Determination of uncertainties of geomechanical parameters of metamorphic rocks using petrographic analyses

Geomechanical parameters of intact metamorphic rocks determined from laboratory testing remain highly uncertain because of the great intrinsic variability associated with the degrees of metamorphism.The aim of this paper is to develop a proper methodology to analyze the uncertainties of geomechanical characteristics by focusing on three domains,i.e.data treatment process,schistosity angle,and mineralogy.First,the variabilities of the geomechanical laboratory data of Westwood Mine(Quebec,Canada)were examined statistically by applying different data treatment techniques,through which the most suitable outlier methods were selected for each parameter using multiple decision-making criteria and engineering judgment.Results indicated that some methods exhibited better performance in identifying the possible outliers,although several others were unsuccessful because of their limitation in large sample size.The well-known boxplot method might not be the best outlier method for most geomechanical parameters because its calculated confidence range was not acceptable according to engineering judgment.However,several approaches,including adjusted boxplot,2MADe,and 2SD,worked very well in the detection of true outliers.Also,the statistical tests indicate that the best-fitting probability distribution function for geomechanical intact parameters might not be the normal distribution,unlike what is assumed in most geomechanical studies.Moreover,the negative effects of schistosity angle on the uniaxial compressive strength(UCS)variabilities were reduced by excluding the samples within a specific angle range where the UCS data present the highest variation.Finally,a petrographic analysis was conducted to assess the associated uncertainties such that a logical link was found between the dispersion and the variabilities of hard and soft minerals.

Methods to detect a vian influenza virus for food safety surveillance

Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization （WHO） and the World Organisation for Animal Health （Office International des Epizooties, OIE） and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.

Blind detection of liquefaction by existing methods for New Zealand M_L6.3 earthquake on Feb. 22,2011

Real-time liquefaction monitoring and warning techniques are new ways to mitigate liquefaction hazard. A key point is to establish a reverse liquefaction detection method based on seismic records. However, the existing methods are quite limited and the reliability requires verification. On Feb. 22, 2011 an earthquake of magnitude 6.3 struck at New Zealand＇s South Island. Remarkable liquefaction phenomena were reported, which provide an opportunity to verify the existing liquefaction detection methods. 27 acceleration records within 50 km to the epicenter were selected to perform a blind detection by using the existing methods, including Miyajima method, Suzuki method, Kostadinov-Yamazaki method and Yuan-Sun method. The blind detection results indicate that Yuan-Sun method gives correct results for seven confirmed sites, and Suzuki method and Yuan-Sun method yield correct detection for a reported non-liquefied site. Four methods including the Yuan-Sun method give identical detection for four sites and three methods also including the Yuan-Sun method give identical detection for ten sites. Besides, there are five sites, for which the four methods give opposite detection.

Research Progress on Detection Methods of Melamine and Cyanuric Acid Residue in Dairy Products and Feedstuff

[Objective] More accurate, rapid and sensitive method of melamine and cyanuricacid residue in dairy products and feedstuff were re- viewed. [ Method] Physicochemical properties, metabolism, uses, harm and detection methods of melamine and cyanuric acid were analyzed and described. [ Result] Melamine and cyanuric acid, when used alone, were slightly toxic, but long -term intake could lead to animal reproductive and urinary system damage. [ Condusion] Establishing a more sensitive, fast and easy to popularize detection method for elarnine and cyanuricacid res- idue in dairy products and feedstuff was necessary.

Advances in Detection Methods for Invasive Pest Bactrocera dorsalis

Bactrocera dorsalis Hendel （Diptera： Tephritidae） is an invasive pest around the world. The paper summarizes biological and ecological characteristics of B, dorsalis, and reviews its detection methods from the aspects of morphological identification, acoustic detection and molecular detection, in order to provide a reference for further research and development of new detection methods. The hot issues in the study of B. dorsalis, such as ecological adaptation pattern, diffusion pathways and mechanisms, sustainable control measures, are also put forward in the paper.

Dengue virus infection:A review of advances in the emerging rapid detection methods

Dengue virus infections are increasing worldwide generally and in Asia,Central and South America and Africa,particularly.It poses a serious threat to the children population.The rapid and accurate diagnostic systems are essentially required due to lack of effective vaccine against dengue virus and the progressive spread of the dengue virus infection.The recent progress in developing micro-and nano-fabrication techniques has led to low cost and scale down the biomedical point-of-care devices.Starting from the conventional and modern available methods for the diagnosis of dengue infection,this review examines several emerging rapid and point-of-care diagnostic devices that hold significant potential for the progress in smart diagnosis tools.The given review revealed that an effective vaccine is required urgently against all the dengue virus serotypes.However,the rapid detection methods of dengue virus help in early treatment and significantly reduce the dengue virus outbreak.

Research progress on detection methods of the asymptomatic COVID- 19 infected persons

The global pandemic of COVID-19 has brought great harm and challenges to many countries and regions around the world.The majority of COVID-19 patients have typical clinical manifestations,but the number of asymptomatic infections is increasing as COVID-19 research continues and SARS-CoV-2 testing improves.Many asymptomatic COVID-19 patients with no obvious clinical symptoms are able to transmit the virus to others due to the presence of SARS-CoV-2 in their bodies,thus greatly accelerating the worldwide pandemic and posing great difficulty and threat to global epidemic prevention and control.Therefore,early detection and identification of asymptomatic infected persons through various testing methods are effective measures to control the COVID-19 pandemic.This article will provide a brief review of the available methods and techniques for detecting asymptomatic COVID-19 patients.

Advances in Detection Methods of Koi Herpes Virus

Koi herpes virus is a new virus found in the aquaculture production of Cryprinus carpiod and common carp in recent years. Currently, virus isolation and identification is still the traditional method for the detection of Koi herpes virus, while molecular biology detection method has become the current developmental di- rection due to its characteristics of more sensitive, specific and rapid. Furthermore, people are still committed to exploring new detection methods for the detection of Koi herpes vires. In this paper, traditional and newly-developed detection methods of Koi herpes vires in recent years were summarized, in order to provide refer- ence for further exploring rapid and accurate diagnostic detection method.

Harms of Mycotoxins to Animals and Research Progress of Detection Methods

Mycotoxin is widely distributed in various feedstuffs and feeds of animals.Mycotoxin not only causes feed deterioration,but also leads to various diseases of animals,or even results in acute toxic death,causing great harm to the breeding industry.In this paper,the harm of mycotoxin to animals and its detection methods in feed and animals are summarized and analyzed,so as to provide the reference basis for further improving the detection methods of mycotoxin and reducing the harm of mycotoxin to breeding industry.

Research Advances in Detection Methods of Plant Growth Regulators for Agricultural Products

In recent years,plant growth regulators are widely used in agricultural products.As the toxicity of plant growth regulator residues has gained increasing concerns,trace analysis methods for plant growth regulators have been developed.In this paper,the major methods with advantages and disadvantages for the detection and pre-treatment of plant growth regulator residues in agricultural products were summarized,including gas chromatography(GC),high performance liquid chromatography(HPLC),chromatographic technique combined with mass spectrometry,enzyme-linked immunosorbent assay(ELISA),capillary electrophoresis(CE)and so on.Meanwhile,the development prospects were also discussed.

Different Detection and Treatment Methods for <i>Entamoeba histolytica</i>and <i>Entamoeba dispar</i>in Water/Wastewater: A Review

Entamoeba histolytica is an anaerobic parasitic protozoan and well known as a human pathogen, while its close relative, Entamoeba dispar, also possesses similar characteristics as an infectious agent. These microorganisms are generally transmitted in fecal-contaminated water. However, E. dispar present in industrial wastewater is also capable of creating biofilms that can cause adverse impacts in piping networks. Therefore, it is important to detect both of these protozoan species in water and to find a cost-effective technique for inactivation or management control. This review article summarizes the available detection methods in water and wastewater matrices along with feasible disinfection techniques.

Food Safety Detection Methods Applied to National Special Rectification of Product Quality and Food Safety

Afour-month period of national special rectification for product quality and food safety officially started on August 25, and was focused on eight fields, including those of agricultural products and processed foods.……

Methods for Detection of Viruses in Water and Wastewater

Viruses present in water might be harmful for human health and life. Nowadays over 100 pathogenic human virus species occur in water polluted with sewage. Chlorination, which is the most popular disinfection method is not able to remove easily viruses from treated water. Due to this, it’s necessary to detect viruses in water before treatment in order to determine disinfectant dose and to ensure the sanitary safety level of treated water. The aim of this article is to review viruses detection methods as well as the problems related to implementation of those methods in analysis of water and wastewater samples.

Sources, distribution, behavior, and detection techniques of microplastics in soil: A review

In recent years, the problem of environmental pollution caused by microplastics has attracted widespread attention. This paper reviews the latest research progress in terms of the source, content and distribution characteristics, harm, and detection technology of soil microplastics by referring to the relevant literature on soil microplastics worldwide. It concludes that:(1) Existing studies worldwide have detected the presence of microplastics in soil, water, and atmosphere, and the use of agricultural films, sewage sludge,and other man-made activities are the main sources of microplastics in soil;(2) microplastics can adsorb heavy metals, persistent organic pollutants and antibiotics in soil, change the physical and chemical properties of soil. This will result in composite pollution and harm to the ecosystem;(3) microplastics in soil not only can destroy the activity of key soil microorganisms, but also enter the body of crops and soil animals, affecting normal growth of crops and soil animals, and further threaten human health;(4) at present, there is no unified operating standard for the sampling, processing, and detection process of microplastics. Analysis methods such as visual inspection, spectroscopy, and thermal analysis have both advantages and disadvantages, and emerging detection technologies require urgent development.Microplastics have become a new pollutant in soil and their distribution characteristics are closely related to human activities. They pollute the environment and threaten human health through the food chain.Although related research on soil microplastics has just begun, it will become the focus of research in the future.

A Secure Hardware Implementation for Elliptic Curve Digital Signature Algorithm

Since the end of the 1990s,cryptosystems implemented on smart cards have had to deal with two main categories of attacks:side-channel attacks and fault injection attacks.Countermeasures have been developed and validated against these two types of attacks,taking into account a well-defined attacker model.This work focuses on small vulnerabilities and countermeasures related to the Elliptic Curve Digital Signature Algorithm(ECDSA)algorithm.The work done in this paper focuses on protecting the ECDSA algorithm against fault-injection attacks.More precisely,we are interested in the countermeasures of scalar multiplication in the body of the elliptic curves to protect against attacks concerning only a few bits of secret may be sufficient to recover the private key.ECDSA can be implemented in different ways,in software or via dedicated hardware or a mix of both.Many different architectures are therefore possible to implement an ECDSA-based system.For this reason,this work focuses mainly on the hardware implementation of the digital signature ECDSA.In addition,the proposed ECDSA architecture with and without fault detection for the scalar multiplication have been implemented on Xilinxfield programmable gate arrays(FPGA)platform(Virtex-5).Our implementation results have been compared and discussed.Our area,frequency,area overhead and frequency degradation have been compared and it is shown that the proposed architecture of ECDSA with fault detection for the scalar multiplication allows a trade-off between the hardware overhead and the security of the ECDSA.

Development of piezoelectric-based technology for application in civil structural health monitoring

Piezoelectric material,as one of the great potential materials,had attracted lots of attention all over the world due to its distinguish advantages.In this paper,the development of piezoelectric-based technology for application in the field of civil structural health monitoring(CSHM),was summarized and discussed.Based on the different identification mechanisms,the piezoelectric transducer-based technology can be divided into two main approaches as the active or passive sensing and detection methods.This paper summarized the development of these two approaches and discussed their applications in the area of civil structural health monitoring,such as structural and concrete engineering,bridge engineering,pipeline engineering,protection engineering for geological hazards and earthquake disasters,and so on.In addition,the electrical mechanical impedance(EMI)technique,as one of the active identification methods,was also detailly presented.Finally,its great potential for the piezoelectric-based technique was presented based on the detail discussion,especially in the areas of civil structural health monitoring.

Establishment of a Loop-mediated Isothermal Amplification Method for Rice Bacterial Leaf Brown Spot Disease

Rice bacterial leaf brown spot disease caused by Pseudomonas syringae pv.syringae(Pss)is a major disease on rice.In recent years,Pss has emerged worldwide,seriously affecting rice production.It is very important to establish a rapid detection method of Pss for the diagnosis and prevention of this disease.In order to robust and accurately diagnose the rice bacterial leaf brown spot disease in the field and laboratory,an assay system for the Pss was developed in this study,and the specific sequence of hrcN was used as the target,based on loop-mediated isothermal amplification(LAMP).The best detection system was MgSO 48 mmol·L^(-1),Bst DNA polymerase 8 U,dNTP 1.4 mmol·L^(-1),the ratio of internal and outer primers was 2:1,the reaction temperature was 63℃,the reaction time was 45 min,and the lowest sensitivity was 104 CFU·mL^(-1).This results provided an accurate and robust method for laboratory and field diagnosis of bacterial leaf brown spot disease of rice.

A reasoning diagram based method for fault diagnosis of railway point system

Railway Point System(RPS)is an important infrastructure in railway industry and its faults may have significant impacts on the safety and efficiency of train operations.For the fault diagnosis of RPS,most existing methods assume that sufficient samples of each failure mode are available,which may be unrealistic,especially for those modes of low occurrence frequency but with high risk.To address this issue,this work proposes a novel fault diagnosis method that only requires the power signals generated under normal RPS operations in the training stage.Specifically,the failure modes of RPS are distinguished through constructing a reasoning diagram,whose nodes are either binary logic problems or those that can be decomposed into the problems of the binary logic.Then,an unsupervised method for the signal segmentation and a fault detection method are combined to make decisions for each binary logic problem.Based on the results of decisions,the diagnostic rules are established to identify the failure modes.Finally,the data collected from multiple real-world RPSs are used for validation and the results demonstrate that the proposed method outperforms the benchmark in identifying the faults of RPSs.

Application Research of Sonar Detection Method in Melting Exploration at the Bottom of Piles

Karst landforms are widely distributed in China,and are most common in Yunnan,Guizhou and Guangxi.If the development of karst caves at the bottom of the piles cannot be accurately ascertained before the construction of bridge pile foundations,accidents such as hole collapse,slurry leakage,and drill sticking will easily occur.In this paper,the principle and method of sonar detection for detecting karst caves at the bottom of bridge piles was introduced,and the sonar detection data and the cave situation at the bottom of the pile during the construction process in combination with the case of Yunnan Zhenguo Highway Project was analyzed,which verifies the practicability and reliability of sonar detection method reliability.