nils-herrmann/clean_scirepeval huggingface dataset:
[Poster] Interacting with your own hands in a fully immersive MR system
Venue: 2014 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
Year: 2014

This poster introduces a fully immersive Mixed Reality system we have recently developed, where the user is free to walk inside a virtual scenario while wearing a HMD. The novelty of the system lies in the fact that users can see and use their real hands by means of a Kinect like camera mounted on the HMD in order to naturally interact with the virtual objects. Our working hypothesis are that the introduction of the photorealistic capture of users' hands in a coherently rendered virtual scenario induces in them a strong feeling of presence and embodiment without the need of using a synthetic 3D modelled avatar as a representation of the self. We also argue that the users' ability of grasping and manipulating virtual objects using their own hands not only provides an intuitive interaction experience, but also improves self perception as well as the perception of the environment.
Active plasmonic band stop filters based on graphene metamaterial at THz wavelengths.
Venue: Optics express
Year: 2016

Active plasmonic band stop filters based on single and double layer doped graphene metamaterials at the THz wavelengths are proposed and investigated numerically by using the finite difference time domain (FDTD) method. The metamaterial unit cell structure is composed of two parallel graphene nanoscale ribbons. Simulated results exhibit that significant resonance wavelength shifts can be achieved with a slight variation of the doping concentration of the graphene ribbons. Besides, the asymmetry double layer graphene metamaterial device has two apparent filter dips while the symmetry single double layer and asymmetry single layer graphene metamaterial devices just only one. The metamaterials with symmetry single layer and asymmetry double layer graphene can be used as a high sensitivity refractive sensor with the sensitivity up to 5100 nm/RIU and a two circuit switch, respectively. These prospects pave the way towards ultrafast active graphene based plasmonic devices for THz applications.
Natural Dyeing of Wool by Madder (Rubia tinctorum L. Root Extract Using Tannin based Biomordants: Colorimetric, Fastness and Tensile Assay
Venue: Fibers and Polymers
Year: 2018

In this work, the natural dyeing behavior of woollen yarn with madder (Rubia tinctorum L. root extract was studied. The effects of different tannin rich plants (Rhus coriaria, Eucalyptus, Terminalia chebula, Quercus castaneifolia, Pomegranate) extract as biomordants and alum (as a chemical mordant) with two mordanting procedures (pre and metamordanting) on color characteristics of the dyed samples were also investigated. The CIEDE2000 values, color strength (K/S) washing fastness and tensile property of the mordanted and dyed samples were assessed. Visually, a range of hues from orange to brownish red were obtained. In general, pre biomordanted samples with Rhus coriaria (10 %owf) Eucalyptus (10 %owf) Terminalia chebula (5 %owf) Quercus castaneifolia (5 %owf) and Pomegranate (5 %owf) showed almost the same color difference (DE00) and wash fastness values compared to those treated with 3 %owf alum. Finally, it was concluded from the comparative studies that the biomordants have good potential to be considered as alternatives to the common chemical mordants.
Boundary conditions for traceability in food supply chains using blockchain technology
Venue: Int. J. Inf. Manag.
Year: 2020

Traceability of ingredients in food supply chains has become paramount in a world in which markets become global, heterogeneous, and complex and in which consumers expect a high level of quality. The food supply chain consists of many organizations having different interests and are often reluctant to share traceability information with each other. Blockchain has been advocated for improving traceability by providing trust. Yet, practice proved to be more stubborn. The goal of this paper is to identify boundary conditions for sharing assurance information to improve traceability. Four cases in the food supply chain have been investigated using a template analysis of 16 interviews. Eighteen boundary conditions categorized in business, regulation, quality and traceability categories have been identified. Some boundary conditions were found in all supply chains, whereas others were found to be supply chain specific. Standardization of traceability processes and interfaces, having a joint platform and independent governance were found to be key boundary conditions before blockchain can be used. Our findings imply that supply chain systems have first to be modified and organizational measures need to be taken to fulfill the boundary conditions, before blockchain can be used successfully.
Pockets of Inequality in the Distribution of U.S. Pharmacists' Wages and Salaries: A Gender Comparison
Venue: Innovations in pharmacy
Year: 2019

The literature contains conflicting arguments regarding inequalities in the distribution of U.S. pharmacists' wages and salaries and the existence of a gender earnings gap. Some authors argue that the dispersion is small compared to other professions and there is no gap; others report that after controlling for number of hours worked, human capital stock, and job related preferences, male pharmacists earn higher wages and salaries than female pharmacists.  Estimate the central tendency and spread of wages and salaries of pharmacists practicing in the U.S. compare earning levels of male and female pharmacists, and examine the pockets of inequality within each gender.  The study used self reported survey data collected from a random sample of licensed pharmacists practicing throughout the United States. The sample consisted of 375 men and 279 women. Means and standard deviations of wage and salary earnings for male and female pharmacists were estimated by age, number of hours worked, years of professional experience, marital status, type of pharmacy degree, main role as pharmacist, and type of practice site. The spread of wages and salaries within gender was analyzed using the Gini coefficient.  A total of 654 pharmacists provided answers to all relevant questions in the questionnaire (28.9% response rate) Wages and salaries of male pharmacists exceeded those of female pharmacists, but the gap was restricted to practitioners with selected characteristics older, married, with more experience, whose primary role was dispensing medications, and practicing in a hospital setting. The greatest wage and salary inequalities were observed among older pharmacists, with more years of professional experience, and whose primary role was dispensing medications. Different gender specific pockets of inequality were identified in all variables studied and all categories within these variables.  The seemingly smooth gender specific distribution of earnings in the pharmacy profession might be the result of opposing trends by different groups of practitioners that cancel each other when analyzed aggregately. By estimating the wages and salaries for selected categories of pharmacists and examining the pockets of inequality within each gender, this study shed light into recent labor market developments and will hopefully stimulate further research into the dynamics of the pharmacist workforce.
Local light field fusion
Venue: ACM Trans. Graph.
Year: 2019

We present a practical and robust deep learning solution for capturing and rendering novel views of complex real world scenes for virtual exploration. Previous approaches either require intractably dense view sampling or provide little to no guidance for how users should sample views of a scene to reliably render high quality novel views. Instead, we propose an algorithm for view synthesis from an irregular grid of sampled views that first expands each sampled view into a local light field via a multiplane image (MPI) scene representation, then renders novel views by blending adjacent local light fields. We extend traditional plenoptic sampling theory to derive a bound that specifies precisely how densely users should sample views of a given scene when using our algorithm. In practice, we apply this bound to capture and render views of real world scenes that achieve the perceptual quality of Nyquist rate view sampling while using up to 4000X fewer views. We demonstrate our approach's practicality with an augmented reality smart phone app that guides users to capture input images of a scene and viewers that enable realtime virtual exploration on desktop and mobile platforms.
A Comprehensive Survey on Aspect Based Sentiment Analysis
Venue: ArXiv
Year: 2020

Aspect Based Sentiment Analysis (ABSA) is the sub field of Natural Language Processing that deals with essentially splitting our data into aspects ad finally extracting the sentiment information. ABSA is known to provide more information about the context than general sentiment analysis. In this study, our aim is to explore the various methodologies practiced while performing ABSA, and providing a comparative study. This survey paper discusses various solutions in depth and gives a comparison between them. And is conveniently divided into sections to get a holistic view on the process.
Electrospun SnSe/C nanofibers as binder free anode for lithium ion and sodium ion batteries
Year: 2020

The design of electrodes with superior mechanical flexibility is the key to developing energy storage devices with mechanical durability and excellent electrochemical performance. Herein, a flexible SnSe/C nanofiber membrane is successfully synthesized by electrospinning technology and subsequent calcination. From the macroscopic view, the SnSe/C nanofiber membrane can tolerate a bending angle of 180deg without any breakage, indicating its superior mechanical flexibility. From the microscopic view, SnSe nanoparticles are uniformly distributed along the carbon nanofiber framework. The carbon nanofiber framework serves not only as a conductive matrix that improves the electrical conductivity of the composite, but also as a buffer material that alleviates the volume expansion during electrochemical reaction. These merits endow excellent electrochemical performance to SnSe/C nanofibers when used as a binder free and current collector free anode for lithium/sodium ion batteries. The SnSe/C nanofiber anode delivers a stable discharge capacity of 405 mAh g 1 at 1000 mA g 1 after 500 cycles in lithium ion battery and 290 mAh g 1 at 200 mA g 1 after 200 cycles in sodium ion battery. These results demonstrate that the SnSe/C nanofiber is a promising anode material for flexible lithium ion and sodium ion batteries.
Circadian control of metabolism and pathological consequences of clock perturbations.
Venue: Biochimie
Year: 2017

Most organisms have developed an autonomous time keeping system that generates self sustained daily fluctuations in behavior and physiological processes. These biological clocks are reset every day by light to adjust physiology to the day/night cycle generated by the rotation of the Earth. Clocks present in organs involved in glucose and lipid metabolism such as the liver, muscle, adipose tissue and pancreas are also reset by feeding cues which permits the local integration of systemic and nutritional signals to switch fuel production and utilization according to the feeding/fasting cycle. However, derangements in this finely tuned system can be induced by extended light exposure, 24/7 food availability and altered food intake patterns, repeated jet lag and shift working, promoting metabolic imbalances ranging from body weight gain to the development of insulin resistance and liver diseases. Here, we review recent findings on the link between the clock and metabolic fluxes to maintain whole body homeostasis, and what clock disruption in mice has revealed about the role of the clock in metabolic regulation.
Application of Music Education in Brain Cognition
Year: 2018

Neuroscience studies have revealed that music education may have a catalytic effect on brain cognition and development. Intensive music training will also intrigue educates' interests in other disciplines for comprehensive quality development. This paper analyzes the findings of domestic and foreign scholars on how music education will be correlated to cranial nerves and finally bears out that music education contributes much to brain cognition and cranial nerve development. More than that, music education plays a more powerful role in several special sensitive periods of human development process. What's the relationship between cranial nerves and bermorgen training is also analyzed herein. In a word, the unique music training mode can develop the human brain potential, activate the cerebral nerve functions to lay a foundation for the development of other skills, thus providing the clue to the reform of education in the new era.
DESENVOLVIMENTO DE UM CONTROLADOR NEURAL APLICADO EM SISTEMAS QUIMICOS MULTIVARIAVEIS.
Year: 2016

O desenvolvimento de controladores avancados representa uma promissora area de aplicacao industrial e academica. A importancia estrategica desta area de conhecimento se da na manutencao da qualidade final dos produtos obtidos e na reducao do consumo de energia. Este trabalho propoe o desenvolvimento teorico e experimental de um controlador neural aplicado em sistemas multivariaveis. Neste estudo serao selecionadas as arquiteturas adequadas ao desenvolvimento do controlador neural e estas serao testadas no sistema de fermentacao de etanol (Nagy, 2007) por simulacao e posteriormente na planta didatica de tanques acoplados (multivariavel) experimentalmente. O desempenho do controlador neural desenvolvido para cada sistema sera determinado por meio da analise dos indices baseados na integral do erro (ITAE) sob diferentes perturbacoes. Neste trabalho espera se a obtencao de subsidios experimentais para a analise do controlador neural aplicado em processos complexos nao lineares.
Automatic Gesture Recognition in Robot assisted Surgery with Reinforcement Learning and Tree Search
Venue: 2020 IEEE International Conference on Robotics and Automation (ICRA)
Year: 2020

Automatic surgical gesture recognition is fundamental for improving intelligence in robot assisted surgery, such as conducting complicated tasks of surgery surveillance and skill evaluation. However, current methods treat each frame individually and produce the outcomes without effective consideration on future information. In this paper, we propose a framework based on reinforcement learning and tree search for joint surgical gesture segmentation and classification. An agent is trained to segment and classify the surgical video in a human like manner whose direct decisions are re considered by tree search appropriately. Our proposed tree search algorithm unites the outputs from two designed neural networks, i.e. policy and value network. With the integration of complementary information from distinct models, our framework is able to achieve the better performance than baseline methods using either of the neural networks. For an overall evaluation, our developed approach consistently outperforms the existing methods on the suturing task of JIGSAWS dataset in terms of accuracy, edit score and F1 score. Our study highlights the utilization of tree search to refine actions in reinforcement learning framework for surgical robotic applications.
A Process Model of Talent Management in Structurally Ambidextrous Organisations
Venue: NHRD Network Journal
Year: 2019

In complex, volatile and unstable environments, organisations aim to effectively develop and retain their key talent to achieve sustainable advantage. Specifically, in the case of ambidextrous organisations which balance tension between exploration and exploitation, talent management (TM) becomes critical. Continuing this stream of thought, the current study explores central questions associated with the role of TM in an ambidextrous organisation. Previous literature does not address the question of how TM facilitates ambidextrous learning in organisations. This conceptual article attempts to address the gap by suggesting a process model of TM in structurally ambidextrous organisations. The process model is explored further to arrive at some key research questions. The article also discusses implications of the research for practitioners.
Therapeutic and Preventive Use of Video Games in Child and Adolescent Psychiatry: A Systematic Review
Venue: Frontiers in Psychiatry
Year: 2020

Over the past decade, the use of commercial video games and serious games has developed in child and adolescent psychiatry. These games may become relevant alternatives or adjuncts to traditional psychotherapy, providing that their effectiveness is properly established. The purpose of this literature review was to evaluate the effectiveness of serious games and commercial video games in the treatment or prevention of psychiatric disorders in children and adolescents.  Medline's database was used to search articles published between January 2012 and July 2019. The following keywords were used for this search: "Video games" OR "Active video game" OR "serious gaming" OR "Serious game" OR "Exergame" AND "Child mental disorder" OR "Adolescent" OR "Child" AND "Therapy" OR "Prevention" Only comparative studies which targeted interventions on children and adolescents suffering from psychiatric disorders were included.  Twenty two studies, focusing on a wide range of psychiatric conditions, met our inclusion criteria's: 14 evaluated serious games and 8 commercial games. All studies were randomized controlled trials but only two studies compared the intervention game to psychotherapeutic gold standard; other studies used a no intervention control group or an alternative game as the control group. Eighteen studies reported significant improvements on the symptoms and test scores targeted.  Serious games and commercially available video games can be an effective trajectory for psychotherapy in child and adolescent psychiatry. However, there is a lack of longitudinal studies which assess the sustained effects of these games, and standards for proper evaluation of their effectiveness are missing.
Meta analysis of first metatarsophalangeal joint implant arthroplasty.
Venue: The Journal of foot and ankle surgery official publication of the American College of Foot and Ankle Surgeons
Year: 2009

Management of late stage degenerative joint disease of the first metatarsophalangeal joint (MPJ) is a complex topic that is frequently the source of debate among foot and ankle surgeons. Several surgical interventions have been described to treat this condition. One of the most contested of these treatments is implant arthroplasty of the first MPJ. The primary aim of this meta analysis was to evaluate the clinical benefit of first MPJ implant arthroplasty in regard to patient satisfaction. Reviewers formally trained in meta analysis abstraction techniques searched databases and indices using medical subject heading terms and other methods to identify all relevant studies published since 1990. Initially, 3874 citations were identified and evaluated for relevance. Abstract screening produced 112 articles to be read in entirety, of which 47 articles studying 3049 procedures with a mean 61.48 (SD 45.03) month follow up met all prospective inclusion criteria necessary for analysis. Overall crude patient satisfaction following first MPJ implant arthroplasty was 85.7% (95% confidence interval: 82.5% 88.3% When adjusting for lower quality studies (retrospective, less than 5 years of follow up, higher percent of patients lost to follow up) the overall patient satisfaction increased to 94.5% (89.6% 97.2% in the highest quality studies. This adjustment also significantly decreased heterogeneity across studies (crude Q 184.6, high quality studies Q 2.053) Additional a priori sources of heterogeneity were evaluated by subgroup analysis and meta regression. In regards to patient satisfaction, this comprehensive analysis provides supportive evidence to the clinical benefit of first MPJ implant arthroplasties.
Method of Review Information Mining Based on Characteristics of Commodity Goods
Year: 2014

Product reviews presented on the Web by the customers are used to be as the feedback on products and meanwhile providing shopping experience for potential customers.However,with the increasing of commodity review information,consumers tend to be submerged in these comments.This paper presents an algorithm for product reviews mining base on opinion mining.First,we collect product reviews using crawler.Second,identify the product features which the customers mention in the view.Third,find the opinion sentences.Last,compute the emotional scores of the opinion sentences and output the emotional distribution.The aims of researching on this question are to provide consumers with more clear,more detailed evaluation to goods.
Generative Adversarial Networks and Perceptual Losses for Video Super Resolution
Venue: 2018 25th IEEE International Conference on Image Processing (ICIP)
Year: 2018

Recent research on image super resolution (SR) has shown that the use of perceptual losses such as feature space loss functions and adversarial training can greatly improve the perceptual quality of the resulting SR output. In this paper, we extend the use of these perceptual focused approaches for image SR to that of video SR. We design a 15 block residual neural network, VSRResNet, which is pre trained on a the traditional mean squared error (MSE) loss and later fine tuned with a feature space loss function in an adversarial setting. We show that our proposed system, VSRRes FeatGAN, produces super resolved frames of much higher perceptual quality than those provided by the MSE based model.
Mixing and hitting times for finite Markov chains
Year: 2012

Let $0<\alpha<1/2$ We show that that the mixing time of a continuous time Markov chain on a finite state space is about as large as the largest expected hitting time of a subset of the state space with stationary measure \geq \alpha$ Suitably modified results hold in discrete time and/or without the reversibility assumption. The key technical tool in the proof is the construction of random set $A$ such that the hitting time of $A$ is a light tailed stationary time for the chain. We note that essentially the same results were obtained independently by Peres and Sousi.
A Simple Language Model for Task Oriented Dialogue
Venue: NeurIPS
Year: 2020

Task oriented dialogue is often decomposed into three tasks: understanding user input, deciding actions, and generating a response. While such decomposition might suggest a dedicated model for each sub task, we find a simple, unified approach leads to state of the art performance on the MultiWOZ dataset. SimpleTOD is a simple approach to task oriented dialogue that uses a single causal language model trained on all sub tasks recast as a single sequence prediction problem. This allows SimpleTOD to fully leverage transfer learning from pre trained, open domain, causal language models such as GPT 2. SimpleTOD improves over the prior state of the art by 0.49 points in joint goal accuracy for dialogue state tracking. More impressively, SimpleTOD also improves the main metrics used to evaluate action decisions and response generation in an end to end setting for task oriented dialog systems: inform rate by 8.1 points, success rate by 9.7 points, and combined score by 7.2 points.