Models of Non-Well-Founded Sets via an Indexed Final Coalgebra Theorem

The paper uses the formalism of indexed categories to recover the proof of a standard final coalgebra theorem, thus showing existence of final coalgebras for a special class of functors on categories with finite limits and colimits. As an instance of this result, we build the final coalgebra for the powerclass functor, in the context of a Heyting pretopos with a class of small maps. This is then proved to provide a model for various non-well-founded set theories, depending on the chosen axiomatisation for the class of small maps

Polynomial Meshes: Computation and Approximation

We present the software package WAM, written in Matlab, that generates Weakly Admissible Meshes and Discrete Extremal Sets of Fekete and Leja type, for 2d and 3d polynomial least squares and interpolation on compact sets with various geometries. Possible applications range from data fitting to high-order methods for PDEs

Organic Livestock Production- A Bibliometric Review

Due to the increasing interest in organic farming, an overview of this research area is provided through a bibliometric analysis conducted between April and May 2019. A total of 320 documents were published up until 2018 on organic livestock farming, with an annual growth rate of 9.33% and a clear increase since 2005; 268 documents have been published in 111 journals. Germany is the country with the largest number of published papers (56 documents). Authors\u2019 top keywords (excluding keywords used for running the search) included: animal welfare (29 times), animal health (22 times), cattle (15 times), grazing (10 times), and sheep (10 times). This could indicate that more research has been done on cattle because of the importance of this species in Germany. Moreover, the prevalence of the terms \u2018animal welfare\u2019 and \u2018animal health\u2019 may indicate that the research on organic livestock production has been focused on these two areas. The bibliometric analysis indicates that: i) countries focused the organic livestock production research on their main production, and ii) more research in species other than cattle and sheep is needed

The use of visible/near-infrared spectroscopy to predict fibre fractions, fibre-bound nitrogen and total-tract apparent nutrients digestibility in beef cattle diets and faeces

Data about diet and digestion process of cattle are important for the fine-tuning of the diet and from an environmental point of view. Given the capacity of the near-infrared reflectance spectroscopy (NIRS) to provide easily, quickly and cheap data its ability in predicting dietary and faecal chemical composition, fibre-bound N and total-tract apparent digestibility (ttaD) of beef cattle were tested. The ttaD was estimated using the dietary and faecal undigestible neutral detergent fibre (uNDF) as an internal marker. A total of 172 pool faecal samples and 164 total mixed ration (TMR) samples were randomly collected 24 h post-feeding across the fattening groups of young males and females Charolaise beef cattle. Both TMR and faeces were analysed chemically and through visible/NIRS instrument. Calibration models were developed using a modified partial least squares (mPLS) regression analysis and tested by a leave-one-out cross-validation procedure and the best calibrations were selected based on various parameters including the coefficient of determination of calibration (R2CrV) and the residual predictive deviation (RPD). The overall composition of TMR and faeces were similar to that reported in literature and the coefficient of variation was higher than 12% for most of the parameters studied. The NIRS was able to accurately predict the ADF, nitrogen (N), and ash content in the TMR, whereas in faeces only the ADF prediction was acceptable. The ttaD and total-tract true digestibility of N using the uNDF as an internal marker were inaccurately predicted both in TMR and in faeces (R2CrV ≤0.66; RPD ≤ 1.71).Highlights Near-infrared spectroscopy was not a suitable technology to predict total tract apparent digestibility. NIRS was able to accurately predict the ADF, nitrogen and ash content in the TMR. NIRS was able to accurately predict the ADF in faeces

Application of a handheld near-infrared spectrometer to predict gelatinized starch, fiber fractions, and mineral content of ground and intact extruded dry dog food

The aim of the present study was to investigate the ability of a handheld near-infrared spectrometer to predict total and gelatinized starch, insoluble fibrous fractions, and mineral content inextruded dry dog food. Intact and ground samples were compared to determine if the homogenization could improve the prediction performance of the instrument. Reference analyses were performed on 81 samples for starch and 99 for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergentlignin (ADL), and minerals, and reflectance infrared spectra (740 to 1070 nm) were recorded with aSCiO™near-infrared (NIR) spectrometer. Prediction models were developed using modified partial least squares regression and both internal (leave-one-out cross-validation) and external validation.The best prediction models in cross-validation using ground samples were obtained for gelatinized starch (residual predictive deviation, RPD = 2.54) and total starch (RPD = 2.33), and S (RPD = 1.92), while the best using intact samples were obtained for gelatinized starch (RPD = 2.45), total starch (RPD = 2.08), and K (RPD = 1.98). Through external validation, the best statistics were obtained for gelatinized starch, with an RPD of 2.55 and 2.03 in ground and intact samples, respectively. Overall, there was no difference in prediction models accuracy using ground or intact samples. In conclusion, the miniaturized NIR instrument offers the potential for screening purposes only for total and gelatinized starch, S, and K, whereas the results do not support its applicability for the other traits

Prediction of chemical composition and peroxide value in unground pet foods by near-infrared spectroscopy

The massive development of the pet food industry in recent years has lead to the formulation of hundreds of canine and feline complete extruded foods with the objective of meeting both the needs of the animals and numerous demands from pet owners. In the meantime, highly variable raw material compositions and the industry's new production techniques oblige manufacturers to monitor all phases of the extrusion process closely in order to ensure the targeted composition and quality of the products. This study aimed at evaluating the potential of infrared technology (visible and near-infrared spectrophotometer; 570-1842 nm) in predicting the chemical composition and peroxide value (PV) of unground commercial extruded dog foods. Six hundred and forty-nine commercial extruded dog foods were collected. For each product, an unground aliquot was analysed by infrared instrument while a second aliquot was sent to a laboratory for proximate analysis and PV quantification. The wide range of extruded dog food typologies included in the study was responsible for the wide variability observed within each nutritional trait, especially crude fibre and ash. The mean value of the 208 pet foods sampled for PV quantification was 17.49 mEq O2/kg fat (min 2.2 and max 94.10 mEq O2/kg fat). The coefficients of determination in cross-validation of NIRS prediction models were 0.77, 0.97, 0.83, 0.86, 0.78 and 0.94 for moisture, crude protein, crude fat, crude fibre, ash and nitrogen-free extract (NFE) respectively. PV prediction was less precise, as demonstrated by the coefficient of determination in cross-validation (0.66). The results demonstrated the potential of NIRS in predicting chemical composition in unground samples, with lower accuracy for moisture and ash, while PV prediction models suggest use for screening purposes only

The Concept of Quality of Life in the Perception of Older Uruguayans: a qualitative study

The research objective was to investigate the conception of quality of life in Uruguayan older adults, trying to build a model adapted to them. Based on Grounded Theory, a qualitative study was carried out between 2017-2018 in several regions of Uruguay. Semi-structured interviews were conducted in older adults (mean age 71 years, SD 5.4) with theoretical and snowball sampling. Theory emerged through the core category “living as best as possible”, interpreted as the conception of older adults about quality of life. The emerging themes were: “context events”, “link with others”, “activities facing life” and “adaptation strategies”. When facing stressful events, participants develop coping strategies through social support and internal locus of control, to achieve quality of life and successful aging. The empirical evidence developed from this qualitative research portrays a model established from a specific age and cultural context, in which social and psychological dimensions interact to face aging and achieve quality of life.El objetivo de este trabajo fue investigar la concepción de calidad de vida en adultos mayores uruguayos, procurando construir un modelo adaptado a ellos. Basado en Teoría Fundamentada, se realizó un estudio cualitativo entre 2017-2018 en varios departamentos de Uruguay. Se realizaron entrevistas semiestructuradas a adultos mayores (edad promedio 71 años, DE 5,4) con muestreo teórico y por bola de nieve. Emergió teoría a través de la categoría madre “vivir lo mejor que se puede”, interpretada como la concepción de adultos mayores sobre calidad de vida. Los temas emergentes fueron: “eventos del contexto”, “vínculo con otros”, “actividades frente a la vida” y “estrategias de adaptación”. Al enfrentar eventos estresantes, los participantes desarrollan estrategias de adaptación por medio del soporte social y locus interno de control, para alcanzar calidad de vida y un envejecimiento exitoso. La evidencia empírica desarrollada a partir de esta investigación cualitativa retrata un modelo establecido en un contexto etario y cultural específico, en el que interactúan dimensiones sociales y psicológicas para enfrentar el envejecimiento y alcanzar calidad de vida

Relativistic Digital Twin: Bringing the IoT to the Future

Complex IoT ecosystems often require the usage of Digital Twins (DTs) of their physical assets in order to perform predictive analytics and simulate what-if scenarios. DTs are able to replicate IoT devices and adapt over time to their behavioral changes. However, DTs in IoT are typically tailored to a specific use case, without the possibility to seamlessly adapt to different scenarios. Further, the fragmentation of IoT poses additional challenges on how to deploy DTs in heterogeneous scenarios characterized by the usage of multiple data formats and IoT network protocols. In this paper, we propose the Relativistic Digital Twin (RDT) framework, through which we automatically generate general-purpose DTs of IoT entities and tune their behavioral models over time by constantly observing their real counterparts. The framework relies on the object representation via the Web of Things (WoT), to offer a standardized interface to each of the IoT devices as well as to their DTs. To this purpose, we extended the W3C WoT standard in order to encompass the concept of behavioral model and define it in the Thing Description (TD) through a new vocabulary. Finally, we evaluated the RDT framework over two disjoint use cases to assess its correctness and learning performance, i.e., the DT of a simulated smart home scenario with the capability of forecasting the indoor temperature, and the DT of a real-world drone with the capability of forecasting its trajectory in an outdoor scenario.Comment: 17 pages, 10 figures, 4 tables, 6 listing