Single event effects evaluation on convolution neural network in Xilinx 28 nm system on chip

Convolutional neural networks(CNNs) exhibit excellent performance in the areas of image recognition and object detection, which can enhance the intelligence level of spacecraft. However, in aerospace, energetic particles, such as heavy ions, protons, and alpha particles, can induce single event effects(SEEs) that lead CNNs to malfunction and can significantly impact the reliability of a CNN system. In this paper, the MNIST CNN system was constructed based on a 28 nm systemon-chip(SoC), and then an alpha particle irradiation experiment and fault injection were applied to evaluate the SEE of the CNN system. Various types of soft errors in the CNN system have been detected, and the SEE cross sections have been calculated. Furthermore, the mechanisms behind some soft errors have been explained. This research will provide technical support for the design of radiation-resistant artificial intelligence chips.

基于SABO-GRU-Attention的锂电池SOC估计

提出一种基于SABO-GRU-Attention(subtraction average based optimizer-gate recurrent unitattention)的锂电池SOC(state of charge)估计方法。采用基于平均减法优化算法自适应更新GRU神经网络的超参数,融合SE(squeeze and excitation)注意力机制自适应分配各通道权重,提高学习效率。对马里兰大学电池数据集进行预处理,输入电压、电流参数,进行锂电池充放电仿真实验,并搭建锂电池荷电状态实验平台进行储能锂电池充放电实验。结果表明,提出的SOC神经网络估计模型明显优于LSTM、GRU以及PSO-GRU等模型,具有较高的估计精度与应用价值。

Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

Efficient stochastic parallel gradient descent training for on-chip optical processor

In recent years,space-division multiplexing(SDM)technology,which involves transmitting data information on multiple parallel channels for efficient capacity scaling,has been widely used in fiber and free-space optical communication sys-tems.To enable flexible data management and cope with the mixing between different channels,the integrated reconfig-urable optical processor is used for optical switching and mitigating the channel crosstalk.However,efficient online train-ing becomes intricate and challenging,particularly when dealing with a significant number of channels.Here we use the stochastic parallel gradient descent(SPGD)algorithm to configure the integrated optical processor,which has less com-putation than the traditional gradient descent(GD)algorithm.We design and fabricate a 6×6 on-chip optical processor on silicon platform to implement optical switching and descrambling assisted by the online training with the SPDG algorithm.Moreover,we apply the on-chip processor configured by the SPGD algorithm to optical communications for optical switching and efficiently mitigating the channel crosstalk in SDM systems.In comparison with the traditional GD al-gorithm,it is found that the SPGD algorithm features better performance especially when the scale of matrix is large,which means it has the potential to optimize large-scale optical matrix computation acceleration chips.

基于Python脚本的SoC寄存器模块自动化设计

片上系统芯片(SoC)包含大量可通过系统总线配置的寄存器模块。在芯片设计流程中,需要人工设计寄存器模块功能,并形成可阅读的设计文档,再由硬件描述语言(Hardware Description Language)描述为实际数字电路,还需要有便于芯片仿真验证的寄存器模型以及基于C语言的嵌入式固件程序用于应用软件开发。本文提供一种基于Python脚本语言的芯片设计流程,将上述芯片设计流程串联起来,做到一次规格设计,自动化输出寄存器模块的不同设计描述,有效提高了SoC芯片设计效率。

Simulation and fabrication of in vitro microfluidic microelectrode array chip for patterned culture and electrophysiological detection of neurons

To enable the detection and modulation of modularized neural networks in vitro,this study proposes a microfluidic microelectrode array chip for the cultivation,compartmentalization,and control of neural cells.The chip was designed based on the specific structure of neurons and the requirements for detection and modulation.Finite-element analysis of the chip’s flow field was conducted using the COMSOL Multiphysics software,and the simulation results show that the liquid within the chip can flow smoothly,ensuring stable flow fields that facilitate the uniform growth of neurons within the microfluidic channels.By employing MEMS technology in combination with nanomaterial modification techniques,the microfluidic microelectrode array chip was fabricated successfully.Primary hippocampal neurons were cultured on the chip,forming a well-defined neural network.Spontaneous electrical activity of the detected neurons was recorded,exhibiting a 23.7%increase in amplitude compared to neuronal discharges detected on an open-field microelectrode array.This study provides a platform for the precise detection and modulation of patterned neuronal growth in vitro,potentially serving as a novel tool in neuroscience research.

On-chip quantum NOON state sensing for temperature and humidity

A maximal photon number entangled state,namely NOON state,can be adopted for sensing with a quantum enhancedprecision.In this work,we designed silicon quantum photonic chips containing two types of Mach-Zehnder interferometerswherein the two-photon NOON state,sensing element for temperature or humidity,is generated.Compared with classicallight or single photon case,two-photon NOON state sensing shows a solid enhancement in the sensing resolution andprecision.As the first demonstration of on-chip quantum photonic sensing,it reveals the advantages of photonic chips forhigh integration density,small-size,stability for multiple-parameter sensing serviceability.A higher sensing precision isexpected to beat the standard quantum limit with a higher photon number NOON state.

Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

A novel integrated microfluidic chip for on-demand electrostatic droplet charging and sorting

On-demand droplet sorting is extensively applied for the efficient manipulation and genome-wide analysis of individual cells.However,state-of-the-art microfluidic chips for droplet sorting still suffer from low sorting speeds,sample loss,and labor-intensive preparation procedures.Here,we demonstrate the development of a novel microfluidic chip that integrates droplet generation,on-demand electrostatic droplet charging,and high-throughput sorting.The charging electrode is a copper wire buried above the nozzle of the microchannel,and the deflecting electrode is the phosphate buffered saline in the microchannel,which greatly simplifies the structure and fabrication process of the chip.Moreover,this chip is capable of high-frequency droplet generation and sorting,with a frequency of 11.757 kHz in the drop state.The chip completes the selective charging process via electrostatic induction during droplet generation.On-demand charged microdroplets can arbitrarilymove to specific exit channels in a three-dimensional(3D)-deflected electric field,which can be controlled according to user requirements,and the flux of droplet deflection is thereby significantly enhanced.Furthermore,a lossless modification strategy is presented to improve the accuracy of droplet deflection or harvest rate from 97.49% to 99.38% by monitoring the frequency of droplet generation in real time and feeding it back to the charging signal.This chip has great potential for quantitative processing and analysis of single cells for elucidating cell-to-cell variations.

Integrated strategy for real-time wind power fluctuation mitigation and energy storage system control

To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.

Rapid fabrication of modular 3D paper-basedmicrofluidic chips using projection-based 3D printing

Paper-based microchips have different advantages,such as better biocompatibility,simple production,and easy handling,making them promising candidates for clinical diagnosis and other fields.This study describes amethod developed to fabricate modular three-dimensional(3D)paper-based microfluidic chips based on projection-based 3D printing(PBP)technology.A series of two-dimensional(2D)paper-based microfluidic modules was designed and fabricated.After evaluating the effect of exposure time on the accuracy of the flow channel,the resolution of this channel was experimentally analyzed.Furthermore,several 3D paper-based microfluidic chips were assembled based on the 2D ones using different methods,with good channel connectivity.Scaffold-based 2D and hydrogel-based 3D cell culture systems based on 3D paper-based microfluidic chips were verified to be feasible.Furthermore,by combining extrusion 3D bioprinting technology and the proposed 3D paper-based microfluidic chips,multiorgan microfluidic chips were established by directly printing 3D hydrogel structures on 3D paperbased microfluidic chips,confirming that the prepared modular 3D paper-based microfluidic chip is potentially applicable in various biomedical applications.

Effects of Using Softwood Pellet Biochar Prepared at Different Temperatures with Grass Chippings on Retention of Heavy Metals in Contaminated Soils

Heavy metals have been viewed as hazardous environmental pollutants, and anthropogenic activities due to their high toxicity and persistent nature in the environment. Anthropogenic activities such as artisanal mining, industrial activities, improper usage of fertilizers and pesticides, and indiscriminate open waste disposal bring about an increase in the presence of heavy metals in the environment. In the Keffi Metropolis, different elements lead to land contamination which debilitates soil quality, plant survival, human well-being, and the environment as a result of extensive dispersion or quantity of heavy metals in the soil and water. In recent years, biochar has emerged as a promising soil amendment for mitigating heavy metal pollution due to its unique physicochemical properties. This paper provides the effects of softwood pellet biochar on the retention of heavy metals in contaminated soils. A microcosm experiment was carried out to investigate the effects of biochar on the retention of heavy metals in contaminated soils. This research aimed to give an overview of the effects of softwood biochar at different temperatures (550˚C and 700˚C) on the retention of heavy metals and metalloids released from the soil during water inundation. The results show that the addition of organic matter (grass chippings) minimizes heavy metal mobilization. Also, biochar at high temperatures is more effective than those at low temperatures. The expected outcome of the research analysis includes providing insights into the role of biochar in retaining heavy metal contamination and further understanding the use of biochar as a sorbent for the management of contaminated soil.

An electrochemiluminescent magneto-immunosensor for ultrasensitive detection of hs-cTnI on a microfluidic chip

Sensitive detection and precise quantitation of trace-level crucial biomarkers in a complex sample matrix has become an important area of research.For example,the detection of high-sensitivity cardiac troponin I (hs-cTnI) is strongly recommended in clinical guidelines for early diagnosis of acute myocardial infarction.Based on the use of an electrode modified by single-walled carbon nanotubes (SWCNTs) and a Ru(bpy)32+-doped silica nanoparticle (Ru@SiO2)/tripropylamine (TPA) system,a novel type of electrochemiluminescent (ECL) magnetoimmunosensor is developed for ultrasensitive detection of hs-cTnI.In this approach,a large amount of[Ru(bpy)3]2+is loaded in SiO2(silica nanoparticles) as luminophores with high luminescent efficiency and SWCNTs as electrode surface modification material with excellent electrooxidation ability for TPA.Subsequently,a hierarchical micropillar array of microstructures is fabricated with a magnet placed at each end to efficiently confine a single layer of immunomagnetic microbeads on the surface of the electrode and enable 7.5-fold signal enhancement In particular,the use of transparent SWCNTs to modify a transparent ITO electrode provides a two-order-of-magnitude ECL signal amplification.A good linear calibration curve is developed for hs-cTnI concentrations over a wide range from 10 fg/ml to 10 ng/ml,with the limit of detection calculated as 8.720 fg/ml (S/N=3).This ultrasensitive immunosensor exhibits superior detection performance with remarkable stability,reproducibility,and selectivity.Satisfactory recoveries are obtained in the detection of hs-cTnI in human serum,providing a potentia analysis protocol for clinical applications.

Exploring the mechanism of electroacupuncture at different acupoints on acute colitis rats based on JAK2/STAT3/SOCS1 signaling pathway

Objective:To investigate the mechanism of JAK2/STAT3/SOCS1 signaling pathway in electroacupuncture of different acupoints on acute colitis rats.Methods:36 SPF SD rats were randomly divided into 6 groups,with 6 rats in each group.The rat model of acute colitis was prepared by enema with glacial acetic acid solution.After the model was established,electroacupuncture was given to each acupoint group,with density wave,frequency 2Hz-50 Hz,intensity 2 mA,muscle tremor as the degree 20 min/time,1 time/day,for 3 consecutive days.Observe the general condition of rats;the pathological changes of colonic mucosa in rats were observed by HE method.The contents of serum interleukin-4(IL-4)and interleukin-8(IL-8)were detected by ELISA.Western blot and RT-PCR were used to detect the expression of JAK2,STAT3,SOCS1 protein and mRNA in rat colon tissue.Results:In contrast to the normal group,the overall condition of the model group was worse,the colonic mucosa was severely damaged,even necrotic,and the ulcer surface was obvious.The content of IL-4 in serum was obviously reduced,and the content of IL-8 was obviously go up(P<0.01).The protein content of JAK2,STAT3 and the expression of JAK2,STAT3 mRNA in colon tissue of rats were obviously go up,while the protein content of SOCS1 and the expression of SOCS1 mRNA were obviously reduced(P<0.01).In contrast to the model group,the general condition of rats in each acupoint group was significantly improved,the damage and necrosis of colonic mucosa and ulcer surface were obviously alleviated,the content of IL-4 in serum was obviously go up,and the content of IL-8 was significantly decreased(P<0.01).The protein content of JAK2,STAT3 and the expression of JAK2,STAT3 mRNA in colon tissue of rats were obviously reduced,while the protein content of SOCS1 and the expression of SOCS1 mRNA were obviously go up(P<0.05,P<0.01).Comparison of different acupoint groups,the colonic mucosal injury in the Zusanli group was significantly reduced,the content of serum IL-4 was significantly increased,and the content of IL-8 was significantly decreased(P<0.05,P<0.01).The protein content and mRNA expression of JAK2 and STAT3 in colon tissue were significantly down-regulated,while the protein content and mRNA expression of SOCS1 were significantly go up(P<0.05,P<0.01).Conclusion:Electroacupuncture at each acupoint can improve the damage of colonic mucosa and reduce the inflammatory response.The therapeutic effect of Zusanli(ST36)is better than that of Tianshu(ST25),Dachangshu(BL25)and Shangjuxu(ST37).The mechanism may be related to the regulation of JAK2/STAT3/SOCS1 signaling pathway related proteins and inflammatory cytokines IL-4 and IL-8.

Analysis of the Tragedy of Vila Socóin Cubatão (São Paulo, Brazil) Using the Haddon Matrix: A Comprehensive Examination of Socio-Environmental Factors and Risk Mitigation Strategies

The tragedy of Vila Socó epitomizes the socio-environmental repercussions of rapid industrialization in Cubatão. Beginning in the 1940s with the construction of the Anchieta highway, the city experienced an influx of migrants drawn by burgeoning industries, leading to unplanned urban growth and the emergence of vulnerable communities like Vila Socó. This article examines the interconnected factors—such as demographic shifts, inadequate planning, and regulatory oversight—that culminated in the devastating fire of 1984, claiming numerous lives and highlighting systemic failures. Utilizing the Haddon Matrix, this study dissects the Vila Socó incident, emphasizing the roles of human error, infrastructure integrity, and socio-economic disparities in disaster causation. By contextualizing the tragedy within Cubatão’s industrial trajectory, it underscores the urgent need for comprehensive risk assessment and proactive mitigation strategies in rapidly developing regions globally. Beyond its immediate focus, this work offers broader insights into the dynamics of industrial disasters and their socio-economic implications. As pipelines continue to play a vital role in global energy infrastructure, the lessons drawn from Vila Socó’s tragedy resonate deeply, emphasizing the imperative of robust safety protocols and accountable governance to prevent similar catastrophes in the future.

An Ensemble Learning Method for SOC Estimation of Lithium-Ion Batteries Using Machine Learning

Accurately assessing the State of Charge(SOC)is paramount for optimizing battery management systems,a cornerstone for ensuring peak battery performance and safety across diverse applications,encompassing vehicle powertrains and renewable energy storage systems.Confronted with the challenges of traditional SOC estimation methods,which often struggle with accuracy and cost-effectiveness,this research endeavors to elevate the precision of SOC estimation to a new level,thereby refining battery management strategies.Leveraging the power of integrated learning techniques,the study fuses Random Forest Regressor,Gradient Boosting Regressor,and Linear Regression into a comprehensive framework that substantially enhances the accuracy and overall performance of SOC predictions.By harnessing the publicly accessible National Aeronautics and Space Administration(NASA)Battery Cycle dataset,our analysis reveals that these integrated learning approaches significantly outperform traditional methods like Coulomb counting and electrochemical models,achieving remarkable improvements in SOC estimation accuracy,error reduction,and optimization of key metrics like R2 and Adjusted R2.This pioneering work propels the development of innovative battery management systems grounded in machine learning and deepens our comprehension of how this cutting-edge technology can revolutionize battery technology.

Review on the Usage of Synchronous and Asynchronous FIFOs in Digital Systems Design

First-Input-First-Output (FIFO) buffers are extensively used in contemporary digital processors and System-on-Chips (SoC). There are synchronous FIFOs and asycnrhonous FIFOs. And different sized FIFOs should be implemented in different ways. FIFOs are used not only for the pipeline design within a processor, for the inter-processor communication networks, for example Network-on-Chips (NoCs), but also for the peripherals and the clock domain crossing at the whole SoC level. In this paper, we review the interface, the circuit implementation, and the various usages of FIFOs in various levels of the digital design. We can find that the usage of FIFOs could greatly facilitate the signal storage, signal decoupling, signal transfer, power domain separation and power domain crossing in digital systems. We hope that more attentions are paid to the usages of synchronous and asynchronous FIFOs and more sophististicated usages are discovered by the digital design communities.

System-on-a-Chip (SoC) Based Hardware Acceleration for Video Codec

Nowadays, from home monitoring to large airport security, a lot of digital video surveillance systems have been used. Digital surveillance system usually requires streaming video processing abilities. As an advanced video coding method, H.264 is introduced to reduce the large video data dramatically (usually by 70X or more). However, computational overhead occurs when coding and decoding H.264 video. In this paper, a System-on-a-Chip (SoC) based hardware acceleration solution for video codec is proposed, which can also be used for other software applications. The characteristics of the video codec are analyzed by using the profiling tool. The Hadamard function, which is the bottleneck of H.264, is identified not only by execution time but also another two attributes, such as cycle per loop and loop round. The Co-processor approach is applied to accelerate the Hadamard function by transforming it to hardware. Performance improvement, resource costs and energy consumption are compared and analyzed. Experimental results indicate that 76.5% energy deduction and 8.09X speedup can be reached after balancing these three key factors.

单片集成计算机系统SOC(System—On—Chip)应用探讨

介绍了目前国际上新发展的单片集成计算机系统SOC(System—On—Chip),按照不同的用途,选取不同功能模块的芯片,只需要很少的外部器件就可以完成普通PC所具有的常用功能,功能比以往的微处理器要强大得多,它的内部属于PC的构架,可扩展性强,同时使产品具有体积小巧、成本低廉的优势。

基于多新息最小二乘和多新息扩展卡尔曼滤波算法的锂电池SOC估计

针对现有SOC(荷电状态)估计方法中电池模型参数恒定,没有考虑电池模型参数的动态变化,导致SOC的估计不够精准的问题,文中提出了一种基于电池模型参数在线辨识与SOC估计联合的算法。在二阶RC等效电路模型基础上,采用多新息最小二乘(Multi Innovation Least Squares,MILS)算法对锂离子电池模型中的参数进行在线辨识,从而对电池模型进行实时修正;同时基于修正后的电池模型,采用多新息扩展卡尔曼滤波(Multi Innovation Extended Kalman Filter,MIEKF)算法对电池荷电状态进行估计。MILS算法可以解决在线参数辨识过程中的初始误差累积问题,能够实现模型参数的在线精准辨识,MIEKF算法融合了多新息理论和卡尔曼滤波理论,加入了遗忘因子以削弱历史数据并修正权重,解决了数据过饱和问题,具有较高的准确性和收敛性。实验结果表明,在对电池模型进行参数辨识时,MILS算法、RLS算法辨识的均方根误差分别为1.4、1.9 mV,MILS算法相比RLS算法的估计精度提高了26.3%;对于参数辨识后SOC的估计,MIEKF算法估计的均方根误差为0.0037,EKF算法、AEKF算法估计的均方根误差分别为0.0073、0.0052,MIEKF算法比EKF算法的估计精度提高了49.31%,比AEKF算法的估计精度提高了28.84%;并且在给定SOC初值错误的情况下,文中所提出算法在电池开始工作后30 s左右就能够收敛到真实值,是一种精度高而且鲁棒性好的有效估计方法。