Wilde’s delight in provocation, and his exploration of alternative morel perspectives, mark his most important work of fiction, ”the picture of Dorian Gray”. The novel’s Preface presents a series of attitudinizing aphorisms about art and literature which end with the bald statement : ”All ar tis quite useless.” The narrative that follows is a melodramatic , Faustian demonstration of the notion that art and morality are quite divorced. It is, nevertheless, a text riven by internal contradictions and qualifications. Aestheticism is both damned and dangerously upheld: hedonism both indulged and disdained. Dorian Gray is a tragedy of sorts with the subtext of a morality play; it is self destructive, darkly sinning central character i sat once a desperate suicide and a martyr.
Aim: To assess coagulation parameters in inflammatory bowel disease (IBD) patients and explore their potential as predictors of disease status.\nMethods: Coagulation was measured in 987 hospitalized IBD patients and 1027 healthy controls during March 2011 to June 2016. Correlations between coagulation and disease status were evaluated. Computer-based predictive models were constructed to estimate the predictive value of coagulation parameters in the diagnosis of IBD.\nResults: Compared with healthy controls, IBD patients showed higher platelet count and plateletocrit, lower mean platelet volume, platelet distribution width and platelet-large cell ratio, prolonged prothrombin time and activated partial thromboplastin time, and increased fibrinogen and INR (p < 0.001). C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) significantly correlated with hypercoagulation (nearly all p < 0.05). Disease extent influenced coagulation status in ulcerative colitis (UC) patients while involvement of colon, stricturing lesion and perianal disease in Crohn’s disease (CD) patients. Coagulation parameters showed medium predictive value for diagnosing IBD with accuracy of 75.00% in an artificial neural network and 73.18% in support vector machine.\nConclusion: Disease status and coagulation are closely related. Coagulation parameters show potential as preliminary screening test for IBD and predict disease activity, colonic involvement, stricturing lesion and perianal disease in CD and disease activity, disease extent and endoscopic severity in UC.
In [2], we have proved a main theorem dealing with $\\varphi-{\\mid{C},\\alpha,\n\\mid}_k$ summability factors of infinite series. In this paper, we will generalize this result for the $\\varphi-{\\mid{C},\\alpha,\\beta\\mid}_k$ summability method. Also, some new and known results are obtained.
The increasing trend of stone crusher industries in India tends to release huge amount of stone crusher dust. The paper examines the source of dust emission due to stone crushing activities, and focus of some selected woody tree species within the stone crusher plant. In the present investigation, sampling was done four sites east, west, north and south of the stone crusher plant (SCP). The observed trend of stone crushing dust accumulation was in the order Butea monosperma > Holiptelia integrifolia > Azadirachta indica >Acacia nilotica. Measurement of dust holding capacity, heavy deposition of dust particles on the leaf surface was noted. Maximum dust interception was done by Butea monosperma in the east aspect 0-100m distance. In all investigated woody tree species that are far away from stone crusher dust more than that near from the stone crusher plant. Highly polluted area was recorded east aspect distance 0-100m to stone crusher plant. The results indicate that the woody tree species are good for dust capturing. They will help in selecting plant species for cultivation in contaminated fields.
In recent decades a lot of research has been carried out to analyze location-based social network data to highlight its applications. Due to the fast proliferation of mobile gadgets, the use of location-based social network services increased rapidly that generates a huge amount of social media data also referred to as “social media big data”. This location-based social network data can be used by researchers to study the user’s check-in behavior and activities associated with those check-ins and activity patterns. Moreover, these location-based social network datasets can be used to propose models and techniques that can analyze and reproduce the spatiotemporal structures, and the symmetries in user activities as well as density estimations. In the current study, different density estimation techniques are utilized to analyze the check-in frequency of users in more detail from location-based social network dataset acquired from Sina-Weibo also referred as Weibo, a popular Chinese microblog, over a specific period in 10 different districts of Shanghai, China. The aim of this study is to analyze the density of users in Shanghai city from geolocation data of Weibo as well as compare density through univariate and bivariate density estimation techniques i-e. Point Density and Kernel Density Estimation (KDE) respectively. The current study shows that the Point Density and KDE methods provide useful insights for modeling spatial patterns using geo-spatial dataset. Furthermore, it shows that KDE produces more smooth density surface as compared to Point Density. Finally, we can conclude that by utilizing KDE technique we can examine the check-in behavior in more detail for an individual as well as broader patterns in population as a whole.
In this paper we adapted the conceptual framework of Tinto (1975) to deduce student attrition\nat a South African higher education institution. We trained several machine learning\nclassification models to deduce the learner into four risk classes: \"No Risk\", \"Low risk\",\n\"Medium risk\", and \"High risk\". We provide the following contributions: (a) a comparison of\ntrained classifiers able to calculate the probability of a learners’ risk profile for a South\nAfrican University; (b) a ranking of input features by Tinto (1975) according to their entropy\nto correctly classify the class variable; and (c) an interactive program which is able to\ncalculate the posterior probability over risk. The C4:5 decision tree achieves the best\nperformance with a 75% accuracy over these risk profiles.
The study examined cross border investment and business development in the Nigeria palm oil industry. It focused on the prospects in the industry for cross border investors and the key success factors for cross border investments inflow in the Nigeria palm oil industry. The study adopted descriptive survey method in estimating the pattern of relationship of the study variables and the results obtained shows that the Pearson’s r values of 0.745, 0.796, 0.866, 0.536 and 0.652 of five prospect indicators and 0.729, 0.351, 0.705, 0.598 and 0.720 of five key success factors, which the study statistically estimated are significant for cross border investment inflows in the industry. The study, based on these findings recommends among others that government should seek for cross border investors in the palm oil industry and provide enabling environment and conditions required to boost business development in the industry. Also, investment policies that are critical to the success of investment promotion in Nigeria should be reviewed by the government and investment experts to enhance the nation’s domestic and foreign investment profiles in the non-oil sectors.