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Health Sector Evolution Plan (HSEP) is known as the biggest and most comprehensive reform in Iran’s health system. One of the goals of HSEP is to reduce inequity in the healthcare financing. The purpose of this paper is to demonstrate HSEP agenda setting from the perspective of equity in healthcare financing (EHCF) using the multiple streams model.

This qualitative study was conducted by 26 documents review and analysis, and 30 semi-structured interview with Iranian key informants in the field of HSEP that were selected based on purposeful and snowball sampling method. Data were collected using a researcher-made checklist based on the goals. All audio-taped interviews were transcribed and analyzed thematically. Data management and analysis were performed using the framework analysis in MAXQDA software.

The framework analysis identified 12 complementary sub-themes totally. Problem stream included four sub-themes (high share of Out Of Pocket, high index of catastrophic health expenditures, low EHCF index, and inappropriate economic state and sanctions). Focus on EHCF in general policies of the Iran World Health Organization’s report in 2000, the Targeted Subsidies Law and emphasis on equalizing healthcare financing in the Fourth and Fifth Development Plan were considered as policy stream sub-themes. Finally, political stream showed four sub-themes including strong support from the Minister of Health for HSEP, mass media, the pressure of WHO and people’s request to reduce health costs.

The limitations of the present study included paying attention to one package (evolution in the treatment sector) of three health packages to assess EHCF, as well as the lack of similar national and international evidence in implementation framework.

The results of this study can be used to analyze other health sector reforms around the word and can help the formulation and implementation of most practical reforms, especially in field of health system financing.

This study gives a holistic view about health system policy setting that can be used for understanding policy-making streams to population.

This is the first study that has examined HSEP (the biggest health sector reform in Iran) from the perspective of agenda setting. In addition, using the popular and well-known Kingdon’s model to explain HSEP agenda setting is one of the strengths of this study. Furthermore, taking advantage of a wide range of related views by including highly informed people increased the strength of the results of the study. In addition, the short interval between the interview and reviewing the results on reforms reduced the recall bias of the participants in the study.

The purpose of this paper is to develop a monitoring multiple-stream processes control chart with a finite mixture of probability distributions in the manufacture industry.

Data were collected during production of a wheat-based dough in a food industry and the control charts were developed with these steps: to collect the master sample from different production batches; to verify, by graphical methods, the quantity and the characterization of the number of mixing probability distributions in the production batch; to adjust the theoretical model of probability distribution of each subpopulation in the production batch; to make a statistical model considering the mixture distribution of probability and assuming that the statistical parameters are unknown; to determine control limits; and to compare the mixture chart with traditional control chart.

A graph was developed for monitoring a multi-stream process composed by some parameters considered in its calculation with similar efficiency to the traditional control chart.

The control chart can be an efficient tool for customers that receive product batches continuously from a supplier and need to monitor statistically the critical quality parameters.

The Orphan Drug Act has provided the pharmaceutical industry with incentives to research and develop drugs for orphan diseases: rare diseases with little profit potential. It is considered very successful legislation by legal scholars, the Food and Drug Administration (FDA), and orphan drug activists. The policy process of the Act provides an important model of the policy process for future incentive-based pharmaceutical legislation. The purpose of this paper is to summarize the important incentives of the Act and the historical events leading up to the Act. The paper applies three different theoretical models of the public policy process to understand the emergence of the Orphan Drug Act: Kingdon’s Multiple Streams Model, the Advocacy Coalition Framework, and Social Constructionism Theory. The paper then synthesizes the public policy process lessons from each perspective and provides four recommendations for other social activists seeking to propel incentive-based pharmaceutical legislation for under-researched diseases.

The author analyzes the history of the Orphan Drug Act based on publicly available scholarly research, government documents, and interest group publications. The author then applies three public policy theories to the history of the Orphan Drug Act to explain the emergence of the Act and to extract policy process lessons for future disease activists.

Regardless of which theoretical perspective the Orphan Drug Act is analyzed from, some common themes of the policy process emerge. First, focussing events are instrumental in capturing the public’s sympathy and Congress’s attention. Second, in its activities and proposed legislation, a coalition should provide a role for all relevant and important actors. Third, the target groups of the legislation were construed positively, increasing the pressure for Congressmen to pass some kind of bill. Finally, the proper construction of “the problem” is instrumental to passing effective legislation as a “solution.”

The Orphan Drug Act is widely considered successful incentive-based pharmaceutical legislation. However, because it was originally passed in 1983 and has not had public attention since the early 1990s (when it was amended), it has rarely been written about in recent years. However, its lessons are still highly relevant to policy activists, especially disease activists. Furthermore, existing articles focus on the impact of the legislation and ways to amend it, rather than on the passage of the Act.

This chapter explores two comparative longitudinal cases studies involving policy entrepreneurs inside and outside government in Taiwan. From 2003 to 2007, the Ministry of Education (MOE) in Taiwan played the conventional role of policy entrepreneur to initiate the “University Corporation Project.” Through this project, the MOE sought to transform all national universities in Taiwan into independent entities, gaining them more autonomy and increasing their accountability as well. From 2008 to 2014, as a policy entrepreneur outside the government, National Cheng Kung University (NCKU) took the lead and proposed the “University Autonomous Governance Project.” This project sought an alternative solution based on public universities’ needs to improve university autonomy and accountability.

The method undertaken in this study includes document analysis and participants’ observation. First, both policy entrepreneurs adopted the strategy of power sharing, but the effectiveness of the strategy is determined by the interaction between policy entrepreneurs and stakeholders. Moreover, facing a multiple-principals condition in both cases, both policy entrepreneurs should negotiated with or compete with other potential agenda competitors. Those findings will be a detailed roadmap for policy makers in East Asia once they plan to initiate policy entrepreneurship in their countries.

The aim of continuous learning is to obtain and fine-tune information gradually without removing the already existing information. Many conventional approaches in streaming data classification assume that all arrived new data is completely labeled. To regularize Neural Networks (NNs) by merging side information like user-provided labels or pair-wise constraints, incremental semi-supervised learning models need to be introduced. However, they are hard to implement, specifically in non-stationary environments because of the efficiency and sensitivity of such algorithms to parameters. The periodic update and maintenance of the decision method is the significant challenge in incremental algorithms whenever the new data arrives.

Hence, this paper plans to develop the meta-learning model for handling continuous or streaming data. Initially, the data pertain to continuous behavior is gathered from diverse benchmark source. Further, the classification of the data is performed by the Recurrent Neural Network (RNN), in which testing weight is adjusted or optimized by the new meta-heuristic algorithm. Here, the weight is updated for reducing the error difference between the target and the measured data when new data is given for testing. The optimized weight updated testing is performed by evaluating the concept-drift and classification accuracy. The new continuous learning by RNN is accomplished by the improved Opposition-based Novel Updating Spotted Hyena Optimization (ONU-SHO). Finally, the experiments with different datasets show that the proposed learning is improved over the conventional models.

From the analysis, the accuracy of the ONU-SHO based RNN (ONU-SHO-RNN) was 10.1% advanced than Decision Tree (DT), 7.6% advanced than Naive Bayes (NB), 7.4% advanced than k-nearest neighbors (KNN), 2.5% advanced than Support Vector Machine (SVM) 9.3% advanced than NN, and 10.6% advanced than RNN. Hence, it is confirmed that the ONU-SHO algorithm is performing well for acquiring the best data stream classification.

This paper introduces a novel meta-learning model using Opposition-based Novel Updating Spotted Hyena Optimization (ONU-SHO)-based Recurrent Neural Network (RNN) for handling continuous or streaming data. This is the first work utilizes a novel meta-learning model using Opposition-based Novel Updating Spotted Hyena Optimization (ONU-SHO)-based Recurrent Neural Network (RNN) for handling continuous or streaming data.

As demand for access to colleges and universities prompts higher education systems for creative and efficient solutions, we examine technology-centric approaches to education delivery and their implications for policy, student outcomes, and resource allocation. Our work is framed by Kingdon’s adapted multiple streams theory of national policymaking. However, the real elephant in the room may be the skyrocketing costs of administration that may need wrangling before resources can be directed to the future potential savings obtained through developing infrastructure for, and delivery of, tech-centric teaching approaches. We provide examples and strategies, policy implications, and recommendations for research and practice.

The purpose of this paper is to revisit the growth mechanism of Indian sugar industry by deploying quantitative and qualitative metaphors.

The research paper has been composed through comprehensive primary research survey using a structured questionnaire, and qualitative discussion following semi- structured interviews with industry professionals on emerging issues across the whole value chain of sugar industry. Respondents regarding primary survey were selected using the purposive sampling, and this collected quantitative information has been verified on the lenses of multiple stream modelling (MSM).

To support the data analysis, MSM – a policy-making framework has been developed which found that government being a central construct exerts a profound presence across whole value chain; in suppliers’ mechanism, marketing of sugar and sugar mills’ infrastructural expansions. Nationwide uniformity in sugar policy instead of states’ monopolistic policies, rational and mutual benefits-based decisions collectively by the government, mills management and sugarcane growers, and diversification in production processes are enumerated as the proposed solutions against the chronical industry problems.

This study enriches extant Asian sugar industry literature. For policymakers, the proposed results should be of help in identifying specific policies to support the competitiveness of local systems and individual manufacturing companies in the Indian sugar industry suggesting that the development of growth mechanisms can contribute simultaneously to improve the financial, market and operational performance of both individual firms and supply chains.

Cyclicality in production, rising sugarcane farmers’ problems and resulting severe financial distress of mills are some of the topical issues of Indian sugar industry, and the study has explored these issues factually, quantitatively and qualitatively in proximity of industry professionals and described in this depository with the help of document analysis.

The discontinuous Galerkin finite element method (DGFEM) is very suited for realizing high order resolution approximations on unstructured grids for calculating the hyperbolic conservation law. However, it requires a significant amount of computing resources. Therefore, this paper aims to investigate how to solve the Euler equations in parallel systems and improve the parallel performance.

Discontinuous Galerkin discretization is used for the compressible inviscid Euler equations. The multi-level domain decomposition strategy was used to deal with the computational grids and ensure the calculation load balancing. The total variation diminishing (TVD) Runge–Kutta (RK) scheme coupled with the multigrid strategy was employed to further improve parallel efficiency. Moreover, the Newton Block Gauss–Seidel (GS) method was adopted to accelerate convergence and improve the iteration efficiency.

Numerical experiments were implemented for the compressible inviscid flow problems around NACA0012 airfoil, over M6 wing and DLR-F6 configuration. The parallel acceleration is near to a linear convergence. The results indicate that the present parallel algorithm can reduce computational time significantly and allocate memory reasonably, which has high parallel efficiency and speedup, and it is well-suited to large-scale scientific computational problems on multiple instruction stream multiple data stream model.

The parallel DGFEM coupled with TVD RK and the Newton Block GS methods was presented for hyperbolic conservation law on unstructured meshes.

The purpose of this paper is to introduce the HEPS project (Healthy Eating and Physical Activity in Schools) and discuss initial steps of the project implementation within EU countries. On the basis of the Health Promoting School approach as a conceptual foundation for the project, HEPS aimed at developing and implementing an effective tool for supporting the development of national policies on healthy eating and physical activity in schools across Europe. For this purpose, a package of publications (HEPS Toolkit) was produced and disseminated within the Schools for Health in Europe (SHE) network.

An initial implementation survey was carried out with national coordinators of the SHE network (n=24).

Results indicate that more than half of the respondents were familiar with and disseminated the HEPS Toolkit to relevant stakeholders at national, regional and local levels. However a number of problems and barriers in the implementation were encountered, such as lack of support and resources, existence of competing programmes, and frequent education and health reforms.

The findings are discussed against two models of implementation and a few recommendations are suggested for optimizing the further implementation of this, and other similar projects.

THE HEPS toolkit is the first attempt to support all EU member states in the development and implementation of a national policy on healthy eating and physical activity in schools. The involvement of the national coordinators of a well established European network of school health can be seen as an innovative way to implement and disseminate the project outcomes.

This paper aims to examine policy innovation among street-level bureaucrats at low-threshold services to people who use drugs during the COVID-19 pandemic in Denmark.

This paper builds on two research projects conducted during the first pandemic lockdown in Denmark. The first is a case study of how COVID-19 impacted on people who use drugs (PWUD) and services for PWUD at the open drug scene in the neighborhood of Vesterbro in Copenhagen. The second is an ethnographic study of how users of services at the intersection of drug use and homelessness were impacted by lockdown.

Drawing on Kingdon’s “multiple policy streams” approach, this study shows how lockdown opened a “policy window” for innovating services to people who use drugs. This paper further shows how the pandemic crisis afforded street-level bureaucrats new possibilities for acting as “policy entrepreneurs” in a context where vertical bureaucratic barriers and horizontal cross-sectoral silos temporarily collapsed. Finally, the authors show how this had more lasting effects through the initiation of outreach opioid substitution treatment.

In Denmark, the emergence of a “policy window” for street-level bureaucrats to act as street-level “entrepreneurs” occurred in a context of rapid government response to the pandemic. For crises to act as “policy windows” for innovation depends on strong, preexisting institutional landscapes.

This paper adds to existing literature on policy innovation during COVID-19 in two ways: methodologically by contributing an ethnographically grounded approach to studying policy innovation and theoretically by examining the conditions that allowed policy innovation to occur.