基于联合变换相关的机载航空相机像移测量

为了提高像移测量精度,针对机载航空摆扫相机提出一种坐标变换法和图像相关法相结合的像移测量方法。利用坐标变换法得到初始像移速度,利用图像联合变换相关法对像移速度残差进行补偿。联合图像通过一个面阵CCD获得,该面阵CCD放置在相机焦平面上并与成像线阵TDI CCD平行,其输出的当前图像与参考图像合并构成联合图像进行二维空间联合变换相关运算,得到像移修正矢量。对该矢量分别在相机摆扫方向和载机飞行方向进行分解,从而得到摆扫像移和前向像移的修正量。仿真实验结果表明,在输入图像信噪比为4 dB时,像移测量误差在0.1 pixel以内。     

Measurement of micro weld joint position based on magneto-optical imaging

In a laser butt joint welding process,it is required that the laser beam focus should be controlled to follow the weld joint path accurately.Small focus wandering off the weld joint may result in insufficient penetration or unacceptable welds.Recognition of joint position offset,which describes the deviation between the laser beam focus and the weld joint,is important for adjusting the laser beam focus and obtaining high quality welds.A new method based on the magneto-optical(MO)imaging is applied to measure the micro weld joint whose gap is less than 0.2 mm.The weldments are excited by an external magnetic field,and an MO sensor based on principle of Faraday magneto effect is used to capture the weld joint images.A sequence of MO images which are tested under different magnetic field intensities and different weld joint widths are acquired.By analyzing the MO image characteristics and extracting the weld joint features,the influence of magnetic field intensity and weld joint width on the MO images and detection of weld joint position is observed and summarized.     

Aqueous‐Solution Route to Zinc Telluride Films for Application to CO2 Reduction

As a photocathode for CO₂ reduction, zinc‐blende zinc telluride (ZnTe) was directly formed on a Zn/ZnO nanowire substrate by a simple dissolution–recrystallization mechanism without any surfactant. With the most negative conduction‐band edge among p‐type semiconductors, this new photocatalyst showed efficient and stable CO formation in photoelectrochemical CO₂ reduction at ?0.2–?0.7 V versus RHE without a sacrificial reagent.     

A Doping Technique that Suppresses Undesirable H2 Evolution Derived from Overall Water Splitting in the Highly Selective Photocatalytic Conversion of CO2 in and by Water

Photocatalytic conversion of CO₂ to reduction products, such as CO, HCOOH, HCHO, CH₃OH, and CH₄, is one of the most attractive propositions for producing green energy by artificial photosynthesis. Herein, we found that Ga₂O₃ photocatalysts exhibit high conversion of CO₂. Doping of Zn species into Ga₂O₃ suppresses the H₂ evolution derived from overall water splitting and, consequently, Zn‐doped, Ag‐modified Ga₂O₃ exhibits higher selectivity toward CO evolution than bare, Ag‐modified Ga₂O₃. We observed stoichiometric amounts of evolved O₂ together with CO. Mass spectrometry clarified that the carbon source of the evolved CO is not the residual carbon species on the photocatalyst surface, but the CO₂ introduced in the gas phase. Doping of the photocatalyst with Zn is expected to ease the adsorption of CO₂ on the catalyst surface.     

Voltage‐Driven Reversible Insertion into and Leaving from a Lipid Bilayer: Tuning Transmembrane Transport of Artificial Channels

Three new artificial transmembrane channel molecules have been designed and synthesized by attaching positively charged Arg‐incorporated tripeptide chains to pillar[5]arene. Fluorescent and patch‐clamp experiments revealed that voltage can drive the molecules to insert into and leave from a lipid bilayer and thus switch on and off the transport of K⁺ ions. One of the molecules was found to display antimicrobial activity toward Bacillus subtilis with half maximal inhibitory concentration (IC₅₀) of 10 μM which is comparable to that of natural channel‐forming peptide alamethicin.     

羟基磷灰石/聚乙烯醇/壳聚糖水凝胶在模拟体液中的力学性能

从仿生学角度出发,将自制的人工角膜支架材料羟基磷灰石/聚乙烯醇/壳聚糖(n-HA/PVA/CS)浸泡在模拟体液中,对材料的含水率及力学性能进行了测试,并利用扫描电镜、X射线衍射仪、电感耦合等离子体原子发射光谱仪及热重分析仪研究了材料在模拟体液中的形貌、晶体结构、元素组成及热稳定性.结果表明,在模拟体液中,n-HA/PVA/CS复合水凝胶的含水率为80%~86%,具有较高的拉伸强度,能承受正常眼压,且热稳定性较好.在浸泡后期,n-HA/CS/PVA复合材料对Ca2+的吸附和释放达到动态平衡;而其表面含有微量的纳米羟基磷灰石沉积,有利于纤维细胞的长入.     

Discrete Hf18 Metal-oxo Cluster as a Heterogeneous Nanozyme for Site-Specific Proteolysis

The selective hydrolysis of proteins by non-enzymatic catalysis is difficult to achieve, yet it is crucial for applications in biotechnology and proteomics. Herein, we report that discrete hafnium metal-oxo cluster [Hf₁₈O₁₀(OH)₂₆(SO₄)₁₃⋅(H₂O)₃₃] ( Hf₁₈ ), which is centred by the same hexamer motif found in many MOFs, acts as a heterogeneous catalyst for the efficient hydrolysis of horse heart myoglobin (HHM) in low buffer concentrations. Among 154 amino acids present in the sequence of HHM, strictly selective cleavage at only 6 solvent accessible aspartate residues was observed. Mechanistic experiments suggest that the hydrolytic activity is likely derived from the actuation of Hf^IV Lewis acidic sites and the Brønsted acidic surface of Hf₁₈ . X-ray scattering and ESI-MS revealed that Hf₁₈ is completely insoluble in these conditions, confirming the HHM hydrolysis is caused by a heterogeneous reaction of the solid Hf₁₈ cluster, and not from smaller, soluble Hf species that could leach into solution.     

Accelerated Nuclear Magnetic Resonance Spectroscopy with Deep Learning

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental times. We present a proof‐of‐concept of the application of deep learning and neural networks for high‐quality, reliable, and very fast NMR spectra reconstruction from limited experimental data. We show that the neural network training can be achieved using solely synthetic NMR signals, which lifts the prohibiting demand for a large volume of realistic training data usually required for a deep learning approach.     

Artificial intelligence–based models for the qualitative and quantitative prediction of a phytochemical compound using HPLC method

Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile , Annona squamosal , Camellia sinensis (tea), and coriander ( Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, three different nonlinear models including artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM),in addition to a classical linear model [multilinear regression analysis (MLR)], were used for the prediction of the retention time (tR) and peak area (PA) for isoquercitrin using HPLC. The simulation uses concentration of the standard, composition of the mobile phases (MP-A and MP-B), and pH as the corresponding input variables. The performance efficiency of the models was evaluated using relative mean square error (RMSE), mean square error (MSE), determination coefficient (DC), and correlation coefficient (CC). The obtained results demonstrated that all four models are capable of predicting the qualitative and quantitative properties of the bioactive compound. A predictive comparison of the models showed that M3 had the highest prediction accuracy among the three models. Further evaluation of the results showed that ANFIS–M3 outperformed the other models and serves as the best model for the prediction of PA. On the other hand, ANN–M3proved its merit and emerged as the best model for tR simulation. The overall predictive accuracy of the best models showed them to be reliable tools for both qualitative and quantitative determination.