This work presents the first evidence that dissolved globular proteins change the arrangement of hydrogen bonds in water, with different proteins showing quantitatively different effects. Using ATR-FTIR (Attenuated Total Reflection – Fourier Transform Infrared) spectroscopic analysis of OH-stretch bands, we obtain quantitative estimates of the relative amounts of the previously reported four subpopulations of water structures coexisting in a variety of aqueous solutions. Where solvatochromic dyes can measure the properties of solutions of non-ionic polymers, the results correlate well with ATR-FTIR measurements. In protein solutions to which solvatochromic dye probes cannot be applied, NMR (Nuclear Magnetic Resonance) spectroscopy was used for the first time to estimate the hydrogen bond donor acidity of water. We found strong correlations between the solvent acidity and arrangement of hydrogen bonds in aqueous solutions for several globular proteins. Even quite similar proteins are found to change water properties in dramatically different ways.

The aim of this work is to compare two softwares (MAUD and TOPAS) based on the Rietveld algorithm and to test the concept of tolerance factor using the dissolution at high temperature of yttrium into BaTiO₃. In general, both softwares give up different values of the crystalline parameters however the trends are similar in most cases but the analysis of the strain and crystallite size in the BaTiO₃ crystals suggests that, in this particular case, MAUD offered results more consistent with the expected behavior. Using the crystalline parameters calculated by Rietveld, the tolerance factor values were obtained and these data suggest even better stability in the crystalline structure than that expected using theoretical parameters. Tolerance factor concept also indicates that Ti⁴⁺ should be preferred.

This paper addresses the lack of analytical tools for visual data analysis in IEEE Xplore, an abstract database of publications on technical problems in electronics and electrical engineering. The openness of the platform and the good fillability of a large number of bibliometric record fields make it attractive for visual data analysis. The topic of machine learning and artificial intelligence applied to power systems, which are critical issues in the energy transition process, is chosen as an example for visual data analysis. The programs and utilities used for data analysis were VOSviewer, Scimago Graphica, FP-Growth algorithm, Inkscape, and MultiDendrograms. The use of IEEE Terms field data to identify publication topics in the exported data is analyzed in the most comprehensive way. This paper can be considered a reference for professionals interested in bibliometric analysis and visualization of IEEE Xplore data.

Objectives. The aim of the study is to identify relevant research topics based on pooled bibliometric data of International Journal of Hydrogen Energy publications from 2022-2024, collected from The Lens and ScienceDirect platforms. Data source. Bibliometric records of International Journal of Hydrogen Energy articles published in 2022-2024 from The Lens and ScienceDirect platforms were used. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The 'Fields of Study' data of The Lens can be rationally interpreted as system keywords similar to Scopus Index Keywords. The possibility of using 'Fields of Study' data in a method similar to bibliographic coupling is shown. The practicality of using an Alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in International Journal of Hydrogen Energy for 2022-2024, which can be described in terms of: 'Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science' and 'Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering'.

Objectives. The aim of this study was to demonstrate the ability to visualize the results of the Scilit platform's bibliometric data analysis on the topic "AI & Machine Learning" to identify publications reflecting specific issues of the topic. Data source. Bibliometric records exported from the Scilit platform on the topic "AI & Machine Learning" for the years 2021–2023 were used. For each year, 6,000 records were downloaded in CSV and RIS format. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility, GSDMM algorithm. Used services: Elicit, QuillBot, Litmaps. Results. It has been shown that bibliometric data from the open access abstract database Scilit can serve as a quality alternative to subscription-only databases. Data exported from the Scilit platform require preprocessing to make them available in a format that can be processed by programs such as VOSviewer and Scimago Graphica. The use of GSDMM and FP-growth algorithms is effective for structuring bibliometric data for further visualization. The Scimago Graphica software provides wide possibilities for building compound diagrams, in particular, for representing the network of keywords in such important coordinates for bibliometric analysis as average year of publication and average normalized citation, as well as for building an alluvial diagram of co-occurrence of more than two keywords. The possibility of using such services as elicit.com, quillbot.com and app.litmaps.com to accelerate the selection of publications on the topic under study is shown.

Background. Keyword co-occurrence analysis is a crucial tool for comprehending research trends, identifying relevant studies, and gaining insight into the connections between various concepts and topics. Objective. This study focuses on analyzing the co-occurrence of keywords using FP-growth algorithm and direct search methods. Materials and methods. The methodology involved extracting bibliometric data of Energies journal for 2023-2024 from MDPI publisher platform, keyword lemmatization and keyword co-occurrence estimation. Clustering and visualization were performed using Multidendrograms and Scimago Graphica software. Results. The results showed that the FP-growth algorithm can achieve a close match with the direct search results, which facilitates data preparation for clustering. In addition, finding the co-occurrence of three or more keywords significantly reduced the number of possible combinations, which allowed the identification of specific research topics. Conclusions. This study highlights the usefulness of the FP-growth algorithm in keyword analysis and provides insights into ways to refine search queries to abstract databases for the purpose of designing and writing literature and systematic reviews.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

Purpose of publication: - Preparation of bibliometric data exported from the Scilit platform on energy efficiency and conservation for further analysis to identify relevant research topics. - To identify potential issues in the processing of data exported from the Scilit platform. - Providing colleagues with the opportunity to use the prepared data and examples of their analysis for independent research on topical issues of energy efficiency and energy conservation using materials provided by the Scilit platform. Research Materials: Files in CSV and RIS formats exported from Scilit for the query "energy conservation OR efficiency" in Common Fields [Title, Abstract, Keyword], using filters: Content Type → Journal Article; Year→2021-2023; Subject → Industrial Engineering (29.8K), Energy and Fuel Technology (9.8K), Manufacturing Engineering (9.2K). A total of 30K records sorted by their relevance (10K for each year) were exported. Data are current as of 14-03-2024. Methods: Preprocessing of title, annotation, and keyword field texts using lemmatization dictionaries collected on GitHub, removal of keywords taken from GATE and spaCy, and "manual" editing. Using VOSviewer to analyze publication topics by clustering keywords based on their co-occurrence. Using Scimago Graphica to build bubble diagrams.Application of the GSDMM algorithm for clustering bibliometric records by title and annotation texts. Creation of a dictionary for this algorithm using the keyword field.Use of the Carrot2 demo version and the NMF algorithm for a more detailed analysis of the topics of the record clusters obtained from GSDMM. Results: are presented in the form of initial and interim tables and graphs obtained in the course of this study. The full tables are provided as references to the attached materials. Supplementary material for this preprint on figshare: Chigarev, Boris (2024). Supplementary material for preprint "Analyzing the Possibilities of Using the Scilit Platform to Identify Current Energy Efficiency and Conservation Issues". figshare. Dataset. https://doi.org/10.6084/m9.figshare.25574058.v1

This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we introduce a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

This article presents a concise survey of basic discrete and semi-discrete nonlinear models which produce two- and three-dimensional (2D and 3D) solitons, and a summary of main theoretical and experimental results obtained for such solitons. The models are based on the discrete nonlinear Schrödinger (DNLS) equations and their generalizations, such as a system of discrete Gross-Pitaevskii (GP) equations with the Lee-Huang-Yang corrections, the 2D Salerno model (SM), DNLS equations with long-range dipole-dipole and quadrupole-quadrupole interactions, a system of coupled discrete equations for the second-harmonic generation with the quadratic (χ⁽²⁾) nonlinearity, a 2D DNLS equation with a superlattice modulation opening mini-gaps, a discretized NLS equation with rotation, a DNLS coupler and its PT-symmetric version, a system of DNLS equations for the spin-orbit-coupled (SOC) binary Bose-Einstein condensate, and others. The article presents a review of basic species of multidimensional discrete modes, including fundamental and vortex solitons, their bound states, gap solitons populating mini-gaps, symmetric and asymmetric solitons in the conservative and PT-symmetric couplers, cuspons in the 2D SM, discrete SOC solitons of the semi-vortex and mixed-mode types, 3D discrete skyrmions, and some others.

It is shown that the 5D geodetic equations and 5D Ricci identities give us a way to create a new viewpoint on some problems of Modern Physics, Astrophysics, and Cosmology. Specifically, the application of the 5D geodetic equations in (4+1) and (3+1+1) splintered forms obtained with the help of the monad and dyad methods made it possible to introduce a new, effective generalized concept of the rest mass of the elementary particle. The latter leads one to novel connections between the General Relativity and quantum field theories, as well as all of that, including the (4+1) splitting of the 5D Ricci identities, brings about a better understanding of the magnetic monopole problem and the vital difference in the origins of the Maxwell equations and gives rise to surprising connections between them. The obtained results also provide new insight into the mechanism of the 4D Universe’s expansion and its following acceleration.

Anomaly detection in equipment processes plays an important role in the oil and gas sector. Algorithms for detecting anomalies in measured data are best understood in computer science and mathematics. Therefore, a possible transfer of knowledge from the latter knowledge area to the former can play a significant role. This paper addresses such a task by analyzing bibliometric data of Computer Science and Mathematics papers published in MDPI journals and publications found on the SPE search platform. It is shown that the main algorithms both extensively studied in MDPI publications and found in SPE publications and reflecting the anomaly detection problem are Random Forest, Support Vector Machine, Long-term Memory Method and Recurrent Neural Network. The main advantages and disadvantages of these methods are briefly described. Examples of classical, highly cited publications describing the work of these algorithms are given. Examples of papers describing their application in the oil and gas industry are given. The sections of SPE disciplines with the largest number of publications using the above algorithms that are frequently used for anomaly detection are presented.

This paper considers the reasonability of using GSDMM as a method for clustering short texts - titles and abstracts of publications 2021-2023 of MDPI journals on sustainable energy topics. The paper proposes an approach to identifying relevant research topics based on the use of the Python script Yake!, the Krovetz streamer, the GSDMM algorithm, and short text annotations. It is emphasized that researchers prefer to rely on specific publications rather than keywords when searching for information on a topic of interest. The bibliometric records of sustainable energy publications from 2021 to 2023 in Sustainability (Energy Sustainability section — 1,926 search results) and Energies (Sustainable Energy section — 994 search results) were used as data for analysis. The GSDMM algorithm was used to cluster the texts, and Yake! to extract the keywords for the GSDMM algorithm's vocabulary. This article summarizes topics found in 9 clusters, including general sustainable energy issues, biomass recycling, region-specific issues, building energy use, economic growth and investment, numerical flow modeling, generation cost optimization, heat to energy conversion, weather-related risks, and false data attacks.

The article presents a bibliometric analysis of conference proceedings 2019-2021 indexed in Scopus and related to the topic "Artificial Intelligence and Energy". The relevance of the topic is considered in the context of the energy transition and the application of artificial intelligence for the rational use of energy resources. A comparative analysis of the publication activity of researchers from Russia, China, India, the United States, and Indonesia on the topic in question is given. Methodologically, the emphasis for determining the subject is not on the co-occurrence of keywords, but on the clustering of documents based on the thesis that the titles of publications most briefly and fully reveal the content of the publication and allow the subject specialist to do a relevant selection of publications necessary for their research. Two tools were used in this work: Carrot2 and Clustering App (CSV Explorer). It is shown that Russian researches are characterized by the tendency of prevailing engineering problems and insufficient attention is paid to environmental, economic and social problems of using AI in the energy sector. Studies from China and the United States are of the greatest informative interest, both in terms of the relevance of their topics and the actuality of their content. Studies from India and Indonesia are more general in nature; of interest are the efforts of these countries to engage in global scientific activities.

EV transmissions operate at high speeds, upto 30,000 rpm. High speed operation puts higher demands on bearings, seals, and gears. Bearings in EV transmissions are prone to electrically induced bearing damage and may exhibit signs of pitting and fluting. Surface-initiated rolling contact fatigue is another common problem gaining increased attention lately. Most EV transmissions require a coupling between an oil-lubricated gearbox to an electrical motor that runs with minimal lubrication at very high rpm. High mechanical and thermal stresses the seals are exposed to under starved lubrication conditions have a detrimental impact on their service life. Hence, proper lubrication is critical. In general, EV transmission fluids call for a somewhat different spectrum of properties compared to conventional ATF. Gear tribology simulations open new ways to the design and optimization of lubrication for EV transmissions. Additionally, such simulations can also provide valuable insights into the effects of different oil properties on cooling and lubrication efficiencies, thereby helping in matching the lubricant and hardware characteristics for optimal performance. In the present communication, we demonstrate the effects of different lubricants and surface finishing technologies on the tribology of high-speed gears using tribological tests and advanced thermal elastohydrodynamic (TEHD) simulations. Important roles of lubricity additives and surface finish optimization are highlighted in conjunction with a move towards ultralow viscosity EV transmission fluids.

This article is devoted to a bibliometric analysis of IEEE Energy Internet and Energy Systems Integration Conference proceedings posted in IEEE Xplore in 2017-2021. The main objective of the study was to identify the actual research issues on the Energy Internet topic. Author Keywords, INSPEC Controlled Terms, and terms compiled from n-grams derived from conference papers title and abstract texts were used to describe the actual issues. The terms were clustered using VOSviewer, and the terms included in each cluster were treated as a description of the actual issues. Brief descriptions of several publications relevant to the issue in question were given for task detail. The actual issue, which in my opinion deserves further, more detailed analysis, is proposed.

The complexity of analysis pipelines in biomedical sciences poses a severe challenge for the transparency and reproducibility of results. Researchers are increasingly incorporating software development technologies and methods into their analyses, but this is a quickly evolving landscape and teams may lack the capabilities to set up their own complex IT infrastructure to aid reproducibility. Basing a reproducible research strategy on readily available solutions with zero or low set-up costs whilst maintaining technological flexibility to incorporate domain-specific software tools is therefore of key importance. We outline a practical approach for robust reproducibility of analysis results. In our examples, we rely exclusively on established open-source tools and free services. Special emphasis is put on the integration of these tools with best practices from software development and free online services for the biostatistics domain.

This article identifies promising research areas on the PETROLEUM SCIENCE topic via bibliometric analysis of the 2018-2021 publications in the highly cited Journal of Petroleum Science and Engineering, which is included in the Journal Citation Reports Section: ENERGY & FUELS — Q2 Quartile, ENGINEERING, PETROLEUM — Q1 Quartile. Bibliometric metadata from Web of Science were used for 866 articles in 2018, 1,142 — in 2019, 1,138 — in 2020, and 1,832 in 2021. The clustering of articles was performed using the texts of the Title, Abstract, Keywords, and Keywords Plus fields. The demo version of the Lingo3G algorithm was used. For the two major clusters, the most promising research topics were determined by comparing the titles of the 350 most cited and 350 least cited articles for each year. The hypothesis that low-cited papers often have the same subject matter as high-cited papers of previous years is discussed.

Attention mechanisms have become a fundamental component of deep learning, including the field of computer vision. The key idea behind attention in computer vision is to help the model focus on the relevant spatial regions of the input image, rather than treating all regions equally. The traditional approaches to attention mechanisms in computer vision often suffer from distribution inconsistencies in the attention maps, resulting in sharp transitions that negatively affect model’s focus and lead to poor generalization on complex shapes. The problem of spatial incoherence is particularly pronounced in the task of semantic segmentation, where accurate pixel-level predictions require a detailed understanding of the spatial relationships within the image. In this paper, we propose an attention mechanism called Smooth Attention designed for convolutional neural networks to address the problem of spatial inconsistency in attention maps through multidimensional spatial smoothing. We conduct a series of experiments to evaluate the effectiveness of the proposed mechanism and demonstrate its superior performance compared to traditional methods.

The high genetic diversity of the tomato and its high micronutrient content make this fruit very interesting from an economic and nutritional point of view. The genetic erosion suffered by this crop, due to breeding objectives based on yield and marketing, makes it necessary to return to the origins in search of the nutritional and organoleptic quality lost in traditional varieties. In this study, the agronomic, physical, organoleptic and nutritional characteristics of eighteen F1 hybrids obtained by crossing fourteen traditional varieties, previously selected for their quality, were studied to select genotypes of superior quality that could be candidates for new. All parameters studied were strongly influenced by genotype, showing a wide range between cultivars. Principal Component Analysis revealed the characteristics of each hybrid that made it stand out from the others. Some hybrids (H3, H4, and H6) stand out because of their high concentration of active compounds, others (H16, H15, H10, H17, H9, and H11) because of agronomic performance and high content of β-carotene, and H5 was the only one to contain chlorophyll in their ripe fruits. Finally, the evaluation index allowed the selection of five hybrids with interesting characteristics, combining good yield performance and high quality

The review analyzes a possible role of autoimmune processes in the pathogenesis of schizophrenia and evolution of concepts on this issue from its origin to present. Risks of autoimmune processes causing schizophrenia are associated with several factors: an impaired functioning of dopaminergic and glutamatergic systems in the brain, kynurenine pathway disorder with overproduction of quinolinic, anthranilic and kynurenic acids (possibly altering both neurons and T-regulators), increased intestinal permeability, as well as food antigens’ effects, stress and infections with various pathogens at different stages of ontogenesis. An increase in the levels of proinflammatory cytokines and chemokines as well as a decrease in the levels of anti-inflammatory ones also may contribute to schizophrenia risks. Schizophrenia often occurs in those patients having various autoimmune diseases and their first-degree relatives. Cases of schizophrenia resulted from autoimmune pathogenesis (including autoimmune encephalitis caused by autoantibodies against various neuronal antigens) are characterized by quite severe cognitive and psychotic symptoms and less favorable prognosis. This severe course may result from the chronic immune damage of the neuronal receptors such as NMDA, GABA, and others and depend on hyperprolactinemia, induced by antipsychotics, but aggravating autoimmune processes [with 2 tables, 4 figures, bibliography: 99 references].

This paper addresses the analysis for the nonlinear vibration response of a rectangular tube with a flexible end and non-rigid acoustic boundaries. This is a further work of the linear structural acoustic problem in a well-known acoustic book. In fact, the acoustic boundaries of an enclosed space sometimes are non-rigid and the structural vibration responses are nonlinear. These two points are the focuses of this paper. The multi-level residue harmonic balance method is applied to this nonlinear structural acoustic problem. The results obtained from the multi-level residue harmonic balance method and numerical method are generally in good agreement. The effects of excitation magnitude, tube length, and phase shift parameter etc. are examined.

Cutaneous mycoses are common infections whose treatment has become more complex due to increasing antifungal resistance and the need for prolonged therapies, hindering patient adher-ence and increasing the incidence of adverse effects. Consequently, the use of physical therapies, especially photodynamic therapy (PDT), has increased for the treatment of onychomycosis due to its antimicrobial capacity mediated by the production of reactive oxygen species. This study investigates the in vitro effect of the combination of blue light (448 nm) and red light (645 nm) with terbinafine on the cell viability of human keratinocytes and the production of reactive ox-ygen species. The combination of terbinafine and blue light exhibits a synergistic effect on the production of reactive oxygen species and a significant increase in the expression of superoxide dismutase (SOD), an enzyme involved in the reduction of superoxide ions (O2-) and the genera-tion of hydrogen peroxide (H2O2). Such effect could be useful in clinical practice to improve the response of cutaneous mycoses to pharmacological treatment, reduce their toxicity, and shorten their duration.

Sustainable agriculture is at the forefront of modern farming practices, with a growing emphasis on optimizing crop production while minimizing environmental impact. The choice of fertilizer application technology plays a critical role in achieving these objectives. Soybean (Glycine max (L.) Merr.), a valuable crop globally, serves both as a source of human nutrition and livestock feed. To address the challenges of enhancing soybean production while minimizing ecological harm, this study evaluates and compares the performance of different fertilizer application technologies. In this study we combined remote and ground surveys to allow a comprehensive understanding of the impact of these technologies on soybean cultivation. The study focuses on deep placement of slow-release nitrogen fertilizers with coated urea at a 20 cm depth, conventional nitrogen fertilizer application, and manure organic fertilizer application. Remote surveys are conducted using advanced smart farming tools such as Unmanned Aerial Vehicle (UAV), ground surveys such as soil plant analysis development SPAD measurements, and soybean parameters to assess the impact of fertilizer application. This study revealed that deep placement fertilizer demonstrated better performance compared to other fertilizer application technologies for soybean cultivation. The findings from this study contribute to the advancement of sustainable agricultural practices and empower farmers with knowledge to make informed decisions for optimizing green soybean production.

We review the literature on medical discourse and attempt to build a computational model of it. Medical discourse sheds a light on communication structure of patient-doctor and other communication scenarios in healthcare and should be leveraged to facilitate and automate this communication when it is possible and practical. We propose a unified framework to represent communication discourse at the meta-level, where the subject of the communication is expressed in a language object. So far, the broad range of work on medical discourse is detached from computational discourse analysis, and we explore the possibilities of filling this gap and computationally treat the peculiarities of how information is passed between the agents in a hospital setting. We select the domain of question answering (QA) against a corpus of medical documents of diverse nature to evaluate our computational model of medical discourse. It turns out that applying specific structures obtained in medical discourse studies improves the relevance and efficiency of question answering.

The article aims to explore social aspects in the area of energy research by using bibliometrics methods and tools. The study is based on the data of Energy Research & Social Science journal publications exported from ScienceDirect database during 2019-2023. Methodologically, the work included clustering of the bibliometric records under consideration. This allowed to identify the main topics of publications and those in which the research of social problems prevails. This stage of the work was carried out using carrot2, an engine for clustering search results. Next, the analysis of publication topics related to social issues research was carried out using VOSviewer — a software tool for visualizing scientific landscapes. The topics of the four clusters obtained at this stage were described by key terms with the maximum total link strength. For the principal ones, a definition was made on the basis of the texts of publications that most fully disclose the meaning of these terms. The 1537 publications in the journal during the period under review deal with many aspects of energy transition research, renewable energy, energy policy, energy justice and energy systems, but only 78 of them are dominated by social issues. The paper reveals the main social issues in the field of energy research: sociology of energy, socio-technical system, community energy, energy democracy, sociology of the future, energy sovereignty, socio-technical imaginary and shows the insufficient attention to this topic, especially to the investment of such research.

The purpose of this article is to demonstrate the ability of bibliometric data from the Lens platform to identify relevant bibliometric/scientometric issues based on the construction of a network of key terms co-occurrence and their clustering. The advantages of using the Lens platform for bibliometric analysis are briefly demonstrated. Key terms were selected on the basis of n-grams and noun phrases. VOSviewer, Scimago Graphica, and Sifaka text mining application were used as analytical tools. Analysis of the Lens metadata on bibliometrics/scientometrics showed their predominant use in the political, social, and medical fields of research.

The article is devoted to identifying promising research issues on the topic of Digital Industry based on the analysis of bibliometric data from Scopus platform for 2018–2022. The definition of promising issues derived from the titles, additionally abstracts, of highly cited works by authors with high publication activity. Authors' Scopus profiles were used to determine their affiliations, which are important for in-depth analysis of selected promising Digital Industry tasks. Metadata filtering to identify highly cited papers on particular issues was performed by keywords, Subject Areas, affiliations with countries and sponsoring organizations. Additionally, bibliometric metadata were clustered based on the co-occurrence of terms using VOSviewer. Within these clusters, articles of interest were identified for the formulation of promising research issues on the topic of Digital Industry, which will be subjected to in-depth analysis in separate papers.

We consider finite and unconditionally convergent infinite expansions of elements of a given topological monoid G in some base B c G as words of the alphabet B, identify insignificantly different words and define a multiplication and a topology on the set of classes of these words. Classical numeral systems are particular cases of this construction. Then we study algebraic and topological properties of the obtained monoid and, for some cases, find conditions under which it is canonically topologically isomorphic to the initial one.

The article is devoted to a bibliometric analysis of scientific publications reflecting trends in scientific publications related to the energy transition of leading universities in Saudi Arabia. The universities were selected based on the presence of joint publications with the Saudi Arabian Oil Company, they are: King Fahd University of Petroleum and Minerals, King Abdullah University of Science and Technology, and King Saud University. The importance of studying the experience of Saudi Arabia for Russia in the context of the energy transition was highlighted. The analysis was based on Scopus platform data related to Subject Areas: Physical Sciences. Scientists from Saudi Arabian universities are increasingly publishing with co-authors from China, India, Egypt, Pakistan, and Malaysia, while maintaining high interaction with co-authors from the United States, South Korea, and the United Kingdom. Authors from the Russian Federation publish poorly with co-authors from Saudi Arabia. The trends in the topics of scientific publications were investigated, and their connection with the renewable energy topic was shown. The VOSviewer software was used to determine the main research areas using the cluster analysis method based on the co-occurrence of key terms. The analysis was done for both Author's keywords and Index keywords of the Scopus system. Graphical representation of the final choice of terms to describe research trends was proposed. TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back

The article is aimed at a brief comparison and analysis of the results of queries to IEEE Xplore and the leading abstract databases Scopus and Web of Science to identify research trends. Some errors in the Author Keywords in Web of Science have been revealed. Therefore, a more detailed analysis was conducted by comparing different types of key terms for IEEE Xplore and Scopus platforms only. I used IEEE Access journal metadata as indexed on both platforms. The sample match for IEEE Xplore and Scopus was achieved by comparing DOI. The IEEE Xplore metadata contains more types of key terms, which provides an advantage in analyzing research trends. Using NSPEC Controlled Terms from expert-compiled vocabulary provides a more stable data, which gives an advantage when considering the change of terms over time. Apriori, an algorithm for finding association rules, has been used to compare co-occurrence of terms for a more detailed description of sample subjects on both platforms. VOSviewer was used to analyze trends in scientific research based on IEEE Xplore data. The 2011-2021 ten-year period was divided into two sub-intervals for comparing the occurrence of Author Keywords, IEEE Terms, and NSPEC Controlled Terms. Using the IEEE conference proceedings bibliometric data, I illustrated the importance of context in estimating the rate of growth of publishing activity on a topic of interest.

The objective of this article: analysis of research trends on the topic "Materials Science for Energy Engineering" for the period 2012-2021. Materials and methods: bibliometric analysis of data from the Scopus abstract database.Results. It is shown that this topic is developing faster than the general energy topics.The key feature of the research trends is a significant increase in work on the development of materials for renewable energy and a decrease in the number of publications related to nuclear power.The primary goal of many studies is to increase the efficiency of renewable energy production through the use of new materials.The importance of the topic is evidenced by the emergence of new journals that quickly entered the first quartile of the abstract databases Scopus and Web of Science, for example: ACS Applied Energy Materials.There has been a significant increase of interest in perovskite solar cells, layered semiconductors, triboelectric nanogenerators, cobalt compounds, sulfur compounds, and oxygen and hydrogen evolution reaction during Electrolysis.Publications on electric batteries are well represented in all time intervals. The focus is on electrode materials and battery efficiency.

Machine learning research has been able to solve problems in multiple aspects. An open area of research is machine learning for solving optimisation problems. An optimisation problem can be solved using a metaheuristic algorithm, which is able to find a solution in a reasonable amount of time. However, there is a problem, the time required to find an appropriate metaheuristic algorithm, that would have the convenient configurations to solve a set of optimisation problems properly. A solution approach is shown here, using a proposal that automatically creates metaheuristic algorithms aided by a reinforced learning approach. Based on the experiments performed, the approach succeeded in creating a metaheuristic algorithm that managed to solve a large number of different continuous domain optimisation problems. This work's implications are immediate because they describe a basis for the generation of metaheuristic algorithms in real-time.

Effects of the convection flow, atmospheric diffusivity and humidity on evolution and travel distances of exhaled aerosol clouds by an infected person are considered. The aim of this work is to evaluate the importance of aerosol transmission routes and the effectiveness of the 2-metre separation distance policy. A potential impact of use of face masks on the infection transmission rate, and an opportunity to reduce infection in hospitals, care homes and other public spaces by appropriate monitoring and filtering of air are also considered. The results obtained demonstrate that aerosol particles generated by coughing and sneezing can travel over 30 m. Modelling of the evolution of aerosol clouds generated by coughing and sneezing enables us to evaluate the deposition dose of aerosol particles in healthy individuals. For example, a person in a public place (e.g. supermarket or car park) can accumulate in the respiratory system up to 200 virus copies in 2 min time by breathing in virus laden aerosols. Wearing face mask considerably reduces the deposited load down to 2 virus copies per 2 min. The modelling also suggests that it should be possible to measure virus causing COVID-19 (SARS-CoV-2) within aerosol particles in hospitals and public places, e.g. care homes and supermarkets.

Purpose: To assess clinical outcomes of corneal cross-linking (CXL) intervention in a population diagnosed with progressive keratoconus. Methods: This single-center retrospective cohort study included consecutive patients who underwent standard CXL or accelerated CXL for progressive keratoconus at a major teaching hospital in south Israel between January 2015 and December 2019. Patient medical files were reviewed to extract demographic, clinical, and tomographic data from outpatient clinic reports before treatment and one year post-operatively. Results: This study included 166 patients (representing 198 eyes), out of which 98 patients (123 eyes) were ethnically Bedouin, and 68 patients (75 eyes) were ethnically Jewish. Overall, 126 patients (144 eyes) had a follow-up of at least 12 months (16.84±5.76). The mean patient age was 20.62 ± 7.1 years old. There were significant baseline differences between the two ethnical groups in best-corrected visual acuity (BCVA; p < 0.001), uncorrected visual acuity (UCVA; p < 0.001), mean keratometry (p = 0.028), and corneal thickness (p < 0.001). Significant changes in BCVA, UCVA, and pachymetry parameters within each group were found after 12 months. Negative binomial regression analysis showed a maximal keratometry below 55D (RR=1.247, p < 0.001) and a standard CXL procedure (RR=1.147, p = 0.041) are significantly related to the stability of KC after 12 months. However, the effect size of the origin of patients is negligible (RR=1.047, p = 0.47). Conclusions: In this study, the Bedouin population suffered from more progressive keratoconus when compared to the Jewish population. CXL was significantly effective in improving BCVA and UCVA in both groups after 12 months of follow-up.

A problem of efficacy of crystal growth methods for crystallization from solution or melt has been investigated. Axial vibrational control (AVC) technique was considered as a perspective method to manage both heat-mass transfer and chemical component composition of the melts in the case of crystallization of complex chemical compounds. Numerical modeling and the search for generalized dependencies made it possible to predict the AVC parameters that provide optimal heat and mass transfer modes for creating flat liquid-solid interfaces, as well as the component composition of dissociated melts of various chemical compounds – Ge, NaNO3, CdTe.

Background and Objectives. Prevalence of GERD is increased among individuals with obesity and RYGB is considered as the most effective procedure to control GERD and obesity. However, some patients continue to have GERD after RYGB. The aim of the study was to investigate the prevalence and the risk factors of GERD after RYGB. Material and Methods. This prospective study included 180 patients operated with RYGB and followed for on average of 12.2 (0.6) years. 126 (70%) patients agreed to participate in online consultations and provided data on weight, GERD symptoms, filled GERD-HRQL, TFEQ-18 and GSRS questionnaires. Results. The average age before surgery was 42.7 (10.5) years and BMI was 45.2 (6.4) kg/m2. 128 (71.1%) were females and preoperative GERD was diagnosed in 74 (41.1%) patients. At 12 years follow-up the mean %EBMIL and %TWL were 60.37 and 25.73, respectively. The median %WR was 18.0 (39.0). The GERD was present in 30 (23.8%) patients, of whom 12 (40%) continued to have GERD symptoms and 18 (60%) developed de novo GERD. The GERD-HRQL score significantly decreased from 3.0 (8.0) at baseline to 2.0 (5.0) (p=0.028) at 12 years. GSRS Diarrhea and Indigestion median scores increased significantly, from 1.33 (0.67) to 1.5 (2.42) (p 3.2.

Gas electron multipliers (GEMs) with wire (WGEMs) or metal electrodes (MGEMs), which don’t use any plastic insulators between electrodes are created. The chambers containing MGEMs (WGEMs) with pin-anodes are proposed as detectors for searching of spin-dependent interactions between Dark Matter (DM) particles and gases with nonzero-spin nuclei (H2, D2, 3He, 21Ne, CF4, CH4, etc.). In this paper, we present a review of such chambers. For investigation of the gas mixtures Ne+10%H2, H2 (D2) +3ppmTMAE, the chamber containing WGEM with pin-anode detection system was constructed. In this paper we present the results of an experimental study of these gaseous mixtures exited by an α - source. Mixture of Ar + 40 ppm C2H4 and mixture 50% Xe + 50%CF4 have been investigated. The spatial distributions of photoelectron clouds produced by primary scintillations on α- and β-particle tracks, as well as the distributions of photoelectron clouds due to photons from avalanches at the pin-anode, have been measured for the first time. In our experiments as another filling of the chambers for search of low-mas WIMP (<10 GeV/c2), solar neutrino and solar axions with spin-dependent interaction we propose to use the mixtures: D2 + 3ppmTMAE, 3He + 3%CH4, 21Ne + 10%H2, at pressure 10-17 bar. And in our experiment with liquid gases is used the mixtures with 19F (LAr + CF4, LXe + CF4) and mixture LCH4 + 40ppm TMAE. The time projection chamber (TPC) with the mixture D2 + 3ppmTMAE filling allow to search of spin-dependent interactions of solar axions and deuterium. As well as we present the detecting systems for search of narrow pp-resonances (quarks) in accelerators experiments.

A text obtained by a Large Language Model (LLM) such as GPT4 usually has issues in terms of incorrectness and hallucinations. We build a fact-checking system 'Truth-O-Meter' which identifies wrong facts, comparing the generation results with the web and other sources of information, and suggests corrections. Text mining and web mining techniques are leveraged to identify correct corresponding sentences; also, the syntactic and semantic generalization procedure adopted to the content improvement task. To handle inconsistent sources while fact-checking, we rely on an argumentation analysis in the form of defeasible logic programming. We compare our fact checking engine with competitive approach based on reinforcement learning on top of LLM or token-based hallucination detection. It is observed that LLM content can be substantially improved for factual correctness and meaningfulness.

Objectives: Describe the epidemiology of burns in the pediatric population. Analyze and compare the results obtained from the treatment of burn wounds by using the bio-preserved human epidermis allograft (BHEA) and other types of dressings and determine the need for further need of a skin graft. Methods: A retrospective cross-sectional study of pediatric population with burn injuries was conducted, grouped into categories based on their age group, and the mechanisms of injury into 6 categories: scald, flame, contact, electrical, chemical and friction. Describing the extension and depth of the burn injury. The results of treatment of two groups; the patients who used (BHEA) and the group with “other dressings” were analyzed by inferential statistics to establish the relationship between the use of BHEA and the need for skin grafts compared to the other group. Results: A total of 65 patients were obtained. The average age was 4.5 years (±3.8). Preschoolers (1-5 years old) were the most frequent age group 64% (n=42). Male patients represented 61% (n=40) of cases. Scald was the most reported mechanism 64% (n=42). The average total body surface area burned (TBSAB) was 10.8% (± 9.2). Mixed partial thickness burn (superficial and deep) was the most common with a 55%. The head was the most affected anatomical site; 30%. The face was the most reported “special anatomical site” with a 40% (n=30). 32.2 % of the population (n=21) was treated with BHEA. The average time of epithelialization of the BHEA group was 8 days (±7.2), and their average hospital stay time was 7 days (±5.7). In the “other dressing” group, the average epithelialization time was 18 days (±13.6), and the average hospital stay time was 11 days (±12.6). Fifty percent (n=22) of the “other dressing” group required skin grafts. In the BHEA group only 19% (n=4) required skin grafts. An OR of 0.23 and CI of 95% (0.06 – 0.81) with a p value of (0.017) for the need of skin grafts after de use of BHEA was obtained. Conclusion: The epidemiological results reported are similar to those described in the literature. The use of (BHEA) proved to be a good option for the management of partial thickness burns and burns in transition, promoting timely epithelilization and avoiding deepening of the burns while reducing morbidity, hospital stay and care costs.

Experimental evidence suggests that chronic intermittent hypoxia (CIH), a major hallmark of obstructive sleep apnea (OSA), boosts carotid body (CB) responsiveness, thereby causing in-creased sympathetic activity, arterial and pulmonary hypertension, and cardiovascular disease. An enhanced circulatory chemoreflex, oxidative stress, and NO signaling appear to play im-portant roles in these responses to CIH in rodents. Since the guinea pig has a hypofunctional CB (i.e., it is a natural CB knockout), in this study we used it as a model to investigate the CB de-pendence of the effects of CIH on pulmonary vascular responses, including those mediated by NO, by comparing them with those previously described in the rat. We have analyzed pulmonary artery pressure (PAP), the hypoxic pulmonary vasoconstriction (HPV) response, endothelial function both in vivo and in vitro, and vascular remodeling (intima-media thickness, collagen fiber content, and vessel lumen area). We demonstrate that 30 days of exposure of guinea pigs to CIH (FiO2, 5% for 40 s, 30 cycles/h) induces pulmonary artery remodeling but does not alter en-dothelial function or the contractile response to phenylephrine in these arteries. In contrast, CIH exposure increased the systemic arterial pressure, and enhanced the contractile response to phenylephrine while decreasing endothelium-dependent vasorelaxation to carbachol in the aorta, without causing its remodeling. We conclude that since all of these effects are independent of CB sensitization, there must be other oxygen sensors, beyond the CB, with the capacity to alter the autonomic control of the heart and vascular function and structure in CIH.

Our objective was to investigate the effects of topically applied neuropeptide Y (NPY) on ischemic wounds. Initially, the animal model for ischemic wound healing was validated using 16 male Sprague-Dawley albino rats. In the intervention study, an additional 28 rats were divided into three groups: NPY (0.025%), the positive control insulin-like growth factor-I (IGF-I, 0.0025%), and the hydrogel carrier alone (control). The hydrogel was selected due to its capacity to prolong NPY release (p &lt; 0.001), as demonstrated in a Franz diffusion cell. In the animals, an 8-mm full-thickness wound was made in a pedunculated dorsal ischemic skin flap. Wounds were then treated and assessed for 14 days, and procured at the end of the experiment for in situ hybridization analysis (RNAscope®) targeting NPY receptor Y2R and for meticulous histologic examination. Wound healing rates, i.e. the percentage wound area changes, did not show an increase with NPY (p = 0.938) but did with rhIGF-I (p = 0.039) compared to the control. Y2R mRNA was not detected in the wounds or adjacent skin but was identified in the rat brain (positive control). Light microscopic examination revealed trends of increased angiogenesis and enhanced inflammatory cell infiltration with NPY compared to control. An interesting secondary discovery was the presence of melanophages in the wounds. Our findings suggest the potential of NPY to enhance neovascularization under ischemic wound healing conditions, but further optimization of the carrier and dosage is necessary. The mechanism is elusive but likely involves NPY receptor subtypes other than Y2R.

We leverage the explainability feature of KAN network and build an explainable language model where certain neurons encode individual words and neuron activation is fully interpretable in terms of the basis of a word. To do that, we propose a continuous word2vec model where a meaning of a word is expressed by a continuous profile of distances of this word from the words in the basis of words which is interpolated. As a result, the whole KAN network can be interpreted as a sequential procedure with word expressions. We then proceed from words to logic programs and develop a clause learning technique based on KAN. A logic program construction process from facts now become fully interpretable. We follow the differentiable inductive logic programming technique, representing a logic program as a matrix learned by KAN. Hence, we obtain an efficient and fully interpretable rule learning approach.

Today, LLMs are not good at personalization providing recommendation. They advise physicians and financial advisors to ask professionals in respective fields for help, even having user information available. Answering questions of software professionals, LLM needs to deliver in-depth answers with codes or algorithms, whereas for professionals in other fields would need definitions and main concepts. The intent of this chapter is to make LLM answer tailored to the needs of users, taking into account available information about them. To do that, we need to generalize available information about a person like her health record, maintaining the privacy of this person. We rely on meta-learning techniques to design a LLM prompt to produce a personalization prompt to obtain a suitable relevant information. Such “meta-prompt” is produced by generalization operation applied to available documents for the user. These documents need to be de-identified so that they are sufficient for personalization on one hand and will maintain user privacy on the other hand. The second neuro-symbolic technique to support personalization is abductive reasoning, acting in parallel to LLM fine-tuning. Traditional recommendation and personalization techniques as well as modern, deep learning – based are presented, and the comparison is drawn to the proposed approach. We also share the evaluation and comparative analyses of these approaches. We consider an example for how to build personalization LLM systems coming from Langchain platform. We will explore how to construct chains to form a personalization profile for a user and apply it to user search and recommendation requests.

In the framework of mean field approximation, we consider a spin system consisting of two interacting sub-ensembles: spins interactions with in each sub-ensemble are ferromagnetic, while the inter-ensemble interactions are antiferromagnetic. We define the effective number of the nearest neighbors, and show that if the two sub-ensembles have the same effective number of the nearest neighbors, the classical form of critical exponents (, , , ) gives way to the non-classical form (, , , ), and the scaling function changes simultaneously. We demonstrate that this system allows for two second-order phase transitions and two first-order phase transitions. We observe that an external magnetic field does not destroy the phase transitions, but only shifts their critical points, allowing for control of the system’s parameters. We discuss the regime when the magnetization as a function of the magnetic field develops a low-magnetization plateau, and show that the height of this plateau abruptly rises to the value of one when the magnetic field reaches a critical value. Our analytical results are supported by a Monte Carlo simulation of a three-dimensional layered model.

The Krudum granite body comprises highly fractionated granitic rocks ranging from medium-F biotite granites to high-F, high-P₂O₅ Li-mica granites. This unique assemblage is an ideal site to continue recent efforts in petrology to characterize the role of zircon, monazite and xenotime as hosts to REEs. The granitic rocks of the Krudum body analysed in this study were found to contain variable concentrations of monazite and zircon, while xenotime was only found in the high-F, high-P₂O₅ Li-mica granites and in the alkali-feldspar syenites of the Vysoký Kámen stock. For analysed monazites of all magmatic suites cheralite substitution was significant. The highest concentration of cheralite was found in monazites from the high-F, Li-mica granites and from the alkali-feldspar syenites. The proportion of YPO₄ in all analysed xenotimes ranges from 71 to 84 mol. %. Some xenotimes were found to be hydrated and the observed water content estimated from analytical data ranged from 5 to 11 wt. % H₂O. Analysed xenotimes were commonly enriched in HREEs (9.3– 19.5 wt. % HREE₂O₃) and thorite-coffinite and cheralite exchange was observed. Analysed zircons from granite suites of the Krudum granite body contained moderate Hf concentrations (1.0–4.7 wt. % HfO₂; 0.010–0.047 apfu Hf). The highest concentrations of HfO₂ were found in zircons from the high-F, high P₂O₅ Li-mica granites (1.2–4.7 wt. % HfO₂) and from the alkali-feldspar syenites (1.3–4.1 wt. % HfO₂). Zircons from the high-F, high-P₂O₅ Li-mica granites were often hydrated and fluorised. The concentrations of F in zircon from partly greisenised high-F, high-P₂O₅ Li-mica granites reached up to 1.2 wt. % (0.26 apfu F). In zircons from the alkali-feldspar syenites enrichment in P, which is not associated with a simultaneous enrichment in Y + REE, was also observed. Analysed zircons from the high-F, high P₂O₅ Li-mica granites were enriched in Y (up to 5.5 wt. % Y₂O₃; 0.10 apfu Y) and Sc (up to 1.17 wt. % Sc₂O₃; 0.03 apfu Sc).

Obstructive sleep apnea (OSA) is a common sleep disorder that is associated with a wide variety of health conditions, including cardiovascular, cerebrovascular, metabolic, neoplastic, and neurocognitive manifestations. OSA as a chronic condition is mainly characterized by repeated upper airway obstructions during sleep that cause episodes of intermittent hypoxia (IH), resulting in tissue hypoxia-reoxygenation cycles. Decreased arterial oxygen pressure (PaO₂) and hemoglobin saturation (SatO₂) stimulate reflex responses to overcome the obstruction. The prevalence of OSA is significant worldwide, and an underrated problem when focusing on women during pregnancy. The physiological changes associated with pregnancy, especially during its latest stages, are related with a higher prevalence of OSA events in pregnant mothers, and associated with an increased risk of hypertension, pre-eclampsia and diabetes, among other deleterious consequences. Furthermore, OSA during pregnancy can interfere with normal fetal development and is associated with growth retardation, preterm birth, or low term weight. Carotid body overstimulation and hypoxia-reoxygenation episodes contribute to cardiovascular disease and oxidative stress, which can harm both mother and fetus and have long-lasting effects that can reach into adulthood. Because IH is the hallmark of OSA, this review examines the literature available about the impact of gestational intermittent hypoxia (GIH) on the respiratory system at maternal, fetal, and offspring levels. Offering the latest scientific data about OSA during pregnancy, we may help to tackle this condition with lifestyle changes and therapeutic approaches, that could influence the mothers, but also impact adult health problems, mostly unknown, inherited from these hypoxic episodes in the uterus.

The purpose of the evaluation of the Peruvian energy generation system is to project the electricity generation and demand until the year 2050. To achieve this, three alternative scenarios have been defined and analyzed using the LEAP (Long-range Energy Alternatives Planning) software. The scenarios are as follows: the first one, Business-as-Usual scenario, based on normal trends according to historical data and referencing projections made by Peruvian state entities; the second one is focused on Energy Efficiency, the highlighted characteristic is taking into consideration the efficient conditions in transmission and distribution of electric energy; and the third one, centered on Geothermal Energy, focused on the development of this type of energy source and prioritizing it. The primary purpose of this analysis is to identity advantages and disadvantages inherent in each scenario in order to get the best of each one. In this way, the intention is to propose solutions based on Peru’s national reality or possible uses of the country’s energy potential to supply its energy demand. Currently, Peru’s energy demand relies on fossil fuels, hydraulic, and thermal energy. However, there is the possibility of transforming this system into a sustainable one, by strengthening existing and growing energy sources such as solar and wind energy, and new technologies for hydraulic and thermal energy, in addition to considering geothermal energy as the main energy source in the third scenario. The new system mentioned satisfactorily indicate that the CO2 equivalent emissions decrease significantly in the third scenario, with a 15.8% reduction compared to the first scenario and a 9.7% reduction in comparison to the second. On the other hand, the second scenario shows a 5.6% decrease in CO2 emissions compared to the first, resulting from improvements in technology and energy efficiency without requiring significant modifications or considerable investments, as in the third scenario.

Stable suspensions of metal/metalloid oxide nanoparticles (Me-NPs) obtained by laser ablation of 99.99% pure elemental aluminum, titanium or silicon under a layer of deionized water were used separately, or in three binary combinations, or in a ternary combination to induce subchronic intoxications in rats. To this end, the Me-NPs were repeatedly injected intraperitoneally (i.p.) 18 times during 6 weeks before measuring a large number of functional, biochemical, morphological and cytological indices for the organism’s status. In many respects, the Al₂O₃-NP was found to be the most toxic species alone and the most dangerous component of the combinations studied. Mathematical modeling with the help of the Response Surface Methodology showed that, as well as in the case of any other binary toxic combinations previously investigated by us, the organism’s response to a simultaneous exposure to any two of the Me-NP species under study was characterized by a complex interaction between all possible types of combined toxicity (additivity, subadditivity or superadditivity of unidirectional action and different variants of opposite effects) depending on which outcome a given type was estimated for and on effect and dose levels. With any third MeO-NP species acting in the background, the type of combined toxicity displayed by the other two remained virtually the same or changed significantly, becoming either more or less unfavorable. Various harmful effects produced by the [Al₂O₃-NP+TiO₂-NP+SiO₂-NP]-combination, including its genotoxicity, were substantially attenuated by giving the rats per os during the entire exposure period a complex of innocuous bioactive substances expected to increase the organism’s antitoxic resistance.

In the modern world, the problem of antibiotic therapy is acute. Despite the diversity of existing antibiotic drugs, their efficacy decreases as new, resistant forms of pathogenic microorganisms emerge. It is extremely difficult to control such processes and even more difficult to treat severe bacterial infections. In such situations, an individual approach to each patient is required and physicians need parameters to estimate the efficacy of antibiotic therapy. This review discusses the significance of monitoring the content of antibiotics in the blood for this purpose, in combination with the content of inflammatory markers, such as C-reactive protein and procalcitonin. The basic principles of antibiotic therapy, and factors in the resistance of microorganisms to antibiotics, are examined. Approaches to assess the efficacy of antibiotic therapy, as well as methods to detect antibiotics and inflammatory markers in the blood of patients, and comparative assessment of their capabilities and limitations, are described.

PIEZO channels PIEZO1 and PIEZO2 are the newly identified mechanosensitive, non-selective cation channels permeable to Ca2+. In higher vertebrates, PIEZO1 expresses ubiquitously in most of the tissues and cells while PIEZO2 expresses more specifically in the peripheral sensory neurons. PIEZO channels contribute to a wide range of biological behaviors and developmental processes, therefore driving a significant attention in the effort to understand their molecular properties. One prominent property of PIEZO channels is their rapid inactivation, which manifests itself as a decrease of channel open probability in the presence of a sustained mechanical stimulus. Lack of the PIEZO channel inactivation is linked to various mechanopathologies emphasizing the significance of studying this PIEZO channel property and the factors affecting it. In the present review, we discuss the mechanisms underlying the PIEZO channel inactivation, its modulation by interaction of the channels with lipids and/or proteins, and how the changes of PIEZO inactivation by the channel mutations can cause a variety of diseases in animals and humans.

It is shown by numerical modelling that anisotropic diffusion can compensate and even overcome diffusion broadening - the main limiting factor of devices working at atmospheric pressure. The thickness of ion clouds coming out of the ionisation chamber is reduced ~ 1000 times in the ADMA inlet increasing the resolution. This finding has a great potential that enables construction of a device with resolution close to that of currently available desktop ion separation devices – high pressure mass spectrometers, but with much lower cost of manufacture and with smaller dimensions. Comprehensive numerical modelling along with mathematical analysis of physical concepts enables reduction of the footprint and manufacturing costs. Modelling determined that the resolving power (RP) potential of the ADMA is greater than the RP of currently available on the market devices for the airport security market. The ADMA technology enables very fast detection of threats; at least 100 times faster than currently used in Ion Mobility Spectrometers (IMS). This potentially allows an increase in passenger throughput in airports.

City Marketing has a strong tradition in Berlin, with two organisations, Berlin Partner and Visit Berlin, responsible for designing and implementing relevant strategies. Sustainability has been on and off the city marketing agenda, almost exclusively in its environmental dimension. In this article we examine the current representations of Berlin as a “sustainable city” in the official City Marketing strategies. We look at how sustainability is used and instrumentalized to create a specific city profile, and also to attract particular target groups in tourism. We propose an analysis of sustainable planning in Berlin since reunification, to show how it has moved into different directions over time and how this has (or has not) been followed by City Marketing. In this endeavour we move between the existing, and as we argue deeper and more sophisticated, environmental planning of the city on the one hand, and the reductions and simplifications of City Marketing representations on the other. Finally, we argue that there are inherent contradictions in marketing a sustainable city, where both in terms of tourism and economic development, the concept of growth seems to be reaching environmental limits.

The stage of a super-early scale-invariant Universe is considered on the basis of the Poincaré–Weyl gauge theory of gravity in a Cartan–Weyl space-time. An approximate solution has been found that demonstrates an inflationary behavior of the scale factor and, at the same time, a sharp exponential decrease in the effective cosmological constant from a huge value at the beginning of the Big Bang to an extremely small (but not zero) value in the modern era, which solves the well-known “cosmological constant problem”.

This paper reports 2 × 4 hybrid Mach-zehnder interferometer (MZI) - multi-mode interferometers (MMI) based compact thermo-optical switch consisting of slab waveguides on silicon-on-insulator, SOI, platform. The device consists of two identical MMIs, each of 6 μm wide and 140 μm long connected with two phase shifters MMIs each with 2 μm wide and 8 μm long and linear tappers each 4 μm long, connected at both ends of the MMIs to minimize the power coupling loss. The loss for linear taper is found to be below 0.02dB. The footprint of the whole device is six 6 μm × 324 μm. This structure is based on unique multimode region shape, which leads optical switch to have less coupling loss and reduced cross-talk. The average thermo-optical switching power consumption is 1.4 mW, the excess losses are 0.8 dB, and the imbalances are 0.1 dB. Aluminum is used as a heating pad, and a trench is created around this pad to prevent from spreading of heat and reduce power loss almost by a factor of 2 to the adjacent phase shifter. Our new heating method has advantages of compact size and ease of fabrication with the current CMOS technology.

A compact Mach-zehnder interferometer with a novel design of directional couplers and a phase shifter has been presented as a thermo-optical sensor. With the aim of reducing device size to micro and nano dimension silicon-on-insulator technology was employed. That allowed miniaturization of device size through the reduction of its cross sectional area to 0.066 µm² and the radius of curvature of both the arms of the directional coupler and S-bends of the phase shifter to 5 µm and C-bends to 3 µm. These nano size device dimensions made it possible to reduce the coupling gap to 0.2 µm, which resulted in a significant reduction in the coupling length. The device geometry and its performance characteristics were analyzed and optimized using coupled mode analysis and finite difference time domain simulation tools, respectively. The wavelength dependent transmission loss of the device was measured at different temperature to verify and validate its performance characteristics. Tested devices showed a remarkable temperature dependent transmission characteristic offering significant changes in transmission loss band – with as low as 0.45 ⁰C change in substrate temperature. The extinction ratio and the free spectral range of the device were 26 dB and 0.26 nm respectively in the wavelength range of 1549.5 nm – 1550.5 nm. These results imply that the devices presented here can be used as compact and highly sensitive thermal sensors and optical switches.

In polymer-based dental composites, wear is a three-body wear system mainly abrasive, because of the food particles and wear products suspended in the oral cavity, which are transferred to the microcavities of the surface of the replacements. Due to this fact, the incorporation of nanodiamond as reinforcement in these polymer matrix composites, which promotes the creation of a solid lubricant tribofilm surface could be advantageous. When nanodiamond is added in contents of 0.8, 1.6 and 3.2 wt %, an increase in microhardness from 95 up to 420 %, compared to the one of neat BisGMA/TEGDMA, is observed. Additionally, the incorporation of a content of 1.6 wt % is enough to cause a diminution of ~78 % in the friction coefficient and a reduction of the specific wear rate and Archard’s coefficient of ~50 %. Nevertheless, the addition of relatively high contents reduces the effectiveness of photoinitiation and UV-curing, which is related to the scattering and absorption of UV radiation by ND.

This paper reports design of a 2 × 4 hybrid multimode interferometer-Mach-zehnder interferometer (MMI-MZI) configuration and compact thermo-optical switch consisting of slab waveguides on the silicon-on-insulator (SOI), platform. The device consisted of two identical MMIs as power splitters and couplers that are connected with two identical MMI-based phase shifters, and linear tapers at both ends of the MMIs to minimize the power coupling loss. A thin Al pad is used as a heating element, and a trench is created around this pad to prevent heat from spreading and to minimize loss. The calculated average thermo-optical switching power consumption, excess loss, and power imbalance are 1.4 mW, 0.9 dB, and 0.1 dB, respectively. The overall footprint of the device is 6 × 304 μm². The new heating method has advantages of compact size, ease of fabrication on SOI platform with the current CMOS technology, and offers low excess loss and power consumption as demanded by devices based on SOI technology. The device can act as two independent optical switches in one structure.

We evaluate the complexity of Colombian climate from extreme behavior of gauge temperature and precipitation, using the the novel Tsallis' non-extensive entropy principle based on physical information through the q-index. We find the spatial structure of non additive universal categories (q-index) and compare with some complex systems with the potential to have some degree of dynamical affinity. Our results evidence the great dynamical variability of regional climate expressed in the large range of values of $q$-index, and the high degree of non-extensitivity for both temperature and precipitation.

A series of Eu³⁺ doped CaSiO₃/SiO₂ nano-phosphor powder of controlled grain size, crystalline structure, and chemical composition were synthesized using the microemulsion technique. XRD profiles of samples sintered over 600 of suggested phase shift from amorphous powder grain to more ordered polycrystalline powder of triclinic type wollastonite, CaSiO₃, with preferred crystal phase orientation of (112) and tetragonal type cristobalites of SiO₂. The grain size, crystallinity, and chemical composition of the host matrix, activator and sensitizer strongly affected both the absorption and emission bands of these samples. The amplitude of both the orange and red emission bands significantly increased with sintering temperature. The emission band is red-shifted with decreasing grain sizes. These bands displayed good sensitivity to ionic concentration of the Si⁴⁺, Ca²⁺, and Eu³⁺. With increasing Ca²⁺ ion concentration both the intensity of the red photoluminescence (PL) band increased and a concentration quenching observed. Increase in Si⁴⁺ ion concentration led to quenching in PL intensity of both the orange and red bands whereas the amplitude of the blue-band slightly increased. With increasing Eu³⁺ ion concentration the red-band initially increased whereas it started decreasing at higher sample concentration. In the presence of Ca²⁺ ion as a sensitizer, the sample showed a remarkable PL property—including—about 100% photon conversion efficiency and a two-fold increase in excitation and emission photons.

Determination of the presence in the blood of antibodies specific to the causative agent of a particular disease (serodiagnosis) is an effective approach in medical analytical chemistry. Serodiagnostics performed in the lateral flow immunoassay format (immunochromatography) meet the modern requirements for point-of-care testing and are supported by existing technologies of large-scale diagnostic tests production—thus raising increased attention in a tense epidemiological situation. For traditional lateral flow serodiagnostics formats, a large number of nonspecific immunoglobulins in the sample significantly reduces the degree of detectable binding. To overcome these limitations, an assay based on the formation of immobilized antigen— specific antibody—labeled antigen complexes detection was proposed. However, the requirements for its implementation, providing maximum sensitivity, have not been established. This article describes the mathematical model for the above assay. The influence of the ratio of reagent concentrations on the analysis results is considered. It is noted that the formation of specific antibody complexes with several labeled antigens is the main limiting factor in reducing the detection limit, and methods are proposed to minimize this factor. Recommendations for the choice of the assay conditions, following from the analysis of the model, are confirmed experimentally.

Multiple drugs administration is a common practice in hospitals and clinics. This is the case when heavy pathologies are treated. In this context, frequently, antivirals and antibiotics are co-administrated either simultaneously or sequentially ignoring potential incompatibilities. In this study, we focused on an antiviral (Acyclovir) and an antibiotic (Ciprofloxacin) compatibility/incompatibility when they co-administrated with special interest on the effect of drugs ratio, pH and delay. By implementing robust HPLC method, we determined the main factors leading to potential modification of concentration of one of the two drugs in the mixture. The results showed that acyclovir is quantitatively recovered in all conditions related to pH, concentration and time (up to 24 hours). However, ciprofloxacin is strongly altered in acidic and basic conditions, the quantity of ciprofloxacin and time after mixing the two drugs. The most valuable piece of information is that the ratio of acyclovir/ciprofloxacin is crucial. The latter should be calculated and managed to provide at least two fold quantity of acyclovir versus ciprofloxacin in order to maintain the administrated doses and warrant efficient therapeutic effect.

This study investigates the valorization potential of yellowfin tuna tails for the production of high-value commercial products. Muscle and skins were firstly mechanically separated by using a specifically designed device. The muscle was then used as a nitrogen source for the growth of the proteolytic enzymes-producer Bacillus subtilis, whereas the skins were employed for gelatin extrac-tion. The proteases from Bacillus subtilis were partially purified and used to produce antioxidant peptides from gelatin obtained. The gelatin obtained formed a gel upon cooling, with gelling and melting temperatures at 16 ºC and 22 ºC, respectively, and Bloom Strength of ≈ 160. RSM was used to determine the optimal hydrolysis conditions to obtain the highest antioxidant activity (35.96%, measured as DPPH radical scavenging activity), which were 50°C / 6.5 IU of enzyme. The findings emphasize the importance of an integrated approach to maximize the value of tuna by-products, promoting sustainability in the frame of circular bioeconomy. Overall, these results contribute to the efficient utilization of tuna by-products, waste reduction, and enhance economic viability of the tuna industry.

Raman spectra of [TeX6](Y2) (X, Y - Cl, Br, I) were recorded in the temperature range 5-300 K. The vibration frequency of molecular halogens as function on temperature and the type of halogen X- in the [TeX6]2- complex was obtained. The vibration frequency of the molecular halogen Y2 depends on the type of halogen X- complex [TeX6]2- The temperature dependence of the Y2 frequency is anomalous compared to what was expected for a conventional anharmonic oscillator. It is shown that the interpretation of the experimental results based on the concept of traditional chemical bonding is quite satisfactory in all cases. The study was motivated by the need to consider the mechanism of interaction in the X-Y2 contacts.

The problem of effective immobilization of liquid radioactive waste (LRW) is key to the successful development of nuclear energy. The possibility of using magnesium potassium phosphate (MKP) compound for LRW immobilization on the example of nitric acid solutions containing actinides and rare earth elements (REE), including high level waste (HLW) surrogate solution is considered in the research work. Under the study of phase composition and structure of the MKP compounds obtained by the XRD and SEM methods, it was established that the compounds are composed of crystalline phases - analogues of natural phosphate minerals (struvite, metaankoleite). The hydrolytic stability of the compounds was determined according to the semi-dynamic test GOST R 52126-2003. Low leaching rates of radionuclides from the compound are established, including a differential leaching rate of ²³⁹Pu and ²⁴¹Am - 3.5 × 10^-7 and 5.3 × 10^-7 g/(cm²∙day). As a result of the research work it was concluded that the MKP compound is promising for LRW immobilization and can become an alternative material combining the advantages of easy implementation of the technology like cementation and the high physical and chemical stability corresponding to a glass-like compound.

In the mean-field approximation, the well-known effect of the critical quantum collapse in a 3D gas of particles pulled to the center by potential U(r) = -U_0/(2r^2) is suppressed by repulsive interparticle interactions, which create the otherwise non-existing s-wave ground state. Here, we address excited bound states carrying the angular momentum, with the orbital and magnetic quantum numbers, l and m. They exist above a threshold value of the potential's strength, U_0 > l(l+1). The sectoral, tesseral, and zonal modes, which correspond to m = l, 0 < m < l, and m = 0, respectively, are found in an approximate analytical form for relatively small values of U_0 - l(l + 1). Explicit results are produced for the p- and d-wave states, with l = 1 and 2, respectively. In the general form, the bound states are obtained numerically, confirming the accuracy of the analytical approximation.

We generalize the dynamical analog of the Berry geometric phase setup to the quaternionic model of Avron et al. In our dynamical quaternionic system, the fast half-integer spin subsystem interacts with a slow two-degrees-of-freedom subsystem. The model is invariant under the 1:1:2 weighted SO(2) symmetry and spin inversion. There is one formal control parameter in addition to four dynamical variables of the slow subsystem. We demonstrate that the most elementary qualitative phenomenon associated with the rearrangement of the energy super-bands of our model consists of the rearrangement of one energy level between two energy superbands which takes place when the formal control parameter takes the special isolated value associated with the conical degeneracy of the semi-quantum eigenvalues. This qualitative phenomenon is of the topological origin, and is characterized by the second Chern class of the associated semi-quantum system. The correspondence between the number of redistributed energy levels and the second Chern number is confirmed through a series of examples.

Nicotiana benthamiana plants infected with a potato virus Y isolate (PVYO) under ambient conditions of 25 °C and ~405 parts-per-million (ppm) ambient CO2 display symptoms of chlorosis, leaf curling, and stunting. However, under elevated temperature and CO2 levels (30 °C, 970 ppm), systemic viral titers decrease several-fold, and plants appear asymptomatic. Under the latter conditions we have studied how infection, drought, or both combined affect infection, drought-driven loss of leaf turgor, plant water content, stomatal conductance, metabolome, and hormone (ABA, SA, and JA) levels. We found that drought did not affect viral titers. As expected, drought decreased plant water content and stomatal conductance. Under drought conditions, infection did not alter significantly final water content or loss of leaf turgor progression, but it increased the levels of some sugars and other osmo-protectants. Infection and drought altered the levels of many components of the metabolome. Some components altered by infection were not altered by drought, but most of those altered by drought were also altered by infection. Drought increased the levels of ABA, infection increased the levels of ABA, SA, and JA, and altered their relative balance. The effects of drought and of infection on hormone levels were cumulative when combined. Thus, under ambient conditions that turn a severe infection into an asymptomatic one both, plant physiology parameters and the interplay with drought are affected.

Drug hypersensitivity reactions (DHR) to platinum-based compounds (PC) are on the rise, and their personalized and safe management is essential to enable first-line treatment of these cancer patients. This study aimed to evaluate the usefulness of basophil activation test by flow cytometry (BAT-FC) and the newly developed sIgE-microarray and BAT-microarray in diagnosing IgE-mediated hypersensitivity reactions to PC. 24 patients with DHR to PC (20 oxaliplatin and four carboplatin) were evaluated: 13 patients diagnosed as allergic with positive skin tests (STs) or drug provocation tests (DPTs), six patients diagnosed as non-allergic with negative STs and DPTs, and five patients classified as suspected allergic because DPTs could not be performed. In addition, four carboplatin-tolerant patients were included as controls. BAT-FC was positive in 2 of 13 allergic patients, with a sensitivity of 15.4% and specificity of 100%. However, the sIgE- and BAT-microarrays were positive in 11 of 13 DHR patients, giving a sensitivity of over 84.6% and a specificity of 90%. Except for one patient, all samples from the non-allergic and control group were negative for the sIgE- and BAT-microarrays. Our experience indicates that sIgE- and BAT-microarray could be helpful in the endophenotyping of IgE-mediated hypersensitivity reactions to PC and may provide an advance in decision-making for drug provocation testing.

Photobiomodulation (PBM) is a procedure that uses light to modulate cellular functions and bio-logical processes. Over the past decades, PBM has gained considerable attention for its potential in various medical applications due to its non-invasive nature and minimal side effects. This narrative review article examines the existing literature on PBM, encompassing research studies, clinical trials, and technological developments. This review highlights the mechanisms of action underlying PBM, including the interaction with cellular chromophores and the activation of in-tracellular signaling pathways. The evidence from clinical trials and experimental studies to evaluate the efficacy of PBM in clinical practice is summarized with a special emphasis on der-matology. Furthermore, advancements in PBM technology, such as novel light sources and treat-ment protocols, are discussed in the context of optimizing therapeutic outcomes and improving patient care. This narrative review underscores the promising role of PBM as a non-invasive therapeutic approach with broad clinical applicability. Despite the need for further research to develop standard protocols, PBM holds great potential for addressing a wide range of medical conditions and enhancing patient outcomes in modern healthcare practice.

This paper addresses the study of synoptic-scale meteorological conditions that favor long-range pollen transport in southern South America combining airborne pollen counts, modeled three-dimensional backward trajectories, and synoptic and surface meteorological data. Alnus pollen transport trajectories indicate origins predominantly in Montane forests of the Yungas between 1500 and 2800 m altitude. The South American Low-Level Jet is the main meteorological feature that explains 64\% of the detected pollen arrival at the target site. Podocarpus and Nothofagus pollen instead are linked primarily to the widespread Subantartic forests in southern Patagonia. Their transport patterns are consistent with previous studies which show an association with synoptic patterns related to cold front passages carrying pollen in the free atmosphere (27% for Nothofagus and 25% for Podocarpus). These results show the significance of understanding long-distance pollen transport for disciplines such as climate change reconstruction and agriculture, emphasizing the need for further research to refine atmospheric circulation models and refine interpretations of past vegetation and climate dynamics.

The reliable online analysis of volatile compounds in exhaled breath remains a challenge as a plethora of molecules occur in different concentration ranges (i.e. ppt to %), and need to be detected against an extremely complex background matrix. While this complexity is commonly addressed by hyphenating a specific analytical technique with appropriate preconcentration and/or preseparation strategies prior to detection, we herein propose the combination of three analytical tools based on truly orthogonal measurement principles as an alternative solution: field-asymmetric ion mobility spectrometry (FAIMS), Fourier-transform infrared (FTIR) spectroscopy-based sensors utilizing substrate-integrated hollow waveguides (iHWG), and luminescence sensing (LS). These three tools have been integrated into a single compact analytical platform suitable for online exhaled breath analysis. The analytical performance of this prototype system was tested via artificial breath samples containing nitrogen (N2), oxygen (O2), carbon dioxide (CO2) and acetone as a model volatile organic compound (VOC) commonly present and detected in breath. Functionality of the combined system was demonstrated by detecting these analytes in their respectively breath-relevant concentration range and mutually independent of each other generating orthogonal yet correlated analytical signals. Finally, adaptation of the system towards the analysis of real breath samples during future studies is discussed.

A comparative study of the photocatalytic decoloration of methylene blue (MB) dissolved in water was conducted, using three semiconductor oxides: zinc oxide (ZnO), tin oxide (SnO2) and titanium dioxide (TiO2) in the form of thin films and varying their thickness ~ 100, 200, and 300 nm for each film. All the films were deposited using the cost-effective dip-coating technique, at moderate temperature processing (400 °C) with sol-gel solutions on cheap glass substrates. The structural, morphological, and compositional properties of the films were analyzed by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Raman spectroscopy, respectively. The degradation of MB was studied by varying both thickness and type of semiconductor oxides through measurements of optical absorbance of decolorated liquid by photocatalytic process. Structural analysis shows that ZnO and SnO2 films were polycrystalline with preferential growth of (002) and (110) planes respectively, whereas, an amorphous structure was observed for TiO2 films. In addition, morphological properties confirms that the surfaces of all the films are conformed with nano grains in round and irregular shapes. Based on all results reported in this work, that authors believe that the degradation efficiency of MB depends on the thickness of the film and the type of semiconductor material used as a catalyst. The highest degradation efficiencies were recorded with an exposure time of 120 min and with an initial concentration of 10 mg/L for ZnO, SnO2, and TiO2 films were: 100, 88 %, and 76 %, respectively.

In order to search possible residual minor phases in Y-Ba-Cu-O family, powdered mixtures of Y₂O₃ + BaCO₃ + CuO and, independently, superconducting compound YBa₂Cu₃O_7-x have been treated in evacuated cells and elevated temperatures.YBa₂Cu₃O_7-x was reduced to YBa₂Cu₃O₅ by use of the special home designed Taconis-Knudsen vacuum device. A subsequent doping by oxygen converts produced insulator YBa₂Cu₃O₅ to semiconductor or metal YBa₂Cu₃O_5+x (0<x<0.3). In addition to YBa₂Cu₃O₅, 0.05 volume percent of the minor delafossite phase Y₂Cu₂O₄ was being spotted in the powder mixture 1/2 Y₂O₃ + 2BaCO₃+6Cu₂O, heated up to 818 °C in an inert gas atmosphere. An attempt to prepare the insulating bulk delafossite samples was successful, and subsequent doping by oxygen produces novel metallic phases.

This study evaluates audiogenic epilepsy in Krushinsky-Molodkina rats using a wireless EEG system to overcome the limitations of traditional methods that restrict animal movement. Nine male KM rats, prone to audiogenic seizures, were implanted with electrodes in areas critical for seizure activity (inferior colliculus, ventrolateral periaqueductal gray, dorsal area of the secondary auditory cortex, and motor cortex). This setup allowed for the observation of seizures without movement restriction. Results showed that targeted neural intervention via electrode implantation reduced the intensity of convulsive seizures in half of the subjects, suggesting a potential therapeutic approach. The severity of seizures was influenced by the pre-phonostimulation EEG background activity in specific brain regions, identifying them as key in the genesis and generalization of seizures. Observations of dual generalized seizure waves and induced hyperkinesis challenge conventional epilepsy models and suggest new directions for research and therapy development.

There are important challenges for modeling large electrical distribution circuits, even more with the presence of distributed renewable generation. Constructing simulations for assessing the effect of the penetration of distributed generation on electrical distribution networks has become of great importance for Distribution Network Operators (DNOs). This paper proposes a simulation strategy based on open-source platforms and the integration of scripting tools for the rapid modeling of large-scale electrical distribution circuits with distributed renewable generation. The implementation is based on the adaptation of a tool called QGIS2OpenDSS, which creates OpenDSS distribution network models directly from an open-source geographic information system, QGIS. The plugin’s capabilities are demonstrated using a real distribution feeder with more than 60% penetration of renewable generation based on photovoltaic systems. These simulations are carried out using real data from a circuit provided by a DNO in the Dominican Republic, which is used to demonstrate how this approach provides a more accessible and flexible way to simulate and assess the effect of Distributed Energy Resources (DERs) in Medium Voltage (MV) and Low Voltage (LV) networks, enabling utilities to evaluate system performance and identify potential issues.

A new data processing method based on Machine Learning (ML) algorithms has been developed and tested in clinical environments during COVID-19 trials at the Medical University of South Carolina (MUSC). Breath samples have been collected in 2020–2021 from 100 participants using gas chromatography combined with ion mobility spectrometry (GC-IMS, G.A.S. mbH). Polymerase chain reaction (PCR) tests combined with clinical diagnostics were used as a reference method. Once the ML training-testing cycle is completed, the diagnostics of a single data set may be completed in as little as a few seconds. A convincing difference in the Volatile Organic Compounds (VOS) breath biomarker signature with COVID-19 positive and negative participants has been found. This approach is a generic method that can be applied to data sets collected with other types of hardware, e.g., different settings of GC, GC-MS, GC-GC, or other methods providing high information density in 2-dimensional data sets.

The research aims to present an innovative methodology to execute the Heritage conservation processes in a collaborative and interdisciplinary BIM project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with the architectural survey using scanning techniques (TLS) and terrestrial photogrammetry (SfM) and taking as a study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the post-processing software, and which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it has been possible to develop an efficient Scan-to-HBIM workflow, where the Heritage-BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural and artistic heritage, focusing on the deformations and deterioration of the masonry in columns, and making multidisciplinary conservation work in an HBIM project more flexible. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment.

The links between mindfulness, savoring positive experiences, and depressive symptoms have been well-established in the literature. Nevertheless, little has been done to disentangle the prospective relations among these constructs. Clarifying the longitudinal relations is crucial, as it enables researchers and practitioners to discern potential trajectories of mental health interventions. In this study, 180 emerging adults between 18 and 27 years old were recruited twice at 3 months apart to complete self-reported measures including mindfulness, savoring positive experiences, and depressive symptoms. Cross-lagged path analysis indicated that savoring the moment was predictive of mindfulness three months later, whereas depressive symptoms were predictive of both mindfulness and savoring the moment three months later, above and beyond the effects of age, gender, and family income. Additionally, mindfulness, savoring positive experiences, and depressive symptoms were significantly correlated at baseline. The present study evidenced short-term inversed effects of depressive symptoms on mindfulness and savoring the moment, as well as a positive effect of savoring the moment on mindfulness. Hence, interventions gearing towards symptom reduction of depression are likely to carry concurrent and prospective benefits of psychological functioning, namely the ability to be present in the moment and to savor. Taken together, reducing depressive symptoms may be crucial in fostering psychological well-being.

Gut bacteria play an important role in several metabolic processes and human diseases, such as obesity and its co-morbidities, like fatty liver disease, insulin resistance/diabetes and cardiovascular events. Among several factors, dietary patterns, probiotics, prebiotics, synbiotics, antimicrobials and non-dietary factors, such as stress, age, exercise and climatic conditions, can dramatically impact the human gut microbiota diversity and equilibrium. However, the effect of minor food constituents, including food additives and trace contaminants, on human gut microbiota has received less attention. Consequently, the present review aimed to provide an objective perspective of the current knowledge regarding the impacts of minor food constituents on human gut microbiota and consequently, on human health.

Chromosomal rearrangements in N. gonorrhoeae and N. meningitidis were studied with the determination of mobile elements and their role in rearrangements. The results of whole-genome sequencing and de novo genome assembly for 50 N. gonorrhoeae isolates collected in Russia were compared with 96 genomes of N. gonorrhoeae and 138 genomes of N. meningitidis from the databases. Rearrangement events with the determination of the coordinates of syntenic blocks were analyzed using the SibeliaZ software, the minimum number of events that allow one genome to pass into another was calculated using the DCJ-indel model using the UniMoG program. Population-level analysis revealed a stronger correlation between changes in the gene order and phylogenetic proximity for N. meningitidis in contrast to N. gonorrhoeae. Mobile elements were identified, including Correa elements, Spencer-Smith elements (in N. gonorrhoeae), Neisserial intergenic mosaic elements, IS elements of IS5, IS30, IS110, IS1595 groups, Nf1-Nf3 prophages, NgoФ1-NgoФ9 prophages, Mu-like prophages Pnm1, Pnm2, MuMenB (in N. meningitidis). More than 44% of the observed rearrangements most likely occurred with the participation of mobile elements, including prophages. No differences were found between the Russian and global N. gonorrhoeae population both in terms of rearrangement events and in the number of transposable elements in genomes.

Potato virus Y (PVY) is one of the most important constraints to potato production worldwide. There is an increasing occurrence of recombinant PVY strains PVYNTN and PVYN-Wi and a decline in the incidence of the nonrecombinant PVYO. We hypothesized that this may be due to the ability of these recombinant strains to antagonize and/or outcompete PVYO in mixed infections. To deter-mine this, we investigated interactions between PVYO and three recombinant PVY strains com-mon in North America: PVYNTN, PVYN-Wi, and PVYN:O. Overall, our study showed that these inter-actions are tissue dependent. Specifically, PVYNTN, the main causal agent of potato tuber necrotic ringspot disease (PTNRD), was found to be more adaptable than PVYO, especially in potato leaves due, at least in part, to the Ny gene that confers hypersensitive resistance (HR) to PVYO. Further-more, PVYN-Wi was found to repress PVYO in potato tubers but act synergistically in potato leaves. The PVYO-induced foliage necrosis in cultivar ‘Ranger Russet’ was observed to be more severe in plants co-infected by PVYN-Wi and PVYN:O, respectively, resulting in plant death. Strikingly, this PVYO -induced necrosis was suppressed by PVYNTN in doubly infected plants. These interactions may, at least partially, explain the decreasing incidence of PVYO in United States potato produc-tion regions, especially given that many cultivars contain the Ny gene, which likely limits PVYO enabling PVYNTN and PVYN-Wi to outcompete. We also found that replication and cell-to-cell movement of these PVY strains in tubers at 4C was similar to levels at ambient temperature.

ZrO2-YO1.5-TaO2.5(ZYTO) composite ceramic is considered to be the candidate of next generation of thermal barrier coatings as its excellent thermal stability and low thermal conductivity in high temperature, however, the mechanical properties and fracture tougheness of ZYTO system may be the shortcomings compared with the 8YSZ. In this study, ZYTO composite ceramics were successfully prepared by chemical coprecipitation reaction, the microsture of resulting composites were studied as a function of doping of M-YTaO4. Mechanical properties, including the density, porosity, hardness and Young's modulus, are determinate; the toughening mechanism were verified by the crack growth behavior of Vickers indentation test Results suggested that M-YTaO4 refines the fluorite phase grain and strengthens the grain interface in the composite ceramic. The thermal mismatch between the second phase and matrix produces residual stress in the bulk and affects the crack propagation behavior. With the increase of M-YTaO4 doping, the grain coarsening and ferroelastic domains are observed in the experiments. The ferroelastic domains with orthogonal polarization directions near crack tip evidences the ferroelastic toughening mechanism. The competition among these crack behaviors, such as cracks deflection, bridging and bifurcation, dominates the actual fracture toughness of the composite. The best toughening formula is determinate in the two-phase region and the highest fracture toughness is about to 3.1MPa·m1/2. Above all, mechanical properties of ZYTO composite ceramics look potential for thermal barrier coatings materials.

Discovery of stable and broad frequency combs in monochromatically pumped high-Q optical Kerr microresonators caused by generation of temporal solitons can be regarded as one of the major breakthroughs in nonlinear optics during the last two decades. Transfer of the soliton-comb concept to χ(2) microresonators promises lowering of the pump power, new operation regimes, and entering new spectral ranges; scientifically, it is of a big challenge. Here we represent an overview of stable and accessible soliton-comb regimes in monochromatically pumped χ(2) microresonators discovered during the last several years. The main stress is made on lithium niobate based resonators. The overview pretends to be rather simple, complete, and comprehensive: It incorporates the main factors affecting the soliton-comb generation, such as the choice of the pumping scheme (pumping to the first or second harmonic), the choice of phase matching scheme (natural or artificial), the effects of temporal walk-off and dispersion coefficients, and also the influence of frequency detunings and Q-factors. Most of discovered nonlinear regimes are self-starting – they can be accessed from noise upon a not very abrupt increase of the pump power. The soliton-comb generation scenarios are not universal – they can be realized only under proper combinations of the above mentioned factors. We indicate what kind of restrictions on the experimental conditions have to be imposed to get the soliton-comb generation.

Stabilization of planar premixed flame front on a lattice (porous) burner is considered. It is rigorously mathematically proved that there exist two different stabilization regimes: one with flame front located nearby the surface of the burner, and another with flame front located inside the lattice. These two regimes result in qualitatively different gas temperature profiles along the flow, that is monotonic and non-monotonic, respectively. Boundary between the two regimes is described in terms of dependence of the lattice solid material temperature on flow Peclet number. Likewise temperature profiles, such dependencies may be both monotonic and non-monotonic. Transition between the two types of dependencies is controlled by Arrhenius number. Conclusions of the study are supported by numerical analysis. They also compare favourably with available experimental data. Novelty of the present approach is fundamentally rigorous analytical analysis of the problem.

Single particle tracking (SPT) is a powerful class of methods for studying the dynamics of biomolecules inside living cells. The techniques reveal the trajectories of individual particles, with a resolution well below the diffraction limit of light, and from them the parameters defining the motion model, such as diffusion coefficients and confinement lengths. Most existing algorithms assume these parameters are constant throughout an experiment. However, it has been demonstrated that they often vary with time as the tracked particles move through different regions in the cell or as conditions inside the cell change in response to stimuli. In this work, we propose an estimation algorithm to determine time-varying parameters of systems that discretely switch between different linear models of motion with Gaussian noise statistics, covering dynamics such as diffusion, directed motion, and Ornstein-Uhlenbeck dynamics. Our algorithm consists of three stages. In the first stage, we use a sliding window approach, combined with Expectation Maximization (EM) to determine maximum likelihood estimates of the parameters as a function of time. These results are only used to roughly estimate the number of model switches that occur in the data to guide the selection of algorithm parameters in the second stage. In the second stage, we use change detection (CD) techniques to identify where the models switch, taking advantage of the off-line nature of the analysis of SPT data to create non-causal algorithms with better precision than a purely causal approach. Finally, we apply EM to each set of data between the change points to determine final parameter estimates. We demonstrate our approach using experimental data generated in the lab under controlled conditions.

The paper deals with the navigation data exchange between two satellites moving in a swarm. It is focused on reduction of the inter-satellite demanded communication channel capacity taking into account dynamics of the satellites relative motion and possible erasing in the channel the navigation data. The feedback control law is designed ensuring regulation of the relative satellites motion. The adaptive binary coding/decoding procedure for the satellites navigation data transmission over the limited capacity communication channel is proposed and studied for the cases of ideal and erasure channels. Dependence of the regulation time on the data transmission rate is numerically evaluated. Results of the numerical study of the closed-loop system performance and accuracy of the data transmission algorithm on the communication channel bitrate and erasure probability are obtained based on the extensive simulations. These results provide dependence of the required load of the communication channel on the desired quality of the regulation process. It is shown that both data transmission error and regulation time depend inversely proportional on the communication rate, and that for the significantly high data transmission rate erasure of data in the channel with probability up to 0.3 does not make an effect on the regulation time.

The highly dangerous trend of escalating bacterial resistance to modern antibiotics has evolved in recent decades, with increasingly more drug-resistant strains of pathogens emerging and spreading each year. This poses a threat to not only public health, but also to entire mankind. Marine bioresources, considered as a promising alternative to traditional antibiotics and a valuable source of biologically active compounds with high pharmacological potential, now attract increasing attention of researchers. Modern biotechnology combines the genetic engineering methods and the unusual biosynthetic pathways utilized by marine microorganisms to produce natural antibiotics. The goal of this review is to summarize the latest trends in searching for new natural antimicrobial agents based on secondary metabolites of marine bacteria. The targeted control of biosynthesis mechanisms using the metabolic engineering methods in order to create hybrid peptide synthetases or to obtain hybrid peptides by disrupting the target gene of nonribosomal synthesis becomes a noteworthy trend in modern biotechnology. This pathway is not only one of the most promising approaches to the development of new antibiotics, but also a potential target for controlling the exocrine activity of pathogenic bacteria and, consequently, their viability.

Superconducting split ring resonator arrays allow to overcome two main limitations affecting metallic metamaterial resonating in the Terahertz (THz) range: Ohmic losses and tunability of their optical response. In this work, we design and experimentally realize direct and complementary square arrays of superconducting YBa2Cu3O7 (YBCO) split ring resonators working in the THz spectral range. The main purpose of this paper is to show how the metamaterial resonances can be tuned by temperature (T) when crossing the superconducting transition temperature Tc of YBCO. The tuning property can be quantified by describing the THz transmittance of the patterned YBCO films vs. T through a model of coupled resonators. This model allows us to estimate the THz resonances of split-ring arrays and their interaction, showing how the kinetic inductance Lk in the superconducting state is the main parameter affecting the metamaterial properties.

Adaptation to the impacts of human induced global heating is inevitable. For a socially just and ecological sustainable adjustment to these new circumstances, we need to draw from diverse knowledge systems while, simultaneously, foster a social-ecological transformation. We approach these concerns through the concept of community-based adaptation (CBA) and discuss remedies. Synergies with feminist knowledge systems and indigenous ways of living show the transdisciplinary essence of CBA. By abstracting from its origin and overlapping disciplines, revealing the social metabolism as a common problem, CBA is prone to achieve more equitable and sustainable adjustments. Transdisciplinarity itself and the current related CBA literature point beyond mere adjustments and call for a redesign of the social metabolism, thereby shifting from adaptation to global heating towards adaptation with nature by focusing on social provisioning. An engagement with transformative adaptation and heterodox economics further shows the potential of CBA to serve as an instrument in support of a social-ecological transformation by addressing root causes of vulnerability and by fostering epistemic justice. Reflecting these points back on the epistemological and ontological assumptions of CBA, the viewpoint proposes critical realism as a guiding philosophy of science to move forward.

This paper presents results of the magnetic dynamics study (the microwave power absorptions at the fixed frequencies, during magnetic field sweeping) in samples of Y3Fe5O12 single crystals in the form of plates and spheres of various sizes, at frequencies exceeding 30 GHz, in magnetic fields up to 18 kOe, at room temperature and T=77 K. It was found, that in this case, the inhomogeneity’s of the magnetic state manifested itself in the Y3Fe5O12 samples in as 2D local phase separation regions. These 2D phase separation regions formed inside domain walls representing superlattices with size’s 700 – 900 Å. Landau diamagnetism or de Haas van Alphen oscillations observed in the 2D phase separation regions at room temperature and T=77 K, depending on the shape and size of the studied plates and spheres.

The wellbeing of the honey bee colonies and the health of humans are connected in numerous ways. Therefore, ensuring the well-being of bees is a crucial component of fostering sustainability and ecological harmony. The colony collapse disorder (CCD) phenomenon was first reported in 2006 when majority of bee colonies in Europe died out, due to increase of diseases infections, contamination of hive with agrochemical pesticides and persistent organic pollutants (POPs). Only 6 years after CCD intimation, about 7 million premature deaths were reported, due to the air pollution to which humans are continuously exposed. The use of insect species, such as honey bee Apis mellifera L. and air matrix inside the bee hive can be used as a tool in biomonitoring, instead of traditional monitoring methods. This may have advantages in terms of cost-effective bioindicators of the environmental health status, showing the ability to record spatial and temporal pollutant variations. In this study, we present the in-field use of the portable membrane inlet mass spectrometry (MIMS) instrument for instant and effective determination of the level of environmental pollution by analytical identification of hive atmosphere volatile organic compound (VOCs) contaminants, contained in polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), monocyclic aromatic hydrocarbons (BTEX) compounds and pesticides. The samples will be taken from hives which are located in urbanized and rural regions, where further differences in contamination will be highlighted. The MIMS results will be benchmarked against a conventional laboratory sampling technique such as GC-MS.

This study provides a comprehensive investigation of lactic acid bacteria (LAB) isolated from Argentinean Capsicum annum L. The research covers important aspects, including genotypic characterization, bacterial stress tolerance, adhesion ability, safety evaluation, and functional and technological properties. The predominant isolates were identified as Lactilactobacillus curvatus and Lactiplantibacillus plantarum. Rep-PCR analysis grouped the isolates into 11 clonal groups. Lp. plantarum LVP 40 and LV 46; Levilactobacillus brevis LVP 41, Pediococcus pentosaseus LV P43, and Lt. curvatus LVP44, displayed both safety and resilience against adverse conditions such a slow pH, bile, and simulated gastric and intestinal juices. Moreover, the LAB strains exhibited high hydrophobicity and auto-aggregation percentages, NaCl tolerance, and substantial acidifying capacity. LAB supernatants demonstrated promising surfactant and emulsifying properties. Likewise, they differentially inhibited Staphylococcus aureus and Pseudomonas aeruginosa biofilms, showcasing their potential as antipathogenic agents. Noteworthy some strains displayed considerable co-aggregation with these pathogens, and several isolates showed an effective antimutagenic and detoxifying power, further emphasizing their multifaceted capabilities. Five pepper bacterial strains showcased probiotic properties, suggesting their potential for gut health enhancement. In summary, these LAB strains hold promise as vegetable fermentation starters, contributing to food safety and versatile applications in food science.

This review was written with the aim of examining the effects that caused an insult such as a wound to an organ such as the skin. Before examining the cellular mechanisms relating to wound healing, the reader is invited to read the structure of the skin as a necessary basis for understand-ing the final aim of this review. The structure of the skin as a basis for understanding the phe-nomena relating to wound healing is addressed taking into account updated literature that ad-dresses the numerous problems of the skin microenvironment. Starting from this awareness, the paragraph dedicated to wound healing becomes complicated when this phenomenon is not im-plemented and therefore the problems dedicated to chronic wounds, keloids and hypertrophic scars are addressed, pathologies that are still difficult to understand and treat today.

The growing population in Yucatan has led to the expansion of construction in the Mayan jungle for tourist spaces, residential areas, and agriculture. Recently, rabies cases in cats (Felis catus) have increased. This study aimed to perform the antigenic and genetic characterization of the RABV and to try to identify factors contributing to the increased transmission of rabies virus from wildlife to cats in the State of Yucatan. The ArcGIS software was employed to generate maps depicting the geographic locations of rabies outbreaks in cats. A mixed-effects Poisson regression model was applied to investigate the association between cat rabies cases and sociodemographic and ecological variables. A total of nine feline rabies cases occurred, three antigenic variants were detected: RVV1 (n=1); (RVV3) (n=1), and the canine-originated atypical variant (n=7). Rabies cases were spatially distributed at the urban-jungle interface, which may favor contact between cats and wildlife. No statistically significant associations with sociodemographic/ecological variables were observed. Urban areas with low (0-2%) to moderate (2-4%) changes in land cover showed a substantial increase in the probability of feline rabies cases. This study highlights the concerning resurgence of rabies infections in cats, emphasizing the looming threat of its reintroduction in dogs should vaccination rates diminish. The genetic affinity between the atypical variant and the canine virus underscores the urgent need for vigilance in maintaining high vaccination coverage across all susceptible species.

Residual stress (RS) is the most challenging problem in metal additive manufacturing (AM) since the build-up of high tensile RS may influence the fatigue life, corrosion resistance, crack initiation, and failure of the additively manufactured components. While tensile RS is inherent in all the AM processes, fast and accurate prediction of stress state within the part is extremely valuable and would result in optimization of the process parameters in achieving a desired RS and control of the build process. This paper proposes a physics-based analytical model to rapidly and accurately predict the RS within the additively manufactured part. In this model, a transient moving point heat source (HS) is utilized to determine the temperature field. Due to the high temperature gradient within the proximity of the melt pool area, material experience high thermal stress. Thermal stress is calculated by combining three sources of stresses known as stresses due to the body forces, normal tension, and hydrostatic stress in a homogeneous semi-infinite medium. The thermal stress determines the RS state within the part. Consequently, by taking the thermal stress history as an input, both the in-plane and out of plane RS distributions are found from incremental plasticity and kinematic hardening behavior of the metal by considering volume conservation in plastic deformation in coupling with the equilibrium and compatibility conditions. In this modeling, material properties are temperature-sensitive since the steep temperature gradient varies the properties significantly. Moreover, the energy needed for the solid-state phase transition is reflected by modifying the specific heat employing the latent heat of fusion. Furthermore, the multi-layer and multi-scan aspects of metal AM are considered by including the temperature history from previous layers and scans. Results from the analytical RS model presented excellent agreement with XRD measurements employed to determine the RS in the Ti-6Al-4V specimens.

Sustainable development has become the aspiration of many developing countries, including Ecuador. The introduction of Bachelor of Tourism studies at the Technical University of Manabí aligns with this interest, implying a challenge for teachers regarding the application of integrative and innovative teaching methods that promote the training of professionals with high scientific rigor, both in technical and professional senses. To achieve this, the pedagogical group started from three fundamental principles based on the application of teaching work methods and pro-cedures, as well as the determination of interactions between the various factors that directly and indirectly influence the training process of professionals in the tourism sector. The results of comprehensive evaluation processes considering both the academic performance of the teachers and the level of satisfaction of students taking the course support the application of these teaching–learning methods, as well as highlighting the convenience of extending the experiences and re-search results of the pedagogical team to other vocational training centers for tourism activities.

Vanadium(IV) chalcogenide materials are of increasing interest for use in catalysis and energy conversion-related applications. Since no ternary compounds are yet known in the V–Se–Te system, we studied ternary VwSeyTe2–y (w = 1.10, 1.13; y = 0.42, 0.72) phases crystallizing in space group P3m1 (no. 164). Two single-crystal specimens with differing compositions of a solid solution were obtained using the ceramic method. All products were characterized by either single-crystal or powder X-ray diffraction. The lattice parameters increase with rising tellurium content in accordance to the larger ionic radius of the tellurium anion compared to selenium. The chemical compositions were confirmed by energy dispersive X-ray spectroscopy. Further, magnetic measurements revealed mostly antiferromagnetic properties. Simultaneous differential scanning calorimetry/thermogravimetric analyses in nitrogen atmosphere showed endothermic decomposition accompanied by the formation of VN. The results of this work can serve as a basis for the synthesis of new phases in the V–Se–Te and related vanadium chalcogenide systems.

A single-crystal of ytterbium-doped “mixed” yttrium-lutetium aluminium garnet with a stoichiometric composition of (Y0.601Lu0.233Yb0.166)3Al5O12 was grown by the Czochralski method and its structure, vibronic, spectroscopic and laser properties were studied. The stimulated-emission cross-section for Yb3+ ions was maximized to 2.53×10-20 cm2 at 1031 nm, the emission bandwidth is ~8 nm and the reabsorption-free luminescence lifetime of the 2F5/2 state is 1.063 ms. Pumped at 941 nm, the Yb-laser generated a maximum output power of 1.04 W at 1.03 and 1.05 μm with a high slope efficiency of 76.4% and a laser threshold of 76 mW. A continuous wavelength tuning over a range of 51.6 nm (1026.4 - 1078.0 nm) was also achieved. Power scaling is achieved using a 969 nm-diode pumped microchip cavity. A maximum output power of ~9 W is obtained at 1.05 μm with a slope efficiency of 76% and with an almost circular laser beam profile.

Compared to tin lead alloys, lead-free tin alloys have lower toxicity, making them more widely used. In this study, Sn-20Bi-0.3Al-xY solders alloys were prepared. The effects of the addition of Y on its microstructure, micro-hardness, wettability and mechanical properties was investigated. The result showed that the addition of Y had significant effect on the refinement of Sn-20Bi-0.3Al-xY. From the spreading tests results, Y increased the wettability of the solders, however when the fraction of Y gradually increased, the wettability reduced. The ultimate tensile and hardness of Sn-20Bi-0.3Al-xY solders alloys were increased as the content of Y increasing.