Hierarchical Relationships Research Articles

An integrated ISM fuzzy MICMAC approach for unfolding the digital servitization implementation

PurposeThis paper aims to identify the interrelationships among critical factors for digital servitization (DS) implementation.Design/methodology/approachA multi-method research was used. Critical factors for a successful DS implementation were identified using a systematic literature review and expert interviews. The interpretive structural modeling (ISM) method was used to develop a hierarchical model of the identified factors, followed by the fuzzy Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis to assess their dependence and driving powers.FindingsA total of 23 factors for DS implementation were identified, and the ISM model was developed. Based on MICMAC analysis, the factors were also grouped under four categories (dependent, driving, autonomous and linkage). A conceptual framework is proposed, highlighting that DS implementation relies on three main layers of critical factors: crafting alignment, scaling the change and achieving results.Originality/valueThe ISM and fuzzy MICMAC methods used in this study provided valuable insights into the interrelationship among the identified DS factors through a conceptual framework. To the best of the authors’ knowledge, the study is one of the first to identify critical factors influencing DS implementation and develop hierarchical relationships among them.

A Formal Concept Analysis approach to hierarchical description of malware threats

The problem of intelligent malware detection has become increasingly relevant in the industry, as there has been an explosion in the diversity of threats and attacks that affect not only small users, but also large organisations and governments. One of the problems in this field is the lack of homogenisation or standardisation in the nomenclature used by different antivirus programs for different malware threats. The lack of a clear definition of what a category is and how it relates to individual threats makes it difficult to share data and extract common information from multiple antivirus programs. Therefore, efforts to create a common naming convention and hierarchy for malware are important to improve collaboration and information sharing in this field.Our approach uses as a tool the methods of Formal Concept Analysis (FCA) to model and attempt to solve this problem. FCA is an algebraic framework able to discover useful knowledge in the form of a concept lattice and implications relating to the detection and diagnosis of suspicious files and threats. The knowledge extracted using this mathematical tool illustrates how formal methods can help prevent new threats and attacks. We will show the results of applying the proposed methodology to the identification of hierarchical relationships between malware.

Ideological attitudes predicting online hate speech: the differential effects of right-wing authoritarianism and social dominance orientation

IntroductionWhile research on online hate speech (OHS) has expanded in recent years, only few studies adopt a theoretical framework to understand how ideological attitudes differentially motivate individuals to engage with OHS. Drawing on the dual-process motivational model of ideology and on previous political psychological research on OHS, this study examines how individual levels of social dominance orientation (SDO) and right-wing authoritarianism (RWA) predict the likelihood of producing OHS for online platforms users.MethodsWe used logistic regressions to analyze the survey data from a representative German sample of social media platform users (N = 7,349).ResultsThe analyses indicate that SDO is related with higher odds of producing OHS, while RWA is related with lower odds. After adjusting for socio-economic factors and controlling for alternative predictors, the odd ratios remain significant, indicating that these two ideological attitudes predict online hate speech in different directions.DiscussionThe results show that high-RWA individuals are less likely to engage with OHS, which is explained through their conservative motivation to conform to social norms and maintain social stability. High-SDO individuals are more likely to produce OHS and may use it following their competitive motivation to increase hierarchical relations and improve their social status within society. The findings are discussed taking into consideration the specificities of the German social context, and corroborate and expand previous research. From these subtle but crucial differential effects, relevant implications are drawn for the platform as well as for social and political levels.

You might want to tone down your advice: An experimental investigation of the speech act of advice in French

AbstractWe present experimental results from a web-based study on the speech act of giving advice in French. 86 L1 speakers of French had to continue short and written fictitious interactions we created, in which we manipulated the adviser’s level of experience (explicitly experienced, explicitly inexperienced, or no precision) and the hierarchical relationship between adviser and advisee (top-down, bottom-up, and equals). Participants had to choose between four types of continuations, from indirect strategies to direct prototypical imperative strategies, with variations of the face-threatening value in some continuations, as per Brown and Levinson’s politeness theory. Main results from Bayesian regression analyses indicate an overall preference for indirect strategies in French, but also suggest influences from the level of experience and hierarchical relationship. These results will allow for a better understanding of advice as a speech act and contribute to a growing body of work in experimental pragmatics.

Probability map-based grape detection and counting

Grape-cluster detection, grape-berry counting, and berry-per-grape-cluster counting are the three major tasks in digital viticulture. Although the detection of clusters and berries was treated as separate tasks in previous studies, due to the clustered nature of the grape phenotype and the close hierarchical spatial distribution relationship between grape clusters and berries, those three tasks should be considered at the same time in our view; further, we define these tasks as subtasks of the grape detection and counting task. The major challenge of combining the three subtasks of grape detection and counting together is how to obtain the detection results of those subtasks from the output of a single neural network. To address this issue, we propose a Probability Map-based Grape Detection and Counting framework that first detects two intermediate probability maps through a neural network and utilizes three postprocessing stages to finish the three grape detection and counting subtasks sequentially. After being trained and validated on the trainval set of WGISD, combining 100 extra images collected in Chengdu by our team, the proposed framework is tested on the test set of WGISD to verify its performance. The proposed framework achieves a localization performance of average precision (AP)(iou0.5) 0.851 and a counting performance of MAE 1.845, RMSE 2.142 for grape clusters, a counting performance of MAE 23.414, RMSE 31.391 for grape berries, and a counting performance of MRD 0.142, 1-FVU 0.865 for berries per grape cluster on the test set of WGISD. Our source code will be publicly available athttps://github.com/volcanoYcc/Probability-Map-based-Grape-Detection-and-Counting.

Syntaxonomical Remarks on the Garrigues from Apulia (S Italy) and Neighboring Territories.

In this study, the garrigues occurring in Apulia and neighboring territories (southern Italy) were surveyed in order to clarify their syntaxonomical arrangement. Many contributions previously focused on this vegetation type, often adopting different and sometimes contrasting treatments from both the nomenclature and syntaxonomical aspects. Our investigations are supported by the multivariate analysis of a dataset containing 292 phytosociological relevés, whose resulting cluster dendrogram highlights the hierarchical relationships between the examined plant communities. Overall, twenty-one associations with several sub-associations were recognized. Some of them are already known in the literature, whereas others are described here for the first time. As concerns the syntaxonomical framework, this vegetation is attributable to the class Cisto cretici-Micromerietea julianae, which in this territory is represented by the order Cisto eriocephali-Ericetalia manipuliflorae and by two alliances: Cisto eriocephali-Ericion multiflorae, grouping the more thermophilous associations usually distributed along coastlines and at low altitudes; and Cytiso spinescentis-Saturejion montanae, including the mesophilic associations occurring in mountain and sub-mountain belts.

Three-way decision based on three-way preference measures and three-level dominance relations in interval-valued systems

Interval-valued systems facilitate data decision, and their preference measures and dominance relations become pivotal for three-way decision (3WD). However, the recent D-type preference measure and partial-overall dominance relation between intervals respectively exhibit the weak representation and incomplete hierarchy, so corresponding results need further development. Aiming at interval-valued systems, an S-type measure is proposed to constitute three-way preference measures, and three-level dominance relations are established, so criss-cross knowledge granulations motivate systematic 3WD models and applications. First, the S-type preference measure is proposed from the sigmoid function, it exhibits good learning semantics and mathematical properties, and its supplementation and improvement induce three-way preference measures. Then, by three-level constructions, three-way preference measures are applied for sorting and classification, and the S-type measure exhibits decision effectiveness and recognition superiority. Furthermore, hierarchical three-way preference measures induce three-level dominance relations, and vertical-horizontal condition granulations generate multiple 3WD models on preference decision classes. Finally, all 3WD strategies from criss-cross dominance relations are comprehensively compared and selected via classification error rates; by data experiments, the S-type measure and its hierarchical relations become effective and optimal for 3WD, and the corresponding 3WD approaches outperform the existing methods from the D-type measure and partial-overall relation.

Nitric oxide contributes to rapid sclerostin protein loss following mechanical load

In response to mechanical loading of bone, osteocytes produce nitric oxide (NO•) and decrease sclerostin protein expression, leading to an increase in bone mass. However, it is unclear whether NO• production and sclerostin protein loss are mechanistically linked, and, if so, the nature of their hierarchical relationship within an established mechano-transduction pathway. Prior work showed that following fluid-shear stress (FSS), osteocytes produce NOX2-derived reactive oxygen species, inducing calcium (Ca2+) influx. Increased intracellular Ca2+ results in calcium-calmodulin dependent protein kinase II (CaMKII) activation, which regulates the lysosomal degradation of sclerostin protein. Here, we extend our discoveries, identifying NO• as a regulator of sclerostin degradation downstream of mechano-activated CaMKII.Pharmacological inhibition of nitric oxide synthase (NOS) activity in Ocy454 osteocyte-like cells prevented FSS-induced sclerostin protein loss. Conversely, short-term treatment with a NO• donor in Ocy454 cells or isolated murine long bones was sufficient to induce the rapid decrease in sclerostin protein abundance, independent of changes in Sost gene expression. Ocy454 cells express all three NOS genes, and transfection with siRNAs targeting eNOS/Nos3 was sufficient to prevent FSS-induced loss of sclerostin protein, while siRNAs targeting iNOS/Nos2 mildly blunted the loss of sclerostin but did not reach statistical significance. Similarly, siRNAs targeting both eNOS/Nos3 and iNOS/Nos2 prevented FSS-induced NO• production. Together, these data show iNOS/Nos2 and eNOS/Nos3 are the primary producers of FSS-dependent NO•, and that NO• is necessary and sufficient for sclerostin protein control.Further, selective inhibition of elements within this sclerostin-controlling mechano-transduction pathway indicated that NO• production occurs downstream of CaMKII activation. Targeting Camk2d and Camk2g with siRNA in Ocy454 cells prevented NO• production following FSS, indicating that CaMKII is needed for NO• production. However, NO• donation (1min) resulted in a significant increase in CaMKII activation, suggesting that NO• may have the ability to tune CaMKII response. Together, these data support that CaMKII is necessary for, and may be modulated by NO•, and that the interaction of these two signals is involved in the control of sclerostin protein abundance, consistent with a role in bone anabolic responses.

Virtual tourism attributes in cultural heritage: Benefits and values

The rapid development of virtual tourism is an opportunity for cultural heritage sites. This study combines the means-end chain theory with the Kano model to explore cultural heritage sites' virtual tourism attributes, benefits, and values. We obtained 29 attributes, 23 benefits, and 14 values of virtual tourism, then discussed the hierarchical relationship among the attributes, benefits, and values. Also, the 29 attributes were classified according to their impact on user satisfaction. The results show that virtual tourism attributes can be divided into four aspects. In addition to the technical attributes, people often attach more importance to the content attributes as their basic requirements. Convenience is the core value of virtual tourism, followed by learning, entertainment, immersion, uniqueness, the sense of novelty,comfort and the sense of participation. It expands and deepens the theoretical framework of virtual tourism and provides theoretical guidance for developing and marketing virtual tourism products/services in cultural heritage sites.

Document-level biomedical relation extraction via hierarchical tree graph and relation segmentation module.

Biomedical relation extraction at the document level (Bio-DocRE) involves extracting relation instances from biomedical texts that span multiple sentences, often containing various entity concepts such as genes, diseases, chemicals, variants, etc. Currently, this task is usually implemented based on graphs or transformers. However, most work directly models entity features to relation prediction, ignoring the effectiveness of entity pair information as an intermediate state for relation prediction. In this article, we decouple this task into a three-stage process to capture sufficient information for improving relation prediction. We propose an innovative framework HTGRS for Bio-DocRE, which constructs a hierarchical tree graph (HTG) to integrate key information sources in the document, achieving relation reasoning based on entity. In addition, inspired by the idea of semantic segmentation, we conceptualize the task as a table-filling problem and develop a relation segmentation (RS) module to enhance relation reasoning based on the entity pair. Extensive experiments on three datasets show that the proposed framework outperforms the state-of-the-art methods and achieves superior performance. Our source code is available at https://github.com/passengeryjy/HTGRS.

The Socio-Environmental Determinants of Childhood Malnutrition: A Spatial and Hierarchical Analysis.

Despite a remarkable reduction in global poverty and famines, substantial childhood malnutrition continues to persist. In 2017, over 50 million and 150 million young children suffered from acute malnutrition (wasting) and chronic malnutrition (stunting), respectively. Yet, the measurable impact of determinants is obscure. We evaluate proposed socio-environmental related determinants of stunting and wasting across Kenya and Nigeria and quantify their effectiveness. We combine health and demographic data from Kenya and Nigeria Demographic Health Surveys (2003, 2008-2009, 2013, 2014) with spatially explicit precipitation, temperature, and vegetation data. Geospatial and disaggregated data help to understand better who is at risk and where to target mitigation efforts. We evaluate the responsiveness of malnutrition indicators using a four-level random intercept hierarchical generalized logit model. We find that spatial and hierarchical relationships explain 28% to 36% of malnutrition outcome variation. Temporal variation in precipitation, temperature, and vegetation corresponds with more than a 50% change in malnutrition rates. Wasting is most impacted by mother's education, family wealth, clinical delivery, and vaccinations. Stunting is most impacted by family wealth, mother's education, clinical delivery, vaccinations, and children asymptomatic of fever, cough, or diarrhea. Remotely monitored climatic variables are powerful determinants, however, their effects are inconsistent across different indicators and locations.

A data-driven short video international communication model based on indicator system communication network and attention BiLSTM neural network

As one of the most popular ways to disseminate Internet content in the current era of media convergence, short videos have increasingly become part of people’s daily lives. This paper takes TikTok as the research object, focusing on the study of short video communication process. The research objective of this paper is to improve the international communication effect of short videos through data-driven analysis and strategy research on the law of international communication of short videos. Firstly, the key objective indicator system about international communication of short videos is constructed, the definition, selection and design logic of key objective indicators are introduced, the construction idea of the corresponding indicator system is proposed, and then the key objective indicator system about international communication of short videos and related data set are constructed. Secondly, an international communication network model for short videos is built. The construction of this network model is divided into three steps, the construction of the short video communication network KOIS-PN based on the key objective indicators system, the construction of AT-BiLSTM neural network model to adapt to the research scenario of short video international communication, the construction of an international communication network model of short videos combining KOIS-PN and AT-BiLSTM. The international short video communication network is constructed according to the key objective index system of international short video, and the key objective index system is used as nodes in the communication network, and the short video communication network is constructed by hierarchical relationship. Thirdly, the performance of the core theoretical model proposed in this paper is verified. The experimental results show that, the KOISPN-ATBiLSTM international communication network model of short videos has certain validity and advancement.

The order characteristics of daily life space in Chinese urban communities--a case of Ningbo Green Axis Sports Park

This paper explores the order characteristics of urban daily life spaces in China through ethnographic studies and field research data, with a focus on Ningbo Green Axis Sports Park. The study identifies four key characteristics of urban community daily life spaces: hierarchical "bounded space", rhythmic temporality, physical embodiment, and habitual occupation. In Chinese urban contexts, the delineation between work and life proves challenging, intertwining hierarchical relationships among neighbors and colleagues within public spaces, thereby forming a structured hierarchy of subcultural groups.Individuals engage with colleagues, neighbors, and diverse individuals within daily life spaces to negotiate identity and hierarchy, thereby shaping the social space of the subject through public interactions. Our analysis posits that the orderliness of public spaces hinges upon empowerment and domain delineation; the preservation of order sustains the publicness, social connectivity, and interactive dynamics of such spaces. The tension between publicness and domain delineation may indeed serve as the linchpin of public space efficacy. Consequently, urban planning endeavors should prioritize the orderly attributes of public spaces and foster the development of human-centric urban environments.

Validation of the Japanese Version of the Modest Behavior Scale for Adults and Age and Gender Differences

AbstractSocial pressures, such as cultural norms of modesty, are thought to contribute to low self‐esteem in East Asians, and modesty is a key concept in understanding the feelings, thoughts, and social behaviors of this population. Modesty has been found to encompass three aspects: avoidance of attention‐seeking (AA), self‐effacement (SE), and other‐enhancement (OE). The current study validated the Modest Behavior Scale and examined age and gender differences in the three aspects of modesty in a sample of adults aged 20–69 years. A total of 400 Japanese individuals participated in the online survey. The results of hierarchical multiple regression analyses and simple slopes analyses revealed that older people tend not to seek attention but also not to devalue themselves, whereas younger people tend to devalue themselves but not to refrain from seeking attention. This implies that people in different age groups use different modesty strategies. In addition, gender differences were found in AA and OE. The age and gender differences in modesty were discussed in terms of hierarchical relationships and social role expectations.

Coloniality, Race, and Europeanness: Britain’s Borders after Brexit

Abstract The scholarship on the politics of immigration often frames governments’ responses to far-right mobilization as a return to border closures and a rowing back on neoliberalism. In this article, I draw on and expand the scholarship on coloniality to address the limitations of this diagnosis. Specifically, I explore the role of political mobilization in the making of the post-Brexit border regime. My research draws on the analysis of legal and policy initiatives between 2020 and 2023 and twenty-three research interviews with individuals who express their opposition to immigration via engagement in think tanks, grassroots organizations and vigilante groups. The interview data indicates multiple connections between these milieus and shows that each engages in action repertoires beyond the nation-state. And while this prompts border closures, the post-Brexit border regime also encodes openings and loopholes for the circulation of financial elites and precariously employed workers. Thus, I argue that state and non-state actors co-produce a neoliberal border regime of stratified rights, partial inclusions, and gradual exclusions. These variegated entitlements draw on and reinvigorate the racial order of coloniality. The post-Brexit immigration regime enables the free mobility of those racialized as “West European,” facilitates disposable labor mobility of those racialized as “Eastern European,” and restricts the movement of those racialized as “non-European.” This racial imaginary does not only operate via binary distinctions of (non)-Britishness but puts people in complex hierarchical relations to “Europeanness.”

Fostering cocoa industry resilience: A collaborative approach to managing farm gate price fluctuations in West Sulawesi, Indonesia

Abstract Agricultural price fluctuations impact the economy and society, highlighting the importance of price stability for sustainable development, poverty alleviation, food security, and economic stability. This issue is particularly pronounced in the cocoa industry, where volatile prices and inefficient supply chains often harm the livelihoods of cocoa farmers. This study aimed to develop a mitigation plan to address cocoa price volatility at the farm level. The study was conducted in Tubbi Taramanu Sub-district, Polewali Mandar District, Indonesia. Through the innovative use of Interpretative Structural Modeling (ISM), the key elements are delineated in their hierarchical relationships and categorized into four quadrants: autonomous, independent, dependent, and linkage, to formulate a strategy for stabilizing cocoa prices at the farm level. This research’s findings underscored the importance of reducing farmers’ dependency on middlemen as the primary strategy for mitigating fluctuations in cocoa bean prices at the farm level. This approach is particularly vital due to the excessive reliance on middlemen, a key driver of price instability at the farm level. Furthermore, it is evident that promoting and nurturing cooperation between farmers and cocoa industry stakeholders can prove highly effective and significant when fortified by the local government’s support through the implementation of appropriate public policies.

Who's leading whom? Mutual influences in moral decision-making between leaders and subordinates over time and the role of self-interest

Ethical behavior within groups is shaped by various situational and social factors, including hierarchy and power asymmetries. We present three preregistered studies (Ntotal = 1253) examining the social dynamics that affect ethical decision-making in hierarchical dyads, employing two novel collaborative cheating tasks. In the first two studies, we find evidence that individuals mutually influenced each other's honesty across repeated interactions, even though they had different power over the outcomes. In addition, the degree and direction of these influences were moderated by the ethical make-up of these dyads. Moreover, there were congruency effects for character judgments, wherein dyads engaging in collaborative cheating behaviors tended to evaluate each other positively, particularly in terms of competence and closeness. In a third study, manipulating whether ignoring cheating is beneficial to an observer or not, we find that observers were less inclined to verify (vs. rely on) potentially dishonest reports when they themselves benefitted from dishonest reporting. In addition, individuals benefiting from dishonest behavior formed close bonds with them, evaluating them positively and contributing more money in a subsequent public goods game. This research illuminates the intricate interplay of social dynamics, ethical orientations, and motivations in hierarchical relationships, offering insights for understanding and managing ethical decision-making in various contexts.

Different understandings of the nature of ‘structural relationships’ in phenomenographic research: views of educational researchers

ABSTRACT Phenomenography, as a qualitative research methodology, is distinguished by its simultaneous focus on investigating (a) variation in ways of experiencing phenomena in the world, and (b) structural relationships that link and separate the different ways of experiencing. The focus on structural relationships is often regarded as the most distinctive and useful aspect of the methodology, but it is also the least well understood aspect. To help explicate the nature of structural relationships in phenomenographic research, this paper reports the outcomes of an empirical study of different understandings of structural relationships amongst educational researchers. Structural relationships were variously described as: (1) hierarchical relationships; (2) hierarchically-inclusive relationships; (3) meaning-structure relationships; (4) part-whole relationships; and (5) multi-faceted relationships. The outcomes of the study highlight a number of critical aspects of the notion of structural relationships that researchers need to become aware of in order to use the methodology in a sophisticated way.

Hybridization of human resource management practices at South Korean online game firms: the effects of inter-organizational networks

ABSTRACT This article examines inter-organizational relationships as a vital context in the hybridization of human resource practices for adopting best practices. Employing an actor-centred institutional approach, it analyzes actor interactions in order to comprehend how institutionalized actors influence the hybridization process in South Korean online game firms. Drawing from interviews and secondary data, the findings highlight the significant impact of evolving actor relationships on situational contexts. Hierarchical relationships between game publishers and developers, coupled with unionization and state involvement, shape the distinct characteristics of hybrid HR practices. This study emphasizes the intricate interplay between national, industry and firm-level contexts in the hybridization process.

Collaborative denoised graph contrastive learning for multi-modal recommendation

Graph neural networks, with their capacity to capture complex hierarchical relations, are extensively employed in multi-modal recommendation. Previous graph-based multi-modal recommendation studies primarily focus on integrating multi-modal features that capture the neighbor relations as auxiliary information. However, such methods heavily rely on graph structure properties for collaborative relations. Furthermore, while the massive implicit feedbacks alleviate the data sparsity issue, the drawback is that they are not as reliable in accurately reflecting users true interests. We propose a Collaborative Denoised Graph Contrastive Learning framework named CDGCL for multi-modal recommendation. Specifically, we present a novel modality-aware item representation with contrastive learning to capture the modality-aware collaborative relations. Besides, we develop a Multi-Policy Denoised module (MPD) to filter out irrelevant interactions. Extensive experiments that include cold-start and warm-start experimental scenarios demonstrate the superiority of CDGCL over baselines.