DeepICP: An End-to-End Deep Neural Network for 3D Point Cloud Registration

We present DeepICP - a novel end-to-end learning-based 3D point cloud registration framework that achieves comparable registration accuracy to prior state-of-the-art geometric methods. Different from other keypoint based methods where a RANSAC procedure is usually needed, we implement the use of various deep neural network structures to establish an end-to-end trainable network. Our keypoint detector is trained through this end-to-end structure and enables the system to avoid the inference of dynamic objects, leverages the help of sufficiently salient features on stationary objects, and as a result, achieves high robustness. Rather than searching the corresponding points among existing points, the key contribution is that we innovatively generate them based on learned matching probabilities among a group of candidates, which can boost the registration accuracy. Our loss function incorporates both the local similarity and the global geometric constraints to ensure all above network designs can converge towards the right direction. We comprehensively validate the effectiveness of our approach using both the KITTI dataset and the Apollo-SouthBay dataset. Results demonstrate that our method achieves comparable or better performance than the state-of-the-art geometry-based methods. Detailed ablation and visualization analysis are included to further illustrate the behavior and insights of our network. The low registration error and high robustness of our method makes it attractive for substantial applications relying on the point cloud registration task.Comment: 10 pages, 6 figures, 3 tables, typos corrected, experimental results updated, accepted by ICCV 201

Paying for Live Broadcast: Predicting Internet Knowledge Product Sharing

Despite researcher’s attempts on examining knowledge sharing behavior, the impact of purchasing behavior on sales of knowledge products remains largely unknown in the existing literature. To fill this void, using the data collected from Zhihu.com, we develop a two-phase framework to assess the impact of factors of live (i.e., price), factors of other audiences (i.e., review scores) and factors of speaker (i.e., reputation) on sales. Moreover, with start date of a live as a dividing point, our study examines the difference of impact of these factors on sales between two sales stages (before a live start VS. after a live starts). Results and implications are analyzed and discussed

Paying for Knowledge: Why People Paying for Live Broadcasts in Online Knowledge Sharing Community?

Powered by the proliferation of social computing and user-generated content, new knowledge sharing platforms in China, including Q&A communities and live broadcasting, were launched and received widely attentions recently. This research is motivated by the tremendous growth of an online knowledge sharing platform, Zhihu Live (www.zhihu.com/lives). Built upon Zhihu community, the usability and functionality of Zhihu Live makes it easy for user to create their own broadcasting lives that can be shared in the community to a wide range of audiences, making this an attractive platform to content creators (speakers) and knowledge consumers (audiences). We therefore propose a two-phase model to investigate the daily sales of Zhihu lives. Hierarchical Linear model was employed to test our hypotheses. Our preliminary results suggest that number of “like” positively affects daily sales before a live starts (phase 1), whereas “like” number, audience review score, and interactions between speakers and audiences during the broadcasting process have significant effects on live’s daily sales after the live starts (phase 2). Implications are discussed and limitations are noted

Modeling the Potential for Aviation Liberalization in Central Asia - Market analysis and implications for the Belt and Road initiative

This study analyzes aviation markets in the five land-locked countries in Central Asia. Panel data spanning from 2007 to 2015 are used to estimate airline entry patterns in origin-destination markets. Econometric estimates for domestic and international markets are subsequently benchmarked, and route groups are paired by alternative matching algorithms so that counter-factual analysis can be conducted. Our investigation suggests that although the Central Asia–China markets are characterized by poor connectivity and high airfares, great benefits could be achieved if more liberal aviation policies such as those proposed by the Belt and Road initiative were introduced. In particular, our counterfactual analysis suggests that if the Central Asia–China markets were regulated and operated in a similar way to the routes between Central Asia and other states, the probability of having aviation services between cities in China and Central Asia would increase by 27%, even by conservative estimates. The number of Chinese destinations could increase by more than 150%. Our study finds strong negative effects of the restrictive regulations on the international aviation markets, and calls for further liberalizations between Central Asia and the region’s major trade partners

Discovery of Novel Insulin Sensitizers: Promising Approaches and Targets

Insulin resistance is the undisputed root cause of type 2 diabetes mellitus (T2DM). There is currently an unmet demand for safe and effective insulin sensitizers, owing to the restricted prescription or removal from market of certain approved insulin sensitizers, such as thiazolidinediones (TZDs), because of safety concerns. Effective insulin sensitizers without TZD-like side effects will therefore be invaluable to diabetic patients. The specific focus on peroxisome proliferator-activated receptor γ- (PPARγ-) based agents in the past decades may have impeded the search for novel and safer insulin sensitizers. This review discusses possible directions and promising strategies for future research and development of novel insulin sensitizers and describes the potential targets of these agents. Direct PPARγ agonists, selective PPARγ modulators (sPPARγMs), PPARγ-sparing compounds (including ligands of the mitochondrial target of TZDs), agents that target the downstream effectors of PPARγ, along with agents, such as heat shock protein (HSP) inducers, 5′-adenosine monophosphate-activated protein kinase (AMPK) activators, 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) selective inhibitors, biguanides, and chloroquines, which may be safer than traditional TZDs, have been described. This minireview thus aims to provide fresh perspectives for the development of a new generation of safe insulin sensitizers

Morphology-dependent photocatalytic activity of TiO2 crystals

646-651TiO2 crystals with different morphologies have been successfully synthesized by simple hydrothermal method. All samples are characterized carefully by XRD, SEM, TEM, and BET techniques and the morphological effect on the photocatalytic activity of the obtained TiO2 crystals has been evaluated by degrading the pollutant molecules. The experimental results show that the TiO2 samples with different morphologies exhibited different activities to pollutant degradation. The core-shell spheres have exhibited the best photocatalytic activity, with the almost complete degradation of methyl orange (MO) and rhodamine B within 15 min under UV-light irradiation. After 20 min UV-light irradiation, the degradation efficiency of the MO solution is about 68.9%. It can be concluded that a morphological effect is responsible for the photocatalytic performance. The crystals with large BET surface area, the small crystallite size shows the better the photocatalytic performance

Assessment of the community status of seagrass bed and its relationship with environmental characteristics in Wenchang, Hainan Island, China

As one of the typical coastal ecosystems, seagrass bed has important ecological service functions. In order to enrich the basic data of multispecies tropical seagrass beds, the main controlling factors affecting the community status of seagrass were identified. In this study, the species, distribution and community characteristics of seagrass in Wenchang were investigated at five stations in 2023, and Spearman correlation analysis and Redundancy analysis were used to investigate the relationship between seagrass and environmental characteristics. The results showed that there were 7 species of seagrass belonging to 5 genera in 2 families along Wenchang coast, including Enhalus acoroides, Thalassia hemprichii, Cymodocea rotundata, Cymodocea serrulata, Halophila ovalis, Halophila minor and Halodule uninervis. The distribution of seagrass beds in Wenchang showed an obvious trend of degradation. Except for the relatively stable of seagrass beds in the central part of Wenchang, the seagrass beds on both the north and south sides decreased significantly, and the coverage of seagrass beds decreased from 24.31% in 2016 to 21.0% in 2020, and further decreased to 20.67% in 2023. The data showed that the coverage and aboveground biomass of seagrass were significantly positively correlated with temperature, and the density of seagrass was significantly positively correlated with DO, but significantly negatively correlated with COD. In addition, increased nutrient salts in the water column could negatively affect seagrass bed. In order to promote the sustainable development of seagrass ecosystem and enhance the stability of seagrass habitat, it is suggested to rationally plan the aquaculture scale of the surrounding area; flexibly manage the rake snail, rake clam and other fishing activities, appropriately reduce the frequency of mining; and scientifically plan marine engineering to reduce the damage to seagrass bed

Research on comprehensive assessment of coastal erosion intensity based on multi index method

The intensity of coastal erosion is a measure of the strength of erosion processes affecting coastal areas. Traditionally, assessments of coastal erosion intensity have relied on singular indices, such as the rate of shoreline retreat or erosion, often prioritizing higher rates over lower ones. This approach, however, lacks comprehensive consideration and scientific rigor. In this study, we adopt a more holistic approach by examining the Qionghai-Wanning coast on the eastern side of Hainan Island. We selected four indices that reflect local conditions and influence coastal erosion strength: Annual rate of shoreline change (T1), Beach annual down-cutting rate (T2), Beach slope (T3), Average particle size of the beach (T4). These indices were used to comprehensively evaluate the erosion intensity of the Qionghai-Wanning coast. The evaluation results categorized the study area into six grades: serious erosion (3.45%), strong erosion (6.90%), erosion (20.69%), micro erosion (44.38%), stabilization (20.69%), and accretion (3.45%). The findings indicate that, under the broader environmental trends of global warming and rising sea levels, most sandy coasts exhibit micro-erosion intensity. Areas experiencing strong and serious erosion are predominantly influenced by human activities, such as those occurring in promenade bays, artificial islands, and harbors. To further understand the relationship between these factors and erosion intensity, we employed the Spearman correlation coefficient method. The analysis revealed that the T1 and the T2 are the primary factors influencing coastal erosion intensity, with the T4 serving as a secondary factor. These factors collectively impact the force and energy absorption of the coast through wave and tidal actions, ultimately determining the intensity of coastal erosion. The multi-index assessment method for coastal erosion intensity demonstrated an accuracy of 82.75%, providing a scientific basis for the management, protection, and restoration of coastal areas