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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 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]

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]

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]

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]

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]

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]

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 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]

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]

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 paper aims to comprehensively explore the pivotal role of simulation and modeling in the field of Artificial Intelligence (AI). It focuses on elucidating the diverse applications of simulation and modeling in training AI systems, optimizing algorithms, and enhancing decision-making processes. To achieve this objective, we conducted an extensive review of the literature from the Scopus database, employing a well-defined selection process. We utilized keywords such as "simulation," "modeling," "Artificial Intelligence," and related terms to identify relevant papers published within the last 10 years. The selection criteria included assessing the relevance, quality, contribution, and recent citations of the papers. After a rigorous screening process, we selected 40 papers with the highest overall scores for inclusion in our review. The selected papers encompass a wide range of domains where simulation and modeling play a vital role in advancing AI applications. These domains include manufacturing, healthcare, energy consumption prediction, public sector decision-making, education, environmental modeling, and more. Our review highlights how AI leverages simulation and modeling to improve predictive accuracy, optimize resource allocation, and enhance decision-making processes across diverse sectors. We also discuss the potential future directions in the integration of simulation and modeling with AI, emphasizing its significance in various fields. [ABSTRACT FROM AUTHOR]

The maximum vibration transmissibility of paper honeycomb sandwich structures with different sizes of honeycomb core under various static stresses was investigated using the sine frequency sweep test. The effects of the cell length of the honeycomb, the thickness of the sandwich structure, and the static stress on the maximum vibration transmissibility were evaluated and a linear polynomial equation for evaluating the maximum vibration transmissibility was obtained. The results show that the maximum vibration transmissibility increases steadily with the increase in the cell length of the honeycomb, the thickness of the sandwich structure, and the static stress. The proposed equation for the maximum vibration transmissibility is suitable for predicting the maximum vibration transmissibility of paper honeycomb sandwich structures. In addition, the fitted three-dimensional diagrams of the effects of the factors on the maximum vibration transmissibility derived from the evaluation equation were shown to be in good agreement with the experimental results. [ABSTRACT FROM AUTHOR]

In this work, a solely gravity and capillary force-driven flow chemiluminescence (GCF-CL) paper-based microfluidic device has been proved for the first time as a new platform for inexpensive, usable, minimally-instrumented dynamic chemiluminescence (CL) detection of chromium (III) [Cr(III)], where an appropriate angle of inclination between the loading and detection zones on the paper produces a rapid flow of CL prompt solution through the paper channel. For this study, we use a cost-effective paper device that is manufactured by a simple wax screen-printing method, while the signal generated from the Cr(III)-catalyzed oxidation of luminol by H2O2 is recorded by a low-cost and luggable CCD camera. A series of GCF-CL affecting factors have been evaluated carefully. At optimal conditions, two linear relationships between GCF-CL intensities and the logarithms of Cr(III) concentrations are obtained in the concentration ranges of 0.025–35 mg/L and 50–500 mg/L separately, with the detection limit of 0.0245 mg/L for a less than 30 s assay, and relative standard deviations (RSDs) of 3.8%, 4.5% and 2.3% for 0.75, 5 and 50 mg/L of Cr(III) (n = 8). The above results indicate that the GCF-CL paper-based microfluidic device possesses a receivable sensitivity, dynamic range, storage stability and reproducibility. Finally, the developed GCF-CL is utilized for Cr(III) detection in real water samples. [ABSTRACT FROM AUTHOR]

Drying of a coated paper is modeled and simulated. The paper sheet is assumed to form three zones, and each zone has its own drying mechanism. Coupling of energy and mass balances must be used in order to solve differential equations. The simulations are carried out in various drying conditions i.e., only hot air drying, only radiant drying, and mixed hot air-radiant drying. Also the effect of one side and two side assumption on evaporation is studied. Effect of venting air speed and radiant heat source presence and its distance from the drying surface on the drying of a coated paper has been studied. It is found that both distance and venting air speed are inversely related to drying in mixed hot air-radiant drying. Both surfaces participate in evaporation however, during the last time of drying, no difference between the upper and the bottom surfaces exist. [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]

The colorimetric method is usually used to test the concentration of substances. However, this method has a big error since different people have different sensitivities to colors. In this paper, in order to solve the identification problem of the color and the concentration of the test paper, firstly, we found out that the concentration of substance is correlated with the color reading by using the Pearson's Chi-squared test method. And by the concentration coefficient of Pearson correlation analysis, the concentration of substance and color reading is highly correlated. Secondly, according to the RGB value of the paper image, the color moments of the image are calculated as the characteristics of the image, and the Levenberg–Marquardt (LM) neural network is established to classify the concentration of the substance. The accuracy of the training set model is 94.5%, and the accuracy of the test set model is 87.5%. The model precision is high, and the model has stronger generalization ability. Therefore, according to the RGB value of the test paper image, it is effective to establish the LM neural network model to identify the substance concentration. [ABSTRACT FROM AUTHOR]

Concerns about sustainability challenges are growing. Companies are under pressure to rethink existing innovation paradigms. In this context, research interest in the resource-constrained innovation concept, frugal innovation, has increased. In this paper, we examine the impact of frugal innovation on the economic, social, and ecological sustainability dimensions by conducting a systematic literature review of 44 papers. We find that frugal innovation is a promising approach to promote sustainable development from an economic perspective and a social perspective. Nevertheless, positive and negative effects exist in all three dimensions. Thus, a positive relationship is not inherent but must be proactively formed. External factors can influence the impact of frugal innovation on sustainability. For future research we recommend (1) establishing a unified understanding of frugal innovation through a clear definition, (2) broadening the research focus to a global perspective, (3) assessing the impact of frugal innovation along the entire product life cycle, and (4) investigating characteristics that make frugal innovation sustainable. [ABSTRACT FROM AUTHOR]

Continual development necessitates innovation. One must discover seeds of innovation and then concentrate resources on these seeds. To do so, one must recognize technology trends and then adopt and execute appropriate innovation strategies. This study used advanced change point detection method to investigate leading indicators that represent changes in technology trends. We examine patents, papers, and newspaper articles in Japan and US for 55 technologies. Results suggest that patents can be more appropriate as leading indicators than either papers or newspapers. This result can contribute to appropriate innovation strategies for planning and updating, and can provide tools that are useful to decision-makers. [ABSTRACT FROM AUTHOR]

Ecotourism potential is a fundamental research effort needed to promote sustainable regional tourism development, and scholars have paid greater attention to it in recent years, which has led to an increase in the publication of literature on this important and widely recognized topic. However, there is still no clear picture of the development direction of research on ecotourism potential. To address this issue, this study attempts to provide a comprehensive analysis of the existing research state in this field. This paper presents a more detailed review of ecotourism potential, a bibliometric analysis of 949 articles selected from 1,027 publications retrieved from the Web of Science Core Collection database, and a systematic descriptive and network analysis of the bibliometric data using the Biblioshiny tool. Here are some interesting findings: (1) research on the ecotourism potential in the academy started in 1992, with a rapid growth in the number of publications after 2013, with an overall interdisciplinary character and the emergence of a research community represented by Milcu, Balmford, Gallagher, and others; (2) ecotourism, conservation, tourism, management, and biodiversity are high-frequency keywords in this field, revealing the main research directions; (3) the development and evolution of research focus are mainly on three aspects: wildlife and biodiversity conservation, nature-based tourism and environmental values, and the modes and contributions of community participation. Future research should focus on the scientific references of ecotourism potential for promoting regional sustainable development. This paper sheds some light on the comprehensive bibliometric studies on ecotourism potential and improves our understanding of the evolution of this academic discourse theme over the last three decades. [ABSTRACT FROM AUTHOR]

Nowadays, environmental problems have attracted the attention of many craftsmen and researchers. They have developed various policies and practices to protect the environment throughout the supply chain. Since suppliers are one of the supply chain partners, paying attention to these policies by them will be very effective in keeping the supply chain green. In today's dynamic environment, there is uncertainty in all decisions of the organizations. The wood and paper industry also faces uncertainty in choosing green and environmentally friendly suppliers. These uncertainties must be taken into account when selecting suppliers. Decision-making techniques will cover uncertainty if developed in a gray environment. Many techniques have been developed in a gray environment. But using a combination of DANP and MABAC techniques in a gray environment will be very useful because of the benefits of each. Therefore, using the combination of DANP and MABAC in a gray environment in order to select a green supplier in the wood and paper industry is a gap that is felt and in this paper we try to overcome it. The research findings show that the identified criteria will be very effective in selecting the green supplier and Gray DANP–MABAC can be used for managers' decisions in the wood and paper industry. [ABSTRACT FROM AUTHOR]

Evolutionary studies of cultural complexity often assume that group members select the best information available in the group, effectively diffusing the best innovations, whose advantages are subsequently passed on to the next generation. This would seem to describe the ideal of the scientific process — each cohort of papers in a field surfacing the best innovations, refining them and passing on to the next "layer" or cohort of scientific works. Here, we use academic journal databases to explore this "forking" (branching) process in the evolution of a scientific paradigm. We apply citation network visualization and Latent Dirichlet allocation topic analysis to three different paradigms defined pragmatically as the set of papers citing a highly influential paper in each respective case. Our three case studies indicate a founder effect in how the seminal paper is highly-embedded in the citation network, and yet peripheral to the evolution of topics in subsequent "layers" of publications within the paradigm. This and additional evidence suggest certain topics are selected and followed, while others are left behind. From these case studies, we discuss how hitherto undeveloped ideas of the past might be located in the topic space of seminal works of the same fruitful time period. [ABSTRACT FROM AUTHOR]

The International Journal of Semantic Computing has published a special issue on Semantic Computing, which includes five selected papers from the 17th IEEE International Conference on Semantic Computing. Semantic Computing focuses on the derivation, description, integration, and use of semantics for various resources. The papers in the special issue cover topics such as intent detection, constructing probabilistic models from knowledge graphs, unsupervised estimation of subjective content descriptions, the influence of noisy labels on question answering systems, and automatic domain-adaptive sentiment analysis. Each paper presents innovative approaches and findings in their respective areas of research. [Extracted from the article]

The Sustainable Development Goals (SDGs) serve as a common aim that brings many nations together, led by the United Nations with the purpose to achieve a set of 17 targets by 2030. One very important factor in achieving these aims is finance. The advancement in financial development all around the world will be able to speed up achieving SDGs where governments, policymakers, and people will be able to grow the economic development and infrastructure of the country, provide adequate job opportunities for many people, reduce poverty, as well as improve sustainability around the world. In opposition to that, some researchers see the advancement in financial development as an activity that will jeopardize achieving SDGs as financial development might lead to the production of carbon footprints at a faster rate. Using bibliometric analysis, this paper was able to discover that there is an increase in attention and interest in the field with the rise in publications in recent years, especially in 2022. Furthermore, this paper also identifies research hotspots within the field while also finding and analyzing the most impactful authors and publications on the topic. Ultimately, this paper hopes to provide a better definition for the relationship between financial development and SDGs with the use of bibliometric analysis, where data is collected from the Scopus database and analyzed using VOSviewer. [ABSTRACT FROM AUTHOR]

With 3D products being widely applied, more attention has focused on studying stereo image super-resolution (SR). Current stereo image SR studies mainly aim to improve the performance by the additional information from a pair of low-resolution stereo images. However, it is challenging for stereo image SR to fully exploit self-similarity information from its own image and parallax information between stereo image pairs. In line with these challenges, this paper presents a Two-Branch Network (TBNet) to integrate self-similarity information and parallax information for SR. In the TBnet, a stereo parallax transfer module with an encoder–decoder structure was first proposed to sufficiently transfer multi-scale parallax information and preserve the stereo consistency between stereo images. This paper further presented a residual pyramid self-attention module to employ self-similarity information to take advantage of self-predictive power. Finally, extensive experiments demonstrate the superiority of our model over the state-of-the-art performance in terms of objective and perceptual quality and the accuracy of disparity estimation. [ABSTRACT FROM AUTHOR]

Traditional requirement verification methods often fail to fully consider the modeling of time-dependent behaviors during system execution, which may lead to inconsistent system requirements, thereby compromise software reliability and correctness. To address this limitation, this paper proposes the Scenario-Specific Verification Method for System Requirements Consistency via Time Modeling. The Scenario-Specific Verification Method converts use case descriptions and problem graphs into Clock Constraint Specification Language (CCSL) constraints, transformed into clock graphs for verifying requirement consistency. The resulting constraints are solved with the Z3 solver to validate correctness, thereby enhancing system reliability. The novel time modeling approach provides techniques for verifying temporal dependencies in requirements. A case study demonstrates the efficiency and accuracy of the Scenario-Specific Verification Method in detecting inconsistencies. The main contributions include that a technique is demonstrated to formalize use case descriptions as CCSL constraints, improving on natural language and a method is presented utilizing CCSL time modeling and clock graphs to analyze requirements for consistency. Overall, an innovative solution for requirement verification using time modeling is offered by this paper, contributing to the enhancement of system development process reliability and correctness. [ABSTRACT FROM AUTHOR]

Amid the pandemic infection, people are bound to use contactless mobile payment (M-Payment) services. M-Payment is a payment method using an application in a mobile device, such as a mobile phone, and gadget. Owing to the convenience, reliability and contact-free feature of M-Payment, it has been diffusely adopted to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating the stabilization of the social economy. Consequently, it has become one of the day's most important topics. Therefore, the purpose of this study is to provide a systematic literature review (SLR) on the applications of M-payment services in financial strategies, focusing on the pandemic crisis. 19 papers were collected and divided into three groups for further analysis. The results showed that M-Payments applications in financial strategies during the pandemic crisis could help reduce the spread of infection risks by hastening the transition to touchless habits. [ABSTRACT FROM AUTHOR]

In recent years, the concurrent occurrences of the COVID-19 pandemic and the Russian invasion of Ukraine have led to global disruptions in supply chains and a surge in commodity prices. Major advanced economies have experienced an increase in inflation rates and a decline in economic activity. Against this economic backdrop, this paper aims to address the strained condition of supply chains by employing the Global Supply Chain Pressure Index (GSCPI) alongside commodity price indices. Furthermore, it seeks to examine how fluctuations in these variables affect Japan's macroeconomic landscape through local projection and structural Vector Autoregression (VAR). In the local projection analysis, it has been observed that the strain on supply chains induces sustained increases in consumer and producer prices, further contributing to long-term declines in production. Within the structural VAR model framework, the identification of structural shocks is conducted through sign restrictions, affirming the significance of supply chain shocks and energy and food price shocks as crucial factors contributing to recent price increases. This confirmation is supported by variance decomposition and historical decomposition analyses. [ABSTRACT FROM AUTHOR]

Despite half a century's extensive scholarly research in the decision-making process of individuals around the adoption of new innovations, innovation practitioners are still not able to capitalise sufficiently on the existing knowledge base to successfully commercialise new products. Evidence of this stems from consumers' continued rejection of new offerings at alarming rates. This makes the marketing of innovation, with a focus on influencing consumers' decision-making process, one of the most challenging corporate challenges for new product managers. To address this gap, this paper sequentially applies a systematic literature review (SLR), followed by extensive descriptive and bibliometric analyses, to reveal and assess the current state of knowledge in this field. Furthermore, the analysis identifies six prominent future research paths that could fill identified gaps in knowledge. Using the results of the bibliometric section, practitioners can pinpoint specific research areas of interest, enabling them to access and utilise findings from past studies more effectively. [ABSTRACT FROM AUTHOR]

Due to increasing environmental regulation and customers' demand for environmentally friendly products, organizations have been required to adopt sustainable manufacturing practices by implementing clean technology (Cleantec) to manufacture green products. By adopting environmental practices, organizations can also achieve qualitative and quantitative benefits that help them remain competitive in the market while meeting governmental environmental policies, such as lowering energy and the cost of materials. The significant number of articles addressing sustainability in manufacturing published in the past few years attests to the importance of the topic. However, not many studies have been developed to understand the decision-making process in sustainable manufacturing. Therefore, the objective of this paper is to conduct a systematic literature review on the application of multi-attribute decision-making (MADM) methods in sustainable manufacturing. A total of 158 papers, published between 2009 and 2018, met the criteria set in the research methodology. The 158 papers were then analyzed and classified into seven categories: (i) SM domain, (ii) activity within the organization, (iii) decision goals, (iv) decision-makers involved (group or individual), (v) uncertain data, (vi) SM aspects (social, environmental, and economic), and (vii) MADM methods. Among the results, we identified that AHP is the most applied MADM method and, regarding the activities of the organization, MADM methods have been the most frequently applied to strategy management and supply chain. We also identified a tendency to consider uncertain and imprecise data in the decision-making process. Another result is that all the three domains — economic, environmental and social — were considered in most of the papers, followed by the combination of the economic and environmental perspectives. In the conclusion, some recent trends and future research directions are highlighted. [ABSTRACT FROM AUTHOR]

In this paper, the method for the design automation of a narrow band-pass amplifier, and hence the amplifier tuned oscillator is discussed. A fixator approach is utilized in this method to design the narrow band-pass amplifiers and a reference circuit is required for this process. The fixator–norator pair helps to generate an extra sub-circuit, generally the feedback network; the addition of this sub-circuit in the actual amplifier circuit will modify the frequency response of the amplifier. The amplifier now behaves like an active narrow band-pass filter, which exactly follows the frequency response of the model circuit. This can be turned into an oscillator by providing positive feedback. Such a circuit possesses independent frequency and amplitude control. Hence, the re-designed circuit can be employed as an active filter or an oscillator at the selected center frequency. In addition to the technical merits, the proposed method has pedagogical importance. Few case studies are worked out in this paper to demonstrate the method. [ABSTRACT FROM AUTHOR]

In the last 30 years, several distinguished researchers have proposed and discussed different fuzzy versions of well-known Saaty's Analytic Hierarchy Process (AHP). The paper recently published by K. Zhü in the European Journal of Operational Research heavily criticizes the fuzzy approaches to AHP, claiming the fallacy of all of them. Therefore, it seems to be necessary to clarify whether the criticisms are well-founded or not. The present paper aims to rebut Zhü's claims by showing that the evidences and the reasonings in his paper are very poor and far from proving the fallacy of fuzzy AHP. [ABSTRACT FROM AUTHOR]

This paper explores citation-based metrics, how they differ in ranking papers and authors, and why. We initially take as example three main metrics that we believe significant; the standard citation count, the more and more popular h-index, and a variation we propose of PageRank applied to papers (called PaperRank), that is appealing as it mirrors proven and successful algorithms for ranking web pages. As part of analyzing them, we develop generally applicable techniques and metrics for qualitatively and quantitatively analyzing indexes that evaluate content and people, as well as for understanding the causes of their different behaviors. Finally, we extend the analysis to other popular indexes, to show whether the choice of the index has a significant effect in how papers and authors are ranked. We put the techniques at work on a dataset of over 260 K ACM papers, and discovered that the difference in ranking results is indeed very significant (even when restricting to citation-based indexes), with half of the top-ranked papers differing in a typical 20-element long search result page for papers on a given topic, and with the top researcher being ranked differently over half of the times in an average job posting with 100 applicants. [ABSTRACT FROM AUTHOR]

In boring operations, tool vibration is a significant parameter which leads to poor surface finish, tool wear and damage of cutting tool. The relative dynamic motion between the cutting tool and work material induces vibration which accelerates tool wear, damage surface finish and produce irritating noise. In order to restrain tool vibration in metal cutting, it is necessary to develop and analyze suitable method which increases stability thereby improving cutting performance. The present investigation aims at developing a smart material controlled boring bar which will respond to an applied field with a dramatic change in rheological behavior. Magnetorheological fluid which was controlled by size of the particle, viscosity of fluid and positioning of rheological fluid is used as smart material in this paper. Magnetorheological fluid was developed and cutting experiments were conducted to arrive at a set of parameters that can reduce tool vibration and promote better cutting performance during boring of hardened AISI 4340 steel. From the results, it was observed that smart material controlled boring bar reduces tool vibration and also improves the cutting performance. [ABSTRACT FROM AUTHOR]

With the economic growth and prosperity, ports and shipping play an increasingly important role in the national economy and international trade. Numerous studies related to the field of port and shipping were conducted to propose some managerial insights. This paper uses the bibliometric method to analyze the research papers published from 2000 to 2019 on port and shipping in the field of management science. The number of published papers, impact score and cite score are identified as evaluation criteria to analyze the research contributions of researchers, affiliated institutions and countries/regions in the port and shipping field. At the same time, the importance of each keyword can be obtained by the bibliometric method, which may help new researchers grasp research hotspots and trends in related fields. [ABSTRACT FROM AUTHOR]

Calendaring is an important operation in pulp and paper mill, with an objective to increase the smoothness or reduce the roughness of paper. Bypassing calendering operation in paper machine, paper of desired quality cannot be produced. In the present investigation, a nip mechanics model for supercalendering has been developed by expanding Meijers nip mechanics model up to fourth term, and using this model the effect of additional fourth term and various design and process parameters on results of supercalendering has been discussed using the data taken from paper industry. [ABSTRACT FROM AUTHOR]

In this paper we present a phenomenological approach to describe a complex systemcolon; scientific research impact through Citation Mining. The novel concept of Citation Mining, a combination of citation bibliometrics and text mining, is used for the phenomenological description. Citation Mining starts with a group of core papers whose impact is to be examined, retrieves the papers that cite these core papers, and then analyzes the bibliometrics characteristics of the citing papers as well as their linguistic and thematic characteristics. The Science Citation Index is used as the source database for the core of citing papers, since its citation-based structure enables the capability to perform citation studies easily. This paper presents illustrative examples in photovoltaics (applied research) and sandpile dynamics (basic research) to show the types of output products possible. Bibliometric profiling is performed over a number of the citing papers' record fields to offer different perspectives on the citing (user) community. Text mining is performed on the aggregate citing papers, to identify aggregate citing community themes, and to identify extra-discipline and applications themes. The photovoltaics applied research papers had of the order of hundreds of citations in aggregate. All of the citing papers ranged from applied research to applications, and their main themes were fully aligned with those of the aggregate cited papers. This seems to be the typical case with applied research. The sandpile dynamics basic research papers had hundreds of citations in aggregate. Most of the citing papers were also basic research whose main themes were aligned with those of the cited paper. This is typically the case with basic research. However, about twenty percent of the citing papers were research or development in other disciplines, or development within the same discipline. In addition, there was a four year lag time between publication and citation by the... [ABSTRACT FROM AUTHOR]

Unreliable suppliers may pose a substantial threat to supply chains, especially when they hold private information of their reliability. We consider a dyadic supply chain where the information of supplier reliability (in the form of random production yield) is asymmetric. We propose a new mechanism-design model and derive the buyer's optimal procurement contract menu offered to suppliers with private information. We prove that the contract menu is as simple as offering two different inflated order amounts and setting the procuring price sufficiently low to let the suppliers earn zero reservation profits. These results are derived analytically under uniform distribution. We test them numerically under beta distribution and find them hold as well. However, the informational rent will become positive when the supplier's reservation profit is positive. Positive informational rent is also found when we consider another structure of the supplier's production cost. This paper provides some new insights into supply chain management under asymmetric information of uncertain supply. [ABSTRACT FROM AUTHOR]

Crowdsourcing is an emerging approach in software development, where software is developed by unknown, heterogeneous people around the globe, via an open call by the employer. Crowdsourcing, when used with agile, faces challenges because of the different development methodologies. Agile development methodology has practices that involve face-to-face frequent interaction, whereas crowdsourcing is a distributed development with no or limited face-to-face interaction. Both concepts are actively being used in the software development industry due to their benefits. However, there is a need to explore the integration of both methodologies for an effective and efficient software development. In this regard, the first step is to identify the challenges of integrating crowdsourcing and agile. In this paper, we intend to identify the possible challenges that may be faced while executing agile along with crowdsourcing. For this, we have conducted a Systematic Literature Review. Five main categories of challenges are presented which are: team issues, coordination and communication issues, organizational issues, project-related issues and task-related issues. A list of possible challenges of Agile–Crowd Software Development (ACSD) is presented in this study. [ABSTRACT FROM AUTHOR]