Construction Of Diagrams Research Articles

FORMULATION OF NANOSTRUCTURED LIPID CARRIERS OF HALOPERIDOL PREPARED BY USING CLARIFIED BUTTER

Objective: To develop the nanostructured lipid carriers (NLC’s) using clarified butter. Methods: Haloperidol-loaded microemulsion templates were prepared by using Smix of Tween 80 and propylene glycol in the ratio 1:2. The selection of the mixture of surfactant and co-surfactant (Smix) and their appropriate proportion were decided by the traditional way of construction of pseudo ternary phase diagrams. 22 factorial design was used to check the amenability of the formulation for its successful scale-up. Sonication time and the amount of Smix were selected as independent variables and their influence on the globular size (Y1) of the microemulsions formed was evaluated by using statistical models. Composition of the optimized microemulsion template was further used to prepare haloperidol-loaded NLC’s by ‘microemulsion quenching method’. Results: The microemulsion formulations containing Tween 80 as a surfactant and propylene glycol as a co-surfactant exhibited the smallest globular size and hence this composition was used further to implement factorial design as design of experiments. The statistical analysis of the data suggested that the microemulsion formulation can be scaled up successfully. NLC’s were prepared from the optimized microemulsion formulation as template. The globular size of NLC’s was confirmed by Transmission Electron Microscopy and was observed to be in the range of 300 to 600 nm. Conclusion: The present work suggested that the latency of the clarified butter as a natural blend of solid lipid and liquid lipids can be successfully explored to prepare nanostructured lipid carriers.

An efficient algorithm for approximate Voronoi diagram construction on triangulated surfaces

Voronoi diagrams on triangulated surfaces based on the geodesic metric play a key role in many applications of computer graphics. Previous methods of constructing such Voronoi diagrams generally depended on having an exact geodesic metric. However, exact geodesic computation is time-consuming and has high memory usage, limiting wider application of geodesic Voronoi diagrams (GVDs). In order to overcome this issue, instead of using exact methods, we reformulate a graph method based on Steiner point insertion, as an effective way to obtain geodesic distances. Further, since a bisector comprises hyperbolic and line segments, we utilize Apollonius diagrams to encode complicated structures, enabling Voronoi diagrams to encode a medial-axis surface for a dense set of boundary samples. Based on these strategies, we present an approximation algorithm for efficient Voronoi diagram construction on triangulated surfaces. We also suggest a measure for evaluating similarity of our results to the exact GVD. Although our GVD results are constructed using approximate geodesic distances, we can get GVD results similar to exact results by inserting Steiner points on triangle edges. Experimental results on many 3D models indicate the improved speed and memory requirements compared to previous leading methods.

Design and Assessment of a Microemulsion-Based Transdermal Drug Delivery System for Meloxicam; Examination of Formulation Ingredients

Background: The goal of creating meloxicam-loaded microemulsion formulations was to increase meloxicam permeability through the skin. Using pseudo-ternary phase diagram construction and full factorial design, eight formulations with three independent variables (water percent, oil percent, and surfactant/co-surfactant percent) were selected to be prepared. 
 Methods: This research evaluated the formulation's characteristics, including particle size, viscosity, and release profile. FT-IR and DSC techniques were also utilized to investigate the effect of microemulsion components on rat abdomen skin, and the permeability of meloxicam-loaded microemulsions via rat abdomen skin was also evaluated by calculating permeability parameters such as Jss, Dapp, Tlag, ERflux, ERD, and ERP. 
 Results: When compared to a saturated aqueous solution of meloxicam as a reference, the findings showed that all microemulsion (ME) formulations considerably increased meloxicam permeability through rat skin. Water percent had a direct and significant relationship with Jss, and oil percent had a direct and significant relationship with Dapp, according to analysis regression. 
 Conclusion: ME components also caused alterations in the skin's lipoprotein bilayers, which might enhance formulation permeability through the skin.

THE INFLUENCE OF FASHION INNOVATIVENESS ON BEHAVIORAL INTENTION MEDIATED BY BRAND IMAGE AND BRAND LOVE

The study aimed to investigate the impact of fashion innovation, brand image, brand love, and behavioral intention on Customers of Ria Miranda products in Malang. The research sample consisted of 200 purposively selected Customers of Ria Miranda products, with the data being analyzed using the partial least squares (PLS) methodology through SmartPLS. The research methodology involved an assessment of the internal consistency of the measurement models, the examination of outer models, the construction of path diagrams, and the testing of hypotheses. The study's findings suggest that fashion innovation directly impacts customer behavioral intention toward Ria Miranda products. Additionally, brand image and love mediate between fashion innovation and customer behavioral intention towards Ria Miranda products. To conclude, the study demonstrated the significant impact of fashion innovation on customer behavioral intention towards Ria Miranda products and the mediating role of brand image and brand love in this relationship. The high satisfaction level of these customers results in strong brand loyalty, further strengthened by brand love. The findings of this study indicate that customer behavioral intention can be formed if the fashion product management focuses on exploring the existing advantages of the brand, such as the dimension of fashion innovativeness while considering the brand image and the emotional feelings of the customer. When processed, a high-quality brand image and the emotional feelings of the customer play a full role as mediators in affecting behavioral intention.

Semianalytic stability algorithm in the frequency domain for interrupted milling

The construction of stability diagrams of interrupted milling cases is generally carried out by means of time-consuming numerical methods in either frequency or time domain, since the period doubling lobes arising under interrupted cutting are omitted by the time-averaged parametric scan of the traditional zeroth order approximation. This paper presents a novel seminalytic method in the frequency domain for interrupted milling. Taking advantage of their analytical chatter frequency distribution, this method adds the period doubling lobes calculated in a single frequency scan to the existing Hopf limits of the zeroth order solution. This, together with intelligent selection of scanning frequency ranges and truncation to the minimum set of harmonics, allows very fast calculation of the stability charts of interrupted milling cases while retaining the analytical basis and advantages of the zeroth order algorithm. The method accurately describes the stability limits at period doubling dominated zones and improves the existing zeroth order solution, but exhibits slight inaccuracies in the prediction of Hopf boundaries due to mode interaction and harmonic truncation effects.

A decision tree analysis to predict clinical outcome of minimally invasive lumbar decompression surgery for lumbar spinal stenosis with and without coexisting spondylolisthesis and scoliosis

Implementing machine learning techniques, such as decision trees, known as prediction models that use logical construction diagrams, are rarely used to predict clinical outcomes. To develop a clinical prediction rule to predict clinical outcomes in patients who undergo minimally invasive lumbar decompression surgery for lumbar spinal stenosis with and without coexisting spondylolisthesis and scoliosis using a decision tree model. A retrospective analysis of prospectively collected data. This study included 331 patients who underwent minimally invasive surgery for lumbar spinal stenosis and were followed up for ≥2 years at 1 institution. Self-report measures: The Japanese Orthopedic Association (JOA) scores and low back pain (LBP)/leg pain/leg numbness visual analog scale (VAS) scores. Physiologic measures: Standing sagittal spinopelvic alignment, computed tomography, and magnetic resonance imaging results. Low achievement in clinical outcomes were defined as the postoperative JOA score at the 2-year follow-up <25 points. Univariate and multiple logistic regression analysis and chi-square automatic interaction detection (CHAID) were used for analysis. The CHAID model for JOA score <25 points showed spontaneous numbness/pain as the first decision node. For the presence of spontaneous numbness/pain, sagittal vertical axis ≥70 mm was selected as the second decision node. Then lateral wedging, ≥6° and pelvic incidence minus lumbar lordosis (PI-LL) ≥30° followed as the third decision node. For the absence of spontaneous numbness/pain, sex and lateral olisthesis, ≥3mm and American Society of Anesthesiologists physical status classification system score were selected as the second and third decision nodes. The sensitivity, specificity, and the positive predictive value of this CHAID model was 65.1, 69.8, and 64.7% respectively. The CHAID model incorporating basic information and functional and radiologic factors is useful for predicting surgical outcomes.

Multiscale Partial Symbolic Transfer Entropy for Time-Delay Root Cause Diagnosis in Nonstationary Industrial Processes

Nonstationary characteristics and lack of time delays analysis remain two large obstacles to diagnosing fault root cause in industrial processes. However, ignoring these two issues, many traditional methods tend to introduce some spurious or indirect causal relationships that interfere with root cause judgments. In this article, multiscale partial symbolic transfer entropy (MPSTE) is proposed to handle the above-mentioned problems. On the one hand, a multivariate multiscale filter module of MPSTE is designed to estimate the information transfer on multiple time scales and detect time delays while considering the indirect causality of the multivariate industrial system. On the other hand, to capture the causal information from the nonstationary processes, MPSTE introduces a segmental symbolization procedure and maps time series into finite rank vectors, overcoming the limitation of stationarity. Moreover, two causal criteria for MPSTE are constructed to identify the direction and significance level of causality correspondingly. MPSTE can thus provide sufficient information for causal relationships and exclude spurious causality. Finally, a causal diagram construction strategy with time delay based on MPSTE is established to diagnose the root cause and trace the fault propagation path. The results of experimental verification in a coal mill rig prove the effectiveness of the proposed strategy.

Dynamical environments of (486958) Arrokoth: prior evolution and present state

ABSTRACTWe consider dynamical environments of (486958) Arrokoth, focusing on both their present state and their long-term evolution, starting from the KBO’s formation. Both analytical (based on an upgraded Kepler-map formalism) and numerical (based on massive simulations and construction of stability diagrams in the 3D setting of the problem) approaches to the problem are used. The debris removal is due to either absorption by the KBO or by leaving the Hill sphere; the interplay of these processes is considered. The clearing mechanisms are explored, and the debris removal time-scales are estimated. We assess survival opportunities for any debris orbiting around Arrokoth. The generic chaotization of Arrokoth’s circumbinary debris disc’s inner zone and generic cloudization of the disc’s periphery, which is shown to be essential in the general 3D case, naturally explains the current absence of any debris in its vicinities.

Практическая и учебно-методическая роли векторных диаграмм силовых трансформаторов

The analysis of scientific, technical and educational literature devoted to the methods of construction and use of vector diagrams of power transformers is carried out. Questions about their applicability in practical calculations remain open. The logic, unambiguity and correctness of the applied method of their construction is questionable. It is shown that vector diagrams of power transformers cannot be used in practical calculations, since they do not allow determining the values of the quantities characterizing the operation of the transformer, since it is impossible to depict all vectors on one diagram with the accuracy necessary for calculations. The applied order of diagram construction leads to an erroneous understanding of cause-and-effect relationships between physical processes in a transformer, contradicts accepted physical concepts and rules of electrical engineering. The requirements that vector diagrams must meet for their effective use for educational and methodological purposes are formulated. These requirements are achieved by applying the proposed new approach to the construction of vector diagrams.

Unveiling the mechanisms behind surface degradation of dental resin composites in simulated oral environments.

Dental resin composites are widely used as restorative materials due to their natural aesthetic and versatile properties. However, there has been limited research on the degradation mechanisms of these composites in gastric acid environments, which would be common in patients with gastroesophageal reflux. This study aims to investigate the degradation behavior of dental composites immersed in simulated oral environments, including acid, saliva, and water. Mechanical and morphological properties of the composites, upon immersion in the simulated environments, were thoroughly examined using hardness testing and SEM imaging. Qualitative analyses of the ions leached from the polymer matrix and fillers were conducted using XPS and ICP-MS. In addition, the thermodynamic stability of the inorganic fillers of the composites in aqueous solutions across a wide range of pH values was theoretically studied through construction of Pourbaix diagrams. This study proposed a mechanism for composite leaching involving interactions between the matrix's hydrophilic groups and the aqueous immersion media, leading to swelling and chemical degradation of the composites. Furthermore, it was demonstrated that filler leaching was followed by ion exchange with Ca and P, resulting in the formation of hard calcified layers on the composite surface. The current findings provide valuable insights into the development of new composite materials with improved durability and resistance to degradation, especially for patients suffering from gastroesophageal reflux.

Limits of entrainment of circadian neuronal networks.

Circadian rhythmicity lies at the center of various important physiological and behavioral processes in mammals, such as sleep, metabolism, homeostasis, mood changes, and more. Misalignment of intrinsic neuronal oscillations with the external day-night cycle can disrupt such processes and lead to numerous disorders. In this work, we computationally determine the limits of circadian synchronization to external light signals of different frequency, duty cycle, and simulated amplitude. Instead of modeling circadian dynamics with generic oscillator models (e.g., Kuramoto-type), we use a detailed computational neuroscience model, which integrates biomolecular dynamics, neuronal electrophysiology, and network effects. This allows us to investigate the effect of small drug molecules, such as Longdaysin, and connect our results with experimental findings. To combat the high dimensionality of such a detailed model, we employ a matrix-free approach, while our entire algorithmic pipeline enables numerical continuation and construction of bifurcation diagrams using only direct simulation. We, thus, computationally explore the effect of heterogeneity in the circadian neuronal network, as well as the effect of the corrective therapeutic intervention of Longdaysin. Last, we employ unsupervised learning to construct a data-driven embedding space for representing neuronal heterogeneity.

Modeling frame of a diesel locomotive bogie in solidworks software

The article considers the possibility of using the finite element method for strength calculations of nodes and parts of modern locomotives. There are examples of solid-state models construction of bogie frames in SolidWorks software package. Developed finite-element models allow determining the tense-strained state of the elements of the crew part of locomotives. The final outcome of modeling is the construction of stress distribution diagrams in the locomotive bogie frame. The data obtained as a result of finite-element modeling can be recommended for use when creating new modern units of locomotives as well as for modernizing and increasing the reliability of existing.

Outdoor nature-based play in early learning and childcare centres: Identifying the determinants of implementation using causal loop diagrams and social network analysis.

Nature-based play benefits children's health and development. However, the delivery of this in early learning and childcare centres (ELC) is extremely diverse, and implementation is not well understood. We applied a systems science perspective to understand the factors crucial to implementing nature-based outdoor play in ELC settings. Through Group Model Building workshops with 20 participants in managerial and practitioner roles, crucial factors were appraised using Causal Loops Diagrams. Twelve thematic causal loops emerged. Network analysis was employed to analyse the diagram. Exponential Random graph models explained the diagram construction process. Centrality measures alongside conditional uniform tests identified six leverage factors: use of outdoor space, culture of being outdoors, ELC culture of outdoor play, perceived child safety and enjoyment, educator confidence and educator agency. This research brings novel and practically relevant evidence about the important factors, and interdependencies, involved in the implementation of outdoor play practice within ELC settings.

Qualitative study of pathways to care among adults with diabetes in rural Guatemala

ObjectiveThe burden of diabetes mellitus is increasing in low-income and middle-income countries (LMICs). Few studies have explored pathways to care among individuals with diabetes in LMICs. This study evaluates care...

Understanding explanatory and pragmatic trials: Examples from randomized controlled trials on vertebroplasty

ObjectivesTo better understand the explanatory–pragmatic distinction in the design and interpretation of randomized controlled trials (RCTs). MethodsWe review the explanatory–pragmatic distinction in clinical trial design. We use the PRECIS-2 tool to evaluate the trial design of selected RCTs on percutaneous vertebroplasty for osteoporotic vertebral compression fractures. We discuss difficulties in the selection of criteria and in the construction of PRECIS diagrams. We also examine how inconsistency in the selection of various items of trial design can cause confusion in the interpretation of results. ResultsThe selection of criteria and the scoring of multiple PRECIS domains were subjective and thus debatable. The pragmascope patterns of various vertebroplasty trials were heterogeneous. Many trials had both pragmatic and explanatory components. Some placebo-controlled trial goals seem to have been explanatory, but their design actually included enough pragmatic items such that the meaning of negative trial results remains ambiguous. ConclusionThe results of a trial cannot be interpreted without understanding the various design choices made along the explanatory-pragmatic spectrum.

Analytical model of deformation of reinforced concrete columns based on fracture mechanics

When conducting seismic calculations of reinforced concrete buildings and structures, it is quite important to use nonlinear models of structural performance, including those taking into account the overcritical operation in the fracture stage. The application of such models is especially important if the structures have an initial damage from fire or corrosion, as well as mechanical damage caused by force factors. The purpose of this study is to develop an analytical model of the deformation of eccentrically compressed reinforced concrete columns considering the stage of failure, which includes such processes as spelling of the protective layer, loss of stability of compressed reinforcement, and softening of confined concrete after reaching the design resistance. The existing models describing hysteresis behavior of reinforced concrete structures under low-cycle loading have been reviewed. The models have been analyzed in terms of considering the defining monotone curves, which are the boundaries of cyclic deformation. The model proposed in the research is constructed by analyzing the stages of the stress-strain state of a reinforced concrete column. At each stage, formulas are found for determining moment and curvature by solving equations of equilibrium of internal forces. Calculations based on the obtained model for a particular reinforced concrete column are carried out, monotonous diagrams are obtained, and a conclusion about the significant influence of the level of axial load on the character of deformation is made. On the basis of the obtained model, the construction of hysteresis diagrams under low-cycle loading is expected in the future.

Network Pharmacology and Molecular Docking Analysis on Molecular Targets and Mechanisms of Aidi Injection Treating of Nonsmall Cell Lung Cancer.

Aidi injection (ADI) is a compound preparation injection of Chinese herbs used to treat patients of nonsmall cell lung cancer (NSCLC) in China. This study aimed to reveal the mechanism of ADI in the treatment of NSCLC by using network pharmacology and molecular docking. The related targets of ADI and NSCLC were obtained from multiple databases. The network diagram of disease-drug-components-targets (DDCT) and protein-protein interaction (PPI) was constructed to screen key targets. Then, the key targets and main signaling pathways were screened by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Next, in order to validate the results of network pharmacology, expression analysis and survival analysis of key genes were performed. Finally, we carried out the technology of molecular docking to further validate the accuracy of the above results. A total of 207 targets of ADI and 5282 targets of NSCLC were obtained finally. Through the construction of DDCT and PPI network diagrams, 28 key targets were finally obtained. The results of the KEGG enrichment analysis indicated that multiple signaling pathways were associated with NSCLC, which included the MAPK signaling pathway, the IL-17 signaling pathway, and the PI3K/AKT signaling pathway. The key genes in the signaling pathway mainly include TP53, CASP3, MMP9, AKT1, PTGS2, and MAPK1. The results of differently expressed analysis of key genes showed that TP53, CASP3, MMP9, AKT1, PTGS2, and MAPK1 had statistical differences in lung squamous cell carcinoma (LUSC) compared with normal tissue (p < 0.001). In lung adenocarcinoma (LUAD), the expression of TP53, CASP3, MMP9, AKT1, and PTGS2 had statistical differences compared with normal tissue (p < 0.001), while the expression of MAPK1 had no statistical difference (p > 0.05). The results of survival analysis of key genes showed that AKT1, MAPK1, CASP3, MMP9, TP53, and PTGS2 had statistical differences in the OS or RFS of NSCLC patients (p < 0.05). In addition, the results of molecular docking indicated that the key genes and the main components have good docking activity. This study revealed the potential mechanism of ADI in the treatment of NSCLC with multipathways and multitargets and provided a scientific basis for the in-depth study of ADI in the treatment of NSCLC.

Development of a method for determining the rational installation location of technical means of symmetry in an electrical complex with the presence of an electric motor load

The work is devoted to the development of a methodological approach to correcting the level of supply voltage in the electrical network by developing an algorithmized method for determining the rational installation location of technical means of symmetry in an electrical complex with the presence of an electric motor load. The developed method makes it possible to implement processes aimed at ensuring the effective functioning of the electrical complex with the presence of an electric motor load in conditions of low-quality supply voltage. The proposed method, based on software, provides design procedures for calculating various options for symmetry and choosing the most economically feasible. Attention is focused on the main criteria for evaluating decisions made when designing the location of technical means of symmetry in the electrical complex. The architecture, the main functional features of the application program as a tool for implementing the calculation method are considered. The program ensures the implementation of electrical calculations in the design, modernization and operation of electrical networks. It provides for the construction of schematic diagrams of sections of electrical complexes with installed means of symmetry. The results of experimental studies demonstrating the effectiveness of the developed method in solving problems of voltage symmetry in the supply electrical network are presented. It is obvious that the developed approach, based on the automatic selection of the locations of the means of symmetry depending on the operating conditions of the electric motor load, makes it possible to automate the design procedures for voltage normalization in the electrical network. Provides minimization of voltage asymmetry in the supply electrical network, contributes to improving the operational reliability of low-voltage asynchronous electric motors. The obtained research results and prospects for the application of the developed approach are discussed, both for solving complex design problems and for the economic justification of local design solutions. A detailed analysis and formalization of the results of the study with relevant conclusions were carried out.

Characterizing Learners’ Construction of Geometry Diagrams in Dynamic Geometry Environments

As a distinct mode of mathematical representation and communication, geometry diagrams are both signs that represent abstract geometric concepts and visual images that offer graphical-spatial properties. Dynamic geometry environment offers a wide range of tools for its users to create and interact with geometry diagrams. In this paper, I propose a framework to characterize geometry diagrams that learners create in DGEs. The framework considers a learner’s approach to creating a geometry diagram (i.e., perceptualbased, measurement-based, construction-based, and transformation-based), the driving force that guides the learner’s specific actions in a DGE (i.e., tool-driven, and property-driven), and the constraints in the resulting diagram (i.e., drawing, underconstrained, overconstrained, and appropriately constrained). Examples of student work on two geometry construction problems are used to illustrate the use of the framework. These examples show that the proposed framework provides a useful tool to characterize geometry diagrams in DGEs.

Machine learning accelerates the materials discovery

As the big data generated by the development of modern experiments and computing technology becomes more and more accessible, the material design method based on machine learning (ML) has opened a new paradigm for materials science research. With its ability to automatically solve complex tasks, machine learning is being used as a new method to help discover the relevance of materials, understand materials' properties, and accelerate the discovery of materials. This paper first introduces the general process of machine learning in materials science. Secondly, the applications of machine learning in material properties prediction, classification and identification, auxiliary micro-scale characterization, phase transformation research and phase diagram construction, process optimization, service behavior evaluation, accelerating the development of computational simulation technology, multi-objective optimization and inverse design of materials are reviewed. Finally, we discuss the main challenges and possible solutions in machine learning, and predict the potential research directions.