Application of Dynamic Linear Detecting Method in Data Processing of the Portable Blood Sugar Analyzer

In this paper,a dynamic linear detecting method,that the non-linear coefficient NL% was led and the non-linearity of data were estimated continuously and dynamically and determined when NL% exceeded reference value (5%),was used for data processing and could solve the problem caused by the phenomenon of substrate depleting occurred following the redox reaction in portable blood sugar analyzer.By contrast to the conventional end-point method,the dynamic linear detecting method is based on multipoint data collecting.Experiments of measuring the calibration glucose solution with 8 various concentrations from 50 mg/dl to 400 mg/dl were carried out with the analyzer developed by our group.The linear regression curve,whose correlation for the data was 0.9995 and the residual was 2.8080,were obtained.The obtained correlation,residual, and the computation workload are all fit for the portable blood sugar analyzer.

Advances in Research of Collection and Detection Methods of Microplastics in Environment

As a new type of environmental pollutants,microplastics have gradually attracted people's attention.A large number of plastics discharged into the environment by human beings are constantly aging and breaking,and finally become microplastics.Microplastics can adsorb pollutants in the environment,and their components have certain toxicity,which can cause different degrees of harm to organisms.Due to the structural characteristics of microplastic particles,such as small particle size,large specific surface area,and their distribution in different environmental media,it is very difficult to accurately detect microplastics.Reliable collection and detection methods are the key to the study of environmental behavior of microplastics.In this study,the collection and detection methods of microplastics in the environment were reviewed,and the development direction of microplastics detection technology in the future was prospected.This study has a certain reference value for the related research and the prevention and treatment of micro-plastic pollution.

Wheeze detecting method based on spectrogram entropy analysis

In order to eliminate the subjectivity of wheeze diagnosis and improve the accuracy of objective detecting methods,this paper introduces a wheeze detecting method based on spectrogram entropy analysis.This algorithm mainly comprises three steps which are preprocessing,features extracting and wheeze detecting based on support vector machine(SVM).Herein,the preprocessing consists of the short-time Fourier transform(STFT) decomposition and detrending.The features are extracted from the entropy of spectrograms.The step of detrending makes the difference of the features between wheeze and normal lung sounds more obvious.Moreover,compared with the method whose decision is based on the empirical threshold,there is no uncertain detecting result any more.Results of two testing experiments show that the detecting accuracy(AC) are 97.1%and 95.7%,respectively,which proves that the proposed method could be an efficient way to detect wheeze.

A detecting method for line-spectrum target by fusing output DC jump to fluctuations ratio of sub-band spatial spectrum and beam space

The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conventional broadband energy integration method. The required spectrum level is theoretically discussed when the detection performance of the known line detection is better than that of broadband energy integration method. Under the condition of the target can be detected in line spectrum band, the relationship between the line spectrum level and signal to noise ratio （SNR） is also discussed. This paper proposes a line spectrum target detection method that a matrix using DC jump to fluctuations ratios of sub-band spatial spectrum and beam space output is constructed. This matrix acts as a filter that the line spectrum target with certain frequency and azimuth is passed at most. By fusing with the other sub band results, the conventional detection performance can be improved. At the same time, the applicable condition and detection performance are analyzed in the paper. The simulation and the sea trial data processing results show that the algorithm can effectively extract weak goal line spectrum target under the condition of multi-interference. The algorithm doesn＇t need multi-frame statistics and the detection performance is closer to the optimal line spectrum method.

A NEW DETECTING METHOD FOR CONDITIONS OF EXISTENCE OF HOPF BIFURCATION

A new detecting method for the conditions of existence of the Hopf bifurcation is given in terms of the coefficients of the characteristic polynomial at the equilibrium by using the Hopf bifurcation theory and matrix theory. The method is available and important for the study of the existence of the Hopf bifurcation for higher differential equations which often occur in biological models, chemical models, epidemiological models, and models of AIDS.

A method for detecting the breaking of wind-generated waves in deep water

The breaking of wind-generated waves is an important phenomenon in the ocean, having close relation to many aspects of the ocean, such as air-sea interaction, ocean wave dynamics, oceanic remote sensing and ocean engineering. The first problem encountered in both its theoretical study and practical measurement is how to detect the breaking of waves.

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.

A Method for Detecting Wide-scale Network Traffic Anomalies

Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as abnormal network routing,can cause network anomalies.Network anomaly detection and analysis are very important to Computer Security Incident Response Teams(CSIRT).But wide-scale traffic anomaly detection requires extracting anomalous modes from large amounts of high-dimensional noise-rich data,and interpreting the modes;so,it is very difficult.This paper proposes a general method based on Principle Component Analysis(PCA)to analyze network anomalies.This method divides the traffic matrix into normal and anomalous subspaces,maps traffic vectors into the normal subspace,gets the distance from detected vector to average normal vector,and detects anomalies based on that distance.

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.

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.

Potential clinical application of microRNAs in bladder cancer

Bladder cancer(BC)is the tenth most prevalent malignancy globally,presenting significant clinical and societal challenges because of its high incidence,rapid progression,and frequent recurrence.Presently,cystoscopy and urine cytology serve as the established diagnostic methods for BC.However,their efficacy is limited by their invasive nature and low sensitivity.Therefore,the development of highly specific biomarkers and effective noninvasive detection strategies is imperative for achieving a precise and timely diagnosis of BC,as well as for facilitating an optimal tumor treatment and an improved prognosis.microRNAs(miRNAs),short noncoding RNA molecules spanning around 20–25 nucleotides,are implicated in the regulation of diverse carcinogenic pathways.Substantially altered miRNAs form robust functional regulatory networks that exert a notable influence on the tumorigenesis and progression of BC.Investigations into aberrant miRNAs derived from blood,urine,or extracellular vesicles indicate their potential roles as diagnostic biomarkers and prognostic indicators in BC,enabling miRNAs to monitor the progression and predict the recurrence of the disease.Simultaneously,the investigation centered on miRNA as a potential therapeutic agent presents a novel approach for the treatment of BC.This review comprehensively analyzes biological roles of miRNAs in tumorigenesis and progression,and systematically summarizes their potential as diagnostic and prognostic biomarkers,as well as therapeutic targets for BC.Additionally,we evaluate the progress made in laboratory techniques within this field and discuss the prospects.

Comparison of Genomic DNA Extraction Methods for Chenopodium quinoa Willd

To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS method and high- salt Iow-pH method, respectively. The quality and yield of extracted DNA was deter- mined using agarose gel electrophoresis and UV spectrophotometry. At the same time, the PCR-SSR and SSCP molecular detection was also performed. The results showed that the gel test strips, without obvious decomposition, of all the extraction methods were relatively obvious; the genomic DNA yield extracted by modified CTAB method was highest, followed by that by SDS method, and the genomic DNA extracted by high-salt Iow-pH method was lowest： the genomic DNA yields extracted by different methods from Chenopodium quinoa Wiltd leaves were all high- er than those from roots and stems; the quality of Chenopodium quinoa Willd ge- nomic DNA extracted by modified CTAB method and high-salt Iow-pH method was better, and polyphenols, polysaccharides and other impurities were removed more completely. The PCR-SSR and SSCP detection results showed that the genomic DNA extracted by different methods from different tissues of Chenopodium quinoa Willd all could be better amplified, and high-quality strips could be obtained. So the Chenopodium quinoa Willd genomic DNA extracted by the three methods all can be used for subsequent molecular biology research.

Establishment of Reverse-transcription Loopmediated Isothermal Amplification Method for Detection of Wheat Streak Mosaic Virus

A reverse-transcription loop-mediated isothermal amplification （RT-LAMP） method was established for the detection of wheat streak mosaic virus （WSMV）. Ac-cording to the conservative regions of the genes that encode the coat protein of WSMV, 2 pairs of primers were designed. Final y, the 1st pair of primers was select-ed through the specificity test. The sensitivity test showed the sensitivity of RT-LAMP method was 10 times higher than that of RT-PCR. In addition, the amplifica-tion of target gene could be judged visual y from the presence of fluorescence （cal-cein） in the final reaction system. The RT-LAMP method, established in this study, was rapid, easy, specific and sensitive. Moreover, it did not require sophisticated equip-ment. The RT-LAMP was suitable for the rapid detection of WSMV.

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.

Impact of climate change and human activities on the spatiotemporal dynamics of surface water area in Gansu Province, China

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas.This study took Gansu Province,China,a typical area with complex terrain and variable climate,as the research subject.Based on Google Earth Engine,we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022,and quantitatively analyzed the main causes of regional differences in surface water area.The findings revealed that surface water area in Gansu Province expanded by 406.88 km2 from 1985 to 2022.Seasonal surface water area exhibited significant fluctuations,while permanent surface water area showed a steady increase.Notably,terrestrial water storage exhibited a trend of first decreasing and then increasing,correlated with the dynamics of surface water area.Climate change and human activities jointly affected surface hydrological processes,with the impact of climate change being slightly higher than that of human activities.Spatially,climate change affected the'source'of surface water to a greater extent,while human activities tended to affect the'destination'of surface water.Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted.Therefore,we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water'supply-demand'balance strategies.The study not only sheds light on the dynamics of surface water area in Gansu Province,but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Research Progress of Agricultural Genetically Modified Crop Safety Evaluation

The commercial cultivation of genetically modified(GM)crops has eased the global food crisis and brought considerable economic and social benefits to countries.Because of the potential safety problems,it is necessary to make clear the molecular genetic characteristics,edible safety,planting,processing,and other aspects of the safety evaluation of GM crops.The safety problems existing in the cultivation of GM crops,safety evaluation and detection of GM crops were introduced in this paper,which provided the basis for safety evaluation and effective supervision of GM crops and their products.Commercial cultivation and reasonable supervision based on safety evaluation have far-reaching significance for ensuring consumer safety,enhancing the credibility of the national political system and enhancing citizens'confidence in the safety of GM crop products for consumption.

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.

Application of Compactness Detection to Complicated Concrete-Filled Steel Tube by Ultrasonic Method

An example of using ultrasonic method to detect the compactness of complicated concrete-filled steel tube in certain high-rise building was discussed in this study.Because of the particularity of the complicated concrete-filled steel tubular column,the plane detection method and embedded sounding pipe method were adopted in the process of effectively detecting the column.According to the results of the plane detection method and embedded sounding pipe method,the cementing status of steel tube and concrete can be concluded,which cannot be judged by the hammering method in the rectangular steel tube-reinforced concrete.

Evaluation of multiple surface irradiance-based clear sky detection methods at Xianghe—A heavy polluted site on the North China Plain

Surface irradiance measurements with high temporal resolution can be used to detect clear skies,which is a critical step for further study,such as aerosol and cloud radiative effects.Twenty-one clear-sky detection(CSD)methods are assessed based on five years of 1-min surface irradiance data at Xianghe—a heavily polluted station on the North China Plain.Total-sky imager(TSI)discrimination results corrected by manual checks are used as the benchmark for the evaluation.The performance heavily relies on the criteria adopted by the CSD methods.Those with higher cloudy-sky detection accuracy rates produce lower clear-sky accuracy rates,and vice versa.A general tendency in common among all CSD methods is the detection accuracy deteriorates when aerosol loading increases.Nearly all criteria adopted in CSD methods are too strict to detect clear skies under polluted conditions,which is more severe if clear-sky irradiance is not properly estimated.The mean true positive rate(CSD method correctly detects clear sky)decreases from 45%for aerosol optical depth(AOD)≤0.2%to 6%for AOD>0.5.The results clearly indicate that CSD methods in a highly polluted region still need further improvements.