Silver nanowire (Ag NW) networks have attracted wide attention as transparent electrodes for emerging flexible optoelectronics. However, the sheet resistance is greatly limited by large wire-to-wire contact resistances. Here, we propose a simple sunlight illumination approach to remarkably improve their electrical conductivity without any significant degradation of the light transmittance. Because the power density is extremely low (0.1 W/cm2, 1-Sun), only slight welding between Ag NWs has been observed. Despite this, a sheet resistance of <20 Ω/sq and transmittance of ~87% at wavelength of 550 nm as well as excellent mechanical flexibility have still been achieved for Ag NW networks after sunlight illumination for 1 hour or longer, which are significant upgrades over those of ITO. Slight plasmonic welding together with the associated self-limiting effect has been investigated by numerical simulations and further verified experimentally through varied solar concentrations. Due to the reduced resistance, high-performance transparent film heaters as well as efficient defrosters have been demonstrated, which are superior to the previously-reported Ag NW based film heaters. Since the sunlight is environmentally friendly and easily available, sophisticated or expensive facilities are not necessary. Our findings are particularly meaningful and show enormous potential for outdoor applications.

No abstract

Rationale: Chordomas are rare malignant neoplasms arised from residual embryonic notochordal tissue, mostly located in the axial midline. Tumors along extra-axial locations in the head and neck are rare. Chordomas located in the jugular foramen are extremely rare, with a low incidence of 0.2%. Patient concerns: A 64-year-old male with 20 years of dizziness history complaining of 6 months of severe dizziness: significant with the changing of the body posture, vertigo which can be self-remissioned within 1 minute and hearing loss of both ears, without headache, nausea, dysphagia, or otalgia. Computed tomography and magnetic resonance imaging (MRI) were performed before surgery which suggests various possibilities. Immunohistochemistry helped to confirm the final diagnosis. Diagnoses: Immunohistochemistry demonstrated diffuse positivity for S100 (+++), positivity for D2-40 (focal +), EMA (+), and PR (+). Ki-67 labeling index was estimated at 2% focally. The final diagnosis was chordoma. Interventions: The tumor was excised via retro-sigmoid approach without postoperative radiotherapy. Outcomes: Facial paralysis occurred in this case. House–Brackmann facial nerve grading system was used to evaluate the facial paralysis of this patient. It is considered as H-B grade IV. The patient was followed up regularly every month after operation, totally for 9 months. An MRI of the brain was performed 6 months after surgery which shows a small range of abnormal signals similar to the previous MRI in the jugular foramen, suggesting that there may be residual or recurrent tumor. And facial paralysis stays at H-B grade IV without any recovery. Lessons: It is a big challenge for us to remove giant tumors located in the jugular foramen because of its unique anatomy. Access should be combined with retro-sigmoid or infra-temporal fossa approach to remove such tumors. Chordomas is a malignant neoplasm which may need radiotherapy after surgery, particularly those with subtotal and partial resection.

No abstract

Summary With the rapid development of smartphones in recent years, we have witnessed an exponential growth of the number of mobile apps. Considering the security and management issues, network operators need to have a clear visibility into the apps running in the network. To this end, this paper presents a novel approach to generating the fingerprints for mobile apps from network traffic. The fingerprints that characterize the unique behaviors of specific mobile apps can be used to identify mobile apps from the real network traffic. In order to handle the large volume of traffic efficiently, we use non‐negative matrix factorization (NMF) to perform traffic analysis to cluster similar network traffic into groups. Then, access patterns of individual apps that are extracted from each group can be used as fingerprints distinguishing apps from others uniquely. The experimental evaluations show that the proposed approach can identify the mobile apps from random and mixed network traffic with high precision. Copyright © 2015 John Wiley & Sons, Ltd.