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Enhancing the sensory appeal of jasmine instant tea, particularly its aroma, poses a significant challenge due to the loss of volatile organic compounds during conventional processing. This study introduces a novel approach to address this issue through the application of microencapsulation techniques, aimed at preserving these key aromatic elements. Our investigation focused on the encapsulating agents gelatin, acacia gum, carboxymethylcellulose (CMC), and maltodextrin, chosen for their compatibility with the volatile organic compounds of tea. A statistical analysis was conducted on the analytical results through comprehensive analytical techniques like Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and Variable Importance in Projection (VIP) analysis for microcapsule characterization. The statistical analysis revealed gelatin to be a particularly effective encapsulating medium, preserving an aroma profile more akin to fresh tea. The statistical analysis confirmed the reliability of these findings, highlighting the potential of microencapsulation in refining the quality of jasmine instant tea products. The results of this research suggest that microencapsulation could be instrumental in improving the sensory quality and shelf life of instant tea products, offering new opportunities for product enhancement in the beverage industry. [ABSTRACT FROM AUTHOR]

The nation faces critical shortages of Hispanic science, technology, engineering, and mathematics (STEM) college graduates--especially in physics. To address youth lack of awareness about physics careers, physics educators at the University of Texas Rio Grande Valley implemented a strategic intervention anchored in Modern Expectancy-Value Theory, Physics Career Education Day, in collaboration with two local school districts. Presurvey and postsurvey results have shown that this intervention significantly increased student awareness and interest in physics careers.

Under low-frequency background noise environments, due to the characteristics of poor stability and many interference targets of noise, the detection of unknown low-frequency sonar signals faces huge challenge. And sonar pulse signal detection methods based on time domain or frequency domain have the limitation of insufficient detection Signal-to-Noise Ratio (SNR). In order to improve the detection capability of weak sonar pulse signal in low frequency background noise environments, a Detection method based on normalized short-time Fourier transform-Radon transform for Low frequency Sonar pulse signal (DNLS) is proposed, which is a constant false alarm detection method in normalized short-time Fourier transform-Radon transform domain. In DNLS method, after the normalized short-time Fourier transform-Radon transformation, low-frequency noise energy to be dispersed into the entire transformation domain, and the sonar pulse signal energy containing the Linear Frequency Modulation (LFM) component is concentrated at a specific target point in the normalized short-time Fourier transform-Radon transform transformation domain, which can obtain a higher local SNR than the time-domain SNR. Moreover, the specific target point is distinguishable from the background noise, and the impulse signal detection decision is completed by constructing hypothesis test statistics on the target point data. The DNLS method solves the detection problems of low-frequency background such as poor stability, large fluctuations, and more interference. And the method of obtaining the test statistics of the constant false alarm detection, estimating the background noise and calculating the detection threshold is given. Extensive simulation results and actual data processing show that, under the simulation condition, in the minimum detection SNR of LFM, Continuous Wave(CW)-LFM and pulse trains of frequency modulated pulse signals with the same pulse width, compared with the dual-threshold constant false alarm rate energy detection method, the DNLS method is improved by 15dB, 13dB and 4dB, respectively. Under actual data conditions, in the detection of CW-LFM pulse signals with the same pulse width, compared with the double-threshold constant false alarm rate energy detection method, the detection performance of the DNLS method in the case of no ship radiated noise interference and strong radiated noise interference improves by 5dB and 5.5dB, respectively. The data analysis results show that the DNLS method has very good detection performance for LFM, pulse trains of frequency modulated, CW-LFM and other sonar pulse signals at low SNR, and can effectively detect the sonar pulse signals under the background of strong ship radiated noise.

The National Academy of Science has published studies showing strong scientific evidence that global warming is caused by human consumption of fossil fuels, yet recent surveys have shown young adults in the U.S. are disengaged or disagree with this fact. Accordingly, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) published learning objectives to educate the world population on global warming and renewable energy by 2030. In this paper, we introduce a reflective writing activity physics educators can employ to foster a deeper understanding of global warming in introductory college physics and physical science courses, without overloading their teaching time.

Molecular dynamics (MD) simulations have become a powerful tool for investigating electrical double layers (EDLs), which play a crucial role in various electrochemical devices. In this Review, we provide a comprehensive overview of the techniques used in MD simulations for EDL studies, with a particular focus on methods for describing electrode polarization, and examine the principle behind these methods and their varying applicability. The applications of these approaches in supercapacitors, capacitive deionization, batteries, and electric double-layer transistors are explored, highlighting recent advancements and insights in each field. Finally, we emphasize the challenges and potential directions for future developments in MD simulations of EDLs, such as considering movable electrodes, improving electrode property representation, incorporating chemical reactions, and enhancing computational efficiency to deepen our understanding of complex electrochemical processes and contribute to the progress in the field involving EDLs. [ABSTRACT FROM AUTHOR]