nils-herrmann/clean_scirepeval huggingface dataset:
A holistic view on hyper-dense heterogeneous and small cell networks

The wireless industry has been experiencing an explosion of data traffic usage in recent years and is now facing an even bigger challenge, an astounding 1000-fold data traffic increase in a decade. The required traffic increase is in bits per second per square kilometer, which is equivalent to bits per second per Hertz per cell × Hertz × cell per square kilometer. The innovations through higher utilization of the spectrum (bits per second per Hertz per cell) and utilization of more bandwidth (Hertz) are quite limited: spectral efficiency of a point-to-point link is very close to the theoretical limits, and utilization of more bandwidth is a very costly solution in general. Hyper-dense deployment of heterogeneous and small cell networks (HetSNets) that increase cells per square kilometer by deploying more cells in a given area is a very promising technique as it would provide a huge capacity gain by bringing small base stations closer to mobile devices. This article presents a holistic view on hyperdense HetSNets, which include fundamental preference in future wireless systems, and technical challenges and recent technological breakthroughs made in such networks. Advancements in modeling and analysis tools for hyper-dense HetSNets are also introduced with some additional interference mitigation and higher spectrum utilization techniques. This article ends with a promising view on the hyper-dense HetSNets to meet the upcoming 1000× data challenge.
Mind the Traps! Design Guidelines for Rigorous BCI Experiments

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Mind the Traps! Design Guidelines for Rigorous BCI Experiments Camille Jeunet, Stefan Debener, Fabien Lotte, Jeremie Mattout, Reinhold Scherer, Catharina Zich
Running in cheetahs, gazelles, and goats: energy cost and limb configuration.

BAHARAV, AND ARIEH BORUT. Running in cheetahs, gazelles, and goats: energy cost and limb conjguration.  1974.-Functional anatomists have argued that an animal can be built to run cheaply by lightening the distal parts of the limbs and/or by concentrating the muscle mass of the limbs around their pivot points. These arguments assume .that much of the energy expended as animals run at a constant speed goes into alternately accelerating and decelerating the limbs. Gazelles, goats, and cheetahs offer a nice gradation of limb configurations in animals of similar total mass and limb length and, therefore, provide the opportunity to quantify the effect of limb design on the energy cost of running. We found that, despite large differences in limb configuration, the energetic cost of running in cheetahs, gazelles, and goats of about the same mass was nearly identical over a wide range of speeds. Also, the observed energetic cost of running was almost the same as that predicted on the basis of body weight for all three species: cheetah, 0.14 ml 02 (g l km)-’ observed vs. 0.13 ml 02 (g *km)-l predicted; gazelle, 0.16 ml 02 (g *km)-’ observed vs. 0.15 ml 02 (g *km)-’ predicted; and goat, 0.18 ml 02 (g . km)-’ observed vs. 0.14 ml 02 (g *km)-’ predicted. Thus the relationship between body weight and energetic cost of running apparently applies to animals with very different limb configurations and is more general than anticipated. This suggests that most of the energy expended in running at a constant speed is not used to accelerate and decelerate the limbs.
Priority based dynamic resource allocation in Cloud computing with modified waiting queue

Today Cloud computing is on demand as it offers dynamic flexible resource allocation, for reliable and guaranteed services in pay-as-you-use manner, to Cloud service users. So there must be a provision that all resources are made available to requesting users in efficient manner to satisfy their needs. This resource provision is done by considering the Service Level Agreements (SLA) and with the help of parallel processing. Recent work considers various strategies with single SLA parameter. Hence by considering multiple SLA parameter and resource allocation by preemption mechanism for high priority task execution can improve the resource utilization in Cloud. In this paper we propose an algorithm which considered Preemptable task execution and multiple SLA parameters such as memory, network bandwidth, and required CPU time. An obtained experimental results show that in a situation where resource contention is fierce our algorithm provides better utilization of resources.
Development and initial validation of an implicit measure of humility relative to arrogance

Data from two studies describe the development of an implicit measure of humility and support the idea that dispositional humility is a positive quality with possible benefits. In Study 1, 135 college students completed Humility and Self-Esteem Implicit Association Tests (IATs) and several self-report measures of personality self-concept. Fifty-four participants also completed the Humility IAT again approximately 2 weeks later and their humility was rated by close acquaintances. The Humility IAT was found to be internally and temporally consistent. Implicit humility correlated with self-reported humility relative to arrogance, implicit self-esteem, and narcissism (inversely). Humility was not associated with self-reported low selfesteem, pessimism, or depression. In fact, self-reported humility relative to arrogance correlated positively with self-reported self-esteem, gratitude, forgiveness, spirituality, and general health. In addition, self-reported humility and acquaintancerated humility correlated positively; however, implicit humility and acquaintance-rated humility were not strongly associated. In Study 2, to examine the idea that humility might be associated with increased academic performance, we examined actual course grades of 55 college students who completed Humility and Self-Esteem IATs. Implicit humility correlated positively with higher actual course grades when narcissism, conscientiousness, and implicit self-esteem were simultaneously controlled. Implications and future research directions are discussed.
Drosophila melanogaster γ-TuRC is dispensable for targeting γ-tubulin to the centrosome and microtubule nucleation

In metazoans, gamma-tubulin acts within two main complexes, gamma-tubulin small complexes (gamma-TuSCs) and gamma-tubulin ring complexes (gamma-TuRCs). In higher eukaryotes, it is assumed that microtubule nucleation at the centrosome depends on gamma-TuRCs, but the role of gamma-TuRC components remains undefined. For the first time, we analyzed the function of all four gamma-TuRC-specific subunits in Drosophila melanogaster: Dgrip75, Dgrip128, Dgrip163, and Dgp71WD. Grip-motif proteins, but not Dgp71WD, appear to be required for gamma-TuRC assembly. Individual depletion of gamma-TuRC components, in cultured cells and in vivo, induces mitotic delay and abnormal spindles. Surprisingly, gamma-TuSCs are recruited to the centrosomes. These defects are less severe than those resulting from the inhibition of gamma-TuSC components and do not appear critical for viability. Simultaneous cosilencing of all gamma-TuRC proteins leads to stronger phenotypes and partial recruitment of gamma-TuSC. In conclusion, gamma-TuRCs are required for assembly of fully functional spindles, but we suggest that gamma-TuSC could be targeted to the centrosomes, which is where basic microtubule assembly activities are maintained.
Rates of Dinosaur Body Mass Evolution Indicate 170 Million Years of Sustained Ecological Innovation on the Avian Stem Lineage

Large-scale adaptive radiations might explain the runaway success of a minority of extant vertebrate clades. This hypothesis predicts, among other things, rapid rates of morphological evolution during the early history of major groups, as lineages invade disparate ecological niches. However, few studies of adaptive radiation have included deep time data, so the links between extant diversity and major extinct radiations are unclear. The intensively studied Mesozoic dinosaur record provides a model system for such investigation, representing an ecologically diverse group that dominated terrestrial ecosystems for 170 million years. Furthermore, with 10,000 species, extant dinosaurs (birds) are the most speciose living tetrapod clade. We assembled composite trees of 614-622 Mesozoic dinosaurs/birds, and a comprehensive body mass dataset using the scaling relationship of limb bone robustness. Maximum-likelihood modelling and the node height test reveal rapid evolutionary rates and a predominance of rapid shifts among size classes in early (Triassic) dinosaurs. This indicates an early burst niche-filling pattern and contrasts with previous studies that favoured gradualistic rates. Subsequently, rates declined in most lineages, which rarely exploited new ecological niches. However, feathered maniraptoran dinosaurs (including Mesozoic birds) sustained rapid evolution from at least the Middle Jurassic, suggesting that these taxa evaded the effects of niche saturation. This indicates that a long evolutionary history of continuing ecological innovation paved the way for a second great radiation of dinosaurs, in birds. We therefore demonstrate links between the predominantly extinct deep time adaptive radiation of non-avian dinosaurs and the phenomenal diversification of birds, via continuing rapid rates of evolution along the phylogenetic stem lineage. This raises the possibility that the uneven distribution of biodiversity results not just from large-scale extrapolation of the process of adaptive radiation in a few extant clades, but also from the maintenance of evolvability on vast time scales across the history of life, in key lineages.
Grading and Classification of Anthracnose Fungal Disease of Fruits based on Statistical Texture Features

In this paper, lesion areas affected by anthracnose are segmented using segmentation techniques, graded based on percentage of affected area and neural network classifier is used to classify normal and anthracnose affected on fruits. We have considered three types of fruit namely mango, grape and pomegranate for our work. The developed processing scheme consists of two phases. In the first phase, segmentation techniques namely thresholding, region growing, K-means clustering and watershed are employed for separating anthracnose affected lesion areas from normal area. Then these affected areas are graded by calculating the percentage of affected area. In the second phase texture features are extracted using Runlength Matrix. These features are then used for classification purpose using ANN classifier. We have conducted experimentation on a dataset of 600 fruits’ image samples. The classification accuracies for normal and affected anthracnose fruit types are 84.65% and 76.6% respectively. The work finds application in developing a machine vision system in horticulture field.
Performance of Medium-Voltage DC-Bus PV System Architecture Utilizing High-Gain DC–DC Converter

The number of large-scale solar photovoltaic (PV) systems continues to increase, while the size of the largest systems has already reached several hundred megawatts. This trend will challenge existing PV system architectures and will require new PV system architectures with higher power ratings and higher voltage levels at the point of common coupling (PCC). This paper reports a medium-voltage (MV) dc-bus PV system architecture based on a high-gain soft-switched interleaved boost (SSIB) dc-dc converter. The interleaved characteristic increases the flexibility of the converter, allowing for either a higher voltage and/or current rating, thus increasing the power rating of the converter. The high-gain capability of the SSIB converter allows it to be connected directly to an MV dc bus. This will facilitate direct connection of a PV system to an MV ac grid (i.e., 20 kV) using only one step-up transformer. Simulation and experimental results are presented to verify the operation of the SSIB converter and to confirm the steady-state and dynamic performance of the proposed PV system architecture.
Analysis of a “/0” Stealth Scan From a Botnet

Botnets are the most common vehicle of cyber-criminal activity. They are used for spamming, phishing, denial of service attacks, brute-force cracking, stealing private information, and cyber warfare. Botnets carry out network scans for several reasons, including searching for vulnerable machines to infect and recruit into the botnet, probing networks for enumeration or penetration, etc. We present the measurement and analysis of a horizontal scan of the entire IPv4 address space conducted by the Sality botnet in February of last year. This 12-day scan originated from approximately 3 million distinct IP addresses, and used a heavily coordinated and unusually covert scanning strategy to try to discover and compromise VoIP-related (SIP server) infrastructure. We observed this event through the UCSD Network Telescope, a /8 darknet continuously receiving large amounts of unsolicited traffic, and we correlate this traffic data with other public sources of data to validate our inferences. Sality is one of the largest botnets ever identified by researchers, its behavior represents ominous advances in the evolution of modern malware: the use of more sophisticated stealth scanning strategies by millions of coordinated bots, targeting critical voice communications infrastructure. This work offers a detailed dissection of the botnet's scanning behavior, including general methods to correlate, visualize, and extrapolate botnet behavior across the global Internet.
Electrical properties of breast cancer cells from impedance measurement of cell suspensions

Impedance spectroscopy of biological cells has been used to monitor cell status, e.g. cell proliferation, viability, etc. It is also a fundamental method for the study of the electrical properties of cells which has been utilised for cell identification in investigations of cell behaviour in the presence of an applied electric field, e.g. electroporation. There are two standard methods for impedance measurement on cells. The use of microelectrodes for single cell impedance measurement is one method to realise the measurement, but the variations between individual cells introduce significant measurement errors. Another method to measure electrical properties is by the measurement of cell suspensions, i.e. a group of cells within a culture medium or buffer. This paper presents an investigation of the impedance of normal and cancerous breast cells in suspension using the Maxwell-Wagner mixture theory to analyse the results and extract the electrical parameters of a single cell. The results show that normal and different stages of cancer breast cells can be distinguished by the conductivity presented by each cell.
Scalable Online Convolutional Sparse Coding

Convolutional sparse coding (CSC) improves sparse coding by learning a shift-invariant dictionary from the data. However, most existing CSC algorithms operate in the batch mode and are computationally expensive. In this paper, we alleviate this problem by online learning. The key is a reformulation of the CSC objective so that convolution can be handled easily in the frequency domain, and much smaller history matrices are needed. To solve the resultant optimization problem, we use the alternating direction method of multipliers (ADMMs), and its subproblems have efficient closed-form solutions. Theoretical analysis shows that the learned dictionary converges to a stationary point of the optimization problem. Extensive experiments are performed on both the standard CSC benchmark data sets and much larger data sets such as the ImageNet. Results show that the proposed algorithm outperforms the state-of-the-art batch and online CSC methods. It is more scalable, has faster convergence, and better reconstruction performance.
Acoustic echo suppression based on speech presence probability

This paper proposes a novel acoustic echo suppression (AES) algorithm based on speech presence probability in a frequency domain. Double talk detection algorithm based on two cross-correlation coefficients modeled by Beta distribution controls the update of echo path response to improve the quality of near-end speech. The near-end speech presence probability combined with the Wiener gain function is used to reduce the residual echo. The performance of the proposed algorithm is evaluated by objective tests. High echo-return-loss enhancement and perceptual evaluation of speech quality (PESQ) scores are obtained by comparing with the conventional AES method.
Dangers of a fixed mindset: implications of self-theories research for computer science education

Psychology studies have shown that students' beliefs about their own intelligence--whether they view intelligence as fixed or malleable-have an important influence on student development and achievement. Yet the impact of these theories on success in Computer Science (CS) has not been directly investigated. Self-theories research has shown that students with a fixed mindset are more likely to exhibit a helpless response to substantial challenges and to experience decreases in self-esteem during college. Those with a growth mindset welcome challenges, displaying a mastery-oriented response, and maintaining self-esteem, primarily because they attribute failure to a lack of effort rather than a lack of intellectual ability. This paper introduces self-theories research, and relates this research to several issues in CS Education. We then make suggestions for how CS educators can consider self-theories in their teaching and research.
Concept of wearable folded half-mode cavity antenna

The half-mode cavity antenna is a typical design of half-size resonator antennas suitable for wearable applications. Based on a classical cavity model, a basic rectangular half-mode cavity antenna is designed for operation at 2.45 GHz. Interestingly, the simulation results show that the antenna has stable performance even when subjected to 180° bending around an axis parallel the direction of the radiating aperture. On that basis, the concept of a folded rectangular half-mode cavity antenna is proposed with a practical feeding method. The S11 curves, internal E-field distributions and radiation patterns of the planar and folded rectangular half-mode cavity antennas are compared using full-wave electromagnetic simulations.
Elastic modulus of tree frog adhesive toe pads

Previous work using an atomic force microscope in nanoindenter mode indicated that the outer, 10- to 15-μm thick, keratinised layer of tree frog toe pads has a modulus of elasticity equivalent to silicone rubber (5–15 MPa) (Scholz et al. 2009), but gave no information on the physical properties of deeper structures. In this study, micro-indentation is used to measure the stiffness of whole toe pads of the tree frog, Litoria caerulea. We show here that tree frog toe pads are amongst the softest of biological structures (effective elastic modulus 4–25 kPa), and that they exhibit a gradient of stiffness, being stiffest on the outside. This stiffness gradient results from the presence of a dense network of capillaries lying beneath the pad epidermis, which probably has a shock absorbing function. Additionally, we compare the physical properties (elastic modulus, work of adhesion, pull-off force) of the toe pads of immature and adult frogs.
Redescription of Skrjabinodon medinae (García-Calvente, 1948) (Nematoda: Pharyngodonidae) from the cloaca of Podarcis pityusensis (Bosca, 1883) (Sauria: Lacertidae) of the Balearic Islands (Spain)

Pharyngodon medinae García-Calvente, 1948 (Nematoda: Pharyngodonidae) is redescribed from Podarcis pityusensis (Bosca, 1883) (Sauria: Lacertidae) of the Balearic Islands (Spain) and confirmed as a member of the genus Skrjabinodon Inglis, 1968. A systematic review of S. medinae and closely related species is also given. Parathelandros canariensis is referred to Skrjabinodon as a new combination and Parathelandros Magzoub et al., 1980 is dismissed as a junior homonym of Parathelandros Baylis, 1930.
A Growing Neural Gas Network Learns Topologies

An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebb-like learning rule. In contrast to previous approaches like the "neural gas" method of Martinetz and Schulten (1991, 1994), this model has no parameters which change over time and is able to continue learning, adding units and connections, until a performance criterion has been met. Applications of the model include vector quantization, clustering, and interpolation.
Closed-loop Servoing using Real-time Markerless Arm Tracking

We present a simple, efficient method of realtime articulated arm pose estimation using stochastic gradient descent to correct unmodeled errors in the robot’s kinematics with point cloud data from commercial depth sensors. We show that our method is robust to error in both the robot’s joint encoders and in the extrinsic calibration of the sensor; and that it is both fast and accurate enough to provide realtime performance for autonomous manipulation tasks. The efficiency of our technique allows us to embed it in a closedloop position servoing strategy; which we extensively use to perform manipulation tasks. Our method is generalizable to any articulated robot, including dexterous humanoids and mobile manipulators with multiple kinematic chains.
Conceptualizing Creativity: From Distributional Semantics to Conceptual Spaces

This paper puts forth a method for discovering computationally-derived conceptual spaces that reflect human conceptualization of musical and poetic creativity. We describe a lexical space that is defined through co-occurrence statistics, and compare the dimensions of this space with human responses on a word association task. Participants’ responses serve as external validation of our computational findings, and frequent terms are also used as input dimensions for creating mappings from the linguistic to the conceptual domain. This novel method finds low-dimensional subspaces that represent particular conceptual regions within a vector space model of distributional semantics. Word-vectors from these discovered conceptual spaces are considered, and argued to be useful for the evaluation of creativity and creative artifacts within computational creativity.