The plasticity of the human perceptual systems in processing auditory- and spatial-frequencies

A common technique in research on visual and auditory perception is to embed stimuli in noise. The traditional assumption is that, when noisy stimuli are repeatedly presented to an observer, each noise component remains equally unpredictable. I challenged that assumption by running two experiments - with visual and auditory stimuli, respectively - under different noise conditions, some of which give the visual (auditory) system the opportunity to learn characteristics of the noise - a form of perceptual learning. The visual stimuli that I used were Gabor patches - spatial patterns that varied sinusoidally in luminance across the image. The visual system is thought to processes spatial patterns through a series of independent channels, each functioning as a band-pass filter centred around a specific spatial-frequency and thus tuned to a sinusoidal pattern of that frequency. The main property to be determined for each selective channel is its width on the spatial-frequency axis. This has been done by using noise masking, i.e. embedding the sinusoid in notched noise - noise from which certain frequency components have been removed - and gradually increasing the width of the notch until no further improvement in threshold is obtained. The auditory stimuli were defined in analogy with the visual ones. My prediction was that the estimates of channel widths derived via noise masking will depend on the way in which the noisy stimuli are presented. My results confirmed that perceptual learning does occur in vision, and to a lesser degree in hearing, thus suggesting that the auditory channels are more "rigid" than those in vision. The sense in which the visual system is deemed to be more "plastic" is discussed in detail. I conclude that context can influence data obtained in notched-noise masking paradigms, and I discuss the possible implications that this might have in other psychophysical investigations

THE PREMISES OF STRATEGIC MARKETING PLANNING IMPLEMENTATION WITHIN SMALL AND MEDIUM SIZED ENTERPRISES

The main purpose of the present paper is to identify the framework and the necessary conditions for the small and medium sized enterprises (SMEs) to be able to adopt the strategic marketing planning. Also, the paper aims to underline the importance of the strategic marketing planning and the manner in which the SMEs can adopt, implement and operationalize the strategic marketing planning instruments, whose correct understanding and usage ensure the capacity to generate competitive advantage, the key element both from the perspective of the fierce competition and the perspective of the future development of the SMEs. Within SMEs the implementation of marketing becomes an evident requirment, mostly due to the relationship that these have with the market, thus, leading towards market orientation of the activities, a new approach developed by the marketing vision on managing the activities from these types of organizations. Regarded upon, from the marketing perspective, the activities from the SMEs, especially the marketing activities, cannot take place randomly. Resource allocation, a characteristic of these types of organizations, and the objectives with regards to superior customer needs satisfaction and economic efficiency maximization, claim thorough plannification and deployment of the activities in a sequence that represents the implementation of a strategy previously assumed. Within this framework, the strategic marketing planning appears as a complex process employing all scientific instruments that comprise segmentation, positioning and marketing mix. Utilizing the strategic marketing planning within SMEs depends to further extend on marketing integration; process directly related with a series of factors such as the nature of the market, development stage, product type, management quality and the influences of the marketing department of the SME. The implications onto the marketing activities from SMEs are reflected upon each strategic marketing planning instrument, where we can find, under correct understanding and application, objectives and market and penetration strategies as product, price, distribution and promotion strategies.marketing, SMEs, segmentation, positioning, marketing mix

ROS-mediated Cytotoxicity and Macrophage Activation Induced by TiO2 Nanoparticles with Different in vitro Non-Cellular Photocatalytic Activities

AIM: The aim of the study described in the present paper was to assess several in vitro effects of TiO2 nanoparticles with different colloidal and photocatalytic properties on RAW 264.7 macrophages.METHODS: The cells were exposed to Degussa P25 titania and two other types of nanoparticles synthesized by a hydrothermal procedure in our laboratory: undoped and Fe3+-doped TiO2. Compared to Degussa P25, the hydrothermal nanomaterials were significantly less active in inducing cytotoxicity, production of intracellular reactive oxygen species (ROS) and release of pro-inflammatory cytokine interleukin-6 (IL-6). The induced effects were analysed with respect to nanoparticle size, surface charge, hydrophilicity, semiconductor bandgap energy and photocatalytic generation of ROS under non-cellular conditions.RESULTS: The overall results indicated that TiO2 nanoparticles with higher surface charge, hydrophilic surfaces and enhanced photocatalytic properties may preferentially induce macrophage cell damage and inflammation compared to other TiO2 nanomaterials.CONCLUSION: The present findings are relevant for studies regarding the evaluation of risks raised by self-cleaning technologies involving nanosized hydrophilic TiO2 photocatalysts as well as development of synthesis methods optimized for producing biocompatible TiO2 nanomaterials

Walking to Infinity on the Fibonacci Sequence

An interesting open problem in number theory asks whether it is possible to walk to infinity on primes, where each term in the sequence has one more digit than the previous. In this paper, we study its variation where we walk on the Fibonacci sequence. We prove that all walks starting with a Fibonacci number and the following terms are Fibonacci numbers obtained by appending exactly one digit at a time to the right have a length of at most two. In the more general case where we append at most a bounded number of digits each time, we give a formula for the length of the longest walk.Comment: arXiv admin note: substantial text overlap with arXiv:2010.1493

Patch Autocorrelation Features: A translation and rotation invariant approach for image classification.

The autocorrelation is often used in signal processing as a tool for finding repeating patterns in a signal. In image processing, there are various image analysis techniques that use the autocorrelation of an image in a broad range of applications from texture analysis to grain density estimation. This paper provides an extensive review of two recently introduced and related frameworks for image representation based on autocorrelation, namely Patch Autocorrelation Features (PAF) and Translation and Rotation Invariant Patch Autocorrelation Features (TRIPAF). The PAF approach stores a set of features obtained by comparing pairs of patches from an image. More precisely, each feature is the euclidean distance between a particular pair of patches. The proposed approach is successfully evaluated in a series of handwritten digit recognition experiments on the popular MNIST data set. However, the PAF approach has limited applications, because it is not invariant to affine transformations. More recently, the PAF approach was extended to become invariant to image transformations, including (but not limited to) translation and rotation changes. In the TRIPAF framework, several features are extracted from each image patch. Based on these features, a vector of similarity values is computed between each pair of patches. Then, the similarity vectors are clustered together such that the spatial offset between the patches of each pair is roughly the same. Finally, the mean and the standard deviation of each similarity value are computed for each group of similarity vectors. These statistics are concatenated to obtain the TRIPAF feature vector. The TRIPAF vector essentially records information about the repeating patterns within an image at various spatial offsets. After presenting the two approaches, several optical character recognition and texture classification experiments are conducted to evaluate the two approaches. Results are reported on the MNIST (98.93%), the Brodatz (96.51%), and the UIUCTex (98.31%) data sets. Both PAF and TRIPAF are fast to compute and produce compact representations in practice, while reaching accuracy levels similar to other state-of-the-art methods