Energy Distribution in disordered elastic Networks

Disordered networks are found in many natural and artificial materials, from gels or cytoskeletal structures to metallic foams or bones. Here, the energy distribution in this type of networks is modeled, taking into account the orientation of the struts. A correlation between the orientation and the energy per unit volume is found and described as a function of the connectivity in the network and the relative bending stiffness of the struts. If one or both parameters have relatively large values, the struts aligned in the loading direction present the highest values of energy. On the contrary, if these have relatively small values, the highest values of energy can be reached in the struts oriented transversally. This result allows explaining in a simple way remodeling processes in biological materials, for example, the remodeling of trabecular bone and the reorganization in the cytoskeleton. Additionally, the correlation between the orientation, the affinity, and the bending-stretching ratio in the network is discussed

Biological synthesis of fluorescent nanoparticles by cadmium and tellurite resistant Antarctic bacteria: exploring novel natural nanofactories

Indexación: Web of ScienceBackground: Fluorescent nanoparticles or quantum dots (QDs) have been intensely studied for basic and applied research due to their unique size-dependent properties. There is an increasing interest in developing ecofriendly methods to synthesize these nanoparticles since they improve biocompatibility and avoid the generation of toxic byproducts. The use of biological systems, particularly prokaryotes, has emerged as a promising alternative. Recent studies indicate that QDs biosynthesis is related to factors such as cellular redox status and antioxidant defenses. Based on this, the mixture of extreme conditions of Antarctica would allow the development of natural QDs producing bacteria. Results: In this study we isolated and characterized cadmium and tellurite resistant Antarctic bacteria capable of synthesizing CdS and CdTe QDs when exposed to these oxidizing heavy metals. A time dependent change in fluorescence emission color, moving from green to red, was determined on bacterial cells exposed to metals. Biosynthesis was observed in cells grown at different temperatures and high metal concentrations. Electron microscopy analysis of treated cells revealed nanometric electron-dense elements and structures resembling membrane vesicles mostly associated to periplasmic space. Purified biosynthesized QDs displayed broad absorption and emission spectra characteristic of biogenic Cd nanoparticles. Conclusions: Our work presents a novel and simple biological approach to produce QDs at room temperature by using heavy metal resistant Antarctic bacteria, highlighting the unique properties of these microorganisms as potent natural producers of nano-scale materials and promising candidates for bioremediation purposes.http://microbialcellfactories.biomedcentral.com/articles/10.1186/s12934-016-0477-

Endmember extraction algorithms from hyperspectral images

During the last years, several high-resolution sensors have been developed for hyperspectral remote sensing applications. Some of these sensors are already available on space-borne devices. Space-borne sensors are currently acquiring a continual stream of hyperspectral data, and new efficient unsupervised algorithms are required to analyze the great amount of data produced by these instruments. The identification of image endmembers is a crucial task in hyperspectral data exploitation. Once the individual endmembers have been identified, several methods can be used to map their spatial distribution, associations and abundances. This paper reviews the Pixel Purity Index (PPI), N-FINDR and Automatic Morphological Endmember Extraction (AMEE) algorithms developed to accomplish the task of finding appropriate image endmembers by applying them to real hyperspectral data. In order to compare the performance of these methods a metric based on the Root Mean Square Error (RMSE) between the estimated and reference abundance maps is used

Some Remarks on the Model Theory of Epistemic Plausibility Models

Classical logics of knowledge and belief are usually interpreted on Kripke models, for which a mathematically well-developed model theory is available. However, such models are inadequate to capture dynamic phenomena. Therefore, epistemic plausibility models have been introduced. Because these are much richer structures than Kripke models, they do not straightforwardly inherit the model-theoretical results of modal logic. Therefore, while epistemic plausibility structures are well-suited for modeling purposes, an extensive investigation of their model theory has been lacking so far. The aim of the present paper is to fill exactly this gap, by initiating a systematic exploration of the model theory of epistemic plausibility models. Like in 'ordinary' modal logic, the focus will be on the notion of bisimulation. We define various notions of bisimulations (parametrized by a language L) and show that L-bisimilarity implies L-equivalence. We prove a Hennesy-Milner type result, and also two undefinability results. However, our main point is a negative one, viz. that bisimulations cannot straightforwardly be generalized to epistemic plausibility models if conditional belief is taken into account. We present two ways of coping with this issue: (i) adding a modality to the language, and (ii) putting extra constraints on the models. Finally, we make some remarks about the interaction between bisimulation and dynamic model changes.Comment: 19 pages, 3 figure

Endmember extraction algorithms from hyperspectral images

During the last years, several high-resolution sensors have been developed for hyperspectral remote sensing applications. Some of these sensors are already available on space-borne devices. Space-borne sensors are currently acquiring a continual stream of hyperspectral data, and new efficient unsupervised algorithms are required to analyze the great amount of data produced by these instruments. The identification of image endmembers is a crucial task in hyperspectral data exploitation. Once the individual endmembers have been identified, several methods can be used to map their spatial distribution, associations and abundances. This paper reviews the Pixel Purity Index (PPI), N-FINDR and Automatic Morphological Endmember Extraction (AMEE) algorithms developed to accomplish the task of finding appropriate image endmembers by applying them to real hyperspectral data. In order to compare the performance of these methods a metric based on the Root Mean Square Error (RMSE) between the estimated and reference abundance maps is used

Super-attracting periodic orbits for a classical third order method

AbstractWe use a classical third order root-finding iterative method for approximating roots of nonlinear equations. We present a procedure for constructing polynomials so that super-attracting periodic orbits of any prescribed period occur when this method is applied. This note can be considered as the second part of our previous study [S. Amat, S. Busquier, S. Plaza, A construction of attracting periodic orbits for some classical third order iterative methods, J. Comput. Appl. Math. 189(1–2) (2006) 22–33]

Efficiency of Artificial Insemination at Natural Estrus in Organic Churra Ewes

Hormonal treatments used in the artificial insemination (AI) of sheep can cause several physiological problems that can affect negatively fertility and animal health; however, AI protocols based on the detection of natural estrus offer a more sustainable option and can achieve high fertility. In this study, an AI protocol at natural estrus in organic Churra sheep was performed. In the first phase (AI protocol development), 125 ewes were exocervically inseminated, and their fertility was assessed based on the following factors: number of AI, physiological state, body condition, estrus detection–AI interval, and vaginal fluids in cervix. That protocol was repeated for six consecutive years. In all individuals, fertilities based on the timing of insemination after estrus detection were very high. Lactating ewes produced better results than did dry ewes, which was probably because of the better feeding of the former. In addition, double insemination increased the fertility of ewes whose estrus was detected within 16 h of onset. Body condition and amount of vaginal fluid were correlated with fertility. Exocervical inseminations at natural estrus can produce acceptable fertility and prolificity in Churra ewes

Performance of Slow-Growing Chickens Fed with Tenebrio molitor Larval Meal as a Full Replacement for Soybean Meal

Insect larval meal is an increasingly common protein source in poultry systems. In this study, the effect of replacing soybean meal with Tenebrio molitor larval meal on the performance of slow-growing chickens was assessed. A total of 128 one-day-old chickens (Colorield) were randomly divided into a control group (C) (n = 64), fed with soybean meal, and an experimental group (TM) (n = 64), fed with T. molitor larvae meal. The chicks were slaughtered after 95 days. Three different isoenergetic and isoproteic diets (F1, F2 and F3) were used for each group. The F1 diet resulted in higher body weight gain and higher feed and water intakes in group C, but a lower feed conversion ratio. Contrarily, diets F2 and F3 did not produce differences in the studied parameters between the two groups, except for body weight gain in the case of diet F2, which was highest in group C. Therefore, weight gain and feed and water intakes were significantly higher in group C, but there were no differences in feed conversion ratio or live weight. In conclusion, the total replacement of soybean meal with T. molitor larvae meal resulted in a reduction in feed intake and a consequent reduction in weight. During this period, partial rather than total substitution may be recommended. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product