Asymmetric Electrolytes Design for Aqueous Multivalent Metal Ion Batteries

With the rapid development of portable electronics and electric road vehicles,high-energy-density batteries have been becoming front-burner issues.Traditionally,homogeneous electrolyte cannot simultaneously meet diametrically opposed demands of high-potential cathode and low-potential anode,which are essential for high-voltage batteries.Meanwhile,homogeneous electrolyte is difficult to achieve bi-or multi-functions to meet different requirements of electrodes.In comparison,the asymmetric electrolyte with bi-or multi-layer disparate components can satisfy distinct requirements by playing different roles of each electrolyte layer and meanwhile compensates weakness of individual electrolyte.Consequently,the asymmetric electrolyte can not only suppress by-product sedimentation and continuous electrolyte decomposition at the anode while preserving active substances at the cathode for high-voltage batteries with long cyclic lifespan.In this review,we comprehensively divide asymmetric electrolytes into three categories:decoupled liquid-state electrolytes,bi-phase solid/liquid electrolytes and decoupled asymmetric solid-state electrolytes.The design principles,reaction mechanism and mutual compatibility are also studied,respectively.Finally,we provide a comprehensive vision for the simplification of structure to reduce costs and increase device energy density,and the optimization of solvation structure at anolyte/catholyte interface to realize fast ion transport kinetics.

Delving into the dissimilarities in electrochemical performance and underlying mechanisms for sodium and potassium ion storage in N-doped carbon-encapsulated metallic Cu_(2)Se nanocubes

The large volumetric variations experienced by metal selenides within conversion reaction result in inferior rate capability and cycling stability,ultimately hindering the achievement of superior electrochemical performance.Herein,metallic Cu_(2)Se encapsulated with N-doped carbon(Cu_(2)Se@NC)was prepared using Cu_(2)O nanocubes as templates through a combination of dopamine polymerization and hightemperature selenization.The unique nanocubic structure and uniform N-doped carbon coating could shorten the ion transport distance,accelerate electron/charge diffusion,and suppress volume variation,ultimately ensuring Cu_(2)Se@NC with excellent electrochemical performance in sodium ion batteries(SIBs)and potassium ion batteries(PIBs).The composite exhibited excellent rate performance(187.7 mA h g^(-1)at 50 A g^(-1)in SIBs and 179.4 mA h g^(-1)at 5 A g^(-1)in PIBs)and cyclic stability(246,8 mA h g^(-1)at 10 A g^(-1)in SIBs over 2500 cycles).The reaction mechanism of intercalation combined with conversion in both SIBs and PIBs was disclosed by in situ X-ray diffraction(XRD)and ex situ transmission electron microscope(TEM).In particular,the final products in PIBs of K_(2)Se and K_(2)Se_(3)species were determined after discharging,which is different from that in SIBs with the final species of Na_(2)Se.The density functional theory calculation showed that carbon induces strong coupling and charge interactions with Cu_(2)Se,leading to the introduction of built-in electric field on heterojunction to improve electron mobility.Significantly,the theoretical calculations discovered that the underlying cause for the relatively superior rate capability in SIBs to that in PIBs is the agile Na~+diffusion with low energy barrier and moderate adsorption energy.These findings offer theoretical support for in-depth understanding of the performance differences of Cu-based materials in different ion storage systems.

An Approach for Human Posture Recognition Based on the Fusion PSE-CNN-BiGRU Model

This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit(PSECNN-BiGRU)fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments.Firstly,the deep convolutional network is integrated with the Mediapipe framework to extract high-precision,multi-dimensional information from the key points of the human skeleton,thereby obtaining a human posture feature set.Thereafter,a double-layer BiGRU algorithm is utilized to extract multi-layer,bidirectional temporal features from the human posture feature set,and a CNN network with an exponential linear unit(ELU)activation function is adopted to perform deep convolution of the feature map to extract the spatial feature of the human posture.Furthermore,a squeeze and excitation networks(SENet)module is introduced to adaptively learn the importance weights of each channel,enhancing the network’s focus on important features.Finally,comparative experiments are performed on available datasets,including the public human activity recognition using smartphone dataset(UCIHAR),the public human activity recognition 70 plus dataset(HAR70PLUS),and the independently developed home abnormal behavior recognition dataset(HABRD)created by the authors’team.The results show that the average accuracy of the proposed PSE-CNN-BiGRU fusion model for human posture recognition is 99.56%,89.42%,and 98.90%,respectively,which are 5.24%,5.83%,and 3.19%higher than the average accuracy of the five models proposed in the comparative literature,including CNN,GRU,and others.The F1-score for abnormal posture recognition reaches 98.84%(heartache),97.18%(fall),99.6%(bellyache),and 98.27%(climbing)on the self-builtHABRDdataset,thus verifying the effectiveness,generalization,and robustness of the proposed model in enhancing human posture recognition.

Aerosol deposition technology and its applications in batteries

Aerosol deposition(AD)method is a kind of additive manufacturing technology for fabricating dense films such as metals and ceramics at room temperature.It resolves the challenge of integrating ceramic films onto temperaturesensitive substrates,including metals,glasses,and polymers.It should be emphasized that the AD is a spray coating technology that uses powder without thermal assistance to generate films with high density.Compared to the traditional sputter-based approach,the AD shows several advantages in efficiency,convenience,better interfacial bonding and so on.Therefore,it opens some possibilities to the field of batteries,especially all-solidstate batteries(ASSBs)and draws much attention not only for research but also for large scale applications.The purpose of this work is to provide a critical review on the science and technology of AD as well as its applications in the field of batteries.The process,mechanism and effective parameters of AD,and recent developments in AD applications in the field of batteries will be systematically reviewed so that a trend for AD will be finally provided.

Novel cyber-physical collaborative detection and localization method against dynamic load altering attacks in smart energy grids

Owing to the integration of energy digitization and artificial intelligence technology,smart energy grids can realize the stable,efficient and clean operation of power systems.However,the emergence of cyber-physical attacks,such as dynamic load-altering attacks(DLAAs)has introduced great challenges to the security of smart energy grids.Thus,this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids.The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer.First,a data-driven method was proposed to predict the DLAA sequence in the cyber layer.By designing a double radial basis function network,the influence of disturbances on attack prediction can be eliminated.Based on the prediction results,an unknown input observer-based detection and localization method was further developed for the physical layer.In addition,an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs.Consequently,through the collaborative work of the cyber-physics layer,injected DLAAs were effectively detected and located.Compared with existing methodologies,the simulation results on IEEE 14-bus and 118-bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.

Atomically Dispersed Zinc Active Sites Efficiently Promote the Electrochemical Conversion of N_(2) to NH_(3)

At present,the research on highly active and stable nitrogen reduction reaction catalysts is still challenging work for the electrosynthesis of ammonia(NH_(3)).Herein,we synthesized atomically dispersed zinc active sites supported on N-doped carbon nanosheets(Zn/NC NSs)as an efficient nitrogen reduction reaction catalyst,which achieves a high ammonia yield of 46.62μg h^(-1)mg^(-1)_(cat).at-0.85 V(vs RHE)and Faradaic efficiency of 95.8%at-0.70 V(vs RHE).In addition,Zn/NC NSs present great stability and selectivity,and there is no significant change in NH_(3)rate and Faradaic efficiencies after multiple cycles.The structural characterization shows that the active center in the nitrogen reduction reaction process is the Zn-N_(4)sites in the catalyst.DFT calculation confirms that Zn/NC with Zn-N_(4)configuration has a lower energy barrier for the formation of^(*)NNH intermediate compared with pure N-doped carbon nanosheets(N-C NSs),thus promoting the hydrogenation kinetics in the whole nitrogen reduction reaction process.

Proof of Aerobically Autoxidized Self-Charge Concept Based on Single Catechol-Enriched Carbon Cathode Material

The self-charging concept has drawn considerable attention due to its excellent ability to achieve environmental energy harvesting,conversion and storage without an external power supply.However,most self-charging designs assembled by multiple energy harvesting,conversion and storage materials increase the energy transfer loss;the environmental energy supply is generally limited by climate and meteorological conditions,hindering the potential application of these selfpowered devices to be available at all times.Based on aerobic autoxidation of catechol,which is similar to the electrochemical oxidation of the catechol groups on the carbon materials under an electrical charge,we proposed an air-breathing chemical self-charge concept based on the aerobic autoxidation of catechol groups on oxygen-enriched carbon materials to ortho-quinone groups.Energy harvesting,conversion and storage functions could be integrated on a single carbon material to avoid the energy transfer loss among the different materials.Moreover,the assembled Cu/oxygen-enriched carbon battery confirmed the feasibility of the air-oxidation self-charging/electrical discharging mechanism for potential applications.This air-breathing chemical self-charge concept could facilitate the exploration of high-efficiency sustainable air self-charging devices.

Progress in magnetic resonance imaging of the glymphatic system

The glymphatic system(GS)is a newly discovered brain anatomy.Its discovery improves our understanding of brain fluid flow and waste removal paths and provides an anatomical basis for the flow of cerebral interstitial fluid(ISF)and cerebrospinal fluid(CSF).GS occurs through a normal exchange within perivascular space(PVS),facilitating the elimination of metabolic wastes generated by nerve cells from the brain.Therefore,the GS is mainly responsible for the removal of metabolic waste.Reduced GS activity has been observed to be associated with central nervous system disorders such as cerebral small vessel disease(CSVD)and neurodegenerative diseases.Its activity is expected to be an indicator for diagnosing diseases and predicting their prognosis.This review introduces the magnetic resonance imaging(MRI)technology related to the GS suitable for clinical use and the difference in the system's activity in normal and abnormal states.Through a summary of previous research,imaging methods suitable for monitoring the activity of the GS in the clinic were proposed,and their diagnostic effect on different brain disorders was analyzed.This review aims to clarify ideas for the clinical translation of basic research focusing on GS and provide future clinical research directions and perspectives.

Volumetric measurement techniques for assessment of cutaneous neurofibromas:A review

Cutaneous neurofibroma(cNF)is a prevalent clinical manifestation of neurofibromatosis type 1,significantly affecting the well-being and quality of life of the affected individuals.The adoption of reliable and reproducible volumetric measurement techniques is essential for precisely evaluating tumor burden and plays a critical role in the development of effective treatments for cNF.This study focuses on widely used volumetric measurement techniques,including vernier calipers,ultrasound,computed tomography,magnetic resonance imaging,and three-dimensional scanning imaging.It outlines the merits and drawbacks of each technique in assessing the cNF load,providing an overview of their current applications and ongoing research advancements in this domain.

Study of Effects of Plant Growth Regulators on Fruit Quality of Table Grape

The effects of different treatments on the seedlessness and fruit quality of‘Miguang’table grape was studied by using plant growth regulators,gibberellin acid(GA 3)and forchlorfenuron(CPPU),under different concentrations and application time.The results showed that the effects of different treatments on the seedlessness and fruit quality were different.Seedless rate,cluster weight,berry weight,berry shape index,soluble solid content,total acid content,soluble solids to acidity ratio,pulling resistance,turgor pressure and flesh firmness without skin were comprehensively evaluated,as a result of which,the optimum treatment on‘Miguang’table grape was to apply with GA 320 mg/L+SM 200 mg/L at one week before bloom and GA 325 mg/L+CPPU 3 mg/L at two weeks after bloom.

多柔比星脂质体联合达卡巴嗪治疗不可手术切除硬纤维瘤的疗效初探

目的:硬纤维瘤是一种交界性肿瘤,易复发,不转移。对于不可手术切除的硬纤维瘤患者可以考虑药物治疗。本研究探讨使用多柔比星脂质体联合达卡巴嗪方案治疗不可手术切除硬纤维瘤患者的临床效果。方法:选取2015年1月至2019年12月北京大学肿瘤医院收治的35例不可手术切除的硬纤维瘤患者作为研究对象,其中男性11例,女性24例;发病年龄3~53岁,平均年龄27.5岁;肿瘤大小:T2(5~10 cm)6例,T3(10~15 cm)11例,T4(>15 cm)12例,6例多发,无T1(<5 cm)。所有患者均接受多柔比星脂质体联合达卡巴嗪方案化疗,每2个周期进行影像学评效,若有效,至少化疗6个周期,最长12个周期。结果:化疗结束时评效,部分缓解(partial response,PR)10例,疾病稳定(stable disease,SD)24例,疾病进展(progressive disease,PD)1例,无完全缓解(complete response,CR)病例;客观反应率(objective response rate,ORR)为28.6%,疾病控制率(disease control rate,DCR)为97.1%。无进展生存时间(progression-free survival,PFS)2~50个月,中位无进展生存期(median progression-free survival,mPFS)为13个月,平均PFS为14.4个月,23例完成计划化疗患者PFS超过12个月,在5例患者中观察到结束化疗后肿瘤仍持续缩小。结论:对于不可手术切除的硬纤维瘤患者,多柔比星脂质体联合达卡巴嗪方案化疗是一种安全有效的药物治疗方法。

智能医疗包设计,高血压患者的私人医生

来源:https://www.jamesdysonaward.org/en-US/2024/project/cordy这是一款专为高血压患者设计的智能家庭医疗包。该产品通过整合日常服药习惯与血压监测功能,重新定义了患者的自我监测方式和慢性病管理流程。产品由手持检测设备、充电底座以及便携药盒组成。在应用程序中,用户可以查看长期的血压变化趋势,并获得个性化的用药建议及生活方式指导。一旦检测到任何异常,该程序会在人工智能技术的辅助下及时为用户提供相应的疾病管理建议与指导。

Near-Infrared Light-Responsive Cubic Vesicles for Enhanced Blood-Brain Barrier Permeability and Drug Delivery

Delivering therapeutic agents to the central nervous system(CNS)is challenging due to the blood-brain barrier(BBB).This study presents a novel approach utilizing near-infrared(NIR)light-responsive gold-coated cubic vesicles(Auslip)to modulate BBB permeability and enhance drug delivery to glioma cells.Upon NIR activation,Auslip releases encapsulated agents and transiently opens the BBB.The results demonstrate that Auslip increases doxorubicin(DOX)delivery to glioma C6 cells in a co-culture model with human brain microvascular endothelial cells(hCMEC/D3).This approach offers a promising strategy for CNS therapeutics by enabling simultaneous BBB opening and drug release through optical stimulation.

Two-Stage Segmentation of Lung Cancer Metastasis Lesions by Fusion of Multi-Resolution Features

The deep learning method automatically extracts advanced features from a large amount of data, avoiding cumbersome manual feature screening, and using digital pathology and artificial intelligence technology to build a computer-aided diagnosis system to help pathologists quickly make objective and reliable diagnoses and improve work efficiency. Because pathological images are limited by factors such as sample size, manual labeling expertise, and complexity, artificial intelligence algorithms have not been extensively and in-depth researched on pathological images of lung cancer metastasis. Therefore, this paper proposes a lung cancer metastasis segmentation method based on pathological images, to further improve the computer-aided diagnosis method of lung cancer.

Efficacy of “Acceptance and Commitment Therapy” Psychological Nursing in a Stroke Patient

Objective: To summarize 1 case of ACT (Acceptance and Commitment Therapy, as “ACT”) psychological nursing clinical experience. Method: ACT Application for psychological nursing, provides detailed program guidance for psychological care. Results: Sleep quality, psychological flexibility and self-management ability of the patient have been improved. Conclusion: It’s the first time to apply ACT to the psychological nursing for a stroke patient, which has achieved good results;it provides a detailed clinical experience as guidance for the development of psychological nursing;it also provides a clinical basis for the follow-up exploration of psychological nursing technology model.

43例血管肉瘤临床治疗结果分析

目的:回顾性分析血管肉瘤(angiosarcoma,AS)患者临床治疗结果,并进行分析比较,确定结果的预测因素。方法:收集2000年1月至2021年3月北京大学肿瘤医院收治的43例血管肉瘤患者临床资料,采用SPSS 20.0软件进行统计学单因素及多因素分析,主要疗效指标包括无进展生存期(progression-free survival,PFS)和总生存期(overall survival,OS),随访方式包括住院、门诊及电话随访,截止时间为2022年5月。结果:截至随访结束,43例患者中死亡21例(49%),生存22例(51%),中位随访时间为52(6~131)个月。中位PFS为16个月,中位OS为52个月。1、3、5年的PFS分别为55.6%、34.3%和22.2%;OS为93%、61.1%和49.7%。单因素分析显示,发病部位、肿瘤深度、分级及治疗方式与PFS相关;肿瘤深度、破溃、分级及治疗方式与OS相关(P<0.05)。多因素分析显示,肿瘤深度及治疗方式是PFS的独立预后因素;肿瘤深度、破溃、分级是OS的独立预后因素(P<0.05)。结论:血管肉瘤临床以手术治疗为基础,但要避免盲目非计划手术;患者或可以从新辅助治疗中获益,化疗以紫杉类和蒽环类为主,对于局部晚期的患者可进行术前转化治疗;放疗对提高局部控制率有帮助;应重视手术、化疗、放疗的综合治疗。

二代分子测序在软组织肉瘤中的应用价值分析

目的:探索中国人群软组织肉瘤常见的基因变异;分析二代基因测序技术(next-generation sequencing,NGS)在软组织肉瘤诊疗中的价值。方法:本研究纳入北京大学肿瘤医院2018年1月至2020年12月接受NGS检测的软组织肉瘤(soft tissue sarcomas,STS)患者,分析基因变异的频率和分布特点;统计具有临床治疗意义的基因变异情况,包括符合美国国立综合癌症网络(NCCN)或中国临床肿瘤学会指南(CSCO)治疗建议、超适应证治疗药物,或正在招募中的针对特定变异的临床试验;探索STS的肿瘤突变负荷(tumor mutational burden,TMB)水平及微卫星不稳定(microsatellite instability,MSI)状态。结果:108例患者中有74例(68.5%)的基因变异数≥1。共发现78种不同的基因变异,变异频率排名前10位的基因包括TP5312.3%(22/179)、MDM27.3%(13/179)、CDK45.6%(10/179)、CDKNB 3.9%(7/179),RB13.9%(7/179),ALK 2.8%(5/179),ATRX 2.8%(5/179),MCL12.8%(5/179),FGFR12.2%(4/179),PIK3CA 2.2%(4/179)。治疗获益方面,108例患者中有7例(6.5%)的突变基因符合指南治疗建议,31例(28.7%)具有超适应证治疗可能,56例(51.9%)可接受正在招募中的针对变异基因的STS临床试验,62例(57.4%)符合指南治疗建议或存在超适应证治疗可能或符合正在招募中的针对变异基因的STS临床实验。全组中位TMB值为2.42(0~60)muts/Mb,108例患者中有10例(9.3%)TMB值≥10 muts/Mb,24例(22.2%)TMB值5~10 muts/Mb,74例(68.5%)TMB值<5 muts/Mb。89例患者接受了MSI检测,仅1例患者为微卫星高度不稳定(MSI-H)(1.1%)。结论:软组织肉瘤常见的基因变异包括TP53、MDM2、CDK4、CDKNB和RB1。通过NGS检测获得符合指南治疗建议的比例较低,但获得超适应证用药和临床试验建议的比例较高。TMB值、MSI状态对STS患者的临床意义还需进一步证实。

聚醚醚酮物理老化行为与成型模拟

通过对注塑成型聚醚醚酮(PEEK)试样进行人工加速物理老化实验,得到试样屈服应力随物理老化时间的变化规律,以132℃为参考温度最终拟合得到以PEEK屈服应力为表征的物理老化模型。基于此模型并结合时温等效原理,预测PEEK注塑成型及后期物理老化过程中的屈服应力变化,并通过实验进行了验证。

Rapamycin promotes Schwann cell migration and nerve growth factor secretion

Rapamycin, similar to FKS06, can promote neural regeneration in vitro. We assumed that the mechanisms of action of rapamycin and FK506 in promoting peripheral nerve regeneration were similar. This study compared the effects of different concentrations of raparnycin and FK506 on Sc hwann cells and investigated effects and mechanisms of rapamycin on improving peripheral nerve regeneration. Results demonstrated that the lowest rapamycin concentration （1.53 nmol/L） more significantly promoted Schwann cell migration than the highest FK506 concentration （100μmol/L）. Rapamycin promoted the secretion of nerve growth factors and upregulated growth-associated protein 43 expression in Schwann cells, but did not significantly affect Schwann cell proliferation. Therefore, rapamycin has potential application in peripheral nerve regeneration therapy.

Chip-Based High-Dimensional Optical Neural Network

Parallel multi-thread processing in advanced intelligent processors is the core to realize high-speed and high-capacity signal processing systems.Optical neural network(ONN)has the native advantages of high parallelization,large bandwidth,and low power consumption to meet the demand of big data.Here,we demonstrate the dual-layer ONN with Mach-Zehnder interferometer(MZI)network and nonlinear layer,while the nonlinear activation function is achieved by optical-electronic signal conversion.Two frequency components from the microcomb source carrying digit datasets are simultaneously imposed and intelligently recognized through the ONN.We successfully achieve the digit classification of different frequency components by demultiplexing the output signal and testing power distribution.Efficient parallelization feasibility with wavelength division multiplexing is demonstrated in our high-dimensional ONN.This work provides a high-performance architecture for future parallel high-capacity optical analog computing.