The use of neurocognitive methods in assessing health communication messages: A systematic review

We review 20 studies that examined persuasive processing and outcomes of health messages using neurocognitive measures. The results suggest that cognitive processes and neural activity in regions thought to reflect self-related processing may be more prominent in the persuasive process of self-relevant messages. Furthermore, activity in the medial prefrontal cortex (MPFC), the superior temporal gyrus, and the middle frontal gyrus were identified as predictors of message effectiveness, with the MPFC accounting for additional variance in behaviour change beyond that accounted for by self-report measures. Incorporating neurocognitive measures may provide a more comprehensive understanding of the processing and outcomes of health messages.

The study of genetic diversity and population structure of the Korean fleshy shrimp, Fenneropenaeus chinensis, using newly developed microsatellite markers

The fleshy shrimp, Fenneropenaeus chinensis, is the family of Penaeidae and one of the most economically important marine culture species in Korea. However, its genetic characteristics have never been studied. In this study, a total of 240 wild F. chinensis individuals were collected from four locations as follows: Narodo (NRD, n = 60), Beopseongpo (BSP, n = 60), Chaesukpo (CSP, n = 60), and Cheonsuman (CSM, n = 60). Genetic variability and the relationships among four wild F. chinensis populations were analyzed using 13 newly developed microsatellite loci. Relatively high levels of genetic variability (mean allelic richness = 16.87; mean heterozygosity = 0.845) were found among localities. Among the 52 population loci, 13 showed significant deviation from the Hardy–Weinberg equilibrium. Neighbor-joining, principal coordinate, and molecular variance analyses revealed the presence of three subpopulations (NRD, CSM, BSP and CSP), which was consistent with clustering based on genetic distance. The mean observed heterozygosity values of the NRD, CSM, BSP, and CSP populations were 0.724, 0.821, 0.814, and 0.785 over all loci, respectively. These genetic variability and differentiation results of the four wild populations can be applied for future genetic improvement using selective breeding and to design suitable management guidelines for Korean F. chinensis culture.

Genetic characterization of field-evolved resistance to phosphine in the rusty grain beetle, Cryptolestes ferrugineus (Laemophloeidae: Coleoptera)

Inheritance of resistance to phosphine fumigant was investigated in three field-collected strains of rusty grain beetle, Cryptolestes ferrugineus, Susceptible (S-strain), Weakly Resistant (Weak-R) and Strongly Resistant (Strong-R). The strains were purified for susceptibility, weak resistance and strong resistance to phosphine, respectively, to ensure homozygosity of resistance genotype. Crosses were established between S-strain × Weak-R, S-strain × Strong-R and Weak-R × Strong-R, and the dose mortality responses to phosphine of these strains and their F1, F2 and F1-backcross progeny were obtained. The fumigations were undertaken at 25 °C and 55% RH for 72 h. Weak-R and Strong-R showed resistance factors of 6.3 × and 505 × compared with S-strain at the LC50. Both weak and strong resistances were expressed as incompletely recessive with degrees of dominance of − 0.48 and − 0.43 at the LC50, respectively. Responses of F2 and F1-backcross progeny indicated the existence of one major gene in Weak-R, and at least two major genes in Strong-R, one of which was allelic with the major factor in Weak-R. Phenotypic variance analyses also estimated that the number of independently segregating genes conferring weak resistance was 1 (nE = 0.89) whereas there were two genes controlling strong resistance (nE = 1.2). The second gene, unique to Strong-R, interacted synergistically with the first gene to confer a very high level of resistance (~ 80 ×). Neither of the two major resistance genes was sex linked. Despite the similarity of the genetics of resistance to that previously observed in other pest species, a significant proportion (~ 15 to 30%) of F1 individuals survived at phosphine concentrations higher than predicted. Thus it is likely that additional dominant heritable factors, present in some individuals in the population, also influenced the resistance phenotype. Our results will help in understanding the process of selection for phosphine resistance in the field which will inform resistance management strategies. In addition, this information will provide a basis for the identification of the resistance genes.

Genetic characterization of field-evolved resistance to phosphine in the rusty grain beetle, Cryptolestes ferrugineus (Laemophloeidae: Coleoptera)

Inheritance of resistance to phosphine fumigant was investigated in three field-collected strains of rusty grain beetle, Cryptolestes ferrugineus, Susceptible (S-strain), Weakly Resistant (Weak-R) and Strongly Resistant (Strong-R). The strains were purified for susceptibility, weak resistance and strong resistance to phosphine, respectively, to ensure homozygosity of resistance genotype. Crosses were established between S-strain × Weak-R, S-strain × Strong-R and Weak-R × Strong-R, and the dose mortality responses to phosphine of these strains and their F1, F2 and F1-backcross progeny were obtained. The fumigations were undertaken at 25 °C and 55% RH for 72 h. Weak-R and Strong-R showed resistance factors of 6.3 × and 505 × compared with S-strain at the LC50. Both weak and strong resistances were expressed as incompletely recessive with degrees of dominance of − 0.48 and − 0.43 at the LC50, respectively. Responses of F2 and F1-backcross progeny indicated the existence of one major gene in Weak-R, and at least two major genes in Strong-R, one of which was allelic with the major factor in Weak-R. Phenotypic variance analyses also estimated that the number of independently segregating genes conferring weak resistance was 1 (nE = 0.89) whereas there were two genes controlling strong resistance (nE = 1.2). The second gene, unique to Strong-R, interacted synergistically with the first gene to confer a very high level of resistance (~ 80 ×). Neither of the two major resistance genes was sex linked. Despite the similarity of the genetics of resistance to that previously observed in other pest species, a significant proportion (~ 15 to 30%) of F1 individuals survived at phosphine concentrations higher than predicted. Thus it is likely that additional dominant heritable factors, present in some individuals in the population, also influenced the resistance phenotype. Our results will help in understanding the process of selection for phosphine resistance in the field which will inform resistance management strategies. In addition, this information will provide a basis for the identification of the resistance genes.

Estimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements

Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.

Computational Methods for Detecting Large-Scale Chromosome Rearrangements in SNP Data

Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

Optimal adaptive sequential spatial sampling of soil using pair-copulas

A spatial sampling design that uses pair-copulas is presented that aims to reduce prediction uncertainty by selecting additional sampling locations based on both the spatial configuration of existing locations and the values of the observations at those locations. The novelty of the approach arises in the use of pair-copulas to estimate uncertainty at unsampled locations. Spatial pair-copulas are able to more accurately capture spatial dependence compared to other types of spatial copula models. Additionally, unlike traditional kriging variance, uncertainty estimates from the pair-copula account for influence from measurement values and not just the configuration of observations. This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination. The proposed design methodology is applied to a soil contamination example from the Swiss Jura region. A partial redesign of the original sampling configuration demonstrates the potential of the proposed methodology.

Sleep quantity and quality during heat-based training and the effects of cold-water immersion recovery

- Introduction Heat-based training (HT) is becoming increasingly popular as a means of inducing acclimation before athletic competition in hot conditions and/or to augment the training impulse beyond that achieved in thermo-neutral conditions. Importantly, current understanding of the effects of HT on regenerative processes such as sleep and the interactions with common recovery interventions remain unknown. This study aimed to examine sleep characteristics during five consecutive days of training in the heat with the inclusion of cold-water immersion (CWI) compared to baseline sleep patterns. - Methods Thirty recreationally-trained males completed HT in 32 ± 1 °C and 60% rh for five consecutive days. Conditions included: 1) 90 min cycling at 40 % power at VO2max (Pmax) (90CONT; n = 10); 90 min cycling at 40 % Pmax with a 20 min CWI (14 ± 1 °C; 90CWI; n = 10); and 30 min cycling alternating between 40 and 70 % Pmax every 3 min, with no recovery intervention (30HIT; n = 10). Sleep quality and quantity was assessed during HT and four nights of 'baseline' sleep (BASE). Actigraphy provided measures of time in and out of bed, sleep latency, efficiency, total time in bed and total time asleep, wake after sleep onset, number of awakenings, and wakening duration. Subjective ratings of sleep were also recorded using a 1-5 Likert scale. Repeated measures analysis of variance (ANOVA) was completed to determine effect of time and condition on sleep quality and quantity. Cohen's d effect sizes were also applied to determine magnitude and trends in the data. - Results Sleep latency, efficiency, total time in bed and number of awakenings were not significantly different between BASE and HT (P > 0.05). However, total time asleep was significantly reduced (P = 0.01; d = 1.46) and the duration periods of wakefulness after sleep onset was significantly greater during HT compared with BASE (P = 0.001; d = 1.14). Comparison between training groups showed latency was significantly higher for the 30HIT group compared to 90CONT (P = 0.02; d = 1.33). Nevertheless, there were no differences between training groups for sleep efficiency, total time in bed or asleep, wake after sleep onset, number of awakenings or awake duration (P > 0.05). Further, cold-water immersion recovery had no significant effect on sleep characteristics (P > 0.05). - Discussion Sleep plays an important role in athletic recovery and has previously been demonstrated to be influenced by both exercise training and thermal strain. Present data highlight the effect of HT on reduced sleep quality, specifically reducing total time asleep due to longer duration awake during awakenings after sleep onset. Importantly, although cold water recovery accelerates the removal of thermal load, this intervention did not blunt the negative effects of HT on sleep characteristics. - Conclusion Training in hot conditions may reduce both sleep quantity and quality and should be taken into consideration when administering this training intervention in the field.

HR-MAS NMR spectroscopy shows regional metabolite variation in bovine articular cartilage

Mechanical stress is an important external factor effecting the development and maintenance of articular cartilage. The metabolite profile of diseased cartilage has been well studied but there is limited information about the variation in metabolite profile of healthy cartilage. With the importance of load in maintaining healthy cartilage, regional differences in metabolite profile associated with differences in load may provide information on how load contributes to the maintenance of healthy cartilage. HR-MAS NMR spectroscopy allows the assessment of tissue samples without modification and was used for assessing the difference in metabolic profile between the load bearing and non-load bearing regions of the bovine articular cartilage. In this preliminary study, we examined cartilage from tibia and femur of four knee joints. Sixteen pairs of 1D-NOESY spectra were acquired. Principle component analysis (PCA) identified chemical shifts responsible for variance. SBASE (AMIX) and the Human Metabolome Database were used in conjunction with previous reported cartilage data for identifying metabolites associated with the PCA results. The major contributors to load-related differences in metabolite profile were N-acetyl groups, lactate and phosphocholine peaks. Integrals of these regions were further analysed using a Student's t-test. In load bearing cartilage regions. N-acetyl groups and phosphocholine were found at significantly higher concentration (p < 0.05 and p < 0.005, respectively) in both femur and tibia, while lactate was reduced in load bearing cartilage (p < 0.005). The results of this pilot HR-MAS NMR study demonstrate its ability to provide useful metabolite information for healthy cartilage.

Robust and High-resolution Voiced/Unvoiced Classification in Noisy Speech Using A Signal Smoothness Criterion

We propose a novel technique for robust voiced/unvoiced segment detection in noisy speech, based on local polynomial regression. The local polynomial model is well-suited for voiced segments in speech. The unvoiced segments are noise-like and do not exhibit any smooth structure. This property of smoothness is used for devising a new metric called the variance ratio metric, which, after thresholding, indicates the voiced/unvoiced boundaries with 75% accuracy for 0dB global signal-to-noise ratio (SNR). A novelty of our algorithm is that it processes the signal continuously, sample-by-sample rather than frame-by-frame. Simulation results on TIMIT speech database (downsampled to 8kHz) for various SNRs are presented to illustrate the performance of the new algorithm. Results indicate that the algorithm is robust even in high noise levels.

Two Stage Transform Vector Quantization of LSFs for Wideband Speech Coding

We investigate the use of a two stage transform vector quantizer (TSTVQ) for coding of line spectral frequency (LSF) parameters in wideband speech coding. The first stage quantizer of TSTVQ, provides better matching of source distribution and the second stage quantizer provides additional coding gain through using an individual cluster specific decorrelating transform and variance normalization. Further coding gain is shown to be achieved by exploiting the slow time-varying nature of speech spectra and thus using inter-frame cluster continuity (ICC) property in the first stage of TSTVQ method. The proposed method saves 3-4 bits and reduces the computational complexity by 58-66%, compared to the traditional split vector quantizer (SVQ), but at the expense of 1.5-2.5 times of memory.

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.

Studies on the variants of the protein toxins ricin and abrin

his study elucidates some structural and biological features of galactose-binding variants of the cytotoxic proteins ricin and abrin. An isolation procedure is reported for ricin variants from Ricinus communis seeds by using lactamyl-Sepharose affinity matrix, similar to that reported previously for variants of abrin from Abrus precatorius seeds [Hegde, R., Maiti, T. K. & Podder, S. K. (1991) Anal. Biochem. 194, 101–109]. Ricin variants, subfractionated on carboxymethyl-Sepharose CL-6B ion-exchange chromatography, were characterized further by SDS/PAGE, IEF and a binding assay. Based on the immunological cross-reactivity of antibody raised against a single variant of each of ricin and abrin, it was established that all the variants of the corresponding type are immunologically indistinguishable. Analysis of protein titration curves on an immobilized pH gradient indicated that variants of abrin I differ from other abrin variants, mainly in their acidic groups and that variance in ricin is a cause of charge substitution. Detection of subunit variants of proteins by two-dimensional gel electrophoresis showed that there are twice as many subunit variants as there are variants of holoproteins, suggesting that each variant has a set of subunit variants, which, although homologous, are not identical to the subunits of any other variant with respect to pI. Seeds obtained from polymorphic species of R. communis showed no difference in the profile of toxin variants, as analyzed by isoelectric focussing. Toxin variants obtained from red and white varieties of A. precatorius, however, showed some difference in the number of variants as well as in their relative intensities. Furthermore, variants analyzed from several single seeds of A. precatorius red type revealed a controlled distribution of lectin variants in three specific groups, indicating an involvement of at least three genes in the production of Abrus lectins. The complete absence or presence of variants in each group suggested a post-translational differential proteolytic processing, a secondary event in the production of abrin variants.

Evolutionary Genetics in the WIld : from Populations to Individuals

Predicting evolutionary outcomes and reconstructing past evolutionary transitions are among the main goals of evolutionary biology. Ultimately, understanding the mechanisms of evolutionary change will also provide answers to the timely question of whether and how organisms will adapt to changing environmental conditions. In this thesis, I have investigated the relative roles of natural selection, random genetic drift and genetic correlations in the evolution of complex traits at different levels of organisation from populations to individuals. I have shown that natural selection has been the driving force behind body shape divergence of marine and freshwater threespine stickleback (Gasterosteus aculeatus) populations, while genetic drift may have played a significant role in the more fine scale divergence among isolated freshwater populations. These results are concurrent with the patterns that have emerged in the published studies comparing the relative importance of natural selection and genetic drift as explanations for population divergence in different traits and taxa. I have also shown that body shape and armour divergence among threespine stickleback populations is likely to be biased by the patterns of genetic variation and covariation. Body shape and armour variation along the most likely direction of evolution the direction of maximum genetic variance reflects the general patterns of variation observed wild populations across the distribution range of the threespine stickleback. Conversely, it appears that genetic correlations between the sexes have not imposed significant constraints on the evolution of sexual dimorphism in threespine stickleback body shape and armour. I have demonstrated that the patterns of evolution seen in the wild can be experimentally recreated to tease out the effects of different selection agents in detail. In addition, I have shown how important it is to take into account the correlative nature of traits, when making interpretations about the effects of natural selection on individual traits. Overall, this thesis provides a demonstration of how considering the relative roles of different mechanism of evolutionary change at different levels of organisation can aid in an emergence of a comprehensive picture of how adaptive divergence in wild populations occurs.

Effect of soil variability on the bearing capacity of clay and in slope stability problems

Site-specific geotechnical data are always random and variable in space. In the present study, a procedure for quantifying the variability in geotechnical characterization and design parameters is discussed using the site-specific cone tip resistance data (qc) obtained from static cone penetration test (SCPT). The parameters for the spatial variability modeling of geotechnical parameters i.e. (i) existing trend function in the in situ qc data; (ii) second moment statistics i.e. analysis of mean, variance, and auto-correlation structure of the soil strength and stiffness parameters; and (iii) inputs from the spatial correlation analysis, are utilized in the numerical modeling procedures using the finite difference numerical code FLAC 5.0. The influence of consideration of spatially variable soil parameters on the reliability-based geotechnical deign is studied for the two cases i.e. (a) bearing capacity analysis of a shallow foundation resting on a clayey soil, and (b) analysis of stability and deformation pattern of a cohesive-frictional soil slope. The study highlights the procedure for conducting a site-specific study using field test data such as SCPT in geotechnical analysis and demonstrates that a few additional computations involving soil variability provide a better insight into the role of variability in designs.