73 research outputs found
Management of Ascending Aorta Calcification in Coronary Artery Bypass Grafting
Neurological complications are one of the most common complications after coronary artery bypass grafting. With the development of off-pump coronary artery bypass grafting (OPCABG), the incidence of postoperative neurological complications caused by aortic intubation decreased significantly; however, the continuous suture of the great saphenous vein-aortic anastomosis in the coronary artery bypass grafting requires the operation of surgical clamp and perforation on the ascending aorta, which may lead to potential plaque detachment. Calcification of ascending aorta is an independent risk factor for cerebrovascular events after OPCABG. Therefore, it is crucial to explore and operate on the ascending aorta. There are three main methods of proximal anastomosis in OPCABG: (1) partial blocking of ascending aorta with side wall clamp for anastomosis; (2) application of proximal anastomosis auxiliary device (Enclose, Heartstring, etc.) for proximal anastomosis; and (3) original auxiliary device (urethra catheter-water sac) or no-clamp surgical techniques for proximal anastomosis
Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priors
3D object-level mapping is a fundamental problem in robotics, which is
especially challenging when object CAD models are unavailable during inference.
In this work, we propose a framework that can reconstruct high-quality
object-level maps for unknown objects. Our approach takes multiple RGB-D images
as input and outputs dense 3D shapes and 9-DoF poses (including 3 scale
parameters) for detected objects. The core idea of our approach is to leverage
a learnt generative model for shape categories as a prior and to formulate a
probabilistic, uncertainty-aware optimization framework for 3D reconstruction.
We derive a probabilistic formulation that propagates shape and pose
uncertainty through two novel loss functions. Unlike current state-of-the-art
approaches, we explicitly model the uncertainty of the object shapes and poses
during our optimization, resulting in a high-quality object-level mapping
system. Moreover, the resulting shape and pose uncertainties, which we
demonstrate can accurately reflect the true errors of our object maps, can also
be useful for downstream robotics tasks such as active vision. We perform
extensive evaluations on indoor and outdoor real-world datasets, achieving
achieves substantial improvements over state-of-the-art methods. Our code will
be available at https://github.com/TRAILab/UncertainShapePose.Comment: Manuscript submitted to ICRA 202
POCD: Probabilistic Object-Level Change Detection and Volumetric Mapping in Semi-Static Scenes
Maintaining an up-to-date map to reflect recent changes in the scene is very
important, particularly in situations involving repeated traversals by a robot
operating in an environment over an extended period. Undetected changes may
cause a deterioration in map quality, leading to poor localization, inefficient
operations, and lost robots. Volumetric methods, such as truncated signed
distance functions (TSDFs), have quickly gained traction due to their real-time
production of a dense and detailed map, though map updating in scenes that
change over time remains a challenge. We propose a framework that introduces a
novel probabilistic object state representation to track object pose changes in
semi-static scenes. The representation jointly models a stationarity score and
a TSDF change measure for each object. A Bayesian update rule that incorporates
both geometric and semantic information is derived to achieve consistent online
map maintenance. To extensively evaluate our approach alongside the
state-of-the-art, we release a novel real-world dataset in a warehouse
environment. We also evaluate on the public ToyCar dataset. Our method
outperforms state-of-the-art methods on the reconstruction quality of
semi-static environments.Comment: Published in Robotics: Science and Systems (RSS) 202
Biomedical applications of artificial exosomes for intranasal drug delivery
Intranasal administration offers a feasible, non-invasive method of delivering therapeutic drugs to the brain, allowing therapeutic pharmaceuticals to be administered directly to the central nervous system by bypassing the blood-brain barrier. Furthermore, exosomes are naturally occurring cell-derived nanovesicles that can serve as carriers for a variety of chemical compounds. Many studies have focused on artificial exosomes as innovative medication delivery methods. As a result, trans-nasal delivery of artificial exosomes might be employed to treat brain illnesses in a novel method. This review will outline the drug delivery mechanism of artificial extracellular vesicles, emphasize its advantages as a nasal drug carrier, particularly its application as a novel nanocarriers in brain diseases, and focus on its prospective application in chronic inflammatory nose disorders. Finally, artificial exosomes may become a unique drug delivery mode for clinical therapeutic usage
Cassava genome from a wild ancestor to cultivated varieties
Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology
Electrospun core-shell Mn3O4/carbon fibers as high-performance cathode materials for aqueous zinc-ion batteries
Š 2020 Elsevier Ltd Core-shell Mn3O4/carbon (Mn3O4@C) hybrid fiber are synthesized by encapsulating Mn3O4 nanoparticles (NPs) in the hollow carbon fibers (Mn3O4@HCFs) according to the coaxial electrospinning technique. As the aqueous Zinc ion battery (ZIBs) cathode, the well-defined Mn3O4@HCFs with 12.7 wt % carbon exhibits superior rate capability (215.8 and 115.7 mAh gâ1 at 0.3 and 2.0 A gâ1, respectively) and excellent cycling stability (225 mAh gâ1 remaining at the current density of 400 mA gâ1 after 1300 cycles). The outstanding electrochemical performances are attributed to the core-shell structure of the Mn3O4@HCFs with much void spaces. The carbon framework on the surface of the Mn3O4 NPs can not only relieve the volume expansion of Mn3O4 during the discharging, but also optimize the electron transportation inside these fibers for the electrode. Furthermore, the amorphous carbon shell could also reduce the dissolution of the Mn3O4 NPs during cycling. This work will provide a new pathway of a technique for enhancing the manganese-based cathode materials for the high-powered rechargeable aqueous ZIBs
Foot measurements from 2D digital images
Foot measurements play an important role in the design of comfortable footwear products. This study proposed a non-invasive and efficient means to obtain foot measurements from 2D digital foot images. The hardware of the proposed image-based measuring system was easy to set up and the developed measuring system was tested for 9 foot measurements with ten male subjects who were also manually measured. The comparison between foot measurements from the image-based and the traditionally manual measured systems showed that there were no significant differences between two systems on 8 out of 9 foot measurements. The errors on foot measurements from the image-based system were also analyzed and discussed. The proposed image-based system under further improvements may be applied into the online sales of shoes, especially customized shoes
Development of High Hydrostatic Pressure Applied in Pathogen Inactivation for Plasma.
High hydrostatic pressure has been used to inactivate pathogens in foods for decades. There is a great potential to adapt this technology to inactivate pathogens in plasma and derivatives. To better evaluate the potential of this method, pathogen inoculated plasma samples were pressurized under different pressure application modes and temperatures. The inactivation efficacy of pathogens and activities of plasma proteins were monitored after treatment. The CFUs of E.coli was examined as the indicator of the inactivation efficiency. The factor V and VIII were chosen as the indicator of the plasma function. Preliminary experiments identified optimized treatment conditions: 200-250MPa, with 5Ă1 minute multi-pulsed high pressure at near 0°C (ice-water bath). Under this conditions, the inactivation efficacy of EMCV was >8.5log. The CFUs of E. coli were reduced by 7.5log, B. cereus were 8log. However, PPV and S. aureus cannot be inactivated efficiently. The activities of factor II, VII, IX, X, XI, XII, fibrinogen, IgG, IgM stayed over 95% compared to untreated. Factor V and VIII activity was maintained at 46-63% and 77-82%, respectively
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