Miracle-dz/UniFAR-FTUs huggingface dataset:
Expansion and equity in Australian higher education: three propositions for new relations

This article outlines three broad propositions for student equity in Australian higher education (HE), arising from the Australian Government's recent policy announcement to expand and widen student participation. The first is that a new relationship between student demand for places and their supply is on the horizon, unlike any other in Australia's history. Specifically, demand will struggle to match the intended supply. Given these new arrangements between government, institution and applicant, the article's second proposition is that governments and universities will need to develop a new regard for the people they seek to attract. And, following on from this, they will need to pay more attention to the nature of HE and its appeal to people who traditionally have not been all that interested. Informing this account are an examination of statistical data, analysis of university outreach programs, and a comparison of current principles of effective teaching in HE. The article concludes that advancing student equity in the current context will require new relations between institutions and students, which include a more sophisticated appreciation for the diversity of students and their communities, and for what they potentially contribute to HE.
Local Quadrature Reconstruction on Smooth Manifolds

Non-Linear Dimensionality Reduction (NLDR) techniques such as ISOMAP, LLE, Laplacian Eigenmaps etc. attempt to estimate low-dimensional latent descriptors for data assumed to be drawn from an m-dimensional manifold in an ambient n-dimensional space. Out-ofSample Extension the problem of estimating the latent vectors for novel data has attracted considerable attention in the literature. In this thesis, we consider the opposite problem, that of reconstructing new high-dimensional points, given a novel latent-vector in a previously discovered embedding. Such a procedure finds relevance in applications such as video interpolation or robot motion planning. Some global methods can be applied to the problem, but these are polynomials on the total number of data points N resulting in a complexity of O(N3), where N is often in the thousands. In contrast, we propose a Local Quadrature Reconstruction approach that looks at only the local k-neighbourhood for which the complexity reduces to O(k3) (k may be about 10). LQR achieves low error by estimating the second order error terms based on a second order differential geometric formulation for a small neighbourhood around the query point on the manifold. Main features of LQR include its fast reconstruction time and lack of a training phase, but since k increases as O(m2) it is currently limited to manifolds with low intrinsic dimension. Performance analysis of LQR on several point and image sets is presented, and a possible application for frame interpolation on videos is also studied. To my parents and sister for their love and support.
Exploiting Agent-Oriented Programming for Building Advanced Web 2.0 Applications

We believe that agent-oriented programming languages and multi-agent programming technologies provide an effective level of abstraction for tackling the design and programming of mainstream software applications, besides being techniques effective for dealing with (Distributed) Artificial Intelligence problems. In this paper we support this claim in practice by discussing the use of a platform integrating two main agent programming technologies – Jason agent programming language and CArtAgO environment programming framework – to the development of Web 2.0 applications. Following the cloud computing perspective, these kinds of applications will more and more replace desktop applications, exploiting the Web infrastructure as a common distributed operating system, raising however challenges that are not effectively tackled – we argue – by mainstream programming paradigms, such as the objectoriented one.
A Spatially Detailed Model of Isometric Contraction Based on Competitive Binding of Troponin I Explains Cooperative Interactions between Tropomyosin and Crossbridges

Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB), tropomyosin and troponin within a contractile regulatory unit (RU) to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU), between crossbridges (XB-XB), as well more complex interactions between crossbridges and regulatory units (XB-RU interactions). For the steady-state force-calcium relationship, our framework predicts that: (1) XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca2+], but have only small effects on cooperativity. (2) XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3) RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RU’s unblocking. (4) Myosin affinity for short (1–4 RU) unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca2+] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment ktr is explained by transient blocking of RU’s by a temporary decrease in XB-RU effects.
Increased Rate of CD4+ T-Cell Decline and Faster Time to Antiretroviral Therapy in HIV-1 Subtype CRF01_AE Infected Seroconverters in Singapore

Background It remains controversial as to whether HIV-1 subtypes influence disease progression. Singapore offers a unique opportunity to address this issue due to the presence of co-circulating subtypes. We compared subtype CRF01_AE and non-CRF01_AE infected patients, with regards to estimated annual rate of CD4+ T-cell loss and time from estimated data of seroconversion (EDS) to antiretroviral therapy (ART). Methods We recruited ART-naive patients with known dates of seroconversion between October 2002 and December 2007 at the Singapore Communicable Disease Centre, the national reference treatment centre. Multilevel mixed-effects models were used to analyse the rate of CD4+ T-cell decline. Time from EDS to ART was analyzed with the Kaplan-Meier survival method and compared with Cox proportional hazards models. Results 54 patients with previously assigned HIV-1 subtypes (24 CRF01_AE, 17 B, 8 B', 1 CRF33_01B, 3 CRF34_01B and 1 G) were observed for 89 patient-years. Subtype CRF01_AE and non-CRF01_AE infected patients did not differ in age, gender, risk factor, rate of symptomatic seroconversion, baseline CD4+ T-cell count, log10 viral load or haemoglobin concentration. The estimated annual rate of CD4+ T-cell loss was 58 cells/mm3/year (95% CI: 7 to 109; P = 0.027) greater in subtype CRF01_AE infected patients compared to non-CRF01_AE patients, after adjusting for age, baseline CD4+ T-cell count and baseline log10 viral load. The median time from EDS to ART was 1.8 years faster comparing CRF01_AE to non-CRF01_AE infected patient with a 2.5 times (95% CI: 1.2-5.0; P = 0.013) higher hazard for ART initiation, after controlling for age, baseline CD4+ T-cell count and baseline log10 viral load. Conclusions Infecting subtype significantly impacted the rate of CD4+ T-cell loss and time to treatment in this cohort. Studies to understand the biological basis for this difference could further our understanding of HIV pathogenesis.
Tense over time: testing the Agreement/Tense Omission Model as an account of the pattern of tense-marking provision in early child English*

ABSTRACT The Agreement/Tense Omission Model (ATOM) predicts that English-speaking children will show similar patterns of provision across different tense-marking morphemes (Rice, Wexler & Hershberger, 1998). The aim of the present study was to test this prediction by examining provision rates for third person singular present tense and first and third person singular forms of copula BE and auxiliary BE in longitudinal data from eleven English-speaking children between the ages of 1 ; 10 and 3 ; 0. The results show, first, that there were systematic differences in the provision rates of the different morphemes; second, that there were systematic differences in the rate at which all of the three morphemes were provided with pronominal and lexical subjects; and, third, that there were systematic differences in the rate at which copula BE and auxiliary BE were provided with the third person singular pronominal subjects It and He and the first person singular subject pronoun I. These results replicate those of Wilson (2003), while controlling for some possible objections to Wilson's analysis. They thus provide further evidence against the generativist view that children's rates of provision of different tense-marking morphemes are determined by a single underlying factor, and are consistent with the constructivist view that children's rates of provision reflect the gradual accumulation of knowledge about tense marking, with much of children's early knowledge being embedded in lexically specific constructions.
EENMDRA: Efficient Energy and Node Mobility based Data Replication Algorithm for MANET

A mobile ad-hoc network (MANET) is a self- organizing, rapidly deployable network which consists of wireless nodes without infrastructure. All nodes in a MANET are capable of moving actively and can be connected dynamically. It is used in various applications like video conferencing, rescue operations, military applications, Disaster Management etc. So the data sharing in network play a vital role. In order to ensure the effective data sharing, the data replication is needed. The main aim of the work is to develop the efficient energy and node mobility based data replication algorithm to balance the Query delay, energy consumption and data availability in MANET. Due to the presence of the network partition, mobile nodes in one partition are not able to access the data hosted by nodes in the other partition. So the performance of data access is degraded. Existing methods aims at balancing trade-off between query delay and data availability. In proposed method we focus on balancing between the node's energy consumption, data availability and delay. By simulation results show that the proposed scheme achieves better performance than the existing methods. Keywords - MANET, Data replication, Query delay, Network partition data availability and energy consumption.
ℛ2: Incremental ℛeprogramming using ℛelocatable code in networked embedded systems

We present ℛ<sup>2</sup>, an incremental ℛeprogramming approach using Relocatable code, to improve program similarity for efficient incremental reprogramming in networked embedded systems. ℛ<sup>2</sup> achieves a higher degree of similarity than existing approaches by mitigating the effects of both function shifts and data shifts. ℛ<sup>2</sup> makes efficient use of memory and does not degrade program quality. It adopts an optimized differencing algorithm to generate small delta files for efficient dissemination. We demonstrate ℛ<sup>2</sup>'s advantages through detailed analysis of TinyOS examples. We also present case studies on the software programs of a large-scale and long-term sensor system—GreenOrbs. Results show that ℛ<sup>2</sup> reduces the dissemination cost by approximately 65% compared to Deluge—state-of-the-art network reprogramming approach, and reduces the dissemination cost by approximately 20% compared to Zephyr and Hermes—the latest works on incremental reprogramming.
Pharmacotherapy of dementia with Lewy bodies

The syndrome of dementia with Lewy bodies (DLB) is characterised by the clinical triad of fluctuating cognitive impairment, recurrent visual hallucinations and spontaneous motor features of Parkinsonism. In an attempt to define DLB as a distinct clinical syndrome separate from Alzheimer’s disease (AD) and Parkinson’s disease (PD) with dementia, a consensus workshop in 1995 established a new set of diagnostic criteria. Dementia that precedes or accompanies the onset of spontaneous (i.e., not neuroleptic-induced) Parkinsonism is termed DLB. In addition, fluctuations in alertness, cognition and function and visual hallucinations are emphasised and included as core features of DLB. The degree to which an individual patient exhibits cognitive impairment, behavioural problems and Parkinsonian features is variable. Therefore, treatment must be individualised. Although there are no officially approved drugs for DLB, limited experience from clinical trials, as well as past experience with the treatment of AD and PD patients, provide some basis for making drug choices. The cholinergic deficit seen in DLB makes cholinesterase inhibitor drugs the mainstay of treatment for cognitive impairment. This class of drugs has also shown therapeutic benefit in reducing hallucinations and other neuropsychiatric symptoms of the disease. Because of their relatively greater therapeutic window, cholinesterase inhibitors are also used as first-line therapy for the treatment of psychosis in DLB. Patients with DLB are extremely sensitive to the extrapyramidal side effects of neuroleptic medications. Thus, only atypical antipsychotic agents such as quetiapine, should be considered as alternative treatment for psychosis. Anxiety and depression are best treated with selective serotonin re-uptake inhibitors, whereas REM sleep behaviour disorder may be treated with low dose clonazepam. Parkinsonism responds to dopaminergic agents; however, precipitation or aggravation of hallucinosis may occur. Levodopa is preferred over dopamine agonists due to its lower propensity to cause hallucinations and somnolence. As the diagnostic criteria for DLB become more refined and validated by postmortem studies, it is hoped that rigorous, well-designed trials will be performed, aimed at alleviating the primary target symptoms of dementia, psychosis and Parkinsonism.
Concept Mapping: Developing Guides to Literature.

Students often complain that they get lost reading literature. Con cept maps, which are diagrams that show the relationships among con cepts in a piece of writing, can help stu dents travel through literature to desti nations that they can identify and de fend. This article describes the use of instructor and student concept maps for Ernest Hemingway's The Old Man and The Sea and Albert Camus' The Stranger and suggests that concept mapping is an aid toward student self education and autonomy. When literature appears confusing to students as readers, they cannot see what their professors consider good. A method to resolve this difficulty, con cept mapping, is a heuristic device de scribed by D. B. Go win in Educating (1981, 84). It is a tool to show the rela tionships among concepts in a particu lar piece of writing, regardless of the discipline. In virtually any formal writ ing, key concepts organize the mate rial. Concepts or regularities in events are linked together into a meaningful whole, which is the concept map. When this method is applied to liter ature, characters, action, and symbols are the concepts. Given a map before reading, a student has a direction in which to travel, signs to consider along the way, and a destination to achieve. After reading, students can draw a
Expression of TRPV6 and CaBP-D28k in the egg shell gland (uterus) during the oviposition cycle of the laying hen

1. The aim of this study was to investigate the localisation of the transient receptor potential vanilloid channel type 6 (TRPV6) in egg shell gland (ESG) and examine the dynamic expression of TRPV6 and Calbindin-d28k (CaBP-D28k), as well as the changes in concentration of total calcium (Ca), total inorganic phosphorus (P), alkaline phosphatase (ALP), parathyroid hormone (PTH) and calcitonin (CT) in plasma during the oviposition cycle. 2. The plasma ALP activity was notably increased at 8 h. In addition, plasma CT was highest at 0 h and significantly lower at 8 h. The change of plasma PTH concentration increased slightly post-oviposition and reached a maximum at 16 h. 3. Immunohistochemical analysis indicated that TRPV6 was strongly localised to the apical luminal epithelium of the mucosa. The mRNA levels of TRPV6 and CaBP-D28k in the ESG remained very low from 0 to 4.5 h, but were significantly increased at 16 h. Furthermore, Western blotting analysis showed that the expression of TRPV6 and CaBP-D28k also reached a maximum at 16 h and was different from the concentration of CaBP-D28k. 4. In conclusion, the epithelial Ca2+ channel TRPV6 is strongly expressed in the epithelial cells of the eggshell gland, and the increase of TRPV6 and CaBP-D28k mRNA and protein expression during eggshell formation suggests that active Ca2+ transcellular transport exerts significant effects in delivering active calcium in the ESG.
A low cost reliable architecture for S-Boxes in AES processors

This paper presents a fault-tolerant architecture for AES processors in order to mitigate the reliability issues introduced by the continued shrinking of CMOS technology. We concentrate on the faults occurring on S-Boxes which consume the largest hardware in AES processor. This hybrid solution combines time redundancy and hardware redundancy strategies for masking all single transient and permanent faults. By exploiting the inherent redundancy of AES processor with parallel implementation, the proposed solution limits the area overhead and overcomes many popular fault-tolerant techniques such as Triple Modular Redundancy approach and Triple Temporal Redundancy approaches.
ECFI: Asynchronous Control Flow Integrity for Programmable Logic Controllers

Programmable Logic Controllers (PLCs) are a family of embedded devices that are being used to control physical processes in critical infrastructures. Similar to other embedded devices, PLCs are vulnerable to memory corruption and control-flow hijacking attacks. Because PLCs are being used for critical control applications, compromised PLCs constitute a significant security and safety risk. In this paper, we introduce a novel, PLC-compatible control-flow integrity (CFI) mechanism named ECFI to protect such devices from control-flow hijacking attacks. Our CFI approach is the first system for real-time PLCs and considers the runtime operation of the PLC as the highest priority. We implemented a prototype of ECFI and tested it in a real-world industrial PLC against different kinds of attacks. Our performance evaluation demonstrates that ECFI is an efficient, non-intrusive CFI solution that does not impose notable performance overhead and maintains the timeliness of PLC runtime operations, a critical property for this kind of embedded systems.
Fast Second Order Stochastic Backpropagation for Variational Inference

We propose a second-order (Hessian or Hessian-free) based optimization method for variational inference inspired by Gaussian backpropagation, and argue that quasi-Newton optimization can be developed as well. This is accomplished by generalizing the gradient computation in stochastic backpropagation via a reparametrization trick with lower complexity. As an illustrative example, we apply this approach to the problems of Bayesian logistic regression and variational auto-encoder (VAE). Additionally, we compute bounds on the estimator variance of intractable expectations for the family of Lipschitz continuous function. Our method is practical, scalable and model free. We demonstrate our method on several real-world datasets and provide comparisons with other stochastic gradient methods to show substantial enhancement in convergence rates.
An evaluation of approaches to classification rule selection

In this paper a number of classification rule evaluation measures are considered. In particular the authors review the use of a variety of selection techniques used to order classification rules contained in a classifier, and a number of mechanisms used to classify unseen data. The authors demonstrate that rule ordering founded on the size of antecedent works well given certain conditions.
A minimal solution to the autocalibration of radial distortion

Epipolar geometry and relative camera pose computation are examples of tasks which can be formulated as minimal problems and solved from a minimal number of image points. Finding the solution leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. In this paper we provide a solution to the problem of estimating radial distortion and epipolar geometry from eight correspondences in two images. Unlike previous algorithms, which were able to solve the problem from nine correspondences only, we enforce the determinant of the fundamental matrix be zero. This leads to a system of eight quadratic and one cubic equation in nine variables. We simplify this system by eliminating six of these variables. Then, we solve the system by finding eigenvectors of an action matrix of a suitably chosen polynomial. We show how to construct the action matrix without computing complete Grobner basis, which provides an efficient and robust solver. The quality of the solver is demonstrated on synthetic and real data.
Multimodal Classification of Violent Online Political Extremism Content with Graph Convolutional Networks

In this paper we present a multimodal approach to categorizing user posts based on their discussion topic. To integrate heterogeneous information extracted from the posts, i.e. text, visual content and the information about user interactions with the online platform, we deploy graph convolutional networks that were recently proven effective in classification tasks on knowledge graphs. As the case study we use the analysis of violent online political extremism content, a challenging task due to a particularly high semantic level at which extremist ideas are discussed. Here we demonstrate the potential of using neural networks on graphs for classifying multimedia content and, perhaps more importantly, the effectiveness of multimedia analysis techniques in aiding the domain experts performing qualitative data analysis. Our conclusions are supported by extensive experiments on a large collection of extremist posts.
Sensorless control of induction motors by artificial neural networks

In this letter, we propose a voltage-source inverter control working in the open loop of an induction motor measuring the stator current and using an artificial neural network. This technique has the mission to estimate the speed and torque of the rotor without using sensors. With this, a simple and cheap method of control is obtained, with as much precision and robustness as other more complex ones.