Search Results (41,874)

One of the major challenges in QLED research is improving the stability of the devices. In this study, we fabricated all inorganic quantum-dot light emitting diodes (QLEDs) using hafnium oxide (HfO_x) as the hole transport layer (HTL), a material commonly used for insulator. Oxygen vacancies in HfO_x create defect states below the Fermi level, providing a pathway for hole injection. The concentration of these oxygen vacancies can be controlled by the annealing temperature. We optimized the all-inorganic QLEDs with HfO_x as the HTL by changing the annealing temperature. The optimized QLEDs with HfO_x as the HTL showed a maximum luminance and current efficiency of 66,258 cd/m² and 9.7 cd/A, respectively. The fabricated all-inorganic QLEDs exhibited remarkable stability, particularly when compared to devices using organic materials for the HTL. Under extended storage in ambient conditions, the all-inorganic device demonstrated a significantly enhanced operating lifetime (T₅₀) of 5.5 h, which is 11 times longer than that of QLEDs using an organic HTL. These results indicate that the all-inorganic QLEDs structure, with ITO/MoO₃/HfO_x/QDs/ZnMgO/Al, exhibits superior stability compared to organic-inorganic hybrid QLEDs. Full article

The South American fruit fly Anastrepha fraterculus (Wiedmann) has a vast range extending from northern Mexico, through Central America, to South America where it is an extremely polyphagous pest of wild and cultivated fruits. It is a complex of cryptic species currently composed of eight recognised morphotypes: “Mexican”, “Venezuelan”, “Andean”, “Peruvian”, “Ecuadorian”, and the three Brazilian morphotypes “Brazilian-1”, “Brazilian-2”, and “Brazilian-3”. Molecular markers that can identify the member species of the complex are crucial for the implementation of effective pest control measures, such as the sterile insect technique. The object of this study was to evaluate the use of the internal transcribed spacer 2 (ITS2) sequence for discriminating several members of the A. fraterculus cryptic species complex (Mexican, Peruvian, and Brazilian-1) and a related species, Anastrepha schultzi Blanchard. The analysis highlighted significant genetic differentiation between the evaluated morphotypes, allowed their discrimination within the A. fraterculus cryptic species complex, and provided new insights into their genetic relationships. The ITS2 marker provides a basis for the development of taxonomic keys for the discrimination of the cryptic taxa within the A. fraterculus cryptic species complex. ITS2 also represents an important marker for the poorly studied species A. schultzi. Full article

The continuous expansion of the vehicle fleet contributes to escalating emissions, with the transportation sector accounting for approximately 21% of CO₂ emissions, based on 2023 data. Focused on reducing emissions and reliance on fossil fuels, the study observes the shift from internal combustion vehicles to electric and hybrid models since 2017. Despite advancements, these vehicles still lack optimal efficiency and suffer from limited range, deterring potential buyers. This article aims to evaluate the range-extending technologies for electric vehicles, emphasizing efficiency, low pollution, and integration compatibility. An algorithm incorporating equations representing mechanical or electrical component curves is developed for Extended-Range Electric Vehicles, facilitating insight into potential range extender behavior. The core objectives of this study involve optimizing the entire powertrain system to ensure peak efficiency. Experimental tests demonstrate that integrating an auxiliary power unit enhances range, with an internal combustion engine generator configuration extending the travel distance by 35.35% at a constant speed. Moreover, with the use of an Equivalent Consumption Minimization Strategy control, the distance traveled increases up to 39.28% on standard driving cycles. The proposed methodology, validated through practical implementations, allows for comprehensive energy analyses, providing a precise understanding of vehicle platform performance with integrated range extenders. Full article

In order to improve the detection range and imaging resolution of dipole remote detection logging, an optimal nonlinear frequency modulation (ONLFM) excitation method is proposed in this paper. In this method, the optimal waveform model of the sound source is designed with objective functions of SNR and resolution to obtain the highest resolution under the condition of the required SNR. This optimal model is a multi-constraint optimization problem, and the simulated annealing method has been used to solve it. Solving the optimal model can obtain the optimal spectrum, and the ONLFM waveform can be designed by using the stationary phase principle. Compared with the electric pulse sound source used in traditional technology, this ONLFM sound source can improve the energy and extend the frequency band range of the reflected wave, which can provide the higher resolution and SNR. The simulation results show that the ONLFM sound source can effectively improve the SNR and resolution of the reflected wave, and the detection range and imaging resolution of dipole shear wave remote detection will be improved. Full article

The project involved applying gamification methodology in the teaching of engineering and materials science through the creation of a board game. This game facilitated the active study of the subject, encouraged self-assessment, and developed general competencies such as teamwork and interdisciplinary collaboration, as well as specific competencies in the structure, description, and characterization of materials and manufacturing processes. During the course, students created questions and tests for the game, which were reviewed by the faculty and used to print and manufacture the game. Students utilized the game to study actively, interact with their peers, and reflect on the course topics. There are plans to extend the project to more specialized subjects within the Materials Engineering degree program. The creation of these contents promotes active student learning, reinforces their knowledge, enhances information retention, and motivates students through gamification. Full article

Fluoride treatment of ZSM-5 zeolite can effectively adjust surface acidity and generate a secondary pore structure. In this study, a series of modified nano-HZSM-5 zeolites were prepared by NH₄F-HF mixed solution treatment and applied to the selective conversion of bioethanol to propylene at 500 °C, atmospheric pressure, and a WHSV of 10 h⁻¹. The results showed that NH₄F-HF modification weakened the surface acidity of nano-HZSM-5 zeolites, thus inhibiting coke formation. Additionally, the mesopores in the nano-HZSM-5 zeolites increased after NH₄F-HF treatment, thereby enhancing the mass transfer rate and improving the coke-resistance ability. The NH₄F-HF mixed solution modification significantly improved the stability of nano-HZSM-5 zeolites in catalyzing bioethanol to propylene and greatly extended the working life of nano-HZSM-5 zeolites. It can be seen from the characterization of the deactivated catalysts that coke deposition and weakening of acidity may be the key factors for catalyst deactivation. Full article

Objectives: To review the evidence on the clinical value of magnetic source imaging (MSI) in patients with refractory focal epilepsy without evidence for an epileptogenic lesion on magnetic resonance imaging (“MRI-negative” or “non-lesional MRI”). Methods: We conducted a systematic literature search on PUBMED, which was extended by researchrabbit.ai using predefined criteria to identify studies that applied MSI in MRI-negative patients with epilepsy. We extracted data on patient characteristics, MSI methods, localization results, surgical outcomes, and correlation with other modalities. Results: We included 23 studies with a total of 512 non-lesional epilepsy patients who underwent MSI. Most studies used equivalent current dipole (ECD) models to estimate the sources of interictal epileptic discharges (IEDs). MEG detected IEDs in 32–100% of patients. MSI results were concordant with other modalities, such as EEG, PET, and SPECT, in 3892% of cases. If MSI concordant surgery was performed, 52–89% of patients achieved seizure freedom. MSI contributed to the decision-making process in 28–75% of cases and altered the surgical plan in 5–33% of cases. Conclusions: MSI is a valuable diagnostic tool for MRI-negative patients with epilepsy, as it can detect and localize IEDs with high accuracy and sensitivity, and provides useful information for surgical planning and predicts outcomes. MSI can also complement and refine the results of other modalities, such as EEG and PET, and optimize the use of invasive recordings. MSI should be considered as part of the presurgical evaluation, especially in patients with non-lesional refractory epilepsy. Full article

Background: Despite its global eradication in 1977, smallpox remains a concern owing to its potential as a biological agent, thereby prompting the ongoing development and utilization of its vaccine. Vaccination with the Vaccinia virus induces immunity against variola virus, the causative agent of smallpox; however, this immunity does not extend to viruses of different genera within the Poxviridae family. In this study, we aimed to assess the efficacy of an enzyme-linked immunosorbent assay (ELISA) method utilizing Vaccinia virus and recombinant A27L antigen for detecting antibodies against smallpox. Methods. An analysis of the serum from 20 individuals pre- and post-vaccination with the CJ strain (CJ50300) revealed neutralizing antibodies, which were confirmed using the plaque reduction neutralization test (PRNT). The ELISA method, validated with a PRNT₅₀ cut-off value of >4, exhibited a sensitivity and specificity of >95% and was particularly reactive with the inactivated virus. Furthermore, adherence to the smallpox vaccination policy revealed significant differences in Orthopoxvirus antibody levels among 300 individuals of different age groups. These findings highlight the reliability and efficacy of the ELISA method in detecting post-vaccination antibodies and contribute significantly to diagnostic methods to prepare for potential smallpox resurgence and bioterrorism threats. Full article

This work is devoted to the investigation of dielectric permittivity which is influenced by electronic, ionic, and dipolar polarization mechanisms, contributing to the material’s capacity to store electrical energy. In this study, an extended dataset of 86 polymers was analyzed, and two quantitative structure–property relationship (QSPR) models were developed to predict dielectric permittivity. From an initial set of 1273 descriptors, the most relevant ones were selected using a genetic algorithm, and machine learning models were built using the Gradient Boosting Regressor (GBR). In contrast to Multiple Linear Regression (MLR)- and Partial Least Squares (PLS)-based models, the gradient boosting models excel in handling nonlinear relationships and multicollinearity, iteratively optimizing decision trees to improve accuracy without overfitting. The developed GBR models showed high R² coefficients of 0.938 and 0.822, for the training and test sets, respectively. An Accumulated Local Effect (ALE) technique was applied to assess the relationship between the selected descriptors—eight for the GB_A model and six for the GB_B model, and their impact on target property. ALE analysis revealed that descriptors such as TDB09m had a strong positive effect on permittivity, while MLOGP2 showed a negative effect. These results highlight the effectiveness of the GBR approach in predicting the dielectric properties of polymers, offering improved accuracy and interpretability. Full article

Bioresorbable magnesium-metal vascular stents are gaining popularity due to their biodegradable nature and good biological and mechanical properties. They are also suitable candidate materials for biodegradable stents. Due to the rapid degradation rate of Mg metal vascular scaffolds, a Mg/Zn bilayer composite was formed by a number of means, such as magnetron sputtering and physical vapor deposition, thus delaying the degradation time of the Mg metal vascular scaffolds while providing good radial support for the stenotic vessels. However, the interlaminar compounds at the metal interface have an essential impact on the mechanical properties of the bi-material interface, especially the cracking and delamination of the Mg matrix Zn coating vascular stent in the radially expanded process layer. Intermetallic compounds (IMCs) are commonly found in dual-layer composites, such as Mg/Zn composites and multi-layer structures. They are frequently overlooked in simulations aiming to predict mechanical properties. This paper analyses the interfacial failure processes and evolutionary mechanisms of interfacial fracture mechanics of a Mg/Zn interface with an intermetallic compound layer between coated Zn and Mg matrix metallic vascular stents. The simulation results show that the fracture mode in the Mg/Zn interface with an intermetallic compound involves typical ductile fracture under static tensile conditions. The dislocation line defects mainly occur on the side of the Mg, which induces the Mg/Zn interfacial crack to expand along the interface into the pure Mg. The stress intensity factor and the critical strain energy release rate decrease as the intermetallic compound layer’s thickness gradually increases, indicating that the intensity of stress and the force of the crack extending and expanding along the crack tip are weakened. The presence of intermetallic compounds at the interface can significantly strengthen the mechanical properties of the material interface and alleviate the crack propagation between the interfaces. Full article

We consider optimal designs for clinical trials when response variance depends on treatment and covariates are included in the response model. These designs are generalizations of Neyman allocation, and commonly employed in personalized medicine where external covariates linearly affect the response. Very often, these designs aim at maximizing the amount of information gathered but fail to assure ethical requirements. We analyze compound optimal designs that maximize a criterion weighting the amount of information and the reward of allocating the patients to the most effective/least risky treatment. We develop a general representation for static (a priori) allocation and propose a semidefinite programming (SDP) formulation to support their numerical computation. This setup is extended assuming the variance and the parameters of the response of all treatments are unknown and an adaptive sequential optimal design scheme is implemented and used for demonstration. Purely information theoretic designs for the same allocation have been addressed elsewhere, and we use them to support the techniques applied to compound designs. Full article

The pollination characteristics and flowering phenology of Calanthe sieboldii were evaluated to elucidate its reproductive characteristics and breeding systems. Field observations and artificial pollination experiments were conducted to study the pollination biology in Xuancheng City, Anhui Province. Meanwhile, gas chromatography–mass spectrometry (GC-MS) was employed to analyze the species’ volatile organic compounds (VOCs). Key findings include the following: (1) the flowering period extends from mid-April to mid-May, with a population-level flowering duration of 29 days in 2017, individual plant flowering averaging 20.22 days, and single flower longevity ranging from 12 to 23 days (mean = 19.30 days); (2) the species exhibits deceptive nectar guides devoid of nectar, indicating food-deceptive pollination, with Bombus sp. identified as its primary pollinator; (3) the pollinial–ovule ratio and hybridization index suggest a high level of self-compatibility without autonomous self-pollination, with no significant difference in pollination success between self- and outcross populations; (4) GC-MS analysis identified methyl benzoate and acacia-related compounds as the primary VOCs of C. sieboldii. These findings provide valuable insights into the conservation and sustainable management of orchids, particularly C. sieboldii. Full article

With the rapid development of the advanced electronic packaging field, the requirements for the connection between solder and Cu substrate are becoming increasingly stringent. Currently, the commonly used Ni-P diffusion barrier layer in the industry lacks long-term reliability, and its resistivity is higher than that of other substrates. This paper introduces the highly conductive metal element W to modify the binary Ni-P coating and prepares a ternary Ni-W-P coating through electrodeposition to improve this situation. The key parameters for the electrodeposition of ternary Ni-W-P are determined. The isothermal aging reaction of Ni-W-P with Sn-Bi solder at 100 °C was studied, and the results showed that, compared to the conventional Ni-P coating, the Ni-W-P barrier coating with higher W content has a much longer lifespan as a barrier layer and exhibits significantly better electrical conductivity. Additionally, the reaction mechanism between Ni-W-P and the Sn-Bi solder is proposed. This research presents a promising advancement in the development of barrier layers for electronic packaging, potentially leading to more reliable and efficient electronic devices. Introducing tungsten into the Ni-P matrix not only extends the lifespan of the coating but also enhances its electrical performance, making it a valuable innovation for applications requiring high conductivity and durability. This study could guide further investigations into the application of ternary coatings in various electronic components, paving the way for improved designs and materials in the semiconductor industry. Full article

This paper offers a historical review of the evolution of mathematical methods in economics, tracing their development from the earliest attempts in the 18th century to the sophisticated models of the late 20th century. The study begins by examining the initial integration of mathematical techniques into economic thought, highlighting key milestones that shaped the field. Symmetry concepts are naturally embedded in many of these mathematical frameworks, particularly in the balance and equilibrium found in economic models. Symmetry in economics often reflects proportional relationships and equilibrium conditions that are central to both micro- and macroeconomic analyses. Then, the paper elaborates on the progression of economic growth models, including the foundational Solow–Swan model, which introduced the concept of technological progress (knowledge) as a key factor influencing growth. The review also encompasses the Lucas growth model and the Mankiw–Romer–Weil model, both of which incorporate human capital into the growth equation, highlighting its importance in driving economic development. Finally, the paper addresses the Nonneman–Vanhoudt model, which extends the analysis of growth by integrating multiple types of capital, providing a more comprehensive framework for understanding economic dynamics. By documenting these developments, the paper demonstrates the significant role that mathematical modeling has played in advancing economic theory, providing tools to quantitatively analyze complex economic phenomena and driving the discipline towards greater analytical precision and rigor. This analysis emphasizes how symmetry principles, such as balance between inputs and outputs, equilibrium in supply and demand, and proportionality in growth models, underpin many economic theories. Full article

Many countries have committed to carbon reductions and carbon neutrality targets in response to the Paris Agreement and Sustainable Development Goals (SDGs). With economic development, the transportation sector has become a major source of carbon emissions. In China, transport infrastructure—as an important carrier of the transportation sector—is important for controlling carbon emissions from this sector and achieving carbon neutrality and the targets of the SDGs. However, most studies have focused on transport vehicles and neglected transport infrastructure. Furthermore, the influences of collusive behavior and digital control technologies on the carbon reduction process have not yet been examined. This study aimed to analyze the influencing factors in the carbon reduction process in transport infrastructure. This study uses partial least squares structural equation modeling (PLS-SEM) to analyze the factors influencing carbon reductions in transport infrastructure and the mediating roles of collusive behavior and digital control technologies in the carbon reduction process. Low-carbon technologies, digital control technologies, and collusive behavior have positive direct and indirect effects on the carbon reduction effect. Digital control technologies have a positive effect on low-carbon regimes. Low-carbon technologies influence carbon reduction effects. Collusive behavior plays a mediating role in low-carbon regimes. Finally, the industrial structure influences carbon reduction effects. This study extends China’s carbon emission research in the transportation sector by focusing on infrastructure rather than vehicles. Additionally, this is the first study to incorporate collusive behavior and digital control technologies into the framework to analyze the impact of carbon reductions. The study also employs PLS-SEM to explore effective carbon reduction paths. The findings provide decision-making support for controlling carbon reductions in transport infrastructure. Full article