bluuebunny/crossref_metadata_2025 huggingface dataset:
Daily Behaviors, Worries and Emotions in Children and Adolescents with ADHD and Learning Difficulties during the COVID-19 Pandemic
Authors: Korpa Terpsichori , Pappa Theodora , Chouliaras Giorgos , Sfinari Anastasia , Eleftheriades Anna , Katsounas Matthaios , Kanaka-Gantenbein Christina , Pervanidou Panagiota
Published: November 2021

The aim of the present study was to investigate the effects of the coronavirus crisis on behavioral and emotional parameters in children and adolescents with ADHD and Learning Difficulties. A total of 101 children, 5–18 years old, were included in the study, 63 (44 boys) of which were diagnosed with ADHD and learning difficulties (ADHD/LD) and 38 were healthy children (19 boys). The CRISIS questionnaire for parents/caregivers was used. The questionnaire was completed during the first national lockdown in Greece and the data referred to two time-points: 3 months before, and the past 2 weeks. A significant deterioration in the “Emotion/Worries (EW)” symptoms was observed during the pandemic in the control group (2.62 ± 0.16 vs. 2.83 ± 0.18, p < 0.001). No such differences were noted in the ADHD group: 3.08 ± 0.25 vs. 3.12 ± 0.29, p = 0.12. Provision of educational and activities support was related to increased EW before the crisis. In ADHD/LD children, higher parental education and child’s younger age were related to increased symptoms of EW. In the entire group, previous mental health conditions, increasing stress due to restrictions, and increased COVID-related worries were positively associated with the EW symptoms during the crisis. Less affected relations with friends and less reduction in contact with people outside the home were negatively related with EW during the crisis. The study revealed specific parameters that negatively affected the emotional and behavioral variables of children with ADHD and learning difficulties.
Nasal Polyps in Children: The Early Origins of a Challenging Adulthood Condition
Authors: Di Cicco Maria E. , Bizzoco Francesca , Morelli Elena , Seccia Veronica , Ragazzo Vincenzo , Peroni Diego G. , Comberiati Pasquale
Published: November 2021

Nasal polyps (NPs) are benign inflammatory masses causing chronic nasal obstruction, usually associated with underlying chronic rhinosinusitis (CRS), which are rarely reported in childhood. The interest in NPs has recently increased due to new therapeutic options, namely biological agents, such as dupilumab, and an update of the European position paper on this topic was released in 2020, providing a detailed classification for these lesions and also discussing diagnostic and therapeutic approaches also in children. In childhood, NPs usually represent red flags for systemic diseases, such as cystic fibrosis and immunodeficiencies. This review outlines the recent data on NPs in childhood, focusing on predisposing factors for CRS as well as on the potential endotypes in this particular age group, for which further studies are required in order to better clarify their pathogenesis and to identify molecular biomarkers that could help achieve more personalized treatments.
Liquid Crystal Thermography in Gas Turbine Heat Transfer: A Review on Measurement Techniques and Recent Investigations
Authors: Ekkad Srinath V. , Singh Prashant
Published: November 2021

Liquid Crystal Thermography is a widely used experimental technique in the gas turbine heat transfer community. In turbine heat transfer, determination of the convective heat transfer coefficient (h) and adiabatic film cooling effectiveness (η) is imperative in order to design hot gas path components that can meet the modern-day engine performance and emission goals. LCT provides valuable information on the local surface temperature, which is used in different experimental methods to arrive at the local h and η. The detailed nature of h and η through LCT sets it apart from conventional thermocouple-based measurements and provides valuable insights into cooling designers for concept development and its further iterations. This article presents a comprehensive review of the state-of-the-art experimental methods employing LCT, where a critical analysis is presented for each, as well as some recent investigations (2016–present) where LCT was used. The goal of this article is to familiarize researchers with the evolving nature of LCT given the advancements in instrumentation and computing capabilities, and its relevance in turbine heat transfer problems in current times.
Assessment and Evaluation in Active Learning Implementations: Introducing the Engineering Education Active Learning Maturity Model
Authors: Arruda Humberto , Silva Édison Renato
Published: November 2021

With the technological changes experienced in the world in recent decades, society has changed as a whole, due to the speed and availability of information that exists today. As student attention decreases, critical thinking and Active Learning, which places the student at the center of the learning process, have gained prominence. Considering the growing popularity of these techniques, this article proposes the Engineering Education Active Learning Maturity Model (E2ALM2), a framework that allows practitioners to assess the current maturity of Active Learning implementation in a program or a course. E2ALM2 was built from a literature review of key success factors (KSF) for Active Learning implementations, which were divided into dimensions. Each KSF is composed of constructs, which are detailed with variables. Each variable has a proposed measurement method and an estimated uncertainty level. The framework can support diagnosis and practical improvements in real settings.
How to Run Your Own Online Business: A Gamification Experience in ESL
Authors: Hernández-Prados Mª Ángeles , Belmonte Mª Luisa , Manzanares-Ruiz Juan Carlos
Published: November 2021

Notwithstanding the importance and relevance of gamification as a topical methodology in education, and after a literature review, there are just a few studies using role-playing games. In order to motivate and facilitate English as second language (ESL) learning of first year of Bachillerato (year 12) students at a public high school in the Region of Murcia (Spain) and following an action research methodology, we design, implement and evaluate a role-playing game, which consists of the creation and management of a company, The Tik Tok School. The results confirm that students felt more comfortable speaking in English because they were more motivated. They also state that during the experience they were more focused on learning rather than winning the game and that they prefer a gamification approach over traditional settings. Furthermore, they have been participating constantly using more English than Spanish. After the data analysis, we conclude that this methodology positively impacts motivation and the acquisition of a second language.
Rethinking the Curriculum in the Context of Education for Sustainability: Lessons from the COVID-19 Pandemic
Authors: Hadzigeorgiou Yannis
Published: November 2021

In considering the current COVID-19 pandemic as a moment of reflection on a wide variety of issues, this paper discusses the need to rethink the curriculum, in regard to its priorities and in the context of education for sustainability. It does so by revisiting some ideas that have received, or have begun to receive, attention in the field of education. More specifically, the paper focuses on the development of global awareness as an educational goal, the notion of hope and the future dimension of the curriculum, the value of systems and ecological thinking, as well as the value of decision making and the role that knowledge of the nature of science can play in decision making. Given that the world will most likely face in the future complex global issues and problems, just like the COVID-19 pandemic, all the aforementioned ideas deserve particular attention, especially if the curriculum is to promote and foster the idea of sustainability.
Novel Bio-Optoelectronics Enabled by Flexible Micro Light-Emitting Diodes
Authors: Lee Han Eol
Published: November 2021

Optical health monitoring and treatment have been spotlighted due to their biocompatible properties. Several researchers are investigating optical devices for obtaining health signals and curing diseases without any damage to the body. In particular, μLEDs have received a lot of attention as a future light source due to their superior optical/electrical properties, environmental stability, and structural advantages. According to their strengths, μLEDs have been used for various biomedical applications, such as optogenetics and hair regrowth. In this paper, we introduce the research tendency of μLEDs and the latest bio-applications.
Direction-of-Arrival Estimation of Electromagnetic Wave Impinging on Spherical Antenna Array in the Presence of Mutual Coupling Using a Multiple Signal Classification Method
Authors: Famoriji Oluwole John , Shongwe Thokozani
Published: November 2021

A spherical antenna array (SAA) is the configuration of choice in obtaining an antenna array with isotropic characteristics. An SAA has the capacity to receive an electromagnetic wave (EM) with equal intensity irrespective of the direction-of-arrival (DoA) and polarization. Therefore, the DoA estimation of electromagnetic (EM) waves impinging on an SAA with unknown mutual coupling needs to be considered. In the spherical domain, the traditional multiple signal classification algorithm (SH-MUSIC) is faced with a computational complexity problem. This paper presents a one-dimensional MUSIC method (1D-MUSIC) for the estimation of the azimuth and elevation angles. An intermediate mapping matrix that exists between Fourier series and the spherical harmonic function is designed, and the Fourier series Vandermonde structure is used for the realization of the polynomial rooting technique. This mapping matrix can be computed prior to the DoA estimation, and it is only a function of the array configuration. Based on the mapping matrix, the 2-D angle search is transformed into two 1-D angle findings. Employing the features of the Fourier series, two root polynomials are designed for the estimation of the elevation and azimuth angles, spontaneously. The developed method avoids the 2-D spectral search, and angles are paired in automation. Both numerical simulation results, and results from experimental measured data (i.e., with mutual coupling effect incorporated), show the validity, potency, and potential practical application of the developed algorithm.
Automatic Unsupervised Fabric Defect Detection Based on Self-Feature Comparison
Authors: Peng Zhengrui , Gong Xinyi , Wei Bengang , Xu Xiangyi , Meng Shixiong
Published: November 2021

Due to the huge demand for textile production in China, fabric defect detection is particularly attractive. At present, an increasing number of supervised deep-learning methods are being applied in surface defect detection. However, the annotation of datasets in industrial settings often depends on professional inspectors. Moreover, the methods based on supervised learning require a lot of annotation, which consumes a great deal of time and costs. In this paper, an approach based on self-feature comparison (SFC) was employed that accurately located and segmented fabric texture images to find anomalies with unsupervised learning. The SFC architecture contained the self-feature reconstruction module and the self-feature distillation. Accurate fiber anomaly location and segmentation were generated based on these two modules. Compared with the traditional methods that operate in image space, the comparison of feature space can better locate the anomalies of fiber texture surfaces. Evaluations were performed on the three publicly available databases. The results indicated that our method performed well compared with other methods, and had excellent defect detection ability in the collected textile images. In addition, the visual results showed that our results can be used as a pixel-level candidate label.
Violence Recognition Based on Auditory-Visual Fusion of Autoencoder Mapping
Authors: Lou Jiu , Zuo Decheng , Zhang Zhan , Liu Hongwei
Published: November 2021

In the process of violence recognition, accuracy is reduced due to problems related to time axis misalignment and the semantic deviation of multimedia visual auditory information. Therefore, this paper proposes a method for auditory-visual information fusion based on autoencoder mapping. First, a feature extraction model based on the CNN-LSTM framework is established, and multimedia segments are used as whole input to solve the problem of time axis misalignment of visual and auditory information. Then, a shared semantic subspace is constructed based on an autoencoder mapping model and is optimized by semantic correspondence, which solves the problem of audiovisual semantic deviation and realizes the fusion of visual and auditory information on segment level features. Finally, the whole network is used to identify violence. The experimental results show that the method can make good use of the complementarity between modes. Compared with single-mode information, the multimodal method can achieve better results.
Automatic Taxonomy Classification by Pretrained Language Model
Authors: Kuwana Ayato , Oba Atsushi , Sawai Ranto , Paik Incheon
Published: November 2021

In recent years, automatic ontology generation has received significant attention in information science as a means of systemizing vast amounts of online data. As our initial attempt of ontology generation with a neural network, we proposed a recurrent neural network-based method. However, updating the architecture is possible because of the development in natural language processing (NLP). By contrast, the transfer learning of language models trained by a large, unlabeled corpus has yielded a breakthrough in NLP. Inspired by these achievements, we propose a novel workflow for ontology generation comprising two-stage learning. Our results showed that our best method improved accuracy by over 12.5%. As an application example, we applied our model to the Stanford Question Answering Dataset to show ontology generation in a real field. The results showed that our model can generate a good ontology, with some exceptions in the real field, indicating future research directions to improve the quality.
A Novel Three-Phase Harmonic Power Flow Algorithm for Unbalanced Radial Distribution Networks with the Presence of D-STATCOM Devices
Authors: Satish Raavi , Vaisakh Kanchapogu , Abdelaziz Almoataz Y. , El-Shahat Adel
Published: November 2021

Due to the rapid advancement in power electronic devices in recent years, there is a fast growth of non-linear loads in distribution networks (DNs). These non-linear loads can cause harmonic pollution in the networks. The harmonic pollution is low, and the resonance problem is absent in distribution static synchronous compensators (D-STATCOM), which is the not case in traditional compensating devices such as capacitors. The power quality issue can be enhanced in DNs with the interfacing of D-STATCOM devices. A novel three-phase harmonic power flow algorithm (HPFA) for unbalanced radial distribution networks (URDN) with the existence of linear and non-linear loads and the integration of a D-STATCOM device is presented in this paper. The bus number matrix (BNM) and branch number matrix (BRNM) are developed in this paper by exploiting the radial topology in DNs. These matrices make the development of HPFA simple. Without D-STATCOM integration, the accuracy of the fundamental power flow solution and harmonic power flow solution are tested on IEEE−13 bus URDN, and the results are found to be precise with the existing work. Test studies are conducted on the IEEE−13 bus and the IEEE−34 bus URDN with interfacing D-STATCOM devices, and the results show that the fundamental r.m.s voltage profile is improved and the fundamental harmonic power loss and total harmonic distortion (THD) are reduced.
Masked Face Recognition Using Deep Learning: A Review
Authors: Alzu’bi Ahmad , Albalas Firas , AL-Hadhrami Tawfik , Younis Lojin Bani , Bashayreh Amjad
Published: November 2021

A large number of intelligent models for masked face recognition (MFR) has been recently presented and applied in various fields, such as masked face tracking for people safety or secure authentication. Exceptional hazards such as pandemics and frauds have noticeably accelerated the abundance of relevant algorithm creation and sharing, which has introduced new challenges. Therefore, recognizing and authenticating people wearing masks will be a long-established research area, and more efficient methods are needed for real-time MFR. Machine learning has made progress in MFR and has significantly facilitated the intelligent process of detecting and authenticating persons with occluded faces. This survey organizes and reviews the recent works developed for MFR based on deep learning techniques, providing insights and thorough discussion on the development pipeline of MFR systems. State-of-the-art techniques are introduced according to the characteristics of deep network architectures and deep feature extraction strategies. The common benchmarking datasets and evaluation metrics used in the field of MFR are also discussed. Many challenges and promising research directions are highlighted. This comprehensive study considers a wide variety of recent approaches and achievements, aiming to shape a global view of the field of MFR.
Modeling of Average Current in Non-Ideal Buck and Synchronous Buck Converters for Low Power Application
Authors: Surya Sumukh , Srinivasan Mohan Krishna , Williamson Sheldon
Published: November 2021

In this paper, a comparative analysis of the average switch/inductor current between ideal and non-ideal buck and synchronous buck converters is performed and verified against a standard LTspice model. The mathematical modeling of the converters was performed using volt-sec and amp-sec balance equations and analyzed using MATLAB/Simulink. The transients in the output voltage and the inductor current were observed. The transfer function of the switch current to the duty cycle (Gid) in open loop configuration for low-power converters operating in continuous conduction mode (CCM) was modeled using thestate space averaging (SSA) technique and analyzed using MATLAB/Simulink. Initially, using the volt-sec and amp-sec, balance equations for the converters were modeled. The switch current to duty ratio (Gid) was derived using the SSA technique and verified using standard average models available in LTspice software. Though the Gid was derived using various methods in earlier works, the analyses of parameters such as low frequency gain, stability, resonant frequency and the location of poles and zeros were not presented. It was observed that the converters were stable, and the non-ideal converter showed smaller resonant frequency than the ideal converter due to the equivalent series resistances (ESR) of the inductor and the capacitor. The non-ideal converters showed higher stability than the ideal converters due to the placement of the poles closer to the s-plane. However, the Gid of the non-ideal converters remained the same in the open loop configuration.
Hybrid AES-ECC Model for the Security of Data over Cloud Storage
Authors: Rehman Saba , Talat Bajwa Nida , Shah Munam Ali , Aseeri Ahmad O. , Anjum Adeel
Published: November 2021

A cloud computing environment provides a cost-effective way for the end user to store and access private data over remote storage using some Internet connection. The user has access to the data anywhere and at any time. However, the data over the cloud do not remain secure all the time. Since the data are accessible to the end user only by using the interference of a third party, it is prone to breach of authentication and integrity of the data. Moreover, cloud computing allows simultaneous users to access and retrieve their data online over different Internet connections, which leads to the exposure, leakage, and loss of a user’s sensitive data in different locations. Many algorithms and protocols have been developed to maintain the security and integrity of the data using cryptographic algorithms such as the Elliptic Curve Cryptography (ECC). This paper proposes a secure and optimized scheme for sharing data while maintaining data security and integrity over the cloud. The proposed system mainly functions by combining the ECC and the Advanced Encryption Standard (AES) method to ensure authentication and data integrity. The experimental results show that the proposed approach is efficient and yields better results when compared with existing approaches.
LoRa Enabled Smart Inverters for Microgrid Scenarios with Widespread Elements
Authors: Arbab-Zavar Babak , Palacios-Garcia Emilio J. , Vasquez Juan C. , Guerrero Josep M.
Published: November 2021

The introduction of low-power wide-area networks (LPWANs) has changed the image of smart systems, due to their wide coverage and low-power characteristics. This category of communication technologies is the perfect candidate to be integrated into smart inverter control architectures for remote microgrid (MG) applications. LoRaWAN is one of the leading LPWAN technologies, with some appealing features such as ease of implementation and the possibility of creating private networks. This study is devoted to analyze and evaluate the aforementioned integration. Initially, the characteristics of different LPWAN technologies are introduced, followed by an in-depth analysis of LoRa and LoRaWAN. Next, the role of communication in MGs with widespread elements is explained. A point-by-point LoRa architecture is proposed to be implemented in the grid-feeding control structure of smart inverters. This architecture is experimentally evaluated in terms of latency analysis and externally generated power setpoint, following smart inverters in different LoRa settings. The results demonstrate the effectiveness of the proposed LoRa architecture, while the settings are optimally configured. Finally, a hybrid communication system is proposed that can be effectively implemented for remote residential MG management.
Tensile, Flexural, and Morphological Properties of Jute/Oil Palm Pressed Fruit Fibers Reinforced High Density Polyethylene Hybrid Composites
Authors: Daramola Oluyemi Ojo , Balogun Oluwatosin Abiodun , Adediran Adeolu Adesoji , Saka Sheriff Olalekan , Oladele Isiaka Oluwole , Akinlabi Esther Titilayo
Published: November 2021

The incorporation of materials that were formally regarded as agricultural wastes into polymeric matrix has drawn the attention of many researchers in recent years. This research focused on reinforcing high-density polyethylene (HDPE) matrix with treated jute fiber (JF)/oil palm pressed fruit fibers (OPPFF) at varying weight proportions. JF and OPPFF were cut to 2.5 mm length and were chemically treated thereafter with 1 M and 1.5 M sodium hydroxide solution respectively. The composites were produced using the compression molding technique. The morphological characterization of the fibers and composites for untreated and treated samples was studied with the aid of a scanning electron microscope (SEM). Tensile and flexural properties of the produced composite samples were also determined. From the result, the surface morphology of the fiber after treatment showed that there was obvious exposure of the fiber surface and removal of impurities as this influenced the microstructure of the composites and in turn the tensile and flexural properties. Hence, it was observed that 20 wt.% treated jute fiber addition shows the most significant enhancements in terms of tensile and flexural properties. The study exposed the effect of surface modification of JF/OPPF hybridization on HDPE matrix composite.
Computational Study of the Dynamics of the Taylor Bubble
Authors: Sharaborin Evgenii L. , Rogozin Oleg A. , Kasimov Aslan R.
Published: November 2021

We perform high-resolution numerical simulations of three-dimensional dynamics of an elongated bubble in a microchannel at moderate Reynolds numbers up to 1800. For this purpose, we use the coupled Brinkman penalization and volume of fluid methods implemented in the open-source framework Basilisk. The new results are validated with available experimental data and compared with previous numerical and theoretical predictions. We extend existing results to regimes with significant inertia, which are characterized by intense deformations of the bubble, including cases with azimuthal symmetry breaking. Various dynamical features are analyzed in terms of their spatiotemporal characteristics, such as frequencies and wavelengths of the bubble surface undulations and vortical structures in the flow.
CFD Simulation Study on the Performance of a Modified Ram Air Turbine (RAT) for Power Generation in Aircrafts
Authors: Saad Magedi Moh M. , Mohd Sofian , Zulkafli Mohd Fadhli , Samiran Nor Afzanizam , Didane Djamal Hissein
Published: November 2021

The present paper aims to study the possibility of dispensing an auxiliary power unit (APU) in an aircraft powered by fossil fuels to reduce air pollution. It particularly seeks to evaluate the amount of power generated by the ram air turbine (RAT) using the novel counter-rotating technique while characterizing its optimum axial distance. The ram air turbine (RAT), which is already equipped in aircrafts, was enhanced to generate the amount of energy produced by the APU. The approach was implemented by a CRRAT system. Six airfoil profiles were tested based on 2D models and the best airfoil was chosen for implantation on the RAT and CRRAT systems. The performance of the conventional single-rotor RAT and CRRAT were analyzed using FLUENT software based on 3D models. The adopted numerical scheme was the Navier–Stokes equation with k–ω SST turbulence modeling. The dynamic mesh and user-defined function (UDF) were used to revolve the rotor turbine via wind. The results indicated that the FX63-137 airfoil profile showed a higher performance in terms of the lift-to-drag ratio compared to the other airfoils. The optimum axial distance between the two rotors was 0.087 m of the rotor diameter and the efficiency of the new CRRAT increased to almost 45% compared to the single-rotor RAT.
Correlation of Mercury Occurrence with Age, Elemental Composition, and Life History in Sea-Run Food Fish from the Canadian Arctic Archipelago’s Lower Northwest Passage
Authors: Koch Iris , Das Pranab , McPhedran Bronte E. , Casselman John M. , Moniz Kristy L. , van Coeverden de Groot Peter , Qitsualik James , Muir Derek , Schott Stephan , Walker Virginia K.
Published: November 2021

As mercury emissions continue and climate-mediated permafrost thaw increases the burden of this contaminant in northern waters, Inuit from a Northwest passage community in the Canadian Arctic Archipelago pressed for an assessment of their subsistence catches. Sea-run salmonids (n = 537) comprising Arctic char (Salvelinus alpinus), lake trout (S. namaycush), lake whitefish (Coregonus clupeaformis), and cisco (C. autumnalis, C. sardinella) were analyzed for muscle mercury. Methylmercury is a neurotoxin and bioaccumulated with fish age, but other factors including selenium and other elements, diet and trophic level as assessed by stable isotopes of nitrogen (δ15N) and carbon (δ13C), as well as growth rate, condition, and geographic origin, also contributed depending on the species, even though all the fish shared a similar anadromous or sea-run life history. Although mean mercury concentrations for most of the species were ~0.09 µg·g−1 wet weight (ww), below the levels described in several jurisdictions for subsistence fisheries (0.2 µg·g−1 ww), 70% of lake trout were above this guideline (0.35 µg·g−1 ww), and 19% exceeded the 2.5-fold higher levels for commercial sale. We thus urge the development of consumption advisories for lake trout for the protection of pregnant women and young children and that additionally, periodic community-based monitoring be initiated.
Hepatoprotective Effects of Sweet Cherry Extracts (cv. Saco)
Authors: Gonçalves Ana C. , Flores-Félix José D. , Costa Ana R. , Falcão Amílcar , Alves Gilberto , Silva Luís R.
Published: November 2021

Cancer is the second cause of death worldwide. Among cancers, hepatocellular carcinoma is one of the most prevalent. Evidence indicates that the daily consumption of fruits and vegetables can prevent the onset of various cancers due to the presence of bioactive compounds. Sweet cherries are known for their richness in phenolics, including anthocyanins, which are the major constituents, and presumably, the key contributors to their biological activity. Therefore, the present study aimed to evaluate the effects of three different cherry fractions on human hepatocellular carcinoma (HepG2) cells viability and effectiveness to improve the redox status of these cells under oxidative damage induced by nitric oxide radicals and hydrogen peroxide. Phenolic characterization of fractions was performed by Fourier transform infrared spectroscopy. The obtained results indicated that enriched phenolic fractions of sweet cherries (cv. Saco, can impair cell viability and suppress cells growth after 72 h of exposure, promoting necrosis at the highest tested concentrations (>50 µg/mL). Additionally, fractions also showed the capacity to protect these cells against oxidative injury by capturing radicals before they can attack cells’ membrane and by modulating reactive oxygen and nitrogen species generation, as demonstrated by bioinformatic tools.
High-Protein Bar as a Meal Replacement in Elite Sports Nutrition: A Pilot Study
Authors: Jovanov Pavle , Sakač Marijana , Jurdana Mihaela , Pražnikar Zala Jenko , Kenig Saša , Hadnađev Miroslav , Jakus Tadeja , Petelin Ana , Škrobot Dubravka , Marić Aleksandar
Published: November 2021

This study was focused on the creation of high-protein bars formulated using whey protein isolate (24%) and soy protein isolate (6%) as the sources of proteins; oat flakes and inulin, both abundant in dietary fibres, and creatine monohydrate and other minor ingredients (vitamin and mineral mixture, potassium sorbate) to achieve the requirements for a meal replacement formula for physically active people. The nutritional profile of the high-protein bar was examined (energy 1215 kJ/288 kcal; protein 34.1 ± 0.20 g, fat 6.01 ± 0.13 g of which was saturated 3.12 ± 0.08 g, fibre 3.10 ± 0.17 g carbohydrate 23.0 ± 0.16 g of which sugars 1.50 ± 0.19 g and starch 21.5 ± 0.11 g in 100 g), and sensory properties with instrumental parameters (texture and colour) were determined and compared with bars commercially available on the market. The created high-protein bar was sensorily acceptable in comparison to other commercially available bars. The dietary intervention study was conducted on elite athletes (professional handball players) to evaluate effects of created versus control bar consumption on their metabolic parameters. The baseline characteristics (mean age, body mass index (BMI), fat mass, muscle mass, lean mass and fat percentage) of the athletes (8) were determined at the start of the study. The cross-over intervention study was organized in two successive phases (5 days each) with a seven-day long washout period between phases. Bars were consumed after the afternoon training unit. Blood samples were collected at the start and the end of the intervention study to analyse the metabolic profiles of the athletes. Serum levels of high-density cholesterol (HDL), low-density cholesterol (LDL) and total cholesterol (HOL), glucose, triacylglycerides (TAG), total and direct bilirubin, creatine kinase (CK), aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) were measured. The results showed that bar consumption significantly decreased serum aspartate transaminase (AST) and lactate dehydrogenase (LDH) and increased total and direct bilirubin levels, suggesting lower exercise-induced muscle damage and increased antioxidative response, respectively. Therefore, it can be concluded that the consumption of the created high-protein bar was able to improve physiological adaptation after training.
Application of 13C Quantitative NMR Spectroscopy to Isotopic Analyses for Vanillin Authentication Source
Authors: Pironti Concetta , Ricciardi Maria , Motta Oriana , Camin Federica , Bontempo Luana , Proto Antonio
Published: November 2021

The carbon stable isotope ratio (δ13C) is a valuable chemical parameter in the investigation of the geographic origin, quality, and authenticity of foods. The aim of this study is the evaluation of the feasibility of 13C-NMR (Nuclear Magnetic Resonance) spectroscopy to determine the carbon stable isotope ratio, at natural abundance, of small organic molecules, such as vanillin, without the use of IRMS (Isotope Ratio Mass Spectrometry). The determination of vanillin origin is an active task of research, and differentiating between its natural and artificial forms is important to guarantee the quality of food products. To reach our goal, nine vanillin samples were analyzed using both 13C quantitative NMR spectroscopy (under optimized experimental conditions) and IRMS, and the obtained δ13C values were compared using statistical analysis (linear regression, Bland–Altman plot, and ANOVA (analysis of variance)). The results of our study show that 13C-NMR spectroscopy can be used as a valuable alternative methodology to determine the bulk carbon isotope ratio and to identify the origin of vanillin. This makes it attractive for the analysis in the same experiment of site-specific and total isotope effects for testing authenticity, quality, and typicality of food samples. Moreover, the improvement of NMR spectroscopy makes it possible to avoid the influence of additives on carbon stable isotope ratio analysis and to clearly identify fraud and falsification in commercial samples.
Characterization of Genetically Modified Microorganisms Using Short- and Long-Read Whole-Genome Sequencing Reveals Contaminations of Related Origin in Multiple Commercial Food Enzyme Products
Authors: D’aes Jolien , Fraiture Marie-Alice , Bogaerts Bert , De Keersmaecker Sigrid C. J. , Roosens Nancy H. C. , Vanneste Kevin
Published: November 2021

Despite their presence being unauthorized on the European market, contaminations with genetically modified (GM) microorganisms have repeatedly been reported in diverse commercial microbial fermentation produce types. Several of these contaminations are related to a GM Bacillus velezensis used to synthesize a food enzyme protease, for which genomic characterization remains currently incomplete, and it is unknown whether these contaminations have a common origin. In this study, GM B. velezensis isolates from multiple food enzyme products were characterized by short- and long-read whole-genome sequencing (WGS), demonstrating that they harbor a free recombinant pUB110-derived plasmid carrying antimicrobial resistance genes. Additionally, single-nucleotide polymorphism (SNP) and whole-genome based comparative analyses showed that the isolates likely originate from the same parental GM strain. This study highlights the added value of a hybrid WGS approach for accurate genomic characterization of GMM (e.g., genomic location of the transgenic construct), and of SNP-based phylogenomic analysis for source-tracking of GMM.
Eating Fermented: Health Benefits of LAB-Fermented Foods
Authors: Castellone Vincenzo , Bancalari Elena , Rubert Josep , Gatti Monica , Neviani Erasmo , Bottari Benedetta
Published: November 2021

Lactic acid bacteria (LAB) are involved in producing a considerable number of fermented products consumed worldwide. Many of those LAB fermented foods are recognized as beneficial for human health due to probiotic LAB or their metabolites produced during food fermentation or after food digestion. In this review, we aim to gather and discuss available information on the health-related effects of LAB-fermented foods. In particular, we focused on the most widely consumed LAB-fermented foods such as yoghurt, kefir, cheese, and plant-based products such as sauerkrauts and kimchi.
Preparation of Anti-Aristolochic Acid I Monoclonal Antibody and Development of Chemiluminescent Immunoassay and Carbon Dot-Based Fluoroimmunoassay for Sensitive Detection of Aristolochic Acid I
Authors: Ou Ai-Fen , Chen Zi-Jian , Zhang Yi-Feng , He Qi-Yi , Xu Zhen-Lin , Zhao Su-Qing
Published: November 2021

Aristolochic acid (AA) toxicity has been shown in humans regarding carcinogenesis, nephrotoxicity, and mutagenicity. Monitoring the AA content in drug homologous and healthy foods is necessary for the health of humans. In this study, a monoclonal antibody (mAb) with high sensitivity for aristolochic acid I (AA-I) was prepared. Based on the obtained mAb, a chemiluminescent immunoassay (CLEIA) against AA-I was developed, which showed the 50% decrease in the RLUmax (IC50) value of 1.8 ng/mL and the limit of detection (LOD) of 0.4 ng/mL. Carbon dots with red emission at 620 nm, namely rCDs, were synthesized and employed in conventional indirect competitive enzyme-linked immunosorbent assay (icELISA) to improve the assay sensitivity of a fluoroimmunoassay (FIA). Oxidized 3,3′′,5,5′′-tetramethylbenzidine dihydrochloride (oxTMB) can quench the emission of the rCDs through the inner-filter effect; therefore, the fluorescence intensity of rCDs can be regulated by the concentration of mAb. As a result, the assay sensitivity of FIA was improved by five-fold compared to CLEIA. A good relationship between the results of the proposed assays and the standard ultra-high performance liquid chromatography-triple quadrupole mass spectrometer (UPLC-QQQ-MS/MS) of real samples indicated good accuracy and practicability of CLEIA and FIA.
On the Effect of Microwave Heating on Quality Characteristics and Functional Properties of Persimmon Juice and Its Residue
Authors: Lalou Sofia , Ordoudi Stella A. , Mantzouridou Fani Th.
Published: November 2021

In this study, it was investigated whether integration of microwave-heating into the pretreatment step of persimmon juice processing allows the concomitant production of both functional juice and added-value solid residue from the Diospyros Kaki “Jiro” cultivar. In this direction, persimmon pulp was treated under three different microwave-heating conditions (0.7, 4.2, and 8.4 kJ/g) prior to enzymatic maceration and compared to the non-heated material. Irrespective of microwave energy employed, the proposed hybrid treatment was highly efficient in terms of juice yield (70% w/w). The mildest heating conditions resulted in juice and residue that were both of inferior quality. Intensification of the microwave energy reduced the microbial load of the juice up to 2-log without compromising the content in total soluble solids, sugars, and L-ascorbic acid. Under the most drastic conditions, the juice was enriched in gallic acid, polyphenols, and potent DPPH● scavengers, but its orange color faded and was more acidic. In parallel, the solid juice residue retained pro-vitamin A carotenoids (~278 µg retinol activity equivalents) and low-methoxy pectin (9 g/100 g DW). Overall, our findings can assist the efforts of the local juice processing industry to utilize persimmon fruits through energy-efficient technologies in a sustainable approach.
Evolution of Global Food Trade Patterns and Its Implications for Food Security Based on Complex Network Analysis
Authors: Wang Jieyong , Dai Chun
Published: November 2021

Global food trade is an integral part of the food system, and plays an important role in food security. Based on complex network analyses, this paper analyzed the global food trade network (FTN) and its evolution from 1992 to 2018. The results show that: (1) food trade relations have increased and global FTN is increasingly complex, efficient, and tighter. (2) Global food trade communities have become more stable and the trade network has evolved from “unipolar” to “multipolar”. (3) Over the nearly 30-year period, the core exporting countries have been stable and concentrated, while the core importing countries are relatively dispersed. The increasingly complex food trade network improves food availability and nutritional diversity; however, the food trade system, led by several large countries, has increased the vulnerability of some countries’ food systems and brings about unsafe factors, such as global natural disasters and political instability. It is supposed to establish a food security community to protect the global food trade market, address multiple risks, and promote global food security.
Non-IgE-Mediated Gastrointestinal Food Protein-Induced Allergic Disorders. Clinical Perspectives and Analytical Approaches
Authors: Zubeldia-Varela Elisa , Barker-Tejeda Tomás Clive , Blanco-Pérez Frank , Infante Sonsoles , Zubeldia José M. , Pérez-Gordo Marina
Published: November 2021

Non-IgE-mediated gastrointestinal food allergy (non-IgE-GI-FA) is the name given to a series of pathologies whose main entities are food protein-induced allergic proctocolitis (FPIAP), food protein-induced enteropathy (FPE), and food protein-induced enterocolitis syndrome (FPIES). These are more uncommon than IgE-mediated food allergies, their mechanisms remain largely unknown, and their diagnosis is mainly done by clinical history, due to the lack of specific biomarkers. In this review, we present the latest advances found in the literature about clinical aspects, the current diagnosis, and treatment options of non-IgE-GI-FAs. We discuss the use of animal models, the analysis of gut microbiota, omics techniques, and fecal proteins with a focus on understanding the pathophysiological mechanisms of these pathologies and obtaining possible diagnostic and/or prognostic biomarkers. Finally, we discuss the unmet needs that researchers should tackle to advance in the knowledge of these barely explored pathologies.
Effects of Radio Frequency Tempering on the Texture of Frozen Tilapia Fillets
Authors: Jiang Jiwei , Zhou Fen , Xian Caining , Shi Yuyao , Wang Xichang
Published: November 2021

Radio frequency (RF) tempering has been proposed as a new alternative method for tempering frozen products because of its advantages of rapid and volumetric heating. In this study, the texture of RF-tempered frozen tilapia fillets was determined under different RF conditions, the effects of related factors on the texture were analyzed, and the mechanisms by which RF tempering affected the texture of the tempered fillets were evaluated. The results show that the springiness (from 0.84 mm to 0.79 mm), cohesiveness (from 0.64 mm to 0.57 mm), and resilience (from 0.33 mm to 0.25 mm) decreased as the electrode gap was increased and the power remained at 600 W, while the shear force increased as the power was increased for the 12 cm electrode gap (from 15.18 N to 16.98 N), and the myofibril fragmentation index (MFI) values were markedly higher at 600 W than at 300 W or 900 W (p < 0.05). In addition, the tempering uniformity had a positive effect on hardness and chewiness. The statistical analysis showed that the texture after RF tempering under different RF conditions correlated relatively strongly with the free water content, cooking loss, and migration of bound water to immobilized water. The decrease in free water and bound water migration to immobilized water resulted in a significant increase in cohesiveness and resilience.
Social Environmental Factors Related to Resuming Driving after Brain Injury: A Multicenter Retrospective Cohort Study
Authors: Sato Mamiko , Kobayashi Yasutaka , Fujita Kazuki , Hitosugi Masahito
Published: November 2021

Many patients resume driving after brain injury regardless of their ability to drive safely. Predictors for resuming driving in terms of actual resumption status and environmental factors are unclear. We evaluated the reasons for resuming driving after brain injury and examined whether social environmental factors are useful predictors of resuming driving. This retrospective cohort study was based on a multicenter questionnaire survey at least 18 months after discharge of brain injury patients with rehabilitation. A total of 206 brain injury patients (cerebrovascular disease and traumatic brain injury) were included in the study, which was conducted according to the International Classification of Functioning (ICF) items using log-binominal regression analysis, evaluating social environmental factors as associated factors of resuming driving after brain injury. Social environmental factors, inadequate public transport (risk ratio (RR), 1.38), and no alternative driver (RR, 1.53) were included as significant independent associated factors. We found that models using ICF categories were effective for investigating factors associated with resuming driving in patients after brain injury and significant association between resuming driving and social environmental factors. Therefore, social environmental factors should be considered when predicting driving resumption in patients after brain injury, which may lead to better counseling and environmental adjustment.
Is the Pain Just Physical? The Role of Psychological Distress, Quality of Life, and Autistic Traits in Ehlers–Danlos Syndrome, an Internet-Based Survey in Italy
Authors: Rocchetti Matteo , Bassotti Alessandra , Corradi Jacopo , Damiani Stefano , Pasta Gianluigi , Annunziata Salvatore , Guerrieri Viviana , Mosconi Mario , Gentilini Davide , Brondino Natascia
Published: November 2021

Background: Ehlers–Danlos syndromes (EDS) have been associated with psychological distress, comorbid psychiatric disorders, and worsening in quality of life (QoL). Among the neurodevelopmental disorders, autism spectrum disorders (ASD) have shown the highest rates of co-occurrence with EDS. The reasons for these associations are unknown and a possible role of pain in increasing the risk of psychiatric disorders in EDS has been suggested. However, a detailed picture of an Italian EDS sample is still lacking. Methods: We conducted a web-based survey in a third level center for the diagnosis of EDS in northern Italy, to investigate psychological distress, QoL, and the presence of autistic traits. Furthermore, we correlated the psychometric data with some clinical variables. Results: We observed a high rate of psychological distress with 91% of the responders at high risk of common mental disorders, low QoL, and high prevalence of autistic traits in EDS patients. Specifically, patients lacking a specific genetic test, diagnosed as suspects of EDS appeared to be at greater risk and reported worse psychological QoL. Pain was significantly associated with both psychological distress and worse QoL. Conclusions: Our findings support the need of further research and of a multi-disciplinary approach to EDS including psychological and psychiatric liaison.
Nursing Students’ Experiences of Gratitude Journaling during the COVID-19 Pandemic
Authors: Ko Heesung , Kim Seryeong , Kim Eunjeong
Published: November 2021

Gratitude journaling has been used to improve grateful disposition. However, there is only limited data available on its application experience. This study aimed to: (1) explore the experiences of nursing students who have participated in gratitude journaling; and (2) assess students’ views of gratitude journaling as a nursing intervention. This study implemented an eight-week program of gratitude journaling with fourth-year nursing students who took a mental health psychiatric nursing course at a South Korean university. Following the eight weeks, students reflected on their gratitude journaling experience in a reflective essay. Using content analysis, 53 essays were analyzed. Five categories were identified from the reflective essay, as follows: “A new beginning”, “The engine that motivates continued participation: gratitude sharing”, “The process driving change”, “Changes brought about by gratitude”, and “Self-reflection”. Based on this experience, nursing students believed that it is important to promote steady participation when administering gratitude journaling as a nursing intervention. The study findings suggest that the gratitude journaling not only helped with nursing students’ perspective, emotional, and behavioral aspects and stress management, but also provided an opportunity to advance a step further based on self-reflection.