Application of Multi-factor Comprehensive Appraisal in Maize Breeding

The study was conducted to evaluate 12 traits of 15 hybrid maize culti- vars using multi-factor comprehensive appraisal. The results showed that Xianyu 335, ND8 and ND2 were better than other cultivars in these agronomic traits. Multi- factor comprehensive appraisal with simple computing, comprehensive and reason- able results is suitable to be used for evaluating the performance of hybrid maize cultivars in field.

批判性思维定义中的“Judgment(s)”问题——与晋荣东教授商榷

在批判性思维研究领域,《德尔菲报告》提出的批判性思维定义由于吸收了当代重要批判性思维学者的意见,反映了专家共识,因而具有很大的权威性。该定义引入中国大学批判性思维教科书也有十几年了。晋荣东对该定义中的一个关键词“judgment(s)”的中译——“判断”,提出了异议并建议将其改译为“判断力”。但是,仔细考察德尔菲研究项目主持人费西万对该定义的阐述就会发现,“判断力”的译法不能成立。李普曼关于批判性思维与判断的论述也表明,批判性思维定义中的judgment(s)是“判断”而非“判断力”。

Value Choice and System Enlightenment of the U.S.Business Judgment Rule

Through analyzing theories and legislative cases in respect of Business Judgment Rule in American justice systems with the com parison method,this article reveals that the business judgment system is conducive to the protection of rights and interests of the directors in decision making,and enables the court to avoid the substantive review on business management in an effective manner;at the same time,in view of the blanks and deficiencies in the legislation of China in the "Company Law" and other relevant laws,it is recommended that the Business Judgment Rule be introduced into China and the legislation in respect of director accountability be strengthened,while the direc tors fiduciary duty and other supporting systems be improved,with the reference of the U.S.practice,to clarify the legal boundary between rights and responsibilities of directors.

Symmetry and tendency judgment of Ms≥8. 0 strong earthquakes in Chile

The Ms ≥ 8.0 strong earthquakes occurring in Chile since 1800 were analyzed using the ternary, quaternary, and quinary commensurability methods and the butterfly structure diagram, and it was believed that the earthquake signal in Chile in 2014 is relatively strong, a large earthquake is likely to occur in Chile in 2014. An analysis of spatial epicenter migrations showed that the longitudinal and latitudinal epicenter migra- tions have symmetry and synchronism, and there were five obvious northward migrations and four southward migrations. The symmetry axis of the longitudinal migrations is at about 71.7°W and that of the latitudinal mi- grations is at about 30°S; these spatial symmetry axes are located at the subduction zone on the western margin of South America, where two major plates （the Nazca Plate and the South American Plate） converge.

Ranking method for the reciprocal judgment matrix based on the unascertained three-valued judgments

The ranking problem is studied when the pairwise comparisons values are unoertain in the analytic hierarchy process （AHP）. The method of constructing the judgment matrix is presented when the pairwise comparisons values are denoted by the unascertained three-valued reciprocal scales. By turning the reciprocal judgment matrix into attribute judgment matrix, the method to check the consistency of the pairwise comparisons judgment matrix and the calculation method of weighting coefficients are given. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.

The multi-factor recombination and processes superimposition model for hydrocarbon accumulation:application to the Silurian in the Tarim Basin

The multi-factor recombination and processes superimposition model for hydrocarbon accumulation is put forward in view of the hydrocarbon geological characteristics of multiple episodes of structural evolution, multiple sets of source-reservoir-seal assemblage, multiple cycles of hydrocarbon accumulation and multiple episodes of readjustment and reconstruction in the complex superimposed basins in China. It is a system including theories and methods that can help to predict favorable exploration regions. According to this model, the basic discipline for hydrocarbon generation, evolution and distribution in the superimposed basins can be summarized in multi-factor recombination, processes superimposition, multiple stages of oil filling and latest stage preservation. With the Silurian of the Tarim basin as an example, based on the reconstruction of the evolution history of the four factors （paleo-anticline, source rock, regional cap rock and kinematic equilibrium belt） controlling hydrocarbon accumulation, this model was adopted to predict favorable hydrocarbon accumulation areas and favorable exploration regions following structural destruction in three stages of oil filling, to provide guidance for further exploration ofoil and gas in the Silurian of the Tarim basin.

Method for multiple attribute decision making based on incomplete linguistic judgment matrix

With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision problem. The incomplete linguistic judgment matrix is transformed into incomplete fuzzy judgment matrix and an optimization model is developed on the basis of incomplete fuzzy judgment matrix provided by the decision maker and the decision matrix to determine attribute weights by Lagrange multiplier method. Then the overall values of all alternatives are calculated to rank them. A numerical example is given to illustrate the feasibility and practicality of the proposed method.

Multi-factor analysis of initial poor graft function after orthotopic liver transplantation

BACKGROUND: In the early period of orthotopic liver transplantation (OLT), initial poor graft function (IPGF) is one of the complications which leads to primary graft non-function (PGNF) in serious cases. This study set out to establish the clinical risk factors resulting in IPGF after OLT. METHODS: Eighty cases of OLT were analyzed. The IPGF group consisted of patients with alanine aminotransferase (ALT) and/or aspartate aminotransferase (AST) above 1500 IU/L within 72 hours after OLT, while those in the non-IPGF group had values below 1500 IU/L. Recipient-associated factors before OLT analyzed were age, sex, primary liver disease and Child-Pugh classification; factors analyzed within the peri-operative period were non-heart beating time (NHBT), cold ischemia time (CIT), rewarming ischemic time (RWIT), liver biopsy at the end of cold ischemia; and factors analyzed within 72 hours after OLT were ALT and/or AST values. A logistic regression model was applied to filter the possible factors resulting in IPGF. RESULTS: Donor NHBT, CIT and RWIT were significantly longer in the IPGF group than in the non-IPGF group; in the logistic regression model, NHBT was the risk factor leading to IPGF (P < 0.05), while CIT and RWIT were possible risk factors. In one case in the IPGF group, PGNF appeared with moderate hepatic steatosis. CONCLUSIONS: Longer NHBT is an important risk factor leading to IPGF, while serious steatosis in the donor liver, CIT and RWIT are potential risk factors.

Risk Judgment of and Suggestions for Shantytown Renovation Based on the Public-Private Partnership (PPP) Model

Shantytown renovation is a livelihood project initiated by the Chinese government to reconstruct urban dilapidated housing and improve housing conditions for families in need. Since the funding problem is a major obstacle in the course of shantytown renovation, the government actively advocates the adoption of the public-private partnership(PPP) model. In view of the particularity of shantytown renovation and the complexity of the PPP model operation procedures, it is considered that the risk management of shantytown renovation based on the PPP model. This paper identified and judged the main risks of the PPP project in shantytown renovation, and put forward corresponding suggestions for the risk management of the PPP project in shantytown renovation, hoping to provide a reference for government decision-making.

Apple Grade Judgment Based on the Neural Network

A processing method on the basis of the technology of computer visual and digital image wasintroduced. The improved LVQ (learning vector quantization) neural network algorithm appliedin the process to identify the grade of apples was proved effective in experiment.

Cellular Automata-based Chloride Ion Diffusion Simulation of Concrete Bridges under Multi-factor Coupling Actions

In order to accurately simulate the diffusion of chloride ion in the existing concrete bridge and acquire the precise chloride ion concentration at given time, a cellular automata （CA）-based model is proposed. The process of chloride ion diffusion is analyzed by the CA-based method and a nonlinear solution of the Fick＇s second law is obtained. Considering the impact of various factors such as stress states, temporal and spatial variability of diffusion parameters and water-cement ratio on the process of chloride ion diffusion, the model of chloride ion diffusion under multi-factor coupling actions is presented. A chloride ion penetrating experiment reported in the literature is used to prove the effectiveness and reasonability of the present method, and a T-type beam is taken as an illustrative example to analyze the process of chloride ion diffusion in practical application. The results indicate that CA-based method can simulate the diffusion of chloride ion in the concrete structures with acceptable precision.

Gender Differences in Neural Mechanisms Underlying Moral Judgment of Disgust: A Functional MRI Study

Much recent research has sought to uncover the gender difference in neural mechanism of moral judgment;however, very few researches study the neural gender differences in a specific area of moral judgment. The aim of this functional magnetic resonance imaging (fMRI) study was to examine possible gender difference in neural response to (sexual) disgusting pictures versus neutral pictures. Seventeen participants (9 males) were scanned while viewing pictures of tactile intimacy in same-sex and being asked to evaluate whether the behaviors between the stimulus persons in the pictures were morally appropriate or not. Both the neural responses to pictures of tactile intimacy in same-sex between male participants and female participants and the neural response to pictures of male-male tactile intimacy and to pictures of female-female tactile intimacy were examined. The results showed that significantly increased differential activations to the disgusting pictures relative to the neutral pictures were observed in the dorsal medial prefrontal cortex (BA 9) and amygdala. Furthermore, greater activation to the pictures of female-female tactile intimacy was observed in the left superior frontal gyrus/dorsal medial prefrontal cortex (BA 6). These results suggested a possible neural gender difference between female’s immoral behavior and male’s immoral behavior.

Ranking Method for Complementary Judgment Matrixes with Fuzzy Numbers Based on Hausdorff Metric Distance

A method for ranking complementary judgment matrixes with traspezoidal fuzzy numbers based on Hausdorff metric distance and fuzzy compromise decision approach is proposed. With regard to fuzzy number complementary judgment matrixes given by a decider group whose members have various weights, the expert＇s information was aggregated first by means of simple weight average（SWA） method and Bonissone calculational method. Hence a matrix including all the experts＇ preference information was got. Then the matrix＇ column members were added up and the fuzzy evaluation values of the alternatives were got. Lastly, the Hausdorff metric distance and fuzzy compromise decision approach were used to rank the fuzzy evaluation values and then the ranking values of all the alternatives were got. Because exact numbers and triangular fuzzy numbers could all be transformed into trapezoidal fuzzy numbers, the method developed can rank complementary judgment matrixes with trapezoidal fuzzy numbers, triangular fuzzy numbers and exact numbers as well. An illustrative example is also given to verify the developed method and to demonstrate its feasibility and practicality.

A Secure Multi-factor Authentication Protocol for Healthcare Services Using Cloud-based SDN

Cloud-based SDN(Software Defined Network)integration offers new kinds of agility,flexibility,automation,and speed in the network.Enterprises and Cloud providers both leverage the benefits as networks can be configured and optimized based on the application requirement.The integration of cloud and SDN paradigms has played an indispensable role in improving ubiquitous health care services.It has improved the real-time monitoring of patients by medical practitioners.Patients’data get stored at the central server on the cloud from where it is available to medical practitioners in no time.The centralisation of data on the server makes it more vulnerable to malicious attacks and causes a major threat to patients’privacy.In recent days,several schemes have been proposed to ensure the safety of patients’data.But most of the techniques still lack the practical implementation and safety of data.In this paper,a secure multi-factor authentication protocol using a hash function has been proposed.BAN(Body Area Network)logic has been used to formally analyse the proposed scheme and ensure that no unauthenticated user can steal sensitivepatient information.Security Protocol Animator(SPAN)–Automated Validation of Internet Security Protocols and Applications(AVISPA)tool has been used for simulation.The results prove that the proposed scheme ensures secure access to the database in terms of spoofing and identification.Performance comparisons of the proposed scheme with other related historical schemes regarding time complexity,computation cost which accounts to only 423 ms in proposed,and security parameters such as identification and spoofing prove its efficiency.

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Based on Multi-Factor Analysis and a Multi-Model Ensemble

Dissolved oxygen(DO)is an important indicator of aquaculture,and its accurate forecasting can effectively improve the quality of aquatic products.In this paper,a new DO hybrid forecasting model is proposed that includes three stages:multi-factor analysis,adaptive decomposition,and an optimizationbased ensemble.First,considering the complex factors affecting DO,the grey relational(GR)degree method is used to screen out the environmental factors most closely related to DO.The consideration of multiple factors makes model fusion more effective.Second,the series of DO,water temperature,salinity,and oxygen saturation are decomposed adaptively into sub-series by means of the empirical wavelet transform(EWT)method.Then,five benchmark models are utilized to forecast the sub-series of EWT decomposition.The ensemble weights of these five sub-forecasting models are calculated by particle swarm optimization and gravitational search algorithm(PSOGSA).Finally,a multi-factor ensemble model for DO is obtained by weighted allocation.The performance of the proposed model is verified by timeseries data collected by the pacific islands ocean observing system(PacIOOS)from the WQB04 station at Hilo.The evaluation indicators involved in the experiment include the Nash–Sutcliffe efficiency(NSE),Kling–Gupta efficiency(KGE),mean absolute percent error(MAPE),standard deviation of error(SDE),and coefficient of determination(R^(2)).Example analysis demonstrates that:①The proposed model can obtain excellent DO forecasting results;②the proposed model is superior to other comparison models;and③the forecasting model can be used to analyze the trend of DO and enable managers to make better management decisions.

Multi-Factor Password-Authenticated Key Exchange via Pythia PRF Service

Multi-factor authentication(MFA)was proposed by Pointcheval et al.[Pointcheval and Zimmer(2008)]to improve the security of single-factor(and two-factor)authentication.As the backbone of multi-factor authentication,biometric data are widely observed.Especially,how to keep the privacy of biometric at the password database without impairing efficiency is still an open question.Using the vulnerability of encryption(or hash)algorithms,the attacker can still launch offline brute-force attacks on encrypted(or hashed)biometric data.To address the potential risk of biometric disclosure at the password database,in this paper,we propose a novel efficient and secure MFA key exchange(later denoted as MFAKE)protocol leveraging the Pythia PRF service and password-to-random(or PTR)protocol.Armed with the PTR protocol,a master password pwd can be translated by the user into independent pseudorandom passwords(or rwd)for each user account with the help of device(e.g.,smart phone).Meanwhile,using the Pythia PRF service,the password database can avoid leakage of the local user’s password and biometric data.This is the first paper to achieve the password and biometric harden service simultaneously using the PTR protocol and Pythia PRF.

Multi-factor sensitivity analysis of shallow unsaturated clay slope stability

An unsaturated clay slope, with various sloping angles and a thickness of 14 m, consists of backfill, slope soil and residual soil. Slide interfaces were determined by geophysical approaches and the original slope was reconstructed. Sub-slope masses were classified based on the varieties of sloping angle. A force recursive principle was proposed to calculate the stability coefficient of the sub-slope masses. The influencing factors such as sloping angle, water content, hydrostatic pressure, seismic force as well as train load were analyzed. The range and correlation of the above-mentioned factors were discussed and coupled wave equations were established to reflect the relationships between unit weight, cohesion, internal frictional angle, and water content, as well as between internal frictional angle and cohesion. The sensitivity analysis of slope stability was carried out and susceptive factors were determined when the factors were taken as independent and dependent variables respectively. The results show that sloping angle, water content and earthquake are the principal susceptive factors influencing slope stability. The impact of hydrostatic pressure on slope stability is similar to the seismic force in quantity. Train load plays a small role in slope stability and its influencing only reaches the roadbed and its neighboring slope segment. If the factors are taken as independent variables, the influencing extent of water content and cohesion on slope stability can be weakened and train load can be magnified.

Investment in deepwater oil and gas exploration projects:a multi-factor analysis with a real options model

Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.

A branch-and-bound algorithm for discrete multi-factor portfolio optimization model

In this paper, a new branch-and-bound algorithm based on the Lagrangian dual relaxation and continuous relaxation is proposed for discrete multi-factor portfolio selection model with roundlot restriction in financial optimization. This discrete portfolio model is of integer quadratic programming problems. The separable structure of the model is investigated by using Lagrangian relaxation and dual search. Computational results show that the algorithm is capable of solving real-world portfolio problems with data from US stock market and randomly generated test problems with up to 120 securities.

Multi-factor high-order intuitionistic fuzzy timeseries forecasting model

Fuzzy sets theory cannot describe the neutrality degreeof data, which has largely limited the objectivity of fuzzy time seriesin uncertain data forecasting. With this regard, a multi-factor highorderintuitionistic fuzzy time series forecasting model is built. Inthe new model, a fuzzy clustering algorithm is used to get unequalintervals, and a more objective technique for ascertaining membershipand non-membership functions of the intuitionistic fuzzy setis proposed. On these bases, forecast rules based on multidimensionalintuitionistic fuzzy modus ponens inference are established.Finally, contrast experiments on the daily mean temperature ofBeijing are carried out, which show that the novel model has aclear advantage of improving the forecast accuracy.