Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of compost rates at different depths on some chemical properties and productivity of soils

Two field experiments were conducted on clay loam soil during the two successive seasons, summer season 2013 using maize plants and winter season 2013/2014 using wheat plants at El-Gemmeiza Agricultural Research Station, El-Gharbia Governorate to evaluate the effect and residual effects of compost rates placed in 20 and 40 cm depths, arranged in parallel orientation with respect to one another and spaced at 3 m apart or placed on the surface soil layer as well as the control on improving some soil chemical properties and availability of some nutrients either macro or micro, and the productivity of yield and yield components of maize and wheat plants. Furthermore, economical analysis was done by calculating the net income and investment ratios to determine the economical treatment. The experiments were conducted in a split plot in a randomized complete block design (RCBD) with three replicates. Results can be summarized as follows:(1)All treatments slightly decreased the soil reaction (pH). Furthermore, all treatments caused progressive increases in soil salinity (EC) and total soluble salts (TSS) for the two soil depths (0-20 and 20-40cm) in the two growing seasons. Also, soluble cations and anions slightly increased with all treatments. While, SAR values were decreased compared with the control for the two soil depths in the two growing seasons. (2)Generally the application depth and the addition rates of compost clearly enhanced the nutrient statues of the investigated soil. ( 3)Organic carbon (O.C, %) and C/N ratio were slightly increased in surface and subsurface soil layers as a result of the application depth and the addition rates of compost. (4)All treatments led to markedly increases in the available macronutrients (N, P and K) and available micronutrients (Fe, Zn, Mn and Cu) of the soil at the two soil depths in the two growing seasons either with mole depth or compost rates. ( 5)The yield and yield components of maize and wheat positively responded to all treatments compared with the control. The highest values of yield and its components for maize and wheat plants were obtained by the addition of 10 ton compost fed in 40 cm mole depth. The highest grain yield of maize plants increased to 68.46 %, also, the highest grain and straw yields of wheat plants increased to 70.27 and 91.67 %, over the control, respectively. (6)According to the economical analysis, the application of 10 ton compost fedin 40 cm mole depth was the best treatment compared with the other treatments, since it gave the highest net income (12346.38 L.E fed.). While, the lowest values were always incorporated with control (10 cm surface depth without any applications of compost). (7)Therefore, it is more useful to use those treatments (compost rates at different depths) to get a markedly improve in both chemical properties and nutrients which reflect on higher yield incorporated with high net income, as well as to substitute a part of chemical fertilizers by using compost to minimize the pollution resulted from the intensive use of it.
Evaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data

Abstract Normalized difference vegetation index (NDVI)-based models have been developed to derive wheat grain yields with multispectral images. In this regard, field measurements and Landsat 8 Operational Land Imager (OLI) data were used for two growing seasons to determine the relationships between NDVI and yields. The number of six statistic parameters were calculated from NDVI values to find the best agreement with actual yield data. A comparison of the results showed that sum-NDVI better matched field measurements. To compare the results of NDVI with other vegetation indices, we applied four other vegetation indices. Results indicated that estimation of wheat yields using sum-NDVI values was more accurate than estimation by sum of the four applied vegetation indices values. Also, the investigation of multi-temporal images showed that the critical time to estimate wheat yield using sum-NDVI values was the time that wheat grains were in the milky and maturity stages.
Evaluation of Some Synthetic Soil Conditioners and Nitrogen Rates on Nitrogen Use Efficiency by Maize - Wheat Crops System in Calcareous Soil

The use of synthetic soil conditioners such as polyvinyl alcohol (PVA), bitumen (Bit.) and polyacrylamide (PAC) can be considered as a specific management to improve the efficiency of the use of nitrogen fertilizers and some chemical properties of calcareous soils that are reflected in crop productivity. Two rates of synthetic soil conditioners (PAV, Bit. and PAC) and three rates of nitrogen fertilizer (50, 75 and 100% N of recommended dose) were included in this study to evaluate their effects on some chemical properties, nutritional status and yield components of both maize and wheat crops along with nitrogen use efficiency. Field experiments were conducted in calcareous soil at Nubaria Agriculture Research Station farm during two successive seasons, summer season cultivated with maize (Zea mays L., cv Giza 10) and winter season cultivated with wheat ( Triticum aestivum L., cv Giza 168). Results showed that the highest significant yield components of maize and wheat crops along with their total content of the indicated macronutrients were observed when applied high rate of polyvinyl alcohol (0.2 %) accompanied with high rate of nitrogen fertilizer (100% N of recommended dose) as compared to other tested treatments. On the contrary, application of high rate polyacrylamide combined with low rate of nitrogen fertilizer generally was inferior for yield components of both maize and wheat plants. Also, data revealed that the nitrogen use efficiency was the highest (65.0 and 42.4) for maize and wheat plant, respectively, receiving 50 % nitrogen fertilizer rate in presence of 0.2 % polyvinyl alcohol. However, applied high rate of polyvinyl alcohol accompanied with low rate of nitrogen fertilizer was superior decreased pH values of soil as compared to either control or other tested treatments. An opposite trend for EC values which were superior increased in presences of all nitrogen fertilizer rates. Also, CaCO3 values were lower when applied high rate of polyacrylamide in two seasons. The highest values of available nitrate and ammonium in soil were due to applied 0.2 % of polyvinyl alcohol combined with 75 % of nitrogen fertilizer rate compared to the other tested treatments.
Methane emissions from dairy heifers as affected by residual feed intake and breed : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Animal Science at Massey University, Manawatū, New Zealand

Figures 2.5, 2.6, 2.7, 2.8, 2.9, 3.1, 3.2 & 3.3 have been removed for copyright reasons, but may be accessed via their sources listed in the References. Chapter 4 has been published as an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/): Flay, H. E. , Kuhn-Sherlock, B. , Macdonald, K. A. , Camara, M. , Lopez-Villalobos, N. , Donaghy, D. J., & Roche, J. R. (2019). Hot topic: Selecting cattle for low residual feed intake did not affect daily methane production but increased methane yield. Journal of Dairy Science, 102(3), 2708–2713. https://doi.org/10.3168/jds.2018-15234
MedLab : A Distance Learning Medical Laboratory via a Tablet

Aim: To present a distance learning solution for medical laboratories. Material and Method: The recent developments in tablet computers and network technologies show ideas which can be useful for application applied in medical laboratories. Results: Here is suggested an important solution based on the recent tablet computer technology combined with mobile WiMAX 2 standard. Conclusions: The suggested idea can be easily used today and can be generally useful in the learning process and not only for medical laboratories.
Toward a Model of Motivated Vocabulary Learning: A Structural Equation Modeling Approach

This study presents a structural model that integrates vocabulary knowledge and motivation with six latent variables: the initial appraisal of vocabulary learning experience, self-regulating capacity of vocabulary learning, strategic vocabulary learning involvement, mastery of vocabulary learning tactics, vocabulary knowledge, and postappraisal of the effectiveness of vocabulary learning tactics. The model suggests that motivated vocabulary learning follows a developmental mode and functions as a cyclic process. The model supports the importance of motivation in the vocabulary learning process and the division of strategic behavior into two components: one frequency-based and metacognitive in nature and the other focusing on the mastery of individual strategies (i.e., how well they are used).
Buoyant forces promote tidewater glacier iceberg calving through large basal stress concentrations

Abstract. Iceberg calving parameterisations currently implemented in ice sheet models do not reproduce the full observed range of calving behaviours. For example, though buoyant forces at the ice front are known to trigger full-depth calving events on major Greenland outlet glaciers, a multi-stage iceberg calving event at Jakobshavn Isbræ is unexplained by existing models. To explain this and similar events, we propose a notch-triggered rotation mechanism, whereby a relatively small subaerial calving event triggers a larger full-depth calving event due to the abrupt increase in buoyant load and the associated stresses generated at the ice–bed interface. We investigate the notch-triggered rotation mechanism by applying a geometric perturbation to the subaerial section of the calving front in a diagnostic flow-line model of an idealised glacier snout, using the full-Stokes, finite element method code Elmer/Ice. Different sliding laws and water pressure boundary conditions are applied at the ice–bed interface. Water pressure has a big influence on the likelihood of calving, and stress concentrations large enough to open crevasses were generated in basal ice. Significantly, the location of stress concentrations produced calving events of approximately the size observed, providing support for future application of the notch-triggered rotation mechanism in ice-sheet models.
Effects of Negative Media on Evangelical Christians' Attitudes Toward Evangelism

This study examined how negative media influenced Evangelical Christians and their attitude toward evangelism practices. Using self-questionnaires, participants identified their level of in-group identification and type of internalized motivation for engaging in religious practices. After viewing a negative media clip about the professional football player, Tim Tebow, and his public expression of faith, 412 Evangelical Christians rated their fear of negative evaluation about engaging in evangelism. A control group of 31 participants completed questionnaires but received no media exposure. Consistent with previous research, the current study found that media exposure activated internalized social norms and feelings of oughtness, which were shown to be statistically significant predictors of anxiety as measured by BFNE-II scores. Internalization types were not found to be significant predictors for control group scores. Although 82% of Evangelical Christians highly identified with their in-group and 72% endorsed voluntary participation in evangelism practices, 59% of all participants registered clinically significant anxiety about evangelism regardless of exposure to negative media. Evangelism anxiety appeared be influenced by a sense of moral duty (Johnston, 2003), feelings of oughtness (Lindenberg et al., 2011), the risk of interpersonal rejection (Ingram, 1989), and fear of prejudicial treatment (Bobkowski & Kalyanaraman, 2010). Results indicated exposure to negative media activated obligatory expectations for conformity with evangelism practices. The electronic version of the dissertation is accessible at the Ohiolink ETD center http://www.ohiolink. edu/etd.
The Tectonic Evolution of Interior Oman

The evolution of Oman’s onshore sedimentary basins from the Late Precambrian to the Present is reflected by six tectono-stratigraphic units. Unit I, the Precambrian basement, represents continental accretion. Units II and III, Infracambrian to Ordovician, may reflect two periods of rifting, possibly related to Najd movements in western Saudi Arabia. The northeast-southwest trending salt basins formed during this time interval. A classical “steer’s head” basin geometry is developed in North Oman, whereas a less complete rift-sag sequence is preserved in South Oman. Of the entire time-span from Late Silurian to Mid-Carboniferous, only little Devonian (Emsian) sediment is preserved. Unit IV, Late Carboniferous to Mid-Cretaceous, reflects the break-up of Gondwana and the creation of the northeastern and southeastern passive margins of the Arabian Plate. Unit V documents intra-plate deformation related to Late Cretaceous continent-ocean obduction in the north and transpressional movements of the Indian Plate in the east. Unit VI, spanning the Tertiary, represents a return to quiet conditions followed by continent-continent collision in the north. Following Late Eocene uplift, the Gulf of Aden rift developed in the south in the early Oligocene, with sea-floor spreading from the Late Miocene onwards. Salt flow and dissolution, both playing a major role in the configuration of most intra- and post-salt hydrocarbon traps in Oman, are episodic and can be related to tectonic events.
Prediction of multi-inputs bubble column reactor using a novel hybrid model of computational fluid dynamics and machine learning

ABSTRACT The combination of machine learning and numerical methods has recently become popular in the prediction of macroscopic and microscopic hydrodynamics parameters of bubble column reactors. Such numerical combination can develop a smart multiphase bubble column reactor with the ability of low-cost computational time when considering the big data. However, the accuracy of such models should be improved by optimizing the data parameters. This paper uses an adaptive-network-based fuzzy inference system (ANFIS) to train four big data inputs with a novel integration of computational fluid dynamics (CFD) model of gas. The results show that the increasing number of input variables improves the intelligence of the ANFIS method up to , and the number of rules during the learning process has a significant effect on the accuracy of this type of modeling. Furthermore, the proper selection of model’s parameters results in higher accuracy in the prediction of the flow characteristics in the column structure.
Turbulence Model Selection for Heavy Gases Dispersion Modeling in
 Topographically Complex Area

The dispersion of hazardous gas in the environment presents dangerous risks for people living close to chemical plants or storages. Since heavy gases tend to stay at lower levels and disperse at a slower pace in the atmosphere, they are potentially more dangerous. In this paper, various mathematical models for turbulence (including k-ε, RNG k-ε, EARSM, LES, DES) and their associated parameters have been assessed, compared and validated against the experimental data in various scenarios to find the most suitable one for atmospheric dispersion of dense-gases. This topic has been investigated and validated by a computational fluid dynamics (CFD) simulation of the Kit-Fox experiment. The precision of the CAD models, practicality, computational resource requirements, and some other factors have been considered and addressed in this paper to achieve a comprehensive solution for atmospheric dispersion. The results here suggest that the proper selection of the turbulence model and the turbulent Schmidt number is crucial. Our results indicate that the most promising combination in the case of atmospheric dense-gas dispersion is the RNG k-ε model with the Schmidt number of 0.4, considering the demand for accuracy and computational resource.
Classification of 2 and 3 dimensional MDS codes for 4<=q<=32. (Working paper of the Laboratory of Operations Research and Decision Systems. (LORDS) WP04-4)

The number of (a) non-equivalent 2 and 3 dimensional MDS codes, (b) non-equivalent 3 dimensional complete MDS codes, (c) 3 dimensional MDS codes that can be described by classical arcs in PG(2, q), (d) arcs in regular hyperovals, and (e) 2 × n and 3 × n superregular matrices over GF(q) are established for q ≤ 19 and for a number of cases when 23 ≤ q ≤ 32. The equivalence classes over both PGL(k, q) and PΓL(k, q) are considered during the computations. Though, most of the results are reached by the help of a computer, also some general theoretical relations are formulated. A computational result of the paper is that there is no complete n-arc in PG(2, 31) for 23 ≤ n ≤ 30 and, consequently, the Main Conjecture for MDS Codes is true for arcs in up to 12 dimensional finite projective spaces of order 31, i.e., for MDS codes of up to 13 dimensions over GF(31).
Controlling sprinkler irrigation runoff, erosion, and phosphorus loss with straw and polyacrylamide

Controlling runoff and soil erosion are important for maintaining soil productivity and reducing off-site impairment due to sediment and nutrient enrichment. Previous research has shown that crop residue and polyacrylamide (PAM) can reduce runoff and soil erosion. We compared the combined effects of surface residue and PAM on runoff, soil loss, and phosphorus loss from sprinkler irrigated soil in the laboratory. We hypothesized that surface residue would enhance the effectiveness of sprinkler-applied PAM by allowing PAM to stabilize the soil surface with less disturbance by water drops. Steel boxes (1.5 m long, l.2 m wide, and 0.2 m deep) were filled with Roza loam (fine, smectitic, mesic xerertic Haplocambids) and irrigated at 80 mm h –1 for 15 min. Wheat straw was applied for two separate tests (70% and 30% straw cover). The PAM was applied at 0, 2 or 4 kg ha –1 during the first irrigation, followed by two water-only irrigations. Applying PAM to straw-covered soil controlled runoff, erosion, and phosphorus losses equally or better than using either PAM or straw alone. The 70% straw cover reduced cumulative runoff for the three irrigations 75 to 80% compared to 30 to 50% reduction with PAM alone. Polyacrylamide alone or 30% surface cover alone produced similar results, both reducing cumulative runoff 10 to 20% compared to untreated bare soil. Since runoff, erosion and phosphorus loss were reduced when PAM and surface residue were used individually and to a greater extent when used together, management choices should depend on overall costs and control needed to meet water quality and production goals.
Transferable Object-Based Framework Based on Deep Convolutional Neural Networks for Building Extraction

Automated building extraction from single, very-high-resolution (VHR) images is still one of the most challenging tasks for urban planning, estimating population, understanding urban dynamics, and many other applications. The complexities of building objects have caused the images of buildings to be oversegmented into multiple segments in the object-based image analysis (OBIA) method. Selecting the appropriate segmentation scale parameter is a major challenge in OBIA that influences the discriminative features extraction, especially for building objects. Furthermore, transferability of OBIA method is another challenge. Presently, convolutional neural networks (CNNs) are a well-understood tool for images scene classification. However, scene classification based on CNNs is still difficult due to the scale variation of the objects in VHR images. To meet these challenges, we propose a novel object-based deep CNN (OCNN) framework for VHR images. The datasets used for testing were Vaihingen (Germany) aerial images and a Tunis Worldview-2 (WV2) satellite imagery. Experimental results prove that our framework is extensible to different types of the image with the same sensor or another sensor (for example WV2) with once-fine-tuning. In addition, our framework extracts the different types of building with respect to size, color, material, spectral similarity to roads, and complex backgrounds. Quantitative evaluation at the object level demonstrated that the proposed framework could yield promising results (average precision 0.88, recall 0.92, quality 0.82, F-score 0.90, overall accuracy 0.95, and Kappa coefficient 0.90). Comparative experimental results indicate that our proposed OCNN significantly outperforms the traditional method for building extraction.
Conformal Field Theory and the Alpha Space Transform

This thesis can be split into two parts. In the first, we expound the alpha space formalism [1] and extend it beyond two dimensions. By performing a Sturm-Liouville analysis of the conformal quadratic Casimir differential equation, we define an invertible integral transform which maps functions on the Lorentzian square to alpha space. We explain how poles correspond to conformal blocks and provide numerous examples of interesting densities. After lifting the crossing equation to alpha space, we present a new representation of the accompanying kernel in terms of analytic Wilson functions. We also offer some comments on Regge physics and analyticity. In the second, we investigate the perturbative renormalisation of deformed conformal field theories from the Hamiltonian perspective. We discuss the relation with conformal perturbation theory, to which we provide an explicit match up to third order in the coupling, and show how second-order anomalous dimensions in the Wilson-Fisher fixed points are straightforwardly computed in the Hamiltonian framework. We then focus on the cut-off employed in the truncated conformal space approach of Yurov and Zamolodchikov [2]. We discuss the appearance of non-covariant and non-local counterterms to second order in the cut-off, explicitly in φ4 theory, and find a smooth cut-off to tame subleading oscillations.
Potent Heterogeneous Catalyst for Low Temperature Selective Oxidation of Cyclohexanol by Molecular Oxygen

Platinum supported on zirconium dioxide catalyst was prepared by standard method and characterized by SEM, EDX, XRD, BET surface area and pore size analyzer, and FT-IR. The catalyst was screened for its catalytic activity in a model reaction, selective oxidation of cyclohexanol. The only one major product, cyclohexanone 31%, with 99.8% selectivity was obtained. Experimental data was analyzed through different kinetic models and we deduced that the reaction follows Langmuir-Hinshelwood mechanism. The apparent activation energy for the model reaction was calculated as 45 kJ/mole. The catalyst was regenerated several times with same efficiency.
Metamagnetism emergence and spectroscopic elucidation of SmFeO3 nanoceramics

Temperature- and field-dependence of magnetization measurements on SmFeO3 nanoceramics have been carried out, and a first order type metamagnetic phase transition has been observed below 280 K. The Arrott plot on M(H) measurements confirms the emergence of such a first order transition, this could be argued by the creation of a ferromagnetic cluster between the antiferromagnetic Sm3+–O–Fe3+ and Fe3+–O–Fe3+ chains by Sm3+ ions around the respective transition. Additionally, a quasi-paramagnetic ordering of Sm3+ spins is observed below 20 K due to canted moment from Sm3+–O–Sm3+. Electron paramagnetic resonance and Raman measurements at various temperatures exhibit an analogue to the instantaneous first order metamagnetic transition, confirming the predominance of Sm3+–O–Fe3+ and Fe3+–O–Fe3+ interactions above and below 273 K, respectively. The present study brings an important aspect of the presence of the magnetic property in SmFeO3 pertaining to active and non-active interaction of Sm–O–Fe at the nanoscale regime.