The identification and analysis of the spatiotemporal dynamic traffic patterns in citywide road networks constitute a crucial process for complex traffic management and control. However, city-scale and synchronal traffic data pose challenges for such kind of quantification, especially during peak hours. Traditional studies rely on data from road-based detectors or multiple communication systems, which are limited in not only access but also coverage. To avoid these limitations, we introduce real-time, traffic condition digital maps as our input. The digital maps keep (...) spatiotemporal urban traffic information in nature and are open to access. Their pixel colors represent traffic conditions on corresponding road segments. We propose a stacked convolutional autoencoder-based method to extract a low-dimension feature vector for each input. We compute and analyze the distances between vectors. The statistical results show different traffic patterns during given periods. With the actual data of Chongqing city, we compare the feature extraction performance between our proposed method and histogram. The result shows our proposed method can extract spatiotemporal features better. For the same data set, there is little difference in the number distribution of red pixels found in the statistics result of the histogram, while differences do exist in the results of our proposed method. We find the most fluctuated morning is on Friday; the most fluctuated evening is on Tuesday; and the most stable evening is on Wednesday. The distance captured by our method can represent the evolution of different traffic conditions during the morning and evening peak hours. Our proposed method provides managers with assistance to sense the dynamics of citywide traffic conditions in quantity. (shrink)

PurposeThe COVID-19 pandemic that began in 2019 has had a significant impact on people’s learning and their lives, including a significant increase in the incidence of academic procrastination and negative emotions. The topic of how negative emotions influences academic procrastination has been long debated, and previous research has revealed a significant relationship between the two. The purpose of this study was to further investigate the mediating and buffering effects of online-shopping addiction on academic procrastination and negative emotions.MethodsThe researchers conducted a (...) correlation analysis followed by a mediation analysis and developed a mediation model. The study used stratified sampling and an online questionnaire as the data collection method. In this study, first, five freshmen students at vocational and technical colleges in Guangdong Province, China, were called to distribute the questionnaire. Second, after communicating with them individually, first-year students of Guangdong origin were selected as participants. Finally, 423 freshman students participated by completing the questionnaire. The questionnaire consisted of 4 parts: demographic information, an online-shopping-addiction scale, an academic-procrastination scale and a negative-emotions scale. A total of 423 students, 118 males and 305 females from 10 vocational and technical colleges in Guangdong were surveyed. SPSS 25.0 was used to process and analyze the data. The data collected were self-reported.ResultsThe results showed that: first, academic procrastination was significantly and positively associated with online-shopping addiction. Second, academic procrastination was significantly and positively associated with negative emotions. Third, online-shopping addiction was significantly and positively associated with negative emotions. In addition, academic procrastination had a significant positive predictive effect on online-shopping addiction. Online-shopping addiction had a significant positive predictive effect on negative emotions.ConclusionThis study explored the relationship between students’ academic procrastination, negative emotions, and online-shopping addiction during the COVID-19 pandemic. The results indicated that students’ level of academic procrastination positively influenced their level of online-shopping addiction and negative emotions, and their level of online-shopping addiction increased their negative emotions. In addition, there was a mediating effect between the degree of participants’ online-shopping addiction and their degree of academic procrastination and negative emotions during the pandemic. In other words, with the mediating effect of online-shopping addiction, the higher the level of a participant’s academic procrastination, the more likely that the participant would have a high score for negative emotions. (shrink)

Working memory (WM) is a fundamental cognitive ability to support complex thought, but it is limited in capacity. WM training has shown the potential to make benefit for those in need. Many studies have shown the potential of transcranial direct current stimulation (tDCS) to transiently enhance WM performance by delivering low current to the brain cortex of interest via electrodes on the scalp. TDCS has also been revealed as a promising intervention to augment WM training in a few studies. However, (...) those few tDCS-paired WM training studies focused more on the effect of tDCS on WM enhancement and its transferability after training but paid less attention to the variation of cognitive performance during the training procedure. The current study attempted to explore the effect of tDCS on the variation of performance during WM training in healthy young adults. All the participant received WM training with the load-adaptive verbal N-back task for five days. During the training procedure, active/sham anodal high-definition tDCS (HD-tDCS) was used to stimulate the left dorsolateral prefrontal cortex (DLPFC). To examine the training effect, pre- and post-test were performed respectively one-day before and after the training sessions respectively. At the beginning of each training session, stable-load WM tasks were performed to examine the performance variation during training. Compared to the sham stimulation, higher learning rates of performance metrics during the training procedure were found when WM training was combined with active anodal HD-tDCS. The performance improvements (post-pre) of the active group were also found to be higher than those of sham group and were transferred to a similar untrained WM task. Further analysis revealed that the negative relation between the training improvements and baseline performance. These findings show the potential that tDCS may be leveraged as an intervention to facilitate WM training for those in need of higher WM ability. (shrink)

This paper studies a simple dynamical system of stock price fluctuation time series based on the rule of stock market. When the stock price fluctuation system is disturbed by external excitations, the system exhibits obviously chaotic phenomena, and its basic dynamic properties are analyzed. At the same time, a new fixed-time convergence theorem is proposed for achieving fixed-time control of stock price fluctuation system. Finally, the effectiveness of the method is verified by numerical simulation.

BackgroundMild cognitive impairment is a common neurological disorder. Moxibustion has been shown to be effective in treating MCI, but its therapeutic mechanisms still remain unclear. This study mainly aimed to investigate the modulation effect of moxibustion treatment for patients with MCI by functional magnetic resonance imaging.MethodsA total of 47 patients with MCI and 30 healthy controls participated in resting-state fMRI imaging scans. Patients with MCI were randomly divided into true moxibustion group and sham moxibustion group. The degree centrality approach was (...) applied to distinguish altered brain functions. Correlation analysis was then performed to examine the relationships between the neuroimaging findings and clinical symptoms.ResultsCompared with HCs, patients with MCI mainly showed decreased DC in the left middle frontal cortex and bilateral middle cingulate cortex. After moxibustion treatment, the SHAM group had no significant DC findings, while TRUE group mainly showed significant increased DC in the bilateral MFC and MCC, as well as decreased DC in the left middle occipital cortex. Repeated measures analysis of variance showed significant interactions between the two groups of patients with MCI. In addition, the higher Mini-Mental State Examination score was significantly positively correlated with increased DC in the right MFC and left MCC after moxibustion treatment.ConclusionOur findings demonstrate that the potential value of moxibustion treatment on MCI, which adds new insights into the popular view that moxibustion treatment may slow cognitive decline in patients with MCI. (shrink)

A portrait recognition system can play an important role in emergency evacuation in mass emergencies. This paper designed a portrait recognition system, analyzed the overall structure of the system and the method of image preprocessing, and used the Single Shot MultiBox Detector (SSD) algorithm for portrait detection. It also designed an improved algorithm combining principal component analysis (PCA) with linear discriminant analysis (LDA) for portrait recognition and tested the system by applying it in a shopping mall to collect and monitor (...) the portrait and establish a data set. The results showed that the missing detection rate and false detection rate of the SSD algorithm were 0.78 and 2.89%, respectively, which were lower than those of the AdaBoost algorithm. Comparisons with PCA, LDA, and PCA + LDA algorithms demonstrated that the recognition rate of the improved PCA + LDA algorithm was the highest, which was 95.8%, the area under the receiver operating characteristic curve was the largest, and the recognition time was the shortest, which was 465 ms. The experimental results show that the improved PCA + LDA algorithm is reliable in portrait recognition and can be used for emergency evacuation in mass emergencies. (shrink)

Model RB is a model of random constraint satisfaction problems, which exhibits exact satisfiability phase transition and many hard instances, both experimentally and theoretically. Benchmarks based on Model RB have been successfully used by various international algorithm competitions and many research papers. In a previous work, Xu and Li defined two notions called i-constraint assignment tuple and flawed i-constraint assignment tuple to show an exponential resolution complexity of Model RB. These two notions are similar to some kind of consistency in (...) constraint satisfaction problems, but seem different from all kinds of consistency so far known in literatures. In this paper, we explicitly define this kind of consistency, called variable-centered consistency, and show an upper bound on a parameter in Model RB, such that up to this bound the typical instances of Model RB are variable-centered consistent. (shrink)

本书对科技与政治交互作用空间的性质、结构及其张力进行了基本阐述,探讨科技政治空间价值张力的离合及有机统一的作用规律以及科技政治空间自由与干涉的权力张力及其作用规律等。.

The interference of the complex background and less information of the small targets are two major problems in vehicle attribute recognition. In this paper, two cascaded networks of vehicle attribute recognition are established to solve the two problems. For vehicle targets with normal size, the multitask cascaded convolution neural network MC-CNN-NT uses the improved Faster R-CNN as the location subnetwork. The vehicle targets in the complex background are extracted by the location subnetwork to the classification subnetwork CNN for the classification. (...) The implementation of this task decomposition strategy effectively eliminates the interference of the complex background in target detection. For vehicle targets with small size, the multitask cascaded convolution neural network MC-CNN-ST applies the network compression strategy and the multilayer feature fusion strategy to extract the feature maps. These strategies enrich the location information and semantic information of the feature maps. In order to optimize the nonlinear mapping ability and the hard-to-detect samples mining ability of the networks, the activation function and the loss function in the two cascaded networks are improved. The experimental results show that MC-CNN-NT for the normal targets and MC-CNN-ST for the small targets achieve the state-of-the-art performance compared with other attribute recognition networks. (shrink)

Ben shu dui ke xue mei xue si xiang shi de yan jiu dui xiang, ren wu he fang fa jin xing le xi tong di lun shu.

本書主要編入了從"唐宋變革論"說到宋代思想史與文化史研究;歷史學意義上的新思想史;"前近代"."亞洲出發思考"與"作為方法的中國";清代學術史與思想史的再認識等四講內容.

本书分四个部分:第一部分以梁漱溟先生的思虑为个案样本,探讨法的一般理念问题;第二部分论及宪政、普通法和近代西方法律教育与法学研究;第三部分意在研索“罪孽理念与罪刑关系”;第四部分为通讯体论文。.

本书是关于新意识形态批评的论文集,本书要论述的意图是:以理论与社会生活的密切关系而言,中国文论家可以创造出自己的“本位话语”,其具体问题集中为两个,即文化转型中的当代中国的精神建构和建立文学理论的本位 话语。.

本书内容包括:孔子思想的主要特征、老子思想的文化地位、墨子思想的历史影响、孟子思想的历史影响、董仲舒在学术思想史上的地位、张衡在中国思想文化上的地位等内容。.

本书简要地介绍了《周易》的一些重要概念及其在二十一世纪的可能应用,指出以《周易》为代表的东方文明对人类社会在新世纪的可持续发展所可能做出的贡献。.

In this paper, I provide a framework for accounting for the self, based on a reconstruction of Galen Strawson’s “theory of SESMETs,” or the Pearl view, with Barry Dainton’s continuous consciousness thesis. I argue that the framework I provide adequately accounts for the self and is preferable to solely adopting either Strawson’s or Dainton’s theory. I call my reconstruction the “Necklace” view of the self.

The Alexandra District Ambulance Service is the only volunteer-based ambulance service in Victoria, Australia. It provides an opportunity to reflect on the ethical issues surrounding the delivery of ambulance service by volunteers, and its impact on the community.