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Satellite-Drone Image Cross-View Geolocalization has wide applications. Due to the pronounced variations in the visual features of 3D objects under different angles, Satellite-Drone cross-view image geolocalization remains an unresolved challenge. The key to successful cross-view geolocalization lies in extracting crucial spatial structure information across different scales in the image. Recent studies improve image matching accuracy by introducing an attention mechanism to establish global associations among local features. However, existing methods primarily focus on using single-scale features and employ a single-channel attention mechanism to correlate local convolutional features from different locations. This approach inadequately explores and utilizes multi-scale spatial structure information within the image, particularly lacking in the extraction and utilization of locally valuable information. In this paper, we propose a cross-view image geolocalization method based on multi-scale information and a dual-channel attention mechanism. The multi-scale information includes features extracted from different scales using various convolutional slices, and it extensively utilizes shallow network features. The dual-channel attention mechanism, through successive local and global feature associations, effectively learns depth discriminative features across different scales. Experimental results were conducted using existing satellite and drone image datasets, with additional validation performed on an independent self-made dataset. The findings indicate that our approach exhibits superior performance compared to existing methods. The methodology presented in this paper exhibits enhanced capabilities, especially in the exploitation of multi-scale spatial structure information and the extraction of locally valuable information. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relationship between immunohistochemical characteristics and recurrence after complete remission (CR) with fertility preservation treatment in patients with endometrial cancer (EC) and endometrial atypical hyperplasia (AH). Methods: The clinical data and immunohistochemical results of 53 patients with EC and 68 patients with AH admitted to Peking University People's Hospital from January 2010 to January 2021 were retrospectively analyzed. Patients were divided into two groups according to whether recurrence after complete remission (CR): group 1: recurrence after CR; group 2: no recurrence after CR, for statistical analysis. Results: (1) The expression rate of ER in group 1 was lower than that in group 2, (P < 0.05). The expression rate of Ki-67 in group 1 was significantly higher than that in group 2, (P < 0.01). The expression rates of PR, P16, P53, and PTEN were not significantly different between the two groups (P > 0.05); (2) combination index ER/ Ki-67 row ROC curve analysis, there was a significant difference (P < 0.01), the best cut-off value was 3.55, sensitivity 0.730, specificity 1.000, Youden index 0.730. The 3-year RFS of high rate patients was 100%, and that of low rate patients was 42.3%, P < 0.01. Conclusions: The expression rate of Ki-67 is of great significance in predicting the recurrence of EC after fertility preservation therapy. The best cut-off value of combination index ER/ Ki-67 (3.55) was better than a single immunohistochemical marker in predicting recurrence of EC after fertility preservation treatment. [ABSTRACT FROM AUTHOR]

High-rise building areas (HRBs) provide significant social and environmental services and play a crucial role in modern urbanization. The large-scale and long-term spatial distribution of HRBs is of great interest to many fields, such as urban planning and local climate analysis. While previous studies have confirmed the value of Sentinel-2 images in extracting HRBs and their changes, current work is limited to relatively local areas and short-term analysis. One reason is due to the fact that the earliest Sentinel-2 image can only date back to 2015. To address this research gap, this paper proposes an efficient procedure to intelligently extract HRBs and their changes from multitemporal Landsat-7 and Sentinel-2 images, using a specifically designed fully convolutional network. To validate the proposed method, we selected four typical cities in China, namely, Beijing, Shanghai, Guangzhou, and Zhengzhou, as study areas. We utilized Landsat-7 images acquired in 2000 and 2010, along with Sentinel-2 images acquired in 2020, as experimental data. We extracted and analyzed three periods of HRBs and their changes in the four cities, along with urban rail terminal data and gross domestic product (GDP) data in the same period. The results show that the proposed method can efficiently extract HRBs and their changes in the four cities over the past 20 years, with an overall accuracy of more than 90%. HRBs changes are primarily driven by urban planning policies and geographical factors. There is a strong positive correlation between the increase in HRBs and the increase in rail terminals, both in terms of quantity and spatial distribution. Additionally, there is a positive correlation between HRBs increase and GDP increase in terms of quantity, but the trend varies in different cities due to their diverse developing modes. Overall, the results indicate that the proposed method can be a potential operational tool to extract large-scale and long-term HRBs and their changes in China. [ABSTRACT FROM AUTHOR]

Since 2018, the outbreak and prevalence of the African swine fever virus (ASFV) in China have caused huge economic losses. Less virulent ASFVs emerged in 2020, which led to difficulties and challenges for early diagnosis and control of African swine fever (ASF) in China. An effective method of monitoring ASFV antibodies and specific antibodies against ASFV to promote the development of prevention techniques are urgently needed. In the present study, ASFV p17 was successfully expressed in CHO cells using a suspension culture system. An indirect enzyme-linked immunosorbent assay (ELISA) based on purified p17 was established and optimized. The monoclonal antibody (mAb) against p17 recognized a conservative linear epitope (3TETSPLLSH11) and exhibited specific reactivity, which was conducive to the identification of recombinant porcine reproductive and respiratory syndrome virus (PRRSV) expressing p17. The ELISA method efficiently detected clinical ASFV infection and effectively monitored the antibody levels in vivo after recombinant PRRSV live vector virus expressing p17 vaccination. Overall, the determination of the conserved linear epitope of p17 would contribute to the in-depth exploration of the biological function of the ASFV antigen protein. The indirect ELISA method and mAb against ASFV p17 revealed efficient detection and promising application prospects, making them ideal for epidemiological surveillance and vaccine research on ASF. [ABSTRACT FROM AUTHOR]

Because of their small size and large specific surface area, nanoparticles (NPs) have special properties that are different from bulk materials. In particular, Au/Ag NPs have been intensively studied for a long time, especially for biomedical applications. Thereafter, they played a significant role in the fields of biology, medical testing, optical imaging, energy and catalysis, MRI contrast agents, tumor diagnosis and treatment, environmental protection, and so on. When synthesizing Au/Ag NPs, the laser ablation and biosynthesis methods are very promising green processes. Therefore, this review focuses on the progress in the laser ablation and biological synthesis processes for Au/Ag NP generation, especially in their fabrication fundamentals and potential applications. First, the fundamentals of the laser ablation method are critically reviewed, including the laser ablation mechanism for Au/Ag NPs and the controlling of their size and shape during fabrication using laser ablation. Second, the fundamentals of the biological method are comprehensively discussed, involving the synthesis principle and the process of controlling the size and shape and preparing Au/Ag NPs using biological methods. Third, the applications in biology, tumor diagnosis and treatment, and other fields are reviewed to demonstrate the potential value of Au/Ag NPs. Finally, a discussion surrounding three aspects (similarity, individuality, and complementarity) of the two green synthesis processes is presented, and the necessary outlook, including the current limitations and challenges, is suggested, which provides a reference for the low-cost and sustainable production of Au/Ag NPs in the future. [ABSTRACT FROM AUTHOR]

In this era of information explosion, smartphones have become a necessary device in our daily life. In order to select a better smartphone, most users try to collect more attributes to help them purchase their own smartphones, including the brand image from the advertisements, features from the specifications, word-of-mouth from their peers, and the average sales from some secondary data webs. In order to assist the users to evaluate the brand performance from the market attributes, in this paper, we selected nine smartphone brands and used multi-criteria decision-making methods to rank the smartphones' functions. We first use TOPSIS to evaluate word-of-mouth, together with average sales collected from the website of each brand, and the brand image obtained by the use of questionnaires. Finally, we summarize the final rankings of these smartphone brands. The brand performance analysis shows that our proposed hybrid method can significantly derive the overall rankings of smartphone brands. [ABSTRACT FROM AUTHOR]

Background: Over 100 mutations in the SRD5A2 gene have been identified in subjects with 46,XY disorder of sex development (DSD). Exploration of SRD5A2 mutations and elucidation of the molecular mechanisms behind their effects should reveal the functions of the domains of the 5α-reductase 2 enzyme and identify the cause of 46,XY DSD. Previously, we reported a novel compound heterozygous p.Q6X/p.H232R mutation of the SRD5A2 gene in a case with 46,XY DSD. Whether the compound heterozygous p.Q6X/p.H232R mutation in this gene causes 46,XY DSD requires further exploration. Methods: The two 46,XY DSD cases were identified and sequenced. In order to identify the source of the compound heterozygous p.Q6X/p.H232R mutation, the parents, maternal grandparents, and maternal uncle were sequenced. Since p.Q6X mutation is a nonsense mutation, p.H232R mutation was transfected into HEK293 cells and dihydrotestosterone (DHT) production were analyzed by liquid chromatography–mass spectrometry (LC–MS) for 5α-reductase 2 enzyme activities test. Apparent michaelis constant (Km) were measured of p.H232R mutation to analyze the binding ability change of 5α-reductase 2 enzyme with testosterone (T) or NADPH. Results: The sequence results showed that the two 46,XY DSD cases were the compound heterozygous p.Q6X/p.H232R mutation, of which the heterozygous p.Q6X mutation originating from maternal family and heterozygous p.H232R mutation originating from the paternal family. The function analysis confirmed that p.H232R variant decreased the DHT production by LC–MS test. The Km analysis demonstrated that p.H232R mutation affected the binding of SRD5A2 with T or NADPH. Conclusions: Our findings confirmed that the compound heterozygous p.Q6X/p.H232R mutation in the SRD5A2 gene is the cause of 46,XY DSD. p.H232R mutation reduced DHT production while attenuating the catalytic efficiency of the 5α-reductase 2 enzyme. [ABSTRACT FROM AUTHOR]

Rapid and accurate battery fault diagnosis and distinction is of great importance in electrical vehicles and electrochemical energy storage system. However, misdiagnosis and missed diagnosis happened occasionally. In this paper, a statistical analysis-based multi-fault diagnosis method is proposed to detect and localize short circuit faults, electrical connection faults and voltage sensor faults in LFP battery packs. This method uses non-redundant interleaved voltage measurement topology to detect battery voltages, where every voltage sensor measures the sum of two neighboring batteries and one connection resistor between them. The statistical analysis method sets detection thresholds based on the battery operating data, and captures fault characteristics by analyzing abnormal changes in battery voltage unrelated to current. Theoretical analysis and tests verified that this method can diagnose these three kinds of faults. Sensor faults of excessive error and data sticking can also be distinguished. • The proposed method can diagnose short circuit faults, electrical connection faults and sensor faults. • The non-redundant interleaved voltage measurement topology does not require additional voltage sensors, which saves costs. • The introduction of time window avoids blocking the fault diagnosis process when a fault occurs. • Sensor faults of excessive error and data sticking can be distinguished. [ABSTRACT FROM AUTHOR]

A Convolution Neural Network and a Bidirectional Long Short-Term Memory network connected architecture with a Multi-Head Attention mechanism (CNN-BiLSTM-MHA) is studied for predicting state of charge (SOC) of lithium-ion batteries (LIBs). Firstly, an adaptive noise based complete ensemble empirical mode decomposition (AN-CEEMD) algorithm is adopted to catch the intrinsic features of measured battery signals by adding white noises. Secondly, a CNN-BiLSTM model with the MHA mechanism is developed to learn the mapping between processed input signals and battery SOC, it has three parts: 1) the CNN extracts features of the processed data, mine the relation among input signals, and promote estimation precision; 2) the BiLSTM has memory ability to catch battery dynamics, and the Swish activation function in the BiLSTM ensures unsaturated and reduces over-fitting due to its upper unbound and lower bound; 3) The multi-head attention mechanism uses several independent self-attention layers to associate input information and variables, extracts more associate information by adding weights; it reduces the overfitting risk of a single attention head, and improves the model generalization performance through joint learning of multiple heads. Finally, experiments and simulations are implemented under four operating conditions at five different temperatures, and the presented method is verified effective. • A CNN-BiLSTM network with multi-head attention (MHA) is explored to identify SOC. • The CNN extracts features of input data, and mine the relation among input signals. • The BiLSTM with feedback structure has memory ability to catch battery dynamics. • The MHA mechanism improves model performance through joint learning of multiple heads. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) stands as the predominant age-related neurodegenerative disorder, for which efficacious treatment remains elusive. An auspicious avenue for this disease lies in natural compounds sourced from tranditional medicine and plant origins. Parthenolide (PTN) is a natural product with multiple biological functionsand. Recent investigations have illuminated PTN's protective properties against neurological maladies; however, its potential therapeutic role against AD remains uncharted. This study aims to explore the role of PTN in treating AD. Our in vitro findings underscore PTN's bioactivity, as evidenced by its capacity to curtail apoptosis, reduce reactive oxygen species (ROS) production, and restore mitochondrial membrane potential in PC12 cells. Moreover, PTN treatment demonstrates a capacity to ameliorate deficits in spatial learning and memory in the 3 ×Tg-AD murine model. Notably, PTN's therapeutic efficacy surpasses that of a clinical agent, donepezil. Mechanistically, PTN's neuroprotective effects stem from its adept regulation of the AMPK/GSK3β(ser9)/Nrf2 signaling pathway and protection on neuronal cells from ROS-related apoptosis. Although the molecular target and the pre-clinical evaluations of PTN need to be further explored, this study indicates PTN as a potential agent or lead compound for the drug development against AD. [Display omitted] [ABSTRACT FROM AUTHOR]

Skeletal muscle, the largest organ in the human body, plays a crucial role in supporting and defending the body and is essential for movement. It also participates in regulating the processes of protein synthesis and degradation. Inhibition of protein synthesis and activation of degradation metabolism can both lead to the development of skeletal muscle atrophy, a pathological condition characterized by a decrease in muscle mass and fiber size. Many physiological and pathological conditions can cause a decline in muscle mass, but the underlying mechanisms of its pathogenesis remain incompletely understood, and the selection of treatment strategies and efficacy evaluations vary. Moreover, the early symptoms of this condition are often not apparent, making it easily overlooked in clinical practice. Therefore, it is necessary to develop and use cell models to understand the etiology and influencing factors of skeletal muscle atrophy. In this review, we summarize the methods used to construct skeletal muscle cell models, including hormone, inflammation, cachexia, genetic engineering, drug, and physicochemical models. We also analyze, compare, and evaluate the various construction and assessment methods. [Display omitted] • A summary of the current muscle atrophy cell models is provided to offer more assistance in studying muscle atrophy. • This paper highlights four cell models for skeletal muscle atrophy: C2C12, L6, primary cells and iPSCs. • We discuss factors including hormones, inflammatory factors, cachexia, drugs, genes, and physical-chemical factors. • Understanding these cell models helps grasp muscle atrophy and guides the construction of new experimental models. [ABSTRACT FROM AUTHOR]

Purpose. Developed a preoperative prediction model based on multimodality imaging to evaluate the probability of inferior vena cava (IVC) vascular wall invasion due to tumor infiltration. Materials and Methods. We retrospectively analyzed the clinical data of 110 patients with renal cell carcinoma (RCC) with level I-IV tumor thrombus who underwent radical nephrectomy and IVC thrombectomy between January 2014 and April 2019. The patients were categorized into two groups: 86 patients were used to establish the imaging model, and the data validation was conducted in 24 patients. We measured the imaging parameters and used logistic regression to evaluate the uni- and multivariable associations of the clinical and radiographic features of IVC resection and established an image prediction model to assess the probability of IVC vascular wall invasion. Results. In all of the patients, 46.5% (40/86) had IVC vascular wall invasion. The residual IVC blood flow (OR 0.170 [0.047-0.611]; P = 0.007), maximum coronal IVC diameter in mm (OR 1.203 [1.065-1.360]; P = 0.003), and presence of bland thrombus (OR 3.216 [0.870-11.887]; P = 0.080) were independent risk factors of IVC vascular wall invasion. We predicted vascular wall invasion if the probability was >42% as calculated by: Ln Pre / 1 − pre = 0.185 × maximum cornal IVC diameter + 1.168 × bland thrombus – 1.770 × residual IVC blood flow – 5.857 . To predict IVC vascular wall invasion, a rate of 76/86 (88.4%) was consistent with the actual treatment, and in the validation patients, 21/26 (80.8%) was consistent with the actual treatment. Conclusions. Our model of multimodal imaging associated with IVC vascular wall invasion may be used for preoperative evaluation and prediction of the probability of partial or segmental IVC resection. [ABSTRACT FROM AUTHOR]

Arsenic trioxide suppresses acute graft-versus-host disease by activating the Nrf2/HO-1 pathway in mice To further confirm that ATO alleviates GVHD symptoms mainly through activating the Nrf2/HO-1 pathway, we established the GVHD+PBS+ATO and GVHD+ML835+ATO groups. The GVHD+ML835+ATO mice showed shorter survival (Fig C) and increased levels of GVHD, as shown by the skin defects (Fig D) than the GVHD+PBS+ATO group. The peripheral blood CD4+ T/CD8+ T ratio (Fig F) and serum concentration of TNF-a and IFN- (Fig G), which were reduced by ATO, were also decreased in the GVHD+ ML835+ATO group. [Extracted from the article]

• Gal-1 overexpression strongly inhibits PRRSV replication in multiple strains. • Gal-1 knockdown or knockout facilitates PRRSV replication. • Interaction between Gal-1 and Nsp11 might regulate IFN and ISG activation. • Gal-1 exhibits antiviral activity against EAV, PEDV, JEV, PRV, and CSFV. • Gal-1 is potentially efficacious for applications to control PRRSV infection. Porcine reproductive and respiratory syndrome virus (PRRSV) causes great economic losses to the swine industry globally; however, effective control measures for this virus are limited. Here, we screened a porcine alveolar macrophage (PAM) cDNA library with a yeast two-hybrid system to reveal that galectin-1 (Gal-1), an endogenous innate immune protein encoded by LGALS1 , interacts with nonstructural protein 11 (Nsp11) of PRRSV. Western blotting and viral titer assays indicated that Gal-1 overexpression suppressed replication in multiple PRRSV strains (P < 0.001), whereas Gal-1 knockdown or knockout increased viral titer and nucleocapsid protein expression. The Gal-1-specific anti-PRRSV effect was associated with the endoribonuclease domain of Nsp11 through inactivation of interferon-antagonist function and stimulation of interferon-stimulated gene expression. Additionally, Gal-1 interacted with PRRSV E protein but not with PRRSV glycoproteins, and recombinant Gal-1 treatment inhibited PRRSV in PAMs and MARC-145 cells. Furthermore, Gal-1 inhibited replication in multiple viruses, including equine arteritis virus, porcine epidemic diarrhea virus, pseudorabies virus, Japanese encephalitis virus, and classical swine fever virus, suggesting its potential broad application for antiviral strategies. Our findings provide insight into the important role of Gal-1 in PRRSV pathogenesis and its potential use as a novel therapeutic target against PRRSV infection. [ABSTRACT FROM AUTHOR]

The safety of integrated circuit design has become a big challenge due to overbuilding, IC (Integrated Circuit) piracy, hardware Trojan, reverse engineering, and other attacks. Over the past decades, the demand for hardware security is increased continually in an integrated circuit. In this paper, we propose a new design of anti-key leakage camouflage gate for reverse engineering based on dummy vias. The design achieves the layout-level camouflage by using XOR, XNOR, buffer and inverter through via's realness, followed by extracting the camouflaged circuit's feature information to generate standard physical library. They are inserted into the circuit netlist to prevent the key leakage of IP solidification. The circuit is verified by TSMC 65 nm process and tested in ISCAS benchmark circuit. The results show that the newly-designed circuit attains 99% similarity in placing and routing in the layout, suggesting that the security of the hardware circuit can be greatly improved. [ABSTRACT FROM AUTHOR]

• ASFV p17 was successfully expressed in CHO cells using a suspension culture system. • 1B4 recognized a conservative linear epitope (8LLSHNLSTREGIK20) among genotype i and genotype II ASFV strains. • 1B4 effectively recognized the ectopically expressed p17 and foreign gene expression in recombinant PRRSV expressing ASFV p17. • 1B4 can be a useful tool to evaluate the expression of p17 in the recombinant virus, making it meaningful for future vaccine research on ASF. As a highly pathogenic large DNA virus, African swine fever virus (ASFV) has huge particles and numerous encoded proteins. At present, few of the existing studies on ASFV proteins have investigated the function of p17. Specific antibodies against p17 to promote the development of prevention techniques against African swine fever (ASF) are urgently needed. Herein, we successfully expressed ASFV p17 in CHO cells using a suspension culture system and generated a monoclonal antibody (mAb) against p17. The mAb recognized a novel linear epitope (8LLSHNLSTREGIK20) and exhibited specific reactivity, which was conducive to the identification of ectopically expressed p17, the recombinant porcine reproductive and respiratory syndrome virus expressing p17, and the ASFV-SY18. The epitope was conservative among genotype I and genotype II ASFV strains. Overall, the mAb against p17 revealed efficient detection and promising application prospects, making it a useful tool for future vaccine research on ASF. Determination of the conserved linear epitope of p17 would contribute to the in-depth exploration of the biological function of ASFV antigen protein. [ABSTRACT FROM AUTHOR]

A new technique to achieve a single bandpass microwave photonic filter (MPF) with wide tunability based on stimulated Brillouin scattering is proposed. The MPF cascades the Brillouin frequency shifter and amplification based on a dual‐fiber structure. The experimental results present a single bandpass MPF located at 21.4 GHz with a 3‐dB bandwidth of 38 MHz and an out‐of‐band rejection ratio over 30 dB. The proposed single bandpass MPF also successfully demonstrates a wide‐band tuning over 40 GHz, which is achieved by employing a frequency shifter based on carrier suppressed single‐sideband modulation scheme in the structure. [ABSTRACT FROM AUTHOR]

The harmonics of line to line voltage in two-stage matrix converter (TSMC) with fixed carrier frequency had discrete and high values and produced powerful electromagnetic interference (EMI). In this paper, chaotic carrier frequency modulation technique (CCFMT) was applied in TSMC for the first time to spread sideband range and suppress harmonic peak value. Although this technique could suppress EMI, it would increase the probability of narrow pulses. In order to improve reliability, the rectifier in the two-stage matrix converter uses PWM modulation with zero vector to extend the zero current commutation time, solves the narrow pulse problem, and simplifies the commutation process. At last, an experiment platform was designed and experimental results showed that harmonics of line to line voltage was efficiently suppressed. [ABSTRACT FROM AUTHOR]

The harmonics of line to line voltage in two-stage matrix converter (TSMC) with fixed carrier frequency had discrete and high values and produced powerful electromagnetic interference (EMI). In this paper, chaotic carrier frequency modulation technique (CCFMT) was applied in TSMC for the first time to spread sideband range and suppress harmonic peak value. Although this technique could suppress EMI, it would increase the probability of narrow pulses. In order to improve reliability, the rectifier in the two-stage matrix converter uses PWM modulation with zero vector to extend the zero current commutation time, solves the narrow pulse problem, and simplifies the commutation process. At last, an experiment platform was designed and experimental results showed that harmonics of line to line voltage was efficiently suppressed. [ABSTRACT FROM AUTHOR]

Porcine galectin-3 (GAL3) is a 29-kDa protein encoded by a single gene, LGALS3 , located on chromosome 1. Here, using a yeast two-hybrid screen of a cDNA library from porcine alveolar macrophage cells (PAMs), we report for the first time that GAL3 interacts with nonstructural protein 12 (Nsp12) of the porcine reproductive and respiratory syndrome virus (PRRSV). Although extensive research has focused on porcine reproductive and respiratory syndrome (PRRS), little is known about the pathogen and host interactions involving individual nonstructural viral proteins, especially Nsp12. Here, we showed that GAL3 interacted with viral Nsp12 following co-transfection of HEK293 cells with GAL3- and Nsp12-expressing plasmids. Additionally, we observed that PPRSV infection led to reduced GAL3 levels during the late phase of infection in both MARC-145 cells and PAMs. Importantly, GAL3 overexpression significantly suppressed the replication of both type 1 and 2 PRRSV strains, whereas knockout of endogenous LGALS3 in MARC-145 cells significantly increased viral titer and expression of the nucleocapsid protein. These results strongly support a direct inhibitory effect of GAL3 on PRRSV replication, which might contribute to an overall antiviral effect. Furthermore, our findings provide insights into the molecular basis of the role Nsp12 plays in PRRSV pathogenesis. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) contribute to gene regulation at the post-transcriptional level and are capable of mRNA silencing by binding to target sites exhibiting high degrees of complementarity. Therefore, cloning host miRNA-recognition sequences into the genome of RNA viruses represents a rational strategy for manipulating viral replication. Here, we performed deep sequencing to obtain small-RNA (sRNA)-expression profiles from in vitro-cultured MARC-145 cells post infection with porcine reproductive and respiratory syndrome virus (PRRSV) and chose six candidate miRNAs of different abundance (miR-21, miR-140-3p, miR-185, miR-26a, miR-505, and miR-199a) for further study. Based on the full-length cDNA clone p7USC, we constructed a number of PRRSV mutants that provided complementary base-pairing target sites for the miRNAs in 3′ untranslated regions. Our results showed that all low- and moderate- abundant miRNA-target mutants showed similar growth properties, whereas the highest-abundant miRNA-target mutant blocked both viral transcription and replication. Discontinuous mutations in high-abundant miRNA-target sites subsequently recovered viral viability and propagation. These results demonstrated the copy number of endogenous miRNAs and the extent of sRNA complementarity were key factors to silence potential mRNA expression/translation, thereby determining PRRSV viability. Interestingly, the mutant containing miR-140-target sites (v140-t) showed strong suppression of viral replication from P1 to P3 in vitro, as shown by virus titer, plaque morphology, and qRT-PCR assays. To assess genetic stability, sequencing of v140-t (P1, P3, P5 and P10) revealed spontaneous mutations preferentially located among several nucleotides near the 3′ end of the insertion region and corresponding to the “seed region” of miR-140-3p, explaining the induced viral repression and the direction of virus evolution. This approach provided a general silencing strategy for limiting PRRSV replication by endogenous miRNAs in MARC-145 cells. [ABSTRACT FROM AUTHOR]

Porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important viral pathogens that has caused tremendous economic losses to the swine industry worldwide. Although extensive research has been focused on PRRSV, little is known about the structure and biological functions of individual nonstructural viral proteins, especially the nonstructural protein 12 (Nsp12). In this study, we generated and identified the monoclonal antibody (mAb) against PRRSV Nsp12. Six strains of hybridoma cells named 2B10, 2B12, 5E1, 5G6, 5E7, and 8B2 secreting anti-Nsp12 mAbs were obtained by the hybridoma technique. All the mAbs were specifically reacted with PRRSV by indirect immunofluorescence assay and four of them (2B12, 5E1, 5G6, and 5E7) were specifically reacted by Western blot. Furthermore, the 5E7 specifically recognized multiple type 2 PRRSV strains, including highly pathogenic and classical PRRSV strains, but not type 1 PRRSV strain. Taken together, the mAbs against Nsp12 provide a valuable tool to specifically recognize type 2 PRRSV as a diagnostic reagent and study the biological function of Nsp12 in the future. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient method based on orthogonal polynomial function (OPF) fitting for hyperspectral remote sensing data representation and discrimination. Given a spectral signature, it is first divided into spectral segments by a splitting strategy. Then, the extracted segments are fitted via OPF fitting. The fitting coefficients of the input spectrum are selected for data representation and discrimination. To validate the usefulness of the proposed method, laboratory spectra and real hyperspectral data were selected for experimental analysis. The results showed that our method can efficiently mine geometric structural information of spectral signatures and compress them into a few fitting parameters. These parameters can be used to sparsely represent the input spectra and effectively distinguish different spectral signatures. In terms of representation, the proposed method is superior to the traditional inverse Gaussian function (IGF) model. Moreover, the OPF sparse feature exhibits better performance than the typical wavelet-based method in terms of achieving a trade-off between feature length and reconstruction error. Furthermore, the use of an optimized nonlinear SVM classifier shows that the discriminative ability for OPF normal features generally improves as the feature length increases and become relatively stable after the length reaches 30. Also the OPF features with the length of 30 can achieve comparable overall accuracies for the original bands and the typical wavelet-based features. As our method is data dependent, the optimal parameter value may vary for different data. In addition, the proposed feature extraction method is very fast and improves the computational efficiency significantly. Overall, the proposed method has considerable potential from the perspective of hyperspectral data analysis. [ABSTRACT FROM AUTHOR]

As a key influence factor on the lifetime of pulsed capacitors, the repetitive frequency (fR) of charge/discharge is studied in this paper based on the theory of space charge. A fact that in the absence of heat accumulation, from 0.1 to 10 Hz, the lifetime of capacitors increases with the fR is found. The measurement of space charge induced by charge/discharge at various frequencies is conducted. The measurement result indicates that the amount of space charge in capacitors experienced charge/discharge at 0.1 Hz is 29% higher than that of 10 Hz, which can reasonably explain why the lifetime of capacitors tested at 10 Hz is twice of that at 0.1Hz. Besides, a simplified TSDC is carried out to qualitatively measure the trap density of capacitors experienced lifetime tests, and found that the traps formed during charge/discharge tests at 0.1 Hz is more than 7x that of 10 Hz. The dielectric loss angle tangent (tan?) of capacitors which have experienced charge/discharge at various frequencies is also tested, and from the tan? tested at 0.001 Hz, (3.7 when fR is 0.1 Hz and 2.4 when fR is 10 Hz), it is revealed that the aging of pulsed capacitors can be slowed by enhancing the fR of charge/discharge, which matches well with the results of lifetime test. [ABSTRACT FROM AUTHOR]

A three-dimensional modelling approach is used to study the effects of operating and ambient conditions on the thermal behaviour of the spiral wound supercapacitor. The transient temperature distribution during cycling is obtained by using the finite element method with an implicit predictor-multicorrector algorithm. At the constant current of 2A, the results show that the maximum temperature appears in core area. After 5 cycles, the maximum temperature is 34.5°C, while in steady state, it’s up to 42.5°C. This paper further studies the relationship between the maximum temperature and charge-discharge current. The maximum temperature will be more than 60°C after 5 cycles at the current of 4A, and cooling measurements should be taken at that time. It can provide thoughts on inner temperature field distribution and structure design of the spiral wound supercapacitor in working process. [ABSTRACT FROM AUTHOR]

In this article, a new strategy is proposed for soft urban land-cover extraction based on mixed training data and Support Vector Machines (SVMs). The strategy is applied to soft classification of urban water cover using Landsat 8 multispectral data in Beijing. The results are validated with extensive manual mapping data and are compared with the results derived from a well-trained SVM and the linear spectral unmixing method using only pure samples. Our experimental results indicate that the proposed strategy works effectively in extracting the water cover in the urban image. The results are better than those obtained by SVM and linear spectral unmixing with only pure samples. Our findings demonstrate that the combination of image-based mixed training data and SVM enhances the strengths of kernel-based approaches for soft mapping urban land cover from imaging data. Therefore, the proposed workflow constitutes a new flexible and extendable approach to soft mapping urban land cover. Future work includes the construction of a comprehensive image-based spectral library for urban areas, and the testing of the proposed strategy on additional land-cover types in urban areas such as grass, tree, and bare soil. [ABSTRACT FROM PUBLISHER]

MicroRNAs (miRNAs) play important roles in viral infections, especially by modulating the expression of cellular factors essential to viral replication or the host innate immune response to infection. To identify host miRNAs important to controlling porcine reproductive and respiratory syndrome virus (PRRSV) infection, we screened 15 miRNAs that were previously implicated in innate immunity or antiviral functions. Over-expression of the miR-26 family strongly inhibited PRRSV replication in vitro, as shown by virus titer assays, Western blotting, and qRT-PCR assays. MiR-26a inhibited the replication of both type 1 and type 2 PRRSV strains. Mutating the seed region of miR-26 restored viral titers. Luciferase reporters showed that miR-26a does not target the PRRSV genome directly but instead affects the expression of type I interferon and the IFN-stimulated genes MX1 and ISG15 during PRRSV infection. These results demonstrate the important role of miR-26a in modulating PRRSV infection and also support the possibility of using host miR-26a to achieve RNAi-mediated antiviral therapeutic strategies. [ABSTRACT FROM AUTHOR]

Abstract: Nitrogen-doped graphene is prepared by a solid microwave method with EDA (ethylenediamine) as the nitrogen source. The experimental results reveal that nitrogen atoms from the grafted EDA molecules on the surface of graphene are successfully doped into the lattices. The NGS (nitrogen-doped graphene nanosheets) sample exhibits outstanding specific capacitances of 197 and 151 F g−1 at the current densities of 0.5 and 5 A g−1 in 6.0 mol L−1 KOH aqueous electrolyte, respectively. Furthermore, the sample also displays more superior rate capacity, which can possess high specific capacitance retention of 77% and 70% at the high current densities of 5 and 40 A g−1, respectively. In addition, a capacity fading lower than 2% after 5000 cycles of charging and discharging is obtained, indicating its long-term electrochemical stability. [Copyright &y& Elsevier]

Numerical modeling of the effect of the gap between electrodes on the MTF of an example liquid crystal lens is presented. The results are compared with those of a lens using a layer of “floating” electrodes above the addressed concentric ring electrodes. [ABSTRACT FROM PUBLISHER]

• An unknown input observer framework is utilized to construct the interval observer to avoid the cooperativity constraint in estimation error dynamics. • The corresponding control scheme composed of upper-lower bounds of the controller is established to treat the time-varying parameter in control input channel. • Sufficient conditions are formulated as LMIs to guarantee the finite-time boundedness of error systems. The paper is concerned with the finite-time control of linear parameter-varying systems by means of the interval observer method. An unknown input observer framework is utilized to construct the interval observer to avoid the cooperativity constraint in estimation error dynamics. The corresponding control scheme composed of upper-lower bounds of the controller is established to treat the time-varying parameter in control input channel. Sufficient conditions are formulated as LMIs to guarantee the finite-time boundedness of error systems. The effectiveness of the proposed strategy is evaluated by numerical simulations. [ABSTRACT FROM AUTHOR]

Abstract: Molybdenum carbide nanoclusters supported on alumina were promoted by Rb2CO3 and tested for higher alcohol synthesis from syngas. At 573K and 30bar syngas (H2/CO=1), the promoted catalyst demonstrated 63% selectivity to alcohols (on a CO2-free basis), with hydrocarbons and ethers as side products. In contrast, the alcohol selectivity of an unpromoted Mo2C/Al2O3 catalyst was very low. DRIFTS of adsorbed CO on Mo2C/Al2O3 revealed a significant red shift in the CO band with added Rb promoter, which correlated to a decrease in hydrocarbon production rate and therefore an increase in alcohol selectivity. A quantum chemical description of CO adsorbed on a model Mo2C surface identified several possible binding modes of the CO. Both reactivity studies and DRIFTS of adsorbed CO demonstrated that mobility of the Rb promoter was enhanced in the presence of water vapor, which facilitates dispersion of Rb across the catalyst surface and effectively neutralizes acid sites that are deleterious to alcohol selectivity. [Copyright &y& Elsevier]

Combining spectral and morphological information to classify hyperspectral data offers a considerable advantage over methods based solely on spectral or morphological data. Previously, a classification method was proposed that concatenated extended morphological profile (EMP) and spectral information into one feature vector for each pixel of an image. Although this method has the merit of simultaneously using spectral and morphological information, it runs the risk of generating new spectral constituents (not present in the original image). In this letter, an improved classification method based on fusing extended multivariate morphological profile (EMMP) and spectral information was proposed. A new vector ordering method based on spectral purity-based criterion was adopted to overcome the problem of generating new constituents in EMP. A feature selection algorithm was employed to improve the efficiency of EMMP. Experiments were carried out on a hyperspectral data set collected by NASA's Airborne Visible-Infrared Imaging Spectrometer sensor. Experimental results showed that EMMP was effective at describing morphological information in hyperspectral data, and that this letter's method was superior to the previous method in terms of classification accuracy but inferior to the previous method in terms of time consumption. [ABSTRACT FROM AUTHOR]

The success of antibody-based pharmaceuticals has led to a resurgence in interest in computational structure-based design. Most efforts to date have been on the redesign of existing interfaces. These efforts have mostly neglected the inherent flexibility of the receptor that is critical for binding. In this work, we extend on a previous study to perform a series of designs of protein binding interfaces by incorporating receptor flexibility using an ensemble of conformers collected from explicit-solvent molecular dynamics (MD) simulations. All designer complexes are subjected to 30 ns of MD in explicit solvent to assess for stability for a total of 480 ns of dynamics. This is followed by end-point free energy calculations whereby intermolecular potential energy, polar and non-polar solvation energy and entropy of ligand and receptor are subtracted from that of the complex and averaged over 320 snapshots collected from each of the 30 ns MD simulations. Our initial effort consisted of redesigning the interface of three well-studied complexes, namely barnase–barstar, lysozyme–antibody D1.3 and trypsin–BPTI. The design was performed with flexible backbone approach. MD simulations revealed that all three complexes remained stable. Interestingly, the redesigned trypsin–BPTI complex was significantly more favorable than the native complex. This was attributed to the favorable electrostatics and entropy that complemented the already favorable non-polar component. Another aspect of this work consisted of grafting the surface of three proteins, namely tenascin, CheY and MBP1 to bind to barnase, trypsin and lysozyme. The process was initially performed using fixed backbone, and more than 300 ns of the explicit-solvent MD simulation revealed some of the complexes to dissociate over the course of the trajectories, whereas others remained stable. Free energy calculations confirmed that the non-polar component of the free energy as computed by summing the van der Waals energy and the non-polar solvation energy was a strong predictor of stability. Four complexes (two stable and two unstable) were selected, and redesigned using multiple conformers collected from the MD simulation. The resulting designer systems were then immersed in explicit solvent and 30 ns of MD was carried out on each. Interestingly, those complexes that were initially stable remained stable, whereas one of the unstable complexes became stable following redesign with flexible backbone. Free energy calculations showed significant improvements in the affinity for most complexes, revealing that the use of multiple conformers in protein design may significantly enhance such efforts. [ABSTRACT FROM PUBLISHER]

The significant work that has been invested toward understanding protein-protein interaction has not translated into significant advances in structure-based predictions. In particular redesigning protein surfaces to bind to unrelated receptors remains a challenge, partly due to receptor flexibility, which is often neglected in these efforts. In this work, we computationally graft the binding epitope of various small proteins obtained from the RCSB database to bind to barnase, lysozyme, and trypsin using a previously derived and validated algorithm. In an effort to probe the protein complexes in a realistic environment, all native and designer complexes were subjected to a total of nearly 400 ns of explicit-solvent molecular dynamics (MD) simulation. The MD data led to an unexpected observation: some of the designer complexes were highly unstable and decomposed during the trajectories. In contrast, the native and a number of designer complexes remained consistently stable. The unstable conformers provided us with a unique opportunity to define the structural and energetic factors that lead to unproductive protein-protein complexes. To that end we used free energy calculations following the MM-PBSA approach to determine the role of nonpolar effects, electrostatics aid entropy in binding. Remarkably, we found that a majority of unstable complexes exhibited more favorable electrostatics than native or stable designer complexes, suggesting that favorable electrostatic interactions are not prerequisite for complex formation between proteins. However, nonpolar effects remained consistently more favorable in native and stable designer complexes reinforcing the importance of hydrophobic effects in protein-protein binding. While entropy systematically opposed binding in all cases, there was no observed trend in the entropy difference between native and designer complexes. A series of alanine scanning mutations of hot-spot residues at the interface of native and designer complexes showed less than optimal contacts of hot-spot residues with their surroundings in the unstable conformers, resulting in more favorable entropy for these complexes. Finally, disorder predictions revealed that secondary structures at the interface of unstable complexes exhibited greater disorder than the stable complexes. [ABSTRACT FROM AUTHOR]

High-rise buildings (HRBs) as a modern and visually distinctive land use play an important role in urbanization. Large-scale monitoring of HRBs is valuable in urban planning and environmental protection and so on. Due to the complex 3D structure and seasonal dynamic image features of HRBs, it is still challenging to monitor large-scale HRBs in a routine way. This paper extends our previous work on the use of the Fully Convolutional Networks (FCN) model to extract HRBs from Sentinel-2 data by studying the influence of seasonal and spatial factors on the performance of the FCN model. 16 Sentinel-2 subset images covering four diverse regions in four seasons were selected for training and validation. Our results indicate the performance of the FCN-based method at the extraction of HRBs from Sentinel-2 data fluctuates among seasons and regions. The seasonal change of accuracy is larger than that of the regional change. If an optimal season can be chosen to get a yearly best result, F1 score of detected HRBs can reach above 0.75 for all regions with most errors located on the boundary of HRBs. FCN model can be trained on seasonally and regionally combined samples to achieve similar or even better overall accuracy than that of the model trained on an optimal combination of season and region. Uncertainties exist on the boundary of detected results and may be relieved by revising the definition of HRBs in a more rigorous way. On the whole, the FCN based method can be largely effective at the extraction of HRBs from Sentinel-2 data in regions with a large diversity in culture, latitude, and landscape. Our results support the possibility to build a powerful FCN model on a larger size of training samples for operational monitoring HRBs at the regional level or even on a country scale. [ABSTRACT FROM AUTHOR]

Abstract: Toxoplasma gondii (T. gondii) invasion of host cells is a complicated process of interaction between parasites and host cells. In the present study we investigated the alterations of free Ca2+ concentration ([Ca2+]i) and cytoskeletons in phagocytic and non-phagocytic host cells and arachidonic acid (AA) concentration in cells supernatant during T. gondii invasion. T. gondii invasion induced significant elevation of intracellular [Ca2+]i in phagocytic cells (J774A.1) but not in non-phagocytic cells (L929). Pre-treatment of J774A.1 cells with Phospholipase C (PLC) inhibitor (U73122), or Ca2+ chelators (EGTA, BAPTA/AM) did not block elevations of [Ca2+]i but the elevations were lower and of shorter duration than that in untreated cells. Pre-treatment of tachyzoites with Phospholipases A (PLA) inhibitors (4-BPB and AACOCF3) resulted in a similar pattern of increasing of [Ca2+]i as that in Ca2+ chelators treated cells. Agglutinations of microfilaments were observed in J774A.1 cells but not in L929 cells. No changes of microtubules were observed in either cell. Treatment of cells with cytoskeleton inhibitors (colchicines, cytochalasin-D) resulted in reduced cell infection ratios. AA concentration in J774A.1 cells supernatant reached 8.44-fold of basal concentration after T. gondii infection and those in 4-BPB or AACOCF3 pre-treated cells reached 7.70-fold and 8.09-fold of basal concentration, respectively. However, elevation of AA concentrations induced by 4-BPB or AACOCF3 treated tachyzoites were 3.02-fold and 2.65-fold of basal AA concentration. AA concentration in L929 cells supernatant reached 5.02-fold of basal concentration after T. gondii infection and those in 4-BPB or AACOCF3 pre-treated cells reached 4.75-fold and 4.78-fold of basal concentration, respectively. However, elevation of AA concentrations induced by 4-BPB or AACOCF3 treated tachyzoites were 2.06-fold and 2.43-fold of basal AA concentration. Results indicated that elevations of [Ca2+]i and AA induced by T. gondii invasion were from both host cells and parasites. T. gondii invasion activated host cell PLC and triggered the PLC-PKC signal pathway, which resulted in the flowing of extracellular Ca2+ and the releasing of intracellular Ca2+ pool. Elevated [Ca2+]i induced reorganization of host cell microfilaments. The invasion also activated secretory PLA2 (sPLA2) and cytosolic PLA2 (cPLA2) of the parasite to release AA, which increased the permeability of cell membrane. [Copyright &y& Elsevier]

Abstract: Single junction p-i-n μc-Si:H solar cells were prepared in a low-cost, large-area single chamber radio frequency plasma enhanced chemical vapor deposition system. The effects of seeding processes on the growth of μc-Si:H i-layers and performance of μc-Si:H solar cells were investigated. Seeding processes, usually featured by highly hydrogen rich plasma, are effective in inducing the growth of μc-Si:H i-layers. It has been demonstrated that p-layer seeding methods are preferable to i-layer seeding. While performance of μc-Si:H solar cells produced by i-layer seeding methods was usually limited by very low fill factors, μc-Si:H solar cells with good initial and stabilized conversion efficiencies were obtained by p-layer seeding. [Copyright &y& Elsevier]

Abstract: In this study, direct structural characterization of μc-Si:H solar cells deposited by conventional RF-PECVD was conducted using Raman spectroscopy, XRD, and AFM. Strong correlations between i-layer structural properties and device performance were established. A wide variety of i-layer microstructures, from mixed-phase Si:H to highly crystalline μc-Si:H, were revealed by Raman scattering. Micro-crystallinity obtained from Raman scattering, presented as Ic/Ia, proved to be sensitive to the microstructure of μc-Si:H i-layers. Strong spatial non-uniformity of i-layer microstructure as well as variations in device performance were observed. It has been demonstrated here that stable, high performance μc-Si:H solar cells can only be obtained with i-layers being μc-Si:H, yet close to the μc-Si:H to mixed-phase Si:H transition edge where an optimum micro-crystallinity range (Ic/Ia at around 1.8) was identified. It was shown by XRD experiments that high performance, optimum μc-Si:H solar cells exhibit smaller grain sizes compared to solar cells with i-layers showing higher micro-crystallinity. Correlations among non-uniformity pattern, i-layer micro-crystallinity, and AFM surface morphologies were also observed. [Copyright &y& Elsevier]

Lithium-ion batteries have been used in all aspects of life for environmental and resource reasons. The accurate estimation of the state of charge (SOC) ensures the proper operation of the battery. However, few methods have focused on the problem of SOC estimation at low temperatures. A hybrid method based on the CNN-BWGRU network is proposed in this paper. The method optimizes the influence of battery information on the results through a "multi-moment input" structure and the bidirectional network. The convolutional neural network (CNN) is used to learn the feature parameters in the input. The bidirectional weighted gated recurrent unit (BWGRU) can improve the fitting performance of the network at low temperatures by changing the weights. The proposed network has a strong generalization capability, estimation accuracy, and robustness. SOC estimation is performed under different conditions to verify the plausibility of the network. The experimental results show that the method has higher accuracy and stability than other networks. In addition, the proposed method can overcome the effect of different initial SOC on the estimation results. Therefore, the CNN-BWGRU network provides a new method in battery SOC estimation while providing helpful guidance for safe and stable battery operation in natural environments. [Display omitted] [ABSTRACT FROM AUTHOR]

Highlights: EIS was used to estimate the SOH of LIBs found to be fast and effective. It is more convenient to use CNN to extract features of EIS data automatically. The improved ECM method and IPSO-CNN-BiLSTM method are proposed in this paper. IPSO algorithm was first proposed to applied to the problem of optimizing the initial parameters of the neural networks. The state of health (SOH) is critical to the efficient and reliable use of lithium-ion batteries (LIBs). Recently, the SOH estimation method based on electrochemical impedance spectroscopy (EIS) has been proven effective. In response to different practical applications, two models for SOH estimation are proposed in this paper. Aiming at based on the equivalent circuit model (ECM) method, a variety of ECMs are proposed. Used EIS to predict the ECM, the results show that the improved method ensures the correctness of the ECM and improves the estimation results of SOH. Aiming at a data-driven algorithm, proposes a convolution neural network (CNN) to process EIS data which can not only extract the key points but also simplifies the complexity of manual feature extraction. The bidirectional long short-term memory (BiLSTM) model was used for serial regression prediction. Moreover, the improved Particle Swarm Optimization (IPSO) algorithm is proposed to optimize the model. Comparing the improved model (IPSO-CNN-BiLSTM) with the traditional PSO-CNN-BiLSTM, CNN-BiLSTM and LSTM models, the prediction results are improved by 13.6%, 93.75% and 94.8%, respectively. Besides that, the two proposed methods are 27% and 35% better than the existing gaussion process regression (GPR) model, which indicates that the proposed improved methods are more flexible for SOH estimation with higher precision. [ABSTRACT FROM AUTHOR]

Ozone (O3) is an important secondary substance that plays a significant role in atmospheric chemistry and climate change. Although O3 is essential in the stratosphere, it is harmful to human health in the troposphere, where this study was conducted. In recent years, O3 pollution in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions has deteriorated, which has become an important environmental problem. The generation of O3 is closely related to meteorological factors. In this study, the weather classification method was adopted to study the effect of meteorological conditions on O3 concentration. In the BTH region, Tianjin was selected as the representative city for the research. The real-time pollutants data, meteorological re-analysis data, and meteorological data in 2019 were combined for the analysis. The subjective weather classification method was adopted to investigate the effects of different weather types on O3 concentration. The backward trajectory tracking model was used to explore the characteristics and changes of O3 pollution under two extreme weather types. The results indicate there is a good correlation between O3 concentration and ambient temperature. Under the control of low pressure on the ground and the influence of southwest airflow in the upper air for Tianjin, heavy O3 pollution occurred frequently. The addition of external transport and local generation will cause high O3 values when the weather system is weak. The O3 concentration is closely related to ambient temperature. Continuous high-temperature weather is conducive to the photochemical reaction. The multi-day O3 pollution process would occur when the weather system is robust. The first and second types of extreme weather are more likely to cause persistent O3 pollution processes. Under the premise of stable emission sources, the change in weather patterns was the main reason affecting the O3 concentration. This study aims to improve O3 pollution control and air quality prediction in the BTH region and large cities in China. [ABSTRACT FROM AUTHOR]

This paper is concerned with anti-disturbance output feedback control of uncertain systems via dynamic guaranteed cost triggering mechanism. An output disturbance observer is constructed to attenuate matched disturbances and the mismatched one is attenuated by the H ∞ approach. A new dynamic event-triggered mechanism is established in terms of guaranteed cost triggering condition and triggering threshold. A composite controller is built on an observer based state feedback controller and an output disturbance compensator. By employing the Lyapunov stability method, a sufficient condition is presented in the framework of linear matrix inequality to ensure the asymptotic stability of the closed-loop system with the prescribed cost. Comparative simulation studies are supplied to verify the effectiveness of the proposed composite control scheme. • Compared with the state DOB [25] , an output DOB is established firstly to reconstruct matched disturbances in input channels. • A new dynamic ETM is put forward and contains [36] as a special case. • A composite controller is constructed by an observer-based state feedback controller and a disturbance compensator. • A structural separation technique is utilized to tackle the controller gain and the observer gains. [ABSTRACT FROM AUTHOR]

A new continuously tunable optoelectronic oscillator based on shifted dispersion‐induced RF‐fading is proposed and experimentally demonstrated. The design provides wideband continuously all‐optical tunability by incorporating the shifted RF‐fading based on a Mach‐Zehnder structure in an optoelectronic feedback loop. By simply varying the path difference between the two arms of the Mach‐Zehnder configuration via an adjustable variable delay line, the fundamental frequency of the oscillator can achieve extremely high and continuous tuning with a frequency upper bound dependent on the delay properties of the variable optical delay line. [ABSTRACT FROM AUTHOR]

• RNF114 exhibits significant anti-PRRSV activity. • RNF114 knockdown facilitates PRRSV replication. • PRRSV infection leads to endogenous RNF114 upregulation. • The E3 ligase RNF114 interacts with Nsp12 and promotes its proteasomal degradation. • RNF114 catalyzes K27-linked polyubiquitination of PRRSV Nsp12. Porcine reproductive and respiratory syndrome virus (PRRSV) poses a significant threat to the swine industry worldwide, and the development of effective and sustainable measures to control PRRSV transmission remains a pressing problem. The function of PRRSV nonstructural protein 12 (Nsp12), which might play essential roles in viral replication and production, remains unknown. In this study, we identified a new host-restricted factor, porcine RING finger protein 114 (RNF114), as an inhibitor of PRRSV replication through its degradation of viral Nsp12. Western blot, quantitative real-time polymerase chain reaction, and viral titer assays indicated that RNF114 overexpression suppressed PRRSV replication, whereas RNF114 knockdown increased viral titer and nucleocapsid protein levels. Additionally, we observed that PPRSV infection led to increased RNF114 levels during the middle and late phases of infection in both porcine alveolar macrophages and MARC-145 cells. Moreover, screening of PRRSV Nsps showed that RNF114 interacted with viral Nsp12, and that RNF114-specific anti-PRRSV effects were associated with its ubiquitin ligase activity, which involves K27-linked polyubiquitination and degradation of Nsp12 through a proteasome-dependent pathway. These findings identified RNF114 as a critical regulator of PRRSV replication and offer insights into the roles of Nsp12 in PRRSV pathogenesis. [ABSTRACT FROM AUTHOR]

Cladophora qinghaiensis, an endemic species of Cladophora in saltwater lakes, was scientifically named in 2021 (hereafter referred to as Cladophora). Cladophora exists in different morphologies, including attached submerged Cladophora (AC), grown floating Cladophora (GFC), and death floating Cladophora (DFC). Previous satellite remote sensing has mainly focused on identifying floating algae. In this study, Qinghai Lake served as a case study, and a classification decision tree model (CDTM) was proposed. The model employed the chlorophyll spectral index (CSI) and the normalized difference vegetation index (NDVI) to differentiate AC, Floating Cladophora (FC), and water. Additionally, the floating Cladophora index (FCI) was introduced to further distinguish GFC and DFC within FC. The method was applicable to Sentinel-2 images from 2016–2023. Visual interpretation methods were used for Landsat series images from the summer months (July to September) to obtain the AC and FC. The results demonstrate that over the past 30 years, the areas inhabited by AC and FC have increased gradually. The three morphologies of Cladophora also exhibited seasonal variations, with growth observed annually in May–June, reaching peaks in August–September, and gradually declining in October. In addition, by combining factors such as water surface area and climatic factors, we analyzed the driving forces influencing the changes in Cladophora. In this research, AC and FC showed significant correlations with the water surface area, with correlation coefficients (r) of approximately 0.9 and 0.7, respectively. These new findings provide valuable insights regarding the spatiotemporal changes and underlying causes for different morphologies of Cladophora in global saline lakes. [ABSTRACT FROM AUTHOR]

This paper studies the use of the Fully Convolutional Networks (FCN) model in the extraction of water bodies from Very High spatial Resolution (VHR) optical images in the case of limited training samples. Two different seasonal GaoFen-2 images with a spatial resolution of 0.8 m in the south of the Beijing metropolitan area were used to extensively validate the FCN model. Four key factors including input features, training data, transfer learning, and data augmentation related to the performance of the FCN model were empirically analyzed by using 36 combinations of various parameter settings. Our findings indicate that the FCN-based method can work as a robust and cost-effective tool in the extraction of water bodies from VHR images. The FCN-based method trained on a small amount of labeled L1A data can also significantly outperform the Normalized Difference Water Index (NDWI) based method, the Support Vector Machine (SVM) based method, and the Sparsity Model (SM) based method, even when radiometric normalization and spatial contexts are introduced to preprocess the input data for the latter three methods. The advantages of the FCN-based method are mainly due to its capability to exploit spatial contexts in the image, especially in urban areas with mixed water and shadows. Though the settings of four key factors significantly affect the performance of the FCN based method, choosing a qualified setting for the FCN model is not difficult. Our lessons learned from the successful use of the FCN model for the extraction of water from VHR images can be extended to extract other land covers. [ABSTRACT FROM AUTHOR]

Due to complex configuration of high power integrated PEMFC systems, the associated systematic condition assessment is still a promising challenge. In this paper, an online systematic condition assessment architecture for high-power integrated PEMFC systems is put forward based on random matrix analysis. The proposed architecture consists of two cascaded procedures, which are the streaming formulation of random characteristic matrices and random matrix analysis based systematic condition assessment, respectively. Benefited from the signal cluster transformation by the fusion of model-driven and data-driven approaches, the residuals characterizing system abnormal can be extracted to formulate the streaming random matrices. On this basis, by recursive eigenpairs' updating of random covariance matrices, high-dimensional analysis can be conducted in real-time even with random tensor augmentation-based matrix dimension expansion, and the systematic condition assessment indicators can be derived. Taking temperature anomaly awareness as an example, detailed experiment results demonstrate that, the derived indicators are more sensitive to system anomaly than traditional threshold-based condition assessment method, and the online evaluation of the operation condition of integrated PEMFC systems can be achieved more effectively under the proposed systematic condition assessment architecture. Finally, a recommended online robust systematic condition assessment procedure with the fusion of multi-indicators is demonstrated. To our best knowledge, this paper represents the attempt to put random matrix analysis into the online systematic condition assessment of high-power integrated PEMFC systems for the first time. • Online condition assessment architecture for integrated PEMFC systems is proposed. • Cascaded two procedures for the proposed architecture are discussed in detail. • The proposed architecture applied to an integrated PEMFC system is evaluated. • The derived systematic condition assessment indicators and control limits are verified. • A robust systematic condition assessment procedure is proposed and demonstrated. [ABSTRACT FROM AUTHOR]

Microwave photonics (MWPs) is an emerging interdisciplinary field, where photonics technologies are adopted to facilitate the generation, transmission, detection, and processing of signals at radio-wave, microwave, and millimeter-wave frequencies. Recently, the integrated photonic technology has demonstrated its capability to miniaturize photonic circuits on a single chip, which paves the way for next-generation integrated MWP signal processing systems having reduced size, weight, and power consumption (SWaP) specifications. In particular, by means of incorporating complementary metal-oxide-semiconductor (CMOS) electronic, optical, and optoelectronic components on a single integrated chip, silicon photonic circuits have brought new architectures and functionalities for MWP signal processing. This accelerates the evolution of MWPs from a single-use microwave signal processor toward a multitasking and cascadable MWP system, which is readily adaptable for a wide variety of uses and applications. In this review article, we provide an overview of the fundamental principle of the MWP signal processing topology. Developments in the microwave filtering technologies are reviewed with a focus on the integrated microwave filtering enhanced by optical phase equalization. We also review the recent progress and give an outlook for the future trend in MWP signal topologies, exploring the realization of multitasking and cascadable microwave signal processing systems based on silicon photonics. [ABSTRACT FROM AUTHOR]