Search results for "Proximate"

Comparative analysis of the proximate and elemental composition of the blue crab Callinectes sapidus, the warty crab Eriphia verrucosa, and the edibl…

2016

AbstractThe proximate composition and element contents of claw muscle tissue of Atlantic blue crabs (Callinectes sapidus) were compared with the native warty crab (Eriphia verrucosa) and the commercially edible crab (Cancer pagurus). The scope of the analysis was to profile the chemical characteristics and nutritive value of the three crab species. Elemental fingerprints showed significant inter-specific differences, whereas non-significant variations in the moisture and ash contents were observed. In the blue crab, protein content was significantly lower than in the other two species, while its carbon content resulted lower than that characterizing only the warty crab. Among micro-elements…

Spontaneous quantity discrimination of artificial flowers by foraging honeybees

2020

ABSTRACTMany animals need to process numerical and quantity information in order to survive. Spontaneous quantity discrimination allows differentiation between two or more quantities without reinforcement or prior training on any numerical task. It is useful for assessing food resources, aggressive interactions, predator avoidance and prey choice. Honeybees have previously demonstrated landmark counting, quantity matching, use of numerical rules, quantity discrimination and arithmetic, but have not been tested for spontaneous quantity discrimination. In bees, spontaneous quantity discrimination could be useful when assessing the quantity of flowers available in a patch and thus maximizing f…

Evaluating the impact of vegetal and microalgae protein sources on proximate composition, amino acid profile, and physicochemical properties of ferme…

2018

Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

2020

Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…

Best proximity point theorems for proximal cyclic contractions

2017

The purpose of this article is to compute a global minimizer of the function $$x\longrightarrow d(x, Tx)$$ , where T is a proximal cyclic contraction in the framework of a best proximally complete space, thereby ensuring the existence of an optimal approximate solution, called a best proximity point, to the equation $$Tx=x$$ when T is not necessarily a self-mapping.

A heuristic, iterative algorithm for change-point detection in abrupt change models

2017

Change-point detection in abrupt change models is a very challenging research topic in many fields of both methodological and applied Statistics. Due to strong irregularities, discontinuity and non-smootheness, likelihood based procedures are awkward; for instance, usual optimization methods do not work, and grid search algorithms represent the most used approach for estimation. In this paper a heuristic, iterative algorithm for approximate maximum likelihood estimation is introduced for change-point detection in piecewise constant regression models. The algorithm is based on iterative fitting of simple linear models, and appears to extend easily to more general frameworks, such as models i…

Use of Aloe vera gel-based edible coating with natural anti-browning and anti-oxidant additives to improve post-harvest quality of fresh-cut 'Fuji' a…

2020

Recently, there is increasing use of edible and biodegradable films and packaging that are both environmentally friendly and functional for storage and market distribution. Fresh-cut &lsquo

Genetic structure and differentiation from early bronze age in the mediterranean island of sicily: Insights from ancient mitochondrial genomes

2022

Sicily is one of the main islands of the Mediterranean Sea, and it is characterized by a variety of archaeological records, material culture and traditions, reflecting the history of migrations and populations’ interaction since its first colonization, during the Paleolithic. These deep and complex demographic and cultural dynamics should have affected the genomic landscape of Sicily at different levels; however, the relative impact of these migrations on the genomic structure and differentiation within the island remains largely unknown. The available Sicilian modern genetic data gave a picture of the current genetic structure, but the paucity of ancient data did not allow so far to make p…

The influence of temperature on growth and proximate body composition of under yearling Lake Inari arctic char (Salvelinus alpinus (L.))

1997

The growth of underyearling Lake Inari arctic char was studied in groups of fish held at 5.9, 8.7, 12.1, 15.1 and 18.0 °C for 31 days. Growth rate increased with increasing water temperature, reached a peak at 15.1 °C, and then declined. The temperature influence on relative growth was expressed as a non-linear function. There were differences in body composition between fish reared at different temperatures: percentage water being highest at the lowest temperature, whereas energy content was highest in the fish held at the three highest temperatures. The body wet weight explained most of the variance in water content and it is suggested that this may also apply to other body constituents.

Investigating the Impact of Radiation-Induced Soft Errors on the Reliability of Approximate Computing Systems

2020

International audience; Approximate Computing (AxC) is a well-known paradigm able to reduce the computational and power overheads of a multitude of applications, at the cost of a decreased accuracy. Convolutional Neural Networks (CNNs) have proven to be particularly suited for AxC because of their inherent resilience to errors. However, the implementation of AxC techniques may affect the intrinsic resilience of the application to errors induced by Single Events in a harsh environment. This work introduces an experimental study of the impact of neutron irradiation on approximate computing techniques applied on the data representation of a CNN.