Gene expression is a vital process through which cells react to the environment and express functional behavior. Understanding the dynamics of gene expression could prove crucial in unraveling the ...physical complexities involved in this process. Specifically, understanding the coherent complex structure of transcriptional dynamics is the goal of numerous computational studies aiming to study and finally control cellular processes. Here, we report the scaling properties of gene expression time series in
and
. Unlike previous studies, which report the fractal and long-range dependency of DNA structure, we investigate the individual gene expression dynamics as well as the cross-dependency between them in the context of gene regulatory network. Our results demonstrate that the gene expression time series display fractal and long-range dependence characteristics. In addition, the dynamics between genes and linked transcription factors in gene regulatory networks are also fractal and long-range cross-correlated. The cross-correlation exponents in gene regulatory networks are not unique. The distribution of the cross-correlation exponents of gene regulatory networks for several types of cells can be interpreted as a measure of the complexity of their functional behavior.
LPS-responsive beige-like anchor protein (LRBA) deficiency is a primary immunodeficiency disease (PID) characterized by a regulatory T cell defect resulting in immune dysregulation and autoimmunity. ...We present two siblings born to consanguineous parents of North African descent with LRBA deficiency and central nervous system (CNS) manifestations. As no concise overview of these manifestations is available in literature, we compared our patient's presentation with a reviewed synthesis of the available literature.
The younger brother presented with enteropathy at age 1.5 years, and subsequently developed Evans syndrome and diabetes mellitus. These autoimmune manifestations led to the genetic diagnosis of LRBA deficiency through whole exome sequencing with PID gene panel. At 11 years old, he had two tonic-clonic seizures. Brain MRI showed multiple FLAIR-hyperintense lesions and a T2-hyperintense lesion of the cervical medulla. His sister presented with immune cytopenia at age 9 years, and developed diffuse lymphadenopathy and interstitial lung disease. Genetic testing confirmed the same mutation as her brother. At age 13 years, a brain MRI showed multiple T2-FLAIR-hyperintense lesions. She received an allogeneic hematopoietic stem cell transplantation (allo-HSCT) 3 months later. Follow-up MRI showed regression of these lesions.
Neurological disease is documented in up to 25% of patients with LRBA deficiency. Manifestations range from cerebral granulomas to acute disseminating encephalomyelitis, but detailed descriptions of neurological and imaging phenotypes are lacking. LRBA deficiency amongst other PIDs should be part of the differential diagnosis in patients with inflammatory brain lesions. We strongly advocate for a more detailed description of CNS manifestations in patients with LRBA deficiency, when possible with MR imaging. This will aid clinical decision concerning both anti-infectious and anti-inflammatory therapy and in considering the indication for allo-HSCT.
Impulsive noise plays an important role in power line communication among other applications. To improve the communication performance, this paper proposes a novel design of nonlinear processing ...which improves the fundamental performance of signal detection in impulsive noise. Power-law tails are firstly introduced in nonlinearity design to provide adjustable decay factors for different distributions. Four modes of nonlinearity functions are developed and analyzed. By taking the exponent and the threshold as two arguments, we formulate the nonlinearity design as an optimization problem of maximizing the efficacy function, which is the fundamental measurement for detecting a deterministic signal in impulsive noise. Given that the efficacy function is differentiable, unimodal but without closed-form derivatives, we propose to solve the optimization problem by derivative-free methods, e.g. the Nelder-Mead simplex method. As concept demonstration, our method is used for three commonly-used distribution examples. Results show that our nonlinearity design can achieve almost the same efficacy and detection performance as the locally optimal detector, with the advantage of easy-to-apply closed form expressions.
Fractional Dynamics of PMU Data Shalalfeh, Laith; Bogdan, Paul; Jonckheere, Edmond A.
IEEE transactions on smart grid,
05/2021, Letnik:
12, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Novel dynamics are emerging in the power system due to the new Smart Grid (SG) environment. The high sampling rate of the Phasor Measurement Units (PMUs) enables them to capture the dynamic ...fluctuations in the power system measurements. Understanding the statistical and dynamic characteristics of the PMU data requires advanced data analytics techniques capable of performing accurate modeling of the power system variables (voltage, frequency, phase angle, and rate of change of frequency (ROCOF)). In this article, we provide evidence of the non-stationarity and fractality of PMU data collected from Europe. We adopt the Autoregressive Fractionally Integrated Moving Average (ARFIMA) models with non-integer differencing parameter to model the short-range and long-range correlations in the PMU data. Furthermore, the goodness-of-fit of the ARFIMA model is confirmed by analyzing the correlation and independence of the model residuals. Anomaly detection is among the promising applications of the PMU ARFIMA models. It is shown that the 2012 Indian blackout is accompanied by a change point in the differencing parameter opening the road to event (anomaly) detection by ARFIMA monitoring.
Time-Domain Sensitivity of the Tracking Error O'Neil, S.; Schirmer, S. G.; Langbein, F. C. ...
IEEE transactions on automatic control,
04/2024, Letnik:
69, Številka:
4
Journal Article
Recenzirano
A strictly time-domain formulation of the log-sensitivity of the error signal to structured plant uncertainty is presented and analyzed through simple but representative classical and quantum ...systems. Results demonstrate that across a wide range of physical systems, maximization of performance (minimization of the error signal) asymptotically or at a specific time comes at the cost of increased log-sensitivity, implying a time-domain constraint analogous to the frequency-domain identity <inline-formula><tex-math notation="LaTeX">\mathbf {S(s) + T(s) = I}</tex-math></inline-formula>. While of limited value in classical problems based on asymptotic stabilization or tracking, such a time-domain formulation is valuable in assessing the reduced robustness cost concomitant with high-fidelity quantum control schemes predicated on time-based performance measures.
The objective of this paper is real-time detection of a change-point in the baseline distribution of the frequency signal generated by Phasor Measurement Units (PMUs) that could indicate potential ...for voltage collapse, false data injection, or other security threats. The alarm flags an anomaly event when the cumulative sum (CUSUM) of the log-likelihood departures of the Hurst exponent of the frequency from its baseline statistic exceeds a threshold set up as a compromise between the conflicting objectives of minimum detection delay and acceptable False Alarm Rate. As main theoretical contribution, an extra protection layer is developed that provides an estimate of the time to the alarm event, giving the Transmission System Operator (TSO) or an autonomous agent more time to deploy proactive measures to avoid large catastrophic system states. The proposed method is illustrated by a retrospective analysis of the 2012 Indian blackout that reveals that 10-12 minutes before the voltage collapse, a significant increase in the Hurst exponent of the frequency could have been detected. Conceptually, this shows that PMUs provide significant value towards ensuring autonomous cognition in the power grid by enabling the abnormal events to be fault-detected in an unsupervised fashion.
Information encoded in networks of stationary, interacting spin-1/2 particles is central for many applications ranging from quantum spintronics to quantum information processing. Without control, ...however, information transfer through such networks is generally inefficient. Currently available control methods to maximize the transfer fidelities and speeds mainly rely on dynamic control using time-varying fields and often assume instantaneous readout. We present an alternative approach to achieving efficient, high-fidelity transfer of excitations by shaping the energy landscape via the design of time-invariant feedback control laws without recourse to dynamic control. Both instantaneous readout and the more realistic case of finite readout windows are considered. The technique can also be used to freeze information by designing energy landscapes that achieve Anderson localization. Perfect state or superoptimal transfer and localization are enabled by conditions on the eigenstructure of the system and signature properties for the eigenvectors. Given the eigenstructure enabled by superoptimality, it is shown that feedback controllers that achieve perfect state transfer are, surprisingly, also the most robust with regard to uncertainties in the system and control parameters.
To identify the biochemical and molecular genetic defect in a 16-year-old patient presenting with apical hypertrophic cardiomyopathy and neuropathy suspected for a mitochondrial disorder.
Measurement ...of the mitochondrial energy-generating system (MEGS) capacity in muscle and enzyme analysis in muscle and fibroblasts were performed. Relevant parts of the mitochondrial DNA were analysed by sequencing. Transmitochondrial cybrids were obtained by fusion of 143B206 TK(-) rho zero cells with patient-derived enucleated fibroblasts. Immunoblotting techniques were applied to study the complex V assembly.
A homoplasmic nonsense mutation m.8529G-->A (p.Trp55X) was found in the mitochondrial ATP8 gene in the patient's fibroblasts and muscle tissue. Reduced complex V activity was measured in the patient's fibroblasts and muscle tissue, and was confirmed in cybrid clones containing patient-derived mitochondrial DNA. Immunoblotting after blue native polyacrylamide gel electrophoresis showed a lack of holocomplex V and increased amounts of mitochondrial ATP synthase subcomplexes. An in-gel activity assay of ATP hydrolysis showed activity of free F(1)-ATPase in the patient's muscle tissue and in the cybrid clones.
We describe the first pathogenic mutation in the mitochondrial ATP8 gene, resulting in an improper assembly and reduced activity of the complex V holoenzyme.
We propose a model-based reinforcement learning (RL) approach for noisy time-dependent gate optimization with reduced sample complexity over model-free RL. Sample complexity is defined as the number ...of controller interactions with the physical system. Leveraging an inductive bias, inspired by recent advances in neural ordinary differential equations (ODEs), we use an autodifferentiable ODE, parametrized by a learnable Hamiltonian ansatz, to represent the model approximating the environment, whose time-dependent part, including the control, is fully known. Control alongside Hamiltonian learning of continuous time-independent parameters is addressed through interactions with the system. We demonstrate an order of magnitude advantage in sample complexity of our method over standard model-free RL in preparing some standard unitary gates with closed and open system dynamics, in realistic computational experiments incorporating single-shot measurements, arbitrary Hilbert space truncations, and uncertainty in Hamiltonian parameters. Also, the learned Hamiltonian can be leveraged by existing control methods like GRAPE (gradient ascent pulse engineering) for further gradient-based optimization with the controllers found by RL as initializations. Our algorithm, which we apply to nitrogen vacancy (NV) centers and transmons, is well suited for controlling partially characterized one- and two-qubit systems.
We investigate the convexity of the joint numerical range of
m-tuples of
n×
n hermitian matrices. The methods come from differential geometry and the differential and algebraic topology. Our main ...result is a sufficient condition for convexity of the joint numerical range for arbitrary
m and
n. Modulo a mild technical assumption, this condition is formulated in terms of the largest eigenvalue of an associated family of hermitian matrices parameterized by the (
m−1)-dimensional unit sphere. The condition is that the eigenvalue has constant multiplicity. We show that the constant multiplicity condition is in fact a criterion for the
stable convexity of numerical ranges. As a byproduct of our main result, we obtain a new proof of the celebrated Toeplitz–Hausdorff theorem, and of its extension: The numerical range of any triple of hermitian
n×
n matrices is convex if
n>2.
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