Exposure to Indoor PM2.5 and Perception of Air Quality and Productivity in an Office Building: An Intervention Study

Health impacts of exposure to particulate matter can be wide-ranging, with some evidence suggesting potential impacts on cognition and productivity. This study was conducted in an urban mixed-mode ventilated office in China. Sixty eligible employees agreed to participate in the study and fifty-five valid responses were obtained. The perception of air quality, productivity and wellbeing were assessed via questionnaires during three conditions: intervention, control, and baseline (a week prior to the intervention). Portable air purifiers on the subjects’ workstations were used as the intervention to control the PM2.5 level at subjects’ breathing zone. The air purifiers during the off and on status were considered as control and intervention conditions respectively. The same cohort was divided into four groups separately participating in each of three conditions on different workdays via a crossover design. The following PM2.5 levels [Average (SD)] during the three conditions (Baseline/Control/Intervention) were:[26.7 (2.1)/18.0 (1.8)/3.7 (0.9)] µg/m³.These levels correspond to interim targets of WHO guidelines for PM2.5. Analysis indicates significant differences between control and intervention regarding perception and satisfaction of air quality, thermal satisfaction and productivity

Local-Global Context Aware Transformer for Language-Guided Video Segmentation

We explore the task of language-guided video segmentation (LVS). Previous algorithms mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context and easily suffering from visual-linguistic misalignment. In light of this, we present Locater (local-global context aware Transformer), which augments the Transformer architecture with a finite memory so as to query the entire video with the language expression in an efficient manner. The memory is designed to involve two components -- one for persistently preserving global video content, and one for dynamically gathering local temporal context and segmentation history. Based on the memorized local-global context and the particular content of each frame, Locater holistically and flexibly comprehends the expression as an adaptive query vector for each frame. The vector is used to query the corresponding frame for mask generation. The memory also allows Locater to process videos with linear time complexity and constant size memory, while Transformer-style self-attention computation scales quadratically with sequence length. To thoroughly examine the visual grounding capability of LVS models, we contribute a new LVS dataset, A2D-S+, which is built upon A2D-S dataset but poses increased challenges in disambiguating among similar objects. Experiments on three LVS datasets and our A2D-S+ show that Locater outperforms previous state-of-the-arts. Further, we won the 1st place in the Referring Video Object Segmentation Track of the 3rd Large-scale Video Object Segmentation Challenge, where Locater served as the foundation for the winning solution. Our code and dataset are available at: https://github.com/leonnnop/LocaterComment: Accepted by TPAMI. Code, data: https://github.com/leonnnop/Locate

Short-term exposure to indoor PM2.5 in office buildings and cognitive performance in adults: An intervention study

Impacts of exposure to particulate matter can be wide-ranging, with some evidence suggesting potential impacts on nervous system, cognition, and productivity. However, most evidence to date addresses ambient exposure and chronic outcomes with limited research on indoor short-term exposure to PM2.5 and cognitive performance. Hence, the aim of this study was to evaluate if there is a relationship between short-term exposure to indoor PM2.5 within the workplace context and cognitive performance in adults. A randomized single-blind cross-over trial was conducted in an urban mixed-mode ventilated office in Beijing (China). Sixty eligible employees participated in the study and fifty-five valid responses were obtained. Cognitive performance was assessed with a validated neurological battery test during intervention and control conditions. Portable air purifiers were placed on the subjects' workstations and used in the intervention condition to control PM2.5 levels at the subjects’ breathing zone whereas in the control condition, the air purifiers were present but switched off. Average PM2.5 levels were respectively 18.0 μg/m³ and 3.7 μg/m³ in the control and intervention condition. In each condition, cognitive performance testing started five to 7 h after arriving in the office. The results showed office workers had significantly better performance for 9 out of the 16 cognitive skills during the intervention, compared to the control condition, with the most consistent effect in the memory domain. This study adds evidence that elevated PM2.5 levels can detrimentally affect cognitive performance even during short-term indoor exposure. Further research is needed on the potential impact of other air pollutants, including ultrafine particles, and on the possible role of sound and air movement from the air purifiers

PathMLP: Smooth Path Towards High-order Homophily

Real-world graphs exhibit increasing heterophily, where nodes no longer tend to be connected to nodes with the same label, challenging the homophily assumption of classical graph neural networks (GNNs) and impeding their performance. Intriguingly, we observe that certain high-order information on heterophilous data exhibits high homophily, which motivates us to involve high-order information in node representation learning. However, common practices in GNNs to acquire high-order information mainly through increasing model depth and altering message-passing mechanisms, which, albeit effective to a certain extent, suffer from three shortcomings: 1) over-smoothing due to excessive model depth and propagation times; 2) high-order information is not fully utilized; 3) low computational efficiency. In this regard, we design a similarity-based path sampling strategy to capture smooth paths containing high-order homophily. Then we propose a lightweight model based on multi-layer perceptrons (MLP), named PathMLP, which can encode messages carried by paths via simple transformation and concatenation operations, and effectively learn node representations in heterophilous graphs through adaptive path aggregation. Extensive experiments demonstrate that our method outperforms baselines on 16 out of 20 datasets, underlining its effectiveness and superiority in alleviating the heterophily problem. In addition, our method is immune to over-smoothing and has high computational efficiency

Combating Bilateral Edge Noise for Robust Link Prediction

Although link prediction on graphs has achieved great success with the development of graph neural networks (GNNs), the potential robustness under the edge noise is still less investigated. To close this gap, we first conduct an empirical study to disclose that the edge noise bilaterally perturbs both input topology and target label, yielding severe performance degradation and representation collapse. To address this dilemma, we propose an information-theory-guided principle, Robust Graph Information Bottleneck (RGIB), to extract reliable supervision signals and avoid representation collapse. Different from the basic information bottleneck, RGIB further decouples and balances the mutual dependence among graph topology, target labels, and representation, building new learning objectives for robust representation against the bilateral noise. Two instantiations, RGIB-SSL and RGIB-REP, are explored to leverage the merits of different methodologies, i.e., self-supervised learning and data reparameterization, for implicit and explicit data denoising, respectively. Extensive experiments on six datasets and three GNNs with diverse noisy scenarios verify the effectiveness of our RGIB instantiations. The code is publicly available at: https://github.com/tmlr-group/RGIB.Comment: Accepted by NeurIPS 202

Young plasma reverses anesthesia and surgery-induced cognitive impairment in aged rats by modulating hippocampal synaptic plasticity

We investigated the protective effect of young plasma on anesthesia- and surgery-induced cognitive impairment and the potential underlying mechanism using bioinformatics, functional enrichment analysis, gene set enrichment analysis, Golgi-Cox staining, dendritic spine analysis, immunofluorescence assay, western blot analysis, and transmission electron microscopy. Furthermore, we performed behavioral assessments using the open field test, the novel object recognition test, and the Morris water maze test. We identified 1969 differentially expressed genes induced by young plasma treatment, including 800 upregulated genes and 1169 downregulated genes, highlighting several enriched biological processes (signal release from synapse, postsynaptic density and neuron to neuron synapse). Anesthesia- and surgery-induced cognitive impairment in aged rats was comparatively less severe following young plasma preinfusion. In addition, the decreased levels of synapse-related and tyrosine kinase B/extracellular signal-regulated protein kinase/cyclic adenosine monophosphate response element-binding protein (TrkB/ERK/CREB) signaling pathway-related proteins, dendritic and spine deficits, and ultrastructural changes were ameliorated in aged mice following young plasma preinfusion. Together, these findings suggest that young plasma reverses anesthesia- and surgery-induced cognitive impairment in aged rats and that the mechanism is associated with the activation of the TrkB/ERK/CREB signaling pathway and improvement in hippocampal synaptic plasticity

Effects of Different Staircase Design Factors on Evacuation of Children from Kindergarten Buildings Analyzed via Agent-Based Simulation

Staircase design is critical to the evacuation of children. Through an agent-based simulation, this study focused on the relationship between staircase design factors and evacuation efficiency in a multi-story kindergarten. A quantitative study was conducted on three critical architectural design factors: stair flight width, positional relationship, and design pattern of the juncture between the staircase and the corridor. The findings were as follows. (1) When the stair flight width ranges from 0.7 to 1.0 m, an increase in this width can improve evacuation efficiency significantly; when the width ranges from 1.1 to 1.4 m, evacuation efficiency is improved continuously, but an increase in this width range has a diminishing effect on evacuation efficiency; when the width is greater than 1.7 m, a further increase has an adverse effect on evacuation efficiency, because such a staircase space allows overtaking behaviors. (2) Under the same stair flight width conditions, evacuation efficiency is higher when the staircase and corridor are perpendicular to each other than when they are parallel, because the natural steering angle of the children was preserved during their evacuation. (3) The cut corner and rounded corner designs between the staircase and corridor improved evacuation efficiency and alleviated the congestion at bottleneck positions; the evacuation efficiency continued to rise with an increase in the cutting angle. These findings are expected to provide a useful reference for the evacuation design of kindergarten buildings and for emergency evacuation management

The Associations between Evacuation Movements and Children’s Physiological Demands Analyzed via Wearable-Based Sensors

During fire evacuations, crawling is recommended to prevent harm from toxic smoke and to access more breathable air. Few studies have evaluated the physiological burden of crawling, especially for children. The method of using wearable sensors to collect data (e.g., electrodermal activity, EDA; skin temperature, SKT) was used to evaluate the effects of different locomotive postures on children’s velocity and physiological demands. Twenty-eight (28) children (13 boys and 15 girls), aged 4 to 6 years old, traveled up to 22.0 m in different postures: Upright walking (UW), stoop walking (SW), knee and hand crawling (KHC). The results showed that: (1) Gender and age had significant impacts on children’s velocity (p < 0.05): Boys were always faster than girls in any of the three postures and the older the child, the faster the velocity for KHC. (2) Physiological results demonstrated that KHC was more physically demanding than bipedal walking, represented by higher scores of the EDA and SKT indicators, similar to the findings of adults. (3) Gender and age had significant impacts on children’s physiological demands (p < 0.05). The physiological demands were greater for boys than girls. In addition, the higher the age, the less physiological demands he/she needs. Overall, the findings suggest that children are unnecessarily required to choose crawling precisely as adults as the best posture to respond to emergency scenarios. In a severe fire, stoop walking is suggested, as there is more respired air and children could move quickly and avoid overworking physiological burdens. The results of this study are expected to be considered in the evaluation of current evacuation recommendations and for the safety guide of preparedness to improve the effectiveness of risk reduction for children

An Ergonomic Assessment of Different Postures and Children Risk during Evacuations

Crawling is recommended for avoiding high heat and toxic fumes and for obtaining more breathable air during evacuations. Few studies have evaluated the effects of crawling on physical joints and velocity, especially in children. Based on motion capture technology, this study proposes a novel method of using wearable sensors to collect exposure (e.g., mean duration, frequency) on children’s joints to objectively quantify the impacts of different locomotion methods on physical characteristics. An on-site experiment was conducted in a kindergarten with 28 children (13 boys and 15 girls) of different ages (4–6 years old) who traveled up to 22 m in three different postures: upright walking (UW), stoop walking (SW), and knee and hand crawling (KHC). The results showed that: (1) The level of joint fatigue for KHC was heavier than bipedal walking (p < 0.05), which was evidenced by higher mean duration and frequency. There was no significant difference between UW and SW (p > 0.05). (2) The physical characteristics of the children in the different postures observed in this study were different (p < 0.05). The ankle was more fatigued than other joints during bipedal walking. Unlike infants, the wrists and hips of the children became fatigued while crawling. The key actions flexion/extension are more likely to induce joint fatigue vs. other actions. (3) Crawling velocity was significantly slower than the bipedal velocities, and UW was 10.6% faster than SW (p < 0.05). The bipedal walking velocity started to decrease after the children had travelled up to 13 m, while the KHC velocity started to decrease after traveling up to 11.6 m. (4) In a severe fire, the adoption of SW is suggested, as the evacuees can both evacuate quickly and avoid overworking their joints. (5) There were no significant differences in the age (p > 0.05) and gender (p > 0.05) of the children on the joints in any of the three postures. To conclude, KHC causes more damage to body joints compared to bipedal walking, as evidenced by higher exposure (mean duration, frequency), whereas UW and SW are similar in terms of the level of joint fatigue. The above findings are expected to provide a useful reference for future applications in the children’s risk assessment and in the prevention design of buildings