Evidence for the Formation of Quasi-Bound-State in an Asymmetrical Quantum Point Contact

Features below the first conductance plateau in ballistic quantum point contacts (QPCs) are often ascribed to electron interaction and spin effects within the single mode limit. In QPCs with a highly asymmetric geometry, we observe sharp resonance peaks when the point contacts are gated to the single mode regime, and surprisingly, under certain gating conditions, a complete destruction of the 2e^2/h, first quantum plateau. The temperature evolution of the resonances suggest non-Fermi liquid behavior, while the overall nonlinear characterizations reveal features reminiscent of the 0.7 effect. We attribute these unusual behaviors to the formation of a quasi bound state, which is stabilized by a momentum-mismatch accentuated by asymmetry.Comment: 5 pages, 5 figure

Leber's Hereditary Optic Neuropathy: A Case Report

Leber's hereditary optic neuropathy (LHON) is a maternally inherited mitochondrial disease that primarily affects the optic nerve, causing bilateral vision loss in juveniles and young adults. A 12-year-old boy had complained of blurred vision in both eyes for more than 1 year. His best-corrected visual acuity was 0.08 in the right eye and 0.1 in the left. Ophthalmologic examination showed bilateral optic disc hyperemia and margin blurring, peripapillary telangiectasis, and a relative afferent pupil defect in his right eye. Fluorescein angiography showed no stain or leakage around the optic disc in the late phase. Visual field analysis showed central scotoma in the left eye and a near-total defect in the right. Upon examination of the patient's mitochondrial DNA, a point mutation at nucleotide position 11778 was found, and the diagnosis of LHON was confirmed. Coenzyme Q10 was used to treat the patient

A Case Report of a Metastatic Gastrointestinal Stromal Tumor Occurring in Femur

Gastrointestinal stromal tumors (GISTs) are mesenchymal neoplasms that most commonly affect the stomach or small intestine, but can occur anywhere throughout the gastrointestinal tract. To the best of our knowledge, few cases have been reported in the literature about the femur metastasis of GIST. This paper describes a metastasis of a gastrointestinal stromal tumour (GIST) to the femur in a 62-year-old male, 2 years after treatment for a gastric primary. There were no signs of tumor recurrence at followup after 12 mo. This case suggests that the femur can be a potential metastatic site of GIST

Building quantum neural networks based on swap test

Artificial neural network, consisting of many neurons in different layers, is an important method to simulate humain brain. Usually, one neuron has two operations: one is linear, the other is nonlinear. The linear operation is inner product and the nonlinear operation is represented by an activation function. In this work, we introduce a kind of quantum neuron whose inputs and outputs are quantum states. The inner product and activation operator of the quantum neurons can be realized by quantum circuits. Based on the quantum neuron, we propose a model of quantum neural network in which the weights between neurons are all quantum states. We also construct a quantum circuit to realize this quantum neural network model. A learning algorithm is proposed meanwhile. We show the validity of learning algorithm theoretically and demonstrate the potential of the quantum neural network numerically.Comment: 10 pages, 13 figure

A 2,2′-bipyridine-palladacycle catalyzed the coupling of arylboronic acids with nitroarenes

AbstractA novel palladium-catalyzed protocol for the synthesis of diaryl ethers derivatives has been developed. In the presence of 2,2′-bipyridine-cyclopalladated ferrocenylimine complex (Cat. Ic), diaryl ethers were selectively generated by adjusting reaction parameters through the coupling of arylboronic acids and nitroarenes with yields ranging from poor to good. The efficiency of this reaction was demonstrated by its compatibility with a range of groups. Moreover, the rigorous exclusion of air or moisture was not required in these transformations

Soundscape Evaluation Outside a Taoist Temple: A Case Study of Laojundong Temple in Chongqing, China

The unique architectural form and religious background of Taoist buildings can lead to a special acoustic environment, but there is a lack of research on the soundscape evaluation of Taoist buildings. Laojundong Taoist Temple was selected as the research site. The psychological and physiological responses of Taoist priests and ordinary people, and strategies for soundscape renovation were investigated by conducting field measurements, interviews, soundwalks, and audio–visual experiments. There was significant negative linear regression between the LAeq,5min and soundscape comfort (p < 0.01). The visual landscape comfort of ordinary people was notably correlated with landscape diversity (p < 0.01), whereas their soundscape comfort was markedly correlated with the degree of natural soundscape and audio–visual harmony (p < 0.01). The soundscape evaluation by Taoist priests was affected by their belief, activity types, social factors, and spatial positions. With the increasing proportion of the natural elements in the visual landscape in the temple, the acoustic comfort of Taoist priests and ordinary people significantly increased with the addition of bird sounds (p < 0.01). However, with the increasing proportion of Taoist scenes, Taoist music only significantly improved the acoustic comfort and heart rate of ordinary people (p < 0.01)

FedBA: Non-IID Federated Learning Framework in UAV Networks

With the development and progress of science and technology, the Internet of Things(IoT) has gradually entered people's lives, bringing great convenience to our lives and improving people's work efficiency. Specifically, the IoT can replace humans in jobs that they cannot perform. As a new type of IoT vehicle, the current status and trend of research on Unmanned Aerial Vehicle(UAV) is gratifying, and the development prospect is very promising. However, privacy and communication are still very serious issues in drone applications. This is because most drones still use centralized cloud-based data processing, which may lead to leakage of data collected by drones. At the same time, the large amount of data collected by drones may incur greater communication overhead when transferred to the cloud. Federated learning as a means of privacy protection can effectively solve the above two problems. However, federated learning when applied to UAV networks also needs to consider the heterogeneity of data, which is caused by regional differences in UAV regulation. In response, this paper proposes a new algorithm FedBA to optimize the global model and solves the data heterogeneity problem. In addition, we apply the algorithm to some real datasets, and the experimental results show that the algorithm outperforms other algorithms and improves the accuracy of the local model for UAVs