bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Throughput Screening and Characterization of Phenolic Compounds in Stone Fruits Waste by LC-ESI-QTOF-MS/MS and Their Potential Antioxidant Activities
Authors: Hong Yili , Wang Zening , Barrow Colin J. , Dunshea Frank R. , Suleria Hafiz A. R.
Published: February 2021

Stone fruits, including peach (Prunus persica L.), nectarine (Prunus nucipersica L.), plum (Prunus domestica L.) and apricot (Prunus armeniaca L.) are common commercial fruits in the market. However, a huge amount of stone fruits waste is produced throughout the food supply chain during picking, handling, processing, packaging, storage, transportation, retailing and final consumption. These stone fruits waste contain high phenolic content which are the main contributors to the antioxidant potential and associated health benefits. The antioxidant results showed that plum waste contained higher concentrations of total phenolic content (TPC) (0.94 ± 0.07 mg gallic acid equivalents (GAE)/g) and total flavonoid content (TFC) (0.34 ± 0.01 mg quercetin equivalents (QE)/g), while apricot waste contained a higher concentration of total tannin content (TTC) (0.19 ± 0.03 mg catechin equivalents (CE)/g) and DPPH activity (1.47 ± 0.12 mg ascorbic acid equivalents (AAE)/g). However, nectarine waste had higher antioxidant capacity in ferric reducing-antioxidant power (FRAP) (0.98 ± 0.02 mg AAE/g) and total antioxidant capacity (TAC) (0.91 ± 0.09 mg AAE/g) assays, while peach waste showed higher antioxidant capacity in 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) assay (0.43 ± 0.09 mg AAE/g) as compared to other stone fruits waste. Qualitative and quantitative phenolic analysis of Australian grown stone fruits waste were conducted by liquid chromatography coupled with electrospray-ionization quadrupole time-of-flight mass spectrometry (LC-ESI-QTOF-MS/MS) and HPLC-photodiode array detection (PDA). The LC-ESI-QTOF-MS/MS result indicates that 59 phenolic compounds were tentatively characterized in peach (33 compounds), nectarine (28), plum (38) and apricot (23). The HPLC-PDA indicated that p-hydroxybenzoic acid (18.64 ± 1.30 mg/g) was detected to be the most dominant phenolic acid and quercetin (19.68 ± 1.38 mg/g) was the most significant flavonoid in stone fruits waste. Hence, it could be concluded that stone fruit waste contains various phenolic compounds and have antioxidant potential. The results could support the applications of these stone fruit wastes in other food, feed, nutraceutical and pharmaceutical industries.
Coenzyme Q10 Analogues: Benefits and Challenges for Therapeutics
Authors: Suárez-Rivero Juan M. , Pastor-Maldonado Carmen J. , Povea-Cabello Suleva , Álvarez-Córdoba Mónica , Villalón-García Irene , Munuera-Cabeza Manuel , Suárez-Carrillo Alejandra , Talaverón-Rey Marta , Sánchez-Alcázar José A.
Published: February 2021

Coenzyme Q10 (CoQ10 or ubiquinone) is a mobile proton and electron carrier of the mitochondrial respiratory chain with antioxidant properties widely used as an antiaging health supplement and to relieve the symptoms of many pathological conditions associated with mitochondrial dysfunction. Even though the hegemony of CoQ10 in the context of antioxidant-based treatments is undeniable, the future primacy of this quinone is hindered by the promising features of its numerous analogues. Despite the unimpeachable performance of CoQ10 therapies, problems associated with their administration and intraorganismal delivery has led clinicians and scientists to search for alternative derivative molecules. Over the past few years, a wide variety of CoQ10 analogues with improved properties have been developed. These analogues conserve the antioxidant features of CoQ10 but present upgraded characteristics such as water solubility or enhanced mitochondrial accumulation. Moreover, recent studies have proven that some of these analogues might even outperform CoQ10 in the treatment of certain specific diseases. The aim of this review is to provide detailed information about these Coenzyme Q10 analogues, as well as their functionality and medical applications.
Oxidative Stress and the Role of NADPH Oxidase in Glaucoma
Authors: Fan Gaskin Jennifer C. , Shah Manisha H. , Chan Elsa C.
Published: February 2021

Glaucoma is characterised by loss of retinal ganglion cells, and their axons and many pathophysiological processes are postulated to be involved. It is increasingly understood that not one pathway underlies glaucoma aetiology, but rather they occur as a continuum that ultimately results in the apoptosis of retinal ganglion cells. Oxidative stress is recognised as an important mechanism of cell death in many neurodegenerative diseases, including glaucoma. NADPH oxidase (NOX) are enzymes that are widely expressed in vascular and non-vascular cells, and they are unique in that they primarily produce reactive oxygen species (ROS). There is mounting evidence that NOX are an important source of ROS and oxidative stress in glaucoma and other retinal diseases. This review aims to provide a perspective on the complex role of oxidative stress in glaucoma, in particular how NOX expression may influence glaucoma pathogenesis as illustrated by different experimental models of glaucoma and highlights potential therapeutic targets that may offer a novel treatment option to glaucoma patients.
Advances in Material Wide Range Temperature Determination by Dual-Color Emissivity Free Methodology in Long-Mid-near Infrared Ranges at Non-stationary Conditions
Authors: De Cesare Mario , Savino Luigi , Del Vecchio Antonio , Di Carolo Francesca , Musto Marilena , Galietti Umberto , Rotondo Giuseppe
Published: February 2021

Dual color emissivity free methodology by thermography allows to obtain 2D (two-dimensional) temperature maps by using local grey body hypotheses and narrowband filters. By using a suitable pair of filters is possible to obtain the ratio between two thermal camera input signals that depend only on the temperature and not on the emissive properties of the investigated surface. The aim of this concise review paper is to summarize and discuss the developments and applications from long- to mid-near infrared ranges and in a wide range of temperature values of the dual-color thermographic technique that has been analysed through the use of an analytical model based on the integration of Planck’s law and attenuated with the transmission curves of sensors, optics, filters, and attenuators during the last years. Moreover, the applicability to the non-stationary temperature conditions and finalized to the materials mainly used in the aerospace plasma wind tunnel (PWT) re-entry are shown.
A Deeper Look at Sheet Music Composer Classification Using Self-Supervised Pretraining
Authors: Yang Daniel , Ji Kevin , Tsai TJ
Published: February 2021

This article studies a composer style classification task based on raw sheet music images. While previous works on composer recognition have relied exclusively on supervised learning, we explore the use of self-supervised pretraining methods that have been recently developed for natural language processing. We first convert sheet music images to sequences of musical words, train a language model on a large set of unlabeled musical “sentences”, initialize a classifier with the pretrained language model weights, and then finetune the classifier on a small set of labeled data. We conduct extensive experiments on International Music Score Library Project (IMSLP) piano data using a range of modern language model architectures. We show that pretraining substantially improves classification performance and that Transformer-based architectures perform best. We also introduce two data augmentation strategies and present evidence that the model learns generalizable and semantically meaningful information.
Special Issue “Advanced Phase Change Materials for Thermal Storage”
Authors: Bayón Rocío
Published: February 2021

Thermal energy storage using phase change materials (PCMs) is a research topic that has attracted much attention in recent decades [...]
Non-Invasive Measurement, Mathematical Simulation and In Situ Detection of Biofilm Evolution in Porous Media: A Review
Authors: Zhang Yajun , Xu Aoshu , Lv Xin , Wang Qian , Feng Caihui , Lin Jun
Published: February 2021

The development of biofilms and the related changes in porous media in the subsurface cannot be directly observed and evaluated. The primary reason that the mechanism of biofilm clogging in porous media cannot be clearly demonstrated is due to the opacity and structural complexity of three-dimensional pore space. Interest in exploring methods to overcome this limitation has been increasing. In the first part of this review, we introduce the underlying characteristics of biofilm in porous media. Then, we summarize two approaches, non-invasive measurement methods and mathematical simulation strategies, for studying fluid–biofilm–porous medium interaction with spatiotemporal resolution. We also discuss the advantages and limitations of these approaches. Lastly, we provide a perspective on opportunities for in situ monitoring at the field site.
Effect of Pd Ions on the Generation of Ag and Au Heterogeneous Nanoparticles Using Laser Ablation in Liquid
Authors: Yoon Sangwoo , Yoo Kye Sang , Kim Joohan
Published: February 2021

Heterogeneous Ag/Au nanoparticles combined with Pd ions were generated by irradiating Ag/Au metal targets in a Pd solution with nanosecond and femtosecond lasers. AgPd and AuPd nanoparticles were generated by laser fragmentation and bonded. We numerically analyzed the hot spots with electromagnetic field enhancement of nanoparticles of different sizes separated by various distances. AgPd and AuPd nanoparticles differing in diameter were generated and showed different characteristics compared to typical core-shell heterogeneous nanoparticles. Pd ions played an important role in the generation of nanoparticles in liquid via laser ablation. The femtosecond laser produced both pure and heterogeneous nanoparticles of uniform size. The nanosecond laser produced pure nanoparticles with a relatively non-uniform size, which developed into spherical heterogeneous nanoparticles with a uniform (small) size in the presence of Pd ions. These nanoparticles could optimize applications such as photothermal therapy and catalysis.
Statistical Uncertainty of DNS in Geometries without Homogeneous Directions
Authors: Oder Jure , Flageul Cédric , Tiselj Iztok
Published: February 2021

In this paper, we present uncertainties of statistical quantities of direct numerical simulations (DNS) with small numerical errors. The uncertainties are analysed for channel flow and a flow separation case in a confined backward facing step (BFS) geometry. The infinite channel flow case has two homogeneous directions and this is usually exploited to speed-up the convergence of the results. As we show, such a procedure reduces statistical uncertainties of the results by up to an order of magnitude. This effect is strongest in the near wall regions. In the case of flow over a confined BFS, there are no such directions and thus very long integration times are required. The individual statistical quantities converge with the square root of time integration so, in order to improve the uncertainty by a factor of two, the simulation has to be prolonged by a factor of four. We provide an estimator that can be used to evaluate a priori the DNS relative statistical uncertainties from results obtained with a Reynolds Averaged Navier Stokes simulation. In the DNS, the estimator can be used to predict the averaging time and with it the simulation time required to achieve a certain relative statistical uncertainty of results. For accurate evaluation of averages and their uncertainties, it is not required to use every time step of the DNS. We observe that statistical uncertainty of the results is uninfluenced by reducing the number of samples to the point where the period between two consecutive samples measured in Courant–Friedrichss–Levy (CFL) condition units is below one. Nevertheless, crossing this limit, the estimates of uncertainties start to exhibit significant growth.
Evolutionary Analysis of the Acoustics of the Baroque Church of San Luis de los Franceses (Seville)
Authors: Alberdi Enedina , Galindo Miguel , León-Rodríguez Ángel L.
Published: February 2021

In the 16th century the Society of Jesus built a large number of churches following the Tridentine model of a Latin cross and a single nave. However, the shift towards this model did not entail the abandonment of the central floor plan, especially in the 17th century. The acoustics of these spaces can present phenomena linked to focalizations which increase the sound pressure level. The church of San Luis de los Franceses, built by the Jesuits for their novitiate in Seville (Spain), is an example of a Baroque church with a central floor plan. Although the church has hosted different congregations since its inauguration it is currently desacralized and used for theatres and concerts. The acoustics of this church were studied by the authors through in situ measurements and virtual models. The main objective was to analyse the evolution and perception of its sound field from the 18th to 21st centuries, considering the different audience distributions and sound sources and the modifications in furniture and coatings. Analysis of the evolution of its sound field shows that the characteristics have remained stable, with a notable influence of the dome on the results for the different configurations studied.
Deep Learning Sensor Fusion in Plant Water Stress Assessment: A Comprehensive Review
Authors: Kamarudin Mohd Hider , Ismail Zool Hilmi , Saidi Noor Baity
Published: February 2021

Water stress is one of the major challenges to food security, causing a significant economic loss for the nation as well for growers. Accurate assessment of water stress will enhance agricultural productivity through optimization of plant water usage, maximizing plant breeding strategies, and preventing forest wildfire for better ecosystem management. Recent advancements in sensor technologies have enabled high-throughput, non-contact, and cost-efficient plant water stress assessment through intelligence system modeling. The advanced deep learning sensor fusion technique has been reported to improve the performance of the machine learning application for processing the collected sensory data. This paper extensively reviews the state-of-the-art methods for plant water stress assessment that utilized the deep learning sensor fusion approach in their application, together with future prospects and challenges of the application domain. Notably, 37 deep learning solutions fell under six main areas, namely soil moisture estimation, soil water modelling, evapotranspiration estimation, evapotranspiration forecasting, plant water status estimation and plant water stress identification. Basically, there are eight deep learning solutions compiled for the 3D-dimensional data and plant varieties challenge, including unbalanced data that occurred due to isohydric plants, and the effect of variations that occur within the same species but cultivated from different locations.
A Scheme for Controlled Cyclic Asymmetric Remote State Preparation in Noisy Environment
Authors: Zhao Nan , Wu Tingting , Yu Yan , Pei Changxing
Published: February 2021

As research on quantum computers and quantum information transmission deepens, the multi-particle and multi-mode quantum information transmission has been attracting increasing attention. For scenarios where multi-parties transmit sequentially increasing qubits, we put forward a novel (N + 1)-party cyclic remote state preparation (RSP) protocol among an arbitrary number of players and a controller. Specifically, we employ a four-party scheme in the case of a cyclic asymmetric remote state preparation scheme and demonstrate the feasibility of the scheme on the IBM Quantum Experience platform. Furthermore, we present a general quantum channel expression under different circulation directions based on the n-party. In addition, considering the impact of the actual environment in the scheme, we discuss the feasibility of the scheme affected by different noises.
PFDA-FMEA, an Integrated Method Improving FMEA Assessment in Product Design
Authors: García Aguirre Pedro Angel , Pérez-Domínguez Luis , Luviano-Cruz David , Solano Noriega Jesús Jaime , Martínez Gómez Erwin , Callejas-Cuervo Mauro
Published: February 2021

Product Design (PD) currently faces challenges in new product development, since the industry is in a rush to introduce new products into the market, with customers demanding products that are faster, cheaper, and free from failure. In addition, global companies are trying to improve their product design risk assessment process to gain advantages over competitors, using proven tools like Failure Mode and Effect Analysis (FMEA) and mixing risk assessment methods. However, with current risks assessment tools and a combination of other methods, there is the opportunity to improve risk analysis. This document aims to reveal a novel integrated method, where FMEA, Pythagorean Fuzzy Sets (PFS), and Dimensional Analysis (DA) are cohesive in one model. The proposed method provides an effective technique to identify risks and remove uncertainty and vagueness of human intervention during risk assessment using the Failure Mode and Effect Analysis method. A real-life problem was carried out to illustrate the proposed method. Finally, the study was substantiated by using a correlation and sensitivity analysis, demonstrating the presented integrated method’s usefulness in decision-making and problem-solving.
Design and Validation of Disturbance Rejection Dynamic Inverse Control for a Tailless Aircraft in Wind Tunnel
Authors: Nie Bowen , Liu Zhitao , Guo Tianhao , Fan Litao , Ma Hongxu , Sename Olivier
Published: February 2021

This paper focuses on the design of a disturbance rejection controller for a tailless aircraft based on the technique of nonlinear dynamic inversion (NDI). The tailless aircraft model mounted on a three degree-of-freedom (3-DOF) dynamic rig in the wind tunnel is modeled as a nonlinear affine system subject to mismatched disturbances. First of all, a baseline NDI attitude controller is designed for sufficient stability and good reference tracking performance of the nominal system. Then, a nonlinear disturbance observer (NDO) is supplemented to the baseline NDI controller to estimate the lumped disturbances for compensation, including unmodeled dynamics, parameter uncertainties, and external disturbances. Mathematical analysis demonstrates the convergence of the employed NDO and the resulting closed-loop system. Furthermore, an anti-windup modification is applied to the NDO for control performance preserving in the presence of actuator saturation. Subsequently, the designed control schemes are preliminarily validated and compared via simulations. The baseline NDI controller demonstrates satisfactory attitude tracking performance in the case of nominal simulation; the NDO augmented NDI controller presents significantly improved ability of disturbance rejection when compared with the baseline NDI controller in the case of robust simulation; the anti-windup modified scheme, rather than the baseline NDI controller nor the NDO augmented NDI controller, can preserve the closed-loop performance in the case of actuator saturation. Finally, the baseline NDI scheme and the NDO augmented NDI scheme are implemented and further validated in the wind tunnel flight tests, which demonstrate that the experimental results are in good agreement with that of the simulations.
Effects of Landscape Features on the Roadside Soil Heavy Metal Distribution in a Tropical Area in Southwest China
Authors: Dong Yuhong , Liu Shiliang , Sun Yongxiu , Liu Yixuan , Wang Fangfang
Published: February 2021

Soil heavy metals along roadsides pose a great threat to ecosystems while their spatial variations and influencing factors still remain unclear in some regions, especially in tropical areas with complex landscape characteristics. Our study was carried out to determine how the land use, vegetation characteristics, topographical factors and distance to the road affect the soil heavy metal distribution. Taking Jinghong county in Yunnan Province, Southwest China as a case, soil samples were collected at different distances off roads and canonical correspondence analysis (CCA) methods were used to determine the relative importance of different factors. Our results showed that heavy metal sources were obtained mainly from the road, based on the principle component analysis (PCA) identification. There were no obvious trends of soil quality index (SQI) with distance to the road in natural soils, while SQI nutrients and SQI metals in farmlands had a decreasing and increasing trend, respectively, which could both be expressed by logarithm models. However, soil properties showed little differences for road levels while they showed significant differences under land use types. The CCA further showed that heavy metal variations in natural soils were jointly affected by distance, plant coverage, relative elevation and soil properties in decreasing order.
Comparison of Three Approaches to Assess the Flavour Characteristics of Scotch Whisky Spirit
Authors: Daute Martina , Jack Frances , Baxter Irene , Harrison Barry , Grigor John , Walker Graeme
Published: February 2021

This study compared the use of three sensory and analytical techniques: Quantitative Descriptive Analysis (QDA), Napping, and Gas Chromatography-Mass Spectrometry (GC-MS) for the assessment of flavour in nine unmatured whisky spirits produced using different yeasts. Hierarchical Multiple Factor Analysis (HMFA) showed a similar pattern of sample discrimination (RV scores: 0.895–0.927) across the techniques: spirits were mostly separated by their Alcohol by Volume (ABV). Low ABV spirits tended to have heavier flavour characteristics (feinty, cereal, sour, oily, sulphury) than high ABV spirits, which were lighter in character (fruity, sweet, floral, solventy, soapy). QDA differentiated best between low ABV spirits and GC-MS between high ABV spirits, with Napping having the lowest resolution. QDA was time-consuming but provided quantitative flavour profiles of each spirit that could be readily compared. Napping, although quicker, gave an overview of the flavour differences of the spirits, while GC-MS provided semi-quantitative ratios of 96 flavour compounds for differentiating between spirits. Ester, arenes and certain alcohols were found in higher concentrations in high ABV spirits and other alcohols and aldehydes in low ABV spirits. The most comprehensive insights on spirit flavour differences produced by different yeast strains are obtained through the application of a combination of approaches.
A Drone-Enabled Approach for Gas Leak Detection Using Optical Flow Analysis
Authors: Nooralishahi Parham , López Fernando , Maldague Xavier
Published: February 2021

The recent development of gas imaging technologies has raised a growing interest for various applications. Gas imaging can significantly enhance functional safety by early detection of hazardous gas leaks. Moreover, optical gas imaging technologies can be used to identify possible gas leakages and to investigate the amount of gas emission in industrial sites, which is essential, primarily based on current efforts to decrease greenhouse gas emissions all around the world. Therefore, exploring the solutions for automating the inspection process can persuade industries for more regular tests and monitoring. One of the main challenges in gas imaging is the proximity condition required for data to be more reliable for analysis. Therefore, the use of unmanned aerial vehicles can be very advantageous as they can provide significant access due to their maneuver capabilities. Despite the advantages of using drones, their movements and sudden motions during hovering can diminish data usability. In this paper, we propose a method for gas leak detection and visually-enhancement of gas emanation involving stabilization and gas leak detection steps. In addition, a comparative analysis of candidate stabilization techniques is conducted to find the most suitable technique for the drone-based application. Moreover, the system is evaluated using three experiments respectively on an isolated environment, a real scenario, and a drone-based inspection.
The Reproduction and Evaluation of Star Fields with the Milky Way in a Planetarium
Authors: Tanaka Midori , Otani Ken’ichi , Setoguchi Saori , Horiuchi Takahiko
Published: February 2021

In this study, we investigated the physical factors required to accurately reproduce the Milky Way in star fields in a planetarium using three evaluation indices: faithfulness, preference, and depth feeling. Psychometric experiments were conducted by manipulating three different physical factors (transmittance, representation size and star density) of the stars projected on a dome screen as experimental stimuli. The three evaluation indices were rated by observers for 12 different reproductions of the Milky Way. By analyzing the experimental results, we developed a common model to estimate the scores for each evaluation index by changing the coefficients of the three physical factors. Our proposed model has good accuracy, and each evaluation index can be represented by transmittance, representation size and star density. The weighting values indicate that density reproduction was the pivotal factor for the majority of observers. In contrast, the observers were not affected by the size of the stars in the projected Milky Way.
Classification of Plant Electrophysiology Signals for Detection of Spider Mites Infestation in Tomatoes
Authors: Najdenovska Elena , Dutoit Fabien , Tran Daniel , Plummer Carrol , Wallbridge Nigel , Camps Cédric , Raileanu Laura Elena
Published: February 2021

Herbivorous arthropods, such as spider mites, are one of the major causes of annual crop losses. They are usually hard to spot before a severe infestation takes place. When feeding, these insects cause external perturbation that triggers changes in the underlying physiological process of a plant, which are expressed by a generation of distinct variations of electrical potential. Therefore, plant electrophysiology data portray information of the plant state. Analyses involving machine learning techniques applied to plant electrical response triggered by spider mite infestation have not been previously reported. This study investigates plant electrophysiological signals recorded from 12 commercial tomatoes plants contaminated with spider mites and proposes a workflow based on Gradient Boosted Tree algorithm for an automated differentiation of the plant’s normal state from the stressed state caused by infestation. The classification model built using the signal samples recorded during daylight and employing a reduced feature subset performs with an accuracy of 80% in identifying the plant’s stressed state. Furthermore, the Hjorth complexity encloses the most relevant information for discrimination of the plant status. The obtained findings open novel access towards automated detection of insect infestation in greenhouse crops and, consequently, more optimal prevention and treatment approaches.
Direct Observation of Terahertz Frequency Comb Generation in Difference-Frequency Quantum Cascade Lasers
Authors: Consolino Luigi , Nafa Malik , De Regis Michele , Cappelli Francesco , Bartalini Saverio , Ito Akio , Hitaka Masahiro , Dougakiuchi Tatsuo , Edamura Tadataka , De Natale Paolo , Fujita Kazuue
Published: February 2021

Terahertz quantum cascade laser sources based on intra-cavity difference frequency generation from mid-IR devices are an important asset for applications in rotational molecular spectroscopy and sensing, being the only electrically pumped device able to operate in the 0.6–6 THz range without the need of bulky and expensive liquid helium cooling. Here we present comb operation obtained by intra-cavity mixing of a distributed feedback laser at λ = 6.5 μm and a Fabry–Pérot device at around λ = 6.9 μm. The resulting ultra-broadband THz emission extends from 1.8 to 3.3 THz, with a total output power of 8 μW at 78 K. The THz emission has been characterized by multi-heterodyne detection with a primary frequency standard referenced THz comb, obtained by optical rectification of near infrared pulses. The down-converted beatnotes, simultaneously acquired, confirm an equally spaced THz emission down to 1 MHz accuracy. In the future, this setup can be used for Fourier transform based evaluation of the phase relation among the emitted THz modes, paving the way to room-temperature, compact, and field-deployable metrological grade THz frequency combs.
Predicting Student Academic Performance by Means of Associative Classification
Authors: Cagliero Luca , Canale Lorenzo , Farinetti Laura , Baralis Elena , Venuto Enrico
Published: February 2021

The Learning Analytics community has recently paid particular attention to early predict learners’ performance. An established approach entails training classification models from past learner-related data in order to predict the exam success rate of a student well before the end of the course. Early predictions allow teachers to put in place targeted actions, e.g., supporting at-risk students to avoid exam failures or course dropouts. Although several machine learning and data mining solutions have been proposed to learn accurate predictors from past data, the interpretability and explainability of the best performing models is often limited. Therefore, in most cases, the reasons behind classifiers’ decisions remain unclear. This paper proposes an Explainable Learning Analytics solution to analyze learner-generated data acquired by our technical university, which relies on a blended learning model. It adopts classification techniques to early predict the success rate of about 5000 students who were enrolled in the first year courses of our university. It proposes to apply associative classifiers at different time points and to explore the characteristics of the models that led to assign pass or fail success rates. Thanks to their inherent interpretability, associative models can be manually explored by domain experts with the twofold aim at validating classifier outcomes through local rule-based explanations and identifying at-risk/successful student profiles by interpreting the global rule-based model. The results of an in-depth empirical evaluation demonstrate that associative models (i) perform as good as the best performing classification models, and (ii) give relevant insights into the per-student success rate assignments.
Essential Oils as Alternatives for Root-Canal Treatment and Infection Control against Enterococcus faecalis—A Preliminary Study
Authors: Nagy-Bota Monica Cristina , Man Adrian , Santacroce Luigi , Brinzaniuc Klara , Pap Zsuzsanna , Pacurar Mariana , Pribac Mirela , Ciurea Cristina Nicoleta , Pintea-Simon Ionela Anca , Kovacs Monika
Published: February 2021

Since natural alternatives are needed in dentistry for the treatment of root canal, where the standard irrigant is NaOCl with significant toxicity, the aim of the study was to assess the antibacterial properties of non-chemical root-canal irrigants (aqueous extracts of oregano, thyme, lemongrass, melaleuca and clove essential oils) against Enterococcus faecalis. For this, aqueous extracts of each essential oil (AqEO) were prepared. A solution of sodium hypochlorite (NaOCl) was used as a positive standard against which the antimicrobial effects of AqEO could be reported. The root canals of seven teeth were inoculated with 20 µL of Enterococcus faecalis ATCC29212 inoculum and incubated overnight at 37 °C. All the teeth canals were instrumented and were irrigated with the corresponding AqEO, NaOCl and saline solution, then rinsed with saline. Bacteriological samples for each canal post-instrumentation were collected with sterile paper points which were inoculated on culture media. A second processing followed the same methodology but involved only irrigation and no instrumentation. Using instrumentation, thyme and clove completely inhibited Enterococcus faecalis growth. Without instrumentation, clove and oregano AqEOs completely reduced the bacterial load as seen in direct inoculation, but bacterial growth was observed in all the samples after enrichment, except for NaOCl. Nevertheless, the turbidity of the enrichment media was lower for the samples irrigated with AqEOs than for control. In conclusion, AqEOs of thyme, oregano and clove showed a promising antibacterial effect, especially when teeth instrumentation was performed.
Optimal Renovation Strategies through Life-Cycle Analysis in a Pilot Building Located in a Mild Mediterranean Climate
Authors: Salmerón Lissen José Manuel , Jareño Escudero Cristina Isabel , Sánchez de la Flor Francisco José , Escudero Miriam Navarro , Karlessi Theoni , Assimakopoulos Margarita-Niki
Published: February 2021

The 2030 climate and energy framework includes EU-wide targets and policy objectives for the period 2021–2030 of (1) at least 55% cuts in greenhouse gas emissions (from 1990 levels); (2) at least 32% share for renewable energy; and (3) at least 32.5% improvement in energy efficiency. In this context, the methodology of the cost-optimal level from the life-cycle cost approach has been applied to calculate the cost of renovating the existing building stock in Europe. The aim of this research is to analyze a pilot building using the cost-optimal methodology to determine the renovation measures that lead to the lowest life-cycle cost during the estimated economic life of the building. The case under study is an apartment building located in a mild Mediterranean climate (Castellon, SP). A package of 12 optimal solutions has been obtained to show the importance of the choice of the elements and systems for renovating building envelopes and how energy and economic aspects influence this choice. Simulations have shown that these packages of optimal solutions (different configurations for the building envelope, thermal bridges, airtightness and ventilation, and domestic hot water production systems) can provide savings in the primary energy consumption of up to 60%.
Does Two-Class Training Extract Real Features? A COVID-19 Case Study
Authors: Muñoz-Saavedra Luis , Civit-Masot Javier , Luna-Perejón Francisco , Domínguez-Morales Manuel , Civit Antón
Published: February 2021

Diagnosis aid systems that use image analysis are currently very useful due to the large workload of health professionals involved in making diagnoses. In recent years, Convolutional Neural Networks (CNNs) have been used to help in these tasks. For this reason, multiple studies that analyze the detection precision for several diseases have been developed. However, many of these works distinguish between only two classes: healthy and with a specific disease. Based on this premise, in this work, we try to answer the questions: When training an image classification system with only two classes (healthy and sick), does this system extract the specific features of this disease, or does it only obtain the features that differentiate it from a healthy patient? Trying to answer these questions, we analyze the particular case of COVID-19 detection. Many works that classify this disease using X-ray images have been published; some of them use two classes (with and without COVID-19), while others include more classes (pneumonia, SARS, influenza, etc.). In this work, we carry out several classification studies with two classes, using test images that do not belong to those classes, in order to try to answer the previous questions. The first studies indicate problems in these two-class systems when using a third class as a test, being classified inconsistently. Deeper studies show that deep learning systems trained with two classes do not correctly extract the characteristics of pathologies, but rather differentiate the classes based on the physical characteristics of the images. After the discussion, we conclude that these two-class trained deep learning systems are not valid if there are other diseases that cause similar symptoms.
3D Numerical Modeling of Rigid Inclusion-Improved Soft Soils Under Monotonic and Cyclic Loading—Case of a Small-Scale Laboratory Experiment
Authors: Van Pham Hung , Dias Daniel
Published: February 2021

This paper is based on small-scale laboratory tests (1:10) of a rigid inclusion-improved soil under normal gravity. A low area improvement ratio (2.4%) under monotonic and cyclic loading was used. 3D numerical calculations are performed to model these tests. The proposed numerical modeling is performed by the finite element method (FEM) using the ABAQUS software. A representative elementary volume model is suggested for reducing the calculation time. A hypoplastic constitutive model (HYP model) is applied for the load transfer platform (LTP). A total of three geometrical configuration cases of the experimental tests are numerically considered including a rigid slab over a mattress of 100 mm on the reinforced soil, a mattress of 100 mm on the reinforced soil, and a rigid slab over a mattress of 50 mm on the reinforced soil. The proposed numerical results are compared to the experimental data and the previous numerical results of Houda. The cyclic response of the systems is shown in terms of soil arching and settlements. The decrease in pile efficacy and the cumulative settlements are exhibited. The HYP model allows to better simulate the soil arching mechanisms inside the LTP than the CYsoil model used in the Houda’s research work. A good concordance between the proposed numerical results and the experimental data was obtained.
Impact of Disabled Driver’s Mass Center Location on Biomechanical Parameters during Crash
Authors: Sybilski Kamil , Małachowski Jerzy
Published: February 2021

Adapting a car for a disable person involves adding additional equipment to compensate for the driver’s disability. During this process, the change in the driver’s position and kinematics and their impact on safety levels during crash is not considered. There is also a lack of studies in the literature on this problem. This paper describes a methodology for conducting a study of the behavior of a disabled driver during a crash using the finite element method, based on an explicit time integration method. A validated car model and a commercial dummy model were used. The results show that the use of a handle on the steering wheel and a hand control unit causes dangerous lateral displacements relative to the seat. Amputation of the left leg or right arm causes significant shoulder rotations, amputation of the left leg causes increased thoracic loads. Amputation or additional equipment have no significant impact on head injuries.
Accelerated Climate Changes in Weddell Sea Region of Antarctica Detected by Extreme Values Theory
Authors: Prete Giuseppe , Capparelli Vincenzo , Lepreti Fabio , Carbone Vincenzo
Published: February 2021

On 13 February 2020, The Guardian, followed by many other newspapers and websites, published the news that on 9 February 2020, Antarctic air temperatures rose to about 20.75 ∘C in a base logged at Seymour Island. This value has not yet been validated by the WMO (World Meteorological Organization), but it is not the first time that an extreme temperature was registered in these locations. The recorded temperatures have often been described as “abnormal and anomalous”, according to a statement made by scientists working at the Antarctic bases. Since polar regions have shown the most rapid rates of climate change in recent years, this abnormality is of primary interest in the context of vulnerability of the Antarctic to climate changes. Using data detected at different Antarctic bases, we investigate yearly maxima and minima of recorded temperatures, in order to establish whether they can be considered as usual extreme events or abnormal. We found evidence for disagreement with the extreme values theory, indicating accelerated climate changes in the Antarctic, that is, a local warming rate that is much faster than global averages.
Impact of Urbanization on Sunshine Duration from 1987 to 2016 in Hangzhou City, China
Authors: Jin Kai , Qin Peng , Liu Chunxia , Zong Quanli , Wang Shaoxia
Published: February 2021

Worldwide solar dimming from the 1960s to the 1980s has been widely recognized, but the occurrence of solar brightening since the late 1980s is still under debate—particularly in China. This study aims to properly examine the biases of urbanization in the observed sunshine duration series from 1987 to 2016 and explore the related driving factors based on five meteorological stations around Hangzhou City, China. The results inferred a weak and insignificant decreasing trend in annual mean sunshine duration (−0.09 h/d decade−1) from 1987 to 2016 in the Hangzhou region, indicating a solar dimming tendency. However, large differences in sunshine duration changes between rural, suburban, and urban stations were observed on the annual, seasonal, and monthly scales, which can be attributed to the varied urbanization effects. Using rural stations as a baseline, we found evident urbanization effects on the annual mean sunshine duration series at urban and suburban stations—particularly in the period of 2002–2016. The effects of urbanization on the annual mean sunshine duration trends during 1987−2016 were estimated to be −0.16 and −0.35 h/d decade−1 at suburban and urban stations, respectively. For urban stations, the strongest urbanization effect was observed in summer (−0.46 h/d decade−1) on the seasonal scale and in June (−0.63 h/d decade−1) on the monthly scale. The notable negative impact of urbanization on local solar radiation changes was closely related to the changes in anthropogenic pollutions, which largely reduced the estimations of solar radiation trends in the Hangzhou region. This result highlights the necessity to carefully consider urbanization impacts when analyzing the trend in regional solar radiation and designing cities for sustainable development.
Responses of Forest Carbon Cycle to Drought and Elevated CO2
Authors: Xiao Jun-Lan , Zeng Feng , He Qiu-Lan , Yao Yu-Xia , Han Xiao , Shi Wei-Yu
Published: February 2021

Forests play a pivotal role in mitigating global warming as an important carbon sink. Recent global greening trends reflect a positive influence of elevated atmospheric CO2 on terrestrial carbon uptake. However, increasingly frequent and intense drought events endanger the carbon sequestration function of forests. This review integrates previous studies across scales to identify potential global trends in forest responses to drought and elevated CO2 as well as to identify data needs in this important research field. The inconsistent responses of ecosystem respiration to drought contributes to the change of forest net CO2 exchange, which depends on the balance of opposite effects of warming and water stress on respiration. Whether CO2 fertilization can offset the effects of drought remains controversial, however, we found a potential overestimation of global CO2 fertilization effects because of increasing water stress and other limitations such as light and nutrients (N, P) as well as the possibility of photosynthetic acclimation.
Mechanisms for Springtime Onset of Isolated Precipitation across the Southeastern United States
Authors: Ferreira Rosana Nieto , Rickenbach Thomas M.
Published: February 2021

This study uses four-year radar-based precipitation organization and reanalysis datasets to study the mechanisms that lead to the abrupt springtime onset of precipitation associated with isolated storms in the Southeast United States (SE US). Although the SE US receives relatively constant precipitation year-round, previous work demonstrated a “hidden” summertime maximum in isolated precipitation features (IPF) whose annual cycle resembles that of monsoon climates in the subtropics. In the SE US, IPF rain abruptly ramps up in May and lasts until sometime between late August and early October. This study suggests that the onset of the IPF season in the SE US is brought about by a combination of slow thermodynamic processes and fast dynamic triggers, as follows. First, in the weeks prior to IPF onset, a gradual seasonal build-up of convective available potential energy (CAPE) occurs in the Gulf of Mexico. Then, in one-to-two pentads prior to onset, the upper-tropospheric jet stream shifts northward, favoring the presence of slow-moving frontal systems in the SE US. This poleward shift in the jet stream location in turn allows the establishment of the North Atlantic subtropical high western ridge over the SE US which, with associated poleward transport of high CAPE air from the Gulf of Mexico, leads to the establishment of the warm-season regime of IPF precipitation in the SE US.
Analyzing the Probability of Acquiring Cloud-Free Imagery in China with AVHRR Cloud Mask Data
Authors: Wu Yingjie , Fang Shibo , Xu Yi , Wang Lei , Li Xuan , Pei Zhifang , Wu Dong
Published: February 2021

Optical remote sensing data are used widely in many fields (such as agriculture, resource management and the environment), especially for the vast territory of China; however, the application of these data is usually limited by clouds. Although it is valuable to analyze the probability of acquiring cloud-free imagery (PACI), PACI using different sensors at the pixel level across China has not been reported. In this study, the PACI of China was calculated with daily Advanced Very High Resolution Radiometer (AVHRR) cloud mask data from 1990 to 2019. The results showed that (1) PACI varies dramatically in different regions and months in China. The value was larger in autumn and winter, and the largest figure reached 49.55% in October in Inner Mongolia (NM). In contrast, relatively small values occurred in summer, and the minimum value (5.26%) occurred in June in South China (SC). (2) As the climate changes, the PACI has increased significantly throughout the country and most regions, especially in North China (NC), with a growth rate of 1.9% per decade. The results can be used as a reference for selecting appropriate optical sensors and observation times in areas of interest.
Multi-Scale Ionospheric Anomalies Monitoring and Spatio-Temporal Analysis during Intense Storm
Authors: Cheng Na , Song Shuli , Li Wei
Published: February 2021

The ionosphere is a significant component of the geospace environment. Storm-induced ionospheric anomalies severely affect the performance of Global Navigation Satellite System (GNSS) Positioning, Navigation, and Timing (PNT) and human space activities, e.g., the Earth observation, deep space exploration, and space weather monitoring and prediction. In this study, we present and discuss the multi-scale ionospheric anomalies monitoring over China using the GNSS observations from the Crustal Movement Observation Network of China (CMONOC) during the 2015 St. Patrick’s Day storm. Total Electron Content (TEC), Ionospheric Electron Density (IED), and the ionospheric disturbance index are used to monitor the storm-induced ionospheric anomalies. This study finally reveals the occurrence of the large-scale ionospheric storms and small-scale ionospheric scintillation during the storm. The results show that this magnetic storm was accompanied by a positive phase and a negative phase ionospheric storm. At the beginning of the main phase of the magnetic storm, both TEC and IED were significantly enhanced. There was long-duration depletion in the topside ionospheric TEC during the recovery phase of the storm. This study also reveals the response and variations in regional ionosphere scintillation. The Rate of the TEC Index (ROTI) was exploited to investigate the ionospheric scintillation and compared with the temporal dynamics of vertical TEC. The analysis of the ROTI proved these storm-induced TEC depletions, which suppressed the occurrence of the ionospheric scintillation. To improve the spatial resolution for ionospheric anomalies monitoring, the regional Three-Dimensional (3D) ionospheric model is reconstructed by the Computerized Ionospheric Tomography (CIT) technique. The spatial-temporal dynamics of ionospheric anomalies during the severe geomagnetic storm was reflected in detail. The IED varied with latitude and altitude dramatically; the maximum IED decreased, and the area where IEDs were maximum moved southward.