nils-herrmann/clean_scirepeval huggingface dataset:
Genital cutting and western discourses on sexuality.

This article explores dominant discourses surrounding male and female genital cutting. Over a similar period of time, these genital operations have separately been subjected to scrutiny and criticism. However, although critiques of female circumcision have been widely taken up, general public opinion toward male circumcision remains indifferent. This difference cannot merely be explained by the natural attributes and effects of these practices. Rather, attitudes toward genital cutting reflect historically and culturally specific understandings of the human body. In particular, I suggest that certain problematic understandings of male and female sexuality are deeply implicated in the dominant Western discourses on genital surgery.
Visual word recognition of single-syllable words.

Speeded visual word naming and lexical decision performance are reported for 2428 words for young adults and healthy older adults. Hierarchical regression techniques were used to investigate the unique predictive variance of phonological features in the onsets, lexical variables (e.g., measures of consistency, frequency, familiarity, neighborhood size, and length), and semantic variables (e.g. imageahility and semantic connectivity). The influence of most variables was highly task dependent, with the results shedding light on recent empirical controversies in the available word recognition literature. Semantic-level variables accounted for unique variance in both speeded naming and lexical decision performance, level with the latter task producing the largest semantic-level effects. Discussion focuses on the utility of large-scale regression studies in providing a complementary approach to the standard factorial designs to investigate visual word recognition.
ViDX: Visual Diagnostics of Assembly Line Performance in Smart Factories

Visual analytics plays a key role in the era of connected industry (or industry 4.0, industrial internet) as modern machines and assembly lines generate large amounts of data and effective visual exploration techniques are needed for troubleshooting, process optimization, and decision making. However, developing effective visual analytics solutions for this application domain is a challenging task due to the sheer volume and the complexity of the data collected in the manufacturing processes. We report the design and implementation of a comprehensive visual analytics system, ViDX. It supports both real-time tracking of assembly line performance and historical data exploration to identify inefficiencies, locate anomalies, and form hypotheses about their causes and effects. The system is designed based on a set of requirements gathered through discussions with the managers and operators from manufacturing sites. It features interlinked views displaying data at different levels of detail. In particular, we apply and extend the Marey's graph by introducing a time-aware outlier-preserving visual aggregation technique to support effective troubleshooting in manufacturing processes. We also introduce two novel interaction techniques, namely the quantiles brush and samples brush, for the users to interactively steer the outlier detection algorithms. We evaluate the system with example use cases and an in-depth user interview, both conducted together with the managers and operators from manufacturing plants. The result demonstrates its effectiveness and reports a successful pilot application of visual analytics for manufacturing in smart factories.
In-body experiences: embodiment, control, and trust in robot-mediated communication

Communication technologies are becoming increasingly diverse in form and functionality, making it important to identify which aspects of these technologies actually improve geographically distributed communication. Our study examines two potentially important aspects of communication technologies which appear in robot-mediated communication - physical embodiment and control of this embodiment. We studied the impact of physical embodiment and control upon interpersonal trust in a controlled laboratory experiment using three different videoconferencing settings: (1) a handheld tablet controlled by a local user, (2) an embodied system controlled by a local user, and (3) an embodied system controlled by a remote user (n = 29 dyads). We found that physical embodiment and control by the local user increased the amount of trust built between partners. These results suggest that both physical embodiment and control of the system influence interpersonal trust in mediated communication and have implications for future system designs.
Evolutionary Design of Intrusion Detection Programs

Intrusion detection is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of intrusions, defined as attempts to compromise the confidentiality, integrity, availability, or to bypass the security mechanisms of a computer or network. This paper proposes the development of an Intrusion Detection Program (IDP) which could detect known attack patterns. An IDP does not eliminate the use of any preventive mechanism but it works as the last defensive mechanism in securing the system. Three variants of genetic programming techniques namely Linear Genetic Programming (LGP), Multi-Expression Programming (MEP) and Gene Expression Programming (GEP) were evaluated to design IDP. Several indices are used for comparisons and a detailed analysis of MEP technique is provided. Empirical results reveal that genetic programming technique could play a major role in developing IDP, which are light weight and accurate when compared to some of the conventional intrusion detection systems based on machine learning paradigms.
Design and Evaluation of Metaphor Processing Systems

System design and evaluation methodologies receive significant attention in natural language processing (NLP), with the systems typically being evaluated on a common task and against shared data sets. This enables direct system comparison and facilitates progress in the field. However, computational work on metaphor is considerably more fragmented than similar research efforts in other areas of NLP and semantics. Recent years have seen a growing interest in computational modeling of metaphor, with many new statistical techniques opening routes for improving system accuracy and robustness. However, the lack of a common task definition, shared data set, and evaluation strategy makes the methods hard to compare, and thus hampers our progress as a community in this area. The goal of this article is to review the system features and evaluation strategies that have been proposed for the metaphor processing task, and to analyze their benefits and downsides, with the aim of identifying the desired properties of metaphor processing systems and a set of requirements for their evaluation.
A Novel UHF Near-Field RFID Reader Antenna Deploying CSRR Elements

A novel ultrahigh frequency (UHF) near-field radio-frequency identification (RFID) reader antenna based on the complementary split ring resonator (CSRR) elements is presented in this communication. The antenna consists of a power divider and two arms. The two arms are terminated with two 50-<inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> terminations. First arm is forward arm, which is a microstrip transmission line. The second arm is backward arm, which is loaded with CSRR elements, instigating backward wave propagation. The oppositely directed currents are generated by this configuration to produce strong and uniform magnetic field over the antenna plane for UHF near-field RFID operations. The proposed antenna operates from 0.76 to 0.88 GHz, and a total impedance bandwidth of 120 MHz is obtained. A near-field read range of 100 mm and an interrogation area of 220 mm <inline-formula> <tex-math notation="LaTeX">$\times180$ </tex-math></inline-formula> mm over the antenna plane at a height of 50 mm is reported for this antenna.
Oculovagal reflex in paediatric orbital floor fractures mimicking head injury.

The oculovagal reflex is well described in ophthalmic surgery, but may be caused by any manner of pressure on the globe. Children with orbital blowout fractures present in a different manner from adults. The classic presentation in children is a white eye injury (ie, no subconjunctival haemorrhage) with upgaze diplopia and general malaise.



A retrospective audit is presented of paediatric and young adult patients referred to the Orbital Service at St George's Hospital who required surgical intervention.



One-third of children with orbital blowout fractures are admitted for head injury observations, while the true cause for the symptoms goes unrecognised and uninvestigated.



Orbital blowout fractures in children require more swift intervention than in adults if muscle ischaemia and permanent impairment of the vision is to be avoided. The delay for head injury observation may therefore compromise the surgical outcome.
LOCALLY REFINED SPLINES REPRESENTATION FOR GEOSPATIAL BIG DATA

When viewed from distance, large parts of the topography of landmasses and the bathymetry of the sea and ocean floor can be regarded as a smooth background with local features. Consequently a digital elevation model combining a compact smooth representation of the background with locally added features has the potential of providing a compact and accurate representation for topography and bathymetry. The recent introduction of Locally Refined B-Splines (LR B-splines) allows the granularity of spline representations to be locally adapted to the complexity of the smooth shape approximated. This allows few degrees of freedom to be used in areas with little variation, while adding extra degrees of freedom in areas in need of more modelling flexibility. In the EU fp7 Integrating Project IQmulus we exploit LR B-splines for approximating large point clouds representing bathymetry of the smooth sea and ocean floor. A drastic reduction is demonstrated in the bulk of the data representation compared to the size of input point clouds. The representation is very well suited for exploiting the power of GPUs for visualization as the spline format is transferred to the GPU and the triangulation needed for the visualization is generated on the GPU according to the viewing parameters. The LR Bsplines are interoperable with other elevation model representations such as LIDAR data, raster representations and triangulated irregular networks as these can be used as input to the LR B-spline approximation algorithms. Output to these formats can be generated from the LR B-spline applications according to the resolution criteria required. The spline models are well suited for change detection as new sensor data can efficiently be compared to the compact LR B-spline representation.
Arc-fault unwanted tripping survey with UL 1699B-listed products

Since adoption of the 2011 National Electrical Code®, many photovoltaic (PV) direct current (DC) arc-fault circuit interrupters (AFCIs) and arc-fault detectors (AFDs) have been introduced into the PV market. To meet the Code requirements, these products must be listed to Underwriters Laboratories (UL) 1699B Outline of Investigation. The UL 1699B test sequence was designed to ensure basic arc-fault detection capabilities with resistance to unwanted tripping; however, field experiences with AFCI/AFD devices have shown mixed results. In this investigation, independent laboratory tests were performed with UL-listed, UL-recognized, and prototype AFCI/AFDs to reveal any limitations with state-of-the-art arc-fault detection products. By running AFCIs and stand-alone AFDs through realistic tests beyond the UL 1699B requirements, many products were found to be sensitive to unwanted tripping or were ineffective at detecting harmful arc-fault events. Based on these findings, additional experiments are encouraged for inclusion in the AFCI/AFD design process and the certification standard to improve products entering the market.
Online Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction

Max-margin matrix factorization (M3F) has been popularly applied to collaborative filtering for personalized recommendations. The nonparametric M3F model represents the latest progress of the M3F methods, which can auto-select the number of factors by using nonparametric techniques. However, existing non-parametric M3F methods assume a collection of user rating data can be fully obtained before training, and they are inapplicable for on-the-fly recommender systems where user rating data arrive continuously. In this paper, we present a new efficient online nonparametric 3F model for flexible recommendation. Specifically, we design an online nonparametric M3F model (OnM3F) based on the online Passive-Aggressive learning and solve the corresponding optimization problem by using the online stochastic gradient descent. Empirical studies on two large real-world data sets verify the effectiveness of the proposed method.
Æminium: a permission based concurrent-by-default programming language approach

The aim of ÆMINIUM is to study the implications of having a concurrent-by-default programming language. This includes language design, runtime system, performance and software engineering considerations.
 We conduct our study through the design of the concurrent-by-default ÆMINIUM programming language. ÆMINIUM leverages the permission flow of object and group permissions through the program to validate the program's correctness and to automatically infer a possible parallelization strategy via a dataflow graph. ÆMINIUM supports not only fork-join parallelism but more general dataflow patterns of parallelism.
 In this paper we present a formal system, called μÆMINIUM, modeling the core concepts of ÆMINIUM. μÆMINIUM's static type system is based on Featherweight Java with ÆMINIUM-specific extensions. Besides checking for correctness ÆMINIUM's type system it also uses the permission flow to compute a potential parallel execution strategy for the program. μÆMINIUM's dynamic semantics use a concurrent-by-default evaluation approach. Along with the formal system we present its soundness proof.
 We provide a full description of the implementation along with the description of various optimization techniques we used. We implemented ÆMINIUM as an extension of the Plaid programming language, which has first-class support for permissions built-in. The ÆMINIUM implementation and all case studies are publicly available under the General Public License.
 We use various case studies to evaluate ÆMINIUM's applicability and to demonstrate that ÆMINIUM parallelized code has performance improvements compared to its sequential counterpart. We chose to use case studies from common domains or problems that are known to benefit from parallelization, to show that ÆMINIUM is powerful enough to encode them. We demonstrate through a webserver application, which evaluates ÆMINIUM's impact on latency-bound applications, that ÆMINIUM can achieve a 70% performance improvement over the sequential counterpart. In another case study we chose to implement a dictionary function to evaluate ÆMINIUM's capabilities to express essential data structures. Our evaluation demonstrates that ÆMINIUM can be used to express parallelism in such data-structures and that the performance benefits scale with the amount of annotation effort which is put into the implementation. We chose an integral computationally example to evaluate pure functional programming and computational intensive use cases. Our experiments show that ÆMINIUM is capable of extracting parallelism from functional code and achieving performance improvements up to the limits of Plaid's inherent performance bounds.
 Overall, we hope that the work helps to advance concurrent programming in modern programming environments.
Swarm Intelligence based Collision Avoidance Between Realistically Modelled UAV Clusters

In this paper problem of collision avoidance in group of UAVs is addressed. Algorithms for two types of collision avoidance: Group-wise and Individual are successfully developed in the three-dimensional plane using various basic swarming behaviors. Limit on both horizontal and vertical acceleration is applied to cater the hardware constraints of UAV. Effect of these basic laws has also been studied on the group behavior of swarms. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settles down at same height on a circle of constant radius. It is also shown analytically that this equilibrium condition is stable for all values of velocity V and acceleration constant k. Finally, noise of zero mean and standard deviation sigma is added to the position of UAVs to study the effect of position uncertainty on group behavior and on both types of collision avoidance.
Experimental Investigations on Nanoclay ( Cloisite-15 A ) Modified Bitumen

This study investigated the influence of Cloisite-15A nanoclay on the physical, performance, and mechanical properties of bitumen binder. Cloisite-15A was blended in the bitumen in variegated percentages from 1% to 9% with increment of 2%. The blended bitumen was characterized using penetration, softening point, and dynamic viscosity using rotational viscometer, and compared with unmodified bitumen equally penetration grade 60/70. The rheological parameters were investigated using Dynamic Shear Rheometer (DSR), and mechanical properties were investigated by using Marshall Stability test. The results indicated an increase in softening point, dynamic viscosity and decrease in binder penetration. Rheological properties of bitumen increase complex modulus, decrease phase angle and improve rutting resistances as well. There was significant improvement in Marshall Stability, rather marginal improvement in flow value. The best improvement in the modified binder was obtained with 5% Cloisite-15A nanoclay. Cloisite-15A, complex shear modulus, phase angle, rutting resistance.
Optimistic and Pessimistic Neural Networks for Scene and Object Recognition

In this paper the application of uncertainty modeling to convolutional neural networks is evaluated. A novel method for adjusting the network’s predictions based on uncertainty information is introduced. This allows the network to be either optimistic or pessimistic in its prediction scores. The proposed method builds on the idea of applying dropout at test time and sampling a predictive mean and variance from the network’s output. Besides the methodological aspects, implementation details allowing for a fast evaluation are presented. Furthermore, a multilabel network architecture is introduced that strongly benefits from the presented approach. In the evaluation it will be shown that modeling uncertainty allows for improving the performance of a given model purely at test time without any further training steps. The evaluation considers several applications in the field of computer vision, including object classification and detection as well as scene attribute recognition.
A signal-processing framework for inverse rendering

Realism in computer-generated images requires accurate input models for lighting, textures and BRDFs. One of the best ways of obtaining high-quality data is through measurements of scene attributes from real photographs by inverse rendering. However, inverse rendering methods have been largely limited to settings with highly controlled lighting. One of the reasons for this is the lack of a coherent mathematical framework for inverse rendering under general illumination conditions. Our main contribution is the introduction of a signal-processing framework which describes the reflected light field as a convolution of the lighting and BRDF, and expresses it mathematically as a product of spherical harmonic coefficients of the BRDF and the lighting. Inverse rendering can then be viewed as deconvolution. We apply this theory to a variety of problems in inverse rendering, explaining a number of previous empirical results. We will show why certain problems are ill-posed or numerically ill-conditioned, and why other problems are more amenable to solution. The theory developed here also leads to new practical representations and algorithms. For instance, we present a method to factor the lighting and BRDF from a small number of views, i.e. to estimate both simultaneously when neither is known.
Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics

Recently several hierarchical inverse dynamics controllers based on cascades of quadratic programs have been proposed for application on torque controlled robots. They have important theoretical benefits but have never been implemented on a torque controlled robot where model inaccuracies and real-time computation requirements can be problematic. In this contribution we present an experimental evaluation of these algorithms in the context of balance control for a humanoid robot. The presented experiments demonstrate the applicability of the approach under real robot conditions (i.e. model uncertainty, estimation errors, etc). We propose a simplification of the optimization problem that allows us to decrease computation time enough to implement it in a fast torque control loop. We implement a momentum-based balance controller which shows robust performance in face of unknown disturbances, even when the robot is standing on only one foot. In a second experiment, a tracking task is evaluated to demonstrate the performance of the controller with more complicated hierarchies. Our results show that hierarchical inverse dynamics controllers can be used for feedback control of humanoid robots and that momentum-based balance control can be efficiently implemented on a real robot.
A case of precocious puberty in a female.

Sexual precocity is considered to be present when indications of genital maturation become apparent in boys before the age of 10 years and in girls before the age of 8 years (Seckel, 1946). It is customary to divide these cases into two groups. In those with true precocious puberty maturation with spermatogenesis or ovulation has occurred in a normal manner, but at an abnormally early age; in those with pseudoprecocious puberty, premature development of the secondary sex organs, but without spermatogenesis or ovulation, has occurred as a result of an ovarian or adreno-cortical tumour, unusual sensitivity of end-organs to normal hormonal stimulation, or exogenous application of sex hormones or other compounds (Talbot, Sobel, McArthur and Crawford, 1952). In a small proportion of cases true precocious puberty is associated with tumours or cysts in the region of the hypothalamus or with post-meningitic or postencephalitic lesions, but in the majority diligent and repeated search fails to reveal any abnormality in the nervous system or endocrine glands (Wilkins, 1957). Such cases are generally referred to as 'idiopathic' or 'constitutional' (Novak, 1944), and it is suggested that the genetic factor or factors that determine the time of hypothalamic sex maturation must be at fault (Seckel, 1946). In a small percentage of cases there is a heredo-familial tendency (Rush, Bilderback, Slocum and Rogers, 1937; Jacobsen and Macklin, 1952). Precocious puberty of idiopathic origin represents simply the early appearance of normal phenomena, and many of the physical and laboratory examinations reveal findings normal for older children (Lloyd, Lobotsky and Morley, 1950). Except for the hazard of precocious pregnancy and the possibility of subnormal stature, the prognosis of girls with idiopathic precocious puberty is good, and it does not appear that the menopause is accelerated or that premature senility occurs (Talbot et al., 1952; Jolly, 1955). The following case of precocious puberty occurring in a female child appears to present features of sufficient interest to warrant publication.