VSB - Technical University of Ostrava

Dalton is a powerful general-purpose program system for the study of molecular electronic structure at the Hartree-Fock, Kohn-Sham, multiconfigurational self-consistent-field, Møller-Plesset, configuration-interaction, and coupled-cluster levels of theory. Apart from the total energy, a wide variety of molecular properties may be calculated using these electronic-structure models. Molecular gradients and Hessians are available for geometry optimizations, molecular dynamics, and vibrational studies, whereas magnetic resonance and optical activity can be studied in a gauge-origin-invariant manner. Frequency-dependent molecular properties can be calculated using linear, quadratic, and cubic response theory. A large number of singlet and triplet perturbation operators are available for the study of one-, two-, and three-photon processes. Environmental effects may be included using various dielectric-medium and quantum-mechanics/molecular-mechanics models. Large molecules may be studied using linear-scaling and massively parallel algorithms. Dalton is distributed at no cost from http://www.daltonprogram.org for a number of UNIX platforms.

This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling salesman problem, vehicle routing problem, scheduling problem, and knapsack problem. It is identified that based on the manner in which NSGA-II has been implemented for solving the aforementioned group of problems, there can be three categories: Conventional NSGA-II, where the authors have implemented the basic version of NSGA-II, without making any changes in the operators; the second one is Modified NSGA-II, where the researchers have implemented NSGA-II after making some changes into it and finally, Hybrid NSGA-II variants, where the researchers have hybridized the conventional and modified NSGA-II with some other technique. The article analyses the modifications in NSGA-II and also discusses the various performance assessment techniques used by the researchers, i.e., test instances, performance metrics, statistical tests, case studies, benchmarking with other state-of-the-art algorithms. Additionally, the paper also provides a brief bibliometric analysis based on the work done in this study.

Additive manufacturing (3D printing) has significantly changed the prototyping process in terms of technology, construction, materials, and their multiphysical properties. Among the most popular 3D printing techniques is vat photopolymerization, in which ultraviolet (UV) light is deployed to form chains between molecules of liquid light-curable resin, crosslink them, and as a result, solidify the resin. In this manuscript, three photopolymerization technologies, namely, stereolithography (SLA), digital light processing (DLP), and continuous digital light processing (CDLP), are reviewed. Additionally, the after-cured mechanical properties of light-curable resin materials are listed, along with a number of case studies showing their applications in practice. The manuscript aims at providing an overview and future trend of the photopolymerization technology to inspire the readers to engage in further research in this field, especially regarding developing new materials and mathematical models for microrods and bionic structures.

With the exponential growth in the mobile device market over the last decade, chatbots are becoming an increasingly popular option to interact with users, and their popularity and adoption are rapidly spreading. These mobile devices change the way we communicate and allow ever-present learning in various environments. This study examined educational chatbots for Facebook Messenger to support learning. The independent web directory was screened to assess chatbots for this study resulting in the identification of 89 unique chatbots. Each chatbot was classified by language, subject matter and developer's platform. Finally, we evaluated 47 educational chatbots using the Facebook Messenger platform based on the analytic hierarchy process against the quality attributes of teaching, humanity, affect, and accessibility. We found that educational chatbots on the Facebook Messenger platform vary from the basic level of sending personalized messages to recommending learning content. Results show that chatbots which are part of the instant messaging application are still in its early stages to become artificial intelligence teaching assistants. The findings provide tips for teachers to integrate chatbots into classroom practice and advice what types of chatbots they can try out.

Abstract Heavy metals are naturally occurring components of the Earth’s crust and persistent environmental pollutants. Human exposure to heavy metals occurs via various pathways, including inhalation of air/dust particles, ingesting contaminated water or soil, or through the food chain. Their bioaccumulation may lead to diverse toxic effects affecting different body tissues and organ systems. The toxicity of heavy metals depends on the properties of the given metal, dose, route, duration of exposure (acute or chronic), and extent of bioaccumulation. The detrimental impacts of heavy metals on human health are largely linked to their capacity to interfere with antioxidant defense mechanisms, primarily through their interaction with intracellular glutathione (GSH) or sulfhydryl groups (R-SH) of antioxidant enzymes such as superoxide dismutase (SOD), catalase, glutathione peroxidase (GPx), glutathione reductase (GR), and other enzyme systems. Although arsenic (As) is believed to bind directly to critical thiols, alternative hydrogen peroxide production processes have also been postulated. Heavy metals are known to interfere with signaling pathways and affect a variety of cellular processes, including cell growth, proliferation, survival, metabolism, and apoptosis. For example, cadmium can affect the BLC-2 family of proteins involved in mitochondrial death via the overexpression of antiapoptotic Bcl-2 and the suppression of proapoptotic (BAX, BAK) mechanisms, thus increasing the resistance of various cells to undergo malignant transformation. Nuclear factor erythroid 2-related factor 2 (Nrf2) is an important regulator of antioxidant enzymes, the level of oxidative stress, and cellular resistance to oxidants and has been shown to act as a double-edged sword in response to arsenic-induced oxidative stress. Another mechanism of significant health threats and heavy metal (e.g., Pb) toxicity involves the substitution of essential metals (e.g., calcium (Ca), copper (Cu), and iron (Fe)) with structurally similar heavy metals (e.g., cadmium (Cd) and lead (Pb)) in the metal-binding sites of proteins. Displaced essential redox metals (copper, iron, manganese) from their natural metal-binding sites can catalyze the decomposition of hydrogen peroxide via the Fenton reaction and generate damaging ROS such as hydroxyl radicals, causing damage to lipids, proteins, and DNA. Conversely, some heavy metals, such as cadmium, can suppress the synthesis of nitric oxide radical (NO · ), manifested by altered vasorelaxation and, consequently, blood pressure regulation. Pb-induced oxidative stress has been shown to be indirectly responsible for the depletion of nitric oxide due to its interaction with superoxide radical (O 2 ·− ), resulting in the formation of a potent biological oxidant, peroxynitrite (ONOO − ). This review comprehensively discusses the mechanisms of heavy metal toxicity and their health effects. Aluminum (Al), cadmium (Cd), arsenic (As), mercury (Hg), lead (Pb), and chromium (Cr) and their roles in the development of gastrointestinal, pulmonary, kidney, reproductive, neurodegenerative (Alzheimer’s and Parkinson’s diseases), cardiovascular, and cancer (e.g. renal, lung, skin, stomach) diseases are discussed. A short account is devoted to the detoxification of heavy metals by chelation via the use of ethylenediaminetetraacetic acid ( EDTA), dimercaprol (BAL), 2,3-dimercaptosuccinic acid (DMSA), 2,3-dimercapto-1-propane sulfonic acid (DMPS), and penicillamine chelators.

Particle Swarm Optimization is a popular heuristic search algorithm which is inspired by the social learning of birds or fishes. It is a swarm intelligence technique for optimization developed by Eberhart and Kennedy [1] in 1995. Inertia weight is an important parameter in PSO, which significantly affects the convergence and exploration-exploitation trade-off in PSO process. Since inception of Inertia Weight in PSO, a large number of variations of Inertia Weight strategy have been proposed. In order to propose one or more than one Inertia Weight strategies which are efficient than others, this paper studies 15 relatively recent and popular Inertia Weight strategies and compares their performance on 05 optimization test problems.

Abstract End-members and species defined with permissible ranges of composition are presented for the true micas, the brittle micas, and the interlayer-deficient micas. The determination of the crystallochemical formula for different available chemical data is outlined, and a system of modifiers and suffixes is given to allow the expression of unusual chemical substitutions or polytypic stacking arrangements. Tables of mica synonyms, varieties, ill-defined materials, and a list of names formerly or erroneously used for micas are presented. The Mica Subcommittee was appointed by the Commission on New Minerals and Mineral Names of the International Mineralogical Association. The definitions and recommendations presented were approved by the Commission.

Antimicrobial resistance (AMR) is one of the biggest threats to the environment and health. AMR rapidly invalidates conventional antibiotics, and antimicrobial nanomaterials have been increasingly explored as alternatives. Interestingly, several antimicrobial nanomaterials show AMR-independent antimicrobial effects without detectable new resistance and have therefore been suggested to prevent AMR evolution. In contrast, some are found to trigger the evolution of AMR. Given these seemingly conflicting findings, a timely discussion of the two faces of antimicrobial nanomaterials is urgently needed. This review systematically compares the killing mechanisms and structure-activity relationships of antibiotics and antimicrobial nanomaterials. We then focus on nano-microbe interactions to elucidate the impacts of molecular initiating events on AMR evolution. Finally, we provide an outlook on future antimicrobial nanomaterials and propose design principles for the prevention of AMR evolution.

INTRODUCTION: The development augmented reality devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency, safety, and cost and to enhance surgical training. However, the awareness of possibilities of augmented reality is generally low. This review evaluates whether augmented reality can presently improve the results of surgical procedures. METHODS: . The initial search yielded 808 studies. After removing duplicates and including only journal articles, a total of 417 studies were identified. By reading of abstracts, 91 relevant studies were chosen to be included. 11 references were gathered by cross-referencing. A total of 102 studies were included in this review. CONCLUSIONS: The present literature suggest an increasing interest of surgeons regarding employing augmented reality into surgery leading to improved safety and efficacy of surgical procedures. Many studies showed that the performance of newly devised augmented reality systems is comparable to traditional techniques. However, several problems need to be addressed before augmented reality is implemented into the routine practice.

In the past decade, two-dimensional (2D) transition metal carbides, nitrides, and carbonitrides (MXenes) have attracted attention and interest from the scientific community due to their superior mechanical strength and flexibility, physical/chemical properties, and multiple exciting functionalities. Among these materials, the ingenious and effective combination of the mechanical and functional properties of MXenes provides a promising opportunity for designing flexible and wearable devices. This review summarizes the recent research progress in the structural stabilities, mechanical strength and deformation mechanism, strain-tunable energy storages, and catalytic and thermoelectric properties along with certain strain modifications and strain-controllable electronic/topological properties of MXenes from a combined theoretical and experimental perspective and illustrates their electronic origins. Taking the design principles as a focus, the theoretical predictions provide guidance, while the experimental work gives a thorough validation, thus setting the foundation for the current scientific achievements, challenges, and prospects in the field of MXenes.

Abstract End members and species defined with permissible ranges of composition are presented for the true micas, the brittle micas and the interlayer-cation-deficient micas. The determination of the crystallochemical formula for different available chemical data is outlined, and a system of modifiers and suffixes is given to allow the expression of unusual chemical substitutions or polytypic stacking arrangements. Tables of mica synonyms, varieties, ill-defined materials and a list of names formerly or erroneously used for micas are presented. The Mica Subcommittee was appointed by the Commission on New Minerals and Mineral Names (“Commission”) of the International Mineralogical Association (IMA). The definitions and recommendations presented were approved by the Commission.

The Analytic Hierarchy Process (AHP) is widely used method in multiple-attribute decision making. In the recent literature many authors used different judgment scales which influenced the results and decisions. In this paper the author reviews and discusses effects of utilization of various judgment scales on priority estimation in AHP. There has been studies that have been concerned with the comparison of judgment scales but there were no studies concerned with consistency measures that are needed. The goal of this paper is to compare and discuss the application of various judgment scales on the results in particular practical example that has been used in previous paper by Saaty (2003). Thus the focus of the paper is to analyze the impact of using different judgment scales on the resulting priorities and consistency to default scale as proposed by Saaty. Results suggest that judgment scales have a profound impact on criteria priorities but not on ranking of criteria. However, the consistency varies among applied judgment scales. Authors calculated the values of random index needed for calculation of the consistency index in AHP for all concerned scales. Based on them the consistency index was computed and compared. Both consistent and inconsistent Saaty matrices were used for comparison.

Current energy and environmental challenges demand the development and design of multifunctional porous materials with tunable properties for catalysis, water purification, and energy conversion and storage. Because of their amenability to de novo reticular chemistry, metal-organic frameworks (MOFs) have become key materials in this area. However, their usefulness is often limited by low chemical stability, conductivity and inappropriate pore sizes. Conductive two-dimensional (2D) materials with robust structural skeletons and/or functionalized surfaces can form stabilizing interactions with MOF components, enabling the fabrication of MOF nanocomposites with tunable pore characteristics. Graphene and its functional derivatives are the largest class of 2D materials and possess remarkable compositional versatility, structural diversity, and controllable surface chemistry. Here, we critically review current knowledge concerning the growth, structure, and properties of graphene derivatives, MOFs, and their graphene@MOF composites as well as the associated structure-property-performance relationships. Synthetic strategies for preparing graphene@MOF composites and tuning their properties are also comprehensively reviewed together with their applications in gas storage/separation, water purification, catalysis (organo-, electro-, and photocatalysis), and electrochemical energy storage and conversion. Current challenges in the development of graphene@MOF hybrids and their practical applications are addressed, revealing areas for future investigation. We hope that this review will inspire further exploration of new graphene@MOF hybrids for energy, electronic, biomedical, and photocatalysis applications as well as studies on previously unreported properties of known hybrids to reveal potential "diamonds in the rough".

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting in larger multidimensional datasets, imaging software must adapt. ImageJ is an open-source image analysis software platform that has aided researchers with a variety of image analysis applications, driven mainly by engaged and collaborative user and developer communities. The close collaboration between programmers and users has resulted in adaptations to accommodate new challenges in image analysis that address the needs of ImageJ's diverse user base. ImageJ consists of many components, some relevant primarily for developers and a vast collection of user-centric plugins. It is available in many forms, including the widely used Fiji distribution. We refer to this entire ImageJ codebase and community as the ImageJ ecosystem. Here we review the core features of this ecosystem and highlight how ImageJ has responded to imaging technology advancements with new plugins and tools in recent years. These plugins and tools have been developed to address user needs in several areas such as visualization, segmentation, and tracking of biological entities in large, complex datasets. Moreover, new capabilities for deep learning are being added to ImageJ, reflecting a shift in the bioimage analysis community towards exploiting artificial intelligence. These new tools have been facilitated by profound architectural changes to the ImageJ core brought about by the ImageJ2 project. Therefore, we also discuss the contributions of ImageJ2 to enhancing multidimensional image processing and interoperability in the ImageJ ecosystem.

Supported single-metal atom catalysts (SACs) are constituted of isolated active metal centers, which are heterogenized on inert supports such as graphene, porous carbon, and metal oxides. Their thermal stability, electronic properties, and catalytic activities can be controlled via interactions between the single-metal atom center and neighboring heteroatoms such as nitrogen, oxygen, and sulfur. Due to the atomic dispersion of the active catalytic centers, the amount of metal required for catalysis can be decreased, thus offering new possibilities to control the selectivity of a given transformation as well as to improve catalyst turnover frequencies and turnover numbers. This review aims to comprehensively summarize the synthesis of Fe-SACs with a focus on anchoring single atoms (SA) on carbon/graphene supports. The characterization of these advanced materials using various spectroscopic techniques and their applications in diverse research areas are described. When applicable, mechanistic investigations conducted to understand the specific behavior of Fe-SACs-based catalysts are highlighted, including the use of theoretical models.

We present LABKIT, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. LABKIT is specifically designed to work efficiently on big image data and enables users of consumer laptops to conveniently work with multiple-terabyte images. This efficiency is achieved by using ImgLib2 and BigDataViewer as well as a memory efficient and fast implementation of the random forest based pixel classification algorithm as the foundation of our software. Optionally we harness the power of graphics processing units (GPU) to gain additional runtime performance. LABKIT is easy to install on virtually all laptops and workstations. Additionally, LABKIT is compatible with high performance computing (HPC) clusters for distributed processing of big image data. The ability to use pixel classifiers trained in LABKIT via the ImageJ macro language enables our users to integrate this functionality as a processing step in automated image processing workflows. Finally, LABKIT comes with rich online resources such as tutorials and examples that will help users to familiarize themselves with available features and how to best use LABKIT in a number of practical real-world use-cases.

Chronic Kidney Disease is one of the most critical illness nowadays and proper diagnosis is required as soon as possible. Machine learning technique has become reliable for medical treatment. With the help of a machine learning classifier algorithms, the doctor can detect the disease on time. For this perspective, Chronic Kidney Disease prediction has been discussed in this article. Chronic Kidney Disease dataset has been taken from the UCI repository. Seven classifier algorithms have been applied in this research such as artificial neural network, C5.0, Chi-square Automatic interaction detector, logistic regression, linear support vector machine with penalty L1 & with penalty L2 and random tree. The important feature selection technique was also applied to the dataset. For each classifier, the results have been computed based on (i) full features, (ii) correlation-based feature selection, (iii) Wrapper method feature selection, (iv) Least absolute shrinkage and selection operator regression, (v) synthetic minority over-sampling technique with least absolute shrinkage and selection operator regression selected features, (vi) synthetic minority over-sampling technique with full features. From the results, it is marked that LSVM with penalty L2 is giving the highest accuracy of 98.86% in synthetic minority over-sampling technique with full features. Along with accuracy, precision, recall, F-measure, area under the curve and GINI coefficient have been computed and compared results of various algorithms have been shown in the graph. Least absolute shrinkage and selection operator regression selected features with synthetic minority over-sampling technique gave the best after synthetic minority over-sampling technique with full features. In the synthetic minority over-sampling technique with least absolute shrinkage and selection operator selected features, again linear support vector machine gave the highest accuracy of 98.46%. Along with machine learning models one deep neural network has been applied on the same dataset and it has been noted that deep neural network achieved the highest accuracy of 99.6%.

Abstract The concept of Galois connection between power sets is generalized from the point of view of fuzzy logic. Studied is the case where the structure of truth values forms a complete residuated lattice. It is proved that fuzzy Galois connections are in one‐to‐one correspondence with binary fuzzy relations. A representation of fuzzy Galois connections by (classical) Galois connections is provided.

We demonstrate, to our knowledge, the first bright circularly polarized high-harmonic beams in the soft X-ray region of the electromagnetic spectrum, and use them to implement X-ray magnetic circular dichroism measurements in a tabletop-scale setup. Using counterrotating circularly polarized laser fields at 1.3 and 0.79 µm, we generate circularly polarized harmonics with photon energies exceeding 160 eV. The harmonic spectra emerge as a sequence of closely spaced pairs of left and right circularly polarized peaks, with energies determined by conservation of energy and spin angular momentum. We explain the single-atom and macroscopic physics by identifying the dominant electron quantum trajectories and optimal phase-matching conditions. The first advanced phase-matched propagation simulations for circularly polarized harmonics reveal the influence of the finite phase-matching temporal window on the spectrum, as well as the unique polarization-shaped attosecond pulse train. Finally, we use, to our knowledge, the first tabletop X-ray magnetic circular dichroism measurements at the N4,5 absorption edges of Gd to validate the high degree of circularity, brightness, and stability of this light source. These results demonstrate the feasibility of manipulating the polarization, spectrum, and temporal shape of high harmonics in the soft X-ray region by manipulating the driving laser waveform.

Plagiarism can be of many different natures, ranging from copying texts to adopting ideas, without giving credit to its originator. This paper presents a new taxonomy of plagiarism that highlights differences between literal plagiarism and intelligent plagiarism, from the plagiarist's behavioral point of view. The taxonomy supports deep understanding of different linguistic patterns in committing plagiarism, for example, changing texts into semantically equivalent but with different words and organization, shortening texts with concept generalization and specification, and adopting ideas and important contributions of others. Different textual features that characterize different plagiarism types are discussed. Systematic frameworks and methods of monolingual, extrinsic, intrinsic, and cross-lingual plagiarism detection are surveyed and correlated with plagiarism types, which are listed in the taxonomy. We conduct extensive study of state-of-the-art techniques for plagiarism detection, including character n-gram-based (CNG), vector-based (VEC), syntax-based (SYN), semantic-based (SEM), fuzzy-based (FUZZY), structural-based (STRUC), stylometric-based (STYLE), and cross-lingual techniques (CROSS). Our study corroborates that existing systems for plagiarism detection focus on copying text but fail to detect intelligent plagiarism when ideas are presented in different words.