A comprehensive data processing plan for crop calendar MSS signature development from satellite imagery

There are no author-identified significant results in this report

Documents from the February 22 and February 23 Final Budgeting Meeting of the Associated Students of the University of Montana (ASUM)

Meeting minutes from the February 22 and February 23 final budgeting session meetings of the Associated Students of the University of Montana (ASUM)

EL IMPLEMENTO DE CALCULADORA DE RIESGO DE SEPSIS NEONATAL DISMINUYE EL USO DE ANTIBIOTICOS EN RECIEN NACIDOS > 34 SEMANAS DE GESTACIÒN EN HOSPITAL GENERAL DE ATIZAPAN DR SALVADOR GONZALEZ HERREJON DE PERIODO MARZO 2020 DICIEMBRE 2020.

La sepsis neonatal es un grave problema de salud pública a escala mundial por sus altas tasas de morbi-mortalidad. La Organización Mundial de la Salud (OMS) calcula que en el mundo fallecen casi 5, 000,000 de recién nacidos al año, siendo la principal causa de muerte las infecciones, asfixia y prematurez. Estudios realizados por la Organización Mundial de la Salud estiman que de 126.377.000 nacimientos que ocurren cada año en los países en vías de desarrollo, aproximadamente un 20% presenta una infección neonatal. [1,3] El 98 % de estas muertes ocurren en países en desarrollo y el 30 a 40 % están relacionados con las infecciones. En un estudio de cohorte prospectivo en RN del Nuevo Hospital Civil de Guadalajara "Dr. Juan I Menchaca" en el año 2015 se determino que En México y otros países en vías de desarrollo se informan tasas de 15 a 30 por cada 1000 recién nacidos con una letalidad entre 25 a 30 % [2,44] La sepsis neonatal es una infección invasiva, en general bacteriana, que se produce durante el período neonatal. Los signos son múltiples, inespecíficos e incluyen disminución de la actividad espontánea, succión menos enérgica, apnea, bradicardia, inestabilidad térmica, dificultad respiratoria, vómitos, diarrea, distensión abdominal, inquietud, convulsiones e ictericia. El diagnóstico es clínico y se confirma con los resultados de los cultivos. El tratamiento inicial se limita a fármacos específicos contra el microorganismo lo antes posible. [6,35] La sepsis neonatal es una causa mayor de mortalidad y morbilidad en prematuros y de muy bajo peso al nacimiento, como resultado los médicos debemos realizar evaluación y tratamiento para posible sepsis en pacientes con muy bajo peso al nacimiento, por la presencia de retraso en el diagnóstico y tratamiento que puede empeorar la clínica.UAEM, la autora

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Peer reviewe

Σχέση των μεταλλάξεων U2504A και C2534T στο 23s rRNA από Staphylococcus epidermidis με την αντίσταση στο αντιβιοτικό λινεζολίδη: μελέτη με προσομοιώσεις μοριακής δυναμικής

Σημείωση: διατίθεται συμπληρωματικό υλικό σε ξεχωριστό αρχείο

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social andMoral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs fromsocial,moral, cognitive, and personality psychology, aswell as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided themost consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Published versio