Miracle-dz/UniFAR-FTUs huggingface dataset:
Task Migration and Resource Allocation Scheme in IoV With Roadside Unit

Mobile Edge Computing (MEC) has attracted attention for its short-range and low-latency computing services for the Internet of Vehicles (IoV). However, in the Vehicle-RSU-MEC environment, incomplete task migration is a problem when Vehicle Users(VUs) are moving at high speeds around the Road Side Units (RSUs). Additionally, during peak traffic periods or road congestion, completed tasks compete for MEC server computing resources, leading to load imbalance. Therefore, making reasonable migration and offloading decisions is an important challenge. To address this challenge, the paper proposes a Cooperative Offloading strategy to jointly optimize offloading Decisions and Allocation of computing resources (CODA) step by step. First, to solve the problem of incomplete task migration, CODA proposed a Greedy-Based Task Completion Migration (GBTCM) algorithm. The algorithm calculates the required RSU set for each task to achieve complete migration, and greedily searches for the optimal migration target in the corresponding set to reduce task transmission latency. Second, after completing the task migration, CODA proposed a Distance-Based Computing Resource Allocation (DBCRA) algorithm to achieve load balancing for MEC servers. The algorithm prioritizes distance and finds MEC servers with sufficient computing resources to achieve better load balancing performance. Experimental results have shown that CODA is a low-complexity algorithm applicable to IoV, which can make reasonable and rapid decisions for task migration and offloading. Compared to three other benchmarks, CODA exhibits higher effectiveness and superiority.
RESEARCH OF LOAD SHEDDING ALGORITHM BASED ON MINIMIZING POWER OUTAGE COST

This paper presents the optimal load shedding model based on minimizing power outage cost and observing system safety and stability restriction during power shortage. With equation restriction and inequation restriction, this model belongs to optimal power flow. A novel optimization algorithm for the model is also presented. Applying improved approximate programming method, optimization is done in the control variable space. Through the sensitivity equation of status variable to control variable, the system objective function and restriction can be linearized at the starting feasible operation point, the control variable can be amended using linear programming method which is simplified by active restriction identifying, the new operating point can be obtained by solving power flow equation. The process is iterated until the operating point converges at the optimal solution. Also, the proposed method has been validated on IEEE 14-bus test system and IEEE 30-bus test system.
Multiwavelet-based ECG compressed sensing with samples difference thresholding

– This paper introduces a novel Multiwavelet-based hybrid method of Compressed sensing (CS). A case study of CS and reconstruction of Electro Cardio Diagram (ECG) signals with the presented method was performed. For ECG signals the proposed method does not require a wave position detector and can reconstruct the signal with minimal DC offset error. The method is completely patient-agnostic and does not require prior patient-specific information as well. The proposed method was evaluated using the MIT-BIT database. The obtained results show a good reconstruction quality while keeping a high compression ratio.
14 nm FinFET low-power single port SRAM with power-gating and multi-VDD

SRAM occupies the main area of SoC, its power consumption performance become crucial. Low power SRAM is widely used in IOT device. Power-gating circuit can help SRAM hold low static power during non-read/write period, and multi-VDD using different voltage thresholds in different modules can help SRAM acquire low dynamic power. Read-Write assistant circuit composed by NMOS capacitor helps SRAM read and write faster than before to gain a fast timing performance, and it helps SRAM get the feature of low Vmin and DRV. This design in single port SRAM was tape-out by 14nm FinFET process, and it was verified by ADVANTEST V93000 test platform. The all test result of Vmin, current and data retention voltage meet the single port SRAM design requirements.
Decentralized Demand Side Participation in Primary Frequency Control: Assessing the Impact of Response Rates

Increasing renewable energy generation is leading to reduced inertia in electric power systems. This challenges conventional frequency control methods, as frequency deviations become faster and more pronounced. One possible approach to maintaining system frequency within acceptable bounds is using demand-side response complementing current generation-side control strategies. However, evaluating the impact of different control strategies on frequency behavior is needed to compare their performance. This paper presents a set of conventional metrics and proposes a new metric for evaluating frequency behavior in electric power systems, based on a case study in an island power system in San Cristobal, Galapagos. Furthermore, it presents the impact on frequency of different demand-side response strategies that contribute to frequency control and their impact on the used batteries.
Effect of poling time and grid voltage on phase transition and piezoelectricity of poly(vinyledene fluoride) thin films using corona poling

Corona poling was used to create piezoelectric polyvinylidene flouride (PVDF) thin films and the effects of poling time and grid voltage on the electric and physical properties of the samples was studied. Using x-ray diffraction, infrared spectroscopy, and direct measurement of piezoelectricity, the phase transition behaviour and piezoelectric constant of stretched and poled PVDF film was investigated. Results indicate that the poling time and grid voltage have no substantial influence on the phase transition behaviour of PVDF. However, they were found to have a significant effect on the piezoelectric charge constant of PVDF.
Traitement d'images inspiré des processus de réaction-diffusion

We propose a new algorithm inspired by the properties of diffusion processes for image filtering. We show that purely nonlinear diffusion processes ruled by Fisher equation allows contrast enhancement and noise filtering, but involves a blurry image. By contrast, anisotropic diffusion, described by Perona and Malik algorithm, allows noise filtering and preserves the edges. We show that combining the properties of anisotropic diffusion with those of nonlinear diffusion provides a better processing tool which enables noise filtering, contrast enhancement and edge preserving.
Research on Logistic Model in Forecasting Subsidence Single-Point During Mining

In order to reveal the inherent mechanism and patterns of rock and ground movement so as to enrich and develop the theory of mining subsidence,we proposed an approach that using mining subsidence-time curve fitted by the logistic model to predict the mining subsidence.In addition,we selected some cases for model fitting,theoretic prediction,and model test,obtaining good fitting acuraccy,with the relative error being only 8%. Finally,we summarized the regularity of single subsidence,showing that this subsidence has an "S" shape.This model is less in parameter and simple in calculation.So it is of great significance for studying ground movement and deformation.
On the Adaptive Control of Robot Manipulators

A new adaptive robot control algorithm is derived, which consists of a PD feedback part and a full dynamics feedfor ward compensation part, with the unknown manipulator and payload parameters being estimated online. The algorithm is computationally simple, because of an effective exploitation of the structure of manipulator dynamics. In particular, it requires neither feedback of joint accelerations nor inversion of the estimated inertia matrix. The algorithm can also be applied directly in Cartesian space.
An exact solution for a reflection coefficient in a medium having an exponential impedance profile

An exact analytical solution for the plane wave reflection coefficient in an isotropic, constant velocity medium exhibiting an exponential impedance space profile is derived. The analysis includes the effects of discontinuities at both boundaries of the impedance transformer. The derivation is based on an exact differential equation that describes the space evolution of the reflection coefficient along a nonuniform transmission line. Power transmission curves for various cases, including the exact quarterwave case, are presented.
Dual Attitude Representations and Kinematics for Six-Degree-of-Freedom Spacecraft Dynamics

This paper focuses on the development of three newly formed representations of dual attitude and their respective kinematics equations - Dual Classical Rodrigues Parameters, Dual Modified Rodrigues Parameters, Dual Principal Axis and Principal Angle (Dual Principal Rotation Vector). These three formulations are developed by building off of the theories and concepts used with Dual Quaternions and utilizing numerous attitude identities for quaternions to create new identities using dual quaternions and dual attitudes while detailing the process used throughout the derivation. The accompanying dual kinematic equations using these dual attitude parameters are also generated using their respective dual attitude coordinate systems. Furthermore, the new dual attitude representations with their respective, distinct kinematic equations and identities are validated against a simulated 6-DOF rigid body spacecraft control problem to verify equivalency across equations using the dual quaternion as a baseline.
Large-Reynolds-number asymptotic analysis of viscous centre modes in vortices

This paper presents a large-Reynolds-number asymptotic analysis of viscous centre modes on an arbitrary axisymmetrical vortex with an axial jet. For any azimuthal wavenumber m and axial wavenumber k, the frequency of these modes is given at leading order by ω0 = mΩ0 + kW0 where Ω0 and W0 are the angular and axial velocities of the vortex at its centre. These modes possess a multi-layer structure localized in an O(Re−1/6) neighbourhood of the vortex. By a multiple-scale matching analysis, we demonstrate the existence of three different families of viscous centre modes whose frequency expands as ω(n) ∼ ω0 + Re−1/3ω1 + Re−1/2ω(n)2. One of these families is shown to have unstable eigenmodes when H0 = 2Ω0k(2kΩ0 − mW2) < 0 where W2 is the second radial derivative of the axial flow in the centre. The growth rate of these modes is given at leading order by σ ∼ (3/2)(H0/4)1/3Re−1/3. Our results prove that any vortex with a jet (or jet with swirl) such that Ω0W2 ≠ 0 is unstable if the Reynolds number is sufficiently large. The spatial structure of the viscous centre modes is obtained and simple approximations which capture the main feature of the eigenmodes are also provided. The theoretical predictions are compared with numerical results for the q-vortex model (or Batchelor vortex) for Re ≥ 105. For all modes, a good agreement is demonstrated for both the frequency and the spatial structure.
The Secondaries of Solar-Type Primaries. I. The Radial Velocities

We studied for duplicity the 167 F7-G8 IV or V primaries within 25 pc of the Sun according to their Hipparcos parallaxes and between declinations of -30° and +75°. We obtained an average of 13 coudé radial velocities with an accuracy of ±0.10 km s-1. Combining these measures with published data, we obtained 39 single-lined and 12 double-lined binaries with orbital elements. This material will be combined in a later paper with the known visual binaries to derive the secondary mass frequencies.
iDHS-DPPE: a method based on dual-path parallel ensemble decision for DNase I hypersensitive sites prediction

The DNase I Hypersensitive site (DHS) is the chromatin region that exhibits a hypersensitive response to cleavage by the DNase I enzyme. It is a universal marker for regulatory DNA and associated with genetic variation in a wide range of diseases and phenotypic traits. However, traditional experimental methods have limited the rapid detection of DHS as well as its development. Therefore, effective and accurate methods to explore potential DHSs need to be developed urgently. In this task, a deep learning approach called iDHS-DPPE to predict DHSs in different cell types and developmental stages of the mouse. iDHS-DPPE uses a dual-path parallel integrated neural network to identify DHSs accurately. First, the DNA sequence is segmented into 2-mers to extract information. Then, the DHSs accurately-attention model captures remote dependencies and the MSFRN model enables hierarchical information fusion. The dual models are trained separately to enhance the feature information. Finally, the ensemble decision of two models yields the prediction results, enabling the integration of information from multiple views. The average AUC across all datasets was 93.1% and 93.3% in the 5-fold cross-validation and independent testing experiments, respectively. The experimental results demonstrate that iDHS-DPPE outperforms the state-of-the-art method on all datasets, proving that iDHS-DPPE is effective and reliable for identifying DHSs.
A method for patient gait real-time monitoring based on powered exoskeleton and digital twin

Powered exoskeletons are a kind of wearable robotics system attached outside the limbs, providing additional force for the limbs, which plays an important role in limb rehabilitation and patient assistance. As the patient gradually recovers, the patient’s gait will change over time. Therefore, the author hopes to get real-time gait data from patients in order to provide medical guidance and help the patients recover better. Inspired by the real-time monitoring of industrial robots, the author puts forward a method of medical monitoring using digital twin onto powered exoskeletons. For cost reasons, the author uses commercially available sensors to build this system. Further, the author fabricates a demonstration system for the exoskeleton to achieve this goal together with collecting and analyzing the data.
Ozone concentration prediction based on deep neural networks

With the continuous development of urban industrialization, the standard of living of the Chinese people has improved to an unprecedented extent. At the same time, however, it has also brought about adverse consequences such as the deterioration of the air and water environment, which can be said to be an inevitable consequence of the development of the modern industry. Since entering the 21st century, a gas that most people are familiar with, ozone, has become the primary pollutant of air pollution and is also a key target for treatment. To better combat pollution caused by ozone, this thesis proposes an ozone concentration prediction model based on deep neural networks in machine learning. Ozone concentration data and various meteorological factors were collected from ground-based monitoring stations, and a cleaning code was used to remove erroneous data. The final graph of the model training process and the comparison of the predicted actual values show that the model in this experiment predicts ozone concentrations effectively.
Comparison of Pronase versus Manual Dechorionation of Zebrafish Embryos for Small Molecule Treatments

Zebrafish are a powerful animal model for small molecule screening. Small molecule treatments of zebrafish embryos usually require that the chorion, an acellular envelope enclosing the embryo, is removed in order for chemical compounds to access the embryo from the bath medium. For large-scale studies requiring hundreds of embryos, manual dechorionation, using forceps, can be a time-consuming and limiting process. Pronase is a non-specific protease that is widely used as an enzymatic alternative for dechorionating zebrafish embryos. However, whether pronase treatments alter the effects of subsequent small molecule treatments has not been addressed. Here, we provide a detailed protocol for large-scale pronase dechorionation of zebrafish embryos. We tested whether pronase treatment can influence the efficacy of drug treatments in zebrafish embryos. We used a zebrafish model for Duchenne muscular dystrophy (DMD) to investigate whether the efficacies of trichostatin-A (TSA) or salermide + oxamflatin, small molecule inhibitors known to ameliorate the zebrafish dmd muscle degeneration phenotype, are significantly altered when embryos are treated with pronase versus manual dechorionation. We also tested the effects of pronase on the ability of the anthracycline cancer drug doxorubicin to induce cardiotoxicity in zebrafish embryos. When comparing pronase- versus forceps-dechorionated embryos used in these small molecule treatments, we found no appreciable effects of pronase on animal survival or on the effects of the small molecules. The significant difference that was detected was a small improvement in the ability of salermide + oxamflatin to ameliorate the dmd phenotype in pronase-treated embryos when compared with manual dechorionation. Our study supports the use of pronase treatment as a dechorionation method for zebrafish drug screening experiments.
Review of the Application of Microwave Heating Technology in Asphalt Pavement Self-Healing and De-icing

In the past decades, a large amount of research was conducted to investigate the application prospect of microwave heating technology in improving the efficiency of asphalt pavement self-healing and de-icing. This paper reviewed the achievements in this area. Firstly, the properties of asphalt concrete after microwave heating were summarized, including microwave sensitivity and heating uniformity. Then, the evaluation indicators and influence factors of the self-healing properties of the asphalt mixtures heated by microwave were reviewed. Finally, the application of microwave heating in asphalt pavement de-icing was explored. In addition, asphalt pavement aging due to microwave heating was also reviewed. It was found that microwave heating technology has good prospects in promoting asphalt pavement self-healing and de-icing. There are also some problems that should be studied in depth, such as the cost-effectiveness of microwave-sensitive additives (MSAs), the performance of the pavement with MSAs, mechanism-based self-healing performance indicators, and the aging of asphalt pavements under cycling microwave heating.
Application of Dental Pulp Stem Cells for Bone and Neural Tissue Regeneration in Oral and Maxillofacial Region

In the oral and maxillofacial region, the treatment of severe bone defects, caused by fractures, cancers, congenital abnormalities, etc., remains a great challenge. In addition, neurological disorders are frequently accompanied by these bone defects or the treatments for them. Therefore, novel bone regenerative techniques and methods to repair nerve injury are eagerly sought. Among them, strategies using dental pulp stem cells (DPSCs) are promising options. Human DPSCs can be collected easily from extracted teeth and are now considered a type of mesenchymal stem cell with higher clonogenic and proliferative potential. DPSCs have been getting attention as a cell source for bone and nerve regeneration. In this article, we reviewed the latest studies on osteogenic or neural differentiation of DPSCs as well as bone or neural regeneration methods using DPSCs and discussed the potential of DPSCs for bone and nerve tissue regeneration.
Oxygen vacancy and hydrogen in amorphous HfO2

Amorphous hafnium dioxide (a-HfO2) is widely used in electronic devices, such as ultra-scaled field-effect transistors and resistive memory cells. The density of oxygen vacancy (OV) defects in a-HfO2 strongly influences the conductivity of the amorphous material. Ultimately, OV defects are responsible for the formation and rupture of conductive filament paths which are exploited in novel resistive switching devices. In this work, we studied neutral OV in a-HfO2 using ab initio methods. We investigated the formation energy of OV, the binding energy of di-OVs, the OV migration, unperturbed and in the close presence of a hydrogen atom, as well as the migration of hydrogen atom towards OV. A shallow and short-range OV migration barrier (0.6 eV) exists in a-HfO2 in contrast to the barrier (2.4 eV) in crystalline HfO2. Nearby hydrogen has a limited impact on the OV migration; however, hydrogen can diffuse easily by hopping among OVs.
A strain rate dependent and anisotropic failure material model for short fiber reinforced plastics based on energy density accounting for local fiber orientation

A failure model for SFRP for FEM simulations is developed to describe the strain rate dependency, the influence of the local fiber orientation and of the stress state on the failure behavior. The material is considered as a continuum while internally calculating the micro-mechanics analytically. The described micro-mechanics are based on experimental observations and on analyzation with numerical studies. In particular the strain rate dependent delamination of fibers and matrix is incorporated in the model. The distortion energy density is defined as the driving value for failure and estimated by the model. This is achieved with the analytic solution by Eshelby for the stress field in the matrix and by introducing an additional phase for the plasticly deformed volume. The validation on characterization specimens as well as component test demonstrates that the influence of strain rate, fiber orientation, and stress state on the failure behavior can be described with only one material parameter, the critical distortion energy density.
The Removal Performance of Bio-Sorption on Sunflower Seed Husk for Copper and Lead Ions from Aqueous Solutions

This study was concerned with the feasibility of using sunflower seed husk (waste material from the food industry) as a low-cost and available sorbent material to remove copper and lead ions. Sunflower seed husk was used for the biosorption of heavy metal ions (Pb(II) and Cu(II)) from aqueous solutions. The properties of natural adsorbent were characterized using Fourier transform infrared spectroscopy (FTIR). Pb(II) and Cu(II) adsorption were in - vestigated in batch experiments through several influencing operating parameters, including contact time, sorbent dosage, initial pH, and initial concentration. The Pseudo-first-order and pseudo-second-order models were also applied to the experimental data to determine the adsorption kinetics. The results showed that adsorption of both ions fitted well by pseudo-Second-order, with determination coefficient R 2 = 0.99, for both ions with SSE (1.628, 1.345) for Pb(II) and Cu(II), respectively.