Trifocal Relative Pose from Lines at Points and its Efficient Solution

We present a new minimal problem for relative pose estimation mixing point features with lines incident at points observed in three views and its efficient homotopy continuation solver. We demonstrate the generality of the approach by analyzing and solving an additional problem with mixed point and line correspondences in three views. The minimal problems include correspondences of (i) three points and one line and (ii) three points and two lines through two of the points which is reported and analyzed here for the first time. These are difficult to solve, as they have 216 and - as shown here - 312 solutions, but cover important practical situations when line and point features appear together, e.g., in urban scenes or when observing curves. We demonstrate that even such difficult problems can be solved robustly using a suitable homotopy continuation technique and we provide an implementation optimized for minimal problems that can be integrated into engineering applications. Our simulated and real experiments demonstrate our solvers in the camera geometry computation task in structure from motion. We show that new solvers allow for reconstructing challenging scenes where the standard two-view initialization of structure from motion fails.Comment: This material is based upon work supported by the National Science Foundation under Grant No. DMS-1439786 while most authors were in residence at Brown University's Institute for Computational and Experimental Research in Mathematics -- ICERM, in Providence, R

Glucagon-like peptide-1 receptor agonists as a disease-modifying therapy for knee osteoarthritis mediated by weight loss:Findings from the Shanghai Osteoarthritis Cohort

Objective: Obesity is a risk factor for knee osteoarthritis (KOA) development and progression. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are indicated for type 2 diabetes mellitus (T2DM) and obesity. However, whether KOA patients can benefit from GLP-1RA therapies has not been sufficiently investigated, especially in the long term. Methods: The Shanghai Osteoarthritis Cohort study is a prospective, observational, multicentre study of &gt;40 000 adults with clinically diagnosed osteoarthritis aged &gt;45 years in Shanghai. We identified all KOA participants with comorbid T2DM enrolled from 1 January 2011 to 1 January 2017. Primary outcome was incidence of knee surgery after enrolment. Secondary outcomes included pain-relieving medication use, number of intra-articular therapies, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and medial femorotibial joint cartilage thickness. To evaluate the effects of GLP-1RA, we performed before-and-after comparison and comparison with participants who had no GLP-1RA exposure. Results: For an intergroup comparison (non-GLP-1RA vs GLP-1RA), more weight loss (adjusted mean difference in weight change from baseline-7.29 kg (95% CI-8.07 to-6.50 kg), p&lt;0.001) and lower incidence of knee surgery (93/1574 (5.9%) vs 4/233 (1.7%), adjusted p=0.014) were observed in the GLP-1RA group. Statistically significant differences in mean change from baseline for the WOMAC total and pain subscale scores were observed (adjusted mean difference in WOMAC total score-1.46 (95% CI-2.84 to-0.08), p=0.038; adjusted mean difference in WOMAC pain subscore-3.37 (95% CI-5.79 to-0.94), p=0.007). Cartilage-loss velocity of the medial femorotibial joint was significantly lower in the GLP-1RA group postadjustment for baseline characteristics (adjusted mean difference-0.02 mm (95% CI-0.03 to-0.002 mm), p=0.004). For the before-and-after comparison within the GLP-1RA group, we observed a significant decrease of symptom-relieving medication consumption and cartilage loss velocity of medial femorotibial joint (after-treatment vs before-treatment:-0.03±0.05 vs-0.05±0.07 mm/year, p&lt;0.001). The association between GLP-1RA exposure and decreased incidence of knee surgery was mediated by weight reduction (mediation proportion: 32.1%), instead of glycaemic control (too small to calculate). Conclusion: With sufficient treatment duration, GLP-1RA therapies might be disease-modifying for KOA patients with comorbid T2DM, possibly mediated by weight loss. Further investigation is needed to elucidate effects of GLP-1RA on disease process, joint structure and patient-reported outcomes of osteoarthritis.</p

Multifocus Image Fusion Using Biogeography-Based Optimization

For multifocus image fusion in spatial domain, sharper blocks from different source images are selected to fuse a new image. Block size significantly affects the fusion results and a fixed block size is not applicable in various multifocus images. In this paper, a novel multifocus image fusion algorithm using biogeography-based optimization is proposed to obtain the optimal block size. The sharper blocks of each source image are first selected by sum modified Laplacian and morphological filter to contain an initial fused image. Then, the proposed algorithm uses the migration and mutation operation of biogeography-based optimization to search the optimal block size according to the fitness function in respect of spatial frequency. The chaotic search is adopted during iteration to improve optimization precision. The final fused image is constructed based on the optimal block size. Experimental results demonstrate that the proposed algorithm has good quantitative and visual evaluations

Managing China's energy sector: between the market and the state

As China has now become the largest energy consumer in the world, its energy sector has understandably huge domestic and global implications. In this Special Issue, which is an interdisciplinary one, comprising a set of eight in-depth empirical studies by leading international experts in the field, we set out to examine the management of the transformation of China's conventional and renewable energy sectors, with special attention to state–business relations and their link to the market

Crowdsourcing with tullock contests: A new perspective

Incentive mechanisms for crowdsourcing have been extensively studied under the framework of all-pay auctions. Along a distinct line, this paper proposes to use Tullock contests as an alternative tool to design incentive mechanisms for crowdsourcing. We are inspired by the conduciveness of Tullock contests to attracting user entry (yet not necessarily a higher revenue) in other domains. In this paper, we explore a new dimension in optimal Tullock contest design, by superseding the contest prize - which is fixed in conventional Tullock contests - with a prize function that is dependent on the (unknown) winner\u27s contribution, in order to maximize the crowdsourcer\u27s utility. We show that this approach leads to attractive practical advantages: (a) it is well-suited for rapid prototyping in fully distributed web agents and smartphone apps; (b) it overcomes the disincentive to participate caused by players\u27 antagonism to an increasing number of rivals. Furthermore, we optimize conventional, fixed-prize Tullock contests to construct the most superior benchmark to compare against our mechanism. Through extensive evaluations, we show that our mechanism significantly outperforms the optimal benchmark, by over three folds on the crowdsourcer\u27s utility cum profit and up to nine folds on the players\u27 social welfare