Construction Of Diagrams Research Articles

Explicit construction of Penrose diagrams for black hole to white hole transition with spacelike thin shells.

In this article, we explicitly construct the coordinates associated with the Penrose diagram in spacetimes connected via a spacelike thin shell in the following two examples: the generalized black-to-white hole bounce with mass difference and the Schwarzschild-to-de Sitter transition. We point out the issue of the first junction condition in the Penrose diagram constructed by cutting and pasting analytically known metrics with spherical symmetry by a static spacelike thin shell. With the goal of a global conformal coordinate chart associated with the corresponding Penrose diagram without discontinuity at the thin shell, we give a procedure consisting of three conformal transformations that serve different purposes. The first two of them are used to generate a continuous coordinate patch covering the entire thin shell, and therefore, the Penrose diagram can be constructed properly by patches with overlapping. The third transformation removes any coordinate singularity reintroduced by the first two transformations at the event horizons.

A high-throughput framework for lattice dynamics

AbstractWe develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction.

Using generative neural networks when training digital engineers to improve the quality of their training

The problem and the aim of the study. Modernized higher education provides great prospects for artificial intelligence technologies to be introduced when training engineers for knowledge-intensive and high-tech industries. Applying generative neural networks makes it possible to meet the requirements both for programs to train relevant specialists and for the level of developed skills key to Industry 4.0 and for further Industry 5.0. The purpose of the study is to identify the possibilities of using generative neural networks when training digital engineers to improve the quality of their professional training. Research methods. The authors consider the generative neural network as an open resource with which it is possible to design, individualize and fill educational content in accordance with the professional interests of the participants in the interaction. The choice of service is justified by the type of information being processed and the engineer's work function being implemented. 68 bachelors of Vyatka State University are involved (Russian Federation). Training program: 08.03.01 – Construction. Focus: hydraulic engineering, industrial and civil engineering, Digital technologies for the examination of construction sites and real estate management. The assessment of the quality (level) of training is carried out with the help of materials from the fund of complex qualification tasks. For statistical processing of data, Pearson's chi-squared test is used. Results. The directions of work of students of the experimental group studying the discipline "Information Technology", including interactive communication supported by neural networks: generation of images and 3D-models, search for original titles, selection of a list of references, construction of diagrams and algorithms, etc. Statistically significant differences were revealed in the changes that occurred in the pedagogical system (χ2 = 9.095; p < 0.05). Conclusion. The summary are formulated that neural network services contribute to improving the quality of training due to the following didactic capabilities: presentation of information in various forms, automation of calculations, analysis of large amounts of data, decision support, etc. Difficulties are also highlighted: constantly updated features of services, the English-language interface, compliance with copyright and ethics of interaction on the network

Research of the distribution symmetrical components in an electrical system with a diesel generator at an unsymmetrical load

Purpose. Investigation symmetrical components of current and voltage in microgrid elements with an autonomous synchronous generator of limited power, which works in parallel with a network transformer under the condition of non-metric load. Methodology. During the research, visual programming methods were used in the Simulink/Matlab package, methods of electrical engineering theory in terms of determining symmetrical component currents and voltages in observation branches, methods of synthesizing schemes for replacing elements of electric power systems for symmetrical component currents, methods of data processing and construction diagrams using specialized software tools.. Findings. As a result the analysis known studies, it was established that under the condition of researching low-power generating systems in conditions of asymmetry, insufficient attention is paid to the nature of the asymmetric load. Using the well-known structure of a microgrid, which includes a synchronous generator, a machine load, and an external network transformer, its model was built, in which, by introducing asymmetric loads of various types, a series of experiments was implemented with the registration of voltages and currents of forward, reverse, and zero sequences in the branches of the network. The analysis of the results obtained during the research established that the positive sequence voltage in the case of a change in the active load does not change its level, under the same circumstances, in the case of an active-capacitive and active-inductive load, the voltage change has the opposite character. In the case of increasing asymmetry of an active-inductive nature, the positive sequence voltage decreases, and in the case of an active-capacitive one, it increases. The specified changes in some cases exceed 3%. Positive sequence currents in the case of active load imbalance differ slightly. In the case of a positive sequence current of the transformer, its continuous growth is observed, which in the case of active-capacitive and active-inductive loads exceeds the active one by an average of 1.5 times. Negative sequence currents in the studied model, which are formed by an asymmetrical load, are completely closed to the transformer, causing zero-sequence voltages, and the nature asymmetrical load significantly affects the value of these currents, a 61% increase was noted. Originality. It was established that in a microgrid, which includes a synchronous generator, a machine load, a symmetrical active load of comparable power to the generator, an external network transformer, in addition to the fact of asymmetry caused by an asymmetrical load, the character of an asymmetrical load (active, active-inductive or active-capacitive). Practical value. In the case of using in microgrids devices that provide an increase in the quality of electrical energy, for example, symmetrical devices, it is necessary, in addition to the asymmetry factor, to take into account the natural load that causes the latter.

ЩОДО ОДНОГО ПІДХОДУ ДО ВИРІШЕННЯ ПИТАННЯ АВТОМАТИЗОВАНОГО БУДУВАННЯ СХЕМИ ПОСИЛАНЬ РЕЛЯЦІЙНИХ БАЗ ДАНИХ

Introduction. The current trend of continuous integration of various areas of scientific and practical human activity contributes to the constant increase in the complexity of problems, the successful solution of which becomes possible only through the use of large volumes of information, as a rule, geographically distributed across multiple database files. In this case, the need to know the locations and features of the interaction of its components becomes of fundamental importance when organizing the most convenient and efficient ways to access it. In some cases, to meet such needs, you can use the services of existing products (Microsoft Access, Microsoft SQL Server, MySQL, FileMaker Pro, Oracle Database, dBASE, etc.). Sometimes, using a specialized SQL language or its dialects, it is more convenient to create a “handmade” one that will satisfy the stated requirements. If the user desires or needs to know the location of the information used in the work, understand the logic of the mechanism for obtaining it, and evaluate the effectiveness of the ways of its delivery to constantly monitor its current and future nomenclature and quantity, its developments can help, which can provide more detailed information, than known means. As experience shows, obtaining an integral and effective solution to this set of closely interrelated issues becomes possible only with the availability of a purely specialized software tool for the automated construction of link diagrams, which is a multifunctional, operational, easy-to-learn, and easy-to-use user environment. Endowed with the ability at any time and with minimal user participation to visualize on the screen the current structure of the created database with the required degree of clarity, detail, and ease of perception, such an environment should become a means of operational analysis and assessment of ways of possible modification of the database itself in the direction of creating a more effective one in practical terms, regarding the variant of its structure. Purpose. Research and practical testing of the existing capabilities of approaches, methods, algorithms, and software modules that were developed during the creation of a universal information software technology for working with undirected graphs of the “mixed forest” type. To evaluate the efficiency and feasibility of using these approaches to improve a set of integrated software tools for the automated construction of relational database link diagrams with minimal user participation in this process. Methods. Database systems, apparatus of graph-tree theory. Result. A new approach is proposed, and the result of its software implementation is presented in the form of a “pilot” version of a set of software tools for the automated construction of relational database link schemes. The basis of the approach is techniques, methods, algorithms, etc. which were created and implemented programmatically in a new, universal information software technology for working with (temporarily) undirected graphs of the “sour cream forest” type. , Software package (SP) makes “formal” the user’s participation in the process of building link diagrams. By greatly reducing the time required for this and providing more than 90% savings in the technical resources of the computer used, SP makes it possible to take into account data tables, the total number of fields of which is limited only by the latter’s capabilities. A positive conclusion about the suitability of such an approach will become an incentive for its further improvement in the form of specialized information software technology as an effective means of solving the problems of constructing relational database link schemes.

Exploring the key pathogenic mechanisms and potential intervention targets for Sophorae Flavescentis radix in managing bone metastasis of lung cancer based on network pharmacology and molecular docking techniques.

Lung cancer often metastasizes to the bone, which significantly complicates treatment and worsens patient prognosis. Thus, new therapeutic strategies need to be established. Using network pharmacology and bioinformatics analysis, this study sought to determine the molecular targets and associated mechanisms of the traditional Chinese medicine (TCM) Sophorae Flavescentis radix in the treatment of lung cancer bone metastasis. The active components of Sophorae Flavescentis radix were screened using the TCM Systems Pharmacology (TCMSP) platform based on drug-likeness and oral bioavailability. The target genes of these active compounds were obtained from the DrugBank database. Differentially expressed genes (DEGs) between primary and bone metastatic lung cancer samples were screened in the GSE175601 dataset from the Gene Expression Omnibus (GEO) database using GEO2R. The intersecting DEGs from both groups were used to construct a Venn diagram to identify the candidate target genes. The expression and prognostic relevance of these genes were validated in The Cancer Genome Atlas (TCGA) database. The GeneMania and Search Tool for Recurring Instances of Neighbouring Genes (STRING) databases were used to generate the protein-protein interaction networks. Molecular docking was performed using the PubChem, Protein Data Bank (PDB), and CB-DOCK2 databases. A Gene Set Enrichment Analysis (GSEA) was conducted to explore the possible mechanisms of action. In the TCMSP database, 28 active compounds and 227 target genes of the Sophorae Flavescentis radix were identified. In total, 952 DEGs related to lung cancer bone metastasis were found in the GSE175601 dataset from the GEO database. Five common DEGs were identified via Venn diagram construction (i.e., F10, JUN, AKR1B1, MMP1, and CCND1). MMP1 was selected as the candidate gene. MMP1 was upregulated in lung cancer tissues, and patients with low MMP1 expression had better survival rates than those with high MMP1 expression (P<0.05). MMP1 has an affinity of -8.9 with luteolin. The GSEA results suggested that MMP1 might influence biological processes in lung cancer by participating in pathways such as chemokine signaling, apoptosis, Wingless/Integrated (Wnt) signaling, tumor protein p53-regulated cell cycle arrest, Hedgehog signaling, and mitogen-activated protein kinase signaling. Patients with lower MMP1 levels had prolonged overall survival and may serve as a novel predictive biomarker for lung cancer. Sophorae Flavescentis radix appears to exert therapeutic effects on lung cancer bone metastasis by inhibiting MMP1 expression and modulating the abnormal activation of the Wnt pathway. Our findings further extend the understanding of the pathogenic mechanisms and potential therapeutic interventions of Sophorae Flavescentis radix in lung cancer bone metastasis, providing a theoretical basis for clinical diagnosis and treatment research.

MICE tourism product value chain

MICE tourism is a segment of the tourism industry that, due to its singularity, requires specific attention. This article offers a holistic approach to the channel of distribution of MICE tourism and targets two main objectives: the proposal of a conceptual framework that depicts all stakeholders, flows of action and possibilities of intermediation and study of the process of intermediation in order to analyze its present status and future development. To achieve our goal in this study, we used research methods - literature analysis, study of scientific publications, scientific research, and also used the construction of tables and diagrams of interaction between the main stakeholders of MICE tourism. When analyzing materials and writing this article, the following methods were used: general scientific methods of cognition (analysis, synthesis, systematization of theoretical data), system content analysis. The results observe a slow but steady process of disintermediation in which intermediaries are being bypassed in order to reduce costs. However, it also reaches the conclusion that total disintermediation is not feasible due to the high standards of quality service that the MICE market demands.

Analysis of Thermophysical Properties of Electro Slag Remelting and Evaluation of Metallographic Cleanliness of Steel.

Improving the competitiveness of steel companies is linked to sustainable, quality-compliant steel production. Therefore, new steel production technologies contributing to increased cleanliness of steel are continuously being developed and optimized. One way to achieve a high steel quality is to use electro slag remelting (ESR) technology. In this paper, the principle of ESR technology and the importance of fused slags for optimizing the process are outlined. The aim of this work was to analyze the main thermophysical properties of steel and fused slags used in the ESR process. Determination of the properties of steel and slags was performed using the FactSage calculation software, which involved the calculation of the liquid and solid temperature of steel and slags, the calculation and construction of quaternary diagrams, and the calculation of viscosity. The resulting quaternary diagrams revealed the substantial influence of chemical composition on melting temperatures of slags. In order to validate the acquired results, a CrNiMoV-type steel was subjected to investigation of its metallographic cleanliness and evaluation of its mechanical properties; the ESR process was shown to significantly improve the cleanliness of the steel and improve the mechanical properties of the steel compared to its cleanliness and quality when produced via vacuum degassing (VD) technology. During the ESR process, the average size of non-metallic inclusions was reduced from 20 μm to 10 μm, and the maximum size of non-metallic inclusions was reduced from 50 μm to 28 μm. The mechanical properties of the steel produced using ESR technology were impacted as follows: the ductility increased by 10%, contraction increased by 18%, notched toughness at 20 °C increased by 46%, and at -40 °C (respectively -50 °C) it increased by 30%.

What physical examinations are observed during an in-person GP consultation? Automatic extraction using a text-based approach

ObjectivesTeleconsultation is anticipated to have a long-term role in primary care. However, conducting virtual physical examinations is a well-known limitation. To anticipate unmet needs general practitioners (GPs) and patients may experience during teleconsultation, this study aims to automatically identify physical examinations typically conducted during in-person GP consultation. Material and MethodsThis study utilizes 281 GP in-person consultations (de-identified transcripts & video recordings) within UK general practices, where 169 eligible ones were included in this study. We propose an automated text-based approach using regular expressions on keywords in GP-patient consultation dialogue (e.g., “roll up your sleeves”) to identify physical examinations (e.g. blood pressure measurement). This approach involves the construction of conceptual diagrams to visually inspect the relationship between keywords and physical examinations, syntax analysis to identify patterns between keywords and generate regular expressions, and the use of these regular expressions in consultation transcripts to detect potential instances of physical examinations, where matching video frames were subsequently retrieved. The performance of our automated text-based approach is compared to manual classification by 2 independent researchers using 5-fold cross-validation (precision, recall, and F1-score). ResultsAmong the 169 eligible GP in-person consultations, 133 (79%) required a physical examination, while the other 33 visits were for psychological reasons. Out of these 133 consultations, a total of 283 physical examinations were observed, with 21 instances conducted behind a curtain. We identified 42 distinct types of physical examinations from these 283 instances, grouped into 10 physical examination categories based on body areas and physical artefacts. The most frequent category of physical examinations is Vital Signs 26.80% (76/283). Overall, blood pressure measurement (also belonging to the Vital Signs category) is the most frequent physical examination at 59.2% (45/76). The comparison between manual classification and the regular expression model demonstrates an average precision of 88.3%, recall of 78.9%, and an F1-score of 83.3% from 5-fold cross-validation, providing significant insights into the frequency and types of physical examinations conducted during in-person GP consultations. ConclusionBy using regular expressions in consultation dialogues between GPs and patients, we can automatically identify physical examinations in GP consultations with a precision of 88.3%. Findings from this study, i.e. physical examinations during in-person GP consultations, provide insights into areas where GPs and patients may need support during teleconsultation.

Thermodynamic study of water/solvent, bitumen/solvent, water/bitumen, and water/bitumen/solvent systems: From CPA EoS parametrization towards phase diagram construction

Various fluid phase equilibria happen in solvent-aided steam-assisted gravity drainage (SA-SAGD). An appropriate fluid model is a prerequisite for reservoir simulation, SA-SAGD operation analysis, and the design of various phase behavior experiments. Computational thermodynamics is a powerful tool for phase behavior studies in this application. We used the Cubic Plus Association Equation of State (CPA EoS) to predict equilibrium properties due to the presence of molecules with highly directional attractive forces. Calibration of the thermodynamic model is performed by parametrizing its unknown parameters versus two-phase equilibrium data. The model’s prediction capability of three-phase experimental data is evaluated, and it is used to construct the phase diagram of water/multicomponent solvent and water/multicomponent solvent/bitumen systems. For the water/multicomponent solvent system, the Txy diagram is obtained at 25 bar, and various phase equilibria regions are specified. These phase regions are presented on ternary diagrams for water/multicomponent solvent/bitumen systems at 25 bar and 475 K, 480 K, and 485 K. The steam/solvent coinjection analysis shows that at the same pressure, temperature, and steam/solvent composition, the multicomponent solvent/steam coinjection yields more aqueous phase compared to pure solvent/steam. This results in the transfer of more latent heat to bitumen, significantly contributing to its viscosity reduction. Analysis of the SA-SAGD operating conditions shows that a multicomponent solvent outperforms pure solvents in promoting steam condensation. The results aids in designing experiments, reducing the risk of failure of experiments, and saving time and resources in phase behavior studies.

Design and Evaluation of Clove Oil-Based Self-Emulsifying Drug Delivery Systems for Improving the Oral Bioavailability of Neratinib Maleate.

Neratinib maleate (NM), a tyrosine kinase inhibitor, is used in the treatment of breast cancer. NM is orally administered at a high dose of 290 mg due to its low solubility and poor dissolution rate at pH > 3, as well as gut-wall metabolism limiting its bioavailability. Self-emulsifying drug delivery systems (SEDDSs) of NM were developed in the current study to improve its oral bioavailability. The oily vehicle (clove oil) was selected based on the solubility of NM, while the surfactant and the cosurfactant were selected based on the turbidimetric analysis. Three different sets were screened for surfactant selection in the preparation of SEDDS formulations, the first set containing Cremophor® EL alone as the surfactant, the second set containing a mixture of Cremophor® EL (surfactant) and Caproyl® PGMC (cosurfactant), and the third set containing a mixture of Cremophor® EL (surfactant) and Capmul® MCM C8 (cosurfactant). Propylene glycol was used as the cosolubilizer in the preparation of SEDDSs. A series of studies, including the construction of ternary phase diagrams to determine the zone of emulsification, thermodynamic stability studies (involving dilution studies, freeze-thaw, and heating-cooling studies), turbidimetric analysis, and physicochemical characterization studies were conducted to identify the two most stable combinations of SEDDSs. The two optimized SEDDS formulations, TP16 and TP25, consisted of clove oil (45% w/w) and propylene glycol (5% w/w) in common but differed with respect to the surfactant or surfactant mixture in the formulations. TP16 was prepared using a mixture of Cremophor® EL (surfactant) and Caproyl® PGMC (cosurfactant) in a 4:1 ratio (50% w/w), while TP25 contained only Cremophor® EL (50% w/w). The mean globule sizes were 239.8 ± 77.8 nm and 204.8 ± 2.4 nm for TP16 and TP25, respectively, with an emulsification time of <12 s for both formulations. In vitro drug dissolution studies performed at different pH conditions (3.0, 4.5, 6.8) have confirmed the increase in solubility and dissolution rate of the drug by TP16 and TP25 at all pH conditions compared to plain NM. An oral pharmacokinetic study in female Wistar rats showed that the relative bioavailability (Frel) values of TP16 and TP25 over the plain NM were 2.18 (p < 0.05) and 2.24 (p < 0.01), respectively.

Contribution of artificial intelligence for understanding animal rabies epidemiology in Morocco: What are the perspectives of an innovative and predictive approaches?

Rabies is a major zoonotic disease legally notifiable in Morocco and elsewhere. Given the burden of rabies and its impact on public health, several national control programs have been implemented since 1986, without achieving their expected objectives.The aim of this study was to design a predictive analysis of rabies in Morocco. The expected outcome was the construction of probabilistic diagrams that can guide actions for the integrated control of this disease, involving all stakeholders, in the country. Such modeling is an essential step in operational epidemiology to optimize expenditure of public funds allocated to the integrated strategy for fighting this disease.The methodology employed combined the use of geospatial analysis tools (kriging) and artificial intelligence models (Machine Learning). In order to investigate the link between the risk of rabies within a territorial municipality (commune) and its socio-economic situation, the following data were analyzed: (1) health data: reported animal cases of rabies between 2004 and 2021 and data obtained through the ArcGIS kriging tool (Geospatial data); (2) demographic and socio-economic data. We compared several Machine Learning models. Of these, the “Imbalanced-Xgboost” model associated with kriging yielded the best results. After optimizing this model, we mapped our results for better visualization.The obtained results complement and consolidate previous study in this field with greater accuracy, showing a strong correlation between a commune's socio-economic status, its geographical location and its risk level of rabies. From this, 399 out of the 1546 communes have been identified as high-risk areas, accounting for 25.8% of the total number of communes. Under this risk-based approach, the results of these analyses make it practical to take targeted decisions for rabies prevention and control, as well as canine population control, in a territorial commune according to its risk level. Such an approach allows obvious optimized distribution of financial resources and adaptation of the control actions to be taken.The study highlights also the importance of using innovative technologies to refine epidemiological approaches and fill gaps in field data. Through this study, we hope to contribute to eradication of rabies in Morocco by providing reliable data and practical recommendations for control actions against rabies.

Emergence of vortex state in the S=1 Kitaev-Heisenberg model with single-ion anisotropy

The search for Kitaev spin liquid states has recently broadened to include a number of honeycomb materials with integer spin moments. The qualitative difference with their spin-1/2 counterparts is the presence of single-ion anisotropy (SIA). This motivates our investigation of the effects of SIA on the ground state of the spin-1 Kitaev-Heisenberg (KH) model using the density-matrix renormalization group which allows construction of detailed phase diagrams around the Kitaev points. We demonstrate that positive out-of-plane SIA induces an in-plane vortex state without the need for off-diagonal interactions. Conversely, negative SIA facilitates the emergence of a state in the presence of antiferromagnetic Heisenberg interactions, whereas a state can emerge for ferromagnetic Heisenberg coupling. These findings, pertinent even for weak SIA, not only enhance our theoretical understanding of the spin-1 KH model but also suggest experimental prospects for observing these novel magnetic states in material realizations. Published by the American Physical Society 2024

Instructional framing for guiding the construction of explanatory diagrams in a science classroom: a metafunction perspective

ABSTRACT This study investigates how to guide students’ drawing diagram activities as constructing explanations in science classrooms from the metafunctions in systemic functional language (SFL). Although a drawing-to-learn approach requires sufficient support, there is still a lack of understanding regarding the pedagogical considerations for guiding students on what and how to draw during their activities. Guided by the metafunctions in SFL, I analysed a case of one teacher’s teaching practices of employing drawing-diagram activities in a general science classroom. I found that the teacher translated the objects to draw from the familiar to the targeted visual meaning for the students (ideational). To provide a clearer understanding of the roles of diagrams, she had reflective discussions with the students about how other people could interpret their diagrams and what would be important to represent iteratively through sharing the diagrams using a visualiser (interpersonal). She also often provided several examples of organising diagrams at the beginning of or during the activities to brainstorm ideas for the compositions (textual). This practical knowledge framed by the metafunctions is aimed at providing a better understanding of how teachers can deploy a drawing-to-learn approach and intervene during drawing activities to facilitate students’ science learning in general science classrooms.

AIPHAD, an active learning web application for visual understanding of phase diagrams

Phase diagrams provide considerable information that is vital for materials exploration. However, the determination of multidimensional phase diagrams typically requires a significant investment of time, cost, and human resources owing to the necessity of numerous experiments or simulations. Machine learning and artificial intelligence techniques present a viable solution for expediting phase diagrams investigations. Additionally, effective visualization is critical for understanding phase diagrams. This study reports the development of AIPHAD (Artificial Intelligence technique for PHAse Diagram), an open-source web application to assist in the investigation and visual understanding of phase diagrams using active learning. AIPHAD employs PDC (Phase Diagram Construction) algorithm, which operates on the principle of uncertainty sampling in active learning. The AIPHAD application facilitates the examination of five diagram types: two-variable diagrams, three-variable diagrams, ternary sections, ternary phase diagrams, and quaternary sections. The efficacy of the application is demonstrated in the study of the Fe-Ti-Sn ternary system, where it efficiently identified the presence of the Heusler phase. The integration of machine learning tools with traditional materials science approaches showcased in this study has the potential to drive groundbreaking advancements in materials exploration and discovery.

Bioinformatic analysis of differentially expressed genes in lung cancer bone metastasis and their implications for disease progression in lung cancer patients.

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death worldwide. Moreover, it is highly susceptible to distant metastasis, which is the main cause of pain in advanced lung cancer, and frequently occurs in the bone. This study aimed to identify the differentially expressed genes (DEGs) related to metastatic bone disease in lung cancer using bioinformatics methods and to analyze the risk factors influencing the incidence of secondary bone metastasis in lung cancer. Gene expression profiles from the GSE175601 and GSE10799 datasets in the Gene Expression Omnibus (GEO) database were analyzed to screen for the DEGs associated with lung cancer bone metastasis. The STRING database was used to construct a protein-protein interaction (PPI) network, and the MCODE plugin was used to identify the key genes. The expression of these important genes in lung tumor tissues and their correlation with prognosis were validated in The Cancer Genome Atlas (TCGA) database. An examination of clinical data from patients diagnosed with stage IV lung adenocarcinoma treated at the Anhui No. 2 Provincial People's Hospital was conducted. Immunohistochemistry was used to examine the expression of key genes in lung cancer tumor tissues. A binary logistic regression analysis was conducted to examine the interactions in the expression of critical genes associated with bone metastasis in lung carcinoma patients. In total, 59 DEGs were identified in the GSE175601 and GSE10799 datasets through Venn diagram construction. The PPI network analysis revealed two significant modules and eight candidate genes (LAPTM5, LCP2, CD53, ARHGAP25, C1QA, DES, MYH11, and VIM). According to TCGA database analysis, in carcinogenic tissues of the lung, the expression of these eight critical genes is downregulated. Further, only the lung cancer patients who had high expressions of ARHGAP25 had an improved progress-free interval (PFI) (P<0.05), disease-specific survival (DSS), and overall survival (OS). Of the 49 with stage IV lung adenocarcinoma patients included in the study, 27 (55.10%) developed bone metastasis. The immunohistochemical (IHC) results indicated that the expression score of ARHGAP25 was significantly lower in the group with bone metastasis (3.93±2.95) than the group without bone metastasis (6.64±3.62) (P=0.006). The proportion of patients with low ARHGAP25 expression was significantly higher in the group with bone metastasis (70.37%, 19/27) than the group without bone metastasis (31.82%, 7/22) (P=0.007). The binary logistic regression analysis identified serum alkaline phosphatase (ALP) and ARHGAP25 expression levels as independent risk factors for the occurrence of secondary bone metastatic disease in lung carcinoma patients. The key gene ARHGAP25 identified through bioinformatics for lung cancer bone metastasis was significantly downregulated. Its low expression constitutes an independent risk factor for secondary bone metastatic disease in patients with lung carcinoma.

Concerning structure-functional features of the leaf apparatus of some stone crops varieties belonging to &lt;i&gt;Prunus&lt;/i&gt; (Rosaceae Juss.) genus

For the Rosaceae family (Rosaceae Juss.), which is part of the group of families with the highest species abundance, one of the largest genera is the Prunus genus, which, according to the Catalog of Life, includes 395 species, 16 subspecies, 55 variations. Various sources for this genus indicate from 250 to 400 species of trees and shrubs widely distributed in the northern temperate zone, subtropical and tropical regions, from forests to deserts, in altitude ranges from sea level to alpine zones. In the Samara Oblast, among 67 species of woody Rosaceae, there are 30 native and 36 introduced species (adventitious and wild). The genus is most widespread in the temperate zone of the Northern Hemisphere, is widely represented in North America, Europe and Northern Asia, and includes a number of cultivated species of global economic importance. The active involvement of interspecific hybridization between representatives of the Prunus genus is considered by experts as a determining factor in the evolutionary development of its species diversity, which manifested itself in the appearance of a number of hybridogenic species that were able to overcome successfully the effects of abiotic stressors in the process of expanding ranges, the formation of cultigenic species of stone crops and their varietal diversity. In recent decades, the characteristics of leaves have gained special place in the research programs of plant ecologists as significant indicators of various aspects of growth, reproduction and functions of the plant organism, water use, nutrients, adaptation to environmental changes, including projected climatic changes. Leaf indicators are the most accessible for study throughout almost the entire growing season, they can be evaluated quickly enough, without involving expensive equipment, the screening procedure for leaf apparatus indicators is well standardized. The combined efforts of researchers led to the creation of large and complete databases of leaf apparatus features for various plant species. For the leaves of 15 varieties of stone crops (cherry Olechka, Chernookaya, Kalinka, Nyusha, Pervinka; apricot Samara, Yantar Povolzhya; Russian plum Dolgozhdannaya, Konservnaya, Velikansha, Naryadnaya, Kompotnaya, Lunnaya; domestic plum Dachnaya, Doch Eurasii) quantitative indicators determined for samples selected in July 2020, 2021 and 2022 are analyzed. In order to visualize the possible features of the leaf apparatus in groups of varieties of various fruit crops, the construction of dot diagrams with a limited area of location for each group of points was used. This technique made it possible to identify both the presence of separate groups of points corresponding to one indicator of the leaves of individual stone fruits, and the overlap of the corresponding ranges of other indicators of values. Probably, this picture is a reflection of a certain ecological and physiological heterogeneity in groups of stone fruit varieties, which are cultigenic hybrids of complex origin.

Intelligent System of Constructing Vector Diagrams of Electrical Circuits

Phasor diagrams are a powerful tool for visualizing and understanding the distribution of current, voltage, and power in electrical systems. During Russia's war against Ukraine, our energy industry has become very vulnerable to enemy attacks, and therefore needs a quick and effective recovery. Energy specialists lack software tools for working with the power system, and in the period of development of artificial intelligence, creating such tools is not so difficult. For example, familiar specialists often have to build vector diagrams - tools for visualizing and understanding the distribution of current, voltage and power in electrical systems. Using a combination of frameworks for working with artificial intelligence and creating a graphic shell, you can achieve the desired result in a few months, and at the same time do a useful thing for our victory. The YOLO model (based on the PyTorch framework) and the QT framework are considered among the proposed tools for creating an intelligent vector diagram construction system. The role of artificial intelligence is to recognize electrical elements in circuits and their connections to each other. Creating a user interface is an equally important thing, which is already implemented in many places with the help of QT. As of today, there is no specialized software tool for solving the problems of manual construction of vector diagrams, but the proposed approaches are already used for its creation. The system uses the Yolov5 model to recognize electrical elements on the circuit. The model is trained on more than 150 images and is able to recognize hand-drawn diagrams. Recognition is run as a separate process from the main program written in C++. This part of the system processes the input data from Yolo, saves it in a convenient format, creates a user interface, and displays the result as a vector diagram.

Creep-fatigue interaction of soft adhesive under shear loading: Damage diagram and life prediction model

Soft adhesives used in cutting-edge technological fields are susceptible to shear fatigue failure under complex in-plane loadings. Although the interaction or coupling effect between creep and fatigue damage have been studied, the effect of the equivalent creep damage during typical fatigue loading on the fatigue life of soft adhesives, as well as the interaction between the equivalent creep damage and fatigue damage of soft adhesives have never been characterized. This study systematically investigates the creep-fatigue interaction of the soft adhesive under various loading conditions. It was found that significant equivalent creep damage occurs and accumulates under typical cyclic loading, which seriously accelerates the shear fatigue failure of soft adhesives. Furthermore, the contribution of the equivalent creep damage to the final shear fatigue failure is even more pronounced than the fatigue damage. The quantitative construction of creep-fatigue damage diagrams has led to the determination of strong creep-fatigue interaction, which could be understood by the interactive mechanism between the stretching, friction, pulling-out, and rupture of molecular chains. In light of the distinctive creep-fatigue interaction mechanism, a modified Chaboche damage model has been developed, which could accurately predict the shear fatigue life of soft adhesives under a wide range of loading conditions.

Construction of color-magnitude diagrams using real astronomical data for teaching at school

In this paper, with the aim of bridging the gap between cutting-edge research and the classroom, we present a situated learning proposal to integrate astronomical data and tools in the teaching of mathematics and physics. Our approach focuses on the construction of magnitude-color diagrams for two well-known star clusters, the Pleiades and 47 Tucanae, which are visible from the southern hemisphere, using virtual observatory-based applications Aladin and Topcat, using Simbad data specifically to separate data differences due to proper motion and/or reddening due to absorption by interstellar dust. To assess the feasibility of implementing these tools at school, we organized a workshop for science teachers that received a positive response. In addition, we also discuss the limitations and challenges that could hinder the effective application of these tools for educational purposes.