第三族金属氧化物离子对二氧化碳转化的红外光谱研究

本文利用红外光解离光谱研究了第三族金属氧化物离子对二氧化碳分子的转化机制. 研究表明，对于[ScO(CO₂)_n]⁺体系，在n≤4时，形成了溶剂化结构；在n=5时，形成了碳酸盐结构，实现了二氧化碳的转化. 对于[YO(CO₂)_n]⁺体系，需要4个二氧化碳分子就可以实现二氧化碳的转化. 而在[YO(CO₂)_n]⁺体系中，只发现了溶剂化结构，没有观察到碳酸盐结构. 理论计算表明，[YO(CO₂)_n]⁺体系拥有最小的溶剂化结构向碳酸盐结构转化能垒，[LaO(CO₂)_n]⁺体系拥有最大的溶剂化结构向碳酸盐结构转化能垒. 本文从分子水平揭示了不同金属氧化物离子对二氧化碳分子转化的影响规律.     

Multifunctional Sulfur-Hyperdoped Silicon Nanoparticles with Engineered Mid-Infrared Sulfur-Impurity and Free-Carrier Absorption

Si nanoparticles (NPs), which are innovative promising light-harvesting components of thin-film solar cells and key-enabling biocompatible theranostic elements of infrared-laser and radiofrequency hyperthermia-based therapies of cancer cells in tumors and metastases, are significantly advanced in their near/mid-infrared band-to-band and free-carrier absorption via donor sulfur-hyperdoping during high-throughput facile femtosecond-laser ablative production in liquid carbon disulfide. High-resolution transmission electron microscopy and Raman microscopy reveal their mixed nanocrystalline/amorphous structure, enabling the extraordinary sulfur content of a few atomic percents and very minor surface oxidation/carbonization characterized by energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy. A 200-nm thick layer of the nanoparticles exhibits near−mid-infrared absorbance, comparable to that of the initial 380-micron thick n-doped Si wafer (phosphor-dopant concentration ≈10¹⁵ cm⁻³), with the corresponding extinction coefficient for the hyperdoped NPs being 4–7 orders higher over the broadband spectral range of 1–25 micrometers. Such ultimate, but potentially tunable mid-IR structured, multi-band absorption of various sulfur-impurity clusters and smooth free-carrier absorption are break through advances in mid-infrared (mid-IR) laser and radiofrequency (RF) hyperthermia-based therapies, as envisioned in the RF-heating tests, and in fabrication of higher-efficiency thin-film and bulk photovoltaic devices with ultra-broad (UV−mid-IR) spectral response.     

桉树杂交种与其亲本的近红外光谱判别

研究桉树控制授粉后目标性状的基因作用方式是探索其基因重组规律的重要内容。常规的数量统计分析精度往往不高,而DNA分析的专业要求高,且费时费力。该研究利用近红外光谱(NIRs)研究不同基因型桉树杂交种、亲本及杂交种与亲本间近红外光谱信息的关系,探索NIRs用于桉树杂交种与其亲本判别的可行性和准确性。以控制授粉的桉树亲本及其杂交F1代材料为对象,每种基因型从各自田间试验分别选取10个单株,采集树冠中上部新鲜健康叶片。用手持式近红外仪Phazir Rx(1624)采集桉树杂交种与其亲本叶片的NIRs信息。每单株选10片完全生理成熟的健康叶片,避开叶脉扫描其正面光谱5次,以50条NIRs信息的均值代表单个叶片的NIRs信息,最终每个基因型获得10条NIRs信息。对原始NIRs采用二阶多项式S.G一阶导数预处理。预处理后的NIRs用于多元统计分析,首先对桉树杂交亲本和子代样本进行主成分分析(PCA),直观展示不同基因型的分类情况。然后运用簇类独立软模式(SIMCA)和偏最小二乘判别分析(PLS-DA)两种有监督的判别模式验证NIRs用于桉树杂交种与其亲本树种的分类判别效果。PCA结果显示,不同的亲本间、杂交种间及杂交种与亲本间样本的主因子得分可以清晰地将各基因型分开。SIMCA模式判别分析中,桉树杂交种样本到亲本PCA模型的样本距离显示,待判别样本能够形成单独的聚类,且能直观反映两者的遗传相似。PLS-DA判别结果显示,桉树杂交亲本的PLS模型能通过预测其杂交子代的响应变量将其与亲本准确分开。结果表明,桉树叶片的NIRs信息可以准确地反映桉树杂交子代遗传信息的传递规律,NIRs判别模型可以准确地将各种基因型予以区分。因此,NIRs信息不仅可用于桉树杂交种和纯种的定性判别,还可以分析桉树基因重组过程中加性遗传效应的大小,从而为桉树遗传基础分析及其育种改良研究提供理论支撑。     

Parallel Translation on K¨ahler Manifolds

In this paper, the author establishs a real-valued function on K¨ahler manifolds by holomorphic sectional curvature under parallel translation. The author proves if such functions are equal for two simply-connected, complete K¨ahler manifolds, then they are holomorphically isometric.     

Noise Reduction in Spur Gear Systems

This article lists some tips for reducing gear case noise. With this aim, a static analysis was carried out in order to describe how stresses resulting from meshing gears affect the acoustic emissions. Different parameters were taken into account, such as the friction, material, and lubrication, in order to validate ideas from the literature and to make several comparisons. Furthermore, a coupled Eulerian–Lagrangian (CEL) analysis was performed, which was an innovative way of evaluating the sound pressure level of the aforementioned gears. Different parameters were considered again, such as the friction, lubrication, material, and rotational speed, in order to make different research comparisons. The analytical results agreed with those in the literature, both for the static analysis and CEL analysis—for example, it was shown that changing the material from steel to ductile iron improved the gear noise, while increasing the rotational speed or the friction increased the acoustic emissions. Regarding the CEL analysis, air was considered a perfect gas, but its viscosity or another state equation could have also been taken into account. Therefore, the above allowed us to state that research into these scientific fields will bring about reliable results.     

Sonication enhances the stability of MnO2 nanoparticles on silk film template for enzyme mimic application

We have developed an in-situ method using sonication (3 mm probe sonicator, 30 W, 20 kHz) and auto-reduction (control) to study the mechanism of the formation of manganese dioxide (MnO₂) on a solid template (silk film), and its resulting enzymatic activity on tetramethylbenzidine (TMB) substrate. The fabrication of the silk film was first optimized for stability (no degradation) and optical transparency. A factorial approach was used to assess the effect of sonication time and the initial concentration of potassium permanganate (KMnO₄). The result indicated a significant correlation with a fraction of KMnO₄ consumed and MnO₂ formation. Further, we found that the optimal process conditions to obtain a stable silk film with highly catalytic MnO₂ nanoparticles (NPs) was 30 min of sonication in the presence of 0.5 mM of KMnO₄ at a temperature of 20–24 °C. Under the optimal condition, we monitored in-situ the formation of MnO₂ on the silk film, and after thorough rinsing, the in-situ catalysis of 0.8 mM of TMB substrate. For control, we used the auto-reduction of KMnO₄ onto the silk film after about 16 h. The result from single-wavelength analysis confirmed the different kinetics rates for the formation of MnO₂ via sonication and auto-reduction. The result from the multivariate component analysis indicated a three components route for sonication and auto-reduction to form MnO₂-Silk. Overall, we found that the smaller size, more mono-dispersed, and deeper buried MnO₂ NPs in silk film prepared by sonication, conferred a higher catalytic activity and stability to the hybrid material.     

A Survey of Information Entropy Metrics for Complex Networks

Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it difficult to identify available metrics and understand the context in which they are applicable. In this work, a narrative literature review of information entropy metrics for complex networks is conducted following the PRISMA guidelines. Existing entropy metrics are classified according to three different criteria: whether the metric provides a property of the graph or a graph component (such as the nodes), the chosen probability distribution, and the types of complex networks to which the metrics are applicable. Consequently, this work identifies the areas in need for further development aiming to guide future research efforts.     

Information percolation and cutoff for the random‐cluster model

We consider the random‐cluster model (RCM) on with parameters p∈(0,1) and q ≥ 1. This is a generalization of the standard bond percolation (with edges open independently with probability p) which is biased by a factor q raised to the number of connected components. We study the well‐known Fortuin‐Kasteleyn (FK)‐dynamics on this model where the update at an edge depends on the global geometry of the system unlike the Glauber heat‐bath dynamics for spin systems, and prove that for all small enough p (depending on the dimension) and any q>1, the FK‐dynamics exhibits the cutoff phenomenon at with a window size , where λ_∞ is the large n limit of the spectral gap of the process. Our proof extends the information percolation framework of Lubetzky and Sly to the RCM and also relies on the arguments of Blanca and Sinclair who proved a sharp mixing time bound for the planar version. A key aspect of our proof is the analysis of the effect of a sequence of dependent (across time) Bernoulli percolations extracted from the graphical construction of the dynamics, on how information propagates.     

Solvable Model of a Generic Driven Mixture of Trapped Bose–Einstein Condensates and Properties of a Many-Boson Floquet State at the Limit of an Infinite Number of Particles

A solvable model of a periodically driven trapped mixture of Bose–Einstein condensates, consisting of N1 interacting bosons of mass m1 driven by a force of amplitude fL,1 and N2 interacting bosons of mass m2 driven by a force of amplitude fL,2, is presented. The model generalizes the harmonic-interaction model for mixtures to the time-dependent domain. The resulting many-particle ground Floquet wavefunction and quasienergy, as well as the time-dependent densities and reduced density matrices, are prescribed explicitly and analyzed at the many-body and mean-field levels of theory for finite systems and at the limit of an infinite number of particles. We prove that the time-dependent densities per particle are given at the limit of an infinite number of particles by their respective mean-field quantities, and that the time-dependent reduced one-particle and two-particle density matrices per particle of the driven mixture are 100% condensed. Interestingly, the quasienergy per particle does not coincide with the mean-field value at this limit, unless the relative center-of-mass coordinate of the two Bose–Einstein condensates is not activated by the driving forces fL,1 and fL,2. As an application, we investigate the imprinting of angular momentum and its fluctuations when steering a Bose–Einstein condensate by an interacting bosonic impurity and the resulting modes of rotations. Whereas the expectation values per particle of the angular-momentum operator for the many-body and mean-field solutions coincide at the limit of an infinite number of particles, the respective fluctuations can differ substantially. The results are analyzed in terms of the transformation properties of the angular-momentum operator under translations and boosts, and as a function of the interactions between the particles. Implications are briefly discussed.     

Side Information Generation Scheme Based on Coefficient Matrix Improvement Model in Transform Domain Distributed Video Coding

In order to effectively improve the quality of side information in distributed video coding, we propose a side information generation scheme based on a coefficient matrix improvement model. The discrete cosine transform coefficient bands of the Wyner–Ziv frame at the encoder side are divided into entropy coding coefficient bands and distributed video coding coefficient bands, and then the coefficients of entropy coding coefficient bands are sampled, which are divided into sampled coefficients and unsampled coefficients. For sampled coefficients, an adaptive arithmetic encoder is used for lossless compression. For unsampled coefficients and the coefficients of distributed video coding coefficient bands, the low density parity check accumulate encoder is used to calculate the parity bits, which are stored in the buffer and transmitted in small amount upon decoder request. At the decoder side, the optical flow method is used to generate the initial side information, and the initial side information is improved according to the sampled coefficients by using the coefficient matrix improvement model. The experimental results demonstrate that the proposed side information generation scheme based on the coefficient matrix improvement model can effectively improve the quality of side information, and the quality of the generated side information is improved by about 0.2–0.4 dB, thereby improving the overall performance of the distributed video coding system.