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The Second Issue of Volume 10 of Water Economics and Policy (WEP) features five research papers that examine various water management challenges at different spatial scales. The papers cover topics such as game theory applied to aquifer sub-basin management in Spain, benefit-cost analysis of river bank erosion investments in Serbia, flood damage assessment models in Turkey, the impact of agricultural production on groundwater depletion in India, and the water footprint and vulnerability of China's provincial energy sector. These studies provide valuable insights into water management challenges and offer potential policy implications for addressing these issues. [Extracted from the article]

The focus of this paper is impulse noise reduction in digital color images. The most popular noise reduction schemes are the vector median filter and its many variants that operate by minimizing the aggregate distance from one pixel to every other pixel in a chosen window. This minimizing operation determines the most confirmative pixel based on its similarity to the chosen window and replaces the central pixel of the window with the determined one. The peer group filters, unlike the vector median filters, determine a set of pixels that are most confirmative to the window and then perform filtering over the determined set. Using a set of pixels in the filtering process rather than one pixel is more helpful as it takes into account the full information of all the pixels that seemingly contribute to the signal. Hence, the peer group filters are found to be more robust to noise. However, the peer group for each pixel is computed deterministically using thresholding schemes. A wrong choice of the threshold will easily impair the filtering performance. In this paper, we propose a peer group filtering approach using principles of Bayesian probability theory and clustering. Here, we present a method to compute the probability that a pixel value is clean (not corrupted by impulse noise) and then apply clustering on the probability measure to determine the peer group. The key benefit of this proposal is that the need for thresholding in peer group filtering is completely avoided. Simulation results show that the proposed method performs better than the conventional vector median and peer group filtering methods in terms of noise reduction and structural similarity, thus validating the proposed approach. [ABSTRACT FROM AUTHOR]

Marine platforms are located in complex environments, and safety deteriorates throughout the day. It is necessary to analyze the jacket platform structure by the finite element method. Problems such as platform structure variation and fatigue corrosion lead to model deviation. In this paper, a finite element model correction method based on deep learning is proposed with a jacket platform as the engineering background. First, different platform design parameters are selected, and the corresponding fundamental frequencies are obtained by finite element simulation. Second, the input features are extended as necessary to increase the damage-sensitive information, with the nonlinear differences between the two reduced by an improved ResNet50 network. Finally, the correction values of the finite element model are obtained by combining the measured data with the inherent structural frequencies obtained by covariance-driven stochastic subspace identification (Cov-SSI). The results show that the error after correction is less than 4%, which can reflect the real marine platform state well. [ABSTRACT FROM AUTHOR]

This paper develops a queueing system model to analyze the operations of a hierarchical healthcare system consisting of general hospitals (GHs) and community healthcare centers (CHCs). GHs typically provide a higher level of health care service than CHCs, and thus are preferred choices for many patients' healthcare service needs. Consequently, GHs are often heavily congested and patients often incur excessive waiting time. In contrast, CHCs are often idle and resources are underutilized. To help balance the utilization of resources in GHs and CHCs, a congestion-based information guidance policy is proposed in this paper to inform patients in the GH service queue about the anticipated delay. Upon being informed the delay for GH service, patients may balk, remain in queue for GH service, or switch to receive service at CHCs. This policy is thus expected to relieve the congestion at GHs and promote CHC usage. To study the effects of the proposed policy, a hierarchical healthcare system is modeled as a queueing system with strategic patients. Stationary performance measures of the system are analytically characterized using a Markov chain model. Stochastic and numerical analyses provide insights on how to design information guidance policy that would help improve overall health care service quality under different scenarios. [ABSTRACT FROM AUTHOR]

In view of the shortcomings of the existing reversible watermarking algorithms for encrypted images, such as low embedding rate and incomplete separation, and at the same time ensuring the embedding rate and the quality of the watermarked image, this paper proposes a reversible watermarking algorithm for encrypted images with high embedding rate and separable effect. This paper proposes a reversible watermarking algorithm for encrypted images with high embedding rate and separable effect. First, the plaintext image is encrypted by using the encryption series generated by chaotic system and Zu Chongzhi's encryption algorithm; Second, analyze the PSNR value of the image under different interpolation conditions, generate the corresponding expected interpolation, and embed the watermark information into the image based on the expected interpolation; Finally, the original image can be recovered by using the encryption key, and the watermark information can be obtained by using the embedded key. The security and embedding ability of the algorithm are analyzed through simulation experiments. The results show that the introduction of ZUC stream cipher can expand the key space of the algorithm, have high security and achieve the separable effect. The embedding of watermark information has little impact on the ciphertext image, and the embedding rate is also higher than the contrast algorithm under the condition of ensuring the visual effect of the image. [ABSTRACT FROM AUTHOR]

The phonocardiogram (PCG) signal is sometimes affected by added parameters that reflect the presence of a specific pathology. The intensity or the energy of the signal is one of the most reliable parameters when studying cardiac severity. Yet, in a pathological electrophysiological and audio signal, the severity information does not fully remain in the intensity or energy, but in other variables. In this paper, we will discuss the ability of a time-frequency parameter to discriminate, separate, and monitor the pathological cardiac severity levels. We studied 14 PCG signal from eight pathologies, six of them contain clicks (reduce murmurs), and eight murmur PCG signals with four different cardiac severity levels. We then calculated the entropy of approximation coefficients (EAC) from a discrete wavelet transform (DWT) analysis, to differentiate the PCG signals with clicks from those with murmurs and to assess the cardiac severity evolution. Since the entropy EAC is also related to the signal's intensity (energy), we compared it to the energetic ratio (ER) evolution, a parameter widely used for PCG signals discrimination and classification, which revealed that the EAC provied better results for the paper' purposes. [ABSTRACT FROM AUTHOR]

In this paper, a new delayed fractional-order model including susceptible migratory birds, infected migratory birds and predators is proposed to discuss the spread of diseases among migratory birds. Fear of predators is considered in the model, as fear can reduce the reproduction rate and disease transmission rate among prey. First, some basic mathematical results of the proposed model are discussed. Then, time delay is regarded as a bifurcation parameter, and the delay-induced bifurcation conditions for such an uncontrolled system are established. A novel periodic pulse feedback controller is proposed to suppress the bifurcation phenomenon. It is found that the control scheme can successfully suppress the bifurcation behavior of the system, and the pulse width can be arbitrarily selected on the premise of ensuring the control effect. Compared with the traditional time-delay feedback controller, the control scheme proposed in this paper has more advantages in practical application, which not only embodies the advantages of low control cost and easy operation but also caters to the periodic changes of the environment. The proposed control scheme, in particular, remains effective even after the system has been disrupted by a constant. Numerical simulation verifies the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the notion of a newly derived signed graph called a coset component graph, based on cosets of subgroups of a group is introduced. Let G be a group and H be its subgroup. Then, the coset component graph of H in G , denoted by Γ cc , is a simple graph with the vertex set consisting of elements of G and two vertices say, a , b ∈ Γ cc are adjacent if either a H = b H or H a = H b. A coset component signed graph of H in G is a signed graph whose edges get the sign in accordance with their inclusion in the edge set of the corresponding coset component graph. The structure and important properties of the coset component signed graphs are determined in this paper. [ABSTRACT FROM AUTHOR]

Traditional two-color lights out games and their solutions have been studied extensively. This paper focuses on the existence, or lack there of, of solutions in more general lights out games, which take on a prime number of color states. The result in this paper generalizes the existence of solutions in the family of lights out games on a (p + 1) × n grid with p -colors where n ∈ N and p. [ABSTRACT FROM AUTHOR]

Scholars from Mainland China have published 8541 papers in 79 Operations Research and Management Science (OR/MS) journals available on the ISI Web of Science (WOS). Data from 2001 to 2013 constitute the basis of the bibliometric method used in this paper for statistical analysis of status of OR/MS research in Mainland China, from the perspectives of number of papers, quality of papers, most productive institutions, co-author analysis, citations analysis and research topic analysis, etc. The results show that although the number of OR/MS papers by Mainland China scholars grew exponentially during this period, the quality of papers needs to be further improved. Besides, the competition among the institutions in Mainland China is very fierce. Furthermore, the co-author analysis shows that the depth of cooperation has increased steadily and yet the breadth of cooperation has much room for development. Moreover, from the perspective of citations, only a small number of papers by Mainland China scholars have influenced the international OR/MS field. In addition, analysis of research topics shows that Mainland China scholars have been studying the OR/MS problems from a variety of perspectives. Additionally, we also visualize the relationship of the keywords to describe the status of development of the OR/MS discipline in Mainland China, and conclude that the connection nodes will have greater potential in the future. [ABSTRACT FROM AUTHOR]

The subject system of this paper is of no particular interest or importance. Rather the intent is to illustrate how artificial intelligence (AI) might someday find new dynamical systems with special properties, analyze their behavior, and prepare a publication reporting the results. In fact, this entire paper was written automatically without human intervention using a template and computer program developed by the author. [ABSTRACT FROM AUTHOR]

The improved reflectance prediction model for printing dot was established with the Monte Carlo method. Reflectance model is a useful approach to predict and control printing quality, which was widely used in color duplication field. The Monte Carlo prediction model for printing dot is a simulation model, satisfying industrial virtual reality needs, which could simulate reflectance data as well as dot shape image. This paper mainly focuses on improving the existing reflectance model for printing dot with simulation program, expanding dot simulation area from one single dot to nine dots. The results showed that the reflectance value closely approached the measured value with high dot area in particular and the correlation coefficient improved to 0.924. 100,000 times was shown to be the optimal number of simulated photon under regular printing condition. The expanding simulation area could significantly eliminate interactive influence among the dots. The photon distribution and dot shape could be sufficiently simulated through this model, providing a reference for quality control. The results indicate that the improved reflectance model increased the reflectance accuracy and could further promote optical study about color duplication. [ABSTRACT FROM AUTHOR]

Hypercomputation is about the feasibility of machines and systems that are either more expressive or computationally more powerful than the Turing machine. A number of researchers and thinkers have put forth a number of supposedly knock-out arguments against hypercomputation. Nevertheless, these arguments are not unwavering as they seem to be and here I explain why. [ABSTRACT FROM AUTHOR]

For managing data redundancy, the proposed Intelligent Data Fusion Technique (IDFT) decreases the quantity of transmitting data, broadens the network life cycle, enhances bandwidth utilization, and therefore resolves the energy and bandwidth usage bottleneck. Over the last five decades, fuzzy optimization has found numerous successful applications in diverse fields including operations research, manufacturing, information technology, energy optimization, data science and smart cities, big data analytics, etc. Fuzzy optimization is one kind of approximation of nonlinear optimization techniques, which has formed some systematic but not unified theories of fuzzy systems and other fuzzy-set-based methodologies. [Extracted from the article]

No abstract received. [ABSTRACT FROM AUTHOR]

The objective work of this paper is to transform the nonlinear space-time fraction Whitham–Broer–Kaup equation into ordinary differential equation by using the conformal fractional derivative, and find the exact solutions through the complete polynomial discriminant system. At the same time, we build the appropriate solution for the identified parameters to show the existence of the solution. In addition, we provide the 3D and 2D graphics to show that the solutions are real and effective. [ABSTRACT FROM AUTHOR]

Konno's idea of quantum walk on trees remains applicable to a wider family of graphs by means of quantum probabilistic machinery for asymptotic spectral analysis of graphs. [ABSTRACT FROM AUTHOR]

Information on the 2nd International Moscow Conference on Computational Molecular Biology which was held in Moscow, Russia from July 18-21, 2005 is presented. Topics discussed during the conference include comparative genomics and proteomics, genome annotation, gene recognition and alternative splicing, systems biology, and molecular evolution.

I give a simple analysis of the game that I previously published in Scientific American which shows the paradoxical behavior whereby two losing games randomly combine to form a winning game. The game, modeled on a random walk, requires only two states and is described by a first-order Markov process. [ABSTRACT FROM AUTHOR]

Let ${\mathbb D}:=\{(x_1,x_2)\in {\mathbb R}^2:x_1^2+x_2^2 < 1\}$ be the 2-dimensional unit disk and $\gamma \in H^{1/2} (\partial {\mathbb D},{\mathbb R}^3) \cap L^\infty (\partial {\mathbb D})$. For suitably small H>0, we consider the Dirichlet problem for H-systems \[ \hskip3.4cm \left\{\begin{array}{rlll} \Delta u &=& 2H u_{x_1} \wedge u_{x_2} &\quad {\rm in}\ {\mathbb D}\\[5pt] u &=& \gamma &\quad {\rm on}\ \partial {\mathbb D}\,.\hskip3.45cm {\rm (H)} \end{array} \right. \] It is well-known that (H) admits at least two distinct solutions for non-constant γ and small H>0. In this paper, we introduce conditions on γ and develop methods of finding at least three distinct solutions to (H) under such conditions on γ. [ABSTRACT FROM AUTHOR]

The Chinese-Russian Workshop on Biophotonics and Biomedical Optics 2023 brought together scientists, engineers, and clinical researchers from Russia and China to discuss the application of optical science, photonics, and imaging technologies in biology and medicine. The workshop featured two plenary lectures and twenty invited presentations, and this special issue of the Journal of Innovative Optical Health Sciences includes selected papers from the workshop. The papers cover a range of topics, including optical imaging techniques, monitoring cell behavior, diffuse reflectance spectroscopy, photodynamic therapy, and neural networks for biomedical applications. The issue provides readers with the latest developments in biophotonics and biomedical optics. [Extracted from the article]

Some intuitionistic fuzzy interpretations of modal logic axioms are discussed. [ABSTRACT FROM AUTHOR]

NiCo2S4/CNTs (NCS/CNTs) hybrid nanostructures have been synthesized by a facile one-step solvothermal method with varying content of CNTs. The structure and morphology of the synthesized NCS/CNTs hybrid revealed the formation of platelets anchored on the CNT matrix. When evaluated as electrode materials for supercapacitor, the as-synthesized NCS/CNT-1 hybrid (with 1% of CNT) manifested remarkable specific capacitance of 1690 F g − 1 at the current density of 5 A g − 1 . More importantly, an asymmetric supercapacitor (ASC) assembled based on NCS/CNT-1 as positive electrode and carbon nanotube paper (CNP) as a negative electrode delivered high energy density of 58 Wh kg − 1 under power density of 8 kW kg − 1 . Furthermore, the ASC device exhibited high cycling stability and 77.7% of initial specific capacitance retention after 7000 charge–discharge cycles at a current density of 8 A g − 1 . The large enhancement in the electrochemical performance is attributed to the benefits of the nanostructured architecture, including good mechanical stability, high electrical conductivity as well as buffering for the volume changes during charge–discharge process. These convincing results show that NCS/CNTs hybrid nanostructures are promising electrode materials for high energy density supercapacitors (SCs). [ABSTRACT FROM AUTHOR]

The vehicle routing problem (VRP) and its variants are a class of network problems that have attracted the attention of many researchers in recent years, owing to their pragmatic approach to solving issues in logistics management. Most surveys/reviews of the extant literature often focus on specific variants or aspects of the VRP. However, a few reviews of the overall VRP literature are available. The focus of these papers is to identify which VRP literature characteristics are the most popular in recent studies. To this end, we analyze 229 articles published between 2015 and 2017. We provide a systematic literature review evaluating the Scenario Characteristics and Problem Physical Characteristics that are most frequently addressed by VRP researchers, the Type of Study and Data Characteristics that they address, the most cited works that constitute the theoretical pillars of the field, and details of three specific problem variants that have been studied extensively in recent years and their opportunities for future research. [ABSTRACT FROM AUTHOR]

Most supply chains in reality are composed of multiple enterprises which are independent individuals in terms of organizational structures and operating modes. From the perspective of performance evaluation, optimizing each enterprise's efficiency independently will probably result in undesired inventory of intermediate products in the supply chain. Taking the two-stage supply chain where the outputs from the upstream supplier are taken as the inputs for the downstream manufacturer as an example, this paper introduces enterprises' relative dominance into allocating the responsibility of inventory management between two decentralized enterprises. To motivate these enterprises to adopt the allocation strategy, this paper takes the loss aversion of enterprises into account to reveal the utility subjectively perceived by each decentralized enterprise insisting on independence instead of cooperation. Subsequently, a DEA-based cooperative model is developed to readjust the production processes of two decentralized enterprises. We find that adjusting the relevant parameters is able to explore the relationship between the proposed model and the non-cooperative model and the relationship between the proposed model and the centralized model. Finally, a practical example of coordinating sustainable supply chains is applied to illustrate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, we focus on two tasks: semantic segmentation and target detection in the visual semantic understanding of tennis sports images and we optimize the network structure to achieve a more complete location contour information mining of the target. In detail, we focus on a weakly supervised image semantic segmentation method based on null convolution pixel relations. To address the problem of incomplete pixel-level pseudo-labeling, we introduce a cavity convolution unit with multiple cavity rates and a self-attentive mechanism in the classification model to adaptively enhance the target regions and suppress other irrelevant regions while expanding the perceptual field to generate high-quality pixel-level pseudo-labeling and then train the semantic segmentation model. The final experimental results show that the hierarchical fusion algorithm proposed in this paper significantly outperforms other algorithms, and the overall classification accuracy of the tandem cavity neural network algorithm reaches 81% with good overall classification results. The recognition accuracy of static movements is higher than that of dynamic movements. [ABSTRACT FROM AUTHOR]

To address the issues of blurred details and distortion of color in the images recovered by the original AOD-Net dehazing method, this paper proposes a CPAD-Net dehazing network model based on attention mechanism and dense residual blocks. The network is improved on the basis of AOD-Net, which can reduce the errors arising from the separately determined transmittance and atmospheric light values. A new dense residual block structure is designed to replace the traditional convolution method, which effectively improves the detail processing capability and the representation ability of the network model for image feature information. On this basis, the attention module determines how to learn the weights according to the feature importance of distinct channels and distinct pixels, and then obtain the recovery of images in terms of color and texture. The experiments showed that the dehazing efficiency of our method are richer in texture detail information and more natural in color recovery. Compared with other algorithms, the PSNR and SSIM indexes of our method are considerably superior to those listed algorithms, which definitively demonstrates that the dehazing effect of our method is more effective, and the recovered images are more realistic and natural. [ABSTRACT FROM AUTHOR]

Concrete crack detection is essential for infrastructure safety, and its detection efficiency and accuracy are the key issues. An improved YOLOV5 and three measurement algorithms are proposed in this paper, where the original prediction heads are replaced by Transformer Heads (TH) to expose the prediction potential with one self-attention model. Experiments show that the improved YOLOV5 effectively enhances the detection and classification of concrete cracks, and the Mean Average Precision (MAP) value of all classes increases to 99.5%. The first method is more accurate for small cracks, whilst the average width obtained based on the axial traverse correction method is more exact for large cracks. The crack width obtained from the concrete picture sample is the same as that obtained from the manual detection, with a deviation rate of 0–5.5%. This research demonstrates the recognition and classification of concrete cracks by integrating deep learning and machine vision with high precision and high efficiency. It is helpful for the real-time measurement and analysis of concrete cracks with potential safety hazards in bridges, high-rise buildings, etc. [ABSTRACT FROM AUTHOR]

Visual Cryptography (VC) is a process employed for the maintenance of secret information by hiding the secret messages that are embedded within the images. Typically, an image is partitioned into a number of shares that are stacked over one another in order to reconstruct back the original image accurately. The major limitation that existed in the traditional VC techniques is pixel expansion, in which pixel expansion is replaced with a number of sub-pixels in individual share, which causes a considerable impact on the contrast and resolution of the image that further gradually decreases the quality of the image. VC is named for its essential characteristics, such as transmitting the images with two or more shares with an equal number of black pixels and color pixel distribution. The secret message can be decrypted using Human Visual System (HVS). In this paper, 50 research papers are reviewed based on various classification algorithms, which are effectively used for the VC technique. The classification algorithms are categorized into three types, namely, meta-heuristic, heuristic, and evolutionary, and the research issues and challenges confronted by the existing techniques are reported in this survey. Moreover, the analysis is done based on the existing research works by considering the classification algorithms, tools, and evaluation metrics. [ABSTRACT FROM AUTHOR]

This paper introduces a new bridge damage indicator, the moving reference influence function (MRIF), to detect bridge bearing damage using deflections inferred from vehicle accelerations. Recently, vehicle acceleration has been used to find the apparent profile (AP) of a bridge when a vehicle passes. This AP consists of bridge profile elevations and bridge deflection components. To describe the relationship between these deflection components and load, a MRIF is proposed for the first time in this paper. An error minimization process is used to find the MRIF and the road surface profile on the bridge. The vehicle acceleration signals used in the paper are assumed to be collected from a partially instrumented vehicle fleet. In the fleet, only the first axle acceleration is collected from each vehicle. To simplify the minimization process, both the MRIF and the bridge profile are represented by kernel density functions. The results show that the bridge profile can be accurately obtained and that bridge bearing damage can be identified from the MRIF. Both area and skewness of the MRIF are damage sensitive and can be used together to find the location and severity of bridge bearing damage. [ABSTRACT FROM AUTHOR]

Currently, the prevalence of various Internet intrusion technologies has brought much challenge to the enterprise management. For many core documents, the information leakage may lead to the loss of secrets of enterprises. Therefore, some core official documents in enterprises are in the format of papers, rather than electronic format. As a consequence, it is of significance to develop automatic information processing techniques for official documents in the format of papers, so as to improve the working efficiency of enterprises. In this paper, a novel business scheduling approach for enterprises via vision sensing-based automatic documental information extraction is proposed. For the first stage, the vision sensing-based optical character recognition (OCR) technique is utilized to extract textual information from official documents in the format of papers. For the second stage, the deep neural network is utilized to output business scheduling results on the basis of digital recognition contents from the first stage. Finally, the experimental simulation is also carried out to verify efficiency of the proposal. [ABSTRACT FROM AUTHOR]

Over the years, the humanities community has increasingly requested the creation of artificial intelligence frameworks to help the study of cultural heritage. Document Layout segmentation, which aims at identifying the different structural components of a document page, is a particularly interesting task connected to this trend, specifically when it comes to handwritten texts. While there are many effective approaches to this problem, they all rely on large amounts of data for the training of the underlying models, which is rarely possible in a real-world scenario, as the process of producing the ground truth segmentation task with the required precision to the pixel level is a very time-consuming task and often requires a certain degree of domain knowledge regarding the documents at hand. For this reason, in this paper, we propose an effective few-shot learning framework for document layout segmentation relying on two novel components, namely a dynamic instance generation and a segmentation refinement module. This approach is able of achieving performances comparable to the current state of the art on the popular Diva-HisDB dataset, while relying on just a fraction of the available data. [ABSTRACT FROM AUTHOR]

The article presents the discussion on theoretical framework being the National Innovation Systems (NIS). Topics include emergence of digital technology replacing analog technology in the 1990s serving as a window for several Asian economies; and nature of organization and institutional changes requiring to strike a good match with new waves of innovation or 4IR.

This document is a guest editorial from the International Journal of Semantic Computing, focusing on a special issue on Transdisciplinary Artificial Intelligence. The special issue includes two papers that were presented at the 4th IEEE International Conference on Transdisciplinary AI. The first paper discusses transparency in medical artificial intelligence systems, presenting four different methods to create transparency and suggesting criteria for their use. The second paper explores learning causal graphs in manufacturing domains using structural equation models, showing how expert knowledge can reduce the difference between learned cause-effect relationships and expert assessment. The guest editors for this special issue are Fabio Persia, Gary Glesener, and Julienne Greer. [Extracted from the article]

Ordered Weighted Averaging (OWA) operators are a family of aggregation functions for data fusion. If the data are real numbers, then OWA operators can be characterized either as a special kind of discrete Choquet integral or simply as an arithmetic mean of the given values previously ordered. This paper analyzes the possible generalizations of these characterizations when OWA operators are defined on a complete lattice. In addition, the set of all n-ary OWA operators is studied as a sublattice of the lattice of all the n-ary aggregation functions defined on a distributive lattice. [ABSTRACT FROM AUTHOR]

We analyze chaos in the well-known nonautonomous Double-Gyre system. A key focus is on folding, which is possibly the less-studied aspect of the "stretching+folding=chaos" mantra of chaotic dynamics. Despite the Double-Gyre not having the classical homoclinic structure for the usage of the Smale--Birkhoff theorem to establish chaos, we use the concept of folding to prove the existence of an embedded horseshoe map. We also show how curvature of manifolds can be used to identify fold points in the Double-Gyre. This method is applicable to general nonautonomous flows in two dimensions, defined for either finite or infinite times. [ABSTRACT FROM AUTHOR]

The article presents information about a special issue of the journal "Parallel Processing Letters" containing the Euro-Par 2003 best papers selection dedicated to the promotion and advancement of all aspects of parallel and distributed computing. The editors have gathered the expanded and improved versions of the 11 best papers selected among 338 submitted papers. Euro-Par is the renowned series of international conferences dedicated to the promotion and advancement of all aspects of parallel and distributed computing, held during 26-29 August 2003 in Klagenfurt, Austria. The major themes fall into the categories of hardware, algorithms, systems and applications.

This paper is a short account of some of the scientific achievements of Wilhelm von Wldenfels with particular attention to the contributions he gave to quantum probability, a field in which he was one of the pioneers. [ABSTRACT FROM AUTHOR]

Scientific memes have been defined as short units of text in a publication that are replicated in citing [T. Kuhn et al., Phys. Rev. X 4, 041036 (2014)]. Here, we investigate how often the meme appears in the title of the paper when driven by a coauthorship with somebody who has already published a paper with the same meme in the paper title. Five memes are investigated: traffic flow (TF), stochastic resonance (SR), key distribution (KD), small world (SW) and prisoner's dilemma (PD). For each meme, a network of papers (GP) and network of authors (GA) are constructed. A meme index is proposed which is a measure how often scientific teams undertake the research on a given area, marked by the meme, without a cooperation with coauthors with previous achievements in the subject. [ABSTRACT FROM AUTHOR]