Instructional Alignment of Workplace Readiness Skills in Marketing Education

This study examined high school marketing education teachers’ knowledge of workplace readiness skills and whether that knowledge had an impact on student workplace readiness skill achievement. Further, this study examined the usage of Virginia’s 13 Workplace Readiness Skills curriculum and identified the teaching methods and instructional strategies used to disseminate the skills to students. Three sets of data were used for this study: teacher workplace readiness skills data, teacher survey data, and student workplace readiness skills post-test data. Pearson’s correlation was used to determine whether teacher knowledge of workplace readiness skills had an impact on student attainment of the same. The results showed that while overall teacher scores did not show a statistical significance on overall student scores, there were four individual skill areas in which there was a relationship between teacher and student scores

Landfast ice controls on turbulence in Antarctic coastal seas

Knowledge of the ocean surface layer beneath Antarctic landfast ice is sparse. In this article surface layer turbulent and fine structure are quantified with and without landfast ice in the same West Antarctic Peninsula location. Landfast ice reduced turbulence levels locally to an order of magnitude less than ice-free values, and near-inertial energy and sub-inertial tidal energy levels to less than half their ice-free values. Vertical turbulent heat and nutrient fluxes were, respectively, 6 and 10 times greater than previously estimated. Under-ice tidal energy dissipation over the entire Antarctic continental shelf due to seasonal landfast ice cover is estimated at 788 MW. The total rate of wind-generated turbulence in the surface ocean is greatly reduced by the presence of seasonal landfast ice to an average of 14% of the ice-free value, but with large sectoral variations. Counter-intuitively, however, tides and wind contribute approximately equally to the turbulent kinetic energy budget of the upper ocean between the Antarctic coastline and the maximal landfast ice extent, with large sectoral variations, attributed to geographic variations in the strength of the barotropic tide

Creation of a Web-Based Tool to Facilitate Community Connectivity

Introduction: Artificial intelligence-based modelling has created an opportunity to improve upon existing hospital readmission risk score systems by redefining priority and uncovering new criteria, but inherent systematic errors known as algorithmic bias can impact applicability. This study evaluated whether there is racial bias for unplanned readmission risk scores in a novel model prepared for the CMS AI challenge. Methods: The study population provided by the CMS challenge included Medicare recipients from 2012 (unique beneficiaries n=1,667,362, total claims n=34,233,260). Risk scores for unplanned hospital readmissions were projected on the basis of clinical and demographic criteria, including age, sex, comorbidities, and prior hospitalizations. Evaluation of algorithmic bias on racial subgroups was estimated using Kernel Density Estimate (KDE) plot and Jensen-Shannon divergence, methods for visualizing probability density and describing similarity between probability distributions. The Jensen-Shannon distances for each race’s model forecasts were calculated between two racial groups and scaled relative to mean values within each individual racial group. Results: Comparison of probability distributions between racial subgroups using Jensen-Shannon distances scaled relative to individual racial groups were 0 to 0.1 and depicted using KDE plot (Figure 1). At a predefined “high risk” model threshold of 0.1, false negatives (missed readmissions predictions) totaled 159,169 (FN rates of 0.36-0.51% for all racial groups). False positives (incorrect high-risk labels) totaled 5,861,737. Discussion: Jensen-Shannon distances of 0-0.01 between racial groups and our KDE plot curves suggest no significant implicit algorithmic bias for racial subgroups with regards to readmission risk. Our threshold yields minimal false negatives at expense of greater false positives, a potentially justified trade-off in cases where costs of failure to identify high risk is greater than cost of intervention. The models prepared in this CMS AI challenge submission may be effective, with low false negative rate, for clinical use in readmission risk assessment for patients regardless of race

Base excision repair apurinic/apyrimidinic endonucleases in apicomplexan parasite Toxoplasma gondii

DNA repair is essential for cell viability and proliferation. In addition to reactive oxygen produced as a byproduct of their own metabolism, intracellular parasites also have to manage oxidative stress generated as a defense mechanism by the host. The spontaneous loss of DNA bases due to hydrolysis and oxidative DNA damage in intracellular parasites is great, but little is known about the type of DNA repair machineries that exist in these early-branching eukaryotes. However, it is clear, processes similar to DNA base excision repair (BER) must exist to rectify spontaneous and host-mediated damage in Toxoplasma gondii. Here we report that T. gondii, an opportunistic protozoan pathogen, possesses two apurinic/apyrimidinic (AP) endonucleases that function in DNA BER. We characterize the enzymatic activities of Toxoplasma exonuclease III (ExoIII, or Ape1) and endonuclease IV (EndoIV, or Apn1), designated TgAPE and TgAPN, respectively. Over-expression of TgAPN in Toxoplasma conferred protection from DNA damage, and viable knockouts of TgAPN were not obtainable. We generated an inducible TgAPN knockdown mutant using a ligand-controlled destabilization domain to establish that TgAPN is critical for Toxoplasma to recover from DNA damage. The importance of TgAPN and the fact that humans lack any observable APN family activity highlights TgAPN as a promising candidate for drug development to treat toxoplasmosis

Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

Large, pretrained models are commonly finetuned with imagery that is heavily augmented to mimic different conditions and scales, with the resulting models used for various tasks with imagery from a range of spatial scales. Such models overlook scale-specific information in the data for scale-dependent domains, such as remote sensing. In this paper, we present Scale-MAE, a pretraining method that explicitly learns relationships between data at different, known scales throughout the pretraining process. Scale-MAE pretrains a network by masking an input image at a known input scale, where the area of the Earth covered by the image determines the scale of the ViT positional encoding, not the image resolution. Scale-MAE encodes the masked image with a standard ViT backbone, and then decodes the masked image through a bandpass filter to reconstruct low/high frequency images at lower/higher scales. We find that tasking the network with reconstructing both low/high frequency images leads to robust multiscale representations for remote sensing imagery. Scale-MAE achieves an average of a $2.4 - 5.6\%$ non-parametric kNN classification improvement across eight remote sensing datasets compared to current state-of-the-art and obtains a $0.9$ mIoU to $1.7$ mIoU improvement on the SpaceNet building segmentation transfer task for a range of evaluation scales

Climate change and marine vertebrates

Climate change impacts on vertebrates have consequences for marine ecosystem structures and services. We review marine fish, mammal, turtle, and seabird responses to climate change and discuss their potential for adaptation. Direct and indirect responses are demonstrated from every ocean. Because of variation in research foci, observed responses differ among taxonomic groups (redistributions for fish, phenology for seabirds). Mechanisms of change are (i) direct physiological responses and (ii) climate-mediated predator-prey interactions. Regional-scale variation in climate-demographic functions makes range-wide population dynamics challenging to predict. The nexus of metabolism relative to ecosystem productivity and food webs appears key to predicting future effects on marine vertebrates. Integration of climate, oceanographic, ecosystem, and population models that incorporate evolutionary processes is needed to prioritize the climate-related conservation needs for these species

Mental health and the criminal justice system: The role of interagency training to promote practitioner understanding of the diversion agenda

Historically there has been a significant under-recognition of mental health problems among people in the criminal justice system, and little research exploring the issues encountered by those with mental health problems who come into contact with the criminal justice system. Recent policy has highlighted the importance of early identification of mental health needs in criminal cases, and the role of diversion of offenders into appropriate mental health services. However research suggests that currently the provision of mental health services for offenders is patchy, and it has been suggested that improved interagency communication and training is required to improve the diversion of offenders with mental health problems into more appropriate mental health provision.The aim of this paper is to consider the current position of those with mental health conditions within the criminal justice system in England, and discuss how joint interagency training can improve understanding of the diversion agenda for the range of practitioners that come into contact with offenders with mental health problems. The perspectives of a range of practitioners who attended a joint interagency training day will be discussed, and recommendations for future training will be offered. © 2014 Taylor & Francis

Multicentre, randomised clinical trial of paediatric concussion assessment of rest and exertion (PedCARE): a study to determine when to resume physical activities following concussion in children.

INTRODUCTION: Rest until symptom-free, followed by a progressive stepwise return to activities, is often prescribed in the management of paediatric concussions. Recent evidence suggests prolonged rest may hinder recovery, and early resumption of physical activity may be associated with more rapid recovery postconcussion. The primary objective is to determine whether the early reintroduction of non-contact physical activity beginning 72 hours postinjury reduces postconcussive symptoms at 2 weeks in children following an acute concussion as compared with a rest until asymptomatic protocol. METHODS AND ANALYSIS: This study is a randomised clinical trial across three Canadian academic paediatric emergency departments. A total of 350 participants, aged 10-17.99 years, who present within 48 hours of an acute concussion, will be recruited and randomly assigned to either the study intervention protocol (resumption of physical activity 72 hours postconcussion even if experiencing symptoms) or physical rest until fully asymptomatic. Participants will document their daily physical and cognitive activities. Follow-up questionnaires will be completed at 1, 2 and 4 weeks postinjury. Compliance with the intervention will be measured using an accelerometer (24 hours/day for 14 days). Symptoms will be measured using the validated Health and Behaviour Inventory. A linear multivariable model, adjusting for site and prognostically important covariates, will be tested to determine differences between groups. The proposed protocol adheres to the RCT-CONSORT guidelines. DISCUSSION: This trial will determine if early resumption of non-contact physical activity following concussion reduces the burden of concussion and will provide healthcare professionals with the evidence by which to recommend the best timing of reintroducing physical activities