Fast Learning Radiance Fields by Shooting Much Fewer Rays

Learning radiance fields has shown remarkable results for novel view synthesis. The learning procedure usually costs lots of time, which motivates the latest methods to speed up the learning procedure by learning without neural networks or using more efficient data structures. However, these specially designed approaches do not work for most of radiance fields based methods. To resolve this issue, we introduce a general strategy to speed up the learning procedure for almost all radiance fields based methods. Our key idea is to reduce the redundancy by shooting much fewer rays in the multi-view volume rendering procedure which is the base for almost all radiance fields based methods. We find that shooting rays at pixels with dramatic color change not only significantly reduces the training burden but also barely affects the accuracy of the learned radiance fields. In addition, we also adaptively subdivide each view into a quadtree according to the average rendering error in each node in the tree, which makes us dynamically shoot more rays in more complex regions with larger rendering error. We evaluate our method with different radiance fields based methods under the widely used benchmarks. Experimental results show that our method achieves comparable accuracy to the state-of-the-art with much faster training.Comment: Accepted by lEEE Transactions on lmage Processing 2023. Project Page: https://zparquet.github.io/Fast-Learning . Code: https://github.com/zParquet/Fast-Learnin

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Quad-Rotor Helicopter Autonomous Navigation Based on Vanishing Point Algorithm

Quad-rotor helicopter is becoming popular increasingly as they can well implement many flight missions in more challenging environments, with lower risk of damaging itself and its surroundings. They are employed in many applications, from military operations to civilian tasks. Quad-rotor helicopter autonomous navigation based on the vanishing point fast estimation (VPFE) algorithm using clustering principle is implemented in this paper. For images collected by the camera of quad-rotor helicopter, the system executes the process of preprocessing of image, deleting noise interference, edge extracting using Canny operator, and extracting straight lines by randomized hough transformation (RHT) method. Then system obtains the position of vanishing point and regards it as destination point and finally controls the autonomous navigation of the quad-rotor helicopter by continuous modification according to the calculated navigation error. The experimental results show that the quad-rotor helicopter can implement the destination navigation well in the indoor environment

An Improved Fast Flocking Algorithm with Obstacle Avoidance for Multiagent Dynamic Systems

Flocking behavior is a common phenomenon in nature, such as flocks of birds and groups of fish. In order to make the agents effectively avoid obstacles and fast form flocking towards the direction of destination point, this paper proposes a fast multiagent obstacle avoidance (FMOA) algorithm. FMOA is illustrated based on the status of whether the flocking has formed. If flocking has not formed, agents should avoid the obstacles toward the direction of target. If otherwise, these agents have reached the state of lattice and then these agents only need to avoid the obstacles and ignore the direction of target. The experimental results show that the proposed FMOA algorithm has better performance in terms of flocking path length. Furthermore, the proposed FMOA algorithm is applied to the formation flying of quad-rotor helicopters. Compared with other technologies to perform the localization of quad-rotor helicopter, this paper innovatively constructs a smart environment by deploying some wireless sensor network (WSN) nodes using the proposed localization algorithm. Finally, the proposed FMOA algorithm is used to conduct the formation flying of these quad-rotor helicopters in the smart environment

Correlation analysis of MR elastography and Ki-67 expression in intrahepatic cholangiocarcinoma

Abstract Background Intrahepatic cholangiocarcinoma (iCCA) is an aggressive primary liver cancer with dismal outcome, high Ki-67 expression is associated with active progression and poor prognosis of iCCA, the application of MRE in the prediction of iCCA Ki-67 expression has not yet been investigated until now. We aimed to evaluate the value of magnetic resonance elastography (MRE) in assessing Ki-67 expression for iCCA. Results In the whole cohort, 97 patients (57 high Ki-67 and 40 low Ki-67; 58 males, 39 females; mean age, 58.89 years, ranges 36–70 years) were included. At the multivariate analysis, tumor stiffness (odds ratio (OR) = 1.669 [95% CI: 1.307–2.131], p < 0.001) and tumor apparent diffusion coefficient (ADC) (OR = 0.030 [95% CI: 0.002, 0.476], p = 0.013) were independent significant variables associated with Ki-67. Areas under the curve of tumor stiffness for the identification of high Ki-67 were 0.796 (95% CI 0.702, 0.871). Tumor stiffness was moderately correlated with Ki-67 level (r = 0.593, p < 0.001). When both predictive variables of tumor stiffness and ADC were integrated, the best performance was achieved with area under the curve values of 0.864 (95% CI 0.780–0.926). Conclusion MRE-based tumor stiffness correlated with Ki-67 in iCCA and could be investigated as a potential prognostic biomarker. The combined model incorporating both tumor stiffness and ADC increased the predictive performance. Critical relevance statement MRE-based tumor stiffness might be a surrogate imaging biomarker to predict Ki-67 expression in intrahepatic cholangiocarcinoma patients, reflecting tumor cellular proliferation. The combined model incorporating both tumor stiffness and apparent diffusion coefficient increased the predictive performance. Key points • MRE-based tumor stiffness shows a significant correlation with Ki-67. • The combined model incorporating tumor stiffness and apparent diffusion coefficient demonstrated an optimized predictive performance for Ki-67 expression. • MRE-based tumor stiffness could be investigated as a potential prognostic biomarker for intrahepatic cholangiocarcinoma. Graphical Abstrac

Chinese SLE Treatment and Research Group Registry (CSTAR) XIV: the subjective well-being of patients with systemic lupus erythematosus

BackgroundSystemic lupus erythematosus (SLE) can significantly influence patients' quality of life and subjective well-being (SWB), but the relationships between clinical characteristics, SWB, and related psychological factors have been little studied. ObjectiveTo measure SWB in patients with SLE and examine how major clinical determinants, emotional variables, and related positive factors affect SWB. MethodsOverall, 1,110 patients with SLE from the Chinese SLE Treatment and Research Group (CSTAR) and 198 age and gender-matched individuals from the general population without self-reported SLE were invited to complete questionnaires of SWB evaluated by the satisfaction with life scale (SWLS), emotional variables assessed by the patient health questionnaire-9 (PHQ-9), and general anxiety disorder-7 (GAD-7) and related positive factors assessed by the self-esteem scale (SES), general self-efficacy scale (GESE), and Connor-Davidson resilience scale (CD-RISC). The multivariate linear regression was used to examine the relationship between clinical manifestations and SWB. ResultsLife satisfaction was significantly lower (p < 0.001) in patients with SLE than in the general population. Active skin involvement (OR = 0.923, 95% CI = 0.868-0.981, p < 0.05) was negatively associated with life satisfaction scores, and age at enrollment (OR = 1.160, 95% CI = 1.092-1.230, p < 0.001) were positively associated with life satisfaction scores in the multivariate regression model. The cumulative organ damage was significantly associated with depression (OR = 1.085, 95% CI = 1.022-1.153, p < 0.01) and the loss of self-esteem (OR = 1.067, 95% CI = 1.004-1.133, p < 0.05). ConclusionSWB provides useful insight into the impact of SLE on psychological health and opportunities to improve quality of life and clinical care