Favorable Choice Research Articles

Impacts of aluminum-cerium alloy deployment on different cerium commodities

An imbalance problem exists in the rare earth element (REE) market with cerium and lanthanum being more abundant and less valuable than REEs used in permanent magnets such as neodymium, praseodymium, and dysprosium. Research has been conducted on new applications for abundant REEs to improve mining economics. However, potential market impacts of these applications on individual REE commodities are unknown. A system dynamics model was built to investigate the impacts of a new aluminum-cerium (Al–Ce) alloy that can theoretically utilize three separate cerium forms: cerium carbonate, cerium oxide, or cerium metal. Cerium carbonate currently possesses the lowest price of the three available forms making it initially the most favorable choice. However, model results showed that cerium oxide could provide the best economics for future Al–Ce alloy deployment because its larger market size buffers major shocks to price.

A comparative DFT study of MgFe2O4 and MnFe2O4 spinel ferrites at various pressures to investigate the structural, mechanical, electronic, magnetic and optical properties for multifunctional applications

The structural, electronic, mechanical, optical, and magnetic properties of the MgFe2O4 and MnFe2O4 ferrites were investigated under pressures ranging from 0 to 20 GPa using the DFT-based CASTEP Code. XRD analyses indicated differences in lattice constants, volumes and d-spacing between these ferrites, with decreasing trends under applied pressure. The MgFe2O4 ferrite has lower X-ray density, but higher electronic bandgap energy compared to the MnFe2O4 ferrite, both showing semiconductor behavior. Magnetic properties show a decrease in total magnetic moment and saturation magnetization under applied pressure for both ferrites, making them potential materials for transformer and inductor cores. Mechanical properties confirm their stability, elastic behavior, ductility and ionic bond nature, suitable for electrochemical devices. The MgFe2O4 ferrite exhibits dominant absorption and optical conductivity in the visible region compared to the MnFe2O4 ferrite, making it a favorable choice for optoelectronic and photocatalytic applications.

Adaptability of Prunus cerasifera Ehrh. to Climate Changes in Multifunctional Landscape

Urban trees play a vital role in mitigating climate changes, maintaining the sustainability of ecosystems. This study focuses on the assessment of the resilience of cherry plums to climate changes, a fruit-bearing species that offers diverse ecosystem services within multifunctional urban and suburban landscapes. This study examines flowering and fruiting in the context of climate characteristics, expressed through the Day of the Year (DOY), Growing Degree Days (GDDs), and a yield over 17 consecutive years. The results indicate significant shifts in the DOY but not in the GDD, apart from the end of flowering. The onset of flowering was earlier and the end postponed, extending the phenophase by an average of 4 days. The cherry plum’s yield was unaffected by climate changes, including extreme events like a late-spring frost. The stability of the cherry plum was confirmed by the phenological patterns of the bullace (cherry plum and blackthorn hybrid) exhibiting repeated flowering in the warmest year of 2023. The cherry plum is an adaptive species, with a high adaptability to a changing climate and a high resistance to late-spring frosts; thus, it is a favorable choice in urban design and planning, demonstrating resilience to climate shifts and thriving in polluted urban environments. It is especially appreciated for multiple ecosystem services: biodiversity conservation in natural and semi-natural areas, yielding good provisions in challenging environments, and the preservation of ornamental values through an extended flowering phenophase.

Enhancing Education in Elementary Schools through Gamified Learning: Exploring the Impact of Kahoot! on the Learning Process

The integration of technology in educational settings has gained popularity, aiming to enhance student engagement and motivation. Kahoot! digital tool activities have emerged as a favored choice for creating dynamic and captivating learning environments. This study investigates the impact of incorporating Kahoot! on students’ learning outcomes and motivation to learn science. The research utilized a quantitative methodology, collecting data through pre- and post-questionnaires administered to both experimental (N = 53) and control groups (N = 56). This study identified that integrating Kahoot! activities led to a significant improvement in students’ grasp of scientific concepts and principles. Moreover, a noteworthy increase in self-efficacy, interest, and enjoyment levels was observed among students in the experimental groups. This indicates that Kahoot! activities not only enhance students’ understanding of scientific concepts but also amplify their motivation to engage with the subject matter. This study also explored potential demographic variables that could influence these outcomes. Notably, the findings suggest that grade level plays a role in students’ motivation to learn science. In conclusion, this study underscores the potential of Kahoot! activities to positively influence students’ science learning experiences, emphasizing the importance of cultivating dynamic and captivating learning environments.

QEMCGAN: Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN for Medical Image Translation.

Generative adversarial networks (GANs) have become popular in medical imaging because of their remarkable performance and ability to translate images across different domains. However, GANs face several issues in image-to-image translation, including training instability, lack of diversity, and mode collapse. These issues become even more complex when using cyclic GANs. Additionally, collecting paired images required for GANs may be costly, especially in the medical domain. Cyclic GANs are a favorable choice for addressing this issue, as they can convert cross-domain images. However, no pre-existing technique or algorithm is comprehensive enough to handle diverse datasets and applications. To address these issues, we propose a novel Quantized Evolutionary Gradient Aware Multiobjective Cyclic GAN (QEMCGAN) that employs evolutionary computation, multiobjective optimization, and an intelligent selection scheme. We use simulated annealing and Pareto ranking selection using three fitness criteria to address local optima stagnation. Additionally, we use model quantization because of its suitability for low-cost IoT-based applications. Extensive trials reveal that EMCGAN and QEMCGAN produces more visually realistic images than other approaches while preserving both background information and salient features. In addition, QEMCGAN performs on par with the baseline approach even when the model size is halved, making it more efficient.

Research progress of direct contact heat storage based on phase change heat storage

AbstractPhase change heat storage presents a promising solution to address challenges related to new energy intermittency and waste heat recovery. However, for it to function as an effective energy hub, heat storage becomes crucial. Among the available options, the direct contact heat accumulator stands out due to its simple structure, substantial heat transfer area, and minimal heat transfer resistance, making it a favorable choice for enhancing energy storage rates. Although a great deal of research has been done on phase change materials and heat accumulators over the years, a systematic review of direct‐contact heat accumulators is lacking. This article reviews the related research on direct contact heat storage, aiming to summarize the research work on direct contact phase change heat storage systems. Various phase change materials (PCMs) for direct contact systems are analyzed, and the study of PCM melting crystallization behavior, heat transfer coefficients and system performance in direct contact systems is summarized, as well as the improvement methods for direct contact vessels and PCMs. It provides a useful reference for future research on direct‐contact heat storage systems.

Hybrid methods for solving structural geometric nonlinear dynamic equations: Implementation of fifth-order iterative procedures within composite time integration methods

This paper studies a class of hybrid methods that implement multi-point iterative procedures as the nonlinear solver within optimized composite implicit methods. These multi-point methods are employed to enhance convergence order and accuracy without requiring higher-order derivatives for solving structural geometric nonlinear dynamic equations. The promising approach provides an opportunity to delve deeper into its implications and explore the potential applications of multi-point techniques and composite methods across the analysis of dynamical systems. This study involves the utilization of two-point and five-point iterative methods with fifth-order convergence within three-step and four-step optimized composite implicit time integration methods. Moreover, a comprehensive hybrid scheme is introduced by integrating a family of optimized composite implicit methods with single-point and multi-point iterative methods. Then, the performance of the hybrid scheme is analyzed through structural examples, considering factors such as time step size, tolerance threshold, and the degrees of freedom of structures. The findings and numerical results illustrate that multi-point methods outperform the single-point method in terms of the number of iterations. Simultaneously, the four-step time integration method exhibits superior performance compared to the three-step time integration method, albeit with a marginal difference. It is observed that the hybrid method, consisting of the four-step time integration method and the five-point iterative method, performs better than other methods in terms of the number of iterations and errors for solving geometric nonlinear dynamic equations, especially in large structures. Thus, it stands out as a favorable choice for practical analyses and a possible candidate for generalization to other types of nonlinear problems in computational mechanics.

Estimation of the percentile of Birnbaum-Saunders distribution and its application to PM2.5 in Northern Thailand.

The Birnbaum-Saunders distribution plays a crucial role in statistical analysis, serving as a model for failure time distribution in engineering and the distribution of particulate matter 2.5 (PM2.5) in environmental sciences. When assessing the health risks linked to PM2.5, it is crucial to give significant weight to percentile values, particularly focusing on lower percentiles, as they offer a more precise depiction of exposure levels and potential health hazards for the population. Mean and variance metrics may not fully encapsulate the comprehensive spectrum of risks connected to PM2.5 exposure. Various approaches, including the generalized confidence interval (GCI) approach, the bootstrap approach, the Bayesian approach, and the highest posterior density (HPD) approach, were employed to establish confidence intervals for the percentile of the Birnbaum-Saunders distribution. To assess the performance of these intervals, Monte Carlo simulations were conducted, evaluating them based on coverage probability and average length. The results demonstrate that the GCI approach is a favorable choice for estimating percentile confidence intervals. In conclusion, this article presents the results of the simulation study and showcases the practical application of these findings in the field of environmental sciences.

Enhanced mixing efficiency and reduced droplet size with novel droplet generators

Nowadays, droplet microfluidics has become widely utilized for high-throughput assays. Efficient mixing is crucial for initiating biochemical reactions in many applications. Rapid mixing during droplet formation eliminates the need for incorporating micromixers, which can complicate the chip design. Furthermore, immediate mixing of substances upon contact can significantly improve the consistency of chemical reactions and resulting products. This study introduces three innovative designs for droplet generators that achieve efficient mixing and produce small droplets. The T-cross and cross-T geometries combine cross and T junction mixing mechanisms, resulting in improved mixing efficiency. Numerical simulations were conducted to compare these novel geometries with traditional T and cross junctions in terms of mixing index, droplet diameter, and eccentricity. The cross-T geometry exhibited the highest mixing index and produced the smallest droplets. For the flow rate ratio of 0.5, this geometry offered a 10% increase in the mixing index and a decrease in the droplet diameter by 10% compared to the T junction. While the T junction has the best mixing efficiency among traditional droplet generators, it produces larger droplets, which can increase the risk of contamination due to contact with the microchannel walls. Therefore, the cross-T geometry is highly desirable in most applications due to its production of considerably smaller droplets. The asymmetric cross junction offered a 8% increase in mixing index and around 2% decrease in droplet diameter compared to the conventional cross junction in flow rate ratio of 0.5. All novel geometries demonstrated comparable mixing efficiency to the T junction. The cross junction exhibited the lowest mixing efficiency and produced larger droplets compared to the cross-T geometry (around 1%). Thus, the novel geometries, particularly the cross-T geometry, are a favorable choice for applications where both high mixing efficiency and small droplet sizes are important.

A Study of the Effects of Alum and PAC on the Coagulation Process of Dug Well Water

The local population of Pal IX Village in West Kalimantan heavily depends on dug wells as their main source of obtaining clean water. The prolonged consumption of elevated concentrations of manganese (Mn) and iron (Fe) in water sourced from dug wells have neurotoxic effects on both adults and children. Therefore, it is imperative to employ alum and PAC coagulants for the treatment of dug well water in order to comply with the established national quality standard. However, the utilization of both coagulants resulted in elevation in the levels of iron (Fe), hence restricting the capacity to satisfy the quality standards. An augmentation in the mass of the coagulant is associated with a decline in the reduction efficiency. It is indicated that utilizing a mass of 0.5 grams of alum coagulant is the most favorable choice, resulting in a reduced of 50.14% for total dissolved solids (TDS), 86.25% for color, 97.70% for turbidity, and 94.48% for the concentration of Mn metal. By PAC coagulant, it has been determined that an ideal coagulant mass of 0.5 gram produces favorable outcomes with a TDS reduction of 45.08%, a color reduction of 97.71%, a turbidity reduction of 97.22%, and a Mn reduction of 95.04%.

A novel extraoral ultrasound-guided approach for mandibular nerve block in Rahmani sheep

BackgroundRegional anesthesia is the favored choice in ruminant animals compared to general anesthesia, primarily due to its high safety margin and reduced demand for cost-intensive equipment in addition to its field applicability. Ultrasound-guided nerve block has gained significant attention in the field of veterinary medicine. This study utilized twenty-seven sheep of the native Rahmani breed to both demonstrate and evaluate the effectiveness of the ultrasound guided inferior alveolar nerve block technique.MethodsThe research comprised three phases: Phase 1 involved an anatomical examination of mandibles and sheep heads to locate the mandibular foramen and delineate the mandibular nerve course. Phase 2 included ultrasound-guided injection of methylene blue dye at specific sites along the mandibular nerve in cadaveric sheep heads. In Phase 3, clinical implementation of ultrasound-guided inferior alveolar nerve blocks was conducted in 27 live sheep, assessing efficacy, onset, and duration.ResultsVertical extraoral ultrasound-guided nerve block was achieved successfully in 25 sheep (98%). A preliminary cadaveric study showed good distribution of the injectate at the mandibular nerve site. The mean onset time was 138 ± 18 s, and the mean duration time was 54 ± 4.1 min. Prominent analgesia of the ipsilateral mandible, medial surface of the cheek, and lateral border of the tongue was observed.ConclusionsUltrasound-guided mandibular nerve block holds promise as a technique for providing effective and safe anesthesia in sheep undergoing mandibular procedures.

Gadolinium: A DFT exploration of structural, electronic, and magnetic features in bulk and film configurations for enhanced magnetocaloric understanding

Gadolinium stands as the favored choice among magnetic refrigerant materials for numerous active magnetic regenerator (AMR) prototypes due to its remarkable ability to exhibit a substantial change in magnetic entropy. This unique characteristic arises from its status as one of the elemental ferromagnets with a high Curie temperature, closely aligning with room temperature conditions, and undergoing a second-order magnetic phase transition. In this comprehensive study, we employ density functional theory (DFT) calculations to explore the structural, electronic, and magnetic properties of both Gadolinium bulk and film configurations. Our primary objective is to gain a deeper understanding of the intricate physics underlying the intriguing magnetocaloric features observed in Gadolinium. This investigation provides valuable insights into the potential applications and the broader implications of Gadolinium in the realm of magnetic refrigeration technology.

MsMYB62-like as a negative regulator of anthocyanin biosynthesis in Malus spectabilis

ABSTRACT Crabapple is a valuable tree species in gardens due to its captivating array of flower and leaf colors, rendering it a favored choice in landscaping. The economic and ornamental values of Malus crabapple are closely associated with the biosynthesis of anthocyanin, a pigment responsible for its vibrant hues. The intricate regulation of anthocyanin biosynthesis involves the concerted activity of various genes. However, the specific mechanism governing this process in crabapple warrants in-depth exploration. In this study, we explored the inhibitory role of MsMYB62-like in anthocyanin biosynthesis. We identified MsDFR and MsANS as two downstream target genes of MsMYB62-like. These genes encode enzymes integral to the anthocyanin biosynthetic pathway. The findings demonstrate that MsMYB62-like directly binds to the promoters of MsDFR and MsANS, resulting in the downregulation of their expression levels. Additionally, our observations indicate that the plant hormone cytokinins exert a suppressive effect on the expression levels of MsMYB62-like, while concurrently upregulating MsDFR and MsANS. This study reveals that the MsMYB62-like-MsDFR/MsANS module plays an important role in governing anthocyanin levels in Malus crabapple. Notably, the regulatory interplay is modulated by the plant hormone cytokinins.

Assessment of COVID-19 infection Risk, thermal Comfort, and energy efficiency in negative pressure isolation wards with varied ventilation modes

Negative pressure isolation wards (NPIWs) play a crucial role in providing care to COVID-19 patients during a pandemic. However, the exhalation of patients releases aerosols containing pathogens, posing a potential infection risk for healthcare workers (HCWs). While robust ventilation systems within NPIWs can help mitigate this risk, they may also lead to increased energy consumption and reduced thermal comfort for patients. Therefore, it is imperative to strike a delicate balance between HCW safety, patient comfort, and energy efficiency when optimizing airflow within NPIWs. This study introduces TARGETING, a novel index designed to assess the efficiency of aerosols removal of ventilation systems in NPIWs. The primary goal of TARGETING is to enhance the precision of ventilation systems, consequently reducing the required air changes per hour (ACH) and minimizing energy consumption. The research delves into the impact of various supply air parameters, including ACH and temperature, as well as different ventilation modes. Through a comprehensive evaluation utilizing an array of metrics such as the Air Diffusion Performance Index (ADPI), Predicted Mean Vote (PMV), TARGETING, infection risk assessment, and energy consumption estimation measured by cooling load (Lcool), this study employs an Analytic Hierarchy Process to assess the aforementioned indices. The findings highlight that air curtain ventilation (ACV) emerges as the most favorable choice, delivering comprehensive benefits, including an infection risk of less than 0.03%, an ADPI score of 90.2%, a PMV close to zero, TARGETING at 1.3, and energy savings ranging from 35.1% to 57.3%.

Enhancing systematic tolerance in Bermuda grass (Cynodon dactylon L.) through amplified alkB gene expression and bacterial-driven hydrocarbon degradation.

This study aimed to access the impact of soil polluted with petroleum (5, 10g petroleum kg-1 soil) on Bermuda grass (Cynodon dactylon L.) with and without applied bacterial inoculants (Arthrobacter oxydans ITRH49 and Pseudomonas sp. MixRI75). Both soil and seed were given bacterial inoculation. The evaluated morphological parameters of Bermuda grass were fresh and dry weight. The results demonstrated that applied bacterial inoculants enhanced 5.4%, 20%, 28% and 6.4%, 21%, and 29% shoot and root fresh/dry weights in Bermuda grass under controlled environment. The biochemical analysis of shoot and root was affected deleteriously by the 10g petroleum kg-1 soil pollution. Microbial inoculants enhanced the activities of enzymatic (catalase, peroxidase, glutathione reductase, ascorbate peroxidase, superoxide dismutase) and non-enzymatic (ɑ-tocopherols, proline, reduced glutathione, ascorbic acid) antioxidant to mitigate the toxic effects of ROS (H2O2) under hydrocarbon stressed condition. The maximum hydrocarbon degradation (75%) was recorded by Bermuda grass at 5g petroleum kg-1 soil contamination. Moreover, bacterial persistence and alkane hydroxylase gene (alkB) abundance and expression were observed more in the root interior than in the rhizosphere and shoot interior of Bermuda grass. Subsequently, the microbe used a biological tool to propose that the application of plant growth-promoting bacteria would be the most favorable choice in petroleum hydrocarbon polluted soil to conquer the abiotic stress in plants and the effective removal of polyaromatic hydrocarbons in polluted soil.

The Influence of Nickel-Titanium (Ni-Ti) Rotary Instrument Systems on Debris and Smear Layer Formation in Endodontic Procedures: An In Vitro Scanning Electron Microscopy Study.

Background Successful endodontic treatment relies on the effective removal of debris and the prevention of smear layer formation within the root canals. The choice of nickel-titanium (Ni-Ti) rotary instrument systems can significantly impact these outcomes. Aim This study aims to evaluate and compare the debris and smear layer formation in root canals of extracted mandibular second premolar teeth following instrumentation with the ProTaper Universal (Dentsply Sirona,Charlotte, NC) (Group II), Twisted File (Kerr Endodontics, Gilbert, AZ) (Group III), and XP Endo (FKG Dentaire,La Chaux-de-Fonds, Switzerland) (Group IV) Ni-Ti rotary instrument systems. Methods In this in vitro study, 60 extracted mandibular second premolar teeth were randomly divided into four groups, each containing 15 teeth. Group I served as the control with no instrumentation. Groups II, III, and IV were instrumented with the ProTaper Universal rotary file, the Twisted File, and the XP Endo file systems, respectively. Debris and smear layer formation were evaluated through scanning electron microscopy (SEM), and photomicrographs were scored using a standardized index. Results Group II (ProTaper) exhibited the highest mean debris and smear layer scores, with values of 3.50 and 2.70, respectively. Group IV (XP Endo) demonstrated the least debris and smear layer formation, with mean scores of 2.65 and 2.08, respectively. Statistical analysis confirmed significant differences among the groups for both debris and smear layer formation. Conclusion The results highlight the practical importance of selecting appropriate Ni-Ti rotary instrument systems to minimize debris and smear layer formation during endodontic procedures. The XP Endo file system showed promise as a favorable choice in this regard, but further clinical research is needed to validate these findings.

How Indomie Survived and Led in the Middle East

The factors contributing to the thriving market penetration of the Indomie brand in the Middle Eastern instant noodle industry. Through an analysis of the brand's localization, affordability, adaptability to dietary needs, marketing, and distribution strategies, the abstract highlights the critical components of Indomie's triumph. The brand's ability to tailor flavors, packaging, and promotional efforts to align with Middle Eastern preferences has played a significant role in its widespread popularity. Moreover, the affordability and accessibility of Indomie products have positioned them as a favored choice across various consumer segments. The brand's recognition and response to dietary considerations, such as halal certification, further underscore its resonance with the regional market. The abstract underscores the insights that can be gleaned from Indomie's success story, particularly in effectively navigating diverse cultural and economic landscapes through strategic alignment and marketing acumen.

On the robustness of the brand positivity effect: Is impulsivity a moderator of overly favorable judgments and choices of focal options?

AbstractFive experiments were conducted to explore trait impulsivity as a possible contributor to the magnitude of the Brand Positivity Effect, and to provide a more sophisticated empirical account of the role of selective processing in driving it than reported in prior research. Although the experiments considered very different choice categories including a product, a service, an experience, and a public good, data were convergent in several ways: (a) the Brand Positivity Effect in judgment, choice intention, and non‐hypothetical choice was replicated, (b) non‐intrusive process‐tracing methodology established that selective processing is related to the magnitude of the Brand Positivity Effect, and (c) the Brand Positivity Effect was demonstrated to be a robust phenomenon that is observed regardless of individuals' trait impulsivity.

Research on Multi-Hole Localization Tracking Based on a Combination of Machine Vision and Deep Learning

In the process of industrial production, manual assembly of workpieces exists with low efficiency and high intensity, and some of the assembly process of the human body has a certain degree of danger. At the same time, traditional machine learning algorithms are difficult to adapt to the complexity of the current industrial field environment; the change in the environment will greatly affect the accuracy of the robot’s work. Therefore, this paper proposes a method based on the combination of machine vision and the YOLOv5 deep learning model to obtain the disk porous localization information, after coordinate mapping by the ROS communication control robotic arm work, in order to improve the anti-interference ability of the environment and work efficiency but also reduce the danger to the human body. The system utilizes a camera to collect real-time images of targets in complex environments and, then, trains and processes them for recognition such that coordinate localization information can be obtained. This information is converted into coordinates under the robot coordinate system through hand–eye calibration, and the robot is then controlled to complete multi-hole localization and tracking by means of communication between the upper and lower computers. The results show that there is a high accuracy in the training and testing of the target object, and the control accuracy of the robotic arm is also relatively high. The method has strong anti-interference to the complex environment of industry and exhibits a certain feasibility and effectiveness. It lays a foundation for achieving the automated installation of docking disk workpieces in industrial production and also provides a more favorable choice for the production and installation of the process of screw positioning needs.

Machine Learning-Based Classification of Turkish Music for Mood-Driven Selection

Music holds a significant role in our daily lives, and its impact on emotions has been a focal point of research across various disciplines, including psychology, sociology, and statistics. Ongoing studies continue to explore this intriguing relationship. With advancing technology, the ability to choose from a diverse range of music has expanded. Recent trends highlight a growing preference for searching for music based on emotional attributes rather than individual preferences or genres. The act of selecting music based on emotional states is important on both a universal and cultural level. This study seeks to employ machine learning-based methods to classify four different music genres using a minimal set of features. The objective is to facilitate the process of choosing Turkish music according to one’s mood. The classification methods employed include Decision Tree, Random Forest (RF), Support Vector Machines (SVM), and k-Nearest Neighbor, coupled with the Mutual Information (MI) feature selection algorithm. Experimental results reveal that, with all features considered in the dataset, RF achieved the highest accuracy at 0.8098. However, when the MI algorithm was applied, SVM exhibited the best accuracy at 0.8068. Considering both memory consumption and accuracy, the RF method emerges as a favorable choice for selecting Turkish music based on emotional states. This research not only advances our understanding of the interaction between music and emotions but also provides practical insights for individuals who want to shape their music according to their emotional preferences.