Unsupervised Domain Adaptation GAN Inversion for Image Editing

Existing GAN inversion methods work brilliantly for high-quality image reconstruction and editing while struggling with finding the corresponding high-quality images for low-quality inputs. Therefore, recent works are directed toward leveraging the supervision of paired high-quality and low-quality images for inversion. However, these methods are infeasible in real-world scenarios and further hinder performance improvement. In this paper, we resolve this problem by introducing Unsupervised Domain Adaptation (UDA) into the Inversion process, namely UDA-Inversion, for both high-quality and low-quality image inversion and editing. Particularly, UDA-Inversion first regards the high-quality and low-quality images as the source domain and unlabeled target domain, respectively. Then, a discrepancy function is presented to measure the difference between two domains, after which we minimize the source error and the discrepancy between the distributions of two domains in the latent space to obtain accurate latent codes for low-quality images. Without direct supervision, constructive representations of high-quality images can be spontaneously learned and transformed into low-quality images based on unsupervised domain adaptation. Experimental results indicate that UDA-inversion is the first that achieves a comparable level of performance with supervised methods in low-quality images across multiple domain datasets. We hope this work provides a unique inspiration for latent embedding distributions in image process tasks

Camera-based Mirror Visual Feedback: Potential to Improve Motor Preparation in Stroke Patients

© 2018 IEEE.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Mirror visual feedback (MVF) is used widely for motor recovery after stroke, but an optimal training setup and systematic procedure are lacking. New optimization strategies have been proposed, one of which is a camera technique. We investigated the effects of a camera-based MVF setup on motor function and motor processes upstream for upper-limb rehabilitation. Seventy-nine stroke patients were assigned randomly to the MVF group (MG; N = 38) or conventional group (CG; N = 41), which respectively received camera-based MVF and dosage-equivalent physiotherapy or/and occupational therapy for 1 h/day and 5 days/week for 4 weeks. Two clinical scales were used to quantify the effect of the intervention methods: the Fugl–Meyer Assessment-Upper Limb (FMA-UL) subscale and Barthel Index (BI). The hand laterality task was used to evaluate the ability of mental rotation, including the reaction time (RT) and accuracy (ACC). All measurements improved significantly for both groups following intervention. FMA-UL was improved significantly in the MG compared with that in the CG. In lateralization tasks, the RT of the MG was significantly shorter than that of the CG at the endpoint. For all patients, judgments for the affected side were significantly slower and less accurate than for the less-affected side. Subgroup analyses suggested greater benefits of motor function, the activities of daily life, and mental rotation were achieved in subacute patients after MVF. A trend towards greater improvements in motor function for patients with severe–moderate motor impairment and patients with right-hemisphere damage were also revealed. Camera-based MVF improved the motor function and ability of mental rotation for stroke patients, especially for patients in the subacute stage, which indicates the potential to improve motor preparation. Further studies might combine mental rotation with electroencephalography to investigate the neuro-mechanism of MVF.Science and Technology Commission of Shanghai Municipality (15441901601, 16441905303)National Natural Science Foundation of China (61771313)National High Technology Research and Development Program of China (SS2015AA020501)Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (2013BAI10B03)Natural Sciences andEngineering Research Council of Canada (072169

Effect of Percutaneous Endoscopic Gastrostomy on Quality of Life after Chemoradiation for Locally Advanced Nasopharyngeal Carcinoma: A Cross-Sectional Study

(1) Background: Prophylactic percutaneous endoscopic gastrostomy (PEG) maintained nutritional status and improved survival of patients with locally advanced nasopharyngeal carcinoma (LA-NPC). However, the role of PEG in patients’ quality of life (QoL) is still controversial. We aimed to investigate the effect of PEG on the QoL of patients with LA-NPC without progression. (2) Methods: Patients with LA-NPC between 1 June 2010 and 30 June 2014 in Fujian Cancer Hospital were divided into PEG and non-PEG groups. The QoL Questionnaire core 30 (QLQ-C30), incidence of adverse effects, weight, and xerostomia recovery were compared between the two groups of patients without progression as of 30 June 2020. (3) Results: No statistically significant difference in the scores of each QLQ-C30 scale between the two groups (p > 0.05). The incidence of xerostomia was higher in the PEG group than in the non-PEG group (p = 0.044), but the association was not seen after adjusting for gender, age, T, and N stage (OR: 0.902, 95%CI: 0.485–1.680). No significant difference in the incidence of other adverse effects as well as in weight and dry mouth recovery (p > 0.05). (4) Conclusion: PEG seems not to have a detrimental effect on long-term Qol, including the self-reported swallowing function of NPC patients without progressive disease

Hierarchically Planning Static Gait for Quadruped Robot Walking on Rough Terrain

Quadruped robot has great potential to walk on rough terrain, in which static gait is preferred. A hierarchical structure based controlling algorithm is proposed in this paper, in which trajectory of robot center is searched, and then static gaits are generated along such trajectory. Firstly, cost map is constructed by computing terrain features under robot body and cost of selecting footholds at default positions, and then the trajectory of robot center in 2D space is searched using heuristic A⁎ algorithm. Secondly, robot state is defined from foothold and robot pose, and then state series are searched recursively along the trajectory of robot center to generate static gaits, where a tree-like structure is used to store such states. Lastly, a classical model for quadruped robot is designed, and then the controlling algorithm proposed in the paper is demonstrated on such robot model for both structured terrain and complex unstructured terrain in a simulation environment

An Access Selection Algorithm for Heterogeneous Wireless Networks Based on Optimal Resource Allocation

Wireless networks form heterogeneous wireless networks (HWNs) with overlapping signal coverage, and access selection is one of the key technologies of HWNs. Today, most access selection algorithms select appropriate networks mainly from the perspective of users while failing to consider resource allocation and optimize the overall transmission performance of HWNs. This paper proposes an access selection algorithm for HWNs based on optimal resource allocation by analyzing the wireless link transmission rate model, focusing on maximizing the HWN transmission rate, using the dynamic programming theory to derive the optimal value of bandwidth allocated to users. Experimental results show that the algorithm proposed in this paper can effectively improve network throughput and resource utilization and can connect users to the appropriate network according to QoS rate requirements

Manipulation on Two-Dimensional Amorphous Nanomaterials for Enhanced Electrochemical Energy Storage and Conversion

Low-carbon society is calling for advanced electrochemical energy storage and conversion systems and techniques, in which functional electrode materials are a core factor. As a new member of the material family, two-dimensional amorphous nanomaterials (2D ANMs) are booming gradually and show promising application prospects in electrochemical fields for extended specific surface area, abundant active sites, tunable electron states, and faster ion transport capacity. Specifically, their flexible structures provide significant adjustment room that allows readily and desirable modification. Recent advances have witnessed omnifarious manipulation means on 2D ANMs for enhanced electrochemical performance. Here, this review is devoted to collecting and summarizing the manipulation strategies of 2D ANMs in terms of component interaction and geometric configuration design, expecting to promote the controllable development of such a new class of nanomaterial. Our view covers the 2D ANMs applied in electrochemical fields, including battery, supercapacitor, and electrocatalysis, meanwhile we also clarify the relationship between manipulation manner and beneficial effect on electrochemical properties. Finally, we conclude the review with our personal insights and provide an outlook for more effective manipulation ways on functional and practical 2D ANMs