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In today’s pulp and paper industry the Kraft process is the most common method for pulp production. This method uses sodium based chemicals (white liquor) in the cooking process to remove lignin from the wood chips and create pulp. The remains from this process is called black liquor and is being sent to a recycling system for the purpose of recovering the cooking chemicals. Evaporation of black liquor is a big part of this recycling, and the evaporation plant consists of many different tanks that stores black liquor. At Smurfit Kappa Piteå a model has previously been created for the purpose of production planning. In this work the opportunity to add a part that simulates how the liquor stock in the chemical recovery system will change based on the planned production was investigated. This was done by estimating the amount of dry black liquor in the tanks through inflows and outflows. A formula for the produced black liquor was also developed. The results showed that simulating tank levels separately was difficult as data was lacking in some key areas. The final model is therefore a simplified version that estimates the total amount of dry black liquor in the evaporation plant. It simulates the black liquor buffer based on the planed production and how it will change over five days. This could be done with an error smaller than 6%, compared to measurements from sensors in the black liquor tanks. Attempts were also made to create similar models for the rest of the chemical recovery system. It was concluded that information about the inflow of green and white liquor has to be further investigated in order to implement these in the production planning model.

Background Global estimates for cholera annually approximate 4 million cases worldwide with 95,000 deaths. Recent outbreaks, including Haiti and Yemen, are reminders that cholera is still a global health concern. Cholera outbreaks can rapidly induce high death tolls by overwhelming the capacity of health facilities, especially in remote areas or areas of civil unrest. Recent studies demonstrated that stool specimens preserved on filter paper facilitate molecular analysis of Vibrio cholerae in resource limited settings. Specimens preserved in a rapid, low-cost, safe and sustainable manner for sequencing provides previously unavailable data about circulating cholera strains. This may ultimately contribute new information to shape public policy response on cholera control and elimination. Methodology/Principal findings Whole genome sequencing (WGS) recovered close to a complete sequence of the V. cholerae O1 genome with satisfactory genome coverage from stool specimens enriched in alkaline peptone water (APW) and V. cholerae culture isolates, both spotted on filter paper. The minimum concentration of V. cholerae DNA sufficient to produce quality genomic information was 0.02 ng/μL. The genomic data confirmed the presence or absence of genes of epidemiological interest, including cholera toxin and pilus loci. WGS identified a variety of diarrheal pathogens from APW-enriched specimen spotted filter paper, highlighting the potential for this technique to explore the gut microbiome, potentially identifying co-infections, which may impact the severity of disease. WGS demonstrated that these specimens fit within the current global cholera phylogenetic tree, identifying the strains as the 7th pandemic El Tor. Conclusions WGS results allowed for mapping of short reads from APW-enriched specimen and culture isolate spotted filter papers. This provided valuable molecular epidemiological sequence information on V. cholerae strains from remote, low-resource settings. These results identified the presence of co-infecting pathogens while providing rare insight into the specific V. cholerae strains causing outbreaks in cholera-endemic areas., Author summary Cholera affects more than 4 million people globally every year; people predominantly living in poverty or in resource-constrained conditions including political crises or natural disasters. Cholera’s typical presentation is characterized by rapid onset of acute watery diarrhea and vomiting which can progress from watery stool to shock in as little as four hours. Laboratory conditions needed for culture confirmation and strain preservation are rarely to never present in these affected areas. In fact, many cholera endemic areas in Sub-Saharan African are so remote that even treatment response alone is often challenging. Here we present the genomic analysis of DNA extracted from dried filter paper, which is a low-cost, low-tech and sustainable method. Previously this method has facilitated cholera confirmation by PCR, but we demonstrate that this method is also suitable for whole genome sequencing and subsequent strain characterization by presenting the analysis of samples from an outbreak in a remote area of Cameroon. This method will facilitate the understanding of the molecular epidemiology in cholera-prone areas, which were previously too challenging to attempt. It also introduces a method that can be used on a broader scale for diarrheal disease surveillance, including providing a window into co-infection and microbiome analyses.

This is a multidisciplinary project, at the intersection between interaction design, software development and media art. Human-Powered Interactions (HPI) is a field of Human-Computer Interactions (HCI) interested in self-sustainable systems in which power generation and the user interaction are simultaneous, unlike, for example, dynamo torches which have rechargeable batteries. Commonly found on electronic readers, Electronic Paper (e-paper) screens are ultra-low powered and do not require electricity for images to stay displayed, only to refresh them. This project explores these technologies through the prism of art, by designing and building The Human-Powered Generative Art Machine, an interactive hand-crank-powered generative art frame with an e-paper display. Through an interview with a researcher working in the field, a series of hands-on workshops and the construction of the machine, I delve into several questions around HPI, e-paper and generative art. The research uncovers new opportunities around programming and creative practices, to understand the constraints of these technologies and how to work around them. Det här är ett tvärvetenskapligt projekt i skärningspunkten mellan interaktionsdesign, mjukvaruutveckling och mediekonst. Människodrivna Interaktioner är ett område inom Människa–DatorInteraktion som intresserar sig för självförsörjande system där kraftgenerering och användarinteraktion sker samtidigt, till skillnad från t.ex. dynamoficklampor som har uppladdningsbara batterier. Elektroniska pappersskärmar, som är vanliga i elektroniska läsplattor, har extremt låg energiförbrukning och kräver inte elektricitet för att bilderna ska visas, utan endast för att uppdatera dem. I detta projekt undersöktes dessa tekniker genom konstens prisma genom att utforma och bygga The Human-Powered Generative Art Machine, en interaktiv, handkrankdriven, generativ konstram med en e-papper-skärm. Genom en intervju med en forskare som arbetar på området, en serie praktiska workshops och en materialutforskning fördjupar jag mig i flera frågor kring Människodrivna Interaktioner, e-papper och generativ konst. Forskningen avslöjar nya möjligheter i fråga om programmering och kreativa metoder för att förstå begränsningarna i denna teknik och hur man kan arbeta runt dem.

Although regression models play a central role in the analysis of medical research projects, there still exist many misconceptions on various aspects of modeling leading to faulty analyses. Indeed, the rapidly developing statistical methodology and its recent advances in regression modeling do not seem to be adequately reflected in many medical publications. This problem of knowledge transfer from statistical research to application was identified by some medical journals, which have published series of statistical tutorials and (shorter) papers mainly addressing medical researchers. The aim of this review was to assess the current level of knowledge with regard to regression modeling contained in such statistical papers. We searched for target series by a request to international statistical experts. We identified 23 series including 57 topic-relevant articles. Within each article, two independent raters analyzed the content by investigating 44 predefined aspects on regression modeling. We assessed to what extent the aspects were explained and if examples, software advices, and recommendations for or against specific methods were given. Most series (21/23) included at least one article on multivariable regression. Logistic regression was the most frequently described regression type (19/23), followed by linear regression (18/23), Cox regression and survival models (12/23) and Poisson regression (3/23). Most general aspects on regression modeling, e.g. model assumptions, reporting and interpretation of regression results, were covered. We did not find many misconceptions or misleading recommendations, but we identified relevant gaps, in particular with respect to addressing nonlinear effects of continuous predictors, model specification and variable selection. Specific recommendations on software were rarely given. Statistical guidance should be developed for nonlinear effects, model specification and variable selection to better support medical researchers who perform or interpret regression analyses.

This research paper is designed as a position paper with empirical elements to analyze the role of AI in the field of art. This work is separated in different parts of analysis, starting by the philosophy of art and its possible meaning in our society, human mind and its correlation with art and Artificial Intelligence. Then, the question of usage of AI in art will be risen. The discussion about AI in art can be separated into 2 parts: AI as a tool for art and AI as an artist. In order to see how those positions in the artistic field are possible, a theoretical research will be made. Moreover, an interview and the ”Turing” test will be launched with people who are related to the field of art, AI or none of them. This will be made in order to reflect on the matter from a practical point of view. The practical research and the theoretical one will be analyzed together. Denna forskningsartikel är utformad som en positionsuppsats med empiriska inslag för att analysera AI:s roll inom konstområdet. Detta arbete är separerat i olika delar av analysen, med början i konstens filosofi och dess möjliga betydelse i vårt samhälle, mänskliga sinne och dess samband med konst och artificiell intelligens. Då kommer frågan om användningen av AI i konsten att väckas. Diskussionen om AI i konst kan delas upp i 2 delar: Ai som verktyg för konst och AI som konstnär. För att se hur dessa positioner inom det konstnärliga området är möjliga kommer den teoretiska forskningen att göras, liksom intervjun och ”turing”-testet kommer att lanseras med personer som är relaterade till konstområdet, AI eller ingen av dem kommer att göra det. göras för att reflektera över saken från den praktiska synpunkten. Den praktiska forskningen och den teoretiska kommer att analyseras tillsammans.

Context: The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. Objective: The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact on systematic reviews and mapping studies. Method: We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. Results: We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., approximately 8.3%. For CS, 56% of retracted papers, provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also a remarkable disparity between different publishers, a tendency for multiple versions of a retracted paper over and above the Version of Record (VoR), and for new citations long after a paper is officially retracted. Conclusions: Unfortunately retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies., Comment: This is a preprint of the paper submitted to PLOS ONE

The breakthrough potentials of research papers can be explained by their boundary-spanning qualities. Here, for the first time, we apply the structural variation analysis (SVA) model and its affiliated metrics to investigate the extent to which such qualities characterize a group of Nobel Prize winning papers. We find that these papers share remarkable boundary-spanning traits, marked by exceptional abilities to connect disparate and topically-diverse clusters of research papers. Further, their publications exert structural variations on the scale that significantly alters the betweenness centrality distributions of existing intellectual space. Overall, SVA not only provides a set of leading indicators for describing future Nobel Prize winning papers, but also broadens our understanding of the similar prize-winning properties that may have been overlooked among other regular publications., 27 pages, 8 figures, 9 tables. Submitted to Frontiers in Research Metrics and Analytics

The Panama Papers comprise one of the most recent influential leaks containing detailed information on intermediary companies (such as law firms), offshore entities and company officers, and serve as a valuable source of insight into the operations of (approximately) 214,000 shell companies incorporated in tax havens around the globe over the past half century. Entities and relations in the papers can be used to construct a network that permits, in principle, a systematic and scientific study at scale using techniques developed in the computational social science and network science communities. In this paper, we propose such a study by attempting to quantify and profile the importance of entities. In particular, our research explores whether intermediaries are significantly more influential than offshore entities, and whether different centrality measures lead to varying, or even incompatible, conclusions. Some findings yield conclusions that resemble Simpson’s paradox. We also explore the role that jurisdictions play in determining entity importance.

Many complex physical systems exhibit a rich variety of discrete behavioural modes. Often, the system complexity limits the applicability of standard modelling tools. Hence, understanding the underlying physics of different behaviours and distinguishing between them is challenging. Although traditional machine learning techniques could predict and classify behaviour well, typically they do not provide any meaningful insight into the underlying physics of the system. In this paper we present a novel method for extracting physically meaningful clusters of discrete behaviour from limited experimental observations. This method obtains a set of physically plausible functions that both facilitate behavioural clustering and aid in system understanding. We demonstrate the approach on the V-shaped falling paper system, a new falling paper type system that exhibits four distinct behavioural modes depending on a few morphological parameters. Using just 49 experimental observations, the method discovered a set of candidate functions that distinguish behaviours with an error of 2.04%, while also aiding insight into the physical phenomena driving each behaviour. © 2019 Howison et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Science is increasingly done in large teams, making it more likely that papers will be written by several authors from different institutes, disciplines, and cultural backgrounds. A small number of “Ten simple rules” papers have been written on collaboration and on writing but not on combining the two. Collaborative writing with multiple authors has additional challenges, including varied levels of engagement of coauthors, provision of fair credit through authorship or acknowledgements, acceptance of a diversity of work styles, and the need for clear communication. Miscommunication, a lack of leadership, and inappropriate tools or writing approaches can lead to frustration, delay of publication, or even the termination of a project. To provide insight into collaborative writing, we use our experience from the Global Lake Ecological Observatory Network (GLEON) to frame 10 simple rules for collaboratively writing a multi-authored paper. We consider a collaborative multi-authored paper to have three or more people from at least two different institutions. A multi-authored paper can be a result of a single discrete research project or the outcome of a larger research program that includes other papers based on common data or methods. The writing of a multi-authored paper is embedded within a broader context of planning and collaboration among team members. Our recommended rules include elements of both the planning and writing of a paper, and they can be iterative, although we have listed them in numerical order. It will help to revisit the rules frequently throughout the writing process. With the 10 rules outlined below, we aim to provide a foundation for writing multi-authored papers and conducting exciting and influential science.

Author summary Conferences are great venues for disseminating algorithmic bioinformatics results, but they unfortunately do not offer an opportunity to make major revisions in the way that journals do. As a result, it is not possible for authors to fix mistakes that might be easily correctable but nevertheless can cause the paper to be rejected. As a reviewer, I wish that I had the opportunity to tell the authors, “Hey, you forgot to do this really important thing, without which it is hard to accept the paper, but if you could go back and fix it, you might have a great paper for the conference.” This lack of a back and forth can be especially problematic for first-time submitters or those from outside the field, e.g., biologists. In this article, I outline Ten Simple Rules to follow when writing an algorithmic bioinformatics conference paper to avoid having it rejected.

This paper provides empirical evidence that individuals substantially revise their stated wealth redistribution preferences after fiscal scandals. The 2016 Panama Papers scandal revealed top-income tax evasion behaviour simultaneously worldwide. The empirical investigation exploits this event as a quasi-natural experiment. I rely on two original datasets, a UK household longitudinal dataset and a survey conducted in 22 European countries. I use a difference-in-differences strategy and find that pro-redistribution statements increased between 2% and 3.3% after the scandal. Responses are heterogeneous and larger for right-wing individuals and low-income individuals. This change in wealth redistribution preferences is likely to have been translated into a slight change in votes. The results suggest an increase in stated voting intentions for the left and a decrease for the right. Complementary estimations reveal that more media coverage and more individuals involved by country increase the magnitude of the response.

In front of you is the thematic Proceedings, as a collection of papers presented at the 2nd MILCON’19 Conference ''Contemporary education based on ADL'', organized on November 12th 2019, by the Military Academy "General MihailoApostolski" - Skopje associated member of the University ''Goce Delcev'' - Shtip, within the RADLI Project (Regional Advance Distributive Learning Initiative), supported by the Kingdom of Norway and implemented by the Jefferson Institute, USA. The objective of the Conference was to gather educators and trainers from different countries in order to give us the opportunity to increase both knowledge and cooperation within all aspects of advance distributed learning - ADL. Hence, the Proceedings contain 32 papers focused on the contemporary trends in the use of information technology in a pedagogical way, as well as the best practices both from a theoretical point of view, but also from a practical aspect on the topics related to educational programs using blended learning, emerging learning technologies, multiplatform delivery of courseware, motivational and pedagogical learning strategies and other topics related to ADL. This international scientific conference gives us a wonderful opportunity for exchanging experience and knowledge between the scientific workers and the practitioners from North Macedonia, USA, Serbia, Poland, Slovenia, Bosna and Hercegovina and Norway. The papers published in the Proceedings are written by eminent scholars as well as by members of the security system participating in the educational process of the army, police and other security services from different countries. Each paper has been reviewed by international experts competent for the field to which the paper is related. The data and information gained with the empirical research, as well as theoretical thoughts and comparative analyses in the Proceedings will give a significant contribution to the development of the use of ADL in a pedagogical way. We wish to extend our gratitude to all authors and participants to the Conference, as well as to all those who contributed to, or supported the Conference, especially the Kingdom of Norway and the Jefferson Institute, as well as to the Ministry of Defense and the Armed Forces of the Republic of North Macedoniafor their immense support of the Conference.

Background Digitally enabled rehabilitation may lead to better outcomes but has not been tested in large pragmatic trials. We aimed to evaluate a tailored prescription of affordable digital devices in addition to usual care for people with mobility limitations admitted to aged care and neurological rehabilitation. Methods and findings We conducted a pragmatic, outcome-assessor-blinded, parallel-group randomised trial in 3 Australian hospitals in Sydney and Adelaide recruiting adults 18 to 101 years old with mobility limitations undertaking aged care and neurological inpatient rehabilitation. Both the intervention and control groups received usual multidisciplinary inpatient and post-hospital rehabilitation care as determined by the treating rehabilitation clinicians. In addition to usual care, the intervention group used devices to target mobility and physical activity problems, individually prescribed by a physiotherapist according to an intervention protocol, including virtual reality video games, activity monitors, and handheld computer devices for 6 months in hospital and at home. Co-primary outcomes were mobility (performance-based Short Physical Performance Battery [SPPB]; continuous version; range 0 to 3; higher score indicates better mobility) and upright time as a proxy measure of physical activity (proportion of the day upright measured with activPAL) at 6 months. The dataset was analysed using intention-to-treat principles. The trial was prospectively registered with the Australian New Zealand Clinical Trials Registry (ACTRN12614000936628). Between 22 September 2014 and 10 November 2016, 300 patients (mean age 74 years, SD 14; 50% female; 54% neurological condition causing activity limitation) were randomly assigned to intervention (n = 149) or control (n = 151) using a secure online database (REDCap) to achieve allocation concealment. Six-month assessments were completed by 258 participants (129 intervention, 129 control). Intervention participants received on average 12 (SD 11) supervised inpatient sessions using 4 (SD 1) different devices and 15 (SD 5) physiotherapy contacts supporting device use after hospital discharge. Changes in mobility scores were higher in the intervention group compared to the control group from baseline (SPPB [continuous, 0–3] mean [SD]: intervention group, 1.5 [0.7]; control group, 1.5 [0.8]) to 6 months (SPPB [continuous, 0–3] mean [SD]: intervention group, 2.3 [0.6]; control group, 2.1 [0.8]; mean between-group difference 0.2 points, 95% CI 0.1 to 0.3; p = 0.006). However, there was no evidence of a difference between groups for upright time at 6 months (mean [SD] proportion of the day spent upright at 6 months: intervention group, 18.2 [9.8]; control group, 18.4 [10.2]; mean between-group difference −0.2, 95% CI −2.7 to 2.3; p = 0.87). Scores were higher in the intervention group compared to the control group across most secondary mobility outcomes, but there was no evidence of a difference between groups for most other secondary outcomes including self-reported balance confidence and quality of life. No adverse events were reported in the intervention group. Thirteen participants died while in the trial (intervention group: 9; control group: 4) due to unrelated causes, and there was no evidence of a difference between groups in fall rates (unadjusted incidence rate ratio 1.19, 95% CI 0.78 to 1.83; p = 0.43). Study limitations include 15%–19% loss to follow-up at 6 months on the co-primary outcomes, as anticipated; the number of secondary outcome measures in our trial, which may increase the risk of a type I error; and potential low statistical power to demonstrate significant between-group differences on important secondary patient-reported outcomes. Conclusions In this study, we observed improved mobility in people with a wide range of health conditions making use of digitally enabled rehabilitation, whereas time spent upright was not impacted. Trial registration The trial was prospectively registered with the Australian New Zealand Clinical Trials Register; ACTRN12614000936628, In a randomised controlled trial, Leanne Hassett and colleagues investigate the impact of digitally-enabled aged care and neurological rehabilitation on activity and mobility outcomes in Australia., Author summary Why was this study done? A higher dose of therapy in physical rehabilitation is associated with better outcomes; however, current rehabilitation models deliver low therapy doses. Use of digital devices such as virtual reality video games, activity monitors, and handheld computer devices can be enjoyable, provide feedback on performance, and may enable a greater dose of task-specific therapy to improve outcomes. Current evidence is yet to confidently confirm the effects of rehabilitation using digital devices in addition to usual rehabilitation care on mobility tasks such as walking and other important outcomes such as quality of life. What did the researchers do and find? In a pragmatic, outcome-assessor-blinded randomised controlled trial, 300 people with walking difficulties (age 72 ± 16 years, 50% female) received usual multidisciplinary inpatient and post-hospital aged care and neurological rehabilitation alone, or in addition used a range of affordable devices such as virtual reality video games, activity monitors, and handheld devices to target mobility and physical activity, as individually prescribed by a physiotherapist for 6 months. On average participants in the intervention group used 4 ± 1 devices in the inpatient setting and 2 ± 1 devices in the post-hospital setting. This approach was feasible and enjoyed, and demonstrated it could be provided across care settings including the post-hospital setting with mostly remote support. Clinically important improvement was seen in mobility at 3 weeks and 6 months after baseline, but this was not accompanied by greater time spent upright. No adverse events were reported by participants whilst undertaking rehabilitation using digital devices, and there was no difference in the rate of falls between groups. What do these findings mean? Digitally enabled rehabilitation using a range of devices prescribed by a physiotherapist to target a range of mobility limitations across care settings for adults with mixed health conditions can improve mobility but not time spent upright. These results need to be interpreted in light of study limitations including a 15%–19% loss to follow-up at 6 months on the co-primary outcomes. Future models of rehabilitation should investigate incorporating digital devices to enhance inpatient and post-hospital rehabilitation, but prescription should ensure quality and quantity of practice.

Objective To survey the knowledge, attitude, and practices of Vietnamese pharmacists regarding the COVID-19 pandemic. Method This cross-sectional, paper-based study was conducted from June to August 2020. A validated questionnaire (Cronbach’s alpha = 0.84) was used to interview 1,023 pharmacists in nine provinces of Vietnam. Analysis of covariance was employed to identify factors associated with the knowledge of pharmacists. The best model was chosen by using the Bayesian Model Averaging method in R software version 4.0.4. Results The mean knowledge score was 12.02 ± 1.64 (range: 6–15), which indicated that 93.4% of pharmacists had good knowledge of COVID-19. There was no difference in the average score between males and females (p > 0.05). The multivariate linear regression model revealed that the knowledge was significantly associated with pharmacists’ age, education level, and residence (p < 0.001). About attitude and practices, pharmacists daily sought and updated information on the COVID-19 pandemic through mass media and the internet (social network and online newspapers). Nearly 48% of them conceded that they communicated with customers when at least one person did not wear a face mask at the time of the COVID-19 outbreak. At medicine outlets, many measures were applied to protect pharmacists and customers, such as equipping pharmacists with face masks and hand sanitizers (95.0%), using glass shields (83.0%), and maintaining at least one-meter distance between two people (85.2%). Conclusion The pharmacists’ knowledge of COVID-19 transmission, symptoms, and prevention was good. Many useful measures against the spread of this perilous virus were applied in medicine outlets. However, pharmacists should restrict forgetting to wear face masks in communication with medicine purchasers. The government and health agencies should have practical remedies to reduce the significant differences in the COVID-19 knowledge of pharmacists among provinces and education-level groups.

Modeling light scattering is important in diverse reasearch fields such as paper and print, optical tomography, remote sensing and also in computer rendering of im­ages. Particularly in paper and printing industry light scattering simulations play a significant role in understanding the optical response of paper in relation to its properties. Light scattering models are used in paper and print for improving the paper making process, designing new paper qualities, and evaluating printing tech­niques. The models most widely used for light scattering calculations in the paper and printing industry are based on the Kubelka-Munk theory. The theory proposed by Kubelka and Munk, a special case of radiative transfer theory, has several limi­tations and it can only be applied to homogeneous media with isotropic scattering and diffuse illumination. Real paper and print in particular do not satisfy these as­sumptions. These limitations of the Kubelka-Munk model encouraged scientists to develop models based on angle-resolved geometry to account for anisotropic scat­tering of light in paper and print, but in a single spatial dimension. To correctly represent spatial inhomogeneities like ink dots which spread as a function of depth, length and width of the paper, one-dimensional (lD) models are insufficient. In addi­tion to angle-resolved geometry, multi-dimensional models are necessary to analyze light scattering effects in a printed paper. The method used in this thesis, unlike the Kubelka-Munk method employs gen­eral radiative transfer formulation to obtain the reflectances of paper with inhomo­geneities like ink dots. These ink dots printed on plain sheet of paper are consid­ered to spread not only as a function of depth but also as a function of length or width of the paper. First, a numerical solution method comprising of a combination of discrete ordinates and finite differences is developed to solve the general two­dimensional (2D) radiative transfer equation (RTE) with the two dimensions repre­senting the depth and length of the paper. The solver is validated by comparing the results obtained with Monte Carlo simulations adapted to suit paper optics and DORT2002. For isotropic scattering, and for angles close to the normal direction, good agreement is observed among all the three solvers. As the anisotropy factor increases, the present solver needs higher number of radiation streams for conver­gence. The 2D radiative transfer (RT) solver is then applied to printed paper and re­flectances obtained are analyzed. The ink distribution is considered to be non-uniform such that the density of ink decreases linearly with depth. The dots are separated by a distance to study the interference pattern of the intensity distribution which is use­ful in understanding defects like print mottle, print density and optical dot gain. The reflectances obtained are analyzed based on medium parameters such as thickness of the paper sample, its optical parameters and assymetry factor. The illuminating and viewing angles and the depth of ink penetration also influence the optical response and appearance of print. It is observed that the reflectance of dots largely depends on the illuminating and viewing angles with an apparent increase in the size of the dots seen more prominently when viewed across the line. A 2D RT solver is superior in understanding the interference pattern of radiation as observed in the results presented in this thesis, when compared to a lD RT solver. A lD RT solver uses independent columns to approximate the radiation in the lateral direction. It also assumes that the layers in the lateral direction are homogeneous and the radiation from the columns do not interfere with each other. The independent column approximation pays little attention to the lateral variations in intensity. Vid tidpunkten för framläggningen av avhandlingen var följande delarbete opublicerat: delarbete 1 (manuskript).At the time of the defence the following paper was unpublished: paper 1 (manuscript).

We propose to use Twitter data as social-spatial sensors. This study deals with the question whether research papers on certain diseases are perceived by people in regions (worldwide) that are especially concerned by these diseases. Since (some) Twitter data contain location information, it is possible to spatially map the activity of Twitter users referring to certain papers (e.g., dealing with tuberculosis). The resulting maps reveal whether heavy activity on Twitter is correlated with large numbers of people having certain diseases. In this study, we focus on tuberculosis, human immunodeficiency virus (HIV), and malaria, since the World Health Organization ranks these diseases as the top three causes of death worldwide by a single infectious agent. The results of the social-spatial Twitter maps (and additionally performed regression models) reveal the usefulness of the proposed sensor approach. One receives an impression of how research papers on the diseases have been perceived by people in regions that are especially concerned by these diseases. Our study demonstrates a promising approach for using Twitter data for research evaluation purposes beyond simple counting of tweets.

Papers describing software are an important part of computational fields of scientific research. These “software papers” are unique in a number of ways, and they require special consideration to improve their impact on the scientific community and their efficacy at conveying important information. Here, we discuss 10 specific rules for writing software papers, covering some of the different scenarios and publication types that might be encountered, and important questions from which all computational researchers would benefit by asking along the way., Author summary Computational researchers have a responsibility to ensure that the software they write stands up to the same scientific scrutiny as traditional research studies. These 10 simple rules make doing so easier by enhancing usability, reproducibility, transparency, and other crucial characteristics that aren’t taught in most computer science or research methods curricula.

AimsTo evaluate the relative efficiencies of five Internet-based digital and three paper-based scientific surveys and to estimate the costs for different-sized cohorts.MethodsInvitations to participate in a survey were distributed via e-mail to employees of two university hospitals (E1 and E2) and to members of a medical association (E3), as a link placed in a special text on the municipal homepage regularly read by the administrative employees of two cities (H1 and H2), and paper-based to workers at an automobile enterprise (P1) and college (P2) and senior (P3) students. The main parameters analyzed included the numbers of invited and actual participants, and the time and cost to complete the survey. Statistical analysis was descriptive, except for the Kruskal-Wallis-H-test, which was used to compare the three recruitment methods. Cost efficiencies were compared and extrapolated to different-sized cohorts.ResultsThe ratios of completely answered questionnaires to distributed questionnaires were between 81.5% (E1) and 97.4% (P2). Between 6.4% (P1) and 57.0% (P2) of the invited participants completely answered the questionnaires. The costs per completely answered questionnaire were $0.57-$1.41 (E1-3), $1.70 and $0.80 for H1 and H2, respectively, and $3.36-$4.21 (P1-3). Based on our results, electronic surveys with 10, 20, 30, or 42 questions would be estimated to be most cost (and time) efficient if more than 101.6-225.9 (128.2-391.7), 139.8-229.2 (93.8-193.6), 165.8-230.6 (68.7-115.7), or 188.2-231.5 (44.4-72.7) participants were required, respectively.ConclusionsThe study efficiency depended on the technical modalities of the survey methods and engagement of the participants. Depending on our study design, our results suggest that in similar projects that will certainly have more than two to three hundred required participants, the most efficient way of conducting a questionnaire-based survey is likely via the Internet with a digital questionnaire, specifically via a centralized e-mail.

The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing.

In this study, we address the question whether (and to what extent, respectively) altmetrics are related to the scientific quality of papers (as measured by peer assessments). Only a few studies have previously investigated the relationship between altmetrics and assessments by peers. In the first step, we analyse the underlying dimensions of measurement for traditional metrics (citation counts) and altmetrics - by using principal component analysis (PCA) and factor analysis (FA). In the second step, we test the relationship between the dimensions and quality of papers (as measured by the post-publication peer-review system of F1000Prime assessments) - using regression analysis. The results of the PCA and FA show that altmetrics operate along different dimensions, whereas Mendeley counts are related to citation counts, and tweets form a separate dimension. The results of the regression analysis indicate that citation-based metrics and readership counts are significantly more related to quality, than tweets. This result on the one hand questions the use of Twitter counts for research evaluation purposes and on the other hand indicates potential use of Mendeley reader counts.

This exploratory paper introduces the terms exploitation and exploration within the business process management (BPM) context. Despite the fact that BPM grows in popularity, more and more organizations report on BPM failure. The most recent development in the BPM field has led to a variety of new requirements. Almost all processes in BPM are different and may thus be almost impossible to standardize. Researchers in the BPM research field have recently differentiated between exploitation and exploration as two distinct goals of BPM. Today, BPM is applied to different purposes and the trend is going from the exploitation capabilities of BPM to exploration capabilities. This paper addresses the following research question: Can an understanding of exploitation and exploration be a help for BPM organizations to become more successful? For long-term success, it is essential for BPM organizations to identify the competencies and skills of their employees according to changed requirements. The paper ends with an overview of the author’s ongoing thesis project.

Mathematical formulations for production planning are increasing complexity, in order to improve their realism. In short-term planning, the desirable level of detail is particularly high. Exact solvers fail to generate good quality solutions for those complex models on medium- and large-sized instances within feasible time. Motivated by a real-world case study in the pulp and paper industry, this paper provides an efficient solution method to tackle the short-term production planning and scheduling in an integrated mill. Decisions on the paper machine setup pattern and on the production rate of the pulp digester (which is constrained to a maximum variation) complicate the problem. The approach is built on top of a mixed integer programming (MIP) formulation derived from the multi-stage general lotsizing and scheduling problem. It combines a Variable Neighbourhood Search procedure which manages the setup-related variables, a specific heuristic to determine the digester's production speeds and an exact method to optimize the production and flow movement decisions. Different strategies are explored to speed-up the solution procedure and alternative variants of the algorithm are tested on instances based on real data from the case study. The algorithm is benchmarked against exact procedures. (C) 2013 Elsevier Ltd. All rights reserved.

It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies.

With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs.

This paper suggests design concepts for augmenting students' collaborative design work. The concepts are based on theoretical discussions as well as analysis of a number of field studies at different settings in the UK. The theoretical frameworks for design work and for collaboration among designers are focusing on how design work is embodied in the physical environment, specifically the importance of sketching on paper versus digital representations. The paper concludes that not only projects in design education but also in professional practice could benefit from concepts augmenting a paper-based design process.

Research paper recommenders emerged over the last decade to ease finding publications relating to researchers' area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user's expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list.

Moderate-to-severe psoriasis is associated with significant comorbidity, an impaired quality of life, and increased medical costs, including those associated with treatments. Systematic reviews (SRs) and meta-analyses (MAs) of randomized clinical trials are considered two of the best approaches to the summarization of high-quality evidence. However, methodological bias can reduce the validity of conclusions from these types of studies and subsequently impair the quality of decision making. As co-authorship is among the most well-documented forms of research collaboration, the present study aimed to explore whether authors' collaboration methods might influence the methodological quality of SRs and MAs of psoriasis. Methodological quality was assessed by two raters who extracted information from full articles. After calculating total and per-item Assessment of Multiple Systematic Reviews (AMSTAR) scores, reviews were classified as low (0-4), medium (5-8), or high (9-11) quality. Article metadata and journal-related bibliometric indices were also obtained. A total of 741 authors from 520 different institutions and 32 countries published 220 reviews that were classified as high (17.2%), moderate (55%), or low (27.7%) methodological quality. The high methodological quality subnetwork was larger but had a lower connection density than the low and moderate methodological quality subnetworks; specifically, the former contained relatively fewer nodes (authors and reviews), reviews by authors, and collaborators per author. Furthermore, the high methodological quality subnetwork was highly compartmentalized, with several modules representing few poorly interconnected communities. In conclusion, structural differences in author-paper affiliation network may influence the methodological quality of SRs and MAs on psoriasis. As the author-paper affiliation network structure affects study quality in this research field, authors who maintain an appropriate balance between scientific quality and productivity are more likely to develop higher quality reviews.

Segmentation of electronic dance music Tim Scarfe, Wouter M Koolen and Yuri Kalnishkan Adaptive evolutionary algorithm for a multi-objective VRP Andreas Konstantinidis, Savvas Pericleous and Christoforos Charalambos Unsupervised clustering and multi-optima evolutionary search Vassilis P Plagianakos Applying hard and fuzzy K-modes clustering for dynamic web recommendations Panayiotis Christodoulou, Marios Lestas and Andreas S Andreou A fuzzy cognitive map system to explore the repercussions of Greek PSI and bank recapitalization on the Cyprus economy Maria Papaioannou, Costas K Neocleous, Charalambos Papageorgiou and Christos N Schizas Fusion and gene and imaging information enhances derivation of robust composite disgnostic biomarkers in the case of melanoma Ioannis Valavanis, Ilias Maglogiannis and Aristotelis Chatziioannou Classification of osteoporosis clinical data using genetic clustering George C Anastassopoulos, Adam Adamopoulos, Georgios Drosos, Konstantinos Kazakos and Harris Papadopoulos Computational intelligence modeling and assessment of industrial noise: the case of wood manufacturing Vasiliki Dimou, Lazaros S Iliadis and Ilias Bougoudis

Under what conditions should a cognitive robot act? How do we define “opportunities” for robot action? How can we characterize their properties? This paper offers an apparatus to frame thediscussion. Starting from a simple introductory example, we specifyan initial version of a formal framework of opportunity which relates current and future states and beneficial courses of action in a certain time horizon. An opportunity reasoning algorithm is presented,which opens up various new questions about the different types of opportunity and how to interleave opportunity reasoning and action execution. An implementation of this algorithm is tested in a simple experiment including a real mobile robot in a smart home environment and a user., Robot-Era

Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a "dying" paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing "offspring". Practically, this might be used to trace the successive published milestones of a research field., SCOPUS: ar.j, info:eu-repo/semantics/published

Whenever new sequences of DNA or proteins have been decoded it is almost compulsory to look at similar sequences and papers describing those sequences in order to both collect relevant information concerning the function and activity of the new sequences and/or know what is known already about similar sequences. In current web sites and data bases of sequences there are, usually, a set of curated paper references linked to each sequence. Those links are a good starting point to look for relevant information related to a set of sequences. One way to implement such approach is to do a blast with the new decoded sequences, and collect similar sequences. Then one looks at the papers linked with the similar sequences. Most often the number of retrieved papers is small and one has to search large data bases for relevant papers. This paper proposes a process of generating a classifier based on the initially set of relevant papers. First, the authors collect similar sequences using an alignment algorithm like Blast. Then, the authors use the enlarges set of papers to construct a classifier. Finally a classifier is used to automatically enlarge the set of relevant papers by searching the MEDLINE using the automatically constructed classifier.

IPID – the International Network for Postgraduate students in ICT4D – arranged a course in the academic year 2008/2009 as a response to several requests from IPID members for an introduction to development theories and for guidance in how to define the ‘D’ in the expression ICT4D. The aim of the course “Development, Globalisation and ICT (Defining the ’D’ in ICT4D) – 7.5 ECTS” was thus to provide a sound foundation for advanced studies in ICT4D. The course was designed to provide insights into some of the most influential development theories. The selection was made on the basis of classical bodies of ideas with strong impact on recent notions of development. Devoted scholars from relevant fields were invited to lecture and comment on student papers. Postgraduate students from all over the world registered for the course. Video recording was used to provide access to the lectures for those who could not attend. In the event we have eleven completed papers, which are presented in this report.