nils-herrmann/clean_scirepeval huggingface dataset:
Querying massive graph data: A compress and search approach

Querying graph data is a fundamental problem that witnesses an increasing interest especially for massive graph databases which come as a promising alternative to relational databases for big data modeling. In this paper, we study the problem of subgraph isomorphism search which consists to enumerate the embedding of a query graph in a data graph. The most known solutions of this NPcomplete problem are backtracking-based and result in a high computational cost when we deal with massive graph databases. We address this problem and its challenges via graph compression with modular decomposition. In our approach, subgraph isomorphism search is performed on compressed graphs without decompressing them yielding substantial reduction of the search space and consequently a significant saving in processing time as well as in storage space for the graphs. We evaluated our algorithms on nine real-word datasets. The experimental results show that our approach is efficient and scalable.
Distilling Knowledge for Search-based Structured Prediction

Many natural language processing tasks can be modeled into structured prediction and solved as a search problem. In this paper, we distill an ensemble of multiple models trained with different initialization into a single model. In addition to learning to match the ensemble’s probability output on the reference states, we also use the ensemble to explore the search space and learn from the encountered states in the exploration. Experimental results on two typical search-based structured prediction tasks – transition-based dependency parsing and neural machine translation show that distillation can effectively improve the single model’s performance and the final model achieves improvements of 1.32 in LAS and 2.65 in BLEU score on these two tasks respectively over strong baselines and it outperforms the greedy structured prediction models in previous literatures.
Adult scoliosis: prevalence, SF-36, and nutritional parameters in an elderly volunteer population.

A prospective self-assessment analysis and evaluation of nutritional and radiographic parameters in a consecutive series of healthy adult volunteers older than 60 years.



To ascertain the prevalence of adult scoliosis, assess radiographic parameters, and determine if there is a correlation with functional self-assessment in an aged volunteer population.



There exists little data studying the prevalence of scoliosis in a volunteer aged population, and correlation between deformity and self-assessment parameters.



There were 75 subjects in the study. Inclusion criteria were: age > or =60 years, no known history of scoliosis, and no prior spine surgery. Each subject answered a RAND 36-Item Health Survey questionnaire, a full-length anteroposterior standing radiographic assessment of the spine was obtained, and nutritional parameters were analyzed from blood samples. For each subject, radiographic, laboratory, and clinical data were evaluated. The study population was divided into 3 groups based on frontal plane Cobb angulation of the spine. Comparison of the RAND 36-Item Health Surveys data among groups of the volunteer population and with United States population benchmark data (age 65-74 years) was undertaken using an unpaired t test. Any correlation between radiographic, laboratory, and self-assessment data were also investigated.



The mean age of the patients in this study was 70.5 years (range 60-90). Mean Cobb angle was 17 degrees in the frontal plane. In the study group, 68% of subjects met the definition of scoliosis (Cobb angle >10 degrees). No significant correlation was noted among radiographic parameters and visual analog scale scores, albumin, lymphocytes, or transferrin levels in the study group as a whole. Prevalence of scoliosis was not significantly different between males and females (P > 0.03). The scoliosis prevalence rate of 68% found in this study reveals a rate significantly higher than reported in other studies. These findings most likely reflect the targeted selection of an elderly group. Although many patients with adult scoliosis have pain and dysfunction, there appears to be a large group (such as the volunteers in this study) that has no marked physical or social impairment.



Previous reports note a prevalence of adult scoliosis up to 32%. In this study, results indicate a scoliosis rate of 68% in a healthy adult population, with an average age of 70.5 years. This study found no significant correlations between adult scoliosis and visual analog scale scores or nutritional status in healthy, elderly volunteers.
Monocrystalline PMNN-PZT thin film ultrasonic rangefinder with 2 meter range at 1 volt drive

In this study, we successfully developed a high signal-to-noise ratio (SNR) rangefinder based on a piezoelectric micromachined ultrasonic transducer (pMUT). A monocrystalline Pb(Mn<inf>1/3</inf>, Nb<inf>2</inf>/3)O<inf>3</inf>-Pb(Zr, Ti)O<inf>3</inf> (PMnN-PZT) thin film was used because it has large figures-of-merit (FOM) for SNR due to its high piezoelectric coefficient and small relative permittivity (typical values: e<inf>31,f</inf> = −14 C/m<sup>2</sup>, ε<inf>r</inf> = 200∼300). The rangefinding ability of the monocrystalline PMnN-PZT pMUT was evaluated using a pair of the devices as transmitter and receiver. The maximum range was estimated to be over 2 m at a low actuating voltage of 1 V<inf>p-p</inf>, when 12 dB was set as the threshold SNR for reliable rangefinding. The energy consumption of the transmitter was as small as ∼55 pJ for the generation of an ultrasonic burst. This performance is suitable for rangefinding applications in consumer electronics.
Optimized Projection for Sparse Representation Based Classification

Dimensionality reduction (DR) methods have been commonly u sed as a principled way to understand the high-dimensional d at such as facial images. In this paper, we propose a new supervi sed DR method called Optimized Projection for Sparse Repres ntation based Classification (OP-SRC), which is based on the recent f ace recognition method, Sparse Representation based Class ification (SRC). SRC seeks a sparse linear combination on all the train ing data for a given query image, and make the decision by the minimal reconstruction residual. OP-SRC is designed on the decision rule of SRC, it aims to reduce the within-class reco nstruction residual and simultaneously increase the between-class re construction residual on the training data. The projection s are optimized and match well with the mechanism of SRC. Therefore, SRC perf orms well in the OP-SRC transformed space. The feasibility a nd effectiveness of the proposed method is verified on the Yale, ORL and UMIST databases with promising results.
Knowledge, attitude, and behavior among Saudis toward cancer preventive practice

To examine self-reported knowledge, attitude, and preventive practices on cancer among Saudis.



Data was collected from Saudis aged 15 years or more, who attended one of the randomly selected 20 Primary Health Centers (PHC) or the four major private hospitals located in the Riyadh region, either as patients or their escorts. The association between the variables was evaluated by the Chi square test.



The study population consisted of 618 males and 719 females. Among the female respondents 23.1% reported that they practiced breast self-examination (BSE); 14.2 and 8.1%, respectively, had clinical breast examination (CBE) and mammography. However, 10.0 and 16.1% of the females, aged 40 years and older, reported having had mammograms and CBE, respectively. The BSE performers were more educated, knew someone with cancer, and had heard of the cancer warning signal. Both educational level and 'heard of cancer warning signal' were significantly related to CBE. Cancer information was received from television / radio by 65.1% and from the physician by 29.4%. Even though 69.4% believed that cancer could be detected early, a vast majority (95.8%) felt early detection of cancer was extremely desirable and 55.1% said their participation was definite in any screening program. A majority of the respondents (92.6%) insisted on the need for physician recommendation to participate and 78.1% expected that any such program should be conducted in the existing hospitals / clinics.



Culturally sensitive health education messages should be tailored to fulfill the knowledge gap among all population strata. Saudis will benefit from partnerships between public health educators and media to speed up the dissemination of cancer information.
A Zero-Voltage Switching Full-Bridge DC--DC Converter With Capacitive Output Filter for Plug-In Hybrid Electric Vehicle Battery Charging

In this paper, a novel zero-voltage switching full-bridge converter with trailing edge pulse width modulation and capacitive output filter is presented. The target application for this study is the second stage dc-dc converter in a two stage 1.65 kW on-board charger for a plug-in hybrid electric vehicle. For this application the design objective is to achieve high efficiency and low cost in order to minimize the charger size, charging time, and the amount and the cost of electricity drawn from the utility. A detailed converter operation analysis is presented along with simulation and experimental results. In comparison to a benchmark full-bridge with an LC output filter, the proposed converter reduces the reverse recovery losses in the secondary rectifier diodes, therefore, enabling a converter switching frequency of 100 kHz. Experimental results are presented for a prototype unit converting 400 V from the input dc link to an output voltage range of 200-450 V dc at 1650 W. The prototype achieves a peak efficiency of 95.7%.
Hair Tourniquet Syndrome of Labia Minora

We present two uncommon cases of adolescent girls with hair-thread strangulation of the labia minora. The first 14-year-old girl presented with a painful pedunculated labial lump . The lesion was covered with exudate. She was examined under sedation and found a coil of long hair forming a tourniquet around a labial segment. Thread removal resulted to immediate relief from pain, and gradual return to normal appearance. Another 10-year-old girl presented with a similar labial swelling. The recent experience of the first case led us straight to the problem. A long hair-thread was found at the neck of the lesion. Hair removal resulted in settling of the pain. The labial swelling subsided in few days.
Dynamic Spectrum Tracking Using Energy and Cyclostationarity-Based Multi-Variate Non-Parametric Quickest Detection for Cognitive Radios

A novel non-parametric, multi-variate quickest detection method is proposed for cognitive radios (CRs) using both energy and cyclostationary features. The proposed approach can be used to track state dynamics of communication channels. This capability can be useful for both dynamic spectrum sharing (DSS) and future CRs, as in practice, centralized channel synchronization is unrealistic and the prior information of the statistics of channel usage is, in general, hard to obtain. The proposed multi-variate non-parametric average sample power and cyclostationarity-based quickest detection scheme is shown to achieve better performance compared to traditional energy-based schemes. We also develop a parallel on-line quickest detection/off-line change-point detection algorithm to achieve self-awareness of detection delays and false alarms for future automation. Compared to traditional energy-based quickest detection schemes, the proposed multi-variate non-parametric quickest detection scheme has comparable computational complexity. The simulated performance shows improvements in terms of small detection delays and significantly higher percentage of spectrum utilization.
Recursive Cross-Domain Face/Sketch Generation from Limited Facial Parts

We start by asking an interesting yet challenging question, “If a large proportion (e.g., more than 90% as shown in Fig. 1) of the face/sketch is missing, can a realistic whole face sketch/image still be estimated?” Existing face completion and generation methods either do not conduct domain transfer learning or can not handle large missing area. For example, the inpainting approach tends to blur the generated region when the missing area is large (i.e., more than 50%). In this paper, we exploit the potential of deep learning networks in filling large missing region (e.g., as high as 95% missing) and generating realistic faces with high-fidelity in cross domains. We propose the recursive generation by bidirectional transformation networks (rBTN) that recursively generates a whole face/sketch from a small sketch/face patch. The large missing area and the cross domain challenge make it difficult to generate satisfactory results using a unidirectional cross-domain learning structure. On the other hand, a forward and backward bidirectional learning between the face and sketch domains would enable recursive estimation of the missing region in an incremental manner  and yield appealing results. r-BTN also adopts an adversarial constraint to encourage the generation of realistic faces/sketches. Extensive experiments have been conducted to demonstrate the superior performance from r-BTN as compared to existing potential solutions.
Key global environmental impacts of genetically modified (GM) crop use 1996–2012

Against the background of increasing awareness and appreciation of issues such as global warming and the impact of mankind's activities such as agriculture on the global environment, this paper updates previous assessments of some key environmental impacts that crop biotechnology has had on global agriculture. It focuses on the environmental impacts associated with changes in pesticide use and greenhouse gas emissions arising from the use of GM crops. The adoption of the technology has reduced pesticide spraying by 503 million kg (-8.8%) and, as a result, decreased the environmental impact associated with herbicide and insecticide use on these crops (as measured by the indicator the Environmental Impact Quotient [EIQ]) by 18.7%. The technology has also facilitated a significant reduction in the release of greenhouse gas emissions from this cropping area, which, in 2012, was equivalent to removing 11.88 million cars from the roads.
1,4-Dihydropyrrolo[3,2-b]pyrroles as a Single Component Photoactive Layer: A New Paradigm for Broadband Detection.

Single component organic photodetectors capable of broadband light sensing represent a paradigm shift for designing flexible and inexpensive optoelectronic devices. The present study demonstrates the application of a new quadrupolar 1,4-dihydropyrrolo[3,2-b]pyrrole derivative with spectral sensitivity across 350-830 nm as a potential broadband organic photodetector (OPD) material. The amphoteric redox characteristics evinced from the electrochemical studies are exploited to conceptualize a single component OPD with ITO and Al as active electrodes. The photodiode showed impressive broadband photoresponse to monochromatic light sources of 365, 470, 525, 589, 623, and 830 nm. Current density-voltage (J-V) and transient photoresponse studies showed stable and reproducible performance under continuous on/off modulations. The devices operating in reverse bias at 6 V displayed broad spectral responsivity (R) and very good detectivity (D*) peaking a maximum 0.9 mA W-1 and 1.9 × 1010 Jones (at 623 nm and 500 μW cm-2) with a fast rise and decay times of 75 and 140 ms, respectively. Low dark current densities ranging from 1.8 × 10-10 Acm-2 at 1 V to 7.2 × 10-9 A cm-2 at 6 V renders an operating range to amplify the photocurrent signal, spectral responsivity, and detectivity. Interestingly, the fabricated OPDs display a self-operational mode which is rarely reported for single component organic systems.
Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications

This paper provides a study of the smart grid projects realised in Europe and presents their technological solutions with a focus on smart metering Low Voltage (LV) applications. Special attention is given to the telecommunications technologies used. For this purpose, we present the telecommunication technologies chosen by several European utilities for the accomplishment of their smart meter national roll-outs. Further on, a study is performed based on the European Smart Grid Projects, highlighting their technological options. The range of the projects analysed covers the ones including smart metering implementation as well as those in which smart metering applications play a significant role in the overall project success. The survey reveals that various topics are directly or indirectly linked to smart metering applications, like smart home/building, energy management, grid monitoring and integration of Renewable Energy Sources (RES). Therefore, the technological options that lie behind such projects are pointed out. For reasons of completeness, we also present the main characteristics of the telecommunication technologies that are found to be used in practice for the LV grid.
Analyzing the applicability of Internet of Things to the battlefield environment

As the Internet of Things (IoT) matures in commercial sectors, the promise of diverse new technologies such as data-driven applications, intelligent adaptive systems, and embedded optimized automation will be realized in every environment. An immediate research question is whether contemporary IoT concepts can be applied also to military battlefield environments and can realize benefits similar to those in industry. Military environments, especially those that depend on tactical communications, are much more challenging than commercial environments. Thus it is likely many commercial IoT architectures and technologies may not translate into the military domain and others will require additional research to enable deployment and efficient implementation. This paper investigates these issues and describes potential military operational activities that could benefit from commercial IoT technologies, including logistics, sensing/surveillance, and situation awareness. In addition, the paper lays out a roadmap for future research necessary to leverage IoT and apply it to the tactical battlefield environment.
Emotions and Personality in Personalized Services

Personalized systems traditionally used the traces of user interactions to learn the user model, which was used by sophisticated algorithms to choose the appropriate content for the user and the situation. Recently, new types of user models started to emerge, which take into account more user-centric information, such as emotions and personality. Initially, these models were conceptually interesting but of little practical value as emotions and personality were difficult to acquire. However, with the recent advancement in unobtrusive technologies for the detection of emotions and personality these models are becoming interesting both for researchers and practitioners in the domain of personalized systems. This chapter introduces the book, which aims at covering the whole spectrum of knowledge needed to research and develop emotionand personality-aware systems. The chapters cover (i) psychological theories, (ii) computational methods for the unobtrusive acquisition of emotions and personality, (iii) applications of personalized systems in recommender systems, conversational systems, music information retrieval, and e-learning, (iv) evaluation methods, and (v) privacy issues. M. Tkalčič (B) Department of Computational Perception, Johannes Kepler University, Altenbergerstrasse 69, Linz, Austria e-mail: marko.tkalcic@jku.at B. De Carolis ·M. de Gemmis Department of Computer Science, University of Bari Aldo Moro, Via E.Orabona, 4, 70125 Bari, Italy e-mail: berardina.decarolis@uniba.it M. de Gemmis e-mail: marco.degemmis@uniba.it A. Odić Outfit7 (Slovenian Subsidiary Ekipa2 D.o.o.), Ljubljana, Slovenia e-mail: ante.odic@outfit7.com A. Košir Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia e-mail: andrej.kosir@fe.uni-lj.si © Springer International Publishing Switzerland 2016 M. Tkalčič et al. (eds.), Emotions and Personality in Personalized Services, Human–Computer Interaction Series, DOI 10.1007/978-3-319-31413-6_1 3
AC 2011-609: LEARNING ROBOTICS THROUGH DEVELOPING A VIR- TUAL ROBOT SIMULATOR IN MATLAB

Due to the expensive nature of an industrial robot, not all universities are equipped with areal robots for students to operate. Learning robotics without accessing to an actual robotic system has proven to be difficult for undergraduate students. For instructors, it is also an obstacle to effectively teach fundamental robotic concepts. Virtual robot simulator has been explored by many researchers to create a virtual environment for teaching and learning. This paper presents structure of a course project which requires students to develop a virtual robot simulator. The simulator integrates concept of kinematics, inverse kinematics and controls. Results show that this approach assists and promotes better students‟ understanding of robotics.
Co-simulation on the optimization design of high-speed electromagnetic repulsion mechanism of vacuum circuit breaker

In recent years high-speed electromagnetic repulsion mechanism (ERM), which is produced based on the eddy-current effect, has been widely applied to vacuum circuit breakers. One of the challenges for the design of ERM is to improve the speed of ERM by optimization design. In this paper, a novel co-simulation model is proposed. The related electromagnetic field, mechanical field and structural field of ERM have been analyzed through co-simulation. Results show that achieving separation in a few milliseconds is possible. Besides, considering the metal plate, as a driver of frequent operation, is possible to reach its mechanic limit, the stress and the strain of it are analyzed. In addition, according to the parametric analysis, the relationship between improving speed and optimizing parameters, e.g., the turns of the coil, the structural size, the storing form of energy and the initial gap are investigated.
The Psychological Health Benefits of Accepting Negative Emotions and Thoughts: Laboratory, Diary, and Longitudinal Evidence.

Individuals differ in the degree to which they tend to habitually accept their emotions and thoughts without judging them-a process here referred to as habitual acceptance. Acceptance has been linked with greater psychological health, which we propose may be due to the role acceptance plays in negative emotional responses to stressors: acceptance helps keep individuals from reacting to-and thus exacerbating-their negative mental experiences. Over time, experiencing lower negative emotion should promote psychological health. To test these hypotheses, Study 1 (N = 1,003) verified that habitually accepting mental experiences broadly predicted psychological health (psychological well-being, life satisfaction, and depressive and anxiety symptoms), even when controlling for potentially related constructs (reappraisal, rumination, and other mindfulness facets including observing, describing, acting with awareness, and nonreactivity). Next, in a laboratory study (Study 2, N = 156), habitual acceptance predicted lower negative (but not positive) emotional responses to a standardized stressor. Finally, in a longitudinal design (Study 3, N = 222), acceptance predicted lower negative (but not positive) emotion experienced during daily stressors that, in turn, accounted for the link between acceptance and psychological health 6 months later. This link between acceptance and psychological health was unique to accepting mental experiences and was not observed for accepting situations. Additionally, we ruled out potential confounding effects of gender, ethnicity, socioeconomic status, and life stress severity. Overall, these results suggest that individuals who accept rather than judge their mental experiences may attain better psychological health, in part because acceptance helps them experience less negative emotion in response to stressors.