Hierarchical Organization Research Articles

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we proposed an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules, and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

A hierarchy index for networks in the brain reveals a complex entangled organizational structure

Networks involved in information processing often have their nodes arranged hierarchically, with the majority of connections occurring in adjacent levels. However, despite being an intuitively appealing concept, the hierarchical organization of large networks, such as those in the brain, is difficult to identify, especially in absence of additional information beyond that provided by the connectome. In this paper, we propose a framework to uncover the hierarchical structure of a given network, that identifies the nodes occupying each level as well as the sequential order of the levels. It involves optimizing a metric that we use to quantify the extent of hierarchy present in a network. Applying this measure to various brain networks, ranging from the nervous system of the nematode Caenorhabditis elegans to the human connectome, we unexpectedly find that they exhibit a common network architectural motif intertwining hierarchy and modularity. This suggests that brain networks may have evolved to simultaneously exploit the functional advantages of these two types of organizations, viz., relatively independent modules performing distributed processing in parallel and a hierarchical structure that allows sequential pooling of these multiple processing streams. An intriguing possibility is that this property we report may be common to information processing networks in general.

Initial validation of the Turkish version of the defense mechanisms rating scales-self-report-30.

The Defense Mechanisms Rating Scales-Self Report-30 (DMRS-SR-30) was recently developed to add a self-report alternative to the assessment of defenses, reflecting their generally accepted hierarchical organization. In this study, we aimed to examine psychometric properties and factor structure of the Turkish language version of the DMRS-SR-30. The sample consisted of 1.002 participants who filled out a survey comprising the DMRS-SR-30, the Brief Symptom Inventory, and the Inventory of Personality Organization through Qualtrics. Confirmatory Factor Analysis indicated a three-factor structure (CFI = 0.89, RMSEA = 0.05) that confirms the DMRS theoretical frame with a relatively acceptable fit. Defensive categories and total scale scores showed good to excellent reliability (α values ranging from 0.64 to 0.89). Correlations between defenses, symptoms, and personality functioning demonstrated good convergent and discriminant validity. The individuals with clinically significant BSI scores (T-score ≥ 63) differed on the DMRS-SR-30 scores from the individuals in the non-clinical range. The Turkish version of the DMRS-SR-30 is a reliable and valid instrument to self-assess the hierarchy of defense mechanisms and overall defensive functioning. Moreover, the current study supports the validity of the tripartite model of defenses in a language and culture different from the origins of the DMRS and DMRS-SR-30.

Modification of Keratin Integrations and the Associated Morphogenesis in Frizzling Chicken Feathers.

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal the intriguing construction of the frizzling feather shaft through the modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

Smart Library Automation: Integrating Classification Tree-Based cataloging with XAMPP Server Environment

Various sectors, including libraries, have experienced a revolution due to the swift progress of technology. This involves introducing automation and monitoring systems for more efficient operations. Hence the study Smart Library Automation and Monitoring System as an appropriate solution for these technological advancements. The proposed system integrates cutting-edge technologies to create a smart interconnected library ecosystem. Object Oriented Design Methodology was used as the software engineering technique, the proposed system leverages classification tree-based cataloging, a hierarchical organization method that enhances the accessibility and navigability of library collections. JavaScript, PHP, HTML, CSS, and XML technologies are integrated to develop an intuitive and interactive user interface for the library management system, XAMMP was later used as local server environment to utilize the automation. The system boasts various advanced functions, such as automatic lending and returning of books, shelf monitoring, and cataloging for resource accessibility assurance. By integrating these features into a comprehensive library management solution, it enables proficient utilization with intellectuality sustainability on par with the modern digital era standards.

Decoupling Charge and Side Chain Effects in Hierarchical Organization of Cationic PFX Peptide and Alginate.

We have successfully created self-assembled membranes by combining positively charged (Pro-X-(Phe-X)5-Pro) PFX peptides with negatively charged alginate. These PFX/alginate membranes were formed by three different peptides that contain either X = Arginine (R), Histidine (H), or Ornithine (O) as their charged amino acid. The assemblies were compared to membranes that were previously reported by us composed of X = lysine (K). This study enabled us to elucidate the impact of amino acids' specific interactions on membrane formation. SEM, SAXS, and cryo-TEM measurements show that although K, R, H, and O may have a similar net charge, the specific traits of the charged amino acid is an essential factor in determining the hierarchical structure of alginate/PFX self-assembled membranes.

Industrially compatible synthesis of MCM-41 with spatial organization at the macro-mesoscale

Nowadays industrial requirements point to high-performance processes but cost-effective materials to maximize their benefit/cost balance. This paper describes the properties of a macro-mesoporous MCM-41 silica with very high surface area obtained from inexpensive reagents —industrial sodium silicate as a source of silicon and industrial CTAC as template— with potential use in an environmental application such as CO2 capture. The MCM-41 silica exhibits an aperiodic 3D hierarchical spatial organization at the macro-mesoscale, formed by well-ordered MCM-41 particles with bowl-like mesopores. These particles are interconnected in three dimensions, creating a web-like structure that imparts macroporosity. This organization can be rationalized in terms of the nature and interaction of the reactants. Thus, the conjunction of poly (N-silicate) and features in CTAC, such as the weakly bonding counterion (Cl−), ethanol and unreacted amine, gave rise to different morphologies and variable channel lengths, porosity at different length scales producing meso/macro arrangements, and a spongy structure as a disordered minority phase. The hierarchical organization enhances the potential of the material for uniform APTS loading, thereby improving CO2 capture. Then the use of industrial reactants offers two important advantages: (i) The presence of macro-mesocavities, enabling applications requiring greater porosity than that intrinsic to MCM-41; (ii) A reduction in production costs by at least 80 % compared to traditional synthesis methods using alkoxysilanes and CTAB, and negligible costs compared to synthesis with analytical grade CTAC.In summary, this study demonstrates the synthesis of a hierarchically structured MCM-41 silica using cost-effective industrial reagents, offering a promising and economical solution for different applications.

Diatom Cribellum-Inspired Hierarchical Metamaterials: Unifying Perfect Absorption Toward Subwavelength Color Printing.

Diatom exoskeletons, known as frustules, exhibit a unique multilayer structure that has attracted considerable attention across interdisciplinary research fields as a source of biomorphic inspiration. These frustules possess a hierarchical porous structure, ranging from millimeter-scale foramen pores to nanometer-scale cribellum pores. In this study, this natural template for nanopattern design is leveraged to showcase metamaterials that integrates perfect absorption and subwavelength color printing. The cribellum-inspired hierarchical nanopatterns, organized in a hexagonal unit cell with a periodicity of 300nm, are realized through a single-step electron beam lithography process. By employing numerical models, it is uncovered that an additional induced collective dipole mode is the key mechanism responsible for achieving outstanding performance in absorption, reaching up to 99%. Analysis of the hierarchical organization reveals that variations in nanoparticle diameter and inter-unit-cell distance lead to shifts and broadening of the resonance peaks. It is also demonstrated that the hierarchical nanopatterns are capable of color reproduction with high uniformity and fidelity, serving as hexagonal pixels for high-resolution color printing. These cribellum-inspired metamaterials offer a novel approach to multifunctional metamaterial design, presenting aesthetic potential applications in the development of robotics and wearable electronic devices, such as smart skin or surface coatings integrated with energy harvesting functionalities.

Voxel-based texture similarity networks reveal individual variability and correlate with biological ontologies

The human brain is organized as a complex, hierarchical network. However, the structural covariance patterns among brain regions and the underlying biological substrates of such covariance networks remain to be clarified. The present study proposed a novel individualized structural covariance network termed voxel-based texture similarity networks (vTSNs) based on 76 refined voxel-based textural features derived from structural magnetic resonance images. Validated in three independent longitudinal healthy cohorts (40, 23, and 60 healthy participants, respectively) with two common brain atlases, we found that the vTSN could robustly resolve inter-subject variability with high test-retest reliability. In contrast to the regional-based texture similarity networks (rTSNs) that calculate radiomic features based on region-of-interest information, vTSNs had higher inter- and intra-subject variability ratios and test-retest reliability in connectivity strength and network topological properties. Moreover, the Spearman correlation indicated a stronger association of the gene expression similarity network (GESN) with vTSNs than with rTSNs (vTSN: r = 0.600, rTSN: r = 0.433, z = 39.784, P < 0.001). Hierarchical clustering identified 3 vTSN subnets with differential association patterns with 13 coexpression modules, 16 neurotransmitters, 7 electrophysiology, 4 metabolism, and 2 large-scale structural and 4 functional organization maps. Moreover, these subnets had unique biological hierarchical organization from the subcortex-limbic system to the ventral neocortex and then to the dorsal neocortex. Based on 424 unrelated, qualified healthy subjects from the Human Connectome Project, we found that vTSNs could sensitively represent sex differences, especially for connections in the subcortex-limbic system and between the subcortex-limbic system and the ventral neocortex. Moreover, a multivariate variance component model revealed that vTSNs could explain a significant proportion of inter-subject behavioral variance in cognition (80.0 %) and motor functions (63.4 %). Finally, using 494 healthy adults (aged 19–80 years old) from the Southwest University Adult Lifespan Dataset, the Spearman correlation identified a significant association between aging and vTSN strength, especially within the subcortex-limbic system and between the subcortex-limbic system and the dorsal neocortex. In summary, our proposed vTSN is robust in uncovering individual variability and neurobiological brain processes, which can serve as biologically plausible measures for linking biological processes and human behavior.

Non-Uniform Spatial Partitions and Optimized Trajectory Segments for Storage and Indexing of Massive GPS Trajectory Data

The presence of abundant spatio-temporal information based on the location of mobile objects in publicly accessible GPS mobile devices makes it crucial to collect, analyze, and mine such information. Therefore, it is necessary to index a large volume of trajectory data to facilitate efficient trajectory retrieval and access. It is difficult for existing indexing methods that primarily rely on data-driven indexing structures (such as R-Tree) or space-driven indexing structures (such as Quadtree) to support efficient analysis and computation of data based on spatio-temporal range queries as a service basis, especially when applied to massive trajectory data. In this study, we propose a massive GPS data storage and indexing method based on uneven spatial segmentation and trajectory optimization segmentation. Primarily, the method divides GPS trajectories in a large spatio-temporal data space into multiple MBR sequences by greedy algorithm. Then, a hybrid indexing model for segmented trajectories is constructed to form a global spatio-temporal segmentation scheme, called HHBITS index, to achieve hierarchical organization of trajectory data. Eventually, a spatio-temporal range query processing method is proposed based on this index. This paper implements and evaluates the index in MongoDB and compares it with two other spatio-temporal composite indexes for performing spatio-temporal range queries efficiently. The experimental results show that the method in this paper has high performance in responding to spatio-temporal queries on large-scale trajectory data.

CAN: Concept‐Aligned Neurons for Visual Comparison of Deep Neural Network Models

AbstractWe present concept‐aligned neurons, or CAN, a visualization design for comparing deep neural networks. The goal of CAN is to support users in understanding the similarities and differences between neural networks, with an emphasis on comparing neuron functionality across different models. To make this comparison intuitive, CAN uses concept‐based representations of neurons to visually align models in an interpretable manner. A key feature of CAN is the hierarchical organization of concepts, which permits users to relate sets of neurons at different levels of detail. CAN's visualization is designed to help compare the semantic coverage of neurons, as well as assess the distinctiveness, redundancy, and multi‐semantic alignment of neurons or groups of neurons, all at different concept granularity. We demonstrate the generality and effectiveness of CAN by comparing models trained on different datasets, neural networks with different architectures, and models trained for different objectives, e.g. adversarial robustness, and robustness to out‐of‐distribution data.

A Constitutive Heterochromatic Region Shapes Genome Organization and Impacts Gene Expression in Neurospora crassa.

Genome organization is essential for proper function, including gene expression. In metazoan genome organization, chromatin loops and Topologically Associated Domains (TADs) facilitate local gene clustering, while chromosomes form distinct nuclear territories characterized by compartmentalization of silent heterochromatin at the nuclear periphery and active euchromatin in the nucleus center. A similar hierarchical organization occurs in the fungus Neurospora crassa where its seven chromosomes form a Rabl conformation, where heterochromatic centromeres and telomeres independently cluster at the nuclear membrane, while interspersed heterochromatic loci in Neurospora aggregate across megabases of linear genomic distance for forming TAD-like structures. However, the role of individual heterochromatic loci in normal genome organization and function is unknown. Here, we examined the genome organization of a Neurospora strain harboring a ~47.4 kilobase facultative (temporarily silent) heterochromatic region deletion, as well as the genome organization of a strain deleted of a 110.6 kilobase permanently silent constitutive heterochromatic region. While the facultative heterochromatin deletion had little effect on local chromatin structure, the constitutive heterochromatin deletion altered local TAD-like structures, gene expression, and the predicted 3D genome structure by qualitatively repositioning genes into the nucleus center. Our work elucidates the role of individual heterochromatic regions for genome organization and function.

Lessons learned: Using a Three-Step Model of Planned Change for nursing curricular revision

BackgroundThe American Association of Colleges of Nursing (AACN, 2021) introduced “The Essentials: Core Competencies for Professional Nursing Education” (Essentials) in 2021. The AACN document necessitated a change in nursing curriculums, both undergraduate and graduate. To meet the revised standards, one college of nursing within a hierarchical organization used a Three-Step Model of Planned Change to guide curricular revisions. This article presents the lessons learned from using the Three-Step Model of Planned Change, which includes barriers, strategies, and a toolkit for implementing planned change. Step One-Desire a ChangeLessons learned include embracing the unifying values of the guiding coalition to understand the motivation(s) and urgency for change. Suggested strategies include creating a cross-sectional organizational team, utilizing collaborative approaches that value members' time, and various communication methods. Step Two-Make the ChangeLessons learned include understanding the larger hierarchical structure's process requirements and time allotment for approval. Suggested strategies include establishing a repository hub for templates and shared documents, implementing various communication channels, and repurposing standing meeting times. Step Three-Live the ChangeAs this process is just beginning, anticipated lessons include an understanding of changes occurring circuitously within and between steps. Considerations include significant and purposeful actions to deliver the new curriculum.

Correlations reveal the hierarchical organization of biological networks with latent variables

Deciphering the functional organization of large biological networks is a major challenge for current mathematical methods. A common approach is to decompose networks into largely independent functional modules, but inferring these modules and their organization from network activity is difficult, given the uncertainties and incompleteness of measurements. Typically, some parts of the overall functional organization, such as intermediate processing steps, are latent. We show that the hidden structure can be determined from the statistical moments of observable network components alone, as long as the functional relevance of the network components lies in their mean values and the mean of each latent variable maps onto a scaled expectation of a binary variable. Whether the function of biological networks permits a hierarchical modularization can be falsified by a correlation-based statistical test that we derive. We apply the test to gene regulatory networks, dendrites of pyramidal neurons, and networks of spiking neurons.

Effects of mineralization on the hierarchical organization of collagen-a synchrotron X-ray scattering and polarized second harmonic generation study.

The process of mineralization fundamentally alters collagenous tissue biomechanics. While the structure and organization of mineral particles have been widely studied, the impact of mineralization on collagen matrix structure, particularly at the molecular scale, requires further investigation. In this study, synchrotron X-ray scattering (XRD) and polarization-resolved second harmonic generation microscopy (pSHG) were used to study normally mineralizing turkey leg tendon in tissue zones representing different stages of mineralization. XRD data demonstrated statistically significant differences in collagen D-period, intermolecular spacing, fibril and molecular dispersion and relative supramolecular twists between non-mineralizing, early mineralizing and late mineralizing zones. pSHG analysis of the same tendon zones showed the degree of collagen fibril organization was significantly greater in early and late mineralizing zones compared to non-mineralizing zones. The combination of XRD and pSHG data provide new insights into hierarchical collagen-mineral interactions, notably concerning possible cleavage of intra- or interfibrillar bonds, occlusion and reorganization of collagen by mineral with time. The complementary application of XRD and fast, label-free and non-destructive pSHG optical measurements presents a pathway for future investigations into the dynamics of molecular scale changes in collagen in the presence of increasing mineral deposition.

ScPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement.

In the past decade, single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal method for transcriptomic profiling in biomedical research. Precise cell-type identification is crucial for subsequent analysis of single-cell data. And the integration and refinement of annotated data are essential for building comprehensive databases. However, prevailing annotation techniques often overlook the hierarchical organization of cell types, resulting in inconsistent annotations. Meanwhile, most existing integration approaches fail to integrate datasets with different annotation depths and none of them can enhance the labels of outdated data with lower annotation resolutions using more intricately annotated datasets or novel biological findings. Here, we introduce scPLAN, a hierarchical computational framework designed for scRNA-seq data analysis. scPLAN excels in annotating unlabeled scRNA-seq data using a reference dataset structured along a hierarchical cell-type tree. It identifies potential novel cell types in a systematic, layer-by-layer manner. Additionally, scPLAN effectively integrates annotated scRNA-seq datasets with varying levels of annotation depth, ensuring consistent refinement of cell-type labels across datasets with lower resolutions. Through extensive annotation and novel cell detection experiments, scPLAN has demonstrated its efficacy. Two case studies have been conducted to showcase how scPLAN integrates datasets with diverse cell-type label resolutions and refine their cell-type labels. https://github.com/michaelGuo1204/scPLAN.

Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair.

Advances in chromatin mapping have exposed the complex chromatin hierarchical organization in mammals, including topologically associating domains (TADs) and their substructures, yet the functional implications of this hierarchy in gene regulation and disease progression are not fully elucidated. Our study delves into the phenomenon of shared TAD boundaries, which are pivotal in maintaining the hierarchical chromatin structure and regulating gene activity. By integrating high-resolution Hi-C data, chromatin accessibility, and DNA double-strand breaks (DSBs) data from various cell lines, we systematically explore the complex regulatory landscape at high-level TAD boundaries. Our findings indicate that these boundaries are not only key architectural elements but also vibrant hubs, enriched with functionally crucial genes and complex transcription factor binding site-clustered regions. Moreover, they exhibit a pronounced enrichment of DSBs, suggesting a nuanced interplay between transcriptional regulation and genomic stability. Our research provides novel insights into the intricate relationship between the 3D genome structure, gene regulation, and DNA repair mechanisms, highlighting the role of shared TAD boundaries in maintaining genomic integrity and resilience against perturbations. The implications of our findings extend to understanding the complexities of genomic diseases and open new avenues for therapeutic interventions targeting the structural and functional integrity of TAD boundaries.

Unraveling Divergent Transcriptomic Profiles: A Comparative Single-Cell RNA Sequencing Study of Epithelium, Gingiva, and Periodontal Ligament Tissues.

The periodontium comprising periodontal ligament (PDL), gingiva, and epithelium play crucial roles in maintaining tooth integrity and function. Understanding tissue cellular composition and gene expression is crucial for illuminating periodontal pathophysiology. This study aimed to identify tissue-specific markers via scRNA-Seq. Primary human PDL, gingiva, and epithelium tissues (n = 7) were subjected to cell hashing and sorting. scRNA-Seq library preparation using 10× Genomics protocol and Illumina sequencing was conducted. The analysis was performed using Cellranger (v3.1.0), with downstream analysis via R packages Seurat (v5.0.1) and SCORPIUS (v1.0.9). Investigations identified eight distinct cellular clusters, revealing the ubiquitous presence of epithelial and gingival cells. PDL cells evolved in two clusters with numerical superiority. The other clusters showed varied predominance regarding gingival and epithelial cells or an equitable distribution of both. The cluster harboring most cells mainly consisted of PDL cells and was present in all donors. Some of the other clusters were also tissue-inherent, while the presence of others was environmentally influenced, revealing variability across donors. Two clusters exhibited genetic profiles associated with tissue development and cellular integrity, respectively, while all other clusters were distinguished by genes characteristic of immune responses. Developmental trajectory analysis uncovered that PDL cells may develop after epithelial and gingival cells, suggesting the inherent PDL cell-dominated cluster as a final developmental stage. This single-cell RNA sequencing study delineates the hierarchical organization of periodontal tissue development, identifies tissue-specific markers, and reveals the influence of environmental factors on cellular composition, advancing our understanding of periodontal biology and offering potential insights for therapeutic interventions.

Urban Texture Identification and Characteristic Analysis Based on Percolation Theory—A Case Study of the Second Ring Road Area in Wuhan City

The urban texture is the physical manifestation of the urban form’s evolution. In the rapid process of urbanization, protecting and reshaping the urban texture has become an essential means to sustain the overall form and vitality of cities. Previous studies in this field have primarily relied on image analysis or typological methods, lacking a quantitative approach to identify and analyze the urban texture on a large scale. Moreover, the hierarchical structure and networked organization of the urban texture are gradually being elucidated and emphasized. This study takes a complex network perspective and applies percolation theory to identify and analyze the urban texture. The hierarchical evolutionary characteristics of the urban fabric and the underlying mechanisms driving the scale-dependent differences are analyzed, and the toughness of the urban texture is evaluated based on hierarchical connections. The research findings reveal the key scale in the cross-scale evolution of urban textures, with variations in scale dependence and hierarchical evolution characteristics among different types of urban texture. The traditional urban texture displays sensitivity to scale changes, maintaining its integrity and internal connectivity at small scales. On the other hand, the texture characteristics of modern and contemporary urban areas are only discernible at larger scales. The emergence of large-scale texture clusters at specific scale levels can be explained using multiple index systems. This study has reference significance for the preservation and renewal of the urban fabric in urban renewal processes.

The Influence of Organizational Culture on Tanzania Public Sector Performance

The study was done in public sector which was TRA-Ilala region. The general objective of this study was to investigate the role of organizational culture on public sector performance and specific objectives were to: Examine organizational culture present in Tanzania public performance and specific objectives were to: determine employees’ perceptions on organizational culture and to determine the influence of organization culture on performance of public sector. Case study research design was employed during the study and research approaches used were qualitative and quantitative research approaches. Data collection methods and instruments used were questionnaire, interview, interview questions, documentary review schedule and documentary review. Descriptive statistics was used during analysis of data. The findings revealed that organizational culture applied specifically by TRA- Ilala region included clan culture, adhocracy culture, market culture and hierarchical organizational culture. The findings further revealed that there were positive perceptions among employees on clan and hierarchical organizational culture and that clan organizational culture has contributed much to the performance of organization. The recommendations are on ensuring stable organizational culture through increasing emphasis on ownership, community and communication as well as improving leadership styles in the organization for stable hierarchical organization culture and entire performance of organization.