Showing papers by "Wrocław University of Technology published in 2020"

A MHz-repetition-rate hard X-ray free-electron laser driven by a superconducting linear accelerator

Abstract: The European XFEL is a hard X-ray free-electron laser (FEL) based on a high-electron-energy superconducting linear accelerator. The superconducting technology allows for the acceleration of many electron bunches within one radio-frequency pulse of the accelerating voltage and, in turn, for the generation of a large number of hard X-ray pulses. We report on the performance of the European XFEL accelerator with up to 5,000 electron bunches per second and demonstrating a full energy of 17.5 GeV. Feedback mechanisms enable stabilization of the electron beam delivery at the FEL undulator in space and time. The measured FEL gain curve at 9.3 keV is in good agreement with predictions for saturated FEL radiation. Hard X-ray lasing was achieved between 7 keV and 14 keV with pulse energies of up to 2.0 mJ. Using the high repetition rate, an FEL beam with 6 W average power was created.

Activity profiling and crystal structures of inhibitor-bound SARS-CoV-2 papain-like protease: A framework for anti-COVID-19 drug design.

Abstract: Viral papain-like cysteine protease (PLpro, NSP3) is essential for SARS-CoV-2 replication and represents a promising target for the development of antiviral drugs. Here, we used a combinatorial substrate library and performed comprehensive activity profiling of SARS-CoV-2 PLpro. On the scaffold of the best hits from positional scanning, we designed optimal fluorogenic substrates and irreversible inhibitors with a high degree of selectivity for SARS PLpro. We determined crystal structures of two of these inhibitors in complex with SARS-CoV-2 PLpro that reveals their inhibitory mechanisms and provides a molecular basis for the observed substrate specificity profiles. Last, we demonstrate that SARS-CoV-2 PLpro harbors deISGylating activity similar to SARSCoV-1 PLpro but its ability to hydrolyze K48-linked Ub chains is diminished, which our sequence and structure analysis provides a basis for. Together, this work has revealed the molecular rules governing PLpro substrate specificity and provides a framework for development of inhibitors with potential therapeutic value or drug repurposing.

Energy Forecasting: A Review and Outlook

Abstract: Forecasting has been an essential part of the power and energy industry. Researchers and practitioners have contributed thousands of papers on forecasting electricity demand and prices, and renewable generation (e.g., wind and solar power). This article offers a brief review of influential energy forecasting papers; summarizes research trends; discusses importance of reproducible research and points out six valuable open data sources; makes recommendations about publishing high-quality research papers; and offers an outlook into the future of energy forecasting.

Evolutionary algorithms and their applications to engineering problems

Abstract: The main focus of this paper is on the family of evolutionary algorithms and their real-life applications. We present the following algorithms: genetic algorithms, genetic programming, differential evolution, evolution strategies, and evolutionary programming. Each technique is presented in the pseudo-code form, which can be used for its easy implementation in any programming language. We present the main properties of each algorithm described in this paper. We also show many state-of-the-art practical applications and modifications of the early evolutionary methods. The open research issues are indicated for the family of evolutionary algorithms.

COVID-19: animals, veterinary and zoonotic links.

Abstract: Coronavirus disease 2019 (COVID-19), has spread over 210 countries and territories beyond China shortly. On February 29, 2020, the World Health Organization (WHO) denoted it in a high-risk category, and on March 11, 2020, this virus was designated pandemic, after its declaration being a Public Health International Emergency on January 30, 2020. World over high efforts are being made to counter and contain this virus. The COVID-19 outbreak once again proves the potential of the animal-human interface to act as the primary source of emerging zoonotic diseases. Even though the circumstantial evidence suggests the possibility of an initial zoonotic emergence, it is too early to confirm the role of intermediate hosts such as snakes, pangolins, turtles, and other wild animals in the origin of SARS-CoV-2, in addition to bats, the natural hosts of multiple coronaviruses such as SARS-CoV and MERS-CoV. The lessons learned from past episodes of MERS-CoV and SARS-CoV are being exploited to retort this virus. Best efforts are being taken up by worldwide nations to implement effective diagnosis, strict vigilance, heightened surveillance, and monitoring, along with adopting appropriate preventive and control strategies. Identifying the possible zoonotic emergence and the exact mechanism responsible for its initial transmission will help us to design and implement appropriate preventive barriers against the further transmission of SARS-CoV-2. This review discusses in brief about the COVID-19/SARS-CoV-2 with a particular focus on the role of animals, the veterinary and associated zoonotic links along with prevention and control strategies based on One-health approaches.

Reciprocal skin effect and its realization in a topolectrical circuit

Abstract: A system is non-Hermitian when it exchanges energy with its environment and nonreciprocal when it behaves differently upon the interchange of input and response. Within the field of metamaterial research on synthetic topological matter, the skin effect describes the conspiracy of non-Hermiticity and nonreciprocity to yield extensive anomalous localization of all eigenmodes in a (quasi) one-dimensional geometry. Here, we introduce the reciprocal skin effect, which occurs in non-Hermitian but reciprocal systems in two or more dimensions: Eigenmodes with opposite longitudinal momentum exhibit opposite transverse anomalous localization. We experimentally demonstrate the reciprocal skin effect in a passive RLC circuit, suggesting convenient alternative implementations in optical, acoustic, mechanical, and related platforms. Skin mode localization brings forth potential applications in directional and polarization detectors for electromagnetic waves.

Vibrational Spectroscopic Map, Vibrational Spectroscopy, and Intermolecular Interaction.

Abstract: Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations In addition, a brief introduction to a newly created repository Web site (http://frequencymaporg) for vibrational spectroscopic maps is presented We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future

Methylhydrazinium Lead Bromide: Noncentrosymmetric Three-Dimensional Perovskite with Exceptionally Large Framework Distortion and Green Photoluminescence

Abstract: Three-dimensional (3D) lead halide perovskites have emerged as a promising class of coordination polymers for solar cells, photodetectors, and light-emitting devices. These compounds thus far compr...

Renewable hydrogen implementations for combined energy storage, transportation and stationary applications

Abstract: The purpose of this paper is to discuss the potential of hydrogen obtained from renewable sources for energy generation and storage systems. The first part of analysis will address such issues as various methods of green hydrogen production, storage and transportation. The review of hydrogen generation methods will be followed by the critical analysis and the selection of production method. This selection is justified by the results of the comparative research on alternative green hydrogen generation technologies with focus on their environmental impacts and costs. The comparative analysis includes the biomass-based methods as well as water splitting and photo-catalysis methods while water electrolysis is taken as a benchmark. Hydrogen storage and transportation issues will be further discussed in purpose to form the list of recommended solutions. In the second part of the paper the technology readiness and technical feasibility for joint hydrogen applications will be analysed. This will include the energy storage and production systems based on renewable hydrogen in combination with hydrogen usage in mobility systems as well as the stationary applications in buildings such as combined heat and power (CHP) plants or fuel cell electric generators. Based on the analysis of the selected case studies the author will discuss the role of hydrogen for the carbon emission reduction with the stress on the real value of carbon footprint of hydrogen depending on the gas source, storage, transportation and applications.

Monoterpenes and Their Derivatives-Recent Development in Biological and Medical Applications.

Abstract: Monoterpenes, comprising hydrocarbons, are the largest class of plant secondary metabolites and are commonly found in essential oils. Monoterpenes and their derivatives are key ingredients in the design and production of new biologically active compounds. This review focuses on selected aliphatic, monocyclic, and bicyclic monoterpenes like geraniol, thymol, myrtenal, pinene, camphor, borneol, and their modified structures. The compounds in question play a pivotal role in biological and medical applications. The review also discusses anti-inflammatory, antimicrobial, anticonvulsant, analgesic, antiviral, anticancer, antituberculosis, and antioxidant biological activities exhibited by monoterpenes and their derivatives. Particular attention is paid to the link between biological activity and the effect of structural modification of monoterpenes and monoterpenoids, as well as the introduction of various functionalized moieties into the molecules in question.

Modern Stereoselective Synthesis of Chiral Sulfinyl Compounds.

Abstract: Chiral sulfinyl compounds, sulfoxides, sulfoximines, sulfinamides, and other derivatives, play an important role in asymmetric synthesis as versatile auxiliaries, ligands, and catalysts. They are also recognized as pharmacophores found in already marketed and well-sold drugs (e.g., esomeprazole) and used in drug design. This review is devoted to the modern methods of preparation of sulfinyl derivatives in enantiopure or enantiomerically enriched form. Selected new approaches leading to racemic products for which the asymmetric variant can be developed in the future are mentioned as well.

TERT—Regulation and Roles in Cancer Formation

Abstract: Telomerase reverse transcriptase (TERT) is a catalytic subunit of telomerase. Telomerase complex plays a key role in cancer formation by telomere dependent or independent mechanisms. Telomere maintenance mechanisms include complex TERT changes such as gene amplifications, TERT structural variants, TERT promoter germline and somatic mutations, TERT epigenetic changes, and alternative lengthening of telomere. All of them are cancer specific at tissue histotype and at single cell level. TERT expression is regulated in tumors via multiple genetic and epigenetic alterations which affect telomerase activity. Telomerase activity via TERT expression has an impact on telomere length and can be a useful marker in diagnosis and prognosis of various cancers and a new therapy approach. In this review we want to highlight the main roles of TERT in different mechanisms of cancer development and regulation.

Three-Dimensional Perovskite Methylhydrazinium Lead Chloride with Two Polar Phases and Unusual Second-Harmonic Generation Bistability above Room Temperature

Abstract: Formation of noncentrosymmetric three-dimensional (3D) lead halide perovskites has been a widely sought after goal because the polar structure opens up new vistas to properties of these materials, ...

Activity profiling and structures of inhibitor-bound SARS-CoV-2-PLpro protease provides a framework for anti-COVID-19 drug design.

Abstract: In December 2019, the first cases of a novel coronavirus infection causing COVID-19 were diagnosed in Wuhan, China. Viral Papain-Like cysteine protease (PLpro, NSP3) is essential for SARS-CoV-2 replication and represents a promising target for the development of antiviral drugs. Here, we used a combinatorial substrate library containing natural and a wide variety of nonproteinogenic amino acids and performed comprehensive activity profiling of SARS-CoV-2-PLpro. On the scaffold of best hits from positional scanning we designed optimal fluorogenic substrates and irreversible inhibitors with a high degree of selectivity for SARS PLpro variants versus other proteases. We determined crystal structures of two of these inhibitors (VIR250 and VIR251) in complex with SARS-CoV-2-PLpro which reveals their inhibitory mechanisms and provides a structural basis for the observed substrate specificity profiles. Lastly, we demonstrate that SARS-CoV-2-PLpro harbors deISGylating activities similar to SARS-CoV-1-PLpro but its ability to hydrolyze K48-linked Ub chains is diminished, which our sequence and structure analysis provides a basis for. Altogether this work has revealed the molecular rules governing PLpro substrate specificity and provides a framework for development of inhibitors with potential therapeutic value or drug repositioning.

Laser powder bed fusion of AA7075 alloy: Influence of process parameters on porosity and hot cracking

Abstract: Laser powder bed fusion (LPBF) is an attractive technology of manufacturing high-strength aluminium alloy parts for the aircraft and automobile industries, limited by poor processability of these alloys. This work was aimed at finding the process window for the LPBF manufacturing of defect-free components of AA7075 alloy. Optimization of the parameters was performed at each stage of the multi-stage research, i.e. for single tracks, thin walls and volumetric specimens. At each stage, the relation between LPBF parameters and defect formation with a focus on hot cracking was investigated and discussed. Due to the optimization of process parameters, the density of volumetric specimens above 99 % was reached and vaporization losses of the alloying elements were significantly reduced, but solidification cracks could not be eliminated. It was found that solidification cracks were formed by the liquid film rupture mode, mainly along columnar grain boundaries. The EDS microanalysis showed intergranular microsegregation, not only of the main alloying elements (Zn, Mg, Cu) but also of minor elements such as Si. Silicon may play a significant role in increasing susceptibility to cracking by increasing the stability of the liquid film. Reduction in the silicon impurity content in the AA7075 powder gives a chance to reduce susceptibility to cracking with no change of the alloy specification.

Improving the Performance of Sentiment Analysis of Tweets Containing Fuzzy Sentiment Using the Feature Ensemble Model

Abstract: The increase in the volume of user-generated content on Twitter has resulted in tweet sentiment analysis becoming an essential tool for the extraction of information about Twitter users' emotional state. Consequently, there has been a rapid growth of tweet sentiment analysis in the area of natural language processing. Tweet sentiment analysis is increasingly applied in many areas, such as decision support systems and recommendation systems. Therefore, improving the accuracy of tweet sentiment analysis has become practical and an area of interest for many researchers. Many approaches have tried to improve the performance of tweet sentiment analysis methods by using the feature ensemble method. However, most of the previous methods attempted to model the syntactic information of words without considering the sentiment context of these words. Besides, the positioning of words and the impact of phrases containing fuzzy sentiment have not been mentioned in many studies. This study proposed a new approach based on a feature ensemble model related to tweets containing fuzzy sentiment by taking into account elements such as lexical, word-type, semantic, position, and sentiment polarity of words. The proposed method has been experimented on with real data, and the result proves effective in improving the performance of tweet sentiment analysis in terms of the $F_{1}$ score.

Exciton g factors of van der Waals heterostructures from first-principles calculations

Abstract: External fields are a powerful tool to probe optical excitations in a material. The linear energy shift of an excitation in a magnetic field is quantified by its effective g factor. Here we show how exciton g factors and their sign can be determined by converged first-principles calculations. We apply the method to monolayer excitons in semiconducting transition metal dichalcogenides and to interlayer excitons in MoSe2/WSe2 heterobilayers and obtain good agreement with recent experimental data. The precision of our method allows us to assign measured g factors of optical peaks to specific transitions in the band structure and also to specific regions of the samples. This revealed the nature of various, previously measured interlayer exciton peaks. We further show that, due to specific optical selection rules, g factors in van der Waals heterostructures are strongly spin- and stacking-dependent. The calculation of orbital angular momenta requires the summation over hundreds of bands, indicating that for the considered two-dimensional materials the basis set size is a critical numerical issue. The presented approach can potentially be applied to a wide variety of semiconductors.

Non-Isolated High-Gain Triple Port DC–DC Buck-Boost Converter With Positive Output Voltage for Photovoltaic Applications

Abstract: The solar PV based power generation systems are growing faster due to the depletion of fossil fuels and environmental concerns Combining PV panels and energy buffers such as battery through multi-port converter is one of the viable solutions to deal with the intermittency of PV power The goal of this paper is to design and analyze the proposed triple port DC-DC buck-boost converter for high step-up/step-down applications It has two unidirectional ports (port-1 and port-3) and one bi-directional port (port-2) for harnessing photovoltaic energy and charging the battery At port-1, the combined structure of buck and buck-boost converter is used with a particular arrangement of switches and inductors The step-up/step-down voltage conversion ratio is higher than the conventional buck-boost converter, and the polarity of the output voltage is maintained positive The battery is added at the bi-directional port, for the storage of energy through the bi-directional boost converter The switches operate synchronously for most of the modes making the control strategy simple The characteristics and modes of operation along with a switching strategy, are elaborated Experimental results are presented which validate the agreement with the developed theoretical expectation

Selective prebiotic formation of RNA pyrimidine and DNA purine nucleosides

Abstract: The nature of the first genetic polymer is the subject of major debate1. Although the 'RNA world' theory suggests that RNA was the first replicable information carrier of the prebiotic era-that is, prior to the dawn of life2,3-other evidence implies that life may have started with a heterogeneous nucleic acid genetic system that included both RNA and DNA4. Such a theory streamlines the eventual 'genetic takeover' of homogeneous DNA from RNA as the principal information-storage molecule, but requires a selective abiotic synthesis of both RNA and DNA building blocks in the same local primordial geochemical scenario. Here we demonstrate a high-yielding, completely stereo-, regio- and furanosyl-selective prebiotic synthesis of the purine deoxyribonucleosides: deoxyadenosine and deoxyinosine. Our synthesis uses key intermediates in the prebiotic synthesis of the canonical pyrimidine ribonucleosides (cytidine and uridine), and we show that, once generated, the pyrimidines persist throughout the synthesis of the purine deoxyribonucleosides, leading to a mixture of deoxyadenosine, deoxyinosine, cytidine and uridine. These results support the notion that purine deoxyribonucleosides and pyrimidine ribonucleosides may have coexisted before the emergence of life5.

Tailoring the separation properties of flexible metal-organic frameworks using mechanical pressure

Abstract: Metal-organic frameworks are widely considered for the separation of chemical mixtures due to their adjustable physical and chemical properties. However, while much effort is currently devoted to developing new adsorbents for a given separation, an ideal scenario would involve a single adsorbent for multiple separations. Porous materials exhibiting framework flexibility offer unique opportunities to tune these properties since the pore size and shape can be controlled by the application of external stimuli. Here, we establish a proof-of-concept for the molecular sieving separation of species with similar sizes (CO2/N2 and CO2/CH4), via precise mechanical control of the pore size aperture in a flexible metal-organic framework. Besides its infinite selectivity for the considered gas mixtures, this material shows excellent regeneration capability when releasing the external mechanical constraint. This strategy, combining an external stimulus applied to a structurally compliant adsorbent, offers a promising avenue for addressing some of the most challenging gas separations. Separation of gasses with similar physical and chemical properties can be energy demanding, and adsorption-based technologies may provide alternatives with lower energy consumption. Here, the authors show mechanical control of pore size aperture in flexible metal-organic frameworks for separation of gasses.

Astaxanthin and other Nutrients from Haematococcus pluvialis-Multifunctional Applications.

Abstract: Bioactive compounds of natural origin are gaining increasing popularity. High biological activity and bioavailability, beneficial effects on health and safety of use are some of their most desirable features. Low production and processing costs render them even more attractive. Microorganisms have been used in the food, medicinal, cosmetic and energy industries for years. Among them, microalgae have proved to be an invaluable source of beneficial compounds. Haematococcus pluvialis is known as the richest source of natural carotenoid called astaxanthin. In this paper, we focus on the cultivation methods of this green microalga, its chemical composition, extraction of astaxanthin and analysis of its antioxidant, anti-inflammatory, anti–diabetic and anticancer activities. H. pluvialis, as well as astaxanthin can be used not only for the treatment of human and animal diseases, but also as a valuable component of diet and feed.

Radial-Based Oversampling for Multiclass Imbalanced Data Classification

Abstract: Learning from imbalanced data is among the most popular topics in the contemporary machine learning. However, the vast majority of attention in this field is given to binary problems, while their much more difficult multiclass counterparts are relatively unexplored. Handling data sets with multiple skewed classes poses various challenges and calls for a better understanding of the relationship among classes. In this paper, we propose multiclass radial-based oversampling (MC-RBO), a novel data-sampling algorithm dedicated to multiclass problems. The main novelty of our method lies in using potential functions for generating artificial instances. We take into account information coming from all of the classes, contrary to existing multiclass oversampling approaches that use only minority class characteristics. The process of artificial instance generation is guided by exploring areas where the value of the mutual class distribution is very small. This way, we ensure a smart oversampling procedure that can cope with difficult data distributions and alleviate the shortcomings of existing methods. The usefulness of the MC-RBO algorithm is evaluated on the basis of extensive experimental study and backed-up with a thorough statistical analysis. Obtained results show that by taking into account information coming from all of the classes and conducting a smart oversampling, we can significantly improve the process of learning from multiclass imbalanced data.

A transition from conventional irrigation to fertigation with reclaimed wastewater: Prospects and challenges

Abstract: The aim of this review was to discuss the transition from traditional irrigation to fertigation using reclaimed wastewater in countries with moderate climate. In most European countries there are no regulations on waste water reuse and on the other hand there are countries where regulations are very strict. An important aspect is to standardize the restrictions, which would minimize uncontrolled use of wastewater for fertigation. Wastewater is a source of plant nutrients and organic matter, but can be contaminated with chemicals and pathogens, which in turn can lead to secondary environmental pollution. The reuse of recovered wastewater may require modification of the wastewater treatment process line or construction of stabilization tanks at farms. In both cases, it is necessary to set up initial installations in real systems in order to develop principles for irrigation with reclaimed wastewater for soil and temperate climate conditions. The additional treatment steps required are also associated with large investments, but could reduce fertilization costs and, more importantly, improve the environmental situation. The current scale of fertilizer application does not allow conventional fertilization to fulfill global demand. The introduction of such a solution is a step towards the practical application of circular economy and sustainable crop production. The paper discusses a challenges related with implementation of transition from conventional irrigation to fertigation with reclaimed wastewater in moderate climate countries. A special focus to providing fertilizer nutrients in terms of required doses was undertaken.

Activity profiling of SARS-CoV-2-PLpro protease provides structural framework for anti-COVID-19 drug design

Abstract: In December 2019, the first cases of a novel coronavirus infection causing COVID-19 were diagnosed in Wuhan, China. Viral Papain-Like cysteine protease (PLpro, NSP3) is essential for SARS-CoV-2 replication and represents a promising target for the development of antiviral drugs which would be facilitated by an understanding of its substrate specificity. Here, we used a combinatorial substrate library containing natural and a wide variety of nonproteinogenic amino acids and performed comprehensive activity profiling of SARS-CoV-2-PLpro. We found that the P2 site of SARS-CoV-2-PLpro is highly specific for Gly, the P3 site exhibits a high degree of promiscuity, and the P4 site exhibits a preference for amino acids with hydrophobic side chains. We also demonstrate that SARS-CoV-2-PLpro harbors deubiquitinating activity. Both the substrate binding profile and deubiquitinating activity are shared with the highly related SARS-CoV-PLpro which harbors near identical S4-S2 binding pockets. On the scaffold of best hits from positional scanning we have designed optimal fluorogenic substrates and irreversible inhibitors with a high degree of selectivity for SARS PLpro variants versus other proteases. Altogether this work has revealed the molecular rules governing PLpro substrate specificity and provides a framework for development of inhibitors with potential therapeutic value or drug repositioning.