Development of a novel continuous statistical modelling technique for detecting the adulteration of extra virgin olive oil with hazelnut oil by using spectroscopic data

The adulteration of extra virgin olive oil with other vegetable oils is a certain problem with economic and health consequences. Current official methods have been proved insufficient to detect such adulterations. One of the most concerning and undetectable adulterations with other vegetable oils is the addition of hazelnut oil. The main objective of this work was to develop a novel dimensionality reduction technique able to model oil mixtures as a part of an integrated pattern recognition solution. This final solution attempts to identify hazelnut oil adulterants in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. The proposed Continuous Locality Preserving Projections (CLPP) technique allows the modelling of the continuous nature of the produced in house admixtures as data series instead of discrete points. This methodology has potential to be extended to other mixtures and adulterations of food products. The maintenance of the continuous structure of the data manifold lets the better visualization of this examined classification problem and facilitates a more accurate utilisation of the manifold for detecting the adulterants.

The need for qualitative methodologies in cancer cachexia research

Background: Cancer cachexia is not well understood or managed in clinical practice (Delmore 2000; Poole and Froggatt 2002). Whilst a dedicated effort has been made towards understanding the biological processes of the syndrome, little attention has been paid to its multidimensional impact. This is despite previous qualitative research, enriching our understanding of the holistic impact of the syndrome which traditional quantitative methods could not have uncovered (Reid 2007).

Aim: The aim of this study is to determine the adequacy of the existing clinical knowledge base of cancer cachexia management.

Methods: A systematic critical review of the literature on cancer cachexia was undertaken.

Results: There is a need to develop protocols for care delivery, which move beyond a purely biological approach to care towards a more holistic approach. This can only be achieved by gaining the perspectives of those who are involved in care delivery to advanced cancer patients with cachexia and their families using qualitative methodologies.

Conclusions: Cancer cachexia is a complex, challenging syndrome, which must be understood from a holistic bio-psychosocial model of care in order to meet the multidimensional needs of this client population. The perspectives of those involved in care delivery is required in order to contribute to a knowledge base which will inform the development of interventions directed at empowering patients and their families to understand cancer cachexia and recognise it as part of the disease process.

Toward Characterization Of The Type IIP Supernova Progenitor Population: A Statistical Sample Of Light Curves From Pan-STARRS1

In recent years, wide-field sky surveys providing deep multi-band imaging have presented a new path for indirectly characterizing the progenitor populations of core-collapse supernovae (SN): systematic light curve studies. We assemble a set of 76 grizy-band Type IIP SN light curves from Pan-STARRS1, obtained over a constant survey program of 4 years and classified using both spectroscopy and machine learning-based photometric techniques. We develop and apply a new Bayesian model for the full multi-band evolution of each light curve in the sample. We find no evidence of a sub-population of fast-declining explosions (historically referred to as "Type IIL" SNe). However, we identify a highly significant relation between the plateau phase decay rate and peak luminosity among our SNe IIP. These results argue in favor of a single parameter, likely determined by initial stellar mass, predominantly controlling the explosions of red supergiants. This relation could also be applied for supernova cosmology, offering a standardizable candle good to an intrinsic scatter of 0.2 mag. We compare each light curve to physical models from hydrodynamic simulations to estimate progenitor initial masses and other properties of the Pan-STARRS1 Type IIP SN sample. We show that correction of systematic discrepancies between modeled and observed SN IIP light curve properties and an expanded grid of progenitor properties, are needed to enable robust progenitor inferences from multi-band light curve samples of this kind. This work will serve as a pathfinder for photometric studies of core-collapse SNe to be conducted through future wide field transient searches.

Methodologies for the Development of the Management of Cough: CHEST Guideline and Expert Panel Report

BACKGROUND: This series of guidance documents on cough, which will be published over time, is a hybrid of two processes: (1) evidence-based guidelines and (2) trustworthy consensus statements based on a robust and transparent process.

METHODS: The CHEST Guidelines Oversight Committee selected a nonconflicted Panel Chair and jointly assembled an international panel of experts in each clinical area with few, if any, conflicts of interest. PICO (population, intervention, comparator, outcome)-based key questions and parameters of eligibility were developed for each clinical topic to inform the comprehensive literature search. Existing guidelines, systematic reviews, and primary studies were assessed for relevance and quality. Data elements were extracted into evidence tables and synthesized to provide summary statistics. These, in turn, are presented to support the evidence-based graded recommendations. A highly structured consensus-based Delphi approach was used to provide expert advice on all guidance statements. Transparency of process was documented.

RESULTS: Evidence-based guideline recommendations and consensus-based suggestions were carefully crafted to provide direction to health-care providers and investigators who treat and/or study patients with cough. Manuscripts and tables summarize the evidence in each clinical area supporting the recommendations and suggestions.

CONCLUSIONS: The resulting guidance statements are based on a rigorous methodology and transparency of process. Unless otherwise stated, the recommendations and suggestions meet the guidelines for trustworthiness developed by the Institute of Medicine and can be applied with confidence by physicians, nurses, other health-care providers, investigators, and patients.

Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

A new statistical framework for the quantification of covariate associations with species distributions

Identifying processes that shape species geographical ranges is a prerequisite for understanding environmental change. Currently, species distribution modelling methods do not offer credible statistical tests of the relative influence of climate factors and typically ignore other processes (e.g. biotic interactions and dispersal limitation). We use a hierarchical model fitted with Markov Chain Monte Carlo to combine ecologically plausible niche structures using regression splines to describe unimodal but potentially skewed response terms. We apply spatially explicit error terms that account for (and may help identify) missing variables. Using three example distributions of European bird species, we map model results to show sensitivity to change in each covariate. We show that the overall strength of climatic association differs between species and that each species has considerable spatial variation in both the strength of the climatic association and the sensitivity to climate change. Our methods are widely applicable to many species distribution modelling problems and enable accurate assessment of the statistical importance of biotic and abiotic influences on distributions.

The subjective numeracy scale as a tool for assessing statistical numeracy in older adult populations

BACKGROUND:
Statistical numeracy, necessary for making informed medical decisions, is reduced among older adults who make more decisions about their medical care and treatment than at any other stage of life. Objective numeracy scales are a source of anxiety among patients, heightened among older adults.
OBJECTIVE:
We investigate the subjective numeracy scale as an alternative tool for measuring statistical numeracy with older adult samples.
METHODS:
Numeracy was assessed using objective measures for 526 adults ranging in age from 18 to 93 years, and all participants provided subjective numeracy ratings.
RESULTS:
Subjective numeracy correlated highly with objective measurements among oldest adults (70+ years; r = 0.51, 95% CI 0.32, 0.66), and for younger age groups. Subjective numeracy explained 33.2% of age differences in objective numeracy.
CONCLUSION:
The subjective numeracy scale provides an effective tool for assessing statistical numeracy for broad age ranges and circumvents problems associated with objective numeracy measures.