nils-herrmann/clean_scirepeval huggingface dataset:
Use of Facebook in Teaching: A Case Study of Fluid Mechanics Course

Fluid mechanics (FM) is a core course of the Chemical, Mechanical, Civil, and Aerospace Engineering programs. Students have both theory and practical classes in FM. The general expectation is that students should be able to demonstrate the fundamentals learnt in theory and get hands on experience during the lab course. In this regard, students were asked to make a video of application of FM in day to day life based on the fundamentals learnt in the classroom and to post it on the Facebook (FB) page entitled "Fluid Mechanics Videos." For the first time, FB is used as a teaching learning assessment tool in the FM undergraduate course. The primary objective was to create interest and passion about chemical engineering among students. Students made videos on different topics of FM, including fluid statics, properties of fluid, applications of mass/momentum/energy equation, and flow through a porous medium. Students opined that they felt confident in designing a storage tank, pipe, and unit operations equipment (e.g. packed bed, fluidized bed, and agitator) after taking this assignment. Through this assignment, students were able to design and conduct experiments. In addition, it gave them a chance to assess their communication ability, work with multidisciplinary teams, and understand contemporary issues. The author was involved right from ideation to preparation of video to its final upload on FB. Based on this pilot study, it can be hypothesized that social networking sites (SNSs) can only supplement, enhance, and strengthen the traditional classroom process, but can never replace it. SNSs can be best used innovatively for assignment, homework, group project, preparatory class, and team activities.
Average monthly and annual climate maps for Bolivia

This study presents monthly and annual climate maps for relevant hydroclimatic variables in Bolivia. We used the most complete network of precipitation and temperature stations available in Bolivia, which passed a careful quality control and temporal homogenization procedure. Monthly average maps at the spatial resolution of 1 km were modeled by means of a regression based approach using topographic and geographic variables as predictors. The monthly average maximum and minimum temperatures, precipitation and potential exoatmospheric solar radiation under clear sky conditions are used to estimate the monthly average atmospheric evaporative demand by means of the Hargreaves model. Finally, the average water balance is estimated on a monthly and annual scale for each 1 km cell by means of the difference between precipitation and atmospheric evaporative demand. The digital layers used to create the maps are available in the digital repository of the Spanish National Research Council.
The role of local joint flexibility (LJF) in the structural assessments of ageing offshore structures

The distribution of fixed steel offshore platforms around the world reveal a global fleet that has exceeded or is approaching the end of its design life. In many operating areas, there is an attraction to continue using these aging facilities due to continued production or as an adjoining structure to facilitate a new field development or expansion. To justify continued operations of the fixed offshore platform, various integrity assessment techniques are often used. One of the major techniques used is the phenomena of Local Joint Flexibility (LJF) The substructure of a fixed offshore platform is generally made up of steel tubular members. These tubular members are connected at joints by thickened sections called joint cans. These joint cans are designed as rigid tubular joint connections however in reality tubular joints exhibit some degree of flexibility. This local flexibility at the tubular joint allows a better redistribution of the moments and thus stresses to other members of the jacket truss structure compared to the rigid joint condition. This re distribution of moments and stresses therefore allow the tubular joint to exhibit much longer fatigue lives and greater strength capacity than the design condition, assessed to 20 30 years previously.
Abstractive Text Summarization using Sequence to sequence RNNs and Beyond
Venue: CoNLL

In this work, we model abstractive text summarization using Attentional Encoder Decoder Recurrent Neural Networks, and show that they achieve state of the art performance on two different corpora. We propose several novel models that address critical problems in summarization that are not adequately modeled by the basic architecture, such as modeling key words, capturing the hierarchy of sentence to word structure, and emitting words that are rare or unseen at training time. Our work shows that many of our proposed models contribute to further improvement in performance. We also propose a new dataset consisting of multi sentence summaries, and establish performance benchmarks for further research.
Discrete Event Simulation and Virtual Reality Use in Industry: New Opportunities and Future Trends
Venue: IEEE Transactions on Human Machine Systems

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real time data streams and Big Data sets.
Deep Neural Network Baseline for DCASE Challenge 2016

The DCASE Challenge 2016 contains tasks for Acoustic Scene Classification (ASC) Acoustic Event Detection (AED) and audio tagging. Since 2006, Deep Neural Networks (DNNs) have been widely applied to computer visions, speech recognition and natural language processing tasks. In this paper, we provide DNN baselines for the DCASE Challenge 2016. In Task 1 we obtained accuracy of 81.0% using Mel DNN against 77.2% by using Mel Frequency Cepstral Coefficients (MFCCs) Gaussian Mixture Model (GMM) In Task 2 we obtained F value of 12.6% using Mel DNN against 37.0% by using Constant Q Transform (CQT) Nonnegative Matrix Factorization (NMF) In Task 3 we obtained F value of 36.3% using Mel DNN against 23.7% by using MFCCs GMM. In Task 4 we obtained Equal Error Rate (ERR) of 18.9% using Mel DNN against 20.9% by using MFCCs GMM. Therefore the DNN improves the baseline in Task 1, 3, and 4, although it is worse than the baseline in Task 2. This indicates that DNNs can be successful in many of these tasks, but may not always perform better than the baselines.
CP JKU SUBMISSIONS FOR DCASE 2016 A HYBRID APPROACH USING BINAURAL I VECTORS AND DEEP CONVOLUTIONAL NEURAL NETWORKS

This report describes the 4 submissions for Task 1 (Audio scene classification) of the DCASE 2016 challenge of the CP JKU team. We propose 4 different approaches for Audio Scene Classification (ASC) First, we propose a novel i vector extraction scheme for ASC using both left and right audio channels. Second, we propose a Deep Convolutional Neural Network (DCNN) architecture trained on spectrograms of audio excerpts in end to end fashion. Third, we use a calibration transformation to improve the performance of our binaural i vector system. Finally, we propose a late fusion of our binaural i vector and the DCNN. We report the performance of our proposed methods on the provided cross validation setup for the DCASE 2016 challenge. Using the late fusion approach, we improve the performance of the baseline by 17 percentage point in accuracy. Our submissions achieved ranks first and second among 49 submissions in the audio scene classification task of DCASE 2016 challenge.
Experiments on the DCASE Challenge 2016: Acoustic Scene Classification and Sound Event Detection in Real Life Recording
Venue: ArXiv

In this paper we present our work on Task 1 Acoustic Scene Classi fication and Task 3 Sound Event Detection in Real Life Recordings. Among our experiments we have low level and high level features, classifier optimization and other heuristics specific to each task. Our performance for both tasks improved the baseline from DCASE: for Task 1 we achieved an overall accuracy of 78.9% compared to the baseline of 72.6% and for Task 3 we achieved a Segment Based Error Rate of 0.76 compared to the baseline of 0.91.
Detection for Real Life Audio DCASE Challenge

We explore logistic regression classifier (LogReg) and deep neural network (DNN) on the DCASE 2016 Challenge for task 3, i.e. sound event detection in real life audio. Our models use the Mel Frequency Cepstral Coefficients (MFCCs) and their deltas and accelerations as detection features. The error rate metric favors the simple logistic regression model with high activation threshold on both segmentand event based contexts. On the other hand, DNN model outperforms the baseline in frame based context.
Estimating an Inverse Gamma distribution

In this paper we introduce five different algorithms based on method of moments, maximum likelihood and full Bayesian estimation for learning the parameters of the Inverse Gamma distribution. We also provide an expression for the KL divergence for Inverse Gamma distributions which allows us to quantify the estimation accuracy of each of the algorithms. All the presented algorithms are novel. The most relevant novelties include the first conjugate prior for the Inverse Gamma shape parameter which allows analytical Bayesian inference, and two very fast algorithms, a maximum likelihood and a Bayesian one, both based on likelihood approximation. In order to compute expectations under the proposed distributions we use the Laplace approximation. The introduction of these novel Bayesian estimators opens the possibility of including Inverse Gamma distributions into more complex Bayesian structures, e.g. variational Bayesian mixture models. The algorithms introduced in this paper are computationally compared using synthetic data and interesting relationships between the maximum likelihood and the Bayesian approaches are derived.
On the Multivariate Gamma Gamma Distribution With Arbitrary Correlation and Applications in Wireless Communications
Venue: IEEE Transactions on Vehicular Technology

The statistical properties of the multivariate gamma gamma (GG) distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (pdf) cumulative distribution function (cdf) and moment generation function (mgf) of the multivariate GG distribution with arbitrary correlation. Furthermore, we present novel approximating expressions for the pdf and cdf of the sum of GG random variables (RVs) with arbitrary correlation. Based on this statistical analysis, we investigate the performance of radio frequency (RF) and optical wireless communication systems. It is worth noting that the presented expressions include several previous results in the literature as special cases.
Determinants of sustainable/green consumption: a review

The resource intensive lifestyle of people has given birth to unsustainable consumption. This paper combines the existing knowledge on antecedents of sustainable consumption (SC) to enhance the understanding and highlights the significance of new research. It also identifies new research ideas in the area of sustainable/green consumption. The review reveals the sparse work done in examining the impact of certain socio psychographic antecedents and the sustainable consumption process as a whole. This review, though a selective rather than exhaustive, identifies 28 independent variables as antecedents of SC and it suggests to look at the linear and nonlinear effects of individual level factors as well as institutional level factors.
Small is green? Urban form and sustainable consumption in selected OECD metropolitan areas

This article examines the relationship between urban form and sustainable consumption practices across selected OECD metropolitan areas. Using resources available from the OECD database and the International Social Survey Programme, the research identifies factors associated with the stated frequency of making efforts to adopt a sustainable lifestyle across the selected areas. Results confirm that everyday sustainability practice is a function of personal factors, i.e. the socio economic characteristics of the individuals and environmental concern, whereas the impacts of contextual factors related to urban form are modest. Residents living in compact developments are not more likely to drive less or reduce energy consumption as a means to mitigate their environmental impacts. The article discusses the implications for spatial planning and policy making in terms of the primary effects of the built environment on sustainable consumption and the tension between urban density and greenspace provision.
Investigation of the Action of the Anolyte after Different Storage Times on the Gram negative Bacteria

The increasing resistance of pathogenic bacteria to antimicrobial agents is one of the biggest problems today. Bacteria develop resistance not only to antibiotics, but also to disinfectants and fighting them becomes more difficult. On the other hand, the protection of the environment from toxic effects of commonly used disinfectants in medicine, household, industry, agriculture and other fields of human activity is an environmental issue with significant importance. Therefore the demand and application of efficient and at the same time safer from the environmental perspective antimicrobials is very topical. One promising modern approaches in this respect is the electrochemical treatment of water with electricity, which leads to the International Journal of Current Microbiology and Applied  (2016) pp. 530 539 Journal homepage: http:/www.ijcmas.com
Negative Effects of Late Bronze Age Human Activity on Modern Soils and Landscapes, a Case study on the Muradymovo Settlement, Urals, Russia

The study site is the Late Bronze Age (1750 1350 BC cal) settlement of Muradymovo located in the Urals, Russia (53deg58'44.8' N, 55deg30'58.8' E) Despite the presence of a humid climate, the modern soils of the study site contain more than 27% of gypsum at a depth of just 10 cm from the surface and have a microrelief typical of a gypsum desert. The nearby background Chernozems are gypsum free to a depth of 2 metres. The ancient people of the "Srubno Alakul" archaeological culture had a tradition of building their houses from gypsum rock. This is an excellent construction material in dry climates, but dissolves quickly under humid conditions. According to the archaeological data, the ancient people rebuilt their houses more than five times within a period of 200 years, thereby bringing a lot of gypsum to this site, which was later abandoned. At the present time, this area is still unsuitable for human settlement, because the water of the nearest small river is still contaminated by gypsum and has a bitter taste. The properties of modern soils directly affected by Late Bronze Age human activities have been identified as a result of our studies on soil morphology and chemistry (pH, Corg. Ptot, gypsum and calcium carbonate concentrations) Remarkably, there is residual soil contamination by gypsum even after 3,500 years since the abandonment of the site. IANSA 2016 VII/2 169 178 Alexandra Golyeva, Olga Khokhlova, Nikolai Shcherbakov, Iia Shuteleva: Negative Effects of Late Bronze Age Human Activity on Modern Soils and Landscapes, a Case study on the Muradymovo Settlement, Urals, Russia 170 data (Shcherbakov et al. 2013; Shcharbakov et al. 2015) the Muradymovo people belonged to the "Srubno Alakul" culture of the Late Bronze Age and came here from an extra arid semidesert region of the southern Kazakhstan, where they used to build their houses of gypsum rock. There is a deposit of gypsum rock just 5 km away from the Muradymovo settlement site. Gypsum is an excellent construction material in the driest parts of arid regions, for example, within depressions that remain from former inland lakes or seas (Rosen, Warren 1990; Bolen et al. 1991) However, in humid climates gypsum is soluble and houses made of it undergo rapid degradation. The residual piles of gypsum rock account for the appearance of the aforementioned hillocky microrelief of the study site (Slavnyi 2003) A similar microrelief typically occurs in deserts (Gorbunova 1977; Watson 1985; Eckardt et.al. 2001; Warren 2006) but would not be expected to be found in this humid region of Urals. In addition, the ancient settlement site Muradymovo is located on a hill, and not within a depression. The aim of our study was to investigate the properties of modern soils at the Bronze Age settlement site and understand more about the factors that led to their formation and transformation. 2.
Transforming food systems with agroecology

Agroecology is a way of redesigning food systems, from the farm to the table, with a goal of achieving ecological, economic, and social sustainability. Through transdisciplinary, participatory, and change oriented research and action, agroecology links together science, practice, and movements focused on social change. But what are the steps that must be taken to transform food systems toward the ultimate goal of sustainability, and away from the mounting evidence of the negative impacts on the environment and society caused by modern industrial agriculture? In the latest edition of my agroecology textbook (Gliessman 2015b) I propose a framework for classifying "levels" of food system change. The first three levels describe the steps farmers can actually take on their farms for converting from industrial or conventional agroecosystems. Two additional levels go beyond the farm to the broader food system and the societies in which they are embedded. All five levels taken together can serve as a roadmap that outlines in an almost stepwise manner a process for transforming the entire global food system:  Increase the efficiency of industrial and conventional practices in order to reduce the use and consumption of costly, scarce, or environmentally damaging inputs. The primary goal of change at this level is to use industrial inputs more efficiently so that fewer inputs will be needed and the negative impacts of their use will also be reduced. Most conventional agricultural research has taken place at this level, through which considerable modern agricultural technologies, inputs, and practices have been developed. This research has helped farmers maintain or increase production through such practices as improved seeds, optimum planting density, more efficient pesticide and fertilizer application, and more precise use of water. So called "precision agriculture" is a recent focus of research at Level 1. Although this kind of research has reduced some of the negative impacts of industrial agriculture, they do not help break its dependence on external human inputs and monoculture practices.  Substitute alternative practices for industrial/conventional inputs and practices. The goal of this level of transition is to replace external input intensive and environmentally degrading products and practices with those that are more renewable, based on natural products, and more environmentally sound. Organic farming and biodynamic agriculture are examples of this approach. They employ alternative practices that include the use of nitrogen fixing covercrops and rotations to replace synthetic nitrogen fertilizers, the use of natural controls of pests and diseases, and the use of organic composts for fertility and soil organic matter AGROECOLOGY AND SUSTAINABLE FOOD SYSTEMS 2016, VOL. 40, NO. 3, 187 189 http:/dx.doi.org/10.1080/21683565.2015.1130765
Current sample preparation methodologies for analysis of emerging pollutants in different environmental matrices

Emerging contaminants such as pharmaceuticals, personal care products, and endocrine disrupting compounds are ever present in environmental matrices and they are known to pose negative effects on living organisms. The determination of these pollutants in different environmental matrices (such as water, soil, and sediments, among others) frequently requires separation techniques that are capable of high efficiency, unique selectivity and high sensitivity. However, direct analysis of these pollutants in complex matrices is difficult. For this reason, rapid, inexpensive, efficient and environmentally friendly sample preparation techniques have been developed prior to chromatographic quantification. Therefore, the aim of this article is to review recent publications (2010 2016) on modern sample preparation techniques combined with chromatographic techniques for identification and quantification of emerging pollutants in environmental matrices. These sample preparation techniques include solid phase extraction, solid phase microextraction, liquid liquid extraction, microwave assisted extraction, liquid phase microextraction techniques, stir bar sorptive extraction, and pressurized liquid extraction, among others.
Influencing the Tumor Microenvironment: A Phase II Study of Copper Depletion Using Tetrathiomolybdate in Patients with Breast Cancer at High Risk for Recurrence and in Preclinical Models of Lung Metastases
Venue: Clinical Cancer Research

Bone marrow derived progenitor cells, including VEGFR2+ endothelial progenitor cells (EPCs) and copper dependent pathways, model the tumor microenvironment. We hypothesized that copper depletion using tetrathiomolybdate would reduce EPCs in high risk for patients with breast cancer who have relapsed. We investigated the effect of tetrathiomolybdate on the tumor microenvironment in preclinical models.  Patients with stage II triple negative breast cancer (TNBC) stage III and stage IV without any evidence of disease (NED) received oral tetrathiomolybdate to maintain ceruloplasmin (Cp) between 8 and 17 mg/dL for 2 years or until relapse. Endpoints were effect on EPCs and other biomarkers, safety, event free (EFS) and overall survival (OS) For laboratory studies, MDA LM2 luciferase cells were implanted into CB17 SCID mice and treated with tetrathiomolybdate or water. Tumor progression was quantified by bioluminescence imaging (BLI) copper depletion status by Cp oxidase levels, lysyl oxidase (LOX) activity by ELISA, and collagen deposition.  Seventy five patients enrolled; 51 patients completed 2 years (1,396 cycles) Most common grade 3/4 toxicity was neutropenia (3.7% Lower Cp levels correlated with reduced EPCs (P 0.002) and LOXL 2 (P 0.001) Two year EFS for patients with stage II III and stage IV NED was 91% and 67% respectively. For patients with TNBC, EFS was 90% (adjuvant patients) and 50% (stage IV NED patients) at a median follow up of 6.3 years, respectively. In preclinical models, tetrathiomolybdate decreased metastases to lungs (P 0.04) LOX activity (P 0.03) and collagen crosslinking (P 0.012)  Tetrathiomolybdate is safe, well tolerated, and affects copper dependent components of the tumor microenvironment. Biomarker driven clinical trials in high risk for patients with recurrent breast cancer are warranted.