Values Of Quantities Research Articles

Realistic phantoms for quantitative MR: the need and a proposal (the B1 sleeve)

Quantitative MR (qMR) has offered direct access to in-vivo biology and physiology for over three decades, yet it has failed to translate into the clinic. Why is this? The development of suitable phantoms is a key stage in the evolution of qMR, and here a systematic categorisation is proposed. Currently there is much attention paid to creating simple head phantoms containing materials with metrologically traceable values of MR quantities. However these are usually unrealistic; many of the disrupting phenomena present in clinical imaging are absent. Good performance with a simple traceable phantom is a necessary but not sufficient requirement for the establishment of good in-vivo measurement performance. There is therefore a premium on developing realistic phantoms. A proposal made for a more realistic body phantom that includes RF B1 imperfections. It consists of lossy annuli placed around a standard head phantom. Other confounding phenomena could be identified, possibly built into an appropriate annulus around a simple head phantom, to form realistic phantoms; these would enable validation of qMR methods and translation to the clinic. The concept is probably applicable to other quantitative diagnostic imaging modalities.

Random forests for detecting weak signals and extracting physical information: A case study of magnetic navigation

It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical quantities of interest. In particular, from time-series data gathered from the cockpit of a flying airplane during various maneuvering stages, where strong background complex signals are caused by other elements of the Earth’s magnetic field and the fields produced by the electronic systems in the cockpit, we demonstrate that the random-forest algorithm performs remarkably well in detecting the weak anomaly field and in filtering the position of the aircraft. With the aid of the conventional inertial navigation system, the positioning error can be reduced to less than 10 m. We also find that, contrary to the conventional wisdom, the classic Tolles–Lawson model for calibrating and removing the magnetic field generated by the body of the aircraft is not necessary and may even be detrimental for the success of the random-forest method.

In-service Physics Teachers in the Light of Principles and Tenets of Human Learning: Introduction to Sampling Frequency

Sensors specially designed for use in schools to measure values of physical quantities within physics education have already had their place in science education theory for some decades. In this contribution, the effective use of sensors is discussed in the light of principles and tenets of human learning, as proposed by colleagues researching the application of neuroscience to education. The contribution focuses on in-service physics teachers’ training, and the application of the principles and tenets is illustrated on the topic of sampling frequency, introduction to sampling frequency at the age of 12 and another example at the higher secondary school.

Research on Condition Assessment Method of Transformer Based on Cloud Model

The traditional evaluation method of transformer has the problems of strong subjectivity of threshold value and fuzzy correlation of state quantity, which is difficult to accurately evaluate the operation quality of transformer. In order to solve these problems, this paper proposes a comprehensive evaluation method of transformer performance evaluation and operation quality based on cloud model. The evaluation index system of power transformer operation quality considering performance is constructed, including target layer, performance layer and index layer. The triangular fuzzy number is used to optimize the set of expert opinions, and the indexes are combined and weighted by fuzzy analytic hierarchy process and entropy weight method. After the data is degraded, the membership matrix of transformer operation index is constructed by using the cloud model, and the performance state weighting and membership degree are comprehensively considered to realize the performance evaluation of transformer and the comprehensive evaluation of operation quality based on performance. By using this method to predict 10 transformers in operation for a period of one month, it is possible to accurately identify abnormal situations on site, with a prediction accuracy of 96.28%. Compared with the traditional method of “predicting first and then diagnosing”, it has improved by 14.32%, overcoming the shortcomings of subjectivity, ambiguity, and ignoring the correlation of state variables in traditional evaluation methods. This method provides new ideas and methods for accurate evaluation of transformers.

How are microbes helping end hunger?

This article explores the potential of microbiology to positively impact all aspects of the food supply chain, improving the quantity, quality, safety, and nutritional value of food products by providing innovative ways of growing, processing, and preserving food and thus contributing to Zero Hunger, one of the Sustainable Development Goals (SDGs) of the United Nations.

Exploring students' proportional reasoning in mathematical literacy problem solving: recognition of multiplicative relationship strategies

Introduction. A multiplicative relationship represents the association between two or more variables in the form of multiplication. For example, when one variable increases, the other variable also escalates proportionally. Accordingly, it is important for students to have the ability to identify the pattern of multiplicative relationships, describe them in the form of equations or comparisons, and apply them in different situations. This study describes the strategies used by students in recognizing multiplicative relationships, particularly in solving mathematical literacy problems containing proportional situations. Study participants and methods. The research was conducted in three junior high schools located in Malang, Indonesia, involving 191 ninth-grade students. They were asked to work on a mathematical literacy question, and then their answer sheets were corrected and grouped based on the developmental stage of proportional reasoning, particularly in recognizing multiplicative relationships. Furthermore, the subjects were interviewed in-depth concerning their experience in solving literacy problems in proportional situations. This study used a qualitative approach with a phenomenological research type. the subject's experience was investigated holistically, along with the appearing phenomenon. The garnered data were interpreted through continuous reflection and analysis for a deeper understanding. The results were then summarized. Results. In this study, two variations of strategies have been identified being used by students at the stage of recognizing multiplicative relationships in solving mathematical literacy problems, namely the multiple strategies and the pattern strategy. This finding serves as a valuable contribution to understanding students' strategies and behaviors in recognizing multiplicative relationships, which has not been revealed in previous studies. The main difference between these two strategy variations lies in the approach used in solving the problem. The multiples strategy emphasizes the conceptual linking of quantity values between objects, relying on the conceptual shifts that transpire as students navigate through their additive reasoning steps within the framework of multiplication. In this case, students need to comprehend various number concepts and number relationships, with frequent focus on multiplication as a form of repeated addition. On the other hand, pattern strategies rely on students' ability to match patterns, use the arrangement of numbers constituting the pattern, and relate them to other patterns in solving problems. Practical significance. The results of this study serve as a crucial reference for more effective and efficient mathematics learning formulation for improving students' proportional reasoning.

Liquid-Liquid Crossover in Water Model: Local Structure vs Kinetics of Hydrogen Bonds.

In equilibrium and supercooled liquids, polymorphism is manifested by thermodynamic regions defined in the phase diagram, which are predominantly of different short- and medium-range order (local structure). It is found that on the phase diagram of the water model, the thermodynamic region corresponding to the equilibrium liquid phase is divided by a line of the smooth liquid-liquid crossover. In the case of the water model TIP4P/2005, this crossover is revealed by various local order parameters and corresponds to pressures on the order of 3150 ± 350 atm at ambient temperature. In the vicinity of the crossover, the dynamics of water molecules change significantly, which is reflected, in particular, in the fact that the self-diffusion coefficient reaches its maximum values. In addition, changes in the structure also manifest themselves in changes in the kinetics of hydrogen bonding, which are captured by values of such quantities as the average lifetime of hydrogen bonding, the average lifetimes of different local coordination numbers, and the frequencies of changes in different local coordination numbers. An interpretation of the hydrogen bond kinetics in terms of the free energy landscape concept in the space of possible coordination numbers is proposed.

CT-derived Epicardial Adipose Tissue Inflammation Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement.

Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR). Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed. The amount and density of EAT and PAT were quantified from single-slice CT images at the level of the aortic valve. Using established risk scores and known independent risk factors, a clinical benchmark model (BMI, Chronic kidney disease stage, EuroSCORE 2, STS Prom, year of intervention) for outcome prediction (2-year mortality) after TAVR was established. Subsequently, we tested whether the additional inclusion of area and density values of EAT and PAT in the clinical benchmark model improved prediction. For this purpose, the cohort was divided into a training (n=798) and a test cohort (n=399). Within the 2-year follow-up, 264 patients died. In the training cohort, particularly the addition of EAT density to the clinical benchmark model showed a significant association with outcome (hazard ratio 1.04, 95% CI: 1.01-1.07; P =0.013). In the test cohort, the outcome prediction of the clinical benchmark model was also significantly improved with the inclusion of EAT density (c-statistic: 0.589 vs. 0.628; P =0.026). EAT density as a surrogate marker of EAT inflammation was associated with 2-year mortality after TAVR and may improve outcome prediction independent of established risk parameters.

Simple calculation of the Moon apsides motion

AbstractA simple and clear method to calculate the averaged motion of the apsis line in the Moon orbit is proposed. The obtained result is for the starry period of the Moon revolution around the Earth or per year. The modern observed value of the latter quantity is per year. In “Principia” Newton derived for the Moon month and per year, that is approximately two times less than the observed values. Contrary to the Newton approach, we use a simple and obvious averaging of the Sun disturbing force for the starry period of the Moon revolution around the Earth. The applicability of the obtained formulae to satellites of other planets and to the planets themselves is argued. Comparing Newton's calculation with our method, we reveal the reason, rather convincing, that brought Newton to an imprecise result.

Optimization and improving of the production capacity of a flexible tyre painting cell

AbstractOptimization of industrial processes is a constant concern and a main task for many companies in several industry sectors. Based on optimized solutions, the company can decrease manufacturing costs, lead times or, more generally, increase benefit. However, when developing a new process, you must be sure that the new solution will add more value to the initial solution. This, among many others, is one of the main reasons why companies opt, in addition to experimentation, for the use of tools that allow for the virtual prototyping, simulation, and integration of complex and sophisticated processes. Experimentation requires approximation testing, searching for the ideal values of quantity, temperature, etc.; simulation provides industrial processes with test support ranging from flows to robotic systems such as the intelligent software. This simulation software allows to develop programs, add Computer Aided Design (CAD) layouts, and simulate the cycle times of the different tasks to be performed. In this paper, an experimental approach is presented with atomization and fan spray pressure as the study basis and a simulation of the robot-based handling solution used in a tyre production line. The result is an improvement of the painting process, optimisation of the amount of fluid deposited on the tyre, of the processed product, as well as of the running times of the robot.

Smartphone-integrated colorimetric sensor for rapid and highly selective detection of spermine in food based on the laccase-mimicking activity of flower-shaped Mn3O4 nanoparticles

Colorimetric methods have the benefits of rapid detection and easy operation in the detection of spermine (SPM). However, the existing colorimetric sensor for detecting SPM still face challenges in terms of performance stability, result reliability and safety of sensing materials. Herein, it was first found that flower-like Mn3O4 nanoparticles (Mnf) exhibit excellent laccase-mimicking activity. Since SPM can effectively inhibit this activity, a colorimetric sensor was developed to detect SPM in food. The addition of positive charged SPM will induce the aggregation of multiple Mnf with negative charge through electrostatic interactions. In this case, the specific surface area of Mnf is reduced, and some surface-active sites are occupied by SPM, leading to a decrease in the laccase-mimicking activity of Mnf. Consequently, the colorimetric sensor appears light pink. Furthermore, a smartphone was utilized to convert the color of the reaction solution into the corresponding G/B value, facilitating on-site and fast analysis of SPM quantity. The proposed colorimetric sensor exhibits outstanding sensitivity and selectivity, with a limit of detection (LOD) as low as 0.094 μg·mL−1. The colorimetric sensor also features stable performance, reliable results and environmentally friendly safety, all of which will provide strong support for the monitoring of SPM in the food industry.

Robots and Employment: Evidence from Japan, 1978–2017

We study the impacts of industrial robots on employment in Japan, the country with the longest tradition of robot adoption. We employ a novel data set of robot shipments by destination industry and robot application (specified task) in quantity and unit values. These features allow us to use an identification strategy leveraging the heterogeneous application of robots across industries and heterogeneous price changes across applications. For example, the price drop of the welding robot relative to the assembling robot induced faster adoption of robots in the automobile industry that intensively uses welding processes than in the electric machine industry that intensively uses assembling processes. Our industrial-level and commuting zone-level analyses both indicate that the decline of robot prices increased the number of robots as well as employment, suggesting that robots and labor are gross complementary in the production process. We compare our estimates with those reported by existing studies and propose a mechanism that explains apparent differences between the results.

Multidimensional Multi-Connected Fuzzy Interval-Logic Controller

The key features and the principle of operation of a multidimensional fuzzy interval-logic controller with interconnected adjustable parameters developed by the authors are considered. The scheme of interpretation of continuous physical quantities by an equivalent set of terms and the basic version of the block diagram of the regulator are presented. The main elements of the logical output block are described, including the block of production rules, which includes a predefined database of values of control actions on control objects in the form of ordinal numbers of terms of output continuous quantities. The advantages and features of setting up the mutual connections between the input and output continuous values of the regulator are considered, which is expressed in determining the functional dependencies between them. The set of parameters possessed by the terms of input continuous quantities in relation to specific output continuous quantities of the regulator is described. The methods of defuzzification of the values of output continuous quantities within the boundaries of their terms are shown. The possibility of combining input and output continuous quantities into groups when setting up mutual connections between them is described. The mechanism of determining groups of interrelated continuous quantities is illustrated, the total number of which is determined by forming a matrix of relationships, according to the author’s scheme. The algorithm of sequential processing of the contents of the cells of the matrix of relationships, consisting of three steps, is considered. Expressions are given for calculating the basic parameters of a multidimensional fuzzy interval-logic controller with interrelated adjustable parameters. The results of a computational experiment to reduce the system of production rules of the regulator in determining the relationships between input and output continuous quantities are presented.

A reformulation of Fisher's runaway identifies the heritability of mate choices as a key parameter and highlights limitations of the hypothesis.

Fisher proposed that female preference for mates with extreme traits could evolve as an essentially arbitrary outcome of a self-reinforcing process. Although Fisher's runaway has been shown to be a theoretical possibility, it is not clear whether it occurs in real populations, in part because existing models express the necessary conditions in terms of parameters that would be nearly impossible to estimate in the wild. Here, I reformulate models of the runaway in terms of two estimable parameters, the heritability and phenotypic variance of realized mate choices. Higher values of both quantities make the runaway more likely. In the most realistic model considered, in which mate choices are based on a mixture of absolute and relative criteria, a runaway cannot occur unless mate choice increases the variance of the male trait, which seems incompatible with the strong directional mating preferences typically observed in polygynous species. Even in the most favourable case for the runaway, purely relative preference without direct selection on preference, a substantial heritability of realized mate choices would be required if there is moderately strong stabilizing selection on the male trait. These results cast some doubt on whether the runaway is a plausible outcome in natural populations.

White-box validation of quantitative product lines by statistical model checking and process mining

We propose a novel methodology to validate software product line (PL) models by integrating Statistical Model Checking (SMC) with Process Mining (PM). We consider the feature-oriented language QFLan from the PL engineering domain. QFLan allows to model PL equipped with rich cross-tree and quantitative constraints, as well as aspects of dynamic PLs such as the staged configurations. This richness allows us to easily obtain models with infinite state-space, calling for simulation-based analysis techniques, like SMC. For example, we use a running example with infinite state space. SMC is a family of analysis techniques based on the generation of samples of the dynamics of a system. SMC aims at estimating properties of a system like the probability of a given event (e.g., installing a feature), or the expected value of quantities in it (e.g., the average price of products from the studied family). Instead, PM is a family of data-driven techniques that uses logs collected on the execution of an information system to identify and reason about its underlying execution process. This often regards identifying and reasoning about process patterns, bottlenecks, and possibilities for improvement. In this paper, to the best of our knowledge, we propose, for the first time, the application of Process Mining (PM) techniques to the byproducts of Statistical Model Checking (SMC) simulations. This aims to enhance the utility of SMC analyses. Typically, if SMC gives unexpected results, the modeler has to discover whether these come from actual characteristics of the system, or from bugs in the model. This is done in a black-box manner, only based on the obtained numerical values. We improve on this by using PM to get a white-box perspective on the dynamics of the system observed by SMC. Roughly speaking, we feed the samples generated by SMC to PM tools, obtaining a compact graphical representation of the observed dynamics. This mined PM model is then transformed into a mined QFLan model, making it accessible to PL engineers. Using two well-known PL models, we show that our methodology is effective (helps in pinpointing issues in models, and in suggesting fixes), and that it scales to complex models. We also show that it is general, by applying it to the security domain.

Calculation of the detection limits with the least-squares method in gamma-ray spectrometry: A simple procedure

A metrologically consistent procedure for assessing the detection limits of activity measurements for gamma-ray emitters with high-resolution spectrometers using the LSQ method is described and tested. As the input to the assessment, besides the measured contents of the spectral channels, the results of the peak analysis, i.e., the indication and its uncertainty, are used. The unfolding of the spectral region of interest into its components corresponding to the peak representing the indication and its background allows us to take into account the uncertainty budget, describing the uncertainty of the indication and the shape of the corresponding peak, making possible to include these sources of uncertainty in the calculation of the decision threshold. To assess the detection limit, the variance of the indication is calculated as a function of the indication itself, while considering the relative uncertainty of the conversion factor. The variance of the indication observed is approximated by a polynomial of the second order of the indication, thus making it possible to calculate the detection limit analytically. The method was tested on measured spectra using the empirically determined spectral shape of the peak representing the indication. It was shown how the empirically determined shape of an isolated and expressive peak close to the peak representing the indication can be used in the calculation of the decision threshold and how the presence of a peak overlapping with the peak representing the indication affects the decision threshold and the detection limit. It is explained that besides the counting statistics, the sources of uncertainty due to the shape of the peak representing indication also contribute to the decision threshold. However, to the increase of the detection limit over the decision threshold, besides the counting statistic, only the uncertainty of the conversion factor contributes. It is shown that in the presence of the indication, the decision threshold and the detection limit can be used to quantify the comparison between the observed value and the true value of the measurand with a predetermined quantity value in terms of the probabilities of making errors of the first and second kind. The application of the decision thresholds and detection limits to a conformity assessment is proposed.

ANALYSIS OF FLUID-FLOW CHARACTERISTICS AND HEAT-TRANSFER PATTERNS AROUND A SQUARE BLUFF BODY

In this study, we investigate a numerical simulation of the flow and heat transfer characteristics around a single square cylinder subjected to incidence in a two-dimensional plane. The Reynolds and Prandtl numbers are set at <i>Re</i> = 100 and <i>Pr</i> = 0.71, respectively. The cylinder's surface is subjected to pressure and viscous forces due to the passing flow, with the magnitude of these forces influenced by the cross-sectional shape of the bluff body, the angle of attack, and flow velocity. The angle of orientation for the square cylinder varies from 0° to 45° in 5° increments. The study begins with comprehensively examining the governing equations, simulation procedures, and grid generation, employing an efficient and robust in-house finite volume code. Subsequently, we present and discuss the instantaneous streamlines, velocity components, vorticity, and isotherm patterns for different angles of attack. Additionally, global quantities such as viscous, pressure, total lift, drag coefficients, their root-mean-square, Strouhal, and Nusselt numbers are analyzed for various angles of attack. It is observed that the frequency of vortex shedding decreases with an increasing angle of attack. Furthermore, the values of global quantities and flow and temperature patterns remain relatively constant for angles of attack in the range of θ = 30°-45°. The numerical results show good agreement with experimental and numerical data in the existing literature.

Advanced Information-Measuring System for the Improvement of the Quality Indicators of Metrological Characteristics

Combined test algorithms have been developed that increase the accuracy of measurements using simple additive and multiplicative tests, which allows us to determine the measured values of non-electrical quantities from the results of additional test measurements used to identify non-linear functions for converting the measurement of system information.

Identification of Hammerstein-Wiener models using Hamiltonian Monte Carlo

This paper develops and illustrates a process for the Identification of Hammer-stein–Wiener model structures using Hamiltonian Monte Carlo. A central aspect is that a very general situation is considered wherein multi-variable data, non-invertible Hammerstein and Wiener nonlinearities, and Gaussian stochastic disturbances both before and after the Wiener non-linearity are all catered for. The posterior distribution of the parameters is directly sampled from and these samples can then be used to quantify the uncertainty of the system model estimates, and to calculate expected values of various quantities.

Non-Negative Universal Differential Equations With Applications in Systems Biology

Universal differential equations (UDEs) leverage the respective advantages of mechanistic models and artificial neural networks and combine them into one dynamic model. However, these hybrid models can suffer from unrealistic solutions, such as negative values for biochemical quantities. We present non-negative UDE (nUDEs), a constrained UDE variant that guarantees non-negative values. Furthermore, we explore regularisation techniques to improve generalisation and interpretability of UDEs.