Miracle-dz/UniFAR-FTUs huggingface dataset:
First stars VII - Lithium in extremely metal poor dwarfs

Context. The primordial lithium abundance is a key prediction of models of big bang nucleosynthesis, and its abundance in metal-poor dwarfs (the Spite plateau) is an important, independent observational constraint on such models. Aims. This study aims to determine the level and constancy of the Spite plateau as definitively as possible from homogeneous highquality VLT-UVES spectra of 19 of the most metal-poor dwarf stars known. Methods. Our high-resolution (R ∼ 43 000), high S /N spectra are analysed with OSMARCS 1D LTE model atmospheres and turbospectrum synthetic spectra to determine effective temperatures, surface gravities, and metallicities, as well as Li abundances for our stars. Results. Eliminating a cool subgiant and a spectroscopic binary, we find 8 stars to have −3.5 < [Fe/H] < −3. 0a nd 9s tars with −3.0 < [Fe/H] < −2.5. Our best value for the mean level of the plateau is A(Li) = 2.10 ± 0.09. The scatter around the mean is entirely explained by our estimate of the observational error and does not allow for any intrinsic scatter in the Li abundances. In addition, we conclude that a systematic error of the order of 200 K in any of the current temperature scales remains possible. The iron excitation equilibria in our stars support our adopted temperature scale, which is based on a fit to wings of the Hα line, and disfavour hotter scales, which would lead to a higher Li abundance, but fail to achieve excitation equilibrium for iron. Conclusions. We confirm the previously noted discrepancy between the Li abundance measured in extremely metal-poor turnoff stars and the primordial Li abundance predicted by standard Big-Bang nucleosynthesis models adopting the baryonic density inferred from WMAP. We discuss recent work explaining the discrepancy in terms of diffusion and find that uncertain temperature scales remain a major question.
Expanding Parallel Resources for Medium-Density Languages for Free

We discuss a previously proposed method for augmenting parallel corpora of limited size for the purposes of machine translation through monolingual paraphrasing of the source language. We develop a three-stage shallow paraphrasing procedure to be applied to the Swedish-Bulgarian language pair for which limited parallel resources exist. The source language exhibits specifics not typical of high-density languages already studied in a similar setting. Paraphrases of a highly productive type of compound nouns in Swedish are generated by a corpus-based technique. Certain Swedish noun-phrase types are paraphrased using basic heuristics. Further we introduce noun-phrase morphological variations for better wordform coverage. We evaluate the performance of a phrase-based statistical machine translation system trained on a baseline parallel corpus and on three stages of artificial enlargement of the source-language training data. Paraphrasing is shown to have no effect on performance for the Swedish-English translation task. We show a small, yet consistent, increase in the BLEU score of Swedish-Bulgarian translations of larger token spans on the first enlargement stage. A small improvement in the overall BLEU score of Swedish-Bulgarian translation is achieved on the second enlargement stage. We find that both improvements justify further research into the method for the Swedish-Bulgarian translation task.
Making radiance and irradiance caching practical: adaptive caching and neighbor clamping

Radiance and irradiance caching are efficient global illumination algorithms based on interpolating indirect illumination from a sparse set of cached values. In this paper we propose an adaptive algorithm for guiding spatial density of the cached values in radiance and irradiance caching. The density is adapted to the rate of change of indirect illumination in order to avoid visible interpolation artifacts and produce smooth interpolated illumination. In addition, we discuss some practical problems arising in the implementation of radiance and irradiance caching, and propose techniques for solving those problems. Namely, the neighbor clamping heuristic is proposed as a robust means for detecting small sources of indirect illumination and for dealing with problems caused by ray leaking through small gaps between adjacent polygons.
Essays on Insurance Economics

Is the relationship between insurance consumption and its determinants spurious? Is general insurance a luxury service? Do bequest motives matter for life insurance consumption? Is private credit important for the development of life insurance? Do socioeconomic development and informal risk sharing institutions matter for formal insurance consumption? This thesis investigates these and other related issues using international datasets and relatively new panel data method, namely the Common Correlated Effects Pooled (CCEP) estimator. A novelty of the CCEP is that it takes into account the impacts of unobserved common factors. The thesis consists of an introduction, three empirical chapters and conclusions. Chapter 2 studies the relationship between nonlife insurance consumption and income/wealth per capita. Estimation results suggest that income elasticity is below unity and that nonlife insurance is positively related to GDP per capita, the law, risk aversion, infrastructural development, and negatively related to socioeconomic development. Chapter 3 explores life insurance consumption driven by bequest motives. We found that life insurance consumption is positively related to GDP per capita, old age dependency ratio, infrastructural development, and social security and welfare; and negatively related to the extended family institution, savings, inflation, and risk aversion. Estimation results suggest the presence of altruistic, and bequest as exchange old age security motives. Chapter 4 investigates the long run relationship and causality direction between private credit consumption and life insurance development. Life insurance development may be explained by GDP per capita, formal and informal credit consumption, infrastructural development, life expectancy, institutional quality, inflation, and Islam, and Orthodox being the dominant religions. Cointegration test results suggest that life and nonlife insurance consumption and its determinants exhibit a long run relationship; and that there is a long run bidirectional causality relationship between life insurance development and private credit consumption. The thesis concludes that insurance development requires institutional and infrastructural development-in particulartelecommunications infrastructure, to facilitate cost effective insurance supply.
Potential Therapeutic Role of Phosphodiesterase Type 5 Inhibition in Hypertension and Chronic Kidney Disease

Chronic kidney disease (CKD) is common, affecting 13% of adults in the United States, with 8% having an estimated glomerular filtration rate (eGFR) of <60 mL/min per 1.73 m2 in the survey from National Health and Nutrition Examination Survey (1999–2004). 1 Prevalence is likely to increase further with an aging population and high levels of obesity, hypertension, and diabetes mellitus and has emerged as a major public health concern worldwide. Importantly, despite increased awareness and treatment of hypertension in patients with CKD, blood pressure (BP) control rates are low.2 The presence of CKD is an independent risk factor for the development of cardiovascular disease (CVD),3 showing a graded risk of cardiovascular events, hospitalizations, and all-cause mortality as eGFR declines, with a sharp rise in events as eGFR falls <45 mL/min per 1.73 m2.4 The 1998 National Kidney Foundation Task Force on Cardiovascular Disease in Chronic Renal Disease report5 emphasized the high prevalence of CVD in CKD and revealed that cardiovascular mortality, defined as death caused by arrhythmias, cardiomyopathy, cardiac arrest, myocardial infarction, atherosclerotic heart disease, or pulmonary edema, is 10 to 30× higher in dialysis patients than in the general population. In fact, the risk of CVD in people with CKD far outweighs the risk of progression, with ≈70% of patients with CKD in a large retrospective study dying of cardiovascular events, whereas only 4% started renal replacement therapy.6,7 Hence, in this area of considerable unmet medical need, we require new therapies that will lower BP, slow the progression of CKD, and minimize cardiovascular risk. This will not only reduce the number of patients reaching end-stage renal disease and the requirement for dialysis but also alleviate the significant incremental burden of CVD with which worsening CKD is associated. In recent …
A historical perspective on the Federal Reserve's monetary aggregates

Data on the monetary aggregates are the fundamental raw material for research in many facets of economics and finance. Money demand modeling, measurement of money stock announcement effects, tests of the rationality of preliminary money stock forecasts and financial market efficiency, and comparison of alternative seasonal adjustment procedures are just a few such areas. Working in the spirit of Friedman and Schwartz, we chronicle the evolution of the Federal Reserve's monetary aggregates. Numerous changes in data sources, definitions, revision procedures, and seasonal adjustment methods suggest caution for all researchers using monetary aggregate time series data. A timeline compiled by Kenneth Kavajecz shows each redefinition, revision and special event that affected the monetary aggregates from 1960-1993.
DSET++: A robust clustering algorithm

Clustering image pixels is an important technique in image segmentation. While normalized cuts is popularly used in image segmentation, dominant set clustering is another promising method and shown to outperform normalized cuts in some experiments. However, dominant set clustering suffers from the problems of sensitiveness to distance measures and over-segmentation tendency. In this paper we present DSET++ to enhance the original dominant set clustering and solve the two problems. Firstly, we use the histogram equalization in image enhancement to transform the similarity matrix and eliminate the sensitiveness to distance measures. In the second step we extend the dominant set based on density information to overcome the tendency of over-segmentation. Preliminary experiments on data clustering tasks validate the effectiveness of DSET++ clustering.
Political Pressure, Rhetoric and Monetary Policy: Lessons for the European Central Bank

Review of the literature political pressure in OECD countries before elections the rhetoric of central banks a new indicator for (political) pressure the role of public support the European context - an economic analysis the European context - a political assessment the impact of EMU enlargement conclusion A - Germany's institutional setting B - the refined "corridor" for the standard deviation C - data sources.
EEG Signal Classification for Brain Computer Interface Applications

2 Statement . 3 List of Figures. 7 List of Tables . 9 1. Preliminary. 10 1.1. Motivation. 10 1.2. Objectives. 10 2. Principles of electroencephalography. 11 2.1. The Nature of the EEG signals. 11 2.2. EEG wave groups. 13 3. Brain Computer Interface Technology. 17 3.1. System Overview. 17 3.2. Neuropsychological signals used in BCI applications. 19 3.3. BCI research: existing systems. 23 4. EEG Signal Pre Processing. 29 4.1. Removing EEG artifacts by ICA blind source separation. 31 4. 2. Artifact rejection based on peak elimination. 33 4. 3. Blinking artifact recognition using artificial neural network. 34 4. 4. Artifact rejection based in bandpass FIR filters. 34 5. EEG Signal Classification. 36 5.
Effective Monetary Policy Strategies in New Keynesian Models: A Reexamination

We explore the importance of the nature of nominal price and wage adjustment for the design of effective monetary policy strategies, especially at the zero lower bound. Our analysis suggests that sticky-price and sticky-information models fit standard macroeconomic time series comparably well. However, the model with information rigidity responds differently to anticipated shocks and persistent zero-lower bound episodes - to a degree important for monetary policy and for understanding the effects of fundamental disturbances when monetary policy cannot adjust. These differences may be important for understanding other policy issues as well, such as fiscal multipliers. Despite these differences, many aspects of effective policy strategy are common across the two models: In particular, highly inertial interest rate rules that respond to nominal income or the price level perform well, even when hit by adverse supply shocks or large demand shocks that induce the zero-lower bound. Rules that respond to the level or change in the output gap can perform poorly under those conditions.
Agents with faces: the effect of personification

It is still an open question whether software agents should be personified in the interface. In order to study the effects of faces and facial expressions in the interface a series of experiments was conducted to compare subjects' responses to and evaluation of different faces and facial expressions. The experimental results obtained demonstrate that: (1) personified interfaces help users engage in a task, and are well suited for an entertainment domain; (2) people's impressions of a face in a task are different from ones of the face in isolation. Perceived intelligence of a face is determined not by the agent's appearance but by its competence; (3) there is a dichotomy between user groups which have opposite opinions about personification. Thus, agent-based interfaces should be flexible to support the diversity of users' preferences and the nature of tasks.
Impacts of information technology (IT) outsourcing on organizational performance: A firm-level empirical analysis

We investigate the impact of Information Technology (IT) outsourcing on firm performance from several dimensions, including changes in labor productivity, improvements in financial and operational performance variables, and stock market valuation of IT outsourcing initiatives as measured by Tobin’s q. While our main objective is to better understand the economics of IT outsourcing, we also aim to contribute to the literature on the business value of IT in general. Our research contributes to the relevant literature from the following perspectives: (i) the change in the performance levels of firms due to IT outsourcing is measured against that of firms not outsourcing at all, (ii) panel data regression model is utilized in order to capture both cross-sectional and time-series differences among firms, (iii) the diversity of IT outsourcing initiatives is explicitly considered in the model, and (iv) a comprehensive data set covering the period between 1984 and 2007 is used.
Impact of the Body Mass on Complications and Outcome in Multiple Trauma Patients: What Does the Weight Weigh?

Obesity is known as an independent risk factor for various morbidities. The influence of an increased body mass index (BMI) on morbidity and mortality in critically injured patients has been investigated with conflicting results. To verify the impact of weight disorders in multiple traumatized patients, 586 patients with an injury severity score >16 points treated at a level I trauma center between 2005 and 2011 were differentiated according to the BMI and analyzed regarding morbidity and outcome. Plasma levels of interleukin- (IL-) 6 and C-reactive protein (CRP) were measured during clinical course to evaluate the inflammatory response to the “double hit” of weight disorders and multiple trauma. In brief, obesity was the highest risk factor for development of a multiple organ dysfunction syndrome (MODS) (OR 4.209, 95%-CI 1.515–11.692) besides injury severity (OR 1.054, 95%-CI 1.020–1.089) and APACHE II score (OR 1.059, 95%-CI 1.001–1.121). In obese patients as compared to those with overweight, normal weight, and underweight, the highest levels of CRP were continuously present while increased systemic IL-6 levels were found until day 4. In conclusion, an altered posttraumatic inflammatory response in obese patients seems to determine the risk for multiple organ failure after severe trauma.
Toward an Overall Analytical Framework for the Integrated Sustainability Assessment of the Production and Supply of Raw Materials and Primary Energy Carriers

The sustainable production and supply of raw materials (“nonenergy raw materials”) and primary energy carriers (“energy raw materials”) is a core element of many policies. The natural resource base for their production and supply, and the access thereto, are limited. Moreover, raw material supply is high on environmental and social impact agendas as well. A broad, quantitative framework that supports decision makers is recommended so as to make use of raw materials and primary energy carriers more sustainably. First, this article proposes a holistic classification of raw materials and primary energy carriers. This is an essential prerequisite for developing an integrated sustainability assessment framework (ISAF). Indeed, frequently, only a subset of raw materials and primary energy carriers are considered in terms of their source, sector, or final application. Here, 85 raw materials and 30 primary energy carriers overall are identified and grouped into seven and five subgroups, respectively. Next, this article proposes a quantitative ISAF for the production and supply of raw materials and primary energy carriers, covering all the sustainability pillars. With the goal of comprehensiveness, the proposed ISAF integrates sustainability issues that have been covered and modeled in quite different quantitative frameworks: ecosystem services; classical life cycle assessment (LCA); social LCA; resource criticality assessment; and particular international concerns (e.g., conflict minerals assessment). The resulting four areas of concerns (i.e., environmental, technical, economic, and social/societal) are grouped into ten specific sustainability concerns. Finally, these concerns are quantified through 15 indicators, enabling the quantitative sustainability assessment of the production and supply of raw materials and primary energy carriers.
Learning context sensitive similarity measure on pair fusion graph

In this paper, we present a new approach for shape/image retrieval by efficiently fusing different shape similarities, called Pair-Graph Diffusion. Different from other algorithms which linearly integrate different similarity measures, our algorithm adopts Tensor Product Graph(TPG) to combine two shape similarities by fusing two single-graphs into a multi-graph for fusion process. In such way, we gain more shape information in a higher order, and the multigraph is able to better reveal the intrinsic relation between shapes especially when the two input similarities are very complementary. We perform the experiments on two popular image datasets: MPEG-7 shape dataset and Nistér and Stewénius (N-S) dataset, and achieve state-of-arts retrieval rates: 98.87% on MPEG-7 dataset and 3.69 on N-S dataset. The results demonstrate that the proposed method can effectively fuse two similarities. In addition, Multi-graph Diffusion is a general similarity learning algorithm, and it can be easily applied other tasks for ranking/retrieval.
Reynolds number limits for jet propulsion: A numerical study of simplified jellyfish

The Scallop Theorem states that reciprocal methods of locomotion, such as jet propulsion or paddling, will not work in Stokes flow (Reynolds number = 0). In nature the effective limit of jet propulsion is still in the range where inertial forces are significant. It appears that almost all animals that use jet propulsion swim at Reynolds numbers (Re) of about 5 or more. Juvenile squid and octopods hatch from the egg already swimming in this inertial regime. The limitations of jet propulsion at intermediate Re is explored here using the immersed boundary method to solve the two-dimensional Navier Stokes equations coupled to the motion of a simplified jellyfish. The contraction and expansion kinematics are prescribed, but the forward and backward swimming motions of the idealized jellyfish are emergent properties determined by the resulting fluid dynamics. Simulations are performed for both an oblate bell shape using a paddling mode of swimming and a prolate bell shape using jet propulsion. Average forward velocities and work put into the system are calculated for Reynolds numbers between 1 and 320. The results show that forward velocities rapidly decay with decreasing Re for all bell shapes when Re<10. Similarly, the work required to generate the pulsing motion increases significantly for Re<10. When compared actual organisms, the swimming velocities and vortex separation patterns for the model prolate agree with those observed in Nemopsis bachei. The forward swimming velocities of the model oblate jellyfish after two pulse cycles are comparable to those reported for Aurelia aurita, but discrepancies are observed in the vortex dynamics between when the 2D model oblate jellyfish and the organism.
A Method for Text Summarization by Bacterial Foraging Optimization Algorithm

Due to rapid and increasingly growth of electronic texts and documents, we need some techniques for integration, communication and appropriate utilization of these texts. Summarizing the literature is one of the most fundamental tasks for integrating and taking advantages of these gathered texts. Selecting key words and then integrating them as a summary text, is the most common method in text summarization. In this paper we present a new method of automatic text summarization, with bacterial foraging optimization. The main idea of this method, is weighting words, then valuing the sentences, and finally extracting key sentences from the text, as the summarized text. It should be noted that, here we used the weighting term TF-IDF method, to determine weight for each text. Also, the bacterial foraging optimization used to converge the solutions is obtained from each bacteria, and finally the best candidate summarized text is given.
Comparing Block Cipher Modes of Operation on MICAz Sensor Nodes

Wireless sensor networks are a key technology for "ubiquitous computing" applications. The challenges of securing such networks are tremendous. On the one side, sensor nodes are commonly deployed in potentially hostile environments, which requires additional protection in comparison to traditional computing systems. On the other side, the capabilities of sensor nodes in terms of computing power, memory, and available energy are severely limited, which makes it hard to adapt existing security solutions. In this paper, we examine different options for providing confidentiality and message authentication to sensor network communication. More specifically, we examine four modern block cipher modes of operation regarding their applicability in sensor networks. These are the Offset Codebook mode (OCB), the Counter Cipher Feedback with Header mode (CCFB+H), the EAX mode, and the Galois/Counter mode (GCM). Our practical evaluation targets the MICAz sensor node and accounts for the typically small packet size of sensor network traffic. Our results indicate that the CCFB+H mode is the best choice for a large range of applications.