Functionalizing Polyester Fiber with a Self-Cleaning Property Using Anatase TiO2 and Low-Temperature Plasma Treatment

Anatase TiO₂ prepared by an aqueous sol–gel process at 60°C was applied to polyester fibers that were treated with low-temperature plasma. This process not only functionalizes polyester but also enhances its adhesion to the anatase. The self-cleaning properties, such as bactericidal activities, colorant decomposition, and degradation of red wine and coffee stains, of the anatase functionalized polyester fibers were studied. The surface morphological changes of polyester fibers before and after plasma treatment, and of plasma-treated fibers before and after anatase coating were characterized by scanning electron microscopy. The adhesion between the anatase TiO₂ and polyester fibers was investigated.     

Strength development of high strength concretes with and without silica fume under the influence of high hydration temperatures

High performance concretes of high compressive strength are finding increasing applications in many fields of construction such as core walls and columns in tall buildings, long-span bridges and marine structures. In thick cross-sections, the high binder contents of some high strength concretes can result in the development of high in-situ temperatures. The combined influence of limited moist curing and high hydration temperatures may significantly influence the progress of hydration. This can affect the long-term development of in-situ strength and other engineering properties. Knowledge of in-situ strength development under these conditions is needed to ensure safe utilisation of this new generation of construction materials.

This paper presents results of an investigation on the strength development of high strength concretes with and without silica fume subjected to high in-situ temperature conditions. A temperature match conditioning (TMC) system was developed and used to simulate the semi-adiabatic temperature development within medium sized high strength concrete columns. The results of this investigation show that in-situ temperatures of up to 70 °C significantly increased the 7-day strength of a high strength silica fume concrete. Although no strength regression was observed up to 1 year, the silica fume concrete subjected to high early temperatures showed significantly lower strengths when compared to concrete cured at standard temperature. For the silica fume concrete subjected to high early temperatures, non-evaporable water contents suggest little additional hydration beyond 3 days.     

HYDRODYNAMICS IN YORK-SCHEIBEL COLUMNS

Dispersed phase hold-up, hold-up profile, drop-size distribution and phase inversion were investigated in a third type of Scheibel column (7.6 cm diameter, 18 stage) with toluene-water as the liquid-liquid system. The concept of characteristic drop velocity was used to describe the relationship between dynamic hold-up and two phase flow rates. The axial dispersed phase hold-up and the mean drop size varied significantly with rotor speed and column height. In addition, the characteristics of phase inversion was explained by Sarkar's model.     

Hypoxia-induced differential apoptosis in the central nervous system of the sturgeon (Acipenser shrenckii)

Hypoxia is a frequent challenge to aquatic vertebrates as compared with that for their terrestrial counterparts. All vertebrates respond to hypoxia in a similar, but not identical manner, indicating that these responses appeared early in the evolution of vertebrates. The aim of this study is to find out the effects of hypoxia on apoptosis in the central nervous system (CNS) of sturgeon, an archaic fish. With the regional specialization of the CNS, we hypothesize that if cell death does occur, the response will vary between regions, i.e., some CNS areas will be more susceptible to hypoxia than the others would. Sturgeons (Acipenser shrenckii) were subjected to hypoxia by exposure to either air or hypoxic water. After 6- or 30-h recovery they were sacrificed and the following regions of the CNS: retina, olfactory lobe, optic tectum, pituitary, cerebellum, pons/medulla, and spinal cord were examined by the terminal transferase mediated dUTP nick end labeling technique and for the cleaved fragment of activated caspase-3 by Western blotting. In hypoxia-treated sturgeons, the retina, optic tectum, pituitary, and spinal cord were found to have significantly more apoptotic cells than did untreated sturgeons at both 6 and 30 h after the hypoxic insults, indicating prolonged damage. Apoptosis was confirmed by Western blotting of the cleaved fragment of activated caspase-3. Olfactory lobe, cerebellum, and pons/medulla had relatively few apoptotic cells. The CNS of sturgeon showed a differential pattern of apoptosis in response to hypoxia.     

Feature Selection for Genomic Signal Processing: Unsupervised,Supervised, and Self-Supervised Scenarios

An effective data mining system lies in the representation of pattern vectors. For many bioinformatic applications, data are represented as vectors of extremely high dimension. This motivates the research on feature selection. In the literature, there are plenty of reports on feature selection methods. In terms of training data types, they are divided into the unsupervised and supervised categories. In terms of selection methods, they fall into filter and wrapper categories. This paper will provide a brief overview on the state-of-the-arts feature selection methods on all these categories. Sample applications of these methods for genomic signal processing will be highlighted. This paper also describes a notion of self-supervision. A special method called vector index adaptive SVM (VIA-SVM) is described for selecting features under the self-supervision scenario. Furthermore, the paper makes use of a more powerful symmetric doubly supervised formulation, for which VIA-SVM is particularly useful. Based on several subcellular localization experiments, and microarray time course experiments, the VIA-SVM algorithm when combined with some filter-type metrics appears to deliver a substantial dimension reduction (one-order of magnitude) with only little degradation on accuracy.     

The impacts of sharing production information on supply chain dynamics: A review of the literature

This paper is a review of research into the impacts of sharing production information on the supply chain dynamics. The purpose of the review is to understand the needs to unravel such impacts on the supply chain design and management, to identify the current research frontier and to study the future trend in this field. The scope of the review is somewhat broad in the sense that more than 100 relevant publications resulting from major research projects and originating from some leading research groups are selected for review. In order to maintain the necessary coherence and consistency, this comprehensive review proposes a loose reference framework to reflect major elements commonly involved in this type of research, including the decision level investigated, supply chain structure, research questions addressed, factors involved, supply chain dynamics measured, modelling methodology adopted, data analysis technique used, and findings and insights from the managerial perspective obtained. The framework serves as a skeleton for categorizing literature and research areas into these key elements. It is hoped that this review is valuable and beneficial both to new researchers entering the field, in order to gain their interest, references and focus, and to experienced researchers, in order, perhaps, to identify new research opportunities and/or issues that intersect these researchers' past and current interests.     

An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.     

A hybrid Hopfield network-genetic algorithm approach to optimal process plan selection

In the automated manufacturing environment, different sets of alternative process plans can normally be generated to manufacture each part. However, this entails considerable complexities in solving the process plan selection problem because each of these process plans demands specification of their individual and varying manufacturing costs and manufacturing resource requirements, such as machines, fixtures/jigs, and cutting tools. In this paper the problem of selecting exactly one representative from a set of alternative process plans for each part is formulated. The purpose is to minimize, for all the parts to be manufactured, the sum of both the costs of the selected process plans and the dissimilarities in their manufacturing resource requirements. The techniques of Hopfield neural network and genetic algorithm are introduced as possible approaches to solve such a problem. In particular, a hybrid Hopfield network-genetic algorithm approach is also proposed in this paper as an effective near-global optimization technique to provide a good quality solution to the process plan selection problem. The effectiveness of the proposed hybrid approach is illustrated by comparing its performance with that of some published approaches and other optimization techniques, by using several examples currently available in the literature, as well as a few randomly generated examples.