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Aims: Previous studies have demonstrated substantial variability in manual assessment of QRS complex duration (QRSd). Disagreements in QRSd measurements were also found in several automated algorithms tested on digitized electrocardiogram (ECG) recordings. The aim of our study was to investigate the variability of automated QRSd measurements performed by two commercially available electrocardiographs.Methods and Results: Two GE MAC 5000 (GE-1 and GE-2) electrocardiographs and two Mortara ELI 350 (Mortara-1 and Mortara-2) electrocardiographs were used in the study. Participants for the study were recruited from patients hospitalized in the department of cardiology of a university hospital. Participants underwent up to four recording sessions within a single day with a different electrocardiograph at each session when two to four immediately successive ECG recordings were undertaken. In 76 patients, 683 ECGs were recorded; the mean QRSd was 109.0 ± 26.1 ms. The QRSd difference ≥10 ms between the first and second intra-session ECG was found in 7, 3, 20, and 14% of ECG pairs for GE-1, GE-2, Mortara-1, and Mortara-2, respectively. No inter-session difference in QRSd was found within both manufacturers. In individual patients, Mortara calculated the mean QRSd to be longer by 7.3 ms (95% CI: 6.2-8.5 ms, P < 0.0001) with a 2.1-times (95% CI: 1.9-2.4) greater standard deviation of the mean QRSd (7.1 vs. 3.3 ms, P < 0.001).Conclusion: Electrocardiographs from two manufacturers measured QRSd values with a systematic difference and a significantly different level of precision. This may have important clinical implications in selection of suitable candidates for cardiac resynchronization therapy. [ABSTRACT FROM AUTHOR]

Background/objectives Pancreatic ductal adenocarcinoma (PDAC) is frequently heralded by an impairment of glucose homeostasis. Dipeptidyl peptidase-IV (DPP-IV) and fibroblast activation protein alpha (FAP) are aminopeptidases that regulate several bioactive peptides involved in glucoregulation, and are frequently dysregulated in cancer. The present study analyzes blood plasma levels and the quantity and localization of DPP-IV and FAP in PDAC tissues. Methods DPP-IV and FAP concentration and enzymatic activity were evaluated in the plasma from 93 PDAC, 39 type 2 diabetes mellitus (T2DM) and 29 control subjects, and in matched paired non-tumorous and tumor tissues from 48 PDAC patients. The localization of DPP-IV and FAP was determined using immunohistochemistry and catalytic histochemistry. Results The enzymatic activity and concentration of DPP-IV was higher in PDAC tumor tissues compared to non-tumorous pancreas. DPP-IV was expressed in cancer cells and in the fibrotic stroma by activated (myo)fibroblasts including DPP-IV + FAP + cells. FAP was expressed in stromal cells and in some cancer cells and its expression was increased in the tumors. Plasmatic DPP-IV enzymatic activity, and in particular the ratio between DPP-IV enzymatic activity and concentration in PDAC with recent onset DM was higher compared to T2DM. In contrast, the plasmatic FAP enzymatic activity was lower in PDAC compared to T2DM and controls and rose after tumor removal. Conclusions DPP-IV-like enzymatic activity is upregulated in PDAC tissues. PDAC patients with recent onset diabetes or prediabetes have increased plasmatic DPP-IV enzymatic activity. These changes may contribute to the frequently observed association of PDAC and recent onset impairment of glucoregulation. [ABSTRACT FROM AUTHOR]

Habitat use of the Aesculapian snake (Zamenis longissimus) at the northern extreme of its range in northwest Bohemia was studied in two areas with different proportions of man-made structures and urban features. Six snakes were equipped with internal transmitters (giving 171 radio locations in total). Compositional analysis at the homerange scale and location-scale revealed that the snakes used habitats and ecotones non-randomly. Man-made structures were preferred significantly over all other habitat types in both study areas with buildings and their surroundings, stone walls and compost heaps preferred microhabitats in both areas. These sites were used mainly as sheltering places or for thermoregulatory activities. In both areas snakes showed a preference for ecotones, transitional areas between biomes. Urban structures were favoured for nesting and overwintering sites. The prevalence of snakes in man-made edge habitats suggests that in climatically challenging conditions, these otherwise heat seeking snakes prefer different habitats than in more southernly areas of this species' range. [ABSTRACT FROM AUTHOR]

The relationship between the clearness index and the time averaged sunshine number is studied over short time intervals such as one hour. Several non-linear statistical models have been used. Meteorological and radiometric data from various weather stations of Romania (South-Eastern Europe) are analyzed. Nonlinearity of the relationship is only apparent near the boundary for relative sunshine σ of 0 or 1 and manifests itself in clearness index jumps mainly at σ = 0 rather than σ = 1. The negative clearness index jump at σ = 0 decreases while the slope of the relationship increases when the sunshine number is averaged over longer time periods. [ABSTRACT FROM AUTHOR]

Factors affecting the seasonal succession of plankton communities in freshwater temperate lakes have been thoroughly studied for decades. However, there are still relatively few data describing the winter season patterns in detail, as the focus has been mostly on spring to autumn conditions. Ice cover is often the crucial factor limiting light availability for winter phytoplankton, but in warm monomictic lakes is usually lacking and the gradually increasing solar radiation should, theoretically, drive phytoplankton growth. In this study conducted in 2002–2010, we documented regular sharp increases in phytoplankton chlorophyll a , starting just after the winter solstice and lasting throughout the total circulation and/or unstable inverse stratification period in the monomictic Slapy reservoir (Czechia). Chlorophyll a concentrations analysed in one-week intervals reached their yearly minimum of 0.2–0.8 µg L−1 in the solstice period, and the spring peak occurred before the onset of stable thermal stratification. The regular pattern was slightly disrupted in some years, associated with short periods of ice cover. Winter phytoplankton were species poor and dominated by diatoms, cryptophytes, green algae, and cyanobacteria. Using semiparametric regression approach, we aimed to test if selected environmental parameters had a significant effect on the observed winter trend. The resulting model revealed that solar radiation and water temperature positively influenced log chlorophyll a concentrations, whereas water age had a significant negative effect. On the other hand, zooplankton density and ice cover effects were not significant. The shapes of the marginal effects of water temperature and solar radiation were nonlinear, and the interaction of these two major factors was significant. The model-based estimated chlorophyll a concentrations showed a shift from radiation dominance to temperature-positive effects along the temperature gradient. This might represent as yet neglected pattern of phytoplankton seasonal development in warm monomictic lakes worldwide. [ABSTRACT FROM AUTHOR]

Accurate prediction of solar radiation is of high importance for proper operation of the electrical grid. Over short horizons, forecasting solar irradiance is often performed by extrapolation of field measurements. Four tailored statistical models for forecasting hourly average solar irradiance are proposed and assessed in this paper. These follow from the well-known regression and ARIMA class of models, but bring into the model formulation various physically motivated additional features. These capture the distribution of solar radiation more effectively. Their performance is compared with the performance of a standard model used in the strictly black-box style often encountered in practice. Overall results demonstrate that the proposed models are significantly more accurate than the standard model, under conditions of mostly cloudy skies. [ABSTRACT FROM AUTHOR]

• First Czech study showing inequalities by municipalities of smoking-related deaths. • Advanced geostatistical modeling used on data from the Czech Mortality Register. • Relationship between mortality and local socioeconomic structure examined. • Despite ecological design, the small-area level reduces chance of a possible fallacy. Smoking-related mortality varies over different social, environmental, and policy contexts. However, spatial patterns, examined at a small area level, have been seldom considered. Therefore, the study provides a detailed analysis of socio-spatial inequalities in premature mortality related to smoking in the contemporary Czech adult population. We conducted a population-based, cross-sectional study to investigate the spatial pattern of the age-adjusted smoking-related mortality across Czechia. The spatial inequalities, as measured at the municipality level, were investigated using geostatistical modeling techniques. The ecological regression of the local mortality risk on socioeconomic composition of municipalities was also conducted. The target population was defined as permanent adult residents of Czechia aged 25–64 years in the period of 2011–2015. Among both sexes, a significant spatial gradient in the South-East (lower relative risk) – North-West (higher relative risk) axis was detected. The local mortality risk was significantly related to the level of relative deprivation of the municipalities (a composite index comprised from unemployment rate and level of education): adjusted RR among males (for an increase by 1 SD): 1.21 [95% CI: 1.158–1.256], p < 0.001; adjusted RR among females (for an increase by 1 SD): 1.14 [95% CI: 1.090–1.186], p < 0.001. Mortality among males was approximately twice as high as opposed to females. Regarding the spatial inequalities of the phenomena, however, only rather minor sex-specific patterns were identified. Contrasted to males, mortality among females was unrelated to unemployment rates. Consistent spatial patterns of the premature mortality were identified. The mortality risk was significantly related to socioeconomic composition of the Czech municipalities. The higher the level of local deprivation, the higher the local mortality risk. The results of the study can be found beneficial for planning of both socially and spatially integrated public health policy. [ABSTRACT FROM AUTHOR]

Macrofungal species richness generally increases with forest continuity as does the richness of so-called ancient forest plant species (AFS). Based on this assumption, we examined the ability of AFS to indicate macrofungal diversity in six study areas covering a range of elevations and environments in the Czech Republic. In total, we used data from 106 sampling plots (2,500 m each) distributed over six types of forest stands reflecting different intensities and temporal stages of forest management. Species composition of vascular plants and macrofungi was recorded by a single inventory and regular 2-year monitoring, respectively. In total, we found 71 AFS and 1,413 macrofungal species, of which 150 were red-listed macrofungal species. We documented that AFS show potential for being used in the prediction of macrofungi species richness, including endangered species, at the local scale (α-diversity). Additionally, we found significant differences in macrofungal species richness depending on study area and type of forest management, which did not, however, derogate the effect of AFS. Spatial congruence between species composition of AFS and macrofungi communities (β-diversity) increased with forest age and decreased with intensity of forest management. If we consider the simplicity of monitoring AFS in comparison to regular monitoring of macrofungi, we found a widely usable tool for estimating macrofungal diversity in all dominant types of managed forest in central Europe. However, we should be aware of the limited ability of AFS to capture macrofungal diversity across a broader spatial context (γ-diversity), especially in areas with a low diversity of AFS. [ABSTRACT FROM AUTHOR]

During the daytime, the sun is shining or not at ground level depending on clouds motion. Two binary variables may be used to quantify this process: the sunshine number (SSN) and the sunshine stability number (SSSN). The sequential features of SSN are treated in this paper by using Markovian Logistic Regression models, which avoid usual weaknesses of autoregressive integrated moving average modeling. The theory is illustrated with results obtained by using measurements performed in 2010 at Timisoara (southern Europe). Simple modeling taking into account internal dynamics with one lag history brings substantial reduction of misclassification compared with the persistence approach (to less than 57%). When longer history is considered, all the lags up to at least 8 are important. The seasonal changes are rather concentrated to low lags. Better performance is associated with a more stable radiative regime. More involved models add external influences (such as sun elevation angle or astronomic declination as well as taking into account morning and afternoon effects separately). Models including sun elevation effects are significantly better than those ignoring them. Clearly, during the winter months, the effect of declination is much more pronounced compared with the rest of the year. SSSN is important in long-term considerations and it also plays a role in retrospective assessment of the SSN. However, it is not easy to use SSSN for predicting future SSN. Using more complicated past beam clearness models does not necessarily provide better results than more simple models with SSN past. [ABSTRACT FROM AUTHOR]

Highlights: [•] Sunshine number (SSN), a binary variable, quantifies the presence of shadow. [•] Logistic Markovian models of SSN dynamics are evaluated. [•] The model including sun elevation captures a large amount of the SSN variability. [•] Overall models are useful in nowcasting events like solar ramp. [ABSTRACT FROM AUTHOR]

We studied a population of Aesculapian Snakes ( Zamenis longissimus) living close to a 1,000-m stretch of busy road located in northwestern Bohemia. We monitored the extent of road mortality and related behavioral characteristics. A large number of snakes regularly inhabited the road's embankment during monitoring in June and September. Some individuals were observed to stay in exactly the same spot continuously for several days. Snakes were active starting between 0800 and 0900 h in the morning and ending by 1900 h in June and 1800 h in September. Activity was greatest during the morning. The most frequent type of observed behavior was related to thermoregulation. The snakes did not react visibly to passing traffic. The Aesculapian Snakes' activity was higher, and started at lower temperatures, in June than in September. The mean body temperature of the Aesculapian Snakes was 24.3°C. On average, it was higher than the ambient air temperature until the ambient air temperature exceeded 27.8°C. We detected very little road mortality of adult snakes. Even though they used the road embankments and adjacent stone abutment walls frequently, they virtually never ventured onto the surface of the road. To cross the road they generally used the culverts under it. Juvenile snakes ventured onto the road frequently and their road mortality was high. [ABSTRACT FROM AUTHOR]

The advent of technological developments is allowing to gather large amounts of data in several research fields. Learning analytics (LA)/educational data mining has access to big observational unstructured data captured from educational settings and relies mostly on unsupervised machine learning (ML) algorithms to make sense of such type of data. Generalized additive models for location, scale, and shape (GAMLSS) are a supervised statistical learning framework that allows modeling all the parameters of the distribution of the response variable with respect to the explanatory variables. This article overviews the power and flexibility of GAMLSS in relation to some ML techniques. Also, GAMLSS' capability to be tailored toward causality via causal regularization is briefly commented. This overview is illustrated via a data set from the field of LA. This article is categorized under:Application Areas > Education and LearningAlgorithmic Development > StatisticsTechnologies > Machine Learning [ABSTRACT FROM AUTHOR]

We present a statistical model for construction and application of standardized load profiles. Standardized load profile curves give a typical natural gas consumption pattern throughout a year in various time resolutions. Our semiparametric regression model uses three types of information, constant characteristics of an individual customer, individual historical consumption and time varying explanatory variables, both to describe typical trend and to correct for departure of current conditions from normal. The model's multiplicative structure allows for convenient separation of individual-specific and common time varying parts. Although corrections are parametric, no substantial information about the typical consumption trend is available, so it is modelled non-parametrically. Corrections for temperature effects are non-linear; hence we deal with them through an obvious extension of the generalized additive model framework. [ABSTRACT FROM AUTHOR]

The glycemic response to ingested glucose for the treatment of hypoglycemia following exercise in type 1 diabetes patients has never been studied. Therefore, we aimed to characterize glucose dynamics during a standardized bout of hypoglycemia-inducing exercise and the subsequent hypoglycemia treatment with the oral ingestion of glucose. Ten male patients with type 1 diabetes performed a standardized bout of cycling exercise using an electrically braked ergometer at a target heart rate (THR) of 50% of the individual heart rate reserve, determined using the Karvonen equation. Exercise was terminated when hypoglycemia was reached, followed by immediate hypoglycemia treatment with the oral ingestion of 20 g of glucose. Arterialized blood glucose (ABG) levels were monitored at 5 min intervals during exercise and for 60 min during recovery. During exercise, ABG decreased at a mean rate of 0.11 ± 0.03 mmol/L·min−1 (minimum: 0.07, maximum: 0.17 mmol/L·min−1). During recovery, ABG increased at a mean rate of 0.13 ± 0.05 mmol/L·min−1 (minimum: 0.06, maximum: 0.19 mmol/L·min−1). Moreover, 20 g of glucose maintained recovery from hypoglycemia throughout the 60 min postexercise observation window. [ABSTRACT FROM AUTHOR]

Most studies addressing heat in urban environments focus on thermal conditions and neglect the mental component of thermal comfort. This study employs mental maps to analyse thermal (dis)comfort in the medium-sized Czech cities of Olomouc and Plzeň in summer. Locations of "mental hotspots" are identified particularly on busy streets, at transport hubs, and in the city centres. The results reveal mental hotspots as highly-frequented locations in which people experience inferior thermal and environmental conditions. Slight variations in the spatial patterns of thermal discomfort for particular groups of persons are described. Mental hotspots overlap with surface temperature hotspots by less than half of their area; differences are statistically significant and spatially modulated. Overlap areas of "mental" and "real" hotspots show a promising approach towards indication of locations prone to development of heat stress in urban areas. These findings may contribute to adaptation to climate change and to urban planning, which should address not only the physical but also the subjectively-perceived issues of thermal comfort. • Mental hotspot areas overlap with surface temperature hotspots by less than half. • Mental hotspots occur in central squares, transport hubs and on busy streets. • Green and blue infrastructure prevents mental thermal discomfort. • Mental and LST hotspot overlaps indicate areas suitable for heat reduction. [ABSTRACT FROM AUTHOR]