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Abstract Many studies have investigated the coronary risk factors (CRFs) among premature coronary artery disease (PCAD) patients. However, reports on the proportion and CRFs of PCAD according to different age cut-offs for PCAD is globally under-reported. This study aimed to determine the proportion of PCAD patients and analyse the significant CRFs according to different age cut-offs among percutaneous coronary intervention (PCI)-treated patients. Patients who underwent PCI between 2007 and 2018 in two cardiology centres were included (n = 29,241) and were grouped into four age cut-off groups that defines PCAD: (A) Males/females:

The purpose of this study was to examine an innovative program called "Always Samawa Forward" which was initiated by the Department of Population and Civil Registration (Disdukcapil), South Solok Regency, from the perspective of maslaḥah. The research was motivated by the efforts made by the Disdukcapil in responding the complaints from the community who find it difficult to process various new residence documents when they are married. This research is qualitative. Data sources are primary and secondary. Primary data comes from interviews with Disdukcapil employees, Head of KUA, Ulama, Head of Jorong, and several communities in South Solok Regency. Data collection techniques are interviews, and documentation. data analysis is descriptive. The results of the study show that this innovation program is very important to do considering the difficulties that must be faced by newlyweds and their families in managing some of their residence documents after marriage. The Mechanism of the program begins with the MoU between Disdukcapil and the heads of KUA in South Solok. From the perspective of maslaḥah, this innovation program is appropriate because it makes it easier for newly married couples and their families to manage various new population documents. When viewed from the level of maslaḥah, the policy of this innovation program can be classified as maslaḥah hajiyah.

Since December 2019, COVID-19 has quickly taken on a massive global form led to the World Health Organization (WHO) classified COVID-19 as a pandemic outbreak as a result. Due to a lack of information about the virus and the absence of medical services in the community during the early stages of this outbreak, the coronavirus spread quickly. Consequently, it becomes extremely difficult to control the influence of the disease outbreak. Thus, this study was aim to predict the peak numbers of the infected population on the first, the second, the third waves and endemic phase by utilizing a Susceptible-Infected-Recovered (SIR) predictive model between 25th January and 16th February 2020, corresponding to the entire first wave, the second, between 27th February 2020 and 30th June 2020, corresponding to part of the second wave, the current third wave began on 7th September 2020 and 1st April 2022, corresponding to the endemic phase, still present at the time of writing this article. The model retrieved the data from a reliable source on the Internet and its design is based on certain assumptions. The estimated reproductive value in this model for all simulations is 5.1, which are interconnected factors that have contributed to the rapid increase in the number of COVID-19 cases. This led to the outbreak of a highly contagious disease. The number of infected populations increase with the rate of disease transmission rate of infected increases and vice versa and the spread of COVID-19 from first, second, third waves and endemic reached maximum level in a very short time. The COVID-19 endemic in Malaysia is predicted to peak by the early of March 2020 for the first wave, mid of April 2020 for the second wave, early of October 2020 for the third wave and around April 22, 2022, for the endemic phase. The peak infected was predicted at 16,280,000 persons out of a total of susceptible individuals 33,573,874. Therefore, in addition to maintaining control measures at least until the anticipated peak time has passed, proper crisis management and efficient resource use are essential for successfully combating the endemic.

The research here was motivated by a number of recent studies on Hankel inequalities and sharp bounds. In this article, we define a new subclass of holomorphic convex functions that are related to tangent functions. We then derive geometric properties like the necessary and sufficient conditions, radius of convexity, growth, and distortion estimates for our defined function class. Furthermore, the sharp coefficient bounds, sharp Fekete-Szegö inequality, sharp 2nd order Hankel determinant, and Krushkal inequalities are given. Moreover, we calculate the sharp coefficient bounds, sharp Fekete-Szegö inequality, and sharp second-order Hankel determinant for the functions whose coefficients are logarithmic. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is known as one of the largest sources of global warming. One of the ways to curb CO2 emissions is by considering the environmental aspect in the supply chain management. This paper analyses the influence of carbon emissions on the Inventory Routing Problem (IRP). The IRP network consists of a depot, an assembly plant and multiple suppliers. The deterministic demands vary and are determined by the assembly plant. Fixed transportation cost, fuel consumption cost and inventory holding cost are used to evaluate the system’s total cost in which fuel consumption cost is determined by fuel consumption rate, distance, and fuel price. Backordering and split pick-up are not allowed. The main purpose of this study is to analyze the distribution network especially the overall costs of the supply chain by considering the CO2 emissions as well. The problem is known as Green Inventory Routing Problem (GIRP). The mixed-integer linear programming of this problem is adopted from Cheng et al. wherein this study a different Hybrid Genetic Algorithm is proposed at mutation operator. As predicted, GIRP has a higher total cost as it considered fuel consumption cost together with the transportation and inventory costs. The results showed the algorithm led to different sequences of routings considering the carbon dioxide emission in the objective function.

Communication is the most important key factor for a student to lead effectively because it helps them to express their opinion. Some students are struggling to socialise with other students due to a lack of communication skills. It is important for students to have effective communication because it helps them develop their leadership skills and can also improvise their self-confidence. The purpose of this study was to identify the level of effective listening, performing tasks completely and effectively, clarity of thought and expression, and leadership skills, to assess the significant difference of demographic variables (gender, age, and semester) on effective listening, performing tasks completely and effectively, clarity of thought and expression and leadership skills, to determine the relationship between effective listening, performing tasks completely and effectively, clarity of thought and expression and leadership skills, and lastly to examine whether effective listening, performing tasks completely and effectively, clarity of thought and expression relate toward leadership skills. The random sample of 155 respondents is from the Faculty of Computer and Mathematical Science (FSKM) at UiTM Perlis. To achieve all the objectives, the researcher has chosen to apply the frequency test, the independent t-Test, the one-way ANOVA, the correlation, and regression performed by the Statistical Package for Social Sciences Version 20.0. (SPSS). Based on the findings, there is a positive relationship between the role of effective communication and leadership skills, but a great deal of determination is still needed to establish leadership criteria among undergraduates, as a few students have not been aware of the importance of leadership skills in their future careers. Moreover, the analysis shows that clarity of thought and expression are the most important roles that contribute to leadership skills. The role of effective communication in enhancing leadership skills among university students must be properly studied so that students can develop their ability to soon become major leaders.

Predictions of future events must be factored into decision-making. Predictions of water quality are critical to assist authorities in making operational, management, and strategic decisions to keep the quality of water supply monitored under specific criteria. Taking advantage of the good performance of long short-term memory (LSTM) deep neural networks in time-series prediction, the purpose of this paper is to develop and train a Long-Short Term Memory (LSTM) Neural Network to predict water quality parameters in the Selangor River. The primary goal of this study is to predict five (5) water quality parameters in the Selangor River, namely Biochemical Oxygen Demand (BOD), Ammonia Nitrogen (NH3-N), Chemical Oxygen Demand (COD), pH, and Dissolved Oxygen (DO), using secondary data from different monitoring stations along the river basin. The accuracy of this method was then measured using RMSE as the forecast measure. The results show that by using the Power of Hydrogen (pH), the dataset yielded the lowest RMSE value, with a minimum of 0.2106 at station 004 and a maximum of 1.2587 at station 001. The results of the study indicate that the predicted values of the model and the actual values were in good agreement and revealed the future developing trend of water quality parameters, showing the feasibility and effectiveness of using LSTM deep neural networks to predict the quality of water parameters.

Predictions of future events must be incorporated into the decision-making process. For tourism demand, forecasting is very important to help directors and investors to make decisions in operational, tactical, and strategic decisions. This study focuses on forecasting performance between Fuzzy Time Series and ARIMA to forecast the tourist arrivals in homestays in Pahang. The main objective of this study is to compare and identify the best method between Fuzzy Time Series and Autoregressive Integrated Moving Average (ARIMA) in forecasting the arrival of tourists based on the secondary data of tourist arrivals to homestay in Pahang from January 2015 to December 2018. ARIMA models are flexible and widely used in time-series analysis and Fuzzy Time Series which do not need large samples and long past time series. These two methods have been compared by using the mean square error (MSE) and mean absolute percentage error (MAPE) as the forecast measures of accuracy. The results show that Fuzzy Time Series outperforms the ARIMA. The lowest value of MSE and MAPE was obtained from using the Fuzzy Time Series method at values 2192305.89 and 11.92256, respectively.

Malaysia enters the endemic phase of Covid-19 on 1st April 2022. Since then, the Malaysia’s economy has started to recover, and domestic tourism has also restarted. Tourism is one of the factors that contributed to the economy. Avoiding the headache to plan their own trips, tourists usually count on tour operators to turn their dream vacations into realities. Booking a tour is the easiest way for a traveller to experience a foreign land and at the same time they could enjoy their vacation and visit the best spots. The main objective of this study is to determine the main criteria of a tour packages in Langkawi Island by using Fuzzy Analytical Hierarchy Process (FAHP). The five criteria identified are transportation, cost, food service, accommodation, and tour guide. Results showed that the transportation is the most important criteria a tourist look forward in the selection of a tour package.

The main objective of the present paper is to define a class of qq-starlike functions with respect to symmetric points in circular domain. Some interesting results of these functions have been evaluated in this article. The sufficiency criteria in the form of convolutions are evaluated. Furthermore, other geometric properties such as coefficient bounds, distortion theorem, closure theorem and extreme point theorem are also obtained for these newly defined functions.

BackgroundFamilial hypercholesterolaemia (FH) patients have elevated levels of low-density lipoprotein cholesterol, rendering them at high risk of premature coronary artery disease (PCAD). However, the FH prevalence among angiogram-proven PCAD (AP-PCAD) patients and their status of coronary risk factors (CRFs) have not been reported in the Asian population.ObjectivesThis study aimed to (1) determine the prevalence of clinically diagnosed FH among AP-PCAD patients, (2) compare CRFs between AP-PCAD patients with control groups, and (3) identify the independent predictors of PCAD.MethodsAP-PCAD patients and FH patients without PCAD were recruited from Cardiology and Specialist Lipid Clinics. Subjects were divided into AP-PCAD with FH (G1), AP-PCAD without FH (G2), FH without PCAD (G3) and normal controls (G4). Medical records were collected from the clinic database and standardised questionnaires. FH was clinically diagnosed using Dutch Lipid Clinic Network Criteria.ResultsA total of 572 subjects were recruited (males:86.4%; mean±SD age: 55.6±8.5years). The prevalence of Definite, Potential and All FH among AP-PCAD patients were 6%(19/319), 16% (51/319) and 45.5% (145/319) respectively. G1 had higher central obesity, family history of PCAD and family history of hypercholesterolaemia compared to other groups. Among all subjects, diabetes [OR(95% CI): 4.7(2.9,7.7)], hypertension [OR(95% CI): 14.1(7.8,25.6)], FH [OR(95% CI): 2.9(1.5,5.5)] and Potential (Definite and Probable) FH [OR(95% CI): 4.5(2.1,9.6)] were independent predictors for PCAD. Among FH patients, family history of PCAD [OR(95% CI): 3.0(1.4,6.3)] and Definite FH [OR(95% CI): 7.1(1.9,27.4)] were independent predictors for PCAD.ConclusionPotential FH is common among AP-PCAD patients and contributes greatly to the AP-PCAD. FH-PCAD subjects have greater proportions of various risk factors compared to other groups. Presence of FH, diabetes, hypertension, obesity and family history of PCAD are independent predictors of PCAD. FH with PCAD is in very-high-risk category, hence, early management of modifiable CRFs in these patients are warranted.

The work presented in this article has been motivated by the recent research going on the Hankel determinant bounds and their related consequences, as well as the techniques used previously by many different authors. We aim to establish a new subfamily of holomorphic functions connected with the hyperbolic tangent function with bounded boundary rotation. We investigate the sharp estimate of the third Hankel determinant for this newly defined family of functions. Moreover, for the defined functions family, the Krushkal inequality, the first four initial sharp bounds of the logarithmic coefficients and the sharp second Hankel determinant of the logarithmic coefficients are given. [ABSTRACT FROM AUTHOR]

In the present article, we define and investigate a new subfamily of holomorphic functions connected with the cosine hyperbolic function with bounded turning. Further some interesting results like sharp coefficients bounds, sharp Fekete-Szego estimate, sharp 2nd Hankel determinant and nonsharp 3rd order Hankel determinant. Moreover, the same estimates have been investigated for 2-fold, 3-fold symmetric functions, the first four initial sharp bounds of logarithmic coefficient and sharp second Hankel determinant of logarithmic coefficients fort his defined function family. [ABSTRACT FROM AUTHOR]