Development of Java based graphical user interface for Diagnosis of Hepatitis UsingI Mixture of Expert

Hepatitis is deadly, and the fifth leading cause of death after heart disease, stroke, chest disease and cancer. Worldwide, 1.5 million deaths per year have been estimated. Detection of hepatitis is a big problem for general practitioners. An expert doctor commonly makes decisions by evaluating the current test results of a patient or by comparing the patient with others with the same condition with reference to the previous decisions. Many machine learning and data mining techniques have been designed for the automatic diagnosis of hepatitis. However, no one tool is available to the general population for the diagnosis of Hepatitis. Hence, a graphical user interface-enabled tool needs to be developed, through which medical practitioners can feed patient data easily and find hepatitis diagnoses instantly and accurately. 
Methods: In this study a hepatitis dataset was taken from the UCI machine repository database with a total of 20 attributes of two classes, Affected and Not Affected. 
Results and Conclusion: The models have been generated with a mixture of experts as a classification method for the diagnosis of hepatitis. Very good accuracy has been observed in the generated models. Finally, the model having the least minimum square error was selected. This model was then linked with GUI for the design of tools for hepatitis prediction

The domestic benefits of tropical forests : a critical review emphasizing hydrological functions

The authors critically review the literature on the net domestic (within-country) economic benefits of protecting tropical forests, focusing on hydrological benefits and the production of nontimber forest products. (The review does not consider other important classes of benefits, including global benefits of all kinds, ecological benefits which do not have instrumental economic value, and the existence value of forests.) Their main conclusions: (1)The level of net domestic benefits from forest preservation is highly sensitive to the alternative land use and to local climatic, biological, geological, and economic circumstances. When the alternative use is agroforestry or certain types of tree crops, the preservation of natural forests may yield no instrumental domestic benefits. (2)The hydrological benefits from forest preservation are poorly understood and likely to be highly variable. They may also be fewer than popularly assumed: Deforestation has not been shown to be associated with large-scale flooding. Tropicaldeforestation is generally associated with higher, not lower, dry season flows. Although it is plausible that deforestation should affect local precipitation, the magnitude and even the direction of the effects are unknown, except in the special case of cloud forests that"harvest"passing moisture. The link between deforestation and downstream sediment damage is sensitive to the basic topography and geology. Where sediment transport is slow - as in large, low-gradient basins - downstream impacts may manifest themselves in the distant future, so that the net present value of damage is small. Steep basins near reservoirs or marine fisheries, on the other hand, can cause substantial damage if land cover is severely disturbed. But only a few pioneering studies have examined the economics of reservoir sedimentation, and improved models of both sediment transport and dam function are needed. (3) The most impressive point estimates of forest value based on nontimber forest products are often based on atypical cases of faulty analysis. Where domesticated or synthetic substitutes exist, the nontimber forest product-related rents for natural forests will usually be driven toward zero.Water Conservation,Roads&Highways,Wetlands,Hydrology,Environmental Economics&Policies,Water Resources Assessment,Forestry,Hydrology,Roads&Highways,Wetlands

3D Face Recognition using Significant Point based SULD Descriptor

In this work, we present a new 3D face recognition method based on Speeded-Up Local Descriptor (SULD) of significant points extracted from the range images of faces. The proposed model consists of a method for extracting distinctive invariant features from range images of faces that can be used to perform reliable matching between different poses of range images of faces. For a given 3D face scan, range images are computed and the potential interest points are identified by searching at all scales. Based on the stability of the interest point, significant points are extracted. For each significant point we compute the SULD descriptor which consists of vector made of values from the convolved Haar wavelet responses located on concentric circles centred on the significant point, and where the amount of Gaussian smoothing is proportional to the radii of the circles. Experimental results show that the newly proposed method provides higher recognition rate compared to other existing contemporary models developed for 3D face recognition

Associations of C-reactive protein and psychological distress are modified by antidepressants, supporting an inflammatory depression subtype: Findings from UKHLS

Background Clinical evidence increasingly suggests inflammation may be important specifically for an etiologically distinct depression subtype, characterised by resistance to antidepressant medication. However, epidemiological investigations of the relationship of inflammation with depression and psychological distress have failed to acknowledge these developments, which may have resulted in bias or masking of associations driven by the subtype. This may have contributed to inconsistent results in epidemiological studies, and equivocal support for an inflammation-depression link. Methods An antidepressant-resistant, inflammatory depression subtype would result in stronger associations of depressive symptomatology with inflammation among antidepressant users than non-users, due to over-representation of subtype individuals among antidepressant users experiencing severe or persistent symptoms. We investigate, in a sample of 10,363 UK adults aged 16–98, modification by antidepressants of cross-sectional and longitudinal associations between C-reactive protein and psychological distress (General Health Questionnaire score, GHQ). We account for confounding by age, gender, income, inflammatory somatic illness, body mass index and, in longitudinal models, baseline psychological distress. Sensitivity analyses consider smoking, ethnicity, and other medications. Results Robust associations of log-CRP and GHQ were seen for antidepressant users but not for non-users in both cross-sectional (coeff: 0.54, p = 0.01 vs 0.06, p = 0.28) and longitudinal models (coeff: 0.57, p = 0.006 vs 0.04, p = 0.39 two waves post-baseline). Cross-sectional associations were strongest for tricyclic users, and longitudinal associations strongest for SSRI users. In multilevel, repeated-measures longitudinal models, associations for antidepressant users peaked two waves after baseline before declining. Conclusions Results suggest evidence for existence of an inflammatory depression subtype. Previous studies’ exclusion of antidepressant users and failure to consider interactive effects may have obscured associations driven by the subgroup. Follow-up work is now needed in community samples with clinical depression measures and prescription histories, to further elucidate the mechanisms involved