Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical, Chemical and Antioxidant Properties of Olive Oil Extracted from Memecik Cultivar

Physical, chemical and antioxidant properties of olive oil extracted from Memecik cultivar, one of the economically important cultivars of Turkey, were studied. Olive samples were handpicked at the last stage of ripening index (RI: 6.91) based on the degree of pulp and skin pigmentation. Olive samples were mechanically processed at laboratory conditions by using two-phase batch extraction equipment. Afterwards olive oil was analytically tested for fatty acid composition and tocopherols. Also main quality parameters such as free acidity, peroxide value, K 232 , K 270 , total chlorophyll, total caretonoids and refractive index were determined. Antioxidant activity of olive oil was determined by 2, 2-diphenyl-1-picrylhydrazyl (DPPH•) scavenging method. Quality parameters of oil extracted from Memecik olives were in good agreement with the literature. Results indicated that late harvest olive oils can have low free fatty acid (FFA) and peroxide values (PV). Total phenolic content and antioxidant activity of oils were 169.25 mg gallic acid equivalent/kg and 89.55 (% inhibition of DPPH · radical), respectively.
ALLELOPATHIC EFFECTS OF WEEDS ON WHEAT (TRITICUM AESTIVUM L.) GERMINATION AND GROWTH

Three weed species viz., Asphodelus tenuifolius Cav. , Euphorbia hirta L. , and Fumaria indica (Haussk.) Pugsley were used in the form of powder with different ratios/quantity as treatments of 10, 25, 50 and 100g and mixed with uniform amount of soil (500g). Wheat seeds were grown and it was observed that 10 and 25g powder/500g soil of Asphodelus tenuifolius considerably increased the germination and rate of germination of wheat, while the powder of other two species reduced this phenomenon in the test species at the concentration of 25, 50 and 100g/500g soil. All the weeds powder treatments showed remarkable varied effects on the plant height and their weights (fresh, dry shoot and root weight) of the test plant. The powder of Fumaria indica and Asphodelus tenuifolius significantly reduced, while the Euphorbia hirta showed non-significant effects on the wheat plant height. Soil containing Euphorbia hirta powder showed the significant reduction in the fresh and dry shoot weight of wheat plant.
Prediction of Evapotranspiration by Artificial Neural Network and Conventional Methods

This study describes the conceptual framework and implementation to estimate the evapotranspiration by using computation technique artificial neural network. The objective of this study is to test an artificial neural network (ANN) to estimate reference evapotranspiration (ETo). Evapotranspiration is one of the main components of the hydrologic cycle. This complex process is dependent on climatic factors. There are many conventional methods to estimate evapotranspiration. Among them three methods that is Modified Penman Method, Thornthwaite method and BlaneyCriddle method equation perform the accurate results of estimating reference evapotranspiration (ETo) among the existing methods. However, the equation requires climatic data that are not always easily available. Artificial neural networks are one of the recent technique and studies for modeling complex systems and nonlinear features have shown very high ability. The major objective of this study is to estimate evapotranspiration using an artificial neural network (ANN) technique and to examine if a trained neural network with limited input variables can estimate evapotranspiration (ETo) efficiently.
Security constrained optimal power flow problems A study of different optimization techniques

The electrical power grid is a critical infrastructure, and in addition to economic dispatch, the grid operation should be resilient to failures of its components. Increased penetration of renewable energy sources is placing greater stress on the grid, shifting operation of the power grid equipment towards their operational limits. Thus, any unexpected contingency could be critical to the overall operation. Consequently, it is essential to operate the grid with a focus on the security measures. Security constrained optimal power flow imposes additional security constraints to the optimal power flow problem. It aims for minimum adjustments in the base precontingency operating state, such that in the event of any contingency, the postcontingency states will remain secure and within operating limits. For a realistic power network, however, with numerous contingencies considered, the overall problem size becomes intractable for single-core optimization tools in short time frames for real-time industrial operations, such as rapid resolution of new optimal operating conditions over changing network demands, or real-time electricity market responses to electricity prices. Optimization software becomes a major bottleneck for the energy system modellers. Given that optimization software becomes a major bottleneck, this thesis aims to explore different optimization frameworks; specifically, it will cover the IPOPT and Optizelle optimization frameworks. Advisor Prof. Olaf Schenk Assistants Juraj Kardoš, Dr. Drosos Kourounis Advisor’s approval (Prof. Olaf Schenk): Date:
Intercomparison of Flow and Transport Models Applied to Vertical Drainage in Cropped Lysimeters

Models predicting flow and transport in the vadose zone differ in their conceptual approach, their complexity, and their mathematical formulation. Four models (MARTHE, TRACE, ANSWERS, and MACRO), which differ significantly in their model concepts and complexity, were applied to a common data set to evaluate and compare the different model approaches. Five free‐draining lysimeters, cropped with winter wheat, barley, and oat were used to monitor actual evapotranspiration, soil moisture, and drainage for 627 d. One of the five lysimeters was also treated with methabenzthiazuron (MBT), and soil residues as well as leaching were experimentally determined. In Europe, MBT has been commonly used as a herbicide for almost 30 years. Generally, the use of given model inputs is recommended, apart from plant parameters, which need calibration. The use of validation criteria revealed proper simulation of water flow for the four models. After calibration, the Richards' equation–based models MARTHE, TRACE, and MACRO performed better for water flow predictions than the capacity‐based ANSWERS. A small amount of preferential flow, which is not included in the model structures of MARTHE, TRACE, and ANSWERS, did not influence the simulation of water flow significantly. But preferential flow was associated with the leaching of 0.0059% of the applied mass of MBT, causing relevant concentrations in the leachate. Leaching could be described well with MACRO after calibration. The difficulty of estimating parameters for modeling macropore transport is seen as an obstacle to common application.
Mountain Torques and Northern Hemisphere Low-Frequency Variability . Part I : Hemispheric Aspects

The NCEP–NCAR reanalysis dataset for 1958–97 is used to analyze intraseasonal variations in mountain torques and the large-scale atmospheric circulation patterns associated with them. Spectral analysis of the atmospheric angular momentum (AAM) budget shows that the dominant variations of mountain torque have periodicities near 30 days and shorter, while the dominant AAM variations occur in the 40–60-day band. This difference is due to the 40–60-day AAM variations being primarily related to equatorial processes, while mountain torque variations are associated mostly with extratropical processes. The Northern Hemisphere (NH) mountain torque has enhanced power and significant spectral peaks in the 20–30-day band. The signal in this band accounts for 33% of the NH mountain torque variance, once the seasonal cycle has been removed. Lag composites of the NH 700-hPa geopotential heights based on the 20–30-day mountain torque signal show the latter to be associated with coherent large-scale patterns that resemble lowfrequency oscillations identified in this band by previous authors. The composite patterns that are in phase quadrature with the 20–30-day NH mountain torque have a pronounced zonally symmetric component. These patterns are associated with substantial AAM variations, arguably driven by the NH mountain torque in this band. Principal component (PC) analysis of the NH 700-hPa heights shows that, in the 20–30-day band, the mountain torque is also in phase quadrature with the two leading PCs; the first corresponds to changes in the midlatitude jet intensity near the subtropics, while the second corresponds to the Arctic Oscillation. The relationships with AAM of the latter essentially occurs through the mass term. Mountain torques are, furthermore, nearly in phase with dominant patterns of low-frequency variability that exhibit substantial pressure gradients across the Rockies and the Tibetan Plateau.
Building and Learning Structures in a Situated Blocks World Through Deep Language Understanding

We demonstrate a system for understanding natural language utterances for structure description and placement in a situated blocks world context. By relying on a rich, domain-specific adaptation of a generic ontology and a logical form structure produced by a semantic parser, we obviate the need for an intermediate, domain-specific representation and can produce a reasoner that grounds and reasons over concepts and constraints with real-valued data. This linguistic base enables more flexibility in interpreting natural language expressions invoking intrinsic concepts and features of structures and space. We demonstrate some of the capabilities of a system grounded in deep language understanding and present initial results in a structure learning task.
Functional morphology of burrows and trophic modes of three thalassinidean shrimp species, and a new approach to the classification of thalassinidean burrow morphology

The burrow morphology and feeding behaviour of 3 species of thalassinidean shrimps, Callianassa subterranea, Jaxea noctuma and Upogebia stellata, from organically enriched sediments on the west coast of Scotland were studied using a resin casting technique and from observations in situ and in the laboratory. C, subterranea is primarily a sub-surface deposit feeder but can also supplement its diet by suspension feeding. The burrow conslsts of a lattice of tunnels and chambers connected to the surface by an inhalant and exhalant shaft and can reach depths of greater than 86 cm. J. nocturna is also a deposit feeder but uses a resuspension technique. Sub-surface material is taken but this species may also scavenge organic material from the sediment surface. The burrow is relatively persistent with a wide spiralling shape. Burrow depths in excess of 92 cm have been recorded. U. stellata is primarily a suspension feeder but has the ability to deposit and resuspension feed. Burrows comprise several connected Uand Y-shaped components and reach depths of at least 26.5 cm. These 3 thalasslnidean species exhibit a degree of plasticity in their feeding and different trophic modes can be utilized in order to exploit the most advantageous food source available. The burrow of each species is described in terms of functional morphology with respect to feeding and discussed in relation to existing models of thalassinidean burrow architecture. A new approach to thalassinidean trophic classification based on individual components of burrow morphology rather than the complete burrow is proposed.
Relationship between HIV Counseling and Testing (HCT) Awareness and HCT Uptake among Young People in Nigeria: Implications for Social Change

This study examined the relationship between HIV counselling and testing (HCT) awareness and HCT uptake among young people in Nigeria and their implications for social change. The study is a quantitative research guided by one research question and one hypothesis. The target population comprised young people in Nigeria ages 15 to 24 years because the focus of this study was to identify the factors affecting HCT uptake among young people in this age cohort. The representative sample was obtained from the updated master sample frame of rural and urban zones developed by the National Population Commission in Nigeria. This master sample frame was a national survey that comprised all 36 states in Nigeria. Probability sampling technique was used to obtain a sample of 10,091 respondents (ages 15 to 24 years) for the study. The multistage cluster sampling was used to select suitable young people with known probability. Data were collected throughout Nigeria between September and December 2012 from 32,543 households (rural = 22,192; urban = 10,351) using structured and semi-structured questionnaires. The individual questionnaires asked about household characteristics, background characteristics of the respondents. Data were analyzed by inputting them into SPSS v21.0 for analysis and then coded them for each participant. The data were summed using descriptive statistics. Frequencies and percentages; measures of central tendencies were used to answer the research question while nonparametric tests such as chi-square were used to analyze non-normally distributed data at 0.5 level of significance. The results of the chi-square test of association between HCT awareness and HCT uptake showed that there was a statistically significant relationship between HCT awareness and HCT uptake among young people ages 15 to 24 years in Nigeria, X2 (1, n = 8916) = 306.66, p < 0.001. In other words, knowledge of the availability of HCT services may have influenced the possibility that the participants would use them. Among others, it was recommended that government should examine the efficacy of HCT treatments in Nigeria, along with conducting a demographic analysis of the at-risk population.
A standardised representation for non-parametric fMRI results

Introduction : Reuse of data collected and analysed at another site is becoming more prevalent in the neuroimaging community (cf. for example (Milham et al. 2017)) but this process usually relies on intensive data and metadata curation. Given the ever-increasing number of research datasets produced and shared, it is desirable to rely on standards that will enable automatic data and metadata retrieval for large-scale analyses (Wilkinson et al. 2016). We recently introduced NIDM-Results (Maumet et al. 2016), a data model to represent and publish data and metadata created as part of a mass univariate neuroimaging study (typically functional magnetic resonance imaging). Here we extend this model to allow for the representation of non-parametric analyses and we introduce a JSON API that will facilitate export into NIDM-Results.
Doctoral Thesis Exploiting Graphics Processing Units for Massively Parallel Multi-Dimensional Indexing

Scientific applications process truly large amounts of multi-dimensional datasets. To efficiently navigate such datasets, various multi-dimensional indexing structures, such as the R-tree [1], have been extensively studied for the past couple of decades. Since the GPU has emerged as a new cost-effective performance accelerator, now it is common to leverage the massive parallelism of the GPU in various applications such as medical image processing [2], computational chemistry [3], and particle physics [4]. However, hierarchical multi-dimensional indexing structures are inherently not well suited for parallel processing because their irregular memory access patterns make it difficult to exploit massive parallelism [5]. Moreover, recursive tree traversal often fails due to the small run-time stack and cache memory in the GPU [6]. First, we propose Massively Parallel Three-phase Scanning (MPTS) R-tree traversal algorithm to avoid the irregular memory access patterns and recursive tree traversal so that the GPU can access tree nodes in a sequential manner. The experimental study shows that MPTS R-tree traversal algorithm consistently outperforms traditional recursive R-Tree search algorithm for multi-dimensional range query processing. Next, we focus on reducing the query response time and extending n-ary multi-dimensional indexing structures R-tree, so that a large number of GPU threads cooperate to process a single query in parallel. Because the number of submitted concurrent queries in scientific data analysis applications is relatively smaller than that of enterprise database systems and ray tracing in computer graphics. Hence, we propose a novel variant of R-trees Massively Parallel Hilbert R-Tree (MPHR-Tree), which is designed for a novel parallel tree traversal algorithm Massively Parallel Restart Scanning (MPRS). The MPRS algorithm traverses the MPHR-Tree in mostly contiguous memory access patterns without recursion, which offers more chances to optimize the parallel SIMD algorithm. Our extensive experimental results show that the MPRS algorithm outperforms the other stackless tree traversal algorithms, which are designed for efficient ray tracing in computer graphics community. Furthermore, we develop query co-processing scheme that makes use of both the CPU and GPU. In this approach, we store the internal and leaf nodes of upper tree in CPU host memory and GPU device memory, respectively. We let the CPU traverse internal nodes because the conditional branches in hierarchical tree structures often cause a serious warp divergence problem in the GPU. For leaf nodes, the GPU scans a large number of leaf nodes in parallel based on the selection ratio of a given range query. It is well known that the GPU is superior to the CPU for parallel scanning. The experimental results show that our proposed multi-dimensional range query co-processing scheme improves the query response time by up to 12x and query throughput by up to 4x compared to the state-of-the-art GPU tree traversal algorithm.
Electron-phonon effects in graphene and armchair (10,10) single-wall carbon nanotubes

The electron-phonon interaction in low-dimensional tight-binding systems is discussed. A sheet of graphite, which is two-dimensional, and an armchair single-wall carbon nanotube ~SWNT! , which is quasi-onedimensional, are taken as examples. For the modulated hopping the matrix elements for both systems are derived in the context of a two parameter model for the phonon vibrational spectrum. It is found that they ~for both structures! display a deformation type of potential, and are reduced by a factor of (12R), where R depends on the phonon parameters. It is also shown that the ordinary electron-phonon coupling displays a deformation type of approximation for both systems. Next, a different type of interaction is considered—the phonon modulated electron-electron interaction. It gives two contributions—random phase approximation with one phonon line and exchange interaction with one phonon line. We find that for the two-dimensional ~2D! graphene and for the quasi-1D ~10,10! SWNT, the modulated hopping and exchange coupling govern the electron transport at room temperatures.
Geometric Inference for General High-Dimensional Linear Inverse Problems

This paper presents a unified geometric framework for the statistical analysis of a general ill-posed linear inverse model which includes as special cases noisy compressed sensing, sign vector recovery, trace regression, orthogonal matrix estimation, and noisy matrix completion. We propose computationally feasible convex programs for statistical inference including estimation, confidence intervals and hypothesis testing. A theoretical framework is developed to characterize the local estimation rate of convergence and to provide statistical inference guarantees. Our results are built based on the local conic geometry and duality. The difficulty of statistical inference is captured by the geometric characterization of the local tangent cone through the Gaussian width and Sudakov minoration estimate.
Psychological Differences in Shame vs. Guilt: Implications for Mental Health Counselors

Recent work on the psychological distinctions between shame and guilt has important implications for mental health counselors. In particular, the work of Lewis (1971) and Tangney (1990, 1995; Tangney & Dearing, 2002) identifies psychological differences between shame and guilt and how they are phenomenologically expressed that provides helpful insight to those working with clients experiencing these emotions. This paper draws upon this work to establish criteria for distinguishing shame and guilt and to offer guidelines for their treatment.
Unfolding case studies throughout the Curriculum to stimulate students deeper learning.

Nursing faculty strive to develop innovative teaching methods that will ideally prepare nursing students for current complex healthcare settings. It is common that faculty perceive a need for content-laden curricula that seems to complicate integration of cutting-edge methods of teaching that are necessary for transforming nursing education. An innovative teaching method that includes unfolding case studies using narrative pedagogy where students, faculty, and nurses connect as they share clinical, simulation, and classroom experiences may lead to more profound learning for students. A unique way of students assisting faculty and nurses in the development of unfolding case studies intends to provide students with enhanced learning opportunities in order to link concepts with evidence-based practice; therefore, discover deeper understanding of nursing concepts.
Teaching informatics for fun and profit

Informatics has little to do with the skilled use of a bunch of specific applications: in fact, being fluent in using a given computer application is largely independent from the knowledge one may have in the discipline. In other words: to be able to read a clock one needs virtually no knowledge about the laws of pendulum. An interesting remark about the various interpretations of the term informatics is due to Claudio Mirolo [6], one of the promoters of the Task Force for the Research on Teaching of Informatics at the University of Udine, who identifies at least three possible acceptations, corresponding to different cultural approaches:
The impact of service learning on the training of pre-service teachers Analysis from a physical education subject

This paper discusses the effects of the use of service learning in pre-service teachers (PSTs). This methodology has been applied for two academic years at a Spanish university, providing a direct service for children with special educational needs (SEN) through motor and expressive games. We used Butin’s model for the analysis of data collected through written reflections. The results show significant academic and personal learning, especially in areas useful for future teachers. The paper also proposes an extension (subcategories) of the original explanatory model.
Synthesis, morphology and rheology of core-shell silicone acrylic emulsion stabilized with polymerisable surfactant

Core-shell silicone acrylic emulsions with 3-methacryloxypropyl trimethoxysilane (MPTS) in the shell were pre- pared by seeded polymerization with the assistance of polymerisable maleate surfactant (MT). Fourier transform infrared (FT-IR) demonstrated the incorporation of polymerisable surfactant in copolymer. It was found that small amount of octadecyl acrylate was beneficial to emulsion stability with decreasing the particle size from 194.6 to 165.7 nm. It was also found that the particle size increased from 165.7 to 242.9 nm with the increase of MPTS concentration. Furthermore, rheo- logical measurement indicated that the emulsion was endowed with pseudoplasticity. At low shear rate, marginal reduction in viscosity was detected when MPTS concentration increased to 2%, while great increase in viscosity was observed with higher MPTS concentration, the interaction force among emulsion particles became the predominant factor instead of par- ticle size. In addition, better water resistance was observed when MT concentration was lower than 1.5%, and MPTS con- centration higher than 2%. Moreover, surface roughness was increased with MPTS addition, the crosslinking among core and shell reconstructed the surface morphology of film.