Position Operators Research Articles

Study on the Influence of a Rigid Wall on Cavitation in Underwater Explosions Near the Free Surface

A two-fluid, phase transition-based multiphase flow model is employed to simulate the dynamics of phase transition between liquid and vapor phases during shock wave and rarefaction wave propagation in underwater explosions. The aim is to understand the influence of a rigid wall on the cavitation evolution process and the cavitation collapse load, considering various charge quantities and water depths. The evolution of crucial physical qualities, such as the density, pressure, and the cavitation domain, within the flow field are analyzed and summarized. The presence of a rigid wall is found to significantly impact the cavitation evolution process in underwater explosions. It affects the shape, size, and dynamics of the cavitation domain, as well as the interaction between the explosion and the surrounding fluid. Specifically, the reflected wave on the wall influences the cavitation collapse load, leading to notable differences in the collapse time and collapse pressure compared to free-field conditions. Under different operating conditions, the size and position of the cavitation domain exhibit distinct changes. The proximity of the rigid wall results in unique patterns of cavitation domain evolution, which in turn lead to variations in the pressure distribution and the emergence of new cavitation regions. The findings of this study provide valuable insights into the behavior of cavitation and atomization induced by underwater explosions near the free surface. The understanding gained from these investigations can contribute to the development of effective safety measures and protective strategies in marine and underwater engineering applications. By accurately predicting and mitigating the effects of cavitation, it is possible to enhance the design and operation of underwater structures, ensuring their integrity and minimizing the potential risks associated with underwater explosions.

Optimized Design of Robotic Arm for Tomato Branch Pruning in Greenhouses

Aiming at the robotic pruning of tomatoes in greenhouses, a new PRRPR configuration robotic arm consisting of two prismatic (P) joints and three revolute (R) joints was designed to locate the end effector to handle randomly growing branches with an appropriate posture. In view of the various spatial posture of the branches, drawing on the skill of manual pruning operation, we propose a description method of the optimal operation posture of the pruning end effector, proposing a method of solving the inverse kinematics of the pruning arm based on the multi-objective optimization algorithm. According to the spatial distribution characteristics of the tomato branches along the main stem, the robotic arm structure is compact and the reachable space is maximized as the objective function, and a method of optimizing the key geometric parameters of the robotic arm is proposed. The optimal maximum length of the arm’s horizontal slide joint was determined to be 953.149 mm and the extension maximum length of its telescopic joint was 632.320 mm. The verification test of the optimal structural parameter showed that the optimized robotic arm could reach more than 89.94% of the branches in the pruning target area with a posture that meets the pruning requirements. This study is supposed to provide technical support for the development of a tomato pruning robot.

Two characterizations of the dense rank

In this paper, we have considered the dense rank for assigning positions to alternatives in weak orders. If we arrange the alternatives in tiers (i.e., indifference classes), the dense rank assigns position 1 to all the alternatives in the top tier, 2 to all the alternatives in the second tier, and so on. We have proposed a formal framework to analyze the dense rank when compared to other well-known position operators, such as the standard, modified and fractional ranks. As the main results, we have provided two different axiomatic characterizations which determine the dense rank by considering position invariance conditions along horizontal extensions (duplication), as well as through vertical reductions and movements (truncation, and upward or downward independency).

Correction: Lorentz-Covariance of Position Operator and its Eigenstates for a Massive Spin 1/2 Field

Correction: Lorentz-Covariance of Position Operator and its Eigenstates for a Massive Spin 1/2 Field

Moderating Role of Gender and Job Position in the Relationship between Compensation Practice and Organizational Citizenship Behaviour

This article aims at investigating how the binary dummy-coded gender (female = 1, male = 0) and job position (operator = 1, supervisor = 0) moderate the direct relationship between compensation practice and organizational citizenship behaviour (OCB) in the ready-made garments manufacturing industry of Bangladesh. The present study employed the PLS-SEM (partial least square-structural equation modelling) technique to test the reliability and validity (convergent and discriminant) of the measurement scales and to verify the study hypotheses. The study used SPSS version 20 for descriptive analysis and SmartPLS version 3.3.9 for inferential statistical analysis. The results of this cross-sectional study of 121 employees revealed the significant moderating effect of gender and job position in the positive relationship between compensation practice and OCB. The study results also evidenced that the positive relationship between compensation practice and OCB showed stronger for female employees compared to males. Besides, the results equally confirmed that the compensation practice–OCB relationship became stronger for operator-level employees than supervisors. Findings are discussed in consistency with the previous studies and suggestions for future researchers and practitioners are highlighted at the end of this study.

Analysis of Aerodynamic Loads on Heliostats at Operation Position Using Large Eddy Simulation and the Consistent Discrete Random Flow Generation Method

Abstract This study utilizes the large eddy simulation model (LES) and a synthetic method based on the Fourier technique called consistent discrete random flow generation (CDRFG) to analyze the peak aerodynamic loads on heliostats due to the atmospheric boundary layer. With the CDRFG technique, key flow parameters, including mean velocity profile, turbulent intensities, integral length scales, and turbulent spectra generated in wind tunnels, can be replicated while also satisfying the divergence-free condition. A three-facet heliostat with an elevation angle of α = 45 deg and the rear aligned to the inflow was analyzed. The heliostat behaves like a lifting surface in this orientation, accentuating the aerodynamic effect. The methodology proposed in this study can accurately reproduce flow statistics and predict the peak loads. Compared to experimental data, differences of 2.62% for drag, 7.43% for lift, and 11.0% for overturning were observed. Furthermore, the simulation reveals the generation of wingtip vortices on the sides of the heliostat, which contribute to the aerodynamic load. Overall, this technique has been demonstrated to be effective in replicating the atmospheric boundary layer and predicting the aerodynamic coefficients of heliostats.

A comprehensive assessment method for manned confined space layouts taking into account operational posture comfort supported by artificial intelligence algorithm

Given its specialized design application, the layout design of confined spaces for human occupancy has a significant impact on the efficiency of operators, especially in the design processes aimed at aviation, aerospace, navigation, and other significant engineering fields. The influence of operational posture on layout comfort is crucial, yet existing assessment methods have limited considerations for the impact of operational posture on layout comfort. Therefore, this study proposes a layout decision support method that integrates posture recognition, simulation, and simulation-based comfort comprehensive assessment. By combining intelligent recognition technology, simulation technology, and comprehensive evaluation methods, it aims to provide a highly reliable comprehensive evaluation result for layout design and decision recommendations. To validate the effectiveness of the method, we conducted a comfort experimental evaluation involving seven individuals in the layout design of human-occupied confined spaces at Northwestern Polytechnical University. The results indicate that the proposed method offers a more objective and comprehensive means for layout design and optimization. This Improvement method not only addresses the deficiencies in existing spatial layout evaluation methods and provides a theoretical basis for architectural layout planning evaluation but also offers new perspectives and methodological support for scientific layout design and planning.

Towards quantum mechanics on the curved cotangent bundle

The minimal-length paradigm is a cornerstone of quantum gravity phenomenology. Recently, it has been demonstrated that minimal-length quantum mechanics can alternatively be described as an undeformed theory set on a nontrivial momentum space. However, there is no fully consistent formulation of these theories beyond Cartesian coordinates in flat space and, in particular, no position representation. This paper is intended to take the first steps in bridging this gap. We find a natural position representation of the position and momentum operators on general curved cotangent bundles. In an expansion akin to Riemann normal coordinates with curvature in both position and momentum space, we apply the formalism perturbatively to the isotropic harmonic oscillator and the hydrogenic atom. Due to the symmetry of the harmonic oscillator under exchange of positions and momenta, we show that it is impossible to distinguish position- from momentum-space curvature with oscillators alone. Thus, we obtain an instantiation of Born reciprocity on the curved cotangent bundle, i.e. in precisely the way Born originally envisioned. It manifests itself as a symmetry mixing UV and IR physics, reminiscent of T-duality in string theory.

A Low-Cost Inertial Measurement Unit Motion Capture System for Operation Posture Collection and Recognition.

In factories, human posture recognition facilitates human-machine collaboration, human risk management, and workflow improvement. Compared to optical sensors, inertial sensors have the advantages of portability and resistance to obstruction, making them suitable for factories. However, existing product-level inertial sensing solutions are generally expensive. This paper proposes a low-cost human motion capture system based on BMI 160, a type of six-axis inertial measurement unit (IMU). Based on WIFI communication, the collected data are processed to obtain the displacement of human joints' rotation angles around XYZ directions and the displacement in XYZ directions, then the human skeleton hierarchical relationship was combined to calculate the real-time human posture. Furthermore, the digital human model was been established on Unity3D to synchronously visualize and present human movements. We simulated assembly operations in a virtual reality environment for human posture data collection and posture recognition experiments. Six inertial sensors were placed on the chest, waist, knee joints, and ankle joints of both legs. There were 16,067 labeled samples obtained for posture recognition model training, and the accumulated displacement and the rotation angle of six joints in the three directions were used as input features. The bi-directional long short-term memory (BiLSTM) model was used to identify seven common operation postures: standing, slightly bending, deep bending, half-squatting, squatting, sitting, and supine, with an average accuracy of 98.24%. According to the experiment result, the proposed method could be used to develop a low-cost and effective solution to human posture recognition for factory operation.

Possibilities of landfills and solid waste sites for energy production in Ukraine

Dynamic changes in the energy sector towards the priority of renewable energy are stimulated by the political decisions in the European integrated environment aimed at achieving climate neutrality within the framework of the European Green Deal. The study aims to provide an in-depth investigation of the potential of landfills and solid waste sites for energy production in Ukraine. The study was conducted using general scientific methods, in particular, analysis and synthesis, abstraction, and comparison. The study examined the issues of developing the bioenergy potential of solid waste sites in Ukraine, including organisational, regulatory, technological, financial and investment aspects. The position of various operations for bioenergy waste processing in the solid waste management system, in particular, anaerobic digestion and solid fuel production, was identified, and an analysis of several thermal waste processing technologies was carried out. Among the features and characteristic requirements for the biogas production process using anaerobic methodology, the aspects of technological availability and economic feasibility are highlighted. The study examines the experience of production and use of organic Refuse Derived Fuel and Solid Recovered Fuel produced from solid waste sites, proving the need to optimise the regulatory support for biogas production at solid waste sites storage sites in the national legislative field. The article emphasises the possibility of practical use of Refuse Derived Fuel and Solid Recovered Fuel, in a partial format, to offset the shortage of fossil fuels in Ukraine and actively implement the concept of a sustainable green course for rational waste management. The results obtained can be used to improve the optimisation of strategic programmes for solid waste management in terms of their bioenergy potential

Prevalence of work-related musculoskeletal disorders and ergonomic risk assessment among production workers of pig slaughterhouse in the town municipality of Ang Thong, Thailand

Introduction: Work-related musculoskeletal disorders (WMSDs) are a significant health concern among workers, especially in the meat processing industry. Their impacts have been well documented and reported on numerous occasions. The study aimed to determine the prevalence of WMSDs and the ergonomic assessment of exposure to their risk factors. Methods: This cross-sectional study was conducted in a pig slaughterhouse in the town municipality of Ang Thong, Thailand. Data were collected from April to July 2021 from 108 participants who answered a questionnaire. The descriptive questionnaire for WMSDs was adapted from the Standardized Nordic Questionnaire in Thai and the Bureau of Occupational and Environmental Diseases, Department of Disease Control of Thailand. Ten individuals received an ergonomic assessment of their exposure to risk factors using the Rapid Entire Body Assessment (REBA) method. Results: According to the study, 94.4% of participants working in pig slaughterhouse production reported experiencing the prevalence of WMSDs in the last seven days. Additionally, 93.5% of workers reported experiencing the prevalence of these disorders within the past 12 months. It has been observed that 29.6% of participants experience higher pain levels in their hands, while 25.9% experience it in their wrists, respectively. Based on the results of an ergonomic risk assessment using the REBA method, the half-cutting operator position presents a moderate level of risk. Conclusion: The study revealed that most of the workers at the pig slaughterhouse had to use their hands and arms to apply repeated pressure consistently. The occurrence rates of WMSDs within the last seven days and 12 months were highest in the hands or wrists, followed by the upper arms and shoulders. Therefore, it is crucial to implement ergonomic measures to minimize the risk factors for WMSDs among production workers in pig slaughterhouses.

Lorentz-covariance of Position Operator and its Eigenstates for a Massive Spin 1/2 Field

Lorentz-covariance of Position Operator and its Eigenstates for a Massive Spin 1/2 Field

Heisenberg versus the Covariant String

A Poincaré multiplet of mass eigenstates (P2-m2)Ψ=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\bigl (P^2 - m^2\\bigr )\\Psi = 0$$\\end{document} cannot be a subspace of a space with a D-vector position operator X=(X0,⋯XD-1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$X=(X_0,\\dots X_{D-1})$$\\end{document}: the Heisenberg algebra [Pm,Xn]=iδmn\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$[P^m, X_n] = \ extrm{i}\\delta ^m{}_n$$\\end{document} implies by a simple argument that each Poincaré multiplet of definite mass vanishes. The same conclusion follows from the Stone-von Neumann theorem. In a quantum theory the constraint of an absolutely continuous spectrum to a lower dimensional submanifold yields zero even if Dirac’s treatment of the corresponding classical constraint defines a symplectic submanifold with a consistent corresponding quantum model. Its Hilbert space is not a subspace of the unconstrained theory. Hence the operator relations of the unconstrained model need not carry over to the constrained model. Our argument excludes quantized worldline models of relativistic particles and the physical states of the covariant quantum string. We correct misconceptions about the generators of Lorentz transformations acting on particles.

Mass Medias Impact on Students Mental Health

Contemporary people live in a reality full of intelligent technology construction, and many practical activities are regulated by technology. The chat content generation pre-training program artificial intelligence developed by the Open Artificial Intelligence Research Center (OpenAI) based on large model data training has aroused wide concern because of its generation and learning ability. It is necessary to admit that the current domestic media publicity seems to focus more on the convenience that big data technology may bring to human society. But not much about its own limitations. In the few discussions on the negative effects of big data technology, more concerns are raised about the ethical risks that may be caused by the abuse of relevant technology, such as the threat of "data greed" to personal privacy, and the decision-making errors that may be caused by the superstition of business decision-makers and government heads about "digital dictatorship", etc. From the perspective of philosophy of information technology and philosophy of cognitive science, this paper reviews the gains and losses of big data technology itself in terms of philosophical thought premise and path strategy. Starting from the theory of "moral materialization", this paper analyzes the ethical value load and risk of artificial intelligence from the perspectives of moral subject status, value position presupposition, operation intervention and operation result effect. And from the moral materialization theory of "top-down" approach and "bottom-up" approach to the ethical governance of modern scientific and technological intelligent artifacts.

Oral Materialization and Ethical Governance of Science and Technology in Artificial Intelligence

Contemporary people live in a reality full of intelligent technology construction, and many practical activities are regulated by technology. The chat content generation pre-training program artificial intelligence developed by the Open Artificial Intelligence Research Center (OpenAI) based on large model data training has aroused wide concern because of its generation and learning ability. It is necessary to admit that the current domestic media publicity seems to focus more on the convenience that big data technology may bring to human society. But not much about its own limitations. In the few discussions on the negative effects of big data technology, more concerns are raised about the ethical risks that may be caused by the abuse of relevant technology, such as the threat of "data greed" to personal privacy, and the decision-making errors that may be caused by the superstition of business decision-makers and government heads about "digital dictatorship", etc. From the perspective of philosophy of information technology and philosophy of cognitive science, this paper reviews the gains and losses of big data technology itself in terms of philosophical thought premise and path strategy. Starting from the theory of "moral materialization", this paper analyzes the ethical value load and risk of artificial intelligence from the perspectives of moral subject status, value position presupposition, operation intervention and operation result effect. And from the moral materialization theory of "top-down" approach and "bottom-up" approach to the ethical governance of modern scientific and technological intelligent artifacts.

Encoding Genetic Circuits with DNA Barcodes Paves the Way for High-Throughput Profiling of Dose-Response Curves of Metabolite Biosensors.

Metabolite biosensors, through which the intracellular metabolite concentrations could be converted to changes in gene expression, are widely used in a variety of applications according to the different output signals. However, it remains challenging to fine-tune the dose-response relationships of biosensors to meet the needs of various scenarios. On the other hand, the short read length of next-generation sequencing (NGS) has greatly limited the design capability of sequence libraries. To address these issues, we describe a DNA trackable assembly method, coupled with fluorescence-activated cell sorting and NGS (Sort-Seq), to achieve the characterization of dose-response curves in a massively parallel manner. As a proof of the concept, we constructed a malonyl-CoA biosensor library containing 5184 combinations with six levels of transcription factor dosage, four different operator positions, and 216 possible upstream enhancer sequence (UAS) designs in Saccharomyces cerevisiae BY4700. By using Sort-Seq and machine learning approach, we obtained comprehensive dose-response relationships of the combinatorial sequence space. Therefore, our pipeline provides a platform for the design, tuning, and profiling of biosensor response curves and shows great potential to facilitate the rational design of genetic circuits.

Frontal Crash Testing of a Class V Lift Truck

Abstract Counterbalanced, center control, high-lift trucks with a sit-down, non-elevating operator position are required to have a restraint system. The restraint system is intended to restrain the operator in the normal operating position and assist in reducing the risk of entrapment of the operator between the truck and the ground in the event of a tip-over. This is typically accomplished through the use of a two-point lap belt. This type of restraint also provides a degree of protection in the event of a collision between the lift truck and another object. Lift trucks operate in relatively low-speed environments, and many are limited to a maximum speed of 8 mph through a limiting device or by job site regulations. Though the speeds are low, lift trucks can operate in close proximity to other lift trucks and stationary rigid structures, creating the potential for collisions. The standards governing lift truck restraints do not mandate impact testing or injury criteria. This paper describes instrumented frontal impact and sled testing with a peak acceleration of 51 g performed on a Class V lift truck using an anthropomorphic test device (ATD) to test the effectiveness of lift truck restraints in this scenario. The results of this testing showed ATD injury metrics within automotive safety standards.

A Data-Driven Bayesian Koopman Learning Method for Modeling Hysteresis Dynamics.

Exploring the mechanism of hysteresis dynamics may facilitate the analysis and controller design to alleviate detrimental effects. Conventional models, such as the Bouc-Wen and Preisach models consist of complicated nonlinear structures, limiting the applications of hysteresis systems for high-speed and high-precision positioning, detection, execution, and other operations. In this article, a Bayesian Koopman (B-Koopman) learning algorithm is therefore developed to characterize hysteresis dynamics. Essentially, the proposed scheme establishes a simplified linear representation with time delay for hysteresis dynamics, where the properties of the original nonlinear system are preserved. Furthermore, model parameters are optimized via sparse Bayesian learning together with an iterative strategy, which simplifies the identification procedure and reduces modeling errors. Extensive experimental results on piezoelectric positioning are elaborated to substantiate the effectiveness and superiority of the proposed B-Koopman algorithm for learning hysteresis dynamics.

High-resolution global geopositioning system for last-mile delivery

High-resolution monitoring systems are commonly used to calculate mechanical and energy performance, as well as environmental impact resulting from the operation of a fleet of vehicles in a region. These systems require recording operational or vehicle position data, energy consumption in the case of electric or electric-assisted vehicles, and buttons for specific signals in the operation, such as the start of operation, end of operation, or package delivery. Some vehicle tracking devices available on the market do not allow speed and energy consumption data to be recorded and accessed at the required sampling frequency. This study presents the development and validation of a remote sensing device to record energy consumption and operational variables of a vehicle under real operating conditions with a frequency of 1 Hz. The functioning of the device, the integrated elements in its development, and the data analysis process are detailed. Finally, using the monitoring equipment data, a comparison was made between the operation of electric vehicles and internal combustion vehicles, achieving savings of up to 83% in operating costs and a 79% reduction in CO2 emissions.

Research on indoor environmental monitoring technology and radiation intensity control method for industrial X-ray flaw detection

Abstract With the development of China’s economy, the application of industrial radiation flaw detection technology is becoming more and more widespread, and the radiation monitoring and protection of flaw detection work has become an important topic in the field of radiation safety and protection. This paper uses pyroelectric technology to track X-ray radiation levels in the environment. It also chooses the scale curve method for calibrating the pyroelectric dosimeter and figures out the scale factor at the same time. The neutron and photon dimensions are used to evaluate the personal dose equivalent. The applicable range of pyroelectric dosimeters is calculated and the method is applied for radiation dose monitoring in industrial X-ray flaw detection rooms. Concrete wall shielding is used to determine the design parameters of the flaw detection room and the location of the distribution points to improve the shielding capacity of the flaw detection room and control the radiation intensity. The monitoring value of the operation position of the flaw detection room of Leshan Leboiler Enterprises in 2018 was 258.2, which was 73 higher than that of 2019. The results of the on-site monitoring of the absorbed dose rate of the ambient air in the flaw detection room showed that the average absorbed rate ranged from 0.015 to 0.546 μSv/h, which was lower than the standard of 2.5 μSv/h, and the shielding capacity of the flaw detection room was better, and the intensity of the radiation could be effectively controlled.