17 research outputs found
Maximal Quantum Fisher Information in a Mach-Zehnder Interferometer without initial parity
Mach-Zehnder interferometer is a common device in quantum phase estimation
and the photon losses in it are an important issue for achieving a high phase
accuracy. Here we thoroughly discuss the precision limit of the phase in the
Mach-Zehnder interferometer with a coherent state and a superposition of
coherent states as input states. By providing a general analytical expression
of quantum Fisher information, the phase-matching condition and optimal initial
parity are given. Especially, in the photon loss scenario, the sensitivity
behaviors are analyzed and specific strategies are provided to restore the
phase accuracies for symmetric and asymmetric losses.Comment: 10 pages, 3 figure
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Image registration is a fundamental medical image analysis task, and a wide
variety of approaches have been proposed. However, only a few studies have
comprehensively compared medical image registration approaches on a wide range
of clinically relevant tasks. This limits the development of registration
methods, the adoption of research advances into practice, and a fair benchmark
across competing approaches. The Learn2Reg challenge addresses these
limitations by providing a multi-task medical image registration data set for
comprehensive characterisation of deformable registration algorithms. A
continuous evaluation will be possible at
https://learn2reg.grand-challenge.org. Learn2Reg covers a wide range of
anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR),
availability of annotations, as well as intra- and inter-patient registration
evaluation. We established an easily accessible framework for training and
validation of 3D registration methods, which enabled the compilation of results
of over 65 individual method submissions from more than 20 unique teams. We
used a complementary set of metrics, including robustness, accuracy,
plausibility, and runtime, enabling unique insight into the current
state-of-the-art of medical image registration. This paper describes datasets,
tasks, evaluation methods and results of the challenge, as well as results of
further analysis of transferability to new datasets, the importance of label
supervision, and resulting bias. While no single approach worked best across
all tasks, many methodological aspects could be identified that push the
performance of medical image registration to new state-of-the-art performance.
Furthermore, we demystified the common belief that conventional registration
methods have to be much slower than deep-learning-based methods
Decision Tree Classification of PolSAR Image Based on Two-dimensional Polarimetric Features
The decision tree model has great significance in the application of polarimetric SAR data classification, whose results in many types of classification applications obtain good accuracy and are interpretable by polarimetric scattering mechanisms. In the traditional decision tree model, because one single feature is employed by the nodes of the decision tree, the accuracy of the classification result tends to be poor, especially, for applications that classify objects with similar scattering characteristics. In this paper, we propose an improved method to create a two-dimensional vector of features instead of one single feature at the decision nodes. As a result, the classification results of the new method adopting the same feature set as the traditional decision tree can achieve better accuracy. In addition, after classification, the new method may employ a confusion matrix to identify the decision node that yields a classification error, which will facilitate the objectoriented feedback adjustment of classification results, thus making it possible to improve the classification accuracy of the specified object. Our experimental results with AIRSAR-Flevoland data prove the validity of the proposed method, and we draw some useful conclusions about the scattering characteristics of several types of vegetation
A Sensitive Co-MOF/CNTs/SiO2 Composite Based Electrode for Determination of Gallic Acid
A novel Co-based organic frameworks/carbon nanotubes/silicon dioxide (Co-MOF/CNTs/SiO2)-modified Au electrode was fabricated and taken as a platform for gallic acid (GA) detection. The composite combined the advantages of Co-MOF, CNTs and SiO2, and higher electrochemical response of Co-MOF/CNTs/SiO2-modified electrode indicated that the composite material exhibited satisfied the catalytic activity towards GA. Moreover, the electrochemical oxidation process of GA was deeply investigated on the surface of electrode based on computational investigations. Hirshfeld charges and condensed Fukui functions of each atom in GA were calculated. Besides, the catalysis of Co-MOF to GA was further investigated based on density functional theory. The quantitative determination of GA was carried out and showed a linear range between 0.05–200 μM, with low limit of detection. The sensitivity value of the self-assembled electrochemical sensor was calculated to be 593.33 μA cm−2 mM−1, and the selectivity, reproducibility and stability of the gallic acid sensor were also confirmed in the study
A Sensitive Co-MOF/CNTs/SiO<sub>2</sub> Composite Based Electrode for Determination of Gallic Acid
A novel Co-based organic frameworks/carbon nanotubes/silicon dioxide (Co-MOF/CNTs/SiO2)-modified Au electrode was fabricated and taken as a platform for gallic acid (GA) detection. The composite combined the advantages of Co-MOF, CNTs and SiO2, and higher electrochemical response of Co-MOF/CNTs/SiO2-modified electrode indicated that the composite material exhibited satisfied the catalytic activity towards GA. Moreover, the electrochemical oxidation process of GA was deeply investigated on the surface of electrode based on computational investigations. Hirshfeld charges and condensed Fukui functions of each atom in GA were calculated. Besides, the catalysis of Co-MOF to GA was further investigated based on density functional theory. The quantitative determination of GA was carried out and showed a linear range between 0.05–200 μM, with low limit of detection. The sensitivity value of the self-assembled electrochemical sensor was calculated to be 593.33 μA cm−2 mM−1, and the selectivity, reproducibility and stability of the gallic acid sensor were also confirmed in the study
Factors responsible for unanticipated hypertension during emergence from general anesthesia
Risk factors for acute postoperative hypertension in non-cardiac major surgery: a case control study
Abstract Purpose Acute postoperative hypertension (APH) is a common complication during the anesthesia recovery period that can lead to adverse outcomes, including cardiovascular and cerebrovascular accidents. Identification of risk factors for APH will allow for preoperative optimization and appropriate perioperative management. This study aimed to identify risk factors for APH. Patients and methods In this retrospective single-center study, 1,178 cases were included. Data was entered by two investigators, and consistency analysis was performed by another. Patients were divided into APH and non-APH groups. A predictive model was built by multivariate stepwise logistic regression. The predictive ability of the logistic regression model was tested by drawing the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Hosmer and Lemeshow goodness-of-fit (GOF) test was performed to reflect the goodness of fit of the model. Calibration curve was created to represent the relationship between predicted risk and observed frequency. Sensitivity analysis was performed to evaluate the robustness of the results. Results Multivariate logistic regression analysis showed that age over 65 years (OR = 3.07, 95% CI: 2.14 ~ 4.42, P < 0.001), female patients (OR = 1.37, 95% CI: 1.02 ~ 1.84, P = 0.034), presence of intraoperative hypertension (OR = 2.15, 95% CI: 1.57 ~ 2.95, P < 0.001), and use of propofol in PACU (OR = 2.14, 95% CI: 1.49 ~ 3.06, P < 0.001) were risk factors for APH. Intraoperative use of dexmedetomidine (OR = 0.66, 95% CI: 0.49 ~ 0.89, P = 0.007) was a protective factor. Higher baseline SBP (OR = 0.90, 95% CI: 0.89 ~ 0.92, P < 0.001) also showed some correlation with APH. Conclusions The risk of acute postoperative hypertension increased with age over 65 years, female patients, intraoperative hypertension and restlessness during anesthesia recovery. Intraoperative use of dexmedetomidine was a protective factor for APH
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Teaching an old carbocation new tricks: Intermolecular C–H insertion reactions of vinyl cations
Vinyl carbocations have been the subject of extensive experimental and theoretical studies over the past five decades. Despite this long history in chemistry, the utility of vinyl cations in chemical synthesis has been limited, with most reactivity studies focusing on solvolysis reactions or intramolecular processes. Here we report synthetic and mechanistic studies of vinyl cations generated through silylium-weakly coordinating anion catalysis. We find that these reactive intermediates undergo mild intermolecular carbon-carbon bond-forming reactions, including carbon-hydrogen (C-H) insertion into unactivated sp3 C-H bonds and reductive Friedel-Crafts reactions with arenes. Moreover, we conducted computational studies of these alkane C-H functionalization reactions and discovered that they proceed through nonclassical, ambimodal transition structures. This reaction manifold provides a framework for the catalytic functionalization of hydrocarbons using simple ketone derivatives
Large negative giant magnetoresistance at room temperature and electrical transport in cobalt ferrite-polyaniline nanocomposites
At room temperature, a large negative out-of-plane magnetoresistance (MR), [R(H)-R(0)]/R(0), with a value of −35.76% at magnetic field of 9 T has been obtained in the cobalt ferrite (CoFe2O4)/polyaniline (PANI) nanocomposites with CoFe2O4 loading of 40.0 wt% prepared by surface initiated polymerization (SIP) method, which is strongly related to the weak localization (WL) model in the weak disordered system. The negative MR at room temperature in the CoFe2O4/PANI nanocomposites exhibits the obvious nanoparticle loading and magnetic field dependent properties. Both thermal activated transport model and Mott variable range hopping (VRH) model are applied to express the electrical transport mechanism for the temperature regimes of 180–290 K and 50–180 K, accordingly. The electrical transport in the CoFe2O4/PANI nanocomposites obeys the 3D VRH transport mechanism at low temperature range of 50–180 K. The estimated activation energy Eg for the CoFe2O4/PANI nanocomposites with different CoFe2O4 nanoparticle loadings of 10.0, 20.0, 40.0, and 60.0 wt% is 61, 63, 65, and 87 meV, respectively. The coating of PANI on the surface of CoFe2O4 nanoparticle reveals the significant effect on both the remanence and coercivity of CoFe2O4 nanoparticle