Electron transfer mechanisms, characteristics and applications of biological cathode microbial fuel cells – A mini review

AbstractSince the microbial fuel cells (MFCs) research in the laboratory has reached an unprecedented success, it has raised a research upsurge internationally in recent years. However, compared with laboratory studies, the widespread applications of the conventional MFCs were restrained by the limitations of high cost and low efficiency. This stimulates researchers to overcome the obstacles. In this condition, bio-cathodes attracted their great interests. This paper is a brief review about the experimental progress of bio-cathodes in microbial fuel cells with an emphasis on the classification according to the final electron acceptors and the comparison with the traditional abiotic cathode MFCs. Bio-cathodes are feasible in removing nutrient in wastewater treatment and being used as biosensors in bioremediation. Presently, tremendous efforts are being made in investigating appropriate electrodes and dominant strains to achieve the effective practical applications

Quantum Entanglement in the S=1/2 Spin Ladder with Ring Exchange

In this paper we study the concurrence and the block-block entanglement in the $S=1/2$ spin ladder with four-spin ring exchange by the exact diagonalization method of finite cluster of spins. The relationship between the global phase diagram and the ground-state entanglement is investigated. It is shown that the block-block entanglement of different block size and geometry manifests richer information of the system. We find that the extremal point of the two-site block-block entanglement on the rung locates a transition point exactly due to SU(4) symmetry at this point. The scaling behavior of the block-block entanglement is discussed. Our results suggest that the block-block entanglement can be used as a convenient marker of quantum phase transition in some complex spin systems.Comment: 5 pages, 7 figure

3-(tert-But­oxy­carbon­yl)-2-(4-chloro­phen­yl)-1,3-thia­zolidine-4-carb­oxy­lic acid. Corrigendum

Corrigendum to Acta Cryst. (2010), E66, o2633

Study of an Improved Fuzzy Direct Torque Control of Induction Motor

The conventional direct torque control will inevitably produce torque ripple because of its way of flux estimates. For the purpose of handling this problem, a new control strategy was presented in this paper. This strategy combined subdivides control with voltage vector and fuzzy logic control in traditional direct torque control. In this model, the fuzzy logic combined the phase angle of the flux, the flux error and torque error as fuzzy variables and classified these fuzzy variables, in order to optimize the choice of voltage space vector, and the same time the traditional PID regulator is replaced by a fuzzy regulator. Simulation results show that, a great improvement torque responses , a great reduction of torque ripples is achieved and the strategy has a better dynamic and steady performance, especially in low-speed area

Exploring Boarding Strategies for High-Speed Railway

In light of the increasing demand for passenger transportation on high-speed railway (HSR), the pedestrian flow at HSR stations has become quite crowded in many countries, which has attracted researchers to study the HSR boarding behavior. In this paper, we propose three boarding strategies based on the features of the boarding behavior at an origin HSR station; we then use a cellular automaton (CA) model to study the impacts of boarding strategies on each passenger’s motion during the boarding process at HSR station. The simulation results indicate that some of the three strategies can optimize some passengers’ boarding time and relieve the congestion degree, and the positive impacts on the boarding process are the most prominent when the three strategies are used simultaneously. The results can help administrators to effectively organize the boarding process at the origin HSR station

Comfort-driven disparity adjustment for stereoscopic video

Pixel disparity—the offset of corresponding pixels between left and right views—is a crucial parameter in stereoscopic three-dimensional (S3D) video, as it determines the depth perceived by the human visual system (HVS). Unsuitable pixel disparity distribution throughout an S3D video may lead to visual discomfort. We present a unified and extensible stereoscopic video disparity adjustment framework which improves the viewing experience for an S3D video by keeping the perceived 3D appearance as unchanged as possible while minimizing discomfort. We first analyse disparity and motion attributes of S3D video in general, then derive a wide-ranging visual discomfort metric from existing perceptual comfort models. An objective function based on this metric is used as the basis of a hierarchical optimisation method to find a disparity mapping function for each input video frame. Warping-based disparity manipulation is then applied to the input video to generate the output video, using the desired disparity mappings as constraints. Our comfort metric takes into account disparity range, motion, and stereoscopic window violation; the framework could easily be extended to use further visual comfort models. We demonstrate the power of our approach using both animated cartoons and real S3D videos

Text-to-3D with Classifier Score Distillation

Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models. While the usage of classifier-free guidance is well acknowledged to be crucial for successful optimization, it is considered an auxiliary trick rather than the most essential component. In this paper, we re-evaluate the role of classifier-free guidance in score distillation and discover a surprising finding: the guidance alone is enough for effective text-to-3D generation tasks. We name this method Classifier Score Distillation (CSD), which can be interpreted as using an implicit classification model for generation. This new perspective reveals new insights for understanding existing techniques. We validate the effectiveness of CSD across a variety of text-to-3D tasks including shape generation, texture synthesis, and shape editing, achieving results superior to those of state-of-the-art methods. Our project page is https://xinyu-andy.github.io/Classifier-Score-DistillationComment: Our project page is https://xinyu-andy.github.io/Classifier-Score-Distillatio

Example-Guided Style-Consistent Image Synthesis from Semantic Labeling

Example-guided image synthesis aims to synthesize an image from a semantic label map and an exemplary image indicating style. We use the term “style” in this problem to refer to implicit characteristics of images, for example: in portraits “style” includes gender, racial identity, age, hairstyle; in full body pictures it includes clothing; in street scenes it refers to weather and time of day and such like. A semantic label map in these cases indicates facial expres- sion, full body pose, or scene segmentation. We propose a solution to the example-guided image synthesis problem us- ing conditional generative adversarial networks with style consistency. Our key contributions are (i) a novel style consistency discriminator to determine whether a pair of im- ages are consistent in style; (ii) an adaptive semantic con- sistency loss; and (iii) a training data sampling strategy, for synthesizing style-consistent results to the exemplar. We demonstrate the efficiency of our method on face, dance and street view synthesis tasks