Implementation of Self-Noise Suppression Techniques for Ultrasonic Correlation Systems

Pseudo-random signal correlation techniques can improve the flaw detection capability of ultrasonic NDE systems. While the correlation-based systems provide significant improvement in the signal-to-noise ratio compared to pulsed systems, their performance is limited by the so-called “self-noise” of the system. Self-noise is a result of imperfect autocorrelation characteristics of the excitation signal. Last year, we suggested some techniques for improving the flaw detection capability of continuous-mode ultrasonic NDE systems [1]. These systems use a continuously transmitted coded waveform as an excitation signal, and the received signal is processed through a correlation filter. This year, we present another new approach and demonstrate performance results and the practicability of each approach.</p

Age-Related Attenuation of Dominant Hand Superiority

The decline of motor performance of the human hand-arm system with age is well-documented. While dominant hand performance is superior to that of the non-dominant hand in young individuals, little is known of possible age-related changes in hand dominance. We investigated age-related alterations of hand dominance in 20 to 90 year old subjects. All subjects were unambiguously right-handed according to the Edinburgh Handedness Inventory. In Experiment 1, motor performance for aiming, postural tremor, precision of arm-hand movement, speed of arm-hand movement, and wrist-finger speed tasks were tested. In Experiment 2, accelerometer-sensors were used to obtain objective records of hand use in everyday activities

Prevalence of hepatitis B and C markers in high-risk hospitalised patients in Crete: a five-year observational study

BACKGROUND: So far the prevalence of viral hepatitis infection in hospitalized patients has not been extensively studied. Therefore we conducted the present five-year observational study to evaluate the prevalence of HBV and HCV infection in high-risk hospitalized patients of Crete, the largest Greek island, Due to the homogeneous population, epidemiological studies can be accurately done. METHODS: The study was carried out in two out of four District General Hospitals, and in the University Hospital of the island. Markers for HBV and HCV were studied and statistically evaluated according to age, sex and geographical area, in a well-defined hospitalized population. RESULTS: The total prevalence of HBsAg and anti-HCV in the three prefectures during the five-year study is 2.66% and 4.75% respectively. Overall the relative risks were higher in males than females for each hepatitis marker (p < 0.001). Higher prevalence of HBcAb was found in the 41–60 years age group for both sexes (males 36.17%, females 27.38%). Peak HBsAg prevalence was found in the age group of 21–40 and 41–60 years for males (5.4%) and females (3.09%) respectively. Anti-HCV prevalence increases with age reaching the highest prevalence in the age group of 41–60 years for males (7.19%) and in the 61–90 years age group for females (7.16%). For both sexes significant differences between the three locations were identified. For HBsAg a higher prevalence in Heraklion (3.96%) compared to Chania (2.30%, males: p < 0.0001, females: p < 0.05) and Rethymnon (1.45%, males: p < 0.01, females: p < 0.0001) was detected. For HCV a significantly higher prevalence in Heraklion (6.54%) compared to Chania (2.39%, males: p < 0.001, females: p < 0.001) but not in Rethymnon (5.15%, NS). A lower prevalence rate of HBcAb in Heraklion compared to Chania (20.07% versus 23.05%, males: p < 0.001, females: p < 0.001) was found. CONCLUSIONS: These results were possibly overestimated, but nevertheless reflect the situation of the general population within the island as shown by our previous publications in other study groups. Moreover they contribute to the mapping of viral hepatitis prevalence in a geographical area of Southern Europe and may be helpful in planning public health interventional strategies

Climate and crown damage drive tree mortality in southern Amazonian edge forests

This is the final version. Available on open access from Wiley via the DOI in this recordData availability statement: The data are available as a data package on ForestPlots.net: https://doi.org/10.5521/forestplots.net/2022_1 (Reis et al., 2022). The tree-level data used in Figure 5 are available on request from ForestPlot.net: https://www.forestplots.net/en/join-forestplots/working-with-dataTree death is a key process for our understanding of how forests are and will respond to global change. The extensive forests across the southern Amazonia edge—the driest, warmest and most fragmented of the Amazon regions—provide a window onto what the future of large parts of Amazonia may look like. Understanding tree mortality and its drivers here is essential to anticipate the process across other parts of the basin. Using 10 years of data from a widespread network of long-term forest plots, we assessed how trees die (standing, broken or uprooted) and used generalised mixed-effect models to explore the contribution of plot-, species- and tree-level factors to the likelihood of tree death. Most trees died from stem breakage (54%); a smaller proportion died standing (41%), while very few were uprooted (5%). The mortality rate for standing dead trees was greatest in forests subject to the most intense dry seasons. While trees with the crown more exposed to light were more prone to death from mechanical damage, trees less exposed were more susceptible to death from drought. At the species level, mortality rates were lowest for those species with the greatest wood density. At the individual tree level, physical damage to the crown via branch breakage was the strongest predictor of tree death. Synthesis. Wind- and water deficit-driven disturbances are the main causes of tree death in southern Amazonia edge which is concerning considering the predicted increase in seasonality for Amazonia, especially at the edge. Tree mortality here is greater than any in other Amazonian region, thus any increase in mortality here may represent a tipping point for these forests

Drought generates large, long-term changes in tree and liana regeneration in a monodominant Amazon forest

The long-term dynamics of regeneration in tropical forests dominated by single tree species remains largely undocumented, yet is key to understanding the mechanisms by which one species can gain dominance and resist environmental change. We report here on the long-term regeneration dynamics in a monodominant stand of Brosimum rubescens Taub. (Moraceae) at the southern border of the Amazon forest. Here the climate has warmed and dried since the mid-1990′s. Twenty-one years of tree and liana regeneration were evaluated in four censuses in 30 plots by assessing species abundance, dominance, and diversity in all regeneration classes up to 5 cm diameter. The density of B. rubescens seedlings declined markedly, from 85% in 1997 to 29% in 2018 after the most intense El Niño-driven drought. While the fraction contributed by other tree species changed little, the relative density of liana seedlings increased from just 1 to 54% and three-quarters of liana species underwent a ten-fold or greater increase in abundance. The regeneration community experienced a high rate of species turnover, with changes in the overall richness and species diversity determined principally by lianas, not trees. Long-term maintenance of monodominance in this tropical forest is threatened by a sharp decline in the regeneration of the monodominant species and the increase in liana density, suggesting that monodominance will prove to be a transitory condition. The close association of these rapid changes with drying indicates that monodominant B. rubescens forests are impacted by drought-driven changes in regeneration, and therefore are particularly sensitive to climatic change

Harvest: an open-source tool for the validation and improvement of peptide identification metrics and fragmentation exploration

<p>Abstract</p> <p>Background</p> <p>Protein identification using mass spectrometry is an important tool in many areas of the life sciences, and in proteomics research in particular. Increasing the number of proteins correctly identified is dependent on the ability to include new knowledge about the mass spectrometry fragmentation process, into computational algorithms designed to separate true matches of peptides to unidentified mass spectra from spurious matches. This discrimination is achieved by computing a function of the various features of the potential match between the observed and theoretical spectra to give a numerical approximation of their similarity. It is these underlying "metrics" that determine the ability of a protein identification package to maximise correct identifications while limiting false discovery rates. There is currently no software available specifically for the simple implementation and analysis of arbitrary novel metrics for peptide matching and for the exploration of fragmentation patterns for a given dataset.</p> <p>Results</p> <p>We present Harvest: an open source software tool for analysing fragmentation patterns and assessing the power of a new piece of information about the MS/MS fragmentation process to more clearly differentiate between correct and random peptide assignments. We demonstrate this functionality using data metrics derived from the properties of individual datasets in a peptide identification context. Using Harvest, we demonstrate how the development of such metrics may improve correct peptide assignment confidence in the context of a high-throughput proteomics experiment and characterise properties of peptide fragmentation.</p> <p>Conclusions</p> <p>Harvest provides a simple framework in C++ for analysing and prototyping metrics for peptide matching, the core of the protein identification problem. It is not a protein identification package and answers a different research question to packages such as Sequest, Mascot, X!Tandem, and other protein identification packages. It does not aim to maximise the number of assigned peptides from a set of unknown spectra, but instead provides a method by which researchers can explore fragmentation properties and assess the power of novel metrics for peptide matching in the context of a given experiment. Metrics developed using Harvest may then become candidates for later integration into protein identification packages.</p