Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of rainfall variation, fire, vegetation and habitat physiognomy on a northern Cape animal community

Animal census, vegetation and abiotic physiognomy data collected at an estate in the Northern Cape Province, South Africa, are analysed using uni- and multi-variate statistics to identify major animal habitats, descriptionbe broad patterns of distribution, abundance and diversity for the fauna, and explain these patterns in the light of possible effects of rainfall variation, fire, vegetation and abiotic physiognomy. Seven major animal associations characterized these distributional patterns, and rainfall variation within a relatively wet year seemed to have little effect on them. During the first half of the next year with a lower rainfall a mesic vlei assosiation was no longer evident; there was also a marked decrease in the number of springbok Antidorcas marsupialis. Other than these changes, broad patterns seemed not to be affected. During the latter half of this same year and immediately after a dry season burn and subsequent period of low rainfall, patterns of animal distribution apparent during pre-fire censusing were disrupted and animal diversity, abundance and dispersion were significantly depressed. The biotic and abiotic factors which influenced the above mentioned patterns are discussed.
Response of Sweet Pepper to The Application of Mineral Fertilizers Mixed with Bio-Fertilizers

Two greenhouse experiments were conducted at the experimental farm of the Faculty of Agriculture, Tanta University, Tanta, Egypt, during 2013/2014 and 2014/2015 seasons. The aim of this research is to study the effect of different levels of mineral fertilizers )50, 75 and 100% of recommended dose ‘RD’) with some bio-fertilizers, i.e. Easterna biofert (commercial bio-fertilizer) and a mixture of Rhizobacterin, Phosphorein and Potassiumage on the growth, yield and fruit quality of sweet pepper plants (Capsicum annuum, L. cv. Gideon F1 hybrid). The experiment was designed in a completely randomized blocks (CRB) with four replicates. Results indicated that the maximum vegetative growth parameters, yield, fruit quality, and chemical composition of the plant leaves and fruits were recorded a result of the following treatments in descending order; application of 100% of RD of mineral fertilizer; 75% RD of mineral fertilizer mixed with phosphorein, potassiumage and rhizobacterin; 75% RD of mineral fertilizer combined with Easterna biofert; however there were no significant differences among these treatments. Application of 50% RD of mineral fertilizer with the bio fertilizers mixture, or with easterna biofert only was significantly reduced those parameters. It could be concluded that fertilizer mix of mineral fertilizes at 75 % RD combined with phosphorein, potassiumage and rhizobacterin, or with easterna biofert only can improve the productivity and fruit characteristics of sweet pepper under greenhouse conditions. In addition to that, mixing mineral fertilizers with biofertilizers reduce the cost of chemical fertilizer, nitrate accumulation in the edible portion that affect human health, and environmental pollution.
Application of Phase Decomposition to the Analysis of Random Time Series From Wave Basin Tests

Many ocean engineering problems involve bound harmonics which are slaved to some underlying assumed close to linear time series. When analyzing signals we often want to remove the bound harmonics so as to “linearise” the data or to extract individual bound harmonic components so that they may be studied. For even moderately broadbanded systems filtering in the frequency domain is not sufficient to separate components as they overlap in frequency. One way to overcome this difficulty is to use input signals with the same linear envelope but with different phases and then use simple addition and subtraction of the resulting signals to extract different harmonics. This approach has been established for the analysis of wave groups. In this paper we examine whether this approach can be used on random time series as well. We analyse random wave time series of wave elevation from the towing tank in Shanghai Jiao Tong University and force measurements on a cylinder taken in the Kelvin tank at the University of Strathclyde.
Sunflower and Livelihood Outcomes among Households of Smallholder Farmers in Iramba District, Tanzania

1 Sunflower production is an important economic activity which is potential for improving livelihood outcomes among smallholder farmers’ households. However, despite such potentials, studies still debate on whether livelihood outcomes among smallholder farmers can be attained through sunflower cultivation or otherwise. This paper presents analysis of the livelihood outcome levels among smallholder farmers before and after engaging in sunflower cultivation. Also, it compared the livelihood outcome levels between sunflower and non-sunflower smallholder farmers. The study adopted a cross-sectional research design whereby household survey, focus group discussion and key informants interviews were used to collect data from 368 respondents. Qualitative data were transcribed, categorised, coded, and grouped into themes and analysed using constant comparison technique. Quantitative data were analysed by using descriptive statistics while difference in difference estimation was run to compare livelihood outcomes. Findings show that households of sunflower smallholder farmers’ had higher levels of livelihood outcomes and they were significantly different unlike before sunflower cultivation. The livelihood outcomes between sunflower and non-sunflower smallholder farmers’ households were significantly different (t = 12.51; p =0.000). The significant differences were evidenced by the number of household assets and access to financial services. Thus, sunflower cultivation stands a better chance for improving livelihood outcomes among smallholder farmers unlike other economic activities in the study area. Since findings show that some of the households had low level of livelihood outcomes it is recommended to smallholder farmers that they should consider building their livelihood capabilities through collective efforts as they are constrained by land size for cultivation. This can be done through forming farmers groups whereby they can join efforts to access microfinance loans and acquire small scale processing machines. This would enable them to increase household incomes by selling sunflower oil as well as seed cakes compared to selling few quantities of raw sunflower seeds individually. This paper should be cited as follows: Mchopa, A.D. and Jeckoniah, J.N. , ​(2018): Sunflower and Livelihood Outcomes among Households of Smallholder Farmers in Iramba District, Tanzania, in Kinyashi, G.F. , Mwang’onda, E. , Mandala, C.G. , Hauli, E. , and Mdendemi, T.R. K (eds.), Conference Proceedings for an International Conference on Planning and Development under the theme Towards Industrialisation in the Global South: Making Rural Regions Inclusive, held at the Institute of Rural Development Planning-Dodoma June 28-30, 2018;pp. ________________________________________________________________________________________ Conference Proceedings for International Conference on Planning and Development held at IRDP under the theme Towards industrialization in the Global South: Making Rural Regions Inclusive on June 28-30​th​ 2018 © IRDP, 2018 ISBN 978-9976-9974-0-8
Meteorological drought in the Miño-Limia-Sil hydrographic demarcation: The role of atmospheric drivers

Abstract. Drought is one of the main natural hazards because of its environmental, economic, and social impacts. Therefore, its study, monitoring and prediction for small regions, countries, or whole continents are challenging. In this work, the meteorological droughts affecting the Miño-Limia-Sil Hydrographic Demarcation (MLSHD) in the northwestern Iberian Peninsula during the period of 1980–2017 were identified. For this purpose, and to assess the combined effects of temperature and precipitation on drought conditions, the Standardised Precipitation-Evapotranspiration Index (SPEI) was utilised. During the study period there was no trend in the series of SPEI at the temporal scale of 1 mo (SPEI1); however, the number of drought episodes and their severity have been increasing historically, but this metric was not statistically significant. Particular emphasis was given to investigating atmospheric circulation as a driver of different drought conditions. To this aim, a daily weather type classification was utilised for the entire Iberian Peninsula. The results showed that atmospheric circulation from the southwest, west, and northwest were directly related to dry and wet conditions in the MLSHD during the entire climatological year. Contrastingly, weather types imposing atmospheric circulation from the northeast, east, and southeast and pure anticyclonic circulation were negatively correlated with the SPEI1. In this sense, the major teleconnection atmospheric patterns related to dry/wet conditions were the Arctic Oscillation, Scandinavian Pattern, and North Atlantic Oscillation. Dry and wet conditions according to the SPEI at shorter temporal scales were closely related to the soil moisture in the root zone, and also strongly influenced the streamflow of the Miño and Limia rivers, especially during the rainy season. However, a direct relationship between soil moisture and streamflow was also observed when dry/wet conditions accumulated for more than 1 y. We concluded that regional patterns of land-use change and moisture recycling are important to consider in explaining runoff change, integrating land and water management, and informing water governance.
Developing Elementary Students’ Digital Literacy Through Augmented Reality Creation: Insights From a Longitudinal Analysis of Questionnaires, Interviews, and Projects

This mixed-method case study investigated digital literacy (DL) development among 32 elementary-level students who created multimodal, contextual, and interactive augmented reality (AR) artifacts in a 20-week after-school program in Northern Taiwan. The instructional design combined situated and spiral learning experiences with AR, implemented through a blended learning environment. Data sources included pre- and post-program digital learning student surveys, student and teacher interviews, classroom observations, and AR artifact assessments. Results indicated statistically significant increases with moderate effect sizes in five areas of students’ DL practices: information management; collaboration; communication and sharing; creation; and evaluation and problem-solving. Students did not increase DL in one area: ethics and responsibility. The situated and spiral learning-by-design approach offered increasingly complex AR creation projects in which students developed and transferred their DL. The face-to-face and online learning settings offered multiple ways to collaborate and facilitated the development of students’ DL. The AR technology enabled students to develop DL through designing AR using three types of representation features: multimodal, interactive, and contextual. Practical and theoretical implications for adapting or enhancing this instructional design in future DL programs and for future research are discussed.
Mitigation of Salinity Stress in Maize by Silicon Nutrition

A survey was conducted in District Sargodha and Okara. The basic purpose of the survey was to estimate the soil and plant silicon (Si) concentration in the major maize growing areas of Punjab so a range of Na, K and Si concentration in maize plants were estimated to plan the future studies. Soil and plant samples were taken from adjacent areas of salt affected soils. Soils of both maize growing areas i-e District Sargodha and Okara have relatively high pH and EC. District Okara soil samples have higher EC values (1.04-3.78 dS m) relative to district Sargodha (0.722.54 dS m). There was significant positive correlation among soil and plant Si in both districts i-e Sargodha and Okara while significantly negative correlation (r= -0.36) found between soil Si and plant Na in District Sargodha samples. Similarly higher concentration of soil Si was found in district Okara samples (0.57 mg Kg) relative to district Sargodha (0.47 mg Kg) which leads to the higher plant Si concentration. District Okara plant samples have higher Na/K ratio relative to District Sargodha. Farmers generally do not grow maize grow maize on salt affected soils in these areas, so we cannot get any toxic effects of Na or deficiency (Si) in our samples.
Complementing knowledge about rare sulphates lonecreekite, NH4Fe3+(SO4)2·12 H2O and sabieite, NH4Fe3+(SO4)2: chemical composition, XRD and RAMAN spectroscopy (Libušín near Kladno, the Czech Republic)

Lonecreekite and sabieite, hydrous and anhydrous ferric ammonium sulphates, were identified among the products of a long-lasting subsurface fire in the waste heap of the Schoeller coal mine in Libušín near Kladno, Central Bohemia, Czech Republic. No monomineralic fractions could be extracted as the minerals occur in a fine-grained aggregate with minor ferroan boussingaultite, tschermigite, and traces of efremovite. Powder X-ray diffraction, electron-microprobe analysis and Raman spectroscopy were used to identify the mineral phases in the mixture. The empirical formula of lonecreekite is [(NH4)0.98K0. 02]∑1.00 (Fe0.70Al0.24Mg0.02)∑0.96 (SO4) 2.05·12 H2O, and the calculated unit-cell (Pa3̅ ) parameter a = 12.2442(2) Å, with a cell volume of V = 1835.68(9) Å3. The composition of sabieite corresponds to the formula [(NH4)0.98K0. 02]∑1.00 (Fe0.70Al0.24Mg0.02)∑0.96 (SO4) 2.05, and the calculated unit-cell parameters (P321) are a = 4.826(1) Å, c = 8.283(2) Å, V = 167.10(8) Å3, assuming that only the 1T polytype is present. Raman spectroscopy was conducted on both minerals, giving strong Raman bands at 1037 cm–1 (ν1), 1272 cm–1 (ν3), 462 cm–1 (ν2), 643 cm–1 (ν4), 313 (M–O vibration) for sabieite; and at 991 cm–1 (ν1), 1132 and 1104 cm–1 (ν3), 461 and 443 cm–1 (ν2), and 616 cm–1 (ν4) for lonecreekite (where ν1 and ν3 are stretching modes of the (SO4)-group and ν2 and ν4 are bending modes). The sabieite most probably formed by in situ decomposition of the siderite-bearing sedimentary rock at ~115–350 °C. The lonecreekite originated through hydration of the sabieite when the sample was stored at ambient temperature. Empirical formulae of associated ferroan boussingaultite and tschermigite are also given, respectively, as (NH4)2 (Mg0.62Fe0.36Mn0.06)∑1.04 (SO4)1.97·6 H2O and [(NH4)0.98K0. 02]∑1.00 (Al0.97Fe0.06)∑1.03 (SO4)2.97·12 H2O.
Partial resistance drilling to assess wood density in trees

Increment core analysis has dominated research for more than half a century and has been used as a standard method for assessing basic wood density in forests, for determining biomass of ecosystems, and for investigating climate history through dendrochronological analysis. Comprehensive wood density models have been developed for commercially important species that use outer wood cores and knowledge of internal wood density distribution to fairly accurately predict the density of major tree components. With the development of SilviScan and near infrared spectroscopy instruments, more wood and fiber properties can be obtained from a single increment core sample, allowing comprehensive wood quality evaluation of plantation trees for genetic improvement, forest management, and optimal wood utilization. However, for many users or in many applications, increment core sampling and subsequent laboratory analysis are time-consuming and expensive. A rapid field-type nondestructive method is needed in various research programs and forest operations. This report provides an in-depth review of the traditional increment coring method and the more recent electronic resistance drilling technique for assessing wood density of trees. This report also proposes a new concept of partial resistance drilling for more efficient and economical collection of wood density data in the forest.
An Integrated Method To Evaluate Formation Damage Resulting from Water and Alkali Sensitivity in Dongping Bedrock Reservoir

Dongping Field with low porosity and permeability, located in the Qaidam Basin, is the largest bedrock reservoir in China. Because of its high content of clay minerals and poor physical properties, the reservoir tends to suffer from formation damage caused by water or alkali sensitivity, which significantly affects production. Therefore, it is crucial to understand the formation-damage mechanisms for reservoir protection and efficient development. In this paper, we propose a new method that integrates pressure-transmission tests (PTTs) with a fixed-point scanning electron microscope (SEM) and nuclear magnetic resonance (NMR) to investigate mechanisms of formation damage. From the macroscopic perspective, PTT, a time-saving and accurate method of measuring permeability for tight rocks, is applied to evaluate the permeability-damage degree of core samples. From the microscopic perspective, the change of pore structure for a specific region and the variation of the fluid volume in the core sample before and after damage are obtained by fixed-point SEM and NMR experiments, respectively. In water-sensitivity damage experiments, the results of PTT show that the permeability-damage rate is approximately 60%, demonstrating that the damage degree of water sensitivity is moderate to severe. The results of the fixed-point SEM demonstrate that the pore sizes suffer from obvious reduction as a result of water-sensitivity damage. NMR experiments demonstrate that the main damage mechanisms vary, depending on the pore sizes. Small pores [0.1 milliseconds ≤ transverse relaxation time (T2) < 10 milliseconds] are damaged by swelling of mixed-layer illite/smectite, and the large pores (10 milliseconds ≤ T2 <100 milliseconds) suffer from the combined damage of swelling of smectite and migration of illite. Using a similar method, the alkali-sensitivity damage test demonstrates that there is no alkali-sensitivity damage in target reservoirs. This novel integrated method is an efficient means to investigate the formation-damage mechanisms for the Dongping bedrock reservoir from comprehensive perspectives. In addition, this method can be widely applied to evaluate formation damage for tight low-permeability reservoirs.
ENERGY AND EXERGY ANALYSIS OF A DOMESTIC REFRIGERATOR: APPROACHING A SUSTAINABLE REFRIGERATOR

In the perspective of reducing the household energy consumption, current research in conventional refrigeration is concentrating on introducing innovative designs and enhances the energy efficiency of the refrigeration system. This research work compares the performance of the domestic refrigerator by employing hotwall air cooled and box type shell and tube water-cooled condenser. The energy and exergy analysis methods help to localize exergy losses in the refrigerator. The investigation is carried out according to ISO 15502:2005. Experimental studies were conducted in the same refrigerator unit operating with a different condenser to determine the coefficient of performance, exergy efficiency, and exergy loss in all components of the domestic refrigerator. The experimental result shows that COP is increased by 18-20% and the exergy efficiency of the refrigerator with water cooled condenser unit is found to be higher by 6.89-9.13% than the one with a hot-wall air cooled condenser. The per day energy consumption of a refrigerator with a water-cooled condenser reduces by 17% in comparison with conventional refrigerator. The irreversibility of the refrigerator with the water-cooled condenser is reduced by 34 % than that of the conventional system under similar operating conditions. The total equivalent warming impact of refrigerator working with the water-cooled condenser is 16% lower than that the refrigerator with air cooled condenser. The utilization of water-cooled condenser in household refrigerators enhances energy efficiency.
The role of vocational training in reducing unemployment rate in the outlying states of United States of America

This paper analyses the contribution of vocational training in reducing the unemployment rate in Guam, the Commonwealth of Northern Mariana Islands (CNMI), American Samoa, and the US Virgin Islands. All of these areas are located in the Pacific Ocean near South East Asia, with the exception of the US Virgin Islands. The data in this study was pulled from the US Census data in 2000 and 2010. This was a quantitative study using a logistic regression method to predict the likelihood of unemployment rate changes between 2000-2010, with the dependent variable being the change of the unemployment rate between 2000-2010 and the independent variable being the percentage of people completing vocational training. The findings show that the percentage of people in the age groups of 16-44 and 45-64 who completed vocational training correlate to declining unemployment rates. This paper illuminates the role of vocational training programs in reducing the unemployment rate in US territories in the Pacific region and in the US Virgin Islands. These results encourage further research that examines training in the workplace through work integrated learning, with work policies widening access to quality vocational education and training programs.
Machine Learning Approaches to Develop Pedotransfer Functions for Tropical Sri Lankan Soils

Poor data availability on soil hydraulic properties in tropical regions hampers many studies, including crop and environmental modeling. The high cost and effort of measurement and the increasing demand for such data have driven researchers to search for alternative approaches. Pedotransfer functions (PTFs) are predictive functions used to estimate soil properties by easily measurable soil parameters. PTFs are popular in temperate regions, but few attempts have been made to develop PTFs in tropical regions. Regression approaches are widely used to develop PTFs worldwide, and recently a few attempts were made using machine learning methods. PTFs for tropical Sri Lankan soils have already been developed using classical multiple linear regression approaches. However, no attempts were made to use machine learning approaches. This study aimed to determine the applicability of machine learning algorithms in developing PTFs for tropical Sri Lankan soils. We tested three machine learning algorithms (artificial neural networks (ANN), k-nearest neighbor (KNN), and random forest (RF)) with three different input combination (sand, silt, and clay (SSC) percentages; SSC and bulk density (BD); SSC, BD, and organic carbon (OC)) to estimate volumetric water content (VWC) at −10 kPa, −33 kPa (representing field capacity (FC); however, most studies in Sri Lanka use −33 kPa as the FC) and −1500 kPa (representing the permanent wilting point (PWP)) of Sri Lankan soils. This analysis used the open-source data mining software in the Waikato Environment for Knowledge Analysis. Using a wrapper approach and best-first search method, we selected the most appropriate inputs to develop PTFs using different machine learning algorithms and input levels. We developed PTFs to estimate FC and PWP and compared them with the previously reported PTFs for tropical Sri Lankan soils. We found that RF was the best algorithm to develop PTFs for tropical Sri Lankan soils. We tried to further the development of PTFs by adding volumetric water content at −10 kPa as an input variable because it is quite an easily measurable parameter compared to the other targeted VWCs. With the addition of VWC at −10 kPa, all machine learning algorithms boosted the performance. However, RF was the best. We studied the functionality of finetuned PTFs and found that they can estimate the available water content of Sri Lankan soils as well as measurements-based calculations. We identified RF as a robust alternative to linear regression methods in developing PTFs to estimate field capacity and the permanent wilting point of tropical Sri Lankan soils. With those findings, we recommended that PTFs be developed using the RF algorithm in the related software to make up for the data gaps present in tropical regions.