nils-herrmann/clean_scirepeval huggingface dataset:
Advantages of integrated and sustainability based assessment for metabolism based strategic planning of urban water systems.

Despite providing water-related services as the primary purpose of urban water system (UWS), all relevant activities require capital investments and operational expenditures, consume resources (e.g. materials and chemicals), and may increase negative environmental impacts (e.g. contaminant discharge, emissions to water and air). Performance assessment of such a metabolic system may require developing a holistic approach which encompasses various system elements and criteria. This paper analyses the impact of integration of UWS components on the metabolism based performance assessment for future planning using a number of intervention strategies. It also explores the importance of sustainability based criteria in the assessment of long-term planning. Two assessment approaches analysed here are: (1) planning for only water supply system (WSS) as a part of the UWS and (2) planning for an integrated UWS including potable water, stormwater, wastewater and water recycling. WaterMet(2) model is used to simulate metabolic type processes in the UWS and calculate quantitative performance indicators. The analysis is demonstrated on the problem of strategic level planning of a real-world UWS to where optional intervention strategies are applied. The resulting performance is assessed using the multiple criteria of both conventional and sustainability type; and optional intervention strategies are then ranked using the Compromise Programming method. The results obtained show that the high ranked intervention strategies in the integrated UWS are those supporting both water supply and stormwater/wastewater subsystems (e.g. rainwater harvesting and greywater recycling schemes) whilst these strategies are ranked low in the WSS and those targeting improvement of water supply components only (e.g. rehabilitation of clean water pipes and addition of new water resources) are preferred instead. Results also demonstrate that both conventional and sustainability type performance indicators are necessary for strategic planning in the UWS.
Analysis of Hashrate-Based Double Spending

Bitcoin () is the world’s first decentralized digital currency. Its main technical innovation is the use of a blockchain and hash-based proof of work to synchronize transactions and prevent double-spending the currency. While the qualitative nature of this system is well understood, there is widespread confusion about its quantitative aspects and how they relate to attack vectors and their countermeasures. In this paper we take a look at the stochastic processes underlying typical attacks and their resulting probabilities of success.
A Reference-Less Clock and Data Recovery Circuit Using Phase-Rotating Phase-Locked Loop

A reference-less half-rate digital clock and data recovery (CDR) circuit employing a phase-rotating phase-locked loop (PRPLL) as phase interpolator is presented. By implementing the proportional control in phase domain within the PRPLL, the proposed CDR decouples jitter transfer (JTRAN) bandwidth from jitter tolerance (JTOL) corner frequency, eliminates jitter peaking, and removes JTRAN dependence on bang-bang phase detector gain. Fabricated in a 90 nm CMOS process, the prototype CDR achieves error-free operation (BER <; 10-12) with PRBS data sequences ranging from PRBS7 to PRBS31. At 5 Gb/s, it consumes 13.1 mW power and achieves a recovered clock long-term jitter of 5.0 ps rms/44.0 ps pp when operating with PRBS31 input data. The measured JTRAN bandwidth is 2 MHz and JTOL corner frequency is 16 MHz. The CDR is tolerant to 110 mV pp of sinusoidal noise on the DCO supply voltage at the worst case noise frequency of 7 MHz. At 2.5 GHz, the PRPLL consumes 2.9 mW and achieves -134 dBc/Hz phase noise at 1 MHz frequency offset. The differential and integral non-linearity of its digital-to-phase transfer characteristic are within ±0.2 LSB and ±0.4 LSB, respectively.
Meshed Patch Antennas Integrated on Solar Cells

This letter presents the study of integrating meshed patch antennas directly onto the solar cells of a small satellite to save valuable surface real estate. The cover glass of the solar cell is used as the substrate for the antennas. The integrated patch antennas are designed to have sufficient optical transparency to ensure the proper functionality of the solar cells. A prototype meshed patch antenna is designed and integrated on after-market solar cells. The antenna has an optical transparency of 93%, and the measurements agree well with the design.
Web scraping technologies in an API world

Web services are the de facto standard in biomedical data integration. However, there are data integration scenarios that cannot be fully covered by Web services. A number of Web databases and tools do not support Web services, and existing Web services do not cover for all possible user data demands. As a consequence, Web data scraping, one of the oldest techniques for extracting Web contents, is still in position to offer a valid and valuable service to a wide range of bioinformatics applications, ranging from simple extraction robots to online meta-servers. This article reviews existing scraping frameworks and tools, identifying their strengths and limitations in terms of extraction capabilities. The main focus is set on showing how straightforward it is today to set up a data scraping pipeline, with minimal programming effort, and answer a number of practical needs. For exemplification purposes, we introduce a biomedical data extraction scenario where the desired data sources, well-known in clinical microbiology and similar domains, do not offer programmatic interfaces yet. Moreover, we describe the operation of WhichGenes and PathJam, two bioinformatics meta-servers that use scraping as means to cope with gene set enrichment analysis.
A practical evaluation of radio signal strength for ranging-based localization

Radio signal strength (RSS) is notorious for being a noisy signal that is difficult to use for ranging-based localization. In this study, we demonstrate that RSS can be used to localize a multi-hop sensor network, and we quantify the effects of various environmental factors on the resulting localization error. We achieve 4.1m error in a 49 node network deployed in a half-football field sized area, demonstrating that RSS localization can be a feasible alternative to solutions like GPS given the right conditions. However, we also show that this result is highly sensitive to subtle environmental factors such as the grass height, radio enclosure, and elevation of the nodes from the ground.
FFitts law: modeling finger touch with fitts' law

Fitts' law has proven to be a strong predictor of pointing performance under a wide range of conditions. However, it has been insufficient in modeling small-target acquisition with finger-touch based input on screens. We propose a dual-distribution hypothesis to interpret the distribution of the endpoints in finger touch input. We hypothesize the movement endpoint distribution as a sum of two independent normal distributions. One distribution reflects the relative precision governed by the speed-accuracy tradeoff rule in the human motor system, and the other captures the absolute precision of finger touch independent of the speed-accuracy tradeoff effect. Based on this hypothesis, we derived the FFitts model - an expansion of Fitts' law for finger touch input. We present three experiments in 1D target acquisition, 2D target acquisition and touchscreen keyboard typing tasks respectively. The results showed that FFitts law is more accurate than Fitts' law in modeling finger input on touchscreens. At 0.91 or a greater R2 value, FFitts' index of difficulty is able to account for significantly more variance than conventional Fitts' index of difficulty based on either a nominal target width or an effective target width in all the three experiments.
Smart homes and their users: a systematic analysis and key challenges

Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home—functional, instrumental, socio-technical; (2) users and the use of the smart home—prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home—hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns—privacy and control—that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified.
Computational analysis of the safe zone for the antegrade lag screw in posterior column fixation with the anterior approach in acetabular fracture: A cadaveric study.

The fluoroscopically-guided procedure of antegrade posterior lag screw in posterior column fixation through anterior approach is technique-dependent and requires an experienced surgeon. The purpose of this study was to establish the safe zone for the antegrade posterior lag screw by using computational analysis.



The virtual three-dimensional model of 178 hemi-pelvises was created from the CT data (DICOM format) by using Mimics® program, and were used to measure the safe zone of antegrade lag screw fixation on the inner table of the iliac wing, and the largest diameter of cylindrical implant inside safe zone. The central point (point A) of the cylinder was assessed and was compared with the intersection point (point B) between the linea terminalis and the anterior border of the sacroiliac articulation.



The safe zone was triangular with an average area of 670.4mm2 (range, 374.8-1084.5mm2). The largest diameter of the cylinder was a mean 7.4mm (range, 5.0-10.0mm). When height was under 156.3cm, the diameter of the cylindrical implant was smaller than 7.0mm (p<0.001, regression coefficient=0.09). The linear distance between points A and B was 32.5mm (range, 19.2-49.3mm). Point A was far enough away from the well-positioned anterior column plate to prevent collision between the two.



The safe zone was shaped like a triangle, and was large enough for multiple screws. Considering the straight-line distance between points A and B, the central screw can be fixed without overlapping with the well-positioned anterior column plate at the point between holes 2 and 3.
GUSS: Solving Collections of Data Related Models Within GAMS

In many applications, optimization of a collection of problems is required where each problem is structurally the same, but in which some or all of the data defining the instance is updated. Such models are easily specified within modern modeling systems, but have often been slow to solve due to the time needed to regenerate the instance, and the inability to use advance solution information (such as basis factorizations) from previous solves as the collection is processed. We describe a new language extension, GUSS, that gathers data from different sources/symbols to define the collection of models (called scenarios), updates a base model instance with this scenario data and solves the updated model instance and scatters the scenario results to symbols in the GAMS database. We demonstrate the utility of this approach in three applications, namely data envelopment analysis, cross validation and stochastic dual dynamic programming. The language extensions are available for general use in all versions of GAMS starting with release 23.7.
Recommendations For Streaming Data

Recommender systems have become increasingly popular in recent years because of the broader popularity of many web-enabled electronic commerce applications. However, most recommender systems today are designed in the context of an offline setting. The online setting is, however, much more challenging because the existing methods do not work very effectively for very large-scale systems. In many applications, it is desirable to provide real-time recommendations in large-scale scenarios. The main problem in applying streaming algorithms for recommendations is that the in-core storage space for memory-resident operations is quite limited. In this paper, we present a probabilistic neighborhood-based algorithm for performing recommendations in real-time. We present experimental results, which show the effectiveness of our approach in comparison to state-of-the-art methods.
Foresight: Recommending Visual Insights

Current tools for exploratory data analysis (EDA) require users to manually select data attributes, statistical computations and visual encodings. This can be daunting for large-scale, complex data. We introduce Foresight, a system that helps the user rapidly discover visual insights from large high-dimensional datasets. Formally, an “insight” is a strong manifestation of a statistical property of the data, e.g., high correlation between two attributes, high skewness or concentration about the mean of a single attribute, a strong clustering of values, and so on. For each insight type, Foresight initially presents visualizations of the top k instances in the data, based on an appropriate ranking metric. The user can then look at “nearby” insights by issuing “insight queries” containing constraints on insight strengths and data attributes. Thus the user can directly explore the space of insights, rather than the space of data dimensions and visual encodings as in other visual recommender systems. Foresight also provides “global” views of insight space to help orient the user and ensure a thorough exploration process. Furthermore, Foresight facilitates interactive exploration of large datasets through fast, approximate sketching.
Sentiment mining in WebFountain

WebFountain is a platform for very large-scale text analytics applications that allows uniform access to a wide variety of sources. It enables the deployment of a variety of document-level and corpus-level miners in a scalable manner, and feeds information that drives end-user applications through a set of hosted Web services. Sentiment (or opinion) mining is one of the most useful analyses for various end-user applications, such as reputation management. Instead of classifying the sentiment of an entire document about a subject, our sentiment miner determines sentiment of each subject reference using natural language processing techniques. In this paper, we describe the fully functional system environment and the algorithms, and report the performance of the sentiment miner. The performance of the algorithms was verified on online product review articles, and more general documents including Web pages and news articles.
The Social Impact of Natural Language Processing

Medical sciences have long since established an ethics code for experiments, to minimize the risk of harm to subjects. Natural language processing (NLP) used to involve mostly anonymous corpora, with the goal of enriching linguistic analysis, and was therefore unlikely to raise ethical concerns. As NLP becomes increasingly wide-spread and uses more data from social media, however, the situation has changed: the outcome of NLP experiments and applications can now have a direct effect on individual users’ lives. Until now, the discourse on this topic in the field has not followed the technological development, while public discourse was often focused on exaggerated dangers. This position paper tries to take back the initiative and start a discussion. We identify a number of social implications of NLP and discuss their ethical significance, as well as ways to address them.
The Past, Present, and Future for Software Architecture

It's been 10 years since David Garlan and Mary Shaw wrote their seminal book Software Architecture Perspective on an Emerging Discipline, since Maarten Boasson edited a special issue of IEEE Software on software architecture, and since the first International Software Architecture Workshop took place. What has happened over these 10 years? What have we learned? Where do we look for information? What's the community around this discipline? And where are we going from here?This article is part of a focus section on software architecture.
Problematizing cultural appropriation

Cultural appropriation in games entails the taking of knowledge, artifacts or expression from a culture and recontextualizing it within game structures. While cultural appropriation is a pervasive practice in games, little attention has been given to the ethical issues that emerge from such practices with regards to how culture is portrayed. This paper problematizes cultural appropriation in the context of a serious game for children inspired by Día de los Muertos, a Mexican festival focused on remembrance of the dead. Taking a research through design approach, we demonstrate that recontextualised cultural elements can retain their basic, original meaning. However, we also find that cultural appropriation is inevitable and its ethical implications can be far reaching. In our context, ethical concerns arose as a result of children's beliefs that death affects prominent others and their destructive ways of coping with death. We argue that revealing emergent ethical concerns is imperative before deciding how and in what way to encourage culturally authentic narratives.
Towards workload shift detection and prediction for autonomic databases

Due to the complexity of industry-scale database systems, the total cost of ownership for these systems is no longer dominated by hardware and software, but by administration expenses. Autonomic databases intend to reduce these costs by providing self-management features. Existing approaches towards this goal are supportive advisors for the database administrator and feedback control loops for online monitoring, analysis and re-configuration. But while advisors are too resource-consuming for continuous operation, feedback control loops suffer from overreaction, oscillation and interference.
 In this position paper we give a general analysis of the parameters that affect the self-management of a database. Out of these parameters, we identify that the workload has major influence on both physical design of data and DBMS configuration. Hence, we propose to employ a workload model for light-weight, continuous workload monitoring and analysis. This model can be used for the identification and prediction of significant workload shifts, which require autonomic re-configuration of the database.
Interactions between auditory and dorsal premotor cortex during synchronization to musical rhythms

When listening to music, we often spontaneously synchronize our body movements to a rhythm's beat (e.g. tapping our feet). The goals of this study were to determine how features of a rhythm such as metric structure, can facilitate motor responses, and to elucidate the neural correlates of these auditory-motor interactions using fMRI. Five variants of an isochronous rhythm were created by increasing the contrast in sound amplitude between accented and unaccented tones, progressively highlighting the rhythm's metric structure. Subjects tapped in synchrony to these rhythms, and as metric saliency increased across the five levels, louder tones evoked longer tap durations with concomitant increases in the BOLD response at auditory and dorsal premotor cortices. The functional connectivity between these regions was also modulated by the stimulus manipulation. These results show that metric organization, as manipulated via intensity accentuation, modulates motor behavior and neural responses in auditory and dorsal premotor cortex. Auditory-motor interactions may take place at these regions with the dorsal premotor cortex interfacing sensory cues with temporally organized movement.
Low-Cost Compact Circularly Polarized Directional Antenna for Universal UHF RFID Handheld Reader Applications

A low-cost compact circularly polarized (CP) directional antenna is proposed for universal ultra-high frequency (UHF) RF identification (RFID) handheld reader applications. The antenna consists of four sequentially rotated inverted-F antennas (IFAs) fed by a compact four-feed network with closed-form design formulas. A prototype is implemented by FR-4 substrates and a thick air layer for the reduction of cost. For return loss (RL) > 13 dB, 3-dB gain variation, and axial ratio (AR) , the prototype achieves the measured bandwidth of 14.9% and exhibits stable symmetrical directional radiation patterns with wide half-power beamwidth. Compared with the reported UHF RFID directional reader antennas, the proposed structure not only exhibits the largest CP bandwidth for easily covering the entire UHF RFID band but also achieves compact size of 95 ×100 ×13.6 mm3.
Image processing using quantum computing

According to the principles of quantum physics, the computing power of a quantum machine is immense compared to that of a classical one. Encouraged by this idea important applications of quantum computation to computer science have been developed (e.g. faster algorithms, secure transmissions). In this paper we investigate the implications of using quantum computing systems in the field of image processing. We consider basic gray level transformations such as image negatives, binarization, histogram computation and histogram equalization and show how these operations can be expressed using the quantum formalism. Moreover, we show how the efficient exploitation of the special properties of quantum computation leads to better performance for the proposed quantum operations as compared to the classical correspondents.
Axial Flux Segmented SRM With a Higher Number of Rotor Segments for Electric Vehicles

Motors for in-wheel electric vehicle application should have high specific torque. In addition, these motors should be rugged, insensitive to vibration, and temperature variation. Therefore, segmented rotor switched reluctance motor (SSRM) could be an attractive alternative to permanent magnet-based motors, which are being used for this application. A limitation of SSRM is that it requires full pitch winding for its operation. Since, in-wheel motors have high diameter to axial length (D/L) ratio, SSRM of these dimensions would be bulky and has high copper loss due to full pitch winding. Hence, in this paper, a novel SSRM with nonoverlapping winding is proposed. This motor is an axial flux SSRM (AFSSRM) with toroidal winding arrangement. It has single-stator, dual-rotor configuration with 12 stator poles and 16 rotor segments on each rotor disc. Design procedure for AFSSRM is developed and a flowchart describing the design algorithm is presented. A finite element method-based simulation is carried out to verify the performance of the proposed AFSSRM. In order to validate the performance of the motor, a prototype is fabricated and experimental results are presented.