Correction of Temperature Variation with Independent Water Samples to Predict Soluble Solids Content of Kiwifruit Juice Using NIR Spectroscopy

Using the framework of aquaphotomics, we have sought to understand the changes within the water structure of kiwifruit juice occurring with changes in temperature. The study focuses on the first (1300–1600 nm) and second (870–1100 nm) overtone regions of the OH stretch of water and examines temperature differences between 20, 25, and 30 °C. Spectral data were collected using a Fourier transform–near-infrared spectrometer with 1 mm and 10 mm transmission cells for measurements in the first and second overtone region, respectively. Water wavelengths affected by temperature variation were identified. Aquagrams (water spectral patterns) highlight slightly different responses in the first and second overtone regions. The influence of increasing temperature on the peak absorbance of the juice was largely a lateral wavelength shift in the first overtone region and a vertical amplitude shift in the second overtone region of water. With the same data set, we investigated the use of external parameter orthogonalisation (EPO) and extended multiple scatter correction (EMSC) pre-processing to assist in building temperature-independent partial least square regression models for predicting soluble solids concentration (SSC) of kiwifruit juice. The interference component selected for correction was the first principal component loading measured using pure water samples taken at the same three temperatures (20, 25, and 30 °C). The results show that the EMSC method reduced SSC prediction bias from 0.77 to 0.1 °Brix in the first overtone region of water. Using the EPO method significantly reduced the prediction bias from 0.51 to 0.04 °Brix, when applying a model made at one temperature (30 °C) to measurements made at another temperature (20 °C) in the second overtone region of water.

A progressive online external parameter calibration and initialization method for stereo-IMU system

Purpose This paper aims to present a pipeline to progressively deal with the online external parameter calibration and estimator initialization of the Stereo-inertial measurement unit (IMU) system, which does not require any prior information and is suitable for system initialization in a variety of environments. Design/methodology/approach Before calibration and initialization, a modified stereo tracking method is adopted to obtain a motion pose, which provides prerequisites for the next three steps. Firstly, the authors align the pose obtained with the IMU measurements and linearly calculate the rough external parameters and gravity vector to provide initial values for the next optimization. Secondly, the authors fix the pose obtained by the vision and restore the external and inertial parameters of the system by optimizing the pre-integration of the IMU. Thirdly, the result of the previous step is used to perform visual-inertial joint optimization to further refine the external and inertial parameters. Findings The results of public data set experiments and actual experiments show that this method has better accuracy and robustness compared with the state of-the-art. Originality/value This method improves the accuracy of external parameters calibration and initialization and prevents the system from falling into a local minimum. Different from the traditional method of solving inertial navigation parameters separately, in this paper, all inertial navigation parameters are solved at one time, and the results of the previous step are used as the seed for the next optimization, and gradually solve the external inertial navigation parameters from coarse to fine, which avoids falling into a local minimum, reduces the number of iterations during optimization and improves the efficiency of the system.

Power-optimal, stabilized entangling gate between trapped-ion qubits

To achieve scalable quantum computing, improving entangling-gate fidelity and its implementation efficiency are of utmost importance. We present here a linear method to construct provably power-optimal entangling gates on an arbitrary pair of qubits on a trapped-ion quantum computer. This method leverages simultaneous modulation of amplitude, frequency, and phase of the beams that illuminate the ions and, unlike the state of the art, does not require any search in the parameter space. The linear method is extensible, enabling stabilization against external parameter fluctuations to an arbitrary order at a cost linear in the order. We implement and demonstrate the power-optimal, stabilized gate on a trapped-ion quantum computer.

Thermodynamic analysis for Non-linear system (Van-der-Waals EOS) with viscous cosmology

The following paper is motivated by the recent works of Kremer [Gen Relativ Gravit 36(6):1423–1432, 2004; Phys Rev D 68(12):123507, 2003], Vardiashvili (Inflationary constraints on the van Der Waals equation of state, arXiv:1701.00748, 2017), Jantsch (Int J Mod Phys D 25(03):1650031, 2016), Capozziello (Phys Lett A 299(5–6):494–498, 2002) on Van-Der-Waals EOS cosmology. The main aim of this paper is to analyze the thermodynamics of a Non-linear system which in this case is Van-Der-Waals fluid EOS (Capozziello et al., Quintessence without scalar fields, arXiv:astro-ph/0303041, 2003). We have investigated the Van-Der-Waals fluid system with the generalized EOS as $$p=w\left( \rho ,t \right) \rho +f\left( \rho \right) -3\eta \left( H,t \right) H$$ p = w ρ , t ρ + f ρ - 3 η H , t H (Brevik et al., Int J Geom Methods Mod Phys 15(09):1850150, 2018). The third term signifies viscosity which has been considered as an external parameter that only modifies pressure but not the density of the liquid. The $$w(\rho ,t)$$ w ( ρ , t ) and $$f(\rho )$$ f ( ρ ) are the two functions of energy density and time that are different for the 3 types of Vander Waal models namely one parameter model, two parameters model and three parameters model (Ivanov and Prodanov, Eur Phys J C 79(2):118, 2019; Elizalde and Khurshudyan, Int J Mod Phys D 27(04):1850037, 2018). The value of EOS parameter ($$w_{EOS})$$ w EOS ) (Capozziello et al., Quintessence without scalar fields, arXiv:astro-ph/0303041, 2003; Obukhov and Timoshkin, Russ Phys J 60(10):1705–1711, 2018) will showdifferent values for different models. We have studied the changes in the parameters for different cosmic phases [Kremer, Phys Rev D 68(12):123507, 2003; Capozziello et al., Phys Lett A 299(5–6):494–498, 2002; Capozziello et al., Quintessence without scalar fields, arXiv:astro-ph/0303041, 2003]. We have also studied the thermodynamics and the stability conditions for the three models in viscous condition [Obukhov and Timoshkin, Russ Phys J 60(10):1705–1711, 2018; Panigrahi and Chatterjee, Gen Relativ Gravit 49(3):35, 2017; Panigrahi and Chatterjee, J Cosmol Astropart Phys 2016(05):052, 2016; Chakraborty et al., Evolution of FRW Universe in Variable Modified Chaplygin Gas Model, arXiv:1906.12185, 2019]. We have discussed the importance of viscosity (Brevik and Grøn, Astrophys Space Sci 347(2):399–404, 2013) in explaining accelerating universe with negative pressure (Panigrahi and Chatterjee, Gen Relativ Gravit 49(3):35, 2017).Finally, we have resolved the finite time future singularity problems [Brevik et al., The effect of thermal radiation on singularities in the Dark Universe, arXiv:2103.08430, 2021; Odintsov and Oikonomou, Phys Rev D 98(2):024013, 2018; Odintsov and Oikonomou, Int J Mod Phys D 26(08):1750085, 2017; Frampton et al., Phys Rev D 85(8):083001, 2012; Frampton et al., Phys Lett B 708(1–2):204–211, 2012; Frampton et al., Phys Rev D 84(6):063003, 2011] and discussed the thermodynamics energy conditions [Visser and Barcelo, Energy conditions and their cosmological implications. In: Cosmo-99, pp 98–112, 2000; Chattopadhyay et al., Eur Phys J C 74(9):1–13, 2014; Arora et al., Phys. Dark Universe 31:100790, 2021; Sharma and Pradhan, Int J Geom Methods Mod Phys 15(01):1850014, 2018; Sahoo et al., AstronomischeNachrichten 342(1–2):89–95, 2021; Yadav et al., Mod Phys Lett A 34(19):1950145, 2019; Sharma et al., Int J Geom Methods Mod Phys 17(07):2050111, 2020, Moraes and Sahoo, Eur Phys J C 77(7):1–8, 2017; Hulke et al., New Astron 77:101357, 2020; Singla et al., Gravit Cosmol 26(2):144–152, 2020; Sharif et al., Eur Phys J Plus 128(10):1–11, 2013] with those models.

A Discrete Formulation of Two Alternative Forced Choice Decision Dynamics Derived from a Double-Well Quantum Landscape

Tools from quantum theory have been effectively leveraged in modeling otherwise poorly understood effects in decision-making such as apparent fallacies in probability judgments and context effects. This approach has described the dynamics of two alternative forced choice (2AFC) decisions in terms of the path of a single quantum particle evolving in a single potential well. Here, we present a variant on that approach, which we name the Multi-Particle and Multi-Well (MPMW) quantum cognitive framework, in which decisions among N alternatives are treated by the sum of positional measurements of many independent quantum particles representing stimulus information, acted on by an N-well landscape that defines the decision alternatives. In this article, we apply the MPMW model to the simplest and most common case of N-alternative decision making, 2AFC dynamics. This application calls for a multi-particle double-well implementation, which allows us to construct a simple, analytically tractable discrete drift diffusion model (DDM), in the form of a Markov chain, wherein the parameters of the attractor wells reflect bottom-up (automatic) and top-down (control-dependent) influences on the integration of external information. We first analyze this Markov chain in its simplest form, as a single integrator with a generative process arising from a static quantum landscape and fixed thresholds, and then consider the case of multi-integrator processing under the same conditions. Within this system, stochasticity arises directly from the double-well quantum attractor landscape as a function of the dimensions of its wells, rather than as an external parameter requiring independent fitting. The simplicity of the Markov chain component of this model allows for easy analytical computation of closed forms for response time distributions and response probabilities that match qualitative properties of the accuracies and reaction times of humans performing 2AFC tasks. The MPMW framework produces response time distributions following inverse gaussian curves familiar from previous DDM models and empirical data, including the common observation that mean response times are faster for incorrect than for correct responses. The work presented in this paper serves as a proof of concept, based on which the MPMW framework can be extended to address more complex decision-making processes, (e.g., N-alternative forced choice, dynamic control allocation, and nesting quantum landscapes to allow for modeling at both the task and stimulus levels of processing) that we discuss as future directions.

Optimization Method of Integrated Light-Screen Array with External Parameters Based on Genetic Algorithm

Due to the high sensitivity and fast response, the light-screen array measurement principle is suitable for the dynamic parameter measurement of small and fast targets including projectile. Since the spatial structures of the light-screen array determine the measurement accuracy, internal parameters such as the angles between the light-screens are usually calibrated and then directly used in the field. However, the effect of the measuring state is ignored in the test field. This paper takes the integrated light-screen array sky vertical target as the research object, and two rotation angles are introduced as external parameters to describe the deviation between the calibration state and measuring state of the target, so as to optimize the measurement model. Aiming at the problem that the external parameters cannot be measured directly, an external parameter inversion method of machine learning based on a genetic algorithm is designed under a complex engineering model. The deviation between the projectile hole and the light-screen array measurement coordinates is used to build an inversion database for the genetic algorithm during the machine learning process. The simulation and the live firing test show that the optimization method and parameter identification algorithm in this paper can optimize the measurement model and improve the measurement accuracy of the light-screen array principle directly and can also provide a reference for the optimization and parameter identification in other engineering problems.

CASE STUDY: DESIGN VALUE MEASURING BY SYSTEM DYNAMICS

The aim of the article is to show a way to measure the economic value of design using system dynamic modeling of key processes in an organization. The article fully accepts the complexity of the concept of design and opens up the possibility for employing system dynamics in design value measuring. The definition of design is given as an integral concept for which it is difficult to find a benchmark. The sequential explanatory method was chosen to solve the research problem. Qualitative data is collected first and it is recorded and examined. After that the data is transformed into numeric values and taken for quantitative evaluation in a system dynamic model. The connection of qualitative research data in a tool for quantitative evaluation allows an original interpretation of relationships that have been obtained and are collected only as qualitative data. Qualitative data collection is based on the visualization of a new definition of design: Design is an integration of functional, distribution, emotional and social experience of the customer. The questionnaire is in the form of Design Value Canvas and is used to determine the initial Design Value Algorithm (DVA) coefficient. As an external parameter, the DVA coefficient influences the development of the number of customers and their willingness to order the company’s products in the system dynamic model. The main result is the finding that an investment in design, which is confronted with customer preferences, fundamentally changes the economic parameters of business. Economic benefits of a design change in a company are always influenced by a strategic decision made by the entrepreneur who has to know the behaviour of their customers and to correctly choose the field of design in which it pays to invest.

Empirical evidence for a jamming transition in urban traffic

Understanding the mechanisms leading to the formation and the propagation of traffic jams in large cities is of crucial importance for urban planning and traffic management. Many studies have already considered the emergence of traffic jams from the point of view of phase transitions, but mostly in simple geometries such as highways for example or in the framework of percolation where an external parameter is driving the transition. More generally, empirical evidence and characterization for a congestion transition in complex road networks are scarce, and here, we use traffic measures for Paris (France) during the period 2014–2018 for testing the existence of a jamming transition at the urban level. In particular, we show that the correlation function of delays due to congestion is a power law (with exponent η ≈ 0.4) combined with an exponential cut-off ξ . This correlation length is shown to diverge during rush hours, pointing to a jamming transition in urban traffic. We also discuss the spatial structure of congestion and identify a core of congested links that participate in most traffic jams and whose structure is specific during rush hours. Finally, we show that the spatial structure of congestion is consistent with a reaction–diffusion picture proposed previously.