Length-frequency estimation for yellowfin tuna (Thunnus albacares) caught by commercial fishing gear in the Eastern Pacific Ocean

ENGLISH: Methods of collecting samples for the purpose of estimating the numbers and weights of fish caught, by length interval, are described. Several models for two-stage sampling are described, and the equations for the estimators and their variances are given. The results from a brief simulation study are used to show the differences between estimates made with the different models. Estimators for the average weights of fish in the catch and their variances are also described. These average weights are used to provide improved estimates of the total annual catches of yellowfin taken from the eastern Pacific Ocean, east of 150°W, between 1955 and 1990. SPANISH: Se describen los métodos de recoger de muestreo para estimar el número o peso de peces capturados, por intervalo de talla. Se describen varios modelos para el muestreo de dos etapas, y se presentan las ecuaciones para los estimadores y sus varianzas. Se usan los resultados de un breve estudio de simulación para indicar las diferencias entre estimaciones realizadas con los distintosmodelos. También se describe un estimador para el peso promedio de peces en la captura y su varianza. Se usan estos estimadores para calcular estimaciones mejoradas de las capturas anuales totales de aleta amarilla tomadas del Océano Pacífico oriental, al este de 150°W, entre 1955 y 1990. (PDF contains 41 pages.)

Some aspects of the dynamics of populations important to the management of the commercial marine fisheries

(PDF contains 33 pages)

Neural representation of auditory temporal structure

Neurons in the songbird forebrain nucleus HVc are highly sensitive to auditory temporal context and have some of the most complex auditory tuning properties yet discovered. HVc is crucial for learning, perceiving, and producing song, thus it is important to understand the neural circuitry and mechanisms that give rise to these remarkable auditory response properties. This thesis investigates these issues experimentally and computationally.

Extracellular studies reported here compare the auditory context sensitivity of neurons in HV c with neurons in the afferent areas of field L. These demonstrate that there is a substantial increase in the auditory temporal context sensitivity from the areas of field L to HVc. Whole-cell recordings of HVc neurons from acute brain slices are described which show that excitatory synaptic transmission between HVc neurons involve the release of glutamate and the activation of both AMPA/kainate and NMDA-type glutamate receptors. Additionally, widespread inhibitory interactions exist between HVc neurons that are mediated by postsynaptic GABA_A receptors. Intracellular recordings of HVc auditory neurons in vivo provides evidence that HV c neurons encode information about temporal structure using a variety of cellular and synaptic mechanisms including syllable-specific inhibition, excitatory post-synaptic potentials with a range of different time courses, and burst-firing, and song-specific hyperpolarization.

The final part of this thesis presents two computational approaches for representing and learning temporal structure. The first method utilizes comput ational elements that are analogous to temporal combination sensitive neurons in HVc. A network of these elements can learn using local information and lateral inhibition. The second method presents a more general framework which allows a network to discover mixtures of temporal features in a continuous stream of input.

Poverty alleviation among fishermen within the floodplains of Kaduna River: implication for introducing commercial fish farming at village level in Doko local government area of Niger State, Nigeria

A diagnostic survey was conducted among the fishermen in six selected villages in Doko Local Government Area of Niger State. One hundred and fifty fishermen were randomly selected and interviewed to find out whether or not they had interest in commercial fish farming aimed at improving their livelihood. The dwindling fish catches in the natural flood plain ponds and Ex-bow Lakes continue to have a serious negative effect on the socio-economic well being of the village communities in question. A break on natural regular annual flooding of the plains had resulted into very low natural fish recruitment. Data analysis using simple descriptive statistics revealed that land tenure system, educational status, inadequate infrastructural facilities, religious taboos, existing fish species among others were found to be favourable indices for commercial fish farming. However, serious conflicts among the fishermen concerning the ownership status of these natural fish ponds are found to be major obstacles to commercial fish farming despite that the traditional ownership of the ponds were vested in the lands of individuals and village communities. Extensive fish farming and small-scale fish farming in the ponds and Ex-bow Lake with improved management practices are considered to be profitable venture. Despite the fact that fish seeds supply and extension effort are still inadequate, the fish farmers have indicated willingness to adopt commercial fish farming in the Ex-bow Lakes and flood plains in order to restore abundant fish production thereby providing for their food security and also increasing the daily income

Convex Relaxation for Low-Dimensional Representation: Phase Transitions and Limitations

There is a growing interest in taking advantage of possible patterns and structures in data so as to extract the desired information and overcome the curse of dimensionality. In a wide range of applications, including computer vision, machine learning, medical imaging, and social networks, the signal that gives rise to the observations can be modeled to be approximately sparse and exploiting this fact can be very beneficial. This has led to an immense interest in the problem of efficiently reconstructing a sparse signal from limited linear observations. More recently, low-rank approximation techniques have become prominent tools to approach problems arising in machine learning, system identification and quantum tomography.

In sparse and low-rank estimation problems, the challenge is the inherent intractability of the objective function, and one needs efficient methods to capture the low-dimensionality of these models. Convex optimization is often a promising tool to attack such problems. An intractable problem with a combinatorial objective can often be "relaxed" to obtain a tractable but almost as powerful convex optimization problem. This dissertation studies convex optimization techniques that can take advantage of low-dimensional representations of the underlying high-dimensional data. We provide provable guarantees that ensure that the proposed algorithms will succeed under reasonable conditions, and answer questions of the following flavor:

More specifically, i) Focusing on linear inverse problems, we generalize the classical error bounds known for the least-squares technique to the lasso formulation, which incorporates the signal model. ii) We show that intuitive convex approaches do not perform as well as expected when it comes to signals that have multiple low-dimensional structures simultaneously. iii) Finally, we propose convex relaxations for the graph clustering problem and give sharp performance guarantees for a family of graphs arising from the so-called stochastic block model. We pay particular attention to the following aspects. For i) and ii), we aim to provide a general geometric framework, in which the results on sparse and low-rank estimation can be obtained as special cases. For i) and iii), we investigate the precise performance characterization, which yields the right constants in our bounds and the true dependence between the problem parameters.

Determination of optimum stocking density of Macrobrachium rosenbergii larvae using multiple feed in a commercial hatchery at Cox’s Bazar, Bangladesh

Experimental stocking density of Macrobrachium rosenbergii in larval rearing was conducted in A.G. Aqua Hatchery, Chakaria, Bangladesh to study the effect of different stocking densities on growth, survival rate and diseases stress under hatchery condition. The research work was conducted using six cemented rectangular tanks having 3m3 capacity (1.5mX2mX1m) each. Stocking density were maintained in three experimental setup as 200, 150 and 100ind/L of the T1, T2 and T3 respectively with one replicate each. The larvae were fed with Artemia nauplii, Custard, Maxima and brine shrimp flakes. Water quality was maintained by exchanging 20-30% (12ppt saline water) daily. During the study period, temperature, pH, DO, salinity, nitrite-nitrogen, ammonia and alkalinity were maintained from 28.5-31.5ºC, 7.5-7.8, 5.8-5.9mg/L, 12-13ppt, 0.14-0.2 mg/L, 0.22-0.3mg/L, and 140-160mg/L respectively. The growth rates of larvae at 11th stage were recorded in terms of body length 0.115, 0.136, and 0.169 mm/day whereas body weight were observed 0.000115, 0.000180, and 0.000240g/day. The survival rate of larvae were found 21.8%, 30.4% and 51.3% in treatments T1, T2 and T3 respectively. PL was obtained as 43, 45, and 51PL/L and days required of 41, 38 and 34 days in stocking density of 200, 150, and 100ind/L respectively. It was found that the minimum of 34 days was required to attain the PL (12th stage) using the stocking density of 100 individuals/L. Cannibalism, Zoothamnium, Exuvia Entrapment Disease (EED), and Bacterial Necrosis (BN) were found to be the threat to the commercial hatchery operation that might responsible for potential larval damages which can be reduced by lowering the stocking densities in larval rearing tank that also increased the survival and growth rate.

Classical correlated imaging from the perspective of coherent-mode representation

We use coherent-mode representation of partially coherent fields to analyze correlated imaging with classical light sources. This formalism is very useful to study the imaging quality. By decomposing the unknown object as the superposition of different coherent modes, the components corresponding to small eigenvalues cannot be well imaged. The generated images depend crucially on the distribution of the eigenvalues of the coherent-mode representation of the source and the decomposition coefficients of the objects. Three kinds of correlated imaging schemes are analyzed numerically.

Hit-or-miss representation of a pattern spectrum and its optical implementation

We demonstrate that a pattern spectrum can be decomposed into the union of hit-or-miss transforms with respect to a series of structure-element pairs. Moreover we use a Boolean-logic function to express the pattern spectrum and show that the Boolean-logic representation of a pattern spectrum is composed of hit-or-miss min terms. The optical implementation of a pattern spectrum is based on an incoherent optical correlator with a feedback operation. (C) 1996 Optical Society of America

Studies of the representation of interatomic distances in molecules and crystal as sum of atomic radii

The electron diffraction investigation of the following compounds has been carried out: sulfur, sulfur nitride, realgar, arsenic trisulfide, spiropentane, dimethyltrisulfide, cis and trans lewisite, methylal, and ethylene glycol.

The crystal structures of the following salts have been determined by x-ray diffraction: silver molybdateand hydrazinium dichloride.

Suggested revisions of the covalent radii for B, Si, P, Ge, As, Sn, Sb, and Pb have been made, and values for the covalent radii of Al, Ga, In, Ti, and Bi have been proposed.

The Schomaker-Stevenson revision of the additivity rule for single covalent bond distances has been used in conjunction with the revised radii. Agreement with experiment is in general better with the revised radii than with the former radii and additivity.

The principle of ionic bond character in addition to that present in a normal covalent bond has been applied to the observed structures of numerous molecules. It leads to a method of interpretation which is at least as consistent as the theory of multiple bond formation.

The revision of the additivity rule has been extended to double bonds. An encouraging beginning along these lines has been made, but additional experimental data are needed for clarification.