A comparative metabolomics analysis of Açaí (Euterpe oleracea Mart.) fruit, food powder, and botanical dietary supplement extracts.

Introduction: Euterpe oleracea Mart. (açaí) is a botanical of interest to many who seek functional foods that provide antioxidant and anti-inflammatory properties. Cancer patients are increasingly taking botanical dietary supplements containing açaí to complement their conventional therapeutics, which may lead to serious adverse events.

CW_ICA: an efficient dimensionality determination method for independent component analysis.

Independent component analysis (ICA) is a widely used blind source separation method for signal pre-processing. The determination of the number of independent components (ICs) is crucial for achieving optimal performance, as an incorrect choice can result in either under-decomposition or over-decomposition. In this study, we propose a robust method to automatically determine the optimal number of ICs, named the column-wise independent component analysis (CW_ICA).

Regulation of friction pair to promote conversion of mechanical energy to chemical energy on BiWO and realization of enhanced tribocatalytic activity to degrade different pollutants.

Recently, friction-induced tribocatalysis has received tremendous attention through converting mechanical energy to chemical energy. However, its efficiency is much lower than those of photocatalysis and piezocatalysis, and its environmental application is limited in dye degradation. Herein, we developed a facile approach to improve the tribocatalytic activity of BiWO via adding trace polymer powders to form friction pairs with BiWO.

Strain-Level Discrimination of Bacteria by Liquid Chromatography and Paper Spray Ion Mobility Mass Spectrometry.

Determining bacterial identity at the strain level is critical for public health to enable proper medical treatments and reduce antibiotic resistance. Herein, we used liquid chromatography, ion mobility, and tandem MS (LC-IM-MS/MS) to distinguish () strains. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) showed the capability of this method to perform strain-level discrimination with prediction rates of 96.

Enhanced photocatalytic activity of S-doped graphitic carbon nitride hollow microspheres: Synergistic effect, high-concentration antibiotic elimination and antibacterial behavior.

For the past few years, graphitic carbon nitride (g-CN) has been widely used to eliminate environmental pollutants, but limited active site on surface and low separation/migration ability suppress its practical uses. Herein, we adopted a supramolecular self-assembly route followed with S doping to synthesize S-doped g-CN with a hollow microsphere composition (SCNHM), where the shell was demonstrated to compose of ultrathin nanosheets. The unique structural characteristics endow the SCNHM with high specific surface area (∼81 m g) to provide abundant reaction sites and enhanced light-harvesting due to the light-scattering effect of hollow structure.

Determination of the key role to affect the piezocatalytic activity of graphitic carbon nitride for tetracycline hydrochloride degradation in water.

Graphitic carbon nitride (g-CN) has been proved to possess intrinsic piezoelectricity and its two-dimensional (2D) nanosheets present piezocatalytic activity to produce hydrogen from water splitting and eliminate organic pollutants in wastewater. Specific surface area and piezoelectric polarization are of great significance to achieve high piezocatalytic activity, but it is difficult to simultaneously improve both of them. Herein, to reveal the dominant role in the piezocatalysis of g-CN, we investigated the effect of exfoliation level on the piezocatalytic activity for degrading tetracycline hydrochloride (TC).

Classification of EEG signals: An interpretable approach using functional data analysis.

Electroencephalography (EEG) is a noninvasive method to record electrical activity of the brain. The EEG data is continuous flow of voltages, in this paper, we consider them as functional data, and propose a three-stage algorithm based on functional data analysis, with the advantage of interpretability. Specifically, the time and frequency information are extracted by wavelet transform in the first stage.

Influencing Factors and Countermeasures of the Health of Residents in the City Clusters Along the Middle Reaches of the Yangtze River.

This paper introduces several factors, namely, environmental pollution, medical level and environmental governance, into the Grossman's production function for health. Then, an empirical analysis was conducted based on the 2004-2016 panel data of the city clusters along the middle reaches of the Yangtze River. Through the analysis, the author evaluated and compared how different factors affect the health of residents in the three city clusters: Changsha-Zhuzhou-Xiangtan (CZT) city cluster, Wuhan city cluster and circum-Poyang Lake (CPL) city cluster.