Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling of an SMA actuator based on the Liang and Rogers model

The purpose of this study is to develop a complete mathematical model of a thick shape memory alloys (SMA) actuator based on the Liang and Rogers model. Due to hysteresis and significant nonlinearities in the behavior of shape memory alloy actuators, the modeling of SMA actuators has been a great challenge in recent years, which limit the application of these actuators. In this paper, a new model is used to represent the major and minor hysteresis loops of SMA actuator based on the Liang and Rogers model. The modified Liang and Rogers model of SMA wire actuated by an electric current is derived and several experiments are used to validate the model and to identify the parameters. A key feature of the proposed model is to predict the martensite starting temperature of minor loops. This model can be used to develop a position control system for the SMA actuator. Simulation results for the model are found to be in good agreement with experimental data.
Optimal Data Selection Rule Mining for Transformer Condition Assessment

The condition of the transformer can be accurately assessed based on dissolved gas online monitoring and analysis technology. With the widespread use of Dissolved Gas Analysis (DGA) technology, a large amount of dissolved gas time series data is obtained and forms DGA big data, which brings challenges to the data selection process of traditional condition assessment methods. Inaccurate results might be generated by selecting excessive or insufficient data from a long-span dissolved gas time series. The shorter dissolved gas time series fails to fully characterize the operation law of transformers, and the longer dissolved gas time series contains redundant information that results in inaccurate analysis models and excessive calculation consumption. This paper attempts to mine the optimal data selection rule of long-span dissolved gas time series for more accurate and efficient analysis. In this paper, C-C method was employed to calculate the phase space parameters of the time series. By analyzing the convergence of the correlation integral, the boundary conditions that maintain the time series phase space stability were revealed, and so was the relationship between the optimal length and the embedding dimension. The real cases show that the optimal data set provides the same accuracy and significantly improves the computation speed by 113.54 times. The optimal data selection rule eliminates redundant information in the long-span dissolved gas time series and retains the “optimal data”, which not only preserves the characteristics of the original data, but also improves the computation speed of transformer condition assessment.
Reconstruction of intestinal microecology of type 2 diabetes by fecal microbiota transplantation: Why and how

Type 2 diabetes (T2D) is a chronic metabolic disease characterized by hyperglycemia due to insulin resistance. Mounting evidence has correlated T2D to alterations in the composition of gut microbiota. Accordingly, targeting the gut microbiota has become an emerging strategy for T2D management. The aim of this article is to get a better insight into the rationale for targeting gut microbiota in T2D treatment. Thus, we herein reviewed the change of gut microbiota composition in T2D, factors shaping gut microbiota, and potential mechanisms behind the contribution of gut microbiota to T2D pathogenesis. At present, it has become possible to use intestinal microorganism capsules, bacteria liquid, and other preparations to carry out fecal microbiota transplantation for the treatment and intervention of T2D with insulin resistance and immune-mediated type 1 diabetes.
Fuzzy logic based automatic diagnosis of power apparatus by infrared imaging

This paper describes a thermographic application system for the electrical power industry. The infrared imager has a range from 40 degrees C to 950 degrees C and maximum resolution down to 0.01 degrees C. A new algorithm for image matching has been devised to match slightly different infrared images of the same object by adaptively adjusting the five parameters, namely x- and y- translation, rotation, x- and y- scaling respectively. The diagnosis is automatically executed by a fuzzy logic-based expert system which extracts the major features within the thermograms and recommends appropriate actions for maintenance. <<ETX>>
Lean Cooperation: A Framework

While both concepts lean management and cooperation not only have received considerable attention in management literature but also have been combined e.g. in the field of supply chain literature, a comprehensive definition of lean cooperation is still missing. Whereas lean supply chain cooperation is only one aspect in a growing field, we aim at considering further forms of cooperation coming up and having consequences for the management of lean initiatives. Based on an extensive literature review, we develop a framework addressing lean cooperation and thus, allowing for systematization. Furthermore we find out that current literature mainly focusses on lean cooperation along the supply chain. This paper presents other forms of cooperation focused on lean management. With a case study of lean cooperation within an industry cluster we will show the potential of knowledge-transfer on lean practices for individual firm´s implementation. This paper provides a definition and a research framework for lean cooperation. Insights will be useful for further analysis of lean management roll-out within outlined forms of cooperation. Practitioners will learn about benefits and restrictions of lean cooperation. The paper also is of value for researchers giving a structured outline of lean cooperation and stating fields for further research.
Automatic Transcription of Piano Music Using Audio-Vision Fusion

Over the last decade many sophisticated and application-specific methods have been proposed for transcription of polyphonic music. However, the performance seems to have reached a limit. This paper describes a high-performance piano transcription system with two main contributions. Firstly, a new onset detection method is proposed using a specific energy envelope matched filter, which has been proved very suitable for piano music. Secondly, a computer-vision method is proposed to enhance audio-only piano music transcription, using the recognition of the player's hands on the piano keyboard. We carried out comparable experiments respectively for onset detection and overall system based on the MAPS database and the video database. The results were compared with the best piano transcription system in MIREX 2008, which still kept the best performance in piano subset till MIREX 2012. The results show that the system outperforms the state-of-art method substantially.
Full-Duplex DF Relaying With Parallel Hybrid FSO/RF Transmissions

The ever-increasing demands for higher data rates in telecommunications networks, along with the significant benefits offered by wireless communications, have pushed the technological developments to new frontiers. Free-space optical (FSO) communications are among the technologies that can address these emerging demands, offering large and unregulated bandwidth. In addition, recent advances in radio frequency (RF) systems have enabled the development of in-band full-duplex (FD) radios with the employment of advanced self-interference cancelation techniques. Therefore, in this paper we study a robust FD relaying system comprised of parallel hybrid FSO/RF communication links, where the coordination of transmissions between the FSO/RF subsystems is carried out by the hard-switching protocol. The operation of the RF links is impaired by Nakagami- $m$ fading, the residual self-interference due to the FD relaying operation, and the in-phase and quadrature-phase imbalance effect due to imperfect RF front-ends. As far as the FSO links are concerned, we consider the influence of the joint effects of atmospheric turbulence, beam wander and pointing errors. We first derive analytical closed-form expressions for the outage probability of both subsystems as well as for the overall FD relaying hybrid system. Then, asymptotic expressions are extracted for the outage performance in the high signal-to-noise ratio regime. The achievable outage diversity orders of both FSO and RF subsystems are determined, which provide significant insight into the design of such hybrid systems in a wide variety of operating conditions. Finally, the numerical results are presented using the derived outcomes, and significant conclusions are drawn about FD relaying hybrid systems.
International education hubs : student, talent, knowledge-innovation models

Dedication. - 1. Introduction Jane Knight. - 2. Understanding Education Hubs within the Context of Crossborder Education Jane Knight. - 3. An Analytical Framework for Education Hubs: Student, Talent, Knowledge-Innovation Jane Knight and Jack Lee. - 4. The Evolution of Qatar as an Education Hub: Moving to a Knowledge Economy Arwa Ibnouf, Lois Dou and Jane Knight. - 5. United Arab Emirates Education Hub: A Decade of Development Warren Halsey Fox and Sabha Al Shamisi. - 6. Hong Kong: The Quest for Regional Education Hub Status Ka Ho Mok and Peter Bodycott. - 7. Malaysia: Becoming an Education Hub to Serve National Development Mohd Ismail Abd Aziz and Doria Abdullah. - 8. Singapore: Building a Knowledge and Education Hub Ravinder Sidhu, Ho Kong-Chong and Brenda Yeoh. - 9. Botswana: Africa's First Education Hub Bridget Poppy John, David Wilmoth and Brian Mokopakgosi. - 10. Emerging Education Hubs: Korea, Sri Lanka, Mauritius, Bahrain Lois Dou and Jane Knight. - 11. Comparative Analysis of Education Hubs Jane Knight. - 12. Issues, Indicators, and Reflections Jane Knight. - Bibliography. - Index.
Utilization of Chebyshev collocation approach for differential, differential-difference and integro-differential equations

Abstract Numerical solutions to differential and integral equations have been a very active field of research. The necessary tools to solving differential equations can add much fuel for acceleration of scientific development. Therefore, it is quite challenging for scientists, especially mathematicians, to work on the solution methodologies for differential equations. In this study, we have discussed the use of Chebyshev collocation method for solving a large variety of problems including various types of integral equations, integro-differential equations, and differential-difference equations. The method under consideration relies on a trial solution which is a linear combination of basic functions derived from Chebyshev polynomials. The trial solution is then used to obtain a residue function whose vanishing weighted residual can be used to obtain a system of algebraic equations which gives the values of constants used in the trial solution. Plugging the constants back into the trial solution, we obtain an approximate solution to the problem at hand. We have provided the comparison between exact and approximate solutions for different problems and found an exceptionally good agreement in results. The comparison has been provided through plots and tables to portray the accurateness of Chebyshev collocation method. The behaviour of the solutions is also displayed with the help of the graphs.
Bistatic spaceborne SAR data processing based on LBF

Bistatic configuration is an attractive concept for synthetic aperture radar (SAR) missions, which benefit from use of separated transmitter and receiver flying on different platforms. The processing of radar data stands out as a fundamental issue to facilitate bistatic SAR research and application in remote sensing. A bistatic processing algorithm based on Loffeld's bistatic formula (LBF) is proposed. The approach involved bistatic term compensation and quasi monostatic processing, and the latter part derived from a chirp z transform algorithm for monostatic case. As steps to a bistatic SAR processor for space configuration, this paper presents an approximation of transmitter/receiver slat range depending on individual incidence angle, and modifies range CZT parameter and azimuth compression operator. First results of this algorithm on simulated raw data are included.
THE INFLUENCE OF THE CEO POPULARITY ON PERFORMANCE OF BANKING COMPANIES AT THE EARLIER STAGES OF COVID-19

This study aims to obtain empirical evidence about the influence of CEO popularity on banking performance at the earlier stages of the COVID-19 pandemic in Indonesia. The CEO popularity significantly improve based on their achievements in the public mass media. The study sample consisted of 108 banking companies listed on the Indonesia Stock Exchange in Q1 - Q3 2020. Panel data regression with a common influence model approach was used for analysis, while the company performance was measured using Tobin's Q. The result showed that CEO popularity in the banking sector positively affects company performance. Therefore, hiring popular CEO helps obtain better company performance.
The Kinematics of Bend-Induced Stirring in Micro-Conduits

The absence of turbulence and the difficulty associated with introducing moving stirrers into microfluidic systems make the mixing problem in microdevices challenging. We studied theoretically steady, laminar, incompressible flow through a sequence of conduits with rectangular cross-sections aligned to form 90° with each other. The feasibility of taking advantage of bend-induced vortices to stir the fluid and enhance the mixing process was evaluated. Since at very low Reynolds numbers the bend-induced vortices decay rapidly, it was necessary to utilize a large number of bends to achieve the desired effects. Since it is not practical to directly simulate the flow through a large number of bends, we borrowed Jones et. al.’s (1989) idea of constructing a two-dimensional map to project fluid particles from a cross-section upstream of the bend to a cross-section downstream of the bend. This map was then applied repetitively to trace particle trajectories in various bend arrangements. Under certain conditions, chaotic advection was observed.
Practical Intrusion Detection Handbook

From the Publisher: The definitive guide to understanding, selecting, and deploying intrusion detection in the enterprise! Product selection, planning, and operations Filled with real-life cases and stories of intrusion detection systems in action Covers host-based and network-based intrusion detection Foreword by Dorothy Denning, author of Cryptography and Data Security and Information Warfare and Security Technical Edit by Ira Winkler, author of Corporate Espionage In The Practical Intrusion Detection Handbook, one of the field's leading experts shows exactly how to detect, deter, and respond to security threats using intrusion detection systems. Using real-world case studies and practical checklists, Paul E. Proctor shows what intrusion detection software can achieve, and how to integrate it into a comprehensive strategy for protecting information and e-commerce assets. No other guide to intrusion detection offers all this: Practical coverage of host-based, network-based, and hybrid solutions Detailed selection criteria and sample RFPs Key factors associated with successful deployment Intrusion detection in action: response, surveillance, damage assessment, data forensics, and beyond Six myths of intrusion detection  and the realities Whether you're a senior IT decision-maker, system administrator, or infosecurity specialist, intrusion detection is a key weapon in your security arsenal. Now, there's a start-to-finish guide to making the most of it: The Practical Intrusion Detection Handbook by Paul E. Proctor. "Intrusion detection has gone from a theoretical concept to a practical solution, from a research dream to a major product area, from an idea worthy of study to a key element of the national plan for cyber defense. Nobody brought that about more than Paul Proctor. Paul brings his considerable knowledge and experience with commercial intrusion detection products to this first-of-a-kind book. " From the Foreword by Dorothy Denning
Insights gained from a TRMM microwave and infrared Sea Surface Temperature comparison

A detailed comparison of Sea Surface Temperatures obtained from one year of infrared and microwave satellite observations was performed on data from the VIRS and TMI sensors, both onboard the Tropical Rainfall Measurement Mission (TRMM). Using VIRS radiances, we developed daily maps of infrared SSTs and compared them to microwave SST daily maps derived from TMI. The intercomparison aims at identifying and minimizing errors in each dataset. Results from the analysis of the correlation of SST differences and possible sources of error (i.e., high winds, diurnal variations of skin layer temperature, atmospheric water vapor, undetected clouds, satellite maneuvers and calibration errors) are discussed. The intercomparison of four tested IR algorithms and the TMI SSTs facilitates the choice of the optimal IR algorithm for use in future data processing. We investigated how co-located MW observations of water vapor help IR SST retrievals by improving the cloud detection algorithm. In addition, the MW retrievals can benefit from the comparison with IR observations, which highlights the effects of land contamination in the TMI retrievals.
Low-energy e-beam proximity projection lithography

Low energy e-beam proximity projection lithography is proposed for integrated circuit lithography for minimum feature sizes <EQ 0.1 micrometers . This new e-beam lithography is similar to optical projection lithography except that photons are replaced by low energy electrons. The low e-beam energy permits the use of single crystal 0.5 micrometers thick silicon membrane masks without an absorbing metal layer of high atomic number. The membrane mask is thick enough for good heat conduction and thin enough for feature sizes <EQ 0.1 micrometers . The proposed system does not suffer form space charge or proximity effects and is fundamentally a low voltage and low power density lithography with respect to both the mask and the wafer. We predict a throughput of 30 12 inch wafers per hour. Furthermore, the cost of this tool is predicted to be considerably less than today's advanced optical steppers.
A 4-μW Bandwidth/Power Scalable Delta–Sigma Modulator Based on Swing-Enhanced Floating Inverter Amplifiers

This article presents a fully dynamic scalable switched-capacitor delta–sigma modulator that achieves a 94.1-dB dynamic range (DR). Power-and- bandwidth scalability by only changing the clock frequency is achieved using a capacitively biased and swing-enhanced floating inverter operational transconductance amplifier (OTA). Fabricated in a 180-nm CMOS process, the prototype achieves an signal-to-noise-and-distortion ratio (SNDR) of >87 dB across <inline-formula> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> scaling from 100 to 400 kHz of the sampling frequency <inline-formula> <tex-math notation="LaTeX">$f_{\mathbf {S}}$ </tex-math></inline-formula>. At 200-kHz <inline-formula> <tex-math notation="LaTeX">$f_{\mathbf {S}}$ </tex-math></inline-formula>, it achieves an SNDR/DR of 89.3/94.1 dB while consuming <inline-formula> <tex-math notation="LaTeX">$4 \mu \text{W}$ </tex-math></inline-formula>, leading to a DR-based Schreier figure of merit (FoM) of 177.1 dB.
Velocity based semi‐active turbo‐Lyapunov control algorithms for seismically excited nonlinear smart structures

This paper presents a novel turbo‐Lyapunov control strategy for the semi‐active control of a nonlinear highway bridge subjected to earthquake ground motions. An optimal control signal has been found to be strongly dependent on the velocity across a magnetorheological (MR) damper. A turbo‐Lyapunov control algorithm that utilizes the relationship between absolute velocity of the damper and control signal based on the traditional Lyapunov control algorithm has been developed. In this approach, the control signal is calculated using an integrated traditional Lyapunov function and a turbo‐function. This turbo‐function adds or subtracts additional voltage depending on the change in the absolute velocity across an MR damper. The performance of the proposed controller has been investigated in reducing response quantities of the highway bridge benchmark model. The results show that the proposed turbo‐Lyapunov control strategy is quite competitive with respect to numerous other control approaches in reducing response quantities of the benchmark bridge model. Copyright © 2012 John Wiley & Sons, Ltd.
Classification and Characteristics of Mesenchymal Stem Cells and Its Potential Therapeutic Mechanisms and Applications against Ischemic Stroke

Ischemic stroke is a serious cerebral disease that often induces death and long-term disability. As a currently available therapy for recanalization after ischemic stroke, thrombolysis, including intravenous thrombolysis and endovascular therapy, still cannot be applicable to all patients due to the narrow time window. Mesenchymal stem cell (MSC) transplantation therapy, which can trigger neuronal regeneration and repair, has been considered as a significant advance in treatment of ischemic stroke. MSC transplantation therapy has exhibited its potential to improve the neurological function in ischemic stroke. Our review describes the current progress and future perspective of MSC transplantation therapy in ischemic stroke treatment, including cell types, transplantation approaches, therapeutic mechanisms, and preliminary clinical trials of MSC transplantation, for providing us an update role of MSC transplantation in ischemic stroke treatment.
Principal component regression of carcass traits in meat line funaab alpha chicken genotype

This study aimed to assess the relationship among carcass traits of meat line FUNAAB Alpha chicken genotype, to identify the components that defined bled weight in them using multivariate principal component regression. A total of 14 different carcass traits from sixty-eight birds were recorded and subjected to one-way analysis of variance to vet for sex effect. Phenotypic relationships among the carcass traits were also established to pave way for the principal component analysis. The results reveal significant effects between the traits measured. The male significantly (P<0.05) had greater mean values for the traits measured. Correlations among the considered carcass traits were found to be positive and significant ranging from r = 0.406 (LrWt) - 0.981 (EdWt) for the female chicken; r = 0.330 (Head Wt) - 0.978 (BdWt) for the male chicken. The extracted components PC1 to PC7 contributed 95.66% with PC1 accounting for 68.68% of the variability in the original parameters. Communality estimates varied from 0.466 (thigh weight) to 0.983 (liver weight). In the principal component regression models, Eviscerated weight accounted for 95% of the variation observed in bled weight. The use of PC1 as a single predictor, explained 96.4% of the variability, whilst combining PC1 and PC4 showed improvements in the variance explained (R2 = 96.7%) with a lower Mallow's cp (5.31). Using the principal components scores from the chicken morphometric traits was more appropriate than using the original traits in bled weight prediction.