bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermographic Analysis of the Metacarpal and Metatarsal Areas in Jumping Sport Horses and Leisure Horses in Response to Warm-Up Duration
Authors: Janczarek Iwona , Kędzierski Witold , Tkaczyk Ewelina , Kaczmarek Beata , Łuszczyński Jarosław , Mucha Karolina
Published: July 2021

This study aimed to assess the impact of various types of warm-up on the metacarpal and metatarsal surface temperature in jumping sport horses in comparison to leisure horses, which work usually less intensively. Six clinically healthy sport geldings, contestants in showjumping competitions, and six geldings used for leisure riding were included in the study. The experiment was conducted for four consecutive days, during which the horses were warmed up by walking and trotting for various durations. Images were taken with a FLUKE Ti9 thermal imager to determine the resting, post-effort, and recovery temperature of the dorsal and plantar surface of the metacarpus and metatarsus of the four limbs. The obtained data were analysed with SmartView 4.1. software. The increase of measured rectal and surface temperatures was proportional to the warm-up duration. The surface temperature increase in the distal limb parts in jumping sport horses was greater than in horses used for leisure. The plantar surface was also warmer than the dorsal surface of the metacarpal/metatarsal areas, with a forelimb being warmer than a hind limb. Elevated temperatures after warm-up persist for 30 min in the recovery period, especially in jumping sport horses compared to leisure horses. Thus, the warming up effect is achieved earlier and lasts longer in heavily trained horses than in non-performance horses.
Effectiveness of Two Plant-Based In-Feed Additives against an Escherichia coli F4 Oral Challenge in Weaned Piglets
Authors: Montoya Daniel , D’Angelo Matilde , Martín-Orúe Susana M. , Rodríguez-Sorrento Agustina , Saladrigas-García Mireia , Araujo Coralie , Chabrillat Thibaut , Kerros Sylvain , Castillejos Lorena
Published: July 2021

This study evaluates the efficacy of two plant-based feed supplementations to fight colibacillosis in weanlings. A total of 96 piglets (32 pens) were assigned to four diets: a control diet (T1) or supplemented with ZnO (2500 ppm Zn) (T2) or two different plant supplements, T3 (1 kg/t; based on essential oils) and T4 (T3 + 1.5 kg/t based on non-volatile compounds). After one week, animals were challenged with ETEC F4, and 8 days after, one animal per pen was euthanized. Performance, clinical signs, microbial analysis, inflammatory response, intestinal morphology, and ileal gene expression were assessed. ZnO improved daily gains 4 days after challenge, T3 and T4 showing intermediate values (96, 249, 170, and 157 g/d for T1, T2, T3, and T4, p = 0.035). Fecal lactobacilli were higher with T3 and T4 compared to ZnO (7.55, 6.26, 8.71, and 8.27 cfu/gFM; p = 0.0007) and T3 increased the lactobacilli/coliforms ratio (p = 0.002). T4 was associated with lower levels of Pig-MAP (p = 0.07) and increases in villus/crypt ratio (1.49, 1.90, 1.73, and 1.84; p = 0.009). Moreover, T4 was associated with an upregulation of the REG3G gene (p = 0.013; pFDR = 0.228) involved in the immune response induced by enteric pathogens. In conclusion, both plant supplements enhanced animal response in front of an ETEC F4 challenge probably based on different modes of action.
Clearance of Gram-Negative Bacterial Pathogens from the Ocular Surface by Predatory Bacteria
Authors: Romanowski Eric G. , Gupta Shilpi , Pericleous Androulla , Kadouri Daniel E. , Shanks Robert M. Q.
Published: July 2021

It was previously demonstrated that predatory bacteria are able to efficiently eliminate Gram-negative pathogens including antibiotic-resistant and biofilm-associated bacteria. In this proof-of-concept study we evaluated whether two species of predatory bacteria, Bdellovibrio bacteriovorus and Micavibrio aeruginosavorus, were able to alter the survival of Gram-negative pathogens on the ocular surface. Clinical keratitis isolates of Pseudomonas aeruginosa (strain PAC) and Serratia marcescens (strain K904) were applied to the ocular surface of NZW rabbits followed by application of predatory bacteria. At time intervals, surviving pathogenic bacteria were enumerated. In addition, B. bacteriovorus and S. marcescens were applied to porcine organ culture corneas under contact lenses, and the ocular surface was examined by scanning electron microscopy. The ocular surface epithelial layer of porcine corneas exposed to S. marcescens, but not B. bacteriovorus was damaged. Using this model, neither pathogen could survive on the rabbit ocular surface for longer than 24 h. M. aeruginosavorus correlated with a more rapid clearance of P. aeruginosa but not S. marcescens from rabbit eyes. This study supports previous evidence that predatory bacteria are well tolerated by the cornea, but suggest that predatory bacteria do not considerably change the ability of the ocular surface to clear the tested Gram-negative bacterial pathogens from the ocular surface.
PhytoAFP: In Silico Approaches for Designing Plant-Derived Antifungal Peptides
Authors: Tyagi Atul , Roy Sudeep , Singh Sanjay , Semwal Manoj , Shasany Ajit K. , Sharma Ashok , Provazník Ivo
Published: July 2021

Emerging infectious diseases (EID) are serious problems caused by fungi in humans and plant species. They are a severe threat to food security worldwide. In our current work, we have developed a support vector machine (SVM)-based model that attempts to design and predict therapeutic plant-derived antifungal peptides (PhytoAFP). The residue composition analysis shows the preference of C, G, K, R, and S amino acids. Position preference analysis shows that residues G, K, R, and A dominate the N-terminal. Similarly, residues N, S, C, and G prefer the C-terminal. Motif analysis reveals the presence of motifs like NYVF, NYVFP, YVFP, NYVFPA, and VFPA. We have developed two models using various input functions such as mono-, di-, and tripeptide composition, as well as binary, hybrid, and physiochemical properties, based on methods that are applied to the main data set. The TPC-based monopeptide composition model achieved more accuracy, 94.4%, with a Matthews correlation coefficient (MCC) of 0.89. Correspondingly, the second-best model based on dipeptides achieved an accuracy of 94.28% under the MCC 0.89 of the training dataset.
The Effect of Amoxicillin in Adult Patients Presenting to Primary Care with Acute Cough Predicted to Have Pneumonia or a Combined Viral-Bacterial Infection
Authors: Bruyndonckx Robin , Stuart Beth , Little Paul , Hens Niel , Ieven Margareta , Butler Christopher , Verheij Theo , Goossens Herman , Coenen Samuel ,   The GRACE Project Group
Published: July 2021

While most cases of acute cough are self-limiting, antibiotics are prescribed to over 50%. This proportion is inappropriately high given that benefit from treatment with amoxicillin could only be demonstrated in adults with pneumonia (based on chest radiograph) or combined viral–bacterial infection (based on modern microbiological methodology). As routine use of chest radiographs and microbiological testing is costly, clinical prediction rules could be used to identify these patient subsets. In this secondary analysis of data from a multicentre randomised controlled trial in adults presenting to primary care with acute cough, we used prediction rules for pneumonia or combined infection and assessed the effect of amoxicillin in patients predicted to have pneumonia or combined infection on symptom duration, symptom severity and illness deterioration. In total, 2056 patients that fulfilled all inclusion criteria were randomised, 1035 to amoxicillin, 1021 to placebo. Neither patients with a predicted pneumonia nor patients with a predicted combined infection were significantly more likely to benefit from amoxicillin. While the studied clinical prediction rules may help primary care clinicians to reduce antibiotic prescribing for low-risk patients, they did not identify adult acute cough patients that would benefit from amoxicillin treatment.
The Role of ArlRS and VraSR in Regulating Ceftaroline Hypersusceptibility in Methicillin-Resistant Staphylococcus aureus
Authors: Villanueva Maite , Roch Melanie , Lasa Iñigo , Renzoni Adriana , Kelley William L.
Published: July 2021

Methicillin-resistant Staphylococcus aureus infections are a global health problem. New control strategies, including fifth-generation cephalosporins such as ceftaroline, have been developed, however rare sporadic resistance has been reported. Our study aimed to determine whether disruption of two-component environmental signal systems detectably led to enhanced susceptibility to ceftaroline in S. aureus CA-MRSA strain MW2 at sub-MIC concentrations where cells normally continue to grow. A collection of sequential mutants in all fifteen S. aureus non-essential two-component systems (TCS) was first screened for ceftaroline sub-MIC susceptibility, using the spot population analysis profile method. We discovered a role for both ArlRS and VraSR TCS as determinants responsible for MW2 survival in the presence of sub-MIC ceftaroline. Subsequent analysis showed that dual disruption of both arlRS and vraSR resulted in a very strong ceftaroline hypersensitivity phenotype. Genetic complementation analysis confirmed these results and further revealed that arlRS and vraSR likely regulate some common pathway(s) yet to be determined. Our study shows that S. aureus uses particular TCS environmental sensing systems for this type of defense and illustrates the proof of principle that if these TCS were inhibited, the efficacy of certain antibiotics might be considerably enhanced.
Limosilactobacillus reuteri Fermented Brown Rice: A Product with Enhanced Bioactive Compounds and Antioxidant Potential
Authors: Tyagi Akanksha , Shabbir Umair , Chelliah Ramachandran , Daliri Eric Banan-Mwine , Chen Xiuqin , Oh Deog-Hwan
Published: July 2021

Oxidative stress has been postulated to play a role in several diseases, including cardiovascular diseases, diabetes, and stress-related disorders (anxiety/depression). Presently, natural plant-derived phytochemicals are an important tool in reducing metabolomic disorders or for avoiding the side effects of current medicinal therapies. Brown Rice (Oryza sativa L.) is an important part of Asian diets reported as a rich source of bioactive phytonutrients. In our present study, we have analyzed the effect of different lactic acid bacteria (LABs) fermentation on antioxidant properties and in the enhancement of bioactive constituents in Korean brown rice. Therefore, the antioxidant activities and phytochemical analysis were investigated for raw brown rice (BR) and different fermented brown rice (FBR). BR fermented with Limosilactobacillus reuteri, showed the highest antioxidant activities among all samples: DPPH (121.19 ± 1.0), ABTS (145.80 ± 0.99), and FRAP (171.89 ± 0.71) mg Trolox equiv./100 g, dry weight (DW). Total phenolic content (108.86 ± 0.63) mg GAE equiv./100 g, DW and total flavonoids content (86.79 ± 0.83) mg catechin equiv./100 g, DW was also observed highest in Limosilactobacillus reuteri FBR. Furthermore, phytochemical profiling using ultra-high-performance liquid tandem chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) and cell antioxidant assay (CAA) revealed L. reuteri FBR as a strong antioxidant with an abundance of bioactive compounds such as gamma-aminobutyric acid, coumarin, cinnamic acid, butanoic acid, ascorbic acid, nicotinic acid, and stearic acid. This study expanded current knowledge on the impact of fermentation leading to the enhancement of antioxidant capacity with an abundance of health-related bioactive compounds in BR. The results obtained may provide useful information on functional food production using fermented brown rice.
Assessment of the Vulnerability of Selected Key Elements of Rail Transport. Slovak Case Study
Authors: Sventekova Eva , Urbancova Zdenka , Holla Katarina
Published: July 2021

Increases in means of transport, developed transport networks, and modernization dependent on computer technology not only lead to huge security demands but also require preventive measures and vulnerability assessments of key elements of transport infrastructure. The analyses carried out have shown that, though the importance of transport continues to grow, there is currently no system for assessing the vulnerability of essential elements that are necessary to keep rail transport safe and operational. Taking into account a number of criteria, the team of authors identified key elements of the railway transport infrastructure—bridges, tunnels, the width of the track, and the marshaling yard. The criteria applied included the significance and uniqueness of the element, its technical parameters, the difficulty of repair after possible damage, potential risks related to the location, and the analysis of rail safety based on statistical data and safety reports. The aim of this contribution is to present a multi-level model for assessing the vulnerability of key elements of rail transport infrastructure. The authors proceeded from the hypothesis that the vulnerability of key elements can be assessed using quantitative and qualitative parameters of the individual elements. The added value of the model is the methodological basis for a comprehensive vulnerability assessment system that will allow competent authorities to objectify the process of vulnerability assessment of key elements and to set up appropriate safeguards to enhance rail safety. The proposed model was verified on the Zilina-Vrútky track section, which is considered one of the most important railway junctions in Slovakia.
Accurate Diagnosis of Diabetic Retinopathy and Glaucoma Using Retinal Fundus Images Based on Hybrid Features and Genetic Algorithm
Authors: Tamim Nasser , Elshrkawey Mohamed , Nassar Hamed
Published: July 2021

Diabetic retinopathy (DR) and glaucoma can both be incurable if they are not detected early enough. Therefore, ophthalmologists worldwide are striving to detect them by personally screening retinal fundus images. However, this procedure is not only tedious, subjective, and labor-intensive, but also error-prone. Worse yet, it may not even be attainable in some countries where ophthalmologists are in short supply. A practical solution to this complicated problem is a computer-aided diagnosis (CAD) system—the objective of this work. We propose an accurate system to detect at once any of the two diseases from retinal fundus images. The accuracy stems from two factors. First, we calculate a large set of hybrid features belonging to three groups: first-order statistics (FOS), higher-order statistics (HOS), and histogram of oriented gradient (HOG). Then, these features are skillfully reduced using a genetic algorithm scheme that selects only the most relevant and significant of them. Finally, the selected features are fed to a classifier to detect one of three classes: DR, glaucoma, or normal. Four classifiers are tested for this job: decision tree (DT), naive Bayes (NB), k-nearest neighbor (kNN), and linear discriminant analysis (LDA). The experimental work, conducted on three publicly available datasets, two of them merged into one, shows impressive performance in terms of four standard classification metrics, each computed using k-fold crossvalidation for added credibility. The highest accuracy has been provided by DT—96.67% for DR, 100% for glaucoma, and 96.67% for normal.
Numerical Analysis of the Effects of the Structure Shape and Orientation of Kelvin Cell Porous Structures during Air Forced Convection
Authors: Calati Michele , De Monte Edoardo , Mancin Simone
Published: July 2021

In recent years, in order to counteract the growth of environmental pollution and the contemporary scarcity of various energy sources, researchers have proposed innovative and efficient solutions for heat transfer applications. Extended surfaces, which can involve the use of fins, open cell metal foams, etc., have been demonstrated to be promising solutions. Open cell metal foams consist of structs intersecting at nodes resulting in stochastic oriented cells. Periodic metal foams have also attracted great interest. These structures are made of a single cell unit periodically replicated. Kelvin cells and Weaire–Phelan ones are two conventional elementary unit cells. In this paper, a numerical model is developed and validated, aiming at analysing the thermal and hydraulic behaviors of modified Kelvin cell-based metal foams during air forced convection. Constant porosity (0.9) and pore density (40 PPI) were adopted. Five different geometrical configurations (one cylindrical and four elliptical) and four orientations (0–15–30–45°) of the struts with respect to the main air flow direction were investigated. The inlet air velocities varied between 0.5 and 4 m s−1. Interesting results were obtained and discussed in terms of pressure drops, heat transfer coefficients, and pumping power per area density.
Quantification of Optical Chirality in Cellulose Nanocrystal Films Prepared by Shear-Coating
Authors: Juárez-Rivera Olga Rubí , Mauricio-Sánchez Reina Araceli , Järrendahl Kenneth , Arwin Hans , Mendoza-Galván Arturo
Published: July 2021

Evaporation-induced-self-assembly is widely used to produce chiral cellulose nanocrystal (CNC) free-standing films reflecting left-handed polarized light. Research on supported chiral CNC films is rather scarce. The reflection and/or transmission of unpolarized light are the most common optical techniques used to characterize the selective reflection of CNC films whereas the use of techniques to quantify chiral properties is limited. Here, the fabrication of chiral CNC films supported on glass substrates by a shear-coating method, as well as a full characterization of their polarization properties, are reported. Optical chirality is evidenced in films, showing a brilliant blue structural color when viewed through a left-handed polarizer and darkness through a right-handed polarizer. Mueller-matrix data in the reflection and transmission modes are used to quantitatively characterize the structural origin of color in the films. The quantification of the linear and circular birefringence, as well as circular dichroism, is performed by analytical inversion of the Mueller matrix data in the transmission mode and regression analysis using Tellegen constitutive equations. The equivalence of the two methods to quantify the structural chirality in CNC films is demonstrated. The swelling of films in water and kinetics during drying is studied by reflection spectroscopy.
A Deep Recurrent Neural Network-Based Explainable Prediction Model for Progression from Atrophic Gastritis to Gastric Cancer
Authors: Kim Hyon , Lim Young , Seo Seung-In , Lee Kyung , Kim Jae , Shin Woon
Published: July 2021

Gastric cancer is the fifth most common cancer type worldwide and one of the most frequently diagnosed cancers in South Korea. In this study, we propose DeepPrevention, which comprises a prediction module to predict the possibility of progression from atrophic gastritis to gastric cancer and an explanation module to identify risk factors for progression from atrophic gastritis to gastric cancer, to identify patients with atrophic gastritis who are at high risk of gastric cancer. The data set used in this study was South Korea National Health Insurance Service (NHIS) medical checkup data for atrophic gastritis patients from 2002 to 2013. Our experimental results showed that the most influential predictors of gastric cancer development were sex, smoking duration, and current smoking status. In addition, we found that the average age of gastric cancer diagnosis in a group of high-risk patients was 57, and income, BMI, regular exercise, and the number of endoscopic screenings did not show any significant difference between groups. At the individual level, we identified that there were relatively strong associations between gastric cancer and smoking duration and smoking status.
BIM and GIS Applications in Bridge Projects: A Critical Review
Authors: Wei Jiangang , Chen Gang , Huang Jizhuo , Xu Li , Yang Yan , Wang Jun , Sadick Abdul-Manan
Published: July 2021

In recent years, interest in BIM and GIS applications in civil engineering has been growing. For bridge engineering, BIM/GIS applications such as simulation, visualization, and secondary development have been used to assist practitioners in managing bridge construction and decision-making, including selection of bridge location maintenance decisions. In situ 3D modelling of existing bridges with detailed images from UAV camera has allowed engineers to conduct remote condition assessments of bridges and decide on required maintenance actions. Several studies have investigated the applications of BIM/GIS technology on bridge projects. However, there has been limited focus on reviewing the outcomes of these studies to identify the limitations of BIM and GIS applications on bridge projects. Therefore, the aim of this study was to review the research on BIM/GIS technology applications in bridge projects over the last decade. Using a systematic review process, a total of 90 publications that met the inclusion criteria were reviewed in this study. The review identified the state-of-the-art methods of BIM and GIS applications, respectively, at the planning and design, construction, and operation and maintenance phases of bridge projects. However, the findings point to segregated application of BIM and GIS at all phases of bridge projects. The findings of this study will contribute to guiding practitioners in selecting appropriate BIM and GIS technologies for different aspects of bridge projects.
DR-Transformer: A Multi-Features Fusion Framework for Tropical Cyclones Intensity Estimation
Authors: Luo Yicheng , Xu Yajing , Li Si , Qian Qifeng , Xiao Bo
Published: July 2021

Convolutional neural networks have achieved great success in analyzing potential features inside tropical cyclones (TCs) using satellite images for intensity estimation. However, due to the high similarity of visual features in TC images, it is still a challenge to learn the accurate mapping between TC images and numerical intensity. Existing works mainly focus on the visual features of a single TC, ignoring the impact of intensity continuity and time evolution among TCs on decision making. Therefore, we propose a DR-transformer framework for temporal TC intensity estimation. Inside DR-transformers, a novel DR-extractor can extract Distance-consistency(DC) and Rotation-invariance (RI) features between TC images, and therefore can better learn the contours, structures, and other visual features of each TC image. DC features can reduce the estimation error between adjacent intensities, and RI features can eliminate feature deviation caused by shooting angles and TC rotation. Additionally, a transformer with a DR-extractor as the backbone is applied to aggregate the temporal correlation in a series of TC images, which can learn the evolution from intensity to the visual features of TC. Experiments show that the final result, an RMSE of 7.76 knots, outperforms the baseline, and is better than any previously reported method trained on the TCIR dataset.
Motion Planning for a Mobile Humanoid Manipulator Working in an Industrial Environment
Authors: Pajak Iwona , Pajak Grzegorz
Published: July 2021

This paper presents the usage of holonomic mobile humanoid manipulators to carry out autonomous tasks in industrial environments, according to the smart factory concept and the Industry 4.0 philosophy. The problem of transporting lengthy objects, taking into account mechanical limitations, the conditions for avoiding collisions, as well as the dexterity of the manipulator arms was considered. The primary problem was divided into three phases, leading to three different types of robotic tasks. In the proposed approach, the pseudoinverse Jacobian method at the acceleration level to solve each of the tasks was used. The redundant degrees of freedom were used to satisfy secondary objectives such as robot kinetic energy, the maximization of the manipulability measure, and the fulfillment mechanical and collision-avoidance limitations. A computer example involving a mobile humanoid manipulator, operating in an industrial environment, illustrated the effectiveness of the proposed method.
Thermal and Mechanical Assessment of PLA-SEBS and PLA-SEBS-CNT Biopolymer Blends for 3D Printing
Authors: Ádám Balázs , Weltsch Zoltán
Published: July 2021

Polylactic acid (PLA) is one of the most promising biopolymers often used as a raw material in 3D printing in many industrial areas. It has good mechanical properties, is characterized by high strength and stiffness, but unfortunately, it has some disadvantages; one is brittleness, and the other is slow crystallization. Amounts of 1–5% SEBS (styrene-ethylene-butylene-styrene) thermoplastic elastomer were blended into the PLA and the thermal and mechanical properties were investigated. DSC (Differential Scanning Calorimetry) measurements on the filaments have shown that SEBS increases the initial temperature of crystallization, thereby acting as a nucleating agent. The cooling rate of 3D printing, on the other hand, is too fast for PLA, so printed specimens behave almost amorphously. The presence of SEBS increases the impact strength, neck formation appears during the tensile test, and in the bending test, the mixture either suffers partial fracture or only bends without fracture. Samples containing 1% SEBS were selected for further analysis, mixed with 0.06 and 0.1% carbon nanotubes (CNTs), and tested for thermal and mechanical properties. As a result of CNTs, another peak appeared on the DSC curve in addition to the original single-peak crystallization, and the specimens previously completely broken in the mechanical tests suffered partial fractures, and the partially fractured pieces almost completely regained their original shape at the end of the test.
Safe Local Aerial Manipulation for the Installation of Devices on Power Lines: AERIAL-CORE First Year Results and Designs
Authors: Cacace Jonathan , Orozco-Soto Santos M. , Suarez Alejandro , Caballero Alvaro , Orsag Matko , Bogdan Stjepan , Vasiljevic Goran , Ebeid Emad , Rodriguez Jose Alberto Acosta , Ollero Anibal
Published: July 2021

The power grid is an essential infrastructure in any country, comprising thousands of kilometers of power lines that require periodic inspection and maintenance, carried out nowadays by human operators in risky conditions. To increase safety and reduce time and cost with respect to conventional solutions involving manned helicopters and heavy vehicles, the AERIAL-CORE project proposes the development of aerial robots capable of performing aerial manipulation operations to assist human operators in power lines inspection and maintenance, allowing the installation of devices, such as bird flight diverters or electrical spacers, and the fast delivery and retrieval of tools. This manuscript describes the goals and functionalities to be developed for safe local aerial manipulation, presenting the preliminary designs and experimental results obtained in the first year of the project.
STEP-NC Compliant Intelligent CNC Milling Machine with an Open Architecture Controller
Authors: Dharmawardhana Mahanama , Ratnaweera Asanga , Oancea Gheorghe
Published: July 2021

A STEP-NC or ISO 14649 compliant machine controller is developed, using Open Architecture Control technology for a three-axis Computer Numerical Control milling machine in this research. The controller is developed on a Raspberry Pi single-board computer, using C++ language. This new development is proposed as a low-cost alternative to ISO6983 standard, ensuring continuous integration in the CAD/CAM/CNC chain in machining; thus, it broadens the spectrum of problems handled by conventional CNC systems. The new machine controller is intelligent enough to extract geometrical and manufacturing parameters, cutting tool data, and material data from the STEP-NC file. Accordingly, tool paths for machining can be generated in the controller itself. The shop floor level modification of parameters and the possibility of regeneration of new toolpaths is an added advantage of this new controller. The modified or improved version of the STEP-NC file can be sent back to the CAD/CAM system to close the CAD/CAM/CNC chain. Machine condition monitoring can be achieved by connecting sensors through an available slave I/O board. In the present development, the current drawn by each servo motor is fed back to the controller for cutting condition monitoring. A laboratory scale three-axis CNC milling machine is developed to test the performance of the newly developed controller. The accuracy of positioning, perpendicularity of axes and linearity of this machine are experimentally verified through standard tests. The STEP-NC compliance of the controller is tested and verified, using a STEP-NC program derived based on a sample program given in ISO 14649 standard.
Demonstration of Phase Change Thermal Energy Storage in Zinc Oxide Microencapsulated Sodium Nitrate
Authors: Neagoe Ciprian , Tudor Ioan Albert , Ciobota Cristina Florentina , Bogdanescu Cristian , Stanciu Paul , Zărnescu-Ivan Nicoleta , Piticescu Radu Robert , Romero-Sanchez Maria Dolores
Published: July 2021

Microencapsulation of sodium nitrate (NaNO3) as phase change material for high temperature thermal energy storage aims to reduce costs related to metal corrosion in storage tanks. The goal of this work was to test in a prototype thermal energy storage tank (16.7 L internal volume) the thermal properties of NaNO3 microencapsulated in zinc oxide shells, and estimate the potential of NaNO3–ZnO microcapsules for thermal storage applications. A fast and scalable microencapsulation procedure was developed, a flow calorimetry method was adapted, and a template document created to perform tank thermal transfer simulation by the finite element method (FEM) was set in Microsoft Excel. Differential scanning calorimetry (DSC) and transient plane source (TPS) methods were used to measure, in small samples, the temperature dependency of melting/solidification heat, specific heat, and thermal conductivity of the NaNO3–ZnO microcapsules. Scanning electron microscopy (SEM) and chemical analysis demonstrated the stability of microcapsules over multiple tank charge–discharge cycles. The energy stored as latent heat is available for a temperature interval from 303 to 285 °C, corresponding to onset–offset for NaNO3 solidification. Charge–self-discharge experiments on the pilot tank showed that the amount of thermal energy stored in this interval largely corresponds to the NaNO3 content of the microcapsules; the high temperature energy density of microcapsules is estimated in the range from 145 to 179 MJ/m3. Comparison between real tank experiments and FEM simulations demonstrated that DSC and TPS laboratory measurements on microcapsule thermal properties may reliably be used to design applications for thermal energy storage.
Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources
Authors: Islam Azharul , Chang KyungHi
Published: July 2021

Unstructured data from the internet constitute large sources of information, which need to be formatted in a user-friendly way. This research develops a model that classifies unstructured data from data mining into labeled data, and builds an informational and decision-making support system (DMSS). We often have assortments of information collected by mining data from various sources, where the key challenge is to extract valuable information. We observe substantial classification accuracy enhancement for our datasets with both machine learning and deep learning algorithms. The highest classification accuracy (99% in training, 96% in testing) was achieved from a Covid corpus which is processed by using a long short-term memory (LSTM). Furthermore, we conducted tests on large datasets relevant to the Disaster corpus, with an LSTM classification accuracy of 98%. In addition, random forest (RF), a machine learning algorithm, provides a reasonable 84% accuracy. This research’s main objective is to increase the application’s robustness by integrating intelligence into the developed DMSS, which provides insight into the user’s intent, despite dealing with a noisy dataset. Our designed model selects the random forest and stochastic gradient descent (SGD) algorithms’ F1 score, where the RF method outperforms by improving accuracy by 2% (to 83% from 81%) compared with a conventional method.
Data-Driven Approach for Rainfall-Runoff Modelling Using Equilibrium Optimizer Coupled Extreme Learning Machine and Deep Neural Network
Authors: Roy Bishwajit , Singh Maheshwari Prasad , Kaloop Mosbeh R. , Kumar Deepak , Hu Jong-Wan , Kumar Radhikesh , Hwang Won-Sup
Published: July 2021

Rainfall-runoff (R-R) modelling is used to study the runoff generation of a catchment. The quantity or rate of change measure of the hydrological variable, called runoff, is important for environmental scientists to accomplish water-related planning and design. This paper proposes (i) an integrated model namely EO-ELM (an integration of equilibrium optimizer (EO) and extreme learning machine (ELM)) and (ii) a deep neural network (DNN) for one day-ahead R-R modelling. The proposed R-R models are validated at two different benchmark stations of the catchments, namely river Teifi at Glanteifi and river Fal at Tregony in the UK. Firstly, a partial autocorrelation function (PACF) is used for optimal number of lag inputs to deploy the proposed models. Six other well-known machine learning models, called ELM, kernel ELM (KELM), and particle swarm optimization-based ELM (PSO-ELM), support vector regression (SVR), artificial neural network (ANN) and gradient boosting machine (GBM) are utilized to validate the two proposed models in terms of prediction efficiency. Furthermore, to increase the performance of the proposed models, paper utilizes a discrete wavelet-based data pre-processing technique is applied in rainfall and runoff data. The performance of wavelet-based EO-ELM and DNN are compared with wavelet-based ELM (WELM), KELM (WKELM), PSO-ELM (WPSO-ELM), SVR (WSVR), ANN (WANN) and GBM (WGBM). An uncertainty analysis and two-tailed t-test are carried out to ensure the trustworthiness and efficacy of the proposed models. The experimental results for two different time series datasets show that the EO-ELM performs better in an optimal number of lags than the others. In the case of wavelet-based daily R-R modelling, proposed models performed better and showed robustness compared to other models used. Therefore, this paper shows the efficient applicability of EO-ELM and DNN in R-R modelling that may be used in the hydrological modelling field.
Impacts on Indoor Thermal Comfort and Heating Energy Use in Hellenic Dwellings from Occupant Behavioral Reactions
Authors: Dascalaki Elena G. , Balaras Constantinos A.
Published: July 2021

In an effort to reduce the operational cost of their dwellings, occupants may even have to sacrifice their indoor thermal comfort conditions. Following the economic recession in Greece over recent years, homeowners have been forced to adapt their practices by shortening heating hours, lowering the indoor thermostat settings, isolating spaces that are not heated or even turning off their central heating system and using alternative local heating systems. This paper presents the results from over 100 occupant surveys using questionnaires and walk-through energy audits in Hellenic households that documented how occupants operated the heating systems in their dwellings and the resulting indoor thermal comfort conditions and actual energy use. The results indicate that the perceived winter thermal comfort conditions were satisfactory in only half of the dwellings, since the actual operating space heating periods averaged only 5 h (compared with the assumed 18 h in standard conditions), while less than half heated their entire dwellings and only a fifth maintained an indoor setpoint temperature of 20 °C, corresponding to standard comfort conditions. Mainstream energy conservation measures include system maintenance, switching to more efficient systems, reducing heat losses and installing controls. This information is then used to derive empirical adaptation factors for bridging the gap between the calculated and actual energy use, making more realistic estimates of the expected energy savings following building renovations, setting prudent targets for energy efficiency and developing effective plans toward a decarbonized building stock.
A Theoretical Concept of Decoupled Current Control Scheme for Grid-Connected Inverter with L-C-L Filter
Authors: Ghasemi Mohamad Amin , Zarei Seyed Fariborz , Peyghami Saeed , Blaabjerg Frede
Published: July 2021

This paper proposes a nonlinear decoupled current control scheme for a grid-connected inverter with LCL filter. Decoupling the active and reactive current control channels is one of the main demands in the control of inverters. For inverters with an L filter, the decoupling can be achieved by a proper feed-forward of grid voltages. However, the coupling of channels is a complex issue for converters with LCL filters. The resonance mode of the LCL filter may cause instability, which adds more complexity to the analysis. In this paper, state equations of the system are provided, which highlight the coupling between active and reactive currents injected into the grid. Accordingly, a non-linear control scheme is proposed which effectively decouples the channels and dampens the resonant modes of the LCL filter. The stability of the proposed control method is verified by the Lyapunov criterion. Independency of the system stability to the grid-impedance is another feature of the proposed approach. Moreover, only grid-side currents are needed for implementation of the proposed scheme, avoiding the need for additional current sensors for the output capacitor and grid-side inductor. For accurate modelling of the inverter, the computation and PWM sampling delays are included in the controller design. Finally, various case studies are provided that verify the performance of the proposed approach and the stability of the system.
Leaching Behaviour of Construction and Demolition Wastes and Recycled Aggregates: Statistical Analysis Applied to the Release of Contaminants
Authors: Diotti Alessandra , Plizzari Giovanni , Sorlini Sabrina
Published: July 2021

Construction and demolition wastes represent a primary source of new alternative materials which, if properly recovered, can be used to replace virgin raw materials partially or totally. The distrust of end-users in the use of recycled aggregates is mainly due to the environmental performance of these materials. In particular, the release of pollutants into the surrounding environment appears to be the aspect of greatest concern. This is because these materials are characterized by a strong heterogeneity which can sometimes lead to contaminant releases above the legal limits for recovery. In this context, an analysis of the leaching behaviour of both CDWs and RAs was conducted by applying a statistical analysis methodology. Subsequently, to evaluate the influence of the particle size and the volumetric reduction of the material on the release of contaminants, several experimental leaching tests were carried out according to the UNI EN 12457-2 and UNI EN 12457-4 standards. The results obtained show that chromium, mercury, and COD are the most critical parameters for both CDWs and RAs. Moreover, the material particle size generally affects the release of contaminants (i.e., finer particles showed higher releases), while the crushing process does not always involve higher releases than the sieving process.
Sensitivity Analysis of the Dust-Generation Algorithm in ADAM3 by Incorporating Surface-Wetness Effects
Authors: Lim Yunkyu , Kang Misun , Kim Jinwon
Published: July 2021

This study examined the surface-wetness effects in calculating dust generation in source regions, using Asian dust aerosol model version 3 (ADAM3; the control run; CNTL). Model sensitivity experiment was conducted in such a way that the dust generation in CNTL is compared against three ADAM3 versions with various surface-wetness effect schemes. The dust-generation algorithm in ADAM_RAIN utilizes precipitation, while the scheme in ADAM3_SM1 and ADAM3_SM2 employs soil water content to account for the surface-wetness effects on dust generation. Each run was evaluated for the spring (March–May) of 2020. ADAM3_SM1 shows the best performance for the dust source region in East Asia based on the root-mean-square error and the skill score, followed by ADAM3_SM2 and ADAM3_RAIN. Particularly, incorporation of the surface-wetness effects improves dust generation mostly in wet cases rather than dry cases. The three surface-wetness-effect runs reduce dust generation in the source regions compared to CNTL; hence, the inclusion of surface-wetness effects improves dust generation in the regions where CNTL overestimates dust generation.
Continuous CO2 and CH4 Observations in the Coastal Arctic Atmosphere of the Western Taimyr Peninsula, Siberia: The First Results from a New Measurement Station in Dikson
Authors: Panov Alexey , Prokushkin Anatoly , Kübler Karl Robert , Korets Mikhail , Urban Anastasiya , Bondar Mikhail , Heimann Martin
Published: July 2021

Atmospheric observations of sources and sinks of carbon dioxide (CO2) and methane (CH4) in the pan-Arctic domain are highly sporadic, limiting our understanding of carbon turnover in this climatically sensitive environment and the fate of enormous carbon reservoirs buried in permafrost. Particular gaps apply to the Arctic latitudes of Siberia, covered by the vast tundra ecosystems underlain by permafrost, where only few atmospheric sites are available. The paper presents the first results of continuous observations of atmospheric CO2 and CH4 dry mole fractions at a newly operated station “DIAMIS” (73.506828° N, 80.519869° E) deployed on the edge of the Dikson settlement on the western coast of the Taimyr Peninsula. Atmospheric mole fractions of CO2, CH4, and H2O are measured by a CRDS analyzer Picarro G2301-f, which is regularly calibrated against WMO-traceable gases. Meteorological records permit screening of trace gas series. Here, we give the scientific rationale of the site, describe the instrumental setup, analyze the local environments, examine the seasonal footprint, and show CO2 and CH4 fluctuations for the daytime mixed atmospheric layer that is representative over a vast Arctic domain (~500–1000 km), capturing both terrestrial and oceanic signals.
Volatile and Non-Volatile Characterization of White and Rosé Wines from Different Spanish Protected Designations of Origin
Authors: Del Barrio-Galán Rubén , Valle-Herrero Héctor del , Bueno-Herrera Marta , López-de-la-Cuesta Pedro , Pérez-Magariño Silvia
Published: July 2021

The quality of wines has often been associated with their geographical area of production, as well as the grape variety used in their elaboration. Many research studies have been carried out to characterize and differentiate between red wines labeled with Protected Designation of Origin (PDO) from different geographical areas, but very few have been carried out on white and rosé wines. The objective of this work was to characterize white and rosé PDO wines from different geographical areas of Spain very close to each other elaborated with different grape varieties and select the variables that most contribute to their differentiation. Analysis of variance (ANOVA) and principal component analysis (PCA) were used as statistical methods. The ethanol content was the nonvolatile variable that most contributed to differentiating between some of the white and rosé wines according to their PDO. The white wines from RD (Ribera del Duero) and BI (Bierzo) were characterized by a high terpenic content (floral notes) while the wines from RU (Rueda), TO (Toro) and CI (Cigales)by a high content of ethyl esters and alcohol acetates (fruity aromas). The rosé wines elaborated with the Mencía grape variety from BI were characterized by their highest polysaccharidic content, which could have a positive sensory effect on the mouthfeel. The rosé wines from CI were characterized by their volatile profile complexity, having the highest content of volatile compounds from the oak wood, terpenes and C6 alcohols which provide pleasant woody, floral and herbaceous aromas. On the contrary, the RD wines were richest in alcohol acetates responsible for fruity aromas.
Morphological and Micromorphological Description of the Larvae of Two Endemic Species of Duvalius (Coleoptera, Carabidae, Trechini)
Authors: Sitar Cristian , Barbu-Tudoran Lucian , Moldovan Oana Teodora
Published: July 2021

The morphological and ultrastructural descriptions of the larvae of two cave species of Trechini—Duvalius (Hungarotrechus) subterraneus (L. Miller, 1868) and Duvalius (Biharotrechus) paroecus (J. Frivaldszkyi, 1865)—are presented in this paper. The interest in studying these larvae lays in their rarity and the limited distribution of the Duvalius species. The larvae were collected from caves in the Romanian Carpathians and were examined under a stereomicroscope and scanning electron microscopy. New important taxonomical and fine morphological characteristics are discussed together with conclusions on the larvae microhabitat as part of the measures to be taken by a proper management of caves.
Dual PARP and RAD51 Inhibitory Drug Conjugates Show Synergistic and Selective Effects on Breast Cancer Cells
Authors: Malka Matthews M. , Eberle Julia , Niedermayer Kathrin , Zlotos Darius P. , Wiesmüller Lisa
Published: July 2021

The genetic principle of synthetic lethality has most successfully been exploited in therapies engaging Poly-ADP-ribose-polymerase (PARP) inhibitors to treat patients with homologous recombination (HR)-defective tumors. In this work, we went a step further following the idea of a local molecular cooperation and designed hybrid compounds M1–M3. The drug conjugates M1–M3 combine Olaparib, the first PARP inhibitor approved for clinical use, with Cpd 1, an inhibitor of RAD51 that blocks its HR functions and yet permits RAD51 nucleoprotein filament formation on single-stranded DNA. While in M2 and M3, the parental drugs are linked by -CO-(CH2)n-CO-spacers (n = 2 and 4, respectively), they are directly merged omitting the piperazine ring of Olaparib in M1. Monitoring anti-survival effects of M1–M3 in six breast cancer cell lines of different molecular subtypes showed that in each cell line, at least one of the drug conjugates decreased viability by one to two orders of magnitude compared with parental drugs. While triple-negative breast cancer (TNBC) cells with frequent BRCA1 pathway dysfunction were sensitive to spacer-linked hybrid compounds M1 and M2 regardless of their HR capacities, non-TNBC cells were responsive to the merged drug conjugate M1 only, suggesting different spatial requirements for dual inhibition in these two groups of cell lines. These results demonstrate that, depending on chemical linkage, dual PARP1-RAD51 inhibitory drugs can either sensitize non-TNBC and re-sensitize TNBC cells, or discriminate between these groups of cells.