Are we focussing wild dog control the wrong time of the year and going about it the wrong way?

Our evaluation of the predation of calves by wild dogs in the 1990s found that the number of calves killed and frequency of years that calf losses occurred, is higher in baited areas compared to adjoining, non-baited areas of similar size. Calf losses were highest with poor seasonal conditions, low prey numbers and where baited areas were re-colonised by wild dogs soon after baiting. We monitored wild dog “activity” before and after 35 baiting programs in southwest, central west and far north Queensland between 1994 and 2006 and found change in activity depends on the timing of the baiting. Baiting programs conducted between October and April show an increase in dog activity post-baiting (average increase of 219.1%, SEM 100.9, n=9, for programs conducted in October and November; an increase of 82.5%, SEM 54.5, n=7 for programs conducted in March and April; and a decrease in activity of 46.5%, SEM 10.2, n=19 for programs conducted between May and September). We monitored the seasonal activity and dispersal of wild dogs fitted with satellite transmitters 2006 to present. We have found that: • Activity of breeding males and females, whilst rearing and nurturing pups, is focussed around the den between July to September and away from areas of human activity. Activity of breeding groups appears to avoid locations of human activity until juveniles become independent (around late November). • While independent and solitary yearlings often have unstable, elliptically-shaped territories in less favourable areas, members of breeding groups have territories that appear seasonally stable and circular located in more favourable habitats. • Extra-territorial forays of solitary yearlings can be huge, in excess of 200 km. The largest forays we have monitored have occurred when the activity of pack members is focussed around rearing pups and juveniles (August to November). • Where wild dogs have dispersed or had significant territorial expansion, it has occurred within days of baiting programs and onto recently baited properties. • The wild dogs we have tracked have followed netting barrier fences for hundreds of kilometres and lived adjacent to or bypassed numerous grids in the barrier. Based on these studies, we conclude that a proportion of the perceived decline in dog activity between May and September, post baiting, is due to a decline in dog activity in areas associated with human activity. The increase in dog activity post-baiting between October and May (and increased calf predation on baited properties) is likely caused by wild dogs dispersing (juveniles and yearlings) or expanding (adults) their territory into baited, now ‘vacant’, areas. We hypothesise that baiting programs should be focussed in summer and autumn commencing late November as soon as juveniles become independent of adults. We also hypothesise that instead of large, annual or semi-annual baiting programs, laying the same number of baits over 4-6 weeks may be more effective. These hypotheses need to be tested through an adaptive management project.

Prediction of bubble growth rates and departure volumes in nucleate boiling at isolated sites

A model has been developed to predict heat transfer rates and sizes of bubbles generated during nucleate pool boiling. This model assumes conduction and a natural convective heat transfer mechanism through the liquid layer under the bubble and transient conduction from the bulk liquid. The temperature of the bulk liquid in the vicinity of the bubble is obtained by assuming a turbulent natural convection process from the hot plate to the liquid bulk. The shape of the bubble is obtained by equilibrium analysis. The bubble departure condition is predicted by a force balance equation. Good agreement has been found between the bubble radii predicted by the present theory and the ones obtained experimentally.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Semi-active vibration isolation using a near-zero-spring-rate device:steady state analysis of a single-degree-of-freedom model

A vibration isolator is described which incorporates a near-zero-spring-rate device within its operating range. The device is an assembly of a vertical spring in parallel with two inclined springs. A low spring rate is achieved by combining the equivalent stiffness in the vertical direction of the inclined springs with the stiffness of the vertical central spring. It is shown that there is a relation between the geometry and the stiffness of the individual springs that results in a low spring rate. Computer simulation studies of a single-degree-of-freedom model for harmonic base input show that the performance of the proposed scheme is superior to that of the passive schemes with linear springs and skyhook damping configuration. The response curves show that, for small to large amplitudes of base disturbance, the system goes into resonance at low frequencies of excitation. Thus, it is possible to achieve very good isolation over a wide low-frequency band. Also, the damper force requirements for the proposed scheme are much lower than for the damper force of a skyhook configuration or a conventional linear spring with a semi-active damper.

A Cointegration Approach to Topics in Empirical Macroeconomics (summary section only)

Mikael Juselius’ doctoral dissertation covers a range of significant issues in modern macroeconomics by empirically testing a number of important theoretical hypotheses. The first essay presents indirect evidence within the framework of the cointegrated VAR model on the elasticity of substitution between capital and labor by using Finnish manufacturing data. Instead of estimating the elasticity of substitution by using the first order conditions, he develops a new approach that utilizes a CES production function in a model with a 3-stage decision process: investment in the long run, wage bargaining in the medium run and price and employment decisions in the short run. He estimates the elasticity of substitution to be below one. The second essay tests the restrictions implied by the core equations of the New Keynesian Model (NKM) in a vector autoregressive model (VAR) by using both Euro area and U.S. data. Both the new Keynesian Phillips curve and the aggregate demand curve are estimated and tested. The restrictions implied by the core equations of the NKM are rejected on both U.S. and Euro area data. These results are important for further research. The third essay is methodologically similar to essay 2, but it concentrates on Finnish macro data by adopting a theoretical framework of an open economy. Juselius’ results suggests that the open economy NKM framework is too stylized to provide an adequate explanation for Finnish inflation. The final essay provides a macroeconometric model of Finnish inflation and associated explanatory variables and it estimates the relative importance of different inflation theories. His main finding is that Finnish inflation is primarily determined by excess demand in the product market and by changes in the long-term interest rate. This study is part of the research agenda carried out by the Research Unit of Economic Structure and Growth (RUESG). The aim of RUESG it to conduct theoretical and empirical research with respect to important issues in industrial economics, real option theory, game theory, organization theory, theory of financial systems as well as to study problems in labor markets, macroeconomics, natural resources, taxation and time series econometrics. RUESG was established at the beginning of 1995 and is one of the National Centers of Excellence in research selected by the Academy of Finland. It is financed jointly by the Academy of Finland, the University of Helsinki, the Yrjö Jahnsson Foundation, Bank of Finland and the Nokia Group. This support is gratefully acknowledged.

Groove Binding Ligands for the Interaction with Parallel-Stranded ps-Duplex DNA and Triplex DNA

DNA adopts different conformations not only based on novel base pairs, but also with different chain polarities. Besides several duplex structures (A, B, Z, parallel stranded (ps)-DNA, etc.), DNA also forms higher-order structures like triplex, tetraplex, and i-motif. Each of these structures has its own biological significance. The ps-duplexes have been found to be resistant to certain nucleases and endonucleases. Molecules that promote triple-helix formation have significant potential. These investigations have many therapeutic advantages which may be useful in the regulation of the expression of genes responsible for certain diseases by locking either their transcription (antigene) or translation (antisense). Each DNA minor groove binding ligand (MGBL) interacts with DNA through helical minor groove recognition in a sequence-specific manner, and this interferes with several DNA-associated processes. Incidentally, these ligands interact with some non-B-DNA and with higher-order DNA structures including ps-DNA and triplexes. While the design and recognition of minor grooves of duplex DNA by specific MGBLs have been a topic of many reports, limited information is available on the binding behavior of MGBLs with nonduplex DNA. In this review, we summarize various attempts of the interaction of MGBLs with ps-DNA and DNA triplexes.

Delamination and solvothermal decomposition of layered zinc hydroxysalt: Formation of bimodal zinc oxide nanostructures

Dodecylsulphate-intercalated zinc hydroxysalt, Zn-5(OH)(8)(DS)(2)center dot mH(2)O delaminates to give monolayer colloidal dispersions in alcohols such as 1-butanol and ethylene glycol. The extent of delamination and the stability of the colloidal dispersion are comparable to those of layered double hydroxides. The solvothermal decomposition of the colloidal dispersion of the hydroxysalt in ethylene glycol yields a bimodal ZnO having a nanotubular structure decorated with nanosheets. (C) 2010 Elsevier Masson SAS. All rights reserved.

A new model for drainage of static foams

Existing theories of foam drainage assume bubbles as pentagonal dodecahedrons, though a close-packed structure built with cells of this shape is not space-filling. The present work develops a theory for calculating drainage rates based on the more realistic beta-tetrakaidecahedral shape for the bubbles. In contrast with the earlier works, three types of films, and Plateau borders had to be considered in view of the more complex shape used in the present work. The exchange of liquid between Plateau borders was treated in a way different From earlier theories, using the idea that the volume of junctions of Plateau borders is negligible. For foams made of large bubble sizes, the present model performs as well as the previous models, but when bubble size is small, its predictions of drainage rates from static foams are in better agreement with the experimental observations.

Total synthesis of (-)-ent-pachastrissamine (ent-Jaspine B)

The total synthesis of the enantiomer of the tetrahydrofuran containing natural product Jaspine B is reported. The key reactions in the synthesis include formation of the tetrahydrofuran unit by an acid mediated Williamson etherification and a subsequent elaboration with an olefin cross metathesis reaction. (C) 2011 Elsevier Ltd. All rights reserved.

Polymer thin film structures for ultra-low cost biosensing

Reflectance change due to binding of molecules on thin film structures has been exploited for bio-molecular sensing by several groups due to its potential in the development of sensitive, low cost, easy to fabricate, large area sensors with high multiplexing capabilities. However, all of these sensing platforms have been developed using traditional semiconductor materials and processing techniques, which are expensive. This article presents a method to fabricate disposable thin film reflectance biosensors using polymers, such as polycarbonate, which are 2-3 orders of magnitude cheaper than conventional semiconductor and dielectric materials and can be processed by alternate low cost methods, leading to significant reduction in consumable costs associated with diagnostic biosensing. (C) 2011 Elsevier GmbH. All rights reserved.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

Timing Calculations for a General N-Level Dodecagonal Space Vector Structure Using Only Reference Phase Voltages

Multilevel inverters with dodecagonal (12-sided polygon) voltage space vector (SV) structures have advantages like extension of linear modulation range, elimination of fifth and seventh harmonics in phase voltages and currents for the full modulation range including extreme 12-step operation, reduced device voltage ratings, lesser dv/dt stresses on devices and motor phase windings resulting in lower EMI/EMC problems, and lower switching frequency-making it more suitable for high-power drive applications. This paper proposes a simple method to obtain pulsewidth modulation (PWM) timings for a dodecagonal voltage SV structure using only sampled reference voltages. In addition to this, a carrier-based method for obtaining the PWM timings for a general N-level dodecagonal structure is proposed in this paper for the first time. The algorithm outputs the triangle information and the PWM timing values which can be set as the compare values for any carrier-based hardware PWM module to obtain SV PWM like switching sequences. The proposed method eliminates the need for angle estimation, computation of modulation indices, and iterative search algorithms that are typical in multilevel dodecagonal SV systems. The proposed PWM scheme was implemented on a five-level dodecagonal SV structure. Exhaustive simulation and experimental results for steady-state and transient conditions are presented to validate the proposed method.