KẾT QUẢ BƯỚC ĐẦU NGHIÊN CỨU KHU HỆ CÁ CỬA SÔNG THU BỒN, TỈNH QUANG NAM

This report presents the result of four surveys in 2013 at 12 sampling stations on fish composition of fish fauna in the Thu Bon estuary of Quang Nam province (the central Vietnam) and a total of 139 species of fishes were identified belonging to 110 genera, 63 families and 17 orders. Analysis of community structure of fish fauna showed that the order Perciformes was the most popular, making up 56.1%; Cypriniformes (8.6%); Pleuronectiformes (6.5%); Clupeiformes and Siluriformes (4.3%); Anguilliformes, Tetraodontiformes (3.6%); Mugiliformes (2.9%); ... The family Gobiidae was the most abundant with 12 species, making up 8.6% of the total number of species; Cyprinidae (10 species, 7.2%); Leiognathidae, Carangidae had the same number of species (6 species, 4.3%); Clupeidae, Lutjanidae: 5 species (3.6%); Serranidae, Mugilidae, Soleidae, Gerreidae, Ambassidae, Tetraodontidae: 4 species (2.9%); In addition, 4 families had 3 species, 12 families had 2 species and 35 families had 1 species. Cluster analysis based on the Bray - Curtis similarity index of nine fish faunas (Bach Dang, Thai Binh, Bu Lu, Son Tra peninsula, Thu Bon, coastal wetlands of Quang Nam, Nha Phu - Binh Cang, Ben Tre and Tra Vinh) showed that fish composition of the coastal - estuaries of Tra Vinh and Ben Tre had the highest similarity (78%), subsequently fish faunas of Thu Bon had similarity with that of Quang Nam (47%), Quang Nam and Nha Phu - Binh Cang (41%), Bu Lu and Thu Bon (38%). The result was also classified into three distinct groups of 9 fish faunas: group 1- Tra Vinh, Ben Tre and Thai Binh; group 2- Quang Nam, Thu Bon, Nha Phu - Binh Cang, Son Tra and Bu Lu; group 3- Bach Đang. The species richness (Margalef’s index) of Thu Bon (28.0) was less abundant than that of other areas: the highest species richness belonging to Tra Vinh (39.4), Thai Binh (38.6), Nha Phu - Binh Cang (35.9), Son Tra (31.8), Bu Lu (29.7), … The diversity of species composition according to the taxa in each region showed the characteristic of each fish fauna. The fish fauna is evidently typical of characteristics of the estuarine waters and coastal lagoons. There are 4 threatened species which are listed in the Vietnam’s Red Data Book (2007) at ex-tremely vulnerable levels.Thực hiện 4 chuyến khảo sát thu mẫu thành phần loài cá vùng cửa sông Thu Bồn trong năm 2013 tại 12 điểm thu mẫu. Kết quả đã ghi nhận được 139 loài thuộc 17 bộ, 63 họ và 110 giống. Phân tích cấu trúc quần xã khu hệ cá cho thấy: bộ cá Vược Perciformes là bộ cá phổ biến nhất chiếm 56,1%; tiếp đến là bộ cá Chép 8,6%; bộ cá Bơn Pleuronectiformes chiếm 6,5%; bộ cá Trích Clupeiformes và cá Nheo Siluriformes mỗi bộ 4,3%; bộ cá Chình Anguilliformes, cá Nóc Tetraodontiformes (3,6%); bộ cá Đối Mugiliformes (2,9%); ... Các họ chiếm ưu thế về loài: họ cá Bống trắng (Gobiidae) 12 loài chiếm 8,6% tổng số loài; cá Chép (Cyprinidae) 7,2%; cá Liệt (Leiognathidae) và cá Khế (Carangidae) mỗi họ 4,3%; cá Trích (Clupeidae), cá Hồng (Lutjanidae): 3,6%, ... So sánh với 8 khu hệ cá cửa sông - ven biển Việt Nam (Bạch Đằng, Thái Bình, Bù Lu, Sơn Trà, vùng đất ngập nước ven biển tỉnh Quảng Nam, Nha Phu - Bình Cang, Bến Tre và Trà Vinh) ghi nhận, vùng ven biển cửa sông Trà Vinh và Bến Tre có mức tương đồng cao nhất 78%, tiếp đến là Quảng Nam và Thu Bồn 47%, Quảng Nam và Nha Phu - Bình Cang 41%, Bu Lu và Thu Bồn 38%. Phân tích chỉ số giống nhau về thành phần loài của 9 khu hệ cá hình thành nên 3 nhóm: nhóm 1: Trà Vinh, Bến Tre và Thái Bình; nhóm 2: Quảng Nam, Thu Bồn, Nha Phu - Bình Cang, Sơn Trà và Bù Lu; Bạch Đằng hình thành riêng nhóm 3. Độ giàu có về loài của Thu Bồn đạt 28,0; Trà Vinh đạt cao nhất 39,4; tiếp đến là Thái Bình (38,6); Nha Phu - Bình Cang (35,9), Sơn Trà (31,8), Bù Lu (29,7), … Tính đa đạng về thành phần loài cá theo các bậc taxon trên từng vùng thể hiện tính đặc trưng riêng cho từng khu hệ. Các khu hệ cá thể hiện rõ tính chất nước lợ điển hình của các thuỷ vực cửa sông, đầm phá ven biển. Có 4 loài cá quý hiếm được ghi trong sách đỏ Việt Nam 2007 ở mức độ rất nguy cấp

The Impact of Social Media Marketing on Brand Awareness and Purchase Intention: Case Study of Vietnam's domestic fashion brands

The study aimed to examine the impact of social media marketing on brand awareness and purchase intention for Vietnamese domestic fashion brands. Quantitative research was conducted on 302 Vietnamese people of Generation Z. The questionnaire designed on Google forms was sent to research samples who were willing to participate. Research results determined the role and benefits of social media marketing in 2 aspects: (1) information about the brand of social media marketing on social networks and (2) brand engagement on social networks. Social media marketing has a positive impact on brand awareness and purchase intention of Vietnamese domestic fashion brands. In particular, brand information when communicating on social networks has a direct and positive impact on brand awareness and purchase intention. Brand engagement on social networks has a positive direct impact on brand awareness and a positive indirect impact on purchase intention through brand awareness. The research results show that Vietnamese domestic fashion brands do quite well in social media marketing, and are highly appreciated by the online community of generation Z in Vietnam. In the future, in order to improve brand awareness and purchase intention, Vietnamese domestic fashion brands need to pay attention to the brand information properties of social media marketing programs and need to invest more in brand engagement characteristics of social networks. Keywords: social media marketing, brand awareness, purchase intentio

The Impact of Social Presence in the Web Interface on Customer's Purchase Intention toward Online Stores: The Case of Vietnam

Abstract To date the expansion of information systems in the wa

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovation in this area, we setup a community-wide challenge using the largest available dataset of its kind to assess nuclear segmentation and cellular composition. Our challenge, named CoNIC, stimulated the development of reproducible algorithms for cellular recognition with real-time result inspection on public leaderboards. We conducted an extensive post-challenge analysis based on the top-performing models using 1,658 whole-slide images of colon tissue. With around 700 million detected nuclei per model, associated features were used for dysplasia grading and survival analysis, where we demonstrated that the challenge's improvement over the previous state-of-the-art led to significant boosts in downstream performance. Our findings also suggest that eosinophils and neutrophils play an important role in the tumour microevironment. We release challenge models and WSI-level results to foster the development of further methods for biomarker discovery

Mulvernet: Nucleus Segmentation and Classification of Pathology Images Using the HoVer-Net and Multiple Filter Units

Nucleus segmentation and classification are crucial in pathology image analysis. Automated nuclear classification and segmentation methods support analysis and understanding of cell characteristics and functions, and allow the analysis of large-scale nuclear forms in the diagnosis and treatment of diseases. Common problems in these tasks arise from the inconsistent sizes and shapes of the cells in each pathology image. This study aims to develop a new method to address these problems based primarily on the horizontal and vertical distance network (HoVer-Net), multiple filter units, and attention gate mechanisms. The results of the study will significantly impact cell segmentation and classification by showing that a multiple filter unit improves the performance of the original HoVer-Net model. In addition, our experimental results show that the Mulvernet achieves outperforming results in both nuclei segmentation and classification compared to several methods. The ability to segment and classify different types of nuclei automatically has a direct influence on further pathological analysis, offering great potential not only to accelerate the diagnostic process in clinics but also for enhancing our understanding of tissue and cell properties to improve patient care and management

N,2,6-Trisubstituted 1H-benzimidazole derivatives as a new scaffold of antimicrobial and anticancer agents : design, synthesis, in vitro evaluation, and in silico studies

Compounds containing benzimidazole moiety occupy privileged chemical space for discovering new bioactive substances. In continuation of our recent work, 69 benzimidazole derivatives were designed and synthesized with good to excellent yields of 46-99% using efficient synthesis protocol i.e. sodium metabisulfite catalyzed condensation of aromatic aldehydes with o-phenylenediamines to form 2-arylbenzimidazole derivatives followed by N-alkylation by conventional heating or microwave irradiation for diversification. Potent antibacterial compounds against MSSA and MRSA were discovered such as benzimidazole compounds 3k (2-(4-nitrophenyl), N-benzyl), 3l (2-(4-chlorophenyl), N-(4-chlorobenzyl)), 4c (2-(4-chlorophenyl), 6-methyl, N-benzyl), 4g (2-(4-nitrophenyl), 6-methyl, N-benzyl), and 4j (2-(4-nitrophenyl), 6-methyl, N-(4-chlorobenzyl)) with MIC of 4-16 mu g mL(-1). In addition, compound 4c showed good antimicrobial activities (MIC = 16 mu g mL(-1)) against the bacteria strains Escherichia coli and Streptococcus faecalis. Moreover, compounds 3k, 3l, 4c, 4g, and 4j have been found to kill HepG2, MDA-MB-231, MCF7, RMS, and C26 cancer cells with low mu M IC50 (2.39-10.95). These compounds showed comparable drug-like properties as ciprofloxacin, fluconazole, and paclitaxel in computational ADMET profiling. Finally, docking studies were used to assess potential protein targets responsible for their biological activities. Especially, we found that DHFR is a promising target both in silico and in vitro with compound 4c having IC50 of 2.35 mu M

Platelet rich fibrin and MTA in the treatment of teeth with open apices

Abstract Background The present study aimed to evaluate the effectiveness of using platelet-rich fibrin (PRF) as the apical matrix for the placement of MTA in nonsurgical endodontic therapy for teeth with periapical lesions and open apices. Methods Twelve teeth from eleven patients with periapical periodontitis and open apices were enrolled in the study. Nonsurgical endodontic therapy was performed with the PRF used as an apical barrier and the MTA manipulated as an apical plug for further thermoplasticized gutta percha in the remaining part of the root canal. Clinical signs and periapical digital radiographs were recorded and analyzed to evaluate the curing progress after periodical follow-ups of 1, 3, and 6 months. The horizontal dimension of the periapical lesion was determined, and the changes in the dimensions were recorded each time. The Friedman test was used for statistical analysis, with P < .05 serving as the threshold for determining statistical significance. Results All patients had no clinical symptoms after the first month of treatment, with a significant reduction in the periapical lesion after periodical appointments. Conclusions PRF is an effective barrier when combined with MTA for the treatment of teeth with periapical periodontitis and open apices

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening