Nature of complex network of dengue epidemic as a scale-free network

Objectives: Dengue epidemic is a dynamic and complex phenomenon that has gained considerable attention due to its injurious effects. The focus of this study is to statically analyze the nature of the dengue epidemic network in terms of whether it follows the features of a scale-free network or a random network. Methods: A multifarious network of Aedes aegypti is addressed keeping the viewpoint of a complex system and modelled as a network. The dengue network has been transformed into a one-mode network from a two-mode network by utilizing projection methods. Furthermore, three network features have been analyzed, the power-law, clustering coefficient, and network visualization. In addition, five methods have been applied to calculate the global clustering coefficient. Results: It has been observed that dengue epidemic follows a powerlaw, with the value of its exponent γ = –2.1. The value of the clustering coefficient is high for dengue cases, as weight of links. The minimum method showed the highest value among the methods used to calculate the coefficient. Network visualization showed the main areas. Moreover, the dengue situation did not remain the same throughout the observed period. Conclusions: The results showed that the network topology exhibits the features of a scale-free network instead of a random network. Focal hubs are highlighted and the critical period is found. Outcomes are important for the researchers, health officials, and policy makers who deal with arbovirus epidemic diseases. Zika virus and Chikungunya virus can also be modelled and analyzed in this manner. © 2019 The Korean Society of Medical Informatics

Network Formation and Analysis of Dengue Complex Network

Several efforts have been made and are constantly being made to keep the Aedes aegypti virus under control. Numerous scholars are involved in the study of medicine, while others are working in computer science and mathematics to model the spread of this disease. This study will help to comprehend how this epidemic sickness behaves. A complex network has been established from the complex dengue phenomenon. We have evaluated dengue network topology by pondering scale-free network properties. The network’s resilience in tracking the dengue epidemic is measured by systematically removing nodes and links. The primary hubs of this network are emphasized, and the vulnerability of the network structure has been examined through an in-depth investigation of the dengue virus’s spreading behavior. Understanding the intricate web of dengue outbreaks relies heavily on geographic representation. The applied method on the dengue epidemic network and the results will be added as scientific additions to the literature on complex networks. Different network analysis metrics have been applied (closeness centrality, betweenness centrality, eigenvector centrality, network density), and the network’s stability has been evaluated. This network is extremely vulnerable to targeted attacks; results showed that after removing 8% of focal hubs, 34% of the network is destroyed

Robustness of dengue complex network under targeted versus random attack

Dengue virus infection is one of those epidemic diseases that require much consideration in order to save the humankind from its unsafe impacts. According to the World Health Organization (WHO), 3.6 billion individuals are at risk because of the dengue virus sickness. Researchers are striving to comprehend the dengue threat. This study is a little commitment to those endeavors. To observe the robustness of the dengue network, we uprooted the links between nodes randomly and targeted by utilizing different centrality measures. The outcomes demonstrated that 5% targeted attack is equivalent to the result of 65% random assault, which showed the topology of this complex network validated a scale-free network instead of random network. Four centrality measures (Degree, Closeness, Betweenness, and Eigenvector) have been ascertained to look for focal hubs. It has been observed through the results in this study that robustness of a node and links depends on topology of the network. The dengue epidemic network presented robust behaviour under random attack, and this network turned out to be more vulnerable when the hubs of higher degree have higher probability to fail. Moreover, representation of this network has been projected, and hub removal impact has been shown on the real map of Gombak (Malaysia)

Usability Evaluation of Freelancing websites A case of Fiverr using SUS

Fiverr.com is one of the biggest freelancing websites in the world. It provides a platform to clients and freelancers. In Fiverr, buyers pay in advance for the “gigs” created by sellers. A “gig” on Fiverr shows a specific service or set of skills of any type of freelance service, ranging from copywriting to social media marketing, to web design. This website is used by all types of users. Many people face problems regarding its interface. For many novice and intermediate users, this website is complicated. In this study, SUS is used to measure the usability of the Fiverr.com website. The main focus of this paper will stay on the SUS survey done on Google forms after performing some tasks. Results from the Google forms survey will be used to get the usability of this website either people are satisfied with the website or not. Usability evaluation of Fiverr is conducted by evaluating it with many parameters like efficiency, effectiveness, and the satisfaction of users. Another objective of this research is to improve the interface of this website. A system usability scale (SUS) is a quick and effective approach to evaluate the usability of a product. It is a low-expense usability scale that can be employed for the assessment of interactive systems. The SUS questionnaire is widely used to measure the usability of e-commerce websites. In this study, novice, intermediate and expert users, a total of 30 participant’s feedback was combined to improve its design. Results from Google forms show a 63.3 mean SUS value. It shows that the Fiverr.com website has minor issues that need to be resolved. If these problems are resolved it will help new clients and sellers in the future

The Impact of Social Media on the Personality Trait of Undergraduates students: A Descriptive Analytical Approach

Personality development of an individual is a continuous process that involves multiple methods and techniques. Study on a person’s personality is conducted by examining inherited and adopted personality traits during their life span. Higher education institutes play a vital role in flourishing student’s personality and significant revolution is noticed by the researchers in this regard. Individual’s personality is being affected by use of social media including Facebook, Twitter, LinkedIn and many more. Facebook (FB) is widely used as an online social network to communicate with other individuals. It is observed that students are also users of FB for learning, interacting, recreating and browsing purposes. Our research falls in the same dimension to study student’s personality traits through their FB use and eventually analyze the change in their personality. For the same, four higher education institutes of Pakistan located in Lahore are targeted. Data is collected for five years from under graduate students from 2015-2019. It has two main purpose; firstly, to present analytical results and secondly, to examine the changes in person’s personality traits (PT) during degree program at the university. Data is collected from FB profiles through an application and Big Five Personality Trait model is used to conduct personality assessment. Five PT are studied namely; extraversion, agreeableness, openness, conscientiousness, and neuroticism. Results interpret the direct relationship of the personality trait with the use of FB and it has shown increased impact on student’s personality over the progress of the degree program. Students of all four universities came up with almost identical results that depict the similar role of an institute in the development of the student’s personality. Research findings contribute towards data science by proving analytical data on student’s personality traits. Also, it acts as guide for educational institutes to deeply cope with targeted PT of a student. Eventually, it facilitates the students to use OSN more effectively in development of their positive personality

Template based procedural rigging of quadrupeds with custom manipulators

Character rigging is a process of endowing a character with a set of custom manipulators and controls making it easy to animate by the animators. These controls consists of simple joints, handles, or even separate characters selection windows. This research paper present an automated rigging system for quadruped characters with customs control and manipulators for animation. The full character rigging mechanism is procedurally driven based on various principles and requirements used by the riggers and animators. The automation is achieved initially by creating widget then can be customized by the rigger according to the character shape, height and proportion. Then joint locations for each body parts are calculated and widgets are replaced programmatically. Finally a complete and fully operational procedural generated character control rig is created and attached with the underlying skeleton joints. The functionality and feasibility of the rig was analyzed from various sources and actual character motion and a requirements criterion was met. The final rigged character provides an efficient and easy to manipulate control rig with no lagging and at high frame rate

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

The Effect of Implementing of Six Sigma Approach in Improving the Quality of Higher Education Institutions in Bahrain

The main important issue in education curriculum currently is best quality in higher learning. The stakeholders and the growing competitive environment has have increased the demand for higher quality. Previously, Six Sigma has successfully been applied in the product and service improvement in the field of business, but still, this concept has not yet been adopted in the higher education. This study outlined the models that can be adopted by improving the quality of higher learning by applying this concept. Applying the six sigma principles, for instance, the continuous improvement, reduction in waste, and process improvement apply closely to the accreditation agencies and the higher education institutions missions. The study used the questionnaire instrument to collect the data randomly from a sample of (357) respondents representing the general staff of higher education institutes at Kingdom of Bahrain. It has been established that majority of the institutions (56.7 per cent) use six sigma model in improving quality. They invest in communicating the quality objectives to the employees. This is important as communicating quality objectives and the modalities of attaining them are important to the institution. Study recommended ensuring that there is elaboration and well-communicated quality policy, and it is essential to be known by all stakeholders

Two-mode complex network modeling of dengue epidemic in Selangor, Malaysia

There are many examples of complex systems in the world. These systems are very difficult to analyze due to huge number of interacting elements and complex interaction patterns between the elements. These systems can be properly analyzed by converting them into complex networks, where nodes can represent elements of the systems and links depicts the interaction patterns between these elements. Recently, many dengue fever cases are reported in Malaysia which shows the exponential increase of this fever in the country. In this paper we have formalized the dataset of dengue fever cases in Malaysia into two-mode complex network to analyze its impact on the localities. By applying network analysis metrics this research has revealed that few locations have high impact of dengue and they should be treated as critical to minimize the overall impact of spreadin