Severity as a Priority Setting Criterion: Setting a Challenging Research Agenda

Priority setting in health care is ubiquitous and health authorities are increasingly recognising the need for priority setting guidelines to ensure efficient, fair, and equitable resource allocation. While cost-effectiveness concerns seem to dominate many policies, the tension between utilitarian and deontological concerns is salient to many, and various severity criteria appear to fill this gap. Severity, then, must be subjected to rigorous ethical and philosophical analysis. Here we first give a brief history of the path to today’s severity criteria in Norway and Sweden. The Scandinavian perspective on severity might be conducive to the international discussion, given its long-standing use as a priority setting criterion, despite having reached rather different conclusions so far. We then argue that severity can be viewed as a multidimensional concept, drawing on accounts of need, urgency, fairness, duty to save lives, and human dignity. Such concerns will often be relative to local mores, and the weighting placed on the various dimensions cannot be expected to be fixed. Thirdly, we present what we think are the most pertinent questions to answer about severity in order to facilitate decision making in the coming years of increased scarcity, and to further the understanding of underlying assumptions and values that go into these decisions. We conclude that severity is poorly understood, and that the topic needs substantial further inquiry; thus we hope this article may set a challenging and important research agenda

In-Line Near-Infrared Spectroscopy Gives Rapid and Precise Assessment of Product Quality and Reveals Unknown Sources of Variation—A Case Study from Commercial Cheese Production

Abstract: Quality testing in the food industry is usually performed by manual sampling and at/offline laboratory analysis, which is labor intensive, time consuming, and may suffer from sampling bias. For many quality attributes such as fat, water and protein, in-line near-infrared spectroscopy (NIRS) is a viable alternative to grab sampling. The aim of this paper is to document some of the benefits of in-line measurements at the industrial scale, including higher precision of batch estimates and improved process understanding. Specifically, we show how the decomposition of continuous measurements in the frequency domain, using power spectral density (PSD), may give a useful view of the process and serve as a diagnostic tool. The results are based on a case regarding the large-scale production of Gouda-type cheese, where in-line NIRS was implemented to replace traditional laboratory measurements. In conclusion, the PSD of in-line NIR predictions revealed unknown sources of variation in the process that could not have been discovered using grab sampling. PSD also gave the dairy more reliable data on key quality attributes, and laid the foundation for future improvements.publishedVersio

Performance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in Norway

Wildlife managers are often asking for reliable information of population density across larger spatial scales. In this study, we examined the spatiotemporal relationships between moose density as estimated by cohort analysis and the density indices (1) harvest density (HD; hunter kills per km2), (2) moose seen per unit effort (SPUE), seen moose density (SMD; seen moose per km2), and density of moosevehicle accidents (MVA density; e.g., traffic kills per km2) in 16 areas in Norway with 13–42 years of data. HD showed a close positive relationship with moose density both within and between regions. However, the temporal variation in HD was best explained as a delayed reflection of moose density and tended to overestimate its growth and decline. Conversely, SMD and SPUE were unable to predict the spatial variation in moose density with high precision, though both indices were relatively precise temporal reflectors of moose density. However, the SPUE tended to underestimate population growth, probably because of a decrease in searching efficiency with increasing moose density. Compared to the other indices, MVA density performed poor as an index of moose density within regions, and not at all among regions, but may, because of its independent source of data, be used to cross-check population trends suggested by other indices. Our study shows that the temporal trends in moose density can be surveyed over large areas by the use of cheap indices based on data collected by hunters and local managers, and supports the general assumption that the number of moose killed per km2 provides a precise and isometric index of the variation in moose density at the spatial scale of our study. cohort analysis; isometric index; management; monitoring; population reconstruction; precision; saturation; seen per unit effort (SPUE).Performance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in NorwaypublishedVersio

In-Line Estimation of Fat Marbling in Whole Beef Striploins (Longissimus lumborum) by NIR Hyperspectral Imaging. A Closer Look at the Role of Myoglobin

publishedVersio

The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry

It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.publishedVersio

The predictive power of earnings conference calls : predicting stock price movement with earnings call transcripts

Earnings conference calls are considered a valuable text based information source for investors. This paper investigates the possibility to predict the direction of stock prices by analyzing the transcripts of earnings conference calls. The paper investigates 29 339 different earnings call transcript from 2014 to 2017 and classify the individual documents to either be part of class up or down. Four different machine learning algorithms are used to classify and predict based on the bag of words method. These machine learning algorithms are Naive Bayes, Logistic regression with lasso regularization, Stochastic Gradient Boosting, and Support Vector Machine. All models are compared to a benchmarks based on S&P 500. The model with best performance is logistic regression with a classification error of 43,8%. In total, 2 of 4 models beats the benchmark significantly, namely logistic regression and gradient boosting. With these results, the paper concludes that earnings calls contain predicting power for next day’s stock price direction.nhhma

Radar based central blood pressure estimation

This is a feasibility study in using radar for estimating blood pressure and which could allow for continuous, non-invasive measurements both inside and outside the clinic. Blood pressure has extensive use in emergency care for monitoring the state of a patient, in detection and treatment of hypertension as an important factor of cardiovascular diseases, in emerging applications and more. The invasive cannula for central, continuous, measurements and the sphygmomanometer for peripheral, punctual measurements are currently the reference tools for measuring blood pressure in the operating room and in the physician’s office respectively. However, new blood pressure estimation devices could increase mobility in the hospital and reduce white-coat hypertension in the office. Moreover, such accessible and low-cost devices could extend measurements outside the clinic. The main work was focused on the estimation of the time-varying aortic radius as a prerequisite for the estimation of blood pressure. This work was conducted primarily based on theoretic considerations and simulations using realistic models of the human thorax. In addition, one article analyzed radar signatures from a phantom model and from an in vivo experiment to test findings. Radar echoes were analyzed for information regarding changes in the aorta radius. A magnetic resonance imaging study was conducted to map tissue movements as an aid to radar analysis. Theoretical considerations proposed an optimal frequency band for aorta radius estimation. Given sufficient dynamic range in the radar system, and shown in both simulations and measurements on a phantom model, interference phenomena determined radius estimation success. In the optimistic scenario, radius changes could be estimated. In the more realistic scenario, only a proxy on aorta radius could be tracked. The magnetic resonance imaging study identified a mechanical coupling between the aorta and the heart which would complicate radius estimation. Despite this coupling, the study confirmed findings in the literature that aorta radius is related to pressure. The in vivo experiment showed evidence of an echo from the aorta, however the study did not find evidence of two distinct reflectors. Although successful in identifying a signature from the aorta, the mechanical coupling between the heart and the aorta implies that this signature contains information on both location and radius. Because two distinct echoes could not be identified, direct estimates of radius was not considered feasible. An indirect approach based on blood pressure propagation speed may still be possible, although the coupling would need to be compensated for. As a feasibility study, certain simplifications were imposed and in particular the effects of respiration were disregarded

Fjernmåling av barmasse - en skoghelsevariabel

Barmasse er sterkt knyttet til kronetetthet og til bladarealindeks (LAI), og er viktig for fjernmåling av skogens helsetilstand. Vi kan nå presentere foreløpige, men lovende resultater for måling av barmasse ved hjelp av flybåren laserskanning.Fjernmåling av barmasse - en skoghelsevariabelpublishedVersio

Fjernmåling av barmasse - en skoghelsevariabel

Barmasse er sterkt knyttet til kronetetthet og til bladarealindeks (LAI), og er viktig for fjernmåling av skogens helsetilstand. Vi kan nå presentere foreløpige, men lovende resultater for måling av barmasse ved hjelp av flybåren laserskanning.publishedVersio