Levels Of Hierarchy Research Articles

Can the energy conservation and emission reduction demonstration city policy enhance urban domestic waste control? Evidence from 283 cities in China

The impact of energy conservation and emission reduction (ECER) policies on domestic waste control has not been determined. Previous papers have focused predominantly on industrial pollution rather than domestic waste control. To fill this gap, this paper evaluates the impact of the ECER demonstration city policy on domestic waste control based on Chinese city-level data from 2010 to 2020 using a staggered difference-in-differences model. This paper finds that the implementation of the policy has significantly increased the amount of urban domestic waste removed and the capacity for harmless disposal. A comprehensive examination of possible mechanisms reveals that ECER demonstration cities have achieved improved domestic waste control through channels such as increased government inputs in waste control, the promotion of green lifestyles among residents, and the promotion of technological advances in waste control. Detailed heterogeneity analyses reveal that the positive impact of the policy on domestic waste control is greater in cities at a high level in the administrative hierarchy, in eastern cities, and in large cities. This study has strong practical significance, as it provides insights supporting differentiated efforts to promote the construction of ECER demonstration cities and guidance for improving domestic waste control capacity by exploiting ECER policies.

Health Services Research in the Public Health Department - An Explorative Interview Study on Scientific Methodological Competence in the PHS in Baden-Württemberg, Germany

One aim of the pact for the Public Health Service ("Pakt für den ÖGD") is to increase scientific activity in the Public Health Service (PHS). This study deals with the question, which methods related to health services research are known and applied in the PHS and which methods are needed by PHS employees in the federal state Baden-Württemberg in Germany. Guideline-based interviews (focus group and individual interviews) were conducted with 12 persons at different hierarchy levels from public health departments in Baden-Württemberg. The interviews were subjected to content analysis acording to Kuckartz. The interviewees described their heterogeneous needs as well as their methodological competences. Staff members expressed existing competences more frequently than leaders. These competencies included those used in everyday work such as literature research in routinely collected data (e. g., school entry examination), or different methods for data analysis. Needs seemed to exist primarily in the area of data analysis and collection, but were also expressed in the area of basic scientific methods. Topics relating to guidelines for good scientific practice (e. g., ethics proposals) and publications were also rather less known. A need for a support from research institutions or higher authorities was frequently mentioned. In addition, motivation and barriers for research in public health departments were mentioned. This study shows that existing methodological competencies and needs are heterogeneous and can be attributed to the heterogeneous backgrounds and fields of activity of the interviewees. Competencies are indicated, for example, in literature research and analysis of existing data. There is a need in methods, for example, of data collection/analysis as well as in basic scientific methods and deepening of existing skills. Furthermore support offers regarding scientific methodological competence for public health departments are required. There is also a lack of research infrastructure (e. g. software, access to literature) and a legal basis. The results can serve as a basis for the design of demand-oriented methodological programs for employees of the PHS in Baden-Württemberg.

COfEE: A comprehensive ontology for event extraction from text

Large volumes of data are constantly being published on the web; however, the majority of this data is often unstructured, making it difficult to comprehend and interpret. To extract meaningful and structured information from such data, researchers and practitioners have turned to Information Extraction (IE) methods. One of the most challenging IE tasks is Event Extraction (EE), which involves extracting information related to specific incidents and their associated actors from text. EE has broad applications, including building a knowledge base, information retrieval, summarization, and online monitoring systems. Over the past few decades, various event ontologies, such as ACE, CAMEO, and ICEWS, have been developed to define event forms, actors, and dimensions of events observed in text. However, these ontologies have some limitations, such as covering only a few topics like political events, having inflexible structures in defining argument roles, lacking analytical dimensions, and insufficient gold-standard data. To address these concerns, we propose a new event ontology, COfEE, which integrates expert domain knowledge, previous ontologies, and a data-driven approach for identifying events from text. COfEE comprises two hierarchy levels (event types and event sub-types) that include new categories related to environmental issues, cyberspace, criminal activity, and natural disasters that require real-time monitoring. In addition, dynamic roles are defined for each event sub-type to capture various dimensions of events. The proposed ontology is evaluated on Wikipedia events, and it is shown to be comprehensive and general. Furthermore, to facilitate the preparation of gold-standard data for event extraction, we present a language-independent online tool based on COfEE. A gold-standard dataset annotated by ten human experts consisting of 24,000 news articles in Persian according to the COfEE ontology is also prepared. To diversify the data, news articles from the Wikipedia event portal and the 100 most popular Persian news agencies between 2008 and 2021 were collected. Finally, we introduce a supervised method based on deep learning techniques to automatically extract relevant events and their corresponding actors.

Upward and Downward Prosocial Influence Across Levels of a Social Hierarchy: Field and Experimental Evidence About Authorities of U.S. Counties

Upward and Downward Prosocial Influence Across Levels of a Social Hierarchy: Field and Experimental Evidence About Authorities of U.S. Counties

Business cycles, real wages, and the quality of jobs

ABSTRACT The primary goal of this study is to shed light on the ongoing debate regarding a supposed extra wage sensitivity for newly hired workers compared to those who remain employed. Recent contributions claim that this apparent greater wage sensitivity may be driven by the correlation between the business cycle and likelihood of workers transitioning to ‘better’ job opportunities, typically associated with higher salaries. Our findings based on Brazilian data align with this claim. In other words, during periods of economic expansion, the availability of ‘better’ job positions increases, leading to a higher influx of newly hired individuals who experience wage increases because of transitioning away from ‘worse’ job positions into better jobs. To assess this, we used two metrics for ranking jobs: The first was based on grouping occupations according to hierarchy levels, with managers and directors occupying the top tier. The other considered formal jobs as better than informal jobs. Importantly, our findings remain robust regardless of how the jobs are ranked.

The intersection of Maslow's theory and African public policy implementation: Insights and perspectives

This study examines the application of Maslow's Hierarchy of Needs to public policy formulation and implementation in African nations, with a focus on Rwanda, South Africa, and Kenya. It analyzes how these countries have aligned their policies with different levels of Maslow's hierarchy, from addressing basic physiological needs to fostering self-actualization and societal progress. The research explores Rwanda's comprehensive post-genocide policy framework, South Africa's efforts to address apartheid legacies, and Kenya's struggle to balance economic growth with basic needs fulfillment. Through these case studies, the study demonstrates the value of applying Maslow's theory to guide policymakers in prioritizing and addressing diverse societal needs while pursuing broader development goals. The analysis reveals both successes and persistent challenges in areas such as social cohesion, economic inequality, and rapid urbanization. The study concludes by offering recommendations for a more holistic, context-specific, and sustainable approach to need-based policy formulation in African countries, emphasizing the importance of inclusive governance, long-term vision, and regional cooperation.

Supply chain optimization: bibliometric analysis, research structure and future outlook

Purpose Supply chain (SC) research has boomed over the past two decades. Significant contributions have been made to the field from various analytical and decision-making perspectives. This paper, a comprehensive bibliometric study, aims to identify the key research contributors, institutions and themes. Design/methodology/approach A comprehensive knowledge domain visualization of over 1,000 articles, published between 2000 and 2022, is carried out to construct a bird’s eye view of the field in terms of research production, key authors, main publication outlets, geographic disparity of the contributions and emerging research trends. Additionally, collaboration patterns among researchers and institutions are mapped to highlight the communication networks underlying research initiatives. Findings Results show an explosive growth in the number of articles tackling supply chain optimization (SCO) issues with a significant concentration of the contributions in a relatively small cluster of authors, journals, institutions and countries. Among the many important findings, our analysis indicates that mixed-integer linear programming is the most commonly used model, while robust optimization is the method of choice for handling uncertainty. Furthermore, most SC models are developed at only one level of the organizational hierarchy and consider only one planning horizon. The importance of developing integrated SCO systems is key for future research. Originality/value The study fills the optimization techniques gap that exists in SC management bibliometric studies and presents a thematic map for the SCO research highlighting the various research foci.

Responses at various levels of ecological hierarchy indicate acclimation to sequential sublethal heatwaves in a temperate benthic ecosystem.

Marine heatwaves have caused massive mortality in coastal benthic ecosystems, altering community composition. Here, we aim to understand the effects of single and sequential sublethal heatwaves in a temperate benthic ecosystem, investigating their disturbance on various levels of ecological hierarchy, i.e. individual physiology, trophic groups' biomass and ecosystem carbon fluxes. To do so, we performed a near-natural experiment using outdoor benthic mesocosms along spring/summer, where communities were exposed to different thermal regimes: without heatwaves (0HW), with one heatwave (1HW) and with three heatwaves (3HWs). Gastropods were negatively impacted by one single heatwave treatment, but the exposure to three sequential heatwaves caused no response, indicating ecological stress memory. The magnitude of ecosystem carbon fluxes mostly decreased after 1HW, with a marked negative impact on mesograzers' feeding, while the overall intensity of carbon fluxes increased after 3HWs. Consumers' acclimation after the exposure to sequential heatwaves increased grazing activity, representing a threat for the macroalgae biomass. The evaluation of physiological responses and ecological interactions is crucial to interpret variations in community composition and to detect early signs of stress. Our results reveal the spread of heatwave effects along the ecological hierarchical levels, helping to predict the trajectories of ecosystem development.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Onboarding: Key to perception of the company as a great place to work

The purpose of this paper is to analyse onboarding practices, in order to test their role in generating a perception of the company as a Great Place to Work (GPTW) and to identify which ones contribute most to this perception. The experience of newcomers during the onboarding process is assessed using a questionnaire based on the 30 onboarding practices of Klein, Polin and Soutton (2015) and the criteria used by GPTW. The sample consisted of 194 university students in their final year in internship programs with companies. We applied descriptive, cluster and correlation analysis. A large part of applied and valued onboarding practices are those where personal support is perceived at different levels of hierarchy, knowledge and roles. Guidance and information practices have the greatest influence on the perception of the company as a GPTW. We demonstrate the existence of a positive relationship between the evaluation of onboarding and GPTW. This research expands the knowledge about onboarding and analyses it from a novel perspective: its relationship with the perception of the company as a GPTW.

Mental Health Planning in the COVID-19 Scenario: a Systematic Review of Literature and Metasynthesis

Objective: The general objective was to investigate mental health planning by the healthcare team in the Covid-19 scenario. Method: The present study is a Systematic Literature Review and Metasynthesis. The guiding question was defined through the “PICo” strategy. The search for evidence took place in the Scielo, Lilacs and Pubmed databases. The review and selection of studies took place through complete reading and evaluation of titles, abstracts and elimination of duplicate articles. Methodological analysis of the study involved the 8 levels of evidence hierarchy. Results: The results were presented using a model based on and adapted to the “Preferred Reporting Items for Systematic Reviews and Meta-Analysis” (PRISMA) protocol, recording the source’s key information through: Author, Year of publication, Origin, Objective, Methodology and Results. Discussion: The discussion of the results took place through meta-synthesis interpretation, with inferences of logical and integrative validity, in the comparison and union of meanings and concepts, characterizing the following axes: Challenges in mental health in the Covid-19 scenario; Strategies for mental health planning in the Covid-19 scenario; And, Importance of mental health planning in the Covid-19 scenario. Final Considerations: Mental health planning acts as a fundamental element in the search for balancing the basic needs of human beings and the absence of this can enable the weakening of care networks, generating a social catastrophe.

Bayesian modeling of spatial ordinal data from health surveys.

Health surveys allow exploring health indicators that are of great value from a public health point of view and that cannot normally be studied from regular health registries. These indicators are usually coded as ordinal variables and may depend on covariates associated with individuals. In this article, we propose a Bayesian individual-level model for small-area estimation of survey-based health indicators. A categorical likelihood is used at the first level of the model hierarchy to describe the ordinal data, and spatial dependence among small areas is taken into account by using a conditional autoregressive distribution. Post-stratification of the results of the proposed individual-level model allows extrapolating the results to any administrative areal division, even for small areas. We apply this methodology to describe the geographical distribution of a self-perceived health indicator from the Health Survey of the Region of Valencia (Spain) for the year 2016.

BOLD fMRI responses to amplitude-modulated sounds across age in adult listeners

Abstract Age-related alterations in the auditory system have been suggested to affect the processing of temporal envelope amplitude modulations (AM) at different levels of the auditory hierarchy, yet few studies have used functional magnetic resonance imaging (fMRI) to study this noninvasively in humans with high spatial resolution. In this study, we utilized sparse-sampling fMRI at 3 Tesla (3T) to investigate regional blood oxygenation level-dependent (BOLD) responses to AM noise stimuli in 65 individuals ranging in age from 19 to 77 years. We contrasted BOLD responses to AM noise stimuli modulated at 4 Hz or 80 Hz with responses to unmodulated stimuli. This allowed us to derive functional measures of regional neural sensitivity to the imposed AM. Compared with unmodulated noise, slowly varying 4 Hz AM noise stimuli elicited significantly greater BOLD responses in the left and right auditory cortex along the Heschl’s gyrus (HG). BOLD responses to the 80 Hz AM stimuli were significantly greater than responses to unmodulated stimuli in putatively primary auditory cortical regions in the lateral HG. BOLD responses to 4 Hz AM stimuli were significantly greater in magnitude than responses to 80 Hz AM stimuli in auditory cortical regions. We find no discernible effects of age on the functional recruitment of the auditory cortex by AM stimuli. While the results affirm the involvement of the auditory cortex in processing temporal envelope rate information, they provide no support for age-related effects on these measures. We discuss potential caveats in assessing age-related changes in responses to AM stimuli in the auditory pathway.

Learn bamboo from bamboo: a kinaesthetic communication approach to curating cultures, crafts, and construction for higher education

PurposeBeyond symptomatic communication barriers between designers and communities, glocal resiliency building (GRB) by intercultural groups often challenges traditional service-learning trajectories. Without ambitious performance hurdles, two higher education institutions from Australia and Thailand built rapport via their shared love for Bamboo to level hierarchies between groups: architects, both social and professional.Design/methodology/approachThe author used Basho’s “self” – object nexus, as depicted in “Learn Bamboo from Bamboo” Haiku, as a methodology to structure our observations of stakeholders (Haas, 1994). This reflective account, narrated through a tabulated account of iterative engagements among various stakeholders, narrates the metacognitive process of GRB.FindingsAmidst intercultural communication tensions that could have alienated efforts, Bamboo’s resourcefulness prompted positive stakeholder interactions. Interculturally relatable Bamboo culture could become an effective mode of communication via a synthesis of craft and construction to cultivate culturally intelligent behaviours.Research limitations/implicationsBamboo was a technology of community that overcame cultural tensions by completing an architectural product.Originality/valueDespite different languages, work ethics and uneasiness, this activism project sensitised differentiating perspectives to transform traditional knowledge hierarchies to negotiate local know-how. Hence, it highlights activism as a methodology for figuring out the unknown layered in spatial and aspatial attributes of material cultures.

Trade Network Resilience of the Global Photovoltaic Industry Chain

Based on the trade data of the global photovoltaic (PV) industry chain from 2005 to 2021, this paper constructs a global PV industry chain trade network model and analyzes its static resilience and dynamic resilience characteristics, reaching the following conclusions. The static resilience of the trade network is analyzed through aggregation, transmission, hierarchy and matching. The upstream polysilicon trade network is relatively loose, while the midstream and downstream trade networks appear to aggregate significantly. The average path length is short and the average clustering coefficient is high, indicating that the global PV industry chain trade network has high transmission efficiency and small-world characteristics. The global PV industry chain trade network is hierarchical. The degree distribution slope of the upstream polysilicon trade network is the largest and has a high level of hierarchy. Meanwhile, the global PV industry chain trade network is a heterogeneous network, which strengthens the connection between the core countries and edge countries, making the global PV industry chain trade network more resilient. Regarding the dynamic resilience of the trade network, the deterministic disturbance strategies have a greater impact on network performance than the random disturbance strategies, indicating that targeted impacts exert greater impact on the resilience of the global PV industry chain trade network. For the deterministic disturbance strategy, the interference based on intermediate centrality has a higher impact on the overall resilience of the network than the interference based on degree centrality, thus the influence of the country with strong trade radiating ability on the network elasticity is greater than that of the country with strong transit ability.

Methods to Enable Evolvable Digital Twins for Flexible Automated Production Systems

Changing requirements cause flexible automated Production Systems (aPS) to evolve over decades. Digital Twins (DT) of the different hierarchy levels and design steps ease this evolution, e.g., by enabling requirement analysis and compatibility checks ahead of any physical changes. To ensure up-to-date models and integrate additional knowledge, information gained during operation is included in DTs. Consequently, evolvability, decomposability, control software modularity, and learning during operation are identified as four requirements to achieve such evolvable DTs. Concepts to realize every requirement are introduced and exemplarily validated using a demonstrator machine. AutomationML (AML), the XML-based vendor neutral language for information modeling and exchange in between different disciplines and their tools and product classification systems like ECLASS that specify components attributes vendor neutral enable evolvability during the design phase. Decomposability is achieved by assembling DTs of components according to ISA 88 levels from control unit to facility. A control primitive concept that realizes control software modularity is introduced and validated. Based on data analytics and operation data the DT can be updated by using the versioning mechanism of AML. Thereby, the DT for the next machine generation is improved with knowledge from operation and represents the already existing machine more precisely.

Theoretical and Experimental Approaches to Study of Biological Objects by Mathematical Methods Using the Example of Hormone Production in the Thyroid Gland

The study of any biological object is a complex process that involves a number of successive stages, one of which tools can be a specially created expert system. It is advisable to present the conclusion about the studied biological object in clear forms of expression – quantitative or binary, which are the results of the practical application of the principles of absorption by some researched factors of others, a compromise between them or the prevailing alternative of the studied properties. The involvement of mathematical technologies in the identification and explanation of the regularities of the activity of biological objects requires the display of the results of their research using a mathematical language. This makes it possible to establish regularities in the course of biological processes and predict their consequences. Since any living system is formed from a large number of elements, the organism has a complex hierarchy of structural and functional levels of organization. A mandatory prerequisite for the activity of a biological system is a variety of states, each of them being characterized by its own characteristics – markers of change, which, according to the degree of completeness of the one state transformation into another, should be divided into markers of primary changes, markers of prevailing majority changes, and markers of final changes. Comprehensive application of the Semi-quantitative analysis of electronograms according to Ryabukha O. (2000) and her method for determining the profiles of hormonopoietic cells’ special capacities (2003) when studying the cytophysiology of the thyroid gland in normal and pathological conditions, it is possible to determine the specific link of the follicular cell’s specialized activity, in which there was a violation of hormonopoiesis, and to assess its intensity. The developed Conceptual apparatus of functional connections between organelles of hormone-producing cells when studying them by the Method of correlation analysis by creating intra- and intersystem correlation portraits reflects the features of mutual influences and interdependencies, which deepens the understanding of the intimate mechanisms of hormonopoiesis.

A clash of clans: an empirical study of conflicting institutional logics and their impact on megaproject collaboration

PurposeManaging megaprojects is challenging due to their inherent complexity and uncertainty. Collaborative project delivery models have been introduced as an alternative to traditional project management in public infrastructure megaprojects and are often realized through collaborative contracts. These project organizations act as institutional arenas for logic interaction as actors with differing institutional backgrounds interact within the project. This paper aims to study the delivery phase of three megaprojects through an institutional lens, investigating the institutional interaction and alignment of logics therein.Design/methodology/approachA multiple case study was employed to reach deep insight into the phenomenon. Sixty-one interviews were conducted over 3 cases with representatives from all levels of the project hierarchy. Respondents were selected through snowball sampling. In two cases, observations of the shared project office were conducted. Data analysis built on first-order codes and second-order themes, collected into a theoretical framework.FindingsThe empirical evidence demonstrates the dynamics shaping institutional logics and gives evidence for changing logics in projects with a well-applied collaborative contract. However, there is a risk of resistance and a return to traditional logics since institutional change is slow and an unsuitably applied collaborative contract can lead to adherence to the conventional way of work.Originality/valueCurrent research has focused on the regulatory framework and procurement phase of such models, but little attention has been given to the delivery phase and the interaction of conflicting logics. This paper can serve as an exemplar of the different logics found within public infrastructure projects and their interaction and alignment. Contributions include a heightened emphasis on the start of the project as a meeting point for differing institutional logics and the role change necessary when using a collaborative contract.

Measuring attentional selection of object categories using hierarchical frequency tagging.

In the present study, we used Hierarchical Frequency Tagging (Gordon etal., 2017) to investigate in electroencephalography how different levels of the neural processing hierarchy interact with category-selective attention during visual object recognition. We constructed stimulus sequences of cyclic wavelet scrambled face and house stimuli at two different frequencies (f1 = 0.8Hz and f2 = 1Hz). For each trial, two stimulus sequences of different frequencies were superimposed and additionally augmented by a sinusoidal contrast modulation with f3 = 12.5Hz. This allowed us to simultaneously assess higher level processing using semantic wavelet-induced frequency-tagging (SWIFT) and processing in earlier visual levels using steady-state visually evoked potentials (SSVEPs), along with their intermodulation (IM) components. To investigate the category specificity of the SWIFT signal, we manipulated the category congruence between target and distractor by superimposing two sequences containing stimuli from the same or different object categories. Participants attended to one stimulus (target) and ignored the other (distractor). Our results showed successful tagging of different levels of the cortical hierarchy. Using linear mixed-effects modeling, we detected different attentional modulation effects on lower versus higher processing levels. SWIFT and IM components were substantially increased for target versus distractor stimuli, reflecting attentional selection of the target stimuli. In addition, distractor stimuli from the same category as targets elicited stronger SWIFT signals than distractor stimuli from a different category indicating category-selective attention. In contrast, for IM components, this category-selective attention effect was largely absent, indicating that IM components probably reflect more stimulus-specific processing.

Awareness of system strategies and their implementation

The aim of this study is to determine the recognition and awareness of systemic strategies within the realm of practical business operations at three different levels of the organizational hierarchy. Two research hypotheses have been formulated. H1: The implemented strategy will be described as systemic. H2: Employees will assert the implementation of strategies through a systemic approach. The hypotheses were tested using a questionnaire survey administered to a convenience sample of postgraduate/post-diploma working students associated with sales functions. The survey included 1,400 respondents, divided into a pre-pandemic sample of 1,050 individuals and a post-pandemic sample of 350 individuals. A combination of traditional paper questionnaires and computer-assisted telephone interviews (CATI) was used to collect responses. The analysis of the survey responses reveals that the respondents from both the 2019 and 2022 cohorts do not affirm the existence of systemic strategies within their respective organizations. Furthermore, they do not claim that these strategies are implemented from a systemic perspective.

Systems Engineering roles to handle emergent properties and behaviors in complex technical systems

AbstractEngineering projects for complex technical systems such as automobiles demand extensive requirement specifications and corresponding hierarchy levels in system architectures. Especially when considering emergent phenomena, such as total weight or aerodynamics, a closely networked collaboration of discipline‐specific and cross‐disciplinary roles is required. Further, in large organizations with a group structure, resulting functional and non‐functional contents need to be managed by distinct Systems Engineering roles. For example, the role “property manager” takes care of achieving overarching product properties, such as weight or aerodynamics, which cannot be directly fixed, but result from many specifications. This paper proposes new Systems Engineering roles and their application in a German Original Equipment Manufacturer (OEM). For validation, the roles have already been applied in everyday engineering projects at the OEM. The concept proved to be indispensable and transferable to other Systems Engineering projects.