On the transport of alkali ions through polymeric mold compounds and polyelectrolyte membranes.

The aim of this work is the attempt in understanding ion transport properties across structured materials such as polyelectrolyte multilayers (PEMs) and highly filled epoxy resins used as an encapsulant, i.e. mold compounds. The ion transport properties are studied by means of the technique of charge attachment induced transport (CAIT), which was recently developed and time-of-flight secondary ion mass spectrometry (ToF-SIMS). The mold compounds studied in this work are of four types (MCP1, MCP2, MCP3, MCP4) with a composition of 80% - 88% of silica filler and the rest of raw materials such as epoxy resin, hardener and flame retardant. The samples are analyzed by means of the CAIT technique, leading to the evaluation of values of ionic conductivity and activation energy related to the process of transport of potassium ions. The ionic conductivity of the mold compounds is on the order of 10-12/10-13 S/cm, while activation energy values are in a range of 1.3 eV - 2.7 eV. For a better understanding of the potassium diffusion process into the mold compounds, the diffusion of potassium through MCP3 sample is investigated via a combination of CAIT method and an ex-situ ToF-SIMS analysis. The ToF-SIMS analysis reveals a depth diffusion profile of the potassium into the material. A mathematical theory is established in order to evaluate the diffusion coefficients for the transport of potassium. According to the numerical procedure, a good fit between experimental and theoretical data is achieved assuming the presence of two different transport pathways operative inside the material: diffusion along the boundaries of grains, i.e. zones of accumulation of the inorganic component of the mold compound and diffusion through the bulk. Diffusion coefficients of DB = 1.8 x 10-21 cm2s-1 and DBG = 5.4 x 10-20 cm2s-1 are found for bulk and grain boundary diffusion, respectively. The PEM films studied in this work are prepared from the layer-by-layer assembly of ionic p-sulfonato-calix[8]arene (calix8) and cationic poly(allylamine hydrochloride) (PAH) onto functionalized gold substrates. Samples with n = 1, 3, 6, 9, 12, 15, 20, 30 bilayers are analyzed by means of the CAIT technique. The data lend support to the conclusion that conductivity, as well as activation energy measurements for (PAH/calix8)n, cannot be acquired under the conditions of the CAIT method, due to the low resistivity shown from the specific PEMs analyzed. Studies on the transport of Li+, K+ and Rb+ through (PAH/calix8)30 are performed by means of CAIT and ToF-SIMS. For each ion beam (Li+, K+, Rb+) two kind of experiments are performed: (PAH/calix8)30 samples are bombarded with the three different alkali ions varying the time for the bombardment, i.e. 5 seconds in one case and 100 seconds in the other. The evaluation of the concentration profiles gives qualitative information regarding the transport properties, whereas numerical analysis of the lithium and rubidium concentration profiles for 5 seconds long bombardment provides quantitative information on the diffusion process. The numerical calculation reveals that the lithium and rubidium transport across the membrane results in a combination of two diffusion pathways accounting for diffusion of slow ions and fast ions. For the lithium case, a good fit is achieved using diffusion coefficients of Dslow,Li+ = 0.4 x 10-16 cm2/s and Dfast,Li+ = 1.2 x 10-15 cm2/s and assuming that 40% of the incoming ions enter the slow pathway, whereas the rest of the ions is transported via a fast pathway. For the rubidium case, the numerical calculation reveals that the fast diffusion pathway is predominant: only the 0.01% of the rubidium ions enter the slow pathway, whereas the rest is dominated from the faster one, with a Dfast,Rb+ = 7 x 10-15 (± 1.5 x 10-15) cm2/s. The study of ion transport of alkali ions Li+ and Rb+ across calixarenes-based PEMs leads thus to the conclusion that the presence of the calixarenes units may influence the type of transport. Lastly, studies of voltage offset measured on current-voltage curves in a typical CAIT experiment are presented. This study aims to give a better understanding of the process beyond the measured voltage offset. In order to do that, a basic CAIT experiment is performed, where a metal plate is bombarded with an ion beam from a potassium emitter of the composition KAlSi2O6 : Mo (1:9). The registered current–voltage curves show finite offsets in the order of 0.5 eV. In order to investigate the detection process of the specific KAlSi2O6 : Mo (1:9) emitter, values of ionic and electronic work function are evaluated. By means of a theoretical model, the recombination of K+ ions from Leucite KAlSi2O6 : Mo (1:9) onto the metal detector is traced to a combination of the ionic work function of the emitter material, the electronic work function of the emitter material and the recombination energy of the elemental potassium I.E.K

ROC-Based Model Estimation for Forecasting Large Changes in Demand

Forecasting for large changes in demand should benefit from different estimation than that used for estimating mean behavior. We develop a multivariate forecasting model designed for detecting the largest changes across many time series. The model is fit based upon a penalty function that maximizes true positive rates along a relevant false positive rate range and can be used by managers wishing to take action on a small percentage of products likely to change the most in the next time period. We apply the model to a crime dataset and compare results to OLS as the basis for comparisons as well as models that are promising for exceptional demand forecasting such as quantile regression, synthetic data from a Bayesian model, and a power loss model. Using the Partial Area Under the Curve (PAUC) metric, our results show statistical significance, a 35 percent improvement over OLS, and at least a 20 percent improvement over competing methods. We suggest management with an increasing number of products to use our method for forecasting large changes in conjunction with typical magnitude-based methods for forecasting expected demand

Continuous glucose monitoring sensors: Past, present and future algorithmic challenges

Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration in real time almost continuously for several days and are provided with hypo/hyperglycemic alerts and glucose trend information. CGM sensors have revolutionized Type 1 diabetes (T1D) management, improving glucose control when used adjunctively to self-monitoring blood glucose systems. Furthermore, CGM devices have stimulated the development of applications that were impossible to create without a continuous-time glucose signal, e.g., real-time predictive alerts of hypo/hyperglycemic episodes based on the prediction of future glucose concentration, automatic basal insulin attenuation methods for hypoglycemia prevention, and the artificial pancreas. However, CGM sensors’ lack of accuracy and reliability limited their usability in the clinical practice, calling upon the academic community for the development of suitable signal processing methods to improve CGM performance. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, to show how they have been tackled by our research group, and to identify the possible future ones

Monitoring the phenolic ripening of red grapes using a multisensor system based on metal-oxide nanoparticles

Producción CientíficaThe maturity of grapes is usually monitored by means of the sugar concentration. However, the assessment of other parameters such as the phenolic content is also important because the phenolic maturity has an important impact on the organoleptic characteristics of wines. In this work, voltammetric sensors able to detect phenols in red grapes have been developed. They are based on metal oxide nanoparticles (CeO2, NiO, and TiO2,) whose excellent electrocatalytic properties toward phenols allows obtaining sensors with detection limits in the range of 10−8 M and coefficients of variation lower than 7%. An electronic tongue constructed using a combination of the nanoparticle-based sensors is capable to monitor the phenolic maturity of red grapes from véraison to maturity. Principal Component Analysis (PCA) can be successfully used to discriminate samples according to the ripeness. Regression models performed using Partial Least Squares (PLS-1) have established good correlations between voltammetric data obtained with the electrochemical sensors and the Total Polyphenolic Index, the Brix degree and the Total Acidity, with correlation coefficients close to 1 and low number of latent variables. An advantage of this system is that the electronic tongue can be used for the simultaneous assessment of these three parameters which are the main factors used to monitor the maturity of grapes. Thus the electronic tongue based on metal oxide nanoparticles can be a valuable tool to monitor ripeness. These results demonstrate the exciting possible applications of metal oxide nanoparticles in the field of electronic tongues.Ministerio de Economía, Industria y Competitividad - Fondo Europeo de Desarrollo Regional (project AGL2015-67482- R)Junta de Castilla y Leon - Fondo Europeo de Desarrollo Regional (project VA011U16)Junta de Castilla y León (grant BOCYL-D-24112015-9

A survey of statistics in three UK general practice journal

Background Many medical specialities have reviewed the statistical content of their journals. To our knowledge this has not been done in general practice. Given the main role of a general practitioner as a diagnostician we thought it would be of interest to see whether the statistical methods reported reflect the diagnostic process. Methods Hand search of three UK journals of general practice namely the British Medical Journal (general practice section), British Journal of General Practice and Family Practice over a one-year period (1 January to 31 December 2000). Results A wide variety of statistical techniques were used. The most common methods included t-tests and Chi-squared tests. There were few articles reporting likelihood ratios and other useful diagnostic methods. There was evidence that the journals with the more thorough statistical review process reported a more complex and wider variety of statistical techniques. Conclusions The BMJ had a wider range and greater diversity of statistical methods than the other two journals. However, in all three journals there was a dearth of papers reflecting the diagnostic process. Across all three journals there were relatively few papers describing randomised controlled trials thus recognising the difficulty of implementing this design in general practice

Using variograms to detect and attribute hydrological change

There have been many published studies aiming to identify temporal changes in river flow time series, most of which use monotonic trend tests such as the Mann–Kendall test. Although robust to both the distribution of the data and incomplete records, these tests have important limitations and provide no information as to whether a change in variability mirrors a change in magnitude. This study develops a new method for detecting periods of change in a river flow time series, using temporally shifting variograms (TSVs) based on applying variograms to moving windows in a time series and comparing these to the long-term average variogram, which characterises the temporal dependence structure in the river flow time series. Variogram properties in each moving window can also be related to potential meteorological drivers. The method is applied to 91 UK catchments which were chosen to have minimal anthropogenic influences and good quality data between 1980 and 2012 inclusive. Each of the four variogram parameters (range, sill and two measures of semi-variance) characterise different aspects of the river flow regime, and have a different relationship with the precipitation characteristics. Three variogram parameters (the sill and the two measures of semi-variance) are related to variability (either day-to-day or over the time series) and have the largest correlations with indicators describing the magnitude and variability of precipitation. The fourth (the range) is dependent on the relationship between the river flow on successive days and is most correlated with the length of wet and dry periods. Two prominent periods of change were identified: 1995–2001 and 2004–2012. The first period of change is attributed to an increase in the magnitude of rainfall whilst the second period is attributed to an increase in variability of the rainfall. The study demonstrates that variograms have considerable potential for application in the detection and attribution of temporal variability and change in hydrological systems

Linkage between increased nociception and olfaction via a SCN9A haplotype

Background and Aims: Mutations reducing the function of Nav1.7 sodium channels entail diminished pain perception and olfactory acuity, suggesting a link between nociception and olfaction at ion channel level. We hypothesized that if such link exists, it should work in both directions and gain-of-function Nav1.7 mutations known to be associated with increased pain perception should also increase olfactory acuity. Methods: SCN9A variants were assessed known to enhance pain perception and found more frequently in the average population. Specifically, carriers of SCN9A variants rs41268673C>A (P610T; n = 14) or rs6746030C>T (R1150W; n = 21) were compared with non-carriers (n = 40). Olfactory function was quantified by assessing odor threshold, odor discrimination and odor identification using an established olfactory test. Nociception was assessed by measuring pain thresholds to experimental nociceptive stimuli (punctate and blunt mechanical pressure, heat and electrical stimuli). Results: The number of carried alleles of the non-mutated SCN9A haplotype rs41268673C/rs6746030C was significantly associated with the comparatively highest olfactory threshold (0 alleles: threshold at phenylethylethanol dilution step 12 of 16 (n = 1), 1 allele: 10.6±2.6 (n = 34), 2 alleles: 9.5±2.1 (n = 40)). The same SCN9A haplotype determined the pain threshold to blunt pressure stimuli (0 alleles: 21.1 N/m2, 1 allele: 29.8±10.4 N/m2, 2 alleles: 33.5±10.2 N/m2). Conclusions: The findings established a working link between nociception and olfaction via Nav1.7 in the gain-of-function direction. Hence, together with the known reduced olfaction and pain in loss-of-function mutations, a bidirectional genetic functional association between nociception and olfaction exists at Nav1.7 level