We present models of topological insulating Hamiltonians exhibiting intrinsic altermagnetic features, protected by combined three-fold or four-fold rotational symmetries with time-reversal. We demonstrate that the spin Chern number serves as a robust topological invariant in two-dimensional systems, while for three-dimensional structures, the topological nature is characterized by the spin Chern numbers computed on the $k_z$=$0$ and $k_z$=$\pi$ planes. The resulting phases support symmetry-protected boundary modes, including corner, hinges and surface states, whose structure is determined by the magnetic symmetry and the local magnetic moments. Our findings bridge the fields of altermagnetism and topological quantum matter, and establish a theoretical framework for engineering spintronic topological systems without net magnetization.

Altermagnets (AM) are a recently discovered third class of collinear magnets, distinctly different from conventional ferromagnets (FM) and antiferromagnets (AF). AM have been actively researched in the last few years, but two aspects so far remain unaddressed: (1) Are there realistic 2D single-layer altermagnets? And (2) is it possible to functionalize a conventional AF into AM by external stimuli? In this paper we address both issues by demonstrating how a well-known 2D AF, MnP(S,Se)$_3$ can be functionalized into strong AM by applying out-of-plane electric field. Of particular interest is that the induced altermagnetism is of a higher even-parity wave symmetry than expected in 3D AM with similar crystal symmetries. We confirm our finding by first-principles calculations of the electronic structure and magnetooptical response. We also propose that recent observations of the time-reversal symmetry breaking in the famous Fe-based superconducting chalchogenides, either in monolayer form or in the surface layer, may be related not to an FM, as previously assumed, but to the induced 2D AM order. Finally, we show that monolayer FeSe can simultaneously exhibit unconventional altermagnetic time-reversal symmetry breaking and quantized spin Hall conductivity indicating possibility to research an intriquing interplay of 2D altermagnetism with topological and superconducting states within a common crystal-potential environment.

Electrical spin-current generation is among the core phenomena driving the field of spintronics. Using {\em ab initio} calculations we show that a room-temperature metallic collinear antiferromagnet RuO$_2$ allows for highly efficient spin-current generation, arising from anisotropically-split bands with conserved up and down spins along the N\'eel vector axis. The zero net moment antiferromagnet acts as an electrical spin-splitter with a 34$^\circ$ propagation angle between spin-up and spin-down currents. Correspondingly, the spin-conductivity is a factor of three larger than the record value from a survey of 20,000 non-magnetic spin-Hall materials. We propose a versatile spin-splitter-torque concept utilizing antiferromagnetic RuO$_2$ films interfaced with a ferromagnet.

The ActivityNet Large Scale Activity Recognition Challenge 2017 Summary: results and challenge participants papers.

Ergonomic risk assessment is now, due to an increased awareness, carried out more often than in the past. The conventional risk assessment evaluation, based on expert-assisted observation of the workplaces and manually filling in score tables, is still predominant. Data analysis is usually done with a focus on critical moments, although without the support of contextual information and changes over time. In this paper we introduce ErgoExplorer, a system for the interactive visual analysis of risk assessment data. In contrast to the current practice, we focus on data that span across multiple actions and multiple workers while keeping all contextual information. Data is automatically extracted from video streams. Based on carefully investigated analysis tasks, we introduce new views and their corresponding interactions. These views also incorporate domain-specific score tables to guarantee an easy adoption by domain experts. All views are integrated into ErgoExplorer, which relies on coordinated multiple views to facilitate analysis through interaction. ErgoExplorer makes it possible for the first time to examine complex relationships between risk assessments of individual body parts over long sessions that span multiple operations. The newly introduced approach supports analysis and exploration at several levels of detail, ranging from a general overview, down to inspecting individual frames in the video stream, if necessary. We illustrate the usefulness of the newly proposed approach applying it to several datasets.

The anomalous Nernst effect generates transverse voltage to the applied thermal gradient in magnetically ordered systems. The effect was previously considered excluded in compensated magnetic materials with collinear ordering. However, in the recently identified class of compensated magnetic materials, dubbed altermagnets, time-reversal symmetry breaking in the electronic band structure makes the presence of the anomalous Nernst effect possible despite the collinear spin arrangement. In this work, we investigate epitaxial Mn5Si3 thin films known to be an altermagnetic candidate. We show that the material manifests a sizable anomalous Nernst coefficient despite the small net magnetization of the films. The measured magnitudes of the anomalous Nernst coefficient reach a scale of microVolts per Kelvin. We support our magneto-thermoelectric measurements by density-functional theory calculations of the material's spin-split electronic structure, which allows for the finite Berry curvature in the reciprocal space. Furthermore, we present our calculations of the intrinsic Berry-curvature Nernst conductivity, which agree with our experimental observations.

Foundation models hold promise for transforming AI in healthcare by providing modular components that are easily adaptable to downstream healthcare tasks, making AI development more scalable and cost-effective. Structured EHR foundation models, trained on coded medical records from millions of patients, demonstrated benefits including increased performance with fewer training labels, and improved robustness to distribution shifts. However, questions remain on the feasibility of sharing these models across different hospitals and their performance for local task adaptation. This multi-center study examined the adaptability of a recently released structured EHR foundation model ($FM_{SM}$), trained on longitudinal medical record data from 2.57M Stanford Medicine patients. Experiments were conducted using EHR data at The Hospital for Sick Children and MIMIC-IV. We assessed both adaptability via continued pretraining on local data, and task adaptability compared to baselines of training models from scratch at each site, including a local foundation model. We evaluated the performance of these models on 8 clinical prediction tasks. In both datasets, adapting the off-the-shelf $FM_{SM}$ matched the performance of GBM models locally trained on all data while providing a 13% improvement in settings with few task-specific training labels. With continued pretraining on local data, label efficiency substantially improved, such that $FM_{SM}$ required fewer than 1% of training examples to match the fully trained GBM's performance. Continued pretraining was also 60 to 90% more sample-efficient than training local foundation models from scratch. Our findings show that adapting shared EHR foundation models across hospitals provides improved prediction performance at less cost, underscoring the utility of base foundation models as modular components to streamline the development of healthcare AI.

Based on results in finite geometry we prove the existence of MRD codes in (F_q)_(n,n) with minimum distance n which are essentially different from Gabidulin codes. The construction results from algebraic structures which are closely related to those of finite fields. Some of the results may be known to experts, but to our knowledge have never been pointed out explicitly in the literature.

The 3rd annual installment of the ActivityNet Large- Scale Activity Recognition Challenge, held as a full-day workshop in CVPR 2018, focused on the recognition of daily life, high-level, goal-oriented activities from user-generated videos as those found in internet video portals. The 2018 challenge hosted six diverse tasks which aimed to push the limits of semantic visual understanding of videos as well as bridge visual content with human captions. Three out of the six tasks were based on the ActivityNet dataset, which was introduced in CVPR 2015 and organized hierarchically in a semantic taxonomy. These tasks focused on tracing evidence of activities in time in the form of proposals, class labels, and captions. In this installment of the challenge, we hosted three guest tasks to enrich the understanding of visual information in videos. The guest tasks focused on complementary aspects of the activity recognition problem at large scale and involved three challenging and recently compiled datasets: the Kinetics-600 dataset from Google DeepMind, the AVA dataset from Berkeley and Google, and the Moments in Time dataset from MIT and IBM Research.

Hierarchies are the hidden backbones of complex systems and their analysis allows for a deeper understanding of their structure and how they evolve. We consider languages also to be complex adaptive systems with several intricate networks that capture their structure and function. Hence, we decided to analyze the hierarchical organization of historical syntactic networks to understand how syntax evolves over time. We created these networks from a corpus of German texts from the 11th to 17th centuries, focusing on the hierarchical levels of these networks. diachronically and to map them to specific communicative needs of speakers. We developed a framework to empirically track the emergence of syntactic structures diachronically, enabling us to map the communicative needs of speakers with these structures. We named these syntactic structures "syntactic communicative hierarchies." We showed that the communicative needs of speakers are the organizational force of syntax. Thus, we argue that the emergence of syntactic communicative hierarchies plays a crucial role in shaping syntax over time. This may indicate that languages evolve not only to increase the efficiency of transferring information, but also to increase our capacity, as a species, to communicate our needs with more and more sophisticated abstractions.

We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.

Electrical manipulation of magnetization is essential for integration of magnetic functionalities such as magnetic memories and magnetic logic devices into electronic circuits. The current induced spin-orbit torque (SOT) in heavy metal/ferromagnet (HM/FM) bilayers via the spin Hall effect in the HM and/or the Rashba effect at the interfaces provides an efficient way to switch the magnetization. In the meantime, current induced SOT has also been used to switch the in-plane magnetization in single layers such as ferromagnetic semiconductor (Ga,Mn)As and antiferromagnetic metal CuMnAs with globally or locally broken inversion symmetry. Here we demonstrate the current induced perpendicular magnetization switching in L10 FePt single layer. The current induced spin-orbit effective fields in L10 FePt increase with the chemical ordering parameter (S). In 20 nm FePt films with high S, we observe a large charge-to-spin conversion efficiency and a switching current density as low as 7.0E6 A/cm2. We anticipate our findings may stimulate the exploration of the spin-orbit torques in bulk perpendicular magnetic anisotropic materials and the application of high-efficient perpendicular magnetization switching in single FM layer.

We consider the bail-out optimal dividend problem under fixed transaction costs for a L\'evy risk model. Furthermore, we consider the version with a constraint expected net present value of injected capital. To characterize the solution to the aforementioned models, we first solve the bail-out optimal dividend problem under transaction costs and capital injection and show the optimality of reflected (c1; c2)- policies. Next, we introduce the dual Lagrangian problem and show that the complementary slackness conditions are satisfied, characterizing the optimal Lagrange multiplier. Finally, we illustrate our findings with a series of numerical examples.

Electrons, commonly moving along the applied electric field, acquire in certain magnets a dissipationless transverse velocity. This spontaneous Hall effect, discovered more than a century ago, has been understood in terms of the time-reversal symmetry breaking by the internal spin-structure of a ferromagnetic, noncolinear antiferromagnetic or skyrmionic form. Here we identify previously overlooked robust Hall effect mechanism arising from collinear antiferromagnetism combined with nonmagnetic atoms at non-centrosymmetric positions. We predict a large magnitude of this crystal Hall effect in a room-temperature collinear antiferromagnet RuO$_2$ and catalogue, based on our symmetry rules, extensive families of material candidates. We show that the crystal Hall effect is accompanied by the possibility to control its sign by the crystal chirality. We illustrate that accounting for the full magnetization density distribution instead of the simplified spin-structure sheds new light on symmetry breaking phenomena in complex magnets and opens an alternative avenue towards quantum materials engineering for low-dissipation nanoelectronics.

The anomalous Hall effect, commonly observed in metallic magnets, has been established to originate from the time-reversal symmetry breaking by an internal macroscopic magnetization in ferromagnets or by a non-collinear magnetic order. Here we observe a spontaneous anomalous Hall signal in the absence of an external magnetic field in an epitaxial film of MnTe, which is a semiconductor with a collinear antiparallel magnetic ordering of Mn moments and a vanishing net magnetization. The anomalous Hall effect arises from an unconventional phase with strong time-reversal symmetry breaking and alternating spin polarization in real-space crystal structure and momentum-space electronic structure. The anisotropic crystal environment of magnetic Mn atoms due to the non-magnetic Te atoms is essential for establishing the unconventional phase and generating the anomalous Hall effect.

The quantum nature of electron spin is crucial for establishing topological invariants in real materials. Since the spin does not in general commute with the Hamiltonian, some of the topological features of the material can be extracted from its study. In insulating materials, the spin operator induces a projected operator on valence states called the spin valence operator. Its spectrum contains information with regard to the different phases of the spin Chern class. If the spin valence spectrum is gapped, the spin Chern numbers are constant along parallel planes thus defining spin Chern insulating materials. If the spin valence spectrum is not gapped, the changes in the spin Chern numbers occur whenever this spectrum is zero. Materials whose spin valence spectrum is gapless will be denoted spin Weyl topological insulators and their definition together with some of their properties will be presented in this work. The classification of materials from the properties of the spin valence operator provides a characterization that complements the existing list of topological invariants.

This work explores the topological properties of altermagnets, a novel class of collinear magnetic materials. We employ equivariant K-theory of magnetic groups and Hamiltonian models to formulate a robust $C^z_4 \mathbb{T}$ topological invariant to classify 2D and 3D altermagnetic systems. Our findings demonstrate that the spin Chern number serves as a robust topological index, corresponding to the half-quantized Chern number of the divided Brillouin zone. This indicator enables the prediction of a topologically protected 2D altermagnetic insulators and 3D Weyl altermagnetic semimetals, highlighting the relationship between altermagnetism and topological phases. Furthermore, our results provide a pathway to the exploration of topological applications in $d$-wave altermagnetic materials.

Bismuth Telluride (Bi$_2$Te$_3$) is a widely studied topological insulator, recognized for its unique surface states, low electronic bandgap, and low thermal conductivity. In this study, we characterize exfoliated Bi$_2$Te$_3$ dispersions produced via solvothermal intercalation, where ferromagnetism was measured at room temperature. DFT simulations show that this ferromagnetic behavior is attributed to the presence of vacancies and antisites in both the bulk material and the exfoliated crystals. Additionally, the DFT results were complemented by experimental measurements of the optical bandgap using UV-Vis spectroscopy, revealing a broadening of the bandgap as the material becomes thinner.

Altermagnetism, a recently proposed and experimentally confirmed class of magnetic order, features collinear compensated magnetism with unconventional d-, g-, or i-wave spin order. Here, we show that in a metallic 2D d-wave altermagnet with combined two-fold spin and four-fold lattice rotational symmetry $[C_2||C_4]$, secondary instabilities can arise. Using an unbiased functional renormalization group approach, we analyze the weak-coupling instabilities of a 2D Hubbard model with a preexisting altermagnetic order inspired by our ab initio electronic structure calculations of realistic material candidates from V$_2$X$_2$O (X = Te, Se) family. We identify two distinct spin density wave (SDW) states that break the underlying altermagnetic $[C_2||C_4]$ symmetry. Additionally, we find spin-fluctuation-induced instabilities leading to a singlet d-wave superconducting state and an unconventional commensurate pair density wave (PDW) state with extended s-wave and spin-triplet symmetry. We establish a general criterion for the unusual exchange statistics for these pair density waves and characterize their excitation spectrum, which exhibits Bogoliubov Fermi surfaces or nodal points depending on the gap size.

In this paper, we propose to use a twisted dihedral group algebra for public-key cryptography. For this, we introduce a new $2$-cocycle $\alpha_{\lambda}$ to twist the dihedral group algebra. Using the ambient space $\mathbb{F}^{\alpha_{\lambda}} D_{2n}$, we then introduce a key exchange protocol and present an analysis of its security. Moreover, we explore the properties of the resulting twisted algebra $\mathbb{F}^{\alpha_{\lambda}}D_{2n}$, exploiting them to enhance our key exchange protocol. We also introduce a probabilistic public-key scheme derived from our key-exchange protocol and obtain a key encapsulation mechanism (KEM) by applying a well-known generic transformation to our public-key scheme. Finally, we present a proof-of-concept implementation of the resulting key encapsulation mechanism.