This paper makes a plea for a new form of international comparative housing research, in which not countries (national housing regimes) but cities or regions (local housing regimes) are the unit of analysis. Why do we need such a new comparative research approach? How can a local housing regime be conceptualised? By answering these questions, the paper attempts to lay the conceptual foundation for international comparative housing research 2.0.
Monitoring changes in populations is fundamental for effective management. The West European hedgehog (Erinaceus europeaus) is of conservation concern in the UK because of recent substantial declines. Surveying hedgehogs is, however, problematic because of their nocturnal, cryptic behaviour. We compared the effectiveness of three methods (infra-red thermal camera, specialist search dog, spotlight) for detecting hedgehogs in three different habitats. Significantly more hedgehogs were detected, and at greater distance, using the camera and dog than the spotlight in amenity grassland and pasture; no hedgehogs were detected in woodland. Increasing ground cover reduced detection distances, with most detections (59.6%) associated with bare soil or mown grass; the dog was the only method that detected hedgehogs in vegetation taller than the target species' height. The additional value of surveying with a detection dog is most likely to be realised in areas where badgers (Meles meles), an intra-guild predator, are and/or where sufficient ground cover is present; both would allow hedgehogs to forage further from refuge habitats such as hedgerows. Further consideration of the effectiveness of detection dogs for finding hedgehogs in nests, as well as developing techniques for monitoring this species in woodland, is warranted.
Precise Point Positioning (PPP) has been considered a powerful method for GNSS data processing. The essential input products, such as precise satellite orbits and clocks, are provided within the International GNSS Service (IGS) with a sufficient quality for estimating receiver coordinates with centimeter level accuracy. However, the IGS satellite clocks enable users to estimate ambiguities only as float values. An additional product for satellite phase biases is necessary for an integer ambiguity resolution (PPP AR). Another approach is the backward smoothing algorithm utilizing already precise and converged parameters for improving those parameters estimated at previous epochs. All the three approaches for ambiguity estimation are compared and assessed in terms of advantages and disadvantages, achieved coordinates precision, and flexibility. The comparison are performed through a processing of GNSS data from selected IGS permanent stations during 30 days in 2018, and a processing of high rate GNSS observations of the station STRF in Greece collected during the seismic event occurred on October 25, 2018. The backward smoothing improved the float solution similarly like the PPP AR, and therefore can be considered an alternative approach providing easier implementation and no dependency on additional satellites products. We utilized two different products for phase biases in the PPP AR, namely Integer Recovery Clocks (IRC) provided by the Centre National d’Études Spatiales/Collecte Localisation Satellites (CNES/CLS) analyses center and Fractional Cycle Biases (FCB) which were estimated at the Geodetic Observatory Pecny (GOP) analyses. The IRC is based on the assimilation phase biases into satellite clocks, while the FCB products are distributed in terms of wide-lane and narrow-lane biases. A similar accuracy obtained from our comparison indicates an interoperability of products when using different strategies and even different software.
Mean development rates under cycling temperature regimes (both alternating and sinusoidal regimes) have been found to be either accelerated, decelerated or unaffected when compared to development at constant temperature regimes with equivalent means. It is generally accepted that this phenomenon is a consequence of the non-linearity inherent in the temperature-rate relationship of insect development and is known as the rate summation, or Kaufmann, effect. Some researchers invoke an additional physiological mechanism or specific adaptation to cycling temperatures resulting in a genuine alteration of development rate. Differences in development rates at constant and cycling temperatures may have important implications for degree-day (linear) population models, which are used in bath pest management and ecological studies.
Larvae of Aglais urticae L. (small tortoiseshell), Inachis io L. (peacock), Polygonia c-album L. (comma) and Vanessa atalanta L. (red admiral) (Lepidoptera: Nymphalidae) were reared at constant (10, 15, 20, 25, 30°C) and alternating (20/10, 25/15, 30/10, 30/20°C) regimes. Development rates under the alternating regimes used were found to differ from those under equivalent constant temperatures in a pattern suggestive of the Kaufmann effect: in all species development at 20/10°C was faster than at 15°C, and for three species development at 30/20°C was slower than at 25°C. The exception was A. urticae. A similar pattern was found for growth rate and pupal weight. The results are discussed with respect to cycling temperature theory and degree-day modelling., Simon R. Bryant, Jeffrey S. Bale, Chris D. Thomas, and Lit
This paper examines the performance of four classifiers for Brain Computer Interface (BCI) systems based on multichannel EEG recordings. The classifiers are designed to distinguish EEG patterns corresponding to performance of several mental tasks. The first one is the basic Bayesian classifier (BC) which exploits only interchannel covariance matrices corresponding to different mental tasks. The second classifier is also based on Bayesian approach but it takes into account EEG frequency structure by exploiting interchannel covariance matrices estimated separately for several frequency bands (Multiband Bayesian Classifier, MBBC). The third one is based on the method of Multiclass Common Spatial Patterns (MSCP) exploiting only interchannel covariance matrices as BC. The fourth one is based on the Common Tensor Discriminant Analysis (CTDA), which is a generalization of MCSP, taking EEG frequency structure into account. The MBBC and CTDA classifiers are shown to perform significantly better than the two other methods. Computational complexity of the four methods is estimated. It is shown that for all classifiers the increase in the classifying quality is always accompanied by a significant increase of computational complexity.
The process of manual species identification is a daunting task, so much so that the number of taxonomists is seen to be declining. In order to assist taxonomists, many methods and algorithms have been proposed to develop semi-automated and fully automated systems for species identification. While semi-automated tools would require manual intervention by a domain expert, fully automated tools are assumed to be not as reliable as manual or semi-automated identification tools. Hence, in this study we investigate the accuracy of fully automated and semi-automated models for species identification. We have built fully automated and semi-automated species classification models using the monogenean species image dataset. With respect to monogeneans’ morphology, they are differentiated based on the morphological characteristics of haptoral bars, an-chors, marginal hooks and reproductive organs (male and female copulatory organs). Landmarks (in the semi-automated model) and shape morphometric features (in the fully automated model) were extracted from four monogenean species images, which were then classified using k-nearest neighbour and artificial neural network. In semi-automated models, a classification accuracy of 96.67 % was obtained using the k-nearest neighbour and 97.5 % using the artificial neural network, whereas in fully automated models, a classification accuracy of 90 % was obtained using the k-nearest neighbour and 98.8 % using the artificial neural network. As for the cross-validation, semi-automated models performed at 91.2 %, whereas fully automated models performed slightly higher at 93.75 %. and Corresponding author: Sarinder Kaur A/p Kashmir Singh