Observation and modelling of snow and sea ice mass balance and its sensitivity to atmospheric forcing during spring and summer 2007 in the Central Arctic

Snow depth and sea ice thickness were observed applying an ice mass balance buoy(IMB)in the drifting ice station Tara during the International Polar Year in 2007.Detailed in situ observations on meteorological variables and surface fluxes were taken during May to August.For this study,the operational analyses and short-term forecasts from two numerical weather prediction(NWP)models(ECMWF and HIRLAM)were extracted for the Tara drift trajectory.We compared the IMB,meteorological and surface flux observations against the NWP products,also applying a one-dimensional thermodynamic sea ice model(HIGHTSI)to calculate the snow and ice mass balance and its sensitivity to atmospheric forcing.The modelled snow depth time series,controlled by NWP-based precipitation,was in line with the observed one.HIGHTSI reproduced well the snowmelt onset,the progress of the melt,and the first date of snow-free conditions.HIGHTSI performed well also in the late August freezing season.Challenges remain to model the“false bottom”observed during the melting season.The evolution of the vertical temperature profiles in snow and ice was better simulated when the model was forced by in situ observations instead of NWP results.During the melting period,the nonlinear ice temperature profile was successfully modelled with both forcing options.During spring and the melting season,total sea ice mass balance was most sensitive to uncertainties in NWP results for the downward longwave radiation,followed by the downward shortwave radiation,air temperature,and wind speed.

Effects of Different Pretreatment Modes on the Enzymatic Digestibility of Corn Leaf and Corn Stalk

Corn leaf and corn stalk were pretreated with only hot water and 0.1% sulfuric acid at 160℃ or 200℃, respectively. For hot water pretreatment, the pH of corn stalk hydrolysate decreased more rapidly than that of corn leaf as the reaction time increased. On the contrary, the pH of corn leaf hydrolysate increased more than that of corn stalk with diluted acid addition. Increasing temperature enhanced the xylose dissolution rate and increased cellulose digestibility. Compared with hot water, 0.1% sulfuric acid addition improved the xylan removal and the enzymatic hydrolysis of both corn leaf and corn stalk residue. Much less xylan must be removed to achieve the same cellulose digestibility for the corn leaf as that for the corn stalk; 55% digestibility was obtained when only 32% xylan was removed from corn leaf, whereas corn stalk required removal of about 50% of the xylan to achieve the same di- gestibility. Overall, the descending order of enzymatic digestibility was: dilute acid hydrolysate of corn leaf > dilute acid hydrolysate of corn stalk > water-only hydrolysate of corn leaf > water-only hydrolysate of corn stalk. Finally, one separate pretreatment strategy was developed to transfer corn leaf and corn stalk to fermentable sugars for fur- ther bioenergy production.

MR-GUIDED PULSE OXIMETRY IMAGING OF BREAST IN VIVO

A near-infrared(NIR)tomography system with spectrally-encoded sources in two wavelength bands was built to quantify the temporal oxyhemoglobin and deoxyhemoglobin contrast in breast tissue at a 20 Hz bandwidth.The system was integrated into a 3T magnetic resonance(MR)imaging system through a customized breast coil interface for simultaneous optical and MRI acquisition.In this configuration,the MR images provide breast tissue structural information for NIR spectroscopy of adipose andfibro-glandular tissue in breast.Spectral characterization performance of the NIR system was verified through dynamic phantom experiments.Normal human subjects were imaged withfinger pulse oximeter(PO)plethysmogram synchronized to the NIR system to provide a frequency-locked reference.Both the raw data from the NIR system and the recovered absorption coefficients of the breast at two wavelengths showed the same frequency of about 1.3 Hz as the PO output.The frequency lock-in approach provided a practical platform for MR-localized recovery of small pulsatile variations of oxyhemoglobin and deoxyhemoglobin in the breast,which are related to the heartbeat and vascular resistance of the tissue.

Zr基块体非晶合金的摩擦磨损行为(英文)

采用销盘式摩擦实验研究Zr基块体非晶合金分别在空气与氩气环境中的摩擦磨损行为。结果表明,在16N和23N2种不同载荷下,非晶试样在氩气中的磨损量都比在空气中的低45%以上。通过X射线衍射仪、差示扫描量热分析仪、扫描电子显微镜和光学表面轮廓仪等检测分析手段对磨损试样摩擦面的形貌和微观结构进行表征,发现在空气中磨损试样的表面存在大量摩擦颗粒和犁沟,而氩气中的试样表面相对平滑;非晶试样的磨损机理在空气中以磨粒磨损为主,而在氩气中则为粘着磨损。

微粒对多晶冰流变行为的影响——(Ⅱ)滞弹性行为

用反相直接加载的方法研究了微粒对多晶冰滞弹性的影响.结果表明:在较高频率时(1Hz和10-1Hz),滞弹性应变与应力峰值呈线性关系;在较低频率时(10-2Hz),其应力/应变偏离线性关系.微粒在高频时(1Hz)通过阻碍晶界滑移对晶界弛豫产生重要影响,增加了模量和降低了内耗.但微粒对低频时的位错弛豫没有明显的影响.通过滞弹性实验计算了非线性弛豫模型的两个重要参数,计算表明K值约为0.07Pa,α值约为0.54.

微粒对多晶冰及冰川流变行为的影响——(Ⅰ)基于位错的弛豫模型

为量化冰及冰川在流变过程中位错密度随流变应力的变化,发展了一个基于位错的非线性弛豫模型.模型的计算表明:在冰的指数蠕变阶段,滞弹性试验所形成的应力/应变滞后环的宽度与面积随流变应力的增加呈线性增加,位错密度随流变应力的增加呈平方增加;在冰的线性蠕变阶段,滞弹性试验所形成的应力/应变滞后环的宽度、面积和位错密度保持不变.

Enabling stable sodium metal cycling by sodiophilic interphase in a polymer electrolyte system

Enabling highly reversible sodium(Na) metal anodes in a polymer electrolyte(PE) system is critical for realizing next-generation batteries with lower cost,higher energy,and improved safety.However,the uneven Na deposition and high Na/PE interphase resistance lead to poor reversibility and short cycle life of Na metal anodes.To tackle these problems,here a variety of metal nanoparticles(M-np,M=Al,Sn,In or Au) are deposited onto copper(Cu) foils to synthesize binder-free M-np@Cu substrates for Na plating/stripping.Notably,the Au-np@Cu substrate provides abundant preferential nucleation/growth sites,decreasing Na nucleation barrier and thus promoting uniform Na deposition.Accordingly,stable Na metal anodes are achieved with high reversible capacities,long cycle life,and high usage of Na.With the Au-np@Cu/Na anode and PE,the full cell using a commercial bulk sulfur cathode exhibits a reversible capacity of>400 mAh g^(-1) with near-100% Coulombic efficiency over 200 cycles.

乳腺肿瘤新辅助化疗反应的断层漫散射频谱评价:肿瘤感兴趣区变化的病例研究

目的评价两种方法通过感兴趣区（ROI）分析总结的断层漫散射频谱（DOS）数据，鉴别进展期乳腺癌病人行新辅助治疗后完全反应和不完全反应，并估算这些方法对于未来大规模研究设计强力分析的标准差。材料和方法本研究经学术审核委员会通过，参试者符合HIPAA影像检查的要求，提供书面知情同意通知，并给与一定补偿。

High-throughput calculations of charged point defect properties with semi-local density functional theory— performance benchmarks for materials screening applications

Calculations of point defect energetics with Density Functional Theory(DFT)can provide valuable insight into several optoelectronic,thermodynamic,and kinetic properties.These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches.For applications of DFT-based high-throughput computation for data-driven materials discovery,point defect properties are of interest,yet are currently excluded from available materials databases.This work presents a benchmark analysis of automated,semi-local point defect calculations with a-posteriori corrections,compared to 245“gold standard”hybrid calculations previously published.We consider three different a-posteriori correction sets implemented in an automated workflow,and evaluate the qualitative and quantitative differences among four different categories of defect information:thermodynamic transition levels,formation energies,Fermi levels,and dopability limits.We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods,while also demonstrating the limits of quantitative accuracy.

A review of non-noble metal-based electrocatalysts for CO_(2)electroreduction

The excessive emission of CO_(2) has caused many environmental issues and is severely threatening the eco-system.CO_(2) electroreduction reaction(CO_(2) RR) that driven by sustainable power is an ideal route for realizing the net reduction of CO_(2) and carbon recycle.Developing efficient electrocatalysts with low cost and high performance is critical for the wide applications of CO_(2) RR electrolysis.Among the various explored CO_(2) RR catalysts,non-noble metal(NNM)-based nanomaterials have drawn increasing attentions due to the remarkable performance and low cost.In this mini-review,the recent advances of NNM-based CO_(2) RR catalysts are summarized,and the catalysts are classified based on their corresponding reduction products.The preparation strategies for engineering the electrocatalysts are introduced,and the relevant CO_(2) RR mechanisms are discussed in detail.Finally,the current challenges in CO_(2) RR research are presented,and some perspectives are proposed for the future development of CO_(2) RR technology.This mini-review introduces the recent advances and frontiers of NNM-based CO_(2) RR catalysts,which should shed light on the further exploration of efficient CO_(2) RR electrocatalysts.

Interfacial structure design of MXene-based nanomaterials for electrochemical energy storage and conversion

2D transition metal carbides,carbonitrides,and nitrides known as MXenes possess high electrical conductivity,large redox active surface area,rich surface chemistry,and tunable structures.Benefiting from these exceptional chemical and physical properties,the applications of MXenes for electrochemical energy storage and conversion have attracted increasing research interests around the world.Notably,the electrochemical performances of MXenes are directly dependent on their synthesis conditions,interfacial chemistries and structural configurations.In this review,we summarize the synthesis techniques of MXenes,as well as the recent advances in the interfacial structure design of MXene-based nanomaterials for electrochemical energy storage and conversion applications.Additionally,we provide an in-depth discussion on the relationship between interfacial structure and electrochemical performance from the perspectives of energy storage and electrocatalysis mechanisms.Finally,the challenges and insights for the future research of interfacial structure design of MXenes are outlined.

Color Cherenkov imaging of clinical radiation therapy

Color vision is used throughout medicine to interpret the health and status of tissue.Ionizing radiation used in radiation therapy produces broadband white light inside tissue through the Cherenkov effect,and this light is attenuated by tissue features as it leaves the body.In this study,a novel time-gated three-channel camera was developed for the first time and was used to image color Cherenkov emission coming from patients during treatment.The spectral content was interpreted by comparison with imaging calibrated tissue phantoms.Color shades of Cherenkov emission in radiotherapy can be used to interpret tissue blood volume,oxygen saturation and major vessels within the body.

Is tumor cell specificity distinct from tumor selectivity in vivo?A quantitative NIR molecular imaging analysis of nanoliposome targeting

The significance and ability for receptor targeted nanoliposomes(tNLs)to bind to their molecular targets in solid tumors in vivo has been questioned,particularly as the efficiency of their tumor accumulation and selectivity is not always predictive of their efficacy or molecular specificity.This study presents,for the first time,in situ near-infrared(NIR)molecular imaging-based quantitation of the in vivo specificity of tNLs for their target receptors,as opposed to tumor selectivity,which includes influences of enhanced tumor permeability and retention.Results show that neither tumor delivery nor selectivity(tumor-to-normal ratio)of cetuximab and IRDye conjugated tNLs correlate with epidermal growth factor receptor(EGFR)expression in U251,U87,and 9L tumors,and in fact underrepresent their imaging-derived molecular specificity by up to 94.2%.Conversely,their in vivo specificity,which we quantify as the concentration of tNL-reported tumor EGFR provided by NIR molecular imaging,correlates positively with EGFR expression levels in vitro and ex vivo(Pearson’s r=0.92 and 0.96,respectively).This study provides a unique opportunity to address the problematic disconnect between tNL synthesis and in vivo specificity.The findings encourage their continued adoption as platforms for precision medicine,and facilitates intelligent synthesis and patient customization in order to improve safety profiles and therapeutic outcomes.

Is clinically measured knee range of motion after total knee arthroplasty‘good enough?’:A feasibility study using wearable inertial measurement units to compare knee range of motion captured during physical therapy versus at home

Total knee arthroplasty is highly successful,in part due to range of motion(RoM)recovery.This is typically estimated goniometrically/visually by physical therapists(PTs)in the clinic,which is imprecise.Accordingly,a validated inertial measurement unit(IMU)method for capturing knee RoM was deployed assessing postoperative RoM both in and outside of the clinical setting.The study's objectives were to evaluate the feasibility of continuously capturing knee RoM pre-/post-op via IMUs,dividing data into PT/non-PT portions of each day,and comparing PT/non-PT metrics.We hypothesized IMU-based clinical knee RoM would differ from IMU-based knee RoM captured outside clinical settings.10 patients(3 M,69±13 years)completed informed consent documents following ethics board approval.A validated IMU method captured long duration(8–12 h/day,~50 days)knee RoM pre-/post-op.Post-op metrics were subdivided(PT versus non-PT).Clinical RoM and patient reported outcome measures were also captured.Compliance and clinical disruption were evaluated.ANOVA compared post-op PT and non-PT means and change scores.Maximum flexion during PT was less than outside PT.PT stance/swing RoM and activity level were greater than outside PT.No temporal variable differences were found PT versus non-PT.IMU RoM measurements capture richer information than clinical measures.Maximum PT flexion was likely less than non-PT due to the exercises completed(i.e.high passive RoM vs.low RoM gait).PT gait flexion likely exceed non-PT because of‘white coat effects’wherein patients are closely monitored clinically.This implies data captured clinically represents optimum performance whereas data captured non-clinically represents realistic performance.

A comparative study on microstructure,nanomechanical and corrosion behaviors of AlCoCuFeNi high entropy alloys fabricated by selective laser melting and laser metal deposition

The present study investigated the microstructure,nanomechanics,and corrosion behavior of AlCoCuFeNi high entropy alloys fabricated by selective laser melting(SLM)and laser metal deposition(LMD).The microstructure of SLM-processed specimens was mainly composed of columnar-grained BCC matrix(^90μm in width)and Cu-rich twinned FCC phase.The columnar grains grew epitaxially along the building direction and exhibited a strong{001}texture.In comparison,a coarse columnar-grained BCC matrix(^150μm in width)with a stronger<001>texture,rod-like B2 precipitates,and large core-shell structured FCC phases were formed in the LMD-processed specimens due to the higher heat accumulation effect.Consequently,the LMD-processed specimens showed a lower hardness,wear resistance,and corrosion resistance,but higher creep resistance and reduced Young's modulus than the SLM-processed specimens.Hot cracks occurred in both types of specimens,which could not be completely suppressed due to Cu segregation.

The evaluation of reverse shoulder lateralization on deltoid forces and scapular fracture risk:A computational study

Reverse shoulder arthroplasty(RSA)can treat severe rotator cuff deficiency,but its medialized design of the shoulder's center of rotation(CoR)has been associated with scapular notching.Although lateralization of CoR provides a larger impingement-free range of motion,the changes in component positioning alter the biomechanics and may cause unforeseen complications.This work quantified the muscle forces and predicted the scapula fracture risk by coupling dynamic simulation analysis with finite element modeling.To identify bone failure patterns,the results were analyzed using three common failure measures.A parametric study showed greater lateralization produced higher strain/stress concentrations in the scapular spine(Levy Region Type II),with approximately a 10%increase for the 12 mm lateralized scenario,compared to a neutral configuration.Significant differences in fracture risk patterns were found between the maximum principal stress/strain results and the von Mises stress results.The lateralized configurations could increase the muscle and joint reaction forces during abduction and induce scapular fracture.Studying the effects of RSA lateralization on scapular fracture risk can help guide the continued optimization of RSA performance and surgical techniques.The findings of relationships between the loading style and bone failure measures can provide valuable insight into the investigation of bone failure criteria.

A gyroscope-based system for intraoperative measurement of tibia coronal plane alignment in total knee arthroplasty

Coronal plane alignment in total knee arthroplasty(TKA)is an important predictor of clinical outcomes including patient satisfaction and device longevity.Radiography and computer assisted navigation are the two primary technologies currently available to surgeons for intraoperative assessment of alignment;however,neither is particularly well-suited for use in this increasingly high volume procedure.Herein we propose a novel gyroscopebased instrument for intraoperative validation of tibia coronal plane alignment,and provide initial analytical and experimental performance assessments.The gyroscope-based alignment estimate is derived from simplified joint geometry and verified experimentally using a custom tibial trial insert containing a consumer-grade inertial measurement unit(IMU).Average accuracy of the gyroscope-based tibia coronal angle estimate was found to be within
1in mechanical leg jig and cadaver testing.These results indicate that the proposed gyroscope-based method shows promise for low cost,accurate intraoperative validation of limb alignment in TKA patients.Integrating IMU technology into the TKA surgical workflow via low-cost instrumentation will enable surgeons to easily validate implant alignment in real time,thereby reducing cost,operating room time,and future revision burden.

A mechanistic consideration of oxygen enhancement ratio, oxygen transport and their relevancies for normal tissue sparing under FLASH irradiation

Our study investigated the role of oxygen in mediating the FLASH efect.This efect,which was frst reported in vitro in the 1950s and in vivo in the 1970s,recently gained prominence with a number of publications showing diferential sparing between normal tissues and tumors.Oxygen depletion(and subsequent induction of transient hypoxia)is the oldest and most prominent hypothesis to explain this efect.To better understand how the oxygen depletion hypothesis and oxygen enhancement ratio(OER)are relevant for interpreting FLASH benefts,an analytical model was proposed to estimate the sparing factor.The model incorporated factors such as OER,oxygen partial pressure(pO_(2)),loco-regional oxygen difusion/metabolism,total dose and dose rate.The sparing factor,was used to quantify the sparing of normal tissue(initially physoxic).The radiosensitivity parameters of two cell types(V79 Chinese hamster cells and T1 human kidney cells)were selected.Furthermore,the transient behavior of OER during fnite time intervals was modeled,for both without and with the presence of oxygen transport using a difusion model.For tissues with an oxygen consumption rate of 20mmHg/s and a distance of 60μm away from blood vessels,the sparing factor demonstrates an increase from 1.03/1.06(V79/T1)at 2.5Gy/s up to 1.28/1.72(V79/T1)at 100Gy/s(total dose:10Gy).For normal tissues of initial pO_(2) between 1.5 and 8mmHg,the beneft from pushing the dose rate above 100Gy/s is found to be marginal.Preliminary animal experiments have been conducted for validation.Overall,our study predicts that the dose rate associated with maximum normal tissue protection is between 50Gy/s and 100Gy/s.Other than the postulation of the hypoxic stem cell niches in normal tissues,we believe that a framework based upon the oxygen depletion hypothesis and OER is not able to efciently interpret diferential responses between normal and tumor tissue under FLASH irradiation.

Emerging technologies in Si active photonics

Silicon photonics for synergistic electronic-photonic integration has achieved remarkable progress in the past two decades. Active photonic devices, including lasers, modulators, and photodetectors, are the key chal- lenges for Si photonics to meet the requirement of high bandwidth and low power consumption in photonic datalinks. Here we review recent efforts and progress in high-performance active photonic devices on Si, focusing on emerging technologies beyond conventional foundry-ready Si photonics devices. For emerging laser sources, we will discuss recent progress towards efficient monolithic Ge lasers, mid-infrared GeSn lasers, and high-per- formance InAs quantum dot lasers on Si for data center applications in the near future. We will then review novel modulator materials and devices beyond the free carrier plasma dispersion effect in Si, including GeSi and graphene electro-absorption modulators and plasmonic-organic electro-optical modulators, to achieve ultralow power and high speed modulation. Finally, we discuss emerging photodetectors beyond epitaxial Ge p-i-n photo- diodes, including GeSn mid-infrared photodetectors, all-Si plasmonic Schottky infrared photodetectors, and Si quanta image sensors for non-avalanche, low noise single photon detection and photon counting. These emerging technologies, though still under development, could make a significant impact on the future of large-scale electron- icSilicon photonics for synergistic electronic-photonic integration has achieved remarkable progress in the past two decades. Active photonic devices, including lasers, modulators, and photodetectors, are the key challenges for Si photonics to meet the requirement of high bandwidth and low power consumption in photonic datalinks. Here we review recent efforts and progress in high-performance active photonic devices on Si, focusing on emerging tech- nologies beyond conventional foundry-ready Si photonics devices. For emerging laser sources, we will discuss re- cent progress towards efficient monolithic Ge lasers, mid-infrared GeSn lasers, and high-performance InAs quantum dot lasers on Si for data center applications in the near future. We will then review novel modulator ma- terials and devices beyond the free carrier plasma dispersion effect in Si, including GeSi and graphene electro-ab- sorption modulators and plasmonic-organic electro-optical modulators, to achieve ultralow power and high speed modulation. Finally, we discuss emerging photodetectors beyond epitaxial Ge p-i-n photodiodes, including GeSn mid-infrared photodetectors, all-Si plasmonic Schottky infrared photodetectors, and Si quanta image sensors for non-avalanche, low noise single photon detection and photon counting. These emerging technologies, though still under development, could make a significant impact on the future of large-scale electronic-photonic integration with performance inaccessible from conventional Si photonics technologies-photonic integration with perform- ance inaccessible from conventional Si photonics technologies.

Materials property prediction for limited datasets enabled by feature selection and joint learning with MODNet

In order to make accurate predictions of material properties,current machine-learning approaches generally require large amounts of data,which are often not available in practice.In this work,MODNet,an all-round framework,is presented which relies on a feedforward neural network,the selection of physically meaningful features,and when applicable,joint-learning.Next to being faster in terms of training time,this approach is shown to outperform current graph-network models on small datasets.In particular,the vibrational entropy at 305 K of crystals is predicted with a mean absolute test error of 0.009 meV/K/atom(four times lower than previous studies).Furthermore,joint learning reduces the test error compared to single-target learning and enables the prediction of multiple properties at once,such as temperature functions.Finally,the selection algorithm highlights the most important features and thus helps to understand the underlying physics.