Estimation of growth and financial analysis through the application of Ipil ipil (Leucaena leucocephala) leaf meal as supplements to soybean and fish meal in the diet of juvenile monosex tilapia (Oreochromis niloticus)

Among plant protein ingredients,ipil ipil (Leucaena leucocephala) leafmeal (ILLM) is considered the most nutritive plant protein source after soybean meal in aquatic feeds. That was proven in a 21-day experiment conducted to assess the response of juvenile Monosex Nile tilapia Oreochromis niloticus with four iso-nitrogenous formulated diets: One control diet was formulated based on fishmeal, one on soybean meal and one on rice bran, ipil ipil leafmeal was also included in experimental diets.

A simple approach for the estimation of food consumption from growth rates at different environmental conditions and its application to juvenile cod (Gadus morhua L.) of a fjordic sea loch on the west coast of Scotland

Abstract Growth and condition of fish are functions of available food and environmental conditions. This led to the idea of using fish as a “consumption sensor” for the measurement of food intake over a defined period of time. A bio-physical model for the estimation of food consumption was developed based on the von Bertalanffy model. Whereas some of the input variables of the model, the initial and final lengths and masses of a fish and the temperature within the time period considered can easily be measured, internal characteristics of the species have to be determined indirectly. Three internal parameters are used in the model: the maintenance consumption at 0°C, the temperature dependence of this consumption and the food efficiency, the percentage of the ingested food utilized. Estimates of the parameters for a given species can be determined by feeding experiments. Here, data from published feeding experiments on juvenile cod, Gadus morhua L., were used to validate the model. The average of the relative error for the food intake predicted by the model for individual fish was about 24 %, indicating that fish used the food with different efficiencies. However, grouping the fish according to size classes and temperature lowered the relative error of the predicted food intake for the group to typically 5 %. For a group containing all fish of the feeding experiment the relative prediction error was about 2 %. Zusammenfassung Wachstum und Kondition der Fische sind von der verfügbaren Nahrung und von Umweltbedingungen abhängig. Dies führte zur Idee, Fisch als „Konsum-Sensor“ für die Messung der Nahrungsaufnahme über einen definierten Zeitraum zu verwenden. Auf Grundlage des von Bertalanffy-Modells wurde ein bio-physikalisches Modell zur Schätzung der Futteraufnahme entwickelt. Während einige der Eingangsgrößen des Modells leicht gemessen werden können (Anfangs- und Endlänge und -körpermasse der Fische und die Temperatur innerhalb des betrachteten Zeitraum), können interne Parameter der betrachteten Art nur indirekt bestimmt werden. Drei interne Parameter werden in dem Modell verwendet: Die Erhaltungskonsumtion bei 0° C, die Temperaturabhängigkeit dieser Rate und der Wirkungsgrad der Nahrung (der Anteil der Nahrung ,der aufgenommen und verwendet und nicht ungenutzt wieder ausgeschieden wird). Die Modellparameter für eine bestimmte Art können durch Fütterungsversuche bestimmt werden. Um das Modell zu validieren wurden Daten aus veröffentlichten Fütterungsversuchen mit juvenilen Kabeljau (Gadus morhua L.) verwendet. Modell und Wirklichkeit weichen in der Regel voneinander ab. Der durchschnittliche relative Fehler der durch das Modell vorhergesagten Nahrungsaufnahme betrug für Einzelfische etwa 24%, was darauf hinweist, dass einzelne Fisch die Nahrung mit unterschiedlichen Wirkungsgraden verwerten. Allerdings senkte die Gruppierung der Fische nach Größenklassen und Temperatur den relativen Vorhersagefehler für die Nahrungsaufnahme der Gruppe auf etwa 5%. Für alle Fische im Fütterungsversuch ist der relative Vorhersagefehler etwa 2%.

Parametric excitation of Rb-87 atoms in a quadrupole-Ioffe-configuration trap

We have experimentally studied the parametric excitation of Rb-87 atoms in a quadrupole-Ioffe-configuration trap. The temperature of an atomic cloud and number of trapped atoms versus time and modulation frequency of the parametric excitation field have been measured. We also noticed that the contribution of atomic collisions to the energy distributions can not be ignored in the case of weak excitation, which results in a lower temperature of the atomic cloud than by Gehm [Phys. Rev. A 58, 3914 (1998)] predicted.

Monte Carlo simulation of cooling induced by parametric resonance

We demonstrate that the parametric resonance in a magnetic quadrupole trap can be exploited to cool atoms by using Bird's method. In our programme the parametric resonance was realized by anisotropically modulating the trap potential. The modulation frequency dependences of temperature and fraction of the trapped atoms are explored. Furthermore, the temperature after the modulation as functions of the modulation amplitude and the mean elastic collision time are also studied. These results are valuable for the experiment of parametric resonance in a quadrupole trap.

Value Estimation and Comparison in Multi-Attribute Choice

The following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?

In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.