Miracle-dz/UniFAR-FTUs huggingface dataset:
Lithospheric flexure and the evolution of sedimentary basins

The sediments that have accumulated in sedimentary basins during geological time represent a load on the lithosphere that should respond by flexure. Simple elastic and viscoelastic (Maxwell) plate models have been used to examine quantitatively the contribution of flexure to basin formation. The models have been used to predict the stratigraphy and gravity anomalies associated with basins for different thermal and loading histories. The predictions of the models have been compared with observed stratigraphy and free-air gravity anomalies from interior and cratonic basins. The best overall fit to the observations is for an elastic plate model in which the flexural strength of the lithosphere increases with age. A similar model has recently been used successfully to explain observations from continental margin basins, oceanic islands and seamounts, and deep-sea trench - outer rise systems. This model explains the increase in the overall width of basins during their evolution as well as the stratigraphy of the basin edges. The apparent decrease in the widths of some basins through time can be explained by the model if sediment deposition is followed by erosion of the basin and its edges. The models results suggest that the flexural properties of continental and oceanic lithosphere are generally similar and that flexure is an important factor to consider in backstripping studies in which the tectonic subsidence of a basin is isolated and stratigraphic studies in which relative changes of sea level are estimated.
A MPI Parallel DGTD Method with Local Time Stepping Technique

This paper proposed a MPI parallel algorithm of discontinuous Galerkin time domain method (DGTD) with local time stepping technique. In order to solve large multi-scale electromagnetic problems with large-scale CPU cores, two-layer parallel transmission and sparse matrix storage format are used to reduce the time of preprocessing. In time stepping procedure, the persistent non-blocking MPI communication method is adopted to overlap the communication and calculation to improve parallel efficiency. Numerical results are given to demonstrate good performance of the proposed method up to 30,000 cores.
Near-Field Dual-Polarized Feedback Technique for Linearity Enhancement of 5G Millimeter-Wave Phased Array

This paper proposes a near-field dual-polarized feedback (NFDPF) technique for tracking real-time status and improving linearity of 5G RF-beamforming millimeter-wave (mm-wave) phased array. The feedback signal captured by NFDPF can be used for array self-calibration and digital predistortion (DPD). A 2×2 dual-polarized 24.25-27.5-GHz phased array prototype with integrated NFDPF is designed for validation of the scheme. Using NFDPF, four RF chains of dualpolarizations are calibrated which is similar to far-field (FF) calibration. Furthermore, the DPD is applied to validate the performance of feedback structure. Experimental results show that the adjacent channel power ratio (ACPR) and normalized mean squared error (NMSE) can be improved from -40dBc and 28dB to -51dBc and -40dB respectively, which is close to the performance of FF DPD.
Modeling of Phase Noise in Mode-Split Open-Loop MEMS Gyroscopes

This paper investigates demodulation phase noise of an open-loop, mode-split MEMS gyroscope. A method to convert a model of an amplitude-modulated gyroscope into a base-band phase space model is provided. We highlight the importance of holistic phase space analysis and distinguish between well-known oscillator phase noise and, as analyzed in this study, phase noise of the angular rate demodulation. A literature review revealed the most probable noise sources for such a model. We found that any possible phase flicker noise source on the input of the PLL, for example from capacitance-to-voltage converter, analog-to-digital converter or the phase detector, would be transferred to directly become demodulation phase flicker noise. As a result, bias instability would be created. Lastly, we discuss possibilities to experimentally validate the proposed model.
FITrans: Skin Lesion Segmentation Based on Feature Integration and Transformer

Automatic segmentation of skin lesions in dermatoscopic images is of great significance for clinical diagnosis and evaluation of melanoma. Most existing skin lesion segmentation methods overfit the primary visual region in skin lesion images but ignore the edge details. When the boundary of the lesion is blurred and the contrast between the lesion and the background is low, it is difficult to obtain an accurate segmentation. To solve this problem, this paper proposes a network model FITrans that combines multi-level feature aggregation and Transformer. Firstly, the convolution neural network uses additional classification information and boundary information to extract discriminative context and edge features by weakly supervised weight feedback and explicit edge guidance, respectively. Secondly, the model integrates the global-level context features, low-level edge features, and high-level semantic features extracted from the backbone network. The integrated multi-level features can compensate for the shortcomings of single-feature segmentation and enhance the segmentation effect of edge areas. On this basis, the Transformer model codes the serialized integration features, which not only make up for the problem that the Transformer does not make full use of the low-level features, but also extracts rich information on distance dependence between pixels. Combining the multi-level integration features with the Transformer can further enhance the segmentation effect of edge regions. In this paper, FITrans are used to analyze the effect of different levels of features on segmentation, and to verify the validity of multi-level feature integration and distance-dependent information. FITrans achieved 88.6 and 81.7 Jaccard coefficients (JAs) on ISIC2016 and ISIC2017, which exceed the five mainstream skin lesion segmentation methods. The experimental results show that the FITrans model can effectively improve the accuracy of target edge segmentation, and is more helpful for the accurate segmentation of complex skin damage images.
Recent Advances in On-Chip Silicon-based Passive Components for RF and Millimeter-Wave Applications

In this brief, an overview of recently published works related to on-chip passive components will be given. As the full potential of CMOS-based active devices has almost reached, it is more important to start looking into passive-inspired designs, which have a potential to demonstrate the performance of the silicon-based RF circuits beyond Moore's Law. In particular, design of minimized passive components, reflectionless filters and passive/active co-designs will be summarized.
EECAAP: Efficient Edge-Computing based Anonymous Authentication Protocol for IoV

Traditional security solutions for the edge have lots of challenges like high power consumption, communication, and computation overhead. These solutions are not feasible for highly dynamic resource-constrained (memory and processing power) Internet of Vehicles (IoV) networks. We can use Physical Unclonable Functions (PUFs) to address this issue. This paper discusses a new PUF-based anonymous mutual authentication and key exchange protocol for the IoV communication environment by combining unique, unpredictable PUFs and one-way hash functions. In the proposed protocol, a three-layered infrastructure, i.e., vehicle layer, edge computing layer, and cloud layer, is used for the IoV networks to make it efficient and improve the throughput and Quality of Service (QoS). The proposed hybrid system provides a security solution for cloning, side-channel and physical attacks along with the less computation and negligible storage cost. The implementation and performance analysis shows that the proposed protocol reduces the computation-communication overhead maximum upto 80% and 60% respectively. It also reduces the time complexity.
Real Time Congestion Management Using Generation Re-Dispatch: Modeling and Controller Design

Increased power demand, poor transmission infrastructure, and uncertain renewable generation cause congestion in the power network. Traditionally network congestion is cleared by the system operator by rescheduling generators once every 5-20 min, which may be too slow for grids with renewable generation. Network congestion can be cleared automatically and immediately by a controller. The controller can obtain synchrophasor measurements of line power flow and maintain it at the desired value by controlling some generators and battery energy storage systems (BESS) in real-time. This paper develops an accurate dynamic model of the line power flow. A disturbance compensation based Model Predictive Control (MPC) strategy is proposed to regulate the line power flow at or below the desired value, e.g., thermal limit, in real-time by re-dispatching some generators and/or BESS’s. The MPC technique considers several realistic constraints such as output and rate limits and active power balance in the network. The control strategy is validated on Kundur 4-machine 2-area and 16-machine 68-bus test systems and shown to have better performance as compared to the existing technique. It has been found out that the proposed controller successfully regulates the line power flow within 20-60 s by controlling synchronous generators and within a few seconds by controlling BESS’s.
A Backward Business-Oriented Approach of Major Sectors in Emphasizing Sustainable Technological Pillars

With the increase in the Globalization of cutting-edge technologies, it stands to reason that a business approach in every sense is required to make it acceptable across the Globe. Having said that, it’s more often necessary to bring pillars of acceptance in each and every industry. Out of the most, technologies including Internet of Things, Edge Computing, and Cloud Computing are the ones which are being coined a lot to debate on sustainability grounds. In this paper, we present major sectors which reflect the need for accessibility, adaptability, reliability, cost-effectiveness, and scalability for seeking exponential growth on sustainability grounds. The widespread use of mentioned technologies brings challenges in architecting secured infrastructure. Additionally, this study presents a business-oriented approach for a secure-based architecture around the sectors including communication, transportation, healthcare, and environment. Finally, this study revolves around proposing a comprehensive approach to analyze the mentioned technologies from an altogether different business perspective to ensure their functioning in the long run.
IMpart: A Partitioning-based Parallel Approach to Accelerate Influence Maximization

Influence maximization (IM) is a fundamental operation among graph problems that involve simulating a stochastic diffusion process on real-world networks. Given a graph G(V, E), the objective is to identify a small set of key influential "seeds"— i.e., a fixed-size set of k nodes, which when influenced is likely to lead to the maximum number of nodes in the network getting influenced. The problem has numerous applications including (but not limited to) viral marketing in social networks, epidemic control in contact networks, and in finding influential proteins in molecular networks. Despite its importance, application of influence maximization at scale continues to pose significant challenges. While the problem is NP-hard, efficient approximation algorithms that use greedy hill climbing are used in practice. However those algorithms consume hours of multithreaded execution time even on modest-sized inputs with hundreds of thousands of nodes. In this paper, we present IMpart, a partitioning-based approach to accelerate greedy hill climbing based IM approaches on both shared and distributed memory computers. In particular, we present two parallel algorithms— one that uses graph partitioning (IMpart-metis) and another that uses community-aware partitioning (IMpart-gratis)— with provable guarantees on the quality of approximation. Experimental results show that our approaches are able to deliver two to three orders of magnitude speedup over a state-of-the-art multithreaded hill climbing implementation with negligible loss in quality. For instance, on one of the modest-sized inputs (Slashdot: 73K nodes; 905K edges), our partitioning-based shared memory implementation yields 4610× speedup, reducing the runtime from 9h 36m to 7 seconds on 128 threads. Furthermore, our distributed memory implementation enhances problem size reach to graph inputs with ×106 nodes and ×108 edges and enables sub-minute computation of IM solutions.
Metasurface-Loaded Wideband Transmission Structure with Inherent Common-Mode Suppression and Reflectionless Differential-Mode Band-Notch

Novel metasurface loaded wideband differential transmission structure is proposed with reflectionless band-notch response for differential-mode (DM) and inherent suppression for common-mode (CM). The proposed differential transmission structure is constructed by two balanced microstrip structures and a long slot transmission line with two open terminals. Owing to the mode mismatch between CM and slot mode, the inherent CM suppression is realized. Furthermore, a resistor-free absorptive metasurface composed of split-ring resonator cells is introduced above the slot transmission line. Under DM excitation, the resonance of metasurface could be excited effectively by slot transmission line, which would contribute to the enhancement of conductor and dielectric losses around resonant frequencies. Therefore, reflectionless band-notch response is achieved for DM based on inherent conductor and dielectric losses without lumped resistors loading. Simulation results show that the proposed wideband differential transmission structure exhibits inherent CM suppression and reflectionless band-notch response for DM from 5.22 to 6.05 GHz (Sdd21<-10 dB, Sdd11<-10 dB).
Spectral Efficiency Analysis for a Spike-Based Pulse Repetition Frequency Modulation Scheme

The massive employment of wireless sensor systems and an increasing number of mobile sensors in the Internet of things (IoT) calls for highly energy-efficient designs for sensor edge nodes. In prior work a sensory system operating in the analog spike domain for sensing and communication was presented where the sensed information is encoded entirely in the pulse repetition frequency (PRF). Such a PRF modulation is also envisioned for joint communication and radar sensing. In this regard, the question on the spectral efficiency arises that is achievable with an end-to-end spike-based PRF modulation and how it compares to the related frequency-shift keying (FSK). Thus, in the present paper we perform a numerical evaluation of the spectral efficiency of PRF modulation considering two receiver architectures. One being a receiver design using a conventional analog-to-digital converter (ADC) while the other one uses an integrate-and-fire time encoding machine (IF-TEM) for sampling. Furthermore we describe an algorithm that selects PRFs that are easily distinguishable at the receiver. Our results show that PRF modulation provides the low spectral efficiencies required for the considered sensor node application, while allowing for end-to-end spike-based signaling covering the whole processing chain from the sensor edge node to the base station receiver. Moreover, the gained insight can be used to identify which spectral efficiency requirements spike-based PRF modulation can meet and for which applications this modulation scheme is a new contender.
Utilizing the L-PSJA for controlling cylindrical wake flow

Purpose – The cylindrical wake flow is an important part of many engineering applications, including wake turbulence, acoustic noise, and lift/drag forces on bodies. The suppression of von Karman vortex street (VKS) is an important goal for flow control devices. The paper aims to discuss these issues. Design/methodology/approach – The linear plasma synthetic jet actuator (L-PSJA) is utilized as a flow control device to suppress the VKS formation. Different configurations of the device is studied numerically. Findings – Of the 12 configurations that were investigated, five configurations were able to suppress the formation of the VKS. Originality/value – For the first time, the L-PSJA has been shown (through numerical simulations) to be able to suppress VKS.
Large Amplitude Linear Drive Quadruple Mass Gyroscope

Coriolis vibratory gyroscope drive amplitude of 16 $\upmu\mathrm{m}$ is demonstrated with $+30$ ppm frequency shift nonlinearity. Here, MEMS quadruple mass gyroscope (QMG) mechanical flexures are specifically designed to separate spurious modes without affecting linear operation of gyroscope drive over large amplitudes. A simulated frequency change of $+480$ ppm was initially predicted, however, when electrostatically driven at large amplitudes comb drive and sense tips begin to introduce spring softening reducing nonlinearity to $+30$ ppm. Careful consideration was also taken to electrostatically tune as-fabricated frequency mismatch without further exacerbating nonlinearity. Angle random walk (ARW) versus drive amplitude is plotted with a demonstrated $8\times$ improvement compared to similar quadruple mass gyroscopes.
A DC to 4GHz Limiter Based in a 0.5um GaAs pHEMT Process

A DC-4GHz limiter is presented in this paper. The anti-parallel diode structure is employed as the core unit of the limiter. The second stage is designed further to limit the power leaked from the previous stage. Snake-shape line is used in the layout routing to reduce the area of the proposed limiter. The limiter is designed and fabricated in a 0.5 μm GaAs process. The measurement results show that the small signal insertion loss is of -0.1dB and the input/output return loss are both less than -20dB in the operating frequency band. The chip area is 1.12mm*0.7mm.
A Physics-Based Model and Its Solution Methodology for Hysteresis Mobile-Ionic Dielectrics

A physics-based model and its corresponding solution methodology for the mobile-ionic (MI) dielectrics exhibiting charge–voltage (<inline-formula> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>) hysteresis behaviors are proposed based on ion drift-diffusion (IDD) equations coupling with Poisson’s equation. The proposed model captures the dynamic distribution of mobile ions’ concentrations within dielectric along the external electric field. The accuracy of the proposed model is validated by comparing the computed results with the experimental ones. Moreover, to investigate the synaptic characters of MI field-effect transistors (MIFETs), numerical model based on coupled non-equilibrium Green’s function (NEGF), IDD, and Poisson’s equations is also established. Potentiation and depression properties of MIFET are decently reproduced with the proposed model, which are consistent with the experiment results.
SGL and CLOT Algorithms Exhibit Both Near-Ideal Behavior and Grouping Effect

In this paper we introduce a new optimization formulation for sparse regression and compressed sensing, called CLOT (Combined L-One and Two), wherein the regularizer is a convex combination of the $\ell_1$- and $\ell_2$-norms. This formulation differs from the Elastic Net (EN) formulation, in which the regularizer is a convex combination of the $\ell_1$- and $\ell_2$-norm squared. It is shown that, in the context of compressed sensing, the EN formulation does not achieve robust recovery of sparse vectors, whereas the new CLOT formulation achieves robust recovery. Also, like EN but unlike LASSO, the CLOT formulation achieves the grouping effect, wherein coefficients of highly correlated columns of the measurement (or design) matrix are assigned roughly comparable values. It is already known LASSO does not have the grouping effect. Therefore the CLOT formulation combines the best features of both LASSO (robust sparse recovery) and EN (grouping effect). The CLOT formulation is a special case of another one called SGL (Sparse Group LASSO) which was introduced into the literature previously, but without any analysis of either the grouping effect or robust sparse recovery. It is shown here that SGL achieves robust sparse recovery, and also achieves a version of the grouping effect in that coefficients of highly correlated columns belonging to the same group of the measurement (or design) matrix are assigned roughly comparable values.
Mind the gap: A review of simulation designs for Qualitative Comparative Analysis

In a simulation-based analysis of Qualitative Comparative Analysis (QCA), Krogslund et al. (2015) conclude that its performance is suboptimal in several settings. I review their simulation setups and discuss three errors that were made in their analysis. First, the simulations involving inclusion thresholds are overpowered based on a misunderstanding of their role in truth table analyses. Second, the fact that a truth table analysis could exhibit model ambiguity and yield more than one model is ignored. If multiple models are derived from a truth table and they are combined into one, one overestimates the complexity of the models and underestimates their number, making it impossible to retrieve the target model of the simulation. Third, the simulations on the consequences of including irrelevant conditions intermingle sensitivity to overfitting with sensitivity to varying the inclusion thresholds. A reconsideration of KCP’s simulations correcting for the errors confirms some of their findings, but also reveals that some of those errors lead to an underestimation of QCA’s robustness. On a broader level, the review underscores that simulations are useful for the evaluation of QCA, but that simulation designs need to match QCA’s mechanics and principles to produce valid conclusions about its performance.