Predicted and Verified Deviations from Zipf's law in Ecology of Competing Products

Zipf's power-law distribution is a generic empirical statistical regularity found in many complex systems. However, rather than universality with a single power-law exponent (equal to 1 for Zipf's law), there are many reported deviations that remain unexplained. A recently developed theory finds that the interplay between (i) one of the most universal ingredients, namely stochastic proportional growth, and (ii) birth and death processes, leads to a generic power-law distribution with an exponent that depends on the characteristics of each ingredient. Here, we report the first complete empirical test of the theory and its application, based on the empirical analysis of the dynamics of market shares in the product market. We estimate directly the average growth rate of market shares and its standard deviation, the birth rates and the "death" (hazard) rate of products. We find that temporal variations and product differences of the observed power-law exponents can be fully captured by the theory with no adjustable parameters. Our results can be generalized to many systems for which the statistical properties revealed by power law exponents are directly linked to the underlying generating mechanism

Pre-transplant immune factors may be associated with BK polyomavirus reactivation in kidney transplant recipients

BK polyomavirus (BKPyV) reactivation in kidney transplant recipients can lead to allograft damage and loss. The elements of the adaptive immune system that are permissive of reactivation and responsible for viral control remain incompletely described. We performed a prospective study evaluating BKPyV-specific T-cell response, humoral response and overall T-cell phenotype beginning pre-transplant through one year post-transplant in 28 patients at two centers. We performed an exploratory analysis of risk factors for the development of viremia and viruria as well as compared the immune response to BKPyV in these groups and those who remained BK negative. 6 patients developed viruria and 3 developed viremia. BKPyV-specific CD8+ T-cells increased post-transplant in viremic and viruric but not BK negative patients. BKPyV-specific CD4+ T-cells increased in viremic, but not viruric or BK negative patients. Anti-BKPyV IgG antibodies increased in viruric and viremic patients but remained unchanged in BK negative patients. Viremic patients had a greater proportion of CD8+ effector cells pre-transplant and at 12 months post-transplant. Viremic patients had fewer CD4+ effector memory cells at 3 months post-transplant. Exploratory analysis demonstrated lower CD4 and higher total CD8 proportions, higher anti-BKPyV antibody titers and the cause of renal failure were associated BKPyV reactivation. In conclusion, low CD4, high CD8 and increased effector CD8 cells were found pre-transplant in patients who became viremic, a phenotype associated with immune senescence. This pre-transplant T-cell senescence phenotype could potentially be used to identify patients at increased risk of BKPyV reactivation

Transition from Persistent to Anti-Persistent Correlations in Postural Sway Indicates Velocity-Based Control

The displacement of the center-of-pressure (COP) during quiet stance has often been accounted for by the control of COP position dynamics. In this paper, we discuss the conclusions drawn from previous analyses of COP dynamics using fractal-related methods. On the basis of some methodological clarification and the analysis of experimental data using stabilogram diffusion analysis, detrended fluctuation analysis, and an improved version of spectral analysis, we show that COP velocity is typically bounded between upper and lower limits. We argue that the hypothesis of an intermittent velocity-based control of posture is more relevant than position-based control. A simple model for COP velocity dynamics, based on a bounded correlated random walk, reproduces the main statistical signatures evidenced in the experimental series. The implications of these results are discussed

Long memory estimation for complex-valued time series

Long memory has been observed for time series across a multitude of fields and the accurate estimation of such dependence, e.g. via the Hurst exponent, is crucial for the modelling and prediction of many dynamic systems of interest. Many physical processes (such as wind data), are more naturally expressed as a complex-valued time series to represent magnitude and phase information (wind speed and direction). With data collection ubiquitously unreliable, irregular sampling or missingness is also commonplace and can cause bias in a range of analysis tasks, including Hurst estimation. This article proposes a new Hurst exponent estimation technique for complex-valued persistent data sampled with potential irregularity. Our approach is justified through establishing attractive theoretical properties of a new complex-valued wavelet lifting transform, also introduced in this paper. We demonstrate the accuracy of the proposed estimation method through simulations across a range of sampling scenarios and complex- and real-valued persistent processes. For wind data, our method highlights that inclusion of the intrinsic correlations between the real and imaginary data, inherent in our complex-valued approach, can produce different persistence estimates than when using real-valued analysis. Such analysis could then support alternative modelling or policy decisions compared with conclusions based on real-valued estimation

Graft Function Variability and Slope and Kidney Transplantation Outcomes

Introduction: It is critical to identify kidney transplant recipients (KTRs) at higher risk for adverse outcomes, to focus on monitoring and interventions to improve outcomes. We examined the associations between graft function variability and long-term outcomes in KTRs in an observational study. Methods: We identified 2919 KTRs in the Wisconsin Allograft Recipient Database (WisARD) who had a functioning allograft 2 years posttransplantation and at least 3 outpatient measurements of estimated glomerular filtration rate (eGFR) from 1 to 2 years posttransplantation. Graft function slope was calculated from a linear regression of eGFR, and variability was defined as the coefficient of variation around this regression line. Associations of eGFR variability and slope with death, graft failure, cardiovascular events, and acute rejection were estimated. Results: Compared to the lowest quartile, the highest quartile of eGFR variability was associated with a higher risk of death (adjusted hazard ratio [HR] = 1.85; 95% CI = 1.23−2.76), but not with a higher risk of graft failure (subhazard ratio = 1.16; 95% CI = 0.85−1.58), independent of eGFR and slope of eGFR. Greater eGFR variability was associated with higher risk of cardiovascular- and infection-related death and cardiovascular events but not malignancy-related death or allograft rejection. Including variability of eGFR significantly improved prediction of mortality but not prediction of graft failure. Conclusion: Variability of eGFR is independently associated with risk of death, especially cardiovascular disease−related death and cardiovascular events, but not graft failure. Variability of eGFR may help identify KTRs at higher risk for death and cardiovascular events