Class Of Observables Research Articles

Helical chromonema coiling is conserved in eukaryotes.

Efficient chromatin condensation is required to transport chromosomes during mitosis and meiosis, forming daughter cells. While it is well accepted that these processes follow fundamental rules, there has been a controversial debate for more than 140 years on whether the higher-order chromatin organization in chromosomes is evolutionarily conserved. Here, we summarize historical and recent investigations based on classical and modern methods. In particular, classical light microscopy observations based on living, fixed, and treated chromosomes covering a wide range of plant and animal species, and even in single-cell eukaryotes suggest that the chromatids of large chromosomes are formed by a coiled chromatin thread, named the chromonema. More recently, these findings were confirmed by electron and super-resolution microscopy, oligo-FISH, molecular interaction data, and polymer simulation. Altogether, we describe common and divergent features of coiled chromonemata in different species. We hypothesize that chromonema coiling in large chromosomes is a fundamental feature established early during the evolution of eukaryotes to handle increasing genome sizes.

Conservative Scattering of Spinning Black Holes at Fourth Post-Minkowskian Order.

Using the N=1 supersymmetric, spinning worldline quantum field theory formalism, we compute the conservative spin-orbit part of the momentum impulse Δp_{i}^{μ}, spin kick ΔS_{i}^{μ}, and scattering angle θ from the scattering of two spinning massive bodies (black holes or neutron stars) up to fourth post-Minkowskian (PM) order. These three-loop results extend the state of the art for generically spinning binaries from 3PM to 4PM. They are obtained by employing recursion relations for the integrand construction and advanced multiloop Feynman integral technology in the causal (in-in) worldline quantum field theory framework to directly produce classical observables. We focus on the conservative contribution (including tail effects) and outline the computations for the dissipative contributions as well. Our spin-orbit results agree with next-to-next-to-next-to-leading-order post-Newtonian and test-body data in the respective limits. We also reconfirm the conservative 4PM nonspinning results.

Adaptive neural network observer for proton-exchange membrane fuel cell system

Abstract This paper develops an adaptive neural network (NN) observer for proton-exchange membrane fuel cells (PEMFCs). Indeed, information on the oxygen excess ratio (OER) value is crucial to ensure optimal management of the durability and reliability of the PEMFC. The OER indicator is computed from the mass of oxygen and nitrogen inside the PEMFC cathode. Unfortunately, the measurement process of both these masses is difficult and costly. To solve this problem, the design of a PEMFC state observer is attractive. However, the behaviour of the fuel cell system is highly non-linear and its modelling is complex. Due to this constraint, a multilayer perceptron neural network (MLPNN)-based observer is proposed in this paper to estimate the oxygen and nitrogen masses. One notable advantage of the suggested MLPNN observer is that it does not require a database to train the NN. Indeed, the weights of the NN are updated in real time using the output error. In addition, the observer parameters, namely the learning rate and the damping factor, are online adapted using the optimization tools of extremum seeking. Moreover, the proposed observer stability analysis is performed using the Lyapunov theory. The observer performances are validated by simulation under MATLAB®/Simulink®. The supremacy of the proposed adaptive MLPNN observer is highlighted by comparison with a fixed-parameter MLPNN observer and a classical high-gain observer (HGO). The mean relative error value of the excess oxygen rate is considered the performance index, which is equal to 1.01% for an adaptive MLPNN and 3.95% and 9.95% for a fixed MLPNN and HGO, respectively. Finally, a robustness test of the proposed observer with respect to measurement noise is performed.

Classical observables from the exponential representation of the gravitational S-matrix

By combining the KMOC-formalism with the exponential representation of the scattering matrix we show that the two-body scattering angle is given by the corresponding matrix element of the exponential representation. This holds to all orders in the Post-Minkowskian expansion of gravity when restricted to the conservative sector. Once gravitational radiation is taken into account new terms correcting this relationship appear starting at fourth Post-Minkowskian order. A systematic expansion of the momentum kick is provided to any order, thus illustrating the iterative structure that partly recycles terms from lower orders in the Post-Minkowskian expansion. We provide explicit results for this computation to fourth Post-Minkowskian order, the first complete calculation at this order based on scattering amplitudes.

A globally exponentially stable observer for torque estimation with only position measurement

A novel estimation scheme for joint torque information is constructed by observer design method in the case that force/torque/velocity/acceleration sensors of manipulator are not available. Based on generalized dynamic scaling function and scalar filtering, the globally exponentially stable observer for torque estimation with only position measurement is presented in this article. The main contribution lies in the development of the classic Nicosia observer with performance improvements and significant order reduction compared to the existing results. Comparative simulations demonstrate the effectiveness and superiority of the proposed scheme.

Robust Speed Control of Uncertain Two-Mass System

The main purpose of this work is to present a robust speed control structure for a two-mass system. The tested system consists of a PI controller with two additional feedback. The coefficients of the control system are selected using a pattern-search optimization method in order to obtain robustness to changes in the system parameters. The control system requires information about non-measurable state variables. For this purpose, it is proposed to use a multilayer observer. In order to show the advantages of the MLO system, this article also presents comparative studies with a classical observer. A number of simulation and experimental tests are carried out. The obtained results confirmed a much higher quality of control in the system cooperating with a multilayer observer compared to the system with a classical observer.

A Comparative Study of Methods Recording Beekeeping Flora

The knowledge of beekeeping flora of an area and of each plant’s provision is crucial for beekeepers to plan their hive transfers when practicing nomadic beekeeping. Thus, in the present study, we evaluated the use of pollen traps as a means of identifying beekeeping plants in target areas, assessing their pollen percentage contributions and estimating their flowering seasons. The results were compared with the classical field observation method, widely used for flora recording. In total, 98.8% of the plants were recognized by using pollen traps and 89.4% from observations in the field, while for 73% there was found an agreement between population size (Wittig Scale) and Pollen Contribution Scale (PCS). The results showed that pollen traps can be helpful tools not only for defining the presence or absence of a beekeeping plant, but also for providing important information regarding the population size of a taxon of major beekeeping importance in the area surrounding the apiary. Finally, the estimation of the flowering season and its maximum point can be accurately predicted by using pollen traps on plants of beekeeping interest.

Revisiting scale invariance and scaling in ecology: River fractals as an example

AbstractScale invariance, which refers to the preservation of geometric properties regardless of observation scale, is a prevalent phenomenon in ecological systems. This concept is closely associated with fractals, and river networks serve as prime examples of fractal systems. Quantifying river network complexity is crucial for unveiling the role of river fractals in riverine ecological dynamics, and researchers have used a metric of “branching probability” to do so. Previous studies showed that this metric reflects the fractal nature of river networks. However, a recent article by Carraro and Altermatt (2022) contradicted this classical observation and concluded that branching probability is “scale dependent.” I dispute this claim and argue that their major conclusion is derived merely from their misconception of scale invariance. Their analysis in the original article (fig. 3a) provided evidence that branching probability is scale‐invariant (i.e., branching probability exhibits a power‐law scaling), although the authors erroneously interpreted this result as a sign of scale dependence. In this article, I re‐introduce the definition of scale invariance and show that branching probability meets this definition. This provided an opportunity to address the divergent use of “scale invariance” and “scaling” between fractal theory and ecology.

An Adaptive Torque Observer Based on Fuzzy Inference for Flexible Joint Application

Torque observation techniques have been widely employed to estimate the load torque of flexible joints driven by a permanent magnet synchronous machine (PMSM). However, the performance of the observer degrades significantly when the position and orientation of the robot continuously changes, resulting in substantial irregular load variations. In this paper, an adaptive torque observer based on fuzzy inference is proposed to overcome this issue. Instead of relying on theoretical or numerical derivation, the relationship between the load inertia and the closed-loop poles of the torque observer is expressed by fuzzy inference. This approach enables the flexible configuration of the poles based on the load inertia, allowing for automatic tuning of the gain matrix. Consequently, the observer can ensure robustness and maintain superior performance under varying load conditions. The effectiveness of the proposed observer is validated through simulation and experimental results. It shows that compared to the classical Luenberger observer, the proposed adaptive torque observer can achieve more accurate observation results and exhibits a more dynamic response in the presence of varying load inertia.

All Order Gravitational Waveforms from Scattering Amplitudes.

Waveforms are classical observables associated with any radiative physical process. Using scattering amplitudes, these are usually computed in a weak-field regime to some finite order in the post-Newtonian or post-Minkowskian approximation. Here, we use strong-field amplitudes to compute the waveform produced in scattering of massive particles on gravitational plane waves, treated as exact nonlinear solutions of the vacuum Einstein equations. Notably, the waveform contains an infinite number of post-Minkowskian contributions, as well as tail effects. We also provide, and contrast with, analogous results in electromagnetism.

A probabilistic assessment of surface water-groundwater exchange flux at a PCE contaminated site using groundwater modelling

Polluted groundwater discharge at a chlorinated solvent contaminated site in Hagfors, Sweden, is affecting a nearby stream flowing through a sparsely populated area. Because of difficulties related to source zone remediation, decision makers recently changed the short-term site management objective to mitigating discharge of polluted groundwater to the stream. To help formulating targeted remediation strategies pertaining to the new objective, we developed a groundwater numerical decision-support model. To facilitate reproducibility, the modelling workflow was scripted. The model was designed to quantify and reduce the uncertainty of surface water-groundwater (SW-GW) exchange fluxes for the studied period (2016–2020) through the use of history-matching. In addition to classical observations, thermal anomalies detected in fiber optic distributed temperature sensing (FO-DTS) measurements were used to inform the model of groundwater discharge. After assessing SW-GW exchange fluxes, we used measurements of surface water chemistry to provide a probabilistic estimation of mass influx and spatio-temporal distributions of contaminated groundwater discharge. Results show 1) SW-GW exchange fluxes are likely to be significantly larger than previously estimated, and 2) prior estimations of mass influx are located near the center of the posterior probability distribution. Based on this, we recommend decision makers to focus remediation action on specific segments of the stream.

Classical gravitational observables from the Eikonal operator

We propose two possible eikonal operators encoding the effects of classical radiation as coherent states of gravitons and show how to compute from them different classical observables. In the first proposal, only genuinely propagating gravitons are included, while, in the second, zero-frequency modes are added in order to recover the effects of a static gravitational field. We first calculate the radiated energy-momentum and the change in each particle's momentum, or impulse, to 3PM order finding agreement with the literature. We then calculate the angular momentum of the gravitational field after the collision. In order to do so, we adapt the method of reverse unitarity to the presence of derivatives in the operators describing the angular momentum and reproduce the result of [1] obtained by resumming the small-velocity expansion. As a new application, we derive also the variation in each particle's angular momentum up to 3PM: calculating separately field and particle contributions allows us to check the balance laws explicitly. We also show how the eikonal operator encodes the linear-response formula of Bini-Damour by deriving the linear radiation-reaction contribution to the transverse impulse at 4PM.

Mean and variance of the cardinality of particles in infinite true polyanalytic Ginibre processes via a coherent states quantization method

We discuss the mean and variance of the number ‘point-particles’ inside a disk D R centered at the origin of the complex plane and of radius R > 0 with respect to an infinite true polyanalytic process of index by quantizing the phase space via a set of generalized coherent states (CSs) of the harmonic oscillator on . By this procedure, the spectrum of the quantum observable representing the indicator function ofD R (viewed as a classical observable) allows to compute the mean value of . The variance of is obtained as a special eigenvalue of a quantum observable involving the auto-convolution of . By adopting a CSs quantization approach, we seek to identify classical observables on whose quantum counterparts may encode the first cumulants of through spectral properties.

Observers for Robust Rotor State Estimation

The paper discusses the synthesis of linear and nonlinear observers to estimate rotor states from fuselage state measurements alone. First, the paper reviews two forms of the classical Luenberger linear observer applied to the rotor state estimation problem and identifies some limitations thereof. Thereafter, the paper proposes a new robust nonlinear discontinuous observer based on the sliding mode theory to simultaneously estimate rotor flapping and lead-lagging states from fuselage state measurements. For this new nonlinear observer, the paper presents stability analyses to determine conditions that guarantee rotor state estimation accuracy despite unknown but bounded turbulence input. The nonlinear observer also lends itself to the online and real-time estimation of the unknown turbulence input. Simulation results in calm and turbulent air conditions highlight the efficacy and performance of the nonlinear discontinuous observer. Such rotor state observers could provide an independent source of online and real-time rotor states estimates to complement or supplement in situ rotor state measurement apparatus for various flight control and health-monitoring functions.

Mixture Basis Function Approximation and Neural Network Embedding Control for Nonlinear Uncertain Systems with Disturbances

A neural network embedding learning control scheme is proposed in this paper, which addresses the performance optimization problem of a class of nonlinear system with unknown dynamics and disturbance by combining with a novel nonlinear function approximator and an improved disturbance observer (DOB). We investigated a mixture basic function (MBF) to approximate the unknown nonlinear dynamics of the system, which allows an approximation in a global scope, replacing the traditional radial basis function (RBF) neural networks technique that only works locally and could be invalid beyond some scope. The classical disturbance observer is improved, and some constraint conditions thus are no longer needed. A neural network embedding learning control scheme is exploited. An arbitrary type of neural network can be embedded into a base controller, and the new controller is capable of optimizing the control performance by tuning the parameters of neural network and satisfying the Lyapunov stability simultaneously. Simulation results verify the effectiveness and advantage of our proposed methods.

New structure to design interval observers for linear continuous-time systems

In this contribution, a new approach to design interval observer for continuous-time linear systems is introduced. First, a more general structure than the classical Luenberger observer is proposed and extended to the interval case based on an explicit set integration method. Then, to obtain tight state enclosures, the computation of the design matrices involved in this new structure is formulated as a nonlinear constrained optimisation problem. In addition, using the symmetric property of interval vectors, a less complex form of the proposed interval observer is presented. On the other hand, compared to the conventional interval observers, no preserving order property on the dynamics of the estimation error is required to apply the introduced method. A numerical case study example is considered to illustrate the effectiveness of the proposed method and to compare its performance to that of a former method.

Estimation of the liquid water saturation in PEM fuel cells: A low-power peaking-free dead-zone observer approach

Water management in polymer electrolyte membrane fuel cells (PEMFCs) is one of the most challenging issues affecting PEMFC efficiency and lifetime. The unavailability of reliably liquid water saturation sensors hinders the applicability of liquid water active control and supervision techniques. A promising technique that can be applied in this context are high-gain observers. However, the performance of this type of observer is significantly limited by the peaking phenomena and its noise sensibility. In general, this performance is not adequate for the considered estimation problem. For this reason, this work proposes a new high-gain observer without peaking and with reduced noise sensibility. The convergence of the observer is proven through rigorous arguments. Moreover, the algorithm is shown to be applicable in PEMFC systems through numerical simulations and experimental validation. It is shown that the proposed approach achieves a reduction of 32.3% of the mean square error in the estimation while maintaining the convergence rate and robustness of classical high-gain observers.

Assessment of nanomechanical properties of Candida albicans as an element of the oral mycobiota in healthy subjects – a preliminary study

Abstract In a healthy physiological state, the mucous membrane of the oral cavity creates a suitable environment for the colonization of Candida spp. yeasts. The aim of the study was to analyze the nanomechanical properties of C. albicans cells derived from the oral cavity of healthy people in a biofilm produced in laboratory conditions. Candida spp. were sampled from the oral cavity of healthy individuals. The process of biofilm formation was analyzed using classic microscopic observation enriched with SEM (scanning electron microscope) and the nanomechanical properties of the cells were assessed with the use of the atomic force microscopy technique (AFM). From all isolated strains in the samples collected of the oral cavity healthy people was detected 79% C. albicans. Other isolated species belonged to the group „non-albicans”. The observations of C. albicans carried out in 24-h cultures revealed a tendency of the cells to form a biofilm structure with multilayer cell systems. The diameter of C. albicans cells in this structure was 5.75 µm, and the length of the pseudohyphae was 17.08 µm. The presence of an extracellular substance surrounding the C. albicans cells was detected. The mean value of the adhesion force determined for C. albicans cells was 4.01 nN. Areas with increased hardness (Force Modulation Mode signal; FMM signal) were found mainly in the zones of cells in contact with the glass substrate. The analysis of Candida cells in liquid samples gives satisfactory results, as it prevents unfavorable changes in the cell surface and thus provides more reliable results. The quality of the biofilm is probably related to the nanomechanical properties of C. albicans cells and may consequently contribute to the stability of the biofilm structures and their susceptibility or resistance to antifungal drugs. The presence of Candida spp. especially in companion animals (dogs, cats) poses a risk of their transmission to the human organism. For this reason, it is advisable to undertake additional research to analyze the ability of zoonotic-origin Candida spp. to form biofilms with comparison of the biofilm-formation capacity of species isolated from humans.

Sulcal morphology of posteromedial cortex substantially differs between humans and chimpanzees

Recent studies identify a surprising coupling between evolutionarily new sulci and the functional organization of human posteromedial cortex (PMC). Yet, no study has compared this modern PMC sulcal patterning between humans and non-human hominoids. To fill this gap in knowledge, we first manually defined over 2500 PMC sulci in 120 chimpanzee (Pan Troglodytes) hemispheres and 144 human hemispheres. We uncovered four new sulci, and quantitatively identified species differences in sulcal incidence, depth, and surface area. Interestingly, some sulci are more common in humans and others, in chimpanzees. Further, we found that the prominent marginal ramus of the cingulate sulcus differs significantly between species. Contrary to classic observations, the present results reveal that the surface anatomy of PMC substantially differs between humans and chimpanzees—findings which lay a foundation for better understanding the evolution of neuroanatomical-functional and neuroanatomical-behavioral relationships in this highly expanded region of the human cerebral cortex.

The sub-leading scattering waveform from amplitudes

We compute the next-to-leading order term in the scattering waveform of uncharged black holes in classical general relativity and of half-BPS black holes in mathcal{N} = 8 supergravity. We propose criteria, generalizing explicit calculations at next-to-leading order, for determining the terms in amplitudes that contribute to local observables. For general relativity, we construct the relevant classical integrand through generalized unitarity in two distinct ways, (1) in a heavy-particle effective theory and (2) in general relativity minimally-coupled to scalar fields. With a suitable prescription for the matter propagator in the former, we find agreement between the two methods, thus demonstrating the absence of interference of quantum and classically-singular contributions. The classical mathcal{N} = 8 integrand for massive scalar fields is constructed through dimensional reduction of the known five-point one-loop integrand. Our calculation exhibits novel features compared to conservative calculations and inclusive observables, such as the appearance of master integrals with intersecting matter lines and the appearance of a classical infrared divergence whose absence from classical observables requires a suitable definition of the retarded time.