New types of artificial intelligence products are gradually transferring to voice interaction modes with the demand for intelligent products expanding from communication to recognizing users' emotions and instantaneous feedback. At present, affective acoustic models are constructed through deep learning and abstracted into a mathematical model, making computers learn from data and equipping them with prediction abilities. Although this method can result in accurate predictions, it has a limitation in that it lacks explanatory capability; there is an urgent need for an (...) empirical study of the connection between acoustic features and psychology as the theoretical basis for the adjustment of model parameters. Accordingly, this study focuses on exploring the differences between seven major “acoustic features” and their physical characteristics during voice interaction with the recognition and expression of “gender” and “emotional states of the pleasure-arousal-dominance (PAD) model.” In this study, 31 females and 31 males aged between 21 and 60 were invited using the stratified random sampling method for the audio recording of different emotions. Subsequently, parameter values of acoustic features were extracted using Praat voice software. Finally, parameter values were analyzed using a Two-way ANOVA, mixed-design analysis in SPSS software. Results show that gender and emotional states of the PAD model vary among seven major acoustic features. Moreover, their difference values and rankings also vary. The research conclusions lay a theoretical foundation for AI emotional voice interaction and solve deep learning's current dilemma in emotional recognition and parameter optimization of the emotional synthesis model due to the lack of explanatory power. (shrink)

Biologists have long known that animal population dynamics are regulated by a combination of bottom-up and top-down forces. Yet, economists have argued that human population dynamics can also be influenced by intraspecific cooperation. Despite awareness of the role of interspecific cooperation in influencing resource availability and animal population dynamics, the role of intraspecific cooperation under different environmental conditions has rarely been considered. Here we examine the role of what we call “lateral forces” that act within populations and interact with external (...) top-down and bottom-up forces in influencing population dynamics using an individual-based model linking environmental quality, intraspecific cooperation, and population size. We find that the proportion of cooperators is higher when the environment is poor and population sizes are greatest under intermediate resources levels due to the contrasting effects of resource availability on behavior and population size. We also show that social populations are more resilient to environmental change than non-social ones because the benefits of intraspecific cooperation can outweigh the effects of constrained resource availability. Our study elucidates the complex relationship between environmental harshness, cooperation, and population dynamics, which is important for understanding the ecological consequences of cooperation. (shrink)

Actions are usually generalized among social group members. Importantly, the efficiency of an action with respect to achieving an external target determines action understanding, and it may have different degrees of social relevance to social groups. Thus, this study explored the role of action efficiency in action generalization. We used computer animations to simulate actions in social groups initiated by visual action cues or category labels, and we measured differences in response times between identifying actions that were and were not (...) consistent with group members, without explicit requirements regarding generalization. It was found that in both visually introduced and explicitly labeled social groups, when the group members acted inefficiently toward the external object, perceivers identified group‐consistent actions faster than group‐inconsistent actions, indicating that the exemplars' common inefficient actions are generalized to the unknown ingroup member, accordingly facilitating the identification of expected consistent inefficient action (Experiment 1). As this effect was not present when removing social group cues, it was determined to be specific to social groups (Experiment 2). Importantly, such generalization was not observed when the identical action was deemed efficient toward the external object (Experiment 3) and was specific to the demonstration of the action being completed by multiple group members rather than being repeated twice by one group member, supporting the group‐based inference and ruling out the possibility of the increased memorability of inefficient actions leading to more generalization relative to efficient actions (Experiment 4). Therefore, the efficiency of an action bounds the generalization of the action across social group members through a process that is spontaneous and implicit. This constrained action generalization may be due to inefficient actions being represented as culture‐specific conventional forms. (shrink)

Chinese mind-body exercises are positively associated with executive function, but their effects on EF, from synthesized evidence using systematic and meta-analytic reviews, have not been conducted. Therefore, the present systematic review with meta-analysis attempted to determine whether CMBEs affect EF and its sub-domains, as well as how exercise, sample, and study characteristics moderate the causal relationship between CMBEs and EF in middle-aged and older adults. Seven electronic databases were searched for relevant studies published from the inception of each database through (...) June 2020. Randomized controlled trials with at least one outcome measure of CMBEs on EF in adults of mean age ≥ 50 years with intact cognition or mild cognitive impairment and with or without chronic diseases were included. A total of 29 studies ultimately were included in this study. The results indicated that CMBEs improved overall EF, as well as its sub-domains of working memory and shifting. The beneficial effects of CMBEs on EF occurred regardless of type, frequency of group classes, session time, total training time, and length of the CMBEs, in addition to that more frequent participation in both group classes and home practice sessions resulted in more beneficial effects. The positive effects of CMBEs on EF were also demonstrated, regardless of participants mean age, sex, and cognitive statuses, health status, as well as training mode and study language. This review thus suggests that CMBEs can be used as an effective method with small to moderate and positive effects in enhancing EF, and that more frequent group classes and home practice sessions may increase these effects. However, certain limitations, including strictly design studies, limited ES samples for specific variables, and possible biased publications, required paying particular attention to, for further exploring the effects of CMBEs on EF. (shrink)

Mathematics is an important foundation for the development of science education. In the past, when instructors taught mathematical concepts of geometry shapes, they usually used traditional textbooks and aids to conduct teaching activities, which resulted in students not being able to understand the principles completely. Nowadays, it has become a trend to integrate emerging technologies into mathematics courses and to use digital instructional aids. Emerging technologies can effectively enhance students’ sensory experience while strengthening their impressions and understandings of subject concepts. (...) In this paper, we apply virtual reality immersive technologies to develop a “virtual reality immersive learning mathematics geometry system,” which is used to teach mathematical geometry concepts. Teachers use the system to develop three basic mathematical geometry learning materials: “Triangular pyramid volume = 1/3 prism volume,” “Cone volume calculation,” and “Triangle center of gravity derivation.” In the experimental activity, the teacher uses virtual reality teaching aids to guide students to learn mathematical geometry concepts in a fun way so that they can achieve the effectiveness of immersive learning. This study explores the impact of using the virtual reality immersive learning mathematics geometry system on students’ technology acceptance, learning motivations, and learning performance. The experimental result showed that using the virtual reality immersive learning mathematics geometry system can improve the learning motivation and learning performance of students. The findings indicated that the experimental group had better learning outcomes after completing the learning tasks of three geometric units. The experimental group used the virtual reality immersive learning mathematics geometry system which can lead to better learning outcomes. According to the ARCS questionnaire, students in the experimental group were confident to understand new subjects. At the same time, the mode of completing the game can effectively give students a sense of accomplishment. The use of emerging technologies in the classroom can be an attractive learning mode for students. (shrink)

Technological innovation has an important impact on environmental pollution. In this paper, first, we analyze the influence mechanism of technological innovation on environmental pollution and then design the index system of technological innovation. Then, we use the entropy method to calculate the technological innovation level of different regions in China based on provincial panel data from 2004 to 2016. Finally, the panel vector autoregression model is adopted, and taking the discharge of sewage, solid waste, and exhaust gas as the research (...) objects, the impact of technological innovation on them is empirically analyzed. The results show that China’s technological innovation level is steadily improving, but there are significant differences in the impact of technological innovation on wastewater, waste gas, and solid waste. Specifically, technological innovation can contribute to an increase in wastewater and solid waste emissions. However, the impact of this technological innovation on them is not equal. Secondly, the impact of technological innovation on exhaust emissions is to inhibit exhaust emissions in the short term and promote exhaust emissions in the long term. Finally, there are clear differences between them in terms of the specific impact of changes in wastewater, solid waste, and exhaust emissions. Changes in wastewater discharges and solid waste generation are largely derived from their own effects, while the role of technological innovation is supportive and insignificant. The change in exhaust emissions is initially influenced by itself, but in the long run, the influence of technological innovation gradually increases and eventually exceeds its own influence. Based on these research results, this paper puts forward corresponding policy suggestions to speed up environmental pollution control. (shrink)

At present, most of the research in the field of medical-assisted diagnosis is carried out based on image or electronic medical records. Although there is some research foundation, they lack the comprehensive consideration of comprehensive image and text modes. Based on this situation, this article proposes a fusion classification auxiliary diagnosis model based on GoogleNet model and Bi-LSTM model, uses GoogleNet to process brain computed tomographic images of ischemic stroke patients and extract CT image features, uses Bi-LSTM model to extract (...) the electronic medical record text, integrates the two features using the full connection layer network and Softmax classifier, and obtains a method that can assist the diagnosis from two modes. Experiments show that the proposed scheme on average improves 3.05% in accuracy compared to individual image or text modes, and the best performing GoogleNet + Bi-LSTM model achieves 96.61% accuracy; although slightly less in recall, it performs better on F1 values, and has provided feasible new ideas and new methods for research in the field of multi-model medical-assisted diagnosis. (shrink)

In recent years, learning materials have gradually been applied to flipped classrooms. Teachers share learning materials, and students can preview the learning materials before class. During class, the teacher can discuss students' questions from their notes from previewing the learning materials. The social media platform Facebook provides access to learning materials and diversified interactions, such as sharing knowledge, annotating learning materials, and establishing common objectives. Previous studies have explored the effect of flipped classrooms on students' learning engagement, attitudes, and performance. (...) In this paper, we apply educational data mining to explore the relationship between students' viewing behaviors in accessing learning materials and their performance in flipped classrooms. The participants are classified into an experimental group and a control group to engage in flipped classroom activities. The experimental group uses the social media platform Facebook for flipped learning, and the control group uses a learning management system for flipped learning. The results show that there is a significant difference in the learning performance between the two groups, with the average score of the experimental group being higher than that of the control group. Furthermore, we find that the viewing behaviors and performance of the students within the experimental group differ significantly. (shrink)

BackgroundPrevious findings indicated that breast cancer patients often have dysfunction in empathy and other cognitive functions during or after chemotherapy. However, the manifestations and possible neuro-electrophysiological mechanisms of pain empathy impairment in breast cancer patients after chemotherapy were still unknown.ObjectiveThe current study aimed to investigate the potential correlations between pain empathy impairment and event-related potentials in breast cancer patients undergoing chemotherapy.MethodsTwenty-two breast cancer patients were evaluated on a neuropsychological test and pain empathy paradigm before and after chemotherapy, containing the Chinese (...) version of the Interpersonal Reactivity Index, while recording ERP data.ResultsThe empathic concern scores were lower and personal distress scores were higher on IRI-C task compared with those before chemotherapy. Meanwhile, the accuracy rates were lower than those before chemotherapy for both pain and laterality tasks on the pain empathy paradigm. However, the response time was no significant differences before and after chemotherapy. Further, the amplitude of the N1 component was significantly increased, and the amplitude of the P2 component was significantly decreased in the subsequent ERP study. A linear mixed effect model was used to analyze the correlation, the average amplitude of N1 and P2 were positively correlated with the accuracy rates in laterality tasks.ConclusionThe results indicated that pain empathy impairment was performed in chemotherapeutic breast cancer patients, which was possibly correlated to the changes of N1 and P2 components in ERP. These findings provide neuro-electrophysiological information about chemo-brain in breast cancer patients. (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)

本书内容包括：审美意识形态与中国马克思主义美学的理论建构、“社会主义文学生产方式”与中当代文学的现代性、文化研究与中国当代文学理论范式及其构成等。.

Ben shu yi "zhou xin shi dai" Zhongguo wen hua ren wen xing te zheng xing cheng ji qi dui Zhongguo zhe xue te zhi de su zao wei qie ru dian, zai xi tong shu li ru xue xin xing lun de ji ben zhu ti he li shi fa zhan, jie shi qi te zheng de ji chu shang, cong dao de yu sheng ming, dao de shi jian deng fang mian dui tang jun yi dao de (...) xing shang xue jin xing le shen ru de yan jiu. (shrink)

本书主要从五个方面对老庄生命哲学进行梳理和阐发.一是老庄生命哲学形成的原因分析.二是老庄的生命本质论.三是老庄的生命价值论.四是老庄的生命过程论.五是老庄的生命境界论.

juan 1. Shaoqu Feng xian sheng -- juan 2. Zhongfu Wang xian sheng -- juan 3-4. Erqu Li xian sheng.

本书阐述的是一种独特而圆润的人生哲学,在统揽古今中外人生哲学的基础上提出了自己认为的人生哲学。本书也是一种别开生面的中西简明哲学史,以人生哲学为切入点,对中国古代哲学、西方古典哲学以及欧美现代哲学等提 出了自己的真知灼见。.

本書並不是一部全面敘述馮友蘭的生平或前半生的傳記，也不是一部單純研究馮友蘭的學術或哲學思想的專著。而是有意以馮友蘭的民族主義思想的形成和發展為個案，藉著探究馮氏如何由一個傳統的士子，轉變為五四反傳統主 義者，又如何由五四反傳統主義者，再變為文化保守主義的重要柱石的學思經歷，來檢視馮友蘭前半生的心路和生命歷程。凡與此相關者則詳之，凡與此不相關或關係不密切者則略之.