General Class Research Articles

Fully extremal black holes: A black hole graveyard?

While the standard point of view is that the ultimate endpoint of black hole evolution is determined by Hawking evaporation, there is a growing evidence that classical and semi-classical instabilities affect both black holes with inner horizons as well as their ultra-compact counterparts. In this paper we start from this evidence pointing towards extremal black holes as stable endpoints of the gravitational collapse, and develop a general class of spherical and axisymmetric solutions with multiple extremal horizons. Excluding more exotic possibilities, entailing regular cores supporting wormhole throats, we argue that these configurations could be the asymptotic graveyard, the end-point, of dynamical black hole evolution — albeit the timescale of such evolution are still unclear and possibly long and compatible with current astrophysical observations.

Relative equilibria of mechanical systems with rotational symmetry

We consider the task of classifying relative equilibria for mechanical systems with rotational symmetry. We divide relative equilibria into two natural groups: a generic class which we call normal, and a non-generic abnormal class. The eigenvalues of the locked inertia tensor descend to shape-space and endow it with the geometric structure of a three-web with the property that any normal relative equilibrium occurs as a critical point of the potential restricted to a leaf from the web. To demonstrate the utility of this web structure we show how the spherical three-body problem gives rise to a web of Cayley cubics on the three-sphere, and use this to fully classify the relative equilibria for the case of equal masses.

Empirical relationships between Arias Intensity and peak ground acceleration for western China

There is little available attenuation relationship for Arias Intensity (AI) in China. Empirical relationships between AI and peak ground acceleration (PGA) provide another option for predicting AI. We establish empirical relationships for AI and PGA for western China, utilizing 3,169 horizontal and 979 vertical strong motion records with PGA ≥0.01 g from 274 earthquakes (MS 4.0–8.0), originating in eight provinces in southwest (Yunnan, Sichuan) and northwest China (Gansu, Shaanxi, Ningxia, Qinghai, Inner Mongolia, and Xinjiang). The influences of MS epicenter distance, and site conditions indicators VS30, generic site classes (i.e., rock and soil) are explored. The results show that the logarithm of AI increases linearly with the increase of the logarithm of PGA and MS, and decreases with the logarithm of VS30. However, the influence of site conditions on AI-PAG relationships can't be recognized by the simple generic rock and soil site classes. The epicenter distance has little effect on the AI-PAG relationships. Empirical relationships are developed to estimate horizontal or vertical AI as a function of PGA (basic model), PGA and MS (model 2) for southwest, northwest, and western China, using all the records. Empirical relationships for AI as a function of PGA, MS, and VS30 (model 1) are established using the 2,248 horizontal (70.9% of the total) and 670 vertical (68.4% of the total) records with VS30 between 148 and 841m/s. The notable disparity between model 1 of the southwest and northwest regions is chiefly attributed to local site conditions, indicating that the AI-PGA correlation is region-dependent. These findings enable one way of estimating AI for western China and will contribute to a better understanding of AI attenuation.

LN: A Flexible Algorithmic Framework for Layered Queueing Network Analysis

Layered queueing networks (LQNs) are an extension of ordinary queueing networks useful to model simultaneous resource possession and stochastic call graphs in distributed systems. Existing computational algorithms for LQNs have primarily focused on mean-value analysis. However, other solution paradigms, such as normalizing constant analysis and mean-field approximation, can improve the computation of LQN mean and transient performance metrics, state probabilities, and response time distributions. Motivated by this observation, we propose the first LQN meta-solver, called LN, that allows for the dynamic selection of the performance analysis paradigm to be iteratively applied to the submodels arising from layer decomposition. We report experiments where this added flexibility helps us to reduce the LQN solution errors. We also demonstrate that the meta-solver approach eases the integration of LQNs with other formalisms, such as caching models, enabling the analysis of more general classes of layered stochastic networks. Additionally, to support the accurate evaluation of the LQN submodels, we develop novel algorithms for homogeneous queueing networks consisting of an infinite server node and a set of identical queueing stations. In particular, we propose an exact method of moment algorithms, integration techniques for normalizing constants, and a fast non-iterative mean-value analysis technique.

The power of second-order conspiracies

ABSTRACT A second-order conspiracy (SOC) is a conspiracy that aims to create (and typically also disseminate) a conspiracy theory. Second-order conspiracy theories (SOCT) are theories that explain the occurrence of a given conspiracy theory by appeal to a conspiracy. In this paper I argue that SOC and SOCT are useful and coherent concepts, while also having numerous philosophically interesting upshots (in terms of epistemology, explanation, and prediction). Secondly, I appeal to the nature of two specific kinds of second-order conspiracies to make the case for what has been called ‘local generalism’ (Stamatiadis-Bréhier 2023a). Specifically, I focus on so-called ‘denial industries’ to argue that the structure of these second-order conspiracies allows us to infer non-accidental generalisations about the domain of conspiracy theories. Even though it is true that there is nothing epistemically problematic with the general class of conspiracy theories, there are specific subsets of conspiracy theories that warrant immediate strong suspicion (cf. Dentith 2022). By looking at the intricate mechanisms by which these denial industries operate, we can infer that the conspiracy theories that are produced by them are epistemically unwarranted. I conclude by making some exploratory remarks about what the metaphysics of second-order conspiracies would look like.

On testing the changes in trends of stock market index and rates

Calibration of interest rate models benefits from grouping data to homogenous classes. Such an approach is typical in many financial time series. Preliminaries have been developed for Cox–Ingersoll–Ross models but this issue remains an open problem for many more realistic interest rate models. Here we develop such a strategy for general class interest rate and classes are based on p-value thresholds for testing for normality and gamma distributions. We use as the benchmark financial series of Chilean stock market index IPSA (Indice de precios selectivo de acciones) and its log-returns. We also study the relationship between interest rate and the market returns represented by the IPSA indicator, with positive correlation in some lags which reveals some interesting facts in the contrary to the conventional theory.

Simple proofs of certain inequalities with logarithmic coefficients of univalent functions

In this paper, we give simple proofs for the bounds (some of them sharp) of the difference of the moduli of the second and the first logarithmic coefficient for the general class of univalent functions and for the class of convex univalent functions.

Stability analysis of a stochastic port-Hamiltonian car-following model

Port-Hamiltonian systems are pertinent representations of many nonlinear physical systems. In this study, we formulate and analyse a general class of stochastic car-following models with a systematic port-Hamiltonian structure. The model class is a generalisation of classical car-following approaches, including the optimal velocity model of Bando et al (1995 Phys. Rev. E 51 1035), the full velocity difference model of Jiang et al (2001 Phys. Rev. E 64 017101), and recent stochastic following models based on the Ornstein–Uhlenbeck process. In contrast to traditional models where the interaction is totally asymmetric (i.e. depending only on the speed and distance to the predecessor), the port-Hamiltonian car-following model also depends on the distance to the follower. We determine the exact stability condition of the finite system with N vehicles and periodic boundaries. The stable system is ergodic with a unique Gaussian invariant measure. Other properties of the model are studied using numerical simulation. It turns out that the Hamiltonian component improves the flow stability and reduces the total energy in the system. Furthermore, it prevents the problematic formation of stop-and-go waves with oscillatory dynamics, even in the presence of stochastic perturbations.

Selective Classes and Early Health Inequalities in Comprehensive Schools in Finland.

The origin of inequalities in health outcomes has been explained by health selection and social causation models. Health selection processes operate particularly at school age. We study, if student allocation to teaching groups with aptitude tests (selective vs general class) differentiates adolescents by health behaviors and mental health. Finnish schoolchildren 12-13 years from 12 selective classes, n = 248; 41 general classes, n = 703 answered a questionnaire on addictive products (tobacco, snus, alcohol, and energy drinks), digital media use, and mental health (health complaints, anxiety, and depression). Structural equation modeling was conducted to identify structures between outcomes, SEP (socioeconomic position), class type, and academic performance. Students in the selective classes reported less addictive digital media and addictive products use than students in the general classes. Differences in academic performance or SEP between the class types did not solely explain these differences. Mental health was not related to the class type. SEP was indirectly associated with health behaviors via the class type and academic performance. Selecting students to permanent teaching groups with aptitude tests differentiates students according to risky health behaviors. The impact of education policies using student grouping should also be evaluated in terms of students' health.

Android-Based Drug Information Application Using Augmented Reality Technology

The use of Augmented Reality technology in the pharmaceutical sector, particularly in pharmacies, has introduced significant innovations in providing drug information to consumers. AR applications can help healthcare workers and patients better understand drug use through three-dimensional visualization superimposed on the real environment. Observations at Sultan Abdul Aziz Syah Peureulak Hospital indicate that 70% of patients still experience confusion regarding the drug information provided by pharmacy staff. This difficulty is caused by the complexity of the information, lack of personal interaction, or low health literacy. To address this problem, the Android-based Mediscan application was developed using AR technology. This application utilizes Unity and Vuforia Engine software to present drug information visually in card form via the smart device screen. Users can point the camera at a particular drug and receive complete information regarding general indications, dosage, drug class, contraindications, and side effects. This research aims to develop the Mediscan application, calculate the level of patient understanding, measure consumer satisfaction, and evaluate the impact of using AR in presenting drug information. The System Development Life Cycle methodology with the Waterfall model was used in this research. The results show that AR technology can be implemented in Android-based applications to present drug information visually and interactively. The majority of patients feel more informed and gain a better understanding of the medication they are taking. AR technology in the Mediscan application improves user experience, supports the education and training of medical personnel and patients, and enhances the quality of healthcare services in hospitals. This application also makes it easier for medical personnel and pharmacists to convey drug information more effectively and efficiently.

Geometric estimates and comparability of Eisenman volume elements with the Bergman kernel on ([formula omitted]-)convex domains

We establish geometric upper and lower estimates for the Carathéodory and Kobayashi-Eisenman volume elements on the class of non-degenerate convex domains, as well as on the more general class of non-degenerate C-convex domains. As a consequence, we obtain explicit universal lower bounds for the quotient invariant both on non-degenerate convex and C-convex domains. Here the bounds we derive, for the above mentioned classes in Cn, only depend on the dimension n for a fixed n≥2. Finally, it is shown that the Bergman kernel is comparable with these volume elements up to small/large constants depending only on n.

Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders

Abstract A general quasilinear sixth-order ordinary differential equation (ODE) is an important class of ODEs. The primary objective of this study is to establish a numerical method for solving a general class of quasilinear sixth-order partial differential equations (PDEs) and ODEs. However, the Runge–Kutta method (RKM) approach for solving special classes of ODEs has been generalized as an effort to solve the general class of ODEs. Nonlinear algebraic order condition (OCs) equations have been obtained up to the tenth order using the Taylor-series expansion methodology which is used to derive the novel generalized Runge–Kutta method (GRKM). In this study, a GRKM integrator has been derived for solving a general class of quasilinear sixth-order ODEs and then this method is modified subsequently to solve a class of PDEs. Accordingly, the proposed GRKM is modified to solve a quasilinear sixth-order PDE by converting it to a system of sixth-ODEs using the method of lines. Nine problems have been implemented to prove the efficiency and accuracy of the proposed method. Simulation results of these problems showed that the proposed numerical GRKM is an accurate and efficient method. In contrast, by comparing the proposed GRKM numerical approach with the classical RK method, the numerical results demonstrate that the direct integrator outperforms the indirect classical RK method in terms of algorithm complexity and function evaluations, proving that the numerical GRKM is efficient.

Canonical Typicality for Other Ensembles than Micro-canonical

AbstractWe generalize Lévy’s lemma, a concentration-of-measure result for the uniform probability distribution on high-dimensional spheres, to a much more general class of measures, so-called GAP measures. For any given density matrix $$\rho $$ ρ on a separable Hilbert space $${\mathcal {H}}$$ H , $${\textrm{GAP}}(\rho )$$ GAP ( ρ ) is the most spread-out probability measure on the unit sphere of $${\mathcal {H}}$$ H that has density matrix $$\rho $$ ρ and thus forms the natural generalization of the uniform distribution. We prove concentration-of-measure whenever the largest eigenvalue $$\Vert \rho \Vert $$ ‖ ρ ‖ of $$\rho $$ ρ is small. We use this fact to generalize and improve well-known and important typicality results of quantum statistical mechanics to GAP measures, namely canonical typicality and dynamical typicality. Canonical typicality is the statement that for “most” pure states $$\psi $$ ψ of a given ensemble, the reduced density matrix of a sufficiently small subsystem is very close to a $$\psi $$ ψ -independent matrix. Dynamical typicality is the statement that for any observable and any unitary time evolution, for “most” pure states $$\psi $$ ψ from a given ensemble the (coarse-grained) Born distribution of that observable in the time-evolved state $$\psi _t$$ ψ t is very close to a $$\psi $$ ψ -independent distribution. So far, canonical typicality and dynamical typicality were known for the uniform distribution on finite-dimensional spheres, corresponding to the micro-canonical ensemble, and for rather special mean-value ensembles. Our result shows that these typicality results hold also for $${\textrm{GAP}}(\rho )$$ GAP ( ρ ) , provided the density matrix $$\rho $$ ρ has small eigenvalues. Since certain GAP measures are quantum analogs of the canonical ensemble of classical mechanics, our results can also be regarded as a version of equivalence of ensembles.

A Preliminary Investigation of Physical Education Teachers’ Perceptions on Pre-Teaching Students with Visual Impairments

Abstract Students with visual impairments (VI) are often left out of physical education classes because they are not provided with appropriate accommodations and instructional strategies by the teacher. Pre-teaching is a recommended method of instruction wherein students with visual impairments are exposed to a lesson prior to whole class instruction. However, little is known about the use of pre-teaching within the context of physical education. Thus, the purpose of this study was to investigate physical education teachers’ experiences using pre-teaching with students with visual impairments. Thirty-nine physical education teachers (ages 23–67 years) completed an electronic survey that measured their demographics and experiences with pre-teaching students with visual impairments. After analyzing the data, four major themes were found regarding pre-teaching: communication, resources, preparation, and time. Participants stressed the importance of communicating with both the student with a visual impairment and other professionals who serve the student. Furthermore, participants shared that they need more resources and time for pre-teaching students with visual impairments. The participants also expressed a lack of exposure to pre-teaching during their teacher preparation programs. Recommendations include increased education or professional development on pre-teaching and the use of self-contained classes to pre-teach students prior to general education classes.

Ανήκουν οι μαθητές με δυσκολίες μάθησης στις ομάδες παιχνιδιού των συμμαθητών τους ή σχηματίζουν δικές τους ομάδες κατά την διάρκεια του διαλείμματος;

The participation of the children in the play groups during recess gives them the opportunity to release the energy that has accumulated during the learning process, to come together and interact with children of the same age. The development of friendships between children with learning difficulties and typically developing children has been of distinctive research interest. Pupils with learning difficulties attend lessons in the general education classes and at the same time they attend specific lessons in the resource room of their school. As this condition does not guarantee their inclusion in the playgroups, the question was raised whether pupils with learning difficulties are ultimately included in the playgroups of their classmates during recess. The study involved 40 students who had been diagnosed with learning difficulties and were attending lessons in the resource room of their school. Data was collected based on consecutive observations and it was found that more than half of the students with learning difficulties did not participate in their peers" play.

Mpemba effect in pure spin systems : A universal picture of the role of spatial correlations at initial states.

The quicker freezing of hotter water, than a colder sample, when quenched to a common lower temperature, is referred to as the Mpemba effect (ME). While this counter-intuitive fact remains a surprize since long, efforts have begun to identify similar effect in other systems. We investigate the ME in a rather general context concerning magnetic phase transitions. From Monte Carlo simulations of model systems, viz., the Ising model and the q-state Potts model, with varying range of interaction and space dimension, we assert that hotter paramagnets undergo ferromagnetic ordering faster than the colder ones. This conclusion we have arrived at following the analyses of the simulation results on decay of energy and growth in ordering following quenches from different starting temperatures, to fixed final temperatures below the Curie points. The general observation, in all the considered models, without any element of frustration, is a crucial and important fact of our study. Furthermore, we have obtained an important scaling picture, on the strength of the effect, with respect to the variation in spatial correlation in the initial states. This behavior appears true irrespective of the nature of order-parameter fluctuation and even order of transition. The observations are expected to be relevant to the understanding of ME in a rather general class of systems.

Using personal development activities to improve learners’ well-being

Abstract During the semester of Oct 2022 to Feb 2023, I decided to incorporate personal development activities into my C1-level General English classes at an Ecuadorian teacher training university in the hope that it would positively impact my students’ well-being both in the present and in preparation for their future careers and lives beyond the classroom. This was only the second face-to-face semester after the COVID pandemic had forced us into online learning for two years, and many students were struggling with a whole host of issues affecting their lives and learning. Throughout the 16-week semester, I supplemented the textbook with various activities focusing on mental and physical health that I had come across in my own self-development journey. This article hopes to point to a possible way to weave well-being competencies into the English language curriculum, which practitioners elsewhere may be interested in applying in their own classrooms.

Solving nonlinear vectorial problems with a stable class of Jacobian-free iterative processes

In this manuscript, a general class of Jacobian-free iterative schemes for solving systems of nonlinear equations is presented. Once its fourth-order convergence is proven, the most efficient sub-family is selected in order to make a qualitative study. It is proven that the most of elements of this family are very stable, and this is checked by means on numerical tests on several problems of different sizes. Their performance is compared with other known Jacobian-free iterative procedure, being better in the most of results.

Well-posedness of a bulk-surface convective Cahn–Hilliard system with dynamic boundary conditions

We consider a general class of bulk-surface convective Cahn–Hilliard systems with dynamic boundary conditions. In contrast to classical Neumann boundary conditions, the dynamic boundary conditions of Cahn–Hilliard type allow for dynamic changes of the contact angle between the diffuse interface and the boundary, a convection-induced motion of the contact line as well as absorption of material by the boundary. The coupling conditions for bulk and surface quantities involve parameters K,L∈[0,∞]\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$K,L\\in [0,\\infty ]$$\\end{document}, whose choice declares whether these conditions are of Dirichlet, Robin or Neumann type. We first prove the existence of a weak solution to our model in the case K,L∈(0,∞)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$K,L\\in (0,\\infty )$$\\end{document} by means of a Faedo–Galerkin approach. For all other cases, the existence of a weak solution is then shown by means of the asymptotic limits, where K and L are sent to zero or to infinity, respectively. Eventually, we establish higher regularity for the phase-fields, and we prove the uniqueness of weak solutions given that the mobility functions are constant.

Variational Quantum Algorithms for Semidefinite Programming

A semidefinite program (SDP) is a particular kind of convex optimization problem with applications in operations research, combinatorial optimization, quantum information science, and beyond. In this work, we propose variational quantum algorithms for approximately solving SDPs. For one class of SDPs, we provide a rigorous analysis of their convergence to approximate locally optimal solutions, under the assumption that they are weakly constrained (i.e., N≫M, where N is the dimension of the input matrices and M is the number of constraints). We also provide algorithms for a more general class of SDPs that requires fewer assumptions. Finally, we numerically simulate our quantum algorithms for applications such as MaxCut, and the results of these simulations provide evidence that convergence still occurs in noisy settings.