Inorganic arsenic in rice-based products for infants and young children

Inorganic arsenic (Asi) is a chronic, non-threshold carcinogen. Rice and rice-based products can be the major source of Asi for many subpopulations. Baby rice, rice cereals and rice crackers are widely used to feed infants and young children. The Asi concentration in rice-based products may pose a health risk for infants and young children. Asi concentration was determined in rice-based products produced in the European Union and risk assessment associated with the consumption of these products by infants and young children, and compared to an identical US FDA survey. There are currently no European Union or United States of America regulations applicable to Asi in food. However, this study suggests that the samples evaluated may introduce significant concentration of Asi into infants’ and young children’s diets. Thus, there is an urgent need for regulatory limits on Asi in food, especially for baby rice-based products

Consumer Demand for Environmental, Social, and Ethical Information in Fishery and Aquaculture Product Labels

Customers’ attention to sustainability labels in fishery and aquaculture products (FAPs) has been increasing in the last decades, and the industry has adapted to this growing interest by adopting fish ecolabels. However, there is a growing interest to widen the sustainability concept to include the social and ethical information of the fishery and aquaculture industry and to go further from the voluntary approach on the labeling of these aspects in FAPs. For this reason, using data from 2021 Eurobarometer and using machine learning techniques, we disentangle the characteristics of the FAP buyers that consider the importance of environmental impact, ethical, and social information appearing on FAP labeling. The results confirmed that most of the consumers who consider environmental, social, and ethical aspects when buying FAPs also think that this information should be labeled. In line with other works, young, educated, and environmentally aware consumers in high-income countries are more likely to request this information in the FAP label. One interesting finding of the study relates with the asymmetric impact of the variables and the important group of respondents who do not consider these aspects but also advocate to include them in the FAP label. The study outcomes can be beneficial for policymakers to design future public policies regarding FAP labeling, as well as to be taken into consideration in the marketing policies of fishery and aquaculture producers and retailers

COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning

A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function is minimized in the framework of trigonometric regression. While, in our subsequent spatial residual correlation analysis, maximization of the likelihood allows us to compute the posterior mode in a Bayesian multivariate time series soft-data framework. The presented approach is applied to the analysis of COVID-19 mortality in the first wave affecting the Spanish Communities, since March, 8, 2020 until May, 13, 2020. An empirical comparative study with Machine Learning (ML) regression, based on random k-fold cross-validation, and bootstrapping confidence interval and probability density estimation, is carried out. This empirical analysis also investigates the performance of ML regression models in a hard- and soft- data frameworks. The results could be extrapolated to other counts, countries, and posterior COVID-19 waves.Comment: This paper is currently submitte

Multivariate manifold-valued curve regression in time

Fr\'echet global regression is extended to the context of bivariate curve stochastic processes with values in a Riemannian manifold. The proposed regression predictor arises as a reformulation of the standard least-squares parametric linear predictor in terms of a weighted Fr\'echet functional mean. Specifically, in our context, in this reformulation, the Euclidean distance is replaced by the integrated quadratic geodesic distance. The regression predictor is then obtained from the weighted Fr\'echet curve mean, lying in the time-varying geodesic submanifold, generated by the regressor process components involved in the time correlation range. The regularized Fr\'echet weights are computed in the time-varying tangent spaces. The uniform weak-consistency of the regression predictor is proved. Model selection is also addressed. A simulation study is undertaken to illustrate the performance of the spherical curve variable selection algorithm proposed in a multivariate framework.Comment: 24 pages, 8 Figure

Advancements in number representation for high-precision computing

Efficient representation of data is a fundamental prerequisite for addressing computational problems effectively using computers. The continual improvement in methods for representing numbers in computers serves as a critical step in expanding the scope and capabilities of computing systems. In this research, we conduct a comprehensive review of both fundamental and advanced techniques for representing numbers in computers. Additionally, we propose a novel model capable of representing rational numbers with absolute precision, catering to specific high precision applications. Specifically, we adopt fractional positional notation coupled with explicit codification of the periodic parts, thereby accommodating the entire rational number set without any loss of accuracy. We elucidate the properties and hardware representation of this proposed format and provide the results of extensive experiments to demonstrate its expressiveness and minimal codification error when compared to other real number representation formats. This research contributes to the advancement of numerical representation in computer systems, empowering them to handle complex computations with heightened accuracy, making them more reliable and versatile in a wide range of applications.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the Spanish Research Agency (AEI) (https://doi.org/10.13039/501100011033) under project HPC4Industry PID2020-120213RB-I00

Reputation Agent: Prompting Fair Reviews in Gig Markets

Our study presents a new tool, Reputation Agent, to promote fairer reviews from requesters (employers or customers) on gig markets. Unfair reviews, created when requesters consider factors outside of a worker's control, are known to plague gig workers and can result in lost job opportunities and even termination from the marketplace. Our tool leverages machine learning to implement an intelligent interface that: (1) uses deep learning to automatically detect when an individual has included unfair factors into her review (factors outside the worker's control per the policies of the market); and (2) prompts the individual to reconsider her review if she has incorporated unfair factors. To study the effectiveness of Reputation Agent, we conducted a controlled experiment over different gig markets. Our experiment illustrates that across markets, Reputation Agent, in contrast with traditional approaches, motivates requesters to review gig workers' performance more fairly. We discuss how tools that bring more transparency to employers about the policies of a gig market can help build empathy thus resulting in reasoned discussions around potential injustices towards workers generated by these interfaces. Our vision is that with tools that promote truth and transparency we can bring fairer treatment to gig workers.Comment: 12 pages, 5 figures, The Web Conference 2020, ACM WWW 202

Determinantes de la eco-innovación en la actividad de costrucción en España

Creative Commons Reconocimiento-NoComercial 3.0 España (CC BY-NC 3.0 ES)[ES] Partiendo del modelo validado por los autores que determina como variables que afectan a la eco-innovación la orientación a procesos, a productos y la obtención de información de fuentes de mercado, identificamos distintos grupos atendiendo al comportamiento eco-innovador de las empresas del sector de la construcción. Utilizando el algoritmo REBUS-PLS aplicado a 222 empresas con datos de PITEC, se detectan 2 grupos, destacando uno más orientado hacia el medioambiente al innovar, con cifras más altas de inversión en I+D así como la ausencia de diferencias significativas en las variables descriptivas (tamaño, cifra de negocios, inversiones, empleados), lo que indica que la eco-orientación al innovar no depende de estas características y sí que va ligada al comportamiento de la empresa. Los resultados tienen importantes aplicaciones prácticas por lo que a las actuaciones de política de promoción de la eco-innovación se refiere, tanto a nivel público como privado.Segarra Oña, MDV.; Peiró Signes, A.; Cervelló Royo, RE. (2015). Determinantes de la eco-innovación en la actividad de costrucción en España. Informes de la Construcción. 67(1):537-548. doi:10.3989/ic.13.124S537548671Pearce, D. (2006). Is the construction sector sustainable?: definitions and reflections. Building Research & Information, 34(3), 201-207. doi:10.1080/09613210600589910Turner, R. K. (2006). Sustainability auditing and assessment challenges. Building Research & Information, 34(3), 197-200. doi:10.1080/09613210600645795Hill, S., & Lorenz, D. (2011). Rethinking professionalism: guardianship of land and resources. Building Research & Information, 39(3), 314-319. doi:10.1080/09613218.2011.563051Du Plessis, C., & Cole, R. J. (2011). Motivating change: shifting the paradigm. 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Implications of market orientation on the environmental transformation of industrial firms. Ecological Economics, 64(4), 752-762. doi:10.1016/j.ecolecon.2006.07.012(26) Segarra-O-a, M., Peiró-Signes, A., Mondéjar-Jiménez, J. (2013). Identifying Variables Affecting the Proactive Environmental Orientation of Firms: An Empirical Study. Polish Journal of Environmental Studies, 22(3): 873-880.Carrascosa-López, C., Segarra-Oña, M.-V., Peiró-Signes, Á., & Segura-García-del-Río, B. (2012). Does It Pay to Be «Greener» than Legislation? An Empirical Study of Spanish Tile Industry. Journal of Sustainable Development, 5(5). doi:10.5539/jsd.v5n5p17(29) Ferrari, G., Mondéjar-Jiménez, J., Vargas-Vargas, M. (2010). Environmental sustainable management of small rural tourist enterprises. International Journal of Environmental Research, 4(3): 407-414.Segarra-Oña, M.-V., Peiró-Signes, Á., Verma, R., & Miret-Pastor, L. (2012). Does Environmental Certification Help the Economic Performance of Hotels? 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Factors psicosocials de cuidadors masculins informals a la dependència. Un estudi en curs

En la nostra societat, cada vegada més envellida, l’augment de la població dependent està implicant canvis. Primer amb la visibilitat de la problemàtica, després del reconeixement de la llei que l’empara (Llei 39/2006, de 14 de desembre, de promoció de l’autonomia personal i atenció a les persones en situació de dependència); i segon, la feminització del paper de persona cuidadora, amb les conseqüències que d’això es deriva. Però com viuen el seu rol cuidador dels homes que l’exerceixen? Poden descobrir elements positius d’aquesta tasca? És possible que els homes puguen assumir la cura com un valor propi

Urinary Arsenic Speciation in Children and Pregnant Women from Spain

Inorganic arsenic (i-As) is a non-threshold human carcinogen that has been associated with several adverse health outcomes. Exposure to i-As is of particular concern among pregnant women, infants and children, as they are specifically vulnerable to the adverse health effects of i-As, and in utero and early-life exposure, even low to moderate levels of i-As, may have a marked effect throughout the lifespan. Ion chromatography-mass spectrometry detection (IC-ICP-MS) was used to analyse urinary arsenic speciation, as an exposure biomarker, in samples of 4-year-old children with relatively low-level arsenic exposure living in different regions in Spain including Asturias, Gipuzkoa, Sabadell and Valencia. The profile of arsenic metabolites in urine was also determined in samples taken during pregnancy (1st trimester) and in the children from Valencia of 7 years old. The median of the main arsenic species found in the 4-year-old children was 9.71 lg/l (arsenobetaine—AsB), 3.97 lg/l (dimethylarsinic acid—DMA), 0.44 lg/l (monomethylarsonic acid—MMA) and 0.35 lg/l (i-As). Statistically significant differences were found in urinary AsB, MMA and i-As according to the study regions in the 4-year-old, and also in DMA among pregnant women and their children. Spearman’s correlation coefficient among urinary arsenic metabolites was calculated, and, in general, a strong methylation capacity to methylate i-As to MMA was observed