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Recognising the need for PQC signature schemes with different sizes and performance trade-offs than the ML-DSA and SLH-DSA standards, in 2023, NIST launched a competition for additional signature algorithms. Among the current candidates in this competition is CROSS, a code-based scheme derived from the syndrome-decoding problem and suitable for memory-constrained devices. This paper presents a fau
This paper analyzes the influence of the interannual variability of climatic drought on ecological and hydrological droughts for a basin in the central Spanish Pyrenees using variables derived from observations and hydro-ecological simulation in order to determine the possible connection between meteorological, ecological and hydrological drought considering a cascading approach and encompassing d
Europe has experienced severe drought events in recent decades, posing challenges to understand vegetation responses due to diverse vegetation distribution, varying growth stages, different drought characteristics, and concurrent hydroclimatic factors. To analyze vegetation response to meteorological drought, we employed multiple vegetation indicators across European biomes. Our findings reveal th
Acute respiratory distress syndrome (ARDS) is a life-threatening condition with mortality rates between 30-50%. Although in vitro models replicate some aspects of ARDS, small and large animal models remain the primary research tools due to the multifactorial nature of the disease. When using these animal models, histology serves as the gold standard method to confirm lung injury and exclude other
We consider a version of the Erdős–Rothschild problem for families of graph patterns. For any fixed k≥3, let r0(k) be the largest integer such that the following holds for all 2≤r≤r0(k) and all sufficiently large n: The Turán graph Tk−1(n) is the unique n-vertex graph G with the maximum number of r-edge-colorings such that the edge set of any copy of Kk in G is rainbow. We use the regularity lemma
Consider discrete-time linear distributed averaging dynamics, whereby a finite number of agents in a network start with uncorrelated and unbiased noisy measurements of a common state of the world modeled as a scalar parameter, and iteratively update their estimates following a non-Bayesian learning rule. Specifically, let every agent update her estimate to a convex combination of her own current e
The design of an adaptive controller with bounded L2-gain from disturbances to errors for linear time-invariant systems with uncertain parameters restricted to a finite set is investigated. The synthesis of the controller requires finding matrices satisfying non-convex matrix inequalities. We propose an approach for finding these matrices based on repeatedly linearizing the terms that cause the no
The manuscript is devoted to optimal control for a class of linear positive systems with linear objective function and linear constraints. The solution to the corresponding Bellman equation is a linear value function, which can be found by linear programming.
The pursuit of commercialization is at the core of economic activity, and limited commercialization success is generally ascribed to the lower scalability or potential of the venture. Drawing on the anti-profit-taking socio-institutional perspective and innovation resistance theory, commercialization of a value-creating technology could be resisted from the demand side. We use a 3D surgical video
Systems that interact with the environment around them generally run some periodic tasks. This class of systems include, among others, embedded control systems. Embedded controllers have been proven vulnerable to various security attacks, including attacks that alter sensor and actuator data and attacks that disrupt the calculation of the control signals. In this paper, we propose, and implement,
In this paper, we present a heuristic method for adapting a networked linear feedback controller to improve its robustness to timing complications, such as long delays, aborted computations, and dropped packets. The core concept of the approach is to log successful sampling and actuation events and then, at discrete time-points, use non-convex parametric optimization to improve the expected perfor
Artificial intelligence (AI)-assisted code generation is everywhere these days. Undoubtedly, AI will help near-future developers substantially by providing code suggestions and automation. In this application, explainability will be a key quality attribute.
Support for Machine Learning (ML) applications in networking has significantly improved over the last decade. The availability of public datasets and programmable switching fabrics (including low-level languages to program them) presents a full-stack to the programmer for deploying in-network ML. However, the diversity of tools involved, coupled with complex optimization tasks of ML model design a
A memetic framework for optimal inverse design is proposed by combining a local gradient-based procedure and a robust global scheme. The procedure is based on method-of-moments matrices and does not demand full inversion of a system matrix. Fundamental bounds are evaluated for all optimized metrics in the same manner, providing natural stopping criteria and quality measures for realized devices. C
The nonlinear, or warped, resolvent recently explored by Giselsson and Bùi-Combettes has been used to model a large set of existing and new monotone inclusion algorithms. To establish convergent algorithms based on these resolvents, corrective projection steps are utilized in both works. We present a different way of ensuring convergence by means of a nonlinear momentum term, which in many cases l
The human vestibulo-ocular reflex (VOR) leads to maintenance of the acuity of an image on the retina and contributes to the perception of orientation during high acceleration head movements. Our objective was to determine whether vision affects the horizontal VOR by assessing and comparing the performance at the boundaries of contribution of: (a) unrestricted visual information and (b) no visual i
With the growth of the cloud industry in recent years, the energy consumption of the underlying infrastructure is a major concern.The need for energy efficient resource management and control in the cloud becomes increasingly important as one part of the solution, where the other is to reduce the energy consumption of the hardware itself.Resource management in the cloud is typically done using rel
This paper explores acceleration of the finite element-boundary integral hybrid method using the adaptive cross approximation. Our code implementing the hybrid method in Python based on open source packages is briefly presented. A simple one-level version of the adaptive cross approximation is described and it is used to accelerate the boundary integral matrices. We present results for scattering
Wireless charging of smartphones using inductive wireless power transfer (IWPT) has become very popular. However, the efficiency of IWPT systems can decrease substantially when the transmitting and receiving coils are not closely coupled. One popular approach to mitigate the efficiency degradation is to utilize higher frequency. However, the higher efficiency is only achieved at a specific range o
We designed and simulated a 1 GHz planar dipole antenna that is cloaked in a band around 10 GHz. Relative to an uncloaked antenna it has a reduced extinction cross-section for the co-antenna polarization, at the cost of an increased cross-polarization. This reduced extinction cross-section characterizes a reduction in scattering and absorption, and so reduced interference to electromagnetic waves
