Dimensions Of Complexity Research Articles

Exploring the Complexity of the Book of Daniel: A Multifaceted Analysis

This research delves into the intricate layers of the Book of Daniel, seeking to unravel its complexities through a comprehensive examination. Emphasizing the historical and literary significance of the text, the study explores the multifaceted nature of the Book of Daniel, which has intrigued scholars for centuries. The primary objective is to illuminate various dimensions of complexity, including symbolic language, prophetic elements, and historical context. Employing a methodological approach that integrates literary analysis, historical investigation, and theological perspectives, the study aims to provide a holistic understanding of the Book of Daniel's intricacies. Positioned within ongoing scholarly discussions on biblical interpretation and prophecy, the research reveals that the Book of Daniel invites diverse approaches, incorporating historical, wisdom, prophetic, and apocalyptic perspectives. Comprehending the Book of Daniel's complexity contributes to bridging the gap between historical, literary, and theological viewpoints, thereby enriching our grasp of biblical texts and fostering scholarly discourse in this field.

Highly Self-Adaptive Path-Planning Method for Unmanned Ground Vehicle Based on Transformer Encoder Feature Extraction and Incremental Reinforcement Learning

Path planning is an indispensable component in guiding unmanned ground vehicles (UGVs) from their initial positions to designated destinations, aiming to determine trajectories that are either optimal or near-optimal. While conventional path-planning techniques have been employed for this purpose, planners utilizing reinforcement learning (RL) exhibit superior adaptability within exceedingly complex and dynamic environments. Nevertheless, existing RL-based path planners encounter several shortcomings, notably, redundant map representations, inadequate feature extraction, and limited adaptiveness across diverse environments. In response to these challenges, this paper proposes an innovative and highly self-adaptive path-planning approach based on Transformer encoder feature extraction coupled with incremental reinforcement learning (IRL). Initially, an autoencoder is utilized to compress redundant map representations, providing the planner with sufficient environmental data while minimizing dimensional complexity. Subsequently, the Transformer encoder, renowned for its capacity to analyze global long-range dependencies, is employed to capture intricate correlations among UGV statuses at continuous intervals. Finally, IRL is harnessed to enhance the path planner’s generalization capabilities, particularly when the trained agent is deployed in environments distinct from its training counterparts. Our empirical findings demonstrate that the proposed method outperforms traditional uniform-sampling-based approaches in terms of execution time, path length, and trajectory smoothness. Furthermore, it exhibits a fivefold increase in adaptivity compared to conventional transfer-learning-based fine-tuning methodologies.

Numerical analysis of velocity slip and magnetic Soret effect on dissipative Maxwell liquid motion about a stretching wall with heat source/sink

The main aim of present numerical analysis is to explore the effects of viscous dissipation and velocity slip on the two-dimensional steady-state viscous incompressible flow of Maxwell fluid over a stretching sheet under the infleunce of magnetic field. Novel collective effects of heat source/sink and Soret impacts have been included in the governing equations to explore the salient features of heat and mass transport mechanism. Further, the velocity slip is introduced into the boundary conditions to depict the momentum transport behavior in the flow region. A typical Maxwell fluid model is deployed to separate the non-Newtonian flow behavior from that of classical Newtonian fluids. However, the visco-elastic Maxwell fluid finds its abundant applications in various fields of engineering and medicine such as plastic sheet drawing, metallurgy, polymer sheet extrusion, chemical engineering, electronic cooling, injection molding and nuclear cooling and many others. Inspired by these applications, authors have made an attempt to disclose the magneto-thermo salient features of slip flow of Maxwell fluid over stretching wall under Soret effect. The current physical situation results the highly nonlinear coupled two-dimensional steady-state partial differential equations and which are not amenable to any of the direct techniques. Due to this, the suitable similarity transformations are deployed to reduce the dimensional complexity of the constructed partial differential equations. A robust Matlab-based bvp4c scheme is utilized as a basic tool to produce the similarity solutions of the governing equations. The computer generated numerical data is presented in view of flow, temperature and concentration profiles including physical quantities of interest like skin-friction coefficient, heat and mass transport rates for the various values of physical parameters range such as, 0 ≤ M ≤ 1 , 0 ≤ β ≤ 1 , − 0.3 ≤ λ ≤ 0.6 , − 0.2 ≤ Q ≤ 0.2 , 0 ≤ Ec ≤ 2.2 , 1.2 ≤ Pr ≤ 2.2 , 0 ≤ Sr ≤ 0.5 and 1.2 ≤ Sc ≤ 2.2 . Accordingly, it is noticed that, enhancing magnetic parameter decreases the Maxwell fluid flow and amplifies the temperature and concentration fields. Enlarging Maxwell fluid parameter decreases the velocity field and increases the temperature and concentration profiles. Amplified slip parameter diminished the Maxwell flow inside the flow regime. Increasing heat source/sink parameter amplifies the temperature field. Further, magnifying Soret number amplifies the concentration field. Magnitude of skin-friction coeffiecient enlarged with amplified magnetic and Maxwell fluid parameters. Heat and mass transport rates decayed with enhancement in heat source/sink and Soret parameters. Finally, it is described that, the present similarity solutions showing good agreement with the previously reported solutions in the literature and this fact confirms the accurateness of the used numerical method and the generated similarity solutions.

Hiding Behind Complexity: Supply Chain, Oversight, Race, and the Opioid Crisis

The opioid crisis has ravaged the United States, taking 69,000 lives in 2020, with prescription opioids accounting for 98% of opioid abuse. Although this epidemic is often considered a White public health crisis nationally, overdose deaths among people of color doubled from 2017 to 2019. As research has shown that the crisis was fueled by excessive supply from the pharmaceutical industry, several individual firms have received significant public criticism. However, we find evidence that the scope of the blame transcends individual actors to indict the very structure of complex supply chains, which may have exacerbated the crisis by dispensing significantly more opioids. In specific, we posit that supply chain complexity allowed mass quantities of opioids to escape detection by the Drug Enforcement Administration (DEA). Further, we find new evidence showing the greater impact of complexity on opioid dispensing in non-White communities, which underscores their exclusion from the public discourse and governmental response surrounding the crisis and suggests possible racial bias in the DEA’s regulatory policies. Our analysis was made possible by the 2019 release of the DEA’s Automation of Reports and Consolidated Orders System database, which logged every shipment in the US opioid supply chain from 2006 to 2014. Using a fixed effects model, we find that a one-unit increase across three dimensions of supply chain complexity is associated with a 16% increase in opioid dispensing. This effect is intensified in non-White communities, where a 10% increase in the non-White population is associated with a 3.39% (1.33%) increase in opioid dispensing by pharmacies that have supply chains with high (average) complexity. To verify that high-complexity pharmacies’ excess dispensing supplied non-medical/recreational demand, we exploit the reformulation of OxyContin (designed to prevent recreational use) as an exogenous shock to the market. In a novel approach, we leverage the fact that different pharmacies received their first shipment of reformulated OxyContin at different times and use a difference-in-differences model to estimate the heterogeneous effect of the shock on dispensing. As the reformulated OxyContin stifled demand, high-complexity pharmacies experienced a 15.31% greater reduction in dispensing compared to lower-complexity pharmacies, suggesting that their excess dispensing was indeed satisfying non-medical/recreational demand.

DTAAD: Dual Tcn-attention networks for anomaly detection in multivariate time series data

Anomaly detection techniques enable effective anomaly detection and diagnosis in multi-variate time series data, which are of major significance for today’s industrial applications. However, establishing an anomaly detection system that can be rapidly and accurately located is a challenging problem due to the lack of anomaly labels, the high dimensional complexity of the data, memory bottlenecks in actual hardware, and the need for fast reasoning. In this paper, we propose an anomaly detection and diagnosis model, DTAAD, based on Transformer and Dual Temporal Convolutional Network (TCN). Our overall model is an integrated design in which an autoregressive model (AR) combines with an autoencoder (AE) structure. Scaling methods and feedback mechanisms are introduced to improve prediction accuracy and expand correlation differences. Constructed by us, the Dual TCN-Attention Network (DTA) uses only a single layer of Transformer encoder in our baseline experiment, belonging to an ultra-lightweight model. Our extensive experiments on seven public datasets validate that DTAAD exceeds the majority of currently advanced baseline methods in both detection and diagnostic performance. Specifically, DTAAD improved F1 scores by 8.38% and reduced training time by 99% compared to the baseline. The code and training scripts are publicly available on GitHub at https://github.com/Yu-Lingrui/DTAAD.

FRACTAL ANALYSIS OF BRANCHING OF HUMAN CEREBELLAR ARTERIES

Human cerebellum is supplied by three arteries: the superior surface is nourished by the superior cerebellar artery (SCA), while the inferior surface is supplied by the anterior inferior cerebellar artery (AICA) and the posterior inferior cerebellar artery (PICA). Traditionally, the branching pattern of the superfi cial vascular network is subjectively assessed, distinguishing between the trunk, lose or mixed types. Fractal analysis is an objective alternative method.The aim of this study is to investigate the fractal dimension of branching complexity of superfi cial arteries in the human cerebellum and to establish the relationship between the magnitude of the fractal index and the shape of the cerebellum.Material and Methods. A total of 100 cerebellum samples, including the brainstem, were examined. The width, length, and height of the cerebellum were measured. Parameters of cerebellar shape, namely relative width (rW), relative length (rL), and relative height (rH), were determined as the ratios of the square of one linear dimension to the product of the other two. For fractal analysis, 15 cerebellar samples of various shapes (9 from male and 6 from female individuals) were selected. Fractal analysis of digital images of the superior and inferior surfaces of the cerebellum was performed bilaterally using the box-counting method.Results. The range of fractal index values was determined, and intervals corresponding to the mixed (1.54-1.73), trunk (<1.54) and loose (>1.73) branching types were identifi ed. The superior surface predominantly exhibited trunk or mixed branching types, whereas the inferior surface was more characteristic of mixed or loose branching types. The greatest diversity of arterial branching patterns – from the trunk to lose type – is observed in the most numerous group – cerebella of proportional shape, regardless of which shape parameter is analyzed. The branching pattern of superfi cial cerebellar arteries tends towards a loose type in relatively narrow and relatively short cerebella, and conversely towards a trunk type in relatively wide and relatively long cerebella. Conversely, relative height has an opposite eff ect: the branching pattern of superfi cial cerebellar arteries tends towards a loose type as the relative height of the cerebellum increases. Thus, relatively low cerebella typically exhibit a trunk branching pattern (more noticeable on the superior surface), while in relatively high cerebella, the branching pattern tends towards loose (more noticeable on the inferior surface).

Montana as Place of (Un)Belonging: Landscape, Identity, and the American West in Bella Vista (2014)

Abstract The American West is not just a geographical terrain but a mythical construct that occupies a powerful place in the popular imagination thanks to myriad literary and artistic works that have presented the region through specific archetypes emphasizing its vast ruggedness, white masculinity, and unique Americanness. In recent decades, revisionist scholarly and artistic works, however, have attempted to offer more nuanced perspectives on the region challenging its assumed homogenous history and fixed and stable identity. In particular, women filmmakers have recast the region through multifaceted representations underlining its complexity, diversity, and transnational dimensions. This article analyzes Vera Brunner-Sung’s film Bella Vista (2014) to examine how the film intervenes in previously constructed representations of the American West through its emphasis on transience, displacement, and belonging. Set and made in Montana, the film employs a “slow cinema” aesthetic to offer deep insights into the local and global dynamics of the place as well as the formation of identity and (un)belonging within a Western landscape. The film, as the article argues, provides a reconsideration of the West through diverse localities that are in constant relation with the outside and in turn have generated diverse individual experiences regarding the place.

Relatedness, Complexity and Regional Diversification in the European Union: The Role of Co‐inventor Networks

AbstractWe investigate the role of both internal and external co‐inventor networks in regional diversification. The impact of co‐inventor networks on regional technological diversification is tested for a data set containing 1,495,699 patents in 643 technologies in 290 European regions at the NUTS‐2 level, between 1987 and 2016. Our results show that both internal co‐inventor network connectivity and external co‐inventor network linkages could benefit regional technology entry and prevent regional technology exit. However, too inwardly oriented or outwardly connected co‐inventor networks would hamper patent production. Regarding regional diversification, we find that both internal and external co‐inventor networks could facilitate the entry of related technologies and restrain the exit of complex technologies. This paper contributes to the literature by initiating the integration of the complexity dimension into analysing the role of co‐inventor networks in regional diversification. This research bears significant policy implications for the advancement of Smart Specialization Strategy in the European Union.

Pekan Sagu Innovation Regains the Public Service Moment of Truth

The digital era has influenced public service innovation. Many districts/cities in Indonesia use digital service innovation to overcome the maladministration problem in civil registration services, however, Seluma regency government has chosen to maintain physical moment of truth through the Pekan Sagu innovation. This innovation is in the form of increasing service hours on Saturdays and Sundays through door-todoor service. The researcher chose a qualitative paradigm in order to reveal the natural conditions of the unit of analysis with a case study design. Primary and secondary data were collected through interviews, observation, and documentation studies, with triangulation of sources, time, and methods. The research results show that Pekan Sagu has the dimensions of compatibility, complexity, trialability and observability. This innovation maintains the public service moment of truth which is actually the weak point of previous problems of public service because of maladministration. A direct in-touch service policy with an extension of service time can be a short-term solution to overcome some target groups’ problem who are not yet technologically literate, however, the government still has to educate citizens and prepare the need for digital-based services to meet the demands of long-term civil registration services.
 Keywords: innovation, public service

Defining urban segregation: A qualitative meta-synthesis

Despite more than a century of research on urban segregation, this phenomenon is still one of the main concerns of urban planners and policymakers and a characteristic of cities that require intervention. Any policy-making in this field as an urban reality requires a clear understanding and definition of this phenomenon. But which definition? In response to this question and obtaining a basis for the definition of segregation, many efforts have been made in the past decades. However, these efforts have failed to present a framework that theoretically and practically responds to all dimensions and approaches in defining segregation. To fill this gap, the present study provides a comprehensive and integrated definition of urban segregation based on a meta-synthesis and qualitative content analysis by reviewing, categorizing, and combining the various and complex definitions in the existing literature. It presents two main categories of definitions of urban segregation: definitions based on the structural dimension and definitions based on the spatial dimension. Considering the complexity and multiple dimensions of urban segregation, a comprehensive definition of this phenomenon to present all aspects of segregation must answer six main questions: What is the nature of segregation? What people, on what basis, why, in what places and times, and how are segregated? The answers to the questions show that the presented categorization of the definitions of urban segregation covers different dimensions and aspects of this phenomenon. Therefore, combining them contributes to a comprehensive definition of it. Being more comprehensive than the previous definitions, the presented definition in this study specifies the main dimensions of urban segregation. It can provide an efficient basis for future theories, policies, and planning in urban segregation. Although the presented categories are inseparable parts of a whole, they can be examined in detail separately in future studies. Also, by connecting the definitions in the literature to intellectual paradigms and planning theories, a deeper understanding of the shaping factors and components of urban segregation can be achieved.

Task complexity and foreign language writing emotions as predictors of EFL writing performance

Emotions and task complexity have gained scant attention in EFL writing. This study, based on control-value theory and a positive psychology perspective, explores the relationship between task complexity, writing anxiety, writing boredom, writing enjoyment, and task complexity and writing emotions interaction on EFL writing performance among English major students in China’s educational context (N = 84). It has been found that difficult writing tasks can result in higher writing anxiety and lower writing boredom. By 6 × 2 between-subject ANOVA, there is a significant interaction of task complexity and different levels of writing anxiety, writing boredom, and writing enjoyment for the dimensions of language fluency, complexity, and accuracy among English major students in China’s educational context. This study is an initial step in extending the writing emotions and task complexity in the production of EFL writing, which promotes the mutual integration of emotion and cognition in EFL writing research and thus supplies suggestions for task-based EFL writing instruction.

Cross-culture analysis of batik sub-culture Pekalongan: A case study on the complexity dimensions of representation, diversity and conflict

Pekalongan batik sub-culture development is influenced by three cultures namely Javanese, Chinese and Arabic. Most studies of batik use a cultural and socioeconomic analysis by focusing mainly its cultural aspects. This research aims to analysis transformation of social and economic assets, by using a different perspective namely cross-cultural theory and democratization framework in order to explain the political economic contestation among the entrepreneurs. This research uses Robert Dahl’s conceptual framework regarding the development of democracy and only uses three of the seven relevant aspects, namely: (a) representation, (b) diversity, and (c) conflict. Case studies as a qualitative methodology are used with in-depth interview techniques, observation and literature reviews as data collection tools. The results of this study are, Pekalongan batik sub-culture has formed a kind of long acculturation formation in the cultural perspective, but secondly it also contributes to develop a kind of political contestation, conflicts and gender-bias political practices This study concludes that regional autonomy and decentralization policies have created space for political contestation and opened up opportunities to transform the social/economic capital of batik entrepreneurs as assets for political contestation and have even raised the issue of identity politics.

Mapping the policy space of public consultations: evidence from the European Union

ABSTRACT Public consultations strengthen the informational advantage and policy legitimacy of bureaucracies by allowing them to collect and aggregate information on stakeholder preferences. How well consultations perform this function depends on the dimensional structure and complexity of the policy spaces describing them. Building on the research on spatial models of politics, we derive a set of expectations about the dimensional structure and policy content of consultation policy spaces. We assess our argument empirically by analysing 42 consultations organised by the European Commission via online surveys across all policy areas. Using Specific Multiple Correspondence Analysis (SMCA) we find that more than 70% of the analysed consultations present low-dimensional policy spaces characterised by one or two main dimensions, although some also display a three-dimensional space. The substantive content of policy dimensions is consultation-specific and varies greatly across events. Most dimensions capture stakeholder alignments with respect to policy instruments, and only a few with respect to the orientation of the policy regime. The unveiled consultation policy spaces reflect a regulatory model of stakeholder engagement in policymaking. Our findings underscore the challenges and opportunities of information provision, preference aggregation and the identification of stable majority equilibria in the context of public consultations and bureaucratic policymaking.

Dickensian Dimensions: A Transatlantic Dialogue

Abstract: “Dickensian Dimensions” makes use of Dickens’s manuscript revisions to uncover the extra dimensions of emotional depth and temporal complexity that his sentences acquire in the immediate midst of composition. When the effects of those little changes were offered to a group of serious ordinary readers in the UK, their responses to selected passages from David Copperfield showed how much the tiny revisions could matter emotionally. The second part of the essay considers revised passages from Dickens’s next first-person narrator, Esther Summerson of Bleak House . We suggest that Esther’s apparently coy evasions can be more sympathetically read as writing problems stemming from her existential situation as a virtual non-person.

The Multi-Skilled Resource-Constrained Project Scheduling Problem: A Systematic Review and an Exploration of Future Landscapes

Abstract The Multi-skilled Resource Constrained Project Scheduling Problem (MS-RCPSP) is a complex and multi-faceted problem that involves scheduling activities whilst considering various resource constraints. These constraints include limited availability of workers, equipment, and materials, with each activity requiring a minimal set of skills to be executed. Furthermore, for a better resemblance to reality, workers/machines are assumed to be multi-skilled/multi-purpose posing another dimension of complexity to the problem. The objective is to minimize project duration, cost, or other relevant criteria while accounting for the inherent resources flexibility. This paper provides a systematic review of the literature pertaining to MS-RCPSP, and an in-depth analysis of 171 papers published between 2000 and 2021 inclusive. The conducted bibliometric analysis identifies the top contributing authors, most influential papers, existing research tendencies, and thematic research topics within the field. In addition, this review highlights different aspects of the MS-RCPSP, spanning the significance of performance measures, solution approaches, application areas, and the incorporation of time constraints. While project completion time, cost, and tardiness are common performance indicators, other measures such as multi-skilled staff assignment and schedule robustness are also deemed important. Although various methods have been employed to solve the MS-RCPSP including exact and approximate approaches, the selection of the most-suited approach depends on the problem’s scale, complexity, and constraints, necessitating careful consideration of each method’s strengths and weaknesses. Interestingly, several studies have jointly addressed resource and time constraints in the context of MS-RCPSP, often considering tardiness, and have proposed different algorithms, models, and metaheuristics to tackle these challenges. This paper clearly highlights research gaps and promising avenues for future research. This work provides valuable insights for project managers to effectively schedule tasks in the presence of multiple flexible resources.

Emerging therapeutic targets in systemic sclerosis.

Systemic sclerosis is an autoimmune connective tissue disease which is characterised by vascular perturbations, inflammation, and fibrosis. Although huge progress recently into the underlying molecular pathways that are perturbed in the disease, currently no therapy exists that targets the fibrosis element of the disease and consequently there is a huge unmet medical need. Emerging studies reveal new dimensions of complexity, and multiple aberrant pathways have been uncovered that have shed light on disturbed signalling in the disease, primarily in inflammatory pathways that can be targeted with repurposed drugs. Pre-clinical animal models using these inhibitors have yielded proof of concept for targeting these signalling systems and progressing to clinical trials. This review will examine the recent evidence of new perturbed pathways in SSc and how these can be targeted with new or repurposed drugs to target a currently intractable disease.

Dimensions of Text Complexity in the Spoken and Written Modes: A Comparison of Theory-Based Models

In many studies, grammatical complexity has been treated as a single unified construct. However, other research contradicts that view, suggesting instead that the different structural types and syntactic functions of complexity features are distributed in texts in fundamentally different ways. These patterns have been documented in general corpora that include a wide range of spoken and written registers. One question that has not been fully addressed is whether grammatical complexity features are organized in the same ways in the spoken versus written modes. The present study tests the empirical adequacy of four competing models based on different theoretical conceptualizations of text complexity, comparing their goodness-of-fit in spoken versus written modes. The results show that text complexity must be treated as a multi-dimensional construct; dimensions that combine structural type and syntactic function provide the best account of the actual patterns of linguistic co-occurrence. To a large extent, the same complexity dimensions operate in both the spoken and written modes. Two of these dimensions—dependent phrases functioning as noun modifiers and finite dependent clauses functioning as clause-level constituents—represent the strongest co-occurrence patterns. In addition, these two dimensions operate in complementary distribution, in both the spoken and written modes. Overall, though, these two dimensions are shown to represent stronger co-occurrence patterns in the written mode than in the spoken mode.

Deepening the synergistic role of additive manufacturing and computational strategies in jewellery

This study investigates the synergy between additive manufacturing (AM) technologies and computational design strategies in jewellery and how that synergy can be successfully exploited to extend innovation in that field further. A case study called Ecdysis, a bioinspired jewellery collection, is presented. A dedicated computational algorithm has been developed and is described in detail. This algorithm allows for the exploitation of the shape and functional complexity dimensions allowed by AM and the control of the printability of the generated concept. Shape and functional complexity are exploited to mimic the beauty and dynamism of snakes’ slithering mechanism. At the same time, starting from the developed algorithm, multiple digital models and physical prototypes have been fabricated, leveraging material extrusion, vat photopolymerisation, and powder bed fusion processes. This further development step of the collection thus confirms the versatility of both the proposed approach and AM technologies for jewellery. Therefore, the paper demonstrates how unique wearing experiences can be created and how uniqueness can be simultaneously preserved and democratised in jewellery by deepening the synergy between AM technologies and computational strategies.

Policy complexity and implementation performance in the European Union

This study examines the relationship between the complexity of EU directives and their successful implementation at the national level. Moving beyond the state‐of‐the‐art, we propose a comprehensive framework considering structural, linguistic, and relational dimensions of policy complexity. We argue that policy complexity entails higher transaction costs, hindering effective implementation. Using a novel dataset covering roughly 1000 directives from 1994 to 2022, we find strong evidence of policy complexity negatively impacting implementation performance. Moreover, we find that states with higher administrative capacity are better able to process high complexity efficiently and that Eurosceptic member states attract fewer infringement proceedings in highly complex policy environments than Europhile member states. This could alternatively point to strategic enforcement behavior of the Commission or to bureaucracies that are less Eurosceptic than their political masters might wish for. Our study thereby contributes to a deeper understanding of the challenges of successful implementation of EU directives.

Generalized weighted permutation entropy analysis of satellite hot-pixel time series in Brazilian biomes

In this work we analyze hot-pixel satellite data, proxy for natural and anthropogenic vegetation and forest fires, using recently proposed method Generalized weighted permutation entropy (GWPE). The current analysis of data from 2002 to 2022 for six Brazilian biomes sheds new light on differences among the biomes in terms of ordinal pattern entropy, for both small and large fluctuations. It is found that for all biomes large fluctuations in fire temporal series show higher complexity level than small fluctuations, small fluctuations being more predictable as indicated by lower entropy values. Moreover, for fire sensitive biomes Amazon and Atlantic Forest the three dimensional complexity entropy curves in the complexity-entropy-scale causality box (CESCB) are rather similar (indicating similar dynamics for both small and large fluctuations), as well as for fire dependent biomes Pantanal and Pampa, while fire independent Caatinga biome shows different, distinct behavior. Finally, the similarity in lower parts of the CESCB curves (corresponding to small fluctuations) between Amazon and Cerrado reflects the changes of fire dynamics due to human activities.