Detailed Policy Research Articles

Policy Learning for Nonlinear Model Predictive Control With Application to USVs

The unaffordable computation load of nonlinear model predictive control (NMPC) has prevented it for being used in robots with high sampling rates for decades. This paper is concerned with the policy learning problem for nonlinear MPC with system constraints, where the nonlinear MPC policy is learned offline and deployed online to resolve the computational complexity issue. A deep neural networks (DNN) based policy learning MPC (PL-MPC) method is proposed to avoid solving nonlinear optimal control problems online. The detailed policy learning method is developed and the PL-MPC algorithm is designed. The strategy to ensure the practical feasibility of policy implementation is proposed, and it is theoretically proved that the closed-loop system under the proposed method is asymptotically stable in probability. In addition, we apply the PL-MPC algorithm successfully to the motion control of unmanned surface vehicles (USVs). It is shown that the proposed algorithm can be implemented at a sampling rate up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{5}~Hz$</tex-math></inline-formula> with high-precision motion control.

Detecting the horizontal/vertical price relationship patterns in the global oil industry chain through network analysis

The investigation of price relationship patterns within the horizontal regional and vertical industry chain domains of oil market represents a crucial yet under-researched area. This study tackles the inherent complexities in identifying these patterns, arising from three key challenges: the presence of numerous downstream petrochemical products, the interconnectedness of oil product prices across two domains, and the existence of price influence loop. To address these challenges, this study selected 51 oil products from various regions and different segments of oil industry chain, and calculated and tested their price lead-lag relationships. Subsequently, we established and analyzed the price lead-lag relationship networks within two domains. Furthermore, we expanded network topological structure analysis from a single domain to encompass both domains. Finally, employing the network motif analysis method, we successfully detected the price relationship patterns, taking into consideration the intricate nature of price influence loops. Our findings illuminate the general characteristics of the oil market within two domains but also shed light on previous ignored price lead-lag relationships. The thorough analysis and conclusions drawn from this study offer detailed policy implications to downstream refineries and policy makers.

VILLAGE GOVERNMENT MANAGEMENT ON THE EFFECTIVENESS OF ACHIEVING THE VILLAGE AUTONOMY PROGRAM THROUGH THE PERFORMANCE OF VILLAGE APPARATUSES IN GARUT REGENCY

The village apparatus in the Garut Regency still needs to be fixed. It is suspected that the village autonomy program will be less successful because the management of village governance has yet to be implemented. This study intends to examine the influence of village government management on the effectiveness of regional apparatus in implementing the village autonomy program. Utilizing a survey approach, quantitative and descriptive analysis is the research methodology used. The research target group was 421 villages included in the village administration in Garut Regency, with 81 villages being the sample of 81 respondents. Statistical analysis method using path analysis is the applied data analysis technique. Based on the discussion results, the village government's management needs to disseminate development to the community optimally. The performance of the village apparatus could have been better for the independence of the apparatus in carrying out its duties and responsibilities and the effectiveness of the achievement of the village autonomy program. The findings of the research results are suggested to the government of Garut Regency to increase the effectiveness of achieving the village autonomy program to make clear and detailed village strategic policy formulations.

Reinforcement learning for intensive care medicine: actionable clinical insights from novel approaches to reward shaping and off-policy model evaluation

BackgroundReinforcement learning (RL) holds great promise for intensive care medicine given the abundant availability of data and frequent sequential decision-making. But despite the emergence of promising algorithms, RL driven bedside clinical decision support is still far from reality. Major challenges include trust and safety. To help address these issues, we introduce cross off-policy evaluation and policy restriction and show how detailed policy analysis may increase clinical interpretability. As an example, we apply these in the setting of RL to optimise ventilator settings in intubated covid-19 patients.MethodsWith data from the Dutch ICU Data Warehouse and using an exhaustive hyperparameter grid search, we identified an optimal set of Dueling Double-Deep Q Network RL models. The state space comprised ventilator, medication, and clinical data. The action space focused on positive end-expiratory pressure (peep) and fraction of inspired oxygen (FiO2) concentration. We used gas exchange indices as interim rewards, and mortality and state duration as final rewards. We designed a novel evaluation method called cross off-policy evaluation (OPE) to assess the efficacy of models under varying weightings between the interim and terminal reward components. In addition, we implemented policy restriction to prevent potentially hazardous model actions. We introduce delta-Q to compare physician versus policy action quality and in-depth policy inspection using visualisations.ResultsWe created trajectories for 1118 intensive care unit (ICU) admissions and trained 69,120 models using 8 model architectures with 128 hyperparameter combinations. For each model, policy restrictions were applied. In the first evaluation step, 17,182/138,240 policies had good performance, but cross-OPE revealed suboptimal performance for 44% of those by varying the reward function used for evaluation. Clinical policy inspection facilitated assessment of action decisions for individual patients, including identification of action space regions that may benefit most from optimisation.ConclusionCross-OPE can serve as a robust evaluation framework for safe RL model implementation by identifying policies with good generalisability. Policy restriction helps prevent potentially unsafe model recommendations. Finally, the novel delta-Q metric can be used to operationalise RL models in clinical practice. Our findings offer a promising pathway towards application of RL in intensive care medicine and beyond.

Grey prediction of carbon emission and carbon peak in several developing countries

The carbon emissions in BRICS countries (Brazil, Russia, India, China and South Africa) account for nearly half of global carbon emissions. To explore the future carbon emissions in BRICS countries and the carbon peak in China and India, the grey Gompertz model with new information priority accumulation is proposed. Intelligent algorithms are used in the parameter optimization. The new model not only increases the influence weight of new information on the predicted results, but also changes the predicted trend of traditional grey prediction model. The effectiveness of the new model for the carbon emission forecast is verified through the known data set. According to the predicted results, the carbon emissions in Russia, Brazil, South Africa tend to stabilize over the long term. The carbon emissions in China and India are rising slowly. China will achieve the carbon peak in 2029 with 10.2 billion tons of carbon emissions. India will not achieve the carbon peak by 2030. The current situations of the carbon emissions in BRICS countries are analyzed. It is concluded that the energy structure, industrial development and the urbanization need to be paid attention to. Detailed policies and suggestions are given in the fourth section. The above research results indicate that the new model can predict the limit value of the carbon emission. The predicted results can provide data support for the policy formulation in carbon reduction.

A critical appraisal of education policy practices ensuring free and compulsory school education: Insights from Nepal

Education policy plays a pivotal role in ensuring access to free and compulsory education for all children, fostering national development and reducing social disparities. This critical appraisal examined the school education policy practices in Nepal that aimed at achieving the goal of free and compulsory school education at basic level. For this, descriptive and analytical research designs were applied for analyzing the education policy provisions. The education policies practices were observed through a field survey in which the information was gathered from schools through the distribution of questionnaires to students, teachers, and guardians, as well as interviews with head teachers and focus group discussions among policy experts and local leaders. The investigation led to the provision of free and compulsory education in basic education. While there was good achievement in teacher training and development, there was insufficient support for teachers-guardians interaction programs. The research also offers suggestions for preparing detailed policy implementation guidelines, including an education plan for policy execution. Nepal has made significant progress in school education in terms of providing free and compulsory school education. This paper has provided a critical appraisal of these policies and practices drawing on evidence from Nepal. By analyzing the evidence and outcomes, this study evaluates the effectiveness, challenges and potential areas for improvement in the Nepalese education system.

Contents analysis of telemedicine applications in South Korea: An analysis of possibility of inducing selective or unnecessary medical care.

The use of telemedicine and telehealth has rapidly increased since the start of the COVID-19 pandemic, however, could lead to unnecessary medical service. This study analyzes the contents of telemedicine apps (applications) in South Korea to investigate the use of telemedicine for selective or unnecessary medical treatments and the presence of advertising for the hospital. This study analyzed 49 telemedicine mobile apps in Korea; a content analysis of the apps' features and quality using a Mobile Application Rating Scale was done. The study analyzed 49 mobile telemedicine apps and found that 65.3% of the apps provide immediate telemedicine service without reservations, with an average rating of 4.35. 87% of the apps offered selective care, but the overall quality of the apps was low, with an average total quality score of 3.27. 73.9% of the apps were able to provide selective care for alopecia or morning-after pill prescription, 65.2% of the apps for weight loss, and 52.2% of the apps for erectile dysfunction, with the potential to encourage medical inducement or abuse. Therefore, before introducing telemedicine, it is helpful to prevent the possibility of abuse of telemedicine by establishing detailed policies for methods and scope of telemedicine.

Assessing the interplay between political globalization, social globalization, democracy, militarization, and sustainable development: evidence from G-7 economies.

Sustainable development can act as a catalyst in boosting environmental sustainability and human welfare by alleviating unsustainable production and consumptionpractices. Political globalization emerges as indispensable in increasing global environmental governance. In addition, social globalization, militarization, and democracy can also affect sustainable development. In light of the overlooked impacts of these crucial variables on sustainable development within prior research studies, this study investigates the heterogeneous effects of political globalization, militarization, social globalization, and democracy on sustainable development from 1990 to 2019in the G-7 panel. The results obtained from the application of the methods of moment quantile regressions reveal that a one-percentage-point increase in political globalization yields a significant enhancement in sustainable development, ranging from 0.015 to 0.017% across the 10th to 90th quantiles. Contrarily, sustainable development exhibits a decline within the range of 0.025 to 0.028% across the 10th to 90th quantiles, on account of a 1% increase in social globalization. Likewise, militarization hampers sustainable development with a slightly increasing effect from the 10th to 90th quantiles. Gross fixed capital formation decreases sustainable development while the relationship between democracy and sustainable development indicates a negative correlation, which has not achieved statistical significance across the majority of quantiles. These novel outcomes are also verified by using some other regression tests. Subsequently, a detailed policy framework is presented for the purpose of fostering sustainable growth within the G-7 group.

Evaluating engagement with equity in Canadian provincial and territorial primary care policies: Results of a jurisdictional scan

Equitable access to primary care is essential to achieving more equitable health outcomes, yet evidence suggests that structurally marginalized populations are less likely to have benefited from varied primary care reforms in Canada. Our objective is to determine how equity is incorporated in public primary care policy and strategy documents across Canada. We conducted string term and snowball searches for provincial/territorial primary care policy documents published between 01 January 2018 and 30 June 2022, extracted the policy objective, and applied a rubric to evaluate each document's engagement with equity. We performed content analysis of the documents which acknowledged inequities and articulated a related policy response. Of the 224 identified documents that discussed primary care policy: 63 (28 %) identified one or more structurally marginalized group(s) experiencing inequities related to primary care, 64 (29 %) identified a structurally marginalized group and articulated a policy response, and 16 (7 %) articulated a detailed policy response to address inequities. Even where policy responses were articulated, in most cases these did not directly address the acknowledged inequities. The absence of measurable goals, meaningful community consultation, and tenuous connections between the policy response and inequities mentioned may help explain persistent inequities in primary care across Canada.

Determinants of Chinese Exports of Metal Manufactures and Discussion on Export Potential During Pandemic: Based on Trade Gravity Model

The year 2020 was the beginning of the Covid-19 pandemic, and the turning point for the industries poorly affected by the unexpected conditions. This paper focused on the impact of a range of factors on China’s exports of metal manufacture in 2020, in particular the impact of the COVID-19 pandemic on it. Using cross-sectional data, the paper collected relevant data for 151 countries in 2020. We applied trade gravity model by considering important parameters impacting on China’s exports of metal manufacture such as GDP, distance, population, the total number of cases of COVID-19, employment rate, economic degrees of freedom, the political environment and the free trade agreement between China and other countries. Then, by collecting the data set for 2021, this paper compares the models for 2020 and 2021 with the aim of making a comparison of the impact of the pandemic on China’s exports of metal manufactures. We also do some analysis about the trend of the effect of COVID-19 in the future. The paper continues with calculation of China’s export potential for metal manufacture for its 151 partner countries including 54 of them are at the Trade Potential Untapped level, 38 at the Trade Potential Growing level and 59 at the Trade Potential Mature level based on gravity model. This paper also offers different detailed trade policies for the distinct levels of trade potential in the light of the impact of the COVID-19.

Global evidence on the economic effects of disease suppression during COVID-19

Governments around the world attempted to suppress the spread of COVID-19 using restrictions on social and economic activity. This study presents the first global analysis of job and income losses associated with those restrictions, using Gallup World Poll data from 321,000 randomly selected adults in 117 countries from July 2020 to March 2021. Nearly half of the world’s adult population lost income because of COVID-19, according to our estimates, and this outcome and related measures of economic harm—such as income loss—are strongly associated with lower subjective well-being, financial hardship, and self-reported loss of subjective well-being. Our primary analysis uses a multilevel model with country and month-year levels, so we can simultaneously test for significant associations between both individual demographic predictors of harm and time-varying country-level predictors. We find that an increase of one-standard deviation in policy stringency, averaged up to the time of the survey date, predicts a 0.37 std increase in an index of economic harm (95% CI 0.24–0.51) and a 14.2 percentage point (95% CI 8.3–20.1 ppt) increase in the share of workers experiencing job loss. Similar effect sizes are found comparing stringency levels between top and bottom-quintile countries. Workers with lower-socioeconomic status—measured by within-country income rank or education—were much more likely to report harm linked to the pandemic than those with tertiary education or relatively high incomes. The gradient between harm and stringency is much steeper for workers at the bottom quintiles of the household income distribution than it is for those at the top, which we show with interaction models. Socioeconomic status is unrelated to harm where stringency is low, but highly and negatively associated with harm where it is high. Our detailed policy analysis reveals that school closings, stay-at-home orders, and other economic restrictions were strongly associated with economic harm, but other non-pharmaceutical interventions—such as contact tracing, mass testing, and protections for the elderly were not.

Empowering sustainability practices through energy transition: The role of digital economy and technological innovation among BRICS economies

AbstractAchieving sustainable development targets requires major changes in the existing economic structure and a transition from a pollution‐intensive energy system to a clean one. The role of the digital economy (DE) in this regard has received much attention in recent eras. However, there is little literature investigating the relationship between the DE and the energy transition in the presence of technological innovation. This study's aim, grounded in the sustainability agenda, is to explore the possible impact of DE and technological innovation on the energy transition for the BRICS nations from 2003 to 2021. Using the most recent Moments Quantile Regression method, the results reveal that the DE can contribute significantly to achieving SDG‐7 by promoting energy transition. While technological innovation does not significantly influence the energy transition. Moreover, economic development is hindering the energy transition in the BRICS countries. Several alternative estimation methods have been applied to confirm the robustness of the results. The empirical results conclude that governments should build digital infrastructure and encourage innovation in the energy sector by supporting energy‐related patents. The detailed policy implications are presented in the study.

A data center expansion scheme considering net-zero carbon operation: Optimization of geographical location, on-site renewable utilization and green certificate purchase

Recently, more and more global attention has been paid to data centers’ energy consumption and climate impact. Serving as the backbone of the digital world, the energy and carbon-intensive data centers have to find a green expansion way to fulfill their obligations in building a carbon-neutral society. Therefore, this paper proposes a net-zero carbon operation oriented data center expansion scheme for the central government to formulate incentive policies. The economic expansion model minimizes newly established data centers’ investment and electricity consumption costs. Geographical location, on-site renewable utilization, and green certificate purchase are integrated and considered to achieve net-zero carbon operation by reducing total electricity consumption, increasing green power consumption, and offsetting inevitable carbon emissions. A case study in China is conducted, and results under different geographical location scenarios, power supply mix scenarios, and green certificates market scenarios are analyzed and compared. It is found that the zero-carbon operation of new data centers mainly relies on clean main-grid power, but a more decentralized layout and a provincial green certificate market can increase the contribution of on-site renewable energy. Lastly, four detailed policy implications for stimulating China’s data center expansion are discussed.

Archiving Archaeological Data: Understanding Current Practice through Case Studies from Established Repositories

The workflows examined are representative of operational workflows around data assessment and data removal that are common to all data repositories, as well as specific strategies of dealing with Microsoft Access Databases, a commonly deposited file format used by archaeologists for assessment and analysis. The paper will present each workflow as a succinct case study with an emphasis on why the decisions have been made to follow a certain method. This will be followed by a discussion on similarities and differences in approach and implementation so as to bring together core recommendations that can be used by others currently building or scoping the development of new digital repositories in the archaeological sector. The paper will link out to copies of the detailed workflows and policies to be deposited within COPTR, a finding aid for helping find tools to deal with practical data management issues.

Managing the regional and local recovery of Ukraine after the war

The article discusses the problems of managing Ukraine’s economic recovery after the Russian-Ukrainian war, which should be taken into account when planning the process of regional and local recovery and the solution of which will help economic growth. The author outlines the results of the decentralization and regional development reforms implemented in Ukraine after 2014: development of a detailed policy, management, and financing systems for regional development; growth of financing for regional and local development; empowerment of regional and local authorities; improvement of the quality of administrative and social services; creation of various policy coordination bodies at the national, regional, and local levels, e.g., regional development agencies. The article analyzes the following development problems and territorial imbalances: mechanisms and practices of financing regional development in Ukraine (need to be strengthened, as their deficiencies significantly affect investment results), the capacity of regions and territorial communities (its strengthening is crucial for effective promotion of post-war recovery), the lack of a clear division of tasks and responsibilities between levels of government (a major problem for the effectiveness of the process of Ukraine’s recovery after the war), poor coordination between national, regional, and local authorities (limits the efficiency and performance at different levels of government). The author suggests implementing the following steps to ensure Ukraine’s recovery after the war, taking into account the peculiarities of regional and local development: to continue the reforms of regional development and decentralization; to promote the exchange of experience between Ukraine and other countries; to ensure that informed, factual, and evidence-based decisions on reconstruction and recovery are made at the regional and local levels; to create mechanisms to prevent corruption in the process of using recovery funds by local authorities; involve regions and territorial communities in the development of immediate recovery schemes and long-term development strategies; to introduce mechanisms at the national and local levels to support the transparent use of funding for Ukraine’s recovery by regional and local governments; to limit the number of regional and local recovery funds to avoid fragmentation of investment costs; to assist (with the support of international partners) regions and territorial communities to strengthen capacity and develop expertise in areas important for the post-war recovery period; to build the technical capacity of authorities at all levels to create, analyze, and disseminate geographically disaggregated socio-economic, demographic, and welfare data. Special attention is paid to the need to simultaneously address urgent recovery tasks and long-term development objectives, as well as to ensure a strong and inclusive recovery, taking into account existing territorial imbalances and governance problems. It will be a feature of Ukraine’s post-war recovery.

European Union’s role as a Global Actor: Shifting focus from Regionalism to International Politics

The emergence of European Union in global politics, addressing pressing issues throughout the world while also championing causes like social justice, individual liberties, and the rule of law. This paper analyses how the European Union’s foreign policy stance affects international relations. Discussions focus on the EEAS and the potential for EU peace missions to grow. The research paper aims to highlight the efforts of EU to protect the peace and stresses the EU's unyielding dedication to preserving calm, preventing conflict, and responding to disasters. This article examines the European Union’s Common Security and Defense Policy in great detail, including the many missions and initiatives the EU has taken to show its proactive engagement in international problems. In this article, we take a look at the European Union's (EU) efforts to improve international norms and safeguard human rights via programs including humanitarian assistance, diplomatic initiatives, and the Common Foreign and Security Policy. The European Union's (EU) dedication to promoting and protecting human rights internationally has been proved via its funding of considerable humanitarian aid, participation in United Nations (UN) programs, and punishment of human rights abusers. It is also notable that EU’s involvement with countries in the Pacific, Africa, and the Caribbean are based on EU's dedication to trade-based development in those regions. The paper also analyses European Union (EU) foreign policy, contrasting the EU's normative stance with the realism paradigm supported by the United States government. It looks at the European Union's role as a regional power on the global arena and how it may work with the United States and other big states to accomplish its own foreign policy goals. Using the European Union's (EU) engagement in the Israel-Palestine conflict as a case study, this paper aims to show how the EU handles complex geopolitical difficulties while remaining true to its core values and promoting the idea of two nations. In the end, the European Union is engaged in a wide variety of global political endeavors, such as peacekeeping, humanitarian aid, and the promotion of progressive principles. Its standing in the international world has improved thanks to its work in international organizations and efforts to address global problems.

Assessing an Indonesian Credit Union’s Internal Control Using COSO ERM Framework: A Case Study at Credit Union Kridha Rahardja

COSO ERM framework has been widely used for assessing the quality of internal control in many forprofit companies. However, there is still limited application of COSO ERM Framework for non-profit organizations and social enterprises with dual objectives like credit unions. This research evaluates how effective and comprehensive the implementation of internal controls is within a Credit Union in Indonesia, a member-based social enterprise offering financial services to middle-low-income groups. This is a collaborative case study of the researcher and the practitioners of the credit union. Participants shared their perspectives through questionnaire feedback, interviews, and focus group discussions, to examine the control activities within the organization and identify risks that may impact the organization’s goals. The findings suggest a critical demand for forming an operational manual with detailed structures and policies. Furthermore, the sense of loyalty is the key to enhancing members’ participation in various activities within the organization.

Direct transfer policies for the poor

We discuss various anti-poverty policies which involve direct transfer policies for the poor, focusing on their different dimensions—namely the size and time sequence of the transfers, whether it is cash or in kind, any conditionality involved, whether they are means-tested. We argue that their pros and cons depend on what is the underlying aspect of poverty that the policy is aiming to address, namely what is the cause of it, what is the time horizon, what is the social objective, and what, if any, limitations on state capacity might be present. We illustrate the issues involved by discussing two transfer policies in detail, a rural asset transfer programme in Bangladesh and a hypothetical universal income support programme in India—and highlight the dual nature of such policies as both redistributive and potentially productive investments. We conclude by discussing the potential complementarities between different types of anti-poverty policies.

Statistical analysis of mental influencing factors for anxiety and depression of rural and urban freshmen.

The freshmen stage is a high incidence period for psychological issues. With the increasing gap between urban and rural areas in China, the mental problems of rural freshmen are more prominent in recent years due to the huge contrast of campus life with their growth environment and other reasons. The concern for the mental well-being of both rural and urban freshman students prompted our comprehensive five-year study (2018-2022) on psychological issues in a group of 12,564 first-year students from dozens of public universities in Shandong province. The investigation employed PPS (probability proportional to size) sampling and was conducted near the the end of the first semester. Using the data gathered, we analyzed and compared the indicators of psychological problems in rural and urban freshmen by Duncan's Multiple Range Test. We also conducted a canonical correlation analysis and pathway analysis to examine the psychological factors that contribute to anxiety and depression in both rural and urban freshmen. According to the findings, rural freshmen exhibit significantly higher levels of anxiety and depression than their urban counterparts. Inferiority, obsession, and internet addiction were identified as the primary influencing factors of anxiety and depression in both rural and urban freshmen. Social phobia was found to be a significant influencing factor for anxiety in rural freshmen, while bigotry was identified as a specific influencing factor for urban freshmen. Furthermore, the results of the path analysis suggest that anxiety plays a crucial role as a mediating factor between the main influencing factors and depression. These results substantially extend former research in this area and have important implications for the development of effective intervention strategies to address anxiety and depression. According to these results, policymakers should assess and intervene of anxiety and depression as a whole, and provide mental health education according to main effect factors of freshmen from rural and urban areas. Detailed policy recommendations are in discussion and conclusion.

Identifying farmers' response to changes in marginal and average subsidies using deep learning

AbstractMuch of the developed world has adopted substantial, complex agricultural subsidy schemes in an attempt to produce desired rural livelihood and environmental outcomes. Understanding how farmers adjust their production activity in response to farm subsidies is crucial for setting optimal agricultural policy. Whereas standard economic theory suggests that farmers largely adjust production levels in response to prices and marginal subsidy rates, recent work in consumer behavior suggests that average (dis‐)incentives may play a relevant role. We use a unique panel covering all farms applying for subsidies in Norway and a flexible deep‐learning method to exploit kinks in the subsidy scheme to answer whether farmers respond more to average or marginal subsidies. In contrast to the standard economic theory of production, we find suggestive empirical evidence that farmers respond more to changes in average payments than to changes in marginal payments. We anticipate that our findings on the relevance of average payment levels for farmers' decision making may inspire further theoretical and empirical inquiries into agricultural policy effects. The study also highlights how novel deep‐learning tools can be applied for detailed policy analysis and what advantages and challenges come with it. We believe that this approach has substantial potential for analysts and policymakers to evaluate and predict the impacts of policy options.