Crack elimination and strength enhancement mechanisms of selective laser melted Si-modified Al−Mn−Mg−Er−Zr alloy

In order to increase the processability and process window of the selective laser melting(SLM)-fabricated Al−Mn−Mg−Er−Zr alloy,a novel Si-modified Al−Mn−Mg−Er−Zr alloy was designed.The effect of Si alloying on the surface quality,processability,microstructure,and mechanical properties of the SLM-fabricated alloy was studied.The results showed that introducing Si into the Al−Mn−Mg−Er−Zr alloy prevented balling and keyhole formation,refined the grain size,and reduced the solidification temperature,which eliminated cracks and increased the processability and process window of the alloy.The maximum relative density of the SLM-fabricated Si/Al−Mn−Mg−Er−Zr alloy reached 99.6%.The yield strength and ultimate tensile strength of the alloy were(371±7)MPa and(518±6)MPa,respectively.These values were higher than those of the SLM-fabricated Al−Mn−Mg−Er−Zr and other Sc-free Al−Mg-based alloys.

A phenology-based vegetation index for improving ratoon rice mapping using harmonized Landsat and Sentinel-2 data

Ratoon rice,which refers to a second harvest of rice obtained from the regenerated tillers originating from the stubble of the first harvested crop,plays an important role in both food security and agroecology while requiring minimal agricultural inputs.However,accurately identifying ratoon rice crops is challenging due to the similarity of its spectral features with other rice cropping systems(e.g.,double rice).Moreover,images with a high spatiotemporal resolution are essential since ratoon rice is generally cultivated in fragmented croplands within regions that frequently exhibit cloudy and rainy weather.In this study,taking Qichun County in Hubei Province,China as an example,we developed a new phenology-based ratoon rice vegetation index(PRVI)for the purpose of ratoon rice mapping at a 30 m spatial resolution using a robust time series generated from Harmonized Landsat and Sentinel-2(HLS)images.The PRVI that incorporated the red,near-infrared,and shortwave infrared 1 bands was developed based on the analysis of spectro-phenological separability and feature selection.Based on actual field samples,the performance of the PRVI for ratoon rice mapping was carefully evaluated by comparing it to several vegetation indices,including normalized difference vegetation index(NDVI),enhanced vegetation index(EVI)and land surface water index(LSWI).The results suggested that the PRVI could sufficiently capture the specific characteristics of ratoon rice,leading to a favorable separability between ratoon rice and other land cover types.Furthermore,the PRVI showed the best performance for identifying ratoon rice in the phenological phases characterized by grain filling and harvesting to tillering of the ratoon crop(GHS-TS2),indicating that only several images are required to obtain an accurate ratoon rice map.Finally,the PRVI performed better than NDVI,EVI,LSWI and their combination at the GHS-TS2 stages,with producer's accuracy and user's accuracy of 92.22 and 89.30%,respectively.These results demonstrate that the proposed PRVI based on HLS data can effectively identify ratoon rice in fragmented croplands at crucial phenological stages,which is promising for identifying the earliest timing of ratoon rice planting and can provide a fundamental dataset for crop management activities.

A preliminary site selection system for underground hydrogen storage in salt caverns and its application in Pingdingshan,China

Large‐scale underground hydrogen storage(UHS)provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition.Of all the existing storage deposits,salt caverns are recognized as ideal sites for pure hydrogen storage.Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues.In this article,the software CiteSpace is used to analyze and filter hot topics in published research.Based on a detailed classification and analysis,a“four‐factor”model for the site selection of salt cavern hydrogen storage is proposed,encompassing the dynamic demands of hydrogen energy,geological,hydrological,and ground factors of salt mines.Subsequently,20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted,which provided a preliminary site selection system for salt cavern hydrogen storage.Ultimately,the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City,Henan Province,thereby confirming its rationality and effectiveness.This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.

The Grey Analysis, Kriging and Selection Index of Flower Yield in Rugosa Rose

The analysis of grey system, kriging interpolation, and integration selection index were employed to investigate the relationships between the flower yield/plant （FY） and 15 other quantitative traits of 20 rugosa rose cultivars. The result showed that： The grey relational grade （GRG） of the number of flowers/plant （NF）, the number of branches/plant （NB）, the width of floral bud （WB）, and the weight/flower （WF） to the FY were larger （〉 0.5）; FY improved with the increase of NF and NB. Moreover, the indirect selection of either trait could not achieve improvement of FY. It is necessary to improve FY by multi-trait selection. The integration selection index （ISI） equation of FY was established with the characters NF, NB, WB, and WF： I= 0.3187x1 - 318.6x2 ＋ 670.1 x4 ＋ 6.3xa, index heritability = 0.8014, selective response of the integration breeding value = 245.8811. This will provide a theoretic basis for the genetic breeding of rugosa rose.

Screen House Assessment of Cowpea [(Vigna unguiculata (L.)] Genotypes for Drought Tolerance Using Selection Indices

Cowpea [Vigna unguiculata (L.)] is one of the most important arid legumes cultivated for pulse and forage production. Drought is one of the most damageable constraints to crop production impacting negatively food security. The potential of cowpea to address food security is well established. However, not much is known about the base index selection method in breeding cowpea for drought tolerance, which is important for yields. Consequently, the present study has been conducted to: 1) evaluate the yield performance of cowpea genotypes under artificial drought and well-watered condition, 2) ranke genotype performance using selection indices, and 3) assess relationship between agronomic traits and yield. The experiment was the 2 watering conditions laid out in a Randomized Complete Block Design (RCBD) with three replications. The experiment was carried out in pots under screen house at the Department of Horticulture at KNUST. The result showed that KPR1-96-73, Simbo, CZ06-4-16, Wilibaly and Agyenkwa were high yielding in well-water condition while Ghana Shoba, Sangaraka, Nketewade, Ghana Shoni and Korobalen were high yielding genotypes in water stress condition. The average yield reduction was 60.6% and 16% for grain and fodder yield respectively. The biplot displays revealed four groups among the genotypes tested which were based on their yielding capacity and drought tolerance. In cluster B high yielding and drought tolerant genotypes were identified, high yielding and drought susceptible have been identified in cluster A, low yielding and drought tolerant in cluster D, and lastly low yielding and drought susceptible in cluster C. Genotypes in cluster B were best due to the fact that it combines high yield and tolerance to drought. They were Ghana Shoni, Nketewade, Sangaraka and Ghana Shoba. These genotypes might be suitably employed in further drought tolerance breeding programs of cowpea. Significant relationships were observed between agronomic trait and yields under drought condition.

选区激光熔化成形TiB_(2)/Al-Si-Mg大尺寸复杂构件

选区激光熔化(SLM)成形大尺寸复杂构件厚度多样、成形高度较高、方向复杂,需要研究构件微观组织均匀性和力学性能稳定性。本文以SLM成形TiB_(2)/Al-Si-Mg复合材料为研究对象,分析复合材料多级微观组织,对比不同成形厚度、高度、方向下复合材料的力学性能。结果表明:复合材料表现出熔池特征结构,细小等轴晶粒组织均匀分布且随机取向,纳米TiB_(2)颗粒在材料内部弥散分布。随成形厚度增加,复合材料伸长率保持稳定,抗拉强度受本征热处理影响略微增大;在不同成形高度下,复合材料抗拉强度和伸长率保持稳定;在不同成形方向下,复合材料抗拉强度保持稳定,伸长率受熔池结构影响在水平方向略高。基于以上结果,成功制备大飞机舱门铰链臂(588 mm×318 mm×470 mm)复杂结构件。

Status of Selective Emitters for p-Type c-Si Solar Cells

Crystalline silicon (c-Si) solar cells have the lion share in world PV market. Solar cells made from crystalline silicon have lower conversion efficiency, hence optimization of each process steps are very important. Achieving low-cost photovoltaic energy in the coming years will depend on the development of third-generation solar cells. Given the trend towards these Si materials, the most promising selective emitter methods are identified to date. Current industrial monocrystalline Cz Si solar cells based on screen-printing technology for contact formation and homogeneous emitter have an efficiency potential of around 18.4%. Limitations at the rear side by the fully covering Al-BSF can be changed by selective emitter designs allowing a decoupling and separate optimization of the metallised and non-metallised areas. Several selective emitter concepts that are already in industrial mass production or close to it are presented, and their specialties and status concerning cell performance are demonstrated. Key issues that are considered here are the cost-effectiveness, added complexity, additional benefits, reliability and efficiency potential of each selective emitter tech- niques.

A New Approach to Select Doubled Haploid Rice Lines under Salinity Stress Using Indirect Selection Index

This study determined the indirect selection index of doubled haploid(DH)rice using a multivariate analysis approach to select lines adaptive to salinity stress,comprising three experiments.The first experiment involved the selection of good agronomic characters in a field experiment conducted at an experimental station in Bogor,Indonesia.The second experiment involved salinity tolerance screening through hydroponic cultures using 0 and 120 mmol/L NaCl,conducted at a greenhouse in Bogor.The third experiment involved the validation of the indirect adaptability selection index(IASI)through a field experiment in Sukra(saline area).Field experiments followed a randomized complete block design(RCBD),whereas an RCBD nested factorial design was used for the greenhouse experiment.The first and second experiments used 56 DH lines and four check varieties with three replications.In the second experiment,Pokkali and IR29 varieties were also added as tolerant and sensitive checks of salinity,respectively.The third experiment used 28 selected DH lines,Inpari 29 and one sensitive DH line.The good agronomic index(GAI)was 0.465 yield+0.433 number of productive tillers+0.31 number of filled grains.This generated 24 DH rice lines with good agronomic traits.The salinity tolerance index(SaTI)was developed through the average of standardized salinity tolerance score and salinity selection index based on discriminant analysis.This generated 34 DH rice lines with good salinity stress tolerance.The IASI(IASI=GAI–SaTI)selected 28 DH rice lines adaptive to salinity stress and it was considered effective by Sukra validation.

Selective Area Growth of GaAs in V-Grooved Trenches on Si(001) Substrates by Aspect-Ratio Trapping

A high quality of GaAs crystal growth in nanoscale V-shape trenches on Si（O01） substrates is achieved by using the aspect-ratio trapping method. GaAs thin films are deposited via metal-organic chemical vapor deposition by using a two-step growth process. Threading disJocations arising from lattice mismatch are trapped by laterally confining sidewalls, and antiphase domains boundaries are completely restricted by V-groove trenches with Si { 111} facets. Material quality is confirmed by scanning electron microscopy （SEM）, transmission electron microscopy （TEM） and high resolution X-ray diffraction. Low temperature photoluminescence （PL） measurement is used to analyze the thermal strain relaxation in GaAs layers. This approach shows great promise for the realization of high mobility devices or optoelectronie integrated circuits on Si substrates.

Variable Selection of Partially Linear Single-index Models

In this article, we study the variable selection of partially linear single-index model(PLSIM). Based on the minimized average variance estimation, the variable selection of PLSIM is done by minimizing average variance with adaptive l1 penalty. Implementation algorithm is given. Under some regular conditions, we demonstrate the oracle properties of aLASSO procedure for PLSIM. Simulations are used to investigate the effectiveness of the proposed method for variable selection of PLSIM.

学术评价中TOPSIS方法系统误差产生机制研究

[目的/意义]TOPSIS评价方法作为一种非常重要的评价手段在学术评价中得到广泛的应用,但其系统误差问题一直没有得到关注。[方法/过程]文章将误差理论引入TOPSIS指标体系评价中,在理论分析的基础上,对TOPSIS系统误差的产生机制、检验方法、改进措施进行了深度分析,并以优秀环境科学技术期刊为例进行了相关说明。[结果/结论]研究发现,TOPSIS评价方法系统误差的产生因素是多方面的,包括评价指标选取、TOPSIS方法自身问题、标准化方法选择、权重设置、结果公布等环节;应综合采取措施以降低TOPSIS学术评价的系统误差;实际权重合理性是TOPSIS评价方法系统误差的重要检验方法,系统误差较大的情况要慎重选用该评价方法。

Automatic Variable Selection for Single-Index Random Effects Models with Longitudinal Data

We consider the problem of variable selection for the single-index random effects models with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold. The proposed method shares some of the desired features of existing variable selection methods: the resulting estimator enjoys the oracle property;the proposed procedure avoids the convex optimization problem and is flexible and easy to implement. Moreover, we use the penalized weighted deviance criterion for a data-driven choice of the tuning parameters. Simulation studies are carried out to assess the performance of our method, and a real dataset is analyzed for further illustration.

Combined Selection Index for New Yorkshire Dam Line with High Prolificacy

The combined selection index used in the breeding of new Yorkshire dam line with high prolificacy according to breeding objects was formulated as /：2.272E- BVNB-0.056EBVDAYS. After 5 generations breeding, the two main selected traits such as total number of born and age at 100 kg weight was 12.17 piglets/litter and 165.18 d, respectively. The genetic improvements per generates was 0.156 and -2.198, respec- tively. The breeding objects of the new Yorkshire dam line with high prolificacy were basically reached. It indicated that the methods and index could be used in pig breeding.

Use of Selection Indices Based on Multivariate Analysis for Improving Grain Yield in Rice

In order to study selection indices for improving rice grain yield, a cross was made between an Iranian traditional rice (Oryza sativa L.) variety, Tarommahalli and an improved indica rice variety, Khazar in 2006. The traits of the parents (30 plants), F1 (30 plants) and F2 generations (492 individuals) were evaluated at the Rice Research Institute of Iran (RRII) during 2007. Heritabilities of the number of panicles per plant, plant height, days to heading and panicle exsertion were greater than that of grain yield. The selection indices were developed using the results of multivariate analysis. To evaluate selection strategies to maximize grain yield, 14 selection indices were calculated based on two methods (optimum and base) and combinations of 12 traits with various economic weights. Results of selection indices showed that selection for grain weight, number of panicles per plant and panicle length by using their phenotypic and/or genotypic direct effects (path coefficient) as economic weights should serve as an effective selection criterion for using either the optimum or base index.

An Embedded Feature Selection Method for Imbalanced Data Classification

Imbalanced data is one type of datasets that are frequently found in real-world applications, e.g., fraud detection and cancer diagnosis. For this type of datasets, improving the accuracy to identify their minority class is a critically important issue.Feature selection is one method to address this issue. An effective feature selection method can choose a subset of features that favor in the accurate determination of the minority class. A decision tree is a classifier that can be built up by using different splitting criteria. Its advantage is the ease of detecting which feature is used as a splitting node. Thus, it is possible to use a decision tree splitting criterion as a feature selection method. In this paper, an embedded feature selection method using our proposed weighted Gini index(WGI) is proposed. Its comparison results with Chi2, F-statistic and Gini index feature selection methods show that F-statistic and Chi2 reach the best performance when only a few features are selected. As the number of selected features increases, our proposed method has the highest probability of achieving the best performance. The area under a receiver operating characteristic curve(ROC AUC) and F-measure are used as evaluation criteria. Experimental results with two datasets show that ROC AUC performance can be high, even if only a few features are selected and used, and only changes slightly as more and more features are selected. However, the performance of Fmeasure achieves excellent performance only if 20% or more of features are chosen. The results are helpful for practitioners to select a proper feature selection method when facing a practical problem.

Development of New Generation Catalysts for Selective Hydrodesulfurization of FCC Naphtha

The influence of active metal components of catalyst, additives and catalyst preparation method on the reactivity of catalyst for selective hydrodesulfurization (HDS) of FCC naphtha was investigated, and the RSDS-21 catalyst with high HDS performance and the RSDS-22 catalyst with high selectivity were developed by RIPP. The composite loading of a new series of catalysts for selective HDS of FCC gasoline has demonstrated excellent desulfurization activity and selectivity and can under conventional hydrotreating conditions manufacture clean gasoline product meeting the national IV emission standard and the Euro V emission standard with less loss in antiknock index. The finalized new series of FCC catalysts upon being adopted for selective HDS of FCC naphtha have good adaptability to different feedstocks along with good stability.

Forecasting S&P 500 Stock Index Using Statistical Learning Models

Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced by other important financial indexes across the world such as commodity price and financial technical indicators. This paper systematically investigated four supervised learning models, including Logistic Regression, Gaussian Discriminant Analysis (GDA), Naive Bayes and Support Vector Machine (SVM) in the forecast of S&P 500 index. After several experiments of optimization in features and models, especially the SVM kernel selection and feature selection for different models, this paper concludes that a SVM model with a Radial Basis Function (RBF) kernel can achieve an accuracy rate of 62.51% for the future market trend of the S&P 500 index.

Phase selection of ternary intermetallic compounds during solidification of high zinc magnesium alloy

The phase selection of ternary intermetallic compound τphase (Mg32(Al, Zn)49 ) and φ phase (Al2Mg5Zn2) in high zinc magnesium alloys was studied by using scanning electron microscope, X-ray diffractometer and differential scanning calorimeter, etc. The results indicate that, when adding element Si in Mg-8Zn-4Al-0.3Mn (ZA84) alloy, φ phase is promoted, whereas τ phase is inhibited. The Chinese script-type Mg2Si and matrix microstructure are greatly refined, the formation of τ phase is facilitated and φ phase is restrained when modifier Al-AlP master alloy is added in ZA84 alloy containing Si. The kinetics study of phase selection indicates that there is a critical degree of undercooling of the melt. If the undercooling exceeds the critical value, τ phase preferentially forms while φ phase is restrained; otherwise, φ phase preferentially forms while τ phase is restrained.

Study and Design of a DC/AC Energy Converter for PV System Connected to the Grid Using Harmonic Selected Eliminated (HSE) Approach

Nowadays, distributing network-connected photovoltaic (PV) systems are expanded by merging a PV system and a Direct Current (DC)/Alternating Current (AC) energy converter. DC/AC conversion of PV energy is in great demand for AC applications. The supply of electrical machines and transfer energy to the distribution network is a typical case. In this work, we study and design a DC/AC energy converter using harmonic selective eliminated (HSE) method. To this end, we have combined two power stages connected in derivation. Each power stage is constituted of transistors and transformers. The connection by switching of the two rectangular waves, delivered by each of the stages, makes it possible to create a quasi-sinusoidal output voltage of the inverter. Mathematical equations based on the current-voltage characteristics of the inverter have been developed. The simulation model was validated using experimental data from a 25.2 kWp grid-coupled (PV) system, connected to Gridfit type inverters. The data were exported and implemented in programming software. A good agreement was observed and this shows all the robustness and the technical performances of the energy converter device. It emerges from this analysis that the inverter output voltage and the phase angle thus simulated are very important to control in order to orientate the transfer of the power flow from the continuous cell to cell to the alternating part. Simulated and field-testing results also show that increases in the value of the modulation factor (m) for low power output are highly significant. This study is an important tool for DC/AC inverter designers during initial planning stages. A short presentation of the design model of the inverter has been proposed in this article.

STUDY ON THE HALF-SIB FAMILY SELECTION FOR THE SUPERIOR TREE OF SCOTS PINE

Investigation and rescarches are carricd out in MaocrshanForcst Farm attached to Northeast Forcstry University in 1988. Comparedwith the contrast, 29 superior familics and 21 inferior families areselected from 112 families of half sib and open pollination of seven-year old scots pine stands by using multicharacters correlations analysis and variance analysis (ANOVA) as well as principal component index (PCI) selection. This index selection which collects multicharacters information has more advantage than monocharacter selection. It is very important to select fine famiIies for buildingthe first generation seed orchard and changing from trial stand toseeding orchard.