Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamics in the Personal and Professional Development of Life-orientation Teachers in South Africa, Gauteng Province

Abstract Worldwide schools are confronted with a myriad of contextual challenges such as teenage pregnancy, HIV and AIDS, poverty, substance abuse, child headed households, suicide, to mention a few. South Africa, a country that is yet to win the war against poverty and underdevelopment is not an exception. Life Orientation (LO) as a subject presents schools in South Africa with opportunities to empower young people with knowledge and life skills to make meaningful choices. Whist the Department of Basic Education in South Africa has developed a clearly set LO curriculum, which has well-defined outcomes; it is not clear whether their training as LO teachers adequately equips them to deal with these multiple social issues affecting learners. The focus of this phenomenological study was to explore the dynamics in the Personal and Professional Development (PPD) of LO teachers in South Africa, in the Gauteng Province. Data were collected through nine individual interviews, two focus group interviews and two collages by participants from 14 districts within the Gauteng Department of Education (GDE). The findings suggested that the PPD of LO teachers was impeded by the fact that it did not address issues such as their personal experiences, their attitudes towards LO, the LO curriculum delivery, and the complex roles they play in dealing with challenging issues. Based on these findings recommendations are made on how to best address these dynamics through their PPD and how to best support LO teachers to ensure meaningful teaching of LO.
Mixed Acceleration Techniques for Solving Quickly Stochastic Shortest-Path Markov Decision Processes

In this paper we propose the combination of accelerated variants of value iteration mixed with improved prioritized sweeping for the fast solution of stochastic shortest-path Markov decision processes. Value iteration is a classical algorithm for solving Markov decision processes, but this algorithm and its variants are quite slow for solving considerably large problems. In order to improve the solution time, acceleration techniques such as asynchronous updates, prioritization and prioritized sweeping have been explored in this paper. A topological reordering algorithm was also compared with static reordering. Experimental results obtained on finite state and action-space stochastic shortest-path problems show that our approach achieves a considerable reduction in the solution time with respect to the tested variants of value iteration. For instance, the experiments showed in one test a reduction of 5.7 times with respect to value iteration with asynchronous updates.
Collective Features in Polyisobutylene. A Study of the Static and Dynamic Structure Factor by Molecular Dynamics Simulations

We present a study of the static and dynamic structure factor of polyisobutylene (PIB) by fully atomistic molecular dynamics simulations. The reliability of the simulated cell is first assured by computing the magnitudes measured by diffraction and neutron spin echo techniques on a fully deuterated sample and directly comparing the results with those previously obtained from experiments [Farago, B. ; Phys. Rev. E 2002, 65, 051803]. Taking advantage of the validated simulations, we have disentangled the contributions to the static and dynamic structure factor by using a suitable grouping of the partial correlation functions based on specific molecular groups in PIB: main-chain (MC) atoms and methyl group (MG) atoms. Regarding the structural features, we can attribute the temperature dependence of the first structure factor peak—which is dominated by interchain correlations mainly from backbone atoms—predominantly to the evolution of the MC/MG cross-correlations. Paradoxically, in the momentum transfer regio.
Phenolic content and antioxidant activity of Phymatopteris hastata

Various solvent extracts of Phymatopteris hastata, a traditional Chinese medicinal material, were screened for their antioxidant activities. Four systems of in vitro testing were employed to investigate the antiradical and antioxidant effect, i.e., the 2,2-diphenyl-1-picryhydrazyl (DPPH) and 2,2'-azinobis(3-ethylbenzothia- zoline-6-sulfonic acid) (ABTS) systems, the hydroxyl radical scavenging assay and the reducing power. In addition, butylated hydroxytoluene (BHT), a widely used synthetic antioxidant, was also studied for comparison. The results revealed that the ethyl acetate extract exhibited outstanding antioxidant activities, which was close or even superior to BHT. Furthermore, the total phenolic (TP) and total flavonoid (TF) contents of different extracts were measured, expressed as gallic acid and rutin equivalent, respectively. The antioxidant activities and the TP/TF content of dif- ferent extracts followed the same order: ethyl acetate extract > butyl alcohol extract > > petroleum ether extract, showing a good correlation between the antioxidant activities and the TP/TF content. The results showed that these extracts, especially the ethyl acetate extract, were rich in phenolics and flavonoids and could be considered as natural antioxidants.
Two‐Temperature Pair Potentials and Phonon Spectra for Simple Metals in the Warm Dense Matter Regime

We develop ion‐ion pair potentials for Al, Na and K for densities and temperatures relevant to the warm‐densematter (WDM) regime. Furthermore, we emphasize non‐equilibrium states where the ion temperature Ti differs from the electron temperature Te. This work focuses mainly on ultra‐fast laser‐metal interactions where the energy of the laser is almost exclusively transferred to the electron sub‐system over femtosecond time scales. This results in a two‐temperature system with Te > Ti and with the ions still at the initial room temperature Ti = Tr. First‐principles calculations, such as density functional theory (DFT) or quantum Monte Carlo, are as yet not fully feasible for WDM conditions due to lack of finite‐T features, e.g. pseudopotentials, and extensive CPU time requirements. Simpler methods are needed to study these highly complex systems. We propose to use two‐temperature pair potentials Uii(r, Ti, Te) constructed from linear‐response theory using the non‐linear electron density n (r) obtained from finite‐T DFT with a single ion immersed in the appropriate electron fluid. We compute equilibrium phonon spectra at Tr which are found to be in very good agreement with experiments. This gives credibility to our non‐equilibrium phonon dispersion relations which are important in determining thermophysical properties, stability, energy‐relaxation mechanisms and transport coefficients. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
I.M.A.G.E.: a New CAD Tool for Device Modeling in Spice

In this paper we describe I.M.A.GE. , a new CAD tool to embed semiconductor device mod- els and, more generally mathematical models ofnon electric devices inside a spice-like circuit simulator. User defined models can be developed and tested quickly, allowing efficient simulation ofeven large circuits. To outline the performance improvement and flexibility obtained by using our tool, we present two different application examples: the implementa- tion ofa fluorescent lamp model and a "multitermi- nal" smart-power bipolar device.
Offline Handwritten Signature Verification method based on Artificial Immune Recognition System and Artificial Neural Network

In the proposed work artificial immune recognition system and artificial neural network is used . AIRS is new research which stimulate biological behaviour ways like neural network. this system protect the system from any virus ,it will detect any foreign substance this process also includes both unchanged and un encountered organism[4]. this helped to develop system which could solve expert and intelligent system problems like fault or anomaly detection. The AIRS algorithm was used for thyroid diagnosis, fault detection and watermarking. In this method ANN is used in the verification stage of signature verification as AIRS algorithm the ANN is mainly used for large number of data or users and have been widely used for forecasting and decision modelling problem.ANN are computational models which are inspired by organising and functioning of biological blocks. This paper contribute two steps feature extraction and classification for feature extraction the Gaussian, Laplacian pyramid and canny edge detector is used and for classification in training AIRS is used and in ABSTRACT Natural immune system offers several fascinating options that motivated the planning of Artificial Immune Systems (AIS) accustomed solve varied issues of engineering and AI. AIS are significantly thriving in fault detection and diagnosing applications where anomalies like errors and failures are assimilated to viruses that ought to be detected. Thereby, AIS appear appropriate to automatically discover forgeries in signature verification systems. This paper proposes a unique technique for offline signature verification that's supports the artificial Immune Recognition System (AIRS) and ANN utilized in verification stage. For feature generation, 2 totally different descriptors are projected to get signature traits. the primary is that the Gaussian pyramid used for texture synthesis that is very redundant, coarse scales offer a lot of the data within the finer scales and Laplacian pyramid Seamlessly stitch along images into an image plaid (i.e., register the photographs and blurring the boundary), by smoothing the boundary in a very scale-dependent style to avoid boundary artefacts. The second descriptor is that the canny edge detector accustomed detects wide selection of edges in image. Performance analysis is administrated on GPDS-100 datasets. The results obtained showed that the proposed system has promising performance and infrequently well outperforms the state of the art.
Glosses, Spatial Intelligence, and L2 Vocabulary Learning in Multimedia Context

Abstract L2 research has consistently shown that providing glosses enhances L2 vocabulary learning. This paper reports on a study that examined the effect of pictorial, pictorial + sound, and video glosses on L2 vocabulary learning in multimedia context. More specifically, we investigated whether learners’ high spatial intelligence ability has any effect on their ability to take advantage of multimedia glosses in L2 vocabulary learning. Sixty two Azari-Turkish pre-university students were randomly assigned to three experimental groups and a control group. The experimental groups read the reading sections of three units of their textbook for six sessions using Scaffoglossing software and consulted one of the glosses, i.e., pictorial, pictorial + sound, or video glosses. All groups took a Persian equivalent test, a multiple-choice test, and a sentence completion test once as the immediate posttest and 25 days later as the delayed posttest. Data analyses revealed the positive effect of multimedia glosses on L2 vocabulary learning. However, there was no significant difference between the participating experimental groups. Contrary to our expectations, no significant difference was observed between the high and low spatial ability groups. The findings and implications of the findings are discussed in detail. Keywords: multimedia glosses, spatial intelligence, cognitive theory of multimedia learning, involvement load hypothesis
ON CARBON NANOTUBES REINFORCED CERAMIC COMPOSITE

This review looks at carbon nanotubes (CNT) capabilities as toughening agent in ceramic composite. CNT have exceptional mechanical strength of up to 60 GPa and stiffness of 1 TPa. Ceramic however is hard, brittle and lack of toughness. CNT were found to be capable to provide up to 173% improvement in fracture toughness of ceramic with 19 vol. % CNT. The degree of toughness improvement on CNT ceramic composite is dependent on the following parameters; i) CNT homogenous dispersion in the composite, ii) inter-wall and interfacial strength between CNT and ceramic, iii) method of producing the CNT ceramic composite, and iv) the resultant toughening mechanisms.
Compact Wideband Dual-Polarized Antenna With High Isolation Using Modified Direct Feeding Structure For Indoor Beamforming Array Applications

A modified direct feeding structure is proposed in this paper to realize a compact ( $45 \times 45$ mm2) wideband dual-polarized antenna with high isolation (33 dB) and low cross-polarization (30 dB). Compared with the conventional crossed dipole antennas, two additional pairs of dipoles are employed as coupling baluns as well as radiators. As a consequence, the proposed antenna with more symmetrical structure has the advantages of both the direct feeding (DF) and the coupling feeding (CF) structures, such as, balanced matching, high isolation, low cross-polarization, and compact size. Besides, the gap structure between adjacent dipoles is designed in elliptical shape to further improve the impedance matching. The proposed antenna realizes a wide impedance bandwidth over 51% (1.7–2.85 GHz) for VSWR <1.5. It is worth mentioning that the compact size and high isolation could greatly reduce the element spacing of beamforming antenna array. In order to investigate the performance of beamforming array, a two-element array fed by the out-of-phase power divider network is developed. The lowest operating frequency can be further extended to 1.6 GHz and the cross-polarization discrimination (XPD) is more than 10 dB within ±60° of the main lobe.
Impact of Diagnosis Related Group Refinement on the Choice Between Scheduled Caesarean Section and Normal Delivery: Recent Evidence from France

Studying quasi-experimental data from French hospitals from 2010 to 2013, we test the effects of a considerable diagnosis related group (DRG) refinement that occurred in 2012. As a result, the reform had a direct impact on hospital-level financial incentives but did not immediately concern individual providers. Using a difference-in-differences approach, controlling for multiple patient, hospital and regional characteristics and allowing for hospital and year effects, we show that introducing new severity levels and clinical factors into the reimbursement algorithm had no significant effect on the probability of a scheduled C-section being performed. The results are robust to multiple formulations of financial incentives, to restricting the sample to bigger (>15%) DRG tariff incentive changes and to analyzing policy effects for individual years following the reform. Our results suggest that the DRG refinement did not lead to a transmission of hospital-level stimuli to midwifes and obstetricians. Our paper is the first study that focuses on the consequences of DRG refinement in obstetrics and develops an approach suitable for measuring monetary incentives in this setting.
Applying the daily inflation to forecast the Broad Consumer Price Index (IPCA)

Since 2006, the Getulio Vargas Foundation (FGV) calculates a daily version of the Broad Consumer Price Index (IPCA), the official inflation index, calculated under the responsibility of the IBGE, the federal statistics agency in Brazil. Ardeo et. al. (2013) showed the importance of this indicator and how this daily information can be useful to a country that had high level of inflation. Despite the fact that this measure is a fair antecedent variable for inflation, due to some peculiarities concerning the collection period, the initial daily rating may not anticipate some effects, such as seasonal factors and the increase in prices controlled by the Brazilian Government. Hence, by taking into account the Monitor s daily time series, this paper intends to forecast the IPCA for the first six days of data collection. The results showed up that the proposal technic improved the IPCA forecast in the beginning of data collection. Key-words: IPCA, daily inflation, Monitor, Time Series, SARIMA
Benchmarking in higher education: a framework for benchmarking for quality improvement purposes

This paper provides an introduction to benchmarking with a focus on the higher education sector. It reviews approaches to date, with reference to the literature and introduces a framework approach, developed as a collaborative project between the Universities of Melbourne and Tasmania. The Framework was trialled in 2004 amongst seven Australian Universities by centres charged with responsibility for supporting teaching and learning.
ANGUILLICOLOSIS AMONG SILVER EELS: A 2-YEAR SURVEY IN 4 HABITATS FROM CAMARGUE (RHÔNE DELTA, SOUTH OF FRANCE)

We have investigated the spread of the infection by Anguillicola crassus among the silver phase of the European eel Anguilla anguilla in the Rhone delta. We reported values of prevalence, mean intensity and abundance in 4 habitats and we revealed negative relationships between these parasitic parameters and values of salinity (prevalence from 52 % in brackish waters to 77 % in fresh waters). We have also assessed the health state of the infected organ, i.e. the swimbladder. This may be a way to check the parasitic history of individuals throughout their continental phase. In silver eels free from parasites, the proportion of past infected individuals was ranged between 40 % and 78 %. When adding individuals showing worms at the autopsy with those showing signs of past infection(s), we highlighted a great proportion of silver eels really affected by anguillicolosis (from 71 % to 95 %, with a negative relationship in respect to salinity values). So, considering the spread of the infection, and its potential impairments on body condition, gas exchanges, hydrostatic abilities, etc., one may legitimately question about the proportion of silver eels that may get back to the Sargasso sea and reproduce.
Morfologia e aptidão da ovelha crioula lanada.

Variedades: ovelha Crioula (Fronteira); ovelha Crioula Preta (Serrana); ovelha Crioula Zebua ou ovelha Presepio; ovelha Crioula Comum ou ovelha Ordinaria; aptidao; Aspecto geral; Cabeca; Pescoco; Tronco; Garupa; Cauda; Escroto; Mamas; Membros; Velo; Defeitos.
Potential impacts of climate change and climate variability on China’s rice yield and production

We assessed the effect of greenhouse gas-induced climate change, as well as the direct fertilization effect of CO2, on rice yields and production in China. Our methodology coupled the regional climate model PRECIS (Providing Regional Climates for Impacts Studies) with the CERES (Crop Environment Resources Synthesis) rice crop model to simulate current (1961-1990) and future (2011-2100) rice yields and production under A2 and B2 climate change scenarios. The movement of rice-producing areas to more favorable climatic conditions was also considered. Results demonstrate that simulated future rice yields decrease without the CO2 fertilization effect and increase in some areas and time slices with it. Yield variability measured by the coefficient of variation exhibits increases in both scenarios, with the largest increases under A2. Due to favorable climatic conditions, single rice cropping may expand further north in China, and double rice cropping may move to the northern portion of the Yangtze River basin. China's potential rice production is projected to increase in the future, due to the CO2 fertilization effect and shifts in rice-producing areas. Three rice cultiva- tion regions (Sichuan basin, Yangtze River basin, and Huang-huaihai plain) are identified as highly sensitive to future climate change if no adaptation measures are implemented, due to yield decreases and large increases in production variability.
Causality, renormalizability and ultra-high energy gravitational scattering

The amplitude  ( s , t ) for ultra-high energy scattering can be found in the leading eikonal approximation by considering propagation in an Aichelburg–Sexl gravitational shockwave background. Loop corrections in the QFT describing the scattered particles are encoded for energies below the Planck scale in an effective action which in general exhibits causality violation and Shapiro time advances. In this paper, we use Penrose limit techniques to calculate the full energy dependence of the scattering phase shift Θ scat ( s ˆ ) , where the single variable s ˆ = Gs / m 2 b d − 2 contains both the CM energy s and impact parameter b, for a range of scalar QFTs in d dimensions with different renormalizability properties. We evaluate the high-energy limit of Θ scat ( s ˆ ) and show in detail how causality is related to the existence of a well-defined UV completion. Similarities with graviton scattering and the corresponding resolution of causality violation in the effective action by string theory are briefly discussed.
Improving Computational efficiency of Tentative Data set

The aim of data mining is to find novel, interesting and useful patterns from data using algorithms that will do it in a way that is more computational efficient than previous method. Current data mining practice is very much driven by practical computational concerns. In focusing almost exclusively on computational issues; it is easy to forget that statistics is in fact a core component. The Conventional decision tree classifies the data whose values are known and particular, but in this paper such classifiers handle data with tentative information. The value vagueness arises in many applications during the data collection process. Example sources of vagueness include currency conversion(Rupees to Dollar), role of packet data transfer, Daily weather report , protein design, Flight reservation, production company data due to fluctuation in raw material. With vagueness, the value of a data item is often represented not by one single value, but by multiple values forming a likelihood distribution. Rather than abstracting tentative data by statistical derivatives (such as mean and median), we discover that the accuracy of a decision tree classifier can be much improved if the "complete information" of a data item (taking into account the probability density function) is utilized . We extend conventional decision tree building algorithms to handle data tuples with tentative values and make a comparison between average based approach and distribution based approach. Since processing probability density function's is computationally more costly than processing single values (e.g., averages), decision tree construction on tentative data is more CPU demanding than that for certain data. To handle this problem, we propose a series of pruning techniques that can greatly improve edifice efficiency.
FitSKIRT: genetic algorithms to automatically fit dusty galaxies with a Monte Carlo radiative transfer code

We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi-dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.