Measurable Quantities Research Articles

Optimal Sensor Placement with Minimal Predicted Posterior Variance

The performance of each monitoring system critically depends on the sensor layout and typical optimization criteria are based on the accessibility to the structure on site, experience with similar structures, and an optimal signal-to-noise ratio. More advanced criteria aim to optimize the feature extraction process, and this paper aims to develop a sensor placement strategy for optimal damage diagnosis. The approach is based on Bayesian updating and the optimization goal is to find a sensor layout that is the most sensitive to small changes in the examined system parameters. It is shown that such layouts manifest themselves through a minimum variance in the posterior distribution. Using Kalman filters, the posterior variance can be “predicted” based on the measurement error and numerical models, so no data from and no simulations in the damaged state are required. By employing a polynomial chaos expansion (PCE)-based Kalman filter, the method becomes applicable for structures with many measurement channels, multiple examined system parameters, and for a large number of sensor combinations. Gaussian distributions are assumed for both system inputs and outputs. For proof of concept, the sensor placement is optimized on a numerical cantilever beam, demonstrating that the method can efficiently find the optimal sensor layout. Moreover, arbitrary measurement quantities (inclinations, vibrations, etc.) or damage-sensitive features (statistical values, modal parameters, etc.) can be used as observations, and multiple system parameters can be considered at the same time. Among other factors, an optimal sensor layout leads to large measurement responses, a small measurement error, and more advanced statistical quantities that will be elaborated on in detail.

Aqueous and Plasma Levels of Phosphorylated Tau 181 in Individuals with Normal Cognition.

Plasma and cerebrospinal fluid (CSF) levels of p-tau181 have been associated with Alzheimer's disease (AD). The retina and vitreous have shown measurable quantities of phosphorylated tau 181 (p-tau181). The aqueous humor, which can be collected during cataract surgery, may have measurable concentrations of p-tau181. To determine whether p-tau181 is detectable in the aqueous humor and if so, whether it is associated with other measures that might be consistent with AD such as higher plasma p-tau181 concentration and lower Montreal Cognitive Assessment (MoCA-BLIND version 7.1) score. Aqueous humor samples, blood samples, and MoCA-BLIND scores were collected from patients who did not carry a clinical diagnosis of cognitive impairment at the time of cataract surgery. Aqueous p-tau181 concentrations and plasma p-tau181 concentrations were then measured using ultra-sensitive single-molecule assay ELISA technology. A rank-transformed mixed-effects multivariate regression model was used to determine associations between aqueous concentrations, plasma concentrations, and MoCA-BLIND scores. 16 eyes of 16 participants were enrolled with an average age of 71.6. Average MoCA-BLIND score was 20.6/22, average aqueous p-tau181 concentration was 6.4 pg/mL, and average plasma p-tau181 concentration was 3.1 pg/mL. Higher plasma p-tau181 was significantly associated with higher aqueous p-tau181 (p = 0.02). Aqueous p-tau181 and plasma p-tau181 were negatively associated with MoCA-BLIND scores (p = 0.005 and p = 0.001 respectively) in these patients. Aqueous p-tau181 is positively correlated with plasma p-tau181 and is negatively correlated with MoCA-BLIND scores. Further study in individuals with mild cognitive impairment or AD characterized by cerebrospinal fluid and volumetric MRI metrics may yield further insights.

Interactions Enable Thouless Pumping in a Nonsliding Lattice

A topological “Thouless” pump represents the quantized motion of particles in response to a slow, cyclic modulation of external control parameters. The Thouless pump, like the quantum Hall effect, is of fundamental interest in physics, because it links physically measurable quantities, such as particle currents, to geometric properties of the experimental system, which can be robust against perturbations and, thus, technologically useful. So far, experiments probing the interplay between topology and interparticle interactions have remained relatively scarce. Here, we observe a Thouless-type charge pump in which the particle current and its directionality inherently rely on the presence of strong interactions. Experimentally, we utilize a two-component Fermi gas in a dynamical superlattice which does not exhibit a sliding motion and remains trivial in the single-particle regime. However, when tuning interparticle interactions from zero to positive values, the system undergoes a transition from being stationary to drifting in one direction, consistent with quantized pumping in the first cycle. Remarkably, the topology of the interacting pump trajectory cannot be adiabatically connected to a noninteracting limit, highlighted by the fact that only one atom is transferred per cycle. Our experiments suggest that Thouless charge pumps are promising platforms to gain insights into interaction-driven topological transitions and topological quantum matter. Published by the American Physical Society 2024

Sulphate reduction and carbonate precipitation in a high-energy algal rim framework

Algal ridges are protective features for coral reefs that form through the accretion and encrustation of reef rubble and debris by crustose coralline algae (CCA) and processes of diagenetic cementation. Carbonate precipitation and dissolution dynamics on and within algal ridge frameworks are poorly understood. We studied the surface and subsurface geochemistry of the algal ridge framework at One Tree Island, Australia. Measurable quantities of hydrogen sulphide were detected in most porewater samples collected from bores, indicating a largely anoxic ridge framework. Total alkalinity (TA) and pH measurements indicate that the precipitation of carbonate minerals within the interior of the ridge framework occurs under largely anoxic conditions and is likely to be driven by TA changes associated with sulphate-reducing bacteria. Modelling of porewater hydrogen sulphide concentrations in combination with TA and dissolved inorganic carbon (DIC) indicates anoxic respiration processes produce alkalinity within the algal ridge framework. However, significantly more TA is removed via the precipitation of mineral carbonate, resulting in porewater TA concentrations falling below the open seawater values. The precipitation of mineral carbonate also lowers interstitial water pH, such that pH changes are not solely from organic carbon diagenesis. The simultaneous precipitation and dissolution of carbonate minerals within the algal ridge framework are key to forming and cementing algal ridges, which are important physical protective features for coral reefs.

Global quark spin correlations in relativistic heavy ion collisions

The observation of the vector meson’s global spin alignment by the STAR Collaboration reveals that strong spin correlations may exist for quarks and antiquarks in relativistic heavy-ion collisions in the normal direction of the reaction plane. We propose a systematic method to describe such correlations in the quark matter. We classify them as local and long range quark spin correlations in the system. We show in particular that the effective quark spin correlations contain the genuine spin correlations originated directly from the dynamical process as well as those induced by averaging over other degrees of freedom. We also show that such correlations can be studied by measuring the vector meson’s spin density matrix and hyperon-hyperon and hyperon-anti-hyperon spin correlations. We present the relationships between these measurable quantities and spin correlations of quarks and antiquarks. Published by the American Physical Society 2024

Mass, charge, and distance to Reissner–Nordström black hole in terms of directly measurable quantities

In this paper, we employ a general relativistic formalism and develop new theoretical tools that allow us to analytically express the mass and electric charge of the Reissner–Nordström black hole as well as its distance to a distant observer in terms of few directly observable quantities, such as the total frequency shift, aperture angle of the telescope, and redshift rapidity. Our analytic and concise formulas are valid on the midline, and the redshift rapidity is a relativistic invariant observable that represents the evolution of the frequency shift with respect to the proper time in the Reissner–Nordström spacetime. This procedure is applicable for particles undergoing circular motion around a spherically symmetric and electrically charged black hole, which is the case for accretion disks orbiting supermassive black holes hosted at the core of active galactic nuclei. Although this type of black hole is expected to be electrically neutral, our results provide a novel method to measure the electric charge of the Reissner–Nordström black hole, hence can shed some light on this claim. Besides, these results allow us to measure the mass of the black hole and its distance from the Earth, and we can employ the general formulas in black hole parameter estimation studies.

Correlations of Surface Free Energy and Solubility Parameters with Dielectric Constant, Refractive Index, and Density for Liquids.

There should be some intrinsic correlations between the surface free energy (γ) and solubility (δ) parameters, called characteristic parameters here, of substances with their fundamental physical properties such as the refractive index (nD), relative dielectric constant (εr), and density (ρ) because they are all related to intermolecular interactions. Understanding the correlations between characteristic parameters and fundamental physical quantities is of great fundamental and practical importance. In the current work, possible relationships between the characteristic parameters (γ and δ) and the physical quantities (nD, εr, and ρ) were explored by a trial-and-error fitting method based on the data of 92 liquids (including 14 nonpolar, 37 polar, and 41 hydrogen-bonded liquids). The γ parameters include total (γt), dispersive (γd), and polar (γp) ones, and the δ parameters include the Hildebrand parameter (δt) and the Hansen-dispersive (δd), polar (δp), and hydrogen-bonded (δh) ones. For each characteristic parameter, its relationship with the physical quantities was established. The applicability of the so-obtained relationships was confirmed using the data of another 66 liquids as an external data set. The empirical relationships can be used to estimate the characteristic parameters of liquids from their easily measurable physical quantities.

The Necessity of Machine Learning Theory in Mitigating AI Risk

Highlights SUMMARY In the last years we have witnessed rapidly accelerating progress in Neural Network-based Artificial Intelligence. Yet our fundamental understanding of these methods has lagged far behind. Never before had a technology been developed so quickly and deployed so widely with so little understanding of its basic principles. In this document we argue that deep learning systems with their human-like complexity cannot be controlled and guided in socially acceptable ways or countered in adversarial situations, without an underlying theory. Theory in this context refers to identifying precise measurable quantities and mathematically describing their patterns, the way it is done in physics and engineering, rather than necessarily proving rigorous theorems. Given the societal impact of rapidly proliferating AI, developing such a theory and applying its analyses to real systems is a compelling and urgent need.

Quantum thermometry based on interferometric power

In the field of quantum thermometry, usually temperature is estimated by the framework of quantum metrology. In this work, an alternative approach to quantum thermometry is suggested, based on interferometric power (IP). IP is defined as the worst-case quantum Fisher information in a double-channel interferometer. Specifically, the time evolution of the IP for a two-qubit state as a probe contacting with a finite-temperature bath is considered. The IP dynamics of the probe with three kinds of initial states (i.e., entangled, separable, and mixed) strongly depend on the bath temperature. The dynamical evolution of IP would be measured experimentally, considering that the IP is a measurable quantity in the experiment. Thus, the IP dynamics can be adopted to extract the value of the bath temperature directly. In this sense, the IP could be exploited as a quantum thermometer.

Defining quantitative rules for identifying influential researchers: Insights from mathematics domain

In the midst of a vast amount of scientific literature, the need for specific rules arise especially when it comes to deciding which impactful researchers should be nominated. These rules are based on measurable quantities that can easily be applied to a researcher's quantitative data. Various search engines, like Google Scholar, Semantic Scholar, Web of Science etc. Are used for recording metadata such as the researcher's total publications, their citations, h-index etc. However, the scientific community has not yet agreed upon a single set of criteria that a researcher has to meet in order to secure a spot on to the list of impactful researchers. In this study, we have provided a comprehensive set of rules for the scientific community within the field of mathematics, derived from the top five quantitative parameters belonging to each category. Within each categorical grouping, we meticulously selected the five most pivotal parameters. This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. To perform the experiment, we focused on the field of mathematics and used a dataset containing 525 individuals who received awards and 525 individuals who did not receive awards. The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. Moreover, the highest-ranked parameters belonging to each category were successful in elevating over 50 to 55 percent of the award recipients to positions within the top 100 ranked researchers' list. These findings have the potential to serve as a guidance for individual researchers, who aimed on to making it to the esteemed list of distinguished scientists. Additionally, the scientific community can utilize these rules to sift through the roster of researchers for a subjective evaluation, facilitating the recognition and rewarding of exceptional researchers in the field.

ROBUST CONTROL OF OXYGEN SATURATION DURING MECHANICAL VENTILATION

Acute respiratory distress syndrome (ARDS) is a disease that has a high reported mortality rate. The treatment for ARDS typically involves mechanical ventilation that is tailored to each patient's needs. A crucial aspect of this treatment is maintaining adequate oxygen saturation of haemoglobin by setting the fraction of inspired oxygen. This paper proposes a design method of robust proportional-integral-derivative (PID) controllers using a gas exchange model during ARDS. Several PID controllers were synthesized for different sub-operational ranges defined by measurable quantities of the mechanical ventilator and the patient using a mixed sensitivity H∞ approach. In simulations, the controller demonstrated high robustness to external changes and changes in the patient's condition, with saturation always above 88%. Although further validation of the controller is required, the results indicate that the presented robust control method has the potential to be clinically relevant.

Comparative analysis of dosimetric uncertainty using Gafchromic™ EBT4 and EBT3 films in radiochromic film dosimetry

Advancements in radiotherapy dosimetry aim to enhance precision and accuracy, with Gafchromic™ EBT4 film emerging as a promising tool. However, its performance compared to EBT3 remains underexplored, necessitating a comprehensive analysis of dosimetric uncertainties. This study evaluates the efficacy of EBT4 in radiochromic dosimetry, comparing it to EBT3. Employing a 6 MV beam quality, absorbed doses ranging from 0 to 10 Gy were investigated using different measurement quantities and fitting functions. Gafchromic™ EBT3 and EBT4 films (8′′ × 10″) were irradiated in a water-equivalent phantom, with calibration doses delivered using a Varian Truebeam Stx linear accelerator. Two measurement quantities, pixel values (PV) and net change transmittance (netΔT), were analyzed, along with calibration functions including a rational function for PV and a logarithmic function for netΔT. Uncertainty analyses considered experimental, fitting, and calibration dose uncertainties. Dose-response curves for EBT3 and EBT4 films demonstrated robust fits, emphasizing the reliability of both. EBT4 consistently exhibited lower uncertainties, particularly below 2 Gy, showcasing superior precision in low-dose scenarios. The choice of response quantity and calibration function influenced results, with PV-rational function excelling for doses 2–10 Gy, and netΔT-logarithmic function showing enhanced precision in the 0–2 Gy range. The uncertainty analysis emphasized EBT4's superior performance, especially in low-dose ranges, with lower relative uncertainties and absolute errors, indicating enhanced reliability in dose measurements. The study underscores EBT4's potential to contribute to improved accuracy in various clinical scenarios. However, users should tailor the choice of response quantities and calibration functions to specific dose calibration ranges, suggesting a nuanced approach.

Definite example of negative entropy production in the Rolie Poly model

While it is known that the Rolie Poly model is not guaranteed to be thermodynamically consistent, definite examples of a thermodynamically inconsistent prediction have not yet been published. Additionally, the source of the problem (and its historical context) may not be widely known. This work provides additional background information and a definite example of negative entropy production in an experimentally relevant flow, including a discussion of the implications in terms of an experimentally measurable quantity like recoverable strain.

Monitoring of Stator Winding Insulation Degradation through Estimation of Stator Winding Temperature and Leakage Current

Switched Reluctance Motors (SRMs), Permanent Magnet Synchronous Motors (PMSMs), and induction motors may experience failures due to insulation-related breakdowns. The SRM rotor is of a non-salient nature and made of solid steel material. There are no windings on the rotor. However, the stator is composed of windings that are intricately insulated from each other using materials such as enamel wire, polymer films, mica tapes, epoxy resin, varnishes, or insulating tapes. The dielectric strength of the insulation may fail over time due to several environmental factors and processes. Dielectric breakdown of the winding insulation can be caused by rapid switching of the winding current, the presence of contaminants, and thermal aging. For reliable and efficient operation of the SRMs and other electrical machines, it is necessary to take into account the physics of the winding insulation and perform appropriate diagnostics and estimations that can monitor the integrity of the insulation. This article presents the estimation problem using a Genetic Algorithm (GA)-optimized Random Forest Regressor. Empirical properties and measurable quantities in the historical data are utilized to derive temperature and leakage current estimation. The developed model is then combined with a moving average function to increase the accuracy of prediction of the stator winding temperature and leakage current. The performance of the model is compared with that of the Feedforward Neural Network and Long Short-Term Memory over the same winding temperature and leakage current historical data. The performance metrics are based on computation of the Mean Square Error and Mean Absolute Error.

The importance of the local structure of fractal aggregates

The pair correlation function, g(r), is a fundamental descriptor of the inner structure of fractal aggregates of monomers. It provides a natural tool for studying physical properties involving two-point interaction (e.g. optics of aggregates). Several domains of distances between pairs of monomers have been identified. The fractal domain (in which g(r) is a power-law) is generally dominant for large aggregates. We show here that the local behavior of g(r)—involving monomers tangent to a given monomer—is necessary for most of the quantitative applications, even if that local domain is not directly related to fractal morphology. We derive a simple generic pair correlation function for fractal aggregates, depending on three structural parameters only: the fractal dimension, df ; the prefactor, kf ; the local mean coordination number, Zˉ . Unlike the fractal dimension, the prefactor and the mean coordination number are not universal since they depend on many parameters of the generation process. We discuss the impact of the definite shape of g(r) on the aggregate structure factor profile (a measurable quantity through small-angle x-ray scattering). Improvement from the new g(r) shape is also illustrated deriving an analytical expression of the geometric cross section, G, of aggregates for fractal dimension <2 . Accuracy is checked by comparing with numerical data from aggregates of fractal dimension df=1.9 . On the up-to-date analytical expression of G, the contributions of the short- and long-range behaviours of g(r) are well separated, and it is clear that the local behavior of the pair correlation function is required to obtain accurate values of the geometric cross section. Thus, in addition to the fractal structure of aggregates, the local structure of aggregates (to which the prefactor kf and the g(r) divergence at short distances are related) also appears important to accurately describe their physical features.

Data Acquiring System for Gas Turbine Engine’s Dynamic Performance; Build and Validate

ABSTRACT Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs’ real data is increasing a recognized need for collecting informative real data sets from GTEs for modeling, monitoring, and fault diagnosis and isolation (FDI). In the present article, a robust versatile data acquisition measuring system has been built to collect real-time data from an axial turboshaft GTE. The system facilitates connectivity and integrity by means of two wiring harnesses connecting the data acquisition card (DAQ), the engine’s control unit, and the operator’s control console. Mobility is guaranteed using a wireless connection between DAQ and a customized programmable LabVIEW interface application. Many experiments have been conducted in different operating conditions to collect the engine and controller’s data in different regimes. The measured signals have been filtered using software-implemented filters and transformed into the right measurement quantities. The experiment data have been analyzed for different regimes, and the milestone documented readings were compared with the measured ones to validate the accuracy and precision of the measuring system. The system is valid for collecting informative data sets that are usable for modeling the engine’s dynamic performance and fault detection.

Raychaudhuri equation and the dynamics of cosmic evolution

The paper deals with the Raychaudhuri equation (RE) which is a non-linear ordinary differential equation in Θ, the expansion scalar corresponding to a geodesic flow. Focusing theorem which follows as a consequence of the RE has been restated in terms of the cosmic parameter q (deceleration parameter) both for Einstein gravity and for modified gravity theories. Measurable quantities namely the luminosity distance and density parameter are shown to have an upper bound using the Raychaudhuri scalar. An analogy between geometric and cosmological RE has been made. Subsequently, to find the solution of the non-linear RE a transformation of variable related to the metric scalar of the hyper-surface has been identified which converts the former to a second order differential equation. Finally, the first integral of this second order differential equation gives the entire picture of the dynamics of cosmic evolution

Interrelatedness of thermodynamics and information: transformation of heat as a measurable information process and quantity, an overview

AbstractNo one has yet investigated the information reach and influence of thermal analysis. Even so the heat and entropy are bound closely. The very problem of the term entropy is that it was defined specifically within the classical, equilibrium Thermodynamics like Clausius entropy, while its meaning is more general. It is usable in all areas of physics, in the communication theory and technology, and also, in social sciences, just as an universal quantitative model. The bridge to this wider world is in Boltzmann’s statistical point of view used in the Shannon’s information point of view. The difference is that the Shannon entropy is defined more generally, both for the uniform and for the not uniform probability distributions. But with renormalization and with the Boltzmann constant we can speak, using the Clausius entropy, about a certain thermodynamic system considered as a heat model of the area of our wider interests. So we will to deal with the heat and its entropy embodied to a wider consideration. In addition to the standard physical meaning, another thermodynamic realization in the form of a message is derived from Shannon’s information theory, where the sample carries a measure of Shannon’s information given by its structure or internal organization. This is also a contribution to improving the approach to thinking about the importance of observation and measurement, reflecting at the same time the costs and influence of the measurement itself and its organization on the measured object or, on its environment or, even on the environment of the measuring itself generally. Statistical sorting also carries with it the internal movement of individual elementary particles, the value of which indicates the resulting state of heat transfer and dissipation to and from the system providing a state of called equilibrium. It is statistically described by a weighted quantity called temperature, the changes of which via momentum alteration satisfy Newton’s laws of inertia allowing enumeration of the related heat information processing. The terminology used is still non-institutional.

Quality Assurance in Safe Handling of Hazardous Drugs Among Healthcare Workers in KSA: A Scoping Review

Healthcare providers are potentially at risk from occupational exposure to drugs. Safe handling accreditation criteria from international occupational safety organizations and associations minimize long-term medication exposure harm. The purpose of this review was to examine healthcare workers' quality assurance in the safe handling of hazardous drugs. This topic underwent a scoping review of the literature to determine what was known about exposure and to spot any knowledge gaps using a variety of electronic databases such as Medline, PubMed, EMBASE, Web of Science, and Google Scholar for the literature search. English-language articles that were published between 1997 and 2022 were included. This review included 26 full-text papers in total. The designs, sample sizes, sample collection durations, and medicines studied differed between the investigations. Numerous studies discovered that at least one sample had measurable quantities of a hazardous substance. The studies examined that hazardous drugs are handled in many different stages throughout the healthcare industry, including production, transportation, storage, preparation for patients, and waste disposal after treatment. Healthcare personnel are constantly exposed to HDs. The findings emphasize the need to establish robust regulations, boost training programs, upgrade personal protective equipment, enhance handling techniques, and strengthen monitoring and surveillance systems. More research is required to fill up the gaps and safeguard the safety and health of Saudi Arabia's healthcare professionals who handle hazardous medications.

Dynamic Interfaces in Self-Healable Polymers.

It is well-established that interfaces play critical roles in biological and synthetic processes. Aside from significant practical applications, the most accessible and measurable quantity is interfacial tension, which represents a measure of the energy required to create or rejoin two surfaces. Owing to the fact that interfacial processes are critical in polymeric materials, this review outlines recent advances in dynamic interfacial processes involving physics and chemistry targeting self-healing. Entropic interfacial energies stored during damage participate in the recovery, and self-healing depends upon copolymer composition and monomer sequence, monomer molar ratios, molecular weight, and polymer dispersity. These properties ultimately impact chain flexibility, shape-memory recovery, and interfacial interactions. Self-healing is a localized process with global implications on mechanical and other properties. Selected examples driven by interfacial flow and shape memory effects are discussed in the context of covalent and supramolecular rebonding targeting self-healable materials development.