Gates joint locally connected network for accurate and robust reconstruction in optical molecular tomography

Optical molecular tomography(OMT)is a potential pre-clinical molecular imaging technique with applications in a variety of biomedical areas,which can provide non-invasive quantitative three-dimensional(3D)information regarding tumor distribution in living animals.The construction of optical transmission models and the application of reconstruction algorithms in traditional model-based reconstruction processes have affected the reconstruction results,resulting in problems such as low accuracy,poor robustness,and long-time consumption.Here,a gates joint locally connected network(GLCN)method is proposed by establishing the mapping relationship between the inside source distribution and the photon density on surface directly,thus avoiding the extra time consumption caused by iteration and the reconstruction errors caused by model inaccuracy.Moreover,gates module was composed of the concatenation and multiplication operators of three different gates.It was embedded into the network aiming at remembering input surface photon density over a period and allowing the network to capture neurons connected to the true source selectively by controlling three different gates.To evaluate the performance of the proposed method,numerical simulations were conducted,whose results demonstrated good performance in terms of reconstruction positioning accuracy and robustness.

引入上下文信息和Attention Gate的GUS-YOLO遥感目标检测算法

目前基于通用YOLO系列的遥感目标检测算法存在并未充分利用图像的全局上下文信息,在特征融合金字塔部分并未充分考虑缩小融合特征之间的语义鸿沟、抑制冗余信息干扰的缺点。在结合YOLO算法优点的基础上提出GUS-YOLO算法,其拥有一个能够充分利用全局上下文信息的骨干网络Global Backbone。除此之外,该算法在融合特征金字塔自顶向下的结构中引入Attention Gate模块,可以突出必要的特征信息,抑制冗余信息。另外,为Attention Gate模块设计了最佳的网络结构,提出了网络的特征融合结构U-Net。最后,为克服ReLU函数可能导致模型梯度不再更新的问题,该算法将Attention Gate模块的激活函数升级为可学习的SMU激活函数,提高模型鲁棒性。在NWPU VHR-10遥感数据集上,该算法相较于YOLOV7算法取得宽松指标mAP^(0.50)1.64个百分点和严格指标mAP^(0.75)9.39个百分点的性能提升。相较于目前主流的七种检测算法,该算法取得较好的检测性能。

An integrated split and dummy gates MOSFET with fast turn-off and reverse recovery characteristics

A power MOSFET with integrated split gate and dummy gate(SD-MOS) is proposed and demonstrated by the TCAD SENTAURUS.The split gate is surrounded by the source and shielded by the dummy gate.Consequently,the coupling area between the split gate and the drain electrode is reduced,thus the gate-to-drain charge(Q_(GD)),reverse transfer capacitance(C_(RSS)) and turn-off loss(E_(off)) are significantly decreased.Moreover,the MOS-channel diode is controlled by the dummy gate with ultra-thin gate oxide t_(ox),which can be turned on before the parasitic P-base/N-drift diode at the reverse conduction,then the majority carriers are injected to the N-drift to attenuate the minority injection.Therefore,the reverse recovery charge(Q_(RR)),time(T_(RR)) and peak current(I_(RRM)) are effectively reduced at the reverse freewheeling state.Additionally,the specific on-resistance(R_(on,sp)) and breakdown voltage(BV) are also studied to evaluate the static properties of the proposed SD-MOS.The simulation results show that the Q_(GD) of 6 nC/cm^(2),the C_(RSS) of 1.1 pF/cm^(2) at the V_(DS) of 150 V,the QRR of 1.2 μC/cm^(2) and the R_(on,sp) of 8.4 mΩ·cm^(2) are obtained,thus the figures of merit(FOM) including Q_(GD) ×R_(on,sp) of50 nC·mΩ,E_(off) × R_(on,sp) of 0.59 mJ·mΩ and the Q_(RR) × R_(on,sp) of 10.1 μC·mΩ are achieved for the proposed SD-MOS.

Skyrmion-based logic gates controlled by electric currents in synthetic antiferromagnet

Skyrmions in synthetic antiferromagnetic(SAF) systems have attracted much attention in recent years due to their superior stability, high-speed mobility, and completely compensated skyrmion Hall effect. They are promising building blocks for the next generation of magnetic storage and computing devices with ultra-low energy and ultra-high density.Here, we theoretically investigate the motion of a skyrmion in an SAF bilayer racetrack and find the velocity of a skyrmion can be controlled jointly by the edge effect and the driving force induced by the spin current. Furthermore, we propose a logic gate that can realize different logic functions of logic AND, OR, NOT, NAND, NOR, and XOR gates. Several effects including the spin–orbit torque, the skyrmion Hall effect, skyrmion–skyrmion repulsion, and skyrmion–edge interaction are considered in this design. Our work may provide a way to utilize the SAF skyrmion as a versatile information carrier for future energy-efficient logic gates.

Thermal spin molecular logic gates modulated by an electric field

Logic gates are fundamental structural components in all modern digital electronic devices. Here, nonequilibrium Green's functions are incorporated with the density functional theory to verify the thermal spin transport features of the single-molecule spintronic devices constructed by a single molecule in series or parallel connected with graphene nanoribbons electrodes. Our calculations demonstrate that the electric field can manipulate the spin-polarized current. Then, a complete set of thermal spin molecular logic gates are proposed, including AND, OR, and NOT gates. The mentioned logic gates enable different designs of complex thermal spin molecular logic functions and facilitate the electric field control of thermal spin molecular devices.

Current-collapse suppression and leakage-current decrease in AlGaN/GaN HEMT by sputter-TaN gate-dielectric layer

In this paper, we explore the electrical characteristics of high-electron-mobility transistors(HEMTs) using a TaN/AlGaN/GaN metal insulating semiconductor(MIS) structure. The high-resistance tantalum nitride(TaN) film prepared by magnetron sputtering as the gate dielectric layer of the device achieved an effective reduction of electronic states at the TaN/AlGaN interface, and reducing the gate leakage current of the MIS HEMT, its performance was enhanced. The HEMT exhibited a low gate leakage current of 2.15 × 10^(-7) mA/mm and a breakdown voltage of 1180 V. Furthermore, the MIS HEMT displayed exceptional operational stability during dynamic tests, with dynamic resistance remaining only 1.39 times even under 400 V stress.

Remote entangling gate between a quantum dot spin and a transmon qubit mediated by microwave photons

Spin qubits and superconducting qubits are promising candidates for realizing solid-state quantum information processors.Designing a hybrid architecture that combines the advantages of different qubits on the same chip is a highly desirable but challenging goal.Here we propose a hybrid architecture that utilizes a high-impedance SQUID array resonator as a quantum bus,thereby coherently coupling different solid-state qubits.We employ a resonant exchange spin qubit hosted in a triple quantum dot and a superconducting transmon qubit.Since this hybrid system is highly tunable,it can operate in a dispersive regime,where the interaction between the different qubits is mediated by virtual photons.By utilizing such interactions,entangling gate operations between different qubits can be realized in a short time of 30 ns with a fidelity of up to 96.5%under realistic parameter conditions.Further utilizing this interaction,remote entangled state between different qubits can be prepared and is robust to perturbations of various parameters.These results pave the way for exploring efficient fault-tolerant quantum computation on hybrid quantum architecture platforms.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Gates法计算的GFR在单侧肾积水患者肾小球滤过功能评价中的应用

目的探讨Gates法计算的肾小球滤过率(GFR)对单侧肾积水患者肾小球滤过功能评估的价值。方法选择经B超检查确诊为单侧肾积水的患者176例(轻度积水组21例、中度积水组33例、重度积水组122例),同期选取泌尿系统及GFR均正常的肾移植供体捐献者22例(正常对照组)。两组均接受99mTc-DTPA肾动态显像检查,用Gates法计算患肾、健肾、双肾GFR值,根据单肾GFR将患者肾功能划分为肾功能正常、轻度下降、中度下降、重度下降及肾无功能。结果与正常对照组比较,中、重度积水组患侧肾GFR降低,轻、中、重度积水组健侧肾GFR升高,中、重度积水组双肾GFR降低(P均<0.05)。轻度积水组90.48%的患肾GFR正常,中度积水组63.64%的患肾GFR轻度下降,重度积水组35.25%的患肾GFR重度下降、33.33%的患肾无功能。积水越严重肾功能越差。结论 Gates法计算的单肾、总肾GFR可定量分析单侧肾积水患者肾小球滤过功能,同步评价健侧肾的代偿能力。

Gow-Gates法下牙槽神经阻滞麻醉在下颌阻生第三磨牙拔除术中的麻醉效果研究

目的通过临床随机对照试验的方法评价Gow-Gates法下牙槽神经阻滞麻醉在下颌阻生第三磨牙拔除术中的麻醉有效性和安全性。方法使用左右半口设计,32例患者的左右下颌阻生第三磨牙分别随机采用Gow-Gates法和传统注射法进行下牙槽神经阻滞麻醉,并拔除下颌阻生第三磨牙,记录麻醉效果及不良事件。结果所有患者均完成研究。Gow-Gates法的麻醉成功率为96.9%,传统注射法的麻醉成功率为90.6%,二者的麻醉成功率无统计学差异(P=0.317)。在麻醉程度上,Gow-Gates法麻醉程度为A和B级的比率为96.9%,明显好于传统注射法的78.1%(P=0.034)。Gow-Gates法的回抽出血率明显低于传统注射法(P=0.025),2种注射方法均未出现血肿。结论 Gow-Gates法下牙槽神经阻滞麻醉在下颌阻生第三磨牙拔除术中的麻醉效果好且较为安全,可以作为传统注射法的有效补充。

肾积水对轻中度肾损伤者Gates法GFR的影响

目的了解轻中度肾积水对肾动态显像GFR的影响。方法回顾2010年1～12月51例双血浆法GFR(tGFR)在30～90ml/(1.73m2.min)范围内的肾积水患者的肾动态显像,按照tGFR的大小并结合肾脏疾病的分期标准分成正常对照组[90ml(1.73m2.min)≤tGFR<120ml/(1.73m2.min)],轻度[60ml/(1.73m2.min)≤tGFR<90ml/(1.73m2.min)]和中度[30ml/(1.73m2.min)≤tGFR<60ml/(1.73m2.min)]肾损伤3组,并比较体表面积标准化前后Gates法GFR(gGFR)和tGFR间差异和相关性。结果大多数情况下,gGFR均高于tGFR,二者差值范围-35.1～26.1ml/(1.73m2.min);tGFRBSA和gGFRBSA间差值范围-38.3～26.8ml/(1.73m2.min)。无论轻度和中度肾损伤组,还是整体患者中,BSA标准化均可改善tGFR和gGFR间的相关性。BSA标准化后,中度肾损伤组的相关系数可达到0.634(P=0.020),而轻度肾损伤组和整体患者中仅为0.298(P=0.229)和0.543(P=0.002)。结论体表面积标准化Gates法GFR可提高其与双血浆法间的相关性,但评估肾积水伴轻中度肾损伤患者GFR价值有限,应参考双血浆法的定量结果。

JE BookⅡ Unit 23 Lesson 90 Bill Gates教学设计

一、教材分析 本课为JE BookⅡ中Unit 23（A famous person）的第2课时，是在第1课时的基础上介绍Bill Gates的成长过程及奋斗经历，文中有较乡单词和疑难长句，是能够培养学生猜测、分析、判断能力的阅读课文。

基于Attention Gates和R2U-Net的遥感影像建筑物提取方法

针对深度语义分割算法提取遥感影像建筑物时易产生建筑物边缘分割不明确、提取精度不高等问题,该文提出一种基于Attention Gates(AG)和R2U-Net的遥感影像建筑物提取方法(AGR2U-Net)。该方法将R2U-Net模型每一层输出的特征图与其相邻层的特征图输入至改进的AG模型中,得到与输入影像大小一致的特征图,以提高R2U-Net模型的多尺度泛化能力,从而增强该模型对建筑物特征的响应及灵敏度,最终提升遥感影像建筑物提取精度。利用WHU卫星影像数据集和WHU航空影像数据集,对该方法与U-Net、Improved U-Net、SegU-Net和R2U-Net方法进行对比实验验证,结果表明,该方法的交并比、像素准确率和召回率均最高,且提取的建筑物边缘更准确、内部信息更完整、误检和漏检情况更少。

弹丸注射质量对Gates法测定活体肾移植供者GFR的影响

目的探讨高质量弹丸注射对Gates法准确测定活体肾移植供者GFR的重要意义。方法收集在我院核医学科行肾动态显像的102例亲属活体肾移植供者的检查资料,将这102例受检者根据弹丸注射质量分为两组:A组(弹丸注射质量良好)56例,B组(弹丸注射质量欠佳以及不合格)46例。对比两组的年龄、性别、肾脏深度、注入体内放射性计数、分肾GFR、总肾GFR、eGFR差异,并将两组的肾动态显像测定的总肾GFR值与eGFR进行相关性和一致性分析。结果A、B两组的年龄、性别、肾脏深度、注入体内放射性计数、eGFR差异均无统计学意义,而两组的左肾GFR、右肾GFR、总GFR的差异均具有统计学意义。与B组相比,A组的总GFR与eGRF有更好的相关性和一致性。结论高质量弹丸注射对Gates法准确测定活体肾移植供者GFR具有重要意义,弹丸质量不佳将导致测定的GFR偏低。

应用^(99m)Tc-DTPA测定GFR——Gates法

应用^(99m)Tc-DTPA检测肾功能的方法很多,Gates法是以^(99m)Tc-DTPA肾摄取率来计算GFR,它可同时评价总肾功能和分肾功能,并且与临床传统检查的内生肌酐清除率有良好的相关性(r=0.89～0.99).本文简要介绍了Gates法及其有关的γ射线吸收校正、肾脏深度的计算、检测时间的设定等问题.

Learning algorithm and application of quantum BP neural networks based on universal quantum gates

A quantum BP neural networks model with learning algorithm is proposed. First, based on the universality of single qubit rotation gate and two-qubit controlled-NOT gate, a quantum neuron model is constructed, which is composed of input, phase rotation, aggregation, reversal rotation and output. In this model, the input is described by qubits, and the output is given by the probability of the state in which （1） is observed. The phase rotation and the reversal rotation are performed by the universal quantum gates. Secondly, the quantum BP neural networks model is constructed, in which the output layer and the hide layer are quantum neurons. With the application of the gradient descent algorithm, a learning algorithm of the model is proposed, and the continuity of the model is proved. It is shown that this model and algorithm are superior to the conventional BP networks in three aspects： convergence speed, convergence rate and robustness, by two application examples of pattern recognition and function approximation.

Quantum logic gates operation using SQUID qubits in bimodal cavity

We present a scheme to realize the basic two-qubit logic gates such as the quantum phase gate and SWAP gate using a detuned microwave cavity interacting with three-level superconducting-quantum-interference-device （SQUID） qubit（s）, by placing SQUID（s） in a two-mode microwave cavity and using adiabatic passage methods. In this scheme, the two logical states of the qubit are represented by the two lowest levels of the SQUID, and the cavity fields are treated as quantized. Compared with the previous method, the complex procedures of adjusting tile level spacing of the SQUID and applying the resonant microwave pulse to the SQUID to create transformation are not required. Based on superconducting device with relatively long decoherence time and simplified operation procedure, the gates operate at a high speed, which is important in view of decoherence.

Effect of X-ray irradiation on threshold voltage of AlGaN/GaN HEMTs with p-GaN and MIS Gates

Commercially available AlGaN/GaN high-electron-mobility transistors(HEMTs)are beginning to enter the public scene froma range of suppliers.Based on previous studies,commercial GaN-based electronics are expected to be tolerant to different types of irradiation in space.To test this assumption,we compared the characteristic electrical curves obtained at different X-ray irradiation doses for GaN HEMT devices manufactured by Infineon and Transphorm.The p-GaN-based device was found to be more robust with a stable threshold voltage,whereas the threshold voltage of the device with ametal-insulator-semiconductor gatewas found to shift first in the negative and then the positive direction.This dynamic phenomenon is caused by the releasing and trapping effects of radiation-induced charges in the dielectric layer and at the interface of irradiated devices.As such,the p-GaNgate-based GaN HEMT provides a promising solution for use as an electric source in space.