Yield and Nutritive Values of Semi- and Non-Fall Dormant Alfalfa Cultivars under Late-Cutting Schedule in California’s Central Valley

California is one of the major alfalfa (Medicago sativa L) forage-producing states in the U.S, but its production area has decreased significantly in the last couple of decades. Selection of cultivars with high yield and nutritive value under late-cutting schedule strategy may help identify cultivars that growers can use to maximize yield while maintaining area for sustainable alfalfa production, but there is little information on this strategy. A field study was conducted to determine cumulative dry matter (DM) and nutritive values of 20 semi- and non-fall dormant (FD) ratings (FD 7 and FD 8 - 10, respectively) cultivars under 35-day cut in California’s Central Valley in 2020-2022. Seasonal cumulative DM yields ranged from 6.8 in 2020 to 37.0 Mg·ha−1 in 2021. Four FD 8 - 9 cultivars were the highest yielding with 3-yrs avg. DM greater than the lowest yielding lines by 46%. FD 7 cultivar “715RR” produced the highest crude protein (CP: 240 g·Kg−1) while FD 8 cultivar “HVX840RR” resulted in the highest neutral detergent fiber digestibility (NDFD: 484 g·Kg−1, 7% greater than the top yielding cultivars) but with DM yield intermediate. Yields and NDFD correlated positively but weakly indicating some semi- and non-FD cultivars performing similarly. These results suggest that selecting high yielding cultivars under 35-day cutting schedule strategy can be used as a tool to help growers to maximize yield while achieving good quality forages for sustainable alfalfa production in California’s Central Valley.

MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as needed.It has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud platforms.However,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing times.The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution space.Moreover,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating process.This study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam model.Simulated outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection scenarios.MCWOA excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage detection.The efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and delay.The simulated data indicates that the new MCWOA outpaces other methods across all metrics.The study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

基于NPV Scheduler软件的露天转地下矿山开采境界研究

基础的L-G图论法未考虑地下开采可能的成本优势,在露天转地下矿山开采境界圈定时存在一定的局限性。本文通过对价格法与储量盈利比较法计算的经济合理剥采比进行分析,结合NPV Scheduler软件研究了露天转地下开采境界圈定方法,并通过工程实例验证了该方法的合理性。研究成果对露天转地下矿山开采境界的确定具有一定的指导意义。

基于Scheduled Sampling采样机制的人体行为预测

针对循环神经网络存在的预测误差累积问题,提出了融合Scheduled Sampling采样机制的序列预测算法。该算法选用较大概率p作为选择使用真实值或是前一帧预测数据作为当前时间步输入依据,并随着时间的推移p值逐渐变小,使解码器更倾向于使用预测序列作为输入,以此增加模型的健壮性。实验结果表明:该算法能够将Human3.6M数据集中绝大多数动作短期预测误差降低到0.5 dm左右,相比原方法降低了0.2~0.4 dm,在行为预测上表现良好。

Performance Improvement through Novel Adaptive Node and Container Aware Scheduler with Resource Availability Control in Hadoop YARN

The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs.This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator(YARN)scheduler,called the Adaptive Node and Container Aware Scheduler(ANACRAC),that aligns cluster resources to the demands of the applications in the real world.The approach performs to leverage the user-provided configurations as a unique design to apportion nodes,or containers within the nodes,to application thresholds.Additionally,it provides the flexibility to the applications for selecting and choosing which node’s resources they want to manage and adds limits to prevent threshold breaches by adding additional jobs as needed.Node or container awareness can be utilized individually or in combination to increase efficiency.On top of this,the resource availability within the node and containers can also be investigated.This paper also focuses on the elasticity of the containers and self-adaptiveness depending on the job type.The results proved that 15%–20%performance improvement was achieved compared with the node and container awareness feature of the ANACRAC.It has been validated that this ANACRAC scheduler demonstrates a 70%–90%performance improvement compared with the default Fair scheduler.Experimental results also demonstrated the success of the enhancement and a performance improvement in the range of 60%to 200%when applications were connected with external interfaces and high workloads.

A Modified Firefly Optimization Algorithm-Based Fuzzy Packet Scheduler for MANET

In Mobile ad hoc Networks(MANETs),the packet scheduling process is considered the major challenge because of error-prone connectivity among mobile nodes that introduces intolerable delay and insufficient throughput with high packet loss.In this paper,a Modified Firefly Optimization Algorithm improved Fuzzy Scheduler-based Packet Scheduling(MFPA-FSPS)Mechanism is proposed for sustaining Quality of Service(QoS)in the network.This MFPA-FSPS mechanism included a Fuzzy-based priority scheduler by inheriting the merits of the Sugeno Fuzzy inference system that potentially and adaptively estimated packets’priority for guaranteeing optimal network performance.It further used the modified Firefly Optimization Algorithm to optimize the rules uti-lized by the fuzzy inference engine to achieve the potential packet scheduling pro-cess.This adoption of a fuzzy inference engine used dynamic optimization that guaranteed excellent scheduling of the necessitated packets at an appropriate time with minimized waiting time.The statistical validation of the proposed MFPA-FSPS conducted using a one-way Analysis of Variance(ANOVA)test confirmed its predominance over the benchmarked schemes used for investigation.

Factors Determining the Postponement of Schedule Gyneaco-Obstetric Surgery at CHUMEFJE in Libreville (Gabon)

The study aimed to identify factors causing delays in scheduled gynaeco-obstetric surgeries at CHUMEFJE in Libreville from January 2019 to July 2020. Through a 16-month observational survey, it was found that out of 346 scheduled procedures, 128 (36.4%) were postponed. Organizational issues in the operating theatre were responsible for 80.3% of these delays, with 95.3% being preventable. To enhance efficiency, improvements in operating theatre organization are recommended.

采用NPV Scheduler软件对某大型露天矿山进行境界优化

某大型矿床随着开采的进行以及补充勘探的深入,加上市场的变化,使得原来的境界设计条件发生了一些变化,因此需要根据最新的边界条件对境界进行优化设计。采用NPV Scheduler软件用L-G图论法对该铜矿的最终开采境界进行了优化圈定,使得最终境界更符合当前采选成本和市场条件。

Multi-objective integrated optimization based on evolutionary strategy with a dynamic weighting schedule

The evolutionary strategy with a dynamic weighting schedule is proposed to find all the compromised solutions of the multi-objective integrated structure and control optimization problem, where the optimal system performance and control cost are defined by H2 or H∞ norms. During this optimization process, the weights are varying with the increasing generation instead of fixed values. The proposed strategy together with the linear matrix inequality （LMI） or the Riccati controller design method can find a series of uniformly distributed nondominated solutions in a single run. Therefore, this method can greatly reduce the computation intensity of the integrated optimization problem compared with the weight-based single objective genetic algorithm. Active automotive suspension is adopted as an example to illustrate the effectiveness of the proposed method.

Real-time and dynamic schedule optimization of construction projects on the basis of lean construction

Lean construction has been newly applied to construction industry. The best performance of a project can be achieved through the precise definition of construction product, rational work break structure, lean supply chain, decrease of resources waste, objective control and so forth. Referring to the characteristics of schedule planning of construction projects and lean construction philosophy, we proposed optimizing methodology of real-time and dynamic schedule of construction projects based on lean construction. The basis of the methodology is process reorganization and lean supply in construction enterprises. The traditional estimating method of the activity duration is fuzzy and random;however, a newly proposed lean forecasting method employs multi-components linear-regression, back-propagation artificial neural networks and learning curve. Taking account of the limited resources and the fixed duration of a project, the optimizing method of the real-time and dynamic schedule adopts the concept of resource driving. To optimize the schedule of a construction project timely and effectively, an intellectualized schedule management system was developed. It can work out the initial schedule, optimize the real-time and dynamic schedule, and display the schedule with the Gant Chart, the net-work graph and the space-time line chart. A case study was also presented to explain the proposed method.

国际商事仲裁文件证据出示表格比较分析——比较Redfern Schedule和Armesto Schedule

为快速准确地确定需要出示的文件证据,使仲裁程序更加高效便捷,国际商事仲裁庭常使用Redfern Schedule和Armesto Schedule归纳申请出示和反对出示的争议焦点。两种表格各有优势,互为补充,灵活机动选用国际商事仲裁文件证据出示表格应被我国仲裁庭和国际仲裁当事人重视。

基于STK/Scheduler的航天任务调度应用研究

STK/Scheduler是与STK（satellite tool kits）完全集成的任务调度软件,通过它可方便的定义任务、资源和各种约束关系。介绍了STK/Scheduler的主要功能,在分析航天任务调度的特点及要素的基础上,建立了调度模型,并利用STK/Scheduler实现了2个典型的卫星任务调度。结果表明：STK/Scheduler能基本满足航天任务调度的需求。

An On-Line Scheduler over Hard Real-Time Communication System

By thorough research on the prominent periodic and aperiodic scheduling algorithms,anon-line hard real-time scheduler is presented,which is applicable to the scheduling of packets over a link.This scheduler,based on both Rate Monotonic,pinwheel scheduling algorithm Sr and Polling Serverscheduling algorithms,can rapidly judge the schedulability and then automatically generate a bus tablefor the scheduling algorithm to schedule the packets as the periodic packets.The implementation of thescheduler is simple and easy to use,and it is effective for the utilization of bus link.The orderly executionof the bus table can not only guarantee the performance of the hard real time but also avoid the blockageand interruption of the message transmission.So the scheduler perfectly meets the demand of hard real-time communication system on the field bus domain.

Study on shift schedule saving energy of automatic transmission of ground vehicles

To improve ground vehicle efficiency, shift schedule energy saving was proposed for the ground vehicle automatic transmission by studying the function of the torque converter and transmission in the vehicular drivetrain. The shift schedule can keep the torque converter working in the high efficiency range under all the working conditions except in the low efficiency range on the left when the transmission worked at the lowest shift, and in the low efficiency range on the right when the transmission worked at the highest shift. The shift quality key factors were analysed. The automatic trans-mission's bench-test adopting this shift schedule was made on the automatic transmission's test-bed. The experimental results showed that the shift schedule was correct and that the shift quality was controllable.

采用Scheduled Thread Pool Executor执行定时重试任务时内存溢出的分析及解决

开发Java Web项目中发现服务之间的调用存在超时情况,由于涉及的处理逻辑全部是异步,引入定时重试的机制,重试工具选择了JDK自带的Scheduled Thread Pool Executor。当A服务依赖B服务,B服务由于在业务高峰期处理能力降低,导致大量A服务过来的请求超时,A加入了超时重试机制,间隔时间根据重试次数的多少来决定,次数越多,两次重试之间间隔的时间越多,此时的业务高峰也会给A带来大量请求,大量的超时会导致重试队列迅速堆积,直到内存溢出。该文从线程池工作机制、Scheduled Thread Pool Executor实例的创建,获取重试任务的过程以及提交任务的过程角度分析,并通过源代码的剖析和测试工具My Eclipse进行演示测试内存泄露的情况,得出避免内存泄露的解决方案。

Immune response to an indigenously developed r-Hepatitis B vaccine in mixed population: Study of an accelerated vaccination schedule

AIM: To establish the safety and efficacy of an indigenously developed r-hepatitis B vaccine using an accelerated schedule and to highlight the social awareness and commitment in preventing the spreading of hepatitis B virus infection. METHODS: The study was a multicentric, double blind, randomized (3:1) study using three doses of vaccine immunization schedule (20μg for those above 10 years old and 10 μg for those below 10 years old) on d 0, 30 and 60. One hundred and sixty-six subjects were enrolled (87 males and 76 females aged 5-35 years). The main outcome measure was assessment of immunogenicity and safety. RESULTS: A 100% seroconversion response was observed on the 30th d after the 1st injection in both the experimental groups. The sero-protection data reported a 41.2-65.6% response on the 30th d after the 1st injection and reached 100% on the 60th d. Descriptive statistical analysis showed a geometric mean titer value of 13.77 mIU/mL in the test (BEVAC) group and 10.95 mlU/mL in the commercial control (ENGERIX-B) group on the 30th d after the 1st injection. The response on the 60th d showed a geometric mean titre value (GMT) of 519.84 mlU/mL in the BEVAC group and 475.46 mlU/mL in the ENGERIX-B group. On the 90th d, the antibody titer response was observed to be 2627.58 mlU/mL in the BEVAC group and 2272.72 mlU/mL in the ENGERIX-B group. Two subjects in each group experienced pains at injection site after the first vaccination. A total of six subjects in both groups experienced a solicited adverse reaction, which included pains, swelling and redness at the injection site, three subjects in the group-B had a pain at the injection site after the third dose. No other serious adverse events occurred and no dose-related local or general symptoms were observed during the study. CONCLUSION: The vaccine is safe, efficacious and immunogenic in comparison with the well documented ENGERIX-B.

Multi-objective optimization of rolling schedule based on cost function for tandem cold mill

In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.

基于NPV Scheduler软件的国外某铅锌矿露天境界优化

基于地质块体模型,采用NPV Scheduler软件对国外某铅锌矿露天境界进行优化,得到了该矿山的最优境界和采剥进度计划,为矿山露天开采和投资提供了技术方案和决策依据。

STUDY ON SHIFT SCHEDULE AND SIMULATION OF AUTOMATIC TRANSMISSION

From the point of view of saving energy, a new shift schedule and auto-controlling strategy for automatic transmission are proposed. In order to verify this shift schedule, a simulation program using a software package of Matlab/ Simulink is developed. The simulation results show the shift schedule is correct. This shift schedule has enriched the theory of vehicle automatic maneuvering and will improve the efficiency of hydrodynanic drive system of the vehicle.

Relative-Residual-Based Dynamic Schedule for Belief Propagation Decoding of LDPC Codes

Two Relative-Residual-based Dynamic Schedules(RRDS) for Belief Propagation(BP) decoding of Low-Density Parity-Check(LDPC) codes are proposed,in which the Variable code-RRDS(VN-RRDS) is a greediness-reduced version of the Check code-RRDS(CN-RRDS).The RRDS only processes the variable(or check) node,which has the maximum relative residual among all the variable(or check) nodes in each decoding iteration,thus keeping less greediness and decreased complexity in comparison with the edge-based Variable-to-Check Residual Belief Propagation(VC-RBP) algorithm.Moreover,VN-RRDS propagates first the message which has the largest residual based on all check equations.For different types of LDPC codes,simulation results show that the convergence rate of RRDS is higher than that of VC-RBP while keeping very low computational complexity.Furthermore,VN-RRDS achieves faster convergence as well as better performance than CN-RRDS.