BUTTERFLIES AND VERTEBRATE FAUNAL DIVERSITY OF THE AMBULUWAWA BIO·DIVERSITY COMPLEX

The Ambuluwawa Biodiversity Complex (ABC) was created recently on theAmbuluwawa Hill (elevation: 1071 meters) situated close to the Gampola Town, KandyDistrict. Its habitats include: lowland rainforest patches, grasslands with exposed rocks,a Pinus plantation, newly designed gardens, and several artificial pondsThe present study was carried out in this forest from 23rd January to 20th February of2003, with the objective of surveying the area's faunal diversity. The 'long transectmethod' was applied for faunal observations (both direct and indirect) along nature trailsin the forest patches and the planted forest, whereas random traversing was done in thegrassland. The observations were made once a week both in day and night times duringthe study period. The breadth of the long transect was restricted by the visibilitydetermined by the daylight and night lamps. Binoculars were used to observe birds. Inthe study of herpetofauna, hand nets were used and the animals were released afteridentification. No ichthyofauna could be observed other than the introduced fish found inthe artificial ponds.The results suggest the presence of the following altogether: 11mamalian species,including 01 endemic (within nine families),59 avian species including 07 endemic species (within 31 families),30 reptilian species including 13 endemic species (within eight families),13 amphibian species including 06 endemic species (within three families) and13 butterfly species including 02 endemic ones (within six families).The total number is 126 speciesOut of the above, 29 endemic species, 28 are nationally threatened. Moreover, there arealso two nationally threatened no-endemic species.It appears that since, the recent development of the Bio Diversity Complex the faunathere is highly threatened due to the construction activities such as rock blasting,deforestation and road development etc. Furthermore, the presence of visitors also has anegative effect on the fauna

Analysing stillbirth data using dynamic self organizing maps

Even with the presence of modern obstetric care, stillbirth rate seems to stay stagnant or has even risen slightly in countries such as England and has become a significant public health concern [1]. In the light of current medical research, maternal risk factors such as diabetes and hypertensive disease were identified as possible risk factors and are taken into consideration in antenatal care. However, medical practitioners and researchers suspect possible relationships between trends in maternal demographics, antenatal care and pregnancy information of current stillbirth in consideration [2]. Although medical data and knowledge is available appropriate computing techniques to analyze the data may lead to identification of high risk groups. In this paper we use an unsupervised clustering technique called Growing Self organizing Map (GSOM) to analyse the stillbirth data and present patterns which can be important to medical researchers

Can online support groups address psychological morbidity of cancer patients? An artificial intelligence based investigation of prostate cancer trajectories

Background Online Cancer Support Groups (OCSG) are becoming an increasingly vital source of information, experiences and empowerment for patients with cancer. Despite significant contributions to physical, psychological and emotional wellbeing of patients, OCSG are yet to be formally recognised and used in multidisciplinary cancer support programs. This study highlights the opportunity of using Artificial Intelligence (AI) in OCSG to address psychological morbidity, with supporting empirical evidence from prostate cancer (PCa) patients. Methods A validated framework of AI techniques and Natural Language Processing (NLP) methods, was used to investigate PCa patient activities based on conversations in ten international OCSG (18,496 patients- 277,805 conversations). The specific focus was on activities that indicate psychological morbidity; the reasons for joining OCSG, deep emotions and the variation from joining through to milestones in the cancer trajectory. Comparative analyses were conducted using t-tests, One-way ANOVA and Tukey-Kramer post-hoc analysis. Findings PCa patients joined OCSG at four key phases of psychological distress; diagnosis, treatment, side-effects, and recurrence, the majority group was ‘treatment’ (61.72%). The four groups varied in expression of the intense emotional burden of cancer. The ‘side-effects’ group expressed increased negative emotions during the first month compared to other groups (p<0.01). A comparison of pre-treatment vs post-treatment emotions showed that joining pre-treatment had significantly lower negative emotions after 12-months compared to post-treatment (p<0.05). Long-term deep emotion analysis reveals that all groups except ‘recurrence’ improved in emotional wellbeing. Conclusion This is the first empirical study of psychological morbidity and deep emotions expressed by men with a new diagnosis of cancer, using AI. PCa patients joining pre-treatment had improved emotions, and long-term participation in OCSG led to an increase in emotional wellbeing, indicating a decrease in psychological distress. It is opportune to further investigate AI in OCSG for early psychological intervention as an adjunct to conventional intervention programs

Computational and Experimental Studies on the Effects of Monomer Planarity on Covalent Organic Framework Formation

We report the synthesis of one new boronate ester-based covalent organic framework (COF) and two new covalent organic polymers (COPs) made with fluor­anthene-containing monomers and hexa­hydroxy­tri­phenylene. The structure of the monomer heavily influences whether this material forms a highly ordered mesoporous material (COF) or an amorphous, microporous material (COP). The synthesis of the fluor­anthene monomers was carried out using a divergent strategy that allows for systematic structural variation and the ability to conduct a careful structure–function study. We found that small structural variations in the monomers dramatically affected the crystallinity, surface area, pore structure, and luminescence properties of the polymers. While each of the monomers contains the same fluor­anthene core, the resultant pore sizes range from micro­porous (10 Å) to meso­porous (37 Å), with surface areas ranging from ∼500 to 1200 m²/g. To help explain how these small structural differences can have such a large effect, we carried out a series of molecular dynamics simulations on the polymers to obtain information with atomic-scale resolution on how the monomer structure affects non-covalent COF layer stacking