How Dangerous!

This morning I came across something dangerous on my way to school,which nearly injured me or even made me lose my life.

Building Indoor Dangerous Behavior Recognition Based on LSTM-GCN with Attention Mechanism

Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition.A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism(GLA)model was proposed aiming at the problem that the existing human skeleton-based action recognition methods cannot fully extract the temporal and spatial features.The network connects GCN and LSTMnetwork in series,and inputs the skeleton sequence extracted by GCN that contains spatial information into the LSTM layer for time sequence feature extraction,which fully excavates the temporal and spatial features of the skeleton sequence.Finally,an attention layer is designed to enhance the features of key bone points,and Softmax is used to classify and identify dangerous behaviors.The dangerous behavior datasets are derived from NTU-RGB+D and Kinetics data sets.Experimental results show that the proposed method can effectively identify some dangerous behaviors in the building,and its accuracy is higher than those of other similar methods.

Recognition for Frontal Emergency Stops Dangerous Activity Using Nano IoT Sensor and Transfer Learning

Currently,it is difficult to extract the depth feature of the frontal emergency stops dangerous activity signal,which leads to a decline in the accuracy and efficiency of the frontal emergency stops the dangerous activ-ity.Therefore,a recognition for frontal emergency stops dangerous activity algorithm based on Nano Internet of Things Sensor(NIoTS)and transfer learning is proposed.First,the NIoTS is installed in the athlete’s leg muscles to collect activity signals.Second,the noise component in the activity signal is removed using the de-noising method based on mathematical morphology.Finally,the depth feature of the activity signal is extracted through the deep transfer learning model,and the Euclidean distance between the extracted feature and the depth feature of the frontal emergency stops dangerous activity signal is compared.If the European distance is small,it can be judged as the frontal emergency stops dangerous activity,and the frontal emergency stops dangerous activity recognition is realized.The results show that the average time delay of activity signal acquisition of the algorithm is low,the signal-to-noise ratio of the action signal is high,and the activity signal mean square error is low.The variance of the frontal emergency stops dangerous activity recognition does not exceed 0.5.The difference between the appearance time of the dangerous activity and the recognition time of the algorithm is 0.15 s,it can accurately and quickly recognize the frontal emergency stops the dangerous activity.

Examination of the Appropriateness of Teaching Materials for Preventing Dangers during Ablution and Bathing of Infants by Mothers and Family Members

Purpose: This study aimed to develop teaching materials to prevent the dangers of ablution and bathing infants, based on the dangerous experiences of mothers and family members, and examine their appropriateness. Methods: A total of 20 midwives and public health nurses were selected as participants. Teaching materials and anonymous self-administered questionnaires were distributed, and the participants were asked to view the teaching materials and fill in the questionnaires. Retrieval was done by mail. The teaching materials included digital content, such as videos, sounds, and characters, which incorporated dangerous situations, preventions, and innovations in ablution and bathing procedures. The analysis was conducted by simple tabulation for each survey item. The free description was coded to preserve anonymity. This study was conducted with the approval of the Research Ethics Review Board of the authors’ affiliated university. Results: The teaching materials were found to be appropriate in terms of suitability to purpose, degree of difficulty of content, ease of viewing the videos, validity of time, appropriateness of expression, and usability. Conclusions: Ablution teaching materials that are used at the present time do not focus on dangers, and to date, no resources on bathing have been used as teaching materials. The created teaching materials in this study can be viewed multiple times, and mothers and family members who are unfamiliar with ablution and bathing can acquire knowledge regarding dangers and danger prevention. The addition of specific preventive measures and countermeasures for the occurrence of danger, along with practice, would result in the development of further appropriate teaching materials to reduce danger and alleviate anxiety.

Asian Honey Bees Use Trace Amount Chemical to Avoid Danger

While foraging,animals can form inter-and intra-specific social signaling(i.e.one organism using signals to alert another about danger)networks to avoid similar predators.Honey bee sting alarm pheromones are multi-component blends,for instance isopentyl acetate(IPA),octyl acetate(OA),benzyl acetate(BA),etc.However,the

Application of"Six Thinking Hats"in the Investigation and Improvement of Hidden Dangers in Food Safety

With the development of economy,people's living standards are constantly improving,and the requirements for food safety are getting higher and higher.The Food Safety Law stipulates that enterprises should implement the main responsibility of food safety,and the investigation and improvement of food safety hazards plays an important role in improving the food safety management level of enterprises and reducing food safety risks.This paper combines the innovative thinking mode of six thinking hats with food safety,discusses the application mode of six thinking hats in food safety investigation and improvement,and hopes to improve food safety level through this way.

Application of Dual-Energy X-Ray Image Detection of Dangerous Goods Based on YOLOv7

X-ray security equipment is currently a more commonly used dangerous goods detection tool, due to the increasing security work tasks, the use of target detection technology to assist security personnel to carry out work has become an inevitable trend. With the development of deep learning, object detection technology is becoming more and more mature, and object detection framework based on convolutional neural networks has been widely used in industrial, medical and military fields. In order to improve the efficiency of security staff, reduce the risk of dangerous goods missed detection. Based on the data collected in X-ray security equipment, this paper uses a method of inserting dangerous goods into an empty package to balance all kinds of dangerous goods data and expand the data set. The high-low energy images are combined using the high-low energy feature fusion method. Finally, the dangerous goods target detection technology based on the YOLOv7 model is used for model training. After the introduction of the above method, the detection accuracy is improved by 6% compared with the direct use of the original data set for detection, and the speed is 93FPS, which can meet the requirements of the online security system, greatly improve the work efficiency of security personnel, and eliminate the security risks caused by missed detection.

The First Reported Case of Co-Infection with Neisseria Meningitidis and Bordetella Pertussis in the Cerebrospinal Fluid Specimen of a Normal Four-Year-Old Child

Pertussis is an acute and highly contagious respiratory disease caused by Bordetella pertussis(B.pertussis),which occurs in people of all ages and is most dangerous for young children,especially infants.The introduction of whole-cell pertussis vaccines(wPVs)in the 1950s dramatically reduced the incidence of pertussis worldwide[1].However,over the past two decades,many studies have reported the resurgence of pertussis in different countries[2].Epidemiological surveillance in Hubei Province over the last 3 years revealed a clear increasing trend in the incidence of pertussis during the coronavirus disease 2019(COVID-19)epidemic.

Quantifying the Impact of In-Cab Alerts on Truck Speed Reductions in Ohio

In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.

School Rules

Every school has its rules.In our school,there are many rules,too.For example,we must go to school on time.We mustn't run in the hallways.We mustn't eat in the classroom but we can eat in the canteen.We mustn't take cell phones and dangerous goods to school.We have to wear the school uniforms when we are at school.

Costa Rica's Cave of Death is lethal to any creature

Activity 1.Think about the following questions and write down your answers before reading the text.1.What do you think might be the most dangerous thing in exploring such mysterious caves?2.If you could discover a new cave with unique features,what kind of features would you hope to find?

Future impacts of climate change on forest fire danger in northeastern China

Climate warming has a rapid and far-reaching impact on forest fire management in the boreal forests of China. Regional climate model outputs and the Canadian Forest Fire Weather Index （FWI） Sys- tem were used to analyze changes to fire danger and the fire season for future periods under IPCC Special Report on Emission Scenarios （SRES） A2 and B2, and the data will guide future fire management planning. We used regional climate in China （1961 1990） as our validation data, and the period （1991–2100） was modeled under SRES A2 and B2 through the weather simulated by the regional climate model system （PRECIS）. Meteorological data and fire danger were interpolated to 1 km 2 by using ANUSPLIN software. The average FWI value for future spring fire sea- sons under Scenarios A2 and B2 shows an increase over most of the region. Compared with the baseline, FWI averages of spring fire season will increase by 0.40, 0.26 and 1.32 under Scenario A2, and increase by 0.60, 1.54 and 2.56 under Scenario B2 in 2020s, 2050s and 2080s, respectively. FWI averages of autumn fire season also show an increase over most of the region. FWI values increase more for Scenario B2 than for Scenario A2 in the same periods, particularly during the 2050s and 2080s. Average future FWI values will increase under both scenarios for autumn fire season. The potential burned areas are expected to increase by 10% and 18% in spring for 2080s under Scenario A2 and B2, respectively. Fire season will be prolonged by 21 and 26 days under ScenariosA2 and B2 in 2080s respectively.

Immune multi-agent model using vaccine for cooperative air-defense system of systems for surface warship formation based on danger theory

Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.

Why is the Danger Cylinder Dangerous in the P3P Problem?

The PnP problem is a widely used technique for pose determination in computer vision community,and finding out geometric conditions of multiple solutions is the ultimate and most desirable goal of the multi-solution analysis,which is also a key research issue of the problem.In this paper,we prove that given 3 control points,if the camera's optical center lies on the so-called“danger cylinder”and is enough far from the supporting plane of control points,the corresponding P3P problem must have 3 positive solutions.This result can bring some new insights into a better understanding of the multi-solution problem.For example,it is shown in the literature that the solution of the P3P problem is instable if the optical center lies on this danger cylinder,we think such occurrence of triple-solution is the primary source of this instability.

Improved genetic algorithm freely searching for dangerous slip surface of slope

Based on the slice method of the non-circular slip surface for the calculation of integral stability of slope, an improved genetic algorithm was proposed, which can freely search for the most dangerous slip surface of slope and the corresponding minimum safety factor without supposing the geometric shape of the most dangerous slip surface. This improved genetic algorithm can simulate the genetic evolution process of organisms and avoid the local minimum value compared with the classical methods. The results of engineering cases show that it is a global optimal algorithm and has many advantages, such as higher efficiency and shorter time than the simple genetic algorithm.

Earthquake-induced collapse mechanism of two types of dangerous rock masses

As the economy of China develops, an increasing number of key traffic projects have been undertaken in the west of China, where there are high, steep rock slopes. The collapse of dangerous rock masses, especially following a strong earthquake, is one of common geological disasters known in rock slope engineering. Therefore, it is important to study the collapse mechanism of dangerous rock masses induced by an earthquake and the analysis approach of its stability. This study provides a simple and convenient method to determine the collapse mechanisms of two types of dangerous rock masses （i.e. cantilever and upright） associated with the definition and calculation of the safety factor, which is based on the flexure theory of a constant-section beam by combining with the maximum tensile-stress criterion to depict the process of crack propagation caused by seismic waves. The calculation results show that there are critical crack depths in each form of the dangerous rock masses. Once the accumulated depth of the crack growth during an earthquake exceeds the critical depth, the collapse will occur. It is also demonstrated that the crack extension amount of each step is not a constant value, and is closely associated with the current accumulated crack depth. The greater the cumulative crack depth, the more easily the crack propagates. Finally, the validity and applicability of the proposed method are verified through two actual engineering examples.

A quantitative model for danger degree evaluation of staged operation of earth dam reservoir in flood season and its application

Based on the natural disaster risk evaluation mode, a quantitative danger degree evaluation model was developed to evaluate the danger degree of earth dam reservoir staged operation in the flood season. A formula for the overtopping risk rate of the earth dam reservoir staged operation was established, with consideration of the joint effect of flood and wind waves in the flood sub-seasons with the Monte Carlo method, and the integrated overtopping risk rate for the whole flood season was obtained via the total probability approach. A composite normalized function was used to transform the dam overtopping risk rate into the danger degree, on a scale of 0-1. Danger degree gradating criteria were divided by four significant characteristic values of the dam overtopping rate, and corresponding guidelines for danger evaluation are explained in detail in this paper. Examples indicated that the dam overtopping danger degree of the Chengbihe Reservoir in China was 0.33-0.57, within the range of moderate danger level, and the flood-limiting water level （FLWL） can be adjusted to 185.00 m for the early and main flood seasons, and 185.00-187.50 m for the late flood season. The proposed quantitative model offers a theoretical basis for determination of the value of the danger degree of an earth dam reservoir under normal operation as well as the optimal scheduling scheme for the reservoir in each stage of the flood season.

Numerical Study on the Leakage and Diffusion Characteristics of Low-Solubility and Low-Volatile Dangerous Chemicals from Ship in Inland Rivers

Considering the accidents of ships for dangerous chemicals transportation in inland rivers,a numerical method for the simulation of the leakage and diffusion processes of dangerous chemicals in inland rivers is proposed in this paper.Geographic information,such as rivers and buildings in the model,is obtained through Google Earth and structures of rivers and buildings are described by Auto CAD.In addition,the Fluent is adopted to simulate the leakage and diffusion processes of the dangerous chemicals where the standard k-εmodel is used to calculate the turbulent flow.Considering the interaction between chemicals and water,the VOF method is used to describe the leakage,drift and diffusion process of dangerous chemicals groups on the water surface.Taking a section of the Yangtze River as an example,the leakage and diffusion processes from a ship carrying 3,000 tons of low-solubility and low-volatile dangerous chemicals are studied,and the characteristics of leakage and diffusion are analyzed in detail.During the simulation,the area of the maximum group of leaked dangerous chemicals reaches up to about 1800 m2,and the number reaches up to 45.Furthermore,the influence of density,viscosity,water velocity and leakage velocity on the leakage and diffusion processes is investigated in this paper.

STUDY ON FOREST FIRE DANGER MODEL WITH REMOTE SENSING BASED ON GIS

Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.

Analysis of the danger zone liable to spontaneous ignition around coal roadway at fully mechanized long-wall top-coal caving face

The intensity of heat output of coal, the rate of oxygen consumption and the influence function of coal size are tested by the big coal spontaneous combustion experiment unit. The independence of the coefficient of heat convection is studied. And based on the conservation principle of energy and the real conditions, such as coal temperature,air temperature, the geometry size of roadway, air flux, the oxygen concentration in the loose coal around the roadway, the threshold parameters resulting coal spontaneous combustion are put forward, and the index determining the danger zone liable to self ignite are evaluated. Finally, the method determining the danger zone liable to spontaneous ignition around coal roadway at fully mechanized long wall top coal caving face is put forward. Based on the determination method and real conditions in the roadway, the coal around roadway can be divided four zones.