Estimating the number of neurons in multi-neuronal spike trains

A common way of studying the relationship between neural activity and behavior is through the analysis of neuronal spike trains that are recorded using one or more electrodes implanted in the brain. Each spike train typically contains spikes generated by multiple neurons. A natural question that arises is "what is the number of neurons $\nu$ generating the spike train?"; This article proposes a method-of-moments technique for estimating $\nu$. This technique estimates the noise nonparametrically using data from the silent region of the spike train and it applies to isolated spikes with a possibly small, but nonnegligible, presence of overlapping spikes. Conditions are established in which the resulting estimator for $\nu$ is shown to be strongly consistent. To gauge its finite sample performance, the technique is applied to simulated spike trains as well as to actual neuronal spike train data.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS371 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Vision-based neural network classifiers and their applications

A thesis submitted for the degree of Doctor of Philosophy of University of LutonVisual inspection of defects is an important part of quality assurance in many fields of production. It plays a very useful role in industrial applications in order to relieve human inspectors and improve the inspection accuracy and hence increasing productivity. Research has previously been done in defect classification of wood veneers using techniques such as neural networks, and a certain degree of success has been achieved. However, to improve results in tenus of both classification accuracy and running time are necessary if the techniques are to be widely adopted in industry, which has motivated this research. This research presents a method using rough sets based neural network with fuzzy input (RNNFI). Variable precision rough set (VPRS) method is proposed to remove redundant features utilising the characteristics of VPRS for data analysis and processing. The reduced data is fuzzified to represent the feature data in a more suitable foml for input to an improved BP neural network classifier. The improved BP neural network classifier is improved in three aspects: additional momentum, self-adaptive learning rates and dynamic error segmenting. Finally, to further consummate the classifier, a uniform design CUD) approach is introduced to optimise the key parameters because UD can generate a minimal set of uniform and representative design points scattered within the experiment domain. Optimal factor settings are achieved using a response surface (RSM) model and the nonlinear quadratic programming algorithm (NLPQL). Experiments have shown that the hybrid method is capable of classifying the defects of wood veneers with a fast convergence speed and high classification accuracy, comparing with other methods such as a neural network with fuzzy input and a rough sets based neural network. The research has demonstrated a methodology for visual inspection of defects, especially for situations where there is a large amount of data and a fast running speed is required. It is expected that this method can be applied to automatic visual inspection for production lines of other products such as ceramic tiles and strip steel

On neural spike sorting with mixture models

Ph.DDOCTOR OF PHILOSOPH

Profitability and Data-Snooping Tests of Four Technical Trade Strategies for Cryptocurrency Pair BTC/USDT and ETH/USDT in Cryptocurrency Markets During 2022–2023

We provide a comprehensive investigation into the profitability of technical trading methods applied to the cryptocurrency pairs BTC/USDT and ETH/USDT. By employing rigorous evaluations and incremental examinations, we address the pervasive issue of data-snooping bias that often plagues the evaluation of trading strategies. Our empirical results indicate the lack of profitable technical trading strategies in both the analysis sample and prediction sample periods, even after rigorous adjustments for data snooping. These findings highlight the difficulties associated with selecting profitable technical trading strategies in the dynamic and volatile cryptocurrency market. Market participants, including individual traders, institutional investors, and regulatory bodies, should take note of our findings when making investment decisions based on technical analysis

Dynamic analysis of a Leslie-Gower predator-prey model with the fear effect and nonlinear harvesting

In this paper, we investigate the stability and bifurcation of a Leslie-Gower predator-prey model with a fear effect and nonlinear harvesting. We discuss the existence and stability of equilibria, and show that the unique equilibrium is a cusp of codimension three. Moreover, we show that saddle-node bifurcation and Bogdanov-Takens bifurcation can occur. Also, the system undergoes a degenerate Hopf bifurcation and has two limit cycles (i.e., the inner one is stable and the outer is unstable), which implies the bistable phenomenon. We conclude that the large amount of fear and prey harvesting are detrimental to the survival of the prey and predator

Practical Distributed Control for VTOL UAVs to Pass a Tunnel

Unmanned Aerial Vehicles (UAVs) are now becoming increasingly accessible to amateur and commercial users alike. An air traffic management (ATM) system is needed to help ensure that this newest entrant into the skies does not collide with others. In an ATM, airspace can be composed of airways, intersections and nodes. In this paper, for simplicity, distributed coordinating the motions of Vertical TakeOff and Landing (VTOL) UAVs to pass an airway is focused. This is formulated as a tunnel passing problem, which includes passing a tunnel, inter-agent collision avoidance and keeping within the tunnel. Lyapunov-like functions are designed elaborately, and formal analysis based on invariant set theorem is made to show that all UAVs can pass the tunnel without getting trapped, avoid collision and keep within the tunnel. What is more, by the proposed distributed control, a VTOL UAV can keep away from another VTOL UAV or return back to the tunnel as soon as possible, once it enters into the safety area of another or has a collision with the tunnel during it is passing the tunnel. Simulations and experiments are carried out to show the effectiveness of the proposed method and the comparison with other methods

Antibody-Targeted Immunocarriers for Cancer Treatment

Nanocarrier’s engineering based on fine chemical design and novel structural tailoring can provide practical solution to solve the problems in traditional cancer immunotherapy. Nanoimmunotherapy is thus defined as the application and further development of novel nanocarriers for enhancing immunotherapy. It has become one of the most intriguing fields due to its unique power in treatment and even cure of cancer since reported in last year. Herein, this chapter illustrates the state-of-the-art development in antibody engineering and cancer immunotherapy and gives an explanation why functional nanocarries including micelles and liposomes can be efficient for nanoimmunotherapy. We further illustrate how to promote the nanoimmunotherapy by the chemical design and carrier’s engineering for the first time

Investigating the Motivations and Constraints of Chinese Peer-to-Peer Accommodation Hosts

Purpose – This research aims to identify peer-to-peer (P2P) accommodation hosts’ perceived motivations and constraints, to examine the prediction of the motivation and constraint factors on hosts’ intention to continue business based on hosts’ attitudes, and to explore the moderating role of business scale. Design/methodology/approach – A scale for hosts’ perceived motivators and constraints was developed. Mixed methods were used to develop and analyse a conceptual framework for demonstrating how constraints and motivations influence hosts’ behavioural intentions. Findings from interviews with hosts interpretatively supported the survey results.Findings – Chinese hosts’ perceived constraints and motivators are identified and explained. The survey results indicate that constraints lower intention to continue one’s business and motivators heightens it. Motivators have a higher effect on attitudes and intentions than constraints do. Business scale was confirmed as a moderator in the constraint—attitude link but not in the motivator—attitude relationship.Practical implications – This paper offers policy implications for governments, online platforms and hosts in terms of establishing incentives and solving problems so that Chinese hosts can sustainably operate their businesses.Originality/value – This paper identifies constraints and motivators and develops a measurement scale for both simultaneously, which provides a holistic explanation of hosts’ attitude and behavioural intention. It also reveals the moderating role of business scale. In investigating the thoughts of existing hosts operating on global and local platforms in China, this paper complements the literature, which mainly focuses on the Western context and a single global platform

Insight Into the Binding Mechanism of p53/pDIQ-MDMX/MDM2 With the Interaction Entropy Method

The study of the p53-MDMX/MDM2 binding sites is a research hotspot for tumor drug design. The inhibition of p53-targeted MDMX/MDM2 has become an effective approach in anti-tumor drug development. In this paper, a theoretically rigorous and computationally accurate method, namely, the interaction entropy (IE) method, combined with the polarized protein-specific charge (PPC) force field, is used to explore the difference in the binding mechanism between p53-MDMX and p53-MDM2. The interaction of a 12mer peptide inhibitor (pDIQ), which is similar to p53 in structure, with MDMX/MDM2 is also studied. The results demonstrate that p53/pDIQ with MDM2 generates a stronger interaction than with MDMX. Compared to p53, pDIQ has larger binding free energies with MDMX and MDM2. According to the calculated binding free energies, the differences in the binding free energy among the four complexes that are obtained from the combination of PPC and IE are more consistent with the experimental values than with the results from the combination of the non-polarizable AMBER force field and IE. In addition, according to the decomposition of the binding free energy, the van der Waals (vdW) interactions are the main driving force for the binding of the four complexes. They are also the main source of the weaker binding affinity of p53/pDIQ-MDMX relative to p53/pDIQ-MDM2. Compared with p53-MDMX/MDM2, according to the analysis of the residue decomposition, the predicated total residue contributions are higher in pDIQ-MDMX/MDM2 than in p53-MDMX/MDM2, which explains why pDIQ has higher binding affinity than p53 with MDMX/MDM2. The current study provides theoretical guidance for understanding the binding mechanisms and designing a potent dual inhibitor that is targeted to MDMX/MDM2