Search results for "techniques"
showing 10 items of 4426 documents
Prove di coltivazione di Calendula (Calendula officinalis L.) in ambiente semi-arido
2008
Inside the family Asteraceae, Marigold is one of the most relevant species bearing some herbal interest. The evaluation of the bio-agronomical and yield response of the species to the field cropping conditions, especially when a low input cropping technique is applied, is the base for its full exploitation. With this objective, a long-term research activity has been started out by the DAAT (Department of Environmental and Land Agronomy) of the University of Palermo in the experimental farm “Sparacia” (Cammarata – AG – Sicily), performing observations on Marigold plants managed with a minimum recourse to external technical inputs (nor pesticides neither chemical weeding, and a light (50 kg h…
Reverse inheritance in statically typed object-oriented programming languages
2010
Reverse inheritance is a new class reuse mechanism, an experimental implementation of which we have built for Eiffel. It enables a more natural design approach, factorization of common features (members), insertion of classes into an existing hierarchy etc. Due to its reuse potential in Eiffel we consider exploring its capabilities in other industrial-strength programming languages like C++, Java and C#.
Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples
2014
Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle …
Estimation of confidence limits for descriptive indexes derived from autoregressive analysis of time series: Methods and application to heart rate va…
2017
The growing interest in personalized medicine requires making inferences from descriptive indexes estimated from individual recordings of physiological signals, with statistical analyses focused on individual differences between/within subjects, rather than comparing supposedly homogeneous cohorts. To this end, methods to compute confidence limits of individual estimates of descriptive indexes are needed. This study introduces numerical methods to compute such confidence limits and perform statistical comparisons between indexes derived from autoregressive (AR) modeling of individual time series. Analytical approaches are generally not viable, because the indexes are usually nonlinear funct…
Sorting of Single Biomolecules based on Fourier Polar Representation of Surface Enhanced Raman Spectra
2016
AbstractSurface enhanced Raman scattering (SERS) spectroscopy becomes increasingly used in biosensors for its capacity to detect and identify single molecules. In practice, a large number of SERS spectra are acquired and reliable ranking methods are thus essential for analysing all these data. Supervised classification strategies, which are the most effective methods, are usually applied but they require pre-determined models or classes. In this work, we propose to sort SERS spectra in unknown groups with an alternative strategy called Fourier polar representation. This non-fitting method based on simple Fourier sine and cosine transforms produces a fast and graphical representation for sor…
Performance Evaluation of a Three- Phase Five-Level Quasi-Z-Source Cascaded H-Bridge for Grid-Connected Applications
2018
In the field of the PV generation, Quasi-Z-source cascaded H-bridge (qZS-CHB) inverters are promising due to their features of modularity and high voltage conversion ratio. Thus, new topology structures and innovative modulation techniques are continuously being developed to improve the performance in terms of voltage stress and harmonic content. This paper proposes an innovative modulation technique that allows reducing the voltage stress and a specially designed grid-connected control strategy is also introduced. Through simulations in MATLAB, it has been validated that the performance of a three-phase five-level qZS-CHB is improved with the proposed solution.
Masonry Compressive Strength Prediction Using Artificial Neural Networks
2019
The masonry is not only included among the oldest building materials, but it is also the most widely used material due to its simple construction and low cost compared to the other modern building materials. Nevertheless, there is not yet a robust quantitative method, available in the literature, which can reliably predict its strength, based on the geometrical and mechanical characteristics of its components. This limitation is due to the highly nonlinear relation between the compressive strength of masonry and the geometrical and mechanical properties of the components of the masonry. In this paper, the application of artificial neural networks for predicting the compressive strength of m…
Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.
2013
Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less). Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing…
Nanomaterials and new biorecognition molecules based surface plasmon resonance biosensors for mycotoxin detection
2019
Mycotoxins are highly toxic secondary metabolites, which may contaminate many types of food and feeds. These toxins have serious health risks for both human and animals. One of the effective ways to prevent food contamination and protect people against mycotoxins is based on timely detection. Several methods like enzyme-linked immunosorbent assay and affinity chromatography are commercially available for this purpose. Nevertheless, sensitive, fast, simple, low-cost, and portable devices are absolutely required for a fast point-of care information and making decisions. Application of biosensors appears to be a possible technique to meet this need for mycotoxins analyze. The present study has…
A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.
2020
Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …