Common CuckoosCuculus canoruschange their nest-searching strategy according to the number of available host nests

Ibis ◽  
2013 ◽  
Vol 156 (1) ◽  
pp. 189-197 ◽  
Author(s):  
Václav Jelínek ◽  
Petr Procházka ◽  
Milica Požgayová ◽  
Marcel Honza

2020 ◽  
Vol 15 (1) ◽  
pp. 37-42 ◽  
Author(s):  
Xiaobin Yang ◽  
Haishi Zheng ◽  
Yuan Liu ◽  
Dingjun Hao ◽  
Baorong He ◽  
...  

Aims/Background: Ovariectomy (OVX)-induced murine model is widely used for postmenopausal osteoporosis study. Our current study was conducted to systematically review and essentially quantified the bone mass enhancing effect of puerarin on treating OVX-induced postmenopausal osteoporosis in murine model. Methods: Literatures from PUBMED, EMBASE, and CNKI were involved in our searching strategy by limited the inception date to January 9th, 2019. Moreover, the enhancing effect of puerarin on bone mass compared to OVX-induced rats is evaluated by four independent reviewers. Finally, all the data were extracted, quantified and analyzed via RevMan, besides that in our current review study, we assessed the methodological quality for each involved study. Results: Based on the searching strategy, eight randomization studies were finally included in current meta-analysis and systematic review. According to the data analysis by RevMan, puerarin could improve bone mineral density (BMD); (eight studies, n=203; weighted mean difference, 0.05; 95% CI, 0.03-0.07; P<0.0001) using a random-effects model. There is no significant difference between puerarin and estrogen (seven studies, n=184; weighted mean difference, 0.00; 95% CI, -0.01 to 0.00; P=0.30). Conclusions: Puerarin showed upregulating effects on bone mass in OVX-induced postmenopausal osteoporosis in murine model. More studies of the effect of puerarin on bone density in OVX animals are needed.



2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sheng-Chu Chi ◽  
Yi-No Kang ◽  
Yi-Ming Huang

AbstractPolypoidal choroidal vasculopathy (PCV) is a vision-threatening disease common in Asian populations. However, the optimal treatment for PCV remains under debate. We searched the databases with optimal searching strategy. The study included randomized clinical trials and prospective studies that recruited patients with active PCV who had received interventions, including PDT, anti-VEGF, or a combination of PDT and anti-VEGF. The Grading of Recommendations Assessment, Development, and Evaluation methodology was used for rating the quality of evidence. Our study included 11 studies involving 1277 patients. The network meta-analysis of RCTs revealed the anti-VEGF group, early combination group, and late combination group had significant BCVA changes compared with the PDT group. Early combination therapy led to a significant decrease in CRT compared with PDT, anti-VEGF, and late combination therapy. Additionally, the early combination group had a significantly higher complete polyp regression rate than the anti-VEGF group. No significant differences were detected in the analysis of the number of anti-VEGF injections and safety profile. This network meta-analysis revealed that early combination therapy exhibited better efficacy related to anatomical outcomes than other therapies. Nonetheless, no significant differences related to BCVA change could be detected between anti-VEGF and late combination therapy.



2008 ◽  
Vol 80 (4) ◽  
pp. 529-537 ◽  
Author(s):  
Marco Vannini ◽  
Stefano Cannicci ◽  
Elisha Mrabu ◽  
Rocco Rorandelli ◽  
Sara Fratini


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kunyong Chen ◽  
Yong Zhao ◽  
Jiaxiang Wang ◽  
Hongwen Xing ◽  
Zhengjian Dong

Purpose This paper aims to propose a fast and robust 3D point set registration method for pose estimation of assembly features with few distinctive local features in the manufacturing process. Design/methodology/approach The distance between the two 3D objects is analytically approximated by the implicit representation of the target model. Specifically, the implicit B-spline surface is adopted as an interface to derive the distance metric. With the distance metric, the point set registration problem is formulated into an unconstrained nonlinear least-squares optimization problem. Simulated annealing nested Gauss-Newton method is designed to solve the non-convex problem. This integration of gradient-based optimization and heuristic searching strategy guarantees both global robustness and sufficient efficiency. Findings The proposed method improves the registration efficiency while maintaining high accuracy compared with several commonly used approaches. Convergence can be guaranteed even with critical initial poses or in partial overlapping conditions. The multiple flanges pose estimation experiment validates the effectiveness of the proposed method in real-world applications. Originality/value The proposed registration method is much more efficient because no feature estimation or point-wise correspondences update are performed. At each iteration of the Gauss–Newton optimization, the poses are updated in a singularity-free format without taking the derivatives of a bunch of scalar trigonometric functions. The advantage of the simulated annealing searching strategy is combined to improve global robustness. The implementation is relatively straightforward, which can be easily integrated to realize automatic pose estimation to guide the assembly process.



2019 ◽  
Vol 3 (2) ◽  
pp. 11-18
Author(s):  
George Mweshi

Extracting useful and novel information from the large amount of collected data has become a necessity for corporations wishing to maintain a competitive advantage. One of the biggest issues in handling these significantly large datasets is the curse of dimensionality. As the dimension of the data increases, the performance of the data mining algorithms employed to mine the data deteriorates. This deterioration is mainly caused by the large search space created as a result of having irrelevant, noisy and redundant features in the data. Feature selection is one of the various techniques that can be used to remove these unnecessary features. Feature selection consequently reduces the dimension of the data as well as the search space which in turn increases the efficiency and the accuracy of the mining algorithms. In this paper, we investigate the ability of Genetic Programming (GP), an evolutionary algorithm searching strategy capable of automatically finding solutions in complex and large search spaces, to perform feature selection. We implement a basic GP algorithm and perform feature selection on 5 benchmark classification datasets from UCI repository. To test the competitiveness and feasibility of the GP approach, we examine the classification performance of four classifiers namely J48, Naives Bayes, PART, and Random Forests using the GP selected features, all the original features and the features selected by the other commonly used feature selection techniques i.e. principal component analysis, information gain, relief-f and cfs. The experimental results show that not only does GP select a smaller set of features from the original features, classifiers using GP selected features achieve a better classification performance than using all the original features. Furthermore, compared to the other well-known feature selection techniques, GP achieves very competitive results.



Author(s):  
Qi Chen ◽  
Shugen Wang ◽  
Xiuguo Liu

Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas) has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.



With increasing usage of technologies and smart solutions smart cities are developed and enabled with many smart services. This paper has conducted a systematic literature review to find out IOT applications and its role in Traffic Control System. The review protocol is formulated to define some of the research questions, searching strategy, selection criteria of papers and how data is extracted. This paper contributed towards one main issue: The various research areas of Internet of Things and Role of IOT in the Traffic Control Services? All the papers were categorized by the application services of IOT and Traffic Control services they discussed. All the recent work were categorised under the application in various area like traffic and transport; Agriculture; Security; Healthcare; energy management; city infrastructure; and modes of transport. This paper reviews the various methods of traffic control system in different perspective of different IOT application areas.



Author(s):  
Nianwang Wan ◽  
Zhenyu Duan ◽  
Yongdong Hua ◽  
Qingbin Wang ◽  
Weihai Li


Author(s):  
Calin Gurau

The use of online shopping agents has increased dramatically in the last 10 years, as a result of e-commerce development. Despite the importance of these online applications, very few studies attempted to identify and analyse the main factors that influence the users’ perception regarding the service quality of online shopping agents, and consequently, the elements that determine the users’ choice of online shopping agents. The present study attempts to fill this literature gap, identifying on the basis of primary data analysis, the various circumstantial or personal factors that can determine the choice of a specific searching strategy and shopping agent.



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