nils-herrmann/clean_scirepeval huggingface dataset:
CRISTAL-iSE - Provenance Applied in Industry

This paper presents the CRISTAL-iSE project as a framework for the management of provenance information in industry. The project itself is a research collaboration between academia and industry. A key factor in the project is the 
use of a system known as CRISTAL which is a mature system based on proven description driven principles. A crucial element in the description driven approach is that the fact that objects (Items) are described at runtime enabling managed systems to be both dynamic and flexible. Another factor is the notion that all Items in CRISTAL are stored and versioned, therefore enabling a provenance collection system. In this paper a concrete application, called 
Agilium, is briefly described and a future application CIMAG-RA is presented which will harness the power of both CRISTAL and Agilium.
Time-Inconsistent Mean-Utility Portfolio Selection with Moving Target

In this paper, we solve the time inconsistent portfolio selection problem by using different utility functions with a moving target as our constraint. We solve this problem by finding an equilibrium control under the given definition as our optimal control. We firstly derive a sufficient equilibrium condition for second-order continuously differentiable utility funtions. Then we use power functions of order two, three and four in our problem and find the respective condtions for obtaining an equilibrium for our different problems. In the last part of the paper, we consider using another definition of equilibrium to solve our problem when the utility function that we use in our problem is the negative part of x and also find the condtions for obtaining an equilibrium.
Linear Programming for Large-Scale Markov Decision Problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.
Synthesis of Parametric Programs using Genetic Programming and Model Checking

Formal methods apply algorithms based on mathematical principles to enhance the reliability of systems. It would only be natural to try to progress from verification, model checking or testing a system against its formal specification into constructing it automatically. Classical algorithmic synthesis theory provides interesting algorithms but also alarming high complexity and undecidability results. The use of genetic programming, in combination with model checking and testing, provides a powerful heuristic to synthesize programs. The method is not completely automatic, as it is fine tuned by a user that sets up the specification and parameters. It also does not guarantee to always succeed and converge towards a solution that satisfies all the required properties. However, we applied it successfully on quite nontrivial examples and managed to find solutions to hard programming challenges, as well as to improve and to correct code. We describe here several versions of our method for synthesizing sequential and concurrent systems.
Multidimensional finite quantum gravity

We advance a class of unitary higher derivative theories of gravity that realize an ultraviolet completion of Einstein general relativity in any dimension. This range of theories is marked by an entire function, which averts extra degrees of freedom (including poltergeists) and improves the high energy behavior of the loop amplitudes. It is proved that only one-loop divergences survive and the theory can be made super-renormalizable regardless of the spacetime dimension. Moreover, using the Pauli-Villars regularization procedure introduced by Diaz-Troost-van Nieuwenhuizen-van Proeyen (DTPN) and applied to Einstein's gravity by Anselmi, we are able to remove the divergences also at one-loop, making the theory completely finite in any dimension as expected by Anselmi and Asorey-Lopez-Shapiro.
Tsunami generated by a granular collapse down a rough inclined plane

In this letter, we experimentally investigate the collapse of initially dry granular media into water and the subsequent impulse waves. We systematically characterize the influence of the slope angle and the granular material on the initial amplitude of the generated leading wave and the evolution of its amplitude during the propagation. The experiments show that whereas the evolution of the leading wave during the propagation is well predicted by a solution of the linearized Korteweg-de Vries equation, the generation of the wave is more complicated to describe. Our results suggest that the internal properties of the granular media and the interplay with the surrounding fluid are important parameters for the generation of waves at low velocity impacts. Moreover, the amplitude of the leading wave reaches a maximum value at large slope angle. The runout distance of the collapse is also shown to be smaller in the presence of water than under totally dry conditions. This study provides a first insight into tsunamis generated by subaerial landslides at low Froude number.
A microfluidic device to sort capsules by deformability: a numerical study.

Guided by extensive numerical simulations, we propose a microfluidic device that can sort elastic capsules by their deformability. The device consists of a duct embedded with a semi-cylindrical obstacle, and a diffuser which further enhances the sorting capability. We demonstrate that the device can operate reasonably well under changes in the initial position of the capsule. The efficiency of the device remains essentially unaltered under small changes of the obstacle shape (from semi-circular to semi-elliptic cross-section). Confinement along the direction perpendicular to the plane of the device increases its efficiency. This work is the first numerical study of cell sorting by a realistic microfluidic device.
A fast, robust algorithm for power line interference cancellation in neural recording

Power line interference may severely corrupt neural recordings at 50/60 Hz and harmonic frequencies. The interference is usually non-stationary and can vary in frequency, amplitude and phase. To retrieve the gamma-band oscillations at the contaminated frequencies, it is desired to remove the interference without compromising the actual neural signals at the interference frequency bands. In this paper, we present a robust and computationally efficient algorithm for removing power line interference from neural recordings.  The algorithm includes four steps. First, an adaptive notch filter is used to estimate the fundamental frequency of the interference. Subsequently, based on the estimated frequency, harmonics are generated by using discrete-time oscillators, and then the amplitude and phase of each harmonic are estimated by using a modified recursive least squares algorithm. Finally, the estimated interference is subtracted from the recorded data.  The algorithm does not require any reference signal, and can track the frequency, phase and amplitude of each harmonic. When benchmarked with other popular approaches, our algorithm performs better in terms of noise immunity, convergence speed and output signal-to-noise ratio (SNR). While minimally affecting the signal bands of interest, the algorithm consistently yields fast convergence (<100 ms) and substantial interference rejection (output SNR >30 dB) in different conditions of interference strengths (input SNR from −30 to 30 dB), power line frequencies (45–65 Hz) and phase and amplitude drifts. In addition, the algorithm features a straightforward parameter adjustment since the parameters are independent of the input SNR, input signal power and the sampling rate. A hardware prototype was fabricated in a 65 nm CMOS process and tested. Software implementation of the algorithm has been made available for open access at https://github.com/mrezak/removePLI.  The proposed algorithm features a highly robust operation, fast adaptation to interference variations, significant SNR improvement, low computational complexity and memory requirement and straightforward parameter adjustment. These features render the algorithm suitable for wearable and implantable sensor applications, where reliable and real-time cancellation of the interference is desired.
General Wahlquist Metrics in All Dimensions

It is shown that the Wahlquist metric, which is a stationary, axially symmetric perfect fluid solution with �+3p = const., admits a rank-2 generalized closed conformal Killing-Yano tensor with a skew-symmetric torsion. Taking advantage of the presence of such a tensor, we obtain a higherdimensional generalization of the Wahlquist metric in arbitrary dimensions, including a family of vacuum black hole solutions with spherical horizon topology such as Schwarzschild-Tangherlini, Myers-Perry and higher-dimensional Kerr-NUT-(A)dS metrics and a familty of static, spherically symmetric perfect fluid solutions in higher dimensions.
Sequential Complexity as a Descriptor for Musical Similarity

We propose string compressibility as a descriptor of temporal structure in audio, for the purpose of determining musical similarity. Our descriptors are based on computing track-wise compression rates of quantized audio features, using multiple temporal resolutions and quantization granularities. To verify that our descriptors capture musically relevant information, we incorporate our descriptors into similarity rating prediction and song year prediction tasks. We base our evaluation on a dataset of 15 500 track excerpts of Western popular music, for which we obtain 7 800 web-sourced pairwise similarity ratings. To assess the agreement among similarity ratings, we perform an evaluation under controlled conditions, obtaining a rank correlation of 0.33 between intersected sets of ratings. Combined with bag-of-features descriptors, we obtain performance gains of 31.1% and 10.9% for similarity rating prediction and song year prediction. For both tasks, analysis of selected descriptors reveals that representing features at multiple time scales benefits prediction accuracy.
Constraints on modified Newtonian dynamics theories from radio tracking data of the Cassini spacecraft

Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive,  March 4, 2014)The MOdi ed Newtonian Dynamics (MOND) is an attempt to modify the gravitation theory tosolve the Dark Matter problem. This phenomenology is very successful at the galactic level. Themain e ect produced by MOND in the Solar System is called the External Field E ect parametrizedby the parameter Q
Saving Human Lives: What Complexity Science and Information Systems can Contribute

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.
THE MASS-INDEPENDENCE OF SPECIFIC STAR FORMATION RATES IN GALACTIC DISKS

The slope of the star formation rate/stellar mass relation (the SFR “Main Sequence”; SFR–M*) is not quite unity: specific star formation rates (SFR/M*) are weakly but significantly anti-correlated with M*. Here we demonstrate that this trend may simply reflect the well-known increase in bulge mass-fractions—portions of a galaxy not forming stars—with M*. Using a large set of bulge/disk decompositions and SFR estimates derived from the Sloan Digital Sky Survey, we show that re-normalizing SFR by disk stellar mass (sSFRdisk ≡ SFR/M*, disk) reduces the M* dependence of SF efficiency by ∼0.25 dex per dex, erasing it entirely in some subsamples. Quantitatively, we find log sSFRdisk–log M* to have a slope βdisk ∈ [ − 0.20, 0.00] ± 0.02 (depending on the SFR estimator and Main Sequence definition) for star-forming galaxies with M* ⩾ 1010 M☉ and bulge mass-fractions B/T ≲ 0.6, generally consistent with a pure-disk control sample (βcontrol = −0.05 ± 0.04). That 〈SFR/M*, disk〉 is (largely) independent of host mass for star-forming disks has strong implications for aspects of galaxy evolution inferred from any SFR–M* relation, including manifestations of “mass quenching” (bulge growth), factors shaping the star-forming stellar mass function (uniform dlog M*/dt for low-mass, disk-dominated galaxies), and diversity in star formation histories (dispersion in SFR(M*, t)). Our results emphasize the need to treat galaxies as composite systems—not integrated masses—in observational and theoretical work.
Holographic representation of local operators in de Sitter space

Assuming the existence of the dS/CFT correspondence, we construct local scalar fields with $m^2>\left( \frac{d}{2} \right)^2$ in de Sitter space by smearing over conformal field theory operators on the future/past boundary. To maintain bulk micro-causality and recover the bulk Wightman function in the Euclidean vacuum, the smearing prescription must involve two sets of single--trace operators with dimensions $\Delta$ and $d-\Delta$. Thus the local operator prescription in de Sitter space differs from the analytic continuation from the prescription in anti--de Sitter space. Pushing a local operator in the global patch to future/past infinity is shown to lead to an operator relation between single--trace operators in conformal field theories at $\mathcal{I}^\pm$, which can be interpreted as a basis transformation, also identified as the relation between an operator in CFT and its shadow operator. Construction of spin$-s$ gauge field operators is discussed, it is shown that the construction of higher spin gauge fields in de Sitter space is equivalent to constructing scalar fields with specific values of mass parameter $m^2<\left( \frac{d}{2} \right)^2$. An acausal higher spin bulk operator which matches onto boundary higher spin current is constructed. Implementation of the scalar operator constructions in AdS and dS with embedding formalism is briefly described.
Nonlinear stimulated Brillouin scattering in a single-mode optical fiber

We predict and experimentally observe a nonlinear variant of stimulated Brillouin scattering in a single-mode fiber that arises from consideration of higher-order processes for phonon generation. The effect manifests itself at high laser excitation as the appearance of Stokes gain for a detuning equal to half of the conventional Brillouin frequency in the fiber, with no accompanying anti-Stokes absorption at the opposite detuning, and requires counter-propagating pump beams for phase-matching. We believe that this could be a new nonlinear optical effect that has not been observed before.
General relativistic laser interferometric observables of the GRACE-Follow-On mission

We develop a high-precision model for laser ranging interferometric (LRI) observables of the GRACE Follow-On (GRACE-FO) mission. For this, we study the propagation of an electromagnetic wave in the gravitational field in the vicinity of an extended body, in the post-Newtonian approximation of the general theory of relativity. We present a general relativistic model for the phase of a plane wave that accounts for contributions of all the multipoles of the gravitating body, its angular momentum, as well as the contribution of tidal fields produced by external sources. We develop a new approach to model a coherent signal transmission in the gravitational field of the solar system that relies on a relativistic treatment of the phase. We use this approach to describe high-precision interferometric measurements on GRACE-FO and formulate the key LRI observables, namely the phase and phase rate of a coherent laser link between the two spacecraft. We develop a relativistic model for the LRI-enabled range between the two GRACE-FO spacecraft, accurate to less than 1 nm, and a high-precision model for the corresponding range rate, accurate to better than 0.1 nm/s. We also formulate high-precision relativistic models for the double one-way range (DOWR) and DOWR-enabled range rate observables originally used on GRACE and now studied for interferometric measurements on GRACE-FO. Our formulation justifies the basic assumptions behind the design of the GRACE-FO mission and highlights the importance of achieving nearly circular and nearly identical orbits for the GRACE-FO spacecraft.
High-dimensional quantum cryptography with twisted light

Quantum key distribution (QKD) systems often rely on polarization of light for encoding, thus limiting the amount of information that can be sent per photon and placing tight bounds on the error rates that such a system can tolerate. Here we describe a proof-of-principle experiment that indicates the feasibility of high-dimensional QKD based on the transverse structure of the light field allowing for the transfer of more than 1 bit per photon. Our implementation uses the orbital angular momentum (OAM) of photons and the corresponding mutually unbiased basis of angular position (ANG). Our experiment uses a digital micro-mirror device for the rapid generation of OAM and ANG modes at 4 kHz, and a mode sorter capable of sorting single photons based on their OAM and ANG content with a separation efficiency of 93%. Through the use of a seven-dimensional alphabet encoded in the OAM and ANG bases, we achieve a channel capacity of 2.05 bits per sifted photon. Our experiment demonstrates that, in addition to having an increased information capacity, multilevel QKD systems based on spatial-mode encoding can be more resilient against intercept-resend eavesdropping attacks.
Nested Regular Path Queries in Description Logics (Extended Abstract)

Two-way regular path queries (2RPQs) have received increased attention recently due to their ability to relate pairs of objects by flexibly navigating graph-structured data. They are present in property paths in SPARQL 1.1, the new standard RDF query language, and in the XML query language XPath. In line with XPath, we consider the extension of 2RPQs with nesting, which allows one to require that objects along a path satisfy complex conditions, in turn expressed through (nested) 2RPQs. We study the computational complexity of answering nested 2RPQs and conjunctions thereof (CN2RPQs) in the presence of domain knowledge expressed in description logics (DLs). We establish tight complexity bounds in data and combined complexity for a variety of DLs, ranging from lightweight DLs (DL-Lite, EL) up to highly expressive ones. Interestingly, we are able to show that adding nesting to (C)2RPQs does not affect worst-case data complexity of query answering for any of the considered DLs. However, in the case of lightweight DLs, adding nesting to 2RPQs leads to a surprising jump in combined complexity, from P-complete to EXP-complete.
Search for Low-Mass WIMPs with SuperCDMS

We report a first search for weakly interacting massive particles (WIMPs) using the background rejection capabilities of SuperCDMS. An exposure of 577 kg-days was analyzed for WIMPs with mass < 30 GeV/c2, with the signal region blinded. Eleven events were observed after unblinding. We set an upper limit on the spin-independent WIMP-nucleon cross section of 1.2e-42 cm2 at 8 GeV/c2. This result is in tension with WIMP interpretations of recent experiments and probes new parameter space for WIMP-nucleon scattering for WIMP masses < 6 GeV/c2.
Two Stage Prediction Process with Gradient Descent Methods Aligning with the Data Privacy Preservation

Privacy preservation emphasize on authorization of data, which signiﬁes that data should be accessed onlyby authorized users. Ensuring the privacy of data is considered as one of the challenging task in datamanagement. The generalization of data with varying concept hierarchies seems to be interesting solution.This paper proposes two stage prediction processes on privacy preserved data. The privacy is preservedusing generalization and betraying other communicating parties by disguising generalized data which addsanother level of privacy. The generalization with betraying is performed in ﬁrst stage to deﬁne the knowledgeor hypothesis and which is further optimized using gradient descent method in second stage prediction foraccurate prediction of data. The experiment is carried with both batch and stochastic gradient methodsand it is shown that bulk operation performed by batch takes long time and more iterations than stochasticto give more accurate solution. Batch Gradient, Gradient Descent, RDF and Ontology, Stochastic Gradient.
Mathematical Model of Semantic Look - An Efficient Context Driven Search Engine

The WorldWideWeb (WWW) is a huge conservatory of web pages. Search Engines are key applications that fetch web pages for the user query. In the current generation web architecture, search engines treat keywords provided by the user as isolated keywords without considering the context of the user query. This results in a lot of unrelated pages or links being displayed to the user. Semantic Web is based on the current web with a revised framework to display a more precise result set as response to a user query. The current web pages need to be annotated by finding relevant meta data to be added to each of them, so that they become useful to Semantic Web search engines. Semantic Look explores the context of user query by processing the Semantic information recorded in the web pages. It is compared with an existing algorithm called OntoLook and it is shown that Semantic Look is a better optimized search engine by being more than twice as fast as OntoLook.
Large-Scale Molecular Dynamics Simulations for Highly Parallel Infrastructures

Computational chemistry allows researchers to experiment in sillico: by running a computer simulations of a biological or chemical processes of interest. Molecular dynamics with molecular mechanics model of interactions simulates N-body problem of atoms$-$it computes movements of atoms according to Newtonian physics and empirical descriptions of atomic electrostatic interactions. These simulations require high performance computing resources, as evaluations within each step are computationally demanding and billions of steps are needed to reach interesting timescales. Current methods decompose the spatial domain of the problem and calculate on parallel/distributed infrastructures. Even the methods with the highest strong scaling hit the limit at half a million cores: they are not able to cut the time to result if provided with more processors. At the dawn of exascale computing with massively parallel computational resources, we want to increase the level of parallelism by incorporating parallel-in-time computation to molecular dynamics simulations. Calculation of results in several successive time points simultaneously without a priori knowledge has been examined with no major success. We will study and implement a novel combinations of methods that according to our theoretical analyses should achieve promising speed-up compared to sequential-in-time calculation.