Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Intervention: Enriching the Developing Brain

Reading is the cornerstone of all educational systems. Without adequate reading skills, learning in all other subject areas becomes very challenging. Children typically learn basic reading skills by age 6 or 7, but there is variation in timing of reading skill acquisition and, thereafter, in reading ability. A strong predictor of whether a child will have difficulties with reading is family history. Twin and family studies confirm that reading ability (including specific reading disorder) is substantively genetically influenced. Molecular genetic studies of reading ability have identified a number of candidate genes that are associated with reading disability and/or reading processes; many more are likely to be discovered. This review discusses implications that increased understanding of the genetic architecture of reading ability has for early identification and intervention for children at risk for reading difficulties.
An FPGA based accelerator for SAT based combinational equivalence checking

In this paper we present software/reconfigurable hardware SAT accelerator for combinational equivalence checking. The SAT binary clauses are mapped into an implication graph and the ternary clauses are kept in an indexed clause database and mapped into the clause evaluator and conflict detector implemented on FPGA. The validity of the proposed approach is shown through the ISCAS'85 benchmark circuits.
Metadata Extraction from Books with Facts about Austria

Digitized fact books are valuable sources of knowledge. Full-text search is a powerful tool to access such knowledge. However, it often delivers too many results for general queries. Therefore we propose an approach to find relevant data by extracting metadata relevant for each page and allow to search for pages on the basis of their metadata as alternative to full-text search. Given the size of scanned data (high quality image scans) clearly this extraction cannot be done manually. As it turns out, although there are some common aspects, different books often need to be treated differently. In particular we can distinguish two kinds of books: lexicons (dictionaries) where items are arranged alphabetically and other books that describe various topics in a more narrative style. In this paper we describe the approach we used on different fact books in detail and share our learnings from this subject.
NetworKit: An Interactive Tool Suite for High-Performance Network Analysis

We introduce NetworKit, an open-source software package for high-performance analysis of large complex networks. Complex networks are equally attractive and challenging targets for data mining, and novel algorithmic solutions as well as parallelization are required to handle data sets containing billions of connections. Our goal for NetworKit is to package results of our algorithm engineering efforts and put them into the hands of domain experts. NetworKit is a hybrid combining the performance of kernels written in C++ with a convenient interactive interface written in Python. The package supports shared-memory parallelism and scales from notebooks to compute servers. In comparison with related software, we propose NetworKit as a package geared towards large networks and satisfying three important criteria: High performance, interactive workflows and integration into an ecosystem of tested tools for data analysis and scientific computation. The current feature set includes analytics kernels such as degree distribution, connected components, clustering coefficients, community detection, k-core decomposition, degree assortativity and multiple centrality indices. Moreover, NetworKit comes with a collection of graph generators. With the current release, we present and open up the project to a community of both algorithm engineers and domain experts
A Brute Force Analysis of the COBE DMR Data

More than a dozen papers analyzing the COBE data have now appeared. We review the different techniques and compare them to a ``brute force" likelihood analysis where we invert the full 4038 x 4038 Galaxy-cut pixel covariance matrix. This method is optimal in the sense of producing minimal error bars, and is a useful reference point for comparing other analysis techniques. Our maximum-likelihood estimate of the spectral index and normalization are n=1.15 (0.95) and Q=18.2 (21.3) micro-Kelvin including (excluding) the quadrupole. Marginalizing over the normalization C_9, we obtain n=1.10 +/- 0.29 (n=0.90 +/- 0.32). When we compare these results with those of the various techniques that involve a linear ``compression'' of the data, we find that the latter are all consistent with the brute-force analysis and have error bars that are nearly as small as the minimal error bars. We therefore conclude that the data compressions involved in these techniques do indeed retain most of the useful cosmological information.
High-Speed Imaging Reveals Neurophysiological Links to Behavior in an Animal Model of Depression

www.sciencemag. org (this information is current as of November 2, 2007 ): The following resources related to this article are available online at http://www.sciencemag. org/cgi/content/full/317/5839/815 version of this article at: including high-resolution figures, can be found in the online Updated information and services, http://www.sciencemag. org/cgi/content/full/317/5839/815/DC1 can be found at: Supporting Online Material found at: can be related to this article A list of selected additional articles on the Science Web sites http://www.sciencemag. org/cgi/content/full/317/5839/815#related-content http://www.sciencemag. org/cgi/content/full/317/5839/815#otherarticles , 15 of which can be accessed for free: cites 26 articles This article 1 article(s) on the ISI Web of Science. cited by This article has been http://www.sciencemag. org/cgi/collection/evolution Evolution : subject collections This article appears in the following http://www.sciencemag. org/about/permissions.dtl in whole or in part can be found at: this article permission to reproduce of this article or about obtaining reprints Information about obtaining
A Decentralized, On-line Coordination Mechanism for Monitoring Spatial Phenomena with Mobile Sensors

In this paper, we introduce the first on-line, decentralised coordination mechanism for monitoring spatial phenomena with multiple mobile sensors that model the environment using Gaussian processes (GPs). These sensors have their application domain in highly dynamic scenarios, where strict time constraints prohibit path planning in advance, or where the characteristics of the spatial phenomena are unknown a priori. Our coordination mechanism enables the sensors to learn the environmental parameters on-line from their collected observations (and represents them using the GP), and to coordinate their movements to maximise their collective information gain in a decentralised way. We evaluate our algorithm using real-world sensor data collected at the Berkeley Intel Research lab, and demonstrate that a team of 5 mobile sensors equipped with our algorithm monitors the environment with a 51% reduction of Root Mean Squared error compared to a network of fixed sensors that have been deployed using an off-line optimisation algorithm that has complete information of the characteristics of the spatial phenomena.
Implications of a Carbon-Based Energy Tax for U.S. Agriculture

Policies to mitigate greenhouse gas emissions are likely to increase energy prices. Higher energy prices raise farmer costs for diesel and other fuels, irrigation water, farm chemicals, and grain drying. Simultaneously, renewable energy options become more attractive to agricultural producers. We consider both of these impacts, estimating the economic and environmental consequences of higher energy prices on U.S. agriculture. To do this we employ a price-endogenous agricultural sector model and solve that model for a range of carbon-tax-based energy price changes. Our results show mostly positive impacts on net farm income in the intermediate run. Through market price adjustments, fossil fuel costs are largely passed on to consumers. Additional farm revenue arises from the production of biofuels when carbon taxes reach $30 per ton of carbon or more. Positive environmental benefits include not only greenhouse gas emission offsets but also reduced levels of nitrogen leaching.
Taxonomy-Based Discovery and Annotation of Functional Areas in the City

Mapping the functional use of city areas (e.g., mapping clusters of hotels or of electronic shops) enables a variety of applications (e.g., innovative way-finding tools). To do that mapping, researchers have recently processed geo-referenced data with spatial clustering algorithms. These algorithms usually perform two consecutive steps: they cluster nearby points on the map, and then assign labels (e.g., 'electronics') to the resulting clusters. When applied in the city context, these algorithms do not fully work, not least because they consider the two steps of clustering and labeling as separate. Since there is no reason to keep those two steps separate, we propose a framework that clusters points based not only on their density but also on their semantic relatedness. We evaluate this framework upon Foursquare data in the cities of Barcelona, Milan, and London. We find that it is more effective than the baseline method of DBSCAN in discovering functional areas. We complement that quantitative evaluation with a user study involving 111 participants in the three cities. Finally, to illustrate the generalizability of our framework, we process temporal data with it and successfully discover seasonal uses of the city.
The Menstrual Cycle and Performance Feedback Alter Gender Differences in Competitive Choices 1 Forthcoming in The Journal of Labor Economics

We use a within-subjects experiment with math and word tasks to show that relative performance feedback moves high ability females towards more competitive forms of compensation and moves low ability men towards less competitive forms and eliminates gender differences in choices. We also examine females across the menstrual cycle, and find that women in the high-hormone phase are more willing to compete than women in the low phase. There are no significant differences between choices after subjects receive feedback. Thus, biological differences lead to economically significant differences, but the impact of those differences can be lowered through relative performance information.
Modeling user variance in time-biased gain

Cranfield-style information retrieval evaluation considers variance in user information needs by evaluating retrieval systems over a set of search topics. For each search topic, traditional metrics model all users searching ranked lists in exactly the same manner and thus have zero variance in their per-topic estimate of effectiveness. Metrics that fail to model user variance overestimate the effect size of differences between retrieval systems. The modeling of user variance is critical to understanding the impact of effectiveness differences on the actual user experience. If the variance of a difference is high, the effect on user experience will be low. Time-biased gain is an evaluation metric that models user interaction with ranked lists that are displayed using document surrogates. In this paper, we extend the stochastic simulation of time-biased gain to model the variation between users. We validate this new version of time-biased gain by showing that it produces distributions of gain that agree well with actual distributions produced by real users. With a per-topic variance in its effectiveness measure, time-biased gain allows for the measurement of the effect size of differences, which allows researchers to understand the extent to which predicted performance improvements matter to real users.
Quantum coding.

A theorem is proven for quantum information theory that is analogous to the noiseless coding theorem of classical information theory. In the quantum result, the von Neumann entropy S of the density operator describing an ensemble of pure quantum signal states is equal to the number of spin-1/2 systems (quantum bits or \qubits") necessary to represent the signal faithfully. The theorem holds whether or not the signal states are orthogonal. Related results are also presented about the delity of quantum coding and about representing entangled quantum states.
Information and Noise in Financial Markets: Evidence from the E-Mini Index Futures

We examine the informational contributions and effects on transitory volatility of trades initiated by different types of traders in three actively traded index futures markets. The results show that trades initiated by exchange member firms account for over 60% of price discovery during the trading day. These institutional trades appear to be more informative than trades of individual exchange members or off-exchange traders. We also find that off-exchange traders introduce more noise into the prices than do exchange members. Our results provide new evidence on the roles of different types of traders in the price formation process.
A Scalable Architecture for Distributed Receive Beamforming: Analysis and Experimental Demonstration

We propose, analyze, and demonstrate an architecture for scalable cooperative reception. In a cluster of N+1 receive nodes, one node is designated as the final receiver, and the N other nodes act as amplify-and-forward relays, which adapt their phases such that the relayed signals add up constructively at the designated receiver. This yields received SNR scaling linearly with N, while avoiding the linear increase in overhead incurred by a direct approach in which received signals are separately quantized and transmitted for centralized processing. By transforming the task of long-distance distributed receive beamforming into one of local distributed transmit beamforming, we can leverage a scalable one-bit feedback algorithm for phase synchronization. We show that time division between the long-distance and local links eliminates the need for explicit frequency synchronization. We provide an analytical framework, whose results closely match Monte Carlo simulations, to evaluate the impact of phase noise due to relaying delay on the performance of the one-bit feedback algorithm. Experimental results from our prototype implementation on software-defined radios demonstrate the expected gains in received signal strength despite significant oscillator drift, and are consistent with results from our analytical framework.
Exploiting Relationships for Domain-Independent Data Cleaning

In this paper, we address the problem of reference disambiguation. Specifically, we consider a situation where entities in the database are referred to using descriptions (e.g., a set of instantiated attributes). The objective of reference disambiguation is to identify the unique entity to which each description corresponds. The key difference between the approach we propose (called RelDC) and the traditional techniques is that RelDC analyzes not only object features but also inter-object relationships to improve the disambiguation quality. Our extensive experiments over two real datasets and over synthetic datasets show that analysis of relationships significantly improves quality of the result.
Classifying Actions and Measuring Action Similarity by Modeling the Mutual Context of Objects and Human Poses

In this paper, we consider two action recognition problems in still images. One is the conventional action classification task where we assign a class label to each action image; the other is a new problem where we measure the similarity between action images. We achieve the goals by using a mutual context model to jointly model the objects and human poses in images of human actions. Experimental results show that our method not only improves action classification accuracy, but also learns a similarity measure that is largely consistent with human perception.
Modelling market sellers in World of Warcraft

The virtual economy operates like the one in the physical world, which is realized by players with two functions–demand and supply, only using the form as avatars. Only that in virtual worlds, the prices of virtual items is decided by the players instead of by its quality or scarcity, so the player behavior analyses became an important tool to monitor the persistent virtual worlds. In order to achieve the idea of a more balanced virtual market, we analyze the trading behaviors in three points – sellers, prices and items, and expect to figure out the selling motivation, pricing rules and the over/underpricing conditions. In this paper, we use the auction house data in World of Warcraft (WoW) to analyze these seller behaviors. After applying clustering and classification, a market seller model of WoW is presented.
ETSP: An Energy-Efficient Time Synchronization Protocol for Wireless Sensor Networks

Wireless sensor networks (WSN) have specific constraints and stringent requirements in contrast to traditional wired and wireless computer networks. Among these specific requirements, energy-efficiency is the most prominent. Sensor motes have finite amount of energy supply. In most WSN applications, hundreds or thousands of motes are deployed in an area (e.g., behind enemy lines or foliage) and there is no provision for battery recharging. Therefore, a fundamental constraint on WSN applications and services is to extend the network's lifetime by making the batteries run longer. In this paper we propose an energy-efficient time synchronization protocol, referred as ETSP, which gives significant improvement in energy consumption over existing time synchronization schemes. We first evaluate the existing reference broadcast synchronization (RBS) and time-sync protocol for sensor networks (TPSN), which are two prominent examples of receiver-receiver and sender-receiver synchronization methods. This performance analysis demonstrates that combination of RBS and TPSN can work better than using these techniques separately. In the proposed ETSP protocol, we identify conditions to toggle between RBS and TPSN based on a threshold value. We experimentally and mathematically derive an optimal value of the switching threshold for different sensor motes. In this way we effectively reduce the number of transmissions which results in saving energy. Moreover, we assess the performance of our protocol on the bit error traces collected over a real WSN test bed to cater for retransmissions overload for the time synchronization protocols under consideration.
A pilot study on the daily control capability of s-EMG prosthetic hands by amputees

Surface electromyography is a valid tool to gather muscular contraction signals from intact and amputated subjects. Electromyographic signals can be used to control prosthetic devices in a noninvasive way distinguishing the movements performed by the particular EMG electrodes activity. According to the literature, several algorithms have been used to control prosthetic hands through s-EMG signals. The main issue is to correctly classify the signals acquired as the movement actually performed. This work presents a study on the Support Vector Machine's performance in a short-time period, gained using two different feature representation (Mean Absolute Value and Waveform Length) of the sEMG signals. In particular, we paid close attention to the repeatability problem, that is the capability to achieve a stable and satisfactory level of accuracy in repeated experiments. Results on a limited setting are encouraging, as they show an average accuracy above 73% even in the worst case scenario.
An Approach to Parallelize Kruskal's Algorithm Using Helper Threads

In this paper we present a Helper Threading scheme used to parallelize efficiently Kruskal's Minimum Spanning Forest algorithm. This algorithm is known for exhibiting inherently sequential characteristics. More specifically, the strict order by which the algorithm checks the edges of a given graph is the main reason behind the lack of explicit parallelism. Our proposed scheme attempts to overcome the imposed restrictions and improve the performance of the algorithm. The results show that for a wide range of graphs of varying structure, size and density the parallelization of Kruskal's algorithm is feasible. Observed speedups reach up to 5.5 for 8 running threads, revealing the potentials of our approach.
Bisphenol A, Bisphenol S, and 4-Hydroxyphenyl 4-Isoprooxyphenylsulfone (BPSIP) in Urine and Blood of Cashiers

Background: Bisphenol A (BPA) is a high-production-volume chemical associated with a wide range of health outcomes in animal and human studies. BPA is used as a developer in thermal paper products, including cash register receipt paper; however, little is known about exposure of cashiers to BPA and alternative compounds in receipt paper. Objective: We determined whether handling receipt paper results in measurable absorption of BPA or the BPA alternatives bisphenol S (BPS) and 4-hydroxyphenyl 4-isoprooxyphenylsulfone (BPSIP). Methods: Cashiers (n = 77) and non-cashiers (n = 25) were recruited from the Raleigh–Durham–Chapel Hill region of North Carolina during 2011–2013. Receipts were analyzed for the presence of BPA or alternatives considered for use in thermal paper. In cashiers, total urine and serum BPA, BPS, and BPSIP levels in post-shift samples (collected ≤ 2 hr after completing a shift) were compared with pre-shift samples. Levels of these compounds in urine from cashiers were compared to levels in urine from non-cashiers. Results: Each receipt contained 1–2% by weight of the paper of BPA, BPS, or BPSIP. The post-shift geometric mean total urinary BPS concentration was significantly higher than the pre-shift mean in 33 cashiers who handled receipts containing BPS. The mean urine BPA concentrations in 31 cashiers who handled BPA receipts were as likely to decrease as to increase after a shift, but the mean post-shift concentrations were significantly higher than those in non-cashiers. BPSIP was detected more frequently in the urine of cashiers handling BPSIP receipts than in the urine of non-cashiers. Only a few cashiers had detectable levels of total BPA or BPS in serum, whereas BPSIP tended to be detected more frequently. Conclusions: Thermal receipt paper is a potential source of occupational exposure to BPA, BPS, and BPSIP. Citation: Thayer KA, Taylor KW, Garantziotis S, Schurman SH, Kissling GE, Hunt D, Herbert B, Church R, Jankowich R, Churchwell MI, Scheri RC, Birnbaum LS, Bucher JR. 2016. Bisphenol A, bisphenol S, and 4-hydroxyphenyl 4-isoprooxyphenylsulfone (BPSIP) in urine and blood of cashiers. Environ Health Perspect 124:437–444; http://dx.doi. org/10.1289/ehp.1409427
Practical semantics for the Internet of Things: Physical states, device mashups, and open questions

The Internet of Things (IoT) envisions cross-domain applications that combine digital services with services provided by resource-constrained embedded devices that connect to the physical world. Such smart environments can comprise a large number of devices from various different vendors. This requires a high degree of decoupling and neither devices nor user agents can rely on a priori knowledge of service APIs. Semantic service descriptions are applicable to heterogeneous application domains due to their high level of abstraction and can enable automatic service composition. This paper shows how the RESTdesc description format and semantic reasoning can be applied to create Web-like mashups in smart environments. Our approach supports highly dynamic environments with resource-constrained IoT devices where services can become unavailable due to device mobility, limited energy, or network disruptions. The concepts are backed by a concrete system architecture whose implementation is publicly available. It is used to evaluate the semantics-based approach in a realistic IoT-related scenario. The results show that current reasoners are able to produce medium-sized IoT mashups, but struggle with state space explosion when physical states become part of the proofing process.