Hierarchical Dimension Research Articles

Lessening The Cost of Whistleblowing Through Hierarchy Peer-Reporting Type: A Grid-Group Cultural Theory Perspective

Purpose – This study examines the moderating effect of peer-reporting type on the influence of microsocial ethical environment, anonymous reporting channel, and perceived personal cost on internal whistleblowing intentions.Methodology – This paper is an empirical study using accounting students at Trunojoyo Madura University and Bahaudin Mudhary University as respondents. By distributing an online questionnaire and using incidental sampling, 156 responses were obtained. WarpPLS software version 7.0 is used to test the hypotheses.Findings – Microsocial ethical environment and perceived personal costs have a significant effect on whistleblowing intentions. Anonymous reporting channel do not have a substantial impact on whistleblowing intentions. Peer-reporting type moderates the influence of anonymous reporting channel on whistleblowing intentions. Still, it does not significantly moderate the effect of microsocial ethical environment and the impact of perceived personal costs on whistleblowing intentions. This research also provides empirical evidence that the hierarchical dimension is a suitable policy to use to report wrongdoing among accounting students at Trunojoyo Madura University and Bahaudin Mudhary University who take forensic accounting courses.Originality – This study is among the earliest to investigate the moderation effect of peer-reporting type. A previous study based on grid-group cultural theory proposes peer-reporting type as one of the antecedents of whistleblowing intentions, albeit at the conceptual level. The present study tries to further develop this concept (peer-reporting type) as a moderating variable by transforming the peer-reporting type concept into a research instrument. Limititation/Implication – The peer-reporting type questionnaire in this research was created referring to the peer-reporting type concept proposed by the previous study. This instrument is based on the four-dimensional concept of grid-group cultural theory, which is still at the conceptual level. Therefore, the validity and reliability of this instrument need to be tested further through settings, respondents, and others research.

SELF TRANSCENDENCE: THE IDEALITY DIMENSIONS OF AL-ISLAM AND KEMUHAMMADIYAHAN LEARNING IMPACT IN MUHAMMADIYAH SCHOOL

The terms al-Islam and Kemuhammadiyahan used by Muhammadiyah schools for learning Islamic religious education are in line with the educational objectives contained in the national education law. Developing the potential of students to have religious spiritual strength is a concrete form of achievement to be realized through the implementation of education. This context has an equivalent to the hierarchy of self-transcendence which is the final level of Maslow's theory of needs. This qualitative-based research with a case study uses a content analysis model on student answers in the form of a description with 1 single question. Respondents used as many as 379 students in Muhammadiyah schools at the junior high school level. The results showed that 53 students' answers lead to a desire to achieve the hierarchical dimension of self-transcendence which is reflected in changes in behavior. Based on the results of the study, it can be concluded that in the perspective of students learning al-Islam to achieve the ideal dimension, namely self-transcendence.

Exogenous shock: hierarchical effect of the industrial entrepreneur confidence in the mist of the COVID-19 pandemic

PurposeIn the context of investment decisions, the intricate interplay between exogenous shocks and their influence on investor confidence significantly shapes their behaviors and, consequently, their outcomes. Investment decisions are influenced by uncertainties, exogenous shocks as well as the sentiments and confidence of investors, factors typically overlooked by decision-makers. This study will meticulously examine these multifaceted influences and discern their intricate hierarchical nuances in the sentiments of industrial entrepreneurs during the COVID-19 pandemic.Design/methodology/approachEmploying the robust framework of the generalized linear latent and mixed models (GLLAMM), this research will thoroughly investigate individual and group idiosyncrasies present in diverse data compilations. Additionally, it will delve deeply into the exogeneity of disturbances across different sectors and regions.FindingsRelevant insights gleaned from this research elucidate the adverse influence of exogenous forces, including pandemics and financial crises, on the confidence of industrial entrepreneurs. Furthermore, a significant discovery emerges in the regional analysis, revealing a notable homogeneity in the propagation patterns of industrial entrepreneurs' perceptions within the sectoral and regional context. This finding suggests a mitigation of regional effects in situations of global exogenous shocks.Originality/valueWithin the realm of academic inquiry, this study offers an innovative perspective in unveiling the intricate interaction between external shocks and their significant impacts on the sentiment of industrial entrepreneurs. Furthermore, the utilization of the robust GLLAMM captures the hierarchical dimension of this relationship, enhancing the precision of analyses. This approach provides a significant impetus for data-informed strategic directions.

Planning Hatvan: Urban Planning and Repression in One of Baia Mare’s Roma Neighbourhoods (1950-1989)

Abstract This paper starts from the premise that social space, the state space, is a socially productive territory characterized, among other things, by hierarchical social, economic and political relations. This hierarchical dimension of space comes to the fore when researching the urban marginalization of Roma people in Romania. The mechanisms of exclusion employed by the state against Roma groups are situated in a wide range of other policies, among which uneven territorial development ranks chief. As such, this paper seeks to analyse the junction between these processes. It asks the question: how did the process of urban planning reinforce the urban marginalization of Roma people during socialism in Baia Mare? In order to address this question, I mobilize the results of two years of archival research in the city of Baia Mare, coupled with the discursive analysis of this archival material. I perform a diachronic analysis of how Roma people were targeted by state practices of urban marginalization, such as stigmatization, criminalization and repression. I show how the policies of systematisation of Baia Mare shaped the territory of a particular neighbourhood – Hatvan, attempting to manage and control the Roma population there. Throughout the 1960s, Hatvan was considered a focal point for crime. This led to a large-scale plan to completely transform the area through evictions, demolitions and the displacement of Roma people. The result was a place that was seen as clean, ordered and lawful social space, which became what is currently known as the Vasile Alecsandri neighbourhood. However, this space continues to this day to be one of social marginalisation, economic deprivation and institutionalised racism.

Hairstyle transfer via manipulating decoupled latent codes of StyleGAN2

Hairstyle transfer aims to combine the hairstyle attributes of the reference images with the face and background of the identity image into one realistic image. This is challenging due to the differences in semantic structure between reference images and identity image, as well as the tangled hairstyle attributes. Existing GAN-based methods tend to simply combine image patches of hair, face, and background, which leads to discordant semantic structures and obvious artifacts in the results. And the GAN inversion-based methods require elaborate orthogonalization of loss gradients with additional calculations to alleviate the entanglement between the complex hairstyle attributes. To address these limitations, we propose a novel framework for hairstyle transfer based on StyleGAN inversion. Specifically, instead of simply combining the image patches, we use StyleGAN’s generative power to get more reasonable target semantic masks. During the alignment with the target masks, background inpainting is performed by StyleGAN rather than auxiliary models, which makes the results more realistic. Furthermore, our method decomposes hairstyle into three attributes: structure, texture, and color to better control the hairstyle transfer process. Besides, we observe that the spatial scales of these attributes match those of the StyleGAN’s latent codes. Then, we decouple the latent code in the hierarchical dimension and use different layers of the latent code to complete the transfer of different hair attributes, which reduces the entanglement between attributes without extra calculations. Correspondingly, our method divides hairstyle transfer into three steps, making the transfer process more controllable. By comparing with state-of-the-art methods, we verify the effectiveness of our method.

THE INTERPERSONAL RELATIONSHIP AND ORGANIZATIONAL COMMITMENT OF PUBLIC ELEMENTARY SCHOOL TEACHERS OF CANDELARIA WEST DISTRICT

This study was conducted to determine the interpersonal dimension and its relationship to the organizational commitment of teachers in selected public schools in Candelaria West District. The subjects of study were ninety-two (92) teachers from the selected public elementary schools in Candelaria West District for the academic year. 2022-2023. This study was a descriptive method and utilized and adapted questionnaire on the level of the dimension of interpersonal relationship such as cooperative vs. competitive dimension, equal vs. hierarchical dimension, intense vs. superficial dimension and the level of organizational commitment such as affective commitment, continuance commitment and normative commitment. The gathered data were analysed using mean, standard deviation and Pearson product moment correlation. This study revealed the following findings: the perception regarding the level of interpersonal relationship is ‘very high’ in all three variables in terms of improving their connection: cooperative, equal and intense. Also, the level of organizational commitment is ‘very high’ in all three variables in terms of improving their connection within the organization: affective, continuance and normative. The findings of this study will be useful to teachers, school’s administrator, the people who work in organizations, and other researchers. The study hereby offers the following recommendations: teachers may continue this kind of interaction within their organization to create and continue a good relationship and to be committed: treating the other members of the organization equally, having interaction, cooperation, working together, and enjoying each other is a good thing to do.

Disinformation a problem for democracy: profiling and risks of consensus manipulation.

The aims of this article is to analyze in the post-pandemic era of technological wars how platformisation and the opacity that characterizes it can generate manipulative effects on the dynamics of consensus building. We are now in the era of the self-informative program; the hierarchical dimension of sources has vanished in parallel to the collapse of the authority, credibility, and trustworthiness of classical sources. Now, the user creates his own informative program, which gives rise to a new relationship between digital individuals. With this framework in mind, I intend to analyze the narrative of this post-pandemic phase proposed by mainstream media, using the tool of the fake news hexagon, to verify the impact and spread of fake news through social networks where emotionalism, hate speech, and polarization are accentuated. In fact, the definition of the fake news hexagon was the starting point to study through a predefined method the dynamics of proliferation of fake news to activate correct identification and blocking tools, in line with what is defined in the Digital Transformation Institute's manifesto. Platforms drive the process of identity construction within containers that adapt to the demands of individuals, leading toward a flattening out of results from web searches as these follow the principle of confirmation bias. We assist to an increasing lack of recognition of the other, the individual moves away from commitment, sacrifice, and achieving a higher collective good. It becomes quite evident how, in the face of the collapse of authority, as this new dimension takes hold, the understanding of reality and the construction of public identity can no longer be the result of the ability to decipher messages alone. Media and social multidimensionality necessitate developing new interpretive processes.

Hierarchical time-series analysis of dynamic bioprocess systems.

Monoclonal antibodies (mAbs) are leading types of 'blockbuster' biotherapeutics worldwide; they have been successfully used to treat various cancers and chronic inflammatory and autoimmune diseases. Biotherapeutics process development and manufacturing are complicated due to lack of understanding the factors that impact cell productivity and product quality attributes. Understanding complex interactions between cells, media, and process parameters on the molecular level is essential to bring biomanufacturing to the next level. This can be achieved by analyzing cell culture metabolic levels connected to vital process parameters like viable cell density (VCD). However, VCD and metabolic profiles are dynamic parameters and inherently correlated with time, leading to a significant correlation without actual causality. Many time-series methods deal with such issues. However, with metabolic profiling, the number of measured variables vastly exceeds the number of experiments, making most of existing methods ill-suited and hard to interpret. Here we propose an alternative workflow using hierarchical dimension reduction to visualize and interpret the relation between evolution of metabolic profiles and dynamic process parameters. The first step of proposed method is focused on finding predictive relation between metabolic profiles and process parameter at all time points using OPLS regression. For each time point, the p(corr) obtained from OPLS model is considered as a differential metabogram and is further assessed using principal components analysis (PCA). Compared to traditional batch modeling, applying proposed methodology on metabolic data from Chinese Hamster Ovary (CHO) antibody production characterized the dynamic relation between metabolic profiles and critical process parameters.

“Thy Words Do Finde Me Out”: Aaron Kunin’s Love Three

“Thy Words Do Finde Me Out”: Aaron Kunin’s <i>Love Three</i>

Bottom-up synthesis strategy of a two-dimensional {Fe5} cluster-based coordination polymer: stepwise formation of a {Fe5} cluster and its dimension augmentation

A 2D cluster-based coordination polymer of {Fe5}-2D was developed by hierarchical dimension augmentation from its 1D coordination polymer of {Fe5}-1D and discrete 0D cluster of {Fe5}-0D. And a possible bottom-up synthesis mechanism was proposed.

Smart-Meter Big Data for Load Forecasting: An Alternative Approach to Clustering

Accurate forecasting of electricity demand is vital to the resilient management of energy systems. Recent efforts in harnessing smart-meter data to improve forecasting accuracy have primarily centered around cluster-based approaches (CBAs), where smart-meter data are grouped into a small number of clusters and separate prediction models are developed for each cluster. The cluster-based predictions are then aggregated to compute the total demand. CBAs have provided promising results compared to conventional approaches that are generally not conducive to integrating smart-meter data. However, CBAs are computationally costly and suffer from the curse of dimensionality, especially under scenarios involving smart-meter data from millions of customers. In this work, we propose an efficient reduced model approach (RMA) that leverages a novel hierarchical dimension reduction algorithm to enable the integration of fine-resolution high-dimensional smart-meter data for millions of customers in load prediction. We demonstrate the applicability of our proposed approach by using data from a utility company, based in Illinois, United States, with more than 3.7 million customers and present model performance in-terms of forecast accuracy. The proposed hierarchical dimension reduction approach enables utilizing the high-resolution data from smart-meters in a scalable manner that is not exploitable otherwise. The results shows significant improvements in forecast accuracy compared to the available approaches that either do not harness fine-resolution data or are not scalable to large-scale smart-meter big data.

Syntactic Complexity of Different Text Types: From the Perspective of Dependency Distance Both Linearly and Hierarchically

ABSTRACT Dependency distance (DD) is a well-established measure of syntactic complexity. Previous studies largely focused on the linear dimension, mostly by mean of dependency distance (MDD). In the present study, a new quantitative indicator –mean hierarchical dependency distance (MHDD), is proposed to discuss DD-related issues. Combining MHDD and MDD, the study investigates syntactic complexity of different texts, using strictly length-controlled sentences of 12 text types from the Freiburg-Brown corpus of American English. Correlations of MHDD and MDD have been identified, and possible reasons are discussed from the mathematical and theoretical perspectives.Mathematically, one is that the numerator of MHDD overlaps with the denominator of MDD, both being (n-1) where n is the number of words in the sentence. The other is that the denominator of MHDD (maximum hierarchical layer: MAXHL) and the numerator of MDD (sum of DD: SOD), are positively correlated. We believe that it is the positive correlation of SOD and MAXHL that ensures the change of MDD and MHDD in the same direction. It is also worth noting that both MAXHL and SOD seem to be minimized at their respective data spectrum, which foreshadows the dependency distance minimization (DDM) tendency on the hierarchical dimension.

The Neuropsychology of Emotion and Emotion Regulation: The Role of Laterality and Hierarchy.

Over the last few decades, work in affective neuroscience has increasingly investigated the neural basis of emotion. A central debate in the field, when studying individuals with brain damage, has been whether emotional processes are lateralized or not. This review aims to expand this debate, by considering the need to include a hierarchical dimension to the problem. The historical journey of the diverse literature is presented, particularly focusing on the need to develop a research program that explores the neural basis of a wide range of emotional processes (perception, expression, experience, regulation, decision making, etc.), and also its relation to lateralized cortical and deep-subcortical brain structures. Of especial interest is the study of the interaction between emotional components; for example, between emotion generation and emotion regulation. Finally, emerging evidence from lesion studies is presented regarding the neural basis of emotion-regulation strategies, for which the issue of laterality seems most relevant. It is proposed that, because emotion-regulation strategies are complex higher-order cognitive processes, the question appears to be not the lateralization of the entire emotional process, but the lateralization of the specific cognitive tools we use to manage our feelings, in a range of different ways.

Do Preschoolers Align Their Preferences With Those of a Powerful Individual?

Very early on, children understand the hierarchical dimension of the social environment and use a variety of cues to guess who has more power in an interaction. A crucial aspect of power perception lies in the evaluation of high-power and low-power individuals. The current study examined the evaluation of power by preschoolers through social influence. Past research has shown that preschoolers take social category information into account when expressing their preferences. In particular, they tend align their preferences with those of same-gender and same-age individuals. In the current study, 4- and 5-year-old children were presented with a power interaction between two children through body postures and were asked whether they would prefer the same items as those preferred by the high-power child or those preferred by the low-power child. Overall, the participants did not choose the items preferred by the high-power child significantly more often than those preferred by the low-power child. However, unexpected gender effects were found and indicated that the power asymmetry influenced more male than female participants. Indeed, when they saw a power interaction between two boys (Experiments 1 and 2), male participants aligned their choices with those of the high-power boy more than with those of the low-power boy. However, when male participants saw an interaction between two girls (Experiment 3), an opposite pattern was observed: they aligned their choices with those of the low-power girl more than with those of the high-power girl. In contrast, in the three experiments, there were approximately as many girls who aligned their preferences with those of the high-power child as there were girls who aligned their preferences with those of the low-power child. The current study reveals the importance of taking gender into account, both at the level of participants and stimuli, in the evaluation of power by preschoolers.

SPATIAL MODELLING OF URBAN GROWTH AND URBAN INFLUENCE: APPROACH OF REGIONAL DEVELOPMENT IN DEVELOPING ECONOMY (INDIA)

Urbanization and regional development are closely associated. Allocation of higher and lower order facilities and specialization of business influence urban growth which diffuses its benefits to the surrounding countryside. Subsequently, socio-economic development of the region comes into being. The continuous increase of urban size can not be sustained rather declining growth will certainly set in long run. Optimum level of its growth depends on the capacity of an urban centre to provide required facilities to the people in fair manner. Hierarchical growth of urban centres in association with location of civic amenities induces regional development in hierarchical dimension which is the common problem in developing economy. Subsequently, few of the urban centres are having large number of facilities while others are lacking corresponding to their population size. Formulation of pragmatic planning model is the rescue of wiping out such problems. It is an attempt to analyze the hierarchical growth of urban centres associated with their functional potentiality and diffusion of urban developmental impulses to the surrounding rural part. Further, it proposes a model for developing economy like India to solve the problem of regional variations of development. Besides, it examines the adequacy and inadequacy of facilities in the urban centres and puts forward planning recommendations, so that a balanced regional development would be achieved by not leaving any rural part out of the zone of functional influence of urban centre.

Design of Guangdong E-commerce Park Performance Evaluation System Based on Computer-aided Technology

In recent years, the development of e-commerce parks economy has become an important measure of industrial restructuring in many places in China, therefore it is of great significance to strengthen the optimization of the evaluation system of e-commerce parks. This paper puts forward the problems in existing evaluation system of Guangdong E-commerce Park based on computer-aided technology, and in view of these problems, optimizes the original performance evaluation system from the aspects of identifying, judging key stakeholders and optimizing the hierarchical dimension of the evaluation system, and illustrates the rationality and operability of the optimization method of the performance evaluation system.

Exploration of the paranoia hierarchy in the general population: evidence of an age effect mediated by maladaptive emotion regulation strategies

ABSTRACT Introduction: Positive psychotic symptoms are suggested to be more prevalent in early adulthood. However, no previous study has examined a potential age effect especially for paranoia considering social reference and persecution as separated hierarchical dimension. Moreover, no previous study has examined the mechanisms involved in the decrease of paranoia with age. This study aims to explore (1) the age effect on paranoia and (2) whether the age effect is mediated by maladaptive emotion regulation strategies (MERS). Methods: A sample of 1644 participants from the general population completed the Green et al., Paranoid Thoughts Scale with measures of MERS and was split into three age groups (18–29; 30–54; 55–82). Results: Age groups comparisons revealed a significant decrease of social reference with age but not of persecution. Mediation analyses indicated that this age effect was partially mediated by MERS. Additional analyses suggested that social reference moderated the relation between age and persecution. Conclusions: The present study showed that social reference and persecution are not equally affected by age and that MERS are important factors to consider when trying to understand the nature of paranoia. Finally, a younger age and the use of MERS are suggested to be risk factors for developing paranoia.

Dimension Reduction Based Non-Parametric Disaggregation for Dependence Modeling in Composite System Reliability Evaluation

The correlated variation of bus loads and wind powers has posed a challenge to power system security. How to construct an accurate dependence model becomes vital for power system reliability evaluation. Most currently used methods in estimating the multivariate probability density function (PDF) not only ignore the aggregation constraint but also encounter the curse of dimensionality. In this paper, a new non-parametric disaggregation (ND) technique is presented to disaggregate an aggregate variable (e.g. system load) into non-aggregate variables (e.g. bus loads) while meeting the aggregation constraint. An innovative hierarchical dimension reduction technique is proposed and integrated into the ND model to transform a high-dimensional conditional PDF estimation into some low-dimensional estimations, which effectively resolves the difficulty associated with high dimensionality. The above two techniques are incorporated into an effective three-stage conditional sampling method to form the proposed dimension reduction based ND model (DRND) for high-dimensional dependence modeling in composite system reliability evaluation. The validity of the proposed DRND is verified by three test systems, i.e. MRTS79, MRTS96, and the latest RTS-GMLC.

Some notes on language, memory and bilingualism

In this commentary on the Special Issue, I will address the question of what memory spans measure concerning language, as language has, at least, a linear and a hierarchical dimension. I suggest that if anything what is measured has to do with the linear dimension. Then, I will discuss the welcome results on bilingual children with language problems and reflect on what it means that working memory measures seem to be more relevant for bilingual children than for monolingual ones. I will tentatively suggest that what is at stake is not memory per se, but inhibitory skills.

Naming oneself in the social mirror: A vignette-based survey

In order to understand the way in which people self-identify in society and as a contribution to debates about class identity in Latin America, in this article the authors assess how individuals categorize themselves and others socially, and discuss whether a significant portion of the population classifies itself as middle class. They address the question of whether or not individuals’ representation of their social position is linked to social class, examining whether that position incorporates a socio-economic dimension, a hierarchical dimension, or even an element of moral value. The authors focus on how individuals name their own social position by means of a vignette-based survey applied in 2016 to a randomized sample of 2000 people in Chile. The results show that the theoretical notion of class is still of relevance to subjective positioning criteria, and that such criteria are specific to individuals who self-identify with lower or higher social positions.