Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed protocol for determining when averaging consensus is reached

Distributed averaging over a large network is a well studied problem that converges asymptotically; however, existing protocols does not provide a way for each node to distributively detect the occurrence of convergence. In this paper a method is developed to distributively determine when the consensus has reached within a given error margin. In absence of such a method all nodes in the network keep running the required computation and communication even if the consensus value are within acceptable tolerance, which is not preferable as in large-scale distributed networks resources like power are limited. Furthermore, this extra communication can cause signal interference with other critical information. This distributed detection takes finite time and occurs at each node simultaneously.
Towards Trustworthy Refactoring in Erlang

Tool-assisted refactoring transformations must be trustworthy if programmers are to be confident in applying them on arbitrarily extensive and complex code in order to improve style or efficiency. We propose a simple, high-level but rigorous, notation for defining refactoring transformations in Erlang, and show that this notation provides an extensible, verifiable and executable specification language for refactoring. To demonstrate the applicability of our approach, we show how to define and verify a number of example refactorings in the system.
A Neurally Motivated Technique for Voicing Detection andF 0 Estimation for Speech

Speech consists of alternating voiced and unvoiced sections. Voiced speech consists of multiple harmonics of some fundamental (F0); unvoiced speech consists of silence, or ltered noise. Here, speech is wideband bandpass ltered into many bands (modelling the cochlea). Each lter output is rectiied (modelling the organ of Corti hair cell action), and bandpass ltered by convolution with the diierence between two causal Gaussian averaging functions. This detects and emphasises the amplitude modulation resulting from unresolved harmonics (and models the combined eeect of the auditory nerve and certain cochlear nucleus cell types). This output is compressed, summed across the bands, then used to discover glottal pulses. The presence of glottal pulses signals voicing, and the time between glottal pulses is used to nd F0. Results show good performance, particularly on male speakers. The system is reasonably resistant to background noise.
Playful teaching work of school science teachers fundamental in a municipal school in Pernambuco, Brazil

ABSTRACTThis study is part of a dissertation which aims to explore and understand the role of play in the teaching-learning process at elementary level in a public school at Pernambuco, Brazil. We opted for a qualitative approach, using the interactive methodology, interviews by the technique of hermeneutic-dialectical circle, observations of science lessons and document analysis (lesson planning). Our sample consisted of five elementary teachers in the school. The results of the study showed that, in general, there was consistency between the didactic and practical teaching strategies used, with teachers placing value on the use of play as a tool to help the process of teaching and learning in science and enabling children to develop their knowledge and understanding of the world. Our observations noted the use of some interesting play strategies within the context of science lessons in the early years. However, some lesson plans proved somewhat insufficient due to lack of information about the play acti.
Evidence Accumulation in asynchronous BCI

The non-invasive Brain-Computer Interface (BCI) developed in our lab targets asynchronous operation of devices by monitoring electroencephalographic (EEG) activity and identifying oscillatory patterns that the user can voluntary modulate through the execution of motor imagery (MI) tasks. Successful self-paced interaction under this framework requires the incorporation of an evidence accumulation module to eliminate the uncertainty of single-sample classification and to drive an efficient feedback visualization. In this work, we motivate the need for this additional module, describe its role in a closed-loop MI BCI and present a comparative study of two different frameworks for evidence accumulation. The exploitation of Event-Related De-synchronization/Synchronization phenomena (ERD/ERS) related to imagination of movements (Neuper, 2006) has been proved to provide the means for achieving self-paced, user-driven brain-computer interaction, where the user voluntary modulates his brain activity compromising the need for external stimuli. The asynchronous MI-based BCI developed in our lab has been reported to successfully operate various devices (Millan, 2004;Galan, 2008) by continuously monitoring sensorimotor rhythms (SMRs) and deriving the subject's intentions through the identification of sustained SMR patterns. Several reasons motivate the existence of an evidence accumulation framework under this perspective: Single sample classification tends to be quite uncertain with regard to the strict requirements imposed by the final goal of controlling devices. Furthermore, abrupt and intense oscillations of the feedback directly driven by the classifier output can hinder user-training. Finally, continuous classification of the user's brain activity for achieving asynchronous interaction can cause random false positives during periods when the user is not executing any MI task. The proposed evidence accumulation module addresses the above issues by smoothing the highly oscillating classifier output to provide informative yet fast feedback, increasing the confidence of single sample inference and significantly eliminating random false positives during non-control periods.
Effects of Aggregate Angularity on Mix Design Characteristics and Pavement Performance

This research targets two primary purposes: to estimate current aggregate angularity test methods and to evaluate current aggregate angularity requirements in the Nebraska asphalt mixture/pavement specification. To meet the first research objective, various aggregate angularity tests are estimated with the same sets of aggregates and are compared by investigating their characteristics on testing repeatability, cost, testing time, workability, and sensitivity of test results. For the second objective, the effect of aggregate angularity on mixture performance is investigated by conducting laboratory performance tests (the uniaxial static creep test and the indirect tensile fracture energy test) of five mixes designed with different combinations of coarse and fine aggregate angularity and statistical analyses of five-year asphalt pavement analyzer test results of field mixtures. Results from the indirect tensile fracture energy test are then incorporated with finite element simulations of virtual specimens, which attempt to explore the detailed mechanisms of cracking related to the aggregate angularity. Results from the estimation of various angularity test methods imply that for the coarse aggregate angularity measurement, the AASHTO T326 method looks better than the current Superpave method, ASTM D5821, in that it is more objective and is very simple to perform with much less testing time. For the fine aggregate angularity measurement, the current Superpave testing method, AASHTO T304, is considered reasonable in a practical sense. Rutting performance test results indicate that higher angularity in the mixture improves rut resistance due to better aggregate interlocking. The overall effect of angularity on the mixtures’ resistance to fatigue damage is positive because aggregate blends with higher angularity require more binder to meet mix design criteria, which mitigates cracking due to increased viscoelastic energy dissipation from the binder, while angular particles produce a higher stress concentration that results in potential cracks. Finite element simulations of virtual specimens support findings from experimental tests. Outcomes from this research are expected to potentially improve current Nebraska asphalt specifications, particularly for aggregate angularity requirements and test methods to characterize local aggregate angularity.
An Axiomatic and Data Driven View on the EPK Paradox ∗

Supported by several recent investigations the empirical pricing kernel (EPK) paradox might be considered as a stylized fact. Some authors suggest that this paradox might be caused by regime switching in financial markets. Based on an economic model with state dependent utilities for the financial investors we want to emphasize a microeconomic view that succeeds in explaining the paradox via state dependent preferences. We shall also develop and investigate calibration problems in terms of data fits for basic values of the pricing kernel.
The impact of early childhood narcissistic injury on rehabilitation prognosis following mild traumatic brain injury in adulthood

The article examines the role of psychodynamic formulation in directing clinical rehabilitation following acquired brain injury, focusing on the contribution of Kohut’s theory of self-psychology. This is based on a case study of a man showing poor emotional and functional recovery following mild traumatic brain injury. Self-psychology formulation was used to understand psychopathology and guide psychodynamic therapy. The brain injury itself served as a severe narcissistic injury, which threatened self-worth and triggered distress. In addition, the patient was particularly vulnerable to narcissistic injury, due to a relational trauma as an infant in which presumably he was deprived of socio-emotional learning during right brain development. This postulates how detrimental early socioaffective experiences provided a growth-inhibiting environment for his developing brain. Thus, his poor recovery may be the outcome of two consecutive brain injuries: one developmental, due to relational trauma, and the other acquired as an adult following a road traffic collision. This helps provide a satisfactory formulation as to why a mild brain injury can result in devastating functional and emotional outcomes. The therapeutic work focused on constructing a sense of coherent self as a means to correct for unsatisfactory self-object experiences in early life and current family dynamics. It is hoped that the article contributes to the growing understanding of the central role childhood experiences can play in shaping the adult’s reactions to a traumatic brain injury, as well as the complex relationship with pre-injury personality, injury severity, and functional outcome.
Unsupervised Measuring of Entity Resolution Consistency

Entity resolution (ER) is a common data cleaning and data-integration task that aims to determine which records in one or more data sets refer to the same real-world entities. In most cases no training data exists and the ER process involves considerable trial and error, with an often time-consuming manual evaluation required to determine whether the obtained results are good enough. We propose a method that makes use of transitive closure within triples of records to provide an early indication of inconsistency in an ER result in an unsupervised fashion. We test our approach on three real-world data sets with different similarity calculations and blocking approaches and show that our approach can detect problems with ER resultsearly on without a manual evaluation.
Divide & Conquer: I/O Efficient Depth-First Search

Depth-First Search (DFS), which traverses a graph in the depth- first order, is one of the fundamental graph operations, and the result of DFS over all nodes in G is a spanning tree known as a DFS-Tree. There are many graph algorithms that need DFS such as connected component computation, topological sort, community detection, eulerian path computation, graph bipartiteness testing, planar graph testing, etc, because the in-memory DFS algorithm shows it can be done in linear time w.r. t. the size of G. However, given the fact that real-world graphs grow rapidly in the big data era, the in-memory DFS algorithm cannot be used to handle a large graph that cannot be entirely held in main memory. In this paper, we focus on I/O efficiency and study semi-external algorithms to DFS a graph G which is on disk. Here, like the existing semi-external algorithms, we assume that a spanning tree of G can be held in main memory and the remaining edges of G are kept on disk, and compute the DFS-Tree in main memory with which DFS can be identified. We propose novel divide & conquer algorithms to DFS over a graph G on disk. In brief, we divide a graph into several subgraphs, compute the DFS-Tree for each subgraph independently, and then merge them together to compute the DFS-Tree for the whole graph. With the global DFS-Tree computed we identify DFS. We discuss the valid division, that can lead to the correct DFS, and the challenges to do so. We propose two division algorithms, named Divide-Star and Divide-TD, and a merge algorithm. We conduct extensive experimental studies using four real massive datasets and several synthetic datasets to confirm the I/O efficiency of our approach.
Solving a Real-World Structural Optimization Problem with a Distributed SMS-EMOA Algorithm

This paper addresses a real-world optimization problem in civil engineering. It lies in the dimensioning of a 162m long bridge composed of 1584 bars so that both its weight and its deformation are to be minimized. Evaluating each possible configuration of the bridge takes several seconds and, as a consequence, running a metaheuristic for several thousands of evaluations would require many days on one single processor. Our approach has been to develop a distributed master/worker version of SMS-EMOA, an indicator-based multiobjective algorithm. By combining the Java implementation of the algorithm in jMetal with the Condor distributed scheduler, we have been able to use more than 350 cores to obtain accurate results in a reasonable amount of time.
Antenna design and characterization for a 61 GHz transceiver in eWLB package

In this article, we present the feasibility of an antenna concept at the ISM (Industrial, Scientific and Medical) band for a two-channel 61 GHz transceiver in embedded wafer level ball grid array (eWLB) technology. The eWLB is an innovative package solution for high-frequency and high-performance applications. We present both simulation and measurement results of antennas which are integrated in the thin-film redistribution layer (RDL) of an eWLB package. Two λ/2-dipole antennas are used for transmitter (TX) and receiver (RX). The package including the antennas is soldered on a RF board in order to measure radiation pattern and scattering parameters (S-parameters). The measured isolation between two antennas is -25 dB and they have a return loss of -26 dB. The observed gain of a single antenna is about 8 dBi and the antenna input impedance bandwidth is 5 GHz. We investigate the impact of package size on the antenna radiation pattern. We present the analysis of the antenna-package interactions and determine the optimum distance of the antennas in package to the reflector on board.
Toward evaluation of shape memory alloy actuators for endosurgery

Previous work in control of shape memory alloy actuators is examined and re-evaluated for possible application to design of tools for endosurgery. Flexible and rigid robotic links actuated by shape memory alloy are constructed and their behavior evaluated to determine and develop suitable control algorithms. The application of these links to electrically controlled surgical instruments such as graspers is discussed.
Erickson’s identity theory and the importance of ethnic exploration for transnational adoptees

ABSTRACT In an effort to promote their child’s ethnic identity development, parents of transnational adoptees regularly engage in cultural exploration activities with their children. This practice is aligned with Erik Erikson’s identity theory and constructs of exploration and commitment. Using qualitative analysis of interviews with adult adoptees, this study identifies four themes common to participants including: (1) travel to one’s birth country is a transformative experience; (2) relationships with other adoptees are important; (3) adoptees feel differently about the importance of cultural activities during childhood; and (4) adoptees feel both unique in their personal ethnic identity and have feelings of marginality.
Application of fuzzy measures in multi-criteria evaluation in GIS

Multi-criteria evaluation (MCE) is perhaps the most fundamental of decision support operations in geographical information systems (GIS). This paper reviews two main MCE approaches employed in GIS, namely Boolean and Weighted Linear Combination (WLC), and discusses issues and problems associated with both. To resolve the conceptual differences between the two approaches, this paper proposes the application of fuzzy measures, a concept that is broader but that includes fuzzy set membership, and argues that the standardized factors of MCE belong to a general class of fuzzy measures and the more specific instance of fuzzy set membership. This perspective provides a strong theoretical basis for the standardization of factors and their subsequent aggregation. In this context, a new aggregation operator that accommodates and extends the Boolean and WLC approaches is discussed: the Ordered Weighted Average. A case study of industrial allocation in Nakuru, Kenya is employed to illustrate the different approaches.
The Open University ’ s repository of research publications and other research outputs Coordination Contracts as Connectors in Component-Based Development Conference Item

Several proposals for component-based development methods have started to appear. However, the emphasis is still very much on the development of components as opposed to the development with components. The main focus is on how to generate ideal reusable components not on how to plug existing components and specify their interactions and connections. The concept of a coordination contract (Andrade and Fiadeiro 1999; Andrade and Fiadeiro 2001; Andrade, Fiadeiro et al. 2001) has been proposed to specify a mechanism of interaction between objects based on the separation between structure, what is stable, and interaction, what is changeable. This separation supports better any change of requirements, as contracts can be replaced, added or removed dynamically, i.e. in run-time, without having to interfere with the components that they coordinate. A coordination contract corresponds to an expressive architectural connector that can be used to plug existing components. In this paper we integrate the concept of a coordination contract with component-based development and show how coordination contracts can be used to specify the connectors between components.
‘The will to empower’: reworking governmentality in the museum

A number of geographers have sought to develop the museum as a space ripe for geographical enquiry and to comprehend the positioning of the museum. This paper aims to contribute to this burgeoning field of museum geography in order to consider the ways in which museum spaces rework notions of governmentality. First, this paper seeks to comprehend how museums (specifically municipal museums) are positioned within processes of governance and how, as a state actor, they develop a form of soft disciplinary power. Second, the paper follows such a strategy, as it traces the pathways taken by participants involved in a community engagement project based at GoMA (Gallery of Modern Art, Glasgow) in Glasgow. The project engaged a group of adult learners in a variety of cultural and arts activities. This allowed the group to explore a series of issues in contemporary art and it engaged them in different forms of creative practice. The community engagement work sought to improve their confidence and aspirations as well as to expand their creative abilities.
On Mobile Agent Itinerary for Collaborative Processing in Sensor Networks

— One of the most important problems studied in wireless sensor network applications is the collaborative processing among sensor nodes in order to compensate for each other's sensing and computing capabilities and to tolerate faults. The client/server based paradigm and the mobile agent based paradigm are two popular computing models used in collabora-tive processing. One of the most challenging problems in mobile agent based computing is the design of mobile agent itinerary. An improper design of itinerary (or route) of mobile agent migration can largely deteriorate the performance of collaborative processing. In this paper, we study the key problem of mobile agent planning for collaborative processing in sensor networks. This paper first models the dynamic mobile agent planning problem. It then presents three itinerary planning algorithms, the static, the dynamic, and the predictive dynamic approaches. We design three metrics (energy consumption, network lifetime, and the number of hops) and use simulation tools to quantitatively measure the performance of different itinerary planning algorithms. Simulation results show considerable improvement over the static itinerary and the dynamic itinerary approaches using the predictive dynamic itinerary algorithm.
Automated Genome Mining of Ribosomal Peptide Natural Products

Ribosomally synthesized and posttranslationally modified peptides (RiPPs), especially from microbial sources, are a large group of bioactive natural products that are a promising source of new (bio)chemistry and bioactivity.1 In light of exponentially increasing microbial genome databases and improved mass spectrometry (MS)-based metabolomic platforms, there is a need for computational tools that connect natural product genotypes predicted from microbial genome sequences with their corresponding chemotypes from metabolomic data sets. Here, we introduce RiPPquest, a tandem mass spectrometry database search tool for identification of microbial RiPPs, and apply it to lanthipeptide discovery. RiPPquest uses genomics to limit search space to the vicinity of RiPP biosynthetic genes and proteomics to analyze extensive peptide modifications and compute p-values of peptide-spectrum matches (PSMs). We highlight RiPPquest by connecting multiple RiPPs from extracts of Streptomyces to their gene clusters and by the discovery of a new class III lanthipeptide, informatipeptin, from Streptomyces viridochromogenes DSM 40736 to reflect that it is a natural product that was discovered by mass spectrometry based genome mining using algorithmic tools rather than manual inspection of mass spectrometry data and genetic information. The presented tool is available at cyclo.ucsd. edu.
Large-Signal Nonlinear Model for MESFET Triode and Saturation Zones

This paper presents a new large-signal nonlinear model for the GaAs MESFET triode and saturation zones. The model is specially tailored for simulating nonlinear distortion of RF circuits, in which the active device is biased in those regions. This new model will be compared to similar results obtained from a previously presented model and to real measurements of a microwave MESFET from Microwave Technologies.
Identification and Analysis of the Putative Pentose Sugar Efflux Transporters in Escherichia coli

Escherichia coli possesses a number of proteins that transport sugars out of the cell. We identified 31 candidate sugar efflux transporters based on their similarity to known sugar efflux transporters. We then tested whether these transporters affect arabinose and xylose metabolism. We identified 13 transporters – setC, cmr, ynfM, mdtD, yfcJ, yhhS, emrD, ydhC, ydeA, ybdA, ydeE, mhpT, and kgtP – that appeared to increase or decrease intracellular arabinose concentrations when respectively deleted or over-expressed. None of the candidate transporters affected xylose concentrations. These results indicate that E. coli possesses multiple arabinose efflux transporters. They also provide a novel target for future metabolic engineering.