The applicability of the distance aggregation problem has attracted the interest of many authors. Motivated by this fact, in this paper we face the modular quasi-(pseudo-)metric aggregation problem. We characterize those functions that allow merging a collection of modular quasi-(pseudo-)metrics into a single one. Specifically, a description of such functions in terms of triangle triplets is given and, in addition, the relationship between modular quasi-(pseudo-)metric aggregation functions and modular (pseudo-)metric aggregation functions is discussed. Such characterizations are illustrated with appropriate examples. A few methods to construct modular quasi-(pseudo-)metrics are yielded. Several properties of modular quasi-(pseudo-)metric aggregation functions are explored and used to develop quick tests for discarding candidate functions to aggregate modular quasi-(pseudo-)metrics. Moreover, a characterization of those modular quasi-(pseudo-)metric aggregation functions that preserve modular quasi-(pseudo-)metrics is also provided. Furthermore, the relationship between modular quasi-(pseudo-)metric aggregation functions and quasi-(pseudo-)metric aggregation functions is studied in such a way that significative differences are displayed.

We carry out a systematic study on the motion of test particles in the region inner to the naked singularity of a quasi–hyperbolically symmetric γ-metric. The geodesic equations are written and analyzed in detail. The obtained results are contrasted with the corresponding results obtained for the axially symmetric γ-metric, and the hyperbolically symmetric black hole. As in this latter case, it is found that test particles experience a repulsive force within the horizon (naked singularity), which prevents them to reach the center. However in the present case this behavior is affected by the parameter γ which measures the departure from the hyperbolical symmetry. These results are obtained for radially moving particles as well as for particles moving in the θ−r subspace. Possible relevance of these results in the explanation of extragalactic jets, is brought out. .

In the framework of a multiplicative metric space. We have discuss some Properties of convex structures in pseudo multiplicative metric space and have applied these properties toiobtain alfixed point results in complete pseudo. It would be interesting to prove some further results in such metric spaces with completeness property.

We introduce the notion of generalized contraction on dualistic partial metric spaces. A fixed point theorem for mappings satisfying above mentioned contraction is obtained. Some consequences of our result are obtained. We construct an example to demonstrate the effectiveness of our result among the corresponding results in partial metric spaces. Our results provide substantial generalizations and improvements of several well known results existing in the comparable literature. We discuss an application of our fixed point results to show the existence of solution of functional equations.

Diverse development models, including waterfall development, iterative development, and agile development, have been put forth and implemented across real-world contexts. When engaging in discussions on project management, the examination and exploration of development models assume paramount importance and are integral. This paper embarks upon an investigation and scrutiny of these development models, culminating in the proposition of "Quasi" Development Models: Quasi-Waterfall and Quasi-Agile.

The life cycle of a microgrid covers all the stages from idea to implementation, exploitation until its end of life, but with a lifespan of around 25 years. Covering them usually requires several software tools, which can make integration of results from different stages very difficult and may imply costs hard to estimate from the beginning of a project. This paper proposes a single platform of four modules developed in Matlab to assist all the processes a microgrid passes during its lifetime. The authors detail the architecture, functions and the development of the platform, either by using existing tools available in Matlab, or by developing new ones and designing new user interfaces linked with scripts based on its complex mathematical libraries. A proof-of-concept for this platform was presented by applying the life-cycle assessment process on a real-case study, a microgrid consisting in a photovoltaic plant, an office building as consumer and energy storage units.

In this paper, we investigate the effects of certain variants of the commutative laws on properties of several families of algebras which are in general not commutative, such as groups, linear algebras, or actually quite anti-commutative, such as $BCK$-algebras and $d$-algebras among others. From results obtained it becomes clear that by considering these variants in the presence of yet other axioms it is to be expected that a quite rich and varied set of results may be obtained both in the general and the particular setting of which what has been accomplished in this paper is a substantial sample.

The study is based on information as the property of matter and its evolution from chemical to digital information. Consequences of these forms of information include molecular, modular, cel-lular, non-human, and human individual interactions, as well as human-machine interaction, and the formation of corresponding modules through self-organizing selective processes. The function of modular structures is decision-making and is analogous to the behavior of an intelligent agent. The evolutionary modular model is proposed based on the interaction of evolutionary factors (matter, energy, information, self-organization, natural selection, and heritability) among themselves and with the arrow of time. In conclusion, we realize that the essence of the evolution of living organ-isms is modular evolution. Modules through which the survival and reproduction of living organ-isms is ensured, are formed by two basic molecular processes, which are molecular recognition or information and modular self-organization.

Helical (frontier) molecular orbitals [Chem. Sci. 2013, 4, 4278] have been reported almost a decade ago. Yet, helical molecular spin densities [Mol. Phys. 2022, e2157774] have been observed by us only very recently. In this work, we have observed that some chiral boron clusters (B–16, B–20, B–24, and B–28) can simultaneously have helical molecular orbitals and helical spin densities. To our best knowledge, it is the first time we have discovered that inorganic boron clusters assume such an unprecedented property. We have unambiguously unraveled that it is chiral Jahn-Teller distortion of quasi-planar boron clusters that drives the formation of helical molecular spin densities. More interestingly, we have shown that elongation/enhancement of helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity properties of these boron clusters are also discussed. Implication of this work is straightforward that boron clusters may find potential applications in spintronics, such as molecular magnets.

This research critically examines the dichotomies in urban public space and discussions on city evolution over the past two centuries. The original discourse identified amplifies the importance that inclusivity needs to address issues deeper than physical accessibility. The growing diversity and changes seen in urban public open spaces are followed throughout history along a timeline of important socio-political and planning injectors in the Western world. These public spaces are the important spine connecting all the private and semi-private parts of the city. Urban public spaces have seen population changes due to globalisation, resulting in mobility and changes due to the different needs of its diverse user base. In this paper, a rigorous quasi-chronological investigation is presented. Firstly, the context of the evolution of space is established. Secondly, a closer focus on inclusion research provides a thorough analysis of the utopian city plans, the development of Haussmann's Paris and the later plans of the Centrist and the Decentrist. Thirdly, a critical and analytical understanding of the effect these precursors have had on the city's public spaces, and the hierarchies it established in a nuanced manner are made explicit. The culmination of this research process is the identification of outcomes associated with inclusivity. Findings are established across three significant themes—a) Understanding public space as social space, b) Components of inclusivity, and c) Values of inclusivity including accessibility, sense of place, conviviality and resilience. Key insights and guidance for inclusivity as a key constituent of social sustainability are the unique contribution.

Splines and quasi-interpolation operators are important both in approximation theory and applications. In this paper, we construct a family of quasi-interpolation operators for the bivariate quintic spline spaces S₅³ (∆_mn⁽²⁾). Moreover, the properties of the proposed quasi-interpolation operators are studied, as well as its applications for solving two-dimensional Burgers’ equation and image reconstruction. Some numerical examples show that these methods, which are easy to implement, provide accurate results.

Soft magnetic composites cores were produced by Spark Plasma Sintering (SPS) from Ni3Fe@ZnFe2O4 and NiFeMo@ZnFe2O4 pseudo-core-shell powders. In the Fe-Ni alloys@ZnFe2O4 pseudo-core-shell composite powders, the core is a large nanocrystalline Permalloy or Supermalloy particle obtained by mechanical alloying, and the shell is a pseudo continuously layer of Zn ferrite particles. The pseudo-core-shell powders have been compacted by SPS at temperatures between 500-700 ºC, with a holding time of 0 minutes. Several techniques were used for the characterisation of the powders and sintered compacts: X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectroscopy, magnetic hysteresis measurements (DC and AC) and electrical resistivity. The electrical resistivity is stabilised at values of about 7·10-3 Ω·m for sintering temperatures between 600-700 °C and this value is 3 orders of magnitude higher than the electrical resistivity of sintered Fe compacts. The best relative initial permeability was obtained for the Supermalloy/ZnFe2O4 composite compacts sintered at 600 ºC, which decreases linearly for the entire frequency range studied, from around 95 to 50. Up a frequency of 2,000 Hz the power losses are lower than 1.5 W/kg. At the frequency of 10 kHz, the power losses are larger, but they remain at a low level. In the case of Supermalloy/ZnFe2O4 composite compact SPS-ed at 700 °C, the specific power losses are even lower than 5 W/kg. The power losses decomposition proved that intra-particles losses give the main part of the losses.

Cyberattacks are rapidly evolving both in terms of techniques and frequency, from low-level attacks through to sophisticated Advanced Persistent Threat (APT). There is a need to consider how testbed environments such as cyber ranges can be readily deployed to improve examination of attack characteristics and the assessment of defences. Whilst cyber ranges are not new, they can often be computational expensive, require significant setup and configuration, or may not provide full support for areas such as logging or ongoing learning. In this paper, we propose GoibhniUWE, a container-based cyber range that provides a flexible platform for investigating the full lifecycle of a cyber attack. Adopting a modular approach, users can seamlessly switch out existing, containerised vulnerable services, deploying multiple different services at once allowing for the creation of complex and realistic deployments. The range is fully instrumented with logging capabilities from a variety of sources including Intrusion Detection Systems (IDS), service logging, and network traffic captures. To demonstrate the effectiveness of our approach, we deploy the GoibhniUWE range under multiple conditions to simulate various vulnerable environments, reporting on and comparing key metrics such as CPU and memory usage. We simulate complex attacks which span multiple services and networks, with logging at multiple levels, modelling an Advance Persistent Threat (APT) and their associated Tactics, Techniques, and Procedures (TTPs). We find that even under continuous, active and targeted deployment GoibhniUWE averaged a CPU usage of less than 2 processors and memory usage of less than 4.5 GB.

Transformation formula under the action of a general linear fractional transformation for generalized Dedekind eta-function has been a subject of intensive study, Rademacher, Dieter, Meyer et al. However, the (Hecke) modular relation structure has not been recognized until the work of Goldstein-de la Torre, and streamlining the classical proofs in the modular relation will reveal the meaning hidden in those works. Our main aim is to elucidate the works of these researchers in the context of modular relations.

This study provides a comprehensive analysis of the conformational dynamics of pseudo-endocannabinoid receptors (p-CBRs) CB₁ and CB₂ in response to ligand binding. The ligands studied include N-arachidonoyl dopamine (NADA), Cannabidiol (CBD), known agonists (FUB-MDMB and E3R), and inverse agonists (Taranabant and AM630). Using homology models based on crystal structures (PDB ID: 5U09 for CB₁ and 5ZTY for CB₂), molecular docking, and molecular dynamics (MD) simulations, the research validates the structural integrity and dynamic behaviours of these pseudo-receptors. Induced-fit docking revealed NADA as having the highest binding affinity for both receptors, with docking scores of −13.92 kcal/mol for CB₁ and −13.32 kcal/mol for CB₂, facilitated by key hydrogen bond interactions. MD simulations over 250 ns at ~298 K showed successful equilibration, indicating the most stable interaction for NADA, thereby further validating the models. CB₁ and CB₂ exhibited distinct conformational responses to ligands, with Cα RMSD and Cα RMSF analyses suggesting a more rigid binding pocket for CB₁ and a flexible binding pocket for CB₂. These findings highlight the significance of receptor behaviour and dynamics in the development of cannabinoid-based therapeutics, supporting the potential of CBD and NADA as modulators for CB₁ and CB₂, respectively.

Most popular machine learning algorithms like k-nearest neighbour, k-means, SVM uses a metric to identify the distance(or similarity) between data instances. It is clear that performances of these algorithm heavily depends on the metric being used. In absence of prior knowledge about data we can only use general purpose metrics like Euclidean distance, Cosine similarity or Manhattan distance etc, but these metric often fail to capture the correct behaviour of data which directly affects the performance of the learning algorithm. Solution to this problem is to tune the metric according to the data and the problem, manually deriving the metric for high dimensional data which is often difficult to even visualize is not only tedious but is extremely difficult. Which leads to put effort on \textit{metric learning} which satisfies the data geometry.Goal of metric learning algorithm is to learn a metric which assigns small distance to similar points and relatively large distance to dissimilar points.

In this paper, we study the semilinear pseudo-parabolic equations $\displaystyle u_{t} - \triangle_{\mathbb{B}}u - \triangle_{\mathbb{B}}u_{t} = \left|u\right|^{p-1}u$ on a manifold with conical singularity, where $\triangle _{\mathbb{B}}$ is Fuchsian type Laplace operator investigated with totally characteristic degeneracy on the boundary $x_{1} = 0$. Firstly, we discuss the invariant sets and the vacuum isolating behavior of solutions with the help of a family of potential wells. Then, we derive a threshold result of existence and nonexistence of global weak solution: for the low initial energy $J(u_{0})<d$, the solution is global in time with $I(u_{0}) >0$ or $\displaystyle\Vert \nabla_{\mathbb{B}}u_{0}\Vert_{L_{2}^{\frac{n}{2}}(\mathbb{B})} = 0$ and blows up in finite time with $I(u_{0}) < 0$; for the critical initial energy $J(u_{0}) = d$, the solution is global in time with $I(u_{0}) \geq0$ and blows up in finite time with $I(u_{0}) < 0$. The decay estimate of the energy functional for the global solution and the estimates of the lifespan of local solution are also given.

Our method for density elimination is generalized to the non-commutative substructural logic GpsUL∗. Then the standard completeness of HpsUL∗follows as a lemma by virtue of previous workbyMetcalfeandMontagna. This result shows that HpsUL∗ is the logic of pseudo-uninorms and their residua and answered the question posed by Prof. Metcalfe, Olivetti, Gabbay and Tsinakis.

Firstly, a new set of Quasi-Cubic Trigonometric Bernstein basis with two tension shape parameters is constructed, and we prove that it is an optimal normalized totally basis in the framework of Quasi Extended Chebyshev space. And the Quasi-Cubic Trigonometric Bézier curve is generated by the basis function and the cutting algorithm of the curve are given, the shape features (cusp, inflection point, loop and convexity) of the Quasi-Cubic Trigonometric Bézier curve are analyzed by using envelope theory and topological mapping; Next we construct the non-uniform Quasi-Cubic Trigonometric B-spline basis by assuming the linear combination of the optimal normalized totally positive basis have partition of unity and continuity, and its expression is obtained. And the non-uniform B-spline basis is proved to have totally positive and high-order continuity. Finally, the non-uniform Quasi Cubic Trigonometric B-spline curve and surface are defined, the shape features of the non-uniform Quasi-Cubic Trigonometric B-spline curve are discussed, and the curve and surface are proved to be continuous.

Quasi-solid composited electrolytes were produced by LiFSI initiated polymerized poly-(Dioxolane) (PDOL) with garnet-LLZO (Li7La2Zr3O12) nanofibers and used in lithium-metal batteries. Linear sweep voltammetry shows that the initial oxidation voltage of 4.6 V for Gel-10% (G10, 10% wt. LLZO in PDOL) vs Li/Li+. EIS test of stainless steel// stainless steel symmetric cells for Gel-1% (G1), Gel-5% (G5) and Gel-10% (G10) show ion conductivity (5*10-5 S/cm). Li/G10/Li symmetric cells have stable stripping-plating cycling performance over 1300 hours continuously with the current density of 0.1 mA/cm2 at 25 oC, indicating a good interface contact and stable lithium-ion transport pathway through the composite electrolytes. LFP/G10/Li batteries have stable charge-discharge plateau, low polarization voltage of 0.07-volt, energy efficiency of 95% and coulombic efficiency of ~99% at current density of 26.3 mA/g at 25 oC for over 100 cycles.

Low-frequency electromagnetic induction (EMI) is a non-invasive geophysical method that is based on the induction of electromagnetic (EM) waves into the subsurface to quantify changes in electrical conductivity. In this study we present an open (design details and software are accessible) and modular system for the collection of EMI data. The instrument proposed allows to adjust the separations between the transmitter and up to four receiving antennas as well as the acquisition frequency (in the range between 3 and 50 kHz) to permit measurements with variable depth of investigation. The sensor provides access to raw data and the software described in this study allows control of the signal processing chain. The design specifications permit apparent conductivity measurements in the range of between 1 mS/m and 1000 mS/m, with a resolution of 1.0 mS/m and with a sampling rate of up to 10 samples per second. The sensor allows for a synchronous acquisition of a time stamp and a location stamp for each data sample. The sensor has a mass of less than 5 kg, is portable and suitable for 1-person operation, provides 4 hours of operation time on one battery charge, and provides sufficient rigidity for practical field operations.

In this article, some kinds of triple belongs to metric dimensions are defined. Some classes of graphs in the matter of these kinds, are studied and the relation amid these kinds are considered. The kind of having equivalency amid these notions and some classes of graphs, is obtained. The kind of locating some vertices by some vertices when the number of locating vertices is increased, has the key role to analyze the classes of graphs, general graphs, and graph's parameters.

In this outlet, I’ve devised the concept of relation amid two points where these points are coming up to make situation which in that the set of objects are greed to represent the story of how to be in whatever situations when these two points have the styles of being everywhere in the highlights of the concept which are coming from the merits of these points where are eligible to make capable situation to overcome every situation when they’re participant in the hugely diverse situations which mean too styles of graphs with have the name or the general results for the general situation as possible as are.

We report on recent experimental results on β decay into self-conjugate (N=Z) nuclei with mass number 58≤A≤70. Super-allowed β decays from the Jπ=0+ ground state of a Z=N+2 parent nucleus are to the isobaric analogue state, through so-called Fermi transitions, and to Jπ=1+ states, by way of Gamow–Teller (GT) transitions. The operator of the latter decay is a generator of Wigner’s SU(4) algebra and as a consequence GT transitions obey selection rules associated with this symmetry. Since SU(4) is progressively broken with increasing A, mainly as a consequence of the spin–orbit interaction, this symmetry is not relevant for the nuclei considered here. We argue, however, that the pseudo-spin–orbit splitting can be small in nuclei with 58≤A≤70, in which case nuclear states exhibit an approximate pseudo-SU(4) symmetry. To test this conjecture, GT decay strength is calculated with use of a schematic Hamiltonian with pseudo-SU(4) symmetry. Some generic features of the GT β decay due to pseudo-SU(4) symmetry are pointed out. The experimentally observed GT strength indicates a restoration of pseudo-SU(4) symmetry for A=70.

This paper investigates pseudo-polymorphism in 2-pyridylmethoxy derivatives of p-tert-butylcalix[4]arene (PyC4), p-tert-butyldihomooxa-calix[4]arenes (PyHOC4), and p-tert-butylhexahomotrioxacalix[3]arenes (PyHO3C3), presenting 11 crystal structures with 15 crystallographically independent molecules. The macrocycle of PyC4 is smaller and less flexible with respect to those of PyHOC4 and PyHO3C3 and in solution, the cone conformation of these three molecules exhibit different point symmetries: C4, Cs and C3, respectively. A correlation is observed between the macrocycle's structural rigidity and the number of pseudo-polymorphs formed. The more rigid PyC4 displays a higher number (6) of pseudo-polymorphs compared to PyHOC4 and PyHO3C3, which exhibit a smaller number of crystalline forms (3 and 2, respectively). The X-ray structures obtained show that the conformation of the macrorings is primarily influenced by the presence of an acetonitrile guest molecule within the cavity, with limited impact from crystal packing and intermolecular cocrystallized solvent molecules. Notably, both calix[4]arene derivatives produce host-guest complex with acetonitrile, while the most flexible and less aromatic PyHO3C3 do not give crystals with acetonitrile as guest. Intertwined 1D and 2D solvent channel networks were observed in the PyHOC4-hexane and in the PyHO3C3-H2O-MeOH crystal structures, respectively, while the other pseudopolymorphs of PyHOC4 and PyHO3C3 and all PyC4 crystal forms exhibit a closely packed crystal structures without open channels.

Khosravi, Drnov\v{s}ek and Moslehian [\textit{Filomat, 2012}] derived Buzano inequality for Hilbert C*-modules. Using this inequality we derive Deutsch entropic uncertainty principle for Hilbert C*-modules over commutative unital C*-algebras.

Part II, like Part I, discusses geometry, kinematics and statics in detail without taking into account power losses in meshing. The main goal of Part II, however, is to prove that there are complex and structurally coupled planetary gear systems, i.e. containing a closed circuit in which no circulation of power flow is generated. The power flow analysis is also carried out using the direct method, with a slight modification in the way of writing the equations identifying active and passive gears, i.e. at the same time the directions of power flow on all transmission paths. The analysed planetary gear system (PGS) is characterised by mobility equal to 1, i.e. single degree of freedom (DoF). It consists of three subsystems in the form of the 2KH type planetary units connected in series-parallel, specially selected to demonstrate the thesis of this paper. It consists of three subsystems in the form of single planetary subsystems of the 2KH type connected series-parallel, specially chosen to illustrate the thesis of this paper.

A semi–numerical approach proposed many years ago for describing gravitational collapse in the post–quasi–static approximation , , , , is modified in order to avoid the numerical integration of the basic differential equations the approach is based upon. For doing that we have to impose some restrictions on the fluid distribution. More specifically, we shall assume the vanishing complexity factor condition, which allows for analytical integration of the pertinent differential equations and leads to physically interesting models. Instead, we show that neither the homologous nor the quasi–homologous evolution are acceptable since they lead to geodesic fluids, which are unsuitable for being described in the post–quasi–static approximation. Also, we prove that, within this approximation, adiabatic evolution also leads to geodesic fluids and therefore we shall consider exclusively dissipative systems. Besides the vanishing complexity factor condition, additional information is required for a full description of models. We shall propose different strategies for obtaining such an information, which are based on observables quantities (e.g. luminosity and redshift), and/or heuristic mathematical ansatz. To illustrate the method, we present two models. One model is inspired in the well known Schwarzschild interior solution, and another one is inspired in Tolman VI solution.

GABAA receptors are channel proteins crucial to mediating neuronal balance in the CNS. The structure of GABAA receptors allows for multiple binding sites and is key to drug development. Yet, the formation mechanism of the receptor’s distinctive pentameric structure is still unknown. This study aims to investigate the role of three predominant subunits of the human GABAA receptor in the formation of protein pentamers. Through purifying and refolding the protein fragments of the GABAA receptor α1, β2, and γ2 subunits, homopentamers were visualised with negative staining and Cryo-EM. To aid the analysis, AlphaFold2 was used to compare the structures. Results show that α1 and β2 subunit fragments successfully formed homo-oligomers, particularly homopentameric structures, while the predominant heteropentameric GABAA receptor was also replicated through the combination of the three subunits. However, it is still unclear whether γ2 subunits can form homopentamers or their main purpose is to bring together the α1 and β2 subunits to form GABAA receptors. Nevertheless, this study will lead to a deeper understanding of the atomic structure of GABAA receptors, especially in the formation mechanism of complex protein structures, and hopefully pave the way to the development of novel therapeutics for neuropsychiatric diseases.

Waterbomb structures are origami-inspired deformable structural components used in new types of robots. They have a unique radially deployable ability that enables robots to better adapt to their environment. In this paper, we propose a series of new waterbomb structures with square, rectangle, and parallelogram base units. Through quasi-static axial and radial compression experiments and numerical simulations, we prove that the parallelogram waterbomb structure has a twist displacement mode along the axial direction. Compared with the square waterbomb structure, the proposed optimal design of the parallelogram waterbomb structure reduces the critical axial buckling load-to-weight ratio by 55.4% and increases the radial stiffness-to-weight ratio by 67.6%. The significant increase in the radial stiffness-to-weight ratio of the waterbomb structure and decrease in the critical axial buckling load-to-weight ratio make the proposed origami pattern attractive for practical robotics applications.

Modular steel buildings (MSBs) interlocking inter-module connections (IMCs) have piqued researchers’ interest. However, the existing literature has not yet studied the optimisation of its plate thicknesses. This paper, therefore, focuses on optimising interlocking (IMCs) plate thickness in (MSBs), leveraging previous experimental and numerical simulation methodologies. Various numerical models for four MSBs interlocking (IMCs) with plate thicknesses (4 mm, 6 mm, 10 mm, and 12 mm) were developed under compression loading conditions. The study’s novelty lay in its comprehensive parametric analysis, which evaluated the slip phenomenon in (MSBs) connections and introduced a slip prediction model validated against empirical data. Further innovative machine learning approach was utilised to predict slip values based on applied force through a random forest regression model trained using the 'Treebagger' function. Sensitivity analysis and comparisons with alternative methods were utilised to underscore the reliability and applicability of the findings. The results showed that 11.03 mm was the optimal plate thickness for interlocking (IMCs) in modular steel buildings, with up to 8.08% reduced material costs. Increasing plate thickness boosts its deformation resistance by up to 50.75%. ‘TreeBagger’ random forest for anomaly detection and machine learning improves slip prediction up to 7% at higher force levels.

Modular inversion on large operands is a time-consuming calculation used in elliptic curve cryptography. Its hardware implementation requires extensive hardware resources such as lookup tables and registers. We investigate state-of-the-art modular inversion algorithms and evaluate the performance and cost of the algorithms and their hardware implementations. We then propose a high-radix modular inversion algorithm aimed at short execution time and low hardware cost. We present a detailed radix-8 hardware implementation based on 256-bit primes in Verilog HDL and compare its cost performance with other implementations. Our implementation on the Altera Cyclone V FPGA chip uses 1227 ALMs (Adaptive logic modules) and 1037 registers. The modular inversion calculation takes 3.67 microseconds. The AT (Area time) factor is 8.30, outperforming other implementations. We also present an implementation of elliptic curve cryptography using the proposed radix-8 modular inversion algorithm. The implementation results also show that our modular inversion algorithm is more efficient in area time than other algorithms.

This paper investigates the periodic and quasi-periodic orbits in the symmetric collinear four-body problem through a variational approach. In Section 3, we analyze the conditions under which homographic solutions minimize the action functional. We demonstrate that these solutions for four equal masses arranged in a linear configuration are indeed the minimizers of the action functional and compute the minimum value of the action functional for these solutions. Additionally, we employ numerical experiments using Poincaré sections to explore the existence and stability of periodic and quasi-periodic solutions within this dynamical system. Our results provide a deeper understanding of the variational principles in celestial mechanics and reveal complex dynamical behaviors that are crucial for further studies in multi-body problems. The findings have significant implications for theoretical research and practical applications in astrodynamics and space mission planning.

This paper propose a kernel geometric mean metric learning (KGMML) algorithm. The basic idea is to obtain the closed-form solution of the geometric mean metric learning (GMML) algorithm in the high-dimensional feature space determined by the kernel function. Then, the solution is generalized as a form of kernel matrix by using the integral representation of the weighted geometric mean and the Woodbury matrix in this new feature space. Experimental results on 15 datasets show that the proposed algorithm can effectively improve the accuracy of the GMML algorithm and other metric algorithms.

New setting is introduced to study quasi-degree and quasi-co-degree arising from co-neighborhood. quasi-degree and quasi-co-degree is about a vertex which are applied into the setting of neutrosophic graphs. . The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs namely path-neutrosophic graphs, cycle-neutrosophic graphs, complete-neutrosophic graphs and star-neutrosophic graphs, complete-bipartite-neutrosophic graphs and complete-multipartite-neutrosophic graphs are investigated in the terms of a vertex which is called either quasi-degree or quasi-co-degree. Neutrosophic number is reused in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number to compare with other vertices. Summation of three values of vertex makes one number and applying it to a comparison. This approach facilitates identifying vertices which form quasi-degree and quasi-co-degree. Quasi-degree is a value of a vertex which is maximum amid all values of vertices which are neighbors to a fixed vertex. Quasi-co-degree is a value of an edge which is maximum amid all values of edges which are neighbors to a fixed vertex but corresponded vertex is representative for this notion. Using different values which are related to a vertex inspire us to focus on edge and vertices which are corresponded to a fixed vertex. The notion of neighborhood is used to collect either vertices are titled neighbors or edges are incident to fixed vertex. In both settings, some classes of well-known neutrosophic graphs are studied. Some clarifications for each result and each definitions are provided. Using fixed vertex has key role to have these notions in the form of vertex or edge. The value of an edge has eligibility to call quasi-co-degree but the value of a vertex has eligibility to call quasi-degree. Some results get more frameworks and perspective about these definitions. The way in that, two vertices have connection together, open the way to define neighborhood and co-neighborhood. The maximum values in neighborhood and co-neighborhood introduces quasi-degree and quasi-co-degree, respectively. New name is chosen from degree. Since amid all vertices with different degrees, one vertex is chosen. In other words, one vertex is fixed and its degree turns out quasi-degree where two degrees could be assigned to a vertex. Degree of edges and degree of vertices. The number of edges which are incident to the vertex and the number of vertices which are neighbors to the vertex. Degree and co-degree are the notions which are transformed to use in quasi-style. Two neutrosophic values introduce two neutrosophic vertices separately in each settings. These notions are applied into neutrosophic graphs as individuals but not family of them as drawbacks for these notions. Finding special neutrosophic graphs which are well-known, is an open way to purse this study. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

The aim of this paper is to discuss the relations between various notions of sequential completeness and the corresponding notions of completeness by nets or by filters in the setting of quasi-metric spaces. We propose a new definition of right $K$-Cauchy net in a quasi-metric space for which the corresponding completeness is equivalent to the sequential completeness. In this way we complete some results of R.~A. Stoltenberg, Proc. London Math. Soc. \textbf{17} (1967), 226--240, and V.~Gregori and J.~Ferrer, Proc. Lond. Math. Soc., III Ser., \textbf{49} (1984), 36. A discussion on nets defined over ordered or pre-ordered directed sets is also included.

New notion of dimension as set, as two optimal numbers including metric number, dimension number and as optimal set are introduced in individual framework and in formation of family. Behaviors of twin and antipodal are explored in fuzzy(neutrosophic) graphs. Fuzzy(neutrosophic) graphs, under conditions, fixed-edges, fixed-vertex and strong fixed-vertex are studied. Some classes as path, cycle, complete, strong, t-partite, bipartite, star and wheel in the formation of individual case and in the case, they form a family are studied in the term of dimension. Fuzzification(neutrosofication) of twin vertices but using crisp concept of antipodal vertices are another approaches of this study. Thus defining two notions concerning vertices which one of them is fuzzy(neutrosophic) titled twin and another is crisp titled antipodal to study the behaviors of cycles which are partitioned into even and odd, are concluded. Classes of cycles according to antipodal vertices are divided into two classes as even and odd. Parity of the number of edges in cycle causes to have two subsections under the section is entitled to antipodal vertices. In this study, the term dimension is introduced on fuzzy(neutrosophic) graphs. The locations of objects by a set of some junctions which have distinct distance from any couple of objects out of the set, are determined. Thus it’s possible to have the locations of objects outside of this set by assigning partial number to any objects. The classes of these specific graphs are chosen to obtain some results based on dimension. The types of crisp notions and fuzzy(neutrosophic) notions are used to make sense about the material of this study and the outline of this study uses some new notions which are crisp and fuzzy(neutrosophic). Some questions and problems are posed concerning ways to do further studies on this topic. Basic familiarities with fuzzy(neutrosophic) graph theory and graph theory are proposed for this article.

In this paper, quasi-static axial compression tests are performed on the nodal Moso bamboos to study the size effect on energy absorption of the bamboos and the damage pattern of the multiple bamboo columns. Experimental results show that under the same moisture content, growth age and growing environment, the specific energy absorption (SEA) of the test samples increases with the increase of the out-diameter and thickness of the bamboo columns, indicating that size effect exists for energy absorption of the Moso Bamboos. For the multiple bamboo columns, there are mainly three failure modes for the constituent single bamboo columns: splitting above the node, splitting below the node and splitting through the node. Also, the tensile tests are conducted on three kinds of dog-bone shaped bamboo samples to investigate the macroscopic tensile fracture mode in the longitudinal direction of Moso bamboos. Results show that there is no direct relationship between the fracture pattern and moisture content of the bamboos, as well as the growth age of the bamboos. However, the tensile loading rate and the shape of the dog-bone shaped bamboo sample could affect the macroscopic fracture pattern of the bamboos in some cases.

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is analyzing the changes in the foot-floor contact sequences of Parkinson’s Disease (PD) patients in the year following the implant for deep brain stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months (T1), and 12 months (T2) after the DBS neurosurgery for bilateral high-frequency subthalamic nucleus stimulation. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5-minute walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in the UPDRS-III score from 19.4±1.8 to 10.2±1.0 points (T0 vs. T2) (p < 0.001). In particular, the percentage change of atypical gait cycles of PD more affected side decreased at T1 (Straigh-line: -72%; Turnings: -43%) and at T2 (Straigh-line: -54%; Turnings: -20%). The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

Quantum theory is the land of indiscernible things, of things that in some situations cannot be put apart. This contrasts in much with standard mathematics and classical logic, which were elaborated to deal with \textit{individuals}, discernible things. Many thinkers, among them the mathematician Yuri Manin, have proposed that a more general theory of `sets' than standard set theories (where sets are collections of discernible elements) should be elaborated to cope with quantum physics. Quasi-set theory was proposed with such an aim. In this paper, we consider some aspects of this theory and discuss the way we can use such a theory as a framework for constructing deformable (not rigid) structures where indiscernible things can be considered but with one additional and fundamental detail: these structures cannot be extended to rigid structures as it happens in the standard frameworks. Really, the way of dealing with indiscernible (or indistinguishable) elements within a `standard' framework such as a `classical' set theory (like the ZFC system) requires the confinement of the discussion to deformable (non-rigid) structures. But in ZFC every structure can be extended to a rigid structure (encompassing only the trivial automorphism -- the identity function), so that in the extended structure (or in the whole universe) one can realize that the supposed indiscernible objects are not indiscernible at all. Quasi-set theory is such that the universe of quasi-sets is deformable and in such a theory one can construct deformable structures which cannot be extended to rigid ones. The aim of this paper is to put these things in a clear way.

Day by day, the share of renewable energy-based power plants such as offshore wind farms and photovoltaic power plants, in the present-day power systems is escalating. Nevertheless, most of these power-producing facilities have been located quite far away from the load centers. At this stage, HVDC power systems provide satisfactory options due to qualities such as reduced line losses, substantial controllability, and environmental advantages. Nevertheless, unique converter designs are required to combine asynchronous HVDC networks with each other and with already existing high voltage alternating current (HVAC) networks. In this study, based on the above special cases, a unique DC-DC modular multilevel converter (MMC) architecture is presented that provides an excellent solution for both integrating modern asynchronous HVDC networks and integrating these modern HVDC power systems with existing asynchronous HVAC power systems. The mathematical analysis of the recommended DC-DC MMC design has been examined in detail and the power transfer between two asynchronous power grids has been realized in a simulation environment. Efficient bilateral power transmission has been made achievable by the control system. The recommended DC-DC MMC topology has shown to be a highly successful approach, in the interconnection of HVDC power systems, according to the simulation results.

In this paper, the integrated performance of a modular biomass boiler with an existing industrial Rankine steam heat and power cycle and a supplementary supercritical-CO2 (sCO2) Brayton cycle is analyzed. The aim is to leverage the high efficiency supplementary sCO2 cycle to increase net generation and energy efficiency from the existing biomass boiler. Two sCO2 heater configurations situated within the flue gas flow path are investigated, namely a single convective-dominant heater, and a dual heater configuration with a radiative and a convective heater. A quasi-steady-state 1D model was developed to simulate the integrated cycle, including detailed component characteristics for the Rankine and Brayton cycles. The model solves the mass, energy, momentum, and species balance equations. The system is analyzed for three cases: (i) the existing Rankine cycle without the sCO2 integration, (ii) with the single convective-dominant sCO2 heater configuration, and (iii) the dual sCO2 heater configuration. The results show the required rate of overfiring for the sCO2 configurations, with a 15.3% increase in fuel flowrate resulting in an additional 21.2% in net power output. The model quantifies the impact of the sCO2 heaters, with reduced heat uptakes for downstream boiler heat exchangers. Furnace water wall heat uptake increased due to overfiring, offsetting the reduced heat uptakes at downstream evaporative heat exchangers. The dual configuration has more impact on Rankine cycle operation due to the radiative sCO2 heater placement in front of the second superheater, absorbing some of the direct radiation from the furnace.

In this article it is shown, first, that a change of basis in Minkowski space is equivalent to a change of basis in Euclidean space if a basis element is replaced by its dual element, constituting a mixed basis set. Second, that such mixed bases can be interpreted as a measurement system used by local, flat observers whose direct distance measurements are restricted to an (n−1)-dimensional submanifold in an n-dimensional Euclidean space. Combining these steps, it is concluded that a local, flat observer in a four-dimensional Euclidean space measures a Minkowski spacetime. This interpretation could be useful for theories in special relativity and related fields that rely on spacetime concepts, as it offers a more intuitive geometric understanding of the Minkowski metric.

In an outstanding article published in 2008, Suzuki obtained a nice generalization of the Banach contraction principle from which derived a characterization of metric completeness. Although Suzuki’s theorem has been successfully generalized and extended in several directions and contexts, we here show by means of a simple example that the problem of achieving, in an obvious way, its full extension to the framework of w-distances does not have an emphatic response. Motivated by this fact we introduce the concept of presymmetric w-distance on metric spaces, we give some properties and examples of this new structure and show that it provides a reasonable setting to obtain a real and hardly forced w-distance generalization of Suzuki’s theorem. This is realized in our main result, which is a fixed point theorem that involves presymmetric w-distances and certain contractions of Suzuki-type. We also discuss the relationship between our main result and the well-known w-distance full generalization of the Banach contraction principle, due to Suzuki and Takahashi. Connected to this approach we prove another fixed point result that compare with our main result through some examples. Finally, we state a characterization of metric completeness by using our fixed point results.

Since general relativity (GR) has already established that matter can simultaneously have two different values of mass depending on its context, we argue that the missing mass attributed to non-baryonic dark matter (DM) actually obtains because there are two different values of mass for the baryonic matter involved. The globally obtained "dynamical mass'' of baryonic matter can be understood as a small perturbation to a background spacetime metric even though it's much larger than the locally obtained "proper mass". Having successfully fit the SCP Union2.1 SN Ia data without accelerating expansion or a cosmological constant, we employ the same ansatz to compute dynamical mass from proper mass and explain galactic rotation curves (THINGS data), the mass profiles of X-ray clusters (ROSAT and ASCA data) and the angular power spectrum of the cosmic microwave background (Planck 2015 data) without DM. We compare our fits to modified Newtonian dynamics (MOND), metric skew-tensor gravity (MSTG) and scalar-tensor-vector gravity (STVG) for each data set, respectively, since these modified gravity programs are known to generate good fits to these data. Overall, we find our fits to be comparable to those of MOND, MSTG and STVG. While this favorable comparison does not establish the validity of our proposition, it does provide confidence in using the fits to pursue an underlying action. Indeed, the functional form of our ansatz reveals an interesting structure in these fits.

The notion of Golden structure was introduced 15 years ago by the present authors and know a constant interest by several geometers. Now, we propose a new generalization apart of that called metallic structure and considered also by the authors. By adding a compatible Riemannian metric we focus on the study of submanifolds in this setting.

Different hypotheses of carcinogenesis have been proposed based on local genetic factors and physiologic mechanisms. It is assumed that changes of the metric invariants of a biologic system (BS) determine general mechanisms of cancer development. Numerous data demonstrate an existence of three invariant feedback patterns of BS: negative feedback (NFB), positive feedback (PFB) and reciprocal links (RL). These base patterns represent basis elements of a Lie algebra sl(2,R) and imaginary part of coquaternion. Considering coquaternion as a model of a functional core of a BS, conditions of the system can be identified with the points of three families of hypersurfaces in R42: hyperboloids of one sheet, hyperboloids of two sheets and double-cones. Corresponding quadratic form relates negative and positive entropy contributions of base elements to the energy level of the system, so that anabolic states of the system will correspond to the points of a hyperboloid of one sheet, while catabolic conditions to the points of a hyperboloid of two sheets. Equilibrium states will lie in a double cone. Hypothetically anabolic and catabolic states dominate intermittently oscillating around the equilibrium. Deterioration of base elements increases positive entropy and causes domination of catabolic states which is the main metabolic determinant of cancer. Corresponding trajectory of a malfunctioning system will have a tendency to remain inside the double cone.

Different hypotheses of carcinogenesis have been proposed based on local genetic factors and physiologic mechanisms. It is assumed that changes of the metric invariants of a biologic system (BS) determine general mechanisms of cancer development. Numerous data demonstrate an existence of three invariant feedback patterns of BS: negative feedback (NFB), positive feedback (PFB) and reciprocal links (RL). These base patterns represent basis elements of a Lie algebra and imaginary part of coquaternion. Considering coquaternion as a model of a functional core of a BS, conditions of the system can be identified with the points of three families of hypersurfaces in R⁴₂: hyperboloids of one sheet, hyperboloids of two sheets and double-cones. Corresponding quadratic form relates negative and positive entropy contributions of base elements to the energy level of the system, so that anabolic states of the system will correspond to the points of a hyperboloid of one sheet, while catabolic conditions to the points of a hyperboloid of two sheets. Equilibrium states will lie in a double cone. Hypothetically anabolic and catabolic states dominate intermittently oscillating around the equilibrium. Deterioration of base elements increases positive entropy and causes domination of catabolic states which is the main metabolic determinant of cancer. Corresponding trajectory of a malfunctioning system will have a tendency to remain inside the double cone.

Fractional-time Schrödinger equation (FTSE) describes the evolution of quantum processes endowed with memory effects. FTSE manifestly breaks all consistency requirements of quantum field theory (unitarity, locality and compliance with the clustering theorem), unless the order of fractional differentiation and integration ( ) falls close to the standard index . Working in the context of the minimal fractal manifold (where , ), we confirm here that FTSE approximates the attributes of gravitational metric and provides an unforeseen generation mechanism for massive fields.

We establish certain modular equations of degree three based on some results of Ramanujan's theta functions.

We recently formulated Modular Dvoretzky, Type-Cotype, Khinchin-Kahane and Grothendieck Inequality problems in the Appendix of \textit{[arXiv:2302.03718v1]}. For the sake of wide accessibility we give a separate treatment of them.

In this work, the conceptions of the electrodynamics of action-at-a-distance and of electromagnetic fields are reviewed and confronted, with the aim of clarifying whether it is possible to propose a Weberian theory of action-at-a-distance, which together with a renewed mechanics (both re-specting the existence of a limiting velocity c) could constitute a framework capable of yielding predictions equivalent to those of the conventional Maxwell-Lorentz and SRT framework. In this work, it is shown that, considering basic assumptions about the interaction process, understanding it as an action exchange process, it is possible to derive the expression of the electrodynamic Phipps’ potential energy between two interacting charges. It is also shown that, with the same assumptions and the additional hypothesis that the interaction is supported by a mediating agent (aether or field) which is perturbed by the transmission of action, this perturbation obeys the wave equation (one of the main drawbacks of Weberian electrodynamics). Another aim of the work is to confront the relational electrodynamic formulations (supported by Galilean transformations that assume a universal time) with the Maxwell-Lorentz formulation of electromagnetism (linked to Lorentz transformations that entail local times), in order to elucidate whether the space-time to which the SRT leads us is a mere mathematical artifice or an inescapable reality.

New ways of generating energy are currently being discussed, with a transition from traditional primary sources to more environmentally friendly options, particularly renewables. Energy storage is also closely related to this transition. Battery storage currently dominates this area. However, flywheel energy storage system (FESS) technology offers an alternative that uses stored kinetic energy to be transformed into mechanical energy and, using a motor-generator, electrical energy. FESS technology is thus flexible and can be applied in different industrial applications. The management of the technology of recycling W-MMC waste material from other products and the subsequent trial production of high-strength W-MMC material with a density of more than 17 500 kg/m3 from recycled powders allowed to test the limits of the so-called "heavy" flywheels used in rotor production. Materials with densities ≥ 7 800 kg/m3, and operating at lower to medium speeds up to 20 000 rpm. The results achieved lead to the conclusion that the developed recycled materials of the W-MMC type with a density ≥ 17 500 kg/m3, with a yield strength of 1 200 - 1 700 MPa depending on the production method, can be used as a substitute for the structural steels used today, without an enforced reduction of the maximum allowed rotor speed due to exceeding the maximum allowed stress.

ABSTRACT: Background: Virtual Reality (VR) emerges as a promising non-pharmacological intervention for managing symptoms and providing distraction during chemotherapy. This study aims to assess VR's effectiveness on cancer-related symptoms, vital signs, and patients' perception of the chemotherapy in lung cancer patients. Methods: A quasi-experimental study was conducted on 100 patients. Participants were allocated into an intervention group (n = 55), which experienced immersive VR, and a comparison group (n = 45), which received usual care. Data were collected through questionnaires and checklists, including feedback on the VR experience, pain, vital signs, and common cancer symptoms, assessed through the Edmonton Symptom Assessment Scale. Results: VR had a significant impact on reducing the perception of the chemotherapy length. Patients reported high levels of satisfaction and tolerability. No adverse events were observed. VR did not have significant influence on pain intensity and vital signs. The only exceptions were oxygen saturation, where a significant difference (p = 0.02) was reported, and perception of chemotherapy duration. Conclusions: As a non-pharmacological intervention, VR proves beneficial in minimizing the perceived length of chemotherapy session for lung cancer patients, enhancing their overall treatment experience. The intervention showed to be a safe, feasible, and well-accepted distraction technique. Future research should explore VR's potential effects on a wider range of symptoms and evaluate its impact on long-term outcomes.

This research investigates precision enhancement in regional quasi-geoid refinement through ADS80 tri-linear array scanning stereoscopic imagery for aerial triangulation, coupled with GNSS gravity-potential modeling. Acquiring stereoscopic imagery and analyzing triangulation accuracy with the ADS80 camera, we performed this study over the Qinghai-Tibet Plateau's elevated, desolate terrain, collecting 593 GNSS points following high-precision stereoscopic imagery model. Utilizing 12 gravity satellite models, we computed geoid heights and China 1985 Yellow Sea elevations for 28 benchmarks and GNSS points, thereby refining the Qinghai Province Quasi-Geoid Model (QPQM) using geometric techniques. The findings reveal that POS-assisted ADS80 stereoscopic imagery yields high-precision triangulation with maximal horizontal and elevation accuracies of 0.083/0.116 cm and 0.053/0.09 cm, respectively, across five control point arrangements. The RMSE of normal heights for 1985, processed via these GNSS points, achieved decimeter precision. By applying error corrections from benchmarks to the 1985 elevation data from gravity satellites and performing weighted averaging, the precision of EGM2008, SGG-UGM-2, and SGG-UGM-1 models improved to 8.61 cm, 9.09 cm, and 9.38 cm, respectively, surpassing the QPQM by 9.22 cm to 9.99 cm. This research demonstrates that the proposed methods can significantly enhance the precision of regional quasi-geoid surfaces. Additionally, these methods offer a novel approach for rapidly establishing regional quasi-geoid models in the uninhabited areas of the Qinghai-Tibet Plateau.

Unsupervised metric learning has been generally studied as a byproduct of dimensionality reduction or manifold learning techniques. Manifold learning techniques like Diusion maps, Laplacian eigenmaps has a special property that embedded space is Euclidean. Although laplacian eigenmaps can provide us with some (dis)similarity information it does not provide with a metric which can further be used on out-of-sample data. On other hand supervised metric learning technique like ITML which can learn a metric needs labeled data for learning. In this work propose methods for incremental unsupervised metric learning. In rst approach Laplacian eigenmaps is used along with Information Theoretic Metric Learning(ITML) to form an unsupervised metric learning method. We rst project data into a low dimensional manifold using Laplacian eigenmaps, in embedded space we use euclidean distance to get an idea of similarity between points. If euclidean distance between points in embedded space is below a threshold t₁ value we consider them as similar points and if it is greater than a certain threshold t₂ we consider them as dissimilar points. Using this we collect a batch of similar and dissimilar points which are then used as a constraints for ITML algorithm and learn a metric. To prove this concept we have tested our approach on various UCI machine learning datasets. In second approach we propose Incremental Diusion Maps by updating SVD in a batch-wise manner.

In many research fields, statistical probability models are often used to analyze real-world data. However, data from many fields, such as the environment, economics, and health care, do not necessarily fit traditional models. New empirical models need to be developed to improve their fit. In this paper, we explore a further extension of the quasi-Lindley model. Maximum likelihood, least square error, Anderson-Darling algorithm, and expectation-maximization algorithm are four techniques for estimating the parameters under study. All techniques provide accurate and reliable estimates of the parameters. However, the mean square error of the expectation maximization approach was lower. The usefulness of the proposed model was demonstrated by analyzing a dynamical systems data set, and the analysis shows that it outperforms the other models in all statistical models considered.

This paper investigates the potential of utilising multilevel quasi-interpolation techniques on Chebyshev sparse grids for complex numerical computations. The paper starts by laying down the motivations for choosing Chebyshev sparse grids and quasi-interpolation methods with Gaussian kernels. It delves into the practical aspects of implementing these techniques. Various numerical experiments are performed to evaluate the efficiency and limitations of the multilevel quasi-sparse interpolation methods with dimensions two dimension and three dimension. The work ultimately aims to provide a comprehensive understanding of the computational efficiency and accuracy achievable through this approach, comparing its performance with traditional methods.

Logic gates made of pairs of NPN and PNP bipolar transistors, similar to CMOS logic gates, have been proposed and patented long ago but did not find any practical application until now. Other bipolar technologies (TTL, TTL-S, ECL), once the technologies of choice for digital systems, were abandoned and superseded by CMOS. In this paper it is shown that now, when truly com-plementary pairs of bipolar transistors can be made, properly biased bipolar gates similar to CMOS gates are feasible, can be thermally stable and find practical applications.

Manufacturing environments, characterized by rapid, unpredictable changes, uncertainties, risks, and uncontrollable fluctuations, pose significant challenges to minimizing disruptions in processes. This study introduces an innovative approach that prioritizes curbing risk propagation among processes to enhance robustness. It emphasizes the integration of engineering management principles and modular design within manufacturing. Adopting a system engineering perspective, all manufacturing process activities are viewed as interrelated components within a unified system. By employing Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, manufacturing process architecture is modularized, yielding heightened robustness. The proposed mathematical model equips engineering and manufacturing managers with a potent tool for designing robust processes while adeptly managing system complexity. The study's outcomes underscore a substantial enhancement in modularization, leading to elevated overall robustness in manufacturing processes. To validate the methodology, the architectural design of manufacturing processes is examined in a real-case scenario, specifically the Barez Industrial Group in Iran. This verification substantiates the 'manufacturing processes' of the case, presenting an optimally modularized architecture. The results affirm the proposed approach's efficacy, demonstrating improved modularization that contributes to bolstered robustness in manufacturing processes.

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually, however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) framework provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis plants are expensive custom designed systems. The plug-and-play prototype approach is first tested by connecting it to the pyrolysis reactor and ensuring it can measure temperature and actuate heaters and a stirring motor. Next, a single circuit board system was created and tested using the designs from the BREAD prototype to reduce the number of microcontrollers required. Both open-source control systems were capable of reliably running the pyrolysis reactor continuously and the overall cost of control was reduced by more than 10X. Open-source, plug-and-play hardware provides a reliable avenue for researchers to quickly develop data acquisition and control electronics for industrial-scale experiments.

Modularity is arguably one of the most influential theses guiding research on brain and cognitive function since phrenology. This paper considers the following question: is modularity entailed by recent Bayesian models of brain and cognitive function, especially the predictive processing framework? It starts by considering three of the most well-articulated arguments for the view that modularity and predictive processing work well together. It argues that all three kinds of arguments for modularity come up short, albeit for different reasons. The analysis in this paper, although formulated in the context of predictive processing, speaks to broader issues with how to understand the relationship between functional segregation and integration and the reciprocal architecture of the predictive brain. These conclusions have implications for how to study brain and cognitive function. Specifically, when cognitive neuroscience works within an acyclic Markov decision scheme, adopted by most Bayesian models of brain and cognitive function, it may very well be methodologically misguided. This speaks to an increasing tendency within the cognitive neurosciences to emphasise recurrent and reciprocal neuronal processing captured within newly emerging dynamical causal modelling frameworks. The conclusions also suggest that functional integration is an organising principle of brain and cognitive function.

The aim of the study was to test the significance of the EPT index in the water quality assessment of three types of water bodies in hilly and mountainous region of Serbia. The aquatic macroinvertebrate community was dominated by the group of insects, of which 95 taxa represent the EPT group. We compared the obtained values of biological indices used for the assessment of water quality according to the national legislation with the overall status assessment represented by the ecological quality classes (EQC). The results of the Spearman correlation test showed a negative correlation of EQC with the EPT index, BMWP score, H', total number of taxa and number of sensitive taxa, while a positive correlation was observed for the values of SI and Tubificinae %. The values of EQC and biological indices were subjected to principal component analysis (PCA). The results showed that the parameters that contributed most to the differences were the EPT index, the BMWP score and the number of sensitive taxa. The results indicate that the EPT index is an excellent indicator of changes in water quality and an important tool for the ecological categorization of water bodies in mountain regions.

The process industry is confronted with rising demands for flexibility and efficiency. One way to achieve this are modular process plants that consist of pre-manufactured modules with their own decentralized intelligence. Plants are then composed of these modules as unchangeable building blocks and can be easily re-configured for different products. Condition monitoring of such plants is necessary, but available solutions are not applicable. The authors suggest an approach in which model-based symptoms are derived from few measurements and observers that are based on manufacturer knowledge. The comparisons of redundant observers lead to residuals that are classified to obtain symptoms. These symptoms can be communicated to the plant control and are inputs to an easily adaptable diagnosis. The implementation and validation at a modular mixing plant showcases the feasibility and the potential of this approach.

Methods for cost calculation of Laser-based Additive Manufacturing (LAM) have evolved over the last two decades. Starting from a rapid prototyping manufacturing method, cost calculation over time included more than single part production for small series or mixed batches. New machine developments nowadays aim at large scale production and introduce modular machine designs that give LAM factory operators more decision freedom on machine configurations and expansibility. To leverage this new possibilities, LAM costing methods must be adapted to calculate and visualize the economic consequences of different module configurations.In this work a modelling architecture of L-PBF machines using virtual modules is presented. Using principles of the industry 4.0 communication standard OPC UA, a virtual machine is set up, parametrized and connected to the AM digital process chain. Two different views on the cost information are used, optimized for different use cases.First, the product view allows detailed analysis of cost allocation to parts in mixed batches and the layered geometry of the part. Second, the machine view tracks utilization of all machine modules, divided into the states idle, active, off and maintenance. The theoretical Overall Equipment Effectiveness (OEE) is calculated on a module basis, enabling economic analysis and optimization of module composition as well as module improvements and new modular machine constellations. This allows focusing research and development on most valuable improvements. By calculating different scenarios like spare part production, mass production or rapid prototyping, the part portfolio to be manufactured can be considered.

3D printing facilitates the straightforward construction of microchannels with complex three-dimensional architectures. Here, we demonstrate 3D-printed modular mixing components that operate on the basis of splitting and recombining fluid streams to decrease interstream diffusion length. These are compared to helical mixers that operate on the principle of chaotic advection.

In this paper, a modular wire-actuated robotic arm was designed to improve the safety and adaptability of service robots during human-robot interaction. To raise the stiffness adjustment range of the robotic arm, a symmetric variable-stiffness unit was designed based on flexure, which had compact and simple structure, and lowly nonlinear stiffness-force relationship. In this paper, we focused on the research of the symmetric 1-DOF joint module. Based on the kinematics and stiffness analysis, the pose of the joint module could be adjusted by controlling the length of the wires, and the stiffness of the joint module could be adjusted by controlling the tension of the wires. Because of the actuation redundancy, the pose and stiffness of the joint module could be controlled synchronously. Furthermore, a directly method was proposed for the stiffness-oriented wire tension distribution problem of the 1-DOF joint module. A simulation was carried out to verify the proposed method.

This paper seeks to fill in the gaps of modern relativistic Cosmology by utilizing the total symmetry between space and time dimensions and re-interpreting the scale factor of the Universe as a gravitational potential generated by the mass/energy of the entire Universe as a whole. The gradient of this potential is along the cosmological time dimension through which the Universe is falling. This gradient gives us an arrow of time, we find explanations for why the Universe began expanding and why the expansion is accelerating without the need for a Cosmological Constant. In a finite time, the gradient will point in the opposite direction of time turning the expanding Universe into a collapsing one where it is shown that when placing the Schwarzschild metric in the dynamic Cosmological background, gravity becomes repulsive and things like would-be Black Holes become White Holes. The model naturally describes a Universe and an anti-Universe (consisting of antimatter) moving in opposite directions of time that collide at the end of collapse, annihilating and subsequently pair producing two new Universes as the cycle begins again. It is shown that the model's Hubble diagram fits the currently available supernova and quasar data. It is found that Dark Matter can perhaps be understood as ordinary matter that is not connected to us with null geodesics.

When the minimal length approach emerging from noncommutative Heisenberg algebra, generalized uncertainty principle (GUP), and thereby integrating gravitational fields to this fundamental theory of quantum mechanics (QM) is thoughtfully extended to Einstein field equations, the possible deformation of the metric tensor could be suggested. This is a complementary term combining the effects of QM and general relativity (GR) and comprising noncommutative algebra together with maximal spacelike four–acceleration. This deformation compiles with GR as curvature in relativistic eight–dimensional spacetime tangent bundle, generalization of Riemannian spacetime, is the recipe applied to derive the deformed metric tensor. This dictates how the affine connection on Riemannian manifold is straightforwardly deformed. We have discussed the symmetric property of deformed metric tensor and affine connection. Also, we have evaluated the dependence of a parallel transported tangent vector on the spacelike four–acceleration given in units of L, where L = rℏcG3 is a universal constant, c is speed of light, and ℏ is Planck constant, and G is Newton’s gravitational constant.

Video quality assessment (VQA) plays an important role in video applications for quality evaluation and resource allocation. It aims to evaluate the video quality consistent with the human perception. In this letter, a hierarchical gradient similarity based VQA metric is proposed inspired by the structure of the primate visual cortex, in which visual information is processed through sequential visual areas. These areas are modeled with the corresponding measures to evaluate the overall perceptual quality. Experimental results on the LIVE database show that the proposed VQA metric significantly outperforms the state-of-the-art VQA metrics.

Quasi-interpolation is a powerful tool for approximating functions using radial basis functions (RBFs) such as Gaussian kernels. This avoids solving large systems of equations as in RBF interpolation. However, quasi-interpolation with Gaussian kernels on compact intervals can have significant errors near the boundaries. This paper proposes a quasi-interpolation method with Gaussian kernels using Chebyshev points and boundary corrections to improve the approximation near the boundaries. The boundary corrections use a linear approximation of the function beyond the interval to estimate the truncation error and add correction terms. Numerical studies on test functions show that the proposed method reduces errors significantly near boundaries compared to quasi-interpolation without corrections, for both equally spaced and Chebyshev points. The convergence and accuracy with the boundary corrections are generally better with Chebyshev points compared to equally spaced points. The proposed method provides an efficient way to perform quasi-interpolation on compact intervals while controlling the boundary errors.

Magnetic quantum oscillations (MQO) are traditionally applied to investigate the electronic structure of metals. In layered quasi-two-dimensional (Q2D) materials the MQO have several qualitative features giving additional useful information, provided their theoretical description is developed. Within the framework of the Kubo formula and the self-consistent Born approximation, we reconsider the phase of beats in the amplitude of Shubnikov oscillations of interlayer conductivity in Q2D metals. We show that the phase shift of beats of the Shubnikov (conductivity) oscillations relative to the de Haas - van Alphen (magnetization) oscillations is larger than expected previously and, under certain conditions, can reach the value of π/2, as observed experimentally. We explain the phase inversion of MQO during the 3D - 2D crossover and predict the decrease of relative MQO amplitude of interlayer magnetoresistance in a strong magnetic field, larger than the beat frequency.

Motivated from the theory of Hilbert-Schmidt morphisms between Hilbert C*-modules over commutative C*-algebras by Stern and van Suijlekom [J. Funct. Anal., 2021], we introduce the notion of p-absolutely summing morphisms between Hilbert C*-modules over commutative C*-algebras. We show that an adjointable morphism between Hilbert C*-modules over monotone closed commutative C*-algebra is 2-absolutely summing if and only if it is Hilbert-Schmidt. We formulate version of Pietsch factorization problem for p-absolutely summing morphisms and solve partially.

Shell-like, double curved and thus above-average performance structures, are usually produced monolithically on site. For industrial advancement, however, they must be divided into transportable modules which can be assembled on the construction site (design for assembly). Models are lattice shells made of steel and glass, in which predominantly flat sub-surfaces (modules) are used. Therefore, the main question is: Which modularizations are suitable for flow production with mineral building materials? In this paper designed free-form surface is going to be discretized as PQ circular mesh system, suitable modules for 3D concrete printing. Moreover, the multi-criteria optimization is done with Response Surface Methodology (RSM) in order to get optimal final shape. The goal is to start from the arbitrary shape, that can be generated from two curves, with possible two-way division into modules and compare it with the resulted discretized PQ circular mesh system, realized with new algorithm. The comparison can be defined through two main criteria: geometrical and structural.

One of the most important component of a Geographic Information Retrieval (GIR) is the geoparser, which performs toponym recognition, disambiguation, and geographic coordinate resolution from unstructured text domain. However, news articles which report several events across many place references mentioned in the document is not yet adequately modeled by regular geoparser types where the scope of resolution is either on toponym-level or document-level. The capacity to detect multiple events, geolocate its true locations and coordinates along with their numerical arguments are still missing from modern geoparsers, much less in Indonesian news corpora domain. We propose a novel type event geoparser which integrates an ACE-based event extraction model and provides precise event-level scope resolution. The geoparser casts the geotagging and event extraction as sequence labeling and uses Conditional Random Field with keywords feature obtained using Aggregated Topic Model as a semantic exploration from large corpus, which eventually increases the generalizability of the model. The geoparser also use Smallest Administrative Level feature along with Spatial Minimality-derived algorithm to improve the identification of Pseudo-location entities, resulting 19.4% increase for weighted F1 score. As a side effect of event extraction, the geoparser also extracts various numerical arguments and able to generate thematic choropleth map from a single news story.

The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids are well-established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge and this results in high costs. To enable a democratization of the technology by reducing the costs this study provides a novel modular plug-and-play open source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink as well as experimental validation. The results show transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems.

This paper addresses the approach of fully automated intelligent control systems in production organizations, focusing on intelligent production systems research. The overview highlights a gap in control operations ahead of assembly as single-purpose control machines are frequently employed, which is precisely their drawback. Conversely, there are accurate multipurpose measurement centers that do not provide total quality control over the manufactured parts because of the cost and length of the measuring procedure. The study's primary objective was to create an intelligent modular control system, whose concept enables it to control various components. The purpose of the modular intelligent control system is to keep an eye on each module's quality during the pre-assembly phase. This system ensures exact control over the production process of modules by integrating sophisticated sensors, diagnostic tools, and intelligent control mechanisms. The technology makes it possible to monitor several parameters and important quality features. Integrated sensors and diagnostic technologies identify possible inaccuracies and disparities, guaranteeing prompt diagnosis of issues in specific modules. The system's intelligent control algorithms streamline the production process and guarantee synchronization between individual modules to achieve consistent quality and performance. One advantage of implementing the solution is that, on average, inspection time is reduced by 40 to 60% as compared to the prior manual inspection approach. In addition, full measurement data archiving was made available, and finally, the human element—which introduced a substantial error rate into this process—was removed. This system also helps to increase the project's overall efficiency, predictability, and safety while allowing for quick adjustments by standards and requirements.

The need for a relatively quick solution to the problem of providing highways with roadside service facilities necessitates the development of a series of appropriate standard projects. To increase the efficiency of these series, it is advisable to carry out the interconnection of space-planning solutions based on a particular module. Taking into account the variety of planning and landscape characteristics of the sites for the placement of objects of the mainline service, it seems advisable to choose as a module not a square or rectangular, but a triangular configuration, which allows in most cases to harmoniously block the modules. The proposed roof module in the form of a "regular" triangle facing the tetrahedron has a structural basis in the form of a single-tier rod spatial plate. The principal space-planning solutions of all four dozen objects from the approved nomenclature of the mainline service performed in the process of analyzing the possibilities show the real possibility of solving the development tasks on the basis of this system. The use of the proposed modular system makes it possible to successfully solve a number of tasks to reduce the harmful impact on the environment and effectively use renewable energy sources.

We analyze the modular geometry of the variable exponent Lebesgue space L^p(.). We show that L^p(.) possesses a modular uniform convexity property. Part of the novelty is that the property holds even in the case supp(x) = ∞ . We present specific applications to fixed point theory. xÆΩ

In this paper, based on the pseudo-totem pole (PTP) circuit, a family of five-level PTP dual boost converters (PDBC) is proposed. Dual boost converter has some unique advantages such as no bridge arm shoot-through risk and no switch body diode reverse recovery problem, so that it has a good application prospect. Compared with conventional three-level PTP converters, PDBCs has higher power density, higher efficiency, and low voltage and current stress. The topological derivation process, working principle, modulation and strategy of the topology are analyzed firstly. Further, the number of power devices, the switches voltage and current stress of the proposed topology is analyzed. Finally, a representative five-level PDBC experimental prototype is designed with AC input 220V/50Hz, DC output 400V/1kW, and peak efficiency of 98.27%. The experimental results show that the five-level PDBC proposed in this paper has higher efficiency and verify the correctness of the topology.

Ofloxacin is a highly efficient and widely used antibiotic drug. It is classified as a refractory pollutant due to its poor biodegradability. Consequently, it is commonly found in water sources, requiring efficient methods for its removal. Advanced Oxidation Processes (AOPs) offer efficient alternatives since those yield complete degradation not achieved in adsorption or membrane processes. Previous studies suggest ofloxacin degradation follows a pseudo-first or -second order processes, whereas for full removal of refractory pollutants – lower pseudo-orders are required. Monitoring the actual “pseudo-order” degradation kinetics of ofloxacin is needed to evaluate any proposed AOP process. This study presents a simple procedure to evaluate pseudo-orders of AOPs. Photolysis of 20 mM ofloxacin solutions follow pseudo-zero order kinetics, with half-life times (t_1/2) of approx. 60 min. TiO₂ heterogenous catalyst show to have no influence at low concentration (0.2 mg L^-1) but a significant reduction of half-life time (t_1/2 = 20 min) and increase in pseudo-order (0.8) is measured at 2.0 mg L^-1. Similar results are obtained with homogenous catalysis by 2.0 mg L^-1 H₂O₂. The combination of H₂O₂ and TiO₂ catalysts shows additional reduction in half-time life with increase in the pseudo-order to 1.2. The conclusions are (1) heterogenous and homogenous photocatalysis can effectively degrade ofloxacin, (2) combined photocatalysis yields higher pseudo-order, being less prone to achieve full removal, (3) analysis of specific pseudo-orders in AOPs of refractory pollutants helps to further elucidate the efficiency of the processes.

For personalized recommender systems,matrix factorization and its variants have become mainstream in collaborative filtering.However,the dot product in matrix factorization does not satisfy the triangle inequality and therefore fails to capture fine-grained information. Metric learning-based models have been shown to be better at capturing fine-grained information than matrix factorization. Nevertheless,most of these models only focus on rating data and social information, which are not sufficient for dealing with the challenges of data sparsity. In this paper,we propose a metric learning-based social recommendation model called SRMC.SRMC exploits users' co-occurrence pattern to discover their potentially similar or dissimilar users with symmetric relationships and change their relative positions to achieve better recommendations.Experiments on three public datasets show that our model is more effective than the compared models.

It is already known that a simple nonlocal de Sitter gravity model, which we denote as dS gravity, contains an exact vacuum cosmological solution which mimics dark energy and dark matter and is in very good agreement with the standard model of cosmology. This success of dS gravity motivated us to investigate how it works at lower than cosmic scale – galactic and the solar system. This paper contains our investigation of the corresponding Schwarzschild-de Sitter metric of the dS gravity model. To get exact solution, it is necessary to solve the corresponding nonlinear differential equation, what is a very complicated and difficult problem. What we obtained is a solution of linearized equation, which is related to space metric far from the massive body, where gravitational field is weak. The obtained approximate solution is of particular interest for examining the possible role of non-local de Sitter gravity dS in describing the effects in galactic dynamics that are usually attributed to dark matter. The solution has been tested on the Milky Way and the spiral galaxy M33 and is in good agreement with observational measurements.

In a series of recent papers we developed a formulation of general relativity in which spacetime and the dynamics of matter evolve with a Poincaré invariant parameter τ. In this paper we apply the formalism to derive the metric induced by a `static’ event evolving uniformly along its t-axis at the spatial origin x=0. The metric is shown to vary with t and τ, as well as spatial distance r, taking its maximum value for a test particle at the retarded time τ=t−r/c. In the resulting picture, an event localized is space and time produces a metric field similarly localized, where both evolve in τ. We first derive this metric as a solution to the wave equation in linearized field theory, and discuss its limitations by studying the geodesic motion it produces for an evolving event. By then examining this solution in the 4+1 formalism, which poses an initial value problem for the metric under τ-evolution, we clarify these limitations and indicate how they may be overcome in a solution to the full nonlinear field equations.

The study of Graviton as Goldstone bosons appeared in the 1960s, after Bjorken interacting idea of Electrodynamics. However, no recent advancement has been done in the field, because of very constraints as well as low-attractiveness of the theory. We do the non-metric tensor (covariant derivative of the metric tensor) case of Gravitation and eventually get SO(1,3) broken in the vacuum state of quantized field theory, then find the Graviton as Goldstone Boson. We, in final, see that Gravitons can have appearances in many modified (and extended) theories of Gravitation.

Imagination is more important than knowledge, but if intellect does not provide the needed logical structures, capacities for envisioning new possibilities are overly constrained. The sustainability problems we face today cannot be solved with the same kind of thinking that created them, but clarity on what counts as a new kind of thinking is sorely lacking. This article proposes methodical, model-based ways of heeding Bateson's warning about the negative consequences for the ecology of mind that follow from ignoring the contexts of relationships. Informed by S. L. Star's sense of boundary objects, a sequence of increasingly complex logical types distinguishes and interconnects qualitatively different kinds of thinking in ways that liberate imaginative new possibilities for life. The economy of thought instantiated at each level of complexity is only as meaningful, useful, beautiful, ethical, and efficient as the standards informing local adaptive improvisations. Standards mediating the general and specific, global and local, universally transcendent and embodied particulars enable meaningful negotiations, agreements, and communications. Attending to the differences between levels of discourse sets up new possibilities for creative and imaginative entrepreneurial approaches to viable, feasible, and desirable goals for measuring and managing sustainable development.

Consider a robot that is navigating in a space modeled by a graph, and that wants to know its current location. It can send a signal to determine how far it is from each landmark among a set of fixed landmarks. We study the problem of computing the minimum required number of landmarks, and where they should be placed so that the robot can always determine its location. Since the problem is an NP-complete problem, the robot's responses to the actions are slow. To accelerate this response, we can use the parallel version of this problem. In this work, we introduce a new parallel implementation for determining the metric dimension of a given graph. We run the proposed algorithm on a symmetric multi-processing (SMP) cluster using C programming language and the Message Passing Interface (MPI) library. Finally, we run our implementation on four categories of graphs (the tracks in which the robot moves): a cycle graph Cn, a path graph Pn, a triangular snake graph and a ladder graph Ln. Preliminary computational results indicate that the metric dimension problem is an NP-complete problem and prove the ability of the proposed algorithm to achieve a speedup of 6 for 8 processors.

We prove a quasi-pseudometric version of the strong Ekeland principle proved by P. Georgiev and T. Suzuki.

The preservative qualities of individual ionic compounds on the infectivity of T4 virions were elucidated. T4 virions were immersed in quasi-pure ionic solutions prior to the adsorption process, and the pfu values of these were measured following the conventional method. In neutral ionic solutions, the minimum and the optimum concentrations for preservative qualities were corresponded with the results obtained from the multi-ionic media/buffers. In acid and alkali solutions, phages show tolerances at a pH range of 5-11 in multi-ionic media/buffers. T4 virions show no tolerance in quasi-pure acid, neutral and weak alkaline conditions. The preservative quality of T4 virions was jumped up in over 10-1 mM OH- solution, equivalent to pH value over 10, which is corresponding to the pKa of the deprotonation of the DNA bases G and T. Infectivity was lost below 10-1 mM OH- and higher than 10 mM OH-. These results implicate the maintaining of infectivity of a virion may need the flexibility of the intra-capsid DNA by deprotonation.

This paper presents the design and implementation of a multichannel bio-impedance spectroscopy system on field programmable gate arrays (FPGA). The proposed system is capable of acquiring multiple signals from multiple bio-impedance sensors, process the data on the FPGA and store the final data in the on-board Memory. The system employs the Digital Automatic Balance Bridge (DABB) method to acquire data from biosensors. The DABB measures initial data of a known impedance to extrapolate the value of the impedance for the device under test. This method offers a simpler design because the balancing of the circuit is done digitally in the FPGA rather than using an external circuit. Calculations of the impedance values for the device under test were done in the processor. The final data is sent to an onboard Flash Memory to be stored for later access. The control unit handles the interfacing and the scheduling between these different modules (Processor, Flash Memory) as well as interfacing to multiple Balance Bridge and multiple biosensors. The system has been simulated successfully and has comparable performance to other FPGA based solutions. The system has a robust design that is capable of handling and interfacing input from multiple biosensors. Data processing and storage is also performed with minimal resources on the FPGA.

This paper studies the dynamic response of corner supported modular steel buildings with a core wall system, under progressive collapse scenarios, associated with corner module removals. Since using secondary systems such as concrete core in mid- to high-rise buildings is currently una-voidable, understanding their impact on load transfer between modules during collapse scenarios becomes essential. The designated buildings with four-, eight- and twelve-story were modelled using the macro-model based finite element method in Abaqus. Also, three different locations are considered for the concrete shear core within the building plan, leading to nine various case scenarios. Each vertical and horizontal inter-module connection was modelled by one axial and two shear springs with predefined nonlinear force-displacement behaviour. The local and global buckling, which plays an essential role in the building's stability, was considered to obtain accurate results. Finally, parametric studies on the building response were carried out, including the intra-module connection rigidity and inter-module connection stiffness. The results demonstrated that the core wall could maintain the robustness of modular steel building through two mechanisms dependent on its location within the plan. Also, preventing plastic hinges from forming in beams could be introduced as an anti-collapse mechanism in the corner module removal scenarios

In order to study the way how to improve the spatial action of precast monolithic composite floor slabs, and would replace the cast-in-place surface layer for reduce the weight of structure, using pseudo-dynamic tests on 1/4 scale models of two-span and three-story frame structure. The lateral load tests compared the stresses and displacements with cast-in-place floor frame-shear wall structure (SJ1) and precast monolithic floor frame-shear wall structure with X horizontal braces at the bottom of the floor (SJ2). The results show the X horizontal braces can improve the spatial action. Structural integrity (SJ2) as well as the effective transmission of the horizontal force can be ensured by additional X bracing at the bottom of the rigidity of the floor without cast-in-place concrete topping. The results show that X horizontal braces more effectively transfer horizontal, which provides a beneficial reference for similar research.

We obtain some generalised Minkowski-type integral formulas for compact Riemannian (resp. spacelike) hypersurfaces in Riemannian (resp. Lorentzian) manifolds admitting an arbitrary vector field that we assume to be timelike in the case where the ambient space is Lorentzian. Some of these formulas generalize existing formulas in the case of conformal and Killing vector fields. We apply these integral formulas to obtain interesting results concerning the characterization of such hypersurfaces in some particular cases such as when the ambient space is Einstein admitting an arbitrary (in particular, conformal or Killing) vector field, and when the hypersurface has constant mean curvature.

This works is related to the modeling of cellulose pyrolysis with a pseudo equilibrium approach. The objective is to model the kinetics of the cellulose pyrolysis with a semi-global mechanism obtained from the literature, in order to obtain the yield and the rate of formation of char. The pseudo equilibrium sense consists in the supposition that the solid phase devolatilization can be described kinetically - at finite rate - , preserving the competitive characteristic between the production of char and tar, while the gas phase can be described by means of chemical equilibrium. A set of ordinary, linear and non linear, differential equations was obtained and solved numerically with a simple but consistent scheme using the Totally Implicit Euler method. Chemical equilibrium was solved using CANTERA coupled with a code written in Matlab. Results showed that the scheme preserve the tar-gas competitive characteristic for cellulose pyrolysis. The gas phase, is defined as a mixture of CO₂, CO, H₂O, CH₄, H₂ and N₂ showed similarly composition compared with models from literature. Finally, the extension of the model to biomass in general, is straightforward, in order to include the hemicellulose and lignin.

Non-standard diesel blends can be harmful to the environment and human health. In this context, a simple analytical method to estimate the biodiesel mixture ratio in diesel was developed based on the impedance spectroscopy (IS) associated with the interdigitated sensors. In this article, four different interdigitated sensors, variable comb spacing (G), were simulated using the COMSOL Multiphysics software. Based on finite element simulations, four interdigitated electrode architectures by manufactured and evaluated. According to the X-ray powder diffraction technique, the deposition of the conductive layer (Au°) over the surface of the dielectric substrate (SiO2) did not alter its phase composition. In the analysis of AFM and SEM, it was possible to observe irregular edges on the electrodes, possibly related to thin layers' manufacturing process and mechanical stability. Another characteristic observed in the AFM images was the height of the step of the gold layer of the sensor. Several cross-sections were obtained, and the mean step value is 225.71 ± 0.0032 nm. Although there are differences in the roughness, the whole sensor has nanometric roughness. Based on the finite element method simulation performed, it can be assumed that the geometric parameters more suitable for the manufacturing of the electrode are: W = 20 µm, L = 1000 µm, G = 50 µm e N = 40 digits. The electrical characterization performed by impedance spectroscopy showed that we could differentiate between biodiesel and diesel fuels and their pseudo-binary mixtures in the low-frequency region.

Deep learning models are part of the family of artificial neural networks and, as such, it suffers of catastrophic interference when they learn sequentially. In addition, most of these models have a rigid architecture which prevents the incremental learning of new classes. To overcome these drawbacks, in this article we propose the Self-Improving Generative Artificial Neural Network (SIGANN), a type of end-to-end Deep Neural Network system which is able to ease the catastrophic forgetting problem when leaning new classes. In this method, we introduce a novelty detection model to automatically detect samples of new classes, moreover an adversarial auto-encoder is used to produce samples of previous classes. This system consists of three main modules: a classifier module implemented using a Deep Convolutional Neural Network, a generator module based on an adversarial autoencoder; and a novelty detection module, implemented using an OpenMax activation function. Using the EMNIST data set, the model was trained incrementally, starting with a small set of classes. The results of the simulation show that SIGANN is able to retain previous knowledge with a gradual forgetfulness for each learning sequence. Moreover, SIGANN can detect new classes that are hidden in the data and, therefore, proceed with incremental class learning.

Radio bursts provide important diagnostics of energetic phenomena of the Sun. In particular, bursts in decimetric and metric wavelengths probe the physical conditions and the energy release processes in the low corona as well as their association with heliospheric phenomena. The advent of spectral radio data with high time and high frequency resolution has provided a wealth of information on phenomena of short duration and narrow bandwidth. Of particular value are spectral data combined with imaging observations at specific frequencies. In this work we briefly review the results of a series of observations comprised from high-sensitivity, low-noise dynamic spectra obtained with the acousto-optic analyzer (SAO) of the ARTEMIS-IV/JLS solar radiospectrograph, in conjunction with high time-resolution images from the Nançay Radioheliograph (NRH). Our studies include fine structures embedded in type IV burst continua (mostly narrow-band "spikes" and intermediate drift "fiber" bursts) and spike-like structures detected near the front of type-II bursts. The implications of the observational results to theoretical models are discussed.

We describe a recently developed approach to quantify welfare loss in animals, the Cumulative Pain metric. It combines the two most relevant dimensions of negative affective experiences: intensity and duration. The metric enables estimating the time individuals spend in negative affective states of a physical or psychological nature (operationally referred to simply as ‘pain’) of different intensities as the result of one or more challenges (e.g., diseases, injuries, deprivations). A new notation protocol (the Pain-Track) is used in which the duration of the experience is represented along the horizontal axis and intensity is represented by four categories in the vertical axis. Pain experiences are partitioned into temporal segments, where hypotheses for the experienced duration and intensity are proposed based on existing welfare indicators (e.g., neurophysiological, behavioral, anatomical, evolutionary). This structure forces transparency about assumptions and uncertainties, highlights knowledge gaps, and enables estimates to be continuously adjusted. Because the Cumulative Pain metric is based on parameters with a broadly common biological meaning, it provides the much needed interoperability among assessments of animal welfare. It enables comparing the impact of practices and living conditions, policies and interventions, and the calculation of welfare footprints of animal-sourced products using a universal measurement unit.

Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be a very powerful for the solution of problems in complex planning. We introduce mctreesearch4j, a standard MCTS implementation written as a standard JVM library following key design principles of object oriented programming. We define key class abstractions allowing the MCTS library to flexibly adapt to any well defined Markov Decision Process or turn-based adversarial game. Furthermore, our library is designed to be modular and extensible, utilizing class inheritance and generic typing to standardize custom algorithm definitions. We demon- strate that the design of the MCTS implementation provides ease of adaptation for unique heuristics and customization across varying Markov Decision Process (MDP) domains. In addition, the implementation is reasonably performant and accurate for standard MDP’s. In addition, via the implementation of mctreesearch4j, the nuances of different types of MCTS algorithms are discussed.

This article reevaluates the Woesean concept of crossing a ‘Darwinian threshold’ from pre-genomic communality, as prevailing in an ancestral ‘progenote’ state, to vertically stable lineages of autonomous and self-similar cells. This transition from collective trunk-line evolution to Darwinian speciation is dependent on the generation of modular organismal genomes. The same general principle should be valid at subcellular levels, allowing the emergence of semi-autonomous genomic agents, such as viruses and plasmid-carrying endogenous vesicles with organelle-like properties. As compartmentalized agents of endogenous nature could start with smaller genomes than those required for fully autonomous cells, it is conjectured that stable subcellular lineages emerged earlier than their cellular counterparts. Referring to the recent ‘pre-endosymbiont hypothesis’, it is proposed that free-living bacteria (the first ‘prokaryote’ cells) arose by ‘lineage escape’ from plasmid-bearing organelle-like compartments, evolving inside the internally complexifying ‘paracells’ of the progenote community. The double-membrane envelopes of diderm bacteria may have resulted from cell-biological processes facilitating cellular lineage escape. The later emergence of archaeal cells (resembling bacteria in ‘prokaryote’ appearance with unichromosomal genomes) and eukaryotic organisms (with compartmented cells and multichromosal genomes) can also be interpreted in terms of this modified progenote hypothesis. Conceivably, the multichromosomal genomes of eukaryotes were bundled in endogenous nuclear compartments to organize a ‘nuclear-cytoplasmic lineage’, which became vertically stable by perfecting mitosis/meiosis-like divisions and yet retained some intra-species population confluence by sexual division-fusion cycles.