Comparing Several Parametric and Nonparametric Approaches to Time Series Clustering: A Simulation Study

One key point in cluster analysis is to determine a similarity or dissimilarity measure between data objects. When working with time series, the concept of similarity can be established in different ways. In this paper, several non-parametric statistics originally designed to test the equality of the log-spectra of two stochastic processes are proposed as dissimilarity measures between time series data. Their behavior in time series clustering is analyzed throughout a simulation study, and compared with the performance of several model-free and model-based dissimilarity measures. Up to three different classification settings were considered: (i) to distinguish between stationary and non-stationary time series, (ii) to classify different ARMA processes and (iii) to classify several non-linear time series models. As it was expected, the performance of a particular dissimilarity metric strongly depended on the type of processes subjected to clustering. Among all the measures studied, the nonparametric distances showed the most robust behavior.     

A dimorphic pheromone circuit in Drosophila from sensory input to descending output

Drosophila show innate olfactory-driven behaviours that are observed in naive animals without previous learning or experience, suggesting that the neural circuits that mediate these behaviours are genetically programmed. Despite the numerical simplicity of the fly nervous system, features of the anatomical organization of the fly brain often confound the delineation of these circuits. Here we identify a neural circuit responsive to cVA, a pheromone that elicits sexually dimorphic behaviours. We have combined neural tracing using an improved photoactivatable green fluorescent protein (PA-GFP) with electrophysiology, optical imaging and laser-mediated microlesioning to map this circuit from the activation of sensory neurons in the antennae to the excitation of descending neurons in the ventral nerve cord. This circuit is concise and minimally comprises four neurons, connected by three synapses. Three of these neurons are overtly dimorphic and identify a male-specific neuropil that integrates inputs from multiple sensory systems and sends outputs to the ventral nerve cord. This neural pathway suggests a means by which a single pheromone can elicit different behaviours in the two sexes.     

集成电路电磁适应性的时钟信号调制

电磁干扰(EMI)是瞬时功能故障的主要来源之一,原因是电源供电线上的噪声注入引起了VDD和GND的额定值的波动.介绍了一种新的方法来增强片上系统(SoC)关于电源和接地电压瞬变时的信号完整性,并且这种方法完全符合IEC 61000-4-29 标准.其基本思想是设计和IEC 61000-4-29兼容的集成电路,通过局部和动态地将时钟占空比去适应传播延迟的变化和扰动的逻辑路径.当无法满足时,该方法导致暂时把集成电路的工作频率减小到满足该标准的最小值.根据异常电网活动,时钟占空比调制(CDCM)是通过使用正和/或负边沿时钟展宽逻辑(CSL)块来实现的.基于这个概念,在尽可能保持时钟高速频率的同时,数字电路对于电源供电线上波动的耐受性将会更强.该方法可被视作一种在线提供动态自适应同步的监视技术.通过SPICE模拟,实验结果表明此方法的有效性.     

Second-Order Cybernetic Analysis to Re-construct Farmers’ Rationale When Regulating Milk Production

This paper presents an activity and knowledge analysis using second-order cybernetics for analysing human activities in social-ecological systems. We do this with the case of smallholder farmers producing milk in Nakuru County, Kenya. The analysis is based on farmers′ actions and the knowledge behind their actions. Using this approach, we analysed how smallholder farmers regulate milk production and how they influence milk quality. Farmers influence milk quality with their routine and problem-solving management actions. The knowledge behind these actions can be represented as rules. We found that Routine Control Rules that influence milk quality aim to (i) minimize contamination (ii) maintain udder health, and (iii) preserve milk. Problem-Solving Control Rules aim to deal with disturbances associated with (i) market imperfection (ii) microbiological contamination (iii) disease, and (iv) unfavourable milk composition. The approach revealed key restrictions and disturbance factors influencing milk quality in smallholder dairy systems. It also allowed for co-identification of best practices and entry points for contextualized innovations, i.e. innovations that fit into the respective production context. The co-analysis led to changes in farmers’ practices, as it fostered the co-development of milk quality standards to be applied at the community level as preparation for collective marketing activities. When emphasis is placed on finding restrictions and developing innovations, the approach can be further applied to other land-use systems.     

Small-molecule inhibitors of the AAA+ ATPase motor cytoplasmic dynein

The conversion of chemical energy into mechanical force by AAA+ (ATPases associated with diverse cellular activities) ATPases is integral to cellular processes, including DNA replication, protein unfolding, cargo transport and membrane fusion. The AAA+ ATPase motor cytoplasmic dynein regulates ciliary trafficking, mitotic spindle formation and organelle transport, and dissecting its precise functions has been challenging because of its rapid timescale of action and the lack of cell-permeable, chemical modulators. Here we describe the discovery of ciliobrevins, the first specific small-molecule antagonists of cytoplasmic dynein. Ciliobrevins perturb protein trafficking within the primary cilium, leading to their malformation and Hedgehog signalling blockade. Ciliobrevins also prevent spindle pole focusing, kinetochore-microtubule attachment, melanosome aggregation and peroxisome motility in cultured cells. We further demonstrate the ability of ciliobrevins to block dynein-dependent microtubule gliding and ATPase activity in vitro. Ciliobrevins therefore will be useful reagents for studying cellular processes that require this microtubule motor and may guide the development of additional AAA+ ATPase superfamily inhibitors.     

Coral reef diversity refutes the neutral theory of biodiversity

The global decline of coral reefs highlights the need to understand the mechanisms that regulate community structure and sustain biodiversity in these systems. The neutral theory, which assumes that individuals are demographically identical regardless of species, seeks to explain ubiquitous features of community structure and biodiversity patterns. Here we present a test of neutral-theory predictions with the use of an extensive species-level data set of Indo-Pacific coral communities. We show that coral assemblages differ markedly from neutral-model predictions for patterns of community similarity and the relative abundance of species. Within local communities, neutral models do not fit relative abundance distributions as well as the classical log-normal distribution. Relative abundances of species across local communities also differ markedly from neutral-theory predictions: coral communities exhibit community similarity values that are far more variable, and lower on average, than the neutral theory can produce. Empirical community similarities deviate from the neutral model in a direction opposite to that predicted in previous critiques of the neutral theory. Instead, our results support spatio-temporal environmental stochasticity as a major driver of diversity patterns on coral reefs.