In this study, we first introduce polygonal cylinder and torus using Cartesian products and topologically identifications and then find their Wiener and hyper-Wiener indices using a quick, interesting technique of counting. Our suggested mathematical structures could be of potential interests in representation of computer networks and enhancing lattice hardware security.

This paper analyses the evolutionary characteristics of the interprovincial population mobility network structure in China and explores the roles of provinces from 2010 to 2015. By constructing the interprovincial population mobility network, we examine the provinces’ functions during periods of population mobility through population mobility diversity, population mobility, and population mobility intermediation. The results show that the coverage and tightness of the interprovincial population mobility network were influenced by national economic development, increasing steadily from 2010 to 2014 and then suddenly (...) falling in 2015. The regions that played essential roles in the province’s mobility diversity and intermediation showed a dispersion trend. In contrast, areas that played a vital role in the inflows or outflows were relatively concentrated and stable. Additionally, this work further explores how economic factors, e.g., GDP, residents’ consumption levels, total population, unemployment rate, and consumer price index, are used as independent variables to analyse the provinces’ roles in the interprovincial population mobility network. The analysis shows that the inflow or outflow volumes are easily affected by the five indices. These five indices are significantly related to network role indicators to different extents. (shrink)

Language teacher research is conducive to the development of teachers’ teaching skills and professional careers. Thus, many English teacher education programs require student teachers to do research. However, some empirical findings suggest that English as a foreign language student teachers lack research motivation. Consequently, finding suitable interventions to increase their research motivation has become increasingly necessary. In light of the importance of research motivation intervention, this study involved designing an experiment to identify the effect of a value and interest intervention (...) including the sharing of positive research experiences to improve student teachers’ research motivation. Quantitative questionnaires and qualitative semi-structured interviews were used to gather evidence on the change in student teachers’ research motivation during the intervention. The interview data revealed that student teachers’ research motivation was influenced by their belief in the value of research to their teaching practice. The experiment results suggested that student teachers’ intrinsic and extrinsic research motivations both increased after the intervention. However, the intervention was not effective in curbing their failure avoidance tendency. Pedagogical implications of the results are discussed at the end of this article. (shrink)

We have refined entropy theory to explore the meaning of the increasing sequence data on nucleic acids and proteins more conveniently. The concept of selection constraint was not introduced, only the analyzed sequences themselves were considered. The refined theory serves as a basis for deriving a method to analyze non-coding regions (NCRs) as well as coding regions. Positions with maximal entropy might play the most important role in genome functions as opposed to positions with minimal entropy. This method was tested (...) in the well-characterized coding regions of 12 strains of Classical Swine Fever Virus (CSFV) and non-coding regions of 20 strains of CSFV. It is suitable to analyze nucleic acid sequences of a complete genome and to detect sensitive positions for mutagenesis. As such, the method serves to formulate the basis for elucidating the functional mechanism. (shrink)

The impact of bilingual education and bilingual experience on working memory has been an important and controversial issue in the field of psycholinguistics. Taking Chinese-English bilinguals as an example, this study aims to investigate the differences in emotional working memory between proficient and non-proficient bilinguals by using delayed matching-to-sample task paradigm and more complex n-back task in the context of emotion. The results show that proficient bilinguals have better performance on both of the two working memory tasks than non-proficient bilinguals, (...) and the advantage effects were more apparent under high memory load conditions. Besides, the negative emotion context has a positive impact on complex n-back tasks. This study supports the notion that bilingual experience can promote the development of an individual’s cognitive ability and enable individuals to possess more advantages in working memory even in the presence of emotional distractions. (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)

Conflicts in land exploration are incisive social problems which have been the subject in many studies. Risk assessment of land conflicts is effective to resolve such problems. Specifically, fuzzy mathematics and the analytic hierarchy process were combined together to evaluate risk in land conflicts in our work, which is proved useful to solve uncertainty and imprecision problems. Based on the analysis of the principles for the risk assessment of a land conflicts index system, a set of risk assessment indexes using (...) the fuzzy analytic hierarchy process was presented. The results show that the overall risk is at medium level, and the risk of the feasibility index and controllability index need to be paid more attention to. The contribution of this article is reflected in two aspects: the application of FAHP in risk assessments of land conflicts is effective and valid; it is helpful for governments to establish a stricter management system of work safety for conflicts in land exploration based on the risk assessment results. (shrink)

OBJECTIVE: To report and analyse the pattern of end-of-life decision making for terminal Chinese cancer patients. DESIGN: Retrospective descriptive study. SETTING: A cancer clinical trials unit in a large teaching hospital. PATIENTS: From April 1992 to August 1997, 177 consecutive deaths of cancer clinical trial patients were studied. MAIN MEASUREMENT: Basic demographic data, patient status at the time of signing a DNR consent, or at the moment of returning home to die are documented, and circumstances surrounding these events evaluated. RESULTS: (...) DNR orders were written for 64.4% of patients. Patients in pain (odds ratio 0.45, 95% CI 0.22-0.89), especially if requiring opioid analgesia (odds ratio 0.40, 95% CI 0.21-0.77), were factors associated with a higher probability of such an order. Thirty-five patients were taken home to die, a more likely occurrence if the patient was over 75 years (odds ratio 0.12, 95% CI 0.04-0.34), had children (odds ratio 0.14, 95% CI 0.02-0.79), had Taiwanese as a first language (odds ratio 6.74, 95% CI 3.04-14.93), or was unable to intake orally (odds ratio 2.73, 95% CI 1.26-5.92). CPR was performed in 30 patients, none survived to discharge. CONCLUSIONS: DNR orders are instituted in a large proportion of dying Chinese cancer patients in a cancer centre, however, the order is seldom signed by the patient personally. This study also illustrates that as many as 20% of dying patients are taken home to die, in accordance with local custom. (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)

Cross-shareholding is a new type of strategic means for capital operation and is an important component of corporate governance. With the increasing complexity of business motivation, the structure of a cross-shareholding network is becoming more intricate, and it exposes various important local patterns with different economic functions. The goal of this paper is to uncover investment mechanisms and economic functions implied in cross-shareholding networks by analyzing the local characteristic patterns of company interactions. In this paper, we construct the CSNs of (...) listed companies and extract the directed triadic motifs to reveal the evolutionary characteristics of local investment patterns at the company and industry levels. On the company level, we find that companies tend to form V-shaped structures with other companies, but bidirectional shareholding patterns and circular relationships in the triads are scarce. On the industry level, we identify the characteristic linking patterns of some industries with a role analysis of the industries. Furthermore, we detect the evolutionary characteristics of industry interrelationships in three implied patterns. Such a motif evolution analysis may provide valuable information for investors and supervisory departments that make decisions about investment portfolios and policy. Meanwhile, this study is also helpful for exploring the implied information in other empirical networks. (shrink)

The study of cyber-attacks, and in particular the spread of attack on the power cyber-physical system, has recently attracted considerable attention. Identifying and evaluating the important nodes under the cyber-attack propagation scenario are of great significance for improving the reliability and survivability of the power system. In this paper, we improve the closeness centrality algorithm and propose a compound centrality algorithm based on adaptive coefficient to evaluate the importance of single-layer network nodes. Moreover, we quantitatively calculated the decouple degree of (...) cascading failures caused by exposed nodes formed by attack propagation. At last, experiments based on the IEEE 57 test system show that the proposed compound centrality algorithm can match the cyber-attack propagation scenario well, and we give the importance values of the nodes in a specific attack scenario. (shrink)

Linear regression and its variants have been widely used for classification problems. However, they usually predefine a strict binary label matrix which has no freedom to fit the samples. In addition, they cannot deal with complex real-world applications such as the case of face recognition where samples may not be linearly separable owing to varying poses, expressions, and illumination conditions. Therefore, in this paper, we propose the kernel negative ε dragging linear regression method for robust classification on noised and nonlinear (...) data. First, a technique called negative ε dragging is introduced for relaxing class labels and is integrated into the LR model for classification to properly treat the class margin of conventional linear regressions for obtaining robust result. Then, the data is implicitly mapped into a high dimensional kernel space by using the nonlinear mapping determined by a kernel function to make the data more linearly separable. Finally, our obtained KNDLR method is able to partially alleviate the problem of overfitting and can perform classification well for noised and deformable data. Experimental results show that the KNDLR classification algorithm obtains greater generalization performance and leads to better robust classification decision. (shrink)

Background: Cognitive impairment is one of the core symptoms of schizophrenia, which is considered to be significantly correlated to prognosis. In recent years, many studies have suggested that metabolic disorders could be related to a higher risk of cognitive defects in a general setting. However, there has been limited evidence on the association between metabolism and cognitive function in patients with early-stage schizophrenia.Methods: In this study, we recruited 172 patients with early-stage schizophrenia. Relevant metabolic parameters were examined and cognitive function (...) was evaluated by using the MATRICS Consensus Cognitive Battery (MCCB) to investigate the relationship between metabolic disorder and cognitive impairment.Results: Generally, the prevalence of cognitive impairment among patients in our study was 84.7% (144/170), which was much higher than that in the general population. Compared with the general Chinese setting, the study population presented a higher proportion of metabolic disturbance. Patients who had metabolic disturbance showed no significant differences on cognitive function compared with the other patients. Correlation analysis showed that metabolic status was significantly correlated with cognitive function as assessed by the cognitive domain scores (p < 0.05), while such association was not found in further multiple regression analysis.Conclusions: Therefore, there may be no association between metabolic disorder and cognitive impairment in patients with early-stage schizophrenia.Trial Registration: Clinicaltrials.gov, NCT02880462. Registered August 26, 2016. (shrink)

本书是一本研究建筑学的书籍, 全书包括有《现象学与建筑学的思考》、《建筑中的神性》等多篇文章.

Social anxiety and stress type can influence strong conformity among adolescents; however, the interaction between them is not clear. In this study, 152 adolescents were recruited and assigned one of two conditions: an interaction and a judgment condition. In the interaction condition, adolescents with high social anxiety (HSA) were less likely to conform when completing a modified Asch task, compared to adolescents who had low social anxiety. In the judgment condition, adolescents with HSA were more likely to conform to the (...) opinions from the unanimous majority. The results suggest that adolescents with HSA may show different styles of strong conformity with the change of stress type. We believe that socially anxious adolescents avoid potential social situations with weaker conformity, while avoiding negative evaluations from others with stronger conformity. These findings contribute to a better understanding of the social dysfunctions among adolescents with HSA and provide a new direction for clinical interventions. (shrink)

We present the interval-valued intuitionistic fuzzy ordered weighted cosine similarity measure in this paper, which combines the interval-valued intuitionistic fuzzy cosine similarity measure with the generalized ordered weighted averaging operator. The main advantage of the IVIFOWCS measure provides a parameterized family of similarity measures, and the decision maker can use the IVIFOWCS measure to consider a lot of possibilities and select the aggregation operator in accordance with his interests. We have studied some of its main properties and particular cases such (...) as the interval-valued intuitionistic fuzzy ordered weighted arithmetic cosine similarity measure and the interval-valued intuitionistic fuzzy maximum cosine similarity measure. The IVIFOWCS measure not only is a generalization of some similarity measure, but also it can deal with the correlation of different decision matrices for interval-valued intuitionistic fuzzy values. Furthermore, we present an application of IVIFOWCS measure to the group decision-making problem. Finally the existing similarity measures are compared with the IVIFOWCS measure by an illustrative example. (shrink)

Efficient knowledge sharing is an important support for the continuous innovation and sustainable development of scientific research teams. However, in realistic management situations, the knowledge sharing of scientific research teams always appears to be unsustainable, and the reasons for this are the subject of considerable debate. In this study, an attempt was made to explore the interactive mechanism of knowledge hiding behaviors in scientific research teams between individual and collective knowledge hiding behaviors and its impact on knowledge sharing by adopting (...) grounded theory to comprehensively understand this situation. The results show that knowledge hiding behavior in the scientific research team is a two-phase interactive process and is capable of affecting sustainable knowledge sharing by reducing the supply of knowledge, creating a poor knowledge sharing atmosphere, and forming an interpersonal distrust relationship. This research may provide a strong basis for a deeper understanding of the interaction mechanism of knowledge hiding behavior and its impact on knowledge sharing. (shrink)

The increase of ETC vehicles on expressways has changed the proportion of ETC/MTC lanes at toll stations. Based on a driving simulator, three toll gate lane warning sign schemes were proposed in this study. Driving simulation experiments were conducted to study the influence of figures in warning signs at the manual toll station on the lane change timing of drivers. It was found that the addition of arrows to the warning signs can significantly shorten the response time and guide the (...) driver to make lane change decisions earlier to reduce the congestion between MTC vehicles and the mainline ETC vehicles at the toll plaza, thereby improving the traffic capacity and safety. (shrink)

ObjectiveSchizophrenia is a mental disorder that is characterized by progressive cognitive impairment. Objective measures of cognitive function may provide reliable neurobiomarkers for patients with schizophrenia. The goal of the current work is to explore the correlation between resting theta power and cognitive performance in patients with schizophrenia.MethodsTwenty-two patients with schizophrenia and 23 age-, sex-, and education-matched healthy controls were included in this study. The MATRICS Consensus Cognitive Battery was used for cognitive evaluation and the Positive and Negative Syndrome Scale for (...) evaluation of clinical symptoms. EEGs were acquired in the resting state with closed and opened eyes. Between the two groups, we compared the relative theta power and examined their relationship with cognitive performance.ResultsCompared to healthy controls, patients with schizophrenia showed significantly higher theta power, both with eyes closed and open. When the eyes were open, negative correlations were found in patients with schizophrenia between theta power in the central and parietal regions with processing speed scores, and between the theta power of the Pz electrode and verbal learning and reasoning and problem-solving scores. In the control group, theta power over the Fz electrode was negatively correlated with processing speed.ConclusionsOur findings showed that theta activity increased in certain brain regions during resting state in schizophrenia. Negative associations between resting theta power over the parietal-occipital regions with MCCB domains scores suggest that altered theta activity can be used as a neurobiological indicator to predict cognitive performance. (shrink)

More and more research on left ventricle quantification skips segmentation due to its requirement of large amounts of pixel-by-pixel labels. In this study, a framework is developed to directly quantify left ventricle multiple indices without the process of segmentation. At first, DenseNet is utilized to extract spatial features for each cardiac frame. Then, in order to take advantage of the time sequence information, the temporal feature for consecutive frames is encoded using gated recurrent unit. After that, the attention mechanism is (...) integrated into the decoder to effectively establish the mappings between the input sequence and corresponding output sequence. Simultaneously, a regression layer with the same decoder output is used to predict multi-indices of the left ventricle. Different weights are set for different types of indices based on experience, and l2-norm is used to avoid model overfitting. Compared with the state-of-the-art, our method can not only produce more competitive results but also be more flexible. This is because the prediction results in our study can be obtained for each frame online while the SOTA only can output results after all frames are analyzed. (shrink)

In the process of rapid urbanization, urban heat island effect has been showing more and more significant impacts on human well-being. Therefore, a more detailed understanding of the impact of three-dimensional building morphology on UHI effect across a continuum of spatial scales will be necessary to guide and improve the human settlement.This study selected 31 provincial capital cities of mainland China to analyze the impacts of the 3D building morphology, including the number, area, height, volume, and the surface area of (...) the buildings, on the land surface temperature. By exploring how the influence of 3D building morphology on LST changes with the increase of spatial scale, this study finally recognized which 3D building morphology index is the most significant index affecting LST in different cities, and which spatial scale these 3D building morphology indexes have the most significant impact on LST. The results showed that the building area is the most important 3D building morphology parameter affecting the LST, while the building height has the slightest influence on the LST. These effects are more significant in the spatial scale of 150 m–540 m, and the spatial scale increases with the increase of building areas in developed cities. These results highlight the necessity of considering fine-grained management in the governance and alleviating of the urban thermal environment through urban planning and urban renewal strategies. (shrink)

We show that for any ω-r.e. degree d and n-r.e. degree b with d

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The present study critically evaluates whether school leadership influences student learning homogenously regardless of school contexts. It examined relationships between four principal leadership variables (envisioning, instructional management, promoting professional development, empowerment) and two types of student outcomes (enjoyment in learning science, science achievement,) in different school contexts (in terms of the availability of science resources, quality of science teachers, and school socioeconomic status (SES)). The sample comprised 248,620 students and 9,370 principals in 35 developed countries who participated in the Programme (...) for International Student Assessment (PISA) 2015. Latent profile analysis (LPA) showed that schools operated in three types of school contexts with different levels of science resources, proportion of quality science teachers, and school SES. There were also differences in the pattern of leadership practices across the three types of school contexts. Three-level hierarchical linear modeling (HLM) showed that among the four leadership variables, only instructional management was positively associated with students’ enjoyment of science in schools with less science resources and quality science teachers. Therefore, instructional management had compensatory effects for students in less-endowed schools. In contrast, principal leadership related to envisioning, teacher professional development, and empowerment was not positively related to students’ science learning in all three school contexts. (shrink)

Green space around the university campus is of paramount importance for emotional and psychological restorations in students. Positive emotions in students can be aroused when immersed in green space and naturalness. However, to what extent can perceived naturalness influence students' positive emotion remains unclear, especially in the context of COVID-19 countermeasures. This study, therefore, attempts to investigate in-depth the nature and strength of the relationships between students' positive emotion and their perceived naturalness, place attachment, and landscape preference, which are potentially (...) varying across universities in different social and environmental contexts and different restrictions policies regarding the COVID-19 pandemic. (shrink)