Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy elevation and economic analysis of canola production in Iran a case study: Mazandaran province

1­ Department of Agricultural Machinery Engineering, Faculty of Biosystems Engineering, University of Tehran, Karaj, Iran. 2­ Department of Agricultural Machinery Engineering, University of Gorgan, Iran asakerehabbas@gmail.com ABSTRACT Energy in agriculture is important in terms of crop production and agroprocessing for value adding. Canola is one of important rapeseed that it is tilled in dry farming systems in north of Iran. The aims of this study were to determine direct input energy and indirect energy in dry farming canola production, to investigate the efficiency of energy consumption and to make an economic analysis of canola farming in Behshahr County of Iran. Data were collected from 62 canola farms by using a face to face questionnaire method. The results revealed that canola production consumed a total of 28705.3 MJ/ha of which chemical fertilizer and diesel fuel energy consumption was 65.5% and 30%, respectively. Output Energy was 41230 MJ/ha. Output– input energy ratio and specific energy of production were 1.44 and 15.1 MJ/kg, respectively. Non ­renewable energy was 99% total input energy that co ncluded that canola production needs to improve the efficiency of energy consumption in production and to employ renewable energy. Total cost ware was 641.1 USD and Benefit­ cost ratio and net income ware 0.86 and 550 USD respectively. Key words: Canol a, Energy ratio, Energy productivity, Economic analysis , Iran .
Shallow landsliding, root reinforcement, and the spatial distribution of trees in the Oregon Coast Range

The influence of root reinforcement on shallow landsliding has been well established through mechanistic and empirical studies, yet few studies have examined how local vegetative patterns influence slope stability. Because root networks spread outward from trees, the species, size, and spacing of trees should influence the spatial distribution of root strength. We documented the distribution and characteristics of trees adjacent to 32 shallow landslides that oc- curred during 1996 in the Oregon Coast Range. Although broadly classified as a conifer-dominated forest, we observed sparse coniferous and abundant hardwood trees near landslide scars in an industrial forest (Mapleton) that experienced widespread burning in the 19th century. In industrial forests that were burned, selectively harvested, and not replanted (Elliott State Forest), swordfern was ubiquitous near landslides, and we observed similar numbers of live conifer and hardwood trees proximal to landslide scarps. We demonstrate that root strength quantified in landslide scarps and soil pits correlates with a geometry-based index of root network contribution derived from mapping the size, species, condi- tion, and spacing of local trees, indicating that root strength can be predicted by mapping the distribution and charac- teristics of trees on potentially unstable slopes. In our study sites, landslides tend to occur in areas of reduced root strength, suggesting that to make site-specific predictions of landslide occurrence slope stability analyses must account for the diversity and distribution of vegetation in potentially unstable terrain.
International student cultural experience: a case study of the Noho Marae Weekend

iv CHAPTER 1: INTRODUCTION 1 1.1 Personal Journey 1 1.2 Rationale and Significance of the Study 1 1.3 Scope and Limitations 7 1.4 Thesis Outline 8 CHAPTER 2: LITERATURE REVIEW ON INTERNATIONAL STUDENTS 9 2.1 International Students in the World 9 2.2 International Students in New Zealand 14 2.3 International Education Agenda 2007-2012 16 2.4 Contextualising the Current Study 19 CHAPTER 3: LITERATURE REVIEW ON CULTURE 22
A Case of Limbic Encephalitis: Antibody LGI1 Associated Encephalitis

Limbic encephalitis (LE) is a rarely encountered disease in modern clinical practice. It is basically autoimmune in nature, with its pathophysiology determined by a number of antibodies to neural surface proteins. However, 20% of cases are paraneoplastic and have a tumour source in the body which leads to limbic encephalitis secondarily. Studies have shown that VGKC complex (Voltage Gated Potassium Channels) is one of the common antibodies found in this disease and is represented by three such proteins out of which LGI1 is most prevalent in limbic encephalitis. This entity is characterized by monophasic presentation with acute or subacute onset memory loss, confusion, seizures and psychiatric symptoms. The presence of anti LGI1 antibodies in serum or CSF confirms the diagnosis. We hereby report a case of a 65 year old woman with 8 months history of peripheral neuropathy followed by memory impairment, focal seizures with behavioural and psychiatric changes. No tumour was found on imaging and the classic paraneoplastic panel was negative. However, she was found to be positive for Antibody LGI1 proving autoimmune basis of her illness which responded majorly to immuno-modulatory therapy in the form of high dose steroids.
Learning, Continuity and Change in Adult Life [Wider Benefits of Learning Research Report No. 3]

This report presents results from extensive fieldwork carried out by the Wider Benefits of Learning research team. It presents an original analytical framework developed specifically for this study, combined with empirical results from 140 in-depth biographical interviews in three different areas of England. The interviews explore the way learning affects people’s health and well-being; their family lives; and their engagement in civic activity. The report addresses these effects at both an individual and collective level. It concludes with a set of significant policy implications.
Prognostic Value of Myeloid Differentiation Primary Response 88 and Toll-Like Receptor 4 in Breast Cancer Patients

Purpose Breast cancer remains a major cause of death in women worldwide, and tumor metastasis is the leading cause of death in breast cancer patients after conventional treatment. Chronic inflammation is often related to the occurrence and growth of various malignancies. This study evaluated the prognosis of breast cancer patients based on contributors to the innate immune response: myeloid differentiation primary response 88 (MyD88) and Toll-like receptor 4 (TLR4). Methods We analyzed data from 205 breast invasive ductal carcinoma (IDC) patients who were treated at the Department of Breast Surgery, Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, from 2002 to 2006. Overall survival (OS) and disease-free survival (DFS) were compared. Results In total, 152 patients (74.15%) were disease-free without relapse or metastasis, whereas 53 (25.85%) patients developed recurrence or metastasis. A significant positive correlation was observed between MyD88 and TLR4 expression (p<0.001). Patients with high expression were more likely to experience death and recurrence/metastasis events (p<0.05). Patients with low MyD88 or TLR4 expression levels had better DFS and OS than patients with high expression levels (log-rank test: p<0.001). Patients with low MyD88 and TLR4 expression levels had better DFS and OS than patients with high expression levels of either (log-rank test: p<0.001). In a multivariate analysis, high MyD88 expression was an independent predictive factor for decreased DFS (adjusted HR, 3.324; 95% CI, 1.663–6.641; p = 0.001) and OS (adjusted HR, 4.500; 95% CI, 1.546–13.098; p = 0.006). Conclusions TLR4-MyD88 signaling pathway activation or MyD88 activation alone may be a risk factor for poor prognosis in breast cancer. Therefore, TLR4-MyD88 signaling pathway activation in tumor biology provides a novel potential target for breast cancer therapy.
Mixture of differentially tagged Tol2 transposons accelerates conditional disruption of a broad spectrum of genes in mouse embryonic stem cells

Among the insertional mutagenesis techniques used in the current international knockout mouse project (KOMP) on the inactivation of all mouse genes in embryonic stem (ES) cells, random gene trapping has been playing a major role. Gene-targeting experiments have also been performed to individually and conditionally knockout the remaining ‘difficult-to-trap’ genes. Here, we show that transcriptionally silent genes in ES cells are severely underrepresented among the randomly trapped genes in KOMP. Our conditional poly(A)-trapping vector with a common retroviral backbone also has a strong bias to be integrated into constitutively transcribed genome loci. Most importantly, conditional gene disruption could not be successfully accomplished by using the retrovirus vector because of the frequent development of intra-vector deletions/rearrangements. We found that one of the cut and paste-type DNA transposons, Tol2, can serve as an ideal platform for gene-trap vectors that ensures identification and conditional disruption of a broad spectrum of genes in ES cells. We also solved a long-standing problem associated with multiple vector integration into the genome of a single cell by incorporating a mixture of differentially tagged Tol2 transposons. We believe our strategy indicates a straightforward approach to mass-production of conditionally disrupted alleles for genes in the target cells.
Hidden conditional random field with distribution constraints for phone classification

We advance the recently proposed hidden conditional random field (HCRF) model by replacing the moment constraints (MCs) with the distribution constraints (DCs). We point out that the distribution constraints are the same as the traditional moment constraints for the binary features but are able to better regularize the probability distribution of the continuousvalued features than the moment constraints. We show that under the distribution constraints the HCRF model is no longer log-linear but embeds the model parameters in non-linear functions. We provide an effective solution to the resulting more difficult optimization problem by converting it to the traditional log-linear form at a higher-dimensional space of features exploiting cubic spline. We demonstrate that a 20.8% classification error rate (CER) can be achieved on the TIMIT phone classification task using the HCRF-DC model. This result is superior to any published single-system result on this heavily evaluated task including the HCRF-MC model, the discriminatively trained HMMs, and the large-margin HMMs using the same features. Index Terms: hidden conditional random field, maximum entropy, moment constraint, distribution constraint, phone classification, TIMIT, cubic spline
Changing Project Delivery Strategy

For organizations such as departments of transportation, other public agencies, and private companies, adopting a new approach to procure services for delivery of construction projects requires significant organizational changes; modifications to both their work processes and existing organizational structures may be needed. Building on findings from a study of public owner organizations that have implemented the design-build method for delivering highway projects, the have developed a conceptual framework for helping owner organizations implement a change in their project delivery strategy. They further refined this framework by comparatively studying four transportation projects in the United States. In addition, many experts in the implementation of the design-build method for transportation projects participated in a Delphi study to validate the developed framework. In this article, the authors present findings from these studies, including application to the construction industry and to other industries.
Volatility Cycles of Output and Inflation: A Good Shock, Bad Shock Story

We explain the close correlation of volatilities of GDP growth and inflation over the 1919-2004 period, using credit and money shocks that have "bad" and "good" effects that are defined in terms of their effects on the spectral variation in GDP. With these shocks, plus standard TFP productivity shocks, we identify, characterize and contrast the two great volatility cycles over the historical period, within an endogenous growth monetary business cycle with micro-based banking production. The Great Moderation post-1983 coincided with good credit shocks from deregulation, which allowed money velocity to diverge from GDP and inflation volatilities, while the Great Depression was faced with bad money and credit shocks that tied together velocity volatility with GDP and inflation volatility.
Molecular dynamics simulations of the interaction between the surfaces of polar solids and aqueous solutions

Molecular dynamics (MD) simulations were performed on the interaction of two solid surfaces, namely the (00.1) hematite and (10.4) calcite surfaces, in contact with aqueous electrolyte solutions containing different concentrations of dissolved NaCl. The structure and a number of properties of the interface were investigated. The size and amount of statistics needed for convergence of these calculations required the use of high performance computers. The two surfaces show different bonding mechanisms with the water, but both result in a distinctive layering of the water, which in turn modifies a range of surface behaviour including diffusivity and charge distribution. We find that the resulting charge distribution from the solvent has a greater control of the disposition of dissolved ions than either surface charge or ionic strength, within reasonable limits. Thus we see a characteristic double layer at neutral surfaces and the charge distribution oscillates into the bulk. Finally, preliminary work on calculating the free energy of dissolution of ions from the surface to the aqueous solution suggests that the presence of dissolved ions makes a small but significant reduction to the dissolution free energies.
The Paralympic Games Explained

1. The History and Development of the Paralympic Games 2. The Olympic Movement and the Paralympic Games 3. The Governance of Paralympic Sport 4. Disability and the Body 5. The Broader Social Issues of Disability within Society and their Impact on Sports Participation 6. Media, Marketing and Disability Sport 7. Major Issues within the Paralympic Movement 8. The Under Representation of Women and Athletes with High Support Needs at the Paralympic Games 9. International Perspectives on Paralympic Participation 10. Special Olympics, Intellectual Disability and the Paralympic Games. Bibliography. Index.
The Isoperimetric Problem

A ccording to lege~d, in the year 800 BC Princess Dido of Tyre fled her Phoenician homeland to free herself of the tyranny of her murderous king brother. She crossed the Mediterranean and sought to purchase land for a new home upon the shores of northern Africa. Confronted with only prejudice and distrust by the natives she was given permission to purchase only as much land as could be surrounded by a hull's hide. She accepted the terms and made the most of them by cutting a hide into very thin strips and piecing them together to form a single, very long string, which she then used to enclose a portion of land of maximal area against the straight line of the coast. The portion of land she consequently purchased for a minimal price turned out to be large enough to build a city. This is said to be the origin of the city of Carthage. Princess Dido, in this legend, solved a variant of the famous isoperimetric problem: Of all figures in the plane with a given perimeter, which encloses the largest area? This is perhaps the oldest problem in global differential geometry. Virgil (70-19 BC) in his work Aeneid refers to the legend of Dido, and the problem, as well as its solution, was certainly known to the Greeks. Throughout the ages many mathematicians have studied the problem offering new approaches and simplified solutions, and for a long while the problem was thought completely solved. In the following twelve problems I lead you through an approach essentially due to Jacob Steiner (1796-1863), with some new twists and tidbits thrown in along the way. Although each puzzle is of interest in its own right, the collection as a whole leads to a thoroughly accessible, and apparently complete, solution to the isoperimetric problem. But there is a warning, one first pointed out by Weierstrass in 1870, that appears in question 12. We will take heed of this warning, but for now, read on, think hard and have fun.
Extended Abstract: A design for a tourist CF system

The use of computer supported travelling in the tourist industry has been steadily increasing and has recently attracted considerable interest. Tourism is in many ways the domain most closely connected with personal preferences and by definition connected to (physical) mobility. Hence, not surprisingly personalised location-based information systems are very suitable for this domain. The modern tourists do not only require general guidance and information but also information specifically tailored to their personal preferences. Local guides and guided tours cover many tourists’ needs by customising tours. Yet, a location-based personalised recommender systems offers a supplement to the available customised services. Recommender systems are designed to help users cope with vast amounts of information, and they do so by presenting only a certain subset of items that is believed to be relevant for the user. The typical tourist will not linger long in any location. Hence, a location-based information system will not be able to effectively learn the idiosyncrasies of any single tourist. This is a challenge when dealing with recommender systems, as they (most often) rely on a classification of the user and the information it is attempting to recommend. Not having sufficient information to give good recommendations to a new user is known as the cold-start-user problem. The cold-start-user problem can to some degree be alleviated by employing user models. However, building user models requires (sufficient) knowledge about the specific user. Acquiring this knowledge is subject to the knowledge bottleneck problem. That is, it is time consuming (for the user) and not necessarily easily accessible. A key question is therefore what type of information to query from a user, to what extent should information be collected, and how should the user information be exploited when the system gives recommendations. In this abstract we give the conclusions of a structured literature review [3] designed to answer these questions. The literature review focuses attention to CF models combining Bayesian networks with user modelling as a means of mitigating both the cold-start-user and knowledge bottleneck problem.
Mining Gene Sets for Measuring Similarities

In recent years, the development of high throughput devices for the massive parallel analyses of genomic data has lead to the generation of large amount of new biological evidences and has triggered the proliferation of data mining algorithms for the extraction of meaningful information. Microarrays for gene expression analyses are part of this revolution and provide important insight in molecular biology often in the form of coherent sets of genes representing previously uncharacterized processes. Large amount of data are continuously produced in this form, and computational approaches can significantly improve the efficient use of these results, since comparison among numbers of genes sets can give new meaningful information at no cost from the experimental biology point of view. To address this opportunity we designed and implemented FIT, a scalable, unsupervised algorithm that quantitatively compares different populations of gene sets using two distinct measures of similarity between any two gene sets. These measures are then used to obtain a summary statistic that describes the tightness of fit between sets belonging to two distinct populations of gene sets. We present the results of FIT on two data sets for the study of Lymphoma and Acute Lymphoblastic Leukemia. In both cases FIT was able to recapitulate the previous analyses on these datasets, to extend the results and to extract information likely to offer potential insights into the underlying biology.
The effect of unemployment benefits on re-employment rates: Evidence from the Finnish UI-benefit reform ♣

In January 2003, the unemployment benefits in Finland were increased for workers with long employment histories. The average benefit increase was 15 per cent for the first 150 days of the unemployment spell. In this paper we evaluate the effect of the benefit increase on the duration of unemployment by comparing the changes in the re-employment hazard profiles among the unemployed who became eligible for the increased benefits to the changes in a comparison group whose benefit structure remained unchanged. We find that the benefit increase reduced the re-employment hazards at the beginning of the unemployment spell. The effect disappears after the eligibility period for the increased benefit expires.
Quality Disclosure Programs and Internal Organizational Practices: Evidence from Airline Flight Delays

Disclosure programs exist in many industries in which consumers are poorly informed about product quality. We study a disclosure program for airline on-time performance, which ranks airlines based on the fraction of their flights that arrive less than 15 minutes late. The program creates incentives for airlines to focus their efforts on flights close to this threshold. We find that firms in this industry are heterogeneous in how they respond to these incentives. Moreover, this heterogeneity correlates with internal firm characteristics. Our findings highlight the importance of interactions between incentives created by a disclosure program and firms' internal organizational practices. (JEL D22, L15, L25, L93)
A General Framework for Analyzing Data from Two Short Time-Series Microarray Experiments

We propose a general theoretical framework for analyzing differentially expressed genes and behavior patterns from two homogenous short time-course data. The framework generalizes the recently proposed Hilbert-Schmidt Independence Criterion (HSIC)-based framework adapting it to the time-series scenario by utilizing tensor analysis for data transformation. The proposed framework is effective in yielding criteria that can identify both the differentially expressed genes and time-course patterns of interest between two time-series experiments without requiring to explicitly cluster the data. The results, obtained by applying the proposed framework with a linear kernel formulation, on various data sets are found to be both biologically meaningful and consistent with published studies.