A^2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes

Constructing of molecular structural models from Cryo-Electron Microscopy (Cryo-EM) density volumes is the critical last step of structure determination by Cryo-EM technologies. Methods have evolved from manual construction by structural biologists to perform 6D translation-rotation searching, which is extremely compute-intensive. In this paper, we propose a learning-based method and formulate this problem as a vision-inspired 3D detection and pose estimation task. We develop a deep learning framework for amino acid determination in a 3D Cryo-EM density volume. We also design a sequence-guided Monte Carlo Tree Search (MCTS) to thread over the candidate amino acids to form the molecular structure. This framework achieves 91% coverage on our newly proposed dataset and takes only a few minutes for a typical structure with a thousand amino acids. Our method is hundreds of times faster and several times more accurate than existing automated solutions without any human intervention.Comment: 8 pages, 5 figures, 4 table

Non-singular assembly mode changing trajectories in the workspace for the 3-RPS parallel robot

Having non-singular assembly modes changing trajectories for the 3-RPS parallel robot is a well-known feature. The only known solution for defining such trajectory is to encircle a cusp point in the joint space. In this paper, the aspects and the characteristic surfaces are computed for each operation mode to define the uniqueness of the domains. Thus, we can easily see in the workspace that at least three assembly modes can be reached for each operation mode. To validate this property, the mathematical analysis of the determinant of the Jacobian is done. The image of these trajectories in the joint space is depicted with the curves associated with the cusp points

Are Chinese consumers at risk due to exposure to metals in crayfish? A bioaccessibility-adjusted probabilistic risk assessment

Freshwater crayfish, the world's third largest crustacean species, has been reported to accumulate high levels of metals, while the current knowledge of potential risk associated with crayfish consumption lags behind that of finfish. We provide the first estimate of human health risk associated with crayfish (Procambarus clarkii) consumption in China, the world's largest producer and consumer of crayfish. We performed Monte Carlo Simulation on a standard risk model parameterized with local data on metal concentrations, bioaccessibility (phi), crayfish consumption rate, and consumer body mass. Bioaccessibility of metals in crayfish was found to be variable (68-95%) and metal-specific, suggesting a potential influence of metal bioaccessibility on effective metal intake. However, sensitivity analysis suggested risk of metals via crayfish consumption was predominantly explained by consumption rate (explaining >92% of total risk estimate variability), rather than metals concentration, bioaccessibility, or body mass. Mean metal concentrations (As, Cd, Cu, Ni, Pb, Se and Zn) in surveyed crayfish samples from 12 provinces in China conformed to national safety standards. However, risk calculation of phi-modified hazard quotient (HQ) and hazard index (HI) suggested that crayfish metals may pose a health risk for very high rate consumers, with a HI of over 24 for the highest rate consumers. Additionally, the phi-modified increased lifetime risk (ILTR) for carcinogenic effects due to the presence of As was above the acceptable level (10(-5)) for both the median (ILTR = 2.5 x 10(-5)) and 90th percentile (ILTR = 1.8 x 10(-4)), highlighting the relatively high risk of As in crayfish. Our results suggest a need to consider crayfish when assessing human dietary exposure to metals and associated health risks, especially for high crayfish-consuming populations, such as in China, USA and Sweden.HZ by the National Natural Science Foundation of China (41273087). LN was supported by European Union Marie Curie Actions, Grant FP People 2010 “IRSES Electroacross” and BG by the SAGE-IGERT Fellowship (US National Science Foundation)

Facial Asymmetry Analysis Based on 3-D Dynamic Scans

Facial dysfunction is a fundamental symptom which often relates to many neurological illnesses, such as stroke, Bell’s palsy, Parkinson’s disease, etc. The current methods for detecting and assessing facial dysfunctions mainly rely on the trained practitioners which have significant limitations as they are often subjective. This paper presents a computer-based methodology of facial asymmetry analysis which aims for automatically detecting facial dysfunctions. The method is based on dynamic 3-D scans of human faces. The preliminary evaluation results testing on facial sequences from Hi4D-ADSIP database suggest that the proposed method is able to assist in the quantification and diagnosis of facial dysfunctions for neurological patients

Do-It-Yourself Single Camera 3D Pointer Input Device

We present a new algorithm for single camera 3D reconstruction, or 3D input for human-computer interfaces, based on precise tracking of an elongated object, such as a pen, having a pattern of colored bands. To configure the system, the user provides no more than one labelled image of a handmade pointer, measurements of its colored bands, and the camera's pinhole projection matrix. Other systems are of much higher cost and complexity, requiring combinations of multiple cameras, stereocameras, and pointers with sensors and lights. Instead of relying on information from multiple devices, we examine our single view more closely, integrating geometric and appearance constraints to robustly track the pointer in the presence of occlusion and distractor objects. By probing objects of known geometry with the pointer, we demonstrate acceptable accuracy of 3D localization.Comment: 8 pages, 6 figures, 2018 15th Conference on Computer and Robot Visio