Search

Abstract Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder afflicting the elderly population worldwide. The identification of potential gene candidates for AD holds promises for diagnostic biomarkers and therapeutic targets. Employing a comprehensive strategy, this study integrated transcriptomic data from diverse data sources, including microarray and single-cell datasets from blood and tissue samples, enabling a detailed exploration of gene expression dynamics. Through this thorough investigation, 19 notable candidate genes were found with consistent expression changes across both blood and tissue datasets, suggesting their potential as biomarkers for AD. In addition, single cell sequencing analysis further highlighted their specific expression in excitatory and inhibitory neurons, the primary functional units in the brain, underscoring their relevance to AD pathology. Moreover, the functional enrichment analysis revealed that three of the candidate genes were downregulated in synaptic signaling pathway. Further validation experiments significantly showed reduced levels of rabphilin-3A (RPH3A) in 3xTg-AD model mice, implying its role in disease pathogenesis. Given its role in neurotransmitter exocytosis and synaptic function, further investigation into RPH3A and its interactions with neurotrophic proteins may provide valuable insights into the complex molecular mechanisms underlying synaptic dysfunction in AD.

Abstract Cluster analysis can also detect abnormalities besides building a basis for identifying elements into clusters. Detecting abnormalities is a highly developed feature in the field of unsupervised learning. However, existing studies have mainly focused on discrete data, not probability density functions. This paper enables a possibilistic approach to solving the clustering for probability density functions dealing with abnormal elements. First, the data are extracted using the density function. Then, they are passed through the proposed algorithm to produce a possibilistic partition. Finally, a decision rule is established to recognize which function is abnormal. We compare the proposed algorithm with baseline algorithms in clustering PDFs, such as k-means, FCF, and Self-Updated Clustering. The results of three numerical examples applied to the image are typical for this new method. Furthermore, The proposed algorithm reaches accuracy at 100% over simulated benchmark data and outperforms baseline methods. Additionally, two last examples apply to image data reaching G-mean up from 96 to 100% (Sensitivity: 92–100% and Specificity: 100%). The proposed method can be researched and used to understand the internal structures of big data in the digital age through the probability density functions.

This study examines a cooperative non-orthogonal multiple access (NOMA) network utilizing an energy-constrained unmanned aerial vehicle (UAV) relay (UAVR) to expand coverage and improve network throughput. In order to provide energy to the UAVR, we consider the hybrid simultaneous wireless information and power transmission (SWIPT) method, which allows the UAVR to harvest energy from the source (i.e., sink node) signal. Herein, a hybrid time switching (TS)-based and power splitting (PS)-based relaying scheme is applied to improve the UAVR’s energy harvesting (EH) efficiency and the system performance. Given this context, we derive the closed-form expression of the outage probability (OP) for the sensors to evaluate the network performance. Based on the achieved analytical results, we apply the bat algorithm optimization (BAO) method to determine the optimal working point (as a fraction of received power and power allocation coefficients, and the 3-D positions of the UAVR) for the system such that the OP is minimized. The numerical analysis indicates that BAO is effective in both exploring and exploiting solutions, making it a suitable choice for similar non-convex optimization problems in continuous search spaces for cooperative NOMA IoT networks.

Deubiquitinating enzymes (DUBs) prevent ubiquitination by eliminating ubiquitin from their substrates. Deubiquitinating enzymes have important roles in a number of cell biology subfields that are highly relevant to diseases like neurodegeneration, cancer, autoimmune disorders, and long-term inflammation. Deubiquitinating enzymes feature a well-defined active site and, for the most part, catalytic cysteine, which makes them appealing targets for small-molecule drug development. Ubiquitin-specific protease 46 (USP46) is a member of the ubiquitin-specific protease family, the largest subfamily of DUBs. Over the past 10 years, some studies have steadily demonstrated the significance of USP46 in several biological processes, although it was identified later and early research progress was modest. Specifically, in the last few years, the carcinogenic properties of USP46 have become more apparent. In the current review, we provide a comprehensive overview of the current knowledge about USP46 including its characteristics, structure, inhibitors, function in diseases, especially in the nervous system, and the correlation of USP46 with cancers.

Vietnam is regarded as one of the developing countries that successfully attracts foreign direct investment (FDI). Approaching and transferring technology in FDI projects is the top priority in promoting Vietnam’s FDI attractiveness strategy. The estimated results show that FDI positively contributed to technology development, stimulating innovation in science and technology applications while improving competitiveness for domestic enterprises. However, due to the lack of R&D activities and management capabilities, it still has numerous difficulties in applying and transferring technology to Vietnam. Therefore, to enhance the efficiency of FDI on technology development, Vietnam needs to strongly implement further solutions.

Manufacturing of adeno-associated viruses (AAV) for gene and cell therapy applications has increased significantly and spurred development of improved mammalian and insect cell-based production systems. We developed a baculovirus-based insect cell production system—the SGMO Helper—with a novel gene architecture and greater flexibility to modulate the expression level and content of individual Rep and Cap proteins. In addition, we incorporated modifications to the AAV6 capsid sequence that improves yield, capsid integrity, and potency. Production of recombinant AAV 6 (rAAV6) using the SGMO Helper had improved yields compared to the Bac-RepCap helper from the Kotin lab. SGMO Helper-derived rAAV6 is resistant to a previously described proteolytic cleavage unique to baculovirus-insect cell production systems and has improved capsid ratios and potency, in vitro and in vivo, compared with rAAV6 produced using Bac-RepCap. Next-generation sequencing sequence analysis demonstrated that the SGMO Helper is stable over six serial passages and rAAV6 capsids contain comparable amounts of non-vector genome DNA as rAAV6 produced using Bac-RepCap. AAV production using the SGMO Helper is scalable using bioreactors and has improved yield, capsid ratio, and in vitro potency. Our studies demonstrate that the SGMO Helper is an improved platform for AAV manufacturing to enable delivery of cutting-edge gene and cell therapies.

Spontaneous idiopathic vulvar edema during the second trimester is a rare condition. The approach to managing this condition involves relieving symptoms, identifying underlying causes, and implementing appropriate treatment. Managing such cases during pregnancy is challenging because of concerns for potential adverse fetal outcomes. Conservative management expects the condition to be relieved spontaneously postpartum, whereas invasive treatment offers a more rapid resolution. Treatment choices are controversial because each method has its pros and cons and influences the delivery process to a certain extent. Surgical drainage becomes a viable option when patients are not responsive to medications. We report a case of spontaneous massive vulvar edema in a 22-year-old primigravida in her 23rd week of pregnancy. After ruling out other notable causes of vulvar edema, we decided to intervene using an invasive procedure because she complained of progressive symptoms and discomfort. Subsequently, the edema subsided postprocedure, and the patient experienced successful labor with no complications. This report aims to alert clinicians that drainage attempts should be considered in pregnant patients with worsening symptoms.

Metanephric adenoma presents as a rare benign tumor in children with differentiated diagnoses: Wilms tumor or renal cell carcinoma. When confronted with small renal tumors, whether they fall into one of these three diagnostic categories, tumor resection surgery with laparoscopic partial nephrectomy is considered a viable and effective operative approach. Herein, we report the case of an 11-year-old female patient initially diagnosed with stage T1a renal cell carcinoma with postoperative pathology results confirming metanephric adenoma. Successfully treated with laparoscopic partial nephrectomy, the patient showed no signs of recurrence or metastasis during follow-up.

Cây Dầu lai có củ (Jatropha podagrica Hook. – Euphorbiaceae) được dùng trong y học cổ truyền để chữa bệnh táo bón, nhiễm trùng da, vàng da, và sốt. Thành phần hóa học chủ yếu là các hợp chất nhóm flavonoid, coumarin, acid phenol, diterpenoid, peptide, và steroid. Một số nghiên cứu đã cho biết các tác dụng dược lý tiềm năng của cây Dầu lai có củ như hoạt tính kháng khuẩn, kháng ung thư, chống oxy hóa, ức chế sự phát triển của côn trùng, ức chế thần kinh cơ và hạ huyết áp. Cho đến nay, Dược điển Việt Nam V vẫn chưa có chuyên luận về dược liệu Dầu lai có củ. Do đó, mục tiêu của nghiên cứu này là xác định các đặc điểm thực vật học của cây Dầu lai có củ. Đặc điểm hình thái, vi phẫu, bột dược liệu của lá, thân và rễ được mô tả chi tiết. Kết quả của nghiên cứu này hữu ích cho việc xác định và kiểm nghiệm dược liệu cũng như xây dựng chuyên luận Dầu lai có củ trong Dược điển Việt Nam.

This paper presents a multi-element multiple-input multiple-output (MIMO) antenna with self-isolation and flexible characteristics. The primary radiators of the proposed antenna consist of multiple ellipse-shaped patches arranged in an H-plane configuration. Self-decoupling is achieved by simultaneously different operating modes on the excited element (TM10 mode) and non-excited element (TM02 mode). The proposed method also shows strong extensibility. The measurements on the fabricated 4-element MIMO antenna demonstrate that the proposed decoupling method can improve the isolation by 14 dB. The antenna shows good MIMO diversity performances with respect to the envelope correlation coefficient and diversity gain. Additionally, the antenna also works effectively in when the substrate is bent, which contributes to significantly increasing the applicability of the proposed method in comparison with the other reported methods.

Abstract Most current genotype imputation methods are reference-based, which posed several challenges to users, such as high computational costs and reference panel inaccessibility. Thus, deep learning models are expected to create reference-free imputation methods performing with higher accuracy and shortening the running time. We proposed a imputation method using recurrent neural networks integrating with an additional discriminator network, namely GRUD. This method was applied to datasets from genotyping chips and Low-Pass Whole Genome Sequencing (LP-WGS) with the reference panels from The 1000 Genomes Project (1KGP) phase 3, the dataset of 4810 Singaporeans (SG10K), and The 1000 Vietnamese Genome Project (VN1K). Our model performed more accurately than other existing methods on multiple datasets, especially with common variants with large minor allele frequency, and shrank running time and memory usage. In summary, these results indicated that GRUD can be implemented in genomic analyses to improve the accuracy and running-time of genotype imputation.

This paper introduces the design of a circularly polarized metasurface-based antenna array for C-band satellite applications that owns broadband operation and high gain characteristics. The single radiating element comprises a Y-shape patch and an above-placed 2 × 2 unit-cell metasurface. Further improvement in operating bandwidth and broadside gain is achieved by arranging four single elements in a 2 × 2 configuration and a sequential-phase feed network. A prototype has been fabricated and measured to validate the feasibility of the proposed antenna array. The measured operating bandwidth is 20% (4.50–5.50 GHz), which is an overlap between a −10 dB impedance bandwidth of 29.8% (4.50–5.99 GHz) and a 3 dB axial ratio bandwidth of 20% (4.50–5.50 GHz). Across this operating band, the peak broadside gain is 10.5 dBi. Compared with the recently published studies, the proposed array is a prominent design for producing a wide operating bandwidth and relatively high gains while maintaining the overall compact dimensions.

Anthrax, a widespread zoonosis in low and middle-income countries with low disease awareness and insufficient livestock vaccination coverage, has been known in Lao Cai Province in northern Vietnam for years before its apparent absence in 2009, which requires investigation as this infection is frequently reported from neighbouring provinces and countries. We aimed to describe the seasonal patterns of anthrax (1991-2008), compare livestock anthrax vaccine coverage to disease occurrence (1991- 2022), and delineate the high-risk areas to inform local disease surveillance in the province. We illustrated the seasonal pattern of anthrax and provided a comparison between livestock vaccine coverage and disease occurrence by purely spatial SaTScan (Poisson model, 25% population at risk) to detect spatial clusters of human and livestock anthrax using population derived from zonal statistics routines. The number of cases, crude cumulative incidence, and spatial clusters of human and livestock anthrax were mapped in QGIS. Results indicate peak anthrax incidence from May to October. Buffalo, domestic cattle, and horses accounted for 75% of total animal cases. Horse anthrax was more common in Lao Cai than in its neighbours and often occurred in years with human mortality. Vaccination covered less than 30% of the livestock population. We found an apparent pattern where anthrax was controlled from 1998-2003 with higher vaccine coverage (>20%) and identified spatial clusters of human and livestock anthrax in Muong Khuong, Bao Thang, and Bac Ha districts of Lao Cai. The local public health and veterinary agencies are recommended to revisit the high-risk areas and communicate with neighbouring provinces for a regional approach to anthrax surveillance and control.

ABSTRACT Siderophores are secreted ferric ion chelators used to obtain iron in nutrient-limited environmental niches, including human hosts. While all Escherichia coli express the enterobactin (Ent) siderophore system, isolates from patients with urinary tract infections additionally express the genetically distinct yersiniabactin (Ybt) siderophore system. To determine whether the Ent and Ybt systems are functionally redundant for iron uptake, we compared the growth of different isogenic siderophore biosynthetic mutants in the presence of transferrin, a human iron-binding protein. We observed that Ybt expression does not compensate for deficient Ent expression following low-density inoculation. Using transcriptional and product analysis, we found this non-redundancy to be attributable to a density-dependent transcriptional stimulation cycle in which Ybt functions as an autoinducer. These results distinguish the Ybt system as a combined quorum-sensing and siderophore system. These functions may reflect Ybt as a public good within bacterial communities or as an adaptation to confined, subcellular compartments in infected hosts. This combined functionality may contribute to the extraintestinal pathogenic potential of E. coli and related Enterobacterales.IMPORTANCEPatients with urinary tract infections are often infected with Escherichia coli strains carrying adaptations that increase their pathogenic potential. One of these adaptations is the accumulation of multiple siderophore systems, which scavenge iron for nutritional use. While iron uptake is important for bacterial growth, the increased metabolic costs of siderophore production could diminish bacterial fitness during infections. In a siderophore-dependent growth condition, we show that the virulence-associated yersiniabactin siderophore system in uropathogenic E. coli is not redundant with the ubiquitous E. coli enterobactin system. This arises not from differences in iron-scavenging activity but because yersiniabactin is preferentially expressed during bacterial crowding, leaving bacteria dependent upon enterobactin for growth at low cell density. Notably, this regulatory mode arises because yersiniabactin stimulates its own expression, acting as an autoinducer in a previously unappreciated quorum-sensing system. This unexpected result connects quorum-sensing with pathogenic potential in E. coli and related Enterobacterales.

In assessing the bending attributes for geopolymer composites augmented with uni-directional fibers, methodologies aligned with the established American and European standards yield quantifiable values for flexural strength, denoted as σm*, and its corresponding elasticity modulus, E*. Notably, these values exhibit a pronounced dependency on the size of the testing parameters. Specifically, within a judicious range of support span L relative to specimen height H, spanning a ratio of 10 to 40, these metrics can vary by a factor between 2 and 4. By conducting evaluations across an extensive array of H/L ratios and adhering to the protocols set for comparable composites with a plastic matrix, it becomes feasible to determine the definitive flexural elastic modulus E and shear modulus G, both of which can be viewed as size-neutral material traits. A parallel methodology can be employed to deduce size-agnostic values for flexural strength, σm. The established linear relationship between the inverse practical value E* (1/E*) and the squared ratio (H/L)2 is acknowledged. However, a congruent 1/σm* relationship has been recently corroborated experimentally, aligning primarily with Tarnopolsky’s theoretical propositions. The parameter T, defined as the inverse gradient of 1/σm* about (H/L)2, is integral to these findings. Furthermore, the significance of the loading displacement rate is underscored, necessitating a tailored consideration for different scenarios.

This study presents an approach to synthesizing a mathematical model for determining the composition of geopolymer foams. The focus is on improving the accuracy of multicriteria optimization for metakaolin-based geopolymer composite composition. Experimental data on the physical and mechanical properties of geopolymers are digitized to establish the computational basis for these calculations. Optimization criteria include density, porosity, compressive strength, flexural strength, Young's modulus, volumetric heat capacity, thermal diffusivity, and thermal conductivity. In addition, parameters such as shrinkage, processability, adsorption, adhesion, and economic aspects are also considered. The proposed format aims to fine-tune the geopolymer composite formulation by using the developed model for multi-criteria analysis of technological and physical-mechanical properties of foamed geopolymer composite materials (FGCM). A synthesis of mathematical models including the main criterion, suboptimization, generalized criterion, lexicographic optimization, sorting of alternatives, interval values, and decision tree methods was used to develop methods for multi-criteria optimization of the composition of foamed geopolymers. The study additionally uses the method of criteria convolution, in which the indices of specific criteria are modified in the form of a ratio scale to clarify the limits and boundaries of changes in the composition of the geopolymer mixture. This minimizes contradictory conclusions and expert opinions and highlights the extreme values for each group of parameters. By filtering the raw information, the accuracy of estimates is improved. The exclusivity of the proposed model for determining the composition of foamed geopolymers lies in the possibility of selecting the necessary formulation by mathematical processing of digitized information of the results of measurements of physical-mechanical and operational-technological properties according to the proposed innovative algorithms and schemes. Compared to existing methods, the focus of the proposed method allows for solving problems that are inaccessible to direct observation. This is due to the discovery of hidden information about the interaction of structural and strength parameters. Combining subjective and objective elements of the choice of the optimal geopolymer formulation, the proposed methodology of information processing allows for improving the quality of determining the optimal composition of the geopolymer mixture. The results of multicriteria optimization for foamed geopolymer indicate that the optimal component composition of the geopolymer matrix, within the selected range of variation, consists of 100g metakaolin, 90g potassium activator, 5g silica fume, 100g silica sand, 7g basalt fiber, and 3g aluminum. These proportions yield the best mechanical, thermal, and technological properties.

Structural damage in the steel bridge anchorage, if not diagnosed early, could pose a severe risk of structural collapse. Previous studies have mainly focused on diagnosing prestress loss as a specific type of damage. This study is among the first for the automated identification of multiple types of anchorage damage, including strand damage and bearing plate damage, using deep learning combined with the EMA (electromechanical admittance) technique. The proposed approach employs the 1D CNN (one-dimensional convolutional neural network) algorithm to autonomously learn optimal features from the raw EMA data without complex transformations. The proposed approach is validated using the raw EMA response of a steel bridge anchorage specimen, which contains substantial nonlinearities in damage characteristics. A K-fold cross-validation approach is used to secure a rigorous performance evaluation and generalization across different scenarios. The method demonstrates superior performance compared to established 1D CNN models in assessing multiple damage types in the anchorage specimen, offering a potential alternative paradigm for data-driven damage identification in steel bridge anchorages.

In order to address the Multi-Objective Optimization Problem (MOOP) in building a two-stage helical gearbox, this work presents a novel application of the Multi-Criterion Decision-Making (MCDM) method. The aim of the study is to determine the optimal primary design factors that will increase gearbox efficiency while decreasing gearbox volume. Three main design parameters were chosen for assessment in this work: the first stage’s gear ratio, and the first and second stages’ Coefficients of Wheel Face Width (CWFW). In addition, the MOOP is divided into two phases: phase 1 solves the single-objective optimization problem to reduce the gap between variable levels, and phase 2 solves the MOOP to determine the optimal primary design factors. Furthermore, the Entropy approach was picked to compute the weight criteria, and the MARCOS method was chosen as an MCDM method to handle the multi-objective optimization issue. The following are important characteristics of the study: Firstly, the MCDM method (MARCOS technique) was successfully applied to solve a MOOP for the first time. Secondly, this work has looked into power losses during idle motion to calculate the efficiency of a two-stage helical gearbox. The results of the study were used in the design of a two-stage helical gearbox in order to identify the optimal values for three important design parameters.

This paper proposes a compact design of dual-sense circularly polarized (CP) antenna for simultaneous transmit (Tx) and receive (Rx) communication systems. The primary radiating aperture of the proposed antenna is a 2 × 2 unit-cell metasurface (MS). The MS is excited by the asymmetric patch in the center, which acts as the CP source of the whole antenna structure. By properly tuning the feeding positions, dual-sense CP with high isolation can be achieved. For verification, an antenna prototype with compact dimensions of 0.36λ × 0.36λ × 0.02λ (λ is the free-space wavelength at the center operating frequency) is fabricated and measured. The measured operating bandwidth is 1.6% (2.45-2.49 GHz), in which the reflection and transmission coefficients are less than-10 dB and the axial ratio is lower than 3 dB. Within this band, the maximum isolation value is 39 dB, and the peak gain is 5.7 dBi.

Early neurological deterioration (END) is progressive neurological deterioration with an increase in NIHSS score of 2 points or more in the first 72 hours from the onset of acute ischemic stroke. END increases the risk of poor clinical outcomes at day 90 of ischemic stroke. We will study the frequency, predictors, and outcomes of patients with END in a case-control study at a comprehensive stroke centre in Vietnam. of the design is a descriptive observational study, longitudinal follow-up of patients with minor stroke hospitalized at the Stroke Center of Bach Mai Hospital from December 1, 2023, to December 1, 2024. Minor stroke patients characterized by NIHSS score ≤ 5 hospitalized within 24 hours of symptom onset will be recruited. The estimated END rate is about 30%, relative accuracy ε = 0.11, 95% reliability, expected 5% of patients lost data or follow-up, and an estimated sample size of 779 patients. This study will help determine the END rate in patients with minor stroke and related factors, thereby building a prognostic model for END. Our study determined the END rate in patients with minor stroke in Vietnam and also proposed risk factors for minor stroke management and treatment.

A multiple-input-multiple-output (MIMO) antenna system with low-profile and small element spacing characteristics is presented in this paper. This antenna contains multiple elements arranged in both E-plane and H-plane configurations. The original strong coupling between the MIMO elements can be suppressed by exciting orthogonal operating modes. To achieve this, a half-wavelength microstrip line and a quarter-wavelength grounded stub are utilized to decouple the H- and E-plane MIMO arrays. A 2 × 2 antenna prototype is fabricated and measured to demonstrate the decoupling concept's feasibility. The measured impedance bandwidth is from 4.78 to 4.81 GHz. Across this band, the isolation is better than 15 dB with extremely small edge-to-edge distances of 0.032λ and 0.026λ in the E- and H-plane, respectively. Featuring the simple decoupling structure, small element spacing, and the capability of extending to a large-scale 2 × N array, the proposed antenna can be used for 5G Internet of Things (IoT) applications operating at the N79 frequency band.

This study investigates the sulfuric acid hydrolysis process to improve the efficiency of paper waste sludge (PWS) hydrolysis in a paper recycling plant. The Response Surface Methodology (RSM) was used to evaluate the influence of factors, including liquid-to-solid ratio, acid concentration, temperature, and time on the hydrolysis process. The optimal conditions for hydrolysis were determined to be a solid-to-liquid ratio of 1/30.15, an acid concentration of 8.17 wt%, at a temperature of 91.31 ?, and a reaction time of 6.15 h, which yielded the highest sugar content of 11.12 g.L-1 (with the hydrolysis efficiency of 61.4 %). The resulting sugar solution was then fermented by Acetobacter xylinum bacteria to produce bacterial cellulose (BC) layers. This study addresses the environmental organic pollution caused by PWS and transforms it into a more valuable form with high carbon content and purity, such as BC.

Background: The novel coronavirus disease 2019 (COVID-19) has raised many concerns among populations worldwide due to its high mortality and morbidity with the lack of treatment options. Many attempts to find preventive and curable approaches have been proposed to prevent infections. The consumption of herbal products or plant extracts was recommended to modulate the body's immunity and reduce the risk of diseases. Methods: In the current study, we evaluated the anti-viral effects of a mixed herbal formula, named Ssanti-Covir, which was obtained from a combination of 8 herbal species extensively employed in traditional medicine in Vietnam. The objective was to investigate the potential efficacy of Ssanti-Covir against COVID-19 infections in vero E6 cells, as well as its immunostimulatory effects on immunosuppressive mice induced by cyclophosphamide (CP). Results: The results of the study revealed that Ssanti-Covir contained significant amounts of andrographolide, silybin A, and silybin B, with concentrations of 137.08 mg/g, 72.01 mg/g, and 81.62 mg/g, respectively. Pre-incubation of Ssanti-Covir at various dilution concentrations effectively prevented cells from being infected by COVID-19, with a viral titer of 100 TCID50/0.1 ml. Oral administration of Ssanti-Covir at doses of 384 mg/kg and 576 mg/kg body weight resulted in a significant increase in the relative weight of the spleen and thymus in mice induced with CP, with p-values of

Machilus thunbergii has a history of traditional applications including treating dyspepsia, apoplexy, headaches, abdominal pain, abdominal distension, and leg edema [1]. It is also employed for alleviating allergies, inflammation, pain relief, promoting blood circulation, addressing costal chondritis, and sinusitis [2]. Research into the chemical composition of M. thunbergii has revealed the presence of lignans, flavonoids, lactones, and essential oils [1,3-5]. While some investigations have explored the inhibitory effects of extracts and lignan compounds from this species on NO production [6–8], there has been no research into the flavonoids isolated from this plant and their potential for inhibiting NO production, given our reachable referencing. The ethyl acetate (EtOAc) soluble fraction of M. thunbergii leaves was subjected to column chromatography (CC) using silica gel and Sephadex LH-20 for compound isolation. Nuclear magnetic resonance (NMR) data primarily facilitated the determination of isolated compound structures. Anti-inflammatory activity was evaluated against lipopolysaccharide (LPS)-induced nitric oxide (NO) production in macrophage RAW264.7 cells. Anti-inflammatory activity-guided fractionation led to the isolation of twelve secondary metabolites (1−12). The compounds were identified as quercetin (1), kaempferol (2), rhamnetin (3), quercitrin (4), hyperoside (5), reynoutrin (6), guaijaverin (7), afzelin (8), astragalin (9), rutin (10), kaempferol-3-O-rutinoside (11), and rhamnetin-3-O-rutinoside (12). Compounds 3, 5, 6, 9, 11, and 12 were isolated from M. thunbergii for the first time. Evaluation against LPS-induced NO production in macrophage RAW264.7 cells showed that 1−3 exhibited potent inhibitory activity with IC50 values of 15.45, 25.44, and 19.82 µM, respectively. Compounds 4−9 demonstrated IC50 values ranging from 42.15 to 67.42 µM, while 10−12 exhibited inactivity (IC50 > 100 µM).

Prostatic abscess (PA) prevalence has decreased in the era of antibiotics. This condition is associated with chronic conditions, including diabetes, immunodeficiency, liver disease, or even severe diseases such as prostate cancer. Concomitant prostatic abscess and prostate cancer are very challenging to treat because of the lack of specific guidelines, significant complications, and controversial treatment approaches. By reporting a case with prostate cancer in the setting of a prostatic abscess treated successfully by surgery, we propose a 2-steps approach including transurethral resection drainage followed by laparoscopic radical prostatectomy.

In this paper, ZnO nanorods were synthesized by the hydrothermal method and used as anodes for zinc-silver batteries. The Tafel and EIS curve analysis results show that ZnO nanorods have better anti-corrosion and charge transport properties than ZnO powders. At 0.1 C discharge conditions, the ZnO electrode exhibits more stable cycle efficiency than the powder electrode; after 25 cycles, the capacity is higher by 95%. The superior electrochemical performance is due to the ZnO nanorods having the ability to conduct electrons and increase the surface area. Therefore, the possible growth mechanism of ZnO nanorods has been investigated.

Population genomic analyses and palaeogeographical modelling combine to help infer the ancient migration of humans into South Asia from Sundaland, driven by rapid sea level rises.

Additive manufacturing (AM), commonly named 3D printing, is a promising technology for many applications. It is the most viable option for widespread use in automated construction processes, especially for harsh environments such as underwater. Some contemporary applications of this technology have been tested in underwater environments, but there are still a number of problems to be solved. This study focuses on the current development of 3D printing technology for underwater applications, including the required improvements in the technology itself, as well as new materials. Information about underwater applications involving part fabrication via AM is also provided. The article is based on a literature review that is supplemented by case studies of practical applications. The main findings show that the usage of additive manufacturing in underwater applications can bring a number of advantages—for instance, increasing work safety, limiting the environmental burden, and high efficiency. Currently, only a few prototype applications for this technology have been developed. However, underwater additive manufacturing is a promising tool to develop new, effective applications on a larger scale. The technology itself, as well as the materials used, still require development and optimization.

A method to significantly improve the isolation of multiple-input-multiple-output (MIMO) antenna is presented in this paper. The proposed design consists of multiple patches arranged in the H-plane configuration. Satisfactory isolation is obtained by using microstrip lines that are positioned along the radiating edges of the patches. The function of the decoupled lines is to excite an orthogonal polarization mode on the non-excited patch. A two-element array is fabricated to demonstrate the effectiveness of the proposed decoupling structure. The experimental results illustrate that the isolation of the 2-element MIMO antenna can be significantly improved by about 26 dB with an extremely small element spacing of $0.017 \lambda _{0}$ . Besides, the antenna exhibits good diversity performances. The decoupling method is also applicable to a multiple-element MIMO antenna. Compared to other related works, the proposed design has the smallest element spacing while achieving high isolation. The antenna can be used for 5.2 WLAN applications.

This paper introduces a compact antenna with bandwidth reconfigurable and flexible characteristics for cognitive radio applications. The antenna consists of a monopole as a primary radiator and is excited by a coplanar waveguide to have a single-layer design. To adjust the operating bandwidth (BW) by fixing the lower frequency and varying the upper one, an additional stub is connected to the feeding line. This stub causes a disturbance in the current distribution, which significantly degrades the matching performance. By controlling its length, the rejected band can be changed and thus, the upper frequency is varied. To validate the proposed approach, two stubs are used, and they are connected to the feeding line through two PIN diodes. By switching the ON/OFF state of the diodes, three different states with different operating BW are attained. The fractional BWs for these states are 18.9, 33.2, and 64.3% respectively. Besides, it is also worth noting that the antenna achieves good performance when bent over a curved surface.

A compact metasurface (MS) based MIMO antenna with wideband operation and high isolation characteristics is proposed for sub-6 GHz applications. A single element is constructed by a slot coupled with $2\times $ 2 unit cells MS. For mutual coupling suppression, the MS of each MIMO element is grounded at proper positions by metallic vias. Compared to other reported designs, the proposed antenna possesses several unique features including a simple decoupling method with no extra space requirement, compact size, and wideband operation. For verification, the measurements have been implemented on a fabricated prototype with overall dimensions of $0.85\lambda _{c} \times 0.48\lambda _{c} \times 0.03\lambda _{c}$ ( $\lambda _{c}$ is the free-space wavelength at center operating frequency) and the center-to-center element spacing of $0.43\lambda _{c}$ . The measured results indicate that the proposed design has a wide operating bandwidth of 15% ( $3.7-4.3$ GHz) with high isolation of better than 25 dB. In addition, the measured maximum gain is about 4.1 dBi, and good diversity performance is also achieved. The proposed MIMO antenna is a potential candidate for 5G applications operating at the NR77 band.

This paper shows a method to reduce the mutual coupling between extremely closely spaced circularly polarized (CP) multiple-input-multiple-output (MIMO) antenna. The strong coupling between dual-sense CP MIMO elements is thoroughly investigated and a method to effectively suppress the mutual coupling by controlling the phase of the coupled signal is proposed. High isolation can be achieved by using a grounded stub, which is positioned along the edges of radiating elements. An antenna prototype is fabricated and measured to verify the feasibility of the utilized decoupling scheme. The measured results show an operating bandwidth of 2.1% (5.21-5.32 GHz) with isolation of better than 20 dB. The poor isolation of the coupled MIMO is significantly enhanced to 38 dB with the use of the proposed decoupling network. A 33 dB improvement can be attained with an extremely small edge-to-edge distance of $0.017\lambda _{c}$ and center-to-center spacing of $0.23\lambda _{c}$ at the center frequency. Compared to other related works, the proposed antenna features the smallest element spacing while achieving high isolation enhancement.

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance.

Artificial Neural Network (ANN) has been widely used for Structural Health Monitoring (SHM) in the last decades. To detect damage in the structure, ANN often uses input data consisting of natural frequencies or mode shapes. However, this data is not sensitive enough to accurately identify minor structural defects. Therefore, in this study, we propose to use transmissibility to generate input data for the input layer of ANN. Transmissibility uses output signals exclusively to preserve structural dynamic properties and is sensitive to damage characteristics. To evaluate the efficiency of the proposed approach, a cable-stayed bridge with a wide variety of damage scenarios is employed. The results show that the combination of transmissibility and ANN not only accurately detect damages but also outperforms natural frequencies-based ANN in terms of accuracy and computational cost.

Abstract Perturbations in the gut microbiome have been associated with colorectal cancer (CRC), with the colonic overabundance of Fusobacterium nucleatum shown as the most consistent marker. Despite its significance in the promotion of CRC, genomic studies of Fusobacterium is limited. We enrolled 43 Vietnamese CRC patients and 25 participants with non-cancerous colorectal polyps to study the colonic microbiomes and genomic diversity of Fusobacterium in this population, using a combination of 16S rRNA gene profiling, anaerobic microbiology, and whole genome analysis. Oral bacteria, including F. nucleatum and Leptotrichia, were significantly more abundant in the tumour microbiomes. We obtained 53 Fusobacterium genomes, representing 26 strains, from the saliva, tumour and non-tumour tissues of six CRC patients. Isolates from the gut belonged to diverse F. nucleatum subspecies (nucleatum, animalis, vincentii, polymorphum) and a potential new subspecies of Fusobacterium periodonticum. The Fusobacterium population within each individual was distinct and in some cases diverse, with minimal intra-clonal variation. Phylogenetic analyses showed that within four individuals, tumour-associated Fusobacterium were clonal to those isolated from non-tumour tissues. Genes encoding major virulence factors (Fap2 and RadD) showed evidence of horizontal gene transfer. Our work provides a framework to understand the genomic diversity of Fusobacterium within the CRC patients, which can be exploited for the development of CRC diagnostic and therapeutic options targeting this oncobacterium.

Abstract Proactive Fault tolerant (FT) approaches for infrastructure's cloud computing which have been increasingly developed in research scope with the support of machine learning need consistent monitoring and highly accurate predicting systems. However, it is difficult to implement the proactive fault tolerant approach of infrastructure's cloud computing because of complex architecture, dynamic services, and many interdependent factors existing in cloud environment. To overcome this problem, a proactive FT approach for cloud‐hosted application is proposed to achieve a high degree of automation, including physical machine (PM) fault analysis and self‐learning virtual machine (VM) migration. It is based on MAPE‐K (Monitor‐Analyze‐Plan‐Execute over a shared Knowledge) loop to take into account the knowledge inside controllers in run time. To evaluate PM fault analysis model, the web e‐Commerce is deployed by OpenStack Stein while the prototype of VM migration component is built by CloudSim for VM migration solution evaluation. The effectiveness of the approach is demonstrated in experiment results.

BackgroundStreptococcus pneumoniae is the most common bacterium that causes community-acquired pneumonia (CAP) in children. The rate of S. pneumoniae resistance to antibiotics is increasing, particularly in patients with severe CAP. Therefore, the level of antibiotic resistance of S. pneumoniae causing severe CAP in Vietnamese children requires regular monitoring.MethodsThis was a cross-sectional descriptive study. Nasopharyngeal aspiration specimens from children were cultured, isolated, and examined for S. pneumoniae. Bacterial strains were assessed for antimicrobial susceptibility, and the minimum inhibitory concentration (MIC) was determined.ResultsEighty-nine strains of S. pneumoniae were isolated from 239 children with severe CAP. The majority of isolates were completely non-susceptible to penicillin (1.1% intermediate, 98.9% resistant) and highly resistant to erythromycin (96.6%) and clarithromycin (88.8%); the rate of resistance to ceftriaxone was 16.9%, with the proportion of intermediate resistance at 46.0%; 100% of strains were susceptible to vancomycin and linezolid. For most antibiotics, MIC50 and MIC90 were equal to the resistance threshold according to the Clinical and Laboratory Standards Institute 2021; penicillin had an eight-fold increase in MIC90 (64 mg/L) and ceftriaxone had a 1.5-fold increase in MIC90 (6 mg/L).ConclusionStreptococcus pneumoniae isolates described in this study were resistant to many antibiotics. Penicillin should not be the first-line antibiotic of choice, and ceftriaxone at an enhanced dose should be used instead.

Abstract A 44‐year‐old woman at 30 weeks of pregnancy was admitted to the Intensive Care Unit with a diagnosis of severe COVID‐19 pneumonia. Her condition worsened quickly, defined by prolonged hypoxia even with intensive therapy and oxygen supplementation. This led to the decision to perform a caesarean delivery and continue pulse corticosteroids therapy after delivery. Soon after she recovered from COVID‐19 pneumonia, her life was threatened again by septic shock from hospital‐acquired pneumonia. After nearly 1 month of hospitalization, she was discharged and fully recovered on the re‐examination day 10 months later.

In the current context, an attempt is being made to improve the electrical discharge machining (EDM) process by using powder particles in a suitable combination. To improve the quality of such procedures, the process parameters should be optimized. The present study proposes to utilize Taguchi–Grey relational analysis to discover the optimal combination of process parameters for SKD61 die steel specimens using titanium powder-mixed EDM (PMEDM). Among the machining parameters chosen, the optimal combination of current (3 A), pulse on-time (37 μs), pulse off-time (37 μs), and powder concentration (4 g/L) was determined experimentally. Due to its relevance in spark energy production, peak current is a more significant factor in PMEDM processes. A superior surface topography was obtained with increased microhardness and fewer microfractures over machined specimens with optimal process parameter in PMEDM. The titanium particles can effectively enhance the surface performance measures during PMEDM-based machining owing to tiny craters and pores with better lubrication.

Abstract Although stretchable electroluminescent (EL) devices have been the research hotspots for decades because of their enormous market value in lighting sources and displays, fabrication of the stretchable EL device through a simple, cost-effective, and scalable method still remains an open issue. Here, a novel all solution-processed method is developed to fabricate a high-performance alternative current electroluminescent (ACEL) device based on copper nanowires (Cu NWs). The Cu NW-based electrode exhibited a low resistance change of less than 10% after 1000 stretching cycles at a tensile strain of 30% and the resistance variation of the electrode in one stretching-releasing cycle was less than 1% at the 1000th. To substantiate suitability for the wearable application, the ACEL device was stretched at a tensile strain of 100% and it retained a luminance of 97.6 cd/m2. Furthermore, the device works well under different deformations such as bending, folding, rolling, and twisting. To the best of our knowledge, this is the first demonstration of Cu NWs applied in a stretchable ACEL, promising cost-effective electrode materials for various wearable electronics applications.

Clematis armandii has been used in many Chinese traditional patent medicines all over the world as a form of Caulis Clematidis Armandii. However, it has often been adulterated by Aristolochia manshuriensis, and Iodes vitiginea. A. manshuriensis must not be part of any herbal medicines because it contains aristolochic acid I, a nephrotoxin and potential carcinogen. The current pharmacopoeial methods have had limitation for differentiation of C. armandii from its adulterants. Thus, a specific, comprehensive, sensitive, and reproducible HPTLC/HPLC for quality control of C. armandii was proposed. Oleanolic acid from C. armandii has been isolated by vacuum liquid chromatography and column chromatography. The purified compound has been identified using Ultra Violet spectrophotometry (UV–Vis), Fourier Transform Infrared (FTIR), mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Therefore, oleanolic acid should be detected for positive identification of Caulis Clematis Armandii. Minimum content of oleanolic acid can be evaluated by the validated HPTLC procedure proposed as well.

Abstract Despite improvements in medical care, the burden of sepsis remains high. In this study, we evaluated the incremental cost associated with postoperative sepsis and the impact of postoperative sepsis on clinical outcomes among surgical patients in Vietnam. We used the national database that contained 1,241,893 surgical patients undergoing seven types of surgery. We controlled the balance between the groups of patients using propensity score matching method. Generalized gamma regression and logistic regression were utilized to estimate incremental cost, readmission, and reexamination associated with postoperative sepsis. The average incremental cost associated with postoperative sepsis was 724.1 USD (95% CI 553.7–891.7) for the 30 days after surgery, which is equivalent to 28.2% of the per capita GDP in Vietnam in 2018. The highest incremental cost was found in patients undergoing cardiothoracic surgery, at 2,897 USD (95% CI 530.7–5263.2). Postoperative sepsis increased patient odds of readmission (OR = 6.40; 95% CI 6.06–6.76), reexamination (OR = 1.67; 95% CI 1.58–1.76), and also associated with 4.9 days longer of hospital length of stay among surgical patients. Creating appropriate prevention strategies for postoperative sepsis is extremely important, not only to improve the quality of health care but also to save health financial resources each year.

Physical layer security is a promising research direction for the fifth-generation and beyond networks. This paper investigates the physical layer security of massive multiple-input multiple-output (MIMO) systems over spatially-uncorrelated Rician fading channels in time-division duplex mode. In such systems, uplink training stage is required for the base station to estimate channel state information (CSI) for design downlink precoding matrices and for uplink data detection. Illegitimate users, or attackers, could intentionally send jamming signals during the training stage to degrade the quality of the CSI obtained at the base station, thus affecting the performance. In this paper, we propose a method for detecting the presence of an attacker. Based on the fundamental properties of Massive MIMO communication, the base station can treat the jamming signals as additive white Gaussian noise. A threshold to detect the existence of the attacker is, therefore, computed in closed-form expression with a sufficiently large number of antennas at the base station. The key merit of our proposed method is that it only requires statistical channel state information and two training time slots to detect the jamming activity. Numerical results show that our proposed attacker-detecting method is effective over various system parameter settings. Furthermore, the benefits of the dominant line-of-sight (LoS) components have been testified. In particular, the detection probability is improved by about 1.5 times with the presence of the LoS components, while the false-alarm probability gets improved by more than ten folds.

The process of damage identification in Structural Health Monitoring (SHM) gives us a lot of practical information about the current status of the inspected structure. The target of the process is to detect damage status by processing data collected from sensors, followed by identifying the difference between the damaged and the undamaged states. Different machine learning techniques have been applied to attempt to extract features or knowledge from vibration data, however, they need to learn prior knowledge about the factors affecting the structure. In this paper, a novel method of structural damage detection is proposed using a hybrid convolution neural network and recurrent neural network. A convolution neural network is used to extract deep features while recurrent neural network is trained to learn the long-term historical dependency in time series data. This proposed method which combines two types of features -spatial and temporal- helps to increase discrimination ability when being compared with the one that contains deep features only. Finally, the neural network is applied to categorize the time series into two states - undamaged and damaged. The accuracy of the proposed method was tested on a benchmark dataset of Z24-bridge (Switzerland). The result shows that the hybrid method provides a high level of accuracy in damage identification of the tested structure

This paper presents a multiple-input-multiple-output (MIMO) antenna array with low-profile and flexible characteristics. Multiple microstrip patches are arranged in the E-plane configuration and decoupled by shorted quarter-wavelength stubs. The antenna has a small element spacing of 0.032 λ, where λ is a free-space wavelength at the center frequency. To demonstrate the feasibility of the proposed concept, a 1 × 4 MIMO array prototype is fabricated. The measured results on the fabricated prototype demonstrate that the MIMO antenna has good operation features at 4.8 GHz with a reflection coefficient of less than -10 dB and an isolation of better than 20 dB. Besides, good radiation patterns and broadside gain of around 4.5 dBi are also attained. The antenna also works in the bending mode and has the capability of extending to large-scale MIMO arrays. Such attractive features prove the utility of the proposed antenna in various modern electronic devices.

This paper shows an effective method to significantly enhance the isolation of a closely spaced two-port patch antenna, which can be deployed for full-duplex transceivers as well as multiple-input-multiple-output (MIMO) systems. Two rectangular microstrip patches are arranged in the E-plane configuration. To achieve high isolation, a grounded stub is positioned between the radiating patches. For validation of the proposed concept, an antenna prototype is fabricated for measurements. The measured data demonstrates that the port-to-port mutual coupling can be suppressed to -50 dB, which is useful in self-interference cancellation for full-duplex communication systems. Compared with the coupled design, the isolation is significantly enhanced by 43 dB with an inter-element spacing of 0.034λc, where λc is a free-space wavelength at the center operating frequency. Regarding MIMO metrics, the antenna also shows good MIMO diversity performance based on an envelope correlation coefficient and a diversity gain.