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To improve the surface properties of low-density wood, poplar wood was functionalized by laminating Al2O3impregnated paper onto poplar wood (Populus tomentosa Carr.) via unilateral surface compression. Bonding strength between Al2O3impregnated paper and wood reached up to 3.08 MPa, meeting commercial grade I requirements for impregnated paper laminated wood flooring. A cross-linked structure between Al2O3impregnated paper and wood was formed without visible cracks or other defects. Density of the functionalized wood surface increased remarkably and the surface hardness was significantly improved, surpassing that of hardwoods for wood flooring. The functionalized wood surface also exhibited high wear resistance, which reached to the specification for commercial grade I impregnated paper laminated wood flooring. Additionally, the water resistance of the functionalized wood surface was significantly improved through lamination with Al2O3impregnated paper. The functionalized wood demonstrated high applicability for wood flooring.

Screen-printed copper electrodes have the potential to replace silver and lithium electrodes in printed batteries and sensors owing to the abundance of copper, its competitive electrical properties, and the low cost of raw materials. Herein, copper microparticle-glycerol-based inks were screen-printed onto paper to develop highly conductive electrodes. The conductivity and particle connectivity enhancement of screen-printed electrodes are the main research topics. These parameters translate to usability including increased sensitivity for sensor applications and reduced resistivity for battery electrode applications. CuO nanoparticles of 50 nm were deposited onto the electrodes at a concentration of 1 μl/cm2, which led to a 4-fold decrease in sheet resistivity from 200 to 50 Ω/m2. The increased connectivity and formation of new channels due to the addition of nanoparticles were visualised via field emission scanning electron microscopy. The CuO nanoparticles were developed via a hybrid approach incorporating wet chemistry for high yield and laser ablation for colloidal conductivity and Zeta potential enhancement which reached up to −45 mV. An optimal screen-printing viscosity of 62 mPa s was achieved through a precise 1.95:1 mass ratio of Cu microparticles to glycerol. Heat treatment at 100 °C after screen-printing enhanced particle connectivity by reducing glycerol content in the ink.

Reducing large scale of insulating wood paper usage in electric power systems is critical for decarbonizing and achieving neat-zero emissions to address climate change. This requires low-carbon substitutes with excellent electrical insulating properties, high mechanical strength, and heat resistance. Herein, we proposed a feasible way to fabricate low-ash content bamboo paper through hydrochloric acid and magnesium salt processing. The monovalent cation contents are substantially reduced by replacement reaction; meanwhile, impurities, such as hemicellulose and lignin, being hydrolyzed, contributing to a higher crystallinity. The purified bamboo paper demonstrates both high mechanical strength, great thermal stability, and improved impregnation performance. Moreover, the fabricated epoxy/bamboo paper composites exhibit high electrical strength and low dielectric loss under power frequency, making it a comparable substitute for traditional insulating wood paper.

The a ging of paper insulation in a transformer produces $\text{H}_{{2}}\text{O}$ molecules, which ultimately gets released into the oil. Reduced dielectric strength and increased conductivity are the consequences of moisture in insulation. At high temperature, the two main guiding factors that cause dielectric relaxation inside an insulation are electrical polarization and dc conductivity. Polarization and conductivity at high temperature are often difficult to segregate from one another. In the present work, moisture present inside transformer oil-paper insulation is estimated to study its effect on dielectric polarization and conductivity at different operating temperatures. Analysis at various complex planes including complex permittivity, complex susceptibility, complex conductivity, and complex dielectric modulus has been proposed to assess different relaxation distribution processes taking place inside the insulation with varying operating temperature.

An expensive power system component, transformers play a crucial role in power systems. Among the parts of transformers whose health status may affect their performance is oil-impregnated paper (OIP) bushings. Therefore, OIP bushings must be monitored to ensure safe transformer operation. It is important to note that moisture is one of the factors that can damage the OIP bushing. Therefore, effective evaluation of moisture in OIP bushings is crucial to ensure the safe operation of power systems. Previous studies have revealed, however, that the insulation’s aging can cause inaccurate moisture level predictions. Consequently, OIP bushing aging should be considered when estimating moisture levels. In recent years, the frequency domain spectroscopy (FDS) technique has been widely used to evaluate the insulation conditions of OIPs. This study introduced a novel approach to evaluate the insulation conditions of OIP bushings based on the FDS results. Twenty-three sets of oil-paper samples with different insulation conditions were selected. Moreover, eight features are introduced to extract from $\text {tan}\delta -{f}$ curves of OIP samples. Using the values of eight extracted features and the regression analysis, a database containing values of eight features and their corresponding insulation conditions was established. A novel technique was proposed based on the triangle’s area similarity-sector’s area similarity (TS-SS) to predict the moisture content and aging degree of OIP bushings. The verification results showed that the average relative error of moisture level and aging degree predictions is 5.57% and 7.32%, respectively. Therefore, the introduced method could be used to evaluate the insulation conditions.

Purpose: This study aims to map the conceptual structure and evolution of the recent scientific literature published in marketing journals to identify the areas of interest and potential future research directions. Design/methodology/approach: The 100 most influential marketing academic papers published between 2018 and 2022 were identified and scrutinized through a bibliometric analysis. Findings: The findings further upheld the critical role of emerging technologies such as Blockchain in marketing and identified artificial intelligence and live streaming as emerging trends, reinforcing the importance of data-driven marketing in the discipline. Research limitations/implications: The data collection included only the 100 most cited documents between 2018 and 2022, and data were limited only to Scopus database and restrained to the Scopus-indexed marketing journals. Moreover, documents were selected based on the number of citations. Nevertheless, the data set may still provide significant insight into the marketing field. Practical implications: Influential authors, papers and journals identified in this study will facilitate future literature searches and scientific dissemination in the field. This study makes an essential contribution to the marketing literature by identifying hot topics and suggesting future research themes. Also, the important role of emerging technologies and the shift of marketing toward a more data-driven approach will have significant practical implications for marketers. Originality/value: To the best of the authors’ knowledge, this is the first comprehensive study offering a general overview of the leading trends and researchers in marketing state-of-the-art research.

AbstractTo help students confront pseudoscientific claims and misinformation in their everyday lives, it is important to develop the epistemic practices of scientists in the classroom. Many of these practices can be illuminated by challenging students to read primary source literature. This article outlines a lesson that has sophomore students reading review and research articles on a pertinent topic. While reading, students think like scientists to extract main ideas, analyze bias, and justify claims with evidence. The papers themselves, as well as the steps employed in the classroom to support students in reading them, highlight the fact that scientists regularly utilize statistics and data, develop a strong theoretical knowledge-base prior to forming conclusions, and seek out critique of their work. Students read these papers collaboratively, working together with one another and with upperclassmen peer mentors to engage in scientific discourse and solidify their understanding of the process of science. This experience challenges students to think as scientists do and provides them with a strong foundation for scientific literacy, preparing them to make more informed decisions about their futures.

For oil-immersed power equipment, the accumulation of cellulose impurities in oil-paper insulation poses a significant problem. To address this issue, this study investigates the migration and bridging characteristics of cellulose impurities in oil-paper insulation under dc voltage. A kinetic analysis model is developed to simulate the impurity trajectories and quantitative analysis of speed, offset distance, and other parameters of cellulose impurities. The results indicate the motion cycle of cellulose impurity under the slightly uneven dc electric field consists of lifting, upward, and downward stages, with a maximum speed of over 102 mm/s and maximum acceleration of over 102 m/s2. During the lifting stage, particle velocity grows quickly and then slows, while during the downward stage velocity increases sharply to a maximum and then gradually decreases. The horizontal offset distance decreases with increased motion cycles. The cellulose impurities departed from the sphere electrode and the insulating paper surface migrate in opposite directions along their respective trajectories. As they gradually approach each other, these impurities undergo collisions and exchange charges, and eventually form a heap-like bridge. Results of this study can guide the development of better insulation materials for high-voltage electrical equipment and aid in the removal of impurities.

The current study is related to fabrication of point-of-care molecularly imprinted paper-based analytical devices, specifically related to ovarian cancer early stage detection. The task involves creating a paper coated with silver nanoparticles (AgNPs) that can be used as a transducer via surface enhanced Raman spectroscopy (SERS) to detect the threshold level of the biomarker lysophosphatidic acid (LPA) as a template molecule to diagnose ovarian cancer. MIPs are synthetic receptors designed for a targeted molecule which are prepared from polymers in the presence of target such as small molecules, proteins or cells etc. Removal of the template results in cavities which are structurally and electrostatically complementary to the template molecule. The molecularly imprinted polymer (MIP) layer was anchored on vinyl trimethoxy silane modified-paper, which served as a detector by hydrolytically modifying the paper surface with vinyl trimethoxy silane. To detect LPA in serum samples for ovarian cancer, MIP-paper based on SERS was developed. Patients with benign ovarian tumors had an LPA level of 7.73 μM whereas those with ovarian cancer have a level of 16.99 μM. A healthy person's LPA level is 2.92 μM. Consequently, the rise in LPA levels may aid in the early detection of ovarian cancer. The study refers to the use of a point of care device to diagnose ovarian cancer early, which should be simple, effective, and cost-effective. The analytical tool in the study is a sensor with high selectivity and sensitivity, quick assay times, and inexpensive costs. For LPA in serum, the binding constant of modified paper-based MIP ranges from 11.00 μM to 0.08 μM. The amalgamation of nanoparticles on 2D-paper with MIP have lead to develop sensor which can effectively select LPA in untreated real samples like serum.

Abstract: Paper substrates possessing features ranging from hydrophobic to oxygen-barrier functional properties are gaining great attention recently due to the global ban on single-use plastics as well as the compulsion to avoid nonbiodegradable polymer packing. In this work, hydrophobic silica carriers are processed first through a direct physical impregnation of silicone oil in various amounts into the 20-nm sized silica nanoparticles and subsequently analyzed for the progressive changes in the surface hydrophobicity by water contact angle measurements. The hydrophobic nano-silica was also systematically analyzed by XRD, TGA, FTIR, SEM, and TEM and the results are presented. It was found that the nano-silica with the bulk BET surface area of 157 m2/g can accommodate 2.5 g of silicone oil per gram of silica, finally resulting in hydrophobic silica with a maximum contact angle of 139°. Later, this hydrophobic nano-silica was dispersed in a polymethylmethacrylate (PMMA) matrix and a coating formulation was prepared to develop water-repellent self-cleaning functional coatings on eco-friendly paper substrates. While applied as topcoats on paper substrates, the hydrophobic silica-PMMA gets embedded into the porous fibrous cellulose network and converts it into an impressive water-repellent packaging material with a contact angle of about 142°. This facile inorganic–organic hybrid topcoat strategy was successfully applied on the fibrous cellulose sludge waste produced by the paper mills to produce lightweight, water/moisture resistance packing material for circular economy. Graphical abstract:

This article aims at developing a copula model for investigating the dependence structure between normalized energy intensity of oil $(\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}})$ and normalized energy intensity of paper ($\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}).$ The normalized energy index is a quantity that is directly related to the energy dissipated during a fault inside an oil filled transformer and reactor. The $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ and $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ are derived from real time dissolved gas analysis data of in-service transformer and reactors. Gumbel copula has been used for evaluating the conditional probabilities between the parameters. Results of the copula model indicate that for an increment of 0.5 kJ/kL in $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ there is an increment in $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ between 1.0 and 2.2 kJ/kL. It demonstrates the importance of considering $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ in addition to $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ for assessing the fault severity and evaluating the internal condition of liquid and solid insulation of transformer and reactor. Subsequently, the health index of transformers and reactors considering oil parameters, $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ and $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ have been evaluated thus making it an unique nature of study. Additionally, a range of values of $\mathbf{NE}{\mathbf{I}}_{\mathbf{oil}}$ and $\mathbf{NE}{\mathbf{I}}_{\mathbf{paper}}$ has been determined which can be used directly for future study. The study undertaken will help in monitoring, maintenance, and conditioning assessment of the equipment based on NEI values, thereby saving unprecedented failure of in-service transformers and reactors.

Bibliometric analysis of highly cited papers facilitates researchers in formulating strategic research possibilities and addressing gaps in specific domains. In this context, a bibliometric analysis was conducted to identify published papers on “oral mucosal lesions in COVID-19” within medical literature.

Academia is already witnessing the abuse of authorship in papers with text generated by large language models (LLMs) such as ChatGPT.LLM‐generated text is testing the limits of publishing ethics as we traditionally know it.We alert the community to imminent risks of LLM technologies, like ChatGPT, for amplifying the predatory publishing ‘industry’.The abuse of ChatGPT for the paper mill industry cannot be over‐emphasized.Detection of LLM‐generated text is the responsibility of editors and journals/publishers.

The pulp and paper industry is an important contributor to global greenhouse gas emissions1,2. Country-specific strategies are essential for the industry to achieve net-zero emissions by 2050, given its vast heterogeneities across countries3,4. Here we develop a comprehensive bottom-up assessment of net greenhouse gas emissions of the domestic paper-related sectors for 30 major countries from 1961 to 2019—about 3.2% of global anthropogenic greenhouse gas emissions from the same period5—and explore mitigation strategies through 2,160 scenarios covering key factors. Our results show substantial differences across countries in terms of historical emissions evolution trends and structure. All countries can achieve net-zero emissions for their pulp and paper industry by 2050, with a single measure for most developed countries and several measures for most developing countries. Except for energy-efficiency improvement and energy-system decarbonization, tropical developing countries with abundant forest resources should give priority to sustainable forest management, whereas other developing countries should pay more attention to enhancing methane capture rate and reducing recycling. These insights are crucial for developing net-zero strategies tailored to each country and achieving net-zero emissions by 2050 for the pulp and paper industry.

Decision prediction based on neurophysiological signals is of great application value in many real‐life situations, especially in human–AI collaboration or counteraction. Single‐trial analysis of electroencephalogram (EEG) signals is a very valuable step in the development of an online decision‐prediction system. However, previous EEG‐based decision‐prediction methods focused mainly on averaged EEG signals of all decision‐making trials to predict an individual's general decision tendency (e.g., risk seeking or aversion) over a period rather than on a specific decision response in a single trial. In the present study, we used a rock–paper–scissors game, which is a common multichoice decision‐making task, to explore how to predict participants' single‐trial choice with EEG signals. Forty participants, comprising 20 females and 20 males, played the game with a computer player for 330 trials. Considering that the decision‐making process of this game involves multiple brain regions and neural networks, we proposed a new algorithm named common spatial pattern‐attractor metagene (CSP‐AM) to extract CSP features from different frequency bands of EEG signals that occurred during decision making. The results showed that a multilayer perceptron classifier achieved an accuracy significantly exceeding the chance level among 88.57% (31 of 35) of participants, verifying the classification ability of CSP features in multichoice decision‐making prediction. We believe that the CSP‐AM algorithm could be used in the development of proactive AI systems.

Although the current transformer (CT) is an essential component in the electrical power system and its failure may result in serious consequences, there are no accelerated aging tests for this equipment prescribed by technical standards. Life estimation for this equipment is generally made based on field experience, something that cannot be done for new models and/or new manufacturers. In this work, experimental results of life tests performed on mockups, representing high-voltage CTs with oil-impregnated paper insulation, are presented and discussed. The analysis is based on the application of a multistress model, which combines the Montsinger rule and inverse power law. The proposed approach considers the existence of threshold values for electrical and thermal stresses, below them, electrical and thermal degradation is negligible. An order of magnitude for the electrical stress threshold value ( ${E}_{{0}}$ ) and for the electrical aging exponent ( ${n}$ ) is obtained from the application of the test results to the model used in this investigation.

The copper sulfide (Cu $_{{2}}\text{S}$ ) generated by the reaction of corrosive sulfur, as occurs in transformer oil and copper windings, is an important factor that induces partial discharge (PD) in power transformers. In this article, the development process and influence trend of PD under Cu $_{{2}}\text{S}$ deposition were studied. The process images of PD caused by Cu $_{{2}}\text{S}$ deposition were obtained through the oil-paper insulation charge transfer model applied to plate–plate electrodes. The law of PD varies when the polarity of the voltage excitation applied to the upper electrode plate varies. Charge build-up will be greater when applying a positive voltage to top plate, whereas reverse discharge will occur with a negative voltage applied. Based on these changes in charge density and electric field strength during PD, the influence of the thickness, width, and spacing of the Cu $_{{2}}\text{S}$ deposition was determined. The increase in deposition thickness increases the intensity of PD development, and the increase in width is conducive to greater diffusion of charges. If the distance is too small, it delays the development of discharge in multiple deposits. This research reveals the physical mechanisms underlying PD caused by Cu $_{{2}}\text{S}$ deposition.

The moisture intrusion of high-voltage oil-immersed paper (OIP) bushing may cause insulation deterioration. Polarization and depolarization current (PDC) technology is an effective and nondestructive method to evaluate the moisture state of OIP bushings’ insulation. However, the current PDC assessment methods are difficult to evaluate the nonuniform moisture status of OIP bushings. To address this issue, this article studies the PDC characteristics of OIP bushings under radial nonuniform moisture distribution. Initially, by combining with the laboratory PDC measurements and finite element method (FEM) simulation, the influence laws of the dampest insulation layer’s moisture content and position on the overall PDC curve of OIP bushings are explored. The results show that the moisture content and position of the dampest insulation layer have a significant influence on the overall polarization current curve. The peak value, steady-state value, and integral value of the polarization current are negatively correlated to the position and positively correlated to the moisture content of the dampest insulation layer. The moistest layer’s position of the radial nonuniformly damped bushing can be determined by polarization current integral difference under positive and negative PDC link-wire ways. This research provides the theoretical basis and technical support for the nonuniform moisture state evaluation of OIP bushing insulation.

Authors submitted over 2,800 original and revised manuscripts in 2023 for possible publication in these Transactions and IEEE Industry Applications Magazine. This Special Feature is offered to recognize the people who volunteered their time and expertise to evaluate those manuscrips and to make the recommendations that determined which papers would be published. Their efforts are greatly appreciated. The names, affiliations, and countries listed below are taken from the user profiles stored in ScholarOne Manuscripts. Some of the entries have been edited for consistency in spelling, length and/or capitalization. We apologize for any omissions or editing errors.

Ecofriendly solution processed organic transistors were demonstrated on a biodegradable paper substrate for −5-V operation. Blend of solution processed organic semiconductor TIPS-pentacene and polystyr- ene (PS) polymer was utilized to form the active layer, along with a natural protein, i.e., gelatin as a primary gate dielectric, both of which offer eco-friendliness from proc- ess and material aspects. Fabricated organic transistors showed excellent transistor behavior for p-channel opera- tion with a maximum process transconductance value of 15 nF/ $\text{V}\cdot \text{s}$ leading to the mobility of 2.3 cm2/ $\text{V}\cdot \text{s}$ obtained from capacitance density derived at 1 kHz. The average threshold voltage of −0.7 V suitable for low-voltage opera- tion was achieved along with decent ON/OFF current ratio of $\sim 10^{{4}}$ . High electrical stability was demonstrated through repeatability of transfer characteristics and bias-stress measurements. Excellent environmental stability in normal ambient was observed up to seven weeks. These devices showed circuit applicability with decent switching in resis- tive load inverters and good sensitivity to ultraviolet (UV) light, making them a suitable candidate for exploration for multifunctional and disposable application.

This communication presents a wide bandpass frequency-selective surface (FSS) based on aramid-paper honeycomb sandwich structures. The proposed FSS consists of a 2-D planar array of hexagonal rings and a 3-D honeycomb array of stepped impedance slotlines. The 2-D structures are constructed on printed circuit board (PCB); meanwhile, the 3-D structures are achieved with printed silver paste circuit. Based on the even- and odd-mode analysis method, equivalent circuit models are extracted and analyzed to explain the operating principles of the proposed structures. The FSS with a thickness of 16.7 mm achieves a wide passband of 2.90–9.55 GHz (106.8% fractional bandwidth). An FSS sample was fabricated and measured to verify the design strategies.

For a century, scientists pondered whether bird flight evolved by animals gliding down from trees or by creatures running and flapping from the ground up. A landmark 1974 paper reset the debate to focus on the evolution of the flight stroke instead.

Frequency domain spectroscopy (FDS) is a common nondestructive test method for insulation diagnosis of a transformer. Rapid and accurate testing can help improve the efficiency of FDS. However, the long test duration of conventional FDS and the unsatisfactory accuracy of existing accelerated FDS methods limit the application of insulation conditions of transformers. To tackle these problems, a new testing method named sFDS is proposed, aiming to achieve rapid and accurate testing. The proposed sFDS consists of two main parts to achieve the goal: first, the test duration is reduced by using sawtooth and regression analysis. Second, to ensure test accuracy, a multidomain signal accurate processing technique is proposed. Specifically, first, a filtering algorithm is used to isolate the noise. Second, the phase correction is used to improve the precision of time-frequency conversion. Third, the line interpolation method is utilized to accurately extract spectral data to compute dielectric loss and complex capacitance. To verify the practicality of sFDS, an sFDS test platform is built and compared with existing accelerated FDS techniques through practical experiments. The results indicate that sFDS performs superiorly in rapidity and accuracy. Meanwhile, sFDS has the potential to become a general method for evaluating more electrical objects.

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The field of Cardio-Oncology has grown significantly, especially during the last decade. While awareness of cardiotoxicity due to cancer disease and/or therapies has greatly increased, much of the attention has focused on myocardial systolic disfunction and heart failure. However, coronary and structural heart disease are also a common issue in cancer patients and encompass the full spectrum of cardiotoxicity. While invasive percutaneous or surgical intervention, either is often needed or considered in cancer patients, limited evidence or guidelines are available for dealing with coronary or structural heart disease. The Society for Cardiovascular Angiography and Interventions consensus document published in 2016 is the most comprehensive document regarding this particular issue, but relevant evidence has emerged since, which render some of its considerations outdated. In addition to that, the recent 2022 ESC Guidelines on Cardio-Oncology only briefly discuss this topic.

Launched in 1952, the Transactions on Reliability is one of the oldest publications in the IEEE portfolio. Many papers published there have become foundational with many hundreds of citations. A listing and summary of the 10 most highly cited papers is presented.