Knowledge of induced fractures can help to evaluate the success of reservoir stimulation. Seismic P-waves through fracturing media can exhibit azimuthal variation in traveltime, amplitude, and thin-bed tuning, so amplitude variation with azimuth can be used to evaluate the hydraulic-fracturing-caused anisotropy. The Barnett Shale of the Fort Worth Basin was the first large-scale commercial shale gas play. We have analyzed two adjacent Barnett Shale seismic surveys: one acquired before hydraulic fracturing and the other acquired after hydraulic fracturing by more than (...) 400 wells. Although not a rigorous time-lapse experiment, comparison of AVAz anisotropy of these two surveys provided valuable insight into the possible effects of hydraulic fracturing. We found that in the survey acquired prior to hydraulic fracturing, AVAz anomalies were stronger and highly correlated with major structural lineaments measured by curvature. In contrast, AVAz anomalies in the survey acquired after hydraulic fracturing were weaker and compartmentalized by rather than correlated to the most-positive curvature lineaments. We found in five microseismic experiments within the survey that these ridge lineaments form fracture barriers. These findings suggested that future time-lapse experiments may be valuable in mapping the modified horizontal stress field to guide future drilling and in recognizing zones of bypassed pay. (shrink)

Autapse is a specific synapse connected to the neuron via close loop, and its functional adjusting is described by applying time-delayed feedback on the membrane potential of the neuron. This paper discussed the possible formation mechanism and biological function of autapse connection on neurons. We believe that the formation and growth of autapse connected to neuron can be associated with injury on axon and blocking in signal transmission; thus auxiliary loop is developed to form an autapse. When autapse is set (...) up, it can propagate the signals and change the modes of electrical activities under self-adaption. Based on the cable neuron model, the injury on axon is generated by poisoning and blocking in ion channels ; thus the conductance of ion channels are changed to form injury-associated defects. Furthermore, auxiliary loop with time delay is designed to restore and enhance signal propagation by setting different time delays and feedback gains. The numerical studies confirmed that appropriate time delay and feedback gain in electric or chemical autapse can help signal propagation across the blocked area. As a result, formation of autapse could be dependent on the injury of neuron and further enhances the self-adaption to external stimuli. (shrink)

Prestack seismic analysis provides information on rock properties, lithology, fluid content, and the orientation and intensity of anisotropy. However, such analysis demands high-quality seismic data. Unfortunately, noise is always present in seismic data even after careful processing. Noise in the prestack gathers may not only contaminate the seismic image, thereby lowering the quality of seismic interpretation, but it may also bias the seismic prestack inversion for rock properties, such as acoustic- and shear-impedance estimation. Common postmigration data conditioning includes running window (...) median and Radon filters that are applied to the flattened common reflection point gathers. We have combined filters across the offset and azimuth with edge-preserving filters along the structure to construct a true “5D” filter that preserves amplitude, thereby preconditioning the data for subsequent quantitative analysis. We have evaluated our workflow by applying it to a prestack seismic volume acquired over the Fort Worth Basin, TX. The inverted results from the noise-suppressed prestack gathers are more laterally continuous and have higher correlation with well logs when compared with those inverted from conventional time-migrated gathers. (shrink)

Legacy seismic surveys cover much of the midcontinent USA and Texas, with almost all 3D surveys acquired in the 1990s considered today to be low fold. Fortunately, recent advances in 5D interpolation have not only enhanced the quality of structural and stratigraphic images, but they have also improved the data sufficiently to allow more quantitative interpretation, such as impedance inversion. Although normal-moveout-corrected, common-midpoint-based 5D interpolation does an excellent job of amplitude balancing and the suppression of acquisition footprint, it appears to (...) misinterpolate undercorrected diffractions, thus smearing fault and stratigraphic edges. We described a least-squares migration-driven 5D interpolation workflow, in which data were interpolated by demigrating the current subsurface image to the missing offsets and azimuths. Such demigration accurately interpolates fault edges and other diffractors, thereby preserving lateral discontinuities, while suppressing footprint and balancing the amplitudes. We have applied this workflow to a highly aliased low-fold survey acquired in the early 1990s now of use in mapping the newly reinvigorated Mississippi Lime play. This workflow improves reflector continuity, preserves faults delineated by coherence, balances the amplitude, and provides improved well ties. (shrink)

Soft-sensor technology plays a vital role in tracking and monitoring the key production indicators of the grinding and classifying process. Least squares support vector machine, as a soft-sensor model with strong generalization ability, can be used to predict key production indicators in complex grinding processes. The traditional crossvalidation method cannot obtain the ideal structure parameters of LSSVM. In order to improve the prediction accuracy of LSSVM, a golden sine Harris Hawk optimization algorithm was proposed to optimize the structure parameters of (...) LSSVM models with linear kernel, sigmoid kernel, polynomial kernel, and radial basis kernel, and the influences of GSHHO algorithm on the prediction accuracy under these LSSVM models were studied. In order to deal with the problem that the prediction accuracy of the model decreases due to changes of industrial status, this paper adopts moving window strategy to adaptively revise the LSSVM, which greatly improves the prediction accuracy of the LSSVM. The prediction accuracy of the regularized extreme learning machine with MW strategy is higher than that of MW-LSSVM at some moments. Based on the training errors of LSSVM and RELM within the window, this paper proposes an adaptive hybrid soft-sensing model that switches between LSSVM and RELM. Compared with the previous MW-LSSVM, MW-neural network trained with extended Kalman filter, and MW-RELM, the prediction accuracy of the hybrid model is further improved. Simulation results show that the proposed hybrid adaptive soft-sensor model has good generalization ability and prediction accuracy. (shrink)

In capable person governing agricultural cooperatives, the internal governance is essential for cooperatives to achieve sustainable development. As an important mechanism of cooperative internal governance, relational governance is the focus of the current research in the field of cooperative internal governance. Based on the theory of organizational justice, relational embeddedness theory, and relational governance theory, this paper constructs the relationship between interactive justice, relational embeddedness, and governance performance based on fuzzy cognitive map and discusses the influence mechanism of interactive justice (...) on relational governance performance. Taking 245 members of 18 agricultural cooperatives as samples, this paper makes an empirical test by using the machine learning method. Through the analysis of the data, we find that interactive justice has a significant positive impact on the governance performance. Relational embeddedness also has a significant positive impact on the governance performance. And relational embeddedness plays an intermediary role in the positive impact of interactive justice on governance performance. To some extent, the research results broaden the relationship between interactive justice and relational governance performance and provide useful reference for cooperatives to strengthen internal governance and achieve sustainable growth. (shrink)

To systematically study the whole-aperture pore-structure characteristics of the marine-continental transitional shale facies in the Upper Palaeozoic Taiyuan and Shanxi Formations of the Qinshui Basin, we have collected a total of 11 samples for high-pressure mercury intrusion, low-pressure gas adsorption, nuclear magnetic resonance, and field-emission scanning electron microscopy with argon-ion polishing experiments to determine the pore morphology and distribution characteristics of shale samples in detail and to perform quantitative analyses. Then compared the pore-development characteristics of the Taiyuan Formation samples with (...) those of the Shanxi Formation to determine which is preferable. The experimental results indicate that the shale samples of the Qinshui Basin mainly develop three types of pores: organic pores, intergranular pores, and microfractures. High-pressure mercury intrusion and gas-adsorption experiments indicate that the pore-size distributions exhibit multiple peaks. The samples contained varying proportions of macropores, mesopores, and micropores, among which the former two are dominant, accounting for approximately 85% of the total pore volume, whereas micropores account for only 15%. However, mesopores and micropores dominate the specific surface area; between them, the micropores are much more prevalent, accounting for more than 99% of the total specific surface area. Macropores contribute less than 1% of the specific surface area and therefore can be neglected. The pore morphology resembles the slit type parallel platy pores with a ballpoint pen structure. The NMR [Formula: see text] spectra have multiple-peak values. In addition, the large difference between the curved areas before and after centrifugation indicates that the samples contain a large proportion of mesopores and macropores, which is consistent with the results presented above. The results demonstrate that the development of pores in the Taiyuan Formation is better than that in the Shanxi Formation. (shrink)

Oilfields have large amounts of old well-logging data, some of which were possibly lost or distorted for borehole situation, limiting the use of well- logging in formation evaluation. Applicating and developing machine learning algorithms provide the chance for completing, correcting, and generating well-logging curves. We took 50 wells in the Ordos Basin, a prolific hydrocarbon production basin, as an example to complete and generate well- loggings. We applied three algorithms, such as random forest, extreme gradient boosting, and deep neural network (...) algorithm, for well-logging curve completion experiments. We reconstructed and generated resistivity loggings such as deep investigate lateral resistivity log and medium investigate lateral resistivity log by using the spontaneous potential, gamma ray, acoustic log, and electrical resistivity log logging. After data preprocessing, we used training data sets and validation data sets, accounting for 90% and 10% of all database, respectively, to complete and generate well-logs. The results reveal that the XGBoost algorithm has a better effect on well-log completion if the parameters used are sufficiently optimized with experience, whereas the DNN algorithm has great advantages if large sufficient amounts of well-log data sets are available in the training sets. In this experiment, the accuracy of results by RF algorithm is better than those by XGBoost algorithm because the optimized parameters are difficult to guarantee without experience, and better than that, by DNN algorithms in which the input number of wells is less than 300 and may not be sufficient. In addition, RF algorithm has wider expansibility, higher efficiency, lower computation requirements, and better generalization ability. Our work provides a better understanding of the conditions and function of the application of different machine learning algorithms to well-logging completion and generation. (shrink)

安徽省社科规划项目 安徽省教育厅人文社科基金项目 安徽师范大学科研出版基金 安徽省省级重点学科——安徽师范大学马克思主义哲学学科建设基金资助项目安徽省高校人文社科重点研究基地——安徽师范大学马克思主义研究中心研究基金资助项目.

This study examined the effects of opportunity to learn or the content coverage in mathematics on student mathematics anxiety, problem-solving performance, and mathematics performance. The pathways examining the influences of OTL on student problem-solving performance and mathematics performance via mathematics anxiety were also tested. A sample of 1,676 students from Shanghai-China, and a sample of 1,511 students from the United States who participated in the Programme for International Student Assessment 2012 were used for the analyses. The results from multilevel models (...) and path models supported our hypotheses that OTL not only showed significant direct effects on student mathematics anxiety, problem-solving performance, and mathematics performance, but also presented indirect effects on student problem-solving performance and mathematics performance via mathematics anxiety in both Shanghai-China and United States, controlling for student gender, grade, and socioeconomic status. The practical implications of the current results were also discussed. (shrink)

The level of organizational self-esteem of employees, whether on the production line or as managers or directors of enterprises, does not only correlate with individual performance but has also become a key factor in determining the completion of team core tasks. Based on the theory of self-consistency, this study explores the correlation between negative workplace gossip and employees’ organizational self-esteem by revealing the intermediary role of workplace exclusion and poor-order atmosphere. A survey of 228 employees from enterprises in Shandong and (...) Shanghai showed that negative workplace gossip exerted a significant negative impact on employees’ organizational self-esteem, suggesting that negative workplace gossip reduces employees’ organizational self-esteem in the context of Chinese organizations. In addition, workplace exclusion exerted a complete intermediary effect between negative workplace gossip and employees’ organizational self-esteem, and poor-order atmosphere perception played a partial intermediary role. This study uncovers the black box that negative workplace gossip affects employees’ organizational self-esteem and has a strong enlightening significance for management practice. (shrink)

With the accelerating aging of the population and the worsening psychological conditions of older people, the traditional mode of family support for the elderly in China does not always meet the physical and psychological needs of the elderly, and more social support modes for the elderly are needed. Based on 3,513 valid questionnaires on the long-term care and protection needs of Chinese residents, this paper uses a logit regression model to analyze the factors influencing the willingness of the elderly to (...) choose nursing care. The results show that intergenerational family support for the elderly is a significant psychological driver on the willingness of the elderly to choose nursing care. Compared with the elderly living with family, empty nesters or older people living alone are more inclined to select nursing care when they have difficulties taking care of themselves. The physical health of the elderly affects their willingness to choose nursing care, and elderly individuals with more hospitalizations are less likely to select nursing care. In addition, elderly females who are relatively young, have a high level of education, have a high income, have a nursing home near the residence, and are already covered by medical insurance are more willing to choose nursing care. The results of this study are of great importance for improving the medical services and aging care services for the elderly and providing theoretical support for alleviating the psychological and social pressure brought by population aging. (shrink)

Porosity is considered as one of the most important indicators for the characterization of the comprehensive performance of thermal barrier coatings. In this study, the ultrasonic technique and the artificial neural network optimized with the genetic algorithm are combined to develop an intelligent method for automatic detection and accurate prediction of TBCs’s porosity. A series of physical models of plasma-sprayed ZrO2 coating are established with a thickness of 288 μm and porosity varying from 5.71% to 26.59%, and the ultrasonic reflection (...) coefficient amplitude spectrum is constructed based on the time-domain numerical simulation signal. The characteristic features f 1, f 2, A max, Δ A of the URCAS, which are highly dependent on porosity, are extracted as input data to train the GA_BPNN model for predicting the unknown porosity. The average error of the prediction results is 1.45%, which suggests that the proposed method can achieve accurate detection and quantitative characterization of the porosity of TBCs with complex pore morphology. (shrink)

Although servant leadership may be equipped to provide a leadership model that addresses the issues of the modern workforce, little literature is available regarding the relationship between servant leadership and employee brand-based equity. This study contends to address this gap for which data have been collected from the service industry under a cross-sectional research design by distributing 410 questionnaires among the participants, out of which 337 were received back. After discarding the partially filled and incomplete responses, the useable responses were (...) 314. Data were analyzed via the Smart PLS approach by applying the structural equation modeling technique. Results indicate that servant leadership directly increased the employee-based brand equity by the mediating role of interpersonal trust. However, this study has not established the moderating role of an ethical work climate. (shrink)

Following the successful cloning of genes for mostly rare genetic diseases in the early 1990s, there was a nearly universal enthusiasm that similar approaches could be employed to hunt down genes predisposing people to complex diseases. Around 1996, several well-funded international gene-hunting teams, enticed by the low cost of collecting biological samples and China’s enormous population, and ushered in by some well-connected Chinese intermediaries, came to China to hunt down disease susceptibility genes. This alarmed and, in some cases, enraged many (...) poorly funded Chinese scientists, who perceived them as formidable competitors. Some depicted foreign gene-hunters as greedy pilferers of the vast Chinese genetic gold mine, comparing it to the plundering of national treasures from China by invaders in the past, and called upon the government and their fellow countrymen to rise up and protect China’s genetic gold mine. Media uproar ensued, proclaiming the imminent “gene war of the century.” This article chronicles the key events surrounding this “war” and its aftermath, exposes some inherent complexities in identifying susceptibility genes for complex diseases, highlights some issues obscured or completely overlooked in the passionate and patriotic rhetoric, and debunks some misconceptions embedded in this conflict. In addition, it argues that during the entire course of this “war,” the public’s interest went conspicuously unmentioned. Finally, it articulates several lessons that can be learned from this conflict, and outlines challenges facing human genetics researchers. (shrink)

Brittleness is an important evaluation parameter in shale fracturing. Current methods of brittleness evaluation can be classified into two categories: elastic parameter-based and mineral content-based methods. However, both categories neglect the effect of anisotropy on the brittleness index computation of shale resources. We have redefined a new BI by integrating failure criteria stress and anisotropy parameters estimated from seismic waves. According to the new definition, the BI at one analysis point varies with the incident angle of the seismic wave and (...) confining pressures. We applied the BIac method to laboratory-measured shale samples acquired from the Monterey Formation, Santa Maria Basin. We found that the delta parameter [Formula: see text] is more responsive to the BIac than the gamma [Formula: see text] and epsilon [Formula: see text] anisotropic parameters, and it indicates a good linear fit relationship with the BIac at different angles. The slope of the linear is variable with the angles, thus delta can be used to predict the BIac in the Monterey Formation, Santa Maria Basin. (shrink)

Multicast can improve network performance by eliminating unnecessary duplicated flows in the data center networks. Thus it can significantly save network bandwidth. However, the network multicast blocking may cause the retransmission of a large number of data packets and seriously influence the traffic efficiency in data center networks, especially in the fat-tree DCNs with multirooted tree structure. In this paper, we build a multicast blocking model and apply it to solve the problem of network blocking in the fat-tree DCNs. Furthermore, (...) we propose a novel multicast scheduling strategy. In the scheduling strategy, we select the uplink connecting to available core switch whose remaining bandwidth is close to and greater than the three times of bandwidth multicast requests so as to reduce the operation time of the proposed algorithm. Then the blocking probability of downlink in the next time-slot is calculated in multicast subnetwork by using Markov chains theory. With the obtained probability, we select the optimal downlink based on the available core switch. In addition, theoretical analysis shows that the multicast scheduling algorithm has close to zero network blocking probability as well as lower time complexity. Simulation results verify the effectiveness of our proposed multicast scheduling algorithm. (shrink)

Because shale gas content plays a very important role in the evaluation of gas shale potential, its calculation and prediction become obligatory. We used two predictive models, namely, the Langmuir and Ambrose models, to calculate the shale gas content. The parameters involved in these two models are calculated by various experiments and analytic methods, including indirect prediction, the isothermal adsorption test, X-ray diffraction analysis, total organic carbon measurement, pyrolysis, and porosity measurement. Then, a new calculation model that is applicable to (...) shales in the Kuqa Depression, Tarim Basin, is established. Further research on influential factors of gas content in well YN2 is implemented. The result indicates that the gas content of terrestrial shales is more influenced by TOC abundance than by the content of clay minerals and quartz. The main parameters in the new calculation model are the TOC, depth, porosity, and gas saturation. The Jurassic shale gas in well YN2 is speculated to be mainly adsorption gas, with a dominant proportion of 75%–90% in the total gas content. As the formation depth increases, the free-gas content rises continuously, whereas the adsorption gas content first increases and then approaches the equilibrium value or even tends to decrease slightly. Based on the foregoing results, the target layer, the Yengisar Formation, is predicted to possess an enormous amount of shale gas potential, with an average total gas content of [Formula: see text]. (shrink)

The relationship between investor attention and stock prices has been a topic of interest in economics. Previous studies have shown that the correlation relationship between the two changes with time. However, there are few studies to explore the time-varying evolution of the relationship, as well as the transmission characteristics under important cycles. Thus, this paper is dedicated to discover the dynamic transmission characteristics of the correlation between investor attention and stock price. We selected the typical stocks of China’s energy industry, (...) PetroChina and Sinopec, as the research objects, as they occupy a large market share and are representative. And the transaction data and attention data are used to build investor attention indicator. In order to reproduce the dynamic transmission process of correlation at different cycles, sliding time window and complex network are applied. The results show that PetroChina and Sinopec stocks have a weakly negative correlation between investor attention and stock price from 2017 to 2018. However, from the perspective of different cycles, the correlation has time-varying characteristics. As the cycle grows, the types of transmission patterns of the five consecutive days of correlation between the two become less, but the transmission intensity between the modes increases and the transition becomes more regular and inclined. In addition, by mining the important transmission modes and main transmission paths under important periods, we find that the series modes of uncorrelated or weakly positive correlation for five consecutive days dominate the transition of modes in the networks. Also, the closed loop formed by these two important modes and related modes is the main transmission path. These findings can reveal the rules of the typical stock market in China’s energy industry and help investors with different investment cycle preferences make sound decisions. (shrink)

This study aimed to develop and test the reliability and validity of a multi-item nurses’ presenteeism behaviour questionnaire. Study 1 administered the Nurse Presenteeism Questionnaire to 250 Chinese nurses. Study 2, surveyed 650 nurses with the NPQ, the Sickness Presenteeism Questionnaire, the Stanford Presenteeism Scale, the General Health Questionnaire, and the Emotional Exhaustion Scale using convenience sampling. After item analysis, the subjects were randomly divided into two groups to verify the questionnaire structure. Study 1 revealed the nurses’ core symptoms when (...) they go to work with illness, and the NPQ with 11 items was developed. Study 2’s item analysis revealed that 11 NPQ items had good discrimination and high homogeneity. Besides, the scale had good reliability and external criterion validity. Thus, the NPQ can be used to measure presenteeism behaviour in nursing. (shrink)

Traditional isothermal adsorption experiments often fail to accurately estimate the adsorption capacity of reservoirs with rapidly changing lithology. Temperature, pressure, and mineral composition can influence the adsorption capacity of shale reservoirs. We have examined the influence of these factors on the amount of gas adsorbed in samples from well Yu-88. Samples consist of marine-continental transitional coal-bearing strata from the Upper Paleozoic Shanxi-Taiyuan Formation of the Ordos Basin of China. Shales occur as frequently interbedded, thin, and single layers that exhibit large (...) cumulative thickness and rapid changes in mineral composition. Our experiments on samples B1 and B2 indicated that Langmuir constant [Formula: see text] varied inversely with temperature, but Langmuir pressure [Formula: see text] did not. The [Formula: see text] exhibits good correlation with illite as well as illite/smectite content but did not clearly correlate with the total organic carbon. The [Formula: see text] correlated positively with TOC and negatively with illite/smectite content. These relationships enabled modeling of [Formula: see text], [Formula: see text], and mineral composition. Novel step-by-step modeling methods of well logs generated optimized estimates for well-log parameters including mineral composition. According to the actual temperature of the reservoir, we corrected the Langmuir constant [Formula: see text]. We calculated a profile for the amount of gas adsorbed in shale intervals of well Yu-88. Comparisons with experimental values indicate relatively high reference values. (shrink)

This paper proposes a recognition methodology for key geometric errors using the feature extraction method and accuracy retentivity analysis and presents the approach of optimization compensation of the geometric error of a multiaxis machine tool. The universal kinematics relations of the multiaxis machine tool are first modelled mathematically based on screw theory. Then, the retentivity of geometric accuracy with respect to the geometric error is defined based on the mapping between the constitutive geometric errors and the time domain. The results (...) show that the variation in the spatial error vector is nonlinear while considering the operation time of the machine tool and the position of the motion axes. Based on this aspect, key factors are extracted that simultaneously consider the correlation, similarity, and sensitivity of the geometric error terms, and the results reveal that the effect of the position-independent geometric errors on the error vectors of the position and orientation is greater than that of the position-dependent geometric errors of the linear and rotary axes. Then, the fruit fly optimization algorithm is adopted to determine the compensation values through multiobjective tradeoffs between accuracy retentivity and fluctuation in the geometric errors. Finally, an experiment on a four-axis horizontal boring machine tool is used to validate the effectiveness of the proposed approach. The experimental results show that the variations in the precision of each test piece are lower than 25.0%, and the maximum variance in the detection indexes between the finished test pieces is 0.002 mm when the optimized parameters are used for error compensation. This method not only recognizes the key geometric errors but also compensates for the geometric error of the machine tool based on the accuracy retentivity analysis results. The results show that the proposed methodology can effectively enhance the machining accuracy. (shrink)

China’s soybean price fluctuates due to the current economic and trade frictions between China and the United States. Brazil and the United States are regarded as two oligarchs in China’s soybean import market. A dynamic price game model is established, and price elasticity parameters are estimated by using statistical data and Rotterdam model. The stability of Nash equilibrium point is discussed through bifurcation diagram, maximum Lyapunov exponent, evolutionary trajectory, and time series diagram. The influence of price adjustment speed on equilibrium (...) price is analyzed. The numerical simulation of price adjustment speed is carried out, which is compared with the actual situation of imported soybean price before and after the trade friction. The results show that the model constructed in this paper can reflect the changing trend of price and demand and predict the short-term import soybean prices of Brazil and the United States. The forecast accuracy of price fluctuation is high. The results provide model and theoretical reference for price game under trade disputes and provide methodological reference for forecasting the price of imported goods. (shrink)

Using data of 26 cities in China from 2004 to 2017, the green total factor productivity is investigated by the SMM-GML method. The corresponding empirical analysis is conducted with the DID model. This paper investigates the relation between low-carbon pilot policy and green total factor productivity and discusses the mediating effect of industrial structure and the number of R&D staff. First, we find that LCC has a significant effect on pilot cities’ GTFP. And, it also promotes GTFP via industrial structure. (...) Second, LCC can improve industrial structure optimization and realization, and industrial structure realization affects GTFP significantly, while optimization cannot. Third, LCC cannot attract more RDS, and RDS harms local GDFP because of talent misallocation. At last, the rate of GTFP presented different upward trends in the order of non-eastern cities and eastern cities. The effect of LCC on GTFP is significant in non-eastern cities, but not eastern ones, which clearly demonstrates the imbalanced development of the green economy. Therefore, the governments of eastern and non-eastern regions should adopt different measures based on local conditions in industrial structure transformation and recruitment and strengthen environmental regulations to make the effect of the low-carbon policy lasting and promote GTFP growth balance in all regions. (shrink)

With the rapid development of information technology in today’s society, the security of transmission and the storage capacity of hardware are increasingly required in the process of image transmission. Compressed sensing technology can achieve data sampling and compression at the rate far lower than that of the Nyquist sampling theorem and can effectively improve the efficiency of information transmission. Aiming at the problem of weak security of compressed sensing, this study combines the cryptographic characteristics of chaotic systems with compressed sensing (...) technology. In the actual research process, the existing image encryption technology needs to be applied to the hardware. This paper focuses on the combination of image encryption based on compressed sensing and digital logic circuits. We propose a novel technology of parallel image encryption based on a sequence generator. It uses a three-dimensional chaotic map with multiple stability to generate a measurement matrix. This study also analyzes the effectiveness, reliability, and security of the parallel encryption algorithm for source noise pollution with different distribution characteristics. Simulation results show that parallel encryption technology can effectively improve the efficiency of information transmission and greatly enhance its security through key space expansion. (shrink)

The lifetime prevalence of major depressive disorder in adolescents is reported to be as high as 20%; thus, MDD constitutes a significant social and public health burden. MDD is often associated with nonsuicidal self-injury behavior, but the contributing factors including cognitive function have not been investigated in detail. To this end, the present study evaluated cognitive impairment and psychosocial factors in associated with MDD with NSSI behavior. Eighteen and 21 drug-naïve patients with first-episode MDD with or without NSSI and 24 (...) healthy control subjects were enrolled in the study. The Hamilton Anxiety Scale, Hamilton Depression Scale, Adolescent Self-injury Questionnaire, Beck Scale for Suicide Ideation–Chinese Version, Shame Scale for Middle School Students, Sensation Seeking Scale and Childhood Trauma Questionnaire were used to assess depression-related behaviors, and event-related potentials were recorded as a measure of cognitive function. The latency of the N1, N2, P3a, P3b, and P50 components of ERPs at the Cz electrode point; P50 amplitude and P50 inhibition showed significant differences between the 3 groups. CTQ scores also differed across three groups, and the NSSI– and NSSI+ groups showed significant differences in scores on the Shame Scale for Middle School Students. Thus, cognitive function was impaired in adolescents with MDD with NSSI behavior, which was mainly manifested as memory decline, attention and executive function deficits, and low anti-interference ability. We also found that childhood abuse, lack of social support, and a sense of shame contributed to NSSI behavior. These findings provide insight into the risk factors for MDD with NSSI behavior, which can help mental health workers more effectively diagnose and treat these patients. (shrink)

This paper proposed a novel tactile-stimuli P300 paradigm for Brain-Computer Interface, which potentially targeted at people with less learning ability or difficulty in maintaining attention. The new paradigm using only two types of stimuli was designed, and different targets were distinguished by frequency and spatial information. The classification algorithm was developed by introducing filters for frequency bands selection and conducting optimization with common spatial pattern on the tactile evoked EEG signals. It features a combination of spatial and frequency information, with (...) the spatial information distinguishing the sites of stimuli and frequency information identifying target stimuli and disturbances. We investigated both electrical stimuli and vibration stimuli, in which only one target site was stimulated in each block. The results demonstrated an average accuracy of 94.88% for electrical stimuli and 95.21% for vibration stimuli, respectively. (shrink)