Global dynamics and noise-induced transitions for a two-dimensional panel system in subsonic flow

A two-dimensional panel in subsonic flow with stochastic excitation is studied by assuming that the aerodynamic pressure contains random pressure fluctuations.Based on the global properties,the sensitivities of system parameters and noise intensities are presented.Firstly,the parameter region with multiple coexisting attractors under different dynamic pressures is obtained.It is found that the coexistence of multiple attractors extensively appears and the basin structure may be complex.Then the periodic time history diagrams are calculated by simulating the random pressure fluctuation as Poisson white noise.The results show that under typical bistable conditions,the noise sensitivity of the subsonic panel system is related to the basin structures and the disposition of the coexisting attractors to the saddle.The transition between two attractors diffuses along the unstable manifold and tends to the position where the basin boundary curvature is relatively large.The findings underscore the importance of global analysis in assessing the noise load carrying capacity,which provides some valuable insights into the safety design of subsonic panel systems.

基因panel在新生儿疑似遗传代谢疾病中的应用

目的探讨基因panel在患有疑似遗传代谢疾病新生儿中的应用。方法对华中科技大学同济医学院附属同济医院2023年1月—2024年3月收治的有遗传代谢高危临床表型的新生儿,采用基因panel检测,同时搜集其临床资料并进行随访观察,分析致病基因的检出情况、患儿基因型与表型的一致性等。结果该研究共纳入53例有遗传代谢高危征象的新生儿,其中致病基因阳性的总体检出率为17.0%(9/53),常见检出的致病基因有氯离子通道基因(CLCN1)、双氧化酶2基因(DUOX2)、间隙连接蛋白β2基因(GJB2)、酪氨酸蛋白磷酸酶非受体11型基因(PTPN11)、钠通道α亚基基因(SCN1A)、痉挛截瘫基因11(SPG11)等,其中DUOX2和GJB2检出比例最高,分别为33.3%(3/9)和22.2%(2/9)。将致病基因阳性组患儿与阴性组患儿进行对比分析,阳性组患儿临床表型个数可能更多,预后相较于基因阴性组也更严重。在致病基因阳性组患儿中,除了病例1和病例9因相关疾病发病较晚导致临床表型与致病基因暂时不相符,其余病例致病基因与临床表型均符合。结论基因panel具有耗时短、检测成本及技术难度低等特点,适用于发展中国家及经济水平相对落后地区疑似遗传代谢疾病患儿的早期筛查。

Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

Energy dissipation mechanism and ballistic characteristic optimization in foam sandwich panels against spherical projectile impact

This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on the geometric topology of the FSP system,three FSP configurations with the same areal density are derived,namely multi-layer,gradient core and asymmetric face sheet,and three key structural parameters are identified:core thickness(t_(c)),face sheet thickness(t_(f))and overlap face/core number(n_(o)).The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity(BLV),deformation modes,energy dissipation mechanism,and specific penetration energy(SPE).The results show that the FSP system exhibits a significant configuration dependence,whose ballistic performance ranking is:asymmetric face sheet>gradient core>multi-layer.The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system.Both BLV and SPE increase with tf,while the raising tcor noleads to an increase in BLV but a decrease in SPE.Further,a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis,based on which the ballistic optimization procedure is also conducted and a design chart is established.This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.

Impact of Different Rooftop Coverings on Photovoltaic Panel Temperature

Photovoltaic(PV)panels are essential to the global transition towards sustainable energy,offering a clean,renewable source that reduces reliance on fossil fuels and mitigates climate change.High temperatures can significantly affect the performance of photovoltaic(PV)panels by reducing their efficiency and power output.This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic(PV)panels.It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels,considering the thermal performance and its implications for enhancing their overall performance and sustainability.The study compares four rooftop covering materials:wooden flakes packs(both dry and wet),polystyrene,and woolen insulation.The measurements were implemented under Iraqi weather conditions.The comparison was based on the PV panels’thermal behavior and its impact on conversion efficiency.The results revealed that covering the roof beneath the installed PV panels reduces their temperature and increases efficiency.The best performance was observedwhen placingwetwooden flakes beneath the panels,with an efficiency increase of 5%.Moreover,thewoolen insulation offered an efficiency rise of 12%near sunset.Themain outcome of thiswork is that the wet–wooden–flakes showed the best performance improvement of the PV panels.

A Novel Integrated Photovoltaic System with a Three-Dimensional Pulsating Heat Pipe

Solar energy is a valuable renewable energy source,and photovoltaic(PV)systems are a practical approach to harnessing this energy.Nevertheless,low energy efficiency is considered a major setback of the system.Moreover,high cell temperature and reflection of solar irradiance from the panel are considered chief culprits in this regard.Employing pulsating heat pipes(PHPs)is an innovative and useful approach to improving solar panel performance.This study presents the results of the power performance of a PV panel attached to a newly designed spiral pulsating heat pipe,while graphene oxide nanofluid with three different concentrations was used as a working fluid to maximize the efficacy of the solar panel.The study proved that the cooling method delivered high efficiency by reducing the temperature,especially in the middle of the day.Using nanofluid graphene oxide at concentrations of 0.2,0.4,and 0.8 gr/lit as the working fluid can reduce the thermal resistance of PHPs by over 30%,24%,and 15%,respectively.This,in turn,enhances the system’s electrical power output by approximately 9%,7%,and 6%,respectively.

How R&D investment promotes green technology innovation in the context of digitalization?-An empirical analysis based on provincial panel data

Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.

Advancements in Photovoltaic Panel Fault Detection Techniques

This paper examines the progression and advancements in fault detection techniques for photovoltaic (PV) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of PV technology grows, the need for effective fault detection strategies becomes increasingly paramount to maximize energy output and minimize operational downtimes of solar power systems. These approaches include the use of machine learning and deep learning methodologies to be able to detect the identified faults in PV technology. Here, we delve into how machine learning models, specifically kernel-based extreme learning machines and support vector machines, trained on current-voltage characteristic (I-V curve) data, provide information on fault identification. We explore deep learning approaches by taking models like EfficientNet-B0, which looks at infrared images of solar panels to detect subtle defects not visible to the human eye. We highlight the utilization of advanced image processing techniques and algorithms to exploit aerial imagery data, from Unmanned Aerial Vehicles (UAVs), for inspecting large solar installations. Some other techniques like DeepLabV3 , Feature Pyramid Networks (FPN), and U-Net will be detailed as such tools enable effective segmentation and anomaly detection in aerial panel images. Finally, we discuss implications of these technologies on labor costs, fault detection precision, and sustainability of PV installations.

Composite Panels from the Combination of Rice Husk and Wood Chips with a Natural Resin Based on Tannins Reinforced with Sugar Cane Molasses Intended for Building Insulation: Physico-Mechanical and Thermal Properties

The objective of this work is to develop new biosourced insulating composites from rice husks and wood chips that can be used in the building sector. It appears from the properties of the precursors that rice chips and husks are materials which can have good thermal conductivity and therefore the combination of these precursors could make it possible to obtain panels with good insulating properties. With regard to environmental and climatic constraints, the composite panels formulated at various rates were tested and the physico-mechanical and thermal properties showed that it was essential to add a crosslinker in order to increase certain solicitation. an incorporation rate of 12% to 30% made it possible to obtain panels with low thermal conductivity, a low surface water absorption capacity and which gives the composite good thermal insulation and will find many applications in the construction and real estate sector. Finally, new solutions to improve the fire reaction of the insulation panels are tested which allows to identify suitable solutions for the developed composites. In view of the flame tests, the panels obtained are good and can effectively combat fire safety in public buildings.

Intelligent Solar Chasing Street Light System Design and Fabrication Summaries

This project adopts an advanced microcontroller as the core control unit,which accurately commands the servo drive,realizes the real-time light chasing and charging function of the solar panel,and effectively manages the power supply system of the street light.At the same time,the system is able to continuously monitor the operation status of the servo within the range of 0°to 180°to ensure that it is trouble-free and not offline.The hardware system construction consists of five modules:a power module,solar panel module,servo module,street light module,and Organic Light-Emitting Diode(OLED)display module.Each module works together to support the stable operation of the whole system.The system workflow is to accurately determine the direction of the light source by collecting real-time light intensity data through four precision photoresistors.Subsequently,the microcontroller intelligently controls the helm module based on these data to drive the solar panel to rotate within a range of 180°to accurately track the sun’s orientation.The street light provides two lighting modes,automatic and manual,to meet the needs of different scenarios.During the daytime,the solar panels work actively to monitor and collect solar energy efficiently in real-time,meanwhile,when night falls,the solar panels switch to standby mode and the streetlights light up automatically,illuminating the road ahead for pedestrians.Compared with the traditional solar street lights on the market,the intelligent solar light chasing road system introduced in this project has significant advantages.Its unique light-chasing algorithm enables the solar panel to continuously track the light source from sunrise to sunset,thus significantly improving the charging efficiency.Compared with traditional street lights,the biggest advantage of this project is the proposed light-chasing algorithm,which can always charge from sunrise until sunset,making the charging efficiency increase by 38%to 47%.The charging efficiency is 20%to 38%higher than that of traditional street lamps.Simultaneously,the biggest advantage of this project is that the power storage capacity is higher than 35%of the traditional solar street light.Bringing users a more durable and stable lighting experience.

Tilt Angle Optimality Criteria for Stand Alone PV Systems

The conventional approach to optimizing tilt angles for fixed solar panels aims to maximize energy generation over the entire year. However, in the context of a supply controlled electric grid, where solar energy availability varies, this criterion may not be optimal. This study explores two alternative optimization criteria focused on maximizing baseload supply potential and minimizing required storage capacity to address seasonality in energy generation. The optimal tilt angles determined for these criteria differed significantly from the standard approach. This research highlights additional factors crucial for designing solar power systems beyond gross energy generation, essential for the global transition towards a fully renewable energy-based electric grid in the future.

Comprehensive Examination of Solar Panel Design: A Focus on Thermal Dynamics

In the 21st century, the deployment of ground-based Solar Photovoltaic (PV) Modules has seen exponential growth, driven by increasing demands for green, clean, and renewable energy sources. However, their usage is constrained by certain limitations. Notably, the efficiency of solar PV modules on the ground peaks at a maximum of 25%, and there are concerns regarding their long-term reliability, with an expected lifespan of approximately 25 years without failures. This study focuses on analyzing the thermal efficiency of PV Modules. We have investigated the temperature profile of PV Modules under varying environmental conditions, such as air velocity and ambient temperature, utilizing Computational Fluid Dynamics (CFD). This analysis is crucial as the efficiency of PV Modules is significantly impacted by changes in the temperature differential relative to the environment. Furthermore, the study highlights the effect of airflow over solar panels on their temperature. It is found that a decrease in the temperature of the PV Module increases Open Circuit Voltage, underlining the importance of thermal management in optimizing solar panel performance.

血清外泌体microRNAs单一及组合panel对结直肠癌的诊断价值

目的 检测血清外泌体miR-15b、miR-16、miR-21和miR-31在结直肠癌患者中的表达水平,并评估其对结直肠癌的诊断价值。方法 选取2018年3月至2022年5月本院收治的123例直肠癌患者(结直肠癌组)及117例大肠腺瘤患者作为研究对象(结直肠癌组),并纳入150例健康对照者作为对照(健康对照组)。提取血清外泌体中miR-15b、miR-16、miR-21和miR-31,qRT-PCR比较4种miRNA在各组中表达水平差异。受试者工作特征(ROC)曲线评价4种miRNA单一及组合panel对结直肠癌的诊断价值。结果 结直肠癌组血清miR-15b、miR-16、miR-21和miR-31水平高于健康对照组(P <0.05),且miR-15b、miR-21和miR-31水平高于结直肠腺瘤组(P <0.05)。Ⅲ-Ⅳ期、伴淋巴结浸润、低分化程度结直肠癌组患者血清miR-15b、miR-21和miR-31水平分别高于Ⅰ-Ⅱ期、不伴淋巴结浸润、中-高分化程度患者,miR-15b、miR-21和miR-31水平与临床TNM分期、伴淋巴结浸润呈正相关,与分化程度呈负相关。4种miRNA中诊断价值最高的指标是miR-15b,其敏感度和特异度分别为81.33%和91.80%(P <0.05);且miR-15b、miR-21和miR-31的组合panel具有更好的诊断价值,其敏感度和特异度分别为95.06%和94.44%(P <0.05)。结论 miR-15b、miR-16、miR-21和miR-31在结直肠癌患者外周血血清中异常表达,miR-15b、miR-21和miR-31水平与结直肠癌的发病及进展密切相关,且miR-15b、miR-21和miR-31组合panel具有作为结直肠癌的新型诊断模型的潜力。

Analysis of Influencing Factors on Lift Coefficients of Autonomous Sailboat Double Sail Propulsion System Based on Vortex Panel Method

Sail is the core part of autonomous sailboat and wing sail is a new type of sail. Wing sail generates not only propulsion but also lateral force and heeling moment. The latter two will affect the navigation status and bring resistance. Double sail can effectively reduce the center of wind pressure and heeling moment. In order to study the effect of distance between two sails, airfoil and attack angle on the total lift coefficient of double sail propulsion system, pressure coefficient distribution and lift coefficient calculation model have been established based on vortex panel method. By using the basic finite solution, the fluid dynamic forces on the two-dimensional sails are computed.The results show that, the distance in the range of 0 to 1 time chord length, when using the same airfoil in the fore and aft sail, the total lift coefficient of the double sail increases with the increase of distance, finally reaches a stable value in the range of one to three times chord length. Lift coefficients of thicker airfoils are more sensitive to the change of distance. The thicker the airfoil, the longer distance is required of the total lift coefficient toward stable.When different airfoils are adopted in fore and aft sail, the total lift coefficient increases with the increase of the thickness of aft sail. The smaller the thickness difference is, the more sensitive to the distance change the lift coefficient is. The thinner the fore sail is, the lower the influence will be on the lift coefficient of aft sail.

Sensitivity analysis of spacecraft in micrometeoroids and orbital debris environment based on panel method

To reduce the risk of mission failure caused by the MM/OD impact of the spacecraft,it is necessary to optimize the design of the spacecraft.Spacecraft survivability assessment is the key technology in the optimal design of spacecraft.Spacecraft survivability assessment includes spacecraft impact sensitivity analysis and spacecraft component vulnerability analysis under MM/OD environment.The impact sensitivity refers to the probability of a spacecraft encountering an MM/OD impact while in orbit.Vulnerability refers to the probability that each component of a spacecraft may fail or malfunction when impacted by space debris.Yet this paper mainly analyzes the impact sensitivity and proposes a spacecraft sensitivity assessment method under the MM/OD environment based on a panel method.Under this panel method,a spacecraft geometric model is discretized into small panels,and whether they are impacted by MM/OD or not is determined through the analysis of the shielding or shadowing relationships between panels.The number of impacts on each panel is obtained through calculation,and accordingly the probability of each spacecraft component encountering MM/OD impact can be acquired,thus generating the impact sensibility.This paper extracts data from the NASA’s ORDEM2000,the ESA’s MASTER8 as well as the SDEEM2015(Space Debris Environmental Engineering Model developed by HIT),and uses the PCHIP(Piecewise Cubic Hermite Interpolating Polynomial)method to interpolate and fit the size-flux relationship of space debris.Compared with linear interpolation and cubic spline interpolation,the fitting results through the method are relatively more accurate.The feasibility of this method is also demonstrated through two actual examples shown in this paper,whose results are close to those from ESABASE,although there are some minor errors mainly due to different debris data input.Through the cross-check by three risk assessment software-BUMPER,MDPANTO and MODAOST-under standard operating conditions,the feasibility of this method is again verified.

Acquisition System for Photovoltaic Panels with Data Storage in Remote Sewer Platforms Using Open Source Platforms Raspberry Pi and Arduino

This paper consists of a prototype for a data acquisition system connected via wireless network for data storage on a remote server. This study presents the acquisition board and the operating principle of the whole system developed starting at the measurement of data up to its storage on a remote server. Using a remote server connected to the Internet implies the possibility of analysis, manipulation and control of such data from anywhere in the world.

Regulation of the growth of sprouting roots of black locust seedlings using root barrier panels

How can we regulate an invasive alien species of high commercial value?Black locust(Robinia pseudoacacia L.)has a unique capacity for seed dispersal and high germination.Field surveys indicate that black locust increases its growing area with sprouting roots and the elongation of horizontal roots at a soil depth of 10 cm.Therefore,a method to regulate the development of horizontal roots could be eff ective in slowing the invasiveness of black locust.In this study,root barrier panels were tested to inhibit the growth of horizontal roots.Since it is labor intensive to observe the growth of roots in the fi eld,it was investigated in a nursery setting.The decrease in secondary fl ush,an increase in yellowed leafl ets,and the height in the seedlings were measured.Installing root barrier panels to a depth of 30 cm eff ectively inhibit the growth of horizontal roots of young black locust.

Developing strategy for rural transformation to alleviate poverty in Pakistan:Stylized facts from panel analysis

Sustainable income growth and poverty reduction remain critical challenges at the forefront of research in Pakistan,particularly in rural areas.To overcome these challenges,the role of rural transformation(RT)has emerged and gained importance in recent years.The present study is based on district-level data and covers the period from 1981 to 2019.The study attempts to quantify the role of rural transformation in boosting rural per capita income and alleviating rural poverty in the country.The study also aims to explore the impact of stages of rural transformation on rural per capita income and rural poverty alleviation.The empirical findings reveal that rural transformation(RT_(1)and RT_(2))is essential in enhancing rural per capita income and alleviating rural poverty.The role of the share of high-value crops(RT_(1))is more pronounced than the share of non-farm employment(RT_(2))in boosting rural per capita income and poverty alleviation.The trend of larger contribution of RT_(1)to enhance rural per capita income also continued at 2nd stage of rural transformation.In the case of poverty reduction,at 3rd stage of rural transformation,the role of RT_(2)is dominant.Our results indicate that districts at higher stages of rural transformation(both RT_(1)and RT_(2))tend to correlate positively with increased rural per capita income and reduced poverty rates,suggesting that progress in rural transformation is associated with improved economic conditions.However,it is important to note that this correlation does not necessarily imply a direct causal relationship between rural transformation and these economic outcomes;other factors may have influenced this relationship.In addition,the welfare impacts are more noticeable among the districts where a simultaneous shift from grain crops to cash crops and from farm employment to non-farm employment is observed.The study provides baseline information to learn experiences from fast-growing districts and to replicate the strategies in other districts,which boosts the RT process that may increase rural per capita income and enhance poverty reduction efforts.

Ghost-Retina Net:Fast Shadow Detection Method for Photovoltaic Panels Based on Improved Retina Net

Based on the artificial intelligence algorithm of RetinaNet,we propose the Ghost-RetinaNet in this paper,a fast shadow detection method for photovoltaic panels,to solve the problems of extreme target density,large overlap,high cost and poor real-time performance in photovoltaic panel shadow detection.Firstly,the Ghost CSP module based on Cross Stage Partial(CSP)is adopted in feature extraction network to improve the accuracy and detection speed.Based on extracted features,recursive feature fusion structure ismentioned to enhance the feature information of all objects.We introduce the SiLU activation function and CIoU Loss to increase the learning and generalization ability of the network and improve the positioning accuracy of the bounding box regression,respectively.Finally,in order to achieve fast detection,the Ghost strategy is chosen to lighten the size of the algorithm.The results of the experiment show that the average detection accuracy(mAP)of the algorithm can reach up to 97.17%,the model size is only 8.75 MB and the detection speed is highly up to 50.8 Frame per second(FPS),which can meet the requirements of real-time detection speed and accuracy of photovoltaic panels in the practical environment.The realization of the algorithm also provides new research methods and ideas for fault detection in the photovoltaic power generation system.