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Investigation of Kenaf Paper in the Presence of PVA for Transformers Application

Umair M, Azis N, Halis R, Jasni J

Materials (Basel), 2020 Nov 06;13(21).
PMID: 33171971 DOI: 10.3390/ma13215002

This paper presents an investigation on the physio-mechanical properties and AC breakdown voltage of the Kenaf paper in the presence of Polyvinyl Alcohol (PVA) for transformers application. Kenaf bast fibers were used in order to produce the paper through the soda pulping process. The pulps were subjected to beating up to 12,000 revolutions, whereby the PVA was added to the pulps at a different weight percentage concentration up to 12%. Morphological study was carried out on the Kenaf paper based on Scanning Electron Microscopy (SEM). The apparent density, Tensile Index (TI), Burst Index (BI), Tear Index (TeI), and AC breakdown voltage of the Kenaf paper were measured. It is found that the TI and BI of Kenaf paper can be slightly improved through the introduction of PVA. On other hand, the TeI of the Kenaf paper decreases with the increment of the PVA. The AC breakdown voltage of the Kenaf paper slightly increases with the increment of PVA weight percentage concentration.
Fulltext A renewable approach to electric vehicle charging through solar energy storage

Umair M, Hidayat NM, Sukri Ahmad A, Nik Ali NH, Mawardi MIM, Abdullah E

PLoS One, 2024;19(2):e0297376.
PMID: 38422065 DOI: 10.1371/journal.pone.0297376

Developing novel EV chargers is crucial for accelerating Electric Vehicle (EV) adoption, mitigating range anxiety, and fostering technological advancements that enhance charging efficiency and grid integration. These advancements address current challenges and contribute to a more sustainable and convenient future of electric mobility. This paper explores the performance dynamics of a solar-integrated charging system. It outlines a simulation study on harnessing solar energy as the primary Direct Current (DC) EV charging source. The approach incorporates an Energy Storage System (ESS) to address solar intermittencies and mitigate photovoltaic (PV) mismatch losses. Executed through MATLAB, the system integrates key components, including solar PV panels, the ESS, a DC charger, and an EV battery. The study finds that a change in solar irradiance from 400 W/m2 to 1000 W/m2 resulted in a substantial 47% increase in the output power of the solar PV system. Simultaneously, the ESS shows a 38% boost in output power under similar conditions, with the assessments conducted at a room temperature of 25°C. The results emphasize that optimal solar panel placement with higher irradiance levels is essential to leverage integrated solar energy EV chargers. The research also illuminates the positive correlation between elevated irradiance levels and the EV battery's State of Charge (SOC). This correlation underscores the efficiency gains achievable through enhanced solar power absorption, facilitating more effective and expedited EV charging.
Fulltext Renewable energy, regional tourism, and exports to tackle stagnant growth in developed economies

Chenhui H, Hassan MS, Afshan S, Hanif I, Umair M, Albalawi O

Heliyon, 2024 Sep 30;10(18):e37190.
PMID: 39678386 DOI: 10.1016/j.heliyon.2024.e37190

This study examines the effects of energy resources in the form of clean and unclean energy on the economic progress of 30 selected developed economies. This study used data from 1990 to 2020 and it employs the CS-ARDL method to obtain results. The results present that both clean and unclean energy significantly stimulate economic progress. The findings further expose that foreign investment resources in the form of inflow are significant factors that accelerate economic progress in developed economies. The results reveal that tourism development, capital accumulation, and exports are significant factors in boosting economic progress in the selected economies. Estimates from Dumitrescu and Hurlin's method for heterogeneous panels confirm the presence of the feedback-effect hypothesis for unclean energy, while the energy-conservation hypothesis holds for clean energy. This study suggests that targeting low-cost clean energy production is crucial for promoting economic growth and protecting the environment through carbon mitigation strategies. There is also a need to develop a policy framework that emphasizes the transformation of industry towards clean energy at a macro level. Furthermore, transitioning from unclean to clean energy may enhance economic progress by improving environmental quality norms in the selected developed economies. Finally, policies for tourism development, export improvement, and increased inflow of FDI should be directed towards fostering clean energy agreements and achieving environment-friendly economic progress in developed economies.
Fulltext Visual deep learning approaches for alphabetic sign language interpretation

Nath JK, Alam SAM, Ullah Y, Dhar M, Dewanjee J, Umair M, et al.

Sci Rep, 2026 Jun 13;16(1).
PMID: 42288698 DOI: 10.1038/s41598-026-57945-w

Sign language plays a vital role in enabling interaction for individuals with hearing and speech impairment, making accurate alphabet-level recognition a fundamental requirement for accessible human-computer interaction systems. This paper investigates visual deep learning approaches for interpreting sign language alphabets from image data. A systematic framework is developed to assess the effectiveness of transfer learning-based convolutional neural networks in capturing discriminative hand gesture features. Using a benchmark American Sign Language (ASL) alphabet dataset, several advanced architectures, including ConvNeXtXLarge, EfficientNet, VGG19, and ResNet-50, are examined under a unified experimental protocol. The comparative analysis reveals that ConvNeXtXLarge achieves the uppermost recognition performance, attaining an accuracy of 99.81%, while EfficientNet, VGG19, and ResNet-50 also demonstrate strong results with accuracy of 99.68%, 99.31%, and 97.29%, respectively. These findings emphasize the effectiveness of modern transfer learning strategies in enhancing visual representation learning for fine-grained motion recognition. The proposed evaluation framework offers practical insights into model selection for scalable and reliable sign language interpretation systems, contributing to the advancement of inclusive assistive technologies and real-world visual language understanding applications.
Global Burden of Elevated LDL-C: Findings From the Global Burden of Disease Study 2023

GBD 2023 LDL Cholesterol Collaborators, Razo C, DeCleene NK, Johnson CO, Stark BA, LeGrand K, et al.

JAMA, 2026 Aug 25;336(8):673-698.
PMID: 42525403 DOI: 10.1001/jama.2026.8628

IMPORTANCE: Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C-related burden is critical for guiding prevention and treatment strategies.
OBJECTIVES: To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends.
DESIGN, SETTING, AND POPULATION: This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals.
EXPOSURE: Population-level LDL-C concentrations.
MAIN OUTCOMES AND MEASURES: Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C-attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals.
RESULTS: In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C-attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings.
CONCLUSIONS AND RELEVANCE: Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.