BackgroundThe Basal ganglia (BG) played a crucial role in the brain-level mechanisms of chronic pain disorders. However, the functional changes of BG in chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are still poorly understood. This study investigated the BG subregions’ resting-state functional connectivity (rs-FC) in CP/CPPS patients compared with healthy controls.MethodsTwenty eight patients with CP/CPPS and 28 age- and education-matched healthy males underwent clinical measurements and 3T brain MR imaging, including T1-weighted structural images and resting-state functional imaging. The data were analyzed (...) by the seeded-based rs-FC analysis. Then, a machine learning method was applied to assess the feasibility of detecting CP/CPPS patients through the changed rs-FC.ResultsCompared with healthy males, patients presented decreased rs-FC between the BG subregions and right middle cingulate cortex, and correlated with pain (r = 0.51, p-uncorrected = 0.005) and urinary symptoms (r = –0.4, p-uncorrected = 0.034). The left superior temporal gyrus and right supramarginal gyrus showed decreased rs-FC with the BG subregions as well. The area under the receiver operating characteristic curve of 0.943 (accuracy = 80%, F1-score = 80.6%) was achieved for the classification of CP/CPPS patients and healthy males with support vector machine (SVM) based on the changed rs-FC.ConclusionThese findings provide evidence of altered BG subregions’ rs-FC in CP/CPPS, which may contribute to our understanding of the BG’s role in CP/CPPS. (shrink)

During the COVID-19 pandemic, online education has become an important approach to learning in the information era and an important research topic in the field of educational technology as well as that of education in general. Teacher–student interaction in online education is an important factor affecting students’ learning performance. This study employed a questionnaire survey to explore the influence of teacher–student interaction on learning effects in online education as well as the mediating role of psychological atmosphere and learning engagement. The (...) study involved 398 college students studying at Chinese universities as the research object. Participants filled out a self-report questionnaire. The study found that the level of teacher–student interaction positively affected students’ learning effects. The psychological atmosphere mediated the positive effect of the level of teacher–student interaction on learning effects with mediating effect value of 0.1248. Learning engagement mediated the positive effect of teacher–student interaction on learning effects with a mediating effect value of 0.1539. The psychological atmosphere and learning engagement play a chain-mediating role in the mechanism of teacher–student interaction affecting students’ learning effects; that is, teacher–student interaction promotes students’ learning engagement by creating a good psychological atmosphere, which, in turn, influences learning effects. The mediating effect value was 0.0403. The results indicate that teacher–student interaction not only directly affects students’ learning effects but also influences students’ learning effects through the mediating effect of the psychological atmosphere and learning engagement. (shrink)

Background and purpose Changes to deceased organ donation policy in the USA, including opt-out and priority systems, have been proposed to increase registration and donation rates. To study attitudes towards such policies, we surveyed healthcare students to assess support for opt-out and priority systems and reasons for support or opposition. Methods We investigated associations with supporting opt-out, including organ donation knowledge, altruism, trust in the healthcare system, prioritising autonomy and participants’ evaluation of the moral severity of incorrectly assuming consent in (...) opt-in systems or opt-out systems, by conducting an online survey among healthcare students at a large academic institution. Results Of 523 respondents, 86% supported opt-out, including 53% who strongly supported the policy. The most popular reason for supporting opt-out was the potential for increased donation rates, followed by convenience for those not registered but willing to donate. The most popular reason for opposing opt-out was the belief that presuming consent is morally wrong. Those strongly supporting opt-out viewed the opt-in error as more morally unacceptable, and had higher knowledge and altruism scores. Those opposing opt-out viewed the opt-out error as more unacceptable, and had higher autonomy scores. 48% of respondents supported priority within opt-in systems; 31% supported priority in opt-out. Conclusions There is strong support for opt-out organ donation among healthcare students, influenced by both practical and moral considerations. (shrink)

In order to manage the electricity consumption information of microgrid users, the reliability of electricity information collection is studied in this paper. The normal communication between the acquisition terminal and the smart meter is a key factor affecting the accurate collection of power information; it is the basis for ensuring the operation of the microgrid as well. In order to improve the reliability of the low power line communication between the acquisition terminal and smart meters, this article first uses the (...) static networking method to layer the smart meters and select relays from them and then select the optimal communication path based on integrating communication quality and relay forwarding number dynamically, which could avoid the signal conflict problem caused by simultaneous communication. Finally, by analyzing the influence of the time-varying power line channel on the smart meter communication, a method based on the integrated communication quality and the relay number to consider the time variability of low power line communication is proposed. Choosing the optimal path of the smart meters when the communication path is abnormal can not only establish a new communication path for communication in time, but also avoid communication failures caused by the time-varying channel. Through MATLAB simulation, the time-varying dynamic network of the power line channel is introduced in this paper, which improves the reliability of the smart meter communication and has certain guiding significance for the actual smart meter network construction in microgrid. (shrink)

ObjectivesThis study aims to systematically analyze the effects of mind–body exercises on post-traumatic stress disorder symptoms, depression, and anxiety in patients with PTSD. Furthermore, it intends to provide scientific evidence-based exercise prescriptions.MethodsChinese and English databases were used as data sources to search for studies on the effects of mind–body exercises on symptoms associated with patients with PTSD from January 1980 to November 2020. After a rigorous screening, 16 eligible randomized controlled trials were included in the meta-analysis.ResultsMind–body exercises exerted a significant (...) effect on PTSD symptoms [standard mean difference = −0.41, 95% confidence interval −0.64 to −0.19, p < 0.001], depression, and anxiety among patients with PTSD. Subgroup analysis demonstrated that 60–150 min per session for 8–16 weeks of mindfulness was more effective in improving symptoms in patients with PTSD under 45 years of age compared with other subgroups. For depression, 150–180 min of yoga exercises once per week was effective. For anxiety, the frequency, timing, duration, and type of mind–body exercises that are most effective in relieving anxiety in patients with PTSD cannot be determined at this time due to the limited number of eligible RCTs.ConclusionsMind–body exercises were found to be significantly effective in improving PTSD symptoms, depression, and anxiety in patients with PTSD. Therefore, they can be used as an adjunct to intervention for symptoms of patients with PTSD. However, this conclusion requires further confirmation through additional scientific and objective RCTs.Systematic Review Registration:Unique Identifier: INPLASY2020120072. (shrink)

Recent decades have witnessed the rapid evolution of robotic applications and their expansion into a variety of spheres with remarkable achievements. This article researches a crucial technique of robot manipulators referred to as visual servoing, which relies on the visual feedback to respond to the external information. In this regard, the visual servoing issue is tactfully transformed into a quadratic programming problem with equality and inequality constraints. Differing from the traditional methods, a gradient-based recurrent neural network for solving the visual (...) servoing issue is newly proposed in this article in the light of the gradient descent method. Then, the stability proof is presented in theory with the pixel error convergent exponentially to zero. Specifically speaking, the proposed method is able to impel the manipulator to approach the desired static point while maintaining physical constraints considered. After that, the feasibility and superiority of the proposed GRNN are verified by simulative experiments. Significantly, the proposed visual servo method can be leveraged to medical robots and rehabilitation robots to further assist doctors in treating patients remotely. (shrink)

From the perspective of the integrative model of organizational trust, this study proposes a multi-level model for whether, how, and when differentiated empowering leadership influences followers’ trust in leaders and their work outcomes. Drawing on a sample of 372 followers from 97 teams in China, it was found that the negative effect of differentiated empowering leadership on followers’ trust in leaders became salient when followers’ Chinese traditionality was low. Moreover, followers’ trust in leaders mediated the effect of differentiated empowering leadership (...) and Chinese traditionality on followers’ in-role performance, extra-role performance, and counterproductive work behaviors toward the organization. These findings have implications for managerial theory and practice in the domains of trust and differentiated empowering leadership. (shrink)

The Coronavirus disease pandemic of 2019 is a vast worldwide public health hazard, impacting people of all ages and socioeconomic statuses. Vaccination is one of the most effective methods of controlling a pandemic like COVID-19. This study aims to investigate the relationship between the number of vaccination injections and fear of COVID-19 and test whether beliefs benefit from vaccination COVID-19 mediate the effect of fear of COVID-19 on the number of vaccination injections. A total of 649 Vietnamese adults were enrolled (...) online to finish answering, including scales The Health Belief Model (HBM) and The Fear of COVID-19 (FCV-19S), consisting of 340 (52.4%) males and 309 (47.6%) females. The data were analyzed using variance, regression, and a simple mediation model. The total score of COVID-19 fear wasM= 22.26,SD= 5.49. Vietnamese fear of COVID-19 was at a medium level. Our results suggest that 18- to 20-year-olds are more fearful of COVID-19 than others. People who received the first dosage exhibited a greater fear of COVID-19 than those who received the second dose and were not inoculated. Additionally, the beliefs benefit of vaccination COVID-19 has a role in the relationship between the number of vaccination injections and fear of COVID-19. During the pandemic, adults in Vietnam are more afraid of COVID-19 than during prior outbreaks. Besides, the Vietnamese populace demonstrated a considerable demand for and high acceptability of the COVID-19 vaccine. The current study indicates that psychological counselors and therapists should counsel clients on the value of vaccination and address the fear of COVID-19 as public understanding of the benefits of vaccines increases. To further clarify the effect of this issue on the correlation between fear of COVID-19 and the number of vaccinations, the results of this study indicate that the existing vaccine communication factor for COVID-19 vaccination should be modified to increase confidence in the benefits of immunization. (shrink)

The strap-down inertial navigation system is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine. During the process of initial alignment, inaccurate or time-varying noise covariance matrices will significantly degrade the accuracy of the initial alignment of the shearer. To overcome the performance degradation of the existing initial alignment algorithm under complex underground environment, a novel adaptive filtering algorithm is proposed by the integration of the strong tracking Kalman filter and (...) the sequential filter for the initial alignment of the shearer with complex underground environment. Compared with the traditional multiple fading factor strong tracking Kalman filter method, the proposed MSTSKF algorithm integrates the advantage of strong tracking Kalman filter and sequential filter, and multiple fading factor and forgetting factor for east and north velocity measurement are designed in the algorithm, respectively, which can effectively weaken the coupling relationship between the different states and increase strong robustness against process uncertainties. The simulation and experiment results show that the proposed MSTSKF method has better initial alignment accuracy and robustness than existing strong tracking Kalman filter algorithm. (shrink)

This work explored the mediating effects of affective commitment on transformational leadership and job performance and job insecurity on transformational leadership and affective commitment. Meanwhile, the inter-relationships between the four verified the mediating effect of affective commitment, including job insecurity. The results were as follows: transformational leadership and job performance were positively related. Transformational leadership was proportional to an emotional commitment. The affective commitment had a positive impact on job performance. Transformational leadership indirectly positively affected job performance through the intermediary (...) effect of affective commitment. Transformational leadership regulated affective commitment through job insecurity. The more job security employees have, the higher the impact of transformational leadership on affective commitment; the lower the contrary. (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)

We clarify different definitions of the density matrix by proposing the use of different names, the full density matrix for a single-closed quantum system, the compressed density matrix for the averaged single molecule state from an ensemble of molecules, and the reduced density matrix for a part of an entangled quantum system, respectively. We show that ensembles with the same compressed density matrix can be physically distinguished by observing fluctuations of various observables. This is in contrast to a general belief (...) that ensembles with the same compressed density matrix are identical. Explicit expression for the fluctuation of an observable in a specified ensemble is given. We have discussed the nature of nuclear magnetic resonance quantum computing. We show that the conclusion that there is no quantum entanglement in the current nuclear magnetic resonance quantum computing experiment is based on the unjustified belief that ensembles having the same compressed density matrix are identical physically. Related issues in quantum communication are also discussed. (shrink)

ObjectiveTo investigate the short-term effect of music therapy combined with binaural frequency difference therapy on patients with consciousness disorder.Materials and methodsNinety patients with definite diagnosis of disorders of consciousness were selected. These patients were randomly divided into control group, experiment 1 group and experiment 2 group, with 30 patients in each group. The control group was treated with routine clinical treatment and rehabilitation. In experiment 1 group, music therapy was added to the control group. In experimental group 2, music therapy (...) combined with binaural α frequency difference therapy was added to the control group. All patients were assessed before and after 30 treatments. The assessment items included Glasgow Coma Scale, Coma Recovery Scale revised, electroencephalogram, upper somatosensory evoked potential, and brainstem auditory evoked potential.ResultsBefore treatment, there were no significant differences in GCS score, CRS-R score, USEP, BAEP, and EEG scores among the three groups. After 30 times of treatment, GCS score, CRS-R score, USEP, BAEP, and EEG scores in 3 groups were significantly higher than those before treatment. And the consciousness rate of experimental group 2 was better than experimental group 1, experimental group 1 was better than the control group and the difference was statistically significant.ConclusionMusic therapy combined with binaural α frequency difference therapy is more effective in stimulating DOC patients. (shrink)

In this paper, we aim to examine the indirect effects of moral leadership on unethical pro-organizational behavior (UPB). Drawing on Social Identity Theory, identification with supervisors (social identity) and taking responsibility (personal identity) were hypothesized as mediators linking moral leadership and UPB. In addition, we aim to investigate the moderating role of moral courage in the relationship between moral leadership and UPB. We conducted two studies with two distinct samples: one on a sample of 161 MBA students, and the other (...) on a sample of 205 enterprise employees in China. Data were collected through a self-reported questionnaire based on a two-wave research design and analyzed through Structural Equation Modeling. Results showed that moral leadership increased UPB through promoting identification with supervisors while reducing UPB via increasing taking responsibility. Additionally, the results also showed that moral courage moderated the mediating effects of identification with supervisors and taking responsibility upon the relationship between moral leadership and UPB. We contribute to the literature by demonstrating that moral leadership exerts its paradoxical effects on UPB indirectly through its impact on identification with supervisors and taking responsibility and therefore offers a better understanding of how and when moral leadership influences UPB. A number of managerial implications are also discussed. (shrink)

This study explores the dynamic feature of organizational citizenship behaviors under the condition of challenge stressors, as this has not been addressed by previous research. Combining the cybernetic theory of stress and social exchange theory, this study builds a dynamic computational model regarding the circular causality between challenge stressors and organizational citizenship behaviors. By conducting a series of simulation experiments, we validated and demonstrated important questions regarding organizational citizenship behaviors. Specifically, when both the initial value of challenge stressors and the (...) importance of challenge appraisal are higher, organizational citizenship behaviors tend to show a sharped inverted U shape at the early stage. When both the equilibrium level of job satisfaction and the initial value of challenge stressors are higher, organizational citizenship behaviors will show an inverted N shape over time. The number and frequency of assigned challenge tasks have an interactive effect on the accumulation of organizational citizenship behaviors within a period. Our theory contributes to identifying the dynamic relationship between challenge stressors and organizational citizenship behaviors. Findings from dynamic computational theory can offer suggestions for managers to encourage employees’ engagement in organizational citizenship behaviors. (shrink)

Memristor is the fourth basic electronic element discovered in addition to resistor, capacitor, and inductor. It is a nonlinear gadget with memory features which can be used for realizing chaotic, memory, neural network, and other similar circuits and systems. In this paper, a novel memristor-based fractional-order chaotic system is presented, and this chaotic system is taken as an example to analyze its dynamic characteristics. First, we used Adomian algorithm to solve the proposed fractional-order chaotic system and yield a chaotic phase (...) diagram. Then, we examined the Lyapunov exponent spectrum, bifurcation, SE complexity, and basin of attraction of this system. We used the resulting Lyapunov exponent to describe the state of the basin of attraction of this fractional-order chaotic system. As the local minimum point of Lyapunov exponential function is the stable point in phase space, when this stable point in phase space comes into the lowest region of the basin of attraction, the solution of the chaotic system is yielded. In the analysis, we yielded the solution of the system equation with the same method used to solve the local minimum of Lyapunov exponential function. Our system analysis also revealed the multistability of this system. (shrink)

Unethical pro-family behavior is prevalent in organizations and has adverse effects on organizations, but very few studies have examined the factors that lead to UPFB. We use a cognitive appraisal theoretical framework to argue that employees’ unethical pro-family behavior results from work and family conflicts are mediated by threat appraisal and moderated family collectivism orientation. Based on the questionnaire data of 496 full-time employees from two-time points, we found that WFC/FWC was positively correlated with UPFB where threat appraisal played a (...) mediating role in this relationship; Family collectivism orientation strengthens the threat appraisal-UPFB relationship and the mediation relationship between WFC/FWC and UPFB via threat appraisal. These findings offer an understanding of the theoretical and practical implications which could help organizations reduce UPFB. Finally, we discuss possible directions for future research. (shrink)

Green consumption values have been shown to motivate consumers to engage in green consumption practices. However, surprisingly little research has examined how green consumption values develop in young people. In the current study, we employed ecological socialization theory as a framework to investigate the process by which parents’ green consumption values shape similar values in their young adolescents. In Study 1, data from 722 Chinese families that included an early adolescent showed that both mothers’ and fathers’ green consumption values were (...) positively associated with early adolescents’ green consumption values, and this association was mediated by each parent’s environmentally responsible consumption behavior. Study 2 replicated the results of Study 1 using two waves of matched parent-adolescent data collected a month apart from another group of 477 Chinese families. Furthermore, Study 2 showed that the mediation process identified in Study 1 was evident only when there was a close parent–child relationship. These findings have implications for cultivating the green consumption values of today’s youth. The results also have heuristic value for future research on the ecological socialization and inter-generational transmission of pro-environmental values. (shrink)

Photovoltaic power forecasting can provide strong support for the safe operation of the power system. Existing forecasting methods are ineffective for grid scheduling decisions or risk analysis. The novel multicluster interval prediction method is proposed to consider the volatility and randomness of PV power output. First, this method utilizes the sparse autoencoder and Bayesian regularized NARX network for point forecasting of PV power. Second, density peak clustering improved by kernel Mahalanobis distance is applied to classify the dataset into multiple clusters, (...) including forecasting error and meteorological factors. Finally, the joint probability density is established by multivariate kernel density estimation to accomplish the PV power interval prediction. The proposed hybrid method is applied for the interval prediction of PV power at Yulara, Australia. Comparative research of point forecasting is implemented to evaluate the machine learning and deep learning methods, with the proposed SAE-BRNARX under four different periods. Results shows that the average values of nRMSE, MRE, nMAE, and R2 for the four periods are 4.45%, 0.90%, −0.15%, 3.39%, and 95.93%, respectively. Moreover, the results of interval prediction obtained by the other interval prediction approaches are compared with the proposed KMDDPC-MKDE. It shows that the average values of PICP, PINAW, ACE, and nMPICD for four periods are 93.93%, 9.50%, 3.93%, and 7.10% at 90% confidence level, respectively. Outcomes demonstrate that the proposed method can obtain more accuracy, a higher coverage rate, narrower average bandwidth, and a closer distance between the middle of interval and actual value than other methods. (shrink)

Improving the resilience of urban road networks suffering from various disruptions has been a central focus for urban emergence management. However, to date the effective methods which may mitigate the negative impacts caused by the disruptions, such as road accidents and natural disasters, on urban road networks is highly insufficient. This study proposes a novel adaptive signal control strategy based on a doubly dynamic learning framework, which consists of deep reinforcement learning and day-to-day traffic dynamic learning, to improve the network (...) performance by adjusting red/green time split. In this study, red time split is regarded as extra traffic flow to discourage drivers to use affected roads, so as to reduce congestion and improve the resilience when urban road networks are subject to different levels of disruptions. In addition, we utilize the convolution neural network as Q-network to approximate Q values, link flow distribution and link capacity are regarded as the state space, and actions are denoted as red/green time split. A small network is utilized as a numerical example, and a fixed time signal control and other two adaptive signal controls are employed for the comparisons with the proposed one. The results show that the proposed adaptive signal control based on deep reinforcement learning can achieve better resilience in most of the cases, particularly in the scenarios of moderate and severe disruptions. This study may shed light on the advantages of the proposed adaptive signal control dealing with major emergencies compared to others. (shrink)

The hippocampus is known to be comprised of several subfields, but the developmental trajectories of these subfields are under debate. In this study, we analyzed magnetic resonance imaging data from a cross-sectional sample using an automated segmentation tool to delineate the development of the hippocampal subregions from 6 to 26 years of age. We also examined whether gender and hemispheric differences influence the development of these subregions. For the whole hippocampus, the trajectory of development was observed to be an inverse-u. (...) A significant increase in volume with age was found for most of the subregions, except for the L/R-parasubiculum, L/R-fimbria, and L-HATA. Gender-related differences were also found in the development of most subregions, especially for the hippocampal tail, CA1, molecular layer HP, GC-DG, CA3, and CA4, which showed a consistent increase in females and an early increase followed by a decrease in males. A comparison of the average volumes showed that the right whole hippocampus was significantly larger, along with the R-presubiculum, R-hippocampal-fissure, L/R-CA1, and L/R-molecular layer HP in males in comparison to females. Additionally, the average volume of the right hemisphere was shown to be significantly larger for the hippocampal tail, CA1, molecular layer HP, GC-DG, CA3, and CA4. However, for the presubiculum, parasubiculum, and fimbria, the left side was shown to be larger. In conclusion, the hippocampal subregions appear to develop in various ways from childhood to adulthood, with both gender and hemispheric differences affecting their development. (shrink)

Financial development is often considered one of the main drivers promoting household consumption. As a form of financial development, whether digital financial inclusion can promote household consumption has been a concern for researchers and policymakers. Considering geographical connectivity characteristics, we examine the effects of digital financial inclusion on household consumption by applying spatial econometric models and using data from 31 provinces in China from 2013 to 2018. The impact of digital financial inclusion is further disaggregated into direct, indirect, and total (...) impacts. The results show that if digital financial inclusion is improved by 1%, household consumption will correspondingly increase by 0.2207%. The spatial spillover effect on neighboring areas is negative: a 1% increase in the level of digital financial inclusion of nearby provinces leads to a 0.1289% decrease in household consumption in the local province. For policymakers, it is necessary to balance the development of digital financial inclusion and view different areas as a whole when making policies to promote consumption. Further analysis based on subsamples finds that the effect of digital financial inclusion on household consumption is more considerable for rural households than for urban households. (shrink)

Après une présentation de l’évolution du solde commercial sino-étasunien ( Partie I ), cet article proposedeux méthodes de mesure de l’échange inégal entre les États-Unis et la Chine, l’une considérant le contenu en travail directement incorporé dans l’échange ( Partie II ), l’autre, inspirée de Ricci (2018), centrée sur la valeur internationale et mobilisant des tableaux entrées-sorties ( Partie III ), permettant d’esquisser une synthèse d’analyse sectorielle ( Partie IV ).

While cochlear implantation has benefitted many patients with single-sided deafness (SSD), there is great variability in cochlear implant (CI) outcomes and binaural performance remains poorer than that of normal-hearing (NH) listeners. Differences in sound quality across ears – temporal fine structure (TFS) information with acoustic hearing versus coarse spectro-temporal envelope information with electric hearing – may limit integration of acoustic and electric patterns. Binaural performance may also be limited by inter-aural mismatch between the acoustic input frequency and the place of (...) stimulation in the cochlea. SSD CI patients must learn to accommodate these differences between acoustic and electric stimulation to maximize binaural performance. It is possible that training may increase and/or accelerate accommodation and further improve binaural performance. In this study, we evaluated lateralization training in NH subjects listening to broad simulations of SSD CI signal processing. A 16-channel vocoder was used to simulate the coarse spectro-temporal cues available with electric hearing; the degree of inter-aural mismatch was varied by adjusting the simulated insertion depth (SID) to be 25 mm (SID25), 22 mm (SID22), and 19 mm (SID19) from the base of the cochlea. Lateralization was measured using headphones and head-related transfer functions (HRTFs). Baseline lateralization was measured for unprocessed speech (UN) delivered to the left ear to simulate SSD and for binaural performance with the acoustic ear combined with the 16-channel vocoders (UN+SID25, UN+SID22, and UN+SID19). After completing baseline measurements, subjects completed 6 lateralization training exercises with the UN+SID22 condition, after which performance was re-measured for all baseline conditions. Post-training performance was significantly better than baseline for all conditions (p<0.05 in all cases), with no significant difference in training benefits among conditions. Given that there was no significant difference between the SSD and the SSD CI conditions before or after training, the results suggest that NH listeners were unable to integrate TFS and coarse spectro-temporal cues across ears for lateralization, and that inter-aural mismatch played a secondary role at best. While lateralization training may benefit SSD CI patients, the training may largely improve spectral analysis with the acoustic ear alone, rather than improve integration of acoustic and electric hearing. (shrink)

Volume 34, Issue 8, December 2020, Page 1646-1663.

The Arf family proteins are best known for their roles in the vesicle biogenesis. However, they also play fundamental roles in a wide range of cellular regulation besides vesicular trafficking, such as modulation of lipid metabolic enzymes, cytoskeleton remodeling, ciliogenesis, lysosomal, and mitochondrial morphology and functions. Growing studies continue to expand the downstream effector landscape of Arf proteins, especially for the less‐studied members, revealing new biological functions, such as amino acid sensing. Experiments with cutting‐edge technologies and in vivo functional studies (...) in the last decade help to provide a more comprehensive view of Arf family functions. In this review, we summarize the cellular functions that are regulated by at least two different Arf members with an emphasis on those beyond vesicle biogenesis. (shrink)

The purpose of this study was to understand the influence mechanism of college students’ entrepreneurial intention in view of the increasing number of college students at present to alleviate college students’ employment competition. The psychological factors that influence the entrepreneurial tendency of art graduates were analyzed and studied. First, venture capital and factors affecting entrepreneurial performance were analyzed. Second, the coefficient calculation is carried out for college students majoring in art through the regression analysis of the logistic model. Finally, a (...) team entrepreneurial performance questionnaire was designed, and team reward levels were discussed. The results show that the logistic model can well reflect the real situation of the respondents. The significance level of the entrepreneurial team was 0.02, which was correlated. Additionally, corresponding suggestions were put forward according to the questionnaire results. Clear team goals, assignment of tasks to members, good pressure resistance, and psychological quality of members are necessary qualities for successful entrepreneurship. This conclusion provides a certain theoretical basis for the current college students’ entrepreneurial learning and a reliable inspiration for helping college students to successfully start a business. (shrink)

In the context of the COVID-19, we examined the relationship between college students’ ego depletion and their prosocial behavior. We explored the mediating role of social self-efficacy between ego depletion and prosocial behavior, we also examined the moderating role of personal belief in a just world in this relationship. 1,122 college students completed the ego depletion questionnaire, prosocial behavior questionnaire, social self-efficacy questionnaire, and personal belief in a just world questionnaire. The current findings suggested that: Social self-efficacy mediated the relationship (...) between college students’ ego depletion and their prosocial behaviors. The ego depletion of college students could be used to predict their prosocial behavior through social self-efficacy. Personal belief in a just world moderated the relationship between social self-efficacy and prosocial behavior. (shrink)

It has been well documented that the auditory system in the superior temporal cortex is responsible for processing basic auditory sound features, such as sound frequency and intensity, while the prefrontal cortex is involved in higher-order auditory functions, such as language processing and auditory episodic memory. The temporal auditory cortex has vast forward anatomical projections to the prefrontal auditory cortex, connecting with the lateral, medial, and orbital parts of the prefrontal cortex. The connections between the auditory cortex and the prefrontal (...) cortex thus help in localizing, recognizing, and comprehending external auditory inputs. In addition, the medial prefrontal cortex is believed to be a core region of episodic memory retrieval and is one of the most important regions in the default mode network. However, previous neural evidence with regard to the comparison between basic auditory processing and auditory episodic memory retrieval mainly comes from fMRI studies. The specific neural networks and the corresponding critical frequency bands of neuronal oscillations underlying the two auditory functions remain unclear. In the present study, we reported results of direct cortical stimulations during stereo-electro-encephalography recording in a patient with drug-resistant epilepsy. Electrodes covered the superior temporal gyrus, the operculum and the insula cortex of bilateral hemispheres, the prefrontal cortex, the parietal lobe, the anterior and middle cingulate cortex, and the amygdala of the left hemisphere. Two types of auditory hallucinations were evoked with direct cortical stimulations, which were consistent with the habitual seizures. The noise hallucinations, i.e., “I could hear buzzing noises in my head,” were evoked with the stimulation of the superior temporal gyrus. The episodic memory hallucinations “I could hear a young woman who was dressed in a red skirt saying: What is the matter with you?,” were evoked with the stimulation of MPFC. The patient described how she had met this young woman when she was young and that the woman said the same sentence to her. Furthermore, by analyzing the high gamma power induced by direct electrical stimulation, two dissociable neural networks underlying the two types of auditory hallucinations were localized. Taken together, the present results confirm the hierarchical processing of auditory information by showing the different involvements of the primary auditory cortex vs. the prefrontal cortex in the two types of auditory hallucinations. (shrink)

Slagging-off is an important preprocessing operation of steel-making to improve the purity of iron. Current manual-operated slag removal schemes are inefficient and labor-intensive. Automatic slagging-off is desirable but challenging as the reliable recognition of iron and slag is difficult. This work focuses on realizing an efficient and accurate recognition algorithm of iron and slag, which is conducive to realize automatic slagging-off operation. Motivated by the recent success of deep learning techniques in smart manufacturing, we introduce deep learning methods to this (...) field for the first time. The monotonous gray value of industry images, poor image quality, and nonrigid feature of iron and slag challenge the existing fully convolutional networks. To this end, we propose a novel spatial and feature graph convolutional network module. SFGCN module can be easily inserted in FCNs to improve the reasoning ability of global contextual information, which is helpful to enhance the segmentation accuracy of small objects and isolated areas. To verify the validity of the SFGCN module, we create an industrial dataset and conduct extensive experiments. Finally, the results show that our SFGCN module brings a consistent performance boost for a wide range of FCNs. Moreover, by adopting a lightweight network as backbone, our method achieves real-time iron and slag segmentation. In the future work, we will dedicate our efforts to the weakly supervised learning for quick annotation of big data stream to improve the generalization ability of current models. (shrink)