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Abstract In spatial crowdsourcing services, the trajectories of the workers are sent to a central server to provide more personalized services. However, for the honest-but-curious servers, it also poses a challenge in terms of potential privacy leakage of the workers. Local differential privacy (LDP) is currently the latest technique to protect data privacy. However, most of LDP-based schemes have limitations in providing good utility due to extensive noise in perturbing trajectories. In this work, to balance the privacy and utility, we propose a novel pattern-aware privacy protection method called trajectory-aware privacy-preserving with local differential privacy (TALDP). The key idea is that, rather than applying the same degree of perturbation to all location points, we employ adaptive privacy budget allocation, assigning varied privacy budgets to individual location points, thereby mitigating the perturbation’s impact and enhancing overall utility. Meanwhile, to ensure the privacy, we give the different perturbing points to different privacy budgets according to their important degree for the patterns of the trajectories. In particular, we use Karman filter method to select the important location points and decide their privacy budgets. We conduct extensive experiments on three real datasets. The results show that our approach improves the utility over many other current methods while still provide good the privacy protection.

Abstract Developing high-performance Pt-based catalysts with low Pt loading is crucial but challenging for CO oxidation at temperatures below 100 °C. Herein, we report a Pt-based catalyst with only a 0.15 wt% Pt loading, which consists of Pt–Ti intermetallic single-atom alloy (ISAA) and Pt nanoparticles (NP) co-supported on a defective TiO2 support, achieving a record high turnover frequency of 11.59 s–1 at 80 °C and complete conversion of CO at 120 °C. This is because the coexistence of Pt–Ti ISAA and Pt NP significantly alleviates the competitive adsorption of CO and O2, enhancing the activation of O2. Furthermore, Pt single atom sites are stabilized by Pt–Ti ISAA, resulting in distortion of the TiO2 lattice within Pt–Ti ISAA. This distortion activates the neighboring surface lattice oxygen, allowing for the simultaneous occurrence of the Mars-van Krevelen and Langmuir–Hinshelwood reaction paths at low temperatures.

ABSTRACT Background Breast cancer is the leading cause of cancer‐related deaths in the female population. Axillary lymph nodes (ALN) are a group of the most common metastatic sites of breast cancer. Timely assessment of ALN status is of paramount clinical importance for medical decision making. Aims To utilize contrast‐enhanced ultrasound (CEUS)‐based radiomics models for noninvasive pretreatment prediction of ALN status. Methods and Results Clinical data and pretreatment CEUS images of primary breast tumors were retrospectively studied to build radiomics signatures for pretreatment prediction of nodal status between May 2015 and July 2021. The cases were divided into the training cohorts and test cohorts in a 9:1 ratio. The mRMR approach and stepwise forward logistic regression technique were used for feature selection, followed by the multivariate logistic regression technique for building radiomics signatures in the training cohort. The confusion matrix and receiver operating characteristic (ROC) analysis were used for accessing the prediction efficacy of the radiomics models. The radiomics models, which consist of six features, achieved predictive accuracy with the area under the ROC curve (AUC) of 0.713 in the test set for predicting lymph node metastasis. Conclusion The CEUS‐based radiomics is promising to be developed as a reliable noninvasive tool for predicting ALN status.

Summary: Background: The epidemiological features of the Klebsiella pneumoniae causing bloodstream infections in Hong Kong and their potential threats to human health remained unknown. Methods: K. pneumoniae strains collected from four hospitals in Hong Kong during the period of 2009–2018 were subjected to molecular typing, string test, antimicrobial susceptibility testing, whole genome sequencing and analysis. Clinical data of patients from whom these strains were isolated were analyzed retrospectively using univariate and multivariate logistic regression approaches. Findings: The 240 Klebsiella spp. strains belonged to 123 different STs and 63 different capsule loci (KLs), with KL1 and KL2 being the major type. 86 out of 212 BSI-KP (40.6%) carried at least one of the virulence genes iuc, iro, rmpA or rmpA2. Virulence plasmid correlated well with the string test positive result, yet 8 strains without rmp genes were also hypermucoviscous, which was due to wzc mutation. The mortality rate of bloodstream infection patients was 43.0%. Univariant analysis showed that factors including renal replacement therapy (FDR adjusted p = 0.0007), mechanical ventilation (FDR adjusted p

ObjectiveWe aimed to investigate the value of contrast-enhanced ultrasound (CEUS) in the preoperative prediction of the histological grades and molecular subtypes of breast cancer.MethodsA total of 183 patients with pathologically confirmed breast cancer were included. Contrast enhancement patterns and quantitative parameters were compared in different groups. The receiver operating characteristic (ROC) curve was used to analyze the efficacy of CEUS in the preoperative prediction of pathological characteristics, including histologic grade and molecular subtypes.ResultsHeterogeneous enhancement, perfusion defects, and peripheral radial vessels were mostly observed in higher histologic grade (grade III) breast cancer. Heterogeneous enhancement and perfusion defect were the most effective indicators for grade III breast cancer, with the areas under the ROC curve of 0.768 and 0.756, respectively. There were significant differences in the enhancement intensity, post-enhanced margin, perfusion defects, and peripheral radial vessel among the different molecular subtypes of breast cancer (all P < 0.01). Perfusion defects and clear edge after enhancement were the best qualitative criteria for the diagnosis of HER-2 overexpressed and triple-negative breast cancers, and the corresponding areas under the ROC curves were 0.804 and 0.905, respectively. There were significant differences in PE, WiR, WiPI, and WiWoAUC between grade III vs grade I and II breast cancer (P < 0.05). PE, WiR, WiPI, and WiWoAUC had good efficiency in the diagnosis of high-histologic-grade breast cancer. PE had the highest diagnostic efficiency in Luminal A, while WiPI had the highest diagnostic efficiency in Luminal B subtype breast cancer, and the areas under the ROC curve were 0.825 and 0.838, respectively. WiWoAUC and WiR were the most accurate parameters for assessing triple-negative subtype breast cancers, and the areas under the curve were 0.932 and 0.922, respectively.ConclusionQualitative and quantitative perfusion analysis of contrast-enhanced ultrasound may be useful in the non-invasive prediction of the histological grade and molecular subtypes of breast cancers.

With developments in the intelligent swarm technology, the cooperation of autonomous undersea vehicle (AUV) swarms in performing underwater tasks has become an inevitable trend for the future development of such tasks. However, owing to the particularity of underwater environments, collaborative tasks of underwater multi-vehicle swarms encounter major challenges. This paper provides an overview of the research progress on AUV swarms. From the perspective of cooperative hunting, path planning, formation control, and so on, multiple tasks and key technologies of intelligent swarms developed worldwide are introduced, and some recent results obtained by the authors based on cooperative hunting and multi-path underwater planning tasks are summarized. Additionally, through a review and analysis of existing research results, some references for the future development of underwater multi-vehicle swarm tasks are provided.

Winter wheat is a significant global food crop, and it is crucial to monitor its distribution for better agricultural management, land planning, and environmental sustainability. However, the distribution style of winter wheat planting fields is not consistent due to different terrain conditions. In mountainous areas, winter wheat planting units are smaller in size and fragmented in distribution compared to plain areas. Unfortunately, most crop-mapping research based on deep learning ignores the impact of topographic relief on crop distribution and struggles to handle hilly areas effectively. In this paper, we propose a cross-modal segmentation network for winter wheat mapping in complex terrain using remote-sensing multi-temporal images and DEM data. First, we propose a diverse receptive fusion (DRF) module, which applies a deformable receptive field to optical images during the feature fusion process, allowing it to match winter wheat plots of varying scales and a fixed receptive field to the DEM to extract evaluation features at a consistent scale. Second, we developed a distributed weight attention (DWA) module, which can enhance the feature intensity of winter wheat, thereby reducing the omission rate of planting areas, especially for the small-sized regions in hilly terrain. Furthermore, to demonstrate the performance of our model, we conducted extensive experiments and ablation studies on a large-scale dataset in Lanling county, Shandong province, China. Our results show that our proposed CM-Net is effective in mapping winter wheat in complex terrain.

The multifunctional development in the field of face masks and the growing demand for scalable manufacturing have become increasingly prominent. In this study, we utilized high-vacuum magnetron sputtering technology to deposit a 5 nm ultra-thin Ag–Cu film on non-woven fabric and fabricated ultra-thin Ag–Cu film face masks. The antibacterial rates against Escherichia coli and Staphylococcus aureus were 99.996% and 99.978%, respectively, while the antiviral activity against influenza A virus H1N1 was 99.02%. Furthermore, the mask’s ability to monitor respiratory system diseases was achieved through color change (from brownish-yellow to grey-white). The low cost and scalability potential of ultra-thin silver–copper film masks offer new possibilities for practical applications of multifunctional masks.

Recent developments in Unmanned Aircraft Vehicles (UAVs), thermal imaging, and Auto-machine learning (AutoML) have shown high potential for precise wildlife surveys but have rarely been studied for habitat assessment. Here, we propose a framework that leverages these advanced techniques to achieve cost-effective habitat quality assessment from the perspective of actual wildlife community usage. The framework exploits vision intelligence hidden in the UAV thermal images and AutoML methods to achieve cost-effective wildlife distribution mapping, and then derives wildlife use indicators to imply habitat quality variance. We conducted UAV-based thermal wildlife surveys at three wetlands in the Rainwater Basin, Nebraska. Experiments were set to examine the optimal protocols, including various flight designs (61 and 122 m), feature types, and AutoML. The results showed that UAV images collected at 61 m with a spatial resolution of 7.5 cm, combined with Faster R-CNN, returned the optimal wildlife mapping (more than 90% accuracy). Results also indicated that the vision intelligence exploited can effectively transfer the redundant AutoML adaptation cycles into a fully automatic process (with around 33 times efficiency improvement for data labeling), facilitating cost-effective AutoML adaptation. Eventually, the derived ecological indicators can explain the wildlife use status well, reflecting potential within- and between-habitat quality variance.

Food-borne antibiotic-resistant Campylobacter poses a serious threat to public health. To understand the prevalence and genetic characteristics of Campylobacter in Chinese local dual-purpose (meat and eggs) chickens, the genomes of 30 Campylobacter isolates, including 13 C. jejuni and 17 C. coli from Jianghan-chickens in central China, were sequenced and tested for antibiotic susceptibility. The results showed that CC-354 and CC-828 were the dominant clonal complexes of C. jejuni and C. coli, respectively, and a phylogenetic analysis showed that three unclassified multilocus sequence types of C. coli were more closely genetically related to C. jejuni than to other C. coli in this study. Of the six antibiotics tested, the highest resistance rates were to ciprofloxacin and tetracycline (100%), followed by lincomycin (63.3%), erythromycin (30.0%), amikacin (26.7%), and cefotaxime (20.0%). The antibiotic resistance rate of C. coli was higher than that of C. jejuni. The GyrA T86I mutation and 15 acquired resistance genes were detected with whole-genome sequencing (WGS). Among those, the GyrA T86I mutation and tet(O) were most prevalent (both 96.7%), followed by the blaOXA-type gene (90.0%), ant(6)-Ia (26.7%), aac(6’)-aph(3’’) (23.3%), erm(B) (13.3%), and other genes (3.3%). The ciprofloxacin and tetracycline resistance phenotypes correlated strongly with the GyrA T86I mutation and tet(O)/tet(L), respectively, but for other antibiotics, the correlation between genes and resistance phenotypes were weak, indicating that there may be resistance mechanisms other than the resistance genes detected in this study. Virulence gene analysis showed that several genes related to adhesion, colonization, and invasion (including cadF, porA, ciaB, and jlpA) and cytolethal distending toxin (cdtABC) were only present in C. jejuni. Overall, this study extends our knowledge of the epidemiology and antibiotic resistance of Campylobacter in local Chinese dual-purpose chickens.

ABSTRACTIonic polymer-metal composites (IPMCs) are typical smart materials that are commonly used in bionic applications, including soft robots, bionic flapping aircraft, and bionic fish. However, their low output force seriously limits device performance. Stacking of multiple IPMC actuators to improve the overall performance of soft actuators is a strategy that is used in practical applications. Under the energy dissipation condition in the IPMC stacking structure, if each single IPMC in the structure has high power density, the structure will produce excellent performance with high efficiency that can greatly promote wider application of IPMC actuators. To meet this requirement, a method for fabrication process integration with multiple optimized factors was used to obtain IPMC materials in this paper. Carbon nanotube (CNT) doping, isopropyl alcohol-assisted plating, and hot pressing with a mesoscopic structural mold were selected as typical optimization methods for process integration and were initially investigated separately to determine the optimal process parameters. By combining the best process parameters in an integrated process, the IPMC treated by isopropyl alcohol-assisted plating and CNT doping process (No. AC7) showed excellent actuation performance and high work density (~9.71/12.36 gf, ~14.93/31.89 kJ/m3 under 3/4 VDC). The enhanced performance meets the requirements for practical bionic applications.

ObjectivePasteurella multocida is a widespread zoonotic pathogen that causes severe damage to the poultry industry. This study focused on the antibacterial effects and mechanism of action of coptisine against P. multocida.MethodsThe minimum inhibitory concentration and half maximal inhibitory concentration of coptisine against P. multocida was measured. Additionally, the effect of coptisine on growth, cell wall, activity of respiratory enzymes, soluble protein content and DNA synthesis were also analyzed. Finally, the effect of coptisine on gene transcription was determined using RNA sequencing.ResultsWe demonstrated that coptisine has a strong antibacterial effect against P. multocida, with a minimum inhibitory concentration of 0.125 mg/mL. Moreover, the measurement of the half maximal inhibitory concentration confirmed that coptisine was safe for the pathogen. The growth curve showed that coptisine inhibited bacterial growth. Measurement of alkaline phosphatase activity in the culture solution showed that coptisine affected cell wall permeability. Transmission electron microscopy revealed that coptisine chloride destroyed the cell structure. In addition, coptisine blocked the respiratory system, as measured by the levels of critical enzymes of the tricarboxylic acid cycle and glycolysis, succinate dehydrogenase and lactate dehydrogenase, respectively. Similarly, coptisine inhibited the synthesis of soluble proteins and genomic DNA. The KEGG pathway analysis of the differentially expressed genes showed that they were associated with cellular, respiratory, and amino acid metabolism, which were downregulated after coptisine treatment. Additionally, genes related to RNA degradation and the aminoacyl-tRNA pathway were upregulated.ConclusionIn this study, we demonstrated that coptisine exerts an antibacterial effect on P. multocida. These findings suggest that coptisine has a multifaceted impact on various pathways, resulting in the inhibition of P. multocida. Thus, coptisine is a potential alternative to antibiotics for the treatment of P. multocida infections in a clinical setting.

ABSTRACT Bacterial morphology is largely determined by the spatial and temporal regulation of peptidoglycan (PG) biosynthesis. Ovococci possess a unique pattern of PG synthesis different from the well studied Bacillus, and the mechanism of the coordination of PG synthesis remains poorly understood. Several regulatory proteins have been identified to be involved in the regulation of ovococcal morphogenesis, among which DivIVA is an important one to regulate PG synthesis in streptococci, while its mechanism is largely unknown. Here, the zoonotic pathogen Streptococcus suis was used to investigate the regulation of DivIVA on PG synthesis. Fluorescent d-amino acid probing and 3D-structured illumination microscopy found that DivIVA deletion caused abortive peripheral PG synthesis, resulting in a decreased aspect ratio. The phosphorylation-depleted mutant (DivIVA3A) cells displayed a longer nascent PG and became longer, whereas the phosphorylation-mimicking mutant (DivIVA3E) cells showed a shorter nascent PG and became shorter, suggesting that DivIVA phosphorylation is involved in regulating peripheral PG synthesis. Several DivIVA-interacting proteins were identified, and the interaction was confirmed between DivIVA and MltG, a cell wall hydrolase essential for cell elongation. DivIVA did not affect the PG hydrolysis activity of MltG, while the phosphorylation state of DivIVA affected its interaction with MltG. MltG was mislocalized in the ΔdivIVA and DivIVA3E cells, and both ΔmltG and DivIVA3E cells formed significantly rounder cells, indicating an important role of DivIVA phosphorylation in regulating PG synthesis through MltG. These findings highlight the regulatory mechanism of PG synthesis and morphogenesis of ovococci. IMPORTANCE The peptidoglycan (PG) biosynthesis pathway provides a rich source of novel antimicrobial drug targets. However, bacterial PG synthesis and its regulation is a very complex process involving dozens of proteins. Moreover, unlike the well studied Bacillus, ovococci undergo unusual PG synthesis with unique mechanisms of coordination. DivIVA is an important regulator of PG synthesis in ovococci, while its exact role in regulating PG synthesis remains poorly understood. In this study, we determined the role of DivIVA in regulating lateral PG synthesis of Streptococcus suis and identified a critical interacting partner, MltG, in which DivIVA influenced the subcellular localizations of MltG through its phosphorylation. Our study characterizes the detailed role of DivIVA in regulating bacterial PG synthesis, which is very helpful for understanding the process of PG synthesis in streptococci.

Stable communication technologies in complex waters are a prerequisite for underwater operations. Underwater acoustic communication is susceptible to multipath interference, while underwater optical communication is susceptible to environmental impact. The underwater electric field communication established based on the weak electric fish perception mechanism is not susceptible to environmental interference, and the communication is stable. It is a new type of underwater communication technology. To address issues like short communication distances and high bit error rates in existing underwater electric field communication systems, this study focuses on underwater electric field communication systems based on direct sequence spread spectrum (DSSS) and binary phase shift keying (BPSK) modulation techniques. To verify the feasibility of the established spread spectrum electric field communication system, static communication experiments were carried out in a swimming pool using the DSSS-based system. The experimental results show that in fresh water with a conductivity of 739 μS/cm, the system can achieve underwater current electric field communication within a 11.2 m range with 10−6 bit errors. This paper validates the feasibility of DSSS BPSK in short-range underwater communication, and compact communication devices are expected to be deployed on underwater robots for underwater operations.

The U.S. federal government’s requirements and guidance for wetland conservation are reflected in a series of federal laws, regulations, and policies. However, the degree to which these requirements are reflected in local planning efforts is unclear. This study using five components with 56 indicators evaluates how well wetland conservation efforts are integrated into 112 local comprehensive plans in Nebraska, USA. The results show that the majority of local comprehensive plans pay little direct attention to wetland conservation, although many conservation efforts are conducted under the umbrella of environmental protection frameworks. The indicators include water resource protection received the highest score and was the descriptor of natural or environmental resources and resulted in the highest level of local awareness on natural assets. The indicator of setting goals for no net loss of wetlands received the lowest score among all indicators, demonstrating a clear gap between the national vision and the local reality of wetland conservation. Findings suggest local governments need more direct and proactive inputs to improve wetland conservation. Further findings from this research provide a practical roadmap for planners globally, particularly for the developing countries, to integrate wetland conservation into the local planning systems.

Antimicrobial resistance (AMR) is a global concern threatening public health. Developing novel antibiotics is one of the effective strategies to tackle AMR. Serine/threonine kinases (STKs) have been recently shown to play critical roles in the physiology and pathogenesis of several important bacterial pathogens which are regarded as a promising antimicrobial drug target. We previously reported the roles of STK in the regulation of bacterial cell division, metabolism, and pathogenesis in Streptococcus suis, an important zoonotic bacterial pathogen. In this study, we firstly identified the Thr167 and Ser175 residues in the activation loop of S. suis STK (ssSTK) as the kinase autophosphorylation sites. Phenotyping results demonstrated that the autophosphorylation deficient strain resembled the stk deletion strain showing essentiality for bacterial growth in minimal medium, abnormal morphology, and decreased virulence when compared with the wild-type S. suis SC19 strain. Based on these findings, we established an ssSTK inhibitor screening approach by measuring the growth of S. suis in a minimal medium and testing the autophosphorylation inhibition by measuring the consumption of ATP in an enzymatic reaction by ssSTK. A series of inhibitors against ssSTK are identified from a commercial kinase inhibitors library, including Staurosporine, K252a, AT9283, and APY29. These inhibitors showed antimicrobial activity in vitro. Moreover, by using Galleria mellonella larvae infection assay, compound APY29 displayed in vivo efficacy against S. suis infection. Additionally, it was predicted by molecular docking that these inhibitors could interact with ssSTK. Collectively, our data illustrated the essential roles of ssSTK autophosphorylation in the physiology and pathogenicity of S. suis and consider these inhibitors as promising antimicrobial lead compounds.

ABSTRACT Streptococcus suis is an important zoonotic bacterial pathogen posing a threat to the pig industry as well as public health, for which the mechanisms of growth and cell division remain largely unknown. Developing convenient genetic tools that can achieve strictly controlled gene expression is of great value for investigating these fundamental physiological processes of S. suis. In this study, we first identified three strong constitutive promoters, Pg, Pt, and Pe, in S. suis. Promoter Pg was used to drive the expression of repressor genes tetR and lacI, and the operator sequences were added within promoters Pt and Pe. By optimizing the insertion sites of the operator sequence, we successfully constructed an anhydrotetracycline (ATc)-inducible expression system and an isopropyl-β-d-thiogalactopyranoside (IPTG)-inducible expression system in S. suis. We showed that these two systems provided inducer-concentration- and induction-time-dependent expression of the reporter gene. By using these tools, we investigated the subcellular localization of a key cell division protein, FtsZ, which showed that it could be correctly localized to the midcell region. In addition, we constructed a conditional knockout strain for the glmS gene, which is an essential gene, and showed that our ATc-inducible promoter could provide strictly controlled expression of glmS in trans, suggesting that our inducible expression systems can be used for deletion of essential genes in S. suis. Therefore, for the first time we developed two inducible expression systems in S. suis and showed their applications in the study of an important cell division protein and an essential gene. These genetic tools will further facilitate the functional study of other important genes of S. suis. IMPORTANCE Streptococcus suis is an important zoonotic bacterial pathogen. Studying the mechanisms of cell growth and division is important for the identification of novel antimicrobial drug targets. Inducible expression systems can provide strictly controlled expression of the protein of interest and are useful tools to study the functions of physiologically important proteins. However, there is a lack of convenient genetic tools that can achieve inducible protein expression in S. suis. In this study, we developed two (ATc-inducible and IPTG-inducible) inducible expression systems and showed their applications in a subcellular localization study of a cell division protein and the construction of conditional knockout of essential genes in S. suis. These systems will be useful for functional studies of important proteins of S. suis.

Single-pixel imaging is a novel imaging technique that can obtain image information through a single-pixel detector. It can effectively avoid the problem of lack of high-quality area array detectors in the terahertz band, and has attracted the attention of a large number of researchers in recent years. In this paper, the basic imaging principles, terahertz beam modulation methods and typical image reconstruction algorithms for terahertz single-pixel imaging are introduced and discussed, as well as its research progresses and developing trends.

Background Hypoxic‐ischemic encephalopathy (HIE) could induce exacerbated changes and unpredictable effects in brain cells, and the mechanism remains unclear. Methods HIE model was established in neonatal rats, Zea‐Longa score and TTC staining were used to observe the neurobehavior and brain infarct volume in rats subjected to cerebral hypoxia‐ischemia (HI). Primary cortical neurons were then cultured in vitro to establish an oxygen and glucose deprivation model. To determine the role of synaptosomal‐associated protein‐25 (SNAP25) in HIE, PC12 cells were cultured and effective siRNA fragments were screened, and SNAP25 was transfected into primary neurons. Then, quantitative real‐time polymerase chain reaction was used to detect the mRNA expression level and immunofluorescence staining was used to observe the morphological changes of neurons before and after the injury. Finally, the abundance values of SNAP25 and its associated genes were filtered using the NCBI and GeneMANIA, respectively. Results HI leads to a decrease in neuronal number and an increase in SNAP25 expression. Whereas, the interference of SNAP25 caused marked decrease in neuronal number and the length of neurite. Moreover, the expression levels of CREB and SYP were significantly decreased after interference of SNAP25. Conclusion SNAP25 exhibited several neuroprotective effects to neuronal protection in neonatal cerebral HI by regulating CREB and SYP.

Abstract Neonatal hypoxic–ischemic (HI) injury derived from asphyxia during perinatal period, is a serious complication of neonatal asphyxia and the main cause of neonatal acute death and chronic neurological injury. Aberrant autophagy occurs in many nervous system diseases, but its role and underlying mechanism in HI injury is largely unknown. Here, we successfully constructed a newborn rat model of HI brain injury, and the knockout-miR-127-3p (KO-miR-127-3p) rats were structured by using CRISPR/Cas9. Subsequently, the in vitro functional experiments, in vivo zea-longa scores, as well as bioinformatics analyses and biological experiments were applied. The expression of autophagy-related proteins, including ATG12, P62, Beclin-1, LC3II in HI cortex with miR-127-3p knockout was significantly decreased, and autophagic vacuoles were disappeared. Moreover, miR-127-3p has a specific regulatory effect on CISD1 expression, another crucial molecule in autophagy process. Accordingly, the overexpression of CISD1 effectively inhibited the autophagic cell death and physiological dysfunction in the brain of HI injury, whereas si-CISD1 reversed the neuroprotective effects of KO-miR-127-3p. Our findings explained the underlying mechanism for HI injury, and miR-127-3p targeting CISD1 signal could be supposed as a new treatment strategy to prevent and treat HI injury.

Dolphin signals are effective carriers for underwater covert detection and communication. However, the environmental and cost constraints terribly limit the amount of data available in dolphin signal datasets are often limited. Meanwhile, due to the low computational power and resource sensitivity of Unmanned Underwater Vehicles (UUVs), current methods for real-time generation of dolphin signals with favorable results are still subject to several challenges. To this end, a Masked AutoEncoder Generative Adversarial Network (MAE-GAN) model is hereby proposed. First, considering the few-shot condition, the dataset is extended by using data augmentation techniques. Then, to meet the low arithmetic constraint, a denoising autoencoder with a mask is used to obtain latent codes through self-supervised learning. These latent codes are then utilized in Conditional Wasserstein Generative Adversarial Network-Gradient Penalty (CWGAN-GP) to generate a whistle signal model for the target dataset, fully demonstrating the effectiveness of the proposed method for enhancing dolphin signal generation in data-limited scenarios. The whistle signals generated by the MAE-GAN and baseline models are compared with actual dolphin signals, and the findings indicate that the proposed approach achieves a discriminative score of 0.074, which is 28.8% higher than that of the current state-of-the-art techniques. Furthermore, it requires only 30.2% of the computational resources of the baseline model. Overall, this paper presents a novel approach to generating high-quality dolphin signals in data-limited situations, which can also be deployed on low-resource devices. The proposed MAE-GAN methods provide a promising solution to address the challenges of limited data and computational power in generating dolphin signals.

Because of the requirements of marine resources exploration and underwater cooperative operation, the underwater operation of common detection and communication equipment is difficult and unreliable. Therefore, it is urgent to establish an accurate underwater target detection and multi-node communication integrated system. An integrated method of underwater electric field detection and communication based on P4 code-modulated OFDM signal is proposed in response to the above requirements. The working principle, system structure, and signal processing of underwater electric field detection and electric field communication are similar. This article uses detection signal P4 code to modulate the phase of OFDM communication signal, thus realizing the integration of Underwater Detection and Communication System (IUDCS). The simulation results show that IUDCS can meet the detection range and velocity characteristics of underwater dynamic targets. The simulation results also meet the requirements for communication error rate and symbol error rate, thereby verifying the performance of underwater electric field IUDCS. This method is necessary for the realization of IUDCS in terms of reducing platform size, reducing power consumption, and enhancing concealment. Moreover, it shows good application prospects in underwater robot cluster operations.

The academia and industry have been pursuing network-on-chip (NoC) related research since two decades ago when there was an urgency to respond to the scaling and technological challenges imposed on intra-chip communication in SoC designs. Like any other research topic, NoC inevitably goes through its life cycle: A. it started up (2000–2007) and quickly gained traction in its own right; B. it then entered the phase of growth and shakeout (2008–2013) with the research outcomes peaked in 2010 and remained high for another four/five years; C. NoC research was considered mature and stable (2014–2020), with signs showing a steady slowdown. Although from time to time, excellent survey articles on different subjects/aspects of NoC appeared in the open literature, yet there is no general consensus on where we are in this NoC roadmap and where we are heading, largely due to lack of an overarching methodology and tool to assess and quantify the research outcomes and evolution. In this paper, we address this issue from the perspective of three specific complex networks, namely the citation network, the subject citation network, and the co-authorship network. The network structure parameters (e.g., modularity, diameter, etc.) and graph dynamics of the three networks are extracted and analyzed, which helps reveal and explain the reasons and the driving forces behind all the changes observed in NoC research over 20 years. Additional analyses are performed in this study to link interesting phenomena surrounding the NoC area. They include: (1) relationships between communities in citation networks and NoC subjects, (2) measure and visualization of a subject’s influence score and its evolution, (3) knowledge flow among the six most popular NoC subjects and their relationships, (4) evolution of various subjects in terms of number of publications, (5) collaboration patterns and cross-community collaboration among the authors in NoC research, (6) interesting observation of career lifetime and productivity among NoC researchers, and finally (7) investigation of whether or not new authors are chasing hot subjects in NoC. All these analyses have led to a prediction of publications, subjects, and co-authorship in NoC research in the near future, which is also presented in the paper.

Aim at the problems of large volume and low degree of sharing of remote sensing data, high complexity of algorithm model and single function of disaster response application system, the main functions and technical framework of GIP, as well as the advantages and potential of GIP in platform, algorithm and application system was introduced.It provided a reference for further mining the research of new intelligent processing algorithm and processing mode for multi-source, high-dimensional, heterogeneous and complex associated earth observation data in other application fi elds with GIP, so as to promote the service ability and form a new information service mode and industrial chain of the GIP.

Based on the investigation result on the training program of information security to undergraduates in Hunan university,an analysis from four aspects was made:domestic and international universities,external specialists,teachers in the college and students in the college.Aiming at issues being found,the training program based on existing experiences and achievements on university-enterprise cooperation were improved.The new training program features university-enterprise joint cultivation.

In this paper, a power-split strategy based on a real-time average power method is developed for improving power output of battery and mode switching frequency of a multi-mode hybrid energy storage system (HESS) in electric vehicles. To achieve mode switching and power distribution for the multi-mode HESS, a rule-based strategy is designed based on the high-frequency power demand. Furthermore, a simple real-time average power method is adopted to process the high-frequency power demand. Then, the real-time average power is used as a variable logic threshold value for the power-split strategy. Since the power-split controller responds to the smooth average power rather than the high-frequency power demand, the high-frequency mode switching of the multi-mode HESS can be avoided. The ultra-capacitor works as an enhanced low-pass power filter and the battery can supply smooth and steady output power to the motor inverter. Comparative simulations between the developed power-split strategy and the rule-based strategy are performed. The advantages of the developed power-split strategy for improving the power output of the battery and the mode switching frequency of the multi-mode HESS in electric vehicles are indicated under three typical driving cycles. Moreover, the longer time duration of the real-time average power is designed, the smoother power output of the battery and the lower mode switching frequency of the multi-mode HESS can be achieved.

Green and low-carbon development is an important element of the Belt and Road Initiative, and a reasonable and objective evaluation of China’s green investment efficiency in B&R countries is of great significance to promote the sustainable development of those area. This paper applies the Slack-based measure model that considers undesirable outputs and Malmquist total factor productivity index to measure the efficiency of China’s green investment in B&R countries from 2011 to 2018 from both static and dynamic perspectives, as well as provides an in-depth analysis of the differences, changes, and influential factors. The empirical results reveal that the overall efficiency of China’s green investment in B&R countries is relatively low, showing a distinctly uneven trend and the main driving force of the decline in total factor productivity comes from technical change. Some significant differences have also been reported amongst these countries in terms of their industrial development and income levels. These findings provide a valuable reference for B&R countries to identify unique strategies that can promote their green total productivity factor.

ObjectivesThe purpose of this study was to establish a nomogram for predicting cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC).Materials and MethodsA total of 418 patients with papillary thyroid carcinoma undergoing total thyroidectomy with cervical lymph node dissection were enrolled in the retrospective study from January 2016 to September 2019. Univariate and multivariate Logistic regression analysis were performed to screen the clinicopathologic, laboratory and ultrasound (US) parameters influencing cervical lymph nodes metastasis and develop the predicting model.ResultsCLNM was proved in 34.4% (144/418) of patients. In the multivariate regression analysis, Male, Age < 45 years, Tumor size > 20mm, multifocality, ambiguous boundary, extracapsular invasion and US-suggested lymph nodes metastasis were independent risk factors of CLNM (p < 0.05). Prediction nomogram showed an excellent discriminative ability, with a C-index of 0.940 (95% confidence interval [CI], 0.888-0.991), and a good calibration.ConclusionThe established nomogram showed a good prediction of CLNM in patients with PTC. It is conveniently used and should be considered in the determination of surgical procedures.

Active sonar systems are one of the most commonly used acoustic devices for underwater equipment. They use observed signals, which mainly include target echo signals and reverberation, to detect, track, and locate underwater targets. Reverberation is the primary background interference for active sonar systems, especially in shallow sea environments. It is coupled with the target echo signal in both the time and frequency domain, which significantly complicates the extraction and analysis of the target echo signal. To combat the effect of reverberation, an attention and cepstrum analysis-guided network (ACANet) is proposed. The baseline system of the ACANet consists of a one-dimensional (1D) convolutional module and a reconstruction module. These are used to perform nonlinear mapping and to reconstruct clean spectrograms, respectively. Then, since most underwater targets contain multiple highlights, a cepstrum analysis module and a multi-head self-attention module are deployed before the baseline system to improve the reverberation suppression performance for multi-highlight targets. The systematic evaluation demonstrates that the proposed algorithm effectively suppresses the reverberation in observed signals and greatly preserves the highlight structure. Compared with NMF methods, the proposed ACANet no longer requires the target echo signal to be low-rank. Thus, it can better suppress the reverberation in multi-highlight observed signals. Furthermore, it demonstrates superior performance over NMF methods in the task of reverberation suppression for single-highlight observed signals. It creates favorable conditions for underwater platforms, such as unmanned underwater vehicles (UUVs), to carry out underwater target detection and tracking tasks.

Ionic polymer–metal composite (IPMC) is a promising candidate for underwater sensing due to the merits of rapid response, flexibility, miniaturization, and self-powered nature. The high sensitivity of a sensor is vital for underwater robots. Inspired by the lateral line cilia of fish, a new water flow sensor system based on the multi-ciliated structure of the IPMC is presented to improve the sensitivity of the sensor. As illustrated by the experiments on oscillatory flow, the sensitivity and detection range of the multi-ciliated sensor reached 3.83 times and increased by about 39%, respectively, compared with that of a single sensor. In addition, an array composed of multi-ciliated systems of IPMCs was successfully applied to the location of a vibrating dipole, while the velocity prediction of underwater moving objects was also realized with a minimum average error rate of 1.70%. The system with high sensitivity proposed in this paper is promising to be an effective supplement to traditional underwater detection methods.

Cooperative hunting is a typical task that reflects the intelligence level of a swarm. For the complex underwater weak information environment with obstacles, a problem description of the multi-autonomous underwater vehicle (AUV) cooperative hunting task is given, considering the influencing factors, including underwater obstacles, AUV sensing interaction range, and target escape strategy. A hybrid adaptive preference method based on improved artificial potential fields (HAP-IAPF) is proposed. Then the strategies of obstacle avoidance and hunting are designed separately according to the task requirements. The adaptive weight control unit is used to adjust the preference strategy. The multi-AUV cooperative hunting in dynamic obstacle underwater environments under weakly connected conditions are achieved. In order to prove the effectiveness of the proposed algorithm, simulation results compared with the traditional artificial potential field method and the optimized artificial potential field method are given in this paper. The results show that the proposed method is robust and effective in different environments.

Conservation easements (CEs) play an important role in the provision of ecological services. This paper aims to use the open-access Sentinel-2 satellites to advance existing conservation management capacity to a new level of near-real-time monitoring and assessment for the conservation easements in Nebraska. This research uses machine learning and Google Earth Engine to classify inundation status using Sentinel-2 imagery during 2018–2021 for all CE sites in Nebraska, USA. The proposed machine learning approach helps monitor the CE sites at the landscape scale in an efficient and low-cost manner. The results confirmed effective inundation performance in these floodplain or wetland-related CE sites. The CE sites under the Emergency Watershed Protection-Floodplain Easement (EWPP-FPE) had the highest inundated area rate of 18.72%, indicating active hydrological inundation in the floodplain areas. The CE sites under the Wetlands Reserve Program (WRP) reached a mean annual surface water cover rate area of 8.07%, indicating the core wetland areas were inundated periodically or regularly. Other types of CEs serving upland conservation purposes had a lower level of inundation while these uplands conservation provided critical needs in soil erosion control. The mean annual surface water cover rate is 0.96% for the CE sites under the Grassland Reserve Program (GRP). The conservation of the CEs on uplands is an important component to reduce soil erosion and improve downstream wetland hydrological inundation performance. The findings support that the sites with higher inundation frequencies can be considered for future wetland-related conservation practices. The four typical wetland-based CE sites suggested that conservation performance can be improved by implementing hydrological restoration and soil erosion reduction at the watershed scale. The findings provided robust evidence to discover the surface water inundation information on conservation assessment to achieve the long-term goals of conservation easements.

Nervous tinnitus is one of the most common hearing impairments, which seriously affects the physical and mental health of patients. We describe a case of a 31‐year‐old female with nervous tinnitus in this report. She suffered from bilateral tinnitus for more than 8 months with the symptoms of earache, anxiety, and sleep disorders at admission. Under the combined treatment of ultrasound‐guided stellate ganglion block and acupuncture at acupoints of the Ermen, Tinggong, Tinghui, and Yifeng, the patient recovered well and the symptoms such as tinnitus and earache disappeared gradually. This case may provide a reference for the subsequent clinical treatment of tinnitus.

Probabilistic computing is an emerging computational paradigm that uses probabilistic circuits to efficiently solve optimization problems such as invertible logic, where traditional digital computations are difficult to solve. This paper proposes a true random number generator (TRNG) based on resistive random-access memory (RRAM), which is combined with an activation function implemented by a piecewise linear function to form a standard p-bit cell, one of the most important parts of a p-circuit. A p-bit multiplexing strategy is also applied to reduce the number of p-bits and improve resource utilization. To verify the superiority of the proposed probabilistic circuit, we implement the invertible p-circuit on a field-programmable gate array (FPGA), including AND gates, full adders, multi-bit adders, and multipliers. The results of the FPGA implementation show that our approach can significantly save the consumption of hardware resources.

This paper presents an optimal sensor placement method for vibration signal acquisition in the field of industrial robot health monitoring and fault diagnosis. Based on the general formula of Bayes and relative entropy, the evaluation function of sensor placement is deduced, and the modal confidence matrix is used to express the redundancy of sensor placement. The optimal placement of vibration sensors is described as a discrete variable optimization problem, which is defined as whether the existing sensor layout can obtain joint state information efficiently. The initial layout of the sensor was obtained from the structural simulation results of the industrial robots, and the initial layout was optimized by the derived objective function. The efficiency of the optimized layout in capturing joint state information is proven by the validation experiment with a simulation model. The problem of popularizing the optimization method in engineering is solved by a verification experiment without a simulation model. The optimal sensor placement method provides a theoretical basis for industrial robots to acquire vibration data effectively.

Bacterial cell division is a highly ordered process regulated in time and space and is a potential target for the development of antimicrobial drugs. Bacteria of distinct shapes depend on different cell division mechanisms, but the mechanisms used by ovococci remain largely unknown.

Streptococcus suis (S. suis) is a zoonotic bacterial pathogen causing lethal infections in pigs and humans. Identification of virulence-related genes (VRGs) is of great importance in understanding the pathobiology of a bacterial pathogen. To identify novel VRGs, a transposon (Tn) mutant library of S. suis strain SC19 was constructed in this study. The insertion sites of approximately 1700 mutants were identified by Tn-seq, which involved 417 different genes. A total of 32 attenuated strains were identified from the library by using a Galleria mellonella larvae infection model, and 30 novel VRGs were discovered, including transcription regulators, transporters, hypothetical proteins, etc. An isogenic deletion mutant of hxtR gene (ΔhxtR) and its complementary strain (CΔhxtR) were constructed, and their virulence was compared with the wild-type strain in G. mellonella larvae and mice, which showed that disruption of hxtR significantly attenuated the virulence. Moreover, the ΔhxtR strain displayed a reduced survival ability in whole blood, increased sensitivity to phagocytosis, increased chain length, and growth defect. Taken together, this study performed a high throughput screening for VRGs of S. suis using a G. mellonella larvae model and further characterized a novel critical virulence factor.

Antimicrobial resistance (AMR) poses a huge threat to public health. The development of novel antibiotics is an effective strategy to tackle AMR. Cyclic diadenylate monophosphate (c-di-AMP) has recently been identified as an essential signal molecule for some important bacterial pathogens involved in various bacterial physiological processes, leading to its synthase diadenylate cyclase becoming an attractive antimicrobial drug target. In this study, based on the enzymatic activity of diadenylate cyclase of Streptococcus suis (ssDacA), we established a high-throughput method of screening for ssDacA inhibitors. Primary screening with a compound library containing 1133 compounds identified IPA-3 (2,2′-dihydroxy-1,1′-dinapthyldisulfide) as an ssDacA inhibitor. High-performance liquid chromatography (HPLC) analysis further indicated that IPA-3 could inhibit the production of c-di-AMP by ssDacA in vitro in a dose-dependent manner. Notably, it was demonstrated that IPA-3 could significantly inhibit the growth of several Gram-positive bacteria which harbor an essential diadenylate cyclase but not E. coli, which is devoid of the enzyme, or Streptococcus mutans, in which the diadenylate cyclase is not essential. Additionally, the binding site in ssDacA for IPA-3 was predicted by molecular docking, and contains residues that are relatively conserved in diadenylate cyclase of Gram-positive bacteria. Collectively, our results illustrate the feasibility of ssDacA as an antimicrobial target and consider IPA-3 as a promising starting point for the development of a novel antibacterial.

Aiming at the task allocation problem of heterogeneous unmanned underwater vehicle (UUV) swarms, this paper proposes a dynamic extended consensus-based bundle algorithm (DECBBA) based on consistency algorithm. Our algorithm considers the multi-UUV task allocation problem that each UUV can individually complete multiple tasks, constructs a “UUV-task” matching matrix and designs new marginal utility, reward and cost functions for the influence of time, path and UUV voyage. Furthermore, in view of the unfavorable factors that restrict the underwater acoustic communication range between UUVs in the real environment, our algorithm complete dynamic task allocation of UUV swarms with optimization in load balance indicator by the update of the UUV individual and the task completion status in the discrete time stage. The performance indicators (including global utility and task completion rate) of the dynamic task allocation algorithm in the scenario with communication constraints can be well close to the static algorithm in the ideal scenario without communication constraints. The simulation experiment results show that the algorithm proposed in this paper can quickly and efficiently obtain the dynamic and conflict-free task allocation assignment of UUV swarms with great performance.

Neonatal hypoxic ischemic encephalopathy (HIE) due to birth asphyxia is common and causes severe neurological deficits, without any effective therapies currently available. Neuronal death is an important driving factors of neurological disorders after HIE, but the regulatory mechanisms are still uncertain. Long non-coding RNA (lncRNA) or ceRNA network act as a significant regulator in neuroregeneration and neuronal apoptosis, thus owning a great potential as therapeutic targets in HIE. Here, we found a new lncRNA, is the most functional in targeting the Igfbp3 gene in HIE, which enriched in the cell growth and cell apoptosis processes. In addition, luciferase reporter assay showed competitive regulatory binding sites to the target gene Igfbp3 between TCONS00044054 (Vi4) and miR-185-5p. The change in blood miR-185-5p and Igfbp3 expression is further confirmed in patients with brain ischemia. Moreover, Vi4 overexpression and miR-185-5p knock-out promote the neuron survival and neurite growth, and suppress the cell apoptosis, then further improve the motor and cognitive deficits in rats with HIE, while Igfbp3 interfering got the opposite results. Together, Vi4-miR-185-5p-Igfbp3 regulatory network plays an important role in neuron survival and cell apoptosis and further promote the neuro-functional recovery from HIE, therefore is a likely a drug target for HIE therapy.

In modern jobs, performing well at work requires to an increasing degree that workers manage and motivate themselves for their tasks. Rather than to rely on a supervisor, they must set their own goals, decide how hard they work to achieve that goal, and decide when the task is completed. This manuscript describes the validation of an instrument that measures the extent to which workers must deal with such “motivational job demands”; the Motivational Demands at Work Scale (Mind@Work). Using data from a Dutch (N = 308) and a Chinese (N = 681) sample of working adults, confirmatory factor analysis showed that this instrument was reliable and robust in both samples, and that the factor structures obtained in both samples were highly comparable. Subsequent analyses demonstrated that high scores on the dimensions of the Mind@Work were associated with higher levels of engagement, work passion, job crafting and innovation behavior, even after controlling for job control, and job demands. These findings suggest that motivational job demands can be measured in a reliable and valid way. Thus, more research that examines the potential of this new concept for well-being and performance of employees seems warranted.

Abstract Background Rice stripe virus (RSV) belongs to the genus Tenuivirus. It is transmitted by small brown planthoppers in a persistent and circulative-propagative manner and causes rice stripe disease (RSD). The NS3 protein of RSV, encoded by the viral strand of RNA3, is a viral suppressor of RNA silencing (VSR). NS3 plays a significant role in viral infection, and NS3-transgenic plants manifest resistance to the virus. Methods The stability and availability of NS3 produced by transgenic Nicotiana benthamiana was investigated by northern blot analysis. The accumulation of virus was detected by western blot analysis. Transcriptome sequencing was used to identify differentially expressed genes (DEGs) in NS3-transgenic N. benthamiana. Results When the host plants were inoculated with RSV, symptoms and viral accumulation in NS3-transgenic N. benthamiana were reduced compared with the wild type. Transcriptome analysis identified 2533 differentially expressed genes (DEGs) in the NS3-transgenic N. benthamiana, including 597 upregulated genes and 1936 downregulated genes. These DEGs were classified into three Gene Ontology (GO) categories and were associated with 43 GO terms. KEGG pathway analysis revealed that these DEGs were involved in pathways associated with ribosomes (ko03010), photosynthesis (ko00195), photosynthesis-antenna proteins (ko00196), and carbon metabolism (ko01200). More than 70 DEGs were in these four pathways. Twelve DEGs were selected for RT-qPCR verification and subsequent analysis. The results showed that NS3 induced host resistance by affecting host gene expression. Conclusion NS3, which plays dual roles in the process of infection, may act as a VSR during RSV infection, and enable viral resistance in transgenic host plants. NS3 from RSV affects the expression of genes associated with ribosomes, photosynthesis, and carbon metabolism in N. benthamiana. This study enhances our understanding of the interactions between VSRs and host plants.

Probiotics have been associated with clinical infections, toxicity, and antimicrobial resistance transfer, raising public concerns. Probiotic enterococci are emerging food risks as opportunistic pathogens, yet little attention has been paid to them. Herein, we collected 88 enterococcal isolates from probiotic products used for humans, companion animals, livestock, and aquaculture. Results showed that all 88 probiotic enterococcal isolates harbored diverse virulence genes, multiple antimicrobial resistance genes, and mobile genetic elements. Notably, 77 isolates were highly resistant to gentamicin. Representative enterococcal isolates exerted toxic activities in both in vitro and in vivo models. Collectively, our findings suggest that probiotic enterococci may be harmful to hosts and pose a potential threat to public health.

Eukaryote-like serine/threonine kinases (STKs) and cognate phosphatases (STPs) comprise an important regulatory system in many bacterial pathogens. The complexity of this regulatory system has not been fully understood due to the presence of multiple STKs/STPs in many bacteria and their multiple substrates involved in many different physiological and pathogenetic processes. Streptococci are the best materials for the study due to a single copy of the gene encoding STK and its cognate STP. Although several studies have been done to investigate the roles of STK and STP in zoonotic Streptococcus suis, respectively, few studies were performed on the coordinated regulatory roles of this system. In this study, we carried out a systemic study on STK/STP in S. suis by using a comparative phenotypic, proteomic, and phosphoproteomic analysis. Mouse infection assays revealed that STK played a much more important role in S. suis pathogenesis than STP. The ∆stk and ∆stp∆stk strains, but not ∆stp, showed severe growth retardation. Moreover, both ∆stp and ∆stk strains displayed defects in cell division, but they were abnormal in different ways. The comparative proteomics and phosphoproteomics revealed that deletion of stk or stp had a significant influence on protein expression. Interestingly, more virulence factors were found to be downregulated in ∆stk than ∆stp. In ∆stk strain, a substantial number of the proteins with a reduced phosphorylation level were involved in cell division, energy metabolism, and protein translation. However, only a few proteins showed increased phosphorylation in ∆stp, which also included some proteins related to cell division. Collectively, our results show that both STP and STK are critical regulatory proteins for S. suis and that STK seems to play more important roles in growth, cell division, and pathogenesis.

The application scenarios and market shares of industrial robots have been increasing in recent years, and with them comes a huge market and technical demand for industrial robot-monitoring system (IRMS). With the development of IoT and cloud computing technologies, industrial robot monitoring has entered the cloud computing era. However, the data of industrial robot-monitoring tasks have characteristics of large data volume and high information redundancy, and need to occupy a large amount of communication bandwidth in cloud computing architecture, so cloud-based IRMS has gradually become unable to meet its performance and cost requirements. Therefore, this work constructs edge–cloud architecture for the IRMS. The industrial robot-monitoring task will be executed in the form of workflow and the local monitor will allocate computing resources for the subtasks of the workflow by analyzing the current situation of the edge–cloud network. In this work, the allocation problem of industrial robot-monitoring workflow is modeled as a latency and cost bi-objective optimization problem, and its solution is based on the evolutionary algorithm of the heuristic improvement NSGA-II. The experimental results demonstrate that the proposed algorithm can find non-dominated solutions faster and be closer to the Pareto frontier of the problem. The monitor can select an effective solution in the Pareto frontier to meet the needs of the monitoring task.

Ocean energy is a kind of renewable energy contained in seawater, which has the characteristics of large total reserves, sustainable use, and its being green and clean. Influenced by rising oil prices and global climate change, an increasing number of countries are attaching great importance to the strategic position of ocean energy in the future energy sector, and are formulating national ocean energy development roadmaps and conducting research and development on ocean energy technologies. Ocean current energy is a widely existing kind of ocean energy with abundant reserves. However, due to the low current velocity in most of the deep sea, low current energy has not been effectively exploited. In this paper, the Blade element momentum (BEM) theory based on Vortex column theory is used to design a special airfoil for low current energy applications, and a prototype turbine with rotor diameter of 4.46 m and tip speed ratio (TSR) of 6 is fabricated. In order to achieve stable electric power output, this paper designs a hydraulic conversion power generation control system with flexible control, and the hydraulic system working pressure designed to 21 MPa. In this paper, we conducted towing experiments on the prototype of an ocean current energy turbine, with hydraulic transmission and a control power generation system applied to the low flow rate, and achieved the target of hydraulic motor speed in the range of 14.7~15.9 r/min and steady-state speed accuracy in the range of ±1%. The research conducted in this paper can provide a research basis for the efficient exploitation of low-flow ocean current energy.

Resistive random access memory (RRAM) is one of the most promising new nonvolatile memories because of its excellent properties. Moreover, due to fast read speed and low work voltage, it is suitable for seldom-write frequent-read applications. However, as technology nodes shrink, RRAM faces many issues, which can significantly degrade RRAM performance. Therefore, it is necessary to optimize the sensing schemes to improve the application range of RRAM. In this paper, the issues faced by RRAM in advanced technology nodes are summarized. Then, the advantages and weaknesses in the novel design and optimization methodologies of sensing schemes are introduced in detail from three aspects, the reference schemes, sensing amplifier schemes, and bit line (BL)-enhancing schemes, according to the development of technology in especially recent years, which can be the reference for designing the sensing schemes. Moreover, the waveforms and results of each method are illustrated to make the design easy to understand. With the development of technology, the sensing schemes of RRAM become higher speed and resolution, low power consumption, and are applied at advanced technology nodes and low working voltage. Now, the most advanced nodes the RRAM applied is 14 nm node, the lowest working voltage can reach 0.32 V, and the shortest access time can be only a few nanoseconds.

Purpose: The aims of this study were to evaluate the expression of matrix metalloproteinase-1 (MMP-1) on laryngeal squamous cell carcinoma (LSCC) and improve the early diagnosis rate via ultrasound molecular imaging (USMI).Methods: The microsized MMP-1-targeted microbubbles (MBMMP-1) and the control MBs (MBIgG) based on perfluorocarbon-filled lipid-shelled MBs were constructed and characterized. The in vitro binding experiment was performed with human epidermoid laryngeal cancer cells (HEp-2) and tested the binding efficiency of MBMMP-1 and MBIgG. In the in vivo study, the LSCC model was established in 10 mice. The MBMMP-1 and MBIgG were randomly injected into tumor-bearing mice via the tail vein at Day 7, Day 12, and Day 17 to dynamically evaluate the differential targeted enhancement (dTE) signals via USMI. Subsequent immunofluorescence analysis was used for confirmation of MMP-1 expression.Result: The effective adhesion rate of MBMMP-1 and MBIgG to HEp-2 was 298.42 ± 16.57 versus 12.38 ± 3.26 bubbles/per field in vitro experiment, which shows a significant difference (P < 0.01). The in vivo ultrasound molecular imaging (USMI) results demonstrated that dTE signal intensity from MBMMP-1 was significantly higher than that from the MBIgG at Day 7, Day 12, and Day 17 (Day 7, 41.21 ± 15.00 versus 2.25 ± 0.6 a.u., P < 0.05; Day 12, 124.64 ± 5.19 versus 11.13 ± 1.13 a.u., P < 0. 05; Day 17, 332.01 ± 64.88 versus 42.99 ± 11.9 a.u., P < 0.01). Moreover, immunofluorescence analysis further confirmed the expression of MMP-1 in LSCC with a gradual increase with the tumor growth.Conclusion: MBMMP-1 could be a potential probe that can be used in the early diagnosis of LSCC by USMI.