bluuebunny/crossref_metadata_2025 huggingface dataset:
Refractory Metal (Nb) Intermetallic Composites, High Entropy Alloys, Complex Concentrated Alloys and the Alloy Design Methodology NICE—Mise-en-scène † Patterns of Thought and Progress
Authors: Tsakiropoulos Panos
Published: February 2021

The paper reflects on the usefulness of the alloy design methodology NICE (Niobium Intermetallic Composite Elaboration) for the development of new Nb-containing metallic ultra-high-temperature materials (UHTMs), namely refractory metal (Nb) intermetallic composites (RM(Nb)ICs), refractory high entropy alloys (RHEAs) and refractory complex concentrated alloys (RCCAs), in which the same phases can be present, specifically bcc solid solution(s), M5Si3 silicide(s) and Laves phases. The reasons why a new alloy design methodology was sought and the foundations on which NICE was built are discussed. It is shown that the alloying behavior of RM(Nb)ICs, RHEAs and RCCAs can be described by the same parameters. The practicality of parameter maps inspired by NICE for describing/understanding the alloying behavior and properties of alloys and their phases is demonstrated. It is described how NICE helps the alloy developer to understand better the alloys s/he develops and what s/he can do and predict (calculate) with NICE. The paper expands on RM(Nb)ICs, RHEAs and RCCAs with B, Ge or Sn, the addition of which and the presence of A15 compounds is recommended in RHEAs and RCCAs to achieve a balance of properties.
Effect of Variation of SiC Reinforcement on Wear Behaviour of AZ91 Alloy Composites
Authors: Kumar Anil , Kumar Santosh , Mukhopadhyay Nilay Krishna , Yadav Anshul , Kumar Virendra , Winczek Jerzy
Published: February 2021

In this investigation, the extensive wear behaviour of materials was studied using SiC reinforced magnesium alloy composites fabricated through the stir casting process. The wear properties of AZ91 alloy composites with a small variation (i.e., 3%, 6%, 9% and 12%) of SiC particulates were evaluated by varying the normal load with sliding velocity and sliding distance. The worn surfaces were examined by scanning electron microscope to predict the different wear mechanisms on the pin while sliding on the hard disk in the dry sliding wear test condition. The microhardness of the SiC reinforced AZ91 composites was found to be more than the un-reinforced AZ91 alloy. Pins tested at load 19.62 N, and 2.6 m/s exhibited a series of short cracks nearly perpendicular to the sliding direction. At higher speed and load, the oxidation and delamination were observed to be fully converted into adhesion wear. Abrasion, oxidation, and delamination wear mechanisms were generally dominant in lower sliding velocity and lower load region, while adhesion and thermal softening/melting were dominant in higher sliding velocity and loads. The wear rate and coefficient of friction of the SiC reinforced composites were lower than that of the unreinforced alloy. This is due to the fact of higher hardness exhibited by the composites. The wear behaviour at the velocity of 1.39 m/s was dominated by oxidation and delamination wear, whereas at the velocity of 2.6 m/s the wear behaviour was dominated by abrasion and adhesion wear. It was also found that the plastic deformation and smearing occurred at higher load and sliding velocity.
Comprehensive Assessment of Distance Learning Modules by Fuzzy AHP-TOPSIS Method
Authors: Bekesiene Svajone , Vasiliauskas Aidas Vasilis , Hošková-Mayerová Šárka , Vasilienė-Vasiliauskienė Virgilija
Published: February 2021

This survey is focussed on distance learning studies, where there can be met a lot of technical obstacles, which creates complications in decision making. To get an ideal solution for these kinds of problems, the Fuzzy TOPSIS (Technique for Order Preference by Similarities to Ideal Solution) is one of the best solutions. Therefore, this paper presents the distance learning quality assessment surveys when the Fuzzy AHP (Analytic Hierarchy Process) and TOPSIS methods are used. Research results describe the application of the Fuzzy AHP—TOPSIS hybrid method. MCDM (Multi-Criteria Decision Making) programs with MATLAB (R2020b) mathematical package were written to calculate the evaluation results for three distance learning courses. In the practical implementation of the proposed distance learning module evaluation methodology, the experts’ evaluation method was applied. Thirty-four judges were chosen with specific knowledge and skills and with very different competencies to assess three alternatives by fourteen criteria. Following the experts’ evaluation, a statistical analysis method was used to process the data. After applying the complex evaluation, the comparative analysis method was used to summarize the obtained results. This work further provides useful guidelines for the development of an easily understandable hierarchy of criteria model that reflects the main goal of study quality assessment.
Fish Waste: From Problem to Valuable Resource
Authors: Coppola Daniela , Lauritano Chiara , Palma Esposito Fortunato , Riccio Gennaro , Rizzo Carmen , de Pascale Donatella
Published: February 2021

Following the growth of the global population and the subsequent rapid increase in urbanization and industrialization, the fisheries and aquaculture production has seen a massive increase driven mainly by the development of fishing technologies. Accordingly, a remarkable increase in the amount of fish waste has been produced around the world; it has been estimated that about two-thirds of the total amount of fish is discarded as waste, creating huge economic and environmental concerns. For this reason, the disposal and recycling of these wastes has become a key issue to be resolved. With the growing attention of the circular economy, the exploitation of underused or discarded marine material can represent a sustainable strategy for the realization of a circular bioeconomy, with the production of materials with high added value. In this study, we underline the enormous role that fish waste can have in the socio-economic sector. This review presents the different compounds with high commercial value obtained by fish byproducts, including collagen, enzymes, and bioactive peptides, and lists their possible applications in different fields.
Increasing Low-Temperature Toughness of 09Mn2Si Steel through Lamellar Structuring by Helical Rolling
Authors: Panin Sergey , Vlasov Ilya , Moiseenko Dmitry , Maksimov Pavel , Maruschak Pavlo , Yakovlev Alexander , Gomorova Julia , Mishin Ivan , Schmauder Siegfried
Published: February 2021

The aim of the paper was to investigate the helical rolling parameters (a number of passes) for the microstructural modification and the low-temperature impact toughness improvement of the 09Mn2Si High Strength Low-Alloyed (HSLA) steel. In order to achieve this purpose, work spent to crack initiation and propagation was analyzed and compared with patterns of fracture surfaces. The microstructure and impact toughness values were presented in the temperature range from +20 to –70°C. Also, the fracture mechanisms in individual regions on the fracture surfaces were discussed. In addition, a methodology for computer simulation of the process was developed and implemented within the framework of the excitable cellular automata method and its integration with the kinetic theory of fracture. Finally, a theoretical analysis of the effect of grain shapes and orientations on the strain response patterns of a certain meso-volume simulating the material after the helical rolling was carried out.
Functionalized Carbon Nanotube and MnO2 Nanoflower Hybrid as an Electrode Material for Supercapacitor Application
Authors: Mothkuri Sagar , Gupta Honey , Jain Pawan K. , Rao Tata Narsinga , Padmanabham Gade , Chakrabarti Supriya
Published: February 2021

Functionalized carbon nanotube (FCNT) and Manganese Oxide (MnO2) nanoflower hybrid material was synthesized using hydrothermal technique as a promising electrode material for supercapacitor applications. The morphological investigation revealed the formation of ‘nanoflower’ like structure of MnO2 connected with FCNT, thus paving an easy path for the conduction of electrons during the electrochemical mechanism. A significant improvement in capacitance properties was observed in the hybrid material, in which carbon nanotube acts as a conducting cylindrical path, while the major role of MnO2 was to store the charge, acting as an electrolyte reservoir leading to an overall improved electrochemical performance. The full cell electrochemical analysis of FCNT-MnO2 hybrid using 3 M potassium hydroxide (KOH) electrolyte indicated a specific capacitance of 359.53 F g−1, specific energy of 49.93 Wh kg−1 and maximum specific power of 898.84 W kg−1 at 5 mV s−1. The results show promise for the future of supercapacitor development based on hybrid electrode materials, where high specific energy can be achieved along with high specific power and long cycle life.
Staphylococcal Communities on Skin Are Associated with Atopic Dermatitis and Disease Severity
Authors: Edslev Sofie Marie , Olesen Caroline Meyer , Nørreslet Line Brok , Ingham Anna Cäcilia , Iversen Søren , Lilje Berit , Clausen Maja-Lisa , Jensen Jørgen Skov , Stegger Marc , Agner Tove , Andersen Paal Skytt
Published: February 2021

The skin microbiota of atopic dermatitis (AD) patients is characterized by increased Staphylococcus aureus colonization, which exacerbates disease symptoms and has been linked to reduced bacterial diversity. Skin bacterial communities in AD patients have mostly been described at family and genus levels, while species-level characterization has been limited. In this study, we investigated the role of the bacteria belonging to the Staphylococcus genus using targeted sequencing of the tuf gene with genus-specific primers. We compared staphylococcal communities on lesional and non-lesional skin of AD patients, as well as AD patients with healthy controls, and determined the absolute abundance of bacteria present at each site. We observed that the staphylococcal community, bacterial alpha diversity, and bacterial densities were similar on lesional and non-lesional skin, whereas AD severity was associated with significant changes in staphylococcal composition. Increased S. aureus, Staphylococcus capitis, and Staphylococcus lugdunensis abundances were correlated with increased severity. Conversely, Staphylococcus hominis abundance was negatively correlated with severity. Furthermore, S. hominis relative abundance was reduced on AD skin compared to healthy skin. In conclusion, various staphylococcal species appear to be important for skin health.
An Engineered Reporter Phage for the Fluorometric Detection of Escherichia coli in Ground Beef
Authors: Chen Anqi , Wang Danhui , Nugen Sam R. , Chen Juhong
Published: February 2021

Despite enhanced sanitation implementations, foodborne bacterial pathogens still remain a major threat to public health and generate high costs for the food industry. Reporter bacteriophage (phage) systems have been regarded as a powerful technology for diagnostic assays for their extraordinary specificity to target cells and cost-effectiveness. Our study introduced an enzyme-based fluorescent assay for detecting the presence of E. coli using the T7 phage engineered with the lacZ operon which encodes beta-galactosidase (β-gal). Both endogenous and overexpressed β-gal expression was monitored using a fluorescent-based method with 4-methylumbelliferyl β-d-galactopyranoside (MUG) as the substrate. The infection of E. coli with engineered phages resulted in a detection limit of 10 CFU/mL in ground beef juice after 7 h of incubation. In this study, we demonstrated that the overexpression of β-gal coupled with a fluorogenic substrate can provide a straightforward and sensitive approach to detect the potential biological contamination in food samples. The results also suggested that this system can be applied to detect E. coli strains isolated from environmental samples, indicating a broader range of bacterial detection.
In Silico Strategy for Targeting the mTOR Kinase at Rapamycin Binding Site by Small Molecules
Authors: Vittorio Serena , Gitto Rosaria , Adornato Ilenia , Russo Emilio , De Luca Laura
Published: February 2021

Computer aided drug-design methods proved to be powerful tools for the identification of new therapeutic agents. We employed a structure-based workflow to identify new inhibitors targeting mTOR kinase at rapamycin binding site. By combining molecular dynamics (MD) simulation and pharmacophore modelling, a simplified structure-based pharmacophore hypothesis was built starting from the FKBP12-rapamycin-FRB ternary complex retrieved from RCSB Protein Data Bank (PDB code 1FAP). Then, the obtained model was used as filter to screen the ZINC biogenic compounds library, containing molecules derived from natural sources or natural-inspired compounds. The resulting hits were clustered according to their similarity; moreover, compounds showing the highest pharmacophore fit-score were chosen from each cluster. The selected molecules were subjected to docking studies to clarify their putative binding mode. The binding free energy of the obtained complexes was calculated by MM/GBSA method and the hits characterized by the lowest ΔGbind values were identified as potential mTOR inhibitors. Furthermore, the stability of the resulting complexes was studied by means of MD simulation which revealed that the selected compounds were able to form a stable ternary complex with FKBP12 and FRB domain, thus underlining their potential ability to inhibit mTOR with a rapamycin-like mechanism.
The Formation of Methyl Ketones during Lipid Oxidation at Elevated Temperatures
Authors: Grebenteuch Sandra , Kanzler Clemens , Klaußnitzer Stefan , Kroh Lothar W. , Rohn Sascha
Published: February 2021

Lipid oxidation and the resulting volatile organic compounds are the main reasons for a loss of food quality. In addition to typical compounds, such as alkanes, aldehydes and alcohols, methyl ketones like heptan-2-one, are repeatedly described as aroma-active substances in various foods. However, it is not yet clear from which precursors methyl ketones are formed and what influence amino compounds have on the formation mechanism. In this study, the formation of methyl ketones in selected food-relevant fats and oils, as well as in model systems with linoleic acid or pure secondary degradation products (alka-2,4-dienals, alken-2-als, hexanal, and 2-butyloct-2-enal), has been investigated. Elevated temperatures were chosen for simulating processing conditions such as baking, frying, or deep-frying. Up to seven methyl ketones in milk fat, vegetable oils, and selected model systems have been determined using static headspace gas chromatography-mass spectrometry (GC-MS). This study showed that methyl ketones are tertiary lipid oxidation products, as they are derived from secondary degradation products such as deca-2,4-dienal and oct-2-enal. The study further showed that the position of the double bond in the precursor compound determines the chain length of the methyl ketone and that amino compounds promote the formation of methyl ketones to a different degree. These compounds influence the profile of the products formed. As food naturally contains lipids as well as amino compounds, the proposed pathways are relevant for the formation of aroma-active methyl ketones in food.
A Systematic Review of the Effects of Equol (Soy Metabolite) on Breast Cancer
Authors: Hod Rafidah , Maniam Sandra , Mohd Nor Nurul Huda
Published: February 2021

Equol is a soy isoflavone metabolite that can be produced by intestinal bacteria. It is lipophilic and resembles natural oestrogens with an affinity to oestrogen receptors. This review is focused on how equol affects breast cancer, as evidenced by in vivo and in vitro studies. Equol is considered chemoprotective in specific endocrine-related pathologies, such as breast cancer, prostate cancer, cardiovascular diseases, and menopausal symptoms. In humans, not everyone can produce equol from gut metabolism. It is postulated that equol producers benefit more than non-equol producers for all the endocrine-related effects. Equol exists in two enantiomers of R-equol and S-equol. Earlier studies, however, did not specify which enantiomer was being used. This review considers equol’s type and concentration variations, pathways affected, and its outcome in in vivo and in vitro studies.
Circulating Levels of Dephosphorylated-Uncarboxylated Matrix Gla Protein in Patients with Acute Coronary Syndrome
Authors: Bilalic Admira , Ticinovic Kurir Tina , Kumric Marko , Borovac Josip A. , Matetic Andrija , Supe-Domic Daniela , Bozic Josko
Published: February 2021

Vascular calcification contributes to the pathogenesis of coronary artery disease while matrix Gla protein (MGP) was recently identified as a potent inhibitor of vascular calcification. MGP fractions, such as dephosphorylated-uncarboxylated MGP (dp-ucMGP), lack post-translational modifications and are less efficient in vascular calcification inhibition. We sought to compare dp-ucMGP levels between patients with acute coronary syndrome (ACS), stratified by ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI) status. Physical examination and clinical data, along with plasma dp-ucMGP levels, were obtained from 90 consecutive ACS patients. We observed that levels of dp-ucMGP were significantly higher in patients with NSTEMI compared to STEMI patients (1063.4 ± 518.6 vs. 742.7 ± 166.6 pmol/L, p < 0.001). NSTEMI status and positive family history of cardiovascular diseases were only independent predictors of the highest tertile of dp-ucMGP levels. Among those with NSTEMI, patients at a high risk of in-hospital mortality (adjudicated by GRACE score) had significantly higher levels of dp-ucMGP compared to non-high-risk patients (1417.8 ± 956.8 vs. 984.6 ± 335.0 pmol/L, p = 0.030). Altogether, our findings suggest that higher dp-ucMGP levels likely reflect higher calcification burden in ACS patients and might aid in the identification of NSTEMI patients at increased risk of in-hospital mortality. Furthermore, observed dp-ucMGP levels might reflect differences in atherosclerotic plaque pathobiology between patients with STEMI and NSTEMI.
Effect of Dataset Size and Train/Test Split Ratios in QSAR/QSPR Multiclass Classification
Authors: Rácz Anita , Bajusz Dávid , Héberger Károly
Published: February 2021

Applied datasets can vary from a few hundred to thousands of samples in typical quantitative structure-activity/property (QSAR/QSPR) relationships and classification. However, the size of the datasets and the train/test split ratios can greatly affect the outcome of the models, and thus the classification performance itself. We compared several combinations of dataset sizes and split ratios with five different machine learning algorithms to find the differences or similarities and to select the best parameter settings in nonbinary (multiclass) classification. It is also known that the models are ranked differently according to the performance merit(s) used. Here, 25 performance parameters were calculated for each model, then factorial ANOVA was applied to compare the results. The results clearly show the differences not just between the applied machine learning algorithms but also between the dataset sizes and to a lesser extent the train/test split ratios. The XGBoost algorithm could outperform the others, even in multiclass modeling. The performance parameters reacted differently to the change of the sample set size; some of them were much more sensitive to this factor than the others. Moreover, significant differences could be detected between train/test split ratios as well, exerting a great effect on the test validation of our models.
Chemical Proprieties of Biopolymers (Chitin/Chitosan) and Their Synergic Effects with Endophytic Bacillus Species: Unlimited Applications in Agriculture
Authors: Rkhaila Amine , Chtouki Tarek , Erguig Hassane , El Haloui Noureddine , Ounine Khadija
Published: February 2021

Over the past decade, reckless usage of synthetic pesticides and fertilizers in agriculture has made the environment and human health progressively vulnerable. This setting leads to the pursuit of other environmentally friendly interventions. Amongst the suggested solutions, the use of chitin and chitosan came about, whether alone or in combination with endophytic bacterial strains. In the framework of this research, we reported an assortment of studies on the physico-chemical properties and potential applications in the agricultural field of two biopolymers extracted from shrimp shells (chitin and chitosan), in addition to their uses as biofertilizers and biostimulators in combination with bacterial strains of the genus Bacillus sp. (having biochemical and enzymatic properties).
Testing the Limits of a Portable NIR Spectrometer: Content Uniformity of Complex Powder Mixtures Followed by Calibration Transfer for In-Line Blend Monitoring
Authors: Casian Tibor , Gavan Alexandru , Iurian Sonia , Porfire Alina , Toma Valentin , Stiufiuc Rares , Tomuta Ioan
Published: February 2021

(1) Background: Portable NIR spectrometers gain more and more ground in the field of Process Analytical Technology due to the easy on-site flexibility and interfacing versatility. These advantages that originate from the instrument miniaturization, also come with a downside with respect to performance compared to benchtop devices. The objective of this work was to evaluate the performance of MicroNIR in a pharmaceutical powder blend application, having three active ingredients and 5 excipients. (2) Methods: Spectral data was recorded in reflectance mode using static and dynamic acquisition, on calibration set samples developed using an experimental design. (3) Results: The developed method accurately predicted the content uniformity of these complex mixtures, moreover it was validated in the entire calibration range using ±10% acceptance limits. With respect to at-line prediction, the method presented lower performance compared to a previously studied benchtop spectrometer. Regarding the in-line monitoring of the blending process, it was shown that the spectral variability-induced by dynamic acquisition could be efficiently managed using spectral pre-processing. (4) Conclusions: The in-line process monitoring resulted in accurate concentration profiles, highlighting differences in the mixing behaviour of the investigated ingredients. For the low dose component homogeneity was not reached due to an inefficient dispersive mixing.
Correction: Gobinath, P., et al. Grindstone Chemistry: Design, One-Pot Synthesis, and Promising Anticancer Activity of Spiro[acridine-9,2′-indoline]-1,3,8-trione Derivatives against the MCF-7 Cancer Cell Line. Molecules 2020, 25, 5862
Authors: Gobinath Perumal , Packialakshmi Ponnusamy , Daoud Ali , Alarifi Saud , Idhayadhulla Akbar , Surendrakumar Radhakrishnan
Published: February 2021

In the original article [...]
Tunable Electronic Properties of Lateral Monolayer Transition Metal Dichalcogenide Superlattice Nanoribbons
Authors: Wang Jinhua , Srivastava Gyaneshwar P.
Published: February 2021

The structural stability and structural and electronic properties of lateral monolayer transition metal chalcogenide superlattice zigzag and armchair nanoribbons have been studied by employing a first-principles method based on the density functional theory. The main focus is to study the effects of varying the width and periodicity of nanoribbon, varying cationic and anionic elements of superlattice parent compounds, biaxial strain, and nanoribbon edge passivation with different elements. The band gap opens up when the (MoS2)3/(WS2)3 and (MoS2)3/(MoTe2)3 armchair nanoribbons are passivated by H, S and O atoms. The H and O co-passivated (MoS2)3/(WS2)3 armchair nanoribbon exhibits higher energy band gap. The band gap with the edge S vacancy connecting to the W atom is much smaller than the S vacancy connecting to the Mo atom. Small band gaps are obtained for both edge and inside Mo vacancies. There is a clear difference in the band gap states between inside and edge Mo vacancies for symmetric nanoribbon structure, while there is only a slight difference for asymmetric structure. The electronic orbitals of atoms around Mo vacancy play an important role in determining the valence band maximum, conduction band minimum, and impurity level in the band gap.
Efficacy of Polyphenols in the Management of Dyslipidemia: A Focus on Clinical Studies
Authors: Feldman Francis , Koudoufio Mireille , Desjardins Yves , Spahis Schohraya , Delvin Edgard , Levy Emile
Published: February 2021

Polyphenols (PLPs), phytochemicals found in a wide range of plant-based foods, have gained extensive attention in view of their antioxidant, anti-inflammatory, immunomodulatory and several additional beneficial activities. The health-promoting effects noted in animal models of various non-communicable diseases explain the growing interest in these molecules. In particular, in vitro and animal studies reported an attenuation of lipid disorders in response to PLPs. However, despite promising preclinical investigations, the effectiveness of PLPs in human dyslipidemia (DLP) is less clear and necessitates revision of available literature. Therefore, the present review analyzes the role of PLPs in managing clinical DLP, notably by dissecting their potential in ameliorating lipid/lipoprotein metabolism and alleviating hyperlipidemia, both postprandially and in long-term interventions. To this end, PubMed was used for article search. The search terms included polyphenols, lipids, triglycerides, cholesterol, LDL-cholesterol and /or HDL-cholesterol. The critical examination of the trials published to date illustrates certain benefits on blood lipids along with co-morbidities in participant’s health status. However, inconsistent results document significant research gaps, potentially owing to study heterogeneity and lack of rigor in establishing PLP bioavailability during supplementation. This underlines the need for further efforts in order to elucidate and support a potential role of PLPs in fighting DLP.
Normal Versus Slowly Processed Pasta and Post-Prandial Glucose Homeostasis in Healthy Subjects: A Pilot Study
Authors: Mengozzi Alessandro , Biancalana Edoardo , Parolini Federico , Baldi Simona , Raggi Francesco , Solini Anna
Published: February 2021

Nutritional science is gaining increasing attention due to the implicit potential to prevent cardio-metabolic diseases. It is also becoming clear that food-making process might influence the metabolic response to the meal. We have conducted a proof-of-concept study to investigate whether slowly processed pasta might positively impact glucose homeostasis. A total of 14 healthy male volunteers underwent two different mixed-meal tests in a randomized order. One meal was composed of 100 g of normally processed pasta and the other 100 g of slowly processed pasta. Each meal was completed with 10 g of olive oil and 10 g of parmesan cheese. Glucose, insulin, and incretin post-prandial responses were assessed at 15, 30, 60, 90, 120, 150, and 180 min. Glucose tolerance, insulin, and incretin response were unaffected by the two different pasta types. However, a slight difference was evident in the shape of the curve of post-prandial insulin (i.e., mildly delayed with the slowly processed pasta). Despite the common belief of a different impact of normally processed and slowly processed pasta on glucose metabolism, they show a superimposable post-prandial metabolic response after a single meal in male healthy individuals. Further studies are required to confirm these results also in chronic, real-life settings and then to translate them to metabolically impaired individuals.
The Effect of Curcumin Supplementation on Anthropometric Measures among Overweight or Obese Adults
Authors: Alsharif Farah J. , Almuhtadi Yara A.
Published: February 2021

Over the past decades, the worldwide prevalence of obesity has dramatically increased, thus posing a serious public health threat. Obesity is associated with the development of comorbid conditions and psychological disorders. Several lifestyle interventions have been proposed to tackle obesity; however, long-term maintenance of these interventions often proves challenging. In addition, among the different types of diets there is still a debate about the optimal macronutrient composition that will achieve the best results in weight loss. Recently, several commonly used spices such as pepper, ginger, and curcumin have been shown to play a beneficial role in obesity management. Therefore, exploring the effects of certain herbs or dietary spices on obesity may be promising. Among these spices, curcumin, which is the primary component of the spice turmeric, has gained great interest for its multiple health benefits. Several randomized controlled trials have investigated the potential favorable effects of curcumin supplementation on anthropometric measures. The aim of this review is to evaluate the effect of curcumin supplementation on the anthropometric indices among overweight or obese adults.
PPO-Inhibiting Herbicides and Structurally Relevant Schiff Bases: Evaluation of Inhibitory Activities against Human Protoporphyrinogen Oxidase
Authors: Jakubek Milan , Masařík Michal , Bříza Tomáš , Kaplánek Robert , Veselá Kateřina , Abramenko Nikita , Martásek Pavel
Published: February 2021

The study of human protoporphyrinogen oxidase (hPPO) inhibition can contribute significantly to a better understanding of some pathogeneses (e.g., porphyria, herbicide exposure) and the development of anticancer agents. Therefore, we prepared new potential inhibitors with Schiff base structural motifs (2-hydroxybenzaldehyde-based Schiff bases 9–13 and chromanone derivatives 17–19) as structurally relevant to PPO herbicides. The inhibitory activities (represented by the half maximal inhibitory concentration (IC50) values) and enzymatic interactions (represented by the hPPO melting temperatures) of these synthetic compounds and commercial PPO herbicides used against hPPO were studied by a protoporphyrin IX fluorescence assay. In the case of PPO herbicides, significant hPPO inhibition and changes in melting temperature were observed for oxyfluorten, oxadiazon, lactofen, butafenacil, saflufenacil, oxadiargyl, chlornitrofen, and especially fomesafen. Nevertheless, the prepared compounds did not display significant inhibitory activity or changes in the hPPO melting temperature. However, a designed model of hPPO inhibitors based on the determined IC50 values and a docking study (by using AutoDock) found important parts of the herbicide structural motif for hPPO inhibition. This model could be used to better predict PPO herbicidal toxicity and improve the design of synthetic inhibitors.
Effect of Choline-Based Deep Eutectic Solvent Pretreatment on the Structure of Cellulose and Lignin in Bagasse
Authors: Li Cuicui , Huang Chongxing , Zhao Yuan , Zheng Chaojian , Su Hongxia , Zhang Lanyu , Luo Wanru , Zhao Hui , Wang Shuangfei , Huang Li-Jie
Published: February 2021

Deep eutectic solvents (DESs) is a newly developed green solvent with low cost, easy preparation and regeneration. Because of its excellent solubility and swelling effect in lignocellulose, it has received widespread attention and recognition. In this study, choline-based deep eutectic solvents (DESs)—choline chloride-urea (CC-U), choline chloride-ethylene glycol (CC-EG), choline chloride-glycerol (CC-G), choline chloride-lactic acid (CC-LA), and choline chloride-oxalic acid (CC-OA)—were used to extract and separate bagasse. The effects of hydrogen bond donors on lignin separation and the fiber and lignin structure were investigated. All five DESs could dissolve lignin from bagasse; acidic DESs exhibited higher solubility than basic DESs. CC-OA effectively separated lignin and hemicellulose. CC-LA showed weaker lignin separation ability than CC-OA. CC-G, CC-EG, and CC-U were more inclined to selectively separate lignin than hemicellulose. The crystalline cellulose II structure was retained after DES pretreatment. Acidic DESs effectively improved the crystallinity of bagasse fiber; the crystallinities for CC-OA and CC-LA pretreatment were 62.26% and 61.65%, respectively. The lignin dissolved in DES was mainly syringyl lignin. The lignin dissolved in CC-U, CC-LA, and CC-OA contained a small amount of guaiacyl lignin.
Evaluating Warfare Myths about Science and Christianity and How These Myths Promote Scientism
Authors: Keas Michael N.
Published: February 2021

Many people assume that there has been ceaseless conflict between science and Christianity. I argue that the real conflict has been between scientism and religion. Scientism is the view that only the sciences generate knowledge or rational belief. Scientism, as typically articulated, entails the opinion that reliable belief about divinity (theological realism) is impossible. I debunk four historic science–Christianity conflict myths and show how they have promoted scientism. These four science–religion myths function as part of a larger warfare narrative about science and Christianity. This misleading warfare thesis often comes packaged with an alternative anti-theistic “myth” in the anthropological sense—in this case, a worldview-shaping narrative that awakens the imagination to interpret the world in scientistic and non-theistic ways. I call this the scientistic warfare myth and explore its major flaws.
Web AR Solution for UAV Pilot Training and Usability Testing
Authors: Ribeiro Roberto , Ramos João , Safadinho David , Reis Arsénio , Rabadão Carlos , Barroso João , Pereira António
Published: February 2021

Data and services are available anywhere at any time thanks to the Internet and mobile devices. Nowadays, there are new ways of representing data through trendy technologies such as augmented reality (AR), which extends our perception of reality through the addition of a virtual layer on top of real-time images. The great potential of unmanned aerial vehicles (UAVs) for carrying out routine and professional tasks has encouraged their use in the creation of several services, such as package delivery or industrial maintenance. Unfortunately, drone piloting is difficult to learn and requires specific training. Since regular training is performed with virtual simulations, we decided to propose a multiplatform cloud-hosted solution based in Web AR for drone training and usability testing. This solution defines a configurable trajectory through virtual elements represented over barcode markers placed on a real environment. The main goal is to provide an inclusive and accessible training solution which could be used by anyone who wants to learn how to pilot or test research related to UAV control. For this paper, we reviewed drones, AR, and human–drone interaction (HDI) to propose an architecture and implement a prototype, which was built using a Raspberry Pi 3, a camera, and barcode markers. The validation was conducted using several test scenarios. The results show that a real-time AR experience for drone pilot training and usability testing is achievable through web technologies. Some of the advantages of this approach, compared to traditional methods, are its high availability by using the web and other ubiquitous devices; the minimization of technophobia related to crashes; and the development of cost-effective alternatives to train pilots and make the testing phase easier for drone researchers and developers through trendy technologies.
Comparison and Evaluation of Integrity Algorithms for Vehicle Dynamic State Estimation in Different Scenarios for an Application in Automated Driving
Authors: Gottschalg Grischa , Leinen Stefan
Published: February 2021

High-integrity information about the vehicle’s dynamic state, including position and heading (yaw angle), is required in order to implement automated driving functions. In this work, a comparison of three integrity algorithms for the vehicle dynamic state estimation of a research vehicle for an application in automated driving is presented. Requirements for this application are derived from the literature. All implemented integrity algorithms output a protection level for the position and heading solution. In the comparison, four measurement data sets obtained for the vehicle dynamic state estimation, which is based on a Global Navigation Satellite Signal receiver, inertial measurement units and odometry information (wheel speeds and steering angles), are used. The data sets represent four driving scenarios with different environmental conditions, especially regarding the satellite signal reception. All in all, the Kalman Integrated Protection Level demonstrated the best performance out of the three implemented integrity algorithms. Its protection level bounds the position error within the specified integrity risk in all four chosen scenarios. For the heading error, this also holds true, with a slight exception in the very challenging urban scenario.
An Investigation of Silica Aerogel to Reduce Acoustic Crosstalk in CMUT Arrays
Authors: Yashvanth Varshitha , Chowdhury Sazzadur
Published: February 2021

This paper presents a novel technique to reduce acoustic crosstalk in capacitive micromachined ultrasonic transducer (CMUT) arrays. The technique involves fabricating a thin layer of diisocyanate enhanced silica aerogel on the top surface of a CMUT array. The silica aerogel layer introduces a highly nanoporous permeable layer to reduce the intensity of the Scholte wave at the CMUT-fluid interface. 3D finite element analysis (FEA) simulation in COMSOL shows that the developed technique can provide a 31.5% improvement in crosstalk reduction for the first neighboring element in a 7.5 MHz CMUT array. The average improvement of crosstalk level over the −6 dB fractional bandwidth was 22.1%, which is approximately 5 dB lower than that without an aerogel layer. The results are in excellent agreement with published experimental results to validate the efficacy of the new technique.
Sequential Sampling and Estimation of Approximately Bandlimited Graph Signals
Authors: Lin Sijie , Xu Ke , Feng Hui , Hu Bo
Published: February 2021

Graph signal sampling has been widely studied in recent years, but the accurate signal models required by most of the existing sampling methods are usually unavailable prior to any observations made in a practical environment. In this paper, a sequential sampling and estimation algorithm is proposed for approximately bandlimited graph signals, in the absence of prior knowledge concerning signal properties. We approach the problem from a Bayesian perspective in which we formulate the signal prior by a multivariate Gaussian distribution with unknown hyperparameters. To overcome the interconnected problems associated with the parameter estimation, in the proposed algorithm, hyperparameter estimation and sample selection are performed in an alternating way. At each step, the unknown hyperparameters are updated by an expectation maximization procedure based on historical observations, and then the next node in the sampling operation is chosen by uncertainty sampling with the latest hyperparameters. We prove that under some specific conditions, signal estimation in the proposed algorithm is consistent. Subsequent validation of the approach through simulations shows that the proposed procedure yields performances which are significantly better than existing state-of-the-art approaches notwithstanding the additional attribute of robustness in the presence of a broad range of signal attributes.
Grasp to See—Object Classification Using Flexion Glove with Support Vector Machine
Authors: Yu Shun-Hsin , Chang Jen-Shuo , Tsai Chia-Hung Dylan
Published: February 2021

This paper proposes an object classification method using a flexion glove and machine learning. The classification is performed based on the information obtained from a single grasp on a target object. The flexion glove is developed with five flex sensors mounted on five finger sleeves, and is used for measuring the flexion of individual fingers while grasping an object. Flexion signals are divided into three phases, and they are the phases of picking, holding and releasing, respectively. Grasping features are extracted from the phase of holding for training the support vector machine. Two sets of objects are prepared for the classification test. One is printed-object set and the other is daily-life object set. The printed-object set is for investigating the patterns of grasping with specified shape and size, while the daily-life object set includes nine objects randomly chosen from daily life for demonstrating that the proposed method can be used to identify a wide range of objects. According to the results, the accuracy of the classifications are achieved 95.56% and 88.89% for the sets of printed objects and daily-life objects, respectively. A flexion glove which can perform object classification is successfully developed in this work and is aimed at potential grasp-to-see applications, such as visual impairment aid and recognition in dark space.
Large-Scale Water Quality Prediction Using Federated Sensing and Learning: A Case Study with Real-World Sensing Big-Data
Authors: Park Soohyun , Jung Soyi , Lee Haemin , Kim Joongheon , Kim Jae-Hyun
Published: February 2021

Green tide, which is a serious water pollution problem, is caused by the complex relationships of various factors, such as flow rate, several water quality indicators, and weather. Because the existing methods are not suitable for identifying these relationships and making accurate predictions, a new system and algorithm is required to predict the green tide phenomenon and also minimize the related damage before the green tide occurs. For this purpose, we consider a new network model using smart sensor-based federated learning which is able to use distributed observation data with geologically separated local models. Moreover, we design an optimal scheduler which is beneficial to use real-time big data arrivals to make the overall network system efficient. The proposed scheduling algorithm is effective in terms of (1) data usage and (2) the performance of green tide occurrence prediction models. The advantages of the proposed algorithm is verified via data-intensive experiments with real water quality big-data.
A Runway Safety System Based on Vertically Oriented Stereovision
Authors: Gradolewski Dawid , Dziak Damian , Kaniecki Damian , Jaworski Adam , Skakuj Michal , Kulesza Wlodek J.
Published: February 2021

In 2020, over 10,000 bird strikes were reported in the USA, with average repair costs exceeding $200 million annually, rising to $1.2 billion worldwide. These collisions of avifauna with airplanes pose a significant threat to human safety and wildlife. This article presents a system dedicated to monitoring the space over an airport and is used to localize and identify moving objects. The solution is a stereovision based real-time bird protection system, which uses IoT and distributed computing concepts together with advanced HMI to provide the setup’s flexibility and usability. To create a high degree of customization, a modified stereovision system with freely oriented optical axes is proposed. To provide a market tailored solution affordable for small and medium size airports, a user-driven design methodology is used. The mathematical model is implemented and optimized in MATLAB. The implemented system prototype is verified in a real environment. The quantitative validation of the system performance is carried out using fixed-wing drones with GPS recorders. The results obtained prove the system’s high efficiency for detection and size classification in real-time, as well as a high degree of localization certainty.
Validation of Player and Ball Tracking with a Local Positioning System
Authors: Blauberger Patrick , Marzilger Robert , Lames Martin
Published: February 2021

The aim of this study was the validation of player and ball position measurements of Kinexon’s local positioning system (LPS) in handball and football. Eight athletes conducted a sport-specific course (SSC) and small sided football games (SSG), simultaneously tracked by the LPS and an infrared camera-based motion capture system as reference system. Furthermore, football shots and handball throws were performed to evaluate ball tracking. The position root mean square error (RMSE) for player tracking was 9 cm for SSCs, the instantaneous peak speed showed a percentage deviation from the reference system of 0.7–1.7% for different exercises. The RMSE for SSGs was 8 cm. Covered distance was overestimated by 0.6% in SSCs and 1.0% in SSGs. The 2D RMSE of ball tracking was 15 cm in SSGs, 3D position errors of shot and throw impact locations were 17 cm and 21 cm. The methodology for the validation of a system’s accuracy in sports tracking requires extensive attention, especially in settings covering both, player and ball measurements. Most tracking errors for player tracking were smaller or in line with errors found for comparable systems in the literature. Ball tracking showed a larger error than player tracking. Here, the influence of the positioning of the sensor must be further reviewed. In total, the accuracy of Kinexon’s LPS has proven to represent the current state of the art for player and ball position detection in team sports.
Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing
Authors: Shahbazi Zeinab , Byun Yung-Cheol
Published: February 2021

Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach.