Search results for: multiplex graph

Authors: Olga Smilevska Spasova, Katerina Boshkovska, Gorica Popova, Mirjana Popovska

Abstract:

Introduction: Pneumonia is an infection of the pulmonary parenchyma. HPIV 3 is one of four viruses that is a member of the Paramyxoviridae family designated types 1-4 that have a nonsegmented, single-stranded RNA genome with a lipid-containing envelope. They are spread from the respiratory tract by aerosolized secretions or by direct contact with secretions. Type 3 is endemic and can cause serious illness in immunocompromised patients. Illness caused by parainfluenza occurs shortly after inoculation with the virus. The level of immunoglobulin A antibody in serum is the best predictor of susceptibility to infection. Streptococcus pneumonia or pneumococcus is a Gram-positive, spherical bacteria, usually found in pairs and it is a member of the genus Streptococcus. Streptococcus pneumonia resides asymptomatically in healthy carriers typically colonizing the respiratory tract, sinuses, and nasal cavity. In individuals with weaker immune systems like young infants, pneumococcal bacterium is the most common cause of community-acquired pneumonia in the world. Case Report: The aim is to present a case of lower respiratory tract infection in an infant caused by parainfluenza virus 3, S. pneumonia and undifferentiated gram-negative bacteria that was successfully treated. The infant is with a history of recurrent episodes of wheezing in the past 3mounts.Infant of 10months presents 2weeks before admittance with high fever, runny nose, and cough. The primary pediatrician prescribed oral cefpodoxime for 10days and inhaled salbutamol. Two days before admittance in hospital the infant with high fever, cough, and difficulty breathing. At admittance, infant is pale, anxious with rapid respirations, cough, wheezing and tachycardia. On auscultation: vesicular breathing sounds with high pitched wheezing and on the right coarse crackles. Investigations: Blood analysis: RBC: 4, 7 x1012L, WBC: 8,3x109L: Neut: 42.73% Lym: 41.57%, Hgb: 9.38 g/dl MCV: 62.7fl, MCH: 20.0pg MCHC: 31.8 g/dl RDW: 18.7% Plt-307.9 x109LCRP: 2,5mg/l, serum iron-7.92umol/l, O2sat-97% on blood gas analysis, puls-125/min.X-ray of chest with hyperinflationand right pericardial consolidation. Microbiological analysis of sputum sample is positive for undifferentiated gram-negative bacteria (colonizer)–resistant to cefotaxime, ampicillin, cefoxitin, sulfamet.+trimetoprim and sensitive to amikacin, gentamicin, and ciprofloxacin. Molecular multiplex RT-PCR for 19 viruses and multiplex PCR for 7 bacteria test for respiratory pathogens positive for Parainfluenza virus 3(Ct=22.73), Streptococcus pneumonia (Ct=26.75).IED: IgG-9.31g/l, IgA-0.351g/l, IgM-0.86g/l. Therapy: Treatment was started with inhaled salbutamol, intravenous antibiotic cefotaxime as well as systemic corticosteroids. On day 7 because of slow clinical resolution of chest auscultation findings and an etiologic clue with a positive sputum sample for resistant undifferentiated gram negative bacteria, a second intravenous antibiotic was administered amikacin. The infant is discharged on day 14 with resolution of clinical findings. Conclusion: Mixed co-infections with respiratory viruses and bacteria in immunocompromised infants are likely to lead to a more severe form of community acquired pneumonia that will need hospitalization.

Keywords: HPIV- 3, infant, pneumonia, S. pneumonia, x-ray chest

Procedia PDF Downloads 75

Authors: Thanusha D. Abeywickrama, Inoka C. Perera, Genji Kurisu

Abstract:

Tuberculosis, considered being as the ninth leading cause of death worldwide, cause from a single infectious agent M. tuberculosis and the drug resistance nature of this bacterium is a continuing threat to the world. Therefore TB preventing treatment is expanding, where this study designed to analyze the regulatory mechanism of GntR transcriptional regulator gene Rv0792c, which lie between several genes codes for some hypothetical proteins, a monooxygenase and an oxidoreductase. The gene encoding Rv0792c was cloned into pET28a and expressed protein was purified to near homogeneity by Nickel affinity chromatography. It was previously reported that the protein binds within the intergenic region (BS region) between Rv0792c gene and monooxygenase (Rv0793). This resulted in binding of three protein molecules with the BS region suggesting tight control of monooxygenase as well as its own gene. Since monooxygenase plays a key role in metabolism, this gene may have a global regulatory role. The natural ligand for this regulator is still under investigation. In relation to the Rv0792 protein structure, a Circular Dichroism (CD) spectrum was carried out to determine its secondary structure elements. Percentage-wise, 17.4% Helix, 21.8% Antiparallel, 5.1% Parallel, 12.3% turn and 43.5% other were revealed from CD spectrum data under room temperature. Differential Scanning Calorimetry (DSC) was conducted to assess the thermal stability of Rv0792, which the melting temperature of protein is 57.2 ± 0.6 °C. The graph of heat capacity (Cp) versus temperature for the best fit was obtained for non-two-state model, which concludes the folding of Rv0792 protein occurs through stable intermediates. Peak area (∆HCal ) and Peak shape (∆HVant ) was calculated from the graph and ∆HCal / ∆HVant was close to 0.5, suggesting dimeric nature of the protein.

Keywords: CD spectrum, DSC analysis, GntR transcriptional regulator, protein structure

Procedia PDF Downloads 222

Authors: M. Nekri, A. Khelladi

Abstract:

The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

Procedia PDF Downloads 272

Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

Abstract:

The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

Procedia PDF Downloads 129

Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

Abstract:

In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

Procedia PDF Downloads 79

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 71

Authors: Souad Slimani, Sylvain Gravier, Simon Schmidt

Abstract:

Recently, several vertex identifying notions were introduced (identifying coloring, lid-coloring,...); these notions were inspired by identifying codes. All of them, as well as original identifying code, is based on separating two vertices according to some conditions on their closed neighborhood. Therefore, twins can not be identified. So most of known results focus on twin-free graph. Here, we show how twins can modify optimal value of vertex-identifying parameters for identifying coloring and locally identifying coloring.

Keywords: identifying coloring, locally identifying coloring, twins, separating

Procedia PDF Downloads 148

Authors: Yuxi Liu, Boris Belousov, Mehrzad Esmaeili Charkhab, Oliver Tessmann

Abstract:

This paper presents a computational solution for designing reconfigurable interlocking structures that are fully assembled with SL Blocks. Formed by S-shaped and L-shaped tetracubes, SL Block is a specific type of interlocking puzzle. Analogous to molecular self-assembly, the aggregation of SL blocks will build a reversible hierarchical and discrete system where a single module can be numerously replicated to compose semi-interlocking components that further align, wrap, and braid around each other to form complex high-order aggregations. These aggregations can be disassembled and reassembled, responding dynamically to design inputs and changes with a unique capacity for reconfiguration. To use these aggregations as architectural structures, we developed computational tools that automate the configuration of SL blocks based on architectural design objectives. There are three critical phases in our work. First, we revisit the hierarchy of the SL block system and devise a top-down-type design strategy. From this, we propose two key questions: 1) How to translate 3D polyominoes into SL block assembly? 2) How to decompose the desired voxelized shapes into a set of 3D polyominoes with interlocking joints? These two questions can be considered the Hamiltonian path problem and the 3D polyomino tiling problem. Then, we derive our solution to each of them based on two methods. The first method is to construct the optimal closed path from an undirected graph built from the voxelized shape and translate the node sequence of the resulting path into the assembly sequence of SL blocks. The second approach describes interlocking relationships of 3D polyominoes as a joint connection graph. Lastly, we formulate the desired shapes and leverage our methods to achieve their reconfiguration within different levels. We show that our computational strategy will facilitate the efficient design of hierarchical interlocking structures with a self-replicating geometric module.

Keywords: computational design, SL-blocks, 3D polyomino puzzle, combinatorial problem

Procedia PDF Downloads 129

Authors: Amirhossein Dodankeh, Hadi Dabiryan, Saeed Hamze

Abstract:

Using fabrics to reinforce composites considerably leads to improved mechanical properties, including resistance to the impact load and the energy absorption of composites. Warp-knitted spacer fabrics (WKSF) are fabrics consisting of two layers of warp-knitted fabric connected by pile yarns. These connections create a space between the layers filled by pile yarns and give the fabric a three-dimensional shape. Today because of the unique properties of spacer fabrics, they are widely used in the transportation, construction, and sports industries. Polyurethane (PU) foams are commonly used as energy absorbers, but WKSF has much better properties in moisture transfer, compressive properties, and lower heat resistance than PU foam. It seems that the use of warp-knitted spacer fabric reinforced PU foam (WKSFRF) can lead to the production and use of composite, which has better properties in terms of energy absorption from the foam, its mold formation is enhanced, and its mechanical properties have been improved. In this paper, the energy absorption efficiency (EAE) of WKSFRF under low-velocity impact is investigated experimentally. The contribution of the effect of each of the structural parameters of the WKSF on the absorption of impact energy has also been investigated. For this purpose, WKSF with different structures such as two different thicknesses, small and large mesh sizes, and position of the meshes facing each other and not facing each other were produced. Then 6 types of composite samples with different structural parameters were fabricated. The physical properties of samples like weight per unit area and fiber volume fraction of composite were measured for 3 samples of any type of composites. Low-velocity impact with an initial energy of 5 J was carried out on 3 samples of any type of composite. The output of the low-velocity impact test is acceleration-time (A-T) graph with a lot deviation point, in order to achieve the appropriate results, these points were removed using the FILTFILT function of MATLAB R2018a. Using Newtonian laws of physics force-displacement (F-D) graph was drawn from an A-T graph. We know that the amount of energy absorbed is equal to the area under the F-D curve. Determination shows the maximum energy absorption is 2.858 J which is related to the samples reinforced with fabric with large mesh, high thickness, and not facing of the meshes relative to each other. An index called energy absorption efficiency was defined, which means absorption energy of any kind of our composite divided by its fiber volume fraction. With using this index, the best EAE between the samples is 21.6 that occurs in the sample with large mesh, high thickness, and meshes facing each other. Also, the EAE of this sample is 15.6% better than the average EAE of other composite samples. Generally, the energy absorption on average has been increased 21.2% by increasing the thickness, 9.5% by increasing the size of the meshes from small to big, and 47.3% by changing the position of the meshes from facing to non-facing.

Keywords: composites, energy absorption efficiency, foam, geometrical parameters, low-velocity impact, warp-knitted spacer fabric

Procedia PDF Downloads 169

Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

Abstract:

Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome

Procedia PDF Downloads 373

Authors: Fahimeh Palizban, Farshad Noravesh, Amir Hossein Saeidian, Mahya Mehrmohamadi

Abstract:

In the recent decade, the emergence of liquid biopsy has significantly improved cancer monitoring and detection. Dying cells, including those originating from tumors, shed their DNA into the blood and contribute to a pool of circulating fragments called cell-free DNA. Accordingly, identifying the tissue origin of these DNA fragments from the plasma can result in more accurate and fast disease diagnosis and precise treatment protocols. Open chromatin regions are important epigenetic features of DNA that reflect cell types of origin. Profiling these features by DNase-seq, ATAC-seq, and histone ChIP-seq provides insights into tissue-specific and disease-specific regulatory mechanisms. There have been several studies in the area of cancer liquid biopsy that integrate distinct genomic and epigenomic features for early cancer detection along with tissue of origin detection. However, multimodal analysis requires several types of experiments to cover the genomic and epigenomic aspects of a single sample, which will lead to a huge amount of cost and time. To overcome these limitations, the idea of predicting OCRs from WGS is of particular importance. In this regard, we proposed a computational approach to target the prediction of open chromatin regions as an important epigenetic feature from cell-free DNA whole genome sequence data. To fulfill this objective, local sequencing depth will be fed to our proposed algorithm and the prediction of the most probable open chromatin regions from whole genome sequencing data can be carried out. Our method integrates the signal processing method with sequencing depth data and includes count normalization, Discrete Fourie Transform conversion, graph construction, graph cut optimization by linear programming, and clustering. To validate the proposed method, we compared the output of the clustering (open chromatin region+, open chromatin region-) with previously validated open chromatin regions related to human blood samples of the ATAC-DB database. The percentage of overlap between predicted open chromatin regions and the experimentally validated regions obtained by ATAC-seq in ATAC-DB is greater than 67%, which indicates meaningful prediction. As it is evident, OCRs are mostly located in the transcription start sites (TSS) of the genes. In this regard, we compared the concordance between the predicted OCRs and the human genes TSS regions obtained from refTSS and it showed proper accordance around 52.04% and ~78% with all and the housekeeping genes, respectively. Accurately detecting open chromatin regions from plasma cell-free DNA-seq data is a very challenging computational problem due to the existence of several confounding factors, such as technical and biological variations. Although this approach is in its infancy, there has already been an attempt to apply it, which leads to a tool named OCRDetector with some restrictions like the need for highly depth cfDNA WGS data, prior information about OCRs distribution, and considering multiple features. However, we implemented a graph signal clustering based on a single depth feature in an unsupervised learning manner that resulted in faster performance and decent accuracy. Overall, we tried to investigate the epigenomic pattern of a cell-free DNA sample from a new computational perspective that can be used along with other tools to investigate genetic and epigenetic aspects of a single whole genome sequencing data for efficient liquid biopsy-related analysis.

Keywords: open chromatin regions, cancer, cell-free DNA, epigenomics, graph signal processing, correlation clustering

Procedia PDF Downloads 150

Authors: Shankaran Sitarama

Abstract:

New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

Procedia PDF Downloads 69

Authors: Mark L. Caay, Rodolfo E. Maza

Abstract:

In this paper, the authors define two new variants of domination in graphs: the marriage and the divorce domination. A subset S ⊆ V (G) is said to be a marriage dominating set of G if for every e ∈ E(G), there exists a u ∈ V (G) such that u is one of the end vertex of e. A marriage dominating set S ⊆ V (G) is said to be a divorce dominating set of G if G\S is a disconnected graph. In this study, the authors present conditions of graphs for which the marriage and the divorce domination will take place and for which the two sets will coincide. Furthermore, the author gives the necessary and sufficient conditions for marriage domination to avoid divorce.

Keywords: domination, decomposition, marriage domination, divorce domination, marriage theorem

Procedia PDF Downloads 17

Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

Abstract:

The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: cytokine, saliva, attention deficit hyperactivity disorder, child

Procedia PDF Downloads 143

Authors: Ebru Cubukcu, Gozde Eksioglu Cetintahra, Burcin Hepguzel Hatip, Mert Cubukcu

Abstract:

Obesity and overweight cause serious health problems. Public and private organizations aim to encourage walking in various ways in order to cope with the problem of obesity and overweight. This study aims to understand how the spatial characteristics of urban street pattern, connectivity and complexity influence young people’s choice to walk or not. 185 public university students in Izmir, the third largest city in Turkey, participated in the study. Each participant had worn an accelerometer and a global positioning (GPS) device for a week. The accelerometer device records data on the intensity of the participant’s activity at a specified time interval, and the GPS device on the activities’ locations. Combining the two datasets, activity maps are derived. These maps are then used to differentiate the participants’ walk trips and motor vehicle trips. Given that, the frequency of walk and motor vehicle trips are calculated at the street segment level, and the street segments are then categorized into two as ‘preferred by pedestrians’ and ‘preferred by motor vehicles’. Graph Theory-based accessibility indices are calculated to quantify the spatial characteristics of the streets in the sample. Six different indices are used: (I) edge density, (II) edge sinuosity, (III) eta index, (IV) node density, (V) order of a node, and (VI) beta index. T-tests show that the index values for the ‘preferred by pedestrians’ and ‘preferred by motor vehicles’ are significantly different. The findings indicate that the spatial characteristics of the street network have a measurable effect on young people’s choice to walk or not. Policy implications are discussed. This study is funded by the Scientific and Technological Research Council of Turkey, Project No: 116K358.

Keywords: graph theory, walkability, accessibility, street network

Procedia PDF Downloads 225

Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

Abstract:

Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

Procedia PDF Downloads 112

Authors: Ghazi Chabchoub, Mouna Feki, Mohamed Abid, Hammadi Ayadi

Abstract:

Autoimmune thyroid diseases (AITDs), including Graves’ disease (GD) and Hashimoto’s thyroiditis (HT), are inherited as complex traits. Genetic factors associated with AITDs have been tentatively identified by candidate gene and genome scanning approaches. We analysed three intragenic microsatellite markers in the thyroid hormone receptor associated protein 2 gene (THRAP2), mapped near D12S79 marker, which have a potential role in immune function and inflammation [THRAP2-1(TG)n, THRAP2-2 (AC)n and THRAP2-3 (AC)n]. Our study population concerned 12 patients affected with AITDs belonging to a multiplex Tunisian family with high prevalence of AITDs. Fluorescent genotyping was carried out on ABI 3100 sequencers (Applied Biosystems USA) with the use of GENESCAN for semi-automated fragment sizing and GENOTYPER peak-calling software. Statistical analysis was performed using the non parametric Lod score (NPL) by Merlin software. Merlin outputs non-parametric NPLall (Z) and LOD scores and their corresponding asymptotic P values. The analysis for three intragenic markers in the THRAP2 gene revealed strong evidence for linkage (NPL=3.68, P=0.00012). Our results suggested the possible role of THRAP2 gene in AITDs susceptibility in this family.

Keywords: autoimmunity, autoimmune disease, genetic, linkage analysis

Procedia PDF Downloads 126

Authors: Dongqin Cheng

Abstract:

The n-dimensional balanced hypercube BHn (n ≥ 1) has been proved to be a bipartite graph. Let P be a set of edges whose induced subgraph consists of pairwise vertex-disjoint paths. For any two vertices u, v from different partite sets of V (BHn). In this paper, we prove that if |P| ≤ 2n − 2 and the subgraph induced by P has neither u nor v as internal vertices, or both of u and v as end-vertices, then BHn contains a Hamiltonian path joining u and v passing through P. As a corollary, if |P| ≤ 2n−1, then the BHn contains a Hamiltonian cycle passing through P.

Keywords: interconnection network, balanced hypercube, Hamiltonian cycle, prescribed edges

Procedia PDF Downloads 205

Authors: S. J. Sirima, C. Thirawan, R.Puntharikorn, K. Ungsumalin, J. Kaemwich

Abstract:

Acinetobacter spp. is a gram negative bacterium causing the high incidence of multi-drug resistance in patients admitted to an intensive care unit. A hundred isolates of Imipenem-resistant Acinetobacter spp. isolated from patients admitted at tertiary health care center, Northeastern region, Ubon Ratchathani, Thailand, were subjected to modified Hodge test and combined disc test in order to evaluate the production of carbapenemases. The results revealed that about 35% of isolates were found to be carbapenemases producers. In addition, multiplex polymerase chain reactions were performed to detect blaOXA-like genes. It showed that 92% of isolates possess blaOXA-51-like and blaOXA-23-like genes. However, blaOXA-58-like gene was detected in only 8 isolates. No detection of blaOXA-24-like gene was observed in all isolates. In conclusion, an ability to produce carbepenemases would be an important mechanism of multi-drug resistance among clinical isolates of Acinetobacter spp. at tertiary health care center, Northeastern region, Ubon Ratchathani, Thailand. Furthermore, it was likely that the class D carbapenemases genes, blaOXA-51-like and blaOXA-23-like, might contribute to imipenem-resistance exhibiting among isolates.

Keywords: Acinetobacter spp., blaOXA-like genes, carbapenemases, tertiary health care center

Procedia PDF Downloads 382

Authors: Haffaf Hafid

Abstract:

Hypergraphs, after being used to model the structural organization of System of Sytems (SoS) at macroscopic level, has recent trends towards generalizing this powerful representation at different stages of complex system modelling. In this paper, we first describe different applications of hypergraph theory, and step by step, introduce multilevel modeling of SoS by means of integrating Constraint Programming Langages (CSP) dealing with engineering system reconfiguration strategy. As an application, we give an A.C.T Terminal controlled by a set of Intelligent Automated Vehicle.

Keywords: hypergraph model, structural analysis, bipartite graph, monitoring, system of systems, reconfiguration analysis, hypernetwork

Procedia PDF Downloads 488

Authors: Reham K. Sebaih, Afaf I. Shehata , Awatif A. Hindi, Tarek Gheith, Amal A. Hazzani Anas Al-Orjan

Abstract:

Staphylococci spp are ubiquitous gram-positive bacteria is often associated with infections, especially nosocomial infections, and antibiotic resistanceStudy pathogenic bacteria and its use as a tool in the technology of Nano biology and molecular genetics research of the latest research trends of modern characterization and definition of different multiresistant of bacteria including Staphylococci. The Staphylococci are widespread all over the world and particularly in Saudi Arabia The present work study was conducted to evaluate the effect of five different types of nanoparticles (biosynthesized zinc oxide, Spherical and rod of each silver and gold nanoparticles) and their antibacterial impact on the Staphylococcus species. Ninety-six isolates of Staphylococcus species. Staphylococcus aureus, Staphylococcus epidermidis, MRSA were collected from different sources during the period between March 2011G to June 2011G. All isolates were isolated from inpatients and outpatients departments at Royal Commission Hospital in Yanbu Industrial, Saudi Arabia. High percentage isolation from males(55%) than females (45%). Staphylococcus epidermidis from males was (47%), (28%), and(25%). For Staphylococcus aureus and Methicillin-resistant Staphylococcus aureus (MRSA. Isolates from females were Staphylococcus aureus with higher percent of (47%), (30%), and (23%) for MRSA, Staphylococcus epidermidis. Staphylococcus aureus from wound swab were the highest percent (51.42%) followed by vaginal swab (25.71%). Staphylococcus epidermidis were founded with higher percentage in blood (37.14%) and wound swab (34.21%) respectively related to other. The highest percentage of methicillin-resistant Staphylococcus aureus (MRSA)(80.77%) were isolated from wound swab, while those from nostrils were (19.23%). Staphylococcus species were isolates in highest percentage from hospital Emergency department with Staphylococcus aureus (59.37%), Methicillin-resistant Staphylococcus aureus (MRSA) (28.13%)and Staphylococcus epidermidis (12.5%) respectively. Evaluate the antibacterial property of Zinc oxide, Silver, and Gold nanoparticles as an alternative to conventional antibacterial agents Staphylococci isolates from hospital sources we screened them. Gold and Silver rods Nanoparticles to be sensitive to all isolates of Staphylococcus species. Zinc oxide Nanoparticles gave sensitivity impact range(52%) and (48%). The Gold and Silver spherical nanoparticles did not showed any effect on Staphylococci species. Zinc Oxide Nanoparticles gave bactericidal impact (25%) and bacteriostatic impact (75%) for of Staphylococci species. Detecting the association of nanoparticles with Staphylococci isolates imaging by scanning electron microscope (SEM) of some bacteriostatic isolates for Zinc Oxide nanoparticles on Staphylococcus aureus, Staphylococcus epidermidis and Methicillin resistant Staphylococcus aureus(MRSA), showed some Overlapping Bacterial cells with lower their number and appearing some appendages with deformities in external shape. Molecular analysis was applied by Multiplex polymerase chain reaction (PCR) used for the identification of genes within Staphylococcal pathogens. A multiplex polymerase chain reaction (PCR) method has been developed using six primer pairs to detect different genes using 50bp and 100bp DNA ladder marker. The range of Molecular gene typing ranging between 93 bp to 326 bp for Staphylococcus aureus and Methicillin resistant Staphylococcus aureus by TSST-1,mecA,femA and eta, while the bands border were from 546 bp to 682 bp for Staphylococcus epidermidis using icaAB and atlE. Sixteen isolation of Staphylococcus aureus and Methicillin resistant Staphylococcus aureus were positive for the femA gene at 132bp,this allowed the using of this gene as an internal positive control, fifteen isolates of Staphylococcus aureus and Methicillin resistant Staphylococcus aureus were positive for mecA gene at163bp.This gene was responsible for antibiotic resistant Methicillin, Two isolates of Staphylococcus aureus and Methicillin resistant Staphylococcus aureus were positive for the TSST-1 gene at326bp which is responsible for toxic shock syndrome in some Staphylococcus species, None were positive for eta gene at 102bpto that was responsible for Exfoliative toxins. Six isolates of Staphylococcus epidermidis were positive for atlE gene at 682 bp which is responsible for the initial adherence, three isolates of Staphylococcus epidermidis were positive for icaAB gene at 546bp that are responsible for mediates the formation of the biofilm. In conclusion, this study demonstrates the ability of the detection of the genes to discriminate between infecting Staphylococcus strains and considered biological tests, they may potentiate the clinical criteria used for the diagnosis of septicemia or catheter-related infections.

Keywords: multiplex polymerase chain reaction, toxic shock syndrome, Staphylococcus aureus, nosocomial infections

Procedia PDF Downloads 339

Authors: Mark Osborn

Abstract:

Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

Procedia PDF Downloads 184

Authors: Nartan Rajpriya

Abstract:

City is a multiplex ecological system made up of social, economic and natural sub systems. Green space system is the foundation of the natural system. It is also suitable part of natural productivity in the urban structure. It is dispensable for constructing a high quality human settlements and a high standard ecocity. Ahmedabad is the fastest growing city of India. Today urban green space is under strong pressure in Ahmedabad city. Due to increasing urbanization, combined with a spatial planning policy of densification, more people face the prospect of living in less green residential environments. In this research analyzes the importance of available Green Space at Bodakdev Park, Ahmedabad, using remote sensing and GIS technologies. High resolution IKONOS image and LISS IV data has been used in this project. This research answers the questions like: • Temporal changes in urban green space area. • Proximity to heavy traffic or roads or any recreational facilities. • Importance in terms of health. • Availability of quality infrastructure. • Available green space per area, per sq. km and per total population. This projects incorporates softwares like ArcGIS, Ecognition and ERDAS Imagine, GPS technologies etc. Methodology includes the field work and collection of other relevant data while preparation of land use maps using the IKONOS imagery which is corrected using GPS.

Keywords: urban green space, ecocity, IKONOS, LISS IV

Procedia PDF Downloads 386

Authors: E. M. Rifqi Wilda Pradana, Bagus Bayu Prabowo, Meida Riski Pujiyati, Efraim Maykhel Hagana Ginting, Virgiawan Arya Hangga Reksa

Abstract:

The VLF (Very Low Frequency) method is an electromagnetic method that uses low frequencies between 10-30 KHz which results in a fairly deep penetration. In this study, the VLF method was used for zonation of disaster-prone areas by identifying geological structures in the form of faults. Data acquisition was carried out in Trimulyo Region, Jetis District, Bantul Regency, Special Region of Yogyakarta, Indonesia with 8 measurement paths. This study uses wave transmitters from Japan and Australia to obtain Tilt and Elipt values that can be used to create RAE (Rapat Arus Ekuivalen or Current Density) sections that can be used to identify areas that are easily crossed by electric current. This section will indicate the existence of a geological structure in the form of faults in the study area which is characterized by a high RAE value. In data processing of VLF method, it is obtained Tilt vs Elliptical graph and Moving Average (MA) Tilt vs Moving Average (MA) Elipt graph of each path that shows a fluctuating pattern and does not show any intersection at all. Data processing uses Matlab software and obtained areas with low RAE values that are 0%-6% which shows medium with low conductivity and high resistivity and can be interpreted as sandstone, claystone, and tuff lithology which is part of the Semilir Formation. Whereas a high RAE value of 10% -16% which shows a medium with high conductivity and low resistivity can be interpreted as a fault zone filled with fluid. The existence of the fault zone is strengthened by the discovery of a normal fault on the surface with strike N550W and dip 630E at coordinates X= 433256 and Y= 9127722 so that the activities of residents in the zone such as housing, mining activities and other activities can be avoided to reduce the risk of natural disasters.

Keywords: current density, faults, very low frequency, zonation

Procedia PDF Downloads 175

Authors: Abdul Jalil M. Khalaf, Esraa M. Kadhim

Abstract:

The Hosoya polynomial of a graph G is a graphical invariant polynomial that its first derivative at x= 1 is equal to the Wiener index and second derivative at x=1 is equal to the Hyper-Wiener index. In this paper we study the Hosoya polynomial of zero-divisor graphs.

Keywords: Hosoya polynomial, wiener index, Hyper-Wiener index, zero-divisor graphs

Procedia PDF Downloads 529

Authors: Rasheed F. G., Hassan H. A., Shehu F. A., Mukhtar M. M., Muhammad Y. Y., Ibrahim S. S., Shehu D., Abdulsalam K., N. Abdullahi

Abstract:

A cross sectional randomized, descriptive cross sectional study was conducted on the frequency of GSTT1 null alleles in patients diagnosed with type-2-diabetes mellitus (T2DM). A total of 40 patients with T2DM and 10 non-diabetic controls were included in the study. GSTT1 null-alleles genotyping was carried out using multiplex PCR amplification to amplify GSTT1 gene (460bp) while using β-globulin (250bp) as an internal control. The results showed that 55% of T2DM patients had BMI within reference limits, 13% are overweight. Additionally, patients with T2DM were found to have significantly higher (p<0.05) serum levels of glucose, total cholesterol, triglyceride and low density lipoprotein. Furthermore, the presence of null genotype of GSTT1 (deletion in GSTT1) was observed in 28% of diabetic patients. Subjects with GSTT1 deletion have significantly higher (p<0.05) levels of serum glucose, low-density lipoprotein and total cholesterol when compared with individuals without deletion (diabetic and non-diabetic). This results suggests that the deletion of GSTT1 gene might serve as a predisposing factor in the development of T2DM and dyslipideamia

Keywords: diabetes, glutathione-S-transferase, lipid profile, PCR, polymorphism.

Procedia PDF Downloads 96

Authors: Giorgi Methodishvili, Iuliia Methodishvili

Abstract:

In this paper product development algorithm is used to determine the optimal management of financial resources in company. Aspects of financial management considered include put initial investment, examine all possible ways to solve the problem and the optimal rotation length of profit. The software of given problems is based using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

Procedia PDF Downloads 56

Authors: Fotis I. Giasemis, Alexandros Sopasakis

Abstract:

This study focuses on detecting traffic anomalies using generative models applied to real-time observations. By integrating a Graph Neural Network with an attention-based mechanism within the Spatiotemporal Generative Adversarial Network framework, we enhance the capture of both spatial and temporal dependencies in traffic data. Leveraging minute-by-minute observations from cameras distributed across Gothenburg, our approach provides a more detailed and precise anomaly detection system, effectively capturing the complex topology and dynamics of urban traffic networks.

Keywords: traffic, anomaly detection, GNN, GAN

Procedia PDF Downloads 6

Authors: B. Selma

Abstract:

The aim of this study is to test the feasibility of SIPINA method to predict the harmfulness parameters controlling the seismic response. The approach developed takes into consideration both the focal depth and the peak ground acceleration. The parameter to determine is displacement. The data used for the learning of this method and analysis nonlinear seismic are described and applied to a class of models damaged to some typical structures of the existing urban infrastructure of Jassy, Romania. The results obtained indicate an influence of the focal depth and the peak ground acceleration on the displacement.

Keywords: SIPINA algorithm, seism, focal depth, peak ground acceleration, displacement

Procedia PDF Downloads 313

Authors: Roman Khanferyan

Abstract:

Endurance exercises and strenuous muscle activity are accompanied by multiple immune dysfunctions due to the activation of cytokines and chemokines synthesis. This study assesses changes in the synthesis of immune regulatory mediators in elite athletes during endurance sports activity. The concentrations of cytokines/chemokines (IL-2, IL-6, IL-8, IL-10, IL-18, MIP-1 beta, GRO-alpha, RANTES, SDF-1a, VEGF) in sera of hockey athletes (n=33) and in supernatants of 24-h cultivated peripheral blood mononuclear cells (PBMC) of boxers (n=6) assayed by ELISA and Luminex xMAP multiplex assays. Estimation of body composition studied by using bioimpedance technology. The dietary energy consumption per person has been estimated using an album of different sizes of portions of the most frequently consumed foods. It has been demonstrated that endurance sports activity enhances the secretions of most pro- and anti-inflammatory cytokines and chemokines in more than 2-6 fold. The study demonstrated that the high increase of more than 3-4 times in the concentration of IL-18 in sera of athletes (327.86 + 45.67 pg/ml) didn’t correlate with BMI (p=0.040) but demonstrated a low correlation with MMI (p=0.234) and BMR (p=0,231). The opposite impact on the concentration of IL-10 has been demonstrated in athletes. It has been shown a negative correlation between its concentration and BMI (p= - 0.251), MMI (p= - 0.327), and BMR (p= - 0.301). In vitro studies in boxers showed greater amounts of chemokines in the PBMC supernatants, including MIP-1β, GRO-α, RANTES, SDF-1α, and IL-8 (P<0.05). At the same time, healthy controls had greater supernatant levels of MCP-1, Eotaxin, and MIP-1α. The study demonstrated a high correlation between physical activity, usual athletes' diet, and consumption of specialized sports nutrition products.

Keywords: sport nutrition, cytokines, chemokines, endurace exercises

Procedia PDF Downloads 43