Miracle-dz/UniFAR-FTUs huggingface dataset:
The influence of EU involvement on the autonomy of Independent Administrative Bodies

This research focuses on ‘agencies’, which are institutions created by legislation and that are organisationally separate from governments. Moreover, they are subject to the controls of elected politicians. But agencies are also highly central actors who can be influential during the phase of agenda-setting and pre-parliamentary discussions on policymaking. In addition, agencies are able to deal with supranational organisations such as the institutions of the European Union: the European Commission and the Council of the European Union. Several empirical studies indicate that EU involvement of national agencies can have an effect on the autonomy of those agencies. To complement this debate this thesis has studied eleven Dutch Independent Administrative Bodies (IABs, ‘Zelfstandige Bestuursorganen’), on their EU involvement and the consequences this involvement has on the autonomy of the IABs during the national policymaking process. Through a co-variational analysis it has been attempted to assess this relation as well as to analyse a possible relation between policy complexity and the autonomy of an IAB. The findings of this research indicate that involvement through the European Commission and through the Council is valuable for the IABs since they gain information on EU legislation and information on best practices through their participation and interaction with the institutions. A strong relation between EU involvement and the autonomy of IABs cannot be demonstrated.
The Staggering Rise of the South

This paper argues that the unprecedented acceleration of growth in the developing world in the new millennium in comparison with advanced economies is due not so much to improvements in underlying fundamentals as to exceptionally favourable global economic conditions, shaped mainly by unsustainable policies in advanced economies. The only developing economy which has had a major impact on global conditions, notably on commodity prices, is China. However, growth in China has been driven first by a rapid expansion of exports to advanced economies and more recently, after the global crisis, by an investment boom, neither of which is replicable or sustainable over the longer term. To maintain a rapid growth, export-led Asian economies need to reduce their dependence on foreign markets. For Latin American and African commodity exporters, gaining greater autonomy and achieving rapid and stable growth depend on their success in reducing reliance on capital flows and commodity earnings – the two key determinants of their growth which are largely beyond national control.
Labor Market Returns to Community Colleges: Evidence for Returning Adults.

Kane and Rouse (1993) furnish evidence that enrollment in a two-year-or four-year-college program increases earnings by 5 to 8 percent per year of college credits, whether or not a degree is earned. This evidence has provided the intellectual basis for policy recommendations to increase access by adult workers to long-term education and training programs, such as those supplied by community colleges. Yet to be answered, however, is the question whether these favorable return estimates hold for experienced adult workers who return to school. For both A.A. and nondegree community college programs, our results indicate returns that are positive and of essentially the same size for returning adults as they are for continuing high school graduates. Among males in nondegree programs, in fact, returning adults enjoy an incremental earnings effect of 8 to 10 percent above that received by continuing students.
Exploiting Multimodal Data for Image Understanding. (Données multimodales pour l'analyse d'image)

This dissertation delves into the use of textual metadata for image understanding. We seek to exploit this additional textual information as weak supervision to improve the learning of recognition models. There is a recent and growing interest for methods that exploit such data because they can potentially alleviate the need for manual annotation, which is a costly and time-consuming process. We focus on two types of visual data with associated textual information. First, we exploit news images that come with descriptive captions to address several face related tasks, including face verification, which is the task of deciding whether two images depict the same individual, and face naming, the problem of associating faces in a data set to their correct names. Second, we consider data consisting of images with user tags. We explore models for automatically predicting tags for new images, i.e. image auto-annotation, which can also used for keyword-based image search. We also study a multimodal semi-supervised learning scenario for image categorisation. In this setting, the tags are assumed to be present in both labelled and unlabelled training data, while they are absent from the test data. Our work builds on the observation that most of these tasks can be solved if perfectly adequate similarity measures are used. We therefore introduce novel approaches that involve metric learning, nearest neighbour models and graph-based methods to learn, from the visual and textual data, task-specific similarities. For faces, our similarities focus on the identities of the individuals while, for images, they address more general semantic visual concepts. Experimentally, our approaches achieve stateof-the-art results on several standard and challenging data sets. On both types of data, we clearly show that learning using additional textual information improves the performance of visual recognition systems.
Culture's consequences on leadership : towards a paradigm

Culture’s Consequences on Leaderships: Towards a Paradigm May 1988 Nnanyelu E. Ezeh B.S. University of Nigeria, Nsukka, Nigeria. M.S. University of Hartford, Hartford, Connecticut. Ed.D. University of Massachusetts, Amherst, Massachusetts. Directed by: Dr. Norma Jean Anderson. The absence of a theory of leadership wide enough to accommodate study and analysis univerally is constraining. This is more true today than ever before, especially in the light of modern trends where different countries come together in economic, scientific and other ventures. The activities of international and multinational organizations are on the increase, in short, we are fast drifting towards a global village. The above situation therefore demands that effort be made to produce a leader knowledgeable enough about his/her own culture and that of the others so as to be able to apply such criteria in decision-making which will adequately consider differences in the cultural values of all concerned. The main aim of this study is to introduce and apply a model of leadership study that can account for different leadership behaviors and patterns found in different cultures. The theoretical underpinning that guided the conduct and
Replacement of cisplatin with nedaplatin in a definitive 5-fluorouracil/cisplatin-based chemoradiotherapy in Japanese patients with esophageal squamous cell carcinoma

Objective: The effects of replacing cisplatin (CDDP) with cis-diammineglycolatoplatinum (nedaplatin, NDP), a second-generation platinum complex, on the pharmacokinetics of 5-fluorouracil (5-FU) were investigated in Japanese patients with esophageal squamous cell carcinoma, who were treated with a definitive 5-FU/CDDP-based chemoradiotherapy. Methods: Fifty-six patients were enrolled, 49 treated with CDDP and 7 treated with NDP. A course consisted of continuous infusion of 5-FU at 400 mg/m2/day for days 1-5 and 8-12, infusion of CDDP or NDP at 40 mg/m2/day on days 1 and 8, and radiation at 2 Gy/day on days 1 to 5, 8 to 12, and 15 to 19, with a second course repeated after a 2-week interval. Plasma concentrations of 5-FU were determined by high performance liquid chromatography at 5 PM on days 3, 10, 38 and45, and at 5 AM on days 4, 11, 39 and 46. Results and conclusions: The circadian rhythm in plasma concentrations of 5-FU observed in the case of CDDP was altered when NDP was used instead. The clinical response can be predicted by monitoring plasma concentrations of 5-FU in the CDDP group, but not in the NDP group.
Biological Control of Alternaria Fruit Rot of Chili by Trichoderma Species under Field Conditions

Abstract Trichoderma strains were evaluated under field conditions to assay their efficacy in suppressing Alternaria fruit rot disease and promoting chili plant growth. The experiment was conducted at the Botanical Garden, Rajshahi University, Bangladesh from July 2006 to March 2007. Application of Trichoderma harzianum IMI 392432 significantly (p = 0.05) suppressed the disease compared to Alternaria tenuis (T2) treatment and improved both growth and yield. The treatment T4 (T. harzianum IMI-392432 + A. tenuis) was most effective in reducing disease percentage (72.27%) compared to A. tenuis (T1) treatment. The highest seed germination rate (85.56%) and the highest growth and yield (12.5 g/plant) was also recorded in the same treatment (T4), followed by T5 (T. harzianum IMI-392433 + A. tenuis), T6 (T. harzianum IMI-392434 + A. tenuis), T2 (T. virens IMI-392430 + A. tenuis), and T3 (T. pseudokoningii IMI-392431 + A. tenuis) treatment, while single treatment with A. tenuis significantly decreased these values.
MedeA®: Atomistic simulations for designing and testing materials for micro/nano electronics systems

Results of atomic-scale simulations are presented including thermal conductivity, elastic moduli, diffusion, and adhesion. This type of simulations is most conveniently performed with the MedeA® computational environment, which comprises experimental structure databases together with building tools to construct models of complex solids, surfaces, and interfaces for both crystalline and amorphous systems. Central to MedeA® are state-of-the-art modules for the automated calculation of thermodynamic, structural, electronic, mechanical, vibrational, and transport properties combined with the corresponding graphical analysis and visualization tools. These capabilities are illustrated for both inorganic and organic materials. For Si-Ge alloys and amorphous-crystalline silicon superlattices we find a drastic reduction of the thermal conductivity compared with bulk crystalline Si. In addition, the Si-Ge alloys reveal a considerable sensitivity of their thermal conductivity to disorder. The second part of this study addresses properties of epoxy resin based thermosets, including their mechanical stiffness, thermal conductivity, and adhesion on alumina. In addition, we present calculated results for oxygen and water diffusivities in cross-linked epoxy systems and discuss factors influencing such diffusivities as, e.g., mass effects or the concentration of residual hydroxyl groups in the polymer.
Prevalence of Sarcopenia and Its Association with Socioeconomic Status among the Elderly in Tehran

Background Sarcopenia is a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength. It imposes significant costs on health care systems. Socioeconomic status is also the root cause of healthy challenges among the elderly. Therefore, investigating the association between sarcopenia and socioeconomic status is very important to improve healthy ageing of the elderly. The aim of this study was to investigate the prevalence of sarcopenia and its association with socioeconomic status among the elderly in Tehran. Methods Cross-sectional and case-control studies were conducted from August 2014–July 2015 among 310 men and 334 women elderly (60 and over years old) in Tehran health centers. Randomization, restriction and matching were setting during study design to minimize selection bias. Then study participants were recruited via phone call. Participants' phone numbers were already recorded in a telephone book electronically. When there were two elderly people in the same house, only one person was invited randomly. Association between sarcopenia and socio-economic status was analyzed by SPSS version 22. Results The overall prevalence of sarcopenia in the elderly was 16.5%. Prevalenceamong the low-income elderly was relatively higher than (20.5%) that among those with middle income status (18.2%) while in the higher income, the proportion of sarcopenia was very low (12.8%). The findings indicated that 339(52.6%) were in low-income status, 304(47.1%) were in middle-income status and 1(.2%) in high-income class. Conclusion There was a significant association between socioeconomic status and sarcopenia (P-value <0.001). The odd risk of sarcopenia was 0.97 times more likely higher in low socioeconomic class than those who were in middle and high income classes.
Conformational studies of Lewis X and Lewis A trisaccharides using NMR residual dipolar couplings.

The conformations of the histo-blood group carbohydrate antigens Lewis X (Le(x)) and Lewis A (Le(a)) were studied by NMR measurements of one-bond C-H residual dipolar couplings in partially oriented liquid crystal solutions. A strategy for rapid calculation of the difference between theoretical and experimental dipolar couplings of a large number of model structures generated by computer simulations was developed, resulting in an accurate model structure for the compounds. Monte Carlo simulations were used to generate models for the trisaccharides, and orientations of each model were sought that could reproduce the experimental residual dipolar coupling values. For both, Le(a) and Le(x), single low energy models giving excellent agreement with experiment were found, implying a compact rigidly folded conformation for both trisaccharides. The new approach was also applied to the pentasaccharides lacto-N-fucopentaose 2 (LNF-2) and lacto-N-fucopentaose 3 (LNF-3) proving its consistency and robustness. For describing the conformation of tightly folded oligosaccharides, a definition for characterization of ring planes in pyranoside chairs is proposed and applied to the analysis of the relation between the fucose and galactose residues in the epitopes, revealing the structural similarity between them.
The neuropsychiatry of multiple sclerosis: Focus on disorders of mood, affect and behaviour

Neuropsychiatric symptoms are common in multiple sclerosis (MS). They include two broad categories of disturbances: abnormalities in cognition, and abnormalities of mood, affect and behaviour. The present review deals with the epidemiology, clinical features, etiology and treatment of disturbances included in the second category, i.e., major depression, fatigue and sleep disorders, bipolar disorder, euphoria, pathological laughing and crying, anxiety, psychosis and personality changes. Major depression is one of the most common neuropsychiatric disorders in MS with an approximate 50% lifetime prevalence rate. Early recognition and management of depression in MS is of major importance because it is a key predictor of morbidity, mortality, quality of life, possibly physical outcome and disease exacerbations, adherence to immunomodulatory treatments and suicide risk in MS patients, as well as of the caregiver's distress and quality of life. The etiopathogenesis of neuropsychiatric disorders in MS has been incompletely investigated. It is postulated that a complex interplay of biological, disease-related, behavioural and psychosocial factors contribute to the pathophysiology of most of them. Management of neuropsychiatric symptoms in MS is often effective, although commonly based on evidence provided by case studies and uncontrolled trials. A comprehensive biopsychosocial neuropsychiatric approach is essential for the optimal care of patients with MS.
Crowdsensing in the Wild with Aliens and Micropayments

This article presents results and lessons learned from two user studies on crowdsensing incentives-specifically, on mobile gaming and micropayments. The analysis of the results suggests that gaming is a cost-effective solution for uniform area coverage, whereas micropayments work well for sensing tasks with tight time constraints or for long-term tasks for personal analytics.
The Provision of Time to the Elderly by Their Children

This paper uses matched data on the elderly and their children to study the provision of time by children to the elderly. It develops a Tobit model as well as a structural model to analyze the determinants of this decision. The main determinants of the amount of time given to parents appear to be the parent's age, reported health, and institutionalization status, and the children's age, health, and sex. Older parents, less healthy parents, and non-institutionalized parents receive more time from their children, while younger children, healthier children, and female children provide more time. In contrast to these demographic determinants, economic variables, such as children's wage rate and income levels, appear to play a rather insignificant role in the provision of time. In addition, the evidence does not support the hypothesis that parents purchase time from their children.
Returns to Education in Bangladesh

Abstract This paper reports labour market returns to education in Bangladesh using data from recent nationwide household survey. Returns are estimated separately for rural and urban samples, males, females and private‐sector employees. Substantial heterogeneity in returns is observed; for example, estimates are higher for urban (than rural sample) and female samples (compared with their male counterparts). Our ordinary least square estimates of returns to education are robust to control for types of schools attended by individuals and selection into waged work.
Combating Terrorism: How Prepared Are State and Local Response Organizations?

Abstract : Since the 9/11 attacks on the World Trade Center and the Pentagon, state and local governments and response organizations have focused attention on preparing for and responding to acts of domestic terrorism. Of particular concern has been improving state and local response capabilities for dealing with terrorist incidents involving weapons of mass destruction (WMD), i.e., biological, radiological, chemical, or nuclear weapons. Much activity has focused on what the federal government itself can do to better support the efforts of state and local organizations in the war on terrorism. The Advisory Panel to Assess Domestic Response Capabilities for Terrorism Involving Weapons of Mass Destruction (also known as the Gilmore Commission) was established by Congress on October 17, 1998, to evaluate the progress of federal preparedness programs for local emergency response and to recommended strategies for effective coordination of preparedness and response efforts between federal, state, and local government and response organizations. As part of its support for this effort, just prior to the 9/11 terrorist attacks, RAND conducted the first wave of a nationwide survey to gather in-depth data about state and local response organizations' assessments of federal preparedness programs for combating terrorism. Follow-on surveys were conducted in 2002 and 2003. The surveys gathered in-depth data on the planning and preparedness activities of the key professional communities involved in preparedness and emergency response: law enforcement, fire services, offices of emergency management, emergency medical services, hospitals, and public health agencies. This national survey provides the first comprehensive picture of efforts in the two years following the 9/11 attacks to improve the nation's preparedness for terrorism. This reports presents a summary of results from the third wave of the survey, conducted in 2003.
Linear Discriminant Trees

We discuss and test empirically the eects of six dimensions along which existing decision tree induction algorithms dier. These are: Node type (univariate versus multivariate), branching factor (two or more), grouping of classes into two if the tree is binary, error (impurity) measure, and the methods for minimization to nd the best split vector and threshold. We then propose a new decision tree induction method that we name linear discriminant trees (LDT) which uses the best combination of these criteria in terms of accuracy, simplicity and learning time. This tree induction method can be univariate or multivariate. The method has a supervised outer optimization layer for converting a K > 2-class problem into a sequence of two-class problems and each two-class problem is solved analytically using Fisher’s Linear Discriminant Analysis (LDA). On twenty datasets from the UCI repository, we compare the linear discriminant trees with the univariate decision tree methods C4.5 and C5.0, multivariate decision tree methods CART, OC1, QUEST, neural trees and LMDT. Our proposed linear discriminant trees learn fast, are accurate, and the trees generated are small.
Title of Document: LOCAL ENSEMBLE TRANSFORM KALMAN FILTER WITH REALISTIC OBSERVATIONS

Title of Document: LOCAL ENSEMBLE TRANSFORM KALMAN FILTER WITH REALISTIC OBSERVATIONS Hong Li, Doctor of Philosophy, 2007 Directed By: Professor Eugenia Kalnay Department of Atmospheric and Oceanic Science The main goal of my research is to improve the performance of the EnKF in assimilating real observations in order to accelerate the development of EnKF systems towards operational applications. A Local Ensemble Transform Kalman Filter (LETKF, Hunt et al. 2007) is used as an efficient representative of other EnKF systems. This dissertation has addressed several issues relating to the EnKF for assimilating real data. The first issue is model errors. We assimilated observations generated from the NCEP/NCAR reanalysis fields into the SPEEDY model. The performance of the LETKF without accounting for model errors is seriously degraded compared with that in the perfect model scenario. We then investigated several methods to handle model errors including model bias and system-noise. Our results suggest that the pure bias removal methods (DdSM and LDM) are not able to beat the multiplicative or additive inflation schemes that account for the effects of total model errors. By contrast, when the bias removal methods (DdSM+ and LDM+) are supplemented by additive noise for representing the system-noise, they outperform the inflation schemes. Of these augmented methods, the LDM+, where the constant bias, diurnal bias and statedependent errors are estimated from a large sample of 6-hour forecast errors, gives the best results. The other two issues addressed are the estimation of the inflation factor and of observation error variance. Without the accurate observation error statistics, a scheme for adaptively estimating inflation alone does not work, and vice versa. We propose to estimate simultaneously both the adaptive inflation and observation error variance. Our results for the Lorenz-96 model examples suggest that the simultaneous approach works perfectly in the perfect model scenario and in the presence of random model errors. For the case of systematic model bias, although it underestimates the observation error variance, our algorithm produces analyses that are comparable with the best tuned inflation value. SPEEDY model experiments indicate that our method is able to retrieve the true error variance for different types of instrument separately when applied to a more realistic high-dimension model. Our research in this dissertation suggests the need to develop a more advanced LETKF with both bias correction and adaptive estimation of inflation within the system. LOCAL ENSEMBLE TRANSFORM KALMAN FILTER WITH REALISTIC OBSERVATIONS