Daren Anderson
Jan 1, 2008; 26:22-27
Bridges to Excellence

Alan M. Delamater
Apr 1, 2006; 24:71-77
Feature Articles

Technology has changed a number of aspects of our everyday lives and has led to increased efficiency. But when it comes to driving, has it helped or hindered the process? In this article, we will be looking into some of the ways that technology has improved safety on our roads in the last 10 years. […]

A new study published in the Educational Evaluation and Policy Analysis journal found that there is potential for 1-to-1 technology programs to increase achievement in the short term, but more so in the medium term.

A $12.2 million dollar grant from the state Department of Public Instruction will go to a program based at North Carolina State University to provide additional training literacy training to teachers in 16 high-needs districts across the state.

Some district technology leaders say having staff email addresses publicly available opens the door for phishing scams and potential hacks.

Academic achievement at Ohio schools eligible for School Improvement Grants during the Obama administration increased for a few years, a new study says, but SIG's legacy remains complicated.

A state department leader outlines what Tennessee is learning about teacher improvement and where the state still needs to learn more.

In 2018, the programs with new coaches had a combined .433 winning percentage (120-157), up from .416 (117-164) a year earlier. Four schools won or shared conference titles and made the postseason - ETSU (under Randy Sanders), UIW (Eric Morris), North Carolina A&T (Sam Washington) and Wofford (Josh Conklin). The winning percentage at schools with new coaches was .448 (137-169), up from .444 (123-154) in 2018, with a decline in record at 13 schools and a better one at the other 12.

Memory.

Hypertension -- Diet therapy -- Recipes.

[Edinburgh] : [publisher not identified], [1823]

Boston : W.D. Ticknor, 1847.

Edinburgh : printed for William Creech, 1787.

Edinburgh : J. Dunn, 1826.

London : J. Churchill, 1849.

Edinburgh : Bell & Bradfute, 1807.

Edinburgh : And for C. Elliot and T. Kay, London, 1789.

London : H. Renshaw, 1849.

A superintendent outlines the importance of various groups coming together to address teacher recruitment and retention challenges in Idaho.

Application and use of deep learning algorithms for different healthcare applications is gaining interest at a steady pace. However, use of such algorithms can prove to be challenging as they require large amounts of training data that capture different possible variations. This makes it difficult to use them in a clinical setting since in most health applications researchers often have to work with limited data. Less data can cause the deep learning model to over-fit. In this paper, we ask how can we use data from a different environment, different use-case, with widely differing data distributions. We exemplify this use case by using single-sensor accelerometer data from healthy subjects performing activities of daily living - ADLs (source dataset), to extract features relevant to multi-sensor accelerometer gait data (target dataset) for Parkinson's disease classification. We train the pre-trained model using the source dataset and use it as a feature extractor. We show that the features extracted for the target dataset can be used to train an effective classification model. Our pre-trained source model consists of a convolutional autoencoder, and the target classification model is a simple multi-layer perceptron model. We explore two different pre-trained source models, trained using different activity groups, and analyze the influence the choice of pre-trained model has over the task of Parkinson's disease classification.

Datasets in sleep science present challenges for machine learning algorithms due to differences in recording setups across clinics. We investigate two deep transfer learning strategies for overcoming the channel mismatch problem for cases where two datasets do not contain exactly the same setup leading to degraded performance in single-EEG models. Specifically, we train a baseline model on multivariate polysomnography data and subsequently replace the first two layers to prepare the architecture for single-channel electroencephalography data. Using a fine-tuning strategy, our model yields similar performance to the baseline model (F1=0.682 and F1=0.694, respectively), and was significantly better than a comparable single-channel model. Our results are promising for researchers working with small databases who wish to use deep learning models pre-trained on larger databases.

Web and mobile applications enhance efficiency and data accuracy using satellite maps and offline capabilities.

(PRWeb April 23, 2020)

Read the full story at https://www.prweb.com/releases/agileassets_v7_5_improves_flexibility_field_productivity_for_tunnel_inspections_asset_maintenance/prweb17071093.htm

Elizabeth Lorenzi, Ricardo Henao, Katherine Heller.

Source: The Annals of Applied Statistics, Volume 13, Number 4, 2637--2661.

Abstract:
Nearly a third of all surgeries performed in the United States occur for patients over the age of 65; these older adults experience a higher rate of postoperative morbidity and mortality. To improve the care for these patients, we aim to identify and characterize high risk geriatric patients to send to a specialized perioperative clinic while leveraging the overall surgical population to improve learning. To this end, we develop a hierarchical infinite latent factor model (HIFM) to appropriately account for the covariance structure across subpopulations in data. We propose a novel Hierarchical Dirichlet Process shrinkage prior on the loadings matrix that flexibly captures the underlying structure of our data while sharing information across subpopulations to improve inference and prediction. The stick-breaking construction of the prior assumes an infinite number of factors and allows for each subpopulation to utilize different subsets of the factor space and select the number of factors needed to best explain the variation. We develop the model into a latent factor regression method that excels at prediction and inference of regression coefficients. Simulations validate this strong performance compared to baseline methods. We apply this work to the problem of predicting surgical complications using electronic health record data for geriatric patients and all surgical patients at Duke University Health System (DUHS). The motivating application demonstrates the improved predictive performance when using HIFM in both area under the ROC curve and area under the PR Curve while providing interpretable coefficients that may lead to actionable interventions.

The pandemic may force certain improvements but I'm not sure that it will, because political distractions are doing a rather good job of drawing our focus away from fixing things now. For instance, we should be ramping domestic manufacturing of PPEs and ventilators permanently to prepare for a likely huge fall spike in COVID-19 infections. Still, we aren't.

Customer attrition and churn are not new problems. Anyone who has spent time in the sales world has heard statistics around the cost of acquiring a new customer. It can be five to 25 times more expensive to acquire a new customer than to retain an existing one. Improving customer retention by just 5 percent can increase profits by 25-95 percent, depending on your industry and company size.

Traditional views of sensorimotor adaptation (i.e., adaptation of movements to perturbed sensory feedback) emphasize the role of automatic, implicit correction of sensory prediction errors. However, latent memories formed during sensorimotor adaptation, manifest as improved relearning (e.g., savings), have recently been attributed to strategic corrections of task errors (failures to achieve task goals). To dissociate contributions of task errors and sensory prediction errors to latent sensorimotor memories, we perturbed target locations to remove or enforce task errors during learning and/or test, with male/female human participants. Adaptation improved after learning in all conditions where participants were permitted to correct task errors, and did not improve whenever we prevented correction of task errors. Thus, previous correction of task errors was both necessary and sufficient to improve adaptation. In contrast, a history of sensory prediction errors was neither sufficient nor obligatory for improved adaptation. Limiting movement preparation time showed that the latent memories driven by learning to correct task errors take at least two forms: a time-consuming but flexible component, and a rapidly expressible, inflexible component. The results provide strong support for the idea that movement corrections driven by a failure to successfully achieve movement goals underpin motor memories that manifest as savings. Such persistent memories are not exclusively mediated by time-consuming strategic processes but also comprise a rapidly expressible but inflexible component. The distinct characteristics of these putative processes suggest dissociable underlying mechanisms, and imply that identification of the neural basis for adaptation and savings will require methods that allow such dissociations.

SIGNIFICANCE STATEMENT Latent motor memories formed during sensorimotor adaptation manifest as improved adaptation when sensorimotor perturbations are reencountered. Conflicting theories suggest that this "savings" is underpinned by different mechanisms, including a memory of successful actions, a memory of errors, or an aiming strategy to correct task errors. Here we show that learning to correct task errors is sufficient to show improved subsequent adaptation with respect to naive performance, even when tested in the absence of task errors. In contrast, a history of sensory prediction errors is neither sufficient nor obligatory for improved adaptation. Finally, we show that latent sensorimotor memories driven by task errors comprise at least two distinct components: a time-consuming, flexible component, and a rapidly expressible, inflexible component.

Reward has a remarkable ability to invigorate motor behavior, enabling individuals to select and execute actions with greater precision and speed. However, if reward is to be exploited in applied settings, such as rehabilitation, a thorough understanding of its underlying mechanisms is required. In a series of experiments, we first demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Specifically, reward promoted the selection of the correct action in the presence of distractors, while also improving execution through increased speed and maintenance of accuracy. These results led to a shift in the speed-accuracy functions for both selection and execution. In addition, punishment had a similar impact on action selection and execution, although it enhanced execution performance across all trials within a block, that is, its impact was noncontingent to trial value. Although the reward-driven enhancement of movement execution has been proposed to occur through enhanced feedback control, an untested possibility is that it is also driven by increased arm stiffness, an energy-consuming process that enhances limb stability. Computational analysis revealed that reward led to both an increase in feedback correction in the middle of the movement and a reduction in motor noise near the target. In line with our hypothesis, we provide novel evidence that this noise reduction is driven by a reward-dependent increase in arm stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate motor performance without compromising accuracy.

SIGNIFICANCE STATEMENT While reward is well-known for enhancing motor performance, how the nervous system generates these improvements is unclear. Despite recent work indicating that reward leads to enhanced feedback control, an untested possibility is that it also increases arm stiffness. We demonstrate that reward simultaneously improves the selection and execution components of a reaching movement. Furthermore, we show that punishment has a similar positive impact on performance. Importantly, by combining computational and biomechanical approaches, we show that reward leads to both improved feedback correction and an increase in stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate performance without compromising accuracy. This work suggests that stiffness control plays a vital, and underappreciated, role in the reward-based imporvemenets in motor control.

Did you know that cash transfer (CT) programmes in countries of the sub-Saharan Africa actually have a significant impact? In Malawi, these programmes helped families invest in agricultural equipment and livestock to produce their own food and reduce levels of negative coping strategies, like begging and school drop-outs. In Kenya, secondary school attendance rose by 9 percent and access to [...]

Have you ever wondered if you are getting adequate nutrients from the food you eat? It is a common misconception that malnutrition means not getting enough food. This is, however, incorrect! People who take in insufficient food can be malnourished, but also those who consume too much face the same risks. Malnutrition is defined as “An abnormal physiological condition caused by [...]

Some of the most innovative ways being used to improve agricultural practices involve nuclear technology. Nuclear applications in agriculture rely on the use of isotopes and radiation techniques to combat pests and diseases, increase crop production, protect land and water resources, ensure food safety and authenticity, and increase livestock production. FAO and the International Atomic Energy Agency (IAEA) have been expanding [...]

Winnipeg will soon test "small cell" technology to improve cellular reception in parts of Winnipeg, ahead of a possible future transition to 5G service. 

The Flint Water Crisis captured national attention about the dangers of lead contamination in public water supplies. Now, nearly six years after the problem was first detected, health officials are reporting on the well-being of children in Flint.

Brydge on Wednesday launched a new update to improve its Brydge Pro+ keyboard with trackpad that recently starting shipping for iPad Pro. AppleInsider goes hands-on with the latest firmware to see how Brydge's improvements have strengthened the user experience of its flagship product.

As the COVID-19 pandemic continues around the world, countries are extending periods of national lockdown and increasing the need for people to stay home. AppleInsider has compiled a list of free resources, apps, tools, and services that are still available to use while social distancing.

Qualcomm CEO Steve Mollenkopf in an interview on Thursday said the chipmaker's relationship with Apple has greatly improved since the two companies ended a bitter legal battle over patent licensing and royalties in 2019.

The post Learn How to Improve Productivity with Simulation appeared first on The SOLIDWORKS Blog.

OBJECTIVES:

To summarize baseline data and lessons learned from the Autism Learning Health Network, designed to improve care and outcomes for children with autism spectrum disorder (ASD). We describe challenging behaviors, co-occurring medical conditions, quality of life (QoL), receipt of recommended health services, and next steps.

OBJECTIVES:

To determine if a multicomponent intervention was associated with increased use of first-line antibiotics (cephalexin or sulfamethoxazole and trimethoprim) among children with uncomplicated urinary tract infections (UTIs) in outpatient settings.

A Fin24 user wants to know whether paying off a car loan or credit card will make her credit score 'look better.'

What is continuous improvement and why are schools and districts jumping on that bandwagon?

Primary care providers (PCPs) identify patients with undescended testis (UDT) and refer them to surgical specialists. Referral beyond the recommended times for orchiopexy has been reported, and PCPs' accuracy in identifying and distinguishing UDTs from retractile testes has been questioned.

We describe 3 observations that are strongly correlated with UDT, that is, birth history of UDT, prematurity, and visible scrotal asymmetry. UDT diagnoses are best made by 8 months of age, to reduce confusion with testicular retraction and to facilitate timely orchiopexy. (Read the full article)

Prematurely born children have an increased prevalence of behavioral problems in the long term. Knowledge regarding the effects of early intervention programs is sparse, and more randomized controlled trials are warranted.

A modified version of the Mother-Infant Transaction Program showed beneficial effects on behavioral outcomes reported by both parents of preterm infants with birth weights of <2000 g at a corrected age of 5 years. (Read the full article)

Comprehensive home visits conducted by Community Health Workers including environmental remediation and office-based nurse case management improve asthma outcomes.

Implementation of a comprehensive quality improvement program as part of enhanced care of pediatric asthma patients with a history of hospitalizations or emergency department visits can improve health outcomes and be cost-effective as well as reduce health disparities. (Read the full article)

Early administration of oral corticosteroids is essential for children presenting to emergency departments with moderate to severe acute asthma exacerbations, because subsequent admission need is directly related to time to receipt of systemic steroids, yet delays to administration remain long.

A medical directive allowing nurse initiation of oral corticosteroids before physician assessment was associated with improved quality and efficiency of care provided in the pediatric emergency department by ensuring implementation of evidence-based practice. (Read the full article)