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There is a relative lack of research on the development of creepage discharge in aged oil-paper insulation subjected to AC-DC combined voltage in converter transformers. In this study, based on the physical and chemical properties of oil-paper, we propose a sphere-plate electrode model to study the creepage discharge parameters and characteristic spectra of aged oil-paper subjected to AC-DC combined voltage. The results show that the creepage discharge inception voltage of aged oil-paper is related to the AC voltage component of the AC-DC combined voltage. However, when the DC voltage component is 60 kV, the flashover phenomenon was found to occur in one of the severely aged samples before the AC voltage was applied. Despite being subjected to the same DC voltage, the flashover phenomenon did not occur in three other samples aged to different degrees. Large-amplitude discharges were found to appear earlier in the severely aged samples. At the same creepage discharge stage, as the aging time of the oil-paper increased, the number of large-amplitude discharges was found to rapidly increase, and the time interval between adjacent discharges was found to gradually decrease. At each stage of the creepage discharge, the small-amplitude discharge has a “hump” shaped distribution. The larger the DC voltage component, the shorter the endurance time of aged oil-paper, and the more severe the damage to the oil-paper. The DC voltage component was found to have an accelerating effect on the development of creepage discharge in aged oil-paper insulation.

This paper demonstrates a simple-in-struct- ure, cost-effective, and environment-friendly Microfluidic Paper-based Analytical Device for Microbial Biofuel Cell ( $\mu $ PAD-MBFC). It consists of a microchannel with biofuel cell (Escherichia.Coli) and an oxidant (aerated tap water) flowing co-parallelly over Multiwalled Carbon Nanotube (MWCNT)-based Bucky Paper (BP) electrodes using a self-capillary and co-laminar flow mechanism. The electrochemical studies, such as open circuit potential (OCP) and polarization were evaluated using a potentiostat. Various volumetric bacterial studies were also carried out to find out the best suitable optimal bacterial volume. Subsequently, the morphological and detailed element composition study of electrode surface was performed using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) techniques. This well-designed portable $\mu $ PAD-MBFC yields a maximum power density of 4 $\mu \text{W}$ /cm2 ( $20~\mu \text{A}$ /cm2) at 0.405 V over $200~\mu \text{l}$ of culture and leveraging to its long-lasting potential to operate miniaturized microelectronics sensors and portable devices.

This paper presents a broadband, simple, re-useable and low-cost approach for noninvasive sweat monitoring using a passive microwave circuit and a cellulose filter paper as a superstrate. The proposed sensor is composed of filter paper with the ability to absorb the sample liquid under test (LUT) placed on top of a coplanar waveguide (CPW) transmission line. Various samples of sodium chloride (NaCl) solutions with concentrations in the range of 0.01-2 mol/L and models of artificial sweat are used to test the proposed sensor. The difference in transmission coefficient (S21) between dry and wet states is used to determine the concentrations of tested solutions in the band of 1-6 GHz. The sensor detects concentrations as low as 0.01 mol/L (0.58 g/L) and quantities as low as 137 μL with a maximum sensitivity of 46.7 dB/g/L. The proposed sensor presents a simple approach to sample and characterize liquids with enhanced sensitivity and consistent performance using microwave signals.

Background: Although some have noted that combining technical and marketing content is precarious, technical communication professionals are increasingly involved in content marketing, which includes the creation of white papers. Literature review: The little existing literature on white papers provides conflicting guidance about managing the combination of technical and marketing content. Both soft-sell and hard-sell marketing approaches have been recommended. One source of such inconsistent guidance may be the lack of agreement about definitions. Research on print advertisements has described hard and soft selling as multidimensional rather than binary aspects of persuasive appeals. Research question: Which dimensions of hard- and soft-sell appeals are predominant in white papers? Research methodology: To complete our descriptive study, we collected a corpus of documents labeled as white papers in TechRepublic, and then selected and trained three raters to complete a series of judgments about dimensions of persuasive appeals in the corpus. We aggregated those ratings, calculating the mean and standard deviation for the dimensions to describe their distribution across the corpus. Results/discussion: Overall, hard-sell dimensions were more prevalent than soft-sell dimensions. However, the soft-sell category of “implicitness” was also dominant. Conclusion: Our results demonstrate the value of treating hard and soft selling as multidimensional, complementary, and combinatory marketing appeals that allow, for example, a single white paper to be both “subjective” (soft sell), and “precise” (hard sell), or both “creative” (soft sell) and “informative” (hard sell).

Insulated tubular busbar is a new type of current-carrying equipment with excellent performance. However, the research on this equipment is insufficient because of the short application and the lack of technical digestion, which has resulted in many accidents. In this paper, the full-scale model of epoxy-impregnated-paper insulated tubular busbar with bubble defects was designed and produced, its electrical breakdown process was investigated by withstand voltage test. In the experiment, the failure mode of breakdown caused by gas expansion was found for the first time. The research showed that the electrical-mechanical breakdown process could be divided into two stages: gas increase stage and breakdown threshold stage. The research also obtained the characteristics and the change criterions of the two stages. The gas in the bubble defects generated from epoxy decomposition which caused by partial discharge. When the gas pressure exceeds the critical fracture toughness of the bubble defects wall, the unstable crack extension occurs, therefore, improving the ability about resistance to partial discharge of epoxy resin or improving the fracture toughness of epoxy resin by modifying would enhance the breakdown performance of insulated tubular busbar. The result also has reference significance for other epoxy-impregnated-paper insulated electrical equipment.

This paper presents the design and analysis of a paper-based chipless RFID sensor for wetness content measurement in plant leaves. The sensor is designed using a passive microwave resonator to measure the ambient physical parameter. The resonator is designed with a rectangular loop inductively coupled with an interdigital capacitor. The experimental analysis of the designed sensor is illustrated here to prove its efficacy. The resonator provides adequate backscattered signal for wireless measurement in the microwave frequency band. When interrogated with a couple of UWB antennas and a VNA, it yields accurate leaf wetness response of the plant. The commercial competence of this sensing device is validated through its experimental analysis on three different types of leaf samples. This sensor is suitable for plant health monitoring in any small-scale gardening applications such as nurseries and greenhouses.

This letter presented a pencil-on-paper-based ecofriendly capacitive touchpad fabricated through a low-cost lab- and solvent-free fabrication process. Economical, readily available, and biodegradable materials, such as pencil and paper, have been used for sensor fabrication. A touchpad based on five such sensors has been developed and evaluated by using it as a user control interface to on/off LEDs and displaying results on LCD and mobile app. The graphite sensors in the user interface have been shielded from the direct interaction of humans and the environment using changeable cling film to make the interface reliable and reusable. The interface can be used in different conditions and users by changing the shielding film. Simultaneously, the system's functionality will remain consistent and functioned similarly to the conventional touch sensors and buttons. These recyclable and easily arrayed touch sensor-based keypads can contribute to future developments in disposable and lightweight interfaces for human–machine interface, medical and healthcare applications, smart packaging, security monitoring, and consumer products.

Rapid increase in scholarly publications on the web has posed a new challenge to the researchers in finding highly relevant and important research articles associated with a particular area of interest. Even a highly relevant paper is sometimes missed especially for novice researchers due to lack of knowledge and experience in finding and accessing the most suitable articles. Scholarly recommender system is a very appropriate tool for this purpose that can enable researchers to locate relevant publications easily and quickly. However, the main downside of the existing approaches is that their effectiveness is dependent on priori user profiles and thus, they cannot recommend papers to the new users. Furthermore, the system uses both public and non-public metadata and therefore, the system is unable to find similarities between papers efficiently due to copyright restrictions. Considering the above challenges, in this research work, a novel hybrid approach is proposed that separately combines a Content Based Filtering (CBF) recommender module and a Collaborative Filtering (CF) recommender module. Unlike previous CBF and CF approaches, public contextual metadata and paper-citation relationship information are effectively incorporated into these two approaches separately to enhance the recommendation accuracy. In order to verify the effectiveness of the proposed approach, publicly available datasets were employed. Experimental results demonstrate that the proposed approach outperforms the baseline approaches in terms of standard metrics (precision, recall, F1-measure, mean average precision, and mean reciprocal rank), indicating that the proposed approach is more efficient in recommending scholarly publications.

Traction transformer is vital equipment in high-speed railway. Insulation status decides its safety and reliability, and the frequency-domain dielectric spectrum (FDS) test is one of the most effective methods reflecting the changing of insulation status. For field applications, the following problems should be addressed: 1) how to obtain the result of paper insulation from the combined result of the oil–paper insulation system and 2) how to discriminate the defects of insulation paper between aging and damp. In this article, the first problem was transferred to a nonlinear equation set, and a cuckoo search algorithm optimized by the differential evolution algorithm and the quadratic interpolation (QI) method (CS-DQ algorithm) was proposed to solve it. Then, the insulation states were discriminated by establishing a multiclass least-squares support vector machine (LS-SVM) model, in which the CS-DQ algorithm was also used. Finally, a diagnostic approach for the insulation paper in the traction transformer was proposed. The results in the laboratory show that the pure result of insulation paper can be obtained, and the insulation states can be discriminated effectively by using the proposed approach. Meanwhile, the proposed CS-DQ algorithm has a better performance than the conventional CS algorithm. The results of field testing also verify the proposed approach.

The effects of furfural generation and partitioning on the aging assessment of oil-paper insulation of power equipment were investigated. Oil-paper samples with various furfural contents were prepared using an accelerated thermal aging experiment. The mass of the furfural generated during the aging of insulation paper was calculated and used to establish the quantitative equation between the accumulated furfural and the degree of polymerization (DP) of the insulation paper. Results showed that the reciprocal of the DP value was linearly related to the amount of furfural generated by the insulation paper. Effects of temperature, moisture, and temperature on the furfural partitioning ratio between oil and paper were analyzed using a furfural partitioning experiment, and a furfural partitioning model was established. Results showed that the furfural partitioning ratio in oil was positively correlated with temperature and moisture but negatively correlated with the DP of the insulation paper. A method for assessing the age of an insulation paper by integrating the furfural generation and partitioning models was proposed and applied on a 500-kV reactor that was returned for factory maintenance. The application result indicated that the method could accurately assess the overall aging condition of the oil-paper insulation of the power equipment.

Moisture accumulates with the growing aging progress of oil-paper insulation and further shortens the remaining life of the transformer. The frequency-domain spectroscopy (FDS) technique can be used to realize the moisture estimation. However, the moisture estimation results would be unreliable once the aging effect on FDS was ignored. Given this issue, an alternative model including the aging effect is thus proposed using FDS and intelligent algorithm. In this work, the feature parameters of FDS data are used to build the databases for characterizing the aging degree and moisture. Then, the moisture estimation models are developed using the weighted K-nearest neighbor (K-NN) algorithm. The accuracy and applicability of the proposed models are finally discussed in laboratory and field conditions. In that respect, the findings reveal that the reported model is available for moisture estimation of transformer oil-paper insulation under various aging degrees and test temperatures.

Paper surfaces under the microscopic view are observed to be formed by intertwisted wood fibers. Such structures of paper surfaces are unique from one location to another and are almost impossible to duplicate. Previous work used microscopic surface normals to characterize such intrinsic structures as a “fingerprint” of paper for security and forensic applications. In this work, we examine several key research questions of feature extraction in both scientific and engineering aspects to facilitate the deployment of paper surface-based authentication when flatbed scanners are used as the acquisition device. We analytically show that, under the unique optical setup of flatbed scanners, the specular reflection does not play a role in norm map estimation. We verify, using a larger dataset than prior work, that the scanner-acquired norm maps, although blurred, are consistent with those measured by confocal microscopes. We confirm that, when choosing an authentication feature, high spatial-frequency subbands of the heightmap are more powerful than the norm map. Finally, we show that it is possible to empirically calculate the physical dimensions of the paper patch needed to achieve a certain authentication performance in equal error rate (EER). We analytically show that log(EER) is decreasing linearly in the edge length of a paper patch.

Finding relevant papers is a non-trivial problem for scholars due to the tremendous amount of academic information in the era of scholarly big data. Scientific paper recommendation systems have been developed to solve such problem by recommending relevant papers to scholars. However, previous paper recommendations calculate paper similarity based on hand-engineered features which are inflexible. To address this problem, we develop a scientific paper recommendation system, namely VOPRec, by vector representation learning of paper in citation networks. VOPRec takes advantages of recent research in both text and network representation learning for unsupervised feature design. In VOPRec, the text information is represented with word embedding to find papers of similar research interest. Then, the structural identity is converted into vectors to find papers of similar network topology. After bridging text information and structural identity with the citation network, vector representation of paper can be learned with network embedding. Finally, top- $Q$ Q recommendation list is generated based on the similarity calculated with paper vectors. Through the APS data set, we show that VOPRec outperforms state-of-the-art paper recommendation baselines measured by precision, recall, F1, and NDCG.

Methanol is regarded as an available indicator to analyze the aging condition of cellulose insulation. However, the diffusion mechanism of methanol molecules in the paper-oil insulation system is still unclear, since it cannot be explored by using only experiments. Given this issue, the molecular dynamics simulations were performed to investigate the diffusion mechanism of methanol molecules. In the current work, the mean square displacement of methanol during the diffusion process was calculated and analyzed, as well as its trajectory tracking. Then, the research on interaction energies and hydrogen bonds in paper/oil system were conducted. Finally, the effect of temperature on the diffusion of methanol molecules was also studied. Findings revealed that the diffusion of methanol in cellulose insulation is faster than that in insulating oil, besides, the presence of hydrogen bonds affects the diffusion rate of methanol molecules in cellulose insulation and insulating oil. Thus, the present findings could support the investigation of the diffusion mechanisms of methanol molecules, by which the aging condition evaluation of cellulose insulation could be also promoted.

The conversion of biowaste to activated carbon (AC) for supercapacitor applications is recently gaining attention due to its extraordinary high specific surface area (SSA), hierarchical pore size distribution, and very good conductivity. Therefore, in this work, we have utilized waste office papers as a precursor to synthesize highly porous carbon to be used as an electrode material for supercapacitors. The sub-nanometre pores in as-synthesized office paper waste-derived activated carbon (OPDAC) material, facilitate easy flow of ions and surprisingly increase the specific capacitance up to 237 F/g at a current density of 1 A/g. Moreover, an all-solid-state symmetric supercapacitor using OPDAC electrodes delivers an ultrahigh energy density of 31 Wh/kg at a power density of 380 W/kg along with a long cycle life of 95% after 3000 charge-discharge cycles. Hence, these remarkable results pave the path for the usage of different biowastes for varying energy storage applications.

Paper-based digital microfluidic biochips (or P-DMFBs) are becoming highly impelling due to its low-cost and in-place fabrication of electrodes and control wiring on a single piece of paper having an inkjet printer and conductive ink. Despite enormous advantages, several complex design rules also subsist, such as avoidance of induced control interference, minimum separation among the control lines, and congestion-free wiring on a single layer, which is to be correlated leading toward overall feasibility of the design. Several cost raising issues, such as schedule length, control pin count, and wire length, must be considered for attaining a successful fluid-control codesign. Moreover, design gaps exist among the subtasks of the fluid level, control level, and fluid-control design as a whole, which undeniably impose expensive design cycles increasing overall cost. This article builds a machine learning-based model for the pin-constrained P-DMFBs to predict violation in control design beforehand and accordingly guides the fluid-control codesign to tackle important cost-driving issues while attaining congestion- and conflict-free wiring. This model effectively eliminates the design cycles producing a low-cost platform. The predictive model has been evaluated over a balanced data set. Several benchmarks for assessing the performance are studied.

Over the last decade, the rapid development in health care industry and security has driven innovations in the field of wearable electronics and smart sensors. This report demonstrates the fabrication of molybdenum diselenide (MoSe2) by a facile, low-cost and scalable hydrothermal synthesis method followed by a vacuum filter deposition on cellulose paper. The fabricated device is utilized as a pressure and strain sensor. The fabricated device is passivated using polydimethylsiloxane (PDMS), and also, PDMS film enhances the flexibility of the device. The calculated sensitivity of pressure sensor is ~0.3 kPa−1, which is comparable and relatively better than the pressure sensor fabricated using sophisticated techniques. Furthermore, the device exhibited significant of merit for strain sensing with a gauge factor of ~6.84. The fabricated device showed excellent resilience in 500 cycle bending tests, which promises the robustness of the device. As an application, the fabricated sensor is used to develop a wireless keyboard by integrating the sensor on fingertips of an individual and a real-time human motion monitoring application in which the data are transmitted wirelessly to a smartphone with a dedicated android application. The successful fabrication of MoSe2/paper-based cost-effective, flexible, and biodegradable pressure-strain sensor shows tremendous applications in future intelligent user interface systems, human security, and personal health care monitoring.

Accurate modeling and simulation of electric field transients in HVDC cables is an important support to optimize insulation system design and to evaluate the influence of voltage transients and steady-state conditions on accelerated ageing mechanisms and insulation reliability. Traditionally, field models considering time-independent permittivity and conductivity are used, but this approach neglects polarization mechanisms and charge trapping-detrapping phenomena. This article includes polarization dynamics in the field model and shows that its impact on transient electric field simulations in HVDC paper-insulated cables can be significant. A method is presented to infer the model parameters from experimental polarization and depolarization current measurements.

This paper establishes a membraneless, co-laminar flow-based approach to develop a cost-effective microfluidic paper-based analytical device for enzymatic biofuel cell ( $\mu $ PAD-EBFC). The developed $\mu $ PAD-EBFC supporting the self-capillary fluid transport action consists of Y-shaped paper microchannel with the fuel (glucose) and oxidant (O2) streaming in parallel over carbon nanotube-based bucky paper electrodes modified with biocompatible electrocatalytic enzymes, such as glucose oxidase and laccase without any additional redox cofactor. The electrochemical performance for the modified bioelectrodes, i.e., electrocatalytic oxidation and reduction reaction, was carried out using linear sweep voltammetry, cyclic voltammetry, and open circuit potential. The overall performance of $\mu $ PAD-EBFC was evaluated using the polarization studies. Subsequently, the catalytic activity of enzymes on the electrode surface was validated by the scanning electron microscope. This simple and portable $\mu $ PAD-EBFC can generate the maximum power density to the order of $100~\mu \text{W}$ /cm2 ( $600~\mu \text{A}$ /cm2) at 0.505 V over prolonged durations of around 50 h. Hence, the presented $\mu $ PAD-EBFC shows good power density and stability, leading to its strong potential to power miniaturized microelectronics devices and sensors.

Due to the increasing size of s (s), their design and optimization phases (i.e., ) grow increasingly complex. At design time, a large design space needs to be explored to find an implementation that fulfills all specifications and then optimizes metrics like energy, area, delay, reliability, etc. At run time, a large configuration space needs to be searched to find the best set of parameters (e.g., voltage/frequency) to further optimize the system. Both spaces are infeasible for exhaustive search typically leading to heuristic optimization algorithms that find some trade-off between design quality and computational overhead. ML can build powerful models that have successfully been employed in related domains. In this survey, we categorize how () may be used and is used for design-time and run-time optimization and exploration strategies of s. A meta-study of published techniques unveils areas in that are well-explored and underexplored with, as well as trends in the employed algorithms. We present a comprehensive categorization and summary of the state of the art on for. Finally, we summarize remaining challenges and promising open research directions.

This paper addresses two key challenges toward an integrated forward error-correcting biosensor based on our previously reported self-assembled quick-response (QR) code. The first challenge involves the choice of the paper substrate for printing and self-assembling the QR code. We have compared four different substrates that includes regular printing paper, Whatman filter paper, nitrocellulose membrane and lab synthesized bacterial cellulose. We report that out of the four substrates bacterial cellulose outperforms the others in terms of probe (gold nanorods) and ink retention capability. The second challenge involves remote activation of the analyte sampling and the QR code self-assembly process. In this paper, we use light as a trigger signal and a graphite layer as a light-absorbing material. The resulting change in temperature due to infrared absorption leads to a temperature gradient that then exerts a diffusive force driving the analyte toward the regions of self-assembly. The working principle has been verified in this paper using assembled biosensor prototypes where we demonstrate higher sample flow rate due to light induced thermal gradients.

A 3D modeling system with all-inclusive functionality is too demanding for a casual 3D modeler to learn. There has been a shift towards more approachable systems, with easy-to-learn, intuitive interfaces. However, most modeling systems still employ mouse and keyboard interfaces, despite the ubiquity of tablet devices and the benefits of multi-touch interfaces. We introduce an alternative 3D modeling and fabrication paradigm using developable surfaces, inspired by traditional papercrafting, and we implement it as a complete system designed for a multi-touch tablet, allowing a user to fabricate 3D scenes. We demonstrate the modeling and fabrication process of assembling complex 3D scenes from a collection of simpler models, in turn shaped through operations applied to virtual paper. Our fabrication method facilitates the assembly of the scene with real paper by automatically converting scenes into a series of cutouts with appropriately added fiducial markers and supporting structures. Our system assists users in creating occluded supporting structures to help maintain the spatial and rigid properties of a scene without compromising its aesthetic qualities. We demonstrate several 3D scenes modeled and fabricated in our system, and evaluate the faithfulness of our fabrications relative to their virtual counterparts and 3D-printed fabrications.

Coater sections are examples of multi-span web transporting systems, with dynamic characteristics related to the sheet properties and control schemes. This paper first describes and analyzes a set of field records of a production 2-coater section paper machine. Then, extending the 1-coater section model developed in a related paper, a precise simulation model of a 2-coater section is implemented. This model is used to evaluate the beginning of the coating process and the effect on the section responses of different bandwidth settings in the tension and speed controllers. Results show agreement with the field records and demonstrate that the developed model is a powerful tool to analyze and understand the behavior of coater sections during both, transient and steady state conditions.

Oil-immersed insulation paper (OIP) bushing is one of the most important equipment in power transmission and distribution systems. Moisture is one of the most serious factors that affect the insulation status of OIP bushing. In this paper, the OIP bushing was assumed to be in a stable and simplicity condition, and then the transient moisture distribution of capacitor core and its effects on the electric field were studied. First, by dissecting a 110 kV OIP bushing, the specific sizes for modelling were obtained. Afterwards, a moisture diffusion model for OIP bushing was established based on COMSOL Multiphysics software, and it was also verified by moisture diffusion experiment. Then, the moisture distribution for different conditions were obtained and analyzed. Finally, a model for the electric field of OIP bushing was established, and then the effects of moisture on the electric field were studied.

Transformer insulation paper is a key indicator for transformer remaining operational life. Paper decomposition is evaluated using the degree of polymerization (DP) which calls for samples of insulation paper from operating transformers. Since collecting such paper samples is extremely difficult, other indicators have been used to indirectly reveal the DP value of insulation paper. This includes dissolved gases in transformer oil such as carbon oxides and hydrocarbon gases, furan compounds, methanol, ethanol, and moisture along with some oil characteristics such as interfacial tension. However, for the same oil sample, these individual parameters lead to different DP values. This is attributed to the lack of accuracy of the established mathematical and artificial intelligence models correlating DP with each of the above mentioned individual parameters. This paper presents a self-learning method to estimate the DP value of transformer insulation paper based on multiple transformer oil aging parameters. The proposed method comprises data processing, fuzzy c-means and linear regression. Results reveal that estimating the DP value based on multiple aging parameters is more accurate than estimating it using one single parameter as per the current practice. The proposed method not only helps to understand the correlation between multiple oil aging parameters and the DP value of paper insulation, but also promotes the establishment of more accurate life assessment models for power transformers based on these oil aging parameters.

Oil-paper insulation ageing of transformer has characteristics of spatial locality due to uneven temperature distribution. The transformer is sealed, it is difficult to obtain the local ageing state of oil-paper insulation by sampling directly. Currently, there are no effective detection method to detect the insulation state of local regions. The oil-immersed paper resistivity inversion method can nondestructively assess the local state of oil-paper insulation. However, the current inversion methods still have shortcomings and need to be improved. In this paper, combining the back propagation neural network (BPNN) and Newton downhill method (NDM), an improved inversion method is proposed to optimize the current inversion method, so as to reduce the effect of initial value on it and make calculated results converge better. Finally, a 3D 10 kV transformer model is established to verify the effectiveness of the proposed method. The resistivity calculated by the improved method show that the method can provide initial resistivity values for technicians and improve the convergence and accuracy of current inversion method, which is more suitable for extending to the engineering practice.

Furfural content in oil has been shown to be a powerful indicator of the deterioration of cellulose paper. The furfural content in oil may increase greatly when the moisture content increases in transformers. The increase of furfural content in oil can be attributed to various factors, such as aging of cellulose paper with the increase of moisture content and the difference in furfural production mechanism. In this research, thermal aging tests of oil-paper system with different moisture contents are conducted under laboratory conditions to determine the cause of such increase. Furfural content, both in insulation oil and in insulation paper, and the degree of polymerization values of insulation paper were regularly measured. Results show that the moisture content plays a significant role on the production of furfural, and the high initial moisture content in insulation paper leads to large amount of furfural produced when DP decreases to the same values. The difference in the moisture content apparently affects the distribution of furfural between oil and paper, and the increase in the moisture content in oil-paper system increases the diffusion of furfural from the insulation paper to the oil.

Dirty paper coding is an interference pre-cancellation method for known interference at the transmitter and serves as a basic building block in the digital watermarking system. In this letter, we investigate the dirty paper model in the simplest digital communication system, where both the codeword and the interference are binary. For watermark embedment, we derive the relevant coding, the constant coding, and the symmetric relevant coding when the encoder focuses on the binary codeword and interference. The channel capacity is analyzed and the optimal parameter is discussed in the case.

Breakdown (BD) and partial discharge (PD) characteristics of insulating paper and transformer board materials are investigated as cost-effective alternatives to high-price materials like polyimide (PI) or polytetrafluoroethylene and fiber reinforced plastic materials typically used in superconducting devices based on high temperature superconductors cooled with liquid nitrogen (LN 2 ). Three different cotton and cellulose based insulating papers are tested in LN 2 at atmospheric pressure and compared to synthetic sheet materials and polypropylene laminated paper (PPLP). Additionally, the BD performance and PD characteristics of three different transformer board materials are investigated in LN 2 . The results reveal that the paper and board materials have nearly the same or even slightly higher BD voltages in LN 2 in comparison to the values in insulating oil. The pure paper materials with thicknesses of 130 μm have a dielectric strength of 70-90 kV/mm, whereas values of 130-140 kV/mm are measured for PPLP and PI with nearly the same thickness. The dielectric strength of the board materials has a maximum value of 76 kV/mm. In the frame of the investigations, the BD performance of the pure paper materials in LN 2 is not influenced by the water content of the materials, dried and undried specimens have nearly the same BD voltage. Only the PPLP material has a 15% higher BD voltage in the dried state in comparison to the undried state.

In this note, it is shown that the results claimed in the paper [1] —as well as the examples presented there—are incorrect.

The International Technology Roadmap for Wide-Bandgap Power Semiconductors (ITRW) materials and devices working group considers the materials science of wide-bandgap (WBG) and ultrawide-bandgap (UWBG) semiconductors in addition to device design, fabrication, and evaluation. Its purpose is to formulate a long-term, international roadmap for WBG and UWBG materials and devices consistent with the packaging and applications working groups of ITRW.

The International Technology Roadmap for Wide-Bandgap Power Semiconductors (ITRW) has four distinct technical working groups, each providing its own perspective on the technology and industrial drivers for the adoption of wide-bandgap (WBG) power semiconductors in power electronics. This article summarizes the progress toward an initial roadmap for the packaging and integration working group of the ITRW.

Paper-based digital microfluidic biochips (P-DMFBs) have recently emerged as a promising low-cost and fast-responsive platform for biochemical assays. In P-DMFBs, electrodes and control lines are printed on a piece of photograph paper using an inkjet printer and carbon nanotubes (CNTs) conductive ink. Compared with traditional digital microfluidic biochips (DMFBs), P-DMFBs enjoy significant advantages, such as faster in-place fabrication with printer and ink, lower costs, and better disposability. Since electrodes and CNT control lines are printed on the same side of this paper, a critical design challenge for P-DMFB is to prevent control interference between moving droplets and the voltages on CNT control lines. Control interference may result in unexpected droplet movements and thus incorrect assay outputs. To address this design challenge, a control-fluidic codesign methodology is proposed in this paper, along with two demonstrative design flows integrating both fluidic design and control design, i.e., the droplet-oriented codesign flow and the electrode-oriented codesign flow. The droplet-oriented flow is suitable for designing biochips with sparse electrodes and relatively larger number of droplets, whereas the electrode-oriented flow is suitable for biochips with dense electrodes and smaller number of droplets. The computational simulation results of real-life bioassays demonstrate the effectiveness of the proposed codesign flows.

Wearable flexible sensors have recently gained much attention as they have the potential to revolutionize the way we monitor activities of the human body. Electronic sensors fabricated on flexible substrates provide compactness, comfort, and flexibility. In this letter, we report a novel design of wearable and mechanically flexible bioimpedance analyzers. We fabricate the analyzers by printing electronic circuits on paper and plastic substrates. The sensor module is lightweight, comfortable, and can be worn on the wrist to measure the body impedance continuously. Failure analysis is performed by bending the flexible sensor modules with the circuit breaking angles at 53° ± 4° and 42° ± 3° for paper and plastic substrates, respectively. The performance of the flexible sensors is compared with an analyzer developed on a conventional rigid printed circuit board. In an active mode, the paper-based sensor consumes more power (83.3 mW) than the plastic (65.7 mW) and rigid (53.42 mW) sensors. The flexible sensor modules are integrated with dry electrodes, while gel-based Ag/AgCl electrodes are attached to the rigid sensor module for bioimpedance measurements. The experiments are conducted on 12 healthy human subjects by using all three sensor modules. The integrated dry electrodes of the flexible sensor modules provide lower skin-electrode contact impedance along with enhanced convenience, durability, and reusability, as compared to commercial Ag/AgCl electrodes.

We present a novel implementation of a Rock-Paper-Scissors (RPS) game interaction with a social robot. The framework is tailored to be computationally lightweight, as well as entertaining and visually appealing through collaboration with designers and animators. The fundamental gesture recognition pipeline employs a Leap motion device and two separate machine learning architectures to evaluate kinematic hand data on-the-fly. The first architecture is used to recognize and segment human motion activity in order to initialize the RPS play, and the second architecture is used to classify hand gestures into rock, paper or scissors. The employed tabletop robot interacts in the RPS play through unique animated gestural movements and vocalizations designed by animators which communicate the robot's choices as well as cognitive reflection on winning, losing and draw states. Performance of both learning architectures is carefully evaluated with respect to accuracy, reliability and run time performance under different feature and classifier types. Moreover, we assess our system during an interactive RPS play between robot and human. Experimental results show that the proposed system is robust to user variations and play style in real environment conditions. As such, it offers a powerful application for the subsequent exploration of social human-machine interaction.

To paraphrase the son of lady macduff in william Shakespeare's Macbeth, "DC is not dead, for all your saying!" When the paper industry was first electrified, the only type of machine capable of variable-speed operation was powered by dc. There were numerous manufacturers and users who knew how the machines worked and how to maintain them. Over time, the control of these machines has changed from relatively simple analog to complex digital systems. Those whose task it was to keep the machines healthy have since moved on to other things. The modern pulp, paper, and forest industries still have applications powered by dc equipment; however, the most recent installation trend is toward ac machines.

Activation energy is popularly used for the estimation of remaining life of transformer insulation. It is defined as the average rate of all reactions that happen with cellulose. Existing literature shows that the activation energy of oil–paper insulation can be obtained from polarization depolarization current (PDC) and return voltage measurement (RVM) data that are measured at a specific temperature. It is practically difficult to ensure the same measurement temperature for both PDC and RVM data. On the other hand, PDC data and its analysis get influenced by de-trapping current. This de-trapping current is generated by ionic charge carriers that get freed from trap sites during PDC measurement process. Formation of these trap sites is related to physical, chemical reactions that happen at oil–paper interface. This paper proposes a methodology which uses de-trapped charge, dislodged from deep and shallow traps, to assess insulation condition and for the prediction of activation energy. Thus, eliminating the need of RVM data. The proposed method is tested using data collected from various real-life in-service transformers.

Assessment of insulation condition by sensing moisture content of oil-impregnated paper at periodic intervals is necessary for reliable operation of transformers. The conventional method of moisture sensing requires application of two cycles of sinusoidal excitation voltage at discrete measurement frequency points over a wide range starting from 0.1 mHz to 1 kHz, which is inadvertently time consuming and practically problematic. Besides, the insulation system in real-life operation is often stressed by voltage waveforms which deviate significantly from sinusoid. Therefore, modification of the existing method is necessary for a reliable insulation diagnostic. Considering the above-mentioned fact, in this article, a new measurement technique for sensing moisture content of oil-paper insulation is proposed using frequency modulated square wave excitations. The proposed technique was experimentally validated on several real-life transformers tested in the laboratory. Investigations revealed that the use of frequency modulated square wave excitations is capable of sensing moisture content in oil-paper insulation almost accurately in comparison with the conventional method but with a significantly reduced measurement time without compromising on measurement accuracy.

This letter demonstrates the fabrication of large area molybdenum diselenide (MoSe2) nanoflowers using a simple, cost-effective hydrothermal synthesis followed by vacuum filtration deposition on cellulose paper as a near-infrared region (NIR) light photodetector. An increase in the photocurrent was observed upon increasing intensity of NIR illumination, which could be attributed to the increased number of photogenerated excitons. The fabricated photodetector under the 780 nm wavelength illumination responded to the responsivity and external quantum efficiency (EQE) of the fabricated photodetector of 9.73 mA/W and 0.015%, respectively. Furthermore, even for an arbitrary bending, the fabricated device exhibits a negligible change in the responsivity and EQE, which display the robustness of the fabricated device. Successful fabrication of MoSe2/paper-based flexible, cost-effective, and environment-friendly NIR photodetector holds tremendous applications in future optoelectronic devices.

The applicability of using 2-furfural (2-FAL) and methanol as aging markers for synthetic ester impregnated paper insulation was investigated through laboratory aging experiments at temperatures of 80, 100 and 120 °C. Methanol in the synthetic ester increased linearly with paper aging until degree of polymerisation (DP) reached 400. During this period concentration of methanol in oil was higher than that of 2-FAL, which proved the concept of using methanol to indicate early paper aging in the synthetic ester. However, the rate of methanol increase against the reduction of DP in the synthetic ester was about three times higher than that seen in mineral oil. This is due to a difference in the partitioning of the marker between oil and paper. Since the synthetic ester is more polar than the mineral oil, it attracted more methanol molecules from the paper, resulting in a higher concentration of methanol in oil for the same reduction of DP. In addition, a reduction in methanol was observed at the later stage of paper aging at 120 °C. This could be due to either a change in the partitioning between oil and paper, or an esterification reaction which consumes methanol in the system.

This article presents a comparative study of two types of transformer solid insulation: standard Kraft and thermally upgraded Kraft papers. The paper samples were impregnated with two different fluids, namely a synthetic dielectric ester fluid, Midel 7131, and a synthesized mineral oil, Luminol Tri. The impregnated papers were submitted to, accelerated aging at 150°C, temperature higher than the temperatures found inside transformers, for extended periods. The results show that for the first hours of aging, the cellulose depolymerization was similar for all the four studied cases. At a specific point, the paper samples aged in the ester fluid exhibited a lower depolymerization exceeding the 8000 hours of aging without reaching the levelling-off degree of polymerization (LODP). A similar trend was observed through the decrease of mechanical properties of papers in the ester-based oil. However, the difference in performance of both fluids was amplified due to the temperature used; at lower temperatures the difference should be smaller. Additionally, a relationship between the degree of polymerization and the mechanical properties accessed by the tensile testing was obtained regardless of the type of paper or oil. The total acidity in the ester fluid was higher than in mineral oil. Methanol, a chemical marker that is closely linked to the rupture of 1,4-s-glycosidic bonds of cellulose, showed a partial sensitivity to the cellulose aging in the ester fluid. Furan (C 4 H 4 O) content was monitored during the aging and its concentration was found to be sensitive to the depolymerization along with the decrease in the mechanical properties of cellulose papers regardless of the type of paper. More importantly, its concentration was found to be dependent on the type of oil. More investigations are needed to further confirm the importance of furan as an indirect indicator of the mechanical performance along with its correlation with the depolymerization of paper aged in ester fluids.

Wireless sensors and networks are used only occasionally in current control loops in the process industry. With rapid developments in embedded and highperformance computing, wireless communication, and cloud technology, drastic changes in the architecture and operation of industrial automation systems seem more likely than ever. These changes are driven by ever-growing demands on production quality and flexibility. However, as discussed in "Summary," there are several research obstacles to overcome. The radio communication environment in the process industry is often troublesome, as the environment is frequently cluttered with large metal objects, moving machines and vehicles, and processes emitting radio disturbances [1], [2]. The successful deployment of a wireless control system in such an environment requires careful design of communication links and network protocols as well as robust and reconfigurable control algorithms.

Aviation is often seen as an innovative sector eager to seek technological solutions. It is often assumed that aircraft cockpits have panels with electronic displays and many buttons, some labeled "auto." While this might be the case for commercial aviation (Figure 1), the vast majority of noncommercial civil aircraft cockpits look nothing like these modern cockpits. Non-commercial civil aircraft, known as general aviation (GA), typically have cockpits that mainly consist of analog instruments that show the heading of the aircraft, the altitude, and the air speed (Figure 2). While flying, the pilots make calculations using a compass and an aviation calculator. Due to the slow entry rate of new, glass-cockpit aircraft [1], the composition of the GA aircraft fleet is not going to change any time soon.

The vast majority of power transformers have an insulation system consisting of both insulating mineral oil and Kraft paper. The principal oil degradation agents are oxygen and temperature, whereas the main mechanisms of insulating Kraft paper degradation are water and acids (acidic hydrolysis degradation), temperature (pyrolytic degradation), and oxygen (oxidative degradation).

Under long-term synergy effect of multi-factors, especially the thermal stress, insulating paper will be degraded and its insulation performance will decline due to carbonization and degradation of cellulose. This paper presents an optical approach for aging feature extraction of the insulating paper, where one of the image processing methods called texture analysis is utilized. By conducting laboratory accelerated thermal aging tests, insulating paper samples with different aging conditions for both Nomex and Kraft, evaluated with the aging time, are prepared. After taking optical microscopic images of insulating paper samples belong to different aging groups, up to 14 texture features are extracted using the gray-level co-occurrence matrix (GLCM). With different feature selection methods applied, several of them are finally selected to represent the aging condition of insulating. Numerical tests with both supervised and unsupervised algorithms, as well as a linear regression method verifies the validity of these features in characterizing the aging condition of the insulating paper.

In the last decade, much effort has been invested in using methanol as an oil-soluble chemical marker for assessing the condition of insulating paper. The use of this marker as paper life index presents many advantages particularly with new transformers insulated with thermally upgraded papers. However, until now, no interpretation model has been available for its extensive use by the transformer community. In this paper, a methanol-based interpretation model is presented for the first time using postmortem paper analysis on core-type transformers. This model allows the evaluation of the average degree of polymerization of a transformer's cellulose winding. Furthermore, threshold values based on the methanol concentration are given using this approach. Finally, model validation was performed on a limited number of papers taken from transformers being assessed in the repair shop.

The papers in this special issue were presented at the 2018 17th International Workshop on Data Mining in Bioinformatics (BIOKDD), held in conjunction with the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. The Workshop was held on August 20, 2018 in London, UK.

In this paper, the nature of thermally upgraded Kraft electrical insulating papers and their characterization by measurement of nitrogen content is discussed. A historical context and explanation of the basics of the various chemical methods used to measure nitrogen content in electrical papers is presented. The Kjeldahl and Dumas methods for quantifying nitrogen content were compared using six insulating papers in different laboratories in an effort to correlate the results obtained with both techniques. The results provide an insight into the viability of the Dumas combustion method as a proposed industry standard test for measuring the nitrogen content of paper. Moreover, data on the accuracy, reproducibility, and repeatability of the Dumas method is provided for the analysis of thermally upgraded electrical papers.

This paper describes a simple and low-cost test strip for on-site monitoring of methiocarb insecticide. Hydrophilic filter paper soaked in agarose solution was bounded by hydrophobic solid wax and then was coated with unmodified gold nanoparticles (AuNPs). AuNPs aggregation caused by methiocarb served as colorimetric response. We demonstrated detection capability of methiocarb both in solution- and substrate-based sensor. A good linear relationship was obtained between the colorimetric response and the concentration of methiocarb ranging from 20 to 80 ng mL $^{-1}$ with a limit of detection of 5 ng mL $^{-1}$ . Excellent selectivity toward methiocarb was observed among various pesticides and cationic and anionic ions. Furthermore, the proposed assay could successfully detect methiocarb in paddy and tap water with satisfactory results. It would be of interest for use as rapid, portable, and technically simple test strip in water quality monitoring.

Cardiac biomarker detection helps in early diagnosis of cardiac syndromes. However, a rapid, cost-effective, reliable, and easy-to-use sensor is still unavailable. Herein, we report a disposable, label free, impedance-based biosensor for the detection of two common cardiac biomarkers, Myoglobin (Myo), and Myeloperoxidase (MPO). The sensor is fabricated on Whatman filter paper coated with a conducting polymer, polyaniline (PAni). The PAni-coated paper is functionalized with glutaraldehyde, a homo-bi functional crosslinker, prior to the covalent attachment of antibodies specific to each biomarker protein. Non-specific active regions of the sensor are blocked by treatment with bovine serum albumin. Conductive silver paste is used to define electrodes for AC impedance measurement on the PAni coated filter paper. Binding of the target protein (Myo or MPO) to the specific antibody changes the impedance between the electrodes; this is detected using AC impedance spectroscopy. The impedance is measured using a frequency response analyzer with an AC excitation voltage of 100 mV in the frequency range of 100 Hz–100 kHz. We can successfully detect Myo and MPO in buffer solution within the concentration range of 100 ng/mL– $50~\mu \text{g}$ /mL. Detection limit obtained for these cardiac biomarkers spiked in human serum is $1~\mu \text{g}$ /mL. Further blocking using human serum improves the lower detection limit to 500 ng/mL. The developed biosensor uses inexpensive materials and fabrication techniques, detects cardiac biomarkers in clinically relevant concentrations rapidly (i.e., within 20 mins), and can be disposed in an environment friendly manner, thus making the sensor suitable for diagnostic applications.