A new class of conformable spectral observers for signal reconstruction

In this work, the design of spectral observers for signal reconstruction based on Kalman filters is performed and evaluated. The conformable derivative and the beta‐derivative were used to design the Kalman filters. Both derivatives satisfy the same formulas of the classical derivation, eg, the chain rule. The derivative order, the Ricatti equation parameters, and the observers tuning parameters were optimized using an optimization algorithm based on the bat's echolocation behavior (Bat algorithm). The simulation results showed the advantages of using the proposed observers for the signal reconstruction.     

Synergistic Effects of Pseudocolor Imaging,Differentiation, and Square and Logarithmic Conversion on Accuracy of Quantification of Chemical Characteristics Using Test Strips and Similar Products

Test strips and similar products are highly feasible tools for the rapid and approximate determination of chemical characteristics. Although the application of both the quantitative observation of coloration and regression modeling has recently enabled these products to become quantitative tools, their precision and accuracy may be further improved. In this study, the pseudocolor imaging of the coloration image, derivative spectrophotometry-like differentiation of the coloration values, and logarithmic conversion of the raw and derivative values were compared in terms of the precision and accuracy of the quantitative determination of corrosiveness, glucose, nitrate, and pH using the products. The best regression models for the determination were provided by the combination of pseudocolor imaging and differentiation (nitrate and pH); pseudocolor imaging, differentiation, and square-conversion (corrosiveness); or all of the techniques (glucose). When compared to the use of the original 10 raw coloration variables of red-green-blue, cyan-magenta-yellow-key black, and L*a*b* color models only, the above combinations improved the normalized mean absolute error from 14.8% to 3.09% (corrosiveness), 6.33% to 3.15% (glucose), 7.46% to 4.56% (nitrate), and 3.22% to 0.94% (pH). These achievements were largely attributed to the combination of multiple variables that have non-linear and nonmonotonic relationships with the chemical characteristics.     

Substituent effects on the Lewis acidity of 4,6-di-tert-butylchatechol boronate esters

In studying the factors which contribute to the Lewis acidity of organoboron compounds we investigated approaches to the design of robust, novel Lewis acids purposed for metal-free catalysis. Based on a sterically encumbered catechol motif, a series of boronate esters are shown to demonstrate modest Lewis acidities for the conventional Gutmann-Beckett test as an inquisitive investigation.     

Research on the ions' axial temperature of a sympathetically-cooled 113Cd+ ion crystal

Molecular dynamics simulation of a sympathetically-cooled ¹¹³Cd⁺ ion crystal system is achieved. Moreover, the relationship between ions' axial temperature and different electric parameters, including radio frequency voltage and end-cap voltage is depicted. Under stable trapping condition, optimum radio frequency voltage, corresponding to minimum temperature and the highest cooling efficiency, is obtained. The temperature is positively correlated with end-cap voltage. The relationship is also confirmed by a sympathetically-cooled ¹¹³Cd⁺ microwave clock. The pseudo-potential model is used to illustrate the relationship and influence mechanism. A reasonable index, indicating ions' temperature, is proposed to quickly estimate the relative ions' temperature. The investigation is helpful for ion crystal investigation, such as spatial configuration manipulation, sympathetic cooling efficiency enhancement, and temporal evolution.     

Nanomaterials in Cerebrovascular Disease Diagnose and Treatment

Cerebrovascular diseases (CVDs) are among the most serious diseases with high mortality and disability rates. The prevalent diagnosis and treatment methods of CVDs include imaging and interventional therapy. With the development of nanotechnology, large numbers of nanomaterials have been applied to the diagnosis and treatment of CVDs, mainly including carbon nanotubes, quantum dots, fullerenes, and dendrimers. In this review, the applications of nanomaterials in the field of diagnosis and treatment of CVDs, mainly including drug target delivery, imaging, therapy, endovascular treatment, and angiogenesis, are summarized. The applications of nanomaterials in the field of CVD are almost in the laboratory, and more effort is needed for clinical translation. The aim of this review is to provide useful information for future research and equipment development.     

Facile Synthesis of Manganese Tellurite Nanoparticles for Magnetic Resonance Imaging-Guided Photothermal Therapy

In this study, manganese tellurite (MnTeO₃) nanoparticles are developed as theranostic agents for magnetic resonance imaging (MRI)-guided photothermal therapy of tumor. MnTeO₃ nanoparticles are synthesized via a simple one-step method. The as-synthesized MnTeO₃ nanoparticles with uniform size show good biocompatibility. In particular, MnTeO₃ nanoparticles exhibit a high photothermal conversion efficiency (η = 26.3%), which is higher than that of gold nanorods. Moreover, MnTeO₃ nanoparticles also have high MRI performance. The longitudinal relaxivity (r₁) value of MnTeO₃ nanoparticles is determined to be 8.08 ± 0.2 mm ⁻¹ s⁻¹, which is higher than that of clinically approved T₁-contrast agents Gd-DTPA (4.49 ± 0.1 mm ⁻¹ s⁻¹). The subsequent MnTeO₃ nanoparticles-mediated photothermal therapy displays a highly efficient ablation of tumor cells both in vitro and in vivo with negligible toxicity. It is demonstrated that MnTeO₃ nanoparticles can serve as promising theranostic agents with great potentials for MRI-guided photothermal therapy.     

Efficient Gating of Ion Transport in Three‐Dimensional Metal–Organic Framework Sub‐Nanochannels with Confined Light‐Responsive Azobenzene Molecules

1D nanochannels modified with responsive molecules are fabricated to replicate gating functionalities of biological ion channels, but gating effects are usually weak because small molecular gates cannot efficiently block the large channels in the closed states. Now, 3D metal–organic framework (MOF) sub‐nanochannels (SNCs) confined with azobenzene (AZO) molecules achieve efficient light‐gating functionalities. The 3D MOFSNCs consisting of a MOF UiO66 with ca. 9–12 Å cavities connected by ca. 6 Å triangular windows work as angstrom‐scale ion channels, while confined AZO within the MOF cavities function as light‐driven molecular gates to efficiently regulate the ion flux. The AZO‐MOFSNCs show good cyclic gating performance and high on–off ratios up to 17.8, an order of magnitude higher than ratios observed in conventional 1D AZO‐modified nanochannels (1.3–1.5). This work provides a strategy to develop highly efficient switchable ion channels based on 3D porous MOFs and small responsive molecules.     

Counterion-Trapped-Molecules: From High Polarity and Enriched IR Spectra to Induced Isomerization

We report extensive computational studies of some novel intermolecular systems and their properties. Recombination of alkali-halide counterions separated by a noncovalently trapped hydrocarbon molecule is prevented by significant potential energy barriers, resulting in unusual metastable insertion complexes. These systems are extremely polar, while the inserted molecule is strongly counter-polarized, leading to significant cooperative nonadditivity effects. The compression and electric field produced by the counterions favours isomerization of the trapped molecule via a significant reduction of the barriers to bond rearrangement, in a field-induced mechanochemical process. The predicted IR intensity spectra clearly reflect (1) formation of the insertion complex, rather than simple attachment of alkali halide, and (2) isomerization of the trapped molecule, thus allowing experimental access to these events.     

Effects of nuclear charge fluctuations on dilepton photoproduction

Fluctuations of dilepton production from two photon interactions γγ→l~+l~- are studied in semicentral and peripheral nuclear collisions.Based on the Weizsacker-Williams approach,electromagnetic(EM) fields generated by moving nuclear charges are approximated as quasi-real photons.As fluctuating EM fields in each collision event are hard to be measured directly in experiments due to its short lifetime,we study the dilepton photoproduction with fluctuating EM fields,which are crucial for the EM fields induced chiral and charged particle evolutions,and calculate the relative standard deviation of the dilepton mass spectrum with the event-by-event fluctuating nuclear charge distributions.This fluctuation effect becomes smaller in more peripheral collisions where the shift of proton positions is implicit for EM fields outside the nucleus.The uncertainty of effective impact parameter △b on the standard deviation is also studied,and its effect is around one-third of the effect of nuclear charge fluctuations when △b is taken as～1 fm.     

基于级联卷积神经网络的前列腺磁共振图像分类

针对深度学习训练成本高，以及基于磁共振图像的前列腺癌临床诊断需要大量医学常识且极为耗时的问题，本文提出了一种基于级联卷积神经网络（Convolutional Neural Network，CNN）和磁共振图像的前列腺癌（Prostate Cancer，PCa）自动分类诊断方法，该网络以Faster-RCNN作为前网络，对前列腺区域进行提取分割，用于排除前列腺附近组织器官的干扰；以基于ResNet改进的网络结构CNN40_bottleneck作为后网络，用于对前列腺区域病变进行分类.后网络由瓶颈结构串联组成，其中使用批量标准化（Batch Normalization，BN）、全局平均池化（Global Average Pooling，GAP）进行优化.实验结果证明，本文方法对前列腺癌诊断结果较好，而且缩减了训练时间和参数量，有效降低了训练成本.