Miracle-dz/UniFAR-FTUs huggingface dataset:
A Distributed Method for Self-Calibration of Magnetoresistive Angular Position Sensor within a Servo System

Magnetoresistive angle position sensors are, beside Hall effect sensors, especially suitable for usage within servo systems due to their reliability, longevity, and resilience to unfavorable environmental conditions. The proposed distributed method for self-calibration of magnetoresistive angular position sensor uses the data collected during the highest allowed speed shaft movement for the identification of the measurement process model parameters. Data acquisition and initial data processing have been realized as a part of the control process of the servo system, whereas the identification of the model parameters is a service of an application server. The method of minimizing of the sum of algebraic distances of the sensor readings and the parametrized model is employed for the identification of parameters of linear compensation, whereas the average shaft rotation speed has been used as a high precision reference for the identification of parameters of harmonic compensation. The proposed method, in addition to a fast convergence, provides for the increase in measurement accuracy for an order of magnitude. Experimentally obtained measurement uncertainty was better than 0.5°, with the residual variance less than 0.02°, comparable to the sensor resolution.
NASA: NVM-Assisted Secure Deletion for Flash Memory

Secure deletion in flash-based storage is crucial for data security. However, existing secure deletion schemes for flash memory suffer from performance degradation and reliability issues and cannot provide secure deletion guarantees. Although emerging nonvolatile memory (NVM) allows in-place updates and provides high performance, it is unable to fully replace flash memory and, thus, cannot solve the secure deletion problem. In this article, we propose NVM-assisted secure deletion scheme for flash memory (NASA), a stale-free storage system that combines NVM and flash memory to provide immediate secure deletion without significant performance degradation in SSDs. NASA uses block erasure to provide secure deletion guarantees for flash memory and exploits NVM to conceal time-consuming erasure operations. We demonstrate that unless the unique characteristics of NVM are considered, schemes that merely implement existing approaches to secure deletion will end up with stale data replicas within their storage media. Moreover, we evaluate NASA with different real-world workloads and demonstrate that NASA increases the average latency by 0.01% compared to LRU and decreases 2.1% average latency over the FIFO caching policy. NASA is a novel storage system that provides strong secure deletion guarantees with high performance.
An Analytical Method for 3-D Sound Source Localization Based on a Five-Element Microphone Array

An analytical method for 3-D sound source localization based on a five-element microphone array is proposed in this work. With four time-difference-of-arrival (TDOA) values, the proposed method realizes the sound source localization by analytical solution. A new five-element microphone array configuration (which is characterized in that four microphones are in the same plane and at four vertices of a concave quadrilateral respectively, while the fifth microphone is out of the plane) is analyzed and studied. It is proven that with the proposed configuration, the five-element microphone array can obtain a unique and analytical solution. To investigate the effectiveness and the localization performance of the proposed method, a practical five-element microphone array is developed and 3-D sound source localization experiments are carried out. The TDOA values are obtained by the generalized cross correlation (GCC) method based on the phase transform (PHAT). The experimental results show that the proposed method is an effective near-field localization method. The localization performance of the practical five-element microphone array is satisfactory. Compared with the conventional methods, the proposed method realizes the 3-D localization by analytical solution and has the advantages of simple construction and lower computational complexity.
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method

Due to the rapid growth in IT technology, digital data have increased availability, creating novel security threats that need immediate attention. An intrusion detection system (IDS) is the most promising solution for preventing malicious intrusions and tracing suspicious network behavioral patterns. Machine learning (ML) methods are widely used in IDS. Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. In the initial phase, the proposed HNIDS utilizes hybrid EGA-PSO methods to enhance the minor data samples and thus produce a balanced data set to learn the sample attributes of small samples more accurately. In the proposed HNIDS, a PSO method improves the vector. GA is enhanced by adding a multi-objective function, which selects the best features and achieves improved fitness outcomes to explore the essential features and helps minimize dimensions, enhance the true positive rate (TPR), and lower the false positive rate (FPR). In the next phase, an IRF eliminates the less significant attributes, incorporates a list of decision trees across each iterative process, supervises the classifier’s performance, and prevents overfitting issues. The performance of the proposed method and existing ML methods are tested using the benchmark datasets NSL-KDD. The experimental findings demonstrated that the proposed HNIDS method achieves an accuracy of 98.979% on BCC and 88.149% on MCC for the NSL-KDD dataset, which is far better than the other ML methods i.e., SVM, RF, LR, NB, LDA, and CART.
Sensing with terahertz radiation: a review of recent progress

This paper aims to provide a technical insight into a selection of recent developments and applications involving terahertz sensing technology. ,Following an introduction, the first part of this paper considers a selection of research activities involving terahertz radiation sources and detectors. The second part seeks to illustrate how the technology is exerting a commercial impact and discusses a number of product developments and applications. ,Terahertz sensing is a rapidly developing field and a strong body of research seeks to develop sources and detectors with enhanced features which often exploit novel materials, phenomena and technologies. Commercialisation is gathering pace, and a growing number of companies are producing terahertz sensing and imaging products which are finding a diversity of applications. ,This provides details of recent research, product developments and applications involving terahertz sensing technology.
Sentiment Analysis of Texts on Public Health Emergencies Based on Social Media Data Mining

Background Since the COVID-19 pandemic, social media has become an important arena for the public to transmit and exchange messages, feelings, opinions, and information about the epidemic. In the era of social media, many UGC contents from self-media and various information about the epidemic on social media have strong emotional colors. These contents are not only rich in resources for text sentiment analysis but also reveal the laws and characteristics of the evolution of users' emotional tendencies in public health emergencies. It even ties together the interaction between media content and society. Objective As the Sina Weibo platform's characteristics of communication are real-time, open, and “many-to-many,” the objective of this study is to collect Weibo-blog contents tagged with the outbreak of COVID-19 in a certain metropolis in China and analyze the emotional evolution situation of Weibo-blogs of the unexpected public health emergency involved. This will provide a dynamic understanding of the mechanisms underlying the evolution of emotional conditions in the context of public health emergencies. Methods This paper uses a Python crawler, the SnowNLP sentiment analysis model, and correlation analysis to calculate the emotional tendencies of the event “Covid-19 outbreak in a Chinese metropolis” on the Sina Weibo platform. The study was carried out in terms of the evolutionary stages of the event and the factors which induce it. Results This paper revealed characteristics of time-varying laws and dynamic propagation of users' emotional evolution in public health emergencies. (1) This study refers to the life cycle model of COVID-19, combined with the statistics of the time series of the quantities of Weibo-blog posting, and divides the law of the quantities of Weibo-blog posting changing with the event into three stages: outbreak period, stalemate period, and resolution period. (2) Users' emotional tendencies are changeable and unstable which are easily induced by various factors. (3) There is a significant positive correlation between the reported confirmed cases and the quantities of Weibo-blog posts. (4) Individual emotional tendencies will have a positive changing trend with the public's average emotional tendencies after the event occurs. (5) There is no correlation between reposts, comments, and Weibo-blog emotional tendencies. Conclusion The research found that, given staged evolution and repeated fluctuations of emotional tendencies, relevant departments should effectively use this law and set up different response plans according to different stages. In addition, what is highly coupled with users' emotional tendencies is not only the information about the virus but more large-scale infected by different intensities of emotions.
An HFman Probe-Based Multiplex Reverse Transcription Loop-Mediated Isothermal Amplification Assay for Simultaneous Detection of Hantaan and Seoul Viruses

Hantaviruses are zoonotic pathogens that are widely distributed worldwide. Hantaan virus (HTNV) and Seoul virus (SEOV) are two most common hantaviruses that infect humans and cause hemorrhagic fever with renal syndrome (HFRS). Rapid and sensitive detection of HTNV and SEOV are crucial for surveillance, clinical treatment and management of HFRS. This study aimed to develop a rapid HFman probe-based mulstiplex reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay to simultaneously detect HTNV and SEOV. A novel multiplex RT-LAMP assay was developed, and 46 serum samples obtained from clinically suspected patients were used for evaluation. The novel RT-LAMP assay can detect as low as 3 copies/reaction of hantaviruses with a detection limit of 41 and 73 copies per reaction for HTNV and SEOV, respectively. A clinical evaluation showed that the consistencies of the multiplex RT-LAMP with RT-qPCR assay were 100% and 97.8% for HTNV and SEOV, respectively. In view of the high prevalence of HTNV and SEOV in rural areas with high rodent density, a colorimetric visual determination method was also developed for point-of-care testing (POCT) for the diagnosis of the two viruses. The novel multiplex RT-LAMP assay is a sensitive, specific, and efficient method for simultaneously detecting HTNV and SEOV.
Speed Control of Switched Reluctance Motor Based on Regulation Region of Switching Angle

This paper studies the speed control strategy of a switched reluctance motor based on angle-position control (APC). The switched reluctance motor has three control parameters: turn-on angle, turn-off angle and voltage PWM duty cycle. This paper studies the function of the three parameters and designs the control algorithms of the parameters, respectively, which can reduce the coupling degree, simplify the control process, and realize the optimal control of the switched reluctance motor. By studying the nonlinear characteristics of the switched reluctance motor, the optimal current waveform in the effective working range of the inductor is obtained, and then a control strategy of the turn-on angle is designed to realize the ideal winding current waveform. According to the torque characteristics of the motor, taking the coincidence of the freewheeling zero point and the position angle at the end of the maximum inductance interval as the control target, a control strategy for the turn-off angle that makes full use of the effective inductance working interval is proposed, which improves the efficiency of the system. For the nonlinear and time-variant switched reluctance motor running process, a data-driven model-free adaptive control algorithm is introduced, and a switched reluctance motor speed control algorithm based on voltage PWM duty cycle is designed. The main contribution of this paper is to propose a control strategy that is generally applicable to switched reluctance motors, which does not depend on the precise mathematical model of the motor. The control algorithms are designed separately for the three control parameters according to the characteristics of the motor, which reduces the degree of coupling among them. A switched reluctance motor drive system based on angle-position control is designed. This strategy is especially suitable for driving the load with sudden large torque pulsation.
Gels, Aerogels and Hydrogels: A Challenge for the Cellulose-Based Product Industries

During recent decades, the interest in renewable, biodegradable, non-fossil materials has been exponentially increasing. Thus, cellulose and cellulose-derived products have been extensively considered for a wide variety of new potential uses. Due to the sustainability of cellulosic raw materials and their excellent properties, the use and modification of cellulose-based materials can be versatile in the material science and technology community. In this featured article, the fundamentals and background of cellulose-based gels are presented, and approaches, prospects and developments in the field, including their potential future applications, are discussed.
Isolated Gluteus Maximus Tear of a Middle-Aged Fitness Coach; A Case Report

Background: Injuries of the hip extensors are not uncommon, with those of the hamstrings being frequent among athletes. On the contrary, isolated injuries of the gluteus maximus muscle have been barely reported in the literature. Case Report: We present a case of a 63-year-old male water aerobics trainer with an acute tear of the right gluteus maximus tendon and describe the clinical presentation, imaging studies, surgical treatment, and functional outcome one year after surgery.
Size-Dependent Structural, Magnetic and Magnetothermal Properties of Y3Fe5O12 Fine Particles Obtained by SCS

Iron-containing oxides are the most important functional substance class and find a tremendous variety of applications. An attractive modern application is their use in biomedical technologies as components in systems for imaging, drug delivery, magnetically mediated hyperthermia, etc. In this paper, we report the results of the experimental investigation of submicron Y3Fe5O12 garnet particles obtained in different sizes by solution combustion synthesis (SCS) using glycine organic fuel to discuss the interdependence of peculiarities of the crystal and magnetic structure and size’s influence on its functional magnetothermal performance. A complex study including Mössbauer and Raman spectroscopy accompanied by X-ray diffractometry, SEM, and measurements of field and temperature magnetic properties were performed. The influence of the size effects and perfectness of structure on the particle set magnetization was revealed. The ranges of different mechanisms of magnetothermal effect in the AC magnetic field were determined.
Pyrenopeziza orientalipetiolaris sp. nov. in Japan and morphological and genetic comparison with its relevant species P. petiolaris in Europe

Some Asian fungi are morphologically very similar to European species but belong to different species. A fungus that resembles Pyrenopeziza petiolaris, which commonly occurs on the petioles of Acer pseudoplatanus in Europe, was found on the petioles of Acer spp. and other tree leaves in Japan. The apothecia of this fungus were smaller than those of P. petiolaris, suggesting that it is a different species. To examine this possibility, specimens of this fungus were collected from various hosts in Japan. A detailed morphological examination elucidated that this fungus differed from P. petiolaris in smaller apothecia, marginal cells of the ectal excipulum, and conidia. The ITS sequence difference between this fungus and P. petiolaris was 3.3-4.3%, and they formed distinct clades in the phylogenetic analysis, supporting that they are different species. Consequently, a new species, P. orientalipetiolaris is described. Since an undescribed phialophora-state was observed in the cultures of P. petiolaris for the first time, the morphology under culture is also reported in detail.
Polysaccharides as Carriers of Polyphenols: Comparison of Freeze-Drying and Spray-Drying as Encapsulation Techniques

Polyphenols have received great attention as important phytochemicals beneficial for human health. They have a protective effect against cardiovascular disease, obesity, cancer and diabetes. The utilization of polyphenols as natural antioxidants, functional ingredients and supplements is limited due to their low stability caused by environmental and processing conditions, such as heat, light, oxygen, pH, enzymes and so forth. These disadvantages are overcome by the encapsulation of polyphenols by different methods in the presence of polyphenolic carriers. Different encapsulation technologies have been established with the purpose of decreasing polyphenol sensitivity and the creation of more efficient delivery systems. Among them, spray-drying and freeze-drying are the most common methods for polyphenol encapsulation. This review will provide an overview of scientific studies in which polyphenols from different sources were encapsulated using these two drying methods, as well as the impact of different polysaccharides used as carriers for encapsulation.
Peer Teaching Method to Support the Students’ Learning Motivation In Arabic Speaking Skills During The Covid-19 Pandemic

The current covid-19 pandemic phenomenon has a major impact on the learning process at various universities in Indonesia. The adoption of the online lecture system caused by the pandemic has become a problem for some lecturers who are still unfamiliar with technological development. This situation is also experienced by a lecturer who teaches the Speaking Skill Course at a Higher Education in Central Kalimantan Province as a consequence of lacking motivation for the students to attend Speaking Course. To overcome this demotivation, the Arabic Students’ Association at the tertiary education institution organizes Speaking learning using the ”Peer Teaching Method. Therefore, this study aims to explore the speaking skill learning process. This study uses a qualitative approach with a case study type and uses two data collection techniques, namely observation and interviews. This study produced two findings. First, there were several steps used by the organizational coordinator in implementing Speaking Skill learning using the peer teaching method, namely (1) selecting prospective tutors based on their scientific capacity and experience in the field of Arabic language learning, (2) Active learning process speaking skill organized by tutors using various interactive games such as nurakkizu, word chain, and ice breaking. Second, there are several motivational factors for students in participating in speaking skill learning using the peer teaching method, namely (1) The convenience of interaction between tutors and students is caused by the age distance that is not too far, (2) Peer tutor creativity in organizing innovative Speaking Skill learning, and (3) flexibility in communication time between tutors and students.
Membership-Mismatched Impulsive Exponential Stabilization for Fuzzy Unconstrained Multilayer Neural Networks With Node-Dependent Delays

This article focuses on the membership-mismatched impulsive exponential stabilization for fuzzy unconstrained multilayer neural networks (MNNs) with node-dependent time-varying delays (NDTVDs). To begin with, this work proposes a novel MNNs model with unconstrained interlayer and intralayer parameters, which may allow nodes in all layers to have inconsistent attributes and structures. Meanwhile, the novel model considers the NDTVDs and removes the strict constraints including node alignment and one-to-one interlayer connection to meet diverse modeling requirements in complex applications. Then, the proposed fuzzy impulsive controller does not need to share the same fuzzy parameters as the fuzzy MNNs model, reducing the implementation complexity of the fuzzy impulsive controller. To derive the main results using the augmented vector form of unconstrained MNNs, the sparse matrix method is proposed to convert the node-dependent delayed MNNs model into an equivalent model with multiple delays. Moreover, the time-dependent Lyapunov function (TDLF) technique is adopted to improve the reliability of the stabilization conditions by fully utilizing the state information of both the current and neighboring impulsive intervals. Finally, the main results are verified using numerical simulation.
Doing Experimental Psychological Research from Remote: How Alerting Differently Impacts Online vs. Lab Setting

Due to pandemic-imposed restrictions on lab-based research, we have recently witnessed a flourishing of online studies in experimental psychology, based on the collection of fine behavioral measures such as reaction times (RTs) and accuracy. However, it remains unclear whether participants’ alerting levels may have a different impact on behavioral performance in the online vs. lab setting. In this work we administered online and in-lab the dynamic temporal prediction (DTP) task, which requires an implicit modulation of participants’ alerting by alternating experimental conditions implying either slower or faster response rates. We then compared data distribution, RTs, accuracy, and time-on-task effects across the adult lifespan between the settings. We replicated online and across the whole age range considered (19–69 y) all the task-specific effects already found in-lab (both in terms of RTs and accuracy) beyond the overall RTs delay typical of the online setting. Moreover, we found an interaction between the setting and task-specific features so that participants showed slower RTs only in experimental conditions implying a less urgent response rate, while no RTs delay and a slight accuracy increase emerged in faster conditions. Thus, the online setting has been shown to be methodologically sound in eliciting comparable effects to those found in-lab. Moreover, behavioral performance seems to be more sensitive to task-induced alerting shifts in the online as compared to the lab setting, leading to either a heightened or reduced efficiency depending on a faster or slower response rate of experimental conditions, respectively.
Systems Biology: Properties of Reconstructed Networks

Preface 1. Introduction 2. Basic concepts in systems biology Part I. Reconstruction of Biochemical Networks: 3. Metabolic networks 4. Regulatory networks 5. Signalling networks Part II. Mathematical Representation of Reconstructed Networks: 6. Basic features of S 7. Topological properties 8. Fundamental subspaces 9. Null space of S 10. The left null space of S 11. The row and column spaces of S Part III. Capabilities of Reconstructed Networks: 12. Dual causality 13. Properties of solution spaces 14. Sampling properties of solution spaces 15. Finding functional states 16. Parametric sensitivity 17. Epilogue Appendix A: nomenclature and abbreviations Appendix B: E. coli core metabolic network Bibliography Index.