Platelet-rich fibrin as an apical barrier for MTA placement in the treatment of teeth with open apices: a pilot study.

OBJECTIVE: The aim of the present pilot study was to assess the effectiveness of the platelet-rich fibrin (PRF) apical barrier for the placement of MTA for the treatment of teeth with periapical lesions and open apices. METHODS: A total of thirty teeth on twenty-eight patients with open apices and periapical periodontitis were enrolled and divided into two groups in the present pilot study. In the PRF group (fourteen teeth in thirteen patients), nonsurgical endodontic treatment was performed using PRF as an apical matrix, after which the apical plug of the MTA was created. For the non-PRF group (fourteen teeth in fourteen patients), nonsurgical endodontic therapy was performed using only the MTA for an apical plug with no further periapical intervention. Clinical findings and periapical digital radiographs were used for evaluating the healing progress after periodic follow-ups of 1, 3, 6, and 9 months. The horizontal dimension of the periapical lesion was gauged, and the changes in the dimensions were recorded each time. The Friedman test, Dunn-Bonferroni post hoc correction, and Mann-Whitney U test were used for statistical analysis, with P < 0.05 serving as the threshold for determining statistical significance. RESULTS: All patients in both groups in the present pilot study had no clinical symptoms after 1 month, with a significant reduction in the periapical lesion after periodic appointments. The lesion width of the PRF group was significantly smaller than that of the non-PRF group in the sixth and ninth month after treatment. CONCLUSIONS: PRF is a promising apical barrier matrix when combined with MTA for the treatment of teeth with open apices and periapical periodontitis. Small number of study subjects and the short time of follow-up period limit the generalizability of these results. TRIAL REGISTRATION: TCTR, TCTR20221109006. Registered 09 November 2022 - Retrospectively registered, https://www.thaiclinicaltrials.org/show/TCTR20221109006 .

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. The proposed approach comprises three main phases: perpendicular constrained wall-plane extraction; coarse registration with plane matching using point-to-point displacement calculation; and fine registration with horizontality constrained iterative closest point (ICP). Experimental results indicate that the proposed method successfully achieved automated registration with an accuracy of 0.044 m and a successful scan rate (SSR) of 100% within a time frame of 424.2 s with 18 sets of scan data acquired from the stop-and-go scanning system in a real-world indoor environment. Furthermore, it surpasses conventional approaches, ensuring reliable registration for point cloud pairs with low overlap in specific indoor environmental conditions.

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 (Nitzschia sp.) as the target objects. In the generally used sample preparation method, the frustule suspension is added dropwise onto a glass substrate or into a glass chamber. While our work confirms good observation of purified frustules using the typical sample preparation method, we also demonstrate a new procedure to observe unseparated structures of frustules prepared by baking them on a mica surface. The baked frustules on the mica surface were transferred to a glass chamber with 1% sodium dodecyl sulfate solution. In this manner, the unseparated structures of the diatom frustules were clearly observed. Furthermore, metal-coated frustules prepared by sputtering onto them on a mica surface were also clearly observed using the same procedure. Our method can be applied for the observation of any target object that is pretreated on a solid surface. We expect our proposed method to be a basis for establishing DHM techniques for microscopic observations of biomaterials.

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., Vietnam). The present study aims to provide an in-depth understanding of ride-sourcing passengers' behavioural intentions when COVID-19 pandemic management successfully prevented community transmission by extending the TPB with two constructs: perceived virus infection risk and problem-focused coping. Using self-administered questionnaires, data were collected from ride-sourcing customers in Ho Chi Minh City (Vietnam). A total of 540 responses were used for validating the proposed theorethical model. The structural equation model results indicate that problem-focused coping is a multi-faceted construct with two dimensions: problem-solving and self-protection. Also, problem-focused coping has the highest total effect on the intention to use ride-sourcing services following a period of COVID-19 suppression (3 months without identified cases). The findings also reveal that attitude partially mediates the link between problem-focused coping and behavioural intention. The results of this study could be used to develop strategies to promote ride-sourcing services in the aftermath of the COVID-19 pandemic.

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. Numerical results show that the method is fast and can be used for large systems. Minimum flow solutions are analyzed using flow decomposition in paths and circuits. Their consistency is also tested by introducing a system of differential equations for the biomasses and examining the stability of the biomass fixed point. The method is illustrated and explained throughout the text on an ecosystem toy model. It is also applied to realistic food models.

The impact of Covid-19 on children's active travel to school in Vietnam.

This is among the first studies to provide empirical evidence on active school travel rates and determinants before and after the first Covid-19 lockdown in spring 2020. We have collected and analyzed primary survey data on the school travel patterns of 472 school-age children in Hanoi, Vietnam. The findings show that the Covid-19 pandemic has been quite detrimental: once schools reopened, the prevalence of active school travel decreased from 53% to less than 31%. Where parents, especially mothers, did not face barriers to motorized travel, they assumed the role of chauffeur. Parents who were more concerned about community infections were more motivated to shift children to motorized modes. Walking was more affected than cycling because it was seen as more likely to lead to physical contact and virus transmission. Active school travel dropped more steeply in urban districts (as opposed to poorer, non-urban districts) and in those areas where home-school distances were the largest. It appears that the most common perceptions around barriers to active school travel have been exacerbated during the pandemic as parents and children adapt to "the new normal".

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[3.1.0] and aza[4.1.0] bicycles with excellent enantioselectivity. The key organopalladium species after bicyclization can be trapped by silanes and terminal alkynes.

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. The research incorporates data from 558 delivery workers in Hanoi and Ho Chi Minh City, Vietnam. The study utilizes two analytical methods to empirically test the hypotheses, considering non-linear relationships between variables: Partial Least Square Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN). The results reveal mixed impacts of factors connected to job resources. Although social support appears to deter MPUWR, work autonomy and rewards seemingly encourage it. Furthermore, a predisposition towards risk-taking behaviour significantly impacts the frequency of mobile phone usage among delivery riders. Interestingly, riders with higher incomes and those who have previously been fined by the police exhibit more frequent mobile phone use. The findings of this study present valuable insights into the crucial factors to be addressed when designing interventions aimed at reducing phone use among food delivery riders.

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. Nor was it clear whether they planned on retuning. Through a survey of more than 800 students in seven higher education institutions, this study aimed to find the answers to these questions. The study revealed that bus ridership was determined by socio-demographic variables (year of studies, household income, employment status, motorcycle ownership), environmental variables (home-university distance), and psychological variables (convenience, bus staff behaviour, risk of sexual harassment, reliability and health, image and status). A negative disruptor such as the fear of Covid-19 infection had little effect on the decision to continue riding buses. Meanwhile, the prospect of riding 'clean and green' electric buses, which were introduced in a pilot program, was a positive disruptor that may lead a portion of students to return to public transport.

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. METHODS: The self-reported data of 393 online food delivery riders were collected in Hanoi and Hochiminh city, Vietnam. Binary logit regression was used to investigate the factors associated with non-fatal crashes. RESULTS: The findings showed that more than half of riders (54%) reported being involved in at least one crash in the last 12 months. The most common risky riding behaviors associated with the crashes included using a mobile phone while riding, neglecting turn signals, red-light running, riding when tired/sleepy, and speeding. The riders who were national migrants, married, and worked on planned delivery routes mainly alone were more likely to experience crashes. At the same time, adequate perceived rewards for their work prevent crash involvement. Perceived risk was not a significant predictor of self-reported crashes. CONCLUSIONS: Ensuring road safety for delivery riders requires a systemic effort involving multiple stakeholders, and the private sector plays a crucial role in discouraging risky riding behaviors. It is imperative for the government and regulatory bodies to redefine the delivery job to alleviate the strain on riders and provide resources such as rewards. Specifically, riders should be considered employees rather than partners. Furthermore, it is crucial for the police to take a more active role in preventing dangerous behaviors among delivery riders, such as running red lights. At the same time, supporting financial strategies should be implemented for delivery riders, particularly for those who are migrants or married and may face additional challenges.

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. Female riders, migrants, persons living with chronic diseases, and those who had seen their income decimated during the pandemic were more likely to want to quit their job. But if a mass of delivery drivers or riders had failed to show up for work, the last-mile delivery sector would have become paralysed, leaving individuals in various states of lockdown or isolation without food and supplies. As the sector is poised to retain its importance in the post-pandemic period, we recommend a number of approaches for both private companies and public policy makers to persuade riders to stay in their jobs. First and foremost, strategies to prevent and mitigate job burnout should be formulated.

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. Compared to absorption-derived parameters, commonly used fluorescence indices such as the fluorescence index (FI), humification index (HIX), biological index (BIX), and protein-like component improved the prediction accuracy. However, the prediction accuracy was decreased when all optical indices were considered for computation due to increased noise and uncertainty in the models. With the exception of chemical oxygen demand (COD), this study successfully replaced biochemical oxygen demand (BOD), dissolved organic carbon (DOC), and nutrients with selected fluorescence indices, demonstrating relatively analogous performance in either training or testing data, with consistent and good coefficient of determination (R2) values of approximately 0.85 and 0.74, respectively. Among all models considered, ensemble learning models consistently outperformed conventional regression models and artificial neural networks (ANNs). However, there was a trade-off between accuracy and computation efficiency among the ensemble learning models (i.e., Stacking and XGBoost) for algal bloom prediction. Our study offers a glimpse of the potential application of spectroscopic measures to improve accuracy and efficiency in algal bloom prediction, but further work should be carried out in other water bodies to further validate our proposed hypothesis.

Phytochemistry, Pharmacology and Mode of Action of the Anti-Bacterial Artemisia Plants.

Over 70,000 people die of bacterial infections worldwide annually. Antibiotics have been liberally used to treat these diseases and, consequently, antibiotic resistance and drug ineffectiveness has been generated. In this environment, new anti-bacterial compounds are being urgently sought. Around 500 Artemisia species have been identified worldwide. Most species of this genus are aromatic and have multiple functions. Research into the Artemisia plants has expanded rapidly in recent years. Herein, we aim to update and summarize recent information about the phytochemistry, pharmacology and toxicology of the Artemisia plants. A literature search of articles published between 2003 to 2022 in PubMed, Google Scholar, Web of Science databases, and KNApSAcK metabolomics databases revealed that 20 Artemisia species and 75 compounds have been documented to possess anti-bacterial functions and multiple modes of action. We focus and discuss the progress in understanding the chemistry (structure and plant species source), anti-bacterial activities, and possible mechanisms of these phytochemicals. Mechanistic studies show that terpenoids, flavonoids, coumarins and others (miscellaneous group) were able to destroy cell walls and membranes in bacteria and interfere with DNA, proteins, enzymes and so on in bacteria. An overview of new anti-bacterial strategies using plant compounds and extracts is also provided.

A Novel Phytogenic Formulation, EUBIO-BPSG, as a Promising One Health Approach to Replace Antibiotics and Promote Reproduction Performance in Laying Hens.

Gut microbiota play a key role in health maintenance and disease pathogenesis in animals. Dietary phytochemicals are crucial factors shaping gut bacteria. Here, we investigated the function and mechanism of a phytogenic formulation, EUBIO-BPSG (BP), in laying hens. We found that BP dose-dependently improved health and egg production in 54-week-old hens. Furthermore, BP was correlated with increased fecal Lactobacillus, decreased Escherichia coli and Salmonella enterica, and reduced antibiotic resistance (AR) and antibiotic resistance genes (ARG) in chicken stools. The 16S rDNA data showed that BP increased seven genera of probiotics and reduced 13 genera of pathogens in chicken feces. In vitro co-culture experiments showed that BP at 4 µg/mL and above promoted growth of L. reuteri while large 100- and 200-fold higher doses suppressed growth of E. coli and S. enterica, respectively. Mechanistic studies indicated that L. reuteri and its supernatants antagonized growth of E. coli and S. enterica but not vice-versa. Five short-chain fatty acids and derivatives (SCFA) produced from L. reuteri directly killed both pathogens via membrane destruction. Furthermore, BP inhibited conjugation and recombination of ARG via interference with conjugation machinery and integrase activity in E. coli. Collectively, this work suggests that BP promotes host health and reproductive performance in laying hens through regulation of gut microbiota through increasing probiotics and decreasing pathogens and spreading ARG.

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. RESULTS: Recreational cycling has become much more popular in Hanoi during the Covid-19 pandemic, with early morning being the preferred time for this activity (to avoid heavy traffic). A quarter of the participants had starting cycling recreationally since the first lockdown in April 2020, and about three quarters reported having noticed an increase in cycling activity around them. Nearly half of the participants cycled regularly (more than four times per week). The groups that were most likely to have taken up cycling for recreations during the pandemic included men, those living with children in the home, and those not working or studying. Age and income were not significant. People have been embracing cycling as a way to maintain or increase physical activity levels, and to safely socialize at the time when social gatherings are limited, walking is prohibited in some zones, and social distancing rules apply everywhere. CONCLUSION: To sustain the growth in recreational cycling and widen the time-window for this activity while ensuring everyone's safety, Hanoi's planning and public health sectors should join forces to adopt a combination of 'hard' and 'soft' measures. The authors recommend creating multi-use paths for micromobility modes, launching a public bikesharing scheme, regulating motorised modes, and social marketing that promotes recreational cycling as trendy.

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. This work proposes a novel deep learning-based Q-H prediction model that overcomes all the shortcomings encountered by existing approaches. Specifically, to address data scarcity and increase prediction accuracy, we design an ensemble learning architecture that takes advantage of multiple deep learning techniques. Furthermore, we leverage the Singular-Spectrum Analysis (SSA) to remove noise and outliers from the original data. Besides, we exploit the Genetic Algorithm (GA) to propose a novel mechanism that can automatically determine the prediction model's optimal hyper-parameters. We conducted extensive experiments on two datasets collected from Vietnam's Red and Dakbla rivers. The results show that our proposed solution outperforms current techniques across a wide range of metrics, including NSE, MSE, MAE, and MAPE. Specifically, by exploiting the ensemble learning technique, we can improve the NSE by at least [Formula: see text]. Moreover, with the aid of the SSA-based data preprocessing technique, the NSE is further enhanced by more than [Formula: see text]. Finally, thanks to GA-based optimization, our proposed model increases the NSE by at least [Formula: see text] and up to [Formula: see text] in the best case.

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. In this study, we attached DNA-wrapped SWNTs (DNA-SWNTs) to frustule (micron-sized nanoporous biosilica) surfaces, which were purified from cultured isolated diatoms. After the injection of an oxidant and a reductant, the SWNTs on the frustules showed prominent PL responses. This suggests that the biodevice functions as a micron-sized redox sensor. Frustules can be easily suspended in aqueous solutions because of their porous structures and can easily be collected as pellets by low-speed centrifugation. Thus, the removal of unbound SWNTs and the recovery of the fabricated DNA-SWNT frustules for reuse were achieved by gentle centrifugation. Our proposal for micron-sized SWNT biodevices would be helpful for various biological applications.

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. Following descriptive statistics, four logit models were fitted to examine the factors associated with (a) sanitizing one's hands, (b) using a face shield, (c) contracting a new health issue, and (d) engaging in riskier traffic behaviors during the lockdown. RESULTS: The riders who were less consistent in adopting health and safety measures tended to be male, older, less-educated, and vaccinated. Also, they were under greater financial pressure and had suffered a larger loss of income during the pandemic. To recover the loss, they worked longer hours and felt under more intense pressure at work. The job pressure, long working hours, and financial burdens led many drivers to adopt risky traffic behaviors, such as speeding. Conversely, where the companies and co-workers were more supportive, riders tended to adopt health prevention measures more often. Fear of Covid-19 also acted as a facilitator. Job and financial pressure combined with the fear of contracting the virus contributed to the occurrence of new heath issues during the pandemic. Again, support from the company and co-workers helped to reduce the risk of new health problems emerging. CONCLUSION: In Ho Chi Minh City and other Global South megacities that employ tens of thousands of riders, ensuring their health and safety is important to support both private businesses and public health. Overall, companies should assume a much larger responsibility here.

Mapping for Engagement: Setting up a Community Based Participatory Research Project to Reach Underserved Communities at Risk for Hepatitis C in Ho Chi Minh City, Vietnam.

BACKGROUND: Approximately 1. 07 million people in Vietnam are infected with hepatitis C virus (HCV). To address this epidemic, the South East Asian Research Collaborative in Hepatitis (SEARCH) launched a 600-patient cohort study and two clinical trials, both investigating shortened treatment strategies for chronic HCV infection with direct-acting antiviral drugs. We conducted ethnographic research with a subset of trial participants and found that the majority were aware of HCV infection and its implications and were motivated to seek treatment. However, people who inject drugs (PWID), and other groups at risk for HCV were under-represented, although injecting drug use is associated with high rates of HCV. MATERIAL AND METHODS: We designed a community-based participatory research (CBPR) study to engage in dialogues surrounding HCV and other community-prioritized health issues with underserved groups at risk for HCV in Ho Chi Minh City. The project consists of three phases: situation analysis, CBPR implementation, and dissemination. In this paper, we describe the results of the first phase (i.e., the situation analysis) in which we conducted desk research and organized stakeholder mapping meetings with representatives from local non-government and community-based organizations where we used participatory research methods to identify and analyze key stakeholders working with underserved populations. RESULTS: Twenty six institutions or groups working with the key underserved populations were identified. Insights about the challenges and dynamics of underserved communities were also gathered. Two working groups made up of representatives from the NGO and CBO level were formed. DISCUSSION: Using the information provided by local key stakeholders to shape the project has helped us to build solid relationships, give the groups a sense of ownership from the early stages, and made the project more context specific. These steps are not only important preliminary steps for participatory studies but also for other research that takes place within the communities.

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. Regarding the perception of HBT, while the fear of COVID-19 was a strong positive factor, difficulties in focusing on work and accessing data were negative factors. Regarding the attitude toward the future development of HBT, attitudinal factors, commute distance, gender, children in household, and the perception of HBT in the social distancing period were the main predictors. The presence of more than one child negatively affected the perception of telework but positively affected the attitude toward establishing the hybrid work mechanism. The findings suggested that HBT has the potential to alleviate traffic congestion in developing countries and it can be promoted by emphasizing its environment-related benefits. The sample used in this research was collected in the initial stage of constrained mobility and it was not well representative; therefore, this study serves as a proof of concept for ongoing wider analyses on HBT post-COVID-19 or in the subsequent lockdown periods.