A new primer pair for barcoding of bees (Hymenoptera: Anthophila) without amplifying the orthologous coxA gene of Wolbachia bacteria

Abstract Objectives DNA barcoding became an effective method for the identification and monitoring of bees. However, standard primer pairs used for barcoding often result in (co-) amplification of bacterial endosymbionts of the genus Wolbachia, which are widespread among bee species. Here we designed a new primer pair and compared it with the performance of the standard Folmer-primers for a small sample set of bees representing the main taxonomic groups of bees. Results The newly designed primer pair (BeeCox1F1/BeeCox1R2) outperformed the standard barcoding primer (LCO1490/HCO2198). By generating barcodes for a small test set of bees we found that the new primer pair produced high-quality sequences in all cases for unambiguous species identification using BOLD. Conversely, the standard barcoding primers often co-amplified the homologous Wolbachia gene and resulted in mixed chromatogram signals. These sequences showed high similarity with the bacterial endosymbiont instead of the host.

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A New Primer Pair for Barcoding Bees (Hymenoptera, Anthophila) Without Amplifying the Homologous Wolbachia Gene

10.21203/rs.3.rs-669019/v1 ◽

2021 ◽

Author(s):

Christoph Bleidorn ◽

Katharina Henze

Keyword(s):

Dna Barcoding ◽

Species Identification ◽

Small Sample ◽

Test Set ◽

Important Method ◽

Bacterial Endosymbionts ◽

Small Test ◽

Taxonomic Groups ◽

Sample Set ◽

Standard Primer

Abstract ObjectivesDNA barcoding became an important method for the identification and monitoring of bees. However, standard primer pairs used for barcoding often result in (co-) amplification of bacterial endosymbionts of the genus Wolbachia, which are widespread among bee species. Here we designed a new primer pair and compared it with the performance of the standard Folmer-primers for small sample set of bees representing the main taxonomic groups of bees.ResultsThe newly designed primer pair (BeeCox1F1/BeeCox1R2) clearly outperformed the standard barcoding primer (LCO1490/HCO2198). By generating barcodes for a small test set of bees we found that the new primer pair produced in all cases clear sequences for unambiguous species identification using BOLD. In contrast, the standard barcoding primers often resulted in the amplification of the homologous Wolbachia gene, which either resulted in a mixed chromatogram signal or identification of the bacterial endosymbiont instead of the host.

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Updated Kriging-Assisted Shape Optimization of a Gravity Dam

Water ◽

10.3390/w13010087 ◽

2021 ◽

Vol 13 (1) ◽

pp. 87

Author(s):

Yongqiang Wang ◽

Ye Liu ◽

Xiaoyi Ma

Keyword(s):

Surrogate Model ◽

Computational Cost ◽

Region Of Interest ◽

Optimization Procedure ◽

Optimal Shape ◽

Small Sample ◽

Gravity Dam ◽

Kriging Surrogate Model ◽

Gravity Dams ◽

Sample Set

The numerical simulation of the optimal design of gravity dams is computationally expensive. Therefore, a new optimization procedure is presented in this study to reduce the computational cost for determining the optimal shape of a gravity dam. Optimization was performed using a combination of the genetic algorithm (GA) and an updated Kriging surrogate model (UKSM). First, a Kriging surrogate model (KSM) was constructed with a small sample set. Second, the minimizing the predictor strategy was used to add samples in the region of interest to update the KSM in each updating cycle until the optimization process converged. Third, an existing gravity dam was used to demonstrate the effectiveness of the GA–UKSM. The solution obtained with the GA–UKSM was compared with that obtained using the GA–KSM. The results revealed that the GA–UKSM required only 7.53% of the total number of numerical simulations required by the GA–KSM to achieve similar optimization results. Thus, the GA–UKSM can significantly improve the computational efficiency. The method adopted in this study can be used as a reference for the optimization of the design of gravity dams.

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Cannabis and breastfeeding

Paediatrics & Child Health ◽

10.1093/pch/pxaa037 ◽

2020 ◽

Vol 25 (Supplement_1) ◽

pp. S26-S28 ◽

Cited By ~ 1

Author(s):

Lisa Graves

Keyword(s):

Health Care Providers ◽

Small Sample ◽

Adverse Outcomes ◽

Care Providers ◽

High Quality ◽

High Quality Evidence ◽

Small Sample Sizes ◽

The Impact ◽

Quality Evidence

Abstract Cannabis is one of the most commonly used substances in Canada with 15% of Canadians reporting use in 2019. There is emerging evidence that cannabis is linked to an impact on the developing brain in utero and adverse outcomes in infants, children, and adolescents. The impact of cannabis during breastfeeding has been limited by studies with small sample sizes, follow-up limited to 1 year and the challenge of separating prenatal exposure from that during breastfeeding. In the absence of high-quality evidence, health care providers need to continue to engage women in conversation about the potential concerns related to breastfeeding and cannabis use.

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Stepwise Response Surface Method and its Application in Reliability Analysis of Ship Hull Structure

Journal of Offshore Mechanics and Arctic Engineering ◽

10.1115/1.1493199 ◽

2002 ◽

Vol 124 (4) ◽

pp. 226-230 ◽

Cited By ~ 11

Author(s):

Lei Yu ◽

Purnendu K. Das ◽

Yunlong Zheng

Keyword(s):

Response Surface ◽

Goodness Of Fit ◽

Weighting Factor ◽

Small Sample ◽

Surface Approach ◽

Hull Structure ◽

One Step ◽

Actual Contribution ◽

Sample Set ◽

Robust Response

A stepwise response surface approach is proposed in this paper. The response surface is determined by modified stepwise regression, so that the square and cross terms can be absorbed into the model automatically according to their actual contribution, which is calculated by repeated variance analysis. Besides, by applying a weighting factor to the statistical value of contribution and changing the thresholds of introduction and rejection, the entry of each term can be controlled in a fairly flexible manner. None other criteria than those in the traditional statistics are needed to check the goodness of fit. Considering the relatively small sample set at the beginning, the algorithm starts with a linear response surface. As the adaptive iteration proceeds, the bar to quadratic terms is lifted gradually to allow ordered entry. Since the sampling points in one step of iteration are recycled in the succeeding ones, a simple experimental design is enough to fit a robust response surface. A double bottom hull system is analyzed with randomized Young’s modulus, load distribution, and geometric properties. The sensitivity analysis is also performed with respect to the random variables and the parameters in their distributions.

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A Novel Computer-Aided Diagnosis Scheme on Small Annotated Set: G2C-CAD

BioMed Research International ◽

10.1155/2019/6425963 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Guangyuan Zheng ◽

Guanghui Han ◽

Nouman Q. Soomro ◽

Linjuan Ma ◽

Fuquan Zhang ◽

...

Keyword(s):

Medical Image ◽

Medical Image Analysis ◽

Ground Glass Opacity ◽

Semisupervised Learning ◽

Small Sample ◽

Negative Image ◽

Cad System ◽

Computer Aided ◽

Sample Set ◽

Aided Diagnosis

Purpose. Computer-aided diagnosis (CAD) can aid in improving diagnostic level; however, the main problem currently faced by CAD is that it cannot obtain sufficient labeled samples. To solve this problem, in this study, we adopt a generative adversarial network (GAN) approach and design a semisupervised learning algorithm, named G2C-CAD. Methods. From the National Cancer Institute (NCI) Lung Image Database Consortium (LIDC) dataset, we extracted four types of pulmonary nodule sign images closely related to lung cancer: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, obtaining a total of 3,196 samples. In addition, we randomly selected 2,000 non-lesion image blocks as negative samples. We split the data 90% for training and 10% for testing. We designed a DCGAN generative adversarial framework and trained it on the small sample set. We also trained our designed CNN-based fuzzy Co-forest on the labeled small sample set and obtained a preliminary classifier. Then, coupled with the simulated unlabeled samples generated by the trained DCGAN, we conducted iterative semisupervised learning, which continually improved the classification performance of the fuzzy Co-forest until the termination condition was reached. Finally, we tested the fuzzy Co-forest and compared its performance with that of a C4.5 random decision forest and the G2C-CAD system without the fuzzy scheme, using ROC and confusion matrix for evaluation. Results. Four different types of lung cancer-related signs were used in the classification experiment: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, along with negative image samples. For these five classes, the G2C-CAD system obtained AUCs of 0.946, 0.912, 0.908, 0.887, and 0.939, respectively. The average accuracy of G2C-CAD exceeded that of the C4.5 random decision tree by 14%. G2C-CAD also obtained promising test results on the LISS signs dataset; its AUCs for GGO, lobulation, spiculation, pleural indentation, and negative image samples were 0.972, 0.964, 0.941, 0.967, and 0.953, respectively. Conclusion. The experimental results show that G2C-CAD is an appropriate method for addressing the problem of insufficient labeled samples in the medical image analysis field. Moreover, our system can be used to establish a training sample library for CAD classification diagnosis, which is important for future medical image analysis.

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Volume management as a key dimension of a high-quality PD prescription

Peritoneal Dialysis International ◽

10.1177/0896860819895365 ◽

2020 ◽

Vol 40 (3) ◽

pp. 282-292 ◽

Cited By ~ 2

Author(s):

Angela Yee-Moon Wang ◽

Jie Dong ◽

Xiao Xu ◽

Simon Davies

Keyword(s):

Blood Pressure ◽

Peritoneal Dialysis ◽

Kidney Function ◽

Clinical Care ◽

Small Sample ◽

Volume Status ◽

Volume Control ◽

High Quality ◽

Volume Management ◽

Residual Kidney Function

Background: Appropriate volume control is one of the key goals in a peritoneal dialysis (PD) prescription. As such it is an important component of the International Society of Peritoneal Dialysis (ISPD) guideline for “High-quality PD prescription” necessitating a review of the literature on volume management. The workgroup recognized the importance of including within its scope measures of volume status and blood pressure in prescribing high-quality PD therapy. Methods: A Medline and PubMed search for publications addressing volume status and its management in PD since the publication of the 2015 ISPD Adult Cardiovascular and Metabolic Guidelines, from October 2014 through to July 2019, was conducted. Results: There were no randomized controlled trials on blood pressure intervention and six randomized trials of bioimpedance-guided volume management. Generally, all studies were of small sample size, short duration, and used surrogate markers as primary outcomes. As a consequence, only “practice points” were drawn. High-quality goal-directed PD prescription should aim to achieve and maintain clinical euvolemia taking residual kidney function and its preservation into account, so that both fluid removal from peritoneal ultrafiltration and urine output are considered and residual kidney function is not compromised. Blood pressure should be included as a key objective parameter in assessing the quality of PD prescription but there is currently no evidence for a specific target in PD. Clinical examination remains the keystone of routine clinical care. Conclusions: High-quality goal-directed PD prescription should include volume management as one of the key dimensions.

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Small Sample Set Inshore Ship Detection From VHR Optical Remote Sensing Images Based on Structured Sparse Representation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2020.2987827 ◽

2020 ◽

Vol 13 ◽

pp. 2145-2160 ◽

Cited By ~ 1

Author(s):

Yin Zhuang ◽

Lianlin Li ◽

He Chen

Keyword(s):

Remote Sensing ◽

Sparse Representation ◽

Small Sample ◽

Optical Remote Sensing ◽

Remote Sensing Images ◽

Ship Detection ◽

Sample Set

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A New Method to Generate Virtual Samples for Solving Small Sample Set Problems

2011 10th International Conference on Machine Learning and Applications and Workshops ◽

10.1109/icmla.2011.18 ◽

2011 ◽

Cited By ~ 2

Author(s):

Asghar Dehghani ◽

Jun Zheng

Keyword(s):

Small Sample ◽

New Method ◽

Virtual Samples ◽

Sample Set

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Rapid assessment of historic, current and future habitat quality for biodiversity around UK Natura 2000 sites

Environmental Conservation ◽

10.1017/s0376892914000137 ◽

2014 ◽

Vol 42 (1) ◽

pp. 31-40 ◽

Cited By ~ 11

Author(s):

I. N. VOGIATZAKIS ◽

M. T. STIRPE ◽

S. RICKEBUSCH ◽

M. J. METZGER ◽

G. XU ◽

...

Keyword(s):

Land Cover ◽

Rapid Assessment ◽

Natura 2000 ◽

Landscape Composition ◽

Future Scenarios ◽

High Quality ◽

Alternative Future ◽

European Development ◽

Alternative Scenarios ◽

Taxonomic Groups

SUMMARYChanges in landscape composition and structure may impact the conservation and management of protected areas. Species that depend on specific habitats are at risk of extinction when these habitats are degraded or lost. Designing robust methods to evaluate landscape composition will assist decision- and policy-making in emerging landscapes. This paper describes a rapid assessment methodology aimed at evaluating land-cover quality for birds, plants, butterflies and bees around seven UK Natura 2000 sites. An expert panel assigned quality values to standard Coordination of Information on the Environment (CORINE) land-cover classes for each taxonomic group. Quality was assessed based on historical (1950, 1990), current (2000) and future (2030) land-cover data, the last projected using three alternative scenarios: a growth-applied strategy (GRAS), a business-as-might-be-usual (BAMBU) scenario, and sustainable European development goal (SEDG) scenario. A quantitative quality index weighted the area of each land-cover parcel with a taxa-specific quality measure. Land parcels with high quality for all taxonomic groups were evaluated for temporal changes in area, size and adjacency. For all sites and taxonomic groups, the rate of deterioration of land-cover quality was greater between 1950 and 1990 than current rates or as modelled using the alternative future scenarios (2000–2030). Model predictions indicated land-cover quality stabilized over time under the GRAS scenario, and was close to stable for the BAMBU scenario. The SEDG scenario suggested an ongoing loss of quality, though this was lower than the historical rate of c. 1% loss per decade. None of the future scenarios showed accelerated fragmentation, but rather increases in the area, adjacency and diversity of high quality land parcels in the landscape.

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