Rapid determination of volatile constituents in safflower from Xinjiang and Henan by ultrasonic-assisted solvent extraction and GC–MS

AbstractThe total volatile components were extracted from safflower by ultrasonic-assisted solvent extraction (USE) and their chemical constituents were analyzed by gas chromatography–mass spectrometry (GC–MS) to provide scientific basis for the quality control of safflower. Five different solvents (diethyl ether, ethanol, ethyl acetate, dichloromethane and acetone) were used and compared in terms of number of volatile components extracted and the peak areas of these components in TIC. The results showed that USE could be used as an efficient and rapid method for extracting the volatile components from safflower. It also could be found that the number of components in the TIC of ethyl acetate extract was more than that in the TIC of other solvent ones. Meanwhile, the volatile components of safflower from Xinjiang Autonomous Region and Henan Province of China were different in chemical components and relative contents. It could be concluded that both the extraction solvents and geographical origin of safflower are responsible for these differences. The experimental results also indicated that USE/GC–MS is a simple, rapid and effective method to analyze the volatile oil components of safflower

Meeting Dividend Thresholds through Earnings Management: A Cross-cultural Comparison

Culture affects accounting rules and practices. Dividend distribution influences corporate operating decisions, and a previous year’s dividends represent an earnings threshold. This study collected various countries’ data from 2004 to 2014 from the COMPUSTAT database and analyzed how cultural factors influence the management of income to achieve a dividend threshold (i.e., desired earnings goal). Prospect theory reported that managers making decisions focus on the value from gains or losses with a certain reference point rather than the levels of wealth. The empirical results show that managers of listed firms in societies that exhibit uncertainty-avoidance, individualistic, power-distance, and masculinity meet or exceed dividend thresholds, whereas those in long term orientation societies do not. These findings emphasize the strong and direct effect of cultural values on meeting or exceeding dividend thresholds through earnings management over multiple years. In addition, our empirical results suggest that investors evaluate firm performance (i.e., earnings) before dividends are paid, which should be considered by financial market participants and regulators when assessing financial statements and the reliability of financial reporting among multiple countries. We only used a modified Jones model to measure earnings management. Therefore, tradeoff tools (i.e., real activities or other DA models) should be used to examine earnings management among managers to ensure the robustness of future studies

Learning Domain Invariant Representations for Generalizable Person Re-Identification

Generalizable person Re-Identification (ReID) has attracted growing attention in recent computer vision community. In this work, we construct a structural causal model among identity labels, identity-specific factors (clothes/shoes color etc), and domain-specific factors (background, viewpoints etc). According to the causal analysis, we propose a novel Domain Invariant Representation Learning for generalizable person Re-Identification (DIR-ReID) framework. Specifically, we first propose to disentangle the identity-specific and domain-specific feature spaces, based on which we propose an effective algorithmic implementation for backdoor adjustment, essentially serving as a causal intervention towards the SCM. Extensive experiments have been conducted, showing that DIR-ReID outperforms state-of-the-art methods on large-scale domain generalization ReID benchmarks

Visual Tracking via Feature Tensor Multimanifold Discriminate Analysis

In the visual tracking scenarios, if there are multiple objects, due to the interference of similar objects, tracking may fail in the progress of occlusion to separation. To address this problem, this paper proposed a visual tracking algorithm with discrimination through multimanifold learning. Color-gradient-based feature tensor was used to describe object appearance for accommodation of partial occlusion. A prior multimanifold tensor dataset is established through the template matching tracking algorithm. For the purpose of discrimination, tensor distance was defined to determine the intramanifold and intermanifold neighborhood relationship in multimanifold space. Then multimanifold discriminate analysis was employed to construct multilinear projection matrices of submanifolds. Finally, object states were obtained by combining with sequence inference. Meanwhile, the multimanifold dataset and manifold learning embedded projection should be updated online. Experiments were conducted on two real visual surveillance sequences to evaluate the proposed algorithm with three state-of-the-art tracking methods qualitatively and quantitatively. Experimental results show that the proposed algorithm can achieve effective and robust effect in multi-similar-object mutual occlusion scenarios

Dynamic Cerebral Autoregulation Remains Stable During the Daytime (8 a.m. to 8 p.m.) in Healthy Adults

Many functions of the human body possess a daily rhythm, disruptions of which often lead to disease. Dynamic cerebral autoregulation (dCA) stabilizes the cerebral blood flow to prompt normal neural function. However, whether dCA is stable across the day remains unknown. This study aimed to investigate the daily rhythm of dCA. Fifty-one healthy adults (38.294 ± 13.279 years, 40 females) were recruited and received six dCA measurements per individual that were conducted at predefined time points: 8:00, 9:00, 11:00, 14:00, 17:00, and 20:00. Although the blood pressure fluctuated significantly, there was no statistical difference in phase difference and gain (autoregulatory parameters) across the six time points. This study demonstrates that dCA remains stable during the interval from 8 a.m. to 8 p.m. and underscores the importance of stable dCA in maintaining cerebral blood flow and neural function

Modulating Linker Composition of Haptens Resulted in Improved Immunoassay for Histamine.

Histamine (HA) is an important food contaminant generated during food fermentation or spoilage. However, an immunoassay for direct (derivatization free) determination of HA has rarely been reported due to its small size to induce the desired antibodies by its current hapten-protein conjugates. In this work, despite violating the classical hapten design criteria which recommend introducing a linear aliphatic (phenyl free) linker into the immunizing hapten, a novel haptens, HA-245 designed and synthesized with a phenyl-contained linker, exhibited significantly enhanced immunological properties. Thus, a quality-improved monoclonal antibody (Mab) against HA was elicited by its hapten-carrier conjugates. Then, as the linear aliphatic linker contained haptens, Hapten B was used as linker-heterologous coating haptens to eliminate the recognition of linker antibodies. Indirect competitive ELISA (ic-ELISA) was developed with a 50% inhibition concentration (IC50) of 0.21 mg/L and a limit of detection (LOD) of 0.06 mg/L in buffer solution. The average recoveries of HA from spiked food samples for this ic-ELISA ranged from 84.1% and 108.5%, and the analysis results agreed well with those of referenced LC-MS/MS. This investigation not only realized derivatization-free immunoassay for HA, but also provided a valuable guidance for hapten design and development of immunoassay for small molecules