菌酶协同改善花生粕的饲用品质

花生粕是重要的蛋白饲料原料，但由于其氨基酸不平衡，特别是精氨酸与赖氨酸比例严重失衡（精氨酸与赖氨酸含量比值在3~4，理想的精氨酸与赖氨酸含量比值为1.0），限制了其在动物养殖中的应用。研究了复合酶预处理结合乳酸菌发酵花生粕对其品质的改善。结果表明：经菌酶协同处理后，花生粕粗蛋白质含量由46.4%提高至506%，大分子蛋白明显降解为小分子蛋白，酸溶蛋白质含量由2.3%提高至17.8%，多肽含量由1.6%提高至15.7%，蛋氨酸和赖氨酸含量分别提高了77.1%和42.0%，精氨酸降解率为18.7%，精氨酸与赖氨酸含量比值从3.7降低至2.1，总酸含量由06%提高到4.7%，其中乳酸含量由0.64 mg/g提高至14.63 mg/g。菌酶协同处理后的花生粕抗氧化性明显增强，其中每克菌酶协同处理后的花生粕对羟自由基的清除能力与171.6 mg VC相当，比花生粕（与47.6 mg VC相当）提高了2.6倍。     

A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network

Identification of feasible region of operations in multivariate processes is a problem of interest in several fields. This is particularly challenging when the process model is black-box in nature and/or is computationally expensive, as analytical solutions are not available and the number of possible model evaluations is limited. An efficient methodology is required to identify samples where the model is evaluated for developing a computationally efficient surrogate model. In this work, an artificial neural network based surrogate model is proposed which is integrated with a statistical-based approach (Jack-knifing) to estimate the variance of the surrogate model prediction. This allows implementation of an adaptive sampling approach where new samples are identified close to the feasible region boundary or in regions of high prediction uncertainty. The proposed approach performs better than a previously published kriging based method for different dimensionality case studies.     

Design and fabrication of lutetium aluminum silicate glass and nanostructured glass for radiation detection

Flexible scintillating fiber plays an important role in X-ray radiation monitoring and high-resolution medical imaging, while construction of scintillating fiber derived from the commercial material system meet with limited success. Here, we report the design and successful fabrication of the Ce-activated lutetium aluminum silicate glass, nanostructured glass, and fiber, and explore their scintillating properties. The scintillating glass with optimized composition and optical properties is determined. The crystallization behavior of lutetium aluminum silicate glass is studied and the nanostructured glass embedded with orthorhombic Lu₂Si₂O₇ phase is successfully constructed for the first time. Importantly, the crystalline layer thickness of the nanostructured glass can be finely tuned and ~172.89% enhancement in the scintillating performance can be achieved. Furthermore, the fiber with large sized core is fabricated and its radiation response properties are tested. The results show that it exhibits high sensitivity and its scintillating emission is lineally dependent on the X-ray power, indicating the potential application for radiation detection.     

人工智能赋能在线实验教学行为分析

教学行为分析作是教学质量分析的重要组成部分，也是教学引导与反馈机制的重要依据。文章阐述了人工智能（AI）的含义及发展历程，重点分析总结了教学行为分析方法及AI在教学行为分析上的应用。文章以东南大学电工电子在线实验为研究平台，探索分析了AI技术在实验教学行为分析上的可行性，梳理了基于专家系统的在线实验分析系统的设计思路，充分探讨了“智能”教育在实验教学中的深刻内涵。     

Understanding the asymmetric perceptions of smartphone security from security feature perspective: A comparative study

Smartphones are being used and relied on by people more than ever before. The open connectivity brings with it great convenience and leads to a variety of risks that cannot be overlooked. Smartphone vendors, security policy designers, and security application providers have put a variety of practical efforts to secure smartphones, and researchers have conducted extensive research on threat sources, security techniques, and user security behaviors. Regrettably, smartphone users do not pay enough attention to mobile security, making many efforts futile. This study identifies this gap between technology affordance and user requirements, and attempts to investigate the asymmetric perceptions toward security features between developers and users, between users and users, as well as between different security features. These asymmetric perceptions include perceptions of quality, perceptions of importance, and perceptions of satisfaction. After scoping the range of smartphone security features, this study conducts an improved Kano-based method and exhaustively analyzes the 245 collected samples using correspondence analysis and importance satisfaction analysis. The 14 security features of the smartphone are divided into four Kano quality types and the perceived quality differences between developers and users are compared. Correspondence analysis is utilized to capture the relationship between the perceived importance of security features across different groups of respondents, and results of importance-satisfaction analysis provide the basis for the developmental path and resource reallocation strategy of security features. This article offers new insights for researchers as well as practitioners of smartphone security.     

Suppressed Lattice Disorder for Large Emission Enhancement and Structural Robustness in Hybrid Lead Iodide Perovskite Discovered by High-Pressure Isotope Effect

The soft nature of organic–inorganic halide perovskites renders their lattice particularly tunable to external stimuli such as pressure, undoubtedly offering an effective way to modify their structure for extraordinary optoelectronic properties. Here, using the methylammonium lead iodide as a representative exploratory platform, it is observed that the pressure-driven lattice disorder can be significantly suppressed via hydrogen isotope effect, which is crucial for better optical and mechanical properties previously unattainable. By a comprehensive in situ neutron/synchrotron-based analysis and optical characterizations, a remarkable photoluminescence (PL) enhancement by threefold is convinced in deuterated CD₃ND₃PbI₃, which also shows much greater structural robustness with retainable PL after high peak-pressure compression–decompression cycle. With the first-principles calculations, an atomic level understanding of the strong correlation among the organic sublattice and lead iodide octahedral framework and structural photonics is proposed, where the less dynamic CD₃ND₃⁺ cations are vital to maintain the long-range crystalline order through steric and Coulombic interactions. These results also show that CD₃ND₃PbI₃-based solar cell has comparable photovoltaic performance as CH₃NH₃PbI₃-based device but exhibits considerably slower degradation behavior, thus representing a paradigm by suggesting isotope-functionalized perovskite materials for better materials-by-design and more stable photovoltaic application.     

Solvothermal synthesis of zirconia nanomaterials: Latest developments and future

Due to excellent mechanical properties, thermal stability and catalytic characteristics, zirconia is considered as the most important ceramic materials. Different crystal forms make zirconia play a huge role in solid electrolyte fuel cells, catalysts, thermal barrier coatings, denture materials, mobile phone backplanes, etc. The purpose of this paper is to provide a comprehensive review about solvothermal synthesis of nano-zirconia. Firstly, the reactors and systems of solvothermal synthesis in recent years are introduced. Especially, the advancement of continuously flowing microreactors and field-coupled systems are analyzed. Secondly, influencing factors of zirconia solvothermal synthesis are discussed. In addition, solvent effects on the synthesis of nano-zirconia products are clarified, and suggestions for solvent selection are given. Furthermore, the design and mechanism of solvothermal synthesis of zero-, one-, two-and three-dimensional zirconia nanostructures are revealed. Simultaneously, experimental methods and kinetic studies are summarized. Finally, potential applications and challenges are presented for future research directions.     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.