Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data.

A Harmonic Suppression Scheme for Open-End Winding Split-Phase IM Drive Using Capacitive Filters for the Full Speed Range

Voltage source inverter (VSI)-fed six-phase induction motor (IM) drives have high 6n +/- 1, n = odd-order harmonic currents. This is because these currents, driven by the corresponding harmonic voltages in the inverter output, are limited only by the stator leakage impedance, as these harmonics are absent in the back electromotive force of the motor. To suppress the harmonic currents, either bulky inductive harmonic filters or complex pulsewidth modulation (PWM) techniques have to be used. This paper proposes a harmonic elimination scheme using switched capacitor filters for a VSI-fed split-phase IM drive. Two 3-phase inverters fed from capacitors are used on the open-end side of the motor to suppress 6n +/- 1, n = odd-order harmonics. A PWM scheme that can suppress the harmonics as well as balance the capacitor voltage is also proposed. The capacitor fed inverters are switched so that the fundamental voltage is not affected, and the fundamental power is always drawn from the main inverters. The proposed scheme is verified with a detailed experimental study. The effectiveness of the scheme is demonstrated by comparing the results with those obtained by disabling the capacitor fed inverters.

Characterising weather patterns associated with fire in a seasonally dry tropical forest in southern India

Anthropogenic fires in seasonally dry tropical forests are a regular occurrence during the dry season. Forest managers in India, who presently follow a fire suppression policy in such forests, would benefit from a system of assessing the potential risk to fire on a particular day. We examined the relationship between weather variables (seasonal rainfall, relative humidity, temperature) and days of fire during the dry seasons of 2004-2010, based on MODIS fire incident data in the seasonally dry tropical forests of Mudumalai in the Western Ghats, southern India. Logistic regression analysis showed that high probabilities of a fire day, indicating successful ignition of litter and grass fuel on the forest floor, were associated with low levels of early dry season rainfall, low daily average relative humidity and high daily average temperatures. These weather conditions are representative of low moisture levels of fine fuels, suggesting that the occurrence of fire is moderated by environmental conditions that reduce the flammability of fine fuels in the dry tropics. We propose a quantitative framework for assessing risk of a fire day to assist forest managers in anticipating fire occurrences in this seasonally dry tropical forest, and possibly for those across South Asia.

Turing and animal coat patterns

The present article describes a beautiful contribution of Alan Turing to our understanding of how animal coat patterns form. The question that Turing posed was the following. A collection of identical cells (or processors for that matter), all running the exact same program, and all communicating with each other in the exact same way, should always be in the same state. Yet they produce nonhomogeneous periodic patterns, like those seen on animal coats. How does this happen? Turing gave an elegant explanation for this phenomenon, namely that differences between the cells due to small amounts of random noise can actually be amplified into structured periodic patterns. We attempt to describe his core conceptual contribution below.

Time-Domain Approach to Estimate Series Capacitance of an Isolated Phase Winding of a Transformer

Information available in frequency response data is equivalently available in the time domain as a response due to an impulse excitation. The idea to pursue this equivalence to estimate series capacitance is linked to the well-known fact that under impulse excitation, the line/neutral current in a transformer has three distinct components, of which, the initial capacitive component is the first to manifest, followed by the oscillatory and inductive components. Of these, the capacitive component is temporally well separated from the rest-a crucial feature permitting its direct access and analysis. Further, the winding initially behaves as a pure capacitive network, so the initial component must obviously originate from only the (series and shunt) capacitances. With this logic, it should therefore be possible to estimate series capacitance, just by measuring the initial capacitive component of line current and the total shunt capacitance. The principle of the method and details of its implementation on two actual isolated transformerwindings (uniformly wound) are presented. For implementation, a low-voltage recurrent surge generator, a current probe, and a digital oscilloscope are all that is needed. The method is simple and requires no programming and needs least user intervention, thus paving the way for its widespread use.

Monitoring urbanization and its implications in a mega city from space: Spatiotemporal patterns and its indicators

Rapid and invasive urbanization has been associated with depletion of natural resources (vegetation and water resources), which in turn deteriorates the landscape structure and conditions in the local environment. Rapid increase in population due to the migration from rural areas is one of the critical issues of the urban growth. Urbanisation in India is drastically changing the land cover and often resulting in the sprawl. The sprawl regions often lack basic amenities such as treated water supply, sanitation, etc. This necessitates regular monitoring and understanding of the rate of urban development in order to ensure the sustenance of natural resources. Urban sprawl is the extent of urbanization which leads to the development of urban forms with the destruction of ecology and natural landforms. The rate of change of land use and extent of urban sprawl can be efficiently visualized and modelled with the help of geo-informatics. The knowledge of urban area, especially the growth magnitude, shape geometry, and spatial pattern is essential to understand the growth and characteristics of urbanization process. Urban pattern, shape and growth can be quantified using spatial metrics. This communication quantifies the urbanisation and associated growth pattern in Delhi. Spatial data of four decades were analysed to understand land over and land use dynamics. Further the region was divided into 4 zones and into circles of 1 km incrementing radius to understand and quantify the local spatial changes. Results of the landscape metrics indicate that the urban center was highly aggregated and the outskirts and the buffer regions were in the verge of aggregating urban patches. Shannon's Entropy index clearly depicted the outgrowth of sprawl areas in different zones of Delhi. (C) 2014 Elsevier Ltd. All rights reserved.

Simultaneously Uncovering the Patterns of Brain Regions Involved in Different Story Reading Subprocesses

Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading that incorporates these and additional subprocesses, simultaneously discovering their fMRI signatures. Our model predicts the fMRI activity associated with reading arbitrary text passages, well enough to distinguish which of two story segments is being read with 74% accuracy. This approach is the first to simultaneously track diverse reading subprocesses during complex story processing and predict the detailed neural representation of diverse story features, ranging from visual word properties to the mention of different story characters and different actions they perform. We construct brain representation maps that replicate many results from a wide range of classical studies that focus each on one aspect of language processing and offer new insights on which type of information is processed by different areas involved in language processing. Additionally, this approach is promising for studying individual differences: it can be used to create single subject maps that may potentially be used to measure reading comprehension and diagnose reading disorders.

The tarani mutation alters surface curvature in Arabidopsis leaves by perturbing the patterns of surface expansion and cell division

The leaf surface usually stays flat, maintained by coordinated growth. Growth perturbation can introduce overall surface curvature, which can be negative, giving a saddle-shaped leaf, or positive, giving a cup-like leaf. Little is known about the molecular mechanisms that underlie leaf flatness, primarily because only a few mutants with altered surface curvature have been isolated and studied. Characterization of mutants of the CINCINNATA-like TCP genes in Antirrhinum and Arabidopsis have revealed that their products help maintain flatness by balancing the pattern of cell proliferation and surface expansion between the margin and the central zone during leaf morphogenesis. On the other hand, deletion of two homologous PEAPOD genes causes cup-shaped leaves in Arabidopsis due to excess division of dispersed meristemoid cells. Here, we report the isolation and characterization of an Arabidopsis mutant, tarani (tni), with enlarged, cup-shaped leaves. Morphometric analyses showed that the positive curvature of the tni leaf is linked to excess growth at the centre compared to the margin. By monitoring the dynamic pattern of CYCLIN D3;2 expression, we show that the shape of the primary arrest front is strongly convex in growing tni leaves, leading to excess mitotic expansion synchronized with excess cell proliferation at the centre. Reduction of cell proliferation and of endogenous gibberellic acid levels rescued the tni phenotype. Genetic interactions demonstrated that TNI maintains leaf flatness independent of TCPs and PEAPODs.

An island called India: phylogenetic patterns across multiple taxonomic groups reveal endemic radiations

Island systems from around the world have provided fascinating opportunities for studies pertaining to various evolutionary processes. One recurring feature of isolated islands is the presence of endemic radiations. In this regard, the Indian subcontinent is an interesting entity given it has been an island during much of its history following separation from Madagascar and currently is isolated from much of Eurasia by the Himalayas in the north and the Indian Ocean in the south. Not surprisingly, recent molecular studies on a number of endemic taxa from India have reported endemic radiations. These studies suggest that the uniqueness of Indian biota is not just due to its diverse origin, but also due to evolution in isolation. The isolation of India has generated some peculiarities typically seen on oceanic islands. However, these patterns might be confined to, groups with low dispersal ability.

Environmental monitoring of bacterial contamination and antibiotic resistance patterns of the fecal coliforms isolated from Cauvery River, a major drinking water source in Karnataka, India

The present study focuses prudent elucidation of microbial pollution and antibiotic sensitivity profiling of the fecal coliforms isolated from River Cauvery, a major drinking water source in Karnataka, India. Water samples were collected from ten hotspots during the year 2011-2012. The physiochemical characteristics and microbial count of water samples collected from most of the hotspots exhibited greater biological oxygen demand and bacterial count especially coliforms in comparison with control samples (p <= 0.01). The antibiotic sensitivity testing was performed using 48 antibiotics against the bacterial isolates by disk-diffusion assay. The current study showed that out of 848 bacterial isolates, 93.51 % (n=793) of the isolates were found to be multidrug-resistant to most of the current generation antibiotics. Among the major isolates, 96.46 % (n=273) of the isolates were found to be multidrug-resistant to 30 antibiotics and they were identified to be Escherichia coli by 16S rDNA gene sequencing. Similarly, 93.85 % (n=107), 94.49 % (n=103), and 90.22 % (n=157) of the isolates exhibited multiple drug resistance to 32, 40, and 37 antibiotics, and they were identified to be Enterobacter cloacae, Pseudomonas trivialis, and Shigella sonnei, respectively. The molecular studies suggested the prevalence of blaTEM genes in all the four isolates and dhfr gene in Escherichia coli and Sh. sonnei. Analogously, most of the other Gram-negative bacteria were found to be multidrug-resistant and the Gram-positive bacteria, Staphylococcus spp. isolated from the water samples were found to be methicillin and vancomycin-resistant Staphylococcus aureus. This is probably the first study elucidating the bacterial pollution and antibiotic sensitivity profiling of fecal coliforms isolated from River Cauvery, Karnataka, India.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Differences in host species relationships and biogeographic influences produce contrasting patterns of prevalence, community composition and genetic structure in two genera of avian malaria parasites in southern Melanesia

1. Host-parasite interactions have the potential to influence broadscale ecological and evolutionary processes, levels of endemism, divergence patterns and distributions in host populations. Understanding the mechanisms involved requires identification of the factors that shape parasite distribution and prevalence. 2. A lack of comparative information on community-level host-parasite associations limits our understanding of the role of parasites in host population divergence processes. Avian malaria (haemosporidian) parasites in bird communities offer a tractable model system to examine the potential for pathogens to influence evolutionary processes in natural host populations. 3. Using cytochrome b variation, we characterized phylogenetic diversity and prevalence of two genera of avian haemosporidian parasites, Plasmodium and Haemoproteus, and analysed biogeographic patterns of lineages across islands and avian hosts, in southern Melanesian bird communities to identify factors that explain patterns of infection. 4. Plasmodium spp. displayed isolation-by-distance effects, a significant amount of genetic variation distributed among islands but insignificant amounts among host species and families, and strong local island effects with respect to prevalence. Haemoproteus spp. did not display isolation-by-distance patterns, showed marked structuring of genetic variation among avian host species and families, and significant host species prevalence patterns. 5. These differences suggest that Plasmodium spp. infection patterns were shaped by geography and the abiotic environment, whereas Haemoproteus spp. infection patterns were shaped predominantly by host associations. Heterogeneity in the complement and prevalence of parasite lineages infecting local bird communities likely exposes host species to a mosaic of spatially divergent disease selection pressures across their naturally fragmented distributions in southern Melanesia. Host associations for Haemoproteus spp. indicate a capacity for the formation of locally co-adapted host-parasite relationships, a feature that may limit intraspecific gene flow or range expansions of closely related host species.

Low-Order Harmonic Suppression for Open-End Winding IM With Dodecagonal Space Vector Using a Single DC-Link Supply

This paper proposes a technique to suppress low-order harmonics for an open-end winding induction motor drive for a full modulation range. One side of the machine is connected to a main inverter with a dc power supply, whereas the other inverter is connected to a capacitor from the other side. Harmonic suppression (with complete elimination of fifth- and seventh-order harmonics) is achieved by realizing dodecagonal space vectors using a combined pulsewidth modulation (PWM) control for the two inverters. The floating capacitor voltage is inherently controlled during the PWM operation. The proposed PWM technique is shown to be valid for the entire modulation range, including overmodulation and six-step mode of operation of the main inverter. Experimental results have been presented to validate the proposed technique.

An Open-End winding IM drive with Multilevel 12-sided Polygonal Vectors with Symmetric Triangles

Multilevel inverters with hexagonal voltage space vector structures have improved performance of induction motor drives compared to that of the two level inverters. Further reduction in the torque ripple on the motor shaft is possible by using multilevel dodecagonal (12-sided polygon) voltage space vector structures. The advantages of dodecagonal voltage space vector based PWM techniques are the complete elimination of fifth and seventh harmonics in phase voltages for the full modulation range and the extension of linear modulation range. This paper proposes an inverter circuit topology capable of generating multilevel dodecagonal voltage space vectors with symmetric triangles, by cascading two asymmetric three level inverters with isolated H-Bridges. This is made possible by proper selection of DC link voltages and the selection of resultant switching states for the inverters. In this paper, a simple PWM timing calculation method is proposed. Experimental results have also been presented in this paper to validate the proposed concept.

Kinematic flow patterns in slow deformation of a dense granular material

The kinematic flow pattern in slow deformation of a model dense granular medium is studied at high resolution using in situ imaging, coupled with particle tracking. The deformation configuration is indentation by a flat punch under macroscopic plane-strain conditions. Using a general analysis method, velocity gradients and deformation fields are obtained from the disordered grain arrangement, enabling flow characteristics to be quantified. The key observations are the formation of a stagnation zone, as in dilute granular flow past obstacles; occurrence of vortices in the flow immediately underneath the punch; and formation of distinct shear bands adjoining the stagnation zone. The transient and steady state stagnation zone geometry, as well as the strength of the vortices and strain rates in the shear bands, are obtained from the experimental data. All of these results are well-reproduced in exact-scale non-smooth contact dynamics simulations. Full 3D numerical particle positions from the simulations allow extraction of flow features that are extremely difficult to obtain from experiments. Three examples of these, namely material free surface evolution, deformation of a grain column below the punch and resolution of velocities inside the primary shear band, are highlighted. The variety of flow features observed in this model problem also illustrates the difficulty involved in formulating a complete micromechanical analytical description of the deformation.