Global expansion of tropical cyclone precipitation footprint.

Precipitation from tropical cyclones (TCs) can cause massive damage from inland floods and is becoming more intense under a warming climate. However, knowledge gaps still exist in changes of spatial patterns in heavy TC precipitation. Here we define a metric, DIST30, as the mean radial distance from centers of clustered heavy rainfall cells (> 30 mm/3 h) to TC center, representing the footprint of heavy TC precipitation. There is significant global increase in DIST30 at a rate of 0.34 km/year. Increases of DIST30 cover 59.87% of total TC impact areas, with growth especially strong in the Western North Pacific, Northern Atlantic, and Southern Pacific. The XGBoost machine learning model showed that monthly DIST30 variability is majorly controlled by TC maximum wind speed, location, sea surface temperature, vertical wind shear, and total water column vapor. TC poleward migration in the Northern Hemisphere contributes substantially to the DIST30 upward trend globally.

Investigation of Unsafe Acts Influence Law Based on System Dynamics Simulation: Thoughts on Behavior Mechanism and Safety Control.

In modern safety management, it is very important to study the influence of the whole safety system on unsafe acts in order to prevent accidents. However, theoretical research in this area is sparse. In order to obtain the influence law of various factors in the safety system on unsafe acts, this paper used system dynamics simulation to carry out theoretical research. First, based on a summary of the causes of the coal and gas outburst accidents, a dynamic simulation model for unsafe acts was established. Second, the system dynamics model is applied to investigate the influence of various safety system factors on unsafe acts. Third, the mechanism and the control measures of unsafe acts in the enterprise safety system are studied. This study's main result and conclusions are as follows: (1) In the new coalmines, the influence of the safety culture, safety management system, and safety ability on the safety acts were similar. The order of influence on the safety acts in production coalmines is as follows: safety management system > safety ability > safety culture. The difference is most evident in months ten to eighteen. The higher the safety level and safety construction standard of the company, the greater the difference. (2) In the construction of the safety culture, the order of influence was as follows: safety measure elements > safety responsibility elements = safety discipline elements > safety concept elements. It shows the difference in influence from the 6th month and attains its maximum value from the 12th month to the 14th month. (3) In the construction of the safety management system, the degree of influence in new coalmines was as follows: safety policy > safety management organization structure > safety management procedures. Among them, especially in the first 18 months, the impact of the safety policy was most apparent. However, in the production mine, the degree of influence was as follows: safety management organization structure > safety management procedures > safety policy, but the difference is very small. (4) The degree of influence on the construct of safety ability was as follows: safety knowledge > safety psychology = safety habits > safety awareness, but the difference on the impact was small.

A numerical tool for assessing human thermal safety and thermal comfort in cold-weather activities.

This paper describes a newly developed software tool to evaluate human thermal safety and thermal comfort in cold-weather activities aimed at guiding users to arrange activity plans and select appropriate clothing ensembles. The software inputs include conditions of activity, environment, human body, and clothing ensemble. It outputs physiological temperatures, cold injury risks, thermal sensations, and thermal comforts in intuitive ways like cloud maps and curves. The software tool is characterized by (1) integration of a thermoregulatory model that predicts human thermophysiological responses under exercise conditions in cold environments, (2) the functions of clothing ensemble database and individual parameter database, (3) the human centric outputs that directly reflect human physiological and mental status, and (4) the user-friendly operation interface and output interface, as well as a wide applicability. The software is validated with human test studies covering ambient temperatures from - 30.6 to 5 °C, clothing ensembles from 1.34 to 3.20 clo, and activity intensities from 2 to 9 Mets. The average prediction RMSEs of core temperature, mean skin temperature, thermal sensation, and thermal comfort are 0.16 °C, 0.45 °C, 0.58, and 1.41, respectively. The software is an advanced expansion to current standards and guidance of cold exposure assessment and a meaningful tool for the fields of occupational health care, cold protection, and environmental ergonomics.

Fire Risk Assessments of Informal Settlements Based on Fire Risk Index and Bayesian Network.

The specific risk assessment of informal settlements (IS) is important for the management of IS and protection of environmental safety and public health. In this paper, we introduced the different types of IS in China, and conducted the fire risk assessment on 26 burning buildings in these IS, providing a semi-quantitative and scenario fire risk perception of IS in China for the readers. Two methods, the risk index and the Bayesian network, are proposed and adopted for the fire risk assessment in IS. First, a risk index system with a total of 69 factors is used to assess the degree of fire risk of buildings in IS semi-quantitatively, and the result shows that fire equipment and fire safety management on IS are seriously lacking. Then, a Bayesian network of building fire risk with a total of 66 nodes was established to assess the fire risk from ignition to spread as well as the safety evacuation. Overall, the possibility of ignition is high, but due to the role of fire equipment and fire protection design, the possibilities of fire from ignition to spread is gradually reduced. Finally, we also put forward some feasible suggestions for occupants in IS, community organizations and emergency managers to reduce the fire risk from the aspects of fire equipment and fire safety management.

A Multi-Segmented Human Bioheat Model for Asymmetric High Temperature Environments.

In workplaces such as steel, power grids, and construction, firefighters and other workers often encounter non-uniform high-temperature environments, which significantly increase the risk of local heat stress and local heat discomfort for the workers. In this paper, a multi-segment human bioheat model is developed to predict the human thermal response in asymmetric high-temperature environments by considering the sensitivity of the modeling to angular changes in skin temperature and the effects of high temperatures on human thermoregulatory and physiological responses simultaneously. The extended model for asymmetric high-temperature environments is validated with the current model results and experimental data. The result shows that the extended model predicts the human skin temperature more accurately. Under non-uniform high-temperature conditions, the local skin temperature predictions are highly consistent with the experimental data, with a maximum difference of 2 °C. In summary, the proposed model can accurately predict the temperature of the human core and skin layers. It has the potential to estimate human physiological and thermoregulatory responses under uniform and non-uniform high-temperature environments, providing technical support for local heat stress and local thermal discomfort protection.

Modelling and experimental study of thermo-physiological responses of human exercising in cold environments.

A numerical human thermo-physiological model is developed with the consideration of characteristics of exercising people in cold environments. The developed model is characterized by: 1) the concept of net exercise efficiency which is used to correct the calculation of metabolic heat production by excluding mechanical energy; 2) the effects of low temperature on basal metabolic rate and basal blood flow rate; 3) the integration with a multi-layer clothing model to calculate the heat and moisture transfer through the clothing system, which takes into account the air gaps between the clothing layers to reflect the ventilation and air penetration effect from the ambient wind. Human subject experiment is conducted in a climate chamber to validate the proposed model. The human subject experiment is also carried out in a cold environment (-5 °C) combined with different air velocity conditions (still air, 2 m/s), taking into account the activities of different intensities (standing statically, 2 km/h walking and 7 km/h running). Thermo-physiological parameters including the core temperature, 8-point local skin temperatures and the clothing layer temperatures, are measured during the experiment. Comparison between the predicted and experimental results gives the root mean squared error (RMSE) of core temperature and mean skin temperature of 0.06-0.10 °C and 0.17-0.27 °C, respectively. RMSE values for local skin and clothing layer temperatures are no higher than 1.5 °C and most within 0.8 °C. The model is also validated with published data under various ambient temperature and activity intensity conditions. The proposed model is shown to be capable of predict the thermo-physiological responses of people exposed and exercising in cold environments.

A numerical study of the effects of ambient temperature and humidity on the particle growth and deposition in the human airway.

A numerical study was conducted on the effects of ambient temperature and humidity on the transportation of sodium chloride particles (100 nm-1 µm) in a human airway model ranging from the nasal cavity to bronchi. A mucus-tissue structure was adopted to model the mass and heat transfer on the airway surface boundary. The temperature and humidity distributions of the respiratory flow were calculated and then the interaction between the particle and water vapor was further analyzed. It was predicted that the particle size grew to the ratio of 5-6 under subsaturation conditions because of hygroscopicity, which shifted the deposition efficiency in opposite directions on dependence of the initial particle size. However, the particles could be drastically raised to 40 times of the initial 100 nm diameter if the supersaturation-induced condensation was established, that was prone to occur under the cold-dry condition, and consequently promoted the deposition significantly. Such behavior might effectively contribute to the revitalized coronavirus disease 2019 (COVID-19) pandemic in addition to the more active virus itself in winter.

A network-based model to explore the role of testing in the epidemiological control of the COVID-19 pandemic.

BACKGROUND: Testing is one of the most effective means to manage the COVID-19 pandemic. However, there is an upper bound on daily testing volume because of limited healthcare staff and working hours, as well as different testing methods, such as random testing and contact-tracking testing. In this study, a network-based epidemic transmission model combined with a testing mechanism was proposed to study the role of testing in epidemic control. The aim of this study was to determine how testing affects the spread of epidemics and the daily testing volume needed to control infectious diseases. METHODS: We simulated the epidemic spread process on complex networks and introduced testing preferences to describe different testing strategies. Different networks were generated to represent social contact between individuals. An extended susceptible-exposed-infected-recovered (SEIR) epidemic model was adopted to simulate the spread of epidemics in these networks. The model establishes a testing preference of between 0 and 1; the larger the testing preference, the higher the testing priority for people in close contact with confirmed cases. RESULTS: The numerical simulations revealed that the higher the priority for testing individuals in close contact with confirmed cases, the smaller the infection scale. In addition, the infection peak decreased with an increase in daily testing volume and increased as the testing start time was delayed. We also discovered that when testing and other measures were adopted, the daily testing volume required to keep the infection scale below 5% was reduced by more than 40% even if other measures only reduced individuals' infection probability by 10%. The proposed model was validated using COVID-19 testing data. CONCLUSIONS: Although testing could effectively inhibit the spread of infectious diseases and epidemics, our results indicated that it requires a huge daily testing volume. Thus, it is highly recommended that testing be adopted in combination with measures such as wearing masks and social distancing to better manage infectious diseases. Our research contributes to understanding the role of testing in epidemic control and provides useful suggestions for the government and individuals in responding to epidemics.

Inhalation airflow and ventilation efficiency in subject-specific human upper airways.

The present numerical study investigated the transportation time of the inhaled chemicals in three realistic human airway models by adopting a methodology from the field of the building ventilation. Two indexes including "scale of ventilation efficiency 3 (SVE3)" and "local purging flow rate (L-PFR)" were used to evaluate the respective arrival time and staying time under different inhalation flow rates. The general trend of the SVE3 was predicted as expected and the exceptions within the nasal cavities were attributed to the uneven allocation of the inhaled flow between the internal channels and the formation of the vortex circulation therein. The complicated situation of the L-PFR was also explained by the structure constrains. Moreover, the variation of the two indexes with the flow rate was sensitive to the inter-subjective differences but the distribution pattern was not changed significantly. By combining the SVE3 and L-PFR, it could help with assessing the potential effect of the inhaled chemicals on the human health for engineering applications to which the relative impacts are more interested than the absolute value. But for the precise evaluation regarding a specific chemical, comprehensive simulation is still necessary with the surface adsorption included under realistic respiration cycles.

A numerical study of the effect of breathing mode and exposure conditions on the particle inhalation and deposition.

OBJECTIVE: The exposure to airborne particles are of great concern in public health. The present study was aimed to clarify the effects of the breathing mode (nasal and oral inhalation) and exposure conditions on particle inhalation and deposition in human airway. METHODS: A scanned upper airway embedded body model in an extended computational domain was constructed to perform numerical investigation into the inhalation and deposition of airborne particles. RESULTS: It was clarified that the inhalation of sub-micro and micro particles was of high efficiency and insensitive to the breathing mode, while super microparticles were much less inhalable, in particular under the nasal intake. Moreover, the relative variation of environmental wind speed and direction could significantly reshape the breathing zone as well as modify the critical inhalable area at far upstream. In addition, the breathing mode was found to be affective on the regional deposition of the microparticles, and increasing the proportion of nasal inhalation flowrate slightly enhanced the total deposition in the upper airway model. CONCLUSION: The breathing mode and exposure conditions significantly influence the particle inhalability and deposition pattern in human airway, which should be considered in the evaluation of health risk associated with airborne particle exposure.

Scenario-Entity Analysis based on an entity-relationship model: Revisiting crime reconstruction.

For a crime case, the related physical evidence and information can be termed entities, and there exist different types of relationships between entities. Entity-relationship models connect numerous entities through different relationships, which is useful in crime reconstructions. However, two types of problems may occur that can mislead crime reconstructions in the real world. Specifically, important entities may not be collected and vital relationships may go undiscovered. In this paper, we used an approach based on an entity-relationship model to address these problems. We organized the related entities used to reconstruct crimes according to their physical properties and sorted the relationships between entities through temporal, spatial and logical dimensions. The proposed approach is called 'Scenario-Entity Analysis' (SEA), and it uses several steps for discovering entities and relationships. The SEA also provides a framework for associating events/scenarios with evidence, which is important for crime reconstructions. Using a combination of SEA and Bayesian networks, a three-layered Bayesian network was constructed for uncertainty reasoning. A knife-attack case is then presented to demonstrate the analytical process of SEA.

Suppression of wood dust explosion by ultrafine magnesium hydroxide.

The suppression effects of ultrafine Mg (OH)2 powders with different particle sizes and mass fractions on explosion flame of wood dust are experimentally studied in a half-closed vertical experimental duct. Flame structures and characteristic parameters, including flame light emission images, propagation velocity, temperature, during the flame propagation of wood dust explosion are recorded by high-speed photography and fine thermocouple. Thermal decomposition behaviors of wood dust and Mg(OH)2 powders are studied using synchronous thermal analyzer. Chemical structures of residual dust samples after the explosion are characterized by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. The experimental results show that explosion flame of wood dust is obviously suppressed by physical and chemical effects of Mg(OH)2 powders, and the suppression effect of nano-Mg(OH)2 is better than that of micron-Mg(OH)2 under same mass fractions. By analyzing multiple characteristics of nano-powders, the advantages of nano-Mg(OH)2 over micron-powders are further investigated.

Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time-Series and Intervention Analysis.

In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014.