nils-herrmann/clean_scirepeval huggingface dataset:
Omeka.net as a librarian led digital humanities meeting place

This case study aims to evaluate Omeka.net, the hosted Web publishing exhibit tool, as a low cost and technology friendly platform encouraging dynamic academic and non academic communities to collaborate, explore and contribute to a genre film festival resource.  A literature review established six variables to assess Omeka.net as a viable platform for libraries seeking to administer a resource focused website adhering to information standards with limited budgets, training and technical or institutional support. The variables identified were cost; website management; content building and management; communities, engagement and collaboration; exploration and knowledge building; and website support. Findings Omeka.net supports many activities with notable functions for website administration; collection building; media formats; collaboration; metadata; social media; user contributions; technical support; and the creation of simple, custom pages. While templates for
[Assessment of Gaseous Nitrogen (NH3 and N2O) Mitigation After the Application of a Range of New Nitrogen Fertilizers in Summer Maize Cultivation]
Venue: Huan jing ke xue= Huanjing kexue

In order to evaluate the potential of a range of new nitrogen fertilizers in comparison with the conventional fertilization to mitigate ammonia (NH3) and nitrous oxide (N2O) emissions, a field experiment was conducted to investigate NH3 volatilization and N2O emissions from the summer maize field and the relevant driving factors under the different nitrogen fertilizer treatments. Five new varieties of nitrogen fertilizers including the urea ammonium (UA) stability urea with dicyandiamide and hydroquinone (UHD) sulfur coated urea (SCU) urea formaldehyde compound fertilizer (UF) and organic fertilizer (OF) were applied in this experiment, and conventional fertilization (compound fertilizer urea, CK) was used as the control. The nitrogen amount of 300 kg*hm 2 was applied in all treatments. Correlation analysis results showed that both NH3 volatilization and N2O emissions were influenced by environmental factors. They were negatively correlated with soil water filled pore space (P<0.05) Moreover, N2O emissions were positively correlated with soil nitrate nitrogen (P<0.01) Regression analysis showed that N2O emissions were mainly determined by the soil nitrate content, while NH3 volatilization was mainly dependent on the values of soil ammonium nitrogen. Compared with CK, in addition to UA, other fertilizer treatments decreased the NH3 volatilization, especially the UF and OF treatments decreased NH3 volatilization by up to 37% 43% while all treatments had no significant difference in N2O emissions. Considering the total gaseous nitrogen losses (NH3 volatilization N2O emissions) in comparison with CK, the UHD, SCU, UF and OF were reduced by 9% 5% 30% and 23% respectively, while the UA was increased by 3% Therefore, considering environmental benefit under this experimental condition,urea formaldehyde compound fertilizer and organic fertilizer were more suitable for maize cultivation.
Ammonia volatilization following nitrogen fertilization with enhanced efficiency fertilizers and urea in loblolly pine (Pinus taeda L. plantations of the southern United States

losses following surface application of urea and three enhanced efficiency nitrogen (N) containing fertilizers (EEFs) were compared in six thinned mid rotation loblolly pine Pinus taeda L. stands across the southern United States. All fertilizer treatments were labeled with 15 N ~370%0, 0.5 AP) and applied during two different seasons (spring, summer) in 2011 to open chamber microcosms. Individual microcosms were sampled 1, 15 and 30 days after fertilization to estimate remaining 15 N. Losses of fertilizer N were determined using a mass balance calculation. Significantly less N loss occurred following fertilization with EEFs compared to urea after all sampling days for both seasons. Because root uptake was eliminated in the microcosms and there was no leaching of 15 N below the microcosms, the most likely loss pathway of the 15 N from the microcosms was NH 3 volatilization. There were generally no differences among the individual EEFs. Following spring application, the mean NH 3 volatilization during the 30 day experiment ranged from 4% to 26% for the EEFs compared to 26 40% for urea. In summer, mean NH 3 volatilization for EEFs ranged from 8% to 23% compared to 29 49% for urea. This research highlights the potential of EEFs to reduce loss of fertilizer N in forest systems, potentially increasing fertilizer N use efficiency in these pine plantations.
Impact of insecure accommodation and theliving environment on Gypsies' and Travellers'health

Gypsies and Travellers experience some of the poorest health outcomes of any group in society. Accommodation insecurity, the conditions of their living environment, community participation and discrimination all play key roles in exacerbating these poor health outcomes, while at the same time these factors also hold the key to effectively addressing and improving the health and wellbeing of these communities. Long term, joined up working is urgently required at both local and national level to address the wider social determinants of Gypsies and Travellers health. This report was commissioned by the Department of Health to inform the work of the National Inclusion Health Board.
Parameter uncertainty and reserve risk under Solvency II

In this article we consider the parameter risk in the context of internal modelling of the reserve risk under Solvency II. We discuss two opposed perspectives on parameter uncertainty and point out that standard methods of classical reserving focusing on the estimation error of claims reserves are in general not appropriate to model the impact of parameter uncertainty upon the actual risk of economic losses from the undertakings's perspective. Referring to the requirements of Solvency II we assess methods to model parameter uncertainty for the reserve risk by comparing the probability of solvency actually attained when modelling the solvency risk capital requirement based on the respective method to the required confidence level. Using the simple example of a normal model we show that the bootstrapping approach is not appropriate to model parameter uncertainty according to this criterion. We then present an adaptation of the approach proposed in \cite {froehlich2014} Experimental results demonstrate that this new method yields a risk capital model for the reserve risk achieving the required confidence level in good approximation.
A COMMUNITY RESILIENCE APPROACH TO ASSESSING TRANSPORTATION RISK IN DISASTERS

This paper addresses the need for new measures and models of infrastructure performance that can facilitate the strengthening of community resilience to disasters. While many infrastructure measures and models focus on performance in terms of disaster induced damage, from the perspective of populations and cities that would be affected, there is a need for analysis of service loss and of approaches to rapidly restore service in an emergency. Focusing on transportation, this paper notes limitations of current performance measures, proposes a systems analytic framework that addresses community resilience, and demonstrates how the framework can be applied to analyze and model transportation disruption in earthquakes and other disasters. The approach is demonstrated for a case study of south coastal British Columbia, Canada, with particular attention to the role of maritime transportation in the distribution of one essential commodity, gasoline fuel. Coastal communities in this region are extremely reliant on maritime transportation for delivery of essential goods such as fuel, and because of the shift towards just in time production systems, have very little storage or warehousing capacity. Expert interviews, stakeholder workshops, satellite based tracking of ships, and network analyses are used to characterize the transportation system and assess risk and resilience. Two approaches to system analysis are implemented: one emphasizing network topology, and the other focusing on network functionality. This enables a comparison of the strengths and limitations of these two major methodological approaches. In the case study demonstration, the topological approach is able to capture, with relatively low data requirements, the relative vulnerability of communities situated in different parts of the network. Resilience enhancing strategies that are related to network topology, such as adding network links as a response in emergencies, can be readily assessed. The topological approach is limited, however, in its ability to address detailed damage and operational issues related to emergency response actions that are key to resilience analysis. In the second approach, a functional model is developed that emphasizes flows in the network. This enables a more realistic representation of system operations, thereby facilitating more specific understanding of how transportation damage can lead to disruption of fuel flows and impacts to communities. The functional model can be readily integrated with hazard and facility damage models. The approach is particularly advantageous in being able to capture time dependent variables such as reserve volumes and supply deliveries, which are crucial types of information for assessing how different decision options (e.g. seismic retrofit of port facilities, increasing storage capacity, adding shipping routes) could enhance community resilience. Data requirements are very high, however, and pose an important limitation to this approach.
Topic trend of event management research

In spite of increasing numbers of publications and newly established journals in event management, research topics and themes have not drawn much attention among event scholars. This research note reports on research trends in event management journals and makes suggestions for future research. A total of 463 research articles published in the four event management journals and 78 event management articles in the loading hospitality and tourism journals were collected. The results showed that topics for event studies have changed over time. Recent studies heavily focus on visitor experiences, investigating motivation, satisfaction, and behavioral intention, while past studies paid more attention to the economic impact of events or volunteer motivation.
Optimization of operational parameters of electrocoagulation process for real textile wastewater treatment using Taguchi experimental design method

AbstractIn this paper, Taguchi method was applied to determine the optimum operating conditions for textile wastewater treatment by electrocoagulation (EC) with iron electrodes. The removal efficiency of chemical oxygen demand (COD) and turbidity was considered as the performance parameters. L9 orthogonal array (OA, three factors in three levels) was selected as the experimental design for three controllable parameters mentioned above. These parameters that mainly affect the EC process were specified as initial pH, current density and electrolysis time. Each parameter was examined at three levels using Taguchi method. Performance analysis was followed by a variance analysis in order to determine the optimum levels and relative magnitude of the effect of parameters. Taguchi's "the larger the better" performance formula was used. The optimum operating conditions in terms of COD and turbidity were found to be initial pH of 7 and 8, current density of 150 A/m2 and electrolysis time of 20 and 30 min. At the op.
Rethinking organizational learning orientation on radical and incremental innovation in high tech firms

Does organizational learning orientation impede radical innovation? The results show that a high level learning orientation promotes myopic learning and incremental innovation, but constrains experimentation and radical innovation in emerging domains. The study tests hypotheses using two separate data analyses, comparing traditional PLS SEM with fsQCA. The empirical results show that fsQCA captures better predictive outcomes than PLS SEM. Entrepreneurs and high tech firms should interpret the findings with some cautions because of their prosperity based on competency and learning orientation in specific fields. For the high tech industry and entrepreneurial ventures, superior capability in a particular area leads to exploitative learning and cultivate incremental innovation.
Welding Groove Mapping Implementation and Evaluation of Image Processing Algorithms on Shiny Surfaces
Venue: VISIGRAPP

Electric arc welding is a key process in the heavy steel industries. It is a very complex task that demands a high degree of control in order to meet the international standards for fusion welding. We propose a Vision Based Measurement (VBM) system and evaluate how different algorithms impact the results. The proposed system joins hardware and software to image the welding plates using a single CMOS camera, run computer vision algorithms and control the welding equipment. A complete prototype, using a commercial linear welding robot is presented. The evaluation of the system as a groove mapping equipment, considering different processing algorithms combined with noise removal and line segment detection techniques, allows us to define the appropriated approach for shop floor operation, combining low asymptotic cost and measurement quality.
Vision based system for welding groove measurements for robotic welding applications
Venue: 2016 IEEE International Conference on Robotics and Automation (ICRA)

Electric arc welding is a complex task that demands a high degree of control in order to meet the international standards for fusion welding. We present a Vision Based Measurement (VBM) system and evaluate how different conditions and algorithms impact the measuring of beveled edges. The proposed system integrates hardware and software to image the welding plates using a single CMOS camera as visual sensor, run computer vision algorithms on a FPGA (Field Programmable Gate Array) board, controls the robot movements and adjust the weld pattern and welder equipment parameters. A complete prototype, using a commercial linear welding robot is presented. The evaluation of the system as a groove mapping equipment, considering different processing algorithms combined with noise removal and line segment detection techniques, shows the potential of the approach for shop floor operation.
Exclusionary Discipline Highest in New Hampshire's Urban Schools Suspension and Expulsion Found to Disproportionately Affect Disadvantaged Students

Exclusionary school discipline that is, suspension and expulsion disproportionately affects already disadvantaged students on both the national and state levels. In New Hampshire, students attending larger urban schools, male students, students of color, students eligible for free and reduced price lunch, students with disabilities, and homeless students are more likely to experience exclusionary school discipline, although racial disparities appear to stem largely from the greater racial diversity at the urban schools that use this type of discipline at higher rates with all students. Previous research indicates that exclusionary discipline and the resulting loss of classroom time is associated with poorer academic outcomes. Therefore, regardless of the precipitates of exclusionary discipline, it is worth exploring the extent to which exclusionary discipline is experienced among New Hampshire students.
"Restorative Justice" or Restoring Order? Restorative School Discipline Practices in Urban Public Schools

Suspension rates for students of color are higher than for White students, even in schools that utilize alternatives to suspension like restorative practices. This study draws on data from a year long multicase ethnography that sought to elucidate why such disproportionality prevails in schools that use restorative practices. This article focuses on one finding: that the individuals hired to be restorative coordinators were consistently young, non White staff from the same neighborhoods as their students. The majority White faculty and administration greatly depended on these coordinators to bond with, contain, and compel obedience from students of color.
Convolutional networks for fast, energy efficient neuromorphic computing
Venue: Proceedings of the National Academy of Sciences

Brain inspired computing seeks to develop new technologies that solve real world problems while remaining grounded in the physical requirements of energy, speed, and size. Meeting these challenges requires high performing algorithms that are capable of running on efficient hardware. Here, we adapt deep convolutional neural networks, which are today's state of the art approach for machine perception in many domains, to perform classification tasks on neuromorphic hardware, which is today's most efficient platform for running neural networks. Using our approach, we demonstrate near state of the art accuracy on eight datasets, while running at between 1,200 and 2,600 frames/s and using between 25 and 275 mW. Deep networks are now able to achieve human level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state of the art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt) and (iii) can be specified and trained using backpropagation with the same ease of use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain inspired computing one step closer.
Exact and approximate algorithms for discounted {0 1} knapsack problem
Venue: Inf. Sci.

The Discounted {0 1} Knapsack Problem (D{0 1}KP) is an extension of the classical 0 1 knapsack problem (0 1 KP) that consists of selecting a set of item groups where each group includes three items and at most one of the three items can be selected. The D{0 1}KP is more challenging than the 0 1 KP because four choices of items in an item group diversify the selection of the items. In this paper, we systematically studied the exact and approximate algorithms for solving D{0 1}KP. Firstly, a new exact algorithm based on the dynamic programming and its corresponding fully polynomial time approximation scheme were designed. Secondly, a 2 approximation algorithm for D{0 1}KP was developed. Thirdly, a greedy repair algorithm for handling the infeasible solutions of D{0 1}KP was proposed and we further studied how to use binary particle swarm optimization and greedy repair algorithm to solve the D{0 1}KP. Finally, we used four different kinds of instances to compare the approximate rate and solving time of the exact and approximate algorithms. The experimental results and theoretical analysis showed that the approximate algorithms worked well for D{0 1}KP instances with large value, weight, and size coefficients, while the exact algorithm was good at solving D{0 1}KP instances with small value, weight, and size coefficients.
Waterpixels and their application to image segmentation learning. (Waterpixels et leur application a l'apprentissage statistique de la segmentation)

In this work, we would like to provide a general method for automatic semantic segmentation, which could adapt itself to any image database in order to be directly used by non experts in im age analysis (such as biologists) To address this problem, we first propose to use pixel classification, a classic approach based on supervised learning, where the aim is to assign to each pixel the label of the object it belongs to. Features describing each pixel properties, and which are used to determine the class label, are often computed on a fixed shape support (such as a centered window) which leads, in particular, to misclassifications on object contours. Therefore, we consider another support which is wider than the pixel itself and adapts to the image content: the superpixel. Superpixels are homogeneous and rather regular regions resulting from a low level segmen tation. We propose a new superpixel generation method based on the watershed, the waterpixels, which are efficient, fast to compute and easy to handle by the user. They are then inserted in the classification pipeline, either in replacement of pixels to be classified, or as relevant supports to compute the features, called Superpixel Adaptive Features (SAF) This second approach consti tutes a general segmentation method whose pertinence is qualitatively and quantitatively evaluated on three databases from the biological field.
"Not on the agenda" A qualitative study of influences on health services use among poor young women who use drugs in Cape Town, South Africa.
Venue: The International journal on drug policy

Poor young women who use alcohol and other drugs (AODs) in Cape Town, South Africa, need access to health services to prevent HIV. Efforts to link young women to services are hampered by limited information on what influences service initiation. We explored perceptions of factors that influence poor AOD using young women's use of health services.  We conducted four focus groups with young women (aged 16 21) who used AODs and were recruited from two township communities in Cape Town. We also conducted 14 in depth interviews with health and social welfare service planners and providers. Discussion topics included young women's use of health services and perceived influences on service use. Qualitative data were analysed using a framework approach.  The findings highlighted structural, contextual, and systemic influences on the use of health services by young women who use AODs. First, young women were absent from the health agenda, which had an impact on the provision of women specific services. Resource constraints and gender inequality were thought to contribute to this absence. Second, gender inequality and stigma toward young women who used AODs led to their social exclusion from education and employment opportunities and health care. Third, community poverty resulted in the emergence of perverse social capital and social disorder that limited social support for treatment. Fourth, the health care system was unresponsive to the multiple service needs of these young women.  To reach young women who use AODs, interventions need to take cognisance of young women's risk environment and health systems need to adapt to respond better to their needs. For these interventions to be effective, gender must be placed on the policy agenda.