nils-herrmann/clean_scirepeval huggingface dataset:
Mirror neurons: from discovery to autism

In the winter of 1991 I (GR) sent to Nature a report on a surprising set of neurons that we (Giuseppe Di Pellegrino, Luciano Fadiga, Leonardo Fogassi, Vittorio Gallese) had found in the ventral premotor cortex of the monkey. The fundamental characteristic of these neurons was that they discharged both when the monkey performed a certain motor act (e.g., grasping an object) and when it observed another individual (monkey or human) performing that or a similar motor act (Di Pellegrino et al. 1992). These neurons are now known as mirror neurons . Nature rejected our paper for its “lack of general interest” and suggested publication in a specialized journal. At this point I called Prof. Otto Creutzfeld, the then Coordinating Editor of Experimental Brain Research. I told him that I thought we found something really interesting and asked him to read our manuscript before sending it to the referees. After a few days he called me back saying that indeed our Wndings were, according to him, of extraordinary interest. Our article appeared in Experimental Brain Research a few months later. The idea of sending our report on mirror neurons to Experimental Brain Research, rather than to another neuroscience journal, was motivated by a previous positive experience with that journal. A few years earlier, Experimental Brain Research accepted an article in which we presented (Rizzolatti et al. 1988) a new view (something that typically referees did not like) on the organization of the ventral premotor cortex of the monkey and reported the Wndings that paved the way for the discovery of mirror neurons. In that article we described how, in the ventral premotor cortex (area F5) of the monkey, there are neurons that respond both when the monkey performs a motor act (e.g., grasping or holding) and when it observes an object whose physical features Wt the type of grip coded by that neuron (e.g., precision grip/small objects; whole hand/large objects). These neurons (now known as “canonical neurons”, Murata et al. 1997) and neurons with similar properties, described by Sakata et al. (1995) in the parietal cortex are now universally considered the neural substrate of the mechanism through which object aVordances are translated into motor acts (see Jeannerod et al. 1995). We performed the experiments on the motor properties of F5 in 1988 using an approach that should almost necessarily lead to the discovery of mirror neurons if these neurons existed in area F5. In order to test the F5 neurons with objects that may interest the monkeys, we used pieces of food of diVerent size and shape. To give the monkey some food, we had, of course, to grasp it. To our surprise we found that some F5 neurons discharged not when the monkey looked at the food, but when the experimenter grasped it. The mirror mechanism was discovered. The next important role of Experimental Brain Research in the discovery of mirror neurons was its acceptance in G. Rizzolatti (&) · M. Fabbri-Destro Dipartimento di Neuroscienze, Sezione Fisiologia, Università di Parma, via Volturno, 39, 43100 Parma, Italy e-mail: giacomo.rizzolatti@unipr.it
Zero-Inflated Exponential Family Embeddings

Word embeddings are a widely-used tool to analyze language, and exponential family embeddings (Rudolph et al., 2016) generalize the technique to other types of data. One challenge to fitting embedding methods is sparse data, such as a document/term matrix that contains many zeros. To address this issue, practitioners typically downweight or subsample the zeros, thus focusing learning on the non-zero entries. In this paper, we develop zero-inflated embeddings, a new embedding method that is designed to learn from sparse observations. In a zero-inflated embedding (ZIE), a zero in the data can come from an interaction to other data (i.e., an embedding) or from a separate process by which many observations are equal to zero (i.e. a probability mass at zero). Fitting a ZIE naturally downweights the zeros and dampens their influence on the model. Across many types of data— language, movie ratings, shopping histories, and bird watching logs—we found that zero-inflated embeddings provide improved predictive performance over standard approaches and find better vector representation of items.
Factors of Transferability for a Generic ConvNet Representation

Evidence is mounting that Convolutional Networks (ConvNets) are the most effective representation learning method for visual recognition tasks. In the common scenario, a ConvNet is trained on a large labeled dataset (source) and the feed-forward units activation of the trained network, at a certain layer of the network, is used as a generic representation of an input image for a task with relatively smaller training set (target). Recent studies have shown this form of representation transfer to be suitable for a wide range of target visual recognition tasks. This paper introduces and investigates several factors affecting the transferability of such representations. It includes parameters for training of the source ConvNet such as its architecture, distribution of the training data, etc. and also the parameters of feature extraction such as layer of the trained ConvNet, dimensionality reduction, etc. Then, by optimizing these factors, we show that significant improvements can be achieved on various (17) visual recognition tasks. We further show that these visual recognition tasks can be categorically ordered based on their similarity to the source task such that a correlation between the performance of tasks and their similarity to the source task w.r.t. the proposed factors is observed.
SensorScope: Application-specific sensor network for environmental monitoring

SensorScope is a turnkey solution for environmental monitoring systems, based on a wireless sensor network and resulting from a collaboration between environmental and network researchers. Given the interest in climate change, environmental monitoring is a domain where sensor networks will have great impact by providing high resolution spatio-temporal data for long periods of time. SensorScope is such a system, which has already been successfully deployed multiple times in various environments (e.g., mountainous, urban). Here, we describe the overall hardware and software architectures and especially focus on the sensor network itself. We also describe one of our most prominent deployments, on top of a rock glacier in Switzerland, which resulted in the description of a micro-climate phenomenon leading to cold air release from a rock-covered glacier in a region of high alpine risks. Another focus of this paper is the description of what happened behind the scenes to turn SensorScope from a laboratory experiment into successful outdoor deployments in harsh environments. Illustrated by various examples, we point out many lessons learned while working on the project. We indicate the importance of simple code, well suited to the application, as well as the value of close interaction with end-users in planning and running the network and finally exploiting the data.
Annual Report Readability , Current Earnings , and Earnings Persistence ∗

This paper examines the relationship between annual report readability and firm performance and earnings persistence. This is motivated by the Securities and Exchange Commission’s plain English disclosure regulations that attempt to make corporate disclosures easier to read for ordinary investors. I measure the readability of public company annual reports using both the Fog Index from computational linguistics and the length of the document. I find that the annual reports of firms with lower earnings are harder to read (i.e., they have higher Fog and are longer). Moreover, the positive earnings of firms with annual reports that are easier to read are more persistent. This suggests that managers may be opportunistically choosing the readability of annual reports to hide adverse information from investors.
The Static Driver Verifier Research Platform

The Sdv Research Platform (Sdvrp) is a new academic release of Static Driver Verifier (Sdv) and the Slam software model checker that contains: (1) a parameterized version of Sdv that allows one to write custom API rules for APIs independent of device drivers; (2) thousands of Boolean programs generated by Sdv in the course of verifying Windows device drivers, including the functional and performance results (of the Bebop model checker) and test scripts to allow comparison against other Boolean program model checkers; (3) a new version of the Slam analysis engine, called Slam2, that is much more robust and performant.
From One-Trick Ponies to All-Rounders: On-Demand Learning for Image Restoration

While machine learning approaches to image restoration offer great promise, current methods risk training “onetrick ponies” that perform well only for image corruption of a particular level of difficulty—such as a certain level of noise or blur. First, we examine the weakness of a one-trick pony model and demonstrate that training general models to handle arbitrary levels of corruption is indeed non-trivial. Then, we propose an on-demand learning algorithm for training image restoration models with deep convolutional neural networks. The main idea is to exploit a feedback mechanism to self-generate training instances where they are needed most, thereby learning models that can generalize across difficulty levels. On four restoration tasks—image inpainting, pixel interpolation, image deblurring, and image denoising—and three diverse datasets, our approach consistently outperforms both the status quo training procedure and curriculum learning alternatives.
Axial Ratio Bandwidth Enhancement of 60-GHz Substrate Integrated Waveguide-Fed Circularly Polarized LTCC Antenna Array

A substrate integrated waveguide (SIW)-fed circularly polarized (CP) antenna array with a broad bandwidth of axial ratio (AR) is presented for 60-GHz wireless personal area networks (WPAN) applications. The widened AR bandwidth of an antenna element is achieved by positioning a slot-coupled rotated strip above a slot cut onto the broadwall of an SIW. A 4 × 4 antenna array is designed and fabricated using low temperature cofired ceramic (LTCC) technology. A metal-topped via fence is introduced around the strip to reduce the mutual coupling between the elements of the array. The measured results show that the AR bandwidth is more than 7 GHz. A stable boresight gain is greater than 12.5 dBic across the desired bandwidth of 57-64 GHz.
Financial Statement Fraud Detection by Data Mining

-------------------------------------------------------------------ABSTRACT---------------------------------------------------------------------Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will usually find ways to circumvent such measures. Detecting fraud is essential once prevention mechanism has failed. Several data mining algorithms have been developed that allow one to extract relevant knowledge from a large amount of data like fraudulent financial statements to detect FSF. It is an attempt to detect FSF ; We present a generic framework to do our analysis.
The influence of a sense of time on human development.

The subjective sense of future time plays an essential role in human motivation. Gradually, time left becomes a better predictor than chronological age for a range of cognitive, emotional, and motivational variables. Socioemotional selectivity theory maintains that constraints on time horizons shift motivational priorities in such a way that the regulation of emotional states becomes more important than other types of goals. This motivational shift occurs with age but also appears in other contexts (for example, geographical relocations, illnesses, and war) that limit subjective future time.
Busbar design for SiC-based H-bridge PEBB using 1.7 kV, 400 a SiC MOSFETs operating at 100 kHz

This paper presents a systematic study of the busbar design and optimization for SiC-based H-bridge power electronics building block (PEBB) used in high-frequency and high-power applications. Step-by-step guidelines are presented in which the design considerations and analysis are given. This paper presents a double-sided busbar concept to create a compact PEBB design with improved thermal and switching performance, which result from having double-side cooling and symmetric minimized current commutation loop inductances, respectively. The proposed concept is verified experimentally by evaluating the high-speed switching performance of the PEBB up to 400 A.
Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval

The World Wide Web (WWW) is becoming one of the most preferred and widespread mediums of learning. Unfortunately, most of the current Web-based learning systems are still delivering the same educational resources in the same way to learners with different profiles. A number of past efforts have dealt with e-learning personalization, generally, relying on explicit information. In this paper, we aim to compute on-line automatic recommendations to an active learner based on his/her recent navigation history, as well as exploiting similarities and dissimilarities among user preferences and among the contents of the learning resources. First we start by mining learner profiles using Web usage mining techniques and content-based profiles using information retrieval techniques. Then, we use these profiles to compute relevant links to recommend for an active learner by applying a number of different recommendation strategies.
An Extensor Mechanism for an Anatomical Robotic Hand

The human finger possesses a structure called the extensor mechanism, a web-like collection of tendinous material that lies on the dorsal side of each finger and connects the controlling muscles to the bones of the finger. In past robotic hand designs, extensor mechanisms have generally not been employed due in part to their complexity and a lack of understanding of their utility. This paper presents our first design and analysis effort of an artificial extensor mechanism. The goal of our analysis is to provide an understanding of the extensor mechanism’s functionality so that we can extract the crucial features that need to be mimicked to construct an anatomical robotic hand. With the inclusion of an extensor mechanism, we believe all possible human finger postures can be achieved using four cable driven actuators. We identified that this extensor mechanism gives independent control of the metacarpo-phalangeal (MCP) joint and acts not only as an extensor but also as a flexor, abductor, adductor, or rotator depending on the finger’s posture.
Credit Scoring Models Using Soft Computing Methods: A Survey

During the last fifteen years, soft computing methods have been successfully applied in building powerful and flexible credit scoring models and have been suggested to be a possible alternative to statistical methods. In this survey, the main soft computing methods applied in credit scoring models are presented and the advantages as well as the limitations of each method are outlined. The main modelling issues are discussed especially from the data mining point of view. The study concludes with a series of suggestions of other methods to be investigated for credit scoring modelling.
Automated characterization of blood vessels as arteries and veins in retinal images

In recent years researchers have found that alternations in arterial or venular tree of the retinal vasculature are associated with several public health problems such as diabetic retinopathy which is also the leading cause of blindness in the world. A prerequisite for automated assessment of subtle changes in arteries and veins, is to accurately separate those vessels from each other. This is a difficult task due to high similarity between arteries and veins in addition to variation of color and non-uniform illumination inter and intra retinal images. In this paper a novel structural and automated method is presented for artery/vein classification of blood vessels in retinal images. The proposed method consists of three main steps. In the first step, several image enhancement techniques are employed to improve the images. Then a specific feature extraction process is applied to separate major arteries from veins. Indeed, vessels are divided to smaller segments and feature extraction and vessel classification are applied to each small vessel segment instead of each vessel point. Finally, a post processing step is added to improve the results obtained from the previous step using structural characteristics of the retinal vascular network. In the last stage, vessel features at intersection and bifurcation points are processed for detection of arterial and venular sub trees. Ultimately vessel labels are revised by publishing the dominant label through each identified connected tree of arteries or veins. Evaluation of the proposed approach against two different datasets of retinal images including DRIVE database demonstrates the good performance and robustness of the method. The proposed method may be used for determination of arteriolar to venular diameter ratio in retinal images. Also the proposed method potentially allows for further investigation of labels of thinner arteries and veins which might be found by tracing them back to the major vessels.
Multilevel Energy Management System for Hybridization of Energy Storages in DC Microgrids

Hybridization of energy storages (ESs) with different ramp rates helps minimization of system bus voltage variation and extension of ESs lifetime in dc microgrids. Hybrid ES system (HESS) control is normally realized with centralized coordination. In this paper, HESS distributed control, which is independent of the communication link, is proposed to enhance system reliability. All ESs are configured as slack terminals to regulate system bus voltage with droop control. System net power decomposition and ESs power sharing are realized with localized low-pass filter (LPF) applied to ESs with low-ramp rates. The relationship between LPF cut-off frequency and ES ramp rate is elaborated in detail. However, bus voltage deviation and power tracking errors are the main drawbacks of HESS distributed control. Multilevel energy management system (EMS) is thus proposed to enhance system control accuracy. HESS distributed control is scheduled as the primary control. Bus voltage restoration and power sharing compensation are applied in secondary control to eliminate the voltage deviation and power tracking errors, respectively. In tertiary control, autonomous state of charge (SoC) recovery is implemented to limit SoC variation of ES with high-ramp rate. A lab-scale dc microgrid is developed to verify the proposed multilevel EMS for HESS control.
QurAna: Corpus of the Quran annotated with Pronominal Anaphora

This paper presents QurAna: a large corpus created from the original Quranic text, where personal pronouns are tagged with their antecedence. These antecedents are maintained as an ontological list of concepts, which has proved helpful for information retrieval tasks. QurAna is characterized by: (a) comparatively large number of pronouns tagged with antecedent information (over 24,500 pronouns), and (b) maintenance of an ontological concept list out of these antecedents. We have shown useful applications of this corpus. This corpus is the first of its kind covering Classical Arabic text, and could be used for interesting applications for Modern Standard Arabic as well. This corpus will enable researchers to obtain empirical patterns and rules to build new anaphora resolution approaches. Also, this corpus can be used to train, optimize and evaluate existing approaches.
UrbanSim : Modeling Urban Development for Land Use , Transportation and Environmental Planning

Metropolitan areas have come under intense pressure to respond to federal mandates to link planning of land use, transportation, and environmental quality; and from citizen concerns about managing the side effects of growth such as sprawl, congestion, housing affordability, and loss of open space. The planning models used by Metropolitan Planning Organizations (MPOs) were generally not designed to address these questions, creating a gap in the ability of planners to systematically assess these issues. UrbanSim is a new model system that has been developed to respond to these emerging requirements, and has now been applied in three metropolitan areas. This paper describes the model system and its application to Eugene-Springfield, Oregon.
Perceptions of traditional information sources and use of the world wide web to seek health information: findings from the health information national trends survey.

As medical information becomes increasingly available and individuals take a more active role in managing their personal health, it is essential for scholars to better understand the general public's information-seeking behavior. The study reported here explores the use of the World Wide Web to seek health information in a contemporary information-media environment. Drawing from uses and gratifications theory and the comprehensive model of health information seeking, perceptions of traditional information sources (e.g., mass media, one's health care provider, etc.) are posited to predict use of the Web to seek health information and perceptions of information acquired from searches. Data from the Health Information National Trends Survey (HINTS; N = 3982) were analyzed to test study hypotheses. Trust in information-oriented media, entertainment-oriented media, and one's health care provider all predicted Web use behavior and perceptions. The implications of the findings for research on information seeking and the role of the Web in patient empowerment are discussed.
On the power efficiency of cascode compensation over Miller compensation in two-stage operational amplifiers

Optimization of power consumption is one of the main design challenges in today's low-power high-speed analog integrated circuits. In this paper, two popular techniques to stabilize two-stage operational amplifiers, namely Miller and cascode compensations are compared from power point of view. To accomplish this, the cascode-compensated structure is basically analyzed to derive the required equations for comparison. The results show that for the same specifications, cascode compensation is more power efficient than Miller compensation especially for heavy capacitive loads. This has been confirmed by circuit-level simulations in 0.25μm CMOS technology.
Indexing the Sphere with the Hierarchical Triangular Mesh

We describe a method to subdivide the surface of a sphere into spherical triangles of similar, but not identical, shapes and sizes. The Hierarchical Triangular Mesh (HTM) is a quad-tree that is particularly good at supporting searches at different resolutions, from arc seconds to hemispheres. The subdivision scheme is universal, providing the basis for addressing and for fast lookups. The HTM provides the basis for an efficient geospatial indexing scheme in relational databases where the data have an inherent location on either the celestial sphere or the Earth. The HTM index is superior to cartographical methods using coordinates with singularities at the poles. We also describe a way to specify surface regions that efficiently represent spherical query areas. This article presents the algorithms used to identify the HTM triangles covering such regions.