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The reflection of light on mineral samples have been widely used to obtain information concerning their composition. In particular, visible and near-infrared reflectance spectrum have offered an inexpensive way to obtain information about their mineralogical composition. In this work, near-infrared hyperspectral reflective images of several mineral samples are obtained and analyzed. The average reflective spectrum of Chalcopyrite (CuFeS2), Pyrite (FeS2), Chalcocite (Cu2S), Covellite (CuS), and Slag (FeO-SiO2) packed into pellets were obtained using a near-infrared hyperspectral camera. In order to analyze copper concentrates, a K-Nearest Neighbor classifier was trained to identify its main components. A 10 fold cross validation approach was used to certify the validity of the classifier. The trained classifier provided the mineralogical spatial distribution of the different components in a concentrate sample. An automatic system controlling all the acquisition and image processing stages provides analysis of the concentrate samples. Further work is underway to include additional minerals and to improve implementation issues such as signal filtering. This is the first step towards the design of a low cost system to provide relevant information about the concentrates feeding copper smelters.

Infrared (IR) imaging systems are known to have a range of sensor and optical limitations that result in degraded imagery. Fixed pattern noise (FPN), resulting from pixel-to-pixel response nonuniformity, is a dominant source of error that manifests in collected imagery through the appearance of temporally and spatially correlated noise patterns that are mixed with each image. Furthermore, finite detector size coupled with imperfect system optics can introduce blurring effects and aliasing, ultimately reducing resolution in acquired images. Here, we propose a unified method to reduce FPN and recover high-frequency image content in IR microscopy images. The proposed method uses regularized nonlocal means to highlight spatial features in the scene while maintaining fine textural image details. We derive an iterative optimization method based upon a gradient descent minimization strategy that applies a Wiener deconvolution in each iteration to estimate the blur artifacts. The method is implemented within an embedded mid-wave IR imaging system for microscopy applications. We demonstrate a reduction in FPN and blurring artifacts, achieving improved image resolution in the reconstructed images that are apparent in recovered details on scene objects.

A three-dimensional point spread function experimental estimation method based on the system’s focal plane array spatial local impulse response of a mid-wave infrared microscope is presented. The method uses several out-of-focus two-dimensional point spread function planes to achieve a single three-dimensional point spread function of the whole microscope’s optical spreading, expanding the limits of infrared optical technology by one dimension. This technique includes stages of image acquisition, nonuniformity correction, filtering, and multi-planar reconstruction steps, and its effectiveness is demonstrated on biological sample image restoration by means of a multi-planar refocusing application.

In this paper, a novel optical technique for following the progress of the blister copper desulfurization process is presented. The technique is based on the changes observed in the continuous spectrum of the visible&ndash, near-infrared (VIS&ndash, NIR) radiation that the blister melt emits while the chemical reactions of the sulfur elimination process are taking place. Specifically, the proposed technique uses an optical probe composed of an optical fiber, a collimating lens, and a quartz tube, which is immersed in the melt. This optical probe provides a field of view of the blowing zone where the desulfurization reaction occurs. The experimental results show that the melt VIS&ndash, NIR total irradiance evolves inversely to the SO2 concentration reported by a gas analyzer based on differential optical absorption spectroscopy. Furthermore, the blister copper spectral emissivity as well as the total emissivity observed throughout the process show strong correlation with the sulfur content during desulfurization reaction.

The effect of genetic crossing and nutritional management on weight gain and the concentration of minerals and trace elements in the carcass, blood, leather, and viscera of sheep were evaluated. Several statistical strategies were used to evaluate the different elemental composition characteristics of pure breed animals, i.e., White Dorper (ODO), Ile de France (OIF), Texel (OTX), and Santa Inês (OSI), as well as their crossbreeds 1/2 White Dorper and 1/2 Santa Inês (ODS), 1/2 Ile de France, and 1/2 Santa Inês (OIS), 1/2 Texel × 1/2 Santa Inês (OTS). Three different diets were evaluated AL (ad libitum), R75, and R63 (75 and 63 g of dry matter/kg of the animal metabolic weight, respectively). Levels of Ca, Cu, Fe, K, Mg, Mn, P, S, and Zn were determined by inductively coupled plasma optical emission spectrometry (ICP OES). The concentration of inorganic elements in the different body components was not affected by the diet (P 0.05), and OTX and OTS were the breeds with the highest weight gain. Random forest importance models demonstrated that Zn in the carcass, K, Ca, and Zn in blood, and K in leather are most associated with separating the different evaluated sheep's breeds. Crossbreeding the native Santa Inês breed with sheep of exotic breeds produces animals well adapted to confinement.

qRT-PCR is the gold standard technique available for SARS-CoV-2 detection. However, the long test run time and costs associated with this type of molecular testing are a challenge in the actual pandemic scenario. Due to high testing demand, pooling sample strategy is an interesting approach to allow cost savings. We aim to evaluate pooling tests in experimental procedures, as well as perform in silico statistical modeling analysis validated with specimen samples obtained from a mass testing program of Industry Federation of the State of Rio de Janeiro (Brazil). Although the sensitivity reduction in samples pooled with 32 individuals was observed, the high-test sensitivity is maintained even when 16 and 8 samples were pooled. The in silico analysis showed high-cost savings in populations with positive rates lower than 15.0% according to the pool size. This data was validated with the results obtained in our mass testing program: statistical modeling predicted a cost saving of 48.0%, which in practice, was 51.5%, already considering the expenditures with pool sampling that were analyzed individually. Our data confirmed that mathematical modeling is a powerful strategy to improve the pooling approach for SARS-CoV-2 mass testing around the world while maintaining high sensitivity and robustness.

In this article we present the development of a biosensor system that integrates nanotechnology, optomechanics and a spectral detection algorithm for sensitive quantification of antibiotic residues in raw milk of cow. Firstly, nanobiosensors were designed and synthesized by chemically bonding gold nanoparticles (AuNPs) with aptamer bioreceptors highly selective for four widely used antibiotics in the field of veterinary medicine, namely, Kanamycin, Ampicillin, Oxytetracycline and Sulfadimethoxine. When molecules of the antibiotics are present in the milk sample, the interaction with the aptamers induces random AuNP aggregation. This phenomenon modifies the initial absorption spectrum of the milk sample without antibiotics, producing spectral features that indicate both the presence of antibiotics and, to some extent, its concentration. Secondly, we designed and constructed an electro-opto-mechanic device that performs automatic high-resolution spectral data acquisition in a wavelength range of 400 to 800 nm. Thirdly, the acquired spectra were processed by a machine-learning algorithm that is embedded into the acquisition hardware to determine the presence and concentration ranges of the antibiotics. Our approach outperformed state-of-the-art standardized techniques (based on the 520/620 nm ratio) for antibiotic detection, both in speed and in sensitivity.

Resumen: El objetivo de este artículo es desarrollar el concepto de gestión de la demanda en relación a los tipos de control existentes y presentar un ejemplo simple de optimización de la demanda para evaluar las potencialidades de un control híbrido. Se presenta una breve introducción, detallando el conocimiento actual en gestión de demanda, se desarrolla el concepto de control directo e indirecto sobre la demanda, se identifica, y se elabora una tabla con las cargas residenciales. Se modelan dos residencias que podrán modificar su carga ante un esquema de precios dados y un objetivo de no concentración de la demanda fijados por la distribuidora, obteniendo una correcta optimización y dispersando las cargas de diferente forma en la segunda ronda. Se concluye que una intervención de la distribuidora puede mejorar la distribución de la demanda por la aleatoriedad del algoritmo genético sin comprometer la privacidad del usuario. Abstract: The article aims is to develop the demand side management concept in relation to existing control types. It also aims to providing a simple example of demand optimization to evaluate the potentialities of a hybrid control. A brief introduction is presented detailing the state of the art. Then, the direct and indirect control over demand was discussed, the types of loads were described, and a table with the residential loads was prepared. Two residences were modeled, which could modify their load before a given price scheme and a non-concentration objective set by the distributor. This resulted in obtaining a correct optimization and distributing of the loads in a different way in the second round. It is concluded that an intervention of the distributor can improve the distribution of the demand by the randomness of the genetic algorithm without compromising user privacy.

espanolEl objetivo de este articulo es desarrollar el concepto de gestion de la demanda en relacion a los tipos de control existentes y presentar un ejemplo simple de optimizacion de la demanda para evaluar las potencialidades de un control hibrido. Se presenta una breve introduccion, detallando el conocimiento actual en gestion de demanda, se desarrolla el concepto de control directo e indirecto sobre la demanda, se identifica, y se elabora una tabla con las cargas residenciales. Se modelan dos residencias que podran modificar su carga ante un esquema de precios dados y un objetivo de no concentracion de la demanda fijados por la distribuidora, obteniendo una correcta optimizacion y dispersando las cargas de diferente forma en la segunda ronda. Se concluye que una intervencion de la distribuidora puede mejorar la distribucion de la demanda por la aleatoriedad del algoritmo genetico sin comprometer la privacidad del usuario. EnglishThe article aims is to develop the demand side management concept in relation to existing control types. It also aims to providing a simple example of demand optimization to evaluate the potentialities of a hybrid control. A brief introduction is presented detailing the state of the art. Then, the direct and indirect control over demand was discussed, the types of loads were described, and a table with the residential loads was prepared. Two residences were modeled, which could modify their load before a given price scheme and a nonconcentration objective set by the distributor. This resulted in obtaining a correct optimization and distributing of the loads in a different way in the second round. It is concluded that an intervention of the distributor can improve the distribution of the demand by the randomness of the genetic algorithm without compromising user privacy.

The diversity of Ceriantharia is known from studies formally describing species from the late 18th Century onwards. However, no nomenclators including a list and discussion of all valid species have been produced since a list discussed by Carlgren in 1912. The present nomenclator presents a complete list of adult species of Ceriantharia of the World, including a discussion on each species. It includes the three families (Arachnactidae, Botrucnidiferidae, Cerianthidae) and the currently accepted 54 species based on their adult form. This study serves as a presentation of the “state-of-the-art” list of species of Ceriantharia, and includes a species identification key to support taxonomic identification. Additional in-depth species-by-species investigations for almost all cerianthid species is still needed, as the information available for most of these species is quite superficial.

The engineering application of natural lignocellulosic fibers (NLFs) has been intensifying all over the world due to their low cost and abundance, as well as their being eco-friendly and presenting favorable technological properties in polymeric and cementitious composites. Brazil, especially the Amazon region, owing to its climate and geographic position, has an abundant variety of NLFs that are still unexplored with great potential for use in various composite materials and applications such as civil construction, automobile parts and armor. Therefore, this review aims to establish a parallel between the technological properties of cementitious composites reinforced with Amazon NLFs, both in fresh and hardened states, and to analyze, compare results and contribute to a better understanding of the similarities and differences between the types of reinforcements. A relevant contribution of this review is the possibility of improving knowledge about Amazon NLFs, showing their potential for application in eco-friendly materials, in addition to contributing to studies with new NLFs not yet applied in composite. For this, it was necessary to carry out a literature survey on the physical, chemical and mechanical properties of cementitious composites reinforced with NLFs, in addition to analyzing case studies involving fibers such as curaua, açai, bamboo, jute and sisal. It can be concluded that the physical and chemical characteristics of the Amazon NLFs directly influence the technological properties of cementitious compounds, such as mechanical strength and water absorption. However, there might be a need for surface treatment aimed at improving adhesion and durability of the cementitious composite. Finally, some suggestions for future research work are highlighted in order to show the need to continue investigations on the application of Amazon NLFs in cementitious composites.

Creating textured 3D meshes of objects for real-time applications can be a laborious, slow and expensive task, demanding specific, highly specialized human resources such as 2D and 3D artists. In this paper, we present a fully automatic 3D modeling methodology based on silhouette carving, capable of creating textured 3D meshes from three pieces of concept art. Our method takes a set of the target object concept art in different views as input and generates a coarse 3D mesh alongside a diffuse color map for texturing the model. The coarse mesh is intended to replace the initial primitive mesh used on the modeling technique known as Box Modeling to accelerate the whole 3D model production. Although, in current 3D model production pipeline there are some more sophisticated methods based on sculpting and retopology, Box Modeling is still a heavily adopted technique used for man-made objects that do not require organic modeling. Our experiments show that it speeds up the 3D content production time up to 40% by providing the coarse model automatically. Also, our method preserve the artist’s trace and can create more accurate meshes compared to a similar approach, photoconsistency-based, and learning-based methods.

In this work, we present a new technique to simultaneously reduce two major degradation artifacts found in mid-wavelength infrared microscopy imagery, namely the inherent focal-plane array nonuniformity noise and the scene defocus presented due to the point spread function of the infrared microscope. We correct both nuisances using a novel, recursive method that combines the constant range nonuniformity correction algorithm with a frame-by-frame deconvolution approach. The ability of the method to jointly compensate for both nonuniformity noise and blur is demonstrated using two different real mid-wavelength infrared microscopic video sequences, which were captured from two microscopic living organisms using a Janos-Sofradir mid-wavelength infrared microscopy setup. The performance of the proposed method is assessed on real and simulated infrared data by computing the root mean-square error and the roughness-laplacian pattern index, which was specifically developed for the present work.