bluuebunny/crossref_metadata_2025 huggingface dataset:
Less Expectation, Less Pain: Low Wealth Alleviates Sense of Unfairness
Authors: Pei Guanxiong , Jin Jia , Li Taihao , Fang Cheng
Published: April 2021

Objective wealth plays an important role in social interaction and economic decision making. Previous studies indicate that objective wealth of others may influence the way we participate in resources allocation. However, the effect of objective wealth on responses to fairness-related resource distribution is far from clear, as are the underlying neural processes. To address this issue, we dynamically manipulated proposers’ objective wealth and analyzed participants’ behavior as responders in a modified Ultimatum Game, during which event-related potentials were recorded. Behavioral results showed that participants were prone to reject unfair proposals although that rejection would reduce their own benefit. Importantly, participants were more likely to accept unfair offers from proposers with low objective wealth than from proposers with high objective wealth, with a drastic increase in acceptance rates of unfair offers from 32.79 to 50.59%. Further electrophysiological results showed that there was significantly enhanced feedback-related negativity amplitude toward proposers with high (relative to low) objective wealth for unfair offers. Furthermore, the late frontal negativity amplitude was larger for all the conditions which are not high-fair, which might be the only option that did not elicit any ambiguity. These findings suggest a strong role of proposers’ objective wealth in modulating responders’ behavioral and neural responses to fairness.
Music Listening in Classical Concerts: Theory, Literature Review, and Research Program
Authors: Wald-Fuhrmann Melanie , Egermann Hauke , Czepiel Anna , O’Neill Katherine , Weining Christian , Meier Deborah , Tschacher Wolfgang , Uhde Folkert , Toelle Jutta , Tröndle Martin
Published: April 2021

Performing and listening to music occurs in specific situations, requiring specific media. Empirical research on music listening and appreciation, however, tends to overlook the effects these situations and media may have on the listening experience. This article uses the sociological concept of the frame to develop a theory of an aesthetic experience with music as the result of encountering sound/music in the context of a specific situation. By presenting a transdisciplinary sub-field of empirical (concert) studies, we unfold this theory for one such frame: the classical concert. After sketching out the underlying theoretical framework, a selective literature review is conducted to look for evidence on the general plausibility of the single elements of this emerging theory and to identify desiderata. We refer to common criticisms of the standard classical concert, and how new concert formats try to overcome alleged shortcomings and detrimental effects. Finally, an empirical research program is proposed, in which frames and frame components are experimentally manipulated and compared to establish their respective affordances and effects on the musical experience. Such a research program will provide empirical evidence to tackle a question that is still open to debate, i.e., whether the diversified world of modern-day music listening formats also holds a place for the classical concert – and if so, for what kind of classical concert.
A Longitudinal Examination of the Association Between Meaning in Life, Resilience, and Mental Well-Being in Times of Coronavirus Pandemic
Authors: Arslan Gökmen , Yıldırım Murat
Published: April 2021

The coronavirus disease possesses an important threat to people's health and well-being. The purpose of the present study is to longitudinally examine whether meaning in life before the pandemic increases resilience and mental well-being during the coronavirus pandemic. The sample of the study comprised 172 young adults (72% women) in a public university in an urban city of Turkey. Participants ranged in age between 18 and 40 years (M = 20.87, SD = 3.92). Mediation analyses were performed to examine the impacts of meaning in life on the outcomes across the two waves of data. Findings from these analyses revealed that meaning in life before the pandemic had a significant predictive effect on resilience and mental well-being of young adults during the coronavirus disease. Resilience also mediated the impacts of meaning in life on mental well-being indicators at the second time. These results suggest the importance of meaning-based preventions and interventions designed to build up resilience experiences for improving psychological health and well-being during a public health crisis.
Effect of Complexity on Speech Sound Development: Evidence From Meta-Analysis Review of Treatment-Based Studies
Authors: Maggu Akshay R. , Kager René , To Carol K. S. , Kwan Judy S. K. , Wong Patrick C. M.
Published: April 2021

In the current study, we aimed at understanding the effect of exposure to complex input on speech sound development, by conducting a systematic meta-analysis review of the existing treatment-based studies employing complex input in children with speech sound disorders. In the meta-analysis review, using a list of inclusion criteria, we narrowed 280 studies down to 12 studies. Data from these studies were extracted to calculate effect sizes that were plotted as forest plots to determine the efficacy of complexity-based treatment approaches. The outcome variables of interest were improvement on the treated and generalization to the untreated sounds. Meta-analysis revealed that the exposure to complex input not only promoted improvement in production of complex speech sounds (d = 1.08, CI = 0.98–1.19) but also facilitated the production of untreated simple speech sounds (d = 2.69, CI = 1.98–3.54). Overall, the current findings revealed that the exposure to complex input promotes acquisition of both complex and simple speech sounds. The current findings are in line with the models of language learnability. The current findings have implications in the treatment of speech sound disorders.
Unobtrusive Sensing Technology for Quantifying Stress and Well-Being Using Pulse, Speech, Body Motion, and Electrodermal Data in a Workplace Setting: Study Concept and Design
Authors: Izumi Keisuke , Minato Kazumichi , Shiga Kiko , Sugio Tatsuki , Hanashiro Sayaka , Cortright Kelley , Kudo Shun , Fujita Takanori , Sado Mitsuhiro , Maeno Takashi , Takebayashi Toru , Mimura Masaru , Kishimoto Taishiro
Published: April 2021

Introduction: Mental disorders are a leading cause of disability worldwide. Depression has a significant impact in the field of occupational health because it is particularly prevalent during working age. On the other hand, there are a growing number of studies on the relationship between “well-being” and employee productivity. To promote healthy and productive workplaces, this study aims to develop a technique to quantify stress and well-being in a way that does not disturb the workplace.

Methods and analysis: This is a single-arm prospective observational study. The target population is adult (>20 years old) workers at companies that often engage in desk work; specifically, a person who sits in front of a computer for at least half their work hours. The following data will be collected: (a) participants' background characteristics; (b) participants' biological data during the 4-week observation period using sensing devices such as a camera built into the computer (pulse wave data extracted from the facial video images), a microphone built into their work computer (voice data), and a wristband-type wearable device (electrodermal activity data, body motion data, and body temperature); (c) stress, well-being, and depression rating scale assessment data. The analysis workflow is as follows: (1) primary analysis, comprised of using software to digitalize participants' vital information; (2) secondary analysis, comprised of examining the relationship between the quantified vital data from (1), stress, well-being, and depression; (3) tertiary analysis, comprised of generating machine learning algorithms to estimate stress, well-being, and degree of depression in relation to each set of vital data as well as multimodal vital data.

Discussion: This study will evaluate digital phenotype regarding stress and well-being of white-collar workers over a 4-week period using persistently obtainable biomarkers such as heart rate, acoustic characteristics, body motion, and electrodermal activity. Eventually, this study will lead to the development of a machine learning algorithm to determine people's optimal levels of stress and well-being.

Ethics and dissemination: Collected data and study results will be disseminated widely through conference presentations, journal publications, and/or mass media. The summarized results of our overall analysis will be supplied to participants.

Registration: UMIN000036814
Animal Design Through Functional Dietary Diversity for Future Productive Landscapes
Authors: Beck Matthew R. , Gregorini Pablo
Published: April 2021

Pastoral livestock production systems are facing considerable societal pressure to reduce environmental impact, enhance animal welfare, and promote product integrity, while maintaining or increasing system profitability. Design theory is the conscious tailoring of a system for a specific or set of purposes. Then, animals—as biological systems nested in grazing environments—can be designed in order to achieve multi-faceted goals. We argue that phytochemical rich diets through dietary taxonomical diversity can be used as a design tool for both current animal product integrity and to develop future multipurpose animals. Through conscious choice, animals offered a diverse array of plants tailor a diet, which better meets their individual requirements for nutrients, pharmaceuticals, and prophylactics. Phytochemical rich diets with diverse arrangements of plant secondary compounds also reduce environmental impacts of grazing animals by manipulating the use of C and N, thereby reducing methane production and excretion of N. Subsequently functional dietary diversity (FDD), as opposed to dietary monotony, offers better nourishment, health benefits and hedonic value (positive reward increasing “liking” of feed), as well as the opportunity for individualism; and thereby eudaimonic well-being. Moreover, phytochemical rich diets with diverse arrangements of plant secondary compounds may translate in animal products with similar richness, enhancing consumer human health and well-being. Functional dietary diversity also allows us to design future animals. Dietary exposure begins in utero, continues through mothers' milk, and carries on in early-life experiences, influencing dietary preferences later in life. More specifically, in utero exposure to specific flavors cause epigenetic changes that alter morphological and physiological mechanisms that influence future “wanting,” “liking” and learning of particular foods and foodscapes. In this context, we argue that in utero and early life exposure to designed flavors of future multifunctional foodscapes allow us to graze future ruminants with enhanced multiple ecosystem services. Collectively, the strategic use of FDD allows us to “create” animals and their products for immediate and future food, health, and wealth. Finally, implementing design theory provides a link between our thoughtscape (i.e., the use of FDD as design) to future landscapes, which provides a beneficial foodscape to the animals, an subsequently to us.
Acid Rain Tolerance in Soybeans: Evaluation of Genetic Variability and Identification of Novel Germplasms Using Multiple Criteria
Authors: Zhang Guozheng , Pu Meijuan , Tian Ruiping , He Xiaohong , Yu Deyue
Published: April 2021

Acid rain (AR) adversely affects soybean growth and seed yield. However, genetic variation of soybean response to AR stress has not been well evaluated. Here, 441 cultivated soybean genotypes were subjected to simulated rainfall with either pH 4.2 (AR) or pH 5.6 (control) from the three-leaf stage to maturity in 2009 and 2010. After maturity, 14 traits potentially related to AR tolerance were determined. Analyses of variance showed that genetic variation in AR tolerance was statistically highly significant for all surveyed traits. Analysis of AR tolerance coefficients (ARTC) distinguished the 14 traits into four types. The Types I, II, and III variables were affected by AR stress to various degrees and displayed variations in AR sensitivity among genotypes with different sizes. Nevertheless, the Type IV variables were not influenced and showed little genetic variation. Among the three evaluation criteria for measuring AR tolerance of soybean genotypes, the ARTC and the ARTI (AR tolerance index) of seed yield were moderately associated, whereas the ARTC of seed yield and the average membership grade of ARTCs of the seven selected traits for comprehensive evaluating were strongly correlated. Applying the comprehensive evaluation method, 22 highly AR-tolerant and 23 highly AR-susceptible germplasms were identified. Seed yield changes after AR exposure of these screened genotypes were primarily attributed to changes in total pod number per plant, which consequently caused corresponding alterations in fruited pod number per plant and seed number per plant, and were secondarily due to changes in hundred seed weight. These novel germplasms will serve as materials for subsequent investigations aiming to explore the genetic mechanisms underlying AR tolerance and to develop AR-tolerant varieties in soybean.
The Influence of Environmental Conditions on Intake Behavior and Activity by Feedlot Steers Fed Corn or Barley-Based Diets
Authors: DelCurto-Wyffels Hannah M. , Dafoe Julia M. , Parsons Cory T. , Boss Darrin L. , DelCurto Timothy , Wyffels Samuel A. , Van Emon Megan L. , Bowman Janice G. P.
Published: April 2021

This study evaluated the influence of diet and environmental conditions on intake behavior and activity of feedlot steers. Feedlot rations used were comprised of a main concentrate: (1) corn or (2) barley. A GrowSafe system measured individual animal intake and behavior and HOBO accelerometers measured steer standing time. An Onset weather station collected on site weather data. Steer daily intake displayed a diet by temperature class interaction (p ≤ 0.05). Relative temperature change had no effect on variation in intake (p = 0.60); however, diet influenced variation of intake (p < 0.01), where corn-fed steers had a greater coefficient of variation (CV) than barley-fed steers (21.89 ± 1.46 vs. 18.72 ± 1.46%). Time spent eating (min d−1) and eating rate (g min−1) both displayed a diet by temperature class interaction (p ≤ 0.05). Diet did not affect steer lying activity (p ≥ 0.12), however, time spent lying (min d−1) and frequency of lying bouts (bouts d−1) increased on relatively cold days while the duration of lying bouts (min bout−1; p < 0.01) decreased. Short-term environmental temperature changes interacted with diet influencing feedlot beef cattle intake behavior; however, they did not interact with basal diet in respect to steer activity.
A Peculiar Distribution of the Emerging Nematode Angiostrongylus cantonensis in the Canary Islands (Spain): Recent Introduction or Isolation Effect?
Authors: Martín-Carrillo Natalia , Feliu Carlos , Abreu-Acosta Néstor , Izquierdo-Rodriguez Elena , Dorta-Guerra Roberto , Miquel Jordi , Abreu-Yanes Estefanía , Martin-Alonso Aarón , García-Livia Katherine , Quispe-Ricalde María Antonieta , Serra-Cobo Jordi , Valladares Basilio , Foronda Pilar
Published: April 2021

Angiostrongylus cantonensis is an emerging zoonotic nematode recognized as the leading cause of eosinophilic meningitis in the word. After its discovery in China, it was recorded in 30 countries worldwide. Recently, it has expanded to new areas such as South America and it has been recently found in the Atlantic island of Tenerife (Canary Islands). In order to characterize the distribution of A. cantonensis in the Canary Islands, the lungs of 1462 rodents were sampled in eight islands of the archipelago over 13 years and were then analyzed for A. cantonensis. Remarkably, the parasite was detected only in Tenerife, in Rattus rattus (19.7%) and Rattus norvegicus (7.14%). They were concretely in the northern part of the island, which had a warmer and more humid climate than the south and main cities. The absence of this nematode in other islands with similar environmental conditions could be explained by an isolation effect or by a recent introduction of the parasite in the islands. Besides, the presence in Tenerife of the most invasive lineage of A. cantonensis reinforced the hypothesis of a recent introduction on this island. This study highlights the need to implement control measures to prevent the expansion to other areas in order to avoid the transmission to humans and other animals.
Presence of Helicobacter pylori and H. suis DNA in Free-Range Wild Boars
Authors: Cortez Nunes Francisco , Letra Mateus Teresa , Teixeira Sílvia , Barradas Patrícia , de Witte Chloë , Haesebrouck Freddy , Amorim Irina , Gärtner Fátima
Published: April 2021

Helicobacter pylori (H. pylori) is a Gram-negative bacterium that infects half of the human population worldwide, causing gastric disorders, such as chronic gastritis, gastric or duodenal ulcers, and gastric malignancies. Helicobacter suis (H. suis) is mainly associated with pigs, but can also colonize the stomach of humans, resulting in gastric pathologies. In pigs, H. suis can induce gastritis and seems to play a role in gastric ulcer disease, seriously affecting animal production and welfare. Since close interactions between domestic animals, wildlife, and humans can increase bacterial transmission risk between species, samples of gastric tissue of 14 free range wild boars (Sus scrofa) were evaluated for the presence of H. pylori and H. suis using PCR. Samples from the antral gastric mucosa from two animals were PCR-positive for H. pylori and another one for H. suis. These findings indicate that these microorganisms were able to colonize the stomach of wild boars and raise awareness for their putative intervention in Helicobacter spp. transmission cycle.
Droplet Digital PCR (ddPCR) Analysis for the Detection and Quantification of Cow DNA in Buffalo Mozzarella Cheese
Authors: Cutarelli Anna , Fulgione Andrea , Fraulo Pasquale , Serpe Francesco Paolo , Gallo Pasquale , Biondi Loredana , Corrado Federica , Citro Angelo , Capuano Federico
Published: April 2021

Buffalo mozzarella cheese is one of the most appreciated traditional Italian products and it is certified as a Protected Designation of Origin (PDO) product under the European Commission Regulation No. 1151/2012. It is obtained exclusively from buffalo milk. If made from cow milk, or a mixture of buffalo and cow milk, buffalo mozzarella cheese does not qualify as a PDO product. In order to maximize their profits, some producers market buffalo mozzarella that also contains cow milk as a PDO product, thus defrauding consumers. New methods for revealing this fraud are therefore needed. One such method is the droplet digital Polymerase Chain Reaction (ddPCR). Thanks to its high precision and sensitivity, the ddPCR could prove an efficacious means for detecting the presence of cow milk in buffalo mozzarella cheese that is marketed as a PDO product. ddPCR has proved able to detect the DNA of cow and/or buffalo milk in 33 buffalo mozzarella cheeses labelled as PDO products, and experimental evidence could support its application in routine analyses.
Hydrogen Sulfide Attenuates Aortic Remodeling in Aortic Dissection Associating with Moderated Inflammation and Oxidative Stress through a NO-Dependent Pathway
Authors: Lu Hsin-Ying , Hsu Hung-Lung , Li Chih-Han , Li Shao-Jung , Lin Shing-Jong , Shih Chun-Ming , Shih Chun-Che
Published: April 2021

Aortic dissection (AD) is a highly lethal vascular disease characterized by separation of the constituent layers of the aortic wall. An increasing body of research indicates that inflammatory response and oxidative stress are implicated in vascular remodeling, which plays a key role in the development of AD. Hydrogen sulfide (H2S) has been found to protect against various types of cardiovascular disease, including myocardial infarction, arthrosclerosis, and hypertension. However, research on the effect of H2S on AD is insufficient. This study therefore elucidated the effect of H2S on the development and progression of AD, and the potential mechanism involved. Using β-aminopropionitrile fumarate (BAPN) and angiotensin II (Ang-II)-induced AD animal models, the administration of NaHS (as H2S donor, 56 μmol/kg body weight/day) was found to retard the development of AD. Murine VSMCs (Movas) exposed to interleukin-6 (IL-6) (20 ng/mL) to induce phenotypic switch. Histological analyses indicated that H2S administration inhibited the accumulation of inflammatory cells in the aortic wall and the related expression of inflammatory genes. Additionally, H2S treatment elevated aortic superoxide dismutase (SOD) activity and ablated malonaldehyde (MDA) and nitric oxide (NO) levels. In mechanistic terms, H2S attenuated IL-6 induced a pathological VSMC phenotypical switch through NO modulation by N(G)-monomethyl-L-arginine acetate salt (L-NMMA) stimulation. H2S inhibits AD formation by decreasing the inflammatory response, and oxidative stress, and by positively participating in vascular remodeling. These findings suggest a role for H2S as a novel and promising therapeutic strategy to prevent AD development.
The Influence of Pipe Bending Curvature on H2-O2 Gaseous Detonation Wave Front
Authors: Zhao Hui , Li Huiyuan , Zhao Haitao , Li Leisheng , Li Jian
Published: April 2021

The influence of different bend curvatures on the detonation wave propagation was analyzed by an advanced numerical simulation system. The mechanism of propagation properties is revealed by cellular structure, internal and external boundary pressure distribution, propagation process of detonation wave and chemical reaction. The cellular structure and detonation wave front of bend with different curvature are very different. The simulation results show that the detonation wave with regular cell structure propagating through the curved parts induces detonation cell size increased by diffraction near the inner wall while detonation reflected on the bottom surface resulting in decrease of cell size. Detonation wave was affected by the rarefaction wave and compression wave in the bent pipe. The pressure distribution of the bend shows that the peak pressure in the 450 curvature is the largest, which should be paid more attention in industrial design. The chemical reaction could indicate the propagation characteristics of detonation wave, and different propagation characteristics have different profiles of chemical components.
Understanding Natural Disaster Scenes from Mobile Images Using Deep Learning
Authors: Tang Shimin , Chen Zhiqiang
Published: April 2021

With the ubiquitous use of mobile imaging devices, the collection of perishable disaster-scene data has become unprecedentedly easy. However, computing methods are unable to understand these images with significant complexity and uncertainties. In this paper, the authors investigate the problem of disaster-scene understanding through a deep-learning approach. Two attributes of images are concerned, including hazard types and damage levels. Three deep-learning models are trained, and their performance is assessed. Specifically, the best model for hazard-type prediction has an overall accuracy (OA) of 90.1%, and the best damage-level classification model has an explainable OA of 62.6%, upon which both models adopt the Faster R-CNN architecture with a ResNet50 network as a feature extractor. It is concluded that hazard types are more identifiable than damage levels in disaster-scene images. Insights are revealed, including that damage-level recognition suffers more from inter- and intra-class variations, and the treatment of hazard-agnostic damage leveling further contributes to the underlying uncertainties.
Study on the Evaluation Methods of the Vertical Ride Comfort of Railway Vehicle—Mean Comfort Method and Sperling’s Method
Authors: Dumitriu Mădălina , Stănică Dragoș Ionuț
Published: April 2021

The paper herein analyzes the ride comfort at the vertical vibrations of the railway vehicle, evaluated by two methods—mean comfort method and Sperling’s method. The two methods have in common that the estimation of the comfort sensation is conducted with the comfort indices, namely ride comfort index NMVZ and ride comfort index Wz. The values of these indices are derived from numerical simulations. The advantage of using the results of the numerical simulations versus using experimental results, on which most previous research is based, resides in the fact that the ride comfort indices can be examined while taking into account the influence of velocity and certain parameters altering the behavior of vertical vibrations of the carbody, i.e., carbody flexibility and the suspension damping. The numerical simulation applications have been developed based on a theoretical model of the vehicle that considers important factors affecting the behavior of vertical vibrations of the carbody, by means of a ‘flexible carbody’ type model and an original model of the secondary suspension. The results presented mainly show that the two assessment methods lead to significantly different outcomes, in terms of ride comfort, under identical running conditions of the vehicle.
Coupled Mode Sound Propagation in Inhomogeneous Stratified Waveguides
Authors: Liu Juan , Li Qi
Published: April 2021

An efficient coupled mode method for modeling sound propagation in horizontally stratified inhomogeneous waveguides, in which the seabed is modeled as a (layered) acoustic medium, is presented. The method is based on Fawcett’s coupled mode method and the multimodal admittance method. The acoustic field is expanded onto the unusual local eigenfunctions composed by normal modes in the corresponding one-layer homogeneous waveguides with constant depth equal to the local total depth of the multilayered waveguide. A set of energy-conserving first-order differential equations governing the modal amplitudes of acoustic fields is derived. The admittance method is employed to solve the differential equations in a numerically stable manna. The coupled mode method considers the backscattering effect of inhomogeneities and full coupling between local modes, and offers improvement from the viewpoint of efficiency and computational cost. The acoustic fields predicted by the method agree well with those computed by the commercial finite element software COMSOL Multiphysics. The method can be extended to further establish fast and accurate 3D sound propagation models in complex shallow water environments.
Optically-Injected-Semiconductor-Laser-Based Tunable Dual-Frequency Optoelectronic Oscillator under Subharmonic Microwave Modulation
Authors: Zhao Jiayi , Gu Yiying , Li Jian , Li Xiaozhou , Zhao Mingshan , Han Xiuyou , Hu Jingjing
Published: April 2021

To obtain low-phase-noise microwave signals with a widely tunable frequency range, an optoelectronic oscillator (OEO) was constructed on the basis of an optically injected semiconductor laser (OISL) for the generation of high-quality microwave signals. Our OEO relied on the effect of wavelength-selective amplification and the period-one (P1) oscillation under optical injection. The signal’s frequency stability, side-mode-suppression ratio (SMSR) and linewidth were optimized by the subharmonic microwave modulation technique in the OEO loop. The experimental results showed that the frequency of the signal obtained by the proposed OEO could be tuned up to 18 GHz. Using the dual-loop OEO structure, the SMSR was increased to 55 dB. Moreover, the phase noise of the obtained microwave signal was lower than −81 dBc/Hz at 1 kHz frequency offset and −119 dBc/Hz at 10 kHz frequency offset. This was achieved by introducing subharmonic microwave modulation in the OEO loop, respectively. Furthermore, via the utilization of a Fabry–Perot laser diode (FP-LD) in the proposed structure, a dual-loop OEO with different dual-frequency configurations (which could be tuned up to 12 and 18 GHz) was obtained.
Order-Based Identification of Bearing Defects under Variable Speed Condition
Authors: Farhat Mohamed Habib , Chiementin Xavier , Chaari Fakher , Bolaers Fabrice , Haddar Mohamed
Published: April 2021

Condition monitoring of rotating machinery plays an important role in reducing catastrophic failures and production losses in the 4.0 Industry. Vibration analysis has proven to be effective in diagnosing rotating machine failures. However, identifying bearing defects based on vibration analysis remains a difficult task, especially in non-stationary operation conditions. This work aims to automate the process of identifying bearing defects under variable operating speeds. Based on an order analysis technique, three frequency domain features: Spectrum peak Ratio Outer (SPRO), Spectrum peak Ratio Inner (SPRI), and Spectrum peak Ratio Rolling element (SPRR) are updated to perform with non-stationary signals. The updated features are extracted from vibration data of a real ball bearing system. They are retained to build a predictive multi-kernel support vector machine (MSVM) classification model. Therefore, the effectiveness of the proposed features is evaluated based on the performance of the constructed classifier. The updated features deployed have proven their effectiveness in identifying bearing: outer race, inner race, ball, and combined defects under variable speed conditions.
Graphene-Based TiO2 Nanocomposite for Photocatalytic Degradation of Dyes in Aqueous Solution under Solar-Like Radiation
Authors: Kocijan Martina , Ćurković Lidija , Ljubas Davor , Mužina Katarina , Bačić Ivana , Radošević Tina , Podlogar Matejka , Bdikin Igor , Otero-Irurueta Gonzalo , Hortigüela María J. , Gonçalves Gil
Published: April 2021

This study presents a novel method for the development of TiO2/reduced graphene oxide (rGO) nanocomposites for photocatalytic degradation of dyes in an aqueous solution. The synergistic integration of rGO and TiO2, through the formation of Ti–O–C bonds, offers an interesting opportunity to design photocatalyst nanocomposite materials with the maximum absorption shift to the visible region of the spectra, where photodegradation can be activated not only with UV but also with the visible part of natural solar irradiation. TiO2@rGO nanocomposites with different content of rGO have been self-assembled by the hydrothermal method followed by calcination treatment. The morphological and structural analysis of the synthesized photocatalysts was performed by FTIR, XRD, XPS, UV-Vis DRS, SEM/EDX, and Raman spectroscopy. The effectiveness of the synthesized nanocomposites as photocatalysts was examined through the photodegradation of methylene blue (MB) and rhodamine B (RhB) dye under artificial solar-like radiation. The influence of rGO concentration (5 and 15 wt.%) on TiO2 performance for photodegradation of the different dyes was monitored by UV-Vis spectroscopy. The obtained results showed that the synthesized TiO2@rGO nanocomposites significantly increased the decomposition of RhB and MB compared to the synthesized TiO2 photocatalyst. Furthermore, TiO2@rGO nanocomposite with high contents of rGO (15 wt.%) presented an improved performance in photodegradation of MB (98.1%) and RhB (99.8%) after 120 min of exposition to solar-like radiation. These results could be mainly attributed to the decrease of the bandgap of synthesized TiO2@rGO nanocomposites with the increased contents of rGO. Energy gap (Eg) values of nanocomposites are 2.71 eV and 3.03 eV, when pure TiO2 particles have 3.15 eV. These results show the potential of graphene-based TiO2 nanocomposite to be explored as a highly efficient solar light-driven photocatalyst for water purification.
Permeability of Coking Coals and Patterns of Its Change in Leninsky Area, Kuznetsk Coal Basin, Russia
Authors: Shilova Tatiana , Serdyukov Sergey
Published: April 2021

A prediction of the permeability of gas-bearing coking coals in the Leninsky area, Kuznetsk coal basin (Kuzbass), which is promising for the production of coal methane, was performed. The results of laboratory studies of coal permeability and cleat compressibility under hydrostatic stress conditions are presented. As the confining pressure increased by 8 times (from 1 MPa to 8 MPa), the coal permeability perpendicular to the butt cleat direction decreased by 6.7 times (from 60 mD to 9 mD). The coal cleat compressibility was 0.085 MPa−1. On the basis of the results of filtration tests and microstructural analysis of the coking coals, we provide the estimation of the permeability anisotropy along the bedding planes (perpendicular to the face and butt cleat directions). The predicted dependences of gas-bearing coking coal permeability perpendicular to the butt and face cleat directions on depth and on features of coal seam bedding were determined under uniaxial strain conditions. It was found that in the coking coal depth intervals, as the depth increased, their permeability decreased by 61–82%. The obtained results can be used to select facilities and to design industrial works for the extraction of coal methane in the region.
Synthesis and Characterization of ZnBi2O4 Nanoparticles: Photocatalytic Performance for Antibiotic Removal under Different Light Sources
Authors: Baaloudj Oussama , Assadi Achraf Amir , Azizi Mohamed , Kenfoud Hamza , Trari Mohamed , Amrane Abdeltif , Assadi Aymen Amine , Nasrallah Noureddine
Published: April 2021

This work aims to synthesize a photocatalyst with high photocatalytic performances and explore the possibility of using it for antibiotic removal from wastewater. For that, the spinel ZnBi2O4 (ZBO) was produced with the co-precipitation method and its optical, dielectric, and electrochemical characteristics were studied. The phase has been determined and characterized by X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR). For the ZBO morphology, a Scanning Electron Microscopy (SEM) has been used. Then, the optical and dielectric properties of ZBO have been evaluated by calculating refractive index n (λ), extinction coefficient (k), dissipation factor (tan δ), relaxation time (τ), and optical conductivity (σopt) using the spectral distribution of T(λ) and R(λ). An optical gap band of 2.8 eV was determined and confirmed. The electrochemical performance of ZBO was investigated and an n-type semiconductor with a flat band potential of 0.54 V_SCE was found. The photocatalytic efficiency of ZBO was investigated in order to degrade the antibiotic Cefixime (CFX) under different light source irradiations to exploit the optical properties. A high CFX degradation of approximately 89% was obtained under solar light (98 mW cm−2) only after 30 min, while 88% of CFX degradation efficiency has been reached after 2 h under UV irradiation (20 mW cm−2); this is in line with the finding of the optical characterizations. According to the obtained data, solar light assisted nanoparticle ZBO can be used successfully in wastewater to remove pharmaceutical products.
The Influence of Stochastic Resonance Whole-Body Vibration on Women over 50 Years of Age—Preliminary Studies Based on Patients’ Own Experiences
Authors: Hartman-Petrycka Magdalena , Lebiedowska Agata , Stolecka-Warzecha Anna , Szumski Andrzej , Błońska-Fajfrowska Barbara
Published: April 2021

Background: During menopause, a woman’s health often deteriorates, and various methods are sought to prevent this decline. The aim of this study was to determine the influence of SR-WBV training on the health and wellbeing of women over 50 years of age. Methods: SR-WBV training was performed twice a week for six weeks using the SRT Zeptor® Medical-plus noise device. Forty-two women were trained on the D program (7–9 series, lasting 45–60 s each), and 23 women on the O program (9–11 series, lasting 50–60 s each). The frequency ranged from 2 to 8 Hz. Due to health problems, 12% of the women did not complete the study protocols. Results: The remaining women declared an improvement in mental state (51%), physical activity (68%), and general well-being (72%), as well as a reduction in lower limb pain (21%), back pain (14%), and urinary incontinence symptoms (17%). Conclusion: The benefits of SR-WBV training include improvement in general well-being and physical fitness, reduction of lower limb and back pain, and reduction of urinary incontinence symptoms. SR-WBV training can provoke or aggravate back pain and lower limb pain and cause other side effects, so the optimization of training parameters for SR-WBV is required.
Important Trading Point Prediction Using a Hybrid Convolutional Recurrent Neural Network
Authors: Yu Xinpeng , Li Dagang
Published: April 2021

Stock performance prediction plays an important role in determining the appropriate timing of buying or selling a stock in the development of a trading system. However, precise stock price prediction is challenging because of the complexity of the internal structure of the stock price system and the diversity of external factors. Although research on forecasting stock prices has been conducted continuously, there are few examples of the successful use of stock price forecasting models to develop effective trading systems. Inspired by the process of human stock traders looking for trading opportunities, we propose a deep learning framework based on a hybrid convolutional recurrent neural network (HCRNN) to predict the important trading points (IPs) that are more likely to be followed by a significant stock price rise to capture potential high-margin opportunities. In the HCRNN model, the convolutional neural network (CNN) performs convolution on the most recent region to capture local fluctuation features, and the long short-term memory (LSTM) approach learns the long-term temporal dependencies to improve stock performance prediction. Comprehensive experiments on real stock market data prove the effectiveness of our proposed framework. Our proposed method ITPP-HCRNN achieves an annualized return that is 278.46% more than that of the market.
Fine Activated Carbon from Rubber Fruit Shell Prepared by Using ZnCl2 and KOH Activation
Authors: Suhdi  , Wang Sheng-Chang
Published: April 2021

Fine activated carbon (FAC) is prepared from rubber fruit shells (RFS) using two chemical activating agents (ZnCl2 and KOH) and three impregnation ratios (1:3, 1:4, and 1:5). The Brunauer–Emmett–Teller (BET) results show that for a constant impregnation ratio, the ZnCl2 activating agent yields a higher specific surface area than the KOH agent. In particular, for the maximum impregnation ratio of 1:5, the FAC prepared using ZnCl2 has a BET surface area of 456 m2/g, a nitrogen absorption capacity of 150.38 cm3/g, and an average pore size of 3.44 nm. Moreover, the FAC structure consists of 70.1% mesopores and has a carbon content of 80.05 at.%. Overall, the results confirm that RFS, activated using an appropriate quantity of ZnCl2, provides a cheap, abundant, and highly promising precursor material for the preparation of activated carbon with high carbon content and good adsorption properties
Estimation of Structural Deformed Configuration for Bridges Using Multi-Response Measurement Data
Authors: Byun Namju , Lee Jeonghwa , Lee Keesei , Kang Young-Jong
Published: April 2021

The structural deformed shape (SDS) is considered an important factor for evaluating structural conditions owing to its direct relationship with structural stiffness. Recently, an SDS estimation method based on displacement data from a limited number of data points was developed. Although the method showed good performance with a sufficient number of measured data points, application of the SDS estimation method for on-site structures has been quite limited because collecting sufficient displacement data measured from a Global Navigation Satellite System (GNSS) can be quite expensive. Thus, the development of an affordable SDS estimation method with a certain level of accuracy is essential for field application of the SDS estimation technique. This paper proposes an improved SDS estimation method using displacement data combined with additional slope and strain data that can improve the accuracy of the SDS estimation method and reduce the required number of GNSSs. The estimation algorithm was established based on shape superposition with various combined response data (displacement, slope, and strain) and the least-squares method. The proposed SDS estimation method was verified using a finite element method model. In the validation process, three important issues that may affect the estimation accuracy were analyzed: effect of shape function type, sensor placement method, and effectiveness of using multi-response data. Then, the improved SDS estimation method developed in this study was compared with existing SDS estimation methods from the literature. Consequently, it was found that the proposed method can reduce the number of displacement data required to estimate rational SDS by using additional slope and strain data. It is expected that cost-effective structural health monitoring (SHM) can be established using the proposed estimation method.
Railway Vehicle Wheel Flat Detection with Multiple Records Using Spectral Kurtosis Analysis
Authors: Mosleh Araliya , Montenegro Pedro Aires , Costa Pedro Alves , Calçada Rui
Published: April 2021

The gradual deterioration of train wheels can increase the risk of failure and lead to a higher rate of track deterioration, resulting in less reliable railway systems with higher maintenance costs. Early detection of potential wheel damages allows railway infrastructure managers to control railway operators, leading to lower infrastructure maintenance costs. This study focuses on identifying the type of sensors that can be adopted in a wayside monitoring system for wheel flat detection, as well as their optimal position. The study relies on a 3D numerical simulation of the train-track dynamic response to the presence of wheel flats. The shear and acceleration measurement points were defined in order to examine the sensitivity of the layout schemes not only to the type of sensors (strain gauge and accelerometer) but also to the position where they are installed. By considering the shear and accelerations evaluated in 19 positions of the track as inputs, the wheel flat was identified by the envelope spectrum approach using spectral kurtosis analysis. The influence of the type of sensors and their location on the accuracy of the wheel flat detection system is analyzed. Two types of trains were considered, namely the Alfa Pendular passenger vehicle and a freight wagon.
Comprehensive Study of Variety Oenological Potential Using Statistic Tools for the Efficient Use of Non-Renewable Resources
Authors: Petronilho Sílvia , Rudnitskaya Alisa , Coimbra Manuel A. , Rocha Sílvia M.
Published: April 2021

The evaluation of the variety suitability regarding each appellation’s specificities should be a strategy for maximizing the varieties’ oenological potential while contributing to the sustainable production of quality wines, keeping their typicity and rationalizing winemaking costs. Thus, the combination of several grape physicochemical attributes, modulated by climate and vineyard characteristics, providing knowledge for each grape variety’s oenological potential, is a relevant and reliable support for winemakers’ decisions. To prove this hypothesis, six mature grape varieties from three harvests, each one from three vineyard parcels with different topographical conditions from Bairrada Appellation (Portugal), were studied using analysis of variance–simultaneous components analysis (ASCA). The effects of harvest year and parcel on grape berry weight, pH, titratable acidity, total sugars, total phenolics, antiradical activity, and volatile composition in free and glycosidically-linked forms were analyzed. The compositional plasticity of autochthonous varieties (white Arinto and Bical and red Baga, Castelão, and Touriga Nacional) was observed. Sauvignon Blanc grape composition was significantly modulated by harvest. This study represents an important contribution for the maintenance of varieties’ biodiversity while contributing to establishing their peculiarities. Autochthonous varieties, if accurately exploited, can provide higher characteristic diversity than worldwide used varieties, an aspect to be more objectively taken into consideration by winemakers.
Ensemble Learning Approach for the Prediction of Quantitative Rock Damage Using Various Acoustic Emission Parameters
Authors: Lee Hang-Lo , Kim Jin-Seop , Hong Chang-Ho , Cho Dong-Keun
Published: April 2021

Monitoring rock damage subjected to cracks is an important stage in underground spaces such as radioactive waste disposal repository, civil tunnel, and mining industries. Acoustic emission (AE) technique is one of the methods for monitoring rock damage and has been used by many researchers. To increase the accuracy of the evaluation and prediction of rock damage, it is required to consider various AE parameters, but this work is a difficult problem due to the complexity of the relationship between several AE parameters and rock damage. The purpose of this study is to propose a machine learning (ML)-based prediction model of the quantitative rock damage taking into account of combined features between several AE parameters. To achieve the goal, 10 granite samples from KAERI (Korea Atomic Energy Research Institute) in Daejeon were prepared, and a uniaxial compression test was conducted. To construct a model, random forest (RF) was employed and compared with support vector regression (SVR). The result showed that the generalization performance of RF is higher than that of SVRRBF. The R2, RMSE, and MAPE of the RF for testing data are 0.989, 0.032, and 0.014, respectively, which are acceptable results for application in laboratory scale. As a complementary work, parameter analysis was conducted by means of the Shapley additive explanations (SHAP) for model interpretability. It was confirmed that the cumulative absolute energy and initiation frequency were selected as the main parameter in both high and low-level degrees of the damage. This study suggests the possibility of extension to in-situ application, as subsequent research. Additionally, it provides information that the RF algorithm is a suitable technique and which parameters should be considered for predicting the degree of damage. In future work, we will extend the research to the engineering scale and consider the attenuation characteristics of rocks for practical application.
Research on Blockchain-Based E-Bidding System
Authors: Wang Dan , Zhao Jindong , Mu Chunxiao
Published: April 2021

In the field of modern bidding, electronic bidding leads a new trend of development, convenience and efficiency and other significant advantages effectively promote the reform and innovation of China’s bidding field. Nowadays, most systems require a strong and trusted third party to guarantee the integrity and security of the system. However, with the development of blockchain technology and the rise of privacy protection, researchers has begun to emphasize the core concept of decentralization. This paper introduces a decentralized electronic bidding system based on blockchain and smart contract. The system uses blockchain to replace the traditional database and uses chaincode to process business logic. In data interaction, encryption techniques such as zero-knowledge proof based on graph isomorphism are used to improve privacy protection, which improves the anonymity of participants, the privacy of data transmission, and the traceability and verifiable of data. Compared with other electronic bidding systems, this system is more secure and efficient, and has the nature of anonymous operation, which fully protects the privacy information in the bidding process.