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Peanut (Arachis hypogaea L.) shell, an abundant by-product of peanut production, contains a complex combination of organic compounds, including flavonoids. Changes in the total phenolic content, flavonoid content, antioxidant capacities, and skin aging-related enzyme (tyrosinase, elastase, and collagenase)-inhibitory activities of peanut shell were investigated after treatment in pressure swing reactors under controlled gas conditions using surface dielectric barrier discharge with different plasma (NOx and O3) and temperature (25 and 150 °C) treatments. Plasma treatment under ozone-rich conditions at 150 °C significantly affected the total phenolic (270.70 mg gallic acid equivalent (GAE)/g) and flavonoid (120.02 mg catechin equivalent (CE)/g) contents of peanut shell compared with the control (253.94 and 117.74 mg CE/g, respectively) (p < 0.05). In addition, with the same treatment, an increase in functional compound content clearly enhanced the antioxidant activities of components in peanut shell extracts. However, the NOx-rich treatment was significantly less effective than the O3 treatment (p < 0.05) in terms of the total phenolic content, flavonoid content, and antioxidant activities. Similarly, peanut shells treated in the reactor under O3-rich plasma conditions at 150 ℃ had higher tyrosinase, elastase, and collagenase inhibition rates (55.72%, 85.69%, and 86.43%, respectively) compared to the control (35.81%, 80.78%, and 83.53%, respectively). Our findings revealed that a reactor operated with O3-rich plasma-activated gas at 150 °C was better-suited for producing functional industrial materials from the by-products of peanuts.

The estimation of large functional and longitudinal data, which refers to the estimation of mean function, estimation of covariance function, and prediction of individual trajectory, is one of the most challenging problems in the field of high-dimensional statistics. Functional Principal Components Analysis (FPCA) and Functional Linear Mixed Model (FLMM) are two major statistical tools used to address the estimation of large functional and longitudinal data; however, the former suffers from a dramatically increasing computational burden while the latter does not have clear asymptotic properties. In this paper, we propose a computationally effective estimator of large functional and longitudinal data within the framework of FLMM, in which all the parameters can be automatically estimated. Under certain regularity assumptions, we prove that the mean function estimation and individual trajectory prediction reach the minimax lower bounds of all nonparametric estimations. Through numerous simulations and real data analysis, we show that our new estimator outperforms the traditional FPCA in terms of mean function estimation, individual trajectory prediction, variance estimation, covariance function estimation, and computational effectiveness.

The fruit of Lycium barbarum L. (FLB) has been used as medicines and functional foods for more than 2000 years in East Asia. In this study, carotenoid, phenolic, flavonoid, and polysaccharide contents as well as the antioxidant activities of FLB from 13 different regions in China from a total of 78 samples were analyzed. The results showed that total carotenoid contents ranged from 12.93 to 25.35 mg β-carotene equivalents/g DW. Zeaxanthin dipalmitate was the predominant carotenoid (4.260–10.07 mg/g DW) in FLB. The total phenolic, total flavonoid, and total polysaccharide contents ranged from 6.899 to 8.253 mg gallic acid equivalents/g DW, 3.177 to 6.144 mg rutin equivalents/g DW, and 23.62 to 42.45 mg/g DW, respectively. Rutin content ranged from 0.1812 to 0.4391 mg/g DW, and ferulic acid content ranged from 0.0994 to 0.1726 mg/g DW. All of these FLB could be divided into two clusters with PCA analysis, and both individual carotenoids and total carotenoid contents could be used as markers for regional characterization. The phenolic components were the main substance for the antioxidant activity of FLB. Considering the functional component and antioxidant activities, FLB produced in Guyuan of Ningxia was the closest to Daodi herbs (Zhongwei of Ningxia), which is commercially available high quality FLB. The results of this study could provide guidance for comprehensive applications of FLB production in different regions.

Functional diversity is regarded as a key concept for understanding the link between ecosystem function and biodiversity. The different and ecologically well‐defined aspects of the concept are reflected by the so‐called functional components , for example, functional richness and divergence. Many authors proposed that components be distinguished according to the multivariate technique on which they rely, but more recent studies suggest that several multivariate techniques, providing different functional representations (such as dendrograms and ordinations) of the community can in fact express the same functional component. Here, we review the relevant literature and find that (1) general ecological acceptance of the field is hampered by ambiguous terminology and (2) our understanding of the role of multivariate techniques in defining components is unclear. To address these issues, we provide new definitions for the three basic functional diversity components namely functional richness, functional divergence and functional regularity. In addition, we present a classification of presence‐/absence‐based approaches suitable for quantifying these components. We focus exclusively on the binary case for its relative simplicity. We find illogical, as well as logical but unused combinations of components and representations; and reveal that components can be quantified almost independently from the functional representation of the community. Finally, theoretical and practical implications of the new classification are discussed.

Rapeseed oil is the third most consumed culinary oil in the world. It is well-known for its high content of unsaturated fatty acids, especially polyunsaturated fatty acids, which make it of great nutritional value. There is increasing evidence that a diet rich in unsaturated fatty acids offers health benefits. Although the consumption of rapeseed oil cuts across many areas around the world, the nutritional elements of rapeseed oil and the exact efficacy of the nutrients remain unclear. In this review, we systematically summarized the latest studies on functional rapeseed components to ascertain which component of canola oil contributes to its function. Apart from unsaturated fatty acids, there are nine functional components in rapeseed oil that contribute to its anti-microbial, anti-inflammatory, anti-obesity, anti-diabetic, anti-cancer, neuroprotective, and cardioprotective, among others. These nine functional components are vitamin E, flavonoids, squalene, carotenoids, glucoraphanin, indole-3-Carbinol, sterols, phospholipids, and ferulic acid, which themselves or their derivatives have health-benefiting properties. This review sheds light on the health-benefiting effects of rapeseed oil in the hope of further development of functional foods from rapeseed.

Individuals with autism spectrum disorder (ASD) tend to experience greater difficulties with social communication and sensory information processing. Of particular interest in ASD biomarker research is the study of visual attention, effectively quantified in eye tracking (ET) experiments. Eye tracking offers a powerful, safe, and feasible platform for gaining insights into attentional processes by measuring moment-by-moment gaze patterns in response to stimuli. Even though recording is done with millisecond granularity, analyses commonly collapse data across trials into variables such as proportion time spent looking at a region of interest (ROI). In addition, looking times in different ROIs are typically analyzed separately. We propose a novel multivariate functional outcome that carries proportion looking time information from multiple regions of interest jointly as a function of trial type, along with a novel constrained multivariate functional principal components analysis procedure to capture the variation in this outcome. The method incorporates the natural constraint that the proportion looking times from the multiple regions of interest must sum up to one. Our approach is motivated by the Activity Monitoring task, a social-attentional assay within the ET battery of the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). Application of our methods to the ABC-CT data yields new insights into dominant modes of variation of proportion looking times from multiple regions of interest for school-age children with ASD and their typically developing (TD) peers, as well as richer analysis of diagnostic group differences in social attention.

In this paper, we group South American countries based on the number of infected cases and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Peru, Paraguay, Uruguay, and Venezuela. The data used are collected from a database of Johns Hopkins University, an institution that is dedicated to sensing and monitoring the evolution of the COVID-19 pandemic. A statistical analysis, based on principal components with modern and recent techniques, is conducted. Initially, utilizing the correlation matrix, standard components and varimax rotations are calculated. Then, by using disjoint components and functional components, the countries are grouped. An algorithm that allows us to keep the principal component analysis updated with a sensor in the data warehouse is designed. As reported in the conclusions, this grouping changes depending on the number of components considered, the type of principal component (standard, disjoint or functional) and the variable to be considered (infected cases or deaths). The results obtained are compared to the k-means technique. The COVID-19 cases and their deaths vary in the different countries due to diverse reasons, as reported in the conclusions.

The growth of functional components containing agricultural foods is enhancing because these components aid the human body against different chronic diseases. Currently, chia seeds basically belong to the mint family and are edible seeds of Salvia hispanica. These seeds are composed of different functional components including fiber, polyphenols, antioxidants, omega‐3 fatty acid vitamins, minerals, and peptides. Besides, these seeds are also a good source of vegetable protein, unsaturated fat, carbohydrates, and ash. Chia seed components are helpful in cardiovascular disease (CVD) by reducing blood pressure, platelet aggregation, cholesterol, and oxidation. In GI‐tract‐related diseases like diabetes and constipation, chia fiber reduces the blood glucose level and provides bulk to stool. However, antioxidants and polyphenols are protected beta cells of the pancreas from inflammation. These components are protected from the cell damage of the different body parts, which can provide help in different types of cancer including breast, colorectal, liver, and pancreatic. Conclusively, some pervious studies approved that chia seed components are played important role in chronic diseases. Conclusively, chia seeds components are played important role in chronic diseases that approved by different previous studies.

Eye tracking (ET) experiments commonly record the continuous trajectory of a subject’s gaze on a two-dimensional screen throughout repeated presentations of stimuli (referred to as trials). Even though the continuous path of gaze is recorded during each trial, commonly derived outcomes for analysis collapse the data into simple summaries, such as looking times in regions of interest, latency to looking at stimuli, number of stimuli viewed, number of fixations, or fixation length. In order to retain information in trial time, we utilize functional data analysis (FDA) for the first time in literature in the analysis of ET data. More specifically, novel functional outcomes for ET data, referred to as viewing profiles, are introduced that capture the common gazing trends across trial time which are lost in traditional data summaries. Mean and variation of the proposed functional outcomes across subjects are then modeled using functional principal component analysis. Applications to data from a visual exploration paradigm conducted by the Autism Biomarkers Consortium for Clinical Trials showcase the novel insights gained from the proposed FDA approach, including significant group differences between children diagnosed with autism and their typically developing peers in their consistency of looking at faces early on in trial time.

A metamaterial-inspired varactor-tuned antenna with frequency reconfigurability and pattern diversity is designed. Two different versions of a reconfigurable structure are integrated into a single antenna to excite two different orthogonal patterns, which realizes pattern diversity for MIMO applications. The outer annular Composite Right-/Left-Handed Transmission Line (CRLH-TL) works at the 1 mode and provides a broadside pattern, and the inner circular radiator loaded with split ring resonators (SRR) operates at the 0 mode and radiates an omnidirectional pattern, which realizes pattern diversity. By using surface-mounted varactors, the operating frequencies for the two radiation patterns can be tuned over a wide frequency range, from 1.7 GHz to 2.2 GHz, covering the 1.71–2.17 GHz LTE band, and a low mutual coupling between the two radiators is achieved. The antenna has also been prototyped. The measured results are in good agreement with the simulation results, verifying the proposed concept. The dual-mode MIMO system equipped with the proposed antenna elements is discussed within the context of a 3-D channel model, and it shows a superior array compactness and spectral efficiency (SE) performance compared to scenarios with single-mode elements.