Multiple Boundaries Research Articles

Approaches for aggregating data from the regional to the global level: importance for conclusions on Earth system state

Abstract A number of initiatives attempt to delimit the safe operating space (SOS) for human pressures on the Earth system, including the Planetary Boundaries framework. In some cases, data describing regional status are spatially aggregated to provide a global assessment. Several aggregation approaches can be observed, and the chosen approach may impact the conclusions. This study systematically reviews approaches of aggregating regional environmental boundaries and their state to the global level and uses a case study to compare them, aiming to highlight assumptions and implications and show how inconsistent approaches affect the accuracy and comparability of global boundary state. In the comprehensive literature review, 25 studies dealing with spatial aggregation of regional occupation of SOS and 43 associated regional boundary records were identified and categorized according to five spatial aggregation approaches and five types of adjustments that apply across approaches. These approaches were further classified as high- and low-risk approaches based on their assumptions and value judgements regarding precautionary levels and accepted regional transgressions. Notably, key publications dealing with multiple environmental boundaries use different aggregation approaches across the boundaries, potentially introducing biases. The application of these approaches to a case study revealed that the choice can influence the resulting aggregated occupation of SOS substantially, impacting conclusions as to whether or not a boundary is exceeded. To mitigate biases and inconsistencies, future estimates of spatially aggregated regional SOS should transparently communicate assumptions underlying the chosen aggregation approach, address potential inconsistencies across boundaries, and advance understanding of spatial propagation mechanisms.

A deep neural network model for parameter identification in deep drawing metal forming process

With the growing demand for complex-shaped, lightweight, and high-strength metal components in manufacturing, using thinner sheets has become a trend. However, this can lead to decreased formability and excessive thinning. Thus, accurately and efficiently predicting thickness distribution is essential in engineering applications. During the deep drawing process, material deformation is complex and involves multiple nonlinear problems, including geometry, physics, and boundary conditions, which often require extensive computation time for analysis. This study presents a data-driven model based on Deep Neural Networks (DNN) that captures the intrinsic relationship between thickness distribution and process parameters (such as punch radius, blank holder force, and temperature) in deep drawing. The cylindrical cup is divided into regions based on theoretical analysis and numerical simulation to determine thickness at key points. By predicting the thickness distribution and maximum thinning of SPCC steel sheets under various process parameters, the results demonstrate that the model has strong applicability and efficiency, providing reliable thickness prediction for engineering design.

Not Your Typical Oriental Carpet

This article examines contemporary Turkish German artist Nevin Aladağ’s carpet collages Wind (2019) and Skylight Spring (2021) in relation to the iconic window designs of American Midwestern architect Frank Lloyd Wright. By cutting up and conjoining pieces of distinctly patterned carpets from around the world, Aladağ plays with the trope of the Oriental carpet and Orientalism’s hierarchical ordering system. Her collagistic compositions, which incorporate stylistic elements of Wright’s design practice, link disparate patterns, times, and places. Building on Wright’s own understanding of windows as light screens that connect inside and outside, Dickinson reads Aladağ’s collages as powerful heterotopias that cut across multiple other boundaries. Upending the scopic regime of Orientalism, they challenge distinctions between Orient/Occident and traditional/modern, while encouraging the viewer to rethink the power of her own gaze and personal associations with the work of art.

The Research Relationship: Negotiating Multiple Selves and Boundaries in Exploring Sensitive Topics.

This article considers responsibilities and challenges inherent in the research relationship, from the position of a researcher who is also a counselling practitioner. It draws on my experience of undertaking a qualitative interview-based doctoral research study with adult survivors of childhood sexual abuse, engaging critically with the debates in the research literature concerning researcher-practitioner role boundaries and comparable (and distinct) areas of practice between research and counselling. I suggest that within well-held, monitored boundaries, practitioner identities and contextual knowledge are invaluable to the research relationship and that a collaborative fluidity can operate between researcher and professional (in this case, counsellor) identities rather than them being in conflict. Though the issues addressed here arise from the researcher as counselling practitioner, I believe they have a wider relevance for all qualitative researchers. What happens in the research relationship is complex, involving the various identities (personal and professional selves), emotions, and subjectivities of both researchers and research contributors. Our personhood in research can help to generate rich sources of understanding and at the same time demands our critical reflexivity to interrogate our subjectivities and their influence. In undertaking research which asks individuals to reflect in detail and depth on intimate areas of their lives, researchers need to be prepared for the potential emergence of distress and feel equipped, through training, support, and contextual-based knowledge, to be able to respond appropriately. It calls for reflexive relational competence at the heart of qualitative research.

Dynamics of variable thermal conductivity and multiple slip conditions in a Carreau hybrid nanofluid flow past a stretching sheet

AbstractThe influence of thermal radiation, multiple slip boundary conditions, and binary chemical reaction on the three‐dimensional circulation of unsteady magnetohydrodynamic (MHD) natural convection Carreau hybrid nanofluid () across a stretching sheet comprised of heat source/sink (H‐SS) and variable thermal conductivity are investigated. Runge‐Kutta‐Fehlberg 4th‐5th order (RKF‐45), in conjunction with the shooting approach, is utilized for numerical computation. Computed solutions indicate that the volume fraction of silicon dioxide and velocity slip parameters tends to retard the velocity profile. It is inferred from the graphs that temperature profile upsurges with enhancing the magnitude of thermal Grashof number, H‐SS parameter, mass Grashof number, variable conductivity parameter, and radiative parameter, whereas converse effects for thermal slip parameter. The chemical reaction parameter and solutal slip constraint tend to decrease the concentration profile. Furthermore, the heat transfer phenomenon uplifts with the consideration of radiative effects, while the mass transfer rate diminishes with enhancing the magnitude of magnetic parameters and activation energy.

Self-adaptive weighted physics-informed neural networks for inferring bubble motion in two-phase flow

Modeling complex fluid flow using machine learning is increasingly recognized as a valuable approach for revealing multiphase fluid phenomena. Bubble dynamics represent a classical two-phase flow problem that plays a crucial role in various engineering domains. In this paper, physics-informed neural networks (PINNs) are applied to facilitate incompressible two-phase bubble motion modeling by integrating governing equations and interface evolution equations. The loss function of PINNs consists of multiple loss terms, including initial and boundary conditions constraints, partial differential equations residuals, and volume fraction constraints. The performance of PINNs is influenced by the competing effects of these loss terms. Therefore, we introduce a heuristic adaptive weights approach to automatically adjust loss weights for each training point, avoiding manual tuning and improving the accuracy of PINNs. We investigate typical bubble motion cases, specifically focusing on bubble rising and breakup, to showcase the capabilities of the proposed method. We explore the impact of weights and present the results in comparison to the baselines. Through the bubble breakup case, we illustrate that our model shows superior performance even with more complex scenarios. Then we further discuss the generalization and robustness of our model, showing their indispensability over traditional solvers in gas–liquid two-phase systems. Specifically, we accelerate computation speed in transfer learning without the need to modify the original model. We also show that our method effectively solves ill-posed problems, such as those without initial data or with incomplete or noisy boundary conditions.

Multiple boundary states in bilayer and decorated Su-Schrieffer-Heeger-like models

Multiple boundary states in bilayer and decorated Su-Schrieffer-Heeger-like models

Method and Implementation of Projected Hybrid Orbitals for Treating Multiple Covalent Bonds in Combined QM/MM Calculations.

The projected hybrid orbital (PHO) method for treatment of multiple boundary atoms introduces a novel solution for handling the covalent connection between quantum mechanical (QM) and molecular mechanical (MM) regions in QM/MM calculations. By projecting the QM basis, typically adequately large for computational accuracy, onto a secondary minimal basis set on the boundary atom, it preserves electronic interactions between the two regions without system-specific parameters. Applicable in both ab initio wave function theory and density functional theory, PHO has been shown to maintain structural and electronic integrity across various systems. It offers key advantages over traditional QM/MM methods, such as avoiding modification of MM charge distribution and energy corrections, while being flexible for biochemical systems and potentially broader QM/QM embedding frameworks.

Numerical analysis and simulation of a quasistatic frictional bilateral contact problem with damage, long-term memory and wear

We present a mathematical model describing the equilibrium of a viscoelastic body with long-term memory in frictional contact with a sliding foundation. The process is quasistatic, and material damage resulting from excessive stress or strain is captured by a damage function. We assume the material is inhomogeneous, leading to multiple contact boundary conditions. The contact interface is partitioned into two segments: One part takes into account the wear of the contact surface, utilizing Archard's law. Here, contact is modeled with a normal compliance condition with unilateral constraints, coupled with a sliding version of Coulomb's law of dry friction. In the other part, contact is modeled with a nonmonotone condition involving normal compliance and a subdifferential frictional boundary condition. Variational formulation of the model is governed by a coupled system consisting of a variational–hemivariational inequality for the displacement field, a parabolic variational inequality for the damage field and an integral equation for the wear function. We study a fully discrete scheme for numerical approximation with an error estimation of the solution to this problem. Optimal error estimates for the linear finite element method are derived, followed by numerical simulations illustrating the behavior of the model.

Engineering multiple nano-twinned high entropy alloy electrocatalysts toward efficient water electrolysis

Inducing defects in high entropy alloys (HEAs) has been recognized as a promising approach for tuning surface energetics and catalytic activities. However, the comprehensive understanding and facile synthetic methods for defect-rich HEAs remain challenging. Herein, we present an interstitial-atom engineering strategy that involves interstitial atom doping to synthesize B-doped FeCoNiCuMoB HEA films containing abundant multiple nano-twin boundaries. The resulting fivefold-twinned FeCoNiCuMoB catalyst exhibits exceptional performance in alkaline hydrogen evolution reaction (HER, 26 mV at −10 mA cm−2) and oxygen evolution reaction (OER, 201 mV at 10 mA cm−2). Notably, the two-electrode electrolyzer composed of the FeCoNiCuMoB film electrodes achieved the 10 mA cm−2 at an ultralow cell voltage (1.48 V) for water electrolysis, simultaneously maintaining long-term durability. Through in-situ Raman spectroscopy, X-ray absorption spectroscopy (XAS), electrochemical analyses, and density functional theory (DFT) calculations, we elucidate that the unique twin boundaries play a crucial role in tailoring surficial electronic structures. Moreover, election-rich B atoms display optimized atomic configurations, synergistically contributing to a thermodynamically favourable HER/OER pathway. This work provides a platform via interstitial-atom engineering for designing exceptional HEA catalysts, integrating planar defects and electronic effects, to enhance the efficiencies in water electrolysis applications.

Taylor wavelet analysis and numerical simulation for boundary value problems of higher order under multiple boundary conditions

Taylor wavelet analysis and numerical simulation for boundary value problems of higher order under multiple boundary conditions

I Care That You Don’t Share: Confidentiality in Student-Robot Interactions

Enabled by technological advances, robot teachers have entered educational service frontlines. Scholars and policymakers suggest that during Human-Robot Interaction (HRI), human teachers should remain “in-the-loop” (i.e., oversee interactions between students and robots). Drawing on impression management theory, we challenge this belief to argue that robot teacher confidentiality (i.e., robot teachers not sharing student interactions with the human teacher) lets students make more use of the technology. To examine this effect and provide deeper insights into multiple mechanisms and boundary conditions, we conduct six field, laboratory and online experiments that use virtual and physical robot teachers (Total N = 2,012). We first show that students indeed make more use of a confidential (vs. nonconfidential) robot teacher (both physical and virtual). In a qualitative study (Study 2), we use structural topic modeling to inductively identify relevant mediators and moderators. Studies 3 through 5 provide support for these, showing two key mediators (i.e., social judgment concern and interaction anxiety) and two moderators (i.e., student prevention focus and teacher benevolence) for the effect of robot teacher confidentiality. Collectively, the present research introduces the concept of service robot confidentiality, illustrating why and how not sharing HRI with a third actor critically impacts educational service encounters.

Experiment and modelling of degradation mechanism of cement mortar with graphene oxide nanosheets under sulfate attack

Degradation of cementitious materials caused by sulfate attack poses a significantly challenge to their durability. Using nano-additives to enhance the mechanical and durability properties of cementitious materials is a promising solution; however, the impact of graphene oxide (GO) on the sulfate resistance is not yet fully understood. While efforts have been made to study the degradation mechanism through accelerated indoor tests with high sulfate concentrations, these methods fail to accurately replicate real-world field exposure conditions. To better understand the degradation mechanism of GO-modified mortars under actual field conditions, this study examines the long-term degradation (over 24 months) of GO-modified mortars exposed to sulfate solutions with varying concentrations: 0 % (reference), 2.1 % (field condition), 5 % (laboratory condition), and 15 % (high-concentration condition). Additionally, a comprehensive chemo-mechanical model that considers multiple factors and time-varying boundary conditions was proposed. The study thoroughly discusses the effects of GO dosage, sulfate concentration, and exposure time on the degradation mechanism. Comparison with experimental data revealed that cement mortar degradation under sulfate attack is primarily driven by the crystallization pressure related to ettringite formation in diluted sulfate solutions, while the precipitation of alkali ions from mortar pore solutions occurs in concentrated sulfate solutions. In real-field conditions, cement mortar degradation primarily involves gypsum precipitation rather than ettringite formation. This study demonstrates that well-dispersed GO nanosheets can significantly enhance durability of cementitious materials against sulfate attack, offering valuable insights for strategic applications of GO nanosheets in cementitious materials.

A Study on Non-Homogeneous Multiplicative Boundary Value Problems

The paper deals with the non-homogeneous boundary value problems established in the multiplicative calculus. For this problem, the multiplicative meanings of concepts such as adjoint operator, self-adjoint operator, Lagrange identity, Green's formula are obtained. Then, a criterion is given for the existence of solutions to non-homogeneous multiplicative boundary value problems.

Multiboundary wormholes and OPE statistics

We derive higher moments in the statistical distribution of OPE coefficients in holographic 2D CFTs, and show that such moments correspond to multiboundary Euclidean wormholes in pure 3D gravity. The nth cyclic non-Gaussian contraction of heavy-heavy-light OPE coefficients follows from crossing symmetry of the thermal n-point function. We derive universal expressions for the cubic and quartic moments and demonstrate that their scaling with the microcanonical entropy agrees with a generalization of the Eigenstate Thermalization Hypothesis. Motivated by this result, we conjecture that the full statistical ensemble of OPE data is fixed by three premises: typicality, crossing symmetry and modular invariance. Together, these properties give predictions for non-factorizing observables, such as the generalized spectral form factor. Using the Virasoro TQFT, we match these connected averages to new on-shell wormhole topologies with multiple boundary components. Lastly, we study and clarify examples where the statistics of heavy operators are not universal and depend on the light operator spectrum. We give a gravitational interpretation to these corrections in terms of Wilson loops winding around non-trivial cycles in the bulk.

Challenges posed by climate hazards to cardiovascular health and cardiac intensive care: implications for mitigation and adaptation.

Global warming, driven by increased greenhouse gas emissions, has led to unprecedented extreme weather events, contributing to higher morbidity and mortality rates from a variety of health conditions, including cardiovascular disease (CVD). The disruption of multiple planetary boundaries has increased the probability of connected, cascading, and catastrophic disasters with magnified health impacts on vulnerable populations. While the impact of climate change can be manifold, non-optimal air temperatures (NOTs) pose significant health risks from cardiovascular events. Vulnerable populations, especially those with pre-existing CVD, face increased risks of acute cardiovascular events during NOT. Factors such as age, socio-economic status, minority populations, and environmental conditions (especially air pollution) amplify these risks. With rising global surface temperatures, the frequency and intensity of heatwaves and cold spells are expected to increase, emphasizing the need to address their health impacts. The World Health Organization recommends implementing heat-health action plans, which include early warning systems, public education on recognizing heat-related symptoms, and guidelines for adjusting medications during heatwaves. Additionally, intensive care units must be prepared to handle increased patient loads and the specific challenges posed by extreme heat. Comprehensive and proactive adaptation and mitigation strategies with health as a primary consideration and measures to enhance resilience are essential to protect vulnerable populations and reduce the health burden associated with NOTs. The current educational review will explore the impact on cardiovascular events, future health projections, pathophysiology, drug interactions, and intensive care challenges and recommend actions for effective patient care.

‘State Brokerage’ in Migration Infrastructure: A Case of State-Led Multilevel Governance of the Employment Permit System in South Korea

This paper examines ‘state brokerage’ in migration infrastructure through South Korea's Employment Permit System (EPS). It introduces the concept of state-led multilevel governance (sMLG)—a synthesis of multilevel governance (MLG) and state transformation (ST)—as a framework for understanding state brokerage, thereby contributing to the greater diversity in migration infrastructure scholarship. By analyzing state archival documents, the paper examines how South Korean state has developed a governance framework that spans multiple political-territorial boundaries through state transformation. The transformation encompasses forging diplomatic relationships with foreign governments and orchestrating cross-border policy collaborations as well as (re)arranging domestic governance by establishing new institutions, enacting and revising laws, and reconfiguring the relationships among these entities. These processes have allowed the EPS to facilitate the migration of less-skilled labor without the involvement of private actors.

Exploring nanoparticle dynamics in binary chemical reactions within magnetized porous media: a computational analysis

Artificial Neural Networks are incredibly efficient at handling complicated and nonlinear mathematical problems, making them very useful for tackling these challenges. Artificial neural networks offer a special computational architecture that is extremely valuable in disciplines like biotechnology, biological computing, and computational fluid dynamics. The present work investigates the applicability of back-propagation artificial neural networks in conjunction with the Levenberg-Marquardt algorithm for evaluating heat transmission in hybrid nanofluids. This work focuses on the computational analysis of a MgO + GO/EG hybrid nanofluid’s steady mixed convection flow over an exponentially stretched sheet, considering multiple slip boundary conditions, thermal conductivity, heat generation, and thermal radiation. A nonlinear system of ordinary differential equations is produced from the basic associated partial differential system by performing the proper exponential similarities modifications. For generating benchmark datasets, the resulting ordinary differential equations are processed employing the bvp4c method. Considering benchmark datasets set aside for training (70%), testing (15%), and validation (15%), the Levenberg-Marquardt algorithm, which employs back-propagation in artificial neural networks, is implemented. The accuracy of the suggested strategy for handling nonlinear problems is verified utilizing mean squared error, error histograms, and regression analysis, which are all used to evaluate the methodology. Outstanding agreement is seen when ANN outputs are compared to numerical results. The flow properties, including temperature, velocity, and concentration profiles, are shown graphically and numerically. For practical purposes, it is therefore essential to analyze the flow and heat transfer in hybrid nanofluids over exponentially extending and shrinking surfaces under mixed convection and heat source scenarios. Hybrid nanofluid problems have a wide range of practical and industrial applications, such as medication delivery, manufacturing, microelectronics, nuclear plant cooling, and marine engineering.

Misorientations across interfaces in spark plasma–sintered WC–Co cemented carbides

AbstractThis interdisciplinary work concerns misorientations across various interfaces in spark plasma–sintered (SPSed) WC–Co cemented carbides, as well as how these misorientations affect the intergranular fracture. The whole boundaries in cemented carbides were divided according to the phases on the two sides of the boundary plane, and carbide/carbide grain boundaries were further divided according to the misorientation across the boundary plane. Stereological statistics and five‐parameter analysis were comprehensively performed on the concerned boundary types. For Σ2 carbide/carbide boundaries, multiple boundary structures are observed. How Σ2 twist inhibits intergranular fracture and how such boundary structure is formed are analyzed. For random carbide/carbide boundaries, the habit planes that they are terminated by are calibrated, and their responses to intergranular fracture are examined according to their energy anisotropy. For WC/α‐cobalt and WC/β‐cobalt phase boundaries, misorientations across these boundary planes and the corresponding crack propagation routines are illustrated. On these bases, approaches to improve the fracture strength of SPSed cemented carbides are suggested.

Framework of acoustic analysis and shape optimization for three-dimensional doubly periodic multilayered structures

In this research, a framework of acoustic analysis and shape optimization, based on isogeometric boundary element method (IGA-BEM), is proposed for three-dimensional doubly periodic multilayered structures. The study addresses a gap in the literature by focusing on the shape optimization of such structures, which has not been extensively explored previously. The interface between different acoustic media is an infinite doubly periodic surface, which can be constructed by an open non-uniform rational B-splines. A periodic IGA-BEM is developed for the sound field analysis of the doubly periodic multilayered structure, in which the Ewald method is used to accelerate the calculation of periodic Green function. Furthermore, the shape derivative of the doubly periodic multiple boundaries is derived by imposing boundary perturbation and using the adjoint variable method. The control points of the NURBS surfaces are defined as the shape design variables, and all shape sensitivities can be quickly calculated by discretizing the shape derivative formula. Finally, in according with shape sensitivities, the corresponding shape optimization problem is solved by the method of moving asymptotes, so that the optimized shape design can be obtained. A series of numerical examples validates the accuracy and applicability of the proposed approaches.