Set-theoretic Research Articles

The impact of virtual laboratories on the academic performance of grade 12 learners in impulse and momentum

Virtual laboratories (labs) have evolved as an important tool in the sciences, delivering interactive and engaging platforms for learners to conduct experiments and comprehend complex concepts without the limitations of physical resources. They are an emerging teaching tool that offers interactive and immersive experiences that improve comprehension of complicated scientific concepts. This study assesses the impact of virtual labs on the academic achievement of Grade 12 learners on the topic of impulse and momentum in physics. It uses a quasi-experimental methodology to compare the performance of learners who used virtual labs to those who learned in the prevailing theoretical settings. A pre-test and post-test were used to assess learners’ academic success, and surveys were used to gather learner feedback on the learning tool. Preliminary data analysis indicates a statistically significant improvement in the test scores of learners using virtual labs, corroborating earlier studies that highlight the advantages of technologically enhanced learning environments. Furthermore, qualitative feedback indicates that learners found virtual labs more interesting and accessible, resulting in a more conducive learning environment. This work adds to the expanding body of evidence supporting the use of virtual labs in science teaching, especially in resource-constrained contexts where traditional laboratory equipment is limited or non-existent. The implications for curriculum design and educational policy are examined, with a focus on the importance of investing in digital infrastructure to support innovative teaching approaches.

Transferable and Interpretable Prediction of Site-Specific Dehydrogenation Reaction Rate Constants with NMR Spectra.

Accurate and efficient determination of site-specific reaction rate constants over a wide temperature range remains challenging, both experimentally and theoretically. Taking the dehydrogenation reaction as an example, our study addresses this issue by an innovative combination of machine learning techniques and cost-effective NMR spectra. Through descriptor screening, we identified a minimal set of NMR chemical shifts that can effectively determine reaction rate constants. The constructed model performs exceptionally well on theoretical data sets and demonstrates impressive generalization capabilities, extending from small molecules to larger ones. Furthermore, this model shows outstanding performance when applied to limited experimental data sets, highlighting its robust applicability and transferability. Utilizing the Sure Independence Screening and Sparsifying Operator (SISSO) algorithm, we also present an interpretable rate constant-temperature-NMR (k-T-NMR) relationship with a mathematical formula. This study reveals the great potential of combining machine learning with easily accessible spectroscopic descriptors in the study of reaction kinetics, enabling the rapid determination of reaction rate constants and promoting our understanding of reactivity.

Investigating the Impact of Quantum Computing on Algorithmic Complexity

This paper investigated the transformation that quantum computing brought into algorithmic complexity in the theoretical setting of computer science. This involved the appearance of new paradigm changes brought forth by quantum technologies, imposing on a glance at the performance of quantum algorithms in respect to classical models of computation regarding their effectiveness. Our contributions encompassed key quantum algorithms, specifically Shor's and Grover's algorithms, underlining the performance metrics of those algorithms. The mathematical modeling was supported by simulations using python libraries like Qiskit, which helped analyze the complexities of both algorithm types. From our simulations, it emerged that for smaller sizes of input, classical algorithms executed faster and illustrated their established efficiency. In contrast, quantum computing-algorithms like Grover's and Shor's - performed so much better for larger input sizes, showing potential advantages that may change the face of computational limitations. While promising much, it seemed from our findings that quantum computing would not show a quantum advantage for all computational tasks, because classical algorithms still remained robust and effective for many scenarios. This nuanced understanding underlines how complementary both the classical and quantum approaches are. Therefore, the insights gained through this work provide the basis for investigating where boundaries of computational capabilities evolve and what practical implications are of the integration of quantum technologies into existing systems.

The Quantum-Inspired Evolutionary Algorithm in the Parametric Optimization of Lithium-Ion Battery Housing in the Multiple-Drop Test

Recent developments in lithium-ion batteries have improved their capacity, which allows them to be used in more applications like power tools. However, they also carry higher risks, such as thermal runaway, which can happen if they are damaged. To make these batteries safer, it is important to improve the design of their housings subjected to multiple drops during their use. This article introduces a new method for optimizing the design of lithium-ion battery housings using a Quantum-Inspired Evolutionary Algorithm (QEA). Previously used mainly in theoretical settings, the authors have adapted QEA for practical engineering tasks. Multiple-drop test simulations were performed, and QEA was used to identify the best housing designs that minimize damage. To support this, a program was developed that automates all drop tests and rebuilds the model. The damage is obtained on the basis of the finite element method (FEM) analyses. The findings show that the algorithm successfully identified designs with the least damage during these tests. This research helps make battery housings safer and explores new uses for QEA in mechanical engineering.

On submodular prophet inequalities and correlation gap

Prophet inequalities and secretary problems have been extensively studied in recent years due to their elegance, connections to online algorithms, stochastic optimization, and mechanism design problems in game theoretic settings. Rubinstein and Singla [31] developed a notion of combinatorial prophet inequalities in order to generalize the standard prophet inequality setting to combinatorial valuation functions such as submodular and subadditive functions. For non-negative submodular functions they demonstrated a constant factor prophet inequality for matroid constraints. Along the way they showed a variant of the correlation gap for non-negative submodular functions.In this paper we revisit their notion of correlation gap as well as the standard notion of correlation gap and prove much tighter and cleaner bounds. Via these bounds and other insights we obtain substantially improved constant factor combinatorial prophet inequalities for both monotone and non-monotone submodular functions over any constraint that admits an Online Contention Resolution Scheme. In addition to improved bounds we describe efficient polynomial-time algorithms that achieve these bounds.

The determination of the price of capital goods: A differential game approach

AbstractIn this paper, we address the determinants of the price of newly installed productive capacity. Specifically, we develop a differential game in which a competitive producer of consumption goods deals with a seller of capital goods endowed with market power. From a theoretical perspective, we demonstrate that an open‐loop Stackelberg equilibrium requires the producer of consumption goods to be more impatient than the seller of capital goods. Thereafter, we show that our theoretical setting can replicate the countercyclical pattern of the relative price of capital goods as well as its negative relationship with the investment–output ratio.

Increasing environmental variability inhibits evolutionary rescue in a long-lived vertebrate

Evolutionary rescue, whereby adaptive evolutionary change rescues populations from extinction, is theorized to enable imperiled animal populations to persist under increasing anthropogenic change. Despite a large body of evidence in theoretical and laboratory settings, the potential for evolutionary rescue to be a viable adaptation process for free-ranging animals remains unknown. Here, we leverage a 38-year dataset following the fates of 53,959 Magellanic penguins (Spheniscus magellanicus) to investigate whether a free-ranging vertebrate species can morphologically adapt to long-term environmental change sufficiently to promote population persistence. Despite strong selective pressures, we found that penguins did not adapt morphologically to long-term environmental changes, leading to projected population extirpation. Fluctuating selection benefited larger penguins in some environmental contexts, and smaller penguins in others, ultimately mitigating their ability to adapt under increasing environmental variability. Under future climate projections, we found that the species cannot be rescued by adaptation, suggesting similar constraints for other long-lived species. Such results reveal how fluctuating selection driven by environmental variability can inhibit adaptation under long-term environmental change. Our eco-evolutionary approach helps explain the lack of adaptation and evolutionary rescue in response to environmental change observed in many animal species.

In-in formalism for the entropy of quantum fields in curved spacetimes

We show how to compute the purity and entanglement entropy for quantum fields in a systematic perturbative expansion. To that end, we generalize the in-in formalism to non-unitary dynamics (i.e. accounting for the presence of an environment) and to the calculation of quantum information measures, which are not observables in the usual sense. This allows us to reduce the problem to one involving standard correlation functions, and to organize their computation in a diagrammatic expansion for which we construct the corresponding Feynman rules. As an illustration, we apply the formalism to a cosmological setting inspired by the effective field theory of inflation. We find that at late times, non-linear loop corrections share the same time behavior as the linear contribution, and only yield a slight redressing of the purity. In particular, when the environment is heavy compared to the Hubble scale, the phenomenon of recoherence previously encountered is robust to the class of non-linear extensions considered. Bridging the gap between perturbative quantum field theory and open quantum systems paves the way to a better understanding of renormalization and resummation in open effective field theories. It also enables a more systematic exploration of quantum information properties in field theoretic settings.

One-Dimensional Relativistic Self-Gravitating Systems.

One of the oldest problems in physics is that of calculating the motion of N particles under a specified mutual force: the N-body problem. Much is known about this problem if the specified force is non-relativistic gravity, and considerable progress has been made by considering the problem in one spatial dimension. Here, I review what is known about the relativistic gravitational N-body problem. Reduction to one spatial dimension has the feature of the absence of gravitational radiation, thereby allowing for a clear comparison between the physics of one-dimensional relativistic and non-relativistic self-gravitating systems. After describing how to obtain a relativistic theory of gravity coupled to N point particles, I discuss in turn the two-body, three-body, four-body, and N-body problems. Quite general exact solutions can be obtained for the two-body problem, unlike the situation in general relativity in three spatial dimensions for which only highly specified solutions exist. The three-body problem exhibits mild forms of chaos, and provides one of the first theoretical settings in which relativistic chaos can be studied. For N≥4, other interesting features emerge. Relativistic self-gravitating systems have a number of interesting problems awaiting further investigation, providing us with a new frontier for exploring relativistic many-body systems.

Assessment of Early Childhood Teachers' Competencies for Care and Education of Toddlers

Contemporary trends in the education and care of toddlers shed light on the specific competencies of early childhood teachers. The aim of this empirical qualitative study with elements of a comparative approach is to investigate, look at and understand the perspective of early childhood teachers about their own competencies for working in toddler groups in kindergartens in Bosnia and Herzegovina and in the Republic of Slovenia. We collected the data needed for the research in 2022 from 91 respondents using a self-created structured online interview in written form. Through the thematic analysis of the content of respondents' answers and the theoretical setting of the concept of early childhood teachers' competencies, nine categories of difficulties and six categories of advantages related to their competencies were distinguished. The findings of this study point to the fact that early childhood teachers for toddlers do not assess their own competencies as optimally developed.

A Review of Improved Methods for Ant Colony Optimization in Path Planning

_ Ant colony optimization is an intelligent evolutionary algorithm that has been widely used in the field of path planning, and the research on its improved methods is proliferating. In this paper, the improvement methods of single and hybrid ant colony optimization in path planning are reviewed in terms of initial pheromone concentration, heuristic function, state transition rule, pheromone update rule, and parameter optimization, respectively. The future research directions of ant colony optimization have been prospected in terms of theoretical aspects, parameter setting and optimization, integration with other algorithms, and multiobjectives. Keywords ant colony optimization; path planning; single ant colony optimization; hybrid ant colony optimization; improvement methods

Design and Experiment of Dual-Row Seedling Pick-Up Device for High-Speed Automatic Transplanting Machine

To address the inefficiency and instability of automatic transplanting machines, a dual-row seedling pick-up device and its corresponding control system were developed. Existing seedling end-effectors are primarily mechanically controlled, and the seedling needles can easily cause damage to the interior of the bowl. In order to reduce the damage inflicted by the end-effectors to the bowl, this paper conducted a mechanical analysis of the end-effector. At the same time, a buffer optimization analysis was conducted on the operation of the end-effector, and a flexible pneumatic end-effector for seedling picking was designed. The control system combined the detection of multiple sensors to monitor the process of seedling picking and throwing. By coordinating the lifting cylinder and clamping cylinder, the system effectively reduced seedling pot damage while improving seedling picking efficiency. By setting the operating parameters of the servo motor, the goal of low-speed and high-efficiency seedling picking was achieved. To evaluate the performance of the control system, the linear displacement sensors and acceleration testing systems were used to analyze the performance of the seedling throwing. The results showed that the seedling picking efficiency could reach 180 plants min−1, with no significant difference between the actual measured moving distance and the theoretical setting distance. The positioning error remained stable between 0.5 and 0.9 mm, which met the requirements for seedling picking accuracy. The buffer optimization design reduced the peak acceleration of the end-effector from −22.1 m/s2 to −13.4 m/s2, and the peak value was reduced by 39.4%, which proved the significant effectiveness of the buffer design. A performance test was conducted using 128-hole seed trays and 33-day-old cabbage seedlings for seedling picking and throwing. When the planting frequency reached 90 plants/row·min−1, the average success rate of picking and throwing seedlings was 97.3%. This indicates that the various components of the designed seedling pick-up device work in good coordination during operation, and the control system operates stably. Technical requirements for the automatic mechanical transplanting of tray seedlings were achieved, which can provide reference for research on automatic transplanting machines.

Student Attendance Management System

The unique traces a real-time face recognition and attendance system designed to streamline attendance tracking in instructive settings. Leveraging OpenCV, face_recognition, and MongoDB, the framework mechanizes the recognizable proof of understudies from video streams or IP camera nourishes, recording their participation precisely and productively. Conventional attendance methods are regularly labor-intensive and inclined to mistakes, inciting the advancement of robotized arrangements. This investigate addresses these challenges by joining strong facial recognition algorithms with real-time video preparing capabilities and adaptable information capacity. By utilizing OpenCV for image processing, face_recognition for facial include location and acknowledgment, and MongoDB for information administration, the framework offers a comprehensive arrangement for participation following. The abstract emphasizes the system's common sense, effectiveness, and potential to revolutionize participation administration in instructive educate. Besides, it highlights the significance of exactness, preparing speed, and versatility in assessing the system's execution. Generally, the theoretical sets the organize for a detailed investigation of the system's design, execution, results, and suggestions for participation administration in educational settings.

Revitalizing Pedagogy in a Medical Problem-Based Learning (PBL) Curriculum

The Medical Programme at Linköping University, committed to Problem-Based Learning (PBL) and interprofessional education, confronted the necessity for pedagogical revitalization due to an upsurge in student numbers, alterations in national physician licensing criteria, and an organizational framework shift. In response to these challenges, stakeholders conducted a comprehensive systematic self-assessment to navigate a course toward a sustainable and contemporary pedagogical transformation. The methodology employed in this assessment involved a systematic examination of scientific pedagogical literature, policy documents, educational materials, and schedules. Additionally, valuable insights were gathered through teacher and student surveys. Key findings underscore the importance of a balanced approach that grants students more time for self-study and reflection. Enhancing tools and methodologies for constructive alignment is crucial to achieve equilibrium in both theoretical and practical training settings. Moreover, establishing seamless collaborations between the university and teaching hospitals is deemed essential for faculty development and the long-term competence within both organizations. The self-assessment underscored the critical importance of continuous evaluation in medical educational settings. The approach not only ensures the ongoing relevance of the curricula but also cultivates an environment conducive to student-centred teaching and learning. This, in turn, prepares students for lifelong learning and the diverse challenges in their future medical profession.

Vortex Circular Dichroism: An experimental technique to assess the scalar/vectorial regime of diffraction.

In classical electrodynamics, light-matter interactions are modelled using Maxwell equations. The solution of Maxwell equations, which is typically given by means of the electric and magnetic field, is vectorial in nature. Yet it is well known that light-matter interactions can be approximately described in a scalar (polarization independent) way for many optical applications. While the accuracy of the scalar approximation can be theoretically computed, to the best of our knowledge, it has never been determined experimentally. Here, we introduce Vortex Circular Dichroism ( VCD), an optical measurement that has the required features to assess the vectoriality of diffraction. VCD is measured as the differential transmission (or absorption) of left and right circularly polarized vortex beams. We test the VCD measurement with two different systems: i) an experimental set of single circular nano-apertures drilled in a gold film with diameters ranging from 150 to 1950 nm; and ii) a theoretical set of golden spheres with the same diameters as the nano-apertures. We observe that in both systems, VCD > 0 for smaller diameters, VCD ≲ 0 for intermediate values and VCD ≈ 0 for larger values of the diameter. Furthermore, the simulations show that a diffraction process characterized by a VCD ≈ 0 ( VCD ≠ 0) is polarization-independent (polarization-dependent). As a result, we relate VCD ≠ 0 to a vectorial diffraction, and VCD ≈ 0 to a scalar one. Overall, our results show compelling evidence that it is possible to experimentally assess the scalar/vectorial regime of a diffraction process, and that the VCD technique possesses the required features to measure the vectoriality of diffraction processes involving plasmonic cylindrically symmetric structures.

Research on the Curriculum System of Top-up Degree Programs under the Background of New Engineering and Technical Disciplines

In response to the new round of technological revolution and industrial transformation, and to support and serve innovation-driven development, new engineering talents focus on the cultivation of practical and innovative abilities. At present, the proportion of upgrading from junior college to undergraduate in China has reached 20%. More and more vocational school graduates have the opportunity to receive high-quality undergraduate education, become skilled professionals. But the cultivation of this group of students is often overlooked by many universities. This study analyses the issues existing in the undergraduate curriculum system of local applied universities in undertaking vocational education. It is pointed out that the application of ordinary undergraduate curriculum systems is not suitable for vocational-to-bachelor s students and cannot meet the training objectives of higher vocational and technical talents. To cultivate new engineering vocational and technical talents, aiming at the current issues in the theoretical and practical settings of the curriculum system, this study proposes to use employment as a guide in the vocational-to-bachelor s curriculum system, set bridging courses to consolidate professional foundations, implement multiple training programs to promote student development, and collaborate with enterprises to carry out project-based practical training. It is necessary to optimize the construction of the curriculum system from theoretical and practical, and fully leverage the advantages of students strong practical abilities, which will reserve high-level vocational and technical talents for the new round of technological and industrial revolution.

Game theoretical analysis in two-echelon sustainable supply chains to manage and coordinate strategic decisions

Business firms and consumers are increasingly and rapidly realizing the benefits of adopting environmental responsibility. The business firms stress including it in their supply chain strategy and/or operations. This paper explores the environmental consciousness and quality attentiveness of consumers in a supply chain. Demand for the product depends on its price, eco-friendly level, and quality of the product. Three decentralized models are developed under three different game theoretical settings. A comparative study of the three game-theoretical models reveals several characteristics. It determines conditions under which channel members can decide the policy for the best possible benefit. The present work explores the effect of customer environmental awareness on the optimal decision. Production of eco-friendly items is also the prime consideration of our paper. It reveals that the manufacturer gets the most profit in the manufacturer Stackelberg game model, but the retailer gets the maximum profit from the retailer Stackelberg game model. Although channel members prefer their leading position to make the game theoretical decision-making process, the most decentralized channel profit is obtained from the Nash game model. Thus, consumers will also benefit, and the best channel profit can be obtained if the channel members agree to make decentralized decisions using the Nash game model. The centralized channel profit outperforms all three decentralized channel profits. The paper applies the concepts of sub-game perfect equilibrium and alternating offer bargaining to coordinate the channel and distribute surplus profit. Finally, analytical results are verified using numerical examples.

No client left behind: A meta-analysis of premature termination from psychotherapy in U.S. service members and veterans.

Dropout has been identified as a significant problem among military populations seeking psychotherapy (Goetter et al., 2015; Hoge et al., 2014), yet an overall estimate of its exact prevalence and predictors does not exist. The aims of the current meta-analysis were to estimate outpatient psychotherapy dropout rates for this population and evaluate potential moderators of this event. In total, 283 articles-comprising data from 719,465 U.S. service members and veterans-met all inclusion criteria and were included in the meta-analysis. The average weighted dropout rate for all outpatient therapies was 25.6%, 95% CI [22.4%, 29.2%], and prediction interval [1.9%, 85.9%]. Furthermore, dropout was 27.0% for cognitive behavioral therapies (CBTs), 25.3% for trauma treatments, 27.6% for the Department of Veterans Affairs (VA), 28.9% for individual therapies, and 9.8% for intensive outpatient settings. Findings from metaregression analyses using mixed-effects models indicated that higher dropout was linked with the following after accounting for other moderators: younger age, CBTs, nonmanualized approaches, VA versus Department of Defense settings, individual versus group therapies, and weekly versus intensive outpatient formats. Dropout was not linked with other client, therapist, treatment, and research variables. Taken together, dropout estimates were obtained for a range of military populations and treatment characteristics, including theoretical orientation, presenting concern, setting, and therapy formats. These estimates may provide potential benchmarks for therapists, administrators, and policymakers serving military populations. Leveraging dropout prevention strategies with at-risk groups highlighted in this study may enhance mental health care outcomes for this high-need population. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Chain reactions: can experimental urbanism provide the formula for productive, place-based, change?

In this commentary, we revisit our previous viewpoint (Varna and Oswell, 2021) and explain how our work has progressed since it was published. The commentary is structured into three sections. In the first, we revisit our original propositions to allow us to critically reflect on them. In the second, we ground our reflective practice within a theoretical context and set out an emerging methodology to trial action research and experiments in urbanism. The third section sets out a strategy for deployment of this methodology in active processes of experimental urbanism in a mix of specific ‘left-behind’ neighbourhoods in northeast England. This article was published open access under a CC BY licence: https://creativecommons.org/licences/by/4.0 .

A matching pursuit approach to the geophysical inverse problem of seismic traveltime tomography under the ray theory approximation

SUMMARYSeismic traveltime tomography is a geophysical imaging method to infer the 3-D interior structure of the solid Earth. Most commonly formulated as a linearized inverse problem, it maps differences between observed and expected wave traveltimes to interior regions where waves propagate faster or slower than the expected average. The Earth’s interior is typically parametrized by a single kind of localized basis function. Here we present an alternative approach that uses matching pursuits on large dictionaries of basis functions.Within the past decade the (Learning) Inverse Problem Matching Pursuits [(L)IPMPs] have been developed. They combine global and local trial functions. An approximation is built in a so-called best basis, chosen iteratively from an intentionally overcomplete set or dictionary. In each iteration, the choice for the next best basis element reduces the Tikhonov–Phillips functional. This is in contrast to classical methods that use either global or local basis functions. The LIPMPs have proven their applicability in inverse problems like the downward continuation of the gravitational potential as well as the MEG-/EEG-problem from medical imaging. Here, we remodel the Learning Regularized Functional Matching Pursuit (LRFMP), which is one of the LIPMPs, for traveltime tomography in a ray theoretical setting. In particular, we introduce the operator, some possible trial functions and the regularization. We show a numerical proof of concept for artificial traveltime delays obtained from a contrived model for velocity differences. The corresponding code is available online.