Graphical Form Research Articles

Revisiting the nexus between financialization and natural Resource efficiency through the lens of financial development and green industrial optimization

Responsible natural resource management has become critical for ensuring the effective use of resources jeopardizing future generations' needs. Financialization based on artificial intelligence, green finance, and lower economic risks are important in this respect. The objective of this study is to explore the impact of financialization and economic uncertainty on the natural resource market. The analysis covers the period from 1980 to 2021 and is performed for selected South Asian Association for Regional Cooperation (SAARC) countries. In addition, among economic financialization processes, artificial intelligence (AI) based financial management (FM) is more significant than domestic financialization strategies. For that purpose, Artificial Neural Network (ANN) method and pooled regression analysis are employed for the empirical analysis. According to the findings, economic uncertainty has a stronger influence than economic financialization. Therefore, risk mitigation plays a larger role in creating shocks in all macroeconomic indicators and, as a result, on the natural resource market. The accuracy measures to support the finding's robustness like the value of R2 is highly acceptable and errors are minimum (% MAPE is 5.06 which falls under the criteria of high accuracy) in both testing and training datasets approximately by 50%. In addition, the findings of Garson method reveal that economic uncertainty and AI based FM are significantly important for the natural resource market as their important values (0.27, 0.26, and 0.20) touch the maximum importance statistics (0.30). The study, therefore, suggests that authorities in South Asian countries should focus on AI-based financial advancement and integrate AI into the traditional financialization methods to upgrade the regional economic financial system, which will help in regulating and improving the efficiency of the resource market. The results also provide the graphical and tabulation formation of financialization and economic uncertainty in SAARC countries. Additionally, analysis on the chosen variable by suing PCA has also been made to transform the dataset. Along with it, the regional corporation is crucial for dwindling economic uncertainty and promoting a steady growth and sustainable environment through the maintenance of the natural resource market.

BioFlow-Insight: facilitating reuse of Nextflow workflows with structure reconstruction and visualization.

Bioinformatics workflows are increasingly used for sharing analyses, serving as a cornerstone for enhancing the reproducibility and shareability of bioinformatics analyses. In particular, Nextflow is a commonly used workflow system, permitting the creation of large workflows while offering substantial flexibility. An increasing number of Nextflow workflows are being shared on repositories such as GitHub. However, this tremendous opportunity to reuse existing code remains largely underutilized. In cause, the increasing complexity of workflows constitute a major obstacle to code reuse. Consequently, there is a rising need for tools that can help bioinformaticians extract valuable information from their own and others' workflows. To facilitate workflow inspection and reuse, we developed BioFlow-Insight to automatically analyze the code of Nextflow workflows and generate useful information, particularly in the form of visual graphs depicting the workflow's structure and representing its individual analysis steps. BioFlow-Insight is an open-source tool, available as both a command-line interface and a web service. It is accessible at https://pypi.org/project/bioflow-insight/ and https://bioflow-insight.pasteur.cloud/.

Analysis of the orthopaedic trauma literature utilizing machine learning and latent dirichlet allocation

Objectives: To demonstrate a new method to review literature utilizing machine learning and latent Dirichlet allocation and summarize the past 20 years of orthopaedic trauma research. Methods: All original research articles published in the Journal of Bone and Joint Surgery American volume, Journal of Orthopaedic Trauma, Journal of Bone and Joint Surgery British volume, Trauma, Injury, Clinical Orthopaedics and Related Research, and the Journal of the American Academy of Orthopaedic Surgeons from 2000-2020 were analyzed using latent Dirichlet allocation (LDA), which is a form of machine learning. 100 topics were created by the algorithm and only topics that were relevant to trauma were included, leaving 30 topics ranked by popularity and associated with a best-fitting article and trend over the past 20 years. Results: Research article abstracts totaling 21,968 from 2000-2020 in the orthopaedic trauma literature were analyzed to create 30 topics. The topics were ranked by popularity, trended over the specified time period, and associated with a best fitting article. The 3 “hottest” and “coldest” topics were visualized in graphical form. Conclusions: This is the first study of its kind to utilize machine learning as a method of reviewing the orthopaedic trauma literature. Machine learning possesses the ability to rapidly synthesize a large body of literature to assess the current state of research and trends of research topics. Machine learning can aid clinicians and researchers in time-intensive tasks to quickly provide clues that will promote avenues further research.

Capturing connectivity information from process flow diagrams by sequential-orthogonalized PLS to improve soft-sensor performance

In the development of data-driven soft sensors for product quality assessment in multi-unit manufacturing processes, the only information that is typically used as an input to the model is real-time measurements from field sensors. However, even if detailed knowledge of the mechanistic behavior of the process may not be available, information about the sequence of processing units, and their connectivity, is available, typically in graphical form through process flow diagrams. In this study, we investigate the use of sequential-orthogonalized partial least-squares (SO-PLS) regression as a way to capture connectivity information from a process flow diagram, and transfer it into a data-driven model to be used as a soft sensor in a multi-unit process. Connectivity between units is captured and translated into a block order that establishes a sequence for block regressions. Orthogonalization between two blocks is then carried out with the aim of eliminating overlapping data and retaining information that is unique to each block. Product quality is finally predicted by summing the contributions from each block, and the accuracy of prediction is enhanced due to the embedded dual feature-extraction procedure, which combines orthogonalization and latent-variable extraction. The effectiveness of the proposed approach is illustrated by comparing the quality prediction performance of two soft sensors for a simulated multi-unit continuous process: one using standard PLS and one using SO-PLS. Superior performance of the SO-PLS soft sensor is achieved, even more markedly so when fewer field measurements are available to build the soft sensor.

Transient analysis of a bulk stream queue with arbitrarily distributed arrival intervals

We study the classical infinite buffer single server queueing model with renewal input of customers in batches of random size, having arbitrarily distributed arrival intervals and exponentially distributed service times. Using the technique of supplementary variable and shift operator we derive closed form expression of the time dependent system content distribution in terms of its Laplace transform. The analysis is mainly based on the root-finding technique of the non-linear characteristic equation in terms of the Laplace transform variable. Additionally, using asymptotic properties of Laplace transform, we deduce the corresponding steady-state distribution. We discuss some special cases of the model, thus providing an alternative approach in deriving the transient distribution. We further evaluate certain performance measures and present extensive numerical examples in tabular and graphical form to illustrate the applicability of our theoretical work. The effect of system parameters, interarrival time distribution and traffic intensity on the system behavior is also demonstrated.

Comparative Analysis of ORM Systems for the .NET Platform

This article presents a comparative study of three popular ORM (Object-Relational Mapping) systems used in the .NET technology: Entity Framework Core, Dapper, and LINQ to DB. The analysis is divided into two main parts: theoretical, focusing on research found in literature, and practical, where an application was implemented to assess the performance of each system and their memory consumption. The results obtained were presented in the form of graphs. Dapper emerged as the most efficient system and consumed the least memory in the majority of test cases.

An Update to The Demagnetizing Factor Dataset Calculated for The General Ellipsoid by Osborn

The exact formulae for calculating the demagnetizing factors of a general ellipsoid along the three main axes a ≥ b ≥ c have been long known. According to these formulae, the demagnetizing factors depend only on the axial ratios b/a and c/a. Although the calculation of the demagnetizing factors is a straightforward task, the calculation itself is not a simple one. Therefore, tabular and graphical representations of these demagnetizing factor data have also been presented which can then be used for approximating the demagnetizing factors of a rectangular ferromagnetic slab with the same axial ratios. It turned out in our recent study, however, that, in some ranges of axial ratios (e.g., for very small c/a values), the available tables and graphs do not provide sufficient resolution for obtaining the demagnetizing factors with reasonable accuracy. It was decided to calculate these missing values, and they are presented here in both tabular and graphical form by giving instructions for how to obtain conveniently further interpolated data. In addition, the previous and current demagnetizing factor data have been replotted and fitted to a polynomial function with high accuracy. The functional form of these fitting polynomials is presented in a table for the whole range of the axial ratios b/a and c/a. By graphically displaying these functions, one can obtain, in a relatively simple manner, the demagnetizing factors of a general ellipsoid with known axial ratios without the need to directly calculate through the exact formulae. This may be helpful in obtaining a quick estimate for the demagnetizing factors of any rectangular ferromagnetic slab of interest.

Terminological Issues and Propositions in the Search for an Ontology of Harmonic Structures

This article presents a fragment from a larger research with the intention of anticipating some of its main topics, which aim to assemble a pedagogical theoretical body for music harmony in the context of the globalized and diverse world of the 21st century. The research fragment presented discusses terminological issues and propositions for an ontological study of harmonic structures that concerns itself with the definition of what types of musical sound objects of definite pitch do exist, how many are there, which properties they possess and their musical consequences, all organized in a logical taxonomical system referred to by means of an adequate terminology. The text first establishes the need for such an ontology, and proceeds with a description of the terminological issues involved in a secondary term formation action, a subsequent renaming effort that is all the more challenging when dealing with a field with a huge lifetime such as music theory. The methodology used in the terminological recreation is then described, explaining its preference for terms that, regardless of their lexicographic origins and prevalence, are single-words that provide biunivocal association, that avoid ambiguity by synonymy and polysemy, that are self-explanatory, and that are of easy translation using same-lexeme words similar in graphical form. It is then given a brief summary of the structure of the created ontology, followed by the definitions, lexicographic origins, and neologism-creating derivational strategies for all its main proposed terms, including those to be used in the classifications of harmonic structures according to the criteria of cardinality, chirality, azimuth, triadic intrinsicality, monadic, triadic, and transpositional proclivities, limiting characteristics, and modalization, superset and subset relationships. To close the text, a schematic view of the organizational structure of the ontology is shown, together with its translation into three different languages.

Deep Learning-Based Detection of Android Malware using Graph Convolutional Networks (GCN)

The study is centered around identifying Android malware using deep learning methods through Graph Neural Networks (GNNs) and Graph Convolutional Networks (GCNs). With Android being widely used worldwide ensuring the security of released applications poses a challenge. Conventional malware detection techniques, like dynamic analysis have limitations in recognizing new malware types leading to a shift towards machine learning and deep learning solutions. The research introduces a malware detection system that employs GNNs particularly focusing on GCNs to analyze the relationships within an applications code by transforming APK files into graph formats. The system follows stages including data gathering, feature extraction, graph construction, model training and implementation. By concentrating on function call graphs the system proves effective in identifying software surpassing traditional machine learning methods in terms of accuracy, precision, recall and F1 score. The GCN based model shows enhancements over approaches with an accuracy rate of 95% compared to 89%, for traditional machine learning models. This progress highlights the potential of learning techniques in bolstering Android security. The system excels not in identifying software but also proves versatile, for different uses like screening apps, in stores and functioning as a standalone antivirus program.

KINETIC MODELLING OF BIOCHEMICAL REACTIONS USING MATHСAD ANALYTICAL TOOLKIT

Background. The study of the kinetics of biochemical reactions provides a better understanding of how biological processes occur in living organisms. Understanding the peculiarities of such reactions is important for the development of new technologies, in particular for the production of biologically active substances and for the synthesis of drugs. A powerful tool for solving problems in biochemical reaction kinetics is mathematical modelling, which can be carried out using computer mathematical systems, in particular the MATHCAD analytical toolkit. Aim: to substantiate the feasibility and effectiveness of using the MATHCAD analytical toolkit to solve problems of kinetic modelling of biochemical reactions in pharmaceutical research, and to review the capabilities of MATHCAD for computer modelling in pharmacy. Materials and methods. In the context of studying the rate of enzymatic reactions and developing models, such as the Michaelis-Menten model, to describe reactions in which enzymes catalyze the transformation of substrates, the use of a computer mathematical system (CMS) is considered. CMS is a software package and environment for performing mathematical computations, modelling and visualization. The possibilities of using the MATHCAD system to create mathematical models of biochemical reactions based on kinetic equations are demonstrated. This involves the creation of differential equations describing changes in reagent concentrations over time. These equations were solved using numerical methods in MATHCAD. In addition, the results obtained are visualized using 3D graphics in MATHCAD. The stages of using the MATHCAD analytical toolkit in the kinetic modelling of biochemical reactions have been determined. Results. The use of MATHCAD in the kinetic modelling of biochemical reactions is effective for the study of: (1) the kinetics of enzymatic reactions, e.g. reactions in which an enzyme catalyzes the conversion of a substrate into a product; (2) biochemical reactions that take place in reaction vessels in which reagents mix and interact; (3) modelling of reactions in reaction vessels based on the solution of differential equations of reaction kinetics; (4) the effect of inhibitors or activators on enzymatic reactions; (5) scenarios of interaction of reagents to determine changes in the kinetics of reactions that occur when different active substances are introduced; (6) kinetics of biochemical reactions in cases where reactions are accompanied by diffusion of reagents through membranes or other semi-permeable barriers; (7) modelling the effect of diffusion processes on the kinetics of biochemical reactions; (8) models describing the kinetics of decomposition of substances, for example the decomposition of biologically active compounds in the body or in the environment; (9) predicting the effect of changes in the conditions of the reaction medium (temperature, pH, concentration of reagents) on the kinetics of biochemical reactions. It is substantiated that model descriptions of the kinetics of biochemical reactions are important for forming an understanding of the functions of biological systems, including metabolism, enzymatic reactions, and other physiological phenomena. Tools have been used to visualize the modelling results in the form of three-dimensional MATHCAD graphics, which improves the understanding of the reaction mechanism and allows a more thorough analysis of its kinetics. Conclusion. MATHCAD provides an optimized environment for kinetic modelling of biochemical reactions through its ergonomic interface. Particular advantages are the ability to work with symbolic expressions and to use a wide range of built-in functions and tools for exploring mathematical models and visualizing results. The obtained results may be important both for further scientific pharmaceutical research and for implementation in the training of future Masters of Pharmacy in the discipline of "Computer Modelling in Pharmacy" in higher medical education institutions.

Implementation of Business Intelligence for Product Optimization to Enhance Profitability Through theUtilization of Synergies Among the Product Departments of the Look Company for the Period 2019-2022

This research discusses the implementation of Business Intelligence (BI) to enhance the profitability of The Look Company through the synergy of product departments. In the era of big data, a company's ability to process and analyse data becomes a crucial factor in achieving competitive advantage. This research aims to present data information from The Look Company's Product Departments in the form of visualizations, graphs, and diagrams that can be used as indicators for decision-making. It also aims to identify products that are not generating significant profitability for the company in order to optimize production costs and to identify products that experience frequent cancellations and returns. This analysis and recommendations are intended to assist The Look Company in its decision-making processthrough the implementation of a comprehensive and detailed Business Intelligence study. Additionally, this research outlines the steps of data collection and processing methods using tools such as Google Colab, Postgree, and Tableau to generate visualizations, graphs, and diagrams that provide indicators and recommendations for decision-making within The Look Company. The research results indicate that the BI data visualization dashboard plays a crucial role in determining business strategies and providing rapid and accurate decision-making recommendations.

Novel exact traveling wave solutions of the space-time fractional Sharma Tasso-Olver equation via three reliable methods

The dominant intention of this article is to extract the new exact traveling waves solutions of the nonlinear space-time fractional Sharma-Tasso-Olver equation in the sense of beta-derivative by using three integration schemes namely, Riccati-Bernoulli (RB) sub-ODE method, Generalized Bernoulli (GB) sub-ODE method and Generalized tanh (GT) method. By the virtue of employed techniques, different types of solutions are obtained in the form of trigonometric, hyperbolic, and exponential functions respectively. The obtained solutions are also verified for the aforesaid equation through symbolic soft computations. To promote the vital propagated features; some investigated solutions are exhibited in the form of 2D and 3D graphics by passing on the specific values to the parameters under the confined conditions. Further, based on the bifurcation theory, we examine the phase portrait of the proposed nonlinear equation. Furthermore, we ensure that all the solutions are innovative and have remarkable impacts on the prevailing solitary wave theory literature.

New mathematical models for the load factor of slip pairs of the ship propulsion complex for non-Newtonian lubricants

The method of boundary variation was applied to the solution of the boundary value problem with respect to the Reynolds differential equation for the lubricating layer in the sliding bearings of ship power plants and auxiliary ship equipment, which made it possible to obtain analytical representations for the hydrodynamic pressure, shear stresses, as well as the integral characteristics of the lubricating layer. This made it possible to build new, easy-to-use mathematical models for the load factor (carrying force factor) of the sliding pairs of the ship propulsion complex, considering the non-Newtonian properties of lubricants, i.e. in the case of the dependence of dynamic viscosity on pressure and temperature. Mathematical models take into account geometric parameters of bearings, operational parameters: relative radial clearance and relative eccentricity, angular velocity; as well as viscosity characteristics of lubricants, in particular, dynamic viscosity and piezo coefficient of viscosity of lubricants. A criterion for the applicability of lubricants for given operating characteristics and bearing parameters has been developed, which uses the viscosity characteristics of lubricants. The research results are illustrated in the form of tables and graphs.

Амплитудно-частотные характеристики виброзащитной системы сиденья с трехсегментной статической силовой характеристикой и участком квазинулевой жесткости

Vibration protection for heavy equipment operators is important. Exposure to vibration is harmful to health. Vibration protection seats are used for protection. Reliable passive systems with quasi-zero stiffness are promising. For the developed design of the seat on the basis of parallelogram mechanism, spring, cable and rollers, the study of vibration-protective properties is carried out. The design scheme has been developed, key parameters have been selected, and their study on vibration protection parameters has been carried out. The static force response was approximated by three linear segments with a horizontal mean. The known dynamic model describing forced oscillations of the mass was used. The displacement of the base was given by a harmonic function. Vibration protection systems with three-segment and with one-segment static force response were compared. The comparison was carried out in terms of transmission coefficients, accelerations and suspension displacement. The results of the computational experiment are presented in the form of graphs: amplitude-frequency characteristics in the form of transmission coefficients in acceleration and displacement, at different amplitudes of base vibrations, damp-ing and stiffness coefficients. Dependences of average values of transmission coefficients in the investigated frequency range are given. Vibration damping is effective when the maximum suspension travel does not exceed the middle section of the static characteristic. The most effective vibration damping, according to the average value of the acceleration transfer coefficient, is achieved at minimum, and for a single-segment characteristic — zero values of the stiffness coefficient. The presence of extreme segments in the characteristic significantly increases the average values of the accelera-tion and displacement transfer coefficients of the suspension. Seat vibration protection systems in real conditions should have a limitation of suspension displacement for ergonomic reasons. The values of the stiffness coefficients of the extreme parts of the static force response, according to the criterion of minimizing the average value of the acceleration transfer coefficient, should be minimized. To substantiate the optimal values of the stiffness coefficients of the extreme sections of the characteristic and viscous friction coefficients, it is advisable to conduct additional studies under step and stochastic impacts.

Revealing Obstacles: Examining High School Students' Difficulties in Understanding Digestive System Concepts in Class XI MIPA

This research aims to determine the internal and external factors that cause learning difficulties experienced by class XI students when studying digestive system material. The research used a survey method with a cross-sectional research design involving high school students from three schools in Banten and a class XI biology teacher. Data collection using questionnaires and interviews. Data analysis was carried out using Microsoft Office Excel, and the findings were displayed in the form of a percentage graph. The results of measuring the student learning interest showed that 55.53% of students stated that difficulty in distinguishing types of digestive system enzymes was one of the factors in students' lack of interest in understanding the material. The learning study habits indicators showed that only 28.9% of students applied understanding of the material in their daily lives, this triggered students' lack of memory for the material. Meanwhile, the teacher teaching method indicator showed that 24.43% of students stated that the learning process in class felt monotonous, this was due to the use of learning strategies by teachers which was still relatively lacking, apart from that in the learning facilities indicator, the teaching materials used in schools were still dominant rely on textbooks

Формування графічної компетентності майбутніх фахівців аграрного профілю у кризових умовах

The article analyzes the theoretical and methodological foundations of the formation of graphic competence of future specialists of the agrarian profile in crisis conditions. The purpose of the article is to study the specifics of graphic activity and the organization of graphic training of students of agrarian universities in crisis conditions. The influence of the war on the organization of the educational process in agrarian institutions of higher education has been clarified. Attention is focused on the specifics of graphic activity and the need to take it into account in remote forms of education, which consists in operating with imaginary spatial images, translating visual information into an imaginary form and reproducing imaginary images into a graphic form. The transition to remote forms of education in crisis conditions complicates communication between the student and the teacher, the educational material is presented more intensively than it is provided by the educational programs, students have to spend more time on independent processing of educational information. For the effective formation of the graphic competence of future specialists, we distinguish two groups of pedagogical conditions: general educational (characteristic of studying any discipline at the university) and specific (inherent in the graphic training of students). The peculiarity of the isolated conditions is that they take into account the shift in emphasis to independent activity caused by the crisis situation in the country. A set of techniques proposed by us in graphic training (special geometric tasks for the use of graphic means of displaying information for integrated disciplines; choosing the type of projection and display of a technical object or process; modeling; a combination of different perspectives; graphic exercises with the construction of models; the use of technologies to expand the ability to graphically reproduce any information, etc.

SEMI-DOMAIN SOLUTIONS TO THE FRACTAL (3+1)-DIMENSIONAL JIMBO–MIWA EQUATION

In this work, the variational direct method (VDM) based on the variational theory and Ritz-like method, combined with the fractal two-scale transformation, is employed to construct the semi-domain solutions of the (3+1)-dimensional fractal Jimbo–Miwa (JM) equation, which is derived by He’s fractal derivative. The applicability and effectiveness of the acquired solutions on the Cantor sets are presented through the numerical results in the form of 3-dimensional graphs. In addition, as a comparison, the exact solutions of the classic (3+1)-dimensional JM equation for [Formula: see text] are also illustrated. The obtained results in this work are expected to open new perspectives for the traveling wave theory.

Propulsion Technologies for CubeSats: Review

This paper explores the wide-ranging topography of micro-propulsion systems that have been flown in different small satellite missions. CubeSats, known for their compact size and affordability, have gained popularity in the realm of space exploration. However, their limited propulsion capabilities have often been a constraint in achieving certain mission objectives. In response to this challenge, space propulsion experts have developed a wide spectrum of miniaturized propulsion systems tailored to CubeSats, each offering distinct advantages. This literature review provides a comprehensive analysis of these micro-propulsion systems, categorizing them into distinct families based on their primary energy sources. The review provides informative graphs illustrating propulsion performance metrics, serving as beneficial resources for mission planners and satellite designers when selecting the most suitable propulsion system for a particular mission requirement.

Monitoring dan Pencegahan Serangan Judi Online (Slot Gacor) pada Website

A website is a complex tool for presenting information. The security of a website is very important to support the reputation of the website. The rise of online gambling has now penetrated the website, the most dangerous is when the website has been infiltrated with an online gambling page. The purpose of the research is to prevent and monitor the website against online gambling hacker attacks. This research uses a descriptive method approach, namely by monitoring and observing the website, we try to provide an in-depth explanation of monitoring and preventing online gambling attacks (Slot Gacor) by utilizing Cloudflare services. Cloudflare is implemented as a security system on the website. In this research, the website that became a case study was the bpti.uhamka.ac.id website with the research location in the UHAMKA data center room. Data collection techniques and data analysis are carried out by direct observation through the cloudflare website. The data analyzed in the form of graphs and money url paths have been blocked. Research results Within 8 days there were 126 url paths that could be blocked by cloudflare and all of them contained online gambling with most of them being gacor slots. Cloudflare has successfully blocked hackers by filtering path URLs from the originating website.

Classification of residual hearing of deaf students based on audiometer using google data studio visualization method

Classification of hearing loss is necessary because it provides treatment or learning methods for students which are certainly not the same. This classification is displayed in a graphical form because graphics are able to provide information quickly. The results of this writing are information in the form of visualization of the residual hearing which is grouped according to the decibels or residual hearing they have. Patterns that will be applied in learning will later be adjusted based on classification, so that students can comfortably follow the learning process. When creating this visualization, use Google Data Studio because it can be used to represent complex data sets in an interesting and clear way. The data used are data on deaf students for 2014-2021, with a total of 357 data and 14 attributes. The results of data processing are in the form of graphs of students for each generation, distribution of student demographics, and classification of student hearing measurement results. From the visualization results, 3 categories were obtained, with the results being 9 light categories,, 129 medium categories and 219 heavy categories. The mild category will receive oral treatment, while the moderate and severe categories will be given sign language and written treatment