EmbryosFormer: Deformable Transformer and Collaborative Encoding-Decoding for Embryos Stage Development Classification

The timing of cell divisions in early embryos during the In-Vitro Fertilization (IVF) process is a key predictor of embryo viability. However, observing cell divisions in Time-Lapse Monitoring (TLM) is a time-consuming process and highly depends on experts. In this paper, we propose EmbryosFormer, a computational model to automatically detect and classify cell divisions from original time-lapse images. Our proposed network is designed as an encoder-decoder deformable transformer with collaborative heads. The transformer contracting path predicts per-image labels and is optimized by a classification head. The transformer expanding path models the temporal coherency between embryo images to ensure monotonic non-decreasing constraint and is optimized by a segmentation head. Both contracting and expanding paths are synergetically learned by a collaboration head. We have benchmarked our proposed EmbryosFormer on two datasets: a public dataset with mouse embryos with 8-cell stage and an in-house dataset with human embryos with 4-cell stage. Source code: https://github.com/UARK-AICV/Embryos.Comment: Accepted at WACV 202

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Composition and early-age temperature regime in massive concrete foundation

The usage of monolithic concrete technology in massive structure construction has created a need for a more detailed design focused on crack control. In this study, the American standard ACI 211.1-09 and absolute volume method were used to determine the composition of heavy weight concrete for the high-rise building foundation. The concrete block temperature behavior has been analyzed by a three-dimensional thermal model in program Midas Civil. The conducted studies' result provided the possibility of obtaining heavy weight concrete from Vietnam local raw materials regarding to the concrete mixture workability of 16 cm standard cone, compressive strength of 42.3 MPa and average tensile strength of 3.5 MPa at the age of 28 days. According to the model analysis results, the maximum temperatures of the massive concrete foundation at the first (after 72 hours) and second pour (after 144 hours) from the beginning of construction are respectively 55.70C and 65.50C. In addition, the temperature differences at the core of each concrete pours with respect to the concrete outer portion, which induces a risk of through cracking in structure body or surface were determined

Machine learning based classification model for screening of infected patients using vital signs

Objectives: The classification of healthy versus infected persons, and the early detection of disease sources, plays an important role in preventing spread of disease and in curing the disease. The current traditional quarantine methods using remote body thermometers as well as questionnaires have not been highly effective due environment and subjective human factors. The use of Machine Learning algorithms may be more objective and optimal for this purpose. Methods: In this paper, a non-contact measuring system using medical radar is proposed to acquire data. Then, data captured from this radar is passed through filters to both eliminate interference and to provide vital parameters such as heart and respiration rate. Finally, the classification between healthy and infected people is executed by using five Machine learning algorithms. With the measured dataset, the classification models are built through training and test steps. Results: The classification results of the algorithms are evaluated based on the f1-score parameter with accuracy greater than 80%. In particular, the Deep Learning algorithms gives the highest result of 98%. Conclusion: This study implements patient classification algorithms, which achieved good performance. This might be beneficial for rapid screening of infected patients at public health centers in underdeveloped areas, where people have little access to healthcare. Motivation & significance: The classification of healthy and infected people can help prevent the spread of disease in a community. With such relatively accurate results, in the future, the system can be directly applied in practice

Na2Fe3(SO4)4 là vật liệu cathode mới với điện thế cao dùng cho pin sodium-ion

Based on the density functional theory, we propose a promising cathode material, Na2Fe3(SO4)4, applicable for sodium-ion batteries. The crystal structure, stability, average voltage, and diffusion mechanism are carefully investigated to evaluate the electrochemical properties. The proposed material exhibits a high voltage of 4.0 V during the Na extraction. A small polaron is proved to be formed preferably at the first nearest Fe sites to Na vacancy and simultaneously accompanies the Na vacancy during its migration. Four elementary diffusion processes of the polaron–Na vacancy complexes, namely two parallel and two crossing processes, have been explored. The significant difference of activation energies between parallel and crossing processes suggests the substantial effect of the small polaron migration on the Na vacancy diffusion. We found that the parallel process along the [001] direction has the lowest activation energy of 808 meV, implying that the Na vacancy preferably diffuses in a zigzag pathway along the [001] direction.Chúng tôi đề xuất một vật liệu cathode mới Na2Fe3(SO4)4 có thể dùng cho pin sodium-ion dựa theo lý thuyết phiếm hàm mật độ. Cấu trúc tinh thể, tính bền, điện thế trung bình và cơ chế khuếch tán được khảo sát cẩn thận để đánh giá các tính chất điện hóa. Vật liệu đề xuất có thể đạt điện thế cao 4.0 V trong quá trình giải phóng ion Na. Chuẩn hạt polaron nhỏ ưu tiên hình thành tại vị trí Fe gần nhất với vị trí khuyết ion Na và chuyển động đồng thời với vị khuyết ion Na trong suốt quá trình chuyển động của nó. Bốn quá trình khuếch tán của tổ hợp vị trí khuyết ion Na và polaron được khảo sát gồm có 2 quá trình song song và 2 quá trình chéo. Sự khác biệt về năng lượng kích hoạt giữa các quá trình song song và chéo cho thấy hiệu ứng đáng kể của các polaron nhỏ đến quá trình khuếch tán của vị trí khuyết ion Na. Chúng tôi nhận thấy quá trình song song dọc theo hướng [001] có năng lượng kích hoạt thấp nhất là 808 meV, điều này gợi ý rằng vị trí khuyết ion Na ưu tiên khuếch tán theo một đường zigzag dọc theo hướng [001]

Establishing the Vertical Movement Map of Cuu Long Delta River by GNSS Data

Mekong Delta is an area with an important position in the socio-economic development of Vietnam. However, due to the impact of climate change as well as of the construction of hydroelectric dams in the upstream of the Mekong River in recent years, saline intrusion and flooding have been occurred because of high tide. According to published researches, the Mekong Delta is being experienced surface subsidence with a rate of up to centimeters per year, that exacerbates the impact of saline intrusion and flooding. Thus, studying to establish the surface subsidence map is an urgent need in this site. There are many of technologies to create the vertical movement map such as: Levelling, INSAR, GNSS, etc. Up to now, there are no scientific reports on the application of GNSS to monitor the vertical movement in this area. In this paper, the authors have calculated the largest vertical displacement velocity up to 3cm/year based on processing GNSS observations of nearly 20 GNSS monitoring station in the area using Bernese software. From these results, the research team has made the vertical movement map of Mekong, Vietnam

Spatiotemporal Variability of Hot Days in Association with the Large-Scale Atmospheric Drivers over Vietnam

The severe heatwaves and hot spells in Vietnam were observed more frequently in intensity and duration due to global warming and climate change impacts. The hot days and extreme summer events make the weather harsh and significantly affect human health and the environment. This study presents the spatiotemporal distribution of the number of hot days (NHDs) in Vietnam. The variability of NHD in seven climate subregions is also examined in association with the large-scale drivers. The European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5) data for the period 1981–2020 are used. Principal component analysis is also applied to the observed monthly NHD to obtain spatial patterns and time series. The results show that the NHD in the Highland and South subregions from March to May is linked with the subtropical high associated with decreased 500hPa-level vertical velocity (VV500). From May to June, the North and Central subregions seem related to deepening the Asiatic low and enhancement of southwest flows across the Indochina Peninsula. Finally, both increased southwest flows and decreased VV500 can partly contribute to the intensification of NHD in the North and Central subregions during July and August. The long trends of NHD are also examined. The results reveal that the increasing trends in NHD occur in most subregions, except for the Central Highland, and changing trends of NHD in June greatly contribute to the annual trend of NHD. Finally, the examinations with the El Niño-Southern Oscillation events show that NHD is significantly higher in El Niño events than in La Niña events in March and April for the Northwest, South Central, Central Highlands, and South, in May and June for all subregions, and in July and August for only the Red River Delta subregion. This suggests that ENSO can provide the potential for improving seasonal climate forecasts and mitigating natural disaster risks for the community

Size Determination of Polystyrene Sub-Microspheres Using Transmission Spectroscopy

Nano/micro polystyrene (PS) beads have found many applications in different fields spanning from drug delivery, bio-diagnostics, and hybrid plasmonics to advanced photonics. The sizes of the PS beads are an important parameter, especially in plasmonic and photonic experiments. In this work, we demonstrate a quick and straightforward method to estimate the diameters of sub-microspheres (0.2 μm to 0.8 μm) using the transmission spectra of a close-packed monolayer of polystyrene beads on glass or quartz substrates. Experimental transmission spectra of the PS monolayers were verified against finite-difference time-domain (FDTD) simulation and showed good agreement. The effects of the substrates on the transmission spectra and, hence, the accuracy of the method were also studied by simulation, which showed that common transparent substrates only cause minor deviation of the PS bead sizes calculated by the proposed method

Flavonoids as dual-target inhibitors against α-glucosidase and α-amylase: a systematic review of in vitro studies

Diabetes mellitus remains a major global health burden and great attention is directed at natural therapeutics. This systematic review aimed to evaluate the potential of flavonoids as antidiabetic agents through their ability to inhibit α-amylase and α-glucosidase, two key starch digestive enzymes. Six scientific databases were queried up until August 21, 2022, for in vitro studies reporting the IC50 results of purified flavonoids on α-amylase or α-glucosidase, along with the respective data of acarbose control. A total of 339 articles were assessed as eligible and subjected to the data extraction process, resulting in 1643 retrieved flavonoid structures. Chemical structures were then rigorously standardized and curated to 974 unique compounds, in which 177 flavonoids showed both inhibitions against α-amylase and α-glucosidase. Quality assessment was conducted following a modified CONSORT checklist. The structure-activity relationships revealed that a double bond C2=C3 and a keto group C4=O is essential for simultaneous inhibition. The hydroxyl group at C3 is favourable for α-glucosidase inhibition but detrimental to the effect against α-amylase. Further notable features which affect α-glucosidase and α-amylase inhibition were also discussed. Several limitations were considered, including the inconsistency among included studies, language restriction, and the contemporaneity of the review. In conclusion, the systematic review has summarized some crucial findings in the investigation of flavonoids as dual-target inhibitors against α-glucosidase and α-amylase and proposed several orientations for future research

Flavonoids as dual-target inhibitors against α-glucosidase and α-amylase : a systematic review of in vitro studies

Diabetes mellitus remains a major global health issue, and great attention is directed at natural therapeutics. This systematic review aimed to assess the potential of flavonoids as antidiabetic agents by investigating their inhibitory effects on alpha-glucosidase and alpha-amylase, two key enzymes involved in starch digestion. Six scientific databases (PubMed, Virtual Health Library, EMBASE, SCOPUS, Web of Science, and WHO Global Index Medicus) were searched until August 21, 2022, for in vitro studies reporting IC50 values of purified flavonoids on alpha-amylase and alpha-glucosidase, along with corresponding data for acarbose as a positive control. A total of 339 eligible articles were analyzed, resulting in the retrieval of 1643 flavonoid structures. These structures were rigorously standardized and curated, yielding 974 unique compounds, among which 177 flavonoids exhibited inhibition of both alpha-glucosidase and alpha-amylase are presented. Quality assessment utilizing a modified CONSORT checklist and structure-activity relationship (SAR) analysis were performed, revealing crucial features for the simultaneous inhibition of flavonoids against both enzymes. Moreover, the review also addressed several limitations in the current research landscape and proposed potential solutions. The curated datasets are available online at https://github.com/MedChemUMP/FDIGA