Miracle-dz/UniFAR-FTUs huggingface dataset:
Opmonoidal Monads

Hopf monads are identified with monads in the 2-category OpMon of monoidal categories, opmonoidal functors and transformations. Using Eilenberg-Moore objects, it is shown that for a Hopf monad S, the categories Alg(Coalg(S)) and Coalg(Alg(S)) are canonically isomorphic. The monadic arrows OpMon are then characterized. Finally, the theory of multicategories and a generalization of structure and semantics are used to identify the categories of algebras of Hopf monads. 1. Hopf Monads The purpose of this note is to put the results of [Moerdijk (1999)] into a 2-categorical framework, highlight their universal nature, and so extend those results. Propositions 1.1 and 1.2 of this section are from [Moerdijk (1999)]. Let C be a monoidal category, and (S, η, μ) a monad on the underlying category of C. A Hopf monad structure on S consists of natural transformations
Modelling immigration flows: an application of the bounds test to Fiji-Australia migration

This paper examines the long-run and short-run determinants of migration from Fiji to Australia between 1972 and 2001 using a human capital framework, which is extended to take account of political instability in Fiji. Our main findings are that in the long run the real wage differential and political instability in Fiji are the main determinants. In the short run, there is some evidence that the wage differential and transport costs are important factors, but this finding is not robust across all specifications. Lagged migration and political instability are the most important determinants in the short run.
Pulsatile shear and Gja5 modulate arterial identity and remodeling events during flow-driven arteriogenesis

In the developing chicken embryo yolk sac vasculature, the expression of arterial identity genes requires arterial hemodynamic conditions. We hypothesize that arterial flow must provide a unique signal that is relevant for supporting arterial identity gene expression and is absent in veins. We analyzed factors related to flow, pressure and oxygenation in the chicken embryo vitelline vasculature in vivo. The best discrimination between arteries and veins was obtained by calculating the maximal pulsatile increase in shear rate relative to the time-averaged shear rate in the same vessel: the relative pulse slope index (RPSI). RPSI was significantly higher in arteries than veins. Arterial endothelial cells exposed to pulsatile shear in vitro augmented arterial marker expression as compared with exposure to constant shear. The expression of Gja5 correlated with arterial flow patterns: the redistribution of arterial flow provoked by vitelline artery ligation resulted in flow-driven collateral arterial network formation and was associated with increased expression of Gja5. In situ hybridization in normal and ligation embryos confirmed that Gja5 expression is confined to arteries and regulated by flow. In mice, Gja5 (connexin 40) was also expressed in arteries. In the adult, increased flow drives arteriogenesis and the formation of collateral arterial networks in peripheral occlusive diseases. Genetic ablation of Gja5 function in mice resulted in reduced arteriogenesis in two occlusion models. We conclude that pulsatile shear patterns may be central for supporting arterial identity, and that arterial Gja5 expression plays a functional role in flow-driven arteriogenesis.
Robust Grassmannian prediction for limited feedback multiuser MIMO systems

In this paper, we propose a robust Grassmannian prediction algorithm to provide channel state information (CSI) at the base station for multiuser multiple-input multiple-output (MIMO) systems with delayed limited feedback. The underlying coherence among adjacent quantized CSIs is fully exploited to achieve robustness against the quantization error caused by the limited feedback. Rather than sticking to the nonlinear manifold, we derive that, using the locally Euclidean property of Grassmannian manifolds, the prediction can be obtained by solving a simple linear system in the embedding vector space. Numerical results show that the proposed algorithm is less sensitive to the quantization residual error and thus improves the achievable sum rate while keeping the amount of feedback to a practically low level.
A preliminary survey on software testing practices in Australia

We present the findings of, to the best of our knowledge, the first survey on software testing practices carried out in Australian ICT industry. A total of 65 organizations from various major capital cities in Australia participated in the survey, which was conducted between 2002 and 2003. The survey focused on five major aspects of software testing, namely testing methodologies and techniques, automated testing tools, software testing metrics, testing standards, and software testing training and education. Based on the survey results, current practices in software testing are reported, as well as some observations and recommendations for the future of software testing in Australia for industry and academia.
Deploying and Evaluating Pufferfish Privacy for Smart Meter Data

Realizing a Smart Grid without sacrificing the privacy of consumers is a challenging problem. Data-centric approaches like Puffer fish ensure privacy by transforming data so that certain user-specified information, so-called secrets, cannot be inferred. Deploying Puffer fish on smart-meter data requires application-specific decisions, i.e., A general definition of secrets in time series. We investigate how to perturb energy consumption data in this manner, and we quantify the trade off between privacy and utility.
Fast Non-Negative Orthogonal Matching Pursuit

One of the important classes of sparse signals is the non-negative signals. Many algorithms have already been proposed to recover such non-negative representations, where greedy and convex relaxed algorithms are among the most popular methods. The greedy techniques have been modified to incorporate the non-negativity of the representations. One such modification has been proposed for Orthogonal Matching Pursuit (OMP), which first chooses positive coefficients and uses a non-negative optimisation technique as a replacement for the orthogonal projection onto the selected support. Beside the extra computational costs of the optimisation program, it does not benefit from the fast implementation techniques of OMP. These fast implementations are based on the matrix factorisations. We here first investigate the problem of positive representation, using pursuit algorithms. We will then describe a new implementation, which can fully incorporate the positivity constraint of the coefficients, throughout the selection stage of the algorithm. As a result, we present a novel fast implementation of the Non-Negative OMP, which is based on the QR decomposition and an iterative coefficients update. We will empirically show that such a modification can easily accelerate the implementation by a factor of ten in a reasonable size problem.
Establishing an In Vivo Assay System to Identify Components Involved in Environmental RNA Interference in the Western Corn Rootworm

The discovery of environmental RNA interference (RNAi), in which gene expression is suppressed via feeding with double-stranded RNA (dsRNA) molecules, opened the door to the practical application of RNAi-based techniques in crop pest management. The western corn rootworm (WCR, Diabrotica virgifera virgifera) is one of the most devastating corn pests in North America. Interestingly, WCR displays a robust environmental RNAi response, raising the possibility of applying an RNAi-based pest management strategy to this pest. Understanding the molecular mechanisms involved in the WCR environmental RNAi process will allow for determining the rate limiting steps involved with dsRNA toxicity and potential dsRNA resistance mechanisms in WCR. In this study, we have established a two-step in vivo assay system, which allows us to evaluate the involvement of genes in environmental RNAi in WCR. We show that laccase 2 and ebony, critical cuticle pigmentation/tanning genes, can be used as marker genes in our assay system, with ebony being a more stable marker to monitor RNAi activity. In addition, we optimized the dsRNA dose and length for the assay, and confirmed that this assay system is sensitive to detect well-known RNAi components such as Dicer-2 and Argonaute-2. We also evaluated two WCR sid1- like (sil) genes with this assay system. This system will be useful to quickly survey candidate systemic RNAi genes in WCR, and also will be adaptable for a genome-wide RNAi screening to give us an unbiased view of the environmental/systemic RNAi pathway in WCR.
UGV-MAV Collaboration for Augmented 2D Maps

Over the past couple of years, with the development of efficient control algorithms, micro aerial vehicles have come into the picture. In this paper, we consider the problem of creating a map of an indoor environment which provides more information than a 2D map and at the same time is more accurate than the contemporary 3D mapping algorithms. We propose a novel collaborative system, consisting of an unmanned ground vehicle and a micro aerial vehicle, which is used to create augmented 2D maps using the distinct sensing capabilities of these two robots. This system works in a collaborative manner such that the two robots complement each others movement and sensing capabilities.
Robust stabilization of interval plants using Kronecker summation method

This paper deals with design of continuous-time robustly stabilizing Proportional-Integral (PI) controllers for interval systems using the combination of Kronecker summation method, sixteen plant theorem and an algebraic approach to controller tuning. The effectiveness and practical applicability of the proposed method is demonstrated in both simulation and real experiments including control of a third order nonlinear electronic plant.
Instantaneous Perturbation of Dentate Interneuronal Networks by a Pressure Wave-Transient Delivered to the Neocortex

Whole-cell patch-clamp recordings and immunocytochemical experiments were performed to determine the short- and long-term effects of lateral fluid percussion head injury on the perisomatic inhibitory control of dentate granule cells in the adult rat, with special reference to the development of trauma-induced hyperexcitability. One week after the delivery of a single, moderate (2.0–2.2 atm) mechanical pressure wave to the neocortex, the feed-forward inhibitory control of dentate granule cell discharges was compromised, and the frequency of miniature IPSCs was decreased. Consistent with the electrophysiological data, the number of hilar parvalbumin (PV)- and cholecystokinin (CCK)-positive dentate interneurons supplying the inhibitory innervation of the perisomatic region of granule cells was decreased weeks and months after head injury. The initial injury to the hilar neurons took place instantaneously after the impact and did not require the recruitment of active physiological processes. Furthermore, the decrease in the number of PV- and CCK-positive hilar interneurons was similar to the decrease in the number of the AMPA-type glutamate receptor subunit 2/3-immunoreactive mossy cells, indicating that the pressure wave-transient causes injurious physical stretching and bending of most cells that are large and not tightly packed in a cell layer. These results reveal for the first time that moderate pressure wave-transients, triggered by traumatic head injury episodes, impact the dentate neuronal network in a unique temporal and spatial pattern, resulting in a net decrease in the perisomatic control of granule cell discharges.
One New Research on Method of Intelligent Substation Network Traffic Prediction

With the gradual implementation of intelligent network transformation substation, the industry began to pay attention from the smart substation network flow forecasting techniques. Intelligent substation network traffic anomaly event directly affects the operation of the protection device reliability, speed and agility. The paper first combination of gray theory and artificial neural network algorithm, create and analyze a gray neural network model, Then through additional momentum variable learning rate method right to update the value of gray neural network strategy to improve, Proposes an model is based on improved gray neural network intelligent substation network traffic prediction, finally the use of smart substation station level switches network traffic data, for example, to the original frequency of data collection as the basis for simulation, experiments show that the model predicts high accuracy, fast convergence, improved intelligent substation network traffic prediction accuracy and rapidity, to protect the safe operation of the power grid.
This paper first analyzes why voltage instability occurs in mature yet competitive power systems , and then investigate diverse voltage stability issues in deregulated power markets using a commercial transient simulation program EUROSTAG

This paper first analyzes why voltage instability occurs in mature yet competitive power systems, and then investigate diverse voltage stability issues in deregulated power markets using a commercial transient simulation program EUROSTAG. Dynamic behaviors of major power system components, i.e., speed governor, excitation element, inductive motor, ULTC and mechanically switched shunt capacitor et al, are thoroughly examined by a small yet typical equivalent system. The presented simulation results help better understand the mechanism of the voltage collapse phenomena, and highlight the importance of dynamic reactive reserves, like generators, in dynamic voltage stability enhancement.
Reproducibility of image quality for moving objects using respiratory-gated computed tomography: a study using a phantom model

To investigate the reproducibility of computed tomography (CT) imaging quality in respiratory-gated radiation treatment planning is essential in radiotherapy of movable tumors. Seven series of regular and six series of irregular respiratory motions were performed using a thorax dynamic phantom. For the regular respiratory motions, the respiratory cycle was changed from 2.5 to 4 s and the amplitude was changed from 4 to 10 mm. For the irregular respiratory motions, a cycle of 2.5 to 4 or an amplitude of 4 to 10 mm was added to the base data (i.e. 3.5-s cycle, 6-mm amplitude) every three cycles. Images of the object were acquired six times using respiratory-gated data acquisition. The volume of the object was calculated and the reproducibility of the volume was decided based on the variety. The registered image of the object was added and the reproducibility of the shape was decided based on the degree of overlap of objects. The variety in the volumes and shapes differed significantly as the respiratory cycle changed according to regular respiratory motions. In irregular respiratory motion, shape reproducibility was further inferior, and the percentage of overlap among the six images was 35.26% in the 2.5- and 3.5-s cycle mixed group. Amplitude changes did not produce significant differences in the variety of the volumes and shapes. Respiratory cycle changes reduced the reproducibility of the image quality in respiratory-gated CT.
Cross-layer optimized placement and routing for FPGA soft error mitigation

As the feature size of FPGA shrinks to nanometers, soft errors increasingly become an important concern for SRAM-based FPGAs. Without consideration of the application level impact, existing reliability-oriented placement and routing approaches analyze soft error rate (SER) only at the physical level, consequently completing the design with suboptimal soft error mitigation. Our analysis shows that the statistical variation of the application level factor is significant. Hence in this work, we first propose a cube-based analysis to efficiently and accurately evaluate the application level factor. And then we propose a cross-layer optimized placement and routing algorithm to reduce the SER by incorporating the application level and the physical level factor together. Experimental results show that, the average difference of the application level factor between our cube-based method and Monte Carlo golden simulation is less than 0.01. Moreover, compared with the baseline VPR placement and routing technique, the cross-layer optimized placement and routing algorithm can reduce the SER by 14% with no area and performance overhead.
Assimilation of photochemically active species and a case analysis of UARS data

We present a short overview of applications of estimation theory in atmospheric chemistry and discuss some common methods of gridding and mapping of irregular satellite observations of chemical constituents. It is shown that these methods are unable to produce truly synoptic maps of short-lived photochemically active species due to insufficient temporal and spatial density of satellite observations. The only way to overcome this limitation is to supplement observations with prior independent information given, for instance, by atmospheric numerical models and/or climatologies. Objective approaches to combining such prior information with observations are commonly referred to as data assimilation. Mathematical basis of data assimilation known as optimal estimation equations is presented following Lorenc [1986]. Two particular techniques of data assimilation, the variational method and the extended Kalman filter, are briefly described, and their applications to time-dependent numerical photochemical models are discussed. We investigate validity of the linear approximation which is utilized in both methods, present time evolution of the linearization and covariance matrices, and discuss some of their properties. On the basis of ideas of Fisher and Lary [1995] we then employ a trajectory model and a photochemical box model for assimilation and mapping of the Upper Atmosphere Research Satellite (UARS) measurements of chemical species. The assimilation is performed using the variational technique and the extended Kalman filter, and results of both methods are presented and discussed.
Binaural auralization based on spherical‐harmonics beamforming

The binaural auralization of a 3D sound field using spherical‐harmonics beamforming (SHB) techniques was investigated and compared with the traditional method using a dummy head. The new procedure was verified by comparing simulated room impulse responses with directly measured ones both monaurally and binaurally. The objective comparisons show that there is good agreement in the frequency range between 0.1 to 6.4 kHz. Psychoacoustic attributes of multi‐channel reproduced sounds were measured in a listening experiment to validate the method subjectively. The results show that subjective ratings of the width, spaciousness and preference of different audio reproduction modes auralized based on SHB were not significantly different from those obtained for dummy head measurements. Thus binaural synthesis using SHB may be a useful tool to reproduce a 3D sound field binaurally while saving considerably on measurement time because head rotation can be simulated based on a single recording.
Web Fact Seeking For Business Intelligence : a Meta Engine Approach

Inspired by our exploration of the applicability of automated question answering (QA) technology to the task of business intelligence and general design science principle, we advocate a meta approach to the QA (fact seeking) applications since it does not rely on a single system and may provide the necessary accuracy and responsiveness. We present our prototype of a fact seeking meta engine, the first known meta QA prototype, and report its empirical evaluation. Our results support the added value of the meta approach: the performance of the combined system surpasses the underlying performances of its components. The evaluation also indicates that, on average, our meta system answers every second answer perfectly, which we believe is very encouraging for its practical applications. We also discuss the challenges that meta approach faces, how they can be addressed and what are the design implications.
20 TYPES AND DOCUMENTS : STRUCTURING BUILDING PROJECT INFORMATION

We describe a methodology for integrating a number of design documents of different formats within a single information structure. When this integrated structure is highly related, it provides support for effective searching and browsing of this information. To achieve such relatedness, we consider a notion of types from architecture as a semantic structure for project document management in the AEC industry. We discuss specific techniques to support this use of types with respect to EDMS’s and Web-based project management systems. We describe a prototype application, a presentation tool for architectural analyses that combines these techniques.
Liquid crystal display surface uniformity defect inspection using analysis of variance and exponentially weighted moving average techniques

Display quality is part of the final liquid crystal display (LCD) inspection process before shipping. A ‘limited sample’ is provided based on the agreement between the manufacturer and the customer. This inspection usually includes an operator who compares the LCD product with the limit sample using the naked eye. The procedure often causes controversy in the manufacturing plant and between the manufacturer and customers. This study attempts to establish a more objective, automatic method to determine the MURA-type defects in LCD panels. A luminance meter is used as the measurement device. An LCD panel is divided into 144 areas. Five points are measured to obtain the luminances. Analysis of variance and the exponentially weighted moving average techniques are applied to determine the existence of MURA defects. Fifty normal LCD panels and 50 MURA defects panels were used to test the inspection method. All 50 LCD panels with MURA defects were correctly identified using the proposed inspection method. The proposed inspection method can help LCD manufacturers reduce the variation in LCD panel inspection results and establish a better relationship with customers through a common inspection mechanism.
“I can feel it too!”: Emergent empathic reactions between synthetic characters

Empathy is often seen as the capacity to perceive, understand and experience others' emotions. This concept has been incorporated in virtual agents to achieve better believability, social interaction and user engagement. However, this has been mostly done to achieve empathic relations with the users. Instead, in this article we focus on empathy between synthetic characters and propose an analytical approach that consists in a generic computational model of empathy, supported by recent neuropsychological studies. The proposed model of empathy was implemented into an affective agent architecture. To evaluate the implementation a small scenario was defined and we asked a group of users to visualize it with the empathy model and another group to visualize it without the model. The results obtained confirmed that our model was capable of producing significant effects in the perception of the emergent empathic responses.