nils-herrmann/clean_scirepeval huggingface dataset:
Computing Visual Correspondence with Occlusions via Graph Cuts

Several new algorithms for visual correspondence based on graph cuts [6, 13, 16] have recently been developed. While these methods give very strong results in practice, they do not handle occlusions properly. Specifically, they treat the two input images asymmetrically, and they do not ensure that a pixel corresponds to at most one pixel in the other image. In this paper, we present two new methods which properly address occlusions, while preserving the advantages of graph cut algorithms. We give experimental results for stereo as well as motion, which demonstrate that our methods perform well both at detecting occlusions and computing disparities.
People needs in the urban landscape: Analysis of Landscape and Urban Planning contributions.

The articles published in Landscape and Urban Planning during the past 16 years provide valuable insights into how humans interact with outdoor urban environments. This review paper explores the wide spectrum of human dimensions and issues, or human needs, addressed by 90 of these studies. As a basis for analysis, the major themes tapped by the findings were classified into two overarching groups containing three categories each. The Nature needs, directly linked with the physical features of the environmental setting, were categorized in terms of contact with nature, aesthetic preference, and recreation and play. The role of the environment is less immediate in the Human-interaction group, which includes the issues of social interaction, citizen participation in the design process, and community identity. Most significantly, the publications offer strong support for the important role nearby natural environments play in human well-being. Urban settings that provide nature contact are valuable not only in their own right, but also for meeting other needs in a manner unique to these more natural settings. In addition, although addressed in different ways, remarkable similarities exist concerning these six people requirements across diverse cultures and political systems. Urban residents worldwide express a desire for contact with nature and each other, attractive environments, places in which to recreate and play, privacy, a more active role in the design of their community, and a sense of community identity. The studies reviewed here offer continued evidence that the design of urban landscapes strongly influences the well-being and behavior of users and nearby inhabitants.
Towards Forward-looking Online Bitrate Adaptation for DASH

Many commercial video players rely on bitrate adaptation algorithm to adapt video bitrate to dynamic network condition. To achieve a high quality of experience, bitrate adaptation algorithm is required to strike a balance between response agility and video quality stability. Existing online algorithms select bitrates according to instantaneous throughput and buffer occupancy, achieving an agile reaction to changes but inducing video quality fluctuations due to the high dynamic of reference signals. In this paper, the idea of multi-step prediction is proposed to guide a better tradeoff, and the bitrate selection is formulated as a predictive control problem. With it, a generalized predictive control based approach is developed to calculate the optimal bitrate by minimizing the cost function over a moving look-ahead horizon. Finally, the proposed algorithm is implemented on a reference video player with performance evaluations conducted using realistic bandwidth traces. Experimental results show that the multi-step predictive control adaptation algorithm can achieve zero rebuffer event and 63.3% of reduction in bitrate switch.
A Sinc Function Analogue of Chebfun

Chebfun is an established software system for computing with functions of a real variable, but its capabilities for handling functions with singularities are limited. Here an analogous system is described based on sinc function expansions instead of Chebyshev series. This experiment sheds light on the strengths and weaknesses of sinc function techniques. It also serves as a review of some of the main features of sinc methods, including construction, evaluation, zerofinding, optimization, integration, and differentiation.
Restrictive right ventricular physiology after tetralogy of Fallot repair is associated with fibrosis of the right ventricular outflow tract visualized on cardiac magnetic resonance imaging.

To determine whether the restrictive physiology seen in Tetralogy of Fallot (TOF) patients can be explained by fibrosis of the right ventricular (RV) outflow tract. The aetiology for restrictive RV physiology after TOF repair is not known.



TOF patients (n = 31, 13 girls, 10.2 years ± 2.8) were included 9.2 ± 2.9 years after total correction and examined with cardiac magnetic resonance (CMR) and Doppler echocardiography. Cine, flow, and late gadolinium contrast enhanced (LGE) CMR imaging were performed to quantify RV volumes, pulmonary flow and regurgitation (PR), and fibrosis. Healthy children (n = 12) were investigated with CMR of the pulmonary flow. Forward flow during atrial contraction above mean + 2 SD of healthy subjects was set as a marker of restrictive physiology. Four patients were excluded due to suboptimal LGE-CMR. Fisher's exact test was used to determine the association between restrictive physiology and fibrosis. Sixteen patients showed fibrosis in the right ventricular outflow tract (RVOT) on LGE-CMR and 14 of them showed restrictive physiology on CMR. Of the 11 patients without fibrosis in the RVOT, 1 showed restrictive physiology. The odds ratio for RVOT fibrosis in patients with restrictive RV physiology was 70.0 (CI: 5.6-882.7, P < 0.001). The transannular patch repair did not differ between the groups (P = 0.37). The degree of RVOT fibrosis correlated positively with PR (r(2) = 0.38, P < 0.001) and RV volumes (r(2) = 0.51 for end-diastolic volume and r(2) = 0.47 for end-systolic volume, P < 0.001).



There is a strong association between the restrictive RV physiology detected on CMR and fibrosis of the RVOT in children after TOF repair.
A WordNet-based Query Expansion Method for Geographical Information Retrieval

This report describes a query expansion method based on the expansion of geographical terms by means of WordNet synonyms and meronyms. We used this method for our participation to the GeoCLEF 2005 English monolingual task, while using the well-known Lucene search engine for indexing and retrieval. The obtained results show that the proposed method was not suitable for the GeoCLEF track, while WordNet can be used in a more effective way during the indexing phase, by adding synonyms and holonyms to the
Swarm intelligence based routing protocol for wireless sensor networks: Survey and future directions

Swarm intelligence is a relatively novel field. It addresses the study of the collective behaviors of systems made by many components that coordinate using decentralized controls and self-organization. A large part of the research in swarm intelligence has focused on the reverse engineering and the adaptation of collective behaviors observed in natural systems with the aim of designing effective algorithms for distributed optimization. These algorithms, like their natural systems of inspiration, show the desirable properties of being adaptive, scalable, and robust. These are key properties in the context of network routing, and in particular of routing in wireless sensor networks. Therefore, in the last decade, a number of routing protocols for wireless sensor networks have been developed according to the principles of swarm intelligence, and, in particular, taking inspiration from the foraging behaviors of ant and bee colonies. In this paper, we provide an extensive survey of these protocols. We discuss the general principles of swarm intelligence and of its application to routing. We also introduce a novel taxonomy for routing protocols in wireless sensor networks and use it to classify the surveyed protocols. We conclude the paper with a critical analysis of the status of the field, pointing out a number of fundamental issues related to the (mis) use of scientific methodology and evaluation procedures, and we identify some future research directions.
Selective Retina Therapy in Acute and Chronic-Recurrent Central Serous Chorioretinopathy.

Selective retina therapy (SRT), the confined laser heating and destruction of retinal pigment epithelial cells, has been shown to treat acute types of central serous chorioretinopathy (CSC) successfully without damaging the photoreceptors and thus avoiding laser-induced scotoma. However, a benefit of laser treatment for chronic forms of CSC is questionable. In this study, the efficacy of SRT by means of the previously used 1.7-µs and shorter 300-ns pulse duration was evaluated for both types of CSC, also considering re-treatment for nonresponders.



In a two-center trial, 26 patients were treated with SRT for acute (n = 10) and chronic-recurrent CSC (n = 16). All patients presented with subretinal fluid (SRF) in OCT and leakage in fluorescein angiography (FA). SRT was performed using a prototype SRT laser system (frequency-doubled Q-switched Nd:YLF-laser, wavelength 527 nm) with adjustable pulse duration. The following irradiation settings were used: a train of 30 laser pulses with a repetition rate of 100 Hz and pulse durations of 300 ns and 1.7 µs, pulse energy 120-200 µJ, retinal spot size 200 µm. Because SRT lesions are invisible, FA was always performed 1 h after treatment to demonstrate laser outcome (5-8 single spots in the area of leakage). In cases where energy was too low, as indicated by missing FA leakage, energy was adjusted and the patient re-treated immediately. Observation intervals were after 4 weeks and 3 months. In case of nonimprovement of the disease after 3 months, re-treatment was considered.



Of 10 patients with active CSC that presents focal leakage in FA, 5 had completely resolved fluid after 4 weeks and all 10 after 3 months. Mean visual acuity increased from 76.6 ETDRS letters to 85.0 ETDRS letters 3 months after SRT. Chronic-recurrent CSC was characterized by less severe SRF at baseline in OCT and weaker leakage in FA than in acute types. Visual acuity changed from baseline 71.6 to 72.8 ETDRS letters after 3 months. At this time, SRF was absent in 3 out of 16 patients (19%), FA leakage had come to a complete stop in 6 out of 16 patients (38%). In 6 of the remaining chronic CSC patients, repeated SRT with higher pulse energy was considered because of persistent leakage activity. After the re-treatment, SRF resolved completely in 5 patients (83.3%) after only 25 days.



SRT showed promising results in treating acute CSC, but was less effective in chronic cases. Interestingly, re-treatment resulted in enhanced fluid resolution and dry conditions after a considerably shorter time in most patients. Therefore, SRT including re-treatment if necessary might be a valuable CSC treatment alternative even in chronic-recurrent cases.
Easy Freshness with Pequod Cache Joins

This thesis presents the design of Pequod, a distributed, application-levelWeb cache.Web developers store data in application-level caches to avoid expensive operations on persistent storage.While useful for reducing the latency of data access, an application-level cache adds complexity to the application. The developer is responsible for keeping the cached data consistent with persistent storage. This consistency task can be difficult and costly, especially when the cached data represent the derived output of a computation. Pequod improves on the state-of-the-art by introducing an abstraction, the cache join, that caches derived datawithout requiring extensive consistency-related applicationmaintenance. Cache joins provide a mechanism for filtering, joining, and aggregating cached data. Pequod assumes the responsibility for maintaining cache freshness by automatically applying updates to derived data as inputs change over time. This thesis describes how cache joins are defined using a declarative syntax to overlay a relational data model on a key-value store, how cache data are generated on demand and kept fresh with a combination of eager and lazy incremental updates, howPequod uses the memory and computational resources of multiple machines to grow the cache, and how the correctness of derived data is maintained in the face of eviction. We show through experimentation that cache joins can be used to improve the performance ofWeb applications that cache derived data.We find that moving computation and maintenance tasks into the cache, where they can often be performed more efficiently, accounts for the majority of the improvement.
Path Planning Algorithm for Automatic Parallel Parking from Arbitrary Initial Angle

This paper presents automatic parallel parking for car-like vehicle, with highlights on a path planning algorithm for arbitrary initial angle using two tangential arcs of different radii. The algorithm is divided into three parts. Firstly, a simple kinematic model of the vehicle is established based on Ackerman steering geometry; secondly, not only a minimal size of the parking space is analyzed based on the size and the performance of the vehicle but also an appropriate target point is chosen based on the size of the parking space and the vehicle; Finally, a path is generated based on two tangential arcs of different radii. The simulation results show that the feasibility of the proposed algorithm.
A Polarization Reconfigurable Patch Antenna With Loop Slots on the Ground Plane

This letter proposes a reconfigurable microstrip patch antenna with polarization states being switched among linear polarization (LP), left-hand (LH) and right-hand (RH) circular polarizations (CP). The CP waves are excited by two perturbation elements of loop slots in the ground plane. A p-i-n diode is placed on every slot to alter the current direction, which determines the polarization state. The influences of the slots and p-i-n diodes on antenna performance are minimized because the slots and diodes are not on the patch. The simulated and measured results verified the effectiveness of the proposed antenna configuration. The experimental bandwidths of the -10-dB reflection coefficient for LHCP and RHCP are about 60 MHz, while for LP is about 30 MHz. The bandwidths of the 3-dB axial ratio for both CP states are 20 MHz with best value of 0.5 dB at the center frequency on the broadside direction. Gains for two CP operations are 6.4 dB, and that for the LP one is 5.83 dB. This reconfigurable patch antenna with agile polarization has good performance and concise structure, which can be used for 2.4 GHz wireless communication systems.
Predictors of stress-related illness in city bus drivers.

This study examines the relation between stress and illness among bus drivers in a large American city. Several factors are identified that predict stress-related ill health for this occupational group. Canonical correlation techniques are used to combine daily work stress and recent stressful life events into a single life/work stress variate. Likewise, somatic symptoms and serious illness reports are combined into a single canonical illness variate. This procedure simplifies the analysis of multiple stress and illness indicators and also permits the statistical control of potential contaminating influences on stress and illness measures (eg, neuroticism). Discriminant function analysis identified four variables that differentiate bus drivers who get ill under high stress (N = 137) from those who remain healthy under stress (N = 137). Highly stressed and ill bus drivers use more avoidance coping behaviors, report more illness in their family medical histories, are low in the disposition of "personality hardiness," and are also low in social assets. The derived stepwise discriminant function correctly classified 71% of cases in an independent "hold-out" sample. These results suggest fruitful areas of attention for health promotion and stress management programs in the public transit industry.
Building a Large Scale Dataset for Image Emotion Recognition: The Fine Print and The Benchmark

Psychological research results have confirmed that people can have different emotional reactions to different visual stimuli. Several papers have been published on the problem of visual emotion analysis. In particular, attempts have been made to analyze and predict people’s emotional reaction towards images. To this end, different kinds of hand-tuned features are proposed. The results reported on several carefully selected and labeled small image data sets have confirmed the promise of such features. While the recent successes of many computer vision related tasks are due to the adoption of Convolutional Neural Networks (CNNs), visual emotion analysis has not achieved the same level of success. This may be primarily due to the unavailability of confidently labeled and relatively large image data sets for visual emotion analysis. In this work, we introduce a new data set, which started from 3+ million weakly labeled images of different emotions and ended up 30 times as large as the current largest publicly available visual emotion data set. We hope that this data set encourages further research on visual emotion analysis. We also perform extensive benchmarking analyses on this large data set using the state of the art methods including CNNs.
Pathogens and host immunity in the ancient human oral cavity

Calcified dental plaque (dental calculus) preserves for millennia and entraps biomolecules from all domains of life and viruses. We report the first, to our knowledge, high-resolution taxonomic and protein functional characterization of the ancient oral microbiome and demonstrate that the oral cavity has long served as a reservoir for bacteria implicated in both local and systemic disease. We characterize (i) the ancient oral microbiome in a diseased state, (ii) 40 opportunistic pathogens, (iii) ancient human–associated putative antibiotic resistance genes, (iv) a genome reconstruction of the periodontal pathogen Tannerella forsythia, (v) 239 bacterial and 43 human proteins, allowing confirmation of a long-term association between host immune factors, 'red complex' pathogens and periodontal disease, and (vi) DNA sequences matching dietary sources. Directly datable and nearly ubiquitous, dental calculus permits the simultaneous investigation of pathogen activity, host immunity and diet, thereby extending direct investigation of common diseases into the human evolutionary past.
Anomaly detection in network traffic using K-mean clustering

With the advancement of digital age and internet technologies cyber-attacks increasingly have been prompting the news headlines. These attacks exploit a network's short comings to gain unauthorized access to the sensitive information or sometimes just create a flood to prevent legitimate users from accessing it. In any case intrusion of the network plays a key role before the execution of any attack. In this paper we will discuss a how these intrusions can be detected with k-means clustering based machine learning approach using big data analytical techniques and put forward the experimental results to prevent attacks at it's very core.
The caveolae membrane system.

The cell biology of caveolae is a rapidly growing area of biomedical research. Caveolae are known primarily for their ability to transport molecules across endothelial cells, but modern cellular techniques have dramatically extended our view of caveolae. They form a unique endocytic and exocytic compartment at the surface of most cells and are capable of importing molecules and delivering them to specific locations within the cell, exporting molecules to extracellular space, and compartmentalizing a variety of signaling activities. They are not simply an endocytic device with a peculiar membrane shape but constitute an entire membrane system with multiple functions essential for the cell. Specific diseases attack this system: Pathogens have been identified that use it as a means of gaining entrance to the cell. Trying to understand the full range of functions of caveolae challenges our basic instincts about the cell.
Public Debt , Corruption and Sustainable Economic Growth

There are many studies that look into the relationship between public debt and economic growth. It is hard to find, however, research addressing the role of corruption between these two variables. Noticing this vacancy in current literature, we strive to investigate the effect of corruption on the relationship between public debt and economic growth. For this purpose, the pooled ordinary least squares (OLS), fixed effects models and the dynamic panel generalized method of moments (GMM) models (Arellano-Bond, 1991) are estimated with data of 77 countries from 1990 to 2014. The empirical results show that the interaction term between public debt and corruption is statistically significant. This confirms the hypothesis that the effect of public debt on economic growth is a function of corruption. The sign of the marginal effect is negative in corrupt countries, but public debt enhances economic growth within countries that are not corrupt, i.e., highly transparent.
Predicting term-relevance from brain signals

Term-Relevance Prediction from Brain Signals (TRPB) is proposed to automatically detect relevance of text information directly from brain signals. An experiment with forty participants was conducted to record neural activity of participants while providing relevance judgments to text stimuli for a given topic. High-precision scientific equipment was used to quantify neural activity across 32 electroencephalography (EEG) channels. A classifier based on a multi-view EEG feature representation showed improvement up to 17% in relevance prediction based on brain signals alone. Relevance was also associated with brain activity with significant changes in certain brain areas. Consequently, TRPB is based on changes identified in specific brain areas and does not require user-specific training or calibration. Hence, relevance predictions can be conducted for unseen content and unseen participants. As an application of TRPB we demonstrate a high-precision variant of the classifier that constructs sets of relevant terms for a given unknown topic of interest. Our research shows that detecting relevance from brain signals is possible and allows the acquisition of relevance judgments without a need to observe any other user interaction. This suggests that TRPB could be used in combination or as an alternative for conventional implicit feedback signals, such as dwell time or click-through activity.
A point-based method for animating elastoplastic solids

In this paper we describe a point-based approach for animating elastoplastic materials. Our primary contribution is a simple method for computing the deformation gradient for each particle in the simulation. The deformation gradient is computed for each particle by finding the affine transformation that best approximates the motion of neighboring particles over a single timestep. These transformations are then composed to compute the total deformation gradient that describes the deformation around a particle over the course of the simulation. Given the deformation gradient we can apply arbitrary constitutive models and compute the resulting elastic forces. Our method has two primary advantages: we do not store or compare to an initial rest configuration and we work directly with the deformation gradient. The first advantage avoids poor numerical conditioning and the second naturally leads to a multiplicative model of deformation appropriate for finite deformations. We demonstrate our approach on a number of examples that exhibit a wide range of material behaviors.