新型功能碳材料的高压截获

高性能功能材料在诸多领域具有广泛的应用前景,是人们一直关注的研究热点。高压可以有效地改变物质的原子间距和成键方式,是获得新型功能材料的重要途径。在碳材料的高压研究中,许多有趣的功能碳材料,如光学透明碳、高强度弹性碳和超硬非晶碳等,已经通过不同的碳前驱体合成。本文简要介绍了作者近年来在低维碳基纳米复合材料高压研究中取得的进展,基于设计的不同低维碳前驱体,高压下截获了具有超硬特性、新型压致共价聚合及发光增强的碳材料。     

Analytical formulas for complex permittivity of periodic composites. Estimation of gain and loss enhancement in active and passive composites

ABSTRACT

The asymptotic homogenization method is applied to complex dielectric periodic composites. An equivalence to coupled dielectric problems with real coefficients is shown. This is similar to a piezoelectric problem: an out-plane mechanical displacement and an in-plane electric potential establishing a correspondence principle. Closed-form formulas for the complex dielectric effective tensor in the case of a square array of circular inclusions embedded in a matrix are given. These formulas are written in terms of a real and symmetric matrix which facilitates the implementation of the computational scheme. We also get similar formulas for multilayered complex dielectric composites. The real closed-form formulas are advantageous for estimating gain and loss enhancement properties of active and passive composites in certain volume fraction intervals. Numerical computations are performed and the results are compared with other approaches showing the usefulness of the obtained formulas. This may be of interest in the context of metamaterials.     

Time-averaged flow characteristics and mixing properties of double-concentric jets

We examined the flow behaviors and mixing characteristics of double-concentric jets using laser-assisted smoke flow visualization method to analyze typical flow patterns and binary boundary detection technique to investigate jet spread width. Time-averaged velocity vectors, streamline patterns, velocity distributions, turbulence properties, and vorticity contours were analyzed using Particle Image Velocimetry (PIV). Topological flow patterns were analyzed to interpret the vortical flow structures. Mixing properties were investigated using a tracer-gas concentration detection method. Four characteristic modes were observed: annular flow dominated mode, transition mode, central jet dominated mode-low shear, and central jet dominated mode-high shear. The jets’ mixing properties were enhanced by two major phenomena: the merging of annular flow and central jet at the centerline and the large turbulence fluctuations produced in the flow field. The merging of the jets induced stagnation points on the central axis in the annular flow dominated mode, which caused reverse flow on the central axis and drastic turbulence fluctuations of the near field region. When the central jet penetrated the recirculation region in the other three modes, the stagnation points on the central axis and the reverse flow vanished. Therefore, the mixing behaviors were prominently enhanced in the annular flow dominated mode.     

基于Retinex理论与概率非局部均值的红外图像增强方法

针对传统红外图像增强算法中细节模糊及过度增强的问题,提出了一种基于Retinex理论与概率非局部均值相结合的红外图像增强方法.首先通过单尺度Retinex方法调整图像中过暗与过亮部分的灰度级;然后利用概率非局部均值对图像进行分解处理得到基本层与细节层,对基本层采用直方图均衡化拉伸对比度,对细节层采用非线性函数进行增强;最后,将不同层次的结果融合得到对比度与细节增强的红外图像.用该方法对多组不同场景的红外图像进行仿真实验,并将其与多种增强方法进行主、客观对比分析,结果表明所提方法在红外图像的细节及对比度增强方面都获得了更好的效果.     

Accurate,sensitive determination of omega-6 and omega-3 polyunsaturated fatty acids in human plasma,urine samples

Quantitative determination of omega-6 and omega-3 polyunsaturated fatty acids in human plasma and urine with high accuracy and precision provides significant information to monitor the underlying etiology of several diseases. In this regard, liquid chromatography-mass spectrometry is a good choice owing to its great selectivity and sensitivity. Additionally, the hybrid quadrupole–time of flight–mass spectrometer systems provides easy identification of target compounds with superior mass measurements. In this study, an analytical method has been developed for simple, accurate and simultaneous determination of linoleic acid, arachidonic acid, docosahexaenoic acid and eicosapentaenoic acid in a short chromatographic analysis period. The developed method is suitable for the quantitative detection of these four compounds with detection limits ranging between 1.1–3.0 ng ml⁻¹ and its applicability was assessed in human urine and plasma samples. As a result, acceptable accuracy (between 83 and 111%) and good precision (<6%) were obtained for target compounds using matrix matching calibration strategy.     

The High Energy X-ray telescope (HE) onboard the Insight-HXMT astronomy satellite

The Insight-Hard X-ray Modulation Telescope(Insight-HXMT) is a broadband X-ray and γ-ray(1-3000 ke V) astronomy satellite. One of its three main telescopes is the High Energy X-ray telescope(HE). The main detector plane of HE comprises 18 Na I(Tl)/Cs I(Na) phoswich detectors, where Na I(Tl) is used as the primary detector to measure ~ 20-250 ke V photons incident from the field of view(FOV) defined by collimators, and Cs I(Na) is used as the active shielding detector to Na I(Tl) by pulse shape discrimination. Additionally, Cs I(Na) is used as an omnidirectional γ-ray monitor. The HE collimators have a diverse FOV,i.e. 1.1°×5.7°(15 units), 5.7°×5.7°(2 units), and blocked(1 unit). Therefore, the combined FOV of HE is approximately5.7°×5.7°. Each HE detector has a diameter of 190 mm resulting in a total geometrical area of approximately 5100 cm2, and the energy resolution is ~15% at 60 ke V. For each recorded X-ray event by HE, the timing accuracy is less than 10 μs and the deadtime is less than 10 μs. HE is used for observing spectra and temporal variability of X-ray sources in the 20-250 ke V band either by pointing observations for known sources or scanning observations to unveil new sources. Additionally, HE is used for monitoring the γ-ray burst in 0.2-3 Me V band. This paper not only presents the design and performance of HE instruments but also reports results of the on-ground calibration experiments.     

A Micellar Mitotane Formulation with High Drug‐Loading and Solubility: Physico‐Chemical Characterization and Cytotoxicity Studies in 2D and 3D In Vitro Tumor Models

Adrenocortical carcinoma (ACC) is a rare tumor and prognosis is overall poor but heterogeneous. Mitotane (MT) has been used for treatment of ACC for decades, either alone or in combination with cytotoxic chemotherapy. Even at doses up to 6 g per day, more than half of the patients do not achieve targeted plasma concentration (14–20 mg L^?1) even after many months of treatment due to low water solubility, bioavailability, and unfavorable pharmacokinetic profile. Here a novel MT nanoformulation with very high MT concentrations in physiological aqueous media is reported. The MT‐loaded nanoformulations are characterized by Fourier transform infrared spectroscopy, differential scanning calorimetry, and powder X‐ray diffraction which confirms the amorphous nature of the drug. The polymer itself does not show any cytotoxicity in adrenal and liver cell lines. By using the ACC model cell line NCI‐H295 both in monolayers and tumor cell spheroids, micellar MT is demonstrated to exhibit comparable efficacy to its ethanol solution. It is postulated that this formulation will be suitable for i.v. application and rapid attainment of therapeutic plasma concentrations. In conclusion, the micellar formulation is considered a promising tool to alleviate major drawbacks of current MT treatment while retaining bioactivity toward ACC in vitro.     

Co-Training for Visual Object Recognition Based on Self-Supervised Models Using a Cross-Entropy Regularization

Automatic recognition of visual objects using a deep learning approach has been successfully applied to multiple areas. However, deep learning techniques require a large amount of labeled data, which is usually expensive to obtain. An alternative is to use semi-supervised models, such as co-training, where multiple complementary views are combined using a small amount of labeled data. A simple way to associate views to visual objects is through the application of a degree of rotation or a type of filter. In this work, we propose a co-training model for visual object recognition using deep neural networks by adding layers of self-supervised neural networks as intermediate inputs to the views, where the views are diversified through the cross-entropy regularization of their outputs. Since the model merges the concepts of co-training and self-supervised learning by considering the differentiation of outputs, we called it Differential Self-Supervised Co-Training (DSSCo-Training). This paper presents some experiments using the DSSCo-Training model to well-known image datasets such as MNIST, CIFAR-100, and SVHN. The results indicate that the proposed model is competitive with the state-of-art models and shows an average relative improvement of 5% in accuracy for several datasets, despite its greater simplicity with respect to more recent approaches.     

Tutorial review on validation of liquid chromatography–mass spectrometry methods: Part II

This is the part II of a tutorial review intending to give an overview of the state of the art of method validation in liquid chromatography mass spectrometry (LC–MS) and discuss specific issues that arise with MS (and MS–MS) detection in LC (as opposed to the “conventional” detectors). The Part II starts with briefly introducing the main quantitation methods and then addresses the performance related to quantification: linearity of signal, sensitivity, precision, trueness, accuracy, stability and measurement uncertainty. The last section is devoted to practical considerations in validation. With every performance characteristic its essence and terminology are addressed, the current status of treating it is reviewed and recommendations are given, how to handle it, specifically in the case of LC–MS methods.     

FRET Enhancement in Aluminum Zero‐Mode Waveguides

Zero‐mode waveguides (ZMWs) can confine light into attoliter volumes, which enables single molecule fluorescence experiments at physiological micromolar concentrations. Of the fluorescence spectroscopy techniques that can be enhanced by ZMWs, Förster resonance energy transfer (FRET) is one of the most widely used in life sciences. Combining zero‐mode waveguides with FRET provides new opportunities to investigate biochemical structures or follow interaction dynamics at micromolar concentrations with single‐molecule resolution. However, prior to any quantitative FRET analysis on biological samples, it is crucial to establish first the influence of the ZMW on the FRET process. Here, we quantify the FRET rates and efficiencies between individual donor–acceptor fluorophore pairs that diffuse into aluminum zero‐mode waveguides. Aluminum ZMWs are important structures thanks to their commercial availability and the large amount of literature that describe their use for single‐molecule fluorescence spectroscopy. We also compared the results between ZMWs milled in gold and aluminum, and found that although gold has a stronger influence on the decay rates, the lower losses of aluminum in the green spectral region provide larger fluorescence brightness enhancement factors. For both aluminum and gold ZMWs, we observed that the FRET rate scales linearly with the isolated donor decay rate and the local density of optical states. Detailed information about FRET in ZMWs unlocks their application as new devices for enhanced single‐molecule FRET at physiological concentrations.