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Infrared (IR) cameras have been important surveillance sensors for autonomous surface vessels; however, their detection ranges are limited by low resolution. In this study, we collect maritime IR images, analyze the characteristics of those images, and develop datasets for training and testing. Then, a new maritime IR image super-resolution network, maritime infrared super-resolution using cascaded residual network, is developed to reconstruct IR images using a scale of 4. Moreover, different loss functions have different effects on output images; a loss function is set to be a combination of three loss functions, including mean absolute error, mean squared error, and perceptual loss. Peak signal-to-noise ratio and structural similarity index measure cannot effectively describe super-resolution performance. As the novel evaluation metric, Canny edge detection method is used because edges are important for human and target detection algorithms. Finally, experiments are conducted and the results demonstrate that the developed residual network can achieve high-quality reconstructed maritime IR images.

The present study investigates the potential role of dioscin (DIO) in the lipopolysaccharide (LPS)‐induced kidney injury. For this purpose, DIO‐loaded zein nanoparticles (DIO‐ZNPs) were formulated and evaluated for physicochemical parameters. The DIO‐ZNPs exhibited a controlled release of drug compared with that of the free drug suspension. Results showed that the cell viability of NRK‐52E consistently decreased with the increase in LPS from 0.01 µg/ml to 2 µg/ml. When compared with LPS, DIO‐induced NPs showed 1.10‐, 1.32‐, 1.57‐ and 1.92‐fold increase in the cell viability for concentrations of 20 µg/ml, 50 µg/ml, 100 µg/ml and 200 µg/ml, respectively. DIO‐ZNPs exhibited the most remarkable recovery in the cell proliferation compared with free DIO as shown by the cellular morphology analysis. Furthermore, Annexin‐V staining analysis showed that the LPS‐treated cells possess the lowest green fluorescence indicating fewer viable cells, whereas DIO‐ZNPs exhibited the maximum green fluorescence comparable with that of the non‐treated cells indicating maximum cell viability. Furthermore, the results show that DIO‐ZNPs significantly increased the expression of miR‐let‐7i in the epithelial kidney cells, whereas the expression levels of TLR4 were significantly downregulated compared with that of the LPS‐treated cells. In conclusion, miR‐let‐7i could be an interesting therapeutic target and nanoparticle‐based DIO could be a potential candidate in the management of acute kidney injury

Location advantages of ports refer to the current developments of ports based on their conditions, such as geographic location, traffic accessibility and hinterland economy, etc., and the spatial pattern of ports’ location advantages reflects the spatial distributions, the regularities and the correlations among their conditions for development. A good understanding of the spatial patterns of ports’ location advantages can help to better identify the relative advantages of ports, position ports’ functions and make strategic plans for development. This paper selected 1259 ports from 63 countries along the Maritime Silk Road as research objects and builds an accessing model to analyze their location advantages on the bases of six factors: the influence of strategic shipping pivot, the competitiveness of port location potential, port network status, the influence of city, the influence of traffic trunk, and road network density in hinterland. The study has the following three findings. Firstly, the location advantages of ports show a “high-low-high” distribution pattern from the west to the east, displaying an obvious “core-periphery” regionalized distribution. Secondly, most ports have high location advantages, mainly located in Strait of Malacca, the United Arab Emirates, northern Mediterranean coastal region and China-Japan region, the top 10 ports are mainly located in Singapore, China, Malaysia and Japan, indicating that the shipping industry in Asia-Pacific region has stepped to the far front of the global competition; slow economic growths, wars, far away from the Belt and Road countries or bad climate have low location advantages, mainly located in African coastal areas, Oceania, Northeast Europe and Russia. Thirdly, compared with the landward location advantages, the seaward location advantages have a higher influence, and different indicators of location advantages have different influences on the evaluation results, the competitiveness of port location potential being the core indicator.

PM2.5 concentration is an important evaluation index of urban air quality. Improving the prediction and early warning ability of PM2.5 concentration is of great significance for guiding residents' real-time protection and efficient control of air pollution. A large number of studies have shown that the temporal and spatial correlation between PM2.5 concentration of surrounding stations and target stations directly affects the prediction accuracy of the model. There is still a lack on how to select strongly correlated and representative temporal and spatial information, and the selection methods are somewhat subjective. In this paper, air pollutants and meteorological factors are taken as the influencing factors, and a PM2.5 prediction model (ST-CCN-PM2.5) based on causal convolution network is proposed to improve the performance of PM2.5 concentration prediction at a fine-grained spatial-temporal scale. We use spatial attention mechanism to fuse spatial correlation information, and optimize threshold parameters. Based on time attention mechanism, the sliding window size is adjusted to dilate the time-series input. Finally, the hourly records of air pollutants and meteorological factors monitored by 95 monitoring stations in Haikou city are employed, and the performance is compared with baseline. Compared with AR and ARMA models, the MSE values decrease by 38.9% and 40.9%, and R2 values increase by 2.3% and 2.6%, respectively. Compared with GRU, SVR, LSTM and ANN models, the MSE value of ST-CCN-PM2.5 decreases by 44.8%, 45.4%, 46.5% and 49.0%, respectively, and its R2 value increases by 3.6%. The final results show that the prediction performance of ST-CCN-PM2.5 model is significantly improved compared with the baseline, which proves that the model has stronger reflection ability and prediction generalization ability for dynamic nonlinear system, and proves the potential of the model in the prediction of fine particle PM2.5 concentration.

Aiming at problems of feature extraction of monitoring data may lose useful information and different feature extraction methods have great influence on the results in rolling bearing performance degradation assessment. A method which is based on random matrix theory to assess the degradation of rolling bearing is proposed to improve production safety. Firstly, the observation matrix was constructed by the raw data of rolling bearing health monitoring, and the random matrix model of rolling bearing operating states was established by the steps of normalization, singular matrix singular value decomposition and standardization. Then, three performance degradation indicators, the average spectral radius, the maximum eigenvalue, and the number of random points in the inner ring are proposed by constructing the linear eigenvalue statistic of the random matrix, combined with the single ring curve of the bearing operating states, to describe the fluctuation discipline of the random matrix elements and the variation law of the characteristic root distribution, thus characterize the statistical random characteristics of the operating states of the rolling bearing as a whole. Finally, the method was applied by the rolling bearing life test vibration data. And four different operation states of the bearing are selected to build the random matrix model and analysis. The analysis results are calculated by single ring curves and quantitative indicators of different states and proved that the method proposed in this paper can effectively identify different degradation states and realize safety states of rolling bearing, meanwhile, it can quantitatively assess the degree of performance degradation.

It is of great significance for intelligent manufacturing to study condition monitoring and diagnosis methods to realize early diagnosis of mechanical equipment faults. An early fault diagnosis method for rolling bearing based on noise-assisted signal feature enhancement and stochastic resonance was proposed. The advantage of this algorithm is that it avoids the shortage of useful information filtering in traditional noise reduction methods. The generalized multi-scale permutation entropy screening criterion was used to screen the vibration signal, and the parameters of the Duffing vibration subsystem were optimized by the particle swarm optimization algorithm to achieve the optimal matching among the Duffing vibration subsystem, the input signal, and noise, thereby improving the stochastic resonance effect. Part of the background noise energy is transferred to the early weak fault signal feature of the rolling bearing, which enhances the feature of the early weak fault signal. The proposed method was applied to the early fault diagnosis of rolling bearing life state and compared with the adaptive morphology method based on variational mode decomposition (VMD). The results show the effectiveness and feasibility of the proposed method.

The objective of this study is to present an analytical subthreshold swing model for fully-depleted metal-oxide semiconductor field-effect transistors (MOSFETs) with vertical Gaussian profile fabricated on modified Silicon-on-Insulator (SOI) wafers. Commercial SOI wafers are radiation hardened by Si+ implantation which creates interface traps at buried SiO2/Si interface. Considering that channel potential is affected by non-uniform doping profile combined with process- and radiation-induced traps, the model is derived based on effective conduction path effect. The proposed model is validated by comparing analytical results with numerical simulation data obtained by using commercially available Sentaurus technology computer-aided design. The model agrees well with experimental extractions of irradiated nMOSFETs. This model is believed to be able to provide better physical insight and understanding of total dose irradiated modified SOI MOSFET devices operating in subthreshold regime.

Since the spread of the coronavirus disease 2019 (COVID-19) pandemic, the transportation of cargo by ship has been seriously impacted. In order to prevent and control maritime COVID-19 transmission, it is of great significance to track and predict ship sailing behavior. As the nodes of cargo ship transportation networks, ports of call can reflect the sailing behavior of the cargo ship. Accurate hierarchical division of ports of call can help to clarify the navigation law of ships with different ship types and scales. For typical cargo ships, ships with deadweight over 10,000 tonnages account for 95.77% of total deadweight, and 592,244 berthing ships&rsquo, records were mined from automatic identification system (AIS) from January to October 2020. Considering ship type and ship scale, port hierarchy classification models are constructed to divide these ports into three kinds of specialized ports, including bulk, container, and tanker ports. For all types of specialized ports (considering ship scale), port call probability for corresponding ship type is higher than other ships, positively correlated with the ship deadweight if port scale is bigger than ship scale, and negatively correlated with the ship deadweight if port scale is smaller than ship scale. Moreover, port call probability for its corresponding ship type is positively correlated with ship deadweight, while port call probability for other ship types is negatively correlated with ship deadweight. Results indicate that a specialized port hierarchical clustering algorithm can divide the hierarchical structure of typical cargo ship calling ports, and is an effective method to track the maritime transmission path of the COVID-19 pandemic.

White-box block cipher (WBC) aims at protecting the secret key of a block cipher even if an adversary has full control over the implementations. At CHES 2016, Bos et al. proved that WBC are also threatened by side-channel analysis (SCA), e.g., differential fault analysis (DFA) and differential computation analysis (DCA). Therefore, advanced countermeasures have been proposed by Lee et al. for resisting DFA and DCA, such as table redundancy and improved masking methods, respectively. In this paper, we introduce a new adaptive side-channel analysis model which assumes that an adversary adaptively collects the intermediate values of a specific function and can mount the DFA/DCA attack with chosen inputs. In the adaptive SCA model, both theoretical analysis and experimental results show that Lee et al.’s proposed methods are vulnerable to DFA and DCA attacks. Moreover, a negative proposition is also demonstrated on the corresponding high-order countermeasures under our new model.

Citrus detection is an essential component of the citrus industry. In order to realize the identification, positioning, segmentation, maturity estimation, and quality evaluation of citrus in complex environments, this paper proposes a multi-task deep learning network that can be applied to multiple scenes for citrus detection. The system is based on the Mask R-CNN network framework. By adding multi-task branches, modifying model parameters, and designing multi-task loss function, it can realize multi-task detection of citrus in a complex environment. The mAP on the validation set of the model obtained after training is 91.56%, and it takes an average of 0.35s to detect a citrus image using GeForce GTX 1080 Ti. Through the comparative analysis of the detection effect and performance evaluation index F value of multi-task citrus under different maturity, quality, citrus quantity, and light angle, the experimental results show that the model can effectively and accurately detect the citrus with different maturity and quality in the environment of citrus fruit overlap, tree branch and leaf occlusion, light change and surface shadow. The code is available at https://github.com/wxx-gan/Multitask.

OBJECTIVE To evaluate the distant metastatic patterns and prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in de novo metastatic nasopharyngeal carcinoma (mNPC) using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS Patients with de novo mNPC who had been diagnosed between 2004 and 2016 were identified from the SEER database. Kaplan-Meier analysis was used to calculate OS and CSS. Log-rank tests were employed to measure survival variation among subgroups. Individual predictors of CSS and OS were examined using Cox proportional-hazards regression models in patients with de novo mNPC. RESULTS We evaluated 224 patients with de novo mNPC who matched our inclusion criteria. Three-year CSS and OS for the whole cohort was 29.8% and 27.9%, respectively. Univariate analysis indicated that CSS and OS were influenced by age, histology, radiotherapy, chemotherapy, and liver metastasis. Neither the number of metastatic sites nor their specific location in bone, lungs, distant lymph nodes or brain significantly affected CSS or OS. The aforementioned independent prognosticators continued to significantly influence survival following multivariate analysis. Taking distant metastasis without liver involvement as a reference, liver metastasis was associated significantly with shorter OS at a hazard ratio (HR) of 1.581 (P = .021) and CSS at a HR of 1.643 (P = .016). Older age, keratinizing squamous cell carcinoma, no chemotherapy, and no radiotherapy were also prognosticators for poor OS (P

This paper investigates the effect of total dose radiation on the electrostatic potential distribution and the related short-channel effects (SCEs) of silicon-on-insulator (SOI) metal–oxide–semiconductor (MOS) devices with a vertical Gaussian doping profile. A new approximation of the 2-D potential function perpendicular to the channel for fully depleted SOI MOS field-effect transistors (FETs) is applied in the analytical threshold voltage model derivation. The impact of interface traps and oxide-trapped charge on the electrostatic potential profile, scaling, and SCEs are verified with TCAD simulations. The model agrees well with the experimental extractions of SCE in n-channel MOSFETs.

This paper focuses on nonsmooth Newton methods of optimal control problems governed by mixed control–state constraints with differential algebraic equations. In contrast to previous results, we analyze lifting operators involved in nonsmooth Newton methods and establish corresponding convergence results. We also give sufficient conditions for regularity of generalized derivatives of systems of nonsmooth operator equations associated with optimal control problems.

This study investigated the risk factors of peritonitis during early peritoneal dialysis for renal failure in patients with antineutrophil cytoplasmic antibody (ANCA)-associated systemic vasculitis (AASV). This study enrolled hospitalized AASV patients with renal failure who underwent peritoneal dialysis at the Department of Nephrology of our hospital between 2008 and 2015. The primary aim of this study was to perform a retrospective analysis to characterize peritonitis during the early period (≤ 8 weeks) of dialysis, and to compare the differences in initial clinical manifestations, vasculitis activity, immunosuppressive therapies prior to the renal replacement therapy, and prognosis between patients with or without peritonitis. The secondary aim of this study was to conduct a literature review of peritoneal dialysis in patients with vasculitis. All 14 enrolled AASV patients had myeloperoxidase (MPO)-positive microscopic polyangiitis (MPA). Six patients (of whom 2 died) withdrew from peritoneal dialysis due to peritonitis caused by enteric bacteria during the early period of dialysis. Their mean Birmingham vasculitis activity score (BVAS) during the early AASV onset was 31.67 ± 3.98, with significant symptoms of gastrointestinal involvement. Also, their BVAS score, anti-MPO antibody titer, erythrocyte sedimentation rate, C-reactive protein level, serum ANCA level, and glucocorticoid dose were higher than the AASV patients without peritonitis (all p 0.05). AASV patients with a higher level of vasculitis (BVAS score 30) during onset as well as gastrointestinal symptoms had a higher risk for intestinal peritonitis. Therefore, peritoneal dialysis is not recommended as a first-choice renal replacement therapy for such patients. .

The robustness of cargo ship transportation networks is essential to the stability of the world trade system. The current research mainly focuses on the coarse-grained, holistic cargo ship transportation network while ignoring the structural diversity of different sub-networks. In this paper, we evaluate the robustness of the global cargo ship transportation network based on the most recent Automatic Identification System (AIS) data available. First, we subdivide three typical cargo ship transportation networks (i.e., oil tanker, container ship and bulk carrier) from the original cargo ship transportation network. Then, we design statistical indices based on complex network theory and employ four attack strategies, including random attack and three intentional attacks (i.e., degree-based attack, betweenness- based attack and flux-based attack) to evaluate the robustness of the three typical cargo ship transportation networks. Finally, we compare the integrity of the remaining ports of the network when a small proportion of ports lose their function. The results show that 1) compared with the holistic cargo ship transportation network, the fine-grain-based cargo ship transportation networks can fully reflect the pattern and process of global cargo transportation; 2) different cargo ship networks behave heterogeneously in terms of their robustness, with the container network being the weakest and the bulk carrier network being the strongest; and 3) small-scale intentional attacks may have significant influence on the integrity of the container network but a minor impact on the bulk carrier and oil tanker transportation networks. These conclusions can help improve the decision support capabilities in maritime transportation planning and emergency response and facilitate the establishment of a more reliable maritime transportation system.

Maritime safety is an important issue for global shipping industries. Currently, most of collision accidents at sea are caused by the misjudgement of the ship’s operators. The deployment of maritime autonomous surface ships (MASS) can greatly reduce ships’ reliance on human operators by using an automated intelligent collision avoidance system to replace human decision-making. To successfully develop such a system, the capability of autonomously identifying other ships and evaluating their associated encountering situation is of paramount importance. In this paper, we aim to identify ships’ encounter situation modes using deep learning methods based upon the Automatic Identification System (AIS) data. First, a segmentation process is developed to divide each ship’s AIS data into different segments that contain only one encounter situation mode. This is different to the majority of studies that have proposed encounter situation mode classification using hand-crafted features, which may not reflect the actual ship’s movement states. Furthermore, a number of present classification tasks are conducted using substantial labelled AIS data followed by a supervised training paradigm, which is not applicable to our dataset as it contains a large number of unlabelled AIS data. Therefore, a method called Semi-Supervised Convolutional Encoder–Decoder Network (SCEDN) for ship encounter situation classification based on AIS data is proposed. The structure of the network is not only able to automatically extract features from AIS segments but also share training parameters for the unlabelled data. The SCEDN uses an encoder–decoder convolutional structure with four channels for each segment (distance, speed, Time to the Closed Point of Approach (TCPA) and Distance to the Closed Point of Approach (DCPA)) been developed. The performance of the SCEDN model are evaluated by comparing to several baselines with the experimental results demonstrating a higher accuracy can be achieved by our proposed model.

The ship’s pilot can obtain the ship auxiliary information through the navigation system, when berthing system can display the parameters such as traverse speed and distance of the ship. But most of the system data show that there are insufficient precision. Taking the CORS system to obtain the location information, data Calculation of Berthing System based on Polar Coordinate Algorithm, this paper puts forward a solution to the “dead point” of the berthing and aiding system, which has a certain reference value for the design of the ship berthing assistance system.

The present study aimed to investigate and compare the analgesic effect and safety of ropivacaine or levobupivacaine in combined spinal-epidural anesthesia during childbirth and their effects on neonatal Apgar scores, as well as maternal and neonatal vital signs. A total of 615 maternal patients undergoing labor between April 2016 and March 2017 were divided into two groups according to the analgesic used for combined spinal-epidural anesthesia during childbirth: The ropivacaine group (n=318) and the levobupivacaine group (n=297). The onset time of analgesia in the two groups was determined and the pain score on the visual analog scale was assessed at the time of delivery (T3). At pre-analgesia, 30 min after analgesia (T2), at T3 and during maternal wound suturing (T4), the systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) were assessed. The cesarean section rate, neonatal 1- and 5-min Apgar scores and neonatal asphyxia at T4 were also determined. The onset time of analgesia in the ropivacaine group was significantly reduced compared with that in the levobupivacaine group (P

This paper introduces the development status of Offshore Wind Farms (OWFs) in the Taiwan Strait. We review some typical conflict cases between OWFs and maritime shipping in the Strait, the reasons why and how these conflicts occur when new OWF are ready to be built close the principal fairway passage through the strait.

This study was conducted to identify factors associated with lymph node (LN) metastasis in nasopharyngeal carcinoma (NPC) patients, analyze node distribution patterns, and explore the prognostic value of the LN metastasis level for survival. We included 2994 patients with primary NPC diagnosed between 2006 and 2015 with information in the Surveillance, Epidemiology, and End Results (SEER) database. Patients’ demographic and clinicopathologic features were compared according to LN status using chi-squared tests. The 5-year overall survival (OS) and cancer-specific survival (CSS) rates were calculated by the Kaplan–Meier method, and the differences were estimated by log-rank tests. Multivariate Cox proportional hazard models were used to evaluate independent risk factors for OS and CSS. Logistic regression was used to evaluate the risk of each LN metastasis category for distant metastasis. There were 695 patients in the N0 stage and 2299 with LN metastasis (classified as stage N1, N2, or N3). The overall incidence of LN metastasis was 76.8%. Sex and T stage were not associated with LN metastasis. Older patients had a significantly worse 5-year OS and CSS than younger patients. In terms of histologic type, keratinizing squamous cell carcinoma had the lowest 5-year OS and CSS at 48.2% and 53.8%, respectively. The most common nodal involvement level was II (65.9%), followed by III (29.1%), V (25.6%), I (17.6%), IV (15.7%), and retropharynx (13.5%). The skip metastasis rate was 5.7% (130/2299). Patients with only level II metastasis (classified as level 2) was the most common category, accounting for 30%. Compared to level 2, patients with only level I (classified as level 1) had an OR of 2.101 (95% CI: 1.090–4.047, P=0.027) for distant metastasis, patients with simultaneous levels II, III, IV, and V (classified as levels 2345) had the highest OR of 4.064 (95% CI: 2.155–7.666, P<0.001) for distant metastasis, and level 24 had an OR of 3.003 (95% CI: 1.074–8.395, P=0.036) for distant metastasis. In survival analysis, levels 235 had a significant HR of 1.708 (95% CI: 1.089–2.678, P=0.020) for CSS compared to level 2 after adjustment for age, sex, race, histology, TNM (tumor, node, and metastasis) stage, and treatment.

Ship voyage optimization provides key theoretical and technical insights for efficient shipping operations. It is critical for developing methodologies and systems that bridge the gaps between the perceived expectations of stakeholders and actual ship operations and for truly applying primary principles and fundamental practices in maritime operations. To develop an advanced and effective shipping voyage optimization system, it is necessary to investigate thoroughly the factors affecting fuel consumption and integrate wisely other aspects, including cargo operation, emissions from fuel consumption, and emission control regulations. The literature on ship voyage optimization is flourishing with the development of green maritime transportation . This paper carefully reviews the latest articles on emission control-driven voyage optimization to investigate the state-of-art and further identify research gaps, ongoing topics, and future research trends.

Maritime traffic can reflect the diverse and complex relations between countries and regions, such as economic trade and geopolitics. Based on the AIS (Automatic Identification System) trajectory data of ships, this study constructs the Maritime Silk Road traffic network. In this study, we used a complex network theory along with social network analysis and network flow analysis to analyze the spatial distribution characteristics of maritime traffic flow of the Maritime Silk Road, further, we empirically demonstrate the traffic inequality in the route. On this basis, we explore the role of the country in the maritime traffic system and the resulting traffic relations. There are three main results of this study. (1) The inequality in the maritime traffic of the Maritime Silk Road has led to obvious regional differences. Europe, west Asia, northeast Asia, and southeast Asia are the dominant regions of the Maritime Silk Road. (2) Different countries play different maritime traffic roles. Italy, Singapore, and China are the core countries in the maritime traffic network of the Maritime Silk Road, Greece, Turkey, Cyprus, Lebanon, and Israel have built a structure of maritime traffic flow in the eastern Mediterranean Sea, and Saudi Arabia serves as a bridge for maritime trade between Asia and Europe. (3) The maritime traffic relations show the characteristics of regionalization, countries in west Asia and the European Mediterranean region are clearly polarized, and competition&ndash, synergy relations have become the main form of maritime traffic relations among the countries in the dominant regions. Our results can provide a scientific reference for the coordinated development of regional shipping, improvement of maritime competition, cooperation strategies for countries, and adjustments in the organizational structure of ports along the Maritime Silk Road.

Large-scale systems of nonlinear equations appear in many applications. In various applications, the solution of the nonlinear equations should also be in a certain interval. A typical application is a discretized system of reaction diffusion equations. It is well known that chemical species should be positive otherwise the solution is not physical and in general blow up occurs. Recently, a projected Newton method has been developed, which can be used to solve this type of problems. A drawback is that the projected Newton method is not globally convergent. This motivates us to develop a new feasible projected Newton–Krylov algorithm for solving a constrained system of nonlinear equations. Combined with a projected gradient direction, our feasible projected Newton–Krylov algorithm circumvents the non-descent drawback of search directions which appear in the classical projected Newton methods. Global and local superlinear convergence of our approach is established under some standard assumptions. Numerical experiments are used to illustrate that the new projected Newton method is globally convergent and is a significate complementarity for Newton–Krylov algorithms known in the literature.

For improving the safety and security of maritime personnel, the rescue terminal based on the short message of the Beidou is designed and realized. The terminal uses ST-M32F103RBT6 as the control processing unit and obtains the latest information of distress personnel through the Beidou short message module GN51, and then converting original information into AIS information and Beidou short message information, and finally through the VHF maritime mobile spectrum and the Beidou satellite to send help information. The terminal enables shore-based control center to know people in distress in the first time and thus to saving time and greatly improving the efficiency of search and rescue.

It is an important means to improve the utilization rate and reliability of the equipment to realize the state health monitoring of the mechanical equipment by building the Internet of things with multi-sensor. Studying the correlation of multi-source and similar sensor signals can improve the comprehensive utilization of information. In this paper, the similarity measure is used to describe and analyze the correlation between the multi-sensor monitoring signals of rolling bearing, and the failure bearing data is used to realize the comprehensive utilization of information prediction of service bearing life. To overcome the disadvantage of inconsistent prediction results and low reliability of rolling bearing single feature characterization and similarity life prediction algorithm, a comprehensive similarity life prediction method of rolling bearing based on multi-dimensional feature fusion is proposed in this paper. Nine degradation features of bearing vibration signal, such as kurtosis and root mean square, are extracted. Based on principal component analysis (PCA), multi-dimensional features are fused to fully characterize the operation state of rolling bearings. The maximum and minimum life values of rolling bearings given by different features under normal conditions are obtained. By calculating the comprehensive similarity, the corresponding life proportional adjustment functions are constructed respectively. The life results predicted by PCA fusion features are corrected in real time, and the predicted life intervals of the monitoring bearings are given. The experimental data of rolling bearings at the University of Cincinnati are used to carry out the applied research. Compared with the single time domain feature prediction results, the multi-dimensional feature prediction algorithm describes the life information of rolling bearings from various angles, and the prediction results are more accurate and reliable. The method presented in this paper provides a theoretical basis for predictive maintenance and health management of rolling bearings.

Rolling bearing is an important part of rotating machinery which operation safety and reliability are directly related to the normal operation of equipment. Remaining useful life is an important index for describing the safe operation of industrial rolling bearing and life prediction technology of machinery equipment is an important method to realize intelligent maintenance and industrial safety operation. According to the idea of data-driven, a new method for predicting the life of rolling bearing was proposed. By using life-cycle data of bearing from normal to failure, based on the new clustering algorithm of K-means and threshold correction, the recognition and partition of different operation states of rolling bearings were realized and the life model was established by defining the state matrix. For the monitoring bearing, comprehensive similarity analysis with the historical data was carried out to construct the life proportional adjustment function and dynamically modify the parameters of the state matrix model, so as to realize the adaptive prediction of the life of the monitoring bearing. The bearing test data of the University of Cincinnati Laboratory Center were used to carry out the applied research. The normal operation state and remaining life of two bearings were predicted by a set of bearing life data. The results showed that the method had better prediction accuracy and generalization compared with hidden Markov model and grey model. This study provides some theoretical guidance and basis for the industrial safe operation and maintenance of rolling bearings during service.

We provide an analysis of the pigment composition of reconstituted wild type CP29 complexes. The obtained stoichiometry of 9 +/- 0.6 Chls a and 3 +/- 0.6 Chls b per complex, with some possible heterogeneity in the carotenoid binding, is in agreement with 9 Chls a and 3.5 Chls b revealed by the modeling of low-temperature optical spectra. We find that similar to 50% of Chl b614 is lost during the reconstitution/purification procedure, whereas Chls a are almost fully retained. The excitonic structure and the nature of the low-energy (low-E) state(s) are addressed via simulations (using Redfield theory) of 5 K absorption and fluorescence/ nonresonant hole-burned (NRHB) spectra obtained at different excitation/burning conditions. We show that, depending on laser excitation frequency, reconstituted complexes display two (independent) low-E states (i.e., the A and B traps) with different NRHB and emission spectra. The red-shifted state A near 682.4 nm is assigned to a minor (similar to 10%) subpopulation (sub. II) that most likely originates from an imperfect local folding occurring during protein reconstitution. Its lowest energy state A (localized on Chl a604) is easily burned with lambda(B) = 488.0 nm and has a red-shifted fluorescence origin band near 683.7 nm that is not observed in native (isolated) complexes. Prolonged burning by 488.0 nm light reveals a second low-E trap at 680.2 nm (state B) with a fluorescence origin band at similar to 681 nm, which is also observed when using a direct low-fluence excitation near 650 nm. The latter state is mostly delocalized over the a611, a612, a615 Chl trimer and corresponds to the lowest energy state of the major (similar to 90%) subpopulation (sub. I) that exhibits a lower hole-burning quantum yield. Thus, we suggest that major sub. I correspond to the native folding of CP29, whereas the red shift of the Chl a604 site energy observed in the minor sub. II occurs only in reconstituted complexes.

In this study, molecular characteristics of march5b and co-expression of march5b and tlr7 in response to the infection of Cryptocaryon irritans in the large yellow croaker Larimichthys crocea were investigated. The full-length complementary (c)DNA of march5b was 1314bp, including an open reading frame of 846bp encoding a polypeptide of 281 amino acids, and the full-length genomic sequence was composed of 23577 nucleotides, including six exons and five introns. The putative March5b protein contained a RINGv motif and four transmembrane domains. The march5b transcripts were broadly distributed in all detected tissues, with a strong expression in blood, brain and gills, and a weak expression in kidney by quantitative PCR analysis. The expression of march5b and tlr7 in the skin, gills, spleen and head kidney changed in the same manner at most time points post-primary infection with C. irritans. Significant increase was observed in the skin with march5b at days 2 and 3 by 2610 and 688 fold, respectively, and with tlr7 at day 3 by 5768 fold, when compared with the control. Their expressions, however, were decreased in the gills, especially at day 3 (march5b by 89%, tlr7 by 2206%). In the spleen and head kidney, march5b and tlr7 transcripts were up-regulated early, then noticeably declined at day 3. These results suggested that march5b and tlr7 are co-expressed in response to parasite infection and March5b probably catalyses ubiquitination of some proteins of TLR7 signalling pathway.