Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of IL-4 and IL-18 genetic polymorphisms with atopic dermatitis in Chinese children

Background Atopic dermatitis (AD) is a common chronic inflammatory skin disease, adversely affecting nearly 20% of the pediatric population worldwide. Interleukin-4 (IL-4) and interleukin-18 (IL-18) are considered to be involved in the pathogenesis and development of AD. The aim of this study was to investigate the association of IL-4 and IL-18 gene polymorphisms with the susceptibility and severity of AD in Chinese children. Methods Six candidate single nucleotide polymorphisms (SNPs) in IL-4 and IL-18 genes were genotyped through multi-PCR combined with next-generation sequencing in 132 AD children and 100 healthy controls, and all the analyses were performed on blood genome DNA. Results The frequencies of G allele, CG genotype and CG + GG genotype of IL-4 rs2243283, as well as the haplotype IL-4/GTT (rs2243283-rs2243250-rs2243248) were all significantly decreased in AD patients compared with the controls [G vs. C: P = 0.033, OR = 0.59; CG vs. CC: P = 0.024, OR = 0.47; CG + GG vs. CC: P = 0.012, OR = 0.49; GTT vs. CCT: P = 0.011, OR = 0.65]. Moreover, the frequencies of A allele, AA genotype and AG + AA genotype of IL-18 rs7106524, along with the haplotype IL-18/CAA (rs187238-rs360718-rs7106524) were statistically increased in the severe AD patients (A vs. G: P < 0.001, OR = 2.79; AA vs. GG: P = 0.003, OR = 5.51; AG + AA vs. GG: P = 0.036, OR = 2.93; CAA vs. CAG: P = 0.001, OR = 2.86). Conclusions Our findings suggested that genetic variation in IL-4 rs2243283 such as G allele, CG genotype and CG + GG genotype might confer the reduced susceptibility to AD in Chinese children. Furthermore, A allele, AA genotype and AG + AA genotype of IL-18 rs7106524 explored the strong association with severity in Chinese AD children.
Research trends and hotspots of post-stroke cognitive impairment: a bibliometric analysis

Background: Post-stroke cognitive impairment (PSCI) is a major complication of stroke that affects more than one-third of stroke survivors, threatening their quality of life and increasing the risk of disability and death. Although various studies have described the etiology, epidemiology, and risk factors of PSCI, there are a limited number of comprehensive and accurate reports on research trends and hotspots in this field. Therefore, this review aimed to evaluate research trends, hotspots, and frontiers in PSCI using bibliometric analysis. Methods: We screened the literature spanning 20 years in the Web of Science Core Collection: Science Citation Index Expanded (SCI-Expanded) database from 1 January 2003 to 31 December 2022. We included all eligible literature reports based on our comprehensive search strategy, inclusion criteria, and exclusion criteria. The analysis of annual publications, countries/regions, institutions, journals, co-cited references, and keywords was conducted using CiteSpace and VOSviewer, and the hotspots and major findings of PSCI were summarized. Results: A total of 1,024 publications were included in this review. We found that the number of publications on PSCI increased annually. These publications were published in 75 countries or regions by over 400 institutions. Although Chinese institutions had the highest number of publications, their international influence was limited. The United States showed a strong influence in the field. The journal “Stroke” published the most publications (57) with a high impact factor and was considered the most co-cited journal. The most frequently cited references focused on the prevalence, incidence, neuropsychological assessment scales, criteria, and guidelines of PSCI. The strongest citation burst keywords for PSCI were “neurotrophic factor” and “synaptic plasticity”, which were regarded as research focuses and research hotspots, respectively. Conclusion: This review provided a comprehensive summary of the literature of PSCI, identified the authoritative and frequently cited literature and journals, clarified the trends in PSCI research, and highlighted the hotspots in this field. Currently, studies on the mechanisms and treatment of PSCI are limited, and we hope that this review has effectively highlighted the research trajectory of PSCI and will lay the foundation for more innovative research in the future.
Similarity Measure based 16X16 MB Mode Decision in H.264 Intra prediction

A lot of computational power is needed for the intra prediction procedure in the H.264 video encoder. A reconfigurable similarity-based intra prediction method for the H.264 video encoder is thus presented in this paper. The analysis of similarity-based intra-prediction algorithms for H.264 yields a total of five distinct similarity approaches, including sum of absolute differences, sum of squared differences, Hamming distance, Euclidean distance, and cosine similarities. The post-analysis shows that using Hamming distance for similarity-based intra prediction allows for less power and hardware usage, with predicted similarity ranging between 78% and 88%.
Strength development of blended blast-furnace slag-cement mortars

Abstract Blast‐furnace slags cooled at different rates were used to study the effect of fineness, mixing method and content of slag on the strength development of blended‐slag mortar. Activator and curing temperature were used to activate the early strength. The microstructure of blended‐slag paste was also investigated in this study to explain the strengthen effect.
Advanced GaN IPM for High-Frequency Converter Applications Enabled with Thin-Substrates

Extracting the potential of Wide Bandgap (WBG) semiconductor devices needs enhanced electrical and thermal packaging. This paper presents a half-bridge GaN-based Integrated Power Module (IPM) with inclusive gate drivers, driver caps, and decoupling caps for a 500kHz/0.8kW converter application. Presented are the design, fabrication, and experimental characterization of a dense, double-side cooled IPM utilizing an advanced epoxy-resin insulated metal substrate (eIMS) with 120µm thin dielectric for 400V/ 8.3ns high edge-rate switching (i.e. with $dv/dt$ of highest frequency of interest (HFI)). The common mode (CM) capacitance has been optimized. The thermal performance of the module was validated through ANSYS simulation, and the symmetry of the sandwiched substrate structure ensured for symmetric temperature distribution and stress management. An experimental Double Pulse Test (DPT) board with low isolation capacitance was developed to characterize the maximum dynamic performance. Finally, the CM effects on a full-bridge converter application are evaluated to show the efficacy of thin-substrate packaging for application at industrial power levels.
A Build-in Gate Driver Design for 1.7kV SiC MOSFET Module with 32-chip Paralleled

Improving current capability of SiC MOSFET is an essential topic for SiC applications. Modular package is a widely applied solution with outstanding power density and integration merit. More dies are paralleled into one module to improve power density, and an auxiliary circuit, like a gate driver, is packaged inside to enhance integration. In this paper, a built-in gate driver is designed to drive a 1.7kV/1.6kA, 32-chip paralleled SiC MOSFET module. To realize the desired feature of the module, corresponding design considerations of the gate driver are discussed. Firstly, the parameters related to driving capability are figured out following a design procedure. Secondly, the delay effect in a transmission line is discussed, and a model is built to analyze the gate-to-source voltage mismatch among dies assembled at different positions. A differentiated threshold voltage strategy for arranging and selecting dies is applied to cancel mismatches. Finally, double pulse test experiments prove the feasibility of the proposed gate driver and corresponding design methods.
Transfer Learning Based Intrusion Detection System for Power Grids with Few Shots

Recent years have witnessed an increasing number of cyber attacks on power grids. It is of paramount significance to effectively detect such cyber attacks before any countermeasure is initiated. However, conventional intrusion detection systems (IDSs) can usually effectively detect known cyber attacks with sufficient attack samples in hand, but often inefficient for cyber attacks with only a few shots or even unknown cyber attacks. To meet this gap, this paper proposes a novel transfer learning based intrusion detection system, called TL-IDS, for power grids, especially under few shots occasions. Specifically, we first design a LeNet-based pre-training model with sufficient attack samples. Then, we develop a transfer learning based intrusion detection model for power grids with only a few shots. Last, extensive experiments show that the proposed TL-IDS can effectively detect cyber attacks on power grids under few shots occasions, and additionally, is capable of identifying certain types of unknown cyber attacks.
Vehicle Information Storage Container with Video Recovering

Automobiles and advancing technologies have created a new level of data services in vehicles. The accident of the vehicle means an unexpected event that may cause damageto the body of the vehicle or of a passenger. The main goal of this Black Box project is to use a method to store vehicle accident data (in case an accident occurs), in which image data is takenby an ESP 32 camera while driving and the data is stored in real-time. In this suggested prototype, in order to connect the sensors and communication devices, Arduino uno microcontroller is used. The GPS work is to retrieve info on the whereabouts of the area. The texts regarding the accident information are sent to the respective person's caretakers by GSM.
Research on Harmonic Compensation Control Strategy Considering Capacity Limitation of PV Grid-connected Inverter

In this paper, a harmonic compensation control strategy based on a PV inverter is proposed to implement in PV inverter with active filtering functions. In addition, the strategy considers the capacity limitation of the inverter, simplifies the control system design, and optimizes the implementation of a PV grid-connected inverter with an integrated active filtering function. Firstly, the theoretical basis for the integration of active filtering function in PV grid-connected inverters is clarified, and the performance differences of different harmonic detection methods and the tracking performance differences between quasi proportional resonant (QPR) control and vector resonant (VR) control for specific harmonics are compared and analyzed. Secondly, the harmonic compensation strategy considering the inverter capacity limit is proposed for the problem of inverter capacity exceeding the limit, and the command current synthesis method and the control loop design scheme are further proposed. The proposed harmonic compensation strategy effectively suppresses harmonics while ensuring the safe and stable operation of the inverter. Finally, the effect of the proposed harmonic compensation control strategy on harmonic current suppression is verified by simulation in Matlab/Simulink, and the simulation results prove the effectiveness of the proposed control strategy.
A Novel Two-Degrees-of-Freedom Current Controller Based on Virtual Impedance for Grid-Connected Inverters under Unbalanced Conditions

This paper proposes a novel current controller for three-phase grid-connected inverters under unbalanced conditions, which is based on the series virtual impedance algorithm. Unlike the conventional methods, the transformation of unbalanced current to positive and negative sequence components is not required. Thus, the current controllers are only two, considering the controller is applied in the d-q synchronous reference frame (SRF). Here, the current controller regards unbalance as disturbance, so current reference and disturbance suppression responses can be separated. By doing separation, the controller has two degrees of freedom, meaning the suppression of disturbance does not affect the reference response. Simulation and experiments have been done to justify the effectiveness of the proposed method, which can suppress the current unbalance factor from 23.33% to 0.13 % and current THD from 8.9 % to 3 %.
Neural Network Modeling of Antennas on Package for 5G Applications

The design and optimization of microwave devices require rigorous electromagnetic (EM) analysis requiring excessive computational resources. To mitigate this, neural network based machine learning methods can be used to generate surrogate models for EM performance analysis. In this study, we constructed a spectral transposed convolutional neural network model for a microstrip patch antenna printed on a package. The model takes geometrical parameters and material properties of the antenna as inputs and generates S11 parameter within the band of 23-33 GHz as output. The results showed a very good correlation between simulations and predictions. This verifies that NN based models can be used for EM analysis of antennas, particularly at the earlier stages of a design process.
Research on Low-voltage Ride-through Control Strategy of VSG under Symmetrical Grid Fault

By simulating the properties of synchronous generators (SG), the virtual synchronous generator (VSG) makes the converter have the inertial damping characteristics of SG and plays an essential role in improving the system inertia and supporting the grid voltage. However, when the grid voltage falls, VSG will face risks such as power angle divergence and overcurrent, resulting in generator disconnection and affecting the system's security and reliability. To solve the above problems, a VSG LVRT strategy with instantaneous power angle control and virtual impedance switching is proposed, which takes full advantage of VSG's flexible and controllable advantages. The proposed method can effectively control the power angle during fault and guarantee synchronous system stability. Virtual impedance is used to restrain the short-circuit current to prevent the risk of over-current and output reactive current to help restore grid voltage. Finally, the proposed LVRT control strategy is verified by using Matlab/Simulink.
A Gate Driver IC for GaN-Based Synchronous Buck Converter with A Double-Sided Adaptive Dead- Time Generator

This paper proposes a gate driver IC for a GaN-based synchronous buck converter with a double-sided adaptive dead-time generator (DTG) to improve the converter efficiency with conventional fixed or single-sided DTG. It contains two main sub-blocks such as the phase error detector (PED) and the coarse/fine controllers. Applying the edge detection principle, the proposed dead-time control can minimize the dead-time and reverse conduction loss on both edges of the switching voltage, Vx, of a 1MHz 12 V to 5 V buck converter using e-mode GaN devices for 0.2 to 1 A load current range. The designed IC is fabricated with TSMC 0.18 µm HVG2 process. According to the post-simulation, the minimum dead time at 1 A load current is 28 ps. Compared with a 10 ns fixed DTG and single-sided DTG, efficiency is improved by 10% and 6%, respectively.
Implant Antenna Reconfigured by Engineered Skeletal Muscle Tissue

Synthetic biology opens new research opportunities for a brand-new generation of sensing systems and devices. With advancements in this area, it is now possible to realize living devices that can undertake sensing at a molecular level. However, the utilization of these devices inside the human body has never been achieved. Moreover, the wireless transfer of the data that the living devices collect remains an open challenge. This work presents a novel bio-hybrid implant that can achieve molecular sensing and wireless communication. The implant consists of an in-body antenna and skeletal muscle tissue. The skeletal tissue is engineered to contract in the presence of molecules of interest. The implant antenna is designed around the engineered tissue to be mechanically deformed as the contraction takes place. This deformation changes the resonance behavior of the implant antenna, which is detected by an on-body antenna. The proposed sensing system is novel in integrating engineered living cells with an implant antenna for wireless real-time monitoring of chemicals in-vivo, as well as a novel in the utilization of skeletal muscle tissue for bio-sensing.
Identifying Abnormal Corporate Financial Data Based on the Comparison of SVM and Logistic Algorithms

With the continuous development of Chinese market economy, Chinese enterprises are facing more and more complicated and fierce challenges if they want to get new opportunities for development in the market. In the market economy environment, the competition between enterprises is fierce. This paper aims to study the abnormal financial data identification based on SVM and Logistic algorithm. Through the research results of SVM, Logistic algorithm and financial identification index at home and abroad, the idea of constructing this model is clarified. In the construction of the enterprise financial abnormal data identification model, 90 enterprises as research objects to identify financial anomalies. The experimental results show that the recognition results are stable and the accuracy is high with SVM modeling, but the accuracy is decreased after the addition of non-financial data. Compared with SVM, Logistic has a lower accuracy in this problem.
Developing a Climbing Assistive Exoskeleton*

This paper presents a design of a climbing assistive exoskeleton (CAE) that reduces stress and strain on the fingers of a climber. Climbers routinely must support their entire body weight with their fingers. While human hands can accommodate climbing, experienced climbers are continuously testing the limits of their bodies, and hand injuries are both a frequent and severe occurrence. This device will help injured mountain climbers to continue training with reduced impact to their hand, and in turn increase climbing endurance and duration. Inexperienced climbers can also benefit from the device as they suffer from a lack of finger and hand muscle mass. This device will aid them in training safely and learn proper grips while developing their strength to be successful. The CAE is a glovelike device which can be slid on over the user's hand while climbing. The exoskeleton will have resistance bands going from the fingertips to the base of the hand, causing the hand to curl. This will create a constant passive force which will reduce the force normally directed through the pulleys and tendons while climbing. In the case of hand opening, the CAE has a motor that should assist the climber to overcome the passive force created by the bands. The glove is controlled through a microcontroller in real-time via feedback from electromyography sensors attached to the forearm of the climber. Our objective is to achieve a 20-40N reduction in force through the fingers while climbing per hand.
Analysis of CP Characteristics By Gain-Bandwidth Product for Metasurface-Based Monopole Antenna

There is a high demand for effective RF front-ends that offers strong circular polarization (CP) features & are feasible from design front with high CP antenna gain, strong radiation, and consistent antenna efficiency at 900 MHz frequency band, in order to properly utilise the RF signals that are present in the ambient RF environment. Thus, CP printed monopole inspired by metasurface reflector is investigated and reported here. It achieves the CP with fractional bandwidth (FBW) of more than 5%, a CP gain of more than 6.8 dBic, and the strong directional radiation pattern with a 3-dB angular beam width of more than 120 degrees with an improved front-to-back ratio (FBR) that is within the allowable bound. Then, the achieved results were then compared to performance trade-offs discovered using cutting -edge technology. Furthermore, a thorough design and analysis are presented for a solution to the problem that the printed monopole antennas frequently encounter in the massive RF-based urban transformation based on 900 MHz for RF energy harvesting application and wireless power transfer transmission.
Decoupling Device for Small Commutation Loop and Improved Switching Performance with Large Power Transistors

Prior work has shown that a power con-verter's commutation loop inductance is critical to switching performance. For designs with surface-mount components, this inductance may be minimized through the use of clever layout techniques. But for many applications, power transistors with large through-hole packages are used, due to their low junction-to-case thermal impedance and compatibility with heatsinks, both of which allow for high power handling capability. In this work, a small surface-mount GaN transistor is added in parallel to the large through-hole Silicon power transistor to improve switching performance. Together with a low-side anti-parallel diode and decoupling capacitor, it forms a smaller commutation loop such that the switching transition can be fast with low overlap loss. A simple method is introduced to control both the power and decoupling devices with a single gate driver. A 250 W, 50 V buck converter is designed, with measured results demonstrating significant improvements in efficiency.
Ambiguity in RMS Delay Spread of Millimeter-Wave Channel Measurements

The root mean square (RMS) delay spread is an important statistical parameter in channel modeling. This paper addresses the ambiguity in the estimation of the RMS delay spread from millimeter-wave (mm-wave) channel measurements, which is caused by the need for a threshold to exclude noise and spurious peaks. An overview of various thresholds used in literature is provided. The suitability of these threshold implementations and methods is investigated by applying them to mm-wave channel measurements. Based on the corresponding results, recommendations are proposed to ease the threshold selection and to enable more consistency in RMS delay spread estimates between different authors. These recommendations include the definition of a noise threshold, a 30 dB multipath threshold and the use of a sample method. The recommendations are derived from mm-wave data, but can also be applied to RMS delay spread measurements at other radio-frequencies.
Accuracy of Rotational and Divergent Kinetic Energy Spectra Diagnosed from Flight-Track Winds

AbstractUnder assumptions of horizontal homogeneity and isotropy, one may derive relations between rotational or divergent kinetic energy spectra and velocities along one-dimensional tracks, such as might be measured by aircraft. Two recent studies, differing in details of their implementation, have applied these relations to the Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft (MOZAIC) dataset and reached different conclusions with regard to the mesoscale ratio of divergent to rotational kinetic energy. In this study the accuracy of the method is assessed using global atmospheric simulations performed with the Model for Prediction Across Scales, where the exact decomposition of the horizontal winds into divergent and rotational components may be easily computed. For data from the global simulations, the two approaches yield similar and very accurate results. Errors are largest for the divergent component on synoptic scales, which is shown to be related to a very dominant rotational mode.
A Broadband Coaxial to Stripline Transition for Millimeter-wave LTCC Circuit Applications

This paper proposes a broadband coaxial to stripline transition for 5G millimeter-wave (mm-wave) band using low temperature co-fired ceramic (LTCC) technology. The proposed structure is specifically designed for Surface-Mount-Device (SMD) coaxial connectors. A back-to-back configuration has been designed and fabricated using a 5-layer LTCC stack and two SMD mini-SMP connectors. Measurements were carried out between 100 MHz and 34 GHz and the results show good agreement with the simulations, with a loss better than 0.7dB for a single transition over the entire range of the operating frequency.