Crosstalk Analysis Research Articles

Crosstalk analysis of multi‐microstrip coupled lines using transmission line modeling

This article presents a new analytical method to predict crosstalk of a homogeneous terminated two microstrip coupled lines over a ground plane using transmission line theory. The derived formula is frequency and location dependent, which can be used to quickly estimate the crosstalk of a coupled line. Also, the effect of the geometrical parameters of the lines and load are included in the derived formula. Presented method can be used for the other types of coupled lines including lossy or lossless lines. To verify the accuracy of the introduced method, a few microstrip coupled line structures with different geometrical parameters are considered numerically and experimentally. The results of crosstalk based on the proposed analytical methods, simulation study using high frequency structure simulator and those obtained by measurements are reported and compared with each other. It is shown that our proposed method accurately estimates the amount of crosstalk for a two microstrip coupled lines.

A new method for excavating feature lncRNA in lung adenocarcinoma based on pathway crosstalk analysis.

Recent theoretical and experimental studies indicate that long-chain noncoding RNAs (lncRNAs) are essential for the growth and differentiation of cells and the occurrence and development of tumors in epigenetics, but the regulation of lncRNA on gene expression, transcriptional activation, and transcriptional interference in diseases is still unclear. There is an urgent need for effective methods to discover significant lncRNAs with their functions on gene regulatory mechanisms. For this purpose, a new method of extracting significant lncRNA based on pathway crosstalk and dysfunction caused by the differentially expressed genes in lung adenocarcinoma (LUAD) was proposed. The pathway analysis method based on global influence (PAGI) was first applied to find the feature genes that play an important role in the crosstalks of disease-related pathways. Then to explore the hub lncRNAs, the weighted gene coexpression network analysis (WGCNA) was used to construct coexpression models of the feature genes and lncRNAs. The experiment results showed that 64 out of the 322 hub lncRNAs were closely related to the clinical features of patients with LUAD. Among them, nine lncRNAs (UCA1, LINC00857, PVT1, PCAT6, LINC00460, LINC00319, AP000553.1, AP000439.2, and AP005233.2) were identified to be tightly correlated with non-small-cell lung cancer (NSCLC) pathways. In summary, we offer an effective way to extract significant lncRNA by dysfunctional pathway crosstalk in LUAD which allows the selected lncRNAs with more biologically interpreted and reproducible results. This method can be applied to other diseases and provide useful information for understanding the pathogenesis of human cancer.

An 11-gene-based prognostic signature for uveal melanoma metastasis based on gene expression and DNA methylation profile.

Uveal melanoma (UM) is the most common intraocular tumor worldwide. We proposed to identifya vital gene signature that has prognostic value for UM metastasis. For this purpose, we obtained a published DNA methylation and gene expression data set associated with UM from the Gene Expression Omnibus. The genes whose aberrant expression significantly associated with UM patients' metastasis-free survival (MFS) were identified by applying a univariate Cox proportional hazards model to the gene expression data set followed by a robust likelihood-based survival analysis to screen the optimal prognostic gene signatures (PGS). A formula for calculating the risk score that represents UM metastasis risk was constructed by including the PGSs' expression values weighted by their regression coefficients, which were obtained by a multivariate Cox regression analysis. As a result, aberrant expression of 2884 genes were found to be significantly associated with UM patients' MFS, which were referred to as MFSGs, and 11 out of those MFSGs, GJC1, TCEA1, MFSD3, FAF2, TLCD1, GPAA1, CYC1, ASAP1, JPH1, LDB3, and KDELR3, were identified as PGSs through which we could accurately separate UM samples with shorter MFS from those with longer MFS. By combining the DNA methylation data set and MFSGs, we further identified 265 MFSGs, which contained CpG sites that significantly hyper- or hypo-methylated in UM samples compared with control samples. Functional enrichment analysis and pathway crosstalk analysis of those genes indicated significant enrichment of cancer-related pathways. In conclusion, we identified an 11-gene-based prognostic signature and several gene biomarkers for UM metastasis, which should be helpful for selecting an appropriate treatment method for specific patients with UM.

Higher plane of nutrition pre-weaning enhances Holstein calf mammary gland development through alterations in the parenchyma and fat pad transcriptome

BackgroundTo reduce costs of rearing replacement heifers, researchers have focused on decreasing age at breeding and first calving. To increase returns upon initiation of lactation the focus has been on increasing mammary development prior to onset of first lactation. Enhanced plane of nutrition pre-weaning may benefit the entire replacement heifer operation by promoting mammary gland development and greater future production.MethodsTwelve Holstein heifer calves (< 1 week old) were reared on 1 of 2 dietary treatments (n = 6/group) for 8 weeks: a control group fed a restricted milk replacer at 0.45 kg/d (R, 20% crude protein, 20% fat), or an accelerated group fed an enhanced milk replacer at 1.13 kg/d (EH, 28% crude protein, 25% fat). At weaning (8 weeks), calves were euthanized and sub-samples of mammary parenchyma (PAR) and mammary fat pad (MFP) were harvested upon removal from the body. Total RNA from both tissues was extracted and sequenced using the Illumina HiSeq2500 platform. The Dynamic Impact Approach (DIA) and Ingenuity Pathway Analysis (IPA) were used for pathway analysis and functions, gene networks, and cross-talk analyses of the two tissues.ResultsWhen comparing EH vs R 1561 genes (895 upregulated, 666 downregulated) and 970 genes (506 upregulated, 464 downregulated) were differentially expressed in PAR and MFP, respectively. DIA and IPA results highlight a greater proliferation and differentiation activity in both PAR and MFP, supported by an increased metabolic activity. When calves were fed EH, the PAR displayed transcriptional signs of greater overall organ development, with higher ductal growth and branching, together with a supportive blood vessel and nerve network. These activities were mediated by intracellular cascades, such as AKT, SHH, MAPK, and Wnt, probably activated by hormones, growth factors, and endogenous molecules. The analysis also revealed strong communication between MFP and PAR.ConclusionThe transcriptomics and bioinformatics approach highlighted key mechanisms that mediate the mammary gland response to a higher plane of nutrition in the pre-weaning period.

Pathways and Network Based Analysis of Candidate Genes to Reveal Cross-Talk and Specificity in the Sorghum (Sorghum bicolor (L.) Moench) Responses to Drought and It's Co-occurring Stresses.

Drought alone or in combination with other stresses forms the major crop production constraint worldwide. Sorghum, one of the most important cereal crops is affected by drought alone or in combination with co-occurring stresses; notwithstanding, sorghum has evolved adaptive responses to combined stresses. Furthermore, an impressive number of sorghum genes have been investigated for drought tolerance. However, the molecular mechanism underling drought response remains poorly understood. We employed a systems biology approach to elucidate regulatory and broad functional features of these genes. Their interaction network would provide insight into understanding the molecular mechanisms of drought tolerance and underpinning signal pathways. Functional analysis was undertaken to determine significantly enriched genesets for pathways involved in drought tolerance. Analysis of distinct pathway cross-talk network was performed and drought-specific subnetwork was extracted. Investigation of various data sources such as gene expression, regulatory pathways, sorghumCyc, sorghum protein-protein interaction (PPI) and Gene Ontology (GO) revealed 14 major drought stress related hub genes (DSRhub genes). Significantly enriched genesets have shown association with various biological processes underlying drought-related responses. Key metabolic pathways were significantly enriched in the drought-related genes. Systematic analysis of pathways cross-talk and gene interaction network revealed major cross-talk pathway modules associated with drought tolerance. Further investigation of the major DSRhub genes revealed distinct regulatory genes such as ZEP, NCED, AAO, and MCSU and CYP707A1. These were involved in the regulation of ABA biosynthesis and signal transduction. Other protein families, namely, aldehyde and alcohol dehydrogenases, mitogene activated protein kinases (MAPKs), and Ribulose-1,5-biphosphate carboxylase (RuBisCO) were shown to be involved in the drought-related responses. This shows a diversity of complex functional features in sorghum to respond to various abiotic stresses. Finally, we constructed a drought-specific subnetwork, characterized by unique candidate genes that were associated with DSRhub genes. According to our knowledge, this is the first in sorghum drought investigation that introduces pathway and network-based candidate gene approach for analysis of drought tolerance. We provide novel information about pathways cross-talk and signaling networks used in further systems level analysis for understanding the molecular mechanism behind drought tolerance and can, therefore, be adapted to other model and non-model crops.

PS02.037: NETWORK AND PATHWAY-BASED ANALYSIS OF GENES ASSOCIATED WITH ESOPHAGEAL SQUAMOUS CELL CARCINOMA

Abstract Background As a highly malignant and aggressive tumor, Esophageal Squamous Cell Carcinoma (ESCC) is not sensitive to chemoradiotherapy and chemotherapy. Although diagnostic methods and treatments have improved over the last few years, the 5-year survival rate of ESCC patients remains generally poor. The development of high-throughput technology has witnessed the great achievements in localization ESCC related genes/proteins, and many genes/proteins are considered as potential targets for detection or treatment. To take a further quest for a thorough understanding of the biological processes involved in the pathogenesis of ESCC at the molecular level, the potential pathogenesis of ESCC needs to be deciphered at a phylogenetic level. Methods The interaction of these genes was explored by collecting genes associated with ESCC, using gene enrichment assays, pathway enrichment assays, pathway crosstalk analysis and extraction of ESCC-specific subnetwork to describe the relevant biochemical processes. Results Through GO enrichment analysis, many molecular functions related to response to chemical, cellular response to stimulus and cell proliferation were found to be significantly enriched in ESCC-related genes. The results of pathway and pathway crosstalk analysis showed that pathways associated with multiple malignant tumors, the immune system and metabolic processes were significantly enriched in ESCC-related genes. Through the analysis of specific subnetwork, we obtained some novel ESCC-related potential genes, such as MUC13, GSTO1, FIN, GRB2, CDC25C and so on. Conclusion The molecular mechanism of ESCC is extremely complex. Some inducing factors change the expression status of many genes. The abnormal expression of genes mediates the biological processes involved in immunity and metabolism, apoptosis and cell proliferation, leading to the occurrence of tumors. Gene MUC13, RYK, FIN may be potential prognostic indicators of ESCC. GRB2 and CDC25C may be potential targets of ESCC in proliferation. Our work may provide valuable information for understanding the molecular mechanisms for the development of ESCC. Disclosure All authors have declared no conflicts of interest.

Modeling and Performance Analysis of MLGNR Interconnects

In this work, we have presented the temperature-dependent analytical time domain model for top-contact multilayer graphene nanoribbon (TC-MLGNR) and side-contact multilayer graphene nanoribbon (SC-MLGNR) interconnects for 16[Formula: see text]nm technology node. Using this analytical model, the effective mean free path (MFP) is calculated for different temperatures and then the resistance of GNR interconnect is calculated. The lower resistance of MLGNR is one of the important factors to reduce interconnect delay. The equivalent capacitance for TC-MLGNR is also calculated. It is observed that the performance of graphene interconnects seriously deteriorates due to the presence of the interlayer capacitance. The presence of this interlayer capacitance increases the equivalent capacitance which is the dominant factor that inhibits the performance of TC-MLGNR interconnects. Further, the delay ratio between copper and TC-MLGNR for different interconnect lengths and for three different temperatures (233[Formula: see text]K, 300[Formula: see text]K, 378[Formula: see text]K) is calculated. It is observed that for longer interconnect lengths, the improvement in delay in TC-MLGNR is less as compared to traditional copper-based interconnect at low temperature. Further, power delay product (PDP) of copper and TC-MLGNR for different interconnect lengths and for three different temperatures is also calculated. It is shown that TC-MLGNR interconnects have better PDP than copper interconnects. The crosstalk analysis is performed to estimate the noise and overshoot/undershoot in TC-MLGNR and SC-MLGNR interconnects. It is shown that SC-MLGNR interconnect has better performance as far as the crosstalk is concerned as compared to that of Cu and TC-MLGNR interconnects.

Bioinformatics Analysis of Key Differentially Expressed Genes in Nonalcoholic Fatty Liver Disease Mice Models.

Nonalcoholic fatty liver disease (NAFLD) is a global health problem characterized by excessive accumulation of fat in the liver without effect of other pathological factors including hepatitis infection and alcohol abuse. Current studies indicate that gene factors play important roles in the development of NAFLD. However, the molecular characteristics of differentially expressed genes (DEGs) and associated mechanisms with NAFLD have not been well elucidated. Using two microarray data associated with the gene expression profiling in liver tissues of NAFLD mice models, we identified and selected several common key DEGs that contributed to NAFLD. Based on bioinformatics analysis, we discovered that the DEGs were associated with a variety of biological processes, cellular components, and molecular functions and were also related to several significant pathways. Via pathway crosstalk analysis based on overlapping DEGs, we observed that the identified pathways could form large and complex crosstalk networks. Besides, large and complex protein interaction networks of DEGs were further constructed. In addition, many hub host factors with a high degree of connectivity were identified based on interaction networks. Furthermore, significant modules in interaction networks were found, and the DEGs in the identified modules were found to be enriched with distinct pathways. Taken together, these results suggest that the key DEGs, associated pathways, and modules contribute to the development of NAFLD and might be used as novel molecular targets for the treatment of NAFLD.

Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer.

Prediction of drug combinations that effectively target cancer cells is a critical challenge for cancer therapy, in particular for triple-negative breast cancer (TNBC), a highly aggressive breast cancer subtype with no effective targeted treatment. As signalling pathway networks critically control cancer cell behaviour, analysis of signalling network activity and crosstalk can help predict potent drug combinations and rational stratification of patients, thus bringing therapeutic and prognostic values. We have previously showed that the non-receptor tyrosine kinase PYK2 is a downstream effector of EGFR and c-Met and demonstrated their crosstalk signalling in basal-like TNBC. Here we applied a systems modelling approach and developed a mechanistic model of the integrated EGFR-PYK2-c-Met signalling network to identify and prioritize potent drug combinations for TNBC. Model predictions validated by experimental data revealed that among six potential combinations of drug pairs targeting the central nodes of the network, including EGFR, c-Met, PYK2 and STAT3, co-targeting of EGFR and PYK2 and to a lesser extent of EGFR and c-Met yielded strongest synergistic effect. Importantly, the synergy in co-targeting EGFR and PYK2 was linked to switch-like cell proliferation-associated responses. Moreover, simulations of patient-specific models using public gene expression data of TNBC patients led to predictive stratification of patients into subgroups displaying distinct susceptibility to specific drug combinations. These results suggest that mechanistic systems modelling is a powerful approach for the rational design, prediction and prioritization of potent combination therapies for individual patients, thus providing a concrete step towards personalized treatment for TNBC and other tumour types.

An Efficient MRTD Model for the Analysis of Crosstalk in CMOS-Driven Coupled Cu Interconnects

An Efficient MRTD Model for the Analysis of Crosstalk in CMOS-Driven Coupled Cu Interconnects

Hub genes and key pathways of non-small lung cancer identified using bioinformatics.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for ~80% of all lung cancer cases. The aim of the present study was to identify key genes and pathways in NSCLC, in order to improve understanding of the mechanism of lung cancer. The GSE33532 gene expression dataset, containing 20 normal and 80 NSCLC samples, was used. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to obtain the enrichment data of differently expressed genes (DEGs). Disease modules within NSCLC were constructed by Cytoscape, using protein-protein interaction (PPI) from the Search Tool for the Retrieval of Interacting Genes database. In addition, the Kaplan Meier plotter KMplot was used to assess the top hub genes in the PPI network. As a result, 1,795 genes were identified in NSCLC; 729 were upregulated and 1,066 were downregulated. The results of the GO analysis indicated that the upregulated DEGs were significantly enriched in ‘biological processes’ (BP), including ‘cell cycle and nuclear division’; the downregulated DEGs were also significantly enriched in BP, including ‘response to wounding’, ‘anatomical structure morphogenesis’ and ‘response to stimulus’. Upregulated DEGs were also enriched in ‘cell cycle’, ‘DNA replication’ and the ‘tumor protein 53 signaling pathway’, while the downregulated DEGs were also enriched in ‘complement and coagulation cascades’, ‘malaria’ and ‘cell adhesion molecules’. The top 9 hub genes were cyclin-dependent kinase 9 (CDK1), polo-like kinase 1, aurora kinase B, cell division cycle 20, baculoviral initiator of apoptosis repeat containing 5, mitotic checkpoint serine/threonine kinase B, proliferating cell nuclear antigen (PCNA), centromere protein A and MAD2 mitotic arrest deficient-like 1, and the KMplot results revealed that the high expression levels of these genes resulted in significantly low survival rates, compared with low expression samples (P<0.05), with the exception of PCNA and CDK1. In the pathway crosstalk analysis, 26 nodes and 41 interactions were divided into two groups: One module of the two groups primarily included ‘metabolism of amino acid’ and the other primarily contained ‘tumor necrosis signaling’ pathways. In conclusion, the present study assisted in improving the understanding of the molecular mechanisms underlying NSCLC development, and the results may help the understanding of the biological mechanism of NSCLC.

2.6 Tbit/s On-Chip Optical Interconnect Supporting Mode-Division-Multiplexing and PAM-4 Signal

In this letter, we combine the use of dense-wavelength-division-multiplexing and mode-division-multiplexing (MDM) with advanced-modulation formats for on-chip optical interconnects. A three-mode MDM multiplexer (MUX) and de-multiplexer (DEMUX) was designed and used. Each wavelength carrier had an aggregate data rate of 192-Gbit/s using 4-level pulse-amplitude-modulation. The mode crosstalk of the MDM MUX/DEMUX was measured to be below −20 dB in the 40-nm wavelength band from 1520 to 1560 nm. Fourteen wavelength channels are multiplexed and successfully transmitted with an aggregate transmission capacity of 2.6 Tbit/s (14 wavelengths $\times$ 3 modes $\times$ 64 Gbit/s) with all channels satisfying the hard-decision forward-error-correction threshold. Numerical analysis of the mode crosstalk is also performed.

Systematic Identification of Druggable Epithelial-Stromal Crosstalk Signaling Networks in Ovarian Cancer.

BackgroundBulk tumor tissue samples are used for generating gene expression profiles in most research studies, making it difficult to decipher the stroma–cancer crosstalk networks. In the present study, we describe the use of microdissected transcriptome profiles for the identification of cancer–stroma crosstalk networks with prognostic value, which presents a unique opportunity for developing new treatment strategies for ovarian cancer.MethodsTranscriptome profiles from microdissected ovarian cancer–associated fibroblasts (CAFs) and ovarian cancer cells from patients with high-grade serous ovarian cancer (n = 70) were used as input data for the computational systems biology program CCCExplorer to uncover crosstalk networks between various cell types within the tumor microenvironment. The crosstalk analysis results were subsequently used for discovery of new indications for old drugs in ovarian cancer by computational ranking of candidate agents. Survival analysis was performed on ovarian tumor–bearing Dicer/Pten double-knockout mice treated with calcitriol, a US Food and Drug Administration–approved agent that suppresses the Smad signaling cascade, or vehicle control (9–11 mice per group). All statistical tests were two-sided.ResultsActivation of TGF-β-dependent and TGF-β-independent Smad signaling was identified in a particular subtype of CAFs and was associated with poor patient survival (patients with higher levels of Smad-regulated gene expression by CAFs: median overall survival = 15 months, 95% confidence interval [CI] = 12.7 to 17.3 months; vs patients with lower levels of Smad-regulated gene expression: median overall survival = 26 months, 95% CI = 15.9 to 36.1 months, P = .02). In addition, the activated Smad signaling identified in CAFs was found to be targeted by repositioning calcitriol. Calcitriol suppressed Smad signaling in CAFs, inhibited tumor progression in mice, and prolonged the median survival duration of ovarian cancer–bearing mice from 36 to 48 weeks (P = .04).ConclusionsOur findings suggest the feasibility of using novel multicellular systems biology modeling to identify and repurpose known drugs targeting cancer–stroma crosstalk networks, potentially leading to faster and more effective cures for cancers.

Front Cover: Site-Specific Systematic Analysis of Lysine Modification Crosstalk

Front Cover: Site-Specific Systematic Analysis of Lysine Modification Crosstalk

Full-Vectorial Mode Coupling in Optical Fibers

Optical full vectorial modes have closely attracted much attention because of their unique optical features and thus may develop the fundamental researches and new functionalities of light. Beyond the conventional linear polarization modal coupling, we thoroughly investigate the inherent polarizationdependence and polarization-isolation features for full vectorial mode coupling in optical fibers, as well as the coupling crosstalk in view of the modal degeneracy. We present the general full vectorial coupling mechanism and numerically simulate the full vectorial mode coupling for both fiber directional and grating assisted coupling cases. Furthermore, we give the detailed analyses of coupling crosstalk based on the unified threemode coupling model. Apart from lifting the modal degeneracy, significantly, the crosstalk can also be reduced by weakening the coupling coefficient and meanwhile increasing the coupling length. This extended full vectorial mode coupling mechanismmay provide theoretical guidance on exploiting new all fiberbased polarization-sensitive passive elements to control fullvectorial fields and modal polarization states.

Analyzing the pathways enriched in genes associated with nicotine dependence in the context of human protein–protein interaction network

Nicotine dependence is the primary addictive stage of cigarette smoking. Although a lot of studies have been performed to explore the molecular mechanism underlying nicotine dependence, our understanding on this disorder is still far from complete. Over the past decades, an increasing number of candidate genes involved in nicotine dependence have been identified by different technical approaches, including the genetic association analysis. In this study, we performed a comprehensive collection of candidate genes reported to be genetically associated with nicotine dependence. Then, the biochemical pathways enriched in these genes were identified by considering the gene’s propensity to be related to nicotine dependence. One of the most widely used pathway enrichment analysis approach, over-representation analysis, ignores the function non-equivalence of genes in candidate gene set and may have low discriminative power in identifying some dysfunctional pathways. To overcome such drawbacks, we constructed a comprehensive human protein–protein interaction network, and then assigned a function weighting score to each candidate gene based on their network topological features. Evaluation indicated the function weighting score scheme was consistent with available evidence. Finally, the function weighting scores of the candidate genes were incorporated into pathway analysis to identify the dysfunctional pathways involved in nicotine dependence, and the interactions between pathways was detected by pathway crosstalk analysis. Compared to conventional over-representation-based pathway analysis tool, the modified method exhibited improved discriminative power and detected some novel pathways potentially underlying nicotine dependence. In summary, we conducted a comprehensive collection of genes associated with nicotine dependence and then detected the biochemical pathways enriched in these genes using a modified pathway enrichment analysis approach with function weighting score of candidate genes integrated. Our results may provide insight into the molecular mechanism underlying nicotine dependence.

Pathway Crosstalk Analysis based on Signaling Pathway Impact Analysis in Alzheimer's Disease

Background: Identifying dysregulated pathways from significant differential expression genes (DEGs) to infer underlying biological insights play an important role in discovering pathogenesis of diseases. However, current pathway-based methods only focus on single pathways in isolation and the analysis of the pathways crosstalk that contains DEGs could improve our understanding of alterations in biological processes. Objective: To explore the underlying dysregulated pathways of Alzheimer's disease (AD) efficiently by the crosstalk analysis on both the significant DEGs and the pathways with high contributions. Method: A novel signaling pathway impact analysis method is used to calculate and rank the signaling pathways of AD. Distance correlation model based on the pathways with ranking contributions is applied to calculate the crosstalk of pathways of AD. Results: The method not only confirms the presence of known pathways associated with AD including Parkinson's disease, Vegf signaling pathway and so on but also predicts the presence of unknown pathways such as Basal cell carcinoma and Olfactory transduction pathways that are significantly associated with the onset and deterioration of AD. Conclusion: The results provide useful supplement and basis for the biological experiments of AD pathogenesis. Keywords: DEGs, pathway-based, crosstalk, distance correlation, Alzheimer's disease, ranking contributions.

FDTD algorithm to achieve absolute stability in performance analysis of SWCNT interconnects

Crosstalk analysis in very-large-scale (VLSI) interconnects is usually carried out using finite-difference time-domain (FDTD) methods. However, the stability of FDTD is limited by the Courant–Friedrichs–Lewy (CFL) stability criteria. In this work, we propose an innovative FDTD algorithm to overcome the stability limitations due to the CFL criteria and make the analysis absolutely stable for all times. Using the proposed FDTD method, we analyze the response of coupled interconnects for symmetric and asymmetric inputs with both in-phase and out-of-phase switching. We further analyzed the functional switching and determined how to reduce noise peaks due to crosstalk. For all responses, we compared our new algorithm with HSPICE results, revealing greatly enhanced accuracy and central processing unit (CPU) runtime compared with conventional FDTD. Finally, relative and absolute stability analyses of the proposed FDTD method were carried out using Nyquist and Routh–Hurwitz (R–H) criteria.

Quantitative analysis of pixel crosstalk in AMOLED displays

ABSTRACTThe resolution of organic light-emitting diode (OLED) displays is increasing steadily as these displays are adopted for mobile and virtual reality (VR) devices. This leads to a stronger pixel crosstalk effect, where the neighbors of active pixels unintentionally emit light due to a lateral electric current between the pixels. Recently, the crosstalk was quantified by measuring the current flowing through the common hole transport layer between the neighboring pixels and comparing it to the current through the active pixel diode [S.-K. Kwon, K.-S. Kim, H.-C. Choi and J. H. Kwon, presented at the International Meeting on Information Display, Jeju, South Korea, 2016]. The measurements showed that the crosstalk is more crucial for low light levels. In such cases, the intended and parasitic currents are similar. The simulations performed in this study validated these measurement results. By simulations, we quantify the crosstalk current through the diode. The luminous intensity can be calculated with the measured current efficiency of the diodes. For low light levels, the unintended luminance can reach up to 40% of the intended luminance. The luminance due to pixel crosstalk is perceivable by humans. This effect should be considered for OLED displays with resolutions higher than 300 PPI.

Dual Biomembrane Force Probe Enables Single-Cell Mechanical Analysis of Signal Crosstalk between Multiple Molecular Species

Dual Biomembrane Force Probe Enables Single-Cell Mechanical Analysis of Signal Crosstalk between Multiple Molecular Species