Miracle-dz/UniFAR-FTUs huggingface dataset:
Conditional price volatility, speculation, and excessive speculation in commodity markets: sheep or shepherd behaviour?

Abstract The present study aims to investigate the dynamics of primary commodity spot prices and the role of speculation for the period 1995–2012. Using a linear and nonlinear Granger causality analysis, the relationship between speculation and GARCH conditional price volatility on the one side, and the linkage between excessive speculation and GARCH conditional price volatility on the other side, is carefully examined with the scope to establish whether volatility drives speculation or speculation drives price volatility, or whether there are no linkages between the two variables. The results show that excessive speculation leads conditional price volatility, and that bilateral relationships often exist between price volatility and speculation. In addition, the lead-lag relationships are not found for the entire sample period, but rather when small sub-periods are taken into account. It turns out, in fact, that excessive speculation has driven price volatility for maize, rice, soybeans, and wheat in particular time frames, but the relationships are not always overlapping for all considered commodities. Generally, the results under linear causality tests are in agreement with those obtained under nonlinear counterparts.
Supplementation levels for non-lactating cows grazing during the rainy season

Objetivou-se avaliar o efeito de niveis de suplementacao concentrada (1,5; 3,0; 4,5 e 6,0 kg dia-1) em vacas leiteiras mantidas em pasto de Panicum maximum Jacq. cv. Tanzânia no periodo das aguas, sobre o consumo e a digestibilidade dos nutrientes e parâmetros ruminais. Foram utilizadas quatro vacas mesticas Holandes x Zebu, nao lactantes, com peso corporal medio de 521,69±31,98 kg no inicio do experimento distribuidas aleatoriamente em delineamento em quadrado latino 4X4. Cada periodo teve duracao de 17 dias, sendo os 10 dias iniciais para adaptacao dos animais aos tratamentos e os sete dias restantes para coletas de dados. Nao houve efeito (P > 0,05) dos niveis de suplementacao sobre o consumo de materia seca total com reducao linear (P 0,05) dos tratamentos nos coeficientes de digestibilidade da materia seca, materia orgânica, proteina bruta e extrato etereo. Houve aumento linear (P 0,05) e tempo apos a suplementacao sobre o pH ruminal. A concentracao de nitrogenio amoniacal ruminal apresentou comportamento quadratico (P < 0,05) em relacao aos tempos apos a alimentacao, sendo estimado valor maximo de 17,61 mg dL-1 no tempo 3,87 horas apos a alimentacao. O aumento dos niveis de suplementacao para vacas leiteiras mantidas a pasto reduz o consumo de forragem, sem afetar negativamente o consumo de materia seca total e sem alterar os valores de pH do liquido ruminal.
The impact of teacher subject knowledge on learner performance in South Africa : A within-pupil across-subject approach

This paper assesses the impact of teacher subject knowledge on learner performance using a nationally representative dataset of grade 6 students in South Africa. Learner test scores in two subjects are used to identify within-pupil across subject variation in performance. Teacher knowledge is only estimated to have a significant positive impact on performance when considering the wealthiest quintile of schools. The effect is removed once controlling for teacher unobservables. The results suggest that a deep knowledge and understanding of subject matter taught are important, but of more importance is the ability to transfer that information in a meaningful way to
Effects of Social Media Use on Cognitive and Affective Empathy

by Kristin M. Whited Previous research suggests an overall decrease in empathy and interpersonal skil ls. Studies implicate social media as a variable in these trends; however, much of this previous r search has only been correlational. The present study examined the effects of social media use as well as face-to-face interpersonal interaction on state empathy and trait empathy. Col lege students ( N = 110) were randomly assigned to scroll through social media posts, participate in a fac e-to-f e conversation, or complete a word search puzzle. They then completed measures of state e mpathy, trait empathy, amount of typical social media use, and amount of typical face-to-fa ce interaction. It was hypothesized that increased typical social media use would be related to dec reased trait empathy, and that participants in the interpersonal group would display the highest state emp thy while those in the social media group would display the lowest. Significant effects o social media on state empathy were found. EFFECTS OF SOCIAL MEDIA USE ON COGNITIVE AND AFFECTIVE EMPATHY by Kristin M. Whited A Thesis presented in partial fulfillment of the requirements for the degree of Master of Science in Psychology Department of Psychological Science University of Central Missouri April, 2016 © 2016 Kristin M. Whited ALL RIGHTS RESERVED EFFECTS OF SOCIAL MEDIA USE ON COGNITIVE AND AFFECTIVE EMPATHY by Kristin M. Whited April, 2016 APPROVED: Thesis Chair: Dr. Steve Schuetz Thesis Committee Member: Dr. David Kreiner Thesis Committee Member: Dr. Kim Stark ACCEPTED: Chair, Department of Psychological Science: Dr. David Kreiner UNIVERSITY OF CENTRAL MISSOURI WARRENSBURG, MISSOURI ACKNOWLEDGMENTS I would like to thank my thesis committee members, Dr. Kreiner and Dr. Stark, for the ir help on this project. I would also like to thank my thesis chair and mentor Dr. Schuetz for his wise advice and friendship. Finally, I would like to thank my family and my fiancé for their const ant support, love, and belief in my ability to be a life-long learner. TABLE OF CONTENTS Page LIST OF TABLES.ix CHAPTER 1: NATURE AND SCOPE OF THE STUDY.1 CHAPTER 2: LITERATURE REVIEW.3 Decreasing Interpersonal Skills.3 Social Media.10 Empathy.19 Hypotheses.27 CHAPTER 3: METHODOLOGY.28 Participants.28 Materials.28 Procedure.37 CHAPTER 4: RESULTS.39 CHAPTER 5: DISCUSSION.44 REFERENCES.53 APPENDICES A. Social Media Posts.62 B. Confederate Script.67 C. Word Search Puzzle.68 D. Emotional Response Questionnaire.69 E. Questionnaire of Cognitive and Affective Empathy.70 vii F. Media Technology Usage and Attitudes Scale.72 G. Interpersonal Interaction Scale.74 H. Informed Consent Form.76 I. Demographics Form.77
Another Look at Student Motivation: A Qualitative Study.

The more that educators understand about student motivation, the better that teachers can tailor their pedagogy to prepare students for the job market. The purpose of this study was to acquire a more complete understanding of what drives secondary students and how student motivation and development relate to effective teaching. It is hoped that an improved understanding of what motivates students will prompt teachers to modify their strategies so as to foster self-directed learning in their students. An examination of the literature suggests that educators should decrease the competitive nature of the classroom, pay more attention to developing students' self-esteem, note the importance of making content relevant and learning enjoyable, and that teachers should work to create an environment conducive to learning. Utilizing a qualitative research design, information was gathered through classroom observations, student interviews, and a teacher interview of a 10th-grade, advanced world history course. Specific themes, such as learning, social, friends, and teacher, were examined as they related to increasing student motivation. The study also describes strategies that teachers can implement in order to increase student motivation. Contains 11 references. (RJM) ********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** Another Look at Student Motivation: A Qualitative Study Douglas Heller Marshall University James M. Sottile, Jr. Marshall University
NOT ALL OF THE RARE OPERATIONAL TAXONOMIC UNITS ( OTU S ) PLAY THE SAME ROLE IN MAINTAINING COMMUNITY STABILITY

The role of rare biosphere in maintaining the community diversity and metabolic activity has recently been highlighted. However, it is still unclear whether the rare species play the same role in maintaining the community diversity. Considering different responses of microbial species on environment changes, we speculate rare species played different roles in maintaining the α-diversity. To verify the speculation, we analyzed the prokaryotic species in three eutrophic rivers and one eutrophic lake via Miseq sequencing of 16S rDNA amplicons. Although more than 50 phyla were identified from 20 samples, only seven were dominant. The dominant species were strictly restricted. The rare operational taxonomic units (OTUs) belonging to the dominant phyla played a crucial role in maintaining the community diversity. These results intensified our knowledge on the role of rare species in maintaining the diversity of microbial community.
Performance Evaluation of Zigbee Coordinator Fails Node with Different Topologies

ZigBee’s feature is low power utilization, approved specifications make it very suitable to be used with application sensor devices. Also features are short distance communication and low cost. ZigBee technology makes that difficult wire repeat can be shunned in the area of home, manufacturing plant, infirmary, etc. This paper compares the cluster tree topology with the star topology of ZigBee in terms of the amount of received data, throughput and delay, it shows that cluster tree topology is more salutary than star topology.
"What Happens in My University Classes That Helps Me to Learn?" Teacher Education Students' Instructional Metacognitive Knowledge.

Teacher education students’ instructional metacognitive knowledge needs to be well developed to promote both their own learning and their prospective students’ learning. In this study, we asked teacher education students to provide answers to the question “What happens in my university classes that helps me to learn? ” Students identified issues such as supportive classroom environments, teachers’ professional and personal qualities, practical activities, reflection, and discussions. Cognitive organisation strategies were not well represented. Cluster analysis and multidimensional scaling of students’ responses identified a perceptual separation between teachers’ and students’ roles, suggesting that participants’ sense of personal agency, shared responsibility for learning, and involvement in a learning community, were not developed in directions suggested by contemporary educational theory. Implications for teaching-learning interactions that have the potential to develop students’ instructional metacognitive knowledge are discussed.
Optimization of Bank Liquidity Management using Goal Programming and Fuzzy AHP

In this research, Goal Programming (GP) and Fuzzy Analytic Hierarchy Process (FAHP) were integrated. The financial objectives of Parsian Bank (a leading private bank in Iran) were identified and prioritized. An optimal liquidity management model incorporating the following objectives was devised; capital sufficiency, liquidity risk, liquidity ratio, claims from other banks, investments portfolio, total consumption to total resources ratio, growth of total assets, fixed assets and other assets. Afterwards, the goal and structural limitations of variables were taken consideration and finally, the optimal liquidity management model was estimated. Then, by using the input variables (the liabilities side in the balance sheet and the related subsets) and the outputs (the assets side in the balance sheet and their subsets) in the period of 2011-2012, the optimal values for liquidity ratios and other items in the balance sheet were calculated using Lingo software. They were then compared with real values in the balance sheet accordingly. Next, the solutions and suggestions were offered for optimizing liquidity management in the bank. The eight objectives used for the preparation of optimal liquidity model were prioritized using the viewpoints of senior financial directors of the bank with the emphasis on a questionnaire, which was designed based on the FAHP method. Furthermore, in order to test the estimated model and assess its efficacy, the total return of the bank (R) was calculated once using the real items in the balance sheet, and another time using the values obtained from the model as well as the return formula (both for the period of 2011-2012). The results demonstrateda noticeable increase in the return of the estimated model in comparison with the real return of the bank. In addition, it should be stated that the estimated model can diminish the liquidity risk and increase the growth of the total assets of Parsian Bank, which evidently presents the reliability, validity, and application of the estimated liquidity management model for the banking system.
Entity Disambiguation with Markov Logic Network Knowledge Graphs

Disambiguating named entities is an important problem in natural language processing, knowledge base, question answering systems. In the paper, we propose a Markov logic network knowledge graph solution for solving entity resolution problem. First, we employ knowledge graph to represent the entity relationship between linked entities in the knowledge base. Then, we utilize MLN to inference the inconsistent relationship in the knowledge graph, and disambiguate the entities in the process of entity disambiguation. As far as we know, inferencing with MLN is a first attempt for entity disambiguation in the knowledge graph. We evaluate the proposed solution with three real world knowledge bases and compare it with four baseline solutions. The experimental results demonstrate that our solution is 7% higher than other baseline methods with F1 measure. We also test our scheme and compare entity resolution systems on four datasets with three knowledge base corpora. Extensive experiments show that our solution achieves higher precision and recall than baseline solutions.
From the Help Desk: Local Polynomial Regression and Stata Plugins

Abstract. Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964) and Watson (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local means, but local polynomial smooths have better statistical properties. The computational complexity may, however, be alleviated by using a Stata plugin. In this article, we describe the locpoly command for performing local polynomial regression. The calculations involved are implemented in both ado-code and with a plugin, allowing the user to assess the speed improvement obtained from using the plugin. Source code for the plugin is also provided as part of the package for this program.
Development of superhydrophobic fabrics by surface fluorination and formation of CNT-induced roughness

Superhydrophobictextile material having self-cleaning function was developed by employing carbon nanotubes (CNTs) and water-repellent agents.Hydrophobic fabrics were prepared on 100% polyester woven fabrics withvarious yarn diameters and yarn types. The wetting behavior of fabrics withdifferent treatments was compared for: siloxanerepellent, fluorocarbon repellent, and CNT added fluorocarbon repellent. Drawn textured yarn (DTY) fabrics exhibited higher contactangle (CA) than filament yarn fabrics due to the larger surface roughness contributed by the textured yarn. Fabrics treated with fluorocarbon presentedlarger CA and lower shedding angle than those treated with siloxane,because of the lower surface energy of fluorocarbon repellent. Specimens madeof 50 denier DTY and treated with CNT-Teflon AF® showed the mostsuperhydrophobic characteristics in the study, producing the static contactangle>150° and the shedding angle<15°. CNT on fabric surface contributedto the nano-scale surface roughness to hold the air traps like papillae oflotus leaf, giving superhydrophobic characteristics. DOI: http://dx.doi. org/10.5755/j01.ms.21.1. 5762
Project Finance Model for Small Contractors in USA

This research looks at the significance of barriers that firms considering entry into the construction industry might face. Drawing on the microeconomic characteristics of imperfectly competitive and oligopolistic markets the analysis finds that there are a dozen barriers to entry that affect the industry, but their significance depends on the product type. The discussion covers the question of product homogeneity in construction and evidence for the existence of barriers to entry in concentration levels. Barriers to entry specific to construction are then identified, which leads to an analysis of how they operate and their significance (high, medium or low) in different market types, thus increasing our understanding of construction industry dynamics.
Variable Selection in Cox's Proportional Hazards Model Using a Parallel Genetic Algorithm

One of the most common objectives for analyzing censored survival data with covariates is to identify a small number of key risk factors. Cox's proportional hazards model is perhaps the most widely used statistical model in such a context. We propose a parallel genetic algorithm (PGA) to select important covariates in the Cox model. Our simulation study shows that PGA is capable of finding the correct subset of covariates with significantly higher probability than stepwise selection. We also illustrate our method with a real data set concerning the treatment of primary biliary cirrhosis of the liver.
Optimization of resonant effects in nanostructures via Weierstrass factorization

Extensive numerical computations are often required to optimize the optical properties of nanostructures. Here, we use the Weierstrass factorization theorem to express the scattering matrix in terms of spectral singularities. We show that the location of poles and zeros of the scattering matrix fully determines all scattering properties, and that the scattering spectra of nanostructures can be decomposed into Lorentzian resonances over an arbitrary range of frequencies. This technique is applied to design nanoshell particles with enhanced absorption.
The Impact of Microfinance on Women Micro-Enterprises "A Case Study of District Quetta, Pakistan"

Lack of financial resources is considered one of the main constraints of women participation in economic development. The microfinance is considered as one of the important tool for resolving this problem. The overall aim of this study is to explore the impact of microfinance on women microenterprises. With the help of survey design; the primary data is collected through structured questionnaires covering one group of 60 female beneficiaries who availed microfinance for two years or more prior to the survey and compare with a group of 20 new clients of the BRAC, Pakistan an NGO in district Quetta. The stratified random sample as used for selection of members from both groups. Results of the study show that microfinance has positive impact on creation of microenterprises. The microfinance is helpful in enhancement of average sale revenue and net income. The microfinance has also positive impact on average net working capital, average fixed assets and helpful in improvement of credit worthiness of beneficiaries’ microenterprises as compare to non-beneficiaries.
Automatic generation of E-LOD1 from LiDAR point cloud

LiDAR as a powerful system has been known in remote sensing techniques for 3D data acquisition and modeling of the earth’s surface. 3D reconstruction of buildings, as the most important component of 3D city models, using LiDAR point cloud has been considered in this study and a new data-driven method is proposed for 3D buildings modeling based on City GML standards. In particular, this paper focuses on the generation of an Enhanced Level of Details 1 (E-LOD1) of buildings containing multi-level flat-roof structures. An important primary step to reconstruct the buildings is to identify and separate building points from other points such as ground and vegetation points. For this, a multi-agent strategy is proposed for simultaneous extraction of buildings and segmentation of roof points from LiDAR point cloud. Next, using a new method named “Grid Erosion” the edge points of roof segments are detected. Then, a RANSAC-based technique is employed for approximation of lines. Finally, by modeling of the rooves and walls, the 3D buildings model is reconstructed. The proposed method has been applied on the LiDAR data over the Vaihingen city, Germany. The results of both visual and quantitative assessments indicate that the proposed method could successfully extract the buildings from LiDAR data and generate the building models. The main advantage of this method is the capability of segmentation and reconstruction of the flat buildings containing parallel roof structures even with very small height differences (e.g. 50 cm). In model reconstruction step, the dominant errors are close to 30 cm that are calculated in horizontal distance.
Carbon emissions from land cover change in Central Vietnam

ABSTRACT The carbon emissions and removals due to land cover changes between 2001 and 2010 in the Vu Gia Thu Bon River Basin, Central Vietnam, were estimated using Landsat satellite images and 3083 forest inventory plots. The net emissions from above- and belowground vegetation biomass were equal to 1.76 ± 0.12 Tg CO2, about 1.1% of the existing stocks. The vast majority of carbon emissions were due to forest loss, with the conversion of forest to cropland accounting for 67% of net emissions. Forest regrowth had a substantial impact on net carbon changes, removing 22% of emissions from deforestation. Most deforestation occurred in regrowth forest (60%) and plantations (29%), characterized by low carbon stock density. Thus identifying the type of forest where deforestation occurred and using local field data were critical with net emissions being 4 times larger when considering only one forest class with average carbon stock, and 5–7 times higher when using literature default values or global emission maps. Carbon emissions from soil (up to 30 cm) were estimated for the main land change class. Due to the low emission factors from biomass, soils proved a key emission category, accounting for 30% of total land emissions that occurred during the monitoring period.
An Evolutionary Cognitive Neuroscience Perspective on Human Self-awareness and Theory of Mind

The evolutionary claim that the function of self-awareness lies, at least in part, in the benefits of theory of mind (TOM) regained attention in light of current findings in cognitive neuroscience, including mirror neuron research. Although certain non-human primates most likely possess mirror self-recognition skills, we claim that they lack the introspective abilities that are crucial for human-like TOM. Primate research on TOM skills such as emotional recognition, seeing versus knowing and ignorance versus knowing are discussed. Based upon current findings in cognitive neuroscience, we provide evidence in favor of an introspection-based simulation theory account of human mindreading.
Back to School after Delivery, the Plight of Teenage Mothers in Zanzibar: Experiences from Mjini Magharibi's Urban and West Districts in Unguja

Teenage pregnancy and motherhood is a global problem. Each year, approximately more than sixteen million teenage girls around the world give birth. Majority of the teenage mothers are found in low and middle income countries (WHO, 2016). Among the low and middle income countries, SubSaharan Africa has the highest rates of teenage pregnancy and births in the world (UNICEF/Plan International, 2014), where it is estimated that more than 50% of all teenage girls in Sub-Saharan Africa give birth before reaching the age of twenty (UNFPA, 2013).