Validation of spectral sky radiance derived from all-sky camera images - a case study

Spectral sky radiance (380–760 nm) is derived from measurements with a hemispherical sky imager (HSI)system. The HSI consists of a commercial compact CCD (charge coupled device) camera equipped with a fish-eye lens and provides hemispherical sky images in three reference bands such as red, green and blue. To obtain the spectral sky radiance from these images, non-linear regression functions for various sky conditions have been derived. The camera-based spectral sky radiance was validated using spectral sky radiance measured with a CCD spectroradiometer. The spectral sky radiance for complete distribution over the hemisphere between both instruments deviates by less than 20% at 500 nm for all sky conditions and for zenith angles less than 80 . The reconstructed spectra of the wavelengths 380–760 nm between both instruments at various directions deviate by less than 20% for all sky conditions.DF

Is multidirectional UV exposure responsible for increasing melanoma prevalence with altitude? A hypothesis based on calculations with a 3D-human exposure model

In a recent study, melanoma incidence rates for Austrian inhabitants living at higher altitudes were found to increase by as much as 30% per 100 m altitude. This strong increase cannot simply be explained by the known increase of erythemally-weighted irradiance with altitude, which ranges between 0.5% and 4% per 100 m. We assume that the discrepancy is partially explainable by upwelling UV radiation; e.g., reflected by snow-covered surfaces. Therefore, we present an approach where the human UV exposure is derived by integrating incident radiation over the 3D geometry of a human body, which enables us to take upwelling radiation into account. Calculating upwelling and downwelling radiance with a radiative transfer model for a snow-free valley and for snow-covered mountain terrain (with albedo of 0.6) yields an increase in UV exposure by 10% per 100 m altitude. The results imply that upwelling radiation plays a significant role in the increase of melanoma incidence with altitude.Austrian Climate Research Program (ACRP

Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

In this case study we compare cloud fractional cover measured by radiometers on polar satellites (AVHRR) and on one geostationary satellite (SEVIRI) to ground-based manual (SYNOP) and automated observations by a cloud camera (Hemispherical Sky Imager, HSI). These observations took place in Hannover, Germany, and in Lauder, New Zealand, over time frames of 3 and 2 months, respectively. Daily mean comparisons between satellite derivations and the ground-based HSI found the deviation to be 6 14% for AVHRR and 8 16% for SEVIRI, which can be considered satisfactory. AVHRR’s instantaneous differences are smaller (2 22 %) than instantaneous SEVIRI cloud fraction estimates (8 29 %) when compared to HSI due to resolution and scenery effect issues. All spaceborne observations show a very good skill in detecting completely overcast skies (cloud cover 6 oktas) with probabilities between 92 and 94% and false alarm rates between 21 and 29% for AVHRR and SEVIRI in Hannover, Germany. In the case of a clear sky (cloud cover lower than 3 oktas) we find good skill with detection probabilities between 72 and 76 %. We find poor skill, however, whenever broken clouds occur (probability of detection is 32% for AVHRR and 12% for SEVIRI in Hannover, Germany). In order to better understand these discrepancies we analyze the influence of algorithm features on the satellite-based data. We find that the differences between SEVIRI and HSI cloud fractional cover (CFC) decrease (from a bias of 8 to almost 0 %) with decreasing number of spatially averaged pixels and decreasing index which determines the cloud coverage in each “cloud-contaminated” pixel of the binary map. We conclude that window size and index need to be adjusted in order to improve instantaneous SEVIRI and AVHRR estimates. Due to its automated operation and its spatial, temporal and spectral resolution, we recommend as well that more automated ground-based instruments in the form of cloud cameras should be installed as they cover larger areas of the sky than other automated ground-based instruments. These cameras could be an essential supplement to SYNOP observation as they cover the same spectral wavelengths as the human eye.DF

Solar simulators for healthy Vitamin D synthesis

Background/Aim: The angular distribution of solar radiance and its spectral characteristics is required for the determination of Vitamin D3 production in humans. Materials and Methods: The Vitamin D3 weighted exposure can be calculated by integrating the incident solar spectral radiance over all relevant parts of the human body. A novel instrument allowing simultaneous measurements of spectral radiance from more than 100 directions has been developed. A large solar simulator for controlled experiments is described. Results: In summer it is relatively easy to obtain sufficient Vitamin D because sun exposure times are short. In winter solstice Vitamin D3 cannot be obtained with realistic clothing even if the exposure were extended to all daylight hours. Conclusion: Improved and controlled experiments to determine Vitamin D3 production are required to assess the positive effects of solar UV radiation and to assess its natural variability

Immersive virtual reality fitness games for enhancement of recovery after colorectal surgery: study protocol for a randomised pilot trial

Abstract Background Physical inactivity after surgery is an important risk factor for postoperative complications. Compared to conventional physiotherapy, activity-promoting video games are often more motivating and engaging for patients with physical impairments. This effect could be enhanced by immersive virtual reality (VR) applications that visually, aurally and haptically simulate a virtual environment and provide a more interactive experience. The use of VR-based fitness games in the early postoperative phase could contribute to improved mobilisation and have beneficial psychological effects. Currently, there is no data on the use of VR-based fitness games in the early postoperative period after colorectal surgery. Methods This pilot trial features a single-centre, randomised, two-arm study design with a 1:1 allocation. Patients undergoing elective abdominal surgery for colorectal cancer or liver metastases of colorectal cancer will be recruited. Participants will be randomly assigned to an intervention group or a control group. Patients randomised to the intervention group will perform immersive virtual reality-based fitness exercises during their postoperative hospital stay. Feasibility and clinical outcomes will be assessed. Discussion Early mobilisation after surgery is crucial for reducing many postoperative complications. VR-based interventions are easy to use and often inexpensive, especially compared to interventions that require more medical staff and equipment. VR-based interventions could serve as an alternative or complement to regular physiotherapy and enhance mobilisation after surgery. The proposed pilot study will be the first step to evaluate the feasibility of VR-based interventions in the perioperative period, with the aim of improving the postoperative rehabilitation of cancer patients. Trial registration The trial has been registered in the German Clinical Trials Register (DRKS) Nr. DRKS00024888 , on April 13, 2021, WHO Universal Trial Number (UTN) U1111-1261–5968

Intraoperative endoluminal pyloromyotomy for reduction of delayed gastric emptying after pylorus preserving partial pancreaticoduodenectomy (PORRIDGE trial): study protocol for a randomised controlled trial

BACKGROUND: Pylorus-preserving pancreaticoduodenectomy (ppPD) is a standard surgical procedure for the treatment of resectable neoplasms of the periampullary region. One of the most common postoperative complications after ppPD is delayed gastric emptying (DGE) which reduces quality of life, prevents a timely return to a solid oral diet and prolongs the length of hospital stay. In a retrospective analysis, intraoperative endoluminal pyloromyotomy was associated with a reduced rate of DGE. The aim of this study is to investigate the effect of intraoperative endoluminal pyloromyotomy on postoperative DGE after ppPD in a randomised and controlled setting. METHODS: This randomised trial features parallel group design with a 1:1 allocation ratio and a superiority hypothesis. Patients with a minimum age of 18 years and an indication for ppPD are eligible to participate in this study and will be randomised intraoperatively to receive either endoluminal pyloromyotomy or atraumatic stretching of the pylorus. The sample size calculation (n=64 per study arm) is based on retrospective data. The primary endpoint is the rate of DGE within 30 days. Secondary endpoints are quality of life, operation time, estimated blood loss, length of hospital stay, morbidity and mortality. DISCUSSION: DGE after ppPD is a common complication with an incomplete understood aetiology. Prevention of DGE could improve outcomes and enhance quality of life after one of the most common procedures in pancreatic surgery. This trial will expand the existing evidence on intraoperative pyloromyotomy, and the results will provide additional data on a simple surgical technique that could reduce the incidence of postoperative DGE. TRIAL REGISTRATION: German Clinical Trials RegisterDRKS00013503. Registered on 27 December 2017

IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.This work was supported by the Austrian Science Fund (Grant No. I-2805-B29) to A.v.H. and by the Australian National University Futures Scheme grant to R.L

Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports

BACKGROUND: Natural language processing (NLP) has the potential to automate the reading of radiology reports, but there is a need to demonstrate that NLP methods are adaptable and reliable for use in real-world clinical applications. METHODS: We tested the F1 score, precision, and recall to compare NLP tools on a cohort from a study on delirium using images and radiology reports from NHS Fife and a population-based cohort (Generation Scotland) that spans multiple National Health Service health boards. We compared four off-the-shelf rule-based and neural NLP tools (namely, EdIE-R, ALARM+, ESPRESSO, and Sem-EHR) and reported on their performance for three cerebrovascular phenotypes, namely, ischaemic stroke, small vessel disease (SVD), and atrophy. Clinical experts from the EdIE-R team defined phenotypes using labelling techniques developed in the development of EdIE-R, in conjunction with an expert researcher who read underlying images. RESULTS: EdIE-R obtained the highest F1 score in both cohorts for ischaemic stroke, ≥93%, followed by ALARM+, ≥87%. The F1 score of ESPRESSO was ≥74%, whilst that of Sem-EHR is ≥66%, although ESPRESSO had the highest precision in both cohorts, 90% and 98%. For F1 scores for SVD, EdIE-R scored ≥98% and ALARM+ ≥90%. ESPRESSO scored lowest with ≥77% and Sem-EHR ≥81%. In NHS Fife, F1 scores for atrophy by EdIE-R and ALARM+ were 99%, dropping in Generation Scotland to 96% for EdIE-R and 91% for ALARM+. Sem-EHR performed lowest for atrophy at 89% in NHS Fife and 73% in Generation Scotland. When comparing NLP tool output with brain image reads using F1 scores, ALARM+ scored 80%, outperforming EdIE-R at 66% in ischaemic stroke. For SVD, EdIE-R performed best, scoring 84%, with Sem-EHR 82%. For atrophy, EdIE-R and both ALARM+ versions were comparable at 80%. CONCLUSIONS: The four NLP tools show varying F1 (and precision/recall) scores across all three phenotypes, although more apparent for ischaemic stroke. If NLP tools are to be used in clinical settings, this cannot be performed "out of the box." It is essential to understand the context of their development to assess whether they are suitable for the task at hand or whether further training, re-training, or modification is required to adapt tools to the target task

Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports

BackgroundNatural language processing (NLP) has the potential to automate the reading of radiology reports, but there is a need to demonstrate that NLP methods are adaptable and reliable for use in real-world clinical applications.MethodsWe tested the F1 score, precision, and recall to compare NLP tools on a cohort from a study on delirium using images and radiology reports from NHS Fife and a population-based cohort (Generation Scotland) that spans multiple National Health Service health boards. We compared four off-the-shelf rule-based and neural NLP tools (namely, EdIE-R, ALARM+, ESPRESSO, and Sem-EHR) and reported on their performance for three cerebrovascular phenotypes, namely, ischaemic stroke, small vessel disease (SVD), and atrophy. Clinical experts from the EdIE-R team defined phenotypes using labelling techniques developed in the development of EdIE-R, in conjunction with an expert researcher who read underlying images.ResultsEdIE-R obtained the highest F1 score in both cohorts for ischaemic stroke, ≥93%, followed by ALARM+, ≥87%. The F1 score of ESPRESSO was ≥74%, whilst that of Sem-EHR is ≥66%, although ESPRESSO had the highest precision in both cohorts, 90% and 98%. For F1 scores for SVD, EdIE-R scored ≥98% and ALARM+ ≥90%. ESPRESSO scored lowest with ≥77% and Sem-EHR ≥81%. In NHS Fife, F1 scores for atrophy by EdIE-R and ALARM+ were 99%, dropping in Generation Scotland to 96% for EdIE-R and 91% for ALARM+. Sem-EHR performed lowest for atrophy at 89% in NHS Fife and 73% in Generation Scotland. When comparing NLP tool output with brain image reads using F1 scores, ALARM+ scored 80%, outperforming EdIE-R at 66% in ischaemic stroke. For SVD, EdIE-R performed best, scoring 84%, with Sem-EHR 82%. For atrophy, EdIE-R and both ALARM+ versions were comparable at 80%.ConclusionsThe four NLP tools show varying F1 (and precision/recall) scores across all three phenotypes, although more apparent for ischaemic stroke. If NLP tools are to be used in clinical settings, this cannot be performed “out of the box.” It is essential to understand the context of their development to assess whether they are suitable for the task at hand or whether further training, re-training, or modification is required to adapt tools to the target task