Hydroacoustic evaluation of spawning red hind (Epinephelus guttatus) aggregations along the coast of Puerto Rico in 2002 and 2003

Red hind (Epinephelus guttatus) have been overfished in the Caribbean and were included with seven other regional grouper species deemed vulnerable to risk of extinction. The Puerto Rico Department of Natural and Environmental Resources desired to map spawning red hind aggregations within commonwealth waters as part of their resource management program for the species. Mobile hydroacoustic surveys were conducted over 3-day periods in 2002 and 2003, indexed to the full moon phase in February or March when red hind were known to aggregate. Four vessels concurrently sampled the southwest, south, and southeast coasts of Puerto Rico in 2002. In 2003, three vessels conducted complementary surveys of the northwest, north, and northeast coasts of the island, completing a circuit of the coastal shelf-spawning habitat. These surveys indicated that red hind spawning aggregations were prevalent along the south and west coasts, and sparse along the north coast during the survey periods. Highest spawning red hind concentrations were observed in three areas offshore of the west coast of Puerto Rico, around Mona and Desecheo islands (20,443 and 10,559 fish/km2, respectively) and in the Bajo de Cico seasonal closed area (4,544 fish/km2). Following both 2002 and 2003 surveys, a series of controlled acoustic measurements of known local fish species in net pens were conducted to assess the mean target strength (acoustic backscatter) of each group. Ten species of fish were measured, including red hind (E. guttatus), coney (E. fulvus), white grunt (Haemulon plumieri), pluma (Calamus pennatula), blue tang (Acanthurus coeruleus), squirrel fish (Holocentrus spp.), black durgeon (Melichtyhs niger), ocean file fish (Canthidermis sufflamen), ocean surgeon fish (Acanthurus bahianus), and butter grouper (Mycteroperca spp.). In general, the mean target strength results from the caged fish experiments were in agreement with published target strength length relationships, with the exception of white grunt and pluma.

Efficient Gate-tunable light-emitting device made of defective boron nitride nanotubes: from ultraviolet to the visible

Boron nitride is a promising material for nanotechnology applications due to its two-dimensional graphene-like, insulating, and highly-resistant structure. Recently it has received a lot of attention as a substrate to grow and isolate graphene as well as for its intrinsic UV lasing response. Similar to carbon, one-dimensional boron nitride nanotubes (BNNTs) have been theoretically predicted and later synthesised. Here we use first principles simulations to unambiguously demonstrate that i) BN nanotubes inherit the highly efficient UV luminescence of hexagonal BN; ii) the application of an external perpendicular field closes the electronic gap keeping the UV lasing with lower yield; iii) defects in BNNTS are responsible for tunable light emission from the UV to the visible controlled by a transverse electric field (TEF). Our present findings pave the road towards optoelectronic applications of BN-nanotube-based devices that are simple to implement because they do not require any special doping or complex growth

Water quality assessment and characterisation of chlorophyll-a variability related to river discharges, within the southeastern Bay of Biscay : evaluation and development of chlorophyll-a algorithms for MODIS and MERIS imagery

222 p. : il.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

Development of an efficient particle approach for micro-scale gas flow simulations

The micro-scale gas flows are usually low-speed flows and exhibit rarefied gas effects. It is challenging to simulate these flows because traditional CFD method is unable to capture the rarefied gas effects and the direct simulation Monte Carlo (DSMC) method is very inefficient for low-speed flows. In this study we combine two techniques to improve the efficiency of the DSMC method. The information preservation technique is used to reduce the statistical noise and the cell-size relaxed technique is employed to increase the effective cell size. The new cell-size relaxed IP method is found capable of simulating micro-scale gas flows as shown by the 2D lid-driven cavity flows.

Protein and amino acid requirements of warm-water fishes: a tool to efficient and low-cost fish feed production in Nigeria

Numerous investigations have utilized various semi-purified and purified diets to estimate the protein and amino acid requirements of several temperate fishes. The vast literature on the protein and amino acid requirements of fishes has continued to omit that of the tropical warm water species. The net effect is that fish feed formulation in Nigeria have relied on the requirement for temperate species. This paper attempts to review the state of knowledge on the protein amino acid requirements of fishes with emphasis on the warm water species, the methods of protein and amino acid requirement determinations and the influence of various factors on nutritional requirement studies. Finally evidence are presented with specific examples on how requirements of warm water fishes are different from the temperate species and used this to justify why fish feed formulation in Nigeria are far from being efficient

Desarrollo de una aplicación para una red de sensores inalámbricos (WSN) mediante Contiki

Durante los últimos años hemos venido observando la tendencia a incorporar capacidad de proce- samiento y comunicación a dispositivos que hasta entonces se utilizaban de modo independiente. La evolución de los móviles a smartphones es un claro ejemplo de dicha tendencia, aunque también cabe mencionar otros ejemplos, como es el caso de los denominados hogares inteligentes, en los que elementos del hogar se encuentran interconectados y pueden actuar de modo conjunto. Esta ten- dencia no se limita a sistemas independientes, sino que propone interconectar todos los elementos disponibles para conformar la denominada Internet de los Objetos/Cosas o Internet of Things, IoT. Una de las mayores dificultades que se presenta en estos sistemas es que las características de es- tos nuevos dispositivos inteligentes, en general limitados en términos de cómputo, almacenamiento, autonomía o comunicación, queda a menudo lejos de los equipos informáticos tradicionales. Esta cuestión, junto con la ausencia de estándares para gestionar estos dispositivos, constituye un impor- tante problema a abordar. Considerando este marco, en este proyecto se ha desarrollado una aplicación orientada a este tipo de dispositivos. Más concretamente, la aplicación tiene como soporte una red de sensores inalámbricos, WSN, con el objetivo de realizar seguimiento de individuos. Cabe destacar que el desarrollo de la aplicación se ha realizado utilizando Contiki OS, sistema ope- rativo diseñado especialmente para dispositivos con características limitadas como los presentados anteriormente y firme candidato a convertirse en estándar.

Soporte a la explotación de datos y gestión de una red de sensores

El seguimiento de distintas especies de animales contribuye en gran medida a su estudio y, por tanto, a su conservación y control. Los avances tecnológicos de los últimos años han facilitado las posibilidades de seguimiento con la creación de distintos dispositivos que permiten conocer los movimientos de la especie que se desea estudiar. Uno de los sistemas más utilizados consiste en la utilización de dispositivos GPS incorporados al espécimen sobre el que se realiza el seguimiento y cuya señal es recogida por satélites que se encargan de almacenar y posteriormente reenviar la información para su almacenamiento y procesamiento en el laboratorio. El principal problema de este sistema es su elevado coste. Existen alternativas que no presentan un coste tal alto, tales como el uso de módulos basados en telefonía móvil. Sin embargo, tienen limitaciones de cobertura, por lo que no es aplicable en todos los ámbitos. Este proyecto forma parte de una propuesta que ofrece realizar seguimiento de ejemplares de una especie de ave, la gaviota Patiamarilla, en Gipuzkoa mediante la utilización de una red de sensores y que tiene varias ventajas frente a las opciones presentadas anteriormente. En este proyecto en concreto se ha diseñado e implementado el módulo que permite recoger la información obtenida por el conjunto de sensores (cada ejemplar lleva incorporado un sensor que permite registrar su posición) y enviarla a un servidor centralizado para su posterior consulta y análisis. Adicionalmente, también se permite consultar el último estado registrado de cada dispositivo de seguimiento, además de contemplar la posibilidad de actualizar su software.

Dense, efficient chip-to-chip communication at the extremes of computing

The scalability of CMOS technology has driven computation into a diverse range of applications across the power consumption, performance and size spectra. Communication is a necessary adjunct to computation, and whether this is to push data from node-to-node in a high-performance computing cluster or from the receiver of wireless link to a neural stimulator in a biomedical implant, interconnect can take up a significant portion of the overall system power budget. Although a single interconnect methodology cannot address such a broad range of systems efficiently, there are a number of key design concepts that enable good interconnect design in the age of highly-scaled CMOS: an emphasis on highly-digital approaches to solving ‘analog’ problems, hardware sharing between links as well as between different functions (such as equalization and synchronization) in the same link, and adaptive hardware that changes its operating parameters to mitigate not only variation in the fabrication of the link, but also link conditions that change over time. These concepts are demonstrated through the use of two design examples, at the extremes of the power and performance spectra.

A novel all-digital clock and data recovery technique for high-performance, high density interconnect has been developed. Two independently adjustable clock phases are generated from a delay line calibrated to 2 UI. One clock phase is placed in the middle of the eye to recover the data, while the other is swept across the delay line. The samples produced by the two clocks are compared to generate eye information, which is used to determine the best phase for data recovery. The functions of the two clocks are swapped after the data phase is updated; this ping-pong action allows an infinite delay range without the use of a PLL or DLL. The scheme's generalized sampling and retiming architecture is used in a sharing technique that saves power and area in high-density interconnect. The eye information generated is also useful for tuning an adaptive equalizer, circumventing the need for dedicated adaptation hardware.

On the other side of the performance/power spectra, a capacitive proximity interconnect has been developed to support 3D integration of biomedical implants. In order to integrate more functionality while staying within size limits, implant electronics can be embedded onto a foldable parylene (‘origami’) substrate. Many of the ICs in an origami implant will be placed face-to-face with each other, so wireless proximity interconnect can be used to increase communication density while decreasing implant size, as well as facilitate a modular approach to implant design, where pre-fabricated parylene-and-IC modules are assembled together on-demand to make custom implants. Such an interconnect needs to be able to sense and adapt to changes in alignment. The proposed array uses a TDC-like structure to realize both communication and alignment sensing within the same set of plates, increasing communication density and eliminating the need to infer link quality from a separate alignment block. In order to distinguish the communication plates from the nearby ground plane, a stimulus is applied to the transmitter plate, which is rectified at the receiver to bias a delay generation block. This delay is in turn converted into a digital word using a TDC, providing alignment information.