Miracle-dz/UniFAR-FTUs huggingface dataset:
Rational versus Plausible Accounting Equivalences in Preference Judgments

Subjective expected utility (SEU) embodies four distinct principles of rational behavior. Although all have been called into some question empirically, the least plausible and least studied is the property that formally equivalent gambles are treated as indifferent in preference. The paper describes some results that arise when this property is sharply weakened and to some degree replaced by alternative rational and not-so-rational-assumptions. The resulting utility representations, like SEU, are weighted averages of the utilities of consequences, but with the weights dependent on more than the underlying chance event. In rank-dependent cases, which arise from a restricted assumption about formally equivalent gambles, the weights depend on the rank position of the corresponding consequence. In rank- and sign-dependent models, they depend both on the rank position of the consequence associated to the event and on whether it is a gain or a loss. The theory giving rise to the latter involves an additional primitive, namely, joint receipt of gambles, in terms of which new rational and irrational assumptions are invoked. The result generalizes prospect theory to gambles with more than a single gain and a single loss.
Conformation of the synthetic DNA poly(amino2dA-dT) duplex in high-salt and aqueous alcohol solutions

It has previously been demonstrated by other workers that the duplex of a synthetic DNA poly(amino2dA-dT) undergoes a salt-induced conformational isomerization. We show in the present work using circular dichroism that the same isomerization is induced in poly(amino2dA-dT) by various alcohols. The isomerization was originally identified as the B-to-Z and then B-to-A conformational transition of DNA but we demonstrate that the high-salt or alcohol conformation of poly (amino2dA-dT) is the non Z-DNA zig-zag double helix we have previously observed with poly(dA-dT) and called X-DNA. X-DNA is a cesium cation specific conformation of poly(dA-dT) while no similar cation specificity is observed with poly(amino2dA-dT). Thus it appears that the extra amino group attached to A and cesium cations make the same thing; they probably dehydrate the double helix minor groove and relieve its conformational variability. Poly(amino2dA-dT) is exceptionally stable in X-DNA and conditions inducing it are mild, which opens the door to assess its molecular structure.
Leptin regulation of the immune response and the immunodeficiency of malnutrition 1

Leptin is a 16 kDa protein mainly produced by adipose tissue in proportion to adipose tissue mass. Originally thought to be a satiety factor, leptin is a pleiotropic molecule. In addition to playing a role in energy regulation, leptin also regulates endocrine and immune functions. Both the structure of leptin and that of its receptor suggest that leptin might be classified as a cytokine. The secondary structure of leptin has similarities to the long‐chain helical cytokines family, which includes interleukin 6 (IL‐6), IL‐11, CNTF, and LIF, and the leptin receptor is homologous to the gp‐130 signal‐transducing subunit of the IL‐6‐type cytokine receptors. Leptin plays a role in innate and acquired immunity. Leptin levels increase acutely during infection and inflammation, and may represent a protective component of the host response to inflammation. More important, leptin deficiency increases susceptibility to infectious and inflammatory stimuli and is associated with dysregulation of cytokine production. Leptin deficiency also causes a defect in hematopoiesis. Leptin regulates T cells responses, polarizing Th cells toward a Th1 phenotype. Low leptin levels occurring during starvation mediate the neuroendocrine and immune dysfunction of starvation. —Faggioni, R. , Feingold, K. R. , Grunfeld, C. Leptin regulation of the immune response and the immunodeficiency of malnutrition. FASEB J. 15, 2565–2571 (2001)
Perfect synthesis for all of the people all of the time

The quality of speech synthesis has drastically improved over the last ten years. Or at least it appears that this is the case. We have moved from diphones to unit selection. However, although we can produce much more natural sounding examples we have also given up an certain amount of control over what can be synthesized. We have reached the stage where playing a few examples to a non-expert can easily convince them that speech synthesis is a solved problem. This paper looks at how we might not only convince some of the people some of the time, but what we must do to produce perfect synthesis for all of the people all of the time.
Statistical Machine Translation for Indian Languages: Mission Hindi

This paper discusses Centre for Development of Advanced Computing Mumbai’s (CDACM) submission to the NLP Tools Contest on Statistical Machine Translation in Indian Languages (ILSMT) 2014 (collocated with ICON 2014). The objective of the contest was to explore the effectiveness of Statistical Machine Translation (SMT) for Indian language to Indian language and English-Hindi machine translation. In this paper, we have proposed that suffix separation and word splitting for SMT from agglutinative languages to Hindi significantly improves over the baseline (BL). We have also shown that the factored model with reordering outperforms the phrase-based SMT for EnglishHindi (en-hi). We report our work on all five pairs of languages, namely Bengali-Hindi (be-hi), Marathi-Hindi (mrhi), Tamil-Hindi (ta-hi), Telugu-Hindi (tehi), and en-hi for Health, Tourism, and General domains.
Why Should Theorists Care about Social Capital

Social capital is embedded in social networks. For the purpose of these notes, I use the terms social capital and social networks interchangeably. At the most basic level it is useful to think of social capital in a supply-demand framework. Individual agents have some demand for social capital. More precisely, agents have demand for the services provided by social capital such as having access to the support of friends in times of need. Agents ’purchase’ access to the services provided by the community by producing links to other members of the community. The joint investments of all agents in building links determine the level of supply of social capital.
What makes workers happy?

This article answers the question what makes workers happy? It does so by combining insights from micro-economics, sociology and psychology. Basis is the standard utility function of a worker that includes income and hours of work and is elaborated with job characteristics. In this way it is possible to answer whether part-time workers are happier than full-time workers. The utility function is estimated on basis of the European Social Survey 2004 which contains all necessary information. The results show that workers optimize income and hours of work as predicted by micro-economics, but also that part-time workers are happier than full-time workers. Challenging work with a high level of autonomy makes the workers happy, work pressure makes workers unhappy. Higher educated workers are unhappier than lower educated workers, we find a negative effect of education, but this is compensated by the type of jobs these higher educated hold.
Managing the complexity of SPI in small companies

Most known models for SPI (e.g. SEI CMM, ISO standards and other methods derived from those mentioned) are primarily suited for large or medium organizations, but with some tailoring they provide substantial support also for the SPI in small organizations considering their specific characteristics. In the article a case of such tailoring – the PROCESSUS model – is presented. The baseline of the methodology is the integration of the CMM and the ISO 9001 together with the ISO 9000-3. According to the integrated model and the study of different lifecycles, a set of standard procedures (SP) and standard documents (SD) was defined. Each standard procedure provides guidelines on how to perform related activities, who is involved, which documents are supposed to be used/derived within the procedure etc. The set of SP and SD is the essential help for SPI conduction – for the purpose of small companies the optimal use of suggested documents and the disposition of roles was defined. The SP-SD set is also described in the article. Copyright © 2000 John Wiley & Sons Ltd
Prior elicitation, variable selection and Bayesian computation for logistic regression models

Bayesian selection of variables is often difficult to carry out because of the challenge in specifying prior distributions for the regression parameters for all possible models, specifying a prior distribution on the model space and computations. We address these three issues for the logistic regression model. For the first, we propose an informative prior distribution for variable selection. Several theoretical and computational properties of the prior are derived and illustrated with several examples. For the second, we propose a method for specifying an informative prior on the model space, and for the third we propose novel methods for computing the marginal distribution of the data. The new computational algorithms only require Gibbs samples from the full model to facilitate the computation of the prior and posterior model probabilities for all possible models. Several properties of the algorithms are also derived. The prior specification for the first challenge focuses on the observables in that the elicitation is based on a prior prediction y0 for the response vector and a quantity a0 quantifying the uncertainty in y0. Then, y0 and a0 are used to specify a prior for the regression coefficients semi‐automatically. Examples using real data are given to demonstrate the methodology.
‘In general, how do you feel today?’ – self-rated health in the context of aging in India

This thesis is centered on self-rated health (SRH) as an outcome measure, as a predictor, and as a marker. The thesis uses primary data from the WHO Study on global AGEing and adult health (SAGE) implemented in India in 2007. The structural equation modeling approach is employed to understand the pathways through which the social environment, disability, disease, and sociodemographic characteristics influence SRH among older adults aged 50 years and above. Cox proportional hazard model is used to explore the role of SRH as a predictor for mortality and the role of disability in modifying this effect. The hierarchical ordered probit modeling approach, which combines information from anchoring vignettes with SRH, was used to address the long overlooked methodological concern of interpersonal incomparability. Finally, multilevel model-based small area estimation techniques were used to demonstrate the use of large national surveys and census information to derive precise SRH prevalence estimates at the district and sub-district level. The thesis advocates the use of such a simple measure to identify vulnerable communities for targeted health interventions, to plan and prioritize resource allocation, and to evaluate health interventions in resource-scarce settings. The thesis provides the basis and impetus to generate and integrate similar and harmonized adult health and aging data platforms within demographic surveillance systems in different regions of India and elsewhere.
Dynamic Motion Models

Real-time animation of virtual characters is a demanding task. We propose dynamic motion models which can create the motion of a virtual character in different styles and have the ability to change the animation while it is played. The motions are created by blending and changing given base motions which contain animation data and additional information. The blending and manipulation operations on the animation data build up a motion tree which can be altered dynamically in real-time. This allows to change the animation of a motion model while its animation is played. Motion trees of different motion models are blended together to build a motion tree which represents the complete animation of the character. This tree is constructed and dynamically changed according to user commands.
Change detection in remotely sensed images using an ensemble of multilayer perceptrons

In the proposed work, a change detection technique is developed using a combination of multilayer perceptrons (MLPs). At the onset, the different MLPs are trained with the labeled patterns. Then, the support values (or, the output values) for the unlabeled patterns are obtained from these trained MLPs. At last, decision regarding the class assignment for the unlabeled patterns has been made by fusing the outcome (i.e., support values) obtained from different trained MLPs. In the present experiment, `mean rule' and `majority voting' are used as combination rules. Experiments are carried out on multi-temporal and multi-spectral remotely sensed images. Results for the proposed methodology are found to be encouraging.
Playing Cool: The Sustainable Cool Cubby

PLAYING IN CUBBY HOUSES has been a long tradition with children. When a cubby house is given sustainable lifestyle components—that is, converted into a ‘Cool Cubby’—how does this influence awareness about sustainability? Since 2009 there have been significant innovations in Australia to promote sustainable practices, and the Cool Cubbies Project is a small-scale example of such an initiative. Giving cubby houses sustainable components is innovative, and represents a play-based approach to teaching, in line with early childhood principles of learning. This paper reports on an evaluation of the Cool Cubbies Project (Rous Water, 2015). Cubby houses in five preschools were converted into Cool Cubbies by adding features of sustainable living, including biodiversity, water, waste and energy. An evaluation of the impact of Cool Cubbies raised awareness about sustainable living with young children, educators, families and community. This is a key example of developing resources to support a more sustainable future, through the act of creating a learning resource grounded in sustainable practices for children's play.
Brainstorming +: Towards a tool for decision-making In the Web 2.0

Web 2.0 to democratize access to information by providing a platform fairly comprehensive, free, open and often gratuitous, which allows players with little technical knowledge to participate and take ownership of the new features of the web. It is in this context where this article is positioned being part of a series of scientific research conducted by our research team, which focuses on Web 2.0 and collaborative decision-making on the net. It aims to propose a new social tool that is based on the method thereby providing a brainstorming technique for generating ideas that stimulates creative collaborative thinking done by users of the web to find the maximum ideas in a minimum time with differed opinion. In this context, we will rely on the participation of users to contribute to the accumulation and sharing of information thereby creating social communities. Our tool combined the features of a blog and a social network in addition to brainstorming techniques, it will be powered by the meeting of a set of investments classified according to decisions themes to achieve the end result in the end with a blog of decisions made in these virtual meetings. For its implementation, we propose a unified modelisation using the language UML to model its various processes.
Using Bayesian statistical methods to determine the level of error in large spreadsheets.

Spreadsheets are ubiquitous with evidence that Microsoft Excel, the leading application in the area, has an install base of 90% on end-user desktops. Nowhere is the usage of spreadsheets more extensive or more critical than in the financial sector, where regulations such as the Sarbanes-Oxley Act of 2002 has placed added pressure on organisations to ensure spreadsheets are error-free. This paper outlines the research that has been carried out into the use of Bayesian Statistical methods to estimate the level of error in large spreadsheets based on expert knowledge and spreadsheet test data. The estimate can aid in the decision to accept or re-examine a large time consuming spreadsheet.
A Prospective Multicenter Study of Staphylococcus aureus Bacteremia: Incidence of Endocarditis, Risk Factors for Mortality, and Clinical Impact of Methicillin Resistance

Our objectives were to determine the incidence of endocarditis in patients whose Staphylococcus aureus bacteremia was community-acquired, related to hemodialysis, or hospital-acquired; to assess clinical factors that would reliably distinguished between S. aureus bacteremia and S. aureus endocarditis; to assess the emergence of methicillin-resistant S. aureus (MRSA) as a cause of endocarditis; and to examine risk factors for mortality in patients with S. aureus endocarditis.We conducted a prospective observational study in 6 university teaching hospitals; we evaluated 505 consecutive patients with Staphylococcus aureus bacteremia. Thirteen percent of patients with S. aureus bacteremia were found to have endocarditis, including 21% with community-acquired S. aureus bacteremia, 5% with hospital-acquired bacteremia, and 12% on hemodialysis. Infection was due to MRSA in 31%. Factors predictive of endocarditis included underlying valvular heart disease, history of prior endocarditis, intravenous drug use, community acquisition of bacteremia, and an unrecognized source. Twelve patients with bacteremia had a prosthetic valve; 17% developed endocarditis. Unexpectedly, nonwhite race proved to be an independent risk factor for endocarditis by both univariate awnd multivariate analyses. Persistent bacteremia (positive blood cultures at day 3 of appropriate therapy) was identified as an independent risk factor for both endocarditis and mortality, a unique observation not reported in other prospective studies of S. aureus bacteremia.Patients with endocarditis due to MRSA were significantly more likely to have complicating renal insufficiency and to experience persistent bacteremia than those with endocarditis due to MSSA. The 30-day mortality was 31% among patients with endocarditis compared to 21% in patients who had bacteremia without endocarditis (p = 0.055). Risk factors for death due to endocarditis included severity of illness at onset of bacteremia (as measured by Apache III and Pitt bacteremia score), MRSA infection, and presence of atrioventricular block on electrocardiogram.Patients with S. aureus bacteremia who have community acquisition of infection, underlying valvular heart disease, intravenous drug use, unknown portal of entry, history of prior endocarditis, and possibly, nonwhite race should undergo echocardiography to screen for the presence of endocarditis. We recommend that blood cultures be repeated 3 days following initiation of antistaphylococcal antibiotic therapy in all patients with S. aureus bacteremia. Positive blood cultures at 3 days may prove to be a useful marker in promoting more aggressive management, including more potent antibiotic therapy and surgical resection of the valve in endocarditis cases. MRSA as the infecting organism should be added to the list of risk factors for consideration of valvular resection in cases of endocarditis.
Automated Blood Vessel Segmentation of Fundus Images Based on Region Features and Hierarchical Growth Algorithm

Automated blood vessel segmentation plays an important role in the diagnosis and treatment of various cardiovascular and ophthalmologic diseases. In this paper, a novel unsupervised segmentation algorithm is proposed to extract blood vessels from fundus images. At first, an enhanced vessel image is generated by morphological reconstruction, and then divided into three parts: preliminary vessel regions, background regions and undetermined regions. Secondly, a list of region features of blood vessels are defined and used to remove the noise regions in preliminary vessel regions and extract the skeletons of blood vessels. An intermediate vessel image is obtained by combing the denoised preliminary vessel regions with vessel skeletons. After that, a novel hierarchical growth algorithm, namely HGA, is proposed to label each pixel in undetermined regions as vessel or not in an incremental way, which takes the advantage of color and spatial information from the intermediate vessel image and background regions. Finally, postprocessing is performed to remove the nonvessel regions. The proposed algorithm has low computational complexity and outperforms many other state-ofart supervised and unsupervised methods in terms of accuracy. It achieves a vessel segmentation accuracy of 96.0%, 95.8% and 95.1% in an average time of 10.72s, 15.74s and 50.71s on images from three publicly available retinal image datasets DRIVE, STARE, and CHASE DB1, respectively.
Time-varying channel estimation using amplitude-division based parallel NLMS technique

In this paper, we propose a channel estimation technique to combat the rapidly time-varying characteristics of multipath channel. The proposed method uses a normalized least mean square (NLMS) based novel adaptation scheme with amplitude-division technique. It supposes multiple linear transversal filters as estimators, which are arranged in a parallel fashion. The coefficient vectors for each estimator are formed with the amplitude-division based classification technique according to the information of the channel coefficient values. The coefficient vector selected at each iteration is adapted with the NLMS algorithm to handle the time variation effect of the rapidly time-varying channel. Computer simulation results demonstrate that the proposed estimator provide better tracking performance than the conventional NLMS estimator and amplitude-division parallel LMS (ADPLMS) estimator for a second order Markov communication channel in various fade rate conditions.
Updated estimate of aerosol direct radiative forcing from satellite observations and comparison against the Hadley Centre climate model

[1] The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) includes a comparison of observation-based and modeling-based estimates of the aerosol direct radiative forcing. In this comparison, satellite-based studies suggest a more negative aerosol direct radiative forcing than modeling studies. A previous satellitebased study, part of the IPCC comparison, uses aerosol optical depths and accumulationmode fractions retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) at collection 4. The latest version of MODIS products, named collection 5, improves aerosol retrievals. Using these products, the direct forcing in the shortwave spectrum defined with respect to present-day natural aerosols is now estimated at � 1.30 and � 0.65 Wm �2 on a global clear-sky and all-sky average, respectively, for 2002. These values are still significantly more negative than the numbers reported by modeling studies. By accounting for differences between present-day natural and preindustrial aerosol concentrations, sampling biases, and investigating the impact of differences in the zonal distribution of anthropogenic aerosols, good agreement is reached between the direct forcing derived from MODIS and the Hadley Centre climate model HadGEM2-A over clear-sky oceans. Results also suggest that satellite estimates of anthropogenic aerosol optical depth over land should be coupled with a robust validation strategy in order to refine the observation-based estimate of aerosol direct radiative forcing. In addition, the complex problem of deriving the aerosol direct radiative forcing when aerosols are located above cloud still needs to be addressed.