nils-herrmann/clean_scirepeval huggingface dataset:
"Gamifying" Online American National Government: Lessons Learned From the First Year of Developing "Citizenship Quest"
Venue: Journal of Political Science Education
Year: 2019

This article considers the development of an ongoing team based project to incorporate a game into an online American National Government class. We start by suggesting that play, and the games that provide for play to occur, is the most natural way for individuals to learn. Technologies offered by online education provide the opportunity to introduce unique game playing elements into introductory classes such as American National Government. We consider the goals established for this course and how we endeavored to achieve them through a fully self contained and integrated game Citizenship Quest making use of the class learning management system. We then consider surveys of students' learning outcomes and feedback concerning the game during the first two semesters, Fall 2017 and Spring 2018. We conclude by considering development issues dealt with by the instructor and the instructional design team in how Citizenship Quest a simulation of the citizenship process was embedded into this class.
Importance of atmospheric transport for microplastics deposited in remote areas.
Venue: Environmental pollution
Year: 2019

Atmospheric transport is an important pathway for the deposition of micro and nano plastics in remote areas. However, the sources and fate of atmospheric microplastics remain poorly understood. A study on atmospheric transport and deposition in the Pyrenean Mountains highlights the movement of microplastics away from known sources (cities, agriculture, and industry) into remote areas. Following this first evidence of atmospheric microplastic deposition in a pristine location, it is necessary to reconsider previous studies on atmospheric microplastic deposition and behavior in remote areas.
Critical Thinking: Tools for Taking Charge of Your Learning and Your Life
Year: 2011

1. Becoming a Fair Minded Thinker. 2. The First Four Stages of Development. 3. Self Understanding. 4. The Parts of Thinking. 5. The Standards for Thinking. 6. Asking Questions That Lead to Good Thinking. 7. Master the Thinking, Master the Content. 8. Designing Your Own Learning. 9. Evaluating Your Own Learning. 10. Making Decisions. 11. Solving Problems. 12. Taking Charge of Your Irrational Tendencies. 13. Monitoring Your Sociocentric Tendencies. 14. Developing as an Ethical Reasoner. 15. Learning Using Information Critically Ethically: Part One. 16. Learning Using Information Critically Ethically: Part Two. 17. Strategic Thinking, Part One. 18. Strategic Thinking, Part Two. 19. Becoming an Advanced Thinker.  A. Critical Questions about Critical Thinking. B. Sample Analyses of "The Logic Of." C. Article: "Iraq Is a Pediatrician's Hell: No Way to Stop the Dying."
Effectiveness Analysis of the Blanket Jamming Mode to GPS M Code Signal
Year: 2015

Aiming at the feature and superiority on anti jamming of global position system(GPS) M code signal, in order to find an effective jamming mode for M code signal, the jamming efficiency of three types of typical blanket jamming, single frequency, band limited Gaussian noise, and pseudo code with the same rate, are analyzed. In the analysis, the power spectral density change of GPS receiver cross correlation filtering output is taken as the qualitative evaluation bases; the code tracking error and the ephemeris bit error rate(BER) are taken as the quantitative evaluation indexes. The influence process of jamming to evaluation factor and the oneness of each evaluation factor are derived theoretically by modeling M code signal receiving system. The simulation results show that single frequency jamming exhibits the best jamming effect while band limited Gaussian noise jamming is the worst, the second comes pseudo code with the same rate jamming when the influence of sub carrier modulation was eliminated. Considering the complexity of smart jamming implementation, it is suggested to choose the pseudo code with the same rate as M code signal jamming since single frequency jamming needs strict frequency setting and it is easily eliminated by frequency domain filtering.
A Reverse Engineering Process for Inferring Conceptual Models from Canonicalized Tables
Venue: 2019 International Multi Conference on Engineering, Computer and Information Sciences (SIBIRCON)
Year: 2019

Conceptual models remain a main technique for visualize and formalize the basic concepts and relationships of any subject area. They provide a communicative function between subject domain specialists and software developers. Despite the existence of tools and notations for conceptual modeling the problem of retrieval of information about concepts and relationships or reverse engineering is stay urgent. Spreadsheets are one of the data sources for reverse engineering. In this paper we propose to transform the canonicalized spreadsheets. UML class diagrams were used as a target formalism for visualization of the obtained models. The description of the transformation algorithm and the mean of its implementation, namely, the Personal Knowledge Base Designer (PKBD) are given. Discussions of experiments are presented. This work is considered as a part of the project for development of a framework for creating systems of data extraction from arbitrary spreadsheets.
A decentralized control strategy for the coordination of AGV systems
Year: 2018

This paper deals with the complex problem of controlling and coordinating Autonomous Guided Vehicles (AGV) by a decentralized approach. Each AGV selects its route by a consensus algorithm based on some Integer Linear Programming problem solutions. Moreover, the AGVs move inside a zone controlled guidepath network and coordinate their movements by a decentralized protocol based on a zone controlled approach, which guarantees the avoidance of deadlocks and collisions. The proposed decentralized strategy is applied to a guidepath network by means of a simulation software.
CRYO EM STRUCTURE OF THE DELTA RETROVIRAL INTASOME IN COMPLEX WITH THE PP2A REGULATORY SUBUNIT B56g
Year: 2020

The Retroviridae delta retrovirus genus includes the most oncogenic pathogen human T cell lymphotropic virus type 1 (HTLV 1)(1) Many of the ~20 million people infected with HTLV 1 will develop severe leukaemia (2) or an ALS like motor disease (3) unless a therapy becomes available. A key step in the establishment of infection is the integration of viral genetic material into the host genome, catalysed by the viral integrase (IN) enzyme. Here we used X ray crystallography and single particle cryo electron microscopy to determine the structure of functional delta retroviral IN assembled on viral DNA ends and bound the B56g subunit of its human host factor, the protein phosphatase 2A (4) The structure reveals a tetrameric IN assembly bound to the phosphatase via a conserved short linear motif found within the extended linker connecting the catalytic core (CCD) and C terminal (CTD) IN domains. Unexpectedly, all four IN subunits are involved in B56g binding, taking advantage of the flexibility of the CCD CTD linkers. Our results fill the current gap in the structural understanding of the delta retroviral integration machinery. Insight into the interactions between the delta retroviral intasome and the host will be crucial for understanding the pattern of integration events in infected individuals and therefore bears important clinical implications.
Band gap structure of the spectrum of the water wave problem in a shallow canal with a periodic family of deep pools
Year: 2020

We consider the linear water wave problem in a periodic channel \Pi^h \subset \mathbb{R}^3$ which is shallow except for a periodic array of deep potholes in it. Motivated by applications to surface wave propagation phenomena, we study the band gap structure of the essential spectrum in the linear water wave system, which includes the spectral Steklov boundary condition posed on the free water surface. We apply methods of asymptotic analysis, where the most involved step is the construction and analysis of an appropriate boundary layer in a neighborhood of the joint of the potholes with the thin part of the channel. Consequently, the existence of a spectral gap for small enough $h$ is proven.
Brain Image Analysis, Classification and Reconstruction
Year: 2020

Decoding brain activity occurs in response to an external stimulus is a great problem and the first step to analysis, classification, reconstruction of the external stimulus which will lead to some marvelous application like reconstructing the visual images from the mind of a person in comma or identifying an object in the head of someone that has some psychological problem in the medical field, and criminal image reconstruction instead of forensic artists in security problems or instant design in marketing, etc. The problem with the brain data analysis is that the brain data like fMRI which we used here is very complicated. also acquiring the data is difficult and requires a lot of resources and time and this is why the fMRI datasets size is small. The data is divided into 3 subjects and each subject data consists of fMRI responses to 3 types of images(letters,artificial,natural) In this work, we focused on 3 main targets analysis and classification of the difference between subjects and types of images, identification of objects presented in the natural images, and finally reconstruction of the images from fMRI data.
Long Term and Transgenerational Effects of Stress Experienced during Different Life Phases in Chickens (Gallus gallus)
Venue: PloS one
Year: 2016

Stress in animals causes not only immediate reactions, but may affect their biology for long periods, even across generations. Particular interest has been paid to perinatal stress, but also adolescence has been shown to be a sensitive period in mammals. So far, no systematic study has been performed of the relative importance of stress encountered during different life phases. In this study, groups of chickens were exposed to a six day period of repeated stress during three different life phases: early (two weeks) early puberty (eight weeks) and late puberty (17 weeks) and the effects were compared to an unstressed control group. The short term effects were assessed by behaviour, and the long term and transgenerational effects were determined by effects on behavior and corticosterone secretion, as well as on hypothalamic gene expression. Short term effects were strongest in the two week group and the eight week group, whereas long term and transgenerational effects were detected in all three stress groups. However, stress at different ages affected different aspects of the biology of the chickens, and it was not possible to determine a particularly sensitive life phase. The results show that stress during puberty appears to be at least equally critical as the previously studied early life phase. These findings may have important implications for animal welfare in egg production, since laying hens are often exposed to stress during the three periods pinpointed here.
Supply of a key value database redis in memory by data from a relational database
Venue: 2018 19th IEEE Mediterranean Electrotechnical Conference (MELECON)
Year: 2018

Key value databases are highly adopted to provide quick access to information that has an associative tabular function, for role to return unstructured values. When you first look at the performance of a database, memory processing is the ultimate solution to latency. The birth of this approach of migration of a relational database towards a key value database Redis is derived from performance improvement. The entire migration is based on the extraction of the data from the relational database and its injection into the key value database following methods that communicate with both databases. The entire migration is done automatically without the interference of the human factor, a prototype has been created that proves the effectiveness of this approach.
Pd supported on clicked cellulose modified magnetite graphene oxide nanocomposite for C C coupling reactions in deep eutectic solvent.
Venue: Carbohydrate polymers
Year: 2021

Cellulose modified magnetite graphene oxide nanocomposite was prepared via click reaction and utilized for immobilization of palladium (Pd) nanoparticles without using additional reducing agent. The abundant OH groups of cellulose provided the uniform dispersion and high stability of Pd nanoparticles, while magnetite graphene oxide as a supporting material offered high specific surface area and easy magnetic separation. The as prepared nanocomposite served as a heterogeneous catalyst for the Heck and Sonogashira coupling reactions in various hydrophilic and hydrophobic deep eutectic solvents (DESs) as sustainable and environmentally benign reaction media. Among the fifteen DESs evaluated for coupling reactions, the hydrophilic DES composed of dimethyl ammonium chloride and glycerol exhibited the best results. Due to the low miscibility of catalyst and DES in organic solvents, the separated aqueous phase containing both of the catalyst and DES can be readily recovered by evaporating water and retrieved eight times with negligible loss of catalytic performance.
Reproducibility of mass spectrometry based metabolomics data
Venue: BMC Bioinform.
Year: 2021

Assessing the reproducibility of measurements is an important first step for improving the reliability of downstream analyses of high throughput metabolomics experiments. We define a metabolite to be reproducible when it demonstrates consistency across replicate experiments. Similarly, metabolites which are not consistent across replicates can be labeled as irreproducible. In this work, we introduce and evaluate the use (Ma)ximum (R)ank (R)eproducibility (MaRR) to examine reproducibility in mass spectrometry based metabolomics experiments. We examine reproducibility across technical or biological samples in three different mass spectrometry metabolomics (MS Metabolomics) data sets.  We apply MaRR, a nonparametric approach that detects the change from reproducible to irreproducible signals using a maximal rank statistic. The advantage of using MaRR over model based methods that it does not make parametric assumptions on the underlying distributions or dependence structures of reproducible metabolites. Using three MS Metabolomics data sets generated in the multi center Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPD) study, we applied the MaRR procedure after data processing to explore reproducibility across technical or biological samples. Under realistic settings of MS Metabolomics data, the MaRR procedure effectively controls the False Discovery Rate (FDR) when there was a gradual reduction in correlation between replicate pairs for less highly ranked signals. Simulation studies also show that the MaRR procedure tends to have high power for detecting reproducible metabolites in most situations except for smaller values of proportion of reproducible metabolites. Bias (i.e. the difference between the estimated and the true value of reproducible signal proportions) values for simulations are also close to zero. The results reported from the real data show a higher level of reproducibility for technical replicates compared to biological replicates across all the three different datasets. In summary, we demonstrate that the MaRR procedure application can be adapted to various experimental designs, and that the nonparametric approach performs consistently well.  This research was motivated by reproducibility, which has proven to be a major obstacle in the use of genomic findings to advance clinical practice. In this paper, we developed a data driven approach to assess the reproducibility of MS Metabolomics data sets. The methods described in this paper are implemented in the open source R package marr which is freely available from Bioconductor at http:/bioconductor.org/packages/marr
Cross Domain Speaker Recognition using Cycle Consistent Adversarial Networks
Venue: 2019 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
Year: 2019

Speaker recognition systems often suffer from severe performance degradation due to the difference between training and evaluation data, which is called domain mismatch problem. In this paper, we apply adversarial strategies in deep learning techniques and propose a method using cycle consistent adversarial networks for i vector domain adaptation. This method performs an i vector domain transformation from the source domain to the target domain to reduce the domain mismatch. It uses a cycle structure that reduces the negative influence of losing speaker information in i vector during the transformation and makes it possible to use unpaired dataset for training. The experimental results show that the proposed adaptation method improves recognition performance of a conventional i vector and PLDA based speaker recognition system by reducing the domain mismatch between the training and the evaluation sets.
In Situ Nanoscale Redox Mapping Using Tip Enhanced Raman Spectroscopy.
Venue: Nano letters
Year: 2019

Electrochemical atomic force microscopy tip enhanced Raman spectroscopy (EC AFM TERS) was used for the first time to spatially resolve local heterogeneity in redox behavior on an electrode surface in situ and at the nanoscale. A structurally well defined Au(111) nanoplate located on a polycrystalline ITO substrate was studied to examine nanoscale redox contrast across the two electrode materials. By monitoring the TERS intensity of adsorbed Nile Blue (NB) molecules on the electrode surface, TERS maps were acquired with different applied potentials. The EC TERS maps showed a spatial contrast in TERS intensity between Au and ITO. TERS line scans near the edge of a 20 nm thick Au nanoplate demonstrated a spatial resolution of 81 nm under an applied potential of 0.1 V vs Ag/AgCl. The intensities from the TERS maps at various applied potentials followed Nernstian behavior, and a formal potential E0' map was constructed by fitting the TERS intensity at each pixel to the Nernst equation. Clear nanoscale spatial contrast between the Au and ITO regions was observed in the E0' map. In addition, statistical analysis of the E0' map identified a statistically significant 4 mV difference in E0' on Au vs ITO. Electrochemical heterogeneity was also evident in the E0' distribution, as a bimodal distribution was observed in E0' on polycrystalline ITO, but not on gold. A direct comparison between an AFM friction image and the E0' map resolved the electrochemical behavior of individual ITO grains with a spatial resolution of ~40 nm. The variation in E0' was attributed to different local surface charges on the ITO grains. Such site specific electrochemical information with nanoscale spatial and few mV voltage resolutions is not available using ensemble spectroelectrochemical methods. We expect that in situ redox mapping at the nanoscale using EC AFM TERS will have a crucial impact on understanding the role of nanoscale surface features in applications such as electrocatalysis.
Analysis of Business Processes with Enterprise Ontology and Process Mining
Venue: EEWC
Year: 2015

This paper describes a business process analysis method that helps determining if a business process complies with the requirements put forward by enterprise ontology's transaction pattern. The method starts by discovering the business process through the application of process mining techniques to the events that are generated by the applications that support the execution of the process. This step discovers the actual implementation of the process from its event trace. Next, the discovered process is analysed against enterprise ontology's transaction pattern to determine whether the process complies with the structure and sequencing of its coordination and production acts. The paper shows that combining process mining with enterprise ontology contributes to the analysis of business processes, especially in terms of determining the boundaries of authority and responsibility of the process. The feasibility and the limitations of the method are discussed using a case study that analyses a semi automated business process.
QASC: A Dataset for Question Answering via Sentence Composition
Venue: AAAI
Year: 2020

Composing knowledge from multiple pieces of texts is a key challenge in multi hop question answering. We present a multi hop reasoning dataset, Question Answering via Sentence Composition(QASC) that requires retrieving facts from a large corpus and composing them to answer a multiple choice question. QASC is the first dataset to offer two desirable properties: (a) the facts to be composed are annotated in a large corpus, and (b) the decomposition into these facts is not evident from the question itself. The latter makes retrieval challenging as the system must introduce new concepts or relations in order to discover potential decompositions. Further, the reasoning model must then learn to identify valid compositions of these retrieved facts using common sense reasoning. To help address these challenges, we provide annotation for supporting facts as well as their composition. Guided by these annotations, we present a two step approach to mitigate the retrieval challenges. We use other multiple choice datasets as additional training data to strengthen the reasoning model. Our proposed approach improves over current state of the art language models by 11% (absolute) The reasoning and retrieval problems, however, remain unsolved as this model still lags by 20% behind human performance.
Approach to generation of random aggregate model and gradient optimization of background grid based on SolidWorks platform
Venue: Cluster Computing
Year: 2018

Use development platform of SolidWorks software to improve the efficiency of generating numerical concrete and aggregate content and can handle with complex geometric shape aggregate. Propose a gravel aggregate generation method that cutting entity with planes and a cobble aggregate generation method that lofting of alpine curves to produce pebbles. Improvements of delivery method are made in three aspects: using the background grid with gradient mesh density to find delivery position; checking interference with SolidWorks API function; and moving aggregate close to and contact with another aggregate in three directions freely. And the generation of three grade numerical concrete is taken as an example. The results show that the method is simple and reliable, and the aggregate content of grade two, grade three and grade four concrete can reach 55, 64 and 72% respectively, and the aggregate with complex shape can be simulated. This paper shows that the pretreatment process of mass numerical concrete is completed for the first time by using SolidWorks, and the pretreatment method of the original background mesh is improved, so that it is more suitable for the large pretreatment process. This method can provide a good reference for the pretreatment process of mass and high content numerical concrete.