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The charge/mass distribution f(q/m) of nanodrops and ions electrosprayed in vacuum from mixtures of formamide (FM) and methylammonium formate (MAF) is studied by time of flight mass spectrometry at MAF/FM volumetric concentrations of 5%, 10%, 25% and 50%. Positive and negative polarities yield comparable f(q/m) curves, though the negative mode yields ~30% larger currents. On shifting from the highest to the lowest liquid flow rates, at which a cone-jet is stable, the more conducting solutions evolve from mostly drop to primarily ion emission. A purely ionic regime is not reached under any condition, but the drops achieve unusually high q/m. As a result, these sprays have excellent electrical propulsion characteristics, some being able to cover a 25-fold range of average q/m with a propulsive efficiency typically in the range of 80%. Results of formamide electrolytes with formates and nitrates of several other amines are more briefly reported.

The KM3NeT Collaboration is constructing two large neutrino detectors in the Mediterranean Sea: ARCA, located near Sicily and aiming at neutrino astronomy, and ORCA located near Toulon and designed for the study of intrinsic neutrino properties. The two detectors together will have hundreds of Detection Units with Digital Optical Modules kept vertically by buoyancy forming a large 3D optical array for detecting the Cherenkov light produced after the neutrino interactions. To properly reconstruct the direction of the incoming neutrino, the position of the DOMs, which are not static due to the sea currents, must be monitored. For this purpose, the detector is equipped with an Acoustic Positioning System, which is composed of fixed acoustic emitters on the sea bottom, a hydrophone in each DU base, and a piezoceramic sensor in each DOM, as acoustic receivers. This network of acoustic sensors can be used not only for positioning, but also for acoustic monitoring studies such as bioacoustics, ship noise monitoring, environmental noise control, and acoustic neutrinos detection. This work explores the possibility of creating a trigger for saving the data for ultra-high-energy neutrino candidates detected acoustically by the hydrophones. The acoustic signal caused by the neutrino interaction in a fluid is a short-time duration Bipolar Pulse extremely directive and with a Fourier transform extending over a wide range of frequencies. A study of signal detection, has been done by simulating BP produced by the interaction of a UHE neutrino at 1 km from the detector at zero-degree incidence added to the experimental real acoustic data. Finally, a trigger proposal has been developed in order to record candidates of BPs and it has been tested. The number of candidates per second, precision, and recall have been monitored according to the cuts applied and parameters calculated by the algorithm., Comment: 9th International Workshop on Acoustic and Radio EeV Neutrino Detection Activities - ARENA2022

Cellular automata are capable of developing complex behaviors based on simple local interactions between their elements. Some of these characteristics have been used to propose and improve meta-heuristics for global optimization; however, the properties offered by the evolution rules in cellular automata have not yet been used directly in optimization tasks. Inspired by the complexity that various evolution rules of cellular automata can offer, the continuous-state cellular automata algorithm (CCAA) is proposed. In this way, the CCAA takes advantage of different evolution rules to maintain a balance that maximizes the exploration and exploitation properties in each iteration. The efficiency of the CCAA is proven with 33 test problems widely used in the literature, 4 engineering applications that were also used in recent literature, and the design of adaptive infinite-impulse response (IIR) filters, testing 10 full-order IIR reference functions. The numerical results prove its competitiveness in comparison with state-of-the-art algorithms. The source codes of the CCAA are publicly available at https://github.com/juanseck/CCAA.git, Comment: 39 pages, 13 figures and 28 tables. Submitted to Expert Systems With Applications

The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new meta-heuristic algorithm called GLNSA (Global-local neighborhood search algorithm), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called "smart_cells" generates and shares information that helps to optimize instances of FJSP. The GLNSA algorithm is complemented with a tabu search that implements a simplified version of the Nopt1 neighborhood defined in [1] to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms and widely cited in the specialized bibliography, using 86 test problems, improving the optimal result reported in previous works in two of them., Comment: 33 pages, 25 figures, Submitted to: PeerJ Comput. Sci

The emergence of complex behaviors in cellular automata is an area that has been widely developed in recent years with the intention to generate and analyze automata that produce space-moving patterns or gliders that interact in a periodic background. Frequently, this type of automata has been found through either an exhaustive search or a meticulous construction of the evolution rule. In this study, the specification of cellular automata with complex behaviors was obtained by utilizing randomly generated specimens. In particular, it proposed that a cellular automaton of $n$ states should be specified at random and then extended to another automaton with a higher number of states so that the original automaton operates as a periodic background where the additional states serve to define the gliders. Moreover, this study presented an explanation of this method. Furthermore, the random way of defining complex cellular automata was studied by using mean-field approximations for various states and local entropy measures. This specification was refined with a genetic algorithm to obtain specimens with a higher degree of complexity. With this methodology, it was possible to generate complex automata with hundreds of states, demonstrating that randomly defined local interactions with multiple states can construct complexity., Comment: 30 pages, 22 figures, Submitted to: Inf Sci

Complexity has been a recurrent research topic in cellular automata because they represent systems where complex behaviors emerge from simple local interactions. A significant amount of previous research has been conducted proposing instances of complex cellular automata; however, most of the proposed methods are based on a careful search or a meticulous construction of evolution rules. This paper presents the emergence of complex behaviors based on reversible cellular automata. In particular, this paper shows that reversible cellular automata represent an adequate framework to obtain complex behaviors adding only new random states. Experimental results show that complexity can be obtained from reversible cellular automata appending a proportion of about two times more states at random than the original number of states in the reversible automaton. Thus, it is possible to obtain complex cellular automata with dozens of states. Complexity appears to be commonly obtained from reversible cellular automata, and using other operations such as permutations of states or row and column permutations in the evolution rule. The relevance of this paper is to present that reversibility can be a useful structure to implement complex behaviors in cellular automata., Comment: 26 pages, 14 figures, Submitted to: Comm Nonlinear Sci Numer Simulat

A semiempirical model, based in the logistic map, has been succesfully applied to forecast important quantities along the several phases of the outbreak of the covid-19 for different countries. This paper shows how the model was calibrated and applied to perform predictions of people needing to be hospitalized, needs of ventilators, or the number of deaths which would be produced. It is shown specifically the results obtained in the case of Spain, showing a prediction of diagnosed infected and deaths which will be observed after the ease of the total lockdown produced the 13th of March. Is also shown how this model can provide an insight of what the level of infection in the different regions of Spain is forecasted. The model predicts for Spain for the end of May more than 400,000 diagnosed infected cases, number which will be probably higher due to the change in the possibilities of performing massive number of tests to the general population. The number of forecasted deaths for that date is 46,000 +/- 15,000. The model also predicts the level of infection at the different Spanish regions, providing a counterintuitive result in the cases of Madrid and Catalonia as the result shows a higher the level of infection at Catalonia than the level at Madrid, according with this model. All of these results can be used to guide policy makers in order to optimize resources and to avoid future outbreaks of the covid-19.

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches.

The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between track-type and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project., Comment: 45 pages, 10 figures

The history of computing in Mexico can not be thought without the name of Prof. Harold V. McIntosh (1929-2015). For almost 50 years, in Mexico he contributed to the development of computer science with wide international recognition. Approximately in 1964, McIntosh began working in the Physics Department of the Advanced Studies Center (CIEA) of the National Polytechnic Institute (IPN), now called CINVESTAV. In 1965, at the National Center of Calculus (CeNaC), he was a founding member of the Master in Computing, first in Latin America. With the support of Mario Baez Camargo and Enrique Melrose, McIntosh continues his research of Martin-Baltimore Computer Center and University of Florida at IBM 709., Comment: 13 pages, 1 figure

High-resolution DMAs requiring hundreds of liters per minute of sheath gas flow Q to classify 1 nm particles have not been previously examined and optimized under the modest Q values (tens of liters per minute) needed to classify particles well above 10 nm. Here we study the resolving power R (based on the relative width of the transfer function) of the Halfmini DMA, at sample flow rates q beyond 1 l/min. The charge-reduced electrosprayed ovalbumin protein used as test aerosol has an accurately determinable Gaussian mobility distribution, which limits the measurable R to at most 25 to 30. Non-ideal DMA response can however be precisely probed by comparing measured peak widths with the convolution of the protein's mobility distribution with the triangular Knutson-Whitby distribution associated to the finite qi/Q ratio. For the unmodified Halfmini DMA, R departs considerably from ideal at qi/Q values as modest as 2%, revealing a problem with the aerosol inlet flow. This imperfection is not removed by either increasing or decreasing the slit width, nor by reorienting axially the sample flow jet as it merges with the sheath gas. By introducing a ring with many perforations upstream of the inlet slit, which favors a more symmetric distribution of the sample flow over the slit perimeter, R values close to ideal are approached with qi/Q ratios as large as 6 to 12%. This improvement enables (in principle) classification of particles larger than 30 nm., Comment: 17 pages, 9 figures, Published in J. Aerosol Science, 2017

We overview networks which characterise dynamics in cellular automata. These networks are derived from one-dimensional cellular automaton rules and global states of the automaton evolution: de Bruijn diagrams, subsystem diagrams, basins of attraction, and jump-graphs. These networks are used to understand properties of spatially-extended dynamical systems: emergence of non-trivial patterns, self-organisation, reversibility and chaos. Particular attention is paid to networks determined by travelling self-localisations, or gliders., Comment: 25 pages, 14 figures

In previous works, hexagonal cellular automata (CA) have been studied as a variation of the famous Game of Life CA, mainly for spiral phenomena simulations; where the most interesting constructions are related to the Belousov-Zhabotinsky reaction. In this paper, we analyse a special kind of hexagonal CA, {\it Spiral rule}. Such automaton shows a non-trivial complex behaviour related to discrete models of reaction-diffusion chemical media, dominated by spiral guns which easily emerge from random initial conditions. The computing capabilities of this automaton are shown by means of logic gates. These are defined by collisions between mobile localizations. Also, an extended classification of complex self-localisation patterns is presented, including some self-organised patterns., Comment: 20 pages, 14 figures, 6 tables

This paper examines the claim that cellular automata (CA) belonging to Class III (in Wolfram's classification) are capable of (Turing universal) computation. We explore some chaotic CA (believed to belong to Class III) reported over the course of the CA history, that may be candidates for universal computation, hence spurring the discussion on Turing universality on both Wolfram's classes III and IV., Comment: arXiv admin note: substantial text overlap with arXiv:1208.2456

Using Rule 126 elementary cellular automaton (ECA) we demonstrate that a chaotic discrete system --- when enriched with memory -- hence exhibits complex dynamics where such space exploits on an ample universe of periodic patterns induced from original information of the ahistorical system. First we analyse classic ECA Rule 126 to identify basic characteristics with mean field theory, basins, and de Bruijn diagrams. In order to derive this complex dynamics, we use a kind of memory on Rule 126; from here interactions between gliders are studied for detecting stationary patterns, glider guns and simulating specific simple computable functions produced by glider collisions.

In this paper, we present the acoustic transceiver developed for the positioning system in underwater neutrino telescopes. These infrastructures are not completely rigid and need a positioning system in order to monitor the position of the optical sensors of the telescope which have some degree of motion due to sea currents. To have a highly reliable and versatile system in the infrastructure, the transceiver has the requirements of reduced cost, low power consumption, high intensity for emission, low intrinsic noise, arbitrary signals for emission and the capacity of acquiring and processing the received signal on the board. The solution proposed and presented here consists of an acoustic transducer that works in the 20-40 kHz region and withstands high pressures (up to 500 bars). The electronic-board can be configured from shore and is able to feed the transducer with arbitrary signals and to control the transmitted and received signals with very good timing precision. The results of the different tests done on the transceiver in the laboratory are described here, as well as the change implemented for its integration in the Instrumentation Line of ANTARES for the in situ tests. We consider the transceiver design is so versatile that it may be used in other kinds of marine positioning systems, alone or combined with other marine systems, or integrated in different Earth-Sea Observatories, where the localization of the sensors is an issue., Comment: 6 pages, 10 figures

In this paper acoustic transmitters that were developed for use in underwater neutrino telescopes are presented. Firstly, an acoustic transceiver has been developed as part of the acoustic positioning system of neutrino telescopes. These infrastructures are not completely rigid and require a positioning system in order to monitor the position of the optical sensors which move due to sea currents. To guarantee a reliable and versatile system, the transceiver has the requirements of reduced cost, low power consumption, high pressure withstanding (up to 500 bars), high intensity for emission, low intrinsic noise, arbitrary signals for emission and the capacity of acquiring and processing received signals. Secondly, a compact acoustic transmitter array has been developed for the calibration of acoustic neutrino detection systems. The array is able to mimic the signature of ultra-high-energy neutrino interaction in emission directivity and signal shape. The technique of parametric acoustic sources has been used to achieve the proposed aim. The developed compact array has practical features such as easy manageability and operation. The prototype designs and the results of different tests are described. The techniques applied for these two acoustic systems are so powerful and versatile that may be of interest in other marine applications using acoustic transmitters., Comment: 21 pages, 14 figures,1 table

Rule 110 is a complex elementary cellular automaton able of supporting universal computation and complicated collision-based reactions between gliders. We propose a representation for coding initial conditions by means of a finite subset of regular expressions. The sequences are extracted both from de Bruijn diagrams and tiles specifying a set of phases fi_1 for each glider in Rule 110. The subset of regular expressions is explained in detail., Comment: by publish in Journal of Cellular Automata