Control Policies Research Articles

The Impact of Assisted Living Organizational Structure and Process Characteristics on Staff Absence During COVID-19

ABSTRACT Quality of care in assisted living communities (ALCs) is important to consumers. The coronavirus disease of 2019 (COVID-19) pandemic and associated emergency policies have posed major challenges on staff recruitment and retention. This study aimed to examine the relationship between organizational characteristics of ALCs in Florida and challenges with staff absence during COVID-19 (N = 129 ALCs). Results indicated that structures (provision of memory care services), processes of care (challenges hiring new staff, staff sent home to comply with precautions, and staff anxiety), and local COVID-19 positivity rate were significantly associated with staff absence due to fear of infection, sickness, or family responsibilities. ALC providers and state regulatory agencies should develop policies and procedures that take these issues into consideration to prepare for future emergencies and disasters. Infection control policies should reflect whether an ALC provides memory care services and inform ways to overcome potential challenges with protocols. Efforts to reduce staff anxiety and disaster-related concerns should also be considered to ensure quality of care during emergencies.

Symmetry and synchrony of bimanual movements are not predicated on interlimb control coupling.

Previous studies suggest that bimanual coordination recruits neural mechanisms that explicitly couple control of the arms, resulting in symmetric kinematics. However, the higher symmetry for actions that require congruous joint motions compared with noncongruous joint motions calls into question the concept of control coupling as a general policy. An alternative view proposes that codependence might emerge from an optimal feedback controller that minimizes control effort and costs in task performance. Support for this view comes from studies comparing conditions in which both hands move a shared or independent virtual objects. Because these studies have mainly focused on congruous bimanual movements, it remains unclear if kinematic symmetry emerges from such control policies. We now examine movements with congruous or noncongruous joint motions (inertially symmetric or asymmetric, respectively) under shared or independent cursors conditions. We reasoned that if a control policy minimizes kinematic differences between limbs, spatiotemporal symmetry should remain relatively unaffected by inertial asymmetries. As shared tasks reportedly elicit greater interlimb codependence, these conditions should elicit higher bilateral covariance regardless of inertial asymmetries. Our results indicate a robust spatiotemporal symmetry only under inertially symmetric conditions, regardless of cursor condition. We simulated bimanual reaching using an optimal feedback controller with and without explicit costs of kinematic asymmetry, finding that only the latter mirrored our empirical data. Our findings support the hypothesis that bimanual control policies do not include kinematic asymmetry as a cost when it is not demanded by task constraints suggesting that kinematic symmetry depends critically on mechanical movement conditions.NEW & NOTEWORTHY Previously, the control coupling hypothesis and task-dependent control hypothesis have been shown to be robust in the bimanually symmetrical movement, but whether the same policy remains robust in the bimanually asymmetrical movement remains unclear. Here, with evidence from empirical and simulation data, we show that a spatiotemporal symmetry between the arms is not predicated on control coupling, but instead it is predicated on the symmetry of mechanical conditions (e.g. limb inertia) between the arms.

Distinct learning, retention, and generalization patterns in de novo learning versus motor adaptation

People correct for movement errors when acquiring new motor skills (de novo learning) or adapting well-known movements (motor adaptation). While de novo learning establishes new control policies, adaptation modifies existing ones, and previous work have distinguished behavioral and underlying brain mechanisms for each motor learning type. However, it is still unclear whether learning in each type interferes with the other. In study 1, we use a within-subjects design where participants train with both 30° visuomotor rotation and mirror reversal perturbations, to compare adaptation and de novo learning respectively. We find no perturbation order effects, and find no evidence for differences in learning rates and asymptotes for both perturbations. Explicit instructions also provide an advantage during early learning in both perturbations. However, mirror reversal learning shows larger inter-participant variability and slower movement initiation. Furthermore, we only observe reach aftereffects following rotation training. In study 2, we incorporate the mirror reversal in a browser-based task, to investigate under-studied de novo learning mechanisms like retention and generalization. Learning persists across three or more days, substantially transfers to the untrained hand, and to targets on both sides of the mirror axis. Our results extend insights for distinguishing motor skill acquisition from adapting well-known movements.

Distributed optimal output synchronization of heterogeneous multiagent systems with communication delays

AbstractThe optimal output synchronization problem of heterogeneous multi‐agent systems (HMASs) with communication delays is studied in this article. In order to compensate for communication delays actively, we employ networked data‐driven predictive control method to predict the agents' outputs. Then the output synchronization issue of HAMSs is transformed into the stabilization issue of the local pseudo systems, and model‐free off‐policy reinforcement learning technique is used to learn optimal control policies of the local systems. Combined predicted output information with optimal control policies, we develop a distributed data‐driven optimal output policy for each follower. Finally, a numerical example is given to show the effectiveness of our results.

Maternal anaemia prevention and control in China: A policy review.

Maternal anaemia is a major public health problem. Developing maternal anaemia prevention and control policies is an important prerequisite for carrying out evidence-based interventions. This articlereviews maternal anaemia prevention and control policies in China, identifies gaps, and provides references for other countries. We examined policies concerning maternal nutrition and other related literature in China, identified through key databases and government websites, and conducted a narrative review of the relevant documentations guided by the Smith Policy-Implementing-Process framework. A total of 65 articles and documents were identified for analysis. We found that Chinese government has committed to reducing maternal anaemia at the policy level, with established objectives and a clear time frame. However, most of policies were not accompanied by operational guidelines, standardized interventions, and vigorous monitoring and evaluation mechanisms, and 85% of the policies don't have quantifiable objectives on anaemia. Maternal anaemia prevention and control services offered in clinical settings were primarily nutrition education and anaemia screening. Population-based interventions such as iron fortification have yet to be scaled up. Furthermore, medical insurance schemes in some regions do not cover anaemia prevention and treatment, and in other regions that offer coverage, the reimbursement rate is low. The number and capacity of health professionals is also limited. Policy changes should focus on the integration of evidence-based interventions into routine antenatal care services and public health service packages, standardization of dosages and provision of iron supplementation, streamline of reimbursement for outpatient expenses, and capacity building of health professionals.

Survey from 61,748 schools in four States of India on sale of tobacco products near schools.

Children form the most vulnerable strata of the society and the tobacco industry is known to target them. Article 16 of the Framework Convention of Tobacco Control (FCTC) calls for prohibition of tobacco sales to and by minors. Although interventions to stop such sales are based on sound science, it is widely acknowledged that many countries find implementation, full of challenges. In India, sales near educational institutions are banned by law, Section 6b of the Cigarettes & Other Tobacco Products Act (COTPA). We conducted a survey of violations in four states [Andhra Pradesh (AP), Karnataka (KA), Meghalaya (ML), Uttar Pradesh (UP)] of India to report the number of violations and to assess if there was an association between the schools with violations and variables such as gender, size, category, location of schools. Schools in these States were asked to report the number of shops selling tobacco within 100 yards on an App circulated to all schools (289,392 in number). Chi-square tests, univariate and multivariate logistic regression performed to find association between schools with violations by Category of School, Size of School, Gender of students and location (Urban/Rural). Responses were received from 61,748 (21.3%) schools of which 16,193 (26.2%) reported violations. It was observed that the percentages of the schools with violations were similar to the prevalence of tobacco usage in the state. Four states AP, KA, ML, UP reported violations 22.2%, 17.5%, 42.9% and 31.4% respectively. On chi-square tests, there was a significant association for the states of KA and ML with regards to variables like size, category, location of schools (p-value <0.001). For AP, all variables were significantly different (p-value <0.001) while for UP variables like size and gender were significant. On logistic regression, there was significant association between the variables like size (>100), category (Upper Primary) and location (urban) for tobacco shops violations in both KA and ML except for the school category that was secondary in ML. While for AP and UP, only size (>100), location (urban) of schools have a significant association with the violations of tobacco shops. Logistic regression of pooled data of four states school size (>100) and school category (primary) and location (urban) had significantly higher association of violation of tobacco shops. This is the first large survey with responses from almost all parts of the four states in India. This study shows significant association with the size, category and location of schools. We anticipate that the lists of schools which have such violations can be used by enforcement agencies to take focused action. Such models will help develop effective tobacco control policies in developing countries with large populations where implementation remains a big challenge.

How does the impact of a two-stage air pollution control policy on air quality different? Evidence from 258 cities in China

Air pollution control has become a core task in the construction of China's “ecological civilization”. From 2013 to 2020, the Chinese government successively implemented two consecutive environmental management policies targeting air pollution, namely the Air Pollution Prevention and Control Action Plan (APPCAP) and the Blue Sky Defense War (BSDW). To compare and analyze the effects of these two consecutive policies on air pollution control and their differences in governance mechanisms, this paper employs daily air pollution data from 258 cities in China from January 2013 to September 2020 for empirical analysis. We examines the direct impact of the two-stage policies on air pollution and explores the impact mechanisms from three aspects: technological effects, structural effects, and scale effects. The results indicate: (1) Both APPCAP and BSDW significantly reduced AQI, PM2.5, PM10, SO2, nitrogen dioxide, and CO. (2) Compared to APPCAP, BSDW had a stronger effect on reducing nitrogen dioxide and managed O3 in coordination. (3) APPCAP did not have significant impacts on technology, scale, and structure effects, whereas BSDW significantly promoted technological innovation and industrial restructuring but significantly suppressed the scale effect. Our work provides new empirical evidence for the policy heterogeneity in air pollution control and offers useful policy implications for improving air quality and coordinated pollution control.

Evaluation of age-structured vaccination strategies forcurbing the disease spread.

Age structure is one of the crucial factors in characterizing the heterogeneous epidemic transmission. Vaccination is regarded as an effective control measure for prevention and control epidemics. Due to the shortage of vaccine capacity during the outbreak of epidemics, how to design vaccination policy has become an urgent issue in suppressing the disease transmission. In this paper, we make an effort to propose an age-structured SVEIHR model with the disease-caused death to take account of dynamics of age-related vaccination policy for better understanding disease spread and control. We present an explicit expression of the basic reproduction number , which determines whether or not the disease persists, and then establish the existence and stability of endemic equilibria under certain conditions. Numerical simulations are illustrated to show that the age-related vaccination policy has a tremendous influence on curbing the disease transmission. Especially, vaccination of people over 65 is better than for people aged 21-65 in terms of rapid eradication of the disease in Italy.

Dynamic departure pushback control at airports: Part A—Linear penalty‐based algorithms and policies

AbstractAirport surface congestion can lead to significantly long taxi‐out times, thus resulting in increased fuel‐burn costs as well as excessive emissions of greenhouse gases. To curtail this undesirable syndrome, in this article, we propose a new penalty‐based dynamic departure pushback control (PDPC) strategy, which employs a linear penalty function dependent not only on the taxiway queue limit but also on the current queue length to ration the pushback frequency at airports, and trades taxiway queueing times with gate‐hold delays to minimize the total operational cost (fuel‐burn and gate‐hold costs). Using data from Beijing Capital International (PEK) airport, four different departure pushback control policies, namely: (i) no‐control (baseline case); (ii) traditional ‐control; (iii) PDPC with a constant taxiway limit; and (iv) PDPC with varying taxiway limits; are compared. Detailed Monte Carlo simulations, which showcase the sensitivity of the total cost function to various problem parameters are presented, and our results indicate that deploying the PDPC policy results in a 42% reduction in total operational costs and a 68% reduction in fuel‐burn (kg) as compared to the baseline case. To analytically reinforce these simulation results, an iterative Markov chain‐based optimization algorithm is also developed to estimate the optimal values of the pushback rate and taxiway queue limit that minimize the total cost function. Such an analytical framework is very useful in the absence of reliable airport data as it only requires estimates of the historical pushback request rates and service times at the taxiway, while yet retaining the capability to closely mirror the simulation results. Our Monte Carlo simulations as well as the Markov chain optimization model validate the strength and impact of the proposed PDPC policy, and demonstrate its practical efficacy in reducing airport surface congestion when applied using data from PEK airport.

Analyzing the Relationship Between COVID-19 Susceptibility and Blood Group Variations: A Comprehensive Investigation into the Impact of ABO Blood Types on the Incidence, Severity, and Clinical Outcomes of the Disease

Background: The covid-19 pandemic, originating from a new strain of coronavirus (SARS-CoV-2), is of concern to the global health arena as no crisis comparable to this has happened in the past. The investigation of not only the genetic components which may predispose for such a disease but also determine the severity of the illness has turned into a pressing research issue in modern days. Although it is desirable for the formulation of effective community health policy which provide tailor-made solutions concerning treatments, it is important that people have a clear understanding of the role played by blood type differences in this regard.&#x0D; Methodology: The research was done at Baghdad Medical City Hospital during the period of June and August of 2021 using the patients with verified COVID-19 cases as their base. The data contained not only demographic information but also a blood type, disorder severity level, as well as the details were about the procedure. Various statistics organizations, include but not limited to the Pearson correlation, Chi-square and data visualization were applied using SPSS to establish the association between different blood types and the aftermath of COVID-19 infections. Results: The study demonstrated that among the many characteristics of COVID-19, blood types tested out to be assciating with a statistically significant number of them. Noteworthy is the significant negative association that connects blood types with the severity of the disease, and this factor also determines the period for recovery. It became clear that the recovery duration and the treatment response didn’t depend on age when the results were adjusted for any statistically insignificant variations that could be attributed to age. This evidences us that it is likely that the age factor is not considered as a premier factor in the progress of the COVID-19 in the analyzed patients. when goes to a green process, the human error disappears.&#x0D; Conclusion: Obtained results of patients with diversified ABO blood types allowed us the data that confirmed disease incidence and severity can be modified during COVID-19. Given this fact, the doctors in the health care institutions and in the government agencies responsible for public health should gain this information. Also, the organizations need this information to develop a disease prevention and control policy. In a wider plan of the research and response strategy to the pandemic, COVID-19, the results reveal that on the genetic side the blood type must be borne in mind, amongst other hereditary features.

Advocacy Coalitions, Policy Entrepreneurs, and Windows of Opportunity: Tobacco Control in South Africa, 1948-2018.

This article examines the political history of tobacco control policy in South Africa from 1948 to 2018 by drawing on available historical documents, media reports, published books and articles, the grey literature, and face-to-face interviews with key policy actors. Tracing the historical evolution of tobacco control policies in South Africa reveals how embedded opposition from vested interest groups at every stage of the policy process complicates responses to the tobacco issue. This case study demonstrates how, despite such embedded difficulties, a confluence of regime change, evidence-based messaging, political will, policy entrepreneurs, and advocacy coalitions have led to the gradual transformation of tobacco control policy in South Africa over time. Understanding the historical evolution of tobacco control policy in South Africa opens up space for an in-depth inquiry that allows researchers to trace the policy-making process over the last seven decades, and to understand how those processes have facilitated a shift in the orientation of policy makers over time.

The Challenge in 2000–2009 to Phillips-Curve-Based Accounts of UK Economic Policy: Comment on Cristiano

Abstract A series of research papers that appeared from 2000 to 2009 made the case that the UK authorities in the 1950s, 1960s, and 1970s eschewed Phillips-curve-based analysis and that, consequently, the UK Great Inflation of the 1970s should not be regarded as resulting from policymakers’ pursuit of a perceived long-run inflation/unemployment trade-off. The position advanced in these 2000−2009 papers was that, instead, UK economic policy until 1979 subscribed to a nonmonetary perspective on inflation. This perspective implied UK authorities’ rejection of Phillips-curve-type trade-off analysis, but it also meant that they misjudged the importance of monetary policy in inflation control, thereby compounding the country's inflation problem. When this series of papers began to appear at the start of the 2000s, the trade-off-centered interpretation of the US Great Inflation was highly prevalent and was also being applied to the UK Great Inflation. By late in the decade, however, the case—as outlined in the 2000−2009 papers—against Phillips-curve-based accounts of historical policy conduct had gained notable acceptance among central bankers and academic researchers who discussed the UK Great Inflation. This article corrects erroneous statements that the challenge to Phillips-curve-based accounts of historical UK policymaker behavior only appeared in research starting in the 2010s.

Perfluoroalkyl substances in the environment and biota from the coasts of the South China Sea: profiles, sources, and potential risks

Perfluoroalkyl substances (PFAS) are an emerging class of contaminants that have been produced since the 1950s. The first report on PFAS to raise global concerns was published in 2001. Since then, many countries have implemented policies to control PFAS. In this study, PFAS in the water, sediment, and biota in coastal areas were surveyed to review their use since their earliest production by using chronological methods combined with previous policy restrictions imposed on PFAS. In the meantime, reports of existing PFAS were evaluated to assess the ecological and health risks of seafood consumption by coastal populations. Following the restrictions on PFAS, the concentrations of PFAS have been decreasing steadily. With regard to the current occurrences of PFAS in water and sediment, there is almost no ecological risk. However, different gender and age groups are still at risk of exposure to perfluorooctane sulfonate and require constant monitoring. It is expected that the negative impacts of PFAS on the environment and human health will continue to decrease with the implementation of the emerging pollution control policy by the Chinese government in 2023.

‘Stopping the start’: support for proposed tobacco control policies – a population-based survey in Great Britain 2021–2023

ObjectivesThis study assessed public support for four proposed tobacco control policies in Great Britain: (1) Raising the sales age of tobacco by 1 year every year (Smokefree Generation); (2) Raising...

Driving factors and key paths of greenhouse gas and air pollutants synergistic control using hybrid multiple-criteria decision-making

Humanity has consumed a large amount of energy and resources to maintain the rapid development of the economy and society, causing greenhouse gas and air pollutants to rise continuously, generating enormous pressures for the sustainable development of many cities. It is economical to control greenhouse gas and air pollutants from the synergy perspective. To identify the key driving factors involved in synergistic control, this paper uses the pressure-state-response (PSR) model to design a performance evaluation model of greenhouse gas and air pollutants synergistic control (GASC) utilizing pressure, state, and response dimensions. The performance evaluation factor system of GASC comprises three primary aspects and 18 criteria. The analytic hierarchy process (AHP) was used to determine the weight of each factor in the evaluation system. The technique for order preference by similarity to an ideal solution (TOPSIS) method was used to calculate the ranking of the synergistic control effects of the four representative provinces in China. We use Importance-performance analysis (IPA) to analyze the performance of driving factors of synergistic control in the province with the lowest ranking from 2016 to 2020. The research shows that in Northeast China, represented by Liaoning province, the government’s response should include changing the support strategy for the new energy consumer, introducing synergistic control standards and policies, and making flexible adjustments to the supply chain. The research provides a scientific basis for the performance evaluation of GASC and decision-making support for lean response strategies.

Balancing Protection and Quality in Big Data Analytics Pipelines.

Existing data engine implementations do not properly manage the conflict between the need of protecting and sharing data, which is hampering the spread of big data applications and limiting their impact. These two requirements have often been studied and defined independently, leading to a conceptual and technological misalignment. This article presents the architecture and technical implementation of a data engine addressing this conflict by integrating a new governance solution based on access control within a big data analytics pipeline. Our data engine enriches traditional components for data governance with an access control system that enforces access to data in a big data environment based on data transformations. Data are then used along the pipeline only after sanitization, protecting sensitive attributes before their usage, in an effort to facilitate the balance between protection and quality. The solution was tested in a real-world smart city scenario using the data of the Oslo city transportation system. Specifically, we compared the different predictive models trained with the data views obtained by applying the secure transformations required by different user roles to the same data set. The results show that the predictive models, built on data manipulated according to access control policies, are still effective.

Safe adaptive output‐feedback optimal control of a class of linear systems

AbstractThe objective of this research is to enable safety‐critical systems to simultaneously learn and execute optimal control policies in a safe manner to achieve complex autonomy. Learning optimal policies via trial and error, that is, traditional reinforcement learning, is difficult to implement in safety‐critical systems, particularly when task restarts are unavailable. Safe model‐based reinforcement learning techniques based on a barrier transformation have recently been developed to address this problem. However, these methods rely on full‐state feedback, limiting their usability in a real‐world environment. In this work, an output‐feedback safe model‐based reinforcement learning technique based on a novel barrier‐aware dynamic state estimator has been designed to address this issue. The developed approach facilitates simultaneous learning and execution of safe control policies for safety‐critical linear systems. Simulation results indicate that barrier transformation is an effective approach to achieve online reinforcement learning in safety‐critical systems using output feedback.

A Cross-Cultural Study on the Effects of Government Control Policies on Mobility in COVID-19

This study sought to explore the impact of government policies aimed at reducing the spread of COVID-19, such as social distancing and quarantine, on the reduction in the mobility of people and the role of national culture in moderating this effect. To test this hypothesis, this study collected 21,150 sets of data from 57 countries worldwide and analyzed them using a multilevel growth model. In addition, the number of COVID-19-infected people, the number of people vaccinated, number of days since the first COVID-19, median age by country, population density, total population, and GDP per capita, which can affect mobility, were added as control variables in the study model. Notably, the results of our analysis revealed that the stringency of government policies had a negative effect on mobility and that this effect differed according to cultural characteristics. The findings of the current study have the following implications. First, differences between countries were explained by exploring the effectiveness of government policies in preventing the increase in infectious diseases based on a cultural perspective. Second, the results of this study provide policy implications that international policy makers can refer to apart from the context of the COVID-19 epidemic by presenting country-specific differences in government policies.

Developing a National Longitudinal Tobacco Cohort of Youth and Young Adults: The Tobacco Epidemic Evaluation Network (TEEN+) Study.

Timely and relevant data are critical to monitoring the rapidly changing youth vaping epidemic and for understanding the prevalence, patterns of use, knowledge, and perceptions of tobacco products. While e-cigarettes have been the most used tobacco product among youth for nearly a decade, new nicotine delivery products continue to be introduced to the US market. Flavored tobacco products, including flavored e-cigarettes, menthol cigarettes, and flavored cigars, drive disparities in use by young people. To examine tobacco use among youth and young adults, the Monitoring E-Cigarette Use among Youth project established a longitudinal cohort of youth and young adults (13-24)-the Tobacco Epidemic Evaluation Network (TEEN+) study. TEEN+ focuses on e-cigarette and other tobacco products use and also includes questions about other substance use (eg, marijuana, alcohol), physical health, mental health, and social determinants of health (eg, discrimination, poverty, sexual and gender identity). Geocoding of responses allows for the evaluation of local tobacco control policies. The cohort includes an oversample of California residents to generate reliable and representative state-level estimates. This manuscript provides an overview of methods and baseline demographics from Wave 1. The initial Wave 1 TEEN+ cohort included 10 255 in the national sample and 2761 in the California sample. TEEN+ study data complement nationally-representative cross-sectional studies and allow for rapid evaluation of local and state policies. This manuscript describes the study's probability-based sample recruitment. Furthermore, we identify this initiative as a resource for evaluating the impact of flavored tobacco restriction policies and informing policy implementation efforts. This manuscript provides an overview of the methodology and baseline characteristics for a new longitudinal cohort of youth and young adults, the Tobacco Epidemic Evaluation Network (TEEN+) study. The TEEN+ study data can be used to evaluate the impact of flavored tobacco product restriction policies and informing policy implementation efforts.

Cooperative motion planning and control of a group of autonomous underwater vehicles using twin-delayed deep deterministic policy gradient

The cooperative execution of complex tasks can lead to desirable outcomes and increase the likelihood of mission success. Nevertheless, coordinating the movements of multiple autonomous underwater vehicles (AUVs) in a collaborative manner is challenging due to nonlinear dynamics and environmental disturbances. The paper presents a decentralized deep reinforcement learning algorithm for AUVs that enables cooperative motion planning and obstacle avoidance. The goal is to formulate control policies for AUVs, empowering each vehicle to create its optimal collision-free path through adjustments in speed and heading. To ensure safe navigation of multiple AUVs, COLlision AVoidance (COLAV) plays a crucial role. Therefore, the implementation of a multi-layer region control strategy enhances the AUVs’ responsiveness to nearby obstacles, leading to improved COLAV. Furthermore, a reward function is formulated to consider four criteria: path planning, obstacle- and self-COLAV, as well as feasible control signals, with the aim of strengthening the proposed strategy. Notably, the devised scheme demonstrates robustness against disturbances A comparative study is conducted with the well-established Artificial Potential Field (APF) planning method. The simulation results indicate that the proposed system effectively and safely guides the AUVs to their goals and exhibits desirable generalizability.