Influence Of Fabrication Condition on the Microstructural and Optical Properties of Lead-Free Ferroelectric Bi0.5_{0.5}Na0.5_{0.5}TiO3_{3} Materials

Lead-free ferroelectric materials have attracted considerable attention due to the increasing potential application in environmental benign materials. Among lead-free ferroelectric materials, the Bi0.5Na0.5TiO3 (BNT) materials were more studied because it exhibited the good ferroelectric and piezoelectric properties which could be promising candidate materials replacing Pb(Zr,Ti)O3. In this work, the lead-free ferroelectric BNT materials were synthesized by sol-gel method. The effects of fabrication process to microstructural and optical properties were studied which includes Na precursor concentration and calcining temperature. The result indicated that the Na precursor concentration were higher 40 mol.% and the calcining temperature

Current Development in Lead-Free Bi

The lead-free piezoelectric ceramics display good piezoelectric properties which are comparable with Pb(Zr,Ti)O3 (PZT) and these materials overcome the hazard to the environment and human health. The Bi0.5(Na,K)0.5TiO3 (BNKT) is rapidly developed because of good piezoelectric, ferroelectric, and dielectric properties compared to PZT. The origin of giant strain of BNKT piezoelectric materials was found at morphotropic phase boundary due to crystal change from tetragonal to orthorhombic and/or precipitation of cubic phases, in addition to domain switching mechanism. The dopants or secondary phases with ABO3 structure as solid solution are expected to change the crystal structure and create the vacancies which results in enhancement of the piezoelectric properties. In this work, we reviewed the current development of BNKT by dopants and secondary phase as solid solution. Our discussion will focus on role of dopants and secondary phase to piezoelectric properties of BNKT. This result will open the direction to control the properties of lead-free piezoelectric materials

TiO 3 -Based Piezoelectric Materials

The lead-free piezoelectric ceramics display good piezoelectric properties which are comparable with Pb(Zr,Ti)O 3 (PZT) and these materials overcome the hazard to the environment and human health. The Bi 0.5 (Na,K) 0.5 TiO 3 (BNKT) is rapidly developed because of good piezoelectric, ferroelectric, and dielectric properties compared to PZT. The origin of giant strain of BNKT piezoelectric materials was found at morphotropic phase boundary due to crystal change from tetragonal to orthorhombic and/or precipitation of cubic phases, in addition to domain switching mechanism. The dopants or secondary phases with ABO 3 structure as solid solution are expected to change the crystal structure and create the vacancies which results in enhancement of the piezoelectric properties. In this work, we reviewed the current development of BNKT by dopants and secondary phase as solid solution. Our discussion will focus on role of dopants and secondary phase to piezoelectric properties of BNKT. This result will open the direction to control the properties of lead-free piezoelectric materials

Fed-LSAE: Thwarting Poisoning Attacks against Federated Cyber Threat Detection System via Autoencoder-based Latent Space Inspection

The significant rise of security concerns in conventional centralized learning has promoted federated learning (FL) adoption in building intelligent applications without privacy breaches. In cybersecurity, the sensitive data along with the contextual information and high-quality labeling in each enterprise organization play an essential role in constructing high-performance machine learning (ML) models for detecting cyber threats. Nonetheless, the risks coming from poisoning internal adversaries against FL systems have raised discussions about designing robust anti-poisoning frameworks. Whereas defensive mechanisms in the past were based on outlier detection, recent approaches tend to be more concerned with latent space representation. In this paper, we investigate a novel robust aggregation method for FL, namely Fed-LSAE, which takes advantage of latent space representation via the penultimate layer and Autoencoder to exclude malicious clients from the training process. The experimental results on the CIC-ToN-IoT and N-BaIoT datasets confirm the feasibility of our defensive mechanism against cutting-edge poisoning attacks for developing a robust FL-based threat detector in the context of IoT. More specifically, the FL evaluation witnesses an upward trend of approximately 98% across all metrics when integrating with our Fed-LSAE defense

Influence of Spray Rate on Structural and Optical Properties of Sprayed ZnO Films

In this report, the ZnO nanostructure films have been deposited by ultrasonic spray pyrolysis technique (USP) on fluorine doped tinoxide~(FTO) substrate using zinc acetate and aqueous 2-propanol as reactants. The effects of solution spray rate on structural, morphological and optical properties of ZnO nanostructure films were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM) and UV-Vis measurements. ZnO films were crystallized in the hexagonal wurtzite phase and preferential orientation changed with changing of spray rate. Grain size and roughness of films depended on spray rate. Increasing spray rate made the films grown with bigger grain size and higher roughness. Band gap energy was determined from the UV-Vis. Its value was found to be of 3.25 eV and was almost independent on the spray rate

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Designing Forecasting Parameter Algorithm of Environmental Shrimp Using Recurrent Neural Network

With the strong development of science and technology, the study of technologies related to environmental forecasting is important. In recent years, the application of smart technology in aquaculture has been widely applied. Based on the requirement, we focus on predicting the environmental parameters applied in shrimp farming, especially white shrimp, one of the seafood grown in our country. In the paper, we exploit a small branch of identification problem. This paper proposes an algorithmic construction method to predict changes in shrimp farm environmental parameters and simulate the next parameters based on current parameters. The goal of the paper is to reduce the parameter of Recurrent Neural Network (RNN) while ensuring data accuracy. Experimental results show that the proposal algorithm improves up to 85 percent when selecting suitable learning factor of neural networks

Na2Fe3(SO4)4 là vật liệu cathode mới với điện thế cao dùng cho pin sodium-ion

Based on the density functional theory, we propose a promising cathode material, Na2Fe3(SO4)4, applicable for sodium-ion batteries. The crystal structure, stability, average voltage, and diffusion mechanism are carefully investigated to evaluate the electrochemical properties. The proposed material exhibits a high voltage of 4.0 V during the Na extraction. A small polaron is proved to be formed preferably at the first nearest Fe sites to Na vacancy and simultaneously accompanies the Na vacancy during its migration. Four elementary diffusion processes of the polaron–Na vacancy complexes, namely two parallel and two crossing processes, have been explored. The significant difference of activation energies between parallel and crossing processes suggests the substantial effect of the small polaron migration on the Na vacancy diffusion. We found that the parallel process along the [001] direction has the lowest activation energy of 808 meV, implying that the Na vacancy preferably diffuses in a zigzag pathway along the [001] direction.Chúng tôi đề xuất một vật liệu cathode mới Na2Fe3(SO4)4 có thể dùng cho pin sodium-ion dựa theo lý thuyết phiếm hàm mật độ. Cấu trúc tinh thể, tính bền, điện thế trung bình và cơ chế khuếch tán được khảo sát cẩn thận để đánh giá các tính chất điện hóa. Vật liệu đề xuất có thể đạt điện thế cao 4.0 V trong quá trình giải phóng ion Na. Chuẩn hạt polaron nhỏ ưu tiên hình thành tại vị trí Fe gần nhất với vị trí khuyết ion Na và chuyển động đồng thời với vị khuyết ion Na trong suốt quá trình chuyển động của nó. Bốn quá trình khuếch tán của tổ hợp vị trí khuyết ion Na và polaron được khảo sát gồm có 2 quá trình song song và 2 quá trình chéo. Sự khác biệt về năng lượng kích hoạt giữa các quá trình song song và chéo cho thấy hiệu ứng đáng kể của các polaron nhỏ đến quá trình khuếch tán của vị trí khuyết ion Na. Chúng tôi nhận thấy quá trình song song dọc theo hướng [001] có năng lượng kích hoạt thấp nhất là 808 meV, điều này gợi ý rằng vị trí khuyết ion Na ưu tiên khuếch tán theo một đường zigzag dọc theo hướng [001]

Two-dimensional complex shear modulus imaging of soft tissues by integration of Algebraic Helmoltz Inversion and LMS filter into dealing with noisy data: a simulation study

Elasticity and viscosity of soft tissues can be obtained from the complex shear modulus imaging (CSMI). CSMI is often used not only to investigate the structure of tissues but also to detect tumors in tissues. One of the most popular ways to categorize the methods used in CSMI is into quasi-static and dynamic methods. In the dynamic method, a force excitation is used to create the shear wave propagation, and the particle velocities are measured to extract their amplitude and phase at spatial locations. These parameters are then employed to directly or indirectly estimate the Complex Shear Modulus (CSM) represented by elasticity and viscosity. Algebraic Helmholtz Inversion (AHI) algorithm provides the direct estimation of CSM using the Finite Difference Time Domain (FDTD) technique. The limitation of this method, however, is that the noise generated from measuring the particle velocity strongly degrades the accuracy of the estimation. To overcome this problem, we proposed in this paper an adaptive AHI (AAHI) algorithm that offers a good performance in CSMI with a mean error of 2.06%