104 research outputs found

    Intermittent 20-HZ-photic stimulation leads to a uniform reduction of alpha-Global Field Power in healthy volunteers

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    19-channel-EEGs were recorded from scalp surface of 30 healthy subjects (16m, 14f, mean age: 34 ys, SD: 11.7 ys) at rest and under IPS (Intermittent Photic Stimulation) at rates of 5, 10 and 20 Hertz (Hz). Digitalized data underwent spectral analysis with fast fourier transformation (FFT) yielding the basis for the computation of global field power (GFP). For quantification GFP values in the frequency ranges of 5, 10 and 20 Hz at rest were divided by the corresponding data gained under IPS. While ratios from PDE data showed no stable parameter due to high interindividual variability, ratios of alpha-power turned out to be uniform in all subjects: IPS at 20 Hz always led to a suppression of alpha-power. Dividing alpha-GFP at rest by alpha-GFP under 20-Hz IPS thus resulted in a ratio <1. We conclude that ratios from GFP data are a stable diagnostic paradigma

    The London Workshop on the Biogeography and Connectivity of the Clarion-Clipperton Zone

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    Recent years have seen a rapid increase in survey and sampling expeditions to the Clarion-Clipperton Zone (CCZ) abyssal plain, a vast area of the central Pacific that is currently being actively explored for deep-sea minerals (ISA, 2016). Critical to the development of evidence-based environmental policy in the CCZ are data on the biogeography and connectivity of species at a CCZ-regional level. The London Workshop on the Biogeography and Connectivity of the CCZ was convened to support the integration and synthesis of data from European Union (EU) CCZ projects, supported by the EU Managing Impacts of Deep-Sea Resource Exploitation (MIDAS) and EU Joint Programming Initiative Healthy and Productive Seas and Oceans (JPI Oceans) projects. The London Workshop had three clear goals: (1) To explore, review and synthesise the latest molecular biogeography and connectivity data from across recent CCZ cruises from both contractor and academia-funded projects; (2) To develop complementary and collaborative institutional and program-based academic publication plans to avoid duplication of effort and ensure maximum collaborative impact; (3) To plan a joint synthetic data publication highlighting key results from a range of planned molecular biogeography/connectivity publications. 32 participants attended the workshop at the Natural History Museum in London from 10-12 May 2016. Presentations and discussions are summarised in this report covering (1) overviews of current CCZ environmental projects, (2) policy and industry perspectives, (3) synthesis of DNA taxonomy and biogeography studies, (4) summaries of the latest population genetic studies, (5) summaries of the latest broader morphological context, (6) an overview of publication and proposal plans to maximise collaborative opportunities and finally a series of workshop recommendations

    Seasonal pattern of peptic ulcer hospitalizations: analysis of the hospital discharge data of the Emilia-Romagna region of Italy

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    BACKGROUND: Previous studies have reported seasonal variation in peptic ulcer disease (PUD), but few large-scale, population-based studies have been conducted. METHODS: To verify whether a seasonal variation in cases of PUD (either complicated or not complicated) requiring acute hospitalization exists, we assessed the database of hospital admissions of the region Emilia Romagna (RER), Italy, obtained from the Center for Health Statistics, between January 1998 and December 2005. Admissions were categorized by sex, age ( or = 75 yrs), site of PUD lesion (stomach or duodenum), main complication (hemorrhage or perforation), and final outcome (intended as fatal outcome: in-hospital death; nonfatal outcome: patient discharged alive). Temporal patterns in PUD admissions were assessed in two ways, considering a) total counts per single month and season, and b) prevalence proportion, such as the monthly prevalence of PUD admissions divided by the monthly prevalence of total hospital admissions, to assess if the temporal patterns in the raw data might be the consequence of seasonal and annual variations in hospital admissions per se in the region. For statistical analysis, the chi2 test for goodness of fit and inferential chronobiologic method (Cosinor and partial Fourier series) were used. RESULTS: Of the total sample of PUD patients (26,848 [16,795 males, age 65 +/- 16 yrs; 10,053 females, age 72 +/- 15 yrs, p or = 75 yrs of age. There were more cases of duodenal (DU). (89.8%) than gastric ulcer (GU) (3.6%), and there were 1,290 (4.8%) fatal events. Data by season showed a statistically difference with the lowest proportion of PUD hospital admissions in summer (23.3%) (p < 0.001), for total cases and rather all subgroups. Chronobiological analysis identified three major peaks of PUD hospitalizations (September-October, January-February, and April-May) for the whole sample (p = 0.035), and several subgroups, with nadir in July. Finally, analysis of the monthly prevalence proportions yielded a significant (p = 0.025) biphasic pattern with a main peak in August-September-October, and a secondary one in January-February. CONCLUSIONS: A seasonal variation in PUD hospitalization, characterized by three peaks of higher incidence (Autumn, Winter, and Spring) is observed. When data corrected by monthly admission proportions are analyzed, late summer-autumn and winter are confirmed as higher risk periods. The underlying pathophysiologic mechanisms are unknown, and need further studies. In subjects at higher risk, certain periods of the year could deserve an appropriate pharmacological protection to reduce the risk of PUD hospitalization

    An overview of the recent developments on fructooligosaccharide production and applications

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    Over the past years, many researchers have suggested that deficiencies in the diet can lead to disease states and that some diseases can be avoided through an adequate intake of relevant dietary components. Recently, a great interest in dietary modulation of the human gut has been registered. Prebiotics, such as fructooligosaccharides (FOS), play a key role in the improvement of gut microbiota balance and in individual health. FOS are generally used as components of functional foods, are generally regarded as safe (generally recognized as safe status—from the Food and Drug Administration, USA), and worth about 150€ per kilogram. Due to their nutrition- and health-relevant properties, such as moderate sweetness, low carcinogenicity, low calorimetric value, and low glycemic index, FOS have been increasingly used by the food industry. Conventionally, FOS are produced through a two-stage process that requires an enzyme production and purification step in order to proceed with the chemical reaction itself. Several studies have been conducted on the production of FOS, aiming its optimization toward the development of more efficient production processes and their potential as food ingredients. The improvement of FOS yield and productivity can be achieved by the use of different fermentative methods and different microbial sources of FOS producing enzymes and the optimization of nutritional and culture parameter; therefore, this review focuses on the latest progresses in FOS research such as its production, functional properties, and market data.Agencia de Inovacao (AdI)-Project BIOLIFE reference PRIME 03/347. Ana Dominguez acknowledges Fundacao para a Ciencia e a Tecnologia, Portugal, for her PhD grant reference SFRH/BD/23083/2005

    Application of Machine Learning Techniques to Parameter Selection for Flight Risk Identification

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    In recent years, the use of data mining and machine learning techniques for safety analysis, incident and accident investigation, and fault detection has gained traction among the aviation community. Flight data collected from recording devices contains a large number of heterogeneous parameters, sometimes reaching up to thousands on modern commercial aircraft. More data is being collected continuously which adds to the ever-increasing pool of data available for safety analysis. However, among the data collected, not all parameters are important from a risk and safety analysis perspective. Similarly, in order to be useful for modern analysis techniques such as machine learning, using thousands of parameters collected at a high frequency might not be computationally tractable. As such, an intelligent and repeatable methodology to select a reduced set of significant parameters is required to allow safety analysts to focus on the right parameters for risk identification. In this paper, a step-by-step methodology is proposed to down-select a reduced set of parameters that can be used for safety analysis. First, correlation analysis is conducted to remove highly correlated, duplicate, or redundant parameters from the data set. Second, a pre-processing step removes metadata and empty parameters. This step also considers requirements imposed by regulatory bodies such as the Federal Aviation Administration and subject matter experts to further trim the list of parameters. Third, a clustering algorithm is used to group similar flights and identify abnormal operations and anomalies. A retrospective analysis is conducted on the clusters to identify their characteristics and impact on flight safety. Finally, analysis of variance techniques are used to identify which parameters were significant in the formation of the clusters. Visualization dashboards were created to analyze the cluster characteristics and parameter significance. This methodology is employed on data from the approach phase of a representative single-aisle aircraft to demonstrate its application and robustness across heterogeneous data sets. It is envisioned that this methodology can be further extended to other phases of flight and aircraft

    Developing grammars in a social context A comparative account of the English of two groups of ethnic minority women

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