Search results for: pneumonia dynamics

Authors: Karl Owen L. Suan, Juliet Marie S. Lambayan, Floramay P. Salo-Curato

Abstract:

Objective: To predict the outcome among patients admitted with community-acquired pneumonia (ages 3 months to 59 months old) admitted in Visayas Community Medical Center using the Respiratory Index of Severity in Children (RISC). Design: A cross-sectional study design was used. Setting: The study was done in Visayas Community Medical Center, which is a private tertiary level in Cebu City from January-June 2013. Patients/Participants: A total of 72 patients were initially enrolled in the study. However, 1 patient transferred to another institution, thus 71 patients were included in this study. Within 24 hours from admission, patients were assigned a RISC score. Statistical Analysis: Cohen’s kappa coefficient was used for inter-rater agreement for categorical data. This study used frequency and percentage distribution for qualitative data. Mean, standard deviation and range were used for quantitative data. To determine the relationship of each RISC score parameter and the total RISC score with the outcome, a Mann Whitney U Test and 2x2 Fischer Exact test for testing associations were used. A p value less of than 0.05 alpha was considered significant. Results: There was a statistical significance between RISC score and clinical outcome. RISC score of greater than 4 was correlated with intubation and/or mortality. Conclusion: The RISC scoring system is a simple combination of clinical parameters and a reliable tool that will help stratify patients aged 3 months to 59 months in predicting clinical outcome.

Keywords: RISC, clinical outcome, community-acquired pneumonia, patients

Procedia PDF Downloads 302

Authors: Jonathan Gong

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

Procedia PDF Downloads 130

Authors: Nadia A. Mohamed, Magdy W. Sabaa, Ahmed H. H. El-Ghandour, Marwa M. Abdel-Aziz, Omayma F. Abdel-Gawad

Abstract:

Eighteen carboxymethyl chitosan (CMCh) schiff bases and their reduced derivatives have been synthesized. They were characterized by spectral analyses (FT-IR and H1-NMR) and scanning electron microscopy observation. Their antibacterial activities against Streptococcus pneumoniae (RCMB 010010), Bacillis subtilis (RCMB 010067), as Gram positive bacteria and Escherichia coli (RCMB 010052) as Gram negative bacteria and the antifungal activity against Aspergillus fumigatus (RCMB 02568), Geotricum candidum (RCMB 05097), and Candida albicans (RCMB 05031) were examined using agar disk diffusion method. The results demonstrate how the antibacterial and the antifungal activity are clearly affected by both the nature and position of the substituent groups in the aryl ring of the prepared derivatives. CMCh-4-nitroBenz Schiff base and its reduced form show higher antimicrobial activity comparing with other para substituted derivatives. CMCh-4-nitroBenz Schiff base: 18.3, 17, and 15.6 mm against Bacillis subtilis, Streptococcus pneumonia, and Escherichia coli respectively and 16.2, 17.3, and 16.4 mm against Aspergillus fumigates, Geotricum candidum, and Candida albicans respectively. CMCh-4-nitroBenz reduced form: 19.5, 18.7, and 16.2 mm against Bacillis subtilis, Streptococcus pneumonia, and Escherichia coli respectively and 17.5, 19.5, and 17.4 mm against Aspergillus fumigates, Geotricum candidum, and Candida albicans respectively. Also CMCh-3-bromoBenz show good results; CMCh-3-bromoBenz schiff base: 19.2, 16.9, and 14.6 mm Bacillis subtilis, Streptococcus pneumonia, and Escherichia coli respectively and 18.4, 17.6, and 15.9 mm against Aspergillus fumigates, Geotricum candidum, and Candida albicans respectively.

Keywords: chitosan, schiff base, minimum inhibition concentration, antimicrobial activity

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Authors: Sathish Kumar Jayaraj

Abstract:

The study of urban traffic dynamics, underpinned by the principles of fluid dynamics, offers a distinct perspective to comprehend and enhance the efficiency of traffic flow within bustling cityscapes. Leveraging the concept of the Traffic Flow Factor (TFF) as an analog to the Reynolds number, this research delves into the intricate interplay between traffic density, velocity, and road category, drawing compelling parallels to fluid dynamics phenomena. By introducing the notion of Vehicle Shearing Resistance (VSR) as an analogy to dynamic viscosity, the study sheds light on the multifaceted influence of traffic regulations, lane management, and road infrastructure on the smoothness and resilience of traffic flow. The TFF equation serves as a comprehensive metric for quantifying traffic dynamics, enabling the identification of congestion hotspots, the optimization of traffic signal timings, and the formulation of data-driven traffic management strategies. The study underscores the critical significance of integrating fluid dynamics principles into the domain of urban traffic management, fostering sustainable transportation practices, and paving the way for a more seamless and resilient urban mobility ecosystem.

Keywords: traffic flow factor (TFF), urban traffic dynamics, fluid dynamics principles, vehicle shearing resistance (VSR), traffic congestion management, sustainable urban mobility

Procedia PDF Downloads 62

Authors: Anca Radulescu, Danae Evans

Abstract:

The relationship between a network’s hardwiring and its emergent dynamics are central to neuroscience. We study the principles of this correspondence in a canonical setup (in which network nodes exhibit well-studied complex quadratic dynamics), then test their universality in biological networks. By extending methods from discrete dynamics, we study the effects of network connectivity on temporal patterns, encapsulating long-term behavior into the rich topology of network Mandelbrot sets. Then elements of fractal geometry can be used to predict and classify network behavior.

Keywords: canonical model, complex dynamics, dynamic networks, fractals, Mandelbrot set, network connectivity

Procedia PDF Downloads 308

Authors: Adel Edwar Waheeb Louka

Abstract:

Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: D. He, Y. Pang, G. Lodewijks

Abstract:

Belt conveyors play an important role in continuous dry bulk material transport, especially at the mining industry. Speed control is expected to reduce the energy consumption of belt conveyors. Transient operation is the operation of increasing or decreasing conveyor speed for speed control. According to literature review, current research rarely takes the conveyor dynamics in transient operation into account. However, in belt conveyor speed control, the conveyor dynamic behaviors are significantly important since the poor dynamics might result in risks. In this paper, the potential risks in transient operation will be analyzed. An existing finite element model will be applied to build a conveyor model, and simulations will be carried out to analyze the conveyor dynamics. In order to realize the soft speed regulation, Harrison’s sinusoid acceleration profile will be applied, and Lodewijks estimator will be built to approximate the required acceleration time. A long inclined belt conveyor will be studied with two major simulations. The conveyor dynamics will be given.

Keywords: belt conveyor , speed control, transient operation, dynamics

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Authors: K. Pandey

Abstract:

The present study is a functional analysis of the relationship between castes which indicates the dynamics of the caste structure in the rural setting. The researcher has tried to show both the cooperation and competition on important ceremonial and social occasions. The real India exists in the villages, so we need to know about their solidarity and also what the village life is and has been shaping into. We need to emphasize a microcosmic study of Indian rural life. Furthermore, caste integration is an acute problem country faces today. To resolve this we are required to know the dynamics of behavior of the people of different castes and for the study of the caste dynamics a study of caste relations are needed. The present study is an attempt in this direction.

Keywords: hierarchial groups, jajmani system, functional dependence, commensalities

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Authors: K. Manmi, Q. X. Wang

Abstract:

This paper investigates microbubble dynamics subject to ultrasound in a weakly viscous fluid near a rigid boundary. The phenomenon is simulated using a boundary integral method. The weak viscous effects are incorporated into the model through the normal stress balance across the bubble surface. The model agrees well with the Rayleigh-Plesset equation for a spherical bubble for several cycles. The effects of the fluid viscosity in the bubble dynamics are analyzed, including jet development, centroid movement and bubble volume.

Keywords: microbubble dynamics, bubble jetting, viscous effect, boundary integral method

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Authors: Ramdas Sonawane, Mahaveer Gadiya

Abstract:

The control problem associated with nuclear dynamics is represented by nonlinear integro-differential equation with additive controls. To control chain reaction, certain amount of neutrons is added into (or withdrawn out of) chamber as and when required. It is not realistic. So, we can think of controlling the reactor dynamics by bilinear control, which enters the system as coefficient of state. In this paper, we study the approximate and exact controllability of parabolic integro-differential equation controlled by bilinear control with non-homogeneous boundary conditions in bounded domain. We prove the existence of control and propose an explicit control strategy.

Keywords: approximate control, exact control, bilinear control, nuclear dynamics, integro-differential equations

Procedia PDF Downloads 444

Authors: Syeda Sahra, Abdullah Jahangir, Rachelle Hamadi, Ahmad Jahangir, Allison Glaser

Abstract:

Background: Antimicrobial resistance is on the rise. The use of redundant and inappropriate antibiotics is contributing to recurrent infections and resistance. Newer antibiotics with more robust coverage for gram-negative bacteria are in great demand for complicated urinary tract infections (cUTIs), complicated intra-abdominal infections (cIAIs), hospital-acquired bacterial pneumonia (H.A.B.P.), and ventilator-associated bacterial pneumonia (V.A.B.P.). Objective: We performed this meta-analysis to evaluate the efficacy and safety profile of a new antibiotic, Imipenem/cilastatin/relebactam, compared to other broad-spectrum antibiotics for complicated infections. Search Strategy: We conducted a systemic review search on PubMed, Embase, and Central Cochrane Registry. Selection Criteria: We included randomized clinical trials (R.C.T.s) with the standard of care as comparator arm with Imipenem/cilastatin/relebactam as intervention arm. Analysis: For continuous variables, the mean difference was used. For discrete variables, we used the odds ratio. For effect sizes, we used a confidence interval of 95%. A p-value of less than 0.05 was used for statistical significance. Analysis was done using a random-effects model irrespective of heterogeneity. Heterogeneity was evaluated using the I2 statistic. Results: The authors observed similar efficacy at clinical and microbiologic response levels on early follow-up and late follow-up compared to the established standard of care. The incidence of drug-related adverse events, serious adverse events, and drug discontinuation due to adverse events were comparable across both groups. Conclusion: Imipenem/cilastatin/relebactam has a non-inferior safety and efficacy profile compared to peer antibiotics to treat severe bacterial infections (cUTIs, cIAIs, H.A.B.P., V.A.B.P.).

Keywords: bacterial pneumonia, complicated intra-abdominal infections, complicated urinary tract infection, Imipenem, cilastatin, relebactam

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Authors: Musadiq Idris, Sajjad Ali, Syed A. Khaliq, Umer Farooq

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Postmortem record of 217 captive ungulates including Black-buck (n=31), Chinkara (n=20), Hog deer (n=116), Spotted deer (n=35), Red Deer n=(04), and Rusa deer (n=11) submitted to the Veterinary Research Institute, Lahore, Pakistan was analyzed to determine the primary cause of mortality in these animals. The submissions included temporal distribution from Government wildlife captive farms, zoo, and private ownerships, over a three year period (2007-2009). The most common cause of death was found to be trauma (20.27%), followed by parasitic diseases (15.67%), bacterial diseases (11.98%), stillbirths (9.21%), snakebites (2.76%), gut affections (2.30%), neoplasia (1.38%) and starvation (0.92%). The exact cause of death could not be determined in 77 of 217 animals. Pneumonia (8.29%) and tuberculosis (3.69%) were the most common bacterial diseases. Analyses for parasitic infestation revealed tapeworms to be highest (11.05%), followed by roundworms (8.29%) and hemoparasitism (5.07%) (babesiosis and theileriosis). The mortality rate in young ungulates was lower as compared to adults (32.26% and 67.74%). Gender wise data presented higher mortality in females (55.30%) compared to males (44.70%). In conclusion, highest mortality factor in captive ungulates was trauma, followed by parasitic and bacterial infestations/infections of tapeworms and pneumonia, respectively. Furthermore, necropsies provided substantial information on etiology of death and other related epidemiological aspects.

Keywords: age, epidemiology, gender, mortality, ungulates

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Authors: Mohammad A. Bani-Khaled

Abstract:

In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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Authors: Pardeep Bishnoi, Mayank Srivastava, Mrityunjay Kumar Sinha

Abstract:

This article represents the numerical investigation of the pressure and velocity field variation of the dynamics of pendant drop formation through a capillary tube. Numerical simulations are executed using volume of fluid (VOF) method in the computational fluid dynamics (CFD). In this problem, Non Newtonian fluid is considered as dispersed fluid whereas air is considered as a continuous fluid. Pressure contours at various time steps expose that pressure varies nearly hydrostatically at each step of the dynamics of drop formation. A result also shows the pressure variation of the liquid droplet during free fall in the computational domain. The evacuation of the fluid from the necking region is also shown by the contour of the velocity field. The role of surface tension in the Pressure contour of the dynamics of drop formation is also studied.

Keywords: pressure contour, surface tension, volume of fluid, velocity field

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Authors: Po-Ting Chen, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

Abstract:

Classical molecular dynamics (CMD) simulations are highly efficient for material simulations but have limited accuracy. In contrast, ab initio molecular dynamics (AIMD) provides high precision by solving the Kohn–Sham equations yet requires significant computational resources, restricting the size of systems and time scales that can be simulated. To address these challenges, we employed NequIP, a machine learning model based on an E(3)-equivariant graph neural network, to accelerate molecular dynamics simulations of a 1M LiPF6 in EC/EMC (v/v 3:7) for Li battery applications. AIMD calculations were initially conducted using the Vienna Ab initio Simulation Package (VASP) to generate highly accurate atomic positions, forces, and energies. This data was then used to train the NequIP model, which efficiently learns from the provided data. NequIP achieved AIMD-level accuracy with significantly less training data. After training, NequIP was integrated into the LAMMPS software to enable molecular dynamics simulations of larger systems over longer time scales. This method overcomes the computational limitations of AIMD while improving the accuracy limitations of CMD, providing an efficient and precise computational framework. This study showcases NequIP’s applicability to electrolyte systems, particularly for simulating the dynamics of LiPF6 ionic mixtures. The results demonstrate substantial improvements in both computational efficiency and simulation accuracy, highlighting the potential of machine learning models to enhance molecular dynamics simulations.

Keywords: lithium-ion batteries, electrolyte simulation, molecular dynamics, neural network

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Authors: Minna Chang

Abstract:

Introduction: M. pneumoniae is a respiratory pathogen, which commonly causes upper and lower respiratory infections. It primarily affects children and young adults. Respiratory symptoms are well recognized, but extrapulmonary involvement is also common. Other systems that have been implicated in the disease include: skin, mucus membranes, central, peripheral nervous systems, cardiovascular, haematological, renal, and musculoskeletal systems. Here, we report a case of an otherwise healthy, young female with M. pneumonia, who presented with right upper quadrant abdominal pain. Case presentation: a healthy 25-year-old female was referred to A&E by her general practitioner, after presenting with fever, malaise, and right upper quadrant pain. M. pneumoniae was confirmed retrospectively by serology. The patient made a full recovery after a six-day course of doxycycline 100mg. Conclusion: M. pneumonia is a well-established cause of respiratory infections in children and young adults. Febrile illness with multisystem involvement, even in the absence of respiratory symptoms, should raise suspicion of M. pneumoniae infection in healthy, young adults. Our case illustrates the multi-system involvement of M. pneumoniae, which was initially missed, due to paucity of respiratory symptoms at presentation.

Keywords: infectious diseases, mycoplasma pneumoniae, respiratory infections, extra-pulmonary manifestations

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Authors: Meziane Belkacem

Abstract:

We aim at converting the original 3D Lorenz-Haken equations, which describe laser dynamics –in terms of self-pulsing and chaos- into 2-second-order differential equations, out of which we extract the so far missing mathematics and corroborations with respect to nonlinear interactions. Leaning on basic trigonometry, we pull out important outcomes; a fundamental result attributes chaos to forbidden periodic solutions inside some precisely delimited region of the control parameter space that governs the bewildering dynamics.

Keywords: Physics, optics, nonlinear dynamics, chaos

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Authors: Iwan Setiawan, Bobby Eka Gunara, Katshuhiro Nakamura

Abstract:

The theory to accelerate system on quantum dynamics has been constructed to get the desired wave function on shorter time. This theory is developed on adiabatic quantum dynamics which any regulation is done on wave function that satisfies Schrödinger equation. We show accelerated manipulation of WFs with the use of a parameter-dependent in asymmetric double-well potential and also when it’s influenced by electromagnetic fields.

Keywords: driving potential, Adiabatic Quantum Dynamics, regulation, electromagnetic field

Procedia PDF Downloads 338

Authors: Melika Masjedi

Abstract:

Post-Traumatic Stress Disorder (PTSD) has a significant impact on the mental health and relationship dynamics of couples, leading to decreased marital satisfaction. This study examines the mediating role of sexual and romantic relationship dynamics in relation to PTSD and marital satisfaction among Iranian couples. Using a sample of 107 participants, quantitative methods were utilized to assess variables such as relationship functioning, PTSD symptom severity, and the influence of sexual and romantic interactions. The findings demonstrate a strong correlation between heightened PTSD symptoms and reduced marital satisfaction, particularly in the domains of intimacy and emotional connection. The study highlights the importance of addressing relational dynamics to improve marital outcomes in PTSD-affected couples.

Keywords: intimacy, marital satisfaction, PTSD, relationship dynamics, trauma

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Authors: Christian Angerer, Markus Lienkamp

Abstract:

Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Boguslaw Schreyer

Abstract:

In this paper, a general dynamical model is derived using the Lagrange formalism. The two masses: sprang and unsprang are included in a six-degree of freedom model for a sprung mass. The unsprung mass is included and shown only in a simplified model, although its equations have also been derived by an author. The simplified equations, more suitable for the computer model of robot’s dynamics are also shown.

Keywords: dynamics, mobile, robot, wheeled mobile robots

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Authors: Christopher I. Ifeacho, Adeleke Omolade

Abstract:

The paper examines the relationship between energy price dynamics and green growth in Sub Sahara African Countries. The quest for adopting green energy in order to improve green growth that can engender sustainability and stability has received more attention from researchers in recent times. This study uses a panel autoregressive distributed lag approach to investigate this relationship. Findings from the result showed that energy price dynamics and exchange rates have more short-run significant impacts on green growth in individual countries rather than the pooled result. Furthermore, the long-run result confirmed that inflation and capital have a significant long-run relationship with green growth. The causality test result revealed the existence of a bi-directional relationship between green growth and energy price dynamics. The study recommends caution in a currency devaluation and improvement in renewable energy production in the Sub Sahara Africa in order to achieve sustainable green growth.

Keywords: green growth, energy price dynamics, Sub Saharan Africa, relationship

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Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.

Keywords: model predictive control, optimal control, process control, crystal growth

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Authors: Luong A. Nguyen, Elihu Deneke, Thomas L. Harman

Abstract:

This paper describes a multibody dynamics algorithm formulated for parallel implementation on multiprocessor computing platforms using the divide-and-conquer approach. The system of interest is a general topology of rigid and elastic articulated bodies with or without loops. The algorithm is an extension of Featherstone’s divide and conquer approach to include the flexible-body dynamics formulation. The equations of motion, configured for the International Space Station (ISS) with its robotic manipulator arm as a system of articulated flexible bodies, are implemented in separate computer processors. The performance of this divide-and-conquer algorithm implementation in multiple processors is compared with an existing method implemented on a single processor.

Keywords: multibody dynamics, multiple processors, multithreading, divide-and-conquer algorithm, computational efficiency, flexible body dynamics

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Authors: Christopher Ikechukwu Ifeacho

Abstract:

The paper examines the relationship between energy price dynamics and green growth in Sub Sahara African Countries. The quest for adopting green energy in order to improve the green growth that can engender sustainability, and stability has received more attention from researchers in recent times. This study uses a panel Autoregressive distributed lag approach to investigate this relationship. Findings from the result showed that energy price dynamics and exchange rate have more short-run significant impacts on green growth in individual countries rather than the pooled result. Furthermore, the long-run result confirmed that inflation and capital have a significant long-run relationship with green growth. The causality test result revealed the existence of a bi-directional relationship between green growth and energy price dynamics. The study recommends caution in a currency devaluation and improvement in renewable energy production in the Sub Sahara Africa in order to achieve sustainable green growth.

Keywords: green growth, energy price dynamics, Sub Sahara Africa., sustainability

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Authors: Nina Tsvetkova, Rumen Harizanov, Aleksandra Ivanova, Iskra Rainova, Nina Yancheva-Petrova, Dimitar Strashimirov, Raina Enikova, Mihaela Videnova, Eleonora Kaneva, Iskren Kaftandjiev, Viktoria Levterova, Ivan Simeonovski, Nikolay Yanev, Georgi Hinkov

Abstract:

The Pneumocystis jirovecii (P. jirovecii) and protozoan of the genera Acanthamoeba, Cryptosporidium, and Toxoplasma gondii are opportunistic pathogens that can cause life-threatening infections in immunocompromised patients. Aim of the study was to evaluate the coinfection rate with opportunistic protozoal agents among Bulgarian patients diagnosed with P. jirovecii pneumonia. Thirty-eight pulmonary samples were collected from 38 patients (28 HIV-infected) with P. jirovecii infection. P. jirovecii DNA was detected by real-time PCR targeting the large mitochondrial subunit ribosomal RNA gene. Acanthamoeba was determined by genus-specific conventional PCR assay. Real-time PCR for the detection of a Toxoplasma gondii and Cryptosporidium DNA fragment was used. Pneumocystis DNA was detected in all 38 specimens; 28 (73.7%) were from HIV-infected patients. Three (10,7%) of them were co-infected with T. gondii and 1 (3.6%) with Cryptosporidium. In the group of non-HIV-infected (n=10), Cryptosporidium DNA was detected in an infant (10%). Acanthamoeba DNA was not found in the tested samples. The current study showed a relatively low rate of coinfections of Cryptosporidium spp./T. gondii and P. jirovecii in the Bulgarian patients studied.

Keywords: coinfection, opportunistic protozoal agents, Pneumocystis jirovecii, pulmonary infections

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Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

Abstract:

This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: state estimation, control systems, observer systems, nonlinear systems

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Authors: Emmanuel Jaluchimike Iloputaife, Kelechi Nkechinyere Mbah-Omeje

Abstract:

This study was designed to determine the antimicrobial activities and minimum inhibitory concentration of three different batches (Fresh, Oven dried and Sundried) of Ass Hay extracted with water, ethanol and methanolagainst selected human pathogenic microorganisms (Escherichia coli, Klebsiella Pneumonia, Staphylococcus aureus, Aspergillus niger and Candidaalbicans). All extracts were reconstituted with peptone water and tested for antimicrobial activity. The antimicrobial activity, the Minimum Inhibitory Concentration and Minimum Bactericidal/Fungicidal concentrations were determined by agar well diffusion methodagainst test organismsin which aseptic conditions were observed. The antimicrobial activities of the different batches of Ass Hay on the test organisms varied considerably. The highest inhibition zone diameter at 200 mg/ml for the different batches of Ass Hay was recorded by sundried methanol extract against Escherichia coli at 36.4 ± 0.2 mm while fresh methanol extract inhibited Klebsiela pneumonia with the least inhibition zone diameter at 20.1 ± 0.1mm. At 100 mg/ml the highest inhibition zone diameter was recorded by oven dried water extract against Escherichia coli at 30.3 ± 0.3 mm while sun dried water extract inhibited Staphylococcus aureus with the least inhibition zone diameter at 15.1 ± 0.1 mm. At 50mg/ml, the highest inhibition zone diameter was recorded by fresh water extract against Escherichia coli at 25.9 ± 0.1 mm while oven dried water extract inhibited Klebsiela pneumonia with least inhibition zone diameter at 12.1 ± 0.2 mm. At 25mg/ml, the highest inhibition zone diameter was recorded by fresh water extract against Escherichia coli at 18.3 ± 0.2 mm while sun dried ethanol extract inhibited Escherichia coli with least inhibition zone diameter at 10.1 ± 0.1 mm. The MIC and MBC result of ethanol extract of fresh Ass Hay showed a uniform value of 6.25 mg/ml and 12.5 mg/ml respectively for all test bacterial isolates. The Minimum Inhibitory concentration and Minimum bactericidal concentration results of Oven dried ethanol Ass Hay extract showed a uniform value of 3.125 mg/ml and 6.25 mg/ml respectively for all test bacterial isolates and Minimum fungicidal concentration value of 12.5 mg/ml for Aspergillus niger. Statistical analysis showed there is significant difference in mean zone inhibition diameter of the products at p < 0.05, p = 0.019. This study has shown there is antimicrobial potential in Ass Hay and at such there is need to further exploit Donkey Ass Hay in order to maximize the potential.

Keywords: microorganisms, Ass Hay, antimicrobial activity, extracts

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Authors: Tai-Young Park, Yangjin Park

Abstract:

Introduction: This study analyzed a family therapy case involving a female client in her thirties with panic disorder (PD) in South Korea. We identified five stages of the psychological process in the development of PD and examined external situations, family dynamics, and psychological experiences at each stage. Method: The client, mother, sister, and husband participated in therapy. Researchers analyzed the transcripts, notes, and video recordings of the therapy sessions. A thematic analysis was used to examine the data and display our findings using a network. Results: The developmental process of PD was as follows: (1) formation of anxiety, (2) sheltered life, (3) crisis, (4) loss of safe haven, and (5) inner breakdown. Conclusion: The family dynamics that developed as a result of coping with external situations in each stage contributed to clients’ psychological experiences. These psychological experiences triggered anxiety, which led to the development of PD. Moreover, this study empirically suggests that family dynamics can be associated with a person’s internal experiences that could lead to PD. Our findings highlight the significance of functional family dynamics and coping patterns when facing difficult external situations or crises.

Keywords: developmental process, family therapy, panic disorder, psychological dynamics

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Authors: Arturo Ayala-Hernandez, Humberto Hijar

Abstract:

We propose a new alternative method for imposing fluid-solid boundary conditions in simulations of Multiparticle Collision Dynamics. Our method is based on the introduction of an explicit potential force acting between the fluid particles and a surface representing a solid boundary. We show that our method can be used in simulations of plane Poiseuille flows. Important quantities characterizing the flow and the fluid-solid interaction like the slip coefficient at the solid boundary and the effective viscosity of the fluid, are measured in terms of the set of independent parameters defining the numerical implementation. We find that our method can be used to simulate the correct hydrodynamic flow within a wide range of values of these parameters.

Keywords: Multiparticle Collision Dynamics, fluid-solid, boundary conditions, molecular dynamics

Procedia PDF Downloads 538