Bactrocera frauenfeldi (Diptera: Tephritidae), an invasive fruit fly in Australia that may have reached the extent of its spread due to environmental variables

Bactrocera frauenfeldi (Schiner), the ‘mango fruit fly’, is a horticultural pest originating from the Papua New Guinea region. It was first detected in Australia on Cape York Peninsula in north Queensland in 1974 and had spread to Cairns by 1994 and Townsville by 1997. Bactrocera frauenfeldi has not been recorded further south since then despite its invasive potential, an absence of any controls and an abundance of hosts in southern areas. Analysis of cue-lure trapping data from 1997 to 2012 in relation to environmental variables shows that the distribution of B. frauenfeldi in Queensland correlates to locations with a minimum temperature for the coldest month >13.2°C, annual temperature range <19.3°C, mean temperature of the driest quarter >20.2°C, precipitation of the wettest month >268 mm, precipitation of the wettest quarter >697 mm, temperature seasonality <30.9°C (i.e. lower temperature variability) and areas with higher human population per square kilometre. Annual temperature range was the most important variable in predicting this species' distribution. Predictive distribution maps based on an uncorrelated subset of these variables reasonably reflected the current distribution of this species in northern Australia and predicted other areas in the world potentially at risk from invasion by this species. This analysis shows that the distribution of B. frauenfeldi in Australia is correlated to certain environmental variables that have most likely limited this species' spread southward in Queensland. This is of importance to Australian horticulture in demonstrating that B. frauenfeldi is unlikely to establish in horticultural production areas further south than Townsville.

The use of metabolomics to monitor simultaneous changes in metabolic variables following supramaximal low volume high intensity exercise

High Intensity Exercise (HIE) stimulates greater physiological remodeling when compared to workload matched low-moderate intensity exercise. This study utilized an untargeted metabolomics approach to examine the metabolic perturbations that occur following two workload matched supramaximal low volume HIE trials. In a randomized order, 7 untrained males completed two exercise protocols separated by one week; 1) HIE150%: 30 x 20s cycling at 150% VO2peak, 40s passive rest; 2) HIE300%: 30 x 10s cycling at 300% VO2peak, 50 s passive rest. Total exercise duration was 30 minutes for both trials. Blood samples were taken at rest, during and immediately following exercise and at 60 minutes post exercise. Gas chromatography-mass spectrometry (GC-MS) analysis of plasma identified 43 known metabolites of which 3 demonstrated significant fold changes (HIE300% compared to the HIE150% value) during exercise, 14 post exercise and 23 at the end of the recovery period. Significant changes in plasma metabolites relating to lipid metabolism [fatty acids: dodecanoate (p=0.042), hexadecanoate (p=0.001), octadecanoate (p=0.001)], total cholesterol (p=0.001), and glycolysis [lactate (p=0.018)] were observed following exercise and during the recovery period. The HIE300% protocol elicited greater metabolic changes relating to lipid metabolism and glycolysis when compared to HIE150% protocol. These changes were more pronounced throughout the recovery period rather than during the exercise bout itself. Data from the current study demonstrate the use of metabolomics to monitor intensity-dependent changes in multiple metabolic pathways following exercise. The small sample size indicates a need for further studies in a larger sample cohort to validate these findings.

Calculating the bound spectrum by path summation in action-angle variables

The density of states n(E) is calculated for a bound system whose classical motion is integrable, starting from an expression in terms of the trace of the time-dependent Green function. The novel feature is the use of action-angle variables. This has the advantages that the trace operation reduces to a trivial multiplication and the dependence of n(E) on all classical closed orbits with different topologies appears naturally. The method is contrasted with another, not applicable to integrable systems except in special cases, in which quantization arises from a single closed orbit which is assumed isolated and the trace taken by the method of stationary phase.

Postoperative Volume Therapy in Cardiac Surgery : Effects on Hemostatic and Circulatory Variables

Background: Patients may need massive volume-replacement therapy after cardiac surgery because of large fluid transfer perioperatively, and the use of cardiopulmonary bypass. Hemodynamic stability is better maintained with colloids than crystalloids but colloids have more adverse effects such as coagulation disturbances and impairment of renal function than do crystalloids. The present study examined the effects of modern hydroxyethyl starch (HES) and gelatin solutions on blood coagulation and hemodynamics. The mechanism by which colloids disturb blood coagulation was investigated by thromboelastometry (TEM) after cardiac surgery and in vitro by use of experimental hemodilution. Materials and methods: Ninety patients scheduled for elective primary cardiac surgery (Studies I, II, IV, V), and twelve healthy volunteers (Study III) were included in this study. After admission to the cardiac surgical intensive care unit (ICU), patients were randomized to receive different doses of HES 130/0.4, HES 200/0.5, or 4% albumin solutions. Ringer’s acetate or albumin solutions served as controls. Coagulation was assessed by TEM, and hemodynamic measurements were based on thermodilutionally measured cardiac index (CI). Results: HES and gelatin solutions impaired whole blood coagulation similarly as measured by TEM even at a small dose of 7 mL/kg. These solutions reduced clot strength and prolonged clot formation time. These effects were more pronounced with increasing doses of colloids. Neither albumin nor Ringer’s acetate solution disturbed blood coagulation significantly. Coagulation disturbances after infusion of HES or gelatin solutions were clinically slight, and postoperative blood loss was comparable with that of Ringer’s acetate or albumin solutions. Both single and multiple doses of all the colloids increased CI postoperatively, and this effect was dose-dependent. Ringer’s acetate had no effect on CI. At a small dose (7 mL/kg), the effect of gelatin on CI was comparable with that of Ringer’s acetate and significantly less than that of HES 130/0.4 (Study V). However, when the dose was increased to 14 and 21 mL/kg, the hemodynamic effect of gelatin rose and became comparable with that of HES 130/0.4. Conclusions: After cardiac surgery, HES and gelatin solutions impaired clot strength in a dose-dependent manner. The potential mechanisms were interaction with fibrinogen and fibrin formation, resulting in decreased clot strength, and hemodilution. Although the use of HES and gelatin inhibited coagulation, postoperative bleeding on the first postoperative morning in all the study groups was similar. A single dose of HES solutions improved CI postoperatively more than did gelatin, albumin, or Ringer’s acetate. However, when administered in a repeated fashion, (cumulative dose of 14 mL/kg or more), no differences were evident between HES 130/0.4 and gelatin.

Electrocardiographic repolarization variables in detecting myocardial infarction and ischemic injury : From body surface potential mapping to a single lead

The aim of the studies was to improve the diagnostic capability of electrocardiography (ECG) in detecting myocardial ischemic injury with a future goal of an automatic screening and monitoring method for ischemic heart disease. The method of choice was body surface potential mapping (BSPM), containing numerous leads, with intention to find the optimal recording sites and optimal ECG variables for ischemia and myocardial infarction (MI) diagnostics. The studies included 144 patients with prior MI, 79 patients with evolving ischemia, 42 patients with left ventricular hypertrophy (LVH), and 84 healthy controls. Study I examined the depolarization wave in prior MI with respect to MI location. Studies II-V examined the depolarization and repolarization waves in prior MI detection with respect to the Minnesota code, Q-wave status, and study V also with respect to MI location. In study VI the depolarization and repolarization variables were examined in 79 patients in the face of evolving myocardial ischemia and ischemic injury. When analyzed from a single lead at any recording site the results revealed superiority of the repolarization variables over the depolarization variables and over the conventional 12-lead ECG methods, both in the detection of prior MI and evolving ischemic injury. The QT integral, covering both depolarization and repolarization, appeared indifferent to the Q-wave status, the time elapsed from MI, or the MI or ischemia location. In the face of evolving ischemic injury the performance of the QT integral was not hampered even by underlying LVH. The examined depolarization and repolarization variables were effective when recorded in a single site, in contrast to the conventional 12-lead ECG criteria. The inverse spatial correlation of the depolarization and depolarization waves in myocardial ischemia and injury could be reduced into the QT integral variable recorded in a single site on the left flank. In conclusion, the QT integral variable, detectable in a single lead, with optimal recording site on the left flank, was able to detect prior MI and evolving ischemic injury more effectively than the conventional ECG markers. The QT integral, in a single-lead or a small number of leads, offers potential for automated screening of ischemic heart disease, acute ischemia monitoring and therapeutic decision-guiding as well as risk stratification.

Process variables in biomimetic synthesis of silver nanoparticles by aqueous extract of Azadirachta indica (Neem) leaves

Owing to widespread applications, synthesis and characterization of silver nanoparticles is recently attracting considerable attention. Increasing environmental concerns over chemical synthesis routes have resulted in attempts to develop biomimetic approaches. One of them is synthesis using plant parts, which eliminates the elaborate process of maintaining the microbial culture and often found to be kinetically favourable than other bioprocesses. The present study deals with investigating the effect of process variables like reductant concentrations, reaction pH, mixing ratio of the reactants and interaction time on the morphology and size of silver nanoparticles synthesized using aqueous extract of Azadirachta indica (Neem) leaves. The formation of crystalline silver nanoparticles was confirmed using X-ray diffraction analysis. By means of UV spectroscopy, Scanning and Transmission Electron Microscopy techniques, it was observed that the morphology and size of the nanoparticles were strongly dependent on the process parameters. Within 4 h interaction period, nanoparticles below 20-nm-size with nearly spherical shape were produced. On increasing interaction time (ageing) to 66 days, both aggregation and shape anisotropy (ellipsoidal, polyhedral and capsular) of the particles increased. In alkaline pH range, the stability of cluster distribution increased with a declined tendency for aggregation of the particles. It can be inferred from the study that fine tuning the bioprocess parameters will enhance possibilities of desired nano-product tailor made for particular applications.

On gravitational fields of stars in f(R) gravity theories

Einstein's general relativity is a classical theory of gravitation: it is a postulate on the coupling between the four-dimensional, continuos spacetime and the matter fields in the universe, and it yields their dynamical evolution. It is believed that general relativity must be replaced by a quantum theory of gravity at least at extremely high energies of the early universe and at regions of strong curvature of spacetime, cf. black holes. Various attempts to quantize gravity, including conceptually new models such as string theory, have suggested that modification to general relativity might show up even at lower energy scales. On the other hand, also the late time acceleration of the expansion of the universe, known as the dark energy problem, might originate from new gravitational physics. Thus, although there has been no direct experimental evidence contradicting general relativity so far - on the contrary, it has passed a variety of observational tests - it is a question worth asking, why should the effective theory of gravity be of the exact form of general relativity? If general relativity is modified, how do the predictions of the theory change? Furthermore, how far can we go with the changes before we are face with contradictions with the experiments? Along with the changes, could there be new phenomena, which we could measure to find hints of the form of the quantum theory of gravity? This thesis is on a class of modified gravity theories called f(R) models, and in particular on the effects of changing the theory of gravity on stellar solutions. It is discussed how experimental constraints from the measurements in the Solar System restrict the form of f(R) theories. Moreover, it is shown that models, which do not differ from general relativity at the weak field scale of the Solar System, can produce very different predictions for dense stars like neutron stars. Due to the nature of f(R) models, the role of independent connection of the spacetime is emphasized throughout the thesis.

Synthesis of plane linkages to generate functions of two variables using point-position reduction—Part 1. Rotary inputs and output

The paper presents simple graphical procedures for position synthesis of plane linkage mechanisms to generate functions of two independent variables. The procedures are based on point-position reduction and permit synthesis of the linkage to satisfy up to six arbitrarily selected precision positions.

Synthesis of plane linkages to generate functions of two variables using point position reduction—II. Sliding inputs and outputs

The paper presents simple graphical procedures for the position synthesis of plane linkage mechanisms with sliding inputs and output to generate functions of two independent variables. The procedures are based on point position reduction and permit synthesis of the linkage to satisfy up to five arbitrarily selected precision positions.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Effect of process variables on die-billet temperature history in a slow speed hot coining type process

A computer code is developed as a part of an ongoing project on computer aided process modelling of forging operation, to simulate heat transfer in a die-billet system. The code developed on a stage-by-stage technique is based on an Alternating Direction Implicit scheme. The experimentally validated code is used to study the effect of process specifics such as preheat die temperature, machine ascent time, rate of deformation, and dwell time on the thermal characteristics in a batch coining operation where deformation is restricted to surface level only.

Estimation of variables at ungaged locations by empirical orthogonal functions

A technique based on empirical orthogonal functions is used to estimate hydrologic time-series variables at ungaged locations. The technique is applied to estimate daily and monthly rainfall, temperature and runoff values. The accuracy of the method is tested by application to locations where data are available. The second-order characteristics of the estimated data are compared with those of the observed data. The results indicate that the method is quick and accurate.