Selection of Exercises to Improve the Effectiveness of Physical Education under the Project of Elective Sports Cockpitching for Female Students K2023 Hanoi Metropolitan University

The interview results have selected 36 exercises belonging to 5 exercise groups to improve the effectiveness of physical education according to the project for female Hanoi Metropolitan University students studying the optional sport of shuttlecock, including Group 1: Exercises to develop strength quickly has 7 exercises; Group 2: Strength development exercises have 6 exercises; Group 3: Exercises to develop endurance has 5 exercises; Group 4: Exercises to develop flexibility and coordination has 5 exercises; Group 5: Exercises with the bridge has 13 exercises with an agreement level of > 70% or more and an average score of > 3.41 - 4.20 points. &nbsp

Investigate the Structural Response of Ultra High Performance Concrete Column under the High Explosion

Most of the structures that are damaged by an explosion are not initially designed to resist this kind of load. In the overall structure of any building, columns play an important role to prevent the collapse of frame structure under blast impact. Hence, the main concept in the blast resistance design of the structure is to improve the blast load capacity of the column. In this study, dynamic analysis and numerical model of Ultra High Performance Concrete (UHPC) column under high explosive load, is presented. Based on the Johnson Holmquist 2 damage model and the subroutine in the ABAQUS platform, a total of twenty UHPC model of the column were calculated. The objective of the article is to investigate the structural response of the UHPC column and locate the most vulnerable scenarios to propose necessary recommendations for the UHPC column in the blast loading resistance design. The input parameters, including the effect of various shapes of cross-section, scaled distance, steel reinforcement ratio, and cross-section area, are analyzed to clarify the dynamic behavior of the UHPC column subjected to blast loading. Details of the numerical data, and the discussion on the important obtained results, are also provided in this paper

Emerging Role of Circulating Tumor Cells in Gastric Cancer

With over 1 million incidence cases and more than 780,000 deaths in 2018, gastric cancer (GC) was ranked as the 5th most common cancer and the 3rd leading cause of cancer deaths worldwide. Though several biomarkers, including carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4), have been identified, their diagnostic accuracies were modest. Circulating tumor cells (CTCs), cells derived from tumors and present in body fluids, have recently emerged as promising biomarkers, diagnostically and prognostically, of cancers, including GC. In this review, we present the landscape of CTCs from migration, to the presence in circulation, biologic properties, and morphologic heterogeneities. We evaluated clinical implications of CTCs in GC patients, including diagnosis, prognosis, and therapeutic management, as well as their application in immunotherapy. On the one hand, major challenges in using CTCs in GC were analyzed, from the differences of cut-off values of CTC positivity, to techniques used for sampling, storage conditions, and CTC molecular markers, as well as the unavailability of relevant enrichment and detection techniques. On the other hand, we discussed future perspectives of using CTCs in GC management and research, including the use of circulating tumor microembolies; of CTC checkpoint blockade in immunotherapy; and of organoid models. Despite the fact that there are remaining challenges in techniques, CTCs have potential as novel biomarkers and/or a non-invasive method for diagnostics, prognostics, and treatment monitoring of GC, particularly in the era of precision medicine

Ultrasound accelerated sulfonylation of amines by <i>p</i>-acetamidobenzenesulfonyl chloride using Mg–Al hydrotalcite as an efficient green base catalyst

<p>The sulfonylation reaction of various aliphatic, alicyclic, aromatic, and hetero-aromatic amines with <i>p</i>-acetamidobenzenesulfonyl chloride has been investigated using different types of base catalysis under varied reaction conditions. Mg–Al hydrotalcite, characterizable as an inexpensive, reusable, and green solid catalyst, was found to be the most efficient catalyst, when the reaction is carried out in a minimum volume of solvent (acetone). The reaction was found to be accelerated drastically with the support of ultrasound irradiation, affording the sulfonamides in yields better or equivalent to those obtained under the longer lasting conventional stirring conditions.</p

Framework of Spatial Flood Risk Assessment for a Case Study in Quang Binh Province, Vietnam

Vietnam has been extensively affected by floods, suffering heavy losses in human life andproperty. While the Vietnamese government has focused on structural measures of flood defence such   as   levees   and   early   warning   systems,   the   country   still   lacks   flood   risk   assessment methodologies  and  frameworks  at  local  and  national  levels.  In  response  to  this  gap,  this  study developed  a  flood  risk  assessment  framework  that  uses  historical  flood  mark  data  and  a  high- resolution  digital  elevation  model  to  create  an  inundation  map,  then  combined  this  map  with exposure and vulnerability data to develop a holistic flood risk assessment map. The case study is the October 2010 flood event in Quang Binh province, which caused 74 deaths, 210 injuries, 188,628 flooded properties, 9019 ha of submerged and damaged agricultural land, and widespread damages to canals, levees, and roads. The final flood risk map showed a total inundation area of 64348 ha, in which 8.3% area of low risk, 16.3% area of medium risk, 12.0% area of high risk, 37.1% area of very high risk, and 26.2% area of extremely high risk. The holistic flood risk assessment map of QuangBinh province is a valuable tool and source for flood preparedness activities at the local scale.Validerad;2020;Nivå 2;2020-04-14 (johcin)</p

Segmentation of hard exudate lesions in color fundus image using two-stage CNN-based methods

The presence of hard exudate (EX) lesions is an early clinical symptom of Diabetic Retinopathy (DR); its accurate segmentation is essential for diagnosis and treatment. Automatic segmentation of EX lesions is challenging because they have a wide range of sizes, shapes, and brightness, and can be confused with soft exudate lesions. In this paper, we present and assess an efficient segmentation method for interactively segmenting EX lesions in fundus images from DR patients. Our approach consisted of two main stages: (1) the first stage generates an automatic segmentation using a CNN-based method. (2) If the obtained segmentation is suboptimal, the second stage is used to refine each inaccurately segmented region using a CNN-based interactive segmentation method. To train and evaluate method performance, we used two public datasets (IDRiD and DDR) and two local datasets from two medical centers (EHos and EWT) containing a wide range of EX lesions. Several state-of-the art CNN-based models and the proposed method were trained and evaluated on IDRiD, DDR and EHos datasets using the area under the precision–recall curve (AUPR), the dice similarity coefficient (Dice) and the intersection over union (IoU). In addition, EWT dataset was used to evaluate the methods without retraining the CNN models. The evaluation results using IDRiD dataset showed that the proposed method achieved AUPR, mean Dice and mean IoU scores of 0.893, 76.6% and 62.4%, respectively, which are comparable to the state-of-the-art method on EX segmentation. When evaluated on the DDR dataset with large portion of small EX lesions, the proposed method achieved AUPR, mean Dice and mean IoU scores of 0.693, 60.8% and 45.5%, yielding state-of-the-art performance. Furthermore, with the main evaluation metric being AUPR, the evaluation results on two datasets, EHos and ETW, with scores of 0.689 and 0.667 demonstrated superiority of the proposed method over the other segmentation methods. The proposed two-stage CNN-based segmentation method is an useful approach for accurately segmenting EX lesions in color fundus images, enabling lesion quantification to aid experts in treating patients with DR. The source code, the trained CNN models and the data are publicly available at: https://github.com/dvquang2000/Interactive_HardExudates_Segmentation.</p