Mejorando las estrategias de Comprensión Lectora en nuestros docentes, mejoraremos los aprendizajes en nuestros estudiantes. plan de acción

En la institución educativa La Unión hay un bajo rendimiento académico en los aprendizajes de los estudiantes. Al tener las reuniones pedagógicas con los docentes de los tres niveles y de todas las Áreas de Secundaria, se puso de manifiesto que ello se debe a que los estudiantes no desarrollan bien sus capacidades o competencias lectoras, no solo en Comunicación, sino que esto incide en el aprendizaje de las otras áreas, por lo cual es impostergable la intervención para el tratamiento de la problemática. Es cierto que hay una notable mejoría en los estudiantes, lo cual se traduce en los resultados obtenidos, principalmente en la ECE, pero también es notorio el gran porcentaje de estudiantes que presentan dificultades en lectura, matemática y sociales. Esto supone implementar estrategias que, partiendo por la capacitación de los docentes en manejo y aplicación de estrategias de comprensión lectora, junto con un adecuado monitoreo y acompañamiento a los docentes, servirá para mejorar el rendimiento escolar en todas las Áreas en Secundaria y, ello permite hacer la proyección hacia la Primaria e Inicial. Es así como se ha diseñado el plan de acción que se desarrollará en nuestra Institución Educativa, a partir del presente año escolar., concordando con el MBDDir. en lo referente a la orientación y uso de estrategias metodológicas de comprensión lectora como base para el aprendizaje de las otras Áreas, como las referentes al asunto, ya que como lo manifiesta Francisco Sacristán Romero ( 2015) “la lectura de la matemática requiere además de comprender las palabras del lenguaje natural, entender el sentido, el significado de los símbolos y las fórmulas(p.3).Trabajo académic

Prospective evaluation of multiplicative hybrid earthquake forecasting models in California

The Regional Earthquake Likelihood Models (RELM) experiment, conducted within the Collaboratory for the Study of Earthquake Predictability (CSEP), showed that the smoothed seismicity (HKJ) model by Helmstetter et al. was the most informative time-independent earthquake model in California during the 2006–2010 evaluation period. The diversity of competing forecast hypotheses and geophysical data sets used in RELM was suitable for combining multiple models that could provide more informative earthquake forecasts than HKJ. Thus, Rhoades et al. created multiplicative hybrid models that involve the HKJ model as a baseline and one or more conjugate models. In retrospective evaluations, some hybrid models showed significant information gains over the HKJ forecast. Here, we prospectively assess the predictive skills of 16 hybrids and 6 original RELM forecasts at a 0.05 significance level, using a suite of traditional and new CSEP tests that rely on a Poisson and a binary likelihood function. In addition, we include consistency test results at a Bonferroni-adjusted significance level of 0.025 to address the problem of multiple tests. Furthermore, we compare the performance of each forecast to that of HKJ. The evaluation data set contains 40 target events recorded within the CSEP California testing region from 2011 January 1 to 2020 December 31, including the 2016 Hawthorne earthquake swarm in southwestern Nevada and the 2019 Ridgecrest sequence. Consistency test results show that most forecasting models overestimate the number of earthquakes and struggle to explain the spatial distribution of epicenters, especially in the case of seismicity clusters. The binary likelihood function significantly reduces the sensitivity of spatial log-likelihood scores to clustering, however; most models still fail to adequately describe spatial earthquake patterns. Contrary to retrospective analyses, our prospective test results show that none of the models are significantly more informative than the HKJ benchmark forecast, which we interpret to be due to temporal instabilities in the fit that forms hybrids. These results suggest that smoothing high-resolution, small earthquake data remains a robust method for forecasting moderate-to-large earthquakes over a period of 5–15 yr in California.This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 821115, Real-time earthquake rIsk reduction for a reSilient Europe (RISE), http://www.rise-eu.org). Additionally, this research was supported by the Southern California Earthquake Center (contribution no. 11011). SCEC is funded by NSF Cooperative agreement EAR-1600087 and USGS Cooperative agreement G17AC00047

Process Deployment: A Taxonomy of Critical Success Factors

Various methods, models and standards for software process improvement have been adopted by organizations to improve their software processes. However, despite these efforts they still encounter difficulties in their process deployment throughout the organization. This is because the vast majority of these efforts focus more on the technical aspects, bypassing the human aspects. There is a set of factors that influence the successful deployment of new or modified processes. This paper presents a taxonomy of critical success factors in software process deployment to achieve the processes institutionalization. The development of a taxonomy related to these critical success factors is based on a systematic review of existing literature on specialized databases and industrial experiences that have deployed or implemented processes

Taxonomía de Factores Críticos para el Despliegue de Procesos Software.

Diversos métodos, modelos y estándares para la mejora de procesos software han sido desarrollados y adoptados por las organizaciones para mejorar sus procesos software. Sin embargo, a pesar de los esfuerzos realizados, presentan aun dificultades en el despliegue de sus procesos a través de la organización. Esto es debido a que en su gran mayoría, los esfuerzos realizados están más orientados hacia los aspectos técnicos, soslayando los aspectos relacionados con las personas. Existe un conjunto de factores que condicionan el éxito del despliegue de los procesos nuevos o que han sido modificados. En este artículo, se presenta una taxonomía de factores críticos que condicionan el éxito del proceso de despliegue, que se traduce en lograr la institucionalización de los procesos. La elaboración de la taxonomía de factores críticos de éxito se sustenta en una revisión sistemática de la bibliografía existente en las bases de datos especializadas y en experiencias en organizaciones que han desplegado procesos basados en el modelo CMMI

Análisis de la competitividad de la pota exportada desde el puerto de Paita al Mercado de Corea del Sur, 2020

La presente investigación tiene como objetivo determinar el nivel de competitividad de la pota exportada desde el puerto de Paita hacia el mercado de Corea del Sur, 2020 para lo cual se considera un tipo de estudio aplicada descriptiva ya que se mencionan las características de las variables; así mismo, posee un enfoque mixto y diseño transversal no experimental debido a que no se manipuló ninguna variable. En lo concerniente a las técnicas de recolección de datos se empleó la encuesta dirigida a los responsables de los procesos de calidad y producción; la entrevista realizada a los responsables del área comercial y/o exportaciones y el análisis de revisión documental efectuada a cada organización; la población estuvo conformada por veintiocho empresas situadas en la provincia de Paita dedicadas al procesamiento y exportación de pota de las cuales se tomó como muestra a seis de ellas quienes exportan al mercado surcoreano. Los resultados muestran que el nivel de competitividad de la pota exportada desde el puerto de Paita es alto, de la misma manera se pudo concluir que el alto nivel de competitividad se sustenta en el nivel de calidad, capacidad de respuesta y variedad de presentaciones ofrecidas de la pota exportada al mercado surcoreano

Effect of a Physician Uncertainty Reduction Intervention on Blood Pressure in Uncontrolled Hypertensives-A Cluster Randomized Trial

BACKGROUND: Clinical inertia, provider failure to appropriately intensify treatment, is a major contributor to uncontrolled blood pressure (BP). Some clinical inertia may result from physician uncertainty over the patient’s usual BP, adherence, or value of continuing efforts to control BP through lifestyle changes. OBJECTIVE: To test the hypothesis that providing physicians with uncertainty reduction tools, including 24-h ambulatory BP monitoring, electronic bottle cap monitoring, and lifestyle assessment and counseling, will lead to improved BP control. DESIGN: Cluster randomized trial with five intervention clinics (IC) and five usual care clinics (UCC). SETTING: Six public and 4 private primary care clinics. PARTICIPANTS: A total of 665 patients (63 percent African American) with uncontrolled hypertension (BP ≥140 mmHg/90 mmHg or ≥130/80 mmHg if diabetic). INTERVENTIONS: An order form for uncertainty reduction tools was placed in the IC participants’ charts before each visit and results fed back to the provider. OUTCOME MEASURES: Percent with controlled BP at last visit. Secondary outcome was BP changes from baseline. RESULTS: Median follow-up time was 24 months. IC physicians intensified treatment in 81% of IC patients compared to 67% in UCC (p\u3c0.001); 35.0% of IC patients and 31.9% of UCC patients achieved control at the last recorded visit (p\u3e0.05). Multi-level mixed effects longitudinal regression modeling of SBP and DBP indicated a significant, non-linear slope difference favoring IC (p time × group interaction=0.048 for SBP and p=0.001 for DBP). The model-predicted difference attributable to intervention was −2.8 mmHg for both SBP and DBP by month 24, and −6.5 mmHg for both SBP and DBP by month 36. CONCLUSIONS: The uncertainty reduction intervention did not achieve the pre-specified dichotomous outcome, but led to lower measured BP in IC patients

Evaluation of a Decade-Long Prospective Earthquake Forecasting Experiment in Italy

Earthquake forecasting models represent our current understanding of the physics and statistics that govern earthquake occurrence processes. Providing such forecasts as falsifiable statements can help us assess a model’s hypothesis to be, at the least, a plausible conjecture to explain the observations. Prospective testing (i.e., with future data, once the model and experiment have been fully specified) is fundamental in science because it enables confronting a model with completely out‐of‐sample data and zero degrees of freedom. Testing can also help inform decisions regarding the selection of models, data types, or procedures in practical applications, such as Probabilistic Seismic Hazard Analysis. In 2010, a 10‐year earthquake forecasting experiment began in Italy, where researchers collectively agreed on authoritative data sources, testing rules, and formats to independently evaluate a collection of forecasting models. Here, we test these models with ten years of fully prospective data using a multiscore approach to (1) identify the model features that correlate with data‐consistent or ‐inconsistent forecasts; (2) evaluate the stability of the experiment results over time; and (3) quantify the models’ limitations to generate spatial forecasts consistent with earthquake clustering. As each testing metric analyzes only limited properties of a forecast, the proposed synoptic analysis using multiple scores allows drawing more robust conclusions. Our results show that the best‐performing models use catalogs that span over 100 yr and incorporate fault information, demonstrating and quantifying the value of these data types. Model rankings are stable over time, suggesting that a 10‐year period in Italy can provide sufficient data to discriminate between optimal and suboptimal forecasts. Finally, no model can adequately describe spatial clustering, but those including fault information are less inconsistent with the observations. Prospective testing assesses relevant assumptions and hypotheses of earthquake processes truly out‐of‐sample, thus guiding model development and decision‐making to improve society’s earthquake resilience

Body shape trajectories and risk of breast cancer: results from the SUN ("Seguimiento Universidad De navarra") Project

Objective: The aim of this study was to assess body shape trajectories in childhood and midlife in relation to subsequent risk of breast cancer (BC) in a Mediterranean cohort. Design: The “Seguimiento Universidad de Navarra” (SUN) Project is a dynamic prospective cohort study of university graduates initiated in 1999. With a group-based modelling approach, we assessed body shape trajectories from age 5 to 40 years. Multivariable Cox regression models were used to estimate the hazard ratio (HR) for BC after the age of 40 years according to the body shape trajectory. Setting: City of Pamplona, in the North of Spain. Participants: 6498 women with a mean age of 40 years (sd 9). Results: We identified four distinct body shape trajectories ("childhood lean-midlife increase" (19·9 %), "childhood medium-midlife stable” (53 %), "childhood heavy-midlife stable" (21 %) and "childhood heavy-midlife increase" (6·1 %)). Among 54 978 women-years of follow-up, we confirmed eighty-two incident cases of BC. Women in the "childhood lean-midlife increase" group showed a higher risk of BC (HR = 1·84, 95 % CI 1·11, 3·04) compared with women in the "childhood medium-midlife stable" category. This association was stronger for postmenopausal BC (HR = 2·42, 95 % CI 1·07, 5·48). Conclusions: Our results suggest a role for lifetime adiposity in breast carcinogenesis.Financial support: The SUN Project has received funding from the Spanish Government-Instituto de Salud Carlos III, and the European Regional Development Fund (FEDER) (RD 06/0045, CIBER-OBN, grants PI10/02658, PI10/02293, PI13/00615, PI14/01668, PI14/01798, PI14/01764, PI17/01795 and G03/140), the Navarra Regional Government (45/2011, 122/2014 and 41/2016) and the University of Navarra

A Draft of the Genome of the Gulf Coast tick, \u3ci\u3eAmblyomma maculatum\u3c/i\u3e

The Gulf Coast tick, Amblyomma maculatum, inhabits the Southeastern states of the USA bordering the Gulf of Mexico, Mexico, and other Central and South American countries. More recently, its U.S. range has extended West to Arizona and Northeast to New York state and Connecticut. It is a vector of Rickettsia parkeri and Hepatozoon americanum. This tick species has become a model to study tick/Rickettsia interactions. To increase our knowledge of the basic biology of A. maculatum we report here a draft genome of this tick and an extensive functional classification of its proteome. The DNA from a single male tick was used as a genomic source, and a 10X genomics protocol determined 28,460 scaffolds having equal or more than 10 Kb, totaling 1.98 Gb. The N50 scaffold size was 19,849 Kb. The BRAKER pipeline was used to find the protein-coding gene boundaries on the assembled A. maculatum genome, discovering 237,921 CDS. After trimming and classifying the transposable elements, bacterial contaminants, and truncated genes, a set of 25,702 were annotated and classified as the core gene products. A BUSCO analysis revealed 83.4% complete BUSCOs. A hyperlinked spreadsheet is provided, allowing browsing of the individual gene products and their matches to several databases