Miracle-dz/UniFAR-FTUs huggingface dataset:
The distribution of research performance across Australian universities, 1992-2003, and its implications for higher education funding models

We contribute to the debate on research performance by comparing the distribution of research inputs and outputs across Australian universities during 1992-2003. We have calculated annual Gini coefficients for various performance measures and Lorenz curves for the final year of the study. Various findings are evident. Research-input measures have remained relatively unevenly distributed across universities. Output measures were more evenly distributed and this exhibited a gradual and rather consistent decline through time, supporting the view that the research output is being generated gradually more equally across Australia’s universities. Excluding the "Group of Eight" (Go8) universities, results in a more even distribution of performance. However, in 2003 this group took the lion’s share of research inputs but produced a smaller share of outputs. Our findings are relevant to current funding policy discussion.
Literature Review: Theory and Application of In-Line Inspection Technologies for Oil and Gas Pipeline Girth Weld Defection

Girth weld cracking is one of the main failure modes in oil and gas pipelines; girth weld cracking inspection has great economic and social significance for the intrinsic safety of pipelines. This paper introduces the typical girth weld defects of oil and gas pipelines and the common nondestructive testing methods, and systematically generalizes the progress in the studies on technical principles, signal analysis, defect sizing method and inspection reliability, etc., of magnetic flux leakage (MFL) inspection, liquid ultrasonic inspection, electromagnetic acoustic transducer (EMAT) inspection and remote field eddy current (RFDC) inspection for oil and gas pipeline girth weld defects. Additionally, it introduces the new technologies for composite ultrasonic, laser ultrasonic, and magnetostriction inspection, and provides reference for development and application of oil and gas pipeline girth weld defect in-line inspection technology.
On half gapped seed.

In this paper, we proposed a new type of seed for Blast-like homology search tools called "half seed''. This new seed is better than the "consecutive seed'' used by the original Blast tools in both sensitivity and efficiency. When compared with the "gapped seed'', which is proposed together with a new Blast-like searching tool, PatternHunter, this new seed offers a much wider range of choices for performing tradeoff between sensitivity and efficiency. This property is especially useful when some searching applications want to get more precise results with limitation on hardware resources, or vice versa.
SnFFT: a Julia toolkit for Fourier analysis of functions over permutations

SnFFT is an easy to use software library written in the Julia language to facilitate Fourier analysis on the symmetric group (set of permutations) of degree n, denoted Sn and make it more easily deployable within statistical machine learning algorithms. Our implementation internally creates the irreducible matrix representations of Sn, and efficiently computes fast Fourier transforms (FFTs) and inverse fast Fourier transforms (iFFTs). Advanced users can achieve scalability and promising practical performance by exploiting various other forms of sparsity. Further, the library also supports the partial inverse Fourier transforms which utilizes the smoothness properties of functions by maintaining only the first few Fourier coefficients. Out of the box, SnFFT currently offers two non-trivial operations for functions defined on Sn, namely convolution and correlation. While the potential applicability of SnFFT is fairly broad, as an example, we show how it can be used for clustering ranked data, where each ranking is modeled as a distribution on Sn.
Multicell MISO Downlink Weighted Sum-Rate Maximization: A Distributed Approach

We develop an easy to implement distributed method for weighted sum-rate maximization (WSRMax) problem in a multicell multiple antenna downlink system. Unlike the recently proposed minimum weighted mean-squared error based algorithms, where at each iteration all mobile terminals needs to estimate the covariance matrices of their received signals, compute and feedback over the air certain parameters to the base stations (BS), our algorithm operates without any user terminal assistance. It requires only BS to BS signalling via reliable backhaul links (e.g., fiber, microwave links) and all required computation is performed at the BSs. The algorithm is based on primal decomposition and subgradient methods, where the original nonconvex problem is split into a master problem and a number of subproblems (one for each BS). A novel sequential convex approximation strategy is proposed to address the nonconvex master problem. In the case of subproblems, we adopt an existing iterative approach based on second-order cone programming and geometric programming. The subproblems are coordinated to find a (possibly suboptimal) solution to the master problem. Subproblems can be solved by BSs in a fully asynchronous manner, though the coordination between subproblems should be synchronous. Numerical results are provided to see the behavior of the algorithm under different degrees of BS coordination. They show that the proposed algorithm yields a good tradeoff between the implementation-level simplicity and the performance.
Selective Attention in Dynamic Vision

Selective attention can enable a vision system to perform eeectively. The high-level vision component developed here uses Bayesian networks combined with a deictic representation to (1) create a dynamic structure to reeect the spatial organisation of the data and (2) measure task relatedness. Together these give at-tentional focus making the reasoning relevant to the task.
Ultrasound pallet part evaluator/grader and cant scanner

Sorting and grading of wooden pallet parts are key factors for manufacturing quality and durable pallets. The feasibility of ultrasonic scanning for defect detection and classification has been examined in this report. Defects, such as sound and unsound knots, decay, bark pockets, wane, and holes were scanned on both red oak (Quercus rubra, L.) and yellow-poplar (Liriodendron tulipifera, L.) pallet materials. Scanning was conducted by two pressure-contact rolling transducers in a pitch-catch arrangement. Pallet parts, such as deckboards, stringers, and cants were fed through the transducers, and data were collected, stored, and processed with software written in the LabView™ environment. Defects were characterized on the basis of time of flight, pulse energy, and pulse duration of the received ultrasonic signals. Significant losses of energies were observed through these defects. Time of flight is less sensitive to defects compared to other parameters. This relative change of parameter values, with respect to values for clear wood, can be used to locate, identify, and quantify various pallet part degrades. Two-dimensional images were constructed using multi-line scanning data. The reconstructed images are able to show the position and surface area of the defects. Defects were classified using a multi-layer perceptron (MLP), a probabilistic neural network (PNN), and a K-nearest neighbor (KNN) classifier. Defective wood was classified quite clearly and accurately by all of these networks with high recognition rates. Decay has a higher recognition rate than the other defects. Wane and holes were readily confused owing to their common loss of transducer contact. The MLP were found to be more efficient for classifying these defects. Results demonstrate that real-time, on-line inspection and classification of defects in wooden pallet parts are possible by ultrasonic scanning.
Importance of nasality measures for speaker recognition data selection and performance prediction

We improve upon our measures relating feature vector distributions to speaker recognition (SR) performances for performance prediction and potential arbitrary data selection for SR, as described in [1]. In particular, we examine the means and variances of 11 features pertaining to nasality (each of which is denoted as a measure), computing them on feature vectors of phones to determine which measures give good SR performance prediction of phones. We’ve found that the combination of nasality measures give a 0.917 correlation with the Equal Error Rates (EERs) of phones on SRE08, exceeding the correlation of our previous best measure (mutual information) by 12.7%. When implemented in our data-selection scheme (which does not require a SR system to be run), the nasality measures allow us to select data with combined EER better than data selected via running a SR system in certain cases, at a fortieth of the computational costs. The nasality measures also require a tenth of the computational costs to compute compared to our previous best measure.
Felt-sensing archetypes: analysing patterns of accessing tacit meaning in design

As technology becomes embedded in our everyday life, the development of methods for accessing experience has become an important theme in the field of human-computer interaction and design. Currently most user evaluation techniques are still concerned with conscious assessment of devices and systems, ignoring that our bodily senses are constantly capturing information at an unconscious level. Based on Gendlin's Focusing technique, we introduce a method of archetype analysis that considers the importance of the body as the door to access meaning encapsulated in people's tacit dimension. Drawing on the outcomes from different somatic exercises involving the reflection on everyday objects and situations, six archetypes reflecting participant's inner connection with each scenario were generated. As a result, richer descriptions and more bodily self-aware archetypes (felt-sensers) were obtained in the reflection on everyday situations over objects. These findings make sense with the interactional process of meaning-generation experienced by the lived body.
CECL: a New Baseline and a Non-Compositional Approach for the Sick Benchmark

This paper describes the two procedures for determining the semantic similarities between sentences submitted for the SemEval 2014 Task 1. MeanMaxSim, an unsupervised procedure, is proposed as a new baseline to assess the efficiency gain provided by compositional models. It outperforms a number of other baselines by a wide margin. Compared to the wordoverlap baseline, it has the advantage of taking into account the distributional similarity between words that are also involved in compositional models. The second procedure aims at building a predictive model using as predictors MeanMaxSim and (transformed) lexical features describing the differences between each sentence of a pair. It finished sixth out of 17 teams in the textual similarity sub-task and sixth out of 19 in the textual entailment subtask.
A Dataset for Joint Noun-Noun Compound Bracketing and Interpretation

We present a new, sizeable dataset of noun– noun compounds with their syntactic analysis (bracketing) and semantic relations. Derived from several established linguistic resources, such as the Penn Treebank, our dataset enables experimenting with new approaches towards a holistic analysis of noun–noun compounds, such as joint-learning of noun–noun compounds bracketing and interpretation, as well as integrating compound analysis with other tasks such as syntactic parsing.
Gas Turbine Performance Deterioration.

With privatization and intense competition in the utility and petrochemical industry, there is a strong incentive for gas turbine operators to minimize and control performance deterioration, as this directly affects profitability. The area of gas turbine recoverable and nonrecoverable performance deterioration is comprehensively treated in this paper. Deterioration mechanisms including compressor and turbine fouling, erosion, increased clearances, and seal distress are covered along with their manifestations, rules of thumb, and mitigation approaches. Permanent deterioration is also covered. Because of the importance of compressor fouling, gas turbine inlet filtration, fouling mechanisms, and compressor washing are covered in detail. Approaches for the performance monitoring of steady-state and transient behavior are presented along with simulations of common deterioration modes of gas turbine combined cycles. As several gas turbines are used in cogeneration and combined cycles, a brief discussion of heat recovery steam generator performance monitoring is made.
Constraint-based routing for ad-hoc networks

Future large-scale networks, such as sensor networks, will consist of hundreds and even thousands of wirelessly connected sensor and actuator nodes. The nodes are typically highly resource-constrained (processor, memory, and power), have limited communication range, and are prone to failure. Furthermore, there is no global information about the exact location and connectivity of the nodes. Consequently, the explicit consideration of network and task constraints and objectives will be an important part of routing algorithms for these networks. We present a distributed constraint-based routing approach that represents destination conditions as well as routing constraints and objectives explicitly. We further present an efficient routing algorithm, CB-LRTA*, that extends traditional Learning Real-Time A* (LRTA*) with back-propagation. We evaluate CB-LRTA* using simulation and demonstrate that it improves convergence to the optimal route over LRTA*.
The Subcellular Dynamics of the Gs-Linked Receptor GPR3 Contribute to the Local Activation of PKA in Cerebellar Granular Neurons

G-protein-coupled receptor (GPR) 3 is a member of the GPR family that constitutively activates adenylate cyclase. We have reported that the expression of GPR3 in cerebellar granular neurons (CGNs) contributes to neurite outgrowth and modulates neuronal proliferation and survival. To further identify its role, we have analyzed the precise distribution and local functions of GPR3 in neurons. The fluorescently tagged GPR3 protein was distributed in the plasma membrane, the Golgi body, and the endosomes. In addition, we have revealed that the plasma membrane expression of GPR3 functionally up-regulated the levels of PKA, as measured by a PKA FRET indicator. Next, we asked if the PKA activity was modulated by the expression of GPR3 in CGNs. PKA activity was highly modulated at the neurite tips compared to the soma. In addition, the PKA activity at the neurite tips was up-regulated when GPR3 was transfected into the cells. However, local PKA activity was decreased when endogenous GPR3 was suppressed by a GPR3 siRNA. Finally, we determined the local dynamics of GPR3 in CGNs using time-lapse analysis. Surprisingly, the fluorescent GPR3 puncta were transported along the neurite in both directions over time. In addition, the anterograde movements of the GPR3 puncta in the neurite were significantly inhibited by actin or microtubule polymerization inhibitors and were also disturbed by the Myosin II inhibitor blebbistatin. Moreover, the PKA activity at the tips of the neurites was decreased when blebbistatin was administered. These results suggested that GPR3 was transported along the neurite and contributed to the local activation of PKA in CGN development. The local dynamics of GPR3 in CGNs may affect local neuronal functions, including neuronal differentiation and maturation.
Unveiling the nature of six HMXBs through IR spectroscopy

Context. The International Gamma-Ray Astrophyiscs Laboratory (INTEGRAL) is discovering a large number of new hard X-ray sources, many of them being HMXBs. The identification and spectral characterization of their optical/infrared counterparts is a necessary step to undertake detailed study of these systems. In particular, the determination of the spectral type is crucial in the case of the new class of Supergiant Fast X-ray Transients (SFXTs), which show X-ray properties common to other objects. Aims. Our goal is to perform spectral analysis and classification of proposed counterparts to HMXBs in order to characterize the system they belong to. Methods. We used the ESO/NTT SofI spectrograph to observe proposed IR counterparts to HMXBs, obtaining Ks medium resolution spectra (R = 1320) with a S /N 100. We classified them through comparison with published atlases. Results. We were able to spectrally classify the six sources. This allowed us to ascribe one of them to the new class of SFXTs and confirm the membership of two sources to this class. We confirmed the spectral classification, derived from optical spectroscopy, of a known system, 4U 1907-09, showing for the first time its infrared spectrum. The spectral classification was also used to estimate the distance of the sources. We compared the extinction as derived from X-ray data with effective interstellar extinction obtained from our data, discussing the absorption component due to the circumstellar environment, which we observed in four systems; in particular, intrinsic absorption seems to emerge as a typical feature of the entire class of SFXTs.
Challenges Facing USDA's Conservation Reserve Program

Reductions in maximum Conservation Reserve Program (CRP) acres mandated by the 2008 Farm Act, along with relatively high agricultural commodity prices, could lead to reduced overall environmental benefits and higher CRP costs. ERS is analyzing alternative enrollment policies and practices that could increase environmental benefits per enrolled acre and lower program costs. The effectiveness of changes will depend on improved data and models to more accurately estimate the environmental benefits provided by competing offers to enroll land in the CRP.
A hybrid biogeography-based optimization method for the inverse kinematics problem of an 8-DOF redundant humanoid manipulator

The redundant humanoid manipulator has characteristics of multiple degrees of freedom and complex joint structure, and it is not easy to obtain its inverse kinematics solution. The inverse kinematics problem of a humanoid manipulator can be formulated as an equivalent minimization problem, and thus it can be solved using some numerical optimization methods. Biogeography-based optimization (BBO) is a new biogeography inspired optimization algorithm, and it can be adopted to solve the inverse kinematics problem of a humanoid manipulator. The standard BBO algorithm that uses traditional migration and mutation operators suffers from slow convergence and prematurity. A hybrid biogeography-based optimization (HBBO) algorithm, which is based on BBO and differential evolution (DE), is presented. In this hybrid algorithm, new habitats in the ecosystem are produced through a hybrid migration operator, that is, the BBO migration strategy and DE/best/1/bin differential strategy, to alleviate slow convergence at the later evolution stage of the algorithm. In addition, a Gaussian mutation operator is adopted to enhance the exploration ability and improve the diversity of the population. Based on these, an 8-DOF (degree of freedom) redundant humanoid manipulator is employed as an example. The end-effector error (position and orientation) and the ‘away limitation level’ value of the 8-DOF humanoid manipulator constitute the fitness function of HBBO. The proposed HBBO algorithm has been used to solve the inverse kinematics problem of the 8-DOF redundant humanoid manipulator. Numerical simulation results demonstrate the effectiveness of this method.
Supervised and Unsupervised Models for Propositional Analysis

At the level of lexical semantics, distributional methods that generate word representations from large text corpora have proven to be useful practical techniques (Landauer, 2002) as well provocative theoretical models (Landauer & Dumais, 1997). Following in the footsteps of Latent Semantic Analysis (LSA, Deerwester, Dumais, Furnas, Landauer, & Harshman, 1991) there has been substantial interest in these techniques, and we are currently aware of some eighteen published methods for deriving semantic content (including Blei, Ng, & Jordan, 2002; Dennis, 2003; Griffiths & Steyvers, 2002; Hofmann, 2001; Lin & Pantel, 2001; Redington, Chater, & Finch, 1998). Similarly, there has also been interest in unsupervised methods for syntactic analysis (Klein & Manning, 2001; Magerman & Marcus, 1990) and the performance of current methods as measured by the recall and precision of constituent identification has been gradually improving.
Atom interferometry in the presence of an external test mass

The influence of an external test mass on the phase of the signal of an atom interferometer is studied theoretically. Using traditional techniques in atom optics based on the density matrix equations in the Wigner representation, we are able to extract the various contributions to the phase of the signal associated with the classical motion of the atoms, the quantum correction to this motion resulting from atomic recoil that is produced when the atoms interact with Raman field pulses, and quantum corrections to the atomic motion that occur in the time between the Raman field pulses. By increasing the effective wave vector associated with the Raman field pulses using modified field parameters, we can increase the sensitivity of the signal to the point where the quantum corrections can be measured. The expressions that are derived can be evaluated numerically to isolate the contribution to the signal from an external test mass. The regions of validity of the exact and approximate expressions are determined.
QUALITY ASSESSMENT IN INTERNATIONAL INDUSTRIAL MARKETS: THE CASE OF NORWEGIAN STOCKFISH

Quality assessment is an important function within a firm. It creates a foundation for production according to the demands of the market, for choice of a distribution channel and for the pricing of products. Although there has been some research on quality assessment, there has been little research on the institutions that shape it. It is often assumed that quality assessment is based on the use of objective rules and evaluation procedures. This paper uses secondary data from industrial export companies within the food sector to investigate whether this is so. It is shown that an institution for quality assessment mainly bases its quality classifications on objective product characteristics, but that the level of supply to the market effects the criteria used for quality assessment, making quality assessment more complex than normally assumed.
A New Method to Persian Text Watermarking Using Curvaceous Letters

Following the expansion of communication, hiding of confidential information has become a crucial requirement. Watermarking is one of the techniques used to hide information in image, sound and especially text. Comparing to English and Chinese texts, there has been little work on Persian texts, because of special characteristics of Persian texts. In this paper, a method is proposed, for the first time, to hide information in the curvatures existing in some Persian letters. One of the main steps in watermarking process is detection and separation of letters using the appearance features of the letters, and the way they stand within the text. Since that in the proposed method, information are embedded in Pixels of curved letters, the results of proposed method show the good quality, the capacity and the robustness of this method.