Dynamic Applications Research Articles

Mechanism and Application of Attitude and Orbit Coupling Dynamics for Spacecraft Proximity Relative Motion

Mechanism and Application of Attitude and Orbit Coupling Dynamics for Spacecraft Proximity Relative Motion

Scientific Study of Brassinosteroids on Production of Fruit Crops: A Review

Brassinosteroids (BRs) are considered as the sixth group of plant growth regulators with significant growth promoting activity in many horticulture and agriculture crops. This phytohormone was discovered from the pollen of Brassica napus L. on the basis of their ability to promote growth. Currently, more than 70 BRs have been isolated from different plant species, but only three viz., Brassinolide (BL), 24-Epibrassinolide (EBL) and 28-Homobrassinolide (HBL) are found to be the most biologically active forms and extensively used in various crops. They are eco-friendly, effective at very low concentration, cost effective and almost always have synergetic effect when interacts with other phytohormones. Owing to diverse physiological roles and cross talk with other hormones influence on plant growth and development, they are being collectively referred as ‘pleiotropic phytohormone’. Although, BRs were discovered towards the end of twentieth century, but the dynamic applications and outcomes were reported mainly during the inception of twenty first century, hence BRs were termed as ‘hormone of the twenty-first century’. The application of BRs at different growth stages have been reported to positively influences such as nutrients uptakes, growth, yield and quality attributes on many fruit crops which includes tropical, sub-tropical and temperate fruit crops at very low concentrations have great roles in terms of growth, yield, fruit quality and stress tolerance mechanisms, which results to lucrative adventure of farming community. This review article will provide an elucidated insight into the application of BR in different fruit crops.

Generalization of KCC-theory to fractional dynamical systems and application to viscoelastic oscillations

Generalization of KCC-theory to fractional dynamical systems and application to viscoelastic oscillations

Development of the Software System for Managing a Digital Pet ID

Recent Research and Publications Analysis: The shift towards digital documentation, such as Ukraine's «Diia» for human records, has not yet been fully embraced in pet care, creating a significant service gap. Ukraine, with a high number of household pets, especially approximately 7.63 million cats, highlights the need for a comprehensive digital pet management system. Given the frequent cases of pets getting lost—with low recovery rates—a robust digital system is essential for improving these figures and enhancing pet safety. When designing software, it is important to choose the right technologies for both the web interface and the backend. Django is recommended for the backend because of its «batteries-included» architecture, which provides a comprehensive set of ready-to-use tools that facilitate rapid development and ensure a high level of security. For the inter-face, it is recommended to use JavaScript integrated with frameworks such as React, An-gular or Vue to create dynamic applications that improve the user experience with asyn-chronous requests, allowing the content of the page to be updated without reloading the page. This combination not only provides scalability and security, but also effectively meets the complex needs of web applications. Purpose of the Study. This study aims to develop a software system that facilitates the management of digital pet IDs, which will integrate medical records, vaccination his-tories, and detailed activity logs. This integration aims to streamline pet care, making it more efficient and significantly more convenient for pet owners. Main Material Presentation. The proposed system's architecture will include: – backend. Utilizing Django REST Framework for creating scalable, secure web APIs that handle data operations efficiently; – frontend. Employing JavaScript, HTML, and CSS to provide a responsive and in-teractive user experience. Key Features: – digital passports for pets, verifiable via QR codes; - detailed activity logs that track and display pet movements and behaviors; – comprehensive vaccination records accessible by both pet owners and veterinari-ans; – a lost pet bulletin board that uses geographical data to notify users of nearby lost or found pets. Conclusions.Technologies have been chosen and a software system has been devel-oped for effective management of digital pet IDs, integrating key functions for compre-hensive data management of pets. It utilizes modern technologies to ensure reliable data security, high scalability, and enhanced user interaction, making it a key achievement in the management of digital pet IDs.

The Important Role of Fluid Mechanics in the Engineering Field

Fluid mechanics, a fundamental discipline within engineering, has gained increasing significance across various fields due to continuous advancements in engineering science and technology. Its principles and methodologies find widespread application in aerospace, energy development, environmental protection, biomedicine, and beyond, serving as a cornerstone for technological progress. However, despite the expanding applications of fluid dynamics, challenges persist in integrating theory with practice in certain domains. This paper aims to synthesize exemplary applications of fluid mechanics in diverse engineering fields, illustrating its crucial role in addressing practical challenges. Additionally, it explores current problems and limitations in fluid dynamics applications, such as numerical simulation accuracy, multiphase flow complexity, and fluid-structure interaction nonlinearity. Furthermore, recommendations are provided for future fluid mechanics development, emphasizing interdisciplinary collaboration, advanced computational methods, and the seamless integration of experimental techniques and theoretical research. Through these discussions, this paper endeavors to offer insights into the ongoing development of fluid mechanics, fostering its broader application and deeper exploration within engineering disciplines.

Determination of Maneuvering Force Coefficients for a Destroyer Model with OpenFOAM

_ Ship maneuvering performance can be predicted using various methods, including physical model tests, rapid simulations using coefficient-based forces, and high-fidelity computational fluid dynamics. This article considers the application of computational fluid dynamics for the prediction of hull force coefficients to be used as inputs to rapid maneuvering simulations. The open-source software OpenFOAM was used to simulate forces on the destroyer model DTMB 5415 for steady drift, oscillatory pure sway motion, and oscillatory yaw motion. Recommendations are provided regarding best practices in a number of areas, including domain size, mesh refinement, time step size, and turbulent modeling. Predicted forces for steady drift angles up to 12 degrees are typically within 10%of experimental values. For oscillatory sway and yaw motions, predicted forces are typically within 25%of experimental values. Keywords maneuvering; OpenFOAM; best modeling practices

Carbon Black Functionalized with Serinol Pyrrole to Replace Silica in Elastomeric Composites

Elastomer composites for dynamic mechanical applications with a low dissipation of energy are of great importance in view of their application in tire compounds. In this work, furnace carbon black functionalized with 2-2,5-dimethyl-1H-pyrrol-1-yl-1,3-propanediol (SP) was used in place of silica in an elastomer composite based on poly(styrene-co-butadiene) from solution anionic polymerization and poly(1,4-cis-isoprene) from Hevea Brasiliensis. The traditional coupling agent used for silica was also used for the CB/SP adduct: 3,3′-bis(triethoxysilylpropyl)tetrasulfide (TESPT). The composite with the CB/SP + TESPT system revealed a lower Payne effect, higher dynamic rigidity, and lower hysteresis, compared to the composite with CB + TESPT, although the latter composite had a higher crosslinking density. The properties of the silica and the CB/SP + TESPT-based composites appear similar, though in the presence of slightly higher hysteresis and lower ultimate properties for the CB/SP-based composite. The use of CB in place of silica allows us to prepare lighter compounds and paves the way for the preparation of tire compounds with lower environmental impacts.

Enhancement of electrochemical reversibility in Poly 3-hexylthiophene layers for flexible dynamic glass windows applications

Thin films of Poly 3-hexylthiophene (P3HT) were deposited onto Indium Tin Oxide (ITO) coated glass substrates using a spin coating method and the films were vacuum annealed at different temperatures to study the effect of annealing on the electrochemical reversibility. From the absorption spectra, the variation of the optical band gap with annealing temperature was studied for different annealing temperatures. The optical band gap obtained for P3HT film deposited at room temperature (RT) was around 1.94 eV and 1.92 eV for the sample annealed at 100 °C. A cyclic voltammetry (CV) analysis showed that at certain applied redox potentials, P3HT thin films changed the colour from magenta to transparent and then back to magenta in the reverse potential. P3HT films annealed at 100 °C showed the best electrochemical reversibility among all the annealed samples. These electrically switchable electrochromic P3HT thin films can be used in flexible dynamic windows (FDWs) as smart windows for controlling the temperature and light in buildings, displays and mirror light modulators.

Improved Local-Mode Zero-Point-Energy Conservation Scheme for Quasiclassical Trajectories.

We present an improvement of the local-pair zero-point-energy (LP-ZPE) scheme of Mukherjee and Barbatti. The new approximation is called the improved LP-ZPE scheme or iLP-ZPE. This scheme can produce trajectories that do not have unphysical leaking of zero-point energy from high-frequency spectator modes into low-frequency modes. We illustrate the method with a successful direct dynamics application to the Ne···HF van der Waals molecule. The method is well suited for direct dynamics calculations because it does not require costly evaluations of local Hessians or instantaneous normal modes along the trajectories.

Materials and manufacturing technology for high reliability rigid-flex multilayer PCB for space 3D-electronics packaging

Abstract Rigid-flex Multilayer PCB Technology enables the elimination of several connectors and bulky harness for interconnecting functional electronic systems. This minimizes packaging complexity and reduces performance degradation at high frequencies with an added advantage of reduced weight and volume in high-reliability space electronic packages. Here, only thermo-mechanically stable adhesiveless all polyimide flexible laminate cores and no-flow glass-polyimide prepregs are employed. To overcome the manufacturing issues like registration, coverlay protrusion into the rigid portions, and residual copper deposition at the intersections of flexible and rigid portions; a novel manufacturing process technology is proposed here. The technology has been successfully devised after choosing the most appropriate flexible, rigid, and low-flow prepreg materials. Herein, for the realization of Rigid-flex Multilayer PCB Technology with 2-layers of flex and 8-layers of rigid to meet the functional requirements of the board is presented. The critical registration issues associated with the dissimilar rigid and flexible substrates are successfully addressed to achieve best-fit registration and obtain minimum annular rings of 50 µm in all the inner layers for high reliability. Experimental results manifest that incorporating rigid-flex multilayer PCB technology significantly reduces weight (>30%) and volume (~40%) to high-reliability space electronics 3D packaging for static and dynamic applications.

Enhancing Students Experience: A Comprehensive Approach through Uni-Connect

In today's digital age, university students seek comprehensive platforms that transcend basic functionalities to enrich their academic, professional, and social experiences. Inspired by this need, we propose the development of UniConnect, a dynamic web application utilizing the MERN stack. UniConnect serves as a centralized hub offering a plethora of features including user authentication, profile management, event management, job placement, real- time notifications, resource hub, project collaboration tools, peer tutoring, career assessments, and more. This paper outlines the phased development approach undertaken to realize UniConnect's vision, culminating in three distinct phases: Basic, Intermediate, and Advanced versions. Each phase incrementally enhances the platform's capabilities, focusing on functionality, usability, and user engagement. Evaluation results demonstrate the effectiveness of the UniConnect platform in meeting the diverse needs of university students, fostering collaboration, networking, and personal development. Through UniConnect, we aim to revolutionize the university experience, empowering students to thrive academically, professionally, and socially.

The Dynamical Equations of the Restricted Three-Body Problem with Poynting-Robertson Drag Force and Variable Masses

The restricted three-body problem (R3BP) is a formulation which defines the motion of a passively gravitating test particle having  infinitesimal mass and moving in the gravitational environment of two bodies, called primaries. The R3BP is still an exciting and active  research field that has been getting attention of scientists and astronomers because of its applications in dynamics of the solar and stellar systems, lunar theory, and artificial satellites. The equations of motion are usually the starting point in the investigations of the  dynamical predictions of the infinitesimal mass. Therefore, in this paper, we examine the derivations of the dynamical equations of the  R3BP with Poynting-Robertson (P-R) Drag force and variable masses. In this model formulation, both primaries are assumed to vary their  masses under the combined Mestschersky law (CML) and they move in the frame of the GyldenMestschersky equation (GME). Further,  the bigger primary is assumed to be emitting radiation force, which is a component of the radiation pressure and the P-R drag. The non- autonomous dynamical equations of the model are derived and converted into the autonomized equations with constant coefficients  using the Mestschersky transformation (MT), the CML, the particular solutions of the GMP, and a transformation for the time dependent  velocity of light. We observed that the P-R drag of the bigger primary depends on the mass parameter, radiation pressure, velocity of  light and the mass variation constant . The derived systems of equations with variable and constant coefficients can be used to model  the long-term motion of satellites and planets in binary systems.   

Heteromultivalent DNA Enhances the Assembly Yield of Hybrid Nanoparticles and Facilitates Dynamic Disassembly for Bioanalysis Using ICP-MS.

To obtain enhanced physical and biological properties, various nanoparticles are typically assembled into hybrid nanoparticles through the binding of multiple homologous DNA strands to their complementary counterparts, commonly referred to as homomultivalent assembly. However, the poor binding affinity and limited controllability of homomultivalent disassembly restrict the assembly yield and dynamic functionality of the hybrid nanoparticles. To achieve a higher binding affinity and flexible assembly choice, we utilized the paired heteromultivalency DNA to construct hybrid nanoparticles and demonstrate their excellent assembly characteristics and dynamic applications. Specifically, through heteromultivalency, DNA-functionalized magnetic beads (MBs) and gold nanoparticles (AuNPs) were efficiently assembled. By utilizing ICP-MS, the assembly efficiency of AuNPs on MBs was directly monitored, enabling quantitative analysis and optimization of heteromultivalent binding events. As a result, the enhanced assembly yield is primarily attributed to the fact that heteromultivalency allows for the maximization of effective DNA probes on the surface of nanoparticles, eliminating steric hindrance interference. Subsequently, with external oligonucleotides as triggers, it was revealed that the disassembly mechanism of hybrid nanoparticles was initiated, which was based on an increased local concentration rather than toehold-mediated displacement of paired heteromultivalency DNA probes. Capitalizing on these features, an output platform was then established based on ICP-MS signals that several Boolean operations and analytical applications can be achieved by simply modifying the design sequences. The findings provide new insights into DNA biointerface interaction, with potential applications to complex logic operations and the construction of large DNA nanostructures.

Man and the Machine: Effects of AI-assisted Human Labeling on Interactive Annotation of Real-time Video Streams

AI-assisted interactive annotation is a powerful way to facilitate data annotation—a prerequisite for constructing robust AI models. While AI-assisted interactive annotation has been extensively studied in static settings, less is known about its usage in dynamic scenarios where the annotators operate under time and cognitive constraints, e.g., while detecting suspicious or dangerous activities from real-time surveillance feeds. Understanding how AI can assist annotators in these tasks and facilitate consistent annotation is paramount to ensure high performance for AI models trained on these data. We address this gap in interactive machine learning (IML) research, contributing an extensive investigation of the benefits, limitations, and challenges of AI-assisted annotation in dynamic application use cases. We address both the effects of AI on annotators and the effects of (AI) annotations on the performance of AI models trained on annotated data in real-time video annotations. We conduct extensive experiments that compare annotation performance at two annotator levels (expert and non-expert) and two interactive labeling techniques (with and without AI assistance). In a controlled study with \(N=34\) annotators and a follow-up study with 51,963 images and their annotation labels being input to the AI model, we demonstrate that the benefits of AI-assisted models are greatest for non-expert users and for cases where targets are only partially or briefly visible. The expert users tend to outperform or achieve similar performance as the AI model. Labels combining AI and expert annotations result in the best overall performance as the AI reduces overflow and latency in the expert annotations. We derive guidelines for the use of AI-assisted human annotation in real-time dynamic use cases.

Dynamical sampling for the recovery of spatially constant source terms in dynamical systems

In this paper, we investigate the problem of source recovery in a dynamical system utilizing space-time samples. This is a specific issue within the broader field of dynamical sampling, which involves collecting samples from solutions to a differential equation across both space and time with the aim of recovering critical data, such as initial values, the sources, the driving operator, or other relevant details. Our focus in this study is the recovery of unknown, stationary sources across both space and time, leveraging space-time samples. This research may have significant applications; for instance, it could provide a model for strategically placing devices to measure the number of pollutants emanating from factory smokestacks and dispersing across a specific area. Space-time samples could be collected using measuring devices placed at various spatial locations and activated at different times. We present necessary and sufficient conditions for the positioning of these measuring devices to successfully resolve this dynamical sampling problem. This paper provides both a theoretical foundation for the recovery of sources in dynamical systems and potential practical applications.

A comparative analysis of non-isolated Bi-directional converters for energy storage applications

Abstract Bi-directional DC-DC converters are required for power flow regulation between storage devices and DC buses in renewable energy based distributed generation systems. The fundamental requirements of the BDC are simple structure, reduced switching components, a wide range of voltage gain, low voltage stress, high efficiency, and reduced size. There are different BDC topologies for different applications based on their requirements. Isolated BDC converters are large due to high-frequency transformers and hence used for static energy storage applications whereas non-isolated BDC is lightweight and suitable for dynamic applications like electric vehicles. This paper reviews and compares different non-isolated BDC topologies by carrying out theoretical analysis and validating them through simulation results. A comparative analysis is done to identify the most efficient topology for the distributed generation systems. Five 200W converters are simulated in MATLAB Simulink to validate their steady state performance.

Active substance and mechanisms of Actinidia chinensis Planch for the treatment of breast cancer was explored based on network pharmacology and in silico study.

In this paper, our objective was to investigate the potential mechanisms of Actinidia chinensis Planch (ACP) for breast cancer treatment with the application of network pharmacology, molecular docking, and molecular dynamics. "Mihoutaogen" was used as a key word to query the Traditional Chinese Medicine Systems Pharmacology database for putative ingredients of ACP and its related targets. DrugBank, GeneCards, Online Mendelian Inheritance in Man, and therapeutic target databases were used to search for genes associated with "breast cancer." Using Cytoscape 3.9.0 we then constructed the protein-protein interaction and drug-ingredient-target-disease networks. An enrichment analysis of Kyoto encyclopedia of genes and genomes pathway and gene ontology were performed to exploration of the signaling pathways associated with ACP for breast cancer treatment. Discovery Studio software was applied to molecular docking. Finally, the ligand-receptor complex was subjected to a 50-ns molecular dynamics simulation using the Desmond_2020.4 tools. Six main active ingredients and 176 targets of ACP and 2243 targets of breast cancer were screened. There were 118 intersections of targets for both active ingredients and diseases. Tumor protein P53 (TP53), AKT serine/threonine kinase 1 (AKT1), estrogen receptor 1 (ESR1), Erb-B2 receptor tyrosine kinase 2 (ERBB2), epidermal growth factor receptor (EGFR), Jun Proto-Oncogene (JUN), and Heat Shock Protein 90 Alpha Family Class A Member 1 (HSP90AA1) selected as the most important genes were used for verification by molecular docking and molecular dynamics simulation. The primary active compounds of ACP against breast cancer were predicted preliminarily, and its mechanism was studied, thereby providing a theoretical basis for future clinical studies.

Microbial chassis design and engineering for production of gamma-aminobutyric acid.

Gamma-aminobutyric acid (GABA) is a non-protein amino acid which is widely applied in agriculture and pharmaceutical additive industries. GABA is synthesized from glutamate through irreversible α-decarboxylation by glutamate decarboxylase. Recently, microbial synthesis has become an inevitable trend to produce GABA due to its sustainable characteristics. Therefore, reasonable microbial platform design and metabolic engineering strategies for improving production of GABA are arousing a considerable attraction. The strategies concentrate on microbial platform optimization, fermentation process optimization, rational metabolic engineering as key metabolic pathway modification, promoter optimization, site-directed mutagenesis, modular transporter engineering, and dynamic switch systems application. In this review, the microbial producers for GABA were summarized, including lactic acid bacteria, Corynebacterium glutamicum, and Escherichia coli, as well as the efficient strategies for optimizing them to improve the production of GABA.

CFD Analysis of Coolant Flow Characteristics in Reactor Pressure Vessel: A Comprehensive Review

This comprehensive review explores the application of Computational Fluid Dynamics (CFD) in analyzing coolant flow within Reactor Pressure Vessels (RPVs) of nuclear power plants. By synthesizing existing research, methodologies, and advancements specific to RPVs, the paper offers in-depth insights into critical aspects such as boundary conditions, turbulence modeling, heat transfer mechanisms, and validation techniques. Examining a range of studies encompassing various reactor types from Pressurized Water Reactors (PWRs) to Integral Pressurized Water Reactors (IPWRs), the review underscores CFD's pivotal role in enhancing safety, efficiency, and performance optimization in nuclear reactors. Through systematic exploration, this study underscores the critical importance of precise modeling in facilitating safety assessments, operational optimization, and design enhancements across various reactor systems. Accurate modeling serves as a cornerstone for informed decision-making processes aimed at maximizing reactor performance while ensuring the highest standards of safety and reliability. The paper navigates through challenges such as computational limitations and turbulence modeling intricacies, while also discussing emerging trends like the porous media method aimed at improving computational efficiency. By offering a comprehensive understanding of thermal-hydraulic behavior in nuclear reactors, the review underscores CFD's contribution to enhancing safety and reliability in nuclear power generation. Overall, this review underscores the indispensable role of CFD in advancing our understanding of nuclear reactor dynamics, thereby contributing significantly to the overarching goals of improved safety and reliability in nuclear power generation.

A novel web-based dynamic prognostic nomogram for gastric signet ring cell carcinoma: a multicenter population-based study.

Gastric signet ring cell carcinoma (GSRCC) is a rare and highly malignant disease with a poor prognosis. To assess the overall survival (OS) and cancer-specific survival (CSS) of patients with GSRCC, prognostic nomograms were developed and validated using common clinical factors. This retrospective cohort study included patients diagnosed with GSRCC between 2011 and 2018 from the National Cancer Center (n = 1453) and SEER databases (n = 2745). Prognostic nomograms were established by identifying independent prognostic factors using univariate and multivariate Cox regression analyses. The calibration curve and C-index were used to assess the predictions. The clinical usefulness of the survival prediction model was further evaluated using the DCA and ROC curves. The models were internally validated in the training cohort and externally validated in the validation cohort. Two web servers were created to make the nomogram easier to use. Patients with GSRCC were divided into training (n = 2938) and validation (n = 1260) cohorts. The nomograms incorporated six predictors: age, race, tumor site, tumor size, N stage, T stage, and AJCC stage. Excellent agreement was observed between the internal and exterior calibration plots for the GSRCC survival estimates. The C-index and area under the ROC curve were roughly greater than 0.7. Both nomograms had adequate clinical efficacy, as demonstrated by the DCA plots. Furthermore, we developed a dynamic web application utilizing the constructed nomograms available at https://jiangyujuan.shinyapps.io/OS-nomogram/ and https://jiangyujuan.shinyapps.io/DynNomapp-DFS/. We developed web-based dynamic nomograms utilizing six independent prognostic variables that assist physicians in estimating the OS and CSS of patients with GSRCC.