Search results for: harvesting insects outbreak dynamics

Authors: Jixiang Zhang, Yanhua Wang

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A dynamic of Bertrand duopoly game is analyzed, where players use different production methods and choose their prices with bounded rationality. The equilibriums of the corresponding discrete dynamical systems are investigated. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability of Nash equilibrium, as some parameters of the model are varied, gives rise to complex dynamics such as cycles of higher order and chaos. On this basis, we discover that an increase of adjustment speed of bounded rational player can make Bertrand market sink into the chaotic state. Finally, the complex dynamics, bifurcations and chaos are displayed by numerical simulation.

Keywords: Bertrand duopoly model, discrete dynamical system, heterogeneous expectations, nash equilibrium

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Authors: Pakize Ozlem Kurt Polat

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GMO (genetically modified organism) is the result of a laboratory process where genes from the DNA of one species are extracted and artificially forced into the genes of an unrelated plant or animal. This technology includes; nucleic acid hybridization, recombinant DNA, RNA, PCR, cell culture and gene cloning techniques. The studies are divided into three groups of properties transferred to the transgenic plant. Up to 59% herbicide resistance characteristic of the transfer, 28% resistance to insects and the virus seems to be related to quality characteristics of 13%. Transgenic crops are not included in the commercial production of each product; mostly commercial plant is soybean, maize, canola, and cotton. Day by day increasing GMO interest can be listed as follows; Use in the health area (Organ transplantation, gene therapy, vaccines and drug), Use in the industrial area (vitamins, monoclonal antibodies, vaccines, anti-cancer compounds, anti -oxidants, plastics, fibers, polyethers, human blood proteins, and are used to produce carotenoids, emulsifiers, sweeteners, enzymes , food preservatives structure is used as a flavor enhancer or color changer),Use in agriculture (Herbicide resistance, Resistance to insects, Viruses, bacteria, fungi resistance to disease, Extend shelf life, Improving quality, Drought , salinity, resistance to extreme conditions such as frost, Improve the nutritional value and quality), we explain all this methods step by step in this research. GMO has advantages and disadvantages, which we explain all of them clearly in full text, because of this topic, worldwide researchers have divided into two. Some researchers thought that the GMO has lots of disadvantages and not to be in use, some of the researchers has opposite thought. If we look the countries law about GMO, we should know Biosafety law for each country and union. For this Biosecurity reasons, the problems caused by the transgenic plants, including Turkey, to minimize 130 countries on 24 May 2000, ‘the United Nations Biosafety Protocol’ signed nudes. This protocol has been prepared in addition to Cartagena Biosafety Protocol entered into force on September 11, 2003. This protocol GMOs in general use by addressing the risks to human health, biodiversity and sustainable transboundary movement of all GMOs that may affect the prevention, transit covers were dealt and used. Under this protocol we have to know the, ‘US Regulations GMO’, ‘European Union Regulations GMO’, ‘Turkey Regulations GMO’. These three different protocols have different applications and rules. World population increasing day by day and agricultural fields getting smaller for this reason feeding human and animal we should improve agricultural product yield and quality. Scientists trying to solve this problem and one solution way is molecular biotechnology which is including the methods of GMO too. Before decide to support or against the GMO, should know the GMO protocols and it effects.

Keywords: biotechnology, GMO (genetically modified organism), molecular marker

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Authors: Jhabakhar Aryal, Kesh Bahadur Rana, Durga Prasad Neupane

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This research analyzes the nature and impacts of the 2015 unofficial blockade in Nepal, a significant event that triggered an economic and humanitarian crisis. While official channels denied claims of involvement, Nepal perceived the blockade as orchestrated by India due to concerns about the newly adopted constitution and Madheshi infringements. The study adopts a qualitative approach, utilizing semi-structured interviews, document analysis, and content analysis to gather data from various perspectives. Employing a "colonial hangover lens," it investigates if colonial legacies continue to influence postcolonial nation dynamics, focusing on India's potential attempt to exert influence over Nepal. The findings suggest that the 2015 blockade had profound consequences for Nepal, potentially reflecting lingering colonial power dynamics in the region. Despite India's denials, a significant portion of Nepalis perceived the blockade as an act of external pressure. Examining these perceptions offers valuable insights into postcolonial relations and their impact on regional stability. The 2015 unofficial blockade serves as a critical case study in understanding the complex interplay of internal dynamics, external influences, and historical legacies in shaping the geopolitics of the region. This research contributes to a deeper understanding of these factors and their ongoing implications for Nepal and its relationship with India.

Keywords: blockade, unofficial, constitution, Madhesis, India, Nepal, postcolonial, regional stability, geopolitics

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

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Authors: Javier Varillas, Jorge Alcalá

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We investigate dislocation avalanche phenomena in face-centered cubic (FCC) and body-centered cubic (BCC) crystals using massive, large-scale molecular dynamics (MD) simulations. The analysis is focused on the intermittent development of dense dislocation arrangements subjected to uniaxial tensile straining under displacement control. We employ a novel computational scheme that allows us to inject an entangled dislocation structure in periodic MD domains. We assess the emission of plastic bursts (or dislocation avalanches) in terms of the sharp stress drops detected in the stress-strain curve. The plastic activity corresponds to the sporadic operation of specific dislocation glide processes exhibiting quiescent periods between successive avalanche events. We find that the plastic intermittences in our simulations do not overlap in time under sufficiently low strain rates as dissipation operates faster than driving, where the dense dislocation networks evolve through the emission of dislocation avalanche events whose carried slip adheres to self-organized power-law distributions. These findings enable the extension of the slip distributions obtained from strict displacement-controlled micropillar compression experiments towards smaller values of slip size. Our results furnish further understanding upon the development of entangled dislocation networks in metal plasticity, including specific mechanisms of dislocation propagation and annihilation, along with the evolution of specific dislocation populations through dislocation density analyses.

Keywords: dislocations, intermittent plasticity, molecular dynamics, slip distributions

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Authors: Nqobile Muleya, Winston Garira, Godwin Mchau

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Citrus Black Spot (CBS) is a fungal disease that is responsible for huge economical loss and poses a threat to the citrus industry worldwide. We construct a mathematical model framework for citrus black spot between fruits to characterise the dynamics of the disease development, paying attention to the pathogen life cycle. We have made an observation from the model analysis that the initial inoculum from ascomata is very important for disease development and thereafter it is no longer important due to conidia which is responsible for secondary infection. Most importantly, the model indicated that ascospores and conidia are very important parameters in developing citrus black spot within a short distance. The basic reproductive number and its importance in relation to citrus black spot persistence are outlined. A numerical simulation of the model was done to explain the theoretical findings.

Keywords: epidemiological modelling, Guidnardia citricarpa, life cycle stage, fungal, disease development

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Authors: Rawaa Maher, Ahmed Allam, Haruichi Kanaya, Adel B. Abdelrahman

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In this paper, a compact, high-efficiency integrated rectenna is presented to operate in the 2.45 GHz band. A comparison between two rectifier topologies is performed to verify the benefits of removing the matching network from the rectifier. A rectifier high conversion efficiency of 74.1% is achieved. To complete the rectenna system, a novel omnidirectional antenna with high gain (3.72 dB) and compact size (25 mm * 29 mm) is designed and fabricated. The same antenna is used with a reflector for raising the gain to nearly 8.3 dB. The simulation and measurement results of the antenna are in good agreement.

Keywords: internet of things, integrated rectenna, rectenna, RF energy harvesting, wireless sensor networks(WSN)

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Authors: Jinali Chaklasiya

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The importance of face masks, gloves, sanitizer, face shield Were only Applied for Doctor Amenities, and because of the outbreak of coronavirus, everybody has to wear Personal Protective Equipment (PPE) for health measures. . The main focus of this research paper is in the area of how doctor amenities changed the importance of gloves, face masks, sanitizer, face shield in day to day life of people. For this research, we have collected data from a quantitative survey. A questionnaire survey was conducted to note down the user point of view in doctor amenities and why is it important. The result of the questionnaire survey has helped to design parameters which were used to ideate new protective products. Thus, it is concluded to keep in mind that these protective devices can be used in day-to-day life by people across the globe. In the coming future, the protective device can make a difference and protect us from other common viruses.

Keywords: equpiment, coronavirus, products, protective, environment

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Authors: Olivier Delage, Hassan Bencherif, Alain Bourdier

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Signal decomposition approaches represent an important step in time series analysis, providing useful knowledge and insight into the data and underlying dynamics characteristics while also facilitating tasks such as noise removal and feature extraction. As most of observational time series are nonlinear and nonstationary, resulting of several physical processes interaction at different time scales, experimental time series have fluctuations at all time scales and requires the development of specific signal decomposition techniques. Most commonly used techniques are data driven, enabling to obtain well-behaved signal components without making any prior-assumptions on input data. Among the most popular time series decomposition techniques, most cited in the literature, are the empirical mode decomposition and its variants, the empirical wavelet transform and singular spectrum analysis. With increasing popularity and utility of these methods in wide ranging applications, it is imperative to gain a good understanding and insight into the operation of these algorithms. In this work, we describe all of the techniques mentioned above as well as their ability to denoise signals, to capture trends, to identify components corresponding to the physical processes involved in the evolution of the observed system and deduce the dimensionality of the underlying dynamics. Results obtained with all of these methods on experimental total ozone columns and rainfall time series will be discussed and compared

Keywords: denoising, empirical mode decomposition, singular spectrum analysis, time series, underlying dynamics, wavelet analysis

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Authors: Ernesto A. Lagarda-Leyva, Manuel A. Valenzuela L., José G. Oshima C., Arnulfo A. Naranjo-Flores

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From August to December of 2016, a diagnostic and strategic planning study was carried out on the supply chain of the company Agropecuaria GABO S.A. de C.V. The final product of the study was the development of the strategic plan and a project portfolio to meet the demands of the three links in the supply chain of the Roma tomato exported annually to the United States of America. In this project, the strategic objective of ensuring the proper handling of the product was selected and one of the goals associated with this was the employment of quantitative methods to support decision making. Considering the antecedents, the objective of this case study was to develop a model to analyze the behavioral dynamics in the distribution chain, from the logistics of storage and shipment of Roma tomato in 81-case pallets (11.5 kg per case), to the two pre-cooling rooms and eventual loading onto transports, seeking to reduce the bottleneck and the associated costs by means of a dynamic interface. The methodology used was that of system dynamics, considering four phases that were adapted to the purpose of the study: 1) the conceptualization phase; 2) the formulation phase; 3) the evaluation phase; and 4) the communication phase. The main practical conclusions lead to the possibility of reducing both the bottlenecks in the cooling rooms and the costs by simulating scenarios and modifying certain policies. Furthermore, the creation of the dynamic interface between the model and the stakeholders was achieved by generating interaction with buttons and simple instructions that allow making modifications and observing diverse behaviors.

Keywords: agrilogistics, distribution, scenarios, system dynamics

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Authors: Aakash Chhunchha, Assma Begum

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The qualitative aspects of hypersonic flow over a range of blunt bodies have been extensively analyzed in the past. It is well known that the curvature of a body’s geometry in the sonic region predominantly dictates the bow shock shape and its standoff distance from the body, while the surface pressure distribution depends on both the sonic region and on the local body shape. The present study is an extension to analyze the hypersonic flow characteristics over several blunt-nosed bodies using modern Computational Fluid Dynamics (CFD) tools to determine the shock shape and its effect on the heat flux around the body. 4 blunt-nosed models with cylindrical afterbodies were analyzed for a flow at a Mach number of 10 corresponding to the standard atmospheric conditions at an altitude of 50 km. The nose radii of curvature of the models range from a hemispherical nose to a flat nose. Appropriate numerical models and the supplementary convergence techniques that were implemented for the CFD analysis are thoroughly described. The flow contours are presented highlighting the key characteristics of shock wave shape, shock standoff distance and the sonic point shift on the shock. The variation of heat flux, due to different shock detachments for various models is comprehensively discussed. It is observed that the more the bluntness of the nose radii, the farther the shock stands from the body; and consequently, the less the surface heating at the nose. The results obtained from the CFD analyses are compared with approximated theoretical engineering correlations. Overall, a satisfactory agreement is observed between the two.

Keywords: aero-thermodynamics, blunt-nosed bodies, computational fluid dynamics (CFD), hypersonic flow

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Authors: Minh Quang Le, Dane Taylor

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Convection is a well-studied topic in fluid dynamics, yet it is less understood in the context of networks flows. Here, we incorporate techniques from topological data analysis (namely, persistent homology) to automate the detection and characterization of convective/cyclic/chiral flows over networks, particularly those that arise for irreversible Markov chains (MCs). As two applications, we study convection cycles arising under the PageRank algorithm, and we investigate chiral edges flows for a stochastic model of a bi-monomer's configuration dynamics. Our experiments highlight how system parameters---e.g., the teleportation rate for PageRank and the transition rates of external and internal state changes for a monomer---can act as homology regularizers of convection, which we summarize with persistence barcodes and homological bifurcation diagrams. Our approach establishes a new connection between the study of convection cycles and homology, the branch of mathematics that formally studies cycles, which has diverse potential applications throughout the sciences and engineering.

Keywords: homology, persistent homolgy, markov chains, convection cycles, filtration

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Authors: Alix Limoges, William Bruch, Christophe Yohia, Jacques Piazzola

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A number of questions arise concerning the long-term impact of the contribution of marine aerosol fluxes generated at the air-sea interface on the occurrence of intense events (storms, floods, etc.) in the coastal environment. To this end, knowledge is needed on sea-spray emission rates and the atmospheric dynamics of the corresponding particles. Our aim is to implement the mesoscale model MESO-NH on the study area using an accurate sea-spray source function to estimate heat fluxes and impact on the precipitations. Based on an original and complete sea-spray source function, which covers a large size spectrum since taking into consideration the sea-spray produced by both bubble bursting and surface tearing process, we propose a comparison between model simulations and experimental data obtained during an oceanic scientific cruise on board the navy ship Atalante. The results show the relevance of the sea-spray flux calculations as well as their impact on the heat fluxes and AOD.

Keywords: atmospheric models, sea-spray source, sea-spray dynamics, aerosols

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Authors: Xiaobo Rui, Zhoumo Zeng, Yibo Li

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A novel tri-cantilever energy harvester with magnetic oscillator was presented, which could convert the ambient vibration into electrical energy to power the low-power devices such as wireless sensor networks. The most common way to harvest vibration energy is based on the use of linear resonant devices such as cantilever beam, since this structure creates the highest strain for a given force. The highest efficiency will be achieved when the resonance frequency of the harvester matches the vibration frequency. The limitation of the structure is the narrow effective bandwidth. To overcome this limitation, this article introduces a broadband tri-cantilever harvester with nonlinear stiffness. This energy harvester typically consists of three thin cantilever beams vertically arranged with Neodymium Magnets ( NdFeB)magnetics at its free end and a fixed base at the other end. The three cantilevers have different resonant frequencies by designed in different thicknesses. It is obviously that a similar advantage of multiple resonant frequencies as piezoelectric cantilevers array structure is built. To achieve broadband energy harvesting, magnetic interaction is used to introduce the nonlinear system stiffness to tune the resonant frequency to match the excitation. Since the three cantilever tips are all free and the magnetic force is distance dependent, the resonant frequencies will be complexly changed with the vertical vibration of the free end. Both model and experiment are built. The electromechanically coupled lumped-parameter model is presented. An electromechanical formulation and analytical expressions for the coupled nonlinear vibration response and voltage response are given. The entire structure is fabricated and mechanically attached to a electromagnetic shaker as a vibrating body via the fixed base, in order to couple the vibrations to the cantilever. The cantilevers are bonded with piezoelectric macro-fiber composite (MFC) materials (Model: M8514P2). The size of the cantilevers is 120*20mm2 and the thicknesses are separately 1mm, 0.8mm, 0.6mm. The prototype generator has a measured performance of 160.98 mW effective electrical power and 7.93 DC output voltage via the excitation level of 10m/s2. The 130% increase in the operating bandwidth is achieved. This device is promising to support low-power devices, peer-to-peer wireless nodes, and small-scale wireless sensor networks in ambient vibration environment.

Keywords: tri-cantilever, ambient vibration, energy harvesting, magnetic oscillator

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Authors: Manjiri A. More, Manisha M. Bhosale

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Agriculture is the backbone of Indian economy and India is one of the world’s largest producers of Rice. Today, paddy crop is facing a severe problem of insect pests and is attacked by more than 100 species of insects, among those 20 species cause economic damage. Rice is the staple food of people of panhala tehasil, Kolhapur, Maharashtra, India. During June 2017 to September 2017 efforts were made to study the diversity of insect pests associated with the paddy crop in the study region. The collection and preservation of the specimens were done by following standard procedure and the identification was done with the help standard literature, taxonomic keys, and webography. In all, 6 species were recorded as pests of paddy in which order Lepidoptera was dominant with 2 species, while orders Diptera, Orthoptera, Hemiptera, and Coleoptera were represented by 1 species each respectively. The results of the present investigation will be helpful for formulating control strategies against these paddy pests.

Keywords: diversity, insect pests, Panhala, staple

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Authors: N. G. Thangan, A. B. Deoghare, P. M. Padole

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Computational Fluid Dynamics (CFD) aids in modeling the prototype of a real world processes. CFD approach is useful in predicting the fluid flow, heat transfer mass transfer and other flow related phenomenon. In present study, hydrodynamic characteristics of gas-solid cylindrical fluidized bed is compared with conical fluidized beds. A 2D fluidized bed consists of different configurations of particle size of iron oxide, bed height and superficial velocities of nitrogen. Simulations are performed to capture the complex physics associated with it. The Eulerian multiphase model is prepared in ANSYS FLUENT v.14 which is used to simulate fluidization process. It is analyzed with nitrogen as primary phase and iron oxide as secondary phase. The bed hydrodynamics is assessed prominently to examine effect on fluidization time, pressure drop, minimum fluidization velocity, and gas holdup in the system.

Keywords: fluidized bed, bed hydrodynamics, Eulerian multiphase approach, computational fluid dynamics

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Authors: Nigar Kantarci Carsibasi

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Coarse-grained elastic network models, namely Gaussian network model (GNM) and Anisotropic network model (ANM), are utilized in order to investigate the fluctuation dynamics of Murine Double Minute 2 (MDM2), which is the native inhibitor of p53. Conformational dynamics of MDM2 are elucidated in unbound, p53 bound, and non-peptide small molecule inhibitor bound forms. With this, it is aimed to gain insights about the alterations brought to global dynamics of MDM2 by native peptide inhibitor p53, and two small molecule inhibitors (HDM201 and NVP-CGM097) that are undergoing clinical stages in cancer studies. MDM2 undergoes significant conformational changes upon inhibitor binding, carrying pieces of evidence of induced-fit mechanism. Small molecule inhibitors examined in this work exhibit similar fluctuation dynamics and characteristic mode shapes with p53 when complexed with MDM2, which would shed light on the design of novel small molecule inhibitors for cancer therapy. The results showed that residues Phe 19, Trp 23, Leu 26 reside in the minima of slowest modes of p53, pointing to the accepted three-finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct regions are identified in MDM2, for which significant conformational changes are observed upon binding. Regions I (residues 50-77) and III (residues 90-105) correspond to the binding interface of MDM2, including (α2, L2, and α4), which are stabilized during complex formation. Region II (residues 77-90) exhibits a large amplitude motion, being highly flexible, both in the absence and presence of p53 or other inhibitors. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 domains, clearly distinguishing the kinetically hot regions. Mode shape analysis revealed that the α4 domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states for proper penetration and binding of p53 and inhibitors, which points to the induced-fit mechanism of p53 binding. P53 interacts with α2 and α4 in a synchronized manner. Collective modes are shifted upon inhibitor binding, i.e., second mode characteristic motion in MDM2-p53 complex is observed in the first mode of apo MDM2; however, apo and bound MDM2 exhibits similar features in the softest modes pointing to pre-existing modes facilitating the ligand binding. Although much higher amplitude motions are attained in the presence of non-peptide small molecule inhibitor molecules as compared to p53, they demonstrate close similarity. Hence, NVP-CGM097 and HDM201 succeed in mimicking the p53 behavior well. Elucidating how drug candidates alter the MDM2 global and conformational dynamics would shed light on the rational design of novel anticancer drugs.

Keywords: cancer, drug design, elastic network model, MDM2

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Authors: Virendra Nath, Vipin Kumar

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Background: TypeII Diabetes mellitus is a foremost health problem worldwide, predisposing to increased mortality and morbidity. Undesirable effects of the current medications have prompted the researcher to develop more potential drug(s) against the disease. The peroxisome proliferator-activated receptors (PPARs) are members of the nuclear receptors family and take part in a vital role in the regulation of metabolic equilibrium. They can induce or repress genes associated with adipogenesis, lipid, and glucose metabolism. Aims: Investigation of PPARα/γ agonistic hits were screened by hierarchical virtual screening followed by molecular dynamics simulation and knowledge-based structure-activity relation (SAR) analysis using approved PPAR α/γ dual agonist. Methods: The PPARα/γ agonistic activity of compounds was searched by using Maestro through structure-based virtual screening and molecular dynamics (MD) simulation application. Virtual screening of nuclear-receptor ligands was done, and the binding modes with protein-ligand interactions of newer entity(s) were investigated. Further, binding energy prediction, Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit along with the structural comparative analysis of approved PPARα/γ agonists with screened hit was done for knowledge-based SAR. Results and Discussion: The silicone chip-based approach recognized the most capable nine hits and had better predictive binding energy as compared to the reference drug compound (Tesaglitazar). In this study, the key amino acid residues of binding pockets of both targets PPARα/γ were acknowledged as essential and were found to be associated in the key interactions with the most potential dual hit (ChemDiv-3269-0443). Stability studies using molecular dynamics (MD) simulation of PPARα and γ complex was performed with the most promising hit and found root mean square deviation (RMSD) stabile around 2Å and 2.1Å, respectively. Frequency distribution data also revealed that the key residues of both proteins showed maximum contacts with a potent hit during the MD simulation of 20 nanoseconds (ns). The knowledge-based SAR studies of PPARα/γ agonists were studied using 2D structures of approved drugs like aleglitazar, tesaglitazar, etc. for successful designing and synthesis of compounds PPARγ agonistic candidates with anti-hyperlipidimic potential.

Keywords: computational, diabetes, PPAR, simulation

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Authors: Khushi, Simrat

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The study aims to investigate the relationship between emotions and employee's social cognition and decision-making among employees. The sample of the study was the total number of participants, which included employees from various industries and job positions. Research papers in the same area were reviewed, providing a comprehensive review of existing literature and theoretical frameworks and shedding light on the interpersonal effects of emotions in the workplace. It emphasizes how one worker's emotions can significantly impact the overall work environment and productivity as well as the work of a common phenomenon known as Emotional contagion at the workplace, affecting social interactions and group dynamics. Therefore, this study concludes that Emotional contagion can lead to a ripple effect within the workplace, influencing the overall atmosphere and productivity. Emotions can shape how employees process information and make choices, ultimately impacting organizational outcomes.

Keywords: employee decision making, social cognition, emotions, industry, emotional contagion, workplace dynamics

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Authors: Pawel Skruch, Marek Dlugosz

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The paper starts with a general model of the temperature dynamics in buildings. The modelling approach relies on thermodynamics, in particular heat transfer, principles. The model considers heat loses by conduction and ventilation and internal heat gains. The parameters of the model can be determined uniquely from the geometry of the building and from thermal properties of construction materials. The model is presented using state space notation and this form is used in the control design procedure. A sliding surface is defined by the system output and the desired trajectory. The control law is designed to force the trajectory of the system from any initial condition to the sliding surface in finite time. The trajectory of the system after reaching the sliding surface remains on it. A simulation example is included to verify the approach and to demonstrate the achievable performance improvement by the proposed solution in the temperature control in buildings.

Keywords: modelling, building, temperature dynamics, sliding-mode control, sliding surface

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Authors: Tivani Phosa Mashamba-Thompson, Mahmoud E. S. Soliman

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To date, the cause of neurodegeneration is not well understood and diseases that stem from neurodegeneration currently have no known cures. Cathepsin B (CB) enzyme is known to be involved in the production of peptide neurotransmitters and toxic peptides in neurodegenerative diseases (NDs). CA-074Me is a membrane-permeable irreversible selective cathepsin B (CB) inhibitor as confirmed by in vivo studies. Due to the lack of the crystal structure, the binding mode of CA-074Me with the human CB at molecular level has not been previously reported. The main aim of this study is to gain an insight into the binding mode of CB CA-074Me to human CB using various computational tools. Herein, molecular dynamics simulations, binding free energy calculations and per-residue energy decomposition analysis were employed to accomplish the aim of the study. Another objective was to identify novel CB inhibitors based on the structure of CA-074Me using fragment based drug design using scaffold hoping drug design approach. Results showed that two of the designed ligands (hit 1 and hit 2) were found to have better binding affinities than the prototype inhibitor, CA-074Me, by ~2-3 kcal/mol. Per-residue energy decomposition showed that amino acid residues Cys29, Gly196, His197 and Val174 contributed the most towards the binding. The Van der Waals binding forces were found to be the major component of the binding interactions. The findings of this study should assist medicinal chemist towards the design of potential irreversible CB inhibitors.

Keywords: cathepsin B, scaffold hopping, docking, molecular dynamics, binding-free energy, neurodegerative diseases

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Authors: Mohamed Adel Sennouni, Jamal Zbitou, Benaissa Abboud, Abdelwahed Tribak, Hamid Bennis, Mohamed Latrach

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A compact UWB planar antenna fed with a microstrip-line is proposed. The new design is composed of a rectangular patch with symmetric L-shaped slots and fed by 50 Ω microstrip transmission line and a reduced ground-plane which have a periodic slots with an overall size of 47 mm x 20 mm. It is intended to be used in wireless applications that cover the ultra-wideband (UWB) frequency band. A wider impedance bandwidth of around 116.5% (1.875

Keywords: UWB planar antenna, L-shaped slots, wireless applications, impedance band-width, radiation pattern, CST

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Authors: Bello Gonzalez, Setten Van M., Brouwer M.

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The chicken small intestine represents a dynamic and complex organ in which the enzymatic digestion and absorption of nutrients take place. The development of an in vitro fermentation chicken small intestinal model could be used as an alternative to explore the interaction between the microbiota and nutrient metabolism and to enhance the efficacy of targeting interventions to improve animal health. In the present study we have developed an in vitro fermentation chicken ileum microbiota model for unrevealing the complex interaction of ileum microbial community under physiological conditions. A two-vessel continuous fermentation process simulating in real-time the physiological conditions of the ileum content (pH, temperature, microaerophilic/anoxic conditions, and peristaltic movements) has been standardized as a proof of concept. As inoculum, we use a pool of ileum microbial community obtained from chicken broilers at the age of day 14. The development and validation of the model provide insight into the initial characterization of the ileum microbial community and its dynamics over time-related to nutrient assimilation and fermentation. Samples can be collected at different time points and can be used to determine the microbial compositional structure, dynamics, and diversity over time. The results of studies using this in vitro model will serve as the foundation for the development of a whole small intestine in vitro fermentation chicken gastrointestinal model to complement our already established in vitro fermentation chicken caeca model. The insight gained from this model could provide us with some information about the nutritional strategies to restore and maintain chicken gut homeostasis. Moreover, the in vitro fermentation model will also allow us to study relationships between gut microbiota composition and its dynamics over time associated with nutrients, antimicrobial compounds, and disease modelling.

Keywords: broilers, in vitro model, ileum microbiota, fermentation

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Authors: Shuenn-Yih Chang, Chiu-Li Huang

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Three structure-dependent integration methods have been developed for solving equations of motion, which are second-order ordinary differential equations, for structural dynamics and earthquake engineering applications. Although they generally have the same numerical properties, such as explicit formulation, unconditional stability and second-order accuracy, a different performance is found in solving the free vibration response to either linear elastic or nonlinear systems with high frequency modes. The root cause of this different performance in the free vibration responses is analytically explored herein. As a result, it is verified that a weak instability is responsible for the different performance of the integration methods. In general, a weak instability will result in an inaccurate solution or even numerical instability in the free vibration responses of high frequency modes. As a result, a weak instability must be prohibited for time integration methods.

Keywords: dynamic analysis, high frequency, integration method, overshoot, weak instability

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Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

Abstract:

Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: K. G. R. M. Jayathilake, S. Rudra

Abstract:

Wood degradation in hot compressed water is modeled with a Computational Fluid Dynamics (CFD) code using cellulose, xylan, and lignin as model compounds. Model compounds are reacted under catalyst-free conditions in a temperature range from 250 to 370 °C. Using a simplified reaction scheme where water soluble products, methanol soluble products, char like compounds and gas are generated through intermediates with each model compound. A modified multistage shrinking core model is developed to simulate particle degradation. In the modified shrinking core model, each model compound is hydrolyzed in separate stages. Cellulose is decomposed to glucose/oligomers before producing degradation products. Xylan is decomposed through xylose and then to degradation products where lignin is decomposed into soluble products before producing the total guaiacol, organic carbon (TOC) and then char and gas. Hydrolysis of each model compound is used as the main reaction of the process. Diffusion of water monomers to the particle surface to initiate hydrolysis and dissolution of the products in water is given importance during the modeling process. In the developed model the temperature variation depends on the Arrhenius relationship. Kinetic parameters from the literature are used for the mathematical model. Meanwhile, limited initial fast reaction kinetic data limit the development of more accurate CFD models. Liquefaction results of the CFD model are analyzed and validated using the experimental data available in the literature where it shows reasonable agreement.

Keywords: computational fluid dynamics, liquefaction, shrinking-core, wood

Procedia PDF Downloads 123

Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

Abstract:

Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Anvar Atayev, Karl Steinborn, Aleksander Lovric, Saif Al-Ibadi, Jorg Fliege

Abstract:

In this paper, we present results obtained from optimising the aerodynamic performance of aerostructures in external ow. The optimisation method used was developed to efficiently handle multi-variable problems with numerous black-box objective functions and constraints. To demonstrate these capabilities, a series of CFD problems were considered; (1) a two-dimensional NACA aerofoil with three variables, (2) a two-dimensional morphing aerofoil with 17 variables, and (3) a three-dimensional morphing aeroplane tail with 33 variables. The objective functions considered were related to combinations of the mean aerodynamic coefficients, as well as their relative variations/oscillations. It was observed that for each CFD problem, an improved objective value was found. Notably, the scale-up in variables for the latter problems did not greatly hinder optimisation performance. This makes the method promising for scaled-up CFD problems, which require considerable computational resources.

Keywords: computational fluid dynamics, optimisation algorithms, aerodynamic design, engineering design

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Authors: M. J. Uddin, M. M. Rahman

Abstract:

Transient natural convective flow dynamics of nanofluids in a horizontal homocentric annulus using nonhomogeneous dynamic model has been experimented numerically. The simulation is carried out for four different shapes of the inner wall, which is either cylindrical, elliptical, square or triangular. The outer surface of the annulus is maintained at constant low temperature while the inner wall is maintained at a uniform temperature; higher than the outer one. The enclosure is permeated by a uniform magnetic field having variable orientation. The Brownian motion and thermophoretic deposition phenomena of the nanoparticles are taken into account in model construction. The governing nonlinear momentum, energy, and concentration equations are solved numerically using Galerkin weighted residual finite element method. To find the best performer, the local Nusselt number is demonstrated for different shapes of the inner wall. The heat transfer enhancement for different nanofluids for four different shapes of the inner wall is exhibited.

Keywords: nanofluids, annulus, nonhomogeneous dynamic model, heat transfer

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Authors: Ramazan Kadiev, Arkadi Ponossov

Abstract:

Semidiscrete systems contain both continuous and discrete components. This means that the dynamics is mostly continuous, but at certain instants, it is exposed to abrupt influences. Such systems naturally appear in applications, for example, in biological and ecological models as well as in the control theory. Therefore, the study of semidiscrete systems has recently attracted the attention of many specialists. Stochastic effects are an important part of any realistic approach to modeling. For example, stochasticity arises in the population dynamics, demographic and ecological due to a change in time of factors external to the system affecting the survival of the population. In control theory, random coefficients can simulate inaccuracies in measurements. It will be shown in the presentation how to incorporate such effects into semidiscrete systems. Stability analysis is an essential part of modeling real-world problems. In the presentation, it will be explained how sufficient conditions for the moment stability of solutions in terms of the coefficients for linear semidiscrete stochastic equations can be derived using non-Lyapunov technique.

Keywords: abrupt changes, exponential stability, regularization, stochastic noises

Procedia PDF Downloads 185