bluuebunny/crossref_metadata_2025 huggingface dataset:
Three-Year Follow-Up of the POIBA Intervention on Childhood Obesity: A Quasi-Experimental Study
Authors: Sánchez-Martínez Francesca , Brugueras Silvia , Serral Gemma , Valmayor Sara , Juárez Olga , López María José , Ariza Carles ,   on behalf of the POIBA Project Evaluation Group
Published: January 2021

Childhood obesity has increased worldwide over the past four decades. This quasi-experimental study aimed to assess the effectiveness of a multicomponent and multilevel school-based intervention (POIBA) at 3 years of follow-up. The nutrition intervention focused on food groups, food pyramid, nutrients, portions, and balanced menus. In total, 3624 children participated in the study. Anthropometric measurements and information on food frequency and behavior, physical activity, and daily screen use were collected in the intervention (IG) and comparison group (CG). Positive unadjusted changes toward adherence to recommendations were found for water, meat, sweets, and fried potato consumption, proper breakfast, not having dinner in front of the TV, out-of-school physical activity, and daily screen use. Three scores were used to calculate the proportion of children making more than one change to improve healthy habits regarding physical activity (global Activity score), nutrition (global Nutrition score), and both (global score). Students exposed to the intervention had a significantly better global Activity score (16.2% IG vs. 11.9% CG; p = 0.012) and Global score (63.9% IG vs. 58.5% CG; p = 0.025). Intervention effects on obesity incidence at 3-year follow-up lost significance but maintained the positive trend. In conclusion, school-based interventions including a family component could be useful to address the childhood obesity problem.
Hyaluronic Acid-Modified and Doxorubicin-Loaded Gold Nanoparticles and Evaluation of Their Bioactivity
Authors: Li Lin-Song , Ren Bin , Yang Xiaojing , Cai Zhong-Chao , Zhao Xue-Jie , Zhao Mei-Xia
Published: January 2021

Functionalized gold nanoparticles (AuNPs) have been successfully used in many fields as a result of having low cytotoxicity, good biocompatibility, excellent optical properties, and their ability to target cancer cells. Here, we synthesized AuNP carriers that were modified by hyaluronic acid (HA), polyethylene glycol (PEG), and adipic dihydrazide (ADH). The antitumor drug doxorubicin (Dox) was loaded into AuNP carriers and attached chemically. The Au nanocomposite AuNPs@MPA-PEG-HA-ADH-Dox was able to disperse uniformly in aqueous solution, with a diameter of 15 nm. The results of a 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyltetrazolium bromide (MTT) assay indicated that AuNP carriers displayed very little toxicity toward cells in high doses, although the antitumor properties of Au nanocomposites were significantly enhanced. Cellular uptake experiments demonstrated that AuNPs modified with hyaluronic acid were more readily ingested by HepG2 and HCT-116 cells, as they have a large number of CD44 receptors. A series of experiments measuring apoptosis such as Rh123 and annexin V-FITC staining, and analysis of mitochondrial membrane potential (MMP) analysis, indicated that apoptosis played a role in the inhibition of cell proliferation by AuNPs@MPA-PEG-HA-ADH-Dox. Excessive production of reactive oxygen species (ROS) was the principal mechanism by which the Au nanocomposites inhibited cell proliferation, leading to apoptosis. Thus, the Au nanocomposites, which allowed cell imaging in real-time and induced apoptosis in specific cell types, represent theragnostic agents with potential for future clinical applications in bowel cancer.
Metabolite Profiling of Methanolic Extract of Gardenia jaminoides by LC-MS/MS and GC-MS and Its Anti-Diabetic, and Anti-Oxidant Activities
Authors: Saravanakumar Kandasamy , Park SeonJu , Sathiyaseelan Anbazhagan , Kim Kil-Nam , Cho Su-Hyeon , Mariadoss Arokia Vijaya Anand , Wang Myeong-Hyeon
Published: January 2021

In this study, the methanolic extract from seeds of Gardenia jasminoides exhibited strong antioxidant and enzyme inhibition activities with less toxicity to NIH3T3 and HepG2 cells at the concentration of 100 µg/mL. The antioxidant activities (DPPH and ABTS), α-amylase, and α-glucosidase inhibition activities were found higher in methanolic extract (MeOH-E) than H2O extract. Besides, 9.82 ± 0.62 µg and 6.42 ± 0.26 µg of MeOH-E were equivalent to 1 µg ascorbic acid for ABTS and DPPH scavenging, respectively while 9.02 ± 0.25 µg and 6.52 ± 0.15 µg of MeOH-E were equivalent to 1 µg of acarbose for inhibition of α-amylase and α-glucosidase respectively. Moreover, the cell assay revealed that the addition of MeOH-E (12.5 µg/mL) increased about 37% of glucose uptake in insulin resistant (IR) HepG2 as compared to untreated IR HepG2 cells. The LC- MS/MS and GC-MS analysis of MeOH-E revealed a total of 54 compounds including terpenoids, glycosides, fatty acid, phenolic acid derivatives. Among the identified compounds, chlorogenic acid and jasminoside A were found promising for anti-diabetic activity revealed by molecular docking study and these molecules are deserving further purification and molecular analysis.
Co-Amorphous Formulations of Furosemide with Arginine and P-Glycoprotein Inhibitor Drugs
Authors: Ruponen Marika , Kettunen Konsta , Santiago Pires Monica , Laitinen Riikka
Published: January 2021

In this study, the amino acid arginine (ARG) and P-glycoprotein (P-gp) inhibitors verapamil hydrochloride (VER), piperine (PIP) and quercetin (QRT) were used as co-formers for co-amorphous mixtures of a Biopharmaceutics classification system (BCS) class IV drug, furosemide (FUR). FUR mixtures with VER, PIP and QRT were prepared by solvent evaporation, and mixtures with ARG were prepared by spray drying in 1:1 and 1:2 molar ratios. The solid-state properties of the mixtures were characterized with X-ray powder diffraction (XRPD), Fourier-transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) in stability studies under different storage conditions. Simultaneous dissolution/permeation studies were conducted in side-by-side diffusion cells with a PAMPA (parallel artificial membrane permeability assay) membrane as a permeation barrier. It was observed with XRPD that ARG, VER and PIP formed co-amorphous mixtures with FUR at both molar ratios. DSC and FTIR revealed single glass transition values for the mixtures (except for FUR:VER 1:2), with the formation of intermolecular interactions between the components, especially salt formation between FUR and ARG. The co-amorphous mixtures were found to be stable for at least two months under an elevated temperature/humidity, except FUR:ARG 1:2, which was sensitive to humidity. The dissolution/permeation studies showed that only the co-amorphous FUR:ARG mixtures were able to enhance both the dissolution and permeation of FUR. Thus, it is concluded that formulating co-amorphous salts with ARG may be a promising option for poorly soluble/permeable FUR.
Introduction to Special Issue “Human Enhancement Technologies and Our Merger with Machines”
Authors: Barfield Woodrow , Blodgett-Ford Sayoko
Published: January 2021

We are pleased to introduce the authors and papers which form the Special Issue “Human Enhancement Technologies and Our Merger with Machines” [...]
Antibacterial Potential of Bacillus amyloliquefaciens GJ1 against Citrus Huanglongbing
Authors: Nan Jing , Zhang Shaoran , Jiang Ling
Published: January 2021

Citrus huanglongbing (HLB) is a destructive disease caused by Candidatus Liberibacter species and is a serious global concern for the citrus industry. To date, there is no established strategy for control of this disease. Previously, Bacillus amyloliquefaciens GJ1 was screened as the biocontrol agent against HLB. In this study, two-year-old citrus infected by Ca. L. asiaticus were treated with B. amyloliquefaciens GJ1 solution via root irrigation. In these plants, after seven irrigation treatments, the results indicated that the photosynthetic parameters, chlorophyll content, resistance-associated enzyme content and the expression of defense-related genes were significantly higher than for the plants treated with the same volume water. The content of starch and soluble sugar were significantly lower, compared to the control treatment. The parallel reaction monitoring (PRM) results revealed that treatment with B. amyloliquefaciens GJ1 solution, the expression levels of 3 proteins with photosynthetic function were upregulated in citrus leaves. The accumulation of reactive oxygen species (ROS) in citrus leaves treated with B. amyloliquefaciens GJ1 flag22 was significantly higher than untreated plants and induced the defense-related gene expression in citrus. Finally, surfactin was identified from the fermentation broth of B. amyloliquefaciens GJ1 by high-performance liquid chromatography. These results indicate that B. amyloliquefaciens GJ1 may improve the immunity of citrus by increasing the photosynthesis and enhancing the expression of the resistance-related genes.
Effects of Fabrication Methods on the Performance of Luminescent Solar Concentrators Based on Doped Polymer Optical Fibers
Authors: Arrospide Eneko , Illarramendi María Asunción , Ayesta Igor , Guarrotxena Nekane , García Olga , Zubia Joseba , Durana Gaizka
Published: January 2021

In this work, we detail two types of fabrication processes of four polymer optical fibers doped with lumogen dyes. The fiber preforms have been manufactured with two different methods: extrusion and casting. We have compared the performance of the two types of fibers as luminescent solar concentrators by calculating their optical efficiencies and concentration factors. The obtained results show better performance for those fibers manufactured by the casting process. We have also studied the photostability of the two types of fibers doped with the dye lumogen red under solar light radiation. A high thermal stability of the doped fibers has been observed.
Investigation of Functionalized Surface Charges of Thermoplastic Starch/Zinc Oxide Nanocomposite Films Using Polyaniline: The Potential of Improved Antibacterial Properties
Authors: Charoensri Korakot , Rodwihok Chatchai , Wongratanaphisan Duangmanee , Ko Jung A. , Chung Jin Suk , Park Hyun Jin
Published: January 2021

Improving the antibacterial activity of biodegradable materials is crucial for combatting widespread drug-resistant bacteria and plastic pollutants. In this work, we studied polyaniline (PANI)-functionalized zinc oxide nanoparticles (ZnO NPs) to improve surface charges. A PANI-functionalized ZnO NP surface was prepared using a simple impregnation technique. The PANI functionalization of ZnO successfully increased the positive surface charge of the ZnO NPs. In addition, PANI-functionalized ZnO improved mechanical properties and thermal stability. Besides those properties, the water permeability of the bionanocomposite films was decreased due to their increased hydrophobicity. PANI-functionalized ZnO NPs were applied to thermoplastic starch (TPS) films for physical properties and antibacterial studies using Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The PANI-functionalized ZnO bionanocomposite films exhibited excellent antibacterial activity for both E. coli (76%) and S. aureus (72%). This result suggests that PANI-functionalized ZnO NPs can improve the antibacterial activity of TPS-based bionanocomposite films.
Integrating Machine Learning, Radio Frequency Identification, and Consignment Policy for Reducing Unreliability in Smart Supply Chain Management
Authors: Sardar Suman Kalyan , Sarkar Biswajit , Kim Byunghoon
Published: January 2021

Adopting smart technologies for supply chain management leads to higher profits. The manufacturer and retailer are two supply chain players, where the retailer is unreliable and may not send accurate demand information to the manufacturer. As an advanced smart technology, Radio Frequency Identification (RFID) is implemented to track and trace each product’s movement on a real-time basis in the inventory. It takes this supply chain to a smart supply chain management. This research proposes a Machine Learning (ML) approach for on-demand forecasting under smart supply chain management. Using Long-Short-Term Memory (LSTM), the demand is forecasted to obtain the exact demand information to reduce the overstock or understock situation. A measurement for the environmental effect is also incorporated with the model. A consignment policy is applied where the manufacturer controls the inventory, and the retailer gets a fixed fee along with a commission for selling each product. The manufacturer installs RFID technology at the retailer’s place. Two mathematical models are solved using a classical optimization technique. The results from those two models show that the ML-RFID model gives a higher profit than the existing traditional system.
Special Issue on “Process Modeling in Pyrometallurgical Engineering”
Authors: Saxén Henrik , Ramírez-Argáez Marco A. , Conejo Alberto N. , Dutta Abhishek
Published: January 2021

This Special Issue on “Process Modeling in Pyrometallurgical Engineering” consists of 39 articles, including two review papers, and covers a wide range of topics related to process development and analysis based on modeling in ironmaking, steelmaking, flash smelting, casting, rolling operations, etc [...]
Fault Detection of Diesel Engine Air and after-Treatment Systems with High-Dimensional Data: A Novel Fault-Relevant Feature Selection Method
Authors: Ran Qilan , Song Yedong , Du Wenli , Du Wei , Peng Xin
Published: January 2021

In order to reduce pollutants of the emission from diesel vehicles, complex after-treatment technologies have been proposed, which make the fault detection of diesel engines become increasingly difficult. Thus, this paper proposes a canonical correlation analysis detection method based on fault-relevant variables selected by an elitist genetic algorithm to realize high-dimensional data-driven faults detection of diesel engines. The method proposed establishes a fault detection model by the actual operation data to overcome the limitations of the traditional methods, merely based on benchmark. Moreover, the canonical correlation analysis is used to extract the strong correlation between variables, which constructs the residual vector to realize the fault detection of the diesel engine air and after-treatment system. In particular, the elitist genetic algorithm is used to optimize the fault-relevant variables to reduce detection redundancy, eliminate additional noise interference, and improve the detection rate of the specific fault. The experiments are carried out by implementing the practical state data of a diesel engine, which show the feasibility and efficiency of the proposed approach.
Low-Viscosity Ether-Functionalized Ionic Liquids as Solvents for the Enhancement of Lignocellulosic Biomass Dissolution
Authors: Rahim Asyraf Hanim Ab , Yunus Normawati M. , Hamzah Wan Suzaini Wan , Sarwono Ariyanti , Muhammad Nawshad
Published: January 2021

Due to the substantial usage of fossil fuels, the utilization of lignocellulosic biomass as renewable sources for fuels and chemical production has been widely explored. The dissolution of lignocellulosic biomass in proper solvents is vital prior to the extraction of its important constituents, and ionic liquids (ILs) have been found to be efficient solvents for biomass dissolution. However, the high viscosity of ILs limits the dissolution process. Therefore, with the aim to enhance the dissolution of lignocellulosic biomass, a series of new ether-functionalized ILs with low viscosity values were synthesized and characterized. Their properties, such as density, viscosity and thermal stability, were analyzed and discussed in comparison with a common commercial IL, namely 1-butyl-3-methylimidazolium chloride (BMIMCl). The presence of the ether group in the new ILs reduces the viscosity of the ILs to some appreciable extent in comparison to BMIMCl. 1-2(methoxyethyl)-3-methylimidazolium chloride (MOE-MImCl), which possesses the lowest viscosity value among the other ether-functionalized ILs, demonstrates an ability to be a powerful solvent in the application of biomass dissolution via the sonication method. In addition, an optimization study employing response surface methodology (RSM) was carried out in order to obtain the optimum conditions for maximum dissolution of biomass in the solvents. Results suggested that the maximum biomass dissolution can be achieved by using 3 weight% of initial biomass loading with 40% amplitude of sonication at 32.23 min of sonication period.
Visible Light-Driven Photocatalytic Rhodamine B Degradation Using CdS Nanorods
Authors: Ullah Haseeb , Viglašová Eva , Galamboš Michal
Published: January 2021

In this work, highly crystalline CdS nanorods (NRs) were successfully synthesized by a facile, one-step solvothermal method. The as-prepared CdS NRs powder was characterized by XRD, FESEM, Raman, PL, XPS, BET, and UV-visible techniques to evaluate the structural, morphological, and optical properties. The photocatalytic performance of the as-synthesized CdS NRs was investigated for the photodegradation of RhB dye under visible light irradiations. It has been found that CdS NRs show maximum RhB degradation efficiency of 88.4% in 120 min. The excellent photodegradation ability of the CdS NRs can be attributed to their rod-like structure together with their large surface area and surface state. The kinetic study indicated that the photodegradation process was best described by the pseudo-first-order kinetic model. The possible mechanism for the photodegradation of RhB dye over CdS NRs was proposed in this paper.
Predicting the Potency of Anti-Alzheimer’s Drug Combinations Using Machine Learning
Authors: Anastasio Thomas J.
Published: January 2021

Clinical trials of single drugs intended to slow the progression of Alzheimer’s Disease (AD) have been notoriously unsuccessful. Combinations of repurposed drugs could provide effective treatments for AD. The challenge is to identify potentially effective combinations. To meet this challenge, machine learning (ML) was used to extract the knowledge from two leading AD databases, and then “the machine” predicted which combinations of the drugs in common between the two databases would be the most effective as treatments for AD. Specifically, three-layered artificial neural networks (ANNs) with compound, gated units in their internal layer were trained using ML to predict the cognitive scores of participants, separately in either database, given other data fields including age, demographic variables, comorbidities, and drugs taken. The predictions from the separately trained ANNs were statistically highly significantly correlated. The best drug combinations, jointly determined from both sets of predictions, were high in nonsteroidal anti-inflammatory drugs; anticoagulant, lipid-lowering, and antihypertensive drugs; and female hormones. The results suggest that the neurodegenerative processes that underlie AD and other dementias could be effectively treated using a combination of repurposed drugs. Predicted drug combinations could be evaluated in clinical trials.
In-Depth Analysis of the Plasma Proteome in ME/CFS Exposes Disrupted Ephrin-Eph and Immune System Signaling
Authors: Germain Arnaud , Levine Susan M. , Hanson Maureen R.
Published: January 2021

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling disease with worldwide prevalence and limited therapies exclusively aimed at treating symptoms. To gain insights into the molecular disruptions in ME/CFS, we utilized an aptamer-based technology that quantified 4790 unique human proteins, allowing us to obtain the largest proteomics dataset yet available for this disease, detecting highly abundant proteins as well as rare proteins over a nine-log dynamic range. We report a pilot study of 20 ME/CFS patients and 20 controls, all females. Significant differences in the levels of 19 proteins between cohorts implicate pathways related to the extracellular matrix, the immune system and cell–cell communication. Outputs of pathway and cluster analyses robustly highlight the ephrin pathway, which is involved in cell–cell signaling and regulation of an expansive variety of biological processes, including axon guidance, angiogenesis, epithelial cell migration, and immune response. Receiver Operating Characteristic (ROC) curve analyses distinguish the plasma proteomes of ME/CFS patients from controls with a high degree of accuracy (Area Under the Curve (AUC) > 0.85), and even higher when using protein ratios (AUC up to 0.95), that include some protein pairs with established biological relevance. Our results illustrate the promise of plasma proteomics for diagnosing and deciphering the molecular basis of ME/CFS.
Belonging through Events? Exploring the Demographic Profile, Motivations, and Experiences of Those Attending the Afternoon Carol Services on Christmas Eve at Liverpool Cathedral
Authors: Francis Leslie J. , Jones Susan H. , McKenna Ursula , Pike Nelson , Williams Emma
Published: January 2021

This study tests the strength of Bishop David Walker’s notion of belonging to God through the Anglican Church through participation in events, by exploring the demographic profile, motivations, and experiences of 1234 participants attending the two afternoon Carol Services on Christmas Eve 2019 at Liverpool Cathedral, alongside 564 participants who completed the same survey at the evening Holly Bough Service on the Fourth Sunday in Advent 2019. The data confirmed the importance of event-belonging for 76% of the participants who do not regularly attend church services but who return year on year to the Cathedral and often invite friends to join them. The data also affirmed the presence of newcomers (12%) alongside returnees. Between two-thirds and three-quarters of the participants perceived beneficial impact on their personal wellbeing. For the participants, what drew them to the Cathedral and what made the experience so special was not simply the quality of the music (93%), but also the opportunity to remember the Christmas story (82%).
On the Necessity of Ritual Sensibility in Public Protest: A Hong Kong Perspective
Authors: Mok Bryan K. M.
Published: January 2021

In Hong Kong, the efficacy of ritualized protest has become an issue of hot debate in recent years. Whereas ritualized protest is a long-term political practice in the Hong Kong pro-democracy movement that has considerable influence, skepticism about it has grown remarkably within the radical faction of the movement. Against this background, this paper aims to offer a theoretical reflection on the role of ritualized protest in the Hong Kong pro-democracy movement. It will take an auto-ethnographic approach to reflect on the material culture of Hong Kong public protests and engage in the recent controversy over ritualized protest. This study shows that although ritualized protest can hardly achieve actual political changes in the short run, ritual sensibility is essential to the promulgation and the passing-on of social and political values. This applies not only to ritualized protests that are largely peaceful, rational, and non-violent but also to militant protests that are open to the use of violence. This emphasis on the underlying importance of ritual sensibility invites both the liberal democratic and the radical factions to introspect whether their own political praxes have portents of formalization and ossification.
An Analysis of Bare Soil Occurrence in Arable Croplands for Remote Sensing Topsoil Applications
Authors: Mzid Nada , Pignatti Stefano , Huang Wenjiang , Casa Raffaele
Published: January 2021

A better comprehension of soil properties and processes permits a progress in agricultural management effectiveness, together with a diminution of environmental damage and more beneficial use of resources. This research investigated the usage of multispectral (Sentinel-2 MSI) satellite data at the farm/regional level, for the identification of agronomic bare soil presence, utilizing bands of the spectral range from visible to shortwave infrared. The research purpose was to assess the frequency of cloud-free bare soil time-series images available during the year in typical agricultural areas, needed for the development of digital soil mapping (DSM) approaches for agricultural applications, using hyperspectral satellite missions such as current PRISMA and the planned EnMAP or CHIME. The research exploited the Google Earth Engine platform, by processing all available cloud-free Sentinel-2 images throughout a time span of four years. Two main results were obtained: (i) bare soil frequency, indicating where and when a pixel (or an agricultural field) was detected as bare surface in three representative agricultural areas of Italy, and (ii) a temporal sensitivity analysis, providing the acquisition frequency of useful bare soil images applicable for the retrieval of soil variables of interest. It was shown that, in order to provide for an effective agricultural soil monitoring capability, a revisit frequency in the range of five to seven days is required, which is less than the planned specifications e.g., of PRISMA or CHIME hyperspectral missions, but could be addressed by combining data from the two sensors.
Infrasonic Earthquake Detectability Investigated in Southern Part of Japan, 2019
Authors: Hamama Islam , Yamamoto Masa-yuki
Published: January 2021

The Kochi University of Technology (KUT) Infrasound Sensor Network contains 30 infrasound sensors which are distributed all over Japan especially in Shikoku Island. At all infrasound stations installed with three-axis accelerometers to measure the peak ground acceleration (PGA). Many earthquakes were detected by our system after establishing of the network since 2016. In this study we will focus on all the possibilities for infrasound detection generated from earthquakes using KUT sensor network and International Monitoring system (IMS) stations for the earthquakes which were detected in southern part of Japan during 2019. As for earthquakes with strike-slip mechanisms the P-waves could not be detected by our sensors. In addition, The conversion from seismic to acoustic waves can be happened through the generating of the T-phase from oceanic earthquakes. On 9 May 2019, progressive multi-channel cross correlation (PMCC) method applied infrasound and hydroacoustic waves from two earthquakes happened in west of Kyushu Island as the T-phase was well-recorded at H11N station near Wake Island. Moreover, infrasound propagation modeling is applied to the reconstructed atmosphere profile by Ground to Space Model (AVO-G2S) to confirm the infrasound arrivals, furthermore the 3D ray tracing process and the calculations by using the transmission loss equation with normal modes and parabolic equation methods are investigated. The study confirmed the infrasound generation scenario from the T-phase of oceanic propagation.
Analysis of FDM and DLP 3D-Printing Technologies to Prototype Electromagnetic Devices for RFID Applications
Authors: Colella Riccardo , Chietera Francesco Paolo , Catarinucci Luca
Published: January 2021

In this work, the application in Radiofrequency Identification (RFID) of different additive manufacturing (AM) 3D-printing technologies is discussed. In particular, the well-known Fused Deposition Modeling (FDM) technology is compared with the promising Digital Light Processing (DLP), which is based on the photopolymerization of liquid resins. Based on the research activity of the authors on this topic, a brief introduction to the fundamentals of 3D-printing in electromagnetics as well as to the different applications of both FDM and DLP in realizing Radio Frequency (RF) devices, is firstly given. Then, a comparison of the two technologies is deeply faced. Finally, after evaluated the rugosity of substrates produced with both techniques to verify the potential impact on the design of electromagnetic structures, the two techniques are both exploited for the realization of the dielectric parts of a tunable RFID tag with unconventional shape. It consists of two elements interlinked one each other. The movement between them enables tuning of the resonance frequency as well as the impedance of the antenna. Despite the differences in terms of losses, rugosity, resolution, and dielectric constant, both techniques guaranteed satisfactory values of tag sensitivity, maximum reading range, and tunability. Nevertheless, the careful analysis of the results proposed at the end of the paper suggests how the selection of one technique over the other must be taken considering the specific application constraints.
Quantitative Evaluation of the Effect of Temperature on Magnetic Barkhausen Noise
Authors: Wang Yujue , Meydan Turgut , Melikhov Yevgen
Published: January 2021

The effect of temperature on magnetic Barkhausen noise (MBN) can be divided into two types: the direct effect of temperature itself and the indirect effect of thermally induced stress. The theoretical model is proposed in this paper to describe the effects of temperature on the MBN signal. For the case considering the direct effect of temperature only, the analytical model allows the prediction of the effect of temperature on MBN profile, and, based on the model, a simple linear calibration curve is presented to evaluate the effect of temperature on MBN amplitude quantitatively. While for the case where the indirect effect of thermal stress is taken into account in addition to the direct effect, the proposed theoretical model allows the deduction of parabolic function for quantitative evaluation of the combined effect on MBN. Both effects of temperature on MBN, i.e., the direct only and the combined one, have been studied experimentally on 0.5 mm thickness non-oriented (NO) electrical steel and the adhesive structure of NO steel and ceramic glass, respectively. The reciprocal of the measured MBN peak amplitude (1/MBNp) in the first case shows a linear function of temperature, which agrees with the proposed linear calibration curve. While in the experiments considering the combined effects, 1/MBNp shows parabolic dependence on temperature, which is further simplified as a piecewise function for the practical applications.
Validity of the Polar H7 Heart Rate Sensor for Heart Rate Variability Analysis during Exercise in Different Age, Body Composition and Fitness Level Groups
Authors: Hernández-Vicente Adrián , Hernando David , Marín-Puyalto Jorge , Vicente-Rodríguez Germán , Garatachea Nuria , Pueyo Esther , Bailón Raquel
Published: January 2021

This work aims to validate the Polar H7 heart rate (HR) sensor for heart rate variability (HRV) analysis at rest and during various exercise intensities in a cohort of male volunteers with different age, body composition and fitness level. Cluster analysis was carried out to evaluate how these phenotypic characteristics influenced HR and HRV measurements. For this purpose, sixty-seven volunteers performed a test consisting of the following consecutive segments: sitting rest, three submaximal exercise intensities in cycle-ergometer and sitting recovery. The agreement between HRV indices derived from Polar H7 and a simultaneous electrocardiogram (ECG) was assessed using concordance correlation coefficient (CCC). The percentage of subjects not reaching excellent agreement (CCC > 0.90) was higher for high-frequency power (PHF) than for low-frequency power (PLF) of HRV and increased with exercise intensity. A cluster of unfit and not young volunteers with high trunk fat percentage showed the highest error in HRV indices. This study indicates that Polar H7 and ECG were interchangeable at rest. During exercise, HR and PLF showed excellent agreement between devices. However, during the highest exercise intensity, CCC for PHF was lower than 0.90 in as many as 60% of the volunteers. During recovery, HR but not HRV measurements were accurate. As a conclusion, phenotypic differences between subjects can represent one of the causes for disagreement between HR sensors and ECG devices, which should be considered specifically when using Polar H7 and, generally, in the validation of any HR sensor for HRV analysis.
A Review of Techniques for RSS-Based Radiometric Partial Discharge Localization
Authors: Upton David W. , Mistry Keyur K. , Mather Peter J. , Zaharis Zaharias D. , Atkinson Robert C. , Tachtatzis Christos , Lazaridis Pavlos I.
Published: January 2021

The lifespan assessment and maintenance planning of high-voltage power systems requires condition monitoring of all the operational equipment in a specific area. Electrical insulation of electrical apparatuses is prone to failure due to high electrical stresses, and thus it is a critical aspect that needs to be monitored. The ageing process of the electrical insulation in high voltage equipment may accelerate due to the occurrence of partial discharge (PD) that may in turn lead to catastrophic failures if the related defects are left untreated at an initial stage. Therefore, there is a requirement to monitor the PD levels so that an unexpected breakdown of high-voltage equipment is avoided. There are several ways of detecting PD, such as acoustic detection, optical detection, chemical detection, and radiometric detection. This paper focuses on reviewing techniques based on radiometric detection of PD, and more specifically, using received signal strength (RSS) for the localization of faults. This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN).
Auditory Cue Based on the Golden Ratio Can Improve Gait Patterns in People with Parkinson’s Disease
Authors: Belluscio Valeria , Iosa Marco , Vannozzi Giuseppe , Paravati Stefano , Peppe Antonella
Published: January 2021

The harmonic structure of walking relies on an irrational number called the golden ratio (ϕ): in healthy subjects, it coincides with the stride-to-stance ratio, and it is associated with a smooth gait modality. This smoothness is lost in people with Parkinson’s disease (PD), due to deficiencies in the execution of movements. However, external auditory cues seem to facilitate movement, by enabling the timing of muscle activation, and helping in initiating and modulating motor output. Based on a harmonic fractal structure of gait, can the administration of an auditory cue based on individual’s ϕ-rhythm improve, in acute, gait patterns in people with PD? A total of 20 participants (16 males, age 70.9 ± 8.4 years, Hoehn and Yahr stage-II) were assessed through stereophotogrammetry: gait spatio-temporal parameters, and stride-to-stance ratio were computed before, during, and after the ϕ-rhythm administration. Results show improvements in terms of stride length (p = 0.018), walking speed (p = 0.014), and toe clearance (p = 0.013) when comparing gait patterns before and after the stimulus. Furthermore, the stride-to-stance ratio seems to correlate with almost all spatio-temporal parameters, but it shows the main changes in the before–during rhythm comparison. In conclusion, ϕ-rhythm seems an effective cue able to compensate for defective internal rhythm of the basal ganglia in PD.
Correction: des Tombe, B., et al. Estimation of Temperature and Associated Uncertainty from Fiber-Optic Raman-Spectrum Distributed Temperature Sensing. Sensors 2020, 20, 2235
Authors: des Tombe Bas , Schilperoort Bart , Bakker Mark
Published: January 2021

The authors wish to make the following two corrections to this paper [...]
Paddle Stroke Analysis for Kayakers Using Wearable Technologies
Authors: Liu Long , Wang Hui-Hui , Qiu Sen , Zhang Yun-Cui , Hao Zheng-Dong
Published: January 2021

Proper stroke posture and rhythm are crucial for kayakers to achieve perfect performance and avoid the occurrence of sport injuries. The traditional video-based analysis method has numerous limitations (e.g., site and occlusion). In this study, we propose a systematic approach for evaluating the training performance of kayakers based on the multiple sensors fusion technology. Kayakers’ motion information is collected by miniature inertial sensor nodes attached on the body. The extend Kalman filter (EKF) method is used for data fusion and updating human posture. After sensor calibration, the kayakers’ actions are reconstructed by rigid-body model. The quantitative kinematic analysis is carried out based on joint angles. Machine learning algorithms are used for differentiating the stroke cycle into different phases, including entry, pull, exit and recovery. The experiment shows that our method can provide comprehensive motion evaluation information under real on-water scenario, and the phase identification of kayaker’s motions is up to 98% validated by videography method. The proposed approach can provide quantitative information for coaches and athletes, which can be used to improve the training effects.
Damage Identification Method of Box Girder Bridges Based on Distributed Long-Gauge Strain Influence Line under Moving Load
Authors: Yang Jing , Hou Peng , Yang Caiqian , Yang Ning , Li Kefeng
Published: January 2021

A new method was proposed for the damage identification of box girder bridges under moving load, wherein the difference of strain influence line (DSIL) was taken as an index to represent the long-gauge strain difference before and after damage. The damage identification theory based on long-gauge strain influence lines was derived for box girder bridges with shear lag effect under consideration, and a regularized index DSIL was proposed for the quantitative identifications of damage location and extent. A series of experiments were carried out to study the influences of speed, vehicle type, and vehicle weight on the damage identification, and the experimental data were obtained by long-gauge fiber Bragg grating strain sensors. Moreover, numerical simulations were performed to confirm the method. The experimental and numerical results show that the method can locate the damage accurately, and quantitatively identify the damage extent under different working conditions. The experimental damage extent is generally slightly higher than the theoretical, with an average identification error smaller than 5%. Additionally, the relative error of damage extent is smaller than 3% under different working conditions. Thus, the effectiveness of this method was verified.
An Analysis of the Water-to-Ice Phase Transition Using Acoustic Plate Waves
Authors: Anisimkin Vladimir , Kolesov Vladimir , Kuznetsova Anastasia , Shamsutdinova Elizaveta , Kuznetsova Iren
Published: January 2021

It is shown that, in spite of the wave radiation into the adjacent liquid, a large group of Lamb waves are able to propagate along piezoelectric plates (quartz, LiNbO3, LiTaO3) coated with a liquid layer (distilled water H2O). When the layer freezes, most of the group’s waves increase their losses, essentially forming an acoustic response towards water-to-ice transformation. Partial contributions to the responses originating from wave propagation, electro-mechanical transduction, and wave scattering were estimated and compared with the coupling constants, and the vertical displacements of the waves were calculated numerically at the water–plate and ice–plate interfaces. The maximum values of the responses (20–30 dB at 10–100 MHz) are attributed to the total water-to-ice transformation. Time variations in the responses at intermediate temperatures were interpreted in terms of a two-phase system containing both water and ice simultaneously. The results of the paper may turn out to be useful for some applications where the control of ice formation is an important problem (aircraft wings, ship bodies, car roads, etc.).
A Panel Data Estimation of Domestic Water Demand with IRT Tariff Structure: The Case of the City of Valencia (Spain)
Authors: Maldonado-Devis Mónica , Almenar-Llongo Vicent
Published: January 2021

In urban water provisioning, prices can improve efficiency, contributing to the achievement of the environmental objective. However, household responses to price changes differ widely based on the household characteristics. Analyses performed at the aggregate level ignore the implications of water demand incentives at the individual household level. A large data sample at the household level enables estimation of econometric models of water demand, capturing the heterogeneity in domestic consumption. This study estimated the domestic water demand in the city of Valencia and its elasticity, along with the demands of its different districts and neighbourhoods (intra-urban scale analysis). Water price structure in Valencia is completely different from that of other Spanish cities: it is a price structure of increasing volume (increasing rate tariffs, IRT). For this estimation, from a microdata panel at the household level, the demand function with average prices for the period 2008–2011 was estimated using panel data techniques including a fixed effect for each neighbourhood. The domestic water demand elasticity at the average price in Valencia was estimated at −0.88 (which is higher than that estimated for other Spanish cities). This value indicates an inelastic demand at the average price of the previous period, which can cause consumers to overestimate the price and react more strongly to changes.
A Clustering Framework to Reveal the Structural Effect Mechanisms of Natural and Social Factors on PM2.5 Concentrations in China
Authors: Yang Wentao , He Zhanjun , Huang Huikun , Huang Jincai
Published: January 2021

Understanding the mechanisms of various factors that affect PM2.5 can assist in the development of scientific measures to improve air quality. Nevertheless, existing research has concentrated on exploring local effect mechanisms, while structural effect mechanisms at regional or national scales have scarcely been analysed. Consequently, this study presents an analytical framework for elucidating the structural effect mechanisms of associated factors on PM2.5. Geographically and temporally weighted regression was used to explore the local effect mechanisms. This was followed by spatial clustering analysis to reveal these mechanisms by detecting their aggregation patterns. In the analysis, datasets for annual mean PM2.5 and socio-economic factors in China from 1999 to 2016 were employed. Urban population, gross industrial output, and sulphur dioxide emissions were identified as factors affecting changes in PM2.5 concentrations. These three factors had both negative and positive effects, while the gross industrial output had the largest coefficient variation degree. Three geographically related factors exhibited different impacts on PM2.5 concentrations in most of mainland China. These factors were the urban population roughly west of the Heihe-Tengchong line, gross industrial output primarily in southwestern China, and sulphur dioxide emissions primarily in southern China.
Fault-Source-Based Probabilistic Seismic Hazard and Risk Analysis for Victoria, British Columbia, Canada: A Case of the Leech River Valley Fault and Devil’s Mountain Fault System
Authors: Goda Katsuichiro , Sharipov Andrei
Published: January 2021

This study develops a fault-source-based seismic hazard model for the Leech River Valley Fault (LRVF) and the Devil’s Mountain Fault (DMF) in southern Vancouver Island, British Columbia, Canada. These faults pose significant risks to the provincial capital, Victoria, due to their proximity and potentially large earthquake magnitudes. To evaluate the effects of including these faults in probabilistic seismic hazard analysis and city-wide seismic loss estimation for Victoria, a comprehensive sensitivity analysis is conducted by considering different fault rupture patterns and different earthquake magnitude models, as well as variations in their parameters. The aim is to assess the relative contributions of the LRVF-DMF system to the overall seismic hazard and risk in Victoria at different return periods. The consideration of the LRVF-DMF system as a potential seismic source increases the seismic risk assessment results by 10 to 30%, especially at the high return period levels. The sensitivity analysis results highlight the importance of determining the slip rate for the fault deformation zone and of specifying the earthquake magnitude models (e.g., characteristic versus truncated exponential models). From urban seismic risk management perspectives, these nearby faults should be considered critical earthquake scenarios.
Development of Rice Bran Mixed Porous Clay Bricks for Permeable Pavements: A Sustainable LID Technique for Arid Regions
Authors: Alharbi Fawaz , Almoshaogeh Meshal , Shafiquzzaman Md. , Haider Husnain , Rafiquzzaman Md. , Alragi Ahmed , ElKholy Sherif , Bayoumi ELSaid Abdallah , EL-Ghoul Yassine
Published: January 2021

Permeable pavement provides sustainable solutions for urban stormwater management. In this research, the potential of rice bran mixed porous clay bricks were evaluated for permeable pavements. Physical, mechanical and hydrological properties along with stormwater treatment capabilities of the brick samples were assessed. The study found that ratio of rice bran and clay soil has significant impacts on the properties of the produced bricks. Water adsorption and porosity increased with increasing rice bran ratio. Compressive strength of brick samples decreased from 29.6 MPa to 6.9 MPa when the ratio of rice bran was increased from 0% to 20%. The permeability coefficient increased from 4 × 10−4 to 1.39 × 10−2 mm/s with the increase in rice bran from 0% to 30%. The preamble clay bricks were efficient to remove turbidity, total suspended solids (TSS), five days’ biochemical oxygen demand (BOD5), and heavy metals (Mn, Cu, and Zn) from stormwater to meet the World Health Organization (WHO) standard for wastewater reuse application. The bricks with ≤10% of rice bran achieved the American Society for Testing and Materials (ASTM) standard of the desire compressive strength and permeability coefficient for pedestrian and light traffic pavements. The porous bricks prepared in this study can be used to construct permeable pavements and would be a sustainable low impact developments technique for stormwater management in urban areas.
Left-Invariant Riemann Solitons of Three-Dimensional Lorentzian Lie Groups
Authors: Wang Yong
Published: January 2021

Riemann solitons are generalized fixed points of the Riemann flow. In this note, we study left-invariant Riemann solitons on three-dimensional Lorentzian Lie groups. We completely classify left-invariant Riemann solitons on three-dimensional Lorentzian Lie groups.
Multiscale Discrete Element Modeling
Authors: Zhuravlev Andrew A. , Abgaryan Karine K. , Reviznikov Dmitry L.
Published: January 2021

A multiscale approach to discrete element modeling is presented. A distinctive feature of the method is that each macroscopic discrete element has an associated atomic sample representing the material’s atomic structure. The dynamics of the elements on macro and micro levels are described by systems of ordinary differential equations, which are solved in a self-consistent manner. A full cycle of multiscale simulations is applied to polycrystalline silicon. Macroscale elastic properties of silicon were obtained only using data extracted from the quantum mechanical properties. The results of computational experiments correspond well to the reference data.
Bootstrapped Motion of an Agent on an Adaptive Resource Landscape
Authors: Phan Trung V. , Wang Gao , Liu Liyu , Austin Robert H.
Published: January 2021

We theoretically show that isolated agents that locally and symmetrically consume resources and sense positive resource gradients can generate constant motion via bootstrapped resource gradients in the absence of any externally imposed gradients, and we show a realization of this motion using robots. This self-generated agent motion can be coupled with neighboring agents to act as a spontaneously broken symmetry seed for emergent collective dynamics. We also show that in a sufficiently weak externally imposed gradient, it is possible for an agent to move against an external resource gradient due to the local resource depression on the landscape created by an agent. This counter-intuitive boot-strapped motion against an external gradient is demonstrated with a simple robot system on an light-emitting diode (LED) light-board.