Rectilinear crossing number of the double circular complete bipartite graph

In this work, we study a mathematically rigorous metric of a graph visualization quality under conditions that relate to visualizing a bipartite graph. Namely we study rectilinear crossing number in a special arrangement of the complete bipartite graph where the two parts are placed on two concentric circles. For this purpose, we introduce a combinatorial formulation to count the number of crossings. We prove a proposition about the rectilinear crossing number of the complete bipartite graph. Then, we introduce a geometric optimization problem whose solution gives the optimum radii ratio in the case that the number of crossings for them is minimized. Later on, we study the magnitude of change in the number of crossings upon change in the radii of the circles. In this part, we present and prove a lemma on bounding the changes in the number of crossings of that is followed by a theorem on asymptotics of the bounds.Comment: 15 pages, 11 figure

Strengthening Relaxed Decision Diagrams for Maximum Independent Set Problem: Novel Variable Ordering and Merge Heuristics

Finding high-quality bounds is key to devising efficient exact solution approaches for Discrete Optimization (DO) problems. To this end, Decision Diagrams (DDs) provide strong and generic bounding mechanisms. This paper focuses on so-called relaxed DDs which, by merging nodes, over-approximate the solution space of DO problems and provide dual bounds the quality of which hinges upon the ordering of the variables in the DD compilation and on the selection of the nodes to merge. Addressing the Maximum Independent Set Problem, we present a novel dynamic variable ordering strategy relying on induced subgraphs of the original graph, and a new tie-based merge heuristic. In a set of computational experiments, we show that our strategies yield much stronger bounds than the standard state-of-the-art approaches. Furthermore, implementing our heuristics in a DD-based branch-and-bound, we reduce the solution times by around 33 % on average and by more than 50 % on hard instances

Mixed coordinate Node link Visualization for Co_authorship Hypergraph Networks

We present an algorithmic technique for visualizing the co-authorship networks and other networks modeled with hypergraphs (set systems). As more than two researchers can co-author a paper, a direct representation of the interaction of researchers through their joint works cannot be adequately modeled with direct links between the author-nodes. A hypergraph representation of a co-authorship network treats researchers/authors as nodes and papers as hyperedges (sets of authors). The visualization algorithm that we propose is based on one of the well-studied approaches representing both authors and papers as nodes of different classes. Our approach resembles some known ones like anchored maps but introduces some special techniques for optimizing the vertex positioning. The algorithm involves both continuous (force-directed) optimization and discrete optimization for determining the node coordinates. Moreover, one of the novelties of this work is classifying nodes and links using different colors. This usage has a meaningful purpose that helps the viewer to obtain valuable information from the visualization and increases the readability of the layout. The algorithm is tuned to enable the viewer to answer questions specific to co-authorship network studies.Comment: 10 pages, 3 figures, 1 tabl

Providing a control method of BTB-VSC Converters under unbalanced faults

Microgrids need control strategies to achieve maximum performance. An appropriate control strategy should have high performance in unbalanced conditions in addition to normal conditions. Today, the use of microgrids, with a variety of power sources, including solar, wind, diesel, energy storage sources to increase the capability of distribution grid has made significant progress. However, controlling and managing their energy in the event of a fault is a challenge that researchers are faced. In this article, two microgrids connected to the grid are studied using a back-to-back (BTB)-voltage source converters (VSC) converter. The results of this research showed that by the usage of above-mentioned convertor first, with power management between microgrids the frequency remains constant in island mode second, they are isolated from each other in terms of faults. The results showed that the use of the proposed method controlled the frequency of two microgrids simultaneously

Performance improvement of decentralized control for bidirectional converters in a DC micro-grid

In this paper, using a neural controller and a genetic optimization algorithm to control the voltage as well as, control the frequency of the grid along with the management of the reactive power of the micro-grid to control the output power during islanding using Simultaneous bilateral power converters with voltage/frequency droop strategy and optimization of PI coefficients of parallel power converters by genetic-neural micro-grid algorithm to suppress AC side-current flow that increases stability and improvement of conditions frequency and voltage are discussed. Given the performance of the micro-grid in two simulation scenarios, namely transition from on-grid to off-grid, the occurrence of a step change in load in island mode as well as return to working mode is connected. The ability to detect the robust performance and proper performance of two-level neural controller. The controller performance time was also very good, indicating the appropriate features of the method used to design the controller, namely two-level neural, genetics. The main advantage of this method is its simplicity of design. The method used is also efficient and resistant to changes in the system, which results from the simulations

Urinary Proteomics in Nephrotic Syndrome

Nephrotic syndrome is the commonest glomerular disease. Typical symptoms could be proteinuria, low serum albumin and oedema. The mechanism of proteinuria in nephrotic syndrome is a defective glomerular filtration barrier. Renal biopsy is the gold standard for diagnosis of nephrotic syndrome currently which is invasive and based on histopathological features, therefore it seems to be necessary to search for noninvasive biomarkers to be used as the complementary tests in the diagnostics and prognostics of glomerular diseases, particularly when renal biopsy is limited or contraindicated. While a big proportion of urinary proteins originate from kidney tissue and these tissue specific proteins excrete more in kidney injury, therefore the identification of urinary proteins can further our understanding of renal dysfunction and renal disease including nephrotic syndrome. The interest of scientist to  urinary proteomics is also growing for biomarker discovery. This review focuses on some types of nephrotic syndrome and proteomic studies applying urine specimen which have been reported

Exploring Biomarkers Beyond Exercise Testing: The Impact of Smoking on Cardiovascular and Pulmonary Health among CKD Patients

Background: Chronic Kidney Disease (CKD) patients often face complex health challenges, including cardiovascular and pulmonary issues. Smoking is a recognized risk factor for these conditions, but its specific impact on CKD patients remains less understood. Materials and Methods: In this cross-sectional study, we investigated the relationship between smoking habits and cardiopulmonary health among CKD patients. We examined baseline characteristics, including demographics, medical history, and biochemical markers, in a cohort of CKD patients. Cardiopulmonary parameters were assessed during exercise testing, including oxygen consumption, ventilation rates, ventilation-perfusion matching markers, and oxygen saturation levels. Results: Our findings revealed no statistically significant differences in cardiopulmonary parameters between smokers and non-smokers within the CKD patient population. This suggests that the relationship between smoking and exercise capacity in CKD patients is complex and influenced by multiple factors. Our analysis of demographics, comorbidities, and medication history provided critical context for interpreting these results. Conclusion: This study contributes to our understanding of the intricate relationship between smoking habits and cardiopulmonary health in CKD patients. While smoking is recognized as a risk factor, its specific impact on exercise capacity within this population may be influenced by individual variables. Further research is needed to explore these relationships in larger and more diverse cohorts. These findings underscore the importance of considering multiple variables when assessing the impact of smoking on the health of CKD patients

Phenol Based RNA Isolation is the Optimum Method for Study of Gene Expression in Human Urinary Sediment

Evaluation of gene expression in urinary sediment has been considered as a promising non-invasive approach for biomarker identification of kidney diseases. Nonetheless, there are several challenges in extraction of RNA from this valuable source of biomarkers, mostly because of the factors that have influence on quality of isolated RNA such as low cellular content. Accordingly, we compared the quality of RNA from urine sediment samples that was isolated by four different methods. TRIzol reagent with basic protocol (method 1), modified procedure of TRIzol (method 2), a column-based protocol (method 3) and combination of method 1 and 3 (method 4) were applied for isolation of RNA from identical aliquots of five healthy urine samples. The quality and yield of isolated RNA were evaluated based on concentration and purity. Expression levels of GAPDH and miR-21 were studied by quantitative RT-PCR. Methods 1 and 2 showed the highest RNA yield while no difference in purity of RNA in different methods was noticed. Quantitative RT-PCR findings indicated that Ct values in samples of method 1 had the lowest level. Although higher concentrations of RNA were isolated by method 2, the declined Ct values in this method might indicate degradation of isolated RNA. Column based protocols (method 3 and 4) were failed to show significant recovery of RNA. It seems that isolation procedure using TRIzol, as a phenol based method, is the most efficient, robust and reliable procedure for RNA isolation from urinary sediment cells

The Novel Diagnostic Biomarkers for Focal Segmental Glomerulosclerosis

Background. Focal segmental glomerulosclerosis (FSGS) is a glomerular injury with various pathogenic mechanisms. Urine proteome panel might help in noninvasive diagnosis and better understanding of pathogenesis of FSGS. Method. We have analyzed the urine sample of 11 biopsy-proven FSGS subjects, 8 healthy controls, and 6 patients with biopsy-proven IgA nephropathy (disease controls) by means of liquid chromatography tandem mass spectrometry (nLC-MS/MS). Multivariate analysis of quantified proteins was performed by principal component analysis (PCA) and partial least squares (PLS). Results. Of the total number of 389 proteins, after multivariate analysis and additional filter criterion and comparing FSGS versus IgA nephropathy and healthy subjects, 77 proteins were considered as putative biomarkers of FSGS. CD59, CD44, IBP7, Robo4, and DPEP1 were the most significant differentially expressed proteins. These proteins are involved in pathogenic pathways: complement pathway, sclerosis, cell proliferation, actin cytoskeleton remodeling, and activity of TRPC6.There was complete absence of DPEP1 in urine proteome of FSGS subjects compared with healthy and disease controls. DPEP1 acts via leukotrienes on TRPC6 and results in increased podocyte motility and proteinuria. Conclusion. The results suggest a panel of candidate biomarkers for noninvasive diagnosis of FSGS, while complete absence of DPEP1 might represent a novel marker of FSGS