Progress in photocatalytic degradation of industrial organic dye by utilising the silver doped titanium dioxide nanocomposite.

Industrial organic dyes represent a significant portion of pollutants discharged into the environment, particularly by the textile industry. These compounds pose serious threats to living organisms due to their high toxicity. Various techniques have been explored for the degradation of organic dyes, among which heterogeneous photocatalysis utilising titanium dioxide (TiO) stands out as a promising technology.

Biochar and biosorbents derived from biomass for arsenic remediation.

Global groundwater contamination by Arsenic (As) presents a grave danger to the health of living beings and wildlife, demanding comprehensive remediation strategies. This review delves into the complex landscape of arsenic remediation, encompassing its chemical forms, occurrences, sources, and associated health risks. Advanced techniques, notably biomass-derived adsorbents, emerge as promising and cost-effective solutions.

Ameliorative Effects of Television Watching Behavior and Motivation on the Fear of COVID-19 in Older Chinese Adults During the Pandemic.

Purpose: The aim of this study was to investigate the television (TV) consumption patterns (viewing behavior and motivation) of older adults in Wuhan, China, during the COVID-19 pandemic and its impact on older adults' mental health, particularly in relation to COVID-19-induced fear.

Participants And Methods: A questionnaire survey was conducted with 405 older adults in Wuhan, China. The data were analyzed using a structural equation model to understand the relationship between TV viewing behavior, motivation, and fear related to COVID-19.

Assessment of the impacts of artificial intelligence (AI) on intercultural communication among postgraduate students in a multicultural university environment.

Artificial intelligence (AI) broadly influences different aspects of human life, especially human communication. One of the main concerns of the broad use of AI in daily interactions among different people could be whether it helps them interact easily or complicates their interactions. To answer the mentioned question, this study assessed the impacts of AI on intercultural communication among postgraduate students in a multicultural university environment.

Integrated metaheuristic algorithms with extreme learning machine models for river streamflow prediction.

Accurate river streamflow prediction is pivotal for effective resource planning and flood risk management. Traditional river streamflow forecasting models encounter challenges such as nonlinearity, stochastic behavior, and convergence reliability. To overcome these, we introduce novel hybrid models that combine extreme learning machines (ELM) with cutting-edge mathematical inspired metaheuristic optimization algorithms, including Pareto-like sequential sampling (PSS), weighted mean of vectors (INFO), and the Runge-Kutta optimizer (RUN).

Corrigendum to "Rainfall-runoff modelling based on global climate model and tropical rainfall measuring mission (GCM -TRMM): A case study in Hulu Terengganu catchment, Malaysia" [Heliyon , Issue 5, May 2023, Article e15740].

[This corrects the article DOI: 10.1016/j.heliyon.

Polyrhodanine-based nanomaterials for biomedical applications: A review.

Rhodanine is a heterocyclic organic compound that has been investigated for its potential biomedical applications, particularly in drug discovery. Rhodanine derivatives have been examined as the medication options for numerous illnesses, including cancer, inflammation, and infectious diseases. Some rhodanine derivatives have also shown promising activity against drug-resistant strains of bacteria and viruses.

Recent progress in ZnCr and NiCr layered double hydroxides and based photocatalysts for water treatment and clean energy production.

In pursuit of advancing photocatalysts for superior performance in water treatment and clean energy generation, researchers are increasingly focusing on layered double hydroxides (LDHs) which have garnered significant attention due to their customizable properties, morphologies, distinctive 2D layered structure and flexible options for modifying anions and cations. No review has previously delved specifically into ZnCr and NiCr LDH-based photocatalysts and therefore, this review highlights the recent surge in ZnCr and NiCr-based LDHs as potential photocatalysts for their applications in water purification and renewable energy generation. The structural and fundamental characteristics of layered double hydroxides and especially ZnCr-LDHs and NiCr-LDHs are outlined.

New peperomin and polyketides from dichloromethane extract of Peperomia blanda Jack. (Kunth).

Much of the new research and investigation in pharmacy sciences are concerned with developing therapeutic agents, and identifying and finding new drugs with their chemical structure to treat different human diseases such as infectious diseases from natural products. Therefore, the present findings relate to isolating five new compounds the dichloromethane extract of Peperomia blanda (Jacq.) Kunth grown on Socotra Island, Yemen.

Online Binge-Watching Among Chinese College Students: Implications for Loneliness, Anxiety, and Depression.

Purpose: This study aimed to investigate binge-watching behavior and addiction among a sample of 446 Chinese college students and assess its consequences for mental health, with a particular focus on feelings of loneliness, anxiety, and depression.

Participants And Methods: We conducted an online survey to gather data, examining participants' binge-watching habits and preferred platforms. We also utilized regression analysis to assess the impact of binge-watching addiction on mental health, exploring the associations between binge-watching addiction and feelings of loneliness, anxiety, and depression.

Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes.

This study aims to assess the practicality of utilizing artificial intelligence (AI) to replicate the adsorption capability of functionalized carbon nanotubes (CNTs) in the context of methylene blue (MB) removal. The process of generating the carbon nanotubes involved the pyrolysis of acetylene under conditions that were determined to be optimal. These conditions included a reaction temperature of 550 °C, a reaction time of 37.

Streamflow classification by employing various machine learning models for peninsular Malaysia.

Due to excessive streamflow (SF), Peninsular Malaysia has historically experienced floods and droughts. Forecasting streamflow to mitigate municipal and environmental damage is therefore crucial. Streamflow prediction has been extensively demonstrated in the literature to estimate the continuous values of streamflow level.

Predicting sea levels using ML algorithms in selected locations along coastal Malaysia.

In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. Data compiled from 1985 to 2018 was utilized for training and testing the developed models. An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model.

Analysis of urban heat islands with landsat satellite images and GIS in Kuala Lumpur Metropolitan City.

Cities are growing geographically in response to the enormous increase in urban population; consequently, comprehending growth and environmental changes is critical for long-term planning. Urbanization transforms naturally permeable surfaces into impermeable surfaces, causing an increase in urban land surface temperature, leading to the phenomenon known as urban heat islands. The urban heat islands are noticeable across Malaysia's rural communities and villages, particularly in Kuala Lumpur.

Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia.

Accurate water level prediction for both lake and river is essential for flood warning and freshwater resource management. In this study, three machine learning algorithms: multi-layer perceptron neural network (MLP-NN), long short-term memory neural network (LSTM) and extreme gradient boosting XGBoost were applied to develop water level forecasting models in Muda River, Malaysia. The models were developed using limited amount of daily water level and meteorological data from 2016 to 2018.

Innovative Metal-Organic Frameworks for Targeted Oral Cancer Therapy: A Review.

Metal-organic frameworks (MOFs) have proven to be very effective carriers for drug delivery in various biological applications. In recent years, the development of hybrid nanostructures has made significant progress, including developing an innovative MOF-loaded nanocomposite with a highly porous structure and low toxicity that can be used to fabricate core-shell nanocomposites by combining complementary materials. This review study discusses using MOF materials in cancer treatment, imaging, and antibacterial effects, focusing on oral cancer cells.

Advanced Theranostic Strategies for Viral Hepatitis Using Carbon Nanostructures.

There are several treatment protocols for acute viral hepatitis, and it is critical to recognize acute hepatitis in its earliest stages. Public health measures to control these infections also rely on rapid and accurate diagnosis. The diagnosis of viral hepatitis remains expensive, and there is no adequate public health infrastructure, while the virus is not well-controlled.

Rainfall-runoff modelling based on global climate model and tropical rainfall measuring mission (GCM -TRMM): A case study in Hulu Terengganu catchment, Malaysia.

The hydropower Plant in Terengganu is one of the major hydroelectric dams currently operated in Malaysia. For better operating and scheduling, accurate modelling of natural inflow is vital for a hydroelectric dam. The rainfall-runoff model is among the most reliable models in predicting the inflow based on the rainfall events.

Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique.

To ease water scarcity, dynamic programming, stochastic dynamic programming, and heuristic algorithms have been applied to solve problem matters related to water resources. Development, operation, and management are vital in a reservoir operating policy, especially when the reservoir serves a complex objective. In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD).

Factors Associated with Mental Health among Malaysian University Music Students: Roles of Fear of COVID-19, Nomophobia, Loneliness, Sleep Quality, and Socioeconomic Status.

Previous mental health studies have shown higher levels of anxiety, stress, and depression symptoms among university music students. In general, some similar findings have been observed for Malaysian music university students. In diagnosing the complications of mental health, there is consensus that it is essential to develop and evaluate a model oriented toward mental health illness prevention and treatment.

Synergistically Enhancing the Therapeutic Effect on Cancer, via Asymmetric Bioinspired Materials.

The undesirable side effects of conventional chemotherapy are one of the major problems associated with cancer treatment. Recently, with the development of novel nanomaterials, tumor-targeted therapies have been invented in order to achieve more specific cancer treatment with reduced unfavorable side effects of chemotherapic agents on human cells. However, the clinical application of nanomedicines has some shortages, such as the reduced ability to cross biological barriers and undesirable side effects in normal cells.

Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms.

Earthquake is one of the natural disasters that have a big impact on society. Currently, there are many studies on earthquake detection. However, the vibrations that were detected by sensors were not only vibrations caused by the earthquake, but also other vibrations.

COVID-19 pandemic and the changing views of mobility: the case of Nepal-Malaysia migration corridor.

For decades, Malaysia has been heavily dependent on unskilled and temporarily contracted migrant workers to fulfil labour gaps in the country. While Malaysia's economy continues to rely on migrant workers, the COVID-19 pandemic has further aggravated their precarious working and living conditions. In-depth interviews with Nepali migrant workers and community leaders in Malaysia and Nepal in 2021 revealed the incidence of labour rights violations, compounded by the lack of access to justice and effective remedies.