HealthMeasures患者报告结局报告清单的解读

美国匹兹堡大学和HealthMeasures指导委员会及PROMIS健康组织标准委员会共同发表了HealthMeasures患者报告结局报告清单,旨在促进不同患者报告结局测量工具的标准化报告,帮助研究人员提高工具报告质量及结果解释的准确性,进一步改善跨研究间的比较分析。本文对HealthMeasures患者报告结局报告清单的主要内容进行介绍和解读,以期为中国患者报告结局研究者提供参考和借鉴。

Effects of drought on non-structural carbohydrates and C,N,and P stoichiometric characteristics of Pinus yunnanensis seedlings

To study non-structural carbohydrate character-istics and nutrient utilization strategies of Pinus yunnanen-sis under continuous drought conditions,2-year-old seed-lings were planted in pots with appropriate water,light and moderate and severe drought treatments[(80±5),(65±5),(50±5),and(35±5)%of field water-holding capacity].Non-structural carbohydrates,carbon(C),nitrogen(N),and phosphorus(P)concentrations were measured in each plant component.The results show that:(1)With increasing drought,non-structural carbohydrates gradually increased in leaves,stems,and coarse roots,while gradually decreased in fine roots;(2)C concentrations of all were relatively stable under different stress levels.Phosphorous utilization of each component increased under light and moderate drought conditions,while N and P utilization efficiency of each plant component decreased under severe drought.Growth was mainly restricted by N,first decreasing and then increasing with increased drought;(3)There was a correlation between the levels of non-structural carbohydrates and C,N,and P in each component.Changes in N concentration affected the interconversion between soluble sugar and starch,which play a regulatory role in the fluctuation of the concentration of non-structural carbohydrates;and,(4)Plasticity analysis showed that P.yunnanensis seedlings responded to drought mainly by altering starch concentration,the ratio of soluble sugar to starch in leaves and stems,and further by alter-ing N and P utilization efficiencies.Overall,these results suggest that the physiological activities of all organs of P.yunnanensis seedlings are restricted under drought and that trade-offs exist between different physiological indicators and organs.Our findings are helpful in understanding non-structural carbohydrate and nutrient adaptation mechanisms under drought in P.yunnanensis seedlings.

Irrigation regimes modulate non-structural carbohydrate remobilization and improve grain filling in rice(Oryza sativa L.)by regulating starch metabolism

Recently developed ‘super’ rice cultivars with greater yield potentials often suffer from the problem of poor grain filling, especially in inferior spikelets. Here, we studied the activities of enzymes related to starch metabolism in rice stems and grains, and the microstructures related to carbohydrate accumulation and transportation to investigate the effects of different water regimes on grain filling. Two ‘super’ rice cultivars were grown under two irrigation regimes of well-watered(WW) and alternate wetting and moderate soil drying(AWMD). Compared with the WW treatment,the activities of ADP glucose pyrophosphorylase(AGPase), starch synthase(StSase) and starch branching enzyme(SBE), and the accumulation of non-structural carbohydrates(NSCs) in the stems before heading were significantly improved, and more starch granules were stored in the stems in the AWMD treatment. After heading, the activities of α-amylase, β-amylase, sucrose phosphate synthase(SPS) and sucrose synthase in the synthetic direction(SSs)were increased in the stems to promote the remobilization of NSCs for grain filling under AWMD. During grain filling, the enzymatic activities of sucrose synthase in the cleavage direction(SSc), AGPase, StSase and SBE in the inferior spikelets were increased, which promoted grain filling, especially for the inferior spikelets under AWMD.However, there were no significant differences in vascular microstructures. The grain yield and grain weight could be improved by 13.1 and 7.5%, respectively, by optimizing of the irrigation regime. We concluded that the low activities of key enzymes in carbon metabolism is the key limitation for the poor grain filling, as opposed to the vascular microstructures, and AWMD can increase the amount of NSC accumulation in the stems before heading, improve the utilization rate of NSCs after heading, and increase the grain filling, especially in the inferior spikelets, by altering the activities of key enzymes in carbon metabolism.

Applying the Shearlet-Based Complexity Measure for Analyzing Mass Transfer in Continuous-Flow Microchannels

Continuous-flow microchannels are widely employed for synthesizing various materials,including nanoparticles,polymers,and metal-organic frameworks(MOFs),to name a few.Microsystem technology allows precise control over reaction parameters,resulting in purer,more uniform,and structurally stable products due to more effective mass transfer manipulation.However,continuous-flow synthesis processes may be accompanied by the emergence of spatial convective structures initiating convective flows.On the one hand,convection can accelerate reactions by intensifying mass transfer.On the other hand,it may lead to non-uniformity in the final product or defects,especially in MOF microcrystal synthesis.The ability to distinguish regions of convective and diffusive mass transfer may be the key to performing higher-quality reactions and obtaining purer products.In this study,we investigate,for the first time,the possibility of using the information complexity measure as a criterion for assessing the intensity of mass transfer in microchannels,considering both spatial and temporal non-uniformities of liquid’s distributions resulting from convection formation.We calculate the complexity using shearlet transform based on a local approach.In contrast to existing methods for calculating complexity,the shearlet transform based approach provides a more detailed representation of local heterogeneities.Our analysis involves experimental images illustrating the mixing process of two non-reactive liquids in a Y-type continuous-flow microchannel under conditions of double-diffusive convection formation.The obtained complexity fields characterize the mixing process and structure formation,revealing variations in mass transfer intensity along the microchannel.We compare the results with cases of liquid mixing via a pure diffusive mechanism.Upon analysis,it was revealed that the complexity measure exhibits sensitivity to variations in the type of mass transfer,establishing its feasibility as an indirect criterion for assessing mass transfer intensity.The method presented can extend beyond flow analysis,finding application in the controlling of microstructures of various materials(porosity,for instance)or surface defects in metals,optical systems and other materials that hold significant relevance in materials science and engineering.

Impacts of Defoliation on Morphological Characteristics and Non-Structural Carbohydrates of Populus talassica × Populus euphratica Seedlings

Leaves are important‘source’organs that synthesize organic matter,providing carbon sources for plant growth.Here,we used Populus talassica×Populus euphratica,the dominant species in ecological and timber forests,to simulate carbon limitation through artificial 25%,50%,and 75%defoliation treatments and explore the effects on root,stem,and leaf morphology,biomass accumulation,and carbon allocation strategies.At the 60th d after treat-ment,under 25%defoliation treatment,the plant height,specific leaf weight,root surface area and volume,and concentrations of non-structural carbohydrates in stem and root were significantly increased by 9.13%,20.00%,16.60%,31.95%,5.12%,and 9.34%,respectively,relative to the control.There was no significant change in the growth indicators under 50%defoliation treatment,but the concentrations of non-structural carbohydrates in the leaf and stem significantly decreased,showing mostly a negative correlation between them.The opposite was observed in the root.Under 75%defoliation treatment,the plant height,ground diameter,leaf number,single leaf area,root,stem,and total biomass were significantly reduced by 14.15%,10.24%,14.86%,11.31%,11.56%,21.87%,and 16.82%,respectively,relative to the control.The concentrations of non-structural carbohydrates in various organs were significantly reduced,particularly in the consumption of the starch concentrations in the stem and root.These results indicated that carbon allocation strategies can be adjusted to increase the con-centration of non-structural carbohydrates in root and meet plant growth needs under 25%and 50%defoliation.However,75%defoliation significantly limited the distribution of non-structural carbohydrates to roots and stems,reduced carbon storage,and thus inhibited plant growth.Defoliation-induced carbon limitation altered the carbon allocation pattern of P.talassica×P.euphratica,and the relationship between carbon reserves in roots and tree growth recovery after defoliation was greater.This study provides a theoretical basis for the comprehen-sive management of P.talassica×P.euphratica plantations,as well as a reference for the study of plantation car-bon allocation strategies in the desert and semi-desert regions of Xinjiang under carbon-limitation conditions.

Bunch-length measurement at a bunch-by-bunch rate based on time–frequency-domain joint analysis techniques and its application

This paper presents a new technique for measuring the bunch length of a high-energy electron beam at a bunch-by-bunch rate in storage rings.This technique uses the time–frequency-domain joint analysis of the bunch signal to obtain bunch-by-bunch and turn-by-turn longitudinal parameters,such as bunch length and synchronous phase.The bunch signal is obtained using a button electrode with a bandwidth of several gigahertz.The data acquisition device was a high-speed digital oscilloscope with a sampling rate of more than 10 GS/s,and the single-shot sampling data buffer covered thousands of turns.The bunch-length and synchronous phase information were extracted via offline calculations using Python scripts.The calibration coefficient of the system was determined using a commercial streak camera.Moreover,this technique was tested on two different storage rings and successfully captured various longitudinal transient processes during the harmonic cavity debugging process at the Shanghai Synchrotron Radiation Facility(SSRF),and longitudinal instabilities were observed during the single-bunch accumulation process at Hefei Light Source(HLS).For Gaussian-distribution bunches,the uncertainty of the bunch phase obtained using this technique was better than 0.2 ps,and the bunch-length uncertainty was better than 1 ps.The dynamic range exceeded 10 ms.This technology is a powerful and versatile beam diagnostic tool that can be conveniently deployed in high-energy electron storage rings.

A New Device for Gas-Liquid Flow Measurements Relying on Forced Annular Flow

A new measurement device,consisting of swirling blades and capsule-shaped throttling elements,is proposed in this study to eliminate typical measurement errors caused by complex flow patterns in gas-liquid flow.The swirling blades are used to transform the complex flow pattern into a forced annular flow.Drawing on the research of existing blockage flow meters and also exploiting the single-phase flow measurement theory,a formula is introduced to measure the phase-separated flow of gas and liquid.The formula requires the pressure ratio,Lockhart-Martinelli number(L-M number),and the gas phase Froude number.The unknown parameters appearing in the formula are fitted through numerical simulation using computational fluid dynamics(CFD),which involves a comprehensive analysis of the flow field inside the device from multiple perspectives,and takes into account the influence of pressure fluctuations.Finally,the measurement model is validated through an experimental error analysis.The results demonstrate that the measurement error can be maintained within±8%for various flow patterns,including stratified flow,bubble flow,and wave flow.

Comparison of bulk snow density measurements using different methods

Snow density is one of the basic properties used to describe snow cover characteristics,and it is critical for remote sensing retrieval,water resources assessment and modeling inputs.There are many instruments available to measure snow density in situ.However,there are mea-surement errors of snow density for bulk and layers or gravimetric and electronic instruments,which may affect the accuracy of remote sensing retrieval and model simulation.Especially in China,due to the noticeable heterogeneity of snowpacks,it is necessary to evaluate in detail the performance and applicability of snow density instruments in different snowpack conditions.This study evaluated the performance of different snow density instruments:the Federal Sampler,the model VS-43 snow density cylinder(VS-43),the wedge snow density cutter(WC1000 and WC25O),and the Snow Fork.The average bulk snow density of all instrument measurements was set as the reference value for evaluation.The results showed that as compared with the reference,the VS-43 cylinder presented the best performance for bulk snow density measurement in the measured range with the lowest RMSE(11 kg m-3),BIAS(3 kg m-3),and MRE(1.6%).For layer observation,bulk snow density was overestimated by 8.1%with WC1000 and underestimated by 11.4%with Snow Fork which was the worst performance compared with the reference value,and there were greater measurement errors of snow density in the depth hoar than other snow layers.Compared with grassland,the uncertainty of snow density measurements was slightly lower in forests.Overall,the Federal Sampler and VS-43 cylinder are more suitable for bulk snow density measurement in deep snowpack regions across China,and it is recommended to use WC1000,WC250 and Snow Fork to measure the snow density of snow layers in the snow stratigraphy.

Enhancing Energy Efficiency with a Dynamic Trust Measurement Scheme in Power Distribution Network

The application of Intelligent Internet of Things(IIoT)in constructing distribution station areas strongly supports platform transformation,upgrade,and intelligent integration.The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer,with the former using intelligent fusion terminals for real-time data collection and processing.However,the influx of multiple low-voltage in the smart grid raises higher demands for the performance,energy efficiency,and response speed of the substation fusion terminals.Simultaneously,it brings significant security risks to the entire distribution substation,posing a major challenge to the smart grid.In response to these challenges,a proposed dynamic and energy-efficient trust measurement scheme for smart grids aims to address these issues.The scheme begins by establishing a hierarchical trust measurement model,elucidating the trust relationships among smart IoT terminals.It then incorporates multidimensional measurement factors,encompassing static environmental factors,dynamic behaviors,and energy states.This comprehensive approach reduces the impact of subjective factors on trust measurements.Additionally,the scheme incorporates a detection process designed for identifying malicious low-voltage end sensing units,ensuring the prompt identification and elimination of any malicious terminals.This,in turn,enhances the security and reliability of the smart grid environment.The effectiveness of the proposed scheme in pinpointing malicious nodes has been demonstrated through simulation experiments.Notably,the scheme outperforms established trust metric models in terms of energy efficiency,showcasing its significant contribution to the field.

Measuring small longitudinal phase shifts via weak measurement amplification

Weak measurement amplification,which is considered as a very promising scheme in precision measurement,has been applied to various small physical quantities estimations.Since many physical quantities can be converted into phase signals,it is interesting and important to consider measuring small longitudinal phase shifts by using weak measurement.Here,we propose and experimentally demonstrate a novel weak measurement amplification-based small longitudinal phase estimation,which is suitable for polarization interferometry.We realize one order of magnitude amplification measurement of a small phase signal directly introduced by a liquid crystal variable retarder and show that it is robust to the imperfection of interference.Besides,we analyze the effect of magnification error which is never considered in the previous works,and find the constraint on the magnification.Our results may find important applications in high-precision measurements,e.g.,gravitational wave detection.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Unknown Environment Measurement Mapping by Unmanned Aerial Vehicle Using Kalman Filter-Based Low-Cost Estimated Parallel 8-Beam LIDAR

The measurement and mapping of objects in the outer environment have traditionally been conducted using ground-based monitoring systems,as well as satellites.More recently,unmanned aerial vehicles have also been employed for this purpose.The accurate detection and mapping of a target such as buildings,trees,and terrains are of utmost importance in various applications of unmanned aerial vehicles(UAVs),including search and rescue operations,object transportation,object detection,inspection tasks,and mapping activities.However,the rapid measurement and mapping of the object are not currently achievable due to factors such as the object’s size,the intricate nature of the sites,and the complexity of mapping algorithms.The present system introduces a costeffective solution for measurement and mapping by utilizing a small unmanned aerial vehicle(UAV)equipped with an 8-beam Light Detection and Ranging(LiDAR)system.This approach offers advantages over traditional methods that rely on expensive cameras and complex algorithm-based approaches.The reflective properties of laser beams have also been investigated.The system provides prompt results in comparison to traditional camerabased surveillance,with minimal latency and the need for complex algorithms.The Kalman estimation method demonstrates improved performance in the presence of noise.The measurement and mapping of external objects have been successfully conducted at varying distances,utilizing different resolutions.

A new centrality measure based on neighbor loop structure for network dismantling

Nearly all real-world networks are complex networks and usually are in danger of collapse.Therefore,it is crucial to exploit and understand the mechanisms of network attacks and provide better protection for network functionalities.Network dismantling aims to find the smallest set of nodes such that after their removal the network is broken into connected components of sub-extensive size.To overcome the limitations and drawbacks of existing network dismantling methods,this paper focuses on network dismantling problem and proposes a neighbor-loop structure based centrality metric,NL,which achieves a balance between computational efficiency and evaluation accuracy.In addition,we design a novel method combining NL-based nodes-removing,greedy tree-breaking and reinsertion.Moreover,we compare five baseline methods with our algorithm on ten widely used real-world networks and three types of model networks including Erd€os-Renyi random networks,Watts-Strogatz smallworld networks and Barabasi-Albert scale-free networks with different network generation parameters.Experimental results demonstrate that our proposed method outperforms most peer methods by obtaining a minimal set of targeted attack nodes.Furthermore,the insights gained from this study may be of assistance to future practical research into real-world networks.

Design and application of thickness measurement calibration system based on laser displacement sensor

This study aims to improve the accuracy and safety of steel plate thickness calibration.A differential noncontact thickness measurement calibration system based on laser displacement sensors was designed to address the problems of low precision of traditional contact thickness gauges and radiation risks of radiation-based thickness gauges.First,the measurement method and measurement structure of the thickness calibration system were introduced.Then,the hardware circuit of the thickness system was established based on the STM32 core chip.Finally,the system software was designed to implement system control to filter algorithms and human-computer interaction.Experiments have proven the excellent performance of the differential noncontact thickness measurement calibration system based on laser displacement sensors,which not only considerably improves measurement accuracy but also effectively reduces safety risks during the measurement process.The system offers guiding significance and application value in the field of steel plate production and processing.

Microstructural and thermal properties of coal measure sandstone subjected to high temperatures

To study the microscopic structure,thermal and mechanical properties of sandstones under the influence of temperature,coal measure sandstones from Southwest China are adopted as the research object to carry out high-temperature tests at 25℃-1000℃.The microscopic images of sandstone after thermal treatment are obtained by means of polarizing microscopy and scanning electron microscopy(SEM).Based on thermogravimetric(TG)analysis and differential scanning calorimetric(DSC)analysis,the model function of coal measure sandstone is explored through thermal analysis kinetics(TAK)theory,and the kinetic parameters of thermal decomposition and the thermal decomposition reaction rate of rock are studied.Through the uniaxial compression experiments,the stress‒strain curves and strength characteristics of sandstone under the influence of temperature are obtained.The results show that the temperature has a significant effect on the microstructure,mineral composition and mechanical properties of sandstone.In particular,when the temperature exceeds 400℃,the thermal fracture phenomenon of rock is obvious,the activity of activated molecules is significantly enhanced,and the kinetic phenomenon of the thermal decomposition reaction of rock appears rapidly.The mechanical properties of rock are weakened under the influence of rock thermal fracture and mineral thermal decomposition.These research results can provide a reference for the analysis of surrounding rock stability and the control of disasters caused by thermal damage in areas such as underground coal gasification(UCG)channels and rock masses subjected to mine fires.

A fast forward computational method for nuclear measurement using volumetric detection constraints

Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sources,the detector response can reflect various types of information of the medium.The Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex environments.However,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response results.Therefore,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is proposed.First,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo simulation.Then,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion model.The environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection volume.Finally,the method is applied to a neutron porosity tool for verification.In various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 p.u.In field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method.

Quantum block coherence with respect to projective measurements

Quantum coherence serves as a defining characteristic of quantum mechanics,finding extensive applications in quantum computing and quantum communication processing.This study explores quantum block coherence in the context of projective measurements,focusing on the quantification of such coherence.Firstly,we define the correlation function between the two general projective measurements P and Q,and analyze the connection between sets of block incoherent states related to two compatible projective measurements P and Q.Secondly,we discuss the measure of quantum block coherence with respect to projective measurements.Based on a given measure of quantum block coherence,we characterize the existence of maximal block coherent states through projective measurements.This research integrates the compatibility of projective measurements with the framework of quantum block coherence,contributing to the advancement of block coherence measurement theory.

A seismic elastic moduli module for the measurements of low-frequency wave dispersion and attenuation of fluid-saturated rocks under different pressures

Knowledge about the seismic elastic modulus dispersion,and associated attenuation,in fluid-saturated rocks is essential for better interpretation of seismic observations taken as part of hydrocarbon identification and time-lapse seismic surveillance of both conventional and unconventional reservoir and overburden performances.A Seismic Elastic Moduli Module has been developed,based on the forced-oscillations method,to experimentally investigate the frequency dependence of Young's modulus and Poisson's ratio,as well as the inferred attenuation,of cylindrical samples under different confining pressure conditions.Calibration with three standard samples showed that the measured elastic moduli were consistent with the published data,indicating that the new apparatus can operate reliably over a wide frequency range of f∈[1-2000,10^(6)]Hz.The Young's modulus and Poisson's ratio of the shale and the tight sandstone samples were measured under axial stress oscillations to assess the frequency-and pressure-dependent effects.Under dry condition,both samples appear to be nearly frequency independent,with weak pressure dependence for the shale and significant pressure dependence for the sandstone.In particular,it was found that the tight sandstone with complex pore microstructure exhibited apparent dispersion and attenuation under brine or glycerin saturation conditions,the levels of which were strongly influenced by the increased effective pressure.In addition,the measured Young's moduli results were compared with the theoretical predictions from a scaled poroelastic model with a reasonably good agreement,revealing that the combined fluid flow mechanisms at both mesoscopic and microscopic scales possibly responsible for the measured dispersion.

Deterioration Reason and Improvement Measure of the Retarding Effect of Protein Retarder on Phosphorus Building Gypsum

The retarding effect of protein retarder on phosphorus building gypsum(PBG)and desulfurization building gypsum(DBG)was investigated,and the results show that protein retarder for DBG can effectively prolong the setting time and displays a better retarding effect,but for PBG shows a poor retarding effect.Furthermore,the deterioration reason of the retarding effect of protein retarder on PBG was investigated by measuring the pH value and the retarder concentration of the liquid phase from vacuum filtration of PBG slurry at different hydration time,and the measure to improve the retarding effect of protein retarding on PBG was suggested.The pH value of PBG slurry(<5.0)is lower than that of DBG slurry(7.8-8.5).After hydration for 5 min,the concentration of retarder in liquid phase of DBG slurry gradually decreases,but in liquid phase of PBG slurry continually increases,which results in the worse retarding effect of protein retarder on PBG.The liquid phase pH value of PBG slurry can be adjusted higher by sodium silicate,which is beneficial to improvement in the retarding effect of the retarder.By adding 1.0%of sodium silicate,the initial setting time of PBG was efficiently prolonged from 17 to 210 min,but little effect on the absolute dry flexural strength was observed.

Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution

We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements.