Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced plasma flow simulations of cathodic-arc and ferroelectric plasma sources for neutralized drift compression experiments

Large-space-scale and long-time-scale plasma flow simulations are executed in order to study the spatial and temporal evolution of plasma parameters for two types of plasma sources used in the neutralized drift compression experiment (NDCX). The results help assess the charge neutralization conditions for ion beam compression experiments and can be employed in more sophisticated simulations, which previously neglected the dynamical evolution of the plasma. Three-dimensional simulations of a filtered cathodic-arc plasma source show the coupling efficiency of the plasma flow from the source to the drift region depends on geometrical factors. The nonuniform magnetic topology complicates the wellknown general analytical considerations for evaluating guiding-center drifts, and particle-in-cell simulations provide a self-consistent evaluation of the physics in an otherwise challenging scenario. Plasma flow profiles of a ferroelectric plasma source demonstrate that the densities required for longitudinal compression experiments involving ion beams are provided over the drift length, and are in good agreement with measurements. Simulations involving azimuthally asymmetric plasma creation conditions show that symmetric profiles are nevertheless achieved at the time of peak on-axis plasma density. Also, the ferroelectric plasma expands upstream on the thermal expansion time scale, and therefore avoids the possibility of penetration into the acceleration gap and transport sections, where partial neutralization would increase the beam emittance. Future experiments on NDCX will investigate the transverse focusing of an axially compressing intense charge bunch to a sub-mm spot size with coincident focal planes using a strong final-focus solenoid. In order to fill a multi-tesla solenoid with the necessary high-density plasma for beam charge neutralization, the simulations predict that supersonically injected plasma from the lowfield region will penetrate and partially fill the high-field region of the solenoid. Because of the magnetic mirroring effect, the on-axis plasma density in the solenoid depends on the injection velocity and magnetic field strength.
Employing learning analytics for monitoring student learning pathways during Problem-Based Learning group-based group work: a novel approach

Learning Analytics (LA) aims to improve the learning process by analysing learning data, and communicating the results of this analysis to both educators and learners. LA has been employed in a few cases for improving PBL group work but the literature has yet to discuss in detail the incorporation and potential of LA in this context. In this paper, we describe our approach that aims at developing a platform employing LA for monitoring students’ learning pathways during Problem-Based Learning (PBL) group work. The platform is developed in Moodle, and it provides a communication and information channel between project supervisors and students, and between students belonging in the same group. Moreover, the platform provides ways for student groups to better manage their projects, and at the same time enables project supervisors to follow groups’ progress during the semester. The platform is also used as a place, where students hand-in assignments that are related to their project work and report their status in the project. In this platform, we employ various LA tools offered by Moodle in order to monitor both group and individual student activity. Such tools provide learning data on individual student engagement and activity within the platform, generic statistics on the use of the platform, and insights into the exchange of information in the platform. In this paper, we present the functionality of the various modules that build up this platform, and discuss the type of learning data generated and the methods to analyse this data. We conclude this paper with a discussion on the benefits and the limitations of this approach.
Variable depth search and iterated local search for the node placement problem in multihop WDM lightwave networks

We address a problem of finding an optimal node placement that minimizes the amount of traffics by reducing the weighted hop distances in multihop lightwave networks. The problem is called Node Placement Problem (NPP). NPP is known to be NP-hard and one of the most important problems in wavelength division multiplexing (WDM) based networks. In this paper we propose a new local search algorithm for the NPP based on variable depth search, and show its extension to an iterated local search algorithm. To evaluate the performance of the proposed methods, we provided the benchmark instances with known optimal solutions, and performed extensive experiments on the instances. The computational results showed that our iterated local search outperformed multistart local search methods and the best available metaheuristic for the problem.
Normalisation between Stimulus Elements in a Model of Pavlovian Conditioning: Showjumping on an Elemental Horse

Harris and Livesey (2010) described an elemental model of associative learning that implements a simple learning rule, that produces equivalent results to that proposed by Rescorla and Wagner (1972), and additionally modifies in "real time" the strength of the associative connections between elements. The novel feature of this model is that stimulus elements interact by suppressively normalising one another's activation. Because of the normalisation process, element activity is a non‐linear function of sensory input strength, and the shape of the function changes depending in the number and salience of all stimuli that are present. The model can solve a range of complex discriminations and account for related empirical findings that have been taken as evidence for configural learning processes. Here we evaluate the model's performance against the host of conditioning phenomena that are outlined in the companion paper, and we present a freely‐ available computer program for use by other researchers to simulate the model's behaviour in a variety of conditioning paradigms.
Methods for Researching the Physical Activity Impacts of 'Natural Experiments' in Modifying the Built Environment

Modifying the built environment is increasingly recommended as a means of increasing physical activity, but there is currently little evidence from intervention studies to support this approach. From a discussion of 3 natural experiments in this area (RESIDE, iConnect, and Commuting and Health in Cambridge), several common lessons emerged. First, researchers should anticipate delays in the implementation of interventions that are outside their control, and research funders need to exercise a degree of flexibility to accommodate changing research timetables. Second, new built environments develop and evolve over time, and so do their effects on human behavior. Study designs and exposure measures should take account of this, and long term outcomes should be measured wherever possible to allow for potential sleeper, snowball, or threshold effects emerging over time. Third, it may be difficult to identify suitable control areas for a conventional parallel-group intervention–control design, and it may be neces.
Superconductivity and antiferromagnetism in the two-dimensional Hubbard model

Despite its apparent simplicity and even if it has been studied intensively in various contexts, the two-dimensional Hubbard model is not yet completely understood. In particular when it describes a system with an intermediate interaction, out of range for perturbative methods, its ground state is still not well known. The discovery in 1986 of a superconducting phase in the copper oxides (cuprates), which appears at rather high temperature, has further enhanced the interest for this model, as it may describe the amazing poperties of these layered materials. Indeed, when the electronic density corresponds to a half-filled band, the Hubbard model is known to nicely account for the antiferromagnetic phase obtained experimentally for the cuprates and it is possible, as first proposed by P. W. Anderson, that it describes equally well the superconducting phase observed below a critical temperature, when the electronic density is moderatly reduced by modifying the compound composition (doping). In this case, the superconductivity originates from purely electronic interactions, contrary to conventional superconductivity where the interaction between electrons and lattice vibrations (phonons) is involved. Unfortunately, very few stringent results are available in order to support this statement and this question is still largely debated. In this thesis, the variational method is used in order to scrutinize the possibility of a superconducting ground state for the repulsive Hubbard model. Although its reliability is based on the adequate choice of the variational wave function, this method is especially suited for treating intermediate interactions, which is the appropriate regime of the cuprates. The optimization of a refined wave function allows us to obtain a variational ground state which is much closer to the exact ground state than those obtained so far using less elaborate wave functions. Actually, the exact study of small systems indicates that the error of our calculation is too small to allow for a qualitatively different behavior. Our results show that an antiferromagnetic phase is dominant at half-filling, while a superconducting phase with a d-wave symmetry of the order parameter emerges at moderate doping. The key features of the copper oxides are therefore found in the variational ground state of the repulsive Hubbard model. Some amazing similarities are also observed at the quantitative level when the properties of this ground state are compared to the experimental data obtained for the cuprates.
Atypical interference effect of action observation in autism spectrum conditions

Background Observing incongruent actions interferes with ongoing action execution. This ‘interference effect’ is larger for observed biological actions than for non-biological actions. The current study used virtual reality to investigate the biological specificity of interference effects of action observation in autism spectrum conditions (ASC). Method High-functioning adults with ASC and age- and IQ-matched healthy controls performed horizontal sinusoidal arm movements whilst observing arm movements conducted by a virtual reality agent with either human or robot form, which moved with either biological motion or at a constant velocity. In another condition, participants made the same arm movements while observing a real human. Observed arm movements were either congruent or incongruent with executed arm movements. An interference effect was calculated as the average variance in the incongruent action dimension during observation of incongruent compared with congruent movements. Results Control participants exhibited an interference effect when observing real human and virtual human agent incongruent movements but not when observing virtual robot agent movements. Individuals with ASC differed from controls in that they showed no interference effects for real human, virtual human or virtual robot movements. Conclusions The current study demonstrates atypical interference effects in ASC.
Paradigms and Perspectives on Learning

Instructional theories are concerned with instructional methods that affect learning. Learning refers to the act, process, or experience of gaining knowledge, skills, and attitudes and as such, learning is inherent to all human life. People learn by doing, by exploring, by listening, by reading books, by studying examples, by being rewarded, by discovering, by making and testing predictions, by trial-and-error, by teaching, by abstracting away from concrete experiences, by observing others, by solving problems, by analyzing information, by repetition, by questioning, by paraphrasing information, Abstract What is the most important factor in fl uencing human learning? Different instructional theories give very different answers to this question, because they take different perspectives on learning and thus focus on other desired learning outcomes, other methods affecting learning processes, and other conditions under which learning takes place. This chapter describes how eight prevailing research paradigms have in fl uenced and still strongly in fl uence theory development in the fi eld of educational communications and technology. According to the perspective of Gestalt psychology, the most important factor in fl uencing learning is insight and understanding; according to behaviorism and neo-behaviorism, it is reinforcement; according to developmental psychology, it is the learner’s stage of cognitive development; according to cultural-historical theory, it is interaction with the world; according to information processing theory, it is active and deep processing of new information; according to cognitive symbolic theory, it is what the learner already knows; according to cognitive resource models, it is the limited processing capacity of the human mind, and according to social constructivism, it is the social construction of meaning. It is argued that research is typically done within one particular paradigm, but that researchers should be conscious of the fact that paradigms heavily affect their research methods and fi ndings. Moreover, researchers should be open to alternative theories and paradigms because new developments often take place at the interface between paradigms.
The Effects of Orbital Precession on Tropical Precipitation

of a thesis at the University of Miami. Thesis supervised by Professor Amy C. Clement. No. of pages in text. (51) The response of tropical precipitation to precessional forcing is investigated using idealized precession experiments from two climate models as well as mid-Holocene experiments from ten climate models participating in the Paleoclimate Modeling Intercomparison Project Phase III. The objectives of this thesis are to analyze an energetic mechanism that describes precessional changes in precipitation and determine if this mechanism is sufficient for explaining changes in precipitation over land and ocean. Both mid-Holocene experiments and idealized experiments show a seasonal land-sea asymmetry in tropical precipitation that cannot be explained simply by monsoon dynamics. Instead, this shift in precipitation is interpreted using an energetic framework that describes how changes in the net top-of-atmosphere radiation affect the atmosphere and surface energy balances. Over land, changes in precipitation can be explained through changes in moist static energy flux divergence, but over the ocean, the moist static energy flux divergence plays a lesser role because the surface energy balance compensates for the majority of the change in top-of-atmosphere radiation. Because this mechanism does not sufficiently describe why precipitation changes over the ocean, we break down the dry and moist energy responses of the atmosphere in order to further explain this process. We find that the atmosphere’s response to precessional forcing over land drives changes in circulation, which influence the thermodynamic structure of the atmosphere over the ocean, ultimately allowing for precipitation changes over the ocean. To conclude, we examine the regional changes in precipitation in the tropical Atlantic and over Africa, and we discuss how paleoclimate records from this region can be used for model verification.
4-Diethylamino-3,5-diisopropylbenzaldehyde

The title benzaldehyde, C17H27NO, was prepared via lithiation of bromoaniline and reaction with DMF. In the crystal, the molecule adopts a C2-symmetrical conformation; nevertheless, two modes of disorder are present: the orientation of the aldehyde group (occupancy ratio 0.5:0.5) and of symmetry-equivalent ethyl groups [occupancy ratio 0.595 (7):0.405 (7)]. The phenylene ring and the carbonyl group are essentially coplanar [C—C—C—O torsion angle = −179.0 (4)°] but the dihedral angle between the mean planes of the phenylene ring and the amino group = 67.5 (2)°. This and the long [1.414 (3) Å] aniline C—N bond indicate electronic decoupling between the carbonyl and amino groups. The angle sum of 359.9 (2)° around the N atom results from steric compression-induced rehybridization.
A New Measure of Earnings surprises and Post-Earnings-Announcement Drift

In this article, we develop a new measure of earnings surprises – the earnings surprise elasticity (ESE), which is defined as the absolute value of earnings announcement abnormal returns (EARs) scaled by earnings surprises (in percentage). The numerator of the ESE captures all the information released around earnings announcement dates and market reactions to the information; the denominator of the ESE gives special emphasis to earnings surprises. We explore the ESE under four different categories in terms of the signs of earnings surprises (+/-) and the signs of EARs (+/-). We find that: a). Across all four sub-samples, larger firms have smaller earnings surprises and higher EARs (both in absolute values), thus have higher ESE quintiles. b). Firms in the highest ESE quintile usually have much smaller post-earnings-announcement cumulative abnormal returns (CARs) in absolute value than firms in the lowest ESE quintile; c). Against conventional wisdom, for around 36% of total observations, earnings surprises and EARs move in opposite directions. d). More than 11% firms have no surprises; those are larger firms with larger institutional shareholdings and followed by more analysts. It is not wise to invest in this group of firms as evidenced in the negative post-earnings-announcement CARs. e). A trading strategy of taking a long position in firms in the lowest ESE quintile when both earnings surprises and EARs are positive and a short position in firms in the lowest ESE quintile when both are negative can generate 5.19% quarterly abnormal return.
The Formulation and Study the Problem of Mining Probabilistically Frequent Sequential Patterns in Uncertain Databases

Uncertainty in various domains implies the necessity for various data mining techniques and algorithms that can handle uncertain datasets. Many studies on uncertain datasets have main focused on modeling, query ranking, classification models, discovering frequent patterns, clustering, etc. However despite the existing need, very few studies have considered uncertainty in sequential data. In this paper, we propose to measure pattern frequentness based on the various possible world semantics. We are looking to establish two uncertain sequence data models abstracted from many real-life applications involving uncertain sequence data, and formulate the problem of mining probabilistically frequent sequential patterns (or p-FSPs) from data that conform to our models. Using the prefix-projection strategy of the famous PrefixSpan algorithm, we are developing two new algorithms, collectively called U-PrefixSpan, for p-FSP mining. UPrefixSpan avoids the problem of “possible world explosion”, and when combined with our three pruning techniques and one validating technique, it achieves good performance
Phenotypic divergence of grapes using productive cycle

Classifying vines regarding the number of days required to complete de productive cycle and the duration of intermediate phenologic phases are essential for genetic improvement programs, implementation of cultivation techniques and handling of the grape harvest. The objective of this study was to evaluate the access phenotypic divergence of grapes from the germplasm collection by the Agronomic Institute - IAC. Evaluations were performed for 4 years of production, from 2012 to 2015, when the plants were 4 years old. The training system applied the espalier, at a 2.0 x 1.0 m spacing between lines and plants, respectively. The IAC's grape germplasm collection comprised 110 varieties of the 'Vitis vinifera', 'Vitis labrusca' species and inter-specific hybrids grafted into the IAC 766 rootstocks, being 3 plants per each variety. After the pruning of the main vine phonologic phases, the number of days was evaluated using the scale proposed by Eichhorn and Lorenz. Two evaluations a week were carried out until the flowering, and afterwards one evaluation was performed a week, the period between pruning and the beginning of sprouting, full flowering with 50% flowers opened, beginning of maturation (veraison) and maturation (harvest), visually mature fruits and content of soluble solids above 14 degrees Brix. Multivariate analysis, such as the correlation between varieties, analysis of the main components (PCA) and methods of non-weighted arithmetic means (UPGMA) was applied to classify the phenotypes according to the productive cycle. A relation was found between the sprouting and the flowering phases, as well as the starting maturation and maturation. The first two components explained 81% of the total variability, being that the starting maturation and maturation were the best variables to study the divergence of vine phenotypes. Also, combining the UPGMA method and the PCA analysis that distinguished three groups, allowed us to divide the phenotypes into 25 processes, 75 median and 10 late varieties, according to their productive cycle. It was possible to conclude that the techniques used to study the genetic diversity applied to phenologic characters were effective to evaluate the vines phenotypic divergence, and therefore, the multivariate analysis may be used to guide future vine improvement programs.
A statistical approach to background subtraction for surveillance systems

Background subtraction is a commonly used process in surveillance systems. One difficult problem when using the process is maintaining a correct background image against changing illumination conditions. Most methods for maintaining the background image are based on intuitive definitions about the illumination change and are implemented as somewhat ad hoc algorithms. In contrast, we first define mathematical models representing the relation between the illumination intensity, a reflection index of objects and a pixel value. We also mathematically define an assumption about illumination, which requires that the distribution of the illumination intensity in a small region does not change. Then we formalize the background subtraction problem as a statistical test (/spl chi//sup 2/ test) based on the models and assumption. The experiments show that our models appropriately express the imaging process of a camera and our method provides stable detection performance for foreground objects.
The Electromagnetic Responses of Under Seabed Layer and Inversion Method Study

Abstract— Seabed hydrocarbon detection by electromagnetic method is widely used for its effectiveness and efficiency. In this paper, we analyze the seabed survey and geometry from the reflection coefficient, develop a new algorithm and complete the software to calculate the EM response of VMD and HED source which is widely used in the seabed detection. At the end of the paper, we inverse the 1D response by least square method based on Monte Carlo method for initial selection. The simulation result shows that our algorithm is stable and efficient.
Constraining fault friction by re-examining earthquake nodal plane dips

We have assembled a catalogue of well-constrained focal mechanisms for earthquakes that occurred on continental dip-slip faults that have experienced only small displacements during their current phase of activity. Nodal planes for both reverse- and normal-faulting events are seen to vary between ∼30° and ∼60°, and are concentrated towards the centre of this range. The observed distributions suggest the reactivation of structures with a low coefficient of friction (less than ∼0.3, and possibly as low as ≤0.1). We propose that this low coefficient of friction corresponds to the presence of weak materials in pre-existing fault zones.