Prediction of Leaf Area in Individual Leaves of Cherrybark Oak Seedlings (Quercus pagoda Raf.)

The prediction of leaf area for cherrybark oak (Quercus pagoda Raf.) seedlings is important for studying the physiology of the species. Linear and polynomial models involving leaf length, width, fresh weight, dry weight, and internodal length were tested independently and collectively to predict leaf area. Twenty-nine cherrybark oak seedlings were grown in a greenhouse for one growing season and a total of 468 leaves were collected. Leaf area was polynomially related with leaf length or width, but linearly related with the cross product of length and width. Average leaf area for flush 3 was significantly greater than those of other flushes. However, variation in leaf area among flushes did not affect the models. Relationship between leaf area and length (or width) was consistent. Since leaf length is easy to measure and does not require destruction of leaves, it can be effectively used to predict leaf area in cherrybark oak seedlings

V-Cache: Towards Flexible Resource Provisioning for Multi-tier Applications in IaaS Clouds

Abstract—Although the resource elasticity offered by Infrastructure-as-a-Service (IaaS) clouds opens up opportunities for elastic application performance, it also poses challenges to application management. Cluster applications, such as multi-tier websites, further complicates the management requiring not only accurate capacity planning but also proper partitioning of the resources into a number of virtual machines. Instead of burdening cloud users with complex management, we move the task of determining the optimal resource configuration for cluster applications to cloud providers. We find that a structural reorganization of multi-tier websites, by adding a caching tier which runs on resources debited from the original resource budget, significantly boosts application performance and reduces resource usage. We propose V-Cache, a machine learning based approach to flexible provisioning of resources for multi-tier applications in clouds. V-Cache transparently places a caching proxy in front of the application. It uses a genetic algorithm to identify the incoming requests that benefit most from caching and dynamically resizes the cache space to accommodate these requests. We develop a reinforcement learning algorithm to optimally allocate the remaining capacity to other tiers. We have implemented V-Cache on a VMware-based cloud testbed. Exper-iment results with the RUBiS and WikiBench benchmarks show that V-Cache outperforms a representative capacity management scheme and a cloud-cache based resource provisioning approach by at least 15 % in performance, and achieves at least 11 % and 21 % savings on CPU and memory resources, respectively. I

RESEARCH AND APPLICATION OF U-BIT CONSTRUCTION METHOD IN SUBWAY STATION ENGINEERING LOCATED IN SATURATED SOFT SOIL AREA

In order to solve the problems existing in the construction of underground structures located in the downtown of saturated soft soil area, such as insufficient construction site, complex adjacent structures and great impact on the surrounding environment, the construction method of underground bundled integrate tunnel(U-BIT) is proposed. In this method, after steel pipes jacking completed, concrete is filled into the pipes, and prestress is tensioned to make each independent pipe combined to form a whole bearing structure, so as to achieve the purpose of reducing the size of structural components, improving the structural stiffness and bearing capacity. Based on the structural mechanical properties test and the project of Wuding Road Station of Shanghai Metro Line 14, the failure mechanism of bundled integrate structure, the tension technology of prestressed tendons in narrow space and the variation rules of ground surface subsidence are systematically studied. The research shows that structural seam sections will be destroyed before pipe sections, so ensuring the mechanical performance of seam sections is very important to make sure the structural safety. Since each independent pipe is combined to form an overall stable structure under the prestress effect, the subsequent soil excavation has little influence on the tension of prestressed tendons and ground surface deformation. Therefore, the above construction method can control the ground surface subsidence effectively and reduce the influence of underground engineering construction on the surrounding environment.  &nbsp

Quantifying the Performance Benefits of Partitioned Communication in MPI

Partitioned communication was introduced in MPI 4.0 as a user-friendly interface to support pipelined communication patterns, particularly common in the context of MPI+threads. It provides the user with the ability to divide a global buffer into smaller independent chunks, called partitions, which can then be communicated independently. In this work we first model the performance gain that can be expected when using partitioned communication. Next, we describe the improvements we made to \mpich{} to enable those gains and provide a high-quality implementation of MPI partitioned communication. We then evaluate partitioned communication in various common use cases and assess the performance in comparison with other MPI point-to-point and one-sided approaches. Specifically, we first investigate two scenarios commonly encountered for small partition sizes in a multithreaded environment: thread contention and overhead of using many partitions. We propose two solutions to alleviate the measured penalty and demonstrate their use. We then focus on large messages and the gain obtained when exploiting the delay resulting from computations or load imbalance. We conclude with our perspectives on the benefits of partitioned communication and the various results obtained

Quantitative prediction of palaeo-uplift reservoir control and favorable reservoir formation zones in Lufeng Depression

In this paper, taking the Lufeng Depression as the study object, the distribution characteristics and reservoir-controlling conditions of palaeo-uplift are analyzed from both qualitative and quantitative perspectives. The distribution characteristics of the three-level palaeo-uplift structural pattern are elucidated, which show that the palaeo-uplifts went through three structural evolutionary stages: Eocene, Early-Middle Miocene, and Late Miocene, with long-term inherited development characteristics. Palaeo-uplift controls the distribution of hydrocarbon planes, the direction of dominant hydrocarbon transport, the development of various traps, and the types of hydrocarbon reservoirs. Applying the principle and method of “multi-element matching reservoir formation model”, the corresponding geological and mathematical models are established, which indicate that 86.29% of the number of reservoirs are distributed on the top and slope of the palaeo-uplift, and the reserves and number decrease with the distance to the top of the palaeo-uplift. Based on the palaeo-uplift control model, four high-probability areas for palaeo-uplift control in the Wenchang and Enping Fms are predicted, which are mainly located in the Lufeng middle-low uplift, the Dongsha uplift, and uplifts within the depression.Cited as: Guo, B., Yu, F., Wang, Y., Li, H., Li, H., Wu, Z. Quantitative prediction of palaeo-uplift reservoir control and favorable reservoir formation zones in Lufeng Depression. Advances in Geo-Energy Research, 2022, 6(5): 426-437. https://doi.org/10.46690/ager.2022.05.0

A robotic arm control system with simultaneous and sequential modes combining eye-tracking with steady-state visual evoked potential in virtual reality environment

At present, single-modal brain-computer interface (BCI) still has limitations in practical application, such as low flexibility, poor autonomy, and easy fatigue for subjects. This study developed an asynchronous robotic arm control system based on steady-state visual evoked potentials (SSVEP) and eye-tracking in virtual reality (VR) environment, including simultaneous and sequential modes. For simultaneous mode, target classification was realized by decision-level fusion of electroencephalography (EEG) and eye-gaze. The stimulus duration for each subject was non-fixed, which was determined by an adjustable window method. Subjects could autonomously control the start and stop of the system using triple blink and eye closure, respectively. For sequential mode, no calibration was conducted before operation. First, subjects’ gaze area was obtained through eye-gaze, and then only few stimulus blocks began to flicker. Next, target classification was determined using EEG. Additionally, subjects could reject false triggering commands using eye closure. In this study, the system effectiveness was verified through offline experiment and online robotic-arm grasping experiment. Twenty subjects participated in offline experiment. For simultaneous mode, average ACC and ITR at the stimulus duration of 0.9 s were 90.50% and 60.02 bits/min, respectively. For sequential mode, average ACC and ITR at the stimulus duration of 1.4 s were 90.47% and 45.38 bits/min, respectively. Fifteen subjects successfully completed the online tasks of grabbing balls in both modes, and most subjects preferred the sequential mode. The proposed hybrid brain-computer interface (h-BCI) system could increase autonomy, reduce visual fatigue, meet individual needs, and improve the efficiency of the system