Detecting long-range chromatin interactions using the chromosome conformation capture sequencing (4C-seq) method.

Eukaryotic transcription is tightly regulated by transcriptional regulatory elements, even though these elements may be located far away from their target genes. It is now widely recognized that these regulatory elements can be brought in close proximity through the formation of chromatin loops, and that these loops are crucial for transcriptional regulation of their target genes. The chromosome conformation capture (3C) technique presents a snapshot of long-range interactions, by fixing physically interacting elements with formaldehyde, digestion of the DNA, and ligation to obtain a library of unique ligation products. Recently, several large-scale modifications to the 3C technique have been presented. Here, we describe chromosome conformation capture sequencing (4C-seq), a high-throughput version of the 3C technique that combines the 3C-on-chip (4C) protocol with next-generation Illumina sequencing. The method is presented for use in mammalian cell lines, but can be adapted to use in mammalian tissues and any other eukaryotic genome.

Measurement of absolute cell volume, osmotic membrane water permeability, and refractive index of transmembrane water and solute flux by digital holographic microscopy.

ABSTRACT. A dual-wavelength digital holographic microscope to measure absolute volume of living cells is proposed. The optical setup allows us to reconstruct two quantitative phase contrast images at two different wavelengths from a single hologram acquisition. When adding the absorbing dye fast green FCF as a dispersive agent to the extracellular medium, cellular thickness can be univocally determined in the full field of view. In addition to the absolute cell volume, the method can be applied to derive important biophysical parameters of living cells including osmotic membrane water permeability coefficient and the integral intracellular refractive index (RI). Further, the RI of transmembrane flux can be determined giving an indication about the nature of transported solutes. The proposed method is applied to cultured human embryonic kidney cells, Chinese hamster ovary cells, human red blood cells, mouse cortical astrocytes, and neurons.

Uso de regressões logísticas múltiplas para mapeamento digital de solos no Planalto Médio do RS

Regressões nominais logísticas estabelecem relações matemáticas entre variáveis independentes contínuas ou discretas e variáveis dependentes discretas. Essas foram avaliadas quanto ao seu potencial em predizer a ocorrência e distribuição de classes de solos na região dos municípios de Ibirubá e Quinze de Novembro (RS). A partir de modelo numérico de terreno digital (MNT) com 90 m de resolução, foram calculadas variáveis de terreno topográficas (elevação, declividade e curvatura) e hidrográficas (distância dos rios, índice de umidade topográfica, comprimento de fluxo de escoamento e índice de poder de escoamento). Foram então estabelecidas regressões logísticas múltiplas entre as classes de solos da região com base em levantamento tradicional na escala 1:80.000 e as variáveis de terreno. As regressões serviram para calcular a probabilidade de ocorrência de cada classe de solo, e o mapa final de solos estimado foi produzido atribuindo-se a cada célula do mapa a denominação da classe de solo com maior probabilidade de ocorrência. Observou-se acurácia geral (AG) de 58 % e acurácia pelo coeficiente Kappa de Cohen de 38 %, comparando-se o mapa original com o mapa estimado dentro da escala original. Uma simplificação de escala foi pouco significativa para o aumento da acurácia do mapa, sendo 61 % de AG e 39 % de Kappa. Concluiu-se que as regressões logísticas múltiplas apresentaram potencial preditivo para serem usadas como ferramentas no mapeamento supervisionado de solos.

Electron capture and emission by the Ti acceptor level in GaP

Previously reported results on deep level optical spectroscopy, optical absorption, deep level transient spectroscopy, photoluminescence excitation, and time resolved photoluminescence are reviewed and discussed in order to know which are the mechanisms involved in electron capture and emission of the Ti acceptor level in GaP. First, the analysis indicates that the 3T1(F) crystal¿field excited state is not in resonance with the conduction band states. Second, it is shown that both the 3T2 and 3T1(F) excited states do not play any significant role in the process of electron emission and capture.

Majority carrier capture cross section determination in the large deep trap concentration cases

A method to determine the thermal cross section of a deep level from capacitance measurements is reported. The results enable us to explain the nonexponential behavior of the capacitance versus capture time when the trap concentration is not negligible with respect to that of the shallow one, and the Debye tail effects are taken into account. A figure of merit for the nonexponential behavior of the capture process is shown and discussed for different situations of doping and applied bias. We have also considered the influence of the position of the trap level"s energy on the nonexponentiality of the capture transient. The experimental results are given for the gold acceptor level in silicon and for the DX center in Al0.55 Ga0.45As, which are in good agreement with the developed theory.

Analysis of Roman pottery graffiti by high resolution capture and 3D laser profilometry

The graffiti on pottery discovered on the site of Aventicum (Avenches, VD/Switzerland) form the largest corpus of minor inscriptions of the Roman Empire studied until now. Indeed, a total of 1828 graffiti have been found. The reading and the recording of the inscriptions are generally dependent on the state of conservation of the graffito and its support. In numerous cases, only a pale shadow of the inscription is visible, which makes traditional observations, such as visual observations with the naked eye, unsuitable for its decipherment. Consequently, advanced techniques have been applied for enhancing the readability of such inscriptions. In our paper we show the efficiency of 3D laser profilometry as well as high resolution photography as powerful means to decipher illegible engraved inscriptions. The use of such analyses to decipher graffiti on pottery or on other materials enables a better understanding of minor inscriptions and improves the knowledge of the daily life of ancient populations substantially.

Selection methods regulate evolution of cooperation in digital evolution.

A key, yet often neglected, component of digital evolution and evolutionary models is the 'selection method' which assigns fitness (number of offspring) to individuals based on their performance scores (efficiency in performing tasks). Here, we study with formal analysis and numerical experiments the evolution of cooperation under the five most common selection methods (proportionate, rank, truncation-proportionate, truncation-uniform and tournament). We consider related individuals engaging in a Prisoner's Dilemma game where individuals can either cooperate or defect. A cooperator pays a cost, whereas its partner receives a benefit, which affect their performance scores. These performance scores are translated into fitness by one of the five selection methods. We show that cooperation is positively associated with the relatedness between individuals under all selection methods. By contrast, the change in the performance benefit of cooperation affects the populations' average level of cooperation only under the proportionate methods. We also demonstrate that the truncation and tournament methods may introduce negative frequency-dependence and lead to the evolution of polymorphic populations. Using the example of the evolution of cooperation, we show that the choice of selection method, though it is often marginalized, can considerably affect the evolutionary dynamics.

Integração de dados do quickbird e atributos do terreno no mapeamento digital de solos por redes neurais artificiais

No presente estudo, foi realizada uma avaliação de diferentes variáveis ambientais no mapeamento digital de solos em uma região no norte do Estado de Minas Gerais, utilizando redes neurais artificiais (RNA). Os atributos do terreno declividade e índice topográfico combinado (CTI), derivados de um modelo digital de elevação, três bandas do sensor Quickbird e um mapa de litologia foram combinados, e a importância de cada variável para discriminação das unidades de mapeamento foi avaliada. O simulador de redes neurais utilizado foi o "Java Neural Network Simulator", e o algoritmo de aprendizado, o "backpropagation". Para cada conjunto testado, foi selecionada uma RNA para a predição das unidades de mapeamento; os mapas gerados por esses conjuntos foram comparados com um mapa de solos produzido com o método convencional, para determinação da concordância entre as classificações. Essa comparação mostrou que o mapa produzido com o uso de todas as variáveis ambientais (declividade, índice CTI, bandas 1, 2 e 3 do Quickbird e litologia) obteve desempenho superior (67,4 % de concordância) ao dos mapas produzidos pelos demais conjuntos de variáveis. Das variáveis utilizadas, a declividade foi a que contribuiu com maior peso, pois, quando suprimida da análise, os resultados da concordância foram os mais baixos (33,7 %). Os resultados demonstraram que a abordagem utilizada pode contribuir para superar alguns dos problemas do mapeamento de solos no Brasil, especialmente em escalas maiores que 1:25.000, tornando sua execução mais rápida e mais barata, sobretudo se houver disponibilidade de dados de sensores remotos de alta resolução espacial a custos mais baixos e facilidade de obtenção dos atributos do terreno nos sistemas de informação geográfica (SIG).

Decay of unstable states in the presence of colored noise and random initial conditions. II. Analog experiments and digital simulations

The decay of an unstable state under the influence of external colored noise has been studied by means of analog experiments and digital simulations. For both fixed and random initial conditions, the time evolution of the second moment ¿x2(t)¿ of the system variable was determined and then used to evaluate the nonlinear relaxation time. The results obtained are found to be in excellent agreement with the theoretical predictions of the immediately preceding paper [Casademunt, Jiménez-Aquino, and Sancho, Phys. Rev. A 40, 5905 (1989)].

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

Mapeamento digital de solos por redes neurais artificiais com base na relação solo-paisagem

Técnicas de mapeamento digital podem contribuir para agilizar a realização de levantamentos pedológicos detalhados. Objetivou-se com este trabalho obter um mapa digital de solos (MDS) com uso de redes neurais artificiais (RNA), utilizando correlações entre unidades de mapeamento (UM) e covariáveis ambientais. A área utilizada compreendeu aproximadamente 12.000 ha localizados no município de Barra Bonita, SP. A partir do resultado de uma análise de agrupamento das covariáveis ambientais, foram escolhidas cinco áreas de referência para realizar o mapeamento convencional. As UM identificadas subsidiaram a aplicação da técnica de RNA. Utilizaram-se o simulador de redes neurais JavaNNS e o algoritmo de aprendizado backpropagation. Pontos de referência foram coletados para avaliar o desempenho do mapa digital produzido. A posição na paisagem e o material de origem subjacente foram determinantes para o reconhecimento dos delineamentos das UM. Houve boa concordância entre as UM delineadas pelo MDS e pelo método convencional. A comparação entre os pontos de referência e o mapa de solos digital evidenciou exatidão de 72 %. O uso da abordagem MDS utilizada pode contribuir para diminuir a falta de informações semidetalhadas de solos em locais ainda não mapeados, tomando-se como base informações pedológicas obtidas de áreas de referência adjacentes.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

An appropriate data set size for digital soil mapping in Erechim, Rio Grande do Sul, Brazil

Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.