Acute Kidney Injury After Percutaneous Coronary Intervention Guided by Intravascular Ultrasound

Purpose We investigated the impact of intravascular ultrasound guidance on reducing the incidence of contrast-induced acute kidney injury (CI-AKI) in patients undergoing percutaneous coronary intervention (PCI). Methods Ninety-nine patients were enrolled in this prospective cohort who were not randomly assigned to angiography-guided percutaneous coronary intervention or intravascular ultrasound-guided percutaneous coronary intervention. The patients were hospitalized at the Vietnam National Heart Institute - Bach Mai Hospital between 2019 and 2020. Acute kidney injury incidence during hospitalization was the primary endpoint. Results A total of 99 patients were divided into two groups: the intravascular ultrasound-guided group (33 participants) and the angiography-guided group (66 participants). The mean ± SD contrast volume of each group was 95.2 ± 37.1 mL and 133.0 ± 36.0 mL for the ultrasound-guided and angiography-guided groups, with P \u3c 0.0001. Intravascular imaging-guided percutaneous coronary intervention (IVUS-guided PCI) was associated with reduced acute kidney injury incidence during hospitalization: 0.0% vs. 12.12% and P = 0.049. Conclusions Intravascular ultrasound is a safe imaging tool that guides percutaneous coronary intervention and significantly reduces the rate of acute kidney injury compared to angiography alone. Patients who have a high chance of experiencing acute kidney injury benefit from using intravascular ultrasound

On the Tightness of the Moment Accountant for DP-SGD

In order to provide differential privacy, Gaussian noise with standard deviation σ is added to local SGD updates after performing a clipping operation in Differential Private SGD (DP-SGD). By non-trivially improving the moment account method we prove a closed form (ϵ, δ)-DP guarantee: DP-SGD is (ϵ ≤ 1/2, δ = 1/N )-DP if σ = p2(ϵ + ln(1/δ))/ϵ with T at least ≈ 2k2/ϵ and (2/e)2k2 − 1/2 ≥ ln(N ), where T is the total number of rounds, and K = kN is the total number of gradient computations where k measures K in number of epochs of size N of the local data set. We prove that our expression is close to tight in that if T is more than a constant factor ≈ 8 smaller than the lower bound ≈ 2k2/ϵ, then the (ϵ, δ)-DP guarantee is violated. Choosing the smallest possible value T ≈ 2k2/ϵ not only leads to a close to tight DP guarantee, but also minimizes the total number of communicated updates and this means that the least amount of noise is aggregated into the global model and in addition accuracy is optimized as confirmed by simulations

Capitalizing on big data and revolutionary 5G technology: extracting and visualizing ratings and reviews of global chain hotels

This paper aims to use machine learning (ML) algorithm for natural language pre-processing (NLP), text mining (TM), and sentiment analysis (SA) techniques to analyze and examine 45,500 online reviews of customers of 50 global chain hotels from different online review sites. Furthermore, the paper addresses the new business value and experiences that the revolutionary 5G technology can bring to the hotel industry. The research findings revealed that the general review star rating corresponds with the opinion (sentiment) scores for the title and the full substance of the online reviews. The case study’s contextual analysis also uncovered that both fulfilled and disappointed customers have a frequent inclination for five categories: food, stay, rooms, service, and staff. This study contributes both theoretically and practically to the multidisciplinary domains of computer science, information systems, and tourism and discovers hidden patterns in data using visual analytics techniques

A Facile Synthesis, Characterization, and Photocatalytic Activity of Magnesium Ferrite Nanoparticles via the Solution Combustion Method

In this study, we adopted the solution combustion method to synthesize magnesium ferrite (MgFe2O4) using urea as the fuel. Various techniques including TGA, XRD, SEM, TEM, FTIR, UV-Vis DRS, and EDS were employed to characterize the synthesized MgFe2O4 nanoparticles. The XRD analysis revealed that single-phase MgFe2O4 was formed at a calcination temperature of at 500–600°C for 3 hours in the absence of an intermediate phase. TEM analysis also revealed the formation of monodisperse magnesium ferrite nanoparticles, averaged at 30 nm in size. The photocatalytic activity of the synthesized MgFe2O4 nanoparticles against methylene blue dye under visible light was investigated, showing the efficiency of 89.73% after 240 minutes of light irradiation with the presence of H2O2

Ce3+/Ce4+-Doped ZrO2/CuO Nanocomposite for Enhanced Photocatalytic Degradation of Methylene Blue under Visible Light

In recent years, photocatalysis has been used as an environmentally friendly method for the degradation of organic pigments in water. In this study, Ce3+/Ce4+-doped ZrO2/CuO as a mixed semiconductor oxide was successfully prepared by a one-step hydrothermal method. The Ce3+/Ce4+-doped ZrO2/CuO has shown high degradation efficiency of methylene blue (MB), and the maximum degradation percentage was observed to be 94.5% at 180 min under irradiation visible light. The photocatalytic activity increases significantly by doping Ce3+/Ce4+ in ZrO2/CuO for MB degradation. Ce3+/Ce4+ doping is shown to reduce the (e-/h+) recombination rate and improve the charge transfer, leading to enhanced photocatalytic activity of materials. The materials were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), FTIR, EDS, BET and diffuse reflectance spectroscopy (DRS)