Selection and application of four QTLs for grain protein content in modern wheat cultivars

The grain protein content(GPC)is the key parameter for wheat grain nutritional quality.This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments,and identified four previously reported GPC QTLs.An analysis of 87 landraces and 259 modern cultivars revealed the loss of superior GPC haplotypes,especially in Chinese cultivars.These haplotypes were preferentially adopted in different agroecological zones and had broad effects on wheat yield and agronomic traits.Most GPC QTLs did not significantly reduce yield,suggesting that high GPC can be achieved without a yield penalty.The results of this study provide a reference for future GPC breeding in wheat using the four identified QTLs.

Optimal urban EV charging station site selection and capacity determination considering comprehensive benefits of vehicle-station-grid

This paper presents an optimization model for the location and capacity of electric vehicle(EV)charging stations.The model takes the multiple factors of the“vehicle-station-grid”system into account.Then,ArcScene is used to couple the road and power grid models and ensure that the coupling system is strictly under the goal of minimizing the total social cost,which includes the operator cost,user charging cost,and power grid loss.An immune particle swarm optimization algorithm(IPSOA)is proposed in this paper to obtain the optimal coupling strategy.The simulation results show that the algorithm has good convergence and performs well in solving multi-modal problems.It also balances the interests of users,operators,and the power grid.Compared with other schemes,the grid loss cost is reduced by 11.1%and 17.8%,and the total social cost decreases by 9.96%and 3.22%.

Trade credit contracting in a risk-averse supply chain under adverse selection and moral hazard

Trade credit,as an effective tool for integrating and coordinating material,information,and financial flows in supply chain management,is becoming increasingly widespread.We explore how a manufacturer can design optimal trade credit contracts when a risk-averse retailer hides its sales cost information(adverse selection)and selling effort level(moral hazard).We develop incentive models for a risk-averse supply chain when adverse selection and moral hazard coexist,which are then compared with the results under single information asymmetry(moral hazard).Moreover,we analyze the effects of private information and risk-aversion coefficient on contract parameters,selling effort level and the profit or utility of the supply chain.The study shows that when the degree of retailer’s risk aversion is within a certain range,reasonable trade credit contracts designed by the manufacturer can effectively induce the retailer to report its real sales cost and encourage it to exert appropriate effort.Furthermore,we find that the optimal trade credit period,optimal transfer payment,and retailer’s optimal sales effort level under dual information asymmetry are less than those under single information asymmetry.Numerical analysis are conducted to demonstrate the effects of the parameters on decisions and profits.

Enhancing Software Cost Estimation Using Feature Selection and Machine Learning Techniques

Software cost estimation is a crucial aspect of software project management,significantly impacting productivity and planning.This research investigates the impact of various feature selection techniques on software cost estimation accuracy using the CoCoMo NASA dataset,which comprises data from 93 unique software projects with 24 attributes.By applying multiple machine learning algorithms alongside three feature selection methods,this study aims to reduce data redundancy and enhance model accuracy.Our findings reveal that the principal component analysis(PCA)-based feature selection technique achieved the highest performance,underscoring the importance of optimal feature selection in improving software cost estimation accuracy.It is demonstrated that our proposed method outperforms the existing method while achieving the highest precision,accuracy,and recall rates.

Study on Path Selection and Implementation Effect of Counselors in College Students’Career Planning Education

Under the background of a severe job market and fierce talent competition,the career planning education of college students is of great importance.In this study,a combination of quantitative and qualitative research methods was used;500 students in Shenzhen Polytechnic of Information Technology were surveyed by questionnaire,and 40 counselors were interviewed in depth to comprehensively analyze the role and practical effect of counselors in career planning education.The research showed that the role positioning of counselors includes the guide of students’career development,emotional support,and job-hunting strategy,and the specific path selection involves the strengthening of professional knowledge,the construction of interpersonal relationship networks,and personalized counseling.Based on the survey and interview data,this paper constructed a model for enhancing the role of counselors in career planning education and put forward a set of targeted work paths.

Using multi-criteria decision-making and machine learning for football player selection and performance prediction:a systematic review

Evaluating and selecting players to suit football clubs and decision-makers (coaches, managers, technical, and medical staff) is a difficult process from a managerial-financial and sporting perspective. Football is a highly competitive sport where sponsors and fans are attracted by success. The most successful players, based on their characteristics (criteria and sub-criteria), can influence the outcome of a football game at any given time. Consequently, the D-day of selection should employ a more appropriate approach to human resource management. To effectively address this issue, a detailed study and analysis of the available literature are needed to assist practitioners and professionals in making decisions about football player selection and hiring. Peer-reviewed journals were selected for collecting published papers between 2018 and 2023. A total of 66 relevant articles (journal articles, conference articles, book sections, and review articles) were selected for evaluation and analysis. The purpose of the study is to present a systematic literature review (SLR) on how to solve this problem and organize the published research papers that answer our four research questions.

Test selection and optimization for PHM based on failure evolution mechanism model

The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.

On selection and scaling of ground motions for analysis of seismically isolated structures

A broader consensus on the number of ground motions to be used and the method of scaling to be adopted for nonlinear response history analysis （RHA） of structures is yet to be reached. Therefore, in this study, the effects of selection and scaling of ground motions on the response of seismically isolated structures, which are routinely designed using nonlinear RHA, are investigated. For this purpose, isolation systems with a range of properties subjected to bidirectional excitation are considered. Benchmark response of the isolation systems is established using large sets of unscaled ground motions systematically categorized into pulse-like, non-pulse-like, and mixed set of motions. Different subsets of seven to 14 ground motions are selected from these large sets using （a） random selection and （b） selection based on the best match of the shape of the response spectrum of ground motions to the target spectrum. Consequences of weighted scaling （also commonly referred to as amplitude scaling or linear scaling） as well as spectral matching are investigated. The ground motion selection and scaling procedures are evaluated from the viewpoint of their accuracy, efficiency, and consistency in predicting the benchmark response. It is confirmed that seven time histories are sufficient for a reliable prediction of isolation system displacement demands, for all ground motion subsets, selection and scaling procedures, and isolation systems considered. If ground motions are selected based on their best match to the shape of the target response spectrum （which should be preferred over randomly selected motions）, weighted scaling should be used if pulse-like motions are considered, either of weighted scaling or spectral matching can be used if non-pulse-like motions are considered, and an average of responses from weighted-scaled and spectrum-matched ground motions should be used for a mixed set of motions. On the other hand, the importance of randomly selected motions in representing inherent variability of response is recognized and it is found that weighted scaling is more appropriate for such motions.

Selection and modification of ground motion records using Newmark-Hall spectrum as target spectrum for long-period structures

Input ground motions have significant impacts on the uncertainty of structural responses in time-history analysis.In this study,records were selected and scaled for the evaluation of mean structural responses according to the target spectrum.The Newmark-Hall spectrum is closely related to seismic response of short,medium and long-period structures,so it was taken as the target spectrum here.The nonlinear time-history analyses of 9-story and 20-story steel moment-resisting frame structures were carried out as examples.They represent medium and long-period buildings,respectively.Three target spectra with risk of 50%,10%and 2%probabilities for exceedance in 50 years were calculated by the average Newmark-Hall spectrum method for three ground motion sets developed in the SAC Steel Project.The predicted structural mean responses of these Newmark-Hall spectra were compared with those calculated by the average spectral acceleration method for the same record set.It is found that both methods have similar accuracy for estimating the structural mean response.However,the method proposed herein is more effective in reducing the variability of the structural responses.Also,the proposed method is more advantageous for the time-history analysis of long-period structures or structures with more severe nonlinear responses under strong seismic excitations.

Selection and Characterization of a Novel Glyphosate Tolerant Upland Cotton(Gossypium hirsutum L.) Mutant(R1098)

Stepwise selection approach was adopted to obtain glyphosate-tolerant upland cotton mutant(R1098) from the embryogenic calli of Coker 312(Gossypium hirsutum L.).The calli were transferred to selection medium and multi-step selection pressure process was carried out until the

Quantum Path Selection and Isolated-Attosecond-Pulse Generation of H2+ with an Intense Laser Pulse and a Static Field

We theoretically investigate the high-order-harmonic generation from the H2^＋ molecular ion exposed to the combi- nation of an intense trapezoidal laser and a static field. The results show that the harmonic spectrum is obviously extended and the short quantum path is selected to contribute to the spectrum, because the corresponding long path is seriously suppressed. Then the combined Coulomb and laser field potentials and the time-dependent electron wave packet distributions are applied to illustrate the physical mechanism of high-order harmonic gen- eration. Finally, by adjusting the intensity of the static field and superposing a properly selected range of the HHG spectrum, a 90-as isolated attosecond pulse is straightforwardly obtained.

Landscape Plants Selection and Design in the Peony Garden of Xibaipo

Peony is a traditional famous flower in China.With the peony garden of Xibaipo as an example,the landscaping planning of functional divisions,the selection and design of landscaping plants for the peony garden are introduced in this study,then the landscaping plants selection and design principles are summarized.

Selection and Application of Landscape Plants in the Construction of Green Mines in Chengde

Role of landscape plants in mine greening has been gradually acknowledged and its application has been attached more and more importance. Through investigating and analyzing environmental conditions, soil, water quality, weather of mines in Chengde, as well as studying growth habits and rate, acid and alkali resistance, anti-pollution property of landscape plants, specific application of landscape plants in creating green mines are investigated in this study, and relevant statistics are sorted out to summarize functions of landscape plants in the greening of mines as well as selection and application of different plants in different parts of mines, which well demonstrates the progresses achieved by Chengde City in its construction of green mines. Scientific selection and application of landscape plants are emphasized to fully develop their functions and improve the utilization efficiency, the significance of applying landscape plants in the construction of green mines in Chengde is pointed out, and several suggestions are proposed in view of existing problems in the present construction, which will provide scientific support for the selection and application of landscape plants in urban areas, industrial areas, mines or other industrial cities with similar environmental conditions.

Plant Selection and Application of Rain Garden in Southern China

Based on the basic principles of rain garden infrastructure, optimal species for rain facilities such as vegetated buffer strip, vegetated shallow groove, artificial wetland were selected, characteristics, configuration principles and methods were summarized.

Supplier selection and order splitting modeling in the pr esence of supplier capacity and resilience

To solve the problem of a supplier＇s failure to deliver thus impacting supply chain system performance in the supply chain operating process, a model of supplier selection and order splitting in the context of a multiple sourcing setting is proposed. First, by the analysis of the elements of expected total costs of the buyer firm, namely, expected loss costs, resilience effort costs, supplier maintenance costs, and cycle purchase costs, the expected total costs function is obtained. And then, the effects of supplier characters on the supplier selection and order splitting decisionmaking are investigated by numerical examples. The results show that the maximum delivery capacity, the probability of failure to deliver and the resilience parameters are crucial elements in determining which suppliers should be selected and how to do order splitting between suppliers. Finally, current analyses focus only on the expected total costs of the buyer firm but ignore the suppliers＇ costs： thus, it is more interesting to examine the supplier decisions from both parties＇ points of view.

Method for test case selection and execution of web application regression testing

In order to improve the efficiency of regression testing in web application,the control flow graph and the greedy algorithm are adopted.This paper considers a web page as a basic unit and introduces a test case selection method for web application regression testing based on the control flow graph.This method is safe enough to the test case selection.On the base of features of request sequence in web application,the minimization technique and the priority of test cases are taken into consideration in the process of execution of test cases in regression testing for web application.The improved greedy algorithm is also raised resulting in optimization of execution of test cases.The experiments indicate that the number of test cases which need to be retested is reduced,and the efficiency of execution of test cases is also improved.

Selection and Breeding of Drought Resistant,Water-saving and High-yield Wheat Variety Cangmai 028

Cangmai 028 was selected and bred according to the climatic characteristic of the winter wheat in Heilonggang Basin taking 98(083)as the female parent and the Canghe 030 as the male parent by "two-row parallel alternate selection" method.Cangmai 028 has characteristics of high resistance,water-saving,high and stable yield,and rich genetic background.This study elaborated selection and breeding background and methods,characteristics,quality,and yield of Cangmai 028.

China Procurement-Leveraging Supplier Selection and Supplier Management for Success

Successful China pro- curement is the result of a comprehensive set of complex and high-ly-specialized processes. Dis- tilling this down to a ＂magical recipe＂ for success is no simple task, and there are no shortcuts. However, as a useful reference, two fundamental ingredients for procurement success are： the selection of the right suppliers： and the effective management of chosen suppliers to optimize their performance.

Antenna Selection and Power Allocation Design for 5G Massive MIMO Uplink Networks

Massive MIMO is one of the key technologies in future 5G communications which can satisfy the requirement of high speed and large capacity. This paper considers antenna selection and power allocation design to promote energy conservation then provide good quality of service(QoS) for the whole massive MIMO uplink network. Unlike previous related works, hardware impairment, transmission efficiency, and energy consumption at the circuit and antennas are involved in massive MIMO networks. In order to ensure the QoS, we consider the minimum rate constraint for each user and the system, which increases the complexity of power allocation problem for maximizing energy and spectral efficiency in massive MIMO system. To this end, a quantum-inspired social emotional optimization(QSEO) algorithm is proposed to obtain the optimal power control strategy in massive MIMO uplink networks. Simulation results assess the great advantages of QSEO which previous strategies do not have.

Use of genomic selection and breeding simulation in cross prediction for improvement of yield and quality in wheat (Triticum aestivum L.)

In wheat breeding, it is a difficult task to select the most suitable parents for making crosses aimed at the improvement of both grain yield and grain quality. By quantitative genetics theory,the best cross should have high progeny mean and large genetic variance, and ideally yield and quality should be less negatively or positively correlated. Usefulness is built on population mean and genetic variance, which can be used to select the best crosses or populations to achieve the breeding objective. In this study, we first compared five models(RR-BLUP, Bayes A, Bayes B, Bayes ridge regression, and Bayes LASSO) for genomic selection(GS) with respect to prediction of usefulness of a biparental cross and two criteria for parental selection, using simulation. The two parental selection criteria were usefulness and midparent genomic estimated breeding value(GEBV). Marginal differences were observed among GS models. Parental selection with usefulness resulted in higher genetic gain than midparent GEBV. In a population of 57 wheat fixed lines genotyped with 7588 selected markers, usefulness of each biparental cross was calculated to evaluate the cross performance, a key target of breeding programs aimed at developing pure lines. It was observed that progeny mean was a major determinant of usefulness, but the usefulness ratings of quality traits were more influenced by their genetic variances in the progeny population. Near-zero or positive correlations between yield and major quality traits were found in some crosses, although they were negatively correlated in the population of parents. A selection index incorporating yield, extensibility, and maximum resistance was formed as a new trait and its usefulness for selecting the crosses with the best potential to improve yield and quality simultaneously was calculated. It was shown that applying the selection index improved both yield and quality while retaining more genetic variance in the selected progenies than the individual trait selection. It was concluded that combining genomic selection with simulation allows the prediction of cross performance in simulated progenies and thereby identifies candidate parents before crosses are made in the field for pure-line breeding programs.