Bulk Density Adjustment of Resin-Based Equivalent Material for Geomechanical Model Test

An equivalent material is of significance to the simulation of prototype rock in geomechanical model test. Researchers attempt to ensure that the bulk density of equivalent material is equal to that of prototype rock. In this work, barite sand was used to increase the bulk density of a resin-based equivalent material. The variation law of the bulk density was revealed in the simulation of a prototype rock of a different bulk density. Over 300 specimens were made for uniaxial compression test. Test results indicated that the substitution of quartz sand by barite sand had no apparent influence on the uniaxial compressive strength and elastic modulus of the specimens but can increase the bulk density, according to the proportional coarse aggregate content. An ideal linearity was found in the relationship between the barite sand substitution ratio and the bulk density. The relationship between the bulk density and the usage of coarse aggregate and barite sand was also presented. The test results provided an insight into the bulk density adjustment of resin-based equivalent materials

Functional near-infrared spectroscopy as a potential objective evaluation technique in neurocognitive disorders after traumatic brain injury

Most patients with neurocognitive disorders after traumatic brain injury (TBI) show executive dysfunction, in which the pre-frontal cortex (PFC) plays an important role. However, less objective evaluation technique could be used to assess the executive dysfunction in these patients. Functional near-infrared spectroscopy (fNIRS), which is a non-invasive technique, has been widely used in the study of psychiatric disorders, cognitive dysfunction, etc. The present study aimed to explore whether fNIRS could be a technique to assess the damage degree of executive function in patients with neurocognitive disorders after TBI by using the Stroop and N-back tasks in PFC areas. We enrolled 37 patients with neurocognitive disorders after TBI and 60 healthy controls. A 22-channel fNIRS device was used to record HbO during Stroop, 1-back and 2-back tasks. The results showed that patients made significantly more errors and had longer response times than healthy controls. There were statistically significant differences in HbO level variation in bilateral frontopolar, bilateral inferior frontal gyrus and left middle temporal gyrus during Stroop color word consistency tasks and in left frontopolar during Stroop color word inconsistency tasks. During 2-back tasks, there were also statistically significant differences in HbO level variation in bilateral frontopolar, bilateral inferior frontal gyrus, bilateral dorsolateral pre-frontal cortex. According to brain activation maps, the patients exhibited lower but more widespread activation during the 2-back and Stroop color word consistency tasks. The fNIRS could identify executive dysfunction in patients with neurocognitive disorders after TBI by detecting HbO levels, which suggested that fNIRS could be a potential objective evaluation technique in neurocognitive disorders after TBI

Segment Anything Model for Medical Images?

The Segment Anything Model (SAM) is the first foundation model for general image segmentation. It designed a novel promotable segmentation task, ensuring zero-shot image segmentation using the pre-trained model via two main modes including automatic everything and manual prompt. SAM has achieved impressive results on various natural image segmentation tasks. However, medical image segmentation (MIS) is more challenging due to the complex modalities, fine anatomical structures, uncertain and complex object boundaries, and wide-range object scales. SAM has achieved impressive results on various natural image segmentation tasks. Meanwhile, zero-shot and efficient MIS can well reduce the annotation time and boost the development of medical image analysis. Hence, SAM seems to be a potential tool and its performance on large medical datasets should be further validated. We collected and sorted 52 open-source datasets, and build a large medical segmentation dataset with 16 modalities, 68 objects, and 553K slices. We conducted a comprehensive analysis of different SAM testing strategies on the so-called COSMOS 553K dataset. Extensive experiments validate that SAM performs better with manual hints like points and boxes for object perception in medical images, leading to better performance in prompt mode compared to everything mode. Additionally, SAM shows remarkable performance in some specific objects and modalities, but is imperfect or even totally fails in other situations. Finally, we analyze the influence of different factors (e.g., the Fourier-based boundary complexity and size of the segmented objects) on SAM's segmentation performance. Extensive experiments validate that SAM's zero-shot segmentation capability is not sufficient to ensure its direct application to the MIS.Comment: 23 pages, 14 figures, 12 table

Research progress of functional near-infrared spectroscopy in patients with psychiatric disorders

Functional near-infrared spectroscopy (fNIRS) is a technique of detecting cerebral cortical function by using near-infrared light, which is a multifunctional neuroimaging technique and provides a convenient and efficient detection method in neuroscience. In consideration of acceptability, safety, high spatial and temporal resolutions compared with electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), fNIRS is widely used to study different psychiatric disorders, most prominently affective disorders, schizophrenic illnesses, brain organic mental disorders and neurodevelopmental disorders, etc. The article focuses on the latest research progress and practical application of fNIRS in psychiatric disorders, especially traumatic brain, including studies on the characterization of phenomenology, treatment effects and descriptions of neuroimaging data

Use of the PiCCO system in critically ill patients with septic shock and acute respiratory distress syndrome: a study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Hemodynamic monitoring is very important in critically ill patients with shock or acute respiratory distress syndrome(ARDS). The PiCCO (Pulse index Contour Continuous Cardiac Output, Pulsion Medical Systems, Germany) system has been developed and used in critical care settings for several years. However, its impact on clinical outcomes remains unknown.</p> <p>Methods/design</p> <p>The study is a randomized controlled multi-center trial. A total of 708 patients with ARDS, septic shock or both will be included from January 2012 to January 2014. Subjects will be randomized to receive PiCCO monitoring or not. Our primary end point is 30-day mortality, and secondary outcome measures include ICU length of stay, days on mechanical ventilation, days of vasoactive agent support, ICU-free survival days during a 30-day period, mechanical-ventilation-free survival days during a 30-day period, and maximum SOFA score during the first 7 days.</p> <p>Discussion</p> <p>We investigate whether the use of PiCCO monitoring will improve patient outcomes in critically ill patients with ARDS or septic shock. This will provide additional data on hemodynamic monitoring and help clinicians to make decisions on the use of PiCCO.</p> <p>Trial registration</p> <p><url>http://www.clinicaltrials.gov</url> NCT01526382</p

A dense obstacle avoidance algorithm for UAVs based on safe flight corridor

Aiming at the problem of autonomous obstacle avoidance of fixed-wing UAVs in a complex, dense and multi-obstacle environment, a path planning algorithm for fixed-wing UAVs based on a safe flight corridor is proposed. The difficulty of avoiding dense obstacles lies in the choice of obstacle circumvention and traversal: although circumvention is safer, the flight cost is greater; although the traversal cost is lower, the safety threat is higher. How to quickly solve the optimal path is the core issue. This paper firstly defines a safe flight corridor innovatively based on the maneuvering characteristics of fixed-wing UAVs and the Dubins curves. By comprehensively considering UAV flight safety and flight costs, an obstacle threat evaluation function is constructed. Secondly, in view of the computational complexity caused by the dense obstacles, an obstacle clustering algorithm based on obstacle density is proposed, and the nonlinear evaluation function in a high dynamic environment is quickly approximated by Monte Carlo sampling method. Finally, simulations verify the effectiveness of the proposed algorithm in solving dense obstacle avoidance for fixed-wing UAVs

High-yield monolayer graphene grids for near-atomic resolution cryoelectron microscopy

© 2020 National Academy of Sciences. All rights reserved. Cryogenic electron microscopy (cryo-EM) has become one of the most powerful techniques to reveal the atomic structures and working mechanisms of biological macromolecules. New designs of the cryo-EM grids - aimed at preserving thin, uniform vitrified ice and improving protein adsorption - have been considered a promising approach to achieving higher resolution with the minimal amount of materials and data. Here, we describe a method for preparing graphene cryo-EM grids with up to 99% monolayer graphene coverage that allows for more than 70% grid squares for effective data acquisition with improved image quality and protein density. Using our graphene grids, we have achieved 2.6-Å resolution for streptavidin, with a molecular weight of 52 kDa, from 11, 000 particles. Our graphene grids increase the density of examined soluble, membrane, and lipoproteins by at least 5-fold, affording the opportunity for structural investigation of challenging proteins which cannot be produced in large quantity. In addition, our method employs only simple tools that most structural biology laboratories can access. Moreover, this approach supports customized grid designs targeting specific proteins, owing to its broad compatibility with a variety of nanomaterials

Peregrine soliton emits dispersive waves within graded-index multimode fibers without higher-order dispersion

We investigate the propagation dynamics of the Peregrine soliton, a significant prototype of rogue waves, within the graded-index multimode fibers, in the absence of higher-order dispersion. The Peregrine soliton keeps the approximate evolution trend when propagating within the graded-index multimode fibers to replace the single-mode fibers when preserving the equivalent nonlinear effect. In addition, a series of dispersive waves (also called resonant radiation) can be emitted by the Peregrine soliton, perturbated by the periodic beam oscillation caused by the spatial self-imaging effect within the graded-index multimode fibers. To be more exact, the location of the multiple resonant frequencies can be predicted using the modified quasi-phase-matching conditions, which are verified by the numerically calculated results. We can also manipulate the locations of spectral sidebands and the peak power of dispersive waves by changing the self-imaging parameter of the graded-index multimode fibers. Our findings can provide a deeper comprehension of the propagation characteristic of Peregrine soliton within the graded-index multimode fibers and provide valuable instruction for further rich nonlinear experiments