Search results for: Beattie magnetic anomaly
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1597

Search results for: Beattie magnetic anomaly

817 Delving into the Concept of Social Capital in the Smart City Research

Authors: Atefe Malekkhani, Lee Beattie, Mohsen Mohammadzadeh

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Unprecedented growth of megacities and urban areas all around the world have resulted in numerous risks, concerns, and problems across various aspects of urban life, including environmental, social, and economic domains like climate change, spatial and social inequalities. In this situation, ever-increasing progress of technology has created a hope for urban authorities that the negative effects of various socio-economic and environmental crises can potentially be mitigated with the use of information and communication technologies. The concept of 'smart city' represents an emerging solution to urban challenges arising from increased urbanization using ICTs. However, smart cities are often perceived primarily as technological initiatives and are implemented without considering the social and cultural contexts of cities and the needs of their residents. The implementation of smart city projects and initiatives has the potential to (un)intentionally exacerbate pre-existing social, spatial, and cultural segregation. Investigating the impact of smart city on social capital of people who are users of smart city systems and with governance as policymakers is worth exploring. The importance of inhabitants to the existence and development of smart cities cannot be overlooked. This concept has gained different perspectives in the smart city studies. Reviewing the literature about social capital and smart city show that social capital play three different roles in smart city development. Some research indicates that social capital is a component of a smart city and has embedded in its dimensions, definitions, or strategies, while other ones see it as a social outcome of smart city development and point out that the move to smart cities improves social capital; however, in most cases, it remains an unproven hypothesis. Other studies show that social capital can enhance the functions of smart cities, and the consideration of social capital in planning smart cities should be promoted. Despite the existing theoretical and practical knowledge, there is a significant research gap reviewing the knowledge domain of smart city studies through the lens of social capital. To shed light on this issue, this study aims to explore the domain of existing research in the field of smart city through the lens of social capital. This research will use the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) method to review relevant literature, focusing on the key concepts of 'Smart City' and 'Social Capital'. The studies will be selected Web of Science Core Collection, using a selection process that involves identifying literature sources, screening and filtering studies based on titles, abstracts, and full-text reading.

Keywords: smart city, urban digitalisation, ICT, social capital

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816 Microstructural Origin of Morphotropic Phase Boundary and Magnetic Ordering in the Multiferroic BiFeO3-PbTiO3

Authors: Bastola Narayan, Rajeev Ranjan

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The morphotropic phase boundary (MPB) in the magnetoelectric (1-x)BiFeO3-(x)PbTiO3 has remained a matter of controversy ever since its discovery in 1964. The nature of the phase stabilized (single phase tetragonal or coexistence of tetragonal and rhombohedral phases) is very sensitive to the slight changes in the synthesis conditions. It thus remained an enigma as to what is the essential physical factor which is controlled by the slight difference in the synthesis conditions that finally determines, whether the phase formed will be single phase or coexistence of phases. In this paper, we demonstrate that the nature of the phase stabilized in this system is uniquely dependent on the crystallite size. The system is shown to exhibit features of abnormal grain growth (AGG) during sintering with abrupt increase in the grain size from ~ 1 micron to ~ 10 microns. The 10 micron grains exhibit pure tetragonal phase while the 1 micron grains exhibit coexistence of rhombohedral and tetragonal ferroelectric phases. The Rietveld analysis of powder neutron diffraction shows a paramagnetic to antiferromagnetic order transition inducing with crystalline size reduction from 10 micron to 1 micron. Since tetragonal phase is known to have paramagnetic order and rhombohedral phase has antiferromagnetic order in room temperature, this further strengthens our argument of size induced structure transition.

Keywords: size driven MPB, size driven magnetic ordering, abnormal grain growth, phase formation in BF-PT system

Procedia PDF Downloads 335
815 MHD Boundary Layer Flow of a Nanofluid Past a Wedge Shaped Wick in Heat Pipe

Authors: Ziya Uddin

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This paper deals with the theoretical and numerical investigation of magneto-hydrodynamic boundary layer flow of a nano fluid past a wedge shaped wick in heat pipe used for the cooling of electronic components and different type of machines. To incorporate the effect of nanoparticle diameter, concentration of nanoparticles in the pure fluid, nano thermal layer formed around the nanoparticle and Brownian motion of nano particles etc., appropriate models are used for the effective thermal and physical properties of nano fluids. To model the rotation of nano particles inside the base fluid, microfluidics theory is used. In this investigation ethylene glycol (EG) based nanofluids, are taken into account. The non-linear equations governing the flow and heat transfer are solved by using a very effective particle swarm optimization technique along with Runge-Kutta method. The values of heat transfer coefficient are found for different parameters involved in the formulation viz. nanoparticle concentration, nanoparticle size, magnetic field and wedge angle etc. It is found that the wedge angle, presence of magnetic field, nanoparticle size and nanoparticle concentration etc. have prominent effects on fluid flow and heat transfer characteristics for the considered configuration.

Keywords: nanofluids, wedge shaped wick, heat pipe, numerical modeling, particle swarm optimization, nanofluid applications, Heat transfer

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814 A Multipurpose Inertial Electrostatic Magnetic Confinement Fusion for Medical Isotopes Production

Authors: Yasser R. Shaban

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A practical multipurpose device for medical isotopes production is most wanted for clinical centers and researches. Unfortunately, the major supply of these radioisotopes currently comes from aging sources, and there is a great deal of uneasiness in the domestic market. There are also many cases where the cost of certain radioisotopes is too high for their introduction on a commercial scale even though the isotopes might have great benefits for society. The medical isotopes such as radiotracers PET (Positron Emission Tomography), Technetium-99 m, and Iodine-131, Lutetium-177 by is feasible to be generated by a single unit named IEMC (Inertial Electrostatic Magnetic Confinement). The IEMC fusion vessel is the upgrading unit of the Inertial Electrostatic Confinement IEC fusion vessel. Comprehensive experimental works on IEC were carried earlier with promising results. The principle of inertial electrostatic magnetic confinement IEMC fusion is based on forcing the binary fuel ions to interact in the opposite directions in ions cyclotrons orbits with different kinetic energies in order to have equal compression (forces) and with different ion cyclotron frequency ω in order to increase the rate of intersection. The IEMC features greater fusion volume than IEC by several orders of magnitude. The particles rate from the IEMC approach are projected to be 8.5 x 10¹¹ (p/s), ~ 0.2 microampere proton, for D/He-3 fusion reaction and 4.2 x 10¹² (n/s) for D/T fusion reaction. The projected values of particles yield (neutrons and protons) are suitable for medical isotope productions on-site by a single unit without any change in the fusion vessel but only the fuel gas. The PET radiotracers are usually produced on-site by medical ion accelerator whereas Technetium-99m (Tc-99m) is usually produced off-site from the irradiation facilities of nuclear power plants. Typically, hospitals receive molybdenum-99 isotope container; the isotope decays to Tc-99mwith half-life time 2.75 days. Even though the projected current from IEMC is lesser than the proton current from the medical ion accelerator but still the IEMC vessel is simpler, and reduced in components and power consumption which add a new value of populating the PET radiotracers in most clinical centers. On the other hand, the projected neutrons flux from the IEMC is lesser than the thermal neutron flux at the irradiation facilities of nuclear power plants, but in the IEMC case the productions of Technetium-99m is suggested to be at the resonance region of which the resonance integral cross section is two orders of magnitude higher than the thermal flux. Thus it can be said the net activity from both is evened. Besides, the particle accelerator cannot be considered a multipurpose particles production unless a significant change is made to the accelerator to change from neutrons mode to protons mode or vice versa. In conclusion, the projected fusion yield from IEMC is a straightforward since slightly change in the primer IEC and ion source is required.

Keywords: electrostatic versus magnetic confinement fusion vessel, ion source, medical isotopes productions, neutron activation

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813 The Motion of Ultrasonically Propelled Nanomotors Operating in Biomimetic Environments

Authors: Suzanne Ahmed

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Nanomotors, also commonly referred to as nanorobotics or nanomachines, have garnered considerable research attention due to their numerous potential applications in biomedicine, including drug delivery and microsurgery. Nanomotors typically consist of inorganic or polymeric particles that are powered to undergo motion. These artificial, man-made nanoscale motors operate in the low Reynolds number regime and typically have no moving parts. Several methods have been developed to actuate the motion of nanomotors including magnetic fields, electrical fields, electromagnetic waves, and chemical fuel. Since their introduction in 2012, ultrasonically powered nanomotors have been explored in biocompatible fluids and even within living cells. Due to the common use of ultrasound within the biomedical community for both imaging and therapeutics, the introduction of ultrasonically propelled nanomotors holds significant potential for biomedical applications. In this work, metallic nanomotors are electrochemically plated within porous anodic alumina templates to have a diameter of 300 nm and a length that is 2-4 µm. Nanomotors are placed within an acoustic chamber capable of producing bulk acoustic waves in the ultrasonic range. The motion of nanomotors within biomimetic confines is explored. The control over nanomotor motion is exerted by virtue of the properties of the acoustic signal within these biomimetic confines to control speed, modes of motion and directionality of motion. To expand the range of control over nanorod motion within biomimetic confines, external forces from biocompatible magnetic fields, are exerted onto the acoustically propelled nanomotors.

Keywords: nanomotors, nanomachines, nanorobots, ultrasound

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812 Attack Redirection and Detection using Honeypots

Authors: Chowduru Ramachandra Sharma, Shatunjay Rawat

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A false positive state is when the IDS/IPS identifies an activity as an attack, but the activity is acceptable behavior in the system. False positives in a Network Intrusion Detection System ( NIDS ) is an issue because they desensitize the administrator. It wastes computational power and valuable resources when rules are not tuned properly, which is the main issue with anomaly NIDS. Furthermore, most false positives reduction techniques are not performed during the real-time of attempted intrusions; instead, they have applied afterward on collected traffic data and generate alerts. Of course, false positives detection in ‘offline mode’ is tremendously valuable. Nevertheless, there is room for improvement here; automated techniques still need to reduce False Positives in real-time. This paper uses the Snort signature detection model to redirect the alerted attacks to Honeypots and verify attacks.

Keywords: honeypot, TPOT, snort, NIDS, honeybird, iptables, netfilter, redirection, attack detection, docker, snare, tanner

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811 Influence of Pretreatment Magnetic Resonance Imaging on Local Therapy Decisions in Intermediate-Risk Prostate Cancer Patients

Authors: Christian Skowronski, Andrew Shanholtzer, Brent Yelton, Muayad Almahariq, Daniel J. Krauss

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Prostate cancer has the third highest incidence rate and is the second leading cause of cancer death for men in the United States. Of the diagnostic tools available for intermediate-risk prostate cancer, magnetic resonance imaging (MRI) provides superior soft tissue delineation serving as a valuable tool for both diagnosis and treatment planning. Currently, there is minimal data regarding the practical utility of MRI for evaluation of intermediate-risk prostate cancer. As such, the National Comprehensive Cancer Network’s guidelines indicate MRI as optional in intermediate-risk prostate cancer evaluation. This project aims to elucidate whether MRI affects radiation treatment decisions for intermediate-risk prostate cancer. This was a retrospective study evaluating 210 patients with intermediate-risk prostate cancer, treated with definitive radiotherapy at our institution between 2019-2020. NCCN risk stratification criteria were used to define intermediate-risk prostate cancer. Patients were divided into two groups: those with pretreatment prostate MRI, and those without pretreatment prostate MRI. We compared the use of external beam radiotherapy, brachytherapy alone, brachytherapy boost, and androgen depravation therapy between the two groups. Inverse probability of treatment weighting was used to match the two groups for age, comorbidity index, American Urologic Association symptoms index, pretreatment PSA, grade group, and percent core involvement on prostate biopsy. Wilcoxon Rank Sum and Chi-squared tests were used to compare continuous and categorical variables. Of the patients who met the study’s eligibility criteria, 133 had a prostate MRI and 77 did not. Following propensity matching, there were no differences between baseline characteristics between the two groups. There were no statistically significant differences in treatments pursued between the two groups: 42% vs 47% were treated with brachytherapy alone, 40% vs 42% were treated with external beam radiotherapy alone, 18% vs 12% were treated with external beam radiotherapy with a brachytherapy boost, and 24% vs 17% received androgen deprivation therapy in the non-MRI and MRI groups, respectively. This analysis suggests that pretreatment MRI does not significantly impact radiation therapy or androgen deprivation therapy decisions in patients with intermediate-risk prostate cancer. Obtaining a pretreatment prostate MRI should be used judiciously and pursued only to answer a specific question, for which the answer is likely to impact treatment decision. Further follow up is needed to correlate MRI findings with their impacts on specific oncologic outcomes.

Keywords: magnetic resonance imaging, prostate cancer, definitive radiotherapy, gleason score 7

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810 Fast and Robust Long-term Tracking with Effective Searching Model

Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

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809 Wireless Sensor Anomaly Detection Using Soft Computing

Authors: Mouhammd Alkasassbeh, Alaa Lasasmeh

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We live in an era of rapid development as a result of significant scientific growth. Like other technologies, wireless sensor networks (WSNs) are playing one of the main roles. Based on WSNs, ZigBee adds many features to devices, such as minimum cost and power consumption, and increasing the range and connect ability of sensor nodes. ZigBee technology has come to be used in various fields, including science, engineering, and networks, and even in medicinal aspects of intelligence building. In this work, we generated two main datasets, the first being based on tree topology and the second on star topology. The datasets were evaluated by three machine learning (ML) algorithms: J48, meta.j48 and multilayer perceptron (MLP). Each topology was classified into normal and abnormal (attack) network traffic. The dataset used in our work contained simulated data from network simulation 2 (NS2). In each database, the Bayesian network meta.j48 classifier achieved the highest accuracy level among other classifiers, of 99.7% and 99.2% respectively.

Keywords: IDS, Machine learning, WSN, ZigBee technology

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808 Radio Frequency Heating of Iron-Filled Carbon Nanotubes for Cancer Treatment

Authors: L. Szymanski, S. Wiak, Z. Kolacinski, G. Raniszewski, L. Pietrzak, Z. Staniszewska

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There exist more than one hundred different types of cancer, and therefore no particular treatment is offered to people struggling with this disease. The character of treatment proposed to a patient will depend on a variety of factors such as type of the cancer diagnosed, advancement of the disease, its location in the body, as well as personal preferences of a patient. None of the commonly known methods of cancer-fighting is recognised as a perfect cure, however great advances in this field have been made over last few decades. Once a patient is diagnosed with cancer, he is in need of medical care and professional treatment for upcoming months, and in most cases even for years. Among the principal modes of treatment offered by medical centres, one can find radiotherapy, chemotherapy, and surgery. All of them can be applied separately or in combination, and the relative contribution of each is usually determined by medical specialist in agreement with a patient. In addition to the conventional treatment option, every day more complementary and alternative therapies are integrated into mainstream care. There is one promising cancer modality - hyperthermia therapy which is based on exposing body tissues to high temperatures. This treatment is still being investigated and is not widely available in hospitals and oncological centres. There are two kinds of hyperthermia therapies with direct and indirect heating. The first is not commonly used due to low efficiency and invasiveness, while the second is deeply investigated and a variety of methods have been developed, including ultrasounds, infrared sauna, induction heating and magnetic hyperthermia. The aim of this work was to examine possibilities of heating magnetic nanoparticles under the influence of electromagnetic field for cancer treatment. For this purpose, multiwalled carbon nanotubes used as nanocarriers for iron particles were investigated for its heating properties. The samples were subjected to an alternating electromagnetic field with frequency range between 110-619 kHz. Moreover, samples with various concentrations of carbon nanotubes were examined. The lowest frequency of 110 kHz and sample containing 10 wt% of carbon nanotubes occurred to influence the most effective heating process. Description of hyperthermia therapy aiming at enhancing currently available cancer treatment was also presented in this paper. Most widely applied conventional cancer modalities such as radiation or chemotherapy were also described. Methods for overcoming the most common obstacles in conventional cancer modalities, such as invasiveness and lack of selectivity, has been presented in magnetic hyperthermia characteristics, which explained the increasing interest of the treatment.

Keywords: hyperthermia, carbon nanotubes, cancer colon cells, ligands

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807 Superparamagnetic Sensor with Lateral Flow Immunoassays as Platforms for Biomarker Quantification

Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

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Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

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806 Simultaneous Determination of Six Characterizing/Quality Parameters of Biodiesels via 1H NMR and Multivariate Calibration

Authors: Gustavo G. Shimamoto, Matthieu Tubino

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The characterization and the quality of biodiesel samples are checked by determining several parameters. Considering a large number of analysis to be performed, as well as the disadvantages of the use of toxic solvents and waste generation, multivariate calibration is suggested to reduce the number of tests. In this work, hydrogen nuclear magnetic resonance (1H NMR) spectra were used to build multivariate models, from partial least squares (PLS) regression, in order to determine simultaneously six important characterizing and/or quality parameters of biodiesels: density at 20 ºC, kinematic viscosity at 40 ºC, iodine value, acid number, oxidative stability, and water content. Biodiesels from twelve different oils sources were used in this study: babassu, brown flaxseed, canola, corn, cottonseed, macauba almond, microalgae, palm kernel, residual frying, sesame, soybean, and sunflower. 1H NMR reflects the structures of the compounds present in biodiesel samples and showed suitable correlations with the six parameters. The PLS models were constructed with latent variables between 5 and 7, the obtained values of r(cal) and r(val) were greater than 0.994 and 0.989, respectively. In addition, the models were considered suitable to predict all the six parameters for external samples, taking into account the analytical speed to perform it. Thus, the alliance between 1H NMR and PLS showed to be appropriate to characterize and evaluate the quality of biodiesels, reducing significantly analysis time, the consumption of reagents/solvents, and waste generation. Therefore, the proposed methods can be considered to adhere to the principles of green chemistry.

Keywords: biodiesel, multivariate calibration, nuclear magnetic resonance, quality parameters

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805 Orbital Tuning of Marl-Limestone Alternations (Upper Tithonian to Upper Berriasian) in North-South Axis (Tunisia): Geochronology and Sequence Implications

Authors: Hamdi Omar Omar, Hela Fakhfakh, Chokri Yaich

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This work reflects the integration of different techniques, such as field sampling and observations, magnetic susceptibility measurement, cyclostratigaraphy and sequence stratigraphy. The combination of these results allows us to reconstruct the environmental evolution of the Sidi Khalif Formation in the North-South Axis (NOSA), aged of Upper Tithonian, Berriasian and Lower Valanginian. Six sedimentary facies were identified and are primarily influenced by open marine sedimentation receiving increasing terrigenous influx. Spectral analysis, based on MS variation (for the outcropped section) and wireline logging gamma ray (GR) variation (for the sub-area section) show a pervasive dominance of 405-kyr eccentricity cycles with the expression of 100-kyr eccentricity, obliquity and precession. This study provides (for the first time) a precise duration of 2.4 myr for the outcropped Sidi Khalif Formation with a sedimentation rate of 5.4 cm/kyr and the sub-area section to 3.24 myr with a sedimentation rate of 7.64 cm/kyr. We outlined 27 5th-order depositional sequences, 8 Milankovitch depositional sequences and 2 major 3rd-order cycles for the outcropping section, controlled by the long eccentricity (405 kyr) cycles and the precession index cycles. This study has demonstrated the potential of MS and GR to be used as proxies to develop an astronomically calibrated time-scale for the Mesozoic era.

Keywords: Berriasian, magnetic susceptibility, orbital tuning, Sidi Khalif Formation

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804 Exploring Spin Reorientation Transition and Berry Curvature Driven Anomalous Hall Effect in Quasi-2D vdW Ferromagnet Fe4GeTe2

Authors: Satyabrata Bera, Mintu Mondal

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Two-dimensional (2D) ferromagnetic materials have garnered significant attention due to their potential to host intriguing scientific phenomena such as the anomalous Hall effect, anomalous Nernst effect, and high transport spin polarization. This study focuses on the investigation of air-stable van der Waals(vdW) ferromagnets, FeGeTe₂ (FₙGT with n = 3, 4, and 5). Particular emphasis is placed on the Fe4GeTe2 (F4GT) compound, which exhibits a complex and fascinating magnetic behavior characterized by two distinct transitions: (i) paramagnetic (PM) to ferromagnetic (FM) around T C ∼ 270 K, and (ii) another spins reorientation transition (SRT) at T SRT ∼ 100 K . Scaling analysis of magnetocaloric effect confirms the second-order character of the ferromagnetic transition, while the same analysis at T SRT suggests that SRT is first-order phase transition. Moreover, the F4GT exhibits a large anomalous Hall conductivity (AHC), ∼ 490 S/cm at 2 K . The near-quadratic behavior of the anomalous Hall resistivity with the longitudinal resistivity suggests that a dominant AHC contribution arises from an intrinsic Berry curvature (BC) mechanism. Electronic structure calculations reveal a significant BC resulting from SOC-induced gapped nodal lines around the Fermi level, thereby giving rise to large AHC. Additionally, we reported exceptionally large anomalous Hall angle (≃ 10.6%) and Hall factor (≃ 0.22 V −1 ) values, the largest observed within this vdW family. The findings presented here, provide valuable insights into the fascinating magnetic and transport properties of 2D ferromagnetic materials, in particular, FₙGT family.

Keywords: 2D vdW ferromagnet, spin reorientation transition, anomalous hall effect, berry curvature

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803 Convolutional Neural Networks versus Radiomic Analysis for Classification of Breast Mammogram

Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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802 Quantification of Magnetic Resonance Elastography for Tissue Shear Modulus using U-Net Trained with Finite-Differential Time-Domain Simulation

Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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801 Temperature Dependent Magneto-Transport Properties of MnAl Binary Alloy Thin Films

Authors: Vineet Barwal, Sajid Husain, Nanhe Kumar Gupta, Soumyarup Hait, Sujeet Chaudhary

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High perpendicular magnetic anisotropy (PMA) and low damping constant (α) in ferromagnets are one of the few necessary requirements for their potential applications in the field of spintronics. In this regards, ferromagnetic τ-phase of MnAl possesses the highest PMA (Ku > 107 erg/cc) at room temperature, high saturation magnetization (Ms~800 emu/cc) and a Curie temperature of ~395K. In this work, we have investigated the magnetotransport behaviour of this potentially useful binary system MnₓAl₁₋ₓ films were synthesized by co-sputtering (pulsed DC magnetron sputtering) on Si/SiO₂ (where SiO₂ is native oxide layer) substrate using 99.99% pure Mn and Al sputtering targets. Films of constant thickness (~25 nm) were deposited at the different growth temperature (Tₛ) viz. 30, 300, 400, 500, and 600 ºC with a deposition rate of ~5 nm/min. Prior to deposition, the chamber was pumped down to a base pressure of 2×10⁻⁷ Torr. During sputtering, the chamber was maintained at a pressure of 3.5×10⁻³ Torr with the 55 sccm Ar flow rate. Films were not capped for the purpose of electronic transport measurement, which leaves a possibility of metal oxide formation on the surface of MnAl (both Mn and Al have an affinity towards oxide formation). In-plane and out-of-plane transverse magnetoresistance (MR) measurements on films sputtered under optimized growth conditions revealed non-saturating behavior with MR values ~6% and 40% at 9T, respectively at 275 K. Resistivity shows a parabolic dependence on the field H, when the H is weak. At higher H, non-saturating positive MR that increases exponentially with the strength of magnetic field is observed, a typical character of hopping type conduction mechanism. An anomalous decrease in MR is observed on lowering the temperature. From the temperature dependence of reistivity, it is inferred that the two competing states are metallic and semiconducting, respectively and the energy scale of the phenomenon produces the most interesting effects, i.e., the metal-insulator transition and hence the maximum sensitivity to external fields, at room temperature. Theory of disordered 3D systems effectively explains the crossover temperature coefficient of resistivity from positive to negative with lowering of temperature. These preliminary findings on the MR behavior of MnAl thin films will be presented in detail. The anomalous large MR in mixed phase MnAl system is evidently useful for future spintronic applications.

Keywords: magnetoresistance, perpendicular magnetic anisotropy, spintronics, thin films

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800 A Comparison between TM: TM Co Doped and TM: RE Co Doped ZnO Based Advanced Materials for Spintronics Applications; Structural, Optical and Magnetic Property Analysis

Authors: V. V. Srinivasu, Jayashree Das

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Owing to the industrial and technological importance, transition metal (TM) doped ZnO has been widely chosen for many practical applications in electronics and optoelectronics. Besides, though still a controversial issue, the reported room temperature ferromagnetism in transition metal doped ZnO has added a feather to its excellence and importance in current semiconductor research for prospective application in Spintronics. Anticipating non controversial and improved optical and magnetic properties, we adopted co doping method to synthesise polycrystalline Mn:TM (Fe,Ni) and Mn:RE(Gd,Sm) co doped ZnO samples by solid state sintering route with compositions Zn1-x (Mn:Fe/Ni)xO and Zn1-x(Mn:Gd/Sm)xO and sintered at two different temperatures. The structure, composition and optical changes induced in ZnO due to co doping and sintering were investigated by XRD, FTIR, UV, PL and ESR studies. X-ray peak profile analysis (XPPA) and Williamson-Hall analysis carried out shows changes in the values of stress, strain, FWHM and the crystallite size in both the co doped systems. FTIR spectra also show the effect of both type of co doping on the stretching and bending bonds of ZnO compound. UV-Vis study demonstrates changes in the absorption band edge as well as the significant change in the optical band gap due to exchange interactions inside the system after co doping. PL studies reveal effect of co doping on UV and visible emission bands in the co doped systems at two different sintering temperatures, indicating the existence of defects in the form of oxygen vacancies. While the TM: TM co doped samples of ZnO exhibit ferromagnetism at room temperature, the TM: RE co doped samples show paramagnetic behaviour. The magnetic behaviours observed are supported by results from Electron Spin resonance (ESR) study; which shows sharp resonance peaks with considerable line width (∆H) and g values more than 2. Such values are usually found due to the presence of an internal field inside the system giving rise to the shift of resonance field towards the lower field. The g values in this range are assigned to the unpaired electrons trapped in oxygen vacancies. TM: TM co doped ZnO samples exhibit low field absorption peaks in their ESR spectra, which is a new interesting observation. We emphasize that the interesting observations reported in this paper may be considered for the improved futuristic applications of ZnO based materials.

Keywords: co-doping, electro spin resonance, microwave absorption, spintronics

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799 Aluminum Based Hexaferrite and Reduced Graphene Oxide a Suitable Microwave Absorber for Microwave Application

Authors: Sanghamitra Acharya, Suwarna Datar

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Extensive use of digital and smart communication createsprolong expose of unwanted electromagnetic (EM) radiations. This harmful radiation creates not only malfunctioning of nearby electronic gadgets but also severely affects a human being. So, a suitable microwave absorbing material (MAM) becomes a necessary urge in the field of stealth and radar technology. Initially, Aluminum based hexa ferrite was prepared by sol-gel technique and for carbon derived composite was prepared by the simple one port chemical reduction method. Finally, composite films of Poly (Vinylidene) Fluoride (PVDF) are prepared by simple gel casting technique. Present work demands that aluminum-based hexaferrite phase conjugated with graphene in PVDF matrix becomes a suitable candidate both in commercially important X and Ku band. The structural and morphological nature was characterized by X-Ray diffraction (XRD), Field emission-scanning electron microscope (FESEM) and Raman spectra which conforms that 30-40 nm particles are well decorated over graphene sheet. Magnetic force microscopy (MFM) and conducting force microscopy (CFM) study further conforms the magnetic and conducting nature of composite. Finally, shielding effectiveness (SE) of the composite film was studied by using Vector network analyzer (VNA) both in X band and Ku band frequency range and found to be more than 30 dB and 40 dB, respectively. As prepared composite films are excellent microwave absorbers.

Keywords: carbon nanocomposite, microwave absorbing material, electromagnetic shielding, hexaferrite

Procedia PDF Downloads 178
798 The Nature and Impact of Trojan Horses in Cybersecurity

Authors: Mehrab Faraghti

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Trojan horses, a form of malware masquerading as legitimate software, pose significant cybersecurity threats. These malicious programs exploit user trust, infiltrate systems, and can lead to data breaches, financial loss, and compromised privacy. This paper explores the mechanisms through which Trojan horses operate, including delivery methods such as phishing and software vulnerabilities. It categorizes various types of Trojan horses and their specific impacts on individuals and organizations. Additionally, the research highlights the evolution of Trojan threats and the importance of user awareness and proactive security measures. By analyzing case studies of notable Trojan attacks, this study identifies common vulnerabilities that can be exploited and offers insights into effective countermeasures, including behavioral analysis, anomaly detection, and robust incident response strategies. The findings emphasize the need for comprehensive cybersecurity education and the implementation of advanced security protocols to mitigate the risks associated with Trojan horses.

Keywords: Trojan horses, cybersecurity, malware, data breach

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797 Dynamical Models for Enviromental Effect Depuration for Structural Health Monitoring of Bridges

Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

Procedia PDF Downloads 38
796 Predicting Oil Spills in Real-Time: A Machine Learning and AIS Data-Driven Approach

Authors: Tanmay Bisen, Aastha Shayla, Susham Biswas

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Oil spills from tankers can cause significant harm to the environment and local communities, as well as have economic consequences. Early predictions of oil spills can help to minimize these impacts. Our proposed system uses machine learning and neural networks to predict potential oil spills by monitoring data from ship Automatic Identification Systems (AIS). The model analyzes ship movements, speeds, and changes in direction to identify patterns that deviate from the norm and could indicate a potential spill. Our approach not only identifies anomalies but also predicts spills before they occur, providing early detection and mitigation measures. This can prevent or minimize damage to the reputation of the company responsible and the country where the spill takes place. The model's performance on the MV Wakashio oil spill provides insight into its ability to detect and respond to real-world oil spills, highlighting areas for improvement and further research.

Keywords: Anomaly Detection, Oil Spill Prediction, Machine Learning, Image Processing, Graph Neural Network (GNN)

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795 Preparation of Fe3Si/Ferrite Micro-and Nano-Powder Composite

Authors: Radovan Bures, Madgalena Streckova, Maria Faberova, Pavel Kurek

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Composite material based on Fe3Si micro-particles and Mn-Zn nano-ferrite was prepared using powder metallurgy technology. The sol-gel followed by autocombustion process was used for synthesis of Mn0.8Zn0.2Fe2O4 ferrite. 3 wt.% of mechanically milled ferrite was mixed with Fe3Si powder alloy. Mixed micro-nano powder system was homogenized by the Resonant Acoustic Mixing using ResodynLabRAM Mixer. This non-invasive homogenization technique was used to preserve spherical morphology of Fe3Si powder particles. Uniaxial cold pressing in the closed die at pressure 600 MPa was applied to obtain a compact sample. Microwave sintering of green compact was realized at 800°C, 20 minutes, in air. Density of the powders and composite was measured by Hepycnometry. Impulse excitation method was used to measure elastic properties of sintered composite. Mechanical properties were evaluated by measurement of transverse rupture strength (TRS) and Vickers hardness (HV). Resistivity was measured by 4 point probe method. Ferrite phase distribution in volume of the composite was documented by metallographic analysis. It has been found that nano-ferrite particle distributed among micro- particles of Fe3Si powder alloy led to high relative density (~93%) and suitable mechanical properties (TRS >100 MPa, HV ~1GPa, E-modulus ~140 GPa) of the composite. High electric resistivity (R~6.7 ohm.cm) of prepared composite indicate their potential application as soft magnetic material at medium and high frequencies.

Keywords: micro- and nano-composite, soft magnetic materials, microwave sintering, mechanical and electric properties

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794 Consideration of Failed Fuel Detector Location through Computational Flow Dynamics Analysis on Primary Cooling System Flow with Two Outlets

Authors: Sanghoon Bae, Hanju Cha

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Failed fuel detector (FFD) in research reactor is a very crucial instrument to detect the anomaly from failed fuels in the early stage around primary cooling system (PCS) outlet prior to the decay tank. FFD is considered as a mandatory sensor to ensure the integrity of fuel assemblies and mitigate the consequence from a failed fuel accident. For the effective function of FFD, the location of them should be determined by contemplating the effect from coolant flow around two outlets. For this, the analysis on computational flow dynamics (CFD) should be first performed how the coolant outlet flow including radioactive materials from failed fuels are mixed and discharged through the outlet plenum within certain seconds. The analysis result shows that the outlet flow is well mixed regardless of the position of failed fuel and ultimately illustrates the effect of detector location.

Keywords: computational flow dynamics (CFD), failed fuel detector (FFD), fresh fuel assembly (FFA), spent fuel assembly (SFA)

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793 Clinical Implication of Hyper-Intense Signal Thyroid Incidentaloma on Time of Flight Magnetic Resonance Angiography

Authors: Inseon Ryoo, Soo Chin Kim, Hyena Jung, Sangil Suh

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Objectives: The purpose of this study is to evaluate the clinical significance of hyper-intense signal thyroid incidentalomas on the time of flight magnetic resonance angiography (TOF-MRA) using correlation study with ultrasound (US). Methods: We retrospectively reviewed 3,505 non-contrast TOF-MRA performed at an institution between September 2014 and May 2017. Two radiologists correlated the thyroid incidentalomas detected on TOF-MRA with US features which was obtained within three months interval between MRA and US examinations in consensus method. Results: The prevalence of hyper-intense signal thyroid nodules incidentally detected on TOF-MRA was 1.2% (43/3505). Among them, 35 people (81.4%) underwent US examinations, and total 45 hyper-intense signal thyroid nodules were detected on US exams. Of these 45 nodules, 35 nodules (72.9%) were categorized as benign (K-TIRADS category 2) on US exams. Fine needle aspiration was performed on 9 nodules according to the indications recommended by Korean Society of Thyroid Radiology. All except one high-suspicious thyroid nodule were confirmed as benign (Bethesda 2) on cytologic exams. One high-suspicious nodule on US showed a non-diagnostic result (Bethesda 1) on cytologic exam. However, this nodule collapsed after aspiration of thick colloid material. Conclusions: Our study showed that the most hyper-intense signal thyroid nodules detected on TOF-MRA were benign. Therefore, if a hyper-intense signal incidentaloma is found on TOF-MRA, further evaluation, especially invasive biopsy of the nodules could be suspended unless the patient had other symptoms or clinical factors suggesting the need for further evaluation.

Keywords: incidentaloma, thyroid nodule, TOF MR angiography, ultrasound

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792 Delineation of Different Geological Interfaces Beneath the Bengal Basin: Spectrum Analysis and 2D Density Modeling of Gravity Data

Authors: Md. Afroz Ansari

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The Bengal basin is a spectacular example of a peripheral foreland basin formed by the convergence of the Indian plate beneath the Eurasian and Burmese plates. The basin is embraced on three sides; north, west and east by different fault-controlled tectonic features whereas released in the south where the rivers are drained into the Bay of Bengal. The Bengal basin in the eastern part of the Indian subcontinent constitutes the largest fluvio-deltaic to shallow marine sedimentary basin in the world today. This continental basin coupled with the offshore Bengal Fan under the Bay of Bengal forms the biggest sediment dispersal system. The continental basin is continuously receiving the sediments by the two major rivers Ganga and Brahmaputra (known as Jamuna in Bengal), and Meghna (emerging from the point of conflux of the Ganga and Brahmaputra) and large number of rain-fed, small tributaries originating from the eastern Indian Shield. The drained sediments are ultimately delivered into the Bengal fan. The significance of the present study is to delineate the variations in thicknesses of the sediments, different crustal structures, and the mantle lithosphere throughout the onshore-offshore Bengal basin. In the present study, the different crustal/geological units and the shallower mantle lithosphere were delineated by analyzing the Bouguer Gravity Anomaly (BGA) data along two long traverses South-North (running from Bengal fan cutting across the transition offshore-onshore of the Bengal basin and intersecting the Main Frontal Thrust of India-Himalaya collision zone in Sikkim-Bhutan Himalaya) and West-East (running from the Peninsular Indian Shield across the Bengal basin to the Chittagong–Tripura Fold Belt). The BGA map was derived from the analysis of topex data after incorporating Bouguer correction and all terrain corrections. The anomaly map was compared with the available ground gravity data in the western Bengal basin and the sub-continents of India for consistency of the data used. Initially, the anisotropy associated with the thicknesses of the different crustal units, crustal interfaces and moho boundary was estimated through spectral analysis of the gravity data with varying window size over the study area. The 2D density sections along the traverses were finalized after a number of iterations with the acceptable root mean square (RMS) errors. The estimated thicknesses of the different crustal units and dips of the Moho boundary along both the profiles are consistent with the earlier results. Further the results were encouraged by examining the earthquake database and focal mechanism solutions for better understanding the geodynamics. The earthquake data were taken from the catalogue of US Geological Survey, and the focal mechanism solutions were compiled from the Harvard Centroid Moment Tensor Catalogue. The concentrations of seismic events at different depth levels are not uncommon. The occurrences of earthquakes may be due to stress accumulation as a result of resistance from three sides.

Keywords: anisotropy, interfaces, seismicity, spectrum analysis

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791 Vibration Analysis of Magnetostrictive Nano-Plate by Using Modified Couple Stress and Nonlocal Elasticity Theories

Authors: Hamed Khani Arani, Mohammad Shariyat, Armaghan Mohammadian

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In the present study, the free vibration of magnetostrictive nano-plate (MsNP) resting on the Pasternak foundation is investigated. Firstly, the modified couple stress (MCS) and nonlocal elasticity theories are compared together and taken into account to consider the small scale effects; in this paper not only two theories are analyzed but also it improves the MCS theory is more accurate than nonlocal elasticity theory in such problems. A feedback control system is utilized to investigate the effects of a magnetic field. First-order shear deformation theory (FSDT), Hamilton’s principle and energy method are utilized in order to drive the equations of motion and these equations are solved by differential quadrature method (DQM) for simply supported boundary conditions. The MsNP undergoes in-plane forces in x and y directions. In this regard, the dimensionless frequency is plotted to study the effects of small scale parameter, magnetic field, aspect ratio, thickness ratio and compression and tension loads. Results indicate that these parameters play a key role on the natural frequency. According to the above results, MsNP can be used in the communications equipment, smart control vibration of nanostructure especially in sensor and actuators such as wireless linear micro motor and smart nano valves in injectors.

Keywords: feedback control system, magnetostrictive nano-plate, modified couple stress theory, nonlocal elasticity theory, vibration analysis

Procedia PDF Downloads 135
790 Catalytic Dehydrogenation of Formic Acid into H2/CO2 Gas: A Novel Approach

Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

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Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of biomass platform, comprising a potential pool of hydrogen energy that stands as a new energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need of in-situ H2 production, which plays a key role in the hydrogenation reactions of biomass into higher value components. It is reported elsewhere in literature that catalytic decomposition of FA is usually performed in poorly designed setup using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. it work suggests an approach that integrates designing a novel catalyst featuring magnetic property with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H2 gas from FA. Using ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under inert medium. Through a novel approach, FA is charged into the reactor via high-pressure positive displacement pump at steady state conditions. The produced gas (H2+CO2) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The novelty of this work lies in designing a very responsive catalyst, pumping consistent amount of FA into a sealed reactor running at steady state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at lower temperature range (35-50°C) yielded more gas while the catalyst loading and Pd doping wt.% were found to be the most significant factors with a P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

Procedia PDF Downloads 52
789 MRI R2* of Liver in an Animal Model

Authors: Chiung-Yun Chang, Po-Chou Chen, Jiun-Shiang Tzeng, Ka-Wai Mac, Chia-Chi Hsiao, Jo-Chi Jao

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This study aimed to measure R2* relaxation rates in the liver of New Zealand White (NZW) rabbits. R2* relaxation rate has been widely used in various hepatic diseases for iron overload by quantifying iron contents in liver. R2* relaxation rate is defined as the reciprocal of T2* relaxation time and mainly depends on the composition of tissue. Different tissues would have different R2* relaxation rates. The signal intensity decay in Magnetic resonance imaging (MRI) may be characterized by R2* relaxation rates. In this study, a 1.5T GE Signa HDxt whole body MR scanner equipped with an 8-channel high resolution knee coil was used to observe R2* values in NZW rabbit’s liver and muscle. Eight healthy NZW rabbits weighted 2 ~ 2.5 kg were recruited. After anesthesia using Zoletil 50 and Rompun 2% mixture, the abdomen of rabbit was landmarked at the center of knee coil to perform 3-plane localizer scan using fast spoiled gradient echo (FSPGR) pulse sequence. Afterward, multi-planar fast gradient echo (MFGR) scans were performed with 8 various echo times (TEs) (2/4/6/8/10/12/14/16 ms) to acquire images for R2* calculations. Regions of interest (ROIs) at liver and muscle were measured using Advantage workstation. Finally, the R2* was obtained by a linear regression of ln(SI) on TE. The results showed that the longer the echo time, the smaller the signal intensity. The R2* values of liver and muscle were 44.8  10.9 s-1 and 37.4  9.5 s-1, respectively. It implies that the iron concentration of liver is higher than that of muscle. In conclusion, R2* is correlated with iron contents in tissue. The correlations between R2* and iron content in NZW rabbit might be valuable for further exploration.

Keywords: liver, magnetic resonance imaging, muscle, R2* relaxation rate

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788 Remote Controlled of In-Situ Forming Thermo-sensitive Hydrogel Nanocomposite for Hyperthermia Therapy Application: Synthesis and Characterizations

Authors: Elbadawy A. Kamoun

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Magnetically responsive hydrogel nanocomposite (NCH) based on composites of superparamagnetic of Fe3O4 nano-particles and temperature responsive hydrogel matrices were developed. The nanocomposite hydrogel system based on the temperature sensitive N-isopropylacrylamide hydrogels crosslinked by poly(ethylene glycol)-400 dimethacrylate (PEG400DMA) incorporating with chitosan derivative, was synthesized and characterized. Likewise, the NCH system was synthesized by visible-light free radical photopolymerization, using carboxylated camphorquinone-amine system to avoid the common risks of the use of UV-light especially in hyperthermia treatment. Superparamagnetic of iron oxide nanoparticles were introduced into the hydrogel system by polymerizing mixture technique and monomer solution. FT-IR with Raman spectroscopy and Wide angle-XRD analysis were utilized to verify the chemical structure of NCH and exfoliation reaction for nanoparticles, respectively. Additionally, morphological structure of NCH was investigated using SEM and TEM photographs. The swelling responsive of the current nanocomposite hydrogel system with different crosslinking conditions, temperature, magnetic field efficiency, and the presence effect of magnetic nanoparticles were evaluated. Notably, hydrolytic degradation of this system was proved in vitro application. While, in-vivo release profile behavior is under investigation nowadays. Moreover, the compatibility and cytotoxicity tests were previously investigated in our studies for photoinitiating system. These systems show promised polymeric material candidate devices and are expected to have a wide applicability in various biomedical applications as mildly.

Keywords: hydrogel nanocomposites, tempretaure-responsive hydrogel, superparamagnetic nanoparticles, hyperthermia therapy

Procedia PDF Downloads 279