nils-herrmann/clean_scirepeval huggingface dataset:
Real Time Bidding in Online Display Advertising
Year: 2017

Display advertising is a major source of revenue for many of the online publishers and content providers. Historically, display advertising impressions have been sold through pre negotiated contracts, known as reservation contracts, between publishers and advertisers. In recent years, a growing number of impressions are being sold in real time bidding (RTB) where advertisers bid for impressions in real time, as consumers visit publishers' websites. RTB allows advertisers to target consumers at an individual level using browser cookie information, and enables them to customize their ads for each individual. The rapid growth of RTB has created new challenges for advertisers and publishers on how much budget and ad inventory to allocate to RTB. In this paper, we use a game theory model with two advertisers and a publisher to study the effects of RTB on advertisers' and publishers' strategies and their profits. We show that symmetric advertisers use asymmetric strategies where one advertiser buys all of his impressions in RTB whereas the other advertiser focuses on reservation contracts. Interestingly, we find that while both advertisers benefit from existence of RTB, the advertiser that focuses on reservation contracts benefits more than the advertiser that focuses on RTB. We show that while RTB lowers the equilibrium price of impressions in reservation contracts, it increases the publisher's total revenue. Despite many analysts' belief that, because of being more efficient, RTB will replace reservation contracts in the future, we show that publishers have to sell a sufficiently large fraction of their impressions in reservation contracts in order to maximize their revenue. We extend our model to consider premium consumers, publisher's uncertainty about the number of future visitors, and effectiveness of ad customization.
Paris, Tokyo, Shanghai: Interaction and Communication of Chinese Modern Art
Year: 2016

This paper analyzes the interaction and communication of modern art in Paris, Tokyo and Shanghai in the early 20th century. Paris was the birthplace of modernist art, Tokyo was the first city to receive a western painting in modern Asia and played an important role in nurturing the art of Asian modern art. Chinese artists from Shanghai, went to Tokyo and Paris to study western painting, providing evidence that Shanghai was influenced from Paris and Tokyo from this western painting communication. In addition to the inheriting relationship, international cooperation and interaction were also found. As a matter of fact, the three cities, Paris, Tokyo and Shanghai play an important role in the development of Chinese western painting. Artists were free to create, imitate the trend, exchange ideas and interact, which promoted the development of Chinese modern art.
Attaining the shot noise limit in the ACME measurement of the electron electric dipole moment
Venue: Journal of Physics B: Atomic, Molecular and Optical Physics
Year: 2019

Experimental searches for the electron electric dipole moment, $d_e$ probe new physics beyond the Standard Model. Recently, the ACME Collaboration set a new limit of |d_e| <1.1\times 10^ 29} $e\cdot \textrm{cm}
Importancia de las NIIF y la seguridad de la informacion para el crecimiento empresarial y financiero del centro del departamento del Huila y Colombia.
Year: 2018

Utilizar reglas definidas suele ser mas facil para el registro de las operaciones economicas que trabajar bajo principios contables, por cuanto las normas establecidas exponen menos a quienes los aplican, en contraposicion de aquellos que incurren en posibles errores de juicio en su accionar; sin embargo, esto es cuestion de principios, como en los que estan basados las Normas Internacionales de Informacion Financiera NIIF. Dentro de este campo existe un concepto de vital importancia referido al criterio profesional. Este, junto con la experiencia son los que dictaminan la pauta a seguir en el asentamiento de los diferentes hechos economicos.
Future changes in climatic water balance determine potential for transformational shifts in Australian fire regimes
Year: 2016

Most studies of climate change effects on fire regimes assume a gradual reorganization of pyrogeographic patterns and have not considered the potential for transformational changes in the climate vegetation fire relationships underlying continental scale fire regimes. Here, we model current fire activity levels in Australia as a function of mean annual actual evapotranspiration (E) and potential evapotranspiration (E 0) as proxies for fuel productivity and fuel drying potential. We distinguish two domains in $E,{E}_{0} space according to the dominant constraint on fire activity being either fuel productivity (PL type fire) or fuel dryness (DL type fire) and show that the affinity to these domains is related to fuel type. We propose to assess the potential for transformational shifts in fire type from the difference in the affinity to either domain under a baseline climate and projected future climate. Under the projected climate changes potential for a transformational shift from DL to PL type fire was predicted for mesic savanna woodland in the north and for eucalypt forests in coastal areas of the south west and along the Continental Divide in the south east of the continent. Potential for a shift from PL to DL type fire was predicted for a narrow zone of eucalypt savanna woodland in the north east.
Near real time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks
Venue: Nature Medicine
Year: 2020

Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery 1 The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of processed tissue is time, resource and labor intensive 2 3 Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed, pathology workforce 4 In the present study, we report a parallel workflow that combines stimulated Raman histology (SRH) 5 7 a label free optical imaging method and deep convolutional neural networks (CNNs) to predict diagnosis at the bedside in near real time in an automated fashion. Specifically, our CNNs, trained on over 2.5 million SRH images, predict brain tumor diagnosis in the operating room in under 150 s, an order of magnitude faster than conventional techniques (for example, 20 30 min) 2 In a multicenter, prospective clinical trial n 278) we demonstrated that CNN based diagnosis of SRH images was noninferior to pathologist based interpretation of conventional histologic images (overall accuracy, 94.6% versus 93.9% Our CNNs learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. In addition, we implemented a semantic segmentation method to identify tumor infiltrated diagnostic regions within SRH images. These results demonstrate how intraoperative cancer diagnosis can be streamlined, creating a complementary pathway for tissue diagnosis that is independent of a traditional pathology laboratory. A prospective, multicenter, case control clinical trial evaluates the potential of artificial intelligence for providing accurate bedside diagnosis of patients with brain tumors.
Lean Automation enabled by Industry 4.0 Technologies
Year: 2015

The Lean Production paradigm has become the major approach to create highly efficient processes in industry since the early 1990s. After the sudden end of the Computer Integrated Manufacturing (CIM) era, which finally was doomed to fail due to its unrulable complexity of the required automation technology, the Lean approach was successful because of its high effectiveness by reducing complexity and avoiding non value creating process steps. Today, the term Industry 4.0 describes a vision of future production. Many people are at least skeptical or even hostile towards this new approach. This position paper gives an overview over existing combinations of Lean Production and automation technology, also called Lean Automation. Furthermore, it discusses major Industry 4.0 corner stones and links them to the well proven Lean approach. Examples of combining both are smart watches for supporting the Andon principle or Cyber Physical Systems (CPS) for a flexible Kanban production scheduling.
Implementation of an Augmented Reality AR Workflow for Human Robot Collaboration in Timber Prefabrication
Venue: Proceedings of the 36th International Symposium on Automation and Robotics in Construction (ISARC)
Year: 2019

In this paper, we present a set of enabling technologies developed for the KUKA Innovation Award to facilitate Human Robot collaboration targeted for the architecture, engineering and construction (AEC) sector. Critically, little progress has been made in the usability of user interfaces for industrial robots  We targeted our investigation explicitly towards human robot collaboration (HRC) in wood based prefabrication production. Although wood is a sustainable material with abundant processing possibilities, it is also a material system where process knowledge remains critically important, making highly automated workflows unfeasible and inefficient. We propose an interactive fabrication process where a user such as a construction worker could wear an augmented reality head mounted display (ARHMD) as an interface to plan robotic trajectories, influence production sequencing, and view superimposed diagnostic feedback. We describe necessary system components including a robotic workcell consisting of a KUKA LBR iiwa, flexFELLOW mobile platform, a Robotiq 2 finger gripper and a custom platform and material feeding station. In addition, we describe a communication framework and set of protocols connecting a CAD digital design environment, a user interface (UI) for Microsoft HoloLens, a ROS server for backend path planning and coordination, and a 3D graphical web interface for downstream visualization of construction status. We conclude with an outlook on enabling technologies for human robot collaboration in construction, and the importance of increasing digital integration and accessibility in characteristic production workflows through accessible and intuitive digital interfaces.
Analisis Perbandingan Klasifikasi Support Vector Machine (SVM) dan K Nearest Neighbors (KNN) untuk Deteksi Kanker dengan Data Microarray
Year: 2020

Cancer is a disease that can cause human death in various countries. According to WHO in 2018, cancer causes 9.6 million human deaths worldwide. Globally, about 1 in 6 deaths is due to cancer. Therefore, we need a technology that can be used for cancer detection with high acuration so that cancer can be detected early. Microarrays technique can predict certain tissues in humans and can be classified as cancer or not. However, microarray data has a problem with very large dimensions. To overcome this problem, in this study use one of the dimension reduction techniques, namely Partial Least Square(PLS) and use Support vector Machine (SVM) and K Nearest Neighbors as a classification method, which will be used to compare which is better.The system built was able to reach 98.54% in leukemia data with PLS KNN, 100% in lung data with KNN, 66.52% in breast data with PLS KNN, and 85.60% in colon data with PLS SVM. KNN is able to get the best in three data from four valued data.
Humic acid as a feed additive in poultry diets: a review.
Venue: Iranian journal of veterinary research
Year: 2019

Many studies tested different feed additives, among these additives, humic substances (HS) have been used in livestock and poultry diets. Humic substances commonly present in nature as they are created from the organic matter decomposition, and are normally found in the soil and natural water. Active components of HS consist of humic acid (HA) humus, ulmic acid, fulvic acid, humin and certain microelements. Humic acid is widely used as an alternative growth promoter for antibiotics in improving poultry performance and health. Moreover, supplementation of a commercial substance as a source of HS through the drinking water or diet improved the feed consumption, feed efficiency and weight gain of broiler chickens, and also improved egg weight, egg mass, and egg production of laying hens. This review describes the useful applications and recent facets of HA including its modes of action and various valuable uses in improving the production and health safeguarding of livestock and poultry.
Data model harmonization for the All Of Us Research Program: Transforming i2b2 data into the OMOP common data model
Venue: PloS one
Year: 2019

is building a nationwide cohort of one million patients' EHR and genomic data. Data interoperability is paramount to the program's success. AOU is standardizing its EHR data around the Observational Medical Outcomes Partnership (OMOP) data model. OMOP is one of several standard data models presently used in national scale initiatives. Each model is unique enough to make interoperability difficult. The i2b2 data warehousing and analytics platform is used at over 200 sites worldwide, which uses a flexible ontology driven approach for data storage. We previously demonstrated this ontology system can drive data reconfiguration, to transform data into new formats without site specific programming. We previously implemented this on our 12 site Accessible Research Commons for Health (ARCH) network to transform i2b2 into the Patient Centered Outcomes Research Network model.  Here, we leverage our investment in i2b2 high performance transformations to support the AOU OMOP data pipeline. Because the ARCH ontology has gained widespread national interest (through the Accrual to Clinical Trials network, other PCORnet networks, and the Nebraska Lexicon) we leveraged sites' existing investments into this standard ontology. We developed an i2b2 to OMOP transformation, driven by the ARCH OMOP ontology and the OMOP concept mapping dictionary. We demonstrated and validated our approach in the AOU New England HPO (NEHPO) First, we transformed into OMOP a fake patient dataset in i2b2 and verified through AOU tools that the data was structurally compliant with OMOP. We then transformed a subset of data in the Partners Healthcare data warehouse into OMOP. We developed a checklist of assessments to ensure the transformed data had self integrity (e.g. the distributions have an expected shape and required fields are populated) using OMOP's visual Achilles data quality tool. This i2b2 to OMOP transformation is being used to send NEHPO production data to AOU. It is open source and ready for use by other research projects.
Are Socially Responsible Managers Really Ethical? Exploring the Relationship between Earnings Management and Corporate Social Responsibility
Year: 2008

This study offers insights for policy makers and managers interested in enhancing CSR. For managers, our findings suggest that projecting a socially friendly image in order to disguise earnings management cannot be sustained over time due to the detrimental effect on financial performance. In addition, this study provides a warning signal to policy makers that certain practices geared toward raising a firm's CSR may simply be a mechanism for hindering other devious practices. This study draws on a generalized agency theory where managers are seen as the agents of all stakeholders and the earnings management literature to highlight that CSR can be used to garner support from stakeholders and, therefore, provides an opportunity for entrenchment to those managers that manipulate earnings. As such, it suggests new avenues of research for both the corporate governance literature, as well as for the stakeholder perspective. Using archival data from a multi national panel sample of 593 firms from 26 countries between 2002 and 2004, we find a positive impact of earnings management practices on CSR; this relationship holds for different robustness checks. Also, we demonstrate that the combination of earnings management and CSR has a negative impact on financial performance. This paper investigates the connection between earnings management and corporate social responsibility (CSR) We argue that earnings management practices damage the collective interests of stakeholders; hence, managers who manipulate earnings can deal with stakeholder activism and vigilance by resorting to CSR practices.
Explaining Willingness to Pay for Pricing Reforms That Improve Electricity Service in India
Venue: Energy Policy
Year: 2019

Quality of electricity service remains poor in many developing countries. Here we examine factors that influence stated willingness to pay for better service (i.e. more hours of power per day) among rural and urban households in Uttar Pradesh, India. Besides suggesting that low willingness to pay is a major obstacle to pricing reform, we find that respondents with more social trust are willing to pay more. In a randomized survey experiment, we also find that delays in service improvements and a lack of community support for pricing reform reduce willingness to pay. These results confirm the importance of non financial considerations in popular support for policies that impose higher prices in exchange for better service. However, we do not find evidence for sense of entitlement the belief that government should offer basic goods and services for free as a predictor of low willingness to pay. These results offer useful input for effective strategies to reform electricity pricing for better service and, ultimately, economic growth, particularly in areas where electricity is heavily underpriced and where governance is weak.
Action Recognition from Videos using Deep Neural Networks
Year: 2017

Convolutional neural network(CNN) models have been extensively used in recent years to solve the problem of image understanding giving state of the art results in tasks like classification, recognition, retrieval, segmentation and object detection. Motivated by this success there have been several attempts to extend convolutional neural networks for video understanding and classification. An important distinction between images and videos is the temporal information that is encoded by the sequence of frames. Most CNN models fail to capture this temporal information. Recurrent neural networks have shown promising results in modelling sequences. In this work we present a neural network model which combines convolutional neural networks and recurrent neural networks. We first evaluate the effect of the convolutional network used for understanding static frames on action recognition. Following this we explore properties that are inherent in the dataset. We combine the representation we get from the convolutional network, the temporal information we get from the sequence of video frames and other properties of the dataset to create a unified model which is trained on the UCF 101 dataset for action recognition. We evaluate our model on the pre defined test set splits of the UCF 101 dataset. We show that our model is able to achieve an improvement over the baseline model. We show comparison between our models and various models proposed in other related works on the UCF 101 dataset. We observe that a good model for action recognition not only needs to understand static frames but also needs to encode the temporal information across a sequence of frames.
Situation Aware IoT Service Coordination Using the Event Driven SOA Paradigm
Venue: IEEE Transactions on Network and Service Management
Year: 2016

Internet of Things (IoT) technology demands a complex, lightweight distributed architecture with numerous diverse components, including end devices and applications adapted for specific contexts. This paper proposes a situation aware IoT services coordination platform based on the event driven service oriented architecture (SOA) paradigm. Focus is placed on the design of an event driven, service oriented IoT services coordination platform, for which we present a situational event definition language (SEDL) an automaton based situational event detection algorithm, and a situational event driven service coordination behavior model, which is based on an extended event condition action trigger mechanism. Moreover, we propose a reliable real time data distribution model to support the effective dispatching sensory data between information providers and consumers, which is based on the grid quorum mechanism to organize those brokers into a grid overlay network to facilitate the asynchronous communication in a large scale, distributed, and loosely coupled IoT applications environment. We also illustrate the various illustrations for IoT services coordination and alarming disposal process of coal mine safety monitoring and control automation scenarios, and also report the measurement and analysis of the platform's performance.
Realtime particle based fluid simulation
Year: 2009

Fluid simulation based on smoothed particle hydrodynamics (SPH) is a practical method for the representation of liquids in interactive applications like virtual surgical training or computer games. In recent years various papers introduced ideas for both, the SPH simulation and its visualization. This thesis explains detailed a straightforward CPU executed implementation of the simulation, as well as an entirely GPU executed visualization technique using isosurface raycasting, which allows the realtime rendering of multiple refractions. Theoretical foundations and alternative techniques are presented where it seems appropriate. Fluidsimulation basierend auf Smoothed Particle Hydrodynamics (SPH) stellt eine praktikable Methode zur Reprasentation von Flussigkeiten in interaktiven Anwendungen wie virtuellem Operationstraining oder Computerspielen dar. In den letzten Jahren wurden vielfaltige Ideen sowohl fur die SPH Simulation selbst, als auch fur deren Visualisierung vorgestellt. Diese Arbeit erklart detailiert sowohl eine moglichst direkt umgesetzte CPU Implementierung der Simulation, als auch eine rein auf der GPU laufende Visualisierungstechnik basierend auf Raycasting der Iso Oberflache, welche die Echtzeitdarstellung mehrfacher Refraktionen erlaubt. Wo es angebracht erscheint, wird auf die theoretischen Grundlagen und auf alternative Techniken eingegangen. Table of contents
Triethylene tetramine dihydrochloride (trientine) in children with Wilson disease: experience at King's College Hospital and review of the literature
Venue: European Journal of Pediatrics
Year: 2008

Our aim was to review our experience of trientine as chelation therapy in children with Wilson disease (WD) and compare to that reported in the literature. We made a retrospective review of the medical notes of 16 of 96 (17% children diagnosed with WD between 1981 and 2006. Children were 6.6 to 15 years old. Only three received trientine as initial therapy [parental choice (two) allergic reactions to penicillamine (one) during the penicillamine challenge] 13 of 16 were converted from penicillamine to trientine because of reactions to penicillamine: haematuria in four, bone marrow suppression in three, neutropenia in three. Trientine was discontinued in three due to allergic rash, low copper excretion and one with compliance problems requiring transplantation. Seventy five per cent of children presented with chronic liver disease. Kayser Fleischer rings were noticed in eight of 16, Wilson Ferenci score range was between 4 and 10 (nl 4) Laboratory indices remained relatively stable. In line with previous reports, trientine was used mainly as secondary treatment when there were severe side effects with penicillamine. Whilst the current evidence is low quality, it appears that trientine is as efficacious as penicillamine and small population studies show a lower side effect profile.