Miracle-dz/UniFAR-FTUs huggingface dataset:
Characteristics of Ice Clouds Over Mountain Regions Detected by CALIPSO and CloudSat Satellite Observations

This study examines the characteristics of orographic ice clouds in steep mountain regions using 3 years of CloudSat and CALIPSO satellite products. A combination of radar and lidar cloud fraction data is used to identify ice cloud systems. Additionally, the retrieved ice water content (IWC) and ice number concentration (NI) are used to analyze the dominant ice cloud microphysics in convective‐ and cirrus‐type clouds. The analysis shows that temporally averaged values of the IWC and NI are larger in mountain regions than in land and ocean regions. For convective clouds over mountains, both the IWC and NI have larger values at atmospheric temperatures warmer than 250 K, suggesting a dominant role for the freezing of supercooled liquid water. For cirrus clouds over mountains, however, only the NI has larger values at atmospheric temperatures colder than 240 K, indicating the importance of homogeneous ice nucleation. These characteristics of ice‐phase clouds in terms of the IWC and NI in mountain regions are distinct, with a horizontal scale smaller than 300 km. This study suggests that it is useful to categorize ice clouds in mountain regions in addition to ocean and land regions to evaluate the microphysical properties (mass and number) of such ice clouds in atmospheric models.
Denoising of Radio Frequency Partial Discharge Signals Using Artificial Neural Network

One of the most promising techniques for condition monitoring of high voltage equipment insulation is partial discharge (PD) measurement using radio frequency (RF) antenna. Nevertheless, the accuracy of monitoring, classification, localization, or lifetime estimation could be negatively affected due to the interferences and noises measured simultaneously and contaminate the RF signals. Therefore, to achieve high accuracy of PD assessment, exploiting the denoising algorithms is inevitable. Hence, this paper seeks to introduce a new technique to suppress white noise, the most prevalent type of noise, especially for RF signals. In the proposed method, the ability of artificial neural network (ANN) in curve fitting is applied to denoising of different types of measured RF signals emitted from PD sources including ‘crack’, ‘internal void’, in the insulator discs and ‘sharp points’ from external hardware. The processes of denoising for named signals with the proposed method are carried out, and the obtained results are compared with the outputs of a wavelet transform-based method named energy conversation-based thresholding. In all tested signals, the proposed technique showed superior denoising capability.
An Improved Aggregated Model of Residential Air Conditioners for FIDVR Studies

Stalling of residential air conditioners (RACs) following a transient fault can delay the voltage recovery ranging from 3 to 20 seconds. This phenomenon is referred to as fault-induced delayed voltage recovery (FIDVR). Several aggregated RAC models have been presented to replicate the actual FIDVR events. However, they usually have two main drawbacks as: i) considering independent stalling voltage and stalling time for all RACs, ii) resulting in only two ultimate modes; either 100% stalled or 100% normal running. This paper amends the abovementioned shortcomings by proposing a simple and effective performance-based RAC model. The proposed model utilizes a simple explicit relation between the stalling voltage and its required time to stall the RAC, furthermore, it can stall a fraction of RACs based on the voltage dip characteristics. The experimental results support the proposed model and computer simulations employing the IEEE 118-bus test system and Iran's electricity grid reveal the effectiveness of the proposed model.
The Spatiotemporal Dynamics and Socioeconomic Factors of SO2 Emissions in China: A Dynamic Spatial Econometric Design

With the great strides of China’s economic development, air pollution has become the norm that is a cause of broad adverse influence in society. The spatiotemporal patterns of sulfur dioxide (SO2) emissions are a prerequisite and an inherent characteristic for SO2 emissions to peak in China. By exploratory spatial data analysis (ESDA) and econometric approaches, this study explores the spatiotemporal characteristics of SO2 emissions and reveals how the socioeconomic determinants influence the emissions in China’s 30 provinces from 1995 to 2015. The study first identifies the overall space- and time-trend of regional SO2 emissions and then visualizes the spatiotemporal nexus between SO2 emissions and socioeconomic determinants through the ESDA method. The determinants’ impacts on the space–time variation of emissions are also confirmed and quantified through the dynamic spatial panel data model that controls for both spatial and temporal dependence, thus enabling the analysis to distinguish between the determinants’ long- and short-term spatial effects and leading to richer and novel empirical findings. The study emphasizes close spatiotemporal relationships between SO2 emissions and the socioeconomic determinants. China’s SO2 emissions variation is the multifaceted result of urbanization, foreign direct investment, industrial structure change, technological progress, and population in the short run, and it is highlighted that, in the long run, the emissions are profoundly affected by industrial structure and technology.
Remote sensing of UV-absorbing aerosols using space-borne spectrometers

The Absorbing Aerosol Index (AAI) was investigated and used to analyse GOME data and compare it to TOMS data. The physical interpretation of the AAI was studied with an extensive theoretical sensitivity analysis. The dependence of the method on a number of atmospheric, surface and aerosol properties was studied using a numerical radiative transfer model. It was found to be sensitive (producing positive values) to absorbing aerosols with wavelength dependent refractive indices and to elevated absorbing aerosols, both with wavelength dependent and wavelength independent (gray) refractive indices. It was found to be insensitive to clouds, while small size scattering aerosols yield negative values. AAIs were calculated from GOME data for the period July 1995 to December 2000 and compared to TOMS AAI data. In a part of this period, July 1995 to October 1996, no TOMS observations were available and the GOME data can be used to supplement the TOMS data set. The GOME AAI corresponds very well with known absorbing aerosol events. It suffers from lower spatial resolution and less frequent temporal coverage as compared to TOMS, but is useful as an independent data source of global aerosol measurements. M. de Graaf, P. Stammes, O. Torres and R.B.A. Koelemeijer (2005), JGR 110 (D01201), : 10.1029/2004JD005178 28 GOME Absorbing Aerosol Index
Electrocardiographic observations in patients with sickle-cell disease.

Electrocardiograms were obtained in 30 homozygous HbS Nigerians aged between 7-24. Analysis of the electrocardiograms showed the patients had a statistically significant preponderance of electro-cardiographic feature of T wave inversion in more than one right ventricular leads compared with controls x 2 =9.610 P<0.01
Energy-and-pitch-angle-resolved escaping beam ion measurements by Faraday-cup-based fast-ion loss detector in Wendelstein 7-X

With the objective of understanding the energetic-particle loss mechanism in three-dimensional plasmas, a Faraday-cup-based fast-ion loss detector (FILD) was developed and installed in OP1.2b in Wendelstein 7-X (W7-X) as a collaboration between the National Institute for Fusion Science and Max-Planck-Institute for Plasma Physics. The FILD, which consists of double apertures and thin aluminum foils, was based on a magnetic spectrometer using the magnetic field of the fusion device. The double aperture limits the thermal ion, but allows the energetic ion to enter the FILD box. The thin aluminum foils serve as the ion collector. Orbit-following calculations were performed in order to find a suitable position for the FILD. The results indicated that barely co- and counter-going transit ions reached the FILD position mounted on the multi-purpose manipulator installed on W7-X. Moreover, because the injection angle of neutral beams injector installed on W7-X was relatively perpendicular, the target range of pitch angle was set to from 91 degrees to 150 degrees. An energy-and-pitch-angle map was created using a grid calculation code in order to decide on the position/size of aperture and aluminum foil. The grid calculation code indicates the position where the energetic ion would strike on the aluminum foil. Here, the map was used as the basis for designing an aluminum foil pattern with two energies and four pitch angle ranges. Also, note that the lower energy range was designed so that it accommodates a neutral beam injection energy of 55 kV. Measurements of beam ion losses were performed in neutral beam (NB) blip experiments, where concurrent increases and decreases of barely co-going transit beam ion losses due to NB injections were observed. Furthermore, this study validated that the FILD installed on a midplane manipulator probe is capable of probing a range of radii spanning 1.0–1.5 cm, over which the beam ion loss current would vary significantly.
A general framework for photoionization calculations applied to nonthermal gas discharges in air

A general framework for photoionization rate calculations in a constant pressure gaseous medium is introduced. The formulation includes the number of photons emitted per unit volume per unit time per unit wavelength due to a radiating source, photobasorption cross sections and density of species comprising the medium, and the photoionization probability (i.e. photoionization yield) of the species being photoionized. We derive a standard integral representation of the photoionization problem that may be readily converted to a set of Helmholtz differential equations for efficient calculation of the photoionization rate. The model is applied to the photoionization problem in air in which b 1 Π u , b ′ 1 Σ u + , c 3 1 Π u , o 3 1 Π u , c 4 ′ 1 Σ u + singlet states of N2 are excited due to collisions with electrons generated as a result of nonthermal discharges. Radiative decay from these states gives rise to respective band systems Birge-Hopfield I, Birge-Hopfield II, Worley-Jenkins, Worley, and Carroll-Yoshino, and to photons which are generally energetic enough to ionize O2. The excitation rates and contribution of each band system to photoionization of O2 in air are calculated for the first time. Using recently measured electron impact excitation cross sections of these states, and the recently measured extreme ultraviolet (XUV) spectra of N2, we quantify the emission from each singlet state. Absorption of emission is modeled using measured photoabsorption cross sections of N2 and O2. The photoionization rate of O2 upon absorption of a photon with a certain energy is calculated using experimental values for the photoionization yield of O2. Finally, we introduce a set of coefficients which define the differential representation of the problem of photoionization in air. The developed modeling framework allows accurate solution of photoionization problems in air for the broad range 10 − 2 < p O 2 R < 10 4 Torr cm, where p O 2 is the partial pressure of O2 in air in units of Torr ( p O 2 = 152 Torr at atmospheric pressure) and R in cm is a characteristic spatial dimension of the system of interest. The model performance is demonstrated using a set of artificial sources leading to photoionization over a representative range of p O 2 R values and a realistic problem of dynamics of a double-headed streamer in air that was used in previous photoionization literature. The validity of the modeling framework is demonstrated by comparisons with the photo-ion yield function in air, Ψ ( p O 2 R ) , derived from the classic photoionization model of Zheleznyak et al () and more recent experimental data on photoionization in air.
The impact of teaching topical structure analysis on EFL writing with special reference to undergraduate students in Libya

ii DEDICATION iv DECLARATION v ACKNOWLEDGEMENTS vi LIST OF ABBREVIATIONS vii LIST OF TABLES xiv Chapter 1 : Introduction 1 1.1 Background 1 1.2 Significance of the study 4 1.3 Scope of the study 7 1.4 Thesis organization 7 Chapter 2 : Approaches to Teaching ESL/EFL Writing 10 2.
Mapping the genes for complex canine autoimmune diseases

The aetiology of autoimmune disease is a complex interplay between genetics, environment and immunological regulation. Our understanding of the genetic aspects of autoimmunity has increased with recent findings from Genome Wide Association Studies (GWAS). There is now a movement towards meta-analyses of GWA studies in order to increase the number of genetic loci detected. There are also efforts to detect common genetic risk factors amongst groups of diseases that potentially share common aetiopathogenic pathways. Animal models have formed the basis of many genetic discoveries and the domestic dog presents a spontaneous model for many diseases, including autoimmunity. Through man? s efforts to create specific breeds, the dog has acquired a genomic architecture consisting of long haplotype blocks and extensive linkage disequilibrium. This means that a GWAS can be conducted in dog breeds with fewer samples and fewer markers than an equivalent study in humans, reducing costs, cohort collection times, and data handling/storage considerations. Successful canine GWA studies are now starting to be published. Building upon this success, the findings from GWA studies in three canine autoimmune diseases (across six different breeds), with equivalent human pathologies, are presented. Dogs with diabetes mellitus (similar to latent autoimmune diabetes of adulthood in man), lymphocytic thyroiditis (similar to Hashimoto? s thyroiditis), and anal furunculosis (similar to perianal Crohn? s disease) were compared to control dogs to identify genetic susceptibility loci underlying disease. Follow-up genotyping of the top hits from the GWAS analyses were conducted to replicate findings and to better characterise the diseases across a number of dog breeds. Typing of MHC class II genes, important in the immune response, was also undertaken in canine diabetes mellitus and canine lymphocytic thyroiditis. In anal furunculosis, high-throughput, next-generation sequencing was utilised to identify novel mutations and fine-map associations at discovered loci. Several genes were identified in all of these canine autoimmune diseases, many with good candidate function. Some of these genes indicated common genetic susceptibility loci and pathways between canine autoimmune diseases. Breed-specific genetic effects underlying canine diabetes mellitus and canine lymphocytic thyroiditis were identified, which has implications for disease diagnosis and clinical management. Novel loci for investigation in the corresponding human disease studies have been identified and future work will begin to genetically link the conditions in dog and man.
Maize root and shoot litter quality controls short-term CO2 and N2O emissions and bacterial community structure of arable soil

Abstract. Chemical composition of root and shoot litter controls decomposition and, subsequently, C availability for biological nitrogen transformation processes in soils. While aboveground plant residues have been proven to increase N2O emissions, studies on root litter effects are scarce. This study aimed (1) to evaluate how fresh maize root litter affects N2O emissions compared to fresh maize shoot litter, (2) to assess whether N2O emissions are related to the interaction of C and N mineralization from soil and litter, and (3) to analyze changes in soil microbial community structures related to litter input and N2O emissions. To obtain root and shoot litter, maize plants (Zea mays L.) were cultivated with two N fertilizer levels in a greenhouse and harvested. A two-factorial 22 d laboratory incubation experiment was set up with soil from both N levels (N1, N2) and three litter addition treatments (control, root, root + shoot). We measured CO2 and N2O fluxes, analyzed soil mineral N and water-extractable organic C (WEOC) concentrations, and determined quality parameters of maize litter. Bacterial community structures were analyzed using 16S rRNA gene sequencing. Maize litter quality controlled NO3- and WEOC availability and decomposition-related CO2 emissions. Emissions induced by maize root litter remained low, while high bioavailability of maize shoot litter strongly increased CO2 and N2O emissions when both root and shoot litter were added. We identified a strong positive correlation between cumulative CO2 and N2O emissions, supporting our hypothesis that litter quality affects denitrification by creating plant-litter-associated anaerobic microsites. The interdependency of C and N availability was validated by analyses of regression. Moreover, there was a strong positive interaction between soil NO3- and WEOC concentration resulting in much higher N2O emissions, when both NO3- and WEOC were available. A significant correlation was observed between total CO2 and N2O emissions, the soil bacterial community composition, and the litter level, showing a clear separation of root + shoot samples of all remaining samples. Bacterial diversity decreased with higher N level and higher input of easily available C. Altogether, changes in bacterial community structure reflected degradability of maize litter with easily degradable C from maize shoot litter favoring fast-growing C-cycling and N-reducing bacteria of the phyla Actinobacteria, Chloroflexi, Firmicutes, and Proteobacteria. In conclusion, litter quality is a major driver of N2O and CO2 emissions from crop residues, especially when soil mineral N is limited.
Attitude formation and change toward people with disabilities

This study investigates attitude formation and change toward people with disabilities in a sample of Australian undergraduate nursing (N=90) and teaching students (N=90). As part of their university training both student groups undertake a mandatory disability course component and, as professionals, are influential in the delivery of quality services to people with disabilities. Stage I of the study included three phases of data collection, corresponding to the three years of students' university study. This stage examined major variables predicted to account for changes in students' attitudes, outcomes of the mandatory disability unit on students, effects of different forms of contact with people with disabilities on resultant attitudes and outcomes of the mandatory disability unit on students' future career and post-graduate study choices. Stage II of the study was an experimental intervention, incorporating three experimental groups and one control, testing the most effective methodology for predicting attitude change toward people with disabilities. Pre-and post-test data is collected, analysed and reported. Confirmation was provided of hypotheses predicting positive attitude change in teaching students across the three years of their university training. This demonstrates the success of mandatory special education units in leading to positive attitudes. Nursing students reported raised levels of discomfort in social interaction and more negative attitudes after completion of the mandatory unit, challenging the assumption that mandatory study leads to positive
Investigating the diet selection and genetic variation of small ruminants in a dryland pastoral system in South Africa

Genetic diversity of small ruminants is essential for livestock farming systems especially in vulnerable regions such as drylands where environments are constantly changing. It is with desire to preserve genetic diversity of small ruminants in drylands as they possess traits that give rise to adaptations to changing climatic and environmental conditions. Farming with small ruminants such as sheep and goat is the main land-use in drylands in Africa. This study was conducted to explore the genetic diversity and differences within small ruminants found in the dryland pastoral system of Steinkopf in South Africa. Mitochondrial DNA analyses of Swakara sheep, cross-bred sheep and Boer goats were studied to determine the genetic differences and phylogenetic relationships between these small ruminants. Results showed that there is high genetic diversity within the cross-bred sheep and Boer goat herds but low genetic diversity within the Swakara population. Understanding the genetic diversity of small ruminants in the Steinkopf pastoral system is important as the climate and environment are constantly changing. Thus, it is essential to put in place management strategies that would ensure the survival of small-scale farming in this region despite the harsh effects of climate change in present and future times.
Increasing soil carbon stocks in eight typical forests in China

Abstract. Forest soils represent a major stock of organic carbon (C) in the terrestrial biosphere, but the dynamics of soil organic carbon (SOC) stock are poorly quantified, especially based on direct field measurements. In this study, we investigated the 20-year changes in the SOC stocks at eight sites from southern to northern China. The averaged SOC stocks increased from 125.2 ± 85.2 Mg C ha−1 in the 1990s to 133.6 ± 83.1 Mg C ha−1 in the 2010s across the forest sites, with a mean increase of 127–908 kg C ha−1 yr−1. This SOC accumulation was resulted primarily from both leaf litter and fallen logs and equivalent to 3.6–16.3 % of aboveground net primary production. Our findings provide strong evidence that China's forest soils have been acting as significant carbon sinks although their strength varies with forests in different climates.
Variation and serial correlation of modulus of elasticity between and within European oak boards (Quercus robur and Q. petraea)

Abstract This research aimed at describing the tensile modulus of elasticity (MOE), density and knot variability between and within oak (Quercus robur, Q. petraea) boards, which is essential for the stochastic modeling of wooden composites, such as glulam. Longitudinal deformations for 100-mm long cells were measured. The local density variation along boards revealed a very low mean coefficient of variation (COV) of 3%. The global MOE was precisely predicted from local (cell) MOEs, which span from 2.6 to 22 GPa. The mean COV of local MOE along board length was 12%, with extremes of 3% and 28%. The cell-related relationships of MOE with either density or knot area ratio showed low R-values of 0.4 and 0.3, respectively. A multivariate linear regression with both variables increased the MOE prediction to R = 0.6, which is below the literature results for beech and spruce wood. A serial correlation analysis of the local MOE was performed for board segments quasi-free of knots and for all cells, investigating different normalization approaches. Applying no MOE normalization delivered too high correlations due to pronounced inter-board MOE variations. A normalization based on an averaged maximum MOE per board delivered reasonable serial correlation results for the first four lags of the MOE knot-free variation (0.61; 0.38; 0.19 and 0.08). Considering also the knot-affected cells reduced the serial correlation roughly by a factor of 2.