Perceptions of Campus Climate by African American Students at a Predominantly White Institution

Studies show that despite the focus of much educational research on closing the gap in higher education between students from different socioeconomic or racial/ethnic backgrounds, the gap remains. While student characteristics do play a role in influencing educational attainment they do not explain the persistence of the gap. To understand this more fully, research has looked into how campus racial climates affect educational outcomes for underrepresented students. These studies have shown that culturally engaging campus environments help students feel a stronger sense of belonging on campus, which improves the likelihood they will eventually attain a degree. The purpose of this study is to gain a deeper understanding of the perception of campus climate by African American students at a predominantly white university utilizing the Culturally Engaging Campus Environments framework (Museus, Yi, & Saelua, 2017). For this study, I interviewed 17 African American students at the University of Pittsburgh about their experience on campus as related to aspects of cultural relevancy and cultural responsiveness to understand their perceptions of campus climate. These interviews provided insight into how students structure their campus environment in ways to promote their success by 1) fostering relationships with faculty and staff that are sources of cultural responsiveness and relationships with peers for a sense of cultural relevancy, 2) choosing peer groups and student organizations which provide support in navigating the mental and emotional load of their experience at a PWI, particularly as related to dealing with racial micro-aggressions, and 3) carefully considering to engage in cross-cultural interactions when given a choice as experiences of cross cultural engagement are complex. The implications of these results for practitioners in higher education are discussed and recommendations are provided on how to improve educational outcomes for African American students at the University

Effects on Task Performance and Psychophysiological Measures of Performance During Normobaric Hypoxia Exposure

Human-autonomous systems have the potential to mitigate pilot cognitive impairment and improve aviation safety. A research team at NASA Langley conducted an experiment to study the impact of mild normobaric hypoxia induction on aircraft pilot performance and psychophysiological state. A within-subjects design involved non-hypoxic and hypoxic exposures while performing three 10-minute tasks. Results indicated the effect of 15,000 feet simulated altitude did not induce significant performance decrement but did produce increase in perceived workload. Analyses of psychophysiological responses evince the potential of biomarkers for hypoxia onset. This study represents on-going work at NASA intending to add to the current knowledge of psychophysiologically-based input to automation to increase aviation safety. Analyses involving coupling across physiological systems and wavelet transforms of cortical activity revealed patterns that can discern between the simulated altitude conditions. Specifically, multivariate entropy of ECG/Respiration components were found to be significant predictors (p< 0.02) of hypoxia. Furthermore, in EEG, there was a significant decrease in mid-level beta (15.19-18.37Hz) during the hypoxic condition in thirteen of sixteen sites across the scalp. Task performance was not appreciably impacted by the effect of 15,000 feet simulated altitude. Analyses of psychophysiological responses evince the potential of biomarkers for mild hypoxia onset.The potential for identifying shifts in underlying cortical and physiological systems could serve as a means to identify the onset of deteriorated cognitive state. Enabling such assessment in future flightdecks could permit increasingly autonomous systems-supported operations. Augmenting human operator through assessment of cognitive impairment has the potential to further improve operator performance and mitigate human error in safety critical contexts. This study represents ongoing work at NASA intending to add to the current knowledge of psychophysiologically-based input to automation to increase aviation safety

Quantum state engineering assisted by entanglement

We suggest a general scheme for quantum state engineering based on conditional measurements carried out on entangled twin-beam of radiation. Realistic detection schemes such as {\sc on/off} photodetection, homodyne detection and joint measurement of two-mode quadratures are analyzed in details. Imperfections of the apparatuses, such as nonunit quantum efficiency and finite resolution, are taken into account. We show that conditional {\sc on/off} photodetection provides a reliable scheme to verify nonclassicality, whereas conditional homodyning represents a tunable and robust source of squeezed light. We also describe optical teleportation as a conditional measurement, and evaluate the degrading effects of finite amount of entanglement, decoherence due to losses, and nonunit quantum efficiency.Comment: Some pics with low resolution. Originals at http://www.qubit.i

Prediction of Cognitive States During Flight Simulation Using Multimodal Psychophysiological Sensing

The Commercial Aviation Safety Team found the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness (ASA), and distraction was involved in all of them. Research on attention-related human performance limiting states (AHPLS) such as channelized attention, diverted attention, startle/surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors was implemented to simultaneously measure their physiological markers during a high fidelity flight simulation human subject study. Twenty-four pilot participants were asked to wear the sensors while they performed benchmark tasks and motion-based flight scenarios designed to induce AHPLS. Pattern classification was employed to predict the occurrence of AHPLS during flight simulation also designed to induce those states. Classifier training data were collected during performance of the benchmark tasks. Multimodal classification was performed, using pre-processed electroencephalography, galvanic skin response, electrocardiogram, and respiration signals as input features. A combination of one, some or all modalities were used. Extreme gradient boosting, random forest and two support vector machine classifiers were implemented. The best accuracy for each modality-classifier combination is reported. Results using a select set of features and using the full set of available features are presented. Further, results are presented for training one classifier with the combined features and for training multiple classifiers with features from each modality separately. Using the select set of features and combined training, multistate prediction accuracy averaged 0.64 +/- 0.14 across thirteen participants and was significantly higher than that for the separate training case. These results support the goal of demonstrating simultaneous real-time classification of multiple states using multiple sensing modalities in high fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents

The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

A core outcome set for studies of gestational diabetes mellitus prevention and treatment

AIMS/HYPOTHESIS: The aim of this systematic review was to develop core outcome sets (COSs) for trials evaluating interventions for the prevention or treatment of gestational diabetes mellitus (GDM). METHODS: We identified previously reported outcomes through a systematic review of the literature. These outcomes were presented to key stakeholders (including patient representatives, researchers and clinicians) for prioritisation using a three-round, e-Delphi study. A priori consensus criteria informed which outcomes were brought forward for discussion at a face-to-face consensus meeting where the COS was finalised. RESULTS: Our review identified 74 GDM prevention and 116 GDM treatment outcomes, which were presented to stakeholders in round 1 of the e-Delphi study. Round 1 was completed by 173 stakeholders, 70% (121/173) of whom went on to complete round 2; 84% (102/121) of round 2 responders completed round 3. Twenty-two GDM prevention outcomes and 30 GDM treatment outcomes were discussed at the consensus meeting. Owing to significant overlap between included prevention and treatment outcomes, consensus meeting stakeholders agreed to develop a single prevention/treatment COS. Fourteen outcomes were included in the final COS. These consisted of six maternal outcomes (GDM diagnosis, adherence to the intervention, hypertensive disorders of pregnancy, requirement and type of pharmacological therapy for hyperglycaemia, gestational weight gain and mode of birth) and eight neonatal outcomes (birthweight, large for gestational age, small for gestational age, gestational age at birth, preterm birth, neonatal hypoglycaemia, neonatal death and stillbirth). CONCLUSIONS/INTERPRETATION: This COS will enable future GDM prevention and treatment trials to measure similar outcomes that matter to stakeholders and facilitate comparison and combination of these studies. TRIAL REGISTRATION: This study was registered prospectively with the Core Outcome Measures in Effectiveness Trials (COMET) database: http://www.comet-initiative.org/studies/details/686/

Apolipoprotein E Genotype and Cardiovascular Diseases in the Elderly

The apolipoprotein E (APOE) genotype is a genetic risk factor for dementia, Alzheimer’s disease, and cardiovascular disease (CVD). It includes three alleles (e2, e3, e4) that are located on chromosome 19q3.2. The e3 allele is the most common and is more common in people of Northern European ancestry and less common in those of Asian ancestry. Those with at least one e4 allele are at increased risk for CVD outcomes. It is well established that the presence of an e4 allele is linked to higher low-density lipoprotein cholesterol levels, even at young ages. Even though most CVD occurs in older people, there are few studies of the effects of APOE on CVD in older people. This review addresses recent research on the links between APOE, CVD, and vascular mechanisms by which APOE may affect CVD in the elderly

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic