Behavior or culture? Investigating the use of cryptocurrencies for electronic commerce across the USA and China

Purpose – This paper claims to identify the behavioral and cultural features that push to use, or not, cryptocurrencies for electronic commerce. Indeed, despite the use of cryptocurrencies for electronic commerce spreading worldwide at a fast and growing pace, there are supporters and detractors among their users. The analysis of what distinguish these two groups of users is fundamental for understanding their different intention to use cryptocurrencies for electronic commerce. Design/methodology/approach – A survey has been administered to 2,532 cryptocurrencies’ users across the USA and China, collecting data on their behavioral predispositions and cultural features. Results were then analyzed through structured equation modeling. Findings – Results showed that while attitude, subjective norms, perceived behavioral control and herding behavior have a positive impact on the intention to use cryptocurrencies for electronic commerce, financial literacy has no influence. Cultural dimensions amplified or reduced the discovered relationships and caused different effects: positive for the USA and negative for China when considering illegal attitude and perceived risk. Originality/value – Theory of planned behavior, financial behavior and cultural factors can, all together, represent a useful framework for envisioning the behavior of users in adopting cryptocurrencies for electronic commerce purposes through a test of all its elements. To the best of the authors’ knowledge, this is the first study considering behavior and cultural variables on the intention to use cryptocurrencies for electronic commerce as well as being the largest carried out, in terms of sample, on the cryptocurrency topic.publishedVersio

Gene Family Abundance Visualization based on Feature Selection Combined Deep Learning to Improve Disease Diagnosis

Advancements in machine learning in general and in deep learning in particular have achieved great success in numerous fields. For personalized medicine approaches, frameworks derived from learning algorithms play an important role in supporting scientists to investigate and explore novel data sources such as metagenomic data to develop and examine methodologies to improve human healthcare. Some challenges when processing this data type include its very high dimensionality and the complexity of diseases. Metagenomic data that include gene families often have millions of features. This leads to a further increase of complexity in processing and requires a huge amount of time for computation. In this study, we propose a method combining feature selection using perceptron weight-based filters and synthetic image generation to leverage deep-learning advancements in order to predict various diseases based on gene family abundance data. An experiment was conducted using gene family datasets of five diseases, i.e. liver cirrhosis, obesity, inflammatory bowel diseases, type 2 diabetes, and colorectal cancer. The proposed method provides not only visualization for gene family abundance data but also achieved a promising performance level

Research collaboration between global North and global South assessed in terms of published output: a case study of Australia and Vietnam

Background: Vietnam and Australia have a long-standing history of collaboration in various fields, notably education, science, and technology. However, the results of this partnership remain indeterminate.Objectives: The aim of this study was to examine the current state of research coop-eration between Australia and Vietnam with reference to the following aspects: (1) increase in the number of research publications over time; (2) proportion of open access (OA) publications in total publications; (3) collaboration involving countries other than Australia and Vietnam; (4) funding sources; (5) top institutions; (6) subject areas; and (7) research topics.Methods: Scopus data set was analysed to identify those papers with two or more authors, with at least one author from Australia and at least one from Vietnam.Results: Most (nearly 84%) of research papers arising out of such collaborative research were published between 2014 and 2022 (7020 of the total of 8460 documents), and almost half (49.6%) of those are OA. Besides Australia and Vietnam, the authors of those papers were from other countries as well nor were the agencies that funded the research reported in those papers limited to Australia or Vietnam. Among the countries involved in terms of co-authorship or funding, the United States was the most influential. The institutional collaborations formed three distinct clusters, each with a varying number of members and a different university at the core (Australian in two clusters and Vietnamese in the third). Medicine was the most frequent field of collaborative research, and the most frequent topics were Vietnam, coronavirus disease 2019, and climate change.Conclusions: The findings offer useful insights to policymakers as well as to senior management of academic institutes in Vietnam and Australia. The study also extends our understanding of collaborative research between the Global North and the Global South

Examining the Intention to Invest in Cryptocurrencies: An Extended Application of the Theory of Planned Behavior on Italian Independent Investors

Among investors of cryptocurrencies there are supporters and detractors; this claims for the identification of the behavioral and socio-demographic factors that push to invest (or not) in cryptocurrencies. A survey has been administered to 275 Italian investors. Together with socio-demographic features (gender, income, age, and education), behavioral factors derived from the theory of planned behavior (attitude, subjective norm, and perceived control behavior) and from the financial behavior literature (illegal attitude, herding behavior, perceived risk, perceived benefit, and financial literacy) have been collected and analyzed. While attitude, illegal attitude, subjective norms, perceived behavioral control, herding behavior, and perceived risk have a positive impact on investors' intentions. Socio-demographic factors and financial literacy have no influence on the intention to invest in cryptocurrencies. This is the first study that comprehensively investigates the influence of behavioral and socio-demographic factors on the intention of investors to invest in cryptocurrencies

Anti-inflammatory effect of Piper longum L. fruit methanolic extract on lipopolysaccharide-treated RAW 264.7 murine macrophages

Context: The Piper species was studied several potential properties such as anti-tumor, anti-inflammatory and antioxidant activity. However, the specific anti-inflammatory activity of the extract from the fruits of P. longum L. has not been investigated. Objectives: Our study want to examine the anti-inflammatory effects of P. longum L. fruit methanolic extracts (PLE) on lipopolysachharide (LPS)-stimulated RAW 264.7 murine macrophages to understand the mechanism of this effect. Method: This study examined the chemical profiling of PLE by LC-HRMS analysis and measured the presence of nitric oxide (NO), interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) in the supernatant using the Griess reagent assay and enzyme-linked immunosorbent assay (ELISA), respectively. The mRNA expression of IL-6, TNF-α, cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS) were evaluated by using real-time quantitative polymerase chain reaction (RT-qPCR). Furthermore, the protein expression of COX-2, iNOS and the phosphorylation of MAPK family, c-Jun N-terminal kinase (JNK), p38 in protein level were observed by western blotting. Result: PLE have detected 66 compounds which belong to different classes such as alkaloids, flavonoids, terpenoids, phenolics, lactones, and organic acids inhibited nitric oxide products with the IC50 = 28.5 ± 0.91 μg/mL. Moreover, PLE at 10–100 μg/mL up-regulate HO-1 protein expression from 3 to 10 folds at 3 h. It also downregulated the mRNA and protein expression of iNOS, COX-2, decreased IL-6 and TNF-α secretion by modulating the mitogen-activated protein kinase (MAPK) signaling pathway, specifically by decreasing the phosphorylation of p38 and JNK. Conclusion: These results shown chemical profiling of PLE and demonstrated that PLE exhibits anti-inflammatory effects by regulating the MAPK family and could be a potential candidate for the treatment of inflammatory diseases

PHÁT TRIỂN THỦ CÔNG MỸ NGHỆ TRONG CÁC LÀNG NGHỀ TRUYỀN THỐNG TỈNH THỪA THIÊN HUẾ

The handicrafts in Thua Thien Hue province have a long development history with many priceless heritage masterpieces. However, the production and consumption of these traditional products have faced many challenges since 2020 due to the COVID-19 pandemic impacts. Principal hardships and constraints such as the market's shrinking, the decrease in orders and contracts, the scarcity and high price of raw materials, outdated technology, small-scale production, monotonous and undiversified products, inadequate advertising, and slow digital conversion have resulted in low competitiveness. For the sustainable development of households producing handicraft products, local authorities may need to implement practical solutions and policies such as applying digital technology, supporting capital for producers through preferential credit programs. Furthermore, it is necessary to encourage enterprises to invest and associate to establish complete supply chains from market research, design, input material supply, production, distribution, and consumption. These solutions are decisive for preserving and promoting traditional handicraft products in Thua Thien Hue Province, thereby better meeting consumers' needs and attracting domestic and foreign tourists.Thủ công mỹ nghệ tỉnh Thừa Thiên Huế là nghề thủ công truyền thống có từ lâu đời với nhiều kiệt tác di sản vô giá. Tuy nhiên, năm 2020, do tác động của đại dịch COVID-19, sản xuất và tiêu thụ sản phẩm các nghề này gặp nhiều khó khăn, hạn chế. Những khó khăn chính như thị trường thu hẹp, số lượng đơn hàng, hợp đồng giảm; nguyên liệu ngày càng khan hiếm, giá cao; công nghệ lạc hậu; quy mô sản xuất nhỏ lẻ, sản phẩm đơn điệu, nghèo nàn; tình hình quảng bá, quảng cáo và chuyển đổi số kém, dẫn đến khả năng cạnh tranh thấp. Để phát triển thủ công mỹ nghệ của tỉnh, chính quyền địa phương cần thực hiện những giải pháp, chính sách thiết thực như áp dụng công nghệ số; hỗ trợ vốn, tín dụng ưu đãi; khuyến khích doanh nghiệp đầu tư, liên doanh, liên kết tạo thành chuỗi cung ứng sản phẩm từ nghiên cứu thị trường, thiết kế đến cung cấp nguyên liệu, sản xuất, phân phối và tiêu thụ… góp phần bảo tồn và phát huy nghề thủ công mỹ nghệ Thừa Thiên Huế, đáp ứng ngày càng tốt hơn nhu cầu của người tiêu dùng và thu hút khách du lịch trong và ngoài nước

Locally weighted learning based hybrid intelligence models for groundwater potential mapping and modeling: A case study at Gia Lai province, Vietnam

The groundwater potential map is an important tool for a sustainable water management and land use planning, particularly for agricultural countries like Vietnam. In this article, we proposed new machine learning ensemble techniques namely AdaBoost ensemble (ABLWL), Bagging ensemble (BLWL), Multi Boost ensemble (MBLWL), Rotation Forest ensemble (RFLWL) with Locally Weighted Learning (LWL) algorithm as a base classifier to build the groundwater potential map of Gia Lai province in Vietnam. For this study, eleven conditioning factors (aspect, altitude, curvature, slope, Stream Transport Index (STI), Topographic Wetness Index (TWI), soil, geology, river density, rainfall, land-use) and 134 wells yield data was used to create training (70%) and testing (30%) datasets for the development and validation of the models. Several statistical indices were used namely Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity (SST), Specificity (SPF), Accuracy (ACC), Kappa, and Receiver Operating Characteristics (ROC) curve to validate and compare performance of models. Results show that performance of all the models is good to very good (AUC: 0.75 to 0.829) but the ABLWL model with AUC = 0.89 is the best. All the models applied in this study can support decision-makers to streamline the management of the groundwater and to develop economy not only of specific territories but also in other regions across the world with minor changes of the input parameters

[Metoda wyznaczania parametrów do opracowania metod klasyfikacji danych chmur punktów zbudowanych z obrazów BSP]

Image data from Drones/Unmanned Aerial Vehicles (UAVs) has been studied and used extensively for establishing maps. The process of UAV data provides three main products including (Digital Surface Model) DSM, Point cloud and Ortho-photos, in which point cloud is a valuable data source in building 3D models and topographic surfaces as well. However, processing point cloud separately to achieve secondary products has not been received much attention from researchers. This study determines parameters to develop a method for classifying point cloud data constructed from UAV images. Consequently, A 3D surface of the ground is built by applying a developed algorithm for the point cloud data for an open-pit mine. The temporal or non-ground objects such as trees, houses, vehicles are automatically subtracted from the point cloud by the algorithms. According to this line, it is possible to calculate and analyze the amount of reserves, the exploited volume to evaluate the efficiency for each mine during operation with the support of UAV integrated camera.Dane uzyskane z dronów / bezzałogowych statków powietrznych (BSP) zostały zbadane i powszechnie wykorzystane do opracowania map. Przetwarzanie danych z BSP zapewnia trzy główne produkty, a mianowicie: Model numeryczny powierzchni (MNS), chmurę punktów i ortofotomapy, w których chmura punktów jest cennym źródłem danych przy budowaniu modeli 3D i powierzchni topograficznych. Dotychczas, kwestia przetwarzania chmury punktów osobno w celu uzyskania produktów wtórnych nie wzbudziła większego zainteresowania naukowców. W artykule, przedstawiono wyniki badania nad sposobem wyznaczenia parametrów niezbędnych do opracowania metod klasyfikacji danych chmur punktów zbudowanych z obrazów BSP. W efekcie tego procesu, powstaje trójwymiarowa powierzchnia powierzchni poprzez zastosowanie opracowanego algorytmu dla danych chmury punktów w kopalni odkrywkowej. Na tej podstawie, można służyć do pomiarów inwentaryzacyjnych, bieżącej kontroli zgodności postępu eksploatacji górniczej z planem ruchu zakładu górniczego, prowadzenia pomiarów postępu frontu eksploatacji w złożu oraz frontów, obejmujących proces zdejmowania nadkładu oraz wyeksploatowanego złoża

55 Khoa học Giáo dục Việt Nam

“55 năm khoa học giáo dục Việt Nam - một phân tích từ dữ liệu Scopus ” là cuốn sách được trình bày dưới dạng báo cáo trắc lượng thư mục khoa học về công bố quốc tế trong lĩnh vực khoa học giáo dục của các tác giả và cơ sở nghiên cứu Việt Nam. Dựa trên dữ liệu thu được từ cơ sở Scopus, cuốn sách khắc họa bức tranh tổng thể về số lượng, cộng đồng nghiên cứu, các nguồn tạp chí, mạng lưới hợp tác, các đơn vị nghiên cứu, các chủ đề và lĩnh vực nghiên cứu được công bố trên các tạp chí khoa học uy tín của các nhà khoa học Việt Nam. Cùng với đó, cuốn sách đưa ra những nhận định về xu hướng tương lai của lĩnh vực này và điểm qua những công trình tiêu biểu nhất đánh dấu các bước tiến trong chặng đường phát triển của lĩnh vực

Improvement of Credal Decision Trees Using Ensemble Frameworks for Groundwater Potential Modeling

Groundwater is one of the most important sources of fresh water all over the world, especially in those countries where rainfall is erratic, such as Vietnam. Nowadays, machine learning (ML) models are being used for the assessment of groundwater potential of the region. Credal decision trees (CDT) is one of the ML models which has been used in such studies. In the present study, the performance of the CDT has been improved using various ensemble frameworks such as Bagging, Dagging, Decorate, Multiboost, and Random SubSpace. Based on these methods, five hybrid models, namely BCDT, Dagging-CDT, Decorate-CDT, MBCDT, and RSSCDT, were developed and applied for groundwater potential mapping of DakLak province of Vietnam. Data of 227 groundwater wells of the study area were utilized for the construction and validation of the models. Twelve groundwater potential conditioning factors, namely rainfall, slope, elevation, river density, Sediment Transport Index (STI), curvature, flow direction, aspect, soil, land use, Topographic Wetness Index (TWI), and geology, were considered for the model studies. Various statistical measures, including area under receiver operating characteristic (AUC) curve, were applied to validate and compare the performance of the models. The results show that performance of the hybrid CDT ensemble models MBCDT (AUC = 0.770), BCDT (AUC = 0.731), Dagging-CDT (AUC = 0.763), Decorate-CDT (AUC = 0.750), and RSSCDT (AUC = 0.766) improved significantly in comparison to the single CDT (AUC = 0.722) model. Therefore, these developed hybrid models can be applied for better ground water potential mapping and groundwater resources management of the study area as well as other regions of the world.Validerad;2020;Nivå 2;2020-04-23 (johcin)</p