bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gas sensing properties of Mg‐doped graphene for H2S, SO2, SOF2, and SO2F2 based on DFT
Authors: Peng Xiao , Liu Dongsheng , Zhao Feng , Tang Chao 
Published: July 2022

AbstractSulfur hexafluoride decompositions have been studied to analyze their adsorption properties on pristine graphene (PG) and Mg‐doped graphene (MgG). First of all, after calculating the formation energy of three Mg doping sites, the T doping site of Mg‐doped graphene is the most stable one. Then, several characteristic structures with different orientations and positions of the gas molecules have been carried out to adsorb on PG and MgG, respectively. By calculating the adsorption energies and distance, the most stable adsorption structure of each gas molecule is obtained. In addition, transferred charge (Qt), the density of states (DOS), the energy of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were used to further analyze the conductivity change and chemical stability of each adsorption system. The results indicate that the adsorption interactions of H2S, SO2, SOF2, and SO2F2 on PG are weak. H2S adsorbed on MgG presented physical adsorption, while the adsorption behaviors of SO2, SOF2, and SO2F2 on MgG are chemisorption. And the adsorption strength was SO2F2 > SOF2 > SO2. In short, MgG shows better selectivity and higher sensitivity to SO2, SOF2, and SO2F2 than PG, demonstrating that the MgG material can be used as suitable gas sensing equipment based on SF6 decomposition products detection, which provides a meaningful guide of alkaline earth metal‐doped graphene in the detection of partial discharge and partial overheat in gas‐insulated switchgears (GIS).
Homemade equity offerings via dividend reinvestment and stock purchase plans
Authors: Bond Shaun , Pai Yu‐Jou , Zheng Suyan 
Published: July 2022

AbstractThis paper investigates equity issuances through dividend reinvestment and stock purchase plans (DRSPPs). Using a unique sample collected from security registration filings, we show that firms can issue new shares through DRSPPs without using underwriters and consequently, save a large part of direct costs. This economical form of equity offering helps high dividend paying firms retain a substantial amount of cash flow from operations. With this innovative strategic practice of capital‐raising, we provide direct evidence showing that the pecking order still drives firms' financing. Furthermore, equity offerings via DRSPPs can avoid negative stock market reactions around the issuance date.
A more exhaustive study on the finite‐time and exponential tracking continuous control for constrained‐input mechanical systems: Improved design and experiments
Authors: Zavala‐Río Arturo , Zamora‐Gómez Griselda I. , Sanchez Tonametl , Reyes‐Cortes Fernando , López‐Araujo Daniela J. 
Published: July 2022

AbstractA more exhaustive study on the finite‐time/exponential tracking continuous control for mechanical systems with input constraints is developed. The resulting control scheme is characterized by the inclusion of position‐error and velocity‐error correction terms which are suitably shaped to achieve the concerned types of convergence. Such a shaping is carried out through control parameters that act as exponential weights on the gained position and velocity errors. As an innovative aspect of the proposal, such exponential weights are not restricted to satisfy a fixed equivalence relation among them but rather a wider comparative one. This gives rise to a wider spectrum of finite‐time convergent closed‐loop trajectories and gives an optional type of (unconventional) exponential convergence (in addition to the conventional one), which enlarges the controller potential for performance adjustment. This is further potentiated through a more generalized saturating structure on the error correction terms, that includes the usual saturating‐proportional saturating‐derivative type one as a particular case. The improved design is supported through a more general analysis based on more general strict Lyapunov functions, stating more solid analytical bases for possible design extensions on the accomplishment of other (more complex) control objectives. The study is further supported through experimental tests on a 3‐degree‐of‐freedom robot manipulator.
Tracking control design for periodic piecewise polynomial systems with multiple disturbances
Authors: Rathinasamy Sakthivel , Narayanan Aravinth , Kwon Ohmin 
Published: July 2022

AbstractThe present study examines the state tracking problem of periodic piecewise polynomial systems subject to multiple disturbances and actuator faults. Specifically, the fundamental period is partitioned into several subintervals and the piecewise matrix polynomial functions can be put together to approximate the dynamics over each period, which are characterized by Bernstein polynomials. Moreover, the system dynamics contains both matched and mismatched disturbances, wherein the matched disturbance is unknown and resulted from some exogenous system, and mismatched case is norm‐bounded. The control law is configured by integrating the output of the disturbance observer with state‐feedback reliable control law. Particularly, a disturbance observer is designed to estimate the disturbance caused by an exogenous system. Besides, by considering time‐varying polynomial Lyapunov function and making use of Bernstein polynomial approach, a set of sufficient conditions is derived which are expressed in terms of linear matrix inequalities. Further, by virtue of MATLAB software the desired controller and observer gain matrices can be computed. In conclusion, the potential and significance of the theoretical findings are confirmed by presenting a numerical example with simulation results.
Confidence interval‐based overload avoidance algorithm for virtual machine placement
Authors: Ahmadi Javad , Toroghi Haghighat Abolfazl , Rahmani Amir Masoud , Ravanmehr Reza 
Published: July 2022

AbstractVirtualization plays an essential role in decreasing energy consumption and optimizing resource utilization by enabling the creation of virtual machines (VM) and their consolidation through live migration. Excessive migrations and a lack of required VMs are two critical factors in QoS degradation. The current consolidation approaches impose an intensive time complexity and cannot be used in large data centers with hundreds of hosts. This article proposes a framework for dynamic consolidation divided into a QoS‐aware algorithm for overload avoidance and a power‐aware algorithm for VM placement. To compute a safe zone criterion for any VM, relations were suggested by applying an interval estimate with a confidence level. By employing this criterion, the offered algorithm could guarantee the quality of service (QoS), particularly for specific VMs, while avoiding overhead. The VM placement algorithm is developed based on the maximum utilization of active hosts. It provides the capability to control the number of active hosts for the data center manager. The simulation results with real workloads revealed that the proposed framework could decline the amount of service level agreement violations by 78% and the number of migrations by 74%, and energy consumption by up to 13% in comparison with the best results of the benchmark algorithms. Hence, the application of this framework upgrades the QoS of data centers and declines their energy costs.
Analytical solution of the bond strength between ribbed steel bar and engineered cementitious composites considering the fiber bridging effect
Authors: Pan Jiaojiao , Han Jian , Lou Tao , Deng Mingke 
Published: July 2022

AbstractThis paper investigated the analytical solution of the bond strength between ribbed steel bar and engineered cementitious composites (ECC). In this method, ECC cover was regarded as a thick‐walled cylinder subjected to the uniform internal pressure which consisted of an elastic uncracked outer ring and a partially cracked inner ring. For the uncracked outer ring, it can be solved by the elastic mechanics theory. To solve the partially cracked inner ring, two key problems that had to be investigated were the crack width and the tensile stress–crack width relationship of ECC. According to the steady‐state cracking mode, the hoop deformation of ECC was expressed by the equal distribution and then the crack width can be determined. Besides, the fictitious crack model in fracture mechanic was introduced to describe the crack propagation process. Then a trilinear model was applied to reflect the tensile stress–crack width relationship of ECC materials, which considered the combined action of aggregate bridging and fiber bridging on the crack surface. Finally, the comparison between the calculation results and experimental results was carried out to prove the validity of the analytic method of bond strength proposed in this paper. Results indicated that the analytical solution and the experimental data fitted in well with each other. Then parameter analyses were conducted based on the analytical method proposed in this paper.
Effect of design‐based learning on achievement in K‐12 education: A meta‐analysis
Authors: Delen Ibrahim , Sen Sedat 
Published: July 2022

AbstractDesign‐based learning (DBL) offers opportunities to support students' content understanding. Previous DBL studies reported different effect sizes by using the data from one participant group. The goal of this study was to conduct a meta‐analysis that would give a comprehensive picture of how DBL is connected to student achievement in different disciplines. In addition, we explored the moderators influencing achievement in DBL for K‐12 education. After investigating content‐related gains in our meta‐analysis on 37 individual articles with 52 effect sizes, we found that DBL had a positive and large effect ( = 0.602) on achievement in K‐12 education, and the effect size for science ( = 0.703) was higher than mathematics ( = 0.418) education. When considering the strong emphasis on science education in different DBL related frameworks and STEM (science, engineering, technology, and mathematics) education studies, this cumulative understanding could play an important role in the difference between science and mathematics. Studies that had control groups in the same school ( = 0.703) had statistically significantly higher effect sizes compared to studies that included control groups from different schools ( = 0.447). Studies with random assignment ( = 0.258) had statistically significantly smaller effect sizes compared to studies with non‐random assignment ( = 0.623). In addition, the effect of DBL on achievement showed statistically significant differences among different countries. The remaining moderators (school level, content support, measurement type, and experimental design) did not show statistically significant differences in terms of the effect of DBL on student achievement. Our review presents evidence that participating in DBL activities supports student achievement after the intervention, but how students transfer their content gains in other situations needs convincing evidence. To overcome this challenge, future studies can prioritize how to support achievement in state mandated tests to understand DBL's effect on students' content gains in different learning situations.
Prioritizing emotion objects in making sense of student learning of socioscientific issues
Authors: Leung Jessica Shuk Ching , Cheng Maurice Man Wai 
Published: July 2022

AbstractWe advance the understanding of how student emotions relate to their learning of socioscientific issues (SSI). Studies have tended to examine how students' positive and negative emotions about an issue contribute to their learning. However, this approach overlooks the fact that students may have different emotions about different objects (i.e., stakeholders, phenomena, the status quo, and the future) within an issue. In this study, we examined students' patterns of emotion objects with respect to the extent of their conceptual change from a reductionist view to a systems view of obesity. Using a multiple case study design, we tracked the emotion objects of four purposefully selected university students, who demonstrated either significant change or minimal change in their view of obesity. Data were collected over a 12‐week general education course on obesity and 6 months after the course, and included weekly reflective journals and delayed postcourse interviews. We found that students with different extents of conceptual change had distinguishable sets of emotion objects. For example, the emotion objects of students with significant conceptual change included obese people and the food industry. Furthermore, their emotions were more often moral in nature. These findings suggest that moral emotions are an integral part of SSI learning. We make two contributions to the literature. First, we identify the need to attend to and specify emotion objects as key variables in future research on emotions. In practice, teachers should consider strategies that help students attend to the emotion objects that matter for SSI learning. Second, we identify stakeholders as key emotion objects in SSI learning. The expression of moral emotions about stakeholders coincided with conceptual change to a systems view. This implies that future research and the practice of SSI learning should pay attention to students' moral emotions about stakeholders.
Review on the ecotoxicological impacts of plastic pollution on the freshwater invertebrate Daphnia
Authors: Samadi Afshin , Kim Youngsam , Lee Sang‐Ah , Kim Young Jun , Esterhuizen Maranda 
Published: July 2022

AbstractThe environmental impacts of plastic pollution have recently attracted universal attention, especially in the aquatic environment. However, research has mostly been focused on marine ecosystems, even though freshwater ecosystems are equally if not more polluted by plastics. In addition, the mechanism and extent to which plastic pollution affects aquatic biota and the rates of transfer to organisms through food webs eventually reaching humans are poorly understood, especially considering leaching hazardous chemicals. Several studies have demonstrated extreme toxicity in freshwater organisms such Daphnia. When such keystone species are affected by ambient pollution, entire food webs are destabilized and biodiversity is threatened. The unremitting increase in plastic contaminants in freshwater environments would cause impairments in ecosystem functions and structure, leading to various kinds of negative ecological consequences. As various studies have reported the effects on daphnids, a consolidation of this literature is critical to discuss the limitations and knowledge gaps and to evaluate the risk posed to the aquatic environment. This review was undertaken due to the evident need to evaluate this threat. The aims were to provide a meaningful overview of the literature relevant to the potential impact of plastic pollution and associated contaminants on freshwater daphnids as primary consumers. A critical evaluation of research gaps and perspectives is conducted to provide a comprehensive risk assessment of microplastic as a hazard to aquatic environments. We outlined the challenges and limitations to microplastic research in hampering better‐focused investigations that could support the development of new plastic materials and/or establishment of new regulations.
Prediction of traffic noise induced annoyance of vendors through noise indices using structural equation modeling: Artificial neural network model
Authors: Das Chidananda Prasad , Goswami Shreerup , Das Mira 
Published: July 2022

AbstractUrbanization and population growth, as well as the movement of diverse vehicles on urban roadways, all contribute to excessive noise in the urban acoustic environment. Annoyance, cardiovascular disease, dementia, hypertension, stress, sleeping problem, irritation, hair‐fall, headache, are the most common reported problems due to traffic noise exposure. The “Structural Equation Modeling–Artificial Neural Network Model” was used in the current study to predict traffic noise induced annoyance among 100 vendors whose shops are located from Khandagiri to Baramunda along the National Highway 16 of the smart city Bhubaneswar Odisha. Due to the movement of large number of heavy vehicles as well as medium and light weight vehicles, these roadways remain noisy throughout the day. Moreover, the annoyance questionnaire was developed in compliance with ISO/TS 15666 criteria for assessing annoyance level. The combination of SEM and ANN is rarely seen in acoustics, especially in noise studies. However, in this study, both SEM and ANN are used to predict annoyance using various noise indices. Moreover, the SEM model revealed a significant association between “Equivalent Noise Level” (Leq) and annoyance (p‐value = 0.031), “Minimum Noise Level” (LMin) and annoyance (p‐value = 0.049), “Background Noise Level” (L90) and annoyance (p‐value = 0.047), “Noise Pollution Level” (NPL) and annoyance (p‐value = 0.038). These associations indicate that Leq, LMin, L90 and NPL have a significant effect on annoyance. Furthermore, the PLS algorithm output from the measurement model verified a 47 percent variance in annoyance level. The ANN model confirmed that NPL is the most significant predictor of noise annoyance, followed by LMin, Leq, and L90. Moreover, the ANN model can predict annoyance with an accuracy of 68.5 percent.
Training-Related Stress and Performance in the Military
Authors: Vartanian Oshin , Boscarino Cathy , Jarmasz Jerzy , Zotov Vlad 
Published: July 2022

AbstractConsiderable research has focused on the effects of stress on the performance of military personnel on the battlefield. Less studied are the effects of stress on the performance of military personnel in the course of routine activities such as training. This chapter takes stock of stressors that impact learning and performance on a wide host of training-related activities, including simulated stress. This literature suggests a nuanced relationship between stress and performance in training, and highlights the moderating and mediating effects that social, contextual, and individual-differences factors exert on that relationship. Importantly, although training scenarios aim to mimic realistic levels of stress to develop resilience, it is critical that stress induced in the training environment does not surpass the regulatory abilities of the trainees to cause impairments in learning. Toward that end, we discuss regulatory mechanisms that can be engaged to manage the effect of stress on training-related performance, as well as novel findings from systems neuroscience on how the brain responds to the presence of acute stress.
Childhood Nature Connection and Constructive Hope
Authors: Chawla Louise 
Published: July 2022

Abstract1. Within a generation, children’s lives have largely moved indoors, with the loss of free-ranging exploration of the nearby natural world, even as research indicates that direct experiences of nature in childhood contribute to care for nature across the life span.2. In response, many conservation organizations advocate connecting children with nature, and there has been rising interest in measuring young people’s connectedness with nature, understanding how it relates to their well-being and stewardship behaviour and creating programs to increase connection.3. This article reviews the literature on these topics, covering both quantitative and qualitative studies. It notes that this research emphasizes positive experiences and emotions, even as global environmental changes and biodiversity loss accelerate.4. Young people’s emotions of worry, frustration and sadness as they learn about environmental degradation also express their understanding that they are connected to the biosphere. Therefore this review includes research on how young people cope with information about large-scale environmental problems, and it identifies practices to sustain hope.5. The review concludes by suggesting how research on connection with nature and coping with environmental change can benefit from integration.
Chemical characterization of cherry (Prunus avium) extract in comparison with commercial mimosa and chestnut tannins
Authors: Cesprini Emanuele , De Iseppi Alberto , Giovando Samuele , Tarabra Elisa , Zanetti Michela , Šket Primož , Marangon Matteo , Tondi Gianluca 
Published: July 2022

AbstractIn a growing context of green and circular economy, gaining knowledge of the composition of every crop is crucial, as this will allow for their full exploitation. Cherry (Prunus avium L.) is a widespread tree of particular interest for its fruits and its valuable timber. Its wood is rich in extractives and its characterization will allow to consider other applications for this feedstock. In this study, chipped cherry wood was extracted and chemically analysed to determine its total phenolic content, total condensed tannin, antioxidant capacity, and polysaccharide content through wet chemistry analysis. These investigations were coupled with 13C-NMR and FTIR spectrometry, with HPLC as well as elemental analysis to conduct a comprehensive chemical characterization. Thermogravimetric measurements were also taken to understand the behaviour of the extract when exposed to high temperature. The registered findings were benchmarked against commercial mimosa (Acacia mearnsii De Wild.) and chestnut (Castanea sativa Mill.) tannins which were selected as template for condensed and hydrolysable tannins, respectively. Cherry extract was found to be the poorest in phenolics which are mainly constituted of pyrogallic flavonoids strongly interconnected with significant amounts of polysaccharides.
Evaluation of Full-Length Versus V4-Region 16S rRNA Sequencing for Phylogenetic Analysis of Mouse Intestinal Microbiota After a Dietary Intervention
Authors: Katiraei Saeed , Anvar Yahya , Hoving Lisa , Berbée Jimmy F. P. , van Harmelen Vanessa , Willems van Dijk Ko 
Published: July 2022

AbstractThe composition of microbial communities is commonly determined by sequence analyses of one of the variable (V) regions in the bacterial 16S rRNA gene. We aimed to assess whether sequencing the full-length versus the V4 region of the 16S rRNA gene affected the results and interpretation of an experiment. To test this, mice were fed a diet without and with the prebiotic inulin and from cecum samples, two primary data sets were generated: (1) a 16S rRNA full-length data set generated by the PacBio platform; (2) a 16S rRNA V4 region data set generated by the Illumina MiSeq platform. A third derived data set was generated by in silico extracting the 16S rRNA V4 region data from the 16S rRNA full-length PacBio data set. Analyses of the primary and derived 16S rRNA V4 region data indicated similar bacterial abundances, and α- and β-diversity. However, comparison of the 16S rRNA full-length data with the primary and derived 16S rRNA V4 region data revealed differences in relative bacterial abundances, and α- and β-diversity. We conclude that the sequence length of 16S rRNA gene and not the sequence analysis platform affected the results and may lead to different interpretations of the effect of an intervention that affects the microbiota.