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Accidents caused by the failure of high-voltage power battery systems are rising with the increase of pure electric commercial vehicles. The fault tree analysis method based on traditional reliability is no longer suitable for quantitative evaluation of polymorphic systems. In this paper, the polymorphic fuzzy fault tree of the high-voltage power battery system for pure electric commercial vehicles is established and analyzed qualitatively and quantitatively based on a combined theory of the polymorphic theory, fuzzy mathematical theory, group decision theory, and fault tree analysis theory. The results showed that the multistate reliability-analysis method of the fuzzy fault tree could describe the various fault states of the high-voltage power battery system. Through quantitative evaluation of the reliability of system, the low-temperature environment and CAN high and low reverse connection were the weakest links of the system, and the problem of the occurrence probability of each state of the unknown polymorphic bottom event in the sub-fault tree of the deteriorated-state mode was solved quickly using group decision-making to deal with fuzzy probability. It provides theoretical reference for system design and detection process, which has important practical significance for the improvement of high-voltage power battery system.

Satellite Interferometric Synthetic Aperture Radar (InSAR) is widely used for topographic, geological and natural resource investigations. However, most of the existing InSAR studies of ground deformation are based on relatively short periods and single sensors. This paper introduces a new multi-sensor InSAR time series data fusion method for time-overlapping and time-interval datasets, to address cases when partial overlaps and/or temporal gaps exist. A new Power Exponential Knothe Model (PEKM) fits and fuses overlaps in the deformation curves, while a Long Short-Term Memory (LSTM) neural network predicts and fuses any temporal gaps in the series. Taking the city of Wuhan (China) as experiment area, COSMO-SkyMed (2011-2015), TerraSAR-X (2015-2019) and Sentinel-1 (2019-2021) SAR datasets were fused to map long-term surface deformation over the last decade. An independent 2011-2020 InSAR time series analysis based on 230 COSMO-SkyMed scenes was also used as reference for comparison. The correlation coefficient between the results of the fusion algorithm and the reference data is 0.87 in the time overlapping region and 0.97 in the time-interval dataset. The correlation coefficient of the overall results is 0.78, which fully demonstrates that the algorithm proposed achieves a similar trend as the reference deformation curve. Based on the long time series settlement results obtained by fusion, we analyze the causes of settlement in detail for several subsidence zones. The subsidence in Houhu is caused by soft soil consolidation and compression. Soil mechanics are therefore used to estimate when the subsidence is expected to finish and to calculate the degree of consolidation for each year. The COSMO-SkyMed PSInSAR results indicate that the area has entered the late stage of consolidation and compression and is gradually stabilizing. The subsidence curve found for the area around Xinrong shows that the construction of an underground tract of subway Line 21 caused large-scale settlement in this area. The temporal granularity of the PSInSAR time series also allows precise detection of a rebound phase following a major flooding event in 2016. The experimental results demonstrate the accuracy of the proposed new fusion method to provide robust time series for the analysis of long-term land subsidence mechanisms and unveil previously unknown characters of land subsidence in Wuhan, thus clarifying the relationship with the urban causative factors.

This work considers the observability problem in bearings-only tracking (BOT). Although the rank criterion has always been used for observability analysis, the evident drawback that it can only give a qualitative result prevents us from exploiting more information from the observability matrix. In reality, we want to know not only if the system is observable but also the degree of the observability. In order to quantitatively describe the system observability, we propose a series of metrics for BOT. Being derived based on the condition number, the novel metrics can reflect the observability degree as well as evaluate the tracking performance. Besides, the metrics can be extended to be used for sensor trajectory optimization and sensor configuration, which are crucial to enhancing the tracking performance.

IntroductionPesticides are widely and excessively used in the world. Reducing pesticide overuse is an important measure to protect the environment and human health.MethodsBased on the survey data of 518 farmers in Shandong Province, China, using the Logit model to empirically test the effect of risk cognition on farmers' pesticide overuse behavior and the moderating effect of cooperatives training on the effect of risk cognition on farmers' pesticide overuse behavior.Results and discussionWe found that 21.24% of farmers overused pesticides. The three dimensions of risk cognition have significant negative effects on farmers' behavior of excessive pesticide use, among which the human health risk cognition has the largest impact (0.74), followed by food safety risk cognition (0.68) and ecological environment risk cognition (0.63). Cooperatives training has a positive moderating effect on the relationship between risk cognition and pesticide overuse behavior, that is, when risk cognition matches farmers participating in cooperatives training, the effect on reducing pesticide overuse is more significant. Years of education, planting scale and detection frequency of pesticide residues have significant effects on farmers' pesticide overuse.ConclusionsThe government should help farmers reduce pesticide overuse by improving risk cognition, developing agricultural cooperatives and perfecting guarantee conditions.

The efficacy of a bearings-only tracking algorithm, to a great extent, depends on the target-sensor geometry and motion. Although the pseudolinear Kalman filter and its variants have demonstrated comparable performance with the elite non-linear filters, they still suffer from bias problems and the tracking performance is inevitably affected by the relative geometry and motion relationships. In this study, an observability metric based on classical control theory is first presented to characterise the relative relationships between the target and the sensor. Then an efficient bearings-only tracking algorithm called Gaussian sum pseudolinear Kalman filter is developed. It is based on the bias-compensated pseudolinear Kalman filter and is built within a Gaussian sum framework. In the novel algorithm, a splitting and merging procedure will be triggered when a low degree of observability is detected. Simulation results show the significant performance improvement of the proposed algorithm.

Both the modeling and the load regulation capacity prediction of a supercritical power plant are investigated in this paper. Firstly, an indirect identification method based on subspace identification method is proposed. The obtained identification model is verified by the actual operation data and the dynamic characteristics of the system are well reproduced. Secondly, the model is used to predict the load regulation capacity of thermal power unit. The power, main steam pressure, main steam temperature and other parameters are simulated respectively when the unit load is going up and down. Under the actual constraints, the load regulation capacity of thermal power unit can be predicted quickly.

Cotton is an important economic crop, but large-scale field extraction and estimation can be difficult, particularly in areas where cotton fields are small and discretely distributed. Moreover, cotton and soybean are cultivated together in some areas, further increasing the difficulty of cotton extraction. In this paper, an innovative method for cotton area estimation using Sentinel-2 images, land use status data (LUSD), and field survey data is proposed. Three areas in Hubei province (i.e., Jingzhou, Xiaogan, and Huanggang) were used as research sites to test the performance of the proposed extraction method. First, the Sentinel-2 images were spatially constrained using LUSD categories of irrigated land and dry land. Seven classification schemes were created based on spectral features, vegetation index (VI) features, and texture features, which were then used to generate the SVM classifier. To minimize misclassification between cotton and soybean fields, the cotton and soybean separation index (CSSDI) was introduced based on the red band and red-edge band of Sentinel-2. The configuration combining VI and spectral features yielded the best cotton extraction results, with F1 scores of 86.93%, 80.11%, and 71.58% for Jingzhou, Xiaogan, and Huanggang. When CSSDI was incorporated, the F1 score for Huanggang increased to 79.33%. An alternative approach using LUSD for non-target sample augmentation was also introduced. The method was used for Huangmei county, resulting in an F1 score of 78.69% and an area error of 7.01%. These results demonstrate the potential of the proposed method to extract cotton cultivated areas, particularly in regions with smaller and scattered plots.

The small scale of transmission towers and the environmental diversity around their situations make their detection in Synthetic Aperture Radar (SAR) images a challenging task. This paper presents a new hierarchical detection algorithm for transmission towers. First, Signal-to-Clutter Ratios (SCRs) of pixels are calculated. Afterwards, a SCR threshold is set. Since transmission towers possess strong scattering characteristics, pixels with SCRs above the threshold are considered as potential transmission tower pixels. Second, spatial densities of potential transmission tower pixels are calculated. According to the aggregation characteristics of transmission tower pixels, some potential transmission tower pixels with small spatial densities are removed. The remained potential transmission tower pixels are considered as candidate transmission tower pixels. The candidate transmission tower pixels are grouped by the nearest neighbour scheme such that in each group the distance between pixels is under a given threshold. Thus, each of the groups is viewed as a quasi-transmission tower. Convex-hulls of quasi-transmission towers are built, and then Minimum Bounding Rectangle (MBR) for each convex-hull is generated. According to the rectangle aspect ratios of MBRs, the real transmission towers are extracted. C-band HH-polarization GaoFen-3 (GF-3) amplitude images are used for experiments and four of the most popular transmission tower detection algorithms are selected as comparing algorithms to validate the proposed algorithms. The detection performance of transmission towers is evaluated with detection rate and quality factor. Experimental results verify that the proposed algorithm can efficiently and accurately detect transmission towers while maintaining the transmission tower geometry to a certain extent, which indicates that the proposed algorithm is efficient and promising.

The measurement of viscosity coefficient of liquids is vital in plentiful fields. There are numerous ways to measure the viscosity coefficient such as capillary and rotary rheometry in which falling ball method is mostly widely used. The uncertainty of the terminal velocity and the limit of the viscosity coefficient scale are the principled disadvantages of the method. In our work, the relationship between the displacement and time is obtained by integral calculation. What’s more, we considered the radius of the ball, the radius of the graduated cylinder, and the height of the graduated cylinder by theoretical correction of the stokes expression. The new correction expression broadens the measured viscosity coefficient scale and also improves the precision dramatically. Experimental verification is also well processed which fits well with our theory. The deviation between the viscosity coefficient of castor oil measured by the new correction method and the standard value is only 0.045. The relationship between displacement and time is consistent with the theoretical prediction, and the room mean square error of the two is 0.065. Based on them, this method can be widely used in scientific researches and teaching practices.

In this article, a digital twin-based subspace model predictive control scheme is proposed for solving model mismatch caused by parameter perturbations of thermal power plants. First, the rational range of essential parameters in the nonlinear model is identified based on the nominal data of an actual 600 MW power plant, which provides necessary foundation for subsequent studies. Second, to improve the load-changing capacity under parameter disturbances, a novel digital twin-based subspace model predictive control algorithm is established by regarding the crucial parameter as extended input of predictive model. Finally, the small fluctuations during steady-state operation are effectively restrained through transforming weights and constraints slowly and smoothly at the end of load change. Simulation results illustrate that compared with the conventional subspace-based model predictive control, the proposed digital twin-based subspace model predictive control scheme can obtain a better performance in terms of both dynamic regulation rate and steady-state performance under parameter perturbations.

This study presents a numerical investigation of the solitary wave breaking over a slope by using the multi-phase smoothed particle hydrodynamics (SPH) method. Four different computational models are proposed to solve the gas-related far-field boundary conditions, and the model with the least disturbance to the internal flow field is selected. Since the artificial viscous coefficient can greatly affect the wave-breaking location, an empirical equation is fitted to quickly determine the optimal value of the artificial viscous coefficient. In addition, the turbulence model and three-dimensional effect on the wave breaking are discussed in this study. The results show that the present two-dimensional multi-phase SPH without a turbulence model can capture the macroscopic characteristics of the flow before the vortices convert to three dimensional flow structures caused by the wave breaking. Then, the processes of shoaling solitary wave breaking with different slopes and relative wave heights are simulated. Compared with the single-phase SPH, the multi-phase SPH is of great help in improving the prediction of wave breaking. A vortex similar to the Rankine Vortex is observed near the wave crest. Its intensity affects the pressure distribution of the gas, and its relative position to the wave crest is relevant to the energy transfer from the water to the gas. During the solitary wave propagating from deep water to shallow water, energy dissipation of gas and water shows four different stages. In the stage of energy dissipation, the gas can absorb the great energy from the water, which effectively dissipates the wave energy.

This paper presents a zero-optical-distance mini-LED backlight with cone-shaped light coupling microstructures to achieve an ultra-thin backlight architecture (~0.1 mm thickness) by combining the characteristics of direct-lit and edge-lit backlights. There is no gap between the light guide plate (LGP) and the reflector, as well as between the LGP and the mini-LED embedded in the reflector. The illuminance uniformity and light extraction efficiency (LEE) of the whole structure reach 91.47% and 77.09%, respectively. Nine sub-modules are spliced together to realize 2D local dimming with 0.29% crosstalk. The structure shows high optical performance while reducing the thickness of the backlight module, which is of great significance for the development of mini-LED backlights.

In recent years, overturning accidents at single-pier bridges have occurred frequently, resulting in significant property losses and safety accidents. Overturning accidents show that there are still many hidden dangers in the design, operation, and management of existing single-pier bridges. Therefore, this paper takes the K503 + 647.4 separated overpass of the Hegang–Dalian Expressway as the research object and carries out an onsite anti-overturning stability test of a single-column pier bridge. Through loading under various working conditions, the displacement changes of each support are measured, and the reaction changes of the supports are calculated. In the process of simulating the field test using the finite element program ANSYS, a rigid model based on ideal support and an elastic model considering beam deformation are established, and the accuracy of the elastic model is verified by comparison with the field-measured data. Furthermore, a series of parameters, such as the bridge side-span ratio, bridge span number, bearing spacing, loading position, and torsional rigidity, are varied, and finite element simulation is carried out on the basis of the elastic model. Through comparison of the results, a relationship between the parameters of the single-pier bridge and the anti-overturning ability is obtained, which provides a theoretical basis for anti-overturning design research and the effective reinforcement of single-pier bridges.

In the growing mass of social media data, how to efficiently extract the collection of interested concerns has become a research hotspot. Due to the large size and regularity of social media data, traditional indexing techniques are not applicable. Our “Learned Index”, which is a part of social media intelligence solutions, uses mathematical principles to summarize the laws from the data. It predicts the location of the data by learning the mathematical properties of the data distribution to build the model. Although existing methods over single dimension and multi-dimension such as setting gaps are proposed to further optimize the performance of index, they do not consider the update-distribution of data. In this paper, we propose an update-distribution-aware learned index for social media data (TALI) to support update operations and handle the data sliding. In TALI, underlying data are learned through machine learning models, and a recursive hierarchical model is built. It also learns the update-distribution of data to adjust the size of each leaf node. Thus, it can more effectively support all kinds of operations in databases due to the decrease of the leaf nodes’ sliding. In addition, TALI uses the model-based insertion method for bulkload and query, resulting in a small prediction error. Thus, exponential search is used to perform secondary lookup to improve query efficiency. Experiments were tested and compared on four realistic and synthetic social media datasets. Through extensive experiments, TALI performed better than the existing state-of-the-art learned index with less space occupancy on four realistic and synthetic social media datasets.

Automatic emotion recognition methods are sensitive to the variations across humans and datasets and their performance drops when evaluated across corpora. Domain adaptation (DA) techniques such as Domain-Adversarial Neural Network (DANN) can mitigate this problem. However, domain adaptation cannot guarantee to preserve local features necessary for emotion recognition while reducing domain discrepancies in global features. In this paper, we propose Face wArping emoTion rEcognition (FATE) to address this problem. Unlike the traditional DA models in which the base model is first trained with the source data and then fine-tuned with the source and target data, we reverse the training order. Specifically, we employ first-order facial animation warping to generate a synthetic dataset and utilize contrastive learning to pre-train the encoder. Then, we fine-tune the encoder and the classifier with the source data. After fine-tuning, the model achieves superior emotion recognition performance by preserving the subtle facial features. Our experiments on cross-domain emotion recognition with facial behaviors (Aff-Wild2, SEWA, and SEMAINE) indicate that the proposed FATE model substantially outperforms the domain adaptation models, suggesting that FATE has a better domain generalizability for emotion recognition.

Background: Maximum oxygen uptake (VO2max) is an important respiratory physiological index of the aerobic endurance of the body, especially for special groups such as drug addicts, and it is an important indicator for assessing the cardiopulmonary function and formulating exercise prescriptions. Although the cardiopulmonary exercise test (CPX) is a classic method to directly measure VO2max, this method is limited by factors such as cumbersome operating procedures and expensive equipment, resulting in its relatively low applicability. Recently, many studies have begun to focus on the estimation of VO2max in different groups of people, but few studies have focused on drug addicts.Methods: Fifteen chemically synthesized drug addicts (such as amphetamines) and Fifteen plant-derived drug addicts (such as heroin) were recruited at the Chongqing Compulsory Isolation and Drug Rehabilitation Center in China. First, the VO2max of subjects was directly measured through the CPX. Second, after subjects were fully rested, they were required to complete the 30-s high-leg raise, 1,000-m walk, and 3-min step experiment. Finally, SPSS 21.0 software was used to perform the correlation and linear regression analysis to verify the estimated effectiveness.Results: (1) Regardless of chemically synthesized or natural plant-derived drug addicts, the years of drug use and walking time of 1,000 m were significantly negatively correlated with VO2max (chemically synthesized: P < 0.01 and natural plant-derived: P < 0.05), the number of 30-s high-leg raises was a significantly positive correlation with VO2max (P < 0.05 and P < 0.01), and the 3-min step index was significantly positively correlated with VO2max (P < 0.01 and P < 0.01). (2) Regression analysis shows that the 30-s high-leg lift, 1,000-m walking, and 3-min step experiment could effectively estimate the VO2max of chemically synthesized and natural plant-derived drug addicts. (3) Multiple linear regression constructed by the years of drug use combined with the step index has the highest estimated accuracy for the VO2max of chemically synthesized drug addicts (96.48%), while the unary regression equation established by a single step index has the highest prediction accuracy for the VO2max of natural plant-derived addicts (94.30%).Conclusion: The indirect measurement method could effectively estimate the VO2max of drug addicts, but different measurement methods have certain differences in the estimation accuracy of VO2max of different drug addicts. In the future, the physical characteristics of drug users can be fully considered, combined with more cutting-edge science and technology, to make the estimation accuracy of VO2max closer to the real level.

An unprecedented time series of 293 COSMO-SkyMed StripMap SAR images acquired in 2011–2020 is exploited to investigate land subsidence and vehicle traffic in Wuhan, China. Persistent Scatterer Interferometry using linear and non-linear deformation models suggests that the spatial and temporal evolution of subsidence relates with the dynamic urban development across the main city districts. Traffic patterns along bridges were captured by detecting vehicles based on their azimuth shift caused by their across-track motion, and identified by type based on their radar cross section and speed. The results of vehicle counting confirm an increasing number of vehicles over the last years, which is currently an urban challenge for Wuhan.

With the aim of finding an alternative ameliorative mechanism for 2-furoylmethyl-amino acid (2-FM-AA) formation in drying technology, this work was conducted. This was achieved by drying banana with relative humidity (RH) convective hot-air dryer at 60, 70 and 80 °C under RH (10% 20% and 30%) at 2.0 m/s air velocity. The results revealed that at every 10% increase in RH, a reduction between 13.4 and 29.4% of the 2-FM-AA was achieved. Based on statistical parameters such as coefficient of correlation (0.9104–0.9998), root mean square error (0.0176–0.3620) and reduced chi-square (1.5 × 10-4–0.1310), the first order model could satisfactorily predict 2-FM-AA formation. Furthermore, rate constants revealed the dependence of 2-FM-AA formation on RH and also demonstrated the critical role played by RH in reducing 2-FM-AA formation. The results also show that, higher temperatures were mainly responsible for 2-FM-AA formation and functional groups deformation; however this can be mitigated when drying is conducted under higher RH.

Wuhan is an important city in central China, with a rapid development that has led to increasingly serious land subsidence over the last decades. Most of the existing Interferometric Synthetic Aperture Radar (InSAR) subsidence monitoring studies in Wuhan are either short-term investigations—and thus can only detect this process within limited time periods—or combinations of different Synthetic Aperture Radar (SAR) datasets with temporal gaps in between. To overcome these constraints, we exploited nearly 300 high-resolution COSMO-SkyMed StripMap HIMAGE scenes acquired between 2012 and 2019 to monitor the long-term subsidence process affecting Wuhan and to reveal its spatiotemporal variations. The results from the Persistent Scatterer Interferometric SAR (PSInSAR) processing highlight several clearly observable subsidence zones. Three of them (i.e., Houhu, Xinrong, and Guanggu) are affected by serious subsidence rates and non-linear temporal behavior, and are investigated in this paper in more detail. The subsidence in Houhu is caused by soft soil consolidation and compression. Soil mechanics are therefore used to estimate when the subsidence is expected to finish and to calculate the degree of consolidation for each year. The COSMO-SkyMed PSInSAR results indicate that the area has entered the late stage of consolidation and compression and is gradually stabilizing. The subsidence curve found for the area around Xinrong shows that the construction of an underground tract of the subway Line 21 caused large-scale settlement in this area. The temporal granularity of the PSInSAR time series also allows precise detection of a rebound phase following a major flooding event in 2016. In the southern industrial park of Guanggu, newly detected subsidence was found. The combination of the subsidence curve with an optical time-series image analysis indicates that urban construction is the main trigger of deformation in this area. While this study unveils previously unknown characters of land subsidence in Wuhan and clarifies the relationship with the urban causative factors, it also proves the benefits of non-linear PSInSAR in the analysis of the temporal evolution of such processes in dynamic and expanding cities.

Background As a global infectious disease, Acquired Immune Deficiency Syndrome (AIDS) poses a serious threat to the safety and health of the society. In recent years, the proportion of drug addicts infected with HIV has been increased, and drug addicts became one of the main carriers of the spread of AIDS, which has attracted worldwide attention. It has been reported that physical activity has positive effects on improving the inhibitory function of drug addicts and reducing their drug craving, but the mechanism of the internal inhibition remains to be further explored. Method The drug addicts in an AIDS treatment center in Chongqing were investigated by means of a Physical Activity Rating Scale (PARS - 3), Internal Inhibition Scale and Drug Craving Scale, and a structural equation model was established. Results (1) There is no gender difference in the internal inhibition and drug craving of drug addicts with AIDS, and there are significant differences across the types and years of drug abuse. (2) The amount of physical activity in drug addicts with AIDS is positively correlated with the intrinsic inhibition, while the internal inhibition is negatively correlated with the drug craving, and the physical exercise amount is negatively correlated with the drug craving. The years of drug abuse were negatively correlated with internal inhibition and positively correlated with drug craving. (3) Internal inhibition plays a partly mediatory role between the physical activity amount and the craving for drugs, and internal inhibition plays a partly mediatory role between the number of years of drug abuse and the craving for drugs, which indicates that internal inhibition has a dual mediating effect. Conclusion Actively participate in physical activity, especially high-intensity physical activity, can effectively enhance the internal inhibition of drug addicts with AIDS and reduce their drug craving. Meanwhile, the difference in the drug-taking years among addicts should be paid attention to, and the physical activity prescription should be formulated according to the actual situation.

Background Maximal oxygen uptake (VO2max), a vital physiological indicator, has been widely used in many fields. In recent years, the measurement method of VO2max has been widely explored in various populations, but few studies have been conducted for women drug abusers. For the importance of VO2max in the formulation of aerobic exercise intensity for drug users, the present study estimated VO2max using the step test index combined with heart rate variability in women with drug use disorder. Methods Forty women methamphetamine (MA) users without cardiovascular disease and dyskinesia participated in a cardiopulmonary exercise test (CPX) and a 3-minute step test. Each of them performed a heart rate variability (HRV) monitoring test after the step test, and VO2max was estimated by step test index and HRV. Results (1) The step test index had a significant positive correlation with VO2max. The standard deviation of normal-to-normal interval (SDNN) had a significant positive correlation with VO2max and a significant positive correlation with the step test index; (2) the R-square values of the estimated VO2max by step test index and post-SDNN for overall MA users were 0.29 and 0.22, with an accuracy of 93.19 and 92.85%, respectively; (3) the R-square values of the estimated VO2max by step test index and post-SDNN in group I were 0.27 and 0.36, respectively, with an accuracy of 94.04 and 93.99%. The R-square value of the estimated VO2max by step test index in group II was 0.44, with an accuracy of 92.65%, however, post-SDNN cannot adequately estimate the VO2max in group II; and (4) there was no significant difference in VO2max obtained by CPX, step test index, or post-SDNN, regardless of overall or grouping variable analysis. Conclusion The 3-minute step test combined with HRV can estimate the VO2max of women MA users to a certain extent, but the size and the coverage of the sample size should be further considered. In the future, more methods, such as machine learning or artificial neural networks, should be used.

Digital light processing (DLP) is currently a cutting-edge technology for desktop projection optical engines. Due to the passive luminescence characteristics, the DLP projection engine needs a few specific illumination optical components for light collimation, homogenization, and color combination, together with a projection lens matching the DLP chip and magnifying the image. In this paper, we propose a design approach that first splits the DLP projection optical engine into individual components for separate design, and then integrates them into a whole system for further verification. For the first step, the collimating lens group is designed for light collection, and the dichroic mirrors are used to fold the light path based on tri-color LED light sources. For the second step, a fly-eye lens and the corresponding relay lens group are designed to achieve uniform illumination on the DMD chip. The third step is to optimize the projection lens group for high-resolution projection display. Based on the design and simulation, the optical efficiency is 63.4% and the uniformity reaches 94.9% on the projection screen. The modulation transfer function (MTF) of the projection lens is higher than 0.4 at 66 lines for the distance of 500 ∼ 1500 m m , and the distortion is lower than 1%. Simulation results show that the total luminous flux is estimated to reach 224.15 lm when the powers of tri-color LEDs are 21 W, 15.5 W, and 25 W, respectively. A projector prototype is built and tested for further verification, which provides a luminous flux of 220.43 lm and uniformity of 90.22%, respectively. The proposed design, demonstrated by both simulation and experiment, exhibits high feasibility and application potential in state-of-the-art commercial projector design.

Aims and Hypothesis: NEDD9 is highly expressed in gastric cancer and has a significant involvement in its pathogenesis. However, the mechanism behind hypoxia-promoted cancer cell migration and its regulation because of NEDD9 is still unknown. The aim of this study is to investigate the involvement of NEDD9 in gastric cancer cell migration under hypoxia and explore the underlying potential molecular mechanisms. Methods Cell motility was measured by wound healing and transwell assay. NEDD9 and MICAL1 expressions were examined by western blot analysis. Interaction between NEDD9 and MICAL1 was assessed by immunohistochemistry and co-immunoprecipitation assay, respectively. Cells were transfected with plasmids or siRNA to upregulate or downregulate the expression of NEDD9 and MICAL1. Rac1, Cdc42, and RhoA activation was assessed by pulldown assay. Results The mRNA and protein level of NEDD9 increased as a result of hypoxia in gastric cancer cell lines BGC-823 and SGC-7901 while decreased levels of NEDD9 caused reduced cell migratory potential in response to hypoxia. Hypoxia also caused the enhancement of MICAL1 expression. Furthermore, it was revealed that there is a positive correlation between NEDD9 and MICAL1 protein while hypoxia played role in increasing their interaction. Under hypoxic conditions, silencing of NEDD9 caused reduction in the stability of MICAL1 protein, while depletion of MICAL1 also inhibited the migration of NEDD9-overexpressing gastric cancer cells. In addition, silencing of NEDD9 or MICAL1 expression reversed the increased GTP forms of Rac1 and Cdc42 in hypoxic cells. However, only the upregulation of Rac1-GTP level was observed in gastric cancer cells that were already overexpressed by MICAL1. Conclusion In all, it is concluded that MICAL1 is regulated by NEDD9 that facilitates hypoxia-induced gastric cancer cell migration via Rac1-dependent manner.

Enhanced migration potential is a common characteristic of cancer cells induced by mechanisms that are incompletely defined. The present study was designed to investigate relationship of a new discovered cytoskeleton regulator MICAL‐L2 and the endogenous epidermal growth factor receptor (EGFR) signalling pathways in gastric cancer cell migration. Increased expression of MICAL‐L2 in gastric cancer cells up‐regulated EGFR protein level, accompanied by the increase of cell migration, whereas silencing MICAL‐L2 down‐regulated EGFR and inhibited cell migration. Expression of MICAL‐L2 was also shown positively correlated with the activation of HSP27/cytoskeleton and HSP27/β‐catenin signalling pathways that provide key mechanisms controlling cell migration. The up‐regulating effect of MICAL‐L2 on EGFR is mediated through a transcription‐independent mechanism that involves inhibiting EGFR protein degradation in lysosome. Further analysis indicated that Cdc42 activation contributed in maintaining the effect of MICAL‐L2 on EGFR stability. Furthermore analysis of clinic specimens revealed increased expression of MICAL‐L2 in carcinoma tissues and a positive correlation between MICAL‐L2 and EGFR expression levels. The above results indicate that MICAL‐L2 potentiates gastric cell migration via inhibiting EGFR degradation in lysosome via a Cdc42‐dependent manner that leads to the activation of EGFR/HSP27 signalling pathways.

Standard Bayesian filtering algorithms only work well when the statistical properties of system noises are exactly known. However, this assumption is not always plausible in real target tracking applications. In this paper, we present a new estimation approach named adaptive fifth-degree cubature information filter (AFCIF) for multi-sensor bearings-only tracking (BOT) under the condition that the process noise follows zero-mean Gaussian distribution with unknown covariance. The novel algorithm is based on the fifth-degree cubature Kalman filter and it is constructed within the information filtering framework. With a sensor selection strategy developed using observability theory and a recursive process noise covariance estimation procedure derived using the covariance matching principle, the proposed filtering algorithm demonstrates better estimation accuracy and filtering stability. Simulation results validate the superiority of the AFCIF.

The paper presents a novel nonlinear filtering algorithm called the Gaussian-sum ensemble Kalman filter (GSEnKF) for the bearings-only tracking problem. It extends the ensemble Kalman filter within a Gaussian-sum framework by using range-parameterized strategy. As a sequential Monte Carlo algorithm, it is not quite computationally demanding, whilst demonstrating better performance than conventional algorithms. Simulation results validate the effectiveness and robustness of the proposed algorithm.

Overexpression of heat shock protein 27(HSP27) in gastric cancer is correlated with poor clinical prognosis. Melatonin, an endogenous hormone, shows promise in gastric cancer therapy. However, there is limited study on the biological activity of HSP27 in response to melatonin treatment. In this study, we show an anti-proliferative action of melatonin on human gastric cancer cell lines BGC-823 and MGC-803. Biochemically, the inhibitory effect of melatonin is accompanied by the upregulation of HSP27 phosphorylation level. Transfection of gastric cancer cells with HSP27-specific siRNA effectively reduces HSP27 phosphorylation and potentiated melatonin-induced inhibitory effect on cell proliferation. The reduction of cyclin D1 in melatonin-treated cells is also aggravated by HSP27 depletion. Moreover, melatonin stimulation increases p38 phosphorylation. Pretreatment with p38 inhibitor SB203580 not only remarkably suppresses melatonin-induced HSP27 phosphorylation, but also augment the inhibitory effect of melatonin on cyclin D1 expression as well as cell proliferation. Taken together, our study indicates the protective pathway of p38/HSP27 against melatonin-induced inhibitory effect on gastric cancer cell proliferation, suggesting that combined with p38/HSP27 pathway inhibitor, the therapeutic efficacy of melatonin on gastric cancer may be improved.