Factors influencing householder self-evacuation in two Australian bushfires

The thesis investigated householder self-evacuation decision-making during bushfires in the Perth and Adelaide Hills in 2014 and 2015. It explored the factors that influenced householders’ decisions to evacuate, identified factors that predict self-evacuation and established the characteristics of self-evacuators. The Protective Action Decision Model (PADM) provided a conceptual framework for the research. Its theoretical and analytical usefulness in an Australian context, was assessed. A mixed methods research strategy was used involving quantitative telephone surveys of 457 bushfire-affected participants and face-to-face interviews of 109 participants in 59 households. The study concluded that environmental and social cues and warnings and householders’ perceptions of the threat, of hazard adjustments and of other stakeholders, influenced self-evacuation decision-making. Protective action perceptions, particularly the effectiveness of evacuating or not evacuating in protecting personal safety or property, were most important in predicting self-evacuation. Receipt of official warnings and the perception of likely impact of the bushfire on property were also important predictors. Undertaking long-run hazard adjustments, although not predictive of self-evacuation, was pivotal in shaping perceptions of the effectiveness of evacuating and remaining in protecting personal safety and property and indirectly influenced evacuation decisions. Seven archetypes that characterised householders’ self-evacuation attitudes and behaviour were identified. These included Threat, and Responsibility Deniers, Dependent, and Considered Evacuators, Community Guided and Experienced Independents all who took different decisional ‘rules of thumb’ and routes toward evacuating or remaining . The PADM needs to be split into two separate models to incorporate the influence of long-run hazard adjustments on protective action decision-making in an Australian bushfire. The findings suggest that future research on those who wait and see during a bushfire should take account of their decisional rules of thumb and that design and targeting of Australian bushfire safety policy should better account for self-evacuator characteristics

Matching of air conditioning power and PV panel output power based on dynamic controlling of air conditioning air supply volume

This paper presents a dynamic control strategy of air-conditioning air supply volume based on statistical data of the spatial and temporal distribution of occupants in the building, aiming at reducing overheating in buildings under local heat island effect. Nowadays, energy consumption in air-conditioning system is relatively high when considering the limited number of occupants and chiller plants operating inefficiently because the traditional central air-conditioning system was not designed to operate at different cooling load demands. Therefore, variable air volume (VAV) air-conditioning system is applied in this paper with corresponding wind volume control method. To address the above issue, in this paper: (1) A spatiotemporal distribution of occupants in the building is analyzed, and the relationship between occupant distribution and characteristics of the thermal dissipating load is established; (2) A strategy for dynamic controlling of the air supply volume in time and space is proposed; (3) A distributed photovoltaic system supplies power to cooling load of the building, and a strategy is proposed for optimizing the match between cooling power and photovoltaic (PV) output power using competitive swarm optimization algorithm; and (4) Air blower total amount of wind control method is adopted in VAV air-conditioning system for dynamic controlling of the air supply volume. This paper uses a simulation to verify the feasibility and optimality of the above strategies. The simulation results show that the building energy consumption is greatly reduced by 39.52%, the PV accommodation is improved as 77.14%, and four control indicators are well satisfied due to the air blower total amount of wind control method.</p

Assessment of the cod stock in NAFO Division 3M

39 páginas, 27 figuras, 21 tablas.-- Scientific council meetingAn assessment of the cod stock in NAFO Division 3M is performed. A Bayesian model, as used in the last assessments, was used to perform the analysis. Results indicat e a fairly substantial increase in SSB, reaching a value well above B lim . The six-years retrospective plot shows that the r ecruitment is overestimated every year. Three year projections indicate that fishing at the F statusquo level should allow SSB to increase slowly, although abundance will remain at levels below those observed at the beginning of the series. If the fishing mortality were return to the levels seen before 1995, stock recovery would become improbablPeer reviewe

DataSheet1_A seamless approach for evaluating climate models across spatial scales.PDF

In regions of the world where topography varies significantly with distance, most global climate models (GCMs) have spatial resolutions that are too coarse to accurately simulate key meteorological variables that are influenced by topography, such as clouds, precipitation, and surface temperatures. One approach to tackle this challenge is to run climate models of sufficiently high resolution in those topographically complex regions such as the North American Regionally Refined Model (NARRM) subset of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 (E3SM v2). Although high-resolution simulations are expected to provide unprecedented details of atmospheric processes, running models at such high resolutions remains computationally expensive compared to lower-resolution models such as the E3SM Low Resolution (LR). Moreover, because regionally refined and high-resolution GCMs are relatively new, there are a limited number of observational datasets and frameworks available for evaluating climate models with regionally varying spatial resolutions. As such, we developed a new framework to quantify the added value of high spatial resolution in simulating precipitation over the contiguous United States (CONUS). To determine its viability, we applied the framework to two model simulations and an observational dataset. We first remapped all the data into Hierarchical Equal-Area Iso-Latitude Pixelization (HEALPix) pixels. HEALPix offers several mathematical properties that enable seamless evaluation of climate models across different spatial resolutions including its equal-area and partitioning properties. The remapped HEALPix-based data are used to show how the spatial variability of both observed and simulated precipitation changes with resolution increases. This study provides valuable insights into the requirements for achieving accurate simulations of precipitation patterns over the CONUS. It highlights the importance of allocating sufficient computational resources to run climate models at higher temporal and spatial resolutions to capture spatial patterns effectively. Furthermore, the study demonstrates the effectiveness of the HEALPix framework in evaluating precipitation simulations across different spatial resolutions. This framework offers a viable approach for comparing observed and simulated data when dealing with datasets of varying spatial resolutions. By employing this framework, researchers can extend its usage to other climate variables, datasets, and disciplines that require comparing datasets with different spatial resolutions.</p

Table1_Pyroptosis-Related Gene to Construct Prognostic Signature and Explore Immune Microenvironment and Immunotherapy Biomarkers in Bladder Cancer.XLS

Bladder cancer is known to be the most common malignant tumor in the urinary system and has a poor prognosis; thus, new targets for drug treatment are urgently needed. Pyroptosis is defined as programmed cell death in the inflammatory form mediated by the gasdermin protein. It has therapeutic potential due to the synergistic effect of radiotherapy and chemotherapy, can reverse chemotherapy resistance, is able to regulate the body environment to alter tumor metabolism, and may enhance the response rate of the immune checkpoint inhibitor. Accordingly, this study attempted to explore the role of pyroptosis in bladder cancer. A prognostic model based on five pyroptosis-related genes was constructed by conducting univariate Cox survival and LASSO regression analyses using The Cancer Genome Atlas (TCGA) cohort. Patients were divided into high- and low-risk groups according to the median risk score, with all five PRGs having downregulated expression in the high-risk group. The high-risk group was shown to have a worse prognosis than the low-risk group, and survival differences between the two groups were then validated in the Gene Expression Omnibus (GEO) cohort. Moreover, the ROC curves demonstrated the model’s moderate predictive ability. The univariate and multivariate Cox regression analyses indicated that risk scores were found to serve as an independent prognosis factor for OS in bladder cancer patients. In addition, the high-risk group was observed to be associated with advanced N and TNM stages. A nomogram combining risk scores and clinical features was then established, with the ROC curve indicating that the AUC of TCGA training cohort in 3 and 5 years was 0.789 and 0.775, respectively. The calibration curve exhibited a high consistency between the actual survival rate and the predicted rate. Furthermore, the GO and KEGG analyses found that antigen processing and presentation of exogenous antigen, exogenous peptide antigen, and peptide antigen were enriched in the low-risk group. A higher abundance of tumor-infiltrating immune cells and additional active immune pathways were also noted in the low-risk group. In addition, immunotherapy biomarkers, including TMB, PD1, PD-L1, CTLA4, and LAG3, were shown to have higher levels in the low-risk group. Therefore, patients in the low-risk group may be potential responders to immune checkpoint inhibitors.</p

DataSheet_1_Single-cell profiling reveals that SAA1+ epithelial cells promote distant metastasis of esophageal squamous cell carcinoma.docx

IntroductionEsophageal squamous cell carcinoma (ESCC) is one of the most common cancers globally, with significant cell heterogeneity and poor prognosis. Distant metastasis in ESCC is one of the key factors that affects the prognosis of patients.Methods and resultsStarting with the analysis of ESCC single-cell sequencing data, we constructed a single-cell atlas of ESCC in detail and clarified the cell heterogeneity within tumor tissues. Through analysis of epithelial-mesenchymal transition (EMT) levels, gene expression, and pathway activation, we revealed the existence of a novel subpopulation of SAA1+ malignant cells in ESCC that are highly aggressive and closely associated with distant metastasis of ESCC. In vitro wound healing and transwell assays confirmed a strong invasion capacity of ESCC tumor cells with high expression of SAA1. Then, we constructed an effective and reliable prediction model based on the gene expression pattern of SAA1+ malignant cell subpopulations and confirmed that patients in the high-risk group had significantly worse prognosis than those in the low-risk group in the training cohort, internal verification cohort and external verification cohort.DiscussionThis manuscript contributes to exploration of the heterogeneity of ESCC tumor tissues and the search for new ESCC subpopulations with special biological functions. These results contribute to our understanding of the underlying mechanisms of distant metastasis of ESCC and thus provide a theoretical basis for improved therapies.</p

Additional file 1 of Integrative metabolome and transcriptome analyses reveal the coloration mechanism in Camellia oleifera petals with different color

Additional file 1: Fig. S1. Heatmap of the metabolites in W, P, CP and R petals. Fig. S2. The co-expressed genes in W, P, CP,  and R petals. Table S1.  Primer sequences used for the qRT-PCR validation. Table S2. Flavonoid metabolome profile in Camellia oleifera petals. Table S3. Differentially accmulated anthocyainins in W_vs_P comparsion. Table S4. Differentially accumulated anthocyanins  in P_vs _CP comparsion. Table S5. Differentially accumulated anthocyanins  in CP_vs_R comparsion. Table S6. Transcriptome sequencing of C. oleifera petals. Table S7. The expression levels of key differentially expressed genes. Table S8. Cis-acting elements present in the CoF3′H promoter. Table S9. Cis-acting elements present in the CoANS promoter

DataSheet1_Pyroptosis-Related Gene to Construct Prognostic Signature and Explore Immune Microenvironment and Immunotherapy Biomarkers in Bladder Cancer.PDF

Bladder cancer is known to be the most common malignant tumor in the urinary system and has a poor prognosis; thus, new targets for drug treatment are urgently needed. Pyroptosis is defined as programmed cell death in the inflammatory form mediated by the gasdermin protein. It has therapeutic potential due to the synergistic effect of radiotherapy and chemotherapy, can reverse chemotherapy resistance, is able to regulate the body environment to alter tumor metabolism, and may enhance the response rate of the immune checkpoint inhibitor. Accordingly, this study attempted to explore the role of pyroptosis in bladder cancer. A prognostic model based on five pyroptosis-related genes was constructed by conducting univariate Cox survival and LASSO regression analyses using The Cancer Genome Atlas (TCGA) cohort. Patients were divided into high- and low-risk groups according to the median risk score, with all five PRGs having downregulated expression in the high-risk group. The high-risk group was shown to have a worse prognosis than the low-risk group, and survival differences between the two groups were then validated in the Gene Expression Omnibus (GEO) cohort. Moreover, the ROC curves demonstrated the model’s moderate predictive ability. The univariate and multivariate Cox regression analyses indicated that risk scores were found to serve as an independent prognosis factor for OS in bladder cancer patients. In addition, the high-risk group was observed to be associated with advanced N and TNM stages. A nomogram combining risk scores and clinical features was then established, with the ROC curve indicating that the AUC of TCGA training cohort in 3 and 5 years was 0.789 and 0.775, respectively. The calibration curve exhibited a high consistency between the actual survival rate and the predicted rate. Furthermore, the GO and KEGG analyses found that antigen processing and presentation of exogenous antigen, exogenous peptide antigen, and peptide antigen were enriched in the low-risk group. A higher abundance of tumor-infiltrating immune cells and additional active immune pathways were also noted in the low-risk group. In addition, immunotherapy biomarkers, including TMB, PD1, PD-L1, CTLA4, and LAG3, were shown to have higher levels in the low-risk group. Therefore, patients in the low-risk group may be potential responders to immune checkpoint inhibitors.</p

sj-docx-1-chl-10.1177_17475198231156358 – Supplemental material for A study on the viscosity, density, and derivative properties of 1-alkyl-3-methylimidazolium bis((trifluoromethyl)sulfonyl)imides with benzo-15-crown-5 binary mixtures

Supplemental material, sj-docx-1-chl-10.1177_17475198231156358 for A study on the viscosity, density, and derivative properties of 1-alkyl-3-methylimidazolium bis((trifluoromethyl)sulfonyl)imides with benzo-15-crown-5 binary mixtures by Ju Tian, Qi Tang, Yongshen Zhang, Yuzhen Shu, Lihua Zhang and Weiming Zheng in Journal of Chemical Research</p