Empirical Frequency Distributions Research Articles

Dynamic modelling of price expectations and judgments

Official data about consumers’ qualitative expectation and perception of inflation are derived from repeated surveys conducted by national statistical institutes. In EU, these data are published in aggregate form, and cannot be described by means of classical methods based on cumulative models for ordinal data. This article illustrates an integrated approach that locates CUB mixture models for ratings in a time series perspective in order to investigate the joint evolution of inflation judgments and expectations in Italy. In order to measure the common sentiment of interviewees through the feeling component of the model, net of possible uncertainty and nuisance effects, its estimation is pursued through profile likelihood methods given the empirical frequency distributions of consumers’ opinions observed over time. Then, the relationship between the time series of the estimated feeling parameters is modelled using a dynamic regression model and the results are compared in three periods marked by different economic conditions. Results indicate that each series has a substantial inertial component, and thus it is characterized by a slow variation over time, and that both judgments about past price levels and previous expectations affect current expectations about the future in fairly different ways for the three time periods.

Peculiarities of the Relationships between Anxiety, Psychological Skills, and Injuries in Cuban Athletes

Background: In the present research, the general and specific relationships of anxiety and psychological skills with the history of injuries in a heterogeneous population of Cuban high-performance athletes are analyzed. Methods: Through a correlational and cross-sectional study, the Villa Clara basketball, baseball, soccer, and softball preselection’s were studied between 2019 and 2022. To obtain data on injuries, a specific questionnaire was applied. The state of the psychological variables was determined by means of the Competition State Anxiety Inventory and the Sports Execution Psychological Inventory. Data were analyzed using empirical frequency distribution, descriptive statistics, the Kolmogorov-Smirnov test, and Kendall's Tau_b nonparametric correlation coefficient. Results and Discussion: High anxiety and psychological skills to compete prevailed. Most of the athletes had been injured with remarkable frequency, severity and in competitions. Lower motivational level, attention and emotional control are related to the occurrence of injuries. The most serious injuries are related to high levels of anxiety, less control of attention and negative coping, while the occurrence in competition is related to less control of attitude. The relationships between variables differ between the sports analyzed. Conclusion: A lower degree of psychological preparation makes the athlete vulnerable to injury, however, the psychological risk factors are established specifically in each sport. These differences must be considered for the design and implementation of injury prevention.

An Analysis of Household Income in Poland and Slovakia Based on Selected Income Models

Abstract Research background: Studies of income distributions may focus on describing empirical distributions by theoretical models. This approach can be useful for many reasons. When choosing a statistical model, it is important both to find out a theoretical distribution function that would characterize empirical frequency distribution and to choose suitable methods to calculate the parameters of the model. In the literature, there are proposals for various types of mathematical functions. Very high accuracy with empirical distribution is characteristic for Dagum and log-normal models. In 2010 Zenga proposed a new three-parameter model for economic size distribution which possesses interesting statistical properties. Purpose: The aim of this paper is to apply and compare Dagum, log-normal and Zenga models to income distributions in Poland and Slovakia. Research methodology: The studies are based on research data from the European Quality of Life Surveys (EQLS), whose purpose is to measure both objective and subjective indicators of the standard of living of citizens and their households. The estimation parameters were obtained by means of the maximum likelihood method and D’Addario’s invariants method. Results: The results of the conducted approximations, presented in the paper confirmed the good consistency of the Dagum and Zenga distributions with the empirical income distribution of households in Poland and Slovakia. Novelty: The Zenga distribution was used for the first time to describe the income distribution of the Slovak population and it allows the best fit to the empirical data of this country.

Characteristics of discharge frequency and their effects on flood channel formation in the middle and lower reaches of the Yangtze River before/after the impoundment of the Three Gorges Reservoir

三峡水库蓄水前后长江中下游流量特征变化及其对造床作用的影响一直受到学者的关注.采用枝城等6个水文站日均流量资料，分别统计了各站流量的经验频率分布，检验了8种概率密度函数的适用性，并讨论了三峡水库蓄水前后流量频率分布特征与造床流量的关系.研究表明：长江中下游干流洪中枯各级流量的频率分布具有分段特性，无法用皮尔逊Ш型或对数正态等常见函数来整体描述，但中洪流量区段符合分段幂函数；拟合得到的分段幂函数转折点可近似反映造床流量，包括临界值在内的函数特征参数受洞庭湖等调蓄作用影响，在螺山站上下游差异较大；三峡水库蓄水后，洪水削减使得各站的流量频率分段特性增强，分段幂函数仍然适用；由于三峡水库蓄水后流量过程变化和频率调整的影响，枝城、沙市、监利站造床流量将变为蓄水前的0.79、0.73、0.74倍，螺山、汉口、大通站造床流量将变为蓄水前的0.89、0.90、0.93倍.本文的方法和认识对于长江中下游径流特征分析和造床流量计算具有参考价值.;The variations of flow characteristics and their effects on channel formation in the middle and lower reaches of the Yangtze River before and after the impoundment of the Three Gorges Reservoir (TGR) have drawn much concern. Based on the data of the average daily discharge at six hydrological stations including Zhicheng Station, the empirical flow frequency distributions were calculated, and the applicabilities of eight probability density functions were tested. Furthermore, the relationships between the flow frequency distribution characteristics and the channel-forming discharges before and after the impoundment of the TGR were discussed. The results show that the flow frequency distributions in the study reach are segmented, which cannot be described as a whole by common functions such as Pearson Ш or Lognormal distribution. However, the frequency distributions of the medium-high flow conform to the broken power-law (BPL). The turning point of the BPL obtained by fitting approximately reflects the channel-forming discharge. Moreover, affected by the regulation and storage of Lake Dongting, the characteristic parameters including the critical values quite differently in the upper and lower reaches of Luoshan Station. After the TGR is impounded, the subsection characteristics of the flow frequency distributions are enhanced by the flood reduction, and the applicability of BPL are still considerable. Due to the influence of the flow process change and frequency adjustment by the impoundment of the TGR, the channel-forming discharge at Zhicheng, Shashi, Jianli, Luoshan, Hankou and Datong stations will be 0.79, 0.73, 0.74, 0.89, 0.90 and 0.93 times of that before the impoundment, respectively. The method presented in this paper are of reference value for the analysis of runoff characteristics and the calculation of channel-forming discharge in the middle and lower reaches of the Yangtze River.

Measuring hydrological connectivity inside soils with different texture by fast field cycling nuclear magnetic resonance relaxometry

The locution “hydrological connectivity inside the soil” is generally used to disclose how the spatial patterns inside the soil affect the physical–chemical processes at a molecular level to influence water transfer into the soil, the surface runoff and related sediment transport. Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry has been used to measure both structural and functional connectivity by two indexes indicated as structural (SCI) and functional (FCI) connectivity index. Here, FFC-NMR relaxometry has been applied to analyze three samples: two non-degraded soils, having different grain-size distribution, and a degraded soil sampled in a badland area. Proton Larmor frequencies (νL) ranging in the 0.015–35 MHz interval were used on water suspended samples. The relaxograms (i.e., the distributions of the longitudinal relaxation times, T1) obtained by the FFC-NMR investigations were integrated. The resulting S-shaped curves were handled to obtain the aforementioned FCI and SCI parameters. Results showed that the empirical frequency distribution of the SCI index is related to soil texture and structure, while soils having similar SCI revealed different functional connectivity values. This approach allowed (i) to distinguish SCI values of degraded soils from those of non-degraded ones and (ii) to verify whether the structural connectivity index is related to soil texture and structure. The analysis also showed that the variation coefficient of SCI and FCI, achieved from the measurements done at different νL values, is minimum in the measurement range 0.015–1 MHz. The frequency of 1 MHz can be considered the optimal value to have accurate measured connectivity indexes. For the investigated samples, the obtained relationship between FCI and SCI allowed to conclude that high structural connectivity values correspond to a better functional connectivity. Finally, the hydrological connectivity inside a soil was defined as the sum of the two components representing structural and functional perspective.

Daily precipitation concentration in Central Coast Vietnam

Empirical frequency distribution of daily precipitation amounts can be fitted by a negative exponential distribution, because anywhere there are many small daily totals and few large ones. Therefore, the cumulative percentages of days with precipitation, sorted in increasing order according to their amounts, against the cumulative percentage of the rainfall amounts that they contribute are fitted by positive exponential curves Y = aXebx, a and b constants. Based on these curves, the Concentration Index (CI) evaluates the contribution of the rainiest days to the total amount. In this study the CI has been calculated for 15 meteorological stations in Da Nang city and Quang Nam province in Central Coast Vietnam, for the 1979–2016 period. The results show high values of CI, ranging from 0.62 to 0.72. Conversely, the linear correlation between altitude and CI is negative (R = -0.60, p < 0.01). There are no correlations between the latitude nor the annual mean number of precipitation days and the CI. CI change for the sub-periods of 1979–1997 and 1998–2016 is also analyzed.

Roughness effect on the correction factor of surface velocity for rill flows

AbstractFlow velocity is one of the most important hydrodynamic variables for both channelized (rill and gullies) and interrill erosive phenomena. The dye tracer technique to measure surface flow velocity Vs is based on the measurement of the travel time of a tracer needed to cover a known distance. The measured Vs must be corrected to obtain the mean flow velocity V using a factor αv = V/Vs which is generally empirically deduced. The Vs measurement can be influenced by the method applied to time the travel of the dye‐tracer and αv can vary in different flow conditions. Experiments were performed by a fixed bed small flume simulating a rill channel for two roughness conditions (sieved soil, gravel). The comparison between a chronometer‐based (CB) and video‐based (VB) technique to measure Vs was carried out. For each slope‐discharge combination, 20 measurements of Vs, characterized by a sample mean Vm, were carried out. For both techniques, the frequency distributions of Vs/Vm resulted independent of slope and discharge. For a given technique, all measurements resulted normally distributed, with a mean equal to one, and featured by a low variability. Therefore, Vm was considered representative of surface flow velocity. Regardless of roughness, the Vm values obtained by the two techniques were very close and characterized by a good measurement precision. The developed analysis on αv highlighted that it is not correlated with Reynolds number for turbulent flow regime. Moreover, αv is correlated neither with the Froude number nor with channel slope. However, the analysis of the empirical frequency distributions of the correction factor demonstrated a slope effect. For each technique (CB, VB)‐roughness (soil, gravel) combination, a constant correction factor was statistically representative even if resulted in less accurate V estimations compared to those yielded by the slope‐specific correction factor.

Some Information Geometric Aspects of Cyber Security by Face Recognition.

Secure user access to devices and datasets is widely enabled by fingerprint or face recognition. Organization of the necessarily large secure digital object datasets, with objects having content that may consist of images, text, video or audio, involves efficient classification and feature retrieval processing. This usually will require multidimensional methods applicable to data that is represented through a family of probability distributions. Then information geometry is an appropriate context in which to provide for such analytic work, whether with maximum likelihood fitted distributions or empirical frequency distributions. The important provision is of a natural geometric measure structure on families of probability distributions by representing them as Riemannian manifolds. Then the distributions are points lying in this geometrical manifold, different features can be identified and dissimilarities computed, so that neighbourhoods of objects nearby a given example object can be constructed. This can reveal clustering and projections onto smaller eigen-subspaces which can make comparisons easier to interpret. Geodesic distances can be used as a natural dissimilarity metric applied over data described by probability distributions. Exploring this property, we propose a new face recognition method which scores dissimilarities between face images by multiplying geodesic distance approximations between 3-variate RGB Gaussians representative of colour face images, and also obtaining joint probabilities. The experimental results show that this new method is more successful in recognition rates than published comparative state-of-the-art methods.

Sexually Transmitted Infections Among US Women and Men: Prevalence and Incidence Estimates, 2018.

The most recent estimates of the number of prevalent and incident sexually transmitted infections (STIs) in the United States were for 2008. We provide updated estimates for 2018 using new methods. We estimated the total number of prevalent and incident infections in the United States for 8 STIs: chlamydia, gonorrhea, trichomoniasis, syphilis, genital herpes, human papillomavirus, sexually transmitted hepatitis B, and sexually transmitted HIV. Updated per-capita prevalence and incidence estimates for each STI were multiplied by the 2018 full resident population estimates to calculate the number of prevalent and incident infections. STI-specific estimates were combined to generate estimates of the total number of prevalent and incident STIs overall, and by sex and age group. Primary estimates are represented by medians, and uncertainty intervals are represented by the 25th (Q1) and 75th (Q3) percentiles of the empirical frequency distributions of prevalence and incidence for each STI. In 2018, there were an estimated 67.6 (Q1, 66.6; Q3, 68.7) million prevalent and 26.2 (Q1, 24.0; Q3, 28.7) million incident STIs in the United States. Chlamydia, trichomoniasis, genital herpes, and human papillomavirus comprised 97.6% of all prevalent and 93.1% of all incident STIs. Persons aged 15 to 24 years comprised 18.6% (12.6 million) of all prevalent infections; however, they comprised 45.5% (11.9 million) of all incident infections. The burden of STIs in the United States is high. Almost half of incident STIs occurred in persons aged 15 to 24 years in 2018. Focusing on this population should be considered essential for national STI prevention efforts.

A flow-weighted ensemble strategy to assess the impacts of climate change on watershed hydrology

Evaluation of hydrological response to future climate change is essential for water quality risk assessment and adaptive management implementation within a watershed context. In this study, we present a modeling framework that integrates a hydrological model with projections of General Circulation Models (GCMs). Temperature and precipitation projections of six GCMs with two downscaling methods are used to force the Soil and Water Assessment Tool (SWAT) model in the Hamilton Harbour watershed in Ontario, Canada. A flow-based weighting strategy was developed to integrate the projections of multiple GCMs based on their ability to recreate empirical flow frequency distributions in multiple monitoring sites. Our study renders support to the ability of the weighted model ensemble to draw meaningful hydrological forecasts. Nonetheless, we also note that the ensemble strategy understates the frequency and magnitude of flow extremes, and therefore the domain that is collectively delineated by individual GCMs can still provide complementary planning information. Climate change is projected to trigger a distinct increase in air temperature and precipitation during the late winter-early spring period, which in turn will likely result in an earlier snowmelt and changes in the magnitude and timing of peak flow events. Analysis of the water cycle shows that the sensitivity of the individual hydrological components to climate change may vary along the urban-to-agriculture gradient. The projected declining soil–water content in agricultural catchments highlights the likelihood of more intensified drought conditions in the croplands. Evapotranspiration rates will likely increase across the entire watershed, whereas surface runoff could be reduced but less so in urbanized locations. Overall, our findings suggest that any future planning exercise to ameliorate the prevailing water quality conditions will only be insightful if we consider the interplay between climate change and urbanization processes in the area.

Flume experiments for assessing the dye-tracing technique in rill flows

Flow velocity controls hillslope soil erosion and is a key hydrodynamic variable involved in sediment transport and deposition processes. The dye-tracer technique is one of the most applied methods for measuring velocity of shallow interrill and rill flow. The technique is based on the injection of a tracer in a specific point and the measurement of its speed to travel the known distance from the injection point to a given channel section. The dye-tracer technique requires that the measured surface flow velocity has to be corrected to obtain the mean flow velocity using a correction factor which is generally empirically deduced. The technique has two sources of uncertainties: i) the method applied for measuring the travel time of the dye-tracer and ii) the estimate of the correction factor, which is the ratio between the mean flow velocity and the surface velocity, in different flow conditions. In this paper the results of a wide experimental investigation, carried out using a fixed bed small flume simulating a rill channel, are presented. At first, the comparison between a chronometer-based (CB) and video-based (VB) technique was carried out for establishing the influence of the travel time measuring technique. For each experimental run, which was characterized by a sample of 20 measurements carried out with the same values of slope and discharge, the developed analysis showed that the empirical frequency distribution of the ratio between the single measurement and the sample mean (i.e., the average of 20 measurements) is more uniform for the VB technique than for the CB one. In any case, this sample mean was representative of surface flow velocity for both the CB and the VB technique. Furthermore, the mean value obtained by the CB measurements lightly underestimated (−1.7%) the corresponding mean obtained by the VB technique. Finally, the effects of slope (0.1–8.7%), flow Reynolds number (3462–10040), Froude number (1.44–5.17) on the correction factor are presented. The analysis demonstrated that the correction factor is independent of flow Reynolds number while a relationship with a Froude number, obtained by surface velocity measurement, or channel slope can be established.

Comparison of spatial and temporal performance of two Regional Climate Models in the Amazon and La Plata river basins

This study aims to present a comprehensive spatio-temporal performance analysis of two water balance variables, precipitation and evapotranspiration, simulated by two Regional Climate Models (RCM) multi-model ensembles. We evaluate simulations from two RCMs from the Coordinated Regional Climate Downscaling Experiment in the two largest hydrological basins in South America, the Amazon River basin and La Plata River basin. Information was analyzed at 0.5°x0.5° resolution, compared with their driving Global Climate Models (GCM) from the Coupled Models Intercomparison Project (CMIP5) and reference datasets from observations and reanalysis for the period 1986–2005. Spatial and temporal model performance metrics were calculated for monthly datasets, at the annual scale. Annual cycles and the spatial distribution of mean fields are well represented by the RCMs, whereas the empirical frequency distributions reveal discrepancies in lower frequencies. In terms of spatial performance of the RCMs, the quantitative metrics showed that mean fields are better simulated by RCA4 and only RegCM4 offers added value with respect to GCM. Statistical metrics for temporal variability assessment presented a better performance over the La Plata basin from both RCMs. Over the Amazon basin, temporal variability of precipitation is better represented by RegCM4, and the opposite occurs for evapotranspiration with lower differences. According to the overall assessment of spatio-temporal results and performance metrics, the RegCM4 ensemble shows a better performance even though the number of members is smaller.

Approximation of wind speed distributions with theoretical distributions of meteorological stations located in different orographic conditions

This research analyses the daily average wind speed time series of ten Transcarpathian meteorological stations in the period from 1991 to 2000 with the help of statistical methods. We approximated the empirical frequency distribution of measured daily average wind speeds by means of theoretical distributions. The results of the fitting test showed that among the applied theoretical distributions, irrespective of the orographic environment, Weibull distribution proves to be the most suitable. However, fitting of the Weibull distribution depends on the methods of determining the k and c parameters. By means of the best fitting parameters, we worked out the distribution density function and some of its indices at the altitude of 80 m contrary to the anemometer altitude that is often the hub height of industrial wind turbines, thus estimating the area’s wind conditions from the point of view of wind energy utilization.

The Study of Stream Sediment Geochemical Data Processing by Using k-Means Algorithm and Centered Logratio Transformation—an Example of a District in Hunan, China

The backgrounds of stream sediment geochemical samples are associated with the underlying geological bodies. Moreover, a stream sediment geochemical data set is a closed number system because it contains compositional variables that are parts of a whole. Consequently, the empirical frequency distributions of stream sediment geochemical data are often skewed or with multiple peaks. While it is clear that data should approach a symmetric distribution before any threshold estimation methods are applied, so the corresponding method for transforming data is required. In this study, a new method for transformation of stream sediment geochemical data is provided. Firstly, the samples are classified by k-means method into different clusters, samples in each of which are thought to be of the same background. Then samples in each cluster are centered logratio transformed. Finally, the data after processed are tested and they all satisfy normal distributions. Furthermore, a stream sediment geochemical data set of a district in Hunan, China is taken as an example. Maps of anomalies of raw and transformed metallogenic Pb, Zn, Cu and W are portrayed respectively for comparison. The results show that anomalies of raw data correspond worse with the known deposits. By contrast, the method of mapping anomalies with transformed data performs better.

Fuzzy rule-based forecast of meteorological drought in western Niger

Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α < 0.05 level) to the SPI-3. Moreover, the implemented fuzzy model compared to decision tree-based forecast model shows better forecast skills.

Morphological characterization of calanchi (badland) hillslope connectivity

AbstractCalanchi, a type of Italian badlands created by a combination of water erosion processes and local geomorphological and tectonic controls, is a striking example of long‐term landscape evolution. In small temporal/spatial scales, the calanchi exhibit many of the geomorphic processes and landforms that may be observed in fluvial landscapes; hence, they may be considered as microbasins where geomorphic dynamics and landscape features can be related. The goal of this research is testing the use of simple morphometric variables for assessing sediment connectivity of calanchi landforms. In order to detect the morphological characteristics controlling the landscape connectivity of calanchi basins, 2 areas located in Sicily (Italy) were examined. The investigated features were identified on 119 calanchi basins and mapped using orthophotographs and 2‐m‐resolution digital elevation models. Application of Hack's law to the calanchi basins showed that the width/length ratio increases with the drainage area, suggesting that calanchi may have a limited connectivity of their hillslopes to the main channel. Moreover, the analysis of the drainage network composition suggested that calanchi are sediment removal systems more efficient than river basins. The empirical frequency distribution of the travel time, which is the ratio between the length and the square root of the hillslope steepness, of each cell of the calanchi digital elevation model was established. Finally, for each calanchi basin, an index of hillslope connectivity was devised. This was explored as a function of the sediment transport efficiency itself estimated by the travel time and the corresponding sediment delivery ratio of each calanco hillslope cell.

Modeling distances between humans using Taylor’s law and geometric probability

ABSTRACTTaylor’s law states that the variance of the distribution of distance between two randomly chosen individuals is a power function of the mean distance. It applies to the distances between two randomly chosen points in various geometric shapes, subject to a few conditions. In Réunion Island and metropolitan France, at some spatial scales, the empirical frequency distributions of inter-individual distances are predicted accurately by the theoretical frequency distributions of inter-point distances in models of geometric probability under a uniform distribution of points. When these models fail to predict the empirical frequency distributions of inter-individual distances, they provide baselines against which to highlight the spatial distribution of population concentrations.

Prevalence of multimodal species abundance distributions is linked to spatial and taxonomic breadth

AbstractAimSpecies abundance distributions (SADs) are a synthetic measure of biodiversity and community structure. Although typically described by unimodal logseries or lognormal distributions, empirical SADs can also exhibit multiple modes. However, we do not know how prevalent multimodality is, nor do we have an understanding of the factors leading to this pattern. Here we quantify the prevalence of multimodality in SADs across a wide range of taxa, habitats and spatial extents.LocationGlobal.MethodsWe used the second‐order Akaike information criterion for small sample sizes (AICc) and likelihood ratio tests (LRTs) to test whether models with more than one mode accurately describe the empirical abundance frequency distributions of the underlying communities. We analysed 117 empirical datasets from intensely sampled communities, including taxa ranging from birds, plants, fish and invertebrates, from terrestrial, marine and freshwater habitats.ResultsWe find evidence for multimodality in 14.5% of the SADs when using AICc and LRT. This is a conservative estimate, as AICc alone estimates a prevalence of multimodality of 22%. We additionally show that the pattern is more common in data encompassing broader spatial scales and greater taxonomic breadth, suggesting that multimodality increases with ecological heterogeneity.Main conclusionsWe suggest that higher levels of ecological heterogeneity, underpinned by larger spatial extent and higher taxonomic breadth, can yield multimodal SADs. Our analysis shows that multimodality occurs with a prevalence that warrants its systematic consideration when assessing SAD shape and emphasizes the need for macroecological theories to include multimodality in the range of SADs they predict.

Multiple signatures of a disease in potential biomarker space: Getting the signatures consensus and identification of novel biomarkers.

BackgroundThe lack of consensus among reported gene signature subsets (GSSs) in multi-gene biomarker discovery studies is often a concern for researchers and clinicians. Subsequently, it discourages larger scale prospective studies, prevents the translation of such knowledge into a practical clinical setting and ultimately hinders the progress of the field of biomarker-based disease classification, prognosis and prediction.MethodsWe define all "gene identificators" (gIDs) as constituents of the entire potential disease biomarker space. For each gID in a GSS of interest ("tested GSS"/tGSS), our method counts the empirical frequency of gID co-occurrences/overlaps in other reference GSSs (rGSSs) and compares it with the expected frequency generated via implementation of a randomized sampling procedure. Comparison of the empirical frequency distribution (EFD) with the expected background frequency distribution (BFD) allows dichotomization of statistically novel (SN) and common (SC) gIDs within the tGSS.ResultsWe identify SN or SC biomarkers for tGSSs obtained from previous studies of high-grade serous ovarian cancer (HG-SOC) and breast cancer (BC). For each tGSS, the EFD of gID co-occurrences/overlaps with other rGSSs is characterized by scale and context-dependent Pareto-like frequency distribution function. Our results indicate that while independently there is little overlap between our tGSS with individual rGSSs, comparison of the EFD with BFD suggests that beyond a confidence threshold, tested gIDs become more common in rGSSs than expected. This validates the use of our tGSS as individual or combined prognostic factors. Our method identifies SN and SC genes of a 36-gene prognostic signature that stratify HG-SOC patients into subgroups with low, intermediate or high-risk of the disease outcome. Using 70 BC rGSSs, the method also predicted SN and SC BC prognostic genes from the tested obesity and IGF1 pathway GSSs.ConclusionsOur method provides a strategy that identify/predict within a tGSS of interest, gID subsets that are either SN or SC when compared to other rGSSs. Practically, our results suggest that there is a stronger association of the IGF1 signature genes with the 70 BC rGSSs, than for the obesity-associated signature. Furthermore, both SC and SN genes, in both signatures could be considered as perspective prognostic biomarkers of BCs that stratify the patients onto low or high risks of cancer development.

At‐A‐Station Hydraulic Geometry Simulator

AbstractPresented in this paper is a hydraulic model that combines a rational regime theory with an at‐a‐station hydraulic geometry simulator (ASHGS) to predict reach‐averaged hydraulic conditions for flows up to but not exceeding the bankfull stage. The hydraulic conditions determined by ASHGS can be paired with an empirical joint frequency distribution equation and applicable habitat suitability indices to generate weighted usable area (WUA) as a function of flow. ASHGS was tested against a 2‐dimensional hydrodynamic model (River2D) of a mid‐size channel in the Interior Region of British Columbia. By linking ASHGS to a regime model, it becomes possible to evaluate the direction and magnitude of habitat changes associated with a wide range of environmental changes. Our regime model considers flow regime, sediment supply, and riparian vegetation: these governing variables can be used to simulate responses to forest fire, flow regulation and changes in climate and land use. Practitioners can examine ‘what‐if’ scenarios that otherwise would be too expensive and time consuming to fully explore. The model boundaries of commonly used data‐intensive hydraulic habitat models (e.g. PHABSIM) are not easily adjusted and such models are not designed to estimate future morphological and hydraulic habitat conditions in rivers the undergo significant channel restructuring. The proposed model has the potential to become an accepted flow assessment tool amongst practitioners due to modest data requirements, user‐friendliness, and large spatial applicability; it can be used to conduct preliminary assessments of channel altering projects and determine if in‐depth habitat assessments are justified.