Lei Yu

Window opening behavior in residential buildings has important theoretical significance and practical value for improving energy conservation, indoor thermal comfort, and indoor air quality. Climate and cultural differences may lead to different window opening behavior by residents. Currently, research on residential window opening behavior in northwest China has focused on indoor air quality, and few probabilistic models of residential window behaviors have been established. Therefore, in this study, we focused on an analysis of factors influencing window opening behavior and the establishment of a predictive model for window opening behavior. Four typical residential buildings in different locations and building types in Xi’an were selected. The indoor and outdoor environments and window opening states were measured. Subsequently, a multivariate analysis of variance was used to determine the factors that had a significant effect on window opening behavior. Single- and multiparameter logistic regression models for window opening behavior were established. Of all the measured factors, we found that indoor temperature and CO2 concentration, outdoor temperature, and relative humidity had significant effects on window opening behavior, and indoor relative humidity and noise did not. Meanwhile, the temperature was positively correlated with the window opening probability, whereas indoor CO2 concentration and outdoor relative humidity were negatively correlated. The prediction accuracy of the multiparameter model was promising, at almost 75%, and the model can provide theoretical support for modelling residential buildings in Xi’an.

Background: Both anxiety and depression in family caregivers of advanced cancer patients are common, and they have a negative influence on both the FCs and the patients. Some studies suggested that a variety of interventions could alleviate the psychological symptoms of FCs. However, there is no consensus on much more effective methods for intervention, and relatively high-quality research is blank in psychological problems of these population in China. The validity of mindfulness-based stress reduction and psychological consultation guided by the needs assessment tool in the psychological status of caregivers will be compared in this study to select a more suitable intervention for the FCs of advanced cancer patients in China.Methods and Analysis: A randomized N-of-1 trial would be conducted at the Cancer Hospital, Chinese Academy of Medical Sciences. Fifty eligible FCs of advanced cancer patients will be recruited, and all will receive three cycles of psychological intervention treatment, with each cycle including both of MBSR and psychological consultation guided by the NST. MBSR and psychological consultation guided by the NST will be compared with each other in each cycle, and the intervention sequence will be based on the random number table generated after the informed consent has been completed. Each treatment period is 2 weeks, and the interval between different treatment cycles or treatment periods is 1 week. The self-reported scales are measured at the beginning and end of each treatment period, including the Self-Rating Anxiety Scale, the Self-Rating Depression Scale, Distress Thermometer, Zarit Burden Interview, Chinese version of the Medical Outcomes Study 12-item Short Form, and Family Carer Satisfaction with Palliative Care scale.Dissemination: The protocol of the study was approved by the Institutional Review Board of the Ethical Committee of the Cancer Hospital, Chinese Academic of Medical Science. The results will be published in a peer-reviewed medical journal. The study is registered at Chinese Clinical Trials Registry with the trial registration number chiCTR2000033707. This study employs an innovative methodological approach on the effectiveness of MBSR and psychological consultation guided by the NST for psychological status of FCs of advanced cancer patients. The findings of the study will be helpful to provide high-quality evidence-based medical data for psychological intervention of FCs of advanced cancer patients, and guide clinicians on best quality treatment recommendations.

Large-screen human-computer interaction technology is reflected in all aspects of daily life. The dynamic gesture tracking algorithm commonly used in recent large-screen interactive technologies demonstrates compelling results but suffers from accuracy and real-time problems. This paper systematically addresses these issues by a switching federated filter method that combines particle filtering and Mean Shifting algorithms based on a 3D sensor. Compared with several algorithms, the results show that the one-hand and two-hand large-screen gesture tracking based on the switched federated filtering algorithm work well, and there is no tracking failure and loss of target. Therefore, the switching federated tracking positioning algorithm can be well applied to the design of human-computer interaction system and provide new ideas for future human-computer interaction.

Large-screen human-computer interaction technology is reflected in all aspects of daily life. The dynamic gesture tracking algorithm commonly used in recent large-screen interactive technologies demonstrates compelling results but suffers from accuracy and real-time problems. This paper systematically addresses these issues by a switching federated filter method that combines particle filtering and Mean Shifting algorithms based on a 3D sensor. Compared with several algorithms, the results show that the one-hand and two-hand large-screen gesture tracking based on the switched federated filtering algorithm work well, and there is no tracking failure and loss of target. Therefore, the switching federated tracking positioning algorithm can be well applied to the design of human-computer interaction system and provide new ideas for future human-computer interaction.