nils-herrmann/clean_scirepeval huggingface dataset:
Common-Mode Suppression in Microstrip Differential Lines by Means of Complementary Split Ring Resonators: Theory and Applications

This paper is focused on the application of complementary split-ring resonators (CSRRs) to the suppression of the common (even) mode in microstrip differential transmission lines. By periodically and symmetrically etching CSRRs in the ground plane of microstrip differential lines, the common mode can be efficiently suppressed over a wide band whereas the differential signals are not affected. Throughout the paper, we present and discuss the principle for the selective common-mode suppression, the circuit model of the structure (including the models under even- and odd-mode excitation), the strategies for bandwidth enhancement of the rejected common mode, and a methodology for common-mode filter design. On the basis of the dispersion relation for the common mode, it is shown that the maximum achievable rejection bandwidth can be estimated. Finally, theory is validated by designing and measuring a differential line and a balanced bandpass filter with common-mode suppression, where double-slit CSRRs (DS-CSRRs) are used in order to enhance the common-mode rejection bandwidth. Due to the presence of DS-CSRRs, the balanced filter exhibits more than 40 dB of common-mode rejection within a 34% bandwidth around the filter pass band.
Is Seeing Belie ving ? How Recommender Interfaces Aff ect Users ’ Opinions

ABSTRA CT Recommender systemsusepeople’ s opinionsaboutitemsin an information domainto help peoplechooseother items. Thesesystemshave succeededin domainsas diverse as movies, news articles,Web pages,andwines. The psychological literatureonconformitysuggeststhatin thecourseof helpingpeoplemake choices,thesesystemsprobablyaffect users’opinionsof the items. If opinionsare influencedby recommendations, they might be lessvaluablefor making recommendations for otherusers.Further, manipulatorswho seekto makethesystemgenerateartificially highor low recommendationsmight benefitif their efforts influenceusers to changethe opinionsthey contribute to the recommender . Westudytwo aspectsof recommender systeminterfacesthat may affect users’opinions: the rating scaleandthe display of predictionsat thetime usersrateitems.We find thatusers rate fairly consistentlyacrossrating scales. Userscan be manipulated,though,tendingto rate toward the prediction thesystemshows, whetherthepredictionis accurateor not. However, userscan detectsystemsthat manipulatepredictions. We discusshow designersof recommendersystems might reactto thesefindings.
Microbial life in the phyllosphere

Our knowledge of the microbiology of the phyllosphere, or the aerial parts of plants, has historically lagged behind our knowledge of the microbiology of the rhizosphere, or the below-ground habitat of plants, particularly with respect to fundamental questions such as which microorganisms are present and what they do there. In recent years, however, this has begun to change. Cultivation-independent studies have revealed that a few bacterial phyla predominate in the phyllosphere of different plants and that plant factors are involved in shaping these phyllosphere communities, which feature specific adaptations and exhibit multipartite relationships both with host plants and among community members. Insights into the underlying structural principles of indigenous microbial phyllosphere populations will help us to develop a deeper understanding of the phyllosphere microbiota and will have applications in the promotion of plant growth and plant protection.
Person Identification in Natural Static Postures Using Kinect

Automatic person identification using un-obtrusive methods are of immense importance in the area of computer vision. Anthropometric approaches are robust to external factors including environmental illumination and obstructions due to hair, spectacles, hats or any other wearable. Recently, there have been efforts made on people identification using walking pattern of the skeleton data obtained from Kinect. In this paper we investigate the possibility of identification using static postures namely sitting and standing. Existing gait based identifications, mostly rely on the dynamics of the joints of the skeleton data. In case of static postures the motion information is not available, hence the identification mainly relies on the static distance information between the joints. Moreover, the variation of pose in a particular posture makes the identification more challenging. The proposed methodology, initially sub-divides the body-parts into static, dynamic and noisy parts followed by a combinatorial element responsible for selectively extracting features for each of those parts. Finally a radial basis function support vector machine classifier is used to perform the training and testing for the identification. Results indicate an identification accuracy of more than 97% in terms of F-score for 10 people using a dataset created with various poses of natural sitting and standing posture.
Investigating voice quality as a speaker-independent indicator of depression and PTSD

We seek to investigate voice quality characteristics, in particular on a breathy to tense dimension, as an indicator for psychological distress, i.e. depression and post-traumatic stress disorder (PTSD), within semi-structured virtual human interviews. Our evaluation identifies significant differences between the voice quality of psychologically distressed participants and not-distressed participants within this limited corpus. We investigate the capability of automatic algorithms to classify psychologically distressed speech in speaker-independent experiments. Additionally, we examine the impact of the posed questions’ affective polarity, as motivated by findings in the literature on positive stimulus attenuation and negative stimulus potentiation in emotional reactivity of psychologically distressed participants. The experiments yield promising results using standard machine learning algorithms and solely four distinct features capturing the tenseness of the speaker’s voice.
From Papercraft to Paper Mechatronics: Exploring a New Medium and Developing a Computational Design Tool

Paper Mechatronics is a novel interdisciplinary design medium, enabled by recent advances in craft technologies: the term refers to a reappraisal of traditional papercraft in combination with accessible mechanical, electronic, and computational elements. I am investigating the design space of paper mechatronics as a new hands-on medium by developing a series of examples and building a computational tool, FoldMecha, to support non-experts to design and construct their own paper mechatronics models. This paper describes how I used the tool to create two kinds of paper mechatronics models: walkers and flowers and discuss next steps.
Follow me robot using bluetooth-based position estimation

Human-Following robots are being actively researched for their immense potential to carry out mundane tasks like load carrying and monitoring of target individual through interaction and collaboration. The recent advancements in vision and sensor technologies have helped in creating more user-friendly robots that are able to coexist with humans by leveraging the sensors for human detection, human movement estimation, collision avoidance, and obstacle avoidance. But most of these sensors are suitable only for Line of Sight following of human. In the case of loss of sight of the target, most of them fail to re-acquire their target. In this paper, we are proposing a novel method to develop a human following robot using Bluetooth and Inertial Measurement Unit (IMU) on Smartphones which can work under high interference environment and can reacquire the target when lost. The proposed method leverages IMU sensors on the smartphone to estimate the direction of human movement while estimating the distance traveled from the RSSI of the Bluetooth. Thus, the Follow Me robot which estimates the position of target human and direction of heading and effectively track the person was implemented using Smartphone on a differential drive robot.
Visual search and reading tasks using ClearType and regular displays: two experiments

Two experiments comparing user performance on ClearType and Regular displays are reported. In the first, 26 participants scanned a series of spreadsheets for target information. Speed of performance was significantly faster with ClearType. In the second experiment, 25 users read two articles for meaning. Reading speed was significantly faster for ClearType. In both experiments no differences in accuracy of performance or visual fatigue scores were observed. The data also reveal substantial individual differences in performance suggesting ClearType may not be universally beneficial to information workers.
TUNING , AVO , AND FLAT-SPOT EFFECTS IN A SEISMIC ANALYSIS OF NORTH SEA BLOCK F 3

Reflection seismic data from the F3 block in the Dutch North Sea exhibits many largeamplitude reflections at shallow horizons, typically categorized as “brightspots ” (Schroot and Schuttenhelm, 2003), mainly because of their bright appearance. In most cases, these bright reflections show a significant “flatness” contrasting with local structural trends. While flatspots are often easily identified in thick reservoirs, we have often occasionally observed apparent flatspot tuning effects at fluid contacts near reservoir edges and in thin reservoir beds, while only poorly understanding them. We conclude that many of the shallow large-amplitude reflections in block F3 are dominated by flatspots, and we investigate the thin-bed tuning effects that such flatspots cause as they interact with the reflection from the reservoir’s upper boundary. There are two possible effects to be considered: (1) the “wedge-model” tuning effects of the flatspot and overlying brightspots, dimspots, or polarity-reversals; and (2) the stacking effects that result from possible inclusion of post-critical flatspot reflections in these shallow sands. We modeled the effects of these two phenomena for the particular stratigraphic sequence in block F3. Our results suggest that stacking of post-critical flatspot reflections can cause similar large-amplitude but flat reflections, in some cases even causing an interface expected to produce a ‘dimspot’ to appear as a ‘brightspot’. Analysis of NMO stretch and muting shows the likely exclusion of critical offset data in stacked output. If post-critical reflections are included in stacking, unusual results will be observed. In the North Sea case, we conclude the tuning effect was the primary reason causing for the brightness and flatness of these reflections. However, it is still important to note that care should be taken while applying muting on reflections with wide range of incidence angles and the inclusion of critical offset data may cause some spurious features in the stacked section.
K-means Algorithm Based on Particle Swarm Optimization Algorithm for Anomaly Intrusion Detection

K-means as a clustering algorithm has been studied in intrusion detection. However, with the deficiency of global search ability it is not satisfactory. Particle swarm optimization (PSO) is one of the evolutionary computation techniques based on swarm intelligence, which has high global search ability. So K-means algorithm based on PSO (PSO-KM) is proposed in this paper. Experiment over network connection records from KDD CUP 1999 data set was implemented to evaluate the proposed method. A Bayesian classifier was trained to select some fields in the data set. The experimental results clearly showed the outstanding performance of the proposed method
Validating viral marketing strategies in Twitter via agent-based social simulation

A number of marketing phenomena are too complex for conventional analytical or empirical approaches. This makes marketing a costly process of trial and error: proposing, imagining, trying in the real world, and seeing results. Alternatively, Agent-based Social Simulation (ABSS) is becoming the most popular approach to model and study these phenomena. This research paradigm allows modeling a virtual market to: design, understand, and evaluate marketing hypotheses before taking them to the real world. However, there are shortcomings in the specialized literature such as the lack of methods, data, and implemented tools to deploy a realistic virtual market with ABSS. To advance the state of the art in this complex and interesting problem, this paper is a seven-fold contribution based on a (1) method to design and validate viral marketing strategies in Twitter by ABSS. The method is illustrated with the widely studied problem of rumor diffusion in social networks. After (2) an extensive review of the related works for this problem, (3) an innovative spread model is proposed which rests on the exploratory data analysis of two different rumor datasets in Twitter. Besides, (4) new strategies are proposed to control malicious gossips. (5) The experimental results validate the realism of this new propagation model with the datasets and (6) the strategies performance is evaluated over this model. (7) Finally, the article is complemented by a free and open-source simulator.
The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist.
Categorizing Health Outcomes and Efficacy of mHealth Apps for Persons With Cognitive Impairment: A Systematic Review

Use of mobile health (mHealth) apps is growing at an exponential rate in the United States and around the world. Mild cognitive impairment (MCI), Alzheimer disease, and related dementias are a global health problem. Numerous mHealth interventions exist for this population, yet the effect of these interventions on health has not been systematically described.



The aim of this study is to catalog the types of health outcomes used to measure effectiveness of mHealth interventions and assess which mHealth interventions have been shown to improve the health of persons with MCI, Alzheimer disease, and dementia.



We searched 13 databases, including Ovid MEDLINE, PubMed, EMBASE, the full Cochrane Library, CINAHL, PsycINFO, Ei Compendex, IEEE Xplore, Applied Science & Technology Source, Scopus, Web of Science, ClinicalTrials.gov, and Google Scholar from inception through May 2017 for mHealth studies involving persons with cognitive impairment that were evaluated using at least one quantitative health outcome.  A hand search of JMIR Publications journals was also completed in July 2017.



After removal of duplicates, our initial search returned 3955 records. Of these articles, 24 met final inclusion criteria as studies involving mHealth interventions that measured at least one quantitative health outcome for persons with MCI, Alzheimer disease, and dementia. Common quantitative health outcomes included cognition, function, mood, and quality of life. We found that 21.2% (101/476) of the fully reviewed articles were excluded because of a lack of health outcomes. The health outcomes selected were observed to be inconsistent between studies. For those studies with quantitative health outcomes, more than half (58%) reported postintervention improvements in outcomes.



Results showed that many mHealth app interventions targeting those with cognitive impairment lack quantitative health outcomes as a part of their evaluation process and that there is a lack of consensus as to which outcomes to use. The majority of mHealth app interventions that incorporated health outcomes into their evaluation noted improvements in the health of persons with MCI, Alzheimer disease, and dementia. However, these studies were of low quality, leading to a grade C level of evidence. Clarification of the benefits of mHealth interventions for people with cognitive impairment requires more randomized controlled trials, larger numbers of participants, and trial designs that minimize bias.
Toward on-chip acceleration of the backpropagation algorithm using nonvolatile memory

By performing computation at the location of data, non-Von Neumann (VN) computing should provide power and speed benefits over conventional (e.g., VN-based) approaches to data-centric workloads such as deep learning. For the on-chip training of largescale deep neural networks using nonvolatile memory (NVM) based synapses, success will require performance levels (e.g., deep neural network classification accuracies) that are competitive with conventional approaches despite the inherent imperfections of such NVM devices, and will also require massively parallel yet low-power read and write access. In this paper, we focus on the latter requirement, and outline the engineering tradeoffs in performing parallel reads and writes to large arrays of NVM devices to implement this acceleration through what is, at least locally, analog computing. We address how the circuit requirements for this new neuromorphic computing approach are somewhat reminiscent of, yet significantly different from, the well-known requirements found in conventional memory applications. We discuss tradeoffs that can influence both the effective acceleration factor (“speed”) and power requirements of such on-chip learning accelerators. P. Narayanan A. Fumarola L. L. Sanches K. Hosokawa S. C. Lewis R. M. Shelby G. W. Burr
A database for microphone array experimentation.

Example of phase correlation between two microphones. The peak of this function indicates the inter-channel delay. index associated with peak value of f(t). This delay estimator is computationally convenient and more robust to noise and reverberation than other approaches based on cross-correlation or adaptive ltering. In ideal conditions, the output of Equation (5) is a delta function centered on the correct delay. In real applications with a wide band signal, e.g., a speech signal, the outcome is not a perfect delta function. Rather it resembles a correlation function of a random process. The time index associated with the maximum value of the output of Equation (5) provides an estimation of the delay. The system can produce wrong answers when two or more peaks of similar amplitude are present, i.e., in highly reverber-ant conditions. The resolution in delay estimation is limited in discrete systems by the sampling frequency. In order to increase the accuracy, oversampling can be applied in the neighborhood of the peak, to achieve sub-sample precision. Fig. 3 demonstrates an example of the result of a cross-power spectrum time delay estimator. Once the relative delays associated with all considered microphone pairs are known, the source position (x s ; y s) is estimated as the point that would produce the most similar delay values to the observed ones. This optimization is performed by a downhill sim-plex algorithm 6] applied to minimize the Euclidean distance between M observed delays ^ i and the corresponding M theoretical delays i : An analysis of the impulse responses associated with all the microphones, given an acoustic source emitting at a speciic position, has shown that constructive interference phenomena occur in the presence of signiicant reverberation. In some cases, the direct wavefront happens to be weaker than a coincidence of reeections, inducing a wrong estimation of the arrival direction and leading to an incorrect result. Selecting only microphone pairs that show the highest peaks of phase correlation generally alleviates this problem. Location results obtained with this strategy show comparable performance (mean posi-Reverb. Time Average Error 10 mic pairs 4 mic pairs 0.1sec 38.4 cm 29.8 cm 0.6sec 51.3 cm 32.1 cm 1.7sec 105.0 cm 46.4 cm Table 1: Average location error using either all 10 pairs or 4 pairs of microphones. Three reverberation time conditions are considered. tion error of about 0.3 m) at reverberation times of 0.1 s and 0.6 s. …
Communication intervention for individuals with Down syndrome: Systematic review and meta-analysis.

A systematic review was conducted to identify effective intervention strategies for communication in individuals with Down syndrome.



We updated and extended previous reviews by examining: (1) participant characteristics; (2) study characteristics; (3) characteristics of effective interventions (e.g., strategies and intensity); (4) whether interventions are tailored to the Down syndrome behavior phenotype; and (5) the effectiveness (i.e., percentage nonoverlapping data and Cohen's d) of interventions.



Thirty-seven studies met inclusion criteria. The majority of studies used behavior analytic strategies and produced moderate gains in communication targets. Few interventions were tailored to the needs of the Down syndrome behavior phenotype.



The results suggest that behavior analytic strategies are a promising approach, and future research should focus on replicating the effects of these interventions with greater methodological rigor.
Leukotrienes: mediators of immediate hypersensitivity reactions and inflammation.

Arachidonic acid plays a central role in a biological control system where such oxygenated derivatives as prostaglandins, thromboxanes, and leukotrienes are mediators. The leukotrienes are formed by transformation of arachidonic acid into an unstable epoxide intermediate, leukotriene A4, which can be converted enzymatically by hydration to leukotriene B4, and by addition of glutathione to leukotriene C4. This last compound is metabolized to leukotrienes D4 and E4 by successive elimination of a gamma-glutamyl residue and glycine. Slow-reacting substance of anaphylaxis consists of leukotrienes C4, D4, and E4. The cysteinyl-containing leukotrienes are potent bronchoconstrictors, increase vascular permeability in postcapillary venules, and stimulate mucus secretion. Leukotriene B4 causes adhesion and chemotactic movement of leukocytes and stimulates aggregation, enzyme release, and generation of superoxide in neutrophils. Leukotrienes C4, D4, and E4, which are released from the lung tissue of asthmatic subjects exposed to specific allergens, seem to play a pathophysiological role in immediate hypersensitivity reactions. These leukotrienes, as well as leukotriene B4, have pro-inflammatory effects.