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The present paper deals with the application of one-dimensional piezoelectric materials in particular piezo-thermo-elastic nanobeam in the context of generalized piezothermoelastic theory. The ends of the nanobeam are considered to be simply supported and at a constant temperature. The mathematical model so formed is solved to obtain the non-dimensional expressions for lateral deflection, electric potential, thermal moment, thermoelastic damping, and frequency shift. Effect of frequency on the lateral deflection, electric potential, thermal moment with generalized piezothermoelastic theory are represented graphically using the MATLAB software. Comparisons aremadewith different theories of thermoelasticity. [ABSTRACT FROM AUTHOR]

African swine fever is a devastating disease of domestic pigs and wild boars caused by African swine fever virus (ASFV). ASFV originates from sub‐Saharan African countries. In the last 10 years, the virus left its endemic range to spread to eastern Europe and Russia. On September 2018, Belgian authorities reported that ASFV had been detected in two wild boars in a southern area of the country. One year later, no domestic pig has been infected, with the last ASFV‐positive wild boar being confirmed in mid‐August 2019, suggesting that the outbreak is now controlled. However, the dispersal dynamics as well as the specific impact of ecological factors and intervention measures on the outbreak remain unknown.In total, 827 positive cases have been reported in wild boar populations. In this study, we exploit the resulting spatio‐temporal distribution of occurrence data to investigate the wavefront progression. We first present the application of recently developed methods to quantify the local wavefront velocity of an invading epidemic. Second, we develop and apply a novel analytical framework that uses occurrence data to investigate the impact of ecological factors on the dispersal dynamics of a wavefront progression.Our analyses highlighted that the network of barriers, involving installed fences, had an impact on both the effective dispersal and the wavefront dispersal velocity. Furthermore, we also demonstrated that the wavefront progression was slower outside forest areas. Together, these results have concrete implications for potential future ASFV epidemics in similar regions.Synthesis and applications. We describe a novel analytical approach that exploits occurrence data to investigate the impact of ecological factors on the wavefront velocity and actual wavefront progression. This methodology has the potential to be quickly applied to outbreak datasets solely made of occurrence data, with key benefits for the epidemiological investigations of external spatial factors impacting pathogen dispersal across non‐endemic areas. Our analytical workflow could also be further applied to investigate the impact of ecological factors on any kind of biological dispersions (pathogen spreads, invasive species). [ABSTRACT FROM AUTHOR]

Studies on the highly pathogenic avian influenza (HPAI) H5N1 suggest that wild bird migration may facilitate its long‐distance spread, yet the role of wild bird community composition in its transmission risk remains poorly understood. Furthermore, most studies on the diversity–disease relationship focused on host species diversity without considering hosts' phylogenetic relationships, which may lead to rejecting a species diversity effect when the community has host species that are only distantly related.Here, we explored the influence of waterbird community composition for determining HPAI H5N1 occurrence in wild birds in a continental‐scale study across Europe. In particular, we tested the diversity–disease relationship using both host species diversity and host phylogenetic diversity.Our results provide the first demonstration that host community composition—compared with previously identified environmental risk factors—can also effectively explain the spatial pattern of H5N1 occurrence in wild birds. We further show that communities with more higher risk host species and more closely related species have a higher risk of H5N1 outbreaks. Thus, both host species diversity and community phylogenetic structure, in addition to environmental factors, jointly influence H5N1 occurrence.Our work not only extends the current theory on the diversity–disease relationship, but also has important implications for future monitoring of H5N1 and other HPAI subtypes. [ABSTRACT FROM AUTHOR]

Abstract: Animal abundance data are essential for endangered species conservation, tracking invasive species spread, biosecurity, agricultural applications and wildlife monitoring; however, obtaining abundance data are a perennial challenge. Recent improvements in the resolution of remotely sensed imagery, and image‐processing tools and software have facilitated improvement of methods for the detection of individual, generally large‐bodied animals. The potential to monitor and survey populations from remotely sensed imagery is an exciting new development in animal ecology. We review the methods used to analyse remotely sensed imagery for their potential to estimate the abundance of wild and domestic animal populations by directly detecting, identifying and counting individuals. Despite many illustrative studies using a variety of methods for detecting animals from remotely sensed imagery, it remains problematic in many situations. Studies that demonstrated reasonably high accuracy using automated and semi‐automated techniques have been undertaken on small spatial scales relative to the geographical range of the species of interest and/or in homogenous environments such as sea ice. The major limitations are the relatively low accuracy of automated detection techniques across large spatial extents, false detections and the cost of high‐resolution data. Future developments in the analysis of remotely sensed data for population surveys will improve detection capabilities, including the advancement of algorithms, the crossover of software and technology from other disciplines, and improved availability, accessibility, cost and resolution of data. [ABSTRACT FROM AUTHOR]

Invading species rarely spread homogeneously through a landscape and invasion patterns typically display irregular frontal boundaries as the invasion progresses through space. Those irregular patterns are generally produced by local environmental factors that may slow or accelerate movement of the frontal boundary. While there is an abundant literature on species distribution modelling methods that quantify local suitability for species establishment, comparatively few studies have examined methods for measuring the local velocity of invasions that can then be statistically analysed in relation to spatially variable environmental factors. Previous studies have used simulations to compare different methods for estimating the overall rate of spread of an invasion. We adopted a similar approach of simulating invasions that resemble two real casestudies, both in terms of their spatial resolution (i.e. considering the size of one cell as one km) and their spatial extent (> 600 000 km2). Simulations were sampled to compare how different methods used to measure local spread rate, namely the neighbouring, nearest distance and Delaunay methods, perform for spatio-temporal comparisons. We varied the assessment using three levels of complexity of the spatio-temporal pattern of invasion, three sample sizes (500, 1000 and 2000 points), three different spatial sampling patterns (stratified, random, aggregated), three interpolation methods (generalized linear model, kriging, thin plate spline regression) and two spatio-temporal modelling structures (trend surface analysis and boundary displacement), resulting in a total of 486 different scenarios. The thin plate spline regression interpolation method, in combination with trend surface analysis, was found to provide the most robust local spread rate quantification as it was able to reliably accommodate different sampling conditions and invasion patterns. This best approach was successfully applied to two case-studies, the invasion of France by the horse-chestnut leafminer Cameraria ohridella and by the bluetongue virus, generally in agreement with previously published values of spread rates. Potential avenues for further research are discussed. [ABSTRACT FROM AUTHOR]

ABSTRACT Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource-based habitat concept ( RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector-borne pathogens is explored and illustrated with the case of bluetongue virus, a midge-transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches. [ABSTRACT FROM AUTHOR]