Reliability evaluation of IGBT power module on electric vehicle using big data

There are challenges to the reliability evaluation for insulated gate bipolar transistors(IGBT)on electric vehicles,such as junction temperature measurement,computational and storage resources.In this paper,a junction temperature estimation approach based on neural network without additional cost is proposed and the lifetime calculation for IGBT using electric vehicle big data is performed.The direct current(DC)voltage,operation current,switching frequency,negative thermal coefficient thermistor(NTC)temperature and IGBT lifetime are inputs.And the junction temperature(T_(j))is output.With the rain flow counting method,the classified irregular temperatures are brought into the life model for the failure cycles.The fatigue accumulation method is then used to calculate the IGBT lifetime.To solve the limited computational and storage resources of electric vehicle controllers,the operation of IGBT lifetime calculation is running on a big data platform.The lifetime is then transmitted wirelessly to electric vehicles as input for neural network.Thus the junction temperature of IGBT under long-term operating conditions can be accurately estimated.A test platform of the motor controller combined with the vehicle big data server is built for the IGBT accelerated aging test.Subsequently,the IGBT lifetime predictions are derived from the junction temperature estimation by the neural network method and the thermal network method.The experiment shows that the lifetime prediction based on a neural network with big data demonstrates a higher accuracy than that of the thermal network,which improves the reliability evaluation of system.

Hadoop-based secure storage solution for big data in cloud computing environment

In order to address the problems of the single encryption algorithm,such as low encryption efficiency and unreliable metadata for static data storage of big data platforms in the cloud computing environment,we propose a Hadoop based big data secure storage scheme.Firstly,in order to disperse the NameNode service from a single server to multiple servers,we combine HDFS federation and HDFS high-availability mechanisms,and use the Zookeeper distributed coordination mechanism to coordinate each node to achieve dual-channel storage.Then,we improve the ECC encryption algorithm for the encryption of ordinary data,and adopt a homomorphic encryption algorithm to encrypt data that needs to be calculated.To accelerate the encryption,we adopt the dualthread encryption mode.Finally,the HDFS control module is designed to combine the encryption algorithm with the storage model.Experimental results show that the proposed solution solves the problem of a single point of failure of metadata,performs well in terms of metadata reliability,and can realize the fault tolerance of the server.The improved encryption algorithm integrates the dual-channel storage mode,and the encryption storage efficiency improves by 27.6% on average.

240 nm AlGaN-based deep ultraviolet micro-LEDs:size effect versus edge effect

240 nm AlGaN-based micro-LEDs with different sizes are designed and fabricated.Then,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge effects.Here,it is revealed that the peak optical output power increases by 81.83%with the size shrinking from 50.0 to 25.0μm.Thereinto,the LEE increases by 26.21%and the LEE enhancement mainly comes from the sidewall light extraction.Most notably,transversemagnetic(TM)mode light intensifies faster as the size shrinks due to the tilted mesa side-wall and Al reflector design.However,when it turns to 12.5μm sized micro-LEDs,the output power is lower than 25.0μm sized ones.The underlying mechanism is that even though protected by SiO2 passivation,the edge effect which leads to current leakage and Shockley-Read-Hall(SRH)recombination deteriorates rapidly with the size further shrinking.Moreover,the ratio of the p-contact area to mesa area is much lower,which deteriorates the p-type current spreading at the mesa edge.These findings show a role of thumb for the design of high efficiency micro-LEDs with wavelength below 250 nm,which will pave the way for wide applications of deep ultraviolet(DUV)micro-LEDs.

Efficient Electromagnetic Wave Absorption and Thermal Infrared Stealth in PVTMS@MWCNT Nano‑Aerogel via Abundant Nano‑Sized Cavities and Attenuation Interfaces

Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size(30-40 nm),high specific surface area(559 m^(2)g^(−1)),high void fraction(91.7%)and enhanced mechanical property:(1)the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect(beneficial for infrared(IR)stealth);(2)the heterogeneous interface was beneficial for IR reflection(beneficial for IR stealth)and MWCNT polarization loss(beneficial for electromagnetic wave(EMW)attenuation);(3)the high void fraction was beneficial for enhancing thermal insulation(beneficial for IR stealth)and EMW impedance match(beneficial for EMW attenuation).Guided by the above theoretical design strategy,PVTMS@MWCNT nano-aerogel shows superior EMW absorption property(cover all Ku-band)and thermal IR stealth property(ΔT reached 60.7℃).Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity,an extremely high electromagnetic interference shielding material(66.5 dB,2.06 mm thickness)with superior absorption performance of an average absorption-to-reflection(A/R)coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz(A/R ratio more than 10)was experimentally obtained in this work.

A data-driven model of drop size prediction based on artificial neural networks using small-scale data sets

An artificial neural network(ANN)method is introduced to predict drop size in two kinds of pulsed columns with small-scale data sets.After training,the deviation between calculate and experimental results are 3.8%and 9.3%,respectively.Through ANN model,the influence of interfacial tension and pulsation intensity on the droplet diameter has been developed.Droplet size gradually increases with the increase of interfacial tension,and decreases with the increase of pulse intensity.It can be seen that the accuracy of ANN model in predicting droplet size outside the training set range is reach the same level as the accuracy of correlation obtained based on experiments within this range.For two kinds of columns,the drop size prediction deviations of ANN model are 9.6%and 18.5%and the deviations in correlations are 11%and 15%.

Extended wet sieving method for determination of complete particle size distribution of general soils

The traditional standard wet sieving method uses steel sieves with aperture?0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.

Evaluation of a software positioning tool to support SMEs in adoption of big data analytics

Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.

BIG评分对接受去骨瓣减压术的中重度创伤性脑损伤儿童早期脑功能的预测价值

目的:探讨BIG评分(由格拉斯哥评分、国际标准化比值、碱剩余组成)对接受去骨瓣减压术(DC)的中重度创伤性脑损伤(TBI)患儿脑功能早期预后的预测价值。方法:回顾性分析2014年3月至2023年7月于我院接受DC治疗的所有中重度TBI患儿,以出院时儿童脑功能分类(PCPC)为结局,分为预后良好组(PCPC 1~2)和预后不良组(PCPC 3~6)。通过病历资料回顾,提取患儿的临床信息,并使用Logistic回归分析评估BIG评分的预测价值。结果:共纳入55例接受DC治疗的中重度TBI患儿,其中25例出院时脑功能良好,30例预后不良(包括9例死亡)。患儿入院时的高BIG评分(p < 0.001)、瞳孔对光反射差(p = 0.027),存在失血性休克(p = 0.042)及多发伤(p = 0.043)、脑水肿(p = 0.007),高血糖(p = 0.042)、高乳酸血症(p = 0.029)均与出院时脑功能不良相关。Logistic回归分析显示,入院时的高BIG评分是出院时脑功能不良的独立危险因素。ROC曲线分析确定的最佳BIG评分阈值为17.5,以此预测不良预后的敏感性为66.7%,特异性为88.0%。结论:接受DC的中重度TBI患儿出院时的总体脑功能不良比例为54.5%。入院时的BIG评分能够预测这些患儿出院时的早期脑功能预后,具有较高的敏感性和特异性。

Determination method of mesh size for numerical simulation of blast load in near-ground detonation

In order to improve the overall resilience of the urban infrastructures, it is required to conduct blast resistant design for important building structures in the city. For complex terrain in the city, it is recommended to determine the blast load on the structures via numerical simulation. Since the mesh size of the numerical model highly depends on the explosion scenario, there is no generally applicable approach for the mesh size selection. An efficient method to determine the mesh size of the numerical model of near-ground detonation based on explosion scenarios is proposed in this study. The effect of mesh size on the propagation of blast wave under different explosive weights was studied, and the correlations between the mesh size effect and the charge weight or the scaled distance was described. Based on the principle of the finite element method and Hopkinson-Cranz scaling law, a mesh size measurement unit related to the explosive weight was proposed as the criterion for determining the mesh size in the numerical simulation. Finally, the applicability of the method proposed in this paper was verified by comparing the results from numerical simulation and the explosion tests and was verified in AUTODYN.

New complex physiological findings evolve hypothesized mechanisms of Dravet syndrome

Developmental and epileptic encephalopathies(DEEs)are neurological disorders generally involving medically intractable seizures and a diverse array of comorbid neuropsychiatric delays and deficits that may severely affect cognition,mood,sleep,social behavior,movement control,learning,and/or memory.Dravet syndrome(DS),also known as Severe Myoclonic Epilepsy of Infancy.

Long-Cycle Lithium Batteries with LiNi_(0.8)Co_(0.1)Mn_(0.1)O_(2) Cathodes above 4.5 V Enabled by Uniform Coating of Nanosized Garnet Electrolytes

The pursuit of high-energy cathode materials has been focused on raising the charging cutoff voltage of nickel (Ni)-rich layered oxide cathode such as LiNi_(0.8)Co_(0.1)Mn_(0.1)O2 (NCM811). However, the NCM811 suffers from rapid capacity fading upon cycling at cutoff voltage higher than 4.5 V, owing to their structural degradation and labile surface reactivity. Surface-coating with solid electrolytes has been recognized as an effective method to mitigate the performance failure of NCM811 at high voltage. Herein, the nano-sized Li_(6.4)La_(3)Ta_(0.6)Zr_(1.4)O_(12) (LLZTO) is uniformly coated on the surface of single-crystal NCM811 particles, accompanied with the long-range Ta^(5+) diffusion into the transition metal layer of NCM811 lattice. It is revealed that the LLZTO coating can not only inhibit the surface reactions of NCM811 with liquid electrolytes but also play an important role in suppressing the bulk microcracking within the NCM811 particles. The incorporation of Ta^(5+) ion expands the lattice spacing and thereby improves the homogeneity of the Li^(+) diffusion in the single-crystal NCM811, which alleviates the mechanical strain and intragranular cracks caused by nonuniform phases-transformation at high charging voltage. The synergy of surface protection and structural stabilization realized by LLZTO coating enables the NCM811-based lithium batteries to achieve a remarkable electrochemical performance. Typically, LLZTO coated NCM811 delivers a high reversible specific capacity of 202.1 mAh⋅g^(−1) with an excellent capacity retention as high as 70% over 1000 cycles upon charging to 4.5 V at 1 C.

Population size estimates based on GPS telemetry

DEAR EDITOR,Accurate estimation of population size is a crucial issue in wildlife population ecology and conservation.While Global Positioning System(GPS)collars are well recognized as an effective method for monitoring wildlife behavior,their application in direct wildlife population size estimation remains underutilized.In this study,GPS telemetry was employed to survey a rhesus macaque(Macaca mulatta)population on Neilingding Island in Guangdong,China.From May 2021 to April 2022,32 macaques across nine groups were fitted with GPS collars,producing a dataset of 109739 location fixes.Analyzing data from all tracked individuals revealed the annual home ranges of the nine groups.

Utilizing sediment grain size characteristics to assess the effectiveness of clay–sand barriers in reducing aeolian erosion in Minqin desert area,China

The clay–sand barriers in Minqin desert area,China,represent a pioneering windbreak and sand fixation project with a venerable history of 60 a.However,studies on evaluating the long-term effectiveness of clay–sand barriers against aeolian erosion,particularly from the perspective of surface sediment grain size,are limited and thus insufficient to ascertain the protective impact of these barriers on regional aeolian activities.This study focused on the surface sediments(topsoil of 0–3 cm depth)of clay–sand barriers in Minqin desert area to explain their erosion resistance from the perspective of surface sediment grain size.In March 2023,six clay–sand barrier sampling plots with clay–sand barriers of different deployment durations(1,5,10,20,40,and 60 a)were selected as experimental plots,and one control sampling plot was set in an adjacent mobile sandy area without sand barriers.Surface sediment samples were collected from the topsoil of each sampling plot in the study area in April 2023 and sediment grain size characteristics were analyzed.Results indicated a predominance of fine and medium sands in the surface sediments of the study area.The deployment of clay–sand barriers cultivated a fine quality in grain size composition of the regional surface sediments,increasing the average contents of very fine sand,silt,and clay by 30.82%,417.38%,and 381.52%,respectively.This trend became markedly pronounced a decade after the deployment of clay–sand barriers.The effectiveness of clay–sand barriers in erosion resistance was manifested through reduced wind velocity,the interception of sand flow,and the promotion of fine surface sediment particles.Coarser particles such as medium,coarse,and very coarse sands predominantly accumulated on the external side of the barriers,while finer particles such as fine and very fine sands concentrated in the upwind(northwest)region of the barriers.By contrast,the contents of finest particles such as silt and clay were higher in the downwind(southeast)region of the sampling plots.For the study area,the deployment of clay–sand barriers remains one of the most cost-effective engineering solutions for aeolian erosion control,with sediment grain size parameters serving as quantitative indicators for the assessment of these barriers in combating desertification.The results of this study provide a theoretical foundation for the construction of windbreak and sand fixation systems and the optimization of artificial sand control projects in arid desert areas.

Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access controlmechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policymanagement efficiency and difficulty in accurately describing the access control policy. To overcome theseproblems, this paper proposes a big data access control mechanism based on a two-layer permission decisionstructure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes areintroduced in the ABAC model as business constraints between entities. The proposed mechanism implementsa two-layer permission decision structure composed of the inherent attributes of access control entities and thebusiness attributes, which constitute the general permission decision algorithm based on logical calculation andthe business permission decision algorithm based on a bi-directional long short-term memory (BiLSTM) neuralnetwork, respectively. The general permission decision algorithm is used to implement accurate policy decisions,while the business permission decision algorithm implements fuzzy decisions based on the business constraints.The BiLSTM neural network is used to calculate the similarity of the business attributes to realize intelligent,adaptive, and efficient access control permission decisions. Through the two-layer permission decision structure,the complex and diverse big data access control management requirements can be satisfied by considering thesecurity and availability of resources. Experimental results show that the proposed mechanism is effective andreliable. In summary, it can efficiently support the secure sharing of big data resources.

Genetic analysis and fine mapping of a grain size QTL in the smallgrain sterile rice line Zhuo201S

The development and application of the small-grain rice sterile line Zhuo201S(Z201S)has demonstrated its potential for mechanized hybrid rice seed production,leading to significant cost reductions.However,the molecular mechanism responsible for the small-grain size characteristic of Z201S remains unclear.In this study,we conducted a genetic analysis using near-isogenic lines constructed from Z210S,a small-grain rice sterile line,and R2115,a normal-grain variety.The results revealed that the small-grain trait in Z201S is governed by a single partially dominant gene which also enhances grain number.Through mapping,we localized the causal gene to the short arm of chromosome 2,within a 113 kb physical region delimited by the molecular markers S2-4-1 and LB63.Transgenic analysis and gene expression assays indicated LOC_Os02g14760 as the most likely candidate gene,suggesting that the small-grain size trait of Z201S is controlled by a novel locus that has not been previously identified.

Tumor size discrepancy between endoscopic and pathological evaluations in colorectal endoscopic submucosal dissection

BACKGROUND Tumor size impacts the technical difficulty and histological curability of colorectal endoscopic submucosal dissection(ESD);however,the preoperative evaluation of tumor size is often different from histological assessment.Analyzing influential factors on failure to obtain an accurate tumor size evaluation could help prepare optimal conditions for safer and more reliable ESD.METHODS This was a retrospective study conducted at a single institution.A total of 377 lesions removed by colorectal ESD at our hospital between April 2018 and March 2022 were collected.We first assessed the difference in size with an absolute per-centage of the scaling discrepancy.Subsequently,we compared the clinicopatho-logical characteristics of the correct scaling group(>-33%and<33%)with that of the incorrect scaling group(<-33%or>33%),which was further subdivided into the underscaling group(-33%or less of the discrepancy)and overscaling group(33%or more of the discrepancy),respectively.As secondary outcome measures,parameters on size estimation were compared between the underscaling and correct scaling groups,as well as between the overscaling and correct scaling groups.Finally,multivariate analysis was performed in terms of the following relevant parameters on size estimation:Pathological size,location,and possible influential factors(P<0.1)in the univariate analysis.RESULTS The mean of absolute percentage in the scaling discordance was 21%,and 91 lesions were considered to be incorrectly estimated in size.The incorrect scaling was significantly remarkable in larger lesions(40 mm vs 28 mm;P<0.001)and less experience(P<0.001),and these two factors were influential on the underscaling(75 lesions;P<0.001).Conversely,compared with the correct scaling group,16 lesions in the overscaling group were significantly small(20 mm vs 28 mm;P<0.001),and the small lesion size was influential on the overscaling(P=0.002).CONCLUSION Lesions indicated for colorectal ESD tended to be underestimated in large tumors,but overestimated in small ones.This discrepancy appears worth understanding for optimal procedural preparation.

High-Volume Mineral Admixtures Cement: The Effects of Particle Size Distribution

The effects of high-volume slag-fly ash cement with different particle sizes on hydration degree,microstructure and mechanical properties were systematically studied,by means of laser particle size(DLS),X-ray diffraction (XRD),comprehensive thermal analysis (TG-DTA),scanning electron microscopy(SEM) and mechanical properties tests.The results show that suitable particle size distribution of cementitious material has significantly promoting effects on hydration reaction rate and mechanical properties.Compared with slag without further grinding,the slag after ball milling for 4 h has an obvious improvement in reactivity,which also provides a faster hydration rate and higher compressive strength for the cementitious material.When the slag milled for 1 and 4 h is mixed at a mass ratio of 2:1 (i e,slag with D_(50) of 7.4μm and average size of 9.9μm,and slag with D_(50) value of 2.6μm and average size of 5.3μm),and a certain amount of fly ash is added in,the most obvious improvement of compressive strength of cement is achieved.

Kinetics insights into size effects of carbon nanotubes'growth and their supported platinum catalysts for 4,6-dinitroresorcinol hydrogenation

Size effects are a well-documented phenomenon in heterogeneous catalysis,typically attributed to alterations in geometric and electronic properties.In this study,we investigate the influence of catalyst size in the preparation of carbon nanotube(CNT)and the hydrogenation of 4,6-dinitroresorcinol(DNR)using Fe_(2)O_(3)and Pt catalysts,respectively.Various Fe_(2)O_(3)/Al_(2)O_(3)catalysts were synthesized for CNT growth through catalytic chemical vapor deposition.Our findings reveal a significant influence of Fe_(2)O_(3)nanoparticle size on the structure and yield of CNT.Specifically,CNT produced with Fe_(2)O_(3)/Al_(2)O_(3)containing 28%(mass)Fe loading exhibits abundant surface defects,an increased area for metal-particle immobilization,and a high carbon yield.This makes it a promising candidate for DNR hydrogenation.Utilizing this catalyst support,we further investigate the size effects of Pt nanoparticles on DNR hydrogenation.Larger Pt catalysts demonstrate a preference for 4,6-diaminoresorcinol generation at(100)sites,whereas smaller Pt catalysts are more susceptible to electronic properties.The kinetics insights obtained from this study have the potential to pave the way for the development of more efficient catalysts for both CNT synthesis and DNR hydrogenation.

On the Optimal Initial Inner-Core Size for Tropical Cyclone Intensification: An Idealized Numerical Study

Recent observational and numerical studies have revealed the dependence of the intensification rate on the inner-core size of tropical cyclones(TCs). In this study, with the initial inner-core size(i.e., the radius of maximum wind—RMW)varied from 20–180 km in idealized simulations using two different numerical models, we found a nonmonotonic dependence of the lifetime maximum intensification rate(LMIR) on the inner-core size. Namely, there is an optimal innercore size for the LMIR of a TC. Tangential wind budget analysis shows that, compared to large TCs, small TCs have large inward flux of absolute vorticity due to large absolute vorticity inside the RMW. However, small TCs also suffer from strong lateral diffusion across the eyewall, which partly offsets the positive contribution from large inward flux of absolute vorticity. These two competing processes ultimately lead to the TC with an intermediate initial inner-core size having the largest LMIR. Results from sensitivity experiments show that the optimal size varies in the range of 40–120 km and increases with higher sea surface temperature, lower latitude, larger horizontal mixing length, and weaker initial TC intensity. The 40–120 km RMW corresponds to the inner-core size most commonly found for intensifying TCs in observations, suggesting the natural selection of initial TC size for intensification. This study highlights the importance of accurate representation of TC inner-core size to TC intensity forecasts by numerical weather prediction models.

qGW11a/OsCAT8,encoding an amino acid permease,negatively regulates grain size and weight in rice

Grain size is a key factor influencing grain weight in rice.In this study,a chromosome segment substitution line(CSSL9-17)was identified,that exhibits a significant reduction in both grain size and weight compared to its donor parent 93-11.Further investigation identified two quantitative trait loci(QTL)on chromosome 11,designated qGW11a and qGW11b,which contribute to 1000-grain weight with an additive effect.LOC_Os11g05690,encoding the amino acid permease OsCAT8,is the target gene of qGW11a.Overexpression of OsCAT8 resulted in decreased grain weight,while OsCAT8 knockout mutants exhibited increased grain weight.The 287-bp located within the OsCAT8 promoter region of 93-11 negatively regulates its activity,which is subsequently correlated with an increase in grain size and weight.These results suggest that OsCAT8 functions as a negative regulator of grain size and grain weight in rice.