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Cloud computing has become an increasingly popular platform for modern applications and daily life, and one of its greatest challenges is task scheduling and allocation. Numerous studies have shown that the performance of cloud computing systems relies heavily on arranging tasks in the execution stream on cloud hosts, which is managed by the cloud's load balancer. In this paper, we investigate task priority based on user behavior using request properties and propose an algorithm that utilizes machine learning techniques, namely k-NN and Regression, to classify task-based priorities of requests, facilitate proper allocation, and scheduling of tasks. We aim to enhance load balancing in the cloud by incorporating external factors of the load balancer. The proposed algorithm is experimentally tested on the CloudSim environment, demonstrating improved load balancer performance compared to other popular LB algorithms.

Currently, additive technology is becoming increasingly popular in different areas, including its applications in construction industry. The main aim of the chapter is to show the selected applications of 3D printing technology in the construction industry and the usage of this technology on distinct stages of a construction project, from architectural design to performance of residential buildings and other civil engineering constructions. The chapter is based on a critical analysis of the literature sources, as well as the authors' experiences. The data collected are supported by selected case studies from five projects. The main findings show that 3D printing brings a lot of advantages in the construction industry, for instance: low labour costs, less waste, and high efficiency, but it still requires development and optimization.

The IL-6/IL-6R or IL-6/GP130 protein-protein interactions play a significant role in controlling the development of chronic inflammatory diseases, such as rheumatoid arthritis, Castleman disease, psoriasis, and, most recently, COVID-19. Modulating or antagonizing protein-protein interactions of IL6 binding to its receptors by oral drugs promises similar efficacy to biological therapy in patients, namely monoclonal antibodies. In this study, we used a crystal structure of the Fab part of olokizumab in a complex with IL-6 (PDB ID: 4CNI) to uncover starting points for small molecule IL-6 antagonist discovery. Firstly, a structure‑based pharmacophore model of the protein active site cavity was generated to identify possible candidates, followed by virtual screening with a significant database Drugbank. After the docking protocol validation, a virtual screening by molecular docking was carried out and a total of 11 top hits were reported. Detailed analysis of the best scoring molecules was performed with ADME/T analysis and molecular dynamics simulation. Furthermore, the Molecular Mechanics-Generalized Born Surface Area (MM/GBSA) technique has been utilized to evaluate the free binding energy. Based on the finding, one newly obtained compound in this study, namely DB15187, may serve as a lead compound for the discovery of IL-6 inhibitors. Communicated by Ramaswamy H. Sarma

Based on density functional theory, the electronic and optical properties of double perovskites Ba2MnWO6 were studied using the generalized gradient approximation. We have looked into four magnetic configurations, such as collinear antiferromagnetic AF-1, AF-2 and noncollinear antiferromagnetic AF-NC1, AF-NC2 structures. The obtained results show that the valence band maximum is mainly dominated by Mn-3 d orbitals, while the conduction band minimum is mainly composed of W-5 d orbitals. In addition, Ba2MnWO6 is shown as an indirect band gap semiconductor. The gap between two main t2 g,↑ and e2 g,↑ manifolds of Mn-3 d states, located at about 1.9 and 1 eV below Fermi level, is initiated as consequence of splitting in crystal field. From calculated optical results, Ba2MnWO6 indicates excellent light absorption in the ultraviolet range. Consequently, this material promises potential optical applications, such as solar cell functional in ultraviolet light.

The role of interleukin-8 (IL-8) and its receptor CXCR2 in inflammatory responses and tumor development and progression has been well documented. Our study aims to discover novel compounds as CXCR2 antagonists to block the IL-8 signaling pathway using an in silico drug design. Herein, a structure-based pharmacophore model was developed based on the crystal structure of inactive CXCR2 in a complex with an allosteric inhibitor. This model was validated and refined, followed by virtual screening with the ZINC15 database. Subsequent molecular docking allows for predicting the best pose of a ligand inside a receptor binding site. We found that the 35 top-ranked hits exhibited docking scores from −30.81 to −25.28 kJ/mol and better interaction potential comparing the reference inhibitor. Analysis of ADME and toxicity properties revealed the efficacy and safety of the selected seven compounds. To validate the stability of the protein-ligand complex structure MD simulations approach has also been performed and confirmed via the critical parameters. The MD results explained that the CXCR2 receptor bound with two best-proposed molecules, including ZINC77105530 and ZINC93176465, was quite stable states as observed from low RMSD, RMSF, Rg, SASA values, and high occupancy of the interaction types. Finally, our data identified that these compounds play as potential inhibitors of IL-8 signaling pathways with the MM/GBSA binding free energies of −41.77 ± 6.45 kcal/mol and −38.84 ± 6.16 kcal/mol, respectively. Communicated by Ramaswamy H. Sarma

Objective We reviewed 50 infant cases with short bowel syndrome (SBS) to examine the treatment outcome of SBS management in a tertiary hospital in Vietnam. Material and Methods A case series was performed at the National Children's Hospital, Hanoi, Vietnam. A total of 50 cases with SBS were reviewed. Clinical and laboratory characteristics before and after treatment were collected. Results The most common cause of SBS was necrotizing enterocolitis. Common clinical symptoms included watery stools, dehydration, and malnutrition. After treatment, the patient's weight, albumin, and prothrombin improved markedly. There are 72% of children with good or fair treatment results. The rate of sepsis was high (18%). There was one case with complications of catheter infection and one case of liver failure. Three children died during treatment, one died from septic shock and multiple organ failure, and two died from respiratory failure. Conclusion This study showed promising treatment outcomes in pediatrics.

The adoption of corporate social responsibility (CSR) practices has been recognized as a significant contributor to the success of companies. Companies that engage in CSR initiatives can achieve positive outcomes that align with economic, social, and environmental goals while maintaining a long-term perspective (Nimani et al., 2022). CSR has become an increasingly important issue for businesses in Vietnam, and several factors have been identified as significant predictors of CSR adoption by Vietnamese-listed enterprises. This study examines the impact of the size of the enterprise, corporate governance, owner structure, board gender diversity, business industry, innovation, and knowledge of environmental, social, and governance (ESG) issues on CSR adoption. The study finds that the size of the enterprise is positively related to CSR adoption. Additionally, corporate governance structures that prioritize stakeholder interests tend to promote greater CSR adoption, while a diverse ownership structure and a higher representation of women on corporate boards also positively influence. Companies in certain industries tend to adopt CSR more readily. Moreover, the study highlights the positive impact of innovation and knowledge of ESG issues on CSR practices. These findings provide valuable insights into the factors that contribute to CSR adoption and suggest that targeted interventions may be necessary to encourage more widespread adoption of CSR practices. Further research is needed to explore these factors in greater depth and to develop effective strategies for promoting CSR adoption in Vietnam.

Five natural secondary metabolites as cinnamic acid (1), (+)-catechin (2), (-)-epicatechin (3), p-coumaric acid (4), and ferulic acid (5) were isolated from Amanita caesarea based on anti-inflammatory activity-guided extraction. Their structures (1-5) were determined by NMR spectra as well as by comparison with previously reported literature. Compounds 3 and 5 have been isolated from A. caesarea for the first time. The anti-inflammatory activity through inhibition of nitric oxide (NO) production of isolates (1-5) was evaluated. Among them, compounds 2 and 3 exhibited strong inhibitory activity with IC50 values of 4.8 and 5.7 μM, respectively. Compounds 4 and 5 with IC50 values of 18.4 and 9.6 μM, respectively showed moderate inhibitory activity. The results proposed that A. caesarea might exert anti-inflammatory effects due to its mainly NO-inhibitory constituents

An efficient and practical method for the synthesis of pyrroles by Cu-catalyzed multicomponent reaction has been described. A range of highly functionalized pyrroles was prepared in good yields under solvent free condition.

Background: Digital learning media have been proven useful tools to meet the increasing needs of students, especially on human anatomy learning. Aims of the study: The study was to evaluate the initial results of the designing and applying in teaching a 3D virtual reality model of human anatomy at Hue University of Medicine and Pharmacy. Methods: A descriptive cross-sectional study was conducted to survey the evaluation of 2nd-year general medical students, at Hue University of Medicine and Pharmacy, in the last two consecutive academic years, including 428 students learning the anatomy of the respiratory and circulatory system with traditional method and 406 students learning with 3D virtual reality model designed by us. Multivariate logistic regression analysis was used to identify related factors. Results: For the 3D virtual model, 83.5% of students rated it attractive and stimulating; 80.0% enjoy learning with 3D modeling; 77.3% think that it is a useful learning resource and 70.9% of learners feel that they can actively self-study with this virtual model. Besides, when learning with the 3D virtual model, the level of stress from learning accounted for less than 16.3% of the learners and the test scores compared to learning with the traditional model were statistically higher, p < 0.05. Conclusion: Our 3D virtual reality model was initially well received by learners and contributed to the improvement of learning for medical students Key words: anatomy, virtual model, 3D model.

Background: To determine the molecular subtypes and correlation between molecular subtypes and histopathological features in breast cancer in Vietnam and Italy. Material and method: 88 patients with invasive breast carcinoma (BC) in both Hue Central Hospital and Hue University Hospital in Vietnam during 1 year from April 2016 to April 2017 as well as 235 patients from the same category of women in Sassari University Hospital, Italy during the year 2016 were collected. All patients were examined for immunohistochemistry (IHC) with four markers ER, PR, HER2, and Ki67. The immunofluorescence in situ hybridization (FISH) test was applied for cases with HER2 (2+)/ IHC. Results: Breast cancer in Vietnam had the highest Luminal B (LB) rate, at 37.5%, followed by HER2 enrich (22.7%) and triple-negative breast cancer accounting for 21.6%. Luminal A (LA) accountd for the lowest proportion (18.2%). In contrast, breast cancer in Italy has the highest rate of Luminal A (54%), LB accounted for 34.5%, triple-negative occupied 10.6% and HER2 enrichment has a very low rate (0.9%). There was a statistically significant correlation between molecular subtypes and pathological features such as histologic grade, axillary lymph node, and stage of disease in both Vietnamese and Italian groups (p

In this paper, we study the first eigenvalue of the stability operator on an integral n n -varifold with constant mean curvature in the unit sphere S n + 1 \mathbb {S}^{n+1} . We find the optimal upper bound and prove a rigidity result characterizing the case when it is attained. This gives a new characterization for certain singular Clifford tori.

Conventional integration of rock physics and seismic inversion can quantitatively evaluate and contrast reservoir properties. However, the available output attributes are occasionally not a perfect indicator for specific information such as lithology or fluid saturation due to technology constraints. Each attribute commonly exhibits a combination of geological characteristics that could lead to subjective interpretations and provides only qualitative results. Meanwhile, machine learning (ML) is emerging as an independent interpreter to synthesise all parameters simultaneously, mitigate the uncertainty of biased cut-off, and objectively classify lithofacies on the accuracy scale. In this paper, multiple classification algorithms including support vector machine (SVM), random forest (RF), decision tree (DT), K-nearest neighbours (KNN), logistic regression, Gaussian, Bernoulli, multinomial Naïve Bayes, and linear discriminant analysis were executed on the seismic attributes for lithofacies prediction. Initially, all data points of five seismic attributes of acoustic impedance, Lambda-Rho, Mu-Rho, density (ρ), and compressional wave to shear wave velocity (VpVs) within 25-metre radius and 25-metre interval offset top and base of reservoir were orbitally extracted on 4 wells to create the datasets. Cross-validation and grid search were also implemented on the best four algorithms to optimise the hyper-parameters for each algorithm and avoid overfitting during training. Finally, confusion matrix and accuracy scores were exploited to determine the ultimate model for discrete lithofacies prediction. The machine learning models were applied to predict lithofacies for a complex reservoir in an area of 163 km2. From the perspective of classification, the random forest method achieved the highest accuracy score of 0.907 compared to support vector machine (0.896), K-nearest neighbours (0.895), and decision tree (0.892). At well locations, the correlation factor was excellent with 0.88 for random forest results versus sand thickness. In terms of sand and shale distribution, the machine learning outputs demonstrated geologically reasonable results, even in undrilled regions and reservoir boundary areas.

Breast augmentation surgery with an injection of free liquid silicone has been performed from the early 1960s but was abandoned by most practitioners because numerous complications have been reported, such as migration of silicone to other parts of the body, inflammation, discoloration, and the formation of granulomas, ulceration and fistulae, anaplastic large cell lymphoma, Silicone-Induced Granuloma, breast carcinoma. In this case report, we describe an invasive breast carcinoma, diagnosed via core needle biopsy, in breast augmentation by injecting free liquid silicone ten years ago, including breast imaging findings on mammography and MRI, macroscopic and microscopic features. The nipple-sparing mastectomy was performed for two breasts that were injected with liquid silicone. In the right breast with adenocarcinoma, surgical margins above nipple-areolar were assessed intra-operatively by frozen section before immediate breast reconstruction was carried out in the same operation. TRAM flap procedure reconstructed for right breast and implant breast reconstruction for the left breast. We received amazing post-operative results. Key words: breast cancer, liquid silicone injection, breast reconstruction

Resources-oriented instruction in physics treats student thinking as sensible and then seeks to connect what students are saying and doing to physics content and practices. This paper uses an illustrative case to make progress toward answering the instructional questions: “What does resources-oriented instruction in physics look like?” and “How can I do it?”. We analyze an interaction between a university TA and a group of four introductory physics students completing a worksheet about mechanical wave propagation. We show some of the ways in which the TA's instructional moves supported students in making conceptual progress, even though several of the students' ideas would not be accepted as correct by many physicists.

Essential oils (EOs) obtained from different medicinal and aromatic plant families by steam distillation have been used in the pharmaceutical, food, and fragrance industries. The plant EOs and their broad diversity of chemical components have attracted researchers worldwide due to their human health benefits and antibacterial properties, especially their treatment of Helicobacter pylori infection. Since H. pylori has been known to be responsible for various gastric and duodenal diseases such as atrophic gastritis, peptic ulcer, gastric adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma, several combination antibiotic therapies have been increasingly used to enhance the eradication rate of the bacterial infection. However, in the last decades, the efficacy of the therapies has decreased significantly due to widespread emergence of multidrug resistant strains of H. pylori. In addition, side-effects from commonly used antibiotics and recurrence of the bacterial infection have drawn public health concern globally.Therefore, this review focuses on in vitro effects of plant EOs and their bioactive constituents on the growth, cell morphology and integrity, biofilm formation, motility, adhesion, and urease activity of H. pylori. Their inhibitory effects on expression of genes necessary for growth and virulence factor productions of the bacterial pathogen are also discussed. Further in vivo and clinical evaluations are required so that plant EOs and their bioactive constituents can be possibly applicable in pharmacy or as adjuvants to the current therapies of H. pylori infection.

In this study, the dynamic responses of a cracked beam layed on a visco-elastic foundation subjected to moving loads are calculated. An Euler–Bernoulli beam model is used to describe the beam behaviors. In addition, the beam has several open cracks one-sided with different depths. By using the Fourier transform, the dynamic responses of the beam are determined analytically in the frequency domain with the help of Green’s function. By coupling with the periodic supported beam model, an analytical model of the railway sleeper is developed. This model allows the fast calculation of the dynamic responses of a damaged sleeper. A dynamic computational model using the FEM method was also developed and compared to the analytical model. The results from the two methods are relatively comparable for three cases of beams without cracks, beams with one crack, and beams with two cracks.

In 1953, Victor Thébault conjectured a link between the altitudes of a tetrahedron and the radical center of the four spheres with the centers at the vertices of this tetrahedron and the corresponding tetrahedron altitudes as radii. This conjecture was proved in 2015. In this paper, we propose an analogue of Th\'{e}bault's theorem. We establish a link between the radical center of the four spheres, the insphere, and the Monge point of a tetrahedron.

In this study, the effect of spike-nosed length on aerodynamic drag of a wing-projectile model was investigated at supersonic conditions. The projectile BK-13 with convex nose was selected for the study. The ratio of nose diameter and model diameter was fixed at around 0.34 while the ratio of the length of the nose and the model diameter was changed from 1.25 to 2.75. Numerical simulation with turbulent model k-ε was applied for flow structure around the model. The effect of mesh size and numerical models on the drag of the standard model was investigated. The study showed that numerical methods allow to obtain highly accurate drag coefficients. As the length of aerospike increases, the drag coefficient quickly decreases and obtains a minimum value at l/D = 2.0. The effect of spike-nosed length and velocity on flow pattern and drag of the model was ex-plained in details in this study

International audience; The reduction of pollutant emissions from internal combustion engines, and in particular greenhouse gases, must be achieved by optimizing the combustion process and choosing fuels with a low carbon impact. Heterogeneous mixture combustions such as Diesel induce a difficulty in managing of the pollutants formation even if in its principle the output efficiency remains favorable. Therefore, it is necessary to distinguish this last point, which refers to the compression ratio, in order to move towards homogeneous combustion with a high compression ratio. We then speak generically of HCCI combustion (Homogeneous Charge Compression Ignition), whose process takes place in the context of auto ignition.An important challenge of this combustion is the control of the ignition timing. This paper presents a concept to control the initiation of combustion of a reactive gas mixture with low susceptibility to auto-ignition, which meets the expectation of high efficiency, via the introduction of biomass particles. From a schematic point of view, these particles will play the role of spark plugs distributed throughout the combustion chamber, and should have an auto ignition time much lower than that of the fuel.For this purpose, a particle injector was conceived to directly inject a controlled quantity of biomass powder into the reactive mixture directly. This part is a challenging point. The reproducibility and viability of the particle injector were qualitatively validated by image analysis acquired at high frequency and high resolution. Thus, the system was integrated into an RCM (Rapid Compression Machine) chamber, allowing diphasic gas/solid biomass combustion study. This preliminary test was investigated by high-speed video on a lean diluted biomass enriched with hydrogen mixture (CH4/CO2/H2) at low fuel-air equivalence ratio (Φ = 0.6), with different auto-ignition delays in the condition of experimentation. It was shown that the direct injection of a small amount of biomass particles was able to promote its reactivity and initiate the combustion process. This study highlights the promising effects of the injection of powder to control the beginning of homogeneous combustion, by bringing locally a spot of energy, distributed in the whole chamber. The control given by a global contribution of weak energy is distinguished from the process of combustion by auto-ignition of the fuel mixture whose properties of equivalence air-fuel ratio or dilution will complete the optimization of the process.