scholarly journals Severe Testing and Characterization of Change Points in Climate Time Series

2021 ◽  
Author(s):  
James Ricketts ◽  
Roger Jones
Keyword(s):  
Statistical Testing ◽  
Detection Methods ◽  
Times Series ◽  
Climate Shifts ◽  
Abrupt Changes ◽  
Simple Detection ◽  
Abrupt Shifts ◽  
Climate Time Series ◽  
Severity Criteria

This paper applies misspecification (M-S) testing to the detection of abrupt changes in climate regimes as part of undertaking severe testing of climate shifts versus trends. Severe testing, proposed by Mayo and Spanos, provides severity criteria for evaluating statistical inference using probative criteria, requiring tests that would find any flaws present. Applying M-S testing increases the severity of hypothesis testing. We utilize a systematic approach, based on well-founded principles that combines the development of probative criteria with error statistical testing. Given the widespread acceptance of trend-like change in climate, especially temperature, tests that produce counter-examples need proper specification. Reasoning about abrupt shifts embedded within a complex times series requires detection methods sensitive to level changes, accurate in timing, and tolerant of simultaneous changes of trend, variance, autocorrelation, and red-drift, given that many of these measures may shift together. Our preference is to analyse the raw data to avoid pre-emptive assumptions and test the results for robustness. We use a simple detection method, based on the Maronna-Yohai (MY) test, then re-assess nominated shift-points using tests with varied null hypotheses guided by M-S testing. Doing so sharpens conclusions while avoiding an over-reliance on data manipulation, which carries its own assumptions.

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.

scholarly journals Genetic and Pathogenic Characterization of QX(GI-19)-Recombinant Infectious Bronchitis Viruses in South Korea

Viruses ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1163
Author(s):  
So-Youn Youn ◽  
Ji-Youn Lee ◽  
You-Chan Bae ◽  
Yong-Kuk Kwon ◽  
Hye-Ryoung Kim
Keyword(s):  
Phylogenetic Analysis ◽  
Disease Prevention ◽  
South Korea ◽  
Prevention And Control ◽  
Genetic Recombination ◽  
Detection Methods ◽  
Infectious Bronchitis ◽  
Reference Sequences ◽  
And Control

Infectious bronchitis viruses (IBVs) are evolving continuously via genetic drift and genetic recombination, making disease prevention and control difficult. In this study, we undertook genetic and pathogenic characterization of recombinant IBVs isolated from chickens in South Korea between 2003 and 2019. Phylogenetic analysis showed that 46 IBV isolates belonged to GI-19, which includes nephropathogenic IBVs. Ten isolates formed a new cluster, the genomic sequences of which were different from those of reference sequences. Recombination events in the S1 gene were identified, with putative parental strains identified as QX-like, KM91-like, and GI-15. Recombination detection methods identified three patterns (rGI-19-I, rGI-19-II, and rGI-19-III). To better understand the pathogenicity of recombinant IBVs, we compared the pathogenicity of GI-19 with that of the rGI-19s. The results suggest that rGI-19s may be more likely to cause trachea infections than GI-19, whereas rGI-19s were less pathogenic in the kidney. Additionally, the pathogenicity of rGI-19s varied according to the genotype of the major parent. These results indicate that genetic recombination between heterologous strains belonging to different genotypes has occurred, resulting in the emergence of new recombinant IBVs in South Korea.

scholarly journals Viruses and Virus Diseases of Rubus

Plant Disease ◽  
2013 ◽  
Vol 97 (2) ◽  
pp. 168-182 ◽  
Author(s):  
Robert R. Martin ◽  
Stuart MacFarlane ◽  
Sead Sabanadzovic ◽  
Diego Quito ◽  
Bindu Poudel ◽  
...  
Keyword(s):  
Far East ◽  
Fruit Production ◽  
Detection Methods ◽  
Center Of Origin ◽  
The Family ◽  
Production Stages ◽  
Rubus Species ◽  
Polymerase Chain ◽  
Made In

Blackberry and raspberry are members of the family Rosaceae. They are classified in the genus Rubus, which comprises hundreds of species and has a center of origin in the Far East. Rubus is divided into 15 subgenera with blackberries classified in the Rubus (formerly Eubatus) and raspberries in the Idaeobatus subgenera. Rubus species are propagated vegetatively and are subject to infection by viruses during development, propagation, and fruit production stages. Reports of initial detection and symptoms of more than 30 viruses, virus-like diseases, and phytoplasmas affecting Rubus spp. were reviewed more than 20 years ago. Since the last review on Rubus viruses, significant progress has been made in the molecular characterization of many of the viruses that infect Rubus spp. Currently, reverse transcription–polymerase chain reaction detection methods are available for most of the viruses known to infect Rubus. The goals of this article are to update the knowledge on previously characterized viruses of Rubus, highlight recently described viruses, review the virus-induced symptoms, describe the advances made in their detection, and discuss our knowledge about several virus complexes that cause serious diseases in Rubus. Virus complexes have been identified recently as the major cause of diseases in blackberries and raspberries.

Econometrics for Modelling Climate Change

2021 ◽  
Author(s):  
Jennifer L. Castle ◽  
David F. Hendry
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Econometric Modeling ◽  
Complex Data ◽  
Explanatory Variables ◽  
Stochastic Trends ◽  
Trend Breaks ◽  
Abrupt Shifts ◽  
Climate Time Series ◽  
Do So

Shared features of economic and climate time series imply that tools for empirically modeling nonstationary economic outcomes are also appropriate for studying many aspects of observational climate-change data. Greenhouse gas emissions, such as carbon dioxide, nitrous oxide, and methane, are a major cause of climate change as they cumulate in the atmosphere and reradiate the sun’s energy. As these emissions are currently mainly due to economic activity, economic and climate time series have commonalities, including considerable inertia, stochastic trends, and distributional shifts, and hence the same econometric modeling approaches can be applied to analyze both phenomena. Moreover, both disciplines lack complete knowledge of their respective data-generating processes (DGPs), so model search retaining viable theory but allowing for shifting distributions is important. Reliable modeling of both climate and economic-related time series requires finding an unknown DGP (or close approximation thereto) to represent multivariate evolving processes subject to abrupt shifts. Consequently, to ensure that DGP is nested within a much larger set of candidate determinants, model formulations to search over should comprise all potentially relevant variables, their dynamics, indicators for perturbing outliers, shifts, trend breaks, and nonlinear functions, while retaining well-established theoretical insights. Econometric modeling of climate-change data requires a sufficiently general model selection approach to handle all these aspects. Machine learning with multipath block searches commencing from very general specifications, usually with more candidate explanatory variables than observations, to discover well-specified and undominated models of the nonstationary processes under analysis, offers a rigorous route to analyzing such complex data. To do so requires applying appropriate indicator saturation estimators (ISEs), a class that includes impulse indicators for outliers, step indicators for location shifts, multiplicative indicators for parameter changes, and trend indicators for trend breaks. All ISEs entail more candidate variables than observations, often by a large margin when implementing combinations, yet can detect the impacts of shifts and policy interventions to avoid nonconstant parameters in models, as well as improve forecasts. To characterize nonstationary observational data, one must handle all substantively relevant features jointly: A failure to do so leads to nonconstant and mis-specified models and hence incorrect theory evaluation and policy analyses.

scholarly journals Use of multi-locus sequencing typing as identification method for the food-borne pathogen Listeria monocytogenes: a review

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Sonia Lamon ◽  
Domenico Meloni ◽  
Simonetta Gianna Consolati ◽  
Anna Mureddu ◽  
Rina Mazzette
Keyword(s):  
Listeria Monocytogenes ◽  
Detection Methods ◽  
Causative Organism ◽  
Intracellular Pathogen ◽  
Bacterial Strains ◽  
New Approach ◽  
Food Borne ◽  
Global Epidemiology ◽  
Selection Of

<em>Listeria monocytogenes</em> is an ubiquitous, intracellular pathogen which has been implicated within the past decade as the causative organism in several outbreaks of foodborne diseases. In this review, a new approach to molecular typing primarily designed for global epidemiology has been described: multi-<em>locus</em> sequencing typing (MLST). This approach is novel, in that it uses data that allow the unambiguous characterization of bacterial strains via the Internet. Our aim is to present the currently available selection of references on <em>L. monocytogenes</em> MLST detection methods and to discuss its use as <em>gold</em> <em>standard</em> to <em>L. monocytogenes</em> subtyping method.

Characterization of the interactions between uranium and colloids in soil by on-line fractionation multi-detection methods

2008 ◽  
pp. 807-814
Author(s):  
Céline Claveranne-Lamolére ◽  
Gaëtane Lespes ◽  
Jean Aupiais ◽  
Eric Pili ◽  
Fabien Pointurier ◽  
...  
Keyword(s):  
Detection Methods ◽  
On Line

scholarly journals Process Intensification of Dichlorodiphenyltrichloroethane Detection Methods for Determining Trace Concentrations in Soils

2020 ◽  
Vol 1 (1) ◽  
pp. 63-74
Author(s):  
Jinghan Zhao ◽  
Stephen Vanderburgt ◽  
Rafael M. Santos ◽  
Yi Wai Chiang
Keyword(s):  
Operating Time ◽  
Process Intensification ◽  
Soil Samples ◽  
Detection Methods ◽  
Ultrasonic Probe ◽  
Time Consumption ◽  
Trace Concentrations ◽  
Similar Yield ◽  
Conventional Detection

Dichlorodiphenyltrichloroethane (DDT) residue in Ontario soil is expected to be found at trace levels, since it has been banned for over 45 years in Canada. This presents challenges to the efficiency and accuracy of conventional detection methods. This study intensified the conventional DDT detection method, in the characterization of aged soil samples collected from historically-treated sites in Ontario. Recovery, time consumption, and labor intensity were considered for the intensification evaluation. Ultrasonic probe extraction was found to significantly shorten the extraction time, with similar yield compared to ultrasonic water bath extraction and homogenized extraction. Homogenized extraction for 24 h following ultrasonic probe extraction can increase yield over 27%. Rotary evaporator concentration was used, since it can reduce the operating time with comparable recovery. The Florisil clean-up column used in the conventional method was removed from the intensified method, due to its negligible effect and high time consumption. The intensified method may be valuable for further investigation to determine other trace level organochlorine pesticide residues in soil samples.

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