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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.

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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 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.

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.

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.

Developing a compact circularly polarized (CP) antenna with good radiation characteristics for handheld radio frequency identification (RFID) readers is a very challenging task. Many compact CP antennas have been reported in the open literature, but most suffer from critical drawbacks of low gain and/or high back radiation. This paper presents a metasurface (MS) based CP antenna with compact size, high gain, and high front-to-back ratio characteristics. The compact size of the proposed design is achieved by using a 2 × 2 unit-cell MS, while the CP realization is accomplished through a coupling between the MS and a Y-shaped patch as a primary CP source. The final antenna has compact overall dimensions of 0.45λ × 0.45λ × 0.02λ, where λ is the guided wavelength at the center frequency. The operating bandwidth is about 2.0% (2.43-2.48 GHz) and the broadside gain is about 6.3 dBi. Besides, the front-to-back ratio (FBR) defined by the difference gain levels between the forward and backward directions is about 18 dB. Compared with the related compact CP antennas in the literature, the proposed design has the advantages of high gain and high FBR, making it suitable for compact RFID readers.

Introduction. Modern digital phased array antenna (DPAA) systems incorporate a large number of identical transceiver modules (TMs). These modules require real-time calibration with a high level of accuracy. In a previous work, we proposed a real-time calibration method for all receiver channels, which is based on the use of a calibration signal (CalSig) of the same frequency spectrum as the reflected signal and modulated in phase and amplitude by BPSK and OOK codes, respectively. This method was found to have a number of advantages over conventional approaches. However, the use of the same CalSig sample for all receiving channels increases the noise power gain at the output of a digital beam-forming unit (DBU). To overcome this limitation, we set out to improve the structure of CalSigs by making them pseudo-orthogonal. As a result, the noise power gain at the DBU output can be significantly reduced compared to that obtained in our previous work.Aim. To propose an improved design of a controlled amplitude modulation code OOK generator, which allows creation of pseudo-orthogonal CalSigs. As a result, the noise power gain at the output will increase insignificantly, thus having no negative effect on the quality of digital beam forming, signal processing and calibration.Materials and methods. Theory of system engineering and technology; theory of digital signal processing; system analysis; mathematical modeling.Results. An improved CalSig for calibrating the receiving channels of TMs was obtained. A structural diagram allowing the formation of pseudo-orthogonal CalSigs was synthesized.Conclusions. We proposed a new approach to improving the structure of signals used for real-time calibrating the DPAA receiving channels. A structural diagram of an amplitude-modulated OOK code generator for pseudo-orthogonal CalSigs was developed.

Recently, non-orthogonal multiple access (NOMA) has been considered as a promising technique in 5G network, and many investigations have addressed on the physical layer security to improve the security performance. In this paper, an alternative problem, where the eavesdropping process is considered as a legal activity, will be analyzed to track suspicious communications. More specifically, we study a wireless surveillance system in which the legitimate monitor is equipped with multi-antenna to overhear the messages between the suspicious receiver and the suspicious transmitter. Suspicious users are grouped into pairs and use the NOMA technique to transmit signals to a suspicious base station. Meanwhile, the legitimate monitor (LM) simultaneously transmits jamming signals, listens to suspicious links, decode-and-forward (DF) the eavesdropped information to the legitimate eavesdropper (LE). Based on the proposed mechanism, we investigate the power allocation policies for jamming signals of the legitimate monitor under deterministic and non-deterministic interference channel. Accordingly, we derive the closed-form expression of the successful eavesdropping probability for the best and the worst user to evaluate the system performance. Monte Carlo simulations are provided to verify our analytical results.

Background: At the early stage of the pandemic, severe COVID-19 was thought to be rare among pregnant women. However, cumulating data showed that gestational state is a risk factor for severe pneumonia, particularly due to the hyperinflammatory state. Recent reports suggested the efficacy of pulse corticosteroids in stopping the cytokine storm in people infected with SARS-CoV-2, but limited data exists regarding its use in pregnant women. Moreover, pregnancy termination is a treatment option in this population, but it has been reported mainly in the third trimester and rarely in the second trimester. Case Presentation: A 37-year-old woman infected with SARS-CoV-2 at 23 weeks of gestation presented with fatigue and dyspnea but soon deteriorated to severely acute respiratory failure and cytokine storm requiring mechanical ventilation combined with hemodialysis just one day after hospitalization. Low-dose corticosteroids and antibiotics were initiated, followed by antiviral therapy, anticoagulant and high-dose corticosteroid therapy. On hospital day 3, a decision to terminate her pregnancy was made; termination led to significant improvement in her clinical condition and a gradual decrease in demand for oxygen supplementation as well as the corticosteroid dose. She was discharged two weeks after admission. Conclusions: Due to the specific immune response, pregnant women with COVID-19 may differ from others in their clinical presentation, especially the probability of classic acute respiratory distress syndrome (ARDS). This report provides evidence related to the efficacy of pulse corticosteroids on this group and the influence of the mid-trimester termination on recovery.

In this paper, we analyze the secrecy outage probability (SOP) and the fairness of average packet transmission time for a non-orthogonal multiple access (NOMA) system which consists of a base station (BS) and two legal NOMA users in the presence of an eavesdropper (Eve). In order to extract the superimposed signal, the Eve is considered in two modes, i.e., successive interference cancellation (SIC) mode and parallel interference cancellation (PIC) mode. Accordingly, we analyze the secrecy performance of the considered system by deriving a new exact expression for SOP. Furthermore, the optimal power allocation between two legal users is determined such that the average transmission time from BS to two legitimate users are approximately equal to achieve the fairness of average packet transmission time. Monte Carlo simulations are provided to verify our analytical results.

In this paper, we investigate the secrecy performance of a Cooperative Cognitive Radio Network (CCRN) in the presence of an eavesdropper (EAV). The secondary users (SUs) are subject to three constraints which include peak transmit power level and interference limitation with respect to the primary user (PU) as well as secrecy outage constraints due to the EAV. Secrecy outage is achieved when the EAV cannot decode the targeted signal, but communications in the secondary network is still possible (non-zero capacity exists). Approximation expressions of the secrecy outage probability and the probability of non-zero secrecy capacity are derived to evaluate the secrecy performance. Monte Carlo simulations are provided to examine the accuracy of the derived approximation expressions. Based on this, power allocation policies for the SUs are derived, satisfying all the constraints while maximizing the secrecy performance as well as the quality of service performance of the secondary network. It can be concluded that with knowledge of the channel state information (CSI) of the EAV it is possible to calculate the optimal value for the secrecy outage threshold of the secondary user (SU) which in turn allows maximizing the secrecy performance. Most interestingly, our numerical results illustrate that the secrecy performance of the system is much improved when the parameters obtained using the CSI of the EAV are calculated optimally. Thence, the system can adjust the power allocation so that no eavesdropping occurs even without reducing quality of service (QoS) performance compared to a network without any EAV.

In this article, we consider the information leakage and outage probabilities of a multiple-input single-output (MISO) energy-harvesting (EH) Internet of Things (IoT) system in which a multiantenna ground base station (GBS) transmits messages to legitimate IoT destinations (LIDs) with the help of IoT relays (IRs) using non-orthogonal multiple access (NOMA) in the presence of a malicious jammer (MJ) and eavesdroppers (EAVs). The communication protocol is separated into two phases. In the EH phase, the IRs harvest energy from a power beacon (PB). In the information transmission (IT) phase, the communication process is further divided into two subphases: 1) The GBS broadcasts signals to the IRs using NOMA. Simultaneously, the MJ sends interfering signals to attack the IRs while the EAVs steal the confidential signals from the GBS, in a process called a cooperative attack. On the other hand, to protect the legitimate communication, an unmanned aerial vehicle (UAV) is used as a friendly jammer to defend against the EAVs. 2) A selected IR employs the time-switching-based relaying (TSR) technique to forward the received signal to the LIDs using NOMA. Similar to the first subphase, the LIDs are subjected to a cooperative attack, and the UAV attacks the EAVs in return. The secrecy performance of this communication protocol is characterized by deriving expressions for the information leakage probabilities (ILPs) for the LIDs' signals. A UAV altitude optimization algorithm is also proposed to achieve the best possible secrecy performance. Furthermore, we evaluate the system performance by deriving closed-form expressions for the outage probabilities (OPs). Accordingly, an algorithm is proposed to guarantee both the secrecy and system performance (in terms of the ILPs and OPs). Monte Carlo simulations are presented to verify our analytical results.

ABSTRACT Siderophores are iron chelators used by microbes to bind and acquire iron, which, once in the cell, inhibits siderophore production through feedback repression mediated by the ferric uptake repressor (Fur). Yersiniabactin (Ybt), a siderophore associated with enhanced pathogenic potential among Enterobacteriaceae, also binds copper ions during human and experimental murine infections. In contrast to iron, we found that extracellular copper ions rapidly and selectively stimulate Ybt production in extraintestinal pathogenic Escherichia coli. The stimulatory pathway requires formation of an extracellular copper-Ybt (Cu(II)-Ybt) complex, internalization of Cu(II)-Ybt entry through the canonical TonB-dependent outer membrane transporter, and Fur-independent transcriptional regulation by the specialized transcription factor YbtA. Dual regulation by iron and copper is consistent with a multifunctional metallophore role for Ybt. Feed-forward regulation is typical of stress responses, implicating Ybt in prevention of, or response to, copper stress during infection pathogenesis. IMPORTANCE Interactions between bacteria and transition metal ions play an important role in encounters between humans and bacteria. Siderophore systems have long been prominent mediators of these interactions. These systems secrete small-molecule chelators that bind oxidized iron(III) and express proteins that specifically recognize and import these complexes as a nutritional iron source. While E. coli and other Enterobacteriaceae secrete enterobactin, clinical isolates often secrete an additional siderophore, yersiniabactin (Ybt), which has been found to also bind copper and other non-iron metal ions. The observation here that an extraintestinal E. coli isolate secretes Ybt in a copper-inducible manner suggests an important gain of function over the enterobactin system. Copper recognition involves using Ybt to bind Cu(II) ions, consistent with a distinctively extracellular mode of copper detection. The resulting Cu(II)-Ybt complex signals upregulation of Ybt biosynthesis genes as a rapid response against potentially toxic extracellular copper ions. The Ybt system is distinguishable from other copper response systems that sense cytosolic and periplasmic copper ions. The Ybt dependence of the copper response presents an implicit feed-forward regulatory scheme that is typical of bacterial stress responses. The distinctive extracellular copper recognition-response functionality of the Ybt system may enhance the pathogenic potential of infection-associated Enterobacteriaceae.

Background A high prevalence of venom-induced consumption coagulopathy has been reported in individuals with viper snakebites. Rotational thromboelastometry (ROTEM) is a rapid technique that could be advantageous in assessing and monitoring coagulation disorders. Purpose To explore correlations between ROTEM and standard coagulation tests. Patients and methods This prospective observational study was performed among 41 patients with viper envenomation admitted to the Vietnam Poison Control Center from April 2016 to October 2017. Standard coagulation measurements [platelet count, prothrombin time (PT), activated partial thromboplastin time (aPTT), and fibrinogen level] and ROTEM indicators [clotting time (CT), amplitude (at set time: 5 and 10 minutes), clot information time (CFT) and maximum clot firmness (MCF) for extrinsic (EXTEM), intrinsic (INTEM), and fibrin based (FIBTEM) ROTEM] were obtained. Results For INTEM, EXTEM, the FIBTEM, proportions of patients with prolonged CT were 34.1%, 63.4%, and 61.0% respectively and the proportions of patients with decreased MCF were 62.2%, 62.2%, and 35.5%, respectively. Moderate correlations were observed between PT and EXTEM CT (r = 0.627), aPTT and INTEM CT (r = 0.626), fibrinogen and FIBTEM MCF (r = 0.723), and platelet count and EXTEM MCF (0.60). Conclusion ROTEM indicated a hypocoagulation state in patients with viper snakebite and was moderately correlated with standard coagulation parameters.

Radio direction finding system is a system that determines the direction or coordinates of radio signal sources. The main function of this system is to determine the direction of arrival (DOA) of an incident radio wave. DOA information plays an important role in array signal processing and has many applications in communications, radar, seismic survey, etc. In this study, we propose a method to estimate the DOA by using the simulated signal dataset obtained at the linear antenna array (ULA) and the suitable Long Short-Term Memory (LSTM) network model. The performance of the method is evaluated based on the root mean square error (RMSE) parameter and then is compared with 2 other algorithms, multiple signal classification (MUSIC) and deep neural network (DNN) in different cases such as deviation of incoming signals, variation of signal-to-noise ratio (SNR), and coherent incoming signals. The obtained results have shown that the proposed method has significantly improved accuracy compared to other methods.

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 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 method with combining two types of features increases discrimination ability when compares with it to 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.

Background Of the estimated 10 million people affected by (TB) each year, one-third are never diagnosed. Delayed case detection within the private healthcare sector has been identified as a particular problem in some settings, leading to considerable morbidity, mortality and community transmission. Using unannounced standardised patient (SP) visits to the pharmacies, we aimed to evaluate the performance of private pharmacies in the detection and treatment of TB.Methods A cross-sectional study was undertaken at randomly selected private pharmacies within 40 districts of Vietnam. Trained actors implemented two standardised clinical scenarios of presumptive TB and presumptive multidrug-resistant TB (MDR-TB). Outcomes were the proportion of SPs referred for medical assessment and the proportion inappropriately receiving broad-spectrum antibiotics. Logistic regression evaluated predictors of SPs’ referral.Results In total, 638 SP encounters were conducted, of which only 155 (24.3%) were referred for medical assessment; 511 (80·1%) were inappropriately offered antibiotics. A higher proportion of SPs were referred without having been given antibiotics if they had presumptive MDR-TB (68/320, 21.3%) versus presumptive TB (17/318, 5.3%; adjusted OR=4.8, 95% CI 2.9 to 7.8). Pharmacies offered antibiotics without a prescription to 89.9% of SPs with presumptive TB and 70.3% with presumptive MDR-TB, with no clear follow-up plan.Conclusions Few SPs with presumptive TB were appropriately referred for medical assessment by private pharmacies. Interventions to improve appropriate TB referral within the private pharmacy sector are urgently required to reduce the number of undiagnosed TB cases in Vietnam and similar high-prevalence settings.

Background: In Vietnam and Italy, breast cancer (BC) occurs in women more frequently than any other cancer. Vietnam has a substantially lower incidence of breast cancer than Italy, but a higher mortality rate. Most Vietnamese patients present to the hospital with severe tumors at the late stages of diagnosis. The purpose of this study was to compare clinicopathologic features, biomarkers, and subtypes of BC between Vietnamese women and Italian ones. Methods: The sample was collected from all Vietnamese patients undergoing surgery with the diagnosis of primary invasive breast carcinoma in Hue Central Hospital as well as Hue University Hospital in Vietnam during 1 year from April 2016 to April 2017, and from the same category of women in Sassari University Hospital, Italy during the year 2016. The study parameters in both groups consisted of age at diagnosis, tumor size, histologic grade, histologic type, axillary node status, stages of diagnosis, biomarkers (Estrogen Receptor - ER, Progesterone Receptor - PR, Ki-67 cell proliferation marker - Ki-67, Human epidermal growth factor receptor 2 - HER2), and molecular subtypes of BC. Results: 323 patients were collected in total (235 from Sassari, Italy, and 88 from Thua Thien - Hue province, Vietnam). Vietnamese patients were diagnosed at a younger age than Italian patients, at just 52.5 on average, while the figure for Italian was 62. The Vietnamese BC patients also had a bigger tumor in size, higher grade, more axillary node positivity as well as a later stage of disease in comparison with Italian ones. The proportion of ER-positive was higher in the Italian group than that in Vietnam (88.1 vs 55.7%). The high Ki-67 expression prevalence was significantly higher in Vietnamese patients compared with Italian (81.8 vs 45.1%). The HER2-positive rate in Vietnam was 33%, higher than that in Italy (8.1%). Histologic grade and cell proliferation index Ki-67 were significantly correlated with HER2 positivity in both groups. Conclusions: Vietnamese patients demonstrated more aggressive tumor features and worse prognostic biomarkers than Italian patients. The prevalence of HER2 positive and high Ki-67 expression in Vietnamese patients was considerably higher than in Italian patients. The remarkable differences in clinicopathological characteristics between the two populations suggest the diversity of biological tumor, ethnicity, and environment as well as the effectiveness of the screening program.

In this paper, we investigate the system performance of multihop energy harvesting (EH) wireless sensor networks (WSNs) with imperfect channel state information (CSI) using cooperative non-orthogonal multiple access (NOMA) and friendly jammers in the presence of multiple passive eavesdroppers (EAVs). Specifically, we propose a two-phase communication protocol consisting of EH and information transmission (IT). In the first phase, relays in all clusters harvest energy from power transfer station (PTS) signals. In the first time slot of the second phase, the gateway simultaneously broadcasts information and interference signals. In the subsequent time slots, a relay acting as a friendly jammer in each cluster uses the harvested energy to send an interference signal. Simultaneously, another EH relay applies the NOMA technique to transmit the information signal according to an optimal scheduling scheme based on the maximum signal-to-interference-plus-noise ratio (SINR) of a far user (MSm) and a near user (MSn). To ensure security performance, we propose an algorithm for determining the EH time constraint for a friendly jammer. Additionally, closed-form expressions for the outage probability and throughput of the considered system are derived. Accordingly, an optimal power allocation coefficient algorithm is proposed to achieve throughput fairness for pairs of users. The results of the mathematical analysis are verified by Monte Carlo simulations. Finally, the numerical results demonstrate that the MSn scheme is recommended for guaranteeing throughput fairness for pairs of users.

In this paper, we analyze the secrecy and throughput of multiple-input single-output (MISO) energy harvesting (EH) Internet of Things (IoT) systems, in which a multi-antenna base station (BS) transmits signals to IoT devices (IoTDs) with the help of relays. Specifically, the communication process is separated into two phases. In the first phase, the BS applies transmit antenna selection (TAS) to broadcast the signal to the relays and IoTDs by using non-orthogonal multiple access (NOMA). Here, the relays use power-splitting-based relaying (PSR) for EH and information processing. In the second phase, the selected relay employs the amplify-and-forward (AF) technique to forward the received signal to the IoTDs using NOMA. The information transmitted from the BS to the IoTD risks leakage by the relay, which is able to act as an eavesdropper (EAV) (i.e., an untrusted relay). To analyze the secrecy performance, we investigate three schemes: random-BS-best-relay (RBBR), best-BS-random-relay (BBRR), and best-BS-best-relay (BBBR). The physical layer secrecy (PLS) performance is characterized by deriving closed-form expressions of secrecy outage probability (SOP) for the IoTDs. A BS transmit power optimization algorithm is also proposed to achieve the best secrecy performance. Based on this, we then evaluate the system performance of the considered system, i.e., the outage probability and throughput. In addition, the impacts of the EH time, the power-splitting ratio, the numbers of BS antennas, and the numbers of untrusted relays on the SOP and throughput are investigated. The Monte Carlo approach is applied to verify our analytical results. Finally, the numerical examples indicate that the system performance of BBBR is greater than that of RBBR and BBRR.

Scutellaria radix is one of the ancientest approaches to treat diseases. The aim of this study was to investigate the effect of Scutellaria radix on the immune responses of Macrobrachium rosenbergii by reverse-gavage feeding and their protection against Lactococcus garvieae. In brief, M. rosenbergii was injected with S. radix water extract at 1, 5 and 10 µg/µl via reverse-gavage feeding (RGF). Phenoloxidase (PO) activity of hemocytes and prophenoloxidase (proPO) gene of hepatopancreas were assessed to determine M. rosenbergii immunity. The results revealed that the concentration of S. radix extract at 5 µg/µl enhanced significantly the phenoloxidase of M. rosenbergii correlated with the control group. For pro PO were up-regulated by all concentration in a time-dependent manner. The highest percentage of survival rates was observed at 5 µg/µlof S. radix water extract after challenged with L. garvieae. The present discoveries suggest that S. radix water extract at the concentration of 5 µg/µlmay raise the immune responses and gene expressions in M. rosenbergii using RGF.

In this paper, we investigate downlink cooperative multiple-input single-output wireless sensor networks with the nonorthogonal multiple access technique and simultaneous wireless information and power transfer over Nakagami-m fading. Specifically, the considered network includes a multiantenna sink node, an energy-limited relay cluster, a high-priority sensor node (SN) cluster, and a low-priority SN cluster. Prior to transmission, a transmit antenna, a relay, a high-priority SN, and a low-priority SN are selected. In this paper, we propose three antenna-relay-destination selection schemes, i.e., sink node-high-priority, sink node-relay, and sink node-low-priority. In each proposed scheme, we consider two relaying strategies, i.e., decode-and-forward and amplify-and-forward, and then, we derive the corresponding closed-form expressions of outage probability at the selected SNs. In addition, we introduce two algorithms: 1) the powersplitting ratio optimization algorithm and 2) the best antenna-relay-destination selection determination algorithm. Finally, we utilize the Monte Carlo simulations to verify our analytical results.

In this paper, the radio frequency energy harvesting (EH) and security issues in Internet of Things (IoT) sensor networks with multiple untrusted relays are considered. In particular, the communication protocol is divided into two phases. The first phase is used for EH, in which the IoT sensor nodes (SNs) and relays harvest energy from multiple power transfer stations. The second phase is used for information transmission in two steps: 1) the selected SN uses the harvested energy to broadcast information to the controller and the relays, and 2) the selected relay forwards information to the controller by applying the amplify-and-forward protocol to improve the quality of the communication between the SN and the controller. During information transmission, the controller is at risk of losing information because the relay may act as an eavesdropper (namely, an untrusted relay). Thus, to improve the secrecy performance of the considered system, we propose an optimal scheme, namely, best-sensor-best-untrusted-relay (BSBR) and compare this scheme with random-sensor-random-untrusted-relay and a threshold-based scheme. The closed-form expressions for the secrecy outage probability (SOP) and secrecy throughput (ST) are obtained and verified through Monte Carlo simulations to confirm the superior performance of our approach. EH time optimization and the target secrecy rate optimization algorithms are also proposed. In addition, the impacts of the EH time, the EH efficiency coefficient, the numbers of SNs and untrusted relays, and the target secrecy rate on the SOP and the ST are investigated. The results indicate that the BSBR generally outperforms the two baseline schemes in terms of the SOP and ST.

In this paper, we investigate an application of two different beamforming techniques and propose a novel downlink power minimization scheme for a two-tier heterogeneous network (HetNet) model. In this context, we employ the time reversal (TR) technique to a femtocell base station, whereby we assume that a macrocell base station uses a zero-forcing-based algorithm, and the communication channels are subject to frequency selective fading. Additionally, the HetNet backhaul connection is unable to support a sufficient throughput for signaling an information exchange between two tiers. Given the considered HetNet model, a downlink power minimization scheme is proposed, and closed-form expressions concerning the optimal solution are provided by taking this constraint into account. Furthermore, considering imperfect channel estimation at TR-employed femtocell, a worst-case robust power minimization problem is formulated. By devising TR worst-case analysis, this robust problem is transformed into an equivalent formulation that is tractable to solve. The results presented in our paper, show that the TR technique outperforms the zero-forcing one from the perspective of beamforming methods for femtocell working environments. Finally, we validate the proposed power loading strategy for both cases of perfect and imperfect channel estimations.

The article analyzes the changing in theage structure of the Vietnam population in the period from 1979 to the present, andthe trend of its changes between now and2049. It deals with the impact of changesin the age structure on the fi nancial balance of the Pension Fund of Vietnam in conditions of population aging.

Economic liberalization in today’s conditions is not so much an effective tool of national economy stimulation but is rather a precondition for its connection to the world markets and global economic space overall. The paper investigates economic effectiveness of liberalization that is determined by a variety of conditions and features in its implementation. Basing on the analysis of correlation between economic liberalization dynamics and macroeconomic indicators of the selected countries of the world, the magnitude of liberal reforms’ stimulating effect in the early 21st century is estimated, and theoretical conclusions regarding liberal economic reforms potential in our time are offered along with the recommendations on strategic priorities and tactical tools to improve national business environment and increase global economic attractiveness.