Combining ability and gene action studies for yield and fibre traits in Gossypium arboreum using Griffings numerical and Haymans graphical approach

Background For the purpose of utilising hybrid vigour to produce possible hybrids with a suitable level of stability,the knowledge of gene activity and combining ability is a crucial prerequisite before choosing desirable parents.The present study was carried out with six parents crossed in full diallel fashion and generated 30 F1 hybrids.These hybrids were evaluated in two replications in Randomized Block Design at Department of Cotton,TNAU for combining ability and gene action.Diallel analysis was carried out according to Griffing’s method-I(parents + F_(1) + reciprocals) and model-I and Hayman’s graphical approach by using INDOSTAT software.Results Analysis of variance for combining ability indicated that mean square values of GCA,SCA and reciprocals were highly significant for all the traits except for the uniformity index.RG763 and K12 showed highly positively significant GCA effects for most of the yield traits while PA838 and K12 for fibre quality traits,so they were found as best general combiners.PAIG379 × K12 and PDB29 × K12 for yield traits,and PDB29 × PA838,RG763 × PA838,and CNA1007 × RG763 cross combinations for fibre quality traits could be recommended for future breeding programms.Conclusion The results of both Griffing’s and Hayman’s approaches showed that non-additive gene action predominates as SCA variance was bigger than GCA variance,so heterosis breeding is thought to be a more fruitful option for enhancing GCA of many traits.

Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

Combining ability of Egyptian cotton(Gossypium barbadense L.)reveals genetic potential for improved yield and fiber quality

Background As the most widely cultivated fiber crop,cotton production depends on hybridization to unlock the yield potential of current varieties.A deep understanding of genetic dissection is crucial for the cultivation of enhanced hybrid plants with desired traits,such as high yield and fine fiber quality.In this study,the general combining ability(GCA)and specific combining ability(SCA)of yield and fiber quality of nine cotton parents(six lines and three testers)and eighteen F1 crosses produced using a line×tester mating design were analyzed.Results The results revealed significant effects of genotypes,parents,crosses,and interactions between parents and crosses for most of the studied traits.Moreover,the effects of both additive and non-additive gene actions played a notably significant role in the inheritance of most of the yield and fiber quality attributes.The F1 hybrids of(Giza 90×Aust)×Giza 86,Uzbekistan 1×Giza 97,and Giza 96×Giza 97 demonstrated superior performance due to their favorable integration of high yield attributes and premium fiber quality characteristics.Path analysis revealed that lint yield has the highest positive direct effect on seed cotton yield,while lint percentage showed the highest negative direct effect on seed cotton yield.Principal component analysis identified specific parents and hybrids associated with higher cotton yield,fiber quality,and other agronomic traits.Conclusion This study provides insights into identifying potential single-and three-way cross hybrids with superior cotton yield and fiber quality characteristics,laying a foundation for future research on improving fiber quality in cotton.

Impact of Earthquake Action on the Design and Sizing of Jointed Masonry Structures in South Kivu, DRC

This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in the province, namely the non-consideration of seismic action in the study of structures by both professionals and researchers. The main objective of the study is to show the importance of dynamic analysis of structures in South Kivu. It adopts a meta-analytical approach referring to previous researches on South Kivu and proposes an efficient and optimal method. To arrive at the results, we use Eurocode 7 and 8. In addition, we conducted static analysis using the Coulomb method and dynamic analysis using the Mononobe-Okabe method and compared the results. At Nyabibwe, the results showed that we have a deviation of 24.47% for slip stability, 12.038% for overturning stability and 9.677% for stability against punching through a weight wall.

Silhouettes Based Human Action Recognition in Video via Procrustes Analysis and Fisher Vector Coding

This paper proposes a framework for human action recognition based on procrustes analysis and Fisher vector coding(FVC).Firstly,we applied a pose feature extracted from silhouette image by employing Procrustes analysis and local preserving projection(LPP).Secondly,the extracted feature can preserve the discriminative shape information and local manifold structure of human pose and is invariant to translation,rotation and scaling.Finally,after the pose feature was extracted,a recognition framework based on FVC and multi-class supporting vector machine was employed to classify the human action.Experimental results on benchmarks demonstrate the effectiveness of the proposed method.

Action time effect of lime on its depressive ability for pyrite

Two sample groups of bulk concentrates consisting mainly of pyrite andchalcopyrite from Daye and Chenghchao Mines in Hubei Province of China were used to investigate theeffect of the action time of lime on its depressive ability for pyrite. The experimental resultsconducted with different samples and collectors showed that the action time between lime and pyritemarkedly influences the depressive ability of lime. The depressive ability of lime increased withthe action time increasing. It was also proved that the depressive results obtained at a large limedosage after a shorter action time are similar to those obtained at a small lime dosage after alonger action time. The increase of depressive ability of lime after a longer action time is becausethat there are different mechanisms in different action time. The composition on the surface ofpyrite acted for different time with lime was studied by using ESCA (Electron Spectroscopic ChemicalAnalysis). The results showed that iron hydroxide and calcium sulphate formed on the pyrite surfaceat the presence of lime in the pulp but the amounts of iron hydroxide and calcium sulphate weredifferent at different action time. At the beginning action time the compound formed on the pyritesurface was mainly calcium sulphate and almost no iron hydroxide formed; but with the action timeincreasing, iron hydroxide formed. The longer the action time, the more iron hydroxide and the lesscalcium sulphate formed. It was considered that the stronger depressive ability of lime after alonger action time is because more iron hydroxide forms on the pyrite surface.

Heterosis, Combining Ability and Gene Action for Yield in Bottle Gourd

The experiment was conducted at the experimental field of Olericulture Division, Horticulture Research Centre (HRC), Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh during the winter season of 2018-2019 to study the genetic architecture of yield in a seven parent half diallel cross of bottle gourd. The values of mean square for GCA (general combining ability) and SCA (specific combining ability) were highly significant which suggested the presence of both additive and non-additive genetic variance in the population. But the higher magnitude of GCA compared to SCA indicated predominance of additive genetic variance. In most of the cases, the cross between poor and poor parents showed positive SCA effect for fruit yield, which indicated the higher yield. The estimates of significant positive better parent heterosis ranged from 6.27 to 49.72 percent. Analysis of genetic components of variation suggested that additive components were more important in the inheritance of fruit yield. This character was observed being controlled by two to three pairs of genes or groups of genes. Narrow sense heritability was 23 percent indicating probability of selection in generations. The graphical analysis also indicated wide genetic diversity among the parents.

Seismic elastic-plastic time history analysis and reliability study of quayside container crane

Quayside container crane is a kind of huge dimension steel structure,which is the major equipment used for handling container at modern ports.With the aim to validate the safety and reliability of the crane under seismic loads,besides conventional analysis,elastic-plastic time history analysis under rare seismic intensity is carried out.An ideal finite element（FEM） elastic-plastic mechanical model of the quayside container crane is presented by using ANSYS codes.Furthermore,according to elastic-plastic time history analysis theory,deformation,stress and damage pattern of the structure under rare seismic intensity are investigated.Based on the above analysis,the established reliability model according to the reliability theory,together with seismic reliability analysis based on Monte-Carlo simulation is applied to practical analysis.The results show that the overall structure of the quayside container crane is generally unstable under rare seismic intensity,and the structure needs to be reinforced.

Genetic variability predicting breeding potential of upland cotton(Gossypium hirsutum L.)for high temperature tolerance

Background High temperature stress at peak flowering stage of cotton is a major hindrance for crop potential.This study aimed to increase genetic divergence regarding heat tolerance in newly developed cultivars and hybrids.Fifty cotton genotypes and 40 F1(hybrids)were tested under field conditions following the treatments,viz.,high temperature stress and control at peak flowering stage in August and October under April and June sowing,respectively.Results The mean squares revealed significant differences among genotypes,treatments,genotype×treatment for relative cell injury,chlorophyll contents,canopy temperature,boll retention and seed cotton yield per plant.The genetic diversity among 50 genotypes was analyzed through cluster analysis and heat susceptibility index(HSI).The heat tolerant genotypes including FH-Noor,NIAB-545,FH-466,FH-Lalazar,FH-458,NIAB-878,IR-NIBGE-8,Weal-AGShahkar,and heat sensitive,i.e.,CIM-602,Silky-3,FH-326,SLH-12 and FH-442 were hybridized in line×tester fashion to produce F1 populations.The breeding materials’populations(40 F1)revealed higher specific combining ability variances along with dominance variances,decided the non-additive type gene action for all the traits.The best general combining ability effects for most of the traits were displayed by the lines,i.e.,FH-Lalazar,NIAB-878 along with testers FH-326 and Silky-3.Specific combining ability effects and better-parent heterosis were showed by the crosses,viz.,FH-Lalazar×Silky-3,FH-Lalazar×FH-326,NIAB-878×Silky-3,and NIAB-878×FH-326 for seed cotton yield and yield contributing traits under high temperature stress.Conclusion Heterosis breeding should be carried out in the presence of non-additive type gene action for all the studied traits.The best combiner parents with better-parent heterosis may be used in crossing program to develop high yielding cultivars,and hybrids for high temperature stress tolerance.

An overview of proven Climate Change Vulnerability Assessment tools for forests and forest-dependent communities across the globe：a literature analysis

Climate Change Vulnerability Assessment（VA） tools for forest ecosystems and forest-dependent communities are important for making decisions and understanding the impact of climate change on both social and natural systems.However,the tools are poorly coordinated,making it difficult for policymakers to carry out VAs properly.The aim of this study was to analyze VA literature worldwide to find representative case studies in terms of methods and tools applied and which have been successful in performing VAs on forests and forest-dependent communities.All successful VA studies analyzed had common characteristics such as significant funding,data availability and technical capacity.An additional characteristic was the development of an integrated approach that considered the vulnerability of both ecosystems and communities by combining qualitative and quantitative methods.Community members and relevant stakeholders were significantly involved in a participatory process that concluded with the identification of adaptation measures.The case studies also revealed how policymakers need to choose suitable methods and tools to undertake efficient assessment of vulnerabilities.They need to consider several aspects of the VA process such as subject matter,availability of resources,time and scale.

Deep Learning-Based Action Classification Using One-Shot Object Detection

Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodies in an image in real-time and simultaneously classifying their actions.There are various related studies on the real-time classification of actions in an image.However,existing deep learning-based action classification models have prolonged response speeds,so there is a limit to real-time analysis.In addition,it has low accuracy of action of each object ifmultiple objects appear in the image.Also,it needs to be improved since it has a memory overhead in processing image data.Deep learning-based action classification using one-shot object detection is proposed to overcome the limitations of multiframe-based analysis technology.The proposed method uses a one-shot object detection model and a multi-object tracking algorithm to detect and track multiple objects in the image.Then,a deep learning-based pattern classification model is used to classify the body action of the object in the image by reducing the data for each object to an action vector.Compared to the existing studies,the constructed model shows higher accuracy of 74.95%,and in terms of speed,it offered better performance than the current studies at 0.234 s per frame.The proposed model makes it possible to classify some actions only through action vector learning without additional image learning because of the vector learning feature of the posterior neural network.Therefore,it is expected to contribute significantly to commercializing realistic streaming data analysis technologies,such as CCTV.

Reliability Analysis of Unmanned Aerial Vehicles Flight Control System Based on Reliability Analysis Technologies

The unmanned aerial vehicles( UAV) has been becoming more and more important in the aviation industry.Despite the superior performance and advanced technology,major accident of UAV happens frequently due to the impact of their systems,long distance of remote control and skill of manipulator technology.According to the application of engineering application,failure mode effects and criticality analysis( FMECA),failure reporting analysis and corrective action comprehensive analysis systems( FRACAS)and fault tree analysis( FTA)( 3 F) were combined.And also a set of user-friendly,more time,more efficient and accurate reliability analysis system were explored.

Static and Dynamic Analysis of Lasing Action from Single and Coupled Photonic Crystal Nanocavity Lasers

The single and coupled photonic crystal nanocavity lasers are fabricated in the InGaAsP material system and their static and dynamic features are compared. The coupled-cavity lasers show a larger lasing e^ciency and generate an output power higher than the single-cavity lasers, results that are consistent with the theoretical results obtained by rate equations. In dynamic regime, the single-cavity lasers produce pulses as short as 113 ps, while the coupled-cavity lasers show a significantly longer lasing duration. These results indicate that the photonic crystal laser is a promising candidate for the light source in high-speed photonic integrated circuit.

An Analysis of Cultivation of College Students'Interpersonal Ability

In modern society,good communicative ability is very important;it plays an important part in communication.But as college students,who enter into the society newly,their interpersonal range is expanded constantly;to a certain extent,there are some communication disorders which many students'worries in life and study are relevant to.So this text will analyze the poor communicative ability from internal and external factors.And then give several suggestions about how to cultivate the college students'communicative ability.

An Empirical Study for Building a Common Reference Scale of Cando statements of Syntactical Analysis Ability

This study conducts an empirical study of building a common reference scale of Can-do statements of Syntactical AnalysisAbility for NMEE.Studying on language proficiency scale has been done a lot at abroad,but we haven't had a unified English languageproficiency scale in China until now.Without a common reference standard,this leads to many descriptive problems:such as differentdescriptive indexes,vague definition,unclear level and so on.As an important part of English comprehensive ability,syntactical analy-sis ability processes a large proportion of NMEE.Theoretically Based on Bachman's(Communicative Language Ability,CLA) and Dengjie's Discourse Information Cognitive Processing Ability,this study finds that syntactical analysis ability can be described from 38 per-spectives.

An Assessment Scale for Evaluating the Experimental Design Ability of Elementary Science Teachers Based on Primary Trait Analysis

In this study,an assessment scale for evaluating the experimental design ability of elementary science teachers was constructed based on primary trait analysis.This assessment scale contains three first-level indexes and eleven second-level indexes.The corresponding weights of indexes were determined by the objective weighting method.The scores of all the descriptions of the indexes were also assigned.After a trial test,this assessment scale was verified to be reliable and valid for evaluating the experimental design ability of elementary science teachers.

SlowFast Based Real-Time Human Motion Recognition with Action Localization

Artificial intelligence is increasingly being applied in the field of video analysis,particularly in the area of public safety where video surveillance equipment such as closed-circuit television(CCTV)is used and automated analysis of video information is required.However,various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging.Video analysis technology applies object classification,detection,and relationship analysis to continuous 2D frame data,and the various meanings within the video are thus analyzed based on the extracted basic data.Motion recognition is key in this analysis.Motion recognition is a challenging field that analyzes human body movements,requiring the interpretation of complex movements of human joints and the relationships between various objects.The deep learning-based human skeleton detection algorithm is a representative motion recognition algorithm.Recently,motion analysis models such as the SlowFast network algorithm,have also been developed with excellent performance.However,these models do not operate properly in most wide-angle video environments outdoors,displaying low response speed,as expected from motion classification extraction in environments associated with high-resolution images.The proposed method achieves high level of extraction and accuracy by improving SlowFast’s input data preprocessing and data structure methods.The input data are preprocessed through object tracking and background removal using YOLO and DeepSORT.A higher performance than that of a single model is achieved by improving the existing SlowFast’s data structure into a frame unit structure.Based on the confusion matrix,accuracies of 70.16%and 70.74%were obtained for the existing SlowFast and proposed model,respectively,indicating a 0.58%increase in accuracy.Comparing detection,based on behavioral classification,the existing SlowFast detected 2,341,164 cases,whereas the proposed model detected 3,119,323 cases,which is an increase of 33.23%.

Dependability Analysis for Fault-Tolerant Computer Systems Using Dynamic Fault Graphs

Dependability analysis is an important step in designing and analyzing safety computer systems and protection systems.Introducing multi-processor and virtual machine increases the system faults' complexity,diversity and dynamic,in particular for software-induced failures,with an impact on the overall dependability.Moreover,it is very different for safety system to operate successfully at any active phase,since there is a huge difference in failure rate between hardware-induced and softwareinduced failures.To handle these difficulties and achieve accurate dependability evaluation,consistently reflecting the construct it measures,a new formalism derived from dynamic fault graphs(DFG) is developed in this paper.DFG exploits the concept of system event as fault state sequences to represent dynamic behaviors,which allows us to execute probabilistic measures at each timestamp when change occurs.The approach automatically combines the reliability analysis with the system dynamics.In this paper,we describe how to use the proposed methodology drives to the overall system dependability analysis through the phases of modeling,structural discovery and probability analysis,which is also discussed using an example of a virtual computing system.