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Dynamic cross-linked networks (DCNs) endow thermoset rubber with self-healability and recyclability to extend its lifetime and alleviate environmental pollution. However, the contradiction between high self-healing and mechanical properties in DCNs rubber is always difficult to be resolved. Herein, we used boronic ester (BO) and Diels-Alder dynamic covalent bonds (DA) to synthesize polybutadiene-based dual networks rubber (PB-BO-DA) via thiol-ene reaction. This approach achieved a tensile strength of 16.46 MPa and 99% self-healing efficiency, facilitated by extensive intermolecular interactions (π-π packing and N-B coordination) and fully dynamic cross-linking. In addition, multiple dynamic cross-linked networks (MDCNs) polybutadiene-based rubber also show excellent shape memory ability and recyclability. This strategy might open a helpful pathway to fabricate intelligent multifunctional polymers with high strength and high self-healing efficiency.

The servo motor has the characteristics of high precision, high speed and stable operation, but it will produce large electromagnetic noise in the process of using, which will affect the user experience. Based on the ANSYS multi-physics finite element analysis platform, this paper studies the electrical noise characteristics of servo motors used in a secondary water supply equipment under different speed conditions. The time and space distribution characteristics of the radial electromagnetic force acting on the motor stator are obtained by electromagnetic field analysis and modal analysis respectively. The natural frequency of the motor structure modal mode can also be obtained from these analyses. The causes of large electromagnetic noise were analyzed from the aspects of radial electromagnetic force and structural mode, and the position distribution of large vibration on the motor is obtained by harmonic response analysis. On this basis, the sound pressure level distribution of servo electromagnetic noise at different frequencies is obtained through acoustic simulation, which has referential significance for noise prediction and shell noise reduction optimization of related servo motors.

The utilization of polyamide 10,12 (PA10,12) composites in various industries has been limited constrained by their inherent low toughness, making it a challenge to achieve a balance between toughness and structural integrity through conventional elastomer addition strategies. Herein, we introduce a straightforward method for the concurrent toughening and reinforcement of PA10,12 composites. This is accomplished by blending polyolefin elastomer (POE) and 3-pentadecylphenol (PDP) with the PA10,12 matrix. The incorporation of 5 wt% PDP effectively blurred the PA10,12/POE interface due to PDP’s role as a compatibilizer. This phenomenon is attributed to the formation of intermolecular hydrogen bonds, as evidenced by Fourier Transform Infrared Spectroscopy (FTIR) analysis. Further investigation, using differential scanning calorimetry (DSC), elucidated the crystallization thermodynamics and kinetics of the resulting binary PA10,12/POE and ternary PA10,12/POE/PDP composites. Notably, the crystallization temperature (Tc) was observed to decrease from 163.1 °C in the binary composite to 161.5 °C upon the addition of PDP. Increasing the PDP content to 10% led to a further reduction in Tc to 159.5 °C due to PDP’s capacity to slow down crystallization. Consequently, the ternary composite of PA10,12/POE/PDP (92/3/5 wt%) demonstrated a synergistic improvement in mechanical properties, with an elongation at break of 579% and a notch impact strength of 61.54 kJ/m2. This represents an approximately eightfold increase over the impact strength of unmodified PA10,12. Therefore, our work provides the potential of PDP as a compatibilizer to develop nylon composites with enhanced stiffness and toughness.

This study addresses the challenges associated with incomplete or missing information in obstacle detection methods that employ a single sensor. Additionally, it tackles the issue of motion distortion in LiDAR point cloud data during synchronization and mapping in complex environments. The research introduces two significant contributions. Firstly, a novel obstacle detection method, named the point-map fusion (PMF) algorithm, was proposed. This method integrates point cloud data from the LiDAR, camera, and odometer, along with local grid maps. The PMF algorithm consists of two components: the point-fusion (PF) algorithm, which combines LiDAR point cloud data and camera laser-like point cloud data through a point cloud library (PCL) format conversion and concatenation, and selects the most proximate point cloud to the quadruped robot dog as the valid data; and the map-fusion (MF) algorithm, which incorporates local grid maps acquired using the Gmapping and OctoMap algorithms, leveraging Bayesian estimation theory. The local grid maps obtained by the Gmapping and OctoMap algorithms are denoted as map A and map B, respectively. This sophisticated methodology enables seamless map fusion, which significantly enhances the precision and reliability of the approach. Secondly, a motion distortion removal (MDR) method for LiDAR point cloud data based on odometer readings was proposed. The MDR method utilizes legged odometer data for linear data interpolation of the original distorted LiDAR point cloud data, facilitating the determination of the corresponding pose of the quadruped robot dog. Subsequently, the LiDAR point cloud data are then transformed to the quadruped robot dog coordinate system, efficiently mitigating motion distortion. Experimental results demonstrated that the proposed PMF algorithm achieved a 50% improvement in success rate compared to using only LiDAR or the PF algorithm in isolation, while the MDR algorithm enhanced mapping accuracy by 45.9% when motion distortion was taken into account. The effectiveness of the proposed methods was confirmed through rigorous experimentation.

Simulating the spatial response of ecosystem service value (ESV) caused by land use change in Heilongjiang Province under different scenarios in the future is of great significance for ensuring ecological security and sustainable development in the region. Heilongjiang Province, an important grain-producing region in China, is taken as the research area in this study. Five land use maps (2000, 2005, 2010, 2015, and 2020) were used to evaluate the change of ecosystem service value in Heilongjiang Province in the past 20 years. In addition, the area of each land use type under different future scenarios was predicted by Markov model and MOP model, the future land use pattern was simulated based on PLUS model, the ESV under different scenarios was calculated, and the spatial distribution and the degree of ESV clustering were further explored. The results show that: (1) During 2000–2020, the built-up land in Heilongjiang Province continued to grow, with a total increase of 5076 km2 during the 20-year period, the area of water continued to grow, the area of unused land gradually decreased, and the area of farmland and forest land changed less. (2) During the study period, the ESV in 2000, 2005, 2010, 2015, and 2020 were 1320.8 billion yuan, 1334.5 billion yuan, 1342.1 billion yuan, 1327.6 billion yuan, and 1328.4 billion yuan, respectively. Generally, it shows a fluctuating trend. (3) The ESV of natural development scenario (NDS), economic priority scenario (ERS) and ecological protection scenario (EPS) are 1334.3 billion yuan, 1254.8 billion yuan and 1455.6 billion yuan, respectively. The ESV of different scenarios is quite different. (4) The spatial distribution of ESV was higher in the northwest, central, and southeast, and lower in the east and west. The hot and cold spots of ESV are widely distributed and the degree of polymerization is high. The methods and conclusions of this study can provide scientific reference for the optimization of national spatial pattern and the formulation of sustainable development policy.

Background: Juvenile xanthogranuloma (JXG) is a type of non-Langerhans cell histiocytosis (non-LCH) that primarily affects infants and young children. It mostly occurs in the skin, while the brain is rarely affected. Multiple intracranial lesions, as found in this case, are even more scarce. Case: We are reporting the case of a 9-year-old boy who presented with an imbalanced gait, ataxia, nystagmus, and right facial droop. Magnetic resonance imaging (MRI) revealed multiple intracranial lesions, while chest contrast-enhanced computed tomography (CT) showed irregular soft tissue density of the lesion, with uneven density, poorly defined border, and mild heterogeneous enhancement. Histopathologic examination of the resected intracranial lesion reported disseminated JXG. Subsequently, the patient received treatment of methylprednisolone and interferon-α. The three-month follow-up CT showed that the lesion within the chest was slightly reduced. Conclusion: This case report aims to highlight the radiological features, diagnosis, and treatment of intracranial JXG and to provide some guidance for clinical management. Given the rarity of such cases and the lack of relevant studies, further research regarding to diagnosis and treatment is needed.

Background: Traumatic brain injury (TBI) is a brain function change caused by external forces, which is one of the main causes of death and disability worldwide. The aim of this study was to identify early diagnostic markers and potential therapeutic targets for TBI.Methods: Differences between TBI and controls in GSE89866 and GSE104687 were analyzed. The two groups of differentially expressed genes (DEGs) were combined for coexpression analysis, and the modules of interest were performed using enrichment analysis. Hub genes were identified by calculating area under curve (AUC) values of module genes, PPI network analysis, and functional similarity. Finally, the difference in immune cell infiltration between TBI and control was calculated by ssGSEA.Results: A total of 4,817 DEGs were identified in GSE89866 and 1,329 DEGs in GSE104687. They were clustered into nine modules. The genes of modules 1, 4, and 7 had the most crosstalk and were identified as important modules. Enrichment analysis revealed that they were mainly associated with neurodevelopment and immune inflammation. In the PPI network constructed by genes with top 50 AUC values in module genes, we identified the top 10 genes with the greatest connectivity. Among them, down-regulated RPL27, RPS4X, RPL23A, RPS15A, and RPL7A had similar functions and were identified as hub genes. In addition, DC and Tem were significantly up-regulated and down-regulated between TBI and control, respectively.Conclusion: We found that hub genes may have a diagnostic role for TBI. Molecular dysregulation mechanisms of TBI are associated with neurological and immune inflammation. These results may provide new ideas for the diagnosis and treatment of TBI.

PurposeDual-specificity protein phosphatases 26 (DUSP26) is a recently identified phosphatase enzyme that regulates MAPK and Akt signaling pathways. The role of DUSP26 in the development and prognosis of high-grade gliomas (HGGs) and primary glioblastoma (GBM) has remained unclear and was the focus of this study.Materials and MethodsThe prognostic value of DUSP26 was assessed using retrospective analyses using online data sets and tissue microarray of HGGs. U251 and U87 cells modified to overexpress DUSP26 were utilized to study the role of DUSP26 in cell growth, migration, and cell apoptosis analyzed by CCK-8 assay, clonogenic, transwell migration, and TUNEL, respectively. The phosphorylation of proteins in MAPK and Akt signaling pathways was assayed by Western blot and immunofluorescence assays.ResultsAnalyses using available online data sets and tissue microarray showed that DUSP26 is down-regulated in high-grade gliomas and GBM as compared to normal brain. Stratification of glioma patients based on DUSP26 expression level showed an inverse correlation between DUSP26 expression and patient survival. At the cellular level, DUSP26 overexpression led to decreased cell proliferation, migration, and senescence in U251 and U87 cells, whereas apoptosis was increased as compared to corresponding controls. Interestingly, the biologic effects of DUSP26 overexpression were associated with the dephosphorylation of proteins in the MAPK and Akt signaling pathways.ConclusionsThese findings suggest that the loss of DUSP26 expression, seen in a subset of high-grade gliomas and GBM patients, facilitates malignant behavior; and with inverse correlation between its expression levels with patient survival. DUSP26 can serve as an independent prognostic factor.

The porous and biomimetic cobalt silicate@diatomite (Co2SiO4@diatomite) was successfully synthesized by a two-step method, including the hydrothermal method and calcination to improve the electromagnetic wave absorption property. Different hydrothermal times were well-tuned for Co2SiO4@diatomite composites with different loadings of Co2SiO4. Interestingly, the Co2SiO4@diatomite composites (6 h, 25 wt%) had a smaller minimum reflection loss. Moreover, the minimum reflection loss (RLmin) could reach −12.03 dB at 16.64 GHz and the matched absorber thickness was 10 mm, while the effective absorption bandwidth (EAB, RL ≤ −10 dB) could be 1.92 GHz. In principle, such findings indicate that Co2SiO4@diatomite nanocomposites could be a promising candidate for high-efficiency microwave absorption capability.

The blood-tumor barrier (BTB) hinders delivery of chemotherapeutic drugs to tumors in the brain; previous studies have shown that the BTB can be selectively opened by endothelial monocyte activating polypeptide-II (EMAP-II), but the specific mechanism involved remains elusive. In this study, we found that microRNA-429 (miR-429) expression in glioma vascular endothelial cells (GECs) was far lower than in human brain microvascular endothelial cells (ECs). miR-429 had lower expression in GECs and glioma tissues compared to ECs or normal tissues of the brain. Furthermore, miR-429 had lower expression in high grade glioma (HGG) than in low grade glioma (LGG). In in vitro BTB models, we also found that EMAP-II significantly increased BTB permeability, decreased expression of ZO-1, occludin and claudin-5 in GECs, in a time- and dose-dependent manner. EMAP-II greatly increased miR-429 expression in GECs of the BTB models in vitro. Overexpression of miR-429 in GECs significantly decreased the transepithelial electric resistance (TEER) values in BTB models, and led to enhanced horseradish peroxidase (HRP) flux. Overexpression of miR-429 in GECs significantly decreased the expression of tight junction (TJ)-associated proteins (ZO-1, occludin and claudin-5), and decreased the distribution continuity. Silencing of miR-429 in GECs increased the expression of TJ-associated proteins and the distribution continuity. The dual-luciferase reporter assay revealed that ZO-1 and occludin were target genes of miR-429, and we demonstrated that miR-429 overexpression markedly down-regulated protein expression of p70S6K, as well as its phosphorylation levels. The dual-luciferase reporter assay also showed that p70S6K was a target gene of miR-429; miR-429 overexpression down-regulated expression and phosphorylation levels of p70S6K, and also decreased phosphorylation levels of S6 and increased BTB permeability. Conversely, silencing of miR-429 increased the expression and phosphorylation levels of p70S6K, and increased phosphorylation levels of S6, while decreasing BTB permeability. In conclusion, the results indicated that EMAP-II caused an increase in miR-429 expression that directly targeted TJ-associated proteins, which were negatively regulated; on the other hand, miR-429 down-regulated the expression of TJ-associated proteins by targeting p70S6K, also negatively regulated. As a result, the BTB permeability increased.

This study was performed to determine whether EMAP II increases the permeability of the blood-tumor barrier (BTB) by affecting the expression of miR-330-3p as well as its possible mechanisms. We determined the over-expression of miR-330-3p in glioma microvascular endothelial cells (GECs) by Real-time PCR. Endothelial monocyte-activating polypeptide-II (EMAP-II) significantly decreased the expression of miR-330-3p in GECs. Pre-miR-330-3p markedly decreased the permeability of BTB and increased the expression of tight junction (TJ) related proteins ZO-1, occludin and claudin-5, however, anti-miR-330-3p had the opposite effects. Anti-miR-330-3p could enhance the effect of EMAP-II on increasing the permeability of BTB, however, pre-miR-330-3p partly reversed the effect of EMAP-II on that. Similarly, anti-miR-330-3p improved the effects of EMAP-II on increasing the expression levels of PKC-α and p-PKC-α in GECs and pre-miR-330-3p partly reversed the effects. MiR-330-3p could target bind to the 3′UTR of PKC-α. The results of in vivo experiments were similar to those of in vitro experiments. These suggested that EMAP-II could increase the permeability of BTB through inhibiting miR-330-3p which target negative regulation of PKC-α. Pre-miR-330-3p and PKC-α inhibitor decreased the BTB permeability and up-regulated the expression levels of ZO-1, occludin and claudin-5 while anti-miR-330-3p and PKC-α activator brought the reverse effects. Compared with EMAP-II, anti-miR-330-3p and PKC-α activator alone, the combination of the three combinations significantly increased the BTB permeability. EMAP-II combined with anti-miR-330-3p and PKCα activator could enhance the DOX’s effects on inhibiting the cell viabilities and increasing the apoptosis of U87 glioma cells. Our studies suggest that low-dose EMAP-II up-regulates the expression of PKC-α and increases the activity of PKC-α by inhibiting the expression of miR-330-3p, reduces the expression of ZO-1, occludin and claudin-5, and thereby increasing the permeability of BTB. The results can provide a new strategy for the comprehensive treatment of glioma.

Background: Escherichia coli is the most common cause of urinary tract infections (UTIs). It is widely accepted that uropathogenic E. coli (UPEC) mainly emerge from the distal gut microbiota. Identification of bacterial characteristics that are able to differentiate UPEC from fecal commensal strains will facilitate the development of novel strategies to detect and monitor the spread of UPEC. Methods: Fifty fecal commensal, 83 UTI-associated and 40 biliary tract infection (BTI)-associated E. coli isolates were analyzed. The NotI restriction patterns of chromosomal DNA in the isolates were determined by pulse-field gel electrophoresis. The phylogenetic types and the presence of 9 known virulence genes of each isolate were determined by PCR analyses. Additionally, the susceptibilities of the isolates to antibiotics were revealed. Then the associations of NotI resistance with UTI-associated isolates, phylotypes, and antibiotic resistance were assessed. Results: NotI resistance was correlated with UTI-associated isolates, compared to the fecal isolates. Consistently, NotI-resistant isolates harbored a greater number of virulence factors and mainly belonged to phylotype B2. Additionally NotI resistance was correlated with chloramphenicol resistance among the bacteria. Among the fecal, UTI-associated and BTI-associated groups, the distribution of NotI-resistant group B2 isolates was correlated with UTI-associated bacteria. Conclusion: NotI resistance alone is a potential marker for distinguishing fecal strains and UPEC, while the combination of NotI resistance and B2 phylogeny is a candidate marker to differentiate UPEC from fecal and other extraintestinal pathogenic E. coli. Additionally, NotI resistance may be valuable for assessing the potential of chloramphenicol resistance of E. coli.

Carbon-based materials have large specific surface area, well-developed pores, and a large number of oxygencontaining functional groups on the surface, which have excellent mechanical properties. Introducing carbon-based materials into the hydrogel system can increase adsorption sites, improve mechanical properties, enrich network structure, realize complementary advantages, and overcome performance defects, which is the main idea for developing highperformance hydrogel adsorbents. In this paper, the structural characteristics of different types of carbon based composite hydrogels were summarized, and the mechanism of carbon based materials to enhance the performance of hydrogels was emphatically introduced. The preparation methods of composite hydrogels and their applications in the field of water purification were reviewed. The prospects, limitations and future research potential of carbon based composite hydrogels adsorbents were analyzed. [ABSTRACT FROM AUTHOR]

Microbial proteases play pivotal roles in many aspects of bacterial physiological processes. Because a protease exerts its biological function by proteolytically regulating its substrates, the identification and characterization of the physiological substrates of a protease advance our understanding of the biological roles of the protease. Prc (also named Tsp) is an Escherichia coli periplasmic protease thought to be indispensable for E. coli to survive under low osmolality at 42°C. The accumulation of the Prc substrate MepS due to Prc deficiency contributes to the conditional growth defect. Because preventing MepS accumulation only partially restored the growth of Prc-deficient E. coli, we hypothesized that other unidentified Prc substrates intracellularly accumulate due to Prc deficiency and contribute to the conditional growth defect. To identify previously undiscovered substrates, 85 E. coli proteins able to physically interact with Prc were identified using E. coli proteome arrays. Ten proteins were shown to be cleavable by Prc in vitro. Among these candidates, MltG was able to interact with Prc in E. coli. Prc regulated the intracellular level of MltG, indicating that MltG is a physiological substrate of Prc. Prc deficiency induced the accumulation of MltG in the bacteria. Blocking MltG accumulation by deleting mltG partially restored the growth of Prc-deficient E. coli. In addition, Prc-deficient E. coli with blocked MltG and MepS expression exhibited higher growth levels than those with only the MltG or MepS expression blocked under low osmolality at 42°C, suggesting that these accumulated substrates additively contributed to the conditional growth defect. MltG is a lytic transglycosylase involved in the biogenesis of peptidoglycan (PG). In addition to MltG, the previously identified physiological Prc substrates MepS and PBP3 are involved in PG biogenesis, suggesting a potential role of Prc in regulating PG biogenesis.

Demand Response (DR) provides an opportunity for customers to reduce their loads during times of high prices and therefore to shave the peak loads. The power outputs of large-scale generator units can be predicted and controlled easily; therefore, the pricing and reliability of conventional power utilities can be assessed straightforwardly. However, the customer loads are very variable and difficult to predict and control; therefore, the integration of DR might cause uncertainty issues on pricing and reliability and is essential to be further investigated. A novel uncertainty model for load reduction is proposed in this paper. The probability intensities of load reduction are first estimated from the measured load reduction variations. A multi-state probability model is then proposed for load reduction and the Markov process is used to calculate the state probabilities. A stochastic analysis scheme using Monte Carlo simulation for pricing and reliability taking the DR uncertainty into account is then investigated. Several cases are designed to compare the effects of DR uncertainty. Simulation results show that the proposed uncertainty model can be integrated into conventional economic dispatch to precisely evaluate the DR uncertainty on system operation and reliability.

This paper studies the system unbalance caused by rooftop Photovoltaic Generation Systems (PVGSs) in distribution networks and proposes an improved method. The voltage and current unbalance studies for three extreme cases considering all rooftop PVGSs being connected to one single phase and then the stochastic analyses for the integration cases of rooftop PVGSs are considered. These three extreme cases lead to severe system unbalance problems. An improving method that combines the On Load Tap Changer (OLTC) and the optimal phase arrangement of distribution transformers is proposed in this paper to mitigate the system unbalance. The OLTC-based improving method is applied first. If the system unbalance is still out of range, the optimal phase arrangement of distribution transformers is further used to mitigate the system unbalance problem. The objective function of optimal phase arrangement is to minimize the system unbalance with the constraints of voltage limits, line flow limit, etc. Test results show that the proposed method can improve the system unbalance significantly even under very extreme cases.

Prokaryotic CRISPR-Cas systems limit the acquisition of genetic elements and provide immunity against invasive bacteriophage. The characteristics of CRISPR-Cas systems in clinical Klebsiella pneumoniae isolates are still unknown. Here, 97 K. pneumoniae genomes retrieved from the Integrated Microbial Genomes & Microbiomes genome database and 176 clinical isolates obtained from patients with bloodstream (BSI, n = 87) or urinary tract infections (UTI, n = 89) in Taiwan, were used for analysis. Forty out of ninety-seven genomes (41.2%) had CRISPR-Cas systems identified by the combination of CRISPRFinder and cas1 gene sequence alignment. The phylogenetic trees revealed that CRISPR-Cas systems in K. pneumoniae were divided into two types (type I-E, 23; subtype I-E∗, 17) based on the sequences of Cas1 and Cas3 proteins and their location in the chromosome. The distribution of type I-E and I-E∗ CRISPR-Cas systems was associated with the multilocus sequence typing and the pulsed-field gel electrophoresis results. Importantly, no CRISPR-Cas system was identified in published genomes of clonal complex 258 isolates (ST11 and ST258), which comprise the largest multi-drug resistant K. pneumoniae clonal group worldwide. PCR with cas-specific primers showed that 30.7% (54/176) of the clinical isolates had a CRISPR-Cas system. Among clinical isolates, more type I-E CRISPR-Cas systems were found in UTI isolates (BSI, 5.7%; UTI, 11.2%), and subtype I-E∗ CRISPR-Cas systems were dominant in BSI isolates (BSI, 28.7%; UTI, 15.7%) (p = 0.042). Isolates which had subtype I-E∗ CRISPR-Cas system were more susceptible to ampicillin-sulbactam (p = 0.009), cefazolin (p = 0.016), cefuroxime (p = 0.039), and gentamicin (p = 0.012), compared to the CRISPR-negative isolates. The strains containing subtype I-E∗ CRISPR-Cas systems had decreased numbers of plasmids, prophage regions, and acquired antibiotic resistance genes in their published genomes. Here, we first revealed subtype I-E∗ CRISPR-Cas system in K. pneumoniae potentially interfering with the acquisition of phages and plasmids harboring antibiotic resistance determinants, and thus maintained these isolates susceptible to antibiotics.

Due to the rapid development of computers, researchers have made efforts since the 1990s to develop typhoon forecasting models and stochastic typhoon simulation models to assess typhoon disasters and risks. Typhoon forecasting models are primarily used to predict and track the movement of typhoons and provide warning information to the general public before landfall. Stochastic typhoon simulation models can assess extreme wind speeds and compensate for the limitations of current observations and simulation data length. Taiwan experiences approximately three to four typhoons yearly, of varying intensities and paths. Whether the marine meteorological data includes events of strong typhoon centers passing through will affect the results of frequency analysis. The development of offshore wind power in Taiwan is closely related to the unique marine meteorological conditions throughout the lifecycle stages, including wind farm site selection, feasibility studies, planning and design, construction and installation, operation and maintenance, and decommissioning. This study references relevant research and analyzes sixty-three scenarios using nine types of maximum storm wind speed radii and seven Holland-B parameters. The data from Japan Meteorological Agency Best Track Data (JMA BTD) is utilized, explicitly selecting 20 typhoon events after 2000 for wind speed simulation using a typhoon wind speed model. After validating the typhoon wind speeds with observation data from the Central Weather Bureau (CWB) in Hsinchu and the Longdong buoy, the technique of Monte Carlo simulation is utilized to generate synthetic typhoons randomly. The average of the relative absolute errors for the simulated maximum wind speeds is calculated, and through comprehensive evaluation, optimal parameter combinations ( R m , B) are obtained. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the clinical and microbiological features of recurrent group B streptococcal (GBS) diseases among non-pregnant adults. Methods: All hospitalized non-pregnant adults who had culture-proven GBS infections between January 2008 and December 2010 were enrolled in this retrospective study. Bacterial isolates were examined for their serotypes, genotypes, and antimicrobial resistance. Results: The recurrence rate of GBS infection in Taiwan was found to be 9.3%. Of the 70 recurrent episodes in 32 patients, infections of the urinary tract (U) were diagnosed clinically in 55.7%, infections of the soft tissue (S) in 31.4%, and infections of the bloodstream (B) in 12.9%. The initial/recurrent episodes in 25 patients were mainly U/U (40.6%), followed by S/S (18.8%) and B/B (6.2%). The serotypes/serogroups identified were serotypes V (34.3%), Ib (22.9%), VI (17.1%), III (12.9%), IV (7.1%), and Ia (5.7%). Recurrent strains showed less resistance to erythromycin or clindamycin than non-recurrent strains. Six distinct genotypes were identified in 12 serotype VI isolates derived from seven patients; five of these isolate pairs had identical genotypes. Conclusions: Recurrent GBS diseases were found to occur considerably more often than previously thought, mainly in adults with a high comorbid index. Relapse, not new acquisition, was found to be more common.

Due to the unbalanced features of distribution systems, a three-phase harmonic analysis method is essential to accurately analyze the harmonic impact on distribution systems. Moreover, harmonic analysis is the basic tool for harmonic filter design and harmonic resonance mitigation; therefore, the computational performance should also be efficient. An accurate and efficient three-phase harmonic analysis method for unbalanced distribution systems is proposed in this paper. The variations of bus voltages, bus current injections and branch currents affected by harmonic current injections can be analyzed by two relationship matrices developed from the topological characteristics of distribution systems. Some useful formulas are then derived to solve the three-phase harmonic propagation problem. After the harmonic propagation for each harmonic order is calculated, the total harmonic distortion (THD) for bus voltages can be calculated accordingly. The proposed method has better computational performance, since the time-consuming full admittance matrix inverse employed by the commonly-used harmonic analysis methods is not necessary in the solution procedure. In addition, the proposed method can provide novel viewpoints in calculating the branch currents and bus voltages under harmonic pollution which are vital for harmonic filter design. Test results demonstrate the effectiveness and efficiency of the proposed method.

Advanced Metering Infrastructure (AMI), the foundation of smart grids, can be used to provide numerous intelligent power applications and services based on the data acquired from AMI. Effective and efficient communication performance between widely-spread smart meters and Data Concentrator Units (DCUs) is one of the most important issues for the successful deployment and operation of AMI and needs to be further investigated. This paper proposes an effective Communication Performance Index (CPI) to assess and supervise the communication performance of each smart meter. Some communication quality measurements that can be easily acquired from a smart meter such as reading success rate and response time are used to design the proposed CPI. Fuzzy logic is adopted to combine these measurements to calculate the proposed CPI. The CPIs for communication paths, DCUs and whole AMI can then be derived from meter CPIs. Simulation and experimental results for small-scale AMIs demonstrate the validity of the proposed CPI. Through the calculated CPIs, the communication performance and stability for AMI can be effectively assessed and supervised.

The harmonic impact caused by wind turbines should be carefully investigated before wind turbines are interconnected. However, the harmonic currents of wind turbines are not easily predicted due to the variations of wind speed. If the harmonic current outputs can be predicted accurately, the harmonic impact of wind turbines and wind farms for power grids can be analyzed efficiently. Therefore, this paper analyzes the harmonic current characteristics of wind turbines and investigates the feasibility of developing harmonic current predictors. Field measurement, data sorting, and analysis are conducted for wind turbines. Two harmonic current predictors are proposed based on the measured harmonic data. One is the Auto-Regressive and Moving Average (ARMA)-based harmonic current predictor, which can be used for real-time prediction. The other is the stochastic harmonic current predictor considering the probability density distributions of harmonic currents. It uses the measured harmonic data to establish the probability density distributions of harmonic currents at different wind speeds, and then uses them to implement a long-term harmonic current prediction. Test results use the measured data to validate the forecast ability of these two harmonic current predictors. The ARMA-based predictor obtains poor performance on some harmonic orders due to the stochastic characteristics of harmonic current caused by the variations of wind speed. Relatively, the prediction results of stochastic harmonic current predictor show that the harmonic currents of a wind turbine in long-term operation can be effectively analyzed by the established probability density distributions. Therefore, the proposed stochastic harmonic current predictor is helpful in predicting and analyzing the possible harmonic problems during the operation of wind turbines and wind farms.

Fault Current Indicators (FCIs) with communication interfaces have been widely used in distribution systems to reduce fault-finding time. The effectiveness of a Fault Management System (FMS) composed of FCIs greatly depends on the performance of the communication network deployed by the FCIs and the failure rates of distribution systems. The conventional techniques only focus on the issues of optimal number and location of FCIs or communication network deployment individually; therefore, the effectiveness of an FMS cannot be assessed realistically. A systematic effectiveness assessment methodology for FMS considering the performance of the communication network deployed by the FCIs and the failure rates of distribution systems is vital and is investigated in this paper. A communication evaluation platform is designed in this paper and used to acquire the field measurements of communication parameters. The communication parameters, especially the Packet Success Rate (PSR), between two adjacent FCIs are measured, and the Probability Density Function (PDF) of the PSR can be built accordingly. The effectiveness of the FMS is then assessed by stochastic analysis considering the failure rates of the distribution system and PSR PDFs between two adjacent FCIs. Due to the characteristics of easy installation, maintenance, longer battery life, lower cost, and so on of ZigBee, the ZigBee-based FCI is mainly discussed in this paper. In order to efficiently find the communication route when a fault occurs, a fast communication route tracking method is also proposed in this paper and its feasibility is demonstrated in an actual distribution system. Experimental and simulation results demonstrate the validity of the proposed systematic effectiveness assessment methodology for an FMS composed of FCIs. The proposed assessment methodology can more realistically react to the actual conditions of the FMS and therefore save on installation time and costs.

The purpose behind the work was to fabricate alginate beads with better drug loading and extended drug release. Ispaghula was used to enhance the drug loading while zein was employed to extend the drug release. Ibuprofen was employed as a model drug in this study. Ibuprofen-loaded alginate beads with and without ispaghula were prepared using vibration technology and coated with zein. The beads prepared with alginate alone were shown to have loading and entrapment efficiencies of 35% and 70% w/w, respectively. Addition of ispaghula in alginate showed a significant increase (p < 0.05) in the drug loading (42% w/w) and entrapment efficiency (84% w/w). Fourier-transform infrared spectroscopy confirmed the presence of ispaghula and zein coating in the alginate beads as well as the ibuprofen loading. Scanning electron microscopy revealed better spherical geometry in the beads with ispaghula. The surface morphology of the uncoated beads was rough due to crystalline and surface drug. The zein coating has produced a smoother surface and particle adhesion. Differential scanning calorimetry has shown a reduction in drug crystallinity. Alginate beads extended the drug release for 4 h and the presence of zein extended the release for 6 h.

The NMDA receptor hypofunction has been implicated in schizophrenia, memory impairment, and Alzheimer's disease. Modulating the abundance of D-serine, a co-agonist of the NMDA receptor, is a strategy to treat symptoms of the NMDA receptor hypofunction. In contrast to D-amino acid oxidase (DAAO) inhibitors, which aim at decreasing the loss of D-serine, this study tried to identify serine racemase (SRR) agonists, which boost the conversion of L-serine to D-serine. We used holo and apo structures of human SRR for the molecular docking against the National Cancer Institute (NCI) and ZINC compound databases and validated their efficacy by in vitro SRR activity assay. We identified NSC294149 (2-amino-3-(3-nitroimidazo[1,2-a]pyridin-2-yl)sulfanylpropanoic acid) as a potential SRR agonist and confirmed its amelioration of the hazard ratio of survival of the AD model of fruit fly (Drosophila melanogaster). These results suggest that the SRR agonist could be a drug design target against the NMDA receptor hypofunction symptoms. [ABSTRACT FROM AUTHOR]

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that enables users to communicate with external environments through their minds. However, current MI-BCI systems ask naïve subjects to perform unfamiliar MI tasks with simple textual instruction or a visual/auditory cue. The unclear instruction for MI execution not only results in large inter-subject variability in the measured EEG patterns but also causes the difficulty of grouping cross-subject data for big-data training. In this study, we designed an BCI training method in a virtual reality (VR) environment. Subjects wore a head-mounted device (HMD) and executed action observation (AO) concurrently with MI (i.e., AO + MI) in VR environments. EEG signals recorded in AO + MI task were used to train an initial model, and the initial model was continually improved by the provision of EEG data in the following BCI training sessions. We recruited five healthy subjects, and each subject was requested to participate in three kinds of tasks, including an AO + MI task, an MI task, and the task of MI with visual feedback (MI-FB) three times. This study adopted a transformer- based spatial-temporal network (TSTN) to decode the user's MI intentions. In contrast to other convolutional neural network (CNN) or recurrent neural network (RNN) approaches, the TSTN extracts spatial and temporal features, and applies attention mechanisms along spatial and temporal dimensions to perceive the global dependencies. The mean detection accuracies of TSTN were 0.63, 0.68, 0.75, and 0.77 in the MI, first MI-FB, second MI-FB, and third MI-FB sessions, respectively. This study demonstrated the AO + MI gave an easier way for subjects to conform their imagery actions, and the BCI performance was improved with the continual learning of the MI-FB training process. [ABSTRACT FROM AUTHOR]