Fisheries and fishing effort at the Indigenous Reserves Ashaninka/Kaxinawá, river Breu, Brazil/Peru

This article aimed to describe the subsistence fisheries of traditional populations of three ethnic groups, one Ashaninka and two Kaxinawá, lying on the banks of the River Breu. Initially, monitors were trained to fill logbooks with data from fisheries of the villages during an annual cycle (august/1995 august/1996). Based on these data, it was realized an inventory of the most common fish species caught as well as one about the fishing environment. The following results were obtained: i) Indians prefer to use pools, locally known as "poços", for fishing; ii) the most common caught species are the "mandis" (35%, Pimelodidae), armored catfishes (Loricariidae), specially Hypostomus sp. (25%), the "curimatá" (9%, Prochilodus sp.) and the "saburus" (8%, Curimatidae), among others; iii) the fishing gears that lead to a high rate of fishing are the native "tingui", nets and bow and arrows; iv) fisheries are more intensive during summer; v) the fishing effort and their associated factors statistically significant in predicting the catches in the Indian Reserve were f1 = number of fishermen, f2 = (number of fishermen*total time devoted to fishing), f3 = [(number of fishermen)*(total time devoted to fishing)-(the time displacement)] and the factor villages and fishing gears; vi) although almost all the fisheries are done by walking to the fishing places, catches increase when paddle boats are used; and vii) the most active fishermen belong to Kaxinawá tribe.

Search for the Xb and other hidden-beauty states in the π+π-ϒ{hooked}(1S) channel at ATLAS

This Letter presents a search for a hidden-beauty counterpart of the X(3872) in the mass ranges 10.05--10.31 GeV and 10.40--11.00 GeV, in the channel Xb→π+π−Υ(1S)(→μ+μ−), using 16.2 fb−1 of s√=8 TeV pp collision data collected by the ATLAS detector at the LHC. No evidence for new narrow states is found, and upper limits are set on the product of the Xb cross section and branching fraction, relative to those of the Υ(2S), at the 95% confidence level using the CLS approach. These limits range from 0.8% to 4.0%, depending on mass. For masses above 10.1 GeV, the expected upper limits from this analysis are the most restrictive to date. Searches for production of the Υ(13DJ), Υ(10860), and Υ(11020) states also reveal no significant signals.

Conversive Hidden non-Markovian models

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Stellwagen Bank National Marine Sanctuary final environmental impact statement/management plan / Sanctuaries and Reserves Division.

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Stellwagen Bank National Marine Sanctuary final environmental impact statement/management plan / Sanctuaries and Reserves Division.

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Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

Regional Hidden Harm Action Plan (PDF 2.21MB)

Regional Hidden Harm Action Plan

Uncovering hidden duplicated content in public transcriptomics data.

As part of the development of the database Bgee (a dataBase for Gene Expression Evolution), we annotate and analyse expression data from different types and different sources, notably Affymetrix data from GEO and ArrayExpress, and RNA-Seq data from SRA. During our quality control procedure, we have identified duplicated content in GEO and ArrayExpress, affecting ∼14% of our data: fully or partially duplicated experiments from independent data submissions, Affymetrix chips reused in several experiments, or reused within an experiment. We present here the procedure that we have established to filter such duplicates from Affymetrix data, and our procedure to identify future potential duplicates in RNA-Seq data. Database URL: http://bgee.unil.ch/

The Phlebotominae sand fly (Diptera: Psychodidae) fauna of two Atlantic Rain Forest Reserves in the State of Rio de Janeiro, Brazil

During two consecutive years, studies on the sand fly fauna in Poço das Antas and Fazenda Bom Retiro, two Atlantic Rain Forest Reserves from the State of Rio de Janeiro, were performed using Shannon traps, CDC light traps and human bait collections. Eleven species were identified; Lutzomyia longipalpis, L. migonei, L. edwardsi, L. intermedia, L. whitmani, L. fischeri, L. shannoni, L. ayrozai, L. hirsuta, L. monticola and L. misionensis (first occurrence in the State of Rio de Janeiro). L. intermedia and L. whitmani were the predominant anthropophilic species around houses, while L. hirsuta predominated in the forest.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

PHA/HSCB Hidden Harm Action Plan

This joint PHA/HSCB Hidden Harm Action Plan - Responding to the needs of children born to and living with parental alcohol and drug misuse in Northern Ireland, has been prepared for the DHSSPS in response to the PfA target on Hidden Harm. The plan was approved by DHSSPS in October 2009.

AirBooking. Reserves en línia

Implantació d'un lloc web de reserves de vol en línia. L'anàlisi i el disseny s'han documentat formalment mitjançant UML i la construcció s'ha efectuat sobre la plataforma de desenvolupament JavaEE 5.