nils-herrmann/clean_scirepeval huggingface dataset:
REM Sleep Behavior Disorder in Parkinson's Disease and Other Synucleinopathies
Venue: Movement disorders official journal of the Movement Disorder Society
Year: 2017

Rapid eye movement sleep behavior disorder is characterized by dream enactment and complex motor behaviors during rapid eye movement sleep and rapid eye movement sleep atonia loss (rapid eye movement sleep without atonia) during polysomnography. Rapid eye movement sleep behavior disorder may be idiopathic or symptomatic and in both settings is highly associated with synucleinopathy neurodegeneration, especially Parkinson's disease, dementia with Lewy bodies, multiple system atrophy, and pure autonomic failure. Rapid eye movement sleep behavior disorder frequently manifests years to decades prior to overt motor, cognitive, or autonomic impairments as the presenting manifestation of synucleinopathy, along with other subtler prodromal "soft" signs of hyposmia, constipation, and orthostatic hypotension. Between 35% and 91.9% of patients initially diagnosed with idiopathic rapid eye movement sleep behavior disorder at a sleep center later develop a defined neurodegenerative disease. Less is known about the long term prognosis of community dwelling younger patients, especially women, and rapid eye movement sleep behavior disorder associated with antidepressant medications. Patients with rapid eye movement sleep behavior disorder are frequently prone to sleep related injuries and should be treated to prevent injury with either melatonin 3 12 mg or clonazepam 0.5 2.0 mg to limit injury potential. Further evidence based studies about rapid eye movement sleep behavior disorder are greatly needed, both to enable accurate prognostic prediction of end synucleinopathy phenotypes for individual patients and to support the application of symptomatic and neuroprotective therapies. Rapid eye movement sleep behavior disorder as a prodromal synucleinopathy represents a defined time point at which neuroprotective therapies could potentially be applied for the prevention of Parkinson's disease, dementia with Lewy bodies, multiple system atrophy, and pure autonomic failure.
EVE: explainable vector based embedding technique using Wikipedia
Venue: Journal of Intelligent Information Systems
Year: 2018

We present an unsupervised explainable vector embedding technique, called EVE, which is built upon the structure of Wikipedia. The proposed model defines the dimensions of a semantic vector representing a concept using human readable labels, thereby it is readily interpretable. Specifically, each vector is constructed using the Wikipedia category graph structure together with the Wikipedia article link structure. To test the effectiveness of the proposed model, we consider its usefulness in three fundamental tasks: 1) intruder detection to evaluate its ability to identify a non coherent vector from a list of coherent vectors, 2) ability to cluster to evaluate its tendency to group related vectors together while keeping unrelated vectors in separate clusters, and 3) sorting relevant items first to evaluate its ability to rank vectors (items) relevant to the query in the top order of the result. For each task, we also propose a strategy to generate a task specific human interpretable explanation from the model. These demonstrate the overall effectiveness of the explainable embeddings generated by EVE. Finally, we compare EVE with the Word2Vec, FastText, and GloVe embedding techniques across the three tasks, and report improvements over the state of the art.
Unsupervised Facial Image Synthesis Using Two Discriminator Adversarial Autoencoder Network
Venue: 2019 IEEE International Conference on Multimedia and Expo (ICME)
Year: 2019

Recent years have witnessed the unprecedented success in single image synthesis by the means of convolutional neural networks (CNNs) High level synthesis of facial image such as expression translation and attribute swap is still a challenging task due to high non linearity. Previous methods suffer from the limitations that being unable to transfer multiple face attributes simultaneously, or incapability of transferring an attribute to another by a continuously changing way. To address this problem, we propose a two discriminator adversarial autoencoder network (TAAN) The latent discriminator is trained to disentangle an input image from its original facial attribute, while the pixel discriminator is trained to make the output image attach to the target facial attribute. By controlling the attribute values, we can choose which and how much a specific attribute can be perceivable in the generated image. Quantitative and qualitative evaluations are conducted on the celebA and KDEF datasets, and the comparison with the state of the art methods shows the competency of our proposed TAAN.
Pelatihan Penyusunan Lembar Kegiatan Siswa (LKS) Matematika Berbantuan Geogebra Training to Create Mathematics Student Activity Sheet Using Geogebra
Year: 2018

Student Activity Sheet (LKS) is one of the teaching materials that should be prepared by the teacher to improve the quality of learning. Especially for math teachers, LKS which is completed with graphical visualization can improve students' enthusiasm. Software that is quite easy but with a complete feature is Geogebra. Therefore, the purpose of the training is for the preparation of Geogebra assisted LKS. This training is in the form of demonstration activity of Geogebra both 2D and 3D for material of geometry, algebra, and calculus. The activity continued with the assistance to the participants by first forming the participants into several groups. Activities are inserted with evaluation and reflection so that participants' needs can be accommodated. Apart from the technical use of Geogebra, the participants are also equipped with theory and motivation for the development of teaching materials. Based on the questionnaire results, a total of 65.38% of participants considered that the training activities are very motivating in improving the implementation of learning in schools. Participants also respond very well in terms of the usefulness of this training and expect continued activities.
Deep Metric Learning Beyond Binary Supervision
Venue: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2019

Metric Learning for visual similarity has mostly adopted binary supervision indicating whether a pair of images are of the same class or not. Such a binary indicator covers only a limited subset of image relations, and is not sufficient to represent semantic similarity between images described by continuous and/or structured labels such as object poses, image captions, and scene graphs. Motivated by this, we present a novel method for deep metric learning using continuous labels. First, we propose a new triplet loss that allows distance ratios in the label space to be preserved in the learned metric space. The proposed loss thus enables our model to learn the degree of similarity rather than just the order. Furthermore, we design a triplet mining strategy adapted to metric learning with continuous labels. We address three different image retrieval tasks with continuous labels in terms of human poses, room layouts and image captions, and demonstrate the superior performance of our approach compared to previous methods.
Feasibility of industrial scale treatment of dye wastewater via bio adsorption technology.
Venue: Bioresource technology
Year: 2019

This review emphasizes the importance of costs in industrial scale treatment of dye wastewater and provides a way to assess the cost based feasibility of bio adsorption technologies. Dye wastewater is one of the major contributors to environmental pollution. Bio adsorption has attracted considerable attentions in dye wastewater treatment due to its technical feasibility, flexibility and operation simplicity. However, industrial scale treatment of dye wastewater via bio adsorption technologies remains stagnant, mainly due to high costs. So far, no review or research articles have systematically discussed the criteria for successful utilization of bio adsorption technologies on a large scale. This review discusses the major factors affecting adsorption and desorption performance based on basic chemical and physical structures of bio adsorbents available in literatures. A quantitative relationship has been summarized based on previous studies to assess the cost to utilize a bio adsorption technology and serve as an access threshold for quality bio adsorbents to be taken into real applications.
Prediction of Reward Functions for Deep Reinforcement Learning via Gaussian Process Regression
Venue: IEEE/ASME Transactions on Mechatronics
Year: 2020

Inverse reinforcement learning (IRL) is a technique for automatic reward acquisition, however, it is difficult to apply to high dimensional problems with unknown dynamics. This article proposes an efficient way to solve the IRL problem based on the sparse Gaussian process (GP) prediction with <inline formula><tex math notation="LaTeX"$l_1$/tex math>/inline formula> regularization only using a highly limited number of expert demonstrations. A GP model is proposed to be trained to predict a reward function using trajectory reward pair data generated by deep reinforcement learning with different reward functions. The trained GP successfully predicts the reward functions of human experts from their collected demonstration trajectory datasets. To demonstrate our approach, the proposed approach is applied to the obstacle avoidance navigation of the mobile robot. The experimental results clearly show that the robots can clone the experts' optimality in navigation trajectories avoiding obstacles using only with a very small number of expert demonstration datasets (e.g. <inline formula><tex math notation="LaTeX"\leq 6$/tex math>/inline formula> Therefore, the proposed approach shows great potential to be applied to complex real world applications in an expert data efficient manner.
Monitoring the Invasion of Smooth Cordgrass Spartina alterniflora within the Modern Yellow River Delta Using Remote Sensing
Venue: Journal of Coastal Research
Year: 2019

Ren, G. B. Wang,  Zhu, Y. L. Wu, P. Q. Ma, Y. and Zhang, J.B. 2019. Monitoring the invasion of smooth cordgrass Spartina alterniflora within the modern.
Analyse du transport turbulent dans une zone de melange issue de l'instabilite de Richtmyer Meshkov a l'aide d'un modele a fonction de densite de probabilite Analyse du transport de l'energie turbulente
Year: 2018

Cette these a pour objet la simulation d'une zone de melange turbulente issue de l'instabilite de Richtmyer Meshkov a l'aide d'un modele a fonction de densite de probabilite (PDF) Nous analysons plus particulierement la prise en charge par le modele PDF du transport de l'energie cinetique turbulente dans la zone de melange.Dans cette optique, nous commencons par mettre en avant le lien existant entre les statistiques en un point de l'ecoulement et ses conditions initiales aux grandes echelles. Ce lien s'exprime a travers le principe de permanence des grandes echelles, et permet d'etablir des predictions pour certaines grandeurs de la zone de melange, telles que son taux de croissance ou son anisotropie.Nous derivons ensuite un modele PDF de Langevin capable de restituer cette dependance aux conditions initiales. Ce modele est ensuite valide en le comparant a des resultats issus de simulations aux grandes echelles (LES).Enfin, une analyse asymptotique du modele propose permet d'eclairer notre comprehension du transport turbulent. Un regime de diffusion est mis en evidence, et l'expression du coefficient de diffusion associe a ce regime atteste l'influence de la permanence des grandes echelles sur le transport turbulent.Tout au long de cette these, nous nous sommes appuyes sur des resultats issus de simulations de Monte Carlo du modele de Langevin. A cet effet, nous avons developpe une methode specifique eulerienne et a l'avons compare a des alternatives lagrangiennes.
Separating the Problem and the Person: Insights From Narrative Therapy With People Who Stutter
Year: 2015

Stuttering is a complex disorder of speech that encompasses motor speech and emotional and cognitive factors. The use of narrative therapy is described here, focusing on the stories that clients tell about the problems associated with stuttering that they have encountered in their lives. Narrative therapy uses these stories to understand, analyze, and address aspects of emotional and cognitive aspects of stuttering. In this form of therapy, the therapist helps the client deconstruct unhelpful, but widely held, discourses about people who stutter. Externalization is a core process in narrative therapy, involving the separation of the problem from the person. This process is an initial step in the reauthoring of the person's narrative. It is explained and illustrated with details from therapy with an adult who stutters.
Development of new applied models for steel corrosion in marine applications including shipping
Year: 2008

Models for the prediction of corrosion often give the misleading impression that corrosion of steel in seawater environments is a linear function of time (the "corrosion rate" More recently non linear functions for corrosion loss have been proposed calibrated to aggregated data from a wide variety of sources. Unfortunately, this use of the data produces models with wide ranges of uncertainty and makes it difficult to predict future corrosion and to assess the effect of steel composition and environmental influences. Recent research has produced a model based on the fundamental characteristics of steel corrosion, including the effect of biological influences. Detailed investigations show that the process controlling the (instantaneous) rate of corrosion changes as corrosion progresses. This is represented as a sequence of phases for which fundamental theoretical justifications and mathematical relationships have been derived. To ensure the model has practical validity, it has been calibrated to carefully selected actual field observations. This has also allowed the effect of water temperature, dissolved oxygen levels, nutrient pollution, depth, water velocity, water salinity, and steel composition to be isolated, as reviewed briefly herein. Some observations about applications and research directions are given.
LOve and aNger: The Grammatical Structure of
Year: 2016

This article integrates grammatical analysis into the study of conceptual metaphors. Although the study accepts lexically based work in metaphors such as Lakoff's Women, Fire, and Dangerous Things, Johnson's The Body in the Mind, and Kovecses' Metaphors of Anger, Pride, and Love, it argues that these lexical approaches are insufficient to offer rigorous and complete analysis of cross reference mapping. It takes the hypothesis that lexis and morpho syntax are interdependent, presented by Langacker in especially Concept, Image, and Symbol and Grammar and Conceptualization and by Talmy in "The Relation of Grammar to Cognition" and Toward a Cognitive Semantics, and examines the grammatical structure of conceptual metaphors. The analysis focuses on two emotion concepts, rOMaNTic lOve and aNger. Firstly, the discussion demonstrates weaknesses in a lexically based analysis of conceptual metaphors by examining aNger. It argues that current approaches to the study of metaphors lack both sufficient means for the verification of results and sufficient tools for revealing the structure of those results. The discussion moves to resolve these issues by examining the emotion concept lOve. Instead of focusing purely on the lexical structure of the conceptual metaphor, it combines this with a study of grammatical structure. In doing so, it demonstrates how this grammatical evidence may help resolve problems faced by lexical analyses. Moreover, by drawing on the invariance hypothesis proposed by Lakoff in "The  and by Turner in "An Image Constraint on Metaphor," it reveals details of conceptual structure that are not visible in lexical analysis, further supporting the need to systematically integrate grammatical evidence into the study of cognitive semantics. Thus, by combining the invariance hypothesis and grammatical analysis, the study demonstrates that the internal structure of conceptual metaphors is more complex than is evident from lexical approaches typically taken in the study of these metaphors. 2. ?Anger is giving Birth: Verifying Co occurrence Purely lexical analyses of cross reference mapping do not offer enough scope for the verification of the results they produce. A lexically based study of concep
Correlation between social factors and anxiety depression in function dyspepsia: do relationships exist?
Venue: Przeglad gastroenterologiczny
Year: 2014

Function dyspepsia (FD) may cause patients to suffer from anxiety and depression, and psychosocial disorders would have a significant effect on FD symptoms.  To examine the prevalence of anxiety and depression among function dyspepsia (FD) patients and to identify social factors of anxiety depression among FD patients.  Patients with FD, who fulfilled the Rome III criteria, were enrolled. All patients were administered a validated Chinese version of the self rating scale (SDS) and self rating anxiety scale (SAS) and investigated regarding the patients' social factors.  A total of 907 patients were enrolled, including 516 (56.89% FD patients within anxiety depression status; SDS mean scores were 51.57 8.22; SAS mean scores were 51.04 7.53; 52.28% were male and 64.25% were female (kh2 262.54, p 0.01) 56.16% were aged 18 29 years, 54.15% were aged 30 39 years, 54.77% were aged 40 49 years, 62.02% were aged 50 59 years, 69.23% were aged above 60 years (kh2 18.14, p 0.01) 67.44% were the retirees; 63.31% were manual workers; 55.10% were soldiers; 43.57% were mental workers; 38.89% were students (kh2 716.53, p 0.01) 64.20% had junior high school degree or below; 57.36% had high school degrees; 42.03% had college degrees; 44.44% had master's or above degrees (kh2 27.21, p 0.05) 38.10% were in good health condition; 61.90% were in poor health condition (kh2 7.94, p 0.01) 20.31% had correlative family history; and 79.69% had no correlative family history (kh2 2.23, p 0.05)  The FD patients have higher rates of anxiety and depression. Gender, age, occupation, education level, and health condition have a significant effect on anxiety and depression status. Female gender, advanced age, high stress occupation, lower education level, and poor health condition all are risk factors. Family history has no relationship with anxiety and depression among FD patients.
Manipulation under anesthesia following total knee arthroplasty: a comprehensive review of literature
Venue: MUSCULOSKELETAL SURGERY
Year: 2018

IntroductionThe etiology of the stiff knee after total knee arthroplasty (TKA) is largely unknown, although excessive scar tissue due to arthrofibrosis is an important reason for a limited range of motion (ROM) after this procedure. Persistent limited ROM after TKA results in poor patient reported outcomes and is increasingly becoming a more prominent reason for TKA revision surgery. narrative review of current literature on manipulation under anesthesia (MUA) after TKA analyzing etiology and risk factors for stiffness after TKA, effectiveness of MUA and what is known about rehabilitation after MUA.ResultsLiterature describes numerous risk factors for insufficient knee ROM after TKA, but a comprehensive valid risk model is lacking. MUA is an effective treatment option with evidence suggesting better outcomes if performed within the first 3 months after TKA. The wide variety in both the indication and timing for MUA, and the lack of scientific evidence on how to rehabilitate patients after MUA, complicates the interpretation of available literature. This is even more so the case on the reporting of one versus two or more MUAs after TKA.ConclusionFuture comparative trials, preferably with a randomized study design, should be conducted to elude more clear indications for MUA, to give clinical guidance on correct timing for MUA and on how to rehabilitate patients afterward.
American Cancer Society Guidelines for Breast Screening with MRI as an Adjunct to Mammography
Year: 2007

New evidence on breast Magnetic Resonance Imaging (MRI) screening has become available since the American Cancer Society (ACS) last issued guidelines for the early detection of breast cancer in 2003. A guideline panel has reviewed this evidence and developed new recommendations for women at different defined levels of risk. Screening MRI is recommended for women with an approximately 20 25% or greater lifetime risk of breast cancer, including women with a strong family history of breast or ovarian cancer and women who were treated for Hodgkin disease. There are several risk subgroups for which the available data are insufficient to recommend for or against screening, including women with a personal history of breast cancer, carcinoma in situ, atypical hyperplasia, and extremely dense breasts on mammography. Diagnostic uses of MRI were not considered to be within the scope of this review.
Diketopyrrolopyrrole Au(I) as singlet oxygen generator for enhanced tumor photodynamic and photothermal therapy
Venue: Science China Chemistry
Year: 2019

Diketopyrrolopyrrole (DPP) derivatived photosensitizers (PSs) with near infrared (NIR) absorption and good photophysical properties have drawn tremendous attention in cancer phototherapy. However, current DPP derivatives present unsatisfactory quantum yield of singlet oxygen 1 O 2 due to the large energy gap between the excited singlet and triplet states. To tackle this challenge, herein the DPP core is functionalized with triphenylphosphine Au(I) group (ThDPP Au) leading to a high 1 O 2 quantum yield of 0.65. Theoretical calculation attributes the enhancement to spin orbit coupling and population of the triplet excition upon photoexcitation. The hydrophilic ThDPP Au nanoparticals (NPs) are prepared via nano reprecipitation, which displays homogeneous size and excellent light absorption ability e =4.382x10 4 M 1 cm 1 And the ThDPP Au NPs exhibit low dark toxicity and high phototoxicity, which can effectively kill tumor cells via 1 O 2 induced mitochondrial apoptotic pathway upon irradiation. Furthermore, in vivo experiments demonstrate that ThDPP Au NPs can selective accumulation in tumor and present excellent synergistic photodynamic/photothermal therapy guided by fluorescence and photothermal dual imaging.