The concept of the sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural, or other contexts, in a sustainable way. The process of sustainable business model cons
We report the Suzaku observation of 1E 1740.7-2942, a black hole candidate called the 'Great Annihilator' (GA). The high-quality spectrum of Suzaku provides the severest constraints on the parameters of the GA. Two clumpy structures are found around
There is an increasing demand for controller design techniques capable of addressing the complex requirements of todays embedded applications. This demand has sparked the interest in symbolic control where lower complexity models of control systems a
In this work we propose a new numerical approach to distinguish between regular and chaotic orbits in Hamiltonian systems, based on the simultaneous integration of both the orbit and the deviation vectors using a symplectic scheme, hereby called {em
Equity options are known to be notoriously difficult to price accurately, and even with the development of established mathematical models there are many assumptions that must be made about the underlying processes driving market movements. As such,
Recent advances in LLMs have outpaced the computational and memory capacities of edge platforms that primarily employ CPUs, thereby challenging efficient and scalable deployment. While ternary quantization enables significant resource savings, existi
We develop an incremental-tableau-based decision procedure for the multi-agent epistemic logic MAEL(CD) (aka S5_n (CD)), whose language contains operators of individual knowledge for a finite set Ag of agents, as well as operators of distributed and
In today's world of computers, any kind of information can be made available within few clicks for different endeavors. The information may be tampered by changing the statistical properties and can be further used for criminal activities. These days
Based on the K'onigl's inhomogeneous jet model, we estimate the jet parameters, such as bulk Lorentz factor Gamma , viewing angle theta and electron number density n_{rm e} from radio VLBI and X-ray data for a sample of active galactic nuclei (A
S5 0716+714 is a well-studied BL Lac object in the sky. Verifying the existence of correlations among the flux variations in different bands serves as an important tool to investigate the emission processes. To examine the possible existence of a lag
The past decade has seen a remarkable series of advances in machine learning, and in particular deep learning approaches based on artificial neural networks, to improve our abilities to build more accurate systems across a broad range of areas, inclu
We experimentally study how redistribution choices are affected by positive and negative information regarding the behaviour of a previous participant in a dictator game with a taking option. We use the strategy method to identify behavioural 'types'
The electronic structure of charybdotoxin (ChTX), a scorpion venom peptide that is known to act as a potassium channel blocker, is investigated with the aid of quantum mechanical calculations. The dipole moment vector (145 D) of ChTX can be stirred b
We employ the Chandra Multiwavelength Project (ChaMP) and the Sloan Digital Sky Survey (SDSS) to study the fraction of X-ray-active galaxies in the field out to z = 0.7. We utilize spectroscopic redshifts from SDSS and ChaMP, as well as photometric r
A generic prediction in the paradigm of weakly interacting dark matter is the production of relativistic particles from dark matter pair-annihilation in regions of high dark matter density. Ultra-relativistic electrons and positrons produced in the c
In a functional calculus, the so called Omega-rule states that if two terms P and Q applied to any closed term N return the same value (i.e. PN = QN), then they are equal (i.e. P = Q holds). As it is well known, in the lambdabeta-calculus the Omega-r
It was proposed earlier that the relativistic ejections observed in microquasars could be produced by violent magnetic reconnection episodes at the inner disk coronal region. Here we revisit this model, which employs a standard accretion disk descrip
We combine IR, optical and X-ray data from the overlapping, 9.3 square degree NOAO Deep Wide-Field Survey (NDWFS), AGN and Galaxy Evolution Survey (AGES), and XBootes Survey to measure the X-ray evolution of 6146 normal galaxies as a function of abso
We summarize a book under publication with his title written by the three present authors, on the theory of Zipf's law, and more generally of power laws, driven by the mechanism of proportional growth. The preprint is available upon request from the
We analyze the long-term tidal evolution of a single-planet system through the use of numerical simulations and averaged equations giving the variations of semi-major axis and eccentricity of the relative orbit. For different types of planets, we com
We propose the timescale-resolved spectroscopy (TRS) as a new method to combine the timing and spectral study. TRS is based on the time domain power spectrum and reflects the variable amplitudes of spectral components on different timescales. We prod
As generative artificial intelligence (GenAI) becomes increasingly capable of delivering personalized learning experiences and real-time feedback, a growing number of students are incorporating these tools into their academic workflows. They use GenA
Retrieval-Augmented Generation (RAG) systems have become a dominant approach to augment large language models (LLMs) with external knowledge. However, existing vector database (VecDB) retrieval pipelines rely on flat or single-resolution indexing str
In a performance based earthquake engineering (PBEE) framework, nonlinear time-history response analysis (NLTHA) for numerous ground motions are required to assess the seismic risk of buildings or civil engineering structures. However, such numerical
We define two transformations from term rewriting systems (TRSs) to context-sensitive TRSs in such a way that termination of the target system implies outermost termination of the original system. In the transformation based on 'context extension', e
With the growing deployment of Vision-Language Models (VLMs), pre-trained on large image-text and video-text datasets, it is critical to equip users with the tools to discern when to trust these systems. However, examining how user trust in VLMs buil
It is widely believed that computing payments needed to induce truthful bidding is somehow harder than simply computing the allocation. We show that the opposite is true: creating a randomized truthful mechanism is essentially as easy as a single cal
Unifying multimodal understanding and generation has shown impressive capabilities in cutting-edge proprietary systems. However, evaluations of unified multimodal models (UMMs) remain decoupled, assessing their understanding and generation abilities
The Distributed Coordination Function (DCF) aims at fair and efficient medium access in IEEE 802.11. In face of its success, it is remarkable that there is little consensus on the actual degree of fairness achieved, particularly bearing its impact on
We study merger histories of dark-matter haloes in a suite of N-body simulations that span different cosmological models. The simulated cases include the up-to-date WMAP5 cosmology and other test cases based on the Einstein-deSitter cosmology with di
We present an updated catalog of 113 X-ray flares detected by Swift in the ~33% of the X-ray afterglows of Gamma-Ray Bursts (GRB). 43 flares have a measured redshift. For the first time the analysis is performed in 4 different X-ray energy bands, all
Currently, there is no universal method to track who shared what, with whom, when and for what purposes in a verifiable way to create an individual incentive for data owners. A platform that allows data owners to control, delete, and get rewards from
Quantum Computing is a rapidly developing field with the potential to tackle the increasing computational challenges faced in high-energy physics. In this work, we explore the potential and limitations of variational quantum algorithms in solving the
Dynamic prediction of locomotor capacity after stroke could enable more individualized rehabilitation, yet current assessments largely provide static impairment scores and do not indicate whether patients can perform specific tasks such as slope walk
Dialogue topic segmentation supports summarization, retrieval, memory management, and conversational continuity. Despite decades of work, evaluation practice remains dominated by strict boundary matching and F1-based metrics. Modern large language mo
We study time-resolved spectra of the prompt emission of Swift Gamma-ray bursts (GRB). Our goal is to see if previous BATSE claims of the existence of a large amount of spectra with the low energy photon indices harder than 2/3 are consistent with Sw
Users increasingly rely on large language models (LLMs) for personal, emotionally charged, and socially sensitive conversations. However, prompts sent to cloud-hosted models can contain personally identifiable information (PII) that users do not want
The Lottery Ticket Hypothesis asserts the existence of highly sparse, trainable subnetworks ('winning tickets') within dense, randomly initialized neural networks. However, state-of-the-art methods of drawing these tickets, like Lottery Ticket Rewind
The breakdown point in its different variants is one of the central notions to quantify the global robustness of a procedure. We propose a simple supplementary variant which is useful in situations where we have no obvious or only partial equivarianc
While large vision-language models (VLMs) demonstrate strong long-context understanding, their prevalent small branches fail on linguistics-photography alignment for a limited window size. We discover that knowledge distillation improves students' ca
Purpose: Robot-assisted minimally invasive surgery relies on endoscopic video as the sole intraoperative visual feedback. The DaVinci Xi system overlays a graphical user interface (UI) that indicates the state of each robotic arm, including the activ
Fully homomorphic encryption (FHE) schemes like RNS-CKKS enable privacy-preserving outsourced computation (PPOC) but suffer from high computational latency and ciphertext expansion, especially on the resource-constrained edge side. Hybrid Homomorphic
Although passwords remain the primary defense against unauthorized access, users often tend to use passwords that are easy to remember. This behavior significantly increases security risks, also due to the fact that traditional password strength eval
Vision-Language Models (VLMs) have demonstrated strong performance on tasks such as video captioning and visual question answering. However, their growing scale and video-level inputs lead to significant computational and memory overhead, posing chal
This paper proposes VLA-AN (Vision-Language-Action framework for Aerial Navigation), an efficient and onboard Vision-Language-Action (VLA) framework dedicated to autonomous drone navigation in complex environments. VLA-AN addresses four major limitat
Unmanned Aerial Vehicles (UAVs) in disaster response require complex, queryable intelligence that on-board CNNs cannot provide. While Vision-Language Models (VLMs) offer this semantic reasoning, their high resource demands make on-device deployment i
Abstract and deep analysis are available in the full post.
Abstract and deep analysis are available in the full post.
Decoding fine-grained movement from non-invasive surface Electromyography (sEMG) is a challenge for prosthetic control due to signal non-stationarity and low signal-tonoise ratios. Generic self-supervised learning (SSL) frameworks often yield subopti
The missing piece in the jigsaw of silicon photonics is a light source that can be easily incorporated into the standard silicon fabrication process. Recent advances in the development of atomically thin layers of semiconducting transition metal dich
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