Experimental Realization of the Fuse Model of Crack Formation

In this work, we present an experimental investigation of the fuse model. Our main goal was to study the influence of the disorder on the fracture process. The experimental apparatus used consisted of an $L\times L$ square lattice with fuses placed on each bond of the lattice. Two types of materials were used as fuses: copper and steel wool wires. The lattice composed only by copper wires varied from a weakly disordered system to a strongly disordered one. The lattice formed only by steel wool wires corresponded to a strongly disordered one. The experimental procedure consisted of applying a potential difference V to the lattice and measuring the respective current I. The characteristic function $I(V)$ obtained was investigated in order to find the scaling law dependence of the voltage and the current on the system size $L$ when the disorder was changed. Our results show that the scaling laws are only verified for the disordered regime.Comment: 4 pages, 8 figures.ep

Green Behaviors in the Laboratory, Environmental Donations in the Field

Behavior within an experiment is generally explained by either a pure profit motive or a response to the context of the experiment which is likely driven by different factors such as individuals\u27 environmental friendliness. Are participants in laboratory experiments responding to the context of the experimental setting and not merely to a profit motive? Using a preliminary analysis, I draw evidence from data collected in a two-stage laboratory experiment designed and conducted by Palm-Forster et al. (In Press) at the University of Delaware. In the first stage of the experiment, participants performed a series of tasks concerning their tradeoffs between monetary profits and environmental friendliness. In the second stage, participants made a choice of donating to a large environmental organization. In total, 156 undergraduate students participated in the experiment. The analysis in this paper provides preliminary results that need to be verified in future research after overcoming key model specification issues

Semantic Similarity in Cheminformatics

Similarity in chemistry has been applied to a variety of problems: to predict biochemical properties of molecules, to disambiguate chemical compound references in natural language, to understand the evolution of metabolic pathways, to predict drug-drug interactions, to predict therapeutic substitution of antibiotics, to estimate whether a compound is harmful, etc. While measures of similarity have been created that make use of the structural properties of the molecules, some ontologies (the Chemical Entities of Biological Interest (ChEBI) being one of the most relevant) capture chemistry knowledge in machine-readable formats and can be used to improve our notions of molecular similarity. Ontologies in the biomedical domain have been extensively used to compare entities of biological interest, a technique known as ontology-based semantic similarity. This has been applied to various biologically relevant entities, such as genes, proteins, diseases, and anatomical structures, as well as in the chemical domain. This chapter introduces the fundamental concepts of ontology-based semantic similarity, its application in cheminformatics, its relevance in previous studies, and future potential. It also discusses the existing challenges in this area, tracing a parallel with other domains, particularly genomics, where this technique has been used more often and for longer

Three interrelated themes in current breast cancer research: gene addiction, phenotypic plasticity, and cancer stem cells

Recent efforts to understand breast cancer biology involve three interrelated themes that are founded on a combination of clinical and experimental observations. The central concept is gene addiction. The clinical dilemma is the escape from gene addiction, which is mediated, in part, by phenotypic plasticity as exemplified by epithelial-to-mesenchymal transition and mesenchymal-to-epithelial transition. Finally, cancer stem cells are now recognized as the basis for minimal residual disease and malignant progression over time. These themes cooperate in breast cancer, as induction of epithelial-to-mesenchymal transition enhances self-renewal and expression of cancer stem cells, which are believed to facilitate tumor resistance

Caracterização de resíduos gerados em análises químicas de tecidos vegetais.

Este trabalho apresenta a caracterização dos resíduos gerados em análises químicas de tecidos vegetais do Laboratório de Análises de Solos e Plantas - LASP da Embrapa Amazônia Ocidental

A metaproteomic analysis of the response of a freshwater microbial community under nutrient enrichment.

Eutrophication can lead to an uncontrollable increase in algal biomass, which has repercussions for the entire microbial and pelagic community. Studies have shown how nutrient enrichment affects microbial species succession, however details regarding the impact on community functionality are rare. Here, we applied a metaproteomic approach to investigate the functional changes to algal and bacterial communities, over time, in oligotrophic and eutrophic conditions, in freshwater microcosms. Samples were taken early during algal and cyanobacterial dominance and later under bacterial dominance. 1048 proteins, from the two treatments and two timepoints, were identified and quantified by their exponentially modified protein abundance index. In oligotrophic conditions, Bacteroidetes express extracellular hydrolases and Ton-B dependent receptors to degrade and transport high molecular weight compounds captured while attached to the phycosphere. Alpha- and Beta-proteobacteria were found to capture different substrates from algal exudate (carbohydrates and amino acids, respectively) suggesting resource partitioning to avoid direct competition. In eutrophic conditions, environmental adaptation proteins from cyanobacteria suggested better resilience compared to algae in a low carbon nutrient enriched environment. This study provides insight into differences in functional microbial processes between oligo- and eutrophic conditions at different timepoints and highlights how primary producers control bacterial resources in freshwater environments

Broad application of a simple and affordable protocol for isolating plant RNA

BACKGROUND: Standard molecular biological methods involve the analysis of gene expression in living organisms under diverse environmental and developmental conditions. One of the most direct approaches to quantify gene expression is the isolation of RNA. Most techniques used to quantify gene expression require the isolation of RNA, usually from a large number of samples. While most published protocols, including those for commercial reagents, are either labour intensive, use hazardous chemicals and/or are costly, a previously published protocol for RNA isolation in Arabidopsis thaliana yields high amounts of good quality RNA in a simple, safe and inexpensive manner. FINDINGS: We have tested this protocol in tomato and wheat leaves, as well as in Arabidopsis leaves, and compared the resulting RNA to that obtained using a commercial phenol-based reagent. Our results demonstrate that this protocol is applicable to other plant species, including monocots, and offers yield and purity at least comparable to those provided by commercial phenol-based reagents. CONCLUSIONS: Here, we show that this previously published RNA isolation protocol can be easily extended to other plant species without further modification. Due to its simplicity and the use of inexpensive reagents, this protocol is accessible and affordable and can be easily implemented to work on different plant species in laboratories worldwide

Diagnóstico rápido participativo (DRP) como método de avaliação do programa de gerenciamento de resíduos laboratoriais (PGRL).

Na Embrapa, o DRP vem sendo utilizado pelo grupo de educação ambiental que adaptou o nome Diagnóstico Rural Participativo para Diagnóstico Rápido Participativo

Exploiting disjointness axioms to improve semantic similarity measures

Motivation: Representing domain knowledge in biology has traditionally been accomplished by creating simple hierarchies of classes with textual annotations. Recently, expressive ontology languages, such as Web Ontology Language, have become more widely adopted, supporting axioms that express logical relationships other than class-subclass, e.g. disjointness. This is improving the coverage and validity of the knowledge contained in biological ontologies. However, current semantic tools still need to adapt to this more expressive information. In this article, we propose a method to integrate disjointness axioms, which are being incorporated in real-world ontologies, such as the Gene Ontology and the chemical entities of biological interest ontology, into semantic similarity, the measure that estimates the closeness in meaning between classes. Results: We present a modification of the measure of shared information content, which extends the base measure to allow the incorporation of disjointness information. To evaluate our approach, we applied it to several randomly selected datasets extracted from the chemical entities of biological interest ontology. In 93.8% of these datasets, our measure performed better than the base measure of shared information content. This supports the idea that semantic similarity is more accurate if it extends beyond the hierarchy of classes of the ontology. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin