nils-herrmann/clean_scirepeval huggingface dataset:
Smart Contract Derivatives
Venue: IACR Cryptol. ePrint Arch.
Year: 2020

The abilities of smart contracts today are confined to reading from their own state. It is useful for a smart contract to be able to react to events and read the state of other smart contracts. In this paper, we devise a mechanism by which a derivative smart contract can read data, observe the state evolution, and react to events that take place in one or more underlying smart contracts of its choice. Our mechanism works even if the underlying smart contract is not designed to operate with the derivative smart contract. Like in traditional finance, derivatives derive their value (and more generally state) through potentially complex dependencies. We show how derivative smart contracts can be deployed in practice on the Ethereum blockchain without any forks or additional assumptions. We leverage any NIPoPoWs mechanism (such as FlyClient or superblocks) to obtain succinct proofs for arbitrary events, making proving them inexpensive for users. The latter construction is of particular interest, as it forms the first introspective SPV client: an SPV client for Ethereum in Ethereum. Last, we describe applications of smart contract derivatives which were not possible prior to our work, in particular the ability to create decentralized insurance smart contracts which insure an underlying on chain security such as an ICO, as well as futures and options.
Asymmetric porous cordierite ceramic membranes prepared by phase inversion tape casting and their desalination performance
Year: 2020

Asymmetric porous cordierite ceramic membranes were fabricated by phase inversion tape casting method. It is shown that the membranes consist of a relatively dense skin layer on the top, a sponge layer at the bottom and a finger like layer in the middle. The membranes have a hierarchical pore structure, where macrovoids (denoted as dozens micron sized (DMS) pores) are present in the finger like layer and micron sized (MS) pores are located in the skin layer, sponge layer and the wall of macrovoids. After surface silylation by post grafting with 1H,1H,2H,2H perfluorodecyltriethoxysilane (FAS) the sample with a starting powder/polyethersulfone (PESf) weight ratio of 9 (M 4) becomes hydrophobic, with a water contact angle of 150deg. At a NaCl concentration of 3.5 wt% a feed rate of 18L/h and a feed temperature of 80 degC, the hydrophobic M 4 membrane exhibits a water permeate flux of 22.33 kg/m2h, which is considerably larger than that of the membranes prepared by dry pressing method previously, and a salt rejection of 99.9% The higher water permeate flux is attributed to the much lower transport resistance of water vapor in the membranes of the present work.
Workflow and Metadata Quality at Springer Nature
Year: 2019

Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in online libraries. For this reason, Springer Nature, the world's largest academic book publisher, has traditionally entrusted this task to their most expert editors. These editors manually analyse all new books, possibly including hundreds of chapters, and produce a list of the most relevant topics. Hence, this process has traditionally been very expensive, time consuming, and confined to a few senior editors. For these reasons, back in 2016 we developed Smart Topic Miner (STM) an ontology driven application that assists the Springer Nature editorial team in annotating the volumes of all books covering conference proceedings in Computer Science. Since then STM has been regularly used by editors in Germany, China, Brazil, India, and Japan, for a total of about 800 volumes per year. Over the past three years the initial prototype has iteratively evolved in response to feedback from the users and evolving requirements. In this paper we present the most recent version of the tool and describe the evolution of the system over the years, the key lessons learnt, and the impact on the Springer Nature workflow. In particular, our solution has drastically reduced the time needed to annotate proceedings and significantly improved their discoverability, resulting in 9.3 million additional downloads. We also present a user study involving 9 editors, which yielded excellent results in term of usability, and report an evaluation of the new topic classifier used by STM, which outperforms previous versions in recall and F measure.
Simplified Multicast Forwarding
Venue: RFC
Year: 2012

This document describes a Simplified Multicast Forwarding (SMF) mechanism that provides basic Internet Protocol (IP) multicast forwarding suitable for limited wireless mesh and mobile ad hoc network (MANET) use. It is mainly applicable in situations where efficient flooding represents an acceptable engineering design trade off. It defines techniques for multicast duplicate packet detection (DPD) to be applied in the forwarding process, for both IPv4 and IPv6 protocol use. This document also specifies optional mechanisms for using reduced relay sets to achieve more efficient multicast data distribution within a mesh topology as compared to Classic Flooding. Interactions with other protocols, such as use of information provided by concurrently running unicast routing protocols or interaction with other multicast protocols, as well as multiple deployment approaches are also described. Distributed algorithms for selecting reduced relay sets and related discussion are provided in the appendices. Basic issues relating to the operation of multicast MANET border routers are discussed, but ongoing work remains in this area and is beyond the scope of this document. This document defines an Experimental Protocol for the Internet community.
Stapes Surgery in Far Advanced Otosclerosis.
Venue: Ear, nose, throat journal
Year: 2021

Surgical treatment of patients with far advanced otosclerosis (FAO) has not yet been standardized. Patients with FAO are the candidates for stapes surgery or cochlear implant (CI) Although many surgeons consider stapes surgery as the first choice, other authors prefer CI because of the excellent hearing results.  The authors discuss their experience in the treatment of patients with FAO, potentially candidates for CI, who underwent stapedotomy.  Eleven adult patients with FAO underwent stapedotomy from 2006 to 2016. Pure tone average (PTA) between 0.5 1 2 3 kHz and speech perception test with hearing aids were determined before and after stapedotomy.  The results show a statistically significant improvement in air condition threshold (PTA) and satisfactory results with regard to speech recognition in 9 (81.8% cases. Postoperative results are not influenced by the type of stapedotomy prosthesis employed and do not change during follow up (3 years)  The authors suggest first performing stapes surgery in patients with FAO and reserving CI in case of failure.
Application Analysis of Cyber Marketing in Real Estate
Year: 2016

Cyber marketing is an important part of real estate E commerce. Compared with the traditional model, it has many advantages. Through internet, the enterprise can perform a variety of marketing activities and communicate with the scattered consumer more interactively with large amount of information and lower cost. The application of cyber marketing in real estate mostly concentrates market survey, market segmentation and targeting, product promotion, and so on. However, there are still some problems. Security of network transactions is difficult to guarantee. Authenticity of network information is being questioned and there is a contradiction between virtual network and reality. To improve the effectiveness of cyber marketing, it is important to protect the customer's information security and innovate upon marketing methods.
The influence of executive functions on phonological awareness skills in 2nd year schools
Year: 2020

The aim of this study is to analyze the influence of executive function on the performance of phonological awareness skills tasks of children in the second grade of elementary school in two schools of municipal public school. 18 children aged 7 years of both genders, enrolled in the second grade of public elementary school, participated in the study. Evaluations of executive functions and phonological awareness were performed. Pearson correlation statistic and Fischer's exact test were used, with significance level p <0.05. The results do not indicate the existence of a positive correlation between the variables. In addition to no statistical difference for any of the variables in relation to gender. The study can analyze that the executive function does not seem to be a variable that, in isolation, influences the phonological awareness abilities for the studied school range.
Effect of Yoga Based Cardiac Rehabilitation on Heart Rate Variability: Randomized Controlled Trial in Patients Post MI.
Venue: International journal of yoga therapy
Year: 2019

Autonomic dysfunction is an independent predictor of cardiovascular and all cause mortality after myocardial infarction (MI) We tested the effects of a 12 week yoga based cardiac rehabilitation program on heart rate variability (HRV) in 80 patients post MI. This randomized controlled trial with two parallel groups was carried out in a tertiary care institution in India. The yoga group received 13 hospital based structured yoga sessions as an adjunct to standard care. Control group participants received enhanced standard care involving three brief educational sessions with a leaflet on the importance of diet and physical activity. HRV was measured in all participants with lead II electrocardiogram (ECG) signals. One yoga group patient's data were excluded due to ECG abnormalities. Baseline measurement was done 3 weeks post MI, and postintervention assessment took place at the 13th week. HRV frequency and time domain indices were analyzed. There were no significant between group differences in the HRV time domain indices. Frequency domain indices showed significant between group differences in HF power (absolute) (yoga vs. control: 114.42 794.80 7,993.78] vs. 38.14 4,843.50 1,617.87] p 0.005) and total power (nu) (yoga vs. control: 44.96 [21.94] vs. 19.55 [15.42] p 0.01) with higher HF power and total power (nu) in the yoga group. It should be noted that these results cannot be generalized to high risk patients. Respiratory frequency control to check for influence of respiratory rate on RR interval was not evaluated. This short term yoga based cardiac rehabilitation program had additive effects in shifting sympathovagal balance toward parasympathetic predominance while increasing overall HRV in optimally medicated post MI patients.
Global Optimal Structured Embedding Learning for Remote Sensing Image Retrieval
Venue: Sensors
Year: 2020

A rich line of works focus on designing elegant loss functions under the deep metric learning (DML) paradigm to learn a discriminative embedding space for remote sensing image retrieval (RSIR) Essentially, such embedding space could efficiently distinguish deep feature descriptors. So far, most existing losses used in RSIR are based on triplets, which have disadvantages of local optimization, slow convergence and insufficient use of similarity structure in a mini batch. In this paper, we present a novel DML method named as global optimal structured loss to deal with the limitation of triplet loss. To be specific, we use a softmax function rather than a hinge function in our novel loss to realize global optimization. In addition, we present a novel optimal structured loss, which globally learn an efficient deep embedding space with mined informative sample pairs to force the positive pairs within a limitation and push the negative ones far away from a given boundary. We have conducted extensive experiments on four public remote sensing datasets and the results show that the proposed global optimal structured loss with pairs mining scheme achieves the state of the art performance compared with the baselines.
Inter Rater Reliability and Concurrent Validity of the Preschool Play Scale with Preschool Children with Autism Spectrum Disorders
Year: 2010

This study examined whether the Revised Knox Preschool Play Scale (PPS R) was reliable and valid for use in assessing play behavior of preschoolers with autism spectrum disorder (ASD) Inter rater reliability of the PPS R was investigated. Comparing scores on the Vineland Adaptive Behavior Scales (VABS) on 61 children determined concurrent validity of the PPS R. Intraclass Correlation and Spearman's Rank Order Correlation coefficients revealed the PPS R had high inter rater reliability (r .94) and correlated significantly (r .52, p< .01) with the total score of the VABS, respectively. Results support the PPS R is a reliable and valid measurement of play behavior for preschoolers with ASD.
A Compact Decoupling Structure Applied in MIMO Antennas for Wideband Radar Applications
Venue: 2020 International Conference on Green and Human Information Technology (ICGHIT)
Year: 2020

In this paper, a novel decoupling structure is proposed to depress mutual coupling among closely spaced elements of MIMO antenna, for the distance of 0.1457 lamda. Basing on gradient line, the proposed design has reduced mutual coupling in a wide range of frequency, for over 800MHz around 9.5GHz, the conventional operating frequency of radar application. The proposed structure was analyzed using equivalent circuit and applied in MIMO and array antenna designs to reduce mutual coupling and distortion of radiation pattern. The measured results were also presented and are agreed well with simulated ones.
MVC Net: A Convolutional Neural Network Architecture for Manifold Valued Images With Applications
Venue: ArXiv
Year: 2020

Geometric deep learning has attracted significant attention in recent years, in part due to the availability of exotic data types for which traditional neural network architectures are not well suited. Our goal in this paper is to generalize convolutional neural networks (CNN) to the manifold valued image case which arises commonly in medical imaging and computer vision applications. Explicitly, the input data to the network is an image where each pixel value is a sample from a Riemannian manifold. To achieve this goal, we must generalize the basic building block of traditional CNN architectures, namely, the weighted combinations operation. To this end, we develop a tangent space combination operation which is used to define a convolution operation on manifold valued images that we call, the Manifold Valued Convolution (MVC) We prove theoretical properties of the MVC operation, including equivariance to the action of the isometry group admitted by the manifold and characterizing when compositions of MVC layers collapse to a single layer. We present a detailed description of how to use MVC layers to build full, multi layer neural networks that operate on manifold valued images, which we call the MVC net. Further, we empirically demonstrate superior performance of the MVC nets in medical imaging and computer vision tasks.
Vehicle Detection Method Based on GhostNet SSD
Venue: 2020 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)
Year: 2020

The traditional vehicle target detection algorithm needs to select appropriate features for different image scenes, resulting in poor generalization ability. In order to solve this problem, this paper proposes an image vehicle detection method based on SSD. This method combines GhostNet and SSD to extract feature maps from GhostNet for classified and location prediction. To some extent, the detection accuracy and speed of the vehicle are improved. Experimental results show that this method has a high recognition rate and is better than the traditional algorithm.
EXTRACURRICULAR ACTIVITIES AND YOUTHFUL VIOLENCE: DIFFERENCES BY RACE/ETHNIC GROUP AND IMMIGRANT GENERATION
Year: 2012

ii Dedication iv Acknowledgments. v Vita vii List of Tables ix List of Figures xi Chapter 1: Introduction 1 Chapter 2: Family Background and Differences in Extracurricular Participation across ImmigrationGenerations..7 Chapter 3: The Role of School Extracurricular Participation on Violence Across Immigrant Generations..34 Chapter 4:Adolescent School Activity Involvement and Violence: Commonalities and Differences across Race/Ethnicity and Immigrant Minorities..67 Chapter 5: Conclusions 96
GPS signal jamming and anti jamming strategy A theoretical analysis
Year: 2016

The weak strength of GPS signal makes it very vulnerable to jamming. This calls for appropriate modeling and implementation of GPS signal source and jammers that are used to jam GPS signal. The present work describes a simple and efficient way to simulate GPS signal using MATLAB(r) with focus on investigation of GPS signal jamming and devising an anti jamming technique to counter different jamming scenarios besides Additive white Gaussian noise (AWGN) The jamming types influencing GPS Signal have been identified and suitable jamming scenarios have been modeled using MATLAB(r) The effect of each jamming signal type on GPS signal has been quantified by estimation of Bit error rate (BER) for different jamming to signal (J/S) ratio. A background study of different anti jamming techniques for GPS signal has been carried out and Turbo coding has been implemented as a suitable measure to counter the effect of GPS signal jamming.
A resource aware semantics for a focused intuitionistic calculus
Venue: Mathematical Structures in Computer Science
Year: 2017

We investigate a new computational interpretation for an intuitionistic focused sequent calculus which is compatible with a resource aware semantics. For that, we associate to Herbelin's syntax a type system based on non idempotent intersection types, together with a set of reduction rules inspired from the substitution at a distance paradigm that preserves (and decreases the size of) typing derivations. The non idempotent approach allows us to use very simple combinatorial arguments, only based on this measure decreasingness, to characterize linear head and strongly normalizing terms by means of typability. For the sake of completeness, we also study typability (and the corresponding strong normalization characterization) in the calculus obtained from the former one by projecting the explicit cuts.
Panoramic video stitching based on multi band image blending
Venue: International Conference on Graphic and Image Processing
Year: 2019

With the fast development and application of virtual reality (VR) panoramic images have been a hot research topic and been widely applied in many areas. Usually, the panoramic images are generated by image stitching with images captured by cameras set in 360 degrees. However, the image captured by the traditional fish eye lens has serious distortion. Many traditional image fusion algorithms are not suitable for this kind of images. In order to handle this problem, we propose a method based on multi band image blending to realize the real time stitching of six way fish eye video, and finally generates output video. The principle of the stitching system is to decompose the video into frames. After image alignment, multi band fusion method is used to fuse the high frequency features, which makes the degree of fusion in the image area smaller and avoids duplication in the mosaic area. Different from the convolution pyramid stitching algorithm which does not depend too much on the overlap area, the proposed algorithm retains more image details and reduces the distortion. Experimental results in terms of both subjective and objective quality show that the system can stitch panoramic video efficiently, and the output image has no stitching artifact in the overlapping area.
As escolhas temporais e a criacao de sentidos em Agua Viva, de Clarice Lispector e em duas de suas traducoes para o ingles
Year: 2018

This article is inserted into an observed gap in the academic literature, when it tries to relate translation and stylistics, by the bias of the tense choices made by Clarice Lispector in Agua Viva, and by two of her English language translators, which result in a great diversity of meanings. To that end, Celce Murcia and Larsen Freeman (1999) Yule (1998) Bechara (2004) and Castilho and Elias (2012) will be used to understand the tense and verbal aspects in English and Portuguese languages, in a discursive approach. Within literary discourse, Benveniste (1989, 1995) Maingueneau (2001) and Fiorin (2005) will ground the relations between verb tenses and the formation of meanings. Finally, Lambert and Van Gorp (1985) and Aubert (1998) will provide references for data selection and interpretation processes. It is expected, therefore, to demonstrate possible intersections between stylistic studies, starting with aspects and tenses, and studies in the area of translation.
Cross Domain Sentiment Classification With Bidirectional Contextualized Transformer Language Models
Venue: IEEE Access
Year: 2019

Cross domain sentiment classification is an important Natural Language Processing (NLP) task that aims at leveraging knowledge obtained from a source domain to train a high performance learner for sentiment classification on a target domain. Existing transfer learning methods applied on cross domain sentiment classification mostly focus on inducing a low dimensional feature representation shared across domains based on pivots and non pivots, which is still a low level representation of sequence data. Recently, there have been great progress in the NLP literature in developing high level representation language models based on Transformer architecture, which are pre trained on large text corpus and fine tuned for specific task with an additional layer on top. Among such language models, the bidirectional contextualized Transformer language models of BERT and XLNet have greatly impacted NLP research field. In this paper, we fine tune BERT and XLNet for the cross domain sentiment classification. We then explore their transferability in the context of cross domain sentiment classification through in depth analysis of two models' performances and update the state of the arts with a significant margin of improvement. Our results show that such bidirectional contextualized language models outperform the previous state of the arts methods for cross domain sentiment classification while using up to 120 times less data.