bluuebunny/crossref_metadata_2025 huggingface dataset:
From LI-RADS Classification to HCC Pathology: A Retrospective Single-Institution Analysis of Clinico-Pathological Features Affecting Oncological Outcomes after Curative Surgery
Authors: Centonze Leonardo , De Carlis Riccardo , Vella Ivan , Carbonaro Luca , Incarbone Niccolò , Palmieri Livia , Sgrazzutti Cristiano , Ficarelli Alberto , Valsecchi Maria Grazia , Dello Iacono Umberto , Lauterio Andrea , Bernasconi Davide , Vanzulli Angelo , De Carlis Luciano
Published: January 2022

Background: The latest Liver Imaging Reporting and Data System (LI-RADS) classification by the American College of Radiology has been recently endorsed in the American Association for the Study of Liver Disease (AASLD) guidelines for Hepatocellular carcinoma (HCC) management. Although the LI-RADS protocol has been developed as a diagnostic algorithm, there is some evidence concerning a possible correlation between different LI-RADS classes and specific pathological features of HCC. We aimed to investigate such radiological/pathological correlation and the possible prognostic implication of LI-RADS on a retrospective cohort of HCC patients undergoing surgical resection. Methods: We performed a retrospective analysis of the pathological characteristics of resected HCC, exploring their distribution among different LI-RADS classes and analyzing the risk factors for recurrence-free, overall and cancer-specific survival Results: LI-RADS-5 (LR-5) nodules showed a higher prevalence of microvascular invasion (MVI), satellitosis and capsule infiltration, as well as higher median values of alpha-fetoprotein (αFP) compared to LI-RADS-3/4 (LR-3/4) nodules. MVI, αFP, satellitosis and margin-positive (R1) resection resulted as independent risk factors for recurrence-free survival, while LI-RADS class did not exert any significant impact. Focusing on overall survival, we identified patient age, Eastern Cooperative Oncology Group performance status (ECOG-PS), Model for End Stage Liver Disease (MELD) score, αFP, MVI, satellitosis and R1 resection as independent risk factors for survival, without any impact of LI-RADS classification. Last, MELD score, log10αFP, satellitosis and R1 resection resulted as independent risk factors for cancer-specific survival, while LI-RADS class did not exert any significant impact. Conclusions: Our results suggest an association of LR-5 class with unfavorable pathological characteristics of resected HCC; tumor histology and underlying patient characteristics such as age, ECOG-PS and liver disease severity exert a significant impact on postoperative oncological outcomes.
Impact of Impaired Glucose Metabolism on Periodontitis Progression over Three Years
Authors: Andriankaja Oelisoa M. , Joshipura Kaumudi , Muñoz Francisco , Dye Bruce A. , Hu Frank B. , Pérez Cynthia M.
Published: January 2022

We evaluated the relationship between glucose abnormalities and periodontitis in overweight/obese individuals. Eight hundred and seventy (870) diabetes-free participants aged 40–65 years completed the three-year follow-up in the San Juan Overweight Adults Longitudinal Study. The ADA thresholds for fasting and 2-h post-load glucose and HbA1c were used to define prediabetes. The NHANES methods were used to assess periodontitis. Multivariable linear regression was used to evaluate the relationship between baseline glucose metabolism measures and periodontitis at follow-up, adjusting for potential confounders. There was no association between impaired glucose measures and mean pocket depth (PD), mean clinical attachment loss (CAL), or mean percent of sites ≥5 mm PD. Impaired glucose tolerance (IGT) was associated with a lower mean percent of sites ≥5 mm CAL (β = −1.6, p = 0.037). Prediabetes and impaired fasting glucose (IFG) were associated with improvement in mean percent of sites ≥5 mm PD (β = −1.4, p = 0.022; β = −1.6, p = 0.032; respectively). IFG and IGT were associated with improvement in mean percent of sites with ≥5 mm CAL (β = −1.6, p = 0.038; β = −1.9, p = 0.020; respectively). In conclusion, there were no consistent associations between baseline prediabetes or insulin resistance and periodontitis progression over a three-year period.
A Decade of UAV Docking Stations: A Brief Overview of Mobile and Fixed Landing Platforms
Authors: Grlj Carlo Giorgio , Krznar Nino , Pranjić Marko
Published: January 2022

Unmanned Aerial Vehicles have advanced rapidly in the last two decades with the advances in microelectromechanical systems (MEMS) technology. It is crucial, however, to design better power supply technologies. In the last decade, lithium polymer and lithium-ion batteries have mainly been used to power multirotor UAVs. Even though batteries have been improved and are constantly being improved, they provide fairly low energy density, which limits multirotors’ UAV flight endurance. This problem is addressed and is being partially solved by using docking stations which provide an aircraft to land safely, charge (or change) the batteries and to take-off as well as being safely stored. This paper focuses on the work carried out in the last decade. Different docking stations are presented with a focus on their movement abilities. Rapid advances in computer vision systems gave birth to precise landing systems. These algorithms are the main reason that docking stations became a viable solution. The authors concluded that the docking station solution to short ranges is a viable option, and numerous extensive studies have been carried out that offer different solutions, but only some types, mainly fixed stations with storage systems, have been implemented and are being used today. This can be seen from the commercially available list of docking stations at the end of this paper. Nevertheless, it is important to be aware of the technologies being developed and implemented, which can offer solutions to a vast number of different problems.
Does Climate Change Affect the Yield of the Top Three Cereals and Food Security in the World?
Authors: Neupane Dhurba , Adhikari Pramila , Bhattarai Dwarika , Rana Birendra , Ahmed Zeeshan , Sharma Umanath , Adhikari Debraj
Published: January 2022

Climate prediction models suggest that agricultural productivity will be significantly affected in the future. The expected rise in average global temperature due to the higher release of greenhouse gases (GHGs) into the atmosphere and increased depletion of water resources with enhanced climate variability will be a serious threat to world food security. Moreover, there is an increase in the frequency and severity of long-lasting drought events over 1/3rd of the global landmass and five times increase in water demand deficits during the 21st century. The top three cereals, wheat (Triticum aestivum), maize (Zea mays), and rice (Oryza sativa), are the major and staple food crops of most people across the world. To meet the food demand of the ever-increasing population, which is expected to increase by over 9 billion by 2050, there is a dire need to increase cereal production by approximately 70%. However, we have observed a dramatic decrease in area of fertile and arable land to grow these crops. This trend is likely to increase in the future. Therefore, this review article provides an extensive review on recent and future projected area and production, the growth requirements and greenhouse gas emissions and global warming potential of the top three cereal crops, the effects of climate change on their yields, and the morphological, physiological, biochemical, and hormonal responses of plants to drought. We also discuss the potential strategies to tackle the effects of climate change and increase yields. These strategies include integrated conventional and modern molecular techniques and genomic approach, the implementation of agronomic best management (ABM) practices, and growing climate resilient cereal crops, such as millets. Millets are less resource-intensive crops and release a lower amount of greenhouse gases compared to other cereals. Therefore, millets can be the potential next-generation crops for research to explore the climate-resilient traits and use the information for the improvement of major cereals.
Accuracy of Body Mass Index and Obesity Status in Police Trainees
Authors: Stojković Miloš , Heinrich Katie M. , Čvorović Aleksandar , Jeknić Velimir , Greco Gianpiero , Kukić Filip
Published: January 2022

The first aim of this study was to compare body mass index (BMI) (indirect method) classification with the body fat percent (PBF) (direct method) and to determine how BMI classifies subjects with different levels of skeletal muscle mass percent (PSMM). The second aim was to determine the prevalence of overweight and obesity status among police trainees (PTs). A total of 103 male PTs participated in this research: age = 21.46 ± 0.64 years, body mass (BM) = 75.97 ± 8.10 kg, body height (BH) = 174.07 ± 6.31 cm, BMI = 25.05 ± 2.12 kg/m2. The InBody 370 multichannel bioelectrical impedance analysis (BIA) measured body composition. Study results indicated that muscular PTs could be misclassified as overweight and that PBF identified more subjects as obese. Namely, three PTs were obese according to BMI, while 13 were obese according to PBF. The information provided by this research could be used to help professionals understand the importance of measuring body composition, and the inaccuracies in BMI classification. In conclusion, whenever possible PSMM and PBF should replace the utilization of BMI to screen overweight and obesity in PTs. Agencies may think of using BIA as non-invasive, quick and inexpensive measurement tool.
Psychometric Properties of the Emotional Exhaustion Scale (ECE) in Chilean Higher Education Students
Authors: Martínez-Líbano Jonathan , Yeomans María-Mercedes , Oyanedel Juan-Carlos
Published: January 2022

The main objective of this study was to estimate the psychometric properties of the Emotional Fatigue Scale (ECE) in a sample of 1308 Chilean university students and confirm the unifactorial structure of the scale. Exploratory and confirmatory factor analyses were carried out. The ECE assessment had an internal consistency of 0.893 (Cronbach’s Alpha). An exploratory factor analysis with Varimax rotation and a confirmatory analysis were performed, obtaining the factor that explains 52.3% of the variance. The results indicated that the ECE has adequate psychometric properties for use with higher education students in Chile. The ECE scale has good psychometric properties to be applied in the Chilean university context. Its usage may be very relevant to contribute to higher education institutions to emphasize students’ mental health and prevent possible severe pathologies in future professionals. It is suggested to use the ECE scale together with the EES-Int, which is the only interpretation table for this instrument.
p-Type Iodine-Doping of Cu3N and Its Conversion to γ-CuI for the Fabrication of γ-CuI/Cu3N p-n Heterojunctions
Authors: Tilemachou Argyris , Zervos Matthew , Othonos Andreas , Pavloudis Theodoros , Kioseoglou Joseph
Published: January 2022

Cu3N with a cubic crystal structure is obtained in this paper by the sputtering of Cu under N2 followed by annealing under NH3: H2 at 400 °C, after which it was doped with iodine at room temperature resulting into p-type Cu3N with hole densities between 1016 and 1017 cm−3. The Cu3N exhibited distinct maxima in differential transmission at ~2.01 eV and 1.87 eV as shown by ultrafast pump-probe spectroscopy, corresponding to the M and R direct energy band gaps in excellent agreement with density functional theory calculations, suggesting that the band gap is clean and free of mid-gap states. The Cu3N was gradually converted into optically transparent γ-CuI that had a hole density of 4 × 1017 cm−3, mobility of 12 cm2/Vs and room temperature photoluminescence at 3.1 eV corresponding to its direct energy band gap. We describe the fabrication and properties of γ-CuI/TiO2/Cu3N and γ-CuI/Cu3N p-n heterojunctions that exhibited rectifying current-voltage characteristics, but no photogenerated current attributed to indirect recombination via shallow states in Cu3N and/or deep states in the γ-CuI consistent with the short (ps) lifetimes of the photoexcited electrons-holes determined from transient absorption–transmission spectroscopy.
Defect- and H-Free Stoichiometric Silicon Carbide by Thermal CVD from the Single Source Precursor Trisilacyclohexane
Authors: Kaloyeros Alain E. , Goff Jonathan , Arkles Barry
Published: January 2022

Stoichiometric silicon carbide (SiC) thin films were grown using thermal chemical vapor deposition (TCVD) from the single source precursor 1,3,5-trisilacyclohexane (TSCH) on c-Si (100) substrates within an optimized substrate temperature window ranging from 650 to 850 °C. X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR) analyses revealed that the as-deposited films consisted of a Si-C matrix with a Si:C ratio of ~1:1. FTIR and photoluminescence (PL) spectrometry studies showed that films deposited ≥ 750 °C were defect- and H-free within the detection limit of the techniques used, while ellipsometry measurements yielded an as-grown SiC average refractive index of ~2.7, consistent with the reference value for the 3C-SiC phase. The exceptional quality of the films appears sufficient to overcome limitations associated with structural defects ranging from failure in high voltage, high temperature electronics to 2-D film growth. TSCH, a liquid at room temperature with good structural stability during transport and handling as well as high vapor pressure (~10 torr at 25 °C), provides a viable single source precursor for the growth of stoichiometric SiC without the need for post-deposition thermal treatment.
Group-Based Sparse Representation for Compressed Sensing Image Reconstruction with Joint Regularization
Authors: Wang Rongfang , Qin Yali , Wang Zhenbiao , Zheng Huan
Published: January 2022

Achieving high-quality reconstructions of images is the focus of research in image compressed sensing. Group sparse representation improves the quality of reconstructed images by exploiting the non-local similarity of images; however, block-matching and dictionary learning in the image group construction process leads to a long reconstruction time and artifacts in the reconstructed images. To solve the above problems, a joint regularized image reconstruction model based on group sparse representation (GSR-JR) is proposed. A group sparse coefficients regularization term ensures the sparsity of the group coefficients and reduces the complexity of the model. The group sparse residual regularization term introduces the prior information of the image to improve the quality of the reconstructed image. The alternating direction multiplier method and iterative thresholding algorithm are applied to solve the optimization problem. Simulation experiments confirm that the optimized GSR-JR model is superior to other advanced image reconstruction models in reconstructed image quality and visual effects. When the sensing rate is 0.1, compared to the group sparse residual constraint with a nonlocal prior (GSRC-NLR) model, the gain of the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) is up to 4.86 dB and 0.1189, respectively.
Approximate Computing Circuits for Embedded Tactile Data Processing
Authors: Osta Mario , Ibrahim Ali , Valle Maurizio
Published: January 2022

In this paper, we demonstrate the feasibility and efficiency of approximate computing techniques (ACTs) in the embedded Support Vector Machine (SVM) tensorial kernel circuit implementation in tactile sensing systems. Improving the performance of the embedded SVM in terms of power, area, and delay can be achieved by implementing approximate multipliers in the SVD. Singular Value Decomposition (SVD) is the main computational bottleneck of the tensorial kernel approach; since digital multipliers are extensively used in SVD implementation, we aim to optimize the implementation of the multiplier circuit. We present the implementation of the approximate SVD circuit based on the Approximate Baugh-Wooley (Approx-BW) multiplier. The approximate SVD achieves an energy consumption reduction of up to 16% at the cost of a Mean Relative Error decrease (MRE) of less than 5%. We assess the impact of the approximate SVD on the accuracy of the classification; showing that approximate SVD increases the Error rate (Err) within a range of one to eight percent. Besides, we propose a hybrid evaluation test approach that consists of implementing three different approximate SVD circuits having different numbers of approximated Least Significant Bits (LSBs). The results show that energy consumption is reduced by more than five percent with the same accuracy loss.
Efficient General Reflectarray Design and Direct Layout Optimization with a Simple and Accurate Database Using Multilinear Interpolation
Authors: Prado Daniel R. , López-Fernández Jesús A. , Arrebola Manuel
Published: January 2022

In this work, a simple, efficient and accurate database in the form of a lookup table to use in reflectarray design and direct layout optimization is presented. The database uses N-linear interpolation internally to estimate the reflection coefficients at coordinates that are not stored within it. The speed and accuracy of this approach were measured against the use of the full-wave technique based on local periodicity to populate the database. In addition, it was also compared with a machine learning technique, namely, support vector machines applied to regression in the same conditions, to elucidate the advantages and disadvantages of each one of these techniques. The results obtained from the application to the layout design, analysis and crosspolar optimization of a very large reflectarray for space applications show that, despite using a simple N-linear interpolation, the database offers sufficient accuracy, while considerably accelerating the overall design process as long as it is conveniently populated.
Processing–Structure–Performance Relationship in Organic Transistors: Experiments and Model
Authors: Liguori Rosalba , Facchetti Antonio , Licciardo Gian Domenico , Di Benedetto Luigi
Published: January 2022

In this paper, organic thin film transistors with different configurations are fabricated, and the effect on their performance when tailoring the semiconductor/insulator and semiconductor/contact interfaces through suitable treatments is analyzed. It is shown that the admittance spectroscopy used together with a properly developed electrical model turns out to be a particularly appropriate technique for correlating the performance of devices based on new materials in the manufacturing methods. The model proposed here to describe the equivalent metal–insulator–semiconductor (MIS) capacitor enables the extraction of a wide range of parameters and the study of the physical phenomena occurring in the transistors: diffusion of mobile ions through the insulator, charge trapping at the interfaces, dispersive transport in the semiconductor, and charge injection at the metal contacts. This is necessary to improve performance and stability in the case, like this one, of a novel organic semiconductor being employed. Atomic force microscopy images are also exploited to support the relationship between the semiconductor morphology and the electrical parameters.
Design and Implementation of a Metadata Repository about UML Class Diagrams. A Software Tool Supporting the Automatic Feeding of the Repository
Authors: Di Felice Paolino , Paolone Gaetanino , Paesani Romolo , Marinelli Martina
Published: January 2022

Model-Driven Engineering is largely recognized as the most powerful method for the design of complex software. This study deals with the automated archival of metadata about the content of UML class diagrams (a particularly relevant category of models) into a pre-existing repository. To define the structure of the repository, we started from the definition of a UML metamodel. From the latter, we derived the schema of the metadata repository. Then, a parser was developed that is responsible for extracting the useful information from the XMI file about class diagrams and enters it as metadata into the repository. The parser has been implemented as a Java web interface, while the metadata repository has been implemented as a PostgreSQL database based on the JSONB data type. The metadata repository is thought to support modelers in the initial phase of the process of the development of new models when looking for artifacts to start from. The schema of the metadata repository and the Java code of the parser are available from the authors.
Power Forecasting of Regional Wind Farms via Variational Auto-Encoder and Deep Hybrid Transfer Learning
Authors: Khan Mansoor , Naeem Muhammad Rashid , Al-Ammar Essam A. , Ko Wonsuk , Vettikalladi Hamsakutty , Ahmad Irfan
Published: January 2022

Wind power is a sustainable green energy source. Power forecasting via deep learning is essential due to diverse wind behavior and uncertainty in geological and climatic conditions. However, the volatile, nonlinear and intermittent behavior of wind makes it difficult to design reliable forecasting models. This paper introduces a new approach using variational auto-encoding and hybrid transfer learning to forecast wind power for large-scale regional windfarms. Transfer learning is applied to windfarm data collections to boost model training. However, multiregional windfarms consist of different wind and weather conditions, which makes it difficult to apply transfer learning. Therefore, we propose a hybrid transfer learning method consisting of two feature spaces; the first was obtained from an already trained model, while the second, small feature set was obtained from a current windfarm for retraining. Finally, the hybrid transferred neural networks were fine-tuned for different windfarms to achieve precise power forecasting. A comparison with other state-of-the-art approaches revealed that the proposed method outperforms previous techniques, achieving a lower mean absolute error (MAE), i.e., between 0.010 to 0.044, and a lowest root mean square error (RMSE), i.e., between 0.085 to 0.159. The normalized MAE and RMSE was 0.020, and the accuracy losses were less than 5%. The overall performance showed that the proposed hybrid model offers maximum wind power forecasting accuracy with minimal error.
Critical Review of Basic Methods on DoA Estimation of EM Waves Impinging a Spherical Antenna Array
Authors: Famoriji Oluwole John , Shongwe Thokozani
Published: January 2022

Direction-of-arrival (DoA) estimation of electromagnetic (EM) waves impinging on a spherical antenna array in short time windows is examined in this paper. Reflected EM signals due to non-line-of-sight propagation measured with a spherical antenna array can be coherent and/or highly correlated in a snapshot. This makes spectral-based methods inefficient. Spectral methods, such as maximum likelihood (ML) methods, multiple signal classification (MUSIC), and beamforming methods, are theoretically and systematically investigated in this study. MUSIC is an approach used for frequency estimation and radio direction finding, ML is a technique used for estimating the parameters of an assumed probability distribution for given observed data, and PWD applies a Fourier transform to the capture response and produces them in the frequency domain. Although they have been previously adapted and used to estimate DoA of EM signals impinging on linear and planar antenna array configurations, this paper investigates their suitability and effectiveness for a spherical antenna array. Various computer simulations were conducted, and plots of root-mean-square error (RMSE) against the square root of the Cramér–Rao lower bound (CRLB) were generated and used to evaluate the performance of each method. Numerical experiments and results from measured data show the degree of appropriateness and efficiency of each method. For instance, the techniques exhibit identical performance to that in the wideband scenario when the frequency f = 8 GHz, f = 16 GHz, and f = 32 GHz, but f = 16 GHz performs best. This indicates that the difference between the covariance matrix of the signal is coherent and that the steering vectors of signals impinging from that angle are small. MUSIC and PWD share the same problems in the single-frequency scenario as in the wideband scenario when the delay sample d = 0. Consequently, the DoA estimation obtained with ML techniques is more suitable, less biased, and more robust against noise than beamforming and MUSIC techniques. In addition, deterministic ML (DML) and weighted subspace fitting (WSF) techniques show better DoA estimation performance than the stochastic ML (SML) technique. For a large number of snapshots, WSF is a better choice because it is more computationally efficient than DML. Finally, the results obtained indicate that WSF and ML methods perform better than MUSIC and PWD for the coherent or partially correlated signals studied.
Performance Entitlement by Using Novel High Strength Electrical Steels and Copper Alloys for High-Speed Laminated Rotor Induction Machines
Authors: Zhang Fengyu , Gerada David , Xu Zeyuan , He Yuling , Zhang He , Hua Wei , Gerada Chris
Published: January 2022

The laminated rotor Induction Machine (IM), with its simple construction and manufacturing, robustness, ease of control and comparatively lower cost remains by far the most utilized electromechanical energy converter. At very high speeds, traditionally its use is considered to be limited to the previously established operational limits of 2.5 × 105 rpm√kW, beyond which the surface Permanent Magnet (PM) Machine and the solid rotor Induction Machine become the machines available for consideration. The aforesaid limits are derived from the use of classic materials. This paper reviews the recent developments in electrical steels and copper alloys and translates these into the resulting performance entitlement and operational limits through a case study involving a marine application, for which an existing rare-earth PM machine is in use. It is concluded that with novel materials, laminated rotor induction machines can be operated up to 6 × 105 rpm√kW, thus opening the use of the rare-earth free Induction Machine for a wider application range previously limited to PM machines.
Molecular Aspects of Spike–ACE2 Interaction
Authors: De Masi Luigi , Argenio Maria Antonia , Giordano Deborah , Facchiano Angelo
Published: January 2022

A new betacoronavirus (CoV-2) is responsible for the pandemic of severe acute respiratory syndrome (SARS) that began in China at the end of 2019, today known as COronaVIrus Disease 2019 (COVID-19). Subsequent studies confirmed the human angiotensin-converting enzyme 2 (hACE2) as the main cell receptor of spike trimeric glycoprotein, located on the viral envelope, mediating the CoV-2 invasion into the host cells through the receptor-binding domain (RBD) of the spike. Computational analysis of the known experimental 3D structures of spike–ACE2 complexes evidenced distinguishing features in the molecular interactions at the RBD-cell receptor binding interface between CoV-2 and previous CoV-1. The spike represents a key target for drug design as well as an optimal antigen for RNA/viral vector vaccines and monoclonal antibodies in order to maximize prevention and therapy of COVID-19.
Functional Characterization of Transporters for L-Aspartate in Bacillus licheniformis
Authors: Wang Hanrong , Li Youran , Xiao Fengxu , Zhang Yupeng , Shi Guiyang , Zhang Liang , Xu Sha , Ding Zhongyang , Gu Zhenghua
Published: January 2022

Amino acid efflux and influx transport systems play vital roles in industrial microorganisms’ cell growth and metabolism. However, although biochemically characterized, most of them remain unknown at the molecular level in Bacillus licheniformis. In this study, three proteins, namely, YdgF, YvbW, and YveA, were predicted to be involved in the active transport of L-aspartate (L-Asp). This was verified by manipulating their encoding genes. When growing in the minimal medium with L-Asp as the only carbon and nitrogen source, the growth of strains lacking proteins YdgF, YvbW, and YveA was significantly inhibited compared with the wild-type strains, while supplementing the expression of the corresponding proteins in the single-gene knockout strains could alleviate the inhibition. Upon overexpression, the recombinant proteins mediated the accumulation of L-aspartate to varying degrees. Compared with the wild-type strains, the single knockout strains of the three protein genes exhibited reduced absorption of L-aspartate. In addition, this study focused on the effects of these three proteins on the absorption of β-alanine, L-glutamate, D-serine, D-alanine, and glycine.
Effect of Lactobacillus plantarum Inoculation on Chemical Composition, Fermentation, and Bacterial Community Composition of Ensiled Sweet Corn Whole Plant or Stover
Authors: Ma Zhi-Yuan , Ungerfeld Emilio , Ouyang Zhu , Zhou Xiao-Ling , Han Xue-Feng , Zeng Yan-Qin , Tan Zhi-Liang
Published: January 2022

Sweet corn is a feed resource with a high content of water-soluble carbohydrates (WSC) available for ruminant production. This study was conducted to investigate the effect of inoculation with Lactobacillus plantarum on fermentation and nutritional quality of sweet corn silage. Sweet corn whole plant (WP) and sweet corn stover (CS) were ensiled in mini silos with or without inoculation of L. plantarum. Proximate composition and fermentation variables, and composition of the bacterial community, were evaluated before ensiling and at the end of the first, second, and third month after ensiling. There was fiber degradation in CS silage after three months of ensilage, but not in WP silage. Inoculation of WP silage, but not of CS silage, with L. plantarum, increased starch content. The relative abundance of genus Lactobacillus was increased by inoculation with L. plantarum by 14.2% and 82.2% in WP and CS silage, respectively. Inoculation with L. plantarum was not necessary to achieve adequate fermentation of either WP or CS silage, as the abundance of native lactic acid bacteria in both materials seemed suitable for adequate fermentation. That said, increased starch content in WP resulting from inoculation with L. plantarum can increase the nutritive value of WP for ruminants.
Determining Firebrand Generation Rate Using Physics-Based Modelling from Experimental Studies through Inverse Analysis
Authors: Wickramasinghe Amila , Khan Nazmul , Moinuddin Khalid
Published: January 2022

Firebrand spotting is a potential threat to people and infrastructure, which is difficult to predict and becomes more significant when the size of a fire and intensity increases. To conduct realistic physics-based modeling with firebrand transport, the firebrand generation data such as numbers, size, and shape of the firebrands are needed. Broadly, the firebrand generation depends on atmospheric conditions, wind velocity and vegetation species. However, there is no experimental study that has considered all these factors although they are available separately in some experimental studies. Moreover, the experimental studies have firebrand collection data, not generation data. In this study, we have conducted a series of physics-based simulations on a trial-and-error basis to reproduce the experimental collection data, which is called an inverse analysis. Once the generation data was determined from the simulation, we applied the interpolation technique to calibrate the effects of wind velocity, relative humidity, and vegetation species. First, we simulated Douglas-fir (Pseudotsuga menziesii) tree-burning and quantified firebrand generation against the tree burning experiment conducted at the National Institute of Standards and Technology (NIST). Then, we applied the same technique to a prescribed forest fire experiment conducted in the Pinelands National Reserve (PNR) of New Jersey, the USA. The simulations were conducted with the experimental data of fuel load, humidity, temperature, and wind velocity to ensure that the field conditions are replicated in the experiments. The firebrand generation rate was found to be 3.22 pcs/MW/s (pcs-number of firebrands pieces) from the single tree burning and 4.18 pcs/MW/s in the forest fire model. This finding was complemented with the effects of wind, vegetation type, and fuel moisture content to quantify the firebrand generation rate.
Inlet and Outlet Boundary Conditions and Uncertainty Quantification in Volumetric Lattice Boltzmann Method for Image-Based Computational Hemodynamics
Authors: Yu Huidan , Khan Monsurul , Wu Hao , Zhang Chunze , Du Xiaoping , Chen Rou , Fang Xin , Long Jianyun , Sawchuk Alan P.
Published: January 2022

Inlet and outlet boundary conditions (BCs) play an important role in newly emerged image-based computational hemodynamics for blood flows in human arteries anatomically extracted from medical images. We developed physiological inlet and outlet BCs based on patients’ medical data and integrated them into the volumetric lattice Boltzmann method. The inlet BC is a pulsatile paraboloidal velocity profile, which fits the real arterial shape, constructed from the Doppler velocity waveform. The BC of each outlet is a pulsatile pressure calculated from the three-element Windkessel model, in which three physiological parameters are tuned by the corresponding Doppler velocity waveform. Both velocity and pressure BCs are introduced into the lattice Boltzmann equations through Guo’s non-equilibrium extrapolation scheme. Meanwhile, we performed uncertainty quantification for the impact of uncertainties on the computation results. An application study was conducted for six human aortorenal arterial systems. The computed pressure waveforms have good agreement with the medical measurement data. A systematic uncertainty quantification analysis demonstrates the reliability of the computed pressure with associated uncertainties in the Windkessel model. With the developed physiological BCs, the image-based computation hemodynamics is expected to provide a computation potential for the noninvasive evaluation of hemodynamic abnormalities in diseased human vessels.
Valorization of By-Products from Biofuel Biorefineries: Extraction and Purification of Bioactive Molecules from Post-Fermentation Corn Oil
Authors: Cairone Francesco , Cesa Stefania , Ciogli Alessia , Fabrizi Giancarlo , Goggiamani Antonella , Iazzetti Antonia , Di Lena Gabriella , Sanchez del Pulgar Jose , Lucarini Massimo , Cantò Luca , Zengin Gokhan , Ondrejíčková Petra
Published: January 2022

The aim of this work was to develop innovative and sustainable extraction, concentration, and purification technologies aimed to recover target substances from corn oil, obtained as side stream product of biomass refineries. Residues of bioactive compounds such as carotenoids, phytosterols, tocopherols, and polyphenols could be extracted from this matrix and applied as ingredients for food and feeds, nutraceuticals, pharmaceuticals, and cosmetic products. These molecules are well known for their antioxidant and antiradical capacity, besides other specific biological activities, generically involved in the prevention of chronic and degenerative diseases. The project involved the development of methods for the selective extraction of these minor components, using as suitable extraction technique solid phase extraction. All the extracted and purified fractions were evaluated by NMR spectroscopic analyses and UV–Vis spectrophotometric techniques and characterized by quali-quantitative HPLC analyses. TPC (total phenolic content) and TFC (total flavonoid content) were also determined. DPPH and ABTS radical were used to evaluate radical quenching abilities. Acetylcholinesterase (AChE), amylase, glucosidase, and tyrosinase were selected as enzymes in the enzyme inhibitory assays. The obtained results showed the presence of a complex group of interesting molecules with strong potential in market applications according to circular economy principles.
Exopolysaccharides Produced by Lactic Acid Bacteria: From Biosynthesis to Health-Promoting Properties
Authors: Jurášková Dominika , Ribeiro Susana C. , Silva Celia C. G.
Published: January 2022

The production of exopolysaccharides (EPS) by lactic acid bacteria (LAB) has attracted particular interest in the food industry. EPS can be considered as natural biothickeners as they are produced in situ by LAB and improve the rheological properties of fermented foods. Moreover, much research has been conducted on the beneficial effects of EPS produced by LAB on modulating the gut microbiome and promoting health. The EPS, which varies widely in composition and structure, may have diverse health effects, such as glycemic control, calcium and magnesium absorption, cholesterol-lowering, anticarcinogenic, immunomodulatory, and antioxidant effects. In this article, the latest advances on structure, biosynthesis, and physicochemical properties of LAB-derived EPS are described in detail. This is followed by a summary of up-to-date methods used to detect, characterize and elucidate the structure of EPS produced by LAB. In addition, current strategies on the use of LAB-produced EPS in food products have been discussed, focusing on beneficial applications in dairy products, gluten-free bakery products, and low-fat meat products, as they positively influence the consistency, stability, and quality of the final product. Highlighting is also placed on reports of health-promoting effects, with particular emphasis on prebiotic, immunomodulatory, antioxidant, cholesterol-lowering, anti-biofilm, antimicrobial, anticancer, and drug-delivery activities.
Efficacy of L-Arabinose in Lowering Glycemic and Insulinemic Responses: The Modifying Effect of Starch and Fat
Authors: Pol Korrie , Puhlmann Marie-Luise , Mars Monica
Published: January 2022

L-arabinose is a bio-active compound derived from the side-streams of plant food processing. L-arabinose lowers glycemic and insulinemic responses when added to simple water-based sugary liquids. However, the effect in more complex foods, including fat and starch, is inconsistent. This study assessed the effect of fat or starch in a sugary drink on the efficacy of L-arabinose. Twenty-three healthy volunteers (12 female/11 male; aged 24 ± 3 years; BMI 23 ± 3 kg/m2) participated in a randomised cross-over trial with six drinks: control: 50 g sucrose in water; fat: control + 22 g oil; starch: control + 50 g starch; and all three with and without the addition of 5 g L-arabinose. The addition of L-arabinose to the control drink lowered glucose and insulin peaks by 15% and 52%; for the fat drink by 8% and 45%; and for the starch drink by 7% and 29%. For all three drinks, adding L-arabinose increased glucagon-like peptide 1 (GLP-1) responses and lowered Glucose-dependent insulinotropic polypeptide (GIP) responses. Despite adding large quantities of starch and fat to sugary drinks, L-arabinose significantly lowered postprandial glycemic and insulinemic responses in healthy subjects. These findings suggest that L-arabinose can be functional in more complex foods; however, the factors affecting its efficacy in solid food matrices need to be studied in more detail.
A Tara Gum/Olive Mill Wastewaters Phytochemicals Conjugate as a New Ingredient for the Formulation of an Antioxidant-Enriched Pudding
Authors: Spizzirri Umile Gianfranco , Caputo Paolino , Oliviero Rossi Cesare , Crupi Pasquale , Muraglia Marilena , Rago Vittoria , Malivindi Rocco , Clodoveo Maria Lisa , Restuccia Donatella , Aiello Francesca
Published: January 2022

Olive mill wastewater, a high polyphenols agro-food by-product, was successfully exploited in an eco-friendly radical process to synthesize an antioxidant macromolecule, usefully engaged as a functional ingredient to prepare functional puddings. The chemical composition of lyophilized olive mill wastewaters (LOMW) was investigated by HPLC-MS/MS and 1H-NMR analyses, while antioxidant profile was in vitro evaluated by colorimetric assays. Oleuropein aglycone (5.8 μg mL−1) appeared as the main compound, although relevant amounts of an isomer of the 3-hydroxytyrosol glucoside (4.3 μg mL−1) and quinic acid (4.1 μg mL−1) were also detected. LOMW was able to greatly inhibit ABTS radical (IC50 equal to 0.019 mg mL−1), displaying, in the aqueous medium, an increase in its scavenger properties by almost one order of magnitude compared to the organic one. LOMW reactive species and tara gum chains were involved in an eco-friendly grafting reaction to synthesize a polymeric conjugate that was characterized by spectroscopic, calorimetric and toxicity studies. In vitro acute oral toxicity was tested against 3T3 fibroblasts and Caco-2 cells, confirming that the polymers do not have any effect on cell viability at the dietary use concentrations. Antioxidant properties of the polymeric conjugate were also evaluated, suggesting its employment as a thickening agent, in the preparation of pear puree-based pudding. High performance of consistency and relevant antioxidants features over time (28 days) were detected in the milk-based foodstuff, in comparison with its non-functional counterparts, confirming LOWM as an attractive source to achieve high performing functional foods.
Vegan Egg: A Future-Proof Food Ingredient?
Authors: Boukid Fatma , Gagaoua Mohammed
Published: January 2022

Vegan eggs are designed with the aim to provide a healthier and more sustainable alternative to regular eggs. The major drivers of this industry are the increasing prevalence of egg allergies, awareness towards environmental sustainability, and the shift to vegan diets. This study intends to discuss, for the first time, the vegan egg market, including their formulation, nutritional aspects, and some applications (i.e., mayonnaise and bakery products). Recreating the complete functionality of eggs using plant-based ingredients is very challenging due to the complexity of eggs. Current, but scarce, research in this field is focused on making mixtures of plant-based ingredients to fit specific food formulations. Nutritionally, providing vegan eggs with similar or higher nutritional value to that of eggs can be of relevance to attract health-conscious consumers. Claims such as clean labels, natural, vegan, animal-free, gluten-free, and/or cholesterol-free can further boost the position of vegan eggs in the market in the coming year. At present, this market is still in its infancy stages, and clear regulations of labeling, safety, and risk assessment are deemed mandatory to organize the sector, and protect consumers.
Optimization of Microwave Pre-Cooked Conditions for Gelatinization of Adzuki Bean
Authors: Zhang Jianyou , Xie Xuehua , Zhang Lyu , Hong Yiling , Zhang Gaopeng , Lyu Fei
Published: January 2022

Pre-cooked adzuki beans (Vigna angularis), which looks like dried adzuki bean, is easily cooked and preserved. This study aimed to optimize the microwave pre-cooked conditions on adzuki beans by applying the response surface methodology. The results showed that soaking time has a significant effect on the gelatinization degree of adzuki beans according to microwave time. The most suitable gelatinization and the sensory scores were obtained with a soaking time of 7.8 h, a microwave power of 830 W, and microwave time of 92 s. The pre-cooked treatment had no significant effect (p > 0.05) on the protein, free amino acid, fat and starch content of adzuki bean products. The results of SEM and polarized light microscopy showed that the surface and center of starch were damaged after microwave treatment. XRD showed that microwave pre-cooking did not change the crystal structure of starch and maintained the original order of type A structure while reducing the relative starch crystallinity. FT-IR showed that the pre-cooked treatment did not produce new structure in adzuki bean starch, but the ratio of 1047/1022 cm−1 was slightly decreased, indicating that the starch crystallization area decreased relative to the amorphous area and the relative crystallinity decreased. The results of FTIR were consistent with X-ray diffraction results. Therefore, microwaves improved the gelatinization of adzuki beans and made the pre-cooked adzuki beans more suitable.
Pigmented Potatoes: A Potential Panacea for Food and Nutrition Security and Health?
Authors: Bvenura Callistus , Witbooi Hildegard , Kambizi Learnmore
Published: January 2022

Although there are over 4000 potato cultivars in the world, only a few have been commercialized due to their marketability and shelf-life. Most noncommercialized cultivars are pigmented and found in remote regions of the world. White-fleshed potatoes are well known for their energy-enhancing complex carbohydrates; however, pigmented cultivars are potentially high in health-promoting polyphenolic compounds. Therefore, we reveal the comprehensive compositions of pigmented cultivars and associated potential health benefits, including their potential role in ameliorating hunger, food, and nutrition insecurity, and their prospects. The underutilization of such resources is a direct threat to plant-biodiversity and local traditions and cultures.
Divergence in the Relativistic Mean Field Formalism: A Case Study of the Ground State Properties of the Decay Chain of 214,216,218U Isotopes
Authors: Joshua Tolulope Majekodunmi , Jain Nishu , Kumar Raj , Anwar Khairul , Abdullah Nooraihan , Bhuyan Mrutunjaya
Published: January 2022

A new α-emitting 214U has been recently observed experimentally. This opens the window to theoretically investigate the ground-state properties of the lightest known even–even neutron deficient 214,216,218U isotopes and to examine α-particle clustering around the shell closure. The decay half-lives are calculated within the preformed cluster-decay model (PCM). To obtain the α-daughter interaction potential, the RMF densities are folded with the newly developed R3Y and the well-known M3Y NN potentials for comparison. The alpha preformation probability (Pα) is calculated from the analytic formula of Deng and Zhang. The WKB approximation is employed for the calculation of the transmission probability. The individual binding energies (BE) for the participating nuclei are estimated from the relativistic mean-field (RMF) formalism and those from the finite range droplet model (FRDM) as well as WS3 mass tables. In addition to Z=84, the so-called abnormal enhancement region, i.e., 84≤Z≤90 and N<126, is normalised by an appropriately fitted neck-parameter ΔR. On the other hand, the discrepancy sets in due to the shell effect at (and around) the proton magic number Z=82 and 84, and thus a higher scaling factor ranging from 10−8–10−5 is required. Additionally, in contrast with the experimental binding energy data, large deviations of about 5–10 MeV are evident in the RMF formalism despite the use of different parameter sets. An accurate prediction of α-decay half-lives requires a Q-value that is in proximity with the experimental data. In addition, other microscopic frameworks besides RMF could be more reliable for the mass region under study. α-particle clustering is largely influenced by the shell effect.