nils-herrmann/clean_scirepeval huggingface dataset:
Data-driven adaptive history for image editing

Digital image editing is usually an iterative process; users repetitively perform short sequences of operations, as well as undo and redo using history navigation tools. In our collected data, undo, redo and navigation constitute about 9 percent of the total commands and consume a significant amount of user time. Unfortunately, such activities also tend to be tedious and frustrating, especially for complex projects.
 We address this crucial issue by adaptive history, a UI mechanism that groups relevant operations together to reduce user workloads. Such grouping can occur at various history granularities. We present two that have been found to be most useful. On a fine level, we group repeating commands patterns together to facilitate smart undo. On a coarse level, we segment commands history into chunks for semantic navigation. The main advantages of our approach are that it is intuitive to use and easy to integrate into any existing tools with text-based history lists. Unlike prior methods that are predominately rule based, our approach is data driven, and thus adapts better to common editing tasks which exhibit sufficient diversity and complexity that may defy predetermined rules or procedures.
 A user study showed that our system performs quantitatively better than two other baselines, and the participants also gave positive qualitative feedbacks on the system features.
Assessing the News Landscape: A Multi-Module Toolkit for Evaluating the Credibility of News

Today, journalist, information analyst, and everyday news consumers are tasked with discerning and fact-checking the news. This task has became complex due to the ever-growing number of news sources and the mixed tactics of maliciously false sources. To mitigate these problems, we introduce the The News Landscape (NELA) Toolkit: an open source toolkit for the systematic exploration of the news landscape. NELA allows users to explore the credibility of news articles using well-studied content-based markers of reliability and bias, as well as, filter and sort through article predictions based on the users own needs. In addition, NELA allows users to visualize the media landscape at different time slices using a variety of features computed at the source level. NELA is built with a modular, pipeline design, to allow researchers to add new tools to the toolkit with ease. Our demo is an early transition of automated news credibility research to assist human fact-checking efforts and increase the understanding of the news ecosystem as a whole. To use this tool, go to http://nelatoolkit.science
New dimensions in endodontic imaging: Part 2. Cone beam computed tomography.

Cone beam computed tomography (CBCT) has been specifically designed to produce undistorted three-dimensional information of the maxillofacial skeleton, including the teeth and their surrounding tissues with a significantly lower effective radiation dose compared with conventional computed tomography (CT). Periapical disease may be detected sooner using CBCT compared with periapical views and the true size, extent, nature and position of periapical and resorptive lesions can be assessed. Root fractures, root canal anatomy and the nature of the alveolar bone topography around teeth may be assessed. The aim of this paper is to review current literature on the applications and limitations of CBCT in the management of endodontic problems.
Constraint Functional Logic Programming for Origami Construction

We describe origami programming methodology based on constraint functional logic programming. The basic operations of origami are reduced to solving systems of equations which describe the geometric properties of paper folds. We developed two software components: one that provides primitives to construct, manipulate and visualize paper folds and the other that solves the systems of equations. Using these components, we illustrate computer-supported origami construction and show the significance of the constraint functional logic programming paradigm in the program development.
A Growing Long-term Episodic & Semantic Memory

The long-term memory of most connectionist systems lies entirely in the weights of the system. Since the number of weights is typically fixed, this bounds the total amount of knowledge that can be learned and stored. Though this is not normally a problem for a neural network designed for a specific task, such a bound is undesirable for a system that continually learns over an open range of domains. To address this, we describe a lifelong learning system that leverages a fast, though non-differentiable, content-addressable memory which can be exploited to encode both a long history of sequential episodic knowledge and semantic knowledge over many episodes for an unbounded number of domains. This opens the door for investigation into transfer learning, and leveraging prior knowledge that has been learned over a lifetime of experiences to new domains.
ForkBase: An Efficient Storage Engine for Blockchain and Forkable Applications

Existing data storage systems offer a wide range of functionalities to accommodate an equally diverse range of applications. However, new classes of applications have emerged, e.g., blockchain and collaborative analytics, featuring data versioning, fork semantics, tamper-evidence or any combination thereof. They present new opportunities for storage systems to efficiently support such applications by embedding the above requirements into the storage. In this paper, we present ForkBase, a storage engine designed for blockchain and forkable applications. By integrating core application properties into the storage, ForkBase not only delivers high performance but also reduces development effort. The storage manages multiversion data and supports two variants of fork semantics which enable different fork worklflows. ForkBase is fast and space efficient, due to a novel index class that supports efficient queries as well as effective detection of duplicate content across data objects, branches and versions. We demonstrate ForkBase’s performance using three applications: a blockchain platform, a wiki engine and a collaborative analytics application. We conduct extensive experimental evaluation against respective state-of-the-art solutions. The results show that ForkBase achieves superior performance while significantly lowering the development effort. PVLDB Reference Format: Sheng Wang, Tien Tuan Anh Dinh, Qian Lin, Zhongle Xie, Meihui Zhang, Qingchao Cai, Gang Chen, Beng Chin Ooi, Pingcheng Ruan.  An Efficient Storage Engine for Blockchain and Forkable Applications. PVLDB, 11(10): 1137-1150, 2018.
The sparsest solutions to Z-tensor complementarity problems

Finding the sparsest solutions to a tensor complementarity problem is generally NP-hard due to the nonconvexity and noncontinuity of the involved 0 norm. In this paper, a special type of tensor complementarity problems with Z -tensors has been considered. Under some mild conditions, we show that to pursuit the sparsest solutions is equivalent to solving polynomial programming with a linear objective function. The involved conditions guarantee the desired exact relaxation and also allow to achieve a global optimal solution to the relaxednonconvexpolynomial programming problem. Particularly, in comparison to existing exact relaxation conditions, such as RIP-type ones, our proposed conditions are easy to verify. This research was supported by the National Natural Science Foundation of China (11301022, 11431002), the State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University (RCS2014ZT20, RCS2014ZZ01), and the Hong Kong Research Grant Council (Grant No. PolyU 502111, 501212, 501913 and 15302114). B Ziyan Luo starkeynature@hotmail.com Liqun Qi liqun.qi@polyu.edu.hk Naihua Xiu nhxiu@bjtu.edu.cn 1 State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, People’s Repubic of China 2 Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, People’s Repubic of China 3 Department of Mathematics, School of Science, Beijing Jiaotong University, Beijing, People’s Repubic of China 123 Author's personal copy
Alobar holoprosencephaly associated with cebocephaly and craniosynostosis.

Cebocephaly is a very rare congenital midline facial anomaly characterized by a blind-ended single nostril and ocular hypotelorism, and is usually combined with alobar holoprosencephaly. We report here a case of alobar holoprosencephaly with cebocephaly and craniosynostosis. Chromosomal analysis revealed normal karyotyping. The facial dysmorphism was characterized by the single nostril, hypotelorism, absence of philtrum and small head girth. The failure of cleavage of the prosencephalon and the fusion of all cranial sutures except for the sagittal suture were documented by computed tomography (CT) and magnetic resonance image (MRI). Early detection by the prenatal ultrasound examination is important because of poor prognosis of alobar holoprosencephaly.
nQuery - A Natural Language Statement to SQL Query Generator

In this research, an intelligent system is designed between the user and the database system which accepts natural language input and then converts it into an SQL query. The research focuses on incorporating complex queries along with simple queries irrespective of the database. The system accommodates aggregate functions, multiple conditions in WHERE clause, advanced clauses like ORDER BY, GROUP BY and HAVING. The system handles single sentence natural language inputs, which are with respect to selected database. The research currently concentrates on MySQL database system. The natural language statement goes through various stages of Natural Language Processing like morphological, lexical, syntactic and semantic analysis resulting in SQL query formation.
Reconfigurable Software Defined Radio and Its Applications

Currently, most Software Defined Radio (SDR) related products and researches focus on analog communication and voice transmission. In this paper, we propose a SDR platform with digital data communication capability. This platform consists of Field Programmable Gate Array (FPGA) based radio hardware and open source SDR software modules. The main features include: 1) Radio Spectrum Sensing; 2) Reconfigurable Radio Modules; 3) Link for Digital Data Communication. Based on the proposed SDR platform, we could easily reconfigure its radio modules and discover the spectrum hole to achieve better communication quality. These features are important basis to accomplish Cognitive Radio (CR) technologies.
The genetical evolution of social behaviour. I.

Grounds for thinking that the model described in the previous paper can be used to support general biological principles of social evolution are briefly discussed. Two principles are presented, the first concerning the evolution of social behaviour in general and the second the evolution of social discrimination. Some tentative evidence is given. More general application of the theory in biology is then discussed, particular attention being given to cases where the indicated interpretation differs from previous views and to cases which appear anomalous. A hypothesis is outlined concerning social evolution in the Hymenoptera; but the evidence that at present exists is found somewhat contrary on certain points. Other subjects considered include warning behaviour, the evolution of distasteful properties in insects, clones of cells and clones of zooids as contrasted with other types of colonies, the confinement of parental care to true offspring in birds and insects, fights, the behaviour of parasitoid insect larvae within a host, parental care in connection with monogyny and monandry and multi-ovulate ovaries in plants in connection with wind and insect pollination.
ZHT: A Light-Weight Reliable Persistent Dynamic Scalable Zero-Hop Distributed Hash Table

This paper presents ZHT, a zero-hop distributed hash table, which has been tuned for the requirements of high-end computing systems. ZHT aims to be a building block for future distributed systems, such as parallel and distributed file systems, distributed job management systems, and parallel programming systems. The goals of ZHT are delivering high availability, good fault tolerance, high throughput, and low latencies, at extreme scales of millions of nodes. ZHT has some important properties, such as being light-weight, dynamically allowing nodes join and leave, fault tolerant through replication, persistent, scalable, and supporting unconventional operations such as append (providing lock-free concurrent key/value modifications) in addition to insert/lookup/remove. We have evaluated ZHT's performance under a variety of systems, ranging from a Linux cluster with 512-cores, to an IBM Blue Gene/P supercomputer with 160K-cores. Using micro-benchmarks, we scaled ZHT up to 32K-cores with latencies of only 1.1ms and 18M operations/sec throughput. This work provides three real systems that have integrated with ZHT, and evaluate them at modest scales. 1) ZHT was used in the FusionFS distributed file system to deliver distributed meta-data management at over 60K operations (e.g. file create) per second at 2K-core scales. 2) ZHT was used in the IStore, an information dispersal algorithm enabled distributed object storage system, to manage chunk locations, delivering more than 500 chunks/sec at 32-nodes scales. 3) ZHT was also used as a building block to MATRIX, a distributed job scheduling system, delivering 5000 jobs/sec throughputs at 2K-core scales. We compared ZHT against other distributed hash tables and key/value stores and found it offers superior performance for the features and portability it supports.
Towards Real-Time People Recognition on Aerial Imagery Using Convolutional Neural Networks

People recognition in aerial imagery is a complex problem since it involves cameras angles, which are subject to six degrees of freedom. Traditional classifiers used in pattern matching algorithms are not robust enough to deal with such issues. Thus it is necessary to use other techniques such as deep learning methods, e.g. Convolutional Neural Networks (CNN), in order to cope with such a complex problem. However, in spite of providing potentially better recognition results, deep learning methods demand greater processing time, hindering its use on on-board embedded systems of small Unmanned Aerial Vehicles (UAV). This work is a step towards real-time (and possibly on-board) people recognition on aerial imagery. We propose a new approach based on CNN for real-time people recognition on aerial images obtained from cameras attached to small UAVs. This approach combines images from a low-cost thermal camera to detect candidate objects and CNN for the classification task. We have compared our approach with two traditional pattern matching approaches: saliency map detection and cascade classifiers. The obtained results show that, by using CNN, higher rates of correct classification within 95% of precision are obtained. These results have been obtained within real-time processing of 1.08 fps in the worst case on a hardware without any GPU processing.
Accurate circuit synthesis of low-pass corrugated waveguide filters

This paper presents a synthesis method for low-pass corrugated filters in rectangular waveguide. Using this method, excellent filter dimensions can be obtained in negligible CPU times, even for a demanding set of specifications. In contrast to previous works, low-pass filters with improved power handling capabilities can be successfully synthesized. The procedure is based on a low-pass prototype able to represent the real filtering structure. First, the structure discontinuities are characterized using an electromagnetical simulator, and the retrieved data is included in the prototype model. Then, the resulting prototype is optimized to obtain a suitable ideal response. From the prototype, the structure physical dimensions are synthesized. This paper aims to show the good performance provided by the proposed method and the benefits which can be obtained from its use.
Staining of Frozen and Formalin-Fixed, Paraffin-Embedded Tissues with Metal-Labeled Antibodies for Imaging Mass Cytometry Analysis.

This unit describes protocols for labeling tissue sections using combinations of metal-tagged antibodies and an iridium-containing DNA intercalator for analysis by imaging mass cytometry. Imaging mass cytometry (IMC) allows the labeling of up to 40 individual markers simultaneously using antibody cocktails. We discuss labeling of both cryostat sections and sections from formalin-fixed, paraffin-embedded (FFPE) tissue blocks. The protocols are similar to those used for optical microscopy techniques, while allowing much higher complexity of analysis.
Base stations placement optimization in wireless networks for emergency communications

Disaster relief operations rely on the rapid deployment of wireless network architectures to provide emergency communications. Future emergency networks will consist typically of terrestrial, portable base stations and base stations on-board low altitude platforms (LAPs). The effectiveness of network deployment will depend on strategically chosen station positions. In this paper a method is presented for calculating the optimal proportion of the two station types and their optimal placement. Random scenarios and a real example from Hurricane Katrina are used for evaluation. The results confirm the strength of LAPs in terms of high bandwidth utilisation, achieved by their ability to cover wide areas, their portability and adaptability to height. When LAPs are utilized, the total required number of base stations to cover a desired area is generally lower. For large scale disasters in particular, this leads to shorter response times and the requirement of fewer resources. This goal can be achieved more easily if algorithms such as the one presented in this paper are used.
Complications and failures in removable partial dentures: a clinical evaluation.

The design of removable partial dentures (RPDs) is an important factor for good prognostication. The purpose of this study was to clarify the effectiveness of denture designs and to clarify the component that had high rates of failure and complications. A total of 91 RPDs, worn by 65 patients for 2-10 years, were assessed. Removable partial dentures were classified into four groups: telescopic dentures (TDs), ordinary clasp dentures (ODs), modified clasp dentures (MDs) and combination dentures (CDs). The failure rates of abutment teeth were the highest and those of retainers were the second highest. The failure rates of connectors were generally low, but they increased suddenly after 6 years. Complication and failure rates of denture bases and artificial teeth were generally low. Complication and failure rates of TDs were high at abutment teeth and low level at retainers. Complication and failure rates of ODs were high at retainers.
Continuous Scatterplots

Scatterplots are well established means of visualizing discrete data values with two data variables as a collection of discrete points. We aim at generalizing the concept of scatterplots to the visualization of spatially continuous input data by a continuous and dense plot. An example of a continuous input field is data defined on an n-D spatial grid with respective interpolation or reconstruction of in-between values. We propose a rigorous, accurate, and generic mathematical model of continuous scatterplots that considers an arbitrary density defined on an input field on an n-D domain and that maps this density to m-D scatterplots. Special cases are derived from this generic model and discussed in detail: scatterplots where the n-D spatial domain and the m-D data attribute domain have identical dimension, 1-D scatterplots as a way to define continuous histograms, and 2-D scatterplots of data on 3-D spatial grids. We show how continuous histograms are related to traditional discrete histograms and to the histograms of isosurface statistics. Based on the mathematical model of continuous scatterplots, respective visualization algorithms are derived, in particular for 2-D scatterplots of data from 3-D tetrahedral grids. For several visualization tasks, we show the applicability of continuous scatterplots. Since continuous scatterplots do not only sample data at grid points but interpolate data values within cells, a dense and complete visualization of the data set is achieved that scales well with increasing data set size. Especially for irregular grids with varying cell size, improved results are obtained when compared to conventional scatterplots. Therefore, continuous scatterplots are a suitable extension of a statistics visualization technique to be applied to typical data from scientific computation.
Short bowel syndrome and intestinal failure: consensus definitions and overview.

Short bowel syndrome (SBS)-associated intestinal failure is a highly disabling condition that impairs quality of life and social integration. Although the condition is not uniformly fatal, it might lead to serious, life-threatening complications. The basic goals of medical treatment are to maintain fluid, electrolyte, and nutrient balances and to make appropriate modifications in disease management to avoid side effects. Various definitions have been proposed for SBS and intestinal failure within the medical literature, but many focus on different aspects of the conditions, leading to confusion. In the past, identifying the cause of intestinal failure was of little consequence, because all patients were managed on total parenteral nutrition at home. However, with the recent development of medical therapies such as recombinant growth hormone, octreotide, and glucagon-like peptide-2 analogues and with improvements in small bowel transplantation, many patients can be made nutritionally autonomous. To evaluate the relative efficacy of these therapies, there is now a need to develop consensus definitions so that patients can be properly categorized before therapy. To this end, a group of experts on the subject was convened to develop the following new definitions: "Intestinal failure results from obstruction, dysmotility, surgical resection, congenital defect, or disease-associated loss of absorption and is characterized by the inability to maintain protein-energy, fluid, electrolyte, or micronutrient balance." "Short-bowel syndrome results from surgical resection, congenital defect, or disease-associated loss of absorption and is characterized by the inability to maintain protein-energy, fluid, electrolyte, or micronutrient balances when on a conventionally accepted, normal diet."