Redundancy Index Research Articles

Optimal PMU placement in the Southern Cameroon Interconnected Grid considering the effect of a group of ZIBs for complete observability and dynamic stability

In this paper, a solution for optimal PMU placement in the southern Cameroon interconnected grid (SIG) is proposed to the issue of dynamic stability within the network. The power system under consideration relies on SCADA parameter monitoring, which offers unsynchronized measurements and inconsistent state estimation of the grid. Moreover, SCADA system's data scan rate hinders its efficiency in capturing the dynamic and transient behaviours in the power grid. The Approach in this research is based on the integer linear programming (ILP) considering the effect of a group of zero-injection buses (ZIBs). Subsequently, a comparative analysis is conducted to evaluate the performance of the ILP method in terms of the number of PMUs, the number of buses observable from one or more nodes, and the sum of redundancy index (SORI) in comparison to other optimization algorithms. The results obtained using MATLAB 2020a demonstrate that the ILP method, considering the effect of a group of ZIBs and the SORI, provides the most optimal solution. Furthermore, a PMU-based dynamic stability assessment is performed, validating the improvement of the visibility of voltage signals.

Integrating HEC-RAS, GIS, and LISREL for assessing and enhancing urban building resilience against flood threats: Comprehensive model and analysis

Floods pose significant threats to urban areas, resulting in substantial human and financial losses annually. The vulnerability of key urban centers to these risks diminishes their efficiency, leading to public dissatisfaction and service deficiencies. Recognizing and enhancing the resilience of essential buildings becomes crucial in mitigating these challenges. This study employs a comprehensive approach to achieve a resilience model for critical buildings facing floods. The research process involves the identification of city assets based on leveling criteria, utilizing GIS technology for spatial mapping. HECRAS software aids in river flow modeling, identifying areas lacking flood-carrying capacity. By overlaying vulnerable gravity centers with flood-prone regions, building resilience components are computed through structural factor analysis and LISREL modeling. The study identifies ten key criteria. Further analysis includes resilience modeling using TOPSIS and AHP methods. The positive ideal and negative ideal solutions are determined, resulting in the grading of building resilience. Notably, the balance redundancy index with cascading potential effects attains the highest positive ideal value at 0.257, while the resistance to a level of stress index achieves the lowest negative ideal value at 0.02. This comprehensive approach and modeling contribute to the understanding and enhancement of urban building resilience in the face of flood threats.

Identifying areas of conservation importance based on spatial patterns of evolutionary diversity for non-volant small mammals in the Andean Puna

Ecosystems around the world face a variety of threats from anthropogenic activities and drylands are among the most affected due to their unique environmental characteristics. To maintain phylogenetic history and ecological functionality in these areas, it is imperative to preserve community structure and composition by identifying and protecting key conservation areas. Various methods have been used to define these areas in need of protection; in this study, we used patterns of taxonomic and phylogenetic diversity in the arid lands of the Altiplano-Puna Bioregion of South America, using non-volant small mammal communities as a model system. Based on detailed records of species presence in the study area we estimated indices of species richness and phylogenetic redundancy. The geographic distribution of these indices was then compared to the distribution of protected areas in the region. These analyses identified areas around Lake Titicaca as being of exceptional conservation importance and in need of protection efforts. We propose a network of interconnected areas that together would provide high conservation value while allowing genetic exchange and facilitating ecological processes across landscapes.

Evaluation mechanism of sustainable development level for the cities in the Yangtze River Economic Belt under the dual-carbon policy.

Low carbon sustainable development (LCSD) has become an inevitable choice, for which China has put forward a "dual-carbon" policy. The purpose of this study is to capture the interaction between the environment and the economy in the context of this goal, thus evaluating LCSD level from a systematic perspective. This paper proposes a super slack based measurement (SBM) model with a non-equal weight structure to assess the LCSD level. Firstly, a maximum influence minimum redundancy (MIMR) index selection algorithm is designed to establish input and output index systems, which avoids redundancy indexes. Secondly, the objective function of the original super SBM employs an equal weight structure, which leads results inadequately reflect the research preferences. Therefore, the weights of indexes are introduced to form an improved super SBM. Finally, 40 cities along the Yangtze River Economic Belt (YREB) are selected for empirical analysis. Results show that (1) the LCSD level of YRBE decreases from downstream to upstream to midstream; (2) Jiangsu, Zhejiang, and Sichuan provinces have higher LCSD levels, while Hunan and Jiangxi provinces have lower levels; and (3) up to 2021, there are 32 effective cities and 8 ineffective cities. The research implies that balancing the economy-environment relationship is crucial for higher efficiency. The LCSD evaluation method not only reflects the coordination level between the economy and the environment, but also integrates the research preference into the results, providing decision support for the government to formulate carbon reduction policies and allocate resources.

DEM investigation on flow instability of particulate assemblies under coupling between volumetric and axial strains

AbstractThe discrete element method (DEM) is employed to investigate the impact of coupling between volumetric and axial strains on the flow liquefaction vulnerability of 3D cubic particulate specimens. The virtual testing program conducted here encompasses a wide range of initial states and varying degrees of coupling between volumetric and axial strains. Utilizing data obtained from DEM simulations, the evolution of micro- and macroscale variables, including coordination number, contact fabric anisotropy, redundancy index, strong force networks, invariants of the effective stress tensor, and excess pore-water pressure, is examined. Results from DEM tests indicate that coupling expansive volumetric strain with axial strain leads to a gradual loosening of the load bearing microstructure, a decrease in coordination number, and a faster change in contact anisotropy. DEM simulations demonstrate that the triggering of flow liquefaction instability is followed by a sudden increase in contact fabric anisotropy and abrupt drops in coordination number and redundancy index. Moreover, a detailed analysis of the findings suggests that the stress ratio at the onset of post-peak softening decreases with increasing expansive volumetric strains.

Optimal PMU Placement to Enhance Observability in Transmission Networks Using ILP and Degree of Centrality

The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work.

Investigation of the dense granular soil behaviour inside and outside the shear band: a three-dimensional DEM-FDM study

The present paper aims to compare the behaviour of dense granular soils inside and outside the Shear Band (SB) during the Plane Strain Compression (PSC) test using the Discrete Element Method (DEM). The flexible membrane in the PSC test was modelled by adopting a discrete element–finite difference (DEM-FDM) hybrid approach. In contrast with previous 2D studies, the present study employed 3D simulations to consider the effects of out-of-plane characteristics such as the intermediate principal stress. According to the findings, the minimum and intermediate principal stresses outside the SB were twice as high as those inside at the residual state. It was also found that mechanical coordination numbers and redundancy indexes both inside and outside the SB decreased up to the onset of the residual phase, with a higher reduction rate inside the SB. As far as fabric anisotropy is concerned, the degree of anisotropy increased both in and out the SB until the peak state, with a somewhat higher rate inside the SB. A further finding was that the distribution of normal contact forces outside the SB remained symmetrical around the vertical axis after shear banding, however, it became asymmetrical inside the SB.

Small vessel disease and cognitive reserve oppositely modulate global network redundancy and cognitive function: A study in middle-to-old aged community participants.

Cerebral small vessel disease (SVD) can disrupt the global brain network and lead to cognitive impairment. Conversely, cognitive reserve (CR) can improve one's cognitive ability to handle damaging effects like SVD, partly by optimizing the brain network's organization. Understanding how SVD and CR collectively influence brain networks could be instrumental in preventing cognitive impairment. Recently, brain redundancy has emerged as a critical network protective metric, providing a nuanced perspective of changes in network organization. However, it remains unclear how SVD and CR affect global redundancy and subsequently cognitive function. Here, we included 121 community-dwelling participants who underwent neuropsychological assessments and a multimodal MRI examination. We visually examined common SVD imaging markers and assessed lifespan CR using the Cognitive Reserve Index Questionnaire. We quantified the global redundancy index (RI) based on the dynamic functional connectome. We then conducted multiple linear regressions to explore the specific cognitive domains related to RI and the associations of RI with SVD and CR. We also conducted mediation analyses to explore whether RI mediated the relationships between SVD, CR, and cognition. We found negative correlations of RI with the presence of microbleeds (MBs) and the SVD total score, and a positive correlation of RI with leisure activity-related CR (CRI-leisure). RI was positively correlated with memory and fully mediated the relationships between the MBs, CRI-leisure, and memory. Our study highlights the potential benefits of promoting leisure activities and keeping brain redundancy for memory preservation in older adults, especially those with SVD.

Rural credit distribution in Bahia in 2017

Rural credit is an important tool for the country's economic development, and its objective is to promote rural development and increase agricultural production. However, credit distribution is uneven, favoring some regions over others. In Bahia it is no different. The objective of the present work is to evaluate and measure the distribution of rural credit in Bahia – the largest agricultural producer in the Northeast region – from the year of 2017. For this, tabular analysis, the entropy index and Theil's T and L indexes were used, as well as the redundancy index to measure the distribution of rural credit with the gross value of production as a productive counterpart. The results of the tabular analysis showed that there is a concentration of credit among the mesoregions of Bahia, an aspect that is less intense when verified by the T and L indices. When analyzing the distribution of credit and its productive counterpart, there was no concentration of credit distribution in the mesoregions bahians.

Rural credit concentration in Brazil in 2017

One of the main public policies for promoting and developing Brazilian agriculture is rural credit. This policy seeks to stimulate production and modernize the sector by applying financial resources for the purposes of costing, investment, industrialization and commercialization. However, historically, these resources have been unevenly concentrated throughout the national territory, favoring the South and Southeast regions, since the moment the rural credit policy was institutionalized. Observing this poor distribution, this study sought to measure the distribution of agricultural credit in relation to its productive response, through tabular analysis and the redundancy index for the major regions and their respective federative entities in 2017. It was concluded that credit continued to be concentrated in the South and Southeast regions, but when analyzing the productive counterpart, there was no concentration.

Type VI secretion system drives bacterial diversity and functions in multispecies biofilms

Type VI secretion system (T6SS) plays an essential role in interspecies interactions and provides an advantage for a strain with T6SS in multispecies biofilms. However, how T6SS drives the bacterial community structure and functions in multispecies biofilms still needs to be determined. Using gene deletion and Illumina sequencing technique, we estimated bacterial community responses in multispecies biofilms to T6SS by introducing T6SS-containing Pseudomonas putida KT2440. Results showed that the niche structure shifts of multispecies biofilms were remarkably higher in the presence of T6SS than in the absence of T6SS. The presence of T6SS significantly drove the variation in microbial composition, reduced the alpha-diversity of bacterial communities in multispecies biofilms, and separately decreased and increased the relative abundance of Proteobacteria and Bacteroidota. Co-occurrence network analysis with inferred putative bacterial interactions indicated that P. putida KT2440 mainly displayed strong negative associations with the genera of Psychrobacter, Cellvibrio, Stenotrophomonas, and Brevundimonas. Moreover, the function redundancy index of the bacterial community was strikingly higher in the presence of T6SS than in the absence of T6SS, regardless of whether relative abundances of bacterial taxa were inhibited or promoted. Remarkably, the increased metabolic network similarity with T6SS-containing P. putida KT2440 could enhance the antibacterial activity of P. putida KT2440 on other bacterial taxa. Our findings extend knowledge of microbial adaptation strategies to potential bacterial weapons and could contribute to predicting biodiversity loss and change in ecological functions caused by T6SS.

Adaptive, morphometric and productive responses of Brazilian hair lambs: Crossing between indigenous breeds - A machine learning approach

For the first time, the thermoregulatory, morphometric and productive responses of the Morada Nova breed and its crosses with the Santa Inês and Rabo Largo breeds in the Brazilian semi-arid region were evaluated. Subsequently, the relationship between thermoregulation and morphometric, productive and non-carcass components was verified. 30 lambs, weighing 2.26 ± 0.53 kg at birth and 7.31 ± 1.85 kg at weaning, were distributed into three genetic groups: Morada Nova (MN) and its F1 crossbred Morada Nova × Rabo Largo (RL×MN) and Morada Nova x Santa Inês (SI×MN) animals in a completely randomized factorial design (3 genetic groups × 2 sexes). Machine learning techniques were performed in order to understand the relationship between the variables and in order to identify phenotypic biomarkers. No interaction effect was observed for any variable under study (P > 0.05). Male lambs have higher heart rate (P = 0.03), are heavier (P < 0.001), have higher weight gain (P < 0.001) and higher skin weight (P = 0.01) when compared to females. MN ×SI lambs showed lower heart rate (P = 0.03) and rectal temperature (P = 0.02). Respiratory rate was similar (P = 0.26) between genetic groups. It was also observed that crossbred lambs had higher morphological measures, non-carcass components and productive responses (P < 0.001). Lung weight in purebred animals was lower (P = 0.01) when compared to MN × SI, but equal to MN × RL. The first component was characterized by morphological, productive and non-carcass components, and the second component by thermoregulatory response. The canonical correlation analysis showed that the thermoregulatory response is influenced by the morphological response (P = 0.002). Furthermore, the weight of non-carcass components does not have a relationship (P = 0.834) with thermoregulatory responses. Finally, the thermoregulatory responses did not influence (P = 0.717) the productive responses of sheep in the Brazilian semi-arid region. The redundancy index showed that 36.1% of the variation in thermoregulatory responses is explained by morphological responses, more specifically: the smaller the body length and chest circumference, the higher the animal's heart rate. The productive and morphometric responses and the non-carcass components are the main phenotypic biomarkers used to differentiate the genetic groups of lambs. The crossing of the native Brazilian semi-arid region breed led to higher body weight attributed to higher adaptability, manifested by lower rectal temperature and heart rate with no recorded increase of the morphological indicators.

Effects of pre-shearing and pre-consolidation histories on liquefaction behaviour of saturated loose sand: DEM investigation

PurposeThe study aims to investigate the effects of pre-loading histories (pre-shearing and pre-consolidation) on the liquefaction behaviour of saturated loose sand via discrete element method (DEM) simulations.Design/methodology/approachThe pre-shearing history is mimicked under drained conditions (triaxial compression) with different pre-shearing strain levels ranging from 0% to 2%. The pre-consolidation history is mimicked by increasing the isotropic compression to different levels ranging from 100 kPa to 300 kPa. The macroscopic and microscopic behaviours are analysed and compared.FindingsTemporary liquefaction, or quasi-steady state (QSS), is observed in most samples. A higher pre-shearing or pre-consolidation level can provide higher liquefaction resistance. The ultimate state line is found to be unique and independent of the pre-loading histories in stress space. The Lade instability line prematurely predicts the onset of liquefaction for all samples, both with and without pre-loading histories. The redundancy index is an effective microscopic indicator to monitor liquefaction, and the onset of the liquefaction corresponds to the phase transition state where the value of redundancy index is one, which is true for all cases irrespective of the proportions of sliding contacts.Originality/valueThe liquefaction behaviour of granular materials still remains elusive, especially concerning the effects of pre-loading histories on soils. Furthermore, the investigation of the effects of pre-consolidation histories on undrained behaviour and its comparison to pre-sheared samples is rarely reported in the DEM literature.

System‐reliability‐based disaster resilience analysis for structures considering aleatory uncertainties in external loads

AbstractThe concept of disaster resilience is getting more prominent in the era of climate change due to the increase in the intensities and uncertainties of disaster events. To effectively assess the holistic capacity of structural systems, a disaster resilience analysis framework has been developed from a system‐reliability‐based perspective. The framework evaluates resilience in terms of reliability, redundancy, and recoverability and provides quantitative indices of reliability and redundancy for structures with a resilience threshold. Although this framework enables the comprehensive evaluation of disaster resilience performance, practical applications of such concepts to the structures subjected to dynamic excitations with large aleatory uncertainty, such as earthquakes, remain challenging. This study develops a framework to assess the resilience performance of structures by taking into account the aleatory uncertainties in external forces. Along with the development of reliability and redundancy curves that can effectively accommodate such excitations, a new resilience threshold representation is proposed to incorporate recoverability in the decision‐making process. Moreover, we provide efficient procedures for calculating the reliability and redundancy curves to alleviate the computational complexity during the resilience analysis. Two earthquake application examples are presented targeting a nine‐story building and a cable‐stayed bridge system to demonstrate the enhanced practical applicability of the proposed framework.

A member redundancy index based on distributed static indeterminacy for optimum material distribution for structures with axially loaded members

Redundancy analysis in structural systems has been typically approached under particular loading conditions. Structural systems that are found to provide adequate levels of redundancy in light of such an approach may face serious threats resulting from accidental loads. Additionally, determining the degree of redundancy of a system as one unique global information ignores the spatial distribution of the redundancy in that system. Improper distribution of redundancy in the system may lead to the presence of superfluous material in parts of the system. One system measure that has been widely used to gage the level of redundancy in structures is the static indeterminacy. Hence, the redundancy matrix is an excellent tool that provides valuable insight into the distribution of the static indeterminacy among the structural members in the system; independently from any loads applied to the system. One of the essential components in the redundancy matrix is the distributed static indeterminacy. While providing satisfactory levels of redundancy in a system is encouraged, it is also necessary to optimize the material distribution in the system. Having members in the system that are highly, or even completely, redundant indicates an inefficient distribution of material and should be avoided. In this paper, a member redundancy index based on the distributed static indeterminacy is derived. This index can be used to efficiently distribute the material in the system in order to optimize its redundancy distribution.

Filter pruning via feature map clustering

With the help of network compression algorithms, deep neural networks can be applied on low-power embedded systems and mobile devices such as drones, satellites, and smartphones. Filter pruning is a sub-direction of network compression research, which reduces memory and computational consumption by reducing the number of parameters of model filters. Previous works utilized the “more-simple-less-important” criterion for pruning filters. That is, filters with the smaller norm or more sparse weights in the network are preferentially pruned. In this paper, we found that feature maps are not fully positively correlated with the sparsity of filter weights by observing the visualization of feature maps and the corresponding filters. Hence, we came up with the idea that the priority of filter pruning should be determined by redundancy rather than sparsity. The redundancy of a filter is the measure of whether the output of the filter is repeated with other filters. Based on this, we defined a criterion called redundancy index to rank the filters and introduced it into our filter pruning strategy. Extensive experiments demonstrate the effectiveness of our approach on different model architectures, including VGGNet, GoogleNet, DenseNet, and ResNet. The models compressed with our strategy surpass the state-of-the-art in terms of Floating Point Operations Per Second (FLOPs), parameters reduction, and classification accuracy.

System-Reliability-Based Disaster Resilience Analysis of Infrastructure Networks and Causality-Based Importance Measure

Abstract Civil infrastructure systems become highly complex and thus get more vulnerable to disasters. The concept of disaster resilience, the overall capability of a system to manage risks posed by catastrophic events, is emerging to address the challenge. Recently, a system-reliability-based disaster resilience analysis framework was proposed for a holistic assessment of the components' reliability, the system's redundancy, and the society's ability to recover the system functionality. The proposed framework was applied to individual structures to produce diagrams visualizing the pairs of the reliability index (β) and the redundancy index (π) defined to quantify the likelihood of each initial disruption scenario and the corresponding system-level failure probability, respectively. This paper develops methods to apply the β-π analysis framework to infrastructure networks and demonstrates its capability to evaluate the disaster resilience of networks from a system reliability viewpoint. We also propose a new causality-based importance measure of network components based on the β-π analysis and a causal diagram model that can consider the causality mechanism of the system failure. Compared with importance measures in the literature, the proposed measure can evaluate a component's relative importance through a well-balanced consideration of network topology and reliability. The proposed measure is expected to provide helpful guidelines for making optimal decisions to secure the disaster resilience of infrastructure networks.

Functional diversity of snakes is explained by the landscape composition at multiple areas of influence.

Roadkill and landscape composition affect snakes at different spatial scales, depending on the functional trait value of the species, which is reflected in the functional diversity indices at the assemblage level. This study evaluated the effect of roads and landscape composition on snakes' functional diversity at different areas of influence (250, 500, 1000, and 2000 m buffer areas). We compared roadkill snake species with those assemblages inhabiting the adjacent vegetation in the Orinoco region, Colombia. We surveyed snakes using transects on the road and adjacent areas on 13 landscapes along the road. We evaluated the effect of 16 landscape metrics at six land cover classes on the snake's functional diversity at four different areas of influence (from 250 to 2000 m around the sampled sites). The functional redundancy index was higher for roadkill species, suggesting that roads eliminate species that play similar roles in the assemblage and ecosystem processes. Likewise, the low values of functional redundancy in the adjacent vegetation call attention to the fact that each species surviving in this transformed landscape has a crucial active role in ecosystem processes in snake assemblages. For roadkill snakes, forest metrics explained changes in functional richness and functional evenness at a 250 m area of influence. In comparison, transient crop and pasture metrics explained changes in functional evenness and divergence at 2000 m. For snakes inhabiting the adjacent vegetation, the cohesion of pasture explained changes in functional richness at 250 m, and forest metrics explained changes in functional redundancy and evenness at 2000 m. Anthropogenic landscape transformation may have a greater effect on snake functional diversity at local scales than roadkill. In savanna ecosystems, the presence of native forest at 2000 m radius around roads promotes the conservation of snake assemblages. However, within a 250 m radius, the risk of snake roadkill increases when the road borders native forest. Therefore, it is necessary to implement wildlife crossing in these sections of the road.

Functional Traits Mediate the Natural Enemy Response to Land Use at the Local Scale

Arthropods are key nodes for the provision of ecosystem services such as pest control, but their response to land-use change is highly variable depending on the scale of analysis and the natural enemies’ life histories. We evaluate the effects of landscape- and local-scale variables of natural enemies’ communities on small-scale agriculture. We consider functional response traits to attain a mechanistic understanding of the effect of land-use changes on the biodiversity and resilience of natural enemies’ communities. Predator and parasitoid arthropods were collected from thirteen raspberry farms to estimate functional diversity, complementarity, and redundancy indices. We found no effects of landscape heterogeneity, local habitat, or management practices on natural enemies’ functional diversity. Regarding resilience, complementarity was high at most of the sites and was not affected by the landscape or local variables. However, redundancy was affected by two management practices. Weed control decreased natural enemies’ abundance as well as the abundance of walker generalist predators and flying specialist parasitoids, while habitat richness decreased flying generalist predators. These results highlight the importance of management when the landscape matrix is heterogeneous. We conclude that small-scale agriculture in a heterogeneous landscape supports a functionally diverse enemy community, potentially promoting the resilience of pest control to land-use change.

Robustness-Based Condition Evaluation Framework for Through Tied-Arch Bridge

For through tied-arch bridges, the corrosion and degradation of the cable’s load-bearing capacity are the main external causes of cable breakage and subsequent structural failure; nevertheless, the progressive collapse after cable breakage is primarily attributed to the weak structural robustness, which makes a huge potential risk of bridge operation and maintenance (O&M). Whereas, as the basis of O&M, current condition evaluation method has not yet taken into consideration the influence of different consequences of cable breakage, resulting in unscientific conclusions for O&M decisions frequently. In this study, a robustness-based condition evaluation framework for the overall structure of the through tied-arch bridge is presented, consisting of three stages: (1) structural robustness assessment associated with tie-bar and suspender failure respectively; (2) classification of evaluation process by the results of robustness assessment, within which the overall structure is either evaluated using the code method or evaluated directly as unqualified (Condition I and II), or the structural member weightings are adjusted according to the robustness weightings (Condition III); and (3) condition evaluation of entire bridge. The evaluation processes of three conditions are further presented in accordance with the tied-arch structure and suspended deck system. To establish the robustness weightings in Condition III, the safety redundancy indexes of through tied-arch structures as well as the suspended deck system are calculated separately, combined with robustness assessment result. Applying the proposed framework to evaluating the condition of a through tied-arch bridge with different structures, the analysis and comparison indicates that, due to the robustness of the through tied-arch structure and suspended deck system, the variation in the potential risk of accidents induced by cable failure is shown intuitively through the evaluation results, which better meets the needs of guiding bridge O&M decisions consequently.