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The sulfuric acid-doping polyaniline (H-PANI-HSO4) are applied to conduct the electrochemical measurement and simulation calculation to investigate the capacitance, electronic structure and energy band properties. The H-PANI-HSO4 growing on graphite carbon paper (H-PANI-HSO4/GCP) is applied as an electroactive electrode to investigate electrochemical properties. The Faradaic capacitance of H-PANI-HSO4/GCP electrode is ascribed to the reversible redox reaction of bisulfate anion doping/dedoping protonated PANI (H-PANI). Cyclic voltammetry measurement at a scan rate of 5mVs−1 determines an equivalent mean response current of 0.64Ag−1 and a capacitance of 128.35Fg−1. Galvanostatic charge–discharge measurement determines specific capacitance from 129.06 to 116.88Fg−1 at current densities from 0.5 to 2.5Ag−1. Cyclic voltammetry-based capacitance at equivalent current density of 0.64Ag−1 is in accordance with galvanostatic charge–discharge-based capacitance at the current density of 0.57Ag−1. Electrochemical impedance spectrum measurements indicate that H-PANI-HSO4/GCP exhibits lower charge-transfer resistance, much lower Warburg resistance, higher quasicapacitance than H-PANI-HSO4 to approaching ideal capacitor. Density functional theory calculations indicate that H-PANI-HSO4 has a higher density of states (10.6 electron/eV) and lower bandgap energy (0.481eV) than H-PANI (5.24 electron/eV, 1.449eV), indicating its enhanced electronic conductivity. The electronic bandgap energy is accordingly decreased from 0.263eV for H-PANI-HSO4/GCP to 0 for H-PANI-HSO4/GCP. Electrochemical measurement and simulation calculation investigation proves that H-PANI-HSO4/GCP electrode with anion-doped and protonated state exhibits higher electronic conductivity and capacitance performance to act as superior electroactive material. [ABSTRACT FROM AUTHOR]

In recent times, among all the substrates used in microfluidic systems, cellulose paper is used as a handy, low-cost substrate that has gained attention for carrying fluid on its surface over capillary pressure. Cellulose paper substrate has exhibited great potential on microfluidic devices owing to prevalent obtainability, easy fluid (sample) flow system, flexibility, and low cost. Cellulose paper is fibrous, biocompatible, and hydrophilic in nature due to the hydroxyl group of the cellulose molecule. Based on the dominance of functional hydroxyl groups, cellulose is very reactive and every single cellulose fiber acts like a microchannel on the paper substrates. Aggregation of inter- and intra-cellulose fiber chains has a strong binding affinity to it and toward materials containing hydroxyls groups. In this paper, impact of inter- and intra-cellulose fiber on the paper substrate has been discussed through an experimental study. For the addition of work a "hydrophobic penetration-on-paper substrate (Hyp-POP)" method has been shown by using TiO2 ink as a hydrophobic material to design the microfluidic channel on the Whatman cellulose filter paper (grade 1) as a paper substrate. In this experimental study, the intra-cellulose fibers of paper substrate interact through hydrogen bonds with water molecules and form a hydrophilic surface on paper substrate while TiO2 binds with intra-cellulose fibers by electrostatic forces which change the crystallinity of intra-cellulose fiber and make the surface of paper substrate; hydrophobic. Field Emission Scanning Electron Microscope (FESEM) analysis is conceded for microfluidic channel analysis on the paper surface and EDS is carried out for TiO2 ink contents analysis. It has been experimentally observed that the printing material of TiO2 ink with 17.2% Ti content is suitable to integrate hydrophobic barrier on paper substrate for microfluidic channel fabrication. The wetting ability of Whatman cellulose filter paper (grade 1) was further evaluated by contact angle measurements (Data physics OCA 15EC). Using "Hyp-POP" method a hydrophobic pattern (width 3140 μ m) on paper substrate has been made for the flow of liquid (blue fountain ink) into a paper fluidic channel (width 1860 μ m) without any leakage. [ABSTRACT FROM AUTHOR]

A thermal stability analysis method of meta-aramid insulating paper based on computer molecular dynamics technology is designed in this paper. First, the raw materials and equipment for preparing meta-aramid insulating paper were determined to prepare meta-aramid insulating paper. Then, the internal structure and morphology of meta-aramid insulating paper are analyzed for the subsequent stability analysis. Finally, the basic principle of computer molecular dynamics technology is analyzed, which is used to analyze the thermal stability of meta-aramid insulating paper, mainly from the stability of its crystal region. The experimental results show that the proposed method is effective and feasible in analyzing the thermal stability of aramid insulating paper between samples. [ABSTRACT FROM AUTHOR]

The Laser Interferometer Space Antenna (LISA) mission, scheduled for launch in the mid-2030s, is a gravitational wave space observatory designed to detect sources emitting in the millihertz band. LISA is an European Space Agency flagship mission, currently entering the Phase-B development phase. It is expected to help us improve our understanding of our Universe by measuring gravitational wave sources of different types, with some of the sources being at very high redshifts (z ∼ 2 0). On February 23, 2022, we organized the first LISA in Greece Workshop. This Workshop aimed to inform the Greek scientific and tech industry communities about the possibilities of participating in LISA science and the LISA mission, with the support of the Hellenic Space Center. In this White Paper, we summarize the outcomes of the Workshop, the most important aspect of it being the inclusion of 1 5 Greek researchers to the LISA Consortium, raising our total number to 2 2. At the same time, we present a road map with the future steps and actions of the Greek Gravitational Wave community with respect to the LISA mission. [ABSTRACT FROM AUTHOR]

Source code is essential for researchers to reproduce the methods and replicate the results of artificial intelligence (AI) papers. Some organizations and researchers manually collect AI papers with available source code to contribute to the AI community. However, manual collection is a labor-intensive and time-consuming task. To address this issue, we propose a method to automatically identify papers with available source code and extract their source code repository URLs. With this method, we find that 20.5% of regular papers of 10 top AI conferences published from 2010 to 2019 are identified as papers with available source code and that 8.1% of these source code repositories are no longer accessible. We also create the XMU NLP Lab README Dataset, the largest dataset of labeled README files for source code document research. Through this dataset, we have discovered that quite a few README files have no installation instructions or usage tutorials provided. Further, a large-scale comprehensive statistical analysis is made for a general picture of the source code of AI conference papers. The proposed solution can also go beyond AI conference papers to analyze other scientific papers from both journals and conferences to shed light on more domains. [ABSTRACT FROM AUTHOR]

Recent and forthcoming technological innovations highlight recycled paper products as a consumer market with promising potential. This study presents the examination of the recycled paper products purchasing behavior (RPPPB), as well as some of the factors that were assumed to affect these specific pro-environmental consumers' choices. Instead of the impact of the customary positive environmental attitudes, this study focused on those negative attitudes, namely Environmental Unconcern, that might be found able to inhibit RPPB. In addition, an effort was made to examine the role of an objective environmental knowledge scale, namely the Eco-literacy scale. A survey among 224 consumers residing in the Municipality of Thessaloniki, Greece was conducted. Multiple regression indicated that just Environmental Knowledge and not the Eco-literacy scale is a predictor of RPPPB. Further, SEM analysis though verified the theoretical assumption that knowledge moderates the relationship between attitudes and behavior. It was concluded that the negative direct relationship between environmental unconcern and the recycled paper products' purchasing behavior strengthens in the group of knowledgeable consumers. Implications are provided for all stakeholders that engage in the recycled paper products market. [ABSTRACT FROM AUTHOR]

In the recent years, the academic paper influence analysis has been widely studied due to its potential applications in the multiple areas of science information metric and retrieval. By identifying the academic influence of papers, authors, etc., we can directly support researchers to easily reach academic papers. These recommended candidate papers are not only highly relevant with their desired research topics but also highly-attended by the research community within these topics. For very recent years, the rapid developments of academic networks, like Google Scholar, Research Gate, CiteSeerX, etc., have significantly boosted the number of new published papers annually. It also helps to strengthen the borderless cooperation between researchers who are interested on the same research topics. However, these current academic networks still lack the capabilities of provisioning researchers deeper into most-influenced papers. They also largely ignore quite/irrelevant papers, which are not fully related with their current interest topics. Moreover, the distributions of topics within these academic papers are considered as varying and it is difficult to extract the main concentrated topics in these papers. Thus, it leads to challenges for researchers to find their appropriated/high-qualified reference resources while doing researches. To overcome this limitation, in this paper, we proposed a novel approach of paper influence analysis through their content-based and citation relationship-based analyses within the biographical network. In order to effectively extract the topic-based relevance from papers, we apply the integrated graph-based citation relationship analysis with topic modeling approach to automatically learn the distributions of keyword-based labeled topics in forms of unsupervised learning approach, named as TopCite. Then, we base on the constructed graph-based paper–topic structure to identify their relevancy levels. Upon the identified relevancy levels between papers, we can support for improving the accuracy performance of other bibliographic network mining tasks, such as paper similarity measurement, recommendation, etc. Extensive experiments in real-world AMiner bibliographic dataset demonstrate the effectiveness of our proposed ideas in this paper. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to retrieve and study the highly cited papers as well as the correlation between the citation frequency and the download frequency of the 20 traditional Chinese medicine journals in China, in order to provide the guidance for improving the influence and academic quality of these journals. Bibliometric analyses were conducted on 1103 papers of 20 traditional Chinese medicine journals from 2011 to 2020 by retrieving for the China Academic Journal Network Publishing Database (CAJD) in China National Knowledge Infrastructure (CNKI). SPSS 17.0 software was used to analyze the correlation between the citation frequency and the download frequency via conducting regression fitting and establishing the mathematical models. The results showed that the total citations of the 1103 papers were 93051 times and the average citations were 84.36 times per paper. The total downloads of the 1103 papers were 2058442 times, and the average downloads were 1866.22 times per paper. China Journal of Chinese Materia Medica ranked first according to the number of papers, total citations and total downloads. The citations of Journal of Chinese Medicinal Materials ranked first based on the number of citations per paper. One of Li's paper had been cited the most (983 times). There were 629 (57.03%) papers whose first author was from universities. The scopes of the first authors were distributed in 29 regions and 2 special administrative regions (Macao, Hong Kong) in China. The authors from Beijing published 283 (25.66%) papers, ranking number one. The number of papers supported by funds was 882 (79.96%). The research results of correlation showed that the citation frequency and the download frequency of the highly cited papers had a highly positive correlation from both journal and paper level for whether the sample data of journals was normally distributed or nonnormally distributed. The correlation coefficients of the 20 journals at journal level and that at paper level were 0.9765 and 0.6677, respectively. The correlation was better at journal level than that at paper level, while the optimal regression fitting was all cubic polynomial. Among the 1103 papers, there were 684 (62.01%) research papers and 419 (37.99%) review papers. The main citation period of the top 15 papers was from the 2nd year to the 6th year after publication, accounting for 78.39%. Papers on clinical therapeutics research, papers on the pharmacological effects and its mechanism of traditional Chinese medicine, and papers on traditional Chinese medicine and natural medicine were the main source of the highly cited papers of the traditional Chinese medicine journals. Editors of the journals should focus on the above-mentioned research areas to select manuscripts for exploiting the excellent sources extensively, while paying attention to review papers, focusing on national major or key projects, paying attention to network spreading, stabilizing authors with quality services, in order to improve the influence and the academic quality of journals. [ABSTRACT FROM AUTHOR]

The feeding unit is an important functional part in the paper industry that requires the development of effective maintenance plan based on its reliability analysis. This study analyzes reliability of the considered unit employing trapezoidal fuzzy numbers in fuzzy λ – τ methodology with Petri net modeling. In this analysis, the collected crisp input data of each subsystem has been fuzzified using trapezoidal fuzzy numbers. Then fuzzy values of several reliability factors of feeding unit, namely, failure rate, repair time, reliability, availability, etc. at ±15%, ±25% and ±40% spread levels have been calculated. Further, the obtained fuzzy values of reliability factors have been defuzzified to analyze system behavior of feeding unit. The analysis is useful for plant maintenance and operation management to understand the behavior of feeding unit in a more realistic manner. [ABSTRACT FROM AUTHOR]

The paper industry supply chain is highly complex and consists of many processes and planning tasks. It starts with the collection of raw wood and ends up in different paper products from paperboard to high class art papers. Managing the supply chain is difficult and the permanently changing business environment constantly brings new challenges. This paper starts with outlining the challenges in the supply chain management of today's paper industry. After that we evaluate the state of research to determine planning problems covered by the literature. The purpose is to catch up time-wise on the previous overview from 2009 and also to update the planning problems. This overview paper summarizes comprehensively the paper industry as of today. It provides a reference work for researchers and other interested parties, and uncovers areas for future research. [ABSTRACT FROM AUTHOR]

The work aims to explore a microscopic observation system of paper surface and achieve high-precision stereoscopic observation with detail characterization of paper surface morphology. Based on the DT-400E precision program-controlled three-dimensional translation stage and KEYENCE LJV-7200 two-dimensional laser scanner, the hardware parts of our own system are developed to scan and transmit point cloud data of paper surface morphology to the computer. The corresponding system software will automatically process the point cloud data acquired from the laser scanner and generate the corresponding vivid 3D model and height histogram. This system scans and characterizes four different types of paper samples, allowing the human eye to visually distinguish the differences in surface morphology as well as automatically calculate the numerical differences in paper surface morphology parameters. The results of the applicability test show that the system is highly efficient in acquiring, observing, and evaluating the topography of the paper surface. The system can not only predict the paper surface quality of printed paper, but can also be extended to the evaluation of 3D printed surfaces. [ABSTRACT FROM AUTHOR]

Incessant streak of unsuccessful attempts to synthesize low cost graphene with larger flake size and purity is frequently reported. Any reported methods that result in few layers of graphene with minimal contamination are definitive to exist. In this work, graphene was prepared economically from source of 'paper' and detailed investigation was done on the effect of synthesizing parameters like paper source, temperature and amount of urea in the formation of graphene. This is a cost effective method, in which the paper that we use in our daily life was carbonized with the help of urea at a temperature of 850C under N2 atmosphere. The paper source was varied, shape of the paper was altered and the graphene paper with large surface area was synthesized without smudging and the prepared graphene paper was analyzed by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) for its structural, morphological investigation. To test the supercapacitance performance, electrochemical behavior was investigated in 6M KOH electrolyte. The specific capacitance of 1122F/g was obtained at 5mV/s scan rate. Chronopotentiometry curves showed an excellent cyclic stability with higher charge/discharge duration and hence could be used for electrochemical supercapacitor applications. [ABSTRACT FROM AUTHOR]

The profusion of documents production at an exponential rate over the web has made it difficult for the scientific community to retrieve most relevant information against the query. The research community is busy in proposing innovative mechanisms to ensure the document retrieval in a flexible manner. The document classification is a core concept of information retrieval that classifies the documents into predefined categories. In scientific domain, classification of documents to predefined category (ies) is an important research problem and supports number of tasks such as information retrieval, finding experts, recommender systems, etc. In Computer Science, the Association for Computing Machinery (ACM) categorization system is commonly used for organizing research papers in the topical hierarchy defined by the ACM. Accurately assigning a research paper to a predefined category (ACM topic) is a difficult task especially when the paper belongs to multiple topics. In this paper, we exploit the reference section of a research paper to predict the topics of the paper. We have proposed a framework called Category-Based Category Identification (CBCI) for multi-label research papers classification. The proposed approach extracted references from training dataset and grouped them in a Topic-Reference (TR) pair such as TR {Topic, Reference}. The references of the focused paper are parsed and compared in the pair TR {Topic, Reference}. The approach collects the corresponding list of topics matched with the references in the said pair. We have evaluated our technique for two datasets that is Journal of Universal Computer Science (JUCS) and ACM. The proposed approach is able to predict the first node in the ACM topic (topic A to K) with 74% accuracy for both JUCS and ACM dataset for multi-label classification. [ABSTRACT FROM AUTHOR]

This paper provides a review of the literature on rigorous definitions and constructions in quantum field theory (QFT), spanning the period of seven decades. Compared with the ideas and constructions found in the modern physics literature, we conclude that none of the existing systems of QFT axioms can cover all the physical situations. Therefore, it is still an outstanding open problem to formulate a complete definition of QFT. We argue that the question is of relevance for both physicists and mathematicians. [ABSTRACT FROM AUTHOR]

The oil-immersed transformer is a crucial piece of equipment in the power system. Operating at the specified temperature is necessary to ensure the normal operation of the transformer. The insulation paper on the winding surface has a significant impact on the actual temperature of the transformers, which is often overlooked by researchers. The one-dimensional steady-state heat conduction model of the transformer is established by analyzing the heat diffusion process of winding to transformer oil. Atomic force microscope was used to observe the microsurface structure of insulation paper and copper. According to the experiment, the heat transfer resistance in the series process of heat transfer at 7 0 ∘ C is 0.0138 m2 K/W. Space thermal circuit model of transformer is established by thermoelectricity analogy method, and the simulation circuit is optimized according to the boundary conditions set up in the actual environment. The results show that the error of the hot spot temperature is closer to the measured temperature and decreases by 2.5% when considering the thermal resistance of insulation paper. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries have received considerable attention as energy storage tool for modern-life equipments. However, drawbacks like low electric conductivity and volume expansion are the obstacles that hinder its application. To solve these problems, we developed a facile method using waste eggshell as hard template to reduce its particle size and change its morphology by simple hydrothermal process. Then, by utilizing waste paper, conductive paper (CP) current collector with graphene and multiwalled carbon nanotube implanted was prepared and combined with MnO2 anode material. The composite anode shows extraordinary electrochemical performances like much smaller impedance, high reversible capacity of 1767/1762 mAh/g even after 200 cycles at 100 mA/g, superior rate performance, etc. Compared with anode using metal current collectors, this composite anode will reduce weight and can be generalized to other high energy storage applications. Our environment-friendly method has far-reaching referential significance to other active materials and battery systems. A composite electrode, with δ -MnO2 as active material and conductive paper as current collector, has been synthesized and used in lithium-ion battery. Waste eggshell and waste paper were used in the synthetic process to protect environment. The electrode is much lighter and has much better electrochemical performances. This method can be generalized to other active materials and battery systems. [ABSTRACT FROM AUTHOR]

The MINimal emission FLUXes (MINFLUX) technique in optical microscopy, widely recognized as the next innovative fluorescence microscopy method, claims a spatial resolution of 1–3 nm in both dead and living cells. To make use of the full resolution of the MINFLUX microscope, it is important to select appropriate fluorescence probes and labeling strategies, especially in living-cell imaging. This paper mainly focuses on recent applications and developments of fluorescence probes and the relevant labeling strategy for MINFLUX microscopy. Moreover, we discuss the deficiencies that need to be addressed in the future and a plan for the possible progression of MINFLUX to help investigators who have been involved in or are just starting in the field of super-resolution imaging microscopy with theoretical support. [ABSTRACT FROM AUTHOR]

Nonlinear optical imaging is a versatile tool that has been proven to be exceptionally useful in various research fields. However, due to the use of photomultiplier tubes (PMTs), the wide application of nonlinear optical imaging is limited by the incapability of imaging under ambient light. In this paper, we propose and demonstrate a new optical imaging detection method based on optical parametric amplification (OPA). As a nonlinear optical process, OPA intrinsically rejects ambient light photons by coherence gating. Periodical poled lithium niobate (PPLN) crystals are used in this study as the media for OPA. Compared to bulk nonlinear optical crystals, PPLN crystals support the generation of OPA signal with lower pump power. Therefore, this characteristic of PPLN crystals is particularly beneficial when using high-repetition-rate lasers, which facilitate high-speed optical signal detection, such as in spectroscopy and imaging. A PPLN-based OPA system was built to amplify the emitted imaging signal from second harmonic generation (SHG) and coherent anti-Stokes Raman scattering (CARS) microscopy imaging, and the amplified optical signal was strong enough to be detected by a biased photodiode under ordinary room light conditions. With OPA detection, ambient-light-on SHG and CARS imaging becomes possible, and achieves a similar result as PMT detection under strictly dark environments. These results demonstrate that OPA can be used as a substitute for PMTs in nonlinear optical imaging to adapt it to various applications with complex lighting conditions. [ABSTRACT FROM AUTHOR]

We report on the fabrication of zinc oxide (ZnO) nanorod-based flexible, cost-effective single electrode triboelectric nanogenerator (STENG) on cellulose paper platform. In particular, the influence of surface functional groups of ZnO nanorods on the STENG output has been investigated. The STENG has been designed with chemically grown ZnO nanorod-coated paper as active triboelectric layer and Teflon/ Aluminum as counter triboelectric layer/ electrode. It has been found that post-annealing of nanorods at 125∘C improves the output voltage by twice compared to the pristine nanorods and delivers an output power of ∼ 0. 2 μ W/cm2. With annealing up to 125∘C, the optimal removal of the chemisorbed water from the defect sites of ZnO surface increases the intrinsic carrier concentration leading to maximum charge transfer and hence higher triboelectric output. On the other hand, a higher extent of oxygen accumulation from air at 150∘C lowers the intrinsic carrier concentration resulting in the reduced output. It has been proposed that the competition between the events like water removal and oxygen accumulation under different annealing temperatures can influence the STENG output largely. Finally, the optimized STENG has been demonstrated to work as wearable bio-mechanical sensors operating through bio-mechanical stimuli. [ABSTRACT FROM AUTHOR]

The editorial in Volume 10 Issue 3 of Water Economics & Policy discusses five research papers that address various aspects of water scarcity, water quality, and water use efficiency. The papers cover topics such as groundwater scarcity, drought impacts, water pricing for conservation, ecological footprints of water, and coastal water quality regulations. Each paper utilizes different methodologies and provides theoretical, empirical, and policy components. The findings from these papers can inform policy decisions at regional and national scales, offering valuable tools for policy evaluation and implementation. [Extracted from the article]

With the prevalence of artificial intelligence technologies, big data has been utilized to higher extent in many cross-domain fields. This paper concentrates on the digital assessment of vocational education level in some specific areas, and proposes a graph neural network-based assessment model for this purpose. Assume that all vocational colleges inside a specific region are with a social graph, in which each college is a node and the relations among them are the edges. The graph neural network (GNN) model is formulated to capture global structured features of all the nodes together. The GNN is then employed for the sequential modeling pattern, and the evolving characteristics of all the colleges can be captured. Some experiments are also conducted to evaluate the performance of the proposed GNN-VEL. It is compared with two typical forecasting methods under evaluation of two metrics. The results show that it performs better than other two methods. [ABSTRACT FROM AUTHOR]

The paper focuses on the cutting behavior of Glass Fiber Reinforced Polymer (GFRP) composites and GNP–GFRP composites that contain varying amounts of Graphene Nano Platelets (GNP). GFRP composites are increasingly being used in a variety of industrial applications due to their excellent mechanical properties, such as high strength, stiffness, and low weight. However, their machining and cutting behavior can be challenging due to the presence of the reinforcing fibers. Therefore, the study aims to investigate the machining behavior of GFRP composites and the effect of adding GNP on their cutting behavior. The effect of different parameters such as cutting speed, feed rate and reinforcement rate on cutting forces and delamination factor is investigated. In addition, the tensile strength and fatigue behavior of the composite materials with the best and worst delamination factors were also determined. Addition of up to 0.2 wt.% of GNP to GFRP composites resulted in an increase in cutting forces and delamination factor when drilling GFRP composites. While the cutting force and delamination factor decreased with the increase in cutting speed, the cutting force and delamination factor increased with the increase in the feed rate. Analysis of variance (ANOVA) was performed to determine the effects of drilling parameters and reinforcement ratio on cutting force and delamination factor according to full factorial experimental design. The most efficient factor on the cutting forces is found to be feed rate (84.97%), followed by the reinforced rate (6.48%) and cutting speed (6.13%). The most efficient factor on the delamination factor is determined to be feed rate for (44.49%), followed by the reinforced rate (29.20%) and cutting speed (21.73%). [ABSTRACT FROM AUTHOR]

A nanoflower structure of Zn 0. 7 6 Co 0. 2 4 S directly grown on carbon fiber papers (CFP) was successfully designed by a mild two-step hydrothermal method. Benefiting from their fascinating structural features, Zn 0. 7 6 Co 0. 2 4 S/CFP electrode exhibits a maximum specific capacitance of 300 F g − 1 at current density of 1 A g − 1 and 84% capacitance retention after 5,000 cycles at current density of 5 A g − 1 . Subsequently, Zn 0. 7 6 Co 0. 2 4 S/CFP//AC all-solid-state asymmetric supercapacitor (ASC) device is assembled and able to illuminate the red LEDs. ASC devices deliver a maximum energy density of 9.59 W h kg − 1 at a power density of 750 W kg − 1 . Therefore, this impressive result demonstrates that the nanoflower Zn 0. 7 6 Co 0. 2 4 S have promising applications in the development of high-performance supercapacitors. Zn0.76Co0.24S/CFP was obtained using two-step hydrothermal method. Its microstructure presents a novel nanoflower arrays. The synergistic effect between Zn0.76Co0.24S nanoflower and CFP improves the electrons transport efficiency, conductivity and structural stability of the hybrid. The as-prepared Zn0.76Co0.24S/CFP electrode delivers a specific capacitances of 300 F g−1 and exhibits an excellent cycling stability (retaining 84% after 5000 cycles) as well as a high energy density of 9.59 W h kg−1. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease — COVID-19 is a historic catastrophe that has caused many devastating impacts on human life and wellness. Researchers in academia and industry strive to understand the causes of this pandemic disease and find new therapeutics combating it. Consequently, the number of COVID-19 related publications increases rapidly, and it is too difficult for medical researchers and practitioners to keep up with the latest research and development. Literature filtering and categorization, and knowledge discovery can use text mining as a powerful tool. In this paper, we propose a text mining method to explore the categories of COVID-19 related themes and identify the standard methodologies that have been used. We discuss the potential limitations of this preliminary study and present future perspectives related to COVID-19 research. This paper provides an quantitative and qualitative mixed analysis example of using some research papers by data mining method to dig out several hidden information and set up a foundation for data scientists to develop more effective algorithms to deal with COVID-19 related problems. [ABSTRACT FROM AUTHOR]

The European Water Framework Directive (WFD) is one of the most analyzed environmental legislations in the scientific literature, influencing the water management in some non-European countries. The WFD has the strong ambition of achieving a good ecological status of water bodies across all river basins in Europe. However, the advances towards sustainable management are falling far behind the planned schedule. The emphasis of the Directive is focused on water quality rather than on water quantity. The advances during the last quarter of the century since its inception have been strong on urban and industrial point pollution, but not on agricultural non-point pollution that remains high and even increases in major basins. Water quantity aspects have been mostly left aside in the Directive, despite the fact that water scarcity is a serious problem in Southern European countries, and will become more critical with climate change in most basins across Europe. Some policy measures of the WFD need to be reformed, in particular measures for abating agricultural pollution, and new measures for addressing water scarcity. The narrow focus of the WFD on water pricing to solve at the same time issues of financing, water allocation and efficiency, environment, opportunity costs and pollution abatement, should be broadened. The challenge is giving more emphasis to command & control and collective action instruments, and designing combinations of instruments adapted to sectoral and spatial locations in basins. This overhaul of the water policy instruments by the European Commission will be needed to advance in the sustainable management of river basins in Europe. [ABSTRACT FROM AUTHOR]

The manufacturing procedures of sandwich composites containing corrugated paper (CP) as a core layer and covered with glass fabrics are discussed herein. The core layer of the sandwich composite was fabricated with CP-reinforced epoxy (E) resin and then stacked with glass fabric on the top and bottom surfaces to fabricate the sandwich composites. Three composites [a CP-reinforced E (CP/E) composite, glass fiber nonwoven mat (GN) sandwich composite with a CP core layer (GN/E/CP) and glass mesh fabric (GM) sandwich composite with a CP core layer (GM/E/CP)] were developed in this study. The bending and compression properties of these sandwich composites were measured on a materials test system. Experimental results revealed that the bending strength of the GN/E/CP sandwich composite was approximately 45% and 150% higher than those of the GM/E/CP and CP/E sandwich composites, respectively. [ABSTRACT FROM AUTHOR]

To address the issues in clothing pattern style migration, this paper proposes a digital simulation and re-editing method for clothing patterns based on deep learning and somatosensory interaction. First, the proposed method encodes the black-and-white line drawing image, generating random noise images through a diffusion process, introducing color information for synthesis, and using a decoder to reconstruct a colored image. Afterwards, an improved VGG19 model is used to reconstruct content features and perform linear color transformation on style images, enabling pattern style migration through the construction of a Gram matrix and resulting in colored clothing texture patterns. Finally, a KinectV2 is utilized for fabric simulation, overlaying colorful clothing texture patterns to achieve 3D virtual dressing. The experimental results show that the proposed method improves the structural similarity index measure (SSIM) by 9–11% and the peak signal-to-noise ratio (PSNR) by 3–8% when compared to existing algorithms. The experiments provide evidence that the proposed method effectively mitigates color overflow, delivers precise image coloring, and accomplishes realistic restoration of clothing texture. Furthermore, the method offers an improved garment fit to fulfill the user's interaction requirements. [ABSTRACT FROM AUTHOR]

This paper presents a new processing method to produce nanotube reinforced composites by using single-walled nanotube (SWNT) bucky paper as reinforcement. The SWNT bucky paper is an entangled mat of SWNTs, which is a highly porous mesh structure. To successfully produce SWNT bucky paper reinforced composites, it is essentially important to prepare a high-quality bucky paper. In this study, the quality of the bucky paper related to the dispersion of nanotubes within the bucky paper, which was quantitatively-characterized with rope size distribution and pore size distribution. An experimental study was conducted to investigate the effects of various process parameters on the dispersion of nanotubes using design of experiments (DOEs) approach. Based on the experimental analysis, the dispersion process of nanotubes within the bucky paper was optimized by selecting appropriate process parameters. [ABSTRACT FROM AUTHOR]

This document is a guest editorial from the International Journal of Semantic Computing, discussing a special issue on Transdisciplinary Artificial Intelligence. The special issue includes seven papers, four from the 5th IEEE International Conference on Transdisciplinary AI and three from the 6th International Conference on Artificial Intelligence for Industries. The papers cover a range of topics, including future visioning in AI research, utilizing satellite imagery to predict socioeconomic indicators, smart city wildfire risk analysis, leveraging community health workers for predicting emergency department readmissions, optimization of 2D irregular packing using deep reinforcement learning, real-time sampling strategies for regression, and efficient dynamic IC design analysis using graph-based semi-supervised learning. The papers underwent a rigorous review process and have been extended with new and unpublished materials. The authors present their findings and highlight the potential applications and implications of their research. [Extracted from the article]

Organic transistors are crucial components in future flexible electronics due to their excellent properties and ease of circuit integration. Previously, we demonstrated that flexible organic (polyimide) thermal transistors could be prepared using commercial graphite paper as the substrate. These materials exhibited excellent temperature sensitivity, linearity and recoverability due to the intrinsically high thermal conductivity of graphite. In this study, boron nitride (BN) sheets/polyimide hybrid dielectric layers were synthesized for the fabrication of flexible organic transistors using a commercial graphite paper. Under test, the results showed that the introduction of BN sheets was beneficial in improving the mobility and transistor characteristics of the device, as well as enhancing the overall stability. The as-fabricated transistors virtually exhibited no hysteresis at all BN contents. Boron nitride (BN) sheets were added to the fluorinated polyimide (FPI) matrix to form hybrid dielectric layer for improving the performance of flexible organic transistors fabricated on commercial graphite paper. The results showed that the device with BN/FPI hybrid dielectric layer exhibited higher output current (Id) and stability. Besides, the devices remained hysteresis-free at all tested BN sheet contents. [ABSTRACT FROM AUTHOR]

The waterproof and flame-retardant properties of corrugated paper (CP) reinforced epoxy resin sandwich composites are discussed. Two composites, a CP-reinforced epoxy composite (CP/E composite) and a CP-reinforced flame-retardant epoxy composite (CP/FRE composite), were developed in this study. A dipping bath was developed for impregnating the paper with epoxy and a flame-retardant epoxy solution to make the CP/P and CP/FRE composite panels. A room-temperature-cured epoxy resin was blended with various contents (10%, 20%, and 30%) of phosphorus-based flame-retardant compounds and then was used as a matrix to make CP/FRE-10, CP/FRE-20, and CP/FRE-30 composite materials. Water absorption tests of these composites were used to estimate the waterproof properties. In addition, vertical and horizontal burning tests were used to evaluate the flame-retardant properties of the composites. [ABSTRACT FROM AUTHOR]

The tensile and compressive properties of jute fabric and corrugated paper (CP)-reinforced polylactic acid (PLA) resin sandwich composites are discussed. A core layer was fabricated with CP-reinforced PLA resin. The core later was then stacked with jute fabric and PLA films on the top and bottom surfaces to fabricate the sandwich composites. Two composites, a CP-reinforced PLA composite (CP/PLA composite) and a jute fabric/PLA sandwich composite with CP as a core layer (J/PLA/CP composite) were developed in this study. A dipping bath was developed for impregnating the paper with a molten PLA solution to make the CP/PLA composite core layer. The resin film method was used to fabricate the jute fabric/PLA/CP sandwich composite on a hot press machine. A material test system (MTS810) was used to evaluate the tensile, flatwise compression, and longitudinal compressive characteristics of the composites. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the impact of moisture on mechanical properties of insulation paper. According to the molecular modeling approach proposed by Theodorou, the amorphous cellulose models of insulation paper with different moisture contents were built up to calculate mechanical parameters and hydrogen bond networks. And relevant conclusions could be drawn through further analysis on these calculation results: water molecules can destroy hydrogen bond network between the neighboring cellulose molecules, which might be responsible for the significant decrease of Young's modulus and other mechanical parameters, while no appreciable effect of intramolecular hydrogen bonds on mechanical properties was detected. Thus tensile tests were also carried out to study the moisture influence on the Young's modulus, by which the result of the simulation was approved. [ABSTRACT FROM AUTHOR]

Despite the resistance-type gas sensors attracting intensive research interest, the vulnerability to the interference of humidity is a great challenge for their large-scale productions and applications. Herein, a convenient "gas-sensitized sensing material + adhesive" approach for the fabrication of superhydrophobic interface has been proposed to settle the problem. The multiwalled carbon nanotubes (MWCNTs)/styrene-ethylene/butylene-styrene block copolymer (SEBS) layer formed by spraying the cyclohexane suspension of MWCNTs and SEBS with micro/nanostructure endows the sensor with outstanding superhydrophobic property, presenting that the apparent contact angles (CA) are up to 179.6∘. The superhydrophobic paper sensor exhibited high sensing performance for acetone vapor and most importantly exceptional anti-humidity. The response of as-prepared sensor for other gaseous chemicals was consistent with that of MWCNTs, which indicated that the "gas-sensitized sensing material + adhesive " approach did not change the MWCNTs gas-sensitive characteristics. The approach builds an efficient bridge between gas-sensitive particles and flexible, superhydrophobic systems, inspiring a new simple way to the development of gas sensor with high immunity to humidity. A convenient "gas sensitized sensing material + adhesive" approach was proposed to form superhydrophobic paper sensor, which not only has outstanding superhydrophobic property, presenting that the apparent contact angle is up to 179.6∘, but also preserves the gas sensitized sensing material origin gas-sensitive characteristics. [ABSTRACT FROM AUTHOR]

In this study, we report the findings that the C-N composites containing Ni and Co (Ni1Co1/C-N, Ni3Co1/C-N, Ni6Co1/C-N, Ni9Co1/C-N, NiCo0/C-N and Ni0Co/C-N) can be produced by direct pyrolysis of the NiCo-doped polyaniline (PANI) precursors in N2 atmosphere at 800C and show efficient electroactivity for oxygen reduction reaction (ORR) in alkaline media. Distribution and compositions of the catalysts were characterized by SEM, TEM, EDS and XRD techniques. The catalysts were loaded on carbon paper to prepare gas diffusion electrodes, in which electrocatalytic activity for ORR in alkaline media was investigated by voltammetric techniques. The ORR current density on these carbon paper-supported NiCo/C-N catalysts exhibits a linear increase with the negative shift of ORR potential. The ORR onset potential is around 0.2V (versus Ag/AgCl) in alkaline media. Among the prepared catalysts, the catalyst Ni6Co1/C-N presents the largest ORR current density, which is 68.5mAcm@0.8V (versus Ag/AgCl) in alkaline media. Moreover, Ni6Co1/C-N catalyst also presents good electrocatalytic activity stability for ORR. Ni/Co-doped C-N nanocomposite catalysts were prepared by direct pyrolysis of the mixture containing Ni/Co salts and polyaniline. The electrochemical test mold was used to study the ORR activity of the catalysts NiCo/C-N loaded on carbon paper. One side of the carbon paper modified with catalyst was in contact with the electrolyte while the other side was in contact with air. Among the prepared catalysts, the Ni6Co1/C-N catalyst shows the largest ORR current density of 68.5 mA cm-2@-0.8 V and high activity stability of ORR in alkaline media. [ABSTRACT FROM AUTHOR]

In this paper, an analysis of the precision of range sensors is presented. Light Detection and Ranging (LIDAR) data from three different sensors (HLS-LFCD-LDS, SICK TIM561, and Kinect V2), stereo data from the Realsense D435, and structured light data from both Kinect V1 for Xbox and the Xtion PRO Live were analyzed regarding the influence of range, incident angle to the surface, and surface material. In addition, a comparison with standard deviation models based on vendor-provided specifications was performed. We found that the vendor specifications are in general not specific enough to facilitate accurate sensor simulations. Therefore, we developed a data-driven model for range precision. Our model can be used to create realistic sensor simulations and to develop robot navigation algorithms weighing sensor range readings based on the precision. [ABSTRACT FROM AUTHOR]