Perturbation Analysis Research Articles

Recirculation through western boundary currents varies nonlinearly with the ocean basin's aspect ratio

Recirculation gyres adjacent to western boundary currents (WBCs) in the ocean enhance the poleward transport of these currents. While it is well-established that the WBC in a barotropic ocean strengthens with increase in basin's aspect ratio (the meridional-to-zonal extent ratio), how intensity of the recirculation through the western boundary layer varies with this parameter remains unexplored. I address this using the non-dimensional form of the nonlinear, wind-driven Stommel–Munk model of westward intensification that comprises three parameters—the aspect ratio (δ), the damping coefficient (ϵ), and the β-Rossby number (Rβ). Here, ϵ is set by the ratio of Rayleigh friction coefficient (or eddy viscosity) to the meridional gradient of the Coriolis frequency and the basin's zonal dimension, while Rβ is proportional to wind stress amplitude and quantifies the strength of nonlinearity. In the weak-to-moderate nonlinearity limit (Rβ<∼ϵ), perturbation analysis reveals that recirculation varies concavely with aspect ratio, suggesting existence of an optimal aspect ratio (δopt) for which the recirculation is maximum and for typical values of ϵ (10−3−10−2), δopt follows the power-law relation δopt=4.3ϵ. Numerical simulations further validate the existence of δopt. For large ϵ (>5×10−3), the power-law predicts δopt for the numerical solutions rather accurately, but does not hold for smaller ϵ (2×10−3) due to increased importance of nonlinear terms. Nevertheless, the nonlinear variation in recirculation through the western boundary layer with aspect ratio is observed for all ϵ values and may contribute to the heterogeneous increase in the WBC's transport across different ocean basins in a warming climate.

Probabilistic perturbation bounds of matrix decompositions

AbstractIn this article, we determine probabilistic approximations of the entries of random perturbation matrices implementing the Markoff inequality. These approximations are used to derive with prescribed probability asymptotic componentwise perturbation bounds of some orthogonal and unitary matrix decompositions. We show that the probabilistic asymptotic bounds are significantly less conservative than the corresponding deterministic perturbation bounds. As case studies, we consider the determining of probabilistic perturbation bounds of the QR decomposition, the singular value decomposition and the Schur decomposition of a matrix using an unified method for asymptotic componentwise perturbation analysis of these decompositions. It is demonstrated that the probability bounds of the orthogonal transformations, singular values and eigenvalues are much tighter than the corresponding deterministic asymptotic bounds. The probabilistic bounds derived are appropriate for perturbation analysis of large‐order matrix problems.

Nonlinear transient disturbance growth analysis for the compressible external flow and application to a flow around circular cylinder

The property of nonlinear optimal perturbation (NLOP) analysis for the flow around the circular cylinder was investigated with a comparison with the linear optimal perturbation analysis (LOP). Our analysis revealed that NLOP is highly dependent on the initial disturbance norm and highlighted the limitation of linear prediction in triggering instability in the flow field. This NLOP shows an asymmetric and deformed vortex structure on the cylinder wall, with the angle of the maximum wall vorticity shifting in relation to the initial disturbance norm. We also observed that the circulation and disturbance vorticity at the shear layer in boundary layer efficiently contributed to larger disturbance growth of the separation vortex behind the cylinder compared with the LOP.

Quantitative Characterization of the Impact of Protein-Protein Interactions on Ligand-Protein Binding: A Multi-Chain Dynamics Perturbation Analysis Method.

Many protein-protein interactions (PPIs) affect the ways in which small molecules bind to their constituent proteins, which can impact drug efficacy and regulatory mechanisms. While recent advances have improved our ability to independently predict both PPIs and ligand-protein interactions (LPIs), a comprehensive understanding of how PPIs affect LPIs is still lacking. Here, we examined 63 pairs of ligand-protein complexes in a benchmark dataset for protein-protein docking studies and quantified six typical effects of PPIs on LPIs. A multi-chain dynamics perturbation analysis method, called mcDPA, was developed to model these effects and used to predict small-molecule binding regions in protein-protein complexes. Our results illustrated that the mcDPA can capture the impact of PPI on LPI to varying degrees, with six similar changes in its predicted ligand-binding region. The calculations showed that 52% of the examined complexes had prediction accuracy at or above 50%, and 55% of the predictions had a recall of not less than 50%. When applied to 33 FDA-approved protein-protein-complex-targeting drugs, these numbers improved to 60% and 57% for the same accuracy and recall rates, respectively. The method developed in this study may help to design drug-target interactions in complex environments, such as in the case of protein-protein interactions.

On the conformal limit of a QED-inspired model

A conformal invariant QED-inspired model is solved for a general covariant linear gauge using the Dyson–Schwinger equations for the propagators assuming a pure vector like interaction. The leading corrections to the asymptotic solutions and the exponents, that characterize the corrections to each of the two fermion propagator functions, are computed as a function of the coupling and gauge fixing parameter ξ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\xi $$\\end{document}. For the scalar component of the fermion propagator our findings generalizes for linear covariant gauges previous results found in the literature and reproduce the outcome of the perturbative analysis of quenched QED in the Landau gauge. Our solution for the exponent associated with vector component of the fermion propagator is new and, in the weak coupling regime, agrees with the estimation based on the perturbative analysis of quenched QED. Of the two critical exponents describing the conformal limit of the vector interaction, one of them is, in QED, associated with the regime where chiral symmetry is broken dynamically, which demands one mass scale, namely the Miransky scaling. A second mass scale has to be introduced at larger coupling constants and is associated with a change on the nature of the fermion wave function. This provides one example, that it is possible to find two interwoven cycles in Quantum Field Theory, albeit in a truncated framework, as it is known in the quantum few-body problem in the limit of a zero-range interaction.

A multi-modal framework improves prediction of tissue-specific gene expression from a surrogate tissue

Tissue-specific analysis of the transcriptome is critical to elucidating the molecular basis of complex traits, but central tissues are often not accessible. We propose a methodology, Multi-mOdal-based framework to bridge the Transcriptome between PEripheral and Central tissues (MOTPEC). Multi-modal regulatory elements in peripheral blood are incorporated as features for gene expression prediction in 48 central tissues. To demonstrate the utility, we apply it to the identification of BMI-associated genes and compare the tissue-specific results with those derived directly from surrogate blood. MOTPEC models demonstrate superior performance compared with both baseline models in blood and existing models across the 48 central tissues. We identify a set of BMI-associated genes using the central tissue MOTPEC-predicted transcriptome data. The MOTPEC-based differential gene expression (DGE) analysis of BMI in the central tissues (including brain caudate basal ganglia and visceral omentum adipose tissue) identifies 378 genes overlapping the results from a TWAS of BMI, while only 162 overlapping genes are identified using gene expression in blood. Cellular perturbation analysis further supports the utility of MOTPEC for identifying trait-associated gene sets and narrowing the effect size divergence between peripheral blood and central tissues. The MOTPEC framework improves the gene expression prediction accuracy for central tissues and enhances the identification of tissue-specific trait-associated genes. This research is supported by the National Natural Science Foundation of China 82204118 (D.Z.), the seed funding of the Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province (2020E10004), the National Institutes of Health (NIH) Genomic Innovator Award R35HG010718 (E.R.G.), NIH/NHGRI R01HG011138 (E.R.G.), NIH/NIA R56AG068026 (E.R.G.), NIH Office of the Director U24OD035523 (E.R.G.), and NIH/NIGMS R01GM140287 (E.R.G.).

Microcystin-LR activates serine/threonine kinases and alters the phosphoproteome in human HepaRG cells

Microcystin-LR (MCLR) exposure has been associated with development of hepatocellular carcinoma (HCC). Many of the carcinogenic mechanisms for MCLR have been attributed to the induction of cell survival and proliferation through altered protein phosphorylation pathways by inhibition of protein phosphatases 1 (PP1) and PP2A. The current study determined MCLR effects on the phosphoproteome in human HepaRG cells. Differentiated HepaRG cells were treated with either vehicle or MCLR followed by phosphoproteomic analysis and Western blotting of MAPK-activated proteins. MCLR decreased cell viability at 24 h at doses as low as 0.03 μM. MCLR also caused a dose-dependent increase in phosphorylation of signaling and stress kinases. The number of decreased phosphosites by 0.1 μM MCLR was similar between the 2 h (212) and 24 h (154) timepoints. In contrast, a greater number of phosphosites were increased at 24 h (567) versus the 2 h timepoint (136), indicating the hyperphosphorylation state caused by MCLR-mediated inhibition of PPs is time-dependent. A kinase perturbation analysis predicted that MCLR exposure at both 2 h and 24 h increased the function of aurora kinase B (AURKB), checkpoint kinase 1 (CHEK1), and serum and glucocorticoid-regulated kinase 1 (SGK1). STRING database analysis of the phosphosites altered by MCLR exposure revealed pathways associated with cell proliferation and survival, including ribosomal protein S6 kinase (RSK), and vascular endothelial growth factor receptor (VEGFR2)-mediated vascular permeability. In addition, several cancer-related KEGG pathways were enriched at both 2 h and 24 h timepoints, and multiple cancer-related disease-gene associations were identified at the 24 h timepoint. Many of the kinases and pathways described above play crucial roles in the development of HCC by affecting processes such as invasion and metastasis. Overall, our data indicate that MCLR-mediated changes in protein phosphorylation involve biological pathways related to carcinogenesis that may contribute to the development of HCC.

Impact of cold dark matter and variable equations of state on the stability of thin-shell wormholes

The goal of this research is to better understand how two identical black hole copies, bounded by a cold dark matter halo, produce and stabilize thin-shell wormholes. The occurrence of a cold dark matter halo is discovered to increase the black hole’s horizon radius. Investigating the stable geometry of these wormholes by linearized radial perturbation analysis is the main objective of the work. It is noteworthy that the development of thin-shell wormholes with reduced energy limitations is associated with the presence of a cold dark matter halo. We study how the stability of the wormholes is affected by variable equations of state, including phantom-like, variable Chaplygin, and barotropic equations of state. The question emphasizes how crucial the existence of a cold dark matter halo is to preserving stable thin-shell wormhole configurations. The findings shed light on the interactions between a cold dark matter halo and wormholes, which improved our knowledge of both phenomena and their possible consequences for extraterrestrial travel.

Estimating the prevalence of terrorism under control policies. A statistical modelling approach

Measuring the intensity of the prevalence of radicalization plays a vital role in countering violent extremism. Hence, several mathematical models have been proposed aiming to describe the complex dynamics of this social phenomenon. It should be noted that existing literature mainly includes deterministic compartmental models, while the measuring of the extremism's intensity is based on the basic reproduction number R0. However, deterministic approaches can only provide an estimation of the mean tendency of the phenomenon, while the R0 index is accompanied by several drawbacks. In this paper, we propose a new compartmental scheme which considers control policies, containing susceptible, resistant, extremist and under-rehabilitation cases. The aforementioned model is combined with the methodology of continuous time Markov processes, leading to the quantification of not just the mean trend but the uncertainty of the phenomenon, too. Moreover, we introduce two new stochastic descriptors for the assessment of the radicalization's severity, namely the exact (Rε) and aggregate (Ra) reproduction numbers that address the limitation of the widely used R0 index. Emphasis is placed on the presentation of theorems and algorithms that describe the computation of their complete distribution functions. We derive formulas for the calculation of elasticities, and perform a perturbation analysis, shedding light on the overall impact of system's parameters on the selected stochastic descriptors. A series of illustrative examples is presented for the illustration of the derived theoretical properties, along with numerical comparisons between the three reproduction numbers. Finally, based on the proposed measures, we pinpoint the most impactful factors, and discuss control policies that facilitate the effective combating of the negative repercussions of terrorism.

Drug Repurposing for COVID-19 by Constructing a Comorbidity Network with Central Nervous System Disorders.

In the post-COVID-19 era, treatment options for potential SARS-CoV-2 outbreaks remain limited. An increased incidence of central nervous system (CNS) disorders has been observed in long-term COVID-19 patients. Understanding the shared molecular mechanisms between these conditions may provide new insights for developing effective therapies. This study developed an integrative drug-repurposing framework for COVID-19, leveraging comorbidity data with CNS disorders, network-based modular analysis, and dynamic perturbation analysis to identify potential drug targets and candidates against SARS-CoV-2. We constructed a comorbidity network based on the literature and data collection, including COVID-19-related proteins and genes associated with Alzheimer's disease, Parkinson's disease, multiple sclerosis, and autism spectrum disorder. Functional module detection and annotation identified a module primarily involved in protein synthesis as a key target module, utilizing connectivity map drug perturbation data. Through the construction of a weighted drug-target network and dynamic network-based drug-repurposing analysis, ubiquitin-carboxy-terminal hydrolase L1 emerged as a potential drug target. Molecular dynamics simulations suggested pregnenolone and BRD-K87426499 as two drug candidates for COVID-19. This study introduces a dynamic-perturbation-network-based drug-repurposing approach to identify COVID-19 drug targets and candidates by incorporating the comorbidity conditions of CNS disorders.

A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology.

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Here, utilizing the Million Veteran Program cohort, we conducted a genome-wide association study in individuals of European and African ancestry. Adding other published data, we performed genome-wide association study meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 208, 14, 3, 2 and 7 independent genome-wide significant loci associated with neuroticism, extraversion, agreeableness, conscientiousness and openness, respectively. These findings represent 62 novel loci for neuroticism, as well as the first genome-wide significant loci discovered for agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety, while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

Sympathetic response following unannounced loss of balance during walking in young adults: laboratory study.

An unannounced balance loss during walking, i.e., balance perturbation, is a stressful event, which changes the activity of the sympathetic nervous system (SNS). We examined SNS response to unannounced balance perturbation during walking, simulating real-life condition of balance loss. We asked: do laboratory-induced unannounced balance losses during walking cause a sympathetic response, and-if so-does it habituate after a series of perturbations? Thirty-four young adults underwent a series of six successive unannounced balance perturbations while walking on a treadmill. Sympathetic activity was monitored continuously using electrodermal activity and compared before and immediately after each unannounced perturbation. All perturbations elicited a significant increase of electrodermal activity (P < 0.001), indicating a phasic increase in the sympathetic drive. The relative phasic increase of electrodermal activity caused by the first perturbation was significantly higher than the last perturbation (P < 0.05). Three different types of electrodermal activity behavior were observed: steady-level tonic SNS activity, increased SNS activity, and decreased SNS activity. Balance loss during walking triggers phasic SNS response, this response habituates after a series of unannounced balance perturbations. In addition, three distinct patterns of tonic sympathetic activity may imply variations in the ability of the SNS response to habituate across individuals.NEW & NOTEWORTHY Up to date, the literature typically provides information about sympathetic nervous system activity and relatively static balance. We believe that exposing participants to a balance loss during walking, i.e., unexpected perturbation, provides a more ecologically valid situation to measure sympathetic nervous system response; this provides new and vital knowledge that can have a significant impact and understanding of how the SNS responds to a loss of balance in a real-life situation.

Krylov complexity of deformed conformal field theories

We consider a perturbative expansion of the Lanczos coefficients and the Krylov complexity for two-dimensional conformal field theories under integrable deformations. Specifically, we explore the consequences of TT¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{T}\\overline{\ extrm{T}} $$\\end{document}, JT¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{J}\\overline{\ extrm{T}} $$\\end{document}, and JJ¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{J}\\overline{\ extrm{J}} $$\\end{document} deformations, focusing on first-order corrections in the deformation parameter. Under TT¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{T}\\overline{\ extrm{T}} $$\\end{document} deformation, we demonstrate that the Lanczos coefficients bn exhibit unexpected behavior, deviating from linear growth within the valid perturbative regime. Notably, the Krylov exponent characterizing the rate of exponential growth of complexity surpasses that of the undeformed theory for positive value of deformation parameter, suggesting a potential violation of the conjectured operator growth bound within the realm of perturbative analysis. One may attribute this to the existence of logarithmic branch points along with higher order poles in the autocorrelation function compared to the undeformed case. In contrast to this, both JJ¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{J}\\overline{\ extrm{J}} $$\\end{document} and JT¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \ extrm{J}\\overline{\ extrm{T}} $$\\end{document} deformations induce no first order correction to either the linear growth of Lanczos coefficients at large-n or the Krylov exponent and hence the results for these two deformations align with those of the undeformed theory.

The core-EP inverse: a numerical approach for its acute perturbation

This paper studies the concept of stable perturbation B ∈ C n × n for the core-EP inverse of a matrix A ∈ C n × n with index k. For a given stable perturbation B of A, explicit expressions of its core-EP inverse B ◯ $ † $ and its projection at zero B π are presented. Then, the perturbation bounds of ∥ B ◯ $ † $ − A ◯ $ † $ ∥ / ∥ A ◯ $ † $ ∥ and ∥ B π − A π ∥ are given provided that B is a stable perturbation of A. In addition, we investigate the concept of acute perturbation of A. We give a perturbation analysis with respect to core-EP inverses. We provide a condition under which the acute perturbation coincides with the stable perturbation for core-EP inverses.

An ice‐obligate seabird responds to a multi‐decadal decline in Arctic sea ice

AbstractThe Arctic has experienced greatly decreased sea ice and increased ocean temperatures in recent decades but there is a paucity of biological time‐series data allowing assessment of resulting temporal variation in the region's marine ecosystems. Seabirds, as highly mobile and highly visible, upper trophic‐level predators, can be valuable monitors of modifications in marine ecosystems, especially for regions lacking commercial fisheries or regular oceanographic sampling. Since 1975, we have studied annually an Arctic Alaskan colony of Mandt's black guillemot (Cepphus grylle mandtii), an ice‐obligate diving seabird, specializing on Arctic cod (Boreogadus saida), the primary forage fish of the ice‐associated cryopelagic ecosystem. Using multi‐state capture–mark–recapture models, matrix population models, and perturbation analysis, we quantified the environmental and demographic drivers of population change from 1980 to 2019 for the individually marked population. The colony increased rapidly, from &lt;20 to &gt;200 breeding pairs from 1975 to 1990 in response to increased availability of nesting cavities, before experiencing intermittent declines to &lt;50 pairs in 2021. Immigration and apparent survival were the primary demographic parameters affecting population growth with sea ice extent in late summer and fall the primary environmental driver. The initial growth occurred during a period of primarily negative winter Arctic Oscillations (WAO) and extensive summer sea ice. The decline began when an extremely positive WAO in 1989/1990 initiated changes in atmospheric and oceanographic circulation causing major reductions in summer sea ice throughout the region. The three‐decade decline in the population saw plateaus or minor growth with increasing frequency of negative WAOs and increasing declines following two previously identified “tipping points” in sea ice loss. Breeding success at the study colony declined with decreased availability of Arctic cod due to sea ice loss and increasing sea surface temperature and is presumed to have occurred at the source colonies for immigrants where similar oceanographic changes were occurring. Quasi‐extinction of the colony (reduction to &lt;25 pairs) is predicted within the next two decades. The sensitivity of Mandt's black guillemot to multi‐decadal changes in the Arctic's cryopelagic ecosystem makes it an excellent sentinel species for the region with its recent collapse having dire implications for the Arctic Ocean's constituent species.

Singular Perturbation Analysis for a Coupled KdV–ODE System

Singular Perturbation Analysis for a Coupled KdV–ODE System

Randomized algorithms for large-scale dictionary learning

Dictionary learning is an important sparse representation algorithm which has been widely used in machine learning and artificial intelligence. However, for massive data in the big data era, classical dictionary learning algorithms are computationally expensive and even can be infeasible. To overcome this difficulty, we propose new dictionary learning methods based on randomized algorithms. The contributions of this work are as follows. First, we find that dictionary matrix is often numerically low-rank. Based on this property, we apply randomized singular value decomposition (RSVD) to the dictionary matrix, and propose a randomized algorithm for linear dictionary learning. Compared with the classical K-SVD algorithm, an advantage is that one can update all the elements of the dictionary matrix simultaneously. Second, to the best of our knowledge, there are few theoretical results on why one can solve the involved matrix computation problems inexactly in dictionary learning. To fill-in this gap, we show the rationality of this randomized algorithm with inexact solving, from a matrix perturbation analysis point of view. Third, based on the numerically low-rank property and Nyström approximation of the kernel matrix, we propose a randomized kernel dictionary learning algorithm, and establish the distance between the exact solution and the computed solution, to show the effectiveness of the proposed randomized kernel dictionary learning algorithm. Fourth, we propose an efficient scheme for the testing stage in kernel dictionary learning. By using this strategy, there is no need to form nor store kernel matrices explicitly both in the training and the testing stages. Comprehensive numerical experiments are performed on some real-world data sets. Numerical results demonstrate the rationality of our strategies, and show that the proposed algorithms are much efficient than some state-of-the-art dictionary learning algorithms. The MATLAB codes of the proposed algorithms are publicly available from https://github.com/Jiali-yang/RALDL_RAKDL.

A Comparative Analysis of Centrality Measures in Complex Networks

Identification of central elements in networks is an ill-defined problem. Hence, a large number of centrality measures have been proposed in the literature. We present a survey of existing axioms, which characterize certain properties of centralities. We also perform a perturbation analysis of centrality measures in real and artificial networks.

Optical theorem in the 3-D scattering from a locally perturbed lossless or lossy thin dielectric plate: silver disk-sealed hole analysis

This paper is aimed at devising a new optical theorem formulation for the 3-D plane-wave scattering from an infinite resistive plane and, more generally, a thin dielectric plate with a finite-size inhomogeneity shaped as a hollow or sealed hole. This formulation is further modified to cover the case of the plane guided wave scattering from the same inhomogeneity. For the lossless plane, the diffracted field combines a classical outgoing spherical wave, satisfying the Silver-Muller radiation condition, with an outgoing cylindrical guided wave supported by the plane; the power absorbed in the lossy filling is finite. When a lossy plane is involved, a complication appears: the total absorbed power is infinite. However, a change in the inhomogeneity characteristics perturbs the absorbed power density, thus suggesting the perturbative absorption analysis. After developing the analytical procedure for the resistive plane case and the corresponding generalization to the thin dielectric plate case, we illustrate the significance of the new optical theorem by the numerical analysis of the visible-light scattering from a dielectric plate with a circular nanosize hole sealed with a silver disk. Our analysis uses the in-house code having mathematically guaranteed convergence; it reveals the scattering and absorption resonances on the plasmon modes of the silver nanodisk. The derived optical theorem allows us to see that, in the resonances, the power carried by the guided waves can be comparable to the power scattered into the free space.

Multiome Perturb-seq unlocks scalable discovery of integrated perturbation effects on the transcriptome and epigenome.

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Pseudotime analysis of perturbations connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state.