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In this paper, we examine the distribution and convergence properties of the estimation error $W = X - \hat{X}(Y)$, where $\hat{X}(Y)$ is the Bayesian estimator of a random variable $X$ from a noisy observation $Y = X +\sigma Z$ where $\sigma$ is the parameter indicating the strength of noise $Z$. Using the conditional expectation framework (that is, $\hat{X}(Y)$ is the conditional mean), we define the normalized error $\mathcal{E}_\sigma = \frac{W}{\sigma}$ and explore its properties. Specifically, in the first part of the paper, we characterize the probability density function of $W$ and $\mathcal{E}_\sigma$. Along the way, we also find conditions for the existence of the inverse functions for the conditional expectations. In the second part, we study pointwise (i.e., almost sure) convergence of $\mathcal{E}_\sigma$ under various assumptions about the noise and the underlying distributions. Our results extend some of the previous limits of $\mathcal{E}_\sigma$ studied under the $L^2$ convergence, known as the \emph{mmse dimension}, to the pointwise case., Comment: 9 pages. Extended version of a paper submitted to IEEE ISIT 2025

This work investigates the influence of a generic anomalous diffusion model on mass convection in a fluid-saturated porous medium, focusing on superdiffusive regimes. A mathematical model is developed, and tability analyses - both linear and nonlinear - are performed. Results demonstrate that the specific form of the time function describing anomalous diffusion significantly affects system stability, allowing stability to persist beyond the classical Rayleigh-B\'enard neutral threshold. Furthermore, transient perturbation growth is observed under certain conditions, followed by eventual decay. The paper systematically examines various memory functions, including power-law, exponential, and logarithmic forms, highlighting their impact on the dynamics of disturbances. The findings underscore the importance of anomalous diffusion in modulating stability and provide new insights into the transient behaviours induced by non-Fickian mass transport., Comment: 20 pages, 7 figures

Characterizing the performance trade-offs between sensing and communication subsystems is essential for enabling integrated sensing and communication systems. Various metrics exist for each subsystem; however, this study focuses on the ergodic capacity of the communication subsystem. Due to the complexity of deriving the sensing mean square error (MSE) and the inapplicability of the Bayesian Cram\'er-Rao Bound to channels with discrete or mixed distributions, this work proposes a Poincar\'e lower bound on the sensing MSE to address these issues. An achievable inner bound for the rate-sensing trade-off in a fading multiple-input multiple-output channel with additive white Gaussian noise and blockage probability is established. In addition, a strategy that is asymptotically optimal for sensing is provided., Comment: 5 pages, 1 figure, 1 table, submitted to IEEE International Symposium on Information Theory (ISIT) 2025 Ann Arbor (Michigan), USA

Artificial Intelligence (AI) in materials science is driving significant advancements in the discovery of advanced materials for energy applications. The recent GNoME protocol identifies over 380,000 novel stable crystals. From this, we identify over 33,000 materials with potential as energy materials forming the Energy-GNoME database. Leveraging Machine Learning (ML) and Deep Learning (DL) tools, our protocol mitigates cross-domain data bias using feature spaces to identify potential candidates for thermoelectric materials, novel battery cathodes, and novel perovskites. Classifiers with both structural and compositional features identify domains of applicability, where we expect enhanced accuracy of the regressors. Such regressors are trained to predict key materials properties like, thermoelectric figure of merit (zT), band gap (Eg), and cathode voltage ($\Delta V_c$). This method significantly narrows the pool of potential candidates, serving as an efficient guide for experimental and computational chemistry investigations and accelerating the discovery of materials suited for electricity generation, energy storage and conversion., Comment: 60 pages, 16 figures

Integrated sensing and communication is regarded as a key enabler for next-generation wireless networks. To optimize the transmitted waveform for both sensing and communication, various performance metrics must be considered. This work focuses on sensing, and specifically on the mean square error (MSE) of channel estimation. Given the complexity of deriving the MSE, the Bayesian Cramer-Rao Bound (BCRB) is commonly recognized as a lower bound on the minimum MSE. However, the BCRB is not applicable to channels with discrete or mixed distributions. To address this limitation, a new lower bound based on a Poincar\'e inequality is proposed and applied to fading MIMO AWGN channels with blockage probability, and the behavior of the lower bound at high SNR is precisely characterized., Comment: Submitted to IEEE WCNC 2025

4H-SiC low gain avalanche detectors (LGADs) have been fabricated and characterized. The devices employ a circular mesa design with low-resistivity contacts and an SiO$_2$ passivation layer. The I-V and C-V characteristics of the 4H-SiC LGADs are compared with complementary 4H-SiC PiN diodes to confirm a high breakdown voltage and low leakage current. Both LGADs and PiN diodes were irradiated with $\alpha$ particles from a $^{210}_{84}\rm{Po}$ source. The charge collected by each device was compared, and it was observed that low-gain charge carrier multiplication is achieved in the 4H-SiC LGAD.

This paper provides a pedagogical introduction to the classical nonlinear stability analysis of the plane Poiseuille and Couette flows. The whole procedure is kept as simple as possible by presenting all the logical steps involved in the application of the energy method and leading to the Euler-Lagrange equations. Then, the eigenvalue problems needed for the evaluation of the nonlinear energy threshold of the Reynolds number for stability are formulated for transverse modes and for longitudinal modes. Such formulations involve the streamfunction and, in the case of longitudinal modes, also the streamwise component of velocity. An accurate numerical solution of the eigenvalue problems, based on Galerkin's method of weighted residuals with the test functions expressed in terms of Chebyshev polynomials, is discussed in details. The numerical codes developed for the software Mathematica 14 (\copyright{} Wolfram Research, Inc.) are also presented. A critical analysis of the obtained results is finally proposed., Comment: 23 pages, 5 figures

The shape of a microchannel cross-section is usually affected by a significant uncertainty due to the small hydraulic diameter. Such an uncertainty is indeed present at any scale, but is amplified in smaller scales, becoming significantly important when the hydraulic diameter is smaller than some tenth micrometers. In this scenario, this paper is focused on analyzing the sensitivity of the heat and fluid flow characteristics with respect to the channel shape, considering a random modifications in the channel cross section. Forced convection in a fully developed regime with a wall slip is considered, and the analysis includes the evaluation of the Fanning friction factor and of the Nusselt number for the H1 thermal boundary condition, considering different slip-flow configurations, as dictated by the slip-length parameter. The heat and fluid flow problem is solved for one thousand randomly generated channel geometries, based on a circular microchannel which is allowed to have its boundary points move within 10\% of its nominal diameter. The calculated data for $f \Re$ and $\Nu$ are then analyzed, and compared with the nominal values (obtained for smooth channels). The results show that, on an average basis, the roughness effect has a tendency to reduce the Nusselt number while increasing the friction factor, however, with a small number of exceptions., Comment: Paper presented at 9h AIGE/IIETA International Conference and 19th AIGE Conference, Caserta (Italy), 3-5 June 2024. arXiv admin note: substantial text overlap with arXiv:2406.11348

The shape of a microchannel is usually affected by a significant uncertainty due to the small size of the cross-section, comparable with the typical wall-roughness length scale. Such an uncertainty is present at any scale, but it is definitely amplified and, hence, significantly important when the hydraulic diameter becomes smaller than some tenth micrometers. The focus of this paper is on the numerical analysis of the sensitivity to shape random modification, within a prefixed maximum extent, of the main flow and heat transfer characteristics of fully-developed forced convection. The numerical solutions are carried out by employing a finite-element solver repeated over a statistical sample of randomly generated perimetral profiles that simulate the wall roughness. The study includes the evaluation of the Fanning friction factor and of the Nusselt number for the T, H1 and H2 thermal boundary conditions., Comment: Paper presented at the 9h AIGE/IIETA International Conference and 19th AIGE Conference (Caserta, Italy, 3-5 June 2024)

The onset of the Rayleigh-Benard instability in a horizontal fluid layer is investigated by assuming the fluid as a binary mixture and the concentration buoyancy as the driving force. The focus of this study is on the anomalous diffusion phenomenology emerging when the mean squared displacement of molecules in the diffusive random walk is not proportional to time, as in the usual Fick's diffusion, but it is proportional to a power of time. The power-law model of anomalous diffusion identifies subdiffusion when the power-law index is smaller than unity, while it describes superdiffusion when the power-law index is larger than unity. This study reconsiders the stability analysis of the Rayleigh-Benard problem by extending the governing equations to include the anomalous diffusion., Comment: 16 pages

In this paper, we i) analyze and classify real-world failures of Kubernetes (the most popular container orchestration system), ii) develop a framework to perform a fault/error injection campaign targeting the data store preserving the cluster state, and iii) compare results of our fault/error injection experiments with real-world failures, showing that our fault/error injections can recreate many real-world failure patterns. The paper aims to address the lack of studies on systematic analyses of Kubernetes failures to date. Our results show that even a single fault/error (e.g., a bit-flip) in the data stored can propagate, causing cluster-wide failures (3% of injections), service networking issues (4%), and service under/overprovisioning (24%). Errors in the fields tracking dependencies between object caused 51% of such cluster-wide failures. We argue that controlled fault/error injection-based testing should be employed to proactively assess Kubernetes' resiliency and guide the design of failure mitigation strategies.

Motivation: Engineering high-affinity binders targeting specific antigenic determinants remains a challenging and often daunting task, requiring extensive experimental screening. Computational methods have the potential to accelerate this process, reducing costs and time, but only if they demonstrate broad applicability and efficiency in exploring mutations, evaluating affinity, and pruning unproductive mutation paths. Results: In response to these challenges, we introduce a new computational platform for optimizing protein binders towards their targets. The platform is organized as a series of modules, performing mutation selection and application, molecular dynamics (MD) simulations to sample conformations around interaction poses, and mutation prioritization using suitable scoring functions. Notably, the platform supports parallel exploration of different mutation streams, enabling in silico high-throughput screening on HPC systems. Furthermore, the platform is highly customizable, allowing users to implement their own protocols. Availability and implementation: the source code is available at https://github. com/pgbarletta/locuaz and documentation is at https://locuaz.readthedocs.io/

The adoption of cloud computing technologies in the industry is paving the way to new manufacturing paradigms. In this paper we propose a model to optimize the orchestration of workloads with differentiated criticality levels on a cloud-enabled factory floor. Preliminary results show that it is possible to optimize the guarantees to deployed jobs without penalizing the number of schedulable jobs. We indicate future research paths to quantitatively evaluate job isolation., Comment: S. Bernardi, T. Zoppi (Editors), Fast Abstracts and Student Forum Proceedings - EDCC 2024 - 19th European Dependable Computing Conference, Leuven, Belgium, 8-11 April 2024

A multi-input multi-output (MIMO) Gaussian channel with two transmit antennas and two receive antennas is studied that is subject to an input peak-power constraint. The capacity and the capacity-achieving input distribution are unknown in general. The problem is shown to be equivalent to a channel with an identity matrix but where the input lies inside and on an ellipse with principal axis length $r_p$ and minor axis length $r_m$. If $r_p \le \sqrt{2}$, then the capacity-achieving input has support on the ellipse. A sufficient condition is derived under which a two-point distribution is optimal. Finally, if $r_m < r_p \le \sqrt{2}$, then the capacity-achieving distribution is discrete., Comment: 8 pages, 1 figure. Submitted to IEEE ISIT 2024

This work considers a binomial noise channel. The paper can be roughly divided into two parts. The first part is concerned with the properties of the capacity-achieving distribution. In particular, for the binomial channel, it is not known if the capacity-achieving distribution is unique since the output space is finite (i.e., supported on integers $0, \ldots, n)$ and the input space is infinite (i.e., supported on the interval $[0,1]$), and there are multiple distributions that induce the same output distribution. This paper shows that the capacity-achieving distribution is unique by appealing to the total positivity property of the binomial kernel. In addition, we provide upper and lower bounds on the cardinality of the support of the capacity-achieving distribution. Specifically, an upper bound of order $ \frac{n}{2}$ is shown, which improves on the previous upper bound of order $n$ due to Witsenhausen. Moreover, a lower bound of order $\sqrt{n}$ is shown. Finally, additional information about the locations and probability values of the support points is established. The second part of the paper focuses on deriving upper and lower bounds on capacity. In particular, firm bounds are established for all $n$ that show that the capacity scales as $\frac{1}{2} \log(n)$., Comment: 15 pages, 1 figure. Extended version of a paper submitted to IEEE ISIT 2024

Calin Galeriu(CG) has commented [1] about our manuscript, "Doppler signature in electrodynamic retarded potentials" [2], that must be properly addressed, amending at the same time of notation errors [3] to clarify some formal aspects which were discussed and criticized in C. Galeriu's comments. The same author (CG) has published three papers concerning the origin of the Doppler term, v/c, in the Li\'enard-Wiechert (L-W) potentials [4-6]., Comment: Reply to arXiv:2302.13404, a comment on arXiv:2202.05393, https://doi.org/10.1016/j.physo.2023.100136

We assume that a sufficiently large database is available, where a physical property of interest and a number of associated ruling primitive variables or observables are stored. We introduce and test two machine learning approaches to discover possible groups or combinations of primitive variables: The first approach is based on regression models whereas the second on classification models. The variable group (here referred to as the new effective good variable) can be considered as successfully found, when the physical property of interest is characterized by the following effective invariant behaviour: In the first method, invariance of the group implies invariance of the property up to a given accuracy; in the other method, upon partition of the physical property values into two or more classes, invariance of the group implies invariance of the class. For the sake of illustration, the two methods are successfully applied to two popular empirical correlations describing the convective heat transfer phenomenon and to the Newton's law of universal gravitation., Comment: 24 pages (main), 8 pages (suppi), 12 figures (main), 3 figures (suppi)

This work considers a discrete-time Poisson noise channel with an input amplitude constraint $\mathsf{A}$ and a dark current parameter $\lambda$. It is known that the capacity-achieving distribution for this channel is discrete with finitely many points. Recently, for $\lambda=0$, a lower bound of order $\sqrt{\mathsf{A}}$ and an upper bound of order $\mathsf{A} \log^2(\mathsf{A})$ have been demonstrated on the cardinality of the support of the optimal input distribution. In this work, we improve these results in several ways. First, we provide upper and lower bounds that hold for non-zero dark current. Second, we produce a sharper upper bound with a far simpler technique. In particular, for $\lambda=0$, we sharpen the upper bound from the order of $\mathsf{A} \log^2(\mathsf{A})$ to the order of $\mathsf{A}$. Finally, some other additional information about the location of the support is provided., Comment: 7 pages, 1 figure, extended version of a paper submitted to IEEE ISIT 2024

We investigate the fully nonlinear model for convection in a Darcy porous material where the diffusion is of anomalous type as recently proposed by Barletta. The fully nonlinear model is analysed but we allow for variable gravity or penetrative convection effects which result in spatially dependent coefficients. This spatial dependence usually requires numerical solution even in the linearized case. In this work we demonstrate that regardless of the size of the Rayleigh number the perturbation solution will decay exponentially in time for the superdiffusion case. In addition we establish a similar result for convection in a bidisperse porous medium where both macro and micro porosity effects are present. Moreover, we demonstrate a similar result for thermosolutal convection., Comment: 9 pages

We discuss single-shot decoding of quantum Calderbank-Shor-Steane codes with faulty syndrome measurements. We state the problem as a joint source-channel coding problem. By adding redundant rows to the code's parity-check matrix we obtain an additional syndrome error correcting code which addresses faulty syndrome measurements. Thereby, the redundant rows are chosen to obtain good syndrome error correcting capabilities while keeping the stabilizer weights low. Optimal joint decoding rules are derived which, though too complex for general codes, can be evaluated for short quantum codes., Comment: 6 pages, 4 figures

The analysis of the Rayleigh-B\'enard instability due to the mass diffusion in a fluid-saturated horizontal porous layer is reconsidered. The standard diffusion theory based on the variance of the molecular position growing linearly in time is generalised to anomalous diffusion, where the variance is modelled as a power-law function of time. A model of anomalous diffusion based on a time-dependent mass diffusion coefficient is adopted, together with Darcy's law, for momentum transfer, and the Boussinesq approximation, for the description of the buoyant flow. A linear stability analysis is carried out for a basic state where the solute has a potentially unstable concentration distribution varying linearly in the vertical direction and the fluid is at rest. It is shown that any, even slight, departure from the standard diffusion process has a dramatic effect on the onset conditions of the instability. This circumstance reveals a strong sensitivity to the anomalous diffusion index. It is shown that subdiffusion yields instability for every positive mass diffusion Rayleigh number, while superdiffusion brings stabilisation no matter how large is the Rayleigh number. A discussion of the linear stability analysis based on the Galilei-variant fractional-derivative model of subdiffusion is eventually carried out., Comment: 19 pages, 6 figures

Narrowband power line communication (NB-PLC) systems are an attractive solution for supporting current and future smart grids. A technology proposed to enhance data rate in NB-PLC is multiple-input multiple-output (MIMO) transmission over multiple power line phases. To achieve reliable communication over MIMO NB-PLC, a key challenge is to take into account and mitigate the effects of temporally and spatially correlated cyclostationary noise. Noise samples in a cycle can be divided into three classes with different distributions, i.e. Gaussian, moderate impulsive, and strong impulsive. However, in this paper we first show that the impulsive classes in their turn can be divided into sub-classes with normal distributions and, after deriving the theoretical capacity, two noise sample sets with such characteristics are used to evaluate achievable information rates: one sample set is the measured noise in laboratory and the other is produced through MIMO frequency-shift (FRESH) filtering. The achievable information rates are attained by means of a spatio-temporal whitening of the portions of the cyclostationary correlated noise samples that belong to the Gaussian sub-classes. The proposed approach can be useful to design the optimal receiver in terms of bit allocation using waterfilling algorithm and to adapt modulation order., Comment: 13 pages, 10 figures, submitted to IEEE Transactions on Communications

This paper explores the Achievable Information Rate (AIR) of a diffusive Molecular Communication (MC) channel featuring a fully absorbing receiver that counts the absorbed particles during symbol time intervals (STIs) and resets the counter at the start of each interval. The MC channel, influenced by memory effect, experiences inter-symbol interference (ISI) arising from the molecules' delayed arrival. The channel's memory is quantified as an integer multiple of the STI and a single-sample memoryless detector is employed to mitigate complexity in computing the mutual information (MI). To maximize MI, the detector threshold is optimized under Gaussian approximation of its input. The channel's MI is calculated, considering the influence of ISI, in the context of binary concentration shift keying modulation. Two distinct scenarios were considered; independent and correlated source-generated symbols, the latter modeled as a first-order Markov process. For each communication scenario, two degrees of knowledge: ISI-Aware and ISI-Unaware were considered. Remarkably, it is demonstrated that employing a correlated source enables the attainment of higher capacity. The results indicate that the capacity-achieving input distribution is not necessarily uniform. Notably, when the STI is small, corresponding to the case of strong ISI, the maximum AIR is not achieved through equiprobable symbol transmission., Comment: 13 pages, 12 figure. arXiv admin note: text overlap with arXiv:2306.04261