化解实体

“化解实体”的目的是把“实体”作为对立面,在化解它的过程中,讨论传统意识中的一种建筑的存在方式一种微与小的状态。“微”与“小”并不指体量,而是指建筑的态度．这个态度源自建筑的目的：“不安四壁怕遮山“。这个目的是一种愉悦的外求,而不是痛苦的自我救赎。     

Models for automated storage and retrieval systems: a literature review

Automated Storage and Retrieval Systems (AS/RS) are warehousing systems that use mechanised devices to accomplish the repetitive tasks of storing and retrieving parts in racks. Since these systems represent a significant investment and considerable operating costs, their use must be as efficient as possible. AS/RS performance is the result of the interaction of many complex and stochastic subsystems. This reality creates a need for robust and efficient evaluation models. This article complements previous surveys on AS/RS by focusing on the particular research question addressed by each work and the associated assumptions used for the various models designed for evaluating AS/RS. Dynamic models based on simulation dominate the most recent literature; however, static approaches based on travel-time modelling have strongly contributed to the study of AS/RS. This review includes dynamic – simulation-based – models, but considers also steady-state (travel-time-based) models. We believe that this review may be of great help to researchers and industrial users in their search for the best modelling approach for a specific problem.     

Analytical model linking growth restriction to solute interaction in model Al based ternary systems

Abstract

An analytical model is constructed to determine the effect of solute–solute interactions on the growth restriction parameter Q. Relevant to analysing the as cast grain size in alloys inoculated with potent nuclei, the value of Q describes the effect of solute partitioning on the growth rates of solid in the liquid. The model is constructed for highly simplified aluminium based ternary systems with two solutes of identical partitioning behaviour. The regular solution coefficient between the two solutes is varied, and its effect on Q is determined. The sign of the change of Q is dependent on the partition coefficient of the solutes: four distinct regimes are found, for k<½, ½<K<1, 1<k<2, and k>2.     

A literature review on selective maintenance for multi‐unit systems

Selective maintenance is regarded as a type of profit‐generating maintenance policy, playing an important role in balancing limited maintenance resources with system performance. Since 1988, increasing interest has been focused on this research area. Nevertheless, to the best of our knowledge, there is a lack of critical reviews of selective maintenance. This paper is the first systematic review focusing on this relevant topic. In this work, a definition and some specific features of selective maintenance are elaborated. Based on these features, a set of criteria that have been considered in selective maintenance optimization are summarized into 3 categories: system characteristics, maintenance characteristics, and mission profile characteristics. Based on these criteria, a comprehensive literature review on selective maintenance is undertaken. The solution approaches, as well as a general procedure for selective maintenance optimization, are discussed. Finally, some possible directions for further research are provided.     

Adversarial Active Learning for Named Entity Recognition in Cybersecurity

Owing to the continuous barrage of cyber threats, there is a massive amount of cyber threat intelligence. However, a great deal of cyber threat intelligence come from textual sources. For analysis of cyber threat intelligence, many security analysts rely on cumbersome and time-consuming manual efforts. Cybersecurity knowledge graph plays a significant role in automatics analysis of cyber threat intelligence. As the foundation for constructing cybersecurity knowledge graph, named entity recognition (NER) is required for identifying critical threat-related elements from textual cyber threat intelligence. Recently, deep neural network-based models have attained very good results in NER. However, the performance of these models relies heavily on the amount of labeled data. Since labeled data in cybersecurity is scarce, in this paper, we propose an adversarial active learning framework to effectively select the informative samples for further annotation. In addition, leveraging the long short-term memory (LSTM) network and the bidirectional LSTM (BiLSTM) network, we propose a novel NER model by introducing a dynamic attention mechanism into the BiLSTM-LSTM encoderdecoder. With the selected informative samples annotated, the proposed NER model is retrained. As a result, the performance of the NER model is incrementally enhanced with low labeling cost. Experimental results show the effectiveness of the proposed method.     

Dynamic quality and pricing decisions in customer-intensive service systems with online reviews

In this paper, we investigate dynamic quality and pricing decisions for customer-intensive service systems with online reviews. We construct a dynamic programming model to determine the optimal quality and pricing strategies. We find that with online reviews, the supplier is forced to provide a higher quality at a higher price for fewer customers, especially when the customer intensity is high. Interestingly, although online reviews deliver quality information for later consumers, the provided quality may decrease over time. Next, we compare the optimal strategies with those of models of either quality flexibility or pricing flexibility, respectively, to examine the merits of our developed model of both quality and pricing flexibilities. The comparison results demonstrate that our model can achieve higher profits, and the advantages of our model increase with the number of periods. In addition, quality (pricing) flexibility is more valuable when consumers are more sensitive to service price (quality). Furthermore, we compare our formulated model with the model for a regular service system, and we illustrate that the optimal quality and pricing strategies in our system are quite different from those of the regular service system.     

Bradford distribution and core authors in classification systems literature

By applying of Bradford's law to analysis of the source documents and their references by classification systems researchers in the world, this paper presents core authors of the field during the period 1981–1990. The findings show that 1) core authors of the international classification systems literature are the Library of Congress, M. Dewey, S. Ranganathan, J. Comaromi, A. Neelameghan, L. Chan and K. Markey; 2) the highly cited authors are linked either to the developers of the classification systems or to a research center, or else they authored the most frequently cited books; and 3) the data confirms to Bradford's law and the unusual rising tail of Bradford distribution is appeared and explained.     

A literature survey on planning and control of warehousing systems

We present a literature survey on methods and techniques for the planning and control of warehousing systems. Planning refers to management decisions that affect the intermediate term (one or multiple months), such as inventory management and storage location assignment. Control refers to the operational decisions that affect the short term (hours, day), such as routing, sequencing, scheduling and order-batching. Prior to the literature survey, we give an introduction into warehousing systems and a classification of warehouse management problems     

Seismic margin reviews of nuclear power plants: Identification of important functions and systems

A study of the results of several seismic PRAs was performed to develop a screening approach for the assessment of the seismic margin of nuclear power plants. This screening approach combines both systems insights and fragility information to simplify the margin review process. The purpose of this paper is to present the basis and method used for the development of the systems screening portion of the seismic margin review methodology.     

A Knowledge-Enriched and Span-Based Network for Joint Entity and Relation Extraction

The joint extraction of entities and their relations from certain texts plays a significant role in most natural language processes. For entity and relation extraction in a specific domain, we propose a hybrid neural framework consisting of two parts: a span-based model and a graph-based model. The span-based model can tackle overlapping problems compared with BILOU methods, whereas the graph-based model treats relation prediction as graph classification. Our main contribution is to incorporate external lexical and syntactic knowledge of a specific domain, such as domain dictionaries and dependency structures from texts, into end-to-end neural models. We conducted extensive experiments on a Chinese military entity and relation extraction corpus. The results show that the proposed framework outperforms the baselines with better performance in terms of entity and relation prediction. The proposed method provides insight into problems with the joint extraction of entities and their relations.     

苯乙烯交联有机无机硅复合涂层的制备与性能研究

本文采用含有C=C双键的烷氧基硅（KH-570）和正硅酸乙酯（TEOS）的共同水解,在SiO2 无机网络结构中引入了不饱和键,并在引发剂存在下与苯乙烯交联形成一种键合型有机无机复合溶胶.键合后KH-570的C=C红外特征吸收峰完全消失,同时,材料的力学性能有显著提高.结果表明,苯乙烯的含量在相当大的变动范围内,均可在金属表面形成高硬度、具有良好附着力的透明薄膜.     

In search of better science: on the epistemic costs of systematic reviews and the need for a pluralistic stance to literature search

Scientometrics - This paper&nbsp;reviews the current status of academic search engines and emerging trends in scientific information retrieval and argues for two key claims. First, since...     

Microemulsions as transdermal drug delivery systems for nonsteroidal anti-inflammatory drugs (NSAIDs): a literature review

Abstract

Pain is a global crisis and significant efforts have gone into the development of drugs that can be used to treat pain. Nonsteroidal anti-inflammatory drugs (NSAIDs) are a class of analgesics that act to selectively relieve pain and inflammation without significantly altering consciousness. Although there have been many advancements with NSAIDs drug development; these drugs still present with severe adverse effects and toxicities, which often limits their use in many patients. Moreover, others are inadequate in relieving specific types of pain such as localized or nerve pain because of poor systemic absorption with conventional delivery systems. The topical route of drug delivery has been used to avoid many of these effects, but not without challenges of its own. The skin acts as an impermeable barrier to most polar drug candidate and absorption across the dermal membranes is often too slow and incomplete to produce meaningful therapeutic benefit. Nevertheless, the use of microemulsions as topical delivery systems for small molecule drug candidates like NSAIDs has been posited as a solution to this problem for years. This review focuses on the recent use of microemulsions as a probable solution to the challenges of transdermal drug delivery of NSAIDs and how microemulsions may be used to enhance the development of more effective but safer analgesic drug products for patients.