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Abstract Whether the future of transportation is going to be electric or not is no longer a question. Electric vehicles (EVs) offer several benefits toward global sustainability. However, without a variety of charging infrastructures that cover diverse forthcoming charging needs, the speed of vehicle electrification may be slow and limited. In this study, we investigate the synergistic benefits of traditional charging stations and an emerging alternative, i.e., wireless dynamic charging roads, focusing on their impact on the daily commute of EV users. We center our evaluation on quantifiable metrics, chiefly time and convenience, and deploy computer simulations utilizing authentic transportation datasets from New York City, USA. Our findings underscore that integrating both charging stations and charging roads can substantially alleviate detours for EV users and remarkably reduce additional charging time. Our research provides evidence to encourage researchers, EV manufacturers, urban infrastructure planners, and policymakers to explore future charging infrastructures for EVs, with a notable emphasis on wireless dynamic charging roads.

Background Transcatheter renal denervation (RDN) has had inconsistent efficacy and concerns for durability of denervation. We aimed to investigate long‐term safety and efficacy of transcatheter microwave RDN in vivo in normotensive sheep in comparison to conventional radiofrequency ablation. Methods and Results Sheep underwent bilateral RDN, receiving 1 to 2 microwave ablations (maximum power of 80–120 W for 240 s–480 s) and 12 to 16 radiofrequency ablations (180 s–240 s) in the main renal artery in a paired fashion, alternating the side of treatment, euthanized at 2 weeks (acute N=15) or 5.5 months (chronic N=15), and compared with undenervated controls (N=4). Microwave RDN produced substantial circumferential perivascular injury compared with radiofrequency at both 2 weeks [area 239.8 (interquartile range [IQR] 152.0–343.4) mm2 versus 50.1 (IQR, 32.0–74.6) mm2, P

AbstractThis paper examines the impact of various corporate governance characteristics on the disclosure of corporate social responsibility (CSR) information in the context of developing markets during the COVID-19 pandemic. We used data from the annual reports of the top 100 companies listed on the Ho Chi Minh Stock Exchange from 2019 to 2021 to investigate the relationship between board independence, board size, CEO duality, foreign ownership, government ownership, and the disclosure level of CSR reporting. We employed a content analysis to measure CSR disclosure level by using the CSR reporting index (CSRRI) with 17 items. The panel regressions including three techniques like the pooled-ordinary least squares (OLS), fixed effects model (FEM), and random effects model (REM), were used to analyze the data, and FEM) shows its best fit to the model. The results suggest that board independence and government ownership correlate positively and significantly with companies’ decisions to disclose CSR information. In contrast, board size, CEO duality, foreign ownership and was found to be insignificant. Our study extends the literature on CSR particularly in developing countries where governments play a significant role in promoting economic development. It also evaluates the CSR disclosure level of the top listed companies in Vietnam. Since then, the paper’s results provide several insights to the policymakers to identify the corporate governance characteristics that will promote CSR reporting in Vietnam’s listed companies.

BackgroundChagas disease, chronic infection with Trypanosoma cruzi, mainly manifests as cardiac disease. However, the liver is important for both controlling parasite burdens and metabolizing drugs. Notably, high doses of anti-parasitic drug benznidazole (BNZ) causes liver damage. We previously showed that combining low dose BNZ with a prototype therapeutic vaccine is a dose sparing strategy that effectively reduced T. cruzi induced cardiac damage. However, the impact of this treatment on liver health is unknown. Therefore, we evaluated several markers of liver health after treatment with low dose BNZ plus the vaccine therapy in comparison to a curative dose of BNZ.MethodologyFemale BALB/c mice were infected with a bioluminescent T. cruzi H1 clone for approximately 70 days, then randomly divided into groups of 15 mice each. Mice were treated with a 25mg/kg BNZ, 25μg Tc24-C4 protein/ 5μg E6020-SE (Vaccine), 25mg/kg BNZ followed by vaccine, or 100mg/kg BNZ (curative dose). At study endpoints we evaluated hepatomegaly, parasite burden by quantitative PCR, cellular infiltration by histology, and expression of B-cell translocation gene 2(BTG2) and Peroxisome proliferator-activated receptor alpha (PPARα) by RT-PCR. Levels of alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) were quantified from serum.ResultsCurative BNZ treatment significantly reduced hepatomegaly, liver parasite burdens, and the quantity of cellular infiltrate, but significantly elevated serum levels of ALT, AST, and LDH. Low BNZ plus vaccine did not significantly affect hepatomegaly, parasite burdens or the quantity of cellular infiltrate, but only elevated ALT and AST. Low dose BNZ significantly decreased expression of both BTG2 and PPARα, and curative BNZ reduced expression of BTG2 while low BNZ plus vaccine had no impact.ConclusionsThese data confirm toxicity associated with curative doses of BNZ and suggest that while dose sparing low BNZ plus vaccine treatment does not reduce parasite burdens, it better preserves liver health.

Tuberculosis is one of the most common infectious diseases in the world, caused by Mycobacterium tuberculosis. The outbreak of multiple drug-resistant tuberculosis has become a major challenge to prevent this disease worldwide. ClpC1 is a Clp ATPase protein of Mycobacterium tuberculosis, functioning as a chaperon when combined with the Clp complex. ClpC1 has emerged as a new target to discover anti-tuberculosis drugs. This study aimed to explore the ClpC1 inhibitors from actinomycetes, which have been known to provide abundant sources of antibiotics. Two cyclic peptides, including nocardamin (1), halolitoralin A (3), and a lactone pleurone (2), were isolated from the culture of Streptomyces aureus (VTCC43181). The structures of these compounds were determined based on the detailed analysis of their spectral data and comparison with references. This is the first time these compounds have been isolated from S. aureus. Compounds 1–3 were evaluated for their affection of ATPase activity of the recombinant ClpC1 protein. Of these compounds, halolitoralin A (1), a macrocyclic peptide, was effective for the ATPase hydrolysis of the ClpC1 protein.

Early detection of skin cancer matters because diagnosis, prognosis and treatment plan differ for each skin cancer type at their stages. Medical imaging taking the advantages of the non-invasive and non-ionizing polarized light is emerging as a tool for the development of screening and diagnotic tests. In this work, we proposed a novel framework to classify human melanoma and nonmelanoma skin cancer using the Classification and Regression T ree algorithm (CART). The samples were prepared from twenty-four non-melanoma skin cancer samples (consisting of twelve squamous cell carcinoma and twelve basal cell carcinoma samples); and three melanoma skin cancer samples. We calculated ten optical parameters from anisotropic biological tissues, namely the LB orientation angle (α), the LB phase retardance (β), the CB optical rotation angle (γ), the LD orientation angle (θd), the linear dichroism (D), the circular dichroism (R), the degrees of linear depolarization (e1 and e2), the degree of circular depolarization (e3), and the depolarization index (∆) using Stokes-Mueller matrix formalism. All effective optical parameters of biological tissue were then input into the CART classifier as predictors. The model yielded an accuracy of 92.6%, which is desirable for any robust and interpretable classification model. The results showed that for biological tissue samples, linear polarization properties dominate over circular ones due to the cellular microstructural composition of tissue, especially under anomalous growth as seen in skin cancer. This novel framework can potentially assist physicians in making timely and well-informed medical decisions.

The monitoring of ecosystem dynamics utilises time and resources from scientists and land-use managers, especially in wetland ecosystems in islands that have been affected significantly by both the current state of oceans and human-made activities. Deep-learning models for natural and anthropogenic ecosystem type classification, based on remote sensing data, have become a tool to potentially replace manual image interpretation. This study proposes a U-Net model to develop a deep learning model for classifying 10 island ecosystems with cloud- and shadow-based data using Sentinel-2, ALOS and NOAA remote sensing data. We tested and compared different optimiser methods with two benchmark methods, including support vector machines and random forests. In total, 48 U-Net models were trained and compared. The U-Net model with the Adadelta optimiser and 64 filters showed the best result, because it could classify all island ecosystems with 93 percent accuracy and a loss function value of 0.17. The model was used to classify and successfully manage ecosystems on a particular island in Vietnam. Compared to island ecosystems, it is not easy to detect coral reefs due to seasonal ocean currents. However, the trained deep-learning models proved to have high performances compared to the two traditional methods. The best U-Net model, which needs about two minutes to create a new classification, could become a suitable tool for island research and management in the future.

Analyzing the dry ports’ impacts on different stakeholders is imperative for assessing the feasibility of a dry port project and promoting the collaboration among such parties to optimize the supply chain between inland customers and seaports. This paper aims at developing a conceptual framework to evaluate the role of dry ports from multi-criteria and multi-stakeholder approaches. Based on an extensive literature review, a hierarchy of evaluation criteria was developed from the perspectives of three main stakeholder groups, i.e. dry port users, seaport-based players and community. Interviews were then carried out to verify the face validity of the initially proposed framework given the context of Vietnam, followed by a survey assessing the dry port’s contributions. The findings highlight the major role of dry port users in driving the success of a dry port, while also recognizes significant roles of seaport-based players and the community. The study provides insights into how different stakeholder groups might value the contribution of dry ports and demonstrates that dry port characteristics have apparent impacts on their role as perceived by each group. Finally, this research points out the current issues of the Vietnamese dry port system and provides recommendations and managerial implications accordingly.

In this study, the energy storage properties of relaxor Pb0.92La0.08(Zr0.52Ti0.48)O3 (PLZT) thin films grown on Pt/ Si substrates using pulsed laser deposition (PLD) and sol-gel methods were investigated. The PLZT thin films deposited by PLD possessed a columnar growth microstructure and mixed orientations of (100) and (110) while a dense microstructure and preferred orientation of (100) were achieved by sol-gel deposition. Although the electric breakdown strength (EBD) of the sol-gel-deposited PLZT thin films (EBD=2200 kV/cm) was slightly higher than that of the films deposited using PLD (EBD=2100 kV/cm), the PLD-deposited PLZT thin films had a larger recoverable energy storage density (Ureco) and energy storage efficiency (η), which can be explained by its slimmer polarization loop, higher maximum polarization, and lower remanent polarization. At corresponding E BD values, the Ureco and η values were 33.2 J/cm3 and 67.5% for the PLD-deposited films and 27.5 J/cm3 and 62.2% for the sol-gel-deposited films. Although the sol-gel-deposited PLZT thin films had lower energy storage performance, the sol-gel method remains a promising method for the fabrication of thin films for dielectric energy storage applications due to its unique advantages of low fabrication cost, simple preparation process, and easy control of chemical composition.

With the increasing demand for greener and more energy efficient transportation solutions, electric vehicles (EVs) have emerged to be the future of transportation across the globe. However, currently, one of the biggest bottlenecks of EVs is the battery. Small batteries limit the EVs driving range, while big batteries are expensive and not environmentally friendly. One potential solution to this challenge is the deployment of charging roads, i.e., dynamic wireless charging systems installed under the roads that enable EVs to be charged while driving. In this paper, we use tools from stochastic geometry to establish a framework that enables evaluating the performance of charging roads deployment in metropolitan cities. We first present the course of actions that a driver should take when driving from a random source to a random destination in order to maximize dynamic charging during the trip. Next, we analyze the distribution of the distance to the nearest charging road. This distribution is vital for studying multiple performance metrics such as the trip efficiency, which we define as the fraction of the total trip spent on charging roads. Next, we derive the probability that a given trip passes through at least one charging road. The derived probability distributions can be used to assist urban planners and policy makers in designing the deployment plans of dynamic wireless charging systems. In addition, they can also be used by drivers and automobile manufacturers in choosing the best driving routes given the road conditions and level of energy of EV battery.

We report the karyotype, some aspects of spermatogenesis, and ovarian trophocytes ploidy in three aquatic bug species: Ilyocoris cimicoides (Linnaeus, 1758), Notonecta glauca Linnaeus, 1758, and Diplonychus rusticus Fabricius, 1871 from previously unexplored regions – South Europe (Bulgaria) and Southeast Asia (Vietnam). Our results add considerable support for the published karyotype data for these species. In I. cimicoides, we observed achiasmate male meiosis – the first report of achiasmy for the family Naucoridae. More comprehensive cytogenetic studies in other species of the Naucoridae are required to elucidate the role of achiasmy as a character in the systematics of the family. Our observations on the association between phases of spermatogenesis and developmental stages in I. cimicoides and N. glauca differ from the previously published data. In these species, we assume that the spermatogenesis phases are not strongly associated with certain developmental stages. For further cytogenetic studies (on the Balkan Peninsula), we recommend July as the most appropriate month for collection of I. cimicoides and N. glauca. In the ovaries of both species, we studied the level of ploidy in metaphase and interphase trophocytes. In I. cimicoides, diploid and tetraploid metaphase trophocytes were found. Heteropycnotic elements, observed in interphase trophocytes of this species, represented the X chromosomes. It allowed us to determine the trophocytes ploidy at interphase (2n was repeated up to 16 times). The situation with N. glauca was different. The metaphase trophocytes were diploid and we were not able to determine the ploidy of interphase trophocytes since such conspicuous heteropycnotic elements were not found. The scarce data available suggest a tendency for a low level of trophocyte ploidy in the basal infraorders (Nepomorpha and Gerromorpha) and for a high level in the more advanced Pentatomomorpha. Data about this character in species from other infraorders are needed to confirm that tendency.

While collaborative filtering (CF) is the most popular approach for recommendation systems, it only makes use of the ratings given to items by users and neglects side information about user attributes or item features. In this work, a natural language processing (NLP) technique is applied to generate a more consistent version of Tag Genome, a side information which is associated with each movie in the MovieLens 20M dataset. Subsequently, we propose a 3-layer autoencoder to create a more compact representation of these tags which improves the performance of the system both in accuracy and in computational complexity. Finally, the proposed representation and the well-known matrix factorization techniques are combined into a unified framework that outperforms the state-of-the-art models by at least 2.87% and 3.36% in terms of RMSE and MAE, respectively.

Abstract Aims Dozens of causative genes and their mechanisms of nonsyndromic cleft lip with or without cleft palate (NSCL/P) were revealed through genome‐wide association and linkage studies. Results were, however, not always replicated in different populations or methodologies. This study used case–control and family based approaches to investigate the etiology of NSCL/P and its two subtypes: nonsyndromic cleft lip only (NSCLO) and nonsyndromic cleft lip and palate (NSCLP) among the Vietnamese population. Methods Two hundred and seventeen NSCL/P case‐parent trios (one affected child and two parents), including 105 NSCLO and 112 NSCLP were involved for a family based design; and 273 ethnic and region‐matched healthy controls with no cleft history in their families were recruited for a case–control design. Three SNPs consisting of TFAP2A (rs1675414 and rs303048) and 8q24 (rs987525) were genotyped using the TaqMan SNP genotyping assay. Results TFAP2A rs1675414 was associated with NSCLO, replicated by both case‐control and family based tests. Other SNPs yielded no evidence of susceptibility to NSCL/P or two subtypes. Conclusion The current investigation suggests an intriguing role of TFAP2A in the etiology of NSCLO among the Vietnamese population.

Amentotaxus argotaenia (Hance) Pilg. is a threatened conifer with a wide distribution range from North to Central Vietnam due to habitat loss and over-exploitation. To provide information for its conservation and sustainable management, in the present study, genetic diversity and population genetic structure for 200 trees from eight populations, representing the natural distribution range of this species were estimated using nuclear microsatellites. The results showed a moderate genetic diversity of A. argotaenia (HO = 0.331, HE = 0.358). Significant heterozygosity deficits were detected in three populations in the Northeast area. Genetic differentiation was low in the same distribution area and high in different areas. However, the gene flow among the studied populations was relatively high (Nm = 1.17). Habitat fragmentation, geographical distance and high mountain range can be the major factors that reduce gene exchange between different areas. Various clustering analyses distinguished three major genetic groups related to the three distribution areas of this species in Vietnam. Based on the study results, we propose that some populations could be prioritized for in situ conservation due to their high genetic diversity with high allelic richness or private alleles, meanwhile other populations should be collected for ex situ conservation as genetic resources in the future.

A mobile-phone-based diagnostic tool, which most of the population can easily access, could be a game changer in increasing the number of examinations of people with dental caries. This study aimed to apply a deep learning algorithm in diagnosing the stages of smooth surface caries via smartphone images. Materials and methods: A training dataset consisting of 1902 photos of the smooth surface of teeth taken with an iPhone 7 from 695 people was used. Four deep learning models, consisting of Faster Region-Based Convolutional Neural Networks (Faster R-CNNs), You Only Look Once version 3 (YOLOv3), RetinaNet, and Single-Shot Multi-Box Detector (SSD), were tested to detect initial caries lesions and cavities. The reference standard was the diagnosis of a dentist based on image examination according to the International Caries Classification and Management System (ICCMS) classification. Results: For cavitated caries, YOLOv3 and Faster R-CNN showed the highest sensitivity among the four tested models, at 87.4% and 71.4%, respectively. The sensitivity levels of these two models were only 36.9 % and 26% for visually non-cavitated (VNC). The specificity of the four models reached above 86% for cavitated caries and above 71% for VNC. Conclusion: The clinical application of YOLOv3 and Faster R-CNN models for diagnosing dental caries via smartphone images was promising. The current study provides a preliminary insight into the potential translation of AI from the laboratory to clinical practice.

Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital transformation is structured, which makes it difficult to utilize the advantages of CNN. This paper introduces a novel autoencoder, named Half Convolutional Autoencoder, which adopts convolutional layers to discover the high-order correlation between structured features in the form of Tag Genome, the side information associated with each movie in the MovieLens 20 M dataset, in order to generate a robust feature vector. Subsequently, these new movie representations, along with the introduction of users’ characteristics generated via Tag Genome and their past transactions, are applied into well-known matrix factorization models to resolve the initialization problem and enhance the predicting results. This method not only outperforms traditional matrix factorization techniques by at least 5.35% in terms of accuracy but also stabilizes the training process and guarantees faster convergence.

Primary nephrotic syndrome (PNS) is common in children, affecting the soft and hard tissues of the oral cavity. This study aimed to investigate the percentage of dental caries, gingivitis, hypertrophic gingivitis, and developmental defects of enamel (DDE) in children with PNS. The association of PNS with these diseases and oral care behavior was also assessed. A total of 407 children with PNS and 407 age- and gender-matched controls were recruited. PNS was diagnosed based on blood and urinary tests. The Simplified Oral Hygiene Index (OHI-S), the Gingival Index (GI), the Gingival Overgrowth Index (GOI), the Decayed, Missing, and Filled Teeth Index (dmft/DMFT), and DDE were collected. The PNS patients showed significantly higher scores of OHI-S, GI, and dmft, and higher proportions of dental caries and DDE than those of the controls (p < 0.001). It is necessary to establish a periodic dental protocol for PNS patients to improve their oral health status.

Abstract Conventional metamaterial absorbers have multilayer designs, where the dielectric interlayer is sandwiched between a top patterned metallic structure and bottom metallic film. Here, we demonstrate that a highly polarization-sensitive perfect absorber canbe realized by replacing the bottom metallic film with a plasmonic grating. Designs for broadband and narrowband of wavelength are proposed and numerically investigated. The designed absorbers perform high light absorption, which is above 90% over the wavelength range of 0.4–1.4 µm for the broadband absorber and 98% for the absorption peak in case of the narrowband design, with a specific polarization of incident light. We find that the absorption is tunable by changing the polarization. Such absorbers offer new approach for active control of light absorbance with strong impacts for solar energy harvesting, light emitting and sensing.

Osteogenesis imperfecta (OI) is a genetic disorder characterized by increased bone fragility and low bone mass, caused mainly by mutations in collagen type I encoding genes. The current study aimed to evaluate dentinogenesis imperfecta (DI), oral manifestations and caries status of OI children. Sixty-eight children (41 males, 27 females) aged from 3 to 17 years old (mean 9 ± 4.13) participated in the study. Participants were classified into three OI type groups (I—2 cases, III—31 cases and IV—35 cases). Clinical examination and an orthopantomogram were used to obtain prevalences and associations of DI, caries status, malocclusion, crossbite, open bite, eruption, impaction and missing teeth with OI. The prevalence of DI among OI patients was 47.1%, more common in OI type III than type IV. The yellow-brown discoloration type was more vulnerable to attrition than the opalescent-grey one in the primary dentition. OI seemed not to have a high risk of caries; the prevalence of caries was 69.1%. A high incidence of malocclusion, crossbite and open bite was observed. In-depth oral information would provide valuable data for better dental management in OI patients. Parents and general doctors should pay more attention to dental care to prevent caries and premature tooth loss.

Recently, the demand for small grid-connected photovoltaic (PV) systems has been rapidly increasing; this is due to the reduction in the costs of grid-connected storage systems as compared to those of the stand-alone ones. Notably, the performance of the solar tracking system is not only depending on the types but also the region that they are set up and used. To understand how solar tracking systems work globally, we need to know their performance in each country and even the different parts of a country. In this study, two grid-connected PV systems with 250 W solar modules were used to investigate the efficient improvement of a single-axis sun tracking system in Central Vietnam. First, a mechanical tracking device with a linear actuator and a controller was designed and then its performance was comprehensively investigated with a grid-connected PV system. In addition to evaluating the energy gain by the tracking system, this study also considered the energy consumption of the linear actuator with its controller and a small grid-connected PV system; this has generally been omitted in previous works. Experimental results indicate that the total energy consumption of the tracking system was approximately 2−8% of the energy generated by the grid-connected PV system. The maximum overall energy generation was confirmed to have increased by up to 30.3% on a sunny day upon using the proposed tracking system; further, the net energy gain by using the sun tracker was ascertained to be 15.2% in average weather conditions. Based on the success of this work, we will keep experimenting with other parts of Vietnam. Also, we will collaborate with colleagues in other countries to create a guideline for understanding and using the solar tracker regionally and globally.

Vital detection on the basis of Doppler radars has drawn a great deal of attention from researchers because of its high potential for applications in biomedicine, surveillance, and finding people alive under debris during natural hazards. In this research, the signal-to-noise ratio (SNR) of the remote vital-sign detection system is investigated. On the basis of different types of noise, such as phase noise, Gaussian noise, leakage noise between the transmitting and receiving antennae, and so on, the SNR of the system has first been examined. Then the research has focused on the investigation of the detection and false alarm probabilities of the system when the transmission link between the human and the radar sensor system took the Nakagami-m channel model. The analytical model for the false alarm and the detection probabilities of the system have been derived. The proposed theoretical models for the SNR and detection probability match with the simulation and measurement results. These theoretical models have the potential to be used as good references for the hardware development of the vital-sign detection radar sensor system.

A new convolution neural network (CNN) architecture for semantic segmentation of high resolution aerial imagery is proposed in this paper. The proposed architecture follows an hourglass-shaped network (HSN) design being structured into encoding and decoding stages. By taking advantage of recent advances in CNN designs, we use the composed inception module to replace common convolutional layers, providing the network with multi-scale receptive areas with rich context. Additionally, in order to reduce spatial ambiguities in the up-sampling stage, skip connections with residual units are also employed to feed forward encoding-stage information directly to the decoder. Moreover, overlap inference is employed to alleviate boundary effects occurring when high resolution images are inferred from small-sized patches. Finally, we also propose a post-processing method based on weighted belief propagation to visually enhance the classification results. Extensive experiments based on the Vaihingen and Potsdam datasets demonstrate that the proposed architectures outperform three reference state-of-the-art network designs both numerically and visually.