bluuebunny/crossref_metadata_2025 huggingface dataset:
Industrial Robot Positioning Performance Measured on Inclined and Parallel Planes by Double Ballbar
Authors: Kuric Ivan , Tlach Vladimír , Sága Milan , Císar Miroslav , Zajačko Ivan
Published: February 2021

Renishaw Ballbar QC20–W is primarily intended for diagnostics of CNC machine tools, but it is also used in connection with industrial robots. In the case of standard measurement, when the measuring plane is parallel to the robot base, not all robot joints move. The purpose of the experiments of the present article was to verify the hypothesis of the motion of all the robot joints when the desired circular path is placed on an inclined plane. In the first part of the conducted experiments is established hypothesis is confirmed, through positional analysis on a simulation model of the robot. They are then carried out practical measurements being evaluated the influence of individual robot joints to deform the circular path, shown as a polar graph. As a result, it is found that in the case of the robot used, changing the configuration of the robot arm has the greatest effect on changing the shape of the polar graph.
Mechanism of Overlying Strata Structure Instability during Mining below Unconsolidated Confined Aquifer and Disaster Prevention
Authors: Wang Xiaozhen , Zhu Weibing , Xu Jialin , Han Hongkai , Fu Xiang
Published: February 2021

There is a layer of the unconsolidated confined aquifer (UCA) made of non-cemented sand and grit on the bed of Quaternary thick topsoil in many coal mines in east and north China. Existing on the bedrock of coal measures, it poses a serious threat to coal mine safety. Worse, it caused many supports crushing and water inrush disasters (SCWIDs) and resulted in significant economic losses. Aiming at the above problems, this paper adopts a simulation experiment, field measurement, engineering detection, and theoretical analysis to conduct the research. The research reveals the overburden’s destructive rules during mining under UCA. The results indicate that UCA plays an important role in the process of load transfer due to its mobility and replenishment in time. When mining close to the aquifer, the load transfer of aquifer leads to overburden breaking entirely and sliding instability of the bond-beam structure, then, the water flowing fractured zone develops rapidly and connects the aquifer, which is the fundamental reason for SCWID under the UCA. Based on the mechanism of SCWID, a prediction method of support crushing and water inrush hazard zones was put forward. Artificial pre-split blasting based on the location of a key stratum was applied to prevent SCWID. The proposed methods have been used in 7131 working face and safe mining was achieved.
Refrigerant Charge Prediction of Vapor Compression Air Conditioner Based on Start-Up Characteristics
Authors: Yun Yechan , Chang Young Soo
Published: February 2021

Refrigerant charge faults, which occur frequently, increase the energy loss and may fatally damage the system. Refrigerant leakage is difficult to detect and diagnose until the fault has reached a severe degree. Various techniques have been developed to predict the refrigerant charge amount based on steady-state operation; however, steady-state experiments used to develop prediction models for the refrigerant charge amount are expensive and time-consuming. In this study, a prediction model was established with dynamic experimental data to overcome these deficiencies. The dynamic models for the condensation temperature, degree of subcooling, compressor discharge temperature, and power consumption were developed with a regression support vector machine (r-SVM) model and start-up experimental data. The dynamic models for the condensation temperature and degree of subcooling can predict the distinct start-up characteristics depending on the refrigerant charge amount. Moreover, the estimated root mean square error (RMSE) of the condensation temperature and degree of subcooling of the test data are 0.53 and 0.84 °C, respectively. The refrigerant charge is one of the predictors that defines the dynamic characteristics. The refrigerant charge can be estimated by minimizing the RMSE of the predicted values of the dynamic models and experimental data. When the dynamic characteristics of the two predictor variables, “condensation temperature” and “degree of subcooling” are used together, the average prediction error of the test data is 2.54%. The proposed method, which uses the dynamic model during start-up operation, is an effective technique for predicting the refrigerant charge amount.
TEDL: A Text Encryption Method Based on Deep Learning
Authors: Wang Peng , Li Xiang
Published: February 2021

Recent years have seen an increasing emphasis on information security, and various encryption methods have been proposed. However, for symmetric encryption methods, the well-known encryption techniques still rely on the key space to guarantee security and suffer from frequent key updating. Aiming to solve those problems, this paper proposes a novel symmetry-key method for text encryption based on deep learning called TEDL, where the secret key includes hyperparameters in the deep learning model and the core step of encryption is transforming input data into weights trained under hyperparameters. Firstly, both communication parties establish a word vector table by training a deep learning model according to specified hyperparameters. Then, a self-update codebook is constructed on the word vector table with the SHA-256 function and other tricks. When communication starts, encryption and decryption are equivalent to indexing and inverted indexing on the codebook, respectively, thus achieving the transformation between plaintext and ciphertext. Results of experiments and relevant analyses show that TEDL performs well for security, efficiency, generality, and has a lower demand for the frequency of key redistribution. Especially, as a supplement to current encryption methods, the time-consuming process of constructing a codebook increases the difficulty of brute-force attacks, meanwhile, it does not degrade the efficiency of communications.
Quantification of the Elastic Moduli of Lumbar Erector Spinae and Multifidus Muscles Using Shear-Wave Ultrasound Elastography
Authors: Lim Tae Hyun , Lee Deukhee , Kim Olga , Lee Song Joo
Published: February 2021

Although spinal surgeries with minimal incisions and a minimal amount of X-ray exposure (MIMA) mostly occur in a prone posture on a Wilson table, the prone posture’s effects on spinal muscles have not been investigated. Thus, this study used ultrasound shear-wave elastography (SWE) to compare the material properties of the erector spinae and multifidus muscles when subjects lay on the Wilson table used for spinal surgery and the flat table as a control condition. Thirteen male subjects participated in the study. Using ultrasound SWE, the shear elastic moduli (SEM) of the erector spinae and multifidus muscles were investigated. Significant increases were found in the SEM of erector spinae muscle 1, erector spinae muscle 2, and multifidus muscles on the Wilson table (W) compared to in the flat table (F; W:22.19 ± 7.15 kPa, F:10.40 ± 3.20 kPa, p < 0.001; W:12.10 ± 3.31 kPa, F: 7.17 ± 1.71 kPa, p < 0.001; W: 18.39 ± 4.80 kPa, F: 11.43 ± 2.81 kPa, p < 0.001, respectively). Our results indicate that muscle material properties measured by SWE can be changed due to table posture, which should be considered in biomechanical modeling by guiding surgical planning to develop minimal-incision surgical procedures.
Evaluation and Application of a Novel Low-Cost Wearable Sensing Device in Assessing Real-Time PM2.5 Exposure in Major Asian Transportation Modes
Authors: Wang Wen-Cheng Vincent , Lung Shih-Chun Candice , Liu Chun-Hu , Wen Tzu-Yao Julia , Hu Shu-Chuan , Chen Ling-Jyh
Published: February 2021

Small low-cost sensing (LCS) devices enable assessment of close-to-reality PM2.5 exposures, though their data quality remains a challenge. This work evaluates the precision, accuracy, wearability and stability of a wearable particle LCS device, Location-Aware Sensing System (LASS, with Plantower PMS3003), which is 104 × 66 × 46 mm3 in size and less than 162 g in weight. Real-time particulate matter (PM) exposures in six major Asian transportation modes were assessed. Side-by-side laboratory evaluation of PM2.5 between a GRIMM aerosol spectrometer and sensors yielded a correlation of 0.98 and a mean absolute error of 0.85 µg/m3. LASS readings collected in the summer of 2016 in Taiwan were converted to GRIMM-comparable values. Mean PM2.5 concentrations obtained from GRIMM and converted LASS values of the six different transportation microenvironments were 16.9 ± 11.7 (n = 1774) and 17.0 ± 9.5 (n = 3399) µg/m3, respectively, showing a correlation of 0.93. The average one-hour PM2.5 exposure increments (concentration increase above ambient levels) from converted LASS values for Mass Rapid Transit (MRT), bus, car, scooter, bike and walk were 15.6, 6.7, −19.2, 8.1, 6.1 and 7.1 µg/m3, respectively, very close to those obtained from GRIMM. This work is one of the earliest studies applying wearable particulate matter (PM) LCS devices in exposure assessment in different transportation modes.
Overview of Aerosol Properties in the European Arctic in Spring 2019 Based on In Situ Measurements and Lidar Data
Authors: Rader Fieke , Traversi Rita , Severi Mirko , Becagli Silvia , Müller Kim-Janka , Nakoudi Konstantina , Ritter Christoph
Published: February 2021

In this work, we analysed aerosol measurements from lidar and PM10 samples around the European Arctic site of Ny-Ålesund during late winter–early spring 2019. Lidar observations above 700 m revealed time-independent values for the aerosol backscatter coefficient (ββ), colour ratio (CR), linear particle depolarisation ratio (δδ) and lidar ratio (LR) from January to April. In contrast to previous years, in 2019 the early springtime backscatter increase in the troposphere, linked to Arctic haze, was not observed. In situ nss-sulphate (nss-SO42−) concentration was measured both at a coastal (Gruvebadet) and a mountain (Zeppelin) station, a few kilometres apart. As we employed different measurement techniques at sites embedded in complex orography, we investigated their agreement. From the lidar perspective, the aerosol load (indicated by ββ) above 700 m changed by less than a factor of 3.5. On the contrary, the daily nss-SO42− concentration erratically changed by a factor of 25 (from 0.1 to 2.5 ng m−3) both at Gruvebadet and Zeppelin station, with the latter mostly lying above the boundary layer. Moreover, daily nss-SO42− concentration was remarkably variable (correlation about 0.7 between the sites), despite its long-range origin. However, on a seasonal average basis the in situ sites agreed very well. Therefore, it can be argued that nss-SO42− advection mainly takes place in the lowest free troposphere, while under complex orography it is mixed downwards by local boundary layer processes. Our study suggests that at Arctic sites with complex orography ground-based aerosol properties show higher temporal variability compared to the free troposphere. This implies that the comparison between remote sensing and in situ observations might be more reasonable on longer time scales, i.e., monthly and seasonal basis even for nearby sites.
Nanobodies Provide Insight into the Molecular Mechanisms of the Complement Cascade and Offer New Therapeutic Strategies
Authors: Zarantonello Alessandra , Pedersen Henrik , Laursen Nick S. , Andersen Gregers R.
Published: February 2021

The complement system is part of the innate immune response, where it provides immediate protection from infectious agents and plays a fundamental role in homeostasis. Complement dysregulation occurs in several diseases, where the tightly regulated proteolytic cascade turns offensive. Prominent examples are atypical hemolytic uremic syndrome, paroxysmal nocturnal hemoglobinuria and Alzheimer’s disease. Therapeutic intervention targeting complement activation may allow treatment of such debilitating diseases. In this review, we describe a panel of complement targeting nanobodies that allow modulation at different steps of the proteolytic cascade, from the activation of the C1 complex in the classical pathway to formation of the C5 convertase in the terminal pathway. Thorough structural and functional characterization has provided a deep mechanistic understanding of the mode of inhibition for each of the nanobodies. These complement specific nanobodies are novel powerful probes for basic research and offer new opportunities for in vivo complement modulation.
Green Biosynthesis of Silver Nanoparticles Using Leaf Extract of Carissa carandas L. and Their Antioxidant and Antimicrobial Activity against Human Pathogenic Bacteria
Authors: Singh Reetika , Hano Christophe , Nath Gopal , Sharma Bechan
Published: February 2021

Carissa carandas L. is traditionally used as antibacterial medicine and accumulates many antioxidant phytochemicals. Here, we expand this traditional usage with the green biosynthesis of silver nanoparticles (AgNPs) achieved using a Carissa carandas L. leaf extract as a reducing and capping agent. The green synthesis of AgNPs reaction was carried out using 1mM silver nitrate and leaf extract. The effect of temperature on the synthesis of AgNPs was examined using room temperature (25 °C) and 60 °C. The silver nanoparticles were formed in one hour by stirring at room temperature. In this case, a yellowish brown colour was developed. The successful formation of silver nanoparticles was confirmed by UV–Vis, Fourier transform infrared (FT-IR) and X-ray diffraction (XRD) analysis. The characteristic peaks of the UV-vis spectrum and XRD confirmed the synthesis of AgNPs. The biosynthesised AgNPs showed potential antioxidant activity through DPPH assay. These AgNPs also exhibited potential antibacterial activity against human pathogenic bacteria. The results were compared with the antioxidant and antibacterial activities of the plant extract, and clearly suggest that the green biosynthesized AgNPs can constitute an effective antioxidant and antibacterial agent.
Color-Patterns to Architecture Conversion through Conditional Generative Adversarial Networks
Authors: Navarro-Mateu Diego , Carrasco Oriol , Cortes Nieves Pedro
Published: February 2021

Often an apparent complex reality can be extrapolated into certain patterns that in turn are evidenced in natural behaviors (whether biological, chemical or physical). The Architecture Design field has manifested these patterns as a conscious (inspired designs) or unconscious manner (emerging organizations). If such patterns exist and can be recognized, can we therefore use them as genotypic DNA? Can we be capable of generating a phenotypic architecture that is manifestly more complex than the original pattern? Recent developments in the field of Evo-Devo around gene regulators patterns or the explosive development of Machine Learning tools could be combined to set the basis for developing new, disruptive workflows for both design and analysis. This study will test the feasibility of using conditional Generative Adversarial Networks (cGANs) as a tool for coding architecture into color pattern-based images and translating them into 2D architectural representations. A series of scaled tests are performed to check the feasibility of the hypothesis. A second test assesses the flexibility of the trained neural networks against cases outside the database.
How Can We Treat Vulvar Carcinoma in Pregnancy? A Systematic Review of the Literature
Authors: Palicelli Andrea , Giaccherini Lucia , Zanelli Magda , Bonasoni Maria Paola , Gelli Maria Carolina , Bisagni Alessandra , Zanetti Eleonora , De Marco Loredana , Torricelli Federica , Manzotti Gloria , Gugnoni Mila , D’Ippolito Giovanni , Falbo Angela Immacolata , Sileo Filomena Giulia , Aguzzoli Lorenzo , Mastrofilippo Valentina , Bonacini Martina , De Giorgi Federica , Ricci Stefano , Bernardelli Giuditta , Ardighieri Laura , Zizzo Maurizio , De Leo Antonio , Santandrea Giacomo , de Biase Dario , Ragazzi Moira , Dalla Dea Giulia , Veggiani Claudia , Carpenito Laura , Sanguedolce Francesca , Asaturova Aleksandra , Boldorini Renzo , Disanto Maria Giulia , Goia Margherita , Wong Richard Wing-Cheuk , Singh Naveena , Mandato Vincenzo Dario
Published: February 2021

According to our systematic literature review (PRISMA guidelines), only 37 vulvar squamous cell carcinomas (VSCCs) were diagnosed during pregnancy (age range: 17–41 years). The tumor size range was 0.3–15 cm. The treatment was performed after (14/37, 38%), before (10/37, 27%), or before-and-after delivery (11/37, 30%). We found that 21/37 (57%) cases were stage I, 2 II (5%), 11 III (30%), and 3 IVB (8%). HPV-related features (condylomas/warts; HPV infection; high-grade squamous intraepithelial lesion) were reported in 11/37 (30%) cases. We also found that 9/37 (24%) patients had inflammatory conditions (lichen sclerosus/planus, psoriasis, chronic dermatitis). The time-to-recurrence/progression (12/37, 32%) ranged from 0 to 36 (mean 9) months. Eight women died of disease (22%) 2.5–48 months after diagnosis, 2 (5%) were alive with disease, and 23 (62%) were disease-free at the end of follow-up. Pregnant patients must be followed-up. Even if they are small, newly arising vulvar lesions should be biopsied, especially in women with risk factors (HPV, dermatosis, etc.). The treatment of VSCCs diagnosed in late third trimester might be delayed until postpartum. Elective cesarean section may prevent vulvar wound dehiscence. In the few reported cases, pregnancy/fetal outcomes seemed to not be affected by invasive treatments during pregnancy. However, clinicians must be careful; larger cohorts should define the best treatment. Definite guidelines are lacking, so a multidisciplinary approach and discussion with patients are mandatory.
Circulating Cell-Free DNA Methylation Profiles in the Early Detection of Ovarian Cancer: A Scoping Review of the Literature
Authors: Guo Xiaoyue M. , Miller Heather , Matsuo Koji , Roman Lynda D. , Salhia Bodour
Published: February 2021

Epithelial ovarian cancer is the most lethal gynecologic malignancy and has few reliable non-invasive tests for early detection or diagnosis. Recent advances in genomic techniques have bolstered the utility of cell-free DNA (cfDNA) evaluation from peripheral blood as a viable cancer biomarker. For multiple reasons, comparing alterations in DNA methylation is particularly advantageous over other molecular assays. We performed a literature review for studies exploring cfDNA methylation in serum and plasma for the early diagnosis of ovarian cancer. The data suggest that serum/plasma cfDNA methylation tests have strong diagnostic accuracies for ovarian cancer (median 85%, range 40–91%). Moreover, there is improved diagnostic performance if multiple genes are used and if the assays are designed to compare detection of ovarian cancer with benign pelvic masses. We further highlight the vast array of possible gene targets and techniques, and a need to include more earlier-stage ovarian cancer samples in test development. Overall, we show the promise of cfDNA methylation analysis in the development of a viable diagnostic biomarker for ovarian cancer.
Black Lives Matter: A Decomposition of Racial Inequalities in Oral Cancer Screening
Authors: Lam Benjamin , Jamieson Lisa M. , Mittinty Murthy
Published: February 2021

(1) Background: The Black Lives Matter movement has highlighted the discrepancies in public health in regard to race. This study aims to investigate tools that can be used to analyze and investigate this discrepancy, which can be applied to policymaking. (2) Methods: National Health and Nutrition Examination Survey (NHANES) data from 2011–2018 was combined (N = 22,617) to investigate discrepancies of oral cancer screening in Black Americans. We give examples of counterfactual techniques that can be used to guide policy. Inverse probability treatment weighting (IPTW) was used to remove all measured confounding in an interaction analysis to assess the combined effect of socioeconomic status and race. Blinder–Oaxaca decomposition was then used to investigate the intervenable factors associated with differences in race. (3) Results: Sub-additive interaction was found on additive and multiplicative scales when all measured confounding was removed via IPTW (relative excess risk due to interaction (RERI)(OR) = −0.55 (−0.67–−0.42)). Decomposition analysis found that 32% of the discrepancy could be explained by characteristics of higher education and poverty status. (4) Conclusions: Black Americans in poverty are less likely to seek oral cancer screening than the additive likelihood would suggest. Blinder–Oaxaca decomposition is a strong tool to use for guiding policy as it quantifies clear breakdowns of what intervenable factors there are that would improve the discrepancy the most.
Regioselective Hydroxylation of Oleanolic Acid Catalyzed by Human CYP3A4 to Produce Hederagenenin, a Chiral Metabolite
Authors: Cao Ngoc Tan , Nguyen Ngoc Anh , Le Thien-Kim , Cha Gun Su , Park Ki Deok , Yun Chul-Ho
Published: February 2021

Oleanolic acid (OA) is a pentacyclic triterpenoid widely found in plants and foods as an aglycone of triterpenoid saponins or as a free acid. OA exhibits beneficial activities for humans, including antitumor, antivirus, and hepatoprotection properties without apparent toxicity. The metabolites produced by the cytochrome P450 (P450) enzymes are critical for the evaluation of the efficacy and safety of drugs. In this study, the potential metabolites of OA were investigated by P450-catalyzed oxidation reactions. Among the various tested human P450s, only human CYP3A4 was active for the hydroxylation of OA. The major metabolite was characterized by a set of analyses using HPLC, LC–MS, and NMR. It was found to be 4-epi-hederagenenin, a chiral product, by regioselective hydroxylation of the methyl group at the C-23 position. These results indicated that CYP3A4 can hydroxylate an OA substrate to make 4-epi-hederagenenin. Possible drug–food interactions are discussed.
A LAT-Based Signaling Complex in the Immunological Synapse as Determined with Live Cell Imaging Is Less Stable in T Cells with Regulatory Capability
Authors: Li Yikui , Tunbridge Helen M. , Britton Graham J. , Hill Elaine V. , Sinai Parisa , Cirillo Silvia , Thompson Clare , Fallah-Arani Farnaz , Dovedi Simon J. , Wraith David C. , Wülfing Christoph
Published: February 2021

Peripheral immune regulation is critical for the maintenance of self-tolerance. Here we have investigated signaling processes that distinguish T cells with regulatory capability from effector T cells. The murine Tg4 T cell receptor recognizes a peptide derived from the self-antigen myelin basic protein. T cells from Tg4 T cell receptor transgenic mice can be used to generate effector T cells and three types of T cells with regulatory capability, inducible regulatory T cells, T cells tolerized by repeated in vivo antigenic peptide exposure or T cells treated with the tolerogenic drug UCB9608 (a phosphatidylinositol 4 kinase IIIβ inhibitor). We comparatively studied signaling in all of these T cells by activating them with the same antigen presenting cells presenting the same myelin basic protein peptide. Supramolecular signaling structures, as efficiently detected by large-scale live cell imaging, are critical mediators of T cell activation. The formation of a supramolecular signaling complex anchored by the adaptor protein linker for activation of T cells (LAT) was consistently terminated more rapidly in Tg4 T cells with regulatory capability. Such termination could be partially reversed by blocking the inhibitory receptors CTLA-4 and PD-1. Our work suggests that attenuation of proximal signaling may favor regulatory over effector function in T cells.
Potential Treatment of Lysosomal Storage Disease through Modulation of the Mitochondrial—Lysosomal Axis
Authors: Kuk Myeong Uk , Lee Yun Haeng , Kim Jae Won , Hwang Su Young , Park Joon Tae , Park Sang Chul
Published: February 2021

Lysosomal storage disease (LSD) is an inherited metabolic disorder caused by enzyme deficiency in lysosomes. Some treatments for LSD can slow progression, but there are no effective treatments to restore the pathological phenotype to normal levels. Lysosomes and mitochondria interact with each other, and this crosstalk plays a role in the maintenance of cellular homeostasis. Deficiency of lysosome enzymes in LSD impairs the turnover of mitochondrial defects, leading to deterioration of the mitochondrial respiratory chain (MRC). Cells with MRC impairment are associated with reduced lysosomal calcium homeostasis, resulting in impaired autophagic and endolysosomal function. This malicious feedback loop between lysosomes and mitochondria exacerbates LSD. In this review, we assess the interactions between mitochondria and lysosomes and propose the mitochondrial–lysosomal axis as a research target to treat LSD. The importance of the mitochondrial–lysosomal axis has been systematically characterized in several studies, suggesting that proper regulation of this axis represents an important investigative guide for the development of therapeutics for LSD. Therefore, studying the mitochondrial–lysosomal axis will not only add knowledge of the essential physiological processes of LSD, but also provide new strategies for treatment of LSD.
Tetra Schiff Bases as Polyvinyl Chloride Thermal Stabilizers
Authors: Ahmed Dina S. , Kadhom Mohammed , Hadi Angham G. , Bufaroosha Muna , Salih Nadia , Al-Dahhan Wedad H. , Yousif Emad
Published: February 2021

Tetra Schiff bases were used as thermal stabilizers to enhance the properties of polyvinyl chloride (PVC) when operated at high temperatures. The thermal stability of PVC films doped with Schiff bases was tested by the weight-loss method, Fourier transform infrared (FTIR) spectroscopy, thermal aging test, optical microscope, and atomic force microscope (AFM). Results showed that embedding these additives increased the stability time of the polymer, which decreased the degradation reaction tendency. Furthermore, the primary color of PVC was improved by adding the Schiff bases using oven-aging. In addition, these Schiff bases resulted in a significant reduction in PVC’s conjugated double bonds and, hence, the weight loss.
Removal of Odors (Mainly H2S and NH3) Using Biological Treatment Methods
Authors: Barbusiński Krzysztof , Parzentna-Gabor Anita , Kasperczyk Damian
Published: February 2021

This study reviews the available and most commonly used methods of gas deodorization. Comparing various methods of odor removal, undoubtedly biological methods of pollution degradation have an advantage over others—chemical and physical. This advantage is manifestedmainly in ecological and economic terms. The possibility of using biological methods to remove H2S and NH3, as the most common emitted by the municipal sector companies, was analyzed in terms of their removal efficiency. The method of bio-purification of air in biotrickling filters is more advantageous than the others, due to the high effectiveness of VOCs and odors degradation, lack of secondary pollutants, and economic aspects—it is a method competitive to the commonly used air purification method in biofilters.
Ultrasound-Assisted Synthesis and Crystal Structure of Novel 2D Cd (II) Metal–Organic Coordination Polymer with Nitrite End Stop Ligand as a Precursor for Preparation of CdO Nanoparticles
Authors: Hanifehpour Younes , Dadashi Jaber , Mirtamizdoust Babak
Published: February 2021

In the present research, a sonochemical approach was applied to prepare new cadmium(II) coordination 2D polymer, [Cd(L)(NO2)2]n (L = 1,2-bis(1-(pyridin-3-yl)ethylidene)hydrazine) and structurally characterized with various spectroscopic techniques including XRD, elemental analysis, SEM, and IR spectroscopy. The coordination number of cadmium (II) ions is seven (CdN2O5) by two nitrogen atoms from two organic Schiff base ligand and five oxygen of nitrite anions. The 2D sheet structures ended by nitrite anions and the nitrite anion displayed the end-stop role. The comprehensive system showed a three-dimensional structure with several weak interactions. The high-intensity ultrasound is regarded as an easy, environmentally-friendly, and flexible synthetic instrument for the compounds of coordination. CdO NPs was obtained by thermolysing 1 at 180 °C with oleic acid (as a surfactant). Further, the size and morphology of the produced CdO nanoparticles were investigated through SEM.
Possible Correlations between the ULF Geomagnetic Signature and Mw6.4 Coastal Earthquake, Albania, on 26 November 2019
Authors: Stănică Dragoș Armand , Stănică Dumitru
Published: February 2021

An earthquake of Mw6.4 hit the coastal zone of Albania on 26 November 2019, at 02:54:11 UTC. It was intensively felt at about 34 km away, in Tirana City, where damages and lives lost occurred. To emphasize a pre-seismic geomagnetic signature before the onset of this earthquake, the data collected on the interval 15 October–30 November 2019, at the Panagjurishte (PAG)-Bulgaria and Surlari (SUA)-Romania observatories were analyzed. Further on, for geomagnetic signal identification we used the polarization parameter (BPOL) which is time invariant in non-seismic conditions and it becomes unstable due to the strain effect related to the Mw6.4earthquake. Consequently, BPOL time series and its standard deviations are performed for the both sites using ultra low frequency (ULF)-fast Fourier transform (FFT) band-pass filtering. A statistical analysis, based on a standardized random variable equation, was applied to emphasize on the BPOL* (PAG) and ABS BPOL* (PAG) time series the anomalous signal’s singularity and, to differentiate the transient local anomalies due to the Mw6.4 earthquake, from the internal and external parts of the geomagnetic field, taken PAG observatory as reference. Finally, the ABS BPOL* (PAG-SUA) time series were obtained on the interval 1–30 November 2019, where a geomagnetic signature greater than 2.0, was detected on 23 November and the lead time was 3 days before the onset of the Mw6.4earthquake.
Improving Climate Change Awareness of Preservice Teachers (PSTs) through a University Science Learning Environment
Authors: Jeong Jin Su , González-Gómez David , Conde-Núñez María Carmen , Sánchez-Cepeda José Samuel , Yllana-Prieto Félix
Published: February 2021

The position of universities is of great importance in climate change education (CCE) if the scientific, environmental, social, and political challenges the world confronts are to be met. It is, therefore, crucial to comprehend the CCE being engaged in globally by higher education institutions (HEIs). It is also important to discover and analyze the ways that HEIs can better address this challenge. Consistent with the requirements of research, this study offers an analysis of climate change awareness-raising of preservice teachers (PSTs) in a university science classroom with a flipped class intervention. A total of 109 students participated in this research: 55 students in the control group (Group 1) and 54 students in the experimental group (Group 2). A questionnaire was used to detect any significant difference in the students’ awareness of climate change for the two groups and before and after course completion. The analyzed results exposed the improved awareness of climate change in PSTs after a flipped class intervention, and, therefore, PSTs were more willing to engage in climate change teaching. Hence, the results of this study will contribute significantly to reducing existing drawbacks, which will be vital to comprehend the professional teaching developments of preservice teachers. Thus, this research can offer various instances of clarifying how climate change education may be placed in a higher science education context with certain adaptations.
Time-Domain Analysis of Fractional Electrical Circuit Containing Two Ladder Elements
Authors: Piotrowska Ewa , Rogowski Krzysztof
Published: February 2021

The paper is devoted to the theoretical and experimental analysis of an electric circuit consisting of two elements that are described by fractional derivatives of different orders. These elements are designed and performed as RC ladders with properly selected values of resistances and capacitances. Different orders of differentiation lead to the state-space system model, in which each state variable has a different order of fractional derivative. Solutions for such models are presented for three cases of derivative operators: Classical (first-order differentiation), Caputo definition, and Conformable Fractional Derivative (CFD). Using theoretical models, the step responses of the fractional electrical circuit were computed and compared with the measurements of a real electrical system.
Review of Electric Vehicle Converter Configurations, Control Schemes and Optimizations: Challenges and Suggestions
Authors: Lipu Molla S. Hossain , Faisal Mohammad , Ansari Shaheer , Hannan Mahammad A. , Karim Tahia F. , Ayob Afida , Hussain Aini , Miah Md. Sazal , Saad Mohamad Hanif Md
Published: February 2021

Electric vehicles are receiving widespread attention around the world due to their improved performance and zero carbon emissions. The effectiveness of electric vehicles depends on proper interfacing between energy storage systems and power electronics converters. However, the power delivered by energy storage systems illustrates unstable, unregulated and substantial voltage drops. To overcome these limitations, electric vehicle converters, controllers and modulation schemes are necessary to achieve a secured and reliable power transfer from energy storage systems to the electric motor. Nonetheless, electric vehicle converters and controllers have shortcomings including a large number of components, high current stress, high switching loss, slow dynamic response and computational complexity. Therefore, this review presents a detailed investigation of different electric vehicle converters highlighting topology, features, components, operation, strengths and weaknesses. Moreover, this review explores the various types of electric vehicle converter controllers and modulation techniques concerning functional capabilities, operation, benefits and drawbacks. Besides, the significance of optimization algorithms in electric vehicle converters is illustrated along with their objective functions, executions and various factors. Furthermore, this review explores the key issues and challenges of electric vehicle converters, controllers and optimizations to identify future research gaps. Finally, important and specific suggestions are delivered toward the development of an efficient converter for future sustainable electric vehicle applications.
Depolarizing Chipless Tags with Polarization Insensitive Capabilities
Authors: Borgese Michele , Costa Filippo , Genovesi Simone , Manara Giuliano
Published: February 2021

A novel depolarizing chipless tag configuration with high angular insensitivity is presented. The basic tag comprises two dipole resonators arranged with a relative rotation of 45°. The proposed configuration improves the depolarization properties performance of a single dipole over the ground plane which provides a peak with perfect polarization conversion only if the electric field impinges at 45° with respect to the dipole resonator. The second dipole arranged at 45° compensates the cross-polar reduction which is observed when the electric field is not correctly polarized. Indeed, when the field is tilted by 90° with respect to the first dipole, it forms an angle of 45° with the second one. The proposed configuration is also analyzed for providing multiple frequency peaks. A tag with 4 angular independent frequency peaks laying between 2 GHz and 5.5 GHz is designed. Angular frequency maps are used to illustrate the peculiar frequency shifts achieved when the electric fields rotate in the plane of the dipole. Finally, a prototype of the polarization insensitive tags is fabricated and measured to confirm the simulated results.
Ensemble Machine Learning Assisted Reservoir Characterization Using Field Production Data–An Offshore Field Case Study
Authors: Wang Baozhong , Sharma Jyotsna , Chen Jianhua , Persaud Patricia
Published: February 2021

Estimation of fluid saturation is an important step in dynamic reservoir characterization. Machine learning techniques have been increasingly used in recent years for reservoir saturation prediction workflows. However, most of these studies require input parameters derived from cores, petrophysical logs, or seismic data, which may not always be readily available. Additionally, very few studies incorporate the production data, which is an important reflection of the dynamic reservoir properties and also typically the most frequently and reliably measured quantity throughout the life of a field. In this research, the random forest ensemble machine learning algorithm is implemented that uses the field-wide production and injection data (both measured at the surface) as the only input parameters to predict the time-lapse oil saturation profiles at well locations. The algorithm is optimized using feature selection based on feature importance score and Pearson correlation coefficient, in combination with geophysical domain-knowledge. The workflow is demonstrated using the actual field data from a structurally complex, heterogeneous, and heavily faulted offshore reservoir. The random forest model captures the trends from three and a half years of historical field production, injection, and simulated saturation data to predict future time-lapse oil saturation profiles at four deviated well locations with over 90% R-square, less than 6% Root Mean Square Error, and less than 7% Mean Absolute Percentage Error, in each case.
Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter
Authors: Yang Kuo , Tang Yugui , Zhang Zhen
Published: February 2021

With the development of new energy vehicle technology, battery management systems used to monitor the state of the battery have been widely researched. The accuracy of the battery status assessment to a great extent depends on the accuracy of the battery model parameters. This paper proposes an improved method for parameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Using a two-order equivalent circuit model, the battery model is divided into two parts based on fast dynamics and slow dynamics. The recursive least squares method is used to identify parameters of the battery, and then the SOC and the open-circuit voltage of the model is estimated with the extended Kalman filter. The two-module voltages are calculated using estimated open circuit voltage and initial parameters, and model parameters are constantly updated during iteration. The proposed method can be used to estimate the parameters and the SOC in real time, which does not need to know the state of SOC and the value of open circuit voltage in advance. The method is tested using data from dynamic stress tests, the root means squared error of the accuracy of the prediction model is about 0.01 V, and the average SOC estimation error is 0.0139. Results indicate that the method has higher accuracy in offline parameter identification and online state estimation than traditional recursive least squares methods.
Practical CO2—WAG Field Operational Designs Using Hybrid Numerical-Machine-Learning Approaches
Authors: Sun Qian , Ampomah William , You Junyu , Cather Martha , Balch Robert
Published: February 2021

Machine-learning technologies have exhibited robust competences in solving many petroleum engineering problems. The accurate predictivity and fast computational speed enable a large volume of time-consuming engineering processes such as history-matching and field development optimization. The Southwest Regional Partnership on Carbon Sequestration (SWP) project desires rigorous history-matching and multi-objective optimization processes, which fits the superiorities of the machine-learning approaches. Although the machine-learning proxy models are trained and validated before imposing to solve practical problems, the error margin would essentially introduce uncertainties to the results. In this paper, a hybrid numerical machine-learning workflow solving various optimization problems is presented. By coupling the expert machine-learning proxies with a global optimizer, the workflow successfully solves the history-matching and CO2 water alternative gas (WAG) design problem with low computational overheads. The history-matching work considers the heterogeneities of multiphase relative characteristics, and the CO2-WAG injection design takes multiple techno-economic objective functions into accounts. This work trained an expert response surface, a support vector machine, and a multi-layer neural network as proxy models to effectively learn the high-dimensional nonlinear data structure. The proposed workflow suggests revisiting the high-fidelity numerical simulator for validation purposes. The experience gained from this work would provide valuable guiding insights to similar CO2 enhanced oil recovery (EOR) projects.
Ethanol Production from Olive Stones through Liquid Hot Water Pre-Treatment, Enzymatic Hydrolysis and Fermentation. Influence of Enzyme Loading, and Pre-Treatment Temperature and Time
Authors: Cuevas Manuel , García Martín Juan F. , Bravo Vicente , Sánchez Sebastián
Published: February 2021

Olive table industry, olive mills and olive pomace oil extraction industries annually generate huge amounts of olive stones. One of their potential applications is the production of bioethanol by fractionation of their lignocellulose constituents and subsequent fermentation of the released sugars using yeasts. In this work, we studied the influence of temperature (175–225 °C) and residence time (0–5 min) in the liquid hot-water pre-treatment of olive stones as well as the initial enzyme loading (different mixtures of cellulases, hemicellulases and β–glucosidases) in the later enzymatic hydrolysis on the release of fermentable sugars. The Chrastil’s model was applied to the d-glucose data to relate the severity of pre-treatment to enzyme diffusion through the pre-treated cellulose. Finally, the hydrolysate obtained under the most suitable conditions (225 °C and 0 min for pre-treatment; 24 CE initial enzyme concentration) was fermented into ethanol using the yeast Pachysolen tannophilus ATCC 32691. Considering the overall process, 6.4 dm3 ethanol per 100 kg olive stones were produced.
In Situ Product Recovery of Bio-Based Industrial Platform Chemicals: A Guideline to Solvent Selection
Authors: De Brabander Pieter , Uitterhaegen Evelien , Verhoeven Ellen , Vander Cruyssen Cedric , De Winter Karel , Soetaert Wim
Published: February 2021

In situ product recovery (ISPR), in the form of an extractive fermentation process, can increase productivity and product titers in the sustainable production of platform chemicals. To establish a guideline for the development of industrially relevant production processes for such bio-based compounds, a wide screening was performed, mapping the potential of an extensive range of solvents and solvent mixtures. Besides solvent biocompatibility with Saccharomyces cerevisiae, distribution coefficients of three organic acids (protocatechuic acid, adipic acid and para-aminobenzoic acid) and four fragrance compounds (2-phenylethanol, geraniol, trans-cinnamaldehyde and β-ionone) were determined. While for highly hydrophobic fragrance compounds, multiple pure solvents were identified that were able to extract more than 98%, reactive extraction mixtures were proven effective for more challenging compounds including organic acids and hydrophilic alcohols. For example, a reactive mixture consisting of 12.5% of the extractant CYTOP 503 in canola oil was found to be biocompatible and showed superior extraction efficiency for the challenging compounds as compared to any biocompatible single solvent. This mapping of biocompatible solvents and solvent mixtures for the extraction of various classes of industrial platform chemicals can be a tremendous step forward in the development of extractive fermentations.
Development of a Methodology for Estimating the Ergosterol in Meat Product-Borne Toxigenic Moulds to Evaluate Antifungal Agents
Authors: Álvarez Micaela , Rodríguez Alicia , Bermúdez Elena , Roncero Elia , Andrade María J.
Published: February 2021

Antifungal agents are commonly used in the meat industry to prevent the growth of unwanted moulds, such as toxigenic ones, on dry-cured meat products. For enhancing the application of antifungals, their mode of action must be evaluated. Their effect on the mould ergosterol content is one of the most studied ones, since it is the target site of some commercialised antifungals or of those that are in development. The aim of this study was to develop a methodology for determining how the antifungal agents used in the meat industry work. A method for analysing ergosterol was firstly developed using high-performance liquid chromatography with fluorescence detection coupled to a diode array detector (HPLC-FLD/DAD). The chromatographically optimised conditions (gradient and mobile phases) allowed us to reduce the time per analysis with respect to previously published methods up to 22 min. Withing the six checked extraction methods, method 5, showing the best mean recovery values (99.51%), the shortest retention time (15.8 min), and the lowest standard deviation values (9.92) and working temperature (60 °C), was selected. The limit of detection and limit of quantification were 0.03 and 0.1 µg/mL, respectively. All the validation parameters corroborated the method’s suitability. Finally, its feasibility for evaluating the effect of a commercial antifungal preparation (AP) and different herbs that are frequently added to meat products on the ergosterol content of several toxigenic moulds was studied. Differences at the strain level were obtained in the presence of AP. Moreover, the addition of herbs significantly reduced the ergosterol content in Penicillium nordicum up to 83.91%. The developed methodology is thus suitable for screening the antifungals’ role in altering mould ergosterol biosynthesis before their application in real meat products.
In Vivo Genotoxicity Evaluation of a Stilbene Extract Prior to Its Use as a Natural Additive: A Combination of the Micronucleus Test and the Comet Assay
Authors: Medrano-Padial Concepción , Puerto María , Prieto Ana Isabel , Ayala Nahúm , Beaumont Pauline , Rouger Caroline , Krisa Stéphanie , Pichardo Silvia
Published: February 2021

Genotoxic data of substances that could be used as food additives are required by the European Food Safety Authority. In this sense, the use of an extract from grapevine shoots containing a stilbene richness of 99% (ST-99), due to its antioxidant and antibacterial activities, has been proposed as an alternative to sulfur dioxide in wine. The aim of this work was to study, for the first time, the in vivo genotoxic effects produced in rats orally exposed to 90, 180, or 360 mg ST-99/kg body weight at 0, 24, and 45 h. The combination of micronucleus assay in bone marrow (OECD 474) and standard (OECD 489) and enzyme-modified comet assay was used to determine the genotoxicity on cells isolated from stomach, liver, and blood of exposed animals. The ST-99 revealed no in vivo genotoxicity. These results were corroborated by analytical studies that confirm the presence of stilbenes and their metabolites in plasma and tissues. Moreover, to complete these findings, a histopathological study was performed under light microscopy in liver and stomach showing only slight modifications in both organs at the highest concentration used. The present work confirms that this extract is not genotoxic presenting a good profile for its potential application as a preservative in the wine industry.