bluuebunny/crossref_metadata_2025 huggingface dataset:
Hyperspectral-Based Classification of Managed Permanent Grassland with Multilayer Perceptrons: Influence of Spectral Band Count and Spectral Regions on Model Performance
Authors: Britz Roland , Barta Norbert , Klingler Andreas , Schaumberger Andreas , Bauer Alexander , Pötsch Erich M. , Gronauer Andreas , Motsch Viktoria
Published: April 2022

Detailed knowledge of botanical composition is a key factor for the sustainable and site-specific management of permanent grassland and facilitates an improvement in the performance and efficiency of livestock feeding. Spectral-based data acquisition combined with machine learning has the potential to classify species groups and plant parts in permanent grassland with high accuracy. However, a disadvantage of this method is the fact that hyperspectral sensors with a wide spectral range and fine spectral and high spatial resolution are costly and create large amounts of data. Therefore, the question arises as to whether these parameters are necessary for accurate grassland classification. Thus, the use of sensors with lower spectral and spatial resolution and correspondingly lower data processing requirements could be a conceivable approach. Therefore, we investigated the classification performance with reduced predictor sets formed by different approaches in permanent grassland. For pixel-based classification, a cross-validated mean accuracy of 86.1% was reached using a multilayer perceptron (MLP) including all 191 available predictors, i.e., spectral bands. Using only 48 high-performing predictors, an accuracy of 80% could still be achieved. In particular, the spectral regions of 954 nm to 956 nm, 684 nm to 744 nm and 442 nm to 444 nm contributed most to the classification performance. These results provide a promising basis for future data acquisition and the analysis of grassland vegetation.
Molecular Markers for Identifying Resistance Genes in Brassica napus
Authors: Van de Wouw Angela P. , Zhang Yueqi , Mohd Saad Nur Shuhadah , Yang Hua , Sheedy Elizabeth , Elliott Candace E. , Batley Jacqueline
Published: April 2022

Blackleg disease, caused by the fungal pathogen Leptosphaeria maculans, is the most devastating disease of canola (Brassica napus, oilseed rape) worldwide. Breeding for genetic resistance is the most widely used tool for controlling this disease and minimizing the impact on yield. To date, five resistance genes (Rlm2, LepR3, Rlm4, Rlm7, Rlm9) have been cloned from B. napus, representing alleles of two different gene loci, Rlm2-LepR3 and Rlm4-7-9. We report on the development and validation of Kompetitive Allele-Specific PCR (KASP) markers that can discriminate between the resistant and susceptible alleles of each resistance gene. These markers will provide valuable tools for both researchers and industry through the ability to characterize resistance genes without phenotyping.
Vascular and Transpiration Flows Affecting Apricot (Prunus armeniaca L.) Fruit Growth
Authors: Giovannini Andrea , Venturi Melissa , Gutiérrez-Gordillo Saray , Manfrini Luigi , Corelli-Grappadelli Luca , Morandi Brunella
Published: April 2022

Fruit growth is a biophysical process that depends mainly on the daily balance between vascular (xylem and phloem) and transpiration flows. This work examines the seasonal and daily behaviour of apricot fruit growth as well as their vascular and transpiration flows. Seasonal patterns of the shoot and fruit growth, as well as fruit surface conductance and dry matter accumulation, were monitored at regular times intervals during the season on “Farbela” and “Ladycot” cultivars. In addition, the daily courses of leaf and stem water potentials and leaf gas exchanges were monitored at 66 and 109 DAFB. On the cultivar “Farbela”, the daily patterns of phloem, xylem, and transpiration flow to and from the fruit were determined through precise and continuous monitoring of fruit diameter variations. Branch sap flow was also determined through the thermal balance method. Apricot fruit growth showed a double sigmoid pattern, typical of other drupaceous species. Stem and leaf water potential maintained values above the stress threshold, and in the last part of the season, the leaf photosynthetic rate increased. Leaves received higher sap flow in the morning and at midday, while a higher amount of xylem water was moved to the fruit in the late afternoon. Fruit showed high transpiration rates, which led to fruit shrinkage during the warmest hours of the day. High xylem inflows balanced the transpiratory losses, while phloem import was lower and occurred mainly during the mid-day hours. As a result, the fruit grew mostly in the late afternoon and night, and its growth was sustained mainly by xylem fluxes, which represented over 90% of the fruit’s total inflows. Later in the season, fruit transpiration and xylem flow decreased but did not stop even at harvest. Phloem import increased its importance throughout the season and, in the final stages, accounted for 36% and then 66% of the daily relative contribution to fruit growth. This knowledge represents a starting point to improving apricot orchard management in terms of irrigation and fertilisation.
The Form in Formal Thought Disorder: A Model of Dyssyntax in Semantic Networking
Authors: Badie Farshad , Augusto Luis M.
Published: April 2022

Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what “formal” means in the plethora of symptoms exhibited. We present a logic-based model for the syntax–semantics interface in semantic networking that can not only explain, but also diagnose, FTD. Our model is based on description logic (DL), which is well known for its adequacy to model terminological knowledge. More specifically, we show how faulty logical form as defined in DL-based Conception Language (CL) impacts the semantic content of linguistic productions that are characteristic of FTD. We accordingly call this the dyssyntax model.
Drug Regimens of Novel Antibiotics in Critically Ill Patients with Varying Renal Functions: A Rapid Review
Authors: Gorham Julie , Taccone Fabio Silvio , Hites Maya
Published: April 2022

There is currently an increase in the emergence of multidrug-resistant bacteria (MDR) worldwide, requiring the development of novel antibiotics. However, it is not only the choice of antibiotic that is important in treating an infection; the drug regimen also deserves special attention to avoid underdosing and excessive concentrations. Critically ill patients often have marked variation in renal function, ranging from augmented renal clearance (ARC), defined as a measured creatinine clearance (CrCL) ≥ 130 mL/min*1.73 m2, to acute kidney injury (AKI), eventually requiring renal replacement therapy (RRT), which can affect antibiotic exposure. All novel beta-lactam (BLs) and/or beta-lactam/beta-lactamases inhibitors (BL/BLIs) antibiotics have specific pharmacokinetic properties, such as hydrophilicity, low plasma–protein binding, small volume of distribution, low molecular weight, and predominant renal clearance, which require adaptation of dosage regimens in the presence of abnormal renal function or RRT. However, there are limited data on the topic. The aim of this review was therefore to summarize available PK studies on these novel antibiotics performed in patients with ARC or AKI, or requiring RRT, in order to provide a practical approach to guide clinicians in the choice of the best dosage regimens in critically ill patients.
Synthesis, Spectroscopic Studies for Five New Mg (II), Fe (III), Cu (II), Zn (II) and Se (IV) Ceftriaxone Antibiotic Drug Complexes and Their Possible Hepatoprotective and Antioxidant Capacities
Authors: El-Megharbel Samy , Qahl Safa , Alaryani Fatima , Hamza Reham
Published: April 2022

Magnesium, copper, zinc, iron and selenium complexes of ceftriaxone were prepared in a 1:1 ligand to metal ratio to investigate the ligational character of the antibiotic ceftriaxone drug (CFX). The complexes were found to have coordinated and hydrated water molecules, except for the Se (IV) complex, which had only hydrated water molecules. The modes of chelation were explained depending on IR, 1HNMR and UV–Vis spectroscopies. The electronic absorption spectra and the magnetic moment values indicated that Mg (II), Cu (II), Zn (II), Fe (III) and Se (VI) complexes form a six-coordinate shape with a distorted octahedral geometry. Ceftriaxone has four donation sites through nitrogen from NH2 amino, oxygen from triazine, β-lactam carbonyl and carboxylate with the molecular formulas [Mg(CFX)(H2O)2]·4H2O, [Cu(CFX)(H2O)2]·3H2O, [Fe(CFX)(H2O)(Cl)]·5H2O, [Zn(CFX)(H2O)2]·6H2O and [Se(CFX)(Cl)2]·4H2O and acts as a tetradentate ligand towards the five metal ions. The morphological surface and particle size of ceftriaxone metal complexes were determined using SEM, TEM and X-ray diffraction. The thermal behaviors of the complexes were studied by the TGA(DTG) technique. This study investigated the effect of CFX and CFX metal complexes on oxidative stress and severe tissue injury in the hepatic tissues of male rats. Fifty-six male rats were tested: the first group received normal saline (1 mg/kg), the second group received CFX orally at a dose of 180 mg/kg, and the other treated groups received other CFX metal complexes at the same dose as the CFX-treated group. For antibacterial activity, CFX/Zn complex was highly effective against Streptococcus pneumoniae, while CFX/Se was highly effective against Staphylococcus aureus and Escherichia coli. In conclusion, successive exposure to CFX elevated hepatic reactive oxygen species (ROS) levels and lipid peroxidation final marker (MDA) and decreased antioxidant enzyme levels. CFX metal complex administration prevented liver injury, mainly suppressing excessive ROS generation and enhancing antioxidant defense enzymes and in male rats.
What Doesn’t Kill Them Makes Them Stronger: The Impact of the Resistance Patterns of Urinary Enterobacterales Isolates in Patients from a Tertiary Hospital in Eastern Europe
Authors: Miftode Ionela-Larisa , Pasare Maria-Antoanela , Miftode Radu-Stefan , Nastase Eduard , Plesca Claudia Elena , Lunca Catalina , Miftode Egidia-Gabriela , Timpau Amalia-Stefana , Iancu Luminita Smaranda , Dorneanu Olivia Simona
Published: April 2022

(1) Background: The evolution of bacterial resistance to antibiotics is one of the factors that make infectious pathology an extremely dynamic field, also inducing a significant burden on public health systems; therefore, continuous updates on the bacterial resistance to antibiotics and their particular regional patterns is crucial for the adequate approach of various infectious diseases. (2) Methods: We retrospectively analyzed 354 patients with Enterobacterales urinary tract infections (UTIs), determined their antibiotic resistance pattern, thus aiming to correlate them with the outcome and other specific markers of poor prognosis. (3) Results: The most frequent causative agent was Escherichia coli, representing 64.6% of all UTIs. We identified 154 patients resistant to multiple antibiotic classes, of which 126 were multidrug-resistant (MDR), 17 were extensive drug-resistant (XDR) and 11 were pandrug-resistant (PDR). Moreover, 25 isolates were resistant to carbapenems (CRE), 25 were difficult-to-treat (DTR), and 84 were extended-spectrum cephalosporin-resistant (ESC), with only 95 isolates susceptible to all tested antibiotics. Mortality ranged from 1% for UTIs caused by isolates susceptible to all tested antibiotics, to 24% for the ones caused by DTR or CRE isolates. Other significant risk factors associated with mortality were: prolonged hospital stay (p = 0.0001), Charlson comorbidity index ≥ 3 (p = 0.02), urinary catheterization (p = 0.001), associated respiratory pathologies (p = 0.004), obesity (p = 0.047), a history of previous hospitalizations (p = 0.007), inappropriate empiric antibiotic regimen (p = 0.001), or hyper inflammatory status (p = 0.006). Basically, we observed that a multiple regression model comprising urinary catheterization, inappropriate empiric anti-biotherapy, obesity, and respiratory comorbidities exhibits the best correlation with mortality rate in patients with UTI (R = 0.347, R2 = 0.12). (4) Conclusions: By focusing on the novel resistance patterns, our study provides complementary evidence concerning the resistance profiles found in an Eastern European region, as well as their prognostic implications in patients with UTI.
Multifractal Analysis to Determine the Effect of Surface Topography on the Distribution, Density, Dispersion and Clustering of Differently Organised Coccal-Shaped Bacteria
Authors: Evans Adele , Slate Anthony J. , Tobin Millie , Lynch Stephen , Wilson Nieuwenhuis Joels , Verran Joanna , Kelly Peter , Whitehead Kathryn A.
Published: April 2022

The topographic features of surfaces are known to affect bacterial retention on a surface, but the precise mechanisms of this phenomenon are little understood. Four coccal-shaped bacteria, Staphylococcus sciuri, Streptococcus pyogenes, Micrococcus luteus, and Staphylococcus aureus, that organise in different cellular groupings (grape-like clusters, tetrad-arranging clusters, short chains, and diploid arrangement, respectively) were used. These differently grouped cells were used to determine how surface topography affected their distribution, density, dispersion, and clustering when retained on titanium surfaces with defined topographies. Titanium-coated surfaces that were smooth and had grooved features of 1.02 µm-wide, 0.21 µm-deep grooves, and 0.59 µm-wide, 0.17 µm-deep grooves were used. The average contact angle of the surfaces was 91°. All bacterial species were overall of a hydrophobic nature, although M. luteus was the least hydrophobic. It was demonstrated that the 1.02 µm-wide featured surface most affected Strep. pyogenes and S. sciuri, and hence the surfaces with the larger surface features most affected the cells with smaller dimensions. The 0.59 µm featured surface only affected the density of the bacteria, and it may be suggested that the surfaces with the smaller features reduced bacterial retention. These results demonstrate that the size of the topographical surface features affect the distribution, density, dispersion, and clustering of bacteria across surfaces, and this is related to the cellular organisation of the bacterial species. The results from this work inform how surface topographical and bacterial properties affect the distribution, density, dispersion, and clustering of bacterial retention.
Mitochondrial Calcium: Effects of Its Imbalance in Disease
Authors: Matuz-Mares Deyamira , González-Andrade Martin , Araiza-Villanueva Minerva Georgina , Vilchis-Landeros María Magdalena , Vázquez-Meza Héctor
Published: April 2022

Calcium is used in many cellular processes and is maintained within the cell as free calcium at low concentrations (approximately 100 nM), compared with extracellular (millimolar) concentrations, to avoid adverse effects such as phosphate precipitation. For this reason, cells have adapted buffering strategies by compartmentalizing calcium into mitochondria and the endoplasmic reticulum (ER). In mitochondria, the calcium concentration is in the millimolar range, as it is in the ER. Mitochondria actively contribute to buffering cellular calcium, but if matrix calcium increases beyond physiological demands, it can promote the opening of the mitochondrial permeability transition pore (mPTP) and, consequently, trigger apoptotic or necrotic cell death. The pathophysiological implications of mPTP opening in ischemia-reperfusion, liver, muscle, and lysosomal storage diseases, as well as those affecting the central nervous system, for example, Parkinson’s disease (PD), Alzheimer’s disease (AD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS) have been reported. In this review, we present an updated overview of the main cellular mechanisms of mitochondrial calcium regulation. We specially focus on neurodegenerative diseases related to imbalances in calcium homeostasis and summarize some proposed therapies studied to attenuate these diseases.
Genome-Wide Association Study of Fluorescent Oxidation Products Accounting for Tobacco Smoking Status in Adults from the French EGEA Study
Authors: Orsi Laurent , Margaritte-Jeannin Patricia , Andrianjafimasy Miora , Dumas Orianne , Mohamdi Hamida , Bouzigon Emmanuelle , Demenais Florence , Matran Régis , Zerimech Farid , Nadif Rachel , Dizier Marie-Hélène
Published: April 2022

Oxidative stress (OS) is the main pathophysiological mechanism involved in several chronic diseases, including asthma. Fluorescent oxidation products (FlOPs), a global biomarker of damage due to OS, is of growing interest in epidemiological studies. We conducted a genome-wide association study (GWAS) of the FlOPs level in 1216 adults from the case-control and family-based EGEA study (mean age 43 years old, 51% women, and 23% current smokers) to identify genetic variants associated with FlOPs. The GWAS was first conducted in the whole sample and then stratified according to smoking status, the main exogenous source of reactive oxygen species. Among the top genetic variants identified by the three GWAS, those located in BMP6 (p = 3 × 10−6), near BMPER (p = 9 × 10−6), in GABRG3 (p = 4 × 10−7), and near ATG5 (p = 2 × 10−9) are the most relevant because of both their link to biological pathways related to OS and their association with several chronic diseases for which the role of OS in their pathophysiology has been pointed out. BMP6 and BMPER are of particular interest due to their involvement in the same biological pathways related to OS and their functional interaction. To conclude, this study, which is the first GWAS of FlOPs, provides new insights into the pathophysiology of chronic OS-related diseases.
A Novel Pathway Phenotype of Temporal Lobe Epilepsy and Comorbid Psychiatric Disorders: Results of Precision Nomothetic Medicine
Authors: Maes Michael , Barbosa Décio Sabbatini , Almulla Abbas F. , Kanchanatawan Buranee
Published: April 2022

No precision medicine models of temporal lobe epilepsy (TLE) and associated mental comorbidities have been developed to date. This observational study aimed to develop a precision nomothetic, data-driven comorbid TLE model with endophenotype classes and pathway phenotypes that may have prognostic and therapeutical implications. We recruited forty healthy controls and 108 TLE patients for this research and assessed TLE and psychopathology (PP) features as well as oxidative stress (OSTOX, e.g., malondialdehyde or MDA, lipid hydroperoxides, and advanced oxidation protein products) and antioxidant (paraoxonase 1 or PON1 status, -SH groups, and total radical trapping potential or TRAP) biomarkers. A large part (57.2%) of the variance in a latent vector (LV) extracted from the above TLE and PP features was explained by these OSTOX and antioxidant biomarkers. The PON1 Q192R genetic variant showed indirect effects on this LV, which were completely mediated by PON1 activity and MDA. Factor analysis showed that a common core could be extracted from TLE, PP, OSTOX and antioxidant scores, indicating that these features are manifestations of a common underlying construct, i.e., a novel pathway phenotype of TLE. Based on the latter, we constructed a new phenotype class that is characterized by increased severity of TLE, PP and OSTOX features and lowered antioxidant defenses. A large part of the variance in episode frequency was explained by increased MDA, lowered antioxidant, and nitric oxide metabolite levels. In conclusion, (a) PP symptoms belong to the TLE phenome, and the signal increased severity; and (b) cumulative effects of aldehyde formation and lowered antioxidants determine epileptogenic kindling.
Green Techniques for Preparation of Red Beetroot Extracts with Enhanced Biological Potential
Authors: Borjan Dragana , Šeregelj Vanja , Andrejč Darija Cör , Pezo Lato , Šaponjac Vesna Tumbas , Knez Željko , Vulić Jelena , Marevci Maša Knez
Published: April 2022

Red beetroot is well known for its high proportion of betalains, with great potential as functional food ingredients due to their health-promoting properties. The objective of this study was to investigate the influence of processing techniques such as Soxhlet, cold, ultrasound and supercritical fluid extraction on the betalains content and its antioxidant, anti-inflammatory and antihyperglycemic activities. Whilst Soxhlet extraction with water has provided the highest yield, the highest content of total phenolics was found in an extract prepared using Soxhlet extraction with 50% ethanol. Amongst eight phenolic compounds detected in the extracts, protocatechuic acid was the most abundant. The concentrations of total phenolics ranged from 12.09 mg/g (ultrasound extraction with 30% methanol) to 18.60 mg/g (Soxhlet extraction with 50% ethanol). The highest anti-inflammatory activity was observed for cold extraction with 50% methanol extract. The high radical scavenging activity of supercritical fluid extracts could be a consequence of nonphenolic compounds. The chemometrics approach was further used to analyse the results to find the “greenest” method for further possible application in the processing of beetroot in the food and/or pharmaceutical industry. According to the standard score, the best extraction method was determined to be Soxhlet extraction with 50% ethanol.
An Antioxidant Supplement Function Exploration: Rescue of Intestinal Structure Injury by Mannan Oligosaccharides after Aeromonas hydrophila Infection in Grass Carp (Ctenopharyngodon idella)
Authors: Lu Zhi-Yuan , Feng Lin , Jiang Wei-Dan , Wu Pei , Liu Yang , Jin Xiao-Wan , Ren Hong-Mei , Kuang Sheng-Yao , Li Shu-Wei , Tang Ling , Zhang Lu , Mi Hai-Feng , Zhou Xiao-Qiu
Published: April 2022

Mannan oligosaccharides (MOS) are a type of functional oligosaccharide which have received increased attention because of their beneficial effects on fish intestinal health. However, intestinal structural integrity is a necessary prerequisite for intestinal health. This study focused on exploring the protective effects of dietary MOS supplementation on the grass carp’s (Ctenopharyngodon idella) intestinal structural integrity (including tight junction (TJ) and adherent junction (AJ)) and its related signalling molecule mechanism. A total of 540 grass carp (215.85 ± 0.30 g) were fed six diets containing graded levels of dietary MOS supplementation (0, 200, 400, 600, 800 and 1000 mg/kg) for 60 days. Subsequently, a challenge test was conducted by injection of Aeromonas hydrophila for 14 days. We used ELISA, spectrophotometry, transmission electron microscope, immunohistochemistry, qRT-PCR and Western blotting to determine the effect of dietary MOS supplementation on intestinal structural integrity and antioxidant capacity. The results revealed that dietary MOS supplementation protected the microvillus of the intestine; reduced serum diamine oxidase and d-lactate levels (p < 0.05); enhanced intestinal total antioxidant capacity (p < 0.01); up-regulated most intestinal TJ and AJ mRNA levels; and decreased GTP-RhoA protein levels (p < 0.01). In addition, we also found several interesting results suggesting that MOS supplementation has no effects on ZO-2 and Claudin-15b. Overall, these findings suggested that dietary MOS supplementation could protect intestinal ultrastructure, reduce intestinal mucosal permeability and maintain intestinal structural integrity via inhibiting MLCK and RhoA/ROCK signalling pathways.
Special Issue: Generative Models in Artificial Intelligence and Their Applications
Authors: Castelli Mauro , Manzoni Luca
Published: April 2022

In recent years, artificial intelligence has been used to generate a significant amount of high-quality data, such as images, music, and videos [...]
AI Ethics—A Bird’s Eye View
Authors: Christoforaki Maria , Beyan Oya
Published: April 2022

The explosion of data-driven applications using Artificial Intelligence (AI) in recent years has given rise to a variety of ethical issues regarding data collection, annotation, and processing using mostly opaque algorithms, as well as the interpretation and employment of the results of the AI pipeline. The ubiquity of AI applications negatively impacts a variety of sensitive areas, ranging from discrimination against vulnerable populations to privacy invasion and the environmental cost that these algorithms entail, and puts into focus on the ever present domain of AI ethics. In this review article we present a bird’s eye view approach of the AI ethics landscape, starting from a historical point of view, examining the moral issues that were introduced by big datasets and the application of non-symbolic AI algorithms, the normative approaches (principles and guidelines) to these issues and the ensuing criticism, as well as the actualization of these principles within the proposed frameworks. Subsequently, we focus on the concept of responsibility, both as personal responsibility of the AI practitioners and sustainability, meaning the promotion of beneficence for both the society and the domain, and the role of professional certification and education in averting unethical choices. Finally, we conclude with indicating the multidisciplinary nature of AI ethics and suggesting future challenges.
Spatiotemporal Matching Cost Function Based on Differential Evolutionary Algorithm for Random Speckle 3D Reconstruction
Authors: Kong Lingyin , Xiong Wei , Ying Sancong
Published: April 2022

Random speckle structured light can increase the texture information of the object surface, so it is added in the binocular stereo vision system to solve the matching ambiguity problem caused by the surface with repetitive pattern or no texture. To improve the reconstruction quality, many current researches utilize multiple speckle patterns for projection and use stereo matching methods based on spatiotemporal correlation. This paper presents a novel random speckle 3D reconstruction scheme, in which multiple speckle patterns are used and a weighted-fusion-based spatiotemporal matching cost function (STMCF) is proposed to find the corresponding points in speckle stereo image pairs. Furthermore, a parameter optimization method based on differential evolutionary (DE) algorithm is designed for automatically determining the values of all parameters included in STMCF. In this method, since there is no suitable training data with ground truth, we explore a training strategy where a passive stereo vision dataset with ground truth is used as training data and then apply the learned parameter value to the stereo matching of speckle stereo image pairs. Various experimental results verify that our scheme can realize accurate and high-quality 3D reconstruction efficiently and the proposed STMCF exhibits superior performance in terms of accuracy, computation time and reconstruction quality than the state-of-the-art method based on spatiotemporal correlation.
Quality Assessment of Components of Wheat Seed Using Different Classifications Models
Authors: Fazel-Niari Zargham , Afkari-Sayyah Amir H. , Abbaspour-Gilandeh Yousef , Herrera-Miranda Israel , Hernández-Hernández José Luis , Hernández-Hernández Mario
Published: April 2022

To use machine vision technology in visual quality control of cereal seeds, sufficient knowledge is necessary. In this work, the capability of machine visual systems, equipped with industrial digital cameras for the identification and classification of seven-grain groups in wheat seed samples, was studied. Two statistical models and three support vector machines were employed in this study. Through image processing of 21,000 single grains, the shape, colour, and textural features of each grain were determined. Ninety-one features were ranked through the ReliefF method. The shape features were the most prominent, followed by the textural and colour features. Among the five models tested, the highest classification accuracy was obtained using quadratic support vector machine (QSVM) and the first 35 features. In the test run of this model with independent data, the classification accuracy for sound white wheat, small white wheat, broken white wheat, shrunken white wheat, red wheat, barley and rye were, respectively, 98.7, 98, 99.3, 90.7, 99, 100, and 97.3%, with an overall average accuracy of 97.6%. In the context of this study, the machine vision system—comprising an industrial digital camera and quadratic support vector machine or non-linear discriminate analysis method—was identified as a valuable system in the investigation of the visual qualities of wheat seeds.
The Limits of SEMA on Distinguishing Similar Activation Functions of Embedded Deep Neural Networks
Authors: Takatoi Go , Sugawara Takeshi , Sakiyama Kazuo , Hara-Azumi Yuko , Li Yang
Published: April 2022

Artificial intelligence (AI) is progressing rapidly, and in this trend, edge AI has been researched intensively. However, much less work has been performed around the security of edge AI. Machine learning models are a mass of intellectual property, and an optimized network is very valuable. Trained machine learning models need to be black boxes as well because they may give away information about the training data to the outside world. As selecting the appropriate activation functions to enable fast training of accurate deep neural networks is an active area of research, it is important to conceal the information of the activation functions used in a neural network architecture as well. There has been research on the use of physical attacks such as the side-channel attack (SCA) in areas other than cryptography. The SCA is highly effective against edge artificial intelligence due to its property of the device computing close to the user. We studied a previously proposed method to retrieve the activation functions of a black box neural network implemented on an edge device by using simple electromagnetic analysis (SEMA) and improved the signal processing procedure for further noisy measurements. The SEMA attack identifies activation functions by directly observing distinctive electromagnetic (EM) traces that correspond to the operations in the activation function. This method requires few executions and inputs and also has little implementation dependency on the activation functions. We distinguished eight similar activation functions with EM measurements and examined the versatility and limits of this attack. In this work, the machine learning architecture is a multilayer perceptron, evaluated on an Arduino Uno.
Remaining Useful Life Estimation of Rotating Machines through Supervised Learning with Non-Linear Approaches
Authors: Chelmiah Eoghan T. , McLoone Violeta I. , Kavanagh Darren F.
Published: April 2022

Bearings are one of the most common causes of failure for rotating electric machines. Intelligent condition-based monitoring (CbM) can be used to predict rolling element bearing fault modes using non-invasive and inexpensive sensing. Strategically placed accelerometers can acquire bearing vibration signals, which contain salient prognostic information regarding the state of health. Machine learning (ML) algorithms are currently being investigated to accurately predict the health of machines and equipment in real time. This is highly advantageous towards reducing unscheduled maintenance, increasing the operational lifetime, as well as mitigation of the associated health risks caused by catastrophic machine failure. Motivated by this, a robust CbM system is presented for rotating machines that is suitable for various industrial applications. Novel non-linear methods for both feature engineering (one-third octave bands) and wear-state modelling (exponential) are investigated. The paper compares two main types of feature extraction, which are derived from Short-Time Fourier Transform (STFT) and Envelope Analysis (EA). In addition, two types of supervised learning, Support Vector Machines (SVM) and k-Nearest Neighbour (k-NN) are explored. The work is tested and validated on the PRONOSTIA platform dataset, with remaining useful life (RUL) classification results of up to 74.3% and a mean absolute error of 0.08 achieved.
Jointing Principles in AMC—Part 1: Design and Preparation of Dry Joints
Authors: Lanwer Jan-Paul , Weigel Hendrik , Baghdadi Abtin , Empelmann Martin , Kloft Harald
Published: April 2022

The study described in this contribution contains a fundamental strategy to select geometries for dry joint profiles in 3D-printed concrete constructions. A database, here called the ‘joint catalogue’, contains a variety of joint types adapted from timber, steel, and bionic connections. Weighting factors and different criteria evaluate and score the various joint profiles (e.g., manufacturability, duration of manufacturing, and mechanical behaviour). Therefore, an algorithm sums up the scores leading to the preselection of better suitable profiles. The preselected joint profiles were afterwards analysed by the finite element method, determining the load capacity of the joint in a unit specimen. According to the joint catalogue, a smooth, triangular, truncated cone and arc joint profile appeared to be the optimal combination for dry joints in additive manufacturing of construction (AMC).
Avoiding Obstacles via Missile Real-Time Inference by Reinforcement Learning
Authors: Hong Daseon , Park Sungsu
Published: April 2022

In the contemporary battlefield where complexity has increased, the enhancement of the role and ability of missiles has become crucial. Thus, missile guidance systems are required to be further developed in a more intelligent and autonomous way to deal with complicated environments. In this paper, we propose novel missile guidance laws using reinforcement learning, which can autonomously avoid obstacles and terrains in complicated environments with limited prior information and even without the need of off-line trajectory or waypoint generation. The proposed guidance laws are focused on two mission scenarios: the first is with planar obstacles, which is used to cope with maritime operations, and the second is with complex terrain, which is used to cope with land operations. We present the detailed design processes for both scenarios, including a neural network architecture, reward function selection, and training method. Simulation results are provided to show the feasibility and effectiveness of the proposed guidance laws and some important aspects are discussed in terms of their advantages and limitations.
Twitter Data Mining to Map Pedestrian Experience of Open Spaces
Authors: Vukmirovic Milena , Raspopovic Milic Miroslava , Jovic Jovana
Published: April 2022

This research investigated the classification and visualisation of Twitter user-generated data. Twitter data were classified based on their sentiment relating to pedestrian experience of the quality of open spaces, based on their content. The research methodology for Twitter data collection, processing and analysis included five phases: data collection, data pre-processing, data classification, data visualisation and data analysis. The territorial focus was on Oxford Street, London, UK. Special attention was placed on the questions regarding the potential of using Twitter data for extracting relevant topics for the public space and investigating whether the sentiment for these topics can relate to urban design and improvement of pedestrian space. The proposed research model considered amount and relevance, its possibilities regarding the interpretation of the collected sample, the potential of the data for the purpose of the analysis of pedestrian space quality, the precision of sentiment determination and the usability of data in relation to a particular open public space.
Structural Characteristics and Formation Mechanism of the Earth Fissures as a Geohazard in Birjand, Iran
Authors: Rashidi Ahmad , Khatib Mohammad Mahdi , Derakhshani Reza
Published: April 2022

Earth fissure structures are a common type of geohazard associated with geotechnical surface ruptures that can occur almost anywhere on the ground surface due to a variety of different mechanisms, and in most cases, these hazardous cracks have resulted in severe damage to infrastructure. Investigation of the structural characteristics of fissures in an active tectonic area (such as Birjand in eastern Iran) can improve our understanding of connections between the fissures and structural geology. The first reported earth fissures in NW Birjand are distributed along the North Birjand fault. Field observations and analysis of the detailed topography cross-sections using the real-time kinematic (RTK) technique have been used to infer the fissure development. Morphometric analysis of faults and fissures shows that the long axis of most fissure structures is distributed perpendicular to the strike of the North Birjand fault. The average volume strain in the study area was calculated to be 14.68 percent based on fissure geometry studies, with the maximum volume strain corresponding to the location of the North Birjand fault’s youngest splay. This splay formed fault-propagation folds with exposed fissure structures. This study shows that the fault-propagation folds in this system are subjected to the activity and evolution of the ground fissure as a result of the expansion of tensile stress.
Pace Running of a Quadruped Robot Driven by Pneumatic Muscle Actuators: An Experimental Study
Authors: Fukuoka Yasuhiro , Komatsu Ryunosuke , Machii Kenta , Yokota Masaaki , Tobe Masaki , Ibrahim Ahmad Najmuddin , Fukui Takahiro , Habu Yasushi
Published: April 2022

Our goal is to design a neuromorphic locomotion controller for a prospective bioinspired quadruped robot driven by artificial muscle actuators. In this paper, we focus on achieving a running gait called a pace, in which the ipsilateral pairs of legs move in phase, while the two pairs together move out of phase, by a quadruped robot with realistic legs driven by pneumatic muscle actuators. The robot is controlled by weakly coupled two-level central pattern generators to generate a pace gait with leg loading feedback. Each leg is moved through four sequential phases like an animal, i.e., touch-down, stance, lift-off, and swing phases. We find that leg loading feedback to the central pattern generator can contribute to stabilizing pace running with an appropriate cycle autonomously determined by synchronizing each leg’s oscillation with the roll body oscillation without a human specifying the cycle. The experimental results conclude that our proposed neuromorphic controller is beneficial for achieving pace running by a muscle-driven quadruped robot.
Expansion of Image Space in Enhanced-NA Fresnel Holographic Display
Authors: Chae Byung Gyu
Published: April 2022

The enhanced-NA Fresnel hologram reconstructs a holographic image at a viewing angle larger than the diffraction angle of a hologram pixel. The image space is limited by the bandwidth of a digital hologram. In this study, we investigate the property of image formation in the extended image space beyond a diffraction zone. A numerical simulation, using the phase Fresnel hologram, is carried out to observe an extension of image space and the effect of this on the changes in the angular field of view. The phase Fresnel hologram, synthesized by restricting the angular view range to a diffraction angle, can reconstruct a uniform image without high-order noises within the primary viewing zone, which is well confirmed by optical experiments. On the other hand, the overlapping of high-order images is inevitable, when the viewing angle depends on the hologram numerical aperture. In principle, the replica noises in both the hologram and image planes would be removed during the optimization algorithm considering suitable constraints. We discuss the development of a method for expanding the image space, while maintaining the viewing angle of a holographic image.
Verification of Longitudinal Level Irregularity Suppression Effect at the Structural Boundary by Ballasted Ladder Track
Authors: Watanabe Tsutomu , Goto Keiichi , Matsuoka Kodai , Minoura Shintaro
Published: April 2022

The ladder sleeper, which is a type of longitudinal sleeper with long beams in the longitudinal direction of the rail, was developed for the maintenance-labor saving of ballast tracks. In this study, to quantify the load distribution performance of the ladder sleepers at the structural boundary, full-scale model tests were conducted to quantify the vibration transmission reduction effect of the ladder sleepers. Following that, numerical experiments were carried out using a three-dimensional numerical analysis model and it was revealed that the ladder sleeper can reduce the pressure on the sleeper bottom plane by approximately 70% when compared to conventional prestressed concrete sleepers. Furthermore, when laying the ladder sleeper at the structural boundary, it was shown that laying across the structural boundary may be more effective in reducing the pressure on the sleeper bottom plane than laying it in front of the structural boundary. Finally, ladder sleepers were installed on the commercial line and long-term measurements of the longitudinal level irregularity verified the effect of suppressing the longitudinal level irregularity of the ballasted ladder track.
Numerical Voids Detection in Bonded Metal/Composite Assemblies Using Acousto-Ultrasonic Method
Authors: Guo Jialiang , Doitrand Aurélien , Sarr Cheikh , Chataigner Sylvain , Gaillet Laurent , Godin Nathalie
Published: April 2022

This research focuses on the application of an acousto-ultrasonics (AU) technique, a combination of ultrasonic characterization and acoustic emission, to nondestructively detect defects such as voids in bonded metal/composite assemblies. Computational methods are established to examine the effects of voids on the collected signal. The position of the receiver sensor with respect to the defect is also investigated. Given a specific structure and type of actuation signal, the sensor location and probability of detection can be enhanced by the model developed in this work. The defect detection is optimal provided the receiver sensor is located around the epicenter of the defect. Moreover, this work highlights the importance of the choice of reception sensor.
A Practical Approach for the Mitigation of Seismic-Induced Vibrations in Slender Metallic Structures through Magnetorheological Fluid Dampers
Authors: Pecora Rosario
Published: April 2022

The mitigation of seismic-induced vibrations is essential for the effective protection of buildings and occupants during earthquakes. This especially applies to slender buildings with metallic frames; in this case, the structure’s geometrical layout and relatively low damping properties favor an excessive and potentially catastrophic oscillatory response to a seismic event. Semiactive systems for energy dissipation are among the most commonly used strategies to control this oscillatory response. They offer the right balance between the reliability of passive devices and the versatility and adaptability of fully active systems. In this work, a vibration-suppression system based on dissipative bracings that integrate commercial magnetorheological fluid dampers (MRDs) was designed and validated through experimental tests on a true-scale structural model that was representative of a five-story slender building with a metallic frame. A practical and robust approach was proposed for: (1) The definition of the MRD type in compliance with a predefined mitigation target for seismic-induced accelerations on each floor of the structure; (2) The modeling of the MRDs, contribute to the dynamic response of the structural system. The approach involves a linearized formulation of the characteristic damping curves of the MRDs at different values of the activating current. By relying upon this linearization, a rapidly converging iterative process was set up to simulate the seismic response of the structure in the case of activated or deactivated dampers. The reference structure and the vibration-suppression system were then manufactured and tested on a sliding table, which provided realistic seismic excitation. The good correlation levels between the numerical predictions and the experimental measurements proved the effectiveness of the conceived system and of the approaches that were used for its design and simulation.
Use of a DNN-Based Image Translator with Edge Enhancement Technique to Estimate Correspondence between SAR and Optical Images
Authors: Toriya Hisatoshi , Dewan Ashraf , Ikeda Hajime , Owada Narihiro , Saadat Mahdi , Inagaki Fumiaki , Kawamura Youhei , Kitahara Itaru
Published: April 2022

In this paper, the local correspondence between synthetic aperture radar (SAR) images and optical images is proposed using an image feature-based keypoint-matching algorithm. To achieve accurate matching, common image features were obtained at the corresponding locations. Since the appearance of SAR and optical images is different, it was difficult to find similar features to account for geometric corrections. In this work, an image translator, which was built with a DNN (deep neural network) and trained by conditional generative adversarial networks (cGANs) with edge enhancement, was employed to find the corresponding locations between SAR and optical images. When using conventional cGANs, many blurs appear in the translated images and they degrade keypoint-matching accuracy. Therefore, a novel method applying an edge enhancement filter in the cGANs structure was proposed to find the corresponding points between SAR and optical images to accurately register images from different sensors. The results suggested that the proposed method could accurately estimate the corresponding points between SAR and optical images.
Exploration and Research on Key Technologies for Improving the Response Speed of Servo-Hydraulic Cylinders
Authors: Chen Xiaolan , Zheng Feilong , Gan Wenbing , Xing Shixiong
Published: April 2022

The operating efficiency of the hydraulic system depends on the response speed and driving efficiency of the hydraulic components. Seeking various methods and technologies to improve performance and work efficiency is an important work for many scholars. In this paper, the development and performance improvement of four generations of hydraulic cylinders are analyzed to obtain the development of the drag reduction technology by examples such as sealing methods, microtextured hydrodynamic lubrication, manufacturing materials, drive methods, control methods, etc. The reviewed results show that the drag reduction and efficiency improvement of hydraulic cylinders are affected by many factors, and the new drag reduction theories, advanced drag reduction technology, and emerging materials point toward the direction of the acceleration of hydraulic cylinders. Finally, according to the higher requirements for future cylinders, four new ideas are proposed for improving the speed performance of hydraulic cylinders, including new material sealing ring with low friction coefficient or self-lubricating, internal leakage suppression from smart material, implementation of servo control techniques and algorithms, and digital hydraulic technology. These new viewpoints may provide some methods and references for the speed improvement of hydraulic cylinders.