bluuebunny/crossref_metadata_2025 huggingface dataset:
Phenotypic and Nodule Microbial Diversity among Crimson Clover (Trifolium incarnatum L.) Accessions
Authors: Moore Virginia , Davis Brian , Poskaitis Megan , Maul Jude E. , Kissing Kucek Lisa , Mirsky Steven
Published: September 2020

Crimson clover (Trifolium incarnatum L.) is the most common legume cover crop in the United States. Previous research found limited genetic variation for crimson clover within the National Plant Germplasm System (NPGS) collection. The aim of this study was to assess the phenotypic and nodule microbial diversity within the NPGS crimson clover collection, focusing on traits important for cover crop performance. Experiments were conducted at the Beltsville Agricultural Research Center (Maryland, USA) across three growing seasons (2012–2013, 2013–2014, 2014–2015) to evaluate 37 crimson clover accessions for six phenotypic traits: fall emergence, winter survival, flowering time, biomass per plant, nitrogen (N) content in aboveground biomass, and proportion of plant N from biological nitrogen fixation (BNF). Accession effect was significant across all six traits. Fall emergence of plant introductions (PIs) ranged from 16.0% to 70.5%, winter survival ranged from 52.8% to 82.0%, and growing degree days (GDD) to 25% maturity ranged from 1470 GDD to 1910 GDD. Biomass per plant ranged from 1.52 to 6.51 g, N content ranged from 1.87% to 2.24%, and proportion of plant N from BNF ranged from 50.2% to 85.6%. Accessions showed particularly clear differences for fall emergence and flowering time, indicating greater diversity and potential for selection in cover crop breeding programs. Fall emergence and winter survival were positively correlated, and both were negatively correlated with biomass per plant and plant N from BNF. A few promising lines performed well across multiple key traits, and are of particular interest as parents in future breeding efforts, including PIs 369045, 418900, 561943, 561944, and 655006. In 2014–2015, accessions were also assessed for nodule microbiome diversity, and 11 genera were identified across the sampled nodules. There was large variation among accessions in terms of species diversity, but this diversity was not associated with observed plant traits, and the functional implications of nodule microbiome diversity remain unclear.
Rootstock Effects on Yield and Some Consumer Important Fruit Quality Parameters of Eggplant cv. ‘Madonna’ under Protected Cultivation
Authors: Mozafarian Maryam , Ismail Nazatul Syaima Binti , Kappel Noémi
Published: September 2020

This study aimed to investigate the effect of different rootstocks on the yield and quality of eggplant cv. ‘Madonna’ in soilless pot culture in an unheated polyethylene greenhouse. The eggplant was grafted onto several rootstocks, including tomato rootstocks Optifort (O) and Emperador (E), and four Solanum rootstocks; Solanum grandiflorum × Solanum melongena (SH), Solanum torvum (ST), Solanum melongena × Solanum integrifolium (SI), and Solanum integrifolium (A) compared with self-grafted (SG) and self-rooted (SR) as control. The results showed that the total marketable yield significantly increased by grafting onto ST (3.94 kg/plant), SH (3.36 kg/plant), and A (3.34 kg/plant) relative to SR (1.65 kg/plant). The chromatics characters of skin and pulp are slightly influenced by rootstocks. Our findings confirmed that grafting eggplant decreased firmness (except SH) of the flesh. Fruit harvested from the Optifort/Madonna combination had the rounded shape, lowest firmness, and Brix value, while the lowest oxidation potential was observed in this combination. The highest seed number was observed in SH/Madonna and SI/Madonna combinations. During the sensory evaluation, the lightest fruit flesh was found in SR, ST, and O, and the sweetest taste was observed in fruits harvested from ST rootstock.
Genome-Wide Association Study (GWAS) Analysis of Camelina Seedling Germination under Salt Stress Condition
Authors: Luo Zinan , Szczepanek Aaron , Abdel-Haleem Hussein
Published: September 2020

Camelina sativa is an important renewable oilseed crop for biofuel and feedstock that can relieve the reliance on petroleum-derived oils and reduce greenhouse gases and waste solids resulting from petroleum-derived oils consumption. C. sativa has recently seen revived attention due to its high oil content, high omega-3 unsaturated fatty acids, short life cycle, broader regional adaptation, and low-input agronomic requirements. However, abiotic stress such as salinity stress has imposed threatens on plant photosynthesis and growth by reducing water availability or osmotic stress, ion (Na+ and Cl−) toxicity, nutritional disorders and oxidative stress yield. There still remains much to know for the molecular mechanisms underlying these effects. In this study, a preliminary study applying 10 C. sativa cultivars to be treated under a gradient NaCl concentrations ranging from 0–250 mM and found that 100 mM was the optimal NaCl concentration to effectively differentiate phenotypic performance among different genotypes. Then, a spring panel consisting of 211 C. sativa accessions were germinated under 100 mM NaCl concentration. Six seedling germination traits, including germination rate at two stages (5-day and 9-day seedling stages), germination index, dry and fresh weight, and dry/fresh ratio, were measured. Significant correlations were found between the germination rate at two stages as well as plant biomass traits. Combining the phenotypic data and previously obtained genotypic data, a total of 17 significant trait-associated single nucleotide polymorphisms (SNPs) for the germination rate at the two stages and dry weight were identified from genome-wide association analysis (GWAS). These SNPs are located on putative candidate genes controlling plant root development by synergistically mediating phosphate metabolism, signal transduction and cell membrane activities. These identified SNPs could provide a foundation for future molecular breeding efforts aimed at improved salt tolerance in C. sativa.
The First Detection of Kudoa hexapunctata in Farmed Pacific Bluefin Tuna in South Korea, Thunnus orientalis (Temminck and Schlegel, 1844)
Authors: Kang Gyoungsik , Choi Kwang-Min , Cho Dong-Hee , Joo Min-Soo , Heo Min-Jin , Woo Won-Sik , Park Chan-Il
Published: September 2020

The consumption of fish and shellfish worldwide is steadily increasing, and tuna is a particularly valuable fish species. However, infection caused by Kudoa spp. is causing problems in many fish including the Pacific bluefin tuna (Thunnus orientalis), and there is much controversy about the association of these infections with foodborne disease. In this study, using haematological and histological analyses of the blood and internal organs (liver, spleen, kidney, heart, stomach, intestine, gill, and muscle) of Pacific bluefin tuna cultured in South Korea, infection with Myxosporea was first identified, and molecular biological analysis was conducted. In this study, Kudoa hexapunctata was finally identified. The Pacific bluefin tunas analysed in this study did not show any gross pathology lesions, such as visible cysts and/or myoliquefaction, of infection with this species. The histological analytical results can provide guidelines for the identification of K. hexapunctata. In the case of K. hexapunctata-induced infection, unlike other countries, such as Japan, there have been no reports in South Korea, and this study is the first to detect K. hexapunctata infection in Pacific bluefin tuna cultured in South Korea. The correlation between K. hexapunctata and food poisoning is not yet clear, however, it is thought that continuous observation of its infection is necessary.
Metabolic Profiling of Plasma in Different Calving Body Condition Score Cows Using an Untargeted Liquid Chromatography-Mass Spectrometry Metabolomics Approach
Authors: Wang Jian , Zhang Chuang , Zhao Qingyao , Li Congcong , Jin Shuang , Gu Xianhong
Published: September 2020

This study was undertaken to identify metabolite differences in plasma of dairy cows with a normal or high calving body condition score (CBCS), using untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics. Sixteen multiparous dairy cows were assigned to one of two groups based on CBCS (0 to 5 scale): Normal group (NBCS, 3.25 ≤ BCS ≤ 3.5, n = 8), and high BCS group (HBCS, BCS ≥ 4, n = 8). Plasma samples were collected for metabolomics analysis and evaluation of biomarkers of lipid metabolism (nonesterified fatty acid (NEFA) and β-hydroxybutyrate (BHB)), and cytokines (leptin, adiponectin, tumor necrosis factor–α (TNF-α) and interleukin 6 (IL-6)). A total of 23 differential metabolites were identified, and functional analyses were performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Among these metabolites, the concentrations of six lysophosphatidylcholines and one phosphatidylethanolamine, were lower in the HBCS group than in the NBCS group (p < 0.01). Furthermore, these metabolites were involved in these four pathways, among others: glycerophospholipid metabolism, retrograde endocannabinoid signaling, autophagy, and glycosylphosphatidylinositol (GPI)-anchor biosynthesis (p < 0.05). In addition, plasma concentrations of leptin (p = 0.06) and TNF-α (p = 0.08) tended to be greater while adiponectin (p = 0.09) lower in HBCS cows than in NBCS cows. The concentrations of NEFA, BHB, or IL-6 did not differ between NBCS and HBCS groups. More importantly, based on the results of the Spearman’s correlation analysis, the seven important metabolites were negatively correlated with indices of lipid metabolisms, proinflammatory cytokines, and leptin, but positively correlated with adiponectin. These results demonstrate that CBCS has a measurable impact on the plasma metabolic profile, even when NEFA and BHB are not different. In addition, the identified differential metabolites were significantly correlated to lipid metabolism and inflammation in the over-conditioned fresh cows, which are expected to render a metabolic basis for the diseases associated with over-conditioned dry cows.
Broad-Spectrum Antimicrobial Activity and Improved Stability of a D-Amino Acid Enantiomer of DMPC-10A, the Designed Derivative of Dermaseptin Truncates
Authors: Zai Yu , Ying Yuan , Ye Zhuming , Zhou Mei , Ma Chengbang , Shi Zhanzhong , Chen Xiaoling , Xi Xinping , Chen Tianbao , Wang Lei
Published: September 2020

DMPC-10A (ALWKKLLKK-Cha-NH2) is a 10-mer peptide derivative from the N-terminal domain of Dermaseptin-PC which has shown broad-spectrum antimicrobial activity as well as a considerable hemolytic effect. In order to reduce hemolytic activity and improve stability to endogenous enzymes, a D-amino acid enantiomer (DMPC-10B) was designed by substituting all L-Lys and L-Leu with their respective D-form amino acid residues, while the Ala1 and Trp3 remained unchanged. The D-amino acid enantiomer exhibited similar antimicrobial potency to the parent peptide but exerted lower cytotoxicity and hemolytic activity. Meanwhile, DMPC-10B exhibited remarkable resistance to hydrolysis by trypsin and chymotrypsin. In addition to these advantages, DMPC-10B exhibited an outstanding antibacterial effect against Methicillin-resistant Staphylococcus aureus (MRSA) and Klebsiella pneumoniae using the Galleria mellonella larva model and displayed synergistic activities with gentamicin against carbapenem-resistant K. pneumoniae strains. This indicates that DMPC-10B would be a promising alternative for treating antibiotic-resistant pathogens.
Treatment of Bloodstream Infections Due to Gram-Negative Bacteria with Difficult-to-Treat Resistance
Authors: Bassetti Matteo , Vena Antonio , Sepulcri Chiara , Giacobbe Daniele Roberto , Peghin Maddalena
Published: September 2020

The rising incidence of bloodstream infections (BSI) due to Gram-negative bacteria (GNB) with difficult-to-treat resistance (DTR) has been recognized as a global emergency. The aim of this review is to provide a comprehensive assessment of the mechanisms of antibiotic resistance, epidemiology and treatment options for BSI caused by GNB with DTR, namely extended-spectrum Beta-lactamase-producing Enterobacteriales; carbapenem-resistant Enterobacteriales; DTR Pseudomonas aeruginosa; and DTR Acinetobacter baumannii.
Comparison of Three Endodontic Irrigant Regimens against Dual-Species Interkingdom Biofilms: Considerations for Maintaining the Status Quo
Authors: Alshanta Om Alkhir , Alqahtani Saeed , Shaban Suror , Albashaireh Khawlah , McLean William , Ramage Gordon
Published: September 2020

Endodontic infections are often interkingdom biofilms, though current clinical management rarely considers this phenomenon. This study aimed to evaluate new and standard endodontic antimicrobial regimens against simple and complex Candida albicans and Enterococcus faecalis mono- and dual-species biofilms. C. albicans and E. faecalis mono- and dual-species biofilms were grown upon Thermanox™ coverslips and treated for 5 min with 3% NaOCl, 3% NaOCl followed by 17% EDTA, or 9% HEDP dissolved in 3% NaOCl. The number of cells remaining immediately after treatment at 0 h and after 72 h of regrowth were assessed using real-time quantitative PCR. All three treatment arms showed a similar positive antimicrobial effect on C. albicans and E. faecalis in both mono- and dual-species biofilms following initial treatment, resulting in ≥98% reduction in colony forming equivalent (CFE). Regardless of species or biofilm type (mono- or dual- species), the antimicrobial effect of NaOCl:HEDP mixture was comparable to that of NaOCl alone, with both showing significant regrowth after 72 h, whereas sequential treatment with NaOCl and EDTA consistently prevented significant regrowth. Our data suggest that sequential irrigation with NaOCl and EDTA remains the antimicrobial strategy of choice as it significantly reduces biofilm persistence and regrowth in our experimental dual-species biofilm conditions.
Modulating Laying Hens Productivity and Immune Performance in Response to Oxidative Stress Induced by E. coli Challenge Using Dietary Propolis Supplementation
Authors: Abbas Ahmed O. , Alaqil Abdulaziz A. , El-Beltagi Hossam S. , Abd El-Atty Hanaa K. , Kamel Nancy N.
Published: September 2020

Propolis (PR) is a resin product of bee colonies that has rich bioactive antioxidant and bactericidal compounds. Endotoxin, a byproduct of bacterial growth, is reported to cause progressive induction of endogenous oxidative stress and has negative impacts on individual health and wellbeing. Hereby, we investigated the ability of PR to alleviate the oxidative stress and immunosuppression imposed by avian pathogenic Escherichia coli using laying hen as a based model. In this study, PR was dietary supplemented to hens for 4 weeks at a concentration of 0.1%. At the beginning of the 4th week of the experiment, hens from control and PR treatment were injected with E. coli (O157:H7; 107 colonies/hen) or saline. The results showed significant (p < 0.05) negative impact of E. coli challenge on antioxidant status, immune response and productive performance. PR supplementation reduced (p < 0.05) inflammation markers levels (tumor necrosis factor α (TNFα) and interleukin 1β (IL-1β)) and plasma corticosterone concentration. The antioxidant status was ameliorated with dietary PR supplementation to challenged hens, showing significant (p < 0.05) reduction in malondialdehyde (MDA) levels and increasing total antioxidant capacity (TAC) concentrations. Cell mediated, as well as, humeral immune response improved significantly (p < 0.05) with dietary PR verified by the enhancement of T- and B-lymphocyte proliferation and the positive respond to phytohemagglutinin (PHA). Leucocyte cells viability increased significantly and the apoptotic factor forkhead box O3 (Foxo3) was reduced with PR supplementation. The current study revealed that dietary PR supplementation can effectively be used as an organic feed additive to overcome the endogenous oxidative stress induced by endotoxins challenge.
The Role of Bilirubin and the Other “Yellow Players” in Neurodegenerative Diseases
Authors: Jayanti Sri , Vítek Libor , Tiribelli Claudio , Gazzin Silvia
Published: September 2020

Bilirubin is a yellow endogenous derivate of the heme catabolism. Since the 1980s, it has been recognized as one of the most potent antioxidants in nature, able to counteract 10,000× higher intracellular concentrations of H2O2. In the recent years, not only bilirubin, but also its precursor biliverdin, and the enzymes involved in their productions (namely heme oxygenase and biliverdin reductase; altogether the “yellow players”—YPs) have been recognized playing a protective role in diseases characterized by a chronic prooxidant status. Based on that, there is an ongoing effort in inducing their activity as a therapeutic option. Nevertheless, the understanding of their specific contributions to pathological conditions of the central nervous system (CNS) and their role in these diseases are limited. In this review, we will focus on the most recent evidence linking the role of the YPs specifically to neurodegenerative and neurological conditions. Both the protective, as well as potentially worsening effects of the YP’s activity will be discussed.
Oxidative Stress, Neuroinflammation and Mitochondria in the Pathophysiology of Amyotrophic Lateral Sclerosis
Authors: Obrador Elena , Salvador Rosario , López-Blanch Rafael , Jihad-Jebbar Ali , Vallés Soraya L. , Estrela José M.
Published: September 2020

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron (MN) disease. Its primary cause remains elusive, although a combination of different causal factors cannot be ruled out. There is no cure, and prognosis is poor. Most patients with ALS die due to disease-related complications, such as respiratory failure, within three years of diagnosis. While the underlying mechanisms are unclear, different cell types (microglia, astrocytes, macrophages and T cell subsets) appear to play key roles in the pathophysiology of the disease. Neuroinflammation and oxidative stress pave the way leading to neurodegeneration and MN death. ALS-associated mitochondrial dysfunction occurs at different levels, and these organelles are involved in the mechanism of MN death. Molecular and cellular interactions are presented here as a sequential cascade of events. Based on our present knowledge, the discussion leads to the idea that feasible therapeutic strategies should focus in interfering with the pathophysiology of the disease at different steps.
Antioxidant and Neuroprotective Effects of Caffeine against Alzheimer’s and Parkinson’s Disease: Insight into the Role of Nrf-2 and A2AR Signaling
Authors: Ikram Muhammad , Park Tae Ju , Ali Tahir , Kim Myeong Ok
Published: September 2020

This paper reviews the results of studies conducted on the role of caffeine in the management of different neurological disorders, such as Parkinson’s disease (PD) and Alzheimer’s disease (AD). To highlight the potential role of caffeine in managing different neurodegenerative diseases, we identified studies by searching PubMed, Web of Science, and Google Scholar by scrutinizing the lists of pertinent publications. According to the collected overall findings, caffeine may reduce the elevated oxidative stress; inhibit the activation of adenosine A2A, thereby regulating the accumulation of Aβ; reduce the hyperphosphorylation of tau; and reduce the accumulation of misfolded proteins, such as α-synuclein, in Alzheimer’s and Parkinson’s diseases. The studies have suggested that caffeine has promising protective effects against different neurodegenerative diseases and that these effects may be used to tackle the neurological diseases and/or their consequences. Here, we review the ongoing research on the role of caffeine in the management of different neurodegenerative disorders, focusing on AD and PD. The current findings suggest that caffeine produces potent antioxidant, inflammatory, and anti-apoptotic effects against different models of neurodegenerative disease, including AD, PD, and other neurodegenerative disorders. Caffeine has shown strong antagonistic effects against the adenosine A2A receptor, which is a microglial receptor, and strong agonistic effects against nuclear-related factor-2 (Nrf-2), thereby regulating the cellular homeostasis at the brain by reducing oxidative stress, neuroinflammation, regulating the accumulation of α-synuclein in PD and tau hyperphosphorylation, amyloidogenesis, and synaptic deficits in AD, which are the cardinal features of these neurodegenerative diseases.
A Chemometric Approach to Oxidative Stability and Physicochemical Quality of Raw Ground Chicken Meat Affected by Black Seed and Other Spice Extracts
Authors: Muzolf-Panek Małgorzata , Kaczmarek Anna , Tomaszewska-Gras Jolanta , Cegielska-Radziejewska Renata , Szablewski Tomasz , Majcher Małgorzata , Stuper-Szablewska Kinga
Published: September 2020

The effects of black seed (Nigella sativa), allspice, bay leaf, caraway, cardamom, clove, and nutmeg extracts on the quality of raw ground chicken legs stored at 4 °C were investigated. During 12 days of storage, conjugated diene (CD) content, thiobarbituric acid reactive substances (TBARS), oxidation induction time (IP) by DSC (differential scanning calorimetry), hexanal content by GC-SPME-MS, thiol group (SH) content were determined. Moreover, microbial growth, pH and color of the samples were investigated. Sensory analysis was also realized. All extracts increased oxidative stability and safety of meat, significantly changed the color of the samples, stabilized the pH and increased their sensory scores (except color of samples with bay leaf and black seed) when comparing to control. Black seed, allspice and clove extracts showed high antioxidant capacity in lipid (CD = 0.23%, 0.28%, and 0.37%, respectively; TBARS = 0.55, 0.50, and 0.48 mg/kg, respectively) and protein fraction (SH content = 47.9, 52.1 and 52.7 nmol/g, respectively), although the ABTS•+ radical scavenging activity of black seed (33.1 µM/g) was significantly lower than the cloves (2496 µM/g) and allspice (815 µM/g). In the sensory analysis the highest scores were ascribed to the sample with cardamom followed by cloves. Principal component analysis (PCA) indicated complex and inseparable interrelationship among lipid and protein oxidation processes and the relationship of the protein oxidation on the lightness of meat. The results enabled to discriminate the meat samples, showing a great impact of the extracts on the final quality of raw chicken meat with black seed being potent antioxidant active additive.
Analysis of Photodiode Monitoring in Laser Cutting
Authors: Garcia Sonia M. , Ramos Joana , Arrizubieta Jon Iñaki , Figueras Jordi
Published: September 2020

The paper presents the results of an analysis based on the photodiode monitoring signals obtained during the laser cutting of aluminum and stainless steel plates. The mean level of the monitoring signal was measured and related to the process parameters and the quality achieved. The investigation was conducted in the visible and infrared spectra simultaneously for each experiment and a similar behavior at both spectra was observed, concluding the existence of a relationship between the monitoring signal, the quality of the performed cut, and the characteristics of the cutting scenario. Both visible and infrared monitoring signals were found not to vary as long as the parameter used values ensuring that the cut quality was good. Nevertheless, their mean values tended to increase as the cutting quality became worse. The measured intensity of the visible spectrum signal was associated with the vapor plume formation during the cutting process, whereas the infrared signal was related to the temperatures reached.
X-Band Photonic-Based Pulsed Radar Architecture with a High Range Resolution
Authors: Bae Youngseok , Yi Minwoo , Shin Jinwoo , Lee Sang-Gug
Published: September 2020

In this paper, we propose an X-band photonic-based pulsed radar architecture with a high range resolution. The proposed architecture is operated as a pulsed radar by adding a Mach-Zehnder modulator (MZM) operating as an optical switch to a transmitter of a conventional photonic-based frequency-modulated continuous wave (FMCW) radar. In addition, a balanced photodetector (BPD) is employed to enhance the amplitude of the received signal and remove common-mode noise. A proposed photonic-based pulsed radar prototype is implemented to operate at a center frequency of 10 GHz, a bandwidth of 640 MHz, and a pulse repetition frequency (PRF) of 1 kHz considering the performances of an arbitrary waveform generator (AWG). The implemented prototype is verified through an indoor experiment. As a result, the positions of targets are detected in real-time with 1.6% error rates of a range accuracy and obtained the range resolution of 0.26 m.
Contributions of Anthropometric and Strength Determinants to Estimate 2000 m Ergometer Performance in Traditional Rowing
Authors: Sebastia-Amat Sergio , Penichet-Tomas Alfonso , Jimenez-Olmedo Jose M. , Pueo Basilio
Published: September 2020

The purpose of this study was to analyze the contribution of anthropometric and strength determinants of 2000 m ergometer performance in traditional rowing. Nineteen rowers competing at national level participated in this study. Anthropometric characteristics, vertical jumps and bench pull tests were assessed to determine conditional factors, whereas the 2000 m test was used to set rowing performance. Pearson correlation coefficient, linear stepwise and allometric regression analyses were used to predict rowing performance (R2 > 50%). Height, body mass and body muscle correlated with rowing performance in male and female rowers. Similarly, power output for squat jump and countermovement jump power correlated with performance. Finally, mean propulsive velocity, mean power and maximum power in bench pull also correlated with the test. Stepwise multiple regression analysis identified body mass (R2 = 0.69, p < 0.001) and mean propulsive velocity in bench pull (R2 = 0.76, p < 0.001) for male rowers and body muscle (R2 = 0.89, p = 0.002) and maximum power in bench pull (R2 = 0.62, p = 0.036) for female rowers as the best predictors of rowing performance. These results determine the relevance of anthropometric characteristics and, in contrast to Olympic rowing, support the greatest importance of upper body power in traditional rowing training.
Editorial on Special Issue “The Advances and Applications of Optogenetics”
Authors: Govorunova Elena G. , Sineshchekov Oleg A.
Published: September 2020

This Special Issue provides an update for the rapidly developing technology known as “optogenetics” that is the use of genetically encoded light-sensitive molecular elements (usually derived from lower organisms) to control or report various physiological and biochemical processes within the cell. Two ongoing clinical trials use optogenetic tools for vision restoration, and optogenetic strategies have been suggested as novel therapies for several neurological, psychiatric and cardiac disorders. The Special Issue comprises two reviews and seven experimental papers on different types of light-sensitive modules widely used in optogenetic studies. These papers demonstrate the efficiency and versatility of optogenetics and are expected to be equally relevant for advanced users and beginners who only consider using optogenetic tools in their research.
Analysis of University Students’ Behavior Based on a Fusion K-Means Clustering Algorithm
Authors: Chang Wenbing , Ji Xinpeng , Liu Yinglai , Xiao Yiyong , Chen Bang , Liu Houxiang , Zhou Shenghan
Published: September 2020

With the development of big data technology, creating the ‘Digital Campus’ is a hot issue. For an increasing amount of data, traditional data mining algorithms are not suitable. The clustering algorithm is becoming more and more important in the field of data mining, but the traditional clustering algorithm does not take the clustering efficiency and clustering effect into consideration. In this paper, the algorithm based on K-Means and clustering by fast search and find of density peaks (K-CFSFDP) is proposed, which improves on the distance and density of data points. This method is used to cluster students from four universities. The experiment shows that K-CFSFDP algorithm has better clustering results and running efficiency than the traditional K-Means clustering algorithm, and it performs well in large scale campus data. Additionally, the results of the cluster analysis show that the students of different categories in four universities had different performances in living habits and learning performance, so the university can learn about the students’ behavior of different categories and provide corresponding personalized services, which have certain practical significance.
Online Application of a Hyperspectral Imaging System for the Sorting of Adulterated Almonds
Authors: Faqeerzada Mohammad Akbar , Perez Mukasa , Lohumi Santosh , Lee Hoonsoo , Kim Geonwoo , Wakholi Collins , Joshi Rahul , Cho Byoung-Kwan
Published: September 2020

Almonds are nutrient-rich nuts. Due to their high level of consumption and relatively high price, their production is targeted for illegal practices, with the intention of earning more profit. The most common adulterants are based on superficial matching, and as an adulterant, the apricot kernel is comparatively inexpensive and almost identical in color, texture, odor, and other physicochemical characteristics to almonds. In this study, a near-infrared hyperspectral imaging (NIR-HSI) system in the wavelength range of 900–1700 nm synchronized with a conveyor belt was used for the online detection of added apricot kernels in almonds. A total of 448 samples from different varieties of almonds and apricot kernels (112 × 4) were scanned while the samples moved on the conveyor belt. The spectral data were extracted from each imaged nut and used to develop a partial least square discrimination analysis (PLS-DA) model coupled with different preprocessing techniques. The PLS-DA model displayed over a 97% accuracy for the validation set. Additionally, the beta coefficient obtained from the developed model was used for pixel-based classification. An image processing algorithm was developed for the chemical mapping of almonds and apricot kernels. Consequently, the obtained model was transferred for the online sorting of seeds. The online classification system feedback had an overall accuracy of 85% for the classification of nuts. However, the model presented a relatively low accuracy when evaluated in real-time for online application, which might be due to the rough distribution of samples on the conveyor belt, high speed, delaying time in suction, and lighting variations. Nevertheless, the developed online prototype (NIR-HSI) system combined with multivariate analysis exhibits strong potential for the classification of adulterated almonds, and the results indicate that the system can be effectively used for the high-throughput screening of adulterated almond nuts in an industrial environment.
Experimental Study of Electrical Properties of Pharmaceutical Materials by Electrical Impedance Spectroscopy
Authors: Vázquez-Nambo Manuel , Gutiérrez-Gnecchi José-Antonio , Reyes-Archundia Enrique , Yang Wuqiang , Rodriguez-Frias Marco-A. , Olivares-Rojas Juan-Carlos , Lorias-Espinoza Daniel
Published: September 2020

The physicochemical characterization of pharmaceutical materials is essential for drug discovery, development and evaluation, and for understanding and predicting their interaction with physiological systems. Amongst many measurement techniques for spectroscopic characterization of pharmaceutical materials, Electrical Impedance Spectroscopy (EIS) is powerful as it can be used to model the electrical properties of pure substances and compounds in correlation with specific chemical composition. In particular, the accurate measurement of specific properties of drugs is important for evaluating physiological interaction. The electrochemical modelling of compounds is usually carried out using spectral impedance data over a wide frequency range, to fit a predetermined model of an equivalent electrochemical cell. This paper presents experimental results by EIS analysis of four drug formulations (trimethoprim/sulfamethoxazole C14H18N4O3-C10H11N3O3, ambroxol C13H18Br2N2O.HCl, metamizole sodium C13H16N3NaO4S, and ranitidine C13H22N4O3S.HCl). A wide frequency range from 20 Hz to 30 MHz is used to evaluate system identification techniques using EIS data and to obtain process models. The results suggest that arrays of linear R-C models derived using system identification techniques in the frequency domain can be used to identify different compounds.
Grousers Effect in Tracked Vehicle Multibody Dynamics with Deformable Terrain Contact Model
Authors: Mocera Francesco , Somà Aurelio , Nicolini Andrea
Published: September 2020

In this work, a multibody model of a small size farming tracked vehicle is shown. Detailed models of each track were coupled with the rigid body model of the vehicle. To describe the interaction between the track and the ground in case of deformable soil, custom defined forces were applied on each link of the track model. Their definition derived from deformable soil mechanics equations implemented with a specifically designed routine within the multibody code. According to the proposed model, it is assumed that the main terrain deformation is concentrated around the vehicle tracks elements. The custom defined forces included also the effects of the track grousers which strongly affect the traction availability for the vehicle. A passive soil failure model was considered to describe the terrain behaviour subjected to the grousers action. A so developed model in a multibody code can investigate vehicle performance and limit operating conditions related to the vehicle and soil characteristics. In this work, particular attention was focused on the results in terms of traction force, slip and sinkage on different types of terrain. Tests performed in the multibody environment show how the proposed model is able to obtain tractive performance similar to equivalent analytical solutions and how the grousers improve the availability of tractive force for certain type of soil characteristics.
Erythemal Solar Irradiance, UVER, and UV Index from Ground-Based Data in Central Spain
Authors: Bilbao Julia , de Migue Argimiro
Published: September 2020

The study shows an analysis of a 7-year data set measuring Ultraviolet-B (UVB) irradiance values and ultraviolet index TABLEUVI) values derived from ground-based broadband irradiance measurements, satellite-derived total ozone, and UVB solar irradiance recorded in Valladolid (Central Spain). Ultraviolet-B (UVB) solar irradiance measurements in the range (280–315 nm) carried out during the period 2013–2019 at a continental Mediterranean solar station, located in Valladolid (Spain), were analyzed. UVB data recorded using a YES UVB-1 pyranometer were used to estimate erythemal irradiance, ultraviolet erythemal irradiance (UVER), UVI, cumulative dose, and sun protection. Hourly UVER data in January (minimum values) and June (maximum values) were analyzed as an average year for the measurement station. Differences between UVI values at solar noon and the maximum daily value were minimal. It was found that on certain summer days, maximum daily UVI and SED (cumulative daily dose) could be over 12 and 60, respectively. The cumulative dose on the horizontal surface was calculated at the station for different skin types. It was observed that over 45% of the annual dose is received in summer, about 30% in spring, over 15% in autumn, and less than 10% in winter. In addition, the relationship between the maximum daily UVI and the annual accumulated dose in SEDs was studied to provide information on sun protection under low UVI conditions.
Degradation State Recognition of Piston Pump Based on ICEEMDAN and XGBoost
Authors: Guo Rui , Zhao Zhiqian , Wang Tao , Liu Guangheng , Zhao Jingyi , Gao Dianrong
Published: September 2020

Under different degradation conditions, the complexity of natural oscillation of the piston pump will change. Given the difference of the characteristic values of the vibration signal under different degradation states, this paper presents a degradation state recognition method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and eXtreme gradient boosting (XGBoost) to improve the accuracy of state recognition. Firstly, ICEEMDAN is proposed to alleviate the mode mixing phenomenon, which decomposes the vibration signal and obtain the intrinsic mode functions (IMFs) with less noise and more physical meaning, and subsequently the optimal IMF is found by using the correlation coefficient method. Then, the time domain, frequency domain, and entropy of the effective IMF are calculated, and the new characteristic values which can represent the degradation state are selected by principal component analysis (PCA) that it realizes dimension reduction. Finally, the above-mentioned characteristic indexes are used as the input of the XGBoost algorithm to achieve the recognition of the degradation state. In this paper, the vibration signals of four different degradation states are generated and analyzed through the piston pump slipper degradation experiment. By comparing the proposed method with different state recognition algorithms, it can be seen that the method based on ICEEMDAN and XGBoost is accurate and efficient, the average accuracy rate can reach more than 99%. Therefore, this method can more accurately describe the degradation state of the piston pump and has a highly practical application value.
Fault Diagnosis of a Reciprocating Compressor Air Valve Based on Deep Learning
Authors: Xiao Shungen , Nie Ang , Zhang Zexiong , Liu Shulin , Song Mengmeng , Zhang Hongli
Published: September 2020

With the development of machine learning in recent years, the application of machine learning to machine fault diagnosis has become increasingly popular. Applying traditional feature extraction methods for complex systems will weaken the characterization capacity of features, which are not conducive to subsequent classification work. A reciprocating compressor is a complex system. In order to improve the fault diagnosis accuracy of complex systems, this paper does not use traditional fault diagnosis methods and applies deep convolutional neural networks (CNNs) to process this nonlinear and non-stationary fault signal. The valve fault data is obtained from the reciprocating compressor test bench of the Daqing Natural Gas Company. Firstly, the single-channel vibration signal is collected on the reciprocating compressor and the one-dimensional CNN (1-D CNN) is used for fault diagnosis and compared with the traditional model to verify the effectiveness of the 1-D CNN. Next, the collected eight channels signals (three channels of vibration signals, four channels of pressure signals, one channel key phase signal) are applied by 1-D CNN and 2-D CNN for fault diagnosis to verify the CNN that it is still suitable for multi-channel signal processing. Finally, further study on the influence of the input of different channel signal combinations on the model diagnosis accuracy is carried out. Experiments show that the seven-channel signal (three-channel vibration signal, four-channel pressure signal) with the key phase signal removed has the highest diagnostic accuracy in the 2-D CNN. Therefore, proper deletion of useless channels can not only speed up network operations but also improve diagnosis accuracy.
Research on Strength Prediction Model of Sand-like Material Based on Nuclear Magnetic Resonance and Fractal Theory
Authors: Deng Hongwei , Tian Guanglin , Yu Songtao , Jiang Zhen , Zhong Zhiming , Zhang Yanan
Published: September 2020

Micro-pore structure has a decisive effect on the physical and mechanical properties of porous materials. To further improve the composition of rock-like materials, the internal relationship between microscopic characteristics (porosity, pore size distribution) and macroscopic mechanical properties of materials needs to be studied. This study selects portland cement, quartz sand, silica fume, and water-reducing agent as raw materials to simulate sandstone. Based on the Nuclear magnetic resonance (NMR) theory and fractal theory, the study explores the internal relationship between pore structure and mechanical properties of sandstone-like materials, building a compressive strength prediction model by adopting the proportion of macropores and the dimension of macropore pore size as dependent variables. Test results show that internal pores of the material are mainly macropores, and micropores account for the least. The aperture fractal dimension, the correlation coefficient of mesopores and macropores are quite different from those of micropores. Fractal characteristics of mesopores and macropores are obvious. The macropore pore volume ratio has a good linear correlation with fractal dimension and strength, and it has a higher correlation coefficient with pore volume ratio, pore fractal dimension and other variable factors. The compressive strength increases with the growth of pore size fractal dimension, but decreases with the growth of macropore pore volume ratio. The strength prediction model has a high correlation coefficient, credibility and prediction accuracy, and the predicted strength is basically close to the measured strength.
A Finite State Method in the Performance Evaluation of the Bernoulli Serial Production Lines
Authors: Hadžić Neven , Ložar Viktor , Abdulaj Filip
Published: September 2020

Research on the performance measure evaluation of Bernoulli serial production lines is presented in this paper. Important aspects of the modeling and analysis using transition systems within the Markovian framework are addressed, including analytical and approximation methods. The “dimensionality curse” problems of the large scale and dense transition systems in the production system engineering field are pointed out as one of the main research and development obstacles. In that respect, a new analytically-based finite state method is presented based on the proportionality property of the stationary probability distribution across the systems’ state space. Simple and differentiable expressions for the performance measures including the production rate, the work-in-process, and the probabilities of machine blockage and starvation are formulated. A finite state method’s accuracy and applicability are successfully validated by comparing the obtained results against the rigorous analytical solution.
Development and Implementation of a Novel Optimization Algorithm for Reliable and Economic Grid-Independent Hybrid Power System
Authors: Kharrich Mohammed , Mohammed Omar Hazem , Kamel Salah , Selim Ali , Sultan Hamdy M. , Akherraz Mohammed , Jurado Francisco
Published: September 2020

Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have been proposed and demonstrated their feasibility in obtaining the optimal solution. Therefore, this paper introduces an improved version of Bonobo Optimizer (BO) based on a quasi-oppositional method to solve the problem of designing a hybrid microgrid system including RES (photovoltaic (PV) panels, wind turbines (WT), and batteries) with diesel generators. A comparison between traditional BO, the Quasi-Oppositional BO (QOBO), and other optimization techniques called Harris Hawks Optimization (HHO), Artificial Electric Field Algorithm (AEFA) and Invasive Weed Optimization (IWO) is carried out to check the efficiency of the proposed QOBO. The QOBO is applied to a stand-alone hybrid microgrid system located in Aswan, Egypt. The results show the effectiveness of the QOBO algorithm to solve the optimal economic design problem for hybrid microgrid power systems.
Dosimetric Issues Associated with Percutaneous Ablation of Small Liver Lesions with 90Y
Authors: D’Arienzo Marco , Sarnelli Anna , Mezzenga Emilio , Chiacchiararelli Laura , Amato Antonino , Romanelli Massimo , Cianni Roberto , Cremonesi Marta , Paganelli Giovanni
Published: September 2020

The aim of the present paper is twofold. Firstly, to assess the absorbed dose in small lesions using Monte Carlo calculations in a scenario of intratumoral injection of 90Y (e.g., percutaneous ablation). Secondly, to derive a practical analytical formula for the calculation of the absorbed dose that incorporates the absorbed fractions for 90Y. The absorbed dose per unit administered activity was assessed using Monte Carlo calculations in spheres of different size (diameter 0.5–20 cm). The spheres are representative of tumor regions and are assumed to be uniformly filled with 90Y. Monte Carlo results were compared with the macrodosimetric approach used for dose calculation in liver radioembolization. The results of this analysis indicate that the use of the analytic model provides dose overestimates below 10% for lesions with diameter larger than approximately 2 cm. However, for lesions smaller than 2 cm the analytic model is likely to deviate significantly (>10%) from Monte Carlo results, providing dose overestimations larger than 50% for lesions of 0.5 cm diameter. In this paper an analytical formula derived from MC calculations that incorporates the absorbed fractions for 90Y is proposed. In a scenario of intratumoral injection of microspheres, the proposed equation can be usefully employed in the treatment planning of spherical lesions of small size (down to 0.5 cm diameter) providing dose estimates in close agreement with Monte Carlo calculations (maximum deviation below 0.5%).
Multidomain Simulation Model for Analysis of Geometric Variation and Productivity in Multi-Stage Assembly Systems
Authors: Benavent Nácher Sergio , Rosado Castellano Pedro , Romero Subirón Fernando , Abellán-Nebot José V.
Published: September 2020

Nowadays, the new era of industry 4.0 is forcing manufacturers to develop models and methods for managing the geometric variation of a final product in complex manufacturing environments, such as multistage manufacturing systems. The stream of variation model has been successfully applied to manage product geometric variation in these systems, but there is a lack of research studying its application together with the material and order flow in the system. In this work, which is focused on the production quality paradigm in a model-based system engineering context, a digital prototype is proposed to integrate productivity and part quality based on the stream of variation analysis in multistage assembly systems. The prototype was modelled and simulated with OpenModelica tool exploiting the Modelica language capabilities for multidomain simulations and its synergy with SysML. A case study is presented to validate the potential applicability of the approach. The proposed model and the results show a promising potential for future developments aligned with the production quality paradigm.