finally, black spots on each motorway were located and their georeferenced coordinates were presented for future use. As a result, precautionary measures and provisions are suggested for concerned authorities to mitigate road safety problems.

Aiqin Li,1 Ifrah Nabi Khan,2 Ikram Ullah Khan,2 Abid Mehmood Yousaf,3 Yasser Shahzad3 1Department of Stomatology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, People’s Republic of China; 2Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University Faisalabad, Faisalabad, Pakistan; 3Department of Pharmacy, COMSATS University Islamabad, Lahore, PakistanCorrespondence: Yasser ShahzadDepartment of Pharmacy, COMSATS University Islamabad, Lahore Campus, Lahore, PakistanEmail y.shahzad@live.comIkram Ullah KhanDepartment of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University Faisalabad, Faisalabad, PakistanEmail ikramglt@gmail.comBackground/Objective: Periodontitis is a widely spread oral infection and various antibiotics are utilized for its treatment, but high oral doses and development of antibiotic resistance limit their use. This study was aimed at development of natural polymer-based mucoadhesive bilayer films loaded with moxifloxacin hydrochloride (Mox) and clove essential oil (CEO) to potentially combat bacterial infection associated with periodontitis.Methods: Films were synthesized by double solvent casting technique having an antibiotic in the gellan gum-based primary layer with clove oil in a hydroxyethyl cellulose-based secondary layer.Results: Prepared films were transparent, flexible, and showed high antibacterial response against both gram-positive and gram-negative bacteria. The films showed excellent pharmaceutical attributes in terms of drug content, folding endurance, swelling index, and mucoadhesive strength. Solid state characterization of formulation showed successful incorporation of drug and oil in separate layers of hydrogel structure. An in-vitro release study showed an initial burst release of drug followed by sustained release for up to 48 hours.Conclusion: The prepared mucoadhesive bilayer buccal films could be used as a potential therapeutic option for the management of periodontitis.Keywords: gellan gum, hydroxyethyl cellulose, bilayer films, mucoadhesive, moxifloxacin hydrochloride, clove oil

The COVID-19 pandemic has stimulated a rapid shift towards telemedicine, which has had tremendous repercussions on all domains of the healthcare ecosystem. The effects of the transition to telemedicine on post-graduate medical education and on patient care provided by trainees have not been fully elucidated. Focusing on the multifaceted scope of endocrinology teaching clinics, the experience garnered by endocrinology fellows, preceptors, and patients through the adoption of virtual visits has shed new light on relevant challenges that require specific attention. First, we identified a divergent trend in glycated hemoglobin in people with type 1 diabetes according to their use of continuous glucose monitoring (CGM). Second, the patient’s perspective highlighted positive aspects, including expanded options for clinical care, but also limitations in communication with clinicians for people without access to videoconferencing tools or EHR-based portals. Finally, regarding medical training evaluation and skills-based learning, academic centers, professional organizations, and clinical educators should develop new teaching curricula suitable for a telemedicine-based environment. While simultaneously facing numerous pressures, fellows can potentially spearhead new models of care delivery and innovative approaches to clinical education leveraging telemedicine.

In an electrical power system, the ultimate aim is to generate and deliver electrical energy to consumer side with minimum cost involved. Thus, least fuel cost, effective unit commitment and minimum transmission losses are desirous to achieve economic dispatch in a distributed generation network. In this research, economic dispatch considering transmission losses in a distributed generation network of Bahawalpur is reported. A MATLAB algorithm is designed which gives optimum division of power between two power plants and their transmission losses. Power plants considered here are thermal power plant Muzafargarh and Kot Addu Power Company (KAPCO), the former being located at smaller distance from Bahawalpur district. Finally, load trend of Bahawalpur district, optimum generation verses power demand, associated transmission losses, penalty factor and fuel cost economy are shown in the Results Section through graphs and tables. It is concluded that thermal power plant shares higher contribution of load power due to smaller distance from load and, thus, smaller transmission losses ensuring minimum cost operation.

Purpose – The purpose of this research is to identify major barriers to the implementation of reverse logistics (RL). Also, the study addresses best practices among reuse, remanufacture, recycling, refurbishment and repair as alternatives for RL processes. Design/methodology/approach – This study targets supply chain management experts for their opinions regarding the identification of critical barriers and alternatives for RL implementation. Their opinions were extracted through a Web questionnaire based on 14 criteria with 5 alternatives. The tools of multi-criteria decision-making are used for analysis, i.e. fuzzy VIKOR and fuzzy TOPSIS. Findings – The results indicate that lack of recognition of competitive advantage to be gained through RL practice is the most critical barrier to RL implementation. The least barrier or major facilitator for RL is “supportive initiative for end-of-life products.” The top-ranked alternative in this study is reuse followed by remanufacturing. The least important alternative is “repair” in the case of Pakistan. These alternatives are ranked based on “q values” derived through fuzzy VIKOR. Research limitations/implications – The results of this study can only be generalized for the manufacturing sector of Pakistan during the period of the study. Practical implications – The findings of this study will assist managers in deploying the best practices concerning RL. Originality/value – Fuzzy VIKOR and fuzzy TOPSIS have not been applied to RL alternatives in previous research.

The aim of this research is to examine the potential influence of FDI inflows and tourism industry on carbon dioxide emissions in China using System GMM models for a sample period of 1980–2019. Using FMOLS and DOLS models, this research examines the long-term relationship between the variables, as well as the long-term association among components. Co-joining the boards of FMOLS and DOLS models shows a general correlation between the investigation elements and CO2 emissions in China. FDI, tourism sector, and environment-friendly electricity use have all been major contributors to rising CO2 emissions in China for a long time. Using System GMM, FMOLS, and DOLS models in China, we examined the influence of the travel sector on carbon dioxide emissions as well as environment-friendly electricity usage and foreign direct investment. The government of China is being pushed to attract more foreign direct investment in order to improve the system and expand the transportation industry. As a reasonable responsibility to an unnatural climate change, methods for developing the movement business and theories relating to the movement business should be adopted.

Agricultural production is greatly influenced by environmental parameters such as temperature, rainfall, humidity, and wind speed. The accurate information about environmental parameters plays a vital and useful role when making policies for the agriculture sector as well as for other sectors. Pakistan meteorological department observed these environmental parameters at more than 90 stations. The allocation of these monitoring stations is not made systematically correct. This leads to inaccurate predictions for unobserved locations. The study aims to propose a monitoring network by which these prediction errors of the environmental parameters can be minimized. The well-known prediction techniques named, model-based ordinary kriging and model-based universal kriging (UK) with the known Matheron variogram model are used for prediction purposes. We investigate the monitoring network of Pakistan for rainfall and focus on both the optimal deletion/addition of monitoring stations from/to this network. The two stochastic search algorithms, spatial simulated annealing, and genetic algorithm are used for optimization purposes. Furthermore, the minimization of the Average Kriging Variance (AKV) is taken as the interpolation accuracy measure. The spatial simulated annealing exhibits a lower AKV as compared to the Genetic algorithm when adding/removing the optimal/redundant locations from the monitoring network.

Sustainable supply chain management techniques have been developed over the last several decades to reduce accidental environmental damage during production and buying. Certifying a practical connection between ecosystems and economic development, circular economies push the limits of environmental sustainability. There are two types of rebound effects in the studied business. The impacts of circular business models and strategies are examined and put in a broader framework to get a better understanding of their role in the transition. In order to put transitory changes in a system perspective, this work approach to the problem in new way. Rebound effects and designing an eco-effective transition are discussed as theory-building elements. We conclude by suggesting several future research directions.

The goal of the study is to examine the dynamic linkages between developing economy and environmental pollution. FDI, the tourism industry, electricity use, and GDP growth have all been studied in relation to CO2 emissions over the period from 1980 to 2019. The study applied the ARDL model for statistical data analysis and to ensure the results reliability, the FMOLS and DOLS models have been used in conjunction. The results disclose a significant negative correlation between GDP squared and the observed data. FDI and GDP growth, in contrast, have significant long-term positive effects on CO2 emissions. Due to Pakistan’s lack of infrastructure and transportation facilities, the tourism industry has a long-term negative impact on Pakistan’s CO2 emissions, which are expected to rise over the next several decades. CO2 emissions and GDP growth are linked in a U-shape. The results also showed that GDP growth and electricity use have no significant short-term impacts on CO2 emissions; only FDI coefficients have a negative significance. The Granger causality test found connections between electricity use, FDI, GDP, and CO2 emissions shows a one-way causation.

Abstract Background It has been shown that gout is associated with left atrium remodeling and a pro‐inflammatory state leading to the development of atrial fibrillation (AF). There is limited evidence whether gout increases the risk of stroke in patients with AF. We assessed the incidence of gout and the risk of stroke in patients with AF. Methods This is a retrospective cohort study using the 2016 US National Inpatient Sample (NIS) based on ICD‐10 codes. The outcomes of the study were the risk and severity of new stroke in patients with pre‐existing AF and gout. Results In 2016, we identified 3 844 057 patients admitted to the hospitals in NIS with history of AF, of which 240 875 had history of gout. Patients with AF and gout have higher risk of new stroke (OR 2.07 [1.97‐2.19], P

In this research, data from 36 countries from 2013 to 2018 were used to examine the factors influencing CO2 emissions in Islamic countries, focusing on the impact of Islamic financial growth. The spatial econometric technique estimation findings indicate that there is no geographical association between CO2 emissions in the analyzed countries. The test findings establish the existence of the Kuznets hypothesis for the environment. Additionally, trade openness and increased energy usage have resulted in an increase in CO2 emissions. The impacts of traditional financial development factors, such as financial market and financial institution variables, were examined in this research. The findings indicate that the two variables have no direct and substantial influence on CO2 emissions and that their significant effect on CO2 emissions appears only when their nonlinear and spillover effects on energy consumption and economic growth are included. Additionally, the growth of financial institutions is inversely proportional to the intensity of carbon emissions. The results indicate that while the development of financial markets and institutions results in a significant increase in CO2 emissions, the negative coefficient of the interaction between financial development and energy consumption indicates that financial development ensures energy efficiency, which reduces the intensity of carbon emissions. The findings indicate that the expansion and depth of Islamic finance, as measured by total assets, asset quality, earnings, and efficiency of Islamic banks, can result in a nonlinear increase in CO2 emissions with a U-shaped relationship. The study of spillover effects demonstrates that in addition to their direct and positive effects on CO2 emissions, the increase in Islamic social responsibility and consumer education, and awareness about Islamic banking reduce the enhancing effects of energy consumption on greenhouse gas emissions.

Energy is considered the oxygen of an economy fueling all economic activities. Energy utilization and its type have an intertemporal and size-based effect on economic development. Therefore, this study empirically analyzes the relationship of fossil energy consumption with economic development in the case of BRICS countries between 1990 and 2019. Fully modified ordinary least squares is used with the quadratic function of coal, oil, and gas consumption to assess the size-based effect across time. This study shows that coal and natural gas consumption follows the inverted U-shaped relationship with HDI, while coal consumption shows a negative relationship with HDI. Hence, coal and gas energy assists in development when its share is small, while over-consumption hampers development. The BRICS countries should optimize coal and gas consumption with respect to economic development. Reducing fossil energy should be substituted with alternative clean energy resources by using advanced technology such as the gasification process.

Achieving sustainable development and the necessity to pay attention to the quality of the environment is one of the challenges of the new century. Experimental studies on deforestation determinants have focused mainly on analyzing an environmental Kuznets curve for deforestation (EKCd). The present study introduces three contributions to experimental studies using data from 15 Asia-Pacific countries over a 16-year period, from 2005 to 2020. In this regard, the effects of six financial development indexes and a new pandemic uncertainty index on forest regions have been investigated. Furthermore, the effects of the variables have been estimated through a spatial econometric model. This estimation can be used to investigate the variables of neighboring countries on the inland forest cover of countries. Diagnostic tests confirmed the spatial Durbin model. The results indicate the existence of an environmental Kuznets curve hypothesis. The trade openness variable has decreased the inland forest cover; however, the trade openness in neighboring countries has increased the inland forest cover in the countries. Besides, similar results were obtained for urbanization. Furthermore, natural resource rent is a beneficial factor dominating the improvement of forest areas. As confirmed by the results, the financial institution depth has a significant adverse effect on the forest cover of countries. The results for other reductions in financial development are meaningless. Despite the theoretically positive and negative dimensions of pandemics, the estimation results highlight its positive effects in forest regions.

Oil supply chains play a vital role in the day-to-day functioning of national economies and obstruction in its services can lead to dire consequences. For this purpose, it is imperative for oil supply chains to be on guard against all probable vulnerabilities and develop adequate protection mechanisms. This research study aims to identify the most important vulnerabilities for oil supply chains in the context of Pakistan, a developing country. Subsequently, these identified vulnerabilities were used to design a protection framework, embodying different supply chain capabilities. For this purpose, this study employs a hybrid Multi-Criteria Decision Making approach. Full Consistency Method (FUCOM) has been used to prioritise vulnerabilities and Fuzzy Quality Function Deployment (QFD) has been used to identify those capabilities that can ensure protection against these vulnerabilities. Results indicate that crude oil price instability, fuel price shocks, unpredictable demand, and information and communication disruptions are the most important and catastrophic vulnerabilities in the context of Pakistan’s oil industry. For mitigation of these vulnerabilities, oil supply chains need to incorporate real-time information sharing, visibility, e-procurement, traceability, and transparency as resilience measures. These recommendations are of considerable importance to Pakistan’s oil industry and policy-making authorities. Moreover, this study fulfils the research gap by focusing on enhancing the resilience of Pakistan’s oil supply chains, with the aid of MCDM techniques.

Lin Zhao, 1 Omer Mustapha, 2 Shumaila Shafique, 2 Talha Jamshaid, 3 Fakhar ud Din, 4 Yasir Mehmood, 5 Khaleeq Anwer, 6 Qurrat ul Ain Yousafi, 7 Talib Hussain, 8 Ikram Ullah Khan, 5 Muhammad Usman Ghori, 9 Yasser Shahzad, 8 Abid Mehmood Yousaf 8 1Department of Rheumatology of Traditional Chinese and Western Medicine, Xinxiang Central Hospital, Xinxiang 453000, People’s Republic of China; 2Faculty of Pharmaceutical Sciences, Dow College of Pharmacy, Dow University of Health Sciences, Karachi 74200, Pakistan; 3Faculty of Pharmacy and Alternative Medicine, Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan; 4Department of Pharmacy, Quaid-i-Azam University, Islamabad 45320, Pakistan; 5Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University Faisalabad, Faisalabad 38040, Pakistan; 6Office of Chief Executive Officer, District Health Authority, Pakpattan 57400, Pakistan; 7Department of Neurosurgery, District Headquarters Hospital, Rawalpindi 46000, Pakistan; 8Department of Pharmacy, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan; 9Department of Pharmacy, School of Applied Science, University of Huddersfield, Huddersfield HD1 3DH, UKCorrespondence: Abid Mehmood Yousaf Tel +92-300-477-4147; +92-345-722-0536Email abid.ucp@hotmail.com Email talib.hussain@cuilahore.edu.pkBackground: Piroxicam exhibits low oral bioavailability, due to its meager solubility in water. The intent of this study was to ameliorate the bioavailability of the drug by employing a solubility-enhancing encapsulation technique.Methods: Seven samples were formulated with piroxicam and gelatin using both solvent evaporation and electrospraying together. Evaluation of solubility and release rate in water and assessment of bioavailability in rats were carried out in comparison with piroxicam plain drug powder (PPDP). Other in vitro explorations were accomplished using powder X-ray diffraction analysis, differential scanning calorimetry, thermogravimetric analysis, scanning electron microscopy, and Fourier-transform infrared spectroscopy.Results: All piroxicam-loaded gelatinnanocontainers (PLGNs) enhanced solubility and release of the payload in water. In particular, a PLGN formulation consisting of piroxicam and gelatin at a 1:8 (w:w) ratio presented about 600-fold the drug solubility of that shown by PPDP. Moreover, 85.12%± 10.96% of the payload was released from this formulation in 10 minutes which was significantly higher than that dissolved from PPDP in 10 minutes (11.81%± 5.34%). Drug content, drug loading, and encapsulation efficiency of this formulation were 93.41%± 0.56%, 10.45%± 0.06%, and 66.74%± 6.87%, respectively. The drug loaded in PLGNs existed in the amorphous state, as confirmed by X-ray diffraction and differential scanning–calorimetry analyses, and was more stable when analyzed by thermogravimetric analysis. Moreover, Fourier-transform infrared spectroscopy analysis suggested nonexistence of any piroxicam–gelatin interaction in the formulation. In the scanning electron–microscopy image, PLGNs appeared as round, smooth particles, with particle size of < 1,000 nm. Amelioration in bioavailability of piroxicam with the aforementioned PLGN formulation was fourfold that of PPDP.Conclusion: The PLGN formulation fabricated with piroxicam and gelatin at 1:8 (w:w) might be a promising system for enhanced biopharmaceutical performance of the drug.Keywords: aqueous solubility, electrospraying, gelatin encapsulation, nanocontainers, oral bioavailability, piroxicam

China Pakistan Economic Corridor (CPEC) is a flagship project of China's Belt and Road (BRI) Initiative. Under the banner of CPEC, enormous developmental and infrastructure up-gradation projects are planned to be executed. These projects vary in their range and diversity from the development of a network of highways to up-gradation of electrical energy powerplants. Thus, the construction of these projects requires an operational and dedicated supply chain. This research study focuses on the identification of different internet of things (IoT) strategies that can be incorporated for increasing the efficiency of these supply chains. Fuzzy VIKOR, a multi-criteria decision-making technique (MCDM), has been employed for the prioritization of these strategies. These strategies are ranked on the basis of their cost-effectiveness, benefit to operational firms and partners, and social and environmental value. A total of twelve strategies are evaluated on the basis of the aforementioned criteria. The results of fuzzy VIKOR analysis prioritised the incorporation of IoT in equipment monitoring, reduction of environmental emissions, identification of security threats, augmented reality and inventory management as the most essential and effective strategies. Therefore, this study recommends the adoption of these strategies in CPEC projects on a priority basis.

Ru Sun, 1 Chengwu Shen, 1 Shumaila Shafique, 2 Omer Mustapha, 2 Talib Hussain, 3 Ikram Ullah Khan, 4 Yasir Mehmood, 4 Khaleeq Anwer, 5 Yasser Shahzad, 3 Abid Mehmood Yousaf 3 1Department of Pharmacy, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250000, People’s Republic of China; 2Faculty of Pharmaceutical Sciences, Dow College of Pharmacy, Dow University of Health Sciences, Karachi 74200, Pakistan; 3Department of Pharmacy, COMSATS University Islamabad, Lahore 54000, Pakistan; 4Department of Pharmaceutics, Faculty of Pharmaceutical Sciences, Government College University Faisalabad, Faisalabad 38000, Pakistan; 5Office of Chief Executive Officer, District Health Authority, Pakpattan 57400, PakistanCorrespondence: Abid Mehmood Yousaf; Talib HussainDepartment of Pharmacy, COMSATS University Islamabad, Lahore Campus, Lahore 54000, PakistanTel +92-300-4774147; +92-345-7220536Email abid.ucp@hotmail.com; talib.hussain@cuilahore.edu.pkBackground: Bezafibrate is a BCS class II drug as it presents very low solubility in water; therefore, its bioavailability after oral administration is very poor. The aim of this work was to enhance solubility and dissolution rate of bezafibrate in water in order to enhance its oral bioavailability.Methods: Several formulations were prepared using PVP K30 and Cremophor ELP employing the solvent-evaporation method and the electrospraying technique. Solubility, release rate, bioavailability in male Sprague Dawley rats, and lipid profile attributes in Wistar rats were assessed in comparison with bezafibrate plain powder. Solid-state characterization was carried out using X-ray diffraction (XRD) analysis, differential scanning calorimetry (DSC), Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM).Results: All the formulations exerted positive effect towards the desired goal. In particular, the optimized formulation furnished about 14-fold enhanced solubility and 85.48 ± 10.16% drug was released in 10 min as compared with bezafibrate alone (4.06 ± 2.59%). The drug existed in the amorphous state in the prepared sample as confirmed by XRD and DSC, whilst no drug-excipient interactions were observed through FTIR analysis. Moreover, SEM revealed smooth-surfaced spherical particles of the optimized formulation. A 5.5-fold higher oral bioavailability was achieved with the optimized formulation in comparison with bezafibrate plain powder. Also, TG, LDL and TC were decreased, and HDL was increased considerably in HFD-treated rats.Conclusion: The optimized formulation consisting of bezafibrate, PVP K30 and cremophor ELP (1/12/1.5, w/w/w) might be a capable drug delivery system for orally administering poorly water-soluble bezafibrate with improved bioavailability and antihyperlipidemic effects.Keywords: aqueous solubility, bezafibrate, electrospraying, lipid profile, oral bioavailability, solid dispersion

This study investigates the consequences of financial development on environmental quality in Malaysia by using monetary access, profundity, and effectiveness as support components from 1990 to 2019. The level of affiliation between the components explored by using appropriate autoregressive lag technique. The variables appeared to have a long-term relationship during the investigation. Monetary events, population expansion, financial development, and energy consumption contribute to environmental degradation in the short and long-run. In contrast, squared fiscal growth boosts green value in the short and long term. As a result, Malaysia hosts the Ecological Carbon Kuznets Bend (ECKC) with a negative and measurable blunder revision phrase that supports the existence of a level connection between these variables. That is, any prior year’s 21.8% imbalance is rectified within a year. Monetary events, financial development, squared monetary development, energy use, and population all impact carbon dioxide flows.

The aim of this research is to investigate the impact of major risks such as geopolitical and pandemic risks on tourism industry in selected countries of Asia-Pacific. The results were obtained using a sample of 10 neighboring countries in the period of 1996 to 2018. Diagnostic tests confirmed the existence of spatial interaction between model variables for these countries. According to the results, the economic growth, internally and in neighboring countries, leads to an increase in the influx of tourists. Whereas increased domestic prices will reduce the influx of domestic tourists, rising prices in neighboring countries intensify tourists’ arrival of the country. Furthermore, results reveal that domestic geopolitical and pandemic risks lead to a decrease in tourist arrivals. In addition, whereas pandemic risks in neighboring countries do not have a significant effect on tourist arrivals, geopolitical risks in neighboring countries lead to more domestic tourists’ arrival.

Entropy is an alternative measure to calculate the risk, simplify the portfolios and equity risk premium. It has higher explanatory power than capital asset price model (CAPM) beta. The comparison of Entropy and CAPM beta provide in depth analysis about the explanatory power of the model that in turn help investor to make right investment decisions that minimizes risk. In this context, this study aims to compare Shannon and Rennyi Entropies with the CAPM beta for measuring the risk. Ordinary Least square approach has been utilized using a dataset of 67 enterprises registered in Pakistan Stock exchange. The comparative analysis of CAPM beta and entropy has been carried out with the R2 parameters. The result indicates that entropy has more explanatory power as compare to CAPM beta's explanatory power, and this turns out to be the best option to evaluate the risk performances. The result implies that an investor should make the best investment decision by choosing an enterprise that provide with good returns at minimum risk based on entropy technique.