Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Assistive Paradigm Based on Neuromuscular Electrical Stimulation and Force Control for Upper Limb Exosuits

Intensive rehabilitation treatments are crucial to recovering motor functions in patients with neuromuscular diseases. Robotic devices and neuromuscular electrical stimulation (NMES) have shown their efficacy with respect to traditional physiotherapy. Both technologies present complementary features but also limitations due to their working principles. However, merging robots and NMES could overcome their boundaries, providing more patient therapy effort. By pursuing such a hybrid concept, we propose a new device that combines NMES and an upper limb exosuit to assist elbow movements. We tested the designed system on healthy people by evaluating kinematics outcomes and metabolic consumption. The outcomes result in more accuracy and less metabolic consumption by assisting people with the hybrid system than the exosuit and the NMES alone. The ability to seamlessly combine NMES with wearable soft mechatronics can open new avenues for restoring human movement in impaired individuals.
Experimental Measurement and Theoretical Analysis of Rectangular Waveguide Filters for C-band Satellite Antenna Systems

In this paper we carried out theoretical and experimental investigations of band-pass filters based on a rectangular waveguide for 4 GHz frequency range. The frequency dependences of the total transmission coefficient and the reflection coefficient of the band-pass filter were analyzed for three variants of size of the aperture window. The concept of equivalent lumped elements was applied to characterize the diaphragms of inductive type. Both experimental and theoretical values of the quality factor for the band-pass filters were determined. Measured quality factors are in the range of 47–128 for transfer resonators of 4 GHz resonance frequencies. In addition, frequency dependences of reflection and transmission coefficients were depicted for theoretical and experimental results. Obtained functions, resonance frequencies and quality factors are in good agreement. Developed and analyzed rectangular waveguide sections with diaphragms can be widely applied in band-pass filters for satellite antenna systems.
Terahertz Windmill-Shaped Circularly Polarized Pattern Reconfigurable Antenna with MEMS Switches

A circularly polarized pattern reconfigurable patch antenna operating in the terahertz band is presented in this paper. The geometry of this antenna can be changed by controlling the on and off state of four MEMS switches. By connecting one of parasitic arms and coupling with the others, the patch antenna at each state will radiate unique circularly polarized tilted beam. The proposed series MEMS switch has high isolation in terahertz band. The mechanical optimization is applied on the switch to achieve a low pull-down voltage while maintaining low profile. Besides, a four-port feeding network is designed to eliminate differences in different states. The simulated results show that the proposed antenna achieves a stable pattern bandwidth from 340 GHz to 350 GHz with reflection coefficient S11<-15 dB.
Using X-ray catalogues to find counterparts to unassociated high-energy Fermi/LAT sources

The first Fermi Large Area Telescope (LAT) catalogue of sources (1FHL) emitting at high energies (above 10 GeV) reports the details of 514 objects detected in the first three years of the Fermi mission. Of these, 71 were reported as unidentified in the 1FHL catalogue, although six are likely to be associated with a supernova remnant (SNR), a Pulsar Wind Nebula (PWN) or a combination of both, thereby leaving a list of 65 still unassociated objects. Herein, we report a preliminary analysis on this sample of objects concentrating on nine 1FHL sources, which were found to have a clear optical extragalactic classification. They are all blazar, eight BL Lac and one flat spectrum radio quasar, typically at redshift greater than 0.1.
Empirical Validation of an Auxetic Structured Foot With the Powered Transfemoral Prosthesis

The toe joint has been studied since it plays a critical role in human ambulation, such as stability, energy storage and propulsion. Despite its critical role, only a few studies have used and tested toe-jointed feet in powered prosthetic walking. In previous studies, we proposed 3D printable prosthetic feet with auxetic structures that provide human-like toe joint properties, termed a flat-toe (FT) foot and a curved-toe (CT) foot. The numerical simulation revealed that these feet could mimic the function of the biological toe joint, but they have not yet been validated in an empirical manner. In this study, we conducted a walking experiment with three subjects (i.e., two able-bodied and one amputee) using a powered prosthesis and two custom-designed prosthetic feet: the FT foot and CT foot. To evaluate the given feet, several metrics (e.g., joint kinematics/kinetics, ground reaction forces, and gait symmetry) were utilized. According to the results, the CT foot exhibited greater toe flexion, resulting in an earlier heel-off, a later toe-off, and a longer push-off duration when compared to the FT foot. Furthermore, less ground reaction forces were measured from both the prosthesis and intact sides, and a more symmetric gait was achieved with the CT foot. Another interesting finding was that the CT foot affected the user's thigh kinematics, leading to an improved gait phase estimation while walking. We concluded that the CT foot allowed for a more natural roll-over, resulting in better consistency and symmetry while walking with the powered prosthesis.
Learning-based Optimal Admission Control in a Single Server Queuing System

We consider admission control for a first-in first-out single class single server queueing model with Poisson arrivals and exponential service times. Specifically, there is a dispatcher that decides on admitting arrivals with the aim to maximize total net profit - each admitted arrival yields a positive reward $R$ (obtained after customer finishes service) that needs to be balanced by a holding cost for the (homogeneous) customers in the queue. Whereas the capacity of this queue is infinite, the dispatcher may decide to reject any customers joining the queue with the profit objective in mind. When the arrival and service rates are known, this model was studied by Naor [1], but in our investigation the dispatcher is assumed to know the arrival rate but not the service rate.
Age of Information Process under Strongly Mixing Communication - Moment Bound, Mixing Rate and Strong Law

The decentralized nature of multi-agent systems requires continuous data exchange to achieve global objectives. In such scenarios, Age of Information (AoI) has become an important metric of the freshness of exchanged data due to the error-proneness and delays of communication systems. Communication systems usually possess dependencies: the process describing the success or failure of communication is highly correlated when these attempts are “close” in some domain (e.g. in time, frequency, space or code as in wireless communication) and is, in general, non-stationary. To study AoI in such scenarios, we consider an abstract event-based AoI process $\Delta (n)$, expressing time since the last update: If, at time $n$, a monitoring node receives a status update from a source node (event $A(n-1)$ occurs), then $\Delta (n)$ is reset to one; otherwise, $\Delta (n)$ grows linearly in time. This $A$ oI process can thus be viewed as a special random walk with resets. The event process $A(n)$ may be non-stationary and we merely assume that its temporal dependencies decay sufficiently, described by $\alpha$ -mixing. We calculate moment bounds for the resulting $A$ oI process as a function of the mixing rate of $A(n)$. Furthermore, we prove that the $A$ oI process $\Delta (n)$ is itself $\alpha$ -mixing from which we conclude a strong law of large numbers for $\Delta (n)$. This opens up future work on renewal processes with non-independent interarrival times.
Popularity Increment Forecast Based on Depth Fully Extracting Spatiotemporal Structure

The data characteristics of the information cascade are essential to the prediction performance of the information cascade. The traditional prediction methods can not well couple the various attributes of cascade data. This paper proposes an approach based on deep extraction of full spatiotemporal structure (FuSTCas). FuSTCas uses the deep learning framework to extract and refine the spatiotemporal information in the raw cascade data. Then FuSTCas combines the time decay function and multi-layer perceptron to make the final cascade prediction. The experimental results show that compared with several baseline models, FuSTCas does improve the prediction accuracy. And the components of FuSTCas effectively extract the spatiotemporal information.
Study of Organic-Inorganic Polymer Nanocomposite Materials for Polyfunctional Resistive Sensor Devices

The research of features of electrical conductivity of organic-inorganic polymer nanocomposite materials, filled with functionalized multiwalled carbon nanotubes depending on humidity and temperature is done using the impedance spectroscopy method. It was showed that the electrical conductivity of the probed systems in the temperature range from 280 K to 370 K increases more than 10 times. It is shown that the probed systems are perspective and can be used as thermoresistive materials for temperature sensors. It was shown, that sensor, which contains 1 % nanotubes, demonstrates the greatest speed of reacting and sensitiveness. This material is very perspective for creation of capacitance-resistance gas sensors for monitoring of environments humidity level.
Mathematical Simulation of Thin Magneto-Dielectric Layered Radiofrequency Coatings for Protection of Electronic Components

With the help of carried mathematical simulation, effectiveness of application of the layered magneto-dielectric coatings with losses for preventing of the electromagnetic waves reflection from conductive parts of the electronic components is shown. Parameters of the relative permittivity and permeability in each layer are chosen equal to each other and their electrical conductivity is increased successively at approaching a protected object. With the help of such coatings having micrometer thickness of each layer, reflection of the electromagnetic waves can be effectively lessened - up to 1 % of the incident wave intensity levels. For simulation, the finite integration technique was applied. To decrease the calculation domain, the electromagnetic wave was presented as a sum of an incident and a reflected waves, and virtual the so-called matched layers were applied at the outer boundaries of the computational domain. These approaches were rearranged in relation to the problem solution in terms of the magnetic vector potential, which provides reduction of the required computational resources and therefore enables more effective search of the protective coatings with better characteristics.
Comparison of Different Sentiment Analysis Techniques for Bangla Reviews

Internet adoption has increased rapidly during the worldwide COVID-19 pandemic. Nowadays people not only prefer to shop using various e-commerce platforms, but also like to provide feedback and express their opinions and experiences using the online platforms. Since new customers try to understand the products' utility and acceptability from other consumers' reviews, it has become crucial to analyze the customers' sentiments and opinions on each product. In this paper, we have presented a sentiment analysis technique on the basis of product reviews written in Bangla language to better understand the combined consumer perspective. Our work aims to compare existing classifiers' performance and find the best algorithm for our dataset. We collected reviews from the leading Bangla bookselling e-commerce site “Rokomari.com” for this work. We implemented ML and DL classifier models and compared their overall performance on this dataset. The experimental studies show that the best accuracy is achieved from LSTM and SGD over the other implemented ML and DL based classifier models.
A 2-D Inductive Power Transfer Network for Powering Massive Neighboring IoT Devices

Due to the wide distribution of Internet of Things (IoT) devices, reliable and convenient power solutions for these devices have been a continuous pursuit recently. In this paper, a two-dimensional (2-D) inductive power transfer (IPT) design based on multiple coupled resonators is proposed for powering IoT devices in a reconfigurable neighboring scenario. There are two types of cells in this system: constant voltage (CV) and constant current (CC) cells. These two types of cells are alternately arranged. In this IPT system, the coupling electromagnetic field is mostly constrained in a small region, so that the radiation leakage to the free space can be relieved without introducing extra complex control. The wireless power makes the whole system convenient and reconfigurable according to the user’s requirements. The circuit model is mathematically formulated. A nine-cell prototype is implemented and tested. Experimental results approve the CC or CV properties in each cell. The power conversion efficiency of the whole system reaches 75%.
Tongs Shaped Dual Band MIMO Antenna for WLAN and WiMAX Applications

The tongs shaped MIMO antenna having the size $45\times 45\times 1.6\ \text{mm}^{3}$ is presented in this paper with dual band characteristics. The dual bands of presented antenna are 2.3 GHz – 2.4 GHz and 3.9 GHz – 7.9 GHz used for the applications of WiMAX and WLAN. The evolution of tongs shaped antenna reduced the interference within the signals and increased the gain of the antenna to 5.8 dB. The designed element structure improved isolation having size compactness and reliability. Correlation between the elements is reduced by orthogonal placement and the diversity parameters of the antenna are simulated and its results are plotted. The performance of MIMO is shown as the plots of gain, efficiency, ECC, CCL, DG, MEG and TARC.
Power Transport Theorem (PTT)-Based Decoupling Mode Theory (DMT) for Wave-Guiding Structures

Power transport theorem (PTT) governing the transport process of the power-flow passing through waveguide is derived. Input power as the source term in PTT is found to be the one for sustaining the steady power transport, and the corresponding input power operator (IPO) is formulated. Travelling-wave condition satisfied by the travelling-wave modes one-directionally propagating along the waveguide is introduced as a counterpart of the famous Sommerfeld’s radiation condition satisfied by the radiative fields distributing in the far zone. Using the travelling-wave condition and some other necessary conditions, the dependent currents in IPO are effectively eliminated. Under the PTT framework, the recently developed decoupling mode theory (DMT) for the wave-port-fed antennas is further generalized to waveguides. The PTT-based DMT (PTT-DMT) focuses on constructing a set of energy-decoupled modes (DMs) for any pre-selected objective waveguide by diagonalizing the IPO with only independent current, and any two different DMs do not have net energy exchange in an integral period. The PTT-DMT is an effective alternative for the classical eigen-mode theory. The alternative realizes an effective unification for the waveguide-oriented modal analysis theory and the antenna-oriented modal analysis theory, such that the theories can be easily integrated into a single theory for the whole waveguide-antenna combined system in the future.
Res-SE-ConvNet: A Deep Neural Network for Hypoxemia Severity Prediction for Hospital In-Patients Using Photoplethysmograph Signal

Determining the severity level of hypoxemia, the scarcity of saturated oxygen (SpO2) in the human body, is very important for the patients, a matter which has become even more significant during the outbreak of Covid-19 variants. Although the widespread usage of Pulse Oximeter has helped the doctors aware of the current level of SpO2 and thereby determine the hypoxemia severity of a particular patient, the high sensitivity of the device can lead to the desensitization of the care-givers, resulting in slower response to actual hypoxemia event. There has been research conducted for the detection of severity level using various parameters and bio-signals and feeding them in a machine learning algorithm. However, in this paper, we have proposed a new residual-squeeze-excitation-attention based convolutional network (Res-SE-ConvNet) using only Photoplethysmography (PPG) signal for the comfortability of the patient. Unlike the other methods, the proposed method has outperformed the standard state-of-art methods as the result shows 96.5% accuracy in determining 3 class severity problems with 0.79 Cohen Kappa score. This method has the potential to aid the patients in receiving the benefit of an automatic and faster clinical decision support system, thus handling the severity of hypoxemia.
Mitigation of RF Sheaths Impurities Generation by Structural Optimization of ICRH Antenna for EAST

Ion Cyclotron Resonant Heating (ICRH) and Current Drive (CD) are effective methods of plasma heating and confinement in tokamaks. The generation of impurities associated with ICRH & CD is one of the critical issues. Studies indicated that the fluxes of ions accelerated in the radio frequency (RF)-driven sheaths closed to antenna give rise to the parasitic impurity sputtering, arcs and the hot spots on the antenna surface, which will deteriorate the plasma confinement and even cause safety issues such as breakdown of ICRH system. This work reveals that the imbalance of magnetic flux through flux surface controlled by the phase composition and the unsatisfactory structures of antenna components can cause large parallel components of electric field (E//), which in turn lead to the formation of RF-driven sheaths. Aiming to mitigate the RF sheaths impurities of the ICRH antenna in Experimental Advanced Superconducting Tokamak (EAST), an alternative plasma load was used during the modeling study to obtain the near-field characteristics. Based on the analysis of the field properties near the antenna, several designs that can alleviate impurity issue on the EAST ICRH antenna were presented, through which the parallel components of electric field and RF-driven sheaths have been greatly improved. The research results expressed in this paper can provide reference for the EAST and China Fusion Engineering Test Reactor (CFETR) ICRH design.
Thermal convection with mixed thermal boundary conditions: effects of insulating lids at the top

The effects of insulating lids on the convection beneath were investigated experimentally using rectangular convection cells in the flux Rayleigh number range $2.3\times 10^{9}\leqslant Ra_{F}\leqslant 1.8\times 10^{11}$ and cylindrical cells in the range $1.4\times 10^{10}\leqslant Ra_{F}\leqslant 1.2\times 10^{12}$ with the Prandtl number $Pr$ fixed at 4.3. It is found that the presence of the insulating lids leads to reduction of the global heat transfer efficiency as expected, which primarily depends on the insulating area but is insensitive to the detailed insulating patterns. At the leading-order level, the magnitude of temperature fluctuations in the bulk fluid is, again, found to be insensitive to the insulating pattern and mainly depends on the insulating area; while the temperature probability density function in the bulk is essentially invariant with respect to both the insulating area and the spatial pattern of the lids. The flow dynamics, on the other hand, is sensitive to both the covering area and the spatial distribution of the lids. At fixed $Ra_{F}$ , the flow strength is found to increase with increasing insulating area so as to transfer the same amount of heat through a smaller cooling area. Moreover, for a constant insulating area, a symmetric insulating pattern results in a symmetric flow pattern, i.e. double-roll structure; whereas an asymmetric insulating pattern leads to asymmetric flow, i.e. single-roll structure. It is further found that the symmetry breaking of the insulating pattern leads to a stronger flow that enhances the horizontal velocity more than the vertical velocity.
FAB Storage for the Hybrid Cloud

Storage is the Achilles heel of hybrid cloud deployments of workloads. Accessing persistent state over a WAN link, even a dedicated one, delivers an over-whelming performance blow to application performance. We propose FAB, a new storage architecture for the hybrid cloud. FAB addresses two major challenges for hybrid cloud storage, performance efficiency and backup efficiency. It does so by creating a new FAB layer in the storage stack that enables fault-tolerance, performance acceleration, and backup for FAB storage volumes. A preliminary evaluation of FAB's performance acceleration mechanism when deployed over Ceph's distributed block storage system offers encouragement to pursue this new hybrid cloud storage architecture.
On the Reproducibility of Bugs in File-System Aware Storage Applications

Many storage applications such as file system checkers, defragmentation tools, etc. require a detailed understanding of file systems. Such file-system aware applications play an essential role today, but unfortunately they are error-prone. To better understand the challenges as well as the opportunities to address the issues, this paper presents an empirical study of real world bugs in file-system aware storage applications. By analyzing 59 bug cases from 4 representative applications in depth, we derive multiple insights in terms of general bug patterns, triggering conditions, and implications for building effective tools to address the issues. We hope that our study and the resulting dataset could contribute to the development of reliability tools for building robust file-system aware storage applications in general.
Biosynthesis and Characterization of Co3O4NPs Utilizing Prickly Pear Fruit Extract and its Biological Activities

In the current research, there is a low level of research and information about the interaction of cobalt oxide nanoparticles (Co3O4NPs) in biological systems. This research creates a very simple and cost-effective preparation of cobalt oxide nanoparticles by using prickly pear fruit extract as a reducing agent, which may be further used for biological applications like antimicrobial, antioxidant, DNA interaction and in-vitro anticancer activity. The use of prickly pear fruit extract acts as a good reducing agent and is responsible for easy preparation and reducing the toxicity of cobalt oxide nanoparticles. The fabricated biogenic nanoparticles were confirmed by microscopic and spectroscopic analytical techniques like Ultra Violet-Visible spectrometer, Fourier transforms infrared spectrometer (FTIR), X-ray Diffraction Method (XRD), Energy-dispersive X-ray spectroscopy (EDS), Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM). The average size of the synthesized nanoparticles is 36.24 nm. In the MTT assay, the prepared cobalt oxide NPs haspotential mechanisms of cytotoxicity and in-vitro anticancer activity in Hepatocellular carcinoma cancer cells (HepG2). The microbial activities like antibacterial and antifungal studies of the biosynthesized nanoparticles were performed by the Disc method. The Co3O4NPs with DNA interaction were examined by UV-Visible and fluorescence spectroscopic methods. The binding constant value of biogenic Co3O4NPs with CT-DNA was observed by UV-Visible spectroscopy with a result of 2.57x105mol-1. The binding parameters and quenching constants were observed by fluorescence spectroscopic methods having values of Ksv=7.1x103, kq=7.1x108, Ka=3.47. 1x105, n=0.9119. From the findings, Co3O4NPs may be utilized as a medicinal aid for their antibacterial, antifungal, antioxidant, DNA binding and in-vitro anticancer activities.