High Altitude Frogs (Rana kukonoris) Adopt a Diversified Bethedging Strategy in the Face of Environmental Unpredictability

Environmental unpredictability can influence strategies of maternal investment among eggs within a clutch. Models predict that breeding females should adopt a diversified bet-hedging strategy in unpredictable environments, but empirical field evidence from Asia is scarce. Here we tested this hypothesis by exploring spatial patterns in egg size along an altitudinal gradient in a frog species （Rana kukunoris） inhabiting the Tibetan Plateau. Within-clutch variability in egg size increased as the environment became variable （e.g., lower mean monthly temperature and mean monthly rainfall at higher altitudes）, and populations in environments with more unpredictable rainfall produced eggs that were smaller and more variable in size. We provide support for a diversified bet-hedging strategy in high-altitude environments, which experience dynamic weather patterns and therefore are of unpredictable environmental quality. This strategy may be an adaptive response to lower environmental quality and higher unpredictable environmental variance. Such a strategy should increase the likelihood of breeding success and maximize maternal lifetime fitness by producing offspring that are adapted to current environmental conditions. We speculate that in high-altitude environments prone to physical disturbance, breeding females are unable to consistently produce the optimal egg size due to physiological constraints imposed by environmental conditions （e.g., duration of the active season, food availability）. Species and populations whose breeding strategies are adapted to cope with uncertain environmental conditions by adjusting offspring size and therefore quality show a remarkable degree of ability to cope with future climatic changes.

Exploring Pedagogical Ideologies and Strategies for College English Writing Instruction from a Generative Artificial Intelligence Perspective

This study,drawing on the commonalities between generative artificial intelligence and foreign language writing instruction,outlines the core ideology of digital humanities-based college English writing instruction,including auxiliary use of generative artificial intelligence tools,primary focus on humanistic education,and the re-production of knowledge,aiming to foster students’critical thinking,collaborative skills,and creativity.Building on this foundation,the study delves into generative artificial intelligence tools applicable to different stages of process-genre writing and their strategic applications.The use of generative artificial intelligence tools is beneficial for students to present,discuss,and share writing content,encouraging them to enhance their writing,collaboration,critical thinking,and creative abilities through deep interaction with model essays and creative discourses.

Generalized CAPP and synthetic evaluation strategy for production line of accuracy welding

This paper presents generalized CAPP （G-CAPP） method which deals with macro process planning for multiobjective in the planning stage of production line of accuracy welding （PLAW） based on the features of accuracy welding production （ AWP ）. G-CAPP offers foundations for prototype design and general equipment sorting, production capacity predication and production analysis by means of simulation and optimization. A synthetic hierarchy evaluation （SHE） model for G-CAPP established according to the planning objective is utilized to estimate the alternate processing plans by using membership function and analytic hierarchy process （AHP） of operational theory. The assembly welding line of hydraulic torque converter （HTC） is as an example of typical A WP to explicate G-CAPP and synthetic evaluating strategy of PLAW. The feasible and rational process configuration strategies of HTC assembly welding line are pointed oat under different planning objective.

Using Multiple Risk Factors and Generalized Linear Mixed Models with 5-Fold Cross-Validation Strategy for Optimal Carotid Plaque Progression Prediction

Background Cardiovascular diseases are closely linked to atherosclerotic plaque development and rupture.Plaque progression prediction is of fundamental significance to cardiovascular research and disease diagnosis,prevention,and treatment.Generalized linear mixed models(GLMM)is an extension of linear model for categorical responses while considering the correlation among observations.Methods Magnetic resonance image(MRI)data of carotid atheroscleroticplaques were acquired from 20 patients with consent obtained and 3D thin-layer models were constructed to calculate plaque stress and strain for plaque progression prediction.Data for ten morphological and biomechanical risk factors included wall thickness(WT),lipid percent(LP),minimum cap thickness(MinCT),plaque area(PA),plaque burden(PB),lumen area(LA),maximum plaque wall stress(MPWS),maximum plaque wall strain(MPWSn),average plaque wall stress(APWS),and average plaque wall strain(APWSn)were extracted from all slices for analysis.Wall thickness increase(WTI),plaque burden increase(PBI)and plaque area increase(PAI) were chosen as three measures for plaque progression.Generalized linear mixed models(GLMM)with 5-fold cross-validation strategy were used to calculate prediction accuracy for each predictor and identify optimal predictor with the highest prediction accuracy defined as sum of sensitivity and specificity.All 201 MRI slices were randomly divided into 4 training subgroups and 1 verification subgroup.The training subgroups were used for model fitting,and the verification subgroup was used to estimate the model.All combinations(total1023)of 10 risk factors were feed to GLMM and the prediction accuracy of each predictor were selected from the point on the ROC(receiver operating characteristic)curve with the highest sum of specificity and sensitivity.Results LA was the best single predictor for PBI with the highest prediction accuracy(1.360 1),and the area under of the ROC curve(AUC)is0.654 0,followed by APWSn(1.336 3)with AUC=0.6342.The optimal predictor among all possible combinations for PBI was the combination of LA,PA,LP,WT,MPWS and MPWSn with prediction accuracy=1.414 6(AUC=0.715 8).LA was once again the best single predictor for PAI with the highest prediction accuracy(1.184 6)with AUC=0.606 4,followed by MPWSn(1. 183 2)with AUC=0.6084.The combination of PA,PB,WT,MPWS,MPWSn and APWSn gave the best prediction accuracy(1.302 5)for PAI,and the AUC value is 0.6657.PA was the best single predictor for WTI with highest prediction accuracy(1.288 7)with AUC=0.641 5,followed by WT(1.254 0),with AUC=0.6097.The combination of PA,PB,WT,LP,MinCT,MPWS and MPWS was the best predictor for WTI with prediction accuracy as 1.314 0,with AUC=0.6552.This indicated that PBI was a more predictable measure than WTI and PAI. The combinational predictors improved prediction accuracy by 9.95%,4.01%and 1.96%over the best single predictors for PAI,PBI and WTI(AUC values improved by9.78%,9.45%,and 2.14%),respectively.Conclusions The use of GLMM with 5-fold cross-validation strategy combining both morphological and biomechanical risk factors could potentially improve the accuracy of carotid plaque progression prediction.This study suggests that a linear combination of multiple predictors can provide potential improvement to existing plaque assessment schemes.

Optimal Hedging Strategies of Stock Index Futures Based on the Perspective of Information Asymmetry

Based on two different risk measurement criteria, this article studied the optimal hedging strategies of stock index futures in the case of asymmetric information, and discussed the influence of insider information on the hedging effect. Through simulation analysis, it can be shown that hedging people with insider information can save hedging costs to a certain extent, which also explains the reason why investors try to obtain corporate information in actual investment activities.

Control strategy of central pattern generator gait movement under condition of attention selection

As a typical rhythmic movement, human being＇s rhythmic gait movement can be generated by a central pattern generator （CPG） located in a spinal cord by self- oscillation. Some kinds of gait movements are caused by gait frequency and amplitude variances. As an important property of human being＇s motion vision, the attention selection mechanism plays a vital part in the regulation of gait movement. In this paper, the CPG model is amended under the condition of attention selection on the theoretical basis of Matsuoka neural oscillators. Regulation of attention selection signal for the CPG model parameters and structure is studied, which consequentially causes the frequency and amplitude changes of gait movement output. Further, the control strategy of the CPG model gait movement under the condition of attention selection is discussed, showing that the attention selection model can regulate the output model of CPG gait movement in three different ways. The realization of regulation on the gait movement frequency and amplitude shows a variety of regulation on the CPG gait movement made by attention selection and enriches the controllability of CPG gait movement, which demonstrates potential influence in engineering applications.

Establishment of a multi-cycle generalized Weng model and its application in forecasts of global oil supply

Low oil prices under the influence of economic structure transformation and slow economic growth have hit the existing markets of traditional big oil suppliers and upgraded the conflict of oil production capacity and interest between OPEC producers and other big oil supplier countries such as the USA and Russia. Forecasting global oil production is significant for all countries for energy strategy planning, although many past forecasts have later been proved to be very seriously incorrect. In this paper,the original generalized Weng model is expanded to a multi-cycle generalized Weng model to better reflect the multi-cycle phenomena caused by political, economic and technological factors. This is used to forecast global oil production based on parameter selection from a large sample, depletion rate of remaining resources, constraints on oil reserves and cycle number determination. This research suggests that the world will reach its peak oil production in 2022, at about 4340×10~6 tonnes. China needs to plan for oil import diversity, a domestic oil production structure based on the supply pattern of large oil suppliers worldwide and the oil demand for China＇s own development.

Torque Distribution Strategy for Integrated Starter/ Generator Hybrid Bus Implemented by Fuzzy Algorithm

A torque distribution strategy was designed by using fuzzy logic to realize the optimal control. The vehicle load zones were dynamically divided into several zones by several torque lines to indicate the drivers demand and the high or low efficient operating areas of the diesel engine. The fuzzy logic controller with trapezoid membership function and Mamdani rule reference mechanism was utilized. There are over 100 rules used in this fuzzy-based torque distribution strategy which are sorted into four rule-bases. The fuel economy and acceleration tests were designed to test and validate the integrated starter/generator (ISG) bus perfor-mance using fuzzy-based torque distribution strategy. The fuel economy is improved 7.7% compared with the rule-based strategy. Finally the road test results reveal that there is about 15% improvement of fuel economy. And the 0-50 km/h acceleration time is 9.5% shorter than the original bus.

Application of generalized predictive control in networked control system

A new framework for networked control system based on Generalized Predictive Control (GPC) is proposed in this paper. Clock-driven sensors, event-driven controller, and clock-driven actuators are required in this framework. A queuing strategy is proposed to overcome the network induced delay. Without redesigning, the proposed framework enables the existing GPC controller to be used in a network environment. It also does not require clock synchronization and is only slightly affected by bad network condition such as package loss. Various experiments are designed over the real network to test the proposed approach, which verify that the proposed approach can stabilize the Networked Control System (NCS) and is robust.

Pinion Tooth Surface Generation Strategy of Spiral Bevel Gears

Aviation spiral bevel gears are often generated by spiral generated modified（SGM） roll method.In this style,pinion tooth surface modified generation strategy has an important influence on the meshing and contact performances.For the optimal contact pattern and transmission error function,local synthesis is applied to obtain the machine-tool settings of pinion.For digitized machine,four tooth surface generation styles of pinion are proposed.For every style,tooth contact analysis（TCA） is applied to obtain contact pattern and transmission error function.For the difference between TCA transmission error function and design objective curve,the degree of symmetry and agreement are defined and the corresponding sub-objective functions are established.Linear weighted combination method is applied to get an equivalent objective function to evaluate the shape of transmission error function.The computer programs for the process above are developed to analyze the meshing performances of the four pinion tooth surface generation styles for a pair of aviation spiral bevel gears with 38/43 teeth numbers.The four analytical results are compared with each other and show that the incomplete modified roll is optimal for this gear pair.This study is an expansion to generation strategy of spiral bevel gears,and offers new alternatives to computer numerical control（CNC） manufacture of spiral bevel gears.

Examining the Relationship of Optimism and Emotion Regulation Strategies with General Health among Students of University of Sistan and Baluchestan

Background and Objective: Individuals apply various emotion regulation strategies, some of which are adaptive and others are maladaptive affecting people’s general health. Moreover, individual life-orientation including favorable expectancies about future (optimism) is associated with health-related behaviors. The purpose of the present study was to investigate the relationship of optimism and emotion regulation strategies with general health of university students. Materials and Methods: This was a correlational study. In this regard, 182 students of University of Sistan and Baluchestan (70 males and 112 females) were chosen. The statistical population of the present study consisted of all undergraduate students of the university of Sistan and Baluchestan in the second semester of the 2009-2010 academic year. Considering the nature of the current study, the correlational method was applied. Based on Krejcie and Morgan’s table, a sample of 200 subjects was selected from students majored at different fields including human sciences, basic sciences and technical-engineering through applying multi-stage random sampling method. Eighteen incomplete questionnaire forms were excluded. Finally, data obtained from 182 subjects (112 females, 70 males) were analyzed. The mean age was 21.1 year-old and standard deviation of the sample was 2.06. Samplings were assessed using the Revised Life-Orientation Test (LOT-R), Emotion Regulation Questionnaire (ERQ) and General Health-28 Questionnaire (GHQ-28). Data were analyzed using the Pearson correlation coefficient and regression analysis. Results: Findings showed that there was a significant positive relationship between optimism and general health (r = 0.22, p < 0.01). Among all research variables, i.e. optimism and emotion regulation strategies (cognitive reappraisal and expressive suppression), only optimism was able to predict 0.06 percent of variance of general health (p < 0.001). Conclusion: Optimists have higher general health and consistent with other findings, optimism is associated with higher levels of applying coping strategies and lower levels of avoidance.

Hedge fund replication using strategy specific factors

Hedge funds have traditionally served wealthy individuals and institutional investors with the promise of delivering protection of capital and uncorrelated positive returns irrespective of market direction,allowing them to better manage portfolio risk.However,the financial crisis of 2008 has heightened investor sensitivity to the high fees,illiquidity,lack of transparency,and lockup periods typically associated with hedge funds.Hedge fund replication products,or clones,seek to answer these challenges by providing daily liquidity,transparency,and immediate exposure to a desired hedge fund strategy.Nonetheless,although lowering cost and adding simplicity by using a common set of factors,traditional replication products might offer lower risk-reward performance compared to hedge funds.This research explores hedge fund replication further by examining the importance of constructing clones with specific factors relevant to each hedge fund strategy,and then compares the strategy specific clone risk and reward performance against both actual hedge fund performance and hedge fund clones constructed using a more general set of common factors.Testing shows that using strategy specific factors to replicate common hedge fund strategies can offer superior risk-reward performance compared to previous general model clones.

Minimal Generalized Time-Bandwidth Product Method for Estimating the Optimum Fractional Fourier Order

A minimal generalized time-bandwidth product-based coarse-to-fine strategy is proposed with one novel ideas highlighted: adopting a coarse-to-fine strategy to speed up the searching process. The simulation results on synthetic and real signals show the validity of the proposed method.

Medical Feature Selection Approach Based on Generalized Normal Distribution Algorithm

This paper proposes a new pre-processing technique to separate the most effective features from those that might deteriorate the performance of the machine learning classifiers in terms of computational costs and classification accuracy because of their irrelevance,redundancy,or less information;this pre-processing process is often known as feature selection.This technique is based on adopting a new optimization algorithm known as generalized normal distribution optimization(GNDO)supported by the conversion of the normal distribution to a binary one using the arctangent transfer function to convert the continuous values into binary values.Further,a novel restarting strategy(RS)is proposed to preserve the diversity among the solutions within the population by identifying the solutions that exceed a specific distance from the best-so-far and replace them with the others created using an effective updating scheme.This strategy is integrated with GNDO to propose another binary variant having a high ability to preserve the diversity of the solutions for avoiding becoming stuck in local minima and accelerating convergence,namely improved GNDO(IGNDO).The proposed GNDO and IGNDO algorithms are extensively compared with seven state-of-the-art algorithms to verify their performance on thirteen medical instances taken from the UCI repository.IGNDO is shown to be superior in terms of fitness value and classification accuracy and competitive with the others in terms of the selected features.Since the principal goal in solving the FS problem is to find the appropriate subset of features that maximize classification accuracy,IGNDO is considered the best.

The Research of Examination Paper Generation Based on Index System Metrics and Multi-Objective Strategy

Since the examination paper generated with computer by the algorithms of random and backtracking takes on inferior quality and inefficient, and the question of generating examination paper with computer has the character of multi-ob-jective because of the index system metrics, the genetic algorithm with multi-objective strategy optimization is proposed to solve this problem. Mapping the index system to multi-objective functions and optimizing the computing with multi-objective strategy are employed in the algorithm. The genetic algorithm experiment based on the multi-objective strategy optimization shows that the result has the advantages getting tradeoff between performance and quality, and having the ability to tune the performance and quality to meet the user’s requirements.

Characteristics of and management strategies for 54 suicidal inpatients in a general hospital

Objective： The aim of this study was to explore the characteristics of and preventive management strategies for suicidal inpatients in a general hospital.Methods： A total of 54 suicide victims were drawn from a patient safety adverse event network reporting system during hospitalization in a general hospital from November 2008 to January 2017.Results： Subjects who committed suicide in the general hospital were women and those who suffered from malignant neoplasms during general hospital treatment. Furthermore, most of the patients who committed suicide used more violent suicide methods. The most common and lethal means was jumping from heights at the windowsill.Conclusions： It is concluded that management straties for suicide prevention can be provided from the aspects of patients, medical staff and the hospital environment. It is not only urgent but also feasible to reduce the suicide rate of inpatients and further improve hospital safety management.

Murtagh安全诊断策略联合思维导图构建临床思维在全科教学门诊中的应用

全科教学门诊是培养住院医师规范化培训(简称住培)全科医生临床思维、提升全科诊疗能力的重要培训方法。本文用1例以乏力为主要表现的患者为教学案例,介绍全科教学门诊中采用澳大利亚著名全科医学专家John Murtagh提出的Murtagh安全诊断策略启发住培全科医生对乏力进行诊断与鉴别诊断:(1)引起乏力的常见疾病有哪些?(2)哪些重要疾病是不能忽视的?(3)乏力有什么容易被遗漏的疾病?(4)是否存在潜在的容易被掩盖的疾病?(5)患者是否有话没有说?结合病史、体格检查和实验室检查结果初步诊断为抗中性粒细胞胞浆抗体相关性血管炎引起急进性肾小球肾炎可能性大,及时转诊,肾病理检查确诊乏力的病因为抗中性粒细胞胞浆抗体相关性肾小球肾炎,取得满意疗效。带教老师基于Murtagh安全诊断策略帮助住培全科医生构建乏力鉴别、分析的系统知识框架,从而提升住培全科医生的临床逻辑思维能力和解决临床实际问题的能力;以思维导图为辅助工具,将Murtagh安全诊断策略诊断与鉴别诊断思路可视化、形象化,优化教学效果。

演化博弈模型下我国光伏发电市场规模分析

针对中国光伏发电市场规模情况,文章通过定义光伏原材料供应商、光伏原材料分销商、政府和光伏发电企业四方参与者的策略选择,利用复制动态方程构建四方演化博弈模型,分析在不同战略选择下每个参与者之间的收益和成本,并对微分方程稳定性原理和光伏市场中参与者策略之间的动态关系进行数据仿真。研究发现:(1)分销商需要筛选优质产品并提高鉴别能力,从而减少与不守规矩的生产商合作的可能性;(2)企业的维权行为对分销商和政府采取的政策具有积极影响;(3)政府在处理产品质量问题时需要采取多种措施进行综合治理。本研究有助于光伏产业参与者和政策制定者更好地了解市场动态,制定有效的政策和战略。

Overview and Analysis of PM Starter/Generator for Aircraft Electrical Power Systems

More Electrical Aircraft(MEA)which replaces the hydraulic and pneumatic power by electrical power leads to reducing emissions and fuel consumption.The MEA concept has led to a growing use of the starter/generator(S/G)system.Permanent magnet(PM)machines have been gaining interests for aircraft S/G system application over the last few years.This is mainly due to the several advantages,including high power density,high efficiency and high speed ability.The shortcoming of the PM machines is the de-­excitation problem in case of a failure,which is a main issue for the aircraft application.However,by using a PM machine with high reactance or multiphase configuration,the fault-­tolerant ability can be improved.In terms of the aircraft S/G system,this paper is going to present a comprehensive analysis of PM machines.Firstly,the state-­of-­the-­art of PM starter/generator(PMS/G)is summarized and the basic structure of PMS/G system is analyzed.Next,key technologies of the PMS/G system are summarized and analyzed.Finally,a flux weakening fault protection strategy that is used to suppress the turn-­to-­turn short circuit(SC)current is studied,simulated and verified.With the breakthrough of key technologies based on the development of high temperature electromagnetic material and high temperature power electronics,the PMS/G will be a potential candidate for aircraft S/G system including the embedded power generation system.

Business Ecosystem Strategies of Mobile Network Operators in the 3G Era

This paper applies the perspective of business ecosystem to mobile communications industry,trying to help mobile network operators improve their strategies in the era of the third generation mobile communications(3G).According to the definition of the business ecosystem,the ecosystem structure of mobile network operators is analyzed.As an important hub in the ecosystem,mobile network operators are advised to take a keystone strategy.The key points of the strategy are summarized.Finally,suggestions for Chinese mobile network operators are given based on the analysis.