e-SAFE: Secure, Efficient and Forensics-Enabled Access to Implantable Medical Devices

To facilitate monitoring and management, modern Implantable Medical Devices (IMDs) are often equipped with wireless capabilities, which raise the risk of malicious access to IMDs. Although schemes are proposed to secure the IMD access, some issues are still open. First, pre-sharing a long-term key between a patient's IMD and a doctor's programmer is vulnerable since once the doctor's programmer is compromised, all of her patients suffer; establishing a temporary key by leveraging proximity gets rid of pre-shared keys, but as the approach lacks real authentication, it can be exploited by nearby adversaries or through man-in-the-middle attacks. Second, while prolonging the lifetime of IMDs is one of the most important design goals, few schemes explore to lower the communication and computation overhead all at once. Finally, how to safely record the commands issued by doctors for the purpose of forensics, which can be the last measure to protect the patients' rights, is commonly omitted in the existing literature. Motivated by these important yet open problems, we propose an innovative scheme e-SAFE, which significantly improves security and safety, reduces the communication overhead and enables IMD-access forensics. We present a novel lightweight compressive sensing based encryption algorithm to encrypt and compress the IMD data simultaneously, reducing the data transmission overhead by over 50% while ensuring high data confidentiality and usability. Furthermore, we provide a suite of protocols regarding device pairing, dual-factor authentication, and accountability-enabled access. The security analysis and performance evaluation show the validity and efficiency of the proposed scheme

Privacy Leakage in Smart Homes and Its Mitigation: IFTTT as a Case Study

The combination of smart home platforms and automation apps introduces much convenience to smart home users. However, this also brings the potential for privacy leakage. If a smart home platform is permitted to collect all the events of a user day and night, then the platform will learn the behavior patterns of this user before long. In this paper, we investigate how IFTTT, one of the most popular smart home platforms, has the capability of monitoring the daily life of a user in a variety of ways that are hardly noticeable. Moreover, we propose multiple ideas for mitigating privacy leakages, which altogether forms a Filter-and-Fuzz (F&F) process: first, it filters out events unneeded by the IFTTT platform; then, it fuzzes the values and frequencies of the remaining events. We evaluate the F&F process, and the results show that the proposed solution makes IFTTT unable to recognize any of the user's behavior patterns

Prevalence of Depression and Anxiety Symptoms of High School Students in Shandong Province During the COVID-19 Epidemic

© Copyright © 2020 Zhang, Zhai, Yang, Zhang, Zhou, Yang, Duan and Zhou. Background: The coronavirus disease 2019 (covid-19) has brought physical risks as well as psychological challenges to the whole world. High school students are a special group suffering from both the academic pressure and the threat of the epidemic. The present study aims to conduct an online survey to investigate the psychological status of high school students in Shandong Province. Methods: Using a web-based cross-sectional survey, data was collected from 1,018 voluntary high school students assessed with demographic information, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7) and a self-designed online-study effect survey. Correlation analysis was performed to explore the relationships between depression symptoms, anxiety symptoms, and study effect. Result: The prevalence of depressive symptoms, anxiety symptoms, and a combination of depressive and anxiety symptoms was 52.4, 31.4, and 26.8%, respectively, among high school students in Shandong Province during the COVID-19 epidemic. And from moderate to severe severity level, the rates of depressive symptoms and anxious symptoms were 17.6 and 4.6%. Female students exhibited a higher rate and severity of mental symptoms than male, and grade one senior high school students got a higher rate and severity of mental symptoms than the other two grades. Nearly half of the students were not satisfied with their online-study effect. The PHQ-9 score had a strong positive correlation with the GAD-7 score. Both the PHQ-9 score the GAD-7 score had a negative correlation with the study-effect survey score. Conclusion: Quite a number of high school students suffered from depression and anxiety symptoms during the COVID-19 epidemic. Sufficient attentions should be paid, and necessary supports should be provided, to protect the mental health of this special group

Self-Catalyzed AlGaAs Nanowires and AlGaAs/GaAs Nanowire-Quantum Dots on Si Substrates

[Image: see text] Self-catalyzed AlGaAs nanowires (NWs) and NWs with a GaAs quantum dot (QD) were monolithically grown on Si(111) substrates via solid-source molecular beam epitaxy. This growth technique is advantageous in comparison to the previously employed Au-catalyzed approach, as it removes Au contamination issues and renders the structures compatible with complementary metal–oxide–semiconductor (CMOS) technology applications. Structural studies reveal the self-formation of an Al-rich AlGaAs shell, thicker at the NW base and thinning towards the tip, with the opposite behavior observed for the NW core. Wide alloy fluctuations in the shell region are also noticed. AlGaAs NW structures with nominal Al contents of 10, 20, and 30% have strong room temperature photoluminescence, with emission in the range of 1.50–1.72 eV. Individual NWs with an embedded 4.9 nm-thick GaAs region exhibit clear QD behavior, with spatially localized emission, both exciton and biexciton recombination lines, and an exciton line width of 490 μeV at low temperature. Our results demonstrate the properties and behavior of the AlGaAs NWs and AlGaAs/GaAs NWQDs grown via the self-catalyzed approach for the first time and exhibit their potential for a range of novel applications, including nanolasers and single-photon sources

Case report: Fully endoscopic microvascular decompression for glossopharyngeal neuralgia

With the advances in endoscopic technology, endoscopy is widely used in many neurosurgical procedures, such as microvascular decompression, which is an effective method to treat glossopharyngeal neuralgia, trigeminal neuralgia, and facial spasm. The purpose of this study was to determine the efficacy of fully endoscopic microvascular decompression in the treatment of glossopharyngeal neuralgia. We managed a patient with glossopharyngeal neuralgia in our department, whose main clinical manifestation was recurrent left ear and facial pain for 3 years. The patient underwent a fully endoscopic microvascular decompression. The pain in the left ear and face was significantly relieved postoperatively, and there was no recurrence at the 6-month follow-up evaluation. We describe a case of glossopharyngeal neuralgia that was successfully treated by fully endoscopic microvascular decompression, which showed that endoscopy has advantages in microvascular decompression, and fully endoscopic microvascular decompression is an effective method for glossopharyngeal neuralgia

Fabrication Process Independent And Robust Aggregation Of Detonation Nanodiamonds In Aqueous Media

In the past detonation nanodiamonds (DNDs), sized 3–5 nm, have been praised for their colloidal stability in aqueous media, thereby attracting vast interest in a wide range of applications including nanomedicine. More recent studies have challenged the consensus that DNDs are monodispersed after their fabrication process, with their aggregate formation dynamics poorly understood. Here we reveal that DNDs in aqueous solution, regardless of their post-synthesis de-agglomeration and purification methods, exhibit hierarchical aggregation structures consisting of chain-like and cluster aggregate morphologies. With a novel characterization approach combining machine learning with direct cryo-transmission electron microscopy and with X-ray scattering and vibrational spectroscopy, we show that their aggregate morphologies of chain and cluster ratios and the corresponding size and fractal dimension distributions vary with the post-synthesis treatment methods. In particular DNDs with positive ζ-potential form to a hierarchical structure that assembles aggregates into large networks. DNDs purified with the gas phase annealing and oxidation tend to have more chain-like aggregates. Our findings provide important contribution in understanding the DND interparticle interactions to control the size, polydispersity and aggregation of DNDs for their desired applications