Are prescription opioids increasing the addictive behavior and death rate in the United States over the last 20 years?

The United States is in an opioid crisis. Of all the opioids that are marketed in the United States the most popular is Oxycontin, containing the active ingredient oxycodone, the chemical equiv-alent of heroin which is more powerful than morphine. Along with heroin and fentanyl, Oxy-contin has become one of the great killers of this era. It is estimated that in 2016 there were over 20,000 overdose deaths related to prescription pain relievers, as opposed to 12,990 over-dose deaths related to heroin in 2015. The state of West Virginia has been the one that has suf-fered the most. The rate of opioid-related overdose deaths in West Virginia, the state worst af-flicted, has gone from 1.8 deaths per 100,000 in 1999 to 43.4 deaths per 100,000 in 2016. For the sake of mathematical exactitude this is a rise of 2400% in the incidence of opioid-related death in a single state, while the rest of the country’s death rate has ‘only’ risen by 700%

Rss-Based Information Delivery Model for Learning Management System

In modern education, e-learning or Internet enabled learning has been extensively used by teaching and learning institutions, especially by higher education for improving their educational services. Learning Management Systems (LMS) are one of the important parts of e-learning solutions for providing learning contents and learning information during the educational process. Information delivery as main functionality of these systems has a vital role in the success of these systems in achieving their goals. An LMS with growing number of users, courses, and frequently updated learning information resources needs a systematic, fast and easy to use information delivery service which can support personalization also. As a response to this need and with considering technical and pedagogical benefits of RSS (Really Simple Syndication), this research applied a combination of RSS 2.0 and RSS 1.0 to design a new RSS-based information delivery framework for LMSs. The proposed RSS based information delivery framework is implemented on e- SPRINT, an existing LMS at Universiti Putra Malaysia as object of experiment, and evaluated regarding to the impact of RSS-based information delivery framework in users satisfaction and usability of the LMS in information delivery. Based on the analysis of the results of experimental design there is positive changes in users satisfaction with information delivery after using the framework compared to before using the framework. According to usability evaluation of the RSS information delivery framework also, positive changes of user perception from the aspect of usability in information delivery has been gained. It is mentionable that the scope of the study was limited to the case study system. The contribution of this study was the design and development of an RSS-based information delivery model for LMSs to support systematic fast and easy to use information delivery

Risky Time Driven Activity Based Costing in a Medical center: A Development, implementation and simulation based optimization approach

Nowadays, with the development of enterprises andincreases in competitions, management needs to do more actual investigation andin-depth analysis. Meanwhile, practical information about the service cost ofeach client/product and determining free capacity of resources are highlydesirable, in order to detect which of clients/products are more profitable.There are several available costing systems in the literature; however till thepresent time, none of them are considered to have a probabilistic nature associatedwith a business environment. In this paper, a standard time driven activitybased costing (TDABC) is combined with a simulation model, proposing a novel algorithmcalled Risky TDABC. The three risky factors which are considered in this study are:1.Resource capacity 2.Estimated activity time 3.The required quantity of an activity.Additionally, the idle time of each resource is also determined, an aspectwhich has not been considered in the standard TDABC system. Therefore, byapplying a resource configuration management in a medical center, differentscenarios are developed and compared to each other, finding the best-knownalternative through a simulation based optimization approach. The obtained resultsare apparently found to be more actual and reliable. The proposed model is finallyvalidated and successfully implemented in a healthcare center department

Religion and the Evolution of Democracy: A Revised Selectorate Model for the Arab Spring

2011 was a seminal year in the history of the Middle East and North Africa (MENA). Popularly referred to as the Arab Spring, the region has experienced a wave of revolutions and instability. It can be classified in three broad categories within 2011: Uprisings that have resulted in the overthrow of standing regimes, uprisings that have failed to overthrow standing regimes, and states that have not experienced popular revolts. In the first category Libya, Egypt, Yemen, and Tunisia have all experienced uprisings resulting in the respective departure of Muamar Gaddafi, Hosni Mubarak, Ali Abdullah Saleh, and Zine Al Abidine Ben Ali. In contrast Syria and Bahrain have experienced uprisings that have not resulted into the toppling of their regimes thus far. Finally, countries such as Saudi Arabia and Iran have experienced none of the instability observed in 2011 within the same time period. In tracking the evolution of selectorates, I identified the rise of actors within the newly developing coalitions whose Islamist preferences are unaccounted for in the standard Selectorate Model. As later explained in detail, Selectorate Theory is driven by the public-private goods argument. The theory states that a leader’s political survival is based on the mix of private payoffs he can provide to his selectorate and public goods provided to the general population. The once secular despots are either gone or are on the way out as evident by the removal of Hosni Mubarak, Zine Abidine Ben-Ali, Saddam Hussein, Muamar Gaddafi, Ali Abdullah Saleh, and the currently embattled Bashar Al- Assad. They are being replaced or have already been removed by governments that are led by Islamic Parties. Therefore, newly elected or appointed leaders must take into account the role of religion in their calculus for political survival in a way that they did not before. This begs the question: what about the regimes in my case studies that have not been toppled such as Saudi Arabia, Iran, and Bahrain? Although these are highly autocratic governments, the leaders of such governments have a legitimacy that is derived from implicit approval of their Islamist allies. This strengthens the argument that religion must be accounted for beyond the standard Selectorate Model rationale for political survival in MENA. In such context I provide a revised Selectorate Model explanation that accounts for the role of religion. I conclude that the standard Selectorate Theory is insufficient for MENA because it is does not account for the role of religion. By testing the coalitional distribution and evolution of selectorates, I developed a revised Selectorate Model that includes the role of religion along with the standard private payoffs – public goods argument. The role of religion is expressed by the presence of religious stakeholders in the agent based model such as clerics, shura councils or Islamic parties present in all selectorates in MENA. I tracked the selectorates through a series of predictions made throughout the course of 2011 using the Senturion agent based model. It serves as a powerful alternative to standard historical analysis and wisdom. I provide an explanation of why certain regimes fell while others remained relatively stable and why some governments experiencing similar instability remain using agent based modeling (ABM) in application to Selectorate Theory

A New Learning Approach for Noise Reduction

Noise is a part of data whether the data is from measurement, experiment or ... A few techniques are suggested for noise reduction to improve the data quality in recent years some of which are based on wavelet, orthogonalization and neural networks. The computational cost of existing methods are more than expected and that's why their application in some cases is not beneficial. In this paper, we suggest a low cost techniques based on special linear algebra structures (tridiagonal systems) to improve the signal quality. In this method, we suggest a tridiagonal model for the noise around the most noisy elements. To update the predicted noise, the algorithm is equipped with a learning/feedback approach. The details are described below and based on presented numerical results this algorithm is successful in computing the noise with lower MSE (mean squared error) in computation time specially when the data size is lower than 5000. Our algorithm is used for low-range noise while for high-range noise it is sufficient to use the presented algorithm in hybrid with moving average. The algorithm is implemented in MATLAB 2019b on a computer with Windows 11 having 8GB RAM. It is then tested over many randomly generated experiments. The numerical results confirm the efficiency of presented algorithm in most cases in comparison with existing methods.Comment: 7 pages, 3 figures, 2 table