Value Of Function Research Articles

An anageometric time scale calculus and its some basic applications

Anageometric calculus is a branch of non-Newtonian calculus introduced by M. Grossman and R. Katz in 1967, in which changes in functional values are measured by linear differences, but arguments are measured by ratios. The theory of time scales was initiated by S. Hilger in 1988 to unify continuous and discrete analysis. In this article, we introduce anageometric time scale calculus to discuss dynamic equations in which the values of the independent variables show nonlinear behaviour. This newly introduced calculus will be more applicable than other calculi in atomic reactors, growth models, etc. We shall discuss some applications of anageometric time scale calculus on the geometric real field R(G) with its optimality and better accuracy.

Pressure-dependent band gap engineering with structural, electronic, mechanical, optical, and thermal properties of CsPbBr3: first-principles calculations.

In the renewable industry, pressure-dependent CsPbBr3 perovskite has a lot of potential due to its exceptional properties. Present work revealed the mechanical stability of CsPbBr3 between 0 to 50GPa. The bandgap of unstressed CsPbBr3 is 2.90eV, indicating a direct bandgap. Band gap values decrease by increasing external pressure. CsPbBr3 structure showed a direct band gap from 0 to 35GPa and in-direct from 40 to 50GPa. The unit cell volume and lattice constants are substantially decreased. Mechanical parameters, i.e., Young's modulus, bulk modulus, anisotropy factor, shear modulus, and poison's ratio are obtained. Under ambient conditions, the mechanical properties of CsPbBr3 showed ductile behavior and with induced pressure, their ductility has significantly improved. By applying stresses ranging from 0 to 50GPa, the considerable fluctuation in values of dielectric function (imaginary and real), absorption, reflectivity, loss function, refractive index (imaginary and real), and conductivity (imaginary and real), was also identified. When pressure rises, the optical parameters increase and drag in the direction of high energies. Response functions are used to predict the density of states and the phonon lattice dispersion to study the phonon properties. By using the quasi-harmonic Debye model, the thermal effect on the free energy, entropy, enthalpy, and heat capacity were predicted and compared. These results would be useful for theoretical research and indicate how external pressure significantly affects the physical characteristics of CsPbBr3 perovskites, which may open up new possibilities for use in optoelectronic, photonic, and solar cell applications. The structural, electrical, mechanical, optical, and thermal properties of cesium lead bromide (CsPbBr3) are investigated by applying external pressure from 0 to 50GPa, using generalized gradient approximations (GGA) and Perdew-Burke-Ernzerhof (PBE) with CASTEP code built-in material studio by density functional theory (DFT).

Dynamical analysis and event-triggered adaptive finite-time prescribed performance control of the FO coupled MEMS resonators

This paper explores the dynamic behaviors and control method of weakly coupled micro-electro-mechanical system (MEMS) resonators with fractional-order (FO) dynamics. In the dynamics analysis session, Lyapunov exponents, bifurcation theory, and phase diagrams are used to analyze the effects of system parameters, coupling stiffness, and FO on the complex dynamical behaviors such as periodicity, pseudo-periodicity, and chaos oscillations. To suppress chaotic oscillations, a dynamic event-triggered finite-time prescribed performance controller is proposed. The unknown nonlinear functions are approximated through the interval type-3 fuzzy system (IT3FS) with an adaptive law. A novel finite-time prescribed performance function (finite-time PPF) is constructed to establish constrained boundaries for tracking errors. Compared with the existing PPFs, the proposed approach allows for more flexible setting of the convergence boundary before reaching steady-state. Subsequently, the constrained tracking errors are mapped to an unconstrained form using a nonlinear transformation function, whether the error constraint is symmetric or asymmetric. To circumvent the “explosion of complexity” arising from backstepping design process, a tracking differentiator (TD) is utilized. Additionally, to alleviate strain on communication resources, an event-triggered mechanism is devised to update control signals. The trigger threshold of the control signals can be adaptively adjusted based on the values of the Lyapunov function and the dynamic auxiliary variables. This control method guarantees finite-time convergence for all signals of the system. Finally, extensive simulations are performed to verify the effectiveness of the proposed algorithm.

Methods for measuring career readiness of high school students: based on multidimensional item response theory and text mining

In contemporary society, career readiness holds paramount significance for individual life, exerting a direct influence on initial employment, job satisfaction, and the sense of career identity. Framed within multidimensional item response theory and text mining, this study embarks on exploring assessment methodologies for high school students’ career readiness by revising the “Career Readiness Questionnaire – Adolescent Version” and employing text mining techniques. Study One collected 1261 valid data points through cluster sampling. With the aid of Bayesian multivariate item response theory parameter estimation procedures and R language, the career readiness measurement tool was revised, yielding a concise scale that aligns with psychometric requirements. The research findings indicated that the concept of “career readiness” is more suitable for the multidimensional graded response model than for the bifactor model. The dataset’s discrimination parameters fell within the range of [1.59, 3.84], the difficulty parameters fell between [−2.91, 2.24], and the peak values of the maximum information functions fell within [0.24, 2.35]. After six items with the lowest peaks were removed (Items 4, 5, 6, 31, 32, and 33), the remaining 30 items composed the Chinese concise version “Career Readiness Questionnaire – Adolescent Version,” with discrimination parameters ranging from [1.45, 3.38], difficulty parameters between [−3.31, 1.76], and maximum information function peaks within [0.50, 2.64]. Building upon the effective participants from Study One, Study Two matched questionnaire data with textual information, resulting in 1012 valid participants. Leveraging text mining, a machine learning model was constructed to predict high school students’ career readiness based on essay texts. The results of Study 2 prove that the revised lexicon was more accurate in feature extraction. Building upon this, the machine learning model for essay text demonstrated excellent performance in predicting career readiness, with random forest outperforming the other algorithms. This study provides a novel approach for schools and parents to comprehend the state of career readiness among high school students, offering a convenient and effective tool for educational activities related to students’ career development.

A new Fermatean fuzzy multi‐objective indefinite quadratic transportation problem with an application to sustainable transportation

AbstractIn this work, a Fermatean fuzzy (FF) multi‐objective indefinite quadratic transportation problem (TP) is introduced. Due to some unavoidable reasons, real‐life transportation parameters such as supply, demand and costs are indeterminate in nature and cannot be expressed in crisp terms. We represent these parameters using FF numbers, an extension of fuzzy numbers, which are capable of representing indeterminacy efficiently. A multi‐objective indefinite quadratic TP where each objective is a product of two linear factors (cost functions) is considered. Defuzzification of FF numbers is accomplished by the introduction of ‐cut for the first time. The obtained crisp TP is solved using the intuitionistic fuzzy programming approach and FF programming approach to arrive at a compromise solution. To substantiate the work, solution methodology based on defuzzification using the ranking function is also deliberated. The applicability of the model is demonstrated through a sustainable TP, which simultaneously minimizes transportation cost with depreciation cost and packaging cost with wastage cost. The resulting value of the objective functions and the aspiration levels are compared to depict the efficacy of the proposed method over the ranking function method. The concluding section summarizes the work, and future avenues along with some limitations of the work are also specified.

Atmospheric Turbulence Phase Reconstruction via Deep Learning Wavefront Sensing.

The fast and accurate reconstruction of the turbulence phase is crucial for compensating atmospheric disturbances in free-space coherent optical communication. Traditional methods suffer from slow convergence and inadequate phase reconstruction accuracy. This paper introduces a deep learning-based approach for atmospheric turbulence phase reconstruction, utilizing light intensity images affected by turbulence as the basis for feature extraction. The method employs extensive light intensity-phase samples across varying turbulence intensities for training, enabling phase reconstruction from light intensity images. The trained U-Net model reconstructs phases for strong, medium, and weak turbulence with an average processing time of 0.14 s. Simulation outcomes indicate an average loss function value of 0.00027 post-convergence, with a mean squared error of 0.0003 for individual turbulence reconstructions. Experimental validation yields a mean square error of 0.0007 for single turbulence reconstruction. The proposed method demonstrates rapid convergence, robust performance, and strong generalization, offering a novel solution for atmospheric disturbance correction in free-space coherent optical communication.

Optical functions of uniaxial rutile and anatase (TiO2) revisited

The optical functions of uniaxial rutile and anatase (TiO2) were determined from 200 to 850 nm (6.2 to 1.46 eV) using several of four optical techniques: (1) standard spectroscopic two-modulator generalized ellipsometry (2-MGE), (2) near-normal-incidence two-modulator generalized ellipsometry microscopy (2-MGEM), (3) Mueller matrix transmission of rutile, and (4) polarized transmission of rutile. The 2-MGE measurements yielded highly accurate values of the dielectric functions and error estimates from 1.46 to 6.2 eV, whereas the polarization-dependent transmission yielded more accurate values of the absorption coefficient below the band edge of rutile. The 2-MGEM also measured the diattenuation, which is related to the birefringence, and other parameters but at near-normal incidence at a single wavelength (577 nm).

N1 and LNC reveal the differential electrophysiological signatures of functional and hedonic images processing

In the process of creative sentence or phrase utilization, novel and appropriate evaluations cause the different brain responses observed in event-related potentials: the N400 reflects the novelty evaluation, whereas a late negative component marks appropriate processing. Do we have similar brain reactions in image perception when we rapidly browse pictures of objects with different novelty, functional/appropriate, and hedonic value? To explore this question, participants were presented with four novel object images with high or low functional and hedonic properties, as well as the ordinary product images, with the instruction to attentively observe and understand each image. We found a clear dissociation between processing of novelty and functional value: novelty objects produced negative deflections in the N2–N400 time window relative to the ordinary object images, whereas images with high functional value elicited a larger N2 and late negative waves (LNC) resembling the late component found for the appropriate phrases. Object images with high hedonic value, however, were associated with earlier aesthetic preference reflected in smaller N1 amplitudes, but failed to elicit a LNC effect. We therefore conclude that the processing of novelty, functional, and hedonic value are dissociation, and the perception of hedonic value is earlier (N1) than the novelty processing (N400) and the verification of functional value (LNC).

Brand Image and Consumer Perceived Values on Purchase Intention of Organic Food: A Conceptual Study

Organic food is quickly developing in China as consumer wealth and consumption levels have grown in recent years; the Chinese government's "Healthy China Action (2019-2030)" promotes a balanced diet and works to raise the standard of agricultural output and food safety. Even though China has Asia's largest organic food market, organic food has a small market share and low consumer expenditure. As a result, decisive steps to boost the growth of China's organic food market are urgently needed. This study aims to explore the factors related to Chinese people’s purchase intention of organic food using the S-O-R model. Brand image and consumer perceived values are crucial because they influence customer purchase behavior. This study emphasizes brand image, perceived functional, emotional and social values on consumer purchase intention. Epistemic value and conditional value were excluded because they have detrimental impacts on consumer choice behavior. The contribution of this study is to enrich the existing literature by providing a deeper understanding of organic food consumer purchase intention in China through the application of brand image and consumer perceived values using the S-O-R model. It also provides Chinese policymakers and organic food suppliers with solutions to increase organic food sales to expand the Chinese organic food market.

Hydrogen adsorption, desorption, sensor and storage properties of Cu doped / decorated boron nitride nanocone materials: A density functional theory and molecular dynamic study

The hydrogen storage and sensor properties of Cu-modified boron nitride nanocone (BNNC) structure were comprehensively investigated using the density functional theory method (DFT). By replacing nitrogen atoms with copper atoms on the BNNC structure, the hydrogen molecule's adsorption enthalpy and Gibbs free energy values were calculated as −48.6 and −16.9 kJ/mol, respectively. 4 Cu-doped BNNC structure achieved a notable hydrogen storage capacity of 5.38 wt%. The molecular dynamics calculations demonstrate that the structure modified with four Cu atoms maintains its dynamic stability. Furthermore, this study reveals that the desorption temperatures tend to rise with an increase in the number of adsorbed hydrogen molecules, and the average desorption temperature under 1 atm pressure is determined to be 332 K. The changes of work function values after hydrogen adsorption point out that the Cu-modified BNNC has Φ-sensor feature. Overall, Cu-modified BNNC structures show promising potential as hydrogen storage materials in ambient conditions.

Could Accelerated Long-Term Forgetting Be a Feature of the Higher Rate of Memory Complaints Associated with Subjective Cognitive Decline? An Exploratory Study.

Recently, subjective cognitive decline (SCD) was proposed as an early risk factor for future Alzheimer's disease (AD). In this study, we investigated whether accelerated long-term forgetting (ALF), assessed with extended testing intervals than those adopted in clinical practice, might be a cognitive feature of SCD. Using an explorative MRI analysis of the SCD sample, we attempted to investigate the areas most likely involved in the ALF pattern. We recruited 31 individuals with SCD from our memory clinic and subdivided them based on their rate of memory complaints into mild SCDs (n = 18) and severe SCDs (n = 13). A long-term forgetting procedure, involving the recall of verbal and visuo-spatial material at four testing delays (i.e., immediate, 30 min, 24 h, and 7 days post-encoding) was used to compare the two sub-groups of SCDs with a healthy control group (HC; n = 16). No significant between-group difference was found on the standard neuropsychological tests, nor in the immediate and 30 min recall of the experimental procedure. By contrast, on the verbal test severe SCDs forgot significantly more than HCs in the prolonged intervals (i.e., 24 h and 7 days), with the greatest decline between 30 min and 24 h. Finally, in the whole SCD sample, we found significant associations between functional connectivity values within some cortical networks involved in memory (default mode network, salience network, and fronto-parietal network) and verbal long-term measures. Our preliminary findings suggest that long-term forgetting procedures could be a sensitive neuropsychological tool for detecting memory concerns in SCDs, contributing to early AD detection.

Optimal algorithms for preemptive two-agent scheduling on uniform parallel machines

This paper studies two scheduling problems involving two agents A and B, where each agent has an independent set of jobs and all jobs are to be processed preemptively on uniform parallel machines. The aims of the two problems are to minimize the objective function value of agent A with the makespan of agent B not exceeding a threshold T. In the first problem, there are m machines and the objective function of agent A is the makespan. In the second problem, there are two machines and the objective function of agent A is the total completion time. For each of the two problems, we propose an optimal algorithm and obtain some extended results.

Flood Susceptibility Mapping Using Information Fusion Paradigm Integrated with Decision Trees

Accurate estimation of flood-damaged zones in a watershed is prominent in guiding a framework for developing sustainable strategies. For these purposes, several flood conditioning factor values at flooded and non-flooded points are extracted, and those points are analyzed using decision tree algorithms and eight novel information fusion techniques to get more reliable flood susceptibility mapping. The belief function values of flood susceptibility values at leaf nodes of the tree are fused by several techniques named Dempster-Shafer (DS), Fuzzy Gamma Overlay (FGO), Hesitant Fuzzy Weighted Averaging (HFWA), Hesitant Fuzzy Weighted Geometric (HFWG), Hesitant Fuzzy Weighted Ordered Averaging (HFWOA), HFWOG, Closeness coefficient (Cc) using Euclidean and Manhattan distances. The flood susceptibility values are extracted from the generated maps and are validated by receiver operating characteristics (ROC) curve parameters, and the seed cell area index (SCAI) of classified flood levels. The area under ROC (AUROC) values of training process are 0.997 for DS, HFWA, HFWOA, and Cc-Euclidean, 0.996 for Cc-Manhattan, 0.995 for FGO and 0.994 for HFWG and HFWOG. The AUROC values of the testing process are 0.951 for DS, HFWA, HFWOA, Cc-Euclidean, and Cc-Manhattan, 0.945 for FGO, 0.943 for HFWG, and 0.941 for HFWOG. True Skill Statistics values are 0.962 and 0.870 for training and testing processes. Although these techniques present excellent performance, the SCAI values versus flood susceptibility classes are fitted to assess the prediction capabilities of the techniques further. HFWA and HFWOG have the first- and second-best performances on the estimations. Hence, information fusion paradigm can be employed to combine flood conditioning factors based on a robust classification method to get reliable predictions of flood potential levels and utilize them for land use and construction planning and management.

A GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width

Abstract The Global Navigation Satellite System/Strapdown Inertial Navigation System (GNSS/SINS) integrated navigation system is an important technology for UAV measurement and vehicle movement measurement. But in the operational process of the GNSS/SINS integrated navigation system, the Global Navigation Satellite System (GNSS) signal is vulnerable to external interference, resulting in abnormal system measurement data, and system faults. These faults will reduce the navigation and positioning performance of the system and reduce the measurement accuracy of the system. Aiming at this problem, a GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width is proposed. The algorithm evaluates the system measurement data based on the innovation residual and incorporates the sliding average filter to design the fault detection function based on the smooth bounded width layer. Accurate detection of system faults using fault detection function. The fault detection function value is used to construct the robust cofactor matrix to correct the measurement error in real-time, to improve the accuracy and robustness of the state estimation. The experimental results show that: The proposed algorithm in the paper compares with two traditional robust adaptive algorithms based on smooth bounded layer fault detection and residual chi-square fault detection. The fault detection rates for small step faults show an increase of more than 44.26% and 9.54%, respectively. Similarly, for slowly varying faults, the fault detection rates exhibit an increase of more than 29.32% and 13.56%, respectively. Throughout the fault, the filtering accuracy demonstrates an increase of more than 16.52% and 15.47%, respectively. The algorithm effectively improves the measurement accuracy of the GNSS/SINS integrated navigation system.

Tourists prefer competent appearance robot over warm one: The effect of busyness perception

This article indicates that perceived busyness affects tourists' appearance preferences for service robots in tourist scenarios. Results from three studies reveal that tourists who feel busy will prefer competent-appearance to warm-appearance service robots. This relationship is serial mediated by efficiency motivation and tourists’ functional value focus, and it is moderated by time orientation. Specifically, we find that the effect occurs only among tourists with high present-orientation and low future-orientation but not among tourists with high future-orientation and low present-orientation. Our study examines tourists' preferences for the appearance of service robots from an individual perspective, providing recommendations for the hotel and tourism industry when considering the implementation of service robots.

Research on the Coupled and Coordinated Development of Tourism and Transport in Chongqing Municipality

By examining the current status of tourism and transport research both domestically and internationally, and analyzing the development trends of Chongqing’s tourism and transport industry, this study evaluates the weight indices and performs a coupling and coordination analysis of various indicators of Chongqing’s tourism and transport industry from 2011 to 2019. The following conclusions are drawn: (1) The value of the comprehensive evaluation function for tourism is higher than that of the transport industry, indicating that Chongqing’s tourism industry is in a period of vigorous development; (2) The degree of coupling coordination development between Chongqing’s tourism and transportation industries from 2011 to 2019 is rising. As the coupling coordination stage continues to improve, the level of coupling coordination also improves, with the overall trend showing a progression from mild dysfunction to primary coordination. Based on these conclusions, corresponding countermeasures are proposed to promote the coupling coordination between tourism and transport in Chongqing, and suggestions are made for the overall improvement of the transport industry and the sustainable development of the tourism industry.

Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum.

Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.

Impact of phase selection on accuracy and scalability in calculating distributed energy resources hosting capacity

Hosting capacity (HC) and dynamic operating envelopes (DOEs), defined as dynamic, time-varying HC, are calculated using three-phase optimal power flow (OPF) formulations. Due to the computational complexity of such optimisation problems, HC and DOE are often calculated by introducing certain assumptions and approximations, including the linearised OPF formulation, which we implement in the Python-based tool ppOPF. Furthermore, we investigate how assumptions of the distributed energy resource (DER) connection phase impact the objective function value and computational time in calculating HC and DOE in distribution networks of different sizes. The results are not unambiguous and show that it is not possible to determine the optimal connection phase without introducing binary variables since, no matter the case study, the highest objective function values are calculated with mixed integer OPF formulations. The difference is especially visible in a real-world low-voltage network in which the difference between different scenarios is up to 14 MW in a single day. However, binary variables make the problem computationally complex and increase computational time to several hours in the DOE calculation, even when the optimality gap different from zero is set.

Mediating Impact of Perceived Functional Value of Audit Service on the Relationship between Audit Characteristics and its Effect on Customer Satisfaction with Total Quality Management in Egyptian Hospitals

Mediating Impact of Perceived Functional Value of Audit Service on the Relationship between Audit Characteristics and its Effect on Customer Satisfaction with Total Quality Management in Egyptian Hospitals

Fermi gas formalism for D-type quiver Chern-Simons theory with non-uniform ranks

We construct the Fermi gas formalism for the partition function of supersymmetric Chern-Simons theories with affine D-type quiver diagrams with non-uniform ranks of the gauge groups and Fayet-Illiopoulos parameters by two different approaches: the open string formalism and the closed string formalism. In the closed string formalism approach, we find a novel connection between the partition function of this theory and the partition function of a four-nodes circular quiver supersymmetric Chern-Simons theory. We also studied a symmetry of a density matrix appeared in the closed string formalism. We further calculate the exact values of the partition function for finite N, with which we identified the exponent of the leading non-perturbative effect in 1/N corresponding to the worldsheet instantons in the circular quiver supersymmetric Chern-Simons theories.