We explore corporate environmental accountability by examining how carbon emissions affect voluntary climate-related information disclosure based on TCFD principles. Using computerized textual analysis to measure such climate-related disclosure, our results show that firms with higher levels of carbon emissions disclose more climate-related information. This relation is stronger in firms belonging to carbon-intensive industries, such as energy, materials, and utilities. We also examine this relationship at the category level for Governance, Strategy, Risk Management, and Metrics and Targets, finding that carbon emissions (...) drive disclosure in all categories except in Governance. Overall, our findings indicate that high carbon emitting firms appear to discharge their corporate accountability by increasing climate-related disclosure, consistent with legitimizing their potentially unethical actions and submitting to stakeholder and societal pressure. (shrink)

In 2022, the renowned historian Katja Guenther published “The Mirror and the Mind: A History of Self-Recognition in the Human Sciences.” Throughout the entirety of the book, Guenther meticulously t...

Biological pacemakers can be achieved by various gene‐based and cell‐based approaches. Embryonic stem cells (ESCs)‐derived pacemaker cells might be the most promising way to form biological pacemakers, but there are challenges as to how to control the differentiation of ESCs and to overcome the neoplasia, proarrhythmia, or immunogenicity resulting from the use of ESCs. As a potential approach to solve these difficult problems, tissue‐engineering techniques may provide a precise control on the different cell components of multicellular aggregates and the forming (...) of a construct with‐defined architectures and functional properties. The combined interactions between ESC‐derived pacemaker cells, supporting cells, and matrices may completely reproduce pacemaker properties and result in a steady functional unit to induce rhythmic electrical and contractile activities. As ESCs have a high capability for self‐renewal, proliferation, and potential differentiation, we hypothesize that ESCs can be used as a source of pacemaker cells for tissue‐engineering applications and the ambitious goal of biological cardiac pacemakers may ultimately be achieved with ESCs via tissue‐engineering technology. (shrink)

Biological pacemakers can be achieved by various gene‐based and cell‐based approaches. Embryonic stem cells (ESCs)‐derived pacemaker cells might be the most promising way to form biological pacemakers, but there are challenges as to how to control the differentiation of ESCs and to overcome the neoplasia, proarrhythmia, or immunogenicity resulting from the use of ESCs. As a potential approach to solve these difficult problems, tissue‐engineering techniques may provide a precise control on the different cell components of multicellular aggregates and the forming (...) of a construct with‐defined architectures and functional properties. The combined interactions between ESC‐derived pacemaker cells, supporting cells, and matrices may completely reproduce pacemaker properties and result in a steady functional unit to induce rhythmic electrical and contractile activities. As ESCs have a high capability for self‐renewal, proliferation, and potential differentiation, we hypothesize that ESCs can be used as a source of pacemaker cells for tissue‐engineering applications and the ambitious goal of biological cardiac pacemakers may ultimately be achieved with ESCs via tissue‐engineering technology. -/- . (shrink)

Due to the population ageing, building an elderly livable community has become an urgent task of social welfare development. This Public-Private Partnership construction project faces a variety of pressures from its complex stakeholders. Based on the Qingdao elderly livable community construction project, this paper builds up interpretations about its relationship governance by conducting stakeholder analysis. The paper aims to explore the relationship governance mechanism of multiple connections between related stakeholders. On the basis of complex network theory, this paper establishes a (...) stakeholder relationship network model and describes different modes of different stakeholder relationship in the Qingdao construction project. The paper analyzes the optimal decision-making behavior and interaction of different stakeholders, constructs the objective functions of stakeholder relationship network, applies centrality measure and dominant-set clustering to analyze the optimal conditions of the whole network, and finally carries out simulation calculation. The results show that it is feasible and effective to apply network analysis method to the study of stakeholder relationship in Public-Private Partnership construction projects. (shrink)

People often judge trustworthiness based on others’ faces (e.g., facial expression and facial gender). However, it is unclear whether social context plays a moderating role in forming trustworthiness judgments. Based on the emotions as social information (EASI) model, differing contexts may impact the effect of facial expression; however, there is no evidence demonstrating that differing contexts will or will not influence the effect of facial gender. In this study, we used two experiments to examine how facial expression and facial gender (...) affect facial trustworthiness judgments and whether the effects on facial trustworthiness judgments are consistent in cooperative and competitive settings. Twenty-seven undergraduates (14 female; Mage = 21.81 years, SD = 2.66) participated in experiment 1. The results showed significant main effects of facial expression and facial gender as well as the interaction between them. To examine the social context effect, 28 undergraduates (18 female; Mage = 20.93 years, SD = 2.94) participated in experiment 2. The results showed the main effects of facial expression, facial gender, and social context. Moreover, there was a significant interaction between facial gender and facial expression and a marginally significant interaction between social context and facial expression. These results suggest that in the process of judging facial trustworthiness, individuals’ judgments are affected by both facial expression and facial gender. Furthermore, the effect of facial gender on facial trustworthiness judgments presents cross-situational stability, and the role of facial expression is influenced by the settings. These findings support and expand the EASI model. (shrink)

Objectives: The corona virus disease-2019 pandemic spread globally, and we aimed to investigate the psychosocial impact on healthcare workers in China during the pandemic.Methods: In this systematic review and meta-analysis, we searched seven electronic databases for cross-sectional studies on psychosocial impact on HWs in relation to COVID-19 from January 1, 2020 to October 7, 2020. We included primary studies involving Chinese HWs during the pandemic, and data were extracted from the published articles. Our primary outcome was prevalence of anxiety, depression, (...) and stress disorders. We pooled prevalence value with their 95% confidence interval using random effect models and assessed study quality on the basis of an 11-item checklist recommended by the Agency for Healthcare Research and Quality. The study protocol was registered in PROSPERO.Results: We identified 25 articles comprising a total of 30,841 completed questionnaires and 22 studies for meta-analysis. The prevalence of anxiety, depression, and stress disorders was 34.4%, 31.1%, and 29.1% for HWs. The pooled prevalence of anxiety disorders for HWs from late January to early February was 46.4%, significantly higher than those in mid-term February and after late February. The pooled prevalence of depression disorders for HWs from late January to early February was 46.5%, significantly higher than those in mid-term February and after late February. HWs working in Hubei Province had a higher prevalence of anxiety and a lower prevalence of depression than those working in other regions. Nurses had a higher prevalence of anxiety and depression than other HWs.Conclusions: About one-third of HWs in China suffered anxiety, depression, and stress at the early epidemic of COVID-19. HWs in Hubei Province, especially nurses, had a higher prevalence of psychological disorders. During the pandemic, a negative psychological state may persist in a proportion of Chinese HWs, fluctuating with the control of the pandemic. The long-term impact should continue to be observed. Attention should be paid to HWs for their psychological impact due to the pandemic.Systematic Review Registration: The study protocol was registered with PROSPERO. (shrink)

Smart grids are rolling out internationally, with the United States nearing completion of a significant USD4-plus-billion federal program funded under the American Recovery and Reinvestment Act. The emergence of smart grids is widespread across developed countries. Multiple approaches to analyzing the benefits of smart grids have emerged. The goals of this white paper are to review these approaches and analyze examples of each to highlight their differences, advantages, and disadvantages. This work was conducted under the auspices of a joint U.S.-China (...) research effort, the Climate Change Working Group Implementation Plan, Smart Grid. We present comparative benefits assessments of smart grid demonstrations in the U.S. and China along with a BA of a pilot project in Europe. In the U.S., we assess projects at two sites: the University of California, Irvine campus, which consists of two distinct demonstrations: Southern California Edison’s Irvine Smart Grid Demonstration Project and the UCI campus itself; and the Navy Yard area in Philadelphia, which has been repurposed as a mixed commercial-industrial, and possibly residential, development. In China, we cover several smart-grid aspects of the Sino-Singapore Tianjin Eco-city and the Shenzhen Bay Technology and Ecology City. In Europe, we look at a BA of a pilot smart grid project in the Malagrotta area west of Rome, Italy, contributed by the Joint Research Centre of the European Commission. The Irvine sub-project BAs use the U.S. Department of Energy Smart Grid Computational Tool, which is built on methods developed by the Electric Power Research Institute. The TEC sub-project BAs apply Smart Grid Multi-Criteria Analysis developed by the State Grid Corporation of China based on the analytic hierarchy process with fuzzy logic. The B-TEC and TNY sub-project BAs are evaluated using new approaches developed by those project teams. JRC has adopted an approach similar to EPRI’s but tailored to the Malagrotta distribution grid. (shrink)

This research focuses on students' online purchase intentions in Pakistan toward different products available for sale on numerous e-business websites. This study's main objective is to determine which methodology is better to enhance customer online purchase intention. It also aims to discover how to improve perceived benefits and lower perceived risks associated with any available online product and entrepreneurship. AMOS 24 has been used to deal with the mediation in study design with bootstrap methodology. The study was conducted on 250 (...) students from different educational institutes in Pakistan using a simple random sampling technique. A finding of this study suggests that both methods positively impact online purchase intention of consumers and sustainable digital economy. But social media advertisement is more effective through enhancing the perceived benefits of products. In contrast, product content factors are more effective at lowering the perceived risks associated with available online products. (shrink)

With the increase in depth of coal mining, the hydrogeological complexity largely increases and water inrush accidents happen more frequently. For the safety of coal mining, horizontal directional drilling and grouting techniques have been implemented to detect and plug the fractures and conduits that deliver high-pressure groundwater to coal mine. Taking the grouting engineering performed at Xingdong coal mine at 980 m below sea level as an example, we collected the data of grouting quantity, the loss of drilling fluid, gamma (...) value, water temperature, average water absorption, distance between grouting loss points, water pressure on coal seam floor, and aquifuge thickness at 90 boreholes in the mine to conduct grey relational analysis, first. The analysis showed that the grouting quantity was highly correlated with all other factors. Subsequently, grey system evaluation was used to evaluate the risk of water inrush from the coal seam floor. The results of risk analysis illustrated that three water inrushes from Ordovician limestone occurred in mining face 2127, 2125, and 2222 in the study area were all located in the area with a risk score higher than 65. Through grouting, the identified cracks were effectively blocked and waterproof layers beneath the coal seam floors were constructed to reduce the threat of water inrush. By comparing the risk assessment results with three water inrush cases before grouting operation, we found that water inrush areas were consistent with the area of higher risk. (shrink)

Despite the fact that the number of neurons in the human brain has been identified in cognitive and neural sciences, the magnitude of human memory capacity is still unknown. This paper reports the discovery of the memory capacity of the human brain, which is on the order of 10 8432 bits. A cognitive model of the brain is created, which shows that human memory and knowledge are represented by relations, i.e., connections of synapses between neurons, rather than by the neurons (...) themselves as the traditional container metaphor described. The determination of the magnitude of human memory capacity is not only theoretically significant in cognitive science, but also practically useful to unveil the human potential, as well as the gap between the natural and machine intelligence. (shrink)

Drawing upon conservation of resources theory, we develop and test a theoretical model that specifies how and when employee humor toward leaders affects leader abusive supervision. We propose that employee humor is negatively associated with leader abusive supervision via leader relational energy. Furthermore, the negative indirect relationship between employee humor and leader abusive supervision via leader relational energy is stronger for female leaders than for male leaders. An experiment and a multi-wave, multi-source field study provide substantial support for our hypotheses. (...) Our findings contribute to the abusive supervision literature by identifying employee humor as a safe and effective bottom-up approach to prevent leader abusive supervision. (shrink)

Background: There is a growing need to offer appropriate services to persons with mild cognitive impairment and dementia who are faced with depression and anxiety distresses beyond traditional pharmacological treatment. Dance-based interventions as multi-dimensional interventions address persons' physical, emotional, social, and spiritual aspects of well-being. However, no meta-analysis of randomized controlled treatment trials has examined the effectiveness of dance-based interventions on depression and anxiety among persons with MCI and dementia, and the results of RCTs are inconsistent. The study aimed to (...) examine the effectiveness of dance-based interventions on depression and anxiety among persons with MCI and dementia.Methods: A systematic review with meta-analysis was conducted. The inclusion criteria were: population: people of all ages with MCI and dementia; intervention: dance-based interventions; control group: no treatment, usual care, or waiting list group; outcome: depression and anxiety; study design: published or unpublished RCTs. Seven electronic databases were searched from 1970 to March 2021. Grey literature and reference lists from relevant articles were also searched and reviewed. The Cochrane “Risk of Bias” tool was used to assess study quality. RevMan 5.4 was used for meta-analysis and heterogeneity was investigated by subgroup and sensitivity analysis. GRADE was applied to assess the evidence quality of depression and anxiety outcomes.Results: Five randomized controlled trials were identified. Sample sizes ranged from 21 to 204. The risk of bias was low, except for being rated as high or unclear for most included studies in two domains: allocation concealment, blinding participants and personnel. Meta-analysis of depression outcome showed no heterogeneity, indicating that the variation in study outcomes did not influence the interpretation of results. There were significant differences in decreasing depression in favor of dance-based interventions compared with controls [SMD = −0.42, 95% CI, p < 0.0001] with a small effect size ; Compared with the post-intervention data, the follow-up data indicated diminishing effects. Dance-based interventions were more effective in reducing depression for persons with dementia than with those having MCI, and were more effective with the delivery frequency of 1 h twice a week than 35 min 2–3 times a week. Also, one included RCT study showed no significant benefit on anxiety rating scores, which demonstrated small effect sizes at 6 weeks and 12 weeks. GRADE analysis indicated the evidence quality of depression was moderate, and the evidence quality of anxiety was low.Conclusions: Dance-based interventions are beneficial to alleviate depression among persons with MCI and dementia. More trials of high quality, large sample sizes are needed to gain more profound insight into dance-based interventions, such as their effects of alleviating anxiety, and the best approaches to perform dance-based interventions. (shrink)

Numerous studies have focused on the understanding of rapid automatized naming, which can be applied to predict reading abilities and developmental dyslexia in children. Eye tracking technique, characterizing the essential ocular activities, might have the feasibility to reveal the visual and cognitive features of RAN. However, traditional measures of eye movements ignore many dynamical details about the visual and cognitive processing of RAN, and are usually associated with the duration of time spent on some particular areas of interest, fixation counts, (...) revisited fixation counts, saccadic velocities, or saccadic amplitudes. To cope with this drawback, we suggested an entropy-based method to measure eye movements for the first time, which first mapped eye movements during RAN in a time-series and then analyzed the time-series by a proper definition of entropy from the perspective of information theory. Our findings showed that the entropy was more sensitive to reflect small perturbation of eye movements, and thus gained better performance than traditional measures. We also verified that the entropy of eye movements significantly deceased with the age and the task complexity of RAN, and significantly correlated with traditional eye-movement measures [e.g., total time of naming ] and the RAN-related skills [e.g., selective attention, cognitive speed, and visual-motor integration]. Our findings may bring some new insights into the understanding of both RAN and eye tracking technique itself. (shrink)

The diffusion of codes is an important processing technology for big data networks. In previous scheme, data analysis was conducted for small samples of big data and complex problems that cannot be processed by big data technology. Due to the limited capacity of intelligence device, a better method is to select a set of nodes to form a connected dominating set to save energy, and constructing CDS is proved to be a complete NP problem. However, it is a challenge to (...) reduce the communication delay and complexity for urgent data transmission in big data. In this paper, an appropriate duty cycle control scheme is proposed to reduce communication delay and complexity while improving energy efficient in CDS-based WSNs. In ADCC scheme, the method for constructing CDS is proposed at lower complexity. Nodes in CDS are selected according to the degree of nodes. Then, duty cycle of dominator nodes in CDS is higher than that of dominated nodes, so the communication delay in the proposed scheme is far less than that of previous scheme. The duty cycle of dominated nodes is small to save energy. This is because the number of dominator nodes in CDS is far less than the number of dominated nodes whose duty cycle is small; thus, the total energy consumption of the network is less than that of the previous scheme. As a result, the performance of energy consumption and communication delay and complex have been improved. Its complexity O∑i=0vm−i+2m−2v−s is reduced a lot for big data. The theoretical analysis shows that compared to the previous scheme, the transmission delay can be reduced 25–92% and the energy efficiency is improved by about 80% while retaining network lifetime. (shrink)

In recent years, sports have achieved rapid development worldwide, and the global economy has been significantly improved and improved. With the in-depth development of the two, the connection between sports and the economy has also become closer. Sports economy is a new type of economic form bred by specialization of sports organization, participation in consumerization, and profit-oriented operation under the condition of market economy. And the development of sports economy cannot be developed at once; it needs healthy and sustainable development. (...) In order to find a better way to study the healthy and sustainable development of sports economy, this paper uses deep learning network algorithm and supports vector machine learning algorithm to build a mental model. It then uses the model to analyze various indicators of the sports industry in a province in China. This article is looking for information and summarizes the province’s sports data from 2017 to 2021. The sports indicators of this experiment include regional GDP, total output of sports industry, sports practitioners, local financial sports expenditures, the number of policies, the number of people participating in physical exercise, and fitness venues and facilities. The realization results show that these variables develop at a relatively small rate under normal conditions, and then predict the data in the next few years under the healthy and sustainable development of the next few years through the mental model. The growth rates of various indicators of the sports economy have increased significantly, and they have been optimized by about 20% compared with the normal development. (shrink)

Live streaming e-commerce, as a kind of new information technology-based business model, is currently the most popular marketing approach, especially in China. This research divides live streaming interactions into three dimensions, interactions for obtaining product information, interactions for grasping the purchase dynamics of others, and interactions for obtaining monetary incentives, and proposes a comprehensive framework to examine whether live streaming interactions with consumers promote both social presence and consumer conformity, and thereby enhance their purchase intentions. Covariance-based structural equation modeling with (...) AMOS was conducted to analyze data collected from 576 Chinese consumers. The main findings are that, first, both IPI and IPD can exert a direct impact on social presence and consumer conformity; second, IMI has a positive impact only on social presence; third, among the three dimensions of interactions, both IPI and IPD tend to increase purchase intention through social presence and consumer conformity, while IMI increases purchase intention only via social presence. Furthermore, given the differences between experience and search products, the results of the multigroup analysis indicate inconsistent path coefficients between the two product groups. This study provides a novel perspective on live streaming e-commerce with evidence on how interactions matter in driving purchase intentions, enriches the content of live streaming e-commerce literature and explores the practical implications for marketing managers are looking for marketing by live streaming. (shrink)

With the rapid development of the Internet, recommendation systems have received widespread attention as an effective way to solve information overload. Social tagging technology can both reflect users’ interests and describe the characteristics of the items themselves, making group recommendation thus becoming a recommendation technology in urgent demand nowadays. In traditional tag-based recommendation systems, the general processing method is to calculate the similarity and then rank the recommended items according to the similarity. Without considering the influence of continuous user behavior, (...) in this article, we propose a personalized recommendation algorithm based on social tags by combining the ideas of Markov chain and collaborative filtering. This algorithm splits the three-dimensional relationship of into two two-dimensional relationships of and. The user’s interest degree to the tags is calculated by the Markov chain model, and then the items corresponding to them are matched by the recommended tag set. The influence between tags is used to model the satisfaction of items based on the correlation between the tags contained in the matched items, and collaborative filtering is used to complete the sparse values when calculating the interest and satisfaction between user–tags and user–items to improve the accuracy of recommendations. The experiments show that in the publicly available dataset, the personalized recommendation algorithm proposed in this article has significantly improved in accuracy and recall rate compared with the existing algorithms. (shrink)

In 2020, the sudden outbreak of coronavirus disease 2019 has had a great impact on the health and life of people all over the world, and the sports industry is facing unprecedented challenges due to its participation and strong clustering. Based on the questionnaire survey, literature analysis, and other research methods, this study introduces the stimulus-organism-response theory, takes the sports and consumption of Kunshan citizens as the research subject, and draws lessons from the structural equation model to build a theoretical (...) model of sports consumption characteristics and future consumption willingness. The results of empirical analysis show that physical sports consumption has been greatly affected by the epidemic, but because people realize the importance of sports, the willingness of residents to consume sports increases, and the venue and other factors affect the ornamental and participating sports consumption willingness decreases. At the same time, the restrictive factors, such as lower educational background, increased age, and lack of time, make the sports consumption willingness of this characteristic group significantly lower than that of other citizens. This study puts forward some suggestions for relevant government departments to improve the sports consumption willingness of citizens. In order to expand the development prospect of sports industry from a long-term perspective, it can provide reference for the development of sports consumption. (shrink)

Purpose: This study aimed to explore the relationship between mathematic achievement and programming self-efficacy, and adopt a mediation model to verify the mediating role of creativity on the relationship between mathematic achievement and programming self-efficacy.Methods: A total of 950 upper-secondary school students were surveyed using their math test scores, the Kirton Adaption-Innovation and the Programmed Self-Efficacy Scale. SPSS-26 was used for descriptive statistical analysis and correlation analysis of related variables. The PROCESS plugin was used to test the mediating effect of (...) creativity.Results: Mathematic achievement has a positive effect on programming self-efficacy, mathematic achievement is positively related to creativity, and creativity also has a positive influence on programming self-efficacy. Creativity has a mediating effect on the relationship between mathematic achievement and programming self-efficacy.Conclusion: The results revealed that mathematic achievement affected programming self-efficacy directly and also indirectly through creativity. This provided certain ideas for the development of programming education for teenagers. Since students’ mathematics learning and creativity are related to programming learning, it is necessary to pay attention to the integration of the disciplines of programming education and mathematics. Further, the cultivation of innovative thinking is also critical to facilitate programming learning. (shrink)

ObjectiveThis study aims to investigate anxiety and its influencing factors in patients with drug-induced liver injury (DILI).Materials and MethodsNinety-four patients with DILI were enrolled and evaluated with a self-rating anxiety scale (SAS). According to the anxiety score, they were divided into four groups: the non-anxiety, mild anxiety, moderate anxiety, or severe anxiety groups, and the scores were analyzed based on demographic and biochemical indicators.ResultsOf the 94 patients with DILI, 63 did not have anxiety and 31 had anxiety (32.9%), of which (...) 27 had mild, 3 had moderate, and 1 had severe anxiety. There were no statistically significant differences in gender, age, occupation, and level of education between the groups (F= 1.42,H= 2.361,H= 6.751,H= 1.796, andP> 0.05); anxiety score and degree of anxiety between the types of drugs that led to the liver injury (H= 0.812,H= 1.712, andP> 0.05); anxiety score between the different degrees of liver injury (H= 2.836,H= 4.957,P> 0.05); or length of hospital stay or prognosis between the degrees of anxiety (F= 1.487,H= 0.761,P> 0.05). However, there were statistically significant differences in the degree of anxiety between different degree and types of liver injury (H= 7.981,H= 8.208,P< 0.05).ConclusionPatients with DILI may have anxiety, especially mild anxiety. The occurrence of anxiety in patients with DILI is not related to gender, age, occupation, or level of education but may be related to the degree and type of liver injury. Anxiety has no impact on the length of stay in hospital or the prognosis of the DILI. These findings may contribute to the development of management strategies for patients with DILI. (shrink)

Network embedding aims to learn the low-dimensional representations of nodes in networks. It preserves the structure and internal attributes of the networks while representing nodes as low-dimensional dense real-valued vectors. These vectors are used as inputs of machine learning algorithms for network analysis tasks such as node clustering, classification, link prediction, and network visualization. The network embedding algorithms, which considered the community structure, impose a higher level of constraint on the similarity of nodes, and they make the learned node embedding (...) results more discriminative. However, the existing network representation learning algorithms are mostly unsupervised models; the pairwise constraint information, which represents community membership, is not effectively utilized to obtain node embedding results that are more consistent with prior knowledge. This paper proposes a semisupervised modularized nonnegative matrix factorization model, SMNMF, while preserving the community structure for network embedding; the pairwise constraints information are effectively fused with the adjacency matrix and node similarity matrix of the network so that the node representations learned by the model are more interpretable. Experimental results on eight real network datasets show that, comparing with the representative network embedding methods, the node representations learned after incorporating the pairwise constraints can obtain higher accuracy in node clustering task and the results of link prediction, and network visualization tasks indicate that the semisupervised model SMNMF is more discriminative than unsupervised ones. (shrink)

BackgroundPublished data and practice recommendations on end-of-life care generally reflect Western practice frameworks; there are limited data on withdrawal of treatment for children in China.MethodsWithdrawal of treatment for children in the pediatric intensive care unit of a regional children’s hospital in eastern China from 2006 to 2017 was studied retrospectively. Withdrawal of treatment was categorized as medical withdrawal or premature withdrawal. The guardian’s self-reported reasons for abandoning the child’s treatment were recorded from 2011.ResultsThe incidence of withdrawal of treatment for children (...) in the PICU decreased significantly; for premature withdrawal the 3-year average of 15.1% in 2006–2008 decreased to 1.9% in 2015–2017. The overall incidence of withdrawal of care reduced over the time period, and withdrawal of therapy by guardians was the main contributor to the overall reduction. The median age of children for whom treatment was withdrawn increased from 14.5 months in 2006 to 40.5 months in 2017. Among the reasons given by guardians of children whose treatment was withdrawn in 2011–2017, “illness is too severe” ranked first, accounting for 66.3%, followed by “condition has been improved”. Only a few guardians ascribed treatment withdrawal to economic reasons.ConclusionsThe frequency of withdrawal of medical therapy has changed over time in this children’s hospital PICU, and parental decision-making has been a large part of the change. (shrink)

本书是“以赛亚·伯林与当代中国国际研讨会”论文集,汇集了国内外著名学者伯林研究的最新成果,从伯林语境下自由与多元的关系出发,探讨了伯林思想对当代中国的经验与智慧有着怎样的启迪意义.