PHÂN TÍCH KHẢ NĂNG ỨNG DỤNG CÔNG NGHỆ BLOCKCHAIN VÀO CHUỖI CUNG ỨNG DẦU TRÀM TẠI HUẾ

On the basis of referenced studies on blockchain technology and the applicability of blockchain in supply chain management of agricultural products, the study analyzes the applicability of blockchain technology in melaleuca oil supply chain in Hue. The study applies both qualitative and quantitative research methods. The results of the qualitative research step help outline a new research framework with 6 groups of aspects to be assessed. Next, the study surveys 215 units/individuals involved in the melaleuca oil supply chain, the sample is selected by simple random method. The obtained results show that the groups of aspects related to readiness (REA), compatibility (COM), cooperatability (COO) and legal environment (LEG) are trickiest obstacles to the applicability of blockchain technology. In addition, the difference test shows that each group of units/individuals in the supply chain has different levels of readiness for the application of new technology.Trên cơ sở tham khảo các nghiên cứu về công nghệ chuỗi khối (blockchain) và khả năng ứng dụng của blockchain trong quản lý chuỗi cung ứng sản phẩm nông nghiệp, nghiên cứu được thực hiện nhằm phân tích khả năng ứng dụng công nghệ blockchain vào chuỗi cung ứng dầu tràm tại Huế. Nghiên cứu áp dụng đồng thời cả hai phương pháp nghiên cứu định tính và định lượng. Kết quả bước nghiên cứu định tính giúp phác thảo nên được khung phân tích mới với 6 nhóm khía cạnh cần đánh giá. Tiếp đến, nghiên cứu khảo sát 215 các đơn vị/cá nhân tham gia vào chuỗi cung ứng dầu tràm, mẫu được chọn theo phương pháp ngẫu nhiên đơn giản. Kết quả thu được chỉ ra rằng: các nhóm khía cạnh liên quan đến điều kiện sẵn có (REA), khả năng tương thích (COM) và môi trường pháp lý (LEG) là những trở ngại lớn nhất cho việc ứng dụng công nghệ blockchain. Ngược lại, khả năng hợp tác (COO), môi trường xã hội (SOC), và môi trường cạnh tranh (CE) là những nền tảng quan trọng thúc đẩy khả năng ứng dụng blockchain. Ngoài ra, kiểm định sự khác biệt cho thấy, mỗi nhóm đơn vị/ cá nhân trong chuỗi cung ứng có mức độ sẵn sàng khác nhau cho việc ứng dụng công nghệ mới

Building a Chatbot System to Analyze Opinions of English Comments

Chatbot research has advanced significantly over the years. Enterprises have been investigating how to improve these tools’ performance, adoption, and implementation to communicate with customers or internal teams through social media. Besides, businesses also want to pay attention to quality reviews from customers via social networks about products available in the market. From there, please select a new method to improve the service quality of their products and then send it to publishing agencies to publish based on the needs and evaluation of society. Although there have been numerous recent studies, not all of them address the issue of opinion evaluation on the chatbot system. The primary goal of this paper’s research is to evaluate human comments in English via the chatbot system. The system’s documents are preprocessed and opinion-matched to provide opinion judgments based on English comments. Based on practical needs and social conditions, this methodology aims to evolve chatbot content based on user inter-actions, allowing for a cyclic and human-supervised process with the following steps to evaluate comments in English. First, we preprocess the input data by collecting social media comments, and then our system parses those comments according to the rating views for each topic covered. Finally, our system will give a rating and comment result for each comment entered into the system. Experiments show that our method can improve accuracy better than the referenced methods by 78.53%

Does the informal economy mitigate poverty and how does it work? : the case of Vietnam

Countries with lower quality institutions or heavier burden of regulation are associated with a larger informal sector. In addition, other studies show that low startup costs are a key determinant in entering the informal economy. The paper investigates the linkage between the informal economy and poverty reduction based on the 2010 Vietnam Household Living Standard Surveys. Among low income households, those with members involved in informal economic activities have a higher per capita income than those with no members in the informal economy, and informal wage workers earn more than informal self-employed workers on average. Meanwhile, among non-poor households an inverse trend is observed

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.Comment: Part of 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 IEEE Xplore submission as part of WACV 202

1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.Comment: MaCVi 2023 was part of WACV 2023. This report (38 pages) discusses the competition as part of MaCV

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

The COVID-19 Pandemic Impact and Responses in Emerging Economies: Evidence from Vietnamese Firms

A nationwide survey of 162,738 firms in Vietnam asked firms to report the impact of the COVID-19 pandemic on the health of the business, coping strategies used, and various firm and situational characteristics. More than 80% of firms reported negative impacts from the pandemic with fewer than 4% reporting positive effects; 63% of the firms adopted at least one coping strategy. The coping strategies were categorized into seven groups as follows: (1) Non-adoption, (2) promoting e-commerce, (3) transforming key products/services, (4) training employees to improve professional qualifications, (5) finding new markets for input materials, (6) finding markets for products outside of the traditional market, (7) producing new products/services according to market demand during the epidemic period, and (8) other strategies. A multinomial logit regression model showed statistically significant associations between a firm’s selected coping strategy and several independent variables, as follows: (1) Firm size, (2) impact of the pandemic on firm health, firm access to inputs, and firm access to domestic markets, (3) decrease in firm revenue, and (4) receipt of government support. However, many businesses have not implemented coping strategies, leading to concerns regarding their resilience to upcoming threats and uncertainties

Effects of ultrafine bubbles on gram-negative bacteria: inhibition or selection?

Ultrafine bubbles exist in all liquids and are naturally stable. As their properties are not entirely known, it is unclear how they impact the surrounding solution and comparable-sized particles within it. It is essential to further investigate the properties of ultrafine bubbles in order to expand their industrial application. In this regard, the effect of ultrafine bubbles on bacterial development is of particular interest. Our current study, using optical density measurements and fluorescence microscopic images has demonstrated that ultrafine gas bubbles impact the morphology and phenotype of Escherichia coli and Pseudomonas aeruginosa. Specifically, Fourier transform infrared spectroscopic measurements indicated a thickening of bacterial membranes in samples exposed to ultrafine bubbles. The study also confirmed that ultrafine bubbles can inhibit bacterial cell growth. This study signifies the role of surface phenomena in bacterial culture, which is crucial in the upstream processes of recombinant DNA technology applications