nils-herrmann/clean_scirepeval huggingface dataset:
Mass spectrometry in combination with a chiral column and multichannel MRM allows comprehensive analysis of glycosphingolipid molecular species from mouse brain.
Venue: Carbohydrate research
Year: 2020

Glycosphingolipids (GSLs) exist exclusively in the outer leaflet of plasma membrane in mammalian cells and have diverse structures including different classes of sugars and various molecular species of ceramide moieties. Establishing methods that measure each molecular species in GSL classes should aid functional characterization of GSLs and reveal details about the mechanism of pathogenesis in glycosphingolipidoses. Using an IF 3 chiral column that has never been used for lipid analyses, we developed a liquid chromatography mass spectrometry (LC MS) method to separate various GSLs based on sugar and ceramide moieties. To examine GSLs in detail a multichannel multiple reaction monitoring (multichannel MRM) mode was used and covered a range of 500 2000 Da. Common fragment ions detected with higher collision energy in the positive ion mode were m/z 264 and 292, and are derived from d18:1 and d20:1 ions, respectively. Both species were used as product ions in the multichannel MRM for the simultaneous measurement of neutral GSLs, gangliosides and sulfatides. Comprehensive analysis of GSLs in mouse brain using this method revealed that for gangliosides and LacCer,  d18:1 C24:0 and d18:1 C24:1 were the major molecular species of sulfatides. The results revealed a diverse GSL fatty acid profile. In conclusion, by combining IF 3 chiral column and the multichannel MRM method various molecular species of GSLs were detected successfully, and a metabolomics approach based on this LC MS method should facilitate functional analysis of GSLs and the discovery of early biomarkers of glycosphingolipidoses at the molecular level.
Language industry views on the profile of the post editor
Year: 2020

The more language service companies (LSCs) include machine translation post editing (MTPE) in their workflows, the more important it is to know how the PE task is performed, who the post editors are, and what skills they should have. This research is designed to address such questions. It aims to deepen our knowledge of current practices to later create new training content and adapt existing training methodologies to different types of audiences. Based on the results of a survey of LSCs and other companies who currently use MTPE, we present a picture of evolving practices in the contemporary European MTPE market, and opinions held about this emerging metier. Our research finds that a high level of expertise in MTPE may not necessarily be indicative of the industry, and that the post editor of MT has a multi and transdisciplinary profile.
Learning to Detect Dysarthria from Raw Speech
Venue: ICASSP 2019 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2019

Speech classifiers of paralinguistic traits traditionally learn from diverse hand crafted low level features, by selecting the relevant information for the task at hand. We explore an alternative to this selection, by learning jointly the classifier, and the feature extraction. Recent work on speech recognition has shown improved performance over speech features by learning from the waveform. We extend this approach to paralinguistic classification and propose a neural network that can learn a filterbank, a normalization factor and a compression power from the raw speech, jointly with the rest of the architecture. We apply this model to dysarthria detection from sentence level audio recordings. Starting from a strong attention based baseline on which mel filterbanks outperform standard low level descriptors, we show that learning the filters or the normalization and compression improves over fixed features by 10% absolute accuracy. We also observe a gain over OpenSmile features by learning jointly the feature extraction, the normalization, and the compression factor with the architecture. This constitutes a first attempt at learning jointly all these operations from raw audio for a speech classification task.
3D FEA Study On Implant Threading Role on Selection of Implant and Crown Materials
Venue: Open access Macedonian journal of medical sciences
Year: 2018

This study deeply investigates the effect of dental implant threading and material selection on the mandibular bone under two different crown materials (Translucent Zirconia and Porcelain fused to metal)  Two different designs of single piece dental implants were supporting dummy crown above simplified bone geometry in two finite element models. Models components were created by general purpose CAD/CAM engineering package and then assembled inside ANSYS before meshing and assigning materials. Compressive loading of 100 N and 45o oblique loading of 50 N were tested.  Twenty four case studies were analysed, and their results were compared. Micro thread reduces implant maximum Von Mises stress by about 50 to 70% than regular thread one. Oblique loading of 50 N will produce 4 to 5 times more maximum Von Mises values on implant body than 100 N vertical loading. Zero or negligible effect on the cortical bone was recorded when exchanging the tested crown material. Although titanium implant can also reduce cortical bone, Von Mises stress by 50 to 100% in comparison to reinforced PEKK (poly ether ketone ketone) or PEEK (poly ether ether ketone)  Reinforced PEKK and PEEK implants can represent a good alternative to titanium implants. Zirconia crown distributes the applied load better than Porcelain fused to a metal one. Regardless of the implant material, an implant with the micro thread has superior behaviour in comparison to a regular one. Zirconia crown above titanium implant with the micro thread may represent the best option for patient bone.
Radiology on Instagram: Analysis of Public Accounts and Identified Areas for Content Creation.
Venue: Academic radiology
Year: 2020

Radiology social media research has focused on Twitter, Facebook, and YouTube, with minimal attention to Instagram, which may be a natural platform for engagement. We evaluated features of public radiology related Instagram accounts.  Instagram accounts were searched using the term "radiology." Two independent raters used a coding system developed through initial content review to categorize account user types and post aims over the study month (October 2019) Multivariate linear regressions were performed.  Instagram accounts and their 459 posts were retrieved. Users had median 117 total posts (interquartile range 43 203) 9 posts during the study month (1 16) 3079 followers (695 19,600) and 106 followed users (50 351) Most users were radiologists (41% most commonly academic) radiology practices (12% most commonly academic) and 10% radiology professional societies. The 459 posts had median 178 likes (interquartile range 51 353) and 2 comments (0 5) single videos had median 4693 views (2183 6080) 75% of posts were radiology images or videos (of these, 29% MRI, 28% CT) 65% of posts were clinical imaging cases (most commonly neuroradiology) Seven posts violated HIPAA regulations, all originating outside the U.S. When controlling for number of account followers, posts by radiology society (b 130.6, p 0.017) and practice accounts (b 90.6, p 0.049) had fewer post likes. An artwork post was the only significant predictor of greater post likes (b +866.2, p 0.001) and comments (b +14.3, p 0.001) CONCLUSION Instagram is commonly used by academic radiologists to present clinical imaging cases. Radiologists should consider opportunities for greater application of this unique image based social media platform.
Strategies for Creating Awareness on Corona virus Disease (Covid 2019) Transmission among Health Workers in Lagos State South West Nigeria
Year: 2020

The study examined the strategies for creating awareness on coronavirus disease (COVID 2019) transmission among health workers in Lagos state South West Nigeria. The design used for the study was a descriptive survey design. The population for the study was 480 and the sample size was 260. Purposive sampling technique was adopted. Structured questionnaires were the instrument used for data collection. Data collected was analyzed using mean. Findings revealed that constant seminars and workshops should be organized for Doctors, Nurses and other related health workers on ways of protecting themselves from contacting the virus, ,awareness on the importance of personal hygiene should be constantly created by stakeholders through radio jingles, newspaper publications and television programs, more research on this deadly coronavirus infection should be encouraged and sponsored, coronavirus vaccines should be manufactured to help in boosting immune systems. Based on the findings, it was recommended among others that good personal hygiene should be maintained constantly by individuals and family members, human to human transmission should be avoided as much as possible, individuals should avoid cross contamination through raw meats and uncooked foods, sanitizers, hand gloves and disinfectants should always be adequately provided for health workers, masks must be properly worn when attending to patients, there must be regular routine checks for health workers, droplets from cough and sneeze should be avoided. Also, direct contact with patients and their personal tools must be discouraged and avoided, persons exhibiting symptoms should be quarantined to prevent transmission and spread of coronavirus.
Trustworthy Computing under Identity Based Encryption
Year: 2011

We propose a fully functional identity based encryption scheme (IBE) The scheme has chosen cipher text security in the random oracle model assuming a variant of the computational DiffieHellman problem. Our system is based on bilinear maps between groups. The Weil pairing on elliptic curves is an example of such a map. We give precise definitions for secure identity based encryption schemes and give several applications for such systems. Trustworthy computing modules like secure coprocessors (ScP) are already in extensive use today, albeit limited predominantly to scenarios where constraints on cost is not a serious limiting factor. However, inexpensive trustworthy computers are required for many evolving application scenarios. The problem of realizing inexpensive ScPs for large scale networks consisting of low complexity devices have not received adequate consideration thus far. We introduce two strategies toward realizing lowcost ScPs. The first is the decrypt only when necessary (DOWN) policy, which can substantially improve the ability of low cost ScPs to protect their secrets. The DOWN policy relies on the ability to operate with fractional parts of secrets. Taking full advantage of the DOWN policy requires consideration of the nature of computations performed with secrets and even the mechanisms employed for distribution of secrets.
How a Google Grant and Google Analytics Improved a Website: A Case Example of a University's Arbitration and Mediation Website Used by Students, Business and the Public
Year: 2014

The purpose of this paper is to describe the Grand Valley State University Arbitration and Mediation Website and to explain how web site analytics provided by Google helped redefine and reshape this website so that it was easier to use and delivered better content for users all over the globe.The web site's focus is on two common forms of alternative dispute resolution, arbitration and mediation. The web site is currently used as both a free resource for arbitration awards and as a teaching tool for these two popular alternative dispute resolution methods. Mediation and arbitration have become the chosen method of dispute resolution in business so the need for more information about these topics is timely.The Websites are aided by a Google Grant that has provided the administrators with an unprecedented amount of data relating to its usage and users. This data has allowed the administrators to change and adapt the website in the goal of making it more user friendly and ultimately a teaching aid. The primary purpose of the team that administers the arbitration web site (and other web sites and mobile applications) is to teach through technology as a public service of the university.The site is used by many in business and the public in general all over the globe.
Perceived Discrimination and Subjective Well being in Chinese Migrant Adolescents: Collective and Personal Self esteem As Mediators
Venue: Front. Psychol.
Year: 2017

This study aimed to examine whether collective and personal self esteem serve as mediators in the relationship between perceived discrimination and subjective well being among Chinese rural to urban migrant adolescents. Six hundred and ninety two adolescents completed a perceived discrimination scale, a collective self esteem scale, a personal self esteem scale, and a subjective well being scale. Structural equation modeling was used to test the mediation hypothesis. The analysis indicated that both collective and personal self esteem partially mediated the relationship between perceived discrimination and subjective well being. The final model also revealed a significant path from perceived discrimination through collective and personal self esteem to subjective well being. These findings contribute to the understanding of the complicated relationships among perceived discrimination, collective and personal self esteem, and subjective well being. The findings suggest that collective and personal self esteem are possible targets for interventions aimed at improving subjective well being. Programs to nurture both the personal and collective self esteem of migrant adolescents may help to weaken the negative relationships between perceived discrimination and subjective well being.
The long term effects of being bullied or a bully in adolescence on externalizing and internalizing mental health problems in adulthood
Venue: Child and Adolescent Psychiatry and Mental Health
Year: 2015

BackgroundThe aim is to examine associations between bullying involvement in adolescence and mental health problems in adulthood.MethodsInformation on bullying involvement (being bullied, bully victim, aggressive toward others) and non involved was collected from 2464 adolescents in Mid Norway at mean age 13.7 and again at mean age 14.9. Information about mental health problems and psychosocial functioning was collected about 12 years later at mean age 27.2 (n 1266).ResultsAll groups involved in bullying in young adolescence had adverse mental health outcomes in adulthood compared to non involved. Those being bullied were affected especially regarding increased total sum of depressive symptoms and high levels of total, internalizing and critical symptoms, increased risk of having received help for mental health problems, and reduced functioning because of a psychiatric problem in adulthood. While those being aggressive toward others showed high levels of total and internalizing symptoms. Both those being bullied and bully victims showed an increased risk of high levels of critical symptoms. Lastly, all groups involved in bullying on adolescence had increased risk of psychiatric hospitalization because of mental health problems.ConclusionInvolvement in bullying in adolescence is associated with later mental health problems, possibly hindering development into independent adulthood.
Neural text normalization with adapted decoding and POS features
Venue: Natural Language Engineering
Year: 2019

Text normalization is the task of mapping noncanonical language, typical of speech transcription and computer mediated communication, to a standardized writing. This task is especially important for languages such as Swiss German, with strong regional variation and no written standard. In this paper, we propose a novel solution for normalizing Swiss German WhatsApp messages using the encoder decoder neural machine translation (NMT) framework. We enhance the performance of a plain character level NMT model with the integration of a word level language model and linguistic features in the form of part of speech (POS) tags. The two components are intended to improve the performance by addressing two specific issues: the former is intended to improve the fluency of the predicted sequences, whereas the latter aims at resolving cases of word level ambiguity. Our systematic comparison shows that our proposed solution results in an improvement over a plain NMT system and also over a comparable character level statistical machine translation system, considered the state of the art in this task till recently. We perform a thorough analysis of the compared systems' output, showing that our two components produce indeed the intended, complementary improvements.
Cross Domain Palmprint Recognition via Regularized Adversarial Domain Adaptive Hashing
Venue: IEEE Transactions on Circuits and Systems for Video Technology
Year: 2021

As an effective method of biometrics, palmprint recognition allows the safe identity recognition of humans without spatial and temporal limitations. To build a more robust palmprint recognition system, recent promising Convolutional Neural Networks (CNN) has been incorporated for better palmprint feature extraction and representation. However, the increasing number of palmprint datasets presents us with a cross domain recognition problem where the upcoming images may come from different imaging conditions compared to the registered palmprints, which will undermine the recognition accuracy significantly. As a supervised approach, the performance of CNN based model depends on the availability of data and labels from the same domain, which is hard for transferring recognition. To keep the outperforming recognition result of CNN based models, we propose a novel Regularized Adversarial Domain Adaptative Hashing method (R ADAH) for cross domain palmprint recognition based on Deep Hashing Network (DHN) During training, the Maximum Mean Discrepancy (MMD) is incorporated for better adaptive performance. In this scenario, we only train a DHN on the source domain. With the adversarial training, the target network is becoming adaptive to the unlabeled palmprint images with more stable training, unbiased sample gradient and less sensitivity to the hyper parameter tuning when only domain specific label is provided. Extensive validation experiments are conducted on benchmark datasets and our self collected palmprint datasets by mobile phones to test the performance of our model. The results show a promising increase of the recognition performance.
Interrogating the impact of scientific and technological development on disabled children in India and beyond
Year: 2017

Products of scientific and technological developments are emerging at an ever increasing speed whereby these developments impact the daily life of humans in numerous ways. We focus for this paper on two classes of emerging products; one being social robots and the other being products that are envisioned to increase the cognitive abilities of humans beyond the species typical and their impact on aspects of childhood such as education and self identity formation. We analyse the utility and impact of these two classes of products through the lens of the alternative report on India to the Convention on the Rights of the Child (CRC) Committee on the Rights of Children authored by the by National Disability Network of India and the lens of ability expectations. We posit that the discourses around these two classes of emerging products do not address the problems the alternative report raises, but could heighten the problems identified by the report. We believe the two classes of products highlight the need for ability expectation governance.
La clase invertida una oportunidad para formacion de competencias en el Ingeniero Industrial
Venue: 2020 IEEE Congreso Bienal de Argentina (ARGENCON)
Year: 2020

El presente trabajo expone una experiencia aulica de la asignatura Sistemas de Representacion en la carrera de Ingenieria Industrial de la Facultad de Ciencias Agrarias de la Universidad Nacional del Nordeste. La propuesta pedagogica utilizo tres herramientas combinadas la clase invertida, tutoria entre pares y aprendizaje basada en desafios. La estrategia educativa busco promover el aprendizaje significativo, donde el estudiante fuera protagonista de su formacion. A su vez, debio asumir la responsabilidad de preparar el tema para ensenar a sus companeros, seleccionar el ejercicio a desarrollar y confeccionar el material de estudio. La respuesta positiva de los estudiantes ante el cambio de roles se manifesto en la mejora del rendimiento academico, la motivacion en las clases y el clima atento ante el discurso de sus pares. Esto permitio el desarrollo de competencias tecnologicas y sociales. El alumno se convirtio en protagonista de su propio aprendizaje, evidenciando a traves de su desempeno sus compromisos para aprender y ensenar a sus pares. La necesidad de adaptacion al cambio constante hace que nuestros futuros profesionales deban contar con las herramientas internas necesarias para afrontar con exito este desafio. El autoaprendizaje y la capacidad de adaptacion resultan evidentes en el mercado laboral. A la vez deben sumarse las competencias sociales, actitudinales y politicas para el buen desempeno en los equipos de trabajo de la empresa en la actualidad
Two Stage Limited Feedback Hybrid Precoding in Multiuser MIMO Systems
Venue: ICC 2020 2020 IEEE International Conference on Communications (ICC)
Year: 2020

Accurate channel state information (CSI) is essential at the base station (BS) in order to serve multiple users simultaneously on the same time frequency resources. Explicit low rate CSI feedback from each user terminal to the BS is indispensable in frequency division duplexing (FDD) multipleinput multiple output (MIMO) hybrid precoding systems. In the presence of correlated Rician fading channels with arbitrary rank, and in order to reduce the feedback overhead, a unified adaptive statistical codebook is designed by leveraging the long term first and second order channel statistics. Moreover, as the feedback overhead scales linearly with the number of BS antennas, which introduces a bottleneck in FDD massive MIMO systems, an adaptive two stage reduced dimensionality codebook design is developed. The main idea stems from the fact that the high dimensional analog beamforming stage could get away with coarse CSI, e.g. statistical CSI, while the low dimensional baseband precoding stage acquires finite rate quantized CSI of the reduced dimensionality channel to eliminate multiuser interference. These steps reduce significantly the CSI training and feedback overhead to scale linearly with the number of radio frequency chains instead. For comparison purposes, the two extremes of full and statistical CSI at the BS are also included. The performance gap between these two extremes justifies the importance of the proposed two stage reduced dimensionality adaptive statistical codebook.
The Recursive Mind: The Origins of Human Language, Thought, and Civilization
Year: 2014

Foreword to the Paperback Edition vii Preface xi Chapter 1 What Is Recursion? 1 PART 1: Language 17 Chapter 2: Language and Recursion 19 Chapter 3: Do Animals Have Language? 36 Chapter 4: How Language Evolved from Hand to Mouth 55 PART 2: Mental Time Travel 81 Chapter 5: Reliving the Past 83 Chapter 6: About Time 100 Chapter 7: The Grammar of Time 112 PART 3: Theory of Mind 129 Chapter 8: Mind Reading 131 Chapter 9: Language and Mind 151 PART 4: Human Evolution 167 Chapter 10: The Recurring Question 169 Chapter 11: Becoming Human 181 Chapter 12: Becoming Modern 208 Chapter 13: Final Thoughts 221 Notes 227 References 253 Index 281