Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical Model of Fingertip Skin Under Constant-Current Electrotactile Stimulation

Due to low energy consumption and fast response, electrotactile feedback has shown great potential in human-machine interaction. However, regulating electrotactile perception remains challenging because of the high variability of electrode-skin impedance. Electrode-skin modelling is a common solution, but current researches are still facing many problems such as non-linearity. This paper focuses on voltage response modelling based on data-driven analysis. Two experiments targeting fingertips have been conducted. Significant correlations between pulse amplitude (<inline-formula><tex-math notation="LaTeX">$PA$</tex-math></inline-formula>), pulse width (<inline-formula><tex-math notation="LaTeX">$PW$</tex-math></inline-formula>) and peak voltage (<inline-formula><tex-math notation="LaTeX">$V_{peak}$</tex-math></inline-formula>) (<inline-formula><tex-math notation="LaTeX">$R^{2}>$</tex-math></inline-formula>0.99) have been found. A mathematical model of fingertip skin is then derived, which enables a precision fitting of the voltage response (RMSE=0.9<inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula>). Finally, two calibration methods are proposed for peak voltage prediction. The accuracy (RMSE=2.5<inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula>) is also verified under different electrode-skin conditions. The results of this paper are expected to provide novel theoretical support for precise regulation of fingertip electrotactile perception.
Cross-linking effect on dielectric properties of polypropylene thin films and applications in electric energy storage

A family of cross-linked polypropylene (x-PP) thin film dielectrics is systematically studied to understand the cross-linking effect on the dielectric properties. Evidently, the butylstyrene (BSt) cross-linkers increase both the dielectric constant (e) and breakdown strength (E), without increasing energy loss. An x-PP dielectric, with 3.65 mol % BSt cross-linkers, exhibits a e∼3, which is independent of a wide range of temperatures and frequencies, slim D-E hysteresis loops, high breakdown strength (E=650 MV/m), narrow breakdown distribution, and reliable energy storage capacity >5 J/cm3 (double that of state-of-the-art biaxially oriented polypropylene capacitors), without showing any increase in energy loss.
EXTRACTION OF ROAD MARKINGS FROM MLS DATA: A REVIEW

Abstract. Nowadays, Mobile Laser Scanning (MLS) systems are more and more used to realize extended topographic surveys of roads. Most of them provide for each measured point an attribute corresponding to a return signal strength, so called intensity value. This value enables to easily understand uncolored MLS as it helps to differentiate materials based on their albedo. In a road context, this intensity information allows to distinguish, among others, the main subject of this paper, i.e. road markings. However, this task is challenging. Road marking detection from dense MLS point cloud is widely studied by the research community. It might concern road management and diagnosis, intelligent traffic systems, high-definition maps, location and navigation services. Dense MLS point clouds provided by surveyors are not processed online, they are thus not directly applicable to autonomous driving, but those dense and precise data can be for instance used for the generation of HD reference maps. This paper presents a review of the different processing chains published in the literature. It underlines their contributions and highlights their potential limitations. Finally, a discussion and some suggestions of improvement are given.
Multi-Sensor Fusion-Based Mirror Adaptive Assist-as-Needed Control Strategy of a Soft Exoskeleton for Upper Limb Rehabilitation

Assist-as-needed (AAN) assistance can promote active voluntary participation in rehabilitation and motor function recovery of post-stroke patients. However, different patients have personalized damaged regions and recovery states, causing difficulties to obtain adaptive and customized assistance in robot-assisted rehabilitation. This paper presents a mirror Adaptive Assist-As-Needed (AAAN) scheme, including two modules of Multi-Sensors Fused Estimation (MSFE) and Online Incremental Mirror Adaptation (OIMA), to encourage the subjects to actively participate in rehabilitation. Specifically, the first MSFE module can obtain the needed assistance based on the functional capability of the post-stroke patients via the data fusion of biological and motional signals using Kalman Filter. The second OIMA module fine-tunes the control torques estimated by MSFE to adapt the muscle fatigue and stiffness varieties of the affected limb based on the motion and physiological reference of the mirror healthy limb. The results demonstrate that the AAAN strategy can realize the transparent mode for healthy subjects and promote post-stroke patients to rehabilitate the affected limb with active participation using EMG signals 90.5% similar to those of the mirror healthy limb. The proposed method can be expected to greatly enhance power assistance and rehabilitation outcome of post-stroke patients using exoskeletons by provoking active participation. Note to Practitioners—For robotic rehabilitation, it is crucial to provide suitable assistances that can maximize the participation of post-stroke patients, which can promote the recovery outcome of therapies. The main purpose of this work is to achieve the adaptive assist-as-needed control strategy for upper limb rehabilitation tasks in two steps. Firstly, the elbow joint torques of a post-stroke patient are estimated by data fusion of motion and electromyography (EMG) signals using Kalman Filter, which can make up for the shortcomings of the individual signals, such as poor reliability and low sensitivity. Secondly, the joint motion and EMG signals of the mirror healthy limb are used as the reference to calculate the adaptive needed assistance to rehabilitate the affected limb. The preliminary experiments with healthy and post-stroke subjects demonstrate that this approach can obtain stable motion with the natural physiological states of subjects and enhance active voluntary participation in rehabilitation. In the future study, it will be investigated how to accelerate the adaptation of new patients based on the knowledge of the learned individuals using machine learning methods, such as lifelong learning and incremental learning.
New design method for discrete-time multi-variable predictive controllers

Abstract A new method for designing discrete-time multi-variable predictive controllers is presented. It is based on the ‘predictive state’ model developed directly from the step response of the plant. With the usual state space techniques, the control law with predictive state feedback is derived by using a discrete-time moving horizon optimization. A predictive state observer is then introduced to realize the control law. Some aspects about parameter selection are discussed. The performance of the new design method is demonstrated by some simulation results. Finally, a comparison between the new method and the usual discrete-time optimal control is made to illustrate the characteristic of the predictive control method.
Sound generated by aerodynamic sources near a deformable body, with application to voiced speech

An analysis is made of sound generation by aerodynamic sources near an acoustically compact body (or compact surface feature on a large boundary) that can deform in an arbitrary manner. It is shown how such problems can be investigated by simple extension of the compact Green's function used in the treatment of compact rigid bodies. It is known that this method can furnish rapid and accurate predictions of sound generated by flows with extensive, non-compact distributions of sources in cases where a numerical treatment requires at best tens or hundreds of hours of CPU time. Illustrative applications are made to study (i) the sound generated by a nominally rigid circular lamina of time-dependent radius held in an irrotational mean stream, and (ii) the production of voiced speech by vorticity interacting with a simple model of the vocal folds. In case (ii), it appears that predictions are represented well by a quasi-static approximation that permits the particular results of this paper and previous investigations to be generalized to arbitrarily configured folds.
Inter-Subject Variability in the Dependence of Medial-Olivocochlear Reflex Strength on Noise Bandwidth

Objectives: The objective of the study was to quantify inter-subject variability in the dependence of the medial-olivocochlear reflex (MOCR) on noise bandwidth. Of specific interest was whether inter-subject variability in MOCR dependence on bandwidth explained variability in the MOCR response elicited by wideband noise. Design: Thirty-two young adults with normal hearing participated in the study. Click-evoked otoacoustic emissions were measured in the ipsilateral ear with and without noise presented in the contralateral ear. Presentation of contralateral noise served to activate the MOCR. The MOCR was activated using five different noise stimuli with bandwidths ranging from 1- to 5-octaves wide (center frequency of 2 kHz; bandwidth incremented in 1-octave steps). Noise spectral levels (19.6 dB SPL/Hz) were held constant across all bandwidths. MOCR metrics included the normalized-percent change in the otoacoustic emission (OAE), the MOCR-induced OAE magnitude shift, and the MOCR-induced OAE phase shift. Linear mixed-effect models were fit to model the dependence of MOCR-induced OAE magnitude and phase changes on noise bandwidth. The use of a mixed-effect modeling approach allowed for the estimation of subject-specific model parameters that capture on- and off-frequency contributions to the MOCR effects. Regression analysis was performed to evaluate the predictive capacity of subject-specific model parameters on the MOCR response elicited by wideband noise. Results: All OAE-based MOCR metrics increased as the noise bandwidth increased from 1- to 5-octaves wide. The dependence of MOCR-induced OAE magnitude and phase shifts on activator bandwidth was well approximated using a linear model with intercept and slope terms. On average, MOCR-induced magnitude and phase shifts increased at a rate of 0.3 dB/octave and 0.01 cycles/octave, respectively, as bandwidth extended beyond the predicted region of OAE generation. A statistically significant random effect of subject was found for both the intercept and slope parameter of each model. Subject-specific slope estimates were statistically significant predictors of a repeated measure of the wideband MOCR response. A higher slope was predictive of larger wideband MOCR effects. Conclusions: MOCR-induced changes to the OAE are greatest when the MOCR is elicited using wideband noise. Variability in the process of spectral integration within the MOCR pathway appears to explain, in part, inter-subject variability in OAE-based estimates of the MOCR response elicited by wideband noise.
Case Study: Self- Help Manuals Based on Cognitive Therapy for Adult with Depression in China

The case study follows a 27 years old lady who suffers from depression, which provides an insight into the society and future studies that self-help can also enhance one’s mental health. The patient was in a mild depression and performed violent behaviors and alcohol obsession. Due to the lack of mental health counseling in china’s unique cultural environment, the research provides a self-analysis and self-healing method. Researchers play the role of instructors and observers who would not disturb the participant. The final depression score after six months returns to a normal range. The result also shows in life clues such as less antisocial behaviors and increased self-control. Thus, the case study provides a new idea for mental health education in developing countries or regions. Social workers can provide self-help for people with depression when counseling is not yet widely available in some areas or when people are very resistant to counseling services.
Constrained Design of Potentiometric RFID Sensors Based on Auto-Tuning ICs

Auto-tuning integrated circuits (ICs), interconnected with radio-frequency identification (RFID) antennas in the UHF band, can provide digital information about the changes in the local boundary conditions in the proximity of the device. This feature, in conjunction with a varactor diode, can be used to create a general-purpose framework for the controlled wireless sensing of chemical agents. The varactor works as a transducer converting the potentiometric output of a chemical sensor into a capacitance change, which in turn is detected by the IC. A constrained optimization method is here introduced to maximize the sensitivity of the above transduction mechanism by deriving closed-form expressions that relate the digital output of the IC to the chemical variation. In this way, said variation will be optimally mapped within the retuning dynamic range of the IC. The method is demonstrated with reference to a pH sensor and is capable of providing a sensitivity of 30 units per unitary pH variation with stable communication performance. Moreover, the application to an on-body plaster-like antenna, namely when there are not fully controllable boundary conditions, demonstrated that the sensing performance is practically unaffected by the placement region over the human body as well as by the inter-user variability.
Renormalization group approach to hot and dense matter

The chiral quark-meson model, being an effective low-energy realization for spontaneous chiral symmetry breaking of QCD at intermediate momentum scales, is often used to study various properties of strongly interacting matter. In this thesis we employ this model to investigate the critical behavior of hot and dense matter with two degenerate light flavors. Using the method of the functional renormalization group, we derive the flow equation for the scale dependent thermodynamic potential at finite temperature and chemical potential in the presence of an explicit symmetry breaking term. We explore the scaling behavior of various observables and confront our results with the Widom-Griffiths form of the equation of state. The focus of our study are especially the scaling properties of the order parameter and its transverse and longitudinal susceptibilities for small, but finite values of the external field when approaching the critical point from the symmetric as well as from the broken phase. We also explore the thermodynamics and the phase structure of strongly interacting hot and dense matter. Apart from the renormalization group formalism, here we also employ the mean field approximation in order to investigate thermodynamic observables sensitive to the phase transition. As an effective model, we use the Polyakov loop extended two flavor chiral quark-meson model in order to connect the chiral and confining properties of QCD. The gluon dynamics is included by coupling quarks with the Polyakov loop and by introducing an effective Polyakov loop potential. We discuss the properties of the net quark number fluctuations in the vicinity of the QCD chiral phase transition. Our main focus of exploration is the ratio of the fourth- to second- order cumulants (kurtosis) and the compressibility. The sensitivity of both observables to the values of the pion mass near the chiral phase transition is also discussed. Within the renormalization group approach, the thermodynamics and the phase structure of the Polyakov loop extended quark-meson model is the main focus of our study. We propose an extended truncation of the effective average action with quarks coupled to background gluonic fields and derive the corresponding flow equation for the scale dependent thermodynamic potential. A full RG treatment of all fields is very complex and thus while solving the flow equation for the quark and meson fields we use the mean field results obtained previously for the Polyakov loop and its conjugate. Thus, within this scheme we determine the phase structure of the model and employ the Taylor expansion coefficients of the thermodynamic pressure in order to locate the position of the critical end point in the phase diagram. Due to the inclusion of fluctuations, we observe a change of the phase diagram compared to that obtained in the mean field approximation. In the end we also briefly discuss the cutoff effect present in the renormalization group method.
The Necessity of the Strong a-Cuts of a Fuzzy Set

Some aspects of the relationship between Goodman and Nguyen's one-point coverage interpretation of a fuzzy set and Zadeh's possibilistic interpretation are discussed. As a result of this, we derive a new interpretation of the strong α-cut of a normalized fuzzy set, namely that of being the most precise set we are sure to contain an unknown parameter with probability greater than or equal to 1-α.
Susan Bassnett’s Philosophy in Translation Studies: A Corpus-based Analysis

As a well-recognized scholar in translation study, Susan Bassnett is known for her proposal of cultural translation which claims a turn from linguistically textual analysis to more sociologically cultural study in translation discipline. Susan Bassnett’s philosophy in translation studies, however, is far beyond the proposal of cultural turn. Based on a corpus analysis on the text of Translation Studies, one of Susan’s popular scholarly books, this study is expected to identify more data proofs of Susan’s contributions, especially those ideas of translation history, translating process and translators’ subjectivity, which will bring significant inspirations for those in translation explorations.
Design of a Compliant Robotic End-Effector Tool for Normal Contact Estimation

The use of industrial robots for machining operations such as polishing is gaining popularity these days. However, maintaining constant normal contact on unknown geometrical surfaces still remains a challenge. In order to cope with the issue, this research has developed a unique compliant robotic end-effector that can measure the depth and angles deviation of the robot from the normal complex surfaces in real-time without any prior geometric model of the workpiece. The indigenously developed compliant robotic end-effector is made up of three main components: a novel three-axis force/torque sensor, a compliant contact pin, and a data acquisition (DAQ) board. Initially, the three-axis force/torque sensor has been validated with both simulation and testing. The advantage of being able to take measurements in real-time is provided by the DAQ’s automatic weight compensation feature. Additionally, the pose correction algorithm receives the estimated contact force as feedback during robot surface tracking in order to assess depth and angles and determine the proper distance and perpendicular relationship between the surface and the end-effector. The proposed scheme is then evaluated using a six-axis industrial robot. The experimental results show that the maximum average depth and angle errors are 0.13 mm and 0.64°, respectively. The developed system has achieved significant improvement in contact-based robot surface measuring.
A new visual odometry algorithm based on multi-path deep fully convolutional neural networks

Visual odometry is one of the key core technologies in the field of autonomous driving. However, images captured in lowlight or unevenly-illuminated scenes still cannot guarantee good performance due to low image contrast and lack of detail features. Therefore, we propose an end-to-end visual odometry method based on image fusion and FCNN-LSTM in the paper. The brightness image of the source image sequence is obtained by gray-scale transformation, and an image fusion algorithm based on spectral residual theory is designed to combine the image sequence and its brightness image to enhance the contrast of the image and provide more detailed information. In order to improve the accuracy of image feature extraction and reduce the error in the pose estimation process, we design a feature extraction algorithm based on skipfusion-FCNN. The traditional fully convolutional neural network (FCNN) is improved, a skip-fusion-FCNN network model is proposed, and three different paths are constructed for feature extraction. In each path, the prediction results of different depths are fused by downsampling to obtain a feature map. Merge three different feature maps to obtain feature fusion information, taking into account the structural information and detail information of the image. Experiments show that this algorithm is superior to the state-of-the-art algorithms.
Properties of the c-Si/Al2O3 interface of ultrathin atomic layer deposited Al2O3 layers capped by SiNx for c-Si surface passivation

This work presents a detailed study of c-Si/Al2O3 interfaces of ultrathin Al2O3 layers deposited with atomic layer deposition (ALD), and capped with SiNx layers deposited with plasma-enhanced chemical vapor deposition. A special focus was the characterization of the fixed charge density of these dielectric stacks and the interface defect density as a function of the Al2O3 layer thickness for different ALD Al2O3 deposition processes (plasma-assisted ALD and thermal ALD) and different thermal post-deposition treatments. Based on theoretical calculations with the extended Shockley–Read–Hall model for surface recombination, these interface properties were found to explain well the experimentally determined surface recombination. Thus, these interface properties provide fundamental insights into to the passivation mechanisms of these Al2O3/SiNx stacks, a stack system highly relevant, particularly for high efficiency silicon solar cells. Based on these findings, it was also possible to improve the surface passi.
Bta-miR-106b Regulates Bovine Mammary Epithelial Cell Proliferation, Cell Cycle, and Milk Protein Synthesis by Targeting the CDKN1A Gene

Our previous studies found that bta-miR-106b and its corresponding target gene, CDKN1A, were differentially expressed between the mammary epithelium of lactating Holstein cows with extremely high and low milk protein and fat percentage, implying the potential role of bta-miR-106b in milk composition synthesis. In this study, with luciferase assay experiment, bta-miR-106b was validated to target the 3′-untranslated region (UTR) of bovine CDKN1A, thereby regulating its expression. Moreover, in bovine mammary epithelial cells (BMECs), over-expression of bta-miR-106b significantly down-regulated the CDKN1A expression at both mRNA and protein levels, and inhibitors of bta-miR-106b increased CDKN1A expression. Of note, we observed that bta-miR-106b accelerated cell proliferation and cell cycle, and changed the expressions of protein synthesis related pathways such as JAK-STAT and PI3K/AKT/mTOR through regulating CDKN1A expression. Our findings highlight the important regulatory role of bta-miR-106b in milk protein synthesis by targeting CDKN1A in dairy cattle.