The interactions between catalyzed H(2)O(2) propagations (CHP-i.e. modified Fenton's reagent) and soil organic matter (SOM) during the treatment of contaminated soils and groundwater was studied in a well-characterized surface soil. The fate of two fractions of SOM, particulate organic matter (POM) and nonparticulate organic matter (NPOM), during CHP reactions was evaluated using concentrations...

Benthic diatoms are widely used in Europe and worldwide to access ecological status of running waters. One of key goals of Water Framework Directive is to classify rivers and streams using biological quality elements and type specifi c reference conditions. According to system B which incorporates additional abiotic descriptors, there are 24 water types in Croatia. For biological analyses 92 ri...

Salmon ovary outer membrane (SOM) is a byproduct of the salmon industry; however, the effective utilization of SOM for food materials and supplements is anticipated as the demand for fish and seafood increases worldwide. The purposes of the present study were to assess the chemical composition of SOM, the characteristics of SOM protein (SOMP), and its effects on serum and fecal biochemical para...

A large proportion of the world's carbon is stored as soil organic matter (SOM). However, the mechanisms regulating the stability of this SOM remain unclear. Recent work suggests that SOM may be stabilized by mechanisms other than chemical recalcitrance. Here, we show that the mineralization rate of starch, a plant polymer commonly found in litter and soil, is concentration dependent, such that...

A characteristic feature in the primary visual cortex is that visual responses are suppressed as a stimulus extends beyond the classical receptive field. Here, we examined the role of inhibitory neurons expressing somatostatin (SOM⁺) or parvalbumin (PV⁺) on surround suppression and preferred receptive field size. We recorded multichannel extracellular activity in V1 of transgenic mice expressin...

Self-organizing map SOM neural networks have been widely applied in information sciences. In particular, Su and Zhao proposes in 2009 an SOM-based optimization SOMO algorithm in order to find a wining neuron, through a competitive learning process, that stands for the minimum of an objective function. In this paper, we generalize the SOM-based optimization SOMO algorithm to so-called SOMO-m alg...

The Kohonen Self-Organizing Map (SOM) is an unsupervised learning technique for summarizing high-dimensional data so that similar inputs are, in general, mapped close to each other. When applied to textual data, SOM has been shown to be able to group together related concepts in a data collection. This article presents research in which we sought to validate this property of SOM, called the Pro...

In the present study, we apply the Self Organizing Map (SOM) algorithm for classifying cognitive states from fMRI data without prior selection of spatial or temporal features. In addition, we compare our method with two other models. We applied the method to single-subject as well as multi-subject classification. BOLD signals from subjects viewing emotional pictures of positive, neutral and neg...

This research intends to introduce a new usage of Artificial Intelligent (AI) approaches in Stepping Stone Detection (SSD) fields of research. By using Self-Organizing Map (SOM) approaches as the engine, through the experiment, it is shown that SOM has the capability to detect the number of connection chains that involved in a stepping stones. Realizing that by counting the number of connection...

In this chapter, we discuss the use of Self Organizing Maps (SOM) to deal with various tasks in Document Image Analysis. The SOM is a particular type of artificial neural network that computes, during the learning, an unsupervised clustering of the input data arranging the cluster centers in a lattice. After an overview of the previous applications of unsupervised learning in document image ana...