A Highly Sensitive,Reversible, and Bidirectional Humidity Actuator by Calcium Carbonate Ionic Oligomers Incorporated Poly(Vinylidene Fluoride)

Sensitivity and multi-directional motivation are major two factors for developing optimized humidity-response materials, which are promising for sensing, energy production, etc. Organic functional groups are commonly used as the water sensitive units through hydrogen bond interactions with water molecules in actuators. The multi-coordination ability of inorganic ions implies that the inorganic ionic compounds are potentially superior water sensitive units. However, the particle forms of inorganic ionic compounds produced by classical nucleation limit the number of exposed ions to interact with water. Recent progress on the inorganic ionic oligomers has broken through the limitation of classical nucleation, and realized the molecular-scaled incorporation of inorganic ionic compounds into an organic matrix. Here, the incorporation of hydrophilic calcium carbonate ionic oligomers into hydrophobic poly(vinylidene fluoride) (PVDF) is demonstrated. The ultra-small calcium carbonate oligomers within a PVDF film endow it with an ultra-sensitive, reversible, and bidirectional response. The motivation ability is superior to other bidirectional humidity-actuators at present, which realizes self-motivation on an ice surface, converting the chemical potential energy of the humidity gradient from ice to kinetic energy.     

使能未来工厂的5G能力综述

5G系统将移动通信服务从移动电话、移动宽带和大规模机器通信扩展到新的应用领域，即所谓对通信服务有特殊要求的垂直领域。对使能未来工厂的5G能力进行了全面的分析总结，包括弹性网络架构、灵活频谱、超可靠低时延通信、时间敏感网络、安全和定位，而弹性网络架构又包括对网络切片、非公共网络、5G局域网和边缘计算的支持。希望从广度到深度，对相关的理论及技术应用做透彻、全面的梳理，对其挑战做清晰的总结，从而为相关研究和工程技术人员提供借鉴。     

优化GD-模糊规则的滑坡预报模型研究

为了提高滑坡灾害预报准确率，改善传统的滑坡监测和预报中存在的参数选取困难及模糊控制系统作为预报模型精确度不高的问题，首先采用山体结构稳定性分析法进行滑坡灾害参数的选取，得出降雨量、含水率、土压力及岩土表面位移增量作为预报参数的结论；其次将选取的参数作为模糊系统的输入，建立滑坡灾害发生概率模型，并引入优化的GD算法修正预报模型中的动态参数，使模糊控制模型具有自适应性；同时与未优化的模糊控制模型以及单独模糊控制模型进行仿真对比，仿真结果表明，该控制算法收敛速度快，具有很好的收敛性；最后将该模型在某滑坡重点灾区实验区进行实验测试，实验结果显示该模型具有较好的收敛性，且预报精度达到90%。     

Critical state model for structured soil

Structure is an evident determinant for macroscopic behaviors of soils. However, this is not taken into account in most constitutive models, as structure is a rather complex issue in models. For this, it is important to develop and implement simple models that can reflect this important aspect of soil behavior. This paper tried to model structured soils based on well-established concepts, such as critical state and sub-loading. Critical state is the core of the classic Cam Clay model. The sub-loading concept implies adoption of an inner (sub-loading) yield surface, according to specific hardening rules for some internal strain-like state variables. Nakai and co-workers proposed such internal variables for controlling density (ρ) and structure (ω), using a modified stress space, called t_ij. Herein, similar variables are used in the context of the better-known invariants (p and q) of the Cam Clay model. This change requires explicit adoption of a non-associated flow rule for the sub-loading surface. This is accomplished by modifying the dilatancy ratio of the Cam Clay model, as a function of the new internal variables. These modifications are described and implemented under three-dimensional (3D) conditions. The model is then applied to simulating laboratory tests under different stress paths and the results are compared to experiments reported for different types of structured soils. The good agreements show the capacity and potential of the proposed model.     

Signature of Meyer-Neldel compensation rule in iso-conversional crystallization under the influence of γ-ray irradiation

In the current article, the influence of three different doses of gamma-rays on the thermally assisted crystal growth in a novel ternary chalcogenide glassy Se₇₈Te₂₀Sn₂ semiconductor has been reported in terms of the re-crystallization. The iso-conversional kinetic approach is used in the present study. The variation of crystal growth rate with temperature obeys the Arrhenius relation for all the doses of gamma-rays irradiation. Further analysis confirms that pre-factor K₀ of crystal growth rate and the corresponding energy ΔE involved in thermally governed crystallization follows Meyer-Neldel compensation rule (MNCR). Further, we have observed a linear correlation i.e., Further Meyer-Neldel compensation rule (FMNCR) between Meyer-Neldel pre-factor K₀₀ and Meyer-Neldel energy kT₀. The observed correlations between these significant parameters (MNCR between K₀ & ΔE and FMNCR between K₀₀ & kT₀) may open a new gateway for revealing the external effects on crystal growth rate during the iso-conversional analysis of crystallization kinetics.     

Characterization of an acrylic polymer under hygrothermal aging as an optically clear adhesive for touch screen panels

Optically clear adhesives (OCAs) are key components of touch screen panels (TSPs). It is important that OCAs do not affect the transparent electrodes in TSPs because OCAs are contacted to the transparent electrodes. Therefore, N-vinyl caprolactam (NVC) was incorporated in the composition of an acrylic pressure sensitive adhesive (PSA) with excluding an acidic component to maintain the cohesion for OCA preparation. With increasing amounts of NVC, the tack and peel strength of UV-cured PSA increased, but high amounts of NVC led to decreased peel strength. The UV-cured PSA films were placed in a high temperature and humidity chamber for 8 weeks to investigate the durability and corrosion property under hygrothermal conditions. In this study, the corrosion test method using copper foil was suggested as a simple and economical method and was used to evaluate the effect of NVC on the corrosion property of PSA. This method helped identify suitable OCAs that do not have corrosive property. PSA films containing more than 20 wt% of NVC promoted the corrosion of copper foil under hygrothermal aging conditions. The caprolactam ring was opened by moisture, and the PSA structure morphed into a polar structure during the aging process. This change caused a glass transition shift, an increase in the storage modulus at the rubbery plateau, and an increase in peel strength. The surface free energy of the PSA films also increased due to the increase in the polar property. However, high amounts of NVC caused a decrease in the peel strength after 8 weeks of aging because of increased molecular interactions.     

GA-based learning for rule identification in fuzzy neural networks

Employing an effective learning process is a critical topic in designing a fuzzy neural network, especially when expert knowledge is not available. This paper presents a genetic algorithm (GA) based learning approach for a specific type of fuzzy neural network. The proposed learning approach consists of three stages. In the first stage the membership functions of both input and output variables are initialized by determining their centers and widths using a self-organizing algorithm. The second stage employs the proposed GA based learning algorithm to identify the fuzzy rules while the final stage tunes the derived structure and parameters using a back-propagation learning algorithm. The capabilities of the proposed GA-based learning approach are evaluated using a well-examined benchmark example and its effectiveness is analyzed by means of a comparative study with other approaches. The usefulness of the proposed GA-based learning approach is also illustrated in a practical case study where it is used to predict the performance of road traffic control actions. Results from the benchmarking exercise and case study effectively demonstrate the ability of the proposed three stages learning approach to identify relevant fuzzy rules from a training data set with a higher prediction accuracy than alternative approaches.     

A proposed expert system for word sense disambiguation: deductive ambiguity resolution based on data mining and forward chaining

One of the major issues in the process of machine translation is the problem of choosing the proper translation for a multi‐sense word referred to as word sense disambiguation (WSD). Two commonly used approaches to this problem are statistical and example‐based methods. In statistical methods, ambiguity resolution is mostly carried out by making use of some statistics extracted from previously translated documents or dual corpora of source and target languages. Example‐based methods follow a similar approach as they also make use of bilingual corpora. However, they perform the task of matching at run‐time (i.e. online matching). In this paper, by looking at the WSD problem from a different viewpoint, we propose a system, which consists of two main parts. The first part includes a data mining algorithm, which runs offline and extracts some useful knowledge about the co‐occurrences of the words. In this algorithm, each sentence is imagined as a transaction in Market Basket Data Analysis problem, and the words included in a sentence play the role of purchased items. The second part of the system is an expert system whose knowledge base consists of the set of association rules generated by the first part. Moreover, in order to deduce the correct senses of the words, we introduce an efficient algorithm based on forward chaining in order to be used in the inference engine of the proposed expert system. The encouraging performance of the system in terms of precision and recall as well as its efficiency will be analysed and discussed through a set of experiments.