Wavelet-denoising of electroencephalogram and the absolute slope method: a new tool to improve electroencephalographic localization and lateralization

OBJECTIVE: In ictal scalp electroencephalogram (EEG) the presence of artefacts and the wide ranging patterns of discharges are hurdles to good diagnostic accuracy. Quantitative EEG aids the lateralization and/or localization process of epileptiform activity. METHODS: Twelve patients achieving Engel Class I/IIa outcome following temporal lobe surgery (1 year) were selected with approximately 1-3 ictal EEGs analyzed/patient. The EEG signals were denoised with discrete wavelet transform (DWT), followed by computing the normalized absolute slopes and spatial interpolation of scalp topography associated to detection of local maxima. For localization, the region with the highest normalized absolute slopes at the time when epileptiform activities were registered (>2.5 times standard deviation) was designated as the region of onset. For lateralization, the cerebral hemisphere registering the first appearance of normalized absolute slopes >2.5 times the standard deviation was designated as the side of onset. As comparison, all the EEG episodes were reviewed by two neurologists blinded to clinical information to determine the localization and lateralization of seizure onset by visual analysis. RESULTS: 16/25 seizures (64%) were correctly localized by the visual method and 21/25 seizures (84%) by the quantitative EEG method. 12/25 seizures (48%) were correctly lateralized by the visual method and 23/25 seizures (92%) by the quantitative EEG method. The McNemar test showed p=0.15 for localization and p=0.0026 for lateralization when comparing the two methods. CONCLUSIONS: The quantitative EEG method yielded significantly more seizure episodes that were correctly lateralized and there was a trend towards more correctly localized seizures. SIGNIFICANCE: Coupling DWT with the absolute slope method helps clinicians achieve a better EEG diagnostic accuracy.

Extracting models from IDEs

Systems must co-evolve with their context. Reverse engineering tools are a great help in this process of required adaption. In order for these tools to be flexible, they work with models, abstract representations of the source code. The extraction of such information from source code can be done using a parser. However, it is fairly tedious to build new parsers. And this is made worse by the fact that it has to be done over and over again for every language we want to analyze. In this paper we propose a novel approach which minimizes the knowledge required of a certain language for the extraction of models implemented in that language by reflecting on the implementation of preparsed ASTs provided by an IDE. In a second phase we use a technique referred to as Model Mapping by Example to map platform dependent models onto domain specific model.

The impact of absolute importance on prospective memory: Instructions matter

Prospective memory (ProM) is the ability to remember and carry out a planned intention in the future. ProM performance can be improved by instructing participants to prioritize the ProM task over the ongoing task. However, the improvement of ProM performance by emphasizing the relative importance typically restricted to situations in which the overlap between processing requirements of the ProM task and the ongoing task is low. Thus, additional processing resources are allocated to the ProM task and consequently, a cost emerges for the ongoing task. The aim of the present study was to further investigate this relationship. Participants were asked to respond to either semantic or perceptual ProM cues, which were embedded in a complex ongoing short term memory task. We manipulated absolute rather than relative importance by emphasizing the importance of the ProM task to half of the participants (i.e., without instructing them to prioritize it over the ongoing task). The results revealed that importance boosted ProM performance independent of the processing overlap between the ProM task and the ongoing task. Moreover, no additional cost was associated with absolute importance. These results challenge the view that importance always enhances the allocation of resources to the ProM task.

Absolute quantitative real-time polymerase chain reaction for the measurement of human papillomavirus E7 mRNA in cervical cytobrush specimens.

BACKGROUND: Few reports of the utilization of an accurate, cost-effective means for measuring HPV oncogene transcripts have been published. Several papers have reported the use of relative quantitation or more expensive Taqman methods. Here, we report a method of absolute quantitative real-time PCR utilizing SYBR-green fluorescence for the measurement of HPV E7 expression in cervical cytobrush specimens. RESULTS: The construction of a standard curve based on the serial dilution of an E7-containing plasmid was the key for being able to accurately compare measurements between cervical samples. The assay was highly reproducible with an overall coefficient of variation of 10.4%. CONCLUSION: The use of highly reproducible and accurate SYBR-based real-time polymerase chain reaction (PCR) assays instead of performing Taqman-type assays allows low-cost, high-throughput analysis of viral mRNA expression. The development of such assays will help in refining the current screening programs for HPV-related carcinomas.

Surface Roughness and Microhardness of Two Recent CAD/CAM-Materials After Storage

Objectives: To investigate surface roughness and microhardness of two recent resin-ceramic materials for computer-aided design/computer-aided manufacturing (CAD/CAM) after polishing with three polishing systems. Surface roughness and microhardness were measured immediately after polishing and after six months storage including monthly artificial toothbrushing. Methods: Sixty specimens of Lava Ultimate (3M ESPE) and 60 specimens of VITA ENAMIC (VITA Zahnfabrik) were roughened in a standardized manner and polished with one of three polishing systems (n=20/group): Sof-Lex XT discs (SOFLEX; three-step (medium-superfine); 3M ESPE), VITA Polishing Set Clinical (VITA; two-step; VITA Zahnfabrik), or KENDA Unicus (KENDA; one-step; KENDA Dental). Surface roughness (Ra; μm) was measured with a profilometer and microhardness (Vickers; VHN) with a surface hardness indentation device. Ra and VHN were measured immediately after polishing and after six months storage (tap water, 37°C) including monthly artificial toothbrushing (500 cycles/month, toothpaste RDA ~70). Ra- and VHN-values were analysed with nonparametric ANOVA followed by Wilcoxon rank sum tests (α=0.05). Results: For Lava Ultimate, Ra (mean [standard deviation] before/after storage) remained the same when polished with SOFLEX (0.18 [0.09]/0.19 [0.10]; p=0.18), increased significantly with VITA (1.10 [0.44]/1.27 [0.39]; p=0.0001), and decreased significantly with KENDA (0.35 [0.07]/0.33 [0.08]; p=0.03). VHN (mean [standard deviation] before/after storage) decreased significantly regardless of polishing system (SOFLEX: 134.1 [5.6]/116.4 [3.6], VITA: 138.2 [10.5]/115.4 [5.9], KENDA: 135.1 [6.2]/116.7 [6.3]; all p<0.0001). For VITA ENAMIC, Ra (mean [standard deviation] before/after storage) increased significantly when polished with SOFLEX (0.37 [0.18]/0.41 [0.14]; p=0.01) and remained the same with VITA (1.32 [0.37]/1.31 [0.40]; p=0.58) and with KENDA (0.81 [0.35]/0.78 [0.32]; p=0.21). VHN (mean [standard deviation] before/after storage) remained the same regardless of polishing system (SOFLEX: 284.9 [24.6]/282.4 [31.8], VITA: 284.6 [28.5]/276.4 [25.8], KENDA: 292.6 [26.9]/282.9 [24.3]; p=0.42-1.00). Conclusion: Surface roughness and microhardness of Lava Ultimate was more affected by storage and artificial toothbrushing than was VITA ENAMIC.

Relation between Excitation Power Density and Er3+ Doping Yielding the Highest Absolute Upconversion Quantum Yield

The upconversion quantum yield (UCQY) is one of the most significant parameters for upconverter materials. A high UCQY is essential for a succesful integration of upconversion in many applications, such as harvesting of the solar radiation. However, little is known about which doping level of the rare-earth ions yields the highest UCQY in the different host lattices and what are the underlying causes. Here, we investigate which Er3+ doping yields the highest UCQY in the host lattices β-NaYF4 and Gd2O2S under 4I15/2 → 4I13/2 excitation. We show for both host lattices that the optimum Er3+ doping is not fixed and it actually decreases as the irradiance of the excitation increases. To find the optimum Er3+ doping for a given irradiance, we determined the peak position of the internal UCQY as a function of the average Er−Er distance. For this purpose, we used a fit on experimental data, where the average Er−Er distance was calculated from the Er3+ doping of the upconverter samples and the lattice parameters of the host materials. We observe optimum average Er−Er distances for the host lattices β-NaYF4 and Gd2O2S with differences <14% at the same irradiance levels, whereas the optimum Er3+ doping are around 2× higher for β-NaYF4 than for Gd2O2S. Estimations by extrapolation to higher irradiances indicate that the optimum average Er−Er distance converges to values around 0.88 and 0.83 nm for β-NaYF4 and Gd2O2S, respectively. Our findings point to a fundamental relationship and focusing on the average distance between the active rare-earth ions might be a very efficient way to optimize the doping of rare-earth ions with regard to the highest achievable UCQY.

Pollen dispersal properties of Poaceae and Cyperaceae: First estimates of their absolute pollen productivities

Pollen-trap results from the Swiss Alps 1996–2009 were used to assess the pollen dispersal–deposition properties of Poaceae (grasses) and Cyperaceae (sedges). Dispersal parameter values were investigated for a modified version of the Prentice–Sugita pollen dispersal–deposition model. Appropriate values (i.e. realistic in the field and allowing realistic modelling results) for wind speed are suggested to be in the range of 3–7 m s− 1 and for pollen an injection height of 0.03–0.1 m above the ground. The appropriate range of pollen injection height values for grasses and sedges differs from that of trees in the same area, suggesting different pollen dispersal properties between herbs and trees. In addition, logarithmic weighting of the vegetation was tested as an alternative to the modified Prentice–Sugita model. This yielded very similar results, suggesting that the use of such much simpler approximations of the pollen–vegetation relationship is a plausible alternative. Based on the modified Prentice–Sugita model, absolute pollen productivity for Poaceae was estimated to 7300 ± 400 grains cm− 2 year− 1 (1 SE). The data basis for Cyperaceae is smaller than for Poaceae, but the dispersal parameter values determined as appropriate for Poaceae yield good results. Absolute pollen productivity for Cyperaceae was estimated to 6300 ± 1100 grains cm− 2 year− 1 (1 SE).

The impact of absolute importance and processing overlaps on prospective memory performance

Prospective memory is the ability to remember an intention at an appropriate moment in the future. Prospective memory tasks can be more or less important. Previously, importance was manipulated by emphasizing the importance of the prospective memory task relative to the ongoing task it was embedded in. This resulted in better prospective memory performance but also ongoing task costs. In the present study, we simply instructed one group of participants that the prospective memory task was important (i.e., absolute importance instruction) and compared them to a group with relative importance instructions and a control group. The results showed that absolute importance lead to an increase in prospective memory performance without enhancing ongoing task costs, whereas relative importance resulted in both increased prospective memory performance and ongoing task costs. Thus, prospective memory can be enhanced without ongoing task costs, which is particularly crucial for safety-work contexts.

Modeling absolute differences in life expectancy with a censored skew-normal regression approach.

Parameter estimates from commonly used multivariable parametric survival regression models do not directly quantify differences in years of life expectancy. Gaussian linear regression models give results in terms of absolute mean differences, but are not appropriate in modeling life expectancy, because in many situations time to death has a negative skewed distribution. A regression approach using a skew-normal distribution would be an alternative to parametric survival models in the modeling of life expectancy, because parameter estimates can be interpreted in terms of survival time differences while allowing for skewness of the distribution. In this paper we show how to use the skew-normal regression so that censored and left-truncated observations are accounted for. With this we model differences in life expectancy using data from the Swiss National Cohort Study and from official life expectancy estimates and compare the results with those derived from commonly used survival regression models. We conclude that a censored skew-normal survival regression approach for left-truncated observations can be used to model differences in life expectancy across covariates of interest.