Fasting - Science topic

In this paper, we propose a user-friendly library in CoCoA to address and completely resolve the challenges posed by the highly efficient and intriguing mathematical model introduced in Hernando et al., (2023) for implementing railway interlocking systems. Although the algebraic model (Hernando et al., 2023) allows for fast performance, it requires...

Multiple floating structures offer a versatile solution for offshore engineering. However, these systems are inherently complex due to hydrodynamic interactions and intricate connections between structures and moorings. This study aims to develop a coupled time-domain model for multiple floating structures, and to demonstrate its application to cat...

This timely book explores the challenges facing universities and individual scholars through an examination of the history and theory underlying the concept of academic freedom. Freedom of speech is widely viewed as a central attribute of contemporary liberal democracies and within limits — differing opinions can be articulated in public without f...

Global wave datasets typically provide coarse spatial resolution, which is insufficient for detailed regional applications. Recently, neural networks have been used for fast downscaling of environmental fields, while their inherent randomness can induce prediction instability. This study aims to enhance the spatial resolution of significant wave he...

Nature-based solutions (NbS) are an increasingly widespread tool in environment and development policies. They embody the idea that nature and natural processes can be purposefully used by humans to provide solutions to pressing environmental and social challenges. However, their potential to meet this ambition is contested, particularly in terms o...

Lithium-ion batteries are an essential component of space power systems. Preventing lithium plating during the fast charging of lithium-ion batteries can ensure the safety and reliability of space power systems. However, there are some shortcomings in the current research on fast charging strategies. On the one hand, the limitation of lithium plati...

We proposed and demonstrated fast light and superluminal propagation based on Rayleigh scattering-induced Brillouin random lasing resonance in optical fibers. A theoretical model of the proposed Brillouin superluminal propagation system has been established, detailing the principle of optical group velocity manipulation based on the combination of...

A recent publication [ Opt. Express, 32, 1342 (2024)10.1364/OE.510084] presents a processing method for multiwavelength pyrometry (MWP) that claims to be accurate without requiring an a priori emissivity model. MWP is known to be an underdetermined problem which, as a result, has an infinite number of exact solutions. The proposed method can theref...

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To address the reduction in instantaneous accuracy caused by the fluctuations in the output signal of a pendulous integrating gyro accelerometer (PIGA), these fluctuations were analyzed and primarily attributed to the subdivision errors of the resolver and the dynamic tracking errors of the servo loop. A novel cascaded PI-LMS adaptive prediction fi...

In the last decades, fast modern microcontrollers have been continuously growing, allowing to develop and implement new and more intelligent control strategies as an alternative to conventional techniques for power converters. Predictive Control is one of these powerful and attractive alternatives that has received special attention in the last tim...

Time-correlated single photon counting (TCSPC) is recognized as a gold-standard technique in many fields, including life science and remote sensing applications. In particular, it is the enabling technology to record extremely fast luminous signals with accuracy down to a few picoseconds. However, setup limits like the presence of pile-up and dead-...

Electro‐fluorochromic (EFC) dual‐functional materials have attracted remarkable attention due to their feature about two distinct display modes. Carbon dots (CDs) stand out as a tunable photoluminescent materials. The pursuit of tunability controlled by electricity in dynamic devices remains a challenging goal. In this study, an EFC material is dev...

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Modern new tanks are difficult to achieve high precision control of the horizontal stabilization system due to electromechanical coupling and road surface disturbance during high‐speed combat. A predefined‐time dynamic surface controller (DSCPT) is proposed for the fast stabilization and strong disturbance problems of the tank horizontal stabilizat...

Spike Adding to Chaos 2D parameter scan of largest Lyapunov exponent A wide region of chaos emerges around a bifurcation curve of many homoclinics to a saddle-focus. We can model the system with 1D maps. The homoclinic bifurcations can be inferred from the maps. We can model the system with 1D maps. The homoclinic bifurcations can be inferred from...

For a given temporal discretization scheme, the iterative diagonalization-based parallel-in-time (ParaDiag) algorithm has shown excellent performance in accelerating computations for evolutionary problems, particularly for hyperbolic equations. Recently, considerable efforts have been made towards the spectral analysis of the involved iteration mat...

Introduction Dockless bike-sharing systems have become popular in urban China. However, how dockless bike-sharing influence users’ daily travel choices has rarely been investigated. Methods Drawing upon travel-related data collected by the day reconstruction method in Fuzhou, this study explores whether and how the mode shift caused by dockless bi...

Zusammenfassung Hintergrund Aufgrund krankheitsbedingter Funktionseinschränkungen sind viele Menschen mit schweren psychischen Erkrankungen auf Unterstützung und Hilfe im Alltag angewiesen, um ein möglichst selbstständiges und gutes Leben führen zu können. Ziel der Arbeit Die Studie untersuchte die Bedarfe, die Bedarfsdeckung sowie deren Einfluss...

Solving for the time evolution of a many particle system whose dynamics is governed by Lindblad equation is hard. We extend the use of the transfer matrix approach to a class of Lindblad equations that admit a closed hierarchy of two point correlators. An example that we treat is the X X spin chain, i.e., free fermions, subject to the local onsite...

Once the network is assembled with a given set of neuronal and synaptic conductances, the fast synapses are calibrated to generate the desired rhythm. The correct tri-phasic rhythm emerges for a given set of synaptic rise and decay values given by the alpha and beta values in the alpha synapse model. A wide area in parameter space results in the co...

Standard hydrogen embrittlement test methods typically take several hours or even days to complete. This results in a long test time. In addition, they must be carried out in situ, as the hydrogen content of preloaded samples can change significantly due to effusion during the long test duration. Testing in a hydrogen atmosphere is generally much m...

This study reports the synthesis of graphene oxide nanosheets (GNs) through a simple one-step electrochemical exfoliation method, followed by the decoration of manganese dioxide (MnO2) on the GNs using a fast, straightforward wet-chemical process. The results show that MnO2 nanosheets are uniformly dispersed on the surface of the graphene oxide, pr...

Dynamic memory allocation is essential in modern programming but remains under-supported in current PIM devices. In this work, we first conduct a design space exploration of PIM memory allocators, examining optimal metadata placement and management strategies. Building on these insights, we propose PIM-malloc, a fast and scalable allocator for real...

Memristors can be applied to the generation of chaotic systems for enhancing the complexity of chaotic signals and assembling potential applicable dynamic behaviors, thereby increasing concerns have been focused on the research of memristive chaotic system (MCS). This paper constructs multi-directional multiscroll memristive chaotic systems (MMCSs)...

In this paper, we aim to examine the importance of security issues in the Internet of Things (IoT). Traditional methods for authentication and authorization in IoT are considered insufficient due to the use of static digital systems and complex computations. Separate security schemes for different layers have been criticized for contributing to sec...

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This study aims to determine whether there are significant differences in resting pulse rates between the pre-test and post-test and whether there are any remarkable differences in vital capacity between the pre test and post-intervention. All participants gave written informed consent before the study started, following a thorough discussion of...

The nonlinear Fourier transform (NLFT) extends the classical Fourier transform by replacing addition with matrix multiplication. While the NLFT on $\mathrm{SU}(1,1)$ has been widely studied, its $\mathrm{SU}(2)$ variant has only recently attracted attention due to emerging applications in quantum signal processing (QSP) and quantum singular value t...

We study the densest subgraph problem and its variants through the lens of learning-augmented algorithms. For this problem, the greedy algorithm by Charikar (APPROX 2000) provides a linear-time $ 1/2 $-approximation, while computing the exact solution typically requires solving a linear program or performing maximum flow computations.We show that g...

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The article deals with cuisine, taste and the culinary arts in eighteenth-century Poland, in particular the relationship of the new aesthetics of taste, attitudes to fasting and nutritional knowledge to the ideas of the Enlightenment.

In this article we try to recall Claus Michael Ringel's works on the Gorenstein-projective modules. This will involve but not limited to his fundamental contributions, such as in, the solution to the independence problem of totally reflexivity conditions; the technique of $\mho$-quivers; a fast algorithm to obtain the Gorenstein-projective modules...

Generally, Spatial Database objects such as Universities, Cities, Hotels and Temples and so on are associated with corresponding keywords. In order to execute services such as University Admissions, Bank services, purchasing, Courier services, research and so on. Already existing spatial keyword search algorithm is called "Keyword Cover" which is c...

Advances in AI generative models facilitate super-realistic video synthesis, amplifying misinformation risks via social media and eroding trust in digital content. Several research works have explored new deepfake detection methods on AI-generated images to alleviate these risks. However, with the fast development of video generation models, such a...

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The core element of current cybersecurity strategies adopts Zero Trust Architecture (ZTA) to implement strong identity checks through restricted network trust relationships. Policy-based access control forms the core principle of Zero Trust where live contextual data points guide the processing of access-related decisions. This paper introduces a Z...

Understanding the statistical properties of deep neural networks (DNNs) at initialization is crucial for elucidating both their trainability and the intrinsic architectural biases they encode prior to data exposure. Mean-field (MF) analyses have demonstrated that the parameter distribution in randomly initialized networks dictates whether gradients...

We formulate time series tasks as input-output mappings under varying objectives, where the same input may yield different outputs. This challenges a model's generalization and adaptability. To study this, we construct a synthetic dataset with numerous conflicting subtasks to evaluate adaptation under frequent task shifts. Existing static models co...

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The transformer architecture has been widely applied to many machine learning tasks. A main bottleneck in the time to perform transformer computations is a task called attention computation. [Alman and Song, NeurIPS 2023] have shown that in the bounded entry regime, there is an almost linear time algorithm to approximate the attention computation....

Attention mechanism has emerged as a foundation module of modern deep learning models and has also empowered many milestones in various domains. Moreover, FlashAttention with IO-aware speedup resolves the efficiency issue of standard attention, further promoting its practicality. Beyond canonical attention, attention with bias also widely exists, s...

DNA barcodes, which are short DNA strings, are regularly used as tags in pooled sequencing experiments to enable the identification of reads originating from the same sample. A crucial task in the subsequent analysis of pooled sequences is barcode calling, where one must identify the corresponding barcode for each read. This task is computationally...

Artificial Intelligence (AI) has become an essential tool in the world of management for decision-making. This article examines the ways in which AI can be used to improve the quality and speed of decision-making, and how AI can improve the operational efficiency of companies. In addition, this article also examines the challenges and opportunities...

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Kernel-based conditional independence (KCI) testing is a powerful nonparametric method commonly employed in causal discovery tasks. Despite its flexibility and statistical reliability, cubic computational complexity limits its application to large datasets. To address this computational bottleneck, we propose \textit{FastKCI}, a scalable and parall...

Evolving magnetic fields are frequently embedded in plasmas that are turbulent. When the primary interest is in effects that are on a large scale compared to that of the turbulence, it is desirable to average over the turbulence to obtain equations for mean-field magnetohydrodynamics. An obvious constraint on the validity of the averaging is that l...

Efficient red-teaming method to uncover vulnerabilities in Large Language Models (LLMs) is crucial. While recent attacks often use LLMs as optimizers, the discrete language space make gradient-based methods struggle. We introduce LARGO (Latent Adversarial Reflection through Gradient Optimization), a novel latent self-reflection attack that reassert...

The attention mechanism of a transformer has a quadratic complexity, leading to high inference costs and latency for long sequences. However, attention matrices are mostly sparse, which implies that many entries may be omitted from computation for efficient inference. Sparse attention inference methods aim to reduce this computational burden; howev...

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Analog in-memory computing is a next-generation computing paradigm that promises fast, parallel, and energy-efficient deep learning training and transfer learning (TL). However, achieving this promise has remained elusive due to a lack of suitable training algorithms. Analog memory devices exhibit asymmetric and non-linear switching behavior in add...

Multi-hop question answering (QA) involves finding multiple relevant passages and performing step-by-step reasoning to answer complex questions. Previous works on multi-hop QA employ specific methods from different modeling perspectives based on large language models (LLMs), regardless of the question types. In this paper, we first conduct an in-de...

With regard to fault diagnosis of rolling bearing, the envelope demodulation method is usually used to analyze the original vibration signal of faulty bearing, then the fault location of the bearing is determined by examining the distributions of fault characteristic frequencies, harmonics and sideband on the envelope demodulation spectral. The fau...

Understanding the fundamental constraint on work far beyond the adiabatic regime is crucial to investigating fast and efficient energy extraction or consumption processes. In this study, we derive thermodynamic speed limits for non-adiabatic work and quantify the fundamental costs of non-adiabatic work extraction or consumption processes in open qu...

Fast radio bursts (FRBs) are mysterious millisecond-duration radio transients from the distant universe. Some of them repeat, while others do not. In order to explore their origin, periodic examinations have been conducted on repeating FRBs. Most of them show irregular properties, including burst rate, dispersion measure (DM), and rotation measure...

Losses are one of the main bottlenecks for the distribution of entanglement in quantum networks, which can be overcome by the implementation of quantum repeaters. The most basic form of a quantum repeater chain is the swap ASAP repeater chain. In such a repeater chain, elementary links are probabilistically generated and deterministically swapped a...

Multi-mode phonon lasers have emerged as a pivotal research direction and have achieved remarkable progress in recent years. However, multi-mode phonon lasers exhibit slower mode competition during the startup process relative to optical lasers, which hinders their extensive application. To solve this conundrum, we explore such mode competition in...

We use a Poisson point process approach to prove distributional convergence to a stable law for non square-integrable observables φ:[0,1]→R, mostly of the form φ(x)=d(x,x0)−1α, 0<α<2, on Gibbs-Markov maps. A key result is to verify a standard mixing condition, which ensures that large values of the observable dominate the time-series, in the range...

The Boolean satisfiability problem (SAT) is a well-known example of monotonic reasoning, of intense practical interest due to fast solvers, complemented by rigorous fine-grained complexity results. However, for non-monotonic reasoning, e.g., abductive reasoning, comparably little is known outside classic complexity theory. In this paper we take a f...

Linear mixed-effects (LME) models are commonly used for analyzing longitudinal data. However, most applications of LME models rely on random intercepts or simple, e.g., stationary, covariance. Here, we extend the Fast and Efficient Mixed-Effects Algorithm (FEMA) and present FEMA-Long, a computationally tractable approach to flexibly modeling longit...

A generalised multiparameter model for linear modal stability and sensitivity analysis is developed. The stability and sensitivity equations are derived from a generalised vector-form governing equation comprised of multiple dimensionless parameters that represent different physical forces affecting the system’s stability. By introducing adjoint va...

We study classification problems using binary estimators where the decision boundary is described by horizon functions and where the data distribution satisfies a geometric margin condition. We establish upper and lower bounds for the minimax learning rate over broad function classes with bounded Kolmogorov entropy in Lebesgue norms. A key novelty...

In the era of big data, music platforms require advanced algorithms to meet growing recommendation demands. This paper proposes a hybrid music recommendation framework, S-VAERec (Similarity-Variational Autoencoder Recommender), leveraging the intrinsic characteristics of music. The framework combines content-based and social-based similarity metric...

The g-materials are widely used in the photocatalytic field because of the advantages such as good stability, but they also have defects such as small specific surface area and fast electron-hole pair complexation rate that limit their applications, so it is necessary to modify the g-materials. In this paper, we study the modification methods of g-...

In the last fifteen years a significant progress was achieved by considering an entropic relaxation of the classical multi-partite optimal transport problem (MPOTP). The entropic relaxation gives rise to the rescaling problem of a given tensor. This rescaling can be achieved fast with the Sinkhorn type algorithms. Recently, it was shown that a simi...

This study is based on the YOLOv7 object detection framework and conducts comparative experiments on early fusion, halfway fusion, and late fusion for multispectral pedestrian detection tasks. Traditional pedestrian detection tasks typically use image data from a single sensor or modality. However, in the field of multispectral remote sensing, fusi...

Kirchoff’s matrix tree theorem of 1847 connects the number of spanning trees of a graph to the spectral determinant of the discrete Laplacian [22]. Recently an analogue was obtained for quantum graphs relating the number of spanning trees to the spectral determinant of a Laplacian acting on functions on a metric graph with standard (Neumann-like) v...

The anomaly detection literature is abundant with offline methods, which require repeated access to data in memory, and impose impractical assumptions when applied to a streaming context. Existing online anomaly detection methods also generally fail to address these constraints, resorting to periodic retraining to adapt to the online context. We pr...

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High-resolution slice-to-volume reconstruction (SVR) from multiple motion-corrupted low-resolution 2D slices constitutes a critical step in image-based diagnostics of moving subjects, such as fetal brain Magnetic Resonance Imaging (MRI). Existing solutions struggle with image artifacts and severe subject motion or require slice pre-alignment to ach...

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Tiered memory systems consisting of fast small memory and slow large memory have emerged to provide high capacity memory in a cost-effective way. The effectiveness of tiered memory systems relies on how many memory accesses can be absorbed by the fast first-tier memory by page migration. The recent studies proposed several different ways of detecti...

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The importance of being a pioneer in a market is one of the major topics in the field of strategic management. While being a pioneer in the market can offer distinct advantages, the strategic importance of being a fast second mover cannot be overstated. This study explores the concept of fast following within the realm of catch-up strategy, highlig...

Purpose Vitamin D deficiency is implicated in the development of prediabetes. However, it is unclear whether vitamin D deficiency showed any relationship with different phenotypes of prediabetes. This study was designed to address this issue. Methods We included participants from the National Health and Nutrition Examination Survey 2011–2016. Pred...

Optical proximity correction (OPC) is a pivotal resolution enhancement technique that compensates for the image distortion in the optical lithography process. However, the turn-around time of modern OPC techniques, namely model-based OPC (MBOPC), increases dramatically as the lithography technology node constantly pushes forward. This paper develop...

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Understanding an agent's intent through its behavior is essential in human-robot interaction, interactive AI systems, and multi-agent collaborations. This task, known as Goal Recognition (GR), poses significant challenges in dynamic environments where goals are numerous and constantly evolving. Traditional GR methods, designed for a predefined set...

Hamilton–Jacobi (HJ) partial differential equations (PDEs) have diverse applications spanning physics, optimal control, game theory, and imaging sciences. This research introduces a first-order optimization-based technique for HJ PDEs, which formulates the time-implicit update of HJ PDEs as saddle point problems. We remark that the saddle point for...

Canonical polyadic decomposition (CPD) is at the core of fast matrix multiplication, a computational problem with widespread implications across several seemingly unrelated problems in computer science. Much recent progress in this field has used randomized heuristic search to find new CPDs, often over a finite field. However, if these techniques f...

Offline reinforcement learning (RL) aims to find optimal policies in dynamic environments in order to maximize the expected total rewards by leveraging pre-collected data. Learning from heterogeneous data is one of the fundamental challenges in offline RL. Traditional methods focus on learning an optimal policy for all individuals with pre-collecte...

Large language models have significantly advanced natural language processing, yet their heavy resource demands pose severe challenges regarding hardware accessibility and energy consumption. This paper presents a focused and high-level review of post-training quantization (PTQ) techniques designed to optimize the inference efficiency of LLMs by th...

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In this study, we investigate the revolutionary impact that large scale organisation's financial closure procedures can have by bringing AI into the picture. And the ways to perform traditional financial close were laborious, error prone and increasingly ineffective in today's high complexity, fast pace business environments. The research represent...

The Sumedang Public Service Mall (MPP) application is a digital platform used to facilitate the public in accessing centralized government services as well as services of State-Owned Enterprises / Regional-Owned Enterprises and Private Sector in order to provide fast, easy, affordable, safe and convenient services. The Sumedang MPP application prov...

Na‐ion batteries (NIBs) need new anode materials to improve energy density. Metal chalcogenides, such as Sb2Se3, represent a promising alternative to commonly used hard carbon materials, demonstrating high‐rate performance up to 5 A g⁻¹ with minimal capacity losses. However, Sb2Se3 is believed to operate under the conversion/alloying mechanism, typ...

Amb aquest panel volem obrir un espai de reflexió col.lectiva sobre com la lògica de la "fast academy" incideix en la pràctica docent de l'antropologia social i cultural. Tot i que els efectes de la fast academy han estat àmpliament analitzats en l'àmbit de la recerca i la producció científica, el panel busca centrar-se especícament en les seves re...

We present a conditional diffusion model - ConDiSim, for simulation-based inference of complex systems with intractable likelihoods. ConDiSim leverages denoising diffusion probabilistic models to approximate posterior distributions, consisting of a forward process that adds Gaussian noise to parameters, and a reverse process learning to denoise, co...

We analyze the decoherence dynamics of a central spin coupled to a spin chain with a time-dependent noisy magnetic field, focusing on how noise influences the system’s decoherence. Our results show that decoherence due to the nonequilibrium critical dynamics of the environment is amplified in the presence of uncorrelated and correlated Gaussian noi...

A lens array is often used for optical components of sensing devices, requiring high surface quality and form accuracy. Fast tool servo (FTS)-based diamond turning is one of the technologies for manufacturing complicated shapes, such as freeform optics, structured surfaces, and microlens arrays, with high machining efficiency. In this study, lens a...

The possibility of deepfake detection using vibraimage technology and pre-trained AI was investigated. The database of 100 deepfake 60-second videos, resolution from 640x480 to 1960x1080 and video compression level from 1 to 10,000 was created. Developed and pre-trained on digital parameters of fast vibraimage transform (FVT) of deepfakes and contr...

Text-to-audio systems, while increasingly performant, are slow at inference time, thus making their latency unpractical for many creative applications. We present Adversarial Relativistic-Contrastive (ARC) post-training, the first adversarial acceleration algorithm for diffusion/flow models not based on distillation. While past adversarial post-tra...

The Valida instruction set architecture is designed for implementation in zkVMs to optimize for fast, efficient execution proving. This specification intends to guide implementors of zkVMs and compiler toolchains for Valida. It provides an unambiguous definition of the semantics of Valida programs and may be used as a starting point for formalizati...

Unmanned aerial vehicles (UAVs) have become important platforms for multi-object tracking. In this paper, we proposed Quick-UAV OCSORT, a fast and robust tracking-by-detection (TBD) algorithm that extends the Observation-centric SORT (OC-SORT) framework. Our method introduced a lightweight LightMBN network for enhanced re-identification, a pre-matc...

Sparse attention is a core building block in many leading neural network models, from graph-structured learning to sparse sequence modeling. It can be decomposed into a sequence of three sparse matrix operations (3S): sampled dense-dense matrix multiplication (SDDMM), softmax normalization, and sparse matrix multiplication (SpMM). Efficiently execu...