nils-herrmann/clean_scirepeval huggingface dataset:
An efficient method for capturing flightless geese

Populations of local breeding or resident Canada geese (Branta canadensis) are widespread and are increasing in the United States (Sheaffer et al. 1987) As these populations have grown, so has the interest in these birds for aesthetic, recreational, and research purposes. This growth also has led to an increase in conflicts with human populations (Nelson and Oetting 1981, Conover and Chasko 1985) Examples of conflicts include damage or nuisance problems on lawns, golf courses, public beaches, parks, and agricultural fields. Other concerns include human health and safety issues such as aircraft collision risk and increased nutrient loading of ponds and public water supplies. Resident geese often are captured and relocated to resolve nuisance problems (Woronecki et al. 1990) or trapped for marking purposes during research or management studies. Trapping is often conducted during the bird's annual prebasic molt in mid summer. Geese lose all their flight feathers simultaneously during this molt and are flightless for a period of several weeks. During this period, they can be rounded up and caught relatively easily. The normal capture method involves erecting a corral or catch pen using chicken wire or nylon net fencing. The catch pen is held in place by threading support poles through the wire or net and hammering them into the ground. Lines or guide wires are often used to stabilize the pen, and ground boards may be needed to secure the bottom of the net to prevent birds from escaping underneath. Fence lines are erected in a similar manner at an angle leading out from the pen and help direct or funnel the geese. Geese are walked or herded toward the funnel and into the catch pen. This catch pen, although relatively simple, can take 30 60 minutes to erect and another 20 30 minutes to dismantle. In addition, the area where birds can be caught is limited. The trapping location must be relatively level so that birds cannot pass under the fence or pen and the ground must be soft enough to drive in the support poles. The process can be equipment heavy, time consuming, and inefficient, especially if only a small number of geese are to be captured. We describe a more efficient capture technique using lightweight, portable panels to herd and surround geese into a moveable catch pen. This method is quick, requires little equipment and preparation, and can be done almost anywhere, including hard surfaces such as pavements. This capture method also has been used to catch flightless (nuisance) ducks and mute swans. This report was completed in part with funds provided under the Federal Aid to Wildlife Restoration Program.
Interprofessional teamwork and team interventions in chronic care: A systematic review
Venue: Journal of interprofessional care

To identify key features of teamwork and interventions for enhancing interprofessional teamwork (IPT) in chronic care and to develop a framework for further research, we conducted a systematic literature review of IPT in chronic care for the years 2002 2014. Database searches yielded 3217 abstracts, 21 of which fulfilled inclusion criteria. We identified two more studies on the topic by scanning the reference lists of included articles, which resulted in a final total of 23 included studies. The key features identified in the articles (e.g. team member characteristics, common task, communication, cooperation, coordination, responsibility, participation, staff satisfaction, patient satisfaction, and efficiency) were structured in line with the input process output model, and evaluated interventions, such as tools, workshops, and changes in team structure, were added to the model. The most frequently evaluated team interventions were complex intervention programs. All but one of the 14 evaluation studies resulted in enhancement of teamwork and/or staff related, patient related, and organization related outcome criteria. To date, there is no consensus about the main features of IPT and the most effective team interventions in chronic care. However, the findings may be used to standardize the implementation and evaluation of IPT and team interventions in practice and for further research.
L'alteration de la permeabilite intestinale chainon manquant entre dysbiose et inflammation au cours de l'obesite

L'incidence croissante de l'obesite et de ses complications est un enjeu mondial de sante publique. Le role de l'intestin dans l'obesite se pose dans le contexte florissant des etudes sur le microbiote. Chez les rongeurs rendus obeses par un regime hyperlipidique, un changement du microbiote est associe a une alteration de la permeabilite intestinale, augmentant le passage d'antigenes alimentaires ou bacteriens et contribuant a une inflammation chronique de bas grade et une insulino resistance. Chez l'homme, les modifications de permeabilite intestinale et ses liens avec le microbiote et l'inflammation au cours de l'obesite sont encore peu documentes mais ces etudes sont en plein essor.
Optimal planning of hybrid renewable energy systems using HOMER: A review

World energy consumption is rising due to population growth and increasing industrialization. Traditional energy resources cannot meet these requirements with notice to their challenges, e.g. greenhouse gas emission and high lifecycle costs. Renewable energy resources are the appropriate alternatives for traditional resources to meet the increasing energy consumption, especially in electricity sector. Integration of renewable energy resources with traditional fossil based resources besides storages creates Hybrid Renewable Energy Systems (HRESs) To access minimum investment and operation costs and also meet the technical and emission constraints, optimal size of HRES's equipment should be determined. One of the most powerful tools for this purpose is Hybrid Optimization Model for Electric Renewables (HOMER) software that was developed by National Renewable Energy Laboratory (NREL) United States. This software has widely been used by many researchers around the world. In this paper a review of the state of the art of researches, which use HOMER for optimal planning of HRES, is presented.
Classification of Normal and Apoptotic Cells from Fluorescence Microscopy Images Using Generalized Polynomial Chaos and Level Set Function
Venue: Microscopy and Microanalysis

Accurate automated quantitative analysis of living cells based on fluorescence microscopy images can be very useful for fast evaluation of experimental outcomes and cell culture protocols. In this work, an algorithm is developed for fast differentiation of normal and apoptotic viable Chinese hamster ovary (CHO) cells. For effective segmentation of cell images, a stochastic segmentation algorithm is developed by combining a generalized polynomial chaos expansion with a level set function based segmentation algorithm. This approach provides a probabilistic description of the segmented cellular regions along the boundary, from which it is possible to calculate morphological changes related to apoptosis, i.e. the curvature and length of a cell's boundary. These features are then used as inputs to a support vector machine (SVM) classifier that is trained to distinguish between normal and apoptotic viable states of CHO cell images. The use of morphological features obtained from the stochastic level set segmentation of cell images in combination with the trained SVM classifier is more efficient in terms of differentiation accuracy as compared with the original deterministic level set method.
Hybrid Planning for Decision Making in Self Adaptive Systems
Venue: 2016 IEEE 10th International Conference on Self Adaptive and Self Organizing Systems (SASO)

Run time generation of adaptation plans is a powerful mechanism that helps a self adaptive system to meet its goals in a dynamically changing environment. In the past, researchers have demonstrated successful use of various automated planning techniques to generate adaptation plans at run time. However, for a planning technique, there is often a trade off between timeliness and optimality of the solution. For some self adaptive systems, ideally, one would like to have a planning approach that is both quick and finds an optimal adaptation plan. To find the right balance between these conflicting requirements, this paper introduces a hybrid planning approach that combines more than one planner to obtain the benefits of each. In this paper, to instantiate a hybrid planner we combine deterministic planning with Markov Decision Process (MDP) planning to obtain the best of both worlds: deterministic planning provides plans quickly when timeliness is critical, while allowing MDP planning to generate optimal plans when the system has sufficient time to do so. We validate the hybrid planning approach using a realistic workload pattern in a simulated cloud based self adaptive system.
Hybrid Planning For Self Adaptation

Self adaptive software systems make decisions at run time that seek to change their behavior in response to faults, changing environments and attacks. Therefore, having an appropriate decision making approach to find an adaptation strategy is critical to successful self adaptation. Ideally, when an adaptation is triggered, one would like to have a decision making approach that is both quick and finds an optimal adaptation strategy. However, often designers have to compromise between an approach that is quick to find an adaptation strategy and an approach that is slow but finds an optimal adaptation strategy. To deal with this trade off between quick decision making and finding an optimal adaptation strategy, this position paper proposes a hybrid planning approach that combines more than one decision making approach to bring their benefits together. As an initial proof of concept, the paper presents the results of a small experiment to demonstrate the potential of a hybrid planning approach in dealing with this trade off.
A Framework for Adaptive and Goal Driven Behaviour Control of Multi robot Systems
Venue: 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W)

Robot and multi robot systems are leaving the friendly well structured world of automation and are facing the challenges of a dynamic world. Such uncertain conditions call for a high degree of robustness and adaptivity for individual robots as well as for the organization of multi robot systems. This corresponds to the concepts of self adaptation and self organization. Robots adapting to the dynamic environment still have to pursue their given tasks or goals. In order to address the requirements of creating adaptive and goal driven multi robot systems, it is necessary to combine existing goal directed planning and decision making approaches with self adaptation and self organization mechanisms. This work addresses this challenge with a new hybrid approach integrated into a common robot framework, combining symbolic planning with reactive behaviour networks, machine learning, and the pattern based selection of suitable mechanisms. On that account it brings together the advantages of bottom up and top down oriented approaches.
Proposal of a novel GaN/SiC hybrid FET (HyFET) with enhanced performance for high voltage switching applications
Venue: 2016 28th International Symposium on Power Semiconductor Devices and ICs (ISPSD)

A novel GaN/SiC HyFET is proposed as a high voltage power switch with low ON resistance and enhanced switching performance. The device combines the merits of SiC vertical devices and GaN lateral HEMTs by utilizing a SiC drift region to sustain high OFF state voltage and an enhancement mode AlGaN/GaN heterojunction channel to reduce the channel resistance. Compared with conventional SiC MOSFETs of the same voltage rating, the HyFET exhibits a greatly reduced Ron owing to the high electron mobility in the channel, together with dramatically lower Crss and QG. Furthermore, the HyFET provides a unipolar reverse conduction diode with a smaller operating voltage and superior reverse recovery property.
Simplified seismic assessment of buildings using non uniform Timoshenko beam model in low to moderate seismicity regions

In low to moderate seismicity regions, the limited seismic displacement demands could probably render tall buildings remaining nearly elastic during a maximum considered earthquake. Previous studies have shown the capability of the uniform Timoshenko beam model in resembling the dynamic behaviors of regular buildings. This article describes response spectrum analyses on the non uniform Timoshenko beam model, considering the first four vibration modes to assess the seismic demands on various building types, which encompass low rise wall or frame buildings and high rise shear wall buildings with or without transfer structures. Simplified design charts correlating the global seismic demands spectral accelerations, maximum interstory drift ratios, roof drift ratios and required shear areas to the fundamental translational period of each building are developed. The structural periods could be determined from in situ dynamic tests, full frame models or an appropriate period height equation, the latter of which is provided here by calibrating from in situ vibration tests of regional buildings constructed in compliance with British Standards. This simplified approach provides a fast track to seismic performance for both existing and new buildings, which could easily be comprehended by engineers without prior knowledge of seismic design.
AMP activated protein kinase mediates mitochondrial fission in response to energy stress
Venue: Science

How to shape mitochondrial networks Mitochondria undergo fragmentation or fusion in response to changes in cellular metabolism. Toyama et al. report that adenosine monophosphate activated protein kinase (AMPK) is both necessary and sufficient to control mitochondrial fragmentation. AMPK functions as a sensor to monitor the energy status of the cell by phosphorylating mitochondrial fission factor (MFF) a protein of the mitochondrial outer membrane. MFF then acts to recruit a cytoplasmic guanosine triphosphatase that promotes mitochondrial fission. Science, this issue p. 275 An energy sensing kinase phosphorylates a mitochondrial membrane protein that initiates fragmentation. Mitochondria undergo fragmentation in response to electron transport chain (ETC) poisons and mitochondrial DNA linked disease mutations, yet how these stimuli mechanistically connect to the mitochondrial fission and fusion machinery is poorly understood. We found that the energy sensing adenosine monophosphate (AMP) activated protein kinase (AMPK) is genetically required for cells to undergo rapid mitochondrial fragmentation after treatment with ETC inhibitors. Moreover, direct pharmacological activation of AMPK was sufficient to rapidly promote mitochondrial fragmentation even in the absence of mitochondrial stress. A screen for substrates of AMPK identified mitochondrial fission factor (MFF) a mitochondrial outer membrane receptor for DRP1, the cytoplasmic guanosine triphosphatase that catalyzes mitochondrial fission. Nonphosphorylatable and phosphomimetic alleles of the AMPK sites in MFF revealed that it is a key effector of AMPK mediated mitochondrial fission.
Childhood socioeconomic disadvantage is associated with lower mortality in older Japanese men: the JAGES cohort study
Venue: International journal of epidemiology

Childhood socioeconomic disadvantage has been previously linked to increased mortality risk in adulthood. However, most previous studies have focused on middle aged adults in Western contexts. Here, we sought to examine the association between childhood socioeconomic status (SES) and mortality among healthy older Japanese adults.  We conducted a 3 year follow up of participants in the Japan Gerontological Evaluation Study (JAGES) a population based cohort of 65 to 103 year old Japanese adults. Childhood SES was assessed by survey at baseline. Mortality from 2010 to 2013 was analysed for 15 449 respondents (7143 men and 8306 women) Cox regression models were used to estimate hazard ratios (HR) for risk of death.  A total of 754 deaths occurred during the 3 year follow up. Lower childhood SES was significantly associated with lower mortality in men, but not in women. Compared with men growing up in more advantaged childhood socioeconomic circumstances, the age adjusted HR for men from low childhood SES backgrounds was 0.75 [95% confidence interval (CI) 0.56 1.00] The association remained significant after adjustment for height, education, adult SES, municipalities of residence, health behaviours, disease status and current social relationships (HR 0.64; 95% CI 0.47 0.87) This association was stronger among men aged 75 years or older, HR 0.67 (95% CI: 0.47 0.95) compared with men aged 65 74 years, HR 0.90 (95% CI: 0.54 1.51)  Childhood socioeconomic disadvantage is associated with lower mortality among men aged 75 years or older, which may be due to selective survival, or alternatively to childhood physical training or postwar calorie restriction in this generation of Japanese males.
Neighbourhood disadvantage and self reported type 2 diabetes, heart disease and comorbidity: a cross sectional multilevel study.
Venue: Annals of epidemiology

This study examines associations between neighborhood socioeconomic disadvantage and self reported type 2 diabetes and heart disease, occurring separately and concurrently at a single time point (comorbidity)  This study included 11,035 residents from 200 neighborhoods in Brisbane, Australia. Respondents self reported type 2 diabetes and heart disease as long term health conditions. Neighborhood socioeconomic disadvantage was measured using a census derived composite index. Individual socioeconomic position was measured using education, occupation, and household income. Data were analyzed using multilevel multinomial mixed effects logistic regression using Markov chain Monte Carlo simulation.  Compared with the most advantaged neighborhoods, residents of the most disadvantaged neighborhoods were more likely to report type 2 diabetes (odds ratio [OR] 2.21, 95% credible interval [CrI] 1.55 3.15) heart disease (OR 1.72, 95% CrI 1.25 2.38) and comorbidity (OR 4.38, 95% CrI 2.27 8.66) This relationship attenuated after adjustment for individual level socioeconomic position, but remained statistically significant for type 2 diabetes (OR 1.81, 95% CrI 1.15 2.83) and comorbidity (OR 3.00, 95% CrI 1.49 6.13) CONCLUSIONS Studies of neighborhood disadvantage that fail to include individual level socioeconomic measures may inflate associations. Establishing why residents of disadvantaged neighborhoods are more likely to experience the co occurrence of heart disease and type 2 diabetes independent of their individual socioeconomic position warrants further investigation.
3D facial landmark localization using texture regression via conformal mapping
Venue: Pattern Recognit. Lett.

We propose a new 3D facial landmark detection method based on regression method on 2D image.Our method combines both 3D shape and 2D texture information.Our method is robust to pose and expression. 3D facial alignment typically requires the accurate estimate of facial landmarks. Most existing landmark detection methods use geometry characterization or resort to regression algorithms performed on point clouds or range images. A method combining both 3D geometry information and 2D texture has rarely been investigated. In this paper, we propose a novel 3D facial landmark localization algorithm, based on conformal geometric mapping, that can convert a 3D model to 2D using both geometry and texture information. Then a two layers regression method is used to improve the stability of landmark localization on the 2D geometry images. This method is impervious to pose changes and robust with respect to changes in expression. We evaluated the proposed approach on publicly available datasets and demonstrate how the use of 2D regression methods boosts the robustness and accuracy of 3D facial landmark localization.
Extraction Algorithms for Hierarchical Header Structures from Spreadsheets
Venue: EDBT/ICDT Workshops

Spreadsheets are widely used to manage statistical data, and a massive amount of valuable spreadsheets are now public as open data. Spreadsheet headers may contain hierarchical structures, and values in spreadsheets are associated with not only headers at the same column or row but also those corresponding to their ancestors. When integrating spreadsheets with other datasets, it is necessary to extract hierarchical header structures and associate this information with values. In this paper, we propose three algorithms to extract hierarchical structures from spreadsheets based on the relation of values. Since our algorithms are focused only on values, they can be applied to heterogeneous spreadsheets such that the structures of row or column headers are not explicitly in
Consumer evaluations of green brand extensions: The role of parent brand quality and perceived fit

The environmental imperative is increasingly influencing the marketing agenda. The pressure for a more environmentally friendly approach in marketing is derived from the environmental issues such as climate change but also from consumers looking for greener options to support their sustainable lifestyles. Many companies have answered these demands by introducing new green products by exploiting brand extension strategies. That is, using an existing brand name to enter new categories and markets. Despite the growing interest in sustainable living, the adoption of green products has remained relatively low, and questions on what influences the evaluation and adoption of green products has raised managerial and academic interest. This paper investigates how Finnish consumers evaluate hypothetical green brand extensions of Finnish consumer goods brands and what is the role of parent brand quality and perceived fit in the evaluations. What is more, the role of consumer's environmental background to fit perceptions is examined. The theoretical background for the current research was derived from corporate social responsibility and brand research, and hypotheses were formed based on previous research in these fields. The empirical data was collected through an online consumer survey during spring 2016 with Finnish consumers as the target population. Altogether 238 responses were collected and the results were analysed with descriptive statistics and two different multivariate data analysis methods: factor analysis and multiple regression analysis. The main finding of the research was that perceived fit between the parent brand and the extension, in addition to perceived fit between the brand and environmental cause were the most important predictors of positive brand extension evaluation. The main contribution of this research is to add understanding on what are the main determinants of green brand extension success.
The Tail at Scale: How to Predict It?
Venue: HotCloud

Scale out applications have emerged as the dominant Internet services today. A request in a scale out workload generally involves task partitioning and merging with barrier synchronization, making it difficult to predict the request tail latency to meet stringent tail Service Level Objectives (SLOs) In this paper, we find that the request tail latency can be faithfully predicted, in the high load region, by a prediction model using only the mean and variance of the task response time as input. The prediction errors for the 99th percentile request latency are found to be consistently within 10% at the load of 90%for both model and measurement based testing cases. Consequently, the work in this paper establishes an important link between the request tail SLOs and the low order task statistics in a high load region, where the resource provisioning is desired. Finally, we discuss how the prediction model may facilitate highly scalable, tail constrained resource provisioning for scaleout workloads.