Advancements in effervescent-assisted dispersive micro-solid phase extraction for the analysis of emerging pollutants.

Emerging pollutants pose an increasing threat to the environment and human well-being, requiring substantial progress in analytical methodologies. Dispersive micro-solid phase extraction (μ-dSPE) has proven successful in detecting and measuring these contaminants, particularly in trace quantities. However, challenges persist in achieving a uniform sorbent distribution and efficient separation from the sample matrix.

Optimizing tumor treating fields for blood cancer therapy: Analysis of electric field distribution and dose density.

Blood cancer is a condition in which white blood cells grow uncontrollably. Tumor treating fields (TTF) are a modality of cancer treatment that utilizes electric fields to target malignant cells. To optimize the efficacy of TTF, it is necessary to investigate the distribution of electric field through varying electrode configurations and input parameters.

Detection of Vancomycin Resistant Genes in Intrinsically Antibiotic Resistant Bacteria from the Gut Microbiota of Indonesian Individuals.

Background: Antibiotic resistance is a global public health concern that has been exacerbated by the overuse and misuse of antibiotics, leading to the emergence of resistant bacteria. The gut microbiota, often influenced by antibiotic usage, plays a crucial role in overall health. Therefore, this study aimed to investigate the prevalence of antibiotic resistant genes in the gut microbiota of Indonesian coastal and highland populations, as well as to identify vancomycin-resistant bacteria and their resistant genes.

Impact of Noise Level on the Accuracy of Automated Measurement of CT Number Linearity on ACR CT and Computational Phantoms.

Background: Methods for segmentation, i.e., Full-segmentation (FS) and Segmentation-rotation (SR), are proposed for maintaining Computed Tomography (CT) number linearity.

Resource-aware video streaming (RAViS) framework for object detection system using deep learning algorithm.

Video streams can come from various sources, such as surveillance cameras, live events, drones, and video-sharing platforms. Video stream mining is challenging due to the extensive resources needed to analyze and extract useful information from continuous video data streams. This situation could result in overwhelmed resources, which causes the system to stall.

Influence of mangrove forests on subjective and psychological wellbeing of coastal communities: Case studies in Malaysia and Indonesia.

Mangrove forests possess multiple functions for the environment and society through their valuable ecosystem services. Along with this, the mangrove forests have large and diverse social values, in combination contributing to the health and wellbeing of the surrounding communities. This study aims (i) to assess the benefits of mangrove forests and their impact on subjective and psychological wellbeing of coastal communities and (ii) to understand the challenges coastal communities face that limit sustainable wellbeing.

Toward developing a sustainability index for the Islamic Social Finance program: An empirical investigation.

Several previous studies state that the Islamic Social Finance program has not fully succeeded in creating prosperity, and there are no definite measurements to show the sustainability impact of the program. Thus, a measurement is needed to analyze various aspects in achieving the success and sustainability of Islamic social finance programs. This study developed an index for performance evaluation with an emphasis on the success and sustainability of the Islamic Social Finance program.

Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand "ThaiChana".

The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thailand. This study aimed to predict factors affecting the perceived usability of Thai Chana by integrating the Protection Motivation Theory and Technology Acceptance Theory considering the System Usability Scale, utilizing deep learning neural network and random forest classifier.

Magnetic mineral characteristics, trace metals, and REE geochemistry of river sediments that serve as inlets to Lake Limboto, Sulawesi, Indonesia.

This article presents magnetic mineral characteristics, trace metals, and REE geochemistry of river sediments that serve as inlets to Lake Limboto, Sulawesi, Indonesia related to article entitled "Lithogenic and anthropogenic components in surface sediments from Lake Limboto as shown by magnetic mineral characteristics, trace metals, and REE geochemistry" [1]. River sediments were obtained from three rivers, namely Alopohu, Bionga, and Talumelito. Sieved sediments were subjected to magnetic susceptibility measurements as well as geochemical analyses that include AAS analyses for trace metals and ICP-OES for REE.

Leak Detection in Water Pipes Using Submersible Optical Optic-Based Pressure Sensor.

Leakage is undesirable in water distribution networks, as leaky pipes are financially costly both to water utilities and consumers. The ability to detect, locate, and quantify leaks can significantly improve the service delivered. Optical fibre sensors (OFS) have previously demonstrated their capabilities in performing real-time and continuous monitoring of pipe strength leak detection.