Ecological and Behavioral Methods for the Study of Bats [2nd. Ed.]

"First published in 1988, Ecological and Behavioral Methods for the Study of Bats is widely acknowledged as the primary reference for both amateur and professional bat researchers. Bats are the second most diverse group of mammals on the earth. They live on every continent except Antarctica, ranging from deserts to tropical forests to mountains, and their activities have a profound effect on the ecosystems in which they live. Despite their ubiquity and importance, bats are challenging to study. This volume provides researchers, conservationists, and consultants with the ecological background and specific information essential for studying bats in the wild and in captivity. Chapters detail many of the newest and most commonly used field and laboratory techniques needed to advance the study of bats, describe how these methods are applied to the study of the ecology and behavior of bats, and offer advice on how to interpret the results of research. The book includes forty-three chapters, fourteen of which are new to the second edition, with information on molecular ecology and evolution, bioacoustics, chemical communication, flight dynamics, population models, and methods for assessing postnatal growth and development. Fully illustrated and featuring contributions from the world’s leading experts in bat biology, this reference contains everything bat researchers and natural resource managers need to know for the study and conservation of this wide-ranging, ecologically vital, and diverse taxon."--Publisher website

Model-based analysis and optimization of bioreactor for hematopoietic stem cell cultivation

One of the problems to be solved in attaining the full potentials of hematopoietic stem cell (HSC) applications is the limited availability of the cells. Growing HSCs in a bioreactor offers an alternative solution to this problem. Besides, it also offers the advantages of eliminating labour intensive process as well as the possible contamination involved in the periodic nutrient replenishments in the traditional T-flask stem cell cultivation. In spite of this, the optimization of HSC cultivation in a bioreactor has been barely explored. This manuscript discusses the development of a mathematical model to describe the dynamics in nutrient distribution and cell concentration of an ex vivo HSC cultivation in a microchannel perfusion bioreactor. The model was further used to optimize the cultivation by proposing three alternative feeding strategies in order to prevent the occurrence of nutrient limitation in the bioreactor. The evaluation of these strategies, the periodic step change increase in the inlet oxygen concentration, the periodic step change increase in the media inflow, and the feedback control of media inflow, shows that these strategies can successfully improve the cell yield of the bioreactor. In general, the developed model is useful for the design and optimization of bioreactor operation.

Preparation, Analysis and Use of an Affinity Adsorbent for the Purification of GST Fusion Protein

Methods are presented for the preparation, ligand density analysis and use of an affinity adsorbent for the purification of a glutathione S-transferase (GST) fusion protein in packed and expanded bed chromatographic processes. The protein is composed of GST fused to a zinc finger transcription factor (ZnF). Glutathione, the affinity ligand for GST purification, is covalently immobilized to a solid-phase adsorbent (Streamline™). The GST–ZnF fusion protein displays a dissociation constant of 0.6 x10-6 M to glutathione immobilized to Streamline™. Ligand density optimization, fusion protein elution conditions (pH and glutathione concentration) and ligand orientation are briefly discussed.

Materials, methods and systems for purification and/or seperation

Materials, methods and systems are provided for the purifn., filtration and​/or sepn. of certain mols. such as certain size biomols. Certain embodiments relate to supports contg. at least one polymethacrylate polymer engineered to have certain pore diams. and other properties, and which can be functionally adapted to for certain purifications, filtrations and​/or sepns. Biomols. are selected from a group consisting of: polynucleotide mols., oligonucleotide mols. including antisense oligonucleotide mols. such as antisense RNA and other oligonucleotide mols. that are inhibitory of gene function such as small interfering RNA (siRNA)​, polypeptides including proteinaceous infective agents such as prions, for example, the infectious agent for CJD, and infectious agents such as viruses and phage.

Using personal construct theory and narrative methods to facilitate reflexive constructions of teaching physical education

This paper reports on two lengthy studies in Physical education teacher education (PETE) conducted independently but which are epistemologically and methodologically linked. The paper describes how personal construct theory (PCT) and its associated methods provided a means for PETE students to reflexively construct their ideas about teaching physical education over an extended period. Data are drawn from each study in the form of a story of a single participant to indicate how this came about. Furthermore we suggest that PCT might be both a useful research strategy and an effective approach to facilitate professional development in a teacher education setting.

Finite volume methods for simulating anomalous transport

In this thesis a new approach for solving a certain class of anomalous diffusion equations was developed. The theory and algorithms arising from this work will pave the way for more efficient and more accurate solutions of these equations, with applications to science, health and industry. The method of finite volumes was applied to discretise the spatial derivatives, and this was shown to outperform existing methods in several key respects. The stability and convergence of the new method were rigorously established.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.