评周大新的长篇小说《预警》

《预警》以军事谍战为叙事框架,关注日益突显的国家安全问题,透视当下社会心理和人性欲望,具有鲜明的时代感和强烈的警世醒人意义。小说注重故事情节的设计,可读性强,在艺术上有独到的探索。

周大新《预警》介入现实的努力和意义

在周大新的小说创作中,《预警》是第一部以军旅为题材的长篇小说。尽管作品表面上所聚焦的是当代新形势下的国家安全和反恐斗争,然而却充满了人道主义情怀。人性的弱点以及随着年龄的增长而日益凸显的精神危机都成为作者思考和探索的重点,同时这种思考和探索紧贴当下的社会环境,将个体的精神世界放置在一个大的背景之中予以观照,具有极强的现实针对性。周大新积极介入生活的态度,是作家自身责任意识和危机意识的表现,在市场化的语境下,他的这种坚守和努力尤为可贵。

Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Non-cooperative Space Target Estimation Algorithm Without Prior Information Dependence Based on Temporal Line of Sight Constraint

Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting.The use of the plane passing through the geo-center and the cutting sequence line of sight(LOS)generates the trajectory-cutting plane.With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated,a motion parameter estimation model in space non-cooperative targets is established,and the Gauss-Newton iteration method is used to solve the flight parameters.The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy,providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning.

WebGIS-based Early Warning System of Farmland Environmental Pollution Caused by Livestock Waste

[Objective]The paper was to quickly get the real-time dynamic status of regional farmland environmental pollution caused by livestock wastes.[Method] With WebGIS as spatial information platform,the network and digital early warning system of farmland environmental pollution caused by livestock wastes was established.[Result] The system realized the functions such as livestock wastes calculation,livestock information query and analysis,nitrogen load quantity estimation of livestock waste,early warning of farmland environmental pollution caused by livestock wastes and visual display of result.[Conclusion] The paper provided scientific basis for the relevant research on farmland environmental pollution caused by livestock wastes.

The Research Status and Enlightenment of Foreign Foodborne Disease Prevention and Control

Foodborne disease is a worldwide il ness and over 1 bil ion people get diseased every year. In China, thousands of foodborne diseases occur every year. It is proved that prevention is the most crucial for control ing foodborne disease. In the research, food safety monitoring system, laws and early warning system in the US and EU were introduced to explore the successful experience and monitoring or control mode suitable for China.

Laws of strata energy release and corresponding safety warning system in metal mine

The strata deformation in mining area was monitored in Dabaoshan copper-iron mine,and an analytical method of strata energy release was put forward.On the basis of chaotic theory,by reconstructing the phase space for time series data of strata energy release,the saturated embedding dimension and the correlation dimension of the dynamic system were obtained to be 4 and 1.212 8,respectively,and the evolution laws of distances between phase points of strata energy release in the phase space were revealed.With grey theory,a prediction model of strata energy release was set up,the maximum error of which was less than 6.7%.The results show that there are chaotic characters in strata energy release during mining;after reconstructing phase space,the subtle changing characteristics of energy release can be magnified,and the internal rules can be fully demonstrated.According to the laws,a warning system for strata stability in mining area was established to provide a technical safeguard for safe mining.

Feature extraction and damage alarming using time series analysis

Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.

Theoretical research on structural damage alarming of long-span bridges using wavelet packet analysis

The state equation and observation equation of the structural dynamic systems under various analysis scales are derived based on wavelet packet analysis. The time-frequency properties of structural dynamic response under various scales are further formulated. The theoretical analysis results reveal that the wavelet packet energy spectrum （WPES） obtained from wavelet packet decomposition of structural dynamic response will detect the presence of structural damage. The sensitivity analysis of the WPES to structural damage and measurement noise is also performed. The transfer properties of the structural system matrix and the observation noise under various analysis scales are formulated, which verify the damage alarming reliability using the proposed WPES with preferable damage sensitivity and noise robusticity.

Short-term warning and integrity monitoring algorithm for coal mine shaft safety

A new short-term warning and integrity monitoring algorithm was proposed for coal mine shaft safety. The Kalman filter (KF) model was used to extract real global positioning system (GPS) kinematic deformation information. The short-term warning model was built by using the two-side cumulative sum (CUSUM) test, which further improves the warning system reliability. Availability (the minimum warning deformation, MWD), false alarm rate (the average run length, ARL), missed rate (the warning delay, WD) and the relationships among them were analyzed and the method choosing warning parameters is given. A test of a deformation simulation platform shows that the warning algorithm can be effectively used for steep deformation warning. A field experiment of the Malan mine shaft in Shanxi coal area illustrates that the proposed algorithm can detect small dynamic changes and the corresponding occurring time. At given warning thresholds (MWD is 15 mm and ARL is 1000),the detected deformations of two consecutive days’ deformation sequences with the algorithm occur at the 705th epoch (705 s) and the 517th epoch (517 s), respectively.

Damage warning of suspension bridges based on neural networks under changing temperature conditions

This paper aims at successive structural damage detection of long-span bridges under changing temperature conditions.First,the frequency-temperature correlation models of bridges are formulated by means of artificial neural network techniques to eliminate the temperature effects on the measured modal frequencies.Then,the measured modal frequencies under various temperatures are normalized to a reference temperature,based on which the auto-associative network is trained to monitor signal damage occurrences by means of neural-network-based novelty detection techniques.The effectiveness of the proposed approach is examined in the Runyang Suspension Bridge using 236-day health monitoring data.The results reveal that the seasonal change of environmental temperature accounts for variations in the measured modal frequencies with averaged variances of 2.0%.And the approach exhibits good capability for detecting the damage-induced 0.1% variance of modal frequencies and it is suitable for online condition monitoring of suspension bridges.

Construction of Early-warning Model for Plant Diseases and Pests Based on Improved Neural Network

By studying principles and methods related to early-warning model of plant diseases and using PSO method, parameter optimization was conducted to backward propagation neural network, and a pre-warning model for plant diseases based on particle swarm and neural network algorithm was established. The test results showed that the construction of early-warning model is effective and feasible, which will provide a via- ble model structure to establish the effective early-warning platform.

Early-warning of Mud Expansion in Sewage Treatment Plants by A/O Technology

Early-warning is an effective way to control mud expansion in sewage treatment plants with A/O technology. In the research, warning indices and technology of active mud were explored and it is concluded that bacteria growth in mud can be obtained by observation of mud appearance and microorganism variety, and measurement of the number of filamentous bacteria, water quality, mud load and age, dissolved oxygen, temperature and pH. Furthermore, filamentous bacteria in mud can be researched through fluorescence in situ hybridization, PCR-temperature denaturing gradient gel electrophoresis and PCR-single-stranded conformation polymorphism in order to determine the characters and states of active mud to achieve early warning of mud expansion.

Construction of Cucumber Powdery Mildew Early Warning System in Solar Greenhouse Based on Internet of Things

ln order to explore the design and construction of cucumber powdery mildew warning system in solar greenhouse, internet of things technology was used to conduct the real-time dynamic monitoring of the incidence of cucumber powdery mildew and cucumber growth environment in solar greenhouse. The growth environ-ment included temperature and humidity of air and soil. Logistic regression model was used to construct cucumber powdery mildew warning model. The results showed that humidity characteristic variable （maximum air humidity） and temperature characteristic variable （maximum air temperature） had significant effects on the inci-dence probability of cucumber powdery mildew in solar greenhouse. And it was fea-sible to construct cucumber powdery mildew warning system in solar greenhouse with internet of things.

Study on the Occurrence and Epidemic Regularity and Region Division of Rice Blast in Nanchong City

With the aim to improve the level of monitoring and warning as well as the comprehensive control of rice blast disease, and to feasibly reduce the disease threat in Nanchong City, the methods of GPS and GIS, systematical monitoring and field survey, rice blast resistance identification, physiologic races of rice blast monitoring, and meteorological data analysis were performed to study the occurrence and epidemic region division, precise demarcation and occurrence and epidemic regularity of rice blast in Nanchong City. This study first completed the epidemic region division and precise demarcation; first clarified the initial affection（beginning period） locations, occurrence characteristics, epidemic trends and characteristics; explicated the existence of four epidemic peak periods of rice blast in the field, where the damage areas of first peak period played a decisive role during the blast epidemic years; in late May, the cumulative occurrence areas and annual occurrence areas presented higher positive correlation with the correlation coefficient of 0.817;and established a prediction model of occurrence areas per year based on the disease field rate at the end of boot stages and the diseased plant rate at dough stages. The results of investigation on the impact factors investigation of blast disease in Nanchong in recent years suggested that the internal causes were the decrease or loss of blast resistance of the rice cultivars, as well as the increase of physiological races with strong resistance to rice blast and the emergence of new virulent physiologic varieties; the external causes were suitable temperature, too much rainy, and sunlight shortage. Between 2010 and 2015, the short-term forecast accuracy for rice blast in Nanchong was up to 100%, and medium-and long-term forecast accuracy was also up to 98% and 95%, respectively, which increased by 5-15% than that before 1997, thereby making the control effect of rice blast in Nanchong increased by 15-30%.

Study on Epidemic Characteristics and Its Causes of Wheat Stripe Rust in Nanchong City

On basis of the research result of stripe rust for 16 years since 1999,the epidemic characteristics and trend of stripe rust in the city were determined.Namely,the earlier the initial stage appeared,the heavier the disease would be.Furthermore,stripe rust has two introduction infection peaks,of which the first peak plays a key role.In farmlands,there are one to three epidemic peaks,and the infection area of the first peak plays the key role on the epidemic area of that year.In addition,the accumulated areas of late January was in significantly positive correlation with annually total area,with a correlation coefficient of 0.769 2.In recent 16 years,the frequency of severe stripe rust was as high as 81.25% which was 50% higher than that before 1995.The slight stripe rust became just in 2013,with a frequency of 6.3%,which indicated that the city has become a region hit by severe stripe rust.The internal reason is the reduction or loss of wheat variety＇s resistance to tripe rust for a new physiological race of rust is becoming pathogenic stronger and be the major race.Big fluctuation of temperatures in warm winter and spring,foggy and dew days slants much would be the external reason.

Early Warning System of Important Meteorological Disasters in Hunan Province

Based on technologies of GRADS, Delphi, WEB and an SQLServer, distri- bution system for major meteorological disasters early warning information in Hunan Province was established. The system consists of warning tips, early warning for different media and early warning query statistics and the network terminal of the system platform includes a business database server, a message platform database server, a sending server and a receiving terminal. The system enjoys some func- tions, such as examination by different users, on-time updating and effectiveness of flood prevention, construction of excessive warning channel, construction of compre-hensive warning information platform and further improvement of information distribution. The system provides references for prevention and reduction of important me- teorological disasters in Hunan.

Design and Realization of Cold Disaster Early Warning System for Subtropics Aquaculture

By analyzing the subtropics aquaculture present situation,the necessity of the construction of cold disaster early warning system for subtropics aquaculture,the research goal and the duty were expounded. The system structure and the frame were introduced in detail. Several key questions and their solutions of the cold disaster early warning system for subtropics aquaculture were put forward.

Research on Resources and Environmental Carrying Capacity

This paper, in the context of resources and environmental carrying capaci-ty, systematic reviewed resources and environmental carrying capacity in monitoring, evaluation and early warning, and then putted forward the development direction for promoting the sustainable development of China’s social and economic environment.

Framework Design of Emergency Public Warning Information Release Platform in Hunan Province

Construction background of Hunan emergency public warning information release platform was introduced,and current status and demands of provincial information release were analyzed.Supported by GIS,Java,and Net,Hunan early warning information release platform of public emergency was constructed based on ORACLE database and Windows 2008 Server,achieving information collection,packaging,transmission,de-packaging,and releasing concentration,standard and processing.In addition,the framework and functional characters of the system were illustrated and the innovation points were explored.The system provides guarantee for meteorological services and disaster prevention or reducing of Hunan public emergencies.