Abstract: Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location, and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance and within study variance, and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach.
Abstract: Background: Persons with schizophrenia patient and misusing methamphetamines suffering from social dysfunction that impact on their quality of life. Knowledge of factors related to social dysfunction will guide the effective intervention. Objectives: To determine the direct effect, indirect effect and total effect of an acerbate Psychotics’ Symptoms, Social Support, Stressful life events, Medication use self-efficacy impact on social dysfunction in Thai schizophrenic patient and methamphetamine misuse. Methods: Data were collected from schizophrenic and methamphetamine misuse patient by self report. A linear structural relationship was used to test the hypothesized path model. Results: The hypothesized model was found to fit the empirical data and explained 54% of the variance of the psychotic symptoms (X2 = 114.35, df = 92, p-value = 0.05, X2 /df = 1.24, GFI = 0.96, AGFI = 0.92, CFI = 1.00, NFI = 0.99, NNFI = 0.99, RMSEA = 0.02). The highest total effect on social dysfunction was psychotic symptoms (0.67, p
Abstract: Social networking sites such as Twitter and Facebook
attracts over 500 million users across the world, for those users, their
social life, even their practical life, has become interrelated. Their
interaction with social networking has affected their life forever.
Accordingly, social networking sites have become among the main
channels that are responsible for vast dissemination of different kinds
of information during real time events. This popularity in Social
networking has led to different problems including the possibility of
exposing incorrect information to their users through fake accounts
which results to the spread of malicious content during life events.
This situation can result to a huge damage in the real world to the
society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting the
fake accounts on Twitter. The study determines the minimized set of
the main factors that influence the detection of the fake accounts on
Twitter, and then the determined factors are applied using different
classification techniques. A comparison of the results of these
techniques has been performed and the most accurate algorithm is
selected according to the accuracy of the results. The study has been
compared with different recent researches in the same area; this
comparison has proved the accuracy of the proposed study. We claim
that this study can be continuously applied on Twitter social network
to automatically detect the fake accounts; moreover, the study can be
applied on different social network sites such as Facebook with minor
changes according to the nature of the social network which are
discussed in this paper.
Abstract: Auditory hallucinations among the most invalidating
and distressing experiences reported by patients diagnosed with
schizophrenia, leading to feelings of powerlessness and helplessness
towards their illness. In more severe cases, these auditory
hallucinations can take the form of commanding voices, which are
often related to high suicidality rates in these patients. Several
authors propose that the meanings attributed to the hallucinatory
experience, rather than characteristics like form and content, can be
determinant in patients’ reactions to hallucinatory activity,
particularly in the case of voice-hearing experiences. In this study, 48
patients diagnosed with paranoid schizophrenia presenting auditory
hallucinations were studied. Multiple regression analyses were
computed to study the influence of several developmental aspects,
such as family and social dynamics, bullying, depression, and sociocognitive
variables on the auditory hallucinations, on patients’
attributions and relationships with their voices, and on the resulting
invalidation of hallucinatory experience. Overall, results showed how
relationships with voices can mirror several aspects of interpersonal
relationship with others, and how self-schemas, depression and actual
social relationships help shaping the voice-hearing experience. Early
experiences of victimization and submission help predict the
attributions of omnipotence of the voices, and increased hostility
from parents seems to increase the malevolence of the voices,
suggesting that socio-cognitive factors can significantly contribute to
the etiology and maintenance of auditory hallucinations. The
understanding of the characteristics of auditory hallucinations and the
relationships patients established with their voices can allow the
development of more promising therapeutic interventions that can be
more effective in decreasing invalidation caused by this devastating
mental illness.
Abstract: To measure or asses any government’s efficiency we need to measure the performance of this government in regards to the quality of the service it provides. Using a technological platform in service provision became a trend and a public demand. It is also a public need to make sure these services are aligned to values and to the whole government’s strategy, vision and goals as well. Providing services using technology tools and channels can enhance the internal business process and also help establish many essential values to government services like transparency and excellence, since in order to establish e-services many standards and policies must be put in place to enable the handing over of decision making to a mature system oriented mechanism. There was no doubt that the Sultanate of Oman wanted to enhance its services and move it towards automation and establishes a smart government as well as links its services to life events. Measuring government efficiency is very essential in achieving social security and economic growth, since it can provide a clear dashboard of all projects and improvements. Based on this data we can improve the strategies and align the country goals to them.
Abstract: Interactions among proteins are the basis of various
life events. So, it is important to recognize and research protein
interaction sites. A control set that contains 149 protein molecules
were used here. Then 10 features were extracted and 4 sample sets
that contained 9 sliding windows were made according to features.
These 4 sample sets were calculated by Radial Basis Functional neutral
networks which were optimized by Particle Swarm Optimization
respectively. Then 4 groups of results were obtained. Finally, these 4
groups of results were integrated by decision fusion (DF) and Genetic
Algorithm based Selected Ensemble (GASEN). A better accuracy was
got by DF and GASEN. So, the integrated methods were proved to
be effective.