High-rise building fire pre-warning model based on the support vector regression

Aiming at reducing the deficiency of the traditional fire pre-warning algorithms and the intelligent fire pre-warning algorithms such as artificial neural network,and then to improve the accuracy of fire prewarning for high-rise buildings,a composite fire pre-warning controller is designed according to the characteristic（ nonlinear,less historical data,many influence factors）,also a high-rise building fire pre-warning model is set up based on the support vector regression（ SV R）. Then the wood fire standard history data is applied to make empirical analysis. The research results can provide a reliable decision support framework for high-rise building fire pre-warning.

Non-destructive testing and pre-warning analysis on the quality of bolt support in deep roadways of mining districts

The bolt support quality of coal roadways is one of the important factors for the efficiency and security of coal production. By means of a self-developed technique and equipment of random non-destructive testing, non-destructive detection and pre-warning analysis on the quality of bolt support in deep roadways of mining districts were performed in a number of mining areas. The measured data were obtained in the detection instances of abnormal in-situ stress and support invalidation etc. The corresponding relation between axial bolt load variation and roadway surrounding rock deformation and stability was summarized in different mining service stages. Pre-warning technology of roadway surrounding rock stability is proposed based on the detection of axial bolt load. Meanwhile, pre-warning indicators of axial bolt load in different mining service stages are offered and some successful pre-warning cases are also illustrated.The research results show that the change rules of axial bolt load in different mining service stages are quite similar in different mining areas. The change of axial bolt load is in accord with the adjustment of surrounding rock stress, which can consequently reflect the deformation and stability state of roadway surrounding rock. Through the detection of axial bolt load in different sections of roadways, the status of real-time bolt support quality can be reflected; meanwhile, the rationality of bolt support design can be evaluated which provides reference for bolting parameters optimization.

A Harmful-Intrusion Detection Method Based on Background Reconstruction and Two-Dimensional K-S Test in an Optical Fiber Pre-Warning System

The key technology and main difficulty for optical fiber intrusion pre-warning systems （OFIPS） is the extraction of harmful-intrusion signals. After being processed by a phase-sensitive optical time-domain reflectometer （O-0TDR）, vibration signals can be preliminarily extracted. Generally, these include noises and intrusions. Here, intrusions can be divided into harmful and harmless intrusions. With respect to the close study of signal characteristics, an effective extraction method of harmful intrusion is proposed in the paper. Firstly, in the part of the background reconstruction, all intrusion signals are first detected by a constant false alarm rate （CFAR）. We then reconstruct the backgrounds by extracting two-part information of alarm points, time and amplitude. This ensures that the detection background consists of intrusion signals. Secondly, in the part of the two-dimensional Kolmogorov-Smirnov （K-S） test, in order to extract harmful ones from all extracted intrusions, we design a separation method. It is based on the signal characteristics of harmful intrusion, which are shorter time interval and higher amplitude. In the actual OFIPS, the detection method is used in some typical scenes, which includes a lot of harmless intrusions, for example construction sites and busy roads. Results show that we can effectively extract harmful intrusions.

Pre-warning information dissemination models of different media under emergencies

Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ensure the safety of human beings during emergencies. In this paper, we propose the models of pre-warning information dissemination via five classical media based on actual pre-warning issue processes, including television, radio, short message service (SMS), electronic screens, and online social networks. The population coverage ability and dissemination efficiency at different issue time of these five issue channels are analyzed by simulation methods, and their advantages and disadvantages are compared by radar graphs. Results show that SMS is the most appropriate way to issue long-term pre-warning for its large population coverage, but it is not suitable for issuing urgent warnings to large population because of the limitation of telecom company's issue ability. TV shows the best performance to combine the dissemination speed and range, and the performance of radio and electronic screens are not as satisfactory as the others. In addition, online social networks might become one of the most promising communication method for its potential in further diffusion. These models and results could help us make pre-warning issue plans and provide guidance for future construction of information diffusion systems, thus reducing injuries, deaths, and other losses under different emergencies.

Current Situations and Future Development Trend of Farmland Pre-warning Researches in China

This paper summarized theory discussion,main research methods,contents,empirical and engineering researches of farmland prewarning in China.It stated that future researches of farmland pre-warning in China will focus on deepening application of farmland security prewarning models,revealing mechanism of changes in different farmland resources,establishing pre-warning models suitable for research areas,accurate evaluation and prediction of farmland security,and exploring establishing and improving farmland security monitoring system and operating mechanism of all levels.

RCoV19:A One-stop Hub for SARS-CoV-2 Genome Data Integration,Variant Monitoring,and Risk Pre-warning

The Resource for Coronavirus 2019(RCoV19)is an open-access information resource dedicated to providing valuable data on the genomes,mutations,and variants of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).In this updated implementation of RCoV19,we have made significant improvements and advancements over the previous version.Firstly,we have implemented a highly refined genome data curation model.This model now features an automated integration pipeline and optimized curation rules,enabling efficient daily updates of data in RCoV19.Secondly,we have developed a global and regional lineage evolution monitoring platform,alongside an outbreak risk pre-warning system.These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns,enabling better preparedness and response strategies.Thirdly,we have developed a powerful interactive mutation spectrum comparison module.This module allows users to compare and analyze mutation patterns,assisting in the detection of potential new lineages.Furthermore,we have incorporated a comprehensive knowledgebase on mutation effects.This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations.In summary,RCoV19 serves as a vital scientific resource,providing access to valuable data,relevant information,and technical support in the global fight against COVID-19.The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.

重庆地震震前气象要素异常特征分析(英文)

The situations of four major earthquakes occurred in Chongqing in modern times were analyzed in this paper.According to the study of the relationship between drought and earthquake and the study on five abnormal indices of meteorological elements,the pre-earthquake abnormal meteorological elements of these earthquakes occurred in Tongjing Town of Yubei,Chongqing in 1989,Xuxi of Rongchang in Chongqing in 1997,Rongchang County of Chongqing in 1999 respectively were systemically tested.Finally,the assumption of establishing an earthquake warning system of abnormal meteorological elements in the whole nation,especially in some high-risk earthquake areas was proposed.

Some new pre-warning criteria for creep slope failure

The forecasting of the failure time of a slope remains a worldwide problem because of many different possibilities of geological conditions in combination with many varying external factors such as climate and vegetation,and not well-defined or unknown time effects in deformation and failure models.The aim of this paper is to suggest a new method to carry out the phase division and to explore tangential angular features of the displacement-time curve of creep slopes as well as the acceleration characteristics in the process of slope deformation and the pre-warning criteria for critical failure.An imminent failure is pro-ceeded with usually three basic deformation phases,namely primary creep("decelerated") ,secondary creep("steadystate") and tertiary creep("accelerated") .Mostly,only during the accelerated phase the imminence of a possible slope failure is rec-ognized.The analysis of displacement data from a series of landslides allowed to recognize different evolutionary patterns of displacement.A quantitative approach was proposed to describe the tangential angle of the displacement-time curve and a new criterion based on the angle was put forward to divide the accelerated phase into three sub-phases:initial acceleration,medium acceleration,and the critical failure.A pre-warning criterion for critical failure is also proposed consequently. Changes of acceleration showed completely different characteristics from those of cumulative displacement and displacement in the process of slope deformation.The values of acceleration usually oscillate around 0 prior to the critical failure phase,whereas the acceleration increases abruptly when the deformation moves into the critical failure phase.This allows,therefore,for a method to forecast the time of the failure.So it is possible to define different alert acceleration threshold values to be used for emergency management.

Spatial and Temporal Evolution Characteristics of PM2.5 in China from 1998 to 2016

The rapid development of China’s economy and urbanization has given rise to noticeable environmental problems,among which the change of air quality has received extensive attention.The panel data of PM2.5(particles with an aerodynamic diameter of 2.5μm or less)in 343 prefecture-level cities in China from 1998 to 2016 were statistically analyzed to reveal the characteristics of the temporal evolution and spatial variation of China’s air quality in the past two decades.The results show that:1)the overall deterioration trend of air quality is obvious throughout the country.The variation trend of PM2.5 was divided into three phases:rapid-growth phase(1998–2007),lag phase(2006–2011)and mildly-incremental phase(2012–2016),with their average growth rates of 7.19%,-3.59%and 0.52%,respectively.2)The spatial difference of PM2.5 values in China increased significantly with time.Since 2003,the high-value area in the east has expanded rapidly,and polarization became much more pronounced.The change rate of PM2.5 is high in the east and west and low in the middle.The change rates of most areas in the west exceed more than 80%,and in the east lie somewhere between 40%and 60%.In the midlands,the change rate is not large and some regions even show a negative growth.3)The change rate of PM2.5 is also high in areas with higher values.However,in regions where the change rate of PM2.5 is high,the value of PM2.5 is not always high.The high change rate is mainly attributable to the low base value of PM2.5 and the cities concerned belong to sensitive areas.4)According to the PM2.5 warning index,the number of strong,medium,weak and non-warning areas in China is 45,85,159 and 54,respectively.

Rainfall Threshold Calculation Method for Debris Flow Pre-Warning in Data-Poor Areas

Debris flows are the one type of natural disaster that is most closely associated with hu- man activities. Debris flows are characterized as being widely distributed and frequently activated. Rainfall is an important component of debris flows and is the most active factor when debris flows oc- cur. Rainfall also determines the temporal and spatial distribution characteristics of the hazards. A reasonable rainfall threshold target is essential to ensuring the accuracy of debris flow pre-warning. Such a threshold is important for the study of the mechanisms of debris flow formation, predicting the characteristics of future activities and the design of prevention and engineering control measures. Most mountainous areas have little data regarding rainfall and hazards, especially in debris flow forming re- gions. Therefore, both the traditional demonstration method and frequency calculated method cannot satisfy the debris flow pre-warning requirements. This study presents the characteristics of pre-warning regions, included the rainfall, hydrologic and topographic conditions. An analogous area with abundant data and the same conditions as the pre-warning region was selected, and the rainfall threshold was calculated by proxy. This method resolved the problem of debris flow pre-warning in ar- eas lacking data and provided a new approach for debris flow pre-warning in mountainous areas.

Seasonal variation of airborne fungi of the Tiantishan Grottoes andWestern Xia Museum,Wuwei,China

In this study,a systematic survey of cultural airborne fungi was carried out in the occurrence environments of wall paintings that are preserved in the Tiantishan Grottoes and the Western Xia Museum,China.A bio-aerosol sampler was used for sampling in four seasons in 2016.Culture-dependent and-independent methods were taken to acquire airborne fungal concentration and purified strains;by the extraction of genomic DNA,amplification of fungal ITS rRNA gene region,sequencing,and phylogenetic analysis,thereafter the fungal community composition and distribution characteristics of different study sites were clarified.We disclosure the main environmental factors which may be responsible for dynamic changes of airborne fungi at the sampling sites.The concentration of cultural airborne fungi was in a range from 13 to 1,576 CFU/m^(3),no significant difference between the two sites at the Tiantishan Grottoes,with obvious characteristics of seasonal variation,in winter and spring were higher than in summer and autumn.Also,there was a significant difference in fungal concentration between the inside and outside of the Western Xia Museum,the outside of the museum was far more than the inside of the museum in the four seasons,particularly in the winter.Eight fungal genera were detected,including Cladosporium,Penicillium,Alternaria,and Filobasidium as the dominant groups.The airborne fungal community structures of the Tiantishan Grottoes show a distinct characteristic of seasonal variation and spatial distribution.Relative humidity,temperature and seasonal rainfall influence airborne fungal distribution.Some of the isolated strains have the potential to cause biodeterioration of ancient wall paintings.This study provides supporting information for the pre-warning conservation of cultural relics that are preserved at local sites and inside museums.

A New Detection Method Based on CFAR and DE for OFPS

Optical fiber pre-warning system （OFPS） is widely utilized in pipeline transport fields. The intrusions of OFPS need to be located. In this system, the original signals consist of noises, interferences, and intrusion signals. Here, noises are background and harmless interferences possessing with high power, and the intrusion signals are the main target of detection in this system. Hence, the study stresses on extracting the intrusion signals from the total ones. The proposed method can be divided into two parts, constant false alarm rate （CFAR） and dilation and erosion （DE）. The former is applied to eliminate noises, and the latter is to remove interferences. According to some researches, the feature of noise background accords with the CFAR spatial detection. Furthermore, the detection results after CFAR can be presented as a binary image of time and space. Besides, interferences are relatively disconnected. Consequently, they can be eliminated by DE which is introduced from the image processing. To sum up, this novel method is based on CFAR and DE which can eliminate noises and interferences effectively. Moreover, it performs a brilliant detection performance. A series of tests were developed in Men Tou Gou of Beijing, China, and the reliability of proposed method can be verified by these tests.