Miracle-dz/UniFAR-FTUs huggingface dataset:
A Nonlinearized Lumped-Charge Model for Power Semiconductor Devices

The lumped-charge (LC) technique is widely used to develop simple and physically based power device models for circuit simulators. The existing models, due to the linearization of the diffusion equations in the drift region, have some limitations that impact accuracy and numerical stability. In this work, the carriers’ transport equations, rather than linearized, are treated as differential equations, and an LC model that exactly solves the diffusion equations is presented. It improves the accuracy of the traditional models and provides a numerically stable expression of the currents while keeping the same simplicity. Furthermore, the continuity equations are rigorously discretized by means of the box integration method, widely used in finite element device simulators, which has been proven to be numerically stable and accurate. The new model is verified both on the static and transient characteristics of commercial insulated-gate bipolar transistors and power diodes.
Flavan derivatives. XXVIII. Stereochemistry of products synthesized from flav-3-enes and flavanones

Further applications of flav-3-enes for synthesis of flavan derivatives are reported, with discussion of stereochemical aspects. Hydrogenation of three 3-sub-stituted flav-3-enes gave the corresponding 2,3-cis-flavans, viz. (±)-epiafzelechin tetramethyl ether, and (±)-epicatechin pentamethyl ether and pentaacetate. Hydroxylation of 5,7,3',4'-tetramethoxyflav-3-ene with osmium tetroxide gave 5,7,3',4'-tetramethoxy-2,3-trans-flavan-3,4-cis-diol. The trans-trans isomer of this diol proved configurationally unstable towards hot acetic anhydride and sodium acetate, and gave the 2,3-trans-3,4-cis diacetate in addition to the normal trans-trans diacetate. Two 2,4-cis-flavan-4-01s were found to give 2,4-trans-4-ethoxyflavans, and thus resembled flavan-3,4-diols in their solvolytic reaction with ethanol. Meerwein-Ponndorf reduction of flavanone gave 2,4-cis-flavan-4-ol (i.e. the quasi-equatorial alcohol).
Graph-Guided Deformation for Point Cloud Completion

For a long time, the point cloud completion task has been regarded as a pure generation task. After obtaining the global shape code through the encoder, a complete point cloud is generated using the shape priorly learnt by the networks. However, such models are undesirably biased towards prior average objects and inherently limited to fit geometry details. In this letter, we propose a Graph-Guided Deformation Network, which respectively regards the input data and intermediate generation as controlling and supporting points, and models the optimization guided by a graph convolutional network(GCN) for the point cloud completion task. Our key insight is to simulate the least square Laplacian deformation process via mesh deformation methods, which brings adaptivity for modeling variation in geometry details. By this means, we also reduce the gap between the completion task and the mesh deformation algorithms. As far as we know, we are the first to refine the point cloud completion task by mimicing traditional graphics algorithms with GCN-guided deformation. We have conducted extensive experiments on both the simulated indoor dataset ShapeNet, outdoor dataset KITTI, and our self-collected autonomous driving dataset Pandar40. The results show that our method outperforms the existing state-of-the-art algorithms in the 3D point cloud completion task.
High-Speed and High Saturation Power Avalanche Photodiode for Coherent Communication

High-speed/power APDs with novel etched-mesa structure are demonstrated to suppress edge breakdown. With 24μm diameters, they achieve 21GHz bandwidths, 5.5A/W responsivity, and RF saturation power over +5 dBm (10 GHz) under 8mA photocurrent and 0.9Vbr.
Food Sample Preparation for the Determination of Sulfonamides by High-Performance Liquid Chromatography: State-of-the-Art

Antibiotics are a common practice in veterinary medicine, mainly for therapeutic purposes. Sectors of application include livestock farming, aquacultures, and bee-keeping, where bacterial infections are frequent and can be economically damaging. However, antibiotics are usually administered in sub-therapeutic doses as prophylactic and growth promoting agents. Due to their excessive use, antibiotic residues can be present in foods of animal origin, which include meat, fish, milk, eggs, and honey, posing health risks to consumers. For this reason, authorities have set maximum residue limits (MRLs) of certain antibiotics in food matrices, while analytical methods for their determination have been developed. This work focuses on antibiotic extraction and determination, part of which was presented at the “1st Conference in Chemistry for Graduate, Postgraduate Students and PhD Candidates at the Aristotle University of Thessaloniki”. Taking a step further, this paper is a review of the most recent sample preparation protocols applied for the extraction of sulfonamide antibiotics from food samples and their determination with high-performance liquid chromatography (HPLC), covering a five-year period.
ShakeReader: ‘Read’ UHF RFID Using Smartphone

UHF RFID technology has become increasingly popular in stores, since it can quickly read a large number of RFID tags from afar. The deployed RFID infrastructure, however, does not directly benefit smartphone users in stores, mainly because smartphones cannot read UHF RFID tags or fetch relevant information. This article aims to bridge the gap and allow users to ‘read’ UHF RFID tags using their smartphones, without any hardware modification to either deployed RFID systems or smartphone hardware. To ‘read’ an interested tag, a user makes a predefined smartphone gesture in front of an interested tag. The smartphone gesture causes changes in 1) RFID measurement data captured by RFID infrastructure, and 2) motion sensor data captured by the user's smartphone. By matching the two data, our system (named <italic>ShakeReader</italic>) can pair the interested tag with the corresponding smartphone, thereby enabling the smartphone to indirectly ‘read’ the interested tag. We build a novel reflector polarization model to analyze the impact of smartphone gesture to RFID backscattered signals. We enhance the basic version of <italic>ShakeReader</italic> [7] by improving its performance in densely deployed scenarios. Experimental results show that <italic>ShakeReader</italic> can accurately pair interested tags with their corresponding smartphones with an accuracy of <inline-formula><tex-math notation="LaTeX">${>}96.3\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>></mml:mo><mml:mn>96</mml:mn><mml:mo>. </mml:mo><mml:mn>3</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="cui-ieq1-3098818.gif"/></alternatives></inline-formula>.
Energy Landscape Investigations Using the Prescribed Path Method in the ZnO System

An important issue in modern solid-state chemistry and nanotechnology is the development of a general methodology to predict possible (meta)stable crystalline and nanocrystalline modifications and to study the possible transition routes among them. To analyze the stability of the various potential modifications and study the possible low energy paths among them, the so-called prescribed path method is employed. This method allows us to explore transition routes and barriers between even distant minima, suggesting possible transition states and specific transition paths for more detailed analysis, as well as to gain more insights into the temperature dependence of the synthesis and transformation processes in the system. In this study, we describe and employ the prescribed path method for the example of the energy landscape of ZnO. The focus is on the influence of the temperature on the transformations along the path and on the stability of the various structures in the ZnO system, such as the wurtzite-, t.
Experimental Determination of Composition-Dependent Diffusivity of Carbon Dioxide in Polypropylene

This work provides the experimentally determined composition-dependent diffusivity of environmentally benign plasticizer such as carbon dioxide in polypropylene. For this purpose, a pressure decay system is employed to determine composition-dependent diffusivity of carbon dioxide in polypropylene at isothermal conditions. On the basis of a detailed mass transfer model, variational calculus is used to establish the conditions necessary to yield the composition-dependent diffusivity that enables the model-predicted mass of absorbed gas in polymer to match with the experimental counterpart. The experimental solubility and composition-dependent diffusivity of carbon dioxide in polypropylene are obtained at (170, 180, and 190) °C for pressures up to 7.32 MPa.
Soviet-Indian Coproductions: Alibaba as Political Allegory

This essay considers the history of Soviet Indian coproductions focusing on Ali Baba and 40 Thieves (1980) as a political allegory over the fate of the multination state. It addresses the formal utopian character of the film and the excessive threat of sexual violence in the song-and-dance numbers.
Optimization of Engineering Design Problems Using Atomic Orbital Search Algorithm

In this paper, optimum design of engineering problems is considered by means of the Atomic Orbital Search (AOS), a recently proposed metaheuristic optimization algorithm. The mathematical development of the algorithm is based on principles of quantum mechanics focusing on the act of electrons around the nucleus of an atom. For numerical investigation, 20 of well-known constrained design problems in different engineering fields are considered; some of which have been benchmarked by the 2020 Competitions on Evolutionary Computation (CEC 2020) for real-world optimization purposes. Statistical results including the best, mean, worst and standard deviation of multiple optimization runs are reported for the AOS algorithm. These results are compared to similar data from previous metaheuristic algorithms found in the literature to establish the efficiency and usefulness of the AOS. It is concluded that the AOS has acceptable behavior in dealing with all the considered constrained optimization problems while the maximum difference of about 40% between the best optimum values of the AOS and other approaches is noted for the robot gripper benchmark problem.
0.5-V High Linear and Wide Tunable OTA for Biomedical Applications

This paper presents a low-voltage nano-power multiple-input operational transconductance amplifier (MI-OTA) with high linearity performance and increased input voltage swing. The enhanced performances are achieved thanks to employing several techniques as the bulk-driven, source-degeneration, self-cascode and negative conductance along with the concept of the input signal attenuation formed by multiple-input MOS transistor. The MI-OTA is widely tunable that serves for biological signals processing. A 3rd-order Butterworth band-pass filter (BPF) for electrocardiogram (ECG) signal processing with 55.8 dB dynamic rang is presented. The MI-OTA circuit is designed for 0.5V voltage supply and offers a 0.22% total harmonic distortion (THD) for 0.2Vpp input signal with total power consumption of 13.4nW. Extensive simulation results including Monte Carlo analysis and process, voltage, temperature (PVT) corners using the $0.18\mu \text{m}$ CMOS technology from TSMC confirm the characteristics of the proposed MI-OTA and the filter.
A Novel Method for Lower Limb Joint Angle Estimation Based on sEMG Signal

Due to the strong dynamic and time-varying characteristics of the surface electromyography (sEMG) signal and the coupling between lower limb muscles, it is challenging to accurately estimate the joint angle of complex lower limb motion. Firstly, we proposed a wavelet packet decomposition correlation dimension (WPD_CD) analysis method. A three-level wavelet packet decomposes the sEMG signal, and the optimal and stable feature vector is extracted by the correlation dimension analysis. A singular spectrum nonlinear autoregressive exogenous model (NARX_SSA) is proposed to map the optimal eigenvector to the lower limb joint angle to improve the angle accuracy and smoothness. The experimental results show that this method only needs to collect three lower limb muscles and accurately estimate four movements of knee and hip angles. The overall RMSE was 0.32, the minimum RMSE was 0.20, and the standard deviation (SD) was 20.23. Compared with other methods, the accuracy of angle estimation was improved by six times, and the smoothness was improved by 13%. Therefore, this method can be effectively applied to the angle estimation of complex lower limb motion patterns.
Adaptive Memory Event-Triggered Observer-Based Control for Nonlinear Multi-Agent Systems Under DoS Attacks

This paper investigates the event-triggered security consensus problem for nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks over an undirected graph. A novel adaptive memory observer-based anti-disturbance control scheme is presented to improve the observer accuracy by adding a buffer for the system output measurements. Meanwhile, this control scheme can also provide more reasonable control signals when DoS attacks occur. To save network resources, an adaptive memory event-triggered mechanism (AMETM) is also proposed and Zeno behavior is excluded. It is worth mentioning that the AMETM's updates do not require global information. Then, the observer and controller gains are obtained by using the linear matrix inequality (LMI) technique. Finally, simulation examples show the effectiveness of the proposed control scheme.
Failure Handling for Time-Sensitive Networks using SDN and Source Routing

We propose a Software-Defined Network (SDN)based approach for ultra-fast recovery of Time Sensitive Networks (TSN) in the case of failure events. We exploit the Source Routing paradigm for explicit path control and the creation of a stateless TSN data plane. We further propose a TSN failure recovery routing heuristic used to minimise link congestion, while we also introduce the concept of TSN subgraphs to quickly reschedule the flows traversing the problematic area. We evaluate our approach using SDN-based Source Routing and Linux-based TSN scheduling integrated into Mininet.
Drought Prediction Based on Feature-Based Transfer Learning and Time Series Imaging

Drought is an extreme climate phenomenon that has a great impact on the economy, tourism, agriculture, and water resources. Drought prediction can provide an early warning of the occurrence of drought and reduce losses. In this article, the standard precipitation evapotranspiration index (SPEI) on four time scales: SPEI-3, SPEI-6, SPEI-9, and SPEI-12 are used to measure and predict drought. Unlike the general methods of directly modeling the SPEI index, time-series imaging and feature-based transfer learning are used to extract the features of the SPEI sequence and use the extracted features for prediction. First, we use Gramian Angular Summation/Difference Field (GASF/GADF), Markov Transition Field (MTF), and Recurrence Plot (RP) as the time series imaging techniques to encode SPEI sequences into images. Secondly, we utilize imaging data sets and convolutional neural networks (CNNs) such as residual network (ResNet) and VGG to train the feature extraction network. Finally, the following four regressors: Random Forest (RF), Long and Short-Term Memory network (LSTM), Wavelet Neural Network (WNN), Support Vector Regression (SVR) are used to model the extracted features and drought prediction. To verify the effectiveness of the method proposed in this article, we use the SPEI of four time scales at eight stations in the Haihe River Basin for prediction. Compared with the existing methods, the prediction results of different time scales and stations are improved. For example, after feature extraction, LSTM can reach MAPE = 0.5400, SMAPE = 0.4452, MAE = 0.2150, MSE = 0.0853 and $R^{2} = 0.8960$ in the SPEI-12 prediction of the Beijing site, and other results show that the proposed method is not sensitive to the time scale of drought prediction.
Incentivizing Opportunistic Data Collection for Time-Sensitive IoT Applications

Urban environments are the most prevalent application scenario for the Internet of Things (IoT). In this context, effective data collection and forwarding to a cloud (or edge) server are particularly important. This work leverages opportunistic data collection based on the mobile crowd sourcing (MCS) paradigm for time-sensitive IoT applications. Specifically, it introduces an incentive mechanism for the crowd to collect data that are valuable to data consumers in terms of regions of interest and time constraints. The proposed approach successfully incorporates the willingness of the crowd to participate in the data collection as part of the related incentives. It also ensures collection of valuable data via selective user incentivization. Accordingly, a weighted social welfare maximization problem is defined for users to decide which sensors to visit subject to deadline constraints. Following the NP-hardness of the problem, an online heuristic algorithm is proposed for sensors to dynamically incentivize mobile users with a low message and time complexity. The proposed solution is shown to be effective for time-sensitive quality data collection through extensive simulations on realistic mobility traces. It significantly increases the overall social welfare as well as the amount of collected data compared to other approaches.
Series Loss-Free Resistor: Analysis, Realization, and Applications

An analysis of the transient behavior of dc networks consisting of voltage sources, capacitors, and series loss-free resistors (SLFRs) is presented. The realization of an SLFR was achieved by means of a topological variation of the positive output voltage buck–boost converter operated in discontinuous-conduction mode. It is demonstrated that even simple RC circuits containing SLFRs exhibit behavior that is described by Abel nonlinear differential equations, which do not have an exact analytical solution. Some possible applications of the SLFRs in power electronics, dc microgrids, and renewable energy power systems include loss-free charge and discharge of capacitor banks, voltage equalization of capacitors, and loss-free voltage clamping circuits. The concept of the SLFR can also be applied for voltage control in dc microgrids, employing the droop voltage technique, equalization of power and current in voltage sources associated in parallel (including batteries and dc–dc converters), and also input and output voltage natural balance in input-series output-series association of dc converters. The theoretical analysis results are validated via numerical examples and computer simulation.
High-Performance In₂O₃-Based 1T1R FET for BEOL Memory Application

In this article, we report high-performance one-transistor-one-resistor (1T1R) FETs for nonvolatile memory application based on nanometer-thick indium oxide (In<sub>2</sub>O<sub>3</sub>) as channel material deposited by atomic layer deposition (ALD). ALD grown hafnium oxide (HfO<sub>2</sub>) and aluminum oxide (Al<sub>2</sub>O<sub>3</sub>) are used as gate dielectrics as well as insulator in resistive part. Two nonvolatile states with different threshold voltages are realized. High <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}} > 10^{10}$ </tex-math></inline-formula> at <inline-formula> <tex-math notation="LaTeX">${V}_{\mathrm {GS}} =0$ </tex-math></inline-formula> V, large memory window (MW) exceeding 10 V, and deep sub-60-mV/dec subthreshold slope (SS) are achieved on ALD In<sub>2</sub>O<sub>3</sub> 1T1R FETs. Channel length (<inline-formula> <tex-math notation="LaTeX">${L}_{\mathrm {ch}}$ </tex-math></inline-formula>) and channel thickness (<inline-formula> <tex-math notation="LaTeX">${T}_{\mathrm {ch}}$ </tex-math></inline-formula>) dependence of device properties are systematically investigated. Optimized In<sub>2</sub>O<sub>3</sub> thickness is determined to 1.2 nm, balancing <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula>, MW, device variation, and stability. The fabrication process has a low thermal budget below 225 °C. Thus, these 1T1R FETs are back-end-of-line (BEOL) compatible and promising for monolithic 3-D integration to realize near-/in-memory computing.
General Formulas for Lightning Impulse Impedance of Horizontal and Vertical Grounding Electrodes

Voltage drop developed between the grounding electrode under lightning current and distant neutral ground determines the protection efficiency. The peak value of such voltage can be computed from known impulse impedance and current peak value. For the first time, in this letter, general formulas are derived for impulse impedance of horizontal and vertical electrodes valid for any length up to 100 m, soil's resistivity of 30 to 1000 Ωm, and current impulse front time of 0.2 to 10 μs. Waveforms of typical lightning impulses given in IEC standards are used, but it is shown that results are also relevant for other impulse waveforms. Soil ionization effects are taken into account, and the accuracy of the formulas is investigated. New formulas enable an estimate of lightning protection grounding's surge efficiency in a wide range of practical situations.
DepFiN: A 12nm, 3.8TOPs depth-first CNN processor for high res. image processing

High resolution pixel processing (PP) tasks like demosaicing, denoising, and super-resolution strongly benefit from Convo-lutional Neural Network (CNN) approaches, yet give rise to different architectural challenges compared to typical classification CNNs, preventing real-time execution on existing SotA CNN processors. The 12nm DepFiN processor is the first processor optimized for a wide range of pixel processing CNNs, innovating 1. ) at system level, by shifting the memory/IO trade-off through line-based extreme layer fusion (depth-first CNN computation); 2. ) at architecture level, by achieving near 100% utilization @3.8TOPs, even on traditionally challenging depthwise (DW)-pointwise (PW) and ShiftNet layers, through an optimized dataflow for high resolution PP; 3. ) at gate level, by drastically reducing switching activity through improved register file (REGF) and Multiply-Accumulate (MAC) interfacing.DepFiN brings high-resolution pixel processing to mobile platforms by achieving up to 3.8 TOPs and 20 TOPs/W, e.g. enabling 2x super-resolution to with the FSRCNN network while limiting off-chip IO to 3.2M features/inference.
Doppler Flow phantom Stability Assessment through STFT Technique in Medical PW Doppler: a preliminary study

Nowadays, a generally accepted standard for Doppler phantom performance assessment is lacking. In this regard, the present study is a first attempt in the definition and detection of the failures that may affect the test object flow stability, resulting in a detriment of the standard reference for Ultrasound (US) Quality Assessment (QA). As a consequence, a novel objective algorithm for the flow velocity stability assessment of flow test objects is proposed. Such image analysis algorithm is based on the application of the Short Time Fourier Transform (STFT) technique to Pulsed Wave (PW) Doppler spectrograms. Firstly, it has been tested on simulated velocity signals in which phantom failures have been added: (a) high velocity pulses deriving from the particle agglomerates of the Blood Mimicking Fluid (BMF) and (b) low frequency oscillations and velocity drifts due to the flow pump performances. Afterwards, it has been applied to real PW spectrograms. Data have been collected at three flow rates from two different flow phantom models, through a single US system equipped with a linear, a phased and a convex array probe. Despite this novel STFT application has revealed itself as a promising tool in the detection of Doppler phantom failures, further tests should be carried out for the optimization of both the algorithm and the test protocol.