Background: Existing evidence on the association between sedentary behavior (SB) and cognitive function remains inconclusive. Therefore, this study investigated the association between SB and the risk of cognitive decline (CD) or mild cognitive impairment (MCI) in the elderly.Methods: A comprehensive search was independently conducted by two researchers (XC and GQ) in seven electronic databases, including Medline (via PubMed), China Biology Medicine, Embase, Web of Science, China National Knowledge Infrastructure, Wanfang database, and VIP database for Chinese technical periodicals, covering studies published from the inception of database to June 2023. Studies that investigated the relationship between SB and the risk of CD or MCI in the elderly were included. The quality of the literature was assessed using the Newcastle–Ottawa Scale (NOS) and the Agency for Healthcare Research and Quality (AHRQ) assessment tools. The combined effect size analysis, subgroup analysis, and publication bias assessment were performed using STATA 14.0.Results: A total of 13 cross-sectional and 6 cohort studies involving 81,791 individuals were included, comprising 17 high-quality studies and 2 medium-quality studies. We found that SB was significantly associated with an increased risk of CD [odds ratio (OR) = 1.69, 95% confidence intervals (CI): 1.47–1.94] or MCI (OR = 1.34, 95% CI: 1.14–1.56) among the elderly. Subgroup analysis stratified according to comorbidity, lifestyle, family structure, publication year, and region showed statistical differences between groups, and the consistency of the results revealed the sources of the heterogeneity.Conclusion: This meta-analysis showed that SB is positively associated with the risk of CD or MCI in the elderly, providing a higher level of evidence for the promotion of healthy behaviors by clinicians and health policymakers. Due to the number and quality of the included articles, more high-quality longitudinal studies are needed to further confirm our findings.

The increasing integration of renewable forms of energy into building energy systems raises the need for the use of more complex energy conversion and distribution systems. These are often equipped with complex automation systems, which require methods for structured development of control algorithms. In practice, textual descriptions of control algorithms represent a considerable source of failures. The digitization of the planning process is a core element in facilitating control development and supporting the engineering in the process automation. With regard to the digitization of the planning process, we have introduced the MODI-method in previous work. This method allows structured control development in early stages of the planning process and can be extended by performing simulations, i.e. an algorithm implemented as a Petri-Net. In this paper, we investigate the integration of this method into the simulation-based planning and an approach to model an algorithm based on Petri-Net. The case study shows the functionality of this method and the modeling approach. In future work, the MODI-method will be compared with other control strategies and applied in complex systems for further development.

Faulty programming of control functions in Building Automation and Control Systems (BACS) might result in inefficient building operations. To reduce programming errors, an automated implementation process of control functions might be a promising solution. Recently, Building Information Modeling (BIM) contributes to digitizing building construction projects but is rarely used in the planning and implementation of control functions in BACS. The control description in BIM also remains unclear. Regarding these problems, a control documentation method for BIM and an automated control implementation approach can simplify control implementation in BACS and hence improve the building operation. In the previous work, we developed the MODI method for a structured planning process of mode-based control algorithms for building energy systems. This method showed the potential to support digitized control planning and implementation in BACS. Based on this, in this paper, we introduce a documentation method to report mode-based control algorithms in the industrial foundation class (IFC), enabling data sharing among BIM, and a software-assisted approach to automatically generate PLC codes for implementing these algorithms. The case study demonstrates the documentation of a desired mode-based control strategy for an energy supply network in IFC and the implementation of this strategy in a PLC program. In the simulation phase, we test the implemented control strategy to verify the functionalities of the PLC program. The results prove that mode-based control strategies can be fully automatically implemented in a PLC program based on IFC data.

The growing share of renewable energy sources in building energy systems leads to more complex energy conversion and distribution systems. The current process of developing appropriate control functions for energy systems is insufficient and consequently error-prone. Regarding this problem, a new method is expected to systematically develop appropriate control functions for buildings and reduce design errors in this process. This paper introduces the MODI method, aiming at a structured development process of mode-based control algorithms to reduce errors in the early design stages of buildings. A complete framework and a standardized application process of the MODI method will be established to systematically design mode-based control algorithms described through signal-interpreted Petri nets. Furthermore, we performed a simulation-assisted evaluation approach to test and improve the performance of the control algorithms generated by MODI. In a case study, we applied MODI to develop a mode-based control strategy for an energy system containing heating and cooling supply networks. The desired control strategy was tested and tuned in a simulation phase. Compared to a reference control, the mode-based control algorithm shows an improvement in system efficiency by 4% in winter and 8% during the transitional season phase.

The increasing use of renewable energy in building energy systems has brought considerable challenges for the traditional planning process to develop appropriate control strategies. In previous work, we have introduced the MODI method to support the structured development of mode-based control algorithms, in which operating modes are core elements. However, modeling of energy systems and control algorithms for control tests is time-consuming and error-prone. Identification of permissible operating modes is also unfeasible. The paper introduces a methodology to identify permissible operating modes and model energy systems with mode-based control algorithms in the modeling language Modelica automatically. In the case study, we apply the methodology for an energy supply network and verify the functionality of the methodology. In future work, automated optimization of control algorithms will be integrated into the methodology.