nils-herrmann/clean_scirepeval huggingface dataset:
Population synthesis for urban resident modeling using deep generative models
Venue: ArXiv
Year: 2020

The impacts of new real estate developments are strongly associated to its population distribution (types and compositions of households, incomes, social demographics) conditioned on aspects such as dwelling typology, price, location, and floor level. This paper presents a Machine Learning based method to model the population distribution of upcoming developments of new buildings within larger neighborhood/condo settings. We use a real data set from Ecopark Township, a real estate development project in Hanoi, Vietnam, where we study two machine learning algorithms from the deep generative models literature to create a population of synthetic agents: Conditional Variational Auto Encoder (CVAE) and Conditional Generative Adversarial Networks (CGAN) A large experimental study was performed, showing that the CVAE outperforms both the empirical distribution, a non trivial baseline model, and the CGAN in estimating the population distribution of new real estate development projects.
UNILATERAL VARIATION OF THE RENAL VEIN AND TESTICULAR VEIN A CASE REPORT
Year: 2016

The right and left renal veins open into the inferior vena cava at right angle. The left renal vein is 3 times longer as compared to right. The right gonadal vein (testicular in male or ovarian in female) drains directly into inferior vena cava and left gonadal vein into left renal vein.  During the routine dissection teaching of posterior abdominal wall for first year MBBS students in the Department of Anatomy, MSRMC, Bangalore, we found the presence of double right renal veins along with variation in the termination of right testicular vein in an adult male cadaver aged 65 years. All the structures were carefully dissected, measurements noted and photographed using a digital camera.  In the present case, two right renal veins (superior and inferior) were found to be draining into inferior vena cava separately and right testicular vein into inferior right renal vein  This type of variation will help the radiologists for planning radiographic procedures; the surgeons for planning surgery to avoid intra and post operative complications and the clinicians in recognition and protection of the variation.
CGC Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images
Venue: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Year: 2019

Colorectal cancer (CRC) grading is typically carried out by assessing the degree of gland formation within histology images. To do this, it is important to consider the overall tissue micro environment by assessing the cell level information along with the morphology of the gland. However, current automated methods for CRC grading typically utilise small image patches and therefore fail to incorporate the entire tissue micro architecture for grading purposes. To overcome the challenges of CRC grading, we present a novel cell graph convolutional neural network (CGC Net) that converts each large histology image into a graph, where each node is represented by a nucleus within the original image and cellular interactions are denoted as edges between these nodes according to node similarity. The CGC Net utilises nuclear appearance features in addition to the spatial location of nodes to further boost the performance of the algorithm. To enable nodes to fuse multi scale information, we introduce Adaptive GraphSage, which is a graph convolution technique that combines multi level features in a data driven way. Furthermore, to deal with redundancy in the graph, we propose a sampling technique that removes nodes in areas of dense nuclear activity. We show that modeling the image as a graph enables us to effectively consider a much larger image (around 16x larger) than traditional patch based approaches and model the complex structure of the tissue micro environment. We construct cell graphs with an average of over 3,000 nodes on a large CRC histology image dataset and report state of the art results as compared to recent patch based as well as contextual patch based techniques, demonstrating the effectiveness of our method.
Modelagem Matematica do Tempo de Vida de Baterias de Litio Ion Polimero a partir do Modelo Eletrico para Predizer Runtime e Caracteristicas V I Suelen
Year: 2018

Neste trabalho e realizada a modelagem matematica do tempo de vida de baterias do tipo Litio Ion Polimero (LiPo) utilizando o modelo eletrico para Predizer Runtime e Caracteristicas V I (i.e. de tensao e corrente)
"The Dose Makes the Poison" Informing Consumers About the Scientific Risk Assessment of Food Additives.
Venue: Risk analysis an official publication of the Society for Risk Analysis
Year: 2016

Intensive risk assessment is required before the approval of food additives. During this process, based on the toxicological principle of "the dose makes the poison," maximum usage doses are assessed. However, most consumers are not aware of these efforts to ensure the safety of food additives and are therefore sceptical, even though food additives bring certain benefits to consumers. This study investigated the effect of a short video, which explains the scientific risk assessment and regulation of food additives, on consumers' perceptions and acceptance of food additives. The primary goal of this study was to inform consumers and enable them to construct their own risk benefit assessment and make informed decisions about food additives. The secondary goal was to investigate whether people have different perceptions of food additives of artificial (i.e. aspartame) or natural origin (i.e. steviolglycoside) To attain these research goals, an online experiment was conducted on 185 Swiss consumers. Participants were randomly assigned to either the experimental group, which was shown a video about the scientific risk assessment of food additives, or the control group, which was shown a video about a topic irrelevant to the study. After watching the video, the respondents knew significantly more, expressed more positive thoughts and feelings, had less risk perception, and more acceptance than prior to watching the video. Thus, it appears that informing consumers about complex food safety topics, such as the scientific risk assessment of food additives, is possible, and using a carefully developed information video is a successful strategy for informing consumers.
Increasing Argument Annotation Reproducibility by Using Inter annotator Agreement to Improve Guidelines
Venue: LREC
Year: 2018

In this abstract we present a methodology to improve Argument annotation guidelines by exploiting inter annotator agreement measures. After a first stage of the annotation effort, we have detected problematic issues via an analysis of inter annotator agreement. We have detected ill defined concepts, which we have addressed by redefining high level annotation goals. For other concepts, that are well delimited but complex, the annotation protocol has been extended and detailed. Moreover, as can be expected, we show that distinctions where human annotators have less agreement are also those where automatic analyzers perform worse. Thus, the reproducibility of results of Argument Mining systems can be addressed by improving inter annotator agreement in the training material. Following this methodology, we are enhancing a corpus annotated with argumentation, available at https:/github.com/ PLN FaMAF/ArgumentMiningECHR together with guidelines and analyses of agreement. These analyses can be used to filter performance figures of automated systems, with lower penalties for cases where human annotators agree less.
RiFCN: Recurrent Network in Fully Convolutional Network for Semantic Segmentation of High Resolution Remote Sensing Images
Venue: ArXiv
Year: 2018

Semantic segmentation in high resolution remote sensing images is a fundamental and challenging task. Convolutional neural networks (CNNs) such as fully convolutional network (FCN) and SegNet, have shown outstanding performance in many segmentation tasks. One key pillar of these successes is mining useful information from features in convolutional layers for producing high resolution segmentation maps. For example, FCN nonlinearly combines high level features extracted from last convolutional layers; whereas SegNet utilizes a deconvolutional network which takes as input only coarse, high level feature maps of the last convolutional layer. However, how to better fuse multi level convolutional feature maps for semantic segmentation of remote sensing images is underexplored. In this work, we propose a novel bidirectional network called recurrent network in fully convolutional network (RiFCN) which is end to end trainable. It has a forward stream and a backward stream. The former is a classification CNN architecture for feature extraction, which takes an input image and produces multi level convolutional feature maps from shallow to deep; while in the later, to achieve accurate boundary inference and semantic segmentation, boundary aware high resolution feature maps in shallower layers and high level but low resolution features are recursively embedded into the learning framework (from deep to shallow) to generate a fused feature representation that draws a holistic picture of not only high level semantic information but also low level fine grained details. Experimental results on two widely used high resolution remote sensing data sets for semantic segmentation tasks, ISPRS Potsdam and Inria Aerial Image Labeling Data Set, demonstrate competitive performance obtained by the proposed methodology compared to other studied approaches.
The Baltic Sea as a time machine for the future coastal ocean
Venue: Science Advances
Year: 2018

Science based, multinational management of the Baltic Sea offers lessons on amelioration of highly disturbed marine ecosystems. Coastal global oceans are expected to undergo drastic changes driven by climate change and increasing anthropogenic pressures in coming decades. Predicting specific future conditions and assessing the best management strategies to maintain ecosystem integrity and sustainable resource use are difficult, because of multiple interacting pressures, uncertain projections, and a lack of test cases for management. We argue that the Baltic Sea can serve as a time machine to study consequences and mitigation of future coastal perturbations, due to its unique combination of an early history of multistressor disturbance and ecosystem deterioration and early implementation of cross border environmental management to address these problems. The Baltic Sea also stands out in providing a strong scientific foundation and accessibility to long term data series that provide a unique opportunity to assess the efficacy of management actions to address the breakdown of ecosystem functions. Trend reversals such as the return of top predators, recovering fish stocks, and reduced input of nutrient and harmful substances could be achieved only by implementing an international, cooperative governance structure transcending its complex multistate policy setting, with integrated management of watershed and sea. The Baltic Sea also demonstrates how rapidly progressing global pressures, particularly warming of Baltic waters and the surrounding catchment area, can offset the efficacy of current management approaches. This situation calls for management that is (i) conservative to provide a buffer against regionally unmanageable global perturbations, (ii) adaptive to react to new management challenges, and, ultimately, (iii) multisectorial and integrative to address conflicts associated with economic trade offs.
Serious injuries in the traffic accident situation: definition, importance and orientation for countermeasures based on a representative sample of in depth accident cases in Germany
Year: 2018

For many years, there are three groups of injury severity used for describing traffic accident patterns, i.e. minor, severe and fatal. In 2015, the European Commission has committed to set a common EU target for the reduction of the number of seriously injured traffic participants by 2020. This leads to the need of new criteria of seriously injured casualties, for which MAIS 3+ is proposed. A study on a representative accident data collection GIDAS (German In Depth Accident Study) was used to calculate the percentages of seriously injured casualties for different kinds of traffic participants based on a statistical random procedure and weighting process in relation to the German national statistics. All injuries (kind, location, AIS) and other accident parameter (deformation, speed, accident types) of the in depth accident sample are documented by a scientific team. Accidents from the years 2009 to 2013 were evaluated for this study. 8,217 accidents with 15,955 participants and 20,083 injured persons of all kind of traffic participants were analysed, 2,000 were severely injured, of these 416 seriously MAIS 3+ The assumption of seriously injured persons except fatalities in traffic accidents for Germany based on GIDAS calculation can be stated as 21% of severe injured persons and as 4% of all injured traffic participants in Germany. The study describes one way to get information (numbers/percentages) of seriously injured casualties based on MAIS 3+ and based on real world in depth accident cases. The study gives proposals for countermeasures on further safety issues for avoiding severe injuries, distinguished for different kinds of traffic participants and shows injury characteristics for the help for protective tasks.
Bacterial community structure and response to nitrogen amendments in Lake Shenandoah (VA, USA)
Venue: Water science and technology a journal of the International Association on Water Pollution Research
Year: 2019

Microbial processes are critical to the function of freshwater ecosystems, yet we still do not fully understand the factors that shape freshwater microbial communities. Furthermore, freshwater ecosystems are particularly susceptible to effects of environmental change, including influx of exogenous nutrients such as nitrogen and phosphorus. To evaluate the impact of nitrogen loading on the microbial community structure of shallow freshwater lakes, water samples collected from Lake Shenandoah (Virginia, USA) were incubated with two concentrations of either ammonium, nitrate, or urea as a nitrogen source. The potential impact of these nitrogen compounds on the bacterial community structure was assessed via 16S rRNA amplicon sequencing. At the phylum level, the dominant taxa in Lake Shenandoah were comprised of Actinobacteria and Proteobacteria, which were not affected by exposure to the various nitrogen treatments. Overall, there was not a significant shift in the diversity of the bacterial community of Lake Shenandoah with the addition of nitrogen sources, indicating this shallow system may be constrained by other environmental factors.
Coping with the impacts of urban heat islands. A literature based study on understanding urban heat vulnerability and the need for resilience in cities in a global climate change context
Year: 2018

The urban heat island (UHI) is a phenomenon whereby temperature levels in urban areas are higher than in surrounding rural settings. Urban heat islands are a matter of increasing concern, since they can affect communities by exacerbating air pollution and greenhouse gas emissions (due to the greater use of air conditioning) and the occurrence of heat related illness, and may lead to higher levels of mortality. This paper provides a description of the phenomena of (UHI) and an analysis of how cities are vulnerable to it. It highlights the need for resilience and the variety of means by which the UHI can be tackled. It describes a set of trends in two regions in Germany and Australia, which illustrate the scope of the problem in the northern and southern hemispheres, and the scale of vulnerability. Then, existing UHI vulnerability assessments are analysed to highlight common features and differences. Based on this, we propose a classification of adaptability parameters to support vulnerability assessments. The paper also discusses current mitigation approaches mentioned in the literature, and how these address some vulnerabilities. It concludes that both a better understanding of the UHI phenomena and consideration of the particular context of each city is needed to make urban areas more resilient to UHI.
Contributions of cognitive inflexibility to eating disorder and social anxiety symptoms.
Venue: Eating behaviors
Year: 2016

Eating disorders and social anxiety are highly co occurring. These disorders share fears of social evaluation, possibly maintained by similar cognitive content and styles, including an inability to adapt or flexibly respond to unexpected conditions. However, the role of cognitive inflexibility in eating disorders in relation to social anxiety has not been explored.  In this study, the link between eating disorder symptoms and cognitive inflexibility, while accounting for social anxiety, is examined.  Participants (N=461) were undergraduates who completed the Detail and Flexibility Questionnaire 12 item Cognitive Rigidity subscale, the Eating Disorders Diagnostic Scale, and the Social Interaction Anxiety Scale.  Eating disorder symptoms and social anxiety were both positively correlated with cognitive inflexibility. After controlling for social anxiety, the relationship between eating disorder symptoms and cognitive inflexibility remained robust.  Further examination of cognitive inflexibility in eating disorders and comorbid social anxiety in clinical samples is warranted. We suggest future directions for examining cognitive inflexibility as a trans diagnostic construct important to eating disorders and frequently comorbid disorders, consistent with NIMH Research Domain Criteria.
Peace Education in Foreign Language Classroom
Year: 2017

Due to the ever improving relations between the nations of the world in many respects for the last decades, foreign language teaching has been an area which occupies a large place in the agenda of every modern individual. Numerous studies have been carried out to realize effective foreign language teaching. Materials designed for this purpose are intended not only to teach the structural language, vocabulary, listening, speaking, reading and writing but also to present texts including knowledge in many different areas presumed to attract attention by learners. Because foreign language teaching materials are also essential course materials that can contribute to the cultural accumulation of learners, topics focusing on 'peace' as a concept indispensable for the present and future of mankind should also be included in the course material as much as possible. In this way, with a focus on peace as a common universal notion, the importance of peace in one's country, peace with neighboring countries and peace in the whole world, students in every single county on earth may be conscious of the concept from a very early age. Growing with an understanding that peace is not an undeniable conclusion but an undeniable reason in every mutual relation, generations receiving peace education at school, especially in foreign language classes which allow flexibility in course content, may be more conscious of and insistent on peaceful approaches.  peace; peace education; foreign language education; global citizenship; global friendship and understanding
Placuit apostolicae (Ep. 1) of Zosimus of Rome and the Ecclesiastical Reorganization of Gaul
Year: 2015

Around the beginning of the fifth century the praetorian prefect for Gaul and the governor of Viennensis relocated their headquarters from Trier and Vienne respectively to Arles, which created a dispute between the bishops of Vienne and Arles as to whom should be metropolitan of the province of Viennensis. While the synod of Turin had proposed dividing the province in two ecclesiastically, problems emerged in 417 when Zosimus, bishop of Rome, within the first week of his election, asserted in his Epistula 1 (JK 328) that the bishop of Arles was to be metropolitan not only of Viennensis but over several provinces in the civil diocese of Septem Provinciae as well (depriving the bishops of Marseille, Vienne, and Narbonne of their metropolitan status) and thereby making him virtual papal vicar in the exercise of Roman prerogatives. This new arrangement created enormous religious conflict, as a further seven letters and synod in Rome in September 417 attest, including the efforts of Zosimus to declare the synod of Turin invalid.  Mathisen investigated this episode and concluded that Zosimus's efforts to assert his own authority over Gaul resulted only in uniting the Gallic churches against him. This paper seeks to analyse Zosimus's involvement in Gaul and argues that this was not really his plan but rather that of the bishop of Arles. It also seeks to ask whether or not Zosimus anticipated the resultant conflict, as well as the authority by which he sought to make these changes.
Joint Object Tracking and Segmentation with Independent Convolutional Neural Networks
Venue: CoVieW@MM
Year: 2018

Object tracking and segmentation are important research topics in computer vision. They provide the trajectory and boundary of an object based on their appearance and shape features. Most studies on tracking and segmentation focus on encoding methods for the feature of an object. However, the tracking trajectory and segmentation mask are acquired separately, although similar visual information is required for both methods. Therefore, in this paper, we propose a CNN based joint object tracking and segmentation framework that provides a segmentation mask while improving the performance of object tacker. In our model, the tracking model determines the trajectory of the target object as a bounding box in each frame. Given the bounding box at each frame, the segmentation model predicts a dense mask of the target object in the bounding box. Then, the segmentation mask is used to refine the bounding box for the tracking model. We evaluate the performance of our algorithm on DAVIS benchmark dataset by AUC score and mean IoU. We showed that the performance of original tracker was improved by our proposed framework.
GABRIELA LOCALITY: STARTING GEODETIC OBSERVATIONS TO DETECT THE SURFACE MANIFESTATIONS FROM UNDERMINING
Year: 2012

A new observation network has been built to observe the surface manifestations of undermining at Gabriela locality. This locality lies in the Czech part of the Upper Silesian Coal Basin and the history of the hard coal underground exploitation is more than 150 years long here. Recently, the last coal mining panel was started to be exploited here. Its location and mining parameters are very suitable for the analysis of the actual and future surface changes caused by undermining. The fixed points of the observation network are surveyed by geodetic GNSS method. This method enables the evaluation of both vertical subsidence and horizontal displacements. Such complex evaluation of processes on the surface of the undermined territory makes it possible to understand the progress of the subsidence depression and to capture the final phase of the surface undermining changes, i.e. the phase of the subsidence decline.
Oscillating Magnetoresistance in Graphene p n Junctions at Intermediate Magnetic Fields.
Venue: Nano letters
Year: 2017

We report on the observation of magnetoresistance oscillations in graphene p n junctions. The oscillations have been observed for six samples, consisting of single layer and bilayer graphene, and persist up to temperatures of 30 K, where standard Shubnikov de Haas oscillations are no longer discernible. The oscillatory magnetoresistance can be reproduced by tight binding simulations. We attribute this phenomenon to the modulated densities of states in the n and p regions.