Sufficient Conditions for Fast Switching Synchronization in Time Varying Network Topologies

In previous work, empirical evidence indicated that a time-varying network could propagate sufficient information to allow synchronization of the sometimes coupled oscillators, despite an instantaneously disconnected topology. We prove here that if the network of oscillators synchronizes for the static time-average of the topology, then the network will synchronize with the time-varying topology if the time-average is achieved sufficiently fast. Fast switching, fast on the time-scale of the coupled oscillators, overcomes the descychnronizing decoherence suggested by disconnected instantaneous networks. This result agrees in spirit with that of where empirical evidence suggested that a moving averaged graph Laplacian could be used in the master-stability function analysis. A new fast switching stability criterion here-in gives sufficiency of a fast-switching network leading to synchronization. Although this sufficient condition appears to be very conservative, it provides new insights about the requirements for synchronization when the network topology is time-varying. In particular, it can be shown that networks of oscillators can synchronize even if at every point in time the frozen-time network topology is insufficiently connected to achieve synchronization.Comment: Submitted to SIAD

Do we really need Confidence Intervals in the new statistics?

This paper compares the use of confidence intervals (CIs) and a sensitivity analysis called the number needed to disturb (NNTD), in the analysis of research findings expressed as ‘effect’ sizes. Using 1,000 simulations of randomised trials with up to 1,000 cases in each, the paper shows that both approaches are very similar in outcomes, and each one is highly predictable from the other. CIs are supposed to be a measure of likelihood or uncertainty in the results, showing a range of possible effect sizes that could have been produced by random sampling variation alone. NNTD is supposed to be a measure of the robustness of the effect size to any variation, including that produced by missing data. Given that they are largely equivalent and interchangeable under the conditions tested here, the paper suggests that both are really measures of robustness. It concludes that NNTD is to be preferred because it requires many fewer assumptions, is more tolerant of missing data, is easier to explain, and directly addresses the key question of whether the underlying effect size is zero or not

Excitability in autonomous Boolean networks

We demonstrate theoretically and experimentally that excitable systems can be built with autonomous Boolean networks. Their experimental implementation is realized with asynchronous logic gates on a reconfigurabe chip. When these excitable systems are assembled into time-delay networks, their dynamics display nanosecond time-scale spike synchronization patterns that are controllable in period and phase.Comment: 6 pages, 5 figures, accepted in Europhysics Letters (epljournal.edpsciences.org

Damaging real lives through obstinacy: re-emphasising why significance testing is wrong

This paper reminds readers of the absurdity of statistical significance testing, despite its continued widespread use as a supposed method for analysing numeric data. There have been complaints about the poor quality of research employing significance tests for a hundred years, and repeated calls for researchers to stop using and reporting them. There have even been attempted bans. Many thousands of papers have now been written, in all areas of research, explaining why significance tests do not work. There are too many for all to be cited here. This paper summarises the logical problems as described in over 100 of these prior pieces. It then presents a series of demonstrations showing that significance tests do not work in practice. In fact, they are more likely to produce the wrong answer than a right one. The confused use of significance testing has practical and damaging consequences for people's lives. Ending the use of significance tests is a pressing ethical issue for research. Anyone knowing the problems, as described over one hundred years, who continues to teach, use or publish significance tests is acting unethically, and knowingly risking the damage that ensues

Analysis of graft survival in a trial of stem cell transplant in ALS

Objective The first US Food and Drug Administration–approved clinical trial to treat amyotrophic lateral sclerosis ( ALS ) with neural stem cell–based therapy is in progress. The goal of the current study was to identify and assess the survival of human spinal cord–derived neural stem cells ( HSSC s) transplanted into the spinal cord in patients with ALS . Methods Spinal cords transplanted with HSSCs were examined from six autopsy cases. Homogenized tissues were interrogated for the presence of donor versus recipient DNA using real‐time PCR methods ( qPCR ). Fluorescence in situ hybridization (FISH) was performed using DNA probes for XY chromosomes to identify male donor HSSCs in one female case, and immunohistochemistry (IHC) was used to characterize the identified donor cells. Results Genomic DNA from donor HSSC s was identified in all cases, comprising 0.67–5.4% of total tissue DNA in patients surviving 196 to 921 days after transplantation. In the one female patient a “nest” of cells identified on H&E staining were XY ‐positive by FISH , confirming donor origin. A subset of XY ‐positive cells labeled for the neuronal marker NeuN and stem cell marker SOX 2. Interpretation This is the first study to identify human neural stem cells transplanted into a human spinal cord. Transplanted HSSC s survived up to 2.5 years posttransplant. Some cells differentiated into neurons, while others maintained their stem cell phenotype. This work is a proof of concept of the survival and differentiation of human stems cell transplanted into the spinal cord of ALS patients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109593/1/acn3134.pd

Standardizing effect size from linear regression models with log-transformed variables for meta-analysis

Background: Meta-analysis is very useful to summarize the effect of a treatment or a risk factor for a given disease. Often studies report results based on log-transformed variables in order to achieve the principal assumptions of a linear regression model. If this is the case for some, but not all studies, the effects need to be homogenized. Methods: We derived a set of formulae to transform absolute changes into relative ones, and vice versa, to allow including all results in a meta-analysis. We applied our procedure to all possible combinations of log-transformed independent or dependent variables. We also evaluated it in a simulation based on two variables either normally or asymmetrically distributed. Results: In all the scenarios, and based on different change criteria, the effect size estimated by the derived set of formulae was equivalent to the real effect size. To avoid biased estimates of the effect, this procedure should be used with caution in the case of independent variables with asymmetric distributions that significantly differ from the normal distribution. We illustrate an application of this procedure by an application to a meta-analysis on the potential effects on neurodevelopment in children exposed to arsenic and manganese. Conclusions: The procedure proposed has been shown to be valid and capable of expressing the effect size of a linear regression model based on different change criteria in the variables. Homogenizing the results from different studies beforehand allows them to be combined in a meta-analysis, independently of whether the transformations had been performed on the dependent and/or independent variables

Eight common genetic variants associated with serum dheas levels suggest a key role in ageing mechanisms

Dehydroepiandrosterone sulphate (DHEAS) is the most abundant circulating steroid secreted by adrenal glands-yet its function is unknown. Its serum concentration declines significantly with increasing age, which has led to speculation that a relative DHEAS deficiency may contribute to the development of common age-related diseases or diminished longevity. We conducted a meta-analysis of genome-wide association data with 14,846 individuals and identified eight independent common SNPs associated with serum DHEAS concentrations. Genes at or near the identified loci include ZKSCAN5 (rs11761528; p = 3.15×10-36), SULT2A1 (rs2637125; p = 2.61×10-19), ARPC1A (rs740160; p = 1.56×10-16), TRIM4 (rs17277546; p = 4.50×10-11), BMF (rs7181230; p = 5.44×10-11), HHEX (rs2497306; p = 4.64×10-9), BCL2L11 (rs6738028; p = 1.72×10-8), and CYP2C9 (rs2185570; p = 2.29×10-8). These genes are associated with type 2 diabetes, lymphoma, actin filament assembly, drug and xenobiotic metabolism, and zinc finger proteins. Several SNPs were associated with changes in gene expression levels, and the related genes are connected to biological pathways linking DHEAS with ageing. This study provides much needed insight into the function of DHEAS

Highlights from the Pierre Auger Observatory

The Pierre Auger Observatory is the world's largest cosmic ray observatory. Our current exposure reaches nearly 40,000 km$^2$ str and provides us with an unprecedented quality data set. The performance and stability of the detectors and their enhancements are described. Data analyses have led to a number of major breakthroughs. Among these we discuss the energy spectrum and the searches for large-scale anisotropies. We present analyses of our X$_{max}$ data and show how it can be interpreted in terms of mass composition. We also describe some new analyses that extract mass sensitive parameters from the 100% duty cycle SD data. A coherent interpretation of all these recent results opens new directions. The consequences regarding the cosmic ray composition and the properties of UHECR sources are briefly discussed.Comment: 9 pages, 12 figures, talk given at the 33rd International Cosmic Ray Conference, Rio de Janeiro 201