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Altermagnetic materials have attracted a lot of attention recently due to the numerous effects, which have an application potential and occur due to the spin-split band structure coexisting with the compensated magnetic order. Incorporation of such intriguing compounds into low-dimensional structures represents an important avenue towards exploiting and enhancing their functionalities. Prominent examples of this group are semiconductors well suited to the band-gap engineering strategies. Here, we present for the first time visible-light-emitting CdSe quantum wells, in which wurtzite MnSe as an alermagnetic candidate plays the role of a barrier. Photoluminescence experiments with temporal resolution demonstrate that in such quantum wells, a built-in electric field is present and strongly influences the energies of the emitted photons, the dynamics of recombination, and excitation power dependence. Numerical simulations allow us to estimate that the magnitude of the electric field is 14MV/m. We anticipate that such quantum wells offer potential to probe the barrier properties and that wurtzite MnSe is an interesting platform to study the interplay of the altermagnetism and built-in e

Low-temperature luminescence spectra reveal the presence of two independant populations of GaN excitons within a $\mathrm{GaN/AlGaN/GaN/Al_2O_3}$ heterostructure in which a thick (1.5 $\mathrm{μm}$) AlGaN layer separates a thin (150 nm) top GaN layer and a thick (3.5 $\mathrm{μm}$) bottom GaN layer grown on sapphire. The presence of these two spectrally-distinct families of excitons in each GaN layer of the heterostructure is demonstrated using three different experimental methods: (i) low-power $\mathrmμ$-photoluminescence ($\mathrm{μPL}$) using laser excitation sources with wavelengths above and below the AlGaN bandgap, (ii) $\mathrm{μPL}$ as a function of optically injected free carrier density, and (iii) quantitative numerical simulation of the $\mathrmμ$-Reflectivity ($\mathrm{μR}$). One major impact of the built-in electric field is the reduction of the excitonic lifetime in the GaN surface layer, which transitions from less than 10 ps in the presence of the built-in electric field to the bulk lifetime (90 ps) when the field is screened. This increase in the excitonic lifetime is related to the modification of the band structure in the presence of optically injected free carr

Multimodal image fusion enables precise lesion localization and characterization for accurate diagnosis, thereby strengthening clinical decision-making and driving its growing prominence in medical imaging research. A powerful multimodal image fusion model relies on high-quality, clinically representative multimodal training data and a rigorously engineered model architecture. Therefore, the development of such professional radiomics models represents a collaborative achievement grounded in standardized acquisition, clinical-specific expertise, and algorithmic design proficiency, which necessitates protection of associated intellectual property rights. However, current multimodal image fusion models generate fused outputs without built-in mechanisms to safeguard intellectual property rights, inadvertently exposing proprietary model knowledge and sensitive training data through inference leakage. For example, malicious users can exploit fusion outputs and model distillation or other inference-based reverse engineering techniques to approximate the fusion performance of proprietary models. To address this issue, we propose AMIF, the first Authorizable Medical Image Fusion model with

While gesture recognition using vision or robot skins is an active research area in Human-Robot Collaboration (HRC), this paper explores deep learning methods relying solely on a robot's built-in joint sensors, eliminating the need for external sensors. We evaluated various convolutional neural network (CNN) architectures and collected a dataset to study the impact of data representation and model architecture on the recognition accuracy. Our results show that spectrogram-based representations significantly improve accuracy, while model architecture plays a smaller role. We also tested generalization to new robot poses, where spectrogram-based models performed better. Implemented on a Franka Emika Research robot, two of our methods, STFT2DCNN and STT3DCNN, achieved over 95% accuracy in contact detection and gesture classification. These findings demonstrate the feasibility of external-sensor-free tactile recognition and promote further research toward cost-effective, scalable solutions for HRC.

Strain engineering is an efficient tool to tune and tailor the electrical and optical properties of 2D materials. The built-in strain can be tuned during the synthesis process of a two dimensional semiconductor, as molybdenum disulfide, by employing different growth substrate with peculiar thermal properties. In this work we demonstrate that the built-in strain of MoS2 monolayers, grown on SiO2/Si substrate using liquid precursors chemical vapor deposition, is mainly dominated by the size of the monolayer. In fact, we identify a critical size equal to 20 um, from which the built-in strain increases drastically. The built-in strain is maximized for 60 um sized monolayer, leading to 1.2% tensile strain with a partial release of strain close to the monolayer triangular vertexes due to formation of nanocracks. These findings also imply that the standard method for evaluation of the number of layers based on the Raman modes separation becomes unreliable for monolayer with a lateral size above 20 um.

Customized built-in elements in HTML5 significantly transform web development. These elements enable developers to create unique HTML components tailored with specific design and purpose. Customized built-in elements enable developers to address the unique needs of web applications more quickly, supporting consistent user interfaces and experiences across diverse digital platforms. This study investigates the role of these features in Component-Based Software Engineering (CBSE) and Design Systems, emphasizing the benefits of code modularity, reusability, and scalability in web development. Customized built-in elements enable developers to address the unique needs of web applications more quickly, supporting consistent user interfaces and experiences across diverse digital platforms. The paper also discusses the difficulties and concerns that must be addressed when creating customized built-in elements, such as browser compatibility, performance optimization, accessibility, security, styling, and interoperability. It emphasizes the importance of standardization, developer tooling, and community interaction in order to fully realize the potential of these features. Looking ahead, cus

A convincing feature of least-squares finite element methods is the built-in a posteriori error estimator for any conforming discretization. In order to generalize this property to discontinuous finite element ansatz functions, this paper introduces a least-squares principle on piecewise Sobolev functions by the example of the Poisson model problem with mixed boundary conditions. It allows for fairly general discretizations including standard piecewise polynomial ansatz spaces on triangular and polygonal meshes. The presented scheme enforces the interelement continuity of the piecewise polynomials by additional least-squares residuals. A side condition on the normal jumps of the flux variable requires a vanishing integral mean and enables the penalization of the jump with the natural power of the mesh size in the least-squares functional. This avoids over-penalization with additional regularity assumptions on the exact solution as usually present in the literature on discontinuous LSFEM. The proof of the built-in a posteriori error estimation for the over-penalized scheme is presented as well. All results in this paper are robust with respect to the size of the domain guaranteed by

We present Chunked Augmented Generation (CAG), an architecture specifically designed to overcome the context window limitations of Google Chrome's built-in Gemini Nano model. While Chrome's integration of Gemini Nano represents a significant advancement in bringing AI capabilities directly to the browser, its restricted context window poses challenges for processing large inputs. CAG addresses this limitation through intelligent input chunking and processing strategies, enabling efficient handling of extensive content while maintaining the model's performance within browser constraints. Our implementation demonstrates particular efficacy in processing large documents and datasets directly within Chrome, making sophisticated AI capabilities accessible through the browser without external API dependencies. Get started now at https://github.com/vivekVells/cag-js.

Ionic crystals terminated at oppositely charged polar surfaces are inherently unstable and expected to undergo surface reconstructions to maintain electrostatic stability. Essentially, an electric field that arises between oppositely charged atomic planes gives rise to a built-in potential that diverges with thickness. In ultra thin film form however the polar crystals are expected to remain stable without necessitating surface reconstructions, yet the built-in potential has eluded observation. Here we present evidence of a built-in potential across polar \lao ~thin films grown on \sto ~substrates, a system well known for the electron gas that forms at the interface. By performing electron tunneling measurements between the electron gas and a metallic gate on \lao ~we measure a built-in electric field across \lao ~of 93 meV/Å. Additionally, capacitance measurements reveal the presence of an induced dipole moment near the interface in \sto, illuminating a unique property of \sto ~substrates. We forsee use of the ionic built-in potential as an additional tuning parameter in both existing and novel device architectures, especially as atomic control of oxide interfaces gains widespread

Built-in electric fields across heterojunctions between semiconducting materials underpin the functionality of modern device technologies. Heterojunctions between semiconductors and epitaxially grown crystalline oxides provide a rich setting in which built-in fields can be explored. Here, we present an electrical transport and hard X-ray photoelectron spectroscopy study of epitaxial SrNbxTi1-xO3-δ / Si heterojunctions. A non-monotonic anomaly in the sheet resistance is observed near room temperature, which is accompanied by a crossover in sign of the Hall resistance. The crossover is consistent with the formation of a hole gas in the Si and the presence of a built-in field. Hard X-ray photoelectron spectroscopy measurements reveal pronounced asymmetric features in both the SrNbxTi1-xO3-δ and Si core-level spectra that we show arise from built-in fields. The extended probe depth of hard X-ray photoelectron spectroscopy enables band bending across the SrNbxTi1-xO3-δ / Si heterojunction to be spatially mapped. Band alignment at the interface and surface depletion in SrNbxTi1-xO3-δ are implicated in the formation of the hole gas and built-in fields. Control of charge transfer and built

Ultrafiltration membrane modules suffer from a permeate flow decrease arising during filtration and caused by concentration polarization and fouling in, e.g., fermentation broth purification. Such performance losses are frequently mitigated by manipulating the hydrodynamic conditions at the membrane-fluid interface using, e.g., mesh spacers acting as static mixers. This additional element increases manufacturing complexity while improving mass transport in general, yet accepting their known disadvantages such as less transport in dead zones. However, the shape of such spacers is limited to the design of commercially available spacer geometries. Here, we present a methodology to design an industrially relevant mini-module with an optimized built-in 3D spacer structure in a flat-sheet ultrafiltration membrane module to eliminate the spacer as a separate part. Therefore, the built-in structures have been conceptually implemented through an in-silico design in compliance with the specifications for an injection molding process. Ten built-in structures were investigated in a digital twin of the mini-module by 3D-CFD simulations to select two options, which were then compared to the empt

Property-based testing is a powerful method to validate program correctness. It is, however, not widely use in industry as the barrier of entry can be very high. One of the hindrances is to write the generators that are needed to generate randomised input data. Program properties often take complicated data structures as inputs and, it requires a significant amount of effort to write generators for such structures in a invariant preserving way. In this paper, we suggest and formalise a new programming language \textsf{pun}; a simple functional programming with properties as a built-in mechanism for program validation. We show how to generate input for \textsf{pun} properties automatically, thus, providing the programmer with a low barrier of entry for using property-based testing. We evaluate our work a on library for binary search trees and compare the test results to a similar library in Haskell.

We analyse a sequential contest with two players in darts where one of the contestants enjoys a technical advantage. Using methods from the causal machine learning literature, we analyse the built-in advantage, which is the first-mover having potentially more but never less moves. Our empirical findings suggest that the first-mover has an 8.6 percentage points higher probability to win the match induced by the technical advantage. Contestants with low performance measures and little experience have the highest built-in advantage. With regard to the fairness principle that contestants with equal abilities should have equal winning probabilities, this contest is ex-ante fair in the case of equal built-in advantages for both competitors and a randomized starting right. Nevertheless, the contest design produces unequal probabilities of winning for equally skilled contestants because of asymmetries in the built-in advantage associated with social pressure for contestants competing at home and away.

The ability to engineer atomically thin nanoscale lateral heterojunctions (HJs) is critical to lay the foundation for future two-dimensional (2D) device technology. However, the traditional approach to creating a heterojunction by direct growth of a heterostructure of two different materials constrains the available band offsets, and it is still unclear if large built-in potentials are attainable for 2D materials. The electronic properties of atomically thin semiconducting transition metal dichalcogenides (TMDs) are not static, and their exciton binding energy and quasiparticle band gap depend strongly on the proximal environment. Recent studies have shown that this effect can be harnessed to engineer the lateral band profile of monolayer TMDs to create a heterojunction. Here we demonstrate the synthesis of a nanoscale lateral heterojunction in monolayer MoSe2 by intercalating Se at the interface of a hBN/Ru(0001) substrate. The Se intercalation creates a spatially abrupt modulation of the local hBN/Ru work function, which is imprinted directly onto an overlying MoSe2 monolayer to create a large built-in potential of 0.83 eV. We spatially resolve the MoSe2 band profile and work fun

Document retrieval is a key stage of standard Web search engines. Existing dual-encoder dense retrievers obtain representations for questions and documents independently, allowing for only shallow interactions between them. To overcome this limitation, recent autoregressive search engines replace the dual-encoder architecture by directly generating identifiers for relevant documents in the candidate pool. However, the training cost of such autoregressive search engines rises sharply as the number of candidate documents increases. In this paper, we find that large language models (LLMs) can follow human instructions to directly generate URLs for document retrieval. Surprisingly, when providing a few {Query-URL} pairs as in-context demonstrations, LLMs can generate Web URLs where nearly 90\% of the corresponding documents contain correct answers to open-domain questions. In this way, LLMs can be thought of as built-in search engines, since they have not been explicitly trained to map questions to document identifiers. Experiments demonstrate that our method can consistently achieve better retrieval performance than existing retrieval approaches by a significant margin on three open-d

It is known that the hazard ratio lacks a useful causal interpretation. Even for data from a randomized controlled trial, the hazard ratio suffers from built-in selection bias as, over time, the individuals at risk in the exposed and unexposed are no longer exchangeable. In this work, we formalize how the observed hazard ratio evolves and deviates from the causal hazard ratio of interest in the presence of heterogeneity of the hazard of unexposed individuals (frailty) and heterogeneity in effect (individual modification). For the case of effect heterogeneity, we define the causal hazard ratio. We show that the observed hazard ratio equals the ratio of expectations of the latent variables (frailty and modifier) conditionally on survival in the world with and without exposure, respectively. Examples with gamma, inverse Gaussian and compound Poisson distributed frailty, and categorical (harming, beneficial or neutral) effect modifiers are presented for illustration. This set of examples shows that an observed hazard ratio with a particular value can arise for all values of the causal hazard ratio. Therefore, the hazard ratio can not be used as a measure of the causal effect without ma

Modified gravity theories can accommodate exact solutions, for which the metric has the same form as the one in general relativity, i.e., stealth solutions. One problem with these stealth solutions is that perturbations around them exhibit strong coupling when the solutions are realized in degenerate higher-order scalar-tensor theories. We show that the strong coupling problem can be circumvented in the framework of the so-called U-DHOST theories, in which the degeneracy is partially broken in such a way that higher-derivative terms are degenerate only in the unitary gauge. In this sense, the scordatura effect is built-in in U-DHOST theories in general. There is an apparent Ostrogradsky mode in U-DHOST theories, but it does not propagate as it satisfies a three-dimensional elliptic differential equation on a spacelike hypersurface. We also clarify how this nonpropagating mode, i.e., the "shadowy" mode shows up at the nonlinear level.

A general model-based extended state observer (GMB-ESO) is proposed for single-input single-output linear time-invariant systems with a given state space model, where the total disturbance, a lump sum of model uncertainties and external disturbances, is defined as an extended state in the same manner as in the original formulation of ESO. The conditions for the existence of such an observer, however, are shown for the first time as 1) the original plant is observable; and 2) there is no invariant zero between the plant output and the total disturbance. Then, the finite-step convergence and error characteristics of GMB-ESO are shown by exploiting its inherent connection to the well-known unknown input observer (UIO). Furthermore, it is shown that, with the relative degree of the plant greater than one and the observer eigenvalues all placed at the origin, GMB-ESO produces the identical disturbance estimation as that of UIO. Finally, an improved GMB-ESO with built-in zero dynamics is proposed for those plants with zero dynamics, which is a problem that has not been addressed in all existing ESO designs.