bluuebunny/crossref_metadata_2025 huggingface dataset:
Open-Source Design and Economics of Manual Variable-Tilt Angle DIY Wood-Based Solar Photovoltaic Racking System
Authors: Vandewetering Nicholas , Hayibo Koami Soulemane , Pearce Joshua M.
Published: June 2022

Fixed-tilt mechanical racking, consisting of proprietary aluminum extrusions, can dominate the capital costs of small-scale solar photovoltaic (PV) systems. Recent design research has shown that wood-racking can decrease the capital costs of small systems by more than 75% in North America. To determine if wood racking provides enough savings to enable labor to be exchanged profitably for higher solar electric output, this article develops a novel variable tilt angle open-source wood-based do-it-yourself (DIY) PV rack that can be built and adjusted at exceptionally low costs. A detailed levelized cost of electricity (LCOE) production analysis is performed after the optimal monthly tilt angles are determined for a range of latitudes. The results show the racking systems with an optimal variable seasonal tilt angle have the best lifetime energy production, with 5.2% more energy generated compared to the fixed-tilt system (or 4.8% more energy, if limited to a maximum tilt angle of 60°). Both fixed and variable wooden racking systems show similar LCOE, which is only 29% of the LCOE of commercial metal racking. The results of this study indicate that the novel variable tilt rack, whether used as a small-scale DIY project or scaled up to fulfill larger energy demands, provides both the lowest cost option even when modest labor costs are included and also may provide specific advantages for applications such as agrivoltaics.
Development of Machine-Learning Model to Predict COVID-19 Mortality: Application of Ensemble Model and Regarding Feature Impacts
Authors: Baik Seung-Min , Lee Miae , Hong Kyung-Sook , Park Dong-Jin
Published: June 2022

This study was designed to develop machine-learning models to predict COVID-19 mortality and identify its key features based on clinical characteristics and laboratory tests. For this, deep-learning (DL) and machine-learning (ML) models were developed using receiver operating characteristic (ROC) area under the curve (AUC) and F1 score optimization of 87 parameters. Of the two, the DL model exhibited better performance (AUC 0.8721, accuracy 0.84, and F1 score 0.76). However, we also blended DL with ML, and the ensemble model performed the best (AUC 0.8811, accuracy 0.85, and F1 score 0.77). The DL model is generally unable to extract feature importance; however, we succeeded by using the Shapley Additive exPlanations method for each model. This study demonstrated both the applicability of DL and ML models for classifying COVID-19 mortality using hospital-structured data and that the ensemble model had the best predictive ability.
Artificial Intelligence-Based Detection of Pneumonia in Chest Radiographs
Authors: Becker Judith , Decker Josua A. , Römmele Christoph , Kahn Maria , Messmann Helmut , Wehler Markus , Schwarz Florian , Kroencke Thomas , Scheurig-Muenkler Christian
Published: June 2022

Artificial intelligence is gaining increasing relevance in the field of radiology. This study retrospectively evaluates how a commercially available deep learning algorithm can detect pneumonia in chest radiographs (CR) in emergency departments. The chest radiographs of 948 patients with dyspnea between 3 February and 8 May 2020, as well as 15 October and 15 December 2020, were used. A deep learning algorithm was used to identify opacifications associated with pneumonia, and the performance was evaluated by using ROC analysis, sensitivity, specificity, PPV and NPV. Two radiologists assessed all enrolled images for pulmonal infection patterns as the reference standard. If consolidations or opacifications were present, the radiologists classified the pulmonal findings regarding a possible COVID-19 infection because of the ongoing pandemic. The AUROC value of the deep learning algorithm reached 0.923 when detecting pneumonia in chest radiographs with a sensitivity of 95.4%, specificity of 66.0%, PPV of 80.2% and NPV of 90.8%. The detection of COVID-19 pneumonia in CR by radiologists was achieved with a sensitivity of 50.6% and a specificity of 73%. The deep learning algorithm proved to be an excellent tool for detecting pneumonia in chest radiographs. Thus, the assessment of suspicious chest radiographs can be purposefully supported, shortening the turnaround time for reporting relevant findings and aiding early triage.
Employment Support and COVID-19: Is Working Time Reduction the Right Tool?
Authors: Aldieri Luigi , Bruno Bruna , Vinci Concetto Paolo
Published: June 2022

The main objectives of this study are to take into account the effects of COVID-19 on labor market functioning, and to evaluate the effects of policies regarding working time reduction, in terms of both containing the spread of infection and economic activity. Accordingly, we describe a macroeconomic model wherein we test the effects of reducing working hours in the Keynesian unemployment framework, which comprises a fixed prices and wages regime, and a consumption demand that is dependent on salaries and autonomous demand components. Moreover, we also describe a neoclassical unemployment framework, wherein the labor market is only governed by dynamic demand forces. Theoretical results show that, according to the epidemiological phase, a reduction in working hours may be a good policy for containing the virus and improving employment in the Keynesian framework when established conditions are maintained. In the neoclassical framework, a work sharing policy will fail if some conditions do not occur, and it could cause an increase in the spread of the virus when a reduction of epidemic containment measures occurs. Employment will increase when the pandemic ends. A numerical simulation confirms that a reduction in working hours could reduce virus diffusion, but only under established, constrained parameters in both frameworks.
Determinants of Qualified Investor Sentiment during the COVID-19 Pandemic in North America, Asia, and Europe
Authors: Reis Pedro M. Nogueira
Published: June 2022

This work delineates the factors determining investor sentiment in specific regions during the pandemic and the influence of attitudes towards vaccination. The findings show that the reactions of knowledgeable investors in different regions to the economic effects of the pandemic were not uniform but depended on a variety of individual factors. Risk perception varied widely due to idiosyncrasies in specific countries and regions, the level of pandemic information, reaction to case reports and deaths, attitudes towards vaccination, lockdown compliance, and government measures to support businesses. These various elements combined to create different outlooks in the minds of investors that strongly influenced their investment strategies. For this investigation, we tested three estimation models: the classic robust standard error for time series regression, the new robust standard errors regression, and the Prais robust estimation. This study applied the lasso system of machine learning to select relevant explanatory variables. The novelty of our work resides in its analysis of the conduct of informed investors, using a reliable proxy, and the discussion of how government policies and different pandemic-related factors, specifically the vaccination status, affected investor sentiment in different regions. As for practical implications, an understanding of how the various economic factors related to the pandemic influenced the behavior of qualified investors in different regions can help regulators, government leaders, fund managers, and investors deal with a future virus outbreak.
Remote Teaching, Self-Resilience, Stress, Professional Efficacy, and Subjective Health among Israeli PE Teachers during the COVID-19 Pandemic
Authors: Ben Amotz Ronit , Green Gizell , Joseph Gili , Levi Sharon , Manor Niva , Ng Kwok , Barak Sharon , Hutzler Yeshayahu , Tesler Riki
Published: June 2022

This study investigated demographic factors, teaching characteristics, psychological characteristics, school-related characteristics, professional efficacy, and subjective health perceptions among PE teachers during the COVID-19 pandemic. We conducted a cross-sectional research design. Questionnaires were distributed to PE teachers online during COVID-19 closures. PE teachers (N = 757) from elementary, middle, and high schools in Israel voluntary completed surveys on the topics of stress levels, self-resilience, remote teaching, professional efficacy, and subjective health perception. Sex, remote-teaching experience and clear remote school policy significantly predicted professional efficacy. Sex, teaching experience and self-resilience significantly predicted subjective health perception. This study demonstrated the need for a clear remote policy, as it likely empowers teacher professional efficacy. Transparent procedures and guidelines, along with clarifying remote policies by a supportive administration, are important for the professional efficacy of PE teachers. In addition, educational programs that are aimed at developing and strengthening the values of a healthy, positive, and balanced lifestyle are important to subjective health perception among PE teachers.
Kernel-Based Real-Time File Access Monitoring Structure for Detecting Malware Activity
Authors: Han Sung-Hwa , Lee Daesung
Published: June 2022

Obfuscation and cryptography technologies are applied to malware to make the detection of malware through intrusion prevention systems (IPSs), intrusion detection systems (IDSs), and antiviruses difficult. To address this problem, the security requirements for post-detection and proper response are presented, with emphasis on the real-time file access monitoring function. However, current operating systems provide only file access control techniques, such as SELinux (version 2.6, Red Hat, Raleigh, NC, USA) and AppArmor (version 2.5, Immunix, Portland, OR, USA), to protect system files and do not provide real-time file access monitoring. Thus, the service manager or data owner cannot determine real-time unauthorized modification and leakage of important files by malware. In this paper, a structure to monitor user access to important files in real time is proposed. The proposed structure has five components, with a kernel module interrelated to the application process. With this structural feature, real-time monitoring is possible for all file accesses, and malicious attackers cannot bypass this file access monitoring function. By verifying the positive and negative functions of the proposed structure, it was validated that the structure accurately provides real-time file access monitoring function, the monitoring function resource is sufficiently low, and the file access monitoring performance is high, further confirming the effectiveness of the proposed structure.
Magnetic Resonance Wire Coil Losses Estimation with Finite-Difference Time-Domain Method
Authors: Giovannetti Giulio , Wang Yong , Jayakumar Naveen Kumar Tumkur , Barney Jeff , Tiberi Gianluigi
Published: June 2022

Radiofrequency (RF) coils are used to transmit and receive signals in magnetic resonance (MR) systems. Optimized RF coil design has to take into account strategies to maximize the coil performance by choosing coil sizes and geometry for achieving the best signal-to-noise ratio (SNR). In particular, coil conductor and radiative loss contributions strongly affect the SNR value, with the first mainly playing a role in low-field MR systems especially, while the second could be the dominant coil loss mechanism for high-frequency tuned coils. This paper investigates the accuracy of the finite-difference time-domain (FDTD) method for separately estimating coil conductor and radiative loss contributions. Comparison with finite element method (FEM) analysis and workbench measurements performed on a home-built coil prototype permitted us to validate the simulation results. Moreover, this research, jointly with literature data on sample-induced losses estimation, demonstrates that an FDTD-based solver permits providing an SNR model for coils with various and complicated geometries.
Ground Pedestrian and Vehicle Detections Using Imaging Environment Perception Mechanisms and Deep Learning Networks
Authors: Liu Haoting , Chen Shuai , Zheng Na , Wang Yuan , Ge Jianyue , Ding Kai , Guo Zhenhui , Li Wei , Lan Jinhui
Published: June 2022

In order to build a robust network for the unmanned aerial vehicle (UAV)-based ground pedestrian and vehicle detection with a small number of training datasets but strong luminance environment adaptability, a system that considers both environment perception computation and a lightweight deep learning network is proposed. Because the visible light camera is sensitive to complex environmental lights, the following computational steps are designed: First, entropy-based imaging luminance descriptors are calculated; after image data are transformed from RGB to Lab color space, the mean-subtracted and contrast-normalized (MSCN) values are computed for each component in Lab color space, and then information entropies were estimated using MSCN values. Second, environment perception was performed. A support vector machine (SVM) was trained to classify the imaging luminance into excellent, ordinary, and severe luminance degrees. The inputs of SVM are information entropies; the output is the imaging luminance degree. Finally, six improved Yolov3-tiny networks were designed for robust ground pedestrian and vehicle detections. Extensive experiment results indicate that our mean average precisions (MAPs) of pedestrian and vehicle detections can be better than ~80% and ~94%, respectively, which overmatch the corresponding results of ordinary Yolov3-tiny and some other deep learning networks.
Optimized Seam-Driven Image Stitching Method Based on Scene Depth Information
Authors: Chen Xin , Yu Mei , Song Yang
Published: June 2022

It is quite challenging to stitch images with continuous depth changes and complex textures. To solve this problem, we propose an optimized seam-driven image stitching method considering depth, color, and texture information of the scene. Specifically, we design a new energy function to reduce the structural distortion near the seam and improve the invisibility of the seam. By additionally introducing depth information into the smoothing term of energy function, the seam is guided to pass through the continuous regions of the image with high similarity. The experimental results show that benefiting from the new defined energy function, the proposed method can find the seam that adapts to the depth of the scene, and effectively avoid the seam from passing through the salient objects, so that high-quality stitching results can be achieved. The comparison with the representative image stitching methods proves the effectiveness and generalization of the proposed method.
Data-Based Engine Torque and NOx Raw Emission Prediction
Authors: Yuan Zheng , Shi Xiuyong , Jiang Degang , Liang Yunfang , Mi Jia , Fan Huijun
Published: June 2022

Low accuracy is the main challenge that plagues the application of engine modeling technology at present. In this paper, correlation analysis technology is used to analyze the main influencing factors of engine torque and NOx (nitrogen oxides) raw emission performance from a statistical point of view, and on this basis, the regression algorithm is used to construct the engine torque and NOx emission prediction model. The prediction RMSE between engine torque prediction value and true value reaches 4.6186, and the torque prediction R2 reaches 1.00. Prediction RMSE between NOx emission prediction value and true value reaches 67.599, and NOx emission prediction R2 reaches 0.99. When using the new WHTC data for model prediction verification, the RMSE between the engine torque predicted value and true value reaches 4.9208, and the prediction accuracy reaches 99.60%, the RMSE between NOx emission prediction value and true value reaches 72.38, and the prediction accuracy reaches 99.2%, indicating that the model is relatively accurate. The evaluation result of the ambient temperature impact on torque shows that ambient temperature is positively correlated with engine torque.
Risk Management of a Fusion Facility: Radiation Protection and Safety Integrated Approach for the Sorgentina-RF Project
Authors: Contessa Gian Marco , Terranova Nicholas , Pinna Tonio , Dongiovanni Danilo Nicola , D’Arienzo Marco , Moro Fabio , Ferrari Paolo , Pietropaolo Antonino ,   The SRF Collaboration
Published: June 2022

The Sorgentina-RF project will use fusion neutrons to produce 99Mo, a precursor of 99mTc, by irradiating natural molybdenum. 99Mo is produced by means of the inelastic reaction 100Mo(n, 2n)99Mo on 100Mo, which is an isotope of natural Mo. From a functional point of view, the project consists of two parts: an irradiation neutron source at 14 MeV and a radiochemistry facility dedicated to the extraction of 99Mo from the solid sample irradiated by the neutron source. Given the degree of complexity of such a facility, the risk management strategy is based on an integrated approach that combines the engineering method of safety with that of radiation protection. Therefore, design issues were studied and systems were planned according to both radiation protection and safety criteria already in the preliminary phase, allowing a general strengthening of the safety of the plant. This work discusses the preventive analysis and the related activities to identify the ways in which potential exposures to radiation may occur. In particular, the preliminary safety analysis is presented for the innovative rotating target, developed for the project, and, accordingly, some specific technical solutions are given to refine the initial design of the facility.
A Multistage Stochastic Program to Optimize Prescribed Burning Locations Using Random Fire Samples
Authors: Nguyen Dung , Wei Yu
Published: June 2022

Selecting the optimal locations and timing for prescribed burning is challenging when considering uncertainties in weather, fire behavior, and future fire suppression. In this study, we present a sample average approximation (SAA) based multistage stochastic mixed integer program with recourse to optimize prescribed burning decisions. The recourse component of the SAA model considers post-fuel-treatment suppression decisions to manage fire spreads in multiple future planning periods. Our research aims at studying how an SAA model may benefit from using random fire samples to find good locations for prescribed burning during the first planning period. Two hypothetical test cases are designed to compare the impact of fire sample sizes on solution quality, and to illustrate how to identify high-quality period-one prescribed burning solutions. Results suggest that running SAA models using larger fire sample sizes can lead to better period-one solutions, but this benefit will diminish after the sample size reaches to certain thresholds. We found multiple period-one prescribed burning decisions that may result in similar effects in mitigating future wildfire risks.
Dynamic Variations in Rumen Fermentation Characteristics and Bacterial Community Composition during In Vitro Fermentation
Authors: Wei Xiao , Ouyang Kehui , Long Tanghui , Liu Zuogui , Li Yanjiao , Qiu Qinghua
Published: June 2022

This study aimed to explore the dynamic variations of rumen fermentation characteristics and bacterial community composition during a 24 h in vitro fermentation. A total of twenty-three samples were collected from original rumen fluid (ORF, n = 3), fermentation at 12 h (R12, n = 10), and fermentation at 24 h (R24, n = 10). Results showed that gas production, concentrations of microbial crude protein, ammonia nitrogen, and individual volatile fatty acids (VFA), as well as total VFA and branched-chain VFA concentrations, were higher in R24 when compared with R12 (p < 0.05). However, no significant differences were observed in acetate to propionate ratio and fermentation efficiency between R12 and R24 (p > 0.05). Bacterial diversity analysis found that Shannon index and Simpson index were higher in R24 (p < 0.05), and obvious clusters were observed in rumen bacterial community between R12 and R24. Taxonomic analysis at the phylum level showed that the abundances of Proteobacteria and Fibrobacteres were higher in R12 than that in R24, and inverse results were observed in Bacteroidetes, Firmicutes, Cyanobacteria, Verrucomicrobia, Lentisphaerae, and Synergistetes abundances. Taxonomic analysis at the genus level revealed that the abundances of Rikenellaceae RC9 gut group, Succiniclasticum, Prevotellaceae UCG-003, Christensenellaceae R-7 group, Ruminococcaceae UCG-002, Veillonellaceae UCG-001, and Ruminococcaceae NK4A214 group were higher in R24, whereas higher abundances of Succinivibrionaceae UCG-002, Ruminobacter, and Fibrobacter, were found in R12. Correlation analysis revealed the negative associations between gas production and abundances of Proteobacteria, Succinivibrionaceae UCG-002, and Ruminobacter. Moreover, the abundances of Firmicutes, Rikenellaceae RC9 gut group, Christensenellaceae R-7 group, and Ruminococcaceae UCG-002 positively correlated with VFA production. These results indicate that both rumen fermentation characteristics and bacterial community composition were dynamic during in vitro fermentation, whereas the fermentation pattern, efficiency, and bacterial richness remained similar. This study provide insight into the dynamics of rumen fermentation characteristics and bacterial composition during in vitro fermentation. This study may also provide a reference for decision-making for the sampling time point when conducting an in vitro fermentation for bacterial community investigation.
Rhizopus oryzae for Fumaric Acid Production: Optimising the Use of a Synthetic Lignocellulosic Hydrolysate
Authors: Swart Reuben Marc , Brink Hendrik , Nicol Willie
Published: June 2022

The hydrolysis of lignocellulosic biomass opens an array of bioconversion possibilities for producing fuels and chemicals. Microbial fermentation is particularly suited to the conversion of sugar-rich hydrolysates into biochemicals. Rhizopus oryzae ATCC 20344 was employed to produce fumaric acid from glucose, xylose, and a synthetic lignocellulosic hydrolysate (glucose–xylose mixture) in batch and continuous fermentations. A novel immobilised biomass reactor was used to investigate the co-fermentation of xylose and glucose. Ideal medium conditions and a substrate feed strategy were then employed to optimise the production of fumaric acid. The batch fermentation of the synthetic hydrolysate at optimal conditions (urea feed rate 0.625mgL−1h−1 and pH 4) produced a fumaric acid yield of 0.439gg−1. A specific substrate feed rate (0.164gL−1h−1) that negated ethanol production and selected for fumaric acid was determined. Using this feed rate in a continuous fermentation, a fumaric acid yield of 0.735gg−1 was achieved; this was a 67.4% improvement. A metabolic analysis helped to determine a continuous synthetic lignocellulosic hydrolysate feed rate that selected for fumaric acid production while achieving the co-fermentation of glucose and xylose, thus avoiding the undesirable carbon catabolite repression. This work demonstrates the viability of fumaric acid production from lignocellulosic hydrolysate; the process developments discovered will pave the way for an industrially viable process.
An Indoor Smart Parking Algorithm Based on Fingerprinting
Authors: Stranieri Silvia
Published: June 2022

In the last few years, researchers from many research fields are investigating the problem affecting all the drivers in big and populated cities: the parking problem. In outdoor environments, the problem can be solved by relying on vehicular ad hoc networks, which guarantee communication among vehicles populating the network. When it comes to indoor settings, the problem gets harder, since drivers cannot count on classic GPS localization. In this work, a smart parking solution for a specific indoor setting is provided, exploiting the fingerprint approach for indoor localization. The considered scenario is a multi-level car park inside an airport building. The algorithm provides a vehicle allocation inside the car park in quadratic time over the number of parking slots, by also considering the driver’s preferences on the terminal to be reached.
Improving Transverse Compressive Modulus of Carbon Fibers during Wet Spinning of Polyacrylonitrile
Authors: Wong Sherman , Hillbrick Linda K. , Kaur Jasjeet , Seeber Aaron J. , Schutz Jurg A. , Pierlot Anthony P.
Published: June 2022

The performance of carbon fibers depends on the properties of the precursor polyacrylonitrile (PAN) fibers. Stretching of PAN fibers results in improved tensile properties, while potentially reducing its compressive properties. To determine optimization trade-offs, the effect of coagulation conditions and the stretching process on the compressive modulus in the transverse direction (ET) was investigated. A method for accurately determining ET from polymer fibers with non-circular cross-sectional shapes is presented. X-ray diffraction was used to measure the crystallite size, crystallinity, and crystallite orientation of the fibers. ET was found to increase with decreasing crystallite orientation along the drawing direction, which decreases the tensile modulus in the longitudinal direction (EL) proportionally to crystallite orientation. Stretching resulted in greater crystallite orientation along the drawing direction for fibers formed under the same coagulation conditions. Increasing the solvent concentration in the coagulation bath resulted in a higher average orientation, but reduced the impact of stretching on the orientation. The relationship between ET and EL observed in the precursor PAN fiber is retained after carbonization, with a 20% increase in ET achieved for a 2% decrease in EL. This indicates that controlled stretching of PAN fiber allows for highly efficient trading off of EL for ET in carbon fiber.
Seasonal Variations in the Composition and Physicochemical Characteristics of Sheep and Goat Milks
Authors: Li Siqi , Delger Munkhzul , Dave Anant , Singh Harjinder , Ye Aiqian
Published: June 2022

There has been growing consumer interest in sheep and goat milk products as alternatives to cow milk products. The physicochemical characteristics of milk vary not only between ruminant species, but also during different seasons; they determine the nutritional quality and processing properties of the milk. In this study, we characterized sheep and goat milks from New Zealand over the seasons for their composition (macronutrients, macro- and micro-minerals, fatty acids, and proteins) and physicochemical properties (e.g., ionic calcium, fat globule size, casein micelle size, viscosity, and melting behavior of milk fat). Heat-induced (95 °C for 5 min) protein interactions and changes in the physical properties of the milks were also investigated. The compositional and structural features of sheep and goat milks were identified and compared with those reported for cow milk. Seasonal variations in the milk characteristics were more pronounced for sheep milk than goat milk and were probably affected by the production systems. Sheep milk, particularly in the late season, had the largest heat-induced increases in casein micelle size and viscosity, probably arising from the greater casein–whey protein and casein–casein interactions during heat treatment. This study provides comprehensive information on the properties of sheep and goat milks and highlights the interaction effects between species, season, and processing.
The Influence of DNA Extraction Methods on Species Identification Results of Seafood Products
Authors: Rodríguez-Riveiro Rosalía , Velasco Amaya , Sotelo Carmen G.
Published: June 2022

In terms of species identification, the ultimate aim of extracting DNA is the subsequent amplification of the selected marker; therefore, the quality and quantity of the extracted DNA must be sufficient for PCR-based methods. The purpose of this study is to compare five DNA extraction methods according to the parameters of quantity, quality and simplicity, among others, in order to determine the most suitable method for identification for Cephalopoda, Gadiformes and Pleuronectiformes. The Wizard DNA clean-up system kit (Promega), MPure-12TM automated nucleic acid purification system (MP Biomedicals), Chelex 100 resin (Biorad), DNeasy blood and tissue kit (Qiagen) and a swab method were examined. The obtained DNA quantity was determined by fluorescence, and quality was evaluated with ratios of absorbance of A260/A280 and A260/A230 by agarose gel visualization of the extracts and by analyzing the success of PCR amplifications of 720 bp fragments of cytochrome c oxidase I (COI) for Cephalopods and 465 bp fragments of cytochrome b for Gadiformes and Pleuronectiformes. Statistical results confirmed significant differences between the tested methods according to yield, efficiency and purity and no significant differences with respect to the species employed. The best yields were obtained with the Wizard kit, whereas other methods stand out in terms of their affordability (Chelex) and automation (Mpure).
Fabrication of High-Acyl Gellan-Gum-Stabilized β-Carotene Emulsion: Physicochemical Properties and In Vitro Digestion Simulation
Authors: Meng Yuecheng , Hang Linyue , Fang Sheng , Li Yanhua , Xu Xuejiao , Zhang Fan , Chen Jie
Published: June 2022

The β-carotene emulsion system using high-acyl gellan gum (HA) as an emulsifier was fabricated and systematically studied. The stability and stabilizing mechanism of the emulsion using medium-chain triglyceride as oil phase with a water-oil mass ratio of 9:1 under different physicochemical conditions of heat, pH, and ions were investigated by analyzing mean particle size (MPS), emulsion yield (EY), and dynamic stability. The effects of the HA-β-carotene emulsion system on the bioaccessibility of β-carotene in vitro were conducted. During the simulated oral digestion stage (SODP) and simulated gastric digestion stage (SGDP), the emulsion systems stabilized with different HA contents showed good stability, and the changes of MPS and zeta potential (ZP) were within 2.5 μm and 3.0 mV, respectively. After entering the simulated intestinal digestion phase (SIDP), β-carotene was released from oil droplets and formed micelles with bile salts, phospholipids, etc. HA-β-carotene emulsion can enhance the release rate of free fatty acid (FFA), which ultimately affects the β-carotene bioaccessibility. These results indicate that HA can be used to prepare carotene emulsion and improve its bioavailability. The study provides a reference for the application of HA as a natural emulsifier and the delivery of β-carotene.
The Effect of Steviol Glycosides on Sensory Properties and Acceptability of Ice Cream
Authors: Muenprasitivej Nannapas , Tao Ran , Nardone Sarah Jeanne , Cho Sungeun
Published: June 2022

There has been a challenge in overcoming the bitter aftertaste of stevia, a natural non-caloric sweetener. Recent research focuses on investigating various types of steviol glycosides, the sweet compounds in stevia leaves, as they exhibit different sensory characteristics. This study determined the sensory properties and acceptability of ice cream sweetened solely with three steviol glycosides, rebaudioside (Reb) A, D, and M (0.09% w/v), using sucrose-sweetened ice cream as a control (14% w/v). Ice cream consumers (n = 92) rated their overall liking, attribute liking, and sweetness and bitterness intensities and described the aftertastes of each sample using check-all-that-apply. The liking scores of Reb D- and M-sweetened ice creams were significantly higher than those of Reb A-sweetened ice cream. Among the three glycosides, only Reb M showed a sweetness intensity comparable with that of sucrose. Consumers perceived the aftertastes of Reb D and M ice creams as being more sweet, pleasant, creamy, and milky, while Reb A was more artificial and chemical. Reb D and M ice creams were also plotted close to sucrose in the correspondence analysis graph, meaning that their aftertaste characteristics were similar to those of sucrose. The present study clearly highlights that Reb D and M have better tastes and provide better perceptions to consumers than Reb A, which is the most widely used glycoside in food industry.
Molecular Cloning and Functional Analysis of DXS and FPS Genes from Zanthoxylum bungeanum Maxim
Authors: Tian Lu , Shi Jingwei , Yang Lin , Wei Anzhi
Published: June 2022

Zanthoxylum bungeanum Maxim. (Z. bungeanum) has attracted attention for its rich aroma. The aroma of Z. bungeanum is mainly volatile terpenes synthesized by plant terpene metabolic pathways. However, there is little information on Z. bungeanum terpene metabolic gene. In this study, the coding sequence of 1-deoxy-D-xylulose-5-phosphate synthase (DXS) and farnesyl pyrophosphate synthase (FPS) were cloned from Z. bungeanum cv. ‘Fengxiandahongpao.’ ZbDXS and ZbFPS genes from Z. bungeanum with CDS lengths of 2172 bp and 1029 bp, respectively. The bioinformatics results showed that Z. bungeanum was closely related to citrus, and it was deduced that ZbFPS were hydrophilic proteins without the transmembrane domain. Subcellular localization prediction indicated that ZbDXS was most likely to be located in chloroplasts, and ZbFPS was most likely to be in mitochondria. Meanwhile, the 3D protein structure showed that ZbDXS and ZbFPS were mainly composed of α-helices, which were folded into a single domain. In vitro enzyme activity experiments showed that purified proteins ZbDXS and ZbFPS had the functions of DXS enzyme and FPS enzyme. Transient expression of ZbDXS and ZbFPS in tobacco significantly increased tobacco’s terpene content. Moreover, ZbDXS and ZbFPS were expressed in different tissues of Z. bungeanum, and the relative expression of the two genes was the highest in fruits. Therefore, this suggests that ZbDXS and ZbFPS are positively related to terpene synthesis. This study could provide reference genes for improving Z. bungeanum breeding as well as for the Rutaceae research.
Analysis of Fungal Microbiomes in Edible Medicinal Morindae Officinalis Radix and Alpiniae Oxyphyllae Fructus Using DNA Metabarcoding
Authors: Jiang Wenjun , Chen Xuyu , Guo Mengyue , Yu Jingsheng , Yang Meihua , Pang Xiaohui
Published: June 2022

Morindae Officinalis Radix (MOR) and Alpiniae Oxyphyllae Fructus (AOF) have been widely used as dietary supplements and traditional herbal medicines for centuries. Fungal and mycotoxin contamination in MOR and AOF has been reported recently. In this study, fungi in MOR and AOF are first investigated using DNA metabarcoding, and the differences in fungal microbiome between moldy and non−moldy samples are analyzed. The results show that Ascomycota is the most prevailing fungus at the phylum level in MOR and AOF with relative abundances of 49.53–94.32% and 14.81–81.85%, respectively. Penicillium (1.86–76.14%), Cladosporium (1.82–56.65%), and Trichoderma (0.12–19.71%) are the dominant genera in MOR. Penicillium (0.27–56.06%), Papiliotrema (0.04–51.71%), and Cladosporium (3.08–44.41%) are the dominant genera in AOF. Two potential toxigenic fungi were detected, namely, Trichoderma atroviride and Fusarium equiseti. Moreover, the differences in fungal communities between moldy and non−moldy samples were monitored. In conclusion, DNA metabarcoding can be used to assess the fungal microbiome in edible medicinal herbs, thereby providing a basis for ensuring food safety and drug efficacy.
Physico-Chemical, Textural and Sensory Evaluation of Spelt Muffins Supplemented with Apple Powder Enriched with Sugar Beet Molasses
Authors: Lončar Biljana , Pezo Lato , Filipović Vladimir , Nićetin Milica , Filipović Jelena , Pezo Milada , Šuput Danijela , Aćimović Milica
Published: June 2022

The present study investigated the effect of incorporating 10, 20, and 30% apple powder obtained by freeze-drying, and apple powder produced with osmotic pre-treatment in sugar beet molasses solution, into muffins. The powder was freeze-dried and introduced as a whole spelt wheat flour replacement in muffins. The obtained products were investigated for their chemical composition and technological properties, and were subjected to a sensory analysis as well as a consumer acceptance test. Increasing the substitution level from 0 to 30% apple powder lowered the protein, starch, and fat content, while moisture content, sugar, and cellulose showed the opposite trend. The sensory analysis results indicated that the addition of apple powder or apple powder with osmotic pre-treatment (apple OT+Lyo powder) to the ingredients of muffins positively affected the taste, smell, mastication, and appearance of the final product. Consumers rated the muffins with 30% apple OT+Lyo powder as the most acceptable. Principal component analysis, an artificial neural network, and global sensitivity analysis were utilized to differentiate among muffin samples, and to estimate the corresponding influence of the substitution of spelt flour with apple powder or apple OT powder on the observed quality and nutritional parameters of the muffins.
Mathematical Models to Describe the Foam Mat Drying Process of Cumbeba Pulp (Tacinga inamoena) and Product Quality
Authors: Diógenes Adelino de Melo Guimarães , de Figueirêdo Rossana Maria Feitosa , Queiroz Alexandre José de Melo , Ferreira João Paulo de Lima , Silva Wilton Pereira da , Gomes Josivanda Palmeira , Santos Francislaine Suelia dos , Castro Deise Souza de , Oliveira Marcela Nobre de , Santos Dyego da Costa , Andrade Romário Oliveira de , Lima Ana Raquel Carmo de
Published: June 2022

The present study investigated the mathematical modeling foam-mat drying kinetics of cumbeba pulp and the effect of drying conditions on the color and contents of ascorbic acid, flavonoids, and phenolic compounds of the powder pulps obtained. Foam-mat drying was carried out in a forced air circulation oven at temperatures of 50, 60, and 70 °C, testing foam-mat thicknesses of 0.5, 1.0, and 1.5 cm. The increase in the water removal rate is a result of the increase in air temperature and the decrease in the thickness of the foam layer. Among the empirical and semi-empirical mathematical models, the Midilli model was the one that best represented the drying curves in all conditions evaluated. Effective water diffusivity ranged from 1.037 × 10−9 to 6.103 × 10−9 m2 s−1, with activation energy of 25.212, 33.397, and 36.609 kJ mol−1 for foam thicknesses of 0.5, 1.0, and 1.5 cm, respectively. Cumbeba powders showed light orangish colors and, as the drying temperature increased from 50 to 70 °C, for all thicknesses, the lightness value (L*) decreased and the values of redness (+a*) and yellowness (+b*) increased. Foam-mat drying at higher temperatures (60 and 70 °C) improved the retention of ascorbic acid and flavonoids, but reduced the content of phenolic compounds, while the increase in thickness, especially for flavonoids and phenolic compounds, caused reduction in their contents. The foam-mat drying method allowed obtaining a good-quality cumbeba pulp powder.
Improving the Thermal and Oxidative Stability of Food-Grade Phycocyanin from Arthrospira platensis by Addition of Saccharides and Sugar Alcohols
Authors: Huo Yan , Hou Xiaoyu , Yu Youzhi , Wen Xiaobin , Ding Yi , Li Yeguang , Wang Zhongjie
Published: June 2022

The water-soluble pigment protein phycocyanin (C-PC) from cyanobacteria Arthrospira sp. is an excellent natural food colorant and nutritional supplement with a brilliant blue color. However, C-PC is highly unstable, especially at high temperatures and when exposed to oxidative stress. The lack of simple and economical methods for improving the stability of C-PC greatly limits the application of this functional protein in the food industry. This study investigated the effect of adding saccharides (glucose, mannose, galactose, and maltose) and sugar alcohols (mannitol and maltitol) on the stability of food-grade C-PC extracted from Arthrospira platensis; the relevant reaction kinetics were also analyzed. The results revealed that glucose, mannose, mannitol, galactose, and maltose could effectively improve the thermal stability of C-PC. This improvement was positively correlated with the concentration of the additives and decreased sharply when the temperature exceeded 60 °C. Furthermore, the results also revealed the instability of C-PC when subjected to oxidative stress and the effectiveness of glucose, mannose, mannitol, and maltose in preventing the oxidative degradation of C-PC. In general, this study demonstrates that glucose, mannose, mannitol, and maltose are promising compounds for promoting the thermal and oxidative stability of C-PC, providing an economical and effective method for C-PC preservation.
Editorial for the Special Issue, “Quality Assay, Processing and Bio-Function of Rice Products”
Authors: Ohtsubo Ken’ichi , Brites Carla Moita , Rosell Cristina M.
Published: June 2022

Rice is one of the most important cereals in the world alongside wheat and maize [...]
Emulsion Gels as Precursors for Porous Silicones and All-Polymer Composites—A Proof of Concept Based on Siloxane Stabilizers
Authors: Racles Carmen , Bele Adrian , Vasiliu Ana-Lavinia , Sacarescu Liviu
Published: June 2022

In spite of its versatility, the emulsion templating method is rather uncommon for the preparation of porous silicones. In this contribution, two siloxane-containing stabilizers, designed to be soluble in polar (water) and non-polar (toluene) solvents, respectively, were used in low concentrations to produce stable emulsions, wherein polysiloxane gels were obtained by UV-photoinitiated thiol-ene click cross-linking. The stabilizers exhibited negative interfacial tension, as measured by Wilhelmy plate tensiometry. The emulsion gels evolved into porous silicones (xerogels), with tunable morphology and properties. According to TEM and SEM investigations, the emulsion template was preserved in the final materials. Several parameters (e.g., the structure of the polysiloxane precursors, composition of the emulsion gels, nature of the continuous phase, cross-linking conditions, or additives) can be varied in order to obtain porous elastic materials with desired properties, such as Janus membranes, absorbent monoliths, all-polymer porous composites, or silicone-swollen gels. The feasibility of these types of materials was tested, and exemplary porous silicones were briefly characterized by contact angle measurements, mechanical testing, and absorption tests. The proposed method is simple, fast, and economic, uses very little amounts of stabilizers, and can be adjusted as a green technique. In this contribution, all the silicon-based materials with a convenient design were prepared in house.
Genetic and Epigenetic Association of Hepatocyte Nuclear Factor-1α with Glycosylation in Post-Traumatic Stress Disorder
Authors: Tudor Lucija , Konjevod Marcela , Nedic Erjavec Gordana , Nikolac Perkovic Matea , Uzun Suzana , Kozumplik Oliver , Zoldos Vlatka , Lauc Gordan , Svob Strac Dubravka , Pivac Nela
Published: June 2022

Post-traumatic stress disorder (PTSD) is a complex trauma-related disorder, the etiology and underlying molecular mechanisms of which are still unclear and probably involve different (epi)genetic and environmental factors. Protein N-glycosylation is a common post-translational modification that has been associated with several pathophysiological states, including inflammation and PTSD. Hepatocyte nuclear factor-1α (HNF1A) is a transcriptional regulator of many genes involved in the inflammatory processes, and it has been identified as master regulator of plasma protein glycosylation. The aim of this study was to determine the association between N-glycan levels in plasma and immunoglobulin G, methylation at four CpG positions in the HNF1A gene, HNF1A antisense RNA 1 (HNF1A-AS1), rs7953249 and HNF1A rs735396 polymorphisms in a total of 555 PTSD and control subjects. We found significant association of rs7953249 and rs735396 polymorphisms, as well as HNF1A gene methylation at the CpG3 site, with highly branched, galactosylated and sialyated plasma N-glycans, mostly in patients with PTSD. HNF1A-AS1 rs7953249 polymorphism was also associated with PTSD; however, none of the polymorphisms were associated with HNF1A gene methylation. These results indicate a possible regulatory role of the investigated HNF1A polymorphisms with respect to the abundance of complex plasma N-glycans previously associated with proinflammatory response, which could contribute to the clinical manifestation of PTSD and its comorbidities.
Environmental and Biological Controls on Sedimentary Bottom Types in the Puquios of the Salar de Llamara, Northern Chile
Authors: Suosaari Erica P. , Oehlert Amanda M. , Lascu Ioan , Decho Alan W. , Piggot Alan M. , Palma Alvaro T. , Machabee Paul F. , Reid R. Pamela
Published: June 2022

The Puquios of the Salar de Llamara in the Atacama Desert, northern Chile, is a system of small lakes that is characterized by evaporitic mineral deposition and that commonly hosts microbial communities. This region is known for its extreme aridity, solar irradiance, and temperature fluctuations. The Puquios are a highly diverse ecosystem with a variety of sedimentary bottom types. Our previous results identified electrical conductivity (EC) as a first-order environmental control on bottom types. In the present paper, we extend our analysis to examine the effects of additional environmental parameters on bottom types and to consider reasons for the importance of EC as a control of sedimentology. Our results identify microbially produced extracellular polymeric substances (EPS) as a major player in the determination of bottom types. The relative amounts and properties of EPS are determined by EC. EPS, in turn, determines the consistency of bottom types, exchange of bottom substrate with the overlying water column, and mineral precipitation within the substrate. Low-EC ponds in the Puquios system have flocculent to semi-cohesive bottom types, with low-viscosity EPS that allows for high-exchange with the surrounding waters and mineral precipitation of granular gypsum, carbonate, and Mg–Si clay in close association with microbes. Ponds with elevated EC have bottom types that are laminated and highly cohesive with high-viscosity EPS that restricts the exchange between sediments and the surrounding waters; mineral precipitation in these high-EC ponds includes granular to laminated gypsum, carbonate and Mg–Si, which also form in close association with microbes. Bottom types in ponds with EC above the threshold for thriving benthic microbial communities have insufficient EPS accumulations to affect mineral precipitation, and the dominant mineral is gypsum (selenite). The variations in EPS production throughout the Puquios, associated with heterogeneity in environmental conditions, make the Puquios region an ideal location for understanding the controls of sedimentary bottom types in evaporative extreme environments that may be similar to those that existed on early Earth and beyond.