A review of the use of a systematic observation method in coaching research between 1997-2016

© 2016 Informa UK Limited, trading as Taylor & Francis Group. A systematic observation method has been one of the most popularly employed methods in coaching research. Kahan’s review of this method conducted between 1975 and 1997 highlighted the key trends in this research, and offered methodological guidance for researchers wishing to use this method in their research. The purpose of this review was to provide an update of the use of a systematic observation method in coaching research and assess the extent to which the calls made by Kahan have been addressed. While in some respect this field of study has progressed (i.e., the introduction of qualitative methods), researchers adopting this method have failed to attend to many of the issues Kahan raised. For this method to continue to make a positive contribution towards the coaching research literature, researchers need to more critically reflect on how and why they are employing this method. At present, some of the decisions made by researchers who have conducted work in this area are not justified with a rationale. It is our intention that this review will serve as guidance for researchers and practitioners, and editors and reviewers of journals when attempting to assess the quality of this type of work

The Lone Ranger

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Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Can Recurrence Quantification Analysis Be Useful in the Interpretation of Airborne Turbulence Measurements?

In airborne data or model outputs, clouds are often defined using information about Liquid Water Content (LWC). Unfortunately LWC is not enough to retrieve information about the dynamical boundary of the cloud, that is, volume of turbulent air around the cloud. In this work, we propose an algorithmic approach to this problem based on a method used in time series analysis of dynamical systems, namely Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA). We construct RPs using time series of turbulence kinetic energy, vertical velocity and temperature fluctuations as variables important for cloud dynamics. Then, by studying time series of laminarity (LAM), a variable which is calculated using RPs, we distinguish between turbulent and non-turbulent segments along a horizontal flight leg. By selecting a single threshold of this quantity, we are able to reduce the number of subjective variables and their thresholds used in the definition of the dynamical cloud boundary

An evaluation of a pilot of daily testing of SARS-CoV-2 contacts in acute hospital and ambulance trusts in England

OBJECTIVES: Healthcare worker (HCW) SARS-CoV-2 contacts in England have been required to quarantine, creating staff shortages. We piloted daily contact testing (DCT) to assess its feasibility as an alternative. STUDY DESIGN: Observational service evaluation. METHODS: We conducted an observational service evaluation of seven-day daily contact testing using antigen lateral flow devices, (LFDs) at four acute hospital trusts and one ambulance trust in England. Mixed methods were employed, utilising aggregate and individual-level test monitoring data, semi-structured interviews, and a survey of eligible contacts. RESULTS: In total, 138 HCWs were identified as contacts of a confirmed SARS-CoV-2 case. Of these, 111 (80%) consented to daily LFD testing, of whom 82 (74%) completed the required programme without interruption, and 12 (11%) completed with interruption. Fifty-eight (52%) participants and two (7·4%) non-participants completed the survey. In total, 28 interviews were conducted with participants, site and infection control leads, and union representatives. One participant tested positive on LFD and polymerase chain reaction (PCR) test. Three participants tested positive on PCR but not LFD. DCT was well-accepted by trusts and staff. Participants reported no relaxation of their infection prevention and control behaviours. No incidents of transmission were detected. An estimated 729 potential days of work absence were averted. CONCLUSIONS: DCT can be acceptably operated in a healthcare setting, averting quarantine-related work absences in HCW SARS-CoV-2 contacts

Effect of Acute Heat Exposure on the Pressor Response to a Voluntary Hypoxic Apnea: A Cross-tolerance Study

The pressor response induced by a voluntary hypoxic apnea is exaggerated in individuals with obstructive sleep apnea and is strongly correlated to sympathetic overactivity. Acute heat exposure alters neural control of blood pressure, but its effect on the pressor response to a voluntary hypoxic apnea has never been explored. PURPOSE: To test the hypothesis that acute heat exposure attenuates the pressor response to a voluntary hypoxic apnea, and thereby manifest as a form of physiological cross-tolerance. METHODS: Eight adults (3 females, 26 ± 2 yrs) were exposed to passive heat stress (water perfused suit) sufficient to increase body core temperature by 1.2 °C. Voluntary hypoxic apneas were performed in duplicate before acute heat exposure (pre-heat) and in recovery when body core temperature returned to ≤ 0.3 °C of baseline. Participants breathed gas mixtures of varying FiO2 (21%, 16%, and 12%; randomized) for 1 min followed immediately by a 15 s end-expiratory apnea. Beat-by-beat arterial blood pressure (Finometer) and arterial oxygen saturation (finger pulse oximetry) were measured throughout. The pressor response was calculated as the difference between baseline mean arterial pressure and the peak response following each apnea. RESULTS: The change in arterial oxygen saturation during each apnea did not differ from pre-heat to recovery (FiO2 21%, pre-heat 0 ± 1 % vs. recovery 0 ± 2 %; FiO2 16%, pre-heat -4 ± 1 % vs. recovery -4 ± 2 %; FiO2 12%, pre-heat -8 ± 3 % vs. recovery -10 ± 4 %; P = 0.3 for interaction). The pressor response to a voluntary apnea was attenuated in recovery from acute heat exposure across all concentrations of FiO2 (FiO2 21%, pre-heat 19 ± 8 mmHg vs. recovery 16 ± 8 mmHg; FiO2 16%, pre-heat 27 ± 8 mmHg vs. recovery 20 ± 8 mmHg; FiO2 12%, pre-heat 33 ± 11 mmHg vs. recovery 27 ± 13 mmHg; P = 0.02 for main effect of time). CONCLUSION: These data suggest that acute heat exposure induces a cross-tolerance effect such that the pressor response to a voluntary hypoxic apnea is reduced. Acute heat exposure could improve hypertension in adults with obstructive sleep apnea, secondary to altered chemoreflex function and sympathetic neural control, and provide additional therapeutic options for this population to improve cardiovascular health

Cloud Cover in the Australian Region: Development and Validation of a Cloud Masking, Classification and Optical Depth Retrieval Algorithm for the Advanced Himawari Imager

This paper presents a cloud masking, cloud classification and optical depth retrieval algorithm and its application to the Advanced Himawari Imager (AHI) on the Himawari-8/9 satellites using visible, near infrared and thermal infrared bands. A time-series-based approach was developed for cloud masking which was visually assessed and quantitatively validated over 1 year of daytime data for both land and ocean against the level 2 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 1 km cloud layer product (version 4.10). An overall hit rate (the proportion of pixels identified by both sensors as either clear or cloudy) of 87% was found. However, analysis revealed that, when partially cloudy conditions were experienced, the small footprint of the CALIOP sensor (70 meters beam size sampling every 330 meters along the ground track) had a major impact on the hit rate. When partially cloudy pixels are excluded a hit rate of ~98% was found, even for thin clouds with optical depth less than 0.25. A two-way confidence index for the cloud mask was developed which could be used to reclassify the pixels depending on applications, either biasing toward clearness or cloudiness. On the basis of the cloud masking, classification and optical depth retrieval was performed based on radiative transfer modeling. Small modeling error was found, and inspection of typical cloud classification examples showed that the results were consistent with cloud texture and cloud top temperatures. While difficult to validate retrieved cloud properties directly, an indirect quantitative validation was performed by comparing surface-level solar flux computed from the retrieved cloud properties with in-situ measurements at 11 sites across Australia for up to 3 years. Excellent agreement between calculated and measured solar flux was found, with a mean monthly bias of 2.96 W/m2 and RMSE of 8.91 W/m2, and the correlation coefficient exceeding 0.98 at all sites. Further assessment was conducted by comparing seasonal and annual cloud fraction with that of ISCCP (International Satellite Cloud Climatology Project) over Australia and surrounding region. It showed high degree of resemblance between the two datasets in their total cloud fraction. The geographical distribution of cloud classes also showed broad resemblance, though detailed differences exist, especially for high clouds, which is probably due to the use of different cloud classification systems in the two datasets. The products generated from this study are being used in several applications including ocean color remote sensing, solar energy, vegetation monitoring and detection of smoke for the study of their health impacts, and aerosol and land surface bidirectional reflectance distribution function (BRDF) retrieval. The method developed herein can be applied to other geostationary sensors