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BACKGROUND
Triflumezopyrim (TFM), a novel mesoionic insecticide, has high efficiency at a low dosage, and is mainly used to control hopper species. A previous study demonstrated that seed dressing with TFM effectively controlled rice planthopper populations in mechanically transplanted rice fields; however, mode of action for control was unclear.
RESULTS
The study shows that seed dressing with...
Stem cell leukemia/lymphoma syndrome (SCLL) is driven by constitutive activation of chimeric FGFR1 kinases generated by chromosome translocations. We have shown that FGFR inhibitors significantly suppress leukemia and lymphoma development in vivo, and cell viability in vitro. Since resistance to targeted therapies is a major reason for relapse, we developed FGFR1‐overexpressing mouse and human cell...
From the analysis of belt conveyor power design method based on the DIN22101 standard, the main factors affecting the energy consumption of the system were educed. Meanwhile, an experiment rig of a belt conveyor and parameters measurement devices were designed and built, and the principles for measuring these parameters were analyzed. After that, the energy consumption laws of the system were investigated...
Matrix-vector multiplication, as a key computing operation, has been largely adopted in applications and hence greatly affects the execution efficiency. A common technique to enhance the performance of matrix-vector multiplication is increasing execution parallelism, which results in higher design cost. In recent years, new devices and structures have been widely investigated as alternative solutions...
We demonstrate an approach to build a selector into ReRAM (memristors) using engineered materials. In this approach, a segment(s) of “nonlinear material” is self-assembled into the conduction channel (s) (filament) of a memristor. The nonlinear material exhibits a highly nonlinear current-voltage characteristic, which gives rise to a nonlinear i-v characteristic of the memristor in the ON state.
The applications of memristors in neuromorphic computing have been extensively studied for its analogy to synapse. To overcome sneak path issue, nonlinear resistive selectors have been introduced to the design of memristor crossbar, enabling a high integration density and robust computing capability. However, the nonlinearity of such selectors also influences the computation accuracy of the vector-matrix...
With the rapid growth of big-data applications, advanced data processing technologies, e.g., machine learning, are widely adopted in many industry fields. Although these technologies demonstrate powerful data analyzing and processing capability, there exist some security concerns that may potentially expose the user/owner of the services to information safety risk. In particular, the adoption of neuromorphic...
Modern smart surveillance systems can not only record the monitored environment but also identify the targeted objects and detect anomaly activities. These advanced functions are often facilitated by deep neural networks, achieving very high accuracy and large data processing throughput. However, inappropriate design of the neural network may expose such smart systems to the risks of leaking the target...
Neuromorphic architectures are widely used in many applications for advanced data processing, and often implements proprietary algorithms. In this work, we prevent an attacker with physical access from learning the proprietary algorithm implemented by the neuromorphic hardware. For this purpose, we leverage the obsolescence effect in memristors to judiciously reduce the accuracy of outputs for any...
Energy consumption is the key indicator of speed control technology for improving energy efficiency of belt conveyor systems. This paper presents the design and verification of a short-term mathematical model intended for the prediction of energy consumption of a belt conveyor system using neural network method. The obtained model corresponds with real operational conditions. It can take advantage...
As process technology continues scaling down, the memory barrier becomes more severe. Thus, spiking neuromorphic computing that can significantly enhance computing and communication efficiencies has been widely studied. Both conventional CMOS technology and emerging devices have been used in hardware implementation of spiking neuromorphic computing. Particularly, the memristor technology that can...
The explosion of big data applications imposes severe challenges of data processing speed and scalability on traditional computer systems. However, the performance of the von Neumann machine is greatly hindered by the increasing performance gap between CPU and memory, motivating the active research on new or alternative computing architectures. As one important instance, neuromorphic computing systems...
Neuromorphic computing system (NCS) is a promising architecture to combat the well-known memory bottleneck in Von Neumann architecture. The recent breakthrough on memristor devices made an important step toward realizing a low-power, small-footprint NCS on-a-chip. However, the currently low manufacturing reliability of nano-devices and the voltage IR-drop along metal wires and memristors arrays severely...
Two very different approaches to theoretical description of interaction of high-pressure arc plasmas with refractory cathodes exist in the literature. One group of researchers believes that space-charge effects on refractory cathodes are small and contribute to the arc voltage no more than one or two volts. Accordingly, these researchers use simulation models which are based on the assumption of quasi-neutrality,...
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