Multi-level Problem Research Articles

Translating Values into Quality: How We Can Use Max Weber’s Ethic of Responsibility to Rethink Professional Ethics

A risk-based reinterpretation of Weber’s ethic of responsibility can resolve core problems of professional ethics (the role of values, the multilevel problem, etc.) and address current issues—such as the social responsibility of professions or the accountability of professionals. From this perspective, professions as organizations and professionals as their individual members share and distribute responsibility (and risk) in that the primary responsibility of a profession is to provide domain-specific quality standards, while that of individual professionals is to be able to justify service against those standards on a case-by-case basis. In this way, as argued in the paper, professionalism translates (sometimes conflicting) values into a case-specific quality.

HERP: Hierarchical and distributed clouds oriented efficient resource scheduling algorithm with stochastic requirements

With the development of cloud technology, hierarchical and distributed cross-cloud architecture is gradually replacing traditional centralized architecture, for example, used in edge (or fog) computing. Due to the fluctuation of resource requirements, if a node does not have sufficient resources to process requests, the same or higher-level nodes can share their resources by offloading or redirecting requests to themselves, at the possible cost of reduced service quality. However, it is difficult to effectively optimize the sharing effect based on mean requirements. We formulate the multilevel problem with horizontal and vertical resource sharing using stochastic models, identify the optimal structures with embedded subproblems, and obtain the approximation solution in an efficient dynamic programming manner. In the problem setting with a wide range of different parameters, the proposed algorithm can outperform existing mean and heuristic algorithms in all scenarios to improve the total satisfied requirements by up to 26%, and can be hundreds of times faster than these heuristic algorithms.

Uncertain Multilevel Programming Based on Hurwicz Criterion with Application to Resource Allocation

A number of uncertain multilevel programming models have been proposed and applied to decentralized decision-making problems. It is assumed that the models of uncertain multilevel problems involve uncertain variables. In these models, the chance constraints are used as constraints, and the objective functions vary according to the requirements of decision-makers. The objective functions in this paper are based on the Hurwicz criterion, which combines optimistic value and pessimistic value to find a balance between optimism and pessimism. To deal with situations in which decision-makers have this type of risk appetite, the uncertain Hurwicz multilevel programming model is proposed based on uncertainty theory and the Hurwicz criterion. Finally, two numerical examples and a case study on resource allocation are given to demonstrate the potential uses of this study.

Multi-level decisions for addressing trade-off in the cross-regional water-environment-agriculture interactive system under constraint of water ecological carrying capacity

The complex-enhanced hierarchical relationship among multiple stakeholders in the water-environment-agriculture interactive system has been overlooked. This study develops a leader-follower-enhanced framework (named as FCMLP) that integrates variable-weight combination prediction model, multi-level programming, and fuzzy credibility constrained programming, which can effectively address the above problems under uncertainties. Five water ecological carrying capacity (WECC) statuses are treated as a critical constraint into the modeling framework to improve the accuracy of decision-making. An interactive fuzzy satisfaction algorithm is advanced for solving this multi-level problem, in which COD discharge minimization, economic benefits maximization, and grain yield maximization are taken as the upper-, middle-, and lower-level goals, respectively. The framework is applied to plan the cross-regional water-environment-agriculture interactive system in the Beijing-Tianjin-Hebei and Yangtze River Economic Belt. Solutions reveal that increased WECC status and credibility level would decrease 1.40%–1.74%, 0.71%–9.61%, and 1.63%–2.26% of water resources allocation, COD emissions, and economic benefits, respectively. Crop area and grain yield would dramatically decline by 4.13%–4.46% and 4.03%–4.67% when a credibility level increases from 0.8 to 1, respectively. The overall satisfactory degree would range from 0.58 to 0.70, which illustrates interactive decision-making process of multiple stakeholders. Significant differences can be observed in the optimized schemes of water resources allocation and environmental-economic-agricultural performances among various models. The amounts of allocated water resources, pollutant discharge, and economic output from the FCMLP model would be respectively 11.30%–13.45%, 14.90%–15.21%, and 73.12%–73.48% higher than those from the environment- and agriculture-oriented schemes, yet 13.81%, 32.05%, and 15.29% lower than those from the economy-oriented scheme. Some water adaptability countermeasures are given for ensuring the scientific operation of the South-to-North Water Transfer Project and alleviating conflicts between water source and receiving areas. Further exploration of the optimization scheme of water-environment-energy-agriculture system driven by climate change is still required for guaranteeing the dynamic balance of regional resources.

Land Distribution in German and Mennonite Colonies During the NEP Period. Expectations and Reality

The article is devoted to the study of the relationship between the Soviet authorities and the German, as well as Mennonite communities, regarding land issues during the NEP period. It is based on the analysis of the official reports, memoirs and documents. The author studies the complex relationships between the central government, the regional level of authorities (provincial and district) and Mennonites. The land distribution in Mennonite colonies, as well as the cause and-effects of the process are analyzed. In the whirlwind of the internal and foreign political processes, the newly created Soviet state found itself on the edge of socio- economic conflicts. In order to solve urgent economic issues and curb mob violence, a number of economic reforms were adopted, which are known in history as the New Economic Policy. Most of the projects of the Soviet government were based on communist ideology at the initial stage. Those advanced farms’ lands, which used to belong to the Mennonites and Germans, were redistributed. Unemployed / recent employed people who had received some land, were not skilled and did not have a knack for agriculture. Therefore, they gradually abandoned their lands. That strategy undermined the land system and, as a result, became another pushing motivation for emigration and agricultural problems in the countryside. As a result of the Bolshevik government’s land program, the Mennonite community became embroiled in complex multilevel problems: a) intra- community land tensions caused by demographic processes and the resettlement of fellow refugees from starving regions of Soviet Russia to the colonies; b) conflicts with the population of neighboring villages and poor peasant committees, which often forced the issue of redistribution of Mennonite lands in their favor; c) failure of provincial and district executive committees to enforce resolutions of the supreme power to settle the land issue of the Mennonite community; d) ineffectiveness of the national minority committee; e) the perception by some Mennonites of new communist ideas – social equality. These reasons became important pushing factors for а large-scale wave of emigration of this ethno- confessional group to North America.

A solution method for stochastic multilevel programming problems. A systematic sampling evolutionary approach

Stochastic multilevel programming is a mathematical programming problem with some given number of hierarchical levels of decentralized decision makers and having some kind of randomness properties in the problem definition. The introduction of some randomness property in its hierarchical structure makes stochastic multilevel problems computationally challenging and expensive. In this article, a systematic sampling evolutionary method is adapted to solve the problem. The solution procedure is based on realization of the random variables and systematic partitioning of each hierarchical level’s decision space for searching an optimal reaction. The search goes sequentially upwards starting from the bottom up through the top hierarchical level problem. The existence of solution and convergence of the solution procedure is shown. The solution procedure is implemented and tested on some selected deterministic test problems from literature. Moreover, the proposed algorithm can be used to solve stochastic multilevel programming problems with additional complexity in their problem definition.

Problems of organizing motor activity and forming need for it

In the conditions of the information society, the problem of decreased motor activity is aggravating. In the relatively near future, the unresolved nature of this problem will account for people’s impaired health. Therefore, the issues related to the organisation of people’s motor activity and the formation of their need for it become relevant. The purpose of the article is the analysis of the pressing problems of motor activity organisation and formation of the need in it. The reliability of the findings is secured by the integrative approach based on the methods of theoretical analysis of scientific literature and the analysis of the results of fitness testing conducted with the help of fitness trackers. The results of foreign research on the given problem were taken into account. The implemented research leads to the conclusion that the formation of motor activity and the motivation for it is a complex multilevel problem. The analysis of “big data” statistics on the use of personal gadgets has made it possible to systematise the trends and regularities in the formation of motor activity and the need for it.

Non-Iterative Solution for Coordinated Optimal Dispatch via Equivalent Projection—Part I: Theory

Coordinated optimal dispatch is of utmost importance for the efficient and secure operation of hierarchically structured power systems. Conventional coordinated optimization methods, such as the Lagrangian relaxation and Benders decomposition, require iterative information exchange among subsystems. Iterative coordination methods have drawbacks including slow convergence, risk of oscillation and divergence, and incapability of multi-level optimization problems. To this end, this paper aims at the non-iterative coordinated optimization method for hierarchical power systems. The theory of the equivalent projection (EP) is proposed, which makes external equivalence of the optimal dispatch model of the subsystem. Based on the EP theory, a coordinated optimization framework is developed, where each subsystem submits the EP model as a substitute for its original model to participate in the cross-system coordination. The proposed coordination framework is proven to guarantee the same optimality as the joint optimization, with additional benefits of avoiding iterative information exchange, protecting privacy, compatibility with practical dispatch scheme, and capability of multi-level problems.

The image of Ethnic Identity in Kazakh cinema in the context of cultural studies

Today, more than ever, the topic of ethnicity, ethnic activity is a topical and it requires a comprehensive study of it. The more changes take place in the world, the more it affects society, attitudes towards other ethnic groups, cultures and people in general. This topic requires detailed study, human identity is a multifaceted and multilevel problem. The construction of identity is a theme that must be understood and realized in order to build a modern cultural society. The relevance of this issue is that it is necessary to be aware of ethnic characteristics against the background of global processes, which leads to the substantiation of the essence of ethnic identity. The goal is to reveal the ways of constructing ethnic identity on the example of the film “Mustafa Shokai”. Researchers set a number of tasks to achieve this goal: - to determine the essence of national identity in the context of cultural studies; - to determine the components of the representation of the image of the nation. The novelty of this subject of the article lies in the fact that the authors analyze the image of ethnic identity in the context of cultural studies. The authors realize the discursive nature of various approaches in understanding the image of ethnic identity, but despite the discourse, they nevertheless try to draw attention to the need to find an unconditional factor in constructing identity and branding the image of national and ethnic identity for the younger generation. The possibility of studying various cinematic strategies for the representation of the image of national and ethnic identity by the authors is carried out in the context of cultural research.

Exploring multilevel data with deep learning and XAI: The effect of personal-care advertising spending on subjective happiness

International business research often links the cultural and institutional characteristics of countries to the features of the individuals inhabiting these countries. A distinct approach to analyzing such multilevel problems with deep learning and explainable artificial intelligence methods is presented, using country characteristics as explicit spatial coordinates. Deep learning is tolerant of noise and faults and can approximate arbitrarily complex mathematical structures by developing multiple abstractions. An applied example demonstrates the applicability of this approach by exploring the effect of personal-care advertising spending in 27 countries on the subjective happiness of 376,442 individuals, indicating a statistically significant positive effect, albeit with a trivial effect size.

Making the invisible visible: Using a qualitative system dynamics model to map disparities in cumulative environmental stressors and children's neurodevelopment

BackgroundThe combined effects of multiple environmental toxicants and social stressor exposures are widely recognized as important public health problems, likely contributing to health inequities. However, US policy makers at state and federal levels typically focus on one stressor exposure at a time and have failed to develop comprehensive strategies to reduce multiple co-occurring exposures, mitigate cumulative risks and prevent harm. This research aimed to move from considering disparate environmental stressors in isolation to mapping the links between environmental, economic, social and health outcomes as a dynamic complex system using children's exposure to neurodevelopmental toxicants as an illustrative example. Such a model can be used to support a broad range of child developmental and environmental health policy stakeholders in improving their understanding of cumulative effects of multiple chemical, physical, biological and social environmental stressors as a complex system through a collaborative learning process. MethodsWe used system dynamics (SD) group model building to develop a qualitative causal theory linking multiple interacting streams of social stressors and environmental neurotoxicants impacting children's neurodevelopment. A 2 1/2-day interactive system dynamics workshop involving experts across multiple disciplines was convened to develop the model followed by qualitative survey on system insights. ResultsThe SD causal map covered seven interconnected themes: environmental exposures, social environment, health status, education, employment, housing and advocacy. Potential high leverage intervention points for reducing disparities in children's cumulative neurotoxicant exposures and effects were identified. Workshop participants developed deeper level of understanding about the complexity of cumulative environmental health risks, increased their agreement about underlying causes, and enhanced their capabilities for integrating diverse forms of knowledge about the complex multi-level problem of cumulative chemical and non-chemical exposures. ConclusionGroup model building using SD can lead to important insights to into the sociological, policy, and institutional mechanisms through which disparities in cumulative impacts are transmitted, resisted, and understood.

Rescue Improvement Conference: A Novel Tool for Addressing Failure to Rescue.

To understand the effectiveness of Rescue Improvement Conference, a forum that addresses FTR. Every year over 150,000 patients die after elective surgery in the United States. FTR is the phenomenon whereby delayed recognition and/or response to serious surgical complications leads to a progressive cascade of adverse events culminating in death. Rescue Improvement Conference is an adapted version of the Ottawa-style morbidity and mortality conference, designed to address common contributors to FTR: ineffective communication and inadequate problem solving. Mixed methods data were used to evaluate Rescue Improvement Conference, a bi-monthly forum that was first introduced in our academic medical center in 2018. Conference effectiveness data were collected via survey and open-text responses after 5 conferences between September 2018 and February 2020. We focused on 5 indicators of effectiveness: educational value, conference takeaways, discussion time, changes to surgical practice, and actionable opportunities for improvement. Twelve surgical faculty and house staff also provided feedback during semi-structured interviews. Qualitative data were analyzed using thematic analysis. Conference attendees (N = 140) felt that Rescue Improvement Conference was effective-all 5 indicators had mean scores above 5 on Likert scales. The qualitative data supports the quantitative findings, and 3 additional themes emerged: Rescue Improvement Conference enables the representation of diverse voices, promotes interdisciplinary collaboration, and encourages multilevel problem solving. Rescue Improvement Conference has the potential to support other surgical departments in developing system-level strategies to recognize and manage postoperative complications by providing stakeholders a forum to identify and discuss factors that contribute to FTR.

Preservation of health of medical students, including those with special educational needs: current problems

The article analyzes the experience of developing health preservation competencies of medical students in the context of blended learning and application of innovative health preservation techniques. Health preservation is a multilevel problem that requires an integrated approach implying readiness of medical graduates to respond flexibly to the changing landscape of their professional activities; therefore, the article discusses some promising options of mastering universal competencies and their integration into the educational process while factoring in the current knowledge on hygiene education, patterns of thinking, psychology of consciousness, decision-making and practical skills, all of which should be developed and consolidated by applying the various current forms, technologies and methods of work.

Drought governance: A cross-level governance analysis in Botswana

Drought, a growing climate change hazard, is a multilevel problem that affects and is affected by decisions that are made at multiple levels of governance (local, district, and national). Understanding the characteristics of governance that might enable effective drought management can greatly enhance the design of drought responses and adaptation measures. Using the case of Botswana, an in-depth analysis of the multi-scalar dynamics and governance of drought was undertaken. Using insights from multi-level governance theories, the research revealed how institutions shaped drought management from the local to the national level during the 2015/2016 drought, the worst that Botswana has experienced in the last thirty years. Important lessons for understanding the governance of drought include that 1) the current framing of drought may limit risk-reduction actions, and 2) cross-sectoral platforms that bring about collaboration are not sufficient on their own: they need to be supported by the requisite capacities, individual interests, and leadership to bring about cross-sectoral integration. Therefore, in order to strengthen drought governance, its framing needs to be broadened, and local actors need to be better integrated into decision-making processes. The paper calls for a reconceptualisation of multi-level governance, as part of a broader set of governance measures for drought across scale.

An adaptive method to solve multilevel multiobjective linear programming problems

This paper is a follow-up to a previous work where we defined and generated the set of all possible compromises of multilevel multiobjective linear programming problems (ML-MOLPP). We introduce a new algorithm to solve ML-MOLPP in which the adaptive method of linear programming is nested. First, we start by generating the set of all possible compromises (set of all non-dominated solutions). After that, an algorithm based on the adaptive method of linear programming is developed to select the best compromise among all the possible settlements achieved. This method will allow us to transform the initial multilevel problem into an ML-MOLPP with bonded variables. Then, apply the adaptive method which is the most efficient to solve all the multiobjective linear programming problems involved in the resolution process instead of the simplex method. Finally, all the construction stages are carefully checked and illustrated with a numerical example.

Research on the Reform of "Problem Solving Oriented" Teaching Mode of Primary School Mathematics under the Concept of Student Based Education

The concept of student based education advocates students as the main body, and its teaching form helps to give play to students' subjective initiative. Therefore, this paper puts forward a research on the reform of "problem solving oriented" teaching mode of primary school mathematics under the concept of student based education. First of all, through the problems set up in the teaching process are inappropriate, the teaching method is single, and the construction of the learning group model is not standardized, the problems in the teaching model reform are explored. According to the above problems, the corresponding solutions are proposed, and the teaching structure is strengthened by establishing multi-level problems, enriching teaching methods, building a standardized learning group model and other strategies to improve the overall teaching effect.

Using meta-reasoning for incremental repairs in multi-object robot manipulation tasks

Robots tasked with object assembly by manipulation of parts require not only a high-level plan for order of placement of parts but also detailed low-level information on how to place and pick the part based on its state. This is a complex multi-level problem prone to failures at various levels. This paper employs meta reasoning architecture along with robotics principles and proposes dual encoding of state expectations during the progression of task to ground nominal scenarios. We present our results on table-top scenario using perceptual expectations based in the concept of occupancy grids and key point representations. Our results in a constrained manipulation setting suggest using low-level information or high-level expectations alone the system performs worse than if the architecture uses them both. We then outline a complete architecture and system which tackles this problem for repairing more generic assembly plans with objects moving in spaces with 6 degrees of freedom.

Women in cardiology leadership of randomized clinical trials and participation of women in late-breaking clinical trials: has the COVID-19 pandemic changed a thing or not exactly?

Abstract Introduction Despite considerable developments made in the representation of women in cardiology (WIC) recently, there still remain substantial disparities in the representation of women participants in clinical trials, as well as women physicians and scientists in clinical trial leadership. Under-representation of women in Randomized Clinical Trials (RCTs) remains the bane of the modern medicine, impeding the development of sex-specific guidelines in cardiovascular diseases. Female leadership in clinical trials has been shown to enhance the inclusion of women as trial participants. Furthermore, while the COVID-19 pandemic has impacted women in academia, there is no data thus far reporting the impact of the pandemic in terms of presenters and leadership of late-breaking clinical trials (LBCT) in cardiology during this period. Purpose We aimed to determine inclusion of WIC in LBCTs leadership and their correlation to inclusion of women in reported RCTs. Methods In our comprehensive analysis, we included all LBCTs presented at major international cardiovascular meetings reported over the period of January 2020 to February 2022. Data were derived from the original presentation at the meeting and/or simultaneous/ subsequent publication of manuscript. Sex of the presenter (woman or man), was assessed by either original videos of the presentation at the meeting, or based on pronoun use in the biographies derived from institutional profiles. The presence or absence of reporting of sex distribution of study participants were also recorded from original presentation at the meeting and/or published manuscript. Proportion of women included in each trial was sourced from either original publication or calculated from any similar data shown during the presentations. Results A total of 400 of RCTs from 19 meetings were included with a total of 400 presenters/principal investigators recorded – 32 (8%) women and 368 (92%) men. There were no significant differences between 2020 and 2021 [15 (7.2%) women in 2021 vs. 17 (19.3%) in 2020 (P=0.446)]. Proportions of women included in RCTs with WIC (37.3%) vs. non-WIC (38.7%) presenters were comparable (p=0.559), while 45% of RCTs didn't report sex distribution of participants. Except for 2 meetings (CRT 2020 and 2022), all others were virtual. Conclusion WIC representation as RCTs presenters was significantly low, despite the opportunity of virtual attendance afforded during the COVID-19 pandemic. Modest inclusion of women irrespective of sex of RCT leadership emphasizes multi-level problems that require more actionable solutions: i.e. implicit bias training started as early as medical school, continuing education on necessity for diversity, equity and inclusion, patient and public involvement, and comprehensive guidance on trial design, such that future RCT participants reflect the populations intended to treat. Funding Acknowledgement Type of funding sources: None.

Explaining transformative change in EU climate policy: multilevel problems, policies, and politics

ABSTRACT The EU's ambition to lead in global climate governance has shaped its engagement with the UNFCCC regime and informed a vast body of regulatory instruments. However, EU climate policy outcomes have not always matched aspirations. We explore how UNFCCC-EU institutional interactions have shaped EU climate policy outcomes by combining a multilevel governance perspective with scholarship on policy entrepreneurship to explain when, why, and how motivated policy entrepreneurs are most likely to secure transformative policy change. We contrast the successful policy transformation of the European Green Deal with the experience of policy stagnation in the aftermath of the economic crisis, shedding light on the interaction between problems, policies, and politics across levels. We find that while the international level is significant in opening up windows of opportunity from above, the presence below of an authoritative and motivated policy entrepreneur within the political stream is a crucial additive to securing transformative policy change.

Deep Brain Stimulation: Emerging Tools for Simulation, Data Analysis, and Visualization.

Deep brain stimulation (DBS) is a well-established neurosurgical procedure for movement disorders that is also being explored for treatment-resistant psychiatric conditions. This review highlights important consideration for DBS simulation and data analysis. The literature on DBS has expanded considerably in recent years, and this article aims to identify important trends in the field. During DBS planning, surgery, and follow up sessions, several large data sets are created for each patient, and it becomes clear that any group analysis of such data is a big data analysis problem and has to be handled with care. The aim of this review is to provide an update and overview from a neuroengineering perspective of the current DBS techniques, technical aids, and emerging tools with the focus on patient-specific electric field (EF) simulations, group analysis, and visualization in the DBS domain. Examples are given from the state-of-the-art literature including our own research. This work reviews different analysis methods for EF simulations, tractography, deep brain anatomical templates, and group analysis. Our analysis highlights that group analysis in DBS is a complex multi-level problem and selected parameters will highly influence the result. DBS analysis can only provide clinically relevant information if the EF simulations, tractography results, and derived brain atlases are based on as much patient-specific data as possible. A trend in DBS research is creation of more advanced and intuitive visualization of the complex analysis results suitable for the clinical environment.