Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Performance Assessment of the Dual-Material Gate GaAs/InAs/Ge Junctionless TFET

In this article, a device called GaAs/InAs/Ge junctionless tunnel field-effect transistor (JL-TFET) is proposed and investigated by a numerical simulator. This device utilizes an InAs pocket at the source side and its digital performance parameters such as subthreshold slope (SS) and ON-state current to OFF-state current (<inline-formula> <tex-math notation="LaTeX">${I}_{ON}/{I}_{OFF}$ </tex-math></inline-formula>) ratio have been improved in comparison with GaAs/Ge JL-TFET. Simulation results show that the electron tunneling mechanism is based on intraband tunneling and interband tunneling in GaAs/InAs/Ge JL-TFET, while the electron tunneling mechanism is interband tunneling in regular JL-TFET. To further reduce SS, we have proposed for the first time GaAs/InAs/Ge JL-TFET structure with a fixed gate (f-gate), the so-called dual-material gate (DMG) GaAs/InAs/Ge JL-TFET. The f-gate induces a local dip in the conduction band edge leading to more abrupt band bending at the vicinity of the InAs/GaAs interface. Simulation results show that DMG GaAs/InAs/Ge JL-TFET is turned on at lower <inline-formula> <tex-math notation="LaTeX">${V}_{\text {GS}}$ </tex-math></inline-formula> compared to GaAs/InAs/Ge JL-TFET, causing a SS is improved. A brief examination of the proposed device has been done on the impacts of both the variations of the f-gate work-function (<inline-formula> <tex-math notation="LaTeX">$\phi _{\text {F}}$ </tex-math></inline-formula>) and the f-gate length (<inline-formula> <tex-math notation="LaTeX">$\text {L}_{\text {f-gate}}$ </tex-math></inline-formula>). The DMG GaAs/InAs/Ge JL-TFET with a channel length of 20 nm, <inline-formula> <tex-math notation="LaTeX">$\phi _{\text {F}} = 3.7$ </tex-math></inline-formula> eV, and <inline-formula> <tex-math notation="LaTeX">$\text {L}_{\text {f-gate}} = {5}$ </tex-math></inline-formula> nm showed the average SS of SS = 2.1 mV/dec, and ON-state current of <inline-formula> <tex-math notation="LaTeX">${I}_{ON} = {0.51}$ </tex-math></inline-formula> mA/ <inline-formula> <tex-math notation="LaTeX">$\mu {\mathrm{ m}}$ </tex-math></inline-formula>. The SS and <inline-formula> <tex-math notation="LaTeX">${I}_{ON}$ </tex-math></inline-formula> of the DMG GaAs/InAs/Ge device are improved by 150% and 76%, respectively, compared to the GaAs/Ge JL-TFET device with similar dimensions. The DMG GaAs/InAs/Ge JL-TFET device proposed in this article can be a reasonable candidate for digital applications.
Highly Sensitive and Flexible Piezoresistive Pressure Sensors Based on 3D Reduced Graphene Oxide Aerogel

The flexible piezoresistive sensors have versatile applications for healthcare. The fabrication procedures of these sensors are generally costly, complex, and environmentally unfriendly. Herein, we use L-cystine as the green reductant and templating agent to prepare 3D reduced graphene oxide (rGO) aerogel, and polyvinyl chloride tape as the substrates to encapsulate the aerogel for making the piezoresistive sensor. The sensor shows good linearity of resistance to logarithmic pressure value in a wide range of 170.4 kPa to 2.4 MPa, and it is capable to monitor the wrist pulse and human motion. Sensors fabricated by this facile and economical method have great potential application in electronic skin.
Parameter identification of a tumor model using artificial neural networks

Mathematical models of tumor growth and the effect of therapy is fundamental for personalizing and optimizing anticancer therapies. The aim of the research is to provide a good estimation of personalized tumor model parameters based on measurements carried out on the patient. We use in silico experiments to create a large set of training data in a span that covers real-life scenarios. The data are used to train neural networks which provide a good initial guess for the model parameters. The estimated parameters can be used as initial estimations for more sophisticated, but local identification algorithms.
Quality-Aware DevOps Research: Where Do We Stand?

DevOps is an emerging paradigm that reduces the barriers between developers and operations teams to offer continuous fast delivery and enable quick responses to changing requirements within the software life cycle. A significant volume of activity has been carried out in recent years with the aim of coupling DevOps stages with tools and methods to improve the quality of the produced software and the underpinning delivery methodology. While the research community has produced a sustained effort by conducting numerous studies and innovative development tools to support quality analyses within DevOps, there is still a limited cohesion between the research themes in this domain and a shortage of surveys that holistically examine quality engineering work within DevOps. In this paper, we address the gap by comprehensively surveying existing efforts in this area, categorizing them according to the stage of the DevOps lifecycle to which they primarily contribute. The survey holistically spans across all the DevOps stages, identify research efforts to improve architectural design, modeling and infrastructure-as-code, continuous-integration/continuous-delivery (CI/CD), testing and verification, and runtime management. Our analysis also outlines possible directions for future work in quality-aware DevOps, looking in particular at AI for DevOps and DevOps for AI software.
On the Performance of the SPICE Method

This letter considers the performance of the SPICE method in the context of line spectrum estimation by exploiting its equivalent square-root lasso (SR-LASSO) representation established in previous work. The inefficiencies of existing analyses are that the guarantees are not applicable to deterministic Fourier measurement matrices, and the studied range of the tuning parameter excludes the SR-LASSO formulation of the SPICE method. The key observation of this letter is that, for a particular range of tuning parameter, the solutions which overfit the noisy measurements are valid SR-LASSO solutions. Based on this observation, we propose to analyze these overfitting solutions and derive the condition of exact on-grid source localization that is applicable to the SPICE method. The numerical experiments demonstrate our theoretical claims.
Adição de carbono e nitrogênio e sua relação com os estoques no solo e com o rendimento do milho em sistemas de manejo

Long-term experiments are essential for research about organic matter dynamics of soils. This paper reports results of an experiment installed in September 1985 on a Paleudult soil degraded under inadequate management for 16 years. The experiment was conducted at the Experimental Station of the Federal University of Rio Grande do Sul (Brazil) in Eldorado do Sul county. Three soil tillage methods (conventional tillage-CT, reduced tillage-RT and no-tillage-NT), three crop systems (oat/corn-O/C, vetch/corn-V/C and oat + vetch/corn + cowpea-O + V/C + Cp), and two N rates applied to corn as urea (0 and 139 kg ha-1) were tested. A split-plot design arranged in randomized blocks with three replications was used with soil tillage as main plot, the cropping systems as sub-plots and nitrogen rates as sub-blocks. Carbon and nitrogen addition by crops was estimated for the experimental period of 13 years. In September 1998, the soil was sampled in six layers down to 0.30 m depth, and total organic carbon (TOC) and total nitrogen (TN) contents were determined in each layer and then calculated for the 0-0.175 m and 0.175-0.30 m layers. Legumes were responsible for the greatest annual soil C and N increase by crops (4.17 to 8.39 Mg ha-1 and -21 to 178 kg ha-1, respectively). The highest C and N additions were positively related to these elements stocks in the soil under NT (0-0.175 m layer), and promoted gradual corn yield increase in all soil tillage treatments. The annual rate of C addition (A) necessary to maintain de initial condition (dC/dt = zero) was estimated at 4.2 Mg ha-1 for NT, 7.3 Mg ha-1 for RT and 8.9 Mg ha-1 for CT. Similarly, the annual rate of N addition required to maintain the initial condition (dN/dt = zero) was 5 kg ha-1 for NT, 31 kg ha-1 for RT, and 94 kg ha-1 for CT. An estimation by the angular coefficient of the linear regression, which relates the annual C addition rates and annual TOC stock variation in the surface layer, calculated that 12.9 % for NT, 8.1 % for RT, and 11.5 % for CT of the C added to the soil was retained in the soil organic matter, representing approximately the humification coefficient (k1). Likewise, it was estimated that 49.7 % of the net annual N addition under NT, 21.0 % under RT, and 33.1 % under CT was retained as TN in the soil. The TOC loss coefficient from the soil (k2), calculated for the condition dC/dt = zero, was 0.0166 yr-1 under NT, 0.0182 yr-1 under RT, and 0.0314 yr-1 under CT. No-tillage systems with the reduction of TOC loss (k2), and legume based crop systems with the high C and N additions are good alternatives to recover the soil TOC and TN stocks and increase corn yield in the subtropical region of southern Brazil.
An RSA-based Algorithm for Secure D2D-aided Multicast Delivery of Multimedia Services

To answer the sharp surge in the number of devices requiring the same multimedia content, an effective management of group-communications (i.e., multicast) in current fifth generation (5G) network appears urgent. Device-to-device (D2D) communications can greatly improve the performance of a multicast transmission as long as effective countermeasures are taken to the several security vulnerabilities they may be suffering. In this paper, we propose an algorithm for the secure D2D-aided delivery of multicast services that exploits the RSA (Rivest-Shamir-Adleman) encryption algorithm for the protection of data transmitted in D2D. The main benefit of this approach is the possibility of delivering the required service in multicast also for D2D transmissions by means of properly selected relay nodes that work as heads of each D2D cluster. Simulation results testify to the effectiveness of the proposed solution in providing security assurance and limited resource consumption.
The Use of Grading in Nb3Sn High-Field Block-Coil Dipoles

High-field Nb3Sn dipoles generating more than 15 T are strongly required, whether it is for the future circular collider studies (CERN 16 T Development Program, CEA-CERN demonstrator) or for test stations (FRESCA2, HEPDipo). The use of magnets graded with different cables now becomes unavoidable to allow for more compact and cost-effective designs. This article presents a 2-D parametric study, which explores possible options for an optimal grading. The study uses analytical formulas for current sources to allow for fast and accurate parametric studies. Block coils are considered, using different cable sizes, and therefore, different current densities. Various parameters are also explored, such as cable combinations, current density ratios, conductor performance, and position of the blocks. The article shows in particular what are the optimal grading factors and amount of conductor required to reach a given bore field, considering margins on the load line, and limitations in current density for quench protection.
RGB-D Videos-Based Early Prediction of Infant Cerebral Palsy via General Movements Complexity

Early detection and intervention of cerebral palsy can promote neural remodeling in the process of brain development, thus reducing the negative effects of cerebral palsy. In this paper, we proposed a novel method for early prediction of infant cerebral palsy based on General Movements Assessment (GMA) theory with RGB-D videos. Firstly, we explored the human pose recognition in supine position based on RGB-D videos. Then we further apply it to auto-GMA. Specifically, we employ current pose estimation method on RGB images to achieve the infant full body 2D key points. By combining the depth information, the 3D movement of infant in supine position can be obtained. Then the infant’s movement complexity index is achieved by extracting the infant’s whole-body movement characteristic. In order to verify the effectiveness of the method, we did some experiments on a public dataset consisting 12 real recorded infants’ movement RGB-D videos, with 4 of the samples were diagnosed as abnormal infants by a GMA expert. We use expert GMA ratings of these recorded movements as the gold standard. Our method achieved state-of-the-art with sensitivity of 100%, specificity of 87.5%, and accuracy of 91.7%. The results show that the method has great potential in assisting doctors in diagnose infant cerebral palsy.
Transmission and deposition behavior of aerosols in sampling inlets

Under many conditions of aerosol sampling, particle deposition inside the inlet has an equal or greater effect on the overall sampling efficiency than particle aspiration from the environment to the inlet face. This paper describes quantitatively the deposition and transmission behavior of particles inside an aerosol sampling inlet. The experimental data have been obtained in a horizontal wind tunnel in which uranine-tagged aerosols are dispersed and subsequently sampled by thin-walled, circular inlets. The inlets are aligned parallel to the wind direction and feed the transmitted aerosols into the view volume of an optical single particle counter. Through washoff and fluorescent analysis of the particle deposits combined with the particle count from the optical particle counter, the transmission efficiencies have been determined for various particle sizes, wind and inlet velocities, and inlet sizes. A model has been developed from the data, and a uniform and general expression for the transmission effici.
Q-Learning-Based Power Allocation for Secure Wireless Communication in UAV-Aided Relay Network

Unmanned aerial vehicle (UAV)-aided wireless relay networks are at risk of eavesdropping activities due to their open nature. In this paper, we study the security of a UAV-aided selective relaying wireless network in which <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> UAVs are employed as decode-and-forward (DF) relays linking a ground base station (BS) with <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> legitimate users on the ground in the presence of a passive eavesdropper (<inline-formula> <tex-math notation="LaTeX">$Eave$ </tex-math></inline-formula>). Direct links between the ground BS and both the ground users and the eavesdropper are assumed to be blocked. The ground-to-air and air-to-ground channels are assumed to follow Rician fading model with opportunistic scheduling scheme for UAVs and users selection. In order to secure data transmissions against such an interception action, the UAV of the worst UAV-selected user link transmits a jamming artificial noise (AN) signal to degrade <inline-formula> <tex-math notation="LaTeX">$Eave$ </tex-math></inline-formula> ability in decoding the confidential information successfully. The transmission outage probability, intercept probability, and hybrid outage probability are derived and analyzed. Due to the heavy computation burden raised by increasing the number of UAVs and users as well as the difficulty in estimating the instantaneous channel state information (CSI), existing traditional optimization methods are not highly efficient in solving the considered power allocation problem. Therefore, we propose a dynamic power control scheme based on Q-learning algorithm combined with statistical CSI where the hybrid outage probability is minimized. Simulation results show that the proposed algorithm efficiently reduces the hybrid outage probability with a noticeable reduction in the computational time.
Probing the orientation of β-lactoglobulin on gold surfaces modified by alkyl thiol self-assembled monolayers

The adsorption of a globular protein on chemically well controlled surfaces was investigated in order to correlate its orientation to the surface properties. To this end, three different alkyl thiols, differing by their end group (-COOH, -CH3, and -NH2), were used to build up self-assembled monolayers (SAMs) on gold substrates. β-Lactoglobulin (βLG) was then adsorbed on these SAMs by immersion in a phosphate buffer solution. The surface modification with alkyl thiols and the subsequent adsorption of proteins were characterized ex situ by polarization modulated infrared reflection-absorption spectroscopy (PM-IRRAS) and X-ray photoelectron spectroscopy (XPS). The adsorption behavior of proteins was also monitored in situ using quartz crystal microbalance with dissipation measurements (QCM-D). Direct evidence regarding the protein orientation in the adsorbed state was obtained by means of time-of-flight secondary ion mass spectrometry (ToF-SIMS). Principal component analysis (PCA), performed on the ToF-SIMS results, enables to separate the samples and shows that the proteins display different distributions of amino acids at the surface depending on the conditioning thiol layer. Our results revealed that the adsorption mode of the protein is influenced by the thiol end groups, and specific orientations of the protein on the surface are proposed for the different substrates. © 2013 American Chemical Society.
Improving the activity recognition using GMAF and transfer learning in post-stroke rehabilitation assessment

An important part of developing a performant assessment algorithm for post-stroke rehabilitation is to achieve a high-precision activity recognition. Convolutional Neural Networks (CNN) are known to give very accurate results, however they require the data to be of a specific structure that differs from the sequential time-series format typically collected from wearable sensors. In this paper, we describe models to improve the activity recognition using the CNN classifier. At first by modifying the Gramian angular field algorithm by encoding all the sensors' channels from a single time window into a single 2D image allows to map the maximum activity characteristics. Feeding the resulting images to a simple 1D CNN classifier improves the accuracy of the test data from 94% for the traditional segmentation approach to 97.06%. Subsequently, we convert the 2D images into the RGB format and use a 2D CNN classifier. This results in increasing the test data accuracy to 97.52%. Finally, we employ transfer learning with the popular VGG_16 model to the RGB images, which yields to improving the accuracy further more to reach 98.53%.
Current Crowding and Stress Effects in WCSP Solder Interconnects: A Simulative and Practical Study about the Effects of Major Electromigration Failure Mechanisms in DC and Pulsed-DC Conditions

Electromigration (EM) induced failure is inevitable in wafer-level chip scale package microelectronic packages (WCSP), especially with the implementation of lead-free solders. Many factors contribute to EM failure such as joule heating and current crowding. EM can induce void formation, which can eventually lead to open-circuit failure. Due to its nature, EM is a critical failure concern to the microelectronic industry and can be influenced by current conditions. This study examines the failure mechanisms in solder joints implemented in WCSP packages in Direct Current (DC) and DC-pulse current conditions with varying Duty Factors (DF). DF represents the on-off time for DC to flow through the device under test (DUT). Further, a transient simulative study using finite element method (FEM) explores the failure mechanism and investigates the stress development with DC and DF conditions. Findings suggested that a lower duty factor yielded longer time to failure (TTF). Meanwhile, higher pulsed DC DF yielded a lower TTF than DC. This study aims to explain the failure mechanism with each DF. This study aims to explain this phenomenon and suggests the need for further exploration.
Giant Piezoelectricity of Janus M₂SeX (M = Ge, Sn; X = S, Te) Monolayers

It is found that many two-dimensional materials are easy to obtain out-of-plane piezoelectric properties because of their Janus structure. Here, based on the monolayer GeSe and SnSe, we study the electronic structure and piezoelectricity of the Janus M2SeX (M=Ge, Sn; X=S, Te) monolayers. Due to the lack of inversion symmetry and mirror symmetry, as well as flexible mechanical properties, the 2D Janus M2SeX monolayers have large in-plane piezoelectric coefficients d11 (up to 345.08pm/V) and out-of-plane piezoelectric coefficients d31 (up to 3.83pm/V). All energy band structures of two-dimensional (2D) Janus M2SeX monolayers show indirect bandgap and Zeeman-type spin splitting after considering spin orbit coupling (SOC). The lack of mirror symmetry leads to out-of-plane spin polarization. In addition, the calculation based on the deformation potential theory shows that the 2D Janus M2SeX monolayers have high carrier mobility. The large piezoelectric properties and high carrier mobility show the application potential of 2D Janus M2SeX monolayers in flexible electronic devices and piezoelectric devices.
Reduction of aromatic nitro compounds catalyzed by biogenic CuO nanoparticles

Synthesis of CuO nanoparticles using the peel of Musa balbisiana and its application in reduction of nitro aryl compounds are reported here. CuO nanoparticles were characterized by using XRD, XPS, PL, SEM and TEM techniques. In XRD analysis, significant peaks appeared at 18.3, 24.4, 33.6, 34.6, 35.2, 38.2 and 42.7 respectively. The BET surface area and total pore volume of CuO were found to be 7.479 m2 g−1 and 0.1259 m3 g−1, respectively. The generated CuO nanoparticles exhibited interplanar lattice fringe spacings of 0.16 nm. SEM images indicate the formation of flower-like CuO architecture. The hierarchical CuO architecture is found to be made up of nanosheets which were self assembled to form flower-like nanostructures. The synthesized CuO nanoparticles show efficient catalytic activity in reduction of nitro aryl compounds to corresponding amino compounds with a high yield of conversion (74–96%). The reaction was carried out in a green solvent i.e. water. The catalyst was found to be active for several runs. It was further confirmed by several pieces of experimental evidence.
EMG & EIMG measurement for Arm & Hand motions using custom made instrumentation based on Raspberry PI

Recording and processing physiological signal that give intrinsic characteristics information is one of scientific community needs. Electromyography (EMG) and Electrical Impedance Myography (EIMG) are both non-invasive approaches to measure and evaluate the muscle conditions and activity. Z-RPI device is a custom-made measurement device developed basically for ECG and ICG records. This paper presents the feasibility of acquiring surface EMG and EIMG signal of biceps and forearm muscle contractions using the Z-RPI device. The results obtained are acceptable, encouraging and converge to literature result. Thus, it shows that the Z-RPI device can be used for relatively several biomedical applications other than the ECG and ICG measurement. For supporting developers in research and engineering education.