Boundary Of Space Research Articles

Testing in GARCH‐X models: boundary, correlations and bootstrap theory

In this article, we consider the so‐called Fixed Shrinkage (FS) bootstrap for the class of GARCH models with explanatory variables (GARCH‐X). Under the assumption of stationary covariates, the proposed FS bootstrap does not require modeling the covariates, as these are kept fixed in the bootstrap generating process. Our main focus is on testing whether one or more of the covariates can be excluded in the GARCH‐X model. As is well‐known the limiting distribution of the likelihood‐ratio (LR) statistic in this setting is non‐standard and depends in particular on whether nuisance parameters are on the boundary or in the interior of the parameter space. In particular, and as detailed here, the non‐standard limiting distribution depends on correlations, or dependence, between the explanatory variables. The FS bootstrap takes the presence of nuisance parameters into account by implementing shrinking as proposed in Cavaliere et al. (2022) for pure ARCH models. We establish asymptotic validity of the FS bootstrap for GARCH‐X models, and demonstrate by simulations that the bootstrap‐based test performs extremely well even when nuisance parameters lie on the boundary of the parameter space. The empirical illustration amplifies that the presence of nuisance parameters (especially whether or not on the boundary) are vital for interpreting the dynamics of conditional volatility in financial stock market indices.

Relativity of the event: examples in JT gravity and linearized GR

Observables in quantum gravity are famously defined asymptotically, at the boundary of AdS or Minkowski spaces. However, by gauge fixing a coordinate system or suitably dressing the field operators, an approximate, “quasi-local” approach is also possible, that can give account of the measurements performed by a set of observers living inside the spacetime. In particular, one can attach spatial coordinates to the worldlines of these observers and use their proper times as a time coordinate. Here we highlight that any such local formulation has to face the relativity of the event, in that changing frame (= set of observers) implies a reshuffling of the point-events and the way they are identified. As a consequence, coordinate transformations between different frames become probabilistic in quantum gravity. We give a concrete realization of this mechanism in Jackiw-Teitelboim gravity, where a point in the bulk can be defined operationally with geodesics anchored to the boundary. We describe different ways to do so, each corresponding to a different frame, and compute the variances of the transformations relating some of these frames. In particular, we compute the variance of the location of the black hole horizon, which appears smeared in most frames. We then suggest how to calculate this effect in Einstein gravity, assuming knowledge of the wavefunction of the metric. The idea is to expand the latter on a basis of semiclassical states. Each element of this basis enjoys standard/deterministic coordinate transformations and the result is thus obtained by superposition. As a divertissement, we sabotage Lorentz boosts by adding to Minkoswki space a quantum superposition of gravitational waves and compute the probabilistic coordinate transformation to a boosted frame at linear order. Finally, we attempt to translate the relativity of the event into the language of dressed operators.

Transient voltage stability assessment and margin calculation based on disturbance signal energy feature learning

With the increasing variation of the network topology and the high complexity of the processing measurement data, the transient voltage stability assessment of the new power system is facing significant challenges in low accuracy and high time costs. To address the shortcomings of the existing method and apply it to online assessment, this paper proposes an assessment method based on feature learning for disturbance signal energy (DSE) from bus voltages. Firstly, the relationship between DSE and system transient voltage stability is established, and the calculation of DSE from bus voltage time series is detailed. Subsequently, a transient voltage stability assessment method based on the ID3 Decision Tree algorithm and DSE is proposed. Finally, by employing the Support Vector Machine (SVM) to construct the optimal boundary in the feature space formed by the key buses, the transient voltage stability margin (TVSM) for specific scenarios is proposed. Simulation results on the IEEE 39-bus system demonstrate that the proposed method can rapidly and accurately assess the transient voltage stability of the system and calculate the stability margin, providing intuitive and interpretable results with high engineering application value.

Research on dangerous flight weather prediction based on machine learning

Abstract With the continuous expansion of the scale of air transport, the demand for aviation meteorological support also continues to grow. The impact of hazardous weather on flight safety is critical. How to effectively use meteorological data to improve the early warning capability of flight dangerous weather and ensure the safe flight of aircraft is the primary task of aviation meteorological services. In this work, support vector machine (SVM) models are used to predict hazardous flight weather, especially for meteorological conditions with high uncertainty such as storms and turbulence. SVM is a supervised learning method that distinguishes between different classes of data by finding optimal decision boundaries in a high-dimensional space. To meet the needs of this study, we chose the radial basis function (RBF) as the kernel function, which helps to deal with nonlinear problems and enables the model to better capture complex meteorological data structures. During the model training phase, we used historical meteorological observations from multiple weather stations, including temperature, humidity, wind speed, wind direction, and other meteorological indicators closely related to flight safety. From this data, the SVM model learns how to distinguish between normal and dangerous flight weather conditions.

Evaluation of supervised machine learning regression models for CFD-based surrogate modelling in indoor airflow field reconstruction

Fast and reliable prediction of indoor airflow distribution is critical for indoor environment control. While neural networks (NN), often interchangeably referred to as Back Propagation Neural Networks (BPNNs), are popular for airflow predictions, optimizing these models is challenging due to their ”black box” nature and complex network structures. This study explores alternative robust regression models, including decision-tree-based models (e.g., XGBoost, LightGBM, Random Forest) and Support Vector Regression (SVR), for predicting indoor airflow. Two BPNN structures were initially developed to evaluate feasibility of NN models. BPNN A was trained using airflow velocities from two inlets as input neurons to directly predict the airflow velocity distribution within the domain. BPNN B was trained additionally with spatial information, including space samples and boundary wall data. Higher-dimensional training structures of BPNN B were applied to decision tree-based models and SVR to assess their capability in predicting non-linear airflow patterns. Results indicated that BPNN A achieved the highest accuracy, while the inclusion of higher-dimensional data in BPNN B led to decreased accuracy. Among all decision-tree-based models, XGBoost demonstrated the greatest potential, achieving an R2 above 99.5% and predictive errors below 10%. XGBoost also outperformed both BPNN models in speed, being 15.78 times faster than BPNN A and 252 times faster than BPNN B. The interpretability of XGBoost was further explored by analysing feature importance, which helps identify the most influential input variables while predicting the airflow velocity. This analysis is expected to offer an enhanced understanding of boundary conditions leading to optimised indoor environment strategy.

3D soft material printer as a mesoscale additive biomanufacturing platform for in-space manufacturing

With the burgeoning in-space manufacturing (ISM) industry, developing an on-demand additive manufacturing (AM) platform will be crucial for long-term space habitation. However, acute space boundary conditions, such as limited physical space, microgravity, vacuum, and others pose unique challenges for designing the printing process, the platform’s structure, and the materials’ printability. An AM platform operable in a space environment would enable production at the point of need (PoN), for example, on-demand food, nutrition, and pharmaceutical products. This research is focused on the design, fabrication, and testing of a 3D printer confined within CubeSat boundaries to study the feasibility of soft material printing aimed toward potential ISM applications. The printer unit was built using components off the shelf (COTS) while adhering to the severe spatial boundary conditions posed by the CubeSat dimensions and was tested using an edible material ink to demonstrate multi-layer prints of soft materials. Printing in ambient Earth conditions as well as under vacuum displayed consistent layer cohesion and comparison to 3D model data although vacuum prints showed visibly dehydrated prints owing to outgassing of air bubbles. The printer equipment’s structural integrity was validated under simulated launch and operation conditions using a vibration testing setup according to the NASA-recommended microsatellites standards. The results indicated that the printer assembly maintained its structural and operational integrity during and after testing. Using soft materials as the basis of testing allows scalability when expanding to more complex and structural materials to produce spare parts using a frugally engineered modular manufacturing platform.

Integrated evaluation of the functioning quality of robotic agricultural vehicle system

The article proposes to use a method for evaluating the effectiveness (Data Envelope Analysis) of a system of robotic agricultural vehicles, which is based on solving the problem of fractional linear programming when analyzing a set of homogeneous production facilities. This method is used for an integrated assessment of the quality of service of robotic vehicles according to the specified key parameters of functioning. The main parameters of the effectiveness of the system of robotic agricultural vehicles are selected: the coefficient of technical readiness, operational speed, downtime in maintenance and repair, the average daily duration of the car, the average monthly mileage of the vehicle, the remaining life of the car, the unit cost of maintenance and specific cargo displacement. Solving systems of linear equations makes it possible to determine the position of each analyzed object relative to the efficiency boundary in a multidimensional parameter space. The solution of the Bunker-Charnes-Cooper problem has been completed. Sets of target changes in the parameters of robotic cars have been obtained, which transfer objects to the efficiency boundary. The analysis of the parameters is carried out by constructing diagrams of production capabilities in a multidimensional space. For two periods of operation of the robotic vehicle system for an agro-industrial enterprise, the Malmquist index was calculated to assess the dynamics of operational efficiency.

Boundary Structure of the Standard Model Coupled to Gravity

AbstractIn this article a description of the reduced phase space of the standard model coupled to gravity is given. For space or time-like boundaries this is achieved as the reduction of a symplectic space with respect to a coisotropic submanifold and with the BFV formalism. For light-like boundaries the reduced phase space is described as the reduction of a symplectic manifold with respect to a set of constraints. Some results about the Poisson brackets of sums of functionals are also proved.

T-duality across non-extremal horizons

When applying T-duality to a generic, non-extreme Killing horizon, T-duality is spacelike on one side and timelike on the other. We show, using simple examples from four-dimensional Einstein-Maxwell theory, that the image of the horizon is a singularity which can be understood as an interface between two different T-dual theories and their solutions. Using an embedding into type-II string theory, we show that the singularity occurs when scalars reach the boundary of moduli space, resulting in a breakdown of the effective field theory due to the presence of tensionless strings.

Data-Driven Radial Compressor Design Space Mapping

Abstract Estimates of turbomachinery performance trends inform system-level compromises during preliminary design. Existing empirical correlations for efficiency use limited experimental data, while analytical loss models require calibration to yield predictive results. From a set of 3708 radial compressor computations, this paper maps efficiency as a function of mean-line aerodynamics, and determines the governing loss mechanisms. An open-source turbomachinery design code creates annulus and blade geometry, then runs a Reynolds-averaged Navier–Stokes simulation for compressors sampled from the mean-line design space. Polynomial surface fits yield a continuous eight-dimensional representation of the design space for analysis, predicting efficiency with a root-mean-square error of 1.2% points. The results show a balance between surface dissipation in boundary layers and mixing loss due to casing separations sets optimum values for inlet Mach number, hub-to-tip ratio, de Haller number, and backsweep angle. Surface dissipation drives the effect of flow coefficient, with high surface areas at low values, and high velocities at high values. Compact compressor designs are achieved by increasing inlet Mach number, reducing hub-to-tip ratio, and minimizing the radial loading coefficient—all of which reduce efficiency approaching design space boundaries. An interactive web-based tool makes the results available to practising engineers, demonstrating large ensembles of automated designs and simulations as a higher-fidelity replacement for legacy empirical correlations in preliminary design.

“Best Before”: On Women, Ageism, and Mental Health

Introduction: Our world has changed over the last decades, and one of the dramatic changes has been the increase in human life expectancy. Due to important life-saving breakthroughs, the current life expectancy for the world in 2024 is 73.33 years; and female global life expectancy is 76.0 years. This trend manifests one of the greatest achievements of human society, which, however, reveals issues that humanity has yet to address. One of them is the place and role of women over 40 in modern society. Purpose: This paper aims to unveil gendered ageism and to identify its negative impact on women’s mental health. Methodology: We conducted a systematic search in the main electronic databases, such as PubMed, Scopus, Web of Science, and Google Scholar. Relevant studies were identified using search terms: women over 40, aging, gendered ageism, mental health, wellbeing, beauty standards, youthfulness, age stereotypes, multiple discrimination, inequity, identity, sexuality, social exclusion, intersectionality. The authors used phenomenological philosophical, hermeneutic, and inductive approaches, as well as the interpretive research paradigm. Review and Discussion: Constant anxiety about aging, attempts to turn back time, desperate cosmetic battles that women are involved in are far from just a tribute to fashion or female vanity, but also an attempt to come out of the shadows, to overcome the boundaries of female limited space, and to make a woman visible. However, women’s grand entrance onto the big stage faces gendered ageism that forces women over 40 feel excluded in society and life by making them invisible. Despite certain changes in public consciousness over the role of women in society, we still live in a men’s world. The centuries-old subordination of women to men, cultural ideas about the “perfect” female face, body, age, weight, compliance with which is a “pass” to the world of success, or, according to evolutionary psychologists, a “mechanism” that promotes survival, crystallize in various disorders, thereby undermining women’s mental health, downplaying the value of wisdom, knowledge and life experience, and eroding women’s self-esteem. Conclusion: Aging is a natural and inevitable process, and old age is a significant part of life, which can be filled with joy, achievements of small and big goals, dissemination of accumulated experience and wisdom. Unfortunately, these wonderful aspirations are hindered by ageism – one of the last socially acceptable prejudices. Inducing age stereotypes and perpetuating internalized ageism, our social environment maintains discrimination of women over 40 in workplace, social settings, and private sphere that has detrimental consequences for women’s mental and physical health. Therefore, combating ageism and sexism and eliminating age discrimination is essential to support older women’s health and wellbeing. Both women and men share the responsibility to progress towards true equity that will help women around the world achieve success on their own terms and reach their full potential. Life journey of every woman is a way of self-discovery and self-development, in which the various aspects of a woman’s personality come together to create unique integrity of body, mind, and spirit. To fully realize the potential of half of humanity, it is necessary to dismantle the systems that maintain inequities, as well as to raise up and empower women of all ages, colors, abilities to assert themselves and be respected in both public and private spheres, to accept reality and move on, to feel comfortable and confident in their own skin, to do wonders for everyone on our planet, and to know that every woman matters.

Optimal nonlinear Fractional-Order Proportional-Integral-Derivative controller design using a novel hybrid atom search optimization for nonlinear Continuously stirred Tank reactor

Atom search optimization (ASO) algorithm derived from physics molecular dynamics. Lennard-Jones(L-J) and bond length potential of molecules are used to derive the model for optimization. In this paper, ASO is used for developing a nonlinear Fractional Order Proportional Integral Derivative controller (NL-FOPID) for Continuously Stirred Tank Reactor (CSTR). The convergence characteristics of ASO was improved by proposing a novel hybridization approach. The proposed hybridization approach called Hybrid ASO(HASO) guides the Atom search algorithm to optimally replace the atoms that goes out of the boundary of the search space. The designed algorithm is implemented to optimize various unimodal and multi model standard benchmark functions. From results obtained from this extensive simulation, it is indicated that proposed approach increased the convergence rate and also improved the optimization effort of conventional ASO. The proposed algorithm also tested with controller design for nonlinear CSTR. The NLPID and NL FOPID designed by HASO was better than conventional controllers found in the literature.

Stokes Phenomena in Lensing

As lensing of coherent astrophysical sources, e.g., pulsars, fast radio bursts, and gravitational waves, becomes observationally relevant, the mathematical framework of Picard–Lefschetz theory has recently been introduced to fully account for wave optics effects. Accordingly, the concept of lensing images has been generalized to include complex solutions of the lens equation referred to as “imaginary images,” and more radically, to the Lefschetz thimbles, which are a sum of the steepest descent contours connecting the real and imaginary images in the complex domain. In this wave-optics-based theoretical framework of lensing, we study the “Stokes phenomena” as the change of the topology of the Lefschetz thimbles. Similar to the well-known caustics at which the number of geometric images changes abruptly, the corresponding Stokes lines are the boundaries in the parameter space where the number of effective imaginary images changes. We map the Stokes lines for a few lens models. The resulting Stokes line-caustics network represents a unique feature of the lens models. The observable signature of the Stokes phenomena is the change of interference behavior, in particular the onset of frequency oscillation for some Stokes lines. We also demonstrate high-order Stokes phenomena where the system has a continuous number of effective images but with an abrupt change in the way they are connected to each other by the Lefschetz thimbles. Their full characterization calls for an analogy of the catastrophe theory for caustics.

Reconciling Tracking Error Volatility and Value-at-Risk in Active Portfolio Management: A New Frontier

AbstractThis article introduces the Risk Balancing Frontier (RBF), a new portfolio boundary in the absolute risk-total return space: the RBF arises when two risk indicators, the Tracking Error Volatility (TEV) and the Value-at-Risk (VaR), are both constrained not to exceed pre-set maximum values. By focusing on the trade-off between the joint restrictions on the two risk indicators, this frontier is the set of all portfolios characterized by the minimum VaR attainable for each TEV level. First, the RBF is defined analytically and its mathematical properties are discussed: we show its connection with the Constrained Tracking Error Volatility Frontier (Jorion in Financ Anal J, 59(5):70–82, 2003. https://doi.org/10.2469/faj.v59.n5.2565) and the Constrained Value-at-Risk Frontier (Alexander and Baptista in J Econ Dyn Control, 32(3):779–820, 2008. https://doi.org/10.1016/j.jedc.2007.03.005) frontiers. Next, we explore computational issues implied with its construction, and we develop a fast and accurate algorithm to this aim. Finally, we perform an empirical example and consider its relevance in the context of applied finance: we show that the RBF provides a useful tool to investigate and solve potential agency problems.

The Prevalence of Self-Exploitation in Media Production: Analyzing the Impact of Technological and Societal Transformations

The development of science and technology and the changes of society have given a new look to traditional conceptual work. The developed network and ubiquitous communication have broken the time and space boundaries of work. Working from home has become a reality. Some people continue to predict that work will become a relaxed enjoyment. But the reality is frustrating. Not only did people not relax, but they also took on increasingly heavy work pressures. The boundaries between work and leisure are eliminated by heavy business, and the office is transformed into a place where people spend the most time. Therefore, work is no longer a pleasure, but self-exploitation behaviour. The unstable and unsafe nature of creative work in the media industry creates stress and anxiety, and the strong emotional pleasure associated with this kind of work exists. The tension between "pleasure" and "pain" in creative occupations has been fully proven. Unstable labour has now become a key feature of creative work. Creative occupations are driven by self-fulfilling desires and are places for exploitation and serious insecurity.

The Prevalence of Self-Exploitation in Media Production: Analyzing the Impact of Technological and Societal Transformations

The development of science and technology and the changes of society have given a new look to traditional conceptual work. The developed network and ubiquitous communication have broken the time and space boundaries of work. Working from home has become a reality. Some people continue to predict that work will become a relaxed enjoyment. But the reality is frustrating. Not only did people not relax, but they also took on increasingly heavy work pressures. The boundaries between work and leisure are eliminated by heavy business, and the office is transformed into a place where people spend the most time. Therefore, work is no longer a pleasure, but self-exploitation behaviour. The unstable and unsafe nature of creative work in the media industry creates stress and anxiety, and the strong emotional pleasure associated with this kind of work exists. The tension between "pleasure" and "pain" in creative occupations has been fully proven. Unstable labour has now become a key feature of creative work. Creative occupations are driven by self-fulfilling desires and are places for exploitation and serious insecurity.

Legitimacy and place leadership: responding to and recovering from disruption in regional soft spaces

ABSTRACT This article explores through interviews the influence of legitimacy on place leadership within regional soft spaces in England during the COVID-19 pandemic. Legitimacy is an important yet underexamined facet of place leadership. Employing a tripartite legitimacy framework – input, throughput and output legitimacy – we illuminate novel insights on the nature of legitimacy relationships at different boundaries of regional soft spaces and how they shape place leadership over time in a changing context. We further argue that political astuteness is vital for multi-hatting leaders within regional soft spaces to enable cross-boundary mobilisation for collective action in response and recovery from disruption.

Finiteness theorems and counting conjectures for the flux landscape

In this paper, we explore the string theory landscape obtained from type IIB and F-theory flux compactifications. We first give a comprehensive introduction to a number of mathematical finiteness theorems, indicate how they have been obtained, and clarify their implications for the structure of the locus of flux vacua. Subsequently, in order to address finer details of the locus of flux vacua, we propose three mathematically precise conjectures on the expected number of connected components, geometric complexity, and dimensionality of the vacuum locus. With the recent breakthroughs on the tameness of Hodge theory, we believe that they are attainable to rigorous mathematical tools and can be successfully addressed in the near future. The remainder of the paper is concerned with more technical aspects of the finiteness theorems. In particular, we investigate their local implications and explain how infinite tails of disconnected vacua approaching the boundaries of the moduli space are forbidden. To make this precise, we present new results on asymptotic expansions of Hodge inner products near arbitrary boundaries of the complex structure moduli space.

Direct Products of Free Groups in Aut(FN)

We give a complete description of the embeddings of direct products of nonabelian free groups into Aut(FN) and Out(FN) when the number of direct factors is maximal. To achieve this, we prove that the image of each such embedding has a canonical fixed point of a particular type in the boundary of Outer space.

Uniform Metric Graphs

We prove that every complete metric space “is” the boundary of a uniform length space whose quasihyperbolization is a geodesic visual Gromov hyperbolic space. There is a natural quasimöbius identification of the original space’s conformal gauge with the canonical gauge on the Gromov boundary. All parameters are absolute constants.