nils-herrmann/clean_scirepeval huggingface dataset:
Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning
Venue: KDD
Year: 2020

Embedding a graph into feature space is a promising approach to understand its structure. Embedding into 2D or 3D space enables visualization; representation in higher dimensional vector space (typically >100D) enables the application of data mining techniques. For the success of knowledge discovery it is essential that the distances between the embedded vertices truly reflect the structure of the graph. Our fundamental idea is to compress the adjacency matrix by predicting the existence of an edge from the Euclidean distance between the corresponding vertices in the embedding, and to use the achieved compression as a quality measure for the embedding. We call this quality measure Predictive Entropy (PE) PE uses a sigmoid function to define the probability which is monotonically decreasing with the Euclidean distance. We use this sigmoid probability to compress the adjacency matrix of the graph by an entropy coding. While PE could be used to assess the result of any graph drawing or representation learning method we particularly use it as objective function in our new method GEMPE (Graph Embedding by Minimizing the Predictive Entropy) We demonstrate in our experiments that GEMPE clearly outperforms comparison methods with respect to quality of the visual result, clustering and node labeling accuracy on the discovered coordinates.
Resistance to root knot nematodes Meloidogyne spp. in woody plants.
Venue: The New phytologist
Year: 2016

I. 42 II. 43 III. 44 IV. 47 V. 49 VI. 50 VII. 50 VIII. 50 IX. 52 52  Root knot nematodes (RKNs) Meloidogyne spp. cause major damage to cultivated woody plants. Among them, Prunus, grapevine and coffee are the crops most infested by worldwide polyphagous species and species with a more limited distribution and/or narrower host range. The identification and characterization of natural sources of resistance are important steps to develop RKN control strategies. In woody crops, resistant rootstocks genetically different from the scion of agronomical interest may be engineered. We describe herein the interactions between RKNs and different woody crops, and highlight the plant species in which resistance and corresponding resistance (R) genes have been discovered. Even though grapevine and, to a lesser extent, coffee have a history of rootstock selection for RKN resistance, few cases of resistance have been documented. By contrast, in Prunus, R genes with different spectra have been mapped in plums, peach and almond and can be pyramided for durable resistance in interspecific rootstocks. We particularly discuss here the Ma Toll/interleukin 1 receptor like nucleotide binding leucine rich repeat gene from Myrobalan plum, one of the longest plant R genes cloned to date, due to its unique biological and structural properties. RKN R genes in Prunus will enable us to carry out molecular studies aimed at improving our knowledge of plant immunity in woody plants.
Question Driven Design Process for Explainable AI User Experiences
Venue: ArXiv
Year: 2021

A pervasive design issue of AI systems is their explainability how to provide appropriate information to help users understand the AI. The technical field of explainable AI (XAI) has produced a rich toolbox of techniques. Designers are now tasked with the challenges of how to select the most suitable XAI techniques and translate them into UX solutions. Informed by our previous work studying design challenges around XAI UX, this work proposes a design process to tackle these challenges. We review our and related prior work to identify requirements that the process should fulfill, and accordingly, propose a Question Driven Design Process that grounds the user needs, choices of XAI techniques, design, and evaluation of XAI UX all in the user questions. We provide a mapping guide between prototypical user questions and exemplars of XAI techniques to reframe the technical space of XAI, also serving as boundary objects to support collaboration between designers and AI engineers. We demonstrate it with a use case of designing XAI for healthcare adverse events prediction, and discuss lessons learned for tackling design challenges of AI systems.
Multiple spatial pooling for visual object recognition
Venue: Neurocomputing
Year: 2014

Global spatial structure is an important factor for visual object recognition but has not attracted sufficient attention in recent studies. Especially, the problems of features' ambiguity and sensitivity to location change in the image space are not yet well solved. In this paper, we propose multiple spatial pooling (MSP) to address these problems. MSP models global spatial structure with multiple Gaussian distributions and then pools features according to the relations between features and Gaussian distributions. Such a process is further generalized into a unified framework, which formulates multiple pooling using matrix operation with structured sparsity. Experiments in terms of scene classification and object categorization demonstrate that MSP can enhance traditional algorithms with small extra computational cost.
Biosimilars
Venue: Lupus
Year: 2020

Biological therapies have widened the therapeutic armamentarium for immune mediated inflammatory diseases, providing in many cases a broad range of treatment options with different mechanisms of action. The widespread use of biological agents in systemic lupus erythematosus is currently limited to belimumab and rituximab, although results of promising larger Phase III clinical trials are awaited or have been recently circulated, especially for anti cytokine therapies. The loss of exclusivity over the last years for several originator biologics has started the successful introduction of biosimilar products into clinical practice. There is an abbreviated pathway to biosimilar approval, but this is underpinned by the same standards of pharmaceutical quality, safety and efficacy that apply to all biological medicines. Nevertheless, there are unique reasons why development of biosimilars may be particularly challenging in lupus.
Pilgrims and MERS CoV: what's the risk?
Venue: Emerging Themes in Epidemiology
Year: 2015

The risk of Middle East Respiratory Syndrome Coronavirus spreading globally is worrying, given the annual mass gathering of the Hajj and the year long influx of pilgrims undertaking the Umrah. Based on the incidence in Saudi Arabia since June 2012, the most likely scenario given recent pilgrim numbers is estimated to be one case per Hajj, and three Umrah pilgrims per year, but which could plausibly reach seven and ten pilgrims respectively. In addition to the 2015 Hajj, national surveillance systems should be on the alert for the low but long lasting risk of infected pilgrims returning from the Umrah throughout the year.
Hepatocellular carcinoma: a global view
Venue: Nature Reviews Gastroenterology &Hepatology
Year: 2010

Hepatocellular carcinoma (HCC) is a global health problem, although developing countries are disproportionally affected: over 80% of HCCs occur in such regions. About three quarters of HCCs are attributed to chronic HBV and HCV infections. In areas endemic for HCV and HBV, viral transmission occurs at an early age, and infected individuals develop HCC in mid adulthood. As these are their most productive years of life, HCC accounts for a substantial burden on the health care system and drain of productive capacity in the low income and middle income countries most affected by HCV and HBV infections. Environments with disparate resource levels require different strategies for the optimal management of HCC. In high resource environments, guidelines from the American Association for the Study of Liver Diseases or European Association for the Study of the Liver should be applied. In intermediate resource or low resource environments, the fundamental focus should be on primary prevention of HCC, through universal HBV vaccination, taking appropriate precautions and antiviral treatments. In intermediate resource and low resource environments, the infrastructure and capacity for abdominal ultrasonography, percutaneous ethanol injection, radiofrequency ablation and surgical resection should be established. Programs to provide targeted therapy at low cost, similar to the approach used for HIV therapy in the developing world, should be pursued.
XGBoost Reliable Large scale Tree Boosting System
Year: 2015

Tree boosting is an important type of machine learning algorithms that is widely used in practice. In this paper, we describe XGBoost, a reliable, distributed machine learning system to scale up tree boosting algorithms. The system is optimized for fast parallel tree construction, and designed to be fault tolerant under the distributed setting. XGBoost can handle tens of millions of samples on a single node, and scales beyond billions of samples with distributed computing.
Unsupervised feature selection technique based on genetic algorithm for improving the Text Clustering
Venue: 2016 7th International Conference on Computer Science and Information Technology (CSIT)
Year: 2016

The increasing amount of text documents in digital forms affect the text analysis techniques. Text clustering (TC) is one of the important techniques used for showing a massive amount of text documents by clusters. Hence, the main problem that affects the text clustering technique is the presence sparse and uninformative features on the text documents. The feature selection (FS) is an essential unsupervised learning technique. This technique is used to select informative features to improve the performance of text clustering algorithm. Recently, the meta heuristic algorithms are successfully applied to solve several hard optimization problems. In this paper, we proposed the genetic algorithm (GA) to solve the unsupervised feature selection problem, namely, (FSGATC) This method is used to create a new subset of informative features in order to obtain more accurate clusters. Experiments were conducted using four benchmark text datasets with variant characteristics. The results showed that the proposed FSGATC is improved the performance of the text clustering algorithm and got better results compared with k mean clustering standalone. Finally, the proposed method "FSGATC" evaluated by F measure and Accuracy, which are common measures used in the domain of text clustering.
Financialization of government debt? European government debt management approaches 1980 2007
Year: 2017

The aim of this article is to explore the strategies European government debt managers used in response to the growing demand for credit by governments since the 1980s and how the introduction of the common currency area influenced the nature of government debt management. The analysis indicated that in the 1980s, a paradigm shift emerged as bilateral debt relationships became negligible, while the role of financial market principles became much stronger. A financialization of the relationship with private investors took place, although still highly regulated. The introduction of the euro resulted not only in the new European rules but also in the financialization of the regulatory framework. The participating governments lost the privilege to encapsulate their markets. Because of these two processes, managing government debt in the common currency area meant developing a strategy to successfully issue in a transnational market without support from public authorities at least until the crisis.
The Effect of Treasury Turnover, Receivable Turnover, Working Capital Turnover and Current Ratio against Profitability Registered Food and Beverage Companies in Indonesia Stock Exchange for the Period 2013 2018
Year: 2020

Every company certainly always wants to achieve maximum profitability in carrying out its business activities. This study aims to determine the effect of treasury turnover, accounts receivable turnover, working capital turnover and current ratio on profitability of food and beverage companies listed on the Indonesia Stock Exchange in the period 2013 2018. This research method uses quantitative research methods. This type of research used in this research is quantitative descriptive research. The nature of the research is explanatory research, namely research carried out by explaining or describing the influence exerted on a variable against other variables so that it can know the magnitude of the influence exerted. The population in this study were 22 companies consisting of 6 years. The selection of sampling in this study uses purposive sampling technique that is sampling with certain criteria so that the number of samples taken is 42 samples. The data analysis method used is multiple regression analysis. The results of the hypothesis show that partial treasury turnover and accounts receivable turnover do not affect profitability, but working capital turnover and current ratio affect profitability. Simultaneous testing of treasury turnover, accounts receivable turnover, working capital turnover and current ratio significantly influence profitability. The coefficient of determination is 55.5% which means that 55.5% of the variation of the dependent variable (profitability) can be explained by the variation of the independent variables in this study.
The Real Impact of Residential Property Stamp Duties
Year: 2017

In a number of markets with high house prices, governments have implemented various forms of stamp duty. Stamp duty is a tax on the transfer of assets, including residential property. Policy makers claim that stamp duty increases are an instrument through which they intend to decrease property demand, and ultimately ease housing costs. However, empirical evidence suggests that such taxes are ineffective in achieving this objective.We present evidence that the likely reason these taxes for this outcome is that the demand function of property buyers in these high house price markets are not elastic. The event study methodology is used to test the impact of stamp duty on the residential property price and transaction volume.Following this, we develop a model to show that the real impact of residential property stamp duties is an increase in government revenue. Governments in high housing cost markets face an agency like problem when determining taxation policy. Our paper aims to examine the impact on government revenue from stamp duty using data from Hong Kong.Hong Kong presents a natural experiment in which to test our model. Often ranked as one of the world's most expensive and unaffordable property markets, the Hong Kong government has introduced various stamp duties since 2010. While their stated aim is to stabilize housing prices and transactions, no prior studies have examined the effect of stamp duty on government revenue.Our findings provide a timely contribution to the current discourse on housing affordability policies. While tax policy may not directly ease housing costs, through redistribution of wealth governments may still use tax policy to alleviate the affordability problem.
Verifying Existence of Resource Bounded Coalition Uniform Strategies
Venue: IJCAI
Year: 2016

We consider the problem of whether a coalition of agents has a knowledge based strategy to ensure some outcome under a resource bound. We extend previous work on verification of multi agent systems where actions of agents produce and consume resources, by adding epistemic pre and postconditions to actions. This allows us to model scenarios where agents perform both actions which change the world, and actions which change their knowledge about the world, such as observation and communication. To avoid logical omniscience and obtain a compact model of the system, our model of agents' knowledge is syntactic. We define a class of coalition uniform strategies with respect to any (decidable) notion of coalition knowledge. We show that the model checking problem for the resulting logic is decidable for any notion of coalition uniform strategies in these classes.
Sustainable business model experimentation by understanding ecologies of business models
Year: 2019

Sustainable business model innovation is about creating superior customer and firm value by addressing societal and environmental needs through the way business is done. Business models require intentional design if they are to deliver aspired sustainability impacts. Scant research has been done on 'ecologies' of different business models in order to understand and improve these and create positive impact on the environment, society, economy and other key stakeholders. Hence, in this paper a novel framework is presented to enable a systemic form of sustainable business model experimentation. The framework is based on the recognition of three key issues which have not yet been sufficiently incorporated in the literature on sustainable business models: construct clarity, boundary setting and uncertainty about outcomes. These concepts are discussed first. Building on earlier work, the resulting framework incorporates potential side effects and boundary setting based on the concept of an 'ecology of business models' Second, an approach is proposed that could stimulate more profound forms of sustainable business model innovation: The Ecology of Business Models Experimentation map. Third, the approach is illustrated through two cases. The approach could help minimise symbiotic dependency on less sustainable business models; help destroy unsustainable business models by outcompeting them; and maximise contributions to favourable institutional infrastructures for more sustainable business models. This paper contributes to research on sustainable business model innovation, design and experimentation by providing a potential approach for 'business model ecology redesign'
Erratum zu: Agilitat, Ambidextrie und organisationale Veranderungskompetenz. Rudi Wimmer uber Erbe und Zukunft des Change Managements
Year: 2020

Der Artikel ,Agilitat, Ambidextrie und organisationale Veranderungskompetenz. Rudi Wimmer uber Erbe und Zukunft des Change Managements" von Rudi Wimmer und Falko von Ameln wurde ursprunglich ohne ,Open Access" Online First
Psychotic like experiences as part of a continuum of psychosis: Associations with effort based decision making and reward responsivity
Venue: Schizophrenia Research
Year: 2019

Research examining psychotic disorders typically involves comparison between individuals with a clinical disorder and healthy controls. However, research suggests that psychotic symptoms, such as delusions and hallucinations, may exist on a continuum ranging from variation in healthy individuals to diagnosable psychotic disorders. On this continuum, some individuals endorse occasional psychotic like experiences (PLEs) that do not cause sufficient impairment or distress to warrant a clinical diagnosis. Given this continuum model, one might expect to observe impairments in those with PLEs in the same behavioral domains impaired in schizophrenia. Thus, we examined two domains typically impaired in schizophrenia, effort allocation and reward responsivity, in a large university sample (n 126) Participants completed tasks assessing effort based decision making, reward responsivity, and questionnaires assessing PLEs. Greater PLEs were associated with greater effort expenditure regardless of probability of receiving a reward or reward value. Higher PLEs were related to greater positive feelings when receiving rewards. Importantly, these relationships remained the same when controlling for other symptoms such as depression, anhedonia, and anxiety. These findings suggest that PLEs may be associated with hypersensitivity to reward at the less severe end of the psychotic continuum, with effort to attain a reward expended in a potentially inefficient manner. This pattern is consistent with models of hyperdopaminergic states in psychotic individuals not taking antipsychotic medications, given the role of dopamine in modulating effort allocation and reward anticipation.
The Association of Dietary Behaviors and Physical Activity Levels with General and Central Obesity among ASEAN University Students
Venue: AIMS public health
Year: 2017

To quantify the prevalence of obesity and obesity related factors (dietary behaviors and physical activity levels) in a cross sectional, observational study of ASEAN undergraduate students.  A total of 6783 (35.5% male and 64.5% female) undergraduate students (Mean age: 20.5, SD 2.0) from eight ASEAN countries completed questionnaires and anthropometric measurements. Multivariable logistic regression was used to estimate odds ratios (ORs) for the association of nutrition behaviors with prevalence of general obesity (body mass index 25 kg/m2) elevated waist to height ratio (WHtR) >0.50) and high waist circumference (WC) =80 cm in females, =90 cm in males) Covariates included sociodemographic factors, dietary behavior, physical activity and sitting time (using the "International Physical Activity Questionnaire"  There was a higher prevalence of general obesity (24.2% versus 9.3% and high WHtR (16.6% versus 12.1) in males relative to females, while high WC (9.4% versus 10.4% did not significantly differ between genders. In multivariable logistic regression analyses, compared to females, males had higher odds of obesity (odds ratio, OR: 2.13, confidence interval, CI: 1.80, 2.77) and high WHtR (OR: 1.90, CI: 1.48, 2.43) (P 0.001 for both) Snacking frequency and avoiding fatty foods were associated with all three obesity indicators; obesity (OR: 1.16, CI: 1.05, 1.28 and OR: 1.54, CI: 1.24, 1.92, respectively) WHtR (OR: 1.17, CI: 1.04, 1.32 and OR: 1.46, CI: 1.04, 1.54) and high WC (OR: 1.16, CI: 2.01, 1.33 and OR 1.52, CI: 1.14, 2.04, respectively) Physical activity and sedentary behavior were not significantly associated with any obesity measure.  There was a low prevalence of healthy behaviors and a high prevalence of obesity in this sample of ASEAN young adults. Specific dietary behaviors but not physical activity nor sedentary behavior were associated with obesity.