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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).

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.

Traction transformers are one of the most important equipment in the traction power supply system. Thermal aging of transformer insulation system determines its reliable life. To achieve an estimation of the insulation life of traction power transformers operated under real load condition, the effects of traction loads on the thermal aging of oil-paper insulation in traction transformers were investigated. First, the design principles for the accelerated thermal aging experiment were studied and proposed by considering magnitude (i.e., load rate) and frequency (i.e. spare time and lasting time) of the traction load. Then, an experimental system was established in the laboratory to conduct extensive accelerated thermal aging experiments, in which the traction loads were mimicked by using positive temperature coefficient (PTC) heating plates and a programmable logic controller (PLC). Finally, the experimental results were analyzed and discussed to reveal the effects of traction load on the thermal aging of oil-paper insulation in traction transformers.

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.

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.

The papers in this special issue were submitted to all the conferences organized by IEEE Technology and Engineering Management Society (TEMS) in a given calendar year. In 2017, IEEE TEMS initiated its flagship conference TEMSCON (held in Silicon Valley), which serves as rebranding from its original International Technology Management Conferences (ITMC). Following that, in 2018, two more conferences were initiated globally, one in Asia known as IEEE TEMS International Symposium on Innovation and Entrepreneurship (ISIE), and one in Europe as IEEE TEMS International Conference on Technology and Entrepreneurship (ICTE). For this special issue, we invited authors attending any of the three aforementioned conferences in 2018 to submit full manuscripts for reviews, and the present special issue with eleven papers is the result of a careful selection following our usual rigid double-blinded peer-review process.

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.

Wearable electrochemical sensors have attracted tremendous attention in recent years. Here, an integrated three-dimensional paper-based microfluidic electrochemical device (3D-PMED) with flexible wireless circuits is demonstrated for real-time monitoring of sweat potassium. The paper-based microfluidic pad is fabricated by printing wax patterns on cellulose paper and then folding the pre-patterned paper four times to form a five-layer stacked structure: sweat collector, vertical channel, transverse channel, electrode layer, and sweat evaporator. Also, we have discussed the different properties with three swear collector types. The sweat monitoring device is realized by integrating a screen-printed potassium ion-selective sensor on the PET substrate with the fabricated paper microfluidic pad. The sweat flow in 3D-PMED is modeled with red ink to generate the flow pathway of sweat and the capability of sweat storage. The detection range of the potassium ion-selective sensor is 1–32 mM, and the electrode response potential is 61.79 mV per decade of K+ concentration. The device has a small size that is suitable for everywhere on the body, and also have shown good selectivity for both anion and cation, and a stable performance within 1 week. This 3D-PMED has provided a simple, low-cost way for real-time dynamic sweat potassium monitoring when exercising.

Pencil (graphite) on paper (PoP) electronics has gained significant attention due to its low cost and versatility in developing customizable disposable electronics. Despite the convenience of the PoP methodology in device fabrication its application in developing electronics is limited due to the absence of a bandgap in graphite. The present work is the first demonstration of the direct writing of 2D MoS2 trace on paper which was utilized as a pressure and strain sensor. Detailed characterization studies revealed the formation of rhombohedral and hexagonal phased MoS2 micro-flowers. XPS studies revealed the formation of mixed 1T (metallic) and 2H (semiconducting) phases of MoS2. With the increase in the number of traces of 2D MoS2 on paper, the resistance of the channel decreased owing to the increase in conducting channels. The as-fabricated pressure sensor displayed a sensitivity of 2.21 kPa−1 and strain sensor displayed a GF of 13. Also, the sensor displayed an excellent durability for 1600 cycles. The superior response of the sensor can be attributed to the synergistic properties of micro fibrous paper substrate and piezo-dependent electron transfer of 2D-MoS2. The presented technique enables “make it yourself” multifunctional device that have numerous potential applications in the field of consumer electronics and personal healthcare monitoring.

This paper examines the role of technology firms in computerizing personality tests from the early 1960s to late 1980s. It focuses on the National Computer Systems (NCS) and their development of an automated interpretation for the Minnesota Multiphasic Personality inventory (MMPI). NCS trumpeted their computerized interpretation as a way to free up clerical labor and mitigate human bias. Yet psychologists cautioned that proprietary algorithms risked obscuring decision rules. I show how clinics, courtrooms, and businesses all had competing interests in the use of computerized personality tests. As I argue, the development of computerized psychological tests was shaped both by business concerns about intellectual property and profits and psychologists' concerns with validity and access to algorithms. Across these domains, the common claim was that computerized psychological testing could provide a technical fix for bias. This paper contributes to histories of computing emphasizing the importance of IP, the relationship between labor, technology, and expertise, and to histories of algorithms.

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.

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.

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.

The existing plethora of document classification techniques exploits different data sources either from the content or metadata of research articles. Various journal publishers like Springer, Elsevier, IEEE, etc., do not provide open access to the content of research articles, whereas metadata is freely available there. Metadata like title, keyword, and abstract can serve as a better alternative to the content in various scenarios. In the current literature, researchers have assessed the role of some of the metadata individually. We believe that the collective contribution of metadata parameters can play a significant role in classifying research papers. This paper presents a comprehensive evaluation of the role of metadata, individually as well as in combinations to achieve the objective of research paper classification. Moreover, we have classified the research articles into ACM hierarchy root categories (e.g. general literature, hardware, software, etc.). In this comprehensive evaluation, we have assessed all the possible combinations of metadata features against different classifiers such as Random Forest, K Nearest Neighbor, and Decision Tree. The results of this research reveal that the title & keywords combination outperforms other combinations with an F-measure score of 0.88.

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 studies the secure transmission in a multiuser broadcast channel where only the statistical channel state information of the eavesdropper is available. We propose to apply secret dirty-paper coding (S-DPC) in this scenario to support the secure transmission of one user and the normal (unclassified) transmission of the other users. By adopting the S-DPC and encoding the secret message in the first place, all the information-bearing signals of the normal transmission are treated as noise by potential eavesdroppers and thus provide secrecy for the secure transmission. In this way, the proposed approach exploits the intrinsic secrecy of multiuser broadcasting and can serve as an energy-efficient alternative to the traditional artificial noise (AN) scheme. To evaluate the secrecy performance of this approach and compare it with the AN scheme, we propose two S-DPC-based secure transmission schemes for maximizing the secrecy rate under constraints on the secrecy outage probability (SOP) and the normal transmission rates. The first scheme directly optimizes the covariance matrices of the transmit signals, and a novel approximation of the intractable SOP constraint is derived to facilitate the optimization. The second scheme combines zero-forcing dirty-paper coding and AN, and the optimization involves only power allocation. We establish efficient numerical algorithms to solve the optimization problems for both schemes. Theoretical and simulation results confirm that, in addition to supporting the normal transmission, the achievable secrecy rates of the proposed schemes can be close to that of the traditional AN scheme, which supports only the secure transmission of one user.

Frequency Domain Spectroscopy (FDS) is proposed as a suitable diagnostic method in this paper for implementation on energized oil-paper insulation systems. In present FDS tests, the measurement method is only designed for offline applications. To overcome the deficiencies with the offline testing, this work investigates the feasibility of performing FDS measurements on energized transformers with the view to developing an online diagnostic tool using neutral connections as injection and measurement paths. In the proposed technique, a low-pass filter system is designed to remove the high frequency noise as well as the power frequency signals present in the measured neutral currents. The technique has been successfully applied in a laboratory environment on transformers with oil-paper insulation systems with different operational ages and is feasible for single-phase as well as 3-phase transformers with the accessible neutral points. Compared with the conventional FDS results, a nonlinear dielectric phenomenon is observed from the energized insulation systems as higher dissipation factor Tanδ values primarily due to the increased losses under power frequency voltage excitation. The degree of the nonlinearity is found to correlate well with the degradation status of insulation systems under test.

This paper presents a wavelet texture analysis of microscopy images acquired from artificially-aged samples of power transformer winding insulation paper. Oil-impregnated Kraft paper samples are prepared for experimental tests where they are thermally stressed in an oven at temperatures above what would normally occur in operation. This accelerated ageing test arrangement is used to produce a set of paper samples with varying levels of insulation deterioration. From the paper samples, microscopy images of the paper surface are obtained using a standard optical microscope. These microscopic images are analyzed using a texture analysis method that utilizes a two-dimensional wavelet transform to extract detailed information from the wavelet decomposition coefficient matrices. These features are analyzed to assess how the texture of paper changes in response to thermal deterioration and ageing. The results suggest that the texture features are correlated to the commonly-used degree of polymerization test. Additionally, statistical classification is performed on the wavelet texture features using both supervised and unsupervised machine learning methods. The results demonstrate that differentiation between oil-impregnated paper samples with different levels of thermal degradation using wavelet texture analysis is effective.

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.

Aging of transformer paper insulation is commonly investigated through indirect measurements conducted in the oil, e.g. furanic compounds. In addition to the conventional indicators, recent investigations showed that alcohols like methanol and ethanol in oil could be used as paper aging indicators. This paper focuses on the applicability of these new paper aging indicators in a novel, gas-to-liquid (GTL) technology based transformer oil through an accelerated laboratory aging experiment. The experiment was conducted at 120 °C for up to 280 days. A conventional mineral oil was also tested as a reference. Kraft paper aged in both oil types showed similar reductions in degree of polymerization (DP) and tensile strength (TS). Amount of methanol in oil is higher than that of 2-FAL in oil when DP is over 375, confirming the promise of using methanol as an early paper aging indicator. Both the new paper aging indicator, methanol and the conventional paper aging indicator, 2-FAL are applicable for the GTL oil without any modifications. In addition, oil only aging experiments showed that oil does produce methanol but it is negligible compared with oil paper aging experiment; however the amount of ethanol measured in the present oil paper aging experiment is believed to be originated from oil oxidation rather than from paper aging.

This report demonstrates the fabrication of SnS/paper based low-cost and flexible pressure sensor, employing a facile solvothermal synthesis followed by vacuum filtration, for artificial electronic skin and touchpad applications. The fabricated pressure sensor displayed a high sensitivity of 3.18 kPa $^{- {\sf 1}}$ and a response time $\sim 300$ msec. Inspired by the high value of sensitivity and an appreciable flexibility, a large-area pressure sensor array ( ${\sf 3} \times {\sf 3}$ ) was fabricated and integrated onto a human arm for demonstrating real-time applications. The fabricated sensor array was able to consistently detect and track random localized points of contact, the shape of an unknown object placed on top of it, and an index finger trajectory along the surface with high accuracy and precision. The fabricated device showed a negligible change in the performance over 500 bending cycles which indicates the highly robust nature of the device. Successful fabrication of such a cost-effective large-area pressure sensor array is a major step in flexible electronics, and holds immense potential in artificial electronic skin, security, personal healthcare applications.

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.

Objective: Early stage diagnosis of sepsis without overburdening health services is essential to improving patient outcomes. Methods: A fast and simple-to-use platform that combines an integrated circuit with paper microfluidics for simultaneous detection of multiple-metabolites appropriate for diagnostics was presented. Paper based sensors are a primary candidate for widespread deployment of diagnostic or test devices. However, the majority of devices today use a simple paper strip to detect a single marker using the reflectance of light. However, for many diseases such as sepsis, one biomarker is not sufficient to make a unique diagnosis. In this work multiple measurements are made on patterned paper simultaneously. Using laser ablation to fabricate microfluidic channels on paper provides a flexible and direct approach for mass manufacture of disposable paper strips. A reusable photodiode array on a complementary metal oxide semiconductor chip is used as the transducer. Results: The system measures changes in optical absorbance in the paper to achieve a cost-effective and easily implemented system that is capable of multiple simultaneous assays. Potential sepsis metabolite biomarkers glucose and lactate have been studied and quantified with the platform, achieving sensitivity within the physiological range in human serum. Conclusion: We have detailed a disposable paper-based CMOS photodiode sensor platform for real-time simultaneous detection of metabolites for diseases such as sepsis. Significance: A combination of a low-cost paper strip with microfluidic channels and a sensitive CMOS photodiode sensor array makes our platform a robust portable and inexpensive biosensing device for multiple diagnostic tests in many different applications.

The eight papers in this special section were presented at the IEEE International Solid-State Circuits Conference (ISSCC)that was held in San Francisco, California, from February 16 to February 20, 2020.

Several miniaturized viscometers, or microviscometers, have been developed exploiting numerous rapid prototyping techniques. Among them, paper microstrips, famously known as microfluidic paper-based analytical devices ( $\mu $ PADs), have become popular due to their cost-efficacy, simple fabrication, fast response, and easily disposable. Many fabrication methods are existing to develop paper microstrips. Herein, an alternative fabrication method is proposed where fused deposition modeling (FDM)-based 3-D printer (3DP) has been employed using polycaprolactone (PCL) filament. F, image processing has been utilized to measure viscosity in such microfluidic domain. Viscosity was calculated by measuring the time taken by the fluid to cover a fixed length between two spots in the microchannel based on the programed and color-coded regions-of-interest. The image processing program was developed considering the change in the gray scale in the virtual region of interests (ROIs) in the microchannel during the fluid flow in the paper microstrips. A 3-D printed handheld platform, containing raspberry pi with on-board camera and display, was developed to execute the image processing and automate the entire work flow. In the proposed device, the accuracy was measured to be >92%.

Cellulosic insulation materials are very widely used in power transformers, in designs up to 1,500 MVA [1]. Cellulosic insulation is formed of either wood, pressboard, or Kraft paper. The wood and thick sections of pressboard are used to manufacture the base of the transformer; pressboard is also used for the spacers and barriers of the windings, and the paper is wrapped around the current carrying conductors. The water content of this cellulosic insulation must be monitored, because if it becomes too high, a transformer can fail on overload, and will reach the end of its functional life sooner because the paper insulation will age faster [2]. Eventually, the paper will become brittle, and will either tear or lift off the conductor. The water content of paper (WCP) is the ratio of the mass of adsorbed water to the mass of dry paper, usually expressed as a percentage. Water can migrate out of the wood and pressboard and around the system, eventually increasing the WCP. If the WCP becomes too high, the transformer may be dried out by the relevant utility [3].

Flexible In2O3 nanowire transistors gated by microporous SiO2-based solid electrolytes are fabricated on paper substrates at room temperature. Low-voltage (1.0 V) operation of these devices is realized owing to the large electric-double-layer capacitance of (1.73 μF/cm2 at 20 Hz) of the microporous SiO2 solid electrolytes, which were deposited at room temperature. The subthreshold swing, current on/off ratio, and field-effect mobility of the paper-based nanowire transistors are estimated to be 74 mV/decade, 1.7×106, and 218.3 cm2/V·s, respectively. These low-voltage paper-based nanowire transistors show promise for use in portable flexible paper electronics and low-cost portable sensors.

This paper presents a wireless, self-powered, affinity-based biosensor based on the integration of paper-based microfluidics with our previously reported method for self-assembling radio-frequency (RF) antennas. At the core of the proposed approach is a silver-enhancement technique that grows portions of a RF antenna in regions where target antigens hybridize with target specific affinity probes. The hybridization regions are defined by a network of nitrocellulose based microfluidic channels which implement a self-powered approach to sample the reagent and control its flow and mixing. The integration substrate for the biosensor has been constructed using polyethylene and the patterning of the antenna on the substrate has been achieved using a low-cost ink-jet printing technique. The substrate has been integrated with passive radio-frequency identification (RFID) tags to demonstrate that the resulting sensor-tag can be used for continuous monitoring in a food supply-chain where direct measurement of analytes is typically considered to be impractical. We validate the proof-of-concept operation of the proposed sensor-tag using IgG as a model analyte and using a 915 MHz Ultra-high-frequency (UHF) RFID tagging technology.

Mobile and wireless communications are playing an irreplaceable role in our daily life. 5G is highly expected and can be considered as the convergence of mobile and wireless communications. This topic becomes one of the hottest research topics recently, and papers on this topic have been paid much attention. Table I lists the top ten papers published in the IEEE Transactions on Microwave Theory and Techniques (TMTT) in 2019 with the highest numbers of Full Text View since published. Seven papers are about millimeter-waves (mm-waves), and because mm-waves multiple-input–multiple-output (MIMO) will be adopted globally, the 24.25–27.5-GHz band and 27–29.5-GHz bands are now approved worldwide as the standard 5G communication bands. The most popular paper is published by Asbeck et al. [item 1) in the Appendix] for mm-wave power amplifiers.

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.

In this study, aiming to characterize the dynamic polarization behavior of water molecules affected by hydrogen bonding with oil-paper insulation, we performed dielectric spectroscopy on oil-paper insulation with moisture contents of 0.4–4.7% in the terahertz band (0.3–3.3 THz). A relaxation-resonance integrated polarization model considering water-participant hydrogen bond (WHB) effects is established to describe the complex dielectric constant of oil-paper insulation with moisture. The theoretical model is in good agreement with the experimental results. By analyzing the relationship between the polarization parameters and moisture content, three states of WHBs are found. The WHB type, strength and disorder show different characteristics with increased moisture. Furthermore, molecular simulation studies are carried out, and the calculation results provided a persuasive argument for the analysis of terahertz dielectric spectroscopy. This research reveals an important new strategy for studying the polarization behavior of water molecules affected by oil-paper insulation as an experimental supplement to molecular simulation. The proposed test and analysis method render effective and sustainable progress in practical applications of rapid nondestructive evaluation and 2D imaging of moisture content distributed in oil-paper insulation.

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.

With the global trend to establish smart distributed-generation grids, the level of AC-voltage harmonics is significantly increasing due to power electronic converters interfacing renewable energy sources with the grid. Such harmonics will not only degrade the power quality and increase the losses in the electricity grids but will also have a severe impact on oil impregnated paper (OIP) in power transformer bushings. While much attention has been given to investigate the deterioration of OIP under thermal and electrical stresses, the impact of voltage harmonics on the OIP structure is still uncertain and calls for more investigations. Therefore, this paper is aimed at investigating the variations of the multilevel structure of an OIP aged under high levels of AC-voltage harmonics. In this context, degree of polymerization of the aged OIP is measured to reveal the changes of OIP secondary structure. Also, X-ray diffraction, deuteration treatment and Fourier transform infra-red spectroscopy are conducted to analyze the changes of the OIP aggregate structure during the aging process. Further experiments are performed to investigate the variation of the microscopic appearance, thermal behavior and dielectric properties, including scanning electronic microscopy, thermal gravity analysis, differential scanning calorimetry and frequency domain spectroscopy. This investigation on the variation of the multilevel structure of aged OIP not only promotes further understanding to the aging behavior and mechanism of OIP under AC-voltage harmonics, but also proposes crystallinity and accessibility as two new effective aging indicators for the OIP structure.

There is an increasing demand for measuring respiratory rate (RR) to monitor the progression of clinical events such as cardiac arrest or during the admission to the intensive care unit (ICU). Current methods of respiration monitoring are complex, invasive, expensive and therefore require alternative techniques. In this paper, we utilized wearable and flexible technology to develop humidity sensors for long-term continuous monitoring of respiration. Using manual drawing and printing techniques, the sensors were made based on graphite trace and silver nanoparticles as two different sensing materials. The surface morphologies of the devices were characterized by Scanning Electron Microscope (SEM) to show the construction of the sensors. Additionally, the material characterization was performed to obtain the Raman Spectra. Paper was chosen as a flexible substrate owing to its biodegradability, porosity, and disposability. The humidity sensing characteristics of the sensors indicated the best sensitivity of 0.0564% for Graphite on Paper (GOP) sensor. Furthermore, the hygroscopic nature of the paper enables converting the humidity changes during inhalation and exhalation into electrical signals. The electrical signals are transmitted via an interface to a computer using a simple data-logging set-up. A set of normal, deep and apnea breathing conditions could be easily differentiated from these signals along with information on respiration rate and pattern. The functionality of sensors was also tested after light and rigorous exercises. The proposed sensor combines the advantages of being low cost, non-invasive, highly sensitive, stable and holds tremendous potential for wearable/flexible healthcare technology.

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.

Contamination of water bodies due to the disposal of natural and anthropogenic pollutants is one of the major global concerns in the recent times. Regular on-spot monitoring of water quality has become mandatory wherein diverse classes of materials such as organic, inorganic, heavy metals, or biological wastes are detected employing standard protocols. However, most of the existing laboratory techniques are either costly and/or time consuming owing to the process involving the expert driven sophisticated analysis techniques. Herein, we report the development of three paper based colorimetric sensors for the on-spot quantitative detection of the levels of fluoride (F−), lead (Pb2+), and pH in drinking water. The variations in the color-intensities of the paper sensors with the variation in the concentration of fluoride (F−), lead (Pb2+), and pH were converted into electronic signals to enable the development of a point-of-care-testing (POCT) device. For this purpose, initially, the sensors were characterized and calibrated with known concentrations of contaminates before successful validations with real samples. Thereafter, the sensors were illuminated with a light emitting diode from one side while the transmitted rays passing through the sensor was captured by a light dependent resistor (LDR) from the other side. The variation in the color intensity of the paper-sensor with the contaminant loading was found linearly varying with the resistance of the LDR. The sensor was then translated into a specific, stable and user friendly POCT device, which enabled inexpensive spot detection of pollutants in drinking water.

Microfluidic paper-based analytical devices ( $\mu $ PADs) are a clean-room free, cost-effective, and self-pumping flow-based rapid prototyping technique, which is compatible with a varying range of fluids. Until now, $\mu $ PADs have been primarily fabricated using crayons, and plotting-machine and solid-ink printers. These devices can be easily employed for various detection schemes, such as electrical, electrochemical, and optical. The presence of a capillary effect in the chromatograph paper has made $\mu $ PADs independent of a passive device, such as pumps and valves. In this paper, an alternative and a novel method is proposed to achieve the $\mu $ PADs effortlessly using a 3-D printer (3DP), which has many advantages over the existing methods. For creating hydrophobic barriers for microchannel walls, polycaprolactone (PCL) filament was used with fused-deposition modeling (FDM) 3DP. PCL filaments were deposited on the chromatography paper followed by heating for determining the overall dimension and depth of the microchannel at which PCL melts and penetrates into this paper. The $\mu $ PADs are characterized and optimized for two parameters. First, fabrication parameters, such as heating temperature and time duration, were used for the creation of the hydrophobic barrier using a hot air oven. Second, the microchannel parameters, such as microchannel width, boundary thickness, chromatography paper grade, and microchannel source shape (rectangular, triangular, and circular) were used for the fluid-flow by measuring the time taken by fluid to travel a fixed length of the microchannel. After rigorous analysis, it was found that for the creation of the hydrophobic barrier, $\mu $ PADs heated between temperature 120°C to 150°C require 30 min. Under optimized conditions for the fluid flow, the chromatography paper grade 1441 with a triangular source microchannel was found to be best. This paper provides an alternate, simple, and optimized method toward the development of the application-specific $\mu $ PADs, such as the micro-viscometer, which, in turn, can be widely used to monitor various types of fluids including human bodily fluids.

Various miniaturized viscometers have been developed utilizing several fabrication methods. Among them, microfluidic paper-based analytical devices ( $\mu $ PADs) are becoming popular due to their fabrication ease, cost-effectiveness, and the fact that the flow can be carried out using the embedded capillaries themselves. Mostly, $\mu $ PADs are reported to be fabricated by a solid-ink printer, which has significantly high capital and operational cost. To overcome such drawbacks, a novel rapid prototyping method has been proposed, wherein the formation of the hydrophobic regions was created by polycaprolactone (PCL) filament using a 3-D printer. To leverage this, $\mu $ PAD as a viscometer, velocity, or time between two points with known distances was required, which was carried out by an amperometric approach, established by fabricating the integrated screen-printed electrodes intersecting the microchannel of the $\mu $ PAD. The time measurement was fully automated by a microcontroller, and the relative viscosity was calculated by comparing the time taken by the reference fluid with that of a test fluid to cover a known length. Such integrated, automated, and low-cost paper-based microviscometer was leveraged to measure and analyze the viscosities of various milk variants, which has an accuracy of >92%.

Wireless, passive, and cost-efficient monitoring of moisture within packaged food and medicine is important to ensure their safety and freshness. This paper presents paper-based single spiral inductance–capacitance (LC) sensors and a distance-insensitive readout system. The parasitic capacitance of the single-spiral coil is used to form an LC resonant circuit with its inductance. The printing paper is utilized as a humidity sensing material. A model for the LC sensor is analyzed and compared with HFSS simulation, showing the relative error within 6.3%. Nano-silver paste for the single-spiral coil was screen printed on the printing paper. The LC sensors with 4, 6, and 8-turns coils were characterized at relative humidity levels of 15%-90%RH by a readout coil at a fixed position. Comparison shows that the 8-turn sensor has the best linearity with respect to humidity. The sensitivity and response time were measured to be 120 kHz/%RH and 60 minutes, respectively, with the hysteresis errors less than 0.9%. During the practical monitoring, the tested signal frequency will have a shift if the coil’s relative position alters. To weaken the influence of the coil’s position, a readout coil, working at the quasi-resonant with the LC sensor was utilized to enhance the readout, resulting in more stable signal. According to the experimental results, the improved readout system can restrain the frequency shift within 1.1% at a readout distance from 2–50 mm when the ambient humidity is 60%RH.

The 2019 International Conference on Modeling and Analysis of Semiconductor Manufacturing (MASM 2019) was part of the 2019 Winter Simulation Conference (WSC) that was held December 8–11 in National Harbor, MD, USA. The MASM conferences provide a forum for the exchange of ideas and industrial innovations between researchers and practitioners from around the world involved in modeling and analysis of complex high-tech manufacturing systems. While the papers from MASM conferences are of high quality and are often cited in journal papers, they are limited in size. As a premier journal for topics covered in the MASM conferences, IEEE T ransactions on S emiconductor M anufacturing , agreed to consider extended article submissions based on the 21 papers accepted and presented at the MASM 2019 conference for a Special Section of an upcoming issue of the journal. were sessions on Scheduling and Dispatching, Fab Scheduling, Maintenance and Engineering, Capacity and Production Planning, Qualification and Wafer-to-Order Allocation, Semiconductor Manufacturing Models, and Semiconductor Modeling Representations. Dr. Sabine Herlitschka, Chief Executive Officer and Chief Technology Officer of Infineon Technologies Austria AG, gave an excellent keynote talk titled “A European View on Future Semiconductor Industry Needs for MASM.” An archive of the MASM 2019 papers can be found at https://informs-sim.org/wsc19papers/by_area.html .

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.

In this article, we put forward the substantial challenges in cyber resilience in the domain of autonomous systems and outline foundational solutions to address these challenges. These solutions fall into two broad themes: resilience-by-design and resilience-by-reaction . We use several application drivers from autonomous systems to motivate the challenges in cyber resilience and to demonstrate the benefit of the solutions. We focus on some autonomous systems in the near horizon (autonomous ground and aerial vehicles) and also a little more distant (autonomous rescue and relief). For resilience-by-design , we focus on design methods in software that are needed for our cyber systems to be resilient. In contrast, for resilience-by-reaction , we discuss how to make systems resilient by responding, reconfiguring, or recovering at runtime when failures happen. We also discuss the notion of adaptive execution to improve resilience, execution transparently and adaptively among available execution platforms (mobile/embedded, edge, and cloud). For each of the two themes, we survey the current state, and the desired state and ways to get there. We conclude the paper by looking at the research challenges we will have to solve in the short and the mid-term to make the vision of resilient autonomous systems a reality. This article came out of discussions that started at the NSF-sponsored Grand Challenges in Resilience Workshop held at Purdue in 2019 with the co-authors contributing to going into the depth of the issues and then this article.

Millimeter-wave imaging may be used to assist in\ud the problem of wastepaper recognition during the sorting and\ud recycling process. Currently, there are a variety of techniques,\ud which are used within materials recovery facilities to sort waste\ud paper and card; however, improvements in sorting capability can\ud be realized using a multiple sensors to provide complementary\ud (orthogonal) data. This paper discusses the issues related to\ud the processes, which are currently used for sorting of recycled\ud wastepaper and the phenomenology for millimeter-wave imaging\ud of a wastepaper material. Experimental measurements and\ud images in the millimeter wave band are presented, which support\ud the proposed application.

The three papers in this special section were presented at the 2019 CVPR conference that was held in Long Beach CA, in June of 2019.

Oil soluble chemical markers such as methanol, ethanol and 2-furaldehyde for assessing the condition of insulating paper still present many challenges for an accurate interpretation in real transformers. Indeed, many conceptual parameters such as design (shell vs. core) or type of cooling are needed for a more accurate interpretation of the data. Moreover, similarly to water, the measured marker concentrations in oil are temperature-dependent, i.e. an existing partition phenomenon between the oil and the solid insulation modify the solubility of the markers, thus changing their apparent concentrations in the oil. Consequently, to follow the real trend of these species during the transformer’s service life, it is crucial to correct their concentrations at a specific temperature, as is done for the water content. Knowing these facts and in order to calibrate a predictive model, Hydro-Quebec decided to access equipment when dismantled, which enables a large amount of paper to be sampled from different sections of the windings. This allows for a more accurate representation of the transformer paper conditions in relation to transformer design. The paper condition obtained by measuring the degree of polymerization in accordance with the presence of chemical markers is a valuable process. We believe that it is possible to better understand the behavior of the paper insulation and to assess markers concentration thresholds using the oil analysis. This article discusses the recent experience in this field with specific cases.