Classification of antituberculosis herbs for remedial purposes by using fuzzy sets

Using fuzzy set theory, we created a system, that assesses a herb's usefulness for the treatment of tuberculosis, based on ethnobotanical data. We analysed two systems which contain different amount of inputs. The first system contains four inputs, the second one contains six inputs. We used the Takagi-Sugeno-Kanga model. Mamdani model is poor at representation as it needs more fuzzy rules than that of TSK to model a real world system where accuracy is demanded. It has been employed a fuzzy controller, and a fuzzy model, in successfully solving difficult control and modelling problems in practice. It is implemented in the Fuzzy Logic Toolbox in Matlab. The data for inputs are gathered in the database named SOPAT (selection of plants against tuberculosis), which is part of a project coordinated by the Oxford International Biomedical Centre. In this database there could be up to one million plant species. It would be cumbersome to select a remedy from one (or some) of these species looking at the data base one-by-one. By means of the fuzzy set theory this remedy can be chosen very quickly.     

Use of tool sets by chimpanzees for multiple purposes in Moukalaba-Doudou National Park,Gabon

We report our recent findings on the use of tool sets by chimpanzees in Moukalaba-Doudou National Park, Gabon. Direct observations and evidences left by chimpanzees showed that chimpanzees used sticks as pounders, enlargers, and collectors to extract honey from beehives of stingless bees (Meliponula sp.), which may correspond to those previously found in the same site for fishing termites and to those found in Loango National Park, Gabon. However, we observed chimpanzees using a similar set of tools for hunting a medium-sized mammal (possibly mongoose) that hid inside a log. This is the first report of hunting with tools by a chimpanzee population in Central Africa. Chimpanzees may recognize the multiple functions and applicability of tools (extracting honey and driving prey), although it is still a preliminary speculation. Our findings may provide us a new insight on the chimpanzee’s flexibility of tool use and cognitive abilities of complex food gathering.     

Segmentation of electron tomographic data sets using fuzzy set theory principles

In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual segmentation continues to be the preferred method. Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy segmentation algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy segmentation algorithm within the framework presented are encouraging.     

Genomic comparison using data mining techniques based on a possibilistic fuzzy sets model

Current copiousness of genomic information stored in biological databases [Mar Albà, M., Lee, M., Pearl, D., Shepherd, F.M.G., Martin, A.J., Orengo, N., Kellam, C.A., 2001. P. VIDA: a virus database system for the organisation of virus genome open reading frames. Nuleic Acids Res. 133-136] makes ultimately feasible the proposal for an application of knowledge management aimed to discover general rules in subcellular phenomena. The goal of this work is primarily to discover relationships between genes by microarray analysis. The tools exploited come from clustering techniques and are mainly based on Knowledge Discovery in Databases (KDD) concepts [Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., 1996. From data mining to knowledge discovery in databases. AI Magazine 17(3), 37-54]. Starting from a data set, each element can be represented by a characteristic matrix, which sums up all data attributes. In this case data mining is oriented to perform a Pattern Recognition of related sequences, hidden in databases [Hand, D.J., Nicholas, A., 2005. Heard finding groups in gene expression data. J. Biomed. Biotechnol. 215-225]. Following a bottom up approach, the next refinement is to compare retrieved data to gather similar features, by dedicated clustering algorithms [Kaufman, L., Rousseeuw, P.J., 1990. Finding groups in data. An Introduction to Cluster Analysis. John Wiley & Sons, New York; Forman, G., Zhang, B., 2000. Distributed Data clustering can be efficient and exact HP. Laboratories Palo Alto HPL-2000, p. 158], driven by fuzzy logic, allowing us to perceive by intuition a common denominator for various genomic families and to anticipate likely future developments.     

While Boolean sets non-gently rip: A theoretical framework on fuzzy sets for mapping landscape patterns

Boolean logic is frequently applied in order to map landscape patterns. Nonetheless this implies to divide the gradual variability of the earth's surface into a finite number of non-overlapping classes, which are considered exhaustive and mutually exclusive. On the contrary, landscapes are expected to be spatially continuous. Fuzzy membership seems to better fit such an issue, by associating for each entity the degree of membership to a class thus maintaining uncertainty information. In this paper, I will disentangle, from a theoretical point of view, the potential of fuzzy set theory for mapping landscape patterns, particularly focusing on those properties of the fuzzy membership concept which are crucial when aiming at extracting the whole information over a landscape.     

Classification of Chinese herbs based on the cluster analysis of delayed luminescence

Traditional Chinese material medica are an important component of the Chinese pharmacopeia. According to the traditional Chinese medicinal concept, Chinese herbal medicines are classified into different categories based on their therapeutic effects, however, the bioactive principles cannot be solely explained by chemical analysis. The aim of this study is to classify different Chinese herbs based on their therapeutic effects by using delayed luminescence (DL). The DL of 56 Chinese herbs was measured using an ultra‐sensitive luminescence detection system. The different DL parameters were used to classify Chinese herbs according to a hierarchical cluster analysis. The samples were divided into two groups based on their DL kinetic parameters. Interestingly, the DL classification results were quite consistent with classification according to the Chinese medicinal concepts of ‘cold’ and ‘heat’ properties. In this paper, we show for the first time that by using DL technology, it is possible to classify Chinese herbs according to the Chinese medicinal concept and it may even be possible to predict their therapeutic properties. Copyright © 2015 John Wiley & Sons, Ltd.     

The potential of microalgal biomass production for biotechnological purposes using wastewater resources

The utilization of microalgae for wastewater treatment represents an attractive opportunity for wastewater valorization through the use of the produced biomass. Five strains of microalgae were isolated from municipal wastewater and grown in autoclaved and non-autoclaved effluent at 30 °C and 150 μmol photons m^?2 s^?1 to study biomass production, nutrient removal, and the biochemical composition of the biomass. All strains reached high biomass productivity (35.6 to 54.2 mg dry weight L^?1 day^?1) within 4 days of batch culturing. In this period, ammonium-N and phosphate were reduced by more than 60 and 90 %, respectively. The high growth rate (0.57 to 1.06 day^?1) ensured a rapid removal of nutrients and thereby a short retention time. By the fourth day of cultivation, the algal biomass contained 32 % protein, but only 11 % lipids and 18 % carbohydrates. It was found that the biomass was a suitable raw material for biogas production by anaerobic digestion. Biodigestion of obtained biomass was simulated by employing the Aspen HYSYS modeling software, resulting in methane yields comparable to those found in the literature. The elemental analysis of the algal biomass showed very low concentrations of pollutants, demonstrating the potential of use of the digestate from biodigestion as a bio-fertilizer.     

Estimating number of families for an urban fox population by using two public data sets

The number of families in the urban fox population of Sapporo, Japan, was estimated from two sets of data reported by the public to government: records of road-killed foxes (information-A) and records of complaints about foxes (information-B). We assumed that fox populations consist of families that have exclusive home ranges, i.e., territories, during the period between gestation and dispersal. The urban area was then divided into hexagons that correspond to the territories. The locations from the two sets of records during the territorial period were plotted on the map. The number of fox families for which information-A and/or B was reported was estimated by counting the number of hexagons that include the record. The total number of families was estimated by using a double-observation method. We adopted Chapman’s unbiased estimator which is based on the hypergeometric distribution that corresponds to the conditional likelihood. We demonstrated the possibility of estimating the abundance of animals from government data such as road kill and complaints if the animals have territories. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Search of chemical scaffolds for novel antituberculosis agents

A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three techniques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear regression, and shrinkage estimation-ridge regression. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N',N'-tetrakis-(2-pyridylmethyl)-ethylenediamine (TPEN), trifluoperazine, pentamidine, and 2-methyl-4,6-dinitro-phenol (DNOC). They show activity comparable to or superior to ethambutol, used in combination with other drugs for the prevention and treatment of Mycobacterium avium complex and drug-resistant tuberculosis.     

Methods for comparing Salmonella mutagenicity data sets using nonlinear models

A variety of linear and nonlinear mathematical models have been proposed to characterize Salmonella mutagenicity data sets, but no systematic procedure has been suggested for comparing two or more data sets across experiments, laboratories, occasions, mutagens or treatment conditions. In this paper, a general method for data-set comparison is provided. Nonlinear regression techniques are applied to real data sets. Data-set and parameter equivalence are described in depth. Confidence-band construction for nonlinear models and other graphical techniques are presented as auxiliary tools. Key Statistical Analysis System (SAS) code programs are provided.     

Classification of finger movements by using the ultra-wide band radar

The coding system of finger movements depends on the differences in the characteristics of the muscles that are responsible for these movements. The ability of ultra-wide band (UWB) radar for use as a tool for identifying the movements of each finger is presented. This will facilitate the ability of the UWB radar in designing a coding system for the movement of fingers of each hand.     

Classification of finger movements by using the ultra-wide band radar

The coding system of finger movements depends on the differences in the characteristics of the muscles that are responsible for these movements. The ability of ultra-wide band (UWB) radar for use as a tool for identifying the movements of each finger is presented. This will facilitate the ability of the UWB radar in designing a coding system for the movement of fingers of each hand.     

Identification of wild and cultivated sunflower for breeding purposes by AFLP markers

Amplified fragment length polymorphisms (AFLPs) represent one of the most powerful polymerase chain reaction (PCR)-based markers which enables one to discriminate single plants by DNA analysis. To date this technique has only been applied in cultivated sunflower to detect genetic diversity among oilseed inbred lines. In this article we report the use of AFLP markers to investigate the level of diversity within and between populations of Helianthus argophyllus collected in the Maputo area, Mozambique, both for taxonomic and breeding purposes. Three primer combinations gave the best results with 92 polymorphic fragments and were able to discriminate these wild endemic populations from H. annuus and from one of its interspecific hybrids. Most of the variation (71%) observed was within population, and the dendrogram based on shared fragments did not divide the H. argophyllus genotypes into distinct groups resembling different populations. Moreover the hybrid genotypes formed distinguishable subgroups with the cultivated sunflower genotype, confirming the suitability of this technique for taxonomic and phylogenetic studies. From a breeding point of view, although the 12 populations of H. argophyllus represent a new valuable genetic resource, only two of them possessed most of the variation observed, suggesting that they can be the most promising material for crossing with cultivated sunflower.