Software Package Research Articles

Взаимосвязь окружной скорости и потерь энергии в проточной части центростремительной турбины с частичным облопачиванием рабочего колеса

Low-consumption turbomachines are devices that play an important role in the drive of various units in the field of shipbuilding, aircraft engineering and other branches of heavy engineering. They have some advantages over a high-average power turbine. The largest number of low-consumption turbomachines are made partial, i.e. with partial intake. The principle of a turbine with partial flapping of the impeller is considered as one of the types of partial turbomachines. The influence of the main velocity characteristic of the turbine stage on the loss of kinetic energy in the stage is investigated. The simulation of gas dynamic processes occurring in the turbine stage was carried out using the ANSYS Workbench software package. With the help of this complex, a three-dimensional geometric model of the turbine stage with varying degrees of impeller damping was created. By applying the finite element method, a computational grid, a computational model are generated, and boundary conditions of a numerical experiment are set. The result of the numerical experiment is graphs of the dependence of kinetic energy loss on the circumferential velocity (speed characteristics of the turbine stage). This dependence can be represented not only graphically, but also with the help of mathematical apparatus. An example of such an apparatus is the polynomial dependence. The considered mathematical design can be used in order to optimize mathematical models of gas flow in the flow part of a low-flow turbine. Cubic two-parameter polynomials of kinetic energy losses in the flow part of the nozzle and impeller are obtained, and an assessment of its applicability in the current mathematical model is given.

Behavioural Study of Beam-Column Joint for Seismic Loading

Abstract: The seismic performance of Reinforced Concrete (RC) structures is a critical aspect of structural engineering, particularly in regions prone to seismic activity. This project presents a detailed study focusing on the behaviour of joints in RC structures following seismic events, utilizing the powerful computational tool ETABS. The primary objectives include understanding the response of joints under seismic loading, assessing their vulnerability, and proposing strategies for enhancing their seismic resilience. The study employs ETABS, a widely used software package for structural analysis and design, to simulate seismic actions on RC structures. Various types of joints, including beam-column joints and slab-column connections, are meticulously analysed under different seismic intensities and structural configurations. Through comprehensive analysis, the project aims to identify critical failure modes, such as shear failure, flexural failure, and joint sliding, and evaluate their impact on overall structural performance. Findings from this study contribute to the advancement of seismic design and retrofitting practices, offering insights into effective strategies for enhancing the seismic resistance of RC structures. The outcomes are valuable for engineers, researchers, and practitioners involved in earthquake engineering, providing essential knowledge for designing resilient structures capable of withstanding seismic hazards. This project underscores the importance of understanding joint behaviours in RC structures subjected to seismic loading, offering practical implications for improving structural safety and mitigating the impact of earthquakes on the built environment.

Кластеризация научных публикаций по морскому автономному надводному судовождению для выявления кластеров ключевых слов

An approach to structuring scientific publications is proposed using the example of scientific works on marine autonomous surface navigation, which allows for data mining with clustering and visualization of the main keywords and phrases related to the designated topic. The resource of the Russian scientific electronic library was used as a source for obtaining data eLIBRARY.RU. Information has been collected on 534 relevant scientific publications for the period from 2013 to the beginning of 2024, containing the title of the work, the year of publication, the list of authors and their affiliation, keywords and phrases, etc. A database for intellectual analysis has been formed, containing 1304 keywords or phrases indicated by the authors of scientific publications related to the selected topic. Data mining was performed using an open source software package for visualization and analysis of related data Gephi. The processing results are presented in the form of undirected graphs. The undirected graphs obtained are presented, and the characteristics of certain graphs for various kernel parameters are indicated. Clusters of keywords or phrases and connections between them have been identified, demonstrating current trends in the development of the chosen scientific field. With the advent of new scientific publications on marine autonomous surface navigation, the graphs will change, fixing new connections between the authors of scientific publications, key words and phrases. Such an approach to data processing may be useful for students, graduate students and researchers to identify a pool of keywords and phrases that need to be paid attention to when studying this topic.

Moats & comets - A methodology to explore for submerged prehistory at sea floor erosional features formed at artificial reefs, Atlantic continental shelf, GeorgiaUSA.

Our primary objective is to demonstrate a method that uses marine processes, principally seafloor scour, to broadly expose prehistoric landforms and associated localities. Too often, the loss of prehistoric strata to scour processes such as ravinement during broad-scale, continental shelf transgressions, are decried without the recognition of the potential for erosion at the local scale can expose those same strata for systematic study. The analysis of sea floor erosional features formed around artificial reefs by turbulent flows in the Georgia Bight have used interferometric side-scan sonar (SSS), Remotely Operated Vehicles (ROVs), ultra-high-definition videography (UHD), and sedimentological, palynological, paleontological, archaeological analytical techniques. These techniques were integrated within a geoarchaeological methodology focused on exploring the Continental Shelf for preserved evidence of prehistoric landforms, flora and fauna once thereon. A stepwise protocol was developed to first gather interferometric side-scan sonar data to be then processed by commercial software packages such as HYPACK Hydrographic and HYSWEEP together with HYSCAN and SONAR Wiz software. The sonar mosaics were imported to ArcGIS/QGIS software to characterize scour features/targets around artificial reefs that had exposed paleo-land surfaces previously obscured by the modern palimpsest sand sheet. Analysis of scours and depressions - “moats and comets” - adjacent to reef structures were evaluated using the profile tool within the HYPACK-HYSWEEP editor package. Symbology for the bathymetric raster layers was edited to provide a clear contrast and measurement at scour features. Measured GIS images were then classified as to scour extent and depth with respect to prevailing current directions responsible for producing turbulence. A ranking of the artificial reefs by factors such as scour depth and extent was used to guide subsequent investigation by ROVs. Sediment cores and grab samples were collected, and those samples underwent particle size analysis (PSA), macro-and micro-botanical analyses. All data – geophysical, GIS, video and geological – were collated and synthesized to produce an assessment of the potential of sea floor scour features to expose previously buried geomorphological/geological, paleontological and/or archaeological features of interest.

Codebase release r0.3 for SmoQyDQMC.jl

We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon (ee-ph) interactions, including non-linear ee-ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.

SmoQyDQMC.jl: A flexible implementation of determinant quantum Monte Carlo for Hubbard and electron-phonon interactions

We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon (ee-ph) interactions, including non-linear ee-ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.

Neonatal sepsis due to NDM-1 and VIM-2 co-producing Pseudomonas aeruginosa in Morocco.

Carbapenem-resistant Pseudomonas aeruginosa are being increasingly described worldwide. Here, we investigated the molecular mechanisms underlying carbapenem resistance in an extremely drug-resistant P. aeruginosa isolate from a neonatal intensive care unit in Morocco. P. aeruginosa strain O82J1 was identified using MALDI-TOF-MS. Carba NP, immunochromatographic assay NG Carba5 and antimicrobial susceptibility testing using disc diffusion and microbroth were performed. Whole-genome sequencing using the Illumina and MinION technologies and different software packages available at the Center of Genomic Epidemiology were used to predict the resistome, sequence type and plasmid types. P. aeruginosa O82J1 co-expressed two metallo-β-lactamases, blaNDM-1 and blaVIM-2, and was susceptible to colistin and apramycin only. It belonged to ST773 that is frequently reported worldwide as a high-risk P. aeruginosa clone. The blaVIM-2 gene was integron-borne on a IncP-2 465-kb plasmid, whereas the blaNDM-1 gene was chromosomally encoded and embedded in an integrative conjugative element, probably at the origin of its acquisition. A total of 23 antimicrobial resistance genes were detected including a blaPER-1 ESBL gene, and an 16S-rRNA methyltransferase gene rmtB. The isolation of XDR P. aeruginosa isolates expressing several carbapenemases in a neonatal intensive care unit is of great concern due to the reduced treatment options, relying only on colistin, but not recommended in neonates, and apramycin, not yet approved for human therapy. Concerns were further elevated due to the resistance to cefiderocol and ATM/AVI, two novel and last-resort antibiotics recommended to treat infections caused by Gram-negative bacteria, particularly XDR P. aeruginosa in adults.

Working with benchmark datasets in the Cuby framework.

The development and benchmarking of computational chemistry methods rely on comparison with benchmark data. More and larger benchmark datasets are becoming available, and working efficiently with them is a necessity. The Cuby framework provides rich functionality for working with datasets, comes with many ready-to-use predefined benchmark sets, and interfaces with a wide range of computational chemistry software packages. Here, we review the tools Cuby provides for working with datasets and provide examples of more advanced workflows, such as handling large numbers of computations on high performance computing resources and reusing previously computed data. Cuby has also been extended recently to include two important benchmark databases, NCIAtlas and GMTKN55.

Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets.

This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0. Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis. The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis. These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.

Theoretical simulation of TADF character of 3,9'-bicarbazole-modified 2,4,6-triphenyl-1,3,5-triazine.

Three donor (D)-acceptor (A)-type temperature-activated delayed fluorescent (TADF) molecules of 9-(2-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9H-3,9'-bicarbazole (o-TrzDCz), 9-(3-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9H-3,9'-bicarbazole (m-TrzDCz), and 9-(4-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9H-3,9'-bicarbazole (p-TrzDCz) were designed in this paper, and the photophysical properties, including the intersystem crossing rate, the reorganization energies (λ), and the intersystem crossing/reverse intersystem crossing (ISC/RISC) rate, were simulated to explore the effect of substitution sites on their TADF character. The values of the twist angle between the D and A moieties in ground state and the molecular root-mean-square deviation (RMSD) of the S1 and T1 states referenced to the S0 state indicate that o-TrzDCz possess bigger steric hindrance and stabler molecular configuration. The λ values of the ISC/RISC process should be 0.06/0.04eV for o-TrzDCz, which are much smaller than those of m-TrzDCz (0.51/0.41eV) and p-TrzDCz (1.93/1.06eV). At the same time, o-TrzDCz possess the biggest kRISC (7.28 × 106s-1) and kr (3.12 × 106s-1) values and the smallest kp (0.10s-1) value among the three titled molecules. These data indicate that o-TrzDCz should have more excellent TADF character than m-TrzDCz and p-TrzDCz. In a word, this research presents that adjusting the molecular linking manner should be a charming way to explore novel high-efficient TADF molecules. Quantum chemical calculations were performed at PBE0/6-31G* level by Gaussian 09 and ORCA 4.1.0 software packages, and reorganization energies and Huang-Rhys were performed by the DUSHIN program and MOMAP 2019B software package based on the Gaussian 09 output files, while the phosphorescence rates were performed at B3LYP/6-31G* level by Dalton 2021.

Hybridexpress: an R/Bioconductor package for comparative transcriptomic analyses of hybrids and their progenitors.

Hybridization, the process of crossing individuals from diverse genetic backgrounds, plays a pivotal role in evolution, biological invasiveness, and crop breeding. At the transcriptional level, hybridization often leads to complex nonadditive effects, presenting challenges for understanding its consequences. Although standard transcriptomic analyses exist to compare hybrids to their progenitors, such analyses have not been implemented in a software package, hindering reproducibility. We introduce hybridexpress, an R/Bioconductor package designed to facilitate the analysis, visualization, and comparison of gene expression patterns in hybrid triplets (hybrids and their progenitors). hybridexpress provides users with a user-friendly and comprehensive workflow that includes all standard comparative analyses steps, including data normalization, calculation of midparent expression values, sample clustering, expression-based gene classification into categories and classes, and overrepresentation analysis for functional terms. We illustrate the utility of hybridexpress through comparative transcriptomic analyses of cotton allopolyploidization and rice root trait heterosis. hybridexpress is designed to streamline comparative transcriptomic studies of hybrid triplets, advancing our understanding of evolutionary dynamics in allopolyploids, and enhancing plant breeding strategies. hybridexpress is freely accessible from Bioconductor (https://bioconductor.org/packages/HybridExpress) and its source code is available on GitHub (https://github.com/almeidasilvaf/HybridExpress).

PREVALENCE AND SUSCEPTIBILITY OF BACTERIA FROM USED TOOTHBRUSHES OF STUDENTS RESIDING IN HALL I AND II UNIVERSITY OF BENIN

Used toothbrushes are reservoirs for varieties of bacteria that are implicated in human disease transmission. Personal oral hygiene and removal of plaque are important roles played by the use of toothbrushes in an act endorsed for oral hygiene resolution and ubiquitously practiced in developing and developed Nations. The study aims to evaluate the prevalence and susceptibility of bacteria present in used toothbrushes of students residing in Halls I and II, University of Benin. New toothbrushes ninety (90) were bought and forty-five (45) each were distributed to students in each hall of residence, these toothbrushes were used for one month and collected for bacteria analysis. Standard bacteriological procedures were observed for the analysis. Data were analyzed using the SPSS 22.0 computer software package. Independent t-test was used to find the differences between the two variables. The value of p< 0.05 was taken to be statistically significant. Heavy bacteria contamination was associated with used toothbrushes while no bacteria contamination in the unused ones, which serves as a control. Klebsiella species 16 (35.53 %), and 19 (42.2 %) were more prevalent than coagulase-negative staphylococci species 2 (4.4 %) and 2(4.4 %) respectively from both halls. All the toothbrushes analyzed in this study had bacteria contaminates that are known to harm human health, contributing significantly to the spread of diseases, and increasing infection risks. Establishing a high aseptic protocol, storage, and management be encouraged in tertiary institution halls of residence as the incidence of these oral bacteria and individual health risks will be minimized.

ZARP: A user-friendly and versatile RNA-seq analysis workflow

Background RNA sequencing (RNA-seq) is a widely used technique in many scientific studies. Given the plethora of models and software packages that have been developed for processing and analyzing RNA-seq datasets, choosing the most appropriate ones is a time-consuming process that requires an in-depth understanding of the data, as well as of the principles and parameters of each tool. In addition, packages designed for individual tasks are developed in different programming languages and have dependencies of various degrees of complexity, which renders their installation and execution challenging for users with limited computational expertise. Workflow languages and execution engines with support for virtualization and encapsulation options such as containers and Conda environments facilitate these tasks considerably. The resulting computational workflows can then be reliably shared with the scientific community, enhancing reusability and the reproducibility of results as individual analysis steps are becoming more transparent and portable. Methods Here we present ZARP, a general purpose RNA-seq analysis workflow that builds on state-of-the-art software in the field to facilitate the analysis of RNA-seq datasets. ZARP is developed in the Snakemake workflow language and can run locally or in a cluster environment, generating extensive reports not only of the data but also of the options utilized. It is built using modern technologies with the ultimate goal to reduce the hands-on time for bioinformaticians and non-expert users and serve as a template for future workflow development. To this end, we also provide ZARP-cli, a dedicated command-line interface that may make running ZARP on an RNA-seq library of interest as easy as executing a single two-word command. Conclusions ZARP is a powerful RNA-seq analysis workflow that is easy to use even for beginners, built using best software development practices, available under a permissive Open Source license and open to contributions by the scientific community.

Molecular characterization, clinical value, and cancer–immune interactions of genes related to disulfidptosis and ferroptosis in colorectal cancer

BackgroundThis research strived to construct a new signature utilizing disulfidptosis-related ferroptosis (SRF) genes to anticipate response to immunotherapy, prognosis, and drug sensitivity in individuals with colorectal cancer (CRC).MethodsThe data for RNA sequencing as well as corresponding clinical information of individuals with CRC, were extracted from The Cancer Genome Atlas (TCGA) dataset. SRF were constructed with the help of the random forest (RF), least absolute shrinkage and selection operator (LASSO), and stepwise regression algorithms. To validate the SRF model, we applied it to an external cohort, GSE38832. Prognosis, immunotherapy response, drug sensitivity, molecular functions of genes, and somatic mutations of genes were compared across the high- and low-risk groups (categories). Following this, all statistical analyses were conducted with the aid of the R (version 4.23) software and various packages of the Cytoscape (version 3.8.0) tool.ResultsSRF was developed based on five genes (ATG7, USP7, MMD, PLIN4, and THDC2). Both univariate and multivariate Cox regression analyses established SRF as an independent, prognosis-related risk factor. Individuals from the high-risk category had a more unfavorable prognosis, elevated tumor mutational burden (TMB), and significant immunosuppressive status. Hence, they might have better outcomes post-immunotherapy and might benefit from the administration of pazopanib, lapatinib, and sunitinib.ConclusionIn conclusion, SRF can act as a new biomarker for prognosis assessment. Moreover, it is also a good predictor of drug sensitivity and immunotherapy response in CRC but should undergo optimization before implementation in clinical settings.

Mechanistic insights into C(sp2)-H activation in 1-Phenyl-4-vinyl-1H-1,2,3-triazole derivatives: a theoretical study with palladium acetate catalyst.

The activation of C-H bonds is a fundamental process in synthetic organic chemistry, which enables their replacement by highly reactive functional groups. Coordination compounds serve as effective catalysts for this purpose, as they facilitate chemical transformations by interacting with C-H bonds. A comprehensive understanding of the mechanism of activation of this type of bond lays the foundation for the development of efficient protocols for cross-coupling reactions. We explored the activation of C(sp2)-H bonds in 1-Phenyl-4-vinyl-1H-1,2,3-triazole derivatives with CH3, OCH3, and NO2 substituents in the para position of the phenyl ring, using palladium acetate as catalyst. The studied reaction is the first step for subsequent conjugation of the triazoles with naphthoquinones in a Heck-type reaction to create a C-C bond. The basic nitrogen atoms of the 1,2,3-triazole coordinate preferentially with the cationic palladium center to form an activated species. A concerted proton transfer from the terminal vinyl carbon to one of the acetate ligands with low activation energy is the main step for the C(sp2)-H activation. This study offers significant mechanistic insights for enhancing the effectiveness of C(sp2)-H activation protocols in organic synthesis. All calculations were performed using the Gaussian 09 software package and density functional theory (DFT). The structures of all reaction path components were fully optimized using the CAM-B3LYP functional with the Def2-SVP basis set. The optimized geometries were analyzed by computing the second-order Hessian matrix to confirm that the corresponding minimum or transition state was located. To account for solvent effects, the Polarizable Continuum Model of the Integral Equation Formalism (IEFPCM) with water as the solvent was used.

Genotyping-by-sequencing and weighted gene co-expression network analysis of genes responsive against Potato virus Y in commercial potato cultivars.

Potato is considered a key component of the global food system and plays a vital role in strengthening world food security. A major constraint to potato production worldwide is the Potato Virus Y (PVY), belonging to the genus Potyvirus in the family of Potyviridae. Selective breeding of potato with resistance to PVY pathogens remains the best method to limit the impact of viral infections. Understanding the genetic diversity and population structure of potato germplasm is important for breeders to improve new cultivars for the sustainable use of genetic materials in potato breeding to PVY pathogens. While, genetic diversity improvement in modern potato breeding is facing increasingly narrow genetic basis and the decline of the genetic diversity. In this research, we performed genotyping-by-sequencing (GBS)-based diversity analysis on 10 commercial potato cultivars and weighted gene co-expression network analysis (WGCNA) to identify candidate genes related to PVY-resistance. WGCNA is a system biology technique that uses the WGCNA R software package to describe the correlation patterns between genes in multiple samples. In terms of consumption, these cultivars are a high rate among Iranian people. Using population structure analysis, the 10 cultivars were clustered into three groups based on the 118343 single nucleotide polymorphisms (SNPs) generated by GBS. Read depth ranged between 5 and 18. The average data size and Q30 of the reads were 145.98 Mb and 93.63%, respectively. Based on the WGCNA and gene expression analysis, the StDUF538, StGTF3C5, and StTMEM161A genes were associated with PVY resistance in the potato genome. Further, these three hub genes were significantly involved in defense mechanism where the StTMEM161A was involved in the regulation of alkalization apoplast, the StDUF538 was activated in the chloroplast degradation program, and the StGTF3C5 regulated the proteins increase related to defense in the PVY infected cells. In addition, in the genetic improvement programs, these hub genes can be used as genetic markers for screening commercial cultivars for PVY resistance. Our survey demonstrated that the combination of GBS-based genetic diversity germplasm analysis and WGCNA can assist breeders to select cultivars resistant to PVY as well as help design proper crossing schemes in potato breeding.

Bioinformatics identification and validation of maternal blood biomarkers and immune cell infiltration in preeclampsia: An observational study.

Preeclampsia (PE) is a pregnancy complication characterized by placental dysfunction. However, the relationship between maternal blood markers and PE is unclear. It is helpful to improve the diagnosis and treatment of PE using new biomarkers related to PE in the blood. Three PE-related microarray datasets were obtained from the Gene Expression Synthesis database. The limma software package was used to identify differentially expressed genes (DEGs) between PE and control groups. Least absolute shrinkage and selection operator regression, support vector machine, random forest, and multivariate logistic regression analyses were used to determine key diagnostic biomarkers, which were verified using clinical samples. Subsequently, functional enrichment analysis was performed. In addition, the datasets were combined for immune cell infiltration analysis and to determine their relationships with core diagnostic biomarkers. The diagnostic performance of key genes was evaluated using the receiver operating characteristic (ROC) curve, C-index, and GiViTi calibration band. Genes with potential clinical applications were evaluated using decision curve analysis (DCA). Seventeen DEGs were identified, and 6 key genes (FN1, MYADM, CA6, PADI4, SLC4A10, and PPP4R1L) were obtained using 3 types of machine learning methods and logistic regression. High diagnostic performance was found for PE through evaluation of the ROC, C-index, GiViti calibration band, and DCA. The 2 types of immune cells (M0 macrophages and activated mast cells) were significantly different between patients with PE and controls. All of these genes except SLC4A10 showed significant differences in expression levels between the 2 groups using quantitative reverse transcription-polymerase chain reaction. This model used 6 maternal blood markers to predict the occurrence of PE. The findings may stimulate ideas for the treatment and prevention of PE.

Optical measurements of solid nitrogen solubility in hydrogen at cryogenic temperatures

The solubility of impurities in hydrogen at cryogenic temperatures is essential information for the design of liquid hydrogen plants. However, large data scatter and inconsistent predictions of impurity solubility by thermodynamic models mean that expensive engineering design margins are required to avoid blockages in cryogenic equipment. Here we report the combination of a stereomicroscope, commercial cryocooler and pressure cell to directly visualise solid impurity freeze-out and melting in stirred hydrogen at low temperatures and elevated pressures. Scattered literature data for nitrogen's solubility in hydrogen are compared to new solid-fluid equilibrium (SFE) measurements for a 1000 ppm N2 in H2 mixture at (1.8–5) MPa, and (42–52) K. These results were used to improve solubility models implemented in the ThermoFAST software package, achieving a three-fold decrease in the root-mean-square deviations between the SFE predictions and the data, helping lower the risk of impurity freeze-out in hydrogen liquefaction.

Relationship Between Posttraumatic Stress Disorder, Death Anxiety, and Insomnia in Adults After the Earthquake.

This study aimed to determine the relationship between posttraumatic stress disorder, death anxiety, and insomnia in adults after the earthquake. This study, designed in a relational-cross-sectional-descriptive model, was conducted with 624 adult individuals living in a province affected by the earthquake that occurred in Turkey on February 6, 2023. The study data were collected using a personal information form, Posttraumatic Stress Disorder Checklist, Turkish Death Anxiety Scale, and Bergen Insomnia Scale. The analysis of the study data was performed by using SPSS 25.0, AMOS 24.0, and G*Power 3.1 Statistical package software. A significant positive correlation was found between posttraumatic stress disorder and Insomnia and Death Anxiety (p < .05). There was a significant positive correlation between Death Anxiety and Insomnia (p < .05). It was determined that Death Anxiety has a mediating role in the impact of posttraumatic stress disorder on insomnia (95% Confidence Interval: 0.572/1.407) (p < .05). It was determined that the model created in line with the hypotheses was compatible and the model fit indices were within the desired limits, with x2/df = 1.795, RMSEA = 0.03, CFI = 0.95, GFI = 0.946, AGFI = 0.93, IFI = 0.95. It was determined that posttraumatic stress disorder increased death anxiety and insomnia after the earthquake. Conducting longitudinal studies on the post-earthquake period is recommended.

#1190 Expression of metabolic disorders in patients with hypertension and chronic kidney disease

Abstract Background and Aims To study the frequency of metabolic disorders in patients with hypertension depending on the stage of chronic kidney disease (CKD). Method The study analyzed 594 case histories of patients with AH of I-III degree (ESC/ESH 2018). CKD stages were determined according to eGFR (EPI-2021), according to the modern KDIGO 2013 classification. All patients were tested for uric acid, glucose, creatinine, and blood lipids using a Daytona autoanalyzer from RANDOX (UK). The study was conducted against the background of antihypertensive therapy (AHT). Statistical analysis was carried out using the SPSS 24.0 software package. Results Among the examined patients, intact renal function of CKD C1 (eGFR&amp;gt;90 ml/min/1.73 m2) was observed in 19.5% (n = 116); CKD C2 (eGFR 60-89 ml/min/1.73 m2) – in 50.5% (n = 300); CKD C3A (eGFR 45-59 ml/min/1.73 m2) – in 20.4% (n = 121); CKD C3B (eGFR 30-44 ml/min/1.73 m2) – in 6.4% (n = 38); CKD C4 (eGFR 29-15 ml/min/1.73 m2) - in 3.2% (n = 19) p &amp;lt; 0.0001. The terminal stage of CKD was not revealed. The mean creatinine in the groups was 66.20 ± 11.74 vs 83.44 ± 11.30 vs 105.84 ± 17.36 vs 139.78 ± 24.40 vs 212.00 ± 19.73 µmol/l, respectively (p &amp;lt; 0.00001) . Mean eGFR 97.99 ± 6.98 vs 75.44 ± 7.15 vs 53.46 ± 4.30 vs 37.82 ± 3.63 vs 23.11 ± 5.63 ml/min/1.73 m2, respectively, (p &amp;lt; 0.00001). The groups did not differ significantly in body mass index (BMI), but patients with high stage of CKD have pronounced abdominal obesity. BMI was 30.71 ± 4.4 vs 32.25 ± 5.8 vs 31.45 ± 4 vs 31.6 ± 5.6 vs 30.36 ± 10.2 kg/m2, respectively, p = 0.11. Waist measurement (WT): 98.68 ± 10 vs 104.36 ± 13.6 vs 103.62 ± 10.7 vs 104.51 ± 12.4 vs 106.94 ± 27.3 cm, respectively (p = 0.001) . It should be noted that the high stages of CKD are characterized by significantly pronounced asymptomatic hyperuremia. At the same time, the level of uric acid was 5.07 ± 1.4 vs 6.1 ± 4.7 vs 6.6 ± 1.7 vs 7.87 ± 1.7 vs 7.52 ± 1.01 µmol/l, respectively (p &amp;lt; 0.00001). When analyzing lipid spectrum data, total blood cholesterol (TC) and triglycerides (TG) in the blood did not differ significantly among the studied groups. However, it was found that increasing of CKD leads to significantly rising of low-density lipoproteins: 107.04 ± 42.57 vs 103.53 ± 38.04 vs 112.44 ± 44.27 vs 120.64 ± 39.27 vs 133.94 ± 29.83 mmol/l, respectively, р = 0.03, while the amount of high density lipoproteins significantly decrease: 42.64 ± 13.79 vs 41.86 ± 11.03 vs 41.51 ± 10.64 vs 39.62 ± 11.08 vs 36.72 ± 7.72 mmol/l, respectively, p = 0.0001. Conclusion In patients with hypertension and CKD, metabolic disorders are more pronounced, which increases the risk of developing complications of arterial hypertension.