Search

Education 4.0 will be the next aspect of the curriculum since programming has been taught from the primary school level. Training 4.0 requires teachers to equip students with not only the knowledge and information but also encourage students to be able to process information, develop creative thinking, and acquire problem-solving skills. However, the competency of teachers to encourage creative thinking and problem-solving skills is still questionable. The purpose of this concept paper is to provide an understanding of the conceptual framework for enhancing the teachers' competency to enhance creativity and innovation in fulfilling the desire of education 4.0. Design thinking is an innovative method that places people right at the center of problem solving. It discusses the variables that may affect the quality of teachers in education 4.0 and presents a literature review of approaches that can contribute to the creation of effective teaching methods to develop successful students and satisfy the demands of the workforce for industrial revolution 4.0. It is found that teachers need to be competent to build students' skills in meeting a competitive and innovative workforce in the wake of the industrial revolution 4.0. There are seven dimensions in the design thinking mindset that teachers need to understand to meet the 4.0 education requirements.

The purpose of this study is to explore postgraduate students' self-directed learning (SDL) readiness using Mobile learning (M-learning) in Massive Open Online Courses (MOOCs) as a platform and task-centred activity. Reflective practice is used to measure students SDL readiness. This study is qualitative in nature. The research employed thematic analysis method, which involved systematic coding processes, entailing coding, finding categories and themes. Hence, 34 postgraduate students from a public university were selected via a purposive sampling method. They were initially introduced to M-learning course content in FutureLearn (MOOCs) platform, followed by reflective practices. Pre-reflective practices happened before students were enlisted into the M-learning process, During-reflective process in FutureLearn platform and Post-reflective upon completion of the task-centered activity. The findings revealed that most of these students were not sure of their own readiness to take on SDL in the M-learning platform during the pre-reflective stage. However, most of them were able to monitor their own readiness at the During-reflective process. Subsequently, they made progress in adopting and self-evaluating their own performance by completing the task-centered activity successfully. Therefore, the contribution of this study is on constructing reflective practices based on three different stages. Hence, the reflective approach practice has given students insight on their own learning capabilities and readiness for SDL in the mobile platform.

Failure in addressing students' needs in the context of student learning experiences may lead to negative impact on the image of higher education. Framed in self-determination theory, this study examined students' relatedness on most satisfying experiences in their respective universities. Participants' (N=1974) responses to open-ended questions were inductively coded to understand relatedness principles of student learning experiences to emerge from the data. The findings revealed that students valued the role of lecturers in professional and personal contexts, peers for friendship and teamwork and academic and non-academic experiences resulted from projects and activities. Given this, to provide a positive learning environment for students, university management needs to address and support lecturers' well-being, pay attention to student relations on campus and support academic and non-academic activities. By understanding the roles of connecting students to lecturers, students to students and students to administrative staff, we could build a dynamic and functional campus environment for each party to live and care about each other.

The shift in contemporary workplaces has caused higher education institutions to place importance on developing non-academic attributes along with academic success to help students accomplish academic and occupational goals. Reflective and integrative learning as a cumulative process of students' experiences inside and outside the classroom during university years can facilitate the development of desired attributes among undergraduates. The current study, grounded in Biggs' ("Higher education research and development," 12(1), 73-85, 1993) 3P model approach, investigated the role of student-faculty interaction, assessment and feedback, and campus environment as presage factors, and reflective and integrative learning as the process factor and academic and soft skills gain as the product factors into a full mediation model. A total of 1892 final year Malaysian undergraduate students from 18 universities across Malaysia participated in the cross-sectional survey study. The hypothesized model was tested using structural equation modeling. The results revealed that reflective and integrative learning fully mediates the relationship between student-faculty interaction, assessment and feedback, campus environment, and academic and soft skills gains. The implications for teaching and learning and student development are discussed.

The top ten killer diseases in Malaysia are largely associated with inactivity. In relation to that, Malaysia has come out with policies on prevention, control and management of non-communicable diseases (NCD) into the social, economic and environmental systems through various stakeholders. Thus, this study examined the level of physical activity (PA) among women with regards to demographic profiles, namely marital status, occupation, academic qualification and BMI. A sample of 390 women in Selangor was randomly selected. This research employed a quantitative method using a set of questionnaire adapted from International Physical Activity Questionnaire (IPAQ) in order to obtain information from the respondents. Then, descriptive analysis was employed to obtain the frequency and percentage of PA level. ANOVA was also used to find out the difference in PA with regards to demographic profiles. This study revealed that women in Selangor were generally at low level of PA. In terms of marital status, single women were moderately participated in PA as compared to married and divorced women who participated in low PA. In terms of occupation, home maker, self-employed, white-collar and students participated moderately in PA. On the other hand, professionals and unemployed women participated in low PA. It was also found that school leavers and women with certificate participated at moderate level of PA, yet, women with degree and above as well as diploma were doing low PA. Women with extra body weight, normal body weight and less body weight were found to participate at high, moderate and low level of PA respectively. Besides, findings proved that academic qualification and BMI were highly associated with PA participation. However, marital status and occupation did not associate with PA participation.

This study examined the extent to which students in one Malaysian university use smartphones to support their school-related learning and how these activities relate to CGPA. For seven consecutive days, 176 students from three academic programs recorded their daily smartphone use for learning. Significant differences were found in uses of smartphones depending on academic program. Further, it was found that the more students utilized their smartphone for university learning activities, the lower their CGPA. The outcome of this study suggests a need to evaluate and better understand the instructional uses of smartphones for tertiary students.

Telecentres in the 21st century may be able to improve standard of living, quality of life, and stability of knowledge for the rural population. The role of telecentres is widely increasing in developing political and management awareness, economic, socio-culture, technology, education and regulation awareness in rural communities. Telecentres in this context is a premise or a centre of information and communications technology (ICT) for rural residents to obtain information and knowledge. The major role of telecentre is to bridge the digital divide and socio-economic gap between rural and urban population. Telecentre is also a centre of lifelong learning activities for the rural population to seek formal and informal knowledge. This paper is intended to demonstrate the development of telecentre experiences in Malaysia that focuses on scholarly activities through lifelong learning of the rural population. The scope of discussion depicts the seven routes of informal symbiosis between lifelong learning with the telecentres that gave positive impact on rural development in Malaysia. The discussion is based on the discourse and experience of telecentre development in Malaysia.

Hypertension is a disorder that needs to be kept in check, as it can lead to cardiovascular diseases, renal failure, and if left unmanaged, to loss of life. Laboratory investigations have revealed that lifestyle alterations, such as changes in the dietary routine, can serve to keep hypertension under control. Among the productive means, of promoting adjustments, in the diet of hypertension patients are educational videos. This study delves into the development and validation of educational videos, aimed at encouraging dietary adjustments among hypertension sufferers. The design and developmental research (DDR) methodology was harnessed for this investigation. The process comes with three phases: (I) content analysis, (II) design and development and (III) evaluation. The objectives, structure/presentation and relevance of the educational videos were scrutinized by way of the Educational Content Validation Instrument in Health. Generally, I-CVI, S-CVI/Ave and S-CVI/UA for each domain met an acceptable content validity level, while several alterations were required for domain Objectives (S-CVI/Ave: 0.91, S-CVI/UA: 0.80) and Structure/Presentation (S-CVI/Ave: 0.93, S-CVI/UA: 0.60). However, no alterations were necessary for domain Relevance (S-CVI/Ave: 1.0, S-CVI/UA: 1.0). Given the abundance of existing educational videos on dietary management for hypertension, the creation of videos in this study and impartial evaluation of these materials would be advantageous for instructional purposes. This study demonstrated that the video content was valid and acknowledged by experts. This information would serve as a dependable and fact-verified means, for the management of hypertension, through dietary adjustments. [ABSTRACT FROM AUTHOR]

Background: Mild Cognitive impairment (MCI) is a pre-demented state in the elderly populace. The Mediterranean & Dietary Approaches to Stop Hypertension (DASH) Intervention for Neurodegenerative Delay (MIND) diet has shown promise in reducing the risk of MCI and Alzheimer's disease in older people. Notably, the existing MIND diet is not adapted to the specific needs of older adults in Malaysia, considering distinct food cultures and availability. Consequently, this study aimed to develop the Malaysian version of the MIND diet (MY-MINDD) scores and investigate their association with MCI in the older adult populace of Malaysia. Methods: A comprehensive pooled data analysis was conducted on combined data from 810 participants sourced from the longitudinal Long-Term Research Grant Scheme-Towards Useful Aging (LRGS-TUA) and Fundamental Research Grant Scheme (FRGS) studies. The MY-MINDD scores were developed by incorporating existing MIND diet food groups, their corresponding scoring mechanisms, and consideration of common Malaysian foods which are proven to be beneficial and detrimental to cognitive function. To substantiate the MY-MINDD scoring system, its association with MCI was evaluated using a series of validated neuropsychological test batteries. Results: MY-MINDD consists of seven food groups promote brain health and four food groups exert negative cognitive outcomes. The study participants had an average age of 67.9 ± 4.7 years. The collective MY-MINDD score for all participants was 6.4 ± 0.1 (out of a maximum 11 points), revealing a lower score in individuals with MCI at 6.0 ± 1.7 compared to those without MCI at 6.6 ± 1.6 (p < 0.001). According to hierarchical multivariate binary logistic regression analysis, being in the highest tertile of MY-MINDD score was linked to reduced odds of MCI (odds ratio (OR) = 0.43, 95% confidence interval (CI): 0.26–0.72, p < 0.001) in the fully adjusted model in comparison to the lowest tertile. Conclusion: The development of the MY-MINDD scores for Malaysian older population revealed that a stronger adherence to this diet is linked to a reduced risk of MCI. Further substantiation of the MY-MINDD scores using more objective measures, such as neuroimaging approaches and other neuropsychological batteries, is necessary. [ABSTRACT FROM AUTHOR]

Background: Traditional risk assessment tools often lack accuracy when predicting the short- and long-term mortality following a non-ST-segment elevation myocardial infarction (NSTEMI) or Unstable Angina (UA) in specific population. Objective: To employ machine learning (ML) and stacked ensemble learning (EL) methods in predicting short- and long-term mortality in Asian patients diagnosed with NSTEMI/UA and to identify the associated features, subsequently evaluating these findings against established risk scores. Methods: We analyzed data from the National Cardiovascular Disease Database for Malaysia (2006–2019), representing a diverse NSTEMI/UA Asian cohort. Algorithm development utilized in-hospital records of 9,518 patients, 30-day data from 7,133 patients, and 1-year data from 7,031 patients. This study utilized 39 features, including demographic, cardiovascular risk, medication, and clinical features. In the development of the stacked EL model, four base learner algorithms were employed: eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF), with the Generalized Linear Model (GLM) serving as the meta learner. Significant features were chosen and ranked using ML feature importance with backward elimination. The predictive performance of the algorithms was assessed using the area under the curve (AUC) as a metric. Validation of the algorithms was conducted against the TIMI for NSTEMI/UA using a separate validation dataset, and the net reclassification index (NRI) was subsequently determined. Results: Using both complete and reduced features, the algorithm performance achieved an AUC ranging from 0.73 to 0.89. The top-performing ML algorithm consistently surpassed the TIMI risk score for in-hospital, 30-day, and 1-year predictions (with AUC values of 0.88, 0.88, and 0.81, respectively, all p < 0.001), while the TIMI scores registered significantly lower at 0.55, 0.54, and 0.61. This suggests the TIMI score tends to underestimate patient mortality risk. The net reclassification index (NRI) of the best ML algorithm for NSTEMI/UA patients across these periods yielded an NRI between 40–60% (p < 0.001) relative to the TIMI NSTEMI/UA risk score. Key features identified for both short- and long-term mortality included age, Killip class, heart rate, and Low-Molecular-Weight Heparin (LMWH) administration. Conclusions: In a broad multi-ethnic population, ML approaches outperformed conventional TIMI scoring in classifying patients with NSTEMI and UA. ML allows for the precise identification of unique characteristics within individual Asian populations, improving the accuracy of mortality predictions. Continuous development, testing, and validation of these ML algorithms holds the promise of enhanced risk stratification, thereby revolutionizing future management strategies and patient outcomes. [ABSTRACT FROM AUTHOR]

Pure community is one of the elements that must be present to create a holistic smart city that is not only focused on economic development. This study aims to measure the level of development of the pure community in the cities of the Klang Valley, Malaysia. The research was conducted at the Klang Valley, Peninsular Malaysia. This study uses cluster sampling to select the respondents. Stratified sampling is a technique used for dividing the population into specific characteristics, and then using simple random sampling, samples are taken from each population. Overall, the level of pure community in Malaysia’s Klang Valley shows that they have a high value of good citizens. Despite this, it is crucial to put a guideline that allows the involvement of urban citizens to carry out mutual responsibilities in the location of their residence to be more organized. The government should be able to create an appropriate task force in the housing area that involves shared responsibility between the city’s residents. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Hospital Pharmacy / Journal Canadien de la Pharmacie Hospitalière is the property of Canadian Society of Hospital Pharmacists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The main function of Higher Educational Institutions (HEIs) is to produce skilled and knowledgeable workforce who are able to not only function with minimal guidance but also to contribute effectively to the hiring organizations. Many studies have indicated that most HEIs have somewhat similar course content and thrived at producing students with good academic achievement. But what differentiated them from one another is their ability to develop knowledge workers with the right employability skills or "soft skills" such as communication, problem-solving, interpersonal and other skills deemed important as the foundations by which they require to function at work regardless of the nature of employment. This paper reports findings of a large-scale study looking into the soft skills attainment of Malaysian HEI graduates. A quantitative survey design was employed whereby data were obtained through the administration of an instrument called the Malaysian Soft Skills Scale (My3S). My3S consists of 180 items covering seven elements namely Communications, Critical Thinking and Problem Solving, Teamwork, Moral and Professional Ethics, Leadership, Life Long Learning and Entrepreneurial aspects. The mean scores for the seven My3S subscales were found to be between 6.3 and 7.8 from the maximum possible score of 10. Specifically, comparisons were made between graduates of public and private institutions with respect to the seven elements. Findings of the study suggest that, in general, students of public HEIs scored higher in all seven skills. With respect to gender, male students scored higher than female students in all elements except for teamwork skills and moral and professional ethics. A comparison between fields of study showed that for both types of HEIs, technical students scored the highest in all skills except for moral and professional ethics. Based on the findings of this study, it is suggested that in addition to offering specific courses to improve soft skills attainment, HEIs need to embed soft skills in their academic curricula.

The high diversity of plant species in homegardens contributes to the provision of a range of goods and services, as well as considerably benefiting the environment and boosting ecological sustainability. Despite their importance, homegardens in Malaysia have not been systematically studied. This paper explores the diversity of useful plant species in Malaysian homegardens, as well as their vertical structure. The effect of the size of homegardens and socio-economic variables on the diversity of plants species were also investigated by using Self Organizing Map, a type of machine learning method. In total, 207 species of useful plants distributed among 169 genera and 78 families were recorded. At the species level, Musa paradisiaca L. had the highest frequency, while Euphorbiaceae had the highest at the family level. The vertical structure of homegardens was divided into five distinct layers: herbaceous layer, shrub layer, understory layer, canopy layer and emergent layer. Plant diversity is influenced by the size of homegardens and socioeconomic variables. As the size of the homegardens increased, as such increased the diversity of plant species. Lower-income households and worked in agriculture sectors that rely on homegrown food and medicinal plants are increasing the diversity of plant species in homegardens, highlighting the importance of these agroecosystems as a food security approach. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate to what extent knowledge inflows have taken place among professional Malaysian workforces and what the significant employee-related factors of knowledge transfer are. The development of technology parks at Technology Park Malaysia (TPM), Kulim High Tech Park (KHTP) and Multimedia Super Corridor (MSC) is the focus of the discussion. Design/methodology/approach: Data were collected through a self-administered survey to 300 local professionals; and 51 percent responded. A multiple regression was used to identify the significant determinants of transfer of knowledge. Findings: Knowledge transfer from foreign expatriate, parent and peer subsidiary companies to local professionals is at a moderate level. The overall multiple regression shows that workplace learning, personal time management, symptom of replication, adaptation and innovation, and work experience significantly contribute to the transferring of expertise to local professional employees. Research limitations/implications: The success of companies in today's competitive economy lies more in their knowledge and intellectual capital rather than other resources. Therefore, transferring new knowledge from foreign multinational corporations (MNCs) to local workforces is a basic step for future sustainable competitive advantage. Empirical evidence from previous research shows that information and communication technology can facilitate the transfer of knowledge. This is not covered in this study. Practical implications: Training mechanisms must be designed in such a way to promote in-plant training or employee attachment at the parent company or foreign peer subsidiaries. Originality/value: The paper shows that the success of knowledge transfer depends on the absorptive capacity, the organizational learning climate and the willingness of foreign expatriates in multinational corporations to transfer knowledge. This is an empirical indication of knowledge inflows within Malaysian technology parks, which is a relatively new topic to be explored.

This study aims to assess the knowledge, attitude, and practice towards pureed diet preparation among food handlers using a newly developed questionnaire for dysphagia management. A descriptive cross-sectional design study with purposive sampling was conducted in three government hospitals in the Klang Valley, Malaysia. A newly developed questionnaire, comprised of 40 quantitative items, was used and distributed to 161 food handlers from three hospitals who were directly involved in preparing pureed diets. The results demonstrated a low to moderate knowledge score among food handlers (57.54 ± 12.33), with scoring at 1.95% (very low), 28.6% (low), and 68.3% (moderate). Only 1.2% scored well in the knowledge section on pureed diet preparation. The attitude among food handlers showed that they were referred to the right source of reference before preparing the pureed diet (3.97 ± 1.35). The findings also clearly showed that the practice of using the right equipment (4.41 ± 1.19) is essential for pureed diet preparation. In conclusion, this study serves as a prognosis for future improvement in knowledge, attitude, and practice among food handlers toward pureed diet preparation. Knowledge among food handlers needs to be enhanced, and a comprehensive guideline and reference module will aid in refining dysphagia management, specifically in food preparation by food handlers. [ABSTRACT FROM AUTHOR]

Cloud-to-ground (CG) lightning is a natural phenomenon that poses significant threats to human safety, infrastructure, and equipment. The destructive impacts of lightning strikes on humans and their property have been a longstanding concern for both society and industry. Countries with high thunderstorm frequencies, such as Malaysia, experience significant fatalities and damage due to lightning strikes. To this end, a lightning locating system (LLS) was developed and deployed in a 400 km2 study area at the University Technology Malaysia (UTM), Johor, Malaysia for detecting cloud-to-ground lightning discharges. The study utilized a particle swarm optimization (PSO) algorithm as a mediator to identify the best location for a lightning strike. The algorithm was initiated with 30 particles, considering the outcomes of the MDF and TDOA techniques. The effectiveness of the PSO algorithm was found to be dependent on how the search process was arranged. The results of the detected lightning strikes by the PSO-based LLS were compared with an industrial lightning detection system installed in Malaysia. From the experimental data, the mean distance differences between the PSO-based LLS and the industrial LLS inside the study area was up to 573 m. Therefore, the proposed PSO-based LLS would be efficient and accurate to detect and map the lightning discharges occurring within the coverage area. This study is significant for researchers, insurance companies, and the public seeking to be informed about the impacts of lightning discharges. [ABSTRACT FROM AUTHOR]

3-Monochloropropane-1,2-diol esters (3-MCPDE) are food contaminants commonly found in refined vegetable oils and fats, which have possible carcinogenic implications in humans. To investigate this clinically, we conducted an occurrence level analysis on eight categories of retail and cooked food commonly consumed in Malaysia. This was used to estimate the daily exposure level, through a questionnaire-based case-control study involving 77 subjects with renal cancer, with 80 matching controls. Adjusted Odds Ratio (AOR) was calculated using the multiple logistic regression model adjusted for confounding factors. A pooled estimate of total 3-MCPDE intake per day was compared between both groups, to assess exposure and disease outcome. Among the food categories analysed, vegetable fats and oils recorded the highest occurrence levels (mean: 1.91 ± 1.90 mg/kg), significantly more than all other food categories (p <.05). Risk estimation found the Chinese ethnic group to be five times more likely to develop renal cancer compared to Malays (AOR = 5.15, p =.001). However, an inverse association was observed as the 3-MCPDE exposure among the Malays (median: 0.162 ± 0.229 mg/day/person) were found to be significantly higher than the Chinese (p =.001). There was no significant difference (p =.405) in 3-MCPDE intake between the cases (median: 0.115 ± 0.137 mg/day/person) and controls (median: 0.105 ± 0.151 mg/day/person), with no association between high intake of 3-MCPDE and the development of renal cancer (OR = 1.41, 95% CI: 0.5091–2.5553). Thus, there was insufficient clinical evidence to suggest that this contaminant contributes to the development of renal malignancies in humans through dietary consumption. Further research is necessary to support these findings, which could have significant public health ramifications for the improvement of dietary practices and food safety measures. [ABSTRACT FROM AUTHOR]

This study seeks to explore Malaysian undergraduates' perspectives on the implementation of remote learning in their university during the period of the movement control order (MCO). Since teaching and learning activities have been impacted by the pandemic, it is imperative to consider students' perspectives on carrying out classes via the online platform as many studies claim that the pandemic has disrupted teaching and learning activities. A total of 1,028 undergraduate students participated in this voluntary study by answering an open-ended survey sent out to their student email addresses during the MCO period that restricted students and lecturers from going to the university. The qualitative responses from the students were critically analyzed for thematic patterns. The four themes emerging from the data provide future teaching and learning plans that should embed self-learning techniques that could aid students if a similar predicament should hit us in the future. Course instructors can use this information to design future lessons that could assist their learners better. [ABSTRACT FROM AUTHOR]

Culture is associated with the nation-building of a country. The influence of culture refers to elements of culture such as customs, values, attitudes, norms, and beliefs. Generally, culture is considered as a set of ways of life for a group of society or community. Kuala Kangsar Royal Town is known as a cultural town. The town is conceptualized as a Royal Town and a historical heritage town based on the existence of the Perak State Sultanate buildings around the town. With this, it is seen as a crucial asset in the nationbuilding. Therefore, this study aims to identify the representation of culture in Kuala Kangsar Royal Town as a factor in nation-building. The research method used secondary data with an analysis of journals, government reports, and structured interviews with stakeholders. The findings indicate that as an old Royal Town, Kuala Kangsar emphasizes and represents the characteristics of historical heritage in enhancing nation-building. From the perspective of cultural development in Kuala Kangsar, it presents a different form of culture compared to other Royal Towns in Malaysia. [ABSTRACT FROM AUTHOR]

The Royal Town is rich in its own heritage history. Royal Town destinations that apply aesthetic values and long history have offered tourism products to fans of Royal Town values or known as tourist heritage. Tourism in the Royal Town in Malaysia is seen to be under -promoted on social media and electronic media. In fact, the Royal Town are also less prominent from the aspect of definition and heritage value found in the town. The concept of the Royal Town is unique, inherited and highlights the Royal elements are poorly documented and not recorded causing the role of the Royal Town as one of the tourist attractions in Malaysia is also left behind. Therefore, differences in terms of tourist patterns also cannot be identified and highlighted as long as tourists visit selected heritage destinations. This paper aims to examine the comparison of royalscape based on the segments of student, youth and family tourists in terms of the variety of visits to Kuala Kangsar. Convenience sampling technique was used by distributing questionnaires to 500 respondents consisting of student tourists, youth and families using descriptive analysis and One -Way Anova inferential analysis. The results show that there is a comparison in the visits of the tourist segment who visit the Royal Town of Kuala Kangsar. The seven royalscape in this study were visited by all tourist segments, Next there were differences in the manner of visits by the three tourist segments. In conclusion, this paper shows a comparison of the variety of visits by tourists based on segments. This study has limited limitations to look at comparisons based on the domestic tourist segment only and does not emphasize the variety of international tourist visits. However, the findings of this study provide space for further study by looking at the variety of international tourists in particular. [ABSTRACT FROM AUTHOR]

Hydrologists rely extensively on anticipating river streamflow (SF) to monitor and regulate flood management and water demand for people. Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. The proposed hybrid work was validated in five different study areas in Malaysia. The statistical tests analysis of the preliminary results revealed that hybrid BA-ANN was superior to forecasting the SF at all five selected study areas, with average RMSE values of 0.103 m3/s for training and 0.143 m3/s for testing as compared to ANN standalone training and testing yielding 0.091 m3/s and 0.116 m3/s, respectively. This finding signifies that the implementation of BA into the ANN model resulted in a 20% improvement. In addition, with an R2 score of 0.951, the proposed model showed a better correlation than the 0.937 value of R2 of standard ANN. Nonetheless, while the proposed work outperformed the conventional ANN, the Taylor diagram, violin plot, relative error, and scatter plot findings confirmed the disparities in the proposed work's performance throughout the research regions. The findings of these evaluations highlighted that the adaptability of the proposed works would need detailed investigation because its performance differed from case to case. [ABSTRACT FROM AUTHOR]

One of the largest hydropower facilities currently in operation in Malaysia is the Terengganu hydroelectric facility. As a result, for hydropower generation to be sustainable, future water availability in hydropower plants must be known. Therefore, it is necessary to precisely estimate how the river flow will alter as a result of changing rainfall patterns. Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. In this research, Artificial Neural Network (ANN) is integrated with a nature-inspired optimizer, namely Cuckoo search algorithm (CS-ANN). The performance of the proposed algorithm then will be examined based on statistical indices namely Root-Mean-Square Error (RSME) and Determination Coefficient (R2). Then, the accuracy of the proposed model will be then examined with the stand-alone Artificial Neural Network (ANN). The statistical indices results indicate that the proposed Hybrid CS-ANN model showed an improvement based on R2 value as compared to ANN model with R2 of 0.900 at training stage and R2 of 0.935 at testing stage. RMSE value, for ANN model, is 127.79 m3/s for training stage and 12.7 m3/s at testing stage. While for the proposed Hybrid CS-ANN model, RMSE value is equal to 121.7 m3/s for training stage and 10.95 m3/s for testing stage. The results revealed that the proposed model outperformed the stand-alone model in predicting the river flow with high level of accuracy. Although the proposed model could be applied in different case study, there is a need to tune the model internal parameters when applied in different case study. [ABSTRACT FROM AUTHOR]

Purpose: Studies have shown that managing household solid waste from low-cost housing in urban and sub-urban communities is challenging, especially in developing countries and COVID-19 era. Previous research proved that the fourth industrial revolution (4IR) technologies could be engaged to improve urban public services such as household solid waste. Thus, the study investigated 4IR role in improving low-cost housing solid waste management (LCHSWM) in the COVID-19 era across Malaysia's cities. Design/methodology/approach: The researchers selected four Malaysian cities (Pulau Pinang, Kuala Lumpur, Kuching and Putrajaya) to achieve the study's objectives via a qualitative research design. The study engaged forty experts through semi-structured virtual interviews. A thematic approach was used to analyse the collected data. Findings: Findings identified initial high implementation and maintenance costs, unwillingness to accept change, inadequate knowledge and skilled personnel to manage the operation, amongst others, as the perceived challenges facing 4IR technologies in managing low-cost housing solid waste across Malaysian cities in the COVID-19 era. Also, the study proffered measures to improve 4IR technologies usage. Research limitations/implications: This paper is limited to the perceived contributory challenges and proffered measures to improve 4IR technologies usage in managing LCHSW across Malaysian cities in the COVID-19 era. Practical implications: Proffered measures will stir policymakers and the political class (city councils) to start thinking of an all-inclusive approach to addressing the issue of LCHSW in the 21st century. As part of the practical implications, the possible outcome might enhance collaboration between the public and private sectors to better service delivery to mitigate environmental degradation. Originality/value: As revealed in the review, there is a paucity of literature regarding digital technology's roles in mitigating LCHSW across Malaysian cities in the COVID-19 era. [ABSTRACT FROM AUTHOR]

The high diversity of trees and shrubs species in homegardens contributes to the provision of a variety of food products and medicinal plants, as well as greatly benefits the environment, improving the socioeconomic status of local communities and ecological sustainability. The purpose of this study is to characterize the diversity and composition of trees and shrubs in homegardens of Kampung Masjid Ijok, Perak, Malaysia, and to investigate the physical and socioeconomic factors that influence the diversity and composition of trees and shrubs in the systems. A total of 40 homegardens were surveyed. In total, 149 species of trees and shrubs were recorded. The mean number of tree and shrub species per homegarden was 40. The average number of trees and shrubs among homegardens ranged from 46 to 121. According to the size, homegardens were categorized into small, medium-sized and large and each category differed not only in the composition of trees and shrubs but also in the type of utilization. Physical and socioeconomic factors influence the composition and diversity of trees and shrubs. The major physical factor was the size of homegardens and the most important socioeconomic factor was the income status of the homegardens owner. The diversity and composition of trees and shrubs species increased as the size of the homegardens increased. Lower-income families are more reliant on homegrown food and medicinal plants, boosting the diversity and richness of tree and shrub species in these agroecosystems, and this relationship underscores the relevance of these agroecosystems as a food security strategy. [ABSTRACT FROM AUTHOR]

Acute pharyngitis (AP) is a common reason for private primary care consultations, thus providing an avenue for widespread antibiotic intake among the community. However, there is limited data on the antibiotic prescription appropriateness and resistance information in the Malaysian private primary care setting, therefore, this study aimed to investigate the prevalence of isolated viruses and bacteria, antibiotic resistance patterns, antibiotic prescription patterns and appropriateness by general practitioners (GPs) and factors affecting antibiotic resistance and antibiotic prescription patterns. To investigate, a cross-sectional study was conducted among 205 patients presenting with AP symptoms at private primary care clinics in central Malaysia from 3rd January 2016 to 30th November 2016. Throat swabs were collected from 205 AP patients for two purposes: (i) the detection of four common respiratory viruses associated with AP via reverse-transcription real-time PCR (qRT-PCR); and (ii) bacterial identification using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Bacterial isolates were then subjected to antibiotic susceptibility screening and McIsaac scoring was calculated post-prescription based on GP selection of criteria. Generalized estimating equations analysis with multiple logistic regression was conducted to identify factors associated with presence of virus and antibiotic prescription. The results showed that 95.1% (195/205) of patients had at least one of the four viruses, with rhinovirus (88.5%) being the most prevalent, followed by adenovirus (74.9%), influenza A virus (4.6%) and enterovirus (2.1%). A total of 862 non-repetitive colonies were isolated from the culture of throat swabs from 205 patients who were positive for bacteria. From a total of 22 genera, Streptococcus constitutes the most prevalent bacteria genus (40.9%), followed by Neisseria (20%), Rothia (13.0%), Staphylococcus (11%) and Klebsiella (4.9%). Only 5 patients carried group A beta-hemolytic streptococci (GABHS). We also report the presence of vancomycin-resistant S. aureus or VRSA (n = 9, 10.1%) among which one isolate is a multidrug-resistant methicillin-resistant S. aureus (MDR-MRSA), while 54.1% (n = 111) were found to carry at least one antibiotic-resistant bacteria species. Application of the McIsaac scoring system indicated that 87.8% (n = 180) of patients should not be prescribed antibiotics as the majority of AP patients in this study had viral pharyngitis. The antibiotic prescription appropriateness by applying post-prescription McIsaac scoring was able to rule out GABHS pharyngitis in this sample with a GABHS culture-positive sensitivity of 40% (n = 2/5) and specificity of 90% (180/200). In conclusion, antibiotic-resistant throat isolates and over-prescription of antibiotics were observed and McIsaac scoring system is effective in guiding GPs to determine occurrences of viral pharyngitis to reduce unnecessary antibiotic prescription. [ABSTRACT FROM AUTHOR]

Limited research has been conducted in Asian elderly patients (aged 65 years and above) for in-hospital mortality prediction after an ST-segment elevation myocardial infarction (STEMI) using Deep Learning (DL) and Machine Learning (ML). We used DL and ML to predict in-hospital mortality in Asian elderly STEMI patients and compared it to a conventional risk score for myocardial infraction outcomes. Malaysia's National Cardiovascular Disease Registry comprises an ethnically diverse Asian elderly population (3991 patients). 50 variables helped in establishing the in-hospital death prediction model. The TIMI score was used to predict mortality using DL and feature selection methods from ML algorithms. The main performance metric was the area under the receiver operating characteristic curve (AUC). The DL and ML model constructed using ML feature selection outperforms the conventional risk scoring score, TIMI (AUC 0.75). DL built from ML features (AUC ranging from 0.93 to 0.95) outscored DL built from all features (AUC 0.93). The TIMI score underestimates mortality in the elderly. TIMI predicts 18.4% higher mortality than the DL algorithm (44.7%). All ML feature selection algorithms identify age, fasting blood glucose, heart rate, Killip class, oral hypoglycemic agent, systolic blood pressure, and total cholesterol as common predictors of mortality in the elderly. In a multi-ethnic population, DL outperformed the TIMI risk score in classifying elderly STEMI patients. ML improves death prediction by identifying separate characteristics in older Asian populations. Continuous testing and validation will improve future risk classification, management, and results. [ABSTRACT FROM AUTHOR]

Rapid growth in industrialization and urbanization have resulted in high concentration of air pollutants in the environment and thus causing severe air pollution. Excessive emission of particulate matter to ambient air has negatively impacted the health and well-being of human society. Therefore, accurate forecasting of air pollutant concentration is crucial to mitigate the associated health risk. This study aims to predict the hourly PM2.5 concentration for an urban area in Malaysia using a hybrid deep learning model. Ensemble empirical mode decomposition (EEMD) was employed to decompose the original sequence data of particulate matter into several subseries. Long short-term memory (LSTM) was used to individually forecast the decomposed subseries considering the influence of air pollutant parameters for 1-h ahead forecasting. Then, the outputs of each forecast were aggregated to obtain the final forecasting of PM2.5 concentration. This study utilized two air quality datasets from two monitoring stations to validate the performance of proposed hybrid EEMD-LSTM model based on various data distributions. The spatial and temporal correlation for the proposed dataset were analysed to determine the significant input parameters for the forecasting model. The LSTM architecture consists of two LSTM layers and the data decomposition method is added in the data pre-processing stage to improve the forecasting accuracy. Finally, a comparison analysis was conducted to compare the performance of the proposed model with other deep learning models. The results illustrated that EEMD-LSTM yielded the highest accuracy results among other deep learning models, and the hybrid forecasting model was proved to have superior performance as compared to individual models. [ABSTRACT FROM AUTHOR]

In this study, we aim to assess general psychological health, associated factors, and the potential of coping strategies as a mediator for middle-aged and older Malaysian adults during the COVID-19 pandemic. A total of 535 individuals aged 52 years and above from the previous cohort and interventional studies in Peninsular Malaysia were contacted during the Movement Control Order (MCO) issued during the COVID-19 pandemic. Telephonic interviews were conducted to obtain participant information concerning socio-demography, physical activity, subjective well-being (SWB) as assessed using flourishing scale, coping strategies, and general psychological health (GHQ-12). Simple linear regression (SLR) and multiple linear regression (MLR) analyses were performed to identify the factors associated with GHQ-12. The associated factors were further analysed using mediation analysis to determine the potential of coping strategies as a mediator. It was observed that participants had a low mean GHQ-12 score (M = 0.80, SD = 2.19), indicating good psychological health. Living arrangement, physical activity, and flourishing scale were associated with psychological health (R2 = 0.412, p < 0.05) in MLR. Positive reinterpretation, emotional support, instrumental support, humour, denial, and self-blame appear to partially mediate the relationship between socio-demography, physical activity, flourishing scale and GHQ-12, with lower coefficient values. Middle-aged and older adults in Malaysia had good psychological health during the COVID-19 pandemic, especially when living with family, physically active, and having good subjective well-being. These findings provide the initial evidence to help promote the ageing population's general well-being and mental health and enable them to cope with change during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This empirical study the relationship between risk management, security supply, financial flow and technology acceleration with sustainability of the business of TNB Malaysia. The study utilised a sample of 107 staff of TNB in Brickfields, Kuala Lumpur. The independent variable risk management, security supply, financial flow and technology acceleration while the dependent variables, is measured by sustainability of the business. The conceptual framework was proposed and the hypotheses of this study were developed. Besides, the multiple regression analysis was used in analysing the data collected in this study. The finding of the study showed that risk management, security supply, financial flow, technology acceleration and sustainability of the business have a high level. Analysis also shows that there is a positive relationship between risk management, technology acceleration and security supply and financial flow with sustainability of the business. The study concluded that it provides a useful insight to different users, the pandemic is accelerating many trends and companies need to adopt new norms for the business sustainability in the future. [ABSTRACT FROM AUTHOR]

Copyright of e-BANGI Journal is the property of e-BANGI Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to understand the reproductive biology of Thynnichthys thynnoides at Rui River, Perak, Malaysia. A total sample of 175 individuals, including 83 from Kuala Rui (S1) and 92 from Air Ganda (S2), were collected from local artisanal fishers. Fish was caught using gill nets and scoop nets during migration and spawning seasons (i.e., November to December 2018). For each fish individual, the total length (TL), body weight (BW), and ovary weight (OW) were and. A Chi-square test was performed to evaluate the sex ratio of the studied population. Simple linear regression analysis was used to explain the relationship between absolute fecundity (FA) or relative fecundity (FR) with total length, body weight, and ovary weight. For a coefficient of determination (r²) and correlation coefficient (r), a regression equation was determined. The results showed that the TL of T. thynnoides varied from 13.3 to 20.3 cm, with a calculated mean of 16.78 ± 1.1 cm. Body weights ranged from 31.86 to 78.86 g, with an average body weight of 53.81 ± 10.1 g. The FA ranged from 14454 to 29531 (mean = 21112 ± 4612) eggs per fish, and the FR from this study ranged from 211 to 658 (mean = 358 ± 93), where the OW was more significantly correlated with the absolute fecundity (r>0.513; p<0.001) than other body metrics. Negative allometric growth of T. thynnoides was observed during this study. The overall ratio of the T. thynnoides was 1:0.82 (male: female). In conclusion, this study has shown that the fecundity of the fish population is declining, although the cause is still unclear. The knowledge of this study would help fisheries managers plan necessary regulations for sustainable fishery practice at the Rui and Perak rivers, specifically during the migration and spawning season of T. thynnoides. [ABSTRACT FROM AUTHOR]

Child marriage is a global issue that concerns the violation of children's rights. All signatory countries to the International Convention on the Rights of the Child (UNCRC), including Malaysia, are obliged to raise the marriageable age to 18 years old as a legal measure to curb child marriage. However, the proposed law reform received strong rejection and criticism from religious groups in various Muslim countries. Religious traditionalist groups saw child marriage as permissible in Islamic law following the authority of the hadith of Aisha's marriage to Prophet Muhammad at the age of six. This article aims to analyse the abovementioned hadith by highlighting the discussion between the conflicting groups of Muslim scholars in the context of child marriage. This study employed content analysis to the Islamic legal texts and hadith commentaries in classical and contemporary works. This study found that the controversial hadith in question is a sound authority and cannot be dismissed as a legal basis for several matters in Islamic family law, including the permissibility of a father to marry off his young child. However, the hadith should not be considered as an authority to condone child marriage in today’s context. As a way forward, child rights’ advocates may pose other arguments within the Islamic law framework such as maslaha and Siyasah Shar'iyya to curb child marriage in Malaysia. [ABSTRACT FROM AUTHOR]

The use of augmented reality as a teaching aid among teachers is becoming more widespread. So, it is a must to create a holistic framework of augmented reality in order to enhance the teaching and learning context. Therefore, the purpose of this study is to develop an augmented reality immersive learning design (AILeaD) framework by using the Fuzzy Delphi Technique. The objective of this research is to gain experts' consensus in building and identifying constructs and elements as well as their place in the AILeaD framework. The Fuzzy Delphi Technique is used as a systematic method to evaluate, verify as well as to make a decision in modifying all needed constructs and elements in order to create the AILeaD framework through the consensus of the experts. The research questionnaire is divided into three sections which are technology skills, instructional designs and type of augmented reality applications in a total of 36 items and using the Likert-7 point scale. The sample of this research consists of 10 experts from educational technology, teaching technology, augmented reality and model development. The finding showed that the experts agreed and approved all of the constructs and elements where the three conditions were fulfilled which are the item value is less than or same with the threshold value (d) < 0.2, experts' consensus percentage exceeded 75% and defuzzification value per item exceeded α-cut = 0.5. This study could contribute to the educational policy that focuses on the development of teaching quality with the improvement of existing skills among educators through the innovation and utilization of technology in the teaching and learning context. This is in line with Malaysia Education Blueprint known as Shift 7 (2013-2025) where it leverages the utilization of ICT to enhance the quality of education in Malaysia. The implication of this study is to make the AILeaD framework as a guideline for teachers, lecturers and instructional designers in producing the teaching aids in accordance with augmented reality and taking Gagne Nine Events, Cognitive Theory of Multimedia Learning dan Revised Bloom Taxonomy into account. [ABSTRACT FROM AUTHOR]

Acridotheres tristis, or common myna or Indian myna is a bird species that can mimic human words and sounds around them. Local trainers used to teach the common myna in the State of Kelantan to mimic the words taught using several training procedures. This study aims to determine whether the training procedures used by local trainers have helped in the training process, and the factors that affect the mimicry process for this species are also highlighted. Interview sessions were conducted in nine districts in the State of Kelantan to collect data from local trainers from November 2021 until May 2022. This study utilised the Kruskal-Wallis test to analyse the significant difference in training time among different training procedures and different types of food and water for common myna. The results indicated that the training procedures used by local trainers have affected the training time of this species (p ≤ 0.05). The mean value of training time for other scrape techniques is the lowest, which is considered the best training method in training common myna to mimic the words. The second highest mean value is none scraping methods, followed by scraping tongue using Lalang, which has the highest mean value. In addition, the types of food and water given to common myna by the local trainers during the training procedure did not show a significant difference in training time. [ABSTRACT FROM AUTHOR]

Introduction: The genomic length of the ABO gene is 18 kb comprising seven exons. The test tube method is the most common method to determine an individual’s blood group, which is prone to human error during interpretation. As the knowledge advances, so do the methods of determining the blood group. The study aims to compare and evaluate the test tube and molecular techniques, Restriction Fragment Length Polymorphism-Polymerase Chain Reaction (RFLP-PCR), in determining the patient’s blood groups. Methods: RFLP-PCR is a method of amplifying the targeted genomic DNA and subjecting it to restriction enzyme digestion. KpnⅠ was used to recognize the cutting site containing SNP rs8176719. Then, gel electrophoresis was also done to confirm the restriction enzyme digestion pattern, and further sequencing was done to validate the SNP’s presence. Results: Out of 150 patients recruited at FMC, HSAAS, 38% were blood group O and 62% were non-O blood group. They were tested using the test tube method. The results for the molecular test show that KpnⅠ could differentiate and indicate the genotype of each tested sample, which was 96.49% of blood group O were wildtype and 3.51% were heterozygous mutant. The frequency of allele C in blood group O was 1.75% with OR of 0.00054 (95% CI). Single Nucleotide Polymorphism (SNP) is a variation at a single base position in a genomic sequence. Studies found that SNPs can be used to tag specific blood groups; for example, rs8176719 is being used to tag blood group O. Conclusion:The results that were obtained from FMSC HSAAS agreed with research conducted at the National Blood Center of Malaysia, which stated the prevalence of blood group O and AB were 36.7% and 8.98% respectively. KpnⅠ can be used to differentiate the genotype of rs8176719, which tagged blood group O. [ABSTRACT FROM AUTHOR]

Malaysia adopted the GHS through the CLASS Regulations of 2013. This new approach for chemical classification is inconsistent with the CIMAH Regulations of 1996 and has introduced new hazard categories, which are not included in the current major hazard identification criteria. For identifying MHI in Malaysia, the chemicals need to be reclassified. Therefore, this study aims to propose the indicative criteria for major hazard installation that are aligned with CLASS in order to simplify the process. The newly listed chemical threshold quantity, focusing on the acute toxicity group, was also identified. The steps involved include comparing major hazard legislation in the selected country, matching the criteria of CIMAH and CLASS, and reclassifying chemicals in Schedule Two of CIMAH. For estimation of TQ for nitric acid, dispersion modeling was selected. A guide for selecting suitable parameters was developed, ALOHA software was used to simulate the model, and the estimation result for nitric acid was 15.5 tonnes. This study provides the opportunity to improve CIMAH by applying CLASS hazard categories to identify major hazard installation. The guide to estimate TQ could be used for other acute toxicity chemicals as an option for regulators to negotiate and decide the TQ in CIMAH. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) has been used for a long time and has gained wide attention over the last several years. It can handle a large amount of data and allow non-linear structures by using complex mathematical computations. However, traditional ML models do suffer some problems, such as high bias and overfitting. Therefore, this has resulted in the advancement and improvement of ML techniques, such as the bagging and boosting approach, to address these problems. This study explores a series of ML models to predict the water quality classification (WQC) in the Kelantan River using data from 2005 to 2020. The proposed methodology employed 13 physical and chemical parameters of water quality and 7 ML models that are Decision Tree, Artificial Neural Networks, K-Nearest Neighbors, Naïve Bayes, Support Vector Machine, Random Forest and Gradient Boosting. Based on the analysis, the ensemble model of Gradient Boosting with a learning rate of 0.1 exhibited the best prediction performance compared to the other algorithms. It had the highest accuracy (94.90%), sensitivity (80.00%) and f-measure (86.49%), with the lowest classification error. Total Suspended Solid (TSS) was the most significant variable for the Gradient Boosting (GB) model to predict WQC, followed by Ammoniacal Nitrogen (NH3N), Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Based on the accurate water quality prediction, the results could help to improve the National Environmental Policy regarding water resources by continuously improving water quality. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the monitoring role of ownership structure (OWS) on real earnings management (REM) practices; previous studies primarily examined the effect of OWS on accrual-based earnings management. Design/methodology/approach: The sample of this study is 490 companies listed on the Malaysian Stock Exchange during the period 2013–2016 (1,960 company-year observations). The regression of a feasible generalized least square was used for data analysis. The authors use three regression models ordinary least squares, panel-corrected standard errors and Driscoll–Kraay standard errors to corroborate the findings and also examine alternative REM measures. Findings: Analysis of the data shows that family, foreign and institutional ownership has a positive link with the quality of financial reporting and, to a large extent, is capable of alleviating REM. The findings also indicate that some form of OWS significantly affects REM, corroborating existing theories on corporate governance (CG) and the perspectives of practitioners. Practical implications: The evidence concerns the significant role played by the OWS in reducing REM activities. The findings are useful in support of regulatory activities, particularly in the design of policies to regulate the OWS. The results may also provide useful insights to inform other policymakers, investors, shareholders and researchers about the active role of family, foreign and institutional investors in monitoring Malaysia's public listed companies (PLCs) to strengthen CG practices. This also leads to less REM and enhances the quality of financial reporting. Originality/value: To the authors' knowledge, this work is pioneering research from a developing country, specifically from Malaysia, to investigate the manner in which all possible OWSs influence REM. More importantly, the study recommends that regulators and researchers do not envisage OWS as a holistic phenomenon. [ABSTRACT FROM AUTHOR]

Prostate cancer is the third most common cancer in Malaysia with the lifetime risk of 1 in 117 men. Here, we initiated a longitudinal Malaysia Prostate Cancer (M‐CaP) Study to investigate the clinical and tumour characteristics, treatment patterns as well as disease outcomes of multi‐ethnic Asian men at real‐world setting. The M‐CaP database consisted of 1839 new patients with prostate cancer diagnosed between 2016 and 2018 from nine public urology referral centres across Malaysia. Basic demographic and clinical parameters, tumour characteristics, primary treatment, follow‐up and vital status data were retrieved prospectively from the hospital‐based patients' case notes or electronic medical records. Primary endpoints were overall survival (OS) and biochemical progression‐free survival (bPFS). The median age at diagnosis of M‐CaP patients was 70 years (interquartile range, IQR 65–75). Majority of patients were Chinese (831, 45.2%), followed by Malays (704, 38.3%), Indians (124, 6.7%) and other races (181, 9.8%). The median follow‐up for all patients was 23.5 months (IQR 15.9–33.6). Although 58.1% presented with late‐stage cancer, we observed ethnic and geographic disparities in late‐stage prostate cancer diagnosis. Curative radiotherapy and primary androgen deprivation therapy were the most common treatment for stage III and stage IV diseases, respectively. The median OS and bPFS of stage IV patients were 40.1 months and 19.2 months (95% CI 17.6–20.8), respectively. Late stage at presentation remains a challenge in multi‐ethnic Asian men. Early detection is imperative to improve treatment outcome and survival of patients with prostate cancer. [ABSTRACT FROM AUTHOR]

Background: Cognitive frailty, a combination of physical frailty and cognitive impairment, is associated with functional decline in older adults. However, there is limited information if cognitive frailty predicts the incidence of falls, injuries, and disability. In this study, we aimed to determine the ability of cognitive frailty in predicting the incidence of falls, injuries and disability among multi-ethnic older adults in Malaysia at 5 years follow-up.Methods: In this prospective cohort study, a total of 400 participants aged 60 years and above were successfully followed up at 5 years. Participants' socio-demographic, medical history, psycho-social, physical, cognitive and dietary intake information was obtained. Cognitive frailty was defined as comorbid physical frailty (> 1 Fried criteria) and mild cognitive impairment (Petersen criteria). Univariate analysis was performed for all variables, followed by hierarchical binary logistic regression (BLR) analysis to identify the ability of CF in predicting the incidence of falls, injuries, and disability. The significant value was set at p < 0.05.Results: Cognitive frailty was found to be associated with greater risk of adverse consequences after adjusting for covariates. Both cognitive frailty (Adjusted Odd ratio (Adj OR) = 2.98, 95% confidence interval (CI): 1.78-4.99, p < 0.05) and physical frailty (Adj OR = 2.88, 95% CI: 1.19-6.99, p < 0.05) were significant predictors of incidence of falls. Risk of injuries was also significantly increased with the presence of cognitive frailty (Adj OR = 3.06, 95% CI: 1.23-7.60, p < 0.05) and physical frailty (Adj OR = 3.04, 95% CI: 1.75-5.28, p < 0.05). In addition, cognitive frailty (Adj OR = 5.17, 95% CI: 1.11-24.21, p < 0.05) and physical frailty (Adj OR = 4.99, 95% CI: 1.11-22.57, p < 0.05) were shown to significantly predict the incidence of disability among older adults.Conclusion: Cognitive frailty is a robust predictor of falls, injuries, and disability in older adults. Possible early multi-domain preventive and management strategies of cognitive frailty that contribute to adverse consequences are required to decrease further functional decline and promote independence in older adults. [ABSTRACT FROM AUTHOR]

Deforestation and forest degradation are among the leading global concerns, as they could reduce the carbon sink and sequestration potential of the forest. The impoundment of Kenyir River, Hulu Terengganu, Malaysia, in 1985 due to the development of hydropower station has created a large area of water bodies following clearance of forested land. This study assessed the loss of forest carbon due to these activities within the period of 37 years, between 1972 and 2019. The study area consisted of Kenyir Lake catchment area, which consisted mainly of forests and the great Kenyir Lake. Remote sensing datasets have been used in this analysis. Satellite images from Landsat 1–5 MSS and Landsat 8 OLI/TRIS that were acquired between the years 1972 and 2019 were used to classify land uses in the entire landscape of Kenyir Lake catchment. Support vector machine (SVM) was adapted to generate the land-use classification map in the study area. The results show that the total study area includes 278,179 ha and forest covers dominated the area for before and after the impoundment of Kenyir Lake. The assessed loss of carbon between the years 1972 and 2019 was around 8.6 million Mg C with an annual rate of 0.36%. The main single cause attributing to the forest loss was due to clearing of forest for hydro-electric dam construction. However, the remaining forests surrounding the study area are still able to sequester carbon at a considerable rate and thus balance the carbon dynamics within the landscapes. The results highlight that carbon sequestration scenario in Kenyir Lake catchment area shows the potential of the carbon sink in the study area are acceptable with only 17% reduction of sequestration ability. The landscape of the study area is considered as highly vegetated area despite changes due to dam construction. [ABSTRACT FROM AUTHOR]

Background: Conventional risk score for predicting short and long-term mortality following an ST-segment elevation myocardial infarction (STEMI) is often not population specific. Objective: Apply machine learning for the prediction and identification of factors associated with short and long-term mortality in Asian STEMI patients and compare with a conventional risk score. Methods: The National Cardiovascular Disease Database for Malaysia registry, of a multi-ethnic, heterogeneous Asian population was used for in-hospital (6299 patients), 30-days (3130 patients), and 1-year (2939 patients) model development. 50 variables were considered. Mortality prediction was analysed using feature selection methods with machine learning algorithms and compared to Thrombolysis in Myocardial Infarction (TIMI) score. Invasive management of varying degrees was selected as important variables that improved mortality prediction. Results: Model performance using a complete and reduced variable produced an area under the receiver operating characteristic curve (AUC) from 0.73 to 0.90. The best machine learning model for in-hospital, 30 days, and 1-year outperformed TIMI risk score (AUC = 0.88, 95% CI: 0.846–0.910; vs AUC = 0.81, 95% CI:0.772–0.845, AUC = 0.90, 95% CI: 0.870–0.935; vs AUC = 0.80, 95% CI: 0.746–0.838, AUC = 0.84, 95% CI: 0.798–0.872; vs AUC = 0.76, 95% CI: 0.715–0.802, p < 0.0001 for all). TIMI score underestimates patients' risk of mortality. 90% of non-survival patients are classified as high risk (>50%) by machine learning algorithm compared to 10–30% non-survival patients by TIMI. Common predictors identified for short- and long-term mortality were age, heart rate, Killip class, fasting blood glucose, prior primary PCI or pharmaco-invasive therapy and diuretics. The final algorithm was converted into an online tool with a database for continuous data archiving for algorithm validation. Conclusions: In a multi-ethnic population, patients with STEMI were better classified using the machine learning method compared to TIMI scoring. Machine learning allows for the identification of distinct factors in individual Asian populations for better mortality prediction. Ongoing continuous testing and validation will allow for better risk stratification and potentially alter management and outcomes in the future. [ABSTRACT FROM AUTHOR]

A reliable river water level model to forecast the changes in different lead times is vital for flood warning systems, especially in countries like Malaysia, where flood is considered the most devastating natural disaster. In the current study, the ability of two artificial intelligence (AI) based data-driven approaches: Multi-layer Perceptron Neural Networks (MLP-NN) and An Adaptive Neuro-Fuzzy Inference System (ANFIS), as reliable models in forecasting the river level based on an hourly basis are investigated. 10-year of hourly measured data of the Muda river's water level in the northern part of Malaysia is used for training and testing the proposed models. Different statistical indices are introduced to validate the reliability of the models. Optimizing the hyper-parameters for both models is explored. Then, sensitivity analysis and uncertainty analysis are carried out. Finally, the capability of the models to forecast the river level for different lead times (1, 3, 6, 9, 12, and 24-hours ahead) is investigated. The results reveal that a high accuracy was achieved for the MLP-NN model with 4 hidden neurons with RMSE (0.01740), while for ANFIS, a model with three G-bell shaped membership functions outperformed other ANFIS models with RMSE (0.0174). MLP-NN and ANFIS achieved a high level of performance when two input combinations were used with RMSE equal to 0.01299 and 0.0130, respectively. However, MLP outperformed ANFIS in terms of running time and the uncertainty analysis test, in which the d-factor is found to be 0.000357. [ABSTRACT FROM AUTHOR]

Mangroves are one of the most productive ecosystems worldwide and provide numerous ecosystem services. This biome hosts nursery habitats and supports a diverse range of organisms including microfauna such as benthic foraminifera. This study integrates all the available information on benthic foraminifera from Malaysian mangroves, with special reference to Penang Island mangrove forests to evaluate the overall diversity and compare with the worldwide mangrove's records. This new compilation reveals 223 benthic foraminiferal species representing 116 genera, 57 families, and nine orders, of which only 48 species have been identified in Malaysian mangroves. These values are relatively higher than the previous records of benthic foraminifera from worldwide mangrove areas, however, are comparatively lower than other both shallow and deep-water environments. The results provide new insight into benthic foraminiferal diversity in mangroves and can be used as baseline data for monitoring and implementing conservation and restoration plans. [ABSTRACT FROM AUTHOR]

Safety and accident issues are considered important problems in the world. Road accident issues would have more conspicuous countenance in Malaysia. Almost every day there will be news about road accident, whether on television, newspapers and internet. Therefore, the aim of this study is to understand the general trend of road accidents in Malaysia, to estimate the best parameters of the Box-Jenkins Model and then to find the best-fitted model for road accidents in Malaysia. A monthly accident data from 2007 to 2016 was obtained form the Malaysia Institude of Road Safety (MIROS). This study applies Autoregressive Integrated Moving Average (ARIMA) time series model to study the trend of road accidents in Malaysia. Based on the result obtained, the trend of the number of road accidents in Malaysia are increasing. The finding also showed that by comparing the AIC and BIC value, ARIMA(1,1,1) was identified as the best model. This study contributes to the implementation of road safety in order to reduce the increasing trend of road accidents in Malaysia. [ABSTRACT FROM AUTHOR]

Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38 m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes. [ABSTRACT FROM AUTHOR]

An Advance Medical Directive (AMD) is a document in which competent patients express their wishes regarding their preferred choice of future medical plans in the event they become incompetent. AMD is important in relation to the patient's right to refuse treatment. However, they must also consider cultural and religious values of different communities. In Islam, there are several concerns that need to be addressed, namely the validity of the AMD according to Islamic jurisprudence and patients' right to end-of-life decision-making. To address these concerns, this article refers to multiple sources of Islamic jurisprudence, such as the Quran, the tradition of Prophet Muhammad and the works of Islamic scholars related to this topic. Based on the findings, Islam does not forbid the use of AMD as a method to honour patients' wishes in their end-of-life care. Islamic jurisprudence emphasises on the importance of seeking patients' consent before carrying out any medical procedures. However, several conditions need to be given due attention, such as: i) a patient's cognitive capacity during the process of drawing up an AMD; ii) the professional views of medical experts; iii) the involvement of family members in end-of-life care and iv) the limitations of a patient's decision-making in creating an AMD. [ABSTRACT FROM AUTHOR]