Graph Technique Research Articles

Are parenchymal cells a source of supplemental diet for aphids?

AbstractPrior to feeding on phloem, aphids perform a preamble of brief intracellular punctures of the cortical parenchyma, ingesting a small amount of cytoplasm from each cell. Given the length of time aphids spend puncturing parenchyma cells before and after phloem feeding, we propose that they are not just testing for potential hosts or mobilizing phloem nutrients, but are actively engaged in ‘cytoplasmic feeding’. We combine the electrical penetration graph (EPG) technique to monitor feeding behavior of Myzus persicae (Sulzer) (Hemiptera: Aphididae) with confocal fluorescence microscopy to determine the uptake of parenchyma cytoplasm in the model plant Arabidopsis thaliana (L.) Heynh. (Brassicaceae). Aphids repetitively punctured parenchyma cells throughout the monitoring period, both before and after phloem feeding. As aphids puncture parenchyma cells of A. thaliana expressing cytoplasmic yellow fluorescent protein, the protein is ingested, increasing the intensity in the aphid stylet. The extended time of high‐frequency punctures of parenchyma cells prior to phloem sap ingestion avoids the dilution of the intestinal content resulting from immediate phloem feeding. The enriched nutrient content of parenchyma cytoplasm has time to be absorbed by the intestine into the hemocoel without dilution and excretion in the honeydew.

Planning of Transportation Infrastructure Networks for Sustainable Development with Case Studies in Chabahar

This article addresses the problem of increasing transport services that intercontinental corridors demand from the urban infrastructure networks along their routes. Yet, attention has not been paid to the coordination between the transportation potentials of a city infrastructure network located on the path of an intercontinental corridor and the sustainable application of the corridor itself. This article discusses solving this problem by increasing the transportation capacities of the cities on the path of the corridor. With field studies in Chabahar, we observe the situation of its transportation infrastructure network to discover shortcomings and suggest required changes. This paper recommends the necessary changes and improvements in the urban transportation system of Chabahar to have a sustainable intercontinental corridor and an effective urban infrastructure network simultaneously. The research methods used include observation of traffic flow and behavior in travel origins, destinations, and paths in Chabahar. Then, this study builds a mathematical model with a graph technique to calculate the traffic capacities on the nodes and streets and determine places that require changes. Analyses show that 13,420 cars enter just the center of Chabahar city due to the increasing pressure of the Chabahar–Milak corridor. This paper recommends a multi-modal transportation system with an urban public transport network. It also suggests physical and geometric corrections in sight distances and longitudinal curves of streets, sidewalks, and squares. We find urban transportation failures in the city and present a comprehensive transportation plan for its improvement. This model is applicable in all cities on the route of corridors and assists their sustainable function and urban transport system simultaneously.

AIMedGraph: a comprehensive multi-relational knowledge graph for precision medicine.

The development of high-throughput molecular testing techniques has enabled the large-scale exploration of the underlying molecular causes of diseases and the development of targeted treatment for specific genetic alterations. However, knowledge to interpret the impact of genetic variants on disease or treatment is distributed in different databases, scientific literature studies and clinical guidelines. AIMedGraph was designed to comprehensively collect and interrogate standardized information about genes, genetic alterations and their therapeutic and diagnostic relevance and build a multi-relational, evidence-based knowledge graph. Graph database Neo4j was used to represent precision medicine knowledge as nodes and edges in AIMedGraph. Entities in the current release include 30 340 diseases/phenotypes, 26 140 genes, 187 541 genetic variants, 2821 drugs, 15 125 clinical trials and 797 911 supporting literature studies. Edges in this release cover 621 731 drug interactions, 9279 drug susceptibility impacts, 6330 pharmacogenomics effects, 30 339 variant pathogenicity and 1485 drug adverse reactions. The knowledge graph technique enables hidden knowledge inference and provides insight into potential disease or drug molecular mechanisms. Database URL: http://aimedgraph.tongshugene.net:8201.

An investigation of distributed computing for combinatorial testing

SummaryCombinatorial test generation, also called ‐way testing, is the process of generating sets of input parameters for a system under test, by considering interactions between values of multiple parameters. In order to decrease total testing time, there is an interest in techniques that generate smaller test suites. In our previous work, we used graph techniques to produce high‐quality test suites. However, these techniques require a lot of computing power and memory, which is why this paper investigates distributed computing for ‐way testing. We first introduce our distributed graph colouring method, with new algorithms for building the graph and for colouring it. Second, we present our distributed hypergraph vertex covering method and a new heuristic. Third, we show how to build a distributed IPOG algorithm by leveraging either graph colouring or hypergraph vertex covering as vertical growth algorithms. Finally, we test these new methods on a computer cluster and compare them to existing ‐way testing tools.

Sugars and cuticular waxes impact sugarcane aphid (Melanaphis sacchari) colonization on different developmental stages of sorghum

Sugarcane aphid (SCA; Melanaphis sacchari) is a devastating pest of sorghum (Sorghum bicolor) that colonizes sorghum plants at different growth stages. Leaf surface characteristics and sugars often influence aphid settling and feeding on host plants. However, how changes in cuticular waxes and sugar levels affect SCA establishment and feeding at different development stages of sorghum have not been explored. In this study, two- and six-week-old BTx623 plants, a reference line of sorghum, was used to evaluate plant-aphid interactions. Monitoring aphid feeding behavior using Electrical Penetration Graph (EPG) technique revealed that aphids spent more time in the sieve element phase of six-week-old plants compared to two-week-old plants. Significant differences were found in the time spent to reach the first sieve element and pathway phases between the two- and six-week-old plants. However, no-choice aphid bioassays displayed that SCA population numbers were higher in two-week-old plants compared to six-week-old plants. Differences in the abundance of wax and sugar contents were analyzed to determine how these plant components influenced aphid feeding and proliferation. Among the cuticular wax compounds analyzed, α-amyrin and isoarborinone increased after 10 days of aphid infestation only in six-week-old plants. Trehalose content was significantly increased by SCA feeding on two- and six-week-old plants. Furthermore, SCA feeding depressed sucrose content and increased levels of glucose and fructose in two-week-old but not in six-week-old plants. Overall, our study indicates that plant age is a determinant for SCA feeding, and subtle changes in triterpenoids and available sugars influence SCA establishment on sorghum plants.

A survey of clustering large probabilistic graphs: Techniques, evaluations, and applications

AbstractGiven the growth of uncertainty in the real world, analysing probabilistic graphs is crucial. Clustering is one of the most fundamental methods of mining probabilistic graphs to discover the hidden patterns in them. This survey examines an extensive and organized analysis of the clustering techniques of large probabilistic graphs proposed in the literature. First, the definition of probabilistic graphs and modelling them are introduced. Second, the clustering of such graphs and their challenges, such as uncertainty of edges, high dimensions, and the impossibility of applying certain graph clustering techniques directly, are expressed. Then, a taxonomy of clustering approaches is discussed in two main categories: threshold‐based and possible worlds‐based methods. The techniques presented in each category are explained and examined. Here, these methods are evaluated on real datasets, and their performance is compared with each other. Finally, the survey is summarized by describing some of the applications of probabilistic graph clustering and future research directions.

Pengaruh Token Ekonomi Terhadap Pengurangan Perilaku Agresif Pada Siswa ADD di TK Inklusi PAS Baitul Qur’an Ponorogo

Aggressive behavior is behavior that is intended to hurt someone intentionally, both physically and psychologically. Children with a diagnosis of ADD or attention deficit disorder often have behavioral problems. This study aims to determine the effect of economic tokens on reducing aggressive behavior in ADD (Attention Deficit Disorder) children. The research subject is a 5 year and 10 month old boy with the initials K who attends Inclusive Kindergarten and is diagnosed with Attention Deficit Disorder ADD by a psychologist. The research method used is an experimental method in the form of single subject research with an A-B-A design, the analysis method used is a visual analysis technique of graphs (visual analysis of graph data). The results of this study state that economic tokens can reduce or reduce aggressive behavior in the form of biting behavior in ADD (Attention Deficit Disorder) children. This can be seen from the percentage comparison between the conditions of besaline 1 (A1) and conditions of besaline 2 (A2) which shows a decrease in the percentage of 25% to 12%.

Engineering Student Profile Related to the Market of Operation: Competence Perspective

This article proposes a method/framework to model and quantify engineer competencies from the point of view of students, teachers, and the market. Design/Methodology/Approach: As this work has a practical nature to solve a real problem related to engineering course design, the applied methodology was design science research (DSR). Limitations of the Investigation: The study carries out in a single course, and the instrument allows it to be applied only in courses that use the competence of the conceive design implement operate (CDIO) Syllabus. The number of respondents tends to be low because the student must attend the components of the course (students of the last year or former students). Practical Implications: This study allows us to analyze the differences between the competence developed during the undergraduate course and the labor market demand. Thus, course design improvements can be implemented more effectively. Originality/Value: There are no works in the literature that propose the use of the graph technique in conjunction with the analytic hierarchy process (AHP) to map engineer competence and model performance indicators for the competence developed by students in an engineering course.

Probing behavior of Aphis fabae and Myzus persicae on three species of grapevines with analysis of grapevine leaf anatomy and allelochemicals

The peach-potato aphid Myzus persicae (Sulzer) and the black bean aphid Aphis fabae Scopoli are polyphagous and cosmopolitan hemipterans, therefore they can infest grapevines in all areas of cultivation. Electrical Penetration Graph (EPG) technique was applied to monitor the probing behavior of A. fabae and M. persicae on Vitis amurensis Rupr., Vitis riparia Michaux, and Vitis vinifera L. The content of major flavonoids and stilbenoids in grapevine leaves and epidermal thickness, distance between abaxial leaf surface and phloem, and the simulated shortest pathway from epidermis to phloem that might have affected aphid probing were also analyzed. Aphid probing was limited mainly to non-vascular tissues on the three studied grapevine species. Phloem phase occurred in 32%, 14%, and 6% of A. fabae and in 76%, 39%, and 74% of M. persicae on V. amurensis, V. riparia and V. vinifera, respectively. Phloem phase consisted of only salivation into sieve elements and lasted less than 2.5 minutes on average in all aphids. The time to reach the first phloem phase on grapevines was 5.0 hours in A. fabae and 2.6–3.6 hours in M. persicae. Of the analyzed flavonoids, catechin, epicatechin, and quercetin occurred in all grapevine species, while rutin – in V. amurensis and V. riparia and isorhamnetin only in V. amurensis. Of the analyzed stilbenoids, piceid occurred in all grapevines, resveratrol in V. amurensis and V. vinifera, and ε-viniferin only in V. vinifera. Aphid behavior demonstrated that V. amurensis, V. riparia and V. vinifera are not attractive host plants to A. fabae and M. persicae. It is likely that the content of flavonoids and stilbenoids contributes to the limited susceptibility of the three grapevine species to A. fabae and M. persicae, while the observed slight differences in the anatomical structure of the leaves seem not significant in this context.

Graph-Based methodology for Multi-Scale generation of energy analysis models from IFC

Process digitalisation and automation is unstoppable in all industries, including construction. However, its widespread adoption, even for non-experts, demands easy-to-use tools that reduce technical requirements. BIM to BEM (Building Energy Models) workflows are a clear example, where ad-hoc prepared models are needed. This paper describes a methodology, based on graph techniques, to automate it by highly reducing the input BIM requirements found in similar approaches, being applicable to almost any IFC. This is especially relevant in retrofitting, where reality capture tools (e.g., 3D laser scanning, object recognition in drawings) are prone to create geometry clashes and other inconsistencies, posing higher challenges for automation. Another innovation presented is its multi-scale nature, efficiently addressing the surroundings impact in the energy model. The application to selected test cases has been successful and further tests are ongoing, considering a higher variety of BIM models in relation to tools and techniques used and model sizes.

An Optimal Transition-Based Recovery Policy for Controlling Deadlock Within Flexible Manufacturing Systems Using Graph Technique

Weighted Petri nets are common tools for modeling and validating discrete event systems involving resource allocation, such as flexible manufacturing systems (FMSs). A subclass of weighted Petri nets called a system of sequential systems with shared resources (S <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> R) has the power for modeling complex FMSs where the execution of an operation may require multiple resource types and multiple units of some resource types. Deadlock resolution is a crucial issue for the operation of an FMS. A direct and efficient policy is developed in this paper for detecting deadlock markings by extracting a weighted resource flow graph (WRFG) from an S <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> R and recovering them by synthesizing a recovery-transition-based controller. This study contributes to the field with five folds: (1) with S <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> R, an efficient integrated policy is put forward for robust supervisor synthesis; (2) it enhances an algorithm for extracting the WRFG from an S <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> R to reveal the shared resource competitions by different processes; (3) to detect partial deadlock markings, a technique for finding weighted circular wait graphs (WCWGs) in WRFG is presented; (4) with WCWGs, an algorithm is designed for the design of recovery-transition-based controller such that the resulting controlled system becomes deadlock-free; and (5) it presents a comprehensive analysis to demonstrate the proposed method by using the Integrated Net Analyzer (INA). With the proposed policy, it is not necessary to generate a reachability graph, making the method efficient. Finally, the performance of the proposed policy is illustrated by some commonly used examples.

OPTIMIZATION OF QUANTITATIVE RESEARCH METHODS IN SOCIAL SCIENCES IN THE ERA OF BIG DATA

As information technology continues to advance, the complexity of data is ever-increasing. Traditional quantitative research methods in the social sciences, such as basic visualization and traditional statistical models, are gradually becoming inadequate in meeting the demands of modern data analysis. Despite the challenges that big data presents, it also brings new opportunities – through its usage, the optimization of traditional methods can be achieved. More intricate graphing techniques such as mosaic plots, alluvial plots, slope charts, and area charts, alongside machine learning algorithms that are better adapted for big data analysis such as decision trees, random forests, and K-Means algorithm, are opening new avenues for quantitative analysis in social sciences. This will ultimately foster further development of the field by allowing new methods and ideas to emerge.

A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions

Vulnerability assessment in industrial IoT networks is critical due to the evolving nature of the domain and the increasing complexity of security threats. This study aims to address the existing gaps in the literature by conducting a comprehensive survey on the use of attack graphs for vulnerability assessment in IoT networks. Attack graphs serve as a valuable cybersecurity tool for modeling and analyzing potential attack scenarios on systems, networks, or applications. The survey covers the research conducted between 2016 and 2021(34 peer-reviewed journal articles and 28 conference papers), identifying and categorizing the main methodologies and technologies employed in generating and analyzing attack graphs. In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. The evaluation of the performance of these attack graph models using IoT networks or devices as case studies is also emphasized. This survey provides valuable insights into the state-of-the-art attack graph techniques for IoT network vulnerability assessment, identifying various applications, performances, research opportunities, and challenges. As a reference source, it serves to inform academicians and practitioners interested in leveraging attack graphs for IoT network vulnerability assessment and guides future research directions in this area.

Subexponential Parameterized Algorithms for Planar and Apex-Minor-Free Graphs via Low Treewidth Pattern Covering

We prove the following theorem. Given a planar graph $G$ and an integer $k$, it is possible in polynomial time to randomly sample a subset $A$ of vertices of $G$ with the following properties: (i) $A$ induces a subgraph of $G$ of treewidth $\mathcal{O}(\sqrt{k}\log k)$, and (ii) for every connected subgraph $H$ of $G$ on at most $k$ vertices, the probability that $A$ covers the whole vertex set of $H$ is at least $(2^{\mathcal{O}(\sqrt{k}\log^2 k)}\cdot n^{\mathcal{O}(1)})^{-1}$, where $n$ is the number of vertices of $G$. Together with standard dynamic programming techniques for graphs of bounded treewidth, this result gives a versatile technique for obtaining (randomized) subexponential parameterized algorithms for problems on planar graphs, usually with running time bound $2^{\mathcal{O}(\sqrt{k} \log^2 k)} n^{\mathcal{O}(1)}$. The technique can be applied to problems expressible as searching for a small, connected pattern with a prescribed property in a large host graph, examples of such problems include Directed $k$-Path, Weighted $k$-Path, Vertex Cover Local Search, and Subgraph Isomorphism, among others. Up to this point, it was open whether these problems can be solved in subexponential parameterized time on planar graphs, because they are not amenable to the classic technique of bidimensionality. Furthermore, all our results hold in fact on any class of graphs that exclude a fixed apex graph as a minor, in particular on graphs embeddable in any fixed surface.

Modeling and simulation of the kinematic behavior of the deployment mechanism of solar array for a 1‐U CubeSat

AbstractKinematics of deployable solar array mechanisms in CubeSat satellites have considerable influence on the stability and attitude control of a satellite, especially in low mass systems as CubeSats. One of the issues with the conventional solar panel deployment mechanisms in CubeSats is the speed of its deployment, especially when position‐lock to hold the panels back from oscillation is lacking. The generated oscillation becomes more pronounced in a system equipped with solar tracking unit and thus, reduces available projected area of the panels and causing fatigue at the yoke and panel hinges. This work aims at modeling and simulation of the 1‐U CubeSat solar panel deployment mechanism vibration control using fisher wire. Two‐fold panel deployment mechanism with a rolling sun‐tracking tilt mechanism was developed. The system performance from viewpoint of vibration analysis was evaluated using mass‐spring‐damper method and bond graph techniques. Numerical simulations and experiments were performed to validate the proposed method. The modeling and computational analysis were done with SOLIDWORKS software. The system was tested for vibration and stability using the seismic mass‐spring‐and‐damper arrangement to validate the model. A 3‐D printing was generated and tested to evaluate its vibration performance and its effects during deployment. The result was such that the two panels attached to a wing hinged at Y – and – Y directions deployed slowly and smoothly at approximately 2 s, giving room for the vibration to decay exponentially towards zero. This agrees with reported works where a DC motor was used to control speed of deployment by increasing time to 6.8 s. The simulated and experimental results of the printed model showed close agreement with the theoretical values with an error of 0.03% in energy supply reliability and up to 400% power generation potential when compared to body mounted solar panels with the same satellite specification without a significant impact on system strength and stability.

Antifeedant Potential of Geranylacetone and Nerylacetone and Their Epoxy-Derivatives against Myzus persicae (Sulz.).

Geranylacetone and nerylacetone are natural sesquiterpenoids, which play various roles in plant-insect interactions, including the deterrent and repellent effects on herbivores. The structural modifications of natural compounds often change their biological activities. The aim of the study was to evaluate the effect of geranylacetone, nerylacetone and their epoxy-derivatives on the probing and settling behavior of Myzus persicae (Sulz.) (Hemiptera: Aphididae). The no-choice test using the Electrical Penetration Graph (EPG) technique showed that the probes before the first phloem phase were usually shorter than 3 min, which means that they were terminated within the epidermis and/or outer layers of mesophyll. This resulted in a tendency to delay the initiation of the phloem phase in aphids, which reflects a weak preingestive deterrent activity of the studied compounds at the level of non-vascular tissues. Most M. persicae showed bouts of sustained phloem sap ingestion. However, the 24-h free-choice test demonstrated that aphids did not settle on the leaves treated with geranylacetone, nerylacetone, and their epoxy-derivatives. The refusal to settle after the consumption of phloem sap on treated plants indicated that the studied compounds had postingestive deterrent activity. The epoxidation of geranylacetone and nerylacetone did not evoke significant changes in their activity profiles.

Local and landscape factors determining the abundance and richness of insect pests and arthropod predators in Bt and non-Bt soybean

Agricultural landscapes of the Pampas and Campos biome have changed considerably due to the expansion of annual crops over non-crop areas, soybean seeding and the adoption of lepidopteran-resistant varieties (Bt technology). These changes have a great impact on predatory and phytophagous arthropods, which have been scarcely studied in Uruguay. The following aspects were evaluated: (a) the effect of vegetation cover composition (landscape factor), Bt technology (varieties expressing Cry1Ac protein) and field margins (local factors), on the abundance of the main pests and predators of soybean; b) the role of refuge areas (non-Bt soybean) in determining the abundance and richness of arthropod predators in Bt soybean crops, and c) the effect of Cry1Ac protein on the biology, reproduction and feeding behavior of Piezodorus guildinii (Hemiptera: Pentatomidae). In the northern Uruguayan littoral, during two years, predators and pests were sampled in 90 commercial non-Bt and Bt soybean fields and refuge areas. Biological and reproductive parameters of P. guildinii fed with Bt soybean pods and their possible effect on feeding behavior were evaluated using the electrical penetration graph technique. The main results obtained were: a) i. Bt soybean presented lower abundance of defoliating lepidoptera, without affecting predator abundance; ii. Soybean predators’ abundance was negatively related to the proportion of this crop in the landscape, but positively related to natural grassland and other crops; iii. Predators’ abundance between margins and within soybean fields was positively associated; b) Bt predators’ abundance and richness was positively associated with their values in refuge areas, evidencing for the first time their role in the conservation of beneficial fauna; c) biological and reproductive parameters and feeding behavior of P. guildinii were not affected by the ingestion of Cry1Ac protein expressed in Bt soybean pods. These results contribute to the possibilities of ecological intensification designs of national and regional production systems through pest management approached from a landscape perspective.

Multiple Graph Adaptive Regularized Semi-Supervised Nonnegative Matrix Factorization with Sparse Constraint for Data Representation

Multiple graph and semi-supervision techniques have been successfully introduced into the nonnegative matrix factorization (NMF) model for taking full advantage of the manifold structure and priori information of data to capture excellent low-dimensional data representation. However, the existing methods do not consider the sparse constraint, which can enhance the local learning ability and improve the performance in practical applications. To overcome this limitation, a novel NMF-based data representation method, namely, the multiple graph adaptive regularized semi-supervised nonnegative matrix factorization with sparse constraint (MSNMFSC) is developed in this paper for obtaining the sparse and discriminative data representation and increasing the quality of decomposition of NMF. Particularly, based on the standard NMF, the proposed MSNMFSC method combines the multiple graph adaptive regularization, the limited supervised information and the sparse constraint together to learn the more discriminative parts-based data representation. Moreover, the convergence analysis of MSNMFSC is studied. Experiments are conducted on several practical image datasets in clustering tasks, and the clustering results have shown that MSNMFSC achieves better performance than several most related NMF-based methods.

Toward Models of Impact and Recovery of the US Western Grid from Earthquake Events

A Cascadia Subduction Zone (CSZ) earthquake will cause widespread damage to numerous lifelines and infrastructure along the northern US west coast. The goal of the presented research is to provide a bottom up estimate of the impact on and subsequent recovery of a Cascadia Subduction Zone earthquake on the US western grid to supplement and enhance the expert opinion estimates provided to date. The scope is limited to only consideration of shaking damage to utility substation equipment components of a power system model. The analysis utilizes probabilistic models of damage and recovery for substation power system assets, along with graph techniques for modeling connectivity, and Monte Carlo quasi steady state power flow solutions. The results show that a conservative estimate of the initial damage and loss of load is approximately 4000 MW, with a recovery estimate of 230 days.

An Augmented Reality CBIR System Based on Multimedia Knowledge Graph and Deep Learning Techniques in Cultural Heritage

In the last few years, the spreading of new technologies, such as augmented reality (AR), has been changing our way of life. Notably, AR technologies have different applications in the cultural heritage realm, improving available information for a user while visiting museums, art exhibits, or generally a city. Moreover, the spread of new and more powerful mobile devices jointly with virtual reality (VR) visors contributes to the spread of AR in cultural heritage. This work presents an augmented reality mobile system based on content-based image analysis techniques and linked open data to improve user knowledge about cultural heritage. In particular, we explore the uses of traditional feature extraction methods and a new way to extract them employing deep learning techniques. Furthermore, we conduct a rigorous experimental analysis to recognize the best method to extract accurate multimedia features for cultural heritage analysis. Eventually, experiments show that our approach achieves good results with respect to different standard measures.