Connectivity patterns inferred from the genetic structure of white seabream (Diplodus sargus L.)

Themarine environment seems, at first sight, to be a homogeneousmediumlacking barriers to species dispersal. Nevertheless, populations of marine species show varying levels of gene flow and population differentiation, so barriers to gene flow can often be detected. Weaimto elucidate the role of oceanographical factors ingenerating connectivity among populations shaping the phylogeographical patterns in the marine realm, which is not only a topic of considerable interest for understanding the evolution ofmarine biodiversity but also formanagement and conservation of marine life. For this proposal,we investigate the genetic structure and connectivity between continental and insular populations ofwhite seabreamin North East Atlantic (NEA) and Mediterranean Sea (MS) aswell as the influence of historical and contemporary factors in this scenario using mitochondrial (cytochrome b) and nuclear (a set of 9 microsatellite) molecular markers. Azores population appeared genetically differentiated in a single cluster using Structure analysis. This result was corroborated by Principal Component Analysis (PCA) and Monmonier algorithm which suggested a boundary to gene flow, isolating this locality. Azorean population also shows the highest significant values of FST and genetic distances for both molecular markers (microsatellites and mtDNA). We suggest that the breakdown of effective genetic exchange between Azores and the others' samples could be explained simultaneously by hydrographic (deep water) and hydrodynamic (isolating current regimes) factors acting as barriers to the free dispersal of white seabream(adults and larvae) and by historical factors which could be favoured for the survival of Azorean white seabream population at the last glaciation. Mediterranean islands show similar genetic diversity to the neighbouring continental samples and nonsignificant genetic differences. Proximity to continental coasts and the current system could promote an optimal larval dispersion among Mediterranean islands (Mallorca and Castellamare) and coasts with high gene flow.

Análise da expressão de APE1 após estresse oxidativo induzido em células proficientes e deficientes na via de reparo por excisão de nucleotídeos.

Riboflavin is a vitamin very important in aerobic organisms, as a precursor of many coenzymes involved in the electron transporter chain. However, after photosensitization of riboflavin with UV or visible light, it generates reactive oxygen species (ROS), which can oxidize the DNA. The repair of oxidative lesions on DNA occurs through the base excision repair pathway (BER), where APE1 endonuclease plays a central role. On the other hand, the nucleotide excision repair pathway (NER) repairs helix-distorting lesions. Recently, it was described the participation of NERproteins in the repair of oxidative damage and in stimulation of repair function fromAPE1. The aim of this research was to evaluate the cytotoxic effects of photosensitized riboflavin (RF*) in cells proficient and deficient in NER, correlating with APE1 expression. For this propose, the cells were treated with RF* and it was performed the cell viability assay, extraction of whole proteins, cells fractionation, immunoblotting, indirect immunofluorescence and analysis of polymorphisms of BER gens. The results evidenced that cells deficient in XPA and CSB proteins were more sensitive to RF*. However, XPC-deficient cells presented similar resistance to MRC5- SV cells, which is proficient in NER. These results indicate that XPA and CSB proteins have an important role on repair of oxidative lesions induced by RF*. Additionally, it was evidenced that single nucleotide polymorphisms (SNPs) in BER enzymes may influence in sensitivity of NER-deficient cell lines. Concerning the APE1 expression, the results showed that expression of this protein after treatment with RF* only changed in XPC-deficient cells. Though, it was observed that APE1 is recruited and is bound to chromatin in MRC5-SV and XPA cells after treatment with RF*. The results also showed the induction of DNA damage after treatment with RF*, through the analysis of-H2AX, since the treatment promoted an increase of endogenous levels of this phosphorylated protein, which acts signaling double strand-break on DNA. On the other hand, in XPC-deficient cells, regardless of resistance of RF*, the endogenous levels of APE1 are extremely reduced when compared with other cell lines and APE1 is not bound to chromatin after treatment with RF*. These results conclude that RF* was able to induce cell death in NERdeficient cells, where XPA and CSB cells were more sensitive when compared with MRC5-SV and XPC-deficient cells. This last result is potentially very interesting, since XPC-deficient cell line presents low levels of APE1. Additionally, the results evidenced that APE1 protein can be involved in the repair of oxidative damage induced by RF*, because APE1 is recruited and bound strongly to chromatin after treatment.

Enhancement to the Mortgage Licensing Process

The Consumer Finance Division of the South Carolina State Board of Financial Institutions is responsible for the supervision, licensing and examination of all consumer finance companies, deferred presentment companies, check cashing companies, and non-depository mortgage lenders and their loan originators. This project specifically focuses on the licensing of Mortgage Lender/Servicer ( company), Mortgage Lender/Servicer Branch (branch) and Mortgage Loan Originator (loan originator) licenses. The problem statement is how the Division can handle increasing the number of mortgage loan originators in the state without delaying the time to process applications. The goal of this project is to make the current licensing process more efficient so that the Division can handle the increased workload without having to hire additional personnel.

Cálculo de constantes ópticas de películas delgadas de Cu3BiS3 a través del método de Wolfe

Se calculó la obtención de las constantes ópticas usando el método de Wolfe. Dichas contantes: coeficiente de absorción (α), índice de refracción (n) y espesor de una película delgada (d ), son de importancia en el proceso de caracterización óptica del material. Se realizó una comparación del método del Wolfe con el método empleado por R. Swanepoel. Se desarrolló un modelo de programación no lineal con restricciones, de manera que fue posible estimar las constantes ópticas de películas delgadas semiconductoras, a partir únicamente, de datos de transmisión conocidos. Se presentó una solución al modelo de programación no lineal para programación cuadrática. Se demostró la confiabilidad del método propuesto, obteniendo valores de α = 10378.34 cm−1, n = 2.4595, d =989.71 nm y Eg = 1.39 Ev, a través de experimentos numéricos con datos de medidas de transmitancia espectral en películas delgadas de Cu3BiS3.

Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance

In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we obtain a lower bound on the maximum-likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QAM. For e. g., in a 32 x 32 V-BLAST MIMO system, the proposed detection algorithm performs close to within 1.7 dB of the proposed ML lower bound at 10(-3) BER for 16-QAM (128 bps/Hz), and close to within 4.5 dB of the bound for 64-QAM (192 bps/Hz).

Closing the gap between bandit and full-information online optimization : high-probability regret bound

We demonstrate a modification of the algorithm of Dani et al for the online linear optimization problem in the bandit setting, which allows us to achieve an O( \sqrt{T ln T} ) regret bound in high probability against an adaptive adversary, as opposed to the in expectation result against an oblivious adversary of Dani et al. We obtain the same dependence on the dimension as that exhibited by Dani et al. The results of this paper rest firmly on those of Dani et al and the remarkable technique of Auer et al for obtaining high-probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

Nature and Properties of a Repulsive Fermi Gas in the Upper Branch of the Energy Spectrum

We generalize the Nozieres-Schmitt-Rink method to study the repulsive Fermi gas in the absence of molecule formation, i.e., in the so-called ``upper branch.'' We find that the system remains stable except close to resonance at sufficiently low temperatures. With increasing scattering length, the energy density of the system attains a maximum at a positive scattering length before resonance. This is shown to arise from Pauli blocking which causes the bound states of fermion pairs of different momenta to disappear at different scattering lengths. At the point of maximum energy, the compressibility of the system is substantially reduced, leading to a sizable uniform density core in a trapped gas. The change in spin susceptibility with increasing scattering length is moderate and does not indicate any magnetic instability. These features should also manifest in Fermi gases with unequal masses and/or spin populations.

A shortest path tree based algorithm for relay placement in a wireless sensor network and its performance analysis

In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met. (C) 2014 Elsevier B.V. All rights reserved.

Phase unwrapping based on branch cut placing and reliability ordering

A new 2-D quality-guided phase-unwrapping algorithm, based on the placement of the branch cuts, is presented. Its framework consists of branch cut placing guided by an original quality map and reliability ordering performed on a final quality map. To improve the noise immunity of the new algorithm, a new quality map, which is used as the original quality map to guide the placement of the branch cuts, is proposed. After a complete description of the algorithm and the quality map, several wrapped images are used to examine the effectiveness of the algorithm. Computer simulation and experimental results make it clear that the proposed algorithm works effectively even when a wrapped phase map contains error sources, such as phase discontinuities, noise, and undersampling. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Phase unwrapping based on branch cut placing and reliability ordering

A new 2-D quality-guided phase-unwrapping algorithm, based on the placement of the branch cuts, is presented. Its framework consists of branch cut placing guided by an original quality map and reliability ordering performed on a final quality map. To improve the noise immunity of the new algorithm, a new quality map, which is used as the original quality map to guide the placement of the branch cuts, is proposed. After a complete description of the algorithm and the quality map, several wrapped images are used to examine the effectiveness of the algorithm. Computer simulation and experimental results make it clear that the proposed algorithm works effectively even when a wrapped phase map contains error sources, such as phase discontinuities, noise, and undersampling. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

An Algorithm for Group Formation and Maximal Independent Set in an Amorphous Computer

Amorphous computing is the study of programming ultra-scale computing environments of smart sensors and actuators cite{white-paper}. The individual elements are identical, asynchronous, randomly placed, embedded and communicate locally via wireless broadcast. Aggregating the processors into groups is a useful paradigm for programming an amorphous computer because groups can be used for specialization, increased robustness, and efficient resource allocation. This paper presents a new algorithm, called the clubs algorithm, for efficiently aggregating processors into groups in an amorphous computer, in time proportional to the local density of processors. The clubs algorithm is well-suited to the unique characteristics of an amorphous computer. In addition, the algorithm derives two properties from the physical embedding of the amorphous computer: an upper bound on the number of groups formed and a constant upper bound on the density of groups. The clubs algorithm can also be extended to find the maximal independent set (MIS) and $Delta + 1$ vertex coloring in an amorphous computer in $O(log N)$ rounds, where $N$ is the total number of elements and $Delta$ is the maximum degree.

A Lower-Bound Result on the Power of a Genetic Algorithm

This paper presents a lower-bound result on the computational power of a genetic algorithm in the context of combinatorial optimization. We describe a new genetic algorithm, the merged genetic algorithm, and prove that for the class of monotonic functions, the algorithm finds the optimal solution, and does so with an exponential convergence rate. The analysis pertains to the ideal behavior of the algorithm where the main task reduces to showing convergence of probability distributions over the search space of combinatorial structures to the optimal one. We take exponential convergence to be indicative of efficient solvability for the sample-bounded algorithm, although a sampling theory is needed to better relate the limit behavior to actual behavior. The paper concludes with a discussion of some immediate problems that lie ahead.

A new organization for a perceptron-based branch predictor and its FPGA implementation

An unaltered rearrangement of the original computation of a neural based predictor at the algorithmic level is introduced as a new organization. Its FPGA implementation generates circuits that are 1.7 faster than a direct implementation of the original algorithm. This faster clock rate allows to implement predictors with longer history lengths using the nearly the same hardware budget.

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.