scholarly journals Spread and Increase of Ratoon Stunting Disease of Sugarcane and Comparison of Disease Detection Methods

Plant Disease ◽  
1999 ◽  
Vol 83 (12) ◽  
pp. 1170-1175 ◽  
Author(s):  
J. W. Hoy ◽  
M. P. Grisham ◽  
K. E. Damann
Keyword(s):  
Yield Loss ◽  
Detection Method ◽  
Xylem Sap ◽  
Disease Spread ◽  
Detection Methods ◽  
Disease Detection ◽  
Correct Identification ◽  
Dot Blot ◽  
Ratoon Stunting Disease ◽  
Enzyme Immunoassays

The spread and increase of ratoon stunting disease (RSD) resulting from two mechanical harvests were compared in eight sugarcane cultivars at two locations. RSD spread and increase were detected in the ratoon crops grown after each harvest and varied among cultivars and locations. Disease spread and increase were greater in plants grown from stalks collected at the first harvest than in the first ratoon growth from the harvested field. RSD infection was determined using five disease detection methods: alkaline-induced metaxylem autofluorescence; microscopic examination of xylem sap; and dot blot, evaporative-binding, and tissue blot enzyme immunoassays. The tissue blot enzyme immunoassay was the most accurate RSD detection method. The dot blot and evaporative-binding enzyme immunoassays were the least sensitive for detection of RSD-infected stalks, and alkaline-induced metaxylem autofluorescence was least accurate for correct identification of noninfected stalks. The results indicate that disease spread and increase are variable even among cultivars susceptible to yield loss due to RSD, and the greatest threat of disease spread and increase occurs at planting.

scholarly journals Penggunaan Pelacak DNA untuk Deteksi Papaya ringspot virus dengan Metode Hibridisasi Asam Nukleat

2018 ◽  
Vol 14 (3) ◽  
pp. 89
Author(s):  
Irsan Nuhantoro ◽  
Sri Hendrastuti Hidayat ◽  
Kikin Hamzah Mutaqin
Keyword(s):  
Nucleic Acid ◽  
Detection Method ◽  
Blot Hybridization ◽  
High Specificity ◽  
Dna Probe ◽  
Ringspot Virus ◽  
Nucleic Acid Hybridization ◽  
Disease Spread ◽  
Papaya Ringspot Virus ◽  
Dot Blot

Use of DNA Probe for Detection of Papaya ringspot virus Using Nucleic Acid Hybridization MethodPapaya ringspot caused by Papaya ringspot virus (PRSV) is one of the most destructive diseases of papaya. The disease had not been found in Indonesia, until disease outbreak in Nangroe Aceh Darussalam was reported in 2012. Since then, the disease spread rapidly in most papaya growing areas in Sumatera, Java and Bali. Papaya ringspot virus (PRSV) is generally detected using serological or polymerase chain reaction methods. Improvement in detection method is necessary to facilitate a more reliable tool for controlling the spread of PRSV. The aim of the research was to construct DNA probe for development of detection method based on nucleic acid hybridization. Molecular characterization based on HCPro gene sequence indicated high homology (97.88 to 99.05%) among PRSV isolates from Boyolali (Central Java), Medan (North Sumatera), Sleman (Yogyakarta) and Tabanan (Bali). Two DNA clones of HCPro gene were selected for probe construction and the probes were then labeled using PCR DIG-dioxigenin. Optimization of nucleic acid dot blot hybridization method to achieve strongest positive reaction was developed, i.e. using stringency washes at 1×SSC, 0.1% SDS, incubation at 60 oC for 15’. The DNA probe for PRSV has a high specificity and sensitifity; it could detect PRSV at the lowest concentration of nucleic acid (0.062 µg µL-1).

scholarly journals PRATD: A Phased Remote Access Trojan Detection Method with Double-Sided Features

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1894
Author(s):  
Chun Guo ◽  
Zihua Song ◽  
Yuan Ping ◽  
Guowei Shen ◽  
Yuhei Cui ◽  
...  
Keyword(s):  
False Positive ◽  
Detection Method ◽  
False Positive Rate ◽  
True Positive Rate ◽  
Remote Access ◽  
Detection Methods ◽  
Security Threats ◽  
True Positive ◽  
Trojan Detection ◽  
Positive Rate

Remote Access Trojan (RAT) is one of the most terrible security threats that organizations face today. At present, two major RAT detection methods are host-based and network-based detection methods. To complement one another’s strengths, this article proposes a phased RATs detection method by combining double-side features (PRATD). In PRATD, both host-side and network-side features are combined to build detection models, which is conducive to distinguishing the RATs from benign programs because that the RATs not only generate traffic on the network but also leave traces on the host at run time. Besides, PRATD trains two different detection models for the two runtime states of RATs for improving the True Positive Rate (TPR). The experiments on the network and host records collected from five kinds of benign programs and 20 famous RATs show that PRATD can effectively detect RATs, it can achieve a TPR as high as 93.609% with a False Positive Rate (FPR) as low as 0.407% for the known RATs, a TPR 81.928% and FPR 0.185% for the unknown RATs, which suggests it is a competitive candidate for RAT detection.

scholarly journals Detection of Movement Events of Long-Track Speed Skating Using Wearable Inertial Sensors

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3649
Author(s):  
Yosuke Tomita ◽  
Tomoki Iizuka ◽  
Koichi Irisawa ◽  
Shigeyuki Imura
Keyword(s):  
Gold Standard ◽  
Detection Method ◽  
Standard Measure ◽  
Detection Methods ◽  
Phase Identification ◽  
Foot Pressure ◽  
Pressure System ◽  
Speed Skating ◽  
Stance Time ◽  
Integrated Detection

Inertial measurement units (IMUs) have been used increasingly to characterize long-track speed skating. We aimed to estimate the accuracy of IMUs for use in phase identification of long-track speed skating. Twelve healthy competitive athletes on a university long-track speed skating team participated in this study. Foot pressure, acceleration and knee joint angle were recorded during a 1000-m speed skating trial using the foot pressure system and IMUs. The foot contact and foot-off timing were identified using three methods (kinetic, acceleration and integrated detection) and the stance time was also calculated. Kinetic detection was used as the gold standard measure. Repeated analysis of variance, intra-class coefficients (ICCs) and Bland-Altman plots were used to estimate the extent of agreement between the detection methods. The stance time computed using the acceleration and integrated detection methods did not differ by more than 3.6% from the gold standard measure. The ICCs ranged between 0.657 and 0.927 for the acceleration detection method and 0.700 and 0.948 for the integrated detection method. The limits of agreement were between 90.1% and 96.1% for the average stance time. Phase identification using acceleration and integrated detection methods is valid for evaluating the kinematic characteristics during long-track speed skating.

scholarly journals Early Detection Methods for Silicosis in Australia and Internationally: A Review of the Literature

2021 ◽  
Vol 18 (15) ◽  
pp. 8123
Author(s):  
Emma K. Austin ◽  
Carole James ◽  
John Tessier
Keyword(s):  
Early Detection ◽  
Literature Review ◽  
Detection Method ◽  
Detection Methods ◽  
X Rays ◽  
Review Of The Literature ◽  
Occupational Lung Disease ◽  
Work Related ◽  
Growing Body ◽  
Future Work

Pneumoconiosis, or occupational lung disease, is one of the world’s most prevalent work-related diseases. Silicosis, a type of pneumoconiosis, is caused by inhaling respirable crystalline silica (RCS) dust. Although silicosis can be fatal, it is completely preventable. Hundreds of thousands of workers globally are at risk of being exposed to RCS at the workplace from various activities in many industries. Currently, in Australia and internationally, there are a range of methods used for the respiratory surveillance of workers exposed to RCS. These methods include health and exposure questionnaires, spirometry, chest X-rays, and HRCT. However, these methods predominantly do not detect the disease until it has significantly progressed. For this reason, there is a growing body of research investigating early detection methods for silicosis, particularly biomarkers. This literature review summarises the research to date on early detection methods for silicosis and makes recommendations for future work in this area. Findings from this review conclude that there is a critical need for an early detection method for silicosis, however, further laboratory- and field-based research is required.

Elimination of outlier measurements for damage detection of structures under changing environmental conditions

2021 ◽  
pp. 147592172199847
Author(s):  
William Soo Lon Wah ◽  
Yining Xia
Keyword(s):  
Damage Detection ◽  
Multiple Regression ◽  
Natural Frequencies ◽  
Detection Method ◽  
Detection Methods ◽  
Structure Model ◽  
Bridge Structure ◽  
Beam Structure ◽  
Dependent Variables ◽  
The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

scholarly journals Recognition of Bimolecular Logic Operation Pattern Based on a Solid-State Nanopore

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 33
Author(s):  
Han Yan ◽  
Zhen Zhang ◽  
Ting Weng ◽  
Libo Zhu ◽  
Pang Zhang ◽  
...  
Keyword(s):  
Self Assembly ◽  
Detection Method ◽  
Logic Gate ◽  
Detection Methods ◽  
Label Free ◽  
Recognition Method ◽  
Operation Pattern ◽  
Simple Detection ◽  
Dna Tetrahedron ◽  
Marker Molecule

Nanopores have a unique advantage for detecting biomolecules in a label-free fashion, such as DNA that can be synthesized into specific structures to perform computations. This method has been considered for the detection of diseased molecules. Here, we propose a novel marker molecule detection method based on DNA logic gate by deciphering a variable DNA tetrahedron structure using a nanopore. We designed two types of probes containing a tetrahedron and a single-strand DNA tail which paired with different parts of the target molecule. In the presence of the target, the two probes formed a double tetrahedron structure. As translocation of the single and the double tetrahedron structures under bias voltage produced different blockage signals, the events could be assigned into four different operations, i.e., (0, 0), (0, 1), (1, 0), (1, 1), according to the predefined structure by logic gate. The pattern signal produced by the AND operation is obviously different from the signal of the other three operations. This pattern recognition method has been differentiated from simple detection methods based on DNA self-assembly and nanopore technologies.

Behavior assessment and applications for BRD diagnosis: preweaned dairy calves

2020 ◽  
pp. 1-4
Author(s):  
Catie Cramer ◽  
Theresa L. Ollivett
Keyword(s):  
Clinical Signs ◽  
Sickness Behavior ◽  
Behavioral Changes ◽  
Dairy Calves ◽  
Detection Methods ◽  
Disease Detection ◽  
Test Characteristics ◽  
Behavioral Studies ◽  
Detection Program ◽  
Behavioral Assessments

Abstract Bovine respiratory disease (BRD) is an important disease in dairy calves due to its long-lasting effects. Early identification results in better outcomes for the animal, but producers struggle to identify all calves with BRD. Sickness behavior, or the behavioral changes that accompany illness, has been investigated for its usefulness as a disease detection tool. Behavioral changes associated with BRD include decreased milk intake and drinking speed, depressed attitude, and less likelihood of approaching a novel object or stationary human. Behavioral measurements are useful, as they can be collected automatically or with little financial input. However, one limitation of many BRD behavioral studies includes the use of either lung auscultation or clinical signs as reference methods, which are imperfect. Additionally, external factors may influence the expression of sickness behavior, which can affect if and when behavior can be used to identify calves with BRD. Behavioral measures available to detect BRD lack adequate sensitivity and specificity to be the sole means of disease detection, especially when detection tools, such as calf lung ultrasound, have better test characteristics. However, using behavioral assessments in addition to other detection methods can allow for a robust BRD detection program that can ameliorate the consequences of BRD.

scholarly journals Over/Undervoltage and Undervoltage Shift of Hybrid Islanding Detection Method of Distributed Generation

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Manop Yingram ◽  
Suttichai Premrudeepreechacharn
Keyword(s):  
Control System ◽  
Distributed Generation ◽  
Hybrid Method ◽  
Detection Method ◽  
System Simulation ◽  
Detection Methods ◽  
Islanding Detection ◽  
Active Method ◽  
Passive Method ◽  
Simulation Results

The mainly used local islanding detection methods may be classified as active and passive methods. Passive methods do not perturb the system but they have larger nondetection zones, whereas active methods have smaller nondetection zones but they perturb the system. In this paper, a new hybrid method is proposed to solve this problem. An over/undervoltage (passive method) has been used to initiate an undervoltage shift (active method), which changes the undervoltage shift of inverter, when the passive method cannot have a clear discrimination between islanding and other events in the system. Simulation results on MATLAB/SIMULINK show that over/undervoltage and undervoltage shifts of hybrid islanding detection method are very effective because they can determine anti-islanding condition very fast.ΔP/P>38.41% could determine anti-islanding condition within 0.04 s;ΔP/P<-24.39% could determine anti-islanding condition within 0.04 s;-24.39%≤ΔP/P≤ 38.41% could determine anti-islanding condition within 0.08 s. This method perturbed the system, only in the case of-24.39% ≤ΔP/P ≤38.41% at which the control system of inverter injected a signal of undervoltage shift as necessary to check if the occurrence condition was an islanding condition or not.

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