Scaling Solutions Research Articles

Global classical solvability and asymptotic behaviors of a parabolic-elliptic Chemotaxis-type system modeling crime activities

This paper is devoted to a two-dimensional parabolic-elliptic system in crime activities. The main difference between this system and the chemotaxis system with logarithmic singular sensitivity and quadratic logistic source is that the source term of this system is a mixtype quadratic term. The local existence of solutions to its intial boundary valve problem associated with homogeneous Neumann boundary conditions was considered by Rodríguez. The present study indicates that for any properly regular initial data there admits global classical solutions. Moreover, the qualitative behaviors of solutions in large time scales are considered as well.

Redefining the wildfire problem and scaling solutions to meet the challenge

ABSTRACT As the climate warms, extended drought and heat events in the United States are driving an increase in acres burned and homes lost to wildfire. The most devastating wildfires happen when dry winds carry embers long distances, start spot fires and ignite homes. Burning homes then become the fuel that ignites other nearby homes, causing mass conflagrations. Today wildfire is largely approached as a problem that can be controlled through vegetation treatments and firefighting, but that strategy has not stopped the loss of homes and even entire communities. However, new observational and analytical tools have given firefighters, governments, and the public a better understanding of wildfire and how to prepare for it. By redefining the wildfire problem as a home ignition problem, communities can survive even extreme fires and can safely reintroduce fire to the land.

Development and Validation of the Amharic Version of Self-Efficacy and Outcome Expectancy Measures on Intention to Take Preventive Actions on Noncommunicable Disease.

This study is aimed at developing and accessing the validity and reliability of an Amharic version of the self-efficacy and outcome expectancy measures on noncommunicable disease prevention strategies. The intentions to take protective measures on NCDs' self-efficacy and outcome expectancy scales were created in Amharic using a sequential nine-step process that included translation and contextualization of the items, content validity, pretesting of the questions, sampling, and survey administration. Principal component analysis was conducted on 829 university students which showed a one-factor solution for self-efficacy and a three-factor solution for outcome expectancy scales using split-half measures. Confirmatory factor analyses supported the factor structure, which also demonstrated good internal consistency (.828 self-efficacy, .766 outcome expectancy). The scales had a moderate level of correlation (r = .35, p.001) between them. The study resulted in reliable and valid Amharic versions of self-efficacy (9-item) and outcome expectancy (12-item) scales.

Efficiency evaluation of very large-scale samples: Data envelopment analysis with angle-index synthesis

In the era of big data, the rapid solution of large-scale data envelopment analysis model has attracted extensive attention of scholars. Finding efficient DMUs has become a key consideration in large-scale evaluation. The parallel building hull method and the framework method offer good performance in terms of finding efficient DMUs. However, with the surge in time series data and high-frequency data, the evaluation problem of large-scale samples has put forward the requirement for faster and larger scale solutions for traditional methods. In this study, we propose a prescoring method for DMUs by synthesizing the angle and the index, hereafter called the angle-index synthesis method. Meanwhile, we combine this proposed method with the framework method to obtain all efficient DMUs. Numerical experiments and a real application to the bankruptcy data of Polish companies show the significant advantages of our algorithm in terms of computational time in the large-scale sampling context, and optimal parameters can be ignored. Finally, in the Monte Carlo simulation of very large-scale samples, we show that our algorithm has linear increasing trend for the computational time and good validity even in 1 billion DMUs.

The Implications of a Co-Created Software Solution for Mobility in Rural Areas

This paper explores the challenges in providing digital services of general interest in rural areas and proposes co-created ride-sharing software solutions to address the specific needs of these regions. This applied research is part of the Smarte.Land.Regionen project, which aims to improve digital public services at the district level. Focusing on rural mobility, the paper introduces ride-sharing benches enhanced with software as a possible low-threshold solution. Via workshops, surveys, and market research, the study identifies barriers to the adoption of ride-sharing benches and investigates factors contributing to their success. The software will be developed in an agile process together with partner counties and applied in a real-world case study. The proposed software solution emphasizes user-centered development, the geographical location of benches, and the prioritization of ride requests over ride offers. The findings highlight safety concerns, a lack of reliability, and the importance of obtaining people who are theoretically interested in solutions to actively participate in them. The paper emphasizes the importance of collaborative development with county stakeholders while also acknowledging the inherent limitations as the overall process becomes more complex and organizational obstacles arise. In addition, the findings suggest that the current state of rural mobility cannot be fundamentally changed by the implementation of ride-sharing software alone. Future research should focus on sustaining and scaling digital solutions, measuring their impact on rural mobility, and ensuring their transferability to other regions. The goal is to contribute to inclusive and sustainable rural development by improving access to digital public services and promoting the adoption of tailored mobility solutions.

Psychometric evaluation of the Pain Vigilance and Awareness Questionnaire (PVAQ) in fibromyalgia: Confirmatory factor analysis and the development of a Swedish 8-item version.

Excessive attention to pain, or hypervigilance, is associated with negative outcomes in chronic pain conditions such as fibromyalgia. The Pain Vigilance and Awareness Questionnaire (PVAQ) is a self-report questionnaire to measure attention to pain. This study aimed to evaluate the psychometric properties of a Swedish version of the PVAQ. Psychometric evaluation on cross-sectional data derived from a clinical trial for fibromyalgia (N = 274). We evaluated item characteristics, factor structure in a confirmatory factor analytic framework, internal consistency, and construct validity in terms of correlations with other clinical variables. Though confirmatory factor analysis did not result in a satisfactory solution for the full 16-item scale, acceptable two-factor solutions could be based on either nine or eight items (the PVAQ-9 and PVAQ-8). Internal consistency for both the PVAQ-9 and PVAQ-8 were good to excellent, and associations with pain catastrophizing, anxiety, depression, disability, and overall fibromyalgia impact were largely supportive of construct validity. An unexpected result was that, contrary to previous findings, no version of the PVAQ correlated consistently with pain intensity. The Swedish PVAQ-9 and PVAQ-8 appear to have acceptable psychometric properties when administered online to individuals with fibromyalgia. The PVAQ-8 may be preferable due to being shorter and including an equal number of items per factor. Replication is warranted. This study evaluated the psychometric properties of a Swedish translation of the PVAQ in individuals with fibromyalgia. No convincing factor structure was found for the 16-item version. We could, however, confirm the factor structure of an established 9-item version (the PVAQ-9), and recommend further use of a new 8-item version (the PVAQ-8). In summary, the PVAQ exhibited more convincing psychometric properties when the number of items was roughly cut in half.

Closed‐form solution for scaling a wireless acoustic sensor network

AbstractA closed‐form solution for localising and synchronising an acoustic sensor node with respect to a Wireless Acoustic Sensor Network (WASN) is presented. The aim is to allow efficient scaling of a WASN by individually calibrating newly joined sensor nodes instead of recalibrating the entire array. A key contribution is that the sensor to be calibrated does not need to include a built‐in emitter. The proposed method uses signals emitted from spatially distributed sources to compute time difference of arrival (TDOA) measurements between the existing WASN and a new sensor. The problem is then modelled as a set of multivariate non‐linear TDOA equations. Through a simple transformation, the non‐linear TDOA equations are converted into a system of linear equations. Then, weighted least squares is applied to find an accurate estimate of the calibration parameters. Signal sources can either be known emitters within the existing WASN or arbitrary sources in the environment, thus allowing for flexible applicability in both active and passive calibration scenarios. Simulation results under various conditions show high joint localisation and synchronisation performance, often compared to the Cramér‐Rao lower bound.

Scaling Smart Contracts via Layer-2 Technologies: Some Empirical Evidence

Blockchain-based smart contracts can potentially replace certain traditional contracts through decentralized enforcement and reduced transaction costs. However, scalability is a key bottleneck hindering their broader application and adoption, often leading to concentrated or exclusive networks. To avoid falling short of the original promise of the technology, firms actively explore “layer-2” methods for scaling. We provide some initial evidence on the economic implications of a layer-2 scaling solution, which moves information aggregation from on-chain to off-chain peer-to-peer networks. A parallel-system experiment allows clean identification because we observe the same unit in the treatment and control systems at the same time. We find that this scaling solution reduces operating costs by 76%, and importantly, leads to decentralization with lower market concentration and more participation, which in turn improves data accuracy. The findings provide insights on how blockchain and smart contracting technologies evolve toward achieving decentralized and scalable trust. This paper was accepted by David Simchi-Levi, information systems. Funding: W. Cong received funding from Ripple’s university blockchain research initiative (UBRI). Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.00281 .

Universal dynamics and non-thermal fixed points in quantum fluids far from equilibrium

AbstractClosed quantum systems far from thermal equilibrium can show universal dynamics near attractor solutions, known as non-thermal fixed points, generically in the form of scaling behaviour in space and time. A systematic classification and comprehensive understanding of such scaling solutions are tasks of future developments in non-equilibrium quantum many-body theory. In this tutorial review, we outline several analytical approaches to non-thermal fixed points and summarise corresponding numerical and experimental results. The analytic methods include a non-perturbative kinetic theory derived within the two-particle irreducible effective action formalism, as well as a low-energy effective field theory framework. As one of the driving forces of this research field are numerical simulations, we summarise the main results of exemplary cases of universal dynamics in ultracold Bose gases. This encompasses quantum vortex ensembles in turbulent superfluids as well as recently observed real-time instanton solutions in one-dimensional spinor condensates.

Comparison study of a landslide-event hazard mapping using a multi-approach of fuzzy logic, TRIGRS model, and support vector machine in a data-scarce Andes Mountain region

Landslides are a significant global hazard, especially prevalent in regions with high rainfall, active tectonic processes, and rugged topography, such as the Colombian Andean region. Therefore, it is crucial to identify areas prone to landslides in order to protect human lives and mitigate the adverse impacts on national economies, especially in developing countries situated in tropical and mountainous regions. Assessing landslide hazard and susceptibility is a fundamental step in comprehending the fundamental characteristics of slopes susceptible to failure, particularly under extreme rainfall conditions. Various researchers have devised methods and techniques to assess and map landslides, employing heuristic, statistical, and deterministic approaches. This study carried out a geographic information system-based approach for shallow landslides, with the objective to compare different methods for a landslide-event hazard mapping using the landslide records on May 18, 2015, triggered by a rainstorm in the La Liboriana basin (Colombia). In the first place, a fuzzy logic gamma model was applied using landslide conditioning factors. Then, the deterministic model TRIGRS was applied to assess shallow landslides. Finally, a support vector machine (SVM) model was used to obtain an intermediate scale solution. All models consider the rainfall that triggered the aforementioned landslide event. The results indicated that the SVM (radial basis function) model permits to obtain a better performance (AUC = 0.95) in landslide hazard zonation rather than quantitative heuristic fuzzy gamma model (AUC = 0.86) and the deterministic TRIGRS model (AUC = 0.60), obtaining best accurate at predicting the landslide hazard in the study area.

The role of the teacher and learning in clinical practicum scales: A psychometric testing of the Finnish versions.

To test the psychometric properties of the further developed Role of the Teacher (Tc2) and the new Learning in Clinical Practicum (LCP) scales in a sample of Finnish healthcare students. Psychometrical testing of the Tc2 and LCP scales. A sample consisting of 1133 healthcare students completed the further developed Tc2 scale and the new LCP scale between January and June 2020. Statistical data analysis was performed using explorative factor analysis and Cronbach's alpha coefficient. The STROBE checklist for cross-sectional studies was applied in reporting. Both the further developed Tc2 and the new LCP scales were shown to be valid and reliable. Explorative factor analysis confirmed a two-factor solution for the Tc2 scale with a 76.3% explained variance and a one-factor solution for the LCP scale with a 58.0% explained variance. The scales' internal consistency reliabilities were high (0.9).

Bluebonnet: Scaling solutions for production analysis from unconventional oil and gas wells

Bluebonnet: Scaling solutions for production analysis from unconventional oil and gas wells

Attractor solutions in interacting dark energy models

We investigate a cosmological model in which dark energy, represented by a quintessential scalar field, is coupled to a dark-matter perfect fluid in the spatially flat Friedmann–Robertson–Walker Universe. This allows an energy exchange in the dark sector which could happen both at early times before recombination era or at late times. We use the coupling function Q=γρdmφ̇ which is induced by conformal transforming scalar-tensor and f(R) gravity theories to Einstein frame. It is argued that there is a connection between this coupling function and Q∝ρdmH. A dynamical analysis is used to show that there are early- and late-time attracting solutions for which the system evolves for a wide range of initial conditions. These attractors generalize the scaling solutions which have been already found in the non-interacting case.

Dynamical analysis of fQ-cosmology

We study the evolution of the physical variables in fQ-gravity for two families of symmetric and flat connections in a spatially flat Friedmann–Lemaître–Robertson–Walker geometry where the equation of motion for the nonmetricity scalar is not trivially identity. From the analysis of dynamics we found that the de Sitter universe is always an attractor while the cosmological models admit scaling solutions which can describe the early acceleration phase of our universe or the matter and the radiation epochs.

A generalized closed-form solution for 3D registration of two-point sets under isotropic and anisotropic scaling

Fitting of two-point sets under non-uniform scaling involves several applications, including ultrasound-guided surgery, where ultrasound images generally show anisotropy between its lateral and depth resolution. However, the current state-of-the-art only accomplishes the closed-form solution under the assumption of isotropic scaling, and only the iterative form of the solution is available for registration regardless of scaling type. A generalized closed-form solution, including anisotropic scaling, could robust the computation in the applications of multi-modality image fusion and surgical navigation based on ultrasound images. In this paper, a generalized closed-form solution (GCFS) that accounts for isotropic scaling and anisotropic scaling is proposed. GCFS finds the least-squares solution of rotation, translation, and scaling based on the singular value decomposition (SVD). The method was demonstrated to 1) register two 3D point sets under the effect of anisotropic scaling and 2) register two coplanar 3D point sets under the effect of anisotropic scaling. This study evaluates 3D registration between the preoperative model and intraoperative ultrasonic scanning of a femur and 2D registration of ultrasound images to the phantom for ultrasound calibration. In addition, the conditions that affect the transformation estimations like estimating reflection and noise degeneracy were also considered in the evaluation.

Assessing the Environmental Sustainability of Polygons Consensus Mechanism and Transaction Processing, Comparing Its Energy Consumption and Carbon Footprint with Other Layer 2 and Layer 1 Blockchain Solutions, And Exploring Potential Avenues for Further Optimization

Abstract: This research paper aims to assess the environmental sustainability of Polygon's consensus mechanism and transaction processing, comparing its energy consumption and carbon footprint with other Layer 2 and Layer 1 blockchain solutions. The growing popularity of blockchain technology has raised concerns about its significant energy consumption and environmental impact. As a Layer 2 scaling solution, Polygon has gained traction for its ability to enhance scalability and reduce transaction costs on the Ethereum network. However, its environmental sustainability remains a critical aspect that needs evaluation. To begin, an in-depth environmental impact assessment is conducted to analyze the energy consumption and carbon footprint associated with Polygon's consensus mechanism and transaction processing. Data on energy consumption is collected and compared with other Layer 2 and Layer 1 blockchain solutions. Through quantitative analysis, the carbon emissions produced by Polygon's operations are quantified and compared to industry benchmarks. This assessment provides a baseline for evaluating Polygon's environmental performance. The research then delves into a comparative analysis, examining the energy consumption efficiency of Polygon's consensus mechanism in relation to other blockchain solutions. This analysis includes an assessment of scalability and transaction throughput, considering the trade-offs between energy consumption and network performance. By comparing Polygon with other Layer 2 and Layer 1 blockchain solutions, insights are gained into the environmental advantages and challenges posed by Polygon's consensus mechanism. Furthermore, potential avenues for optimizing Polygon's consensus mechanism and transaction processing are explored. The research explores innovative techniques and improvements that could enhance the sustainability of Polygon's operations. These optimization strategies focus on reducing energy consumption and minimizing the carbon footprint. Additionally, the feasibility and benefits of integrating renewable energy sources into Polygon's infrastructure are investigated. The potential of renewable energy integration to contribute to sustainable transaction processing is examined, considering challenges and opportunities. Governance and policy considerations play a crucial role in promoting environmental sustainability within Polygon's ecosystem. This research evaluates the governance structures and policies that influence sustainable practices within Polygon. The decision-making processes and mechanisms driving sustainability-related initiatives are analyzed, highlighting the importance of effective governance in driving environmental sustainability. Economic incentives and rewards are also explored as mechanisms to encourage sustainable practices within Polygon's ecosystem. The research examines existing economic incentives and mechanisms designed to incentivize energy efficiency and carbon reduction. The effectiveness of these incentives is evaluated, and potential strategies for further incentivization are discussed. The economic aspects of sustainability are crucial in encouraging stakeholders to prioritize environmental concerns

Analysis on optimal length scale of thermoelectric generators when using different circuit layouts

Using thermoelectric generators (TEGs) to recover waste heat is a potential technological approach. To achieve maximum thermoelectric conversion power, scale optimization of thermoelectric modules has been reported in previous studies. However, the results obtained were all based on numerical calculations, and the analytical solution could not be proven theoretically. Therefore, understanding of the internal mechanism of the structural optimization theory is limited. In addition, the relevant optimization results were based on a full-series circuit, and no structural optimization theory for other circuit types has been proposed. To fill this gap, this study adopts a method that combines theoretical derivation and numerical calculation. First, the analytical solution of the optimal scale is derived by taking the full series as an example, and the existence of an optimal structure of the thermoelectric modules is theoretically confirmed. Subsequently, the scale optimization performance of the thermoelectric structure based on different circuit structures was further analyzed, providing theoretical guidance for the optimization of the thermoelectric structure under different circuit connection modes. The results indicate that the optimal lengths for different circuit layouts are quite different, regardless of whether maximum total power or net power is used as the optimization objective. However, for convenience, the optimal length of the full-series circuit mode can be used to design a constant length for all types of multi-stage series circuit modes when the objective is to maximize the net power output. Using this method, the percentage deviation of the obtained power from its theoretical peak net power can be less than 0.6% for the example presented in this study.

A village in a dish model system for population-scale hiPSC studies

The mechanisms by which DNA alleles contribute to disease risk, drug response, and other human phenotypes are highly context-specific, varying across cell types and different conditions. Human induced pluripotent stem cells are uniquely suited to study these context-dependent effects but cell lines from hundreds or thousands of individuals are required. Village cultures, where multiple induced pluripotent stem lines are cultured and differentiated in a single dish, provide an elegant solution for scaling induced pluripotent stem experiments to the necessary sample sizes required for population-scale studies. Here, we show the utility of village models, demonstrating how cells can be assigned to an induced pluripotent stem line using single-cell sequencing and illustrating that the genetic, epigenetic or induced pluripotent stem line-specific effects explain a large percentage of gene expression variation for many genes. We demonstrate that village methods can effectively detect induced pluripotent stem line-specific effects, including sensitive dynamics of cell states.

Stability of domain wall network with initial inflationary fluctuations and its implications for cosmic birefringence

We study the formation and evolution of domain walls with initial inflationary fluctuations by numerical lattice calculations that, for the first time, correctly take into account correlations on superhorizon scales. We find that, contrary to the widely-held claim over the past few tens of years, the domain wall network exhibits remarkable stability even when the initial distribution is largely biased toward one of the minima. This is due to the fact that the domain wall network retains information about initial conditions on superhorizon scales, and that the scaling solution is not a local attractor in this sense. Our finding immediately implies that such domain walls will have a significant impact on cosmology, including the production of gravitational waves, baryogenesis, and dark matter from domain walls. Applying this result to the axion-like particle domain wall, we show that it not only explains the isotropic cosmic birefringence suggested by the recent analysis, but also predicts anisotropic cosmic birefringence that is nearly scale-invariant on large scales and can be probed by future CMB observations.

Evaluation of an organic acid descaling solution for removal calcareous scales on pipelines

Evaluation of an organic acid descaling solution for removal calcareous scales on pipelines