nils-herrmann/clean_scirepeval huggingface dataset:
Human placental GLUT1 glucose transporter expression and the fetal insulin like growth factor axis in pregnancies complicated by diabetes.
Venue: Biochimica et biophysica acta. Molecular basis of disease
Year: 2019

We have previously described regulation of syncytial GLUT1 glucose transporters by IGF I. Despite this, it is not clear what signal regulates transplacental glucose transport. In this report we asked whether changes in GLUT1 expression and glucose transport activity in diabetic pregnancies were associated with alterations in the fetal IGF axis. Cord blood samples and paired syncytial microvillous and basal membranes were isolated from normal term pregnancies and pregnancies characterized by gestational diabetes type A2 (GDM A2) and pre existing insulin dependent diabetes mellitus (IDDM) Circulating IGF I, basal membrane GLUT1 expression and glucose transporter activity were correlated with birth weight, but only in control, not diabetic groups. Basal membrane GLUT1 and transporter activity were correlated with IGF I concentrations in control, but not diabetic groups. IGF binding protein (IGFBP) binding capacity showed a =50% reduction in the diabetic groups compared to control; both showed a higher level of free IGF I. The absence of a correlation between birth weight and factors such as fetal IGF I or GLUT1 expression in the diabetic groups suggests that IGF I stimulated effects may have reached a limiting threshold, such that further increases in IGF I (or GLUT1) are without effect. These data support that fetal IGF I acts as a fetal nutritional signal, modulating placental GLUT1 expression and birth weight via altered levels of fetal circulating IGFBPs. Diabetes appears to exert its effects on fetal and placental factors prior to the third trimester and, despite good glycemic control immediately prior to, and in the third trimester, these effects persist to term.
Solutions for patients depend on whether we can bridge the divide between social and natural science research approaches in the area of mental health
Year: 2012

Research aimed at understanding the basis of mental disorders has expanded exponentially in the last decades. While many interesting findings have been produced, there have been no major breakthroughs in treatment over the last 20 years, and treatments that once were considered breakthroughs, later were shown effective only in particular subgroups or not more effective than simpler non specific interventions. Despite extensive research involving genetic, immunological, hormonal, cognitive, neurophysiological and neuroradiological variables, no diagnostic test, biological or other, exists for any mental disorder. Two approaches can be envisaged to overcome this state of affairs. The first can be characterised as 'focussed' i.e. to select a specific natural science focus that, coupled
AB0435 REAL WORLD DATA OF A PATIENT COHORT WITH RHEUMATOID ARTRITIS TREATED WITH JAK/STAT INHIBITORS
Venue: Abstracts Accepted for Publication
Year: 2019

We present the real World data of a patient cohort with rheumatoid arthritis (RA) that received one of the two JAK/STAT inhibitors approved by the EMA for this indication.  To describe the Real World Data of a patient cohort attending Rheumatology consult of a reference hospital in Valencia with RA diagnosis and that were treated with JAK/STAT inhibitors.  A descriptive retrospective study was carried out. There were revised medical histories of 28 patients with a RA diagnosis that attended our consults between 2017 and 2018. All 28 patients were JAK/STAT treatment receivers of one of the two JAK/STAT inhibitors approved: Tofacitinib 10 mg oral QD or Bariticinib 4 mg oral QD. There were collected patient baseline demographic data: sex, age, BMI, activity disease score measured by DAS28 CRP and visual pain analogue scale for patient's assessment (VAS) In addition, there were collected the previous synthetic(s) and biological (s) DMARD treatments, as well as the associated treatments. Efficacy and security were also analysed. There were assessed serum biochemical variables, among them acute phase reactants such as CRP and and ESR  The study population consisted in 28 patients with the following distribution: M/F Mean age (years) BMI (kg/m2) Baricitinib Tofacitinib DAS28/CRP (at de begining) Mean treatment time (days) 12 (42%/16 (58% 58.39 30.12 9 (32.14% 19 (67.85% 4.81 230.11 With regards to the previous treatments received, we obtained the following results: Previous DMARDb Previous DMARDc 3TB 2TB 1TB Naive 3 2 1 Naive 5 3 10 10 2 9 15 2 DMARDb: Number of previous biological treatment DMARDc: Number of synthetic previous treatments With regards to efficacy, there were collected 6 treatment withdrawals: 1 primary treatment failure (in Tofacitinib Group) and 5 secondary treatment failures (1 in Baricitiib Group and 4 in Tofacitinib Group) and the mean treatment duration was 152 days.  Despite the study population was small and the follow up time was short, we highlight in our patients that both JAK inhibitor alternatives have shown a security and efficacy profile similar to the results shown in pivotal clinical trials. Despite the previous biological treatment failure and obesity are considered as predictors of bad response to treatment, in our cohort did not represent a high risk to treatment failure, it can be an alternative in the same scenary. Disclosure of Interests: Isabel de la Morena Speakers bureau: Abbvie, Celgene, Pfzier, UCB, Ghebro, Roche, Sanofi, Janssen. Juan Alberto Paz Solarte Employee of: He is working at UCB since December 2018, when the patient recruitment ended.  Abbvie, Roche, Pfzier, Novartis, Celgene, Amgen, MSD, Janssen, Diego Bedoya: None declared, Pilar Trenor Larraz: None declared
A critical evaluation of alternative methods and paradigms for conducting mediation analysis in operations management research
Year: 2014

Mediation as a theory testing approach has witnessed considerable adoption among Operations Management (OM) researchers. Although mediation testing methods have evolved tremendously in the past decade, their dissemination in the OM field has not seen parallel growth. These advanced techniques facilitate the testing of existing and complex hypotheses in a more precise manner. With the intent of critically evaluating existing and alternative methods for conducting mediation analysis needed to support sophisticated empirical research, this paper first reviews OM studies that tested for mediation in the past eleven years (2002 2012) from top tier OM journals. Four commonly used mediation approaches were identified. Based on principles of good theory building, type of mediation model, and properties of empirical data, we evaluate the existing methodologies and make recommendations on how to improve the rigor of OM mediation testing. Using published OM studies in top journals as examples, we then illustrate the relevance and advantages of these recommendations, as well as their ease of use. Furthermore, we empirically show that more robust and insightful results can be achieved by adopting these techniques, which in turn have the promise of leading to better theory building and testing in the field of operations management.
Finetuned Language Models Are Zero Shot Learners
Venue: ArXiv
Year: 2021

This paper explores a simple method for improving the zero shot learning abilities of language models. We show that instruction tuning finetuning language models on a collection of datasets described via instructions substantially boosts zeroshot performance on unseen tasks. We take a 137B parameter pretrained language model and instruction tune it on over 60 NLP datasets verbalized via natural language instruction templates. We evaluate this instruction tuned model, which we call FLAN, on unseen task types. FLAN substantially improves the performance of its unmodified counterpart and surpasses zero shot 175B GPT 3 on 20 of 25 datasets that we evaluate. FLAN even outperforms few shot GPT 3 by a large margin on ANLI, RTE, BoolQ, AI2 ARC, OpenbookQA, and StoryCloze. Ablation studies reveal that number of datasets and model scale are key components to the success of instruction tuning. Target Input (Commonsense Reasoning) keep stack of pillow cases in fridge Inference on unseen task type Finetune on many tasks "instruction tuning" Translate this sentence to Spanish: The new office building was built in less than three months. Translation) El nuevo edificio de oficinas se construyo en tres meses. Target Input (Natural Language Inference) It is not possible to tell FLAN Response Coreference resolution tasks Sentiment analysis tasks GPT 3 175B zero shot GPT 3 175B few shot FLAN 137B zero shot Performance on unseen task types Natural language inference 42.9 53.2 56.2 Reading Comprehension 63.7 72.6 77.4 Closed Book QA 49.8 55.7 56.6 Here is a goal: Get a cool sleep on summer days. How would you accomplish this goal?  Keep stack of pillow cases in fridge. Keep stack of pillow cases in oven.  At my age you will probably have learnt one lesson.  It's not certain how many lessons you'll learn by your thirties. Does the premise entail the hypothesis?  yes it is not possible to tell  Top: overview of instruction tuning and FLAN. Instruction tuning finetunes a pretrained language model on a mixture of tasks phrased as instructions. At inference time, we evaluate on an unseen task type; for instance, we could evaluate the model on natural language inference (NLI) when no NLI tasks were seen during instruction tuning. Bottom: performance of zero shot FLAN on unseen task types, compared with zero shot GPT 3 and few shot. NLI datasets: ANLI R1 R3, CB, RTE. Reading comprehension datasets: BoolQ, MultiRC, OBQA. Closed book QA datasets: ARC easy, ARC challenge, NQ, TriviaQA. Lead contributors. Author contributions listed at end of paper. 1 ar X iv :2 10 9. 01 65 2v 2 cs .C L 5 O ct 2 02 1
Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO OFDM Dynamic Spectrum Sharing
Venue: AAAI
Year: 2020

In this paper, we introduce a deep spiking delayed feedback reservoir (DFR) model to combine DFR with spiking neuros: DFRs are a new type of recurrent neural networks (RNNs) that are able to capture the temporal correlations in time series while spiking neurons are energy efficient and biologically plausible neurons models. The introduced deep spiking DFR model is energy efficient and has the capability of analyzing time series signals. The corresponding field programmable gate arrays (FPGA) based hardware implementation of such deep spiking DFR model is introduced and the underlying energy efficiency and recourse utilization are evaluated. Various spike encoding schemes are explored and the optimal spike encoding scheme to analyze the time series has been identified. To be specific, we evaluate the performance of the introduced model using the spectrum occupancy time series data in MIMO OFDM based cognitive radio (CR) in dynamic spectrum sharing (DSS) networks. In a MIMO OFDM DSS system, available spectrum is very scarce and efficient utilization of spectrum is very essential. To improve the spectrum efficiency, the first step is to identify the frequency bands that are not utilized by the existing users so that a secondary user (SU) can use them for transmission. Due to the channel correlation as well as users' activities, there is a significant temporal correlation in the spectrum occupancy behavior of the frequency bands in different time slots. The introduced deep spiking DFR model is used to capture the temporal correlation of the spectrum occupancy time series and predict the idle/busy subcarriers in future time slots for potential spectrum access. Evaluation results suggest that our introduced model achieves higher area under curve (AUC) in the receiver operating characteristic (ROC) curve compared with the traditional energy detection based strategies and the learning based support vector machines (SVMs)
The UAVid Dataset for Video Semantic Segmentation
Venue: ArXiv
Year: 2018

Video semantic segmentation has been one of the research focus in computer vision recently. It serves as a perception foundation for many fields such as robotics and autonomous driving. The fast development of semantic segmentation attributes enormously to the large scale datasets, especially for the deep learning related methods. Currently, there already exist several semantic segmentation datasets for complex urban scenes, such as the Cityscapes and CamVid datasets. They have been the standard datasets for comparison among semantic segmentation methods. In this paper, we introduce a new high resolution UAV video semantic segmentation dataset as complement, UAVid. Our UAV dataset consists of 30 video sequences capturing high resolution images. In total, 300 images have been densely labelled with 8 classes for urban scene understanding task. Our dataset brings out new challenges. We provide several deep learning baseline methods, among which the proposed novel Multi Scale Dilation net performs the best via multi scale feature extraction. We have also explored the usability of sequence data by leveraging on CRF model in both spatial and temporal domain.
Assessing metacognition of grade 2 and grade 4 students using an adaptation of multi method interview approach during mathematics problem solving
Year: 2018

The important role that metacognition plays as a predictor for student mathematical learning and for mathematical problem solving, has been extensively documented. But only recently has attention turned to primary grades, and more research is needed at this level. The goals of this paper are threefold: (1) to present metacognitive framework during mathematics problem solving, (2) to describe their multi method interview approach developed to study student mathematical metacognition, and (3) to empirically evaluate the utility of their model and the adaptation of their approach in the context of grade 2 and grade 4 mathematics problem solving. The results are discussed not only with regard to further development of the adapted multi method interview approach, but also with regard to their theoretical and practical implications.
Parallel Randomized Block Coordinate Descent for Neural Probabilistic Language Model with High Dimensional Output Targets
Venue: CCPR
Year: 2016

Training a large probabilistic neural network language model, with typical high dimensional output is excessively time consuming, which is one of the main reasons that more simplified models such as n gram is often more popular despite the inferior performance. In this paper a Chinese neural probabilistic language model is trained using the Fudan Chinese Language Corpus. As hundreds of thousands of distinct words have been tokenized from the raw corpus, the model contains tens of millions of parameters. To address the challenge, popular parallel computing platform MPI (Message Passing Interface) based on cluster is employed to implement the parallel neural network language model. Specifically, we propose a new method termed as Parallel Randomized Block Coordinate Descent (PRBCD) to train this model cost effectively. Different from traditional coordinate descent method, our new method could be employed in network with multiple layers, allowing scaling up the gradients with respect to hidden units proportionally based on sampled parameters. We empirically show that our PRBCD is stable and is well suited for language models, which contain only a few layers while often have a large amount of parameters and extremely high dimensional output targets.
On the Integrability of the Benjamin Ono Equation on the Torus
Year: 2019

In this paper we prove that the Benjamin Ono equation, when considered on the torus, is an integrable (pseudo)differential equation in the strongest possible sense: it admits global Birkhoff coordinates on the space $L^2(\T) These are coordinates which allow to integrate it by quadrature and hence are also referred to as nonlinear Fourier coefficients. As a consequence, all the $L^2(\T) solutions of the Benjamin Ono equation are almost periodic functions of the time variable. The construction of such coordinates relies on the spectral study of the Lax operator in the Lax pair formulation of the Benjamin Ono equation and on the use of a generating functional, which encodes the entire Benjamin Ono hierarchy.
Essays: Representations of Youth and Political Consciousness in the Music of Bob Marley
Year: 2010

The evaluation of Bob Marley's legacy should begin with consideration of the elaborate profile that he constructed through his music. Over the course of his career, Marley wrote music that encompassed a rich variety of subjects and sentiments, ranging from praise of youth culture in Jamaica to spiritual meditations, denunciations of war to reflections on intimacy and love. Marley's lyrics undoubtedly expressed his private feelings about personal relationships as well as his own political convictions rooted in the oppressive conditions of urban Jamaica in the 1960s and 1970s. But the character of the expression of these sentiments, especially through the figurative language of Rastafari, also opens them up to an array of possible interpretations and enables the ongoing process of identification with his music. Literary scholar Carolyn Cooper has suggested about Marley's music that meaning is not immanent: 'The audience, as much as the performer, engages in the making/spreading of the text and its meanings' (1995:118) One important ramification of this premise is that the extent of Marley's influence on social and political consciousness across the world should not be considered fixed. Broadening our sense of the ways in which people have identified politically with Marley's music may be accomplished by considering the ways in which the lyrical subjects and 1. Paul Gilroy has argued that, in analyzing Marley's global appeal, 'attention should be placed upon the processes and mechanisms of identification. Do people connect themselves and their hopes with the mythic figure of Bob Marley as a man, as a Jamaican, a Caribbean, an African or panAfrican artist? He was somehow all of the above and yet more' (2005:240) Review: Literature and Arts of the Americas, Issue 81, Vol. 43, No. 2, 2010, 237 242
Uniform ripening Encodes a Golden 2 like Transcription Factor Regulating Tomato Fruit Chloroplast Development
Venue: Science
Year: 2012

Pretty or Sweet The grocery store tomato that looks beautiful but tastes like tart cardboard arises from selection processes favoring phenotypes that make commercial production more reliable. Significant in that selection process was a mutation that reduced the mottled color variations of unripe green tomatoes, leaving them a uniform, pale, green. Powell et al. (p. 1711) analyzed the molecular biology of the mutation. The uniform ripening mutation turns out to disable a transcription factor called Golden 2 like (GLK2) GLK2 expression increases the fruit's photosynthetic capacity, resulting in higher sugar content. Controlling when tomatoes turn from green to red requires knocking out the gene that adds flavor. Modern tomato (Solanum lycopersicum) varieties are bred for uniform ripening (u) light green fruit phenotypes to facilitate harvests of evenly ripened fruit. U encodes a Golden 2 like (GLK) transcription factor, SlGLK2, which determines chlorophyll accumulation and distribution in developing fruit. In tomato, two GLKs SlGLK1 and SlGLK2 are expressed in leaves, but only SlGLK2 is expressed in fruit. Expressing GLKs increased the chlorophyll content of fruit, whereas SlGLK2 suppression recapitulated the u mutant phenotype. GLK overexpression enhanced fruit photosynthesis gene expression and chloroplast development, leading to elevated carbohydrates and carotenoids in ripe fruit. SlGLK2 influences photosynthesis in developing fruit, contributing to mature fruit characteristics and suggesting that selection of u inadvertently compromised ripe fruit quality in exchange for desirable production traits.
Modified Bernstein Function and a Uniform Approximation of Some Rational Fractions by Polynomials
Year: 2018

P. L. Chebyshev posed and solved (1857, 1859) the problem of finding an improper rational fraction least deviating from zero in the uniform metric on a closed interval among rational fractions whose denominator is a fixed polynomial of a given degree m that is positive on the interval and whose numerator is a polynomial of a given degree n m with unit leading coefficient. In 1884, A.A.Markov solved a similar problem in the case when the denominator is the square root of a given positive polynomial. In the 20th century, this research direction was developed by S.N.Bernstein, N. I.Akhiezer, and other mathematicians. For example, in 1964, G. Szego extended Chebyshev's result to the case of trigonometric fractions using the methods of complex analysis. In this paper, using the methods of real analysis and developing Bernstein's approach, we find the best uniform approximation on the period by trigonometric polynomials of a certain order for an infinite series of proper trigonometric fractions of a special form. It turned out that, in the periodic case, it is natural to formulate some results in terms of the generalized Poisson kernel Pr,x(t) (cosx)Pr(t) (sinx)Qr(t) which is a linear combination of the Poisson kernel Pr(t) (1 r2)[2(1 r2 2r cos t) and the conjugate Poisson kernel Qr(t) (r sin t)(1 r2 2r cos t) where r 1, 1) and x R. We find the best uniform approximation on the period by the subspace Tn of trigonometric polynomials of order at most n for the linear combination Pr,x(t) 1)nPr,x(t p) of the generalized Poisson kernel and its translation. For x 0, this yields Bernstein's known results on the best uniform approximation on 1, 1] of the fractions 1/(x2 a2) and x/(x2 a2) |a| 1, by algebraic polynomials. For x p/2, we obtain the weight analogs (with the weight \sqrt {1 {x^2} $1 x2x2) of these results. In addition, we find the value of the best uniform approximation on the period by the subspace Tn of a special linear combination of the mentioned Poisson kernel Pr and the Poisson kernel Kr for the biharmonic equation in the unit disk.
Contributions geographiques a la definition d'une culture du risque en milieu littoral le cas des residents de l'ile d'Oleron (Charente Maritime, France)
Venue: Norois
Year: 2019

Le point de depart de cette these a ete l'expression de <culture du risque> telle qu'elle a ete employee par l'Etat suite aux evenements lies a la tempete Xynthia en 2010. A travers celle ci, ce dernier rend compte d'un manque de connaissances et de comportements inadaptes, caracterisant les populations vis a vis des aleas cotiers. Parallelement, il affiche sa volonte de favoriser leur sensibilisation vis a vis de ces problematiques. Cependant, nous avons constate qu'un dispositif legislatif de communication et de sensibilisation existe depuis les annees 1980, mais que son bilan parait toujours mitige. De plus, deux visions principales paraissent s'affronter d'un cote, l'Etat qui cherche a limiter l'implantation des enjeux dans des zones dites a risque de l'autre les populations locales qui demandent a proteger leurs enjeux. Ainsi, la confrontation aux memes aleas ne donne pas lieu a des interpretations identiques differentes cultures du risque existent. Afin de comprendre ces differences, nous tenterons de demontrer l'hypothese stipulant que les differents discours observes aupres des individus en matiere de risques cotiers sont determines par leurs rapports au milieu. Il sera donc question de caracteriser ces rapports et d'illustrer en quoi ceux ci sont susceptibles d'affecter leurs discours et leurs comportements a propos des aleas cotiers. Parallelement, nous tenterons de definir les composantes d'une culture du risque et d'en evaluer le niveau aupres des residents oleronais. Pour cela, nous nous appuierons sur l'analyse statistique de resultats issus d'une enquete par questionnaire, mais aussi sur l'analyse de cartes mentales.