Miracle-dz/UniFAR-FTUs huggingface dataset:
Combined brain connectivity and cooperative sensor networks for modelling movement related cortical activities

The elucidation of the brain’s anatomical and functional organisation during specific tasks is a challenging field in modern brain research. There is also a growing interest in the field of brain connectivity and its relation to specific motor and mental tasks, as well as neurodegenerative diseases like Parkinson’s and Alzheimer’s. In this thesis, a novel approach for modelling motor tasks is proposed. This approach combines diffusion adaptation and brain connectivity measures in order to build models which describe complex tasks through time and space. In particular, an S-transform based measure is introduced to estimate the connectivity on single-trial basis. The connectivity values, corresponding to different frequency bands across time, are effectively coupled with diffusion adaptation. The diffusion strategy exploits the time-space characteristics in a distributed and collaborated manner, and leads to an enhanced model for motor or mental tasks. Specifically, the imaginary part of S-transform coherency is introduced as an EEG connectivity measure. The performance improvement over the existing connectivity measures on a single-trial basis is demonstrated. Moreover, diffusion Kalman filtering is used as it performs well for nonstationary problems like this. This novel method is tested on various scenarios. Initially, its performance is demonstrated for simulated datasets which are based on realistic scenarios. Then, the method is applied to two datasets of real data. The first set of experiments includes a complex motor task of clockwise and anticlockwise hand movement and the second set includes a multi-modal dataset acquired from Parkinson’s patients. The results show that the connectivity enhanced modelling outperforms the simple case where connectivity information is ignored, and can build a robust task-related model.
A study of relation extraction for biomedical text

A crucial area of Biomedical Natural Language Processing is relation extraction, the study of identifying relations between entities. One main challenge of relation extraction is text variations. They hinder pattern-based approaches to encode all patterns necessary for achieving a high recall, and limit the generalizability of machine-learning models especially when the size of training data is small. This thesis exams the representation of sentences for relation extraction. In particular, we are concerned with a suitable level of abstraction, which will improve the performance of the relation extraction systems, and in turn lead to advances in other text-mining fields. This thesis describes three steps along these lines. First, we propose an automatic approach for sentence simplification. It reduces the sentence complexity by detecting various syntactic constructs and generating simplified sentences. Second, we describe a framework to facilitate the development of pattern-based biomedical relation extraction systems. The framework leverages various linguistic theories to semi-automatically generate lexico-syntactic patterns. It also applies sentence simplification and semantic relations to increase the pattern coverage. Finally, we propose a structured representation, called Extended Dependency Graph (EDG). It provides an abstract representation accounting for textual variations, by not only considering syntactic dependencies between words in a sentence, but also utilizing information beyond syntax to capture dependencies. In each of these steps, we conduct experiments to evaluate the efficacy of the ideas. The results (1) show that various text-mining approaches can benefit from sentence simplification, (2) demonstrate that we can create state-of-the-art pattern-based systems using the framework to extract different types of relations, and (3) validate the utility of EDG in both pattern-based and machine-learning relation extraction systems.
Mathematical Epidemiology Of Infectious Diseases Model Building Analysis And Interpretation

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Varietal variability of less grown mints: influence on selected antioxidants

Genus Mentha belongs among the important part of spice, aromatic and medical plants. It includes a large amount of varieties and forms which are not spread generally because of low knowledgeability about possibilities of individual varieties using and also about their high content of bioactive substances. Five less-known varieties and forms (Mentha x piperita var. ´Danica´, Mentha x piperita var. ´Chocolate´, Mentha arvensis f. Banana, Mentha sp. f. Mojito, Mentha sp. f. White Grape) with different aroma and plant habitus were chosen to estimate the content of essential oils, chlorophyll a, chlorophyll b and carotenoids. From obtained results varietal variability of individual varieties and forms have been specified and compared with commonly used Mentha x piperita. The content of essential oils was estimated by steam distillation. The pigment content was determined by spectrophotometric measurement of absorbance at a wavelength of 649 nm (chlorophyll a), 665 nm (chlorophyll b) and 450 nm (carotenoids). The results showed that ´Danica´ and ´Chocolate´ varieties have reached the highest amount of essential oils. Most of the chlorophyll a, b and carotenoids content reached commonly used Mentha x piperita, but there wasn´t found significant difference when compared with ´Danica´ and ´Chocolate´. The effect of varietal variability on the content of qualitative characteristics in the case of essential oils, chlorophyll a and b was confirmed according to used statistical analyse (p <0.05). The varietal variability of tested mint forms and varieties on carotenoids content was not confirmed.
Model Based Control Of A Robot Manipulator

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Analysis of scientific argumentation in two physical chemistry classrooms using the POGIL approach

xi! CHAPTER 1. INTRODUCTION . 1! CHAPTER 2. LITERATURE REVIEW . 5! Physical Chemistry . 5! Process-Oriented Guided Inquiry Learning (POGIL) . 6! Classroom Discourse in Undergraduate Inquiry Chemistry . 8! Scientific Argumentation . 10! Instructor Facilitation of Argumentation . 12! Curricular Materials Influence . 15! Evaluating Scientific Argumentation and Reasoning . 16! Theoretical Frameworks . 19! Sociocultural Perspective . 19! Situated Learning . 21! CHAPTER 3. METHODS . 23! Research Questions . 23! Theoretical Frameworks . 23! Analytic Framework . 24! Methods. 26! Participants and Setting . 26! Data Collection . 28! Data Analysis . 29! Argument Log Generation . 29! Analysis of Discursive Moves . 30!
Dynamics of a sensory network of ON and OFF cells with global delayed feedback

We study the sensory processing features of a network built of ON and OFF cells with global delayed feedback. We investigate the response of neural populations to spatio-temporal forcing, mimicking that found in most sensory systems. The network architecture is inspired from the physiology of the electrosensory lateral line lobe (ELL) of the weakly electric fish, where we describe the collective behavior of populations in the pyramidal cell layer. ON pyramidal cells receive sensory inputs directly, while OFF cells receive a mirror image of the stimuli via an interneuron, inverting their response. The two opposed responses propagate upstream where they recruit the inhibitory feedback pathways. To enhance the distinction between the sub-populations, different baseline firing rates are implemented (to which we refer as asymmetry). As a novel approach to this problem, we model the neural circuit using a system of neural field equations, where the connectivity is determined solely by all-to-all and non-topographic inhibitory recurrent connections. Motivated by numerical and experimental results on the electrosensory system, we determine the conditions for which global rhythmic activity states appear in response to spatially organized stimuli. Novel responses to localized pulses are shown in the steady state regime, where the feedback connections interfere with local ON and OFF activities. These effects are systematically compared to the dynamics of a noisy Integrate-And-Fire network sharing the same architecture and parameters with the neural field formulation. Lastly, we investigate the impact of intrinsic cellular adaptation on oscillatory dynamics. Together these results establish the theoretical basis for input driven transitions to rhythmic states in delayed feedback networks with realistic neural populations.
Assessing the interactions between micropollutants and nanoparticles in engineered and natural aquatic environments

Abstract Increasing concerns about the occurrence and toxicity of micropollutants (MPOs) have triggered more research and the need for stringent environmental regulations. These pollutants pose a serious challenge due to their low-level occurrence in which human and ecological receptors can suffer adverse effects. The lack of sufficient data on their fate and transport in the environment has hampered realistic ecological and human health risk assessments. The partition and transformation of MPOs in the environment are further complicated by the identification of various nanoparticles. In this review, the interaction between nanoparticles (NPs) and MPOs present in the environment are summarized. In particular, the review focused on the sorption of MPOs by NPs which are largely influenced by the surface area of NPs, the presence of Natural Organic Matter (NOM), pH and ionic strength etc. A dominating interaction mechanism has been proposed although it is recognized that more in-depth research is required to understand the influences of NPs in a complex environmental matrix. Understanding the fate of MPOs influenced by NPs is important for risk assessment, given that NPs can transport MPOs; alter their toxicity, mobility, transformation and bioavailability. The review provides a state of knowledge and gaps to promote future research initiatives.
Palladium Isolation and Purification from Nitrate Media: Efficient Process Based on Malonamides

ABSTRACT Solvents based on malonamides have been described to be very efficient and selective for liquid-liquid extraction of Pd(II) from nitrate media. The present study details the possibility to selectively extract Pd(II) over common metallic cations, Cu(II), Ni(II), Co(II), Zn(II), Nd(III), Fe(III) and Al(III) using N,N’-dimethyl,N,N’-dibutyltetradecylmalonamide (DMDBTDMA) in toluene. The lowest selectivity was obtained considering Fe(III) and Nd(III), the extraction of all other cations being negligible. Pd(II) distribution and selectivity regarding Fe(III) have been fine-tuned using the aqueous HNO3 concentration as the sole parameter, so that extraction, scrubbing and stripping steps can be simply designed without the need for other specific metal chelating reagents and/or aqueous media and without the extensive generation of aqueous effluents. DMDBTDMA was also benchmarked with other classical Pd(II) extractants such as tributylphosphate (TBP), dihexylsulfide (DHS), tetraoctyl diglycolamide (TODGA) and bis(2-ethylhexyl)sulfoxide (BESO) in toluene and in n-heptane. Overall, this study reveals that malonamides are very well positioned and should be considered for further processing of aqueous nitrate wastes containing Pd contaminated with common base metals.
Synthesis, Structure and Physical Properties of GdCu4Al and GdCu4Ga.

Abstract Two non-stoichiometric Gd compounds, GdCu5−xTrx (Tr=Al, Ga) have been synthesized from the corresponding elements by high temperature reactions in sealed tantalum containers. They crystallize in the hexagonal CaCu5-type (Pearson's symbol hP6, space group P6/mmm, No. 191) with lattice parameters determined from single-crystal X-ray diffraction at room temperature as follows: a=5.0831(10) A; c=4.156(2) A for GdCu3.98(4)Al1.02(4), and a=5.1025(10) A; c=4.155(2) A for GdCu3.9(1)Ga1.1(1), respectively. Structure refinements from single crystal X-ray diffraction data reveal that substitution of Cu for Al or Ga takes place preferably on one of the two transition metal sites with site symmetry mmm (3g). Both compounds order antiferromagnetically below ∼40 K and ∼36 K, respectively, as determined from temperature dependent dc-magnetization, resistivity and heat-capacity measurements.
A data driven analysis of telephone interpreting

The telephone is quickly becoming the predominant medium through which interpreting services are delivered. However, aside from some initial descriptive works (Wadensjo 1999; Niska 1998), objective empirical analysis of this kind of interpreting is conspicuous by its absence in the literature. Over a two-year period I collected data on the features of some 1876 interpreter-mediated telephone calls. The analysis of this data shows that these calls are far more complex than as suggested in earlier studies. Three main subcategories are analysed herein: telephone interpreting or, three-way telephone conversation, speakerphone interpreting, remote interpretation of a face-to-face encounter, and finally, telephone passing, a face-to-face encounter where the telephone is passed from one party to another.
Towards sound refactoring in erlang

Erlang is an actor-based programming language used extensively for building concurrent, reactive systems that are highly available and su er minimum downtime. Such systems are often mission critical, making system correctness vital. Refactoring is code restructuring that improves the code but does not change behaviour. While using automated refactoring tools is less error-prone than performing refactorings manually, automated refactoring tools still cannot guarantee that the refactoring is correct, i.e., program behaviour is preserved. This leads to lack of trust in automated refactoring tools. We rst survey solutions to this problem proposed in the literature. Erlang refactoring tools as commonly use approximation techniques which do not guarantee behaviour while some other works propose the use of formal methodologies. In this work we aim to develop a formal methodology for refactoring Erlang code. We study behavioural preorders, with a special focus on the testing preorder as it seems most suited to
Synopsizing “literature review” for scientific publications

Because the number of scientific publications in most disciplines is expanding rapidly, traditional academic search engines can hardly satisfy scholars’ need to retrieve and assimilate the information they are looking for. In this study we investigate a new summarization problem: creating a synopsis “Literature Review” of a collection of candidate cited papers in response to a query, via different methods and indicators. In more detail, we compare the use of different methods and indicators for generating citation clusters and summarized reviews by analyzing publication abstracts, citation contexts, and co-cite relationships. We also validate the usefulness of a user’s query during this process by comparing querydependent and query-independent clustering and summarization. One interesting outcome of this study is that citation contexts are more suitable for clustering related papers, whereas abstracts are more accurate for generating longer review-like summaries. The initial user query is also helpful for enhancing clustering and summarization performance.
ANTIOXIDANT AND ANTIRADICAL ACTIVITY OF GREEN TEA (Camellia sinensis) AQUEOUS EXTRACT AND ITS CAPABILITY TO RETARDATION OF RATS LIVER CIRRHOSIS

he aim of the present study was to optimize the extraction conditions of green tea aqueous extract [green tea concentration (G) and extraction temperature (T)]. Response surface methodology was applied to determine the highest radical scavenging activity (RSA), Ferric reducing antioxidant power (FRAP) and reducing power (RP) of the prepared green tea extract. Effect of green tea aqueous extract prepared using the optimal conditions on the liver cirrhosis retardation in rats was also investigated. Two-factors central composite design was established to determine the effects of G or T and radical scavenging holding time as independent variables on RSA, FRAP and RP as dependent variables. The optimum G, T and holding time with maximum RSA were 1.0 %, 88.7 °C for 25 min, with a predicted RSA of 81.3 % (r2=0.9115) compared to the BHT, which had a scavenging value of 87.4 % at concentration 150 ppm and holding time 30 min The same predicted concentration and temperature obtained with the highest FRAP and RP were 2.566 and 1.687 with r2 0.9780 and 0.9550, respectively. The phenolic and flavonoid contents were 81.2 mg gallic acid equivalent and 33.5 mg quercetin equivalent per 100 ml green tea extract. The extract prepared at optimal conditions was used for treatment of cirrhotic rats by CCl4. Insignificant (P≥0.05) differences were observed between the green tea group and control group in obtained total protein or albumin values. Total protein and albumin were dramatically decreased in the group treated by CCL4. The same trend was observed with studying the transaminase enzymes. Histopathological sections appeared the effect of green tea extract on the retardation of liver cirrhosis in rats.
X-ray study of the spinel LiMn2O4 at low temperatures

Stoichiometric LiMn{sub 2}O{sub 4} undergoes a structural phase transition close to room temperature from cubic to orthorhombic symmetry. The crystal structure at 230 K (space group Fddd and a = 24.743(1), b = 24.840(1), and c = 8.199(1){angstrom}) corresponds to an orthorhombic {similar{underscore}to} 3a x 3a x a superstructure of the cubic spinel structure, induced by a charge ordering on the manganese sites. By use of synchrotron X-ray diffraction, it is shown that the transition is first-order with the coexistence of two phases in a small range of temperatures and that the cell volume very slightly increases on cooling. Synchrotron X-ray diffraction confirms the symmetry of the low-temperature phase and reveals that the orthorhombic phase studied at 230 K progressively shifts to a symmetry close to tetragonal when cooled to lower temperatures. However, the symmetry of LiMn{sub 2}O{sub 4} is never tetragonal, even down to 1.5 K, and this tends to exclude the onset to a complete charge-ordered state.
Rules and schemas in the development and use of the English past tense

Consistent error patterns in English past-tense forms are reported for three age groups: preschoolers, 8-10-year-olds, and adults. It is argued that, although irregular forms are rote-learned, speakers make generalizations about such forms. Such a generalization is defined as a SCHEMA which describes general phonological properties of a morphological class, and is used in organizing and accessing the lexicon. Schemas for the English past tense develop and change with age, yielding implications for both acquisitional and diachronic theory. *
Curriculum expectations for teaching science and statistics

This paper focuses on the curriculum links between Statistics and Science that teachers need to understand and apply in order to be effective teachers of the two fields of study. Meaningful Statistics does not exist without context, and Science is the content focus of Session 1A. Although curriculum documents differ from country to country, this paper uses extracts from The Australian Curriculum: Mathematics and the US Common Core State Standards for Mathematics and links the statistical ideas with the relevant parts of The Australian Curriculum: Science and the US Next Generation Science Standards for States, by States. Teachers of Mathematics need to be aware of the potential of Science to provide meaningful contexts within which to set statistical investigations. Similarly teachers of Science, developing methods for implementing investigations and experiments in their classrooms, need to be aware of the close ties to statistical tools for decision-making.
Evaluating Parsers with Dependency Constraints

Many syntactic parsers now score over 90%onEnglish in-domain evaluation, but the remaining errors have been challenging to address and difficult to quantify. Standard parsing metrics provide a consistent basis for comparison between parsers, but do not illuminate what errors remain to be addressed. This thesis develops a constraint-based evaluation for dependency and Combinatory Categorial Grammar (ccg) parsers to address this deficiency. We examine the constrained and cascading impact, representing the direct and indirect effects of errors on parsing accuracy. This identifies errors that are the underlying source of problems in parses, compared to those which are a consequence of those problems. Kummerfeld et al. (2012) propose a static post-parsing analysis to categorise groups of errors into abstract classes, but this cannot account for cascading changes resulting from repairing errors, or limitations which may prevent the parser from applying a repair. In contrast, our technique is based on enforcing the presence of certain dependencies during parsing, whilst allowing the parser to choose the remainder of the analysis according to its grammar and model. We draw constraints for this process from gold-standard annotated corpora, grouping them into abstract error classes such as np attachment, pp attachment, and clause attachment. By applying constraints from each error class in turn, we can examine how parsers respond when forced to correctly analyse each class. We show how to apply dependency constraints in three parsers: the graph-based MSTParser (McDonald and Pereira, 2006) and the transition-based ZPar (Zhang and Clark, 2011b) dependency parsers, and the C&C ccg parser (Clark and Curran, 2007b). Each is widely-used and influential in the field, and each generates some form of predicate-argument dependencies. We compare the parsers, identifying common sources of error, and differences in the distribution of errors between constrained and cascaded impact. Our work allows us to contrast the implementations of each parser, and how they respond to constraint application.