130,542 research outputs found
Sull’individuazione delle soglie pluviali di piena nei bacini costieri laziali: i casi studio dei fiumi Marta e Mignone
No full textQuesto lavoro si propone di illustrare l’applicazione di una metodologia per l’individuazione delle soglie pluviali di piena relative a due sezioni critiche appartenenti rispettivamente ai fiumi Marta e Mignone. Inizialmente, viene determinata la sezione idraulica critica dei bacini oggetto di studio e la relativa portata critica, cui si associa, mediante un’analisi statistica, un tempo di ritorno; in seguito si procede alla taratura e verifica del modello A/D rappresentativo del bacino sotteso dalla sezione critica. Infine, mediante una back analysis, vengono determinate le soglie pluviali di piena di cui viene verificata l’affidabilità utilizzando i dati degli eventi salienti di piena disponibili.This work aims to illustrate the application of a methodology for the identification of thresholds rain flood relating to two critical sections belonging respectively to the rivers Marta and Mignone. Initially, the hydraulic section is determined critics of the basins under study and the corresponding critical flow, which is associated, through statistical analysis, a return time, after which we proceed to the calibration and verification of the A / D representative of the basin subtended by the critical section. Finally, through a back analysis, the thresholds are determined rainforests full of whose reliability is verified using the data of the highlights of the full available
Substance use disorders: treatment with genetic potential?
No full textSubstance use disorders are a growing global public health concern. Recognized by the DSM-V and ICD-10 as a chronic psychiatric disorder, substance use disorders cause significant morbidity and mortality, accounting for almost 5% of the global burden of disease. Substance abusers are at increased risk for psychiatric conditions and have higher rates of comorbid disease, including: HIV, Hepatitis B, Hepatitis C, and Tuberculosis. Economically, substance use disorders cost the United States over 193 billion dollars each year through costs incurred by the criminal court system, healthcare costs from increased morbidity, and loss of productivity from disability and incarceration. The negative stigma attached to addicts and addition causes many individuals to deny their illness and avoid treatment. Significant disparities exist in subsets of the US population in both the prevalence of substance use disorders as well as access and referral to treatment. Individuals from the LGBT community, active service members of the US military, military veterans, women and incarcerated individuals face considerable barriers in accessing treatment. These disorders, due to their chronic nature, require long-term prevention efforts and continued treatment throughout the affected individual’s life. Recovered substance abusers are always at risk for relapse, particularly when they lack support, coping skills and understanding from their community. Substance use disorders are affected by environmental and genetic factors, as well as gene-environment interactions. Through the use of better prevention efforts, improved treatment protocols and changes to the criminal justice system, the public health burden in the United States can be lowered, improving the economy, and setting a positive example for other countries to emulate. Incorporating the information known about genetics and addiction into current treatment practices could have significant positive effects on treatment outcomes and future prevention efforts, improving the overall health of the public
SUPPRESSIVE ACTIVITY OF ORGANIC AMENDMENTS ENRICHED WITH MICROBIAL ANTAGONISTS AGAINST FUSARIOSIS OF TOMATO AND CUCURBIT PLANTS
No full textAntifungal Lipopeptides from Bacillus amyloliquefaciens Strain BO7
No full textThree new lipopeptides (1-3) were isolated from the organic extract of Bacillus amyloliquefaciens strain (BO7). These compounds represented the major Constituents (>60%) of the total cell lipids extractable with CHCl(3)/MeOH (2:1). Elucidation of their chemical structure was carried out by spectroscopic analyses, including 1D and 2D NMR spectroscopy, mass spectrometry (MS), and secondary ion mass spectrometry (MS/MS), along with chemical degradation. The compounds are members of the surfactins family and are based on, the heptapeptide Glu-Leu-Leu-Ala-Asp-Leu-Leu, N-acylated to the N-terminal by an (R)-3-hydroxy fatty acid with linear alkyl chains from 16:0 to 18:0 (1-3, respectively). An ester bond between the 3-hydroxyl group of the fatty add and the carboxylic group of the C-terminal amino acid closes a 13, membered lactone ring. The bacterial lipopeptides, particularly compound 3, displayed strong and dose-dependent antifungal activity against the plant pathogenic fungus Fusarium oxysporum
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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