POEM: Reconstructing Hand in a Point Embedded Multi-view Stereo

Enable neural networks to capture 3D geometrical-aware features is essential in multi-view based vision tasks. Previous methods usually encode the 3D information of multi-view stereo into the 2D features. In contrast, we present a novel method, named POEM, that directly operates on the 3D POints Embedded in the Multi-view stereo for reconstructing hand mesh in it. Point is a natural form of 3D information and an ideal medium for fusing features across views, as it has different projections on different views. Our method is thus in light of a simple yet effective idea, that a complex 3D hand mesh can be represented by a set of 3D points that 1) are embedded in the multi-view stereo, 2) carry features from the multi-view images, and 3) encircle the hand. To leverage the power of points, we design two operations: point-based feature fusion and cross-set point attention mechanism. Evaluation on three challenging multi-view datasets shows that POEM outperforms the state-of-the-art in hand mesh reconstruction. Code and models are available for research at https://github.com/lixiny/POEM.Comment: Accepted by CVPR 202

Radiomic Features From Multi-Parameter MRI Combined With Clinical Parameters Predict Molecular Subgroups in Patients With Medulloblastoma

The 2016 WHO classification of central nervous system tumors has included four molecular subgroups under medulloblastoma (MB) as sonic hedgehog (SHH), wingless (WNT), Grade 3, and Group 4. We aimed to develop machine learning models for predicting MB molecular subgroups based on multi-parameter magnetic resonance imaging (MRI) radiomics, tumor locations, and clinical factors. A total of 122 MB patients were enrolled retrospectively. After selecting robust, non-redundant, and relevant features from 5,529 extracted radiomics features, a random forest model was constructed based on a training cohort (n= 92) and evaluated on a testing cohort (n= 30). By combining radiographic features and clinical parameters, two combined prediction models were also built. The subgroup can be classified using an 11-feature radiomics model with a high area under the curve (AUC) of 0.8264 for WNT and modest AUCs of 0.6683, 0.6004, and 0.6979 for SHH, Group 3, and Group 4 in the testing cohort, respectively. Incorporating location and hydrocephalus into the radiomics model resulted in improved AUCs of 0.8403 and 0.8317 for WNT and SHH, respectively. After adding gender and age, the AUCs for WNT and SHH were further improved to 0.9097 and 0.8654, while the accuracies were 70 and 86.67% for Group 3 and Group 4, respectively. Prediction performance was excellent for WNT and SHH, while that for Group 3 and Group 4 needs further improvements. Machine learning algorithms offer potentials to non-invasively predict the molecular subgroups of MB.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Differences in the Gaze Behaviours of Pedestrians Navigating between Regular and Irregular Road Patterns

While a road pattern influences wayfinding and navigation, its influence on the gaze behaviours of navigating pedestrians is not well documented. In this study, we compared gaze behaviour differences between regular and irregular road patterns using eye-tracking technology. Twenty-one participants performed orientation (ORI) and shortest route selection (SRS) tasks with both road patterns. We used accuracy of answers and response time to estimate overall performance and time to first fixation duration, average fixation duration, fixation count and fixation duration to estimate gaze behaviour. The results showed that participants performed better with better accuracy of answers using irregular road patterns. For both tasks and both road patterns, the Label areas of interest (AOIs) (including shops and signs) received quicker or greater attention. The road patterns influenced gaze behaviour for both Road AOIs and Label AOIs but exhibited a greater influence on Road AOIs in both tasks. In summary, for orientation and route selection, users are more likely to rely on labels, and roads with irregular patterns are important. These findings may serve as the anchor point for determining how people&rsquo;s gaze behaviours differ depending on road pattern and indicate that labels and unique road patterns should be highlighted for better wayfinding and navigation

Nitrogen enrichment alters plant N: P stoichiometry and intensifies phosphorus limitation in a steppe ecosystem

Although many studies have demonstrated that N deposition decreases biodiversity and alters ecosystem functioning, fewer studies have tested how N enrichment affect plant N and P limitation, N: P stoichiometry and ecosystem functioning. We examined the independent and interactive effects of N and P enrichment on plant N: P stoichiometry, nutrient limitation, and thereby ecosystem functioning based on two N, P, and N+P addition experiments in a typical steppe. At the species level, N enrichment increased leaf N: P ratio and P limitation of dominant species. The resporises of plant tissue N: P ratio tend to saturate at soil available N: P supply ratio of approximately 20 for leaf N: P and 10 for root N: P ratio. At the community level, patterns of N and P limitation shifted from N limitation in a normal year to N and P co-limitation in a wet year, triggered mainly by inter-annual changes in soil N and P availability. The homoeostasis of N: P stoichiometry increases from plant leaves to roots and to microbes although the available N: P supply ratio varied by 56-fold in soil. Given that N deposition rates are projected to increase in upcoming decades, N deposition may further alter the stoichiometric balance of N and P and intensify P limitation of steppe ecosystems in future. (C) 2016 Elsevier B.V. All rights reserved

Assessing Similarities and Differences between Males and Females in Visual Behaviors in Spatial Orientation Tasks

Spatial orientation is an important task in human wayfinding. Existing research indicates sex-related similarities and differences in performance and strategies when executing spatial orientation behaviors, but few studies have investigated the similarities and differences in visual behaviors between males and females. To address this research gap, we explored visual behavior similarities and differences between males and females using an eye-tracking method. We recruited 40 participants to perform spatial orientation tasks in a desktop environment and recorded their eye-tracking data during these tasks. The results indicate that there are no significant differences between sexes in efficiency and accuracy of spatial orientation. In terms of visual behaviors, we found that males fixated significantly longer than females on roads. Males and females had similar fixation counts in building, signpost, map, and other objects. Males and females performed similarly in fixation duration for all five classes. Moreover, fixation duration was well fitted to an exponential function for both males and females. The base of the exponential function fitted by males&rsquo; fixation duration was significantly lower than that of females, and the coefficient difference of exponential function was not found. Females were more effective in switching from maps to signposts, but differences of switches from map to other classes were not found. The newfound similarities and differences between males and females in visual behavior may aid in the design of better human-centered outdoor navigation applications

Real-Time Forecasting of Hand-Foot-and-Mouth Disease Outbreaks using the Integrating Compartment Model and Assimilation Filtering

Abstract Hand-foot-and-mouth disease (HFMD) is a highly contagious viral infection, and real-time predicting of HFMD outbreaks will facilitate the timely implementation of appropriate control measures. By integrating a susceptible-exposed-infectious-recovered (SEIR) model and an ensemble Kalman filter (EnKF) assimilation method, we developed an integrated compartment model and assimilation filtering forecast model for real-time forecasting of HFMD. When applied to HFMD outbreak data collected for 2008–11 in Beijing, China, our model successfully predicted the peak week of an outbreak three weeks before the actual arrival of the peak, with a predicted maximum infection rate of 85% or greater than the observed rate. Moreover, dominant virus types enterovirus 71 (EV-71) and coxsackievirus A16 (CV-A16) may account for the different patterns of HFMD transmission and recovery observed. The results of this study can be used to inform agencies responsible for public health management of tailored strategies for disease control efforts during HFMD outbreak seasons

Mechanical Properties and Crack Resistance of Basalt Fiber Self-Compacting High Strength Concrete: An Experimental Study

Pure self-compacting concrete has many disadvantages, such as early shrinkage and cracking. The addition of fibers can effectively improve the properties of resistance to tension and cracking of self-compacting concrete, thereby the effect of improving its strength and toughness can be achieved. Basalt fiber is a “new green industrial material” that has unique advantages, such as high crack resistance and being lightweight compared with other fiber materials. In order to study the mechanical properties and crack resistance of basalt fiber self-compacting high-strength concrete intensively, the self-compacting high-strength concrete of C50 was designed and obtained using the absolute volume method with multiple proportions. Orthogonal experimental methods were used to study the influence of the water binder ratio, fiber volume fraction, fiber length, and fly ash content on the mechanical properties of the basalt fiber self-compacting high-strength concrete. Meanwhile, the efficiency coefficient method was used to determine the best experiment plan (water binder ratio 0.3, fiber volume ratio 0.2%, fiber length 12 mm, fly ash content 30%), and the effect of fiber volume fraction and fiber length on the crack resistance of the self-compacting high-performance concrete was investigated using improved plate confinement experiments. The results show that (1) the water binder ratio had the greatest impact on the compressive strength of basalt fiber self-compacting high-strength concrete, and as the fiber volume fraction increased, the splitting tensile strength and flexural strength both increased; (2) there was an optimal value for the effect of the fiber length on the mechanical properties; (3) with the increase in fiber volume fraction, the total crack area of the fiber self-compacting high-strength concrete significantly decreased. When the fiber length increased, the maximum crack width first decreased and then slowly increased. The best crack resistance effect was achieved when the fiber volume fraction was 0.3% and the fiber length was 12 mm. Therefore, basalt fiber self-compacting high-strength concrete can be widely used in engineering fields, such as national defense construction, transportation, and building structure reinforcement and repair, due to its excellent mechanical and crack resistance properties

Thermal displacement prediction model of SVR high-speed motorized spindle based on SA-PSO optimization

In view of the problem that a lot of heat is generated inside the motorized spindle when it is working, which causes thermal errors and affects the processing quality, this paper optimizes the Support Vector Regression through the particle swarm algorithm to establish a thermal displacement model of the motorized spindle to predict the thermal elongation change, To thermally compensate the motorized spindle. The sensors are arranged to collect the temperature rise data and thermal displacement data of the motorized spindle at different speeds according to the temperature field distribution of the motorized spindle's steady-state temperature simulation analysis results. Taking the temperature data as the training set and the thermal displacement data as the feature set, the support vector regression machine based on improved particle swarm optimization of the simulated annealing algorithm (SA-PSO-SVR) is used to establish the thermal displacement model of the motorized spindle. The results show that the SA-PSO-SVR model can predict the thermal elongation change, clarify the thermal error system real-time motorized spindle thermal displacement change, compensate for the thermal error, and improve the machining accuracy of the motorized spindle