nils-herrmann/clean_scirepeval huggingface dataset:
Dynamic Attention Aggregation with BERT for Neural Machine Translation
Venue: 2020 International Joint Conference on Neural Networks (IJCNN)
Year: 2020

The recently proposed BERT has demonstrated great power in various natural language processing tasks. However, the model does not perform effectively on cross lingual tasks, especially on machine translation. In this work, we propose three methods to introduce pre trained BERT into neural machine translation without fine tuning. Our approach consists of a) a linear attention aggregation that leverages a parameter matrix to capture the key knowledge of BERT, b) a self attention aggregation which aims to learn what is vital for input and output, and c) a switch gate aggregation to dynamically control the balance of the information flowing from the pre trained BERT or the NMT model. We conduct experiments on several translation benchmarks and substantially improve over 2 BELU points on the IWSLT'14 English German task with switch gate aggregation method compared to a strong baseline, while our proposed model also performs remarkably on the other tasks.
Effective Fingerprint Extraction and Positioning Method Based on Crowdsourcing
Venue: IEEE Access
Year: 2019

At present, WiFi fingerprinting indoor positioning technology is a research hotspot, and the construction of a radio map based on crowdsourcing can significantly reduce the amount of labor required. However, when users collect fingerprint information using crowdsourcing data in practical applications, the received signal strength (RSS) information collected by user phones updates slowly and will remain the same for a certain distance and time. Therefore, crowdsourcing data is inaccurate, and a radio map thereby established will also lead to inaccurate indoor positioning. In order to address this issue, this paper proposes a method for extracting effective RSS information from crowdsourcing data in order to establish the radio map and achieve positioning. By analyzing the crowdsourcing data characteristics, effective RSS information is identified and extracted. Based on inertial sensors data, the position of effective RSS information is determined. The effective crowdsourcing data associated with the position is weighted and fused in order to establish the radio map. Aimed at the issue of the RSS collected by phones updating slowly, a combined positioning method for position calculation is proposed in order to achieve effective positioning. Experiments were conducted in a real environment to validate the algorithm, and the positioning accuracy could reach 1.5 m by using crowdsourcing data to construct the radio map and executing an indoor positioning algorithm, which is close to the accuracy achieved when using manual data collected by professionals at a certain distance and saves a great deal of labor.
Survey on deep learning with class imbalance
Venue: J. Big Data
Year: 2019

The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in many real world applications, e.g. fraud detection and cancer detection. Moreover, highly imbalanced data poses added difficulty, as most learners will exhibit bias towards the majority class, and in extreme cases, may ignore the minority class altogether. Class imbalance has been studied thoroughly over the last two decades using traditional machine learning models, i.e. non deep learning. Despite recent advances in deep learning, along with its increasing popularity, very little empirical work in the area of deep learning with class imbalance exists. Having achieved record breaking performance results in several complex domains, investigating the use of deep neural networks for problems containing high levels of class imbalance is of great interest. Available studies regarding class imbalance and deep learning are surveyed in order to better understand the efficacy of deep learning when applied to class imbalanced data. This survey discusses the implementation details and experimental results for each study, and offers additional insight into their strengths and weaknesses. Several areas of focus include: data complexity, architectures tested, performance interpretation, ease of use, big data application, and generalization to other domains. We have found that research in this area is very limited, that most existing work focuses on computer vision tasks with convolutional neural networks, and that the effects of big data are rarely considered. Several traditional methods for class imbalance, e.g. data sampling and cost sensitive learning, prove to be applicable in deep learning, while more advanced methods that exploit neural network feature learning abilities show promising results. The survey concludes with a discussion that highlights various gaps in deep learning from class imbalanced data for the purpose of guiding future research.
THE EVOLUTION OF THE BANK CREDIT STRUCTURE BY ACTIVITY OF BORROWER AND RISK CATEGORIES
Year: 2019

The evolution of bank loans in structure and dynamics is analyzed during the period 2015 2018. This research proposes a comparative analysis of the evolution of bank credits by sectors of economic activity (Industry; Services; Construction; Agriculture, forestry, fishery; Financial intermediation; Public administration and Individuals) The evolution of bank loans by risk categories (Treasury loans, Inventory loans, Equipment loans, Foreign trade loans, Commercial loans and others) shows the priorities of banks to finance these activity. Banking prudence is also found in the selection by banks in the types of loans granted to clients.
The aggressive spiegeldanio, carrying a mutation in the fgfr1a gene, has no advantage in dyadic fights with zebrafish of the AB strain
Venue: Behavioural Brain Research
Year: 2019

Zebrafish which carries a mutation in the fibroblast growth factor receptor 1A (fgfr1a) also known as spiegeldanio (spd) has previously been reported to be bolder and more aggressive than wildtype (AB) zebrafish. However, in previous studies aggression has been quantified in mirror tests. In dyadic fights the behavior of the combatants is modified by the behavior of their opponent, and fighting a mirror has been reported to have different effects on brain gene expression and brain monoaminergic systems. In the present study aggression was quantified in fgfr1a mutants and AB zebrafish using a mirror test after which the fish were allowed to interact in pairs, either consisting of two fgfr1a mutants or one AB and one fgfr1a mutant fish. Following dyadic interaction aggressive behavior was again quantified in individual fish in a second mirror test after which the fish were sacrificed and brain tissue analyzed for monoamines and monoamine metabolites. The results confirm that fgfr1a mutants are more aggressive than AB zebrafish in mirror tests. However, fgfr1a mutant fish did not have any advantage in fights for social dominance, and agonistic behavior of fgfr1a mutants did not differ from that of AB fish during dyadic interactions. Moreover, as the AB fish, fgfr1a mutant fish losing dyadic interactions showed a typical loser effect and social subordination resulted in an activation of the brain serotonergic system in fgfr1a mutants as well as in AB fish. Overall the effects of dyadic interaction were similar in fgfr1a mutant fish and zebrafish of the AB strain.
Tactical Network Automation with NetZTP and One Shot
Venue: 2019 IEEE 40th Sarnoff Symposium
Year: 2019

Network automation promises to improve network operations by increasing efficiency and consistency but is difficult to achieve in practice due to the large variety of infrastructure devices within the network as well as vendor specific management and control interfaces. This paper explores options for the tactical deployment of network automation to provide maximum return on investment as organizations explore strategic approaches to network automation.
Numerical investigation of dual stage high velocity oxy fuel (HVOF) thermal spray process: A study on nozzle geometrical parameters
Year: 2017

The present study takes the advantage of computational fluid dynamics (CFD) methods to model steady state, two dimensional, axisymmetric, turbulent, compressible and combusting flow in a dual stage high velocity oxy fuel (HVOF) thermal spray system. The Eulerian method is used to solve the continuum gas phase and the Lagrangian method is utilized for tracking the particles. The effects of particle loads on the continuous gas phase are included in the simulation. Thus, compared to the previous studies, we investigate the influence of coupling between the particle and gas phases in modeling of the dual stage HVOF process. It is found that decouple modeling of the particle and the continuous phase causes a significant error in velocity of particle at the impact moment, even for low powder particle loading. We further investigate the effects of four geometrical parameters on the behavior of gas phase and consequently the particle phase. Results also show that the turbulent intensity of flow at different sections of the warm spray process is the most important factor determining the radial distribution of nitrogen and temperature in the barrel. It also determines the radial distribution of oxygen in the free jet outside of the barrel. It is further found that reduction of the first nozzle diameter and increasing the length of the divergent section (for a fixed divergent angle) of the convergent divergent nozzle reduce the particle temperature while these changes do not affect the particle velocity. In other words, changing these geometrical parameters has a desirable effect on the particle temperature without causing an undesirable change on the particle velocity.
The many faces of FcgRI: implications for therapeutic antibody function
Venue: Immunological reviews
Year: 2015

Fcg receptor I (FcgRI or CD64) is the sole human Fc receptor with high affinity for monovalent IgG. While it contains an immunoreceptor tyrosine based activation motif in its cytoplasmic domain, binding of FcgRI can result in a complex array of activating and inhibitory outcomes. For instance, binding of monomeric IgG provides a low intensity tonic signal through FcgRI that is necessary for full interferon g receptor signaling in the same cell. Interaction of FcgRI with larger high avidity complexes can result in phagocytosis, the generation of reactive oxygen species, as well as the synthesis and release of inflammatory cytokines. However, numerous reports also document potent anti inflammatory effects brought about by FcgRI engagement with immune complexes such as the inhibition of IFNg and TLR4 signaling, and secretion of interleukin 10. This has led to conflicting hypotheses regarding the function of FcgRI, especially with regard to its role in the efficacy of several therapeutic monoclonal antibodies. While many of these issues are still unclear, continued characterization of the regulation and context dependence of FcgRI function, as well as the molecular mechanisms responsible for these various outcomes, will improve our understanding of FcgRI biology as well as the therapeutic strategies designed to harness or constrain its actions.
Integration of gross anatomy in an organ system based medical curriculum: Strategies and challenges
Venue: Anatomical sciences education
Year: 2015

The University of Alabama School of Medicine (UASOM) instituted a fully integrated, organ system based preclinical curriculum in 2007. Gross anatomy and embryology were integrated with other basic science disciplines throughout the first two years of undergraduate medical education. Here we describe the methods of instruction and integration of gross anatomy and embryology in this curriculum as well as challenges faced along the way. Gross anatomy and embryology are taught through a combination of didactic lectures, team based learning activities, and cadaveric dissection laboratories. Vertical integration occurs through third and fourth year anatomy and embryology elective courses. Radiology is integrated with anatomy instruction through self study modules and hands on ultrasound sessions. Our model of anatomy instruction is time efficient, clinically relevant, and effective as demonstrated by student performance on the United States Medical Licensing Examination(r) (USMLE(r) Step 1 examination. We recommend that medical schools considering full integration of gross anatomy and embryology (1) carefully consider the sequencing of organ system modules, (2) be willing to sacrifice anatomical detail for clinical application, (3) provide additional electives to third and fourth year students, and (4) integrate radiology with anatomical education. Anat Sci Educ 8: 266 274.
Deliverable 2.1: Policy. A review of policies and practices throughout Europe on mineral resources and land use
Year: 2019

Access to mineral resources in Europe is important for the economic development of Europe. At the same time, it is widely recognised that it is essential that minerals are responsibly sourced for the sustainable development of Europe. The question is how to balance societal interests, such as expanding cities, infrastructure development, agriculture and nature conservation with the exploration and mining of mineral resources. Land use planning is a key mechanism to balance various societal interests to guide sustainable spatial development. Therefore, the integration of mineral resources policies into land use planning at different levels is a key factor for achieving responsibly sourced minerals. This deliverable of MinLand assesses the current state of affairs on land use planning in relation to mineral exploration and the safeguarding of mineral resources. The deliverable reviews the issue of governance (e.g. the division of responsibilities between different levels) with a special emphasis on the coherence between existing mineral policies, legislation and land use planning. To analyse this, a survey was conducted amongst 18 participating countries (16 EU Member States plus Ukraine and Norway) to assess the current state of affairs. The mineral land use process has been further visualized for nine EU countries in section 2. In addition to the questionnaire and its updates, additional information has been gathered by contact through emails with consortium experts. Mineral land use processes are further analysed and scrutinized in Deliverable D4.2. D4.2 provides the reader with an evaluation of the interplay between the different parts of the land use processes and permitting procedures. The current deliverable is one in a series related to mineral policies and land use. This is a first step in describing how mineral raw materials relate to land use together with deliverables D2.3, D3.2 and D3.3. These land use issues will be further elaborated within WP4 (particularly D4.2) WP5, WP6 and WP7. The next step in this process building upon the gathered information is the D4.2.
Fonksiyon yaklasimi probleminde esnek kucuk dunya aglarinin topolojik degisiminin performansa etkisi
Year: 2020

Ileri yonlu yapay sinir aglari performansi topolojiyle dogrudan iliskilidir. Son yillarda, topolojik degisikliklerle ag performansinin artirilmasi uzerine yapilan calismalar cok onemli bir surec haline gelmistir. Bu nedenle, noronlar arasi sinaptik baglantilarin degistirildigi bir yaklasim olan kucuk dunya ag modeli gelecek calismalar icin onemli bir yere sahiptir. Bu calismada, fonksiyon yaklasimi problemleri icin esnek kucuk dunya ag modelinin katmansal ve noronal degisimlerle performansinin nasil degistigi arastirilmistir. Elde edilen sonuclar gosterdi ki, geleneksel esnek yapay sinir agi topolojisine gore esnek kucuk dunya aginin performansi cok daha fazla iyilestirdigi ve katman sayisinin artirilmasinin ag performansina ciddi katki sagladigi gozlemlenmistir. Diger taraftan, katman sayisi ile birlikte gizli katman noron sayisinin artirildikca performansa negatif etki ettigi gorulmustur. Bu baglamda, coklu gizli katmana sahip esnek kucuk dunya aglarinin fonksiyon yaklasimi probleminin cozumunde pozitif etki ettigi gosterilmis ve ozellikle bu modelin gelecekte derin noron aglari performansinin gelistirilmesinde anahtar rol oynayacagi vurgulanmistir.
Planning for Change in Instrument FSW: Successes and Failures on MMS HPCA
Venue: 2019 IEEE Aerospace Conference
Year: 2019

Instrument Flight Software Developers face challenges when designing for operations. On the one hand, a highly flexible and reconfigurable system can permit adaptation on orbit without the need to develop, validate, and update software on orbit. On the other hand, projects are limited in budget and schedule, and predicting future needs for requirements that are not currently in scope may be untenable. For the Magnetospheric Multiscale Hot Plasma Composition Analyzer, we tried to anticipate future needs and build adaptable software. We had significant success, but some needs were difficult to predict. We discuss what we predicted correctly, what we missed, and interesting operational adaptions that allowed us to avoid flight software updates.
El uso de Duolingo como herramienta de apoyo en el aprendizaje del Idioma Ingles
Year: 2021

El rol de la tecnologia en el proceso ensenanza aprendizaje, cada vez toma mas fuerza en un entorno en el cual el dominio del conocimiento constituye la base fundamental para su desarrollo. En base a este principio, se han podido evidenciar un sinnumero de aportes tecnologicos en muchas areas del campo educativo, incluyendo el aprendizaje de una lengua extranjera. En lo que a la ensenanza aprendizaje del idioma ingles concierne, es posible notar la amplia gama de herramientas tecnologicas con las cuales tanto docentes como estudiantes pueden contar para cumplir con sus objetivos y logros de aprendizaje de manera autonoma, didactica y eficaz en una atmosfera atractiva y desafiante para los estudiantes, como por ejemplo la aplicacion Duolingo. Este articulo explora los beneficios de usar esta aplicacion en la clase como una herramienta de apoyo en el aprendizaje del idioma ingles como segunda lengua, en un curso de estudiantes con un nivel basico (A1) en una universidad publica de Ecuador. Ademas, detalla aspectos relevantes en el uso de Duolingo en la clase, y sus beneficios para el desarrollo de las diferentes destrezas comunicativas que el aprendizaje de una lengua extranjera requiere. Estudios anteriores senalan que Duolingo es un recurso didactico de alto potencial ya que esta aplicacion movil se basa en la gamificacion que es una tecnica de aprendizaje cada vez mas puesta en practica, que permite a los estudiantes aprender a traves de juegos los cuales se convierten en retos que desafian las destrezas de los estudiantes fortaleciendo su motivacion y autonomia, lo cual fue posible evidenciar en los resultados del post test. Estos resultados ademas reflejan que existe un significativo grado de aceptacion y actitud positiva de los estudiantes al competir y esforzarse por lograr sus objetivos completando los diferentes tipos de tareas enfocadas en las diferentes destrezas, cuyo grado de complejidad se incrementa gradualmente a medida que se superan los retos en los diferentes niveles. Este articulo tambien explica como el profesor asigna las tareas y como puede hacer un seguimiento a ellas.
Variants of Cloze Test Based Tasks and Vocabulary Achievement
Year: 2020

Vocabulary is an integral part of a language and language education. In view of the close relationship between vocabulary knowledge and language learning, there is a significant need for language learners, especially in the ESL context, to develop, enrich and master their vocabulary in order to be proficient users of the language. ESL teachers could help learners acquire vocabulary knowledge if they have the pedagogical knowledge on how vocabulary may be learned and taught effectively. The study aimed to determine Malaysian primary school learners' vocabulary achievement by using cloze test based tasks. A total of five primary schools from Sabah, Malaysia were selected in this study. The total number of research participants was 135 and they were at low to intermediate level of proficiency. This study made use of four different cloze based passages as research instruments in assessing learners' vocabulary knowledge. This research primarily concerned on the descriptive data in the form of frequency and percentage of the learners' vocabulary achievement scores and qualitative data from semi structured interview. The findings of this study revealed that the research participants scored well in the fourth task whereby cloze based passages were given along with general pictures and multiple choice items. A significant correlation between these four variants of cloze based task with the learners' vocabulary achievement was established. The main pedagogical implication of the research is that teachers should ponder what type of variants to be used in vocabulary task as this could enhance ESL learners' vocabulary achievement.
Lanosterol reverses protein aggregation in cataracts
Venue: Nature
Year: 2015

The human lens is comprised largely of crystallin proteins assembled into a highly ordered, interactive macro structure essential for lens transparency and refractive index. Any disruption of intra or inter protein interactions will alter this delicate structure, exposing hydrophobic surfaces, with consequent protein aggregation and cataract formation. Cataracts are the most common cause of blindness worldwide, affecting tens of millions of people, and currently the only treatment is surgical removal of cataractous lenses. The precise mechanisms by which lens proteins both prevent aggregation and maintain lens transparency are largely unknown. Lanosterol is an amphipathic molecule enriched in the lens. It is synthesized by lanosterol synthase (LSS) in a key cyclization reaction of a cholesterol synthesis pathway. Here we identify two distinct homozygous LSS missense mutations (W581R and G588S) in two families with extensive congenital cataracts. Both of these mutations affect highly conserved amino acid residues and impair key catalytic functions of LSS. Engineered expression of wild type, but not mutant, LSS prevents intracellular protein aggregation of various cataract causing mutant crystallins. Treatment by lanosterol, but not cholesterol, significantly decreased preformed protein aggregates both in vitro and in cell transfection experiments. We further show that lanosterol treatment could reduce cataract severity and increase transparency in dissected rabbit cataractous lenses in vitro and cataract severity in vivo in dogs. Our study identifies lanosterol as a key molecule in the prevention of lens protein aggregation and points to a novel strategy for cataract prevention and treatment.