nils-herrmann/clean_scirepeval huggingface dataset:
Review on solving the inverse problem in EEG source analysis

In this primer, we give a review of the inverse problem for EEG source localization. This is intended for the researchers new in the field to get insight in the state-of-the-art techniques used to find approximate solutions of the brain sources giving rise to a scalp potential recording. Furthermore, a review of the performance results of the different techniques is provided to compare these different inverse solutions. The authors also include the results of a Monte-Carlo analysis which they performed to compare four non parametric algorithms and hence contribute to what is presently recorded in the literature. An extensive list of references to the work of other researchers is also provided. This paper starts off with a mathematical description of the inverse problem and proceeds to discuss the two main categories of methods which were developed to solve the EEG inverse problem, mainly the non parametric and parametric methods. The main difference between the two is to whether a fixed number of dipoles is assumed a priori or not. Various techniques falling within these categories are described including minimum norm estimates and their generalizations, LORETA, sLORETA, VARETA, S-MAP, ST-MAP, Backus-Gilbert, LAURA, Shrinking LORETA FOCUSS (SLF), SSLOFO and ALF for non parametric methods and beamforming techniques, BESA, subspace techniques such as MUSIC and methods derived from it, FINES, simulated annealing and computational intelligence algorithms for parametric methods. From a review of the performance of these techniques as documented in the literature, one could conclude that in most cases the LORETA solution gives satisfactory results. In situations involving clusters of dipoles, higher resolution algorithms such as MUSIC or FINES are however preferred. Imposing reliable biophysical and psychological constraints, as done by LAURA has given superior results. The Monte-Carlo analysis performed, comparing WMN, LORETA, sLORETA and SLF, for different noise levels and different simulated source depths has shown that for single source localization, regularized sLORETA gives the best solution in terms of both localization error and ghost sources. Furthermore the computationally intensive solution given by SLF was not found to give any additional benefits under such simulated conditions.
ElastiFace: matching and blending textured faces

In this paper we present ElastiFace, a simple and versatile method for establishing correspondence between textured face models, either for the construction of a blend-shape facial rig or for the exploration of new characters by morphing between a set of input models. While there exists a wide variety of approaches for inter-surface mapping and mesh morphing, most techniques are not suitable for our application: They either require the insertion of additional vertices, are limited to topological planes or spheres, are restricted to near-isometric input meshes, and/or are algorithmically and computationally involved. In contrast, our method extends linear non-rigid registration techniques to allow for strongly varying input geometries. It is geometrically intuitive, simple to implement, computationally efficient, and robustly handles highly non-isometric input models. In order to match the requirements of other applications, such as recent perception studies, we further extend our geometric matching to the matching of input textures and morphing of geometries and rendering styles.
Dual-side and three-dimensional microelectrode arrays fabricated from ultra-thin silicon substrates

A method for fabricating planar implantable microelectrode arrays was demonstrated using a process that relied on ultra-thin silicon substrates, which ranged in thickness from 25 to 50 μm. The challenge of handling these fragile materials was met via a temporary substrate support mechanism. In order to compensate for putative electrical shielding of extracellular neuronal fields, separately addressable electrode arrays were defined on each side of the silicon device. Deep reactive ion etching was employed to create sharp implantable shafts with lengths of up to 5 mm. The devices were flip-chip bonded onto printed circuit boards (PCBs) by means of an anisotropic conductive adhesive film. This scalable assembly technique enabled three-dimensional (3D) integration through formation of stacks of multiple silicon and PCB layers. Simulations and measurements of microelectrode noise appear to suggest that low impedance surfaces, which could be formed by electrodeposition of gold or other materials, are required to ensure an optimal signal-to-noise ratio as well a low level of interchannel crosstalk. (Some figures in this article are in colour only in the electronic version)
Modification of gene activity in mouse embryos in utero by a tamoxifen-inducible form of Cre recombinase

The ability to generate specific genetic modifications in mice provides a powerful approach to assess gene function. When genetic modifications have been generated in the germ line, however, the resulting phenotype often only reflects the first time a gene has an influence on - or is necessary for - a particular biological process. Therefore, systems allowing conditional genetic modification have been developed (for a review, see ); for example, inducible forms of the Cre recombinase from P1 phage have been generated that can catalyse intramolecular recombination between target recognition sequences (loxP sites) in response to ligand [2]   . Here, we assessed whether a tamoxifen-inducible form of Cre recombinase (Cre-ERTM) could be used to modify gene activity in the mouse embryo in utero. Using the enhancer of the Wnt1 gene to restrict the expression of Cre-ERTM to the embryonic neural tube, we found that a single injection of tamoxifen into pregnant mice induced Cre-mediated recombination within the embryonic central nervous system, thereby activating expression of a reporter gene. Induction was ligand dependent, rapid and efficient. The results demonstrate that tamoxifen-inducible recombination can be used to effectively modify gene function in the mouse embryo.
Efficient processing of data warehousing queries in a split execution environment

Hadapt is a start-up company currently commercializing the Yale University research project called HadoopDB. The company focuses on building a platform for Big Data analytics in the cloud by introducing a storage layer optimized for structured data and by providing a framework for executing SQL queries efficiently. This work considers processing data warehousing queries over very large datasets. Our goal is to maximize perfor mance while, at the same time, not giving up fault tolerance and scalability. We analyze the complexity of this problem in the split execution environment of HadoopDB. Here, incoming queries are examined; parts of the query are pushed down and executed inside the higher performing database layer; and the rest of the query is processed in a more generic MapReduce framework.
 In this paper, we discuss in detail performance-oriented query execution strategies for data warehouse queries in split execution environments, with particular focus on join and aggregation operations. The efficiency of our techniques is demonstrated by running experiments using the TPC-H benchmark with 3TB of data. In these experiments we compare our results with a standard commercial parallel database and an open-source MapReduce implementation featuring a SQL interface (Hive). We show that HadoopDB successfully competes with other systems.
Service Level Agreement (SLA) in Utility Computing Systems

In recent years, extensive research has been conducted in the area of Service Level Agreement (SLA) for utility computing systems. An SLA is a formal contract used to guarantee that consumers’ service quality expectation can be achieved. In utility computing systems, the level of customer satisfaction is crucial, making SLAs significantly important in these environments. Fundamental issue is the management of SLAs, including SLA autonomy management or trade off among multiple Quality of Service (QoS) parameters. Many SLA languages and frameworks have been developed as solutions; however, there is no overall classification for these extensive works. Therefore, the aim of this chapter is to present a comprehensive survey of how SLAs are created, managed and used in utility computing environment. We discuss existing use cases from Grid and Cloud computing systems to identify the level of SLA realization in state-of-art systems and emerging challenges for future research.
Vitamins D, C, and E in the prevention of type 2 diabetes mellitus: modulation of inflammation and oxidative stress

The incidence of type 2 diabetes mellitus (T2DM) is increasing worldwide, and certain population subgroups are especially vulnerable to the disease. To reduce T2DM risk and progression at the population level, preventative strategies are needed that can be implemented on a population-wide scale with minimal cost and effort. Chronic low-grade inflammation resulting from oxidative stress and imbalances in the innate immune system has been associated with obesity, metabolic syndrome, and insulin resistance - critical stages in the development and progression of T2DM. Therefore, inflammation may play a causal role in the pathogenesis of T2DM, and reducing it via modulation of oxidative stress and the innate immune response could lead to a status of improved insulin sensitivity and delayed disease onset. Dietary supplementation with anti-inflammatory and antioxidant nutritional factors, such as micronutrients, might present a novel strategy toward the prevention and control of T2DM at the population level. This review examines current knowledge linking oxidation, inflammatory signaling pathways, and vitamin supplementation or intake to the risk of T2DM. The concept that micronutrients, via attenuation of inflammation, could be employed as a novel preventive measure for T2DM is evaluated in the context of its relevance to public health.
Speaker Recognition System Based On MFCC and DCT

This paper examines and presents an approach to the recognition of speech signal using frequency spectral information with Mel frequency. It is a dominant feature for speech recognition. Mel-frequency cepstral coefficients (MFCCs) are the coefficients that collectively represent the shortterm power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a non linear mel scale of frequency. The performance of MFCC is affected by the number of filters, the shape of filters, the way that filters are spaced, and the way that the power spectrum is warped. In this paper the optimum values of above parameters are chosen to get an efficiency of 99.5 % over a very small length of audio file.
Autonomous question answering with mobile robots in human-populated environments

Autonomous mobile robots will soon become ubiquitous in human-populated environments. Besides their typical applications in fetching, delivery, or escorting, such robots present the opportunity to assist human users in their daily tasks by gathering and reporting up-to-date knowledge about the environment. In this paper, we explore this use case and present an end-to-end framework that enables a mobile robot to answer natural language questions about the state of a large-scale, dynamic environment asked by the inhabitants of that environment. The system parses the question and estimates an initial viewpoint that is likely to contain information for answering the question based on prior environment knowledge. Then, it autonomously navigates towards the viewpoint while dynamically adapting to changes and new information. The output of the system is an image of the most relevant part of the environment that allows the user to obtain an answer to their question. We additionally demonstrate the benefits of a continuously operating information gathering robot by showing how the system can answer retrospective questions about the past state of the world using incidentally recorded sensory data. We evaluate our approach with a custom mobile robot deployed in a university building, with questions collected from occupants of the building. We demonstrate our system's ability to respond to these questions in different environmental conditions.
Refactoring sequential Java code for concurrency via concurrent libraries

Parallelizing existing sequential programs to run efficiently on multicores is hard. The Java 5 package java.util.concurrent (j.u.c.) supports writing concurrent programs: much of the complexity of writing thread-safe and scalable programs is hidden in the library. To use this package, programmers still need to reengineer existing code. This is tedious because it requires changing many lines of code, is error-prone because programmers can use the wrong APIs, and is omission-prone because programmers can miss opportunities to use the enhanced APIs. This paper presents our tool, Concurrencer, that enables programmers to refactor sequential code into parallel code that uses three j.u.c. concurrent utilities. Concurrencer does not require any program annotations. Its transformations span multiple, non-adjacent, program statements. A find-and-replace tool can not perform such transformations, which require program analysis. Empirical evaluation shows that Concurrencer refactors code effectively: Concurrencer correctly identifies and applies transformations that some open-source developers overlooked, and the converted code exhibits good speedup.
Data Provenance: A Categorization of Existing Approaches

In many application areas like e-science and data-warehousing detailed information about the origin of data is required. This kind of information is often referred to as data provenance or data lineage. The provenance of a data item includes information about the processes and source data items that lead to its creation and current representation. The diversity of data representation models and application domains has lead to a number of more or less formal definitions of provenance. Most of them are limited to a special application domain, data representation model or data processing facility. Not surprisingly, the associated implementations are also restricted to some application domain and depend on a special data model. In this paper we give a survey of data provenance models and prototypes, present a general categorization scheme for provenance models and use this categorization scheme to study the properties of the existing approaches. This categorization enables us to distinguish between different kinds of provenance information and could lead to a better understanding of provenance in general. Besides the categorization of provenance types, it is important to include the storage, transformation and query requirements for the different kinds of provenance information and application domains in our considerations. The analysis of existing approaches will assist us in revealing open research problems in the area of data provenance.
Normative and criterion-related standards for shuttle run performance in youth.

The purpose of this study was to calculate and validate reference standards for the 20-m shuttle run test (SR) in youths aged 10-18 years. Reference standards based on the number of completed SR laps were calculated by LMS method in a reference group of 5559 students. Cut-off values for SR laps were determined and tested by ROC curve analysis in a validation group (633 students), from which waist circumference, HDL-cholesterol, triglycerides, fasting glucose and mean arterial pressure were assessed to calculate a metabolic risk score, later dichotomized in low and high metabolic risk (HMRS). The accuracy of SR laps standards was significant for girls (AUC = 0.66; 95% CI = 0.58-0.74; p < .001) and boys (AUC = 0.71; 95% CI = 0.62-0.79; p < .001) for identifying subjects at HMRS. The 40th percentile was the best cut-off for SR laps in girls (SENS = 0.569; 1-SPEC = 0.330) and boys (SENS = 0.634; 1-SPEC = 0.266). New SR laps reference standards are able to discriminate metabolic risk levels, and may provide a valuable tool for early prevention of cardiovascular risk factors.
Hierarchical Mixtures of Experts and the EM Algorithm

We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are generalized linear models (GLIM's). Learning is treated as a maximum likelihood problem; in particular, we present an Expectation-Maximization (EM) algorithm for adjusting the parameters of the architecture. We also develop an on-line learning algorithm in which the parameters are updated incrementally. Comparative simulation results are presented in the robot dynamics domain.
Faster and More Focused Control-Flow Analysis for Business Process Models Through SESE Decomposition

We present a technique to enhance control-flow analysis of business process models. The technique considerably speeds up the analysis an d improves the diagnostic information that is given to the user to fix control-flow errors . The technique consists of two parts: Firstly, the process model is decomp osed into single-entry-single-exit (SESE) fragments, which are usually subs tantially smaller than the original process. This decomposition is done in linear time. S econdly, each fragment is analyzed in isolation using a fast heuristic that ca n an lyze many of the fragments occurring in practice. Any remaining fragme nts that are not covered by the heuristic can then be analyzed using any known c omplete analysis technique. We used our technique in a case study with more than 340 real business pr ocesses modeled with the IBM WebSphere Business Modeler. The results s uggest that control-flow analysis of many real process models is feasible withou t significant delay (less than a second). Therefore, control-flow analysis co uld be used frequently during editing time, which allows errors to be caught at earliest possible time.
Numerical method for Darcy flow derived using Discrete Exterior Calculus

We derive a numerical method for Darcy flow, hence also for Poisson’s equation in first order form, based on discrete exterior calculus (DEC). Exterior calculus is a generalization of vector calculus to smooth manifolds and DEC is its discretization on simplicial complexes such as triangle and tetrahedral meshes. We start by rewriting the governing equations of Darcy flow using the language of exterior calculus. This yields a formulation in terms of flux differential form and pressure. The numerical method is then derived by using the framework provided by DEC for discretizing differential forms and operators that act on forms. We also develop a discretization for spatially dependent Hodge star that varies with the permeability of the medium. This also allows us to address discontinuous permeability. The matrix representation for our discrete non-homogeneous Hodge star is diagonal, with positive diagonal entries. The resulting linear system of equations for flux and pressure are saddle type, with a diagonal matrix as the top left block. Our method requires the use of meshes in which each simplex contains its circumcenter. The performance of the proposed numerical method is illustrated on many standard test problems. These include patch tests in two and three dimensions, comparison with analytically known solution in two dimensions, layered medium with alternating permeability values, and a test with a change in permeability along the flow direction. A short introduction to the relevant parts of smooth and discrete exterior calculus is included in this paper. We also include a discussion of the boundary condition in terms of exterior calculus.
Virtual machine workloads: the case for new benchmarks for NAS

Network Attached Storage (NAS) and Virtual Machines (VMs) are widely used in data centers thanks to their manageability, scalability, and ability to consolidate resources. But the shift from physical to virtual clients drastically changes the I/O workloads seen on NAS servers, due to guest file system encapsulation in virtual disk images and the multiplexing of request streams from different VMs. Unfortunately, current NAS workload generators and benchmarks produce workloads typical to physical machines. This paper makes two contributions. First, we studied the extent to which virtualization is changing existing NAS workloads. We observed significant changes, including the disappearance of file system meta-data operations at the NAS layer, changed I/O sizes, and increased randomness. Second, we created a set of versatile NAS benchmarks to synthesize virtualized workloads. This allows us to generate accurate virtualized workloads without the effort and limitations associated with setting up a full virtualized environment. Our experiments demonstrate that the relative error of our virtualized benchmarks, evaluated across 11 parameters, averages less than 10%.
High-Throughput Parallel Architecture for H.265/HEVC Deblocking Filter

A novel parallel VLSI architecture is proposed in order to improve the performance of the H.265/HEVC deblocking filter. The overall computation is pipelined, and a new parallel-zigzag processing order is introduced to achieve high throughput. The processing order of the filter is efficiently rearranged to process the horizontal edges and vertical edges at the same time. The proposed H.265/HEVC deblocking filter architecture improves the parallelism by dissolving the data dependency between the adjacent filtering operations. Our design is also compatible with H.264/AVC. Experimental results demonstrate that our architecture shows the best performance compared with other architectures known so far at the expense of the slightly increased gate count. We improve the performance by 52.3%, while the area is increased by 25.8% compared with the previously known best architecture for H.264/AVC. The operating clock frequency of our design is 226 MHz in TSMC LVT 65 process. The proposed design delivers the performance to process 1080p HD at 60 fps.
X-COM: UFO Defense vs. XCOM: Enemy Unknown - Using gameplay design patterns to understand game remakes

We analyze X-COM: UFO Defense and its successful remake XCOM: Enemy Unknown to understand how remakes can repropose a concept across decades, updating most mechanics, and yet retain the dynamic and aesthetic values that defined the original experience. We use gameplay design patterns along with the MDA framework to understand the changes, identifying an unchanged core among a multitude of differences. We argue that two forces polarize the context within which the new game was designed, simultaneously guaranteeing a sameness of experience across the two games and at the same time pushing for radical changes. The first force, which resists the push for an updated experience, can be described as experiential isomorphism, or “sameness of form” in terms of related Gestalt qualities. The second force is generated by the necessity to update the usability of the design, aligning it to a current usability paradigm. We employ game usability heuristics (PLAY) to evaluate aesthetic patterns present in both games, and to understand the implicit vector for change. Our finding is that while patterns on the mechanical and to a slight degree the dynamic levels change between the games, the same aesthetic patterns are present in both, but produced through different means. The method we use offers new understanding of how sequels and remakes of games can change significantly from their originals while still giving rise to similar experiences.