Teacher Perceptions on Advisory Model at the Middle Level Through the Lens of Conflict and Connection

In education, we seek to prepare students in a variety of facets. In order to prepare those students, we must look at a multitude of different factors in regard to that preparation. As students continue through their educational career, their time with the teachers that are educating them often decreases. In order to continue to advocate for students and build skills with students, we have seen a shift to focus on student relationships as well as curriculum. Using data collected with Pianta’s Student-Teacher Relationship Scale-Short Form and open-ended questions, this study seeks to investigate the effectiveness of the current middle school advisory model, and the preparation and training received in regard to that model. Previous studies have indicated that the advisory model has been given a clear purpose, but teachers may not always know that purpose. There is also little research completed in regard to the best practices for advisory programs at middle school and how to train and prepare staff. To investigae this issue, staff completed two Likert Scale surveys and four open-ended questions. Each survey was completed with a student in the teacher’s advisory in mind, a student with exemplary behavior and a student with challenging behavior. These categories were then used to review variance between whole group responses, and teachers who were deemed high in each categories responses. The open-ended questions were reviewed using grounded-theory open-coding, and codes were determined for each response. Results of the study indicated that teachers had a clear understanding of purpose, but that more research need to be completed to determine best practice for training and preparation

Comprehensive assessment of a peer mentor program for first-year students

College students who engage in first-year programs such as peer mentorship are correlated with higher achievement. Peer mentorship can also have a significant impact on students\u27 feelings of belonging to their campus community. This mixed-methods study will provide a comprehensive assessment of a Class Leader (CL) program. Data will include first-semester outcomes (i.e., first-term GPA; retention) for all students (N ~ 1850) and first-generation students as compared to non-participants, survey responses (n ~ 471) about students\u27 experiences with CLs and perceptions related to the program, and focus group data from students, CLs, and instructors at the end of the semester

Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

Background: Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to predict use of healthcare resources at community level by comparing the predictive power of four different multimorbidity measures. Methods: A population health study including all citizens ≥18 years (n = 6,102,595) living in Catalonia (ES) on 31 December 2014 was done using registry data. Primary care service utilization during 2015 was evaluated through four outcome variables: A) Frequent attendants, B) Home care users, C) Social worker users, and, D) Polypharmacy. Prediction of the four outcome variables (A to D) was carried out with and without multimorbidity assessment. We compared the contributions to model fitting of the following multimorbidity measures: i) Charlson index; ii) Number of chronic diseases; iii) Clinical Risk Groups (CRG); and iv) Adjusted Morbidity Groups (GMA). Results: The discrimination of the models (AUC) increased by including multimorbidity as covariate into the models, namely: A) Frequent attendants (0.771 vs 0.853), B) Home care users (0.862 vs 0.890), C) Social worker users (0.809 vs 0.872), and, D) Polypharmacy (0.835 vs 0.912). GMA showed the highest predictive power for all outcomes except for polypharmacy where it was slightly below than CRG. Conclusions: We confirmed that multimorbidity assessment enhanced prediction of use of healthcare resources at community level. The Catalan population-based risk assessment tool based on GMA presented the best combination of predictive power and applicability

Combined assimilation of IASI and MLS observations to constrain tropospheric and stratospheric ozone in a global chemical transport model

Accurate and temporally resolved fields of free-troposphere ozone are of major importance to quantify the intercontinental transport of pollution and the ozone radiative forcing. We consider a global chemical transport model (MOdèle de Chimie Atmosphérique à Grande Échelle, MOCAGE) in combination with a linear ozone chemistry scheme to examine the impact of assimilating observations from the Microwave Limb Sounder (MLS) and the Infrared Atmospheric Sounding Interferometer (IASI). The assimilation of the two instruments is performed by means of a variational algorithm (4D-VAR) and allows to constrain stratospheric and tropospheric ozone simultaneously. The analysis is first computed for the months of August and November 2008 and validated against ozonesonde measurements to verify the presence of observations and model biases. Furthermore, a longer analysis of 6 months (July–December 2008) showed that the combined assimilation of MLS and IASI is able to globally reduce the uncertainty (root mean square error, RMSE) of the modeled ozone columns from 30 to 15% in the upper troposphere/lower stratosphere (UTLS, 70–225 hPa). The assimilation of IASI tropospheric ozone observations (1000–225 hPa columns, TOC – tropospheric O₃ column) decreases the RMSE of the model from 40 to 20% in the tropics (30° S–30° N), whereas it is not effective at higher latitudes. Results are confirmed by a comparison with additional ozone data sets like the Measurements of OZone and wAter vapour by aIrbus in-service airCraft (MOZAIC) data, the Ozone Monitoring Instrument (OMI) total ozone columns and several high-altitude surface measurements. Finally, the analysis is found to be insensitive to the assimilation parameters. We conclude that the combination of a simplified ozone chemistry scheme with frequent satellite observations is a valuable tool for the long-term analysis of stratospheric and free-tropospheric ozone

Mmokolodi solar PV project – Demonstrating sustainable renewable energy system design and potential for Botswana rural electrification

The aim of this paper is to introduce the AU-funded distributed solar photovoltaic (PV) research project currently being implemented at the Mmokolodi Village in Botswana. The paper shall outline the potential of the project for rural electrification and assess system design considerations guaranteeing its sustainability. A descriptive methodology is considered sufficient to capture the complexity of the project's design goal and its sustenance beyond the project time. The inherent complexity cited underlines the need for a holistic system design view embracing technical, social, economical, environmental, and ownership dimensions. These dimensions are substantiated in the paper applying suitable frameworks. Within one of the frameworks, an overview of possible business models is explored, in particular looking at Product-Service Systems and related ownership models as promising approach for project sustainability. The current status of this ongoing research work limits definitive commentary about the expected final result. Whereas valid business case statements for sustaining the Mmokolodi project can already be made, the other sustainability metrics namely feasibility, viability and desirability remain projected goals. The results of this research exemplify the need for interdisciplinary collaboration in sustainable energy research undertakings. The assessments made will help future project implementers to anticipate implementation hurdles proactively. The results will help energy end-users at the Mmokolodi community to access affordable modern energy and assess its desirability. For policy planners these results may shape energy planning to embrace the complexity inherent in the energy planning process

FARMAPRICE: A Pharmacogenetic Clinical decision support system for precise and Cost-Effective Therapy

Pharmacogenetic (PGx) guidelines for the precise dosing and selection of drugs remain poorly implemented in current clinical practice. Among the barriers to the implementation process is the lack of clinical decision support system (CDSS) tools to aid health providers in managing PGx information in the clinical context. The present study aimed to describe the first Italian endeavor to develop a PGx CDSS, called FARMAPRICE. FARMAPRICE prototype was conceived for integration of patient molecular data into the clinical prescription process in the Italian Centro di Riferimento Oncologico (CRO)-Aviano Hospital. It was developed through a coordinated partnership between two high-tech companies active in the computerization of the Italian healthcare system. Introducing FARMAPRICE into the clinical setting can aid physicians in prescribing the most efficacious and cost-effective pharmacological therapy available

Long-term effect of neonatal inhibition of APP gamma-secretase on hippocampal development in the Ts65Dn mouse model of Down syndrome

Neurogenesis impairment is considered a major determinant of the intellectual disability that characterizes Down syndrome (DS), a genetic condition caused by triplication of chromosome 21. Previous evidence obtained in the Ts65Dn mouse model of DS showed that the triplicated gene APP (amyloid precursor protein) is critically involved in neurogenesis alterations. In particular, excessive levels of AICD (amyloid precursor protein intracellular domain) resulting from APP cleavage by gamma-secretase increase the transcription of Ptch1, a Sonic Hedgehog (Shh) receptor that keeps the mitogenic Shh pathway repressed. Previous evidence showed that neonatal treatment with ELND006, an inhibitor of gamma-secretase, reinstates the Shh pathway and fully restores neurogenesis in Ts65Dn pups. In the framework of potential therapies for DS, it is extremely important to establish whether the positive effects of early intervention are retained after treatment cessation. Therefore, the goal of the current study was to establish whether early treatment with ELND006 leaves an enduring trace in the brain of Ts65Dn mice. Ts65Dn and euploid pups were treated with ELND006 in the postnatal period P3-P15 and the outcome of treatment was examined at ~ one month after treatment cessation. We found that in treated Ts65Dn mice the pool of proliferating cells in the hippocampal dentate gyrus (DG) and total number of granule neurons were still restored as was the number of pre- and postsynaptic terminals in the stratum lucidum of CA3, the site of termination of the mossy fibers from the DG. Accordingly, patch-clamp recording from field CA3 showed functional normalization of the input to CA3. Unlike in field CA3, the number of pre- and postsynaptic terminals in the DG of treated Ts65Dn mice was no longer fully restored. The finding that many of the positive effects of neonatal treatment were retained after treatment cessation provides proof of principle demonstration of the efficacy of early inhibition of gamma-secretase for the improvement of brain development in DS

Expanding the Landscape of Chromatin Modification (CM)-Related Functional Domains and Genes in Human

Chromatin modification (CM) plays a key role in regulating transcription, DNA replication, repair and recombination. However, our knowledge of these processes in humans remains very limited. Here we use computational approaches to study proteins and functional domains involved in CM in humans. We analyze the abundance and the pair-wise domain-domain co-occurrences of 25 well-documented CM domains in 5 model organisms: yeast, worm, fly, mouse and human. Results show that domains involved in histone methylation, DNA methylation, and histone variants are remarkably expanded in metazoan, reflecting the increased demand for cell type-specific gene regulation. We find that CM domains tend to co-occur with a limited number of partner domains and are hence not promiscuous. This property is exploited to identify 47 potentially novel CM domains, including 24 DNA-binding domains, whose role in CM has received little attention so far. Lastly, we use a consensus Machine Learning approach to predict 379 novel CM genes (coding for 329 proteins) in humans based on domain compositions. Several of these predictions are supported by very recent experimental studies and others are slated for experimental verification. Identification of novel CM genes and domains in humans will aid our understanding of fundamental epigenetic processes that are important for stem cell differentiation and cancer biology. Information on all the candidate CM domains and genes reported here is publicly available