A vision driven wayfinding simulation system based on the architectural features perceived in the office environment

Human wayfinding in the built environment is extensively investigated in the last 50 years. One major aspect of the outcome is the decision made on the egresses based on the information perceived during the wayfinding. Information acquired of the environment could be categorized into several types, namely the verbal (information obtained from the reception, staff members, etc.), the graphic (map of the environment, signage showing the location or pointing to certain location, etc.), the architectural (entrances, stairs, corridors, etc.), and the spatial (spatial relationship of objects in the environment). Early analyses of indoor wayfinding suggested that signage and colour codes could provide landmarks, but the addition of these cues after construction can be futile. This suggests that, architectural information has a significant influence on individual’ s decision making. However, inmost researches, the function of the architectural information was underestimated -- it was often treated as the constraint of the architectural spaces. The presented research aims at developing of an agent-based system that can find certain destination in a virtual office building environment using artificial vision and cognition based on the architectural features in this built environment. During the wayfinding, this agent’ s egress choices follows an estimated model that based on experimental data with real human. Before running the experiments with real humans, pre-experiments were conducted to investigate the conditions for vision research using standard LCD monitors. The thresholds obtained in the pre-experiments for lighting in the virtual environment and for the testing environment served as input to the development of the following experiments. In the first experiment subjects were asked to make choices between two egresses in a sequence of isolated convex rooms. The architectural features of these rooms and of the egresses were varied systematically. The room features included: size and colour; while the egress features were: colour, distance, angle and width. From the collected data a preference function was estimated on egress choice given the architectural features. In the second experiment the assignment was to find the destination and then return to the start in a virtual building. Subjects executed three different assignments given different locations for the destination and the start, and every assignment was repeated two to three times subsequently. Each subject’ s routes in the experiments were recorded. From these routes search strategies used for wayfinding were determined, namely: Orientation Based, Architectural Features Based, Boundary Based, Random Choice, Minimum rooms and Shortest Distance. A preference function was estimated for the next room choice, based upon the architectural features of the current room, and the given familiarity of the environment. The implemented agent uses a simplified version of the virtual building model. This simplified version only includes those architectural elements and features that are relevant for vision driven navigation, i.e. the type of egress, egress colour, egress width, room colour and room size. Room colour is converted into three levels of grey. The agent’ s wayfinding behaviour is validated with the hit ratio, the average visit frequency of each room, and the average total number of rooms visited, respectively. The agent-based simulation system developed in not only an interpretation of the empirical findings obtained from the research, but it is also applicable for testing and evaluation purposes in architectural design problems. After certain transformations, a CAD model of an office environment can be presented to the simulation system as input. By setting the wayfinding task, the designed agent can be employed to predict how individuals may behave in this office environment in reality. This helps the architects, with regard to wayfinding efficiency and space utility, to improve their design

NiO hollow microspheres interconnected by carbon nanotubes as an anode for lithium ion batteries

In this work, NiO hollow microspheres interconnected by multi-walled carbon nanotubes (MWCNTs) were prepared, characterized, and evaluated in terms of lithium ion storage properties. Characterization results showed that the NiO hollow microspheres were formed by self assembly of NiO nanoparticles promoted by MWCNTs, which connected the NiO microspheres to form a long-range network. Electrochemical measurement results showed a charge capacity as high as 597.2 mAh g when cycling at the rate 2 C and maintained 85.3% capacity of 0.1 C. After cycling for 100 times at 1 C, it maintained a capacity of 692.3 mAh g with retention 89.3% of the initial capacity. The observed excellent electrochemical performance is attributed to the presence of MWCNTs interconnecting the NiO microspheres of the composite material, of which electronic conductivity was improved, and the mesoporous hollow structure effectively alleviated the volume changes to maintain the structural stability during cycling

Reactive Oxygen Species Affect the Tenderness of Bovine Muscle by Regulating Glycolysis during the Early Stage of Postmortem Cold Storage

This study was conducted to investigate the regulatory mechanism of reactive oxygen species (ROS) on the glycolysis pathway of bovine muscle and its impact on meat tenderness at the early stage of postmortem cold storage. Fresh beef was treated with hydrogen peroxide (H2O2) as a major ROS, N-acetyl-L-cysteine (NAC) as an ROS scavenger, or physiological saline as a control before being stored at 4 ℃. After 0.5, 6, 12, 24, and 48 hours, the glycolysis level and tenderness indices were assessed. In addition, tandem mass tag (TMT)-labeled quantitative proteomics was used for protein identification and quantitative analysis of the samples after 24 hours and for screening of differential proteins in the glycolysis pathway. The findings showed that the glycolysis level increased significantly in the H2O2-treated group, and glycogenolysis and lactic acid accumulation were significantly higher than those in the other two groups (P < 0.05). In contrast, the glycolysis process was significantly suppressed by NAC treatment. The H2O2-treated group reached the ultimate pH after 12 hours, 12 and 36 hours earlier than the control and NAC groups, respectively. The shear force of the H2O2-treated group reached its maximum after 12 hours, and the myofibrillar fragmentation index (MFI) was significantly greater than that of the other two groups after 6–48 hours (P < 0.05), indicating that a higher ROS level can accelerate the tenderization of bovine muscle by enhancing the glycolysis capacity during postmortem refrigeration. Totally eight up-regulated proteins and two down-regulated proteins in the glycolysis pathway were identified in the H2O2-treated versus control groups after 24 hours of refrigeration. Among these proteins, the up-regulated core proteins of phosphoglycerate mutase (PGAM), enolase (ENO), and pyruvate dehydrogenase E1 subunit beta (PDHB) coordinated with the down-regulated pyruvate dehydrogenase E1 subunit alpha (PDHA) to accelerate the glycolysis process. In conclusion, ROS can speed up glycolysis and consequently improve meat tenderness by regulating the expression of key proteins in the glycolysis pathway

From concept to action: a united, holistic and One Health approach to respond to the climate change crisis

It is unequivocal that human influence has warmed the planet, which is seriously affecting the planetary health including human health. Adapting climate change should not only be a slogan, but requires a united, holistic action and a paradigm shift from crisis response to an ambitious and integrated approach immediately. Recognizing the urgent needs to tackle the risk connection between climate change and One Health, the four key messages and recommendations that with the intent to guide further research and to promote international cooperation to achieve a more climate-resilient world are provided

Management Policy of Farmers&rsquo; Cultivated Land Abandonment Behavior Based on Evolutionary Game and Simulation Analysis

Agricultural land abandonment is a complex, multidimensional, and nonlinear global phenomenon driven by multiple factors and has contrasting impacts on agrobiodiversity, the environment, and society. Appropriate management strategies on abandoned cultivated land are helpful in maintaining food and ecological security. However, there are few studies on the management of cultivated land abandonment from the perspective of stakeholders. Based on the stakeholder perspective and focusing on the two main modes of farmland abandonment management, namely, &ldquo;transfer-oriented management&rdquo; and &ldquo;condition-improved management&rdquo;, this study constructs two evolutionary game models to analyze the interest conflicts, decision-making behaviors and interest game foci of different subjects in the two management modes. Simulation analysis is conducted to verify the equilibrium results of the evolutionary game to find the key problems in abandonment management and put forward corresponding management policies. This study reveals the internal mechanism of abandonment management, thus providing a theoretical basis for the classified management of abandoned cultivated land

Management Policy of Farmers’ Cultivated Land Abandonment Behavior Based on Evolutionary Game and Simulation Analysis

Agricultural land abandonment is a complex, multidimensional, and nonlinear global phenomenon driven by multiple factors and has contrasting impacts on agrobiodiversity, the environment, and society. Appropriate management strategies on abandoned cultivated land are helpful in maintaining food and ecological security. However, there are few studies on the management of cultivated land abandonment from the perspective of stakeholders. Based on the stakeholder perspective and focusing on the two main modes of farmland abandonment management, namely, “transfer-oriented management” and “condition-improved management”, this study constructs two evolutionary game models to analyze the interest conflicts, decision-making behaviors and interest game foci of different subjects in the two management modes. Simulation analysis is conducted to verify the equilibrium results of the evolutionary game to find the key problems in abandonment management and put forward corresponding management policies. This study reveals the internal mechanism of abandonment management, thus providing a theoretical basis for the classified management of abandoned cultivated land

Agent-based simulation of human movement in building spaces using vision

The aim of this project is to develop a dynamic model for the simulation of human vision and visual interpretation in complex buildings. The dynamic model will be implemented in a computer program to analyze and predict movement patterns within a building model. Dynamics are modelled using computer vision and agent technology. Virtual reality techniques will be used to model the environment for experimenting and data collection