Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

Research on the optimization strategy of customers’electricity consumption based on big data

Current power systems face significant challenges in supporting large-scale access to new energy sources,and the potential of existing flexible resources needs to be fully explored from the power supply,grid,and customer perspectives.This paper proposes a multi-objective electricity consumption optimization strategy considering the correlation between equipment and electricity consumption.It constructs a multi-objective electricity consumption optimization model that considers the correlation between equipment and electricity consumption to maximize economy and comfort.The results show that the proposed method can accurately assess the potential for electricity consumption optimization and obtain an optimal multi-objective electricity consumption strategy based on customers’actual electricity consumption demand.

A Multi-View Gait Recognition Method Using Deep Convolutional Neural Network and Channel Attention Mechanism

In many existing multi-view gait recognition methods based on images or video sequences,gait sequences are usually used to superimpose and synthesize images and construct energy-like template.However,information may be lost during the process of compositing image and capture EMG signals.Errors and the recognition accuracy may be introduced and affected respectively by some factors such as period detection.To better solve the problems,a multi-view gait recognition method using deep convolutional neural network and channel attention mechanism is proposed.Firstly,the sliding time window method is used to capture EMG signals.Then,the back-propagation learning algorithm is used to train each layer of convolution,which improves the learning ability of the convolutional neural network.Finally,the channel attention mechanism is integrated into the neural network,which will improve the ability of expressing gait features.And a classifier is used to classify gait.As can be shown from experimental results on two public datasets,OULP and CASIA-B,the recognition rate of the proposed method can be achieved at 88.44%and 97.25%respectively.As can be shown from the comparative experimental results,the proposed method has better recognition effect than several other newer convolutional neural network methods.Therefore,the combination of convolutional neural network and channel attention mechanism is of great value for gait recognition.

Reappraise role of lymph node status in patterns of recurrence following curative resection of gastric adenocarcinoma

Objective: To examine the association between lymph node status and recurrence patterns in completely resected gastric adenocarcinoma.Methods: We retrospectively assessed 1,694 patients who underwent curative gastrectomy from January 2010 to August 2014. Patients stratified according to lymph node status and recurrence patterns among different subgroups were compared.Results: Of all, 517(30.5%) patients developed recurrent disease, and complete data of recurrence could be obtained in 493(95.4%) patients. For p^(N0) patients, the patterns of recurrence were different according to p T stage: locoregional recurrence was most common in patients with p T1-2 disease(57.1%), distant recurrence was most common in patients with p T3 disease(57.1%), and peritoneal recurrence was most common in patients with p T4 a disease(66.7%). For p^(N+) patients, distant metastasis was most common pattern irrespective of p T stage. The site-specific trend of recurrence showed that locoregional recurrence increased within 5 years in patients with p^(N0)-2 disease but plateaued 3 years after surgery in patients with p N3 disease. Time to recurrence was significantly longer for the p^(N0) patients compared with the p^(N+) patients(median: 25 vs. 16 months, P=0.001).Moreover, post-recurrence survival was significantly better for the p^(N0) patients than for the p^(N+) patients(median:12 vs. 6 months, P<0.001), especially in patients with non-peritoneal recurrence, late recurrence, single recurrence,and receipt of potential curative treatment.Conclusions: Among clinicopathologic factors, lymph node status is the most important factor associated with recurrence patterns after curative gastrectomy. Lymph node status may be used as an adjunct in clinical decisionmaking about postoperative therapeutic and follow-up strategies.

高速列车过隧道产生压力波的三维特性

本文采用滑移网格法模拟了时速350 km的高速列车通过350 m标准单线隧道,研究了列车前方不同隧道横截面的压力分布,基于等压力曲面描述了压力波的三维特征和传播机理,并提出了一种新式精确的压力传感器布置方案.研究结果表明,隧道横截面距离列车车头越远,平面压力差异越小.受列车车头和隧道横截面形状的影响,压力波不是简单的平面波,而是在传播过程中复杂变化的球面波.以隧道断面的压力差异小于1 Pa来定义平面波,可发现平面波出现在列车前方16.6 m附近.此外,在70-90 m的隧道断面上,隧道壁面测点和建筑限界测点之间的压力峰峰值差异可达13%,因此应将压力传感器布置在附属设施表面而不是隧道壁面.综上所述,本研究对于理解压力波的形成和传播机理以及指导隧道内压力传感器的科学布置具有重要意义.

网络运营商侵害用户个人信息的现状和法律保护

大数据技术的进步促进了网络的蓬勃发展,当今时代,网络用户的个人信息不仅仅包括其隐私安全,还有其广泛的精神价值。虽然网络给大众带来了更多的便利,但同时也是把双刃剑,因为其便利了网络运营商对用户信息的侵害。当前《个人信息保护法》开始实施,我国个人信息保护逐渐步入正轨,但个人信息保护法律体系仍需完善,以防范大数据时代产生的个人信息风险。在此背景下,需要以《民法典》《个人信息保护法》等法律法规为基础,严格监管网络运营商的个人信息处理活动,筑牢个人信息保护网,切实保障公民的合法信息权益,实现个人利益与社会公共利益的有效均衡。基于此背景,围绕我国网络运营商对用户个人信息的侵害和法律保护展开探讨。

基于常见术前指标预测肥胖患者腹腔镜袖状胃切除术后早期减重达标的列线图模型构建

目的构建一个基于常见术前指标预测肥胖患者腹腔镜袖状胃切除术(LSG)后早期(1年内)减重效果的列线图模型。方法回顾性分析2015年1月至2022年5月于福建医科大学附属协和医院和福建医科大学附属泉州第一医院行LSG的肥胖症患者的临床病例资料。排除腹部大手术史、严重胃食管反流病、术后1年内怀孕及失访患者后,共200例患者入组(福建医科大学附属协和医院190例,福建医科大学附属泉州第一医院10例),其中男性51例,女性149例,年龄(29.9±8.2)岁,体质指数(BMI)为(38.7±6.5)kg/m^(2)。本组患者均接受标准化程序的LSG手术。将LSG术后1年达到理想体质量,即BMI≤25 kg/m^(2)定义为早期减重达标。采用单因素和多因素分析患者基本资料、临床指标、术前血液学指标以及合并症情况与LSG术后早期减重达标的关系,并将相关因素纳入列线图预测模型。采用受试者工作特征(ROC)曲线[曲线下面积(AUC)越大,模型的预测能力和预测准确性越好]、似然比检验(似然比越高,模型同质性越强)、决策曲线分析法(DCA;净获益越高,模型越好)、赤池信息量准则(AIC值;AIC值越小,模型拟合越好)及贝叶斯信息量准则(BIC值;BIC值越小,模型拟合越好)验证列线图模型的预测性能。结果200例接受LSG手术的肥胖患者中,早期减重达标136例(68.0%)。与未早期减重达标组(64例)相比,早期减重达标组患者BMI更小,丙氨酸转氨酶(ALT)、天冬氨酸转氨酶(AST)、甘油三酯(TG)水平更低,总胆固醇(CHOL)水平更高;女性占比更高,合并脂肪肝及高血压比率更低(均P<0.05)。多因素logistic回归分析显示,术前BMI(OR=0.852,95%CI:0.796~0.912,P<0.001)、ALT(OR=0.992,95%CI:0.985~0.999,P=0.024)及合并脂肪肝(OR=0.185,95%CI:0.038~0.887,P=0.035)和高血压(OR=0.374,95%CI:0.144~0.969,P=0.043)是阻碍早期减重达标的独立影响因素,CHOL(OR=1.428,95%CI:1.052~1.939,P=0.022)是有利于早期减重达标的独立影响因素。基于以上变量,我们建立了减重效果列线图预测模型。ROC曲线分析、决策曲线分析、似然比检验、赤池信息量准则(AIC值)及贝叶斯信息量准则(BIC值)均显示,列线图模型预测性能明显优于BMI(AUC值:0.840比0.798,P=0.047;似然比:58.785比36.565,AIC值:193.066比207.063,BIC值:212.856比213.660)。结论相较于只基于BMI的预测模型,本研究构建的术前指标预测模型可以更有效地预测LSG术后早期减重达标。

Highly sensitive torsion sensor based on Mach–Zehnder interference in helical seven-core fiber taper

We propose a high-sensitivity bidirectional torsion sensor using a helical seven-core fiber taper embedded in multimode fiber(MHSTM).Sensors with different taper waists and helical pitches are fabricated,and their transmission spectra are obtained and analyzed.The waist and length of the sandwiched seven-core fiber are finally determined to be 68 μm and3 mm,respectively.The experimental results show that the clockwise and counterclockwise torsion sensitivities of the proposed sensor are 2.253 nm/(rad/m) and-1.123 nm/(rad/m),respectively.When tapered waist diameter reduces to48 μm,a superior torsion sensitivity of 5.391 nm/(rad/m) in the range of 0-4.24 nm/(rad/m) is obtained,which is 46 times as large as the traditional helical seven-core fiber structure.In addition,the MHSTM structure is also relatively stable to temperature variations.

Effect of low operating temperature on the aerodynamic characteristics of a high-speed train

In this study,an improved delayed detached eddy simulation(IDDES)method based on the shear-stress transport(SST)k-ωturbulence model has been used to investigate the underbody flow characteristics of a high-speed train operating at lower temperatures with Reynolds number Re=1.85×10^(6).The accuracy of the numerical method has been validated by wind tunnel tests.The aerodynamic drag of the train,pressure distribution on the surface of the train,the flow around the vehicle,and the wake flow are compared for four temperature values:+15℃,0℃,−15℃,and−30℃.It was found that lower operating t emperatures significantly increased the aerodynamic drag force of the train.The drag overall at low temperatures increased by 5.3%(0℃),11.0%(−15℃),and 17.4%(−30℃),respectively,relative to the drag at+15℃.In addition,the low temperature e nhances the positive and negative pressures around and on the surface of the car body,raising the peak positive and negative pressure values in areas susceptible to impingement flow and to rapid changes in flow velocity.The range of train-induced winds around the car body is significantly reduced,the distribution area of vorticity moves backwards,and the airflow velocity in the bogie cavity is significantly increased.At the same time,the temperature causes a significant velocity reduction in the wake flow.It can be seen that the temperature reduction can seriously disturb the normal operation of the train while increasing the aerodynamic drag and energy consumption,and significantly interfering with the airflow characteristics around the car body.

Quantum squeezing enhancement based on phase-sensitive cascaded four-wave mixing processes

Quantum squeezing is an important quantum resource for quantum metrology as it can improve the measurement precision.By enhancing the quantum squeezing level,the measurement precision can be further improved.Here,we experimentally implement quantum squeezing enhancement based on phase-sensitive cascaded four-wave mixing(CFWM)processes.The intensitydifference squeezing(IDS)between the two outputs of the phase-sensitive CFWM processes is enhanced to about 7.42 dB compared with IDS generated by the single four-wave mixing(FWM)process(about 3.31 or 4.01 dB).Such enhancement is enabled by both the intrinsic interference nature of phase-sensitive CFWM processes and the contribution of more gain from the two FWM processes.In addition,we measure IDS levels generated by phase-sensitive CFWM processes at different internalphase-locking points,which shows that the internal phase plays an important role in IDS enhancement.Our scheme provides a new method for improving the degree of IDS and may find potential applications in enhancing the measurement precision in quantum metrology.

Characterization of a LAL-type regulator NemR in nemadectin biosynthesis and its application for increasing nemadectin production in Streptomyces cyaneogriseus

Nemadectin, a macrocyclic lactone antibiotic, is produced by Streptomyces cyaneogriseus ssp. noncyanogenus. A methoxime derivative of nemadectin, moxdectin, has been widely used to control insect and helminth in animal health. Despite the importance of nemadectin, little attention has been paid to the regulation of nemadectin biosynthesis, which has hindered efforts to improve nemadectin production via genetic manipulation of regulatory genes. Here, we characterize the function of nemR, the cluster-situated regulatory gene encoding a LAL-family transcriptional regulator, in the nemadectin biosynthesis gene cluster of S. cyaneogriseus ssp. noncyanogenus NMWT1. NemR is shown to be essential for nemadectin production and found to directly activate the transcription of nemA1-1/A1-2/A2, nemC and nemA4/A3/E/D operons, but indirectly activate that of nemG and nemF. A highly conserved sequence 5′-TGGGGTGKATAGGGGGTA-3′(K=T/G) is verified to be essential for NemR binding.Moreover, four novel targets of NemR, including genes encoding an SsgA-like protein(TU94_12730), a methylmalonyl-CoA mutase(TU94_19950), a thioesterase of oligomycin biosynthesis(TU94_22425) and a MFS family transporter(TU94_24835)are identified. Overexpression of nemR significantly increased nemadectin production by 79.9%, in comparison with NMWT1,suggesting that nemR plays an important role in the nemadectin biosynthesis.

Synthesis of magnetic polyphosphazene-Ag composite particles as surface enhanced Raman spectroscopy substrates for the detection of melamine

Magnetic polyphosphazene(MPZS) particles coated by Ag nanoparticles(MPZS-Ag) have been developed as surface enhanced Raman spectroscopy(SERS) substrates for sensitive detection of melamine in aqueous solutions and milk samples.5,5’-Dithiobis-(2-nitrobenzoic acid)(DTNB) was used as model analyte to test the SERS activity of the MPZS-Ag particles.The prepared MPZS-Ag particles possess both magnetic responsiveness and excellent SERS properties.SERS detection of different concentrations of melamine aqueous solutions and spiked milk samples were performed by the MPZS-Ag particles.The limit of detection(LOD) of the melamine in aqueous solutions was 10^-7 mol/L(0.0126 mg/L) and 0.6 mg/L in real milk samples using the MPZS-Ag particles as SERS substrates.The LOD of the melamine are much lower than the safety values of Food and Drug Administration and Codex Alimentarius Commission.These results indicate that the MPZS-Ag particles have promising application prospect for SERS analysis in food safety fields.

Carbon Nanotube Transistor with Short-Term Memory

Short-Term Memory （STM） is a primary capability of the human brain. Humans use STM to remember a small amount of information, like someone＇s phone number, for a short period of time. Usually the duration of STM is less than 1 minute. Synapses, the connections between neurons, are of vital importance to memory in biological brains. For mimicking the memory function of synapses, Carbon Nanotube （CNT） networks based thin- film transistors with Electric Double Layers （EDL） at the dielectric/channel interface were researched in this work. A response characteristic of pre-synaptic potential pulses on the gate electrode of this CNT synaptic transistor was shown remarkably similar to Excitatory Post-Synaptic Current （EPSC） of biological synapses. Also a multi-level modulatable STM of CNT synaptic transistors was investigated. Post-synaptic current was shown with tunable peak values, on-off ratio, and relaxation time.

Magnetomotive Force Harmonic Reduction Techniques for Fractional-Slot Non-Overlapping Winding Configurations in Permanent-Magnet Synchronous Machines

Compared to conventional distributed winding configurations,the fractional-slot non-overlapping(concentrated)windings exhibit advantages such as short end-winding length,high copper packing factor(particularly with segmented stator structure),low cogging torque,good field weakening capability owing to relatively large d-axis inductance,and better fault tolerant capability due to low mutual inductance.However,one of the key problems of employing concentrated windings in Permanent-magnet Synchronous Machines(PMSMs)is the high eddy-current losses in rotor magnets and/or rotor iron due to the presence of a large number of lower and higher order space harmonics in the stator Magneto-Motive Force(MMF).These MMF harmonics also result in other undesirable effects,such as acoustic noise and vibrations,and localized core saturation which tend to reduce reluctance torque.This paper reviews the current state-of-the-art of the MMF harmonic reduction techniques for concentrated winding configurations in PMSMs,including winding split and shift,delta-star connected windings,multiple 3-phase windings,multilayer windings,uneven turn numbers,and stator flux barriers.Their concepts,advantages and disadvantages are presented and assessed.

Short-circuit fault-tolerant control for five-phase fault-tolerant permanent magnet motors with trapezoidal back-EMF

When a short-circuit fault occurs in a phase,the faulty phase needs to be removed artificially from the system because of the loss of the capability to generate torque.In this case,both the short-circuit current and phase-loss fault would generate additional torque ripples.In this study,a novel fault-tolerant control strategy is introduced to achieve low torque ripple operation of five-phase fault-tolerant permanent magnet synchronous motors with trapezoidal back electromotive force(FTPMSM-TEMF)in the event of a short-circuit fault.The key concept of this method is to compensate for the torque ripples caused by the short-circuit current and the adverse effect of the phase-loss.Based on the torque expression under fault conditions,the torque ripple caused by the short-circuit current can be offset by injecting a certain pulsating component into the torque expression in the phase-loss condition.This would result in smooth operation under fault conditions.Moreover,to track the fault-tolerant alternating currents,the model of the deadbeat current predictive control is extended and restructured for the fault condition.The effectiveness and feasibility of the proposed fault-tolerant strategy are verified by experimental results.

Evaluation of Waste Heat Recovery of Electrical Powertrain with Electro-thermally Coupled Models for Electric Vehicle Applications

The mile range of an electric vehicle(EV)may be reduced significantly in cold weather owing to the energy demand for meeting thermal comfort in the vehicle cabin,as waste heat from a combustion engine is not available for this purpose.Various heat pump-based heating,ventilation,and air conditioning(HVAC)systems can be employed to absorb the heat energy from the surroundings and/or the waste heat from the electrical powertrain to facilitate cabin thermal comfort,thereby extending the EV mile range.However,there is a lack of research on the electro-thermally coupled modelling and evaluation of the thermal performance of HVAC systems.This paper proposes electro-thermally coupled models for the electrical machine and inverter by modelling the key electromagnetic quantities as functions of the torque and speed based on offline parameter extraction from two-dimensional electromagnetic finite element analysis.The proposed electro-thermally coupled models,which are computationally efficient,are integrated into HVAC thermofluid simulation.Comparative studies of three heat pump-based HVAC architectures(conventional ambient heat only,waste heat only,and dual heat source)are performed using the proposed electro-thermally coupled models.The dual heat source HVAC architecture exhibits superior thermal performance over its counterparts in cold weather conditions.