nils-herrmann/clean_scirepeval huggingface dataset:
Windows Azure Storage: a highly available cloud storage service with strong consistency

Windows Azure Storage (WAS) is a cloud storage system that provides customers the ability to store seemingly limitless amounts of data for any duration of time. WAS customers have access to their data from anywhere at any time and only pay for what they use and store. In WAS, data is stored durably using both local and geographic replication to facilitate disaster recovery. Currently, WAS storage comes in the form of Blobs (files), Tables (structured storage), and Queues (message delivery). In this paper, we describe the WAS architecture, global namespace, and data model, as well as its resource provisioning, load balancing, and replication systems.
A Complete Proof of Correctness of the Knuth-Bendix Completion Algorithm

We give in this paper a complete description of the Knuth-Bendix completion algorithm. We prove its correctness in full, isolating carefully the essential abstract notions, so that the proof may be extended to other versions and extensions of the basic algorithm. We show that it defines a semidecision algorithm for the validity problem in the equational theories for which it applies, yielding a decision procedure whenever the algorithm terminates.
Optimal learning spaces : design implications for primary schools

ii 2 for Construction and of the European Construction Technology Platform. He has produced over one hundred and seventy single volume publications, refereed papers and reports, and has made over one hundred and ten presentations in around sixteen countries. Peter has been leading the CIB initiative on Revaluing Construction for some years and part of this concerns better understanding how value from the built environment is gained by those in society. This has led to work in the area of Senses, Brain and Spaces, ie how spaces are experienced by people through their senses and interpreted by their brains. The practical application of this interest has been around school buildings and in particular how to create " optimal learning spaces ". use environmental control strategies to modify their internal environment. In January 2008, she joined SCRI as a Research Fellow. Yufan's work in SCRI is to conduct research on a variety of issues related to 'realising value in use' of the built environment. This involves the identification of international good practice, linking this to evidence from applied activities, such as the post occupant evaluations, in order to develop a stronger evidence base to better understand the characteristics of beneficial spaces for users, especially in the design and refurbishment of schools. Dr Yufan Zhang is an architect. She carried out her PhD in the School of Architecture, University of Sheffield. Her PhD work was focused on occupants' comfort and behaviour and how they Contacting SCRI If you would like to find out more of this project please contact any of the following team members: All rights reserved; no part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photopying, recording, or otherwise without prior written permission of the copyright owner. However, there is no restriction on the onward circulation of this report in electronic form provided it is transmitted in its entirety. iii Acknowledgements Many people and organisations collaborated to produce this report. Firstly we have to express our gratitude to the Manchester City Council (MCC) who understood the potential value of this work and strongly supported the study. Thanks also go to the primary schools that were involved in the post-occupancy evaluations. They took time from their very busy schedules to share information, arrange visits and review the results of the surveys. We are also grateful to …
Guillain–Barré and Miller Fisher syndromes—new diagnostic classification

Guillain–Barré syndrome (GBS) and its variant, Miller Fisher syndrome (MFS), exist as several clinical subtypes with different neurological features and presentations. Although the typical clinical features of GBS and MFS are well recognized, current classification systems do not comprehensively describe the full spectrum of either syndrome. In this Perspectives article, GBS and MFS are classified on the basis of current understanding of the common pathophysiological profiles of each disease phenotype. GBS is subclassified into classic and localized forms (for example, pharyngeal–cervical–brachial weakness and bifacial weakness with paraesthesias), and MFS is divided into incomplete (for example, acute ophthalmoparesis, acute ataxic neuropathy) and CNS subtypes (Bickerstaff brainstem encephalitis). Diagnostic criteria based on clinical characteristics are suggested for each condition. We believe this approach to be more inclusive than existing systems, and argue that it could facilitate early clinical diagnosis and initiation of appropriate immunotherapy.
Embodiment in attitudes, social perception, and emotion.

Findings in the social psychology literatures on attitudes, social perception, and emotion demonstrate that social information processing involves embodiment, where embodiment refers both to actual bodily states and to simulations of experience in the brain's modality-specific systems for perception, action, and introspection. We show that embodiment underlies social information processing when the perceiver interacts with actual social objects (online cognition) and when the perceiver represents social objects in their absence (offline cognition). Although many empirical demonstrations of social embodiment exist, no particularly compelling account of them has been offered. We propose that theories of embodied cognition, such as the Perceptual Symbol Systems (PSS) account (Barsalou, 1999), explain and integrate these findings, and that they also suggest exciting new directions for research. We compare the PSS account to a variety of related proposals and show how it addresses criticisms that have previously posed problems for the general embodiment approach.
An updated review of Parkinson's disease genetics and clinicopathological correlations.

Knowledge regarding the pathophysiological basis of Parkinson's disease (PD) has been greatly expanded over the past two decades, with extraordinary contributions from the field of genetics. However, genetic classifications became complex, difficult to follow, and at times misleading, by placing well-established monogenic forms of the disease along with others associated with risk loci, often ill characterized. The present paper summarizes the genetic, clinical, and neuropathological findings of the currently described monogenic forms of PD and also approaches the progress made in determining genetic risk factors for PD. Furthermore, the text incorporates the data into a recently proposed classification system that will hopefully bring a "user-friendly" approach to this issue. This paper also highlights a number of inconsistencies regarding classification of PD as a single, unique clinicopathological entity-in fact, in order to achieve the development of truly innovative therapies, PD should probably be regarded clinically as a "Parkinson's disease cluster", instead of a single disease. In the future, we hope that an in-depth and groundbreaking understanding of PD will allow the development of truly disease-modifying therapies that will target the molecular processes responsible for the cascade of pathological events underlying each form of PD.
Prokaryotic evolution in light of gene transfer.

Accumulating prokaryotic gene and genome sequences reveal that the exchange of genetic information through both homology-dependent recombination and horizontal (lateral) gene transfer (HGT) is far more important, in quantity and quality, than hitherto imagined. The traditional view, that prokaryotic evolution can be understood primarily in terms of clonal divergence and periodic selection, must be augmented to embrace gene exchange as a creative force, itself responsible for much of the pattern of similarities and differences we see between prokaryotic microbes. Rather than replacing periodic selection on genetic diversity, gene loss, and other chromosomal alterations as important players in adaptive evolution, gene exchange acts in concert with these processes to provide a rich explanatory paradigm-some of whose implications we explore here. In particular, we discuss (1) the role of recombination and HGT in giving phenotypic "coherence" to prokaryotic taxa at all levels of inclusiveness, (2) the implications of these processes for the reconstruction and meaning of "phylogeny," and (3) new views of prokaryotic adaptation and diversification based on gene acquisition and exchange.
IoT solutions for smart cities

The concept of Smart City IoTisa comprehensive and layered framework that caters to the needs of multiple facets of projects related to smart city and thus allowing cities to utilise urban networking in order to increase economic prowess, and build more efficient, unique technological solutions to deal with the numerous challenges of the city. Smart City is the product of advanced development of the new era of information technology and smart economy, based on the mesh networking of the Internet, telecommunications network, broadcast network, wireless networking and other end-to-end sensor networking where Internet of Things technology (IoT) as its heart. The Internet of Things is modular approach to integrate sensors (RFID, IR, GPS, laser scanners, etc.) Into everyday objects, and inter connecting them over the internet through specific protocols for exchange of information and communications, which leads to achieving intelligent recognition, location tracking, monitoring and management. Along with the technological support from IoT, smart cities quintessentially need to conquer three features of being; instrumented, interconnected and intelligent. A Smart City can only be formed by interconnecting all of these intelligent features at their advanced stage of IOT development. The objective of this paper is how Internet and Sensors can help to develop a city to smart.
RealPigment: paint compositing by example

The color of composited pigments in digital painting is generally computed one of two ways: either alpha blending in RGB, or the Kubelka-Munk equation (KM). The former fails to reproduce paint like appearances, while the latter is difficult to use. We present a data-driven pigment model that reproduces arbitrary compositing behavior by interpolating sparse samples in a high dimensional space. The input is an of a color chart, which provides the composition samples. We propose two different prediction algorithms, one doing simple interpolation using radial basis functions (RBF), and another that trains a parametric model based on the KM equation to compute novel values. We show that RBF is able to reproduce arbitrary compositing behaviors, even non-paint-like such as additive blending, while KM compositing is more robust to acquisition noise and can generalize results over a broader range of values.
Community Similarity Networks

Sensor-enabled smartphones are opening a new frontier in the development of mobile sensing applications. The recognition of human activities and context from sensor data using classification models underpins these emerging applications. However, conventional approaches to training classifiers struggle to cope with the diverse user populations routinely found in large-scale popular mobile applications. Differences between users (e.g., age, sex, behavioral patterns, lifestyle) confuse classifiers, which assume everyone is the same. To address this, we propose Community Similarity Networks (CSN), which incorporates inter-person similarity measurements into the classifier training process. Under CSN, every user has a unique classifier that is tuned to their own characteristics. CSN exploits crowd-sourced sensor data to personalize classifiers with data contributed from other similar users. This process is guided by similarity networks that measure different dimensions of inter-person similarity. Our experiments show CSN outperforms existing approaches to classifier training under the presence of population diversity.
A case study of mobile robot's energy consumption and conservation techniques

Mobile robots are used in many applications, such as carpet cleaning, pickup and delivery, search and rescue, and entertainment. Energy limitation is one of the most important challenges for mobile robots. Most existing studies on mobile robots focus on motion planning to reduce motion power. However, motion is not the only power consumer. In this paper, we present a case study of a mobile robot called Pioneer 3DX. We analyze the energy consumers. We build power models for motion, sonar sensing and control based on experimental results. The results show that motion consume less than 50% power on average. Therefore, it is important to consider the other components in energy-efficient designs. We introduce two energy-conservation techniques: dynamic power management and real-time scheduling. We provide several examples showing how these techniques can be applied to robots. These techniques together with motion planning provide greater opportunities to achieve better energy efficiency for mobile robots. Although our study is based on a specific robot, the approach can be applied to other types of robots
An Archive of Their Own: A Case Study of Feminist HCI and Values in Design

Rarely are computing systems developed entirely by members of the communities they serve, particularly when that community is underrepresented in computing. Archive of Our Own (AO3), a fan fiction archive with nearly 750,000 users and over 2 million individual works, was designed and coded primarily by women to meet the needs of the online fandom community. Their design decisions were informed by existing values and norms around issues such as accessibility, inclusivity, and identity. We conducted interviews with 28 users and developers, and with this data we detail the history and design of AO3 using the framework of feminist HCI and focusing on the successful incorporation of values into design. We conclude with considering examples of complexity in values in design work: the use of design to mitigate tensions in values and to influence value formation or change.
STREAMER: A distributed framework for incremental closeness centrality computation

Networks are commonly used to model the traffic patterns, social interactions, or web pages. The nodes in a network do not possess the same characteristics: some nodes are naturally more connected and some nodes can be more important. Closeness centrality (CC) is a global metric that quantifies how important is a given node in the network. When the network is dynamic and keeps changing, the relative importance of the nodes also changes. The best known algorithm to compute the CC scores makes it impractical to recompute them from scratch after each modification. In this paper, we propose Streamer, a distributed memory framework for incrementally maintaining the closeness centrality scores of a network upon changes. It leverages pipelined and replicated parallelism and takes NUMA effects into account. It speeds up the maintenance of the CC of a real graph with 916K vertices and 4.3M edges by a factor of 497 using a 64 nodes cluster.
An Enterprise Ontology-Based Database for Continuous Monitoring Application

Sometimes information systems fail or have operational and communication problems because designers may not have knowledge of the domain which is intended to be modeled. The same happens with systems for monitoring. Thus, an ontological model is needed to represent the organizational domain, which is intended to be monitored in order to develop an effective monitoring system. In this way, the purpose of the paper is to present a database based on Enterprise Ontology, which represents and specifies organizational transactions, aiming to be a repository of references or models of organizational transaction executions. Therefore, this database intends to be a generic risk profiles repository of organizational transactions for monitoring applications. Moreover, the Risk Profiles Repository presented in this paper is an innovative vision about continuous monitoring and has demonstrated to be a powerful tool for technological representations of organizational transactions and processes in compliance with the formalisms of a business ontological model.
A Survey on the Reading Habits among Colleges of Education Students in the Information Age

Reading is the gateway to success in education. It is the heartbeat of all courses offered in institutions. It is therefore crucial to investigate Colleges of Education students reading habits and how to improve the skill. The study was a descriptive survey with a validated questionnaire on “Reading Habits among Colleges of Education students in the Information Age” (RHCESIA). A total number of two hundred (200) students were used from the two Colleges of Education in Oyo town, with gender and age as the moderating variables. The findings showed that almost all the respondents understand the importance of reading. 65.5% love to read from their various fields of specialization on a daily basis while 25.0% love reading from their fields of specialization every week. The study confirmed that good reading habits enhance academic performance. The study recommended that courses on communication skills should be included for the first year (100 level) students and prose work and fiction such as novels should be a compulsory course for second year students (200 level)
Hierarchical power management for asymmetric multi-core in dark silicon era

Asymmetric multi-core architectures integrating cores with diverse power-performance characteristics is emerging as a promising alternative in the dark silicon era where only a fraction of the cores on chip can be powered on due to thermal limits. We introduce a hierarchical power management framework for asymmetric multi-cores that builds on control theory and coordinates multiple controllers in a synergistic manner to achieve optimal power-performance efficiency while respecting the thermal design power budget. We integrate our framework within Linux and implement/evaluate it on real ARM big.LITTLE asymmetric multi-core platform.
Personalization in cultural heritage: the road travelled and the one ahead

Over the last 20 years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed.
Novel substrate integrated waveguide (SIW) type high power amplifier using microstrip-to-SIW transition

In this paper, a novel 10W substrate integrated waveguide (SIW) high power amplifier (HPA) designed with SIW matching network (MN) is presented. The SIW MN is connected with microstrip line using microstrip-to-SIW transition. An inductive metallized post in SIW is employed to realize impedance matching. At the fundamental frequency of 2.14 GHz, the impedance matching is realized by moving the position of the inductive metallized post in the SIW. Both the input and output MNs are designed with the proposed SIW-based MN concept. One SIW-based 10W HPA using GaN HEMT at 2.14 GHz is designed, fabricated, and measured. The proposed SIW-based HPA can be easily connected with any microstrip circuit with microstrip-to-SIW transition. Measured results show that the maximum power added efficiency (PAE) is 65.9 % with 39.8 dBm output power and the maximum gain is 20.1 dB with 30.9 dBm output power at 2.18 GHz. The size of the proposed SIW-based HPA is comparable with other microstrip-based PAs designed at the operating frequency.
The combination of L-theanine and caffeine improves cognitive performance and increases subjective alertness.

The non-proteinic amino acid L-theanine and caffeine, a methylxanthine derivative, are naturally occurring ingredients in tea. The present study investigated the effect of a combination of 97 mg L-theanine and 40 mg caffeine as compared to placebo treatment on cognitive performance, alertness, blood pressure, and heart rate in a sample of young adults (n = 44). Cognitive performance, self-reported mood, blood pressure, and heart rate were measured before L-theanine and caffeine administration (i.e. at baseline) and 20 min and 70 min thereafter. The combination of moderate levels of L-theanine and caffeine significantly improved accuracy during task switching and self-reported alertness (both P < 0.01) and reduced self-reported tiredness (P < 0.05). There were no significant effects on other cognitive tasks, such as visual search, choice reaction times, or mental rotation. The present results suggest that 97 mg of L-theanine in combination with 40 mg of caffeine helps to focus attention during a demanding cognitive task.
Generating Chinese Captions for Flickr 30 K Images

We trained a Multimodal Recurrent Neural Network on Flickr30K dataset with Chinese sentences. The RNN model is from Karpathy and Fei-Fei, 2015 . As Chinese sentence has no space between words, we implemented the model on Flickr30 dataset in two methods. In the first setting, we tokenized each Chinese sentence into a list of words and feed them to the RNN. While in the second one, we split each Chinese sentence into a list of characters and feed them into the same model. We compared the BLEU score achieved by our two methods to that achieved by . We found that the RNN model trained with char-level method for Chinese captions outperforms the word-level one. The former method performs very close to that trained on English captions by . This came to a conclusion that the RNN model works universally well, or at least the same, for image caption system on different languages.