A Two-Wheeled Self-Balancing Robot with the Fuzzy PD Control Method

A two-wheeled self-balancing robot with a fuzzy PD control method is described and analyzed as an example of a high-order, multiple-variable, nonlinear, strong-coupling, and unstable system. Based on a system structure model, a kinetic equation is constructed using Newtonian dynamics and mechanics. After a number of simulation experiments, we get the best , , and state-feedback matrices. Then a fuzzy PD controller is designed for which the position and speed of the robot are inputs and for which the angle and angle rate of the robot are controlled by a PD controller. Finally, this paper describes a real-time control platform for the two-wheeled self-balancing robot that controls the robot effectively, after some parameter debugging. The result indicates that the fuzzy PD control algorithm can successfully achieve self-balanced control of the two-wheeled robot and prevent the robot from falling

Strip-MLP: Efficient Token Interaction for Vision MLP

Token interaction operation is one of the core modules in MLP-based models to exchange and aggregate information between different spatial locations. However, the power of token interaction on the spatial dimension is highly dependent on the spatial resolution of the feature maps, which limits the model's expressive ability, especially in deep layers where the feature are down-sampled to a small spatial size. To address this issue, we present a novel method called \textbf{Strip-MLP} to enrich the token interaction power in three ways. Firstly, we introduce a new MLP paradigm called Strip MLP layer that allows the token to interact with other tokens in a cross-strip manner, enabling the tokens in a row (or column) to contribute to the information aggregations in adjacent but different strips of rows (or columns). Secondly, a \textbf{C}ascade \textbf{G}roup \textbf{S}trip \textbf{M}ixing \textbf{M}odule (CGSMM) is proposed to overcome the performance degradation caused by small spatial feature size. The module allows tokens to interact more effectively in the manners of within-patch and cross-patch, which is independent to the feature spatial size. Finally, based on the Strip MLP layer, we propose a novel \textbf{L}ocal \textbf{S}trip \textbf{M}ixing \textbf{M}odule (LSMM) to boost the token interaction power in the local region. Extensive experiments demonstrate that Strip-MLP significantly improves the performance of MLP-based models on small datasets and obtains comparable or even better results on ImageNet. In particular, Strip-MLP models achieve higher average Top-1 accuracy than existing MLP-based models by +2.44\% on Caltech-101 and +2.16\% on CIFAR-100. The source codes will be available at~\href{https://github.com/Med-Process/Strip_MLP{https://github.com/Med-Process/Strip\_MLP}

Synthesis of a magnetic π-extended carbon nanosolenoid with Riemann surfaces

Riemann surfaces are deformed versions of the complex plane in mathematics. Locally they look like patches of the complex plane, but globally, the topology may deviate from a plane. Nanostructured graphitic carbon materials resembling a Riemann surface with helicoid topology are predicted to have interesting electronic and photonic properties. However, fabrication of such processable and large π-extended nanographene systems has remained a major challenge. Here, we report a bottom-up synthesis of a metal-free carbon nanosolenoid (CNS) material with a low optical bandgap of 1.97 eV. The synthesis procedure is rapid and possible on the gram scale. The helical molecular structure of CNS can be observed by direct low-dose high-resolution imaging, using integrated differential phase contrast scanning transmission electron microscopy. Magnetic susceptibility measurements show paramagnetism with a high spin density for CNS. Such a π-conjugated CNS allows for the detailed study of its physical properties and may form the base of the development of electronic and spintronic devices containing CNS species

The Long Noncoding RNA TUG1 Promotes Laryngeal Cancer Proliferation and Migration

Background/Aims: Researchers have shown that long noncoding RNAs are closely associated with the pathogenesis of laryngeal squamous cell carcinoma (LSCC). However, the role of the long noncoding RNA taurine-upregulated gene 1 (TUG1) in the pathogenesis of LSCC remains unclear, although it is recognized as an oncogenic regulator for several types of squamous cell carcinoma. Methods: qRT-PCR was performed to measure the expression of TUG1 in LSCC tissues and cell lines. 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) was used to measure the effect of TUG1 on cell proliferation. Transwell assay and flow cytometry were employed to determine the effect of TUG1 on cell migration and invasion. Western-blot were performed to explore the relation of TUG1 and p53 mRNA. Results: Higher TUG1 expression in LSCC than in paired normal tumor-adjacent tissue specimens (N = 64) was observed using quantitative real-time polymerase chain reaction. Also, high TUG1 expression was positively associated with advanced T category, worse lymph node metastasis and late clinical stage. Furthermore, in vitro experiments demonstrated that silencing of TUG1 markedly inhibited proliferation, cell-cycle progression, migration, and invasion of LSCC cells, whereas depletion of TUG1 led to increased apoptosis. Conclusion: These findings demonstrated that upregulated TUG1 expression exerted oncogenic effects by promoting proliferation, migration, and invasion, and inhibiting apoptosis in LSCC cells

Influence of contouring the lithium metal/solid electrolyte interface on the critical current for dendrites

Contouring or structuring of the lithium/ceramic electrolyte interface and therefore increasing its surface area has been considered as a possible strategy to increase the charging current in solid-state batteries without lithium dendrite formation and short-circuit. By coupling together lithium deposition kinetics and the me chanics of lithium creep within calculations of the current distribution at the interface, and leveraging a model for lithium dendrite growth, we show that efforts to avoid dendrites on charging by increasing the interfacial surface area come with significant limitations associated with the topography of rough surfaces. These limitations are sufficiently severe such that it is very unlikely contouring could increase charging currents while avoiding dendrites and short-circuit to the levels required. For example, we show a sinusoidal surface topography can only raise the charging current before dendrites occur by approx. 50% over a flat interface

Influence of contouring the lithium metal/solid electrolyte interface on the critical current for dendrites

Contouring or structuring of the lithium/ceramic electrolyte interface and therefore increasing its surface area has been considered as a possible strategy to increase the charging current in solid-state batteries without lithium dendrite formation and short-circuit. By coupling together lithium deposition kinetics and the me chanics of lithium creep within calculations of the current distribution at the interface, and leveraging a model for lithium dendrite growth, we show that efforts to avoid dendrites on charging by increasing the interfacial surface area come with significant limitations associated with the topography of rough surfaces. These limitations are sufficiently severe such that it is very unlikely contouring could increase charging currents while avoiding dendrites and short-circuit to the levels required. For example, we show a sinusoidal surface topography can only raise the charging current before dendrites occur by approx. 50% over a flat interface

Sequential experimental design approaches to helicopter rotor tuning

Two different approaches based on sequential experimental design concepts have been studied for helicopter rotor tuning, which is the process of adjusting the rotor blades so as to reduce the aircraft vibration and the spread of rotors. One uses an interval model adapted sequentially to improve the search for the blade adjustments. The other uses a probability model to search for the blade adjustments with the maximal probability of success. In the first approach, an interval model is used to represent the range of effect of blade adjustments on helicopter vibration, so as to cope with the nonlinear and stochastic nature of aircraft vibration. The coefficients of the model are initially defined according to sensitivity coefficients between the blade adjustments and helicopter vibration, to include the expert knowledge of the process. The model coefficients are subsequently transformed into intervals and updated after each tuning iteration to improve the model\u27s estimation accuracy. The search for the blade adjustments is performed according to this model by considering the vibration estimates of all of the flight regimes so as to provide a comprehensive solution for rotor tuning. The second approach studied uses a probability model to maximize the likelihood of success of the selected blade adjustments. The underlying model in this approach consists of two segments: a deterministic segment to include a linear regression model representing the relationships between the blade adjustments and helicopter vibration, and a stochastic segment to comprise probability densities of the vibration components. The blade adjustments with the maximal probability of generating acceptable vibration are selected as recommended adjustments. The effectiveness of the proposed approaches is evaluated in simulation based on a series of neural networks trained with actual vibration data. To incorporate the stochastic behavior of the helicopter vibration and better simulate the tuning process, the probability density function of the prediction error is used to simulate noise. Due to the stochastics of the helicopter vibration, the proposed approaches cannot be evaluated by deterministic measures. Therefore, several performance measures have been devised to represent the various aspects of helicopter rotor tuning as the evaluation criteria

Rail Quality Based Index

The aim of this thesis is to establish an integrated rail quality based index to evaluate different freight wagons’ performance. All materials are collected through literature reviews and interviews. The Rail Quality Based Index (RQBI) is established in the form of cost that can represent the main quality aspects associated with freight wagons self-characteristics. The index construction includes four main components, i.e. infrastructure, energy, maintenance and noise. Each component’s cost can be calculated by applying different methods from previous studies. By comparing index value with benchmark, the RQBI can help different parties in rail freight industry to evaluate and compare their freight wagons quality performance. This research concludes costs differentiated by wagons’ characteristics and tries to represent them in an integrated index’s form. Though, due to data deficiency, validation of the index and establishment of relevant benchmarks are not fully discussed in this research, it helps to further understand quality evaluation of freight wagons and points out a new perspective of future relevant researches

Comparison of WC/C nanocomposite films in load-bearing capacity via interface micro-cracks during tribology behavior: A feasible judgment mechanism

Comparison of WC/C nanocomposite films in load-bearing capacity via interface micro-cracks during tribology behavior: A feasible judgment mechanis