University of West Bohemia in Pilsen

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Abstract: SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

In 1997, the International Association for the Properties of Water and Steam (IAPWS) adopted a new formulation for the thermodynamic properties of water and steam for industrial use. This new formulation, called IAPWS Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam (IAPWS-IF97), replaces the previous industrial formulation, IFC-67, that had formed the basis for power-plant calculations and other applications in energy engineering since the late 1960’s. IAPWS-IF97 improves significantly both the accuracy and the speed of the calculation of the thermodynamic properties compared with IFC-67. The differences between IAPWS-IF97 and IFC-67 will require many users, particularly boiler and turbine manufacturers, to modify design and application codes. This paper summarizes the need and the requirements for such a new industrial formulation and gives the entire numerical information about the individual equations of IAPWS-IF97. Moreover, the scientific basis for the development of the equations is summarized and the achieved quality of IAPWS-IF97 is presented regarding the three criterions accuracy, consistency along region boundaries, and computation speed. For comparison, corresponding results for the previous standard IFC-67 are also presented. [S0742-4795(00)02201-8]

Abstract Efficient photo‐ and piezoelectric‐induced molecular oxygen activation are both achieved by macroscopic polarization enhancement on a noncentrosymmetric piezoelectric semiconductor BiOIO 3 . The replacement of V 5+ ions for I 5+ in IO 3 polyhedra gives rise to strengthened macroscopic polarization of BiOIO 3 , which facilitates the charge separation in the photocatalytic and piezoelectric catalytic process, and renders largely promoted photo‐ and piezoelectric induced reactive oxygen species (ROS) evolution, such as superoxide radicals ( . O 2 − ) and hydroxyl radicals ( . OH). This work advances piezoelectricity as a new route to efficient ROS generation, and also discloses macroscopic polarization engineering on improvement of multi‐responsive catalysis.

Redox-flow batteries, based on their particular ability to decouple power and energy, stand as prime candidates for cost-effective stationary storage, particularly in the case of long discharges and long storage times. Integration of renewables and subsequent need for energy storage is promoting effort on the development of mature and emerging redox-flow technologies. This review aims at providing a critical analysis of redox-flow technologies that can potentially fulfill cost requirements and enable large scale storage, mainly aqueous based systems. A comprehensive overview of the status of those technologies, including advantages and weaknesses, is presented. Compiled data on the market permeability, performance and cost should serve, together with the perspective included, to understand the different strategies to reach the successful implementation, from component development to innovative designs.

This paper investigates whether entrepreneurial education (EE) contributes to the entrepreneurial intentions (EI) of university students in the Visegrád countries (Czech Republic, Hungary, Poland and Slovakia). The results show several differences with regard to the impact of education and entrepreneurial self-efficacy (ESE) on entrepreneurial intentions across the four nations. The direct impact of entrepreneurship education was positive and significant in only one country, Poland, the only of the four countries to have introduced entrepreneurship education at high-school level. Additionally, an indirect influence of EE on EI was uncovered. Using a multi-construct approach to ESE, the research proves that ESEs related to searching, planning and marshalling activities mediate the impact of entrepreneurial education on intentions, although these effects differ across the studied countries. Lastly, a gender comparison indicates that although women generally have lower entrepreneurial intentions and display lower levels of ESE they benefit more than men do from entrepreneurship education.

The vision of Industry 4.0 will be bring not only new approaches but also the methodologies and technologies, which will have to be introduced into companies. The transition to such a sophisticated production will not be possible immediately. The main reasons are high financial costs and the lack of qualified employees. This article deals with identification of job roles in the companies.

Abstract Lifted Kramers spin degeneracy (LKSD) has been among the central topics of condensed-matter physics since the dawn of the band theory of solids 1,2 . It underpins established practical applications as well as current frontier research, ranging from magnetic-memory technology 3–7 to topological quantum matter 8–14 . Traditionally, LKSD has been considered to originate from two possible internal symmetry-breaking mechanisms. The first refers to time-reversal symmetry breaking by magnetization of ferromagnets and tends to be strong because of the non-relativistic exchange origin 15 . The second applies to crystals with broken inversion symmetry and tends to be comparatively weaker, as it originates from the relativistic spin–orbit coupling (SOC) 16–19 . A recent theory work based on spin-symmetry classification has identified an unconventional magnetic phase, dubbed altermagnetic 20,21 , that allows for LKSD without net magnetization and inversion-symmetry breaking. Here we provide the confirmation using photoemission spectroscopy and ab initio calculations. We identify two distinct unconventional mechanisms of LKSD generated by the altermagnetic phase of centrosymmetric MnTe with vanishing net magnetization 20–23 . Our observation of the altermagnetic LKSD can have broad consequences in magnetism. It motivates exploration and exploitation of the unconventional nature of this magnetic phase in an extended family of materials, ranging from insulators and semiconductors to metals and superconductors 20,21 , that have been either identified recently or perceived for many decades as conventional antiferromagnets 21,24,25 .

COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19's spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long/Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications.

The International Association for the Properties of Water and Steam (IAPWS) encouraged an extensive research effort to update the IAPS Formulation 1985 for the Viscosity of Ordinary Water Substance, leading to the adoption of a Release on the IAPWS Formulation 2008 for the Viscosity of Ordinary Water Substance. This manuscript describes the development and evaluation of the 2008 formulation, which provides a correlating equation for the viscosity of water for fluid states up to 1173K and 1000MPa with uncertainties from less than 1% to 7% depending on the state point.

Motivation: Studying the transport paths of ligands, solvents, or ions in transmembrane proteins and proteins with buried binding sites is fundamental to the understanding of their biological function. A detailed analysis of the structural features influencing the transport paths is also important for engineering proteins for biomedical and biotechnological applications. Results: CAVER Analyst 2.0 is a software tool for quantitative analysis and real-time visualization of tunnels and channels in static and dynamic structures. This version provides the users with many new functions, including advanced techniques for intuitive visual inspection of the spatiotemporal behavior of tunnels and channels. Novel integrated algorithms allow an efficient analysis and data reduction in large protein structures and molecular dynamic simulations. Availability and implementation: CAVER Analyst 2.0 is a multi-platform standalone Java-based application. Binaries and documentation are freely available at www.caver.cz. Supplementary information: Supplementary data are available at Bioinformatics online.

This paper empirically examines interdependencies between BitCoin and altcoin markets in the short- and long-run. We apply time-series analytical mechanisms to daily data of 17 virtual currencies (BitCoin + 16 alternative virtual currencies) and two Altcoin price indices for the period 2013-2016. Our empirical findings confirm that indeed BitCoin and Altcoin markets are interdependent. The BitCoin-Altcoin price relationship is significantly stronger in the short-run than in the long-run. We cannot fully confirm the hypothesis that the BitCoin price relationship is stronger with those Altcoins that are more similar in their price formation mechanism to BitCoin. In the long-run, macro-financial indicators determine the altcoin price formation to a greater degree than BitCoin does. The virtual currency supply is exogenous and therefore plays only a limited role in the price formation.

Graphene quantum dots (GQDs) are an attractive nanomaterial consisting of a monolayer or a few layers of graphene having excellent and unique properties. GQDs are endowed with the properties of both carbon dots (CDs) and graphene. This review addresses applications of GQD based materials in sensing, bioimaging and energy storage. In the first part of the review, different approaches of GQD synthesis such as top-down and bottom-up synthesis methods have been discussed. The prime focus of this review is on green synthesis methods that have also been applied to the synthesis of GQDs. The GQDs have been discussed thoroughly for all the aspects along with their potential applications in sensors, biomedicine, and energy storage systems. In particular, emphasis is given to popular applications such as electrochemical and photoluminescence (PL) sensors, electrochemiluminescence (ECL) sensors, humidity and gas sensors, bioimaging, lithium-ion (Li-ion) batteries, supercapacitors and dye-sensitized solar cells. Finally, the challenges and the future perspectives of GQDs in the aforementioned application fields have been discussed.

Using the fibrering method, we prove the existence of multiple positive solutions of quasilinear problems of second order. The main part of our differential operator is p -Laplacian and we consider solutions both in the bounded domain Ω⊂ℝ N and in the whole of ℝ N . We also prove nonexistence results.

Altermagnets are an emerging elementary class of collinear magnets. Unlike ferromagnets, their distinct crystal symmetries inhibit magnetization while, unlike antiferromagnets, they promote strong spin polarization in the band structure. The corresponding unconventional mechanism of time-reversal symmetry breaking without magnetization in the electronic spectra has been regarded as a primary signature of altermagnetism but has not been experimentally visualized to date. We directly observe strong time-reversal symmetry breaking in the band structure of altermagnetic RuO 2 by detecting magnetic circular dichroism in angle-resolved photoemission spectra. Our experimental results, supported by ab initio calculations, establish the microscopic electronic structure basis for a family of interesting phenomena and functionalities in fields ranging from topological matter to spintronics, which are based on the unconventional time-reversal symmetry breaking in altermagnets.

Selective Laser Melting (SLM) is a method of additive manufacturing (AM), which builds metal parts in a layer by layer procedure based on a CAD template. The cross section of the CAD part is melted into the respective layer. The melting of metal powder by an energy beam and successful mastering of the whole manufacturing procedure requires complex management, because multitudes of variables enter the SLM process. These variables are laser power, scan speed, thickness of layer, overlap rate and building direction. This article summarizes their impact on tensile properties and structure of printing materials. An important finding of the investigation follows. The SLM built steel samples usually have better tensile properties than those conventionally manufactured providing the additive manufacturing is properly managed.

Abstract In recent years, biopolymers are getting wide attention with the perspective of developing high‐performance biocomposites with low environmental impact owing to their unique and useful features such as abundant availability, renewability, eco‐friendliness and lightweight. Biopolymer composites are expected to replace many conventional materials in optical, biological, and engineering applications as the investment and research on these materials increase substantially. The desired properties of biopolymer composites can be achieved by blending an appropriate biopolymer with suitable additives, which pave the way for polymer‐filler interaction. A variety of parameters such as chemical composition, degradation kinetics and mechanical properties of biopolymer composites can be tailored according to the application needs. The interfacial interactions between the biopolymer and the nanofiller have a significant effect on the mechanical properties of biopolymer composites. The present review is focused on the recent advances in the mechanical properties of various biopolymer composites. In the first part of this review, the unfamiliar mechanical characterization techniques such as fatigue test, nanoindentation and nondestructive testing of biopolymer composites have been discussed. In the later part, the various popular processing techniques of biocomposite fabrication have been discussed. In addition, in the conclusion section, few challenges associated with the processing and mechanical performance of biopolymer composites have been described.

Industry 4.0 is a comparatively new method of managing production processes. In the area of risk management, as a result of new approaches, modified frameworks, more complex IT infrastructure and so on, new types of risks may occur. In many cases, the implementation of Industry 4.0 has shown that the connections between humans, systems and objects have become a more complex, dynamic and real-time optimized network. On the other hand, there is the fact of data volume and availability enhancement in real time which causes new requirements of the infrastructure, management, technologies and so on. The aim of this paper is to conduct research on Industry 4.0 related to key aspects and presentation of a design of framework to implement risk management for the Industry 4.0 concept.