Cysteine is one of the body’s essential amino acids to build proteins. For the early diagnosis of a number of diseases and biological issues, L-cysteine (L-Cys) is essential. Our study presents an electrochemical sensor that detects L-cysteine by immobilizing the horseradish peroxidase (HRP) enzyme on a reduced graphene oxide (GCE) modified glassy carbon electrode. The morphologies and chemical compositions of synthesized materials were examined using Fourier transform infrared spectroscopy (FTIR) and field-emission scanning electron microscopy (FESEM). The modified electrode’s electrochemical behavior was investigated using cyclic voltammetry (CV). Cyclic voltammetry demonstrated HRP/rGO/GCE has better electrocatalytic activity than bare GCE in the oxidation of L-cysteine oxidation in a solution of acetate buffer. The electrochemical sensor had a broad linear range of 0 µM to 1 mM, a 0.32 µM detection limit, and a sensitivity of 6.08 μA μM⁻¹ cm⁻². The developed sensor was successfully used for the L-cysteine detection in a real blood sample with good results.

The problem of flooding in the capital is still classified as a classic problem, but this problem still continues to emerge and becomes a trending problem during the rainy season in urban weather. This research aims to analyze the effectiveness of governance collaboration in overcoming the Jakarta flood problem. This research uses qualitative analysis and a content analysis approach. This research found that flood management using a collaborative governance approach was running optimally, the involvement of the private sector and the community was a good and rare synergy. support from international funding sources is used with effective management with the aim of using the budget on target. In the end, this research concludes that collaborative governance in Jakarta flood management is carried out optimally but requires sustainable collaborative efforts. This research has limitations in reaching the involvement of personal actors as a source of supporting information in disaster mitigation studies. Further research requires a more comprehensive discussion by reviewing the involvement of important actors in flood disaster mitigation.

This study addresses the critical issue of employee turnover intention within Malaysia’s manufacturing sector, focusing on the semiconductor industry, a pivotal component of the inclusive economy growth. The research aims to unveil the determinants of employee turnover intentions through a comprehensive analysis encompassing compensation, career development, work-life balance, and leadership style. Utilizing Herzberg’s Two-Factor Theory as a theoretical framework, the study hypothesizes that motivators (e.g., career development, recognition) and hygiene factors (e.g., compensation, working conditions) significantly influence employees’ intentions to leave. The quantitative research methodology employs a descriptive correlation design to investigate the relationships between the specified variables and turnover intention. Data was collected from executives and managers in northern Malaysia’s semiconductor industry, revealing that compensation, rewards, and work-life balance are significant predictors of turnover intention. At the same time, career development and transformational leadership style show no substantial impact. The findings suggest that manufacturing firms must reevaluate their compensation strategies, foster a conducive work-life balance, and consider a diverse workforce’s evolving needs and expectations to mitigate turnover rates. This study contributes to academic discourse by filling gaps in current literature and offers practical implications for industry stakeholders aiming to enhance employee retention and organizational competitiveness.

Mangifera indica L. (Mango, Anacardiaceae) is a popular tropical evergreen tree known for its nutritional and medicinal values. It is native to India and Southeast Asia and is known as the “king of fruits” in India and the Philippines. It is considered important in Ayurveda and other systems of medicine. Mango fruit is unique in its taste, colour, aroma, and nutritional qualities. Mangoes are a rich source of polyphenols (Mangiferin, Gallotannins, Quercetin, Isoquercetin, Ellagic acid, Glucogallin, Kaempferol, Catechins, Tannins, and the unique Xanthonoid), phenolic acids (Hydroxybenzoic acids- Gallic, Vanillic, Syringic, Protocatechuic, and p-Hydroxybenzoic acids, Hydroxycinnamic acid derivatives-p-Coumaric, Chlorogenic, Ferulic, and Caffeic acids), flavonoids (β-carotene, α-carotene, β-cryptoxanthin, and Lutein), Vitamin A, Vitamin-B6 (pyridoxine), Vitamin-C, Vitamin-E, Carbohydrates, Amino acids, Organic acids,  micronutrients (Potassium, Copper), fats (Omega-3 and 6 polyunsaturated fatty acids), dietary fibre and certain volatile compounds. About 25 different types of carotenoids have been isolated from the fruit pulp, which contributes to the colour of the fruit. Phytochemical and nutrient content may vary depending on the cultivar. Mangoes possess potential medicinal properties such as antioxidant, gastro-protective, anti-inflammatory, analgesic, immunomodulatory, anti-microbial, and many more. Mango fruit is an abundant source of all essential nutrients and phytochemicals; it could be ultilized as a nutritional supplement in the prevention and cure of several diseases. A comprehensive report on the nutritional and medicinal properties of fruit is presented below.

Optimizing Storage Location Assignment (SLA) is essential for improving warehouse operations, reducing operational costs, travel distances and picking times. The effectiveness of the optimization process should be evaluated. This study introduces a novel, generalized objective function tailored to optimize SLA through integration with a Genetic Algorithm. The method incorporates key parameters such as item order frequency, storage grouping, and proximity of items frequently ordered together. Using simulation tools, this research models a picker-to-part system in a warehouse environment characterized by complex storage constraints, varying item demands and family-grouping criteria. The study explores four scenarios with distinct parameter weightings to analyze their impact on SLA. Contrary to other research that focuses on frequency-based assignment, this article presents a novel framework for designing SLA using key parameters. The study proves that it is advantageous to deviate from a frequency-based assignment, as considering other key parameters to determine the layout can lead to more favorable operations. The findings reveal that adjusting the parameter weightings enables effective SLA customization based on warehouse operational characteristics. Scenario-based analyses demonstrated significant reductions in travel distances during order picking tasks, particularly in scenarios prioritizing ordered-together proximity and group storage. Visual layouts and picking route evaluations highlighted the benefits of balancing frequency-based arrangements with grouping strategies. The study validates the utility of a tailored generalized objective function for SLA optimization. Scenario-based evaluations underscore the importance of fine-tuning SLA strategies to align with specific operational demands, paving the way for more efficient order picking and overall warehouse management.

Freshwater problems in coastal areas include the process of salt intrusion which occurs due to decreasing groundwater levels below sea level which can cause an increase in salt levels in groundwater so that the water cannot be used for water purposes, human consumption and agricultural needs. The main objective of this research is to implementation of RWH to fulfill clean water needs in tropical coastal area in Tanah Merah Village, Indragiri Hilir Regency, with the aim of providing clean water to coastal communities. The approach method used based on fuzzy logic (FL). The model input data includes the effective area of the house’s roof, annual rainfall, roof runoff coefficient, and water consumption based on the number of families. The BWS III Sumatera provided the rainfall data for this research, which was collected from the Keritang rainfall monitoring station during 2015 and 2021. The research findings show that FL based on household scale RWH technology is used to supply clean water in tropical coastal areas that the largest rainwater contribution for the 144 m² house type for the number of residents in a house of four people with a tank capacity of 29 m² is 99.45%.