We propose a new method for constructing the consistent space of scattering amplitudes by parameterizing the imaginary parts of partial waves and utilizing dispersion relations, crossing symmetry, and full unitarity. Using this framework, we explicitly compute bounds on the leading couplings and examine the Regge behaviors of the constructed amplitudes. The method also readily accommodates spinning bound states, which we use to constrain glueball couplings. By incorporating dispersion relations, our approach inherently satisfies the Froissart-Martin/Jin-Martin bounds or softer high-energy behaviors by construction. This, in turn, allows us to formulate a new class of fractionally subtracted dispersion relations, through which we investigate the sensitivity of coupling bounds to the asymptotic growth rate.

We investigate Riguet congruences and generalized congruences on a category, focusing on their interrelations from both lattice-theoretic and category-theoretic perspectives. We also characterize functors that are full and surjective on objects in terms of regular epimorphisms, extremal epimorphisms and in terms of strong and regular generalized congruences. On the lattice-theoretic side, we prove that for a category $\mathsf{C}$, the set $\mathrm{RCgr}(\mathsf{C})$ of all Riguet congruences, ordered by inclusion, is a bounded directed-complete ordered set, while the set $\mathrm{GCgr}(\mathsf{C})$ of all generalized congruences is an algebraic lattice. We establish a bridge between these structures via a Scott continuous morphism. From a category-theoretic standpoint, we lift these results to relative adjunctions between the categories $\mathsf{RCgr}(\mathsf{C})$ and $\mathsf{GCgr}(\mathsf{C})$ associated to the above ordered sets, as well as between the categories $\mathsf{RCCat}$, of Riguet classified categories, and $\mathsf{GCCat}$, of generalized classified categories. Furthermore, within Manes' framework of categories of $\mathsf{K}$-objects with structure, we investigate the relationship between the wide subcategory $\mathsf{RCCat}_{\mathrm{full}}$ of $\mathsf{RCCat}$, whose morphisms are the full morphisms of $\mathsf{RCCat}$, and $\mathsf{GCCat}$, relating these constructions to the Grothendieck theory of fibrations. Finally, we present applications of Riguet congruences across various mathematical fields.

Dielectric barrier discharges (DBDs) are widely used in applications such as ozone generation and volatile organic compound treatment, where performance can be enhanced through catalyst integration. A fundamental understanding of reactive species generation is essential for advancing these technologies. However, temporally resolving reactive species production, especially during the initial discharges, remains a challenge, despite its importance for controlling production rates and energy efficiency. This study examines atomic oxygen production as a model system for reactive species production in a micro-cavity plasma array, a custom surface DBD confined to micrometer-sized cavities. Optical emission spectroscopy was employed to investigate plasma-chemical processes in helium with 0.1-0.25$\%$ molecular oxygen admixture at atmospheric pressure. The discharge, powered by a 15$\,$kHz, 600$\,$V amplitude triangular voltage, achieved near-complete oxygen dissociation (up to 100$\%$), as determined via helium state-enhanced actinometry (SEA). A novel multi-photomultiplier system enabled precise temporal tracking of atomic oxygen density and dissociation dynamics. To ensure measurement accuracy, a basic 0D chemical model was developed, reinforcing the reliability of the experimental results.

A fundamental question in information theory is to quantify the loss of information under a noisy channel. Partial orders and contraction coefficients are typical tools to that end, however, they are often also challenging to evaluate. For the special class of binary input symmetric output (BISO) channels, Geng et al. showed that among channels with the same capacity, the binary symmetric channel (BSC) and binary erasure channel (BEC) are extremal with respect to the more capable order. Here, we show two main results. First, for channels with the same KL contraction coefficient, the same holds with respect to the less noisy order. Second, for channels with the same Dobrushin coefficient, or equiv. maximum leakage or Doeblin coefficient, the same holds with respect to the degradability order. In the process, we provide a closed-form expression for the contraction coefficients of BISO channels. We also discuss the comparability of BISO channels and extensions to binary channels in general.

Wasserstein distances are widely used in modern data analysis but pose significant computational and statistical challenges in high dimensions. The sliced Wasserstein distance alleviates these challenges by leveraging one-dimensional projections. Building on the Efron-Stein inequality-a technique proven effective in related problems-and a non-trivial control of the optimal transport potentials across directions, we establish a central limit theorem for the p-sliced Wasserstein distance, for p>1, centered at the expected empirical cost. Unlike for the general Wasserstein distance, the centering can be replaced by the population cost, enabling valid statistical inference. This generalizes and refines existing one-dimensional results, providing the first asymptotically valid inference framework for the sliced Wasserstein distance between possibly non-compact measures. Finally, we address other practical aspects crucial for inference, including Monte Carlo approximation of the slicing integral and consistent variance estimation.

The generation of time-reversal-odd spin-current in metallic altermagnets has attracted considerable interest in spintronics. However, producing pure spin-current in insulating materials remains both challenging and desirable, as insulating states are frequently found in antiferromagnets. Nonlinear photogalvanic effects offer a promising method for generating spin-current in insulators. We here revealed that spin and charge photocurrents in altermagnets are protected by spin point group symmetry. Unlike the photocurrents in parity-time symmetric materials, where spin-orbit coupling (SOC) induces a significant charge current, the spin-current in altermagnets can exist as a pure spin current along specific crystal directions regardless of SOC. We applied our predictions using first-principles calculations to several distinct materials, including wurtzite MnTe and multiferroic BiFeO3. Additionally, we elucidated the previously overlooked linear-inject-current mechanism in BiFeO3 induced by SOC, which may account for the enhanced bulk photovotaic effect in multiferroics.

This work explores the intersection of quantum mechanics and curved spacetime by employing the Wigner formalism to investigate quantum systems in the vicinity of black holes. Specifically, we study the quantum dynamics of a probe particle bound to a Schwarzschild black hole using a phase-space representation of quantum mechanics. The analysis begins with a review of the covariant Wigner function in curved spacetime, highlighting its application to spherically symmetric, uncharged black holes. We then derive an effective potential from the Schwarzschild metric, which defines the Hamiltonian for the electron. Relativistic corrections are treated perturbatively to estimate energy levels and associated Wigner functions for the bound state. Additionally, we compare the results obtained through the Schrodinger equation with those derived directly using the symplectic formalism, demonstrating the consistency and versatility of the phase-space approach. The study sheds light on quantum behavior near black holes and suggests new avenues for combining quantum kinetic theory with relativistic gravitational settings.

We establish general quantitative conditions for stochastic evolution equations with locally monotone drift and degenerate additive Wiener noise in variational formulation resulting in the existence of a unique invariant probability measure for the associated exponentially ergodic Markovian Feller semigroup. We prove improved moment estimates for the solutions and the $e$-property of the semigroup. Furthermore, we provide quantitative upper bounds for the $2$-Wasserstein $\varepsilon$-mixing times. Examples on possibly unbounded domains include the stochastic incompressible 2D Navier-Stokes equations, shear thickening stochastic power-law fluid equations, the stochastic heat equation, as well as, stochastic semilinear equations such as the 1D stochastic Burgers equation.

For nonzero finitely generated $R$-modules $M$ and $N$ over a Noetherian local ring $R$, Auslander's depth formula is the equality $$ \operatorname{depth} M + \operatorname{depth} N = \operatorname{depth} R + \operatorname{depth}(\operatorname{Tor}_q^R(M,N)) - q, $$ where $ q := \sup\{ i \ge 0 \mid \operatorname{Tor}_i^R(M,N) \neq 0 \}$. Gheibi, Jorgensen, and Takahashi introduced a homological invariant called quasi-projective dimension, which generalizes projective dimension, and proved that Auslander's depth formula holds when $M$ has finite quasi-projective dimension and $q=0$. In this paper, we prove that the formula still holds when $M$ has finite quasi-projective dimension, $q<\infty$ and $\operatorname{depth}(\operatorname{Tor}_q^R(M,N)) \leq 1$. We present several applications of this result; in particular, we recover a theorem of Araya and Yoshino, extend our result to the setting of semidualizing modules, and in this framework derive an improved version of the dependency formula for quasi-projective dimension with respect to a semidualizing module recently obtained by Dey, Ferraro, and Gheibi.

We present the first iterative spectral algorithm to find near-optimal solutions for a random quadratic objective over the discrete hypercube, resolving a conjecture of Subag [Subag, Communications on Pure and Applied Mathematics, 74(5), 2021]. The algorithm is a randomized Hessian ascent in the solid cube, with the objective modified by subtracting an instance-independent potential function [Chen et al., Communications on Pure and Applied Mathematics, 76(7), 2023]. Using tools from free probability theory, we construct an approximate projector into the top eigenspaces of the Hessian, which serves as the covariance matrix for the random increments. With high probability, the iterates' empirical distribution approximates the solution to the primal version of the Auffinger-Chen SDE [Auffinger et al., Communications in Mathematical Physics, 335, 2015]. The per-iterate change in the modified objective is bounded via a Taylor expansion, where the derivatives are controlled through Gaussian concentration bounds and smoothness properties of a semiconcave regularization of the Fenchel-Legendre dual to the Parisi PDE. These results lay the groundwork for (possibly) demonstrating low-degree sum-of-squares certificates over high-entropy step distributions for a relaxed version of the Parisi formula [Open Question 1.8, arXiv:2401.14383].

We study the optimization of navigational graph queries, i.e., queries which combine recursive and pattern-matching fragments. Current approaches to their evaluation are not effective in practice. Towards addressing this, we present a number of novel powerful optimization techniques which aim to constrain the intermediate results during query evaluation. We show how these techniques can be planned effectively and executed efficiently towards the first practical evaluation solution for complex navigational queries on real-world workloads. Indeed, our experimental results show several orders of magnitude improvement in query evaluation performance over state-of-the-art techniques on a wide range of queries on diverse datasets.

A connected graph, on four or more vertices, is matching covered (aka 1-extendable) if every edge is present in some perfect matching. An ear decomposition theorem exists for bipartite matching covered graphs due to Hetyei. From the results and proofs of Lovász and Plummer, that rely on Hetyei's theorem, one may deduce that any minimal bipartite matching covered graph has at least $2(m-n+2)$ vertices of degree two (where minimal means that deleting any edge results in a graph that is not matching covered); such a graph is said to be extremal if it attains the stated lower bound. In this paper, we provide a complete characterization of the class of extremal minimal bipartite matching covered graphs. In particular, we prove that every such graph $G$ is obtained from two copies of a tree devoid of degree two vertices, say $T$ and $T'$, by adding edges -- each of which joins a leaf of $T$ with the corresponding leaf of $T'$. Apart from the aforementioned bound, there are four other bounds that appear in, or may be deduced from, the work of Lovász and Plummer. Each of these bounds leads to a notion of extremality. In this paper, we obtain a complete characterization of all of these extremal classes and also establish relationships between them. Two of our characterizations are in the same spirit as the one stated above. For the remaining two extremal classes, we reduce each of them to one of the already characterized extremal classes using standard matching theoretic operations. A connected graph is k-extendable if it has a matching of cardinality $k$ and each such matching extends to a perfect matching. We also discuss bounds proved by Lou (1999) for minimal k-extendable bipartite graphs. We conjecture stronger bounds and provide evidence for our conjectures by constructing tight examples that are straightforward generalizations of the ones that appear in the 1-extendable case.

We study existence and computability of finite bases for ideals of polynomials over infinitely many variables. In our setting, variables come from a countable logical structure A, and embeddings from A to A act on polynomials by renaming variables. First, we give a sufficient and necessary condition for A to guarantee the following generalisation of Hilbert's Basis Theorem: every polynomial ideal which is equivariant, i.e. invariant under renaming of variables, is finitely generated. Second, we develop an extension of classical Buchberger's algorithm to compute a Gröbner basis of a given equivariant ideal. This implies decidability of the membership problem for equivariant ideals. Finally, we sketch upon various applications of these results to register automata, Petri nets with data, orbit-finitely generated vector spaces, and orbit-finite systems of linear equations.

Microwave Kinetic Inductance Detectors (MKIDs) have been demonstrated as capable phonon sensors when coupled to crystalline substrates, and have been proposed as detectors for next-generation rare-event searches such as for the direct detection of dark matter. These Kinetic Inductance Phonon Mediated (KIPM) detector designs, favoring large superconducting absorber volumes and high readout powers, are oftentimes limited in their sensitivity by low temperature amplifier noise introduced in the signal readout chain. We report here an effort to couple a wideband Kinetic Inductance Travelling Wave Parametric Amplifier (KI-TWPA), operated near the Standard Quantum Limit of minimal added amplifier noise, to sensors spanning a 70 MHz bandwidth at 3.5 GHz. This results in a ~5x improvement in the inferred detector energy resolution in the best sensor and highlights the potential of constructing O(100) meV resolving phonon-mediated particle detectors. We detail limitations introduced by lossy passive components, degraded RF responsivity, and microphysical noise sources like two-level systems (TLS), in achieving ultimate quantum-limited system noise levels.

Invariant causal prediction provides a useful framework for identifying causal predictors of a response using heterogeneous data from multiple environments. One valuable property of the original invariant causal prediction method is that it guarantees no false causal discoveries with high probability. Such a guarantee, however, can be overly conservative in some applications, resulting in few or no causal discoveries. This raises a natural question: can invariant causal prediction be equipped with less conservative error guarantees and thereby extract more causal information from the data? In this paper, we address this question by focusing on two widely used and more liberal guarantees: false discovery rate control and simultaneous true discovery bounds. A key step in our approach is to reformulate invariant causal prediction as a multiple testing problem. We then adopt the e-Closure principle to obtain (simultaneous) false discovery rate control, together with new p-to-e calibrators tailored to this setting. We also derive simultaneous true discovery bounds via closed testing, which provide additional causal information without requiring extra assumptions and retain all discoveries from the original invariant causal prediction method. Through simulations and a real data application on educational attainment of teenagers in the United States, we show that these more liberal error control guarantees can improve the practical usefulness of invariant causal prediction.

The main goal of this paper is to provide a point-based expression for the Hoffman constant of the argmin mapping in linear optimization, understood as the sharp Lipschitz constant restricted to its domain. The work is mainly developed in the parametric context of right-hand side perturbations of the constraint system. To the authors' knowledge, this is the first exact formula for this constant, although we can find in the literature different upper estimates. The paper tackles this objective from a broader perspective, which introduces new tools of their own interest, such as the concept of well-connected piecewise convex mapping. We isolate the nice behavior of such mappings to derive a crucial equality between the Hoffman constant (which is a global stability measure) and the supremum of calmness moduli (of local nature). The paper also includes some specifics about directional stability of optimal solutions and finishes with some conclusions and notes about further research.

Let $R$ be a strongly $\mathbb{Z}^2$-graded ring, and let $C$ be a bounded chain complex of finitely generated free $R$-modules. The complex $C$ is $R_{(0,0)}$-finitely dominated, or of type FP over $R_{(0,0)}$, if it is chain homotopy equivalent to a bounded complex of finitely generated projective $R_{(0,0)}$-modules. We show that this happens if and only if $C$ becomes acyclic after taking tensor product with a certain eight rings of formal power series, the graded analogues of classical Novikov rings. This extends results of Ranicki, Quinn and the first author on Laurent polynomial rings in one and two indeterminates.

The Rosenzweig-Porter random matrix ensemble serves as a qualitative phenomenological model for the level statistics and fractality of eigenstates across the many-body localization transition in static systems. We propose a unitary (circular) analogue of this ensemble, which similarly captures the phenomenology of many-body localization in periodically driven (Floquet) systems. We define this ensemble as the outcome of a Dyson Brownian motion process. We show numerical evidence that this ensemble shares some key statistical properties with the Rosenzweig-Porter ensemble for both the eigenvalues and the eigenstates.

The "fundamental theorem" for algebraic $K$-theory expresses the $K$-groups of a Laurent polynomial ring $L[t,t^{-1}]$ as a direct sum of two copies of the $K$-groups of $L$ (with a degree shift in one copy), and certain "nil" groups of $L$. It is shown here that a modified version of this result generalises to strongly $\mathbb{Z}$-graded rings; rather than the algebraic $K$-groups of $L$, the splitting involves groups related to the shift actions on the category of $L$-modules coming from the graded structure. (These action are trivial in the classical case). The nil groups are identified with the reduced $K$-theory of homotopy nilpotent twisted endomorphisms, and analogues of Mayer-Vietoris and localisation sequences are established.

A Laurent polynomial ring $A[t,1/t]$ with coefficients in a unital ring $A$ determines a category of quasi-coherent sheaves on the projective line over $A$; its $K$-theory is known to split into a direct sum of two copies of the $K$-theory of $A$. In this paper, the result is generalised to the case of an arbitrary strongly $\mathbb{Z}$-graded ring $R$ in place of the Laurent polynomial ring. The projective line associated with $R$ is indirectly defined by specifying the corresponding category of quasi-coherent sheaves. Notions from algebraic geometry like sheaf cohomology and twisting sheaves are transferred to the new setting, and the $K$-theoretical splitting is established.

A cut $C:=\partial(X)$ of a matching covered graph $G$ is a separating cut if both its $C$-contractions $G/X$ and $G/\overline{X}$ are also matching covered. A brick is solid if it is free of nontrivial separating cuts. In 2004, we (Carvalho, Lucchesi and Murty) showed that the perfect matching polytope of a brick may be described without recourse to odd set constraints if and only if it is solid. In 2006, we proved that the only simple planar solid bricks are the odd wheels. The problem of characterizing nonplanar solid bricks remains unsolved. A bi-subdivision of a graph $J$ is a graph obtained from $J$ by replacing each of its edges by paths of odd length. A matching covered graph $J$ is a conformal minor of a matching covered graph $G$ if there exists a bi-subdivision $H$ of $J$ which is a subgraph of $G$ such that $G-V(H)$ has a perfect matching. For a fixed matching covered graph $J$, a matching covered graph $G$ is $J$-based if $J$ is a conformal minor of $G$ and, otherwise, $G$ is $J$-free. A basic result due to Lovász (1983) states that every nonbipartite matching covered graph is either $K_4$-based or is $\overline{C_6}$-based or both, where $\overline{C_6}$ is the triangular prism. In 2016, we (Kothari and Murty) showed that, for any cubic brick $J$, a matching covered graph $G$ is $J$-free if and only if each of its bricks is $J$-free. We also found characterizations of planar bricks which are $K_4$-free and those which are $\overline{C_6}$-free. Each of these problems remains unsolved in the nonplanar case. In this paper we show that the seemingly unrelated problems of characterizing nonplanar solid bricks and of characterizing nonplanar $\overline{C_6}$-free bricks are essentially the same. We do this by establishing that a simple nonplanar brick, other than the Petersen graph, is solid if and only if it is $\overline{C_6}$-free.

A $3$-connected graph $G$ is a brick if, for any two vertices $u$ and $v$, the graph $G-\{u,v\}$ has a perfect matching. Deleting an edge $e$ from a brick $G$ results in a graph with zero, one or two vertices of degree two. The bicontraction of a vertex of degree two consists of contracting the two edges incident with it; and the retract of $G-e$ is the graph $J$ obtained from it by bicontracting all its vertices of degree two. An edge $e$ is thin if $J$ is also a brick. Carvalho, Lucchesi and Murty [How to build a brick, Discrete Mathematics 306 (2006), 2383-2410] showed that every brick, distinct from $K_4$, the triangular prism $\overline{C_6}$ and the Petersen graph, has a thin edge. Their theorem yields a generation procedure for bricks, using which they showed that every simple planar solid brick is an odd wheel. A brick $G$ is near-bipartite if it has a pair of edges $α$ and $β$ such that $G-\{α,β\}$ is bipartite and matching covered; examples are $K_4$ and $\overline{C_6}$. The significance of near-bipartite graphs arises from the theory of ear decompositions of matching covered graphs. The object of this paper is to establish a generation procedure which is specific to the class of near-bipartite bricks. In particular, we prove that if $G$ is any near-bipartite brick, distinct from $K_4$ and $\overline{C_6}$, then $G$ has a thin edge $e$ so that the retract $J$ of $G-e$ is also near-bipartite. In a subsequent work, with Marcelo H. de Carvalho, we use the results of this paper to prove a generation theorem for simple near-bipartite bricks.

We introduce a random matrix framework for studying statistical-mechanical lattice systems through spectral observables. Equilibrium configurations sampled from a Boltzmann measure are mapped to matrix ensembles whose covariance structure is inherited from the spatial correlations of the underlying model. This construction maps real-space correlation functions to a momentum-space variance profile, providing a direct bridge between statistical-mechanical correlations and correlated random matrix ensembles. We derive this variance profile in finite-correlation-length and critical regimes, and compute spectral moments within a Wick-contraction expansion. A complementary self-consistent description of the bulk density is developed using the resolvent formalism. These analytical methods are benchmarked against Monte Carlo data for the two-dimensional Ising model and three-dimensional Edwards--Anderson spin glasses. In both cases, the spectra evolve from the semicircle law at high temperature to model-dependent critical forms reflecting the structure of correlations. The framework, therefore, provides a quantitative spectral route to probing collective behavior in ordered and disordered statistical systems, while also defining a class of physically motivated correlated random matrix ensembles.

We propose that holography contains an exact kinematic sector distinct from holographic dynamics. The appropriate setting for this sector is a CFT on an open solid torus in the Weyl frame. The open solid torus introduces an intrinsic scale, and the Weyl frame makes this scale manifest as an extra bulk direction. The resulting bulk-boundary pairs are exact and finite: no cutoff, large-$N$ limit, strong-coupling assumption, or heavy-operator approximation is required. The AdS geometry appearing in this sector should be understood as a kinematic geometry; only in special CFTs and appropriate limits is it promoted to a dynamical semiclassical bulk. The standard boundary-anchored dictionary entries are recovered only as singular limits. As a striking demonstration, we show that Weyl-frame two-point functions provide a replica-free definition of entanglement entropy.

Fourier transform infrared nanospectroscopy (nano-FTIR) is a novel, increasingly adopted characterization method that leverages decades of established knowledge in infrared spectroscopy at the nanoscale. It opens up new possibilities in the characterization of composite materials and nanophotonic systems. Besides the rapid adoption and new possibilities, the nanoscale nature of these measurements poses new challenges for infrared spectroscopy. The current implementations of hyperspectral image acquisition at high spatial resolution suffer from significant artifacts due to thermal instabilities, which heavily affect positioning. As a result, the spatial and spectral fidelity of the measurements can be unreliable for long acquisitions. Here, we propose a new nano-FTIR measurement methodology based on step-scan interferometry and image registration. We demonstrate that the method provides superior spatial fidelity for photonics research and enables the collection of larger datasets, paving the way for bringing machine learning to characterize nanoscale heterogeneity.

We study stochastic graph optimization problems in a novel distributed setting. As in the standard centralized setting, a random subgraph $G^*$ of a known base graph $G$ is realized by including each edge $e$ independently with a known probability $p_e$, and we must solve an optimization problem on $G^*$ despite uncertainty about its edges. In the standard setting, to cope with this uncertainty, the algorithm can query any edge of $G$ to learn if the edge exists in $G^*$, and its complexity is the number of queried edges. The distributed setting incorporates uncertainty in a natural manner, by having each vertex know only about its own edges in $G^*$ (and only communicate over them), and the complexity is measured by the number of synchronous communication rounds. We establish that distributed stochastic algorithms can be drastically faster than their non-stochastic counterparts and overcome known lower bounds, by showing fast distributed approximation algorithms for maximum matching, minimum vertex cover, and minimum dominating set.

Phishing remains one of the most pervasive cybersecurity threats, shifting the focus from technological vulnerabilities to human cognitive and psychological factors. In coherence with the trend of studies on phishing to increasingly focus on human aspects and vulnerable users profiling, this study investigates the multidimensional nature of user susceptibility by analyzing data from the Spamley dataset, involving 1,086 participants evaluated through a realistic phishing detection task. Using Exploratory Factor Analysis (EFA), five latent constructs were identified, named: Seniority, Expertise, Creativity, Stability, and Vulnerability. Behavioral findings, validating self-reported impulsivity through its negative correlation with response times, demonstrate that faster decision-making significantly distinguishes vulnerable users from resilient ones. A K-Means clustering procedure, driven by the dimensions of Seniority (F1) and Creativity (F3), revealed two distinct user profiles: the Aware User and the High-Risk User. The results demonstrate that technical knowledge alone is insufficient to guarantee resilience; rather, the interaction between operational maturity, decision-making speed, and cognitive approach determines effectiveness. The findings suggest that the majority of users fall into the High-Risk category, characterized by hasty evaluation processes and lower critical analysis. These results underline the urgent need to move beyond "one-size-fits-all" training toward personalized, adaptive cybersecurity programs that actively address cognitive biases and behavioral tendencies.

It is shown how to obtain state vectors associated with measurements on the separated subystems of an entangled state, revealing how a single wavefunction encodes a set of statistical measurement outcomes. The result explains why measurements on the subsystems give definite outcomes and why measurements on one subsystem are correlated with those on the other. It is therefore concluded that the theory of quantum mechanics, without nonlinearities or \emph{ad hoc} assertions, can explain both the mechanism of state vector collapse and the reason for the paradoxical nonlocal correlations between separated subsystems.The theory also explains how quantum correlations, including correlations that violate Bell's inequality, are read out by classical measurements.

Multimodal Emotion Recognition (MER) focuses on identifying and interpreting emotions from modality-compound inputs. Closely mirroring human cognitive processes in real-world environments, MER has drawn substantial attention from both academia and industry. Recently, a paradigm shift has been unveiled in MER, from leveraging small-scale, task-specific models to Large Language Models (LLMs). We refer to the latter as the MER-with-LLMs paradigm, which offers unprecedented generality, spurring numerous empirical attempts, even alongside speculation about LLMs' potential to achieve general emotional intelligence. However, with these new opportunities come new challenges, including the scarcity of emotionally annotated data, the affective gap both within and across modalities, and the opacity of affective interpretation. To systematically review existing research and guide future exploration, this paper categorizes prior works according to their focus on addressing these challenges into three directions: Affective Data Augmentation, Multimodal Affective Representation, and Multimodal Affective Reasoning. By thoroughly tracing the development, emerging trends, and remaining issues within each direction, this paper aims to provide a clear academic map of the MER-with-LLMs paradigm and foster its structured advancement.

Dockerfiles enable the creation of portable container-based execution environments for the application code, and have become an important part of the modern software development process. As Dockerfiles are a form of Infrastructure-as-Code (IaC), they can include temporary workarounds and other suboptimal implementations, leading to the accrual of technical debt that affects their reliability, security, and maintainability in the future. Prior work characterized self-admitted technical debt (SATD) in Dockerfile comments and the surrounding file chunks. This single-file view is incomplete since source code evolution involves changes across different types of software artifacts such as production, test, build, and other configuration files. Thus, we address this gap by studying SATD events in Dockerfiles alongside the related source code. We find that approximately 27% of admission events and 40% of repayment events are coupled to non-Dockerfile artifacts, and coupling sources are subtype-specific. We also observed that coupled SATD in general are repaid significantly faster overall (p = 0.0201), while coupled SATD regarding missing functionalities persists longer than its isolated counterparts; Lastly, we conducted open and axial coding of coupled SATD events, and we observe that external dependency issues, more particularly regarding unreleased upstream packages and bug fixes, are the most common cause of admission triggers in the source code; we also observe that architectural refactoring is the most common prerequisite for the repayment of SATD in Dockerfiles. These findings indicate that both practitioners (e.g. developers and project managers) and SATD researchers should integrate the source code-side co-evolution, rather than the single-file view, as the primary unit of analysis.