Memristor Neural Network Design

Neural network, a powerful learning model, has archived amazing results. However, the current Von Neumann computing system–based implementations of neural networks are suffering from memory wall and communication bottleneck problems ascribing to the Complementary Metal Oxide Semiconductor (CMOS) technology scaling down and communication gap. Memristor, a two terminal nanosolid state nonvolatile resistive switching, can provide energy‐efficient neuromorphic computing with its synaptic behavior. Crossbar architecture can be used to perform neural computations because of its high density and parallel computation. Thus, neural networks based on memristor crossbar will perform better in real world applications. In this chapter, the design of different neural network architectures based on memristor is introduced, including spiking neural networks, multilayer neural networks, convolution neural networks, and recurrent neural networks. And the brief introduction, the architecture, the computing circuits, and the training algorithm of each kind of neural networks are presented by instances. The potential applications and the prospects of memristor‐based neural network system are discussed

Equilibrium price and optimal insider trading strategy under stochastic liquidity with long memory

In this paper, the Kyle model of insider trading is extended by characterizing the trading volume with long memory and allowing the noise trading volatility to follow a general stochastic process. Under this newly revised model, the equilibrium conditions are determined, with which the optimal insider trading strategy, price impact and price volatility are obtained explicitly. The volatility of the price volatility appears excessive, which is a result of the fact that a more aggressive trading strategy is chosen by the insider when uninformed volume is higher. The optimal trading strategy turns out to possess the property of long memory, and the price impact is also affected by the fractional noise.Comment: 21 pages; 2 figure

A Stochastic Simulation Procedure for Selecting Herbicides with Minimum Environmental Impact

A mathematical environmental transport model of roadside applied herbicides at the site scale (∼100 m) was stochastically applied using a Monte-Carlo technique to simulate the concentrations of 33 herbicides in stormwater runoff. Field surveys, laboratory sorption data, and literature data were used to generate probability distribution functions for model input parameters to allow extrapolation of the model to the regional scale. Predicted concentrations were compared to EPA acute toxicity end points for aquatic organisms to determine the frequency of potentially toxic outcomes. Results are presented for three geographical regions in California and two highway geometries. For a given herbicide, frequencies of potential toxicity (FPTs) varied by as much as 36% between region and highway type. Of 33 herbicides modeled, 16 exhibit average FPTs greater than 50% at the maximum herbicide application rate, while 20 exhibit average FPTs less than 50% at the minimum herbicide application rate. Based on these FPTs and current usage statistics, selected herbicides were determined to be more environmentally acceptable than others in terms of acute toxicity and other documented environmental effects. This analysis creates a decision support system that can be used to evaluate the relative water quality impacts of varied herbicide application practices

An analytical approximation of European option prices under a hybrid GARCH-Vasicek model with double exponential jump in the bid-ask price economy

Conic finance theory, which has been developed over the past decade, replaces classical one-price theory with the bid-ask price economy in option pricing since the one-price principle ignores the bid-ask spread created by market liquidity. Within this framework, we investigate the European option pricing problem when stochastic interest rate, stochastic volatility, and double exponential jump are all taken into account. We show that the corresponding bid and ask prices can be formulated into a semi-analytical form with the Fourier-cosine method once the solution to the characteristic function is obtained. Some interesting properties regarding the new results are displayed via numerical implementation

An Open and Comprehensive Pipeline for Unified Object Grounding and Detection

Grounding-DINO is a state-of-the-art open-set detection model that tackles multiple vision tasks including Open-Vocabulary Detection (OVD), Phrase Grounding (PG), and Referring Expression Comprehension (REC). Its effectiveness has led to its widespread adoption as a mainstream architecture for various downstream applications. However, despite its significance, the original Grounding-DINO model lacks comprehensive public technical details due to the unavailability of its training code. To bridge this gap, we present MM-Grounding-DINO, an open-source, comprehensive, and user-friendly baseline, which is built with the MMDetection toolbox. It adopts abundant vision datasets for pre-training and various detection and grounding datasets for fine-tuning. We give a comprehensive analysis of each reported result and detailed settings for reproduction. The extensive experiments on the benchmarks mentioned demonstrate that our MM-Grounding-DINO-Tiny outperforms the Grounding-DINO-Tiny baseline. We release all our models to the research community. Codes and trained models are released at https://github.com/open-mmlab/mmdetection/tree/main/configs/mm_grounding_dino.Comment: 10 pages, 6 figure

α-Synuclein: A Multifunctional Player in Exocytosis, Endocytosis, and Vesicle Recycling

α-synuclein (α-Syn) is a presynaptic enriched protein involved in the pathogenesis of Parkinson’s disease. However, the physiological roles of α-Syn remain poorly understood. Recent studies have indicated a critical role of α-Syn in the sensing and generation of membrane curvature during vesicular exocytosis and endocytosis. It has been known to modulate the assembly of SNARE complex during exocytosis including vesicle docking, priming and fusion steps. Growing evidence suggests that α-Syn also plays critical roles in the endocytosis of synaptic vesicles. It also modulates the availability of releasable vesicles by promoting synaptic vesicles clustering. Here, we provide an overview of recent progresses in understanding the function of α-Syn in the regulation of exocytosis, endocytosis, and vesicle recycling under physiological and pathological conditions

Formation of TiC via interface reaction between diamond grits and Sn-Ti alloys at relatively low temperatures

In this paper, interfacial reaction between diamond grit and Sn-6Ti alloy was systematically studied at brazing temperatures from 600 to 1030 °C. A thin and uniform layer of scallop-like nano-sized TiC grains was formed after brazing for 30 min at 600 °C, and interfacial TiC grains subsequently coarsened as brazing temperature increased to 740 and 880 °C. Strip-like columnar TiC grains in a bilayer structure was further grown as brazing temperature increased to 930 °C. After brazing at 1030 °C, a dense layer of columnar TiC grains were formed. Based on the TEM micrographs of interfacial TiC, the formation and evolution of the growth morphologies of interfacial TiC was believed to be controlled by the diffusion of C flux from diamond grits, which is dependent on the brazing temperatures

Response of riparian vegetation to water-table changes in the lower reaches of Tarim River, Xinjiang Uygur, China

The lower reaches of Tarim River in the Xinjiang Uygur region of western China had been dried out for more than 30 years before water began to be diverted from Konqi (Peacock) River via a 927-km-long channel in year 2000, aimed at improving the riparian ecological systems. Since then, eight intermittent water deliveries have been carried out. To evaluate the response of riparian vegetation to these operations, the groundwater regime and vegetation changes have been monitored along the 350-km-long stem of the river using a network of 40 dug wells at nine transects across the river and 30 vegetation plots at key sites. Results show that the water table rose remarkably, i.e. from a depth of 9.87m before the water delivery to 3.16m after the third water delivery. The lateral distance of affected water table extended to 1,050m from the riverbank after the fourth water delivery. The riparian vegetation has changed in composition, type, distribution, and growing behavior. This shows that the water deliveries have had significant effects on restoration of riparian ecosystems