Relational Complexity Research Articles

Identifying Key Risk Factors in Air Traffic Controller Workload by SEIR Model

To address the controller workload with the forecast, the capacity of the air traffic management system is effectively enhanced. It should be based on a specific analysis of the controller workload. In the current controller workload studies, there is no clear means to analyze the process of controller workload development propagation. In this paper, we propose a new method for analyzing the factors influencing the controller workload. This method takes into account the influence of various situations in the actual work of controllers and objectively quantifies the complexity of work conditions. A complex network is constructed by treating various factors as nodes and the complexity relationships between these nodes as edges. The complexity network was then tested using the contagion model. The sum of the number of times of infecting other nodes and being infected in the detection result was defined as the infection capacity of the nodes, and the point with the strongest infection capacity was controlled and analyzed. The results show that the point with the strongest infection capacity is the key factor for the development of controller workload generation. In addition, the analysis of the key factors using a backpropagation neural network shows that the prediction of the controller workload can be made by the key factors. It will provide a new effective method to control controller workload and improve air traffic control capability.

The use of EPR spectroscopy to study transcription mechanisms.

Electron paramagnetic resonance (EPR) spectroscopy has become a promising structural biology tool to resolve complex and dynamic biological mechanisms in-vitro and in-cell. Here, we focus on the advantages of continuous wave (CW) and pulsed EPR distance measurements to resolve transcription processes and protein-DNA interaction. The wide range of spin-labeling approaches that can be used to follow structural changes in both protein and DNA render EPR a powerful method to study protein-DNA interactions and structure-function relationships in other macromolecular complexes. EPR-derived data goes well beyond static structural information and thus serves as the method of choice if dynamic insight is needed. Herein, we describe the conceptual details of the theory and the methodology and illustrate the use of EPR to study the protein-DNA interaction of the copper-sensitive transcription factor, CueR.

Application of knowledge-embedded graph neural network for multivariate state prediction of wind turbines

State prediction of wind turbines is a key aspect of wind power's digitalization as well as its intelligent operation and maintenance (O&M). Deep learning has been gradually applied to the state prediction due to its powerful potential in mining the hidden relationships of complex and high-dimensional data; however, it also has some practical limitations such as poor inference and interpretation. Therefore, effectively combining domain knowledge with intelligent algorithms gives an important direction to the intelligent O&M. In this paper, we propose a knowledge-embedded graph neural network (K-GNN) model based on the general framework of multivariate time series graph neural network (MT-GNN), so as to predict the multivariate time series state data of wind turbines. We combine the knowledge embedding module and the auto-graph-learning module to better describe the relationships among state variables by embedding three knowledge matrices, i.e. correlation, causality and expert experience. The results demonstrated that among the three types of K-GNN models, the one with the embedded expert experience matrix performs best in prediction, indicating that domain knowledge can effectively improve the generalizability and interpretability of GNN models. It is also believed that the demonstrated work is valuable to the R&D and promotion of wind power predictive maintenance techniques.

Structure-digestibility relationship of starch inclusion complex with salicylic acid

Amylose, the linear component of starch, can complex with small molecules to form single helical inclusion complexes of 6, 7, or 8 glucosyl units per helical turn, known as V6, V7, and V8. In this study, starch-salicylic acid (SA) inclusion complexes with different amounts of residual SA were obtained. Their structural characteristics and digestibility profiles were obtained with complementary techniques and an in vitro digestion assay. Upon complexation with excess SA, V8 type starch inclusion complex was formed. When excess SA crystals were removed, the V8 polymorphic structure could remain, while further removing intra-helical SA converted the V8 conformation to V7. Furthermore, the digestion rate of the resulted V7 was lowered as indicated by increased resistant starch (RS) content, which could be due to its tight helical structure, whereas the two V8 complexes were highly digestible. Such findings could have practical implications for novel food product development and nanoencapsulation technology.

Modeling intraspecific variation in habitat utilization of the Indo-Pacific humpback dolphin using self-organizing map

Coastal cetaceans are recognized as ecologically important species and have been the target for environmental monitoring programs and conservation strategies. Although supervised models have increasingly been used to better monitor complexity relationships between cetaceans and their habitats, the development of unsupervised learning techniques that have significant advantages in visualizing, grouping and reducing the dimensionality of data has been overlooked. Here, using the unsupervised artificial neural network of self-organizing map (SOM), we examined the intraspecific variation of habitat utilization among three geographically neighboring populations (waters southwest of Hainan Island abbreviated as WS Hainan, Sanniang Bay, and Zhanjiang waters) of the Indo-Pacific humpback dolphin (Sousa chinensis) in the northern South China Sea. The results showed that the population inhabiting in WS Hainan occupied a largest area with scattered patterns comparing to the other two in Sanniang Bay and Zhanjiang waters. The SOM analysis further showed that the examined populations in different waters have distinct habitat characteristics. S. chinensis in WS Hainan was sighted in deeper water with higher salinity, whereas the population in Sanniang Bay inhabited in estuary with lower pH and salinity. More complicated distributed patterns and environmental heterogeneity were observed in Zhanjiang waters, where the dolphins distributed contractively in a small area at the entrance of Zhanjiang Port and dispersed in another large area in Leizhou Bay. Correspondently, part of the sightings in Zhanjiang waters had similar habitat with those in WS Hainan, while others were reported in more inshore, deeper and muddied waters. Based on these findings, we hypothesized that S. chinensis can be divided into two ecotypes: estuarine and non-estuarine. Here, we confirmed that the SOM can well identify the habitat differentiation in S. chinensis, and therefore suggested it is a powerful modeling tool for cetacean monitoring program. Our findings contribute to a specific habitat conservation strategy that one integrated protected area would be better for S. chinensis in Sanniang Bay and Zhanjiang waters, while several small protected areas with connecting corridors were more suitable for population in WS Hainan.

The Effect Of Audit Complexity Of Budget Pressure Time And Auditor Experience On Audit Quality With An Understanding Of Information Systems As A Moderate Variable

The development of the world of accounting requires every accountant to use a system to make financial statements. The number of accountants in each company has also become small, along with the development of financial statements that are already paperless. It is also experienced for a public accountant where every audit activity must be able to understand information technology. So that in every audit process, every client who uses a qualified financial system can be followed by the auditor concerned. This study aims to determine the influence of task complexity, budget time pressure, and auditor experience on audit quality. This study uses the understanding of information systems as a moderation variable to determine whether the relationship between the three variables can strengthen audit quality by understanding the information system for an auditor. This research was conducted at a Public Accounting Firm in Bali, with a sample determination method based on criteria. This study is looking for auditors with more than one year of experience as a sample of respondents. The regression tool used is moderation regression. The results of this study involved 56 respondents from 11 public accounting firms in Bali, understanding that the information system could not moderate the relationship of audit complexity to audit quality. Understanding information systems can weaken the relationship of time budget pressures to audit quality, and understanding information systems can also strengthen the relationship of work experience to audit quality.

Transition metal complexes with strong and long-lived excited state absorption: from molecular design to optical power limiting behavior

Abstract Transition metal complexes (TMCs) with strong and long-lived excited state absorption (ESA) usually exhibit high-performance optical power limiting (OPL) response. Several techniques, such as transmission vs. incident fluence curves and Z-scan have been widely used to assess the OPL performance of typical TMCs. The OPL performance of TMCs is highly molecular structure-dependent. Special emphasis is placed on the structure-OPL response relationships of Pt(II), Ir(III), Ru(II), and other metal complexes. This review concludes with perspectives on the current status of OPL field, as well as opportunities that lie just beyond its frontier.

Biological evaluation and in silico molecular docking studies of newly synthesized homoleptic and heteroleptic Cd(II) carboxylates

As a part of our on-going efforts to investigate the therapeutic potential of metal complexes, nine newly synthesized homoleptic and heteroleptic Cd(II) carboxylates were investigated for their inhibitory potential against α-glycosidase enzyme, urease enzyme and protein glycation. Cd(II) complexes 5 and 2 demonstrated potent inhibition against α-glycosidase with IC50 values of 23.63.±1.50 µM and 34.71±2.00 µM, respectively. Moreover, complex 8 (IC50 = 175.56±1.00 µM) and complex 6 (IC50 = 286.91±1.50 µM) both displayed significant α-glycosidase inhibitory potential. Against urease enzyme complex 2 with an IC50 value of 42.82±1.5 µM, complex 8 with an IC50 value of 82.71±1.00 µM, complex 9 with an IC50 value of 103.52, and complex 1 with an IC50 value of 109.232 µM exhibited significant inhibition. The structure-activity relationship (SAR) of complexes was examined by probing the substitution pattern of different ligands. Furthermore, in silico molecular docking was used to investigate the interactions of Cd(II) complexes within the active sites of α-glycosidase and urease enzymes.The docking results revealed that these complexes specifically bind with the active site residues, thus blocking the activity of the enzymes.

Latin square tasks: A multi-study evaluation

The Latin Square Task (LST) was proposed as a theoretically well-grounded paradigm for measuring fluid intelligence. In four studies (total N = 3,439) we systematically investigated the psychometric properties of LSTs. Results provided evidence that (a) the construct is unidimensional, (b) the administered stimulus types and the rotation of the item matrix only played a minor role, and (c) the relations with other measures of reasoning ability were in the expected range (about r = .50), confirming the validity of LSTs. For unsupervised automated test construction, item difficulty was only insufficiently accounted for by relational complexity and the number of steps that need to be memorized for solving an item. We discuss possible remedies for improving the paradigm including its generalizability. Furthermore, we propose that the binding-hypothesis of working memory is theoretically suited to account for item difficulties in LSTs.

Microbial network complexity drives non-linear shift in biodiversity-nutrient cycling in a saline urban reservoir

Aquatic biodiversity is important in mediating ecosystem functioning, contributing to ecosystem sustainability and human wellbeing. However, how microbial network complexity affects the biodiversity-nutrient cycling relationship in saline freshwater ecosystems remains underexplored. Using high-resolution time-series data, we examined the relationships between microeukaryotic-bacterial community network complexity, biodiversity and multi-nutrient cycling in an urban reservoir undergoing a freshwater salinization-desalinization cycle. We found that low microbial diversity enhanced ecosystem multi-nutrient cycling under high salinity stress. In addition, multi-nutrient cycling declined with increased network complexity. Further, we found a non-linear relationship between salinity-induced shifts in the complexity of the microbial network and biodiversity-nutrient cycling (BNC) relationship of keystone taxa, i.e. the strength of the BNC relationship first became weak and then strong with increased network complexity. Together, these results highlighted the significant insight that there is not always positive relationship between biodiversity/network complexity and multi-nutrient cycling, even between network complexity and BNC relationship in real-world ecosystems, suggesting that preserving microbial association is important in aquatic health managing and evaluating the freshwater salinization problem.

DETERMINANTS OF FACTORS INFLUENCING TAX AVOIDANCE IN PREPARING FINANCIAL STATEMENT AMONG SME TAXPAYERS

The tax avoidance cases in Malaysia increased year by year. The tax avoidance led to country revenue under collected. Therefore, this study aims to investigate the factors that lead to tax avoidance among SME taxpayers in Penang, Malaysia. The study is performed by adopting the Approach-Avoidance Theory model. This model widely used to explain the decision making by the taxpayers to involve in tax avoidance activities. The framework of the study focused on four level factors namely tax complexity, tax compliance costs, tax rate and government transparency spending and tax education and tax knowledge. The objectives of this study are to determine the level and the relationship of tax complexity, tax compliance costs, tax rate and government transparency spending and tax education and tax knowledge and tax avoidance. This study employed the quantitative method by distributing the surveys to the SME taxpayers in Penang state. The total sample of this study was 420 respondents. Collected data were analyzed by using SPSS statistic version 25. As a result, the findings from the regression analysis revealed that tax complexity, tax compliance costs and tax education and tax knowledge significantly on the tax avoidance activities among SME taxpayers in Penang state. However, the study discovered that there is an insignificantly relationship between tax rate and government transparency spending with tax avoidance activities in Penang state. The results of this research are used to develop awareness among the SME owners and to reduce the tax avoidance cases in Penang, Malaysia.

The impact of working memory on divergent thinking flexibility

The current study focuses on the relationship between working memory (WM) and flexibility, which is a dimension of divergent thinking. The research consisted of two experiments in which the participants’ task was to categorize given objects into as many categories as possible. We assumed that manipulation of the visual or relational complexity of a set of figures would respectively affect WM’s ability to maintain and process goal-relevant information. Additionally, the dual-task paradigm was used to observe the relocation of attention resources in the task because WM capacity is limited by attention resources. We hypothesized that both attentional control and the ability to maintain/process goal-relevant information in WM would affect the level of flexibility. The results show that an increased load on WM storage and on processing mechanisms leads to a decline in flexibility scores, which becomes especially apparent when the secondary task, which makes WM capacity more vulnerable, is applied. We conclude that the flexibility of divergent thinking is equally positively associated with the efficiency of WM mechanisms, i.e., storage and processing of current information, and the ability to use controlled attention.

On relational complexity and base size of finite primitive groups

In this paper we show that if $G$ is a primitive subgroup of $S_{n}$ that is not large base, then any irredundant base for $G$ has size at most $5 \log n$. This is the first logarithmic bound on the size of an irredundant base for such groups, and is best possible up to a small constant. As a corollary, the relational complexity of $G$ is at most $5 \log n+1$, and the maximal size of a minimal base and the height are both at most $5 \log n.$ Furthermore, we deduce that a base for $G$ of size at most $5 \log n$ can be computed in polynomial time.

Cryo-EM structures of the Synechocystis sp. PCC 6803 cytochrome b6f complex with and without the regulatory PetP subunit.

In oxygenic photosynthesis, the cytochrome b6f (cytb6f) complex links the linear electron transfer (LET) reactions occurring at photosystems I and II and generates a transmembrane proton gradient via the Q-cycle. In addition to this central role in LET, cytb6f also participates in a range of processes including cyclic electron transfer (CET), state transitions and photosynthetic control. Many of the regulatory roles of cytb6f are facilitated by auxiliary proteins that differ depending upon the species, yet because of their weak and transient nature the structural details of these interactions remain unknown. An apparent key player in the regulatory balance between LET and CET in cyanobacteria is PetP, a ∼10 kDa protein that is also found in red algae but not in green algae and plants. Here, we used cryogenic electron microscopy to determine the structure of the Synechocystis sp. PCC 6803 cytb6f complex in the presence and absence of PetP. Our structures show that PetP interacts with the cytoplasmic side of cytb6f, displacing the C-terminus of the PetG subunit and shielding the C-terminus of cytochrome b6, which binds the heme cn cofactor that is suggested to mediate CET. The structures also highlight key differences in the mode of plastoquinone binding between cyanobacterial and plant cytb6f complexes, which we suggest may reflect the unique combination of photosynthetic and respiratory electron transfer in cyanobacterial thylakoid membranes. The structure of cytb6f from a model cyanobacterial species amenable to genetic engineering will enhance future site-directed mutagenesis studies of structure-function relationships in this crucial ET complex.

Dynamic dispatch of connected taxis for large-scale urban road networks with stochastic demands: An MFD-enabled hierarchical and cooperative approach

The dynamic dispatch of taxis is an important way to improve the service efficiency of taxis and reduce cruising distance. However, in a complex urban road network with extensive and stochastic roadside service demands, current macroscopic dispatch methods can hardly establish accurate and real-time matching relationships between taxis and passengers, and microscopic dispatch methods have the disadvantage of excessive computational complexity and nonupdatable match relationships. To this end, this paper proposes a hierarchical and cooperative macroscopic and microscopic dynamic dispatching approach for real-time urban network taxis in a connected taxi (CTaxi) information environment. First, network traffic flow dynamic evolution is described based on a macroscopic fundamental diagram (MFD), and the optimal macroscopic dispatching model is proposed to optimize the distribution of CTaxis for large-scale urban road networks with multiple MFD sub-regions. Second, to avoid the phenomenon of CTaxis blindly searching for passengers, a microscopic and relationship-updatable dispatching strategy between CTaxis and passengers is established within each MFD sub-region considering stochastic service demands and the signal timing of intersections. Finally, numerical experiments are conducted in a real road network to compare the performance of four methods: no CTaxi dispatch (NCD), conventional CTaxi dispatch (CCD), MPC dispatching (MPCD) and the dispatching strategy cooperating macro and micro (DSCMM) proposed in this paper. The results show that the DSCMM method can reduce the idle driving distance by 26.8%, 10.8% and 8.3% and the passenger waiting time by 11.0%, 13.4% and 6.4% compared to NCD, CCD and MPCD, respectively. Additionally, the market allocation of CTaxis under four scenarios is discussed, and the results demonstrate that the proposed DSCMM method is effective in improving the efficiency of CTaxis operation and reducing the waste of service resources in urban road networks with different service scales.

Health System Resilience and Community Participation amidst the Covid 19 Pandemic: A Case Study of SONJO (Sambatan Jogja) in the Special Region of Yogyakarta, Indonesia

There is a growing concern over how the Covid-19 pandemic might affect low- and medium- income countries (LMOCs) worse compared to high-income countries. The main contributor to this aggravation is the health system is not strong enough to sustain the shock the system caused by the pandemic. Therefore, strengthening the health system resilience in LMOCs is imperative to lessen the gap between countries. The health system resilience constitutes a set of capabilities to maintain shocks, adapt to the shock and transform into actions to keep the essential functions of the health system. The essential factor contributing to the resilience of a health system is the recognition of the complexity and dynamic power relationship underlying the system, including opening access for community participation. This study aims to describe how SONJO, a community-based organization in the Special Region of Yogyakarta (SRY), Indonesia, has played a crucial role in strengthening the health system resilience in the province during the Covid-19 pandemic 2021. As the nature of the research, this study conducts a qualitative approach to collect and analyze the data. The study shows that SONJO can develop adaptive mechanisms to cope with the outbreak through the collective action of diverse actors in the health system translated from shared knowledge, coordination, and values. SONJO acts as a social broker that bridges a wide range of actors in the health system of SRY through a digital platform.

Soil microbial network complexity predicts ecosystem function along elevation gradients on the Tibetan Plateau

The contributions of soil microbial diversity for the multifunctionality of ecosystem functions remain little understood despite the well-known importance of soil microbial communities for regulating many ecosystem functions. Existing studies have typically focused on the role of univariate diversity or composition metrics, while ignoring that ecosystem processes are carried out via complex webs of co-occurrence networks among microbiome members. Here, the relationships of soil microbial diversity and network complexity (reflected by linkage density of inferred co-occurrence patterns) with multiple types of ecosystem functions (ecosystem multifunctionality) were assessed along a multi-elevation gradient (3755–5120 m) on the Tibetan Plateau. These functions included a suite of 18 variables related to soil nutrient status, soil carbon, nitrogen, and phosphorous cycles, plant growth, mitigation of greenhouse gases, and control of potential fungal plant pathogens in soils. The findings showed that the diversity, network complexity of both bacterial and fungal communities, as well as ecosystem multifunctionality significantly declined with increasing elevation. Although significant linear positive relationships were identified between diversity, network complexity of both microbial communities, and ecosystem multifunctionality, the relationships of network complexity had more positive relationships and explained more variance than diversity. These relationships remained robust when the confounding multifunctionality drivers (i.e., climatic, soil, and biotic factors) were simultaneously accounted for and when multiple multifunctionality approaches (i.e., multiple single functions, average multifunctionality, multithreshold, and multidimensional functions) were used. Further analysis showed that microbial diversity effects on multifunctionality were indirectly driven by microbial network complexity. This explicit empirical evidence shows that microbial network complexity enables a better prediction of ecosystem functions than the simplified microbial diversity metrics most studies applied in the past. Our results highlight the importance of co-occurrence networks as a key component of microbial biodiversity linking it with ecosystem multifunctionality.

Social complexity and core-periphery relationships in an Andean Formative ceremonial centre: domestic occupation at Chavín de Huántar

The site of Chavín de Huántar, Peru, lies at the heart of developing social complexity in the Andean Formative period. The archaeological contexts on the site's immediate periphery are assessed to investigate the nature of occupation, activities practised, and relationships between the area's inhabitants and Chavín's ceremonial centre. The peripheral Wacheqsa sector, which began as a modest, domestic occupation in the second millennium BC, was reconfigured c. 800 cal BC into a more substantial settlement, perhaps inhabited by craftspeople producing artefacts for the Chavín authorities. The implications of this study are relevant to wider questions regarding relationships between monumental ceremonial centres and their immediate peripheries, and the study of early socio-economic complexity.

Relational integration predicted numerical inductive reasoning: ERP Evidence from the N400 and LNC.

As relational integration performance can be used to predict reasoning ability, the present study aimed to provide electrophysiological evidence for numerical inductive reasoning. Number series with two levels of relational complexity were utilized, including simple and hierarchical problems (such as "15-16-17" versus "15-16-18"). Two tasks were adopted: a relational integration task that required to determine whether the numerical relations were changed across numbers; a number series task that required to determine whether a hidden rule was acquired (Experiment 1) or to predict the subsequent number (Experiment 2), whose phases were divided as rule searching, rule discovery, and rule following. The event-related potential (ERP) results of both experiments indicated that, in contrast to simple problems, hierarchical problems triggered enhanced N400 and late negative component (LNC), reflecting numerical fact retrieval, and generalizing novel hypotheses about the hidden rules by integrating adjacent numerical relations, respectively; relational integration showed similar N400 and LNC activation patterns to rule discovery (Experiment 1) or rule searching (Experiment 2). Additionally, the N400 and LNC elicited by relational integration showed strong positive correlations and even were able to predict the ones triggered by rule discovery (Experiment 1) or rule searching (Experiment 2). Therefore, the results supported the role of relational integration in numerical inductive reasoning and thereby in intelligence.

Corporate Sustainability Efficiency and Firm Value. A Study of Nigeria’s Deposit Money Banks

Concerns about climate change, and environmental sustainability have brought to the public fore the need for corporate organizations to incorporate sustainability information in their reports. This study was carried out to examine the relationship between corporate sustainability efficiency and market value of listed Deposit Money Banks in Nigeria. The population of the study consist of all listed DMBs in Nigeria. Data for the study were obtained from published financial reports for the period 2017 to 2020. Findings of the study showed that social, economic and environmental efficiency practices have a significant positive effect on market values of listed DMBs in Nigeria. The study also finds a positive but not significant relationship of bank complexity with market value of DMBs and recommends amongst others that DMBs should intensify efforts to ensure adequate attention is given to sustainability efficiency practices to attract higher stock market values.