Effect of innovative finishing operations on the tribological performance of steel 27MnCr5

Transmission shafts used in the automotive sector must have a good tribological performance, and therefore an enhanced surface integrity. This paper aims to study the effect of eco-friendly innovative finishing operations (belt finishing, cryogenic grinding and dry grinding) on the surface integrity and tribological performance of steel grade 27MnCr5, and compare to the behavior of components produced by conventional wet grinding process. For that purpose, a total of seven finishing conditions were analysed: wet grinding as reference, two dry grinding conditions, two cryogenic grinding conditions and two hard turning+belt finishing conditions. The surface integrity (roughness, residual stresses, hardness and microstructural defects) of samples was assessed. Finally, the step-loading test method was used to determine the scuffing resistance of the samples. Tested innovative finishing operations led to higher scuffing resistance than conventional wet grinding. Results demonstrate that higher surface hardness and roughness leads to higher scuffing resistance, while the effect of surface residual stresses is not significant

Influence of cryogenic grinding surface on fatigue performance of carburised 27MnCr5

Automotive transmission components are subjected to cyclic loads and, thus, must have a reliable fatigue performance. Since fatigue cracks nucleate at the surface, it is necessary to guarantee that its surface integrity accomplishes the required specifications. Typically, those components are finished by wet grinding after carburising heat treatment. However, there is an increasing demand to reduce pollutants and hazardous lubricants in the industry, and eco-friendly finishing operations have been highly encouraged. To this end, it is necessary to understand the effect of these novel finishing processes on surface integrity and, consequently, on fatigue behaviour. This study aims to assess the surface integrity and the fatigue performance of cryo-ground surfaces of 27MnCr5 steel, extensively used in fabricating shafts and gears for gearboxes. Fatigue specimens for pure torsion tests were initially case-hardened and afterwards finished using two different cryogenic grinding conditions applying liquid N2 and, as a reference, using the conventional wet grinding process. First, the surface integrity was analysed in terms of texture, residual stresses, microstructure, and microhardness. Second, the batches of specimens were tested under pure torsion fatigue. Surface residual stress relaxation was also measured during fatigue tests. Finally, fracture surfaces were observed to identify crack initiation sites and establish correlations with the surface integrity. Specimens produced by cryogenic and conventional wet grinding did not show microstructural defects or hardness reductions in the carburised layer. All conditions induced compressive residual stresses, and they barely relaxed during fatigue tests. Compressive residual stresses induced by cryogenic grinding were 10–20% lower than those generated by conventional wet grinding. This decrease resulted in a minor reduction of the fatigue resistance (4–6%) compared to the wet grinding. Importantly, this study demonstrates that with a slight geometrical radio correction in the design of the mechanical components (around 2.2%), cryogenic grinding generates pieces with the same fatigue strength as conventional grinding. Therefore, it confirms that cryogenic cooling could be a potential solution to replace pollutant coolant/lubricant fluid in grinding operations

Experimental evaluation and surface integrity analysis of cryogenic coolants approaches in the cylindrical plunge grinding

Replacement of pollutant fuids with eco-friendly strategies in machining operations signifcantly contributes to protecting the environment, diminishing global warming, and ensuring a healthier workplace for employees. This study compares cryogenic coolants with conventional coolants in cylindrical plunge grinding using a Cubic Boron Nitride (CBN) wheel. Samples of 27MnCr5 steel used in the manufacture of automotive transmission components were ground using (i) Liquid Nitrogen (LN2), (ii) a combination of LN2 +Minimum Quantity Lubrication (MQL), and (iii) a conventional coolant. The efects of the diferent cooling methods on the surface integrity of the ground surfaces were examined in terms of surface roughness, microstructural defects, microhardness profles, and residual stresses. In general, surface roughness was similar for the tested cooling systems, even after grinding three subsequent surfaces in which the process stability was analyzed. Interestingly, the use of eco-friendly cryogenic systems induced fewer microstructural defects than conventional systems, and particularly, LN2+MQL lead to more compressive surface residual stresses that would improve the in-service performance of components. These results show opportunities for replacing conventional pollutant systems with eco-friendly cryogenic strategies for refrigerating/lubricating grinding processes to reduce harmful efects on the environment and pose health risks to operators

Identificación y caracterización molecular de virus Orf en mujeres de Sudamérica expuestas laboralmente

Contagious Ecthyma (CE) is a severe exanthematous dermatitis caused by the Orf virus (ORFV) that mainly affects domestic small ruminants such as sheep and goats. It is a worldwide-distributed occupational zoonosis, particularly infecting those in close contact with animals or animal products such as shepherds, farmers and veterinarians, among others. In the present work, we report the first human CE case confirmed in Argentina. A phylogenetic analysis based on four gene sequences of the isolated strain responsible for the disease showed that this isolate grouped with other ORFV sequences that caused reported CE cases in sheep from the same Argentine province. We also sequenced a sample from a Chilean human case reported in 2017, whose phylogenetic analysis showed that it groups together with other Argentine isolates from locations close to the border with Chile.Fil: Peralta, Andrea Verónica. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Flores Olivares, Carlos. Universidad Mayor; ChileFil: Verna, Andrea Elizabeth. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible. - Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Buenos Aires Sur. Estacion Experimental Agropecuaria Balcarce. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible.; ArgentinaFil: Gonzalez Altamiranda, Erika Analia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible. - Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Buenos Aires Sur. Estacion Experimental Agropecuaria Balcarce. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible.; ArgentinaFil: Odriozola, Ernesto Raul. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Madariaga, Carolina. Universidad Santo Tomás (ust);Fil: Odeón, Anselmo. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: König, Guido Alberto. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Agrobiotecnología y Biología Molecular. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Canton, German. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible. - Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Buenos Aires Sur. Estacion Experimental Agropecuaria Balcarce. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible.; Argentin

Machine learning-based model for prediction of clinical deterioration in hospitalized patients by COVID 19

[EN] Despite the publication of great number of tools to aid decisions in COVID-19 patients, there is a lack of good instruments to predict clinical deterioration. COVID19-Osakidetza is a prospective cohort study recruiting COVID-19 patients. We collected information from baseline to discharge on: sociodemographic characteristics, comorbidities and associated medications, vital signs, treatment received and lab test results. Outcome was need for intensive ventilatory support (with at least standard high-flow oxygen face mask with a reservoir bag for at least 6 h and need for more intensive therapy afterwards or Optiflow high-flow nasal cannula or noninvasive or invasive mechanical ventilation) and/or admission to a critical care unit and/or death during hospitalization. We developed a Catboost model summarizing the findings using Shapley Additive Explanations. Performance of the model was assessed using area under the receiver operating characteristic and prediction recall curves (AUROC and AUPRC respectively) and calibrated using the Hosmer-Lemeshow test. Overall, 1568 patients were included in the derivation cohort and 956 in the (external) validation cohort. The percentages of patients who reached the composite endpoint were 23.3% vs 20% respectively. The strongest predictors of clinical deterioration were arterial blood oxygen pressure, followed by age, levels of several markers of inflammation (procalcitonin, LDH, CRP) and alterations in blood count and coagulation. Some medications, namely, ATC AO2 (antiacids) and N05 (neuroleptics) were also among the group of main predictors, together with C03 (diuretics). In the validation set, the CatBoost AUROC was 0.79, AUPRC 0.21 and Hosmer-Lemeshow test statistic 0.36. We present a machine learning-based prediction model with excellent performance properties to implement in EHRs. Our main goal was to predict progression to a score of 5 or higher on the WHO Clinical Progression Scale before patients required mechanical ventilation. Future steps are to externally validate the model in other settings and in a cohort from a different period and to apply the algorithm in clinical practice. Registration: ClinicalTrials.gov Identifier: NCT04463706.This work was supported in part by grants from the Instituto de Salud Carlos III and the European Regional Development Fund COVID20/00459; the health outcomes group from Galdakao-Barrualde Health Organization; the Kronikgune Institute for Health Service Research; and the thematic network–REDISSEC (Red de Investigación en Servicios de Salud en Enfermedades Crónicas)–of the Instituto de Salud Carlos III. The funder of the study had no role in study design, data collection, analysis, management or interpretation, or writing of the report

Operational Earthquake Forecasting: State of Knowledge and Guidelines for Utilization

Following the 2009 L'Aquila earthquake, the Dipartimento della Protezione Civile Italiana (DPC), appointed an International Commission on Earthquake Forecasting for Civil Protection (ICEF) to report on the current state of knowledge of short-term prediction and forecasting of tectonic earthquakes and indicate guidelines for utilization of possible forerunners of large earthquakes to drive civil protection actions, including the use of probabilistic seismic hazard analysis in the wake of a large earthquake. The ICEF reviewed research on earthquake prediction and forecasting, drawing from developments in seismically active regions worldwide. A prediction is defined as a deterministic statement that a future earthquake will or will not occur in a particular geographic region, time window, and magnitude range, whereas a forecast gives a probability (greater than zero but less than one) that such an event will occur. Earthquake predictability, the degree to which the future occurrence of earthquakes can be determined from the observable behavior of earthquake systems, is poorly understood. This lack of understanding is reflected in the inability to reliably predict large earthquakes in seismically active regions on short time scales. Most proposed prediction methods rely on the concept of a diagnostic precursor; i.e., some kind of signal observable before earthquakes that indicates with high probability the location, time, and magnitude of an impending event. Precursor methods reviewed here include changes in strain rates, seismic wave speeds, and electrical conductivity; variations of radon concentrations in groundwater, soil, and air; fluctuations in groundwater levels; electromagnetic variations near and above Earth's surface; thermal anomalies; anomalous animal behavior; and seismicity patterns. The search for diagnostic precursors has not yet produced a successful short-term prediction scheme. Therefore, this report focuses on operational earthquake forecasting as the principle means for gathering and disseminating authoritative information about time-dependent seismic hazards to help communities prepare for potentially destructive earthquakes. On short time scales of days and weeks, earthquake sequences show clustering in space and time, as indicated by the aftershocks triggered by large events. Statistical descriptions of clustering explain many features observed in seismicity catalogs, and they can be used to construct forecasts that indicate how earthquake probabilities change over the short term. Properly applied, short-term forecasts have operational utility; for example, in anticipating aftershocks that follow large earthquakes. Although the value of long-term forecasts for ensuring seismic safety is clear, the interpretation of short-term forecasts is problematic, because earthquake probabilities may vary over orders of magnitude but typically remain low in an absolute sense (< 1% per day). Translating such low-probability forecasts into effective decision-making is a difficult challenge. Reports on the current utilization operational forecasting in earthquake risk management were compiled for six countries with high seismic risk: China, Greece, Italy, Japan, Russia, United States. Long-term models are currently the most important forecasting tools for civil protection against earthquake damage, because they guide earthquake safety provisions of building codes, performance-based seismic design, and other risk-reducing engineering practices, such as retrofitting to correct design flaws in older buildings. Short-term forecasting of aftershocks is practiced by several countries among those surveyed, but operational earthquake forecasting has not been fully implemented (i.e., regularly updated and on a national scale) in any of them. Based on the experience accumulated in seismically active regions, the ICEF has provided to DPC a set of recommendations on the utilization of operational forecasting in Italy, which may also be useful in other countries. The public should be provided with open sources of information about the short-term probabilities of future earthquakes that are authoritative, scientific, consistent, and timely. Advisories should be based on operationally qualified, regularly updated seismicity forecasting systems that have been rigorously reviewed and updated by experts in the creation, delivery, and utility of earthquake information. The quality of all operational models should be evaluated for reliability and skill by retrospective testing, and they should be under continuous prospective testing against established long-term forecasts and alternative time-dependent models. Alert procedures should be standardized to facilitate decisions at different levels of government and among the public. Earthquake probability thresholds should be established to guide alert levels based on objective analysis of costs and benefits, as well as the less tangible aspects of value-of-information, such as gains in psychological preparedness and resilience. The principles of effective public communication established by social science research should be applied to the delivery of seismic hazard information

La docencia en emprendimiento y emprendimiento social en los ecosistemas universitarios de referencia: Aplicación de las metodologías docentes de aprender a emprender en la Universidad Complutense de Madrid.

Fac. de Ciencias Económicas y EmpresarialesFALSEsubmitte