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MOLECULAR INVESTIGATION AND PHYLOGENETIC ANALYSIS OF ANAPLASMOSIS IN DOGS

Ghauri HN, Ijaz M, Ahmed A, Muhammad Naveed MUA, Nawab Y, Javed MU, et al.

J Parasitol, 2021 03 01;107(2):295-303.
PMID: 33844841 DOI: 10.1645/20-50

Anaplasmosis is a widespread vector-borne disease affecting dogs, and Anaplasma platys is the major etiological agent of the disease. The study examines anaplasmosis molecular prevalence, related risk factors, and alteration of hematological variables in Anaplasma-affected dogs. A total of 150 blood samples were collected from dogs in the district of Lahore, Pakistan. The samples were screened with PCR targeting the 16S rRNA gene of Anaplasma. Sequencing of samples that were found positive after performing PCR was conducted. A questionnaire was developed to collect epidemiological data on subject dogs, and the information was analyzed with a logistic regression model using SPSS. The current study revealed an 11.34% (17/150) prevalence of anaplasmosis in dogs based on PCR detection. Tick infestation, previous tick history, house hygiene, and tick control status were major risk factors linked with disease occurrence. Red blood cell count, packed cell volume, hemoglobin, and platelet count were decreased significantly (P < 0.05) in Anaplasma-infected dogs. Phylogenetically, the 2 isolates of the current study clustered together, and that cluster was very similar to A. platys isolates from India, Malaysia, and Thailand.
Fulltext The Malay posttraumatic stress disorder checklist for DSM-5 (MPCLC-5) as screening tool for ptsd: determination of cut-off point against clinician administered PTSD scale for DSM-5 (CAPS-5)

Muhammad Najib Mohamad Alwi, Rafidah Bahari

Malaysian Journal of Medicine and Health Sciences, 2020;16(107):13-17.
MyJurnal

Introduction: Posttraumatic stress disorder (PTSD) is a mental health condition which develops following exposure to life-threatening events. This cross-sectional study was conducted among adult patients from all walks of life who had injuries related to motor vehicle accidents to determine the cut-off point of the Malay Posttraumatic Stress Disorder Checklist For DSM-5 (MPCLC-5) for its use as a screening tool for PTSD in the Malaysian population. Methods: Using convenient sampling method, 204 subjects who fulfilled the inclusion criteria were recruited and they were given the 17 item self-rated MPCLC-5 to fill up. Subsequently, trained personnel administered the gold standard Clinician Administered PTSD Scale for DSM 5 (CAPS-5). ROC curve analysis was done to determine appropriate cut-off point for the MPCLC-5. Results: Cut off point of 42/43 would yield the most preferable sensitivity and specificity for MPCLC-5 when compared to CAPS-5 (Sensitivity: 67.56% (95%CI 55.68% to 78.00%); Specificity : 80% (95% CI 72.08% to 86.50%) ). Conclusion: The easy to administer MPCLC-5 is suitable for screening of PTSD among local patients with a proposed cut off point of 42/43.
Fulltext Mechanical deformation of superelastic niti wire at different deflections in an orthodontic bracket system

Muhammad Fauzinizam Razali, Abdus Samad Mahmud

Malaysian Journal of Medicine and Health Sciences, 2020;16(108):13-17.
MyJurnal

Introduction: Most patients with malocclusion are given orthodontic leveling therapy with the aim of reducing the vertical discrepancy between teeth. This computational study aims to evaluate the degree of deformation of su- perelastic NiTi arch wire upon bending at different deflections in a bracket system. Methods: A three-dimensional finite-element model of a wire-bracket system was developed to simulate the bending behavior of superelastic NiTi arch wire in three-brackets configuration. A superelastic subroutine was integrated in the model to anticipate the superelastic behavior of the arch wire. The mid span of the arch wire was loaded to different extent of deflections, ranging from 1.0 to 4.0 mm. The mechanical deformation of the arch wires was accessed from three parameters, in specific the unloading force, the bending stress and the martensite fraction. Results: The superelastic wire deflected at 4.0 mm yielded smaller unloading force than the wire bent at 1.0 mm. The bending stress was highly localized at the wire curvature, with the stress magnitude increased from 465 MPa at 1.0 mm to 951 MPa at 4.0 mm deflection. The martensite volume consistently increased throughout the bending, with a fully transformed martensite was ob- served as early as 2.0 mm of deflection. The magnitude of bending stress and the volume of fully transformed mar- tensite increased gradually in relation to the wire deflection. Conclusion: The wire-bracket system induced localize wire deformation, hindering complete utilization of superelasticity during orthodontic treatment.
Fulltext Modelling Tax-Consumption Relationship: An Empirical Evidence from Asia

SHU HUI TAN, MUHAMMAD ASRAF ABDULLAH

Trends in Undergraduate Research, 2019;2(2):0-0.
MyJurnal

This study examines the impact of tax on consumption behaviour by focusing on selected countries from Asia. The study adopts panel fixed effect and random estimators to gauge the influence of tax on consumption expenditures. Findings of the study support negative influence of tax on household consumption. The finding is parallel with the absolute income hypothesis that high volume of tax collected from the public results in falling households’ disposable incomes, hence downwardly affecting households’ consumption levels. The study’s finding implies the importance of carefully observing appropriate tax policy that suit the country’s level of development in promoting high rates of economic growth and consumption.
Fulltext The relationshp between caffeine intake and aggression levels among University Suksis Corp Athletes

Megat Muhammad Asri Salleh, Normah Jusoh

Jurnal Sains Sukan & Pendidikan Jasmani, 2020;9(2):38-46.
MyJurnal

Kajian ini adalah bertujuan untuk meneliti hubungan antara pengambilan kafein dan tahap keagresifan dalam kalangan atlet Kor SUKSIS. Kajian ini berbentuk kaedah tinjauan dengan menggunakan borang soal selidik berkaitan pengambilan kafein dan tahap keagresifan The Judgements About Moral Behavior in Youth Sport (JAMBYSQ). Peserta kajian terdiri daripada 80 orang atlet sukan berpasukan SUKSIS yang dipilih secara rawak. Data telah dianalisis menggunakan ujian statistik deskriptif, ujian t tidak bersandar dan korelasi Pearson. Hasil kajian mendapati bahawa terdapat perbezaan signifikan (p = 0.014) bagi tahap kekerapan pengambilan kafein antara atlet lelaki (2.00 ± 0.87) dan atlet perempuan (1.50 ± 0.76). Selain itu, bagi tahap keagresifan pula tidak terdapat perbezaan signifikan antara atlet lelaki (3.37 ± 0.60) dan atlet perempuan (3.23 ± 0.66) serta tidak terdapat hubungan yang signifikan antara pengambilan kafein dengan tahap keagresifan semasa bersukan (r = 0.024, n = 80, p =0.831). Kesimpulannya, walaupun kekerapan pengambilan kafein berbeza mengikut jantina tetapi ia tidak mempengaruhi tahap keagresifan dalam kalangan atlet Kor SUKSIS. Oleh itu, terdapat keperluan untuk mengkaji dos kafein yang sesuai yang dapat mencetus tahap keagresifan dalam kalangan atlet
Fulltext INFLUENCES OF HYGIENE PRACTICES, AWARENESS AND INVOLVEMENT LEVELS ON ENVIRONMENTAL HYGIENE AMONG UMT STUDENTS

NUR SYUHADA IBRAHIM, ZIKRI MUHAMMAD, JUMADIL SAPUTRA

UMT Journal of Undergraduate Research, 2019;1(2):69-74.
MyJurnal

Industrial development plays the most important role inthe degradationof the global environment. In line with this issue, most universities in the world have introduced environmentalmanagement to increase awarenessamong young generation towards the environment. Therefore, this study is employed to examine the influences of hygiene practices, awareness and involvement levels towards environmentalhygiene among UMT students. The design of this study is quantitative using cross-sectionaldata collectedfrom students at residential colleges in Universiti Malaysia Terengganu. A total of 120 respondents participatedbut only data from 100 students could be used for further analysis after the datascreening process. The result of this study showed that the level of awareness of UMT students on environmental issues could be categorized as moderate. Besides that, this study found that the level of awareness had significant positive influences on environmentalhygiene. Meanwhile, hygiene practices and the level of involvement did not have significant influences on environmentalhygiene. In addition, using the findings of this study, we suggest that the stakeholders of UMT increase the hygiene practice and involvement among young generation to increase the level of awareness regarding environmental hygiene.
Fulltext Prevalence of falls and its characteristics among malaysian older adults: a review

Muhammad Iqbal, S., Bahman, J., Aslinda, C.M.

Medicine & Health, 2020;15(1):18-33.
MyJurnal

Kejatuhan adalah isu kesihatan yang sering dikaitkan dengan warga emas di seluruh dunia. Kejatuhan boleh menyebabkan kesan negatif pada individu dan juga menyebabkan kematian dalam kes tertentu. Kajian semasa kejatuhan adalah amat terhad di Malaysia. Tujuan kajian ini adalah untuk merumuskan kajian semasa yang dijalankan di Malaysia yang mengenai prevalens dan ciri-cirinya. Artikel telah dikenalpasti melalui menggunakan pangkalan data elektronik berikut: EBSCOhost, ClinicalKey, ScienceDirect, Wiley Online Library, SpringerLink dan Google Scholar. Pemilihan artikel adalah terhad kepada artikel bahasa Inggeris yang diterbitkan antara tahun 2013 hingga 2019. Kajian ini menilai golongan warga emas yang berumur 60 tahun ke atas; sama ada di kediaman, komuniti atau institut perubatan. Sembilan artikel yang berkaitan telah dikenalpasti dan disiasat. Hasil kajian menunjukkan variasi yang ketara dengan julat 4-74 % dalam prevalens kejatuhan di kalangan warga emas di Malaysia. Salah satu kajian yang dijalankan dalam komuniti menunjukkan prevalens kejatuhan yang lebih rendah. Majoriti peristiwa kejatuhan berlaku pada waktu pagi seperti yang dilaporkan oleh tiga kajian iaitu sebanyak 49%-64.7%. Kejatuhan dalam kawasan bangunan adalah jumlah tertinggi lokasi jatuh dengan 50-87% manakala di luar bangunan adalah 13-49.3%. Lokasi di bilik mandi / tandas mempunyai peratusan kejatuhan tertinggi dalam bangunan. Kejatuhan yang menyebabkan kecederaan adalah antara 47% -82%. Perubahan pada prevalens kejatuhan dalam warga emas ditentukan oleh faktor-faktor seperti lokasi dan keadaan kesihatan. Maklumat yang dikumpulkan dalam kajian ini menunjukkan terdapat kekurangan alat ukur piawai bagi mengkaji ciri-ciri kejatuhan di Malaysia. Kajian prospektif diperlukan untuk menubuhkan prevalens dan hubungan faktor-kesan kejatuhan di Malaysia.
Fulltext MALAY SINGLE SENTENCE PARSER

MUHAMMAD IQBAL NORDIN, NOOR HAFHIZAH ABD RAHIM

UMT Journal of Undergraduate Research, 2019;1(3):87-95.
MyJurnal

Parser is aprocess of classifying sentence structuresof a language. Parser receives a sentence and breaks it up into correct phrases. The purpose of this research is to develop a Malay single sentence parser that can help primary school studentsto learn Malay language according to the correct phrases. Thisis because research in Malay sentenceparsinghasnot gottenenough attention from researchers tothe extent ofbuildingparserprototypes. This research used top-down parsing technique,and grammar chosen was context-free grammar (CFG) for Malay language. However, to parse a sentence with correct phrase was a difficult task due to lack of resourcesfor obtainingMalay lexicon. Malay lexicon is a database that storesthousands of words with their correct phrases. Therefore, this research developeda Malay lexicon based on an articlefrom Dewan Masyarakatmagazine. In conclusion, this research can providehelpto the primaryschoolstudentsto organize correct Malay single sentences.
Fulltext Concept the greatness of Al-Quran as a constitution of life and its manifestation towards mercy for all nature

Muhammad Fahmi Md Ramzan, Nurfarhana Mohd Daud

Borneo Akademika, 2019;3(2):23-30.
MyJurnal
Fulltext Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring

Ahsan M, Khusna H, Wibawati, Lee MH

Sci Rep, 2023 Nov 06;13(1):19149.
PMID: 37932421 DOI: 10.1038/s41598-023-46719-3

Multivariate control charts have been applied in many sectors. One of the sectors that employ this method is network intrusion detection. However, the issue arises when the conventional control chart faces difficulty monitoring the network-traffic data that do not follow a normal distribution as required. Consequently, more false alarms will be found when inspecting network traffic data. To settle this problem, support vector data description (SVDD) is suggested. The control chart based on the SVDD distance can be applied for the non-normal distribution, even the unknown distributions. Kernel density estimation (KDE) is the nonparametric approach that can be applied in estimating the control limit of the non-parametric control charts. Based on these facts, a multivariate chart based on the integrated SVDD and KDE (SVDD-KDE) is proposed to monitor the network's anomaly. Simulation using the synthetic dataset is performed to examine the performance of the SVDD-KDE chart in detecting multivariate data shifts and outliers. Based on the simulation results, the proposed method produces better performance in detecting shifts and higher accuracy in detecting outliers. Further, the proposed method is applied in the intrusion detection system (IDS) to monitor network attacks. The NSL-KDD data is analyzed as the benchmark dataset. A comparison between the SVDD-KDE chart with the other IDS-based-control chart and the machine learning algorithms is executed. Although the it has high computational cost, the results show that the IDS based on the SVDD-KDE chart produces a high accuracy at 0.917 and AUC at 0.915 with a low false positive rate compared to several algorithms.
Analytical assessment of modulated electric flux triggered degradation of chlorfenapyr and deltamethrin pesticides in guava fruits

Ruman UE, Zubair M, Zeeshan MH

Anal Biochem, 2023 Jun 01;670:115148.
PMID: 37019252 DOI: 10.1016/j.ab.2023.115148

The purpose of this study was to explore the new effective method and investigate the dissipation of chlorfenapyr and deltamethrin (DM) pesticides used in the treatment of guava fruit from tropical and sub-tropical areas of Pakistan. Five different solutions of varying concentrations of pesticides were prepared. This study involved the in-vitro and in-vivo analysis of modulated electric flux-triggered degradation as an efficient method for the safer degradation of selected pesticides. The Taser gun was used as a tool for providing different numbers of electrical shocks of million voltages to the pesticides present in guava fruit at different temperatures. The degraded pesticides were extracted and analyzed by High-performance liquid chromatography (HPLC). The HPLC chromatograms verified that significant dissipation of pesticides took place when these were exposed to 9 shocks at 37 °C, which proved the efficiency of this degradation method. More than 50% of the total spray of both pesticides was dissipated. Thus, modulated electrical flux-triggered degradation is one of the effective methods for pesticide degradation.
Fulltext Improved accuracy and less fault prediction errors via modified sequential minimal optimization algorithm

Asim Shahid M, Alam MM, Mohd Su'ud M

PLoS One, 2023;18(4):e0284209.
PMID: 37053173 DOI: 10.1371/journal.pone.0284209

The benefits and opportunities offered by cloud computing are among the fastest-growing technologies in the computer industry. Additionally, it addresses the difficulties and issues that make more users more likely to accept and use the technology. The proposed research comprised of machine learning (ML) algorithms is Naïve Bayes (NB), Library Support Vector Machine (LibSVM), Multinomial Logistic Regression (MLR), Sequential Minimal Optimization (SMO), K Nearest Neighbor (KNN), and Random Forest (RF) to compare the classifier gives better results in accuracy and less fault prediction. In this research, the secondary data results (CPU-Mem Mono) give the highest percentage of accuracy and less fault prediction on the NB classifier in terms of 80/20 (77.01%), 70/30 (76.05%), and 5 folds cross-validation (74.88%), and (CPU-Mem Multi) in terms of 80/20 (89.72%), 70/30 (90.28%), and 5 folds cross-validation (92.83%). Furthermore, on (HDD Mono) the SMO classifier gives the highest percentage of accuracy and less fault prediction fault in terms of 80/20 (87.72%), 70/30 (89.41%), and 5 folds cross-validation (88.38%), and (HDD-Multi) in terms of 80/20 (93.64%), 70/30 (90.91%), and 5 folds cross-validation (88.20%). Whereas, primary data results found RF classifier gives the highest percentage of accuracy and less fault prediction in terms of 80/20 (97.14%), 70/30 (96.19%), and 5 folds cross-validation (95.85%) in the primary data results, but the algorithm complexity (0.17 seconds) is not good. In terms of 80/20 (95.71%), 70/30 (95.71%), and 5 folds cross-validation (95.71%), SMO has the second highest accuracy and less fault prediction, but the algorithm complexity is good (0.3 seconds). The difference in accuracy and less fault prediction between RF and SMO is only (.13%), and the difference in time complexity is (14 seconds). We have decided that we will modify SMO. Finally, the Modified Sequential Minimal Optimization (MSMO) Algorithm method has been proposed to get the highest accuracy & less fault prediction errors in terms of 80/20 (96.42%), 70/30 (96.42%), & 5 fold cross validation (96.50%).
Fulltext Enhanced cumulative sum charts for monitoring process dispersion

Abujiya MR, Riaz M, Lee MH

PLoS One, 2015;10(4):e0124520.
PMID: 25901356 DOI: 10.1371/journal.pone.0124520

The cumulative sum (CUSUM) control chart is widely used in industry for the detection of small and moderate shifts in process location and dispersion. For efficient monitoring of process variability, we present several CUSUM control charts for monitoring changes in standard deviation of a normal process. The newly developed control charts based on well-structured sampling techniques - extreme ranked set sampling, extreme double ranked set sampling and double extreme ranked set sampling, have significantly enhanced CUSUM chart ability to detect a wide range of shifts in process variability. The relative performances of the proposed CUSUM scale charts are evaluated in terms of the average run length (ARL) and standard deviation of run length, for point shift in variability. Moreover, for overall performance, we implore the use of the average ratio ARL and average extra quadratic loss. A comparison of the proposed CUSUM control charts with the classical CUSUM R chart, the classical CUSUM S chart, the fast initial response (FIR) CUSUM R chart, the FIR CUSUM S chart, the ranked set sampling (RSS) based CUSUM R chart and the RSS based CUSUM S chart, among others, are presented. An illustrative example using real dataset is given to demonstrate the practicability of the application of the proposed schemes.
Fulltext Achieving Reliability in Cloud Computing by a Novel Hybrid Approach

Shahid MA, Alam MM, Su'ud MM

Sensors (Basel), 2023 Feb 09;23(4).
PMID: 36850563 DOI: 10.3390/s23041965

Cloud computing (CC) benefits and opportunities are among the fastest growing technologies in the computer industry. Cloud computing's challenges include resource allocation, security, quality of service, availability, privacy, data management, performance compatibility, and fault tolerance. Fault tolerance (FT) refers to a system's ability to continue performing its intended task in the presence of defects. Fault-tolerance challenges include heterogeneity and a lack of standards, the need for automation, cloud downtime reliability, consideration for recovery point objects, recovery time objects, and cloud workload. The proposed research includes machine learning (ML) algorithms such as naïve Bayes (NB), library support vector machine (LibSVM), multinomial logistic regression (MLR), sequential minimal optimization (SMO), K-nearest neighbor (KNN), and random forest (RF) as well as a fault-tolerance method known as delta-checkpointing to achieve higher accuracy, lesser fault prediction error, and reliability. Furthermore, the secondary data were collected from the homonymous, experimental high-performance computing (HPC) system at the Swiss Federal Institute of Technology (ETH), Zurich, and the primary data were generated using virtual machines (VMs) to select the best machine learning classifier. In this article, the secondary and primary data were divided into two split ratios of 80/20 and 70/30, respectively, and cross-validation (5-fold) was used to identify more accuracy and less prediction of faults in terms of true, false, repair, and failure of virtual machines. Secondary data results show that naïve Bayes performed exceptionally well on CPU-Mem mono and multi blocks, and sequential minimal optimization performed very well on HDD mono and multi blocks in terms of accuracy and fault prediction. In the case of greater accuracy and less fault prediction, primary data results revealed that random forest performed very well in terms of accuracy and fault prediction but not with good time complexity. Sequential minimal optimization has good time complexity with minor differences in random forest accuracy and fault prediction. We decided to modify sequential minimal optimization. Finally, the modified sequential minimal optimization (MSMO) algorithm with the fault-tolerance delta-checkpointing (D-CP) method is proposed to improve accuracy, fault prediction error, and reliability in cloud computing.
Compulsive digital use: the risk and link of loneliness among adolescents

Amran MS, Roslan MZ, Sommer W

Int J Adolesc Med Health, 2024 Aug 01;36(4):419-423.
PMID: 38997216 DOI: 10.1515/ijamh-2024-0047

PURPOSE OF REVIEW: The current rise of digital technologies is causing adolescents to spend more time on their digital devices, especially since the lockdown period of the pandemic. Adolescents are among those who are affected by lifestyle changes and are at risk of digital addiction due to the overuse of digital technologies. This opinion paper discusses the possible risk of loneliness among adolescents due to the overuse of digital devices. In this article, we would like to propose the concept of digital abuse and its risk of loneliness, as well as discuss some proposed solutions by referring to recent statistics and research evidence to reduce digital abuse among adolescents.
RECENT FINDINGS: Evidence from previous studies highlights the association between digital addiction and loneliness among adolescents. Overusing digital devices among adolescents is also associated with various physical and psychological side effects.
SUMMARY: Recent findings support the rapid rise of digital device usage among adolescents and its contributions to digital use. More research is needed to support existing interventions, provide early screening, and combat digital addiction to protect adolescents from the risks of loneliness due to the overuse of digital devices.
Fulltext A fact based analysis of decision trees for improving reliability in cloud computing

Asim Shahid M, Alam MM, Mohd Su'ud M

PLoS One, 2024;19(12):e0311089.
PMID: 39625991 DOI: 10.1371/journal.pone.0311089

The popularity of cloud computing (CC) has increased significantly in recent years due to its cost-effectiveness and simplified resource allocation. Owing to the exponential rise of cloud computing in the past decade, many corporations and businesses have moved to the cloud to ensure accessibility, scalability, and transparency. The proposed research involves comparing the accuracy and fault prediction of five machine learning algorithms: AdaBoostM1, Bagging, Decision Tree (J48), Deep Learning (Dl4jMLP), and Naive Bayes Tree (NB Tree). The results from secondary data analysis indicate that the Central Processing Unit CPU-Mem Multi classifier has the highest accuracy percentage and the least amount of fault prediction. This holds for the Decision Tree (J48) classifier with an accuracy rate of 89.71% for 80/20, 90.28% for 70/30, and 92.82% for 10-fold cross-validation. Additionally, the Hard Disk Drive HDD-Mono classifier has an accuracy rate of 90.35% for 80/20, 92.35% for 70/30, and 90.49% for 10-fold cross-validation. The AdaBoostM1 classifier was found to have the highest accuracy percentage and the least amount of fault prediction for the HDD Multi classifier with an accuracy rate of 93.63% for 80/20, 90.09% for 70/30, and 88.92% for 10-fold cross-validation. Finally, the CPU-Mem Mono classifier has an accuracy rate of 77.87% for 80/20, 77.01% for 70/30, and 77.06% for 10-fold cross-validation. Based on the primary data results, the Naive Bayes Tree (NB Tree) classifier is found to have the highest accuracy rate with less fault prediction of 97.05% for 80/20, 96.09% for 70/30, and 96.78% for 10 folds cross-validation. However, the algorithm complexity is not good, taking 1.01 seconds. On the other hand, the Decision Tree (J48) has the second-highest accuracy rate of 96.78%, 95.95%, and 96.78% for 80/20, 70/30, and 10-fold cross-validation, respectively. J48 also has less fault prediction but with a good algorithm complexity of 0.11 seconds. The difference in accuracy and less fault prediction between NB Tree and J48 is only 0.9%, but the difference in time complexity is 9 seconds. Based on the results, we have decided to make modifications to the Decision Tree (J48) algorithm. This method has been proposed as it offers the highest accuracy and less fault prediction errors, with 97.05% accuracy for the 80/20 split, 96.42% for the 70/30 split, and 97.07% for the 10-fold cross-validation.
Reliability and validity of the Game Addiction Scale in Malaysian Adolescents

Roslan MZ, Amran MS, Sommer W

Int J Adolesc Med Health, 2024 Nov 25.
PMID: 39582428 DOI: 10.1515/ijamh-2024-0150

OBJECTIVES: Problematic gaming behavior has been an issue in many countries, raising the need for assessment tools. The Game Addiction Scale for Adolescents (GASA) by Lemmens et al. is widely used for assessing game addiction and has been adopted for use in various countries. The GASA consists of 21 items covering several criteria of game addiction: salience, tolerance, mood modification, relapse, withdrawal, conflict, and problems. The present study aimed to investigate the reliability and validity of the GASA when applied to Malaysian adolescents.
METHODS: The study was conducted in two phases (reliability assessment for phase 1 and validity assessment for phase 2). The Malay version of the Game Addiction Scale was created using a forward-translation procedure with the help of panelists consisting of researchers and educators from the fields of Psychology, Medicine, and Education to translate from English to Malay. The participants of the study were presented with both versions (Malay and English) during the data collection process. The study checked content validity with the help of 33 panelists and reliability based on the scores of 116 participants who spent at least 1 h and up to 6 h per week playing games.
RESULTS: The reliability was measured using Cronbach's alpha and provided high reliability ranging from 0.671 to 0.903 for all criteria. All criteria scored higher than 0.8 except for relapse (α=0.788) and problems (α=0.671) criteria, indicating that the instrument provides high reliability. The findings from the study show acceptable content validity with high I-CVI values ranging from 0.73 to 0.94 and an S-CVI/Ave value of 0.80. Internal consistency was excellent (α=0.949) and the Content Validity Index (I-CVI) was high for most items.
CONCLUSIONS: The results suggest that GASA is suitable for application among adolescents in Malaysia.
Optimization, physicochemical stability and in vivo study of alginate-chitosan composites as nanocarriers for low molecular weight angiotensin I-converting enzyme (ACE)-inhibitory peptide

Auwal SM, Ghanisma SBM, Saari N

J Food Drug Anal, 2024 Sep 13;32(3):358-370.
PMID: 39636769 DOI: 10.38212/2224-6614.3522

Chitosan and alginate, are non-toxic and biodegradable polymers used to enhance the stability of biotherapeutics by loading them into nanocarriers. In this study, the stone fish-derived low molecular weight peptide (Ala-Leu-Gly-Pro-Gln-Phe-Tyr), exhibited an in vitro ACE-inhibitory activity of 94.43 ± 2.05% and an IC50 of 0.012 ± 0.001 mM. The peptide was encapsulated via ionic gelation with alginate followed by polyelectrolyte complexation with chitosan. The resulting ACE-inhibitory peptide-loaded alginate-chitosan nanoparticles (ACE-I-ALG-CS NPs) were optimized to achieve small particle size (212.60 nm) and high encapsulation efficiency (EE, 74.48%). This was based on an optimum chitosan concentration (0.420%w/v), homogenization speed (6000 rpm), and homogenization time (30 min) using Box Behnken experimental design (BBED). Characterization of the ACE-I-ALG-CS NPs revealed a spherical, monodispersed morphology with high physicochemical stability during storage at 2 °C, 7 °C, and 12 °C for 12 weeks. Moreover, the in vivo study conducted on spontaneously hypertensive rats (SHRs) demonstrated a significantly higher (p < 0.05) systolic blood pressure (SBP)-lowering effect of the ACE-I-ALG-CS NPs compared to captopril and unencapsulated peptide. Hence, alginate and chitosan can be used as biocompatible coating materials to enhance the stability and in vivo anti-hypertensive effect of Ala-Leu-Gly-Pro-Gln-Phe-Tyr through encapsulation, thereby making it potentially valuable for various applications in pharmaceuticals and food industry.
The nexus between green intellectual capital, blockchain technology, green manufacturing, and sustainable performance

Umar M, Ahmad A, Sroufe R, Muhammad Z

Environ Sci Pollut Res Int, 2024 Feb;31(10):15026-15038.
PMID: 38285260 DOI: 10.1007/s11356-024-31952-8

Enterprises across the globe are facing increasing pressure to effectively utilize resources and reduce costs through green supply chain practices. Emerging technology, such as blockchain technology which enables green practices, has become a contemporary industrial paradigm. However, enterprises need to build green intellectual capital to implement blockchain technology, which can be key to realizing green supply chain practices. This research examines the impact of green intellectual capital (GIC) on blockchain technology and its role in implementing green manufacturing to achieve sustainability. Partial least squares structural equation modeling was utilized for assessing the proposed hypotheses, and cross-sectional data was accumulated from manufacturing firms. As per the results, GIC, which includes green human capital, green structural capital, and green relational capital has a crucial role in the implementation of blockchain technology. The outcomes also indicated that the adoption of blockchain technology significantly influences green manufacturing. Moreover, green manufacturing (GM) has a substantial role in improving business sustainability. This empirical research provides a deeper understanding of how GIC and blockchain technology contribute to the implementation of GM. This research also provides guidelines that managers, policymakers, and producers can use to facilitate the incorporation of GM practice into business activities.
Growth-corruption-health triaca and environmental degradation: empirical evidence from Indonesia, Malaysia, and Thailand

Azam M, Khan AQ

Environ Sci Pollut Res Int, 2017 Jul;24(19):16407-16417.
PMID: 28550635 DOI: 10.1007/s11356-017-9299-4

This study examines the impact of economic growth, corruption, health, and poverty on environmental degradation for three countries from ASEAN, namely Indonesia, Malaysia, and Thailand using annual data over the period of 1994-2014. The relationship between environmental degradation (pollution) by carbon dioxide (CO2) emissions and economic growth is examined along with some other variables, namely health expenditure, poverty, agriculture value added growth, industrial value added growth, and corruption. The ordinary least squares (OLS) method is applied as an analytical technique for parameter estimation. The empirical results reveal that almost all variables are statistically significant at the 5% level of significance, whereby test rejects the null hypotheses of non-cointegration, indicating that all variables play an important role in affecting the environment across countries. Empirical results also indicate that economic growth has significant positive impact, while health expenditures show significantly negative impact on the environment. Corruption has significant positive effect on environment in the case of Malaysia; while in the case of Indonesia and Thailand, it has insignificant results. However, for the individual analysis across countries, the regression estimate suggests that economic growth has a significant positive relationship with environment for Indonesia, while it is found insignificantly negative and positive in the case of Malaysia and Thailand, respectively, during the period under the study. Empirical findings of the study suggest that policy-makers require to make technological-friendly environment sequentially to surmount unregulated pollution, steady population transfers from rural areas to urban areas are also important, and poverty alleviation and better health provision can also help to improve the environment.

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