nils-herrmann/clean_scirepeval huggingface dataset:
VISIOCYT l'intelligence artificielle (IA) au service du diagnostic du carcinome urothelial de la vessie
Venue: Progres en Urologie
Year: 2019

Objectifs La cytologie urinaire mictionnelle (CUM) est non invasive, mais souffre d'un manque de sensibilite et reste pathologiste dependante, notamment dans les lesions urotheliales de bas grade. Afin d'ameliorer le diagnostic sur les urines, VitaDX a developpe dans le cadre de l'essai clinique VISIOCYT un dispositif medical qui utilise des algorithmes de traitement d'image et de machine learning (IA) pour predire le caractere tumoral des CUM. Methodes VISIOCYT est une etude clinique prospective multicentrique, portant sur 1360 patients repartis en deux groupes les temoins negatifs (TNeg) confirmes par une CUM et une endoscopie negatives et les patients porteur d'une tumeur urotheliale (PTU) par le resultat d'une histologie positive de carcinome urothelial. Les resultats de cette communication portent sur 586 patients 127 TNeg et 459 PTU (242 haut grade et 217 bas grade) Les performances ont ete evaluees par validation croisee, une approche statistique standard en IA. Les 586 patients ont donc ete subdivises aleatoirement 42 fois dans les proportions suivantes 5/6 des donnees pour l'apprentissage et 1/6 pour l'evaluation. Resultats A l'issue de la validation croisee, les mesures de performance obtenues sur chacune des 42 partitions sont moyennees pour evaluer les performances de l'algorithme. La sensibilite moyenne de l'algorithme est de 82,6 pour une specificite de 71,4 En detail, on observe une sensibilite moyenne de 89,3 pour les diagnostics de haut grades et de 76,4 pour les diagnostics de bas grade. Sur les memes partitions, a titre de comparaison, la sensibilite moyenne des praticiens de l'essai clinique est de 43 sur l'ensemble des malades, avec en particulier une sensibilite de 61,1 pour les haut grades et de 26,3 pour les bas grades. La specificite des praticiens est par defaut de 100 car la cytologie negative est un critere d'inclusion pour le groupe temoin Tableau 1 Conclusion L'approche algorithmique (IA) semble permettre un meilleur diagnostic des lesions urotheliales de bas grade par rapport a la CUM traditionnelle. Ces resultats devront etre confirmes a l'issu de l'essai clinique en sachant que les performances devraient augmenter avec l'accumulation de donnees supplementaires.
Video Compression With Rate Distortion Autoencoders
Venue: 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2019

In this paper we present a a deep generative model for lossy video compression. We employ a model that consists of a 3D autoencoder with a discrete latent space and an autoregressive prior used for entropy coding. Both autoencoder and prior are trained jointly to minimize a rate distortion loss, which is closely related to the ELBO used in variational autoencoders. Despite its simplicity, we find that our method outperforms the state of the art learned video compression networks based on motion compensation or interpolation. We systematically evaluate various design choices, such as the use of frame based or spatio temporal autoencoders, and the type of autoregressive prior. In addition, we present three extensions of the basic method that demonstrate the benefits over classical approaches to compression. First, we introduce \emph{semantic compression} where the model is trained to allocate more bits to objects of interest. Second, we study \emph{adaptive compression} where the model is adapted to a domain with limited variability, \eg videos taken from an autonomous car, to achieve superior compression on that domain. Finally, we introduce \emph{multimodal compression} where we demonstrate the effectiveness of our model in joint compression of multiple modalities captured by non standard imaging sensors, such as quad cameras. We believe that this opens up novel video compression applications, which have not been feasible with classical codecs.
Data Is the New Oil
Year: 2019

The digital economy creates new business models. These models are based upon platforms that enable both producers and consumers to connect to the ecosystem and create mutual value. A lot of data gets generated in this process, which is core virtue of these systems. Mobility service providers, including airlines, offer mostly physical assets these days. This article intends to depict the most important concepts in terms of data driven companies and will illustrate how the airline industry will be able to profit from this transformation. While today airlines are seen the bridge between airport to airport, a digital transformation has the opportunity to link air traffic with ground transportation modes, making a travel journey seamless.
Introducing a new dataset on leadership change in rebel groups, 1946 2010
Year: 2019

Leaders and leadership changes are found to influence states' foreign policy decisions, in particular with respect to war and peace between states. Although this issue is also addressed in the qualitative literature on intrastate wars, the influence of leadership turnovers in civil war has received limited systematic attention. One reason for this is the scarcity of quantitative data on rebel group leaderships. To fill this gap, we present a comprehensive dataset on leadership changes in rebel groups, 1946 2010, organized by rebel month. The effects of leadership changes among parties engaged in civil war are argued to be more complex than those found in interstate disputes. In this article we present our theoretical argument followed by presentation of the variables in the dataset and descriptive statistics. To demonstrate the potential research value of the dataset we examine the impact of leader shifts on civil war settlement in Africa. We conclude with avenues for future research which might benefit from this dataset.
Profitability determinants of infrastructure public private partnerships (PPPs) empirical evidence from Indian data
Year: 2021

The purpose of this study is to empirically investigate the variables having an impact on profitability of public private partnerships (PPPs) in India using a balanced panel data of 171 unlisted PPPs from different infrastructure sectors such as road, power generation, real estate and ports.  Estimations were done using Arellano Bond dynamic panel data estimation and seemingly unrelated regression models on a balanced panel data of 855 firm years for 171 unlisted PPPs in India. To further test the estimation robustness, panel corrected standard errors model was used.  The study findings indicate that in firm specific factors, leverage, size, non debt tax shield, growth and risk have significant positive impact on PPPs' profitability, whereas in macroeconomic factors, only inflation has significant positive relationship. Although the relationship of all determinants is in sync with various theories and approaches, but these are not significant. Using the robustness test, the results are found to be robust and consistent with resource based view and strategy structure performance approaches.  As PPPs are gaining prominence in the development of infrastructural resources, their profitability is of significant importance to drive private investments in infrastructure development, the identification of factors which determine profitability is critical for researchers, practitioners, policymakers and fund providers such as equity investors and debt providers.  The empirical literature on profitability determinants is focused on various sectors including small and mid size enterprises (SMEs) and micro firms, but to the best of the authors' knowledge, this is the first study, in both developed and developing economies, to empirically investigate the determinants of profitability for PPPs.
Pricing efficiency of Saudi exchange traded funds (ETFs)
Year: 2020

This paper aims to investigate the pricing efficiency of Saudi Sharia compliant (i.e. Islamic) exchange traded funds (ETFs),The paper adheres to a positivist research philosophy with a deductive research approach where data is collected, analyzed and interpreted to examine a hypothesis. Ordinary least squares (OLS) regressions are applied to investigate pricing efficiency and persistence.,The results show that Saudi ETFs do not currently offer proper diversification for investors, possibly due to their low trading volumes and the delays of market prices in reflecting net asset value (NAV) On average, ETFs trade at a premium to their NAVs. Moreover, the authors find that the deviations of ETF prices from their NAVs (i.e. premiums or discounts) do not disappear in one day. The results reveal a significant positive relationship between the trading volume of Saudi ETFs and volatility, a significant positive correlation between ETF returns and contemporaneous deviations and a significant negative relationship between returns and lagged deviations. These findings can be interpreted as evidence against the market efficiency of Saudi ETFs.,Individual and institutional investors can use Saudi ETFs, especially as their efficiency improves with increased trading volume (liquidity) Saudi regulators must increase their efforts to educate market participants and expand the availability of information to enhance transparency and awareness of the benefits of investing in ETFs, which will positively affect liquidity and pricing efficiency in the future.,This paper is the first to perform empirical tests on Saudi ETFs. Saudi Arabia deserves further attention because it is the most significant stock market in the Gulf Cooperation Council and only recently allowed foreigners to participate.
Potenzial von Methoden der kunstlichen Intelligenz fur die Qualitatssicherung
Venue: Der Ophthalmologe
Year: 2020

Hintergrund Verfahren der kunstlichen Intelligenz (KI) wie kunstliche neuronale Netzwerke zeigen vielversprechende Ergebnisse im Bereich der automatisierten Analyse ophthalmologischer Bilddaten. Fragestellung Der vorliegende Beitrag diskutiert, inwiefern die Diskussion und Anwendung von KI Algorithmen auch zur Qualitatssicherung im Bereich der Augenheilkunde beitragen kann.  Ergebnisse in der Diagnostik von Augenerkrankungen, indem beispielsweise OCT(optische Koharenztomographie) Bilder sehr gut segmentiert und Lasionsbestandteile detektiert werden konnen.  Trainieren dieser Netzwerke werden grosse Datensatze genutzt. Qualitat und Verfugbarkeit dieser Datensatze bestimmen die kontinuierliche Verbesserung der Algorithmen. Der Vergleich zwischen KI Algorithmen und der arztlichen Bildinterpretation hat auch Einblicke in die diagnostische Ubereinstimmung zwischen ArztInnen erlaubt. Aktuelle Herausforderungen liegen in der Entwicklung von Verfahren zur Modellierung der Unsicherheit und besseren Nachvollziehbarkeit automatisierter diagnostischer Entscheidungen. Schlussfolgerungen KI Systeme konnten zeitnah als Systeme zur Entscheidungsunterstutzung zum Einsatz kommen. Dadurch konnen sie zur effizienteren Qualitatssicherung beitragen.  Procedures with artificial intelligence (AI) such as deep neural networks, show promising results in automatic analysis of ophthalmological imaging data.  This article discusses to what extent the application of AI algorithms can contribute to quality assurance in the field of ophthalmology.  Relevant aspects from the literature are discussed.  Systems based on artificial deep neural networks achieve remarkable results in the diagnostics of eye diseases, such as diabetic retinopathy and are very helpful, for example by segmenting optical coherence tomographic (OCT) images and detecting lesion components with high fidelity. To train these algorithms large data sets are required. The quality and availability of such data sets determine the continuous improvement of the algorithms. The comparison between the AI algorithms and physicians for image interpretation has also enabled insights into the diagnostic concordance between physicians. Current challenges include the development of methods for modelling decision uncertainty and improved interpretability of automated diagnostic decisions.  Systems based on AI can support decision making for physicians and thereby contribute to a more efficient quality assurance.
Using Domain Similarity for Performance Estimation
Venue: ACL 2010
Year: 2010

Many natural language processing (NLP) tools exhibit a decrease in performance when they are applied to data that is linguistically different from the corpus used during development. This makes it hard to develop NLP tools for domains for which annotated corpora are not available. This paper explores a number of metrics that attempt to predict the cross domain performance of an NLP tool through statistical inference. We apply different similarity metrics to compare different domains and investigate the correlation between similarity and accuracy loss of NLP tool. We find that the correlation between the performance of the tool and the similarity metric is linear and that the latter can therefore be used to predict the performance of an NLP tool on out of domain data. The approach also provides a way to quantify the difference between domains.
Environmental change and social conflict: the northeast Atlantic mackerel dispute
Venue: Regional Environmental Change
Year: 2017

A recurrent critique of the proposition of a causal relation between environmental change and social conflict is that it fails to account for the complexities and dynamics of processes of social ecological change. In this article, we open the black box of contextual factors that influence the causal pathway from environmental change to social conflict. Firstly, we argue for the consideration of three social factors that influence that pathway: (a) institutions, (b) power, and (c) knowledge. Taking a deductive approach, we ascertain their causal importance in the case of the "mackerel dispute," an interstate conflict that unfolded after the abrupt and rapid change in distribution of the northeast Atlantic mackerel stock after 2007. We analyze the historical development of the mackerel dispute through process tracing and demonstrate the importance and causal role of the three factors. Secondly, based on our assessment, we argue to increase the diversity of the scope conditions relevant for the environmental change social conflict nexus. We propose to consider a wider variety of conflicts as outcome of environmental change, high income regions as an arena for those conflicts, and a wider variety of environmental change, such as alterations in abundance in the context of climate change. Lastly, we discuss how future research on this topic can handle the wider scope conditions and greater case variability.
Comparing the knowledge quality in rough classifier and decision tree classifier
Venue: 2008 International Symposium on Information Technology
Year: 2008

This paper presents a comparative study of two rule based classifier; rough set (Rc) and decision tree (DTc) Both techniques apply different approach to perform classification but produce same structure of output with comparable result. Theoretically, different classifiers will generate different sets of rules via knowledge even though they are implemented to the same classification problem. Hence, the aim of this paper is to investigate the quality of knowledge produced by Rc and DTc when similar problems are presented to them. In this case, four important performance metrics are used as comparison, the accuracy of classification, rules quantity, rules length and rules coverage. Five dataset from UCI Machine Learning are chosen and then mined using Rc toolkit namely ROSETTA while C4.5 algorithm in WEKA application is chosen as DTc rule generator. The experimental result shows that Rc and DTc own capability to generate quality knowledge since most of the results are comparable. Rc outperform as an accurate classifier, produce shorter and simpler rule with higher coverage. Meanwhile, DTc obviously generates fewer numbers of rules with significant difference.
Telomere length and telomerase activity in T cells are biomarkers of high performing centenarians
Venue: Aging cell
Year: 2019

It is generally recognized that the function of the immune system declines with increased age and one of the major immune changes is impaired T cell responses upon antigen presentation/stimulation. Some "high performing" centenarians (100+ years old) are remarkably successful in escaping, or largely postponing, major age related diseases. However, the majority of centenarians "low performing" have experienced these pathologies and are forced to reside in long term nursing facilities. Previous studies have pooled all centenarians examining heterogeneous populations of resting/unstimulated peripheral blood mononuclear cells (PBMCs) T cells represent around 60% of PBMC and are in a quiescence state when unstimulated. However, upon stimulation, T cells rapidly divide and exhibit dramatic changes in gene expression. We have compared stimulated T cell responses and identified a set of transcripts expressed in vitro that are dramatically different in high vs. low performing centenarians. We have also identified several other measurements that are different between high and low performing centenarians: (a) The amount of proliferation following in vitro stimulation is dramatically greater in high performing centenarians compared to 67 to 83 year old controls and low performing centenarians; (b) telomere length is greater in the high performing centenarians; and (c) telomerase activity following stimulation is greater in the high performing centenarians. In addition, we have validated a number of genes whose expression is directly related to telomere length and these are potential fundamental biomarkers of aging that may influence the risk and progression of multiple aging conditions.
Nonsurgical or Surgical Treatment of ACL Injuries: Knee Function, Sports Participation, and Knee Reinjury: The Delaware Oslo ACL Cohort Study.
Venue: The Journal of bone and joint surgery. American volume
Year: 2014

While there are many opinions about the expected knee function, sports participation, and risk of knee reinjury following nonsurgical treatment of injuries of the anterior cruciate ligament (ACL) there is a lack of knowledge about the clinical course following nonsurgical treatment compared with that after surgical treatment.  This prospective cohort study included 143 patients with an ACL injury. Isokinetic knee extension and flexion strength and patient reported knee function as recorded on the International Knee Documentation Committee (IKDC) 2000 form were collected at baseline, six weeks, and two years. Sports participation was reported monthly for two years with use of an online activity survey. Knee reinjuries were reported at the follow up evaluations and in a monthly online survey. Repeated analysis of variance (ANOVA) generalized estimating equation (GEE) models, and Cox regression analysis were used to analyze group differences in functional outcomes, sports participation, and knee reinjuries, respectively.  The surgically treated patients (n 100) were significantly younger, more likely to participate in level I sports, and less likely to participate in level II sports prior to injury than the nonsurgically treated patients (n 43) There were no significant group by time effects on functional outcome. The crude analysis showed that surgically treated patients were more likely to sustain a knee reinjury and to participate in level I sports in the second year of the follow up period. After propensity score adjustment, these differences were nonsignificant; however, the nonsurgically treated patients were significantly more likely to participate in level II sports during the first year of the follow up period and in level III sports over the two years. After two years, 30% of all patients had an extensor strength deficit, 31% had a flexor strength deficit, 20% had patient reported knee function below the normal range, and 20% had experienced knee reinjury.  There were few differences between the clinical courses following nonsurgical and surgical treatment of ACL injury in this prospective cohort study. Regardless of treatment course, a considerable number of patients did not fully recover following the ACL injury, and future work should focus on improving the outcomes for these patients.
Dendritic cell development in infection.
Venue: Molecular immunology
Year: 2020

The immune system protects from infections primarily by detecting and eliminating invading pathogens. This is predominantly mediated by innate immune cells like neutrophils, monocytes and dendritic cells (DCs) expressing specific receptors recognizing pathogen associated molecular patterns. DC activation by pathogens leads to the initiation of antigen specific adaptive immune responses, thereby bridging the innate and adaptive immune systems. However, various pathogens have evolved immune evasion strategies to ensure their survival. In this review, we highlight recent findings on how various microorganisms or their structural features affect or modulate DC development and whether this has any consequences for a protective immune response.
Cutaneous Adnexal Tumors
Year: 2013

Adnexal tumors of the skin are complex, with confusing nomenclature. Many lesions show marked variation in histological appearance and there is considerable morphological overlap between different entities. These tumors are relatively rare, compared for example with melanocytic lesions, but still are part of everyday routine work for all histopathologists. Therefore, many general pathologists (the majority of whom are obliged to report dermatopathology specimens) are unfamiliar with the topic and even the experts have difficulties with the more challenging cases. Although the majority of adnexal tumors represent benign lesions, malignant counterparts do occur and these often represent a diagnostic pitfall. There are many inherited syndromes in which cutaneous adnexal tumors are a feature, and failure to recognize these associations may have serious implications.
Post operative morbidity ensuing surgery for insular gliomas: a systematic review and meta analysis
Venue: Neurosurgical Review
Year: 2019

The surgical resection of insular gliomas remains a challenge. Middle cerebral artery perforating arteries and deep functional pathways affect the extent of resection and the rate of post operative morbidity. The authors performed a systematic review and meta analysis of the literature examining early and permanent post operative deficits in patients who underwent resection of insular gliomas using awake craniotomy with direct electrical stimulation (DES) versus surgery under general anesthesia. A systematic search of three databases was performed for studies published between 1990 and 2018. Random effect meta analysis was used to pool the rate of early and permanent post operative deficits. Random effect meta regression was used to examine the association between the rate of post operative deficit and the anesthesia protocol. We included eight studies evaluating 227 patients with insular glioma. The rate of permanent sequelae was lower after awake craniotomy with DES (3.5% vs 15.7% P .001) and early deficits were lower after surgery under general anesthesia (27.3% vs 47.7% P .04) Awake surgery was significantly more common among patients with tumor located within the dominant hemisphere P .001) No significant association arose between the rates of post operative deficits and the use of intraoperative neuronavigation and the neurophysiological monitoring. Furthermore, neither extent of resection nor tumor histology influenced the onset of permanent sequelae. Awake craniotomy with DES is associated with a significantly lower rate of permanent neurological morbidity after an early increase of transient post operative deficits. These data support the use of awake mapping in insular glioma resection.