Good knowledge management is important for enterprises to maintain competitive advantage; however, the knowledge hiding behavior may hinder this process. Based on the conservation of resources and psychological ownership theories, using a chain intermediary model, this study investigates the effect of justice sensitivity on knowledge hiding through perceived time pressure and territoriality, and further tests the moderating role of territoriality. For the study, we collected 436 questionnaires from China through the Wenjuanxing Sample Service, of which 391 were valid. We then (...) conducted multiple regression analysis and employed the bootstrap method for our tests. The results show that victim sensitivity has a significant effect on perceived time pressure, territoriality, and knowledge hiding, and that a chain mediating effect of perceived time pressure and territoriality is established between justice sensitivity and knowledge hiding. Further, territoriality has a positive moderating effect on perceived time pressure and knowledge hiding, while the mediating effect of perceived time pressure on justice sensitivity and knowledge hiding is also moderated by territoriality. Further, the study offers important practical implications in that enterprises should not blindly pursue results by making employees work excessively overtime. And there should have rationalized regulations in organization to ensure justice. The management should pay close attention to the psychological problems of victim and perpetrator. Instead, enterprises should have a certain degree of control, offer rationales for overtime work, and give high wages to the employees to compensate for their time, thus making the employees feel the worthiness of their overtime work and reducing the probability of engaging in knowledge hiding behaviors. (shrink)

本书根据马克思主义的哲学原理,就价值观念、道德观念、知识观念、人才观念等展开论述,在传统文化背景下对以上诸观念进行历史地沉思,力图揭示观念文化与时代发展的内在联系,揭示社会发展中观念更新的历史必然性。 .

ObjectivesSeveral studies have examined the effects of repetitive transcranial magnetic stimulation (rTMS) on associative memory (AM) but findings were inconsistent. Here, we aimed to test whether twice-daily rTMS could significantly improve AM.MethodsIn this single-blind, sham-controlled experiment, 40 participants were randomized to receive twice-daily sham or real rTMS sessions for five consecutive days (a total of 16,000 pulses). The stimulation target in left inferior parietal lobule (IPL) exhibiting peak functional connectivity to the left hippocampus was individually defined for each participant. Participants (...) completed both a picture-cued word association task and Stroop test at baseline and 1 day after the final real or sham rTMS session. Effects of twice-daily rTMS on AM and Stroop test performance were compared using two-way repeated measures analysis of variance with main factors Group (real vs. sham) and Time (baseline vs. post-rTMS).ResultsThere was a significant Group × Time interaction effect. AM score was significantly enhanced in the twice-daily real group after rTMS, but this difference could not survive the post hoc analysis after multiple comparison correction. Further, AM improvement in the twice-daily real group was not superior to a previously reported once-daily rTMS group receiving 8,000 pulses. Then, we combined the twice- and once-daily real groups, and found a significant Group × Time interaction effect. Post hoc analysis indicated that the AM score was significantly enhanced in the real group after multiple comparisons correction.ConclusionOur prospective experiment did not show significant rTMS effect on AM, but this effect may become significant if more participants could be recruited as revealed by our retrospective analysis. (shrink)

Gender plays an important role in various aspects of second language acquisition, including lexicon learning. Many studies have suggested that compared to males, females are less likely to experience boredom, one of the frequently experienced deactivating negative emotions that may impair language learning. However, the contribution of boredom to gender-related differences in lexicon learning remains unclear. To address this question, here we conducted two experiments with a large sample of over 1,000 college students to explore the relationships between gender differences (...) in boredom and lexicon learning. In Experiment 1, a cohort of 527 participants completed the trait and state boredom scales as well as a novel lexicon learning task without awareness of the testing process. In Experiment 2, an independent cohort of 506 participants completed the same novel lexicon learning task with prior knowledge of the testing procedure. Results from both experiments consistently showed significant differences between female and male participants in the rate of forgetting words and the state boredom scores, with female participants performing better than male participants. Furthermore, differences in state boredom scores partially explained differences in the rate of forgetting words between female and male participants. These findings demonstrate a novel contribution of state boredom to gender differences in lexicon learning, which provides new insights into better language-learning ability in females. (shrink)

Early and accurate diagnosis of glaucoma is critical for avoiding human vision deterioration and preventing blindness. A deep-neural-network model has been developed for the diagnosis of glaucoma based on Heidelberg retina tomography, called “Seeking Common Features and Reserving Differences Net” to make full use of the HRT data. In this work, the proposed SCRD-Net model achieved an area under the curve of 94.0%. For the two HRT image modalities, the model sensitivities were 91.2% and 78.3% at specificities of 0.85 and (...) 0.95, respectively. These results demonstrate a significant improvement over earlier results. In addition, we visualized the network outputs to develop an interpretation of the learned mechanism for discriminating glaucoma and normal images. Thus, the SCRD-Net can be an effective diagnostic indicator of glaucoma during clinical screening. To facilitate SCRD-Net utilization by the scientific community, the code implementation will be made publicly available. (shrink)

Green finance plays a crucial bridge as an intermediary between finance and the environment, facilitating resource allocation. The disclosure of environmental information (EID) is vital for promoting sustainable economic development. This study utilizes panel data covering the period from 2012 to 2019, focusing on Chinese companies listed in high-polluting industries. The findings demonstrate that green finance policies have a significant positive impact on EID, while increased managerial power has a detrimental effect. However, green finance policies can mitigate the negative consequences (...) arising from moral hazard and adverse selection resulting from managerial power. They enhance the quality of EID by restricting long-term loan resources for polluting entities. The heterogeneity test reveals that the effectiveness of green finance policies in promoting EID varies across different regions of China. In non-state-owned companies, green finance policies are more effective in constraining managerial power. The moderating effect of green finance on managerial power is weakened by improvements in internal control. Green financing can offset the adverse impact of managerial power on EID when debt levels are high. Our research plays a crucial role in advancing micro-academic studies in the field of green finance. By strengthening internal controls for corporate managers and promoting EID policies, we provide essential support and guidance to decision-makers. (shrink)

The topology optimization of computer communication network is studied based on improved genetic algorithm, a network optimization design model based on the establishment of network reliability maximization under given cost constraints, and the corresponding improved GA is proposed. In this method, the corresponding computer communication network cost model and computer communication network reliability model are established through a specific project, and the genetic intelligence algorithm is used to solve the cost model and computer communication network reliability model, respectively. It has (...) been proved that GA can solve the complex problems of computer working environment better, which is 80% higher than the general algorithm, and can select the optimal scheme pertinently. (shrink)

BackgroundPsychological resilience may reduce the impact of psychological distress to some extent. We aimed to investigate the mental health status of the public during the outbreak of coronavirus disease 2019 and explore the level and related factors of anxiety and depression.MethodsFrom February 8 to March 9, 2020, 3,180 public completed the Zung’s Self-Rating Anxiety Scale for anxiety, Zung’s Self-Rating Depression Scale for depression, the Connor–Davidson resilience scale for psychological resilience, and the Simplified Coping Style Questionnaire for the attitudes and coping (...) styles.ResultsThe number of people with depressive symptoms was 1,303. The number of people with anxiety symptoms was 1,184. The depressed group and anxiety group had less education, more unmarried and younger age, as well as had significant different in SDS total score, SAS total score, CD-RISC total score, and SCSQ score. The binary logistic regression showed that female, strength, and the subscales of active coping style in SCSQ remained protective factors and passive coping style and higher SAS score were risk factors for depression. Optimism in CD-RISC was a protective factor, and passive coping styles and higher SDS score were risk factors for anxiety.LimitationsThis study adopted a cross-sectional design and used self-report questionnaires.ConclusionThe mental health of the public, especially females, the younger and less educational populations, and unmarried individuals, should be given more attention. Individuals with high level of mental resilience and active coping styles would have lower levels of anxiety and depression during the outbreak of COVID-19. (shrink)

Publications by Chinese researchers in scientific journals have dramatically increased over the past decade; however, academic misconduct also becomes more prevalent in the country. The aim of this prospective study was to understand the perceptions of Chinese biomedical researchers towards academic misconduct and the trend from 2010 to 2015. A questionnaire comprising 10 questions was designed and then validated by ten biomedical researchers in China. In the years 2010 and 2015, respectively, the questionnaire was sent as a survey to biomedical (...) researchers at teaching hospitals, universities, and medical institutes in mainland China. Data were analyzed by the Chi squared test, one-way analysis of variance with the Tukey post hoc test, or Spearman’s rank correlation method, where appropriate. The overall response rates in 2010 and 2015 were 4.5% and 5.5%, respectively. Data from 15 participants in 2010 were invalid, and analysis was thus performed for 1263 participants. Among the participants, 54.7% thought that academic misconduct was serious-to-extremely serious, and 71.2% believed that the Chinese authorities paid no or little attention to the academic misconduct. Moreover, 70.2 and 65.2% of participants considered that the punishment for academic misconduct at the authority and institution levels, respectively, was not appropriate or severe enough. Inappropriate authorship and plagiarism were the most common forms of academic misconduct. The most important factor underlying academic misconduct was the academic assessment system, as judged by 50.7% of the participants. Participants estimated that 40.1% of published scientific articles were associated with some form of academic misconduct. Their perceptions towards academic misconduct had not significantly changed over the 5 years. Reform of the academic assessment system should be the fundamental approach to tackling this problem in China. (shrink)

The recent rapid development of information technology, such as sensing technology, communications technology, and database, allows us to use simulation experiments for analyzing serious accidents caused by hazardous chemicals. Due to the toxicity and diffusion of hazardous chemicals, these accidents often lead to not only severe consequences and economic losses, but also traffic jams at the same time. Emergency evacuation after hazardous chemical accidents is an effective means to reduce the loss of life and property and to smoothly resume the (...) transport network as soon as possible. This paper considers the dynamic changes of the hazardous chemicals’ concentration after their leakage and simulates the diffusion process. Based on the characteristics of emergency evacuation of hazardous chemical accidents, we build a mixed-integer programming model and design a heuristic algorithm using network optimization and diffusion simulation. We then verify the validity and feasibility of the algorithm using Jinan, China, as a computational example. In the end, we compare the results from different scenarios to explore the key factors affecting the effectiveness of the evacuation process. (shrink)

It was meaningful to predict the customers' decision-making behavior in the field of market. However, due to individual differences and complex, non-linear natures of the electroencephalogram signals, it was hard to classify the EEG signals and to predict customers' decisions by using traditional classification methods. To solve the aforementioned problems, a recurrent t-distributed stochastic neighbor embedding neural network was proposed in current study to classify the EEG signals in the designed brand extension paradigm and to predict the participants' decisions. The (...) recurrent t-SNE neural network contained two steps. In the first step, t-SNE algorithm was performed to extract features from EEG signals. Second, a recurrent neural network with long short-term memory layer, fully connected layer, and SoftMax layer was established to train the features, classify the EEG signals, as well as predict the cognitive performance. The proposed network could give a good prediction with accuracy around 87%. Its superior in prediction accuracy as compared to a recurrent principal component analysis network, a recurrent independent component correlation algorithm [independent component analysis ] network, a t-SNE support vector machine network, a t-SNE back propagation neural network, a deep LSTM neural network, and a convolutional neural network were also demonstrated. Moreover, the performance of the proposed network with different activated channels were also investigated and compared. The results showed that the proposed network could make a relatively good prediction with only 16 channels. The proposed network would become a potentially useful tool to help a company in making marketing decisions and to help uncover the neural mechanisms behind individuals' decision-making behavior with low cost and high efficiency. (shrink)

Compared with the large number of studies on reading of children with hearing loss in alphabetic languages, there are only a very limited number of studies on reading of Chinese-speaking children with HL. It remains unclear how phonological, orthographic, and semantic skills contribute to reading fluency of Chinese school-age children with HL. The present study explored this issue by examining the performances of children with HL on reading fluency and three linguistic skills compared with matched controls with normal hearing. Specifically, (...) twenty-eight children with HL and 28 chronological-age-matched children with NH were tested on word/sentence reading fluency, phonological awareness which was composed of onset/vowel/lexical tone awareness, orthographic knowledge, and semantic competence which comprised animal word identification, pseudo-homophone detection, and word segmentation. Results showed that children with HL lagged behind their peers with NH in WRF/SRF and most of the phonological, orthographic, and semantic subskills except onset awareness and pseudo-homophone detection. Furthermore, the significant contributors to WRF differed between the two groups with PA being the significant contributor in the children with NH while OK being the significant contributor in the children with HL. However, the significant contributor to SRF did not differ between the two groups with SC being the only significant contributor. These results revealed not only between-group differences but also similarities in the relative contributions of PA, OK, and SC to reading fluency at both word and sentence levels, which has practical implications for developing better training programs to improve reading for children with HL. (shrink)

ObjectiveTo investigate the instant impact of hemodialysis on the cerebral morphological measurements of patients with end-stage renal disease.Materials and methodsTwenty-five patients undergoing maintenance HD and twenty-eight age-, sex-, and education-matched healthy control were included. The HD group and HC group had 3D high-resolution structural magnetic resonance imaging scans twice and once, respectively. Both groups underwent neuropsychologic tests. The morphological measurements of structural MRI were measured using CAT12 and these measures were compared among three groups. The relationship between morphological measures and (...) clinical parameters and neuropsychological tests were investigated through multiple regression analysis.ResultsCompared to the HC group, the cortical thickness before HD significantly decreased in the bilateral temporal lobe and significantly decreased in the left superior temporal gyrus after HD. The cortical thickness significantly increased in the bilateral temporal lobe, frontal lobe and occipital lobe after HD compared to before HD. The sulcus depth in the bilateral insula, frontal lobe, and parietal lobe after HD significantly increased compared to before HD. No significant differences in sulcus depth between HD and HC were detected. After HD, the cortical thickness of the right parsopercularis was positively correlated with the number connection test-A. Cortical thickness in multiple regions were positively correlated with blood flow velocity and cortical thickness in the left parahippocampal gyrus was negatively correlated with ultrafiltration volume. Patients showed better performance in the digit symbol test and line tracing test after HD compared to before HD, but there were no significant differences in the comparison of neuropsychologic tests between patients and HC.ConclusionThe instant morphological changes were captured during a single hemodialysis in HD patients. There was an association between these instant changes in the brain and clinical parameters and neuropsychologic tests. This work implied the instant impact of a single hemodialysis impact on the brain in HD patients. (shrink)

A sector is a basic unit of airspace whose operation is managed by air traffic controllers. The operation complexity of a sector plays an important role in air traffic management system, such as airspace reconfiguration, air traffic flow management, and allocation of air traffic controller resources. Therefore, accurate evaluation of the sector operation complexity is crucial. Considering there are numerous factors that can influence SOC, researchers have proposed several machine learning methods recently to evaluate SOC by mining the relationship between (...) factors and complexity. However, existing studies rely on hand-crafted factors, which are computationally difficult, specialized background required, and may limit the evaluation performance of the model. To overcome these problems, this paper for the first time proposes an end-to-end SOC learning framework based on deep convolutional neural network specifically for free of hand-crafted factors environment. A new data representation, i.e., multichannel traffic scenario image, is proposed to represent the overall air traffic scenario. A MTSI is generated by splitting the airspace into a two-dimension grid map and filled with navigation information. Motivated by the applications of deep learning network, the specific CNN model is introduced to automatically extract high-level traffic features from MTSIs and learn the SOC pattern. Thus, the model input is determined by combining multiple image channels composed of air traffic information, which are used to describe the traffic scenario. The model output is SOC levels for the target sector. The experimental results using a real dataset from the Guangzhou airspace sector in China show that our model can effectively extract traffic complexity information from MTSIs and achieve promising performance than traditional machine learning methods. In practice, our work can be flexibly and conveniently applied to SOC evaluation without the additional calculation of hand-crafted factors. (shrink)

Ultra-short-term wind speed prediction can assist the operation and scheduling of wind turbines in the short term and further reduce the adverse effects of wind power integration. However, as wind is irregular, nonlinear, and nonstationary, to accurately predict wind speed is a difficult task. To this end, researchers have made many attempts; however, they often use only point forecasting or interval forecasting, resulting in imperfect prediction results. Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing (...) strategy, a novel optimization model, and multiple prediction algorithms. This combined forecasting system can overcome the inherent disadvantages of the traditional forecasting methods and further improve the prediction performance. To test the effectiveness of the forecasting system, the 10-min and one-hour wind speed sequences from the Sotavento wind farm in Spain were applied for conducting comparison experiments. The results of both the interval forecasting and point forecasting indicated that, in terms of the forecasting capability and stability, the proposed system was better than the compared models. Therefore, because of the minimum prediction error and excellent generalization ability, we consider this forecasting system to be an effective tool to assist smart grid programming. (shrink)

Objective: Cognitive impairment is a common neurological complication in patients with end-stage renal disease undergoing maintenance hemodialysis. Brain network analysis based on graph theory is a promising tool for studying CI. Therefore, the purpose of this study was to analyze the changes of functional brain networks in patients on MHD with and without CI by using graph theory and further explore the underlying neuropathological mechanism of CI in these patients.Methods: A total of 39 patients on MHD and 25 healthy controls (...) matched for age, sex, and years of education were enrolled in the study. Resting-state functional magnetic resonance imaging and T1-weighted high-resolution anatomical data were obtained, and functional brain networks for each subject were constructed. The brain network parameters at the global and regional levels were calculated, and a one-way analysis of covariance was used to compare the differences across the three groups. The associations between the changed graph-theory parameters and cognitive function scores in patients on MHD were evaluated using Spearman correlation analysis.Results: Compared with HCs, the global parameters [sigma, gamma, and local efficiency ] in both patient groups decreased significantly. The clustering coefficient in patients with CI was significantly lower than that in the other two groups. The regional parameters were significantly lower in the right superior frontal gyrus, dorsolateral and gyrus rectus of patients with CI than those of patients without CI; however the nodal local efficiency in the left amygdala was significantly increased. The global Cp and regional parameters in the three brain regions were significantly correlated with the cognitive function scores.Conclusion: This study confirmed that the topology of the functional brain network was disrupted in patients on MHD with and without CI and the disruption of brain network was more severe in patients with CI. The abnormal brain network parameters are closely related to cognitive function in patients on MHD. (shrink)

Indirectness is often used in our daily communication as a major communicative skill to keep a harmonious interpersonal relationship. From an Asian perspective, this paper is to discuss the various motives of indirectness, such as: politeness, self-protection, humor, rejection or denial, etc.

Previous work has shown that children with dyslexia are impaired in speech recognition in adverse listening conditions. Our study further examined how semantic context and fundamental frequency contours contribute to word recognition against interfering speech in dyslexic and non-dyslexic children. Thirty-two children with dyslexia and 35 chronological-age-matched control children were tested on the recognition of words in normal sentences versus wordlist sentences with natural versus flat F0 contours against single-talker interference. The dyslexic children had overall poorer recognition performance than non-dyslexic (...) children. Furthermore, semantic context differentially modulated the effect of F0 contours on the recognition performances of the two groups. Specifically, compared with flat F0 contours, natural F0 contours increased the recognition accuracy of dyslexic children less than non-dyslexic children in the wordlist condition. By contrast, natural F0 contours increased the recognition accuracy of both groups to a similar extent in the sentence condition. These results indicate that access to semantic context improves the effect of natural F0 contours on word recognition in adverse listening conditions by dyslexic children who are more impaired in the use of natural F0 contours during isolated and unrelated word recognition. Our findings have practical implications for communication with dyslexic children when listening conditions are unfavorable. (shrink)

Background: Upper limb functional exercise has a positive effect on promoting the rehabilitation of upper limb function. However, little is known, about what drives postoperative patients to engage in and even maintain the advised exercises. This study integrated the health action process approach and the theory of planned behavior theory to investigate the psychosocial determinants on the initiation and maintenance of ULFE in breast cancer patients. In addition, this study also tests key hypotheses relating to reasoned and implicit pathways to (...) ULFE and its maintenance among postoperative patients with breast cancer.Methods: Purposive sampling was used to recruit patients from two breast cancer wards in a provincial hospital in Jiangsu, China. Patients completed self-reported questionnaire about constructs from integrated theories concerning ULFE at an initial time point : task self-efficacy, positive outcome expectations, negative outcome expectations, risk perception, attitude behavior, subjective norm, perceived behavioral control, behavioral intention, and ULFE-in hospital. Three months later, patients self-reported: maintenance self-efficacy, action planning, coping planning, recovery self-efficacy, and ULFE-maintenance.Results: The model has a good fit. For behavioral intention of ULFE, subjective norm and perceived behavioral control were positively directly related to behavioral intention. Regarding the initiation of ULFE, perceived behavioral control and behavioral intention had a direct positive relation to ULFE-IH. In the maintenance of ULFE, action planning, coping planning, maintenance self-efficacy, and recovery self-efficacy all had significant positive relation on ULFE-M. In addition, maintenance self-efficacy had a significant positive association on action planning, coping planning, and recovery self-efficacy. Coping planning was significantly predicted by behavioral intention. Additionally, behavioral intention is a mediator of subjective norm and perceived behavioral control to ULFE-IH. Action planning, coping planning, and recovery self-efficacy are mediators of maintaining self-efficacy to ULFE-M.Conclusions: This study presents the first attempt to integrate the health behavior model in ULFE in postoperative patients with breast cancer. The study has shown that the HAPA-TPB integrated model has good applicability and effectiveness to explain and predict ULFE initiation and maintenance. Future work can be considered to develop appropriate intervention strategies based on this integrated behavioral theory. (shrink)

ObjectiveTwo subregions of the dorsolateral prefrontal cortex have been identified as effective repetitive transcranial magnetic stimulation targets for the “anxiosomatic” and “dysphoric” symptoms, respectively. We aimed to develop a convenient approach to locate these targets on the scalp.Materials and methodsIn a discovery experiment, the two personalized targets were precisely identified on 24 subjects using a neuronavigation system. Then, a localized approach was developed based on individual scalp landmarks. This “landmark-based approach” was replicated and validated in an independent cohort. Reliability of (...) the approach was tested by calculating the correlation of both the inter-rater and intra-rater results. Validity was tested by comparing the mean distance between the personalized and landmark-based targets to the TMS spatial resolution. We further conducted a total of 24 sham rTMS sessions to estimate the misplacement between the coil center and target during a 10-min stimulation without neuronavigation.ResultsThe parameters of the “landmark-based approach” in the discovery experiment were replicated well in an independent cohort. Using discovery parameters, we successfully identified the symptom-specific targets in the independent cohort. Specifically, the mean distance between the personalized and landmark-based targets on the cortex was not significantly larger than 5 mm. However, the personalized and landmark-based targets distance exceeded 5 mm in more than 50% of subjects. During the 10-min sham rTMS session, the average coil misplacement was significantly larger than 5 mm.ConclusionThe “landmark-based approach” can conveniently and reliably locate the two symptom-specific targets at group level. However, the accuracy was highly varied at individual level and further improvement is needed. (shrink)

Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients (...) with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. (shrink)

This article mitigates the challenges of previously reported literature by reducing the operating cost and improving the performance of network. A genetic algorithm-based tabu search methodology is proposed to solve the link capacity and traffic allocation problem in a computer communication network. An efficient modern super-heuristic search method is used to influence the fixed cost, delay cost, and variable cost of a link on the total operating cost in the computer communication network are discussed. The article analyses a large number (...) of computer simulation results to verify the effectiveness of the tabu search algorithm for CFA problems and also improves the quality of solutions significantly compared with traditional Lagrange relaxation and subgradient optimization algorithms. The experimental results show that with the increase of the weighted coefficient of variable cost, the proportion of variable cost in the total cost increases from 10 to 35%. The growth is relatively slow, and the fixed cost is still the main component. In addition, due to the increase in the variable cost, the tabu search algorithm will also choose the link with large luxury to reduce the variable cost, which makes the fixed cost slightly increase, while the network delay cost and average delay slightly decrease. The proposed method, when compared with the genetic algorithm, has more advantages for large-scale or heavy-load networks. (shrink)

Electroacupuncture (EA) and electroconvulsive therapy (ECT) are often used in the management of schizophrenia. This study sought to determine whether additional EA and ECT could augment antipsychotic response and reduce related side effects. In this retrospective controlled study, 287 hospitalized schizophrenic patients who received antipsychotics (controls, n = 50) alone or combined with EA (n = 101), ECT (n = 55) or both (EA+ECT, n = 81) were identified. EA and ECT were conducted for 5 and 3 sessions per week, (...) respectively, with a maximum of 12 sessions for ECT during hospitalization. The Scale for the Assessment of Positive Symptoms (SAPS) and Scale for the Assessment of Negative Symptoms (SANS) were used to assess the severity of psychotic symptoms. Clinical response on SAPS and SANS, weight gain, and adverse events were compared. Survival analysis revealed that the ECT and EA+ECT groups had markedly greater clinical response rate than controls on SAPS [72.7% and 90.1% vs. 64.0%; relative risk (RR), 1.974 and 2.628, respectively, P ≤ 0.004] and on SANS (67.3% and 70.4% vs. 42.0%; RR, 1.951 and 2.009, respectively, P ≤ 0.015). A significantly greater response rate on SANS than controls was also observed in the EA group (64.4% versus 42.0%; RR = 1.938, P = 0.008). EA-containing regimens remarkably reduced weight gain and incidences of headache, insomnia, dry mouth, and electrocardiographic abnormalities. These results suggest that EA and ECT can serve as additional treatment for enhancing antipsychotic response and reduce the side effects in hospitalized patients with schizophrenia. (shrink)

本书收30多篇文章,共分6部分:“中西哲学会通篇”、“审美意识新论篇”、“语言的哲学思考篇”、“人生境界解析篇”、“杂感琐谈篇”和“学术自述篇”。.

Chinese students’ outstanding performance in several rounds of PISA tests has attracted extensive attention on Chinese teacher professional development practices and system. The school-based teachi...

The time-scale dynamic equations play an important role in modeling complex dynamical processes. In this paper, the Mei symmetry and new conserved quantities of time-scale Birkhoff’s equations are studied. The definition and criterion of the Mei symmetry of the Birkhoffian system on time scales are given. The conditions and forms of new conserved quantities which are found from the Mei symmetry of the system are derived. As a special case, the Mei symmetry of time-scale Hamilton canonical equations is discussed and (...) new conserved quantities for the Hamiltonian system on time scales are derived. Two examples are given to illustrate the application of results. (shrink)

本书对处于社会转型期中国的审美文化特性以及其中出现的种种让人困惑的问题,从不同角度、不同层面作了阐述。.

Anxious major depressive disorder is a common subtype of major depressive disorder; however, its unique neural mechanism is not well-understood currently. Using multimodal MRI data, this study examined common and specific alterations of amygdala subregions between patients with and without anxiety. No alterations were observed in the gray matter volume or intra-region functional integration in either patient group. Compared with the controls, both patient groups showed decreased functional connectivity between the left superficial amygdala and the left putamen, and between the (...) right superficial amygdala and the bilateral anterior cingulate cortex and medial orbitofrontal cortex, while only patients with anxiety exhibited decreased activity in the bilateral laterobasal and superficial amygdala. Moreover, the decreased activity correlated negatively with the Hamilton depression scale scores in the patients with anxiety. These findings provided insights into the pathophysiologic processes of anxious major depressive disorder and may help to develop new and effective treatment programs. (shrink)