Analysis of Hot Points on Data Mining Research of Medical in Foreign Countries

To promote the current development of medical data mining research, a quantitative statistics and qualitative analysis of the papers in the field of medical data mining technologies were made with the methodology of bibliometric and knowledge mapping, which were enlisted in the database of Web of Science analyzing the general situation of the papers about data mining from several aspects: period sequences, subject funds, countries and regions, core authors and research institutions, the hotspots and research frontiers. Our analysis exposed that the research of data mining in medical showed a multi-disciplinary integration of the development trend, but high-yield leading author group has not yet formed. It is important to note that scholars should raise awareness of clinical medical data mining as well as explore new research directions for further studying

Research on lethal levels of buildings based on historical seismic data

Due to the influences of buildings, geographical and geomorphological environments, road conditions, etc., the probabilities and numbers of casualties in different areas after an earthquake are different. Accordingly, we propose the concept of the lethal level, which attains different grades representing the mortality rate of differing intensities. Different regions have unique lethal levels, and regional lethal levels are affected mainly by the proportion of each building type and the corresponding lethal level, as different types of buildings also have unique lethal levels. Based on data of 52 historical earthquake disasters, we constructed a lethal level calculation model and obtained the lethal level of each building type. The results reveal that the lethal level ranges of different building types are fixed and unequal; moreover, the ranges of different building types overlap each other. The lethal level range of adobe structures is 0.85–1, that of civil structures is 0.75–0.95, that of brick-wood structures is 0.6–0.9, that of brick-concrete structures is 0.33–0.6, that of wood structures is 0.2–0.35, and that of reinforced concrete structures is 0.1–0.25. Based on the lethal levels of these building types, the overall level of a region can be quantified and graded, and this classification does not depend on the geographical location or administrative boundaries. In pre-earthquake evaluation efforts, the lethal level of an area can be derived through field research. After an earthquake, the number of casualties can be quickly assessed based on the mortality rate corresponding to the intensity of the area. This approach can further provide scientific support for risk zoning and risk assessment research

Role of dimensional crossover on spin-orbit torque efficiency in magnetic insulator thin films

Magnetic insulators (MIs) attract tremendous interest for spintronic applications due to low Gilbert damping and absence of Ohmic loss. Magnetic order of MIs can be manipulated and even switched by spin-orbit torques (SOTs) generated through spin Hall effect and Rashba-Edelstein effect in heavy metal/MI bilayers. SOTs on MIs are more intriguing than magnetic metals since SOTs cannot be transferred to MIs through direct injection of electron spins. Understanding of SOTs on MIs remains elusive, especially how SOTs scale with the film thickness. Here, we observe the critical role of dimensionality on the SOT efficiency by systematically studying the MI layer thickness dependent SOT efficiency in tungsten/thulium iron garnet (W/TmIG) bilayers. We first show that the TmIG thin film evolves from two-dimensional to three-dimensional magnetic phase transitions as the thickness increases, due to the suppression of long-wavelength thermal fluctuation. Then, we report the significant enhancement of the measured SOT efficiency as the thickness increases. We attribute this effect to the increase of the magnetic moment density in concert with the suppression of thermal fluctuations. At last, we demonstrate the current-induced SOT switching in the W/TmIG bilayers with a TmIG thickness up to 15 nm. The switching current density is comparable with those of heavy metal/ferromagnetic metal cases. Our findings shed light on the understanding of SOTs in MIs, which is important for the future development of ultrathin MI-based low-power spintronics

Exploiting Fine-Grained DCT Representations for Hiding Image-Level Messages within JPEG Images

Unlike hiding bit-level messages, hiding image-level messages is more challenging, which requires large capacity, high imperceptibility, and high security. Although recent advances in hiding image-level messages have been remarkable, existing schemes are limited to lossless spatial images as covers and cannot be directly applied to JPEG images, the ubiquitous lossy format images in daily life. The difficulties of migration are caused by the lack of targeted design and the loss of details due to lossy decompression and re-compression. Considering that taking DCT densely on $8\times8$ image patches is the core of the JPEG compression standard, we design a novel model called \textsf{EFDR}, which can comprehensively \underline{E}xploit \underline{F}ine-grained \underline{D}CT \underline{R}epresentations and embed the secret image into quantized DCT coefficients to avoid the lossy process. Specifically, we transform the JPEG cover image and hidden secret image into fine-grained DCT representations that compact the frequency and are associated with the inter-block and intra-block correlations. Subsequently, the fine-grained DCT representations are further enhanced by a sub-band features enhancement module. Afterward, a transformer-based invertibility module is designed to fuse enhanced sub-band features. Such a design enables a fine-grained self-attention on each sub-band and captures long-range dependencies while maintaining excellent reversibility for hiding and recovery. To our best knowledge, this is the first attempt to embed a color image of equal size in a color JPEG image. Extensive experiments demonstrate the effectiveness of our \textsf{EFDR} with superior performance.Comment: ACM Multimedia 23 submitted by Xin Liao (https://xin-liao.github.io/

Practical Lossless Federated Singular Vector Decomposition over Billion-Scale Data

With the enactment of privacy-preserving regulations, e.g., GDPR, federated SVD is proposed to enable SVD-based applications over different data sources without revealing the original data. However, many SVD-based applications cannot be well supported by existing federated SVD solutions. The crux is that these solutions, adopting either differential privacy (DP) or homomorphic encryption (HE), suffer from accuracy loss caused by unremovable noise or degraded efficiency due to inflated data. In this paper, we propose FedSVD, a practical lossless federated SVD method over billion-scale data, which can simultaneously achieve lossless accuracy and high efficiency. At the heart of FedSVD is a lossless matrix masking scheme delicately designed for SVD: 1) While adopting the masks to protect private data, FedSVD completely removes them from the final results of SVD to achieve lossless accuracy; and 2) As the masks do not inflate the data, FedSVD avoids extra computation and communication overhead during the factorization to maintain high efficiency. Experiments with real-world datasets show that FedSVD is over 10000 times faster than the HE-based method and has 10 orders of magnitude smaller error than the DP-based solution on SVD tasks. We further build and evaluate FedSVD over three real-world applications: principal components analysis (PCA), linear regression (LR), and latent semantic analysis (LSA), to show its superior performance in practice. On federated LR tasks, compared with two state-of-the-art solutions: FATE and SecureML, FedSVD-LR is 100 times faster than SecureML and 10 times faster than FATE.Comment: 10 page

Porosification-reduced optical trapping of silicon nanostructures

Metal-assisted chemical etching (MACE) was carried out to fabricate solid silicon nanowires (s-SiNWs) and mesoporous silicon nanowires (mp-SiNWs). Total reflection and transmission were measured using an integrated sphere to study optical properties of the MACE-generated silicon nanostructures. Without NW aggregation, mp-SiNWs vertically standing on a mesoporous silicon layer trap less light than s-SiNWs over a wavelength range of 400–800 nm, owing to porosification-enhanced optical scattering from the rough inner surfaces of the mesoporous silicon skeletons. Porosification substantially weakens the NW mechanical strength; hence the elongated mp-SiNWs aggregate after 30 min etching and deteriorate optical trapping

A Rice R2R3-Type MYB Transcription Factor OsFLP Positively Regulates Drought Stress Response via OsNAC

Abiotic stresses adversely affect plant growth and the yield of crops worldwide. R2R3-MYB transcriptional factors have been found to be vital for plants to confer stress response. In Arabidopsis, FOUR LIPS (FLP, MYB124) and its paralogous MYB88 function redundantly regulated the symmetric division of guard mother cells (GMCs) and abiotic stress response. Here, OsFLP was identified as an R2R3-MYB transcriptional activator and localized in the nucleus. OsFLP was transiently induced by drought, salt stress and abscisic acid (ABA). Overexpression of OsFLP showed enhanced tolerance to drought and salt stresses. The stomatal density in OsFLP-OE plants was not changed, whereas the stomatal closure was sensitive to ABA treatment compared to wild-type plants. In contrast, OsFLP-RNAi plants had abnormal stomata and were sensitive to drought. Moreover, the transcripts of stomatal closure-related genes DST and peroxidase 24 precursor, which are identified as downstream of OsNAC1, were inhibited in OsFLP-RNAi plants. The yeast-one-hybrid assay indicated that OsFLP can specifically bind and positively regulate OsNAC1 and OsNAC6. Meanwhile, stress response genes, such as OsLEA3 and OsDREB2A, were up-regulated in OsFLP-OE plants. These findings suggested that OsFLP positively participates in drought stress, mainly through regulating regulators’ transcripts of OsNAC1 and OsNAC6

Molecular Dynamics Simulation on Microstructure and Physicochemical Properties of FexO-SiO2-CaO-MgO-“NiO” Slag in Nickel Matte Smelting under Modulating CaO Content

To improve the conditions of extracting iron from nickel smelting residues, the composition modulating from FexO-SiO2-CaO-MgO-“NiO” slag source for matte smelting using high MgO nickel sulfide concentrate was carried out. Based on the molecular dynamics simulation and experimental characterization, the effect of CaO content in nickel slags on the physicochemical properties, the microstructure evolution, and the feasibility of subsequent iron extraction were analyzed. The results showed that, for nickel smelting slag with 9 wt.% MgO, 13–15 wt.% CaO and Fe/SiO2 ratio of 1.2, the melting temperature of nickel slag was lower than 1200 °C, and the viscosity was lower than 0.22 Pa·s at 1350 °C. The electric conductivity was similar to that of the industrial slag, and the interfacial tension between slag and matte was relatively large, which ensured a good separating characteristic. It not only met the requirements for the slag performances in the existing flash smelting process but also improved conditions for the subsequent iron extraction. Additionally, it could be adapted to the current situation where an increasing MgO content exists in the nickel sulfide concentrate

Blended learning with Moodle in medical statistics: an assessment of knowledge, attitudes and practices relating to e-learning

Abstract Background Blended learning that combines a modular object-oriented dynamic learning environment (Moodle) with face-to-face teaching was applied to a medical statistics course to improve learning outcomes and evaluate the impact factors of students’ knowledge, attitudes and practices (KAP) relating to e-learning. Methods The same real-name questionnaire was administered before and after the intervention. The summed scores of every part (knowledge, attitude and practice) were calculated using the entropy method. A mixed linear model was fitted using the SAS PROC MIXED procedure to analyse the impact factors of KAP. Results Educational reform, self-perceived character, registered permanent residence and hours spent online per day were significant impact factors of e-learning knowledge. Introversion and middle type respondents’ average scores were higher than those of extroversion type respondents. Regarding e-learning attitudes, educational reform, community number, Internet age and hours spent online per day had a significant impact. Specifically, participants whose Internet age was no greater than 6 years scored 7.00 points lower than those whose Internet age was greater than 10 years. Regarding e-learning behaviour, educational reform and parents’ literacy had a significant impact, as the average score increased 10.05 points (P < 0.0001). Conclusions This educational reform that combined Moodle with a traditional class achieved good results in terms of students’ e-learning KAP. Additionally, this type of blended course can be implemented in many other curriculums

[Cp*IrCl₂]₂‑Catalyzed Amidocarbonation of Olefins with Sulfoxonium Ylides toward Functionalized Isoindolin-1-ones

A [Cp*IrCl2]2-catalyzed amidocarbonation of olefins with sulfoxonium ylides has been developed to generate diverse biologically important isoindolin-1-ones in high efficiency under mild reaction conditions. Mechanism studies indicated that this cascade reaction was triggered by amino-iridation of the olefin unit to generate iridacycle, followed by formal migratory insertion with sulfoxonium ylides. This newly developed method features broad substrate scopes and operational simplicity