17362 research outputs found
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Inflation threshold effects on stock prices: Evidence from the plantation sector in Malaysia
No full textThis study aims to examine the threshold effect of inflation on stock prices in the Malaysian plantation sector. This study used earnings per share (EPS) and return on equity (ROE) as proxies for microeconomic variables, and inflation (INF which proxies for the consumer price index) as a proxy for macroeconomic variables. A panel dataset covering 32 listed companies in the plantation sector from 2008Q3 to 2023Q3 is used. The results of threshold analysis show that inflation has a nonlinear effect, with a threshold value of 4.6128%. This implies that when inflation crosses this value, it significantly alters the outcome of stock prices. Inflation consistently has a negative effect on stock prices across both regimes, although the impact slightly decreases under higher inflation. Higher inflation will increase the detrimental effects of ROE and reverses the significance effect of EPS and DTE to insignificant, while enhancing the positive contributions of revenue and operating cash flow
Analyzing the influence of macroeconomic variables on tourism receipts in OIC countries: A quantile analysis approach across varying income levels
No full textThis study examines the heterogeneous effects of macroeconomic variables on tourism receipts across income tiers in Organization of Islamic Cooperation (OIC) countries, addressing a critical gap in tourism economics literature. Employing a panel quantile regression approach on data from 34 OIC countries (1995–2020), the research analyzes how exchange rates, income per capita, inflation, and trade openness differentially influence tourism receipts at lower, middle, and upper quantiles of tourism spending. The methodology leverages quantile regression for panel data (QRPD) to account for non-linear relationships and income-level heterogeneity, offering a nuanced alternative to traditional linear models. Key findings reveal significant income-tiered disparities. Exchange rate depreciation enhances tourism receipts in most contexts, except in upper-middleincome countries, where volatility signals instability. Income per capita exhibits positive yet inelastic effects in low- and lower-middle-income nations, but adverse impacts in high-income countries, suggesting market saturation. Inflation erodes receipts in low-income economies but stimulates demand in high-income OIC states, reflecting divergent tourist price sensitivities. Trade openness consistently suppresses tourism across quantiles, with high-income countries experiencing the steepest declines. These results challenge the universality of the Tourism-Led Growth Hypothesis, emphasizing context-specific dynamics. Policy recommendations advocate for income-tiered strategies: low-income countries should prioritize exchange rate stabilization, inflation control, and infrastructure investments via Islamic finance instruments, while high-income nations must pivot to premium niches like halal and cultural tourism. Regional cooperation through unified visa policies and OICwide halal certification standards is critical to harnessing collective tourism potential. Policymakers are urged to balance trade liberalization with targeted tourism-sector incentives to mitigate resource diversion. By aligning interventions with macroeconomic realities, OIC countries can transform tourism into an engine of equitable growth, advancing Sustainable Development Goals (SDGs) on economic diversification and inclusive employment
Metal-bearing nanomaterials for oral antibacteria: Mechanisms and applications
No full textThe prevalent oral diseases, such as dental caries, chronic gingivitis, and periodontitis, which are primarily caused by pathogenic bacteria, pose significant public health risks and impose substantial economic burdens. However, conventional treatment strategies for oral pathogens rely on mechanical debridement and antibiotic treatment, which remain unsatisfactory and contribute to the emergence of antimicrobial resistance pathogens. The escalating crisis of antibiotic resistance and the intricate microbial communities in oral niches urgently demand innovative antimicrobial strategies that can overcome these issues. Metal-bearing nanomaterials (MBNs), as an integration of metallic components with other substances such as polymers or inorganic materials, have demonstrated improved antimicrobial effectiveness while mitigating the toxicity associated with pure metals in oral environments. This review provides an innovative overview of designing and utilizing MBNs for oral antimicrobial applications, bridging the gap between nanomaterial design and clinical dentistry needs while guiding the development of next-generation antimicrobials in the post-antibiotic era. Firstly, we categorize and elucidate the main antibacterial mechanisms of metallic components in MBNs. Furthermore, a comprehensive summary is provided on the up-to-date advancements in using MBNs for oral antibacterial purposes, highlighting the pivotal role of metals in enhancing antibacterial properties. Finally, we discuss the existing challenges and potential future developments to establish a theoretical foundation for ongoing progress and clinical approval
Hubungan komuniti pembelajaran profesional (PLC) dengan komitmen guru
No full textKajian ini dilakukan bertujuan untuk mengenal pasti hubungan Komuniti Pembelajaran Profesional (PLC) dengan komitmen guru dalam kalangan guru sekolah menengah harian biasa bantuan penuh kerajaan di negeri Sabah. Kajian berbentuk bukan jenis eksperimental ini menggunakan kaedah tinjauan dan menggabungkan dua teknik pensampelan kebarangkalian untuk mendapatkan sampel. Dua set soal selidik iaitu TCM Employee Commitment Survey dan Learning Community Questionnaire Revised digunakan untuk mendapatkan data daripada 379 responden guru. Data dianalisis menggunakan perisian Statistical Packages for Social Sciences (SPSS) Version 21. Berpandukan analisis deskriptif, didapati PLC dan komitmen berada pada tahap tinggi. Berdasarkan analisis statitistik inferensi, ujian-t bagi PLC berdasarkan jantina adalah tidak signifikan (t=1.04, df=377, p>0.05) yang menunjukkan tidak terdapat perbezaan yang signifikan PLC berdasarkan jantina. Sementara ujian ANOVA sehala berdasarkan umur juga adalah tidak signifikan (F=.788, df =375, p>0.05) tetapi berdasarkan tempoh perkhidmatan ujian ANOVA adalah signifikan (F=9.83, df=375, p<0.05). Manakala hasil ujian-t bagi komitmen guru berdasarkan jantina menunjukkan hasil yang signifikan (t=2.86, df=377, p<0.05) yang menunjukkan terdapat perbezaan yang signifikan komitmen guru berdasarkan jantina. Ujian ANOVA sehala bagi komitmen berdasarkan umur dan tempoh perkhidmatan pula menunjukkan hasil yang tidak signifikan. Ini bermakna tidak terdapat perbezaan yang signifikan komitmen guru berdasarkan umur dan tempoh perkhidmatan. Melalui ujian Kolerasi Pearson didapati terdapat hubungan signifikan yang positif dengan kekuatan yang lemah (r=.454, p<0.01) PLC dengan komitmen guru. Kajian mencadangkan agar PLC diamalkan pada tahap tinggi memandangkan terdapat hubungan signifikan yang positif PLC dengan komitmen guru
Phytochemical contents and bioactivity of nephelium lappaceum l. (rambutan) and nephelium ramboutan-ake (pulasan)
No full textFruits are the natural sources of antioxidants. In this study, we determined the total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activities of various parts (peels, seeds, and pulps) of Nephelium lappaceum L. (rambutan merah and rambutan kuning) and Nephelium ramboutan-ake (pulasan). The fruit extracts were obtained by maceration with ethanol (70%) as the solvent. The TPC, TFC, and antioxidant activities were determined by FolinCiocalteu reagent, aluminum chloride colorimetric method, and 2, 2-diphenyl-1picrylhydrazyl (DPPH) radical scavenging method, respectively. The results were statistically analyzed by ANOVA and Tukey’s Honest Significant Difference (HSD) post hoc test. Overall, the fruits peel yielded the highest TPC (9.63 mg gallic acid equivalents, GAE/g on average) and TFC (740.83 mg quercetin equivalent, QE/g on average). Furthermore, the fruit peels showed the highest antioxidant activity (1.483 antioxidant activity index, AAI on average). Meanwhile, by comparing the edible pulps, Nephelium ramboutan-ake showed the highest TPC (4.33 mg GAE/g), TFC (94.31 mg QE/g), and antioxidant activity (1.17 AAI) among the fruits. In conclusion, the results suggest that the byproducts (peels and seeds) of the fruits could be potentially processed as functional foods and alternative sources of antioxidants
ATR-FTIR with chemometrics tools for classification and prediction of hydrogen peroxide in liquid milk
No full textHydrogen peroxide (H2O2) is a powerful oxidising agent that can serve as milk adulterant to extend its shelf life. Hydrogen peroxide (H2O2) is incorporated into milk in minimal quantities to suppress bacterial proliferation and enhance the milk's coloration. This study effectively employed Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy alongside multivariate data analysis techniques, including Principal Component Analysis (PCA), Discriminant Analysis (DA), and Multiple Linear Regression (MLR), for the discrimination and prediction of H2O2 in milk. There were 3 different approaches of wavenumber used to see the suitable wavenumber window for identification of H2O2 in UHT milk which are full spectra (4000–500 cm−1), 3200–1020 cm−1, 900–600 cm−1. The PCA indicated a cumulative variability of 85.4 % with four groups including unadulterated and different level groups of adulterants. Consequently, the DA model exhibited an exceptional differentiation between unadulterated and adulterated UHT milk, achieving a classification accuracy exceeding 95.0 % during cross-validation and 82.0 % for testing dataset utilizing the full spectra. The MLR model yielded R² values of 0.957 and 0.923, with RMSE and MSE below 1 for calibration and validation respectively. Subsequently, MLR models were externally validated with a test dataset, revealing a result for t-test (p > 0.05) demonstrating MLR's capability to ascertain the percentage of H2O2 in UHT milk as low as 0.5 %v/v. The wavenumber 2826.06 cm−1 is an appropriate fingerprint region for identifying H2O2 in the UHT milk
Extraction and characterization of tannin from Mangifera Pajang (Bambangan) peels using different extraction methods
No full textMangifera pajang is a seasonal tropical fruit tree native to Southeast Asia, known for its significant phytochemical compounds and antioxidant properties. Due to its tannin content, it can be utilized as a natural coagulant for water and wastewater treatment, offering an alternative to chemical coagulants, which are often unsustainable and have various disadvantages. This study aims to extract tannin from the peel of Mangifera pajang by exploring three extraction methods: solid-liquid extraction (SLE), soxhlet extraction (SE), and ultrasonicassisted extraction (UAE). The total tannin content (TTC), radical scavenging activity (RSA), and percentage yield were measured to determine the most effective extraction technique. The findings revealed that the SLE method yielded the highest tannin content, with an approximate TTC of 10.14%. Additionally, the SLE method showed antioxidant activity of 85%-86% and a percentage yield of 94.85%, outperforming the SE and UAE techniques
Effect of coating concentration on gas separation performance of polysulfone mixed matrix membrane for biomethane recovery from wastewater
No full textAnaerobic membrane bioreactor (AnMBR) provides a range of benefits which include high performance in extracting organic matter and energy production in the form of biogas. In this study, performance of mixed matrix membrane (MMM) to recover biomethane from wastewater was studied. Polymer matrix of polysulfone (Psf) incorporated with different inorganic fillers, halloysite nanotubes (HNT) and activated carbon (AC). Different concentration (3%, 4% and 5%) of MMM’s polydimethylsiloxane (PDMS) coating were examined by using scanning electron microscopy (SEM-EDX) and gas permeation tests. The morphological structures as well as permeability and selectivity of MMM towards carbon dioxide (CO₂) and methane (CH₄) were investigated. SEM analysis showed that increasing the concentration increases the thickness of the coated surface of the membrane. For MMMs-HNT, the thickness of the top layer increased 29.1% from the uncoated membrane to the highest concentration of PDMS coating while MMMs-AC showed the thickness of the membrane increased by 64.7%. The EDX results showed that there is 46% increase and 9.63% increased of silicon composition for both MMMs-HNT and MMMs-AC. For the gas separation performance, PDMS coated MMMs showed lower permeability but higher selectivity than uncoated MMMs. The highest selectivity of the membrane can be observed in 3wt% PDMS coated MMMs-HNT which is 15.83 with CO₂ and CH₄ permeance of 0.76 and 0.05 GPU, respectively
A review of machine learning in hyperspectral imaging for food safety
No full textManual detection methods such as human visual inspection are not quantitative and could lead to inconsistencies in food safety assessments. Conversely, traditional laboratory techniques offer quantitative assessments, but they involve expensive equipment, are time-consuming, and are destructive to the samples. To address these limitations, advances in non-destructive monitoring techniques with the implementation of machine learning (ML) algorithms can be alternative solutions. For instance, hyperspectral imaging technology, which combines spatial and spectral data to acquire a data-rich hypercube, can be integrated with ML models to assess food safety without damaging the samples. Different from the existing review studies on ML models, this review domain focuses more on staple foods and how these ML algorithms can quantify the chemical constituents in staple food sources. This study aims to differentiate the various ML models employed in food safety and discusses the challenges and future directions for effectively quantifying samples like adulterants in foods to ensure food safety. In addition, a bibliometric analysis of ML algorithms was also conducted to understand the research trends in hyperspectral imaging and ML. Besides, this review study also addresses different image-sensing technologies and contributes to research pursuing ML and deep learning for food safety purposes in agriculture
Embedding 21st century soft skills in Islamic higher education
No full textSoft skills such as communication, leadership, teamwork, problem solving and entrepreneurship are increasingly recognised as essential for preparing graduates to thrive in today’s complex and competitive global workforce. This study investigates the integration of these 21st-century soft skills within Malaysian higher education, with a specific focus on the Special Arabic Language Program (SALP) at a public institution. Using a qualitative case study design, data were collected through semi-structured interviews with SALP alumni and supported by document analysis related to the programme. The findings reveal that both academic and co-curricular components of the SALP have played a significant role in developing students’ soft skills. These experiences have fostered competencies in communication, leadership, social engagement and entrepreneurship, all nurtured within a framework grounded in Islamic values