A negative feedback between anthropogenic ozone pollution and enhanced ocean emissions of iodine

Naturally emitted from the oceans, iodine compounds efficiently destroy atmospheric ozone and reduce its positive radiative forcing effects in the troposphere. Emissions of inorganic iodine have been experimentally shown to depend on the deposition to the oceans of tropospheric ozone, whose concentrations have significantly increased since 1850 as a result of human activities. A chemistry-climate model is used herein to quantify the current ocean emissions of inorganic iodine and assess the impact that the anthropogenic increase in tropospheric ozone has had on the natural cycle of iodine in the marine environment since pre-industrial times. Our results indicate that the human-driven enhancement of tropospheric ozone has doubled the oceanic inorganic iodine emissions following the reaction of ozone with iodide at the sea surface. The consequent build-up of atmospheric iodine, with maximum enhancements of up to 70% with respect to pre-industrial times in continental pollution outflow regions, has in turn accelerated the ozone chemical loss over the oceans with strong spatial patterns. We suggest that this ocean-atmosphere interaction represents a negative geochemical feedback loop by which current ocean emissions of iodine act as a natural buffer for ozone pollution and its radiative forcing in the global marine environment.Fil: Prados Roman, C.. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Cuevas, Carlos Alberto. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Fernandez, Rafael Pedro. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Kinnison, Douglas E.. National Center For Atmospheric Research. Amospheric Chemistry División; Estados UnidosFil: Lamarque, Jean Francoise. National Center For Atmospheric Research. Amospheric Chemistry División; Estados UnidosFil: Saiz-lopez, Alfonso. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; Españ

Ligand synthesis catalyst and complex metal ion: multicomponent synthesis of 1,3-bis(4-phenyl-[1,2,3]triazol-1-yl)-propan-2-ol copper(i) complex and application in copper-catalyzed alkyne-azide cycloaddition

A new bistriazole copper complex was synthesized by direct treatment of an alkyne, an azide, and CuI as copper salt through in situ ligand formation under a multicomponent reaction process. This complex was analyzed by XPS, TGA, DSC, and SEM techniques and revealed a triangular-shapedmorphology, high thermal stability, and catalytic power in CuAAC reactions, requiring only 2.5% mol catalyst to afford 1,2,3-triazoles in good yields which can be reused at least for 4 cyclesCONACYT, proyecto 13505

A case-based tool to assess college students’ perceptions about ethical competence

[EN] The main objective of this study was to design a new tool to explore the perception of professionally-related ethical values in Health Sciences undergraduate students. For this purpose, 24 conversational interviews, as well as an extensive literature review, were initially employed. Then, five ethical values were selected: respect for the patient, altruism, empathy, responsibility for my actions, and lifelong learning. Next, twenty cases with ethical dilemmas were created with protagonists pertaining to four degrees in the Health Sciences: Nursing, Dentistry, Physical Therapy, and Medicine. These cases were examined by professionals from these fields and presented to a sample of students to analyze their functioning. Our results indicate that the cases are easy to understand as most cases were identified correctly. Interestingly, students reported “respect for the patient” as the most important ethical value. The least important value was “altruism.” This new tool adds a practical perspective based on clinical cases with real-life dilemmas. Further studies are needed to continue exploring this topic.Gonzalez-Cuevas, G.; Lopez Del Hierro, M.; Martinez, N.; Hernando, MA. (2017). A case-based tool to assess college students’ perceptions about ethical competence. En Proceedings of the 3rd International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 1271-1277. https://doi.org/10.4995/HEAD17.2017.55811271127

An analysis of unconscious gender bias in academic texts by means of a decision algorithm

Inclusive language focuses on using the vocabulary to avoid exclusion or discrimination, specially referred to gender. The task of finding gender bias in written documents must be performed manually, and it is a time-consuming process. Consequently, studying the usage of non-inclusive language on a document, and the impact of different document properties (such as author gender, date of presentation, etc.) on how many non-inclusive instances are found, is quite difficult or even impossible for big datasets. This research analyzes the gender bias in academic texts by analyzing a study corpus of more than 12,000 million words obtained from more than one hundred thousand doctoral theses from Spanish universities. For this purpose, an automated algorithm was developed to evaluate the different characteristics of the document and look for interactions between age, year of publication, gender or the field of knowledge in which the doctoral thesis is framed. The algorithm identified information patterns using a CNN (convolutional neural network) by the creation of a vector representation of the sentences. The results showed evidence that there was a greater bias as the age of the authors increased, who were more likely to use non-inclusive terms; it was concluded that there is a greater awareness of inclusiveness in women than in men, and also that this awareness grows as the candidate is younger. The results showed evidence that the age of the authors increased discrimination, with men being more likely to use non-inclusive terms (up to an index of 23.12), showing that there is a greater awareness of inclusiveness in women than in men in all age ranges (with an average of 14.99), and also that this awareness grows as the candidate is younger (falling down to 13.07). In terms of field of knowledge, the humanities are the most biased (20.97), discarding the subgroup of Linguistics, which has the least bias at all levels (9.90), and the field of science and engineering, which also have the least influence (13.46). Those results support the assumption that the bias in academic texts (doctoral theses) is due to unconscious issues: otherwise, it would not depend on the field, age, gender, and would occur in any field in the same proportion. The innovation provided by this research lies mainly in the ability to detect, within a textual document in Spanish, whether the use of language can be considered non-inclusive, based on a CNN that has been trained in the context of the doctoral thesis. A significant number of documents have been used, using all accessible doctoral theses from Spanish universities of the last 40 years; this dataset is only manageable by data mining systems, so that the training allows identifying the terms within the context effectively and compiling them in a novel dictionary of non-inclusive terms