Educator Motivation for Acquiring Expertise to Support Students with Dyslexia: A Phenomenological Study

The purpose of this phenomenological study is to describe the invested motivation for acquiring expertise to support students with dyslexia for elementary school teachers at a charter school in a northeastern state. Teachers employed at Oakdale-Mission Charter School are uniquely positioned to receive in-service teacher training support regarding teaching those with dyslexia. The lack of Orton Gillingham-certified teachers to provide for those with dyslexia prevents these students from adequately receiving access and equity in a school district in a large metropolitan city in a northeastern state. Therefore, Oakdale-Mission Charter School was explored as a unique and innovative solution for those with dyslexia using an in-service teacher training model. The central question of this study was: What are the lived experiences of elementary charter school teachers with invested motivation for acquiring expertise to support students with dyslexia? The theory that supported this central question and guided this study was Knowles’ adult learning theory and the concept of andragogy, predicated on the notion that teacher investment is a critical component in adopting effective instructional practices. The hermeneutical phenomenological design of this study offered an analysis of the various factors associated with teacher motivation. The data collection process included interviews, a focus group, and a journal prompt. This study included 12 participants who experienced professional development training using the Orton Gillingham methodologies. The research uncovered invested motivation associated with supporting those with dyslexia. Future research should explore further options for developing teacher expertise using other teacher support training models through a qualitative study method

Is depression a real risk factor for acute myocardial infarction mortality? A retrospective cohort study

Background: Depression has been associated with a higher risk of cardiovascular events and a higher mortality in patients with one or more comorbidities. This study investigated whether continuative use of antidepressants (ADs), considered as a proxy of a state of depression, prior to acute myocardial infarction (AMI) is associated with a higher mortality afterwards. The outcome to assess was mortality by AD use. Methods: A retrospective cohort study was conducted in the Veneto Region on hospital discharge records with a primary diagnosis of AMI in 2002-2015. Subsequent deaths were ascertained from mortality records. Drug purchases were used to identify AD users. A descriptive analysis was conducted on patients' demographics and clinical data. Survival after discharge was assessed with a Kaplan-Meier survival analysis and Cox's multiple regression model. Results: Among 3985 hospital discharge records considered, 349 (8.8%) patients were classified as AD users'. The mean AMI-related hospitalization rate was 164.8/100,000 population/year, and declined significantly from 204.9 in 2002 to 130.0 in 2015, but only for AD users (-40.4%). The mean overall follow-up was 4.64.1years. Overall, 523 patients (13.1%) died within 30days of their AMI. The remainder survived a mean 5.3 +/- 4.0years. After adjusting for potential confounders, use of antidepressants was independently associated with mortality (adj OR=1.75, 95% CI: 1.40-2.19). Conclusions: Our findings show that AD users hospitalized for AMI have a worse prognosis in terms of mortality. The use of routinely-available records can prove an efficient way to monitor trends in the state of health of specific subpopulations, enabling the early identification of AMI survivors with a history of antidepressant use

Memory-aware sizing for in-memory databases

In-memory database systems are among the technological drivers of big data processing. In this paper we apply analytical modeling to enable efficient sizing of in-memory databases. We present novel response time approximations under online analytical processing workloads to model thread-level forkjoin and per-class memory occupation.We combine these approximations with a non-linear optimization program to minimize memory swapping in in-memory database clusters. We compare our approach with state-of-the-art response time approximations and trace-driven simulation using real data from an SAP HANA in-memory system and show that our optimization model is significantly more accurate than existing approaches at similar computational costs

Linear Growth through 12 Years is Weakly but Consistently Associated with Language and Math Achievement Scores at Age 12 Years in 4 Low- or Middle-Income Countries.

BackgroundWhether linear growth through age 12 y is associated with language and math achievement at age 12 y remains unclear.ObjectiveOur objective was to investigate associations of linear growth through age 12 y with reading skill, receptive vocabulary, and mathematics performance at age 12 y in 4 low- or middle-income countries (LMICs).MethodsWe analyzed data from the Young Lives Younger Cohort study in Ethiopia (n = 1275), India (n = 1350), Peru (n = 1402), and Vietnam (n = 1594). Age 1, 5, 8, and 12 y height-for-age z scores (HAZ) were calculated. Language and math achievement at age 12 y was assessed with the use of country-specific adaptations of the Peabody Picture Vocabulary Test, the Early Grades Reading Assessment, and a mathematics test; all test scores were standardized by age within country. We used path analysis to examine associations of HAZ with achievement scores. Twelve models were examined at each age (3 tests across 4 countries).ResultsMean HAZ in each country was <-1.00 at all ages. Overall, linear growth through age 12 y was associated with 0.4-3.4% of the variance in achievement scores. HAZ at 1 y was positively and significantly associated with the test score in 11 of the 12 models. This association was significantly mediated through HAZ at 5, 8, and 12 y in 9 of the models. HAZ at 5, 8, and 12 y was positively and significantly associated with test scores in 8, 8, and 6 models, respectively. These associations were mediated through HAZ at older ages in 6 of the HAZ at 5-y models and in 6 of the HAZ at 8-y models.ConclusionChild relative linear growth between ages 1 and 12 y was weakly but consistently associated with language and math achievement at age 12 y in 4 LMICs

Performance engineering for microservices and serverless applications: the RADON approach

Microservices and serverless are becoming integral parts of mod-ern cloud-based applications. Tailored performance engineering isneeded for assuring that the applications meet their requirementsfor quality attributes such as timeliness, resource efficiency, andelasticity. A novel DevOps-based framework for developing mi-croservices and serverless applications is being developed in theRADON project. RADON contributes to performance engineeringby including novel approaches for modeling, deployment optimiza-tion, testing, and runtime management. This paper summarizes thecontents of our tutorial presented at the 11th ACM/SPEC Interna-tional Conference on Performance Engineering (ICPE)

Immunomodulation in the treatment and/or prevention of bronchial asthma

ABSTRACTThe immunologic hallmark of atopic allergy and asthma is an increased production of IgE and T helper (h) type 2 cell cytokines (interleukin (IL)-4, IL-5, IL-9 and IL-13) by Th cells reacting to common environmental allergens. All of us inhale allergens and healthy non-atopics produce allergen-specific IgG1, IgG4 and the Th1 cytokine interferon-α, as well as IL-12 from macrophages. We now have many modalities of immunomodulation to decrease the effect of IL-4 or IL-5 or production and level of IgE or agents to shift the immune response from a Th2 to a Th1 response, thereby decreasing the allergic inflammatory response in the airways. In the present review we focus on conventional immunotherapy, mycobacterial vaccines, DNA vaccines using cytosine guanosine, inhibitors of IL-4 and IL-5 and anti-IgE: Omalizumab

Strength asymmetries are muscle-specific and metric-dependent

We investigated if dominance affected upper limbs muscle function, and we calculated the level of agreement in asymmetry direction across various muscle-function metrics of two heterologous muscle groups. We recorded elbow flexors and extensors isometric strength of the dominant and non-dominant limb of 55 healthy adults. Participants performed a series of explosive contractions of maximal and submaximal amplitudes to record three metrics of muscle performance: maximal voluntary force (MVF), rate of force development (RFDpeak), and RFD-Scaling Factor (RFD-SF). At the population level, the MVF was the only muscle function that showed a difference between the dominant and non-dominant sides, being on average slightly (3-6%) higher on the non-dominant side. At the individual level, the direction agreement among heterologous muscles was poor for all metrics (Kappa values ≤ 0.15). When considering the homologous muscles, the direction agreement was moderate between MVF and RFDpeak (Kappa = 0.37) and low between MVF and RFD-SF (Kappa = 0.01). The asymmetries are muscle-specific and rarely favour the same side across different muscle-performance metrics. At the individual level, no one side is more performative than the other: each limb is favoured depending on muscle group and performance metric. The present findings can be used by practitioners that want to decrease the asymmetry levels as they should prescribe specific exercise training for each muscle

Guest Editorial: Special section on embracing artificial intelligence for network and service management

Artificial Intelligence (AI) has the potential to leverage the immense amount of operational data of clouds, services, and social and communication networks. As a concrete example, AI techniques have been adopted by telcom operators to develop virtual assistants based on advances in natural language processing (NLP) for interaction with customers and machine learning (ML) to enhance the customer experience by improving customer flow. Machine learning has also been applied to finding fraud patterns which enables operators to focus on dealing with the activity as opposed to the previous focus on detecting fraud

The importance of passive integrated transponder (PIT) tags for measuring life-history traits of sea turtles

Capture-mark-recapture studies rely on the identification of individuals through time, using markers or tags, which are assumed to be retained. This assumption, however, may be violated, having implications for population models. In sea turtles, individual identification is typically based on external flipper tags, which can be combined with internal passive integrated transponder (PIT) tags. Despite the extensive use of flipper tags, few studies have modelled tag loss using continuous functions. Using a 26-year dataset for sympatrically nesting green (Chelonia mydas) and loggerhead (Caretta caretta) turtles, this study aims to assess how PIT tag use increases the accuracy of estimates of life-history traits. The addition of PIT tags improved female identification: between 2000 and 2017, 53% of green turtles and 29% of loggerhead turtles were identified from PIT tags alone. We found flipper and PIT tag losses were best described by decreasing logistic curves with lower asymptotes. Excluding PIT tags from our dataset led to underestimation of flipper tag loss, reproductive periodicity, reproductive longevity and annual survival, and overestimation of female abundance and recruitment for both species. This shows the importance of PIT tags in improving the accuracy of estimates of life-history traits. Thus, estimates where tag loss has not been corrected for should be interpreted with caution and could bias IUCN Red List assessments. As such, long-term population monitoring programmes should aim to estimate tag loss and assess the impact of loss on life-history estimates, to provide robust estimates without which population models and stock assessments cannot be derived accurately

Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

<p>Abstract</p> <p>Background</p> <p>Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system.</p> <p>Results</p> <p>We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples.</p> <p>Conclusion</p> <p>RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the sensitivity of the DNA microarray expression profiling assay for whole blood samples. While blockage of globin transcripts during first strand cDNA synthesis with globin PNAs resulted in the best overall performance in this study, we conclude that selection of a protocol for expression profiling studies in blood should depend on several factors, including implementation requirements of the method and study design. RNA isolated from either freshly collected or frozen blood samples stored in PAXGene tubes can be used without altering gene expression profiles.</p