Miracle-dz/UniFAR-FTUs huggingface dataset:
Analytical Calculation and Experimental Verification of Superconducting Electrodynamic Suspension System Using Null-Flux Ground Coils

Superconducting (SC) electrodynamic suspension (EDS) has a wide application prospect due to the advantages of no active control, self-stability and large gap, especially in the ultra-high speed maglev, rocket launching, Electromagnetic Aircraft Launching System and other high speed fields. SC coils and null-flux Ground Coils which are the primary and secondary windings respectively are applied in a typical EDS system, in that the null-flux ground coils provide levitation and guidance force. The calculation of electromagnetic forces that has been extensively studied by scholars all over the world is the basis of the design and optimization of the system. However, due to the limitation of complex structure, the calculation formula is often so complicated that the results have to be obtained by means of finite element method and numerical simulation. This paper aims to derive an analytical calculation of electromagnetic forces for SC EDS system based on some reasonable assumptions. The experimental data of MLX01 on the Japanese Yamanashi testline was used to verify the calculation model of this paper. In order to get a further validation, a small EDS rotary table was built based on null-flux ground coils and permanent magnets. The results of the experiment confirms the effectiveness of the proposed analytical calculation model.
Effects of Resistance Training on Oxidative Stress Markers and Muscle Damage in Spinal Cord Injured Rats

Simple Summary Spinal Cord Injury is a devastating condition that compromises the individual’s health, quality of life and functional independence. Rats submitted to Spinal Cord Injury were evaluated after four weeks of resistance training. Analyses of levels of muscle damage and oxidative stress surgery were performed. Resistance training demonstrated increase antioxidative activity while decreased oxidative damage in injured rats, in addition to having presented changes in the levels of muscle damage in that same group. The results highlight that resistance training promoted a decrease in oxidative stress and a significant response in muscle damage markers. Abstract Background: Spinal cord injury (SCI) is a condition that affects the central nervous system, is characterized by motor and sensory impairments, and impacts individuals’ lives. The objective of this study was to evaluate the effects of resistance training on oxidative stress and muscle damage in spinal cord injured rats. Methodology: Forty Wistar rats were selected and divided equally into five groups: Healthy Control (CON), Sham (SHAM) SCI Untrained group (SCI-U), SCI Trained group (SCI- T), SCI Active Trained group (SCI- AT). Animals in the trained groups were submitted to an incomplete SCI at T9. Thereafter, they performed a protocol of resistance training for four weeks. Results: Significant differences in muscle damage markers and oxidative stress in the trained groups, mainly in SCI- AT, were found. On the other hand, SCI- U group presented higher levels of oxidative stress and biomarkers of LDH and AST. Conclusion: The results highlight that resistance training promoted a decrease in oxidative stress and a significative response in muscle damage markers.
An application of artificial neural networks for autonomous ship navigation through a channel

A neural network model based on reinforcement learning is investigated for use as a shipboard autonomous channel navigator. The model used consists of two neuron-like elements. The basic learning scheme involves learning with a critic. The network consists of an adaptive critic element (ACE) and an adaptive search element (ASE). The ASE explores the channel region while the ACE criticizes the actions of the ASE and tries to predict failures of the ASE's attempt to navigate. The neural network model developed has been shown to be useful through software simulation with graphical feedback. A similar implementation could have applications in many electronic mapping systems utilizing vector information. The performance of such a system and its adaptability to new channels are investigated. <<ETX>>
Modeling Soil Detachment on Unpaved Road Surfaces on the Loess Plateau

Soil loss from unpaved rural roads contributes largely to watershed sediment yield. A road erosion model is therefore urgently needed to evaluate road erosion production. Field flow simulation experiments were conducted on unpaved loess roads under five flow rates and three slope gradients in order to quantify road surface hydraulics and develop soil detachment prediction models. The results showed that flow velocity was highly related to flow rate but generally independent of slope gradient. The hydraulic roughness of the road surface was much less than that of cropland and was influenced significantly by relatively intensive erosion on steep slopes. Easily obtainable parameters such as flow rate and slope gradient could be used to estimate soil detachment accurately. Furthermore, power functions of chosen hydraulic parameters, (i.e., shear stress, stream power, and unit stream power) could be used to predict detachment rates. Among these parameters, flow shear stress was the best predictor. A detachment prediction model similar to that used in the WEPP model was proposed. Corresponding to the excess shear stress model in WEPP, loess road surface soil erodibility is 0.0066 s m-1 and critical shear stress is 3.25 Pa.
Magneto Rheological for Motorcycle Suspension Using Bouc-Wen Model

This paper discusses the application of Magneto-rheological (MR) for motorcycle suspension. Previous studies on the usage of the MR fluids could enhance the performance and improved the vibration in systems such as buildings and vehicles. Therefore, MR motorcycle suspension system is proposed and investigated here by using Bouc-wen model. It is designed to bring comfort and safety to both rider and passenger also to improve the handling ability to the motorcycle. The effectiveness between the MR motorcycle suspension and the passive system is demonstrated by computer simulation. It is found that MR suspension system could eliminate external disturbance which obtain much better ride quality and handling performance to the motorcycle.
Application of Six Sigma Model in Library Management System for Process Improvement

Six Sigma is a set of strategies and principles for the process improvement and to produce quality products while reducing the waste substantially. Six Sigma is applied to produce near zero-defect products and services and it also ensures to meets all the quality and customer specifications. In this paper we will show how Six Sigma can be implemented in a college Library Management System for further improvement of the existing automated process. We will follow the basic Six Sigma methodologies (DMIAC) to identify the scopes of further improvement and to implement the new tool.
(−)-Methyl-Oleocanthal, a New Oleocanthal Metabolite Reduces LPS-Induced Inflammatory and Oxidative Response: Molecular Signaling Pathways and Histones Epigenetic Modulation

The antioxidant and anti-inflammatory responses of (−)-methyl-oleocanthal (met-OLE), a new metabolite of the extra virgin olive oil (EVOO) phenolic oleocanthal (OLE), were explored in lipopolysaccharide (LPS)-induced murine peritoneal macrophages. Possible signaling pathways and epigenetic modulation of histones were studied. Met-OLE inhibited LPS-induced intracellular reactive oxygen species (ROS) and nitrite (NO) production and decreased the overexpression of the pro-inflammatory enzymes COX-2, mPGES-1 and iNOS in murine macrophages. In addition, met-OLE was able to significantly decrease the activation of p38, JNK, and ERK mitogen-activated protein kinases (MAPKs) and blocked canonical and non-canonical inflammasome signaling pathways. On the contrary, met-OLE upregulated haem oxigenase 1 (HO-1) and nuclear factor (erythroid-derived 2)-like 2 (Nrf-2) expression in treated cells. Finally, met-OLE pretreated spleen cells counteracted LPS induction, preventing H3K18 acetylation or H3K9 and H3K27 demethylation. Overall, these results provide novel mechanistic insights into the beneficial effects of met-OLE regarding the regulation of the immune–inflammatory response through epigenetic changes in histone markers. This revealing evidence suggests that the methylated metabolite of OLE may contribute significantly to the beneficial effects that are associated with the secoiridoid-related compound and the usual consumption of EVOO.
Currency substitution as an automatic stabilizer

In the presence of frictions, the existing literature shows that currency substitution is detrimental for domestic aggregate stability. This paper singles out the role of currency substitution and shows that diversified currency holdings operate as an automatic stabilizer that mitigates belief-driven cyclical fluctuations in Farmer’s (1997) indeterminate monetary economy. When the foreign inflation rate is lower than the domestic inflation rate, the model’s steady state always displays saddle-path stability. Hence, equilibrium indeterminacy originally present in the domestic country is entirely removed in the presence of diversified currency holdings. When the foreign inflation rate is higher than the domestic inflation rate, then depending on the degrees of currency substitution and relative risk aversion, indeterminacy is either impossible or the requisite level of the foreign inflation rate for indeterminacy is too high to square with data. The stabilizing effect of diversified currency holdings on domestic aggregate stability is robust to whether domestic and foreign currencies display as Edgeworth substitutes or complements, or are additively separable in the household’s preferences.
Performance Analysis of Mobile Radio for Automatic Control in Smart Grids

In the context of a ―Smart Grid‖ research project, together with industrial partners, the OTH-Regensburg realized an intelligent medium-voltage grid in the local area. Goal was to improve the current voltage regulation and to counter the problems with inconsistent energy feed-in of decentralized renewable energy producers. In this paper we discuss the possibilities of using 3 rd generation (3G) cellular networks (UMTS) as basic technology to communicate the voltage-levels within a medium-voltage grid. We build an experimental hardware setup to generate data-traffic as specified for the smart grid. By analyzing the performance of 3G cellular networks in terms of transmission latency and rate of failure, we tried to evaluate the usability of this technology for such critical data exchange. Though mobile communication in its structure is not specified for the use of transmitting such infrastructure critical data, the results show a promising high reliability with low transmission latency. The experiments served just to test a fragment of the conditions of use in a real scenario. An expanded test scope is needed to further analyze the performance of mobile radio for automatic control in smart grids. In the end the results discussed in this paper led to a successful prototype of an intelligent medium-voltage grid with mobile radio as communication technology. (Abstract)
Impact of fixed choice design on blockmodeling outcomes

The main goal of blockmodeling is to reveal the essential structure of the network based on patterns of relationships. Social network data usually contain different types of errors and one of them is caused by some limitation of number of selected actors in the research design. The impact of fixed choice design compared to free choice design on the results of blockmodeling are studied through simulations. The resulting blockmodels are compared with two indices where position membership of actors and the structure of the blockmodels are examined. Limiting the number of actors that can be selected has an impact on delineated blockmodel structure where the deletion of ties has higher effect than addition of them.
Introduction to Neural Engineering for Motor Rehabilitation

The only book that covers in detail a broad range of cutting-edge topics within motor rehabilitation technologyNeural engineering is a discipline that uses engineering techniques to understand, repair, replace, enhance, or treat diseases of neural systems. This book describes state-of-the-art methods within this field, from brain-computer interfaces to spinal and cortical plasticity. Touching on electrode design, signal processing, the neurophysiology of movement, robotics, and much more, this innovative book presents the latest information for readers working in biomedical engineering.Each section of Introduction to Neural Engineering for Motor Rehabilitation begins with an overview of techniques before moving on to provide information on the most recent findings. Topics include:INJURIES OF THE NERVOUS SYSTEMincluding diseases and injuries of the central nervous system leading to sensory-motor impairment; peripheral and spinal plasticity after nerve injuries; and motor control modules of human movement in health and diseaseSIGNAL DETECTION AND CONDITIONINGincluding progress in peripheral neural interfaces; multi-modal, multi-site neuronal recordings for brain research; methods for non-invasive electroencephalograph detection; wavelet denoising and conditioning of neural recordingsFUNCTION REPLACEMENT (Prostheses and Orthosis)including an introduction to upper limb prosthetics; controlling prostheses using peripheral nerve stimulation invasive interfaces for amputees; and exoskeletal robotics for functional substitutionFUNCTION RESTORATIONincluding methods for movement restoration; advanced user interfaces for upper limb functional electrical stimulation; and selectivity of peripheral neural interfacesREHABILITATION THROUGH NEUROMODULATIONincluding brain-computer interface applied to motor recovery after brain injury; functional electrical therapy of upper extremities; and robotic assisted neurorehabilitationIntroduction to Neural Engineering for Motor Rehabilitation is an important textbook and reference for graduate students and researchers in the fields of biomedical and neural engineering.
Effectiveness Observed by Passengers Taking the Taiwan High Speed Railway Service: Especially their Observation of Overall Quality and Satisfaction

Abstract. This paper is regarding research concerning Taiwan’s High Speed Railway (THSR) service; its quality and performance. Most of the passengers preferred this transportation when compared with other trains because it is clean, convenient, comfortable, and saves time, while offering high quality service. The paper has 5 service quality dimensions. It includes 28 items in the form of a questionnaire for passengers which focused on the Hsichu station. The first dimension concerns boarding the train; the second is inside the train station; the third is on the platform; the fourth is riding the train, and the last one is leaving the THSR station. The analysis shows the Strengths, Weaknesses, Opportunities, Threats (SWOT) and the Importance Performance Analysis (IPA). The research is in regard to passenger’s satisfaction with the quality of service and customer satisfaction.
Early Diagnosis of Alzheimer's Disease Using Cerebral Catheter Angiogram Neuroimaging: A Novel Model Based on Deep Learning Approaches

Neuroimaging refers to the techniques that provide efficient information about the neural structure of the human brain, which is utilized for diagnosis, treatment, and scientific research. The problem of classifying neuroimages is one of the most important steps that are needed by medical staff to diagnose their patients early by investigating the indicators of different neuroimaging types. Early diagnosis of Alzheimer’s disease is of great importance in preventing the deterioration of the patient’s situation. In this research, a novel approach was devised based on a digital subtracted angiogram scan that provides sufficient features of a new biomarker cerebral blood flow. The used dataset was acquired from the database of K.A. U.H hospital and contains digital subtracted angiograms of participants who were diagnosed with Alzheimer’s disease, besides samples of normal controls. Since each scan included multiple frames for the left and right ICA’s, pre-processing steps were applied to make the dataset prepared for the next stages of feature extraction and classification. The multiple frames of scans transformed from real space into DCT space and averaged to remove noises. Then, the averaged image was transformed back to the real space, and both sides filtered with Meijering and concatenated in a single image. The proposed model extracts the features using different pre-trained models: InceptionV3 and DenseNet201. Then, the PCA method was utilized to select the features with 0.99 explained variance ratio, where the combination of selected features from both pre-trained models is fed into machine learning classifiers. Overall, the obtained experimental results are at least as good as other state-of-the-art approaches in the literature and more efficient according to the recent medical standards with a 99.14% level of accuracy, considering the difference in dataset samples and the used cerebral blood flow biomarker.
New 2,5-bis(2-ethylhexyl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione-2,2’-bipyridine-based co-polymer, synthesis, photophysical properties and response to metal cations

A new co-polymer based on fragments of 2-(2-pyridyl)monoazatriphenylene and 2,5-bis (2-ethylhexyl)-3,6-di(thiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione was prepared by using the Sonogashira reaction. The photophysical properties of the polymer were studied. The presence of a strong bathochromic shift of the absorption and emission maxima in comparison with the previously described monomer units is shown. The polymer exhibits an intense “turn-off” response toward Cu2+ cations.
Reduced-complexity Capon for direction of arrival estimation in a monostatic multiple-input multiple-output radar

In this study, the authors consider the direction of arrival (DOA) estimation problem for a monostatic multiple-input multiple-output (MIMO) radar. A DOA estimation algorithm for the monostatic MIMO radar using Capon and the reduced-dimension transformation is proposed. The proposed algorithm can achieve lower computational complexity than the Capon algorithm, while not debasing the performance of the angle estimation. The proposed algorithm has better angle estimation performance than the Capon algorithm and estimation of signal parameters via rotational invariance techniques algorithm, and it has close angle estimation performance to the CrameŕRao bound (CRB). The variance of the estimation error and the CRB of the DOA estimation are derived. Simulation results present the usefulness of the proposed algorithm.
Technopreneurial Intentions: The Effect of Innate Innovativeness and Academic Self-Efficacy

Several factors can affect students’ intention to start a new technology-based venture (technopreneurial intentions). Understanding these factors is important when developing technical educational programs. This study investigates the effect of innate innovativeness and academic self-efficacy on technopreneurial self-efficacy and the forming of technopreneurial intentions. It does this by developing a conceptual model that relates technopreneurial intentions, technopreneurial self-efficacy, academic self-efficacy, and innate innovativeness. The data was collected from 378 undergraduate engineering students enrolled in a Jordanian university with a self-administered questionnaire survey. The results of the structural equation modeling (SEM) using AMOS showed that technopreneurial self-efficacy had a positive and significant impact on technopreneurial intentions. Academic self-efficacy had both a direct and indirect positive effect on technopreneurial intention. The indirect effect occurred through increased technopreneurial self-efficacy. Innate innovativeness had a direct effect on technopreneurial intentions, but it did not have a significant indirect effect through technopreneurship self-efficacy as was initially hypothesized. The findings suggest that those who show interest in starting a new technology-based venture have a strong belief in their abilities to perform the technological and entrepreneurial tasks needed, are confident about their ability to acquire the academic technical skills required, and have the inner motivation to seek what is technologically new and different.
Influence of gap length on the gas‐puff z‐pinch plasma produced by an inductive pulsed power system

In this study, an argon gas‐puff z‐pinch plasma was produced by an inductive pulsed power system. The gap length dependence of plasma characteristics such as the pinch plasma behavior, soft x‐ray emissions, and spatial distribution of hot spots, was investigated. The soft x‐ray output decreased with gap length, and hot spots generated by sausage instability were distributed along the z‐axis for shorter delay times of the discharge onset. However, hot spots were distributed in the center of the gap space with increased delay times, regardless of the gap length, and the number of hot spots decreased. © 2003 Wiley Periodicals, Inc. Electr Eng Jpn, 144(4): 1–8, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10126
A 103-dB SFDR Calibration-Free Oversampled SAR ADC With Mismatch Error Shaping and Pre-Comparison Techniques

This work presents a 14-bit oversampled successive-approximation-register (SAR) analog-to-digital converter (ADC) with mismatch error shaping (MES) and pre-comparison techniques. A pre-comparison technique is proposed to solve the over-range problem caused by MES. With MES and pre-comparison, the digital-to-analog converter (DAC) mismatch error can be first-order shaped, while a full input range is maintained. Besides, data-driven noise reduction and chopping techniques are combined to reduce the comparator noise efficiently. The prototype in 65-nm CMOS achieves 84.5-dB signal-to-noise-and-distortion ratio (SNDR) and 103-dB spurious-free dynamic range (SFDR) in a 4-kHz bandwidth, with a power consumption of 0.98 <inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> from a single 0.8-V supply and an area of 0.033 mm<sup>2</sup>, resulting in a Schreier figure of merit (FoM) of 180.6 dB and a Walden FoM of 8.9 fJ/conversion-step, respectively. Among ADCs with above 100-dB SFDR, this is the smallest design without calibration and the only sub-<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> and sub-1-V design. These features make it suitable for high-resolution and low-cost applications.
Behavior of the Embedded Phase in a Shock-Driven Two-Phase Flow

This thesis presents an experimental study of droplet acceleration in a shock-driven two-phase flow. The study serves to identify the characteristics of the boundary layer growth behind a normal moving shock wave in a shock tunnel. Liquid propylene glycol droplets are pre-mixed with air, and slowly injected into the test section of the shock tunnel. Two test sections are evaluated during the course of this study. Each test section is constructed of square, transparent polycarbonate with internal cross section of 7.62 cm. The first test section contains features on the upper and lower surfaces of the test section, consistent with the holes used for the injection system during earlier Richtmyer-Meshkov Instability studies. The second test section has no surface features interfering with the flow, with smooth interfaces. The quiescent air seeded with propylene glycol droplets (diameter 0.5-3μm) is impulsively accelerated with a planar shock wave. A cross-section of the flow is illuminated with multiple pulses from Nd:YAG lasers, producing time-resolved visualizations of the seeded volume. The illuminated images are analyzed to quantify droplet velocity and vorticity from