An Embeddable Strain Sensor with 30 Nano-Strain Resolution based on Optical Interferometry

A cost-effective, robust and embeddable optical interferometric strain sensor with nanoscale strain resolution is presented in this paper. The sensor consists of an optical fiber, a quartz rod with one end coated with a thin gold layer, and two metal shells employed to transfer the strain and orient and protect the optical fiber and the quartz rod. The optical fiber endface, combining with the gold-coated surface, forms an extrinsic Fabry—Perot interferometer. The sensor was firstly calibrated, and the result showed that our prototype sensor could provide a measurement resolution of 30 nano-strain (nε) and a sensitivity of 10.01 µε/ µm over a range of 1000 µε. After calibration of the sensor, the shrinkage strain of a cubic brick of mortar in real time during the drying process was monitored. The strain sensor was compared with a commercial linear variable displacement transducer, and the comparison results in four weeks demonstrated that our sensor had much higher measurement resolution and gained more detailed and useful information. Due to the advantages of the extremely simple, robust and cost-effective configuration, it is believed that the sensor is significantly beneficial to practical applications, especially for structural health monitoring

Data query mechanism based on hash computing power of blockchain in internet of things

Funding: This work is supported by the NSFC (61772280, 61772454, 61811530332, 61811540410), the PAPD fund from NUIST. This work was funded by the Researchers Supporting Project No. (RSP-2019/102) King Saud University, Riyadh, Saudi Arabia. Jin Wang and Osama Alfarraj are the corresponding authors. Acknowledgments: We thank Researchers Supporting Project No. (RSP-2019/102) King Saud University, Riyadh, Saudi Arabia for funding this paper. Author Contributions: Y.R., F.Z. and O.A. conceived the mechanism design and wrote the paper, P.K.S. built the models. T.W. and A.T. developed the mechanism, J.W. and O.A. revised the manuscript. All authors have read and agreed to the published version of the manuscript.Peer reviewedPublisher PD

Prevalence of workplace violence against healthcare workers: a systematic review and meta-analysis

We aim to quantitatively synthesise available epidemiological evidence on the prevalence rates of workplace violence (WPV) by patients and visitors against healthcare workers. We systematically searched PubMed, Embase and Web of Science from their inception to October 2018, as well as the reference lists of all included studies. Two authors independently assessed studies for inclusion. Data were double-extracted and discrepancies were resolved by discussion. The overall percentage of healthcare worker encounters resulting in the experience of WPV was estimated using random-effects meta-analysis. The heterogeneity was assessed using the I2 statistic. Differences by study-level characteristics were estimated using subgroup analysis and meta-regression. We included 253 eligible studies (with a total of 331 544 participants). Of these participants, 61.9% (95% CI 56.1% to 67.6%) reported exposure to any form of WPV, 42.5% (95% CI 38.9% to 46.0%) reported exposure to non-physical violence, and 24.4% (95% CI 22.4% to 26.4%) reported experiencing physical violence in the past year. Verbal abuse (57.6%; 95% CI 51.8% to 63.4%) was the most common form of non-physical violence, followed by threats (33.2%; 95% CI 27.5% to 38.9%) and sexual harassment (12.4%; 95% CI 10.6% to 14.2%). The proportion of WPV exposure differed greatly across countries, study location, practice settings, work schedules and occupation. In this systematic review, the prevalence of WPV against healthcare workers is high, especially in Asian and North American countries, psychiatric and emergency department settings, and among nurses and physicians. There is a need for governments, policymakers and health institutions to take actions to address WPV towards healthcare professionals globally

Keragaman Genetik Dan Pendugaan Jumlah Gen Ketahanan Kacang Panjang (Vigna Sinensis L.) Terhadap Penyakit Kuning

Penyakit kuning pada kacang panjang berdampak pada penurunan produksi. Gejala serangan diawali dari gejala daun keriting serta mengakibatkan polong berwarna kuning. Penelitian ini bertujuan mengetahui nilai heritabilitas dan ragam genetik serta menduga jumlah gen pengendali ketahanan kacang panjang terhadap penyakit kuning. Penelitian dilaksanakan di Kabupaten Kediri pada bulan April sampai Juli 2013. Bahan penelitian adalah populasi UB 715 A (P1), Hitam Putih (P2), populasi F1 dan populasi F2. Berdasarkan hasil penelitian, populasi UB 715 A (P1 ) menunjukkan respon tahan terhadap penyakit kuning, populasi Hitam Putih (P2) menunjukkan respon rentan, dan populasi F1 dan F2 menunjukkan respon sedang. Karakter jumlah polong dan jumlah biji per tanaman memiliki keragaman yang sempit sedangkan karakter panjang polong, bobot segar polong, umur berbunga, dan umur panen memiliki keragaman yang luas. Karakter panjang polong dan jumlah biji per polong memiliki nilai heritabilitas rendah, sedangkan karakter jumlah polong, bobot segar polong, umur berbunga, dan umur panen memiliki nilai heritabilitas tinggi. Rasio sifat ketahanan terhadap penyakit kuning pada populasi F2 adalah 9 tahan : 3 sedang : 4 rentan yang berarti ketahanan terhadap penyakit kuning dikendalikan oleh dua gen dengan aksi gen epistasis resesif

Using graphene to protect DNA from cleavage during cellular delivery

We have proved that functionalized nanoscale graphene oxide can protect oligonucleotides from enzymatic cleavage and efficiently deliver oligonucleotides into cells.National Natural Science Foundation of China [20775019, 20735002, 20975023]; National Basic Research Program of China [2010CB732403

Prevalence of atrial fibrillation in different socioeconomic regions of China and its association with stroke: Results from a national stroke screening survey

Background: Atrial fibrillation (AF) is the most common sustained arrhythmia in clinical practice. This study aimed to estimate the prevalence of AF in different socioeconomic regions of China and identify its association with stroke, through a national survey. Methods: The study included 726,451 adults aged ≥40 years who were participants of the China National Stroke Screening and Prevention Project, a nationally representative cross-sectional study. Stepwise logistic regression analyses were conducted to investigate the association between AF and stroke. Results: The overall standardized prevalence rate of AF was 2.31%. The prevalence of AF was highest in high-income regions (2.54%), followed by middle-income regions (2.33%), and lowest in low-income regions (1.98%). Women had a higher prevalence of AF than men in all regions (low-income regions, 2.30% vs 1.65%; middle-income regions, 2.78% vs 1.89%; and high-income regions, 2.96% vs 2.12%). Compared with urban residents, the prevalence of AF among rural residents was higher in low- (2.03% vs 1.91%) and middle-income regions (2.69% vs 1.90%), but lower in high-income regions (2.44% vs 2.58%). Participants with AF were more likely to have a stroke than those without AF (9.48% vs 2.26%). After adjusting for age, sex, location, overweight or obese, smoking, drinking, physical inactivity, hypertension, diabetes, dyslipidemia, and a family history of stroke, results showed that AF was significantly associated with stroke. Conclusions: The prevalence of AF has increased in recent years, and it was positively correlated with socioeconomic status, sex (women), location (rural areas), and stroke

A lending scheme based on smart contract for banks

In this paper, we work towards bank loans. This task is nontrivial due to the following problem: small enterprises and individuals have difficulties in lending, banks bear high risks, and the lending business is greatly affected by the subjective influence of staff. Towards this end, we propose a novel loan investment model and smart contract algorithm. Afterwords, we build an intelligent risk control evaluation algorithm based on deep learning. To justify our work, we implemented a distributed application that can run safely. In addition, using the data set of paipai loan, the accuracy of our intelligent risk control evaluation algorithm is 94.33%

Identification of Sonar Detection Signal Based on Fractional Fourier Transform

Aiming at the source of underwater acoustic emission, in order to identify the enemy emission sonar source accurately. Using the digital watermarking technology and combining with the good time-frequency characteristics of fractional Fourier transform (FRFT), this paper proposes a sonar watermarking method based on fractional Fourier transform. The digital watermark embedding in the fractional Fourier transform domain and combined with the coefficient properties of the sonar signal in the fractional Fourier transform to select the appropriate watermark position. Using the different characteristics of the signals before and after embedding, an adaptive threshold was set for the watermark detection to realize the discrimination of sonar signals. The simulation results show the feasibility and has better resolution and large watermark capacity of this method, while the robustness of the watermark is better, and the detection precision is further improved

Identity Management and Access Control Based on Blockchain under Edge Computing for the Industrial Internet of Things

Edge computing provides a unified platform for computing, networking, and storage resources, enabling data to be processed in a timely and efficient manner near the source. Thus, it has become the basic platform for industrial Internet of things (IIoT). However, computing′s unique features have also introduced new security problems. To solve the problem, in this paper, blockchain-based identity management combining access control mechanism is designed under edge computing. The self-certified cryptography is utilized to realize the registration and authentication of network entities. We bind the generated implicit certificate to its identity and construct the identity and certificate management mechanism based on blockchain. Secondly, an access control mechanism based on Bloom filter is designed and integrated with identity management. Moreover, for secure communication in resource-constrained edge devices, a lightweight secret key agreement protocol based on self-authenticated public key is constructed. These mechanisms work together to provide data security guarantees for IIoT such as authentication, auditability, and confidentiality

Data Storage Mechanism Based on Blockchain with Privacy Protection in Wireless Body Area Network

Wireless body area networks (WBANs) are expected to play a vital role in the field of patient-health monitoring shortly. They provide a convenient way to collect patient data, but they also bring serious problems which are mainly reflected in the safe storage of the collected data. The privacy and security of data storage in WBAN devices cannot meet the needs of WBAN users. Therefore, this paper adopts blockchain technology to store data, which improves the security of the collected data. Moreover, a storage model based on blockchain in WBAN is proposed in our solution. However, blockchain storage brings new problems, for example, that the storage space of blockchain is small, and the stored content is open to unauthorized attackers. To solve the problems above, this paper proposed a sequential aggregate signature scheme with a designated verifier (DVSSA) to ensure that the user’s data can only be viewed by the designated person and to protect the privacy of the users of WBAN. In addition, the new signature scheme can also compress the size of the blockchain storage space