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This work presents an omics-driven modeling pipeline that integrates machine-learning tools to facilitate the dynamic modeling of multiscale biological systems. Random forests and permutation feature importance are proposed to mine omics datasets, guiding feature selection and dimensionality reduction for dynamic modeling. Continuous and differentiable machine-learning functions can be trained to link the reduced omics feature set to key components of the dynamic model, resulting in a hybrid model. As proof of concept, we apply this framework to a high-dimensional proteomics dataset of $\textit{Saccharomyces cerevisiae}$. After identifying key intracellular proteins that correlate with cell growth, targeted dynamic experiments are designed, and key model parameters are captured as functions of the selected proteins using Gaussian processes. This approach captures the dynamic behavior of yeast strains under varying proteome profiles while estimating the uncertainty in the hybrid model's predictions. The outlined modeling framework is adaptable to other scenarios, such as integrating additional layers of omics data for more advanced multiscale biological systems, or employing alternative machine-learning methods to handle larger datasets. Overall, this study outlines a strategy for leveraging omics data to inform multiscale dynamic modeling in systems biology and bioprocess engineering.

We examine the distribution and popularity of different parameters (such as the number of descents, runs, valleys, peaks, right-to-left minima, and more) on the sets of increasing and flattened permutations. For each parameter, we provide an exponential generating function for its corresponding distribution and popularity.Additionally, we present one-to-one correspondences between these permutations and some classes of simpler combinatorial objects.

UniGlyph is a constructed language (conlang) designed to create a universal transliteration system using a script derived from seven-segment characters. The goal of UniGlyph is to facilitate cross-language communication by offering a flexible and consistent script that can represent a wide range of phonetic sounds. This paper explores the design of UniGlyph, detailing its script structure, phonetic mapping, and transliteration rules. The system addresses imperfections in the International Phonetic Alphabet (IPA) and traditional character sets by providing a compact, versatile method to represent phonetic diversity across languages. With pitch and length markers, UniGlyph ensures accurate phonetic representation while maintaining a small character set. Applications of UniGlyph include artificial intelligence integrations, such as natural language processing and multilingual speech recognition, enhancing communication across different languages. Future expansions are discussed, including the addition of animal phonetic sounds, where unique scripts are assigned to different species, broadening the scope of UniGlyph beyond human communication. This study presents the challenges and solutions in developing such a universal script, demonstrating the potential of UniGlyph to bridge linguistic gaps in cross-language communication, educational phonetics, and AI-driven applications., Comment: This submission includes 23 pages and tables. No external funding has been received for this research. Acknowledgments to Jeseentha V. for contributions to the phonetic study

Topological crystalline insulators (TCIs) host topological phases of matter protected by crystal symmetries. Topological surface states in three-dimensional TCIs have been predicted and observed in IV-VI SnTe-class semiconductors. Despite the prediction of a two-dimensional (2D) TCI characterized by two pairs of edge states inside the bulk gap, materials challenges have thus far prevented its experimental realization. Here we report the growth and characterization of bilayer SnTe on the 2$H$-NbSe$_2$ substrate by molecular beam epitaxy and scanning tunneling microscopy. We experimentally observe two anticorrelated, periodically modulated pairs of conducting edge states along the perimeters of the sample with a large band gap exceeding $0.2$ eV. We identify these states with a 2D TCI through first principles calculations. Finally, we probe the coupling of adjacent topological edge states and demonstrate the resulting energy shift driven by a combination of electrostatic interactions and tunneling coupling. Our work opens the door to investigations of tunable topological states in 2D TCIs, of potential impact for spintronics and nanoelectronics applications at room temperature.

The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

Super-moire materials represent a novel playground to engineer states of matter beyond the possibilities of conventional moire materials. However, from the computational point of view, understanding correlated matter in these systems requires solving models with several millions of atoms, a formidable task for state-of-the-art methods. Conventional wavefunction methods for correlated matter scale with a cubic power with the number of sites, a major challenge for super-moire materials. Here, we introduce a methodology capable of solving correlated states in super-moire materials by combining a kernel polynomial method with a quantics tensor cross matrix product state algorithm. This strategy leverages a mapping of the super-moire structure to a many-body Hilbert space efficiently sampled with a tensor cross matrix product state method, where individual evaluations are performed with a Chebyshev kernel polynomial algorithm. We demonstrate this approach with interacting super-moire systems with up to several millions of atoms, showing its ability to capture correlated states in moire-of-moire systems and domain walls between different moire systems. Our manuscript puts forward a widely applicable methodology to study correlated matter in ultra-long length scales, enabling rationalizing correlated super-moire phenomena., Comment: 11 pages, 5 figures

Topological phases of matter provide a flexible platform to engineer unconventional quantum excitations in quantum materials. Beyond single particle topological matter, in systems with strong quantum many-body correlations, many-body effects can be the driving force for non-trivial topology. Here, we propose a one-dimensional engineered Kondo lattice where the emergence of topological excitations is driven by collective many-body Kondo physics. We first show the existence of topological zero modes in this system by solving the interacting model with tensor networks, and demonstrate their robustness against disorder. To unveil the origin of the topological zero modes, we analyze the associated periodic Anderson model showing that it can be mapped to a topological non-Hermitian model, enabling rationalizing the origin of the topological zero modes. We finally show that the topological invariant of the many-body Kondo lattice can be computed with a correlation matrix pumping method directly with the exact quantum many-body wavefunction. Our results provide a strategy to engineer topological Kondo insulators, highlighting quantum magnetism as a driving force in engineering topological matter., Comment: 7+2 pages, 3 figures

This work presents a novel rehabilitation framework designed for a therapist, wearing an inertial measurement unit (IMU) suit, to virtually interact with a lower-limb exoskeleton worn by a patient with motor impairments. This framework aims to harmonize the skills and knowledge of the therapist with the capabilities of the exoskeleton. The therapist can guide the patient's movements by moving their own joints and making real-time adjustments to meet the patient's needs, while reducing the physical effort of the therapist. This eliminates the need for a predefined trajectory for the patient to follow, as in conventional robotic gait training. For the virtual interaction medium between the therapist and patient, we propose an impedance profile that is stiff at low frequencies and less stiff at high frequencies, that can be tailored to individual patient needs and different stages of rehabilitation. The desired interaction torque from this medium is commanded to a whole-exoskeleton closed-loop compensation controller. The proposed virtual interaction framework was evaluated with a pair of unimpaired individuals in different teacher-student gait training exercises. Results show the proposed interaction control effectively transmits haptic cues, informing future applications in rehabilitation scenarios.

Recent developments in very long baseline interferometry (VLBI) have made it possible for the Event Horizon Telescope (EHT) to resolve the innermost accretion flows of the largest supermassive black holes on the sky. The sparse nature of the EHT's $(u, v)$-coverage presents a challenge when attempting to resolve highly time-variable sources. We demonstrate that the changing (u, v)-coverage of the EHT can contain regions of time over the course of a single observation that facilitate dynamical imaging. These optimal time regions typically have projected baseline distributions that are approximately angularly isotropic and radially homogeneous. We derive a metric of coverage quality based on baseline isotropy and density that is capable of ranking array configurations by their ability to produce accurate dynamical reconstructions. We compare this metric to existing metrics in the literature and investigate their utility by performing dynamical reconstructions on synthetic data from simulated EHT observations of sources with simple orbital variability. We then use these results to make recommendations for imaging the 2017 EHT Sgr A* data set., Comment: 20 pages, 14 figures, published in ApJL (2022), uploaded for open access

Van der Waals monolayers featuring magnetic states provide a fundamental building block for artificial quantum matter. Here, we establish the emergence of a multicomponent ground state featuring magneto-orbital excitations of the 3d2-transition metal trihalide VCl3 monolayer. We show that monolayer VCl3 realizes a ground state with simultaneous magnetic and orbital ordering using density functional theory. Using first-principles methods we derive an effective Hamiltonian with intertwined spin and orbital degree of freedom, which we demonstrate can be tuned by strain. We show that magneto-orbitons appear as the collective modes of this complex order, and arise from coupled orbiton magnon excitations due to the magneto-orbital coupling in the system. Our results establish VCl3 as a promising 2D material to observe emergent magneto-orbital excitations and provide a platform for multicomponent symmetry breaking., Comment: 7 pages, 3 figures

Property~(A) is a week symmetry condition that plays a fundamental role in the characterization of greedy-type bases in the isometric case, i.e., when the constants involved in the study of the efficiency of the thresholding greedy algorithm in Banach spaces are sharp. In this note we build examples of Banach spaces with Schauder bases that have Property~(A) but fail to be unconditional, thus settling a long standing problem in the area. As a by-product of our work we hone our construction to produce counterexamples that solve other open questions in the isometric theory of greedy bases.

The aim of this paper is twofold. On the one hand, we manage to identify Banach-valued Hardy spaces of analytic functions over the disc $\mathbb{D}$ with other classes of Hardy spaces, thus complementing the existing literature on the subject. On the other hand, we develop new techniques that allow us to prove that certain Hilbert-valued atomic lattices have a unique unconditional basis, up to normalization, equivalence and permutation. Combining both lines of action we show that that $H_p(\mathbb{D},\ell_2)$ for $0

Predicting the phase diagram of interacting quantum many-body systems is a challenging problem in condensed matter physics. Strong interactions and correlation effects may lead to exotic states of matter, such as quantum spin liquids and unconventional superconductors, that often compete with other symmetry broken states including ordered magnets and charge density waves. Here, we put forward a formalism for determining the phase diagram of fermionic systems that combines recent progress in the field of Lee-Yang theories of phase transitions with many-body tensor-network methods. Using this strategy, we map out the phase diagram of a fermionic chain, where charge density waves form due to strong repulsion. Specifically, from the high cumulants of the order parameter, we extract the dominant zeros of the moment generating function in chains of finite size. By extrapolating their positions to the thermodynamic limit, we determine the boundaries between competing phases. Our formalism provides a strategy for determining critical points in fermionic systems, and it is based on fluctuations of the order parameter, which are measurable quantities., Comment: 9 pages, 6 figures

Twisted magnetic van der Waals materials provide a flexible platform to engineer new forms of unconventional magnetism. Here we demonstrate the emergence of electrically tunable topological moir\'e magnetism in twisted bilayers of the spin-spiral multiferroic NiI$_2$. We establish a rich phase diagram featuring uniform spiral phases, a variety of $k\pi$-skyrmion lattices, and nematic spin textures ordered at the moir\'e scale. The emergence of these phases is driven by the local stacking and the resulting modulated frustration in the spin spiral stemming from the moir\'e pattern. Notably, when the spin-spiral wavelength is commensurate with the moir\'e length scale by an integer $k$, multi-walled skyrmions become pinned to the moir\'e pattern. We show that the strong magnetoelectric coupling displayed by the moir\'e multiferroic allows the electric control of the $k\pi$-skyrmion lattices by an out-of-plane electric field, which couples to the moir\'e-induced electric polarization. While adiabatic changes in the electric field preserve the topology of the spin configurations, abrupt variations can trigger transitions between different skyrmion lattice ground states. Our results establish a highly tunable platform for skyrmionics based on twisted van der Waals multiferroics, potentially enabling a new generation of ultrathin topologically-protected spintronic devices., Comment: 8 pages, 4 figures

Competing interactions in quantum magnets lead to a variety of emergent states, including ordered phases, nematic magnets and quantum spin liquids. Among them, topological quantum magnets represent a promising platform to create topological excitations protected by the bulk many-body excitation gap. Here we establish the phase diagram of a breathing frustrated antiferromagnetic J1-J2-Heisenberg model, featuring both ordered states and a higher-order topological quantum magnet state. Using exact many-body methods based on neural network quantum states and tensor networks, we determine the existence of a first order phase transition between stripe order and the topological quantum magnet and the second order phase transition between the Neel order and quantum magnet phase, further corroborated by calculations of the many-body gap. Using an auxiliary fermion parton formalism, we show the emergence of topological spinon corner modes stemming from the breathing order parameter of the parent Heisenberg model. Our results establish the breathing frustrated square lattice Heisenberg model as a paradigmatic system to engineer topological quantum magnetism, as recently realized in Ti lattices at MgO., Comment: 4 figures

In this paper we solve some differential equations in the $D_h$ derivative in Ward's sense. We use a special metric in the formal power series ring $\K[[x]]$. The solutions of that equations are giving in terms of fixed points for certain contractive maps in our metric framework. Our main tools are Banach's Fixed Point Theorem, Fundamental Calculus Theorem and Barrow's rule for Ward's calculus. Later, we return to the usual differential calculus via Sheffer's expansion of some kind of operators. Finally, we give some examples related, in some sense, to combinatorics.

We present ultraviolet, optical and near-infrared photometric and optical spectroscopic observations of the luminous, fast blue optical transient (LFBOT), CSS161010:045834-081803 (CSS161010). The transient was found in a low-redshift (z=0.033) dwarf galaxy. The light curves of CSS161010 are characterized by an extremely fast evolution and blue colours. The V-band light curve shows that CSS161010 reaches an absolute peak of M$_{V}^{max}=-20.66\pm0.06$ mag in 3.8 days from the start of the outburst. After maximum, CSS161010 follows a power-law decline $\propto t^{-2.8\pm0.1}$ in all optical bands. These photometric properties are comparable to those of well-observed LFBOTs such as AT 2018cow, AT 2020mrf and AT 2020xnd. However, unlike these objects, the spectra of CSS161010 show a remarkable transformation from a blue and featureless continuum to spectra dominated by very broad, entirely blueshifted hydrogen emission lines of velocities of up to 10% of the speed of light. The persistent blueshifted emission and the lack of any emission at the rest wavelength of CSS161010 are unique features not seen in any transient before CSS161010. The combined observational properties of CSS161010 and its M$_{*}\sim10^{8}$ M$_\odot$ dwarf galaxy host favour the tidal disruption of a star by an intermediate-mass black hole as its origin., Comment: 29 pages (including the appendix); 8 figures in the main text, 4 figures and 8 tables in the appendix. Accepted for publication in ApJ

Many ligands commonly used to prepare nanoparticle catalysts with precise nanoscale features contain nitrogen (e.g., oleylamine); here, we found that the use of nitrogen-containing ligands during the synthesis of metal oxide nanoparticle catalysts substantially impacted product analysis during photocatalytic studies. We confirmed these experimental results via hybrid Density Functional Theory computations of the materials' electronic properties to evaluate their viability as photocatalysts for nitrogen reduction. This nitrogen ligand contamination, and subsequent interference in photocatalytic studies, is avoidable through the careful design of synthetic pathways that exclude nitrogen-containing constituents. This result highlights the urgent need for careful evaluation of catalyst synthesis protocols, as contamination by nitrogen-containing ligands may go unnoticed since the presence of nitrogen is often not detected or probed., Comment: 13 pages, 3 figures

Layered van der Waals two-dimensional (2D) magnets are a cornerstone of ultrathin spintronic and magnonic devices. The recent discovery of a 2D multiferroic with strong magnetoelectric coupling in NiI$_2$ offers a promising platform for the electrical control of spin-wave transport. In this work, using ab initio calculations, we investigate how the magnonic properties of monolayer NiI$_2$ can be controlled using an external electric field. We show that the emergence of a ferroelectric polarization leads to an energy splitting in the magnon spectrum, thus establishing a way to detect the electric polarization experimentally. We also show the modulation of the magnon splitting and the energy position of the singularities in magnon DOS by an electric field due to the strong magnetoelectric coupling. Our results highlight the interplay between ferroelectricity and magnons in van der Waals multiferroics and pave the way to design electrically tunable magnetic devices at the 2D limit.

We present results from MeerKAT single-dish HI intensity maps, the final observations to be performed in L-band in the MeerKAT Large Area Synoptic Survey (MeerKLASS) campaign. The observations represent the deepest single-dish HI intensity maps to date, produced from 41 repeated scans over $236\,{\rm deg}^2$, providing 62 hours of observational data for each of the 64 dishes before flagging. By introducing an iterative self-calibration process, the estimated thermal noise of the reconstructed maps is limited to ${\sim}\,1.21\,$mK ($1.2\,\times$ the theoretical noise level). This thermal noise will be sub-dominant relative to the HI fluctuations on large scales ($k\,{\lesssim}\,0.15\,h\,\text{Mpc}^{-1}$), which demands upgrades to power spectrum analysis techniques, particularly for covariance estimation. In this work, we present the improved MeerKLASS analysis pipeline, validating it on both a suite of mock simulations and a small sample of overlapping spectroscopic galaxies from the Galaxy And Mass Assembly (GAMA) survey. Despite only overlapping with ${\sim}\,25\%$ of the MeerKLASS deep field, and a conservative approach to covariance estimation, we still obtain a ${>}\,4\,\sigma$ detection of the cross-power spectrum between the intensity maps and the 2269 galaxies at the narrow redshift range $0.39\,{<}\,z\,{<}\,0.46$. We briefly discuss the HI auto-power spectrum from this data, the detection of which will be the focus of follow-up work. For the first time with MeerKAT single-dish intensity maps, we also present evidence of HI emission from stacking the maps onto the positions of the GAMA galaxies., Comment: 29 pages, 27 figures. See Fig.14 and 15 for auto-HI and HI-galaxy cross power spectra. Fig 19 and 20 for stacking detections. Submitted to MNRAS

Modeling and Simulation (M&S) is finding increasing application in development and testing of command and control systems comprised of information-intensive component systems. Achieving interoperability is one of the chief System of Systems (SoS) engineering objectives in the development of command and control (C2) capabilities for joint and coalition warfare. In this paper, we apply an SoS perspective on the integration of M&S with such systems. We employ recently developed interoperability concepts based on linguistic categories along with the Discrete Event System Specification (DEVS) formalism to implement a standard for interoperability. We will show how the developed standard is implemented in DEVS/SOA net-centric modeling and simulation framework that uses XML-based Service Oriented Architecture (SOA). We will discuss the simulator interfaces and the design issues in their implementation in DEVS/SOA. We will illustrate the application of DEVS/SOA in a multi-agent test instrumentation system that is deployable as a SOA., Comment: arXiv admin note: substantial text overlap with arXiv:2407.03686

We find conditions on a function space $\bf{L}$ that ensure that it behaves as an $L_p$-space in the sense that any unconditional basis of a complemented subspace of $\bf{L}$ either is equivalent to the unit vector system of $\ell_2$ or has a subbasis equivalent to a disjointly supported basic sequence. This dichotomy allows us to classify the symmetric basic sequences of $\bf{L}$. Several applications to Orlicz function spaces are provided., Comment: 36 pages

Modeling and Simulation (M&S) for system design and prototyping is practiced today both in the industry and academia. M&S are two different areas altogether and have specific objectives. However, most of the times these two separate areas are taken together. The developed code is tightly woven around both the model and the underlying simulator that executes it. This constraints both the model development and the simulation engine that impacts scalability of the developed code. Furthermore, a lot of time is spent in development of a model because it needs both domain knowledge and simulation techniques, which also requires communication among users and developers. Unified Modeling Language (UML) is widely accepted in the industry, whereas Discrete Event Specification (DEVS) based modeling that separates the model and the simulator, provides a cleaner methodology to develop models and is much used in academia. DEVS today is used by engineers who understand discrete event modeling at a much detailed level and are able to translate requirements to DEVS modeling code. There have been earlier efforts to integrate UML and DEVS but they haven't succeeded in providing a transformation mechanism due to inherent differences in these two modeling paradigms. This paper presents an integrated approach towards crosstransformations between UML and DEVS using the proposed eUDEVS, which stands for executable UML based on DEVS. Further, we will also show that the obtained DEVS models belong to a specific class of DEVS models called Finite Deterministic DEVS (FD-DEVS) that is available as a W3C XML Schema in XFD-DEVS. We also put the proposed eUDEVS in a much larger unifying framework called DEVS Unified Process that allows bifurcated model-continuity based lifecycle methodology for systems M&S. Finally, we demonstrate the laid concepts with a complete example.

Understanding the dynamics of open quantum many-body systems is a major problem in quantum matter. Specifically, efficiently solving the spectrum of the Liouvillian superoperator governing such dynamics remains a critical open challenge. Here, we put forward a method for solving the many-body Liouvillian spectrum and dynamics based on the non-Hermitian kernel polynomial method and tensor-network techniques. We demonstrate the faithfulness of our method by computing the dynamics of the dephasing quantum compass model with a gradient magnetic field and comparing it with exact results. In particular, we show that our method allows us to characterize the quantum Zeno crossover and the reduction of relaxation rate due to Stark localization in this model. We further demonstrate the ability of our method to go beyond exact results by exploring nearest-neighbor interaction effects on the Liouvillian dynamics, elucidating the interplay between Stark localization and many-body interactions. Our method provides an efficient solution to many-body Liouvillian spectrum and dynamics, establishing a methodology to explore large open quantum many-body systems., Comment: 5+5 pages, 4+3 figures. Source codes will be available at https://github.com/GUANGZECHEN/NHKPM.jl

Discrete EVent Specification (DEVS) environments are known to be implemented over middleware systems such as HLA, RMI, CORBA and others. DEVS exhibits concepts of systems theory and modeling and supports capturing the system behavior from the physical and behavioral perspectives. Further, they are implemented using Object-oriented languages like Java and C++. This research work uses the Java platform to implement DEVS over a Service Oriented Architecture (SOA) framework. Called the DEVS/SOA, the framework supports a development and testing environment known as DEVS Unified Process that is built on a model-continuity-based life cycle methodology. DEVS Unified Process allows DEVS-based Modeling and Simulation (M&S) over net-centric platforms using DEVS/SOA. This framework also provides the crucial feature of run-time composability of coupled systems using SOA. We describe the architecture and designs of the both the server and the client. The client application communicates with multiple servers hosting DEVS simulation services. These Simulation services are developed using the proposed symmetrical services architecture wherein the server can act as both a service provider and a service consumer contrary to the unidirectional client-server paradigm. We also discuss how this Services based architecture provides solutions for cross-platform distributed M&S. We demonstrate DEVS/SOA framework with a scenario of Joint Close Air Support specified in Business Process Modeling Notation (BPMN). We also provide a real-world application of Network health monitoring using DEVS/SOA layered architectural framework.

Carbon-based nanostructures possessing {\pi}-electron magnetism have attracted tremendous interest due to their great potential for nano spintronics. In particular, quantum chains with magnetic molecular units synthesized by on-surface reactions provide an ideal playground for investigating magnetic exchange interactions between localized spin components. Here, we present an extensive study of antiferromagnetic nanographene chains with the diazahexabenzocoronene molecule as the repeating unit. A combination of bond-resolved scanning tunneling microscopy, density functional theory and quantum spin models revealed their detailed structures and electronic and magnetic properties. We found that the antiferromagnetic chains host a collective state featuring gapped excitations for an even number of repeating units and one featuring a Kondo excitation for an odd number. Comparing with exact many-body quantum spin models, our molecular chains provide the realization of an entangled quantum Heisenberg model. Coupled with the tunability of the molecular building blocks, these systems can act as an ideal platform for the experimental realization of topological spin lattices.

For the last thirty years, several Dynamic Memory Managers (DMMs) have been proposed. Such DMMs include first fit, best fit, segregated fit and buddy systems. Since the performance, memory usage and energy consumption of each DMM differs, software engineers often face difficult choices in selecting the most suitable approach for their applications. This issue has special impact in the field of portable consumer embedded systems, that must execute a limited amount of multimedia applications (e.g., 3D games, video players and signal processing software, etc.), demanding high performance and extensive memory usage at a low energy consumption. Recently, we have developed a novel methodology based on genetic programming to automatically design custom DMMs, optimizing performance, memory usage and energy consumption. However, although this process is automatic and faster than state-of-the-art optimizations, it demands intensive computation, resulting in a time consuming process. Thus, parallel processing can be very useful to enable to explore more solutions spending the same time, as well as to implement new algorithms. In this paper we present a novel parallel evolutionary algorithm for DMMs optimization in embedded systems, based on the Discrete Event Specification (DEVS) formalism over a Service Oriented Architecture (SOA) framework. Parallelism significantly improves the performance of the sequential exploration algorithm. On the one hand, when the number of generations are the same in both approaches, our parallel optimization framework is able to reach a speed-up of 86.40x when compared with other state-of-the-art approaches. On the other, it improves the global quality (i.e., level of performance, low memory usage and low energy consumption) of the final DMM obtained in a 36.36% with respect to two well-known general-purpose DMMs and two state-of-the-art optimization methodologies.

The investigation of crystallographic, electronic, and magnetic characteristics, especially the mixed valences of Eu$^{2+}$ and Eu$^{3+}$ under pressure of a novel europium-based bismuth selenide compound, Eu$_4$Bi$_6$Se$_{13}$, presented. This new compound adopts a monoclinic crystal structure classified under the P$2_1$/m space group (#11). It exhibits distinctive structural features, including substantial Eu-Se coordination numbers, Bi-Se ladders, and linear chains of Eu atoms that propagate along the b-axis. Electronic resistivity assessments indicate that Eu$_{4}$Bi$_{6}$Se$_{13}$ exhibits weak metallic behaviors. Magnetic characterization reveals uniaxial magnetic anisotropy, with a notable spin transition at approximately 1.2 T when the magnetic field is oriented along the b-axis. This behavior, coupled with the specific Eu-Eu interatomic distances and the magnetic saturation observed at low fields, supports the identification of metamagnetic properties attributable to the flipping of europium spins. The Curie-Weiss analysis of the magnetic susceptibility measured both perpendicular and parallel to the b-axis and high-pressure partial fluorescence yield (PFY) results detected by X-ray absorption spectroscopy (XAS) reveal the tendency of the material to enter a mixed valent state where the trivalent state becomes more prominent with the pressure increase or temperature decrease., Comment: 22 pages 8 figures

The last mile of unsupervised domain adaptation (UDA) for semantic segmentation is the challenge of solving the syn-to-real domain gap. Recent UDA methods have progressed significantly, yet they often rely on strategies customized for synthetic single-source datasets (e.g., GTA5), which limits their generalisation to multi-source datasets. Conversely, synthetic multi-source datasets hold promise for advancing the last mile of UDA but remain underutilized in current research. Thus, we propose DEC, a flexible UDA framework for multi-source datasets. Following a divide-and-conquer strategy, DEC simplifies the task by categorizing semantic classes, training models for each category, and fusing their outputs by an ensemble model trained exclusively on synthetic datasets to obtain the final segmentation mask. DEC can integrate with existing UDA methods, achieving state-of-the-art performance on Cityscapes, BDD100K, and Mapillary Vistas, significantly narrowing the syn-to-real domain gap.

Inspired by the ancient spiral constructed by the greek philosopher Theodorus which is based on concatenated right triangles, we have created a spiral. In this spiral, called \emph{Fibonacci--Theodorus}, the sides of the triangles have lengths corresponding to Fibonacci numbers. Towards the end of the paper, we present a generalized method applicable to second-order recurrence relations. Our exploration of the Fibonacci--Theodorus spiral aims to address a variety of questions, showcasing its unique properties and behaviors. For example, we study topics such as area, perimeter, and angles. Notably, we establish a relationship between the ratio of two consecutive areas and the golden ratio, a pattern that extends to angles sharing a common vertex. Furthermore, we present some asymptotic results. For instance, we demonstrate that the sum of the first $n$ areas comprising the spiral approaches a multiple of the sum of the initial $n$ Fibonacci numbers. Moreover, we provide a sequence of open problems related to all spiral worked in this paper. Finally, in his work Hahn, Hahn observed a potential connection between the golden ratio and the ratio of areas between spines of lengths $\sqrt{F_{n+1}}$ and $\sqrt{F_{n+2}-1}$ and the areas between spines of lengths $\sqrt{F_{n}}$ and $\sqrt{F_{n+1}-1}$ in the Theodorus spiral. However, no formal proof has been provided in his work. In this paper, we provide a proof for Hahn's conjecture., Comment: Accepted for publication by Proceedings of Fibonacci Quarterly

In this paper, we explore some generalizations of a counting problem related to tilings in grids of size 2xn, which was originally posed as a question on Mathematics Stack Exchange (Question 3972905). In particular, we consider this problem for the product of two graphs G and P(n), where P(n) is the path graph of n vertices. We give explicit bivariate generating functions for some specific cases., Comment: In Proceedings GASCom 2024, arXiv:2406.14588

For the last thirty years, a large variety of memory allocators have been proposed. Since performance, memory usage and energy consumption of each memory allocator differs, software engineers often face difficult choices in selecting the most suitable approach for their applications. To this end, custom allocators are developed from scratch, which is a difficult and error-prone process. This issue has special impact in the field of portable consumer embedded systems, that must execute a limited amount of multimedia applications, demanding high performance and extensive memory usage at a low energy consumption. This paper presents a flexible and efficient simulator to study Dynamic Memory Managers (DMMs), a composition of one or more memory allocators. This novel approach allows programmers to simulate custom and general DMMs, which can be composed without incurring any additional runtime overhead or additional programming cost. We show that this infrastructure simplifies DMM construction, mainly because the target application does not need to be compiled every time a new DMM must be evaluated and because we propose a structured method to search and build DMMs in an object-oriented fashion. Within a search procedure, the system designer can choose the "best" allocator by simulation for a particular target application and embedded system. In our evaluation, we show that our scheme delivers better performance, less memory usage and less energy consumption than single memory allocators., Comment: arXiv admin note: substantial text overlap with arXiv:2403.04414

AI personal assistants deployed via robots or wearables require embodied understanding to collaborate with humans effectively. However, current Vision-Language Models (VLMs) primarily focus on third-person view videos, neglecting the richness of egocentric perceptual experience. To address this gap, we propose three key contributions. First, we introduce the Egocentric Video Understanding Dataset (EVUD) for training VLMs on video captioning and question answering tasks specific to egocentric videos. Second, we present AlanaVLM, a 7B parameter VLM trained using parameter-efficient methods on EVUD. Finally, we evaluate AlanaVLM's capabilities on OpenEQA, a challenging benchmark for embodied video question answering. Our model achieves state-of-the-art performance, outperforming open-source models including strong Socratic models using GPT-4 as a planner by 3.6%. Additionally, we outperform Claude 3 and Gemini Pro Vision 1.0 and showcase competitive results compared to Gemini Pro 1.5 and GPT-4V, even surpassing the latter in spatial reasoning. This research paves the way for building efficient VLMs that can be deployed in robots or wearables, leveraging embodied video understanding to collaborate seamlessly with humans in everyday tasks, contributing to the next generation of Embodied AI., Comment: Code available https://github.com/alanaai/EVUD

We present the Black Hole Explorer (BHEX), a mission that will produce the sharpest images in the history of astronomy by extending submillimeter Very-Long-Baseline Interferometry (VLBI) to space. BHEX will discover and measure the bright and narrow "photon ring" that is predicted to exist in images of black holes, produced from light that has orbited the black hole before escaping. This discovery will expose universal features of a black hole's spacetime that are distinct from the complex astrophysics of the emitting plasma, allowing the first direct measurements of a supermassive black hole's spin. In addition to studying the properties of the nearby supermassive black holes M87* and Sgr A*, BHEX will measure the properties of dozens of additional supermassive black holes, providing crucial insights into the processes that drive their creation and growth. BHEX will also connect these supermassive black holes to their relativistic jets, elucidating the power source for the brightest and most efficient engines in the universe. BHEX will address fundamental open questions in the physics and astrophysics of black holes that cannot be answered without submillimeter space VLBI. The mission is enabled by recent technological breakthroughs, including the development of ultra-high-speed downlink using laser communications, and it leverages billions of dollars of existing ground infrastructure. We present the motivation for BHEX, its science goals and associated requirements, and the pathway to launch within the next decade., Comment: Proceedings for SPIE Astronomical Telescopes and Instrumentation

This paper presents a trajectory optimization and control approach for the guidance of an orbital four-arm robot in extravehicular activities. The robot operates near the target spacecraft, enabling its arm's end-effectors to reach the spacecraft's surface. Connections to the target spacecraft can be established by the arms through specific footholds (docking devices). The trajectory optimization allows the robot path planning by computing the docking positions on the target spacecraft surface, along with their timing, the arm trajectories, the six degrees of freedom body motion, and the necessary contact forces during docking. In addition, the paper introduces a controller designed to track the planned trajectories derived from the solution of the nonlinear programming problem. A weighted controller formulated as a convex optimization problem is proposed. The controller is defined as the optimization of an objective function that allows the system to perform a set of tasks simultaneously. Simulation results show the application of the trajectory optimization and control approaches to an on-orbit servicing scenario., Comment: 8 pages. To be presented at the 15th IEEE International Conference on Mechanical and Aerospace Engineering (ICMAE)

The Robot Operating System (ROS) has significantly gained popularity among robotic engineers and researchers over the past five years, primarily due to its powerful infrastructure for node communication, which enables developers to build modular and large robotic applications. However, ROS presents a steep learning curve and lacks the intuitive usability of vendor-specific robotic Graphical User Interfaces (GUIs). Moreover, its modular and distributed nature complicates the control and monitoring of extensive systems, even for advanced users. To address these challenges, this paper proposes a highly adaptable and reconfigurable web-based GUI for intuitively controlling, monitoring, and configuring complex ROS-based robotic systems. The GUI leverages ROSBridge and roslibjs to ensure seamless communication with ROS systems via topics and services. Designed as a versatile platform, the GUI allows for the selective incorporation of modular features to accommodate diverse robotic systems and applications. An initial set of commonly used features in robotic applications is presented. To demonstrate its reconfigurability, the GUI was customized and tested for four industrial use cases, receiving positive feedback. The project's repository has been made publicly available to support the robotics community and lower the entry barrier for ROS in industrial applications., Comment: 14 pages, 12 figures, 3 tables

Although the basic idea behind the concept of a greedy basis had been around for some time, the formal development of a theory of greedy bases was initiated in 1999 with the publication of the article [S.~V.~Konyagin and V.~N.~Temlyakov, A remark on greedy approximation in Banach spaces, East J. Approx. 5 (1999), no. 3, 365--379]. The theoretical simplicity of the thresholding greedy algorithm became a model for a procedure widely used in numerical applications and the subject of greedy bases evolved very rapidly from the point of view of approximation theory. The idea of studying greedy bases and related greedy algorithms attracted also the attention of researchers with a classical Banach space theory background. From the more abstract point of functional analysis, the theory of greedy bases and its derivates evolved very fast as many fundamental results were discovered and new ramifications branched out. Hundreds of papers on greedy-like bases and several monographs have been written since the foundational paper mentioned above appeared. After twenty-five years, the theory is very much alive and it continues to be a very active research topic both for functional analysts and for researchers interested in the applied nature of nonlinear approximation alike. This is why we believe it is a good moment to gather a selection of 25 open problems (one per year since 1999!) whose solution would contribute to advance the state of art of this beautiful topic.

In the quest for better energy storage solutions, the role of designing effective electrodes is crucial. Previous research has shown that using materials like single-side fluorinated graphene can improve the stability of ion insertion in few-layer graphene (FLG), which is vital as we move beyond lithium-ion batteries. Alternatives such as sodium and potassium, which are more abundant on Earth, appear promising, but thorough studies on how these ions insert into electrodes in stages are still needed. Our research focuses on the initial three alkali (Li, Na, K) and alkaline (Be, Mg, Ca) earth metals. Using Density Functional Theory (DFT) with advanced calculations, we've investigated how these ions interact with modified graphene at various stages of insertion. This method provides more precise electrical data and has helped us understand the complex interactions involved. Specifically, we found a new site for ion insertion that is energetically favorable. We also explored how modifying the graphene surface affects ions of different sizes and charges and examined how the number of graphene layers influences these interactions. Our discoveries are crucial for developing new materials that could replace lithium-ion batteries and provide a foundation for adjusting electrical properties in battery design through ion staging and surface modifications.

Layered two-dimensional (2D) materials, particularly MX$_2$ transition metal dichalcogenides (TMDCs), where M represents Mo or W and X is S, Se, or Te, exhibit unique properties when configured into hetero- and homo-bilayers with diverse stacking arrangements. This study emphasizes the impact of "magic angles" in twisted homobilayers that lead to transformative Moir\'e patterns, crucial for manipulating material properties. Our computational analysis of heterostructures covered 30 combinations from six MX$_2$ types, revealing that both the materials' choice and stacking significantly affect stability and band gap energy (E$_g$). Notably, the MoTe$_2$/WSe$_2$ heterostructure with a 60$^{\circ}$ twist demonstrates a direct E$_g$, underscoring its potential in novel applications. In homobilayers, both fully relaxed and low-strain scenarios were examined across various stackings and twists. We found that optimal bilayers' E$_g$ is highly dependent on stacking alignment. Particularly, 1T-MoS$_2$, WS$_2$, and WSe$_2$ can exhibit direct or indirect E$_g$ under specific twisted conditions, with 1T-MoS$_2$ showing a capability to transition between semiconductor and conductor states. Specific "magic angles" at 17.9$^{\circ}$ and 42.1$^{\circ}$ in twisted WS$_2$ and WSe$_2$ bilayers form symmetrical Moir\'e patterns, enabling fine-tuning of E$_g$ through angle adjustments and influencing electronic band flatness. Compared to monolayers, these TMDC bilayers display enhanced stability, which can be strategically adjusted. The use of controlled twisted angles in these bilayers emerges as a powerful tool in materials engineering, offering precise control over various electronic properties.

In this work, we define flattened Catalan words as Catalan words whose runs of weak ascents have leading terms that appear in weakly increasing order. We provide generating functions, formulas, and asymptotic expressions for the number of flattened Catalan words based on the number of runs of ascents (descents), runs of weak ascents (descents), $\ell$-valleys, valleys, symmetric valleys, $\ell$-peaks, peaks, and symmetric peaks., Comment: arXiv admin note: substantial text overlap with arXiv:2404.05672

Contemporary quantum devices are reaching new limits in size and complexity, allowing for the experimental exploration of emergent quantum modes. However, this increased complexity introduces significant challenges in device tuning and control. Here, we demonstrate autonomous tuning of emergent Majorana zero modes in a minimal realization of a Kitaev chain. We achieve this task using cross-platform transfer learning. First, we train a tuning model on a theory model. Next, we retrain it using a Kitaev chain realization in a two-dimensional electron gas. Finally, we apply this model to tune a Kitaev chain realized in quantum dots coupled through a semiconductor-superconductor section in a one-dimensional nanowire. Utilizing a convolutional neural network, we predict the tunneling and Cooper pair splitting rates from differential conductance measurements, employing these predictions to adjust the electrochemical potential to a Majorana sweet spot. The algorithm successfully converges to the immediate vicinity of a sweet spot (within 1.5 mV in 67.6% of attempts and within 4.5 mV in 80.9% of cases), typically finding a sweet spot in 45 minutes or less. This advancement is a stepping stone towards autonomous tuning of emergent modes in interacting systems, and towards foundational tuning machine learning models that can be deployed across a range of experimental platforms.

We present an analysis of very early high-resolution spectroscopic observations of the Type II supernova (SN) 2024ggi, a nearby SN that occurred in the galaxy NGC 3621 at a distance of 7.24 Mpc ($z\approx0.002435$). These observations represent the earliest high-resolution spectra of a Type II SN ever made. We analyzed the very early-phase spectroscopic evolution of SN 2024ggi obtained in a short interval at 20.6 and 27.8 h after its discovery, or 26.6 and 33.8 h after the SN first light. Observations were obtained with the high-resolution spectrograph MIKE ($R \approx 22600 - 28000$) at the 6.5 m Magellan Clay Telescope, located at the Las Campanas Observatory, on the night of April 12, 2024 UT. We analyzed the evolution of ions of HI, HeI, HeII, NIII, CIII, SiIV, NIV and CIV detected across the spectra. We modeled these features with multiple Gaussian and Lorentzian profiles, and estimated their velocities and full widths at half maximum (FWHMs). The spectra show asymmetric emission lines of HI, HeII, CIV, and NIV that can be described by narrow Gaussian cores with broader Lorentzian wings, and symmetric narrow emission lines of HeI, NIII, and CIII. The emission lines of HeI are detected only in the first spectrum, indicating the rapid ionization of HeI to HeII. The narrow components of the emission lines show a systematic blueshift relative to their zero-velocity position, with an increase of $\sim18$ km s$^{-1}$ in the average velocity between the two epochs. The broad Lorentzian components show a blueshift in velocity relative to the narrow components, and a significant increase in the average velocity of $\sim103$ km s$^{-1}$. Such a rapid evolution and significant ionization changes in a short period of time were never observed before, and are probably a consequence of the radiative acceleration generated in the SN explosion., Comment: 9 pages, 6 figures, accepted for publication at A&A

This paper investigates a broad class of non-Gaussian measures, $ \mu_\Psi$, associated with a family of generalized Wright functions, $_m\Psi_q$. First, we study these measures in Euclidean spaces $\mathbb{R}^d$, then define them in an abstract nuclear triple $\mathcal{N}\subset\mathcal{H}\subset\mathcal{N}'$. We study analyticity, invariance properties, and ergodicity under a particular group of automorphisms. Then we show the existence of an Appell system which allows the extension of the non-Gaussian Hilbert space $L^2(\mu_\Psi)$ to the nuclear triple consisting of test functions' and distributions' spaces, $(\mathcal{N})^{1}\subset L^2(\mu_\Psi)\subset(\mathcal{N})_{\mu_\Psi}^{-1}$. Thanks to this triple, we can study Donsker's delta as a well-defined object in the space of distributions $(\mathcal{N})_{\mu_\Psi}^{-1}$.

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.

3D stacked technology has emerged as an effective mechanism to overcome physical limits and communication delays found in 2D integration. However, 3D technology also presents several drawbacks that prevent its smooth application. Two of the major concerns are heat reduction and power density distribution. In our work, we propose a novel 3D thermal-aware floorplanner that includes: (1) an effective thermal-aware process with 3 different evolutionary algorithms that aim to solve the soft computing problem of optimizing the placement of functional units and through silicon vias, as well as the smooth inclusion of active cooling systems and new design strategies,(2) an approximated thermal model inside the optimization loop, (3) an optimizer for active cooling (liquid channels), and (4) a novel technique based on air channel placement designed to isolate thermal domains have been also proposed. The experimental work is conducted for a realistic many-core single-chip architecture based on the Niagara design. Results show promising improvements of the thermal and reliability metrics, and also show optimal scaling capabilities to target future-trend many-core systems.

Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40 minutes, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises.

Managing energy efficiency under timing constraints is an interesting and big challenge. This work proposes an accurate power model in data centers for time-constrained servers in Cloud computing. This model, as opposed to previous approaches, does not only consider the workload assigned to the processing element, but also incorporates the need of considering the static power consumption and, even more interestingly, its dependency with temperature. The proposed model has been used in a multi-objective optimization environment in which the Dynamic Voltage and Frequency Scaling (DVFS) and workload assignment have been efficiently optimized.

For integer $k \geq 1$, let $S_k(n)$ denote the sum of the $k$th powers of the first $n$ positive integers $1^k + 2^k + \cdots + n^k$. In this paper, we derive a new formula expressing $2^{2k}$ times $S_{2k}(n)$ as a sum of $k$ terms involving the numbers in the $k$th row of the integer sequence A304330, which is closely related to the central factorial numbers of the second kind with even indices. Furthermore, we provide an alternative proof of Knuth's formula for $S_{2k}(n)$ and show that it can equally be expressed in terms of A304330. We also deduce the corresponding formulas for the odd-indexed power sums $S_{2k-1}(n)$. Finally, we determine the Faulhaber form of $S_{2k}(n)$ and $S_{2k+1}(n)$ in terms of the sequence A304330 and the Legendre-Stirling numbers of the first kind., Comment: 20 pages