18 research outputs found

    Effect of Evaporation Temperature on the Performance of Organic Rankine Cycle in Near-Critical Condition

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    Considering the large variations of working fluid's properties in near-critical region, this paper presents a thermodynamic analysis of the performance of organic Rankine cycle in near-critical condition (NORC) subjected to the influence of evaporation temperature. Three typical organic fluids are selected as working fluids. They are dry R236fa, isentropic R142b, and wet R152a, which are suited for heat source temperature from 395 to 445 K. An iteration calculation method is proposed to calculate the performance parameters of organic Rankine cycle (ORC). The variations of superheat degree, specific absorbed heat, expander inlet pressure, thermal efficiency, and specific net power of these fluids with evaporation temperature are analyzed. It is found that the working fluids in NORC should be superheated because of the large slope variation of the saturated vapor curve in near-critical region. However, the use of dry R236fa or isentropic R142b in NORC can be accepted because of the small superheat degree. The results also indicate that a small variation of evaporation temperature requires a large variation of expander inlet pressure, which may make the system more stable. In addition, due to the large decrease of latent heat in near-critical region, the variation of specific absorbed heat with evaporation temperature is small for NORC. Both specific net power and thermal efficiency for the fluids in NORC increase slightly with the rise of the evaporation temperature, especially for R236fa and R142b. Among the three types of fluids, dry R236fa and isentropic R142b are better suited for NORC. The results are useful for the design and optimization of ORC system in near-critical condition

    Grounded Language-Image Pre-training

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    This paper presents a grounded language-image pre-training (GLIP) model for learning object-level, language-aware, and semantic-rich visual representations. GLIP unifies object detection and phrase grounding for pre-training. The unification brings two benefits: 1) it allows GLIP to learn from both detection and grounding data to improve both tasks and bootstrap a good grounding model; 2) GLIP can leverage massive image-text pairs by generating grounding boxes in a self-training fashion, making the learned representation semantic-rich. In our experiments, we pre-train GLIP on 27M grounding data, including 3M human-annotated and 24M web-crawled image-text pairs. The learned representations demonstrate strong zero-shot and few-shot transferability to various object-level recognition tasks. 1) When directly evaluated on COCO and LVIS (without seeing any images in COCO during pre-training), GLIP achieves 49.8 AP and 26.9 AP, respectively, surpassing many supervised baselines. 2) After fine-tuned on COCO, GLIP achieves 60.8 AP on val and 61.5 AP on test-dev, surpassing prior SoTA. 3) When transferred to 13 downstream object detection tasks, a 1-shot GLIP rivals with a fully-supervised Dynamic Head. Code is released at https://github.com/microsoft/GLIP.Comment: CVPR 2022; updated visualizations; fixed hyper-parameters in Appendix C.

    Voxel-Mirrored Homotopic Connectivity of Resting-State Functional Magnetic Resonance Imaging in Blepharospasm

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    Objective: Several networks in human brain are involved in the development of blepharospasm. However, the underlying mechanisms for this disease are poorly understood. A voxel-mirrored homotopic connectivity (VMHC) method was used to quantify the changes in functional connectivity between two hemispheres of the brain in patients with blepharospasm.Methods: Twenty-four patients with blepharospasm and 24 healthy controls matched by age, sex, and education were recruited. The VMHC method was employed to analyze the fMRI data. The support vector machine (SVM) method was utilized to examine whether these abnormalities could be applied to distinguish the patients from the controls.Results: Compared with healthy controls, patients with blepharospasm showed significantly high VMHC in the inferior temporal gyrus, interior frontal gyrus, posterior cingulate cortex, and postcentral gyrus. No significant correlation was found between abnormal VMHC values and clinical variables. SVM analysis showed a combination of increased VMHC values in two brain areas with high sensitivities and specificities (83.33 and 91.67% in the combined inferior frontal gyrus and posterior cingulate cortex; and 83.33 and 87.50% in the combined inferior temporal gyrus and postcentral gyrus).Conclusion: Enhanced homotopic coordination in the brain regions associated with sensory integration networks and default-mode network may be underlying the pathophysiology of blepharospasm. This phenomenon may serve as potential image markers to distinguish patients with blepharospasm from healthy controls

    Passive Continuous Variable Quantum Key Distribution through the Oceanic Turbulence

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    Continuous variable quantum key distribution (CVQKD) can be potentially implemented through seawater channels, whereas the involved oceanic turbulence has a negative effect on the maximal transmission distance of quantum communication systems. Here, we demonstrate the effects of the oceanic turbulence on the performance of the CVQKD system and suggest an implementation feasibility of the passive CVQKD through the oceanic turbulence-based channel. We achieve the channel transmittance characterized by the transmission distance and depth of the seawater. Moreover, a non-Gaussian approach is used for performance improvement while counteracting the effects of excess noises on the oceanic channel. Numerical simulations show that the photon operation (PO) unit can bring reductions of excess noise when taking into account the oceanic turbulence, and hence results in performance improvement in terms of transmission distance and depth as well. The passive CVQKD explores the intrinsic field fluctuations of a thermal source without using an active scheme and hence has a promising application in chip integration for portable quantum communications

    Quality Evaluation of Bioactive Ingredients in Lianhua Qingwen Capsule Based on Quantitative Analysis of Multicomponent by the Single Marker Method and the Chemical Recognition Patterns Method

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    Based on high performance liquid chromatography with the diode array detector (HPLC-DAD), a new strategy for simultaneous determination of ten bioactive ingredients in Lianhua Qingwen capsule (LHQW) was developed for comprehensive quality assessment of LHQW. In this work, with rhein regarded as the internal reference substance (IRS), the relative correction factors (RCFs) of neochlorogenic acid, amygdalin, chlorogenic acid, forsythoside A, quercitrin, phillyin, glycyrrhizic acid, isoforsythiaside, and (+) pinoresinol-β-D-glucoside were calculated for simultaneous determination of ten bioactive ingredients. More importantly, compared to previous work, the simultaneous determination of the content of ten pharmacologically important active ingredients at one detection wavelength with only one reference substance has been achieved. Based on the contents of ten bioactive ingredients, the quality of the 20 batches of LHQW samples was further analyzed by chemical recognition patterns method. Ten bioactive ingredients showed a good linear relationship in their respective concentration ranges (r ≥ 0.999). The relative standard deviations (RSDs) of precision (≤4.62%), stability (≤4.04%), repeatability (≤3.87%), and the average recovery of ten bioactive components (99.8%∼104.1%) demonstrated the QAMS developed for LHQW which had good durability. The correlation coefficient (P>0.05) showed that no significant difference existed in the results of QAMS and external standard method (ESM). Hierarchical clustering analysis (HCA) divided samples into three main groups. Radar plot analysis and principal component analysis (PCA) found some quality differences existed between the three groups of samples. Orthogonal partial least-squares discrimination analysis (OPLS-DA) showed that forsythoside A could be used as the primary marker responsible for the quality differences. In conclusion, the established QAMS method combined with chemometric analysis can simultaneously determine the content of 10 active components and comprehensively evaluate the quality of different batches of LHQW. It can provide scientific basis and reference of quality consistency evaluation for the formulation manufacturers and drug regulatory authorities

    Alterations of Interhemispheric Functional Connectivity and Degree Centrality in Cervical Dystonia: A Resting-State fMRI Study

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    Background. Cervical dystonia (CD) is a neurological movement disorder characterized by involuntary head and neck movements and postures. Reports on microstructural and functional abnormalities in multiple brain regions not limited to the basal ganglia have been increasing in patients with CD. However, the neural bases of CD are unclear. This study is aimed at identifying cerebral functional abnormalities in CD by using resting-state functional magnetic resonance imaging (rs-fMRI). Methods. Using rs-fMRI data, voxel-mirrored homotopic connectivity (VMHC) and degree centrality were used to compare the alterations of the rs-functional connectivity (FC) between 19 patients with CD and 21 healthy controls. Regions showing abnormal FCs from two measurements were the regions of interest for correlation analyses. Results. Compared with healthy controls, patients with CD exhibited significantly decreased VMHC in the supplementary motor area (SMA), precuneus (PCu)/postcentral gyrus, and superior medial prefrontal cortex (MPFC). Significantly increased degree centrality in the right PCu and decreased degree centrality in the right lentiform nucleus and left ventral MPFC were observed in the patient group compared with the control group. Further correlation analyses showed that the VMHC values in the SMA were negatively correlated with dystonia severity. Conclusion. Local abnormalities and interhemispheric interaction deficits in the sensorimotor network (SMA, postcentral gyrus, and PCu), default mode network (MPFC and PCu), and basal ganglia may be the key characteristics in the pathogenesis mechanism of CD
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