HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

To date, facial recognition has been one of the most intriguing, interesting research topics over years. It requires some specific face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition as well; however, all of these algorithms derive from heavy deep learning architectures that cause limitations for development, scalability, flawed accuracy, and deployment into publicity with mere CPU servers. It also calls for large datasets containing hundreds of thousands of records for training purposes. In this paper, we propose a full pipeline for an effective face recognition application which only uses a small Vietnamese celebrity dataset and CPU for training that can solve the leakage of data and the need for GPU devices. It is based on a face vector-to-string tokens algorithm then saves face’s properties into Elasticsearch for future retrieval, so the problem of online learning in Facial Recognition is also tackled. Comparison with another popular algorithm on the dataset, our proposed pipeline not only outweighs the accuracy counterpart, but it also achieves a very speedy time inference for a real-time face recognition application

Iron and calcium nutrition interventions among Vietnamese women

Iron and calcium deficiencies remain a concern amongst working-age women in low to middle-income countries. This study aimed to evaluate the effect of nutritional intervention on the improvement of the iron status and calcium intake of this population. Non-pregnant workers at a company were divided into two groups. The intervention group (n=118) received nutritional intervention including nutritional education and an 8-week course of oral nutritional supplements (ONS). The control group (n=106) did not receive any intervention. Nutritional assessment, level of Hb concentration, serum iron, and ferritin were taken at baseline and after eight weeks. The results showed iron and calcium intake increased significantly in the intervention group. The effective intervention of serum iron was 33.3%. In conclusion, nutritional intervention such as nutritional education and ONS consumption is effective for improving iron status and calcium intake in working-age women

HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

peer reviewedFacial recognition has been one of the most intriguing and exciting research topics over the last few years. It involves multiple face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition. However, all of these algorithms are derived from large deep-learning architectures, leading to limitations in development, scalability, accuracy, and deployment for public use with mere CPU servers. Also, large data sets that contain hundreds of thousands of records are often required for training purposes. In this paper, we propose a complete pipeline for an effective face-recognition application that requires only a small dataset of Vietnamese celebrities and a CPU for training, solving the problem of data leakage, and the need for GPU devices.The pipeline is based on the combination of a conversion algorithm from face vectors to string tokens and the indexing & retrieval process by Elasticsearch, thereby tackling the problem of online learning in facial recognition. Compared with other popular algorithms on the same data set, our proposed pipeline not only outperforms the counterpart in terms of accuracy but also delivers faster inference, which is essential to real-time applications

FTIR Combined with Chemometrics for Fast Simultaneous Determination of Penicillin and Cephalexin in Pharmaceutical Tablets

In this research, the potential of combining chemometrics with FTIR techniques to provide a rapid and simultaneous quantitative analyses method for determination penicillin, cephalexin is studied. Unlike other methods, FTIR is considered as a time saving method due to its non-destructive and simple sample preparation. Due to the similarity of infrared spectral, PLS and PCR couples with spectral treatment techniques are applied to make the calibration model for penicillin and cephalexin determination at the same time. The result is also validated in term of RMSEP and R2 value using validation set. The FTIR combined with PLS method shows the best results

Pichia pastoris versus Saccharomyces cerevisiae:a case study on the recombinant production of human granulocyte-macrophage colony-stimulating factor

BACKGROUND: Recombinant human granulocyte-macrophage colony-stimulating factor (rhGM-CSF) is a glycoprotein that has been approved by the FDA for the treatment of neutropenia and leukemia in combination with chemotherapies. Recombinant hGM-CSF is produced industrially using the baker's yeast, Saccharomyces cerevisiae, by large-scale fermentation. The methylotrophic yeast, Pichia pastoris, has emerged as an alternative host cell system due to its shorter and less immunogenic glycosylation pattern together with higher cell density growth and higher secreted protein yield than S. cerevisiae. In this study, we compared the pipeline from gene to recombinant protein in these two yeasts. RESULTS: Codon optimization in silico for both yeast species showed no difference in frequent codon usage. However, rhGM-CSF expressed from S. cerevisiae BY4742 showed a significant discrepancy in molecular weight from those of P. pastoris X33. Analysis showed purified rhGM-CSF species with molecular weights ranging from 30 to more than 60 kDa. Fed-batch fermentation over 72 h showed that rhGM-CSF was more highly secreted from P. pastoris than S. cerevisiae (285 and 64 mg total secreted protein/L, respectively). Ion exchange chromatography gave higher purity and recovery than hydrophobic interaction chromatography. Purified rhGM-CSF from P. pastoris was 327 times more potent than rhGM-CSF from S. cerevisiae in terms of proliferative stimulating capacity on the hGM-CSF-dependent cell line, TF-1. CONCLUSION: Our data support a view that the methylotrophic yeast P. pastoris is an effective recombinant host for heterologous rhGM-CSF production

Making sense of Vietnamese consumers in the casual wear market

With Focus Groups Interviews as the main research approach, this project aims at providing a comprehensive understanding of Vietnamese consumers in the casual wear market. From this understanding, marketing implications and recommendations are discussed further

α-Amylase and α-Glucosidase Inhibitory Activities of Chemical Constituents from Wedelia chinensis (Osbeck.) Merr. Leaves

As part of an ongoing search for new natural products from medicinal plants to treat type 2 diabetes, two new compounds, a megastigmane sesquiterpenoid sulfonic acid (1) and a new cyclohexylethanoid derivative (2), and seven related known compounds (3–9) were isolated from the leaves of Wedelia chinensis (Osbeck.) Merr. The structures of the compounds were conducted via interpretation of their spectroscopic data (1D and 2D NMR, IR, and MS), and the absolute configurations of compound 1 were determined by the modified Mosher’s method. The MeOH extract of W. chinensis was found to inhibit α-amylase and α-glucosidase inhibitory activities as well as by the compounds isolated from this extract. Furthermore, compound 7 showed the strongest effect with IC50 values of 112.8 ± 15.1 μg/mL (against α-amylase) and 785.9 ± 12.7 μg/mL (against α-glucosidase). Compounds 1, 8, and 9 showed moderate α-amylase and α-glucosidase inhibitory effects. Other compounds showed weak or did not show any effect on both enzymes. The results suggested that the antidiabetic properties from the leaves of W. chinensis are not simply a result of each isolated compound but are due to other components such as the accessibility of polyphenolic groups to α-amylase and α-glucosidase activities

Effectiveness of a Mobile Application-Based Intervention to Improve Knowledge and Practice Regarding Silicosis Among High-Risk Workers of Dust Exposure in a Northern Province of Vietnam

Objectives: to analyze changes in knowledge and practices regarding silicosis in groups of workers at high risk of silicosis before - after an intervention. Methods: The study was conducted from 2018 to 2019 based on structured questions related to knowledge and practices of silicosis of workers directly exposed to silica dust in a Northern province of Vietnam. The mobile app-based intervention was applied to steel workers, then compared with ironworkers in improvements in silicosis knowledge and practices. Results: Significant changes in the intervention group related to workers' knowledge about the signs suggestive of silicosis, disease consequences, measures to reduce the risk of silicosis, and participation in annual occupational disease examinations were reported. Conclusion: Mobile applicationbased interventions could improve silicosis knowledge and practice among workers at high risk of exposure to silica dust

Hybrid end-to-end approach integrating online learning with face-identification system

Facial recognition has been one of the most intriguing and exciting research topics over the last few years. It involves multiple face-based algorithms such asfacial detection, facial alignment, facial representation, and facial recognition. However, all of these algorithms are derived from large deep-learning architectures, leading to limitations in development, scalability, accuracy, and deployment for public use with mere CPU servers. Also, large data sets that contain hundreds of thousands of records are often required for training purposes. In this paper, we propose a complete pipeline for an effective face-recognition application that requires only a small data set of Vietnamese celebrities and a CPU for training, solving the problem of data leakage, and the need for GPU devices. The pipeline is based on the combination of a conversion algorithm from face vectors to string tokens and the indexing & retrieval process by Elasticsearch, thereby tackling the problem of online learning in facial recognition. Compared with other popular algorithms on the same data set, our proposed pipeline not only outperforms the counterpart in terms of accuracy but also delivers faster inference, which is essential to real-time applications

Clinical screening of paraquat in plasma samples using capillary electrophoresis with contactless conductivity detection: Towards rapid diagnosis and therapeutic treatment of acute paraquat poisoning in Vietnam

The employment of a purpose-made capillary electrophoresis (CE) instrument with capacitively coupled con tactless conductivity detection ((CD)-D-4) as a simple and cost-effective solution for clinical screening of paraquat in plasma samples for early-stage diagnosis of acute herbicide poisoning is reported. Paraquat was determined using an electrolyte composed of 10 mM histidine adjusted to pH 4 with acetic acid. A detection.limit of 0.5 mg/L was achieved. Good agreement between results from CE-(CD)-D-4 and the confirmation method (HPLC-UV) was obtained, with relative errors for the two pairs of data better than 20% for 31 samples taken from paraquat-intoxicated patients. The results were used by medical doctors for identification and prognosis of acute paraquat poisoning cases. The objective of the work is the deployment of the developed approach in rural areas in Vietnam as a low-cost solution to reduce the mortality rate due to accidental or suicidal ingestion of paraquat