Miracle-dz/UniFAR-FTUs huggingface dataset:
EL — a possible indicator to monitor the magnetic field stretching at global scale during substorm expansive phase : case study

The Ion Isotropy Boundary (IB) is known to correlate well wi th the magnetic field inclination at geosynchronous orbit around 00 MLT and therefore provides a way to monitor th e magnetotail stretching. Several ways to identify IB have been developed in the literature. Based on in situ spacecraft data, Sergeev and Gvozdevsky [12] have defined the IB position using NOAA data and Newell et al. [10] defined a comparable boundary (the b2i boundary) based on Defense Meteorological Satellite Program (DMSP) data. Fro m the ground, Donovan et al. [3] used Meridian Scanning Photometers (MSP) to determine the ”optical b2i” and Jayach andran et al. [6] demonstrated the coincidence of the b2i and the equatorward boundary of the SuperDARN evening secto r E-region scatter. To complement these methods, an IB determination on a wide range of Magnetic Local Time (MLT) with a high temporal resolution is useful. To do this, Trondsen et al. [13] use IMAGE-FUV-SI12 imager to monitor IB by simultaneous comparison with MSP data during a 7 day period. Recently, Blockx et al., [1] have shown the poten tial of SI12 data for monitoring the magnetotail stretching during quiet periods. In this study, we focus our attention o n the ability of SI12 to provide information on tail stretchi ng during active periods and more specifically during the subst orm expansive phase. Because of the dynamic character of expansive phases and mechanisms acting between the plasma s ources and ionosphere during this phase, deduceing IB position from auroral optical data is likely impossible. In order to avoid confusion between the physical meaning of IB and its role as a stretching indicator, we validate a stretch ing determination method using the EL indicator (determine d by the Donovan’s algorithm applied on SI12 data) instead of IB. For this validation, we use more than 250 isolated substorms observed by IMAGE-SI12 between 2000 and 2002. Simultaneous c mparison with GOES-8 and DMSP data allows us to estimate how strong is the relation between the EL position d educed from SI12 and the magnetic field stretching. Time evolutions of the EL position are also presented for differe nt local times during individual events.
L 1 phonetic drift in ! Dutch L 2 speakers of English ? !

This longitudinal study examines the development of voice onset time (VOT) for the stops /t/ and /d/ and the central frequency of the /s/ sibilant in a group of fluent L2 speakers of English whose L1 is Dutch, over a period of 3 years. The speakers are Dutch students who live and study at a residential college where the lingua franca is English. The student community is international, with ca. 60% being Dutch L1 speakers, and the remaining 40% comprising over 30 different L1s. A detailed description of the making of this corpus can be found in [5]. The core hypothesis which motivated the collection of this corpus is that, over the three years of these students’ undergraduate study, their accents of English will gradually converge to some kind of UCU Accent of English, which is not a native accent for any speaker. As part of this convergence, the influence of the Dutch accent of English is expected to play a large role, since the Dutch population forms the majority. For this study, we look at possible phonetic drift in word-initial /d/ and /t/, and the sibilant /s/, which are realised differently in Dutch and english. In nonclustered word-initial position, typical VOT values for Dutch voiceless stop /t/ and the English voiced stop /d/ are quite similar. Dutch voiced stops have a shorter lag time and English voiceless stops have a much longer lag time, being generally aspirated. Dutch has only one sibilant /s/ whereas English has two, namely /s/ and /S/ [3, 2]. The articulation of the Dutch /s/ is described as being somewhere between the two English sibilants, having a more retracted position of articulation, a flatter tongue, and more lip rounding [3]. Because these particular phonemes exhibit phonetic, rather than phonemic differences in Dutch and English, it is interesting to explore them in the context of Flege’s speech learning model (SLM), which suggests that the ability to perceive within-phoneme differences between an L1 and an L2 may drive the formation of a new phonetic category within a single phoneme [7]. Conversely, if a speaker does not perceive the difference, this new category may not be formed at all, but both L1 and L2 values will assimilate towards each other. We hypothesize that this will be the case for the Dutch L1 speakers’ VOT values for /t/ and /d/, and for the production of /s/.
University of Groningen Evaluation of a lifestyle intervention program in primary care on physical and mental health and quality of life of cancer survivors Beumeler,

Introduction: Cancer survivors often suffer from fatigue and (mental) health impairments. Despite evidence for effectiveness, lifestyle interventions are seldom applied in their aftercare. The aim of this study was to assess feasibility of a lifestyle intervention program on physical and mental wellbeing and quality of life (QoL) of cancer survivors, and to get a first impression of effectiveness, by means of a pilot study. Methods: Nine subjects were enrolled in a 12-month lifestyle intervention pilot study without a control group, conducted in a Dutch primary care centre. The intervention consisted of individual and group lifestyle training focusing on diet, exercise and mind-body interaction. The main outcomes were physical and mental health and QoL. Results: All 9 subjects completed the 12-month lifestyle intervention program. We found a large positive effect on fatigue (r=-0.9), stress (r=-0.8) and anxiety (r=-0.9). With respect to quality of life, large improvements in vitality (r=0.7), role limitations due to physical health (r=-0.7), role limitations due to emotional problems (r=-0.8) and personal health experience (r=0.8) were found. Subjects’ arm strength increased (r=0.9), but there were no significant changes in other physical parameters, depressive symptoms, social optimism and autonomy. Contradictory results were found for pain. Conclusion: Implementation of this lifestyle intervention program seems feasible in this small uncontrolled pilot study. The reduced QoL that is typical for cancer survivors was positively influenced by this program. Most prominent results were retrieved for fatigue and mental functioning, whereas little effects were found for physical health.
Effects of Physical Environment on Brand Loyalty and Moderated Effects of Brand Image

In this study, we will establish differentiated marketing strategies (Physical Environment) in saturated market and we analyzed the interrelation between Physical Environment and Brand Loyalty as well as moderating effect on brand image. We visited 50 screen golf range places in Daegu city and Gyeungbuk province, and then conducted a survey from 300 people, using Self-Legislation Period for the questionnaires. Collected questionnaires were analyzed by Hierarchical Regression Analysis. As a result, the causal relationship between physical environment and brand loyalty has the partially positive effect, but moderating effect on brand image has not moderated between Physical environment and brand loyalty. Therefore, we may build some strategies in Golf industry. First, High-brand-image (physical environment) strategies for increasing the brand loyalty must provide a feedback to customer for product and service aspects. Second, the enterprises have to select a target accordingly (high cost & luxury physical environment strategy or low cost & normal physical environment). In further study, the research samples need to be collected within expanded scale. To understand customer needs, the factors of brand loyalty should be divided more specifically (including individual factors).
Constraints to the Use of Off-site Production on Construction Projects

Abstract Off-site production (OSP) has been promoted as one of the solutions to the industry's performance problems. Numerous works have demonstrated the possible benefits of adopting such approaches to construction projects, yet uptake has been slow. Addressing these concerns, a series of factors were identified that affect the use of OSP within construction projects. From these factors a pattern emerged in which some factors drove OSP adoption, whereas others constrained its implementation. These constraints were investigated further using a questionnaire survey that was sent to all major stakeholders, ranging from clients through to end manufacturers. The extent to which the constraints inhibit the use of OSP were ascertained, scored and ranked. Four broad constraint themes emerged from the findings, namely process, value, supply-chain and knowledge constraints. A model illustrating the relationship between the four themes provides further insight into the constraints to OSP uptake. The authors further suggest that a broader understanding of the constraints is required, arguing that although OSP can contribute to change in the industry, it itself depends on change in order to be widely adopted.
Entry size , Ownership Form , and Spatial Location : An Analysis of the Hotel Industry

This paper analyses the impact of ownership type on the locating behavior and capacity choice of prospective entrant hotels. An important aspect which has often been neglected in the entry literature is the relevance of the ownership that defines an establishment. A hotel outlet can be company-owned, franchised, or independently owned. The type of ownership is an important driver of the incentive structure for a firm as well as a strategic indicator for its (prospective) competitors, thus this paper argues that ownership form is a necessary explanatory factor in market conduct analysis. We show using a spatial lag model that a disaggregated analysis provides a good understanding of market interaction among hotels.
Two-dimensional Solute Dispersion Along and Against the Unsteady Groundwater Flow in Aquifer

Two-dimensional solute dispersion in saturated poro us media is discussed. The model is solved analytically, using the Laplace Transform Te chnique (LTT) and numerically with the help of Explicit Finite Difference (EFD) method. We assu me that the aquifer is homogeneous, anisotropic and semi-infinite in nature. Initially the aquifer is not supposed to be solute free. A pulse type input source concentration is considered at the top layer of the outer boundary at the far end from the origin i.e., at the intermediate p ortion in the aquifer different from origin. For this reason two cases arises involving: i) concentr ation distribution of solute along the flow and ii) concentration distribution of solute against th e flow. At the other end of the aquifer, the concentration gradient is supposed to be zero. The dispersion coefficient is assumed proportional to the temporally dependent seepage velocity. Root Mean Square (RMS) error is explored for the accuracy of the solution. CPU time in matlab coding is also executed.
Detecting Differences between Clinical Presentations in ADHD through the Cognitive Profile Obtained from WISC-IV

Objective: The current study explores whether WISC-IV cognitive profiles could allow to differentiate between presentations of ADHD. Method: A clinical sample of 216 subjects aged between 6 and 16 years and distributed into 2 subgroups (ADHD inattentive type group aged M = 8.5, SD = 2.4; and ADHD combined group M = 10.1, SD = 2.6) was recruited for the study. Results: Processing Speed Index mean score was significantly higher (F (1,214) = 14.7, p< . 001, d = 0.52) in ADHD-Inattentive group (M = 90.7; SD = 12.1) than ADHD-Combined group (M = 97.7; SD = 14.7). Furthermore, PSI was negatively associated with “Inattention” dimension (β = -.21, p< .001 family and β = -.19, p< .001 teachers) while it was positively associated with “Hyperactivity/Impulsivity” dimension (β = .27, p< .001 family and β = .33, p< .001 teachers). Conclusions: The higher inattentiveness the lower PSI mean score, while a higher hyperactivity/impulsivity mean score would reduce the impact caused for inattentiveness. Thus, ADHD-I profile would tend to show a significant lower PSI mean score than ADHD-C.
INTELLIGENT PREDICTION OF CONCRETE CARBORATION DEPTH USING NEURAL NETWORKS

Carbonation problem in concrete has the potential to cause severe degradations in structures and therefore, its accurate prediction is critical in the field of civil engineering. This study involves the results obtained from the preliminary investigations on the use of artificial neural networks (ANN) as a non-destructive method for the prediction of carbonation depth in concrete. A total of 225 experimental cases obtained from the related literature have been used as the training and testing data set, with 18 different input parameters identified to be influencing the output, which is the carbonation depth measured in concrete. Two learning schemes were suggested with varying training: testing data distributions and three different values for hidden neurons were tested in combination. Results show that the use of ANN for the prediction of carbonation depth has a potential to provide predictions with satisfactory accuracy. Variations in the coefficient of determination (R), the mean squared error (MSE) and in the number of iterations required for learning, within the proposed changing combinations of training:testing data distribution and the number of hidden neurons has been discussed. The combination of highest coefficient of determination ( R), and the lowest mean squared error (MSE) that were determined as 0.975 and 0.0018 respectively, was observed when CGP method is used with 50%:50% training:testing data distribution) and with 10 hidden neurons. 2010 Mathematics Subject Classification: Primary 92B20, 68T10; Secondary 82C32, 93C85.
Fast LP-based Approximations for Geometric Packing and Covering Problems

We derive fast approximation schemes for LP relaxations of several well-studied geometric optimization problems that include packing, covering, and mixed packing and covering constraints. Previous work in computational geometry concentrated mainly on the rounding stage to prove approximation bounds, assuming that the underlying LPs can be solved efficiently. This work demonstrates that many of those results can be made to run in nearly linear time. In contrast to prior work on this topic our algorithms handle weights and capacities, side constraints, and also apply to mixed packing and covering problems, in a unified fashion. Our framework relies crucially on the properties of a randomized MWU algorithm of [41]; we demonstrate that it is well-suited for range spaces that admit efficient approximate dynamic data structures for emptiness oracles. Our framework cleanly separates the MWU algorithm for solving the LP from the key geometric data structure primitives, and this enables us to handle side constraints in a simple way. Combined with rounding algorithms that can also be implemented efficiently, we obtain the first near-linear constant factor approximation algorithms for several problems.
THE DEVIL IN THE DETAILS: POPULATION ESTIMATION FOR CONSERVATION MANAGEMENT OF TEXAS HORNED LIZARDS (PHRYNOSOMA CORNUTUM) by ALEXIS ACKEL

THE DEVIL IN THE DETAILS: POPULATION ESTIMATION FOR CONSERVATION MANAGEMENT OF TEXAS HORNED LIZARDS (PHRYNOSOMA CORNUTUM) By: Alexis Ackel, M.Sc., 2016 Department of Environmental Science Texas Christian University Thesis Advisor: Dean Williams, Associate Professor in Biology Population estimation is an important monitoring technique for threatened and endangered species as a means of informing management decisions and gauging conservation efforts. However, many threatened species exhibit crypticism in behavior and appearance that confound detection and thus impede accurate population estimation. The Texas horned lizard (Phyrnosoma cornutum) is a cryptic reptile with a broad distribution throughout the Southwestern U.S., including most of Texas. They have experienced putative declines throughout much of their range over the last several decades but there is currently a paucity of population data to inform their conservation. We censused for P. cornutum in two small Texas towns in order to investigate effective sampling and population estimation methods for rare and cryptic species. CaptureMark-Recapture (CMR) is one of the oldest and most commonly employed methods and has traditionally relied on the physical capture and permanent marking of individuals to identify recaptures. Non-invasive genetic sampling of hair, scat, or feathers represents an increasingly popular alternative to physical tagging since it poses less risk to study organisms, requires less effort, and is more cost effective than traditional sampling schemes. However, it has not been widely used in reptile populations. Thus, we conducted both traditional capture-based (marking with PIT tags) and non-invasive genetic sampling (via scat) and compared population estimations as modeled by the programs MARK and CAPWIRE. We also investigated effective population size within the study area as well as correlations between scat counts and lizard abundance. We concluded that non-invasive genetic sampling represents a viable alternative to traditional sampling for Texas horned lizards and potentially other cryptic reptiles. Simple scat counts show promise as a rapid censusing method for establishing baseline abundance but additional research on scat deposition and persistence in the study area and the applicability of these relationships to other habitat types and regions is needed.
THE PROJECTION AND THE ANALYSIS OF THE CELLULAR AUTOMATA FOR PROCESSING OF INFORMATION

The major objective of this research is to develop techniques for realizing a software and hardware encryption system with low cost, high speed and good security. This has been achieved by using a simple structure called cellular automata. In present, the necessity of a circuits and communication systems with reduced power consumption, ample transmission capacity, flexibility and reliability at a low fabrication cost are essential technical-economic challenge.
RELIABILITY IMPROVEMENT OF RADIAL DISTRIBUTION SYSTEM WITH INCROPORATING PROTECTIVE DEVISES-CASE STUDY

This paper present an effective approach of real time evaluation of radial distribution system power flow solution with an objective of determining the voltage profiles, total losses and indices. Two matrices the businjection to branch-current matrix (BIBC) and the branch-current to bus voltage matrix (BCBV) and a simple matrix multiplication are used to obtain power flow solutions. In this work we have considered the load diversity factor for analysis of load data for real time system. Assessment of customer and energy oriented indices is an important part of distribution system operation and planning. Distribution system reliability assessment is a measure of continuity and quality of power supply to the consumers, which mainly depends on interruption profile, based on system topology and component reliability data. The performance of the system was investigated on two stage basis first consisting a standard 33 bus systems and then real time distribution system as case study. To demonstrate the effectives of the proposed method, a 24-node 11kv Jeevakona urban distribution feeder is selected, which is a heavily loaded feeder and is already installed by 18 KVAR capacitor bank at each Distribution Transformer (DTR) in LT side with pole mounted. For analyzing the results average load data is considered with an average power factor for feeder and distributed depending on the connected load. The results are presented
Hybrid Models for Aspects Extraction without Labelled Dataset

One of the important tasks in opinion mining is to extract aspects of the opinion target. Aspects are features or characteristics of the opinion target that are being reviewed, which can be categorised into explicit and implicit aspects. Extracting aspects from opinions is essential in order to ensure accurate information about certain attributes of an opinion target is retrieved. For instance, a professional camera receives a positive feedback in terms of its functionalities in a review, but its overly high price receives negative feedback. Most of the existing solutions focus on explicit aspects. However, sentences in reviews normally do not state the aspects explicitly. In this research, two hybrid models are proposed to identify and extract both explicit and implicit aspects, namely TDM-DC and TDM-TED. The proposed models combine topic modelling and dictionary-based approach. The models are unsupervised as they do not require any labelled dataset. The experimental results show that TDM-DC achieves F1-measure of 58.70%, where it outperforms both the baseline topic model and dictionary-based approach. In comparison to other existing unsupervised techniques, the proposed models are able to achieve higher F1-measure by approximately 3%. Although the supervised techniques perform slightly better, the proposed models are domain-independent, and hence more versatile.
Adaptive Basis Selection for Exponential Family Smoothing Splines with Application in Joint Modeling of Multiple Sequencing Samples

Second-generation sequencing technologies have replaced array-based technologies and become the default method for genomics and epigenomics analysis. Second-generation sequencing technologies sequence tens of millions of DNA/cDNA fragments in parallel. After the resulting sequences (short reads) are mapped to the genome, one gets a sequence of short read counts along the genome. Effective extraction of signals in these short read counts is the key to the success of sequencing technologies. Nonparametric methods, in particular smoothing splines, have been used extensively for modeling and processing single sequencing samples. However, nonparametric joint modeling of multiple second-generation sequencing samples is still lacking due to computational cost. In this article, we develop an adaptive basis selection method for efficient computation of exponential family smoothing splines for modeling multiple second-generation sequencing samples. Our adaptive basis selection gives a sparse approximation of smoothing splines, yielding a lower-dimensional effective model space for a more scalable computation. The asymptotic analysis shows that the effective model space is rich enough to retain essential features of the data. Moreover, exponential family smoothing spline models computed via adaptive basis selection are shown to have good statistical properties, e.g., convergence at the same rate as that of full basis exponential family smoothing splines. The empirical performance is demonstrated through simulation studies and two second-generation sequencing data examples.
Assessment of synthetic winds through spectral modeling and validation using FAST

In this paper, we analyse the simulated and measured wind data with respect to their spectral characteristics and their effect on wind turbine loads. The synthetic data is generated from a stochastic full-field turbulent wind simulator TurbSim for neutral stability conditions. We first investigate a model for velocity spectra and, a coherence model, by comparing the model results with the measurements. In the second part we analyse the synthetic data via spectra and coherence for two cases; without and with adding coherent events. Finally, we compare wind turbine loads calculated by using FAST simulation of 5 MW reference wind turbine on the basis of simulated and measured data for the given mean wind speed.