Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Inference: Test and Multiple Tests

In this paper, we view that real-world scientific inference about an assertion of interest on unknown quantities is to produce a probability triplet (p, q, r), conditioned on available data. The probabilities p and q are for and against the truth of the assertion, whereas r = 1 − p − q is the remaining probability called the probability of " don't know ". Such a (p, q, r)-formulation provides a promising way of representing realistic uncertainty assessment in statistical inference. With a brief discussion of what we call inferential models for producing (p, q, r) probability triplets for assertions, we focus on a particular inferen-tial model for inference about an unobserved sorted uniform sample. We show how this inferential model can be used for (i) single tests, (ii) robust estimation of the empirical null distribution in the context of the local FDR method of Bradley Efron, and (iii) large-scale simultaneous hypothesis problems, including the many-normal-means problem and the problem of identifying significantly expressed genes in microarray data analysis. These examples indicate that hypothesis testing problems can be formulated and solved in a new way of probabilistic inference.
Recent Productivity Trends in New Zealand Primary Sectors

This technical paper on the productivity trends in the agriculture sector and the forestry and logging sector is an update and extension of MAF Policy Technical Paper 96/2. In the latter, productivity trends in the agriculture sector were measured from year ended March 1972 to 1992 using two approaches, the Laspeyre and the Tornqvist. The extension of the methodologies to the forestry and logging sector brings together all the land based primary sectors that MAF has policy responsibilities for.
SIOC: an approach to connect web-based communities

Online communities are islands of people and topics that are not interlinked. Complementary discussions exist on disparate systems but it is currently difficult to exploit the available distributed information. A Semantically Interlinked Online Community (SIOC) can enable efficient information dissemination across communities by creating an ontology that will model concepts identified in discussion methods. Data instances can be accessed from community sites using this ontology, enabling connections between local and remote concept instances, and allowing queries on, or transfer of, the data. By searching on one forum, the ontology and interface will allow users to find information on other forums that use a SIOC-based system architecture. Other uses include cross-site querying, topic-related searches, and the importing of SIOC data into other systems. Fusing information and inferring links among various applications and types of information with SIOC provide relevant insights that make the community information available on the internet more valuable.
Empirical study on Parsing Chinese Based on Collins ’ Model

There is a large set of details in Collins’ model which has been proved to be quite important in English parsing. When we apply the model to parse other languages such as Chinese, it is very important to know whether these details will still work. We present a careful assessment of the applicability of a number of detail features in Collins’ model when adapted to Chinese. We find that most of them work well for Chinese parsing; some of them do not help or even hurt the performance of Chinese parser. By combining a lexicalized tagging model and Collins’ model, we present the syntactic parsing result on the newly available CTB5.1 and achieve 84.45% precision and 84.34% recall on the standard test set.
Two-level Hierarchical Scheduling Algorithm for Real-time Multiprocessor Systems

The Earliest Deadline First (EDF) scheduling algorithm has the least runtime complexity among joblevel fixed-priority algorithms for scheduling tasks on multiprocessor architectures. However, EDF suffers from suboptimality in multiprocessor systems. This paper proposes a new restricted migration-based scheduling algorithm for multiprocessor real-time systems, called Two-level Hierarchical Scheduling Algorithm (2L-HiSA), to address this sub-optimality. 2L-HiSA algorithm divides the problem of multiprocessor scheduling into a two-level hierarchy of schedulers. This algorithm works in two phases: i- A taskpartitioning phase in which, each task from application task set is assigned to a specific processor by following simple bin-packing approach. If a task can not be partitioned on any processor in the platform, it qualifies as migrating task. ii- A processor-grouping phase in which, processors are clustered together such that, per cluster, the unused fragmented computation power equivalent to at most one processor is available. We provide schedulability analysis and experimental evaluation to support our proposition. Moreover, our simulation results show an average difference of 18-folds in the number of preemptions and 10-folds in the number of task migrations under 2L-HiSA and PD2 algorithm.
Expression of structurally diverse Qa-2-encoded molecules on the surface of cloned cytotoxic T lymphocytes

Extracts of 125I-labeled cloned murine cytotoxic T lymphocytes (CTL) were immunoprecipitated with alloantisera to the cloned CTL and rabbit antisera to beta-2 microglobulin. Polyacrylamide gel electrophoresis (PAGE) of the specific precipitates revealed, as expected, 125I-labeled components that corresponded to products of class I genes of the major histocompatibility complex (MHC). However, additional class I gene products of relatively low apparent molecular weight (Mr) were also observed. Similar analyses of spleen cells from a variety of MHC- congenic mouse strains suggested that the class I molecules of relatively low Mr are encoded in the Qa-2 region of the MHC, and this was confirmed by immunoprecipitation with a monoclonal antibody to Qa- 2. Surprisingly, however, the cell surface Qa-2 molecules of different CTL clones differed in Mr, in isoelectric focusing (IEF) pattern, and in the number of distinguishable molecules expressed per clone: some clones seemed to express only a single Qa-2-encoded molecule while others expressed two distinct ones. Treatment of the immunoprecipitated Qa-2 with endoglycosidase F (Endo F) resulted in a decrease in Mr of approximately 5,000-6,000, corresponding to the expected loss of N- linked oligosaccharides, but the decrease did not eliminate structural variability among the clones. Structural diversity of the Qa-2-encoded molecules expressed on CTL could arise because CTL clones differ (a) in the particular Qa-2 genes they express, (b) in the way they splice Qa-2 gene transcripts or, perhaps, (c) in Endo F-resistant oligosaccharides on their Qa-2 molecules.
Zhang fractals yielded via solving nonlinear equations by discrete-time complex-valued ZD

In this paper, a novel kind of new fractals, named Zhang fractals, is yielded by using the discrete-time complex-valued Zhang dynamics (DTCVZD) to solve the nonlinear equations in the complex domain. Such a novel DTCVZD model is designed based on the elimination of an indefinite complex-valued error function, instead of a square-based non-negative energy function associated with the discrete-time complex-valued gradient-based dynamics (DTCVGD). Comparing with the well-known (generalized) Newton fractals (i.e., the famous fractals generated by the well-known Newton iteration), we find that the novel Zhang fractals synthesized by the proposed DTCVZD model incorporate such Newton fractals as special cases. The Zhang fractals generated by the novel DTCVZD model are completely different from Newton fractals. The DTCVZD model using different types of activation functions can be seen as a new iterative algorithm to generate new fractals, i.e., Zhang fractals.
Text Summarization Review

With the explosion of information supplied by the growth of the World Wide Web, it is no longer suitable for a human observer to understand all the data coming in diverse languages. With this growth of information and available computing power, automatic classification and summarization of textual data gains increasingly high importance. The idea of text summarization research is to summarize a body of texts by extracting sentences that have particular properties. Review of text summarization such as impotentness, related works, evaluation benchmark etc. In the future, we will propose solution for the limitations have been identified in this paper.
Latent Factor Model Based on Simple Singular Value Decomposition for Personalized Comment Recommendation

With the fast development of the e-commercial and content management web application in web 2.0 communities, more and more web communities support users in making comment about the objects they have reviewed. Comments do assist users to learn about the items they are reviewing. However, there are always hundreds of comments about an item, and to review them one by one is a time consuming job. Since there are some comments are given casually and some are irrelevant to the user. Motivated by this situation, we propose a latent factor model based on singular value decomposition(SVD) for profiling user and comment in order to achieve what we call "Personalized Comment Recommendation". We also conduct experiment on the new proposed model in a real life data set, and the experimental result shows that our implementation achieves an good performance.
Neurally plausible sparse coding via local competition and thresholding

While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms underlying this ability are not known. We present a class of neurally plausible locally competitive algorithms that correspond to a collection of interesting sparse coding principles that attempt to minimize a weighted combination of MSE and a coefficient cost function. These systems operate via local inhibitory competitions and thresholding and are amenable to analog hardware implementation for time-varying inputs. We examine one of these systems and illustrate several important properties: it encourages sparsity as much as possible (exhibiting performance comparable to greedy algorithms), but allows sparsity to be slightly sacrificed to get increased regularity when encoding time-varying inputs.
Assessment of applicability of robotic walker for post-stroke hemiparetic individuals through muscle pattern analysis

Stroke is a leading cause of morbidity and mortality worldwide. In most patients, the stroke causes disabilities that hamper the performance of daily tasks autonomously. The most common clinical features in these individuals are hemiparesis, abnormal gait pattern, muscle spasticity and balance loss. There are several studies about the use of robotic devices in hemiparetic individuals, for example for rehabilitation. The robotic walker developed at UFES/Brazil will be assessed for its applicability, using Surface Electromyography (sEMG) to verify the muscle activation during the gait in individuals with post-stroke hemi-paresis. Preliminary tests are being made with the proposed methodology to analyse the robotic walker, but first using a conventional walker two frontal wheels as assistant gait. Two healthy volunteers performed initially a path without the aid of the walker and then with its aid along a flat straight route. sEMG signals are analyzed in order to assess the muscle activity during the gait. After analyzing the data, the results were compared between the free and assisted gait. With the use of the walker the gait speed in healthy volunteers was reduced and, consequently, changes occurred during activation of the muscles. Changes caused by shifting down are important due to improper adjustment of the height of the walker leads to gait changes. As future work, we intend assess the use of robotic walker in clinical trials.
Prefrontal Lobe Brain Reserve Capacity with Resistance to Higher Global Amyloid Load and White Matter Hyperintensity Burden in Mild Stage Alzheimer’s Disease

Background Amyloid deposition and white matter lesions (WMLs) in Alzheimer's disease (AD) are both considered clinically significant while a larger brain volume is thought to provide greater brain reserve (BR) against these pathological effects. This study identified the topography showing BR in patients with mild AD and explored the clinical balances among BR, amyloid, and WMLs burden. Methods Thirty patients with AD were enrolled, and AV-45 positron emission tomography was conducted to measure the regional standardized uptake value ratio (SUVr) in 8 cortical volumes-of- interests (VOIs). The quantitative WMLs burden was measured from magnetic resonance imaging while the normalized VOIs volumes represented BR in this study. The cognitive test represented major clinical correlates. Results Significant correlations between the prefrontal volume and global (r = 0.470, p = 0.024), but not regional (r = 0.264, p = 0.223) AV-45 SUVr were found. AD patients having larger regional volume in the superior- (r = 0.572, p = 0.004), superior medial- (r = 0.443, p = 0.034), and middle-prefrontal (r = 0.448, p = 0.032) regions had higher global AV-45 SUVr. For global WML loads, the prefrontal (r = -0.458, p = 0.019) and hippocampal volume (r = -0.469, p = 0.016) showed significant correlations while the prefrontal (r = -0.417, p = 0.043) or hippocampal volume (r = -0.422, p = 0.04) also predicted better composite memory scores. There were no interactions between amyloid SUVr and WML loads on the prefrontal volume. Conclusions BR of the prefrontal region might modulate the adverse global pathological burden caused by amyloid deposition. While prefrontal volume positively associated with hippocampal volume, WMLs had an adverse impact on the hippocampal volume that predicts memory performance in mild stage AD.
Towards Mentoring Object-Oriented Evolutionary Development

Object-oriented software is increasingly developed using an evolutionary development process model. Therefore, capturing and understanding the evolution that the system’s logical design has gone through can provide valuable insights in support of consistently maintaining and evolving the system, without compromising the integrity and stability of its architecture. In this paper, we present a method for capturing and analyzing the design evolution of object-oriented software systems. This method relies on UMLDiff, a heuristic UML-structure differencing algorithm, which, given a sequence of UML class models corresponding to the logical design of a sequence of system code releases, produces a sequence of “change records” that describe the design-level structural changes between subsequent system releases. Various design evolution patterns are then analyzed to reveal the rationale underlying design decisions that may affect the software system. The recovered knowledge about the system’s logic design evolution enables the overall understanding of system design evolution and provides the basis for mentoring the developers on future maintainance activities. We report on one real world case study evaluating our approach.
Investigation of Sequential Growth Factor Delivery during Cuprizone Challenge in Mice Aimed to Enhance Oligodendrogliogenesis and Myelin Repair

Repair in multiple sclerosis involves remyelination, a process in which axons are provided with a new myelin sheath by new oligodendrocytes. Bone morphogenic proteins (BMPs) are a family of growth factors that have been shown to influence the response of oligodendrocyte progenitor cells (OPCs) in vivo during demyelination and remyelination in the adult brain. We have previously shown that BMP4 infusion increases numbers of OPCs during cuprizone-induced demyelination, while infusion of Noggin, an endogenenous antagonist of BMP4 increases numbers of mature oligodendrocytes and remyelinated axons following recovery. Additional studies have shown that insulin-like growth factor-1 (IGF-1) promotes the survival of OPCs during cuprizone-induced demyelination. Based on these data, we investigated whether myelin repair could be further enhanced by sequential infusion of these agents firstly, BMP4 to increase OPC numbers, followed by either Noggin or IGF-1 to increase the differentiation and survival of the newly generated OPCs. We identified that sequential delivery of BMP4 and IGF-1 during cuprizone challenge increased the number of mature oligodendrocytes and decreased astrocyte numbers following recovery compared with vehicle infused mice, but did not alter remyelination. However, sequential delivery of BMP4 and Noggin during cuprizone challenge did not alter numbers of oligodendrocytes or astrocytes in the corpus callosum compared with vehicle infused mice. Furthermore, electron microscopy analysis revealed no change in average myelin thickness in the corpus callosum between vehicle infused and BMP4-Noggin infused mice. Our results suggest that while single delivery of Noggin or IGF-1 increased the production of mature oligodendrocytes in vivo in the context of demyelination, only Noggin infusion promoted remyelination. Thus, sequential delivery of BMP4 and Noggin or IGF-1 does not further enhance myelin repair above what occurs with delivery of Noggin alone.
Modelling atmospheric transport of α-hexachlorocyclohexane in the Northern Hemispherewith a 3-D dynamical model: DEHM-POP

The Danish Eulerian Hemispheric Model (DEHM) is a 3-D dynamical atmospheric transport model originally developed to describe the atmospheric transport of sulphur into the Arctic. A new version of the model, DEHM- POP, developed to study the atmospheric transport and en- vironmental fate of persistent organic pollutants (POPs) is presented. During environmental cycling, POPs can be de- posited and re-emitted several times before reaching a final destination. A description of the exchange processes be- tween the land/ocean surfaces and the atmosphere is included in the model to account for this multi-hop transport. The -isomer of the pesticide hexachlorocyclohexane ( -HCH) is used as tracer in the model development. The structure of the model and processes included are described in de- tail. The results from a model simulation showing the atmo- spheric transport for the years 1991 to 1998 are presented and evaluated against measurements. The annual averaged atmo- spheric concentration of -HCH for the 1990s is well de- scribed by the model; however, the shorter-term average con- centration for most of the stations is not well captured. This indicates that the present simple surface description needs to be refined to get a better description of the air-surface ex- change processes of POPs.
Bilevel Optimization Model for Determining Highway Tolls

The problem of determining an optimal set for the tolls for the arcs of a multiproduct transportation network is presented. The problem is formulated as a bilevel optimization problem, where the upper level consists of an administrator who establishes the tolls on the network, while the lower level is represented by a group of users who travel along the shortest paths with respect to a given travel cost. The objective is not only to increase tolls, but also to maintain an optimal flow on the arcs of the network in order to maximize benefits. A methodology to solve this problem using an optimization software at the lower level and the metaheuristic Scatter Search at the upper level is proposed.
The impact of Academic Emotions on Language Learning in the university context: a Narrative Review

Emotions affect learning in general and language learning (LL) in particular since they contain useful information that guides human cognition, behaviour and motivation. As such, emotions experienced in an academic setting affect the learner in a variety of ways. University students are frequently affected by emotions as a result of the difficulty in adjusting. This condition is observed as having impacted on LL, particularly on English, which has now become a very decisive factor in academic learning and achievement in Sri Lanka. The study aimed at identifying the wide array of emotions that are experienced in academic settings, their properties, the theoretical underpinnings, sources, functions and the impact of positive academic emotions (PAE) and negative academic emotions (NAE) on LL. It was also expected to identify the research trends in emotions and LL over the decades. This article is composed in the form a narrative review for which 30 studies on emotions and learning during the past 16 years were explored. A narrative inductive method was utilized to identify patterns across gathered data and to condense varied secondary data gathered from extensive reading into a summary format. The information found were analysed thematically in relation to the research questions. The findings suggest that, it is very difficult to set clear cut rules to prove positive emotions (PE) foster and negative emotions (NE) hinder LL for they serve different useful purposes. The impact of emotions on LL should therefore be further analyzed theoretically and investigated empirically pertaining to different contexts. There also exists a need to empirically test the existing limited theories on emotion to figure out the range of their validity within diverse contexts. The major implication derived from the study is that, language teaching in Sri Lankan universities, where English is taught as a second language (L2), is quite a mindful undertaking which should be planned and carried out with great care bearing in mind the strong relationship between emotions and learning. Keywords— Emotions, Academic Emotions, Learning, Foreign & Second Language Learning
Recovering the missing components in a large noisy low-rank matrix: application to SFM

In computer vision, it is common to require operations on matrices with "missing data," for example, because of occlusion or tracking failures in the Structure from Motion (SFM) problem. Such a problem can be tackled, allowing the recovery of the missing values, if the matrix should be of low rank (when noise free). The filling in of missing values is known as imputation. Imputation can also be applied in the various subspace techniques for face and shape classification, online "recommender" systems, and a wide variety of other applications. However, iterative imputation can lead to the "recovery" of data that is seriously in error. In this paper, we provide a method to recover the most reliable imputation, in terms of deciding when the inclusion of extra rows or columns, containing significant numbers of missing entries, is likely to lead to poor recovery of the missing parts. Although the proposed approach can be equally applied to a wide range of imputation methods, this paper addresses only the SFM problem. The performance of the proposed method is compared with Jacobs' and Shum's methods for SFM.
Detection performance of the fractional Fourier transform (chirp FFT) for frequency modulated signals

The Fractional Fourier transform (FrFT) is well suited to the processing of linear frequency modulated signals. Amongst the abilities it potentially offers are: the detection of signals at lower SNRs, better signal separation and the possibility of estimating the chirp rate of a signal. This work concentrates on using such a transform for detecting frequency modulated signals. For the detection problem the magnitude of the FrFT is sufficient and consequently the algorithm can be implemented efficiently by modifying a standard FFT, this implementation we shall refer to as a ‘Chirp-FFT’. This study considers the performance of the Chirp-FFT routine compared to the FFT routine for the detection of quiet underwater signals of both biological and man-made origin whose chirp rates are unknown a priori. Critically, the performance analysis here includes the effect the algorithms have on the background noise – a factor overlooked in other similar studies. The comparison is made on the basis of real data. It is shown that, unsurprisingly, the detection advantage offered by the Chirp-FFT is very much dependent on the character of the signal, but for the examples considered the gain in performance is in the range 0 - 3 dB