The Dragon Tree in the Age of Exploration

he dragon tree, a peculiar species native to Socotra, southwest Arabia, east Africa, Morocco, Macaronesia, and the Canary islands, possesses an intriguing iconographic history. The first wave of images date from 1470 to 1550, beginning with Martin Schongauer’s 1470 engraving of The Flight into Egypt. These depictions portray the dragon tree in the context of a handful of biblical themes and with apparent symbolic import. After 1550, religious images of the dragon tree vanish abruptly and are replaced by representations of an empirical nature. Dragon tree iconography is notable for the extent to which it did and did not leave an impression on European art. In this paper I examine the inability of dragon tree images to gain the momentum required to propel them into European iconography more permanently, and the forces that may account for the abrupt change from biblical to botanical renderings.

Radiocarbon in tropical tree rings during the Little Ice Age

Cross-dated tree-ring cores (Pinus merkusii) from north-central Thailand, spanning AD 1620-1780, were used to investigate atmospheric C-14 for the tropics during the latter part of the Little Ice Age. In addition, a cross-dated section of Huon pine from western Tasmania, covering the same period of time, was investigated. A total of 16 pairs of decadal samples were extracted to alpha-cellulose for AMS C-14 analysis using the ANTARES facility at ANSTO. The C-14 results from Thailand follow the trend of the southern hemisphere, rather than that of the northern hemisphere. This is a surprising result, and we infer that atmospheric C-14 for north-central Thailand, at 17degrees N, was strongly influenced by the entrainment of southern hemisphere air parcels during the southwest Asian monsoon, when the Inter-Tropical Convergence Zone moves to the north of our sampling site. Such atmospheric transport and mixing are therefore considered to be one of the principal mechanisms for regional C-14 offsets. (C) 2004 Elsevier B.V. All rights reserved.

How is a fruit tree like you? Using artistic metaphors to explore and develop emotional competence in children

Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Light environment and tree development of young Acacia melanoxylon in mixed-species regrowth forest, Tasmania, Australia

Blackwood (Acacia melanoxylon R. Br.) is a valuable leguminous cabinetwood species which is commonly found as a canopy or subcanopy tree in a broad range of mixed-species moist forests on tablelands and coastal escarpments in eastern Australia. This paper reports on the competitive light environment of a commercially valuable multi-species regrowth forest in NW Tasmania, in order to define some of the functional interactions and competitive dynamics of these stands. Comparative observations were made of the internal forest light environment in response to small-gap silvicultural treatments, in a young regenerative mix of three codominant tree species. Light measurements were made during periods of maximum external irradiance of the regrowth Eucalyptus obliqua/A. melanoxylon forest canopy at age 10.5 years. This was at a time of vigourous stand development, 4.5 years following the application of three experimental silvicultural treatments whose effects were observed in comparison with an untreated canopy sample designed as a control. Minimal irradiance was observed within and beneath the dense subcanopy of the native nurse species (Pomaderris apetala) which closely surrounds young blackwood regeneration. Unlike current plantation nurse systems, the dense foliage of the native broadleaved Pomaderris all but eliminated direct side-light and low-angle illumination of the young blackwood, from the beginning of tree establishment. The results demonstrated that retention of these densely stocked native codominants effectively suppressed both size and frequency of blackwood branches on the lower bole, through effective and persistent interception of sunlight. Vigorous young blackwood crowns later overtopped the codominant nurse species, achieving a predictable height of branch-free bole. This competitive outcome offers a valuable tool for management of blackwood crown dynamics, stem form and branch habit through manipulation of light environment in young native regrowth systems. Results demonstrate that effective self-pruning in the lower bole of blackwood is achieved through a marked reduction in direct and diffuse sunlight incident on the lower crown, notably to less than 10-15% of full sunlight intensity during conditions of maximum insolation. The results also contain insights for the improved design of mixed-species plantation nurse systems using these or functionally similar species' combinations. Based on evidence presented here for native regrowth forest, plantation nurse systems for blackwood will need to achieve 85-90% interception of external side-light during early years of tree development if self-pruning is to emulate the results achieved in the native nurse system.

From a tree to a stand in Finnish boreal forests: biomass estimation and comparison of methods

There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61º50' N, 24º22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg/yr for understorey spruce to 7 kg/yr for dominant pine) when the trees were 100 years old. Tree biomass was estimated to be about 70 Mg/ha in Young-Stand and about 220 Mg/ha in Mature-Stand. In the region (58.00-62.13 ºN, 14-34 ºE, ≤ 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg/ha at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg/ha with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg/ha. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach.