Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

A 1 km 2 resolution digital elevation model (DEM) of Ireland was constructed and used as the basis for generating digital maps of the climate parameters required to run a model of ecosystem carbon and water cycling. The DEM had mean absolute errors of 30 m or less for most of Ireland. The ecosystem model requires inputs of monthly precipitation, monthly averaged maximum and minimum daily temperature, and monthly averaged daily solar radiation. Long-term (1951 to 1980) averaged monthly data were obtained from sites measuring precipitation (618 sites), temperature (62 sites), and the number of hours of bright sunshine per day ('sunshine hours') (61 sites). Polynomial regression was used to derive a simple model for each monthly climate variable to relate climate to position and ele- vation on the DEM. Accuracy assessments with subsets of each climate data set determined that poly- nomial regression can predict average monthly climate in Ireland with mean absolute errors of 5 to 15 mm for monthly precipitation, 0.2 to 0.5°C for monthly averaged maximum and minimum tempera- ture, and 6 to 15 min for monthly averaged sunshine hours. The polynomial regression estimates of cli- mate were compared with estimates from a modified inverse-distance-squared interpolation. Predic- tion accuracy did not differ between the 2 methods, but the polynomial regression models demanded less time to generate and less computer storage space, greatly decreasing the time required for regional modeling runs.
Analyzing Wavelet and Bidimensional Empirical Mode Decomposition of MRI Segmentation using Fuzzy C-Means Clustering

Image segmentation is a vital step in medical image processing. Magnetic resonance imaging (MRI) is used for brain tissues extraction in white and gray matter. These tissues extraction help in image segmentation applications such as radiotherapy planning, clinical diagnosis, treatment planning. This paper presents utilization of fuzzy C-means (FCM) clustering by using wavelet and bidimensional empirical mode decomposition (BEMD) to improve the quality of noisy MR images. The signal to noise ratio (SNR) value is calculated from FCM clustering data to examine the best segmentation technique. The experiment with synthetic Brain Web images has demonstrated the efficiency and robustness of the appropriate approach in segmenting medical MRI.
Potential drivers of the downward carbon and particle flux in Arctic marine ecosystems under contrasting hydrographical and ecological situations

Sammenfatningen kan gjerne publiseres pa Munin. Paper I er publisert som "open access" og sa vidt jeg vet er det ikke noe problem a ogsa publisere det pa Munin. Paper II er et manuskript som skal sendes til et vitenskapelig tidskrift i host og Paper III er "under revisjon". Jeg onsker ikke at Paper II + III er tilgjenglig pa Munin na, men kan gjerne gi beskjed nar de er publisert (det er planlagt a publisere begge to som "open access") og sa kan de bli lagt ut pa Munin.
Pinwheels in the sky, with dust : 3D modelling of the Wolf-Rayet 98a environment

The Wolf-Rayet 98a (WR 98a) system is a prime target for interferometric surveys, since its identification as a 'rotating pinwheel nebulae', where infrared images display a spiral dust lane revolving with a 1.4 yr periodicity. WR 98a hosts a WC9+OB star, and the presence of dust is puzzling given the extreme luminosities of Wolf-Rayet stars. We present 3D hydrodynamic models for WR 98a, where dust creation and redistribution are self-consistently incorporated. Our grid-adaptive simulations resolve details in the wind collision region at scales below one percent of the orbital separation (similar to 4 au), while simulating up to 1300 au. We cover several orbital periods under conditions where the gas component alone behaves adiabatic, or is subject to effective radiative cooling. In the adiabatic case, mixing between stellar winds is effective in a well-defined spiral pattern, where optimal conditions for dust creation are met. When radiative cooling is incorporated, the interaction gets dominated by thermal instabilities along the wind collision region, and dust concentrates in clumps and filaments in a volume-filling fashion, so WR 98a must obey close to adiabatic evolutions to demonstrate the rotating pinwheel structure. We mimic Keck, ALMA or future E-ELT observations and confront photometric long-term monitoring. We predict an asymmetry in the dust distribution between leading and trailing edge of the spiral, show that ALMA and E-ELT would be able to detect fine-structure in the spiral indicative of Kelvin-Helmholtz development, and confirm the variation in photometry due to the orientation. Historic Keck images are reproduced, but their resolution is insufficient to detect the details we predict.
An Illustrated list of basic morphotypes of Gymnamoebia (Rhizopoda, Lobosea)

Summary Detailed analyses of the diversity of locomotive forms among naked lobose amoebae (Lobosea, Gymnamoebia) allow us to construct a typology consisting of 19 “morphotypes” encompassing all known species of the subclass Gymnamoebia. We identify a “morphotype” as a “general pattern of the morphodynamic organisation of the locomotive form of an amoeba”. This system of morphotypes is not a taxonomical one and does not duplicate existing systematic classifications of the respective taxa, although some morphotypes correspond well to the systematic groups of gymnamoebae. Morphotypes are illustrated with schematic drawings and accompanied with brief diagnoses. Selected representatives of different morphotypes are illustrated with photomicrographs. The proposed system of morphotypes seems to be a useful tool for description of gymnamoebae and for elaboration of an iconographic key to gymnamoebae. It can be a helpful tool for preliminary determination of naked amoebae (especially in ecological studies).
Patterns of naming objects and actions in children with word finding difficulties

Children who experience difficulties in naming are described as having word finding difficulties (WFDs). In the present study 31 children with WFDs were identified through a wider survey of educational provision for those with language and communication difficulties. The children were included if they were between 6;4-7;10 years, had normal non-verbal intelligence, no major articulation difficulties, and had WFDs as diagnosed by the Test of Word Finding Difficulties. Three control groups were identified who were matched on: chronological age (N = 31), naming age (N = 31), and level of receptive grammar (N = 31). Children's comprehension of words, accuracy of naming, and latency to name were assessed for numerals, letters, and pictures of objects and actions. Half the pictures presented were high frequency items and half were low frequency items. The children with WFDs formed a heterogeneous group with respect to other language measures with the primary defining feature being their poor performance in word retrieval and their poor performance on a semantic fluency test. No differences were found between the children with WFDs and their age-matched peers when naming letters and numerals or in the comprehension of objects and actions. In contrast, the accuracy and latency of naming were significantly worse than that of age-matched peers. Accuracy of naming was equivalent to that of the language-matched peers and error patterns also were similar. However, the children with WFDs were the slowest to provide responses and for naming high frequency objects this difference approached significance in comparison to language-matched peers (p = .052). The findings point to the importance of using appropriate control groups, and are discussed in relation to the idea that WFDs are caused by impoverished semantic representations.
Explaining Change in Social Fluidity: Educational Equalization and Educational Expansion in Twentieth‐Century Sweden1

The authors analyze social fluidity among Swedish men and women using a series of 24 annual surveys, 1976–99 (N=63,280). A theoretical model suggests that changes in fluidity are normally driven by cohort rather than period effects. The results support this argument: changes in fluidity between the mid‐1970s and late 1990s were due to the successive replacement of older and less fluid, by younger and more fluid, cohorts. Cohorts differed in their fluidity because the effect of class origins on educational attainment declined (an equalization effect) and because greater shares of each cohort had higher levels of educational attainment, which placed them in labor markets that operate more meritocratically (a compositional effect). The article discusses the relevance of these results for other countries and for policy.
FUZZY LOGIC METHODOLOGIES FOR TORQUE RIPPLE FREQUENCY REDUCTION IN DIRECT TORQUE CONTROL OF AN INDUCTION MOTOR DRIVE

Direct Torque Control (DTC) is one of the commonly used techniques for speed control of induction motor drive. Among the various control techniques available, DTC is characterized by the absence of coordinate transformations, current regulators and PWM signal generators. Though its design is very simple, it provides good torque control. However, the hysteresis band in DTC introduces ripples in torque and flux. In this paper, a comparison of classical DTC technique, conventional fuzzy logic based DTC and the 12 sector methodology fuzzy logic DTC is carried out based on the output torque ripple frequency. Simulated results using MATLAB/ Simulink show improved performance of fuzzy logic methodologies over the classical DTC technique. In addition, advantages of the 12 sector methodology based fuzzy logic DTC over the conventional fuzzy logic based DTC is brought out in this paper.
Self-reported sleep and cognition: An examination of competing functional models

There are contrasting models that attempt to explain the mechanisms by which sleep impacts on cognition. One model suggests that there is a direct effect of sleep on memory and executive functioning. An opposing model suggests that sleep impacts on cognition indirectly – via sleepiness and lapses in attention. This study investigated the impact of sleep on cognition using self-report data from 205 participants. Overnight sleep duration/efficiency was assessed using the Sleep Efficiency factor of the PSQI to provide a measure of quantitative sleep. Daytime consequences of poor sleep, reflecting low arousal levels, were assessed using the PSQI Daily Disturbances factor and sleepiness on the Epworth Sleepiness Scale. Contrasting hypotheses were: (i) Poorer sleep duration/efficiency would directly predict poorer memory and executive functioning; and (ii) Lower daytime arousal would predict attention deficits, which would predict poorer memory and executive functioning. Regression analyses revealed support for an indirect effect of sleep on cognition, as attention largely explained the association. Results provide evidence of the critical role of low arousal on cognition. Importantly, the impact of Sleep Efficiency on cognition was accounted for by depression. Objective studies are needed to extend these findings, taking into account the role of attention and depression.
X-OUTLIER DETECTION AND PERIODICITY DETECTION IN LOAD CURVE DATA IN POWER SYSTEMS

Load curve data is a type of time series data which records the electric energy consumptions at time points and plays an important role in operation and planning of power systems. Unfortunately, load curves always contain abnormal, noisy, unrepresentative and missing data due to various random factors. It is crucial to power systems to identify and repair corrupted and unrepresentative data before load curve data can be used for planning and modeling. In this thesis we present a new class of X-outliers that have abnormal power consumption levels related to periodicity (X-axis) and propose a novel solution to detect these outliers. The underlying assumption is that the data set follows a periodicity and the length (not the pattern) of the periodicity is known. This is the case for most real load curve data collected at BC Hydro. In the above the periodicity is assumed to be known for X-outlier detection. In some other applications, however, the periodicity needs to be discovered. The latter is the case when the periodicity evolves, when a new time series is collected, or when conditions that affect time series have changed. Periodicity detection for time series has important applications in forecasting, planning, trend detection, and outlier detection. For time series with unknown periodicity, X-outlier detection could still be performed after the periodicity is detected. Thus X-outlier detection and periodicity detection are highly related and periodicity detection could be considered as a pre-processing step of X-outlier detection for time series with unknown periodicity. Therefore, in this thesis, we also propose a trend based periodicity detection algorithm for time series data with unknown periodicity. This approach is trend preserving and noise resilient. Real load curve data in the BC Hydro system is used to demonstrate the effectiveness and accuracy of the proposed methods.
Heat Pipes for Computer Cooling Applications

There is an increasing demand for efficient cooling techniques in computer industry to dissipate the associated heat from the newly designed and developed computer processors to accommodate for their enhanced processing power and faster operations. Such a demand necessitates researchers to explore efficient approaches for central processing unit (CPU) cooling. Consequently, heat pipes can be a viable and promising solution for this challenge. In this chapter, a CPU thermal design power (TDP), cooling methods of electronic equipments, heat pipe theory and operation, heat pipes components, such as the wall material, the wick structure, and the working fluid, are presented. Moreover, we review experimentally, analytically and numerically the types of heat pipes with their applications for electronic cooling in general and the computer cooling in particular. Summary tables that compare the content, methodology, and types of heat pipes are presented. Due to the numerous advantages of the heat pipe in electronic cooling, this chapter definitely leads to further research in computer cooling applications.
Temperature and daylength regulate encystment in calcareous cyst-forming dinoflagellates

We tested the effect of temperature (15, 20, and 25°C), daylength (8:16, 12:12 and 16:8 h light:dark cycles), and culture medium (K/5 and K/50) conditions on cyst production in batch cultures of 4 dinoflagellate species that form calcareous resting stages (Scrippsiella trochoidea var. aciculifera, Pentapharsodinium tyrrhenicum, Calciodinellum operosum and S. rotunda). The 4 species showed different encystment patterns at the temperature conditions tested; cyst production was inversely related to daylength conditions, and higher cyst yields were obtained with the less concentrated growth medium. Experiments with semi-continuous cultures of S. rotunda, in which nutrient concentration was kept within values comparable to in situ concentrations, were carried out with the aim of decoupling the effect of nutrient depletion on cyst production from that of daylength. Cyst production in this species, kept at a constant growth rate in non-depleted nutrient conditions, was only obtained at the shortest daylengths, thus supporting the role of short daylength in inducing the production of calcareous cysts. Our data suggest that encystment in the 4 species is regulated by a complex interplay of at least 3 factors: daylength, temperature and nutrient concentration. These results contribute to explain the timing of resting-stage production at sea, and point to the possible role of daylength as an environmental signal for the regulation of life cycles in dinoflagellates.
Pre-Service Student Teacher Practices in the Teaching of English as a Second Language: Experiences, Opportunities and Challenges

Teaching Practice (TP) was an integral component of teacher preparation that served as an important link between theory and practice and that entailed the inculcation of professional practice and conduct. However, research studies about teaching practice highlighted that pre-service teachers on TP faced a wide range of challenges that militated against effective pedagogy. The use of a foreign language as the language of Education usually one of the major challenges encountered by both teachers and learners. Student teachers who are users of English as a Second Language (ESL) and who are tasked with the responsibility of teaching English to second language learners therefore faced a double barrelled challenge of the low proficiency level and the limited proficiency of the learners. This study used the qualitative research design, utilizing document analysis and focus group discussions to investigate the practices of; and challenges encountered by B. Ed. pre-service teachers in teaching ESL during Teaching Practice. The study intended to establish the extent to which pre-service teachers employed their pedagogic, content knowledge and competences to effectively manage classroom pedagogy. The study argued that, during college based tuition; student teachers received, internalised and mastered some measure of teacher knowledge and competences which should enable them to teach effectively. The study further purported that; reflections and articulations from pre-service teachers’ experiences and critiques from their supervisors, provided enough feedback to reveal student-teacher strengths or weaknesses and to provide solutions for programme improvement. The results of the study led to the conclusion that there were several challenges faced in teaching English during TP and that some of the challenges could be mitigated by the adoption of critical pedagogies.
Modified Lifting Based DWT/IDWT Architecture for OFDM on Virtex-5 FPGA

A future Wireless communication requires high performance and high speed integrated data, audio, video and multimedia services. This performance is achieved using discrete wavelet transforms in terms of ISI and bandwidth compatibility over FFT based OFDM. Where FFT based OFDM has very compact spectral utilization which cannot satisfy the future needs. This project proposes implementation of new modified lifting wavelet transform for designing wavelets and performing the transform. By implementing LDWT, it is able to increase the spectral efficiency and also decrease the bit error rate. This paper presents a performance measure of mean squared error by using lifting wavelet transform. This paper shows that DWT-OFDM outperformed FFT-OFDM by approximately 6dB gain in BER, Haar wavelet showed best performance over other wavelets by approximately 2dB. However, computation complexity of DWT restricts use of DWT for OFDM due to its hardware requirements on VLSI platform. In this work, lifting based DWT is modified and a new architecture is derived that can compute DWT in less than 3.429ns, and consumes power of less than 28mW. The modified DWT is realized on Virtex II FPGA and occupies resources less than 114 slices. Thus the proposed DWT architecture is suitable for OFDM application.
An Improved EigenAnt Algorithm That Achieves a Balance between Intensification and Diversification

The EigenAnt algorithm has been proposed to find the shortest path between two nodes with a proof of convergence. Two novel features are noticeable in EigenAnt compared to the conventional ant colony optimization algorithms. Pheromone evaporation in the EigenAnt algorithm is done locally for the selected path and it does not use heuristic information in its selection phase. On the other hand, a simple version of ant colony optimization that also does not use heuristic information has been used for analyzing convergence, considering parameter impact analysis, in the problem of finding the shortest path for 1-node binary chain problems. In this paper, we propose to improve the EigenAnt algorithm by adding additional parameters in such a way as to be able to take advantage of the analysis developed for the simple ant colony optimization algorithm. We demonstrate through our analysis that since the Improved EigenAnt algorithm has one parameter more than ant colony optimization algorithms, tuning of convergence speed is decoupled from tuning of convergence features in the algorithm. Thus, IEigenAnt, which can be interpreted as having two uncorrelated intensification and diversification components, makes it possible to achieve a balance between intensification and diversification. In order to illustrate the advantages of this decoupling, we present experimental results for the routing network problem.
CORPORATE GOVERNANCE AND FIRM PERFORMANCE: EVIDENCE FROM INSTITUTIONAL INVESTORS AND PROXY VOTING IN KOREA

This paper investigates the role of institutional investors as corporate monitors by analyzing the relationship between proxy voting decisions and firm performance in Korea. We find that institutional investors support more proposals when firm performance is strong. They are more likely to support the proposals when ownership of the blockholder and foreign investors are high. It suggests that institutional investors monitor firms through active voting on the proposals relating to performance. On the contrary, National Pension Service' affirmative voting decisions is negatively related to firm performance. Furthermore, we also find that institutional investors' voting is significantly related to the long-term performance and impact the pass of proposal and they more carefully monitor financially distressed firm.
Overwinter Habitat and the Relationship of Overwinter to In-lake Densities of the Milfoil Weevil, Euhrychiopsis lecontei, a Eurasian Watermilfoil Biological Control Agent

The native weevil Euhrychiopsis lecontei has been associated with declines of Eurasian watermilfoil ( Myriophyllum spicatum ). The weevil spends all summer on submersed plants, producing 3 to 6 generations. In September to November adult weevils move to shore where they overwinter in leaf litter at drier sites near the shoreline. Mean November shoreline densities from 1992-1998 at Lake Auburn (mean = 43 N/ m 2 ) and Smith’s Bay of Lake Minnetonka, (mean = 125 N/ m 2 ) have ranged from zero to over 200 N/m 2 . Overwinter mortality is not severe (survival was typically >60%). Adults collected from terrestrial habitat have developed flight muscles and limited flight has been observed in the spring but submersed adults in summer do not have developed flight muscles. Adults return to the water in spring and females begin to develop and lay eggs after the water temperature reaches 10-15C. Spring (May-June) and Fall (September) inlake densities in these two lakes have ranged from zero to 40 N/m 2 and Lake Auburn typically had higher in-lake weevil densities (mean of 15 N/m 2 compared to 4 N/m 2 at Smith’s Bay). There was no relationship between in-lake and shoreline densities at Lake Auburn, but Smith’s Bay spring in-lake densities were correlated with spring shoreline densities. Inlake densities were not correlated between the two lakes but shoreline densities were correlated over time, suggesting that regional climatic factors may influence shoreline densities. Weevils disappeared from Lake Auburn in-lake samples in July 1998; no weevils were found there in shoreline or in-lake samples in 1999. In-lake factors such as fish predation may be more limiting than overwinter conditions.