Dynamic assessment of dust hazard risk in the reconstruction of old industrial buildings: coupling effects of dust distribution and personnel trajectories.

Since the old industrial buildings bear many functions of industrial production and storage in the service stage, the dust generated by the regeneration construction is often accompanied by industrial pollutants, causing irreversible damage to the personal safety of construction workers. However, little consideration has been given to the uncertainty of dust emissions and the dynamics of construction personnel movement. Therefore, reducing the risk of dust hazards during the regeneration of old industrial buildings is imperative. This study draws on the trace intersecting theory to analyse the cause of the hazard risk associated with reconstruction dust and explore the impact of the spatiotemporal distribution characteristics of reconstruction dust and its coupling effect with construction on-site personnel activity trajectories and uses the risk matrix method to assess the dust hazard risk in the reconstruction of old industrial buildings. Finally, the renovation and reinforcement process of the first floor of a printing building in Xi'an was considered as an example for verification. The results indicate that the risk assessment model results were highly consistent with the actual situation and risk value for the entire area was 6.05, indicating a risk level of IV. Immediate measures should be implemented to reduce dust concentrations or the frequency of construction personnel activity, thereby minimising potential harm.

Joint hybrid recursive feature elimination based channel selection and ResGCN for cross session MI recognition.

In the field of brain-computer interface (BCI) based on motor imagery (MI), multi-channel electroencephalography (EEG) data is commonly utilized for MI task recognition to achieve sensory compensation or precise human-computer interaction. However, individual physiological differences, environmental variations, or redundant information and noise in certain channels can pose challenges and impact the performance of BCI systems. In this study, we introduce a channel selection method utilizing Hybrid-Recursive Feature Elimination (H-RFE) combined with residual graph neural networks for MI recognition. This channel selection method employs a recursive feature elimination strategy and integrates three classification methods, namely random forest, gradient boosting, and logistic regression, as evaluators for adaptive channel selection tailored to specific subjects. To fully exploit the spatiotemporal information of multi-channel EEG, this study employed a graph neural network embedded with residual blocks to achieve precise recognition of motor imagery. We conducted algorithm testing using the SHU dataset and the PhysioNet dataset. Experimental results show that on the SHU dataset, utilizing 73.44% of the total channels, the cross-session MI recognition accuracy is 90.03%. Similarly, in the PhysioNet dataset, using 72.5% of the channel data, the classification result also reaches 93.99%. Compared to traditional strategies such as selecting three specific channels, correlation-based channel selection, mutual information-based channel selection, and adaptive channel selection based on Pearson coefficients and spatial positions, the proposed method improved classification accuracy by 34.64%, 10.8%, 3.25% and 2.88% on the SHU dataset, and by 46.96%, 5.04%, 5.81% and 2.32% on the PhysioNet dataset, respectively.

Health damage assessment of reconstruction dust from old industrial buildings under multi-process.

The regeneration of old industrial buildings produces considerable construction dust, thereby seriously threatening the occupational health of construction workers. The existing articles concerning the exposure and health impacts of reconstruction dust in enclosed spaces are limited, but this research field has received increasing attention. In this study, multi-process during the demolition and reinforcement stages of a reconstruction project were monitored to determine the respirable dust concentration distribution. A questionnaire survey was conducted to obtain the exposure parameters of reconstruction workers. Moreover, a health damage assessment system for the reconstruction process of old industrial buildings was established by applying the disability-adjusted life year and human capital method to explore the health damage caused by the generated dust at different stages to the construction personnel. The assessment system was applied to the reconstruction stage of an old industrial building regeneration project in Beijing to obtain dust health damage values for different work types and to conduct comparative analysis. The results indicate that there are significant differences in the dust concentration and health damage at different stages. During the demolition stage, the manual demolition of concrete structures has the highest dust concentration, reaching 0.96 mg/m3. This exceeds the acceptable concentration by 37%, and the health damage cost is 0.58 yuan per person per day. In the reinforcement stage, the dust concentration generated by mortar/concrete mixing is the highest, but the risk level is acceptable. The health damage cost of concrete grinding, which is 0.98 yuan per person per day, is the highest. Therefore, it is necessary to strengthen the protective facilities and improve the reconstruction technology to reduce dust pollution. The results of this study can help in improving the existing dust pollution control measures at construction sites to reduce the risk of dust hazards during reconstruction.

NLRP3 Inflammasome: A key contributor to the inflammation formation.

Inflammation is an important part of the development of various organ diseases. The inflammasome, as an innate immune receptor, plays an important role in the formation of inflammation. Among various inflammasomes, the NLRP3 inflammasome is the most well studied. The NLRP3 inflammasome is composed of skeletal protein NLRP3, apoptosis-associated speck-like protein (ASC) and pro-caspase-1. There are three types of activation pathways: (1) "classical" activation pathway; (2) "non-canonical" activation pathway; (3) "alternative" activation pathway. The activation of NLRP3 inflammasome is involved in many inflammatory diseases. A variety of factors (such as genetic factors, environmental factors, chemical factors, viral infection, etc.) have been proved to activate NLRP3 inflammasome and promote the inflammatory response of the lung, heart, liver, kidney and other organs in the body. Especially, the mechanism of NLRP3 inflammation and its related molecules in its associated diseases remains not to be summarized, namely they may promote or delay inflammatory diseases in different cells and tissues. This article reviews the structure and function of the NLRP3 inflammasome and its role in various inflammations, including inflammations caused by chemically toxic substances.

Unveiling the Electrocatalytic Activity of the GdBa0.5Sr0.5Co2-xCuxO5+δ (x ≥ 1) Oxygen Electrodes for Solid Oxide Cells.

The A-site cation-ordered GdBa0.5Sr0.5Co2-xCuxO5+δ (GBSCC) double perovskites are evaluated regarding the development of high-performance oxygen electrodes for reversible solid oxide cells (rSOCs). The aims are to maximally decrease the content of toxic and expensive cobalt by substitution with copper while at the same time improving or maintaining the required thermomechanical and electrocatalytic properties. Studies reveal that compositions with 1 ≤ x ≤ 1.15 are particularly interesting. Their thermal and chemical expansions are decreased, and sufficient transport properties are observed. Complementary density functional theory calculations give deeper insight into oxygen defect formation in the considered materials. Chemical compatibility with La0.8Sr0.2Ga0.8Mg0.2O3-δ (LSGM) and Ce0.9Gd0.1O2-δ (GDC) solid electrolytes is evaluated. It is documented that the GdBa0.5Sr0.5Co0.9Cu1.1O5+δ oxygen electrode enables obtaining very low electrode polarization resistance (Rp) values of 0.017 Ω cm2 at 850 °C as well as 0.111 Ω cm2 at 700 °C, which is lower in comparison to that of GdBa0.5Sr0.5CoCuO5+δ (respectively, 0.026 and 0.204 Ω cm2). Systematic distribution of relaxation times analyses allows studies of the electrocatalytic activity and distinguishing elementary steps of the electrochemical reaction at different temperatures. The rate-limiting process is found to be oxygen atom reduction, while the charge transfer at the electrode/electrolyte interface is significantly better with LSGM. The studies also allow elaborating on the catalytic role of the Ag current collector as compared with Pt. The electrodes manufactured using materials with x = 1 and 1.1 permit reaching high power outputs, exceeding 1240 mW cm-2 at 850 °C and 1060 mW cm-2 at 800 °C, for the LSGM-supported cells, which can also work in the electrolysis mode.

The hepatocyte in the innate immunity.

The hepatocytes, as the main cells in the liver, exert liver functions by expressing innate immune receptors. The innate immune receptors include Toll-like receptors (TLRs), RIG-like receptors (retinoic acid inducible gene I-like receptors, RLRs) and NOD-like receptors (nucleotide binding oligomerization domain-like receptors, NLRs). The hepatocytes, recognize extracellular pathogen-associated molecular patterns (PAMPs) and intracellular damage-associated molecular patterns (DAMPs) through the above receptors. After the activation of the innate immune receptors, the hepatocytes produce cytokines, such as interferon (IFN), to protect the liver, through a series of signaling cascades.

Enhancing electrochemical detection of dopamine via dumbbell-like FePt-Fe3O4 nanoparticles.

We synthesize dumbbell-like FePt-Fe3O4 nanoparticles (NPs) and study their electrocatalytic oxidation and sensing of dopamine (DA). The FePt and Fe3O4 NPs are strongly coupled in the dumbbell structure and as a result, the dumbbell FePt-Fe3O4 NPs show the best activity for DA oxidation with the DA detection limit reaching 1 nM. They are used successfully to monitor the DA concentration increase induced by K+-stimulation of PC12 cells. Our data show that an electrode modified with dumbbell-like FePt-Fe3O4 NPs can serve as the most sensitive probe for real-time quantitative detection of DA in a neurological environment.