Statistical significance of sequential firing patterns in multi-neuronal spike trains

Sequential firings with fixed time delays are frequently observed in simultaneous recordings from multiple neurons. Such temporal patterns are potentially indicative of underlying microcircuits and it is important to know when a repeatedly occurring pattern is statistically significant. These sequences are typically identified through correlation counts. In this paper we present a method for assessing the significance of such correlations. We specify the null hypothesis in terms of a bound on the conditional probabilities that characterize the influence of one neuron on another. This method of testing significance is more general than the currently available methods since under our null hypothesis we do not assume that the spiking processes of different neurons are independent. The structure of our null hypothesis also allows us to rank order the detected patterns. We demonstrate our method on simulated spike trains.

Estimating daily methane production in individual cattle with irregular feed intake patterns from short-term methane emission measurements

Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.

Estimation and evaluation of multi-decadal fire severity patterns using Landsat sensors

Retrospective identification of fire severity can improve our understanding of fire behaviour and ecological responses. However, burnt area records for many ecosystems are non-existent or incomplete, and those that are documented rarely include fire severity data. Retrospective analysis using satellite remote sensing data captured over extended periods can provide better estimates of fire history. This study aimed to assess the relationship between the Landsat differenced normalised burn ratio (dNBR) and field measured geometrically structured composite burn index (GeoCBI) for retrospective analysis of fire severity over a 23 year period in sclerophyll woodland and heath ecosystems. Further, we assessed for reduced dNBR fire severity classification accuracies associated with vegetation regrowth at increasing time between ignition and image capture. This was achieved by assessing four Landsat images captured at increasing time since ignition of the most recent burnt area. We found significant linear GeoCBI–dNBR relationships (R2 = 0.81 and 0.71) for data collected across ecosystems and for Eucalyptus racemosa ecosystems, respectively. Non-significant and weak linear relationships were observed for heath and Melaleuca quinquenervia ecosystems, suggesting that GeoCBI–dNBR was not appropriate for fire severity classification in specific ecosystems. Therefore, retrospective fire severity was classified across ecosystems. Landsat images captured within ~ 30 days after fire events were minimally affected by post burn vegetation regrowth.

Constructing Ethical Patterns in Times of Globalization : Hans Küng's Global Ethic Project and Beyond

The purpose of this study is to evaluate contemporary philosophical models for global ethics in light of the Catholic theologian Hans Küng s Global Ethic Project (Projekt Weltethos). Küng s project starts with the motto, No survival without world ethos. No global peace without peace between religions. I will use the philosophically multidimensional potential of Projekt Weltethos in terms of its possible philosophical interpretations to evaluate the general discussion of global ethics within political philosophy today. This is important in its own right, but also because through it, opportunities will emerge to articulate Küng s relatively general argument in a way that leaves less room for mutually contradictory concretizations of what global ethics ultimately should be like. The most important question in this study is the problem of religious and ideological exclusivism and its relation to the ethically consistent articulation of global ethics. I will first explore the question of the role of religion as the basis for ethics in general and what Küng may mean by his claim that only the unconditional can oblige unconditionally. I will reconstruct two different overall philosophical interpretations of the relationship between religious faith and human rationality, each having two different sub-divisions: a liberal interpretation amounts to either a Kantian-Scheiermacherian or a Jaspersian view, whereas what I call postliberal interpretation amounts to either an Aristotelian-Thomistic or an Augustinian view. Thereafter, I will further clarify how Küng views the nature of ethics beyond the question of its principal foundation in religious faith: Küng searches for a middle way between consequentialist and non-consequentialist ethics, a way in which the latter dimension has the final stake. I will then set out to concretize further this more or less general notion of the theoretical potential of Projekt Weltethos in terms of certain precise philosophico-political models. I categorize these models according to their liberal or postliberal orientation. The liberal concretization leads me to consider a wide spectrum of post-Kantian and post-Hegelian models from Rawls to Derrida, while the alternative concretization opens up my ultimate argument in favor of a postliberal type of modus vivendi. I will suggest that the only theoretically and practically plausible way to promote global ethics, in itself a major imperative today, is the recognition of a fundamental and necessary contest between mutually exclusive ideologies in the public sphere. On this basis I will proceed to my postliberal proposal, namely, that a constructive and peaceful encountering of exclusive difference as an ethical vantage point for an intercultural and inter-religious peace dialogue is the most acute challenge for global ethics today.

Tax compliance and psychic costs: Behavioral experimental evidence using a physiological marker

Although paying taxes is a key element of a well-functioning society, there is still limited understanding as to why people actually pay their taxes. Models emphasizing that taxpayers make strategic, financially motivated compliance decisions seemingly assume an overly restrictive view of human nature. Law abidance may be more accurately explained by social norms, a concept that has gained growing importance as research attempts to understand the tax compliance puzzle. This study analyzes the influence of psychic stress generated by the possibility of breaking social norms in the tax compliance context. We measure psychic stress using heart rate variability (HRV), which captures the psychobiological or neural equivalents of psychic stress that may arise from the contemplation of real or imagined actions, producing immediate physiologic discomfort. The results of our laboratory experiments provide empirical evidence of a positive correlation between psychic stress and tax compliance, thus underscoring the importance of moral sentiments for tax compliance. We also identify three distinct types of individuals who differ in their levels of psychic stress, tax morale, and tax compliance.

Patterns of support in an online community for smoking cessation

Social support offers various benefits for health and behaviour change. However, previous work has shown that individuals are typically reluctant to ask for support on social network sites, unless they can present a changed, healthier identity. To examine the relationship between stage of change and social support we conducted a thematic analysis of messages posted in a public Facebook support group for people trying to quit smoking. Our findings show that the kind of support exchanged online is related to participants' stage of change. Contrary to our expectations, supportive responses and leadership in the support group came mainly from users who just started their change process rather than people who had already changed. We discuss contributions to theories of online participation and impression management as well as implications for practitioners who seek to establish support groups.

On the expressive power of behavioral profiles

Behavioral profiles have been proposed as a behavioral abstraction of dynamic systems, specifically in the context of business process modeling. A behavioral profile can be seen as a complete graph over a set of task labels, where each edge is annotated with one relation from a given set of binary behavioral relations. Since their introduction, behavioral profiles were argued to provide a convenient way for comparing pairs of process models with respect to their behavior or computing behavioral similarity between process models. Still, as of today, there is little understanding of the expressive power of behavioral profiles. Via counter-examples, several authors have shown that behavioral profiles over various sets of behavioral relations cannot distinguish certain systems up to trace equivalence, even for restricted classes of systems represented as safe workflow nets. This paper studies the expressive power of behavioral profiles from two angles. Firstly, the paper investigates the expressive power of behavioral profiles and systems captured as acyclic workflow nets. It is shown that for unlabeled acyclic workflow net systems, behavioral profiles over a simple set of behavioral relations are expressive up to configuration equivalence. When systems are labeled, this result does not hold for any of several previously proposed sets of behavioral relations. Secondly, the paper compares the expressive power of behavioral profiles and regular languages. It is shown that for any set of behavioral relations, behavioral profiles are strictly less expressive than regular languages, entailing that behavioral profiles cannot be used to decide trace equivalence of finite automata and thus Petri nets.

An annotated checklist of amphibian of India with some insights into the patterns of species discoveries, distribution and endemism

An annotated checklist of 284 species of amphibians of India accommodated under 50 genera and 14 families is provided. Synonyms, English names, type localities, deposition of type specimens, type specimen availability and distributional records in India and outside India are provided for all the species. Among the 284 species of amphibians from India, 132 are endemic to Western Ghats; 29 to Northeastern India; and 5 to Andaman Nicobar islands. Species discovery patterns from the various biogeographic zones in India are discussed in detail. Cumulative discovery pattern with special reference to the genera Fejervarya (17 species), Nyctibatrachus (16 species), Indirana (10 species), Micrixalus (11 species), Philautus (46 species) and Gegeneophis (10 species) are also discussed.

Mining topical relevant patterns for multi-document summarization

Multi-document summarization addressing the problem of information overload has been widely utilized in the various real-world applications. Most of existing approaches adopt term-based representation for documents which limit the performance of multi-document summarization systems. In this paper, we proposed a novel pattern-based topic model (PBTMSum) for the task of the multi-document summarization. PBTMSum combining pattern mining techniques with LDA topic modelling could generate discriminative and semantic rich representations for topics and documents so that the most representative and non-redundant sentences can be selected to form a succinct and informative summary. Extensive experiments are conducted on the data of document understanding conference (DUC) 2007. The results prove the effectiveness and efficiency of our proposed approach.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.