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We detail the evolutionary history of the desert woodrat complex (lepida group, genus Neotoma) of western North America. Our analyses include standard multivariate morphometrics of museum specimens coupled with mitochondrial and nuclear DNA sequences and microsatellite loci. We trace the spatial and temporal diversification of this group of desert dwelling rodents, revising species boundaries and delineate subspecies we consider valid.

An artificial macromolecule (foldamer) was designed as a novel nanomaterial with the backbone of phosphodiester and the side chain of functional molecules and nucleobases. The functional molecules tethered on D-threoninol and the nucleosides on D-ribose can be lined up with any sequence and ratio by using standard phosphoramidite chemistry. The nucleobases that form Watson-Crick base pairs provide the sequence recognition which is required for constructing complicate nanostructures. The multiple functional molecules give applicable and advanced functions such as photoresponsiveness when azobenzenes were used. Unexpectedly, a stable double helix was formed even in the case that the ratio of azobenzene molecules and base pairs was as high as 2:1. More interestingly, this artificial duplex showed high sequence specificity: the stability decreased greatly when a mismatched base pair was present. Furthermore, the formation and dissociation of the constructed artificial duplex were reversibly and completely modulated with light irradiation. By using this new nanomaterial, a variety of functional nanostructures and nanodevices are promising to be designed. [ABSTRACT FROM AUTHOR]

The discipline of hematopathology traditionally relies upon morphologic evaluation, cytochemical stains, immunohistochemistry, flow cytometry, and karyotypic analysis to classify hematolymphoid neoplasms. Although these time-honored methods still comprise the primary diagnostic arsenal of the pathologist, the last few decades have borne witness to the widespread acceptance of molecular techniques to classify these neoplasms. No longer considered ancillary, molecular analyses have led to a greater understanding of the biological and clinical heterogeneity of hematolymphoid neoplasms, and now form the primary diagnostic criteria for many diagnoses as set forth by the World Health Organization [1]. They also provide extremely sensitive and specific methods for prognostic marker detection and minimal residual disease monitoring. These techniques have evolved rapidly over the last decade from Southern blot and hybridization assays to polymerase chain reaction and its variants to gene expression profiling and single-nucleotide polymorphism analysis, and more recently to microarray technology and whole-genome analysis. Despite technological advancements, molecular techniques are critically dependent upon the nature of nucleic acids retrieved from the specimen. Results cannot be correctly interpreted if the quantity and/or the integrity of nucleic acids are not optimal for the desired molecular application. As such, the purpose of this chapter is twofold. First, issues pertaining to specimen collection, handling and processing, and nucleic acid extraction, stability, and storage are reviewed. Second, molecular techniques commonly utilized in hematopathology are reviewed. Cytogenetics, fluorescent in situ hybridization (FISH), and microarray techniques are discussed in Chapter 2. [ABSTRACT FROM AUTHOR]

The endemic land snails, genus Mandarina of the Ogasawara Islands, have diversified into arboreal, semi-arboreal and ground ecotypes. Shell morphologies of Mandarina species have a clear relationship with their respective ecotypes. In addition, marked geographical variations in morphology and genes are found within species. Phylogenetic relationships based on mitochondrial DNA (mtDNA) sequences suggests that Mandarina evolved from Euhadra, a genus distributed on the mainland of Japan. The inferred phylogeny suggests that similar morphologies and ecotypes appeared independently and rapidly in different lineages and islands at different times. This rapid evolution produced some incongruities among phylogenetic relationships, morphology, species taxonomy, and the level of reproductive isolation. Interspecific hybridization occurs between sympatric species due to environmental change, resulting in an admixture of genetic and morphological characteristics. These findings reveal the importance of Mandarina as a model system for evolutionary study. However, a predatory land snail and flatworm have recently been introduced into the Ogasawaras. These predators may rapidly cause the extinction of Mandarina, and thus, a conservation program is needed for Mandarina. In the conservation program for Mandarina, species taxonomy should not be used as a criterion for selection of populations for captive breeding because of incongruence among the phylogeny, morphology, ecology, species taxonomy and reproductive isolation. In addition, the danger of interspecific hybridization should be considered when captive-bred snails are reintroduced into restored or secure habitat. Reprinted from Chiba S (2003) Global Environmental Research 7:29–37, with permission of the Association of International Research Initiatives for Environmental Studies. Figure 3 and Figure 7 were modified from the originals [ABSTRACT FROM AUTHOR]

Metaheuristic algorithms have been widely used for solving Combinatorial Optimization Problem (COP) since the last decade. The algorithms can produce amazing results in solving complex real life problems such as scheduling, time tabling, routing and tasks allocation. We believe that many researchers will find COP methods useful to solve problems in many different domains. However, there are some technical hurdles such as the steep learning curve, the abundance and complexity of the algorithms, programming skill requirement and the lack of user friendly platform to be used for algorithm development. As new algorithms are being developed, there are also those that come in the form of hybridization of multiple existing algorithms. We reckon that there is also a need for an easy, flexible and effective development platform for user defined metaheuristic hybridization. In this article, a comparative study has been performed on several metaheuristics software frameworks. The result shows that available software frameworks are not adequately designed to enable users to easily develop hybridization algorithms. At the end of the article, we propose a framework design that will help bridge the gap. We foresee the potential of scripting language as an important element that will help improve existing software framework with regards to the ease of use, rapid algorithm design and development. Thus, our efforts are now directed towards the study and development of a new scripting language suitable for enhancing the capabilities of existing metaheuristic software framework. [ABSTRACT FROM AUTHOR]

Genetic Algorithms have been used from 1989 for both Neural Network training and design. Nevertheless, the use of a Genetic Algorithm for adjusting the Neural Network parameters can still be engaging. This work presents the study and validation of a different approach to this matter by introducing a Genetic Algorithm designed for Neural Network training. This algorithm features a mutation operator capable of working on three levels (network, neuron and layer) and with the mutation parameters encoded and evolving within each individual. We also explore the use of three types of hybridization: post-training, Lamarckian and Baldwinian. These proposes in combination with the algorithm, show for a fast and powerful tool for Neural Network training. [ABSTRACT FROM AUTHOR]

Ornamental ponds are important sites for conserving threatened native fish species (e.g. crucian carp Carassius carassius L.), but pond management plans rarely include considerations of native fishes. We developed and implemented a management plan for a small (0.8 h), ornamental estate pond in Hertfordshire (England) using historical information (aquatic plant and animal surveys) and a 9-year data set on climatic variables and crucian carp body condition. Crucian carp growth was not correlated with climatic variables, but body condition decreased with increasing temperature (in degree-days), which suggests that temperature influences on growth are counter-balanced by environmental factors. Management included the removal of one fish species (to eliminate hybridization with another species) and the introduction of two native species (to re-balance the fish assemblage), a reduction in floating aquatic plants (to reduce shading of the sediments) as well as the use of a chemical agent to compact the pond΄s fine sediments and barley straw to enhance invertebrate habitat and thus fish prey production. [ABSTRACT FROM AUTHOR]

Nanoscale DNA tweezers operated by photo-irradiation were constructed by using azobenzene-modified DNA as materials. The azobenzenes that can photoisomerize between trans and cis form were used as the engines to open and close the tweezers. The work principle is based on the reversible photoregulation of complementary DNA hybridization. When non-substituted azobenzene was used, the tweezers were opened after UV light irradiation (330-350 nm, cis form), and closed after visible light irradiation (440-460 nm, trans form). More interestingly, the operation reversed when an azobenzene derivative with a para-isopropyl group was used: UV light irradiation closed the tweezers and visible light irradiation opened them. As compared with the oligonucleotide-fueled DNA machines, the nanomachines constructed here were ˵environment-friendly″ because no dsDNA waste was produced. Furthermore, the operation can be repeated many times simply by switching the photo-irradiation without any decrease of the cycling efficiency. [ABSTRACT FROM AUTHOR]

Oligonucleotide Microarrays have become powerful tools in genetics, as they serve as parallel scanning mechanisms to detect the presence of genes using test probes. The detection of each gene depends on the multichannel differential expression of perfectly matched segments against mismatched ones. This methodology posse some interesting problems under the point of view of Genomic Signal Processing, as test probes express themselves in rather different patterns, not showing proportional expression levels for most of the segment pairs, as it would be expected. The method proposed in this paper consists in isolating gene expressions showing unexpected behavior using independent component analysis. [ABSTRACT FROM AUTHOR]

Recently population-based meta-heuristics under the cover of swarm intelligence have gained prominence. This includes particle swarm optimization (PSO), where the search strategy draws ideas from the social behavior of organisms. While PSO has been reported as an effective search method in several papers, we are interested in the critical success factors of PSO for solving combinatorial optimization problems. In particular, we examine the application of PSO with different crossover operators and hybridization with variable neighborhood descent as an embedded local search procedure. Computational results are reported for the continuous (nowait) flow-shop scheduling problem. The findings demonstrate the importance of local search as an element of the applied PSO procedures. We report new best solutions for a number of problem instances from the literature. [ABSTRACT FROM AUTHOR]

In this paper we propose and study the behavior of a new hybrid heuristic algorithm for the DNA fragment assembly problem. The DNA fragment assembly is a problem solved in the early phases of the genome project and thus very important, since the other steps depend on its accuracy. This is an NP-hard combinatorial optimization problem which is growing in importance and complexity as more research centers become involved on sequencing new genomes. Our contribution is a hybrid method that combines a promising heuristic, PALS, with a well-know metaheuristic, a genetic algorithm, obtaining as result a very efficient assembler that allows to find optimal solutions for large instances of this problem. [ABSTRACT FROM AUTHOR]

Keep up your bright swords, for the dew will rust them. Water is the most common substance on Earth, and it no doubt has the best known of all chemical formulas: H2O. It is one of only two liquids that occur naturally in appreciable quantities, the other example being petroleum. More than three quarters of the Earth's surface is covered with water, and if it were not for this compound, there would be no life. About 60% of the weight of the human body is water, it being present in the interior of every cell. It also accounts for the bulk of such specialized aqueous media as blood and mucous. The central role played by water was of course clear from the earliest times, and Aristotle regarded it as one of the four elements, together with air, fire and earth. Its chemical structure became clear in the late eighteenth century, when Henry Cavendish and Antoine Lavoisier established that it is a combination of hydrogen (discovered by Cavendish in 1766) and oxygen (discovered by Joseph Priestley in 1774). Cavendish burned measured quantities of these two gases together and found that they produced water, no change in total weight having occurred during the reaction. The reverse process, decomposition of water into hydrogen and oxygen, was first achieved by Lavoisier. In spite of its abundance and apparent simplicity, water is an unusual compound, and compared with other liquids we could call it exotic. [ABSTRACT FROM AUTHOR]

The force of nature could no farther go; to make a third she join'd the former two. Most substances are mixtures of two or more elements, and chemical compounds are found to have definite compositions. They are also found to consist of molecules, which are the smallest particles that can exist in the free state and still retain the characteristics of the substance. Thus the chemical formula for water is always H2O, indicating that its molecules contain two hydrogen atoms and one oxygen. (The subscript 1 is not written explicitly; H2O implies H2O1.) The formula H2O2, in which the relative proportions of hydrogen and oxygen are different from those in water, belongs to a different chemical compound, the common bleaching agent hydrogen peroxide. Similarly, sodium chloride, also known as common salt, has the formula NaCl, and not Na2Cl or NaCl3. This shows that the forces that hold atoms together in groups must have certain characteristics which determine the rules of combination. The occurrence of chemical reactions reveals that the forces can be overcome, allowing the atoms to move apart and establish bonds with other atoms. A simple example of such an event is the reaction Zn + 2HCl → ZnCl2 + H2 in which the addition of hydrochloric acid to zinc produces zinc chloride and hydrogen, which is liberated as a gas. This demonstrates that the binding forces between zinc and chlorine atoms are stronger than those which hold hydrogen to chlorine. [ABSTRACT FROM AUTHOR]

DNA hybridization was used to make a probabilistic computation to identify the optimal path for a fully connected asymmetric 10 city traveling salesman problem. Answer set formation was achieved using a unique DNA 20mer for each edge capable of hybridizing to half of each neighboring vertex. This allowed the vertex 20mers to be linked in all possible combinations to form paths through the network. Hybridization occurred in the presence of an excess of vertex 20mers, while edge 20mers were added in limiting amounts inversely proportional to the weight of each edge, resulting in the paths with the least cumulative weight being the most abundant. Correct answers, 230bp in length, contained a single copy of each vertex and were purified by PAGE and by successive magnetic bead affinity separations with probes for each vertex. Answer detection was accomplished using LCR of probes complementary to each vertex in a manner that identified the sequential order of vertices in each path by identifying vertex pairs. Optimal answer identification was accomplished using a conventional computer by normalizing the abundance of vertex pairings, and was found to be the same as that calculated by in silico. [ABSTRACT FROM AUTHOR]

In order to accurately measure the gene expression levels in microarray experiments, it is crucial to design unique, highly specific and sensitive oligonucleotide probes for the identification of biological agents such as genes in a sample. Unique probes are difficult to obtain for closely related genes such as the known strains of HIV genes. The non-unique probe selection problem is to select a probe set that is able to uniquely identify targets in a biological sample, while containing a minimal number of probes. This is an NP-hard problem. We define a probe selection function that allows to decide which are the best probes to include in or exclude from a candidate probe set. We then propose a new deterministic greedy heuristic that uses the selection for solving the non-unique probe selection problem. Finally, we combine the selection function with an evolutionary method for finding near minimal non-unique probe sets. When used on benchmark data sets, our greedy method outperforms current greedy heuristics for non-unique probe selection in most instances. Our genetic algorithm also produced excellent results when compared to advanced methods introduced in the literature for the non-unique probe selection problem. [ABSTRACT FROM AUTHOR]