Introduced species shed friends as well as enemies

Many studies seeking to understand the success of biological invasions focus on species' escape from negative interactions, such as damage from herbivores, pathogens, or predators in their introduced range (enemy release). However, much less work has been done to assess the possibility that introduced species might shed mutualists such as pollinators, seed dispersers, and mycorrhizae when they are transported to a new range. We ran a cross-continental field study and found that plants were being visited by 2.6 times more potential pollinators with 1.8 times greater richness in their native range than in their introduced range. Understanding both the positive and negative consequences of introduction to a new range can help us predict, monitor, and manage future invasion events.

The great escape: patterns of enemy release are not explained by time, space or climate

When a plant is introduced to a new ecosystem it may escape from some of its coevolved herbivores. Reduced herbivore damage, and the ability of introduced plants to allocate resources from defence to growth and reproduction can increase the success of introduced species. This mechanism is known as enemy release and is known to occur in some species and situations, but not in others. Understanding the conditions under which enemy release is most likely to occur is important, as this will help us to identify which species and habitats may be most at risk of invasion. We compared in situ measurements of herbivory on 16 plant species at 12 locations within their native European and introduced Australian ranges to quantify their level of enemy release and understand the relationship between enemy release and time, space and climate. Overall, plants experienced approximately seven times more herbivore damage in their native range than in their introduced range. We found no evidence that enemy release was related to time since introduction, introduced range size, temperature, precipitation, humidity or elevation. From here, we can explore whether traits, such as leaf defences or phylogenetic relatedness to neighbouring plants, are stronger indicators of enemy release across species.

Pair Density Wave Order from Electron Repulsion

A pair density wave (PDW) is a superconductor whose order parameter is a periodic function of space, without an accompanying spatially uniform component. Since PDWs are not the outcome of a weak-coupling instability of a Fermi liquid, a generic pairing mechanism for PDW order has remained elusive. We describe and solve models having robust PDW phases. To access the intermediate coupling limit, we invoke large-N limits of Fermi liquids with repulsive BCS interactions that admit saddle point solutions. We show that the requirements for long-range PDW order are that the repulsive BCS couplings must be nonmonotonic in space and that their strength must exceed a threshold value. We obtain a phase diagram with both finite temperature transitions to PDW order and a T=0 quantum critical point, where non-Fermi liquid behavior occurs.

Elucidation of the population structure and genetic diversity of Bipolaris oryzae associated with rice brown spot disease using SSR markers

Brown spot disease, caused by Bipolaris oryzae, is one of the several disastrous diseases affecting rice. The brown spot fungus illustrates substantial pathogenic and genetic variability. To the best of our knowledge, extensive analysis utilizing specific SSR primers for B. oryzae genome is quite inadequate for the population structure and genetic diversity of Indian B. oryzae isolates. A total of 84 brown spot isolates were collected from rice-cultivating areas across southern and eastern Indian states, viz., Tamil Nadu, Andhra Pradesh, Odisha and Chhattisgarh. The pathogenicity and virulence characteristics of these isolates were assessed with the susceptible cultivar CR Dhan 201. Twelve genome-specific SSR markers of B. oryzae warranted the investigation of the population structure and genetic diversity among the isolates. These isolates were categorized based on their disease grade as highly virulent isolates (4 nos.), virulent isolates (8 nos.), moderately virulent isolates (47 nos.) and less virulent isolates (25 nos.). PCR amplification and DNA sequencing confirmed the isolates to be B. oryzae. PCR amplification and DNA sequencing confirmed the isolates to be B. oryzae. The SSR markers produced a total of 35 alleles with 1 to 4 alleles per locus with a gene diversity ranging between 0.00 and 0.687 and a major allele frequency variation of 0.425-0.975. The PIC value ranged from 0.00 to 0.638 having a mean value of 0.34. Cluster analysis technique was applied to group the brown spot isolates into four distinct clusters. Principal coordinate and structure analysis identified two genetic clusters of B. oryzae isolates for individual states with some degree of distinctness complying with their virulence. Analysis of molecular variance revealed more genetic variation within populations and less among populations. The study outcome would expedite the comprehension of genetic diversity of B. oryzae across the southern and eastern states of India. Furthermore, we anticipate its guidance in the development of more effective disease management strategies as well as in the generation of novel resistant varieties through marker-assisted breeding.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03347-4.

Advancing the missed mutualist hypothesis, the under-appreciated twin of the enemy release hypothesis

Introduced species often benefit from escaping their enemies when they are transported to a new range, an idea commonly expressed as the enemy release hypothesis. However, species might shed mutualists as well as enemies when they colonize a new range. Loss of mutualists might reduce the success of introduced populations, or even cause failure to establish. We provide the first quantitative synthesis testing this natural but often overlooked parallel of the enemy release hypothesis, which is known as the missed mutualist hypothesis. Meta-analysis showed that plants interact with 1.9 times more mutualist species, and have 2.3 times more interactions with mutualists per unit time in their native range than in their introduced range. Species may mitigate the negative effects of missed mutualists. For instance, selection arising from missed mutualists could cause introduced species to evolve either to facilitate interactions with a new suite of species or to exist without mutualisms. Just as enemy release can allow introduced populations to redirect energy from defence to growth, potentially evolving increased competitive ability, species that shift to strategies without mutualists may be able to reallocate energy from mutualism toward increased competitive ability or seed production. The missed mutualist hypothesis advances understanding of the selective forces and filters that act on plant species in the early stages of introduction and establishment and thus could inform the management of introduced species.

Transmogrifying waste blister packs into defect-engineered graphene-like turbostratic carbon: novel lithium-ion (Li-ion) battery anode with noteworthy electrochemical characteristics

Blister packing materials (BMs) made up of foamed plastics are one of the major components in consumer goods, pharmaceuticals, and medical devices, which lead to a serious environmental concern as the waste management processes often result in land filling and incineration. The effective recycling of these foamed plastics has turned out to be a topic of interest in recent years to address environmental issues. Under stipulated experimental conditions, the foamed plastic of blister packaging materials, consisting of a higher percentage of carbon can provide an efficient anode material for energy storage devices. The present work outlines the preparation steps of defect-engineered graphene-like turbostratic carbon via. a physico-chemical activation method resulting in the formation of ultralow surface area (∼11.4 m² g^-1) carbon materials. In addition, graphene-like wrinkled morphologies were found to exist in the carbonaceous materials prepared at higher activation temperature (∼1400 °C) with a notable change in the crystalline characteristics on par with the commercial graphite anode. Therefore, it is expected that the material could be used in the same manner as conventional graphite materials to fabricate the cells. The prepared carbon, when explored as a lithium-ion battery (Li-ion) anode, provided outstanding electrochemical properties with a noteworthy Li-ion storage capacity of 594 mA h g^-1 measured at a current rate of 0.1 C after 200 cycles, thanks to its graphene-like features, facilitating faster Li⁺ diffusion. Even at a high C-rate (1 C), the waste plastic-derived carbon displayed outstanding rate performance (∼304 mA h g^-1) with noteworthy capacity retention (∼89%) and enhanced cycling stability (over 2000 cycles). Thus, the present research paves a new route for generating value-added carbon materials using foamed plastic med-wastes derived from blister packs.

Waste tire derived carbon as potential anode for lithium-ion batteries

The uncontrolled accumulation of end-of-life tires every year leads to serious environmental concerns, rendering setback to the sustainable growth of the society. The most viable solution to overcome this environmental issue is to convert these hazardness waste tires into value added products. In the present investigation, carbonecous based anode materials has been developed by a novel chemical activation strategy involving aqua regia followed by controlled pyrolytic condition in the selective atmospheres. Raman spectroscopic study displayed a graphitic carbon with significant degree of disordered arrangements. The generation of the turbostratic carbon with higher content of broken crystal edges is corroborated using the structural characterization such as X-ray diffraction (XRD). This fact is further corroborated from surface energy results calculated using the contact angles measured by dynamic wicking method. The prepared turbostratic carbon, when used as lithium anode, renders excellent electrochemical performances with reversible specific capacity of 350 mAhg^-1 (at 300 mAg^-1) with 81% capacity retention after 500 cycles. The present research provides new roadmap in recycling the waste tires for energy storage applications.

Erratum: Numerical Study of a Dual Representation of the Integer Quantum Hall Transition [Phys. Rev. Lett. 126, 056802 (2021)]

This corrects the article DOI: 10.1103/PhysRevLett.126.056802.

Revealing the Introduction History and Phylogenetic Relationships of Passiflora foetida sensu lato in Australia

Genomic analysis can be a valuable tool to assistmanagement of non-native invasive species, through determining source and number of introductions as well as clarifying phylogenetic relationships. Here, we used whole chloroplast sequencing to investigate the introduction history of Passiflora foetida sensu lato in Australia and clarify its relationship with other Passiflora species present. Phylogenetic analysis of chloroplast genome data identified three separate genetic lineages of P. foetida s. l. present in Australia, indicating multiple introductions. These lineages had affinities to samples from three separate areas within the native range in Central and South America that represented phylogenetically distinct lineages. These results provide a basis for a targeted search of the native range of P. foetida s. l. for candidate biological control agents that have co-evolved with this species and are thus better adapted to the lineages that are present in Australia. Results also indicated that the Passiflora species native to Australia are in a separate clade to that of P. foetida s. l. and other introduced Passiflora species cultivated in Australia. This knowledge is important to assess the likelihood of finding biological control agents for P. foetida s. l. that will be sufficiently host-specific for introduction in Australia. As P. foetida s. l. is a widespread non-native invasive species across many regions of the world, outcomes from this work highlight the importance of first evaluating the specific entities present in a country before the initiation of a biological control program.

Climate Mismatch between Introduced Biological Control Agents and Their Invasive Host Plants: Improving Biological Control of Tropical Weeds in Temperate Regions

Simple Summary

Mismatched distributions between biological control agents and their host plants occur for a variety of reasons but are often linked to climate, specifically differences in their low-temperature tolerances. How to measure and use low-temperature tolerances of control agents to inform agent prioritization, selection for redistribution, or predict efficacy is vitally important, but has not been previously synthesized in a single source. We discuss causes of climate mismatches between agents and target weeds, the traditional and non-traditional approaches that could be used to decrease the degree of mismatch and improve control, and regulatory issues to consider when taking such approaches. We also discuss the variety of cold tolerance metrics, their measurement and ecological value, and the types of modeling that can be carried out to improve predictions about potential distributions of agents. We also briefly touch on molecular bases for cold tolerance and opportunities for improving cold tolerance of agents using modern molecular tools.

Abstract

Many weed biological control programs suffer from large-scale spatial variation in success due to restricted distributions or abundances of agents in temperate climates. For some of the world’s worst aquatic weeds, agents are established but overwintering conditions limit their survival in higher latitudes or elevations. The resulting need is for new or improved site- or region-specific biological control tools. Here, we review this challenge with a focus on low-temperature limitations of agents and propose a roadmap for improving success. Investigations across spatial scales, from global (e.g., foreign exploration), to local (selective breeding), to individual organisms (molecular modification), are discussed. A combination of traditional (foreign) and non-traditional (introduced range) exploration may lead to the discovery and development of better-adapted agent genotypes. A multivariate approach using ecologically relevant metrics to quantify and compare cold tolerance among agent populations is likely required. These data can be used to inform environmental niche modeling combined with mechanistic modeling of species’ fundamental climate niches and life histories to predict where, when, and at what abundance agents will occur. Finally, synthetic and systems biology approaches in conjunction with advanced modern genomics, gene silencing and gene editing technologies may be used to identify and alter the expression of genes enhancing cold tolerance, but this technology in the context of weed biological control has not been fully explored.

Numerical Study of a Dual Representation of the Integer Quantum Hall Transition

We study the critical properties of the noninteracting integer quantum Hall to insulator transition (IQHIT) in a "dual" composite-fermion (CF) representation. A key advantage of the CF representation over electron coordinates is that at criticality CF states are delocalized at all energies. The CF approach thus enables us to study the transition from a new vantage point. Using a lattice representation of CF mean-field theory, we compute the critical and multifractal exponents of the IQHIT. We obtain ν=2.56±0.02 and η=0.51±0.01, both of which are consistent with the predictions of the Chalker-Coddington network model formulated in the electron representation.

The golden-tailed gecko: a disturbance-tolerant species in a fragmenting environment

Abstract ContextIn central Queensland, Australia, the development of a coal-seam gas (CSG) industry is creating additional fragmentation of landscapes consisting of woodland and open forest that are already highly fragmented. AimsTo assess the response to fragmentation of Strophurus taenicauda (golden-tailed gecko). The species is ‘near threatened’ in Queensland. MethodsOccurrence and abundance were examined across three categories of patch size – small (≤10 ha), medium (10–100 ha) and large (≥100 ha) – across three geographic areas of the species’ range. Minimal impact (i.e. sighting only) active searches for geckos were conducted at night. A minimum of three replicate sites of each patch size category was surveyed in each of the three geographic areas. Eleven additional patches (each <4 ha and located in the southern geographic area) were surveyed to investigate how size and spatial isolation of small patches affected occurrence and abundance of S. taenicauda. At all sites a standardised set of 22 habitat variables was collected, and the presence of other species of arboreal gecko was recorded. Key resultsThe species was located across patches of all sizes, including those as small as 1.11 ha. It was also located opportunistically in the matrix among patches and occurred in isolated trees within an urban area. The abundance of another commonly occurring arboreal gecko, Gehyra dubia (dubious dtella), was negatively correlated with S. taenicauda abundance in small patches. The most important habitat variable for S. taenicauda was average basal area of trees. As this increased, especially above 5.7 m2 ha−1, it was more likely to be present. When considering only the small patches, the main factors influencing presence and abundance of S. taenicauda were the average basal area of Callitris glaucophylla (white cypress) and grazing (negligible or absent). ConclusionsStrophurus taenicauda is a species that is tolerant of disturbance and can persist in fragmented habitat, provided the fragments have adequate cover of white cypress. ImplicationsThe species appears to be resilient to the current level of CSG development within its geographic range.

Interaction-Induced Metallicity in a Two-Dimensional Disordered Non-Fermi Liquid

The interplay of interactions and disorder in two-dimensional (2D) electron systems has actively been studied for decades. The paradigmatic approach involves starting with a clean Fermi liquid and perturbing the system with both disorder and interactions. Instead, we start with a clean non-Fermi liquid near a 2D ferromagnetic quantum critical point and consider the effects of disorder. In contrast with the disordered Fermi liquid, we find that our model does not suffer from runaway flows to strong coupling and the system has a marginally stable fixed point with perfect conduction.

Cross-database evaluation of EEG based epileptic seizures detection driven by adaptive median feature baseline correction

OBJECTIVE

In long-term electroencephalogram (EEG) signals, automated classification of epileptic seizures is desirable in diagnosing epilepsy patients, as it otherwise depends on visual inspection. To the best of the author's knowledge, existing studies have validated their algorithms using cross-validation on the same database and less number of attempts have been made to extend their work on other databases to test the generalization capability of the developed algorithms. In this study, we present the algorithm for cross-database evaluation for classification of epileptic seizures using five EEG databases collected from different centers. The cross-database framework helps when sufficient epileptic seizures EEG data are not available to build automated seizure detection model.

METHODS

Two features, namely successive decomposition index and matrix determinant were extracted at a segmentation length of 4 s (50% overlap). Then, adaptive median feature baseline correction (AM-FBC) was applied to overcome the inter-patient and inter-database variation in the feature distribution. The classification was performed using a support vector machine classifier with leave-one-database-out cross-validation. Different classification scenarios were considered using AM-FBC, smoothing of the train and test data, and post-processing of the classifier output.

RESULTS

Simulation results revealed the highest area under the curve-sensitivity-specificity-false detections (per hour) of 1-1-1-0.15, 0.89-0.99-0.82-2.5, 0.99-0.73-1-1, 0.95-0.97-0.85-1.7, 0.99-0.99-0.92-1.1 using the Ramaiah Medical College and Hospitals, Children's Hospital Boston-Massachusetts Institute of Technology, Temple University Hospital, Maastricht University Medical Centre, and University of Bonn databases respectively.

CONCLUSIONS

We observe that the AM-FBC plays a significant role in improving seizure detection results by overcoming inter-database variation of feature distribution.

SIGNIFICANCE

To the best of the author's knowledge, this is the first study reporting on the cross-database evaluation of classification of epileptic seizures and proven to be better generalization capability when evaluated using five databases and can contribute to accurate and robust detection of epileptic seizures in real-time.

Quantifying the social and economic benefits of the biological control of invasive alien plants in natural ecosystems

Invasive alien plants reduce ecosystem service delivery, resulting in environmental, economic and social costs. Here we review the returns on investment from biological control of alien plants that invade natural ecosystems. Quantifying the economic benefits of biological control requires estimates of the reductions in ecosystem goods and services arising from invasion. It also requires post-release monitoring to assess whether biological control can restore them, and conversion of these estimates to monetary values, which has seldom been done. Past studies, mainly from Australia and South Africa, indicate that biological control delivers positive and substantial returns on investment, with benefit:cost ratios ranging from 8:1 to over 3000:1. Recent studies are rare, but they confirm that successful biological control delivers attractive returns on investment, which increase over time as the value of avoided impacts accumulates.

Gene technologies in weed management: a technical feasibility analysis

With the advent of new genetic technologies such as gene silencing and gene drive, efforts to develop additional management tools for weed management is gaining significant momentum. These technologies promise novel ways to develop sustainable weed control options because gene silencing can switch-off genes mediating adaptation (e.g. growth, herbicide resistance), and gene drive can be used to spread modified traits and to engineer wild populations with reduced fitness. However, applying gene silencing and/or gene drive is expected to be inherently complex as their application is constrained by several methodological and technological difficulties. In this review we explore the challenges of these technologies, and discuss strategies and resources accessible to accelerate the development of gene-tech based tools for weed management. We also highlight how gene technologies can be integrated into existing management tactics such as classical biological control, and their possible interactions.

Gene drives in plants: opportunities and challenges for weed control and engineered resilience

Plant species, populations and communities are under threat from climate change, invasive pathogens, weeds and habitat fragmentation. Despite considerable research effort invested in genome engineering for crop improvement, the development of genetic tools for the management of wild plant populations has rarely been given detailed consideration. Gene drive systems that allow direct genetic management of plant populations via the spread of fitness-altering genetic modifications could be of great utility. However, despite the rapid development of synthetic tools and their enormous promise, little explicit consideration has been given to their application in plants and, to date, they remain untested. This article considers the potential utility of gene drives for the management of wild plant populations, and examines the factors that might influence the design, spread and efficacy of synthetic drives. To gain insight into optimal ways to design and deploy synthetic drive systems, we investigate the diversity of mechanisms underlying natural gene drives and their dynamics within plant populations and species. We also review potential approaches for engineering gene drives and discuss their potential application to plant genomes. We highlight the importance of considering the impact of plant life-history and genetic architecture on the dynamics of drive, investigate the potential for different types of resistance evolution, and touch on the ethical, regulatory and social challenges ahead.

Constraints on the superconducting order parameter in Sr2RuO4 from oxygen-17 nuclear magnetic resonance

Phases of matter are usually identified through spontaneous symmetry breaking, especially regarding unconventional superconductivity and the interactions from which it originates. In that context, the superconducting state of the quasi-two-dimensional and strongly correlated perovskite Sr₂RuO₄ is considered to be the only solid-state analogue to the superfluid ³He-A phase^1,2, with an odd-parity order parameter that is unidirectional in spin space for all electron momenta and breaks time-reversal symmetry. This characterization was recently called into question by a search for an expected 'split' transition in a Sr₂RuO₄ crystal under in-plane uniaxial pressure, which failed to find any such evidence; instead, a dramatic rise and a peak in a single-transition temperature were observed^3,4. Here we use nuclear magnetic resonance (NMR) spectroscopy of oxygen-17, which is directly sensitive to the order parameter via hyperfine coupling to the electronic spin degrees of freedom, to probe the nature of superconductivity in Sr₂RuO₄ and its evolution under strain. A reduction of the Knight shift is observed for all strain values and at temperatures below the critical temperature, consistent with a drop in spin polarization in the superconducting state. In unstrained samples, our results contradict a body of previous NMR work reporting no change in the Knight shift⁵ and the most prevalent theoretical interpretation of the order parameter as a chiral p-wave state. Sr₂RuO₄ is an extremely clean layered perovskite and its superconductivity emerges from a strongly correlated Fermi liquid, and our work imposes tight constraints on the order parameter symmetry of this archetypal system.

Candidate screening of blast resistance donors for rice breeding

Rice blast is one of the most serious diseases in the world. The use of resistant cultivars is the most preferred means to control this disease. Resistance often breaks down due to emergence of new races; hence identification of novel resistance donors is indispensable. In this study, a panel of 80 released varieties from National Rice Research Institute, Cuttack was genotyped with 36 molecular markers that were linked to 36 different blast resistance genes, to investigate the varietal genetic diversity and molecular marker-trait association with blast resistance. The polymorphism information content of 36 loci varied from 0.11 to 0.37 with an average of 0.34. The cluster analysis and population structure categorized the 80 National Rice Research Institute released varieties (NRVs) into three major genetic groups. The principal co-ordinate analysis displays the distribution of resistant and moderately resistant NRVs into different groups. Analysis of molecular variance result demonstrated maximum (97%) diversity within populations and minimum (3%) diversity between populations. Among tested markers, two markers (RM7364 and pi21_79-3) corresponding to the blast resistance genes (Pi56(t) and pi21) were significantly associated and explained a phenotypic variance of 4.9 to 5.1% with the blast resistance. These associated genes could be introgressed through marker-assisted to develop durable blast resistant rice varieties. The selected resistant NRVs could be good donors for the blast resistance in rice crop improvement research.

Blast resistance in Indian rice landraces: Genetic dissection by gene specific markers

Understanding of genetic diversity is important to explore existing gene in any crop breeding program. Most of the diversity preserved in the landraces which are well–known reservoirs of important traits for biotic and abiotic stresses. In the present study, the genetic diversity at twenty-four most significant blast resistance gene loci using twenty-eight gene specific markers were investigated in landraces originated from nine diverse rice ecologies of India. Based on phenotypic evaluation, landraces were classified into three distinct groups: highly resistant (21), moderately resistant (70) and susceptible (70). The landraces harbour a range of five to nineteen genes representing blast resistance allele with the frequency varied from 4.96% to 100%. The cluster analysis grouped entire 161 landraces into two major groups. Population structure along with other parameters was also analyzed to understand the evolution of blast resistance gene in rice. The population structure analysis and principal coordinate analysis classified the landraces into two sub–populations. Analysis of molecular variance showed maximum (93%) diversity within the population and least (7%) between populations. Five markers viz; K3957, Pikh, Pi2–i, RM212and RM302 were strongly associated with blast disease with the phenotypic variance of 1.4% to 7.6%. These resistant landraces will serve as a valuable genetic resource for future genomic studies, host–pathogen interaction, identification of novel R genes and rice improvement strategies.

Automated epileptic seizures detection using multi-features and multilayer perceptron neural network

Detection of epileptic seizure activities from long-term multi-channel electroencephalogram (EEG) signals plays a significant role in the timely treatment of the patients with epilepsy. Visual identification of epileptic seizure in long-term EEG is cumbersome and tedious for neurologists, which might also lead to human error. Therefore, an automated tool for accurate detection of seizures in a long-term multi-channel EEG is essential for the clinical diagnosis. This study proposes an algorithm using multi-features and multilayer perceptron neural network (MLPNN) classifier. After appropriate approval from the ethical committee, recordings of EEG data were collected from the Institute of Neurosciences, Ramaiah Memorial College and Hospital, Bengaluru. Initially, preprocessing was performed to remove the power-line noise and motion artifacts. Four features, namely power spectral density (Yule–Walker), entropy (Shannon and Renyi), and Teager energy, were extracted. The Wilcoxon rank-sum test and descriptive analysis ensure the suitability of the proposed features for pattern classification. Single and multi-features were fed to the MLPNN classifier to evaluate the performance of the study. The simulation results showed sensitivity, specificity, and false detection rate of 97.1%, 97.8%, and 1 h⁻¹, respectively, using multi-features. Further, the results indicate the proposed study is suitable for real-time seizure recognition from multi-channel EEG recording. The graphical user interface was developed in MATLAB to provide an automated biomarker for normal and epileptic EEG signals.

Exact Boson-Fermion Duality on a 3D Euclidean Lattice

The idea of statistical transmutation plays a crucial role in descriptions of the fractional quantum Hall effect. However, a recently conjectured duality between a critical boson and a massless two-component Dirac fermion extends this notion to gapless systems. This duality sheds light on highly nontrivial problems such as the half-filled Landau level, the superconductor-insulator transition, and surface states of strongly coupled topological insulators. Although this boson-fermion duality has undergone many consistency checks, it has remained unproven. We describe the duality in a nonperturbative fashion using an exact UV mapping of partition functions on a 3D Euclidean lattice.

Flight of Rhyzopertha dominica (Coleoptera: Bostrichidae)-a Spatio-Temporal Analysis With Pheromone Trapping and Population Genetics

The flight of the lesser grain borer, Rhyzopertha dominica (F.), near grain storages and at distances from them, was investigated to assess the potential of these beetles to infest grain and spread insecticide resistance genes. We caught R. dominica in pheromone-baited flight traps (and blank controls) set at storages, in fields away from storages, and in native vegetation across a 12-mo period. A functional set of highly polymorphic microsatellite markers was developed, enabling population genetic analyses on the trapped beetles. Pheromone-baited traps caught just as many R. dominica adults at least 1 km from grain storages as were caught adjacent to grain storages. Samples of beetles caught were genetically homogeneous across the study area (over 7,000 km²) in South Queensland, Australia. However, a change in genetic structure was detected at one bulk storage site. Subsequent analysis detected a heterozygous excess, which indicated a population bottleneck. Only a few beetles were caught during the winter months of June and July. To assess the mating status and potential fecundity of dispersing R. dominica females, we captured beetles as they left grain storages and quantified offspring production and life span in the laboratory. Nearly all (95%) of these dispersing females had mated and these produced an average of 242 offspring. We demonstrated that R. dominica populations in the study area display a high degree of connectivity and this is a result of the active dispersal of mated individuals of high potential fecundity.

Revision of the genus Eueupithecia Prout, 1910 from Argentina (Lepidoptera, Geometridae, Sterrhinae)

A new species is described from Argentina: Eueupithecia vollonoides sp. n. and a differential diagnosis from E. cisplatensis Prout, 1910 is given. The genus Eueupithecia Prout, 1910 (Sterrhinae), so far having been retained to be monotypic, includes two species now.

Soil-mediated eco-evolutionary feedbacks in the invasive plant Alliaria petiolata

Ecological and evolutionary processes historically have been assumed to operate on significantly different time-scales. We know now from theory and work in experimental and model systems that these processes can feed back on each other on mutually relevant time-scales.Here, we present evidence of a soil-mediated eco-evolutionary feedback on the population dynamics of an invasive biennial plant, Alliaria petiolata.As populations age, natural selection drives down production of A. petiolata's important antimycorrhizal allelochemical, sinigrin. This occurs due to density-dependent selection on sinigrin, which is favoured under interspecific, but disfavoured under intraspecific, competition.We show that population stochastic growth rates (λS) and plant densities are positively related to sinigrin concentration measured in seedling roots. This interaction is mediated by sinigrin's positive effect on seedling and summer survival, which are important drivers of λS.Together, these illustrate how the evolution of a trait shaped by natural selection can influence the ecology of a species over a period of just years to decades, altering its trajectory of population growth and interactions with the species in the soil and plant communities it invades.Our findings confirm the predictions that eco-evolutionary feedbacks occur in natural populations. Furthermore, they improve our conceptual framework for projecting future population growth by linking the variation in plant demography to a critical competitive trait (sinigrin) whose selective advantages decrease as populations age.

Localized polarons in in situ synthesized polyaniline nanocomposite improve the morphology and the thermal and electrical conductivity

This paper reports the localized polarons improves the morphology, thermal and electrical conductivity of dodecyl benzene sulfonic acid (DBSA) surfactant based polyaniline (PANI) – cobalt oxide (Co₃O₄) nano have synthesized by using in situ chemical reaction method.

Effect of Wavelet Packet Log Energy Entropy on Electroencephalogram (EEG) Signals

The scaling behavior of human electroencephalogram (EEG) signals is well exploited by appropriate extraction of time – frequency domain and entropy based features. Such measurable inherently helps understanding the neurophysiological phenomenon of brain as well as its associated cortical activities. Being a non-linear time series, EEG's are assumed to be fragment of fluctuations. Several attempts have been made to study the EEG signals for clinical applications such as epileptic seizure detection, evoked response potential recognition, tumor detection, identification of alcoholics and so on. In all such applications appropriate selection of feature parameter plays an important role in discriminating normal EEG from abnormal. In the recent past one can find the importance of wavelet and wavelet packet towards EEG analysis. This proposed research work investigates the effect of wavelet packet log energy entropy on EEG signals. Entropy being the measure of relative information, the proposed study attempts to discriminate the normal EEGs from abnormal EEG's by employing the log energy entropy features. For better brevity, this study restricts to the analysis of epileptic seizure from normal EEGs. Different decomposition levels from 2 to 5 were considered for wavelet packets with application of Haar, rbio3.1, sym7, dmey wavelets. A one second windowing was introduced for the data segmentation and Shannon's log energy entropy was estimated. Then the statistical non-parametric Wilcoxon model was employed. The result shows that the application of wavelet packet log energy entropy found to be a potential indicator for discriminating epileptic seizure from normal.

The importance of space, time, and stochasticity to the demography and management of Alliaria petiolata

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single- or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (lambda(S)) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of lambda(S) ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (lambda) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where lambda >1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on lambda. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of lambda in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on lambda. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.

Field-induced p-wave superconducting state of mesoscopic systems

By using Bogoliubov-de Gennes equations, we study superconducting (SC) states in a quasi-two-dimensional system of radius R. It is shown that no vortices exist in s-wave SC samples with R < R(c) ~ ξ(0), the T = 0 coherence length. We predict that chiral p-wave states exhibit superconductivity for R < R(c) only in the presence of a vortex with opposite chirality. This induced SC phase is a consequence of nonzero chirality of the pairing order parameter and implies the presence of chiral edge currents. Our study may be applied to sharply probing the pairing symmetry of unconventional superconductors.

The spatiotemporal dynamics of Tribolium castaneum (Herbst): adult flight and gene flow

Tribolium castaneum (Herbst) has been used as a model organism to develop and test important ecological and evolutionary concepts and is also a major pest of grain and grain products globally. This beetle species is assumed to be a good colonizer of grain storages through anthropogenic movement of grain, and active dispersal by flight is considered unlikely. Studies using T. castaneum have therefore used confined or walking insects. We combine an ecological study of dispersal with an analysis of gene flow using microsatellites to investigate the spatiotemporal dynamics and adult flight of T. castaneum in an ecological landscape in eastern Australia. Flying beetles were caught in traps at grain storages and in fields at least 1 km from the nearest stored grain at regular intervals for an entire year. Significantly more beetles were trapped at storages than in fields, and almost no beetles were caught in native vegetation reserves many kilometres from the nearest stored grain. Genetic differentiation between beetles caught at storages and in fields was low, indicating that although T. castaneum is predominantly aggregated around grain storages, active dispersal takes place to the extent that significant gene flow occurs between them, mitigating founder effects and genetic drift. By combining ecological and molecular techniques, we reveal much higher levels of active dispersal through adult flight in T. castaneum than previously thought. We conclude that the implications of adult flight to previous and future studies on this model organism warrant consideration.

Hidden quasi-one-dimensional superconductivity in Sr₂RuO₄

We show that the interplay between spin and charge fluctuations in Sr₂RuO₄ leads unequivocally to triplet pairing which has a hidden quasi-one-dimensional character. The resulting superconducting state spontaneously breaks time-reversal symmetry and is of the form Δ ~(p(x)+ip(y))z(^) with sharp gap minima and a d vector that is only weakly pinned. The superconductor lacks robust chiral Majorana fermion modes along the boundary. The absence of topologically protected edge modes could explain the surprising absence of experimentally detectable edge currents in this system.