I propose a semiparametric Bayesian inference framework for conditional moment equalities. The core idea is that these models deterministically map a conditional distribution of data to a structural parameter via the restriction that a conditional expectation equals zero. Consequently, a posterior for the conditional distribution leads to a posterior for the structural parameter by minimizing the distance of the conditional moments to zero. The method has similar flexibility to frequentist semiparametric estimators and does not require converting the conditional moments into unconditional moments. I also establish frequentist asymptotic optimality of my proposal via a semiparametric Bernsteinvon Mises theorem (BvM), which establishes that the posterior for the structural parameter is asymptotically normal and matches the Chamberlain (1987) semiparametric efficiency bound. The BvM conditions are verified for Gaussian process priors and complement the numerical aspects of the paper in which these priors are used to estimate welfare effects.

We construct a simple toy model of a closed FLRW spacetime by starting from a flat five dimensional scalar field space. The action contains no curvature terms. A string-like potential is used for the field space. The model is fully covariant and the spacetime metric is uniquely determined from the dynamical equations of the metric tensor. An SO(4) invariant ansatz for the scalar fields is shown to be sufficient to build the FLRW cosmology.

We consider the general framework of perturbative quantum field theory for the general Yang-Mills model including massless and massive vector fields and also scalar and Dirac fields. We describe the chronological products using Wick submonomials and give rigorous proofs of gauge invariance for tree and loop contributions in the second order of the perturbation theory.

We investigate a large ensemble of Quadratic Integrate-and-Fire (QIF) neurons with heterogeneous input currents and adaptation variables. Our analysis reveals that for a specific class of adaptation, termed quadratic spike-frequency adaptation (QSFA), the high-dimensional system can be exactly reduced to a low-dimensional system of ordinary differential equations, which describes the dynamics of three mean-field variables: the population's firing rate, the mean membrane potential, and a mean adaptation variable. The resulting low-dimensional firing rate equations (FRE) uncover a key generic feature of heterogeneous networks with spike frequency adaptation: Both the center and the width of the distribution of the neurons' firing frequencies are reduced, and this largely promotes the emergence of collective synchronization in the network. Our findings are further supported by the bifurcation analysis of the FRE, which accurately captures the collective dynamics of the spiking neuron network, including phenomena such as collective oscillations, bursting, and macroscopic chaos.

We show that some holographic dark energy models can lead to a future evolution of the universe in which the scale factor $a$ is asymptotically constant, while $\dot a \rightarrow 0$ and the corresponding energy and pressure densities also vanish. We provide specific examples of such models and general conditions that can lead to an asymptotically static universe, which we have called the ``long freeze." In some cases, such evolution can follow an arbitrarily long exponential expansion essentially identical to the asymptotic evolution of $Λ$CDM. When nonrelativistic matter is added to the holographic dark energy, it tends to destroy the long freeze behavior, driving the universe to recollapse. We show that a long freeze evolution is still possible, but only for a more limited set of HDE models.

The function $p_{xy}$ that interchanges two logical variables $x,y$ in formulas is hard to describe in the following sense. Let $F$ denote the Lindenbaum-Tarski formula-algebra of a finite-variable first order logic, endowed with $p_{xy}$ as a unary function. Each equational axiom system for the equational theory of $F$ has to contain, for each finite $n$, an equation that contains together with $p_{xy}$ at least $n$ algebraic variables, and each of the operations $\exists, =, \lor$. This solves a problem raised by Johnson [J. Symb. Logic] more than 50 years ago: the class of representable polyadic equality algebras of a finite dimension $α\ge 3$ cannot be axiomatized by adding finitely many equations to the equational theory of representable cylindric algebras of dimension $α$. Consequences for proof systems of finite-variable logic and for defining equations of polyadic equality algebras are given. The proof uses a family of nonrepresentable polyadic equality algebras ${\cal A}_n$ that are more and more nearly representable as $n$ increases: their $n$-generated subalgebras as well as their proper reducts are representable. The lattice of subvarieties of $RPEA_α$ is investigated and new open problems are asked about the interplay between the transposition operations and about generalizability of the results to infinite dimensions.

Variational interpolants are an indispensable tool for the construction of gradient-flow solutions via the Minimizing Movement Scheme. The De Giorgi lemma provides the associated discrete energy-dissipation inequality. It was originally developed for metric gradient systems. Drawing from this theory we study the case of generalized gradient systems in Banach spaces, where a refined theory allows us to extend the validity of the discrete energy-dissipation inequality and to establish it as an equality. For the latter we have to impose the condition of radial differentiability of the dissipation potential. Several examples are discussed to show how sharp the results are.

A fundamental result in extremal graph theory is attributed to Mantel's theorem, which states that every graph on $n$ vertices with more than $\lfloor n^2/4 \rfloor$ edges must contain a triangle. Lovász and Simonovits (1975) provided a supersaturation phenomenon by showing that for any $q< n/2$, every graph with $\lfloor n^2/4 \rfloor +q$ edges contains at least $q\lfloor n/2 \rfloor$ triangles. This result resolved a conjecture proposed by Erdős in 1962. In this paper, we establish a spectral counterpart of the result of Lovász and Simonovits. Let $Y_{n,2,q}$ be the graph obtained from the bipartite Turán graph $T_{n,2}$ by embedding a matching with $q$ edges into the partite set of size $\lceil n/2\rceil$. Using the supersaturation-stability method and the spectral techniques, we firstly prove that for $q\le \frac{1}{11}\sqrt{n}$, every graph $G$ on $n$ vertices with spectral radius $λ(G) \ge λ(Y_{n,2,q})$ contains at least $q\lfloor n/2 \rfloor$ triangles. We also show that the bound $q=O(\sqrt{n})$ is tight up to a constant factor, yielding a phenomenon different from that in edge supersaturation. Our result answers a spectral triangle counting problem proposed by Ning and Zhai (2023). Secondly, let $T_{n,2,q}$ be the graph obtained from $T_{n,2}$ by embedding a star with $q$ edges into the partite set of size $\lceil n/2\rceil$. We show further that $T_{n,2,q}$ is the unique extremal graph that contains at most $q\lfloor n/2 \rfloor$ triangles and attains the maximum spectral radius. Thirdly, we present an asymptotic spectral stability result under a specific constraint on the triangle covering number. This result could be viewed as a spectral extension of a recent result proved by Balogh and Clemen (2023), and independently by Liu and Mubayi (2022).

While the automated detection of cryptographic API misuses has progressed significantly, its precision diminishes for intricate targets due to the reliance on manually defined patterns. Large Language Models (LLMs) offer a promising context-aware understanding to address this shortcoming, yet the stochastic nature and the hallucination issue pose challenges to their applications in precise security analysis. This paper presents the first systematic study to explore LLMs' application in cryptographic API misuse detection. Our findings are noteworthy: The instability of directly applying LLMs results in over half of the initial reports being false positives. Despite this, the reliability of LLM-based detection could be significantly enhanced by aligning detection scopes with realistic scenarios and employing a novel code and analysis validation technique, achieving a nearly 90% detection recall. This improvement substantially surpasses traditional methods and leads to the discovery of previously unknown vulnerabilities in established benchmarks. Nevertheless, we identify recurring failure patterns that illustrate current LLMs' blind spots. Leveraging these findings, we deploy an LLM-based detection system and uncover 63 new vulnerabilities (47 confirmed, 7 already fixed) in open-source Java and Python repositories, including prominent projects like Apache.

Animals flexibly change their behavior depending on context. It is reported that the hippocampus is one of the most prominent regions for contextual behaviors, and its sequential activity shows context dependency. However, how such context-dependent sequential activity is established through reorganization of neuronal activity (remapping) is unclear. To better understand the formation of hippocampal activity and its contribution to context-dependent flexible behavior, we present a novel biologically plausible reinforcement learning model. In this model, Context selector promotes the formation of context-dependent sequential activity and allows for flexible switching of behavior in multiple contexts. This model reproduces a variety of findings from neural activity, optogenetic inactivation, human fMRI, and clinical research. Furthermore, our model predicts that imbalances in the ratio between sensory and contextual representations in Context selector account for schizophrenia (SZ) and autism spectrum disorder (ASD)-like behaviors.

For any non-Archimedean local field $\mathbb{K}$ and any integer $n \geq 1$, we show that the Taibleson operator admits a bounded $\mathrm{H}^\infty(Σ_θ)$ functional calculus on the Bochner space $\mathrm{L}^p(\mathbb{K}^n,Y)$ for any $\mathrm{UMD}$ Banach function space $Y$ and any angle $θ> 0$, where $Σ_θ=\{ z \in \mathbb{C}^*: |\arg z| < θ\}$ and $1 < p < \infty$. Moreover, we prove that it even admits a bounded Hörmander functional calculus of order $\frac{3}{2}$. In our study, we explore harmonic analysis on locally compact Spector-Vilenkin groups and establish the $R$-boundedness of a family of convolution operators. Our results contribute to the theory of functional calculi for operators acting on vector-valued $\mathrm{L}^p$-spaces over totally disconnected spaces. As an application, we obtain maximal regularity results and well-posedness for a class of evolution equations driven by the Taibleson operator.

This paper presents the design and comprehensive measurements of a high-performance 8-element linear array and a compact high-gain 32-element planar antenna array covering the n257 (26.5--29.5 GHz) FR-2 millimeter-wave (mmWave) band. First, an 8-element series-fed linear array is designed with a fan-shaped pattern for 5G point-to-multipoint connectivity. Then a 4-way corporate-series feed network is designed for a high-gain 32-element compact and directive array for point-to-point mmWave connectivity. Comprehensive over-the-air (OTA) measurements are conducted using a state-of-the-art compact antenna test range (CATR) system, enabling precise characterization of radiation patterns across a 180^\circ span in the azimuth and elevation planes. The planar array achieves a peak measured gain of 18.45 dBi at 28.5 GHz, with half-power beamwidths ranging from 11^\circ--13^\circ (wide axis) and 23^\circ--27^\circ (narrow axis) across the band of interest. The sidelobe levels are below -10 dB in the desired band of interest. The measured results match well with the simulation results. The designed antenna array is applicable to various emerging 5G and beyond mmWave applications such as high data rate mmWave wireless backhaul, mmWave near-field focusing, high-resolution indoor radar systems, 28 GHz Local Multipoint Distribution Service (LMDS), as well as the characterization of mmWave path loss and channel sounding in diverse indoor environments.

The paper establishes several inequalities between cardinal characteristics of the continuum. In particular, it is shown that the partition splitting number is not larger than the uniformity of the meagre ideal; not all sets of reals having the cardinality of an the $\varepsilon$-almost bisecting number are of strong measure zero; no fewer sets of strong measure zero than indicated by the statistically reaping number suffice to cover the reals; the pair-splitting number is not smaller than the evasion number; and the subseries number is neither smaller than the pair-splitting number nor than the minimum of the unbounding number and the unbisecting number. Moreover, a diagram putting these results into context is provided and a brief historical account is given.

Microarcsecond resolutions afforded by an optical-NIR array with kilometer-baselines would enable breakthrough science. However significant technology barriers exist in transporting weakly coherent photon states over these distances: primarily photon loss and phase errors. Quantum telescopy, using entangled states to link spatially separated apertures, offers a possible solution to the loss of photons. We report on an initiative launched by NSF NOIRLab in collaboration with the Center for Quantum Networks and Arizona Quantum Initiative at the University of Arizona, Tucson, to explore these concepts further. A brief description of the quantum concepts and a possible technology roadmap towards a quantum-enhanced very long baseline optical-NIR interferometric array is presented. An on-sky demonstration of measuring spatial coherence of photons with apertures linked through the simplest Gottesman protocol over short baselines and with limited phase fluctuations is envisaged as the first step.

Kagome metal CsV$_3$Sb$_5$ has attracted much recent attention due to the coexistence of multiple exotic orders and the associated proposals to mimic unconventional high temperature superconductors. Nevertheless, magnetism and strong electronic correlations -- two essential ingredients for unconventional superconductivity, are absent in this V-based Kagome metal. CsCr$_3$Sb$_5$ is a newly discovered Cr-based parallel of CsV$_3$Sb$_5$, in which magnetism appears with charge density wave and superconductivity at different temperature and pressure regions. Enhanced electronic correlations are also suggested by theoretical proposals due to the calculated flat bands. Here, we report angle-resolved photoemission measurements and first-principles calculations on this new material system. Electron energy bands and the associated orbitals are resolved. Flat bands are observed near the Fermi level. Doping dependent measurements on Cs(Cr$_x$V$_{1-x}$)$_3$Sb$_5$ reveal a gradually enhanced band renormalization from CsV$_3$Sb$_5$ to CsCr$_3$Sb$_5$, accompanied by distinct spatial symmetry breaking states in the phase diagram.

For several years, the metastable helium triplet line has been successfully used as a tracer to probe atmospheric escape in transiting exoplanets. This absorption in the near-infrared (1083.3 nm) can be observed from the ground using high-resolution spectroscopy, providing new constraints on the mass-loss rate and the temperature characterizing the upper atmosphere of close-in exoplanets. The aim of this work is to search for the He triplet signature in 15 transiting exoplanets -- ranging from super-Earths to ultrahot Jupiters -- observed with SPIRou, a high-resolution (R~70 000) near-infrared spectropolarimeter at the CFHT, in order to bring new constraints or to improve existing ones regarding atmospheric escape through a homogeneous study. We developed a full data processing and analysis pipeline to correct for the residual telluric and stellar contributions. We then used two different 1D models based on the Parker-wind equations and nonlocal thermodynamic equilibrium (NLTE) radiative transfer to interpret the observational results. We confirm published He triplet detections for HAT-P-11 b, HD 189733 b, and WASP-69 b. We tentatively detect the signature of escaping He in HD 209458 b, GJ 3470 b, and WASP-76 b. We report new constraints on the mass-loss rate and temperature for our three detections and set upper limits for the tentative and nondetections. We notably report improved constraints on the mass-loss rate and temperature of the escaping gas for TOI-1807 b, and report a nondetection for the debated atmospheric escape in GJ 1214 b. We also conducted the first search for the He signature in GJ 486 b since its discovery and report a nondetection of the He triplet. Finally, we studied the impact of important model assumptions on our retrieved parameters, notably the limitations of 1D models and the influence of the H/He ratio on the derived constraints.

This paper studies strategic communication in the context of social learning. Product reviews are used by consumers to learn product quality, but in order to write a review, a consumer must be convinced to purchase the item first. When reviewers care about welfare of future consumers, this leads to a conflict: a reviewer today wants the future consumers to purchase the item even when this comes at a loss to them, so that more information is revealed for the consumers that come after. We show that due to this conflict, communication via reviews is inevitably noisy, regardless of whether reviewers can commit to a communication strategy or have to resort to cheap talk. The optimal communication mechanism involves truthful communication of extreme experiences and pools the moderate experiences together.

Kuroda's translation embeds first-order classical logic into intuitionistic logic, such that a formula and its translation are equivalent in classical logic. Recently, Brown and Rizkallah extended this translation to higher-order logic. However, they showed that the translation fails in the presence of functional extensionality, and they did not prove the classical equivalence between a formula and its translation. In this paper, we emphasize different conditions under which Kuroda's translation works in the presence of functional extensionality, including the double-negation shift. We show that the classical equivalence between a formula and its translation does not necessarily hold in higher-order logic. However, it is sufficient to assume both functional extensionality and propositional extensionality.

The fifth generation of the telecommunication networks (5G) established the service-oriented paradigm on the mobile networks. In this new context, the 5G Core component has become extremely flexible so, in addition to serving mobile networks, it can also be used to connect devices from the so-called non-3GPP networks, which contains technologies such as WiFi. The implementation of this connectivity requires specific protocols to ensure authentication and reliability. Given these characteristics and the possibility of convergence, it is necessary to carefully choose the encryption algorithms and authentication methods used by non-3GPP user equipment. In light of the above, this paper highlights key findings resulting from an analysis on the subject conducted through a test environment which could be used in the context of the Eduroam federation.

Holographic principles have proven to be a very interesting approach towards dealing with the issues of the late-time acceleration of the universe, which has resulted in a great amount of work on holographic dark energy models. We consider one such very interesting holographic scenario, namely the Tsallis Holographic dark energy model and consider an ansatz based approach to such models. We consider three cosmological scenarios in such models, namely those with viscous , non-viscous and Chaplygin gas scenarios, discussing various crucial aspects related to these models. We discuss various crucial properties of the Tsallis model in such scenarios and see how the phantom divide is crossed in each case, but it's only the Chaplygin gas models which give a better view on stability issues.

The paper is concerned with a McKean-Vlasov type SDE with drift in anisotropic Besov spaces with negative regularity and with degenerate diffusion matrix under the weak H{ö}rmander condition. The main result is of existence and uniqueness of a solution in law for the McKean-Vlasov equation, which is formulated as a suitable martingale problem. All analytical tools needed are derived in the paper, such as the well-posedness of the Fokker-Planck and Kolmogorov PDEs with distributional drift, as well as continuity dependence on the coefficients. The solutions to these PDEs naturally live in anisotropic Besov spaces, for which we developed suitable analytical inequalities, such as Schauder estimates.

In the context of the AdS/CFT correspondence, we propose a general scheme for reconstructing bulk geometric quantities in a static pure AdS background using the partial entanglement entropy (PEE), a measure of the entanglement structure on the boundary CFT. The PEE between any two points $\mathcal{I}(\vec{x}, \vec{y})$ serves as the fundamental building block of the PEE structure. Any two-point PEE $\mathcal{I}(\vec{x}, \vec{y})$ can be geometrized by the bulk geodesic connecting two boundary points $\vec{x}$ and $\vec{y}$, which we call the PEE thread, with the density of the threads determined by the boundary PEE structure. In the AdS bulk, the set of all the PEE threads forms a continuous ``network'', which we call the PEE network. In this paper, we show that the density of the PEE threads passing through any bulk point is exactly $1/(4G)$. Based on this observation we give a reformulation of the Ryu-Takayanagi (RT) formula for a generic boundary region in general dimensional Poincaré AdS space. More explicitly, for any static boundary region $A$, the homologous surface $Σ_{A}$ that has the minimal number of intersections with the bulk PEE network is exactly the RT surface of $A$, and the minimal number of intersections reproduces the holographic entanglement entropy. The reconstruction for the area of bulk geometric quantities by counting the number of intersections with the bulk PEE network applies to generic bulk geometric quantities. Interestingly, this reconstruction indicates a pure geometric statement, which is exactly the so-called \emph{Crofton formula} in Poincaré AdS.

We simulate the dynamics of systems with $N$ = 1-20 qubits coupled to a cavity in order to assess their potential for quantum metrology of a parameter in the open systems limit. The qubits and the cavity are both allowed to have losses and the system is studied under various coupling strength regimes. The focus is primarily on the coupling between the qubits using the quantum Fisher information as the measured parameter. Some results on estimating the qubit-cavity detuning parameter are also presented. We investigate the scaling of the uncertainty in the estimate of the qubit-cavity coupling with the number of qubits and for different initial states of the qubits that act as the quantum probe. As initial probe states, we consider Dicke states with varying excitation numbers, the GHZ state, and separable X-polarized states. It is shown that in the strong coupling regime, i.e., when the coupling between the qubits and the cavity is greater than the decay parameters of both the qubits and the cavity, Dicke states with a large excitation number can achieve the Heisenberg limit, with the precision scaling improving as the excitation number increases. A particularly intriguing finding of our study is that in the weak coupling regime, as well as in situations where either the qubit or cavity decay parameters exceed the coupling, the separable $X$-polarized state is the best in terms of scaling and is even able to achieve the Heisenberg limit in these lossy regimes for the range of $N$ considered.

Simulating spontaneous structural rearrangements in macromolecules with classical Molecular Dynamics (MD) is an outstanding challenge. Conventional supercomputers can access time intervals up to tens of $μ$s, while many key events occur on exponentially longer time scales. Transition path sampling techniques have the advantage of focusing the computational power on barrier-crossing trajectories, but generating uncorrelated transition paths that explore diverse conformational regions remains an unsolved problem. We employ a path-sampling paradigm combining machine learning (ML) with quantum computing (QC) to address this issue. We use ML on a classical computer to perform a preliminary uncharted exploration of the conformational space. The data set generated in this exploration is then post-processed to obtain a network representation of the reactive kinetics. Quantum annealing machines can exploit quantum superposition to encode all the transition pathways in this network in the initial quantum state and ensure the generation of completely uncorrelated transition paths. In particular, we resort to the DWAVE quantum computer to perform an all-atom simulation of a protein conformational transition that occurs on the ms timescale. Our results match those of a special purpose supercomputer designed to perform MD simulations. These results highlight the role of biomolecular simulation as a ground for applying, testing, and advancing quantum technologies.

We establish an area formula for the spherical measure of intrinsic graphs of any codimension in homogeneous groups. Our approach relies on the assumption that the map defining the intrinsic graph is continuously intrinsically differentiable. The main novelty is a notion of Jacobian defined using an auxiliary scalar product.

The non-Gaussian Cold Spot (CS) surrounded by its hot ring is one of the most striking features of the CMB. It has been speculated that either new physics or ISW effect induced by the presence of a cosmic void at high redshift can account for the observations. Here we investigate if the systematic decrease in CMB temperature in the neighbourhood of nearby galaxies may create such a strong temperature depression. In particular, we note that the Eridanus supergroup and its neighbouring groups, is in the CS area. Our goal is to analyse observational galaxy data to characterise the neighbourhood of the CS, explore the properties of these galaxies and thereby make a prediction of the CMB temperature decrement in this region. We use the Planck SMICA maps and the galaxy catalogues 2MRS, 6dF and HIPASS as foreground tracers. We apply mean temperature profiles to model the temperature decrement from the galaxies in the CS area. Even after correcting for the mean low temperature of the CS region, we find that the temperature decrement around galaxies is significantly stronger than the mean decrement in other parts of the sky. We discuss whether this could be attributed to the fact that the CS area coincides with one of the regions populated by the most HI deficient galaxies. Modelling the foreground temperature profile, we find a particularly strong temperature decrement due to the presence of the late-type overabundant largest group complex in the nearby universe. A CS shape, which to a large degree overlaps with the CMB CS, is observed. We conclude that the coincidence of the only nearby spiral rich group complex located in the CS region, and the success of the modelling performed, adds strong evidence to the existence of a local extragalactic foreground which could account for the observed temperature depression, alleviating the tension with an otherwise Gaussian field expected in the CMB.

Large language models (LLMs), like ChatGPT, have greatly simplified text generation tasks. However, they have also raised concerns about privacy risks such as data leakage and unauthorized data collection. Existing solutions for privacy-preserving inference face practical challenges related to computation time and communication costs. In this paper, we propose InferDPT, the first practical framework for the privacy-preserving Inference of black-box LLMs, implementing Differential Privacy in Text generation. InferDPT comprises two key modules: the "perturbation module" utilizes the exponential mechanism to generate a perturbed prompt, facilitating privacy-preserving inference with black-box LLMs, and the "extraction module", inspired by knowledge distillation and retrieval-augmented generation, extracts coherent and consistent text from the perturbed generation result, ensuring successful text generation completion. To address privacy concerns related to previous exponential mechanisms' susceptibility to embedding revision attacks, we introduce RANTEXT, a novel differential privacy mechanism integrated into the perturbation module of InferDPT, which introduces the concept of "RANdom adjacency" for TEXT perturbation within the prompt. Experimental results across three datasets demonstrate that the text generation quality of InferDPT is comparable to that of non-private GPT-4, and RANTEXT surpasses existing state-of-the-art mechanisms, namely, SANTEXT+ and CUSTEXT+ in the trade-off between privacy and utility. Even with an privacy parameter epsilon value of 6.0, RANTEXT achieves an average privacy protection rate exceeding 90% against embedding revision attacks, which is 0.58 times higher than that of SANTEXT+ and 3.35 times higher than that of CUSTEXT+.

We study the Rumin differentials of the 5-dimensional graded nilpotent Lie group that appears as osculating group of generic rank two distributions in dimension five. In irreducible unitary representations of this group, the Rumin differentials provide intriguing generalizations of the classical quantum harmonic oscillator. For the Schrodinger representations, we compute the spectrum and the zeta regularized determinant of each Rumin differential. In the generic representations, we evaluate their alternating product, i.e., the analytic torsion of the Rumin complex.

Aerial simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) enables full-space coverage in dynamic wireless networks. However, most existing works assume fixed user grouping, overlooking the fact that STAR-RIS deployment inherently determines whether users are served via transmission or reflection. To address this, we propose a joint deployment and beamforming framework, where an aerial STAR-RIS dynamically adjusts its location and orientation to adaptively control user grouping and enhance hybrid beamforming. We formulate a Markov decision process (MDP) capturing the coupling among deployment, grouping, and signal design. To solve the resulting non-convex and time-varying problem, we develop a PPO-based reinforcement learning algorithm that adaptively balances user grouping and beamforming resources through online policy learning. Simulation results show 57.1\% and 285\% sum-rate gains over fixed-deployment and RIS-free baselines, respectively, demonstrating the benefit of user-grouping-aware control in STAR-RIS-aided systems.

In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains more than 510K citations made by approximately 60K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI.