SPOT和Bayes递推估计融合的运载火箭样本量设计

针对运载火箭小子样条件,结合序贯验后加权检验(sequential posterior odd test, SPOT)和Bayes递推估计法,分别从假设检验和参数估计两方面,对传统试验样本量评估方法进行改进。在对运载火箭服从正态分布的性能指标进行评估时,引入复合等效系数来有效融合多源数据,弥补真实试验数据或现场数据的不足。综合考虑两类风险和置信度要求,制定合理的评估方案,有效减少所需试验样本数量,从而控制试验成本。通过算例分析发现,提出样本量评估方法结果真实可信,能够有效降低样本量需求,可较好用于小子样条件下的运载火箭样本量试验设计。

Analysis of Renewable Energy Absorption and Economic Feasibility in Multi-Energy Complementary Systems under Spot Market Conditions

As the power system transitions to a new green and low-carbon paradigm,the penetration of renewable energy in China’s power system is gradually increasing.However,the variability and uncertainty of renewable energy output limit its profitability in the electricity market and hinder its market-based integration.This paper first constructs a wind-solar-thermalmulti-energy complementary system,analyzes its external game relationships,and develops a bi-level market optimization model.Then,it considers the contribution levels of internal participants to establish a comprehensive internal distribution evaluation index system.Finally,simulation studies using the IEEE 30-bus system demonstrate that the multi-energy complementary system stabilizes nodal outputs,enhances the profitability of market participants,and promotes the market-based integration of renewable energy.

ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the ocean.Among the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant to oceanic research.In this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,STLSTM-SA,combines Spatiotemporal Long Short-Term Memory(ST-LSTM) with a self-attention mechanism to enable accurate and real-time prediction of SVFs.To circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-tuning it using in-situ analysis data to obtain the final prediction model.By utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three months.We compare the performance of five models:Artificial Neural Networks(ANN),Long ShortTerm Memory(LSTM),Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a test experiment spanning 2019 to 2022.Our results demonstrate that the ST-LSTM-SA model significantly improves the prediction accuracy and stability of sound velocity in both temporal and spatial dimensions.The ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediction of other oceanic environmental variables.

Effects of spot size on the operation mode of Ga As photoconductive semiconductor switch employing extrinsic photoconductivity

To guide the illuminating design to improve the on-state performances of gallium arsenide(GaAs)photoconductive semiconductor switch(PCSS),the effect of spot size on the operation mode of GaAsPCSS based on a semi-insulating wafer with a thickness of 1 mm,triggered by a 1064-nm extrinsic laser beam with the rectangular spot,has been investigated experimentally.It is found that the variation of the spot size in length and width can act on the different parts of the output waveform integrating the characteristics of the linear and nonlinear modes,and then significantly boosts the PCSS toward different operation modes.On this basis,a two-channel model containing the active and passive parts is introduced to interpret the relevant influencing mechanisms.Results indicate that the increased spot length can peak the amplitude of static domains in the active part to enhance the development of the nonlinear switching,while the extended spot width can change the distribution of photogenerated carriers on both parts to facilitate the linear switching and weaken the nonlinear switching,which have been proved by comparing the domain evolutions under different spot sizes.

电子音乐的组织结构与诗意化呈现——安承弼作品Sound Assembly技法探微

安承弼为钢琴独奏和电子音乐创作的Sound Assembly,运用“预置声音+钢琴演奏+人机交互”的演奏方式,探索声音设备与电子系统之间的关系,将钢琴现场演奏与电子声音进行实时合成,开拓了多维空间的声音回响,并运用音集统一、踏板动机以及声音激振方式的内在关联形成严密的组织结构,将预置声音的“定格性”与现场演奏的“随机性”有机结合,在绝对控制与自由演化之间寻求有机联系,创造出富有诗意的奇妙音响,这一作品将给当代电子音乐的创作带来新的启示。

6-48月龄婴幼儿Spot屈光度异常结果分析

目的:分析6-48月龄婴幼儿Spot屈光异常情况,为婴幼儿屈光不正矫正及弱视早期防治提供依据。方法:对6-48月龄婴幼儿使用Spot双目视力筛查仪进行自然状况下验光,根据Spot屈光筛查仪4岁以下儿童转诊标准,收集屈光异常婴幼儿临床资料;使用睫状肌麻痹剂视网膜检影验光,并对验光结果进行统计分析。结果:根据转诊标准共收集Spot屈光度异常婴幼儿168例336眼。其中远视及散光异常占比高,分别为38.4%和28.6%,而近视占比低(12.2%)。168例Spot屈光度异常婴幼儿中,屈光参差(≥1.00 D)共90例,其中散光性屈光参差41例(45.6%)、远视性屈光参差33例(36.7%),近视性屈光参差16例(17.8%)占比最少。共109例Spot屈光度异常婴幼儿完成睫状肌麻痹剂视网膜检影验光。对其Spot屈光度与睫状肌麻痹后检影验光结果差异及相关性分析结果显示,两者散光度差异为0.34±0.64 D(P<0.001),远视度差异为-2.10±1.27 D(P<0.001),近视度差异为-0.43±0.91 D(P=0.023);虽然二者结果存在统计学差异,但二者散光度、远视度及近视度均呈正相关(r=0.694、0.762、0.909)。结论:6-48月龄婴幼儿Spot屈光异常主要以散光、远视异常和屈光参差为主,近视异常较少;对Spot筛查异常者应进一步睫状肌麻痹剂视网膜检影验光,给予配镜矫正,有效防止婴幼儿屈光性弱视。

Deep learning-based lung sound analysis for intelligent stethoscope

Auscultation is crucial for the diagnosis of respiratory system diseases.However,traditional stethoscopes have inherent limitations,such as inter-listener variability and subjectivity,and they cannot record respiratory sounds for offline/retrospective diagnosis or remote prescriptions in telemedicine.The emergence of digital stethoscopes has overcome these limitations by allowing physicians to store and share respiratory sounds for consultation and education.On this basis,machine learning,particularly deep learning,enables the fully-automatic analysis of lung sounds that may pave the way for intelligent stethoscopes.This review thus aims to provide a comprehensive overview of deep learning algorithms used for lung sound analysis to emphasize the significance of artificial intelligence(AI)in this field.We focus on each component of deep learning-based lung sound analysis systems,including the task categories,public datasets,denoising methods,and,most importantly,existing deep learning methods,i.e.,the state-of-the-art approaches to convert lung sounds into two-dimensional(2D)spectrograms and use convolutional neural networks for the end-to-end recognition of respiratory diseases or abnormal lung sounds.Additionally,this review highlights current challenges in this field,including the variety of devices,noise sensitivity,and poor interpretability of deep models.To address the poor reproducibility and variety of deep learning in this field,this review also provides a scalable and flexible open-source framework that aims to standardize the algorithmic workflow and provide a solid basis for replication and future extension:https://github.com/contactless-healthcare/Deep-Learning-for-Lung-Sound-Analysis.

Analysis and construction of evaluation index system of inter-provincial electricity spot markets

Because of the contradiction between the scale of new energy installations and the continuous load growth in the central and eastern regions of China,the balance problems of the electricity market are becoming increasingly prominent,and it is urgent to solve such problems through inter-provincial electricity spot markets.First,the development history and construction status of the inter-provincial electricity spot market are summarized;second,the mechanism design of the inter-provincial electricity spot market is sorted out in terms of the market operation framework,transaction declaration,and clearing methods;subsequently,the evaluation index system of the inter-provincial electricity spot market is constructed,including four themes of electricity mutual aid and support,new energy consumption,economic benefits of market-based allocation,and social benefits of market-based allocation;finally,the operation of the inter-provincial electricity spot market is comprehensively analyzed by the algorithm based on the market operation data of 2022,which proves the feasibility and practicality of the proposed index system.

Topology optimization of chiral metamaterials with application to underwater sound insulation

Chiral metamaterials have been proven to possess many appealing mechanical phenomena,such as negative Poisson's ratio,high-impact resistance,and energy absorption.This work extends the applications of chiral metamaterials to underwater sound insulation.Various chiral metamaterials with low acoustic impedance and proper stiffness are inversely designed using the topology optimization scheme.Low acoustic impedance enables the metamaterials to have a high and broadband sound transmission loss(STL),while proper stiffness guarantees its robust acoustic performance under a hydrostatic pressure.As proof-of-concept demonstrations,two specimens are fabricated and tested in a water-filled impedance tube.Experimental results show that,on average,over 95%incident sound energy can be isolated by the specimens in a broad frequency range from 1 k Hz to 5 k Hz,while the sound insulation performance keeps stable under a certain hydrostatic pressure.This work may provide new insights for chiral metamaterials into the underwater applications with sound insulation.

Can urban forests provide acoustic refuges for birds?Investigating the influence of vegetation structure and anthropogenic noise on bird sound diversity

As a crucial component of terrestrial ecosystems,urban forests play a pivotal role in protecting urban biodiversity by providing suitable habitats for acoustic spaces.Previous studies note that vegetation structure is a key factor influencing bird sounds in urban forests;hence,adjusting the frequency composition may be a strategy for birds to avoid anthropogenic noise to mask their songs.However,it is unknown whether the response mechanisms of bird vocalizations to vegetation structure remain consistent despite being impacted by anthropogenic noise.It was hypothesized that anthropogenic noise in urban forests occupies the low-frequency space of bird songs,leading to a possible reshaping of the acoustic niches of forests,and the vegetation structure of urban forests is the critical factor that shapes the acoustic space for bird vocalization.Passive acoustic monitoring in various urban forests was used to monitor natural and anthropogenic noises,and sounds were classified into three acoustic scenes(bird sounds,human sounds,and bird-human sounds)to determine interconnections between bird sounds,anthropogenic noise,and vegetation structure.Anthropogenic noise altered the acoustic niche of urban forests by intruding into the low-frequency space used by birds,and vegetation structures related to volume(trunk volume and branch volume)and density(number of branches and leaf area index)significantly impact the diversity of bird sounds.Our findings indicate that the response to low and high frequency signals to vegetation structure is distinct.By clarifying this relationship,our results contribute to understanding of how vegetation structure influences bird sounds in urban forests impacted by anthropogenic noise.

T-SPOT联合颗粒酶B阳性Ts淋巴细胞对成人结核病诊断的价值

目的探讨结核感染T细胞斑点试验(T-SPOT.TB)联合颗粒酶B(GrB)+CD8^(+)T淋巴细胞在诊断结核病中的价值。方法选取南昌大学第一附属医院2021年2月至2022年3月疑似结核病患者212例,所有患者均保留T-SPOT结果,流式细胞仪检测外周血中T淋巴细胞亚群及其穿孔素和GrB的表达,根据出院最终诊断分为结核病组和非结核病组,比较两组间T-SPOT斑点数和淋巴细胞亚群及其穿孔素和GrB表达差异,ROC曲线分析ESAT-6斑点数,CFP-10斑点数,结核特异性抗原(TBAg)与植物血凝素(PHA)斑点数的比值(TBAg/PHA)(ESAT-6/PHA和CFP-10/PHA中较大的一个),GrB^(+)Ts(CD8^(+)T)及“结核比值”[TBAg/(PHA*GrB^(+)Ts)]的诊断效能。结果GrB^(+)Ts细胞百分比在结核组中显著高于非结核组(44.95±2.98 vs 33.49±1.87,P<0.05),而总T细胞、穿孔素+T细胞,GrB^(+)T细胞,Ts细胞和穿孔素+Ts细胞百分比差异无统计学意义(P>0.05);非结核组T-SPOT.TB阳性率为51.85%,明显低于结核组的92%,且结核组的A抗原斑点数及B抗原斑点数显著大于非结核组(P<0.05),ROC曲线显示A抗原诊断结核病的灵敏度和特异性分别为80.0%和56.8%,曲线下面积(AUC)为0.748,约登指数为0.368;B抗原的灵敏度和特异性为分别62.0%和77.8%,AUC为0.758,约登指数为0.398;A抗原+B抗原灵敏度和特异性为72.0%和74.1%,AUC为0.796,约登指数为0.461;结核组的TBAg/PHA比率要显著高于非结核组(1.21±0.17 vs 0.26±0.02,P<0.001)以0.59为cut-off值时,诊断结核病的灵敏度和特异性分别为66%和91.4%,AUC高达0.852,约登指数为0.574;结核组的“结核比值”要显著高于非结核组(4.58±0.87 vs 1.71±0.24,P<0.01),以1.24为cut-off值时,诊断结核病的灵敏度和特异性分别为82.0%和72.2%,AUC为0.794,约登指数为0.542。结论应用TBAg/PHA比率和TBAg/(PHA*GrB^(+)Ts)比值诊断结核病的效能要优于常规的T-SPOT检测,两者结合使用对结核病诊断可能具有重要价值。

Optimization for sound insulation of a sandwich plate with a corrugation and auxetic honeycomb hybrid core

A sandwich plate with a corrugation and auxetic honeycomb hybrid core is constructed,and its sound insulation and optimization are investigated.First,the motion governing equation of the sandwich plate is established by the third-order shear deformation theory(TSDT),and then combined with the fluid-structure coupling conditions,and the sound insulation is solved.The theoretical results are validated by COMSOL simulation results,and the effects of the structural parameter on the sound insulation are analyzed.Finally,the standard genetic algorithm is adopted to optimize the sound insulation of the sandwich plate.

Effects of Poria cocos polysaccharide on growth performance,physiological parameters,and lipid metabolism of spotted sea bass Lateolabrax maculatus

The aquaculture industry has developed significantly over the past few decades and has had a substantial impact on the global food supply and marine fisheries resources.However,some problems arise behind the scenes due to excessive intensive farming,such as slow animal growth,frequent disease,and lipid metabolism disorders.These problems have limited the sustainable development of the aquaculture industry,and a continuable solution is required.The use of fungal polysaccharide appears to provide a solution to these problems.Therefore,different supplemented levels of Poria cocos polysaccharide(PCP)(0,0.4,0.8,1.2,1.6,and 2.0 g/kg,respectively)were fed to spotted sea bass(Lateolabrax maculatus)in similar size(30.28±0.18 g)in current study.The effects of PCP on growth,physiological parameters,and lipid metabolism of spotted sea bass were investigated after a 4-week rearing period.Results showed,fish with PCP intake presented a significantly higher weight gain,specific growth rate,and a significantly lower feed conversion ratio.Significantly higher trypsin activity in liver and intestine were observed in fish with PCP intake.The superoxide dismutase activity in serum and liver of fish with PCP intake were significantly improved,while significantly higher serum total antioxidant capacity and hepatic catalase activity were also observed.However,no significant differences in lysozyme and alkaline phosphatase activity were evident among groups.Fish with PCP intake showed a significantly lower total cholesterol,but no noteworthy change in triglyceride and lipid-metabolismrelated genes expression were observed among groups.Results indicated that intake of PCP has a positive effect on growth and antioxidant capacity of spotted sea bass,but seems to have a limited effect on the non-specific immunity and lipid metabolism of spotted sea bass.Based on the regression analysis results,1.4 g/kg of PCP is the optimal dose for spotted sea bass in size(30.28±0.18 g).

Experimental and numerical investigations on acoustic damping of monoclinic crystalline wideband sound absorbing structures

In order to overcome the limitations of traditional microperforated plate with narrow sound absorption bandwidth and a single structure,two multi-cavity composite sound-absorbing materials were designed based on the shape of monoclinic crystals:uniaxial oblique structure(UOS)and biaxial oblique structure(BOS).Through finite element simulation and experimental research,the theoretical models of UOS and BOS were verified,and their sound absorption mechanisms were revealed.At the same time,the influence of multi-cavity composites on sound absorption performance was analyzed based on the theoretical model,and the influence of structural parameters on sound absorption performance was discussed.The research results show that,in the range of 100-2000 Hz,UOS has three sound absorption peaks and BOS has five sound absorption peaks.The frequency range of the half-absorption bandwidth(α>0.5)of UOS and BOS increases by 242% and 229%,respectively.Compared with traditional microperforated sound-absorbing structures,the series and parallel hybrid methods significantly increase the sound-absorbing bandwidth of the sound-absorbing structure.This research has guiding significance for noise control and has broad application prospects in the fields of transportation,construction,and mechanical design.

Development characteristics and controlling factors of fractures in lacustrine shale and their geological significance for evaluating shale oil sweet spots in the third member of the Shahejie Formation in the Qikou Sag, Bohai Bay Basin

Natural fractures are critical for shale oil and gas enrichment and development. Due to the extremely high heterogeneity of shale, the factors controlling the formation of internal fractures, especially horizontal fractures, remain controversial. In this study, we integrate thin section analysis and microcomputed tomography(CT) data from several lacustrine shale samples from the third member(Es3) of the Shahejie Formation, Qikou Sag, Bohai Bay Basin, to assess the fractures in detail. The goal is to reveal the development characteristics, controlling factors, and geological significance for evaluating sweet spots in a shale oil play. The fractures in the Es3contain high-angle structural and horizontal bed-parallel fractures that are mostly shear and extensional. Various factors influence fracture development,including lithofacies, mineral composition, organic matter content, and the number of laminae. Structural fractures occur predominantly in siltstone, whereas bed-parallel fractures are abundant in laminated shale and layered mudstone. A higher quartz content results in higher shale brittleness, causing fractures, whereas the transformation between clay minerals contributes to the development of bedparallel fractures. Excess pore pressure due to hydrocarbon generation and expulsion during thermal advance can cause the formation of bed-parallel fractures. The density of the bed-parallel and structural fractures increases with the lamina density, and the bed-parallel fractures are more sensitive to the number of laminae. The fractures are critical storage spaces and flow conduits and are indicative of sweet spots. The laminated shale in the Es3with a high organic matter content contains natural fractures and is an organic-rich, liquid-rich, self-sourced shale play. Conversely, the siltstone, massive mudstone, and argillaceous carbonate lithofacies contain lower amounts of organic matter and do not have bed-parallel fractures. However, good reservoirs can form in these areas when structural fractures are present and the source, and storage spaces are separated.

Vibration properties of Paulownia wood for Ruan sound quality using machine learning methods

As an important material for manufacturing resonant components of musical instruments,Paulownia has an important influence on the sound quality of Ruan.In this paper,a model for evaluating the sound quality of Ruan based on the vibration characteristics of wood is developed using machine learning methods.Generally,the selection of materials for Ruan manufacturing relies primarily on manually weighing,observing,striking,and listening by the instrument technician.Deficiencies in scientific theory have hindered the quality of the finished Ruan.In this study,nine Ruans were manufactured,and a prediction model of Ruan sound quality was proposed based on the raw material information of Ruans.Out of a total of 180 data sets,145 and 45 sets were chosen for training and validation,respec-tively.In this paper,typical correlation analysis was used to determine the correlation between two single indicators in two adjacent pairwise combinations of the measured objects in each stage of the production process in Ruan.The vibra-tion characteristics of the wood were tested,and a model for predicting the evaluation of Ruan’s acoustic qualities was developed by measuring the vibration characteristics of the resonating plate material.The acoustic quality of the Ruan sound board wood was evaluated and predicted using machine learning model generalized regression neural net-work.The results show that the prediction of Ruan sound quality can be achieved using Matlab simulation based on the vibration characteristics of the soundboard wood.When the model-predicted values were compared with the tradi-tional predicted results,it was found that the generalized regression neural network had good performance,achieving an accuracy of 93.8%which was highly consistent with the experimental results.It was concluded that the model can accurately predict the acoustic quality of the Ruan based on the vibration performance of the soundboards.

Characterization of Aquifers in Crystalline and Crystallophyll Basement Zones Using the Electrical Resistivity Method (Trails and Electrical Soundings) in the Gagnoa Region, (Central-Western Côte d’Ivoire)

Introduction: Located in the central-western part of Côte d’Ivoire, the subsoil of the Gagnoa region is made up of sedimentary volcano formations and granitoids with developed fracturing. This complex Precambrian basement contains most of the region’s water resources. This is at the origin of the high failure rate during the various hydrogeological prospecting campaigns. Methodology: The database consists of resistivities from 42 holes and 51 trails drilled as part of the implementation of high-throughput drilling in the study area. The objective of this study is to deepen the knowledge of the fissured basement by interpreting profile curves and electrical soundings. It will be a question of classifying the different types of anomalies obtained on the profiles and their shapes. The orientation of the lineaments observed on the profiles was determined. Results: The interpretation of the geophysical data revealed various anomalies, the main ones being of the CC (Conductor Compartment) and CEDP (Contact between two bearings) types. These types of anomalies are mainly expressed in various forms: the “V”, “W” and “U” shapes. From these anomalies and the appearance of the electrical profiles, lineaments and their orientations were identified with N90-100, N130-140, N170-180 as major orientations. Conclusion: These results could contribute to a better understanding of the fractured environment of the Gagnoa region.

识解理论视角下The Sound and the Fury汉译本中的认知偏离

翻译偏离通常源于语言的文化差异、译者的识解能力和方式的局限。兰盖克(Langacker)2019年最新提出的识解理论五维度,为认识The Sound and the Fury四个汉译本中的认知偏离现象提供了理论支撑。这些汉译本中的偏离现象虽遵循认知规律,但深层原因主要涉及译者的视角差异、场景选择、信息突显、动态性表达及想象性再现等多个层面。在语言认知加工过程中,译者的认知框架和识解方式,以及他们与源语文本、作者和读者之间的认知互动对意义的动态构建会产生显著的影响和制约。

The hcp-bcc transition of Be via anisotropy of modulus and sound velocity

Based on ab initio calculations,we utilize the mean-field potential approach with the quantum modification in conjunction with stress–strain relation to investigate the elastic anisotropies and sound velocities of hcp and bcc Be under high-temperature(0–6000 K)and high-pressure(0–500 GPa)conditions.We propose a general definition of anisotropy for elastic moduli and sound velocities.Results suggest that the elastic anisotropy of Be is more significantly influenced by pressure than by temperature.The pressure-induced increase of c/a ratio makes the anisotropy of hcp Be significantly strengthen.Nevertheless,the hcp Be still exhibits smaller anisotropy than bcc Be in terms of elastic moduli and sound velocities.We suggest that measuring the anisotropy in shear sound velocity may be an approach to distinguishing the hcp–bcc phase transition under extreme conditions.

The effect of right versus left long-term single-sided deafness on sound source localization

Purpose: To analyze the effect of right versus left long-term single-sided deafness(SSD) on sound source localization(SSL), discuss the necessity of intervention and treatment for SSD patients, and analyze the therapeutic effect of long-term unilateral cochlear implantation(UCI) from the perspective of SSL.Methods: This study included 25 patients with SSD, 11 patients with UCI, and 30 participants with normal hearing(NH). Their SSL ability was tested by obtaining their average root mean square(RMS) error values of SSL test.Results: The results showed that the RMS error value of SSD, UCI and NH groups were 52.26 ± 20.25°, 69.84 ±12.14° and 4.27 ± 2.66°, respectively. The ability of SSL was better in the SSD-L group than that in the SSD-R group, and no significant difference existed in the SSD-R and the UCI group.Conclusion: When bilateral deafness patients select unilateral treatment, right-side cochlear implantation may be more beneficial in terms of SSL, which means that the central auditory cortex in long-term SSD patients is affected differently based on which side their deafness occurs.