Measurement of aqueous film thickness between charged mercury and mica surfaces : a direct experimental probe of the Poisson-Boltzmann distribution

A stable aqueous electrolyte film is formed between a mercury drop and a flat mica surface due to electrical double-layer repulsion when a negative potential is applied to the mercury. Film thickness has been measured as a function of applied potential while keeping the film pressure constant. By making measurements in this way, it is possible to map the data directly according to the Poisson-Boltzmann equation. An excellent fit to the data is obtained, providing direct evidence for this classical equation and its use as the basis of the Gouy-Chapman model of the diffuse double layer in electrolyte solutions.

A nonparametric Bayesian Poisson Gamma model for count data

We propose a nonparametric Bayesian, linear Poisson gamma model for count data and use it for dictionary learning. A key property of this model is that it captures the parts-based representation similar to nonnegative matrix factorization. We present an auxiliary variable Gibbs sampler, which turns the intractable inference into a tractable one. Combining this inference procedure with the slice sampler of Indian buffet process, we show that our model can learn the number of factors automatically. Using synthetic and real-world datasets, we show that the proposed model outperforms other state-of-the-art nonparametric factor models.

Predicting future purchases with the Poisson log-normal model

The negative binomial distribution (NBD) has been widely used in marketing for modeling purchase frequency counts, particularly in packaged goods contexts. A key managerially relevant use of this model is Conditional Trend Analysis (CTA)—a method of benchmarking future sales utilizing the NBD conditional expectation. CTA allows brand managers to identify whether the sales change in a second period is accounted for by previous non-, light, or heavy buyers of the brand. Although a useful tool, the conditional prediction of the NBD suffers from a bias: it under predicts what the period-one non-buyer class will do in period two and over predicts the sales contribution of existing buyers. In addition, the NBD's assumption of a gamma-distributed mean purchase rate lacks theoretical support—it is not possible to explain why a gamma distribution should hold. This paper therefore proposes an alternative model using a log-normal distribution in place of the gamma distribution, hence creating a Poisson log-normal (PLN) distribution. The PLN distribution has a stronger theoretical grounding than the NBD as it has a natural interpretation relying on the central limit theorem. Empirical analysis of brands in multiple categories shows that the PLN distribution gives better predictions than the NBD.

Effect of elastic modulus and poisson's ratio on guided wave dispersion using transversely isotropic material modelling

Timber poles are commonly used for telecommunication and power distribution networks, wharves or jetties, piling or as a substructure of short span bridges. Most of the available techniques currently used for non-destructive testing (NDT) of timber structures are based on one-dimensional wave theory. If it is essential to detect small sized damage, it becomes necessary to consider guided wave (GW) propagation as the behaviour of different propagating modes cannot be represented by one-dimensional approximations. However, due to the orthotropic material properties of timber, the modelling of guided waves can be complex. No analytical solution can be found for plotting dispersion curves for orthotropic thick cylindrical waveguides even though very few literatures can be found on the theory of GW for anisotropic cylindrical waveguide. In addition, purely numerical approaches are available for solving these curves. In this paper, dispersion curves for orthotropic cylinders are computed using the scaled boundary finite element method (SBFEM) and compared with an isotropic material model to indicate the importance of considering timber as an anisotropic material. Moreover, some simplification is made on orthotropic behaviour of timber to make it transversely isotropic due to the fact that, analytical approaches for transversely isotropic cylinder are widely available in the literature. Also, the applicability of considering timber as a transversely isotropic material is discussed. As an orthotropic material, most material testing results of timber found in the literature include 9 elastic constants (three elastic moduli and six Poisson's ratios), hence it is essential to select the appropriate material properties for transversely isotropic material which includes only 5 elastic constants. Therefore, comparison between orthotropic and transversely isotropic material model is also presented in this article to reveal the effect of elastic moduli and Poisson's ratios on dispersion curves. Based on this study, some suggestions are proposed on selecting the parameters from an orthotropic model to transversely isotropic condition.

Landscape characteristics associated with species richness and occurrence of small native mammals inhabiting a coastal heathland: a spatial modelling approach

In the coastal region of south-western Victoria, Australia, populations of native small mammal species are restricted to patches of suitable habitat in a highly fragmented landscape. The size and spatial arrangement of these patches is likely to influence both the occupancy and richness of species at a location. Geographic Information System (GIS)-based habitat models of the species richness of native small mammals, and individual species  occurrences, were developed to produce maps displaying the spatial  configuration of suitable habitat. Models were generated using either generalised linear Poisson regression (for species richness) or logistic regression (for species occurrences) with species richness or  presence/absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictor variables. A multi-model inference approach based on the Akaike Information Criterion was used and the resulting model was applied in a GIS framework to extrapolate predicted richness/likelihood of occurrence across the entire area of the study. A negative association between species  richness and elevation, habitat complexity and sun index indicated that richness within the study area decreases with increasing altitude, vertical vegetation structure and exposure to solar radiation. Landform  characteristics were important (to varying degrees) in determining habitat occupancy for all of the species examined, while the influence of habitat complexity was important for only one of the species. Performance of all but one of the models generated using presence/absence data was high, as indicated by the area under the curve of a receiver-operating characteristic plot. The effective conservation of the small mammal species in the area of concern is likely to depend on management actions that promote the protection of the critical habitats identified in the models.

Urban amphibian assemblages as metacommunities

1. Urban ecosystems are expanding throughout the world, and urban ecology is attracting increasing research interest. Some authors have questioned the value of existing ecological theories for understanding the processes and consequences of urbanization.
2. In order to assess the applicability of metacommunity theory to urban systems, I evaluated three assumptions that underlie the theory – the effect of patch area, the effect of patch isolation, and species–environment relations – using data on assemblages of pond-breeding amphibians in the Greater Melbourne area of Australia. I also assessed the relative impact of habitat fragmentation, habitat isolation, and changes to habitat quality on these assemblages.
3. Poisson regression modelling provided support for an important increase in species richness with patch area (pond size) and a decrease in species richness with increasing patch isolation, as measured by surrounding road cover. Holding all other variables constant, species richness was predicted to be 2·8–5·5 times higher at the largest pond than at the smallest, while the most isolated pond was predicted to have 12–19% of the species richness of the least isolated pond. Thus, the data were consistent with the first two assumptions of metacommunity theory evaluated.
4. The quality of habitat at a pond was also important, with a predicted 44–56% decrease in the number of species detected at ponds with a surrounding vertical wall compared with those with a gently sloping bank. This demonstrates that environmental differences between habitat patches were also influencing amphibian assemblages, providing support for the species-sorting and/or mass-effect perspectives of metacommunity theory.
5. Without management intervention, urbanization may lead to a reduction in the number of amphibian species persisting in urban ponds, particularly where increasing isolation of ponds by roads and associated infrastructure reduces the probability of re-colonization following local extinction.

Entropy-based collaborative detection of DDOS attacks on community networks

A community network often operates with the same Internet service provider domain or the virtual network of different entities who are cooperating with each other. In such a federated network environment, routers can work closely to raise early warning of DDoS attacks to void catastrophic damages. However, the attackers simulate the normal network behaviors, e.g. pumping the attack packages as poisson distribution, to disable detection algorithms. It is an open question: how to discriminate DDoS attacks from surge legitimate accessing. We noticed that the attackers use the same mathematical functions to control the speed of attack package pumping to the victim. Based on this observation, the different attack flows of a DDoS attack share the same regularities, which is different from the real surging accessing in a short time period. We apply information theory parameter, entropy rate, to discriminate the DDoS attack from the surge legitimate accessing. We proved the effectiveness of our method in theory, and the simulations are the work in the near future. We also point out the future directions that worth to explore in the future.

Is jump risk in iTraxx Sector Indices diversifiable?

The article presents an analysis of jump risks in iTraxx Europe index in a multivariate structural time-series setting for the stochastic process, as well as in the credit default swap (CDS) market. It also examines the rapid development of the credit derivatives market, particularly the CDS market. This analysis found a significant Poisson-distributed jumps in the iTraxx Non-Financials index and its subindices. Based on a statistical analysis, nondiversifiable jump risk strongly exists in the CDS market.

Revisiting delta-6 desaturate regulation by C18 unsaturated fatty acids, depending on the nutritional status

Dietary polyunsaturated fatty acids (PUFA) play a key role in regulating delta-6 desaturase (D6D), the key enzyme for long-chain PUFA biosynthesis. Nevertheless, the extent of their effects on this enzyme remains controversial and difficult to assess. It has been generally admitted that C18 unsaturated fatty acids (UFAs) regulate negatively delta-6 desaturase (D6D). This inhibition has been evidenced in regard to a high glucose/fat free (HG/FF) diet used in reference. However, several nutritional investigations did not evidence any inhibition of desaturases when feeding fatty acids.

Because the choice of the basal diet appeared to be of primary importance in such experiments, our goal was to reconsider the specific role of dietary UFAs on D6D regulation, depending on nutritional conditions. For that, sixteen adult Wistar rats were fed purified linoleic acid, α-linolenic acid or oleic acid, included in one of two diets at 4% by weight: an HG/FF or a high starch base (HS) where the pure UFAs replaced a mixed vegetable oil. Our results showed first that D6D specific activity was significantly greater when measured in presence of an HG/FF than with an HS/4% vegetable oil diet. Secondly, we found that linoleic and alpha-linolenic acids added to HG/FF reduced the specific activity of D6D. In contrast, when pure UFAs were added to an HS base, D6D specific activities remained unchanged or increased. Concordant results were obtained on D6D mRNA expression.

Altogether, this study evidenced the importance of the nutritional status in D6D regulation by C18 UFAs: when used as control, HG/FF diet stimulates D6D compared with a standard control diet containing starch and 4% fats, leading to an overestimation of the D6D regulation by UFAs. Then, UFAs should be considered as repressors for unsaturated fatty acid biosynthesis only in very specific nutritional conditions.

Is extrapair mating random? On the probability distribution of extrapair young in avian broods

A dichotomy in female extrapair copulation (EPC) behavior, with some females seeking EPC and others not, is inferred if the observed distribution of extrapair young (EPY) over broods differs from a random process on the level of individual offspring (binomial, hypergeometrical, or Poisson). A review of the literature shows such null models are virtually always rejected, with often large effect sizes. We formulate an alternative null model, which assumes that 1) the number of EPC has a random (Poisson) distribution across females (broods) and that 2) the probability for an offspring to be of extrapair origin is zero without any EPC and increases with the number of EPC. Our brood-level model can accommodate the bimodality of both zero and medium rates of EPY typically found in empirical data, and fitting our model to EPY production of 7 passerine bird species shows evidence of a nonrandom distribution of EPY in only 2 species. We therefore argue that 1) dichotomy in extrapair mate choice cannot be inferred only from a significant deviation in the observed distribution of EPY from a random process on the level of offspring and that 2) additional empirical work on testing the contrasting critical predictions from the classic and our alternative null models is required.

A microscopic competition model and its dynamics analysis on network attacks

Modeling network traffic has been a critical task in the development of Internet. Attacks and defense are prevalent in the current Internet. Traditional network models such as Poisson-related models do not consider the competition behaviors between the attack and defense parties. In this paper, we present a microscopic competition model to analyze the dynamics among the nodes, benign or malicious, connected to a router, which compete for the bandwidth. The dynamics analysis demonstrates that the model can well describe the competition behavior among normal users and attackers. Based on this model, an anomaly attack detection method is presented. The method is based on the adaptive resonance theory, which is used to learn the model by normal traffic data. The evaluation shows that it can effectively detect the network attacks.

Forces between bilayers of cetyltrimethylammonium bromide in micellar solutions

A direct force-measuring technique has been used to study the interaction forces between adsorbed CTAB (cetyltrimethylammonium bromide) bilayers at concentrations well above the CMC (critical micelle concentration). An analysis of these results based on the Poisson-Boltzmann equations leads to the conclusion that CTAB micelles and adsorbed bilayers are about 22(±4)% dissociated. The apparent agreement of bilayer and micellar ion binding parameters raises an important challenge for theories of double-layer interactions. In addition, the double-layer decay lengths observed in these micellar solutions appear to be due entirely to the dissociated bromide and free CTA+ ions, with no apparent contribution from charged micelles.

Human behavior recognition with generic exponential family duration modeling in the hidden semi-Markov model

The ability to learn and recognize human activities of daily living (ADLs) is important in building pervasive and smart environments. In this paper, we tackle this problem using the hidden semi-Markov model. We discuss the state-of-the-art duration modeling choices and then address a large class of exponential family distributions to model state durations. Inference and learning are efficiently addressed by providing a graphical representation for the model in terms of a dynamic Bayesian network (DBN). We investigate both discrete and continuous distributions from the exponential family (Poisson and Inverse Gaussian respectively) for the problem of learning and recognizing ADLs. A full comparison between the exponential family duration models and other existing models including the traditional multinomial and the new Coxian are also presented. Our work thus completes a thorough investigation into the aspect of duration modeling and its application to human activities recognition in a real-world smart home surveillance scenario.