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The structure of wool fibre is a key point in clarifying its properties and performances. Wool fibre can be separated into cuticle cells, cortical cells and even macrofibrils using formic acid as the medium by ultrasonication. The disintegration process of wool fibre is significantly subjected to many parameters. In order to obtain the maximum ratio of disintegration of wool fibre, the effect of these parameters on the disintegration process is studied. The separated wool fibre components are examined with a scanning electron microscopy and the disintegration rates are calculated from the weight proportion of residual and original wool fibres. The results indicate that wool fibre can be separated into cortical cells and macrofibrils by ultrasonication in formic acid. The broken ratio of wool fibre varies greatly with different conditions of ultrasonic irradiation, such as irradiation time, temperature, output power of a transducer, shape of vessel, position of probe, ratio of wool fibre to formic acid, and state of wool fibre. Additionally, ultrasonic irradiation is an efficient method for the preparation of intact cortical cells with high yield from wool fibre in appropriate conditions.

In this paper, an emerging state-of-the-art machine intelligence technique called the Hierarchical Temporal Memory (HTM) is applied to the task of short-term load forecasting (STLF). A HTM Spatial Pooler (HTM-SP) stage is used to continually form sparse distributed representations (SDRs) from a univariate load time series data, a temporal aggregator is used to transform the SDRs into a sequential bivariate representation space and an overlap classifier makes temporal classifications from the bivariate SDRs through time. The comparative performance of HTM on several daily electrical load time series data including the Eunite competition dataset and the Polish power system dataset from 2002 to 2004 are presented. The robustness performance of HTM is also further validated using hourly load data from three more recent electricity markets. The results obtained from experimenting with the Eunite and Polish dataset indicated that HTM will perform better than the existing techniques reported in the literature. In general, the robustness test also shows that the error distribution performance of the proposed HTM technique is positively skewed for most of the years considered and with kurtosis values mostly lower than a base value of 3 indicating a reasonable level of outlier rejections.

Wool fibres consist of micro to nano scale protein constituents that could be used for innovative applications. While techniques for extracting these constituents or making wool fibres into organic powders have been developed, effectively dispersing the particles and accurately determining their size has been difficult in practice. In this study, an ultrasonic method was employed to disperse cortical cells extracted from wool fibres into an immersion oil or ethanol. Specimens of the cortical cells were then observed under optical microscopy and scanning electron microscopy, respectively. Cell length and maximum cell diameter were measured to quantify the cell size. The results suggest significant discrepancies exist in the cortical cell size obtained from the two different measurement techniques. The maximum diameter of wool cortical cells obtained from the optical microscope was much larger than that from the scanning electron microscope, while the length was much shorter. A correction factor is given so that cortical cell size obtained from the two measurement techniques can be compared.

A technique in which the features of retinal receptors, receptive fields of the peripheral cells and cortical retinotopic mapping can be combined to perform a template matching system requiring a single reference pattern has been devised for artificial vision algorithms.

Using results explained in previous papers, we show how specific properties of great cortical cells give rise to electro‐encephalographic events. Analogies between EEG rhythms and spontaneous retinal rhythms are considered. The regulations shaping the various EEG waves are described.

This paper aims to investigate the effects of the pia matter on cerebral cortical folding.

A three-layer buckling simulation model composited by the white matter, gray matter and the pia matter is adopted to analyze the effect of the pia matter on cortical folding. The volume growth of brain tissues is simulated using thermal expansion. The effects of the pia matter growth rate, thickness and stiffness on cortical folding is investigated.

The simulation results show that all of these three aforementioned factors of pia matter have obvious effects on cerebral cortical folding. Especially, the thickening of the pia matter may lead to cortical folding malformation such as polymicrogyria, which is in good agreement with the recent reported anatomical findings.

The three-layer model in this paper composited by the white matter, gray matter and the pia matter is different from the usually used two-layer model only composited by the white matter and gray matter. This three-layer model has successfully validated the effect of the pia matter on cerebral cortical folding. The simulation results can explain the anatomical findings very well.

We complete our general parametric description of the working of any neuron by furnishing a simple model of the synaptic transmission and a general formula for post‐synaptic integration. We discuss the influence of some synaptic parameters upon the logical functions performed by the neuron. The same ionic and molecular phenomena explain the pre‐synaptic inhibition and the ability to “gestallt” synthesizing huge cortical cells.

Models describe complex systems or events in simple terms. A better understanding is achieved by replacing intricate and complex systems with simpler and more familiar analogies. This paper deals with the complex visual system. The bibliographical survey given in this paper aims at showing the analogies adopted by authoritative workers in order to obtain a better understanding of “how and what we see”.

The purpose of this paper is to investigate technologies improving image quality and understanding in life‐science microscopy.

The new technique of high‐content analysis is described, along with the equipment available from various manufacturers. Advances in fluorescence imaging and confocal microscopy are then addressed. The paper concludes by reporting a powerful 3D visualisation package, and equipment for networked viewing of high‐resolution microscopy images.

High‐content analysis has developed rapidly in the last four or five years, due largely to improvements in the software interface. Automation and powerful software acquire and manage vast quantities of data, allowing scientists experiment afresh on archived images. Improvements in laser scanning techniques and the emergence of microLED arrays assist microscopy imaging of live cells, whilst techniques giving high‐spectral discrimination improve image understanding.

The paper describes how image‐processing technologies are assisting the work of cell biologists. Stresses the importance of software and hardware design to user uptake, which is relevant for all engineers.