Evaluation of mechanical responses of asphalt mixtures incorporating plastic waste as additives by different compaction efforts and mixing temperatures for a sustainable mixture.

Sustainable pavement is essential for country development, offering durable, environmentally friendly, and cost-effective infrastructure. For Malaysia, sustainable pavement supports Sustainable Development Goals (SDGs) 9 and 11 while addressing road deterioration caused by increasing traffic volumes and loads. This deterioration shortens pavement service life and necessitates frequent maintenance, driving the need for innovative solutions.

Operative strategies and outcomes for patients with severe pulmonary artery hypertension and intestinal obstruction: case series from single institution-sharing lessons to improve surgical outcomes.

Pulmonary hypertension is a known perioperative risk factor that carries a high morbidity and mortality rate. Severe pulmonary hypertension is related to high morbidity after general anaesthesia. We are reporting three patients with underlying severe pulmonary hypertension, who presented with intestinal obstruction managed with different perioperative approaches.

Glass fiber waste as a potential bitumen modifier and stabilizing agent in asphalt mixture.

The deterioration of Malaysia's flexible road pavements due to rutting and moisture damage presents a critical problem. Meanwhile, disposing of glass fiber wastes from manufacturing process further worsens environmental concerns. This research explores the feasibility of using glass fiber wastes as bitumen modifiers and stabilizers in stone mastic asphalt (SMA).

Prevalence of Preterm Birth and Perinatal Outcomes in a Tertiary Hospital in Malaysia.

Background Preterm birth (PTB) is defined as neonates that are born alive >22 weeks of gestation and <37 weeks of gestation. Because of the immaturity of different organ systems, 14.84 million newborns worldwide are born prematurely, which is the largest contributing factor to mortality and morbidity.

Bayesian multivariant fine mapping using the Laplace prior.

Currently, the only effect size prior that is routinely implemented in a Bayesian fine-mapping multi-single-nucleotide polymorphism (SNP) analysis is the Gaussian prior. Here, we show how the Laplace prior can be deployed in Bayesian multi-SNP fine mapping studies. We compare the ranking performance of the posterior inclusion probability (PIP) using a Laplace prior with the ranking performance of the corresponding Gaussian prior and FINEMAP.