MXene Hollow Spheres Supported by a C–Co Exoskeleton Grow MWCNTs for Efficient Microwave Absorption

High-performance microwave absorption(MA) materials must be studied immediately since electromagnetic pollution has become a problem that cannot be disregarded. A straightforward composite material, comprising hollow MXene spheres loaded with C–Co frameworks, was prepared to develop multiwalled carbon nanotubes(MWCNTs). A high impedance and suitable morphology were guaranteed by the C–Co exoskeleton, the attenuation ability was provided by the MWCNTs endoskeleton, and the material performance was greatly enhanced by the layered core–shell structure. When the thickness was only 2.04 mm, the effective absorption bandwidth was 5.67 GHz, and the minimum reflection loss(RLmin) was-70.70 d B. At a thickness of 1.861 mm, the sample calcined at 700 ℃ had a RLmin of-63.25 d B. All samples performed well with a reduced filler ratio of 15 wt%. This paper provides a method for making lightweight core–shell composite MA materials with magnetoelectric synergy.

Ageing-related bone and immunity changes:insights into the complex interplay between the skeleton and the immune system

Ageing as a natural irreversible process inherently results in the functional deterioration of numerous organ systems and tissues,including the skeletal and immune systems.Recent studies have elucidated the intricate bidirectional interactions between these two systems.

Rational design of carbon skeleton interfaces for highly reversible sodium metal battery anodes

Sodium metal batteries(SMBs)have attracted increasing attention over time due to their abundance of sodium resources and low cost.However,the widespread application of SMBs as a viable technology remains a great challenge,such as uneven metallic deposition and dendrite formation during cycling.Carbon skeletons as sodiophilic hosts can alleviate the dendrite formation during the plating/stripping.For the carbon skeleton,how to rationalize the design sodiophilic interfaces between the sodium metal and carbon species remains key to developing desirable Na anodes.Herein,we fabricated four kinds of structural features for carbon skeletons using conventional calcination and flash Joule heating.The roles of conductivity,defects,oxygen content,and the distribution of graphite for the deposition of metallic sodium were discussed in detail.Based on interface engineering,the J1600 electrode,which has abundant Na-C species on its surface,showed the highest sodiophilic.There are uniform and rich F-Na species distributed in the inner solid electrolyte interface layer.This study investigated the different Na-deposition behavior in carbon hosts with distinct graphitic arrangements to pave the way for designing and optimizing advanced electrode materials.

Vacancy defect MoSeTe embedded in N and F co-doped carbon skeleton for high performance sodium ion batteries and hybrid capacitors

Sodium-ion batteries(SIBs) and hybrid capacitors(SIHCs) have garnered significant attention in energy storage due to their inherent advantages,including high energy density,cost-effectiveness,and enhanced safety.However,developing high-performance anode materials to improve sodium storage performa nce still remains a major challenge.Here,a facile one-pot method has been developed to fabricate a hybrid of MoSeTe nanosheets implanted within the N,F co-doped honeycomb carbon skeleton(MoSeTe/N,F@C).Experimental results demonstrate that the incorporation of large-sized Te atoms into MoSeTe nanosheets enlarges the layer spacing and creates abundant anion vacancies,which effectively facilitate the insertion/extraction of Na^(+) and provide numerous ion adsorption sites for rapid surface capacitive behavior.Additionally,the heteroatoms N,F co-doped honeycomb carbon skeleton with a highly conductive network can restrain the volume expansion and boost reaction kinetics within the electrode.As anticipated,the MoSeTe/N,F@C anode exhibits high reversible capacities along with exceptional cycle stability.When coupled with Na_(3)V_(2)(PO_(4))_(3)@C(NVPF@C) to form SIB full cells,the anode delivers a reversible specific capacity of 126 mA h g^(-1) after 100 cycles at 0.1 A g^(-1).Furthermore,when combined with AC to form SIHC full cells,the anode demonstrates excellent cycling stability with a reversible specific capacity of50 mA h g^(-1) keeping over 3700 cycles at 1.0 A g^(-1).In situ XRD,ex situ TEM characterization,and theoretical calculations(DFT) further confirm the reversibility of sodium storage in MoSeTe/N,F@C anode materials during electrochemical reactions,highlighting their potential for widespread practical application.This work provides new insights into the promising utilization of advanced transition metal dichalcogenides as anode materials for Na^(+)-based energy storage devices.

The integration of dinitropyrazole and 1,3,4-oxadiazole:A novel hybrid heterocyclic skeleton for balancing energy and stability

In this study,a new energetic hybrid skeleton was constructed through the integration of nitropyrazole and 1,3,4-oxadiazole skeletons in a molecule.Furthermore,the energetic precursor(2),the azo-bridged compound(3),the neutral nitramine(4)and the corresponding energetic salts(5-7)were synthesized.Their physicochemical and energetic properties we re experimentally and theo retically evaluated.Among the developed compounds,the azo-bridged compound(3)and dihydroxylammoinium(6)display high detonation performances(3,D_(v)=8904 m/s,P=34.47 GPa;6,D_(v)=9025 m/s,P=34.66 GPa),moderate sensitivities(3,IS=16 J,FS=120 N;6,IS=20 J,FS=312 N)and good densities(3,1.87 g/cm^(3);6,1.81 g/cm^(3)),which indicates that they have the potential to replace the traditional high-energy explosive RDX.The results show that the integration of different energetic skeletons can achieve a good balance between energy and sensitivity.

Semantic segmentation of pyramidal neuron skeletons using geometric deep learning

Neurons can be abstractly represented as skeletons due to the filament nature of neurites.With the rapid development of imaging and image analysis techniques,an increasing amount of neuron skeleton data is being produced.In some scienti fic studies,it is necessary to dissect the axons and dendrites,which is typically done manually and is both tedious and time-consuming.To automate this process,we have developed a method that relies solely on neuronal skeletons using Geometric Deep Learning(GDL).We demonstrate the effectiveness of this method using pyramidal neurons in mammalian brains,and the results are promising for its application in neuroscience studies.

Ultrathin poly(cyclocarbonate-ether)-based composite electrolyte reinforced with high-strength functional skeleton

Composite polymer electrolytes(CPEs)are considered to be the most promising to break through the performance and safety limitations of traditional lithium-ion batteries because of their excellent electrochemical and mechanical properties.Aiming at the performance limitations of the most common polyether matrix such as poly(ethylene oxide)(PEO),a novel poly(cyclocarbonate-ether)polymer matrix was prepared by in-situ thermal curing,the weaker interaction between its C=O bond and Li^(+)can promote the rapid transport of Li^(+).Adding ionic liquid and active filler LLZTO to the matrix can synergistically reduce the crystallinity of matrix and promote the dissociation of lithium salts.In addition,a 3D functional skeleton made of polyacrylonitrile(PAN)and lithium fluoride(LiF)can greatly improve the mechanical strength of polymer matrix after cold pressing,and Li F is also conducive to interface stability.The thickness of the optimal sample(VP6L/CPL)was only 25μm,and its ionic conductivity,lithium ion transference number,and electrochemical stability window were as high as 7.17×10^(-4)S cm^(-1)(25℃),0.54 and 5.4 V,respectively,while the mechanical strength reaches 6.1 MPa,which can fully inhibit the growth of lithium dendrites.The excellent electrochemical performance and mechanical strength enable the assembled Li|VP6L/CPL|Li battery to be continuously charged for over 200 h and cycled stably for more than 2300 h,and Li|VP6L/CPL|LFP battery can be stably cycled for more than 400 and 550 cycles at 1 C(40℃)and 0.5 C(25℃),respectively.

Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and prediction.However,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized assessment.In this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin Lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton features.Furthermore,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in monkeys.Using the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual detection.Mon Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.

Glucose uptake and distribution across the human skeleton using state-of-the-art total-body PET/CT

A growing number of studies have demonstrated that the skeleton is an endocrine organ that is involved in glucose metabolism and plays a significant role in human glucose homeostasis.However,there is still a limited understanding of the in vivo glucose uptake and distribution across the human skeleton.To address this issue,we aimed to elucidate the detailed profile of glucose uptake across the skeleton using a total-body positron emission tomography(PET)scanner.A total of 41 healthy participants were recruited.Two of them received a 1-hour dynamic total-body^(18)F-fluorodeoxyglucose(^(18)F-FDG)PET scan,and all of them received a10-minute static total-body^(18)F-FDG PET scan.The net influx rate(K_i)and standardized uptake value normalized by lean body mass(SUL)were calculated as indicators of glucose uptake from the dynamic and static PET data,respectively.The results showed that the vertebrae,hip bone and skull had relatively high Kiand SUL values compared with metabolic organs such as the liver.Both the K_(i) and SUL were higher in the epiphyseal,metaphyseal and cortical regions of long bones.Moreover,trends associated with age and overweight with glucose uptake(SUL_(max)and SUL_(mean))in bones were uncovered.Overall,these results indicate that the skeleton is a site with significant glucose uptake,and skeletal glucose uptake can be affected by age and dysregulated metabolism.

In Situ Reaction Fabrication of a Mixed-Ion/Electron-Conducting Skeleton Toward Stable Lithium Metal Anodes

Lithium metal batteries are emerging as a strong candidate in the future energy storage market due to its extremely high energy density.However,the uncontrollable lithium dendrites and volume change of lithium metal anodes severely hinder its application.In this work,the porous Cu skeleton modified with Cu_(6)Sn_(5)layer is prepared via dealloying brass foil following a facile electroless process.The porous Cu skeleton with large specific surface area and high electronic conductivity effectively reduces the local current density.The Cu_(6)Sn_(5)can react with lithium during the discharge process to form lithiophilic Li_(7)Sn_(2)in situ to promote Li-ions transport and reduce the nucleation energy barrier of lithium to guide the uniform lithium deposition.Therefore,more than 300 cycles at 1 mA cm^(−2)are achieved in the half-cell with an average Coulombic efficiency of 97.5%.The symmetric cell shows a superior cycle life of more than 1000 h at 1 mA cm^(−2)with a small average hysteresis voltage of 16 mV.When coupled with LiFePO_(4)cathode,the full cell also maintains excellent cycling and rate performance.

Skeleton-Based Volumetric Parameterizations for Lattice Structures

Lattice structures with excellent physical properties have attracted great research interest.In this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice structures.The skeleton model is divided into three types of nodes.And the corresponding algorithms are utilized to construct diverse types of volume parametric nodes.The unit-cell is assembled with distinct nodes according to the geometric features.The final lattice structure is created by the periodic arrangement of unit-cells.Several different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed method.The quality is assessed in terms of the value of the Jacobian matrix.Moreover,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.

The skeleton of 5,7-fused bicyclic imidazole-diazepine for heat-resistant energetic materials

In light of the low yields and complex reaction routes of some well-known 5,5-fused and 5,6-fused bicyclic compounds,a series of 5,7-fused bicyclic imidazole-diazepine compounds were developed with high yields by only two efficient steps.Significantly,the seven-membered heterocyclic ring has a stable energetic skeleton with multiple modifiable sites.However,the 5,7-fused bicyclic energetic compounds were rarely reported in the area of energetic materials.Three neutral compounds 1,2 and 4 were synthesized in this work.To improve the detonation performances of the 5,7-fused neutral compounds,corresponding perchlorate 1a and 2a were further developed.The physicochemical and energetic performances of all newly developed compounds were experimentally determined.All newly prepared energetic compounds exhibit high decomposition temperatures(Td:243.8-336℃)and low mechanical sensitivities(IS:>15 J,FS:>280 N).Among them,the velocities performances of 1a(Dv=7651 m/s)and 4(Dv=7600 m/s)are comparable to that of typical heat-resistant energetic material HNS(Dv=7612 m/s).Meanwhile,the high decomposition temperature and low mechanical sensitivities(Td=336℃;IS=32 J;FS>353 N)of 4 are superior to that of HNS(Td=318℃;IS=5 J;FS=250 N).Hence,the 5,7-fused bicyclic compounds with high thermostability,low sensitivities and adjustable detonation performance have a clear tendency to open up a new space for the development of heat-resistant energetic materials.

IMC-skeletons reinforced high-temperature interconnections through low-temperature TLP bonding and micron composite solders

The traditional nano-sintering or TLP techniques are generally expensive,time-consuming,and hence unsuitable for realizing practical mass production.Herein,we have developed an improved TLP process to rapidly produce IMC-skeleton structures across the bonding region by initiating a localized liquid-solid interaction among micron particles at traditional soldering temperatures.The developed IMC skeletons can reinforce solder alloys and provide remarkable mechanical stability and electrical capabilities at high temperatures.As a result,the IMC-skeleton strengthened interconnections exhibited higher thermal/electrical conductivity,lower hardness and almost doubled strength than traditional full-IMC joints,attaining 87.4 MPa and 30.2 MPa at room condition and 350℃.Meanwhile,the necessary heating time to form metallurgical bonds was shortened,one-fifth of nano-sintering and one-tenth of TLP bonding,and the material cost was significantly reduced.This proposed technique enabled the fast,low-cost manufacturing of electronics that can serve at temperatures as high as 200−350℃.Besides,the interfacial reactions among particles and the correlated phase evolution process were studied in this research.The formation mechanism of IMC skeletons was analyzed.The correlated influencing factors and their effect on the mechanical,thermal and electrical properties of joints were revealed,which may help the design and extensive uses of such techniques in various high-temperature/power applications.

Uniform nanoplating of metallic magnesium film on titanium dioxide nanotubes as a skeleton for reversible Na metal anode

To meet the low-cost concept advocated by the sodium metal anode,this paper reports the use of a pulsed electrodeposition technology with ionic liquids as electrolytes to achieve uniform nanoplating of metallic magnesium films at around 20 nm on spaced titanium dioxide(TiO_(2))nanotubes(STNA-Mg).First,the sodiophilic magnesium metal coating can effectively reduce the nucleation overpotential of sodium metal.Moreover,three-dimensional STNA can limit the volume expansion during sodium metal plating and stripping to achieve the ultrastable deposition and stripping of sodium metals with a high Coulombic efficiency of up to 99.5%and a small voltage polarization of 5 mV in symmetric Na||Na batteries.In addition,the comparative study of sodium metal deposition behavior of STNA-Mg and STNA-Cu prepared by the same route further confirmed the advantage of magnesium metal to guide sodium metal growth.Finally,the prepared STNA-Mg-Na metal anode and commercial sodium vanadium phosphate cathode were assembled into a full cell,delivering a discharge capacity of 110.2 mAh·g^(-1)with a retention rate of 95.6%after 110 cycles at 1C rate.

Two stream skeleton behavior recognition algorithm based on Motif-GCN

Compared with RGB videos and images,human bone data is less vulnerable to external factors and has stronger robustness.Therefore,behavior recognition methods based on skeletons are widely studied.Because graph convolution network(GCN)can deal with the irregular topology data of hu-man skeletons very well,more and more researchers apply GCN to human behavior recognition.Tra-ditional graph convolution methods only consider the joints with physical connectivity or the same type when building the behavior recognition model based on human skeletons structure,which cannot capture higher-order information better.To solve this problem,Motif-GCN is used in this paper to ex-tract spatial features.The relationship between the joints with natural connection in the human body is encoded by the first Motif-GCN,and the possible relationship between the unconnected joints in the human skeleton is encoded by the second Motif-GCN.In this way,the relationship between non-physical joints can be strengthened.Then a two stream framework combining joint and bone informa-tion is used to capture more action information.Finally,experiments are conducted on two subdata-sets X-Sub and X-View of NTU-RGB+D,and the accuracy shown in Top-1 classification results is 89.5%and 95.4%respectively.The experimental results are 1.0%and 0.3%higher than those of the 2S-AGCN model respectively.The superiority of this method is also proved by the experimental results.

Comparison of Sternal Wound Complication after Off-Pump CABG between Skeletonized and Pedicled LIMA Harvesting: A Single Centre Experience in Bangladesh

Background: Off-pump coronary artery bypass grafting (OPCAB) is a surgical procedure that has gained popularity due to its potential benefits over traditional coronary artery bypass grafting, including reduced morbidity and mortality. However, sternal wound complication (SWC) remains challenging following the procedure. The technique of left internal mammary artery (LIMA) harvesting has been shown to impact the incidence of SWC. This study aimed to compare the incidence of SWC between two techniques of LIMA harvesting, i.e., skeletonized and pedicled. Methods: The study was conducted at the Department of Cardiac Surgery, Bangabandhu Sheikh Mujib Medical University, and included 60 patients who underwent OPCAB. The patients were divided into two groups of 30 each based on the technique of LIMA harvesting used, i.e., skeletonized (group A) or pedicled (group B). The postoperative ICU care was given to each patient as per the protocol. The statistical analysis was conducted using the SPSS version 26.0 for Windows software. Results: The results showed that 5 (8.33%) patients developed SWC, with 1 (1.67%) patient in group A and 4 (6.66%) patients in group B. However, the occurrence of SWC was not statistically significant between the two groups (p = 0.35). The mean age, gender distribution, and comorbidities such as hypertension, diabetes, dyslipidemia, and anemia were also not statistically significant between the two groups. The number of smokers was statistically significant between the two groups (p = 0.03), and the occurrence of SWC was found to be higher in smoker patients in group B (p = 0.04). Preoperative and postoperative parameters such as duration of operation, duration of mechanical ventilation, duration of chest drains, duration of the central venous line, and amount of postoperative mediastinal bleeding were also not statistically significant between the two groups. The distribution of wound complications, duration of ICU stays, and hospital stay between the two groups was also not statistically significant. Conclusion: In conclusion, this study found that the incidence of SWC was less in skeletonized LIMA harvesting than in pedicled LIMA harvesting after OPCAB. However, this finding was not statistically significant. Further studies with larger sample sizes may be needed to confirm these results and determine the appropriate technique of LIMA harvesting to decrease the incidence of SWC after OPCAB.

基于多流语义图卷积网络的人体行为识别

与基于图像的行为识别方法相比,利用人体骨架信息进行识别能有效克服复杂背景、光照变化以及外貌变化等因素影响。但是,目前主流的基于人体骨架的行为识别方法存在参数量过大、运算速度慢等问题。对此,提出一种多流轻量级语义图卷积的行为识别方法。设计多流语义引导的图卷积网络(MS-SGN),将骨架信息分别表达为骨长流、关节流和细粒度流3种数据流形式,再对嵌入语义信息的数据流通过自适应图卷积提取空间特征,并采用不同内核和膨胀率的多尺度时域卷积提取时域特征,最后对各流分类结果进行加权融合。实验结果表明,该方法在NTU60 RGB+D数据集上的识别精度分别为90.0%(X-Sub)和95.83%(X-View),在NTU120 RGB+D数据集上的识别精度分别为83.4%(X-Sub)和84.0%(X-View),优于SGN、Logsin-RNN等主流方法,且网络框架更为轻量化。

瓮马铁路乌江特大桥设计关键技术研究

新建瓮马铁路乌江特大桥跨越两山之间深谷,地形复杂、设计难度大。为研究该桥梁方案,首先阐述了主桥的方案构思和结构设计,然后通过空间有限元软件对本桥进行静、动力仿真分析,总结了大跨铁路劲性骨架混凝土拱桥构造和受力特性。结果表明:主跨337 m上承式劲性骨架混凝土拱桥具有刚度大、徐变小、后期养护维修工作量小等优点,主拱圈采用小矢跨比设计,兼顾安全、经济、环保和美观,能够满足铁路桥梁跨越山区“V”形峡谷的要求;主拱圈由劲性钢管混凝土骨架外包C55无收缩混凝土构成,通过分层分段浇筑方案改善拱圈各构件的内力;拱上结合梁采用两片工字形钢与混凝土桥面板相结合的形式,钢梁栓焊结合,便于制造、运输和施工;拱座采用梯形断面扩大基础,基础开挖永临结合,有效降低施工风险;数值分析表明该桥结构的刚度、强度、稳定性均能满足规范要求,能够满足客货共线铁路的安全性和乘坐舒适性要求。可为其他山区铁路桥梁桥式研究提供参考。

海相优质烃源岩中硅钙质来源:生物骨壁壳及其碎屑

应用超显微有机岩石学等技术,从生物分子构成及其稳定性的角度,探讨硅质、钙质骨壁壳等生物碎屑与优质烃源岩的关系。常见的具有生物硅及硅质衍生物的生物主要是放射虫等原生动物、海绵动物、硅藻、金藻及某些似鱼鳞藻疑源类等浮游藻类的硅质骨壁壳及其碎屑。在优质烃源岩中能保存下来的生物钙主要来源于浮游有孔虫、翼足虫等动物和颗石藻等浮游藻类或疑源类的钙质骨壁壳及其碎屑。这些生物硅质、钙质骨壁壳碎屑颗粒中常常含有不等量的有机质(果胶或硬蛋白,相当于Ⅲ型有机质),高成熟—过成熟阶段可生成一定量烃气,并可保存于生物结构的原生孔隙中。

废旧发泡混凝土定型相变材料制备及热性能研究

为规模化消纳城市固体废弃物,降低废旧发泡混凝土大量堆积对城市生态环境的破坏。提出以废旧发泡混凝土作为骨架材料,对其进行预烧结处理,以Na_(2)CO_(3)为相变材料制备定型相变材料。结果表明:废旧发泡混凝土可以负载质量分数为45%的Na_(2)CO_(3);差示扫描量热法(DSC)测得该定型相变材料的熔化潜热为126.7 J/g;X射线衍射法(XRD)和傅里叶变换红外法(FT-IR)表明,骨架材料和相变材料之间有良好的化学相容性;激光导热分析法(LFA)测得该定型相变材料的导热系数最大为0.24 W/(m·K)。