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  1. Zawawi NNM, Azmi WH, Ghazali MF, Ali HM
    Micromachines (Basel), 2022 Oct 30;13(11).
    PMID: 36363892 DOI: 10.3390/mi13111871
    To reduce fuel consumption, the automotive air-conditioning (AAC) system's coefficient of performance (COP) needs to be improved. The use of a diverse selection of hybrid nanolubricant composition ratios is expected to improve the properties of single nanolubricants, resulting in improved AAC system performance. The goal of this study was to find the best combination of hybrid nanolubricants for the best performance of the AAC system. Al2O3-SiO2/PAG hybrid nanolubricants at 0.06% volume concentrations with various composition ratios (20:80, 40:60, 50:50, 60:40, and 80:20) were investigated. An initial refrigerant charge of up to 155 g and a compressor speed of up to 2100 rpm were used in the experiment. The cooling capacity, compressor work, and COP of the AAC system were measured to determine its efficiency. The COP enhancement and compressor work reduction were recorded up to 16.31% and 18.65% for the 60:40 composition ratio, respectively. The maximum cooling capacity up to 75.84% was recorded for the 80:20 ratio, followed by 60:40. The maximum COP value of 8.81 for 155 g of hybrid nanolubricants was obtained at 900 rpm with a 60:40 composition ratio. Therefore, for optimal performance in the AAC system, a 60:40 composition ratio of the Al2O3-SiO2/PAG nanolubricant combination is strongly recommended.
  2. Hamidi RM, Siyal AA, Luukkonen T, Shamsuddin RM, Moniruzzaman M
    RSC Adv, 2022 Nov 15;12(51):33187-33199.
    PMID: 36425209 DOI: 10.1039/d2ra06056f
    Nitrogen loss from urea fertiliser due to its high solubility characteristics has led to the invention of controlled release urea (CRU). Majority of existing CRU coatings are produced from a non-biodegradable, toxic and expensive synthetic polymers. This study determines the feasibility of fly ash-based geopolymer as a coating material for urea fertilizer. The effects of fly ash particle size (15.2 μm, 12.0 μm, and 8.6 μm) and solid to liquid (S : L) ratio (3 : 1, 2.8 : 1, 2.6 : 1, 2.4 : 1 and 2.2 : 1) on the geopolymer coating, the characterization such as FTIR analysis, XRD analysis, surface area and pore size analysis, setting time analysis, coating thickness, and crushing strength, and the release kinetics of geopolymer coated urea in water and soil were determined. Lower S : L ratio was beneficial in terms of workability, but it had an adverse impact on geopolymer properties where it increased porosity and decreased mechanical strength to an undesirable level for the CRU application. Geopolymer coated urea prepared from the finest fly ash fraction and lowest S : L ratio demonstrated high mechanical strength and slower urea release profile. Complete urea release was obtained in 132 minutes in water and 15 days in soil from geopolymer-coated urea whereas for uncoated urea it took only 20 minutes in water and 3 days in soil. Thus, geopolymer can potentially be used as a coating material for urea fertilizer to replace commonly used expensive and biodegradable polymer-based coatings.
  3. Behjati M, Nordin R, Zulkifley MA, Abdullah NF
    Sensors (Basel), 2022 Nov 19;22(22).
    PMID: 36433554 DOI: 10.3390/s22228957
    This paper proposes an effective global path planning technique for cellular-connected UAVs to enhance the reliability of unmanned aerial vehicles' (UAVs) flights operating beyond the visual line of sight (BVLOS). Cellular networks are considered one of the leading enabler technologies to provide a ubiquitous and reliable communication link for UAVs. First, this paper investigates a reliable aerial zone based on an extensive aerial drive test in a 4G network within a suburban environment. Then, the path planning problem for the cellular-connected UAVs is formulated under communication link reliability and power consumption constraints. To provide a realistic optimization solution, all constraints of the optimization problem are defined based on real-world scenarios; in addition, the presence of static obstacles and no-fly zones is considered in the path planning problem. Two powerful intelligent optimization algorithms, the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, are used to solve the defined optimization problem. Moreover, a combination of both algorithms, referred to as PSO-GA, is used to overcome the inherent shortcomings of the algorithms. The performances of the algorithms are compared under different scenarios in simulation environments. According to the statistical analysis of the aerial drive test, existing 4G base stations are able to provide reliable aerial coverage up to a radius of 500 m and a height of 85 m. The statistical analysis of the optimization results shows that PSO-GA is a more stable and effective algorithm to rapidly converge to a feasible solution for UAV path planning problems, with a far faster execution time compared with PSO and GA, about two times. To validate the performance of the proposed solution, the simulation results are compared with the real-world aerial drive test results. The results comparison proves the effectiveness of the proposed path planning method in suburban environments with 4G coverage. The proposed method can be extended by identifying the aerial link reliability of 5G networks to solve the UAV global path planning problem in the current 5G deployment.
  4. Nuhma MJ, Alias H, Tahir M, Jazie AA
    Molecules, 2022 Nov 18;27(22).
    PMID: 36432121 DOI: 10.3390/molecules27228018
    Due to their high lipid content, microalgae are one of the most significant sources of green hydrocarbons, which might help lessen the world's need for fossil fuels. Many zeolite-based catalysts are quickly deactivated by coke production and have a short lifetime. In this study, a bimetallic Lanthanum-Cerium (La-Ce)-modified HZSM-5 zeolite catalyst was synthesized through an impregnation method and was tested for the conversion of hydrolyzed oil into oxygen-free hydrocarbon fuels of high energy content. Initially, hydrolyzed oil (HO), the byproduct of the transesterification process, was obtained by the reaction of crude oil derived from Chlorella vulgaris microalgae and a methanol. Various catalysts were produced, screened, and evaluated for their ability to convert algal HO into hydrocarbons and other valuable compounds in a batch reactor. The performance of HZSM-5 was systematically tested in view of La-Ce loaded on conversion, yield, and selectivity. NH3-TPD analysis showed that the total acidity of the La-Ce-modified zeolites was lower than that of the pure HZSM-5 catalyst. TGA testing revealed that including the rare earth elements La and Ce in the HZSM-5 catalyst lowered the catalyst propensity for producing coke deposits. The acid sites necessary for algal HO conversion were improved by putting La and Ce into HZSM-5 zeolite at various loading percentages. The maximum hydrocarbon yield (42.963%), the highest HHV (34.362 MJ/Kg), and the highest DOD% (62.191%) were all achieved by the (7.5%La-2.5%Ce)/HZSM-5 catalyst, which was synthesized in this work. For comparison, the hydrocarbon yield for the parent HZSM-5 was 21.838%, the HHV was (33.230 MJ/Kg), and the DOD% was 44.235%. In conclusion, La and Ce-loading on the parent HZSM-5 may be responsible for the observed alterations in textural properties; nevertheless, there is no clear correlation between the physical features and the hydrocarbon yield (%). The principal effect of La and Ce modifying the parent HZSM-5 zeolite was to modify the acidic sites needed to enhance the conversion (%) of the algal HO during the catalytic deoxygenation process, which in turn raised the hydrocarbon yield (%) and increased the HHV and DOD%.
  5. Alauddin MS, Yusof NM, Adnan AS, Said Z
    Eur J Dent, 2022 Oct;16(4):901-910.
    PMID: 35189641 DOI: 10.1055/s-0041-1742121
    OBJECTIVE:  Concentrated growth factor (CGF) is particularly gaining acceptance and popularity in regenerative dentistry. Nonetheless, there are no available studies showing its effect against microorganisms of oral cavity particularly in chronic oral disease-induced biofilms. This in vitro research was conducted to determine the antimicrobial effects of CGF against Staphylococcus aureus sp. (S. aureus) and Streptococcus mutans sp. (S. mutans).

    MATERIALS AND METHODS:  Blood samples were obtained from a healthy volunteer. CGF was then prepared using specialized centrifugation equipment (Medifuge, Silfradent, Santa Sofia FC, Italy) and protocol. Antimicrobial activity of the CGF was observed and recorded on standard strains of S. aureus and S. mutans using a well diffusion method to determine the inhibition zone, broth microdilution to determine minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC), and crystal violet assay for biofilm assessment, with chlorhexidine (CHX) 0.12% used as a positive control. Statistical analysis was then performed using one-way analysis of variance followed by Tukey Test post hoc analysis.

    RESULTS:  It was observed that there was a presence of clear zones of inhibition around the CGF after 24 hours of incubation. The mean diameter of the inhibition zone was 1.26 ± 0.12 nm and 1.20 ± 0.06 nm for S. aureus and S. mutans, respectively, with significance difference (p 

  6. Khairul-Anuar MA, Mazumdar P, Othman RY, Harikrishna JA
    Ann Bot, 2022 Sep 26;130(4):579-594.
    PMID: 35980362 DOI: 10.1093/aob/mcac103
    BACKGROUND: Flower pigment and shape are determined by the coordinated expression of a set of structural genes during flower development. R2R3-MYB transcription factors are known regulators of structural gene expression. The current study focused on two members of this large family of transcription factors that were predicted to have roles in pigment biosynthesis and organ shape development in orchids.

    METHODS: Phylogenetic analysis was used to identify candidate Dendrobium catenatum R2R3-MYB (DcaMYB) sequences associated with pigment and cell shape development. Gene silencing of candidate DhMYBs in Dendrobium hybrid by direct application of dsRNA to developing flowers was followed by observation of gene expression level and flower phenotypes. Silencing of the structural gene chalcone synthase was used as a comparative control.

    KEY RESULTS: Ten candidate flower-associated DcaMYBs were identified. Flowers treated with dsRNA of DhMYB22 and DhMYB60 sequences were less pigmented and had relatively low expression of anthocyanin biosynthetic genes (F3'H and DFR), lower total anthocyanin concentration and markedly lower levels of cyanidin-3-glucoside and cyanidin-3-rutinoside. Petals of DhMYB22-treated flowers and sepals of DhMYB60-treated flowers showed the greatest colour difference relative to the same organs in untreated flowers. DhMYB22-treated flowers had relatively narrow and constricted lips, while DhMYB60-treated flowers had narrow and constricted sepals. No significant difference in shape was observed for DhCHS-treated or untreated flowers.

    CONCLUSIONS: Our results demonstrate that DhMYB22 and DhMYB60 regulate pigment intensity and floral organ shape in Dendrobium. This is a first report of MYB regulation of floral organ shape in orchids.

  7. Naeem MA, Karim S, Farid S, Tiwari AK
    Econ Anal Policy, 2022 Sep;75:548-562.
    PMID: 35789957 DOI: 10.1016/j.eap.2022.06.015
    In the backdrop of the recent COVID-19 pandemic, the study examines the comparative asymmetric efficiency of dirty and clean energy markets pre and during the COVID-19 pandemic. For this purpose, we utilize an asymmetric multifractality detrended fluctuation analysis (A-MF-DFA). The study's findings uncover the presence of asymmetric multifractality in clean and dirty energy markets. In addition, multifractality in the energy markets is sensitive to trends, time horizon and major events. More importantly, the results suggest superior efficiency of clean-energy markets compared to conventional energies. We confirm the time-varying nature of market efficiency in the energy markets, and during the recent COVID-19 outbreak, market inefficiencies in the clean and dirty energy markets soared. In this way, the study holds meaningful insights for policymakers, energy policy practitioners, investors, and financial market participants to choose between clean (dirty) investments based on their asymmetric efficiency (inefficiency).
  8. Sohail MT, Yang M, Maresova P, Mustafa S
    Front Public Health, 2022;10:1046780.
    PMID: 36339186 DOI: 10.3389/fpubh.2022.1046780
    This study was conducted to evaluate public awareness about COVID with aimed to check public strategies against COVID-19. A semi structured questionnaire was collected and the data was analyzed using some statistical tools (PLS-SEM) and artificial neural networks (ANN). We started by looking at the known causal linkages between the different variables to see if they matched up with the hypotheses that had been proposed. Next, for this reason, we ran a 5,000-sample bootstrapping test to assess how strongly our findings corroborated the null hypothesis. PLS-SEM direct path analysis revealed HRP -> PA-COVID, HI -> PA-COVID, MU -> PA-COVID, PM -> PA-COVID, SD -> PA-COVID. These findings provide credence to the acceptance of hypotheses H1, H3, and H5, but reject hypothesis H2. We have also examined control factors such as respondents' age, gender, and level of education. Age was found to have a positive correlation with PA-COVID, while mean gender and education level were found to not correlate at all with PA-COVID. However, age can be a useful control variable, as a more seasoned individual is likely to have a better understanding of COVID and its effects on independent variables. Study results revealed a small moderation effect in the relationships between understudy independent and dependent variables. Education significantly moderates the relationship of PA-COVID associated with MU, PH, SD, RP, PM, PA-COVID, depicts the moderation role of education on the relationship between MU*Education->PA-COVID, HI*Education->PA.COVID, SD*Education->PA.COVID, HRP*Education->PA.COVID, PM*Education -> PA.COVID. The artificial neural network (ANN) model we've developed for spreading information about COVID-19 (PA-COVID) follows in the footsteps of previous studies. The root means the square of the errors (RMSE). Validity measures how well a model can predict a certain result. With RMSE values of 0.424 for training and 0.394 for testing, we observed that our ANN model for public awareness of COVID-19 (PA-COVID) had a strong predictive ability. Based on the sensitivity analysis results, we determined that PA. COVID had the highest relative normalized relevance for our sample (100%). These factors were then followed by MU (54.6%), HI (11.1%), SD (100.0%), HRP (28.5%), and PM (64.6%) were likewise shown to be the least important factors for consumers in developing countries struggling with diseases caused by contaminated water. In addition, a specific approach was used to construct a goodness-of-fit coefficient to evaluate the performance of the ANN models. The study will aid in the implementation of effective monitoring and public policies to promote the health of local people.
  9. Ting YW, Jalaludin MY, Zaini AA, Mohamed R
    Front Endocrinol (Lausanne), 2022;13:1071350.
    PMID: 36589844 DOI: 10.3389/fendo.2022.1071350
    BACKGROUND: Insulin resistance (IR), one of the key components of the metabolic syndrome, is recognized as the pathophysiological hallmark of non-alcoholic fatty liver disease (NAFLD). This study aims to investigate the relationship between surrogate markers of IR and the severity of NAFLD among overweight or obese children.

    METHODOLOGY: A total of 56 consecutive children aged 6 to 18 years old were recruited from the pediatric obesity and type 2 diabetes mellitus (T2DM) clinic in University Malaya Medical Centre (UMMC) from 2016 to 2019. Data on anthropometric measurements, clinical components of metabolic syndrome and fasting serum insulin were collected. Triglyceride to high-density lipoprotein cholesterol ratio (TG: HDL-C), Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and Single Point Insulin Sensitivity Estimator (SPISE) were calculated. Transient elastography was performed with hepatic steatosis and liver fibrosis assessed by controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), respectively.

    RESULTS: A total of 44 children (78.6%) had liver steatosis and 35.7% had presence of significant liver fibrosis (stage F≥2). Majority (89.3%) are obese and 24 children (42.9%) were diagnosed with metabolic syndrome. Higher number of children with T2DM and significant liver fibrosis were associated with higher tertiles of TG: HDL-C ratio (p<0.05). Top tertile of TG: HDL-C ratio was an independent predictor of liver fibrosis (OR=8.14, 95%CI: 1.24-53.36, p=0.029). ROC analysis showed that the area under the curve (AUC) of HOMA-IR (0.77) and TG: HDL-C ratio (0.71) were greater than that of metabolic syndrome (0.70), T2DM (0.62) and SPISE (0.22). The optimal cut-off values of HOMA-IR and TG: HDL-C ratio for detecting liver fibrosis among children with NAFLD are 5.20 and 1.58, respectively.

    CONCLUSION: Children with NAFLD and higher TG: HDL-C ratio are more likely to have liver fibrosis. TG: HDL-C ratio is a promising tool to risk stratify those with NAFLD who are at risk of developing advanced liver disease.

  10. Ibrahim NS, Noor NNM, Nasruddin NNABM
    J Adv Vet Anim Res, 2022 Sep;9(3):527-535.
    PMID: 36382029 DOI: 10.5455/javar.2022.i622
    Objective: There are three objectives in this study; 1) to measure the live weight of pre-and post-weaning Saanen kids; 2) to determine the growth curves between males and females pre-and post-weaning Saanen kids; and 3) to analyze the body condition score (BCS) between male and female pre-and post-weaning kids.

    Materials and Methods: This study included pre-weaning kids aged 1 month, as well as post-weaning kids aged 3-6 months. 10 pre-weaning purebred Saanen kids (n = 5 male and n = 5 female) and 20 post-weaning Saanen kids (n = 10 male and n = 10 female) were employed in this investigation. Pre-and post-weaning kids' live weights were assessed weekly on a weighing scale, and BCS was calculated based on their body frame. In the data analysis, the two-sample t-test with Minitab Software was utilized.

    Results: The findings revealed that pre-weaning Saanen kids gained weight steadily from week 1 to week 6, with males being heavier than females. The p-value, on the other hand, suggested that there was no difference in live weight between pre-weaning male and female Saanen kids. Over 6 weeks of sampling, the male had a larger proportion of live weight gain (80%) than the female (75%). Meanwhile, the BCS of pre-weaning Saanen kids grew from week 1 to week 6. It is critical to account for the development of muscle mass while still evaluating the fat cover to determine whether the kids are maintaining an adequate BCS. However, the live weight of post-weaning kids was inconsequential because they were still in the growing phase. As a result, from the 1st to 6th week, post-weaning kids' body weight and BCS increased as their growth progressed. After 6 weeks of sampling, females had a higher percentage of live weight than males. This is because the kids raised on the farm do not have complete control over the environmental effects. Over 6 weeks of sampling, female post-weaning Saanen kids grew a slightly higher percentage of live weight (88%) than males (85%).

    Conclusion: This study conducted a direct assessment study, which monitored and determined the live weight and BCS of pre-and post-weaning Saanen kids. Pre-weaning kids' average values of live weight were calculated as insignificant at the age of 1 month. The mean live weight is most affected by milk consumption from its mothers, the management of the farm, and the environment. For the post-weaning Saanen kids, the females have a slightly higher average live weight gained for 6 weeks than the males (p > 0.05). In conclusion, the live weight changes of Saanen kids during the weaning stages are independent of the BCS.

  11. Nuhma MJ, Alias H, Tahir M, Jazie AA
    Molecules, 2022 Oct 25;27(21).
    PMID: 36364078 DOI: 10.3390/molecules27217251
    Despite the extensive research into the catalytic uses of zeolite-based catalysts, these catalysts have a limited useful lifetime because of the deactivating effect of coke production. This study looks at the use of Cerium (Ce) loaded HZSM-5 zeolite catalysts in the hydrocarbon and oxygenated chemical conversion from Chlorella Vulgaris microalgae crude oil. Characterization of structure, morphology, and crystallinity was performed after the catalysts were manufactured using the impregnation technique. Soxhlet extraction was carried out to extract the crude oil of microalgae. Transesterification reaction was used to produce algal hydrolyzed oil (HO), and the resulting HO was put to use in a batch reactor at 300 °C, 1000 rpm, 7 bars of nitrogen pressure, a catalyst to the algal HO ratio of 15% (wt. %), and a retention time of 6 h. To determine which Ce-loaded HZSM-5 catalysts would be most effective in converting algal HO into non-oxygenated molecules (hydrocarbons), we conducted a series of tests. Liquid product characteristics were analyzed for elemental composition, higher heating value (HHV), atomic ratios of O/C and H/C, and degree of deoxygenation (DOD%). Results were categorized into three groups: product yield, chemical composition, and carbon number distribution. When Cerium was added to HZSM-5 zeolite at varying loading percentages, the zeolite's acid sites became more effective in facilitating the algal HO conversion. The results showed that 10%Ce/HZSM-5 had the greatest conversion of the algal HO, the yield of hydrocarbons, HHV, and DOD% (98.2%, 30%, 34.05 MJ/Kg, and 51.44%, respectively) among all the synthesized catalysts in this research. In conclusion, the physical changes seen in the textural characteristics may be attributed to Cerium-loading on the parent HZSM-5; nevertheless, there is no direct association between the physical features and the hydrocarbons yield (%). The primary impact of Cerium alteration of the parent HZSM-5 zeolite was to change the acidic sites required to boost the conversion (%) of the algal HO in the catalytic deoxygenation process, which in turn increased the hydrocarbons yield (%), which in turn increased the HHV and DOD%.
  12. Roslan MA, Ngui R, Vythilingam I, Wan Sulaiman WY
    J Vector Ecol, 2022 Dec;47(2):142-152.
    PMID: 36314668 DOI: 10.52707/1081-1710-47.2.142
    The study assessed the distribution of Malaysian Ae. albopictus adults associated with Wolbachia detection in low-rise residential areas using a modified sticky ovitrap (MSO). The relationship between Ae. albopictus and climatological parameters were also determined. Fifty-two weeks of surveillance using 273 MSOs were conducted in four installation areas of eleven sampling sites. Specimens were subjected to PCR using wsp-specific primers for Wolbachia detection. The relationship between climatological parameters and Ae. albopictus captured were analyzed using Spearman rank correlation coefficient test. The majority of Ae. albopictus were captured in residential houses (87%), followed by playgrounds or parks (11.5%), guardhouses (1%), and community halls (0.5%). Most of the specimens (92%) were superinfected with wAlbA and wAlbB strains. A positive correlation with no significant association was found for rainfall (r = 0.015, P = 0.072), relative humidity (r = 0.005, P = 0.526), minimum temperature (r = 0.005, P = 0.516), and mean temperature (r = 0.003, P = 0.689). MSO effectively captured a high number of Ae. albopictus that was determined to be the predominant mosquito species found in low-rise residential areas. The adult collection is not only influenced by climatological parameters but also by other factors, including environmental conditions and general sanitation status.
  13. Jan N, Li Z, Xiyu L, Farhan Basheer M, Tongkachok K
    Front Psychol, 2022;13:796287.
    PMID: 36507039 DOI: 10.3389/fpsyg.2022.796287
    The objective of this study is to investigate the impact of the COVID-19 pandemic and stock market psychology on investor investment decisions in different business units operating in the Shandong stock market. The sample size of the study consists of 5,000 individuals from six different business units. The study used the event study statistical technique to analyze the market reaction to newly released information from the stock market perspective to assess whether the number of COVID-19 positive cases impacted it. With a Z score value of 40.345 and a P-value of 0.000, the Wilcoxon test indicated that stock prices before and after the pandemic were quite different. The test showed a positive relationship between the pandemic and the stock market. Further, the results indicated that COVID-19 and stock market psychology had a significant positive impact on investor investment decisions in cosmetic and beauty, consumer household, textiles and apparel, and consumer electronics industries; however, in the sporting and consumer appliance industries, it had an insignificant negative impact. This study serves to guide investors to make suitable changes in their stock market trading practices to counter these challenges to increase their required rate of return from their specific stock market investment. The findings have important insights for various stakeholders including governments, regulatory bodies, practitioners, academia, industry, and researchers.
  14. Krishna Sahith Sayani J, English NJ, Khan MS, Ali A
    Chemosphere, 2023 Feb;313:137550.
    PMID: 36521742 DOI: 10.1016/j.chemosphere.2022.137550
    Gas Hydrate modelling has gained huge attention in the past decade due to its increase in usage for various energy as well as environmental applications at an industrial scale. As the experimental approach is highly expensive and time-consuming, modelling is the best way to predict the conditions before the actual applications at industrial scales. The commercial software currently existing uses the equation of states (EOS) to predict the thermodynamic conditions of gas hydrates. But, in certain cases, the prediction by using EOS fails to predict the hydrate conditions accurately. Therefore, there arose a need for an accurate prediction model to estimate the hydrate formation conditions. So, in this work, an accurate prediction model has been proposed to predict the thermodynamic equilibrium conditions of the gas hydrate formation. The performance of prediction accuracy for the proposed model is compared with those of the SRK equation of state and Peng Robinson (PR) Equation of state. It was observed that in most of the cases the proposed model has predicted the thermodynamic conditions more accurately than the PR and SRK equation of state. This work helps in understanding the limitations of EOS for the prediction hydrate conditions. Also, the current work helps in strengthening the conventional statistical modelling technique to predict the hydrate conditions for a broader range.
  15. Sarwar A, Islam MA, Mohiuddin M, Tareq MA, Siddika A
    Int J Environ Res Public Health, 2022 Nov 27;19(23).
    PMID: 36497866 DOI: 10.3390/ijerph192315791
    The rising prevalence of depression among teenagers in Malaysia as well as globally makes it a vital issue to study. The purpose of this research is to examine the effects of social connection and self-perceived depression towards the improved mental wellbeing of the teenagers of Malaysia. Moreover, the mediating role of self-perceived depression on the improvement of the mental wellbeing of teenagers is examined in this study. This study followed a questionnaire-based approach. The sample of this study included 289 students aged between 15 and 19 years from Klang Valley, Malaysia. Prior permission was obtained from school authorities as well as from parents to allow their children to participate in the survey. To find out the structural relationship between the variables, PLS-SEM was utilized. This study finds that stronger social connections with family and friends may result in reduced self-perceived depression among Malaysian teenagers. Moreover, self-perceived depression among the teenagers surveyed had a negative effect on their improved mental wellbeing. The findings of this study will significantly affect how depression theories are currently understood and have consequences for social work, services, and policy interventions regarding teenagers in Malaysia.
  16. Jahan R, Putra ZA, Ayoub M, Abdullah B
    ACS Omega, 2022 Nov 29;7(47):42700-42710.
    PMID: 36467939 DOI: 10.1021/acsomega.2c03066
    Ionic liquids (ILs) are efficient media for the liquid-phase sulfuric acid reaction. Under mild situations, the reaction of H2S with CH4 in ILs happens extremely quick and virtually complete, resulting in liquid sulfuric acid (H2SO4(l)). 1-hexyl-3-methylimidazolium chloride ([hmim][Cl]) ILs were formerly the most effective at capturing and converting H2S. It can convert H2S to H2SO4(l) with a proportion of up to 96%. This study aimed to develop cutting-edge techniques and assess their applicability for different acidic gas capacities and H2S amounts by considering three sustainability metrics which are people (safety), planet (ecological), and profit. Then, to maximize profit while lowering the global warming potential (GWP), fire explosion damage index (FEDI), and toxicity damage index (TDI), a multiobjective optimization (MOO) case was performed. The trade-off between economic, environmental, and safety performance was expressed through Pareto-optimal solutions. The improved wet sulfuric acid (WSA)-based IL method was safer (lower fire and explosion damage index), ecologically friendly (lower GWP), and portable. The findings indicate that the improved WSA-based on IL gives the optimum results compared to conventional WSA processes, such as the profit of 5688$/h increased from 1896$/h, the GWP of 0.0138-ton CO2-eq decreased from 0.0275-ton CO2-eq, the TDI of 6.72 decreased from 13.44, and the FEDI of 6.18 decreased from 20.6, respectively. This discovery opens the door to a viable strategy for capturing and converting H2S from an acid gas stream.
  17. Murti MA, Junior R, Ahmed AN, Elshafie A
    Sci Rep, 2022 Dec 08;12(1):21200.
    PMID: 36482200 DOI: 10.1038/s41598-022-25098-1
    Earthquake is one of the natural disasters that have a big impact on society. Currently, there are many studies on earthquake detection. However, the vibrations that were detected by sensors were not only vibrations caused by the earthquake, but also other vibrations. Therefore, this study proposed an earthquake multi-classification detection with machine learning algorithms that can distinguish earthquake and non-earthquake, and vandalism vibration using acceleration seismic waves. In addition, velocity and displacement as integration products of acceleration have been considered additional features to improve the performances of machine learning algorithms. Several machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and Artificial Neural Network (ANN) have been used to develop the best algorithm for earthquake multi-classification detection. The results of this study indicate that the ANN algorithm is the best algorithm to distinguish between earthquake and non-earthquake, and vandalism vibrations. Moreover, it's also more resistant to various input features. Furthermore, using velocity and displacement as additional features has been proven to increase the performance of every model.
  18. Naeem MA, Yousaf I, Karim S, Tiwari AK, Farid S
    Econ Model, 2023 Jan;118:106095.
    PMID: 36341042 DOI: 10.1016/j.econmod.2022.106095
    The ever-emerging environmental, social, and governance (ESG) concerns have received significant attention of policymakers, governments, regulation bodies, and investors. Considering the markets volatilities due to economic and financial uncertainties that can drive the informational price inefficiencies across the markets, this study compares the asymmetric price efficiency of regional ESG markets by using an asymmetric multifractal detrended fluctuation analysis before and during COVID-19 crisis. We then examine whether global factors influence the asymmetric efficiency of regional ESG markets. Our findings reveal that COVID-19 outbreak reduced the efficiency of regional ESG markets, except for Europe, which sustained its efficiency even during the pandemic. Moreover, global factors drive the efficiency of regional ESG markets significantly before and during COVID-19. A major implication of our findings stems from the fact that a contagion reduces the efficiency of the markets while stable economic conditions make those markets informationally efficient.
  19. Yusof MZ, Cherrie JW, Samsuddin N, Semple S
    Ann Work Expo Health, 2022 10 11;66(8):1044-1055.
    PMID: 35661855 DOI: 10.1093/annweh/wxac038
    BACKGROUND: Use of pesticides has been linked to neurobehavioral deficits among exposed workers. In Malaysia, organophosphate and pyrethroid pesticides are commonly used to control mosquito-borne diseases.

    OBJECTIVES: This study aims to assess workers' lifetime occupational pesticide exposure and examine the relationship with neurobehavioral health.

    METHODS: A cross-sectional study was conducted on 158 pesticide-exposed and 176 non-exposed workers. To collect historical exposure and job tasks, a questionnaire and an occupational history interview were used. Pesticide exposure was measured in a subgroup of workers via inhalation and skin contact. The total pesticide intake of each worker was assessed using inhalation and dermal exposure models. CANTAB® computerised neurobehavioral performance assessments were used.

    RESULTS: The participants' mean age was 31 (8) years. Pirimiphos-methyl (median = 0.569 mg/m3, Interquartile range [IQR] = 0.151, 0.574) and permethrin (median = 0.136 mg/m3, IQR = 0.116, 0.157) had the highest measured personal inhalation concentrations during thermal spraying. The estimated total lifetime pesticide intake for exposed workers ranged from 0.006 g to 12800 g (median = 379 g and IQR = 131, 794 g). Dermal exposure was the predominant route of pesticide intake for all workers. Compared to controls, workers with high lifetime pesticide intake had lower Match to Sample Visual (adjusted B = -1.4, 95% Confidence Interval (CI) = -2.6, 0.1), Spatial Recognition Memory (adjusted B = -3.3, 95% CI = -5.8, 0.8), Spatial Span (SSP) (adjusted B = -0.6, 95% CI = -0.9, 0.3) scores. Workers with low pesticide intake performed worse than controls (adjusted B = -0.5, 95% CI = -0.8, -0.2) in the SSP test, but scored higher in the Motor Screening test (adjusted B = 0.9, 95% CI = 0.1, 1.6). Higher Paired Associates Learning test scores were observed among higher (adjusted B = 7.4, 95% CI = 2.3, 12.4) and lower (adjusted B = 8.1, 95% CI = 3, 13.2) pesticide intake groups. There was no significant difference between the Reaction Time and Pattern Recognition Memory tests with lifetime pesticide intake after adjusting for confounders.

    CONCLUSION: Pesticide exposure has been linked to poorer neurobehavioral performance. As dermal exposure accounts for a major fraction of total intake, pesticide prevention should focus on limiting dermal exposure.

  20. Ali M, Ullah S, Ahmad MS, Cheok MY, Alenezi H
    Environ Sci Pollut Res Int, 2023 Feb;30(9):23335-23347.
    PMID: 36322356 DOI: 10.1007/s11356-022-23811-1
    Social media is playing a vital role in the promotion of green products by reshaping the millennial green purchasing intention and green consumption behaviors, resulting in progressive growth toward sustainable environment and lower carbon emission. Non-organic consumption among humans has increased the carbon emission in contrary risked environment; therefore, consumption behavior and purchasing intention are required to change for better sustainable environment. This study's goal is to determine the effects of social media in molding the consumption behaviors while considering eco-labeling, eco-branding, social norms, and purchase intensions among millennials to promote green consumption and lower carbon emission. It was decided to use a cross-sectional questionnaire survey to get information from the students of different faculties including social sciences, engineering, and bio-sciences. SPSS.V.22 and Smart-PLS were used to analyzed the data. Results indicated that social media has a profoundly good impact on molding and impacting youth behaviors regarding the green consumption, resulting in increasing intention toward sustainable environment which results in lower carbon emission. The results are in line with the predictions and contextual analysis, as the whole world is coming back toward natural life and is working for environmental protection and sustainability specially to lower the carbon emission. Therefore, students are molding themselves toward green consumption. The study recommends that future research may be conducted to study more contextual variables, who has influence on the green consumption among the general public regarding green consumptions and lowering carbon emission and stepping toward the sustainable environment.
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