Daily estimation of NO concentrations using digital tachograph data.

Traffic information is crucial for estimating NO concentrations, but it is static and limited in predicting constantly changing NO levels. To overcome these challenges, this study utilized real-time spatial big data to capture both the spatial and temporal fluctuations in traffic. Digital tachograph (DTG) data, sourced from digital devices in all commercial vehicles, are employed to construct a DTG land use regression (LUR) model, and its performance is compared with that of a non-DTG-LUR model.

Impact of a community-based participatory research project with underserved communities at risk for hepatitis C virus in Ho Chi Minh City, Vietnam: an evaluation study.

Background: Participatory approaches have become a widely applied research approach. Despite their popularity, there are many challenges associated with the evaluation of participatory projects. Here we describe an evaluation of a community-based participatory research study of underserved communities in Ho Chi Minh City (HCMC), Vietnam at risk for hepatitis C virus.

Distracted on duty: A theory-based exploration of influences leading to mobile phone distracted riding among food delivery workers.

Using mobile phones while riding is a form of distracted riding that significantly elevates crash risk. Regrettably, the factors contributing to mobile phone use while riding (MPUWR) among food delivery riders remain under-researched. Addressing this literature gap, the current study employs the Job Demands-Resources (JD-R) model and various socio-economic factors to examine the determinants of MPUWR.

Automated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning System.

The latest advances in mobile platforms, such as robots, have enabled the automatic acquisition of full coverage point cloud data from large areas with terrestrial laser scanning. Despite this progress, the crucial post-processing step of registration, which aligns raw point cloud data from separate local coordinate systems into a unified coordinate system, still relies on manual intervention. To address this practical issue, this study presents an automated point cloud registration approach optimized for a stop-and-go scanning system based on a quadruped walking robot.

What if delivery riders quit? Challenges to last-mile logistics during the Covid-19 pandemic.

Notoriously precarious, hazardous, and stressful, delivery jobs became even more onerous and dangerous during the pandemic. In this study, set in Ho Chi Minh City, Vietnam, we applied Structural Equation Modelling to a large sample of primary data to measure delivery riders' intention to quit their jobs at the height of the pandemic. We found that job burnout was the key trigger to the intention to quit whereas the risk of Covid-19 infection did not directly affect this behavioral intention.

Non-fatal traffic crashes among food delivery riders in Vietnam: What is the problem?

Objective: The rapid development of information technologies and the COVID-19 pandemic have resulted in the proliferation of online food shopping and food delivery motorcyclists. In contrast to the relatively ample literature on factors influencing fatalities and risky riding behaviors of food delivery motorcyclists, little is known about the determinants of non-fatal crashes involving online food delivery riders. The present study examines the prevalence and factors of non-fatal crashes among food delivery riders.

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea.

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and time-consuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for forecasting algal blooms is a feasible and useful method to overcome these problems. This study explores the potential application of optical measures to enhance algal bloom prediction in terms of prediction accuracy and workload reduction, aided by machine learning (ML) models.

Attachment of DNA-Wrapped Single-Walled Carbon Nanotubes (SWNTs) for a Micron-Sized Biosensor.

We fabricated a micron-sized biodevice based on the near-infrared photoluminescence (PL) response of single-walled carbon nanotubes (SWNTs). Various biosensors using the unique optical responses of SWNTs have been proposed by many research groups. Most of these employed either colloidal suspensions of dispersed SWNTs or SWNT films on flat surfaces, such as electrodes.

Accurate discharge and water level forecasting using ensemble learning with genetic algorithm and singular spectrum analysis-based denoising.

Forecasting discharge (Q) and water level (H) are essential factors in hydrological research and flood prediction. In recent years, deep learning has emerged as a viable technique for capturing the non-linear relationship of historical data to generate highly accurate prediction results. Despite the success in various domains, applying deep learning in Q and H prediction is hampered by three critical issues: a shortage of training data, the occurrence of noise in the collected data, and the difficulty in adjusting the model's hyper-parameters.

An Efficient Method of Observing Diatom Frustules via Digital Holographic Microscopy.

Herein, we propose a convenient method to enable pretreatment of target objects using digital holographic microscopy (DHM). As a test sample, we used diatom frustules ( sp.) as the target objects.

Intentions to use ride-sourcing services in Vietnam: What happens after three months without COVID-19 infections?

The COVID-19 pandemic has brought new risks and stress for paid transport users worldwide. COVID-19 has changed mobility dynamics worldwide, including low- and middle-income countries (e.g.

Health and safety risks faced by delivery riders during the Covid-19 pandemic.

Objectives: Delivery riders have been front-line workers throughout the pandemic but little is known about their own health and safety during this time. This study explores the health and safety issues facing delivery riders in Ho Chi Minh City, Vietnam, during the Covid-19 pandemic, in particular during the second lockdown (May-October 2021).

Method: A web-based survey of more than 800 riders was conducted in August-September 2021.

Why are Hanoi students giving up on bus ridership?

University students are regarded as a readily available market segment for public transport. In Hanoi, as elsewhere, they constitute a large portion of bus passengers. However, one portion has been quitting buses, and the reasons were so far unknown.

The emergence of recreational cycling in Hanoi during the Covid-19 pandemic.

Objectives: This study examined recreational cycling in Hanoi, Vietnam, with a particular focus on changes brought about by the Covid-19 pandemic. The research questions were: (1) Has recreational cycling increased during the Covid-19 pandemic?; (2) If so, what factors have led to the increase?; and (3) What are some of the typical traits and behaviors of recreational cyclists?

Method: Face-to-face surveys of 356 recreational cyclists were carried out in March-April 2021 in four areas of inner Hanoi. The survey data were modelled through two binary and one ordinal logit regression.

Analysis of trophic networks: an optimisation approach.

We introduce a methodology to study the possible matter flows of an ecosystem defined by observational biomass data and realistic biological constraints. The flows belong to a polyhedron in a multi dimensional space that may make statistical exploration difficult in practice; instead, we propose to solve a convex optimization problem. Seven criteria based on ecological network indices have been selected to be used as convex goal functions.

Covid-19 need not spell the death of public transport: Learning from Hanoi's safety measures.

Objectives: In contrast to other cities worldwide, the pandemic has not decimated bus ridership in Hanoi. Notably, the Vietnamese capital has mostly relied on the use of face masks and hand sanitizer during travel, instead of requiring physical distancing on buses. This study examines public bus passengers' levels of compliance with Covid-19 safety measures, and the factors that affect compliance.

Factors influencing home-based telework in Hanoi (Vietnam) during and after the COVID-19 era.

During the era of COVID-19 (COronaVIrus Disease of 2019), telework has been adopted extensively in developing countries for the first time. This study analyzes data of 355 teleworkers in Hanoi (Vietnam) during April 2020, the period of social distancing, to examine various factors associated with (1) complete home-based telework (HBT), (2) the perception of HBT, and (3) the attitude toward the combination between HBT and conventional work at workplace post-COVID-19. It finds that the company's closure policy and the frequency of working from a distance before the social distancing period were the primary determinants of exclusively teleworking.

pn-Heterojunction of the SWCNT/ZnO nanocomposite for temperature dependent reaction with hydrogen.

A hydrogen breath test is a non-invasive and safe diagnostic tool to explore the functional gastrointestinal disorders. For the diagnosis of small intestinal bacterial overgrowth syndrome as well as carbohydrate malabsorption such as fructose, lactose, and sorbitol malabsorption, a hydrogen breath test is considered one of the gold criterions. Since the more sensitive hydrogen sensor enables the more accurate prediction about the disease, many efforts have been to the development of the high performance H sensor.

Asymmetric Reductive and Alkynylative Heck Bicyclization of Enynes to Access Conformationally Restricted Aza[3.1.0]bicycles.

Conformationally restricted azabicycles are becoming increasingly important in medicinal research. Asymmetric Heck bicyclization of enynes proceeds to give medicinally useful aza[3.1.