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    Provided is a method for isolating a mammal early follicle to obtain a single oocyte and a single granulocyte. The method is capable of isolating a mammal early follicle to obtain an active single oocyte and a corresponding granulocyte thereof. Further provided is a kit for obtaining a single oocyte and a single granulocyte thereof from a mammal early follicle.
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    Various embodiments include methods for data management in a computing device utilizing a plurality of processing units. Embodiment methods may include generating a data transfer heuristic model based on measurements from a plurality of sample data transfers between a plurality of data storage units. The generated data transfer heuristic model may be used to calculate data transfer costs for each of a plurality of tasks. The calculated data transfer costs may be used to schedule execution of the plurality of tasks in an execution order on selected ones of the plurality of processing units. The data transfer heuristic model may be updated based on measurements of data transfers occurring during the executions of the plurality of tasks (e.g., time, power consumption, etc.). Code executing on the processing units may indicate to a runtime when certain data blocks are no longer needed and thus may be evicted and/or pre-fetched for others.
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    Aspects include computing devices, systems, and methods for implementing scheduling and execution of lightweight kernels as simple tasks directly by a thread without setting up a task structure. A computing device may determine whether a task pointer in a task queue is a simple task pointer for the lightweight kernel. The computing device may schedule a first simple task for the lightweight kernel for execution by the thread. The computing device may retrieve, from an entry of a simple task table, a kernel pointer for the lightweight kernel. The entry in the simple task table may be associated with the simple task pointer. The computing device may directly execute the lightweight kernel as the simple task.
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    A signal monitoring method and apparatus for a wavelength selective switch (WSS). The method comprises: according to an input WDM signal, encoding a phase of a first optical engine, so that the WDM signal is split into a transmission signal and a monitoring signal after passing through the first optical engine; inputting the monitoring signal to a second optical engine arranged at an output side optical grating; and controlling the second optical engine so that same rotates in a wavelength plane of the WDM signal, so that monitoring light with a set wavelength in the monitoring signal is output from the second optical engine at a pre-set angle. The method and apparatus provided in the present invention solve the problems in the prior art that a monitoring scheme for an optical signal is time-consuming and a quick fault positioning requirement for a future network cannot be satisfied.
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    Provided is a method for screening a biomarker related to severe oligoasthenospermia. The method comprises firstly carrying out mass spectrometry on non-coding amino acids of multiple groups of sperm proteins in the case of severe oligoasthenospermia by means of a NanoHPLC-MS/MS mass spectrometry system and an non-labelled quantitative proteomics method; then searching for the mass spectrometry data by means of a non-limiting amino acid protein modification analysis method, and carrying out multivariable Gaussian mixture distribution clustering analysis to identify the non-coding amino acids in the sperm protein groups to the greatest possible extent; and finally, comparing the non-coding amino acids of normal and patient sperm protein groups to obtain non-coding amino acid sites of the protein related to severe oligoasthenospermia, wherein same are thereby used as molecular markers of severe oligoasthenospermia. The method provides new diagnostic and therapeutic targets for severe oligoasthenospermia.
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    Provided are an optical signal transmission method and device, and a wavelength selective switch. The method comprises: performing diffraction processing on an input optical signal to obtain signal light and cross-talk light, wherein the signal light is used for being output to a target output port in a plurality of output ports; and the diffraction processing comprises: deflecting, in a second direction, a diffraction direction of a part of or the whole of the cross-talk light, so as to output the part of or the whole of the cross-talk light to an area excepting the output ports.
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  • Simulation Model and Method for Active Torsional Vibration Control of an HEV

    Zhong, Biqing   Deng, Bin   Zhao, Han  

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    Some embodiments include apparatuses and methods having a memory cell string including memory cells located in different levels of the apparatus and a data line coupled to the memory cell string. The memory cell string includes a pillar body associated with the memory cells. At least one of such apparatus can include a module configured to store information in a memory cell among memory cells and/or to determine a value of information stored in a memory cell among memory cells. The module can also be configured to apply a voltage having a positive value to the data line and/or a source to control a potential of the body. Other embodiments are described.
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    Various embodiments proactively balance workloads between a plurality of processing units of a multi-processor computing device by making work-stealing determinations based on operating state data. An embodiment method includes obtaining static characteristics data associated with each of a victim processor and one or more of a plurality of processing units that are ready to steal work items from the victim processor (work-ready processors), obtaining dynamic characteristics data for each of the processors, calculating priority values for each of the processors based on the obtained data, and transferring a number of work items assigned to the victim processor to a winning work-ready processor based on the calculated priority values. In some embodiments, the method may include acquiring control over a probabilistic lock for a shared data structure and updating the shared data structure to indicate the number of work items transferred to the winning work-ready processor.
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  • Smart hydrogels with high tunability of stiffness as a biomimetic cell carrier

    Zhao, Han   Xu, Kang   Zhu, Peng   Wang, Chunli   Chi, Qingjia  

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  • Exceptional point engineered glass slide for microscopic thermal mapping

    Zhao, Han   Chen, Zhaowei   Zhao, Ruogang   Feng, Liang  

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    Methods, devices, and non-transitory process-readable storage media for dynamically adapting a frequency for detecting work-stealing operations in a multi-processor computing device. A method according to various embodiments and performed by a processor includes determining whether any work items of a cooperative task have been reassigned from a first processing unit to a second processing unit, calculating a chunk size using a default equation in response to determining that no work items of the cooperative task have been reassigned from the first processing unit, calculating the chunk size using a victim equation in response to determining that one or more work items of the cooperative task have been reassigned from the first processing unit, and executing a set of work items of the cooperative task that correspond to the calculated chunk size.
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  • Co-Simulation of Radar Antenna Azimuth Based on Adams and Simulink

    Zhao, Han   Wu, Guan Hong   Zong, Wei  

    Large antenna is susceptible to external influence in the actual work load; it causes the azimuth change and affects the radar work. In order to solve this problem, Adams and Simulink co-simulation method and the antenna board PID control are used. Simulation results show that angular variation of the callback can be achieved, and the response time can be greatly reduced less than 2 seconds.
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  • Controlling Uncertain Swarm Mechanical Systems: A β-Measure Based Approach

    Zhao, Xiaomin   Chen, Ye-Hwa   Dong, Fangfang   Zhao, Han  

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  • Exploring Fine-Grained Resource Rental Planning in Cloud Computing

    Zhao, Han   Pan, Miao   Liu, Xinxin   Li, Xiaolin   Fang, Yuguang  

    Application services based on cloud computing infrastructure are proliferating over the Internet. In this paper, we investigate the problem of how to minimize cloud resource rental cost associated with hosting such cloud-based application services, while meeting the projected service demand. This problem arises when applications generate high volume of data that incurs significant cost on storage and transfer. As a result, an application service provider (ASP) needs to carefully evaluate various resource rental options before finalizing the application deployment. We choose Amazon EC2 marketplace as a case of study, and analyze the economical trade-off for on-demand resource rental strategies. Given fixed resource pricing, we first develop a deterministic model, using a mixed integer linear program, to facilitate resource rental decision making. Evaluation results show that our planning optimization model reduces resource rental cost by as much as 50 percent compared with a baseline strategy. Next, we further investigate planning solutions to resource market featuring time-varying pricing (Amazon Spot Instance Market). We perform time-series analysis over the spot price trace and examine its predictability using auto-regressive integrated moving-average (ARIMA). We also develop a stochastic planning model based on multistage recourse. By comparing these two approaches, we discover that spot price forecasting does not provide our planning model with a crystal ball due to the weak correlation of past and future price, and the stochastic planning model better hedges against resource pricing uncertainty than resource rental planning using forecast prices.
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  • Towards efficient and fair resource trading in community-based cloud computing

    Zhao, Han   Liu, Xinxin   Li, Xiaolin  

    In this paper, we investigate the resource trading problem in a community-based cloud computing setting where multiple tenants communicate in a peer-to-peer (P2P) fashion. Enabling resource trading in a community cloud unleashes the untapped cloud resources, thus presents a flexible solution for managing resource allocation. However, finding an efficient and fair resource allocation is challenging mainly due to the heterogeneity of tenants. Our work first develops a market-oriented model to support resource negotiation and trading. Based on this model, we adopt a multiagent-based technique that allows a group of autonomous tenants to reach an efficient and fair resource allocation. Further, when budget constraint presents, we propose a directed hypergraph model to facilitate resource trading amongst heterogeneous tenants. We analyze the application of the directed hypergraph model to trading decision making, and design a series of heuristic-based resource trading protocols for both budget-unaware and budget-aware scenarios. The performances of the proposed protocols are validated through simulations. The results are in tune with the theoretical analysis and provide insights into practical application issues. Published by Elsevier Inc.
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