Versions Of Variants Research Articles

Optimization of the Automated Production Process Using Software Simulation Tools

The purpose of this article is to point out the need to use software simulation tools in industrial practice to optimize the production process and assess the economic effectiveness of investment, including risk. The goal of the research is to find an optimal investment variant to ensure an increase in the production volume of at least 50% and to achieve the maximum economic efficiency of the investment, even considering the risk. The article presents a comprehensive approach that enables the achievement of the set research goal. The selection of the optimal version of the investment is carried out in three steps. Firstly, the versions of the investment variants are assessed from the production point of view using the program Tecnomatix Plant Simulation. Subsequently, the versions of the investment variants are assessed from an economic point of view and from a risk point of view. Economic efficiency is assessed using the financial criteria net present value (NPV), profitability index (PI), and discounted payback period (DPP), and risk analysis is carried out using Monte Carlo simulations. Finally, the accepted outputs are evaluated overall using a multi-criteria method, namely the method of partial order.

Two-Round n-out-of-n and Multi-Signatures and Trapdoor Commitment from Lattices

Although they have been studied for a long time, distributed signature protocols have garnered renewed interest in recent years in view of novel applications to topics like blockchains. Most recent works have focused on distributed versions of ECDSA or variants of Schnorr signatures; however, and in particular, little attention has been given to constructions based on post-quantum secure assumptions like the hardness of lattice problems. A few lattice-based threshold signature and multi-signature schemes have been proposed in the literature, but they either rely on hash-and-sign lattice signatures (which tend to be comparatively inefficient), use expensive generic transformations, or only come with incomplete security proofs. In this paper, we construct several lattice-based distributed signing protocols with low round complexity following the Fiat–Shamir with Aborts (FSwA) paradigm of Lyubashevsky (Asiacrypt 2009). Our protocols can be seen as distributed variants of the fast Dilithium-G signature scheme and the full security proof can be made assuming the hardness of module SIS and LWE problems. A key step to achieving security (unexplained in some earlier papers) is to prevent the leakage that can occur when parties abort after their first message—which can inevitably happen in the Fiat–Shamir with Aborts setting. We manage to do so using homomorphic commitments. Exploiting the similarities between FSwA and Schnorr-style signatures, our approach makes the most of observations from recent advancements in the discrete log setting, such as Drijvers et al.’s seminal work on two-round multi-signatures (S&P 2019). In particular, we observe that the use of commitment not only resolves the subtle issue with aborts, but also makes it possible to realize secure two-round n-out-of-n distributed signing and multi-signature in the plain public key model, by equipping the commitment with a trapdoor feature. The construction of suitable trapdoor commitment from lattices is a side contribution of this paper.

Block Gram-Schmidt algorithms and their stability properties

Block Gram-Schmidt algorithms serve as essential kernels in many scientific computing applications, but for many commonly used variants, a rigorous treatment of their stability properties remains open. This work provides a comprehensive categorization of block Gram-Schmidt algorithms, particularly those used in Krylov subspace methods to build orthonormal bases one block vector at a time. Known stability results are assembled, and new results are summarized or conjectured for important communication-reducing variants. Additionally, new block versions of low-synchronization variants are derived, and their efficacy and stability are demonstrated for a wide range of challenging examples. Numerical examples are computed with a versatile Matlab package hosted at https://github.com/katlund/BlockStab, and scripts for reproducing all results in the paper are provided. Block Gram-Schmidt implementations in popular software packages are discussed, along with a number of open problems. An appendix containing all algorithms type-set in a uniform fashion is provided.

Denoising electromyogram and electroencephalogram signals using improved complete ensemble empirical mode decomposition with adaptive noise

The health of the brain and muscles depends on the proper analysis of electroencephalogram and electromyogram signals without noise. The latter blends into the recording of biomedical signals for external or internal reasons of the human body. Therefore, to obtain a more accurate signal, it is needed to select filtering techniques that minimize the noise. In this study, the techniques used are empirical mode decomposition and its variants. Among the new versions of variants is the improved complete ensemble empirical mode decomposition with adaptive noise. These methods are applied to electroencephalogram and electromyogram signals corrupted by natural noise and white Gaussian noise. The obtained results through the use of the improved complete ensemble empirical mode decomposition with adaptive noises how the high performance that includes minimizing the noise and the effectiveness of the components of the signals used in the present research. This method has low values of the mean square error and high values of signal-to-noise ratio compared to other methods used in this study.

N- and S-oxygenation activity of truncated human flavin-containing monooxygenase 3 and its common polymorphic variants

Human flavin-containing monooxygenase 3 (FMO3) is a membrane-bound, phase I drug metabolizing enzyme. It is highly polymorphic with some of its variants demonstrating differences in rates of turnover of its substrates: xenobiotics including drugs as well as dietary compounds. In order to measure its in vitro activity and compare any differences between the wild type enzyme and its polymorphic variants, we undertook a systematic study using different engineered proteins, heterologously expressed in bacteria, purified and catalytically characterized with 3 different substrates. These included the full-length as well as the more soluble C-terminal truncated versions of the common polymorphic variants (E158K, V257M and E308G) of FMO3 in addition to the full-length and truncated wild-type proteins. In vitro activity assays were performed with benzydamine, tamoxifen and sulindac sulfide, whose products were measured by HPLC. Differences in catalytic properties between the wild-type FMO3 and its common polymorphic variants were similar to those observed with the truncated, more soluble versions of the enzymes. Interestingly, the truncated enzymes were better catalysts than the full-length proteins. The data obtained point to the feasibility of using the more soluble forms of this enzyme for in vitro drug assays as well as future biotechnological applications possibly in high throughput systems such as bioelectrochemical platforms and biosensors.

Retest test selection for product-line regression testing of variants and versions of variants

Testing is a crucial activity of product-line engineering. Due to shared commonality, testing each variant individually results in redundant testing processes. By adopting regression testing strategies, variants are tested incrementally by focusing on the variability between variants to reduce the overall testing effort. However, product lines evolve during their life-cycle to adapt, e.g., to changing requirements. Hence, quality assurance has also to be ensured after product-line evolution by efficiently testing respective versions of variants. In this paper, we propose retest test selection for product-line regression testing of variants and versions of variants. Based on delta-oriented test modeling, we capture the commonality and variability of an evolving product line by means of differences between variants and versions of variants. We exploit those differences to apply change impact analyses, where we reason about changed dependencies to be retested when stepping from a variant or a version of a variant to its subsequent one by selecting test cases for reexecution. We prototypically implemented our approach and evaluated its effectiveness and efficiency by means of two evolving product lines showing positive results.

Relative quantity and allocation disagreement measures for category-level accuracy assessment

Accuracy assessment of classified imagery is an important task in remote sensing. A commonly used approach for assessing classification accuracy is based on the error matrix. The error matrix can be summarized by overall and category accuracy measures, e.g. the overall agreement and the user’s and producer’s accuracies. Two relatively new measures are the so-called quantity disagreement and allocation disagreement. In this article, relative versions of the category-level variants of these measures are defined. It is also shown how the new category measures are related to the overall quantity and allocation disagreement measures.

Erdős–Szekeres Theorem for Lines

According to the Erd?s---Szekeres theorem, for every n, a sufficiently large set of points in general position in the plane contains n in convex position. In this note we investigate the line version of this result, that is, we want to find n lines in convex position in a sufficiently large set of lines that are in general position. We prove almost matching upper and lower bounds for the minimum size of the set of lines in general position that always contains n in convex position. This is quite unexpected, since in the case of points, the best known bounds are very far from each other. We also establish the dual versions of many variants and generalizations of the Erd?s---Szekeres theorem.

Distributed heterogeneous mixing of differential and dynamic differential evolution variants for unconstrained global optimization

This paper proposes a novel distributed differential evolution framework called distributed mixed variants (dynamic) differential evolution ( $$dmvD^{2}E)$$ d m v D 2 E ) . This novel framework is a heterogeneous mix of effective differential evolution (DE) and dynamic differential evolution (DDE) variants with diverse characteristics in a distributed framework to result in $$dmvD^{2}E$$ d m v D 2 E . The $$dmvD^{2}E$$ d m v D 2 E , discussed in this paper, constitute various proportions and combinations of DE/best/2/bin and DDE/best/2/bin as subpopulations with each variant evolving independently but also exchanging information amongst others to co-operatively enhance the efficacy of $$dmvD^{2}E$$ d m v D 2 E as whole. The $$dmvD^{2}E$$ d m v D 2 E variants have been run on 14 test problems of 30 dimensions to display their competitive performance over the distributed classical and dynamic versions of the constituent variants. The $$dmvD^{2}E$$ d m v D 2 E , when benchmarked on a different 13 test problems of 500 as well as 1,000 dimensions, scaled well and outperformed, on an average, five existing distributed differential evolution algorithms.

Distributed mixed variant differential evolution algorithms for unconstrained global optimization

This paper proposes a novel distributed differential evolution algorithm called Distributed Mixed Variant Differential Evolution (dmvDE). To alleviate the time consuming trial-and-error selection of appropriate Differential Evolution (DE) variant to solve a given optimization problem, dmvDE proposes to mix effective DE variants with diverse characteristics in a distributed framework. The novelty of dmvDEs lies in mixing different DE variants in an island based distributed framework. The 19 dmvDE algorithms, discussed in this paper, constitute various proportions and combinations of four DE variants (DE/rand/1/bin, DE/rand/2/bin, DE/best/2/bin and DE/rand-to-best/1/bin) as subpopulations with each variant evolving independently but also exchanging information amongst others to co-operatively enhance the efficacy of the distributed DE as a whole. The dmvDE algorithms have been run on a set of test problems and compared to the distributed versions of the constituent DE variants. Simulation results show that dmvDEs display a consistent overall improvement in performance than that of distributed DEs. The best of dmvDE algorithms has also been benchmarked against five distributed differential evolution algorithms. Simulation results reiterate the superior performance of the mixing of the DE variants in a distributed frame work. The best of dmvDE algorithms outperforms, on average, all five algorithms considered.

Assessment of the Performance of MP2 and MP2 Variants for the Treatment of Noncovalent Interactions

For many years, MP2 served as the principal method for the treatment of noncovalent interactions. Until recently, this was the only technique that could be used to produce reasonably accurate binding energies, with binding energy errors generally below ~35%, at a reasonable computational cost. The past decade has seen the development of many new methods with improved performance for noncovalent interactions, several of which are based on MP2. Here, we assess the performance of MP2, LMP2, MP2-F12, and LMP2-F12, as well as spin component scaled variants (SCS) of these methods, in terms of their abilities to produce accurate interaction energies for binding motifs commonly found in organic and biomolecular systems. Reference data from the newly developed S66 database of interaction energies are used for this assessment, and a further set of 38 complexes is used as a test set for SCS methods developed herein. The strongly basis set-dependent nature of MP2 is confirmed in this study, with the SCS technique greatly reducing this behavior. It is found in this work that the spin component scaling technique can effectively be used to dramatically improve the performance of MP2 and MP2 variants, with overall errors being reduced by factors of about 1.5-2. SCS versions of all MP2 variants tested here are shown to give similarly accurate overall results.

Modelling the Impact of Land Cover Changes on Flood Mitigation in the Upper Lužnice Basin

The study presented herein investigates the impact of simulated changes in land cover on rainfall-runoff conditions for the transboundary basin of the upper Lužnice. The HEC-HMS hydrological model was chosen for these simulations. Scenario models were used to simulate the impact of modifications in basin land cover with individual scenarios reflecting ground cover changes. The years 1990 and 2000, which are available in the CORINE Landcover database, were chosen as variants of river basin land cover. In addition, two theoretical versions of possible extreme variants in fundamental land cover changes – the conversion from agricultural land to grassland and the forestation of the river basin, with the exception of roads and bodies of water – were also included. Single day rainfall totals with a recurrence period of 10, 20, 50 and 100 years were selected to calculate the volume of runoff and culmination discharge. These results demonstrate a clear decrease in the degree of impact of land cover structure on runoff conditions, increasing with the magnitude of precipitation.

Catalytic Enantioselective Olefin Metathesis in Natural Product Synthesis. Chiral Metal‐Based Complexes that Deliver High Enantioselectivity and More

Chiral olefin metathesis catalysts enable chemists to access enantiomerically enriched small molecules with high efficiency; synthesis schemes involving such complexes can be substantially more concise than those that would involve enantiomerically pure substrates and achiral Mo alkylidenes or Ru-based carbenes. The scope of research towards design and development of chiral catalysts is not limited to discovery of complexes that are merely the chiral versions of the related achiral variants. A chiral olefin metathesis catalyst, in addition to furnishing products of high enantiomeric purity, can offer levels of efficiency, product selectivity and/or olefin stereoselectivity that are unavailable through the achiral variants. Such positive attributes of chiral catalysts (whether utilized in racemic or enantiomerically enriched form) should be considered as general, applicable to other classes of transformations.

Functional Expression of the Na-K-2Cl Cotransporter NKCC2 in Mammalian Cells Fails to Confirm the Dominant-negative Effect of the AF Splice Variant

The renal bumetanide-sensitive Na-K-2Cl cotransporter (NKCC2) is the major salt transport pathway in the apical membrane of the mammalian thick ascending limb. It is differentially spliced and the three major variants (A, B, and F) differ in their localization and transport characteristics. Most knowledge about its regulation comes from experiments in Xenopus oocytes as NKCC2 proved difficult to functionally express in a mammalian system. Here we report the cloning and functional expression of untagged and unmodified versions of the major splice variants from ferret kidney (fNKCC2A, -B, and -F) in human embryonic kidney (HEK) 293 cells. Many NKCC2 antibodies used in this study detected high molecular weight forms of the transfected proteins, probably NKCC2 dimers, but not the monomers. Interestingly, monomers were strongly detected by phosphospecific antibodies directed against phosphopeptides in the regulatory N terminus. Bumetanide-sensitive 86Rb uptake was significantly higher in transfected HEK-293 cells and could be stimulated by incubating cells in a medium containing a low chloride concentration prior the uptake measurements. fNKCC2 was less sensitive to the reduction in chloride concentration than NKCC1. Using HEK-293 cells stably expressing fNKCC2A we also show that co-expression of variant NKCC2AF does not have the dominant-negative effect on NKCC2A activity that was seen in Xenopus oocytes, nor is it trafficked to the cell surface. In addition, fNKCC2AF is neither complex glycosylated nor phosphorylated in its N terminus regulatory region like other variants.

Impact of Disease Mutations on the Desmin Filament Assembly Process

It has been documented that mutations in the human desmin gene lead to a severe type of myofibrillar myopathy, termed more specifically desminopathy, which affects cardiac and skeletal as well as smooth muscle. We showed recently that 14 recombinant versions of these disease-causing desmin variants, all involving single amino acid substitutions in the α-helical rod domain, interfere with in vitro filament formation at distinct stages of the assembly process. We now provide mechanistic details of how these mutations affect the filament assembly process by employing analytical ultracentrifugation, time-lapse electron microscopy of negatively stained and glycerol-sprayed/low-angle rotary metal-shadowed samples, quantitative scanning transmission electron microscopy, and viscometric studies. In particular, the soluble assembly intermediates of two of the mutated proteins exhibit unusually high s-values, compatible with octamers and other higher-order complexes. Moreover, several of the six filament-forming mutant variants deviated considerably from wild-type desmin with respect to their filament diameters and mass-per-length values. In the heteropolymeric situation with wild-type desmin, four of the mutant variants caused a pronounced “hyper-assembly”, when assayed by viscometry. This indicates that the various mutations may cause abortion of filament formation by the mutant protein at distinct stages, and that some of them interfere severely with the assembly of wild-type desmin. Taken together, our findings provide novel insights into the basic intermediate filament assembly mechanisms and offer clues as to how amino acid changes within the desmin rod domain may interfere with the normal structural organization of the muscle cytoskeleton, eventually leading to desminopathy.

Should thrombolysis be given to a stroke patient refusing therapy due to profound anosognosia?

<h3>Abstract</h3> Soluble ACE2 (sACE2) decoy receptors are promising agents to inhibit SARS-CoV-2, as their efficiency is less likely to be affected by common escape mutations in viral proteins. However, their success may be limited by their relatively poor potency. To address this challenge, we developed a large decoy library of sACE2 fusion proteins, generated with several protease inhibitors or multimerization tags. Among these decoys, multimeric sACE2 consisting of SunTag or MoonTag systems, which were originally utilized for signal amplification or gene activation systems, were extremely effective in neutralizing SARS-CoV-2 in pseudoviral systems and in clinical isolates. These novel sACE2 fusion proteins exhibited greater than 100-fold SARS-CoV-2 neutralization efficiency, compared to monomeric sACE2. SunTag or MoonTag in combination with a more potent version of sACE2, which has multiple point mutations for greater binding (v1), achieved near complete neutralization at a sub-nanomolar range, comparable with clinical monoclonal antibodies. Pseudoviruses bearing mutant versions of Spike, alpha, beta, gamma or delta variants, were also neutralized efficiently with SunTag or MoonTag fused sACE2(v1). Finally, therapeutic treatment of sACE2(v1)-MoonTag provided protection against SARS-CoV-2 infection in an <i>in vivo</i> mouse model. Overall, we suggest that the superior activity of the sACE2-SunTag or sACE2-MoonTag fusions is due to the greater occupancy of the multimeric sACE2 receptors on Spike protein as compared to monomeric sACE2. Therefore, these highly potent multimeric sACE2 decoy receptors may offer a promising treatment approach against SARS-CoV-2 infections. <h3>One Sentence Summary</h3> Multimerization of sACE2 markedly enhanced the neutralization of SARS-CoV-2 by blocking multiple viral spike proteins simultaneously.

Histone H2A variants and the inactive X chromosome: identification of a second macroH2A variant.

MacroH2A1 is an unusual variant of the core histone H2A which is enriched in chromatin on the inactive X chromosome of female mammals. The N-terminal third of the protein shares 65% amino acid identity with core histone H2A, while the remaining two-thirds of the protein are novel, with a small stretch of basic amino acids and a putative leucine zipper motif. We have now cloned a second macroH2A gene, encoding macroH2A2 which shares 80% amino acid identity with macroH2A1. Despite mapping to different chromosomes, the genomic organization of the macroH2A2 and macroH2A1 genes are nearly identical. The leucine zipper motif of macroH2A1 is not conserved in macroH2A2. Like macroH2A1, macroH2A2 forms a Macro Chromatin Body in the nuclei of female cells which is coincident with an X chromosome and co-localizes with macroH2A1. To address the distribution of other histone H2A variants in relation to macroH2A and the inactive X chromosome, we constructed a series of epitope-tagged versions of other histone H2A variants. Like the recently described H2A-Bbd (Barr body-deficient) variant, the histone variant H2A.Z was found to be deficient in chromatin on the inactive X chromosome in a significant proportion of female nuclei. This study provides further information about the nucleosomal composition of chromatin on the inactive X chromosome and indicates that a number of H2A variants are non-randomly distributed on the active and inactive X chromosomes.

SOLUTION OF LARGE LINEAR SYSTEMS ON PIPELINED SIMD MACHINES

We developed a direct out-of-core solver for dense non-symmetric linear systems of ‘arbitrary’ size N×N. The algorithm fully employs the Basic Linear Algebra Subprograms (BLAS), and can therefore easily be adapted to different computer architectures by using the corresponding optimized routines. We used blocked versions of left-looking and right-looking variants of LU decomposition to perform most of the operations in Level 3 BLAS, to reduce the number of I/O operations and to minimize the CPU time usage. The storage requirements of the algorithm are only 2N×NB data elements where NB≪N. Depending on the sustained floating point performance and the sustained I/O rate of the given hardware, we derived formulas that allow for choosing optimal values of NB to balance between CPU time and I/O time. We tested the algorithm by means of linear systems derived from 3D-BEM for strongly and weakly singular integral equations and from interpolation problems for scattered data on closed surfaces in ℝ3. It took only about 2⋅5 CPU minutes on a 5 GFLOPS vector computer SNI S600/20 to solve a linear system of size 10000, which corresponds to a performance of 4⋅3 GFLOPS; a value of NB=650 gives a reasonable I/O time and the necessary main storage size is about 13 Mwords. In addition, we compared the algorithm with (1) an out-of-core version of GMRES and (2) a wavelet transform followed by in-core GMRES after thresholding. At least for boundary integral equations of classical boundary value problems of potential theory, the out-of-core version of GMRES is superior to the direct out-of-core solver and the wavelet transform since the algorithm converged after at most 5 iteration steps. It took about 17 s to solve a system with 8192 unknowns compared with 146 s for direct out-of-core and 402 s for wavelet transform followed by in-core GMRES. © 1997 by John Wiley & Sons, Ltd.