Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanical characterisation of PEEK-HA composite as an orthopaedic implant

ABSTRACT Nowadays research in the biopolymers is prominent area for research in medical fields. The metallic implants are used in many numbers for the orthopaedic surgeries. But some unavoidable issues are arising after surgeries like stress-shielding, osteogenesis imperfection, etc. To overcome such issues, re-surgery is only one painful option available for the patient. Sometimes, this option is not feasible for the weak and old patients, which results in increased life risk in such situation. Hence, a biopolymer may be the best solutions to eliminate such problems. Polyether ether ketone (PEEK) and hydroxyapatite (HA) are having biocompatible characteristic with different mechanical properties. Hence in this paper, three different compositions of PEEK-HA are considered and the composites were prepared using compression moulding technique. To compare the mechanical properties for different compositions of PEEK-HA, the porosity and tensile strength were calculated. Unlike the other techniques, the fracture toughness was evaluated through J-integral method to ensure the matching of the cracking phenomenon with the human bone. Tribological properties, for example, wear resistance and plasticity index for all compositions of PEEK and HA were executed in both static and dynamic mode. The result reveals that PEEK5HA can be used for the possible bone replacement.
Quantifying adaptive divergence of the snowfinches in a common landscape

Species living in a shared environment face similar selective pressures and often evolve adaptive divergence to avoid competition. Quantifying phenotypic divergence and its genetic parallelism among sympatric species is important for understanding of ecologically moderated biodiversity. Here, we integrate ecologic, phenotypic and genomic datasets to study to what extent three sympatrically snowfinches (Montifringilla adamsi, Pyrgilauda ruficollis and Onychostruthus taczanowskii) differ in their adaptations in order to co‐exist in a shared environment.
Anthropometric Characterization and Physical Performance by Age and Biological Maturation in Young Tennis Players

The objective was to analyze anthropometric and physical performance variables as a function of chronological age and biological maturity in young Chilean tennis players. The study was observational, cross-sectional, with descriptive and analytical characteristics. Eighty-seven tennis players were evaluated (58 men 15.1 ± 0.8 years and 29 women, 15.3 ± 0.8 years). The measured anthropometric variables were a sprint test of 20m; a modified agility test; a sit-and-reach test and shoulder flexibility; manual grip strength; horizontal jump in feet; a medicine ball throw; a countermovement vertical jump; an abalakov vertical jump and a 20-m shuttle-run test. The growth velocity acceleration peak (APHV), skeletal muscle mass and fat mass were calculated, R2 and standard error of estimate (SEE) were examined. The results show that chronological age explained the anthropometric variables between 1 and 23% in men and 1 and 29% in women; by biological age, variables were explained between 3 and 53% in men and 2 and 42% in women. Of the physical performance variables, chronological age described between 2 and 24% of them in men and 1 and 29% in women; the same were explained by biological age between 1 and 19% in men and 1 and 26% in women. We conclude that anthropometric variables showed a better relationship with biological age, except for volume of fat tissue, while physical performance variables showed low association with both biological and chronological age.
A Compact Gradient Refractive Index Metamaterial Lens for Endfire Fan-Beam Radiation

This letter presents an endfire fan-beam radiation antenna by utilizing a gradient refractive index metamaterial lens. The lens includes one core and two impedance matching layers, which are both based on the proposed metamaterial unit cells with a large refractive index variation range. An incident wave is excited from the antenna source and propagates to the lateral side of the lens. Two parallel plates set for the TE<sub>1</sub> mode condition are utilized such that <italic>E</italic>-plane radiating beam can be controlled. To validate our proposed design, a prototype working at 10 GHz is fabricated and measured. Measured results are in good agreement with the simulation. The height and thickness of the metamaterial lens are about 0.44 <italic>λ</italic><sub>0</sub> and 0.36 <italic>λ</italic><sub>0</sub>, where <italic>λ</italic><sub>0</sub> is the wavelength of the center frequency in free space. The measured <italic>E</italic>- and <italic>H</italic>-planes 3 dB beamwidths are 25° and 82° at the center frequency, respectively. The measured peak gain of the antenna is about 11.1 dBi, which implies a 5.4 dB gain enhancement compared with initial radiation source. Furthermore, this lens offers a high aperture efficiency of 72.4%.
Antimicrobial activity of some essential oils against Streptococcus agalactiae, an important pathogen for fish farming in Brazil

ABSTRACT The antimicrobial activity of the essential oils from Lippia alba, Lippia sidoides, Mentha piperita, Ocimum gratissimum and Zingiber officinale was tested against Streptococcus agalactiae. The major compounds in the oils, identified by gas chromatography and mass spectrometry (GC/MS), were geranial (25.4%), neral (16.6%) and caryophyllene oxide (16.0%) in L. alba; thymol (76.6%), p-cymene (6.3%) and β-caryophyllene (5.0%) in L. sidoides; menthol (30.5%), menthyl acetate (14.6%), pulegone (14.2%) and menthone (12.9%) in M. piperita; eugenol (43.3%), 1,8-cineole (28.2%) and β-selinene (5.5%) in O. gratissimum; and geranial (23.2%), neral (16.7%) and 1,8-cineole (15.8%) in Z. officinale. All essential oils evaluated showed bactericidal action against S. agalactiae with minimum inhibitory concentration (MIC) ranging from 312.5–2,500 μg mL−1 and minimum bactericidal concentration (MBC) ranging from 416.7–2,500 μg mL−1. In this study, L. sidoides essential oil showed the better results against S. agalactiae.
Temperature Dependent n‐Type Self Doping in Nominally 19‐Electron Half‐Heusler Thermoelectric Materials

The discovery of a semiconducting ground state XyYZ (y = 0.8 or 0.75) in nominally 19‐electron half‐Heusler materials warrants a closer look at their apparently metallic properties that often make them good thermoelectric (TE) materials. By systematically investigating the temperature dependence of off‐stoichiometry (x) in V0.8+xCoSb, Nb0.8+xCoSb, and Ti0.75+xNiSb it is found that x invariably increases with increasing temperature, leading to an n‐type self‐doping behavior. In addition, there is also a large phase width (range of x) associated with each phase that is temperature dependent. Thus, unlike in typical 18‐electron half‐Heuslers (e,g, TiNiSn), the temperature dependence of vacancy and carrier concentration (n) in nominally 19‐electron half‐Heuslers links its transport properties to synthesis conditions. The temperature dependence of x and n are understood using density functional theory based defect energies (Ed) and phase diagrams. Ed are calculated for 21 systems which can be used in predicting solubility in this family of compounds. Using this simple strategy, suitable composition and temperature synthesis conditions are devised for obtaining an optimized n to engineer TE properties in phase‐pure V0.8+xCoSb, and the previously unexplored Ta0.8+xCoSb.
Monte Carlo Modeling of Astrophysically-Relevant Temperature-Programmed Desorption Experiments

Abstract The formation of molecules in the interstellar medium is significantly driven by grain chemistry, ranging from simple (e.g. H2) to relatively complex (e.g. CH3OH) products. The movement of atoms and molecules on amorphous ice surfaces is not well constrained, and this is a quintessential component of surface chemistry. We show that ice structure created by utilizing an off-lattice Monte Carlo kinetics model is highly dependent on deposition parameters (i.e. angle, rate, and temperature). The model, thus far, successfully predicts the densities of deposition rate- and temperature-dependent laboratory experiments. The simulations indicate, when angle and deposition rate increase, the density decreases. On the other hand, temperature has the opposite effect and will increase the density. We can make ices with desired densities and monitor how molecules, like CO, percolate through H2O ice pores. The strength of this model lies in the ability to replicate TPD-like experiments by monitoring molecules diffusing on and desorbing from user-defined surfaces.
Review of Recent Development of MEMS Speakers

Facilitated by microelectromechanical systems (MEMS) technology, MEMS speakers or microspeakers have been rapidly developed during the past decade to meet the requirements of the flourishing audio market. With advantages of a small footprint, low cost, and easy assembly, MEMS speakers are drawing extensive attention for potential applications in hearing instruments, portable electronics, and the Internet of Things (IoT). MEMS speakers based on different transduction mechanisms, including piezoelectric, electrodynamic, electrostatic, and thermoacoustic actuation, have been developed and significant progresses have been made in commercialization in the last few years. In this article, the principle and modeling of each MEMS speaker type is briefly introduced first. Then, the development of MEMS speakers is reviewed with key specifications of state-of-the-art MEMS speakers summarized. The advantages and challenges of all four types of MEMS speakers are compared and discussed. New approaches to improve sound pressure levels (SPLs) of MEMS speakers are also proposed. Finally, the remaining challenges and outlook of MEMS speakers are given.
Inhibition of Spinal TRPV1 Reduces NMDA Receptor 2B Phosphorylation and Produces Anti-Nociceptive Effects in Mice with Inflammatory Pain

Transient receptor potential vanilloid 1 (TRPV1) has been implicated in peripheral inflammation and is a mediator of the inflammatory response to various noxious stimuli. However, the interaction between TRPV1 and N-methyl-D-aspartate (NMDA) receptors in the regulation of inflammatory pain remains poorly understood. This study aimed to investigate the analgesic effects of intrathecal administration of capsazepine, a TRPV1 antagonist, on carrageenan-induced inflammatory pain in mice and to identify its interactions with NMDA receptors. Inflammatory pain was induced by intraplantar injection of 2% carrageenan in male ICR mice. To investigate the analgesic effects of capsazepine, pain-related behaviors were evaluated using von Frey filaments and a thermal stimulator placed on the hind paw. TRPV1 expression and NMDA receptor phosphorylation in the spinal cord and glutamate concentration in the spinal cord and serum were measured. Intrathecal treatment with capsazepine significantly attenuated carrageenan-induced mechanical allodynia and thermal hyperalgesia. Moreover, carrageenan-enhanced glutamate and phosphorylation of NMDA receptor subunit 2B in the spinal cord were suppressed by capsazepine administration. These results indicate that TRPV1 and NMDA receptors in the spinal cord are associated with inflammatory pain transmission, and inhibition of TRPV1 may reduce inflammatory pain via NMDA receptors.
Behavioral strategy: mapping the trends, sources and intellectual evolution

PurposeThis paper presents a comprehensive review of academic research dedicated to the field of Behavioral Strategy. Based on a series of Bibliometric and network analyses, the paper identifies the prominent trend and growth patterns pertaining to the evolution of this important strategic management subfield; it documents which particular journals, articles and authors have most influenced its development, and it maps the intellectual structure and network of authors, publications and countries. Finally, the paper considers the substantive research themes emerging from the analyses reported, in terms of their implications for future work.Design/methodology/approachThe authors undertook a series of Bibliometric and network analyses of 217 relevant articles, published between 1975 and 2020, in journals listed in the Scopus database, using R-studio and VOSviewer. Articles incorporated in the study were selected based on relevant key terms searched from the title, abstract and list of keywords associated with each publication.FindingsThe results demonstrate that behavioral strategy has enjoyed robust and sustained growth, with widespread impact across many areas of the heterogeneous business and management field as a whole. Three distinct periods are identified: an infancy stage (prior to 1999); a steady growth stage (1999–2010); and a take-off stage (2011 onwards). The top three journals in terms of content coverage, based on the number of relevant articles published in relation to behavioral strategy, are Strategic Management Journal, Advances in Strategic Management (AiSM) and the Journal of Management, while the top three most influential journals, in terms of citations pertaining to Behavioral Strategy, based on an analysis of citations in the Scopus database, are Strategic Management Journal, Academy of Management Perspectives and Journal of Management Studies. Gerard P. Hodgkinson and Thomas C. Powell are the most prolific authors. The emerging themes based on intellectual structures have been identified as Behavioral Strategy, Behavioral Theory of Firm; Strategic Leadership and Dynamic Capabilities; and Strategic Cognition and Decision Making.Practical implicationsThe study contributes to knowledge advancement concerning Behavioral Strategy by opening new possibilities to discover important research areas.Originality/valueThe study is the first of its kind on Behavioral Strategy providing a comprehensive systematic literature review.
Thermodynamic limits for assimilation of silicate crust in primitive magmas

Some geochemical models for basaltic and more primitive rocks suggest that their parental magmas have assimilated tens of weight percent of crustal silicate wall rock. But what are the thermodynamic limits for assimilation in primitive magmas? We pursue this question quantitatively using a freely available thermodynamic tool for phase equilibria modeling of open magmatic systems—the Magma Chamber Simulator (https://mcs.geol.ucsb.edu)—and focus on modeling assimilation of wall-rock partial melts, which is thermodynamically more efficient compared to bulk assimilation of stoped wall-rock blocks in primitive igneous systems. In the simulations, diverse komatiitic, picritic, and basaltic parental magmas assimilate progressive partial melts of preheated average lower, middle, and upper crust in amounts allowed by thermodynamics. Our results indicate that it is difficult for any subalkaline primitive magma to assimilate more than 20–30 wt% of upper or middle crust before evolving to compositions with higher SiO2 than a basaltic magma (52 wt%). On the other hand, typical komatiitic magmas have thermodynamic potential to assimilate as much as their own mass (59–102 wt%) of lower crust and retain a basaltic composition. The compositions of the parental melt and the assimilant heavily influence both how much assimilation is energetically possible in primitive magmas and the final magma composition given typical temperatures. These findings have important implications for the role of assimilation in the generation and evolution of, e.g., ultramafic to mafic trans-Moho magmatic systems, siliceous high-Mg basalts, and massif-type anorthosites.
Measuring How Decision Support Systems Improve Newsvendors’ Performance: The Subjects’ Version

Despite the emerging contribution of machine automation, artificial intelligence and information systems, humans remain yet the most fragile ring of any organization. Decision support systems are widespread, supporting us to decide among uncertainties, such as weather conditions, suppliers’ performances and financial opportunities, but how humans take into account this information and, most of all, how they trust their own management knowledge is a controversial issue. This paper assesses, by means of a controlled experiment and ex post interviews, how individuals consider and use decision support systems in the context of the Newsvendor Problem. In accordance with prior research, the results show that individuals’ order quantities are pull-to-center biased. Moreover, ex post direct interviews suggest that (i) the individuals’ trust in decision support systems is not blind; (ii) individuals do not play the business game as a real task, (iii) they are biased by the type of incentive promised and (iv) they seem not skilled or trained enough. Ex post interviews shed a new light on controlled human experiments: they should be better analyzed and re-engineered.
Effect of Hydrated Deep Eutectic Solvents on the Thermal Stability of DNA

DNA’s structure stability in hydrated deep eutectic solvents (DESs) is getting growing attention for emerging bio-applications. The employment of DESs as novel co-solvents in water media could favor eco-friendly and biodegradable materials for DNA storage and handling. Understanding the molecular interactions between nucleic acids and aqueous DES is crucial for developing new-generation solvents for biomolecules. In this work, we exploit the molecular sensitivity and selectivity of synchrotron radiation UV resonance raman (SR-UVRR) spectroscopy to explore the interplay between a choline chloride:urea (ChCl:U) DES and double-stranded DNA. Our study analyzes the impact of ChCl:U on the DNA’s thermal unfolding pathway by focusing on the guanine nucleobases whose Raman signal could be strongly enhanced through careful tuning of the excitation wavelength.
Food Choices and Their Impact on Health and Environment

Food choices are complex and highly variable, even over short periods, as they are influenced by numerous psychological, social, and cultural factors, in addition to biological and economic ones. Consumer choices are increasingly complex because of the growing quantity and variety of available food products, which also affects individuals’ environments. This paper is part of a larger study on health-related food choices, and it discusses how food choices affect the environment. To achieve the research goal, classes of respondents that are homogeneous in their food choices were identified. The authors used an algorithm to build classification trees and found that health status is determined by respondents’ age and food consumption habits. The paper demonstrates that understanding individual nutritional choices is a prerequisite for changing consumption habits and shaping healthy behavior, which is in line with the principle of sustainable development through sustainable consumption. The findings are relevant to public health researchers and practitioners who wish to understand the relationship between nutritional practices and health in line with sustainable development.
Effect of Attraction, the Quality of Destination, Motivation, and Satisfaction of Intention to Revisit on Heritage Destination

This study aims to examine the intention to revisit the model of heritage tourism in Yogyakarta. Intention to revisit in this study is influenced by attractiveness, destination quality, tourist motivation and tourist satisfaction. This study uses respondents of tourists visiting heritage. The sampling technique used was purposive sampling with a total of 250 respondents. Data analysis techniques used the AMOS Structural Equation Modeling. The results showed that the intention to revisit the model was acceptable. It was further explained that attractiveness, destination quality, tourist motivation and tourist satisfaction had a positive influence on the intention to return to tourism heritage in the Special Region of Yogyakarta.
Saline stress and potassium/calcium ratio in fertigated eggplant

ABSTRACT In order to evaluate the effect of irrigation water salinity in interaction with different potassium and calcium ratios applied through fertigation in eggplant, an experiment was carried out at the Department of Environmental and Technological Sciences of the Federal Rural University of the Semi-Arid Region, in Mossoró, RN, Brazil. The experimental design was randomized blocks, in a 5 x 4 factorial scheme, with four replicates. The treatments were obtained by the combination between five ionic ratios of potassium and calcium (F1 = 4.2/1; F2 = 3.5/1; F3 = 2.8/1; F4 = 2.2/1; F5 = 1.8/1) and four levels of irrigation water salinity (S1 – 0.5; S2 – 2.0; S3 – 3.5; and S4 – 5.0 dS m-1). The following variables were evaluated: number of fruits per plant, fruit length, fruit diameter, fruit fresh weight and yield. Yield, fruit length, fruit fresh weight and number of fruits decreased with the increase of salinity in all the treatments. Salinity significantly affected fruit diameter, which increased only under fertigation with potassium-rich solutions.
Mutual Information-Based Graph Co-Attention Networks for Multimodal Prior-Guided Magnetic Resonance Imaging Segmentation

Multimodal magnetic resonance imaging (MRI) provides complementary information about targets, and the segmentation of multimodal MRI is widely used as an essential preprocessing step for initial diagnosis, stage differentiation, and post-treatment efficacy evaluation in clinical situations. For the main modality or each of the modalities, it is important to enhance the visual information by modeling the connection and effectively fusing the features among them. However, the existing methods for multimodal segmentation have a drawback; they coincidentally drop information of individual modality during the fusion process. Recently, graph learning-based methods have been applied in segmentation, and these methods have achieved considerable improvements by modeling the relationships across feature regions and reasoning using global information. In this paper, we propose a graph learning-based approach to efficiently extract modality-specific features and establish regional correspondence effectively among all modalities. In detail, after projecting features into a graph domain and employing graph convolution to propagate information across all regions for learning global modality-specific features, we propose a mutual information-based graph co-attention module to learn the weight coefficients of one bipartite graph constructed by the fully connected graphs having different modalities in the graph domain and by selectively fusing the node features. Based on the deformation diagram between the spatial-graph space and our proposed graph co-attention module, we present a multimodal prior-guided segmentation framework, which uses two strategies for two clinical situations: Modality-Specific Learning Strategy and Co-Modality Learning Strategy. Besides, the improved Co-Modality Learning Strategy is used with trainable weights in the multi-task loss for the optimization of the proposed framework. We validated our proposed modules and frameworks on two multimodal MRI datasets: our private liver lesion dataset and a public prostate zone dataset. Our experimental results on both datasets prove the superiority of our proposed approaches.