scholarly journals Estimation accuracy of species abundance based on environmental DNA with relation to its production source, state, and assay methodology suggested by meta-analyses

2021 ◽  
Author(s):  
Toshiaki Jo ◽  
Hiroki Yamanaka
Keyword(s):  
Meta Analysis ◽  
Empirical Studies ◽  
Species Abundance ◽  
Environmental Dna ◽  
Efficient Estimation ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Abundance Estimation ◽  
Natural Environments ◽  
Promising Tool

Environmental DNA (eDNA) analysis is a promising tool for non-disruptive and cost-efficient estimation of species abundance. However, its practical applicability in natural environments is limited because it is unclear whether eDNA concentrations actually represent species abundance in the field. Although the importance of accounting for eDNA dynamics, such as transport and degradation, has been discussed, the influences of eDNA characteristics, including production source and state, and methodology, including collection and quantification strategy and abundance metrics, on the accuracy of eDNA-based abundance estimation were entirely overlooked. We conducted a meta-analysis using 56 previous eDNA literature and investigated the relationships between the accuracy (R2) of eDNA-based abundance estimation and eDNA characteristics and methodology. Our meta-regression analysis found that R2 values were significantly lower for crustaceans than fish, suggesting that less frequent eDNA production owing to their external morphology and physiology may impede accurate estimation of their abundance via eDNA. Moreover, R2 values were positively associated with filter pore size, indicating that selective collection of larger-sized eDNA, which is typically fresher, could improve the estimation accuracy of species abundance. Furthermore, R2 values were significantly lower for natural than laboratory conditions, while there was no difference in the estimation accuracy among natural environments. Our findings shed a new light on the importance of what characteristics of eDNA should be targeted for more accurate estimation of species abundance. Further empirical studies are required to validate our findings and fully elucidate the relationship between eDNA characteristics and eDNA-based abundance estimation.

scholarly journals Estimation accuracy of species abundance based on environmental DNA with relation to its production source and state suggested by meta-analyses

2021 ◽  
Author(s):  
Toshiaki Jo ◽  
Hiroki Yamanaka
Keyword(s):  
Empirical Studies ◽  
Species Abundance ◽  
Environmental Dna ◽  
Molecular State ◽  
Efficient Estimation ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Abundance Estimation ◽  
Natural Environments ◽  
Meta Analyses

Environmental DNA (eDNA) analysis is a promising tool for non-disruptive and cost-efficient estimation of species abundance. However, its practical applicability in natural environments is limited owing to a potential gap between eDNA concentration and species abundance in the field. Although the importance of accounting for eDNA dynamics, such as transport and degradation, has been discussed, the influence of eDNA characteristics, including production source and cellular/molecular state, on the accuracy of eDNA-based abundance estimation was entirely overlooked. We conducted meta-analyses using 44 of previous eDNA studies and investigated the relationships between the accuracy (R) of eDNA-based abundance estimation and eDNA characteristics. First, we found that estimated R values were significantly lower for crustaceans and mussels than fish. This finding suggests that less frequent eDNA production of these taxa owing to their external morphology and physiology may impede accurate estimation of their abundance via eDNA. Moreover, linear mixed modeling showed that, despite high variances, R values were positively correlated with filter pore size, indicating that selective collection of larger-sized eDNA, which is typically fresher, could improve the estimation accuracy of species abundance. Although our collected dataset was somewhat biased to the studies targeting specific taxa, our findings shed a new light on the importance of what characteristics of eDNA should be targeted for more accurate estimation of species abundance. Further empirical studies are required to validate our findings and fully elucidate the relationship between eDNA characteristics and eDNA-based abundance estimation.

scholarly journals Functionality of the Crosswise Model for assessing sensitive or transgressive behavior: A systematic review and meta-analysis

2021 ◽  
Author(s):  
Dominic Sagoe ◽  
Maarten J.L.F. Cruyff ◽  
Owen Spendiff ◽  
Razieh Chegeni ◽  
Olivier de Hon ◽  
...  
Keyword(s):  
Systematic Review ◽  
Quality Assessment ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Indirect Estimation ◽  
Promising Tool ◽  
Reliable Assessment ◽  
Transgressive Behavior ◽  
Crosswise Model ◽  
Estimation Models

Tools for reliable assessment of socially sensitive or transgressive behavior warrant constant development. Among them, the Crosswise Model (CM) has gained considerable attention. Therefore, we systematically reviewed and meta-analysed empirical applications of CM and addressed a gap for quality assessment of indirect estimation models. To our knowledge, the present study presents the first systematic review of the functionality of CM, and quality assessment of CM and indirect estimation models in general. Guided by the PRISMA protocol, we identified 35 empirical studies from electronic database and reference searches, of which 25 were comparative validation studies (CVS) with CM estimates and direct question (DQ). Results of the meta-analysis indicate that CM outperforms DQ on the “more is better” validation criterion, and increasingly so with more behavior sensitivity. However, little difference was observed between DQ and CM estimates for items with DQ prevalence around 50%. Based on empirical evidence available to date, our study provides support for the superiority of CM to DQ. Despite some limitations, CM is a valuable and promising tool for assessing sensitive or transgressive behavior.

scholarly journals Functionality of the Crosswise Model for Assessing Sensitive or Transgressive Behavior: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Dominic Sagoe ◽  
Maarten Cruyff ◽  
Owen Spendiff ◽  
Razieh Chegeni ◽  
Olivier de Hon ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Tax Evasion ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Population Level ◽  
Academic Misconduct ◽  
Prevalence Studies ◽  
Promising Tool ◽  
Transgressive Behavior ◽  
Crosswise Model

Tools for reliable assessment of socially sensitive or transgressive behavior warrant constant development. Among them, the Crosswise Model (CM) has gained considerable attention. We systematically reviewed and meta-analyzed empirical applications of CM and addressed a gap for quality assessment of indirect estimation models. Guided by the PRISMA protocol, we identified 45 empirical studies from electronic database and reference searches. Thirty of these were comparative validation studies (CVS) comparing CM and direct question (DQ) estimates. Six prevalence studies exclusively used CM. One was a qualitative study. Behavior investigated were substance use and misuse (k = 13), academic misconduct (k = 8), and corruption, tax evasion, and theft (k = 7) among others. Majority of studies (k = 39) applied the “more is better” hypothesis. Thirty-five studies relied on birthday distribution and 22 of these used P = 0.25 for the non-sensitive item. Overall, 11 studies were assessed as high-, 31 as moderate-, and two as low quality (excluding the qualitative study). The effect of non-compliance was assessed in eight studies. From mixed CVS results, the meta-analysis indicates that CM outperforms DQ on the “more is better” validation criterion, and increasingly so with higher behavior sensitivity. However, little difference was observed between DQ and CM estimates for items with DQ prevalence estimate around 50%. Based on empirical evidence available to date, our study provides support for the superiority of CM to DQ in assessing sensitive/transgressive behavior. Despite some limitations, CM is a valuable and promising tool for population level investigation.

scholarly journals Simultaneous absolute quantification and sequencing of fish environmental DNA in a mesocosm by quantitative sequencing technique

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tatsuhiko Hoshino ◽  
Ryohei Nakao ◽  
Hideyuki Doi ◽  
Toshifumi Minamoto
Keyword(s):  
Fish Species ◽  
High Throughput Sequencing ◽  
Correlation Coefficients ◽  
Environmental Dna ◽  
Digital Pcr ◽  
Absolute Quantification ◽  
Taqman Probe ◽  
Individual Species ◽  
Natural Environments ◽  
Target Sequence

AbstractThe combination of high-throughput sequencing technology and environmental DNA (eDNA) analysis has the potential to be a powerful tool for comprehensive, non-invasive monitoring of species in the environment. To understand the correlation between the abundance of eDNA and that of species in natural environments, we have to obtain quantitative eDNA data, usually via individual assays for each species. The recently developed quantitative sequencing (qSeq) technique enables simultaneous phylogenetic identification and quantification of individual species by counting random tags added to the 5′ end of the target sequence during the first DNA synthesis. Here, we applied qSeq to eDNA analysis to test its effectiveness in biodiversity monitoring. eDNA was extracted from water samples taken over 4 days from aquaria containing five fish species (Hemigrammocypris neglectus, Candidia temminckii, Oryzias latipes, Rhinogobius flumineus, and Misgurnus anguillicaudatus), and quantified by qSeq and microfluidic digital PCR (dPCR) using a TaqMan probe. The eDNA abundance quantified by qSeq was consistent with that quantified by dPCR for each fish species at each sampling time. The correlation coefficients between qSeq and dPCR were 0.643, 0.859, and 0.786 for H. neglectus, O. latipes, and M. anguillicaudatus, respectively, indicating that qSeq accurately quantifies fish eDNA.

scholarly journals Online State-of-Charge Estimation Based on the Gas–Liquid Dynamics Model for Li(NiMnCo)O2 Battery

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 324
Author(s):  
Haobin Jiang ◽  
Xijia Chen ◽  
Yifu Liu ◽  
Qian Zhao ◽  
Huanhuan Li ◽  
...  
Keyword(s):  
Stress Test ◽  
Robustness Analysis ◽  
Open Circuit ◽  
Combined Cycle ◽  
State Of Charge ◽  
Constant Current ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Battery Management System ◽  
Liquid Dynamics

Accurately estimating the online state-of-charge (SOC) of the battery is one of the crucial issues of the battery management system. In this paper, the gas–liquid dynamics (GLD) battery model with direct temperature input is selected to model Li(NiMnCo)O2 battery. The extended Kalman Filter (EKF) algorithm is elaborated to couple the offline model and online model to achieve the goal of quickly eliminating initial errors in the online SOC estimation. An implementation of the hybrid pulse power characterization test is performed to identify the offline parameters and determine the open-circuit voltage vs. SOC curve. Apart from the standard cycles including Constant Current cycle, Federal Urban Driving Schedule cycle, Urban Dynamometer Driving Schedule cycle and Dynamic Stress Test cycle, a combined cycle is constructed for experimental validation. Furthermore, the study of the effect of sampling time on estimation accuracy and the robustness analysis of the initial value are carried out. The results demonstrate that the proposed method realizes the accurate estimation of SOC with a maximum mean absolute error at 0.50% in five working conditions and shows strong robustness against the sparse sampling and input error.

scholarly journals Driver Liability Assessment in Vehicle Collisions in Spain

2021 ◽  
Vol 18 (4) ◽  
pp. 1475
Author(s):  
Almudena Sanjurjo-de-No ◽  
Blanca Arenas-Ramírez ◽  
José Mira ◽  
Francisco Aparicio-Izquierdo
Keyword(s):  
Road Safety ◽  
Accurate Estimation ◽  
Main Hypothesis ◽  
Self Organizing Maps ◽  
Safety Measures ◽  
Vehicle Collisions ◽  
Promising Tool ◽  
Visual Clustering ◽  
Open Question ◽  
The Impact

An accurate estimation of exposure is essential for road collision rate estimation, which is key when evaluating the impact of road safety measures. The quasi-induced exposure method was developed to estimate relative exposure for different driver groups based on its main hypothesis: the not-at-fault drivers involved in two-vehicle collisions are taken as a random sample of driver populations. Liability assignment is thus crucial in this method to identify not-at-fault drivers, but often no liability labels are given in collision records, so unsupervised analysis tools are required. To date, most researchers consider only driver and speed offences in liability assignment, but an open question is if more information could be added. To this end, in this paper, the visual clustering technique of self-organizing maps (SOM) has been applied to better understand the multivariate structure in the data, to find out the most important variables for driver liability, analyzing their influence, and to identify relevant liability patterns. The results show that alcohol/drug use could be influential on liability and further analysis is required for disability and sudden illness. More information has been used, given that a larger proportion of the data was considered. SOM thus appears as a promising tool for liability assessment.

scholarly journals A meta-analysis of the literature on climate change and migration

2021 ◽  
pp. 1-52
Author(s):  
Michel Beine ◽  
Lionel Jeusette
Keyword(s):  
Climate Change ◽  
Climatic Factors ◽  
Human Mobility ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Displacement Effect ◽  
Methodological Choices ◽  
Econometric Methods ◽  
And Migration

Abstract Recent surveys of the literature on climate change and migration emphasize the important diversity of outcomes and approaches of the empirical studies. In this paper, we conduct a meta-analysis in order to investigate the role of the methodological choices of these empirical studies in finding some particular results concerning the role of climatic factors as drivers of human mobility. We code 51 papers representative of the literature in terms of methodological approaches. This results in the coding of more than 85 variables capturing the methodology of the main dimensions of the analysis at the regression level. These dimensions include authors' reputation, type of mobility, measures of mobility, type of data, context of the study, econometric methods, and last but not least measures of the climatic factors. We look at the influence of these characteristics on the probability of finding any effect of climate change, a displacement effect, an increase in immobility, and evidence in favor of a direct vs. an indirect effect. Our results highlight the role of some important methodological choices, such as the frequency of the data on mobility, the level of development, the measures of human mobility and of the climatic factors as well as the econometric methodology.

How Spatially Concentrated Are Industrial Clusters?: A Meta-analysis

2021 ◽  
pp. 088541222110129
Author(s):  
Li Fang ◽  
Joshua Drucker
Keyword(s):  
Spatial Scale ◽  
Knowledge Spillovers ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Industrial Clusters ◽  
Policy Makers ◽  
Unit Of Analysis ◽  
Industry Sector

This study conducts a meta-analysis of empirical studies that have measured the spatial scale of industrial clustering. Two types of scales are examined: the peak scale (at which cluster effects are maximized) and the maximum reach (beyond which cluster effects are undetectable). We find that the scale varies significantly by the unit of analysis, industry sector, country of study, and the sources of cluster effects examined (e.g., knowledge spillovers, localization, and urbanization). Planners and policy makers should tailor the geographies embodied in cluster strategies to match the specific local needs and circumstances.

scholarly journals Development of a Deep Neural Network Model for Estimating Joint Location of Occupant Indoor Activities for Providing Thermal Comfort

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 696
Author(s):  
Eun Ji Choi ◽  
Jin Woo Moon ◽  
Ji-hoon Han ◽  
Yongseok Yoo
Keyword(s):  
Neural Network ◽  
Thermal Comfort ◽  
Deep Neural Network ◽  
Mean Squared Error ◽  
Thermal Environment ◽  
The Body ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Body Parts ◽  
Joint Location

The type of occupant activities is a significantly important factor to determine indoor thermal comfort; thus, an accurate method to estimate occupant activity needs to be developed. The purpose of this study was to develop a deep neural network (DNN) model for estimating the joint location of diverse human activities, which will be used to provide a comfortable thermal environment. The DNN model was trained with images to estimate 14 joints of a person performing 10 common indoor activities. The DNN contained numerous shortcut connections for efficient training and had two stages of sequential and parallel layers for accurate joint localization. Estimation accuracy was quantified using the mean squared error (MSE) for the estimated joints and the percentage of correct parts (PCP) for the body parts. The results show that the joint MSEs for the head and neck were lowest, and the PCP was highest for the torso. The PCP for individual activities ranged from 0.71 to 0.92, while typing and standing in a relaxed manner were the activities with the highest PCP. Estimation accuracy was higher for relatively still activities and lower for activities involving wide-ranging arm or leg motion. This study thus highlights the potential for the accurate estimation of occupant indoor activities by proposing a novel DNN model. This approach holds significant promise for finding the actual type of occupant activities and for use in target indoor applications related to thermal comfort in buildings.

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