Environmentally friendly synthesis and photopolymerization of acrylated methyl ricinoleate for biomedical applications

In this study, we aimed to develop an efficient synthesis and photopolymerization of acrylated methyl ricinoleate (AMR) for biomedical applications. During the first step of the synthesis, methyl ricinoleate (MR) and boric acid were esterified via azeotropic distillation in toluene. Afterward, MR–boric acid ester was acrylated with acrylic acid at 165 °C via a boric acid ester acidolysis reaction. The bulk photopolymerization of AMR was performed in the presence of the photoinitiator 2,2-dimethoxy-2-phenyl acetophenone (DMPA) under 365 nm UV irradiation. Even with the use of 0.4% DMPA, a 35% monomer conversion was achieved within 30 min. Moreover, AMR, the plant-oil-based monomer, was also copolymerized with N-isopropyl acrylamide to obtain thermoresponsive hydrogels on the glass surface for biomedical applications. The synthesized materials were characterized by Fourier transform infrared (FTIR) spectroscopy, ¹H-NMR spectroscopy, and thermal characterization via thermogravimetric analysis (TGA) and differential scanning calorimetry techniques. The surfaces were characterized by FTIR and Energy Dispersive X-ray (EDS) spectroscopy. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47969.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

基于学生群体心理测试系统的设计

心理测试的根本目的是为了让人们在测试过程中，产生某些特定行为，即个体对测试题目的反应，并根据这些行为反应来推论其相应的心理特性。在一定程度上帮助我们了解人类的心理活动，并从中得到帮助。因此，本文对基于学生群体心理测试系统的设计进行深入研究。     

Models for solar radiation prediction based on different measurement sites

The modeling of solar radiation for forecasting its availability is a key tool for managing photovoltaic (PV) plants and, hence, is of primary importance for energy production in a smart grid scenario. However, the variability of the weather phenomena is an unavoidable obstacle in the prediction of the energy produced by the solar radiation conversion. The use of the data collected in the past can be useful to capture the daily and seasonal variability, while measurement of the recent past can be exploited to provide a short term prediction. It is well known that a good measurement of the solar radiation requires not only a high class radiometer, but also a correct management of the instrument. In order to reduce the cost related to the management of the monitoring apparatus, a solution could be to evaluate the PV plant performance using data collected by public weather station installed near the plant. In this paper, two experiments are conducted. In the first, the plausibility of the short term prediction of the solar radiation, based on data collected in the near past on the same site is investigated. In the second experiment, the same prediction is operated using data collected by a public weather station located at ten kilometers from the solar plant. Several prediction techniques belonging from both computational intelligence and statistical fields have been challenged in this task. In particular, Support Vector Machine for Regression, Extreme Learning Machine and Autoregressive models have been used and compared with the persistence and the k-NN predictors. The prediction accuracy achieved in the two experimental conditions are then compared and the results are discussed.     

A new catalyst based on a nickel(II) complex of diiminodiphosphine for hydrogen evolution and oxidation

Based on that hydrogen energy is widely used in fuel cells, we focus our interests on the design and research of new complexes that catalyze the reaction in both directions, such as hydrogen evolution reactions (HERs) and hydrogen oxidation reactions (HORs). A highly efficient catalyst for both hydrogen evolution and oxidation, based on a nickel(II) complex, [Ni-en-P₂](ClO₄)₂, has been designed and provided by the reaction of Ni(ClO₄)₂ with N,N′-bis[o-(diphenylphosphino)benzylidene]ethylenediamine (en-P₂) in our group. Its structure has been determined by X-ray diffraction. [Ni-en-P₂](ClO₄)₂ can electro-catalyze hydrogen evolution both from acetic acid and a neutral buffer (pH 7.0) with a turnover frequency (TOF) of 204 and 1327 mol of hydrogen per mole of catalyst per hour (H₂/mol catalyst/h) under an overpotential (OP) of 914.6 mV and 836.6 mV, respectively. [Ni-en-P₂](ClO₄)₂ also can electro-catalyze hydrogen oxidation with a TOF of 111.7 s⁻¹ under an OP of 330 mV. The results can be attributed to that [Ni^II-en-P₂](ClO₄)₂ has three good reversible redox waves at 1.01 (Ni^III/II), −0.79 (Ni^II/I) and −1.38 V (Ni^I/0) versus Fc^+/0, respectively. We hope these findings can afford a new method for the design of electrocatalysts for both H₂ evolution and H₂ oxidation.     

Effects of anion and cation doping on the thermoelectric properties of n-type PbS

The PbCl_xS_1-x and Pb_1-xBi_xS (x? =?0–0.05) bulks were fabricated with a facile method of hydrothermal synthesis and microwave sintering, and the effect of anionic and cationic donors on the thermoelectric performance of PbS was investigated. Although Cl^? and Bi³⁺ both effectively improved the thermoelectric properties of n-type PbS, more excellent thermoelectric performance was obtained from Cl^? doped samples because of higher electrical property and lower thermal conductivity at higher temperature (T? >?600?K). The thermoelectric figure of merit (ZT) reaches 1.04 for PbCl_0.015S_0.985 at 800?K and increases with temperature increasing without sign of saturation, which is probably the highest value ever reported for single-phase polycrystalline n-type PbS. The results also indicate that the hydrothermal synthesis and microwave sintering can realize anion doping as well as cation doping for n-type PbS at low cost, and PbS should be a robust alternative for PbTe thermoelectric materials.     

Technical and economic analysis of solvent-based lithium-ion electrode drying with water and NMP

Processing lithium-ion battery (LIB) electrode dispersions with water as the solvent during primary drying offers many advantages over N-methylpyrrolidone (NMP). An in-depth analysis of the comparative drying costs of LIB electrodes is discussed for both NMP- and water-based dispersion processing in terms of battery pack $/kWh. Electrode coating manufacturing and capital equipment cost savings are compared for water vs. conventional NMP organic solvent processing. A major finding of this work is that the total electrode manufacturing costs, whether water- or NMP-based, contribute about 8–9% of the total pack cost. However, it was found that up to a 2?×?reduction in electrode processing (drying and solvent recovery) cost can be expected along with a $3–6?M savings in associated plant capital equipment (for a plant producing 100,000 10-kWh Plug-in Hybrid Electric Vehicle (PHEV) batteries) using water as the electrode solvent. This paper shows a different perspective in that the most important benefits of aqueous electrode processing actually revolve around capital equipment savings and environmental stewardship and not processing cost savings.     

Thermal Bending Analysis of Doubly Curved Composite Laminated Shell Panels with General Boundary Conditions and Laminations

Thermal bending analysis of doubly curved laminated shell panels with general boundary conditions and laminations is presented. The equations of equilibrium are derived in the form of two coupled sets of ordinary differential equations based on a general shell theory and solved through the state-space approach in a repeated manner. It is depicted that the results of the present method are in great agreement with analytical solutions. Cylindrical shell panels with general boundary conditions and laminations, where no analytical solution is available, are solved. It is found that the present method exhibits a high convergence rate as well as presenting accurate results in all cases.     

基于深度学习的人体姿态估计方法综述

基于深度学习的人体姿态估计方法旨在通过构建合适的神经网络，直接从二维的图像特征中回归出人体姿态信息。主要按照2D人体姿态估计到3D人体姿态估计的顺序，并从单人检测与多人检测、稀疏的关节点检测与密集的模型构建等方面，对近年来基于深度学习的人体姿态估计方法进行系统介绍，从而初步了解如何通过深度学习的方法得到人体姿态的各个要素，包括肢体部件的相对朝向和比例尺度、骨骼关节点的位置坐标和连接关系，甚至更为复杂的人体蒙皮模型信息。最后,对当前研究面临的挑战以及未来的热点动向进行概述，清晰地呈现出该领域的发展脉络。