Miracle-dz/UniFAR-FTUs huggingface dataset:
Heretical Multiple Importance Sampling

Multiple importance sampling (MIS) methods approximate moments of complicated distributions by drawing samples from a set of proposal distributions. Several ways to compute the importance weights assigned to each sample have been recently proposed, with the so-called deterministic mixture (DM) weights providing the best performance in terms of variance, at the expense of an increase in the computational cost. A recent work has shown that it is possible to achieve a tradeoff between variance reduction and computational effort by performing an a priori random clustering of the proposals (partial DM algorithm). In this paper, we propose a novel “heretical” MIS framework, where the clustering is performed a posteriori with the goal of reducing the variance of the importance sampling weights. This approach yields biased estimators with a potentially large reduction in variance. Numerical examples show that heretical MIS estimators can outperform, in terms of mean squared error, both the standard and the partial MIS estimators, achieving a performance close to that of DM with less computational cost.
Two-Host, Two-Vector Basic Reproduction Ratio (R 0) for Bluetongue

Mathematical formulations for the basic reproduction ratio (R 0) exist for several vector-borne diseases. Generally, these are based on models of one-host, one-vector systems or two-host, one-vector systems. For many vector borne diseases, however, two or more vector species often co-occur and, therefore, there is a need for more complex formulations. Here we derive a two-host, two-vector formulation for the R 0 of bluetongue, a vector-borne infection of ruminants that can have serious economic consequences; since 1998 for example, it has led to the deaths of well over 1 million sheep in Europe alone. We illustrate our results by considering the situation in South Africa, where there are two major hosts (sheep, cattle) and two vector species with differing ecologies and competencies as vectors, for which good data exist. We investigate the effects on R 0 of differences in vector abundance, vector competence and vector host preference between vector species. Our results indicate that R 0 can be underestimated if we assume that there is only one vector transmitting the infection (when there are in fact two or more) and/or vector host preferences are overlooked (unless the preferred host is less beneficial or more abundant). The two-host, one-vector formula provides a good approximation when the level of cross-infection between vector species is very small. As this approaches the level of intraspecies infection, a combination of the two-host, one-vector R 0 for each vector species becomes a better estimate. Otherwise, particularly when the level of cross-infection is high, the two-host, two-vector formula is required for accurate estimation of R 0. Our results are equally relevant to Europe, where at least two vector species, which co-occur in parts of the south, have been implicated in the recent epizootic of bluetongue.
The effects of AGN feedback on present-day galaxy properties in cosmological simulations

We show that feedback from active galactic nuclei (AGN) plays an essential role in reproducing the down-sizing phenomena, namely: the colour-magnitude relation; specific star formation rates; and the $\alpha$ enhancement of early type galaxies. In our AGN model, black holes originate from Population III stars, in contrast to the merging scenario of previous works. In this paper, we show how the properties of present-day galaxies in cosmological chemo-hydrodynamical simulations change when we include our model for AGN feedback. Massive galaxies become redder, older, less massive, less compact, and show greater $\alpha$ enhancement than their counterparts without AGN. Since we reproduce the black hole mass and galaxy mass relation, smaller galaxies do not host a supermassive black hole and their star formation history is affected very little, but they can get external enrichment from nearby AGN depending on their environment. Nonetheless, the metallicity change is negligible, and the mass--metallicity relations, which are mainly generated by supernova feedback at the first star burst, are preserved.
Radiation dose reduction for patients with extranodal NK/T-cell lymphoma with complete response after initial induction chemotherapy

Previous studies have found that radiotherapy (RT) dose less than 50 Gy resulted in inferior outcomes for early stage extranodal NK/T-cell lymphoma (ENKTL). Nowadays, induction chemotherapy (CT) followed by RT consolidation is often used. For patients who get complete response (CR) after CT, whether RT dose can be safely reduced or not remains unknown. This retrospective study compared the survival outcomes between patients who received higher dose (>50 Gy) and lower dose (≤50 Gy) RT after CR was attained by CT. One hundred and forty four patients of early stage ENKTL got CR after induction CT and received RT consolidation. Thirty-one patients received lower dose RT (median 46 Gy, range, 36–50 Gy), and 113 patients received higher dose RT (median 56 Gy, range, 52–66 Gy). In univariate survival analysis, age >60, local tumor invasion, and non-asparaginase-based CT were associated with inferior progression-free survival (PFS) and overall survival (OS). However, there were no differences in PFS and OS between patients treated with higher and lower dose RT, which was confirmed in the multivariate survival analysis. Furthermore, reduced dose RT did not affect local control rate. Most common RT-related side effects were grade 1/2 mucositis and dermatitis, and the incidence rate of grade 3 mucositis or dermatitis was lower in patients treated with reduced dose RT (9.7% vs 15.0% for mucositis, and 6.5% vs 17.7% for dermatitis). In conclusion, this study found that RT dose could be safely reduced without compromising survival outcomes and further improved RT-related side effects. Prospective randomized controlled trials are warranted to validate our findings.
Mapping the Voxel-Wise Effective Connectome in Resting State fMRI

A network approach to brain and dynamics opens new perspectives towards understanding of its function. The functional connectivity from functional MRI recordings in humans is widely explored at large scale, and recently also at the voxel level. The networks of dynamical directed connections are far less investigated, in particular at the voxel level. To reconstruct full brain effective connectivity network and study its topological organization, we present a novel approach to multivariate Granger causality which integrates information theory and the architecture of the dynamical network to efficiently select a limited number of variables. The proposed method aggregates conditional information sets according to community organization, allowing to perform Granger causality analysis avoiding redundancy and overfitting even for high-dimensional and short datasets, such as time series from individual voxels in fMRI. We for the first time depicted the voxel-wise hubs of incoming and outgoing information, called Granger causality density (GCD), as a complement to previous repertoire of functional and anatomical connectomes. Analogies with these networks have been presented in most part of default mode network; while differences suggested differences in the specific measure of centrality. Our findings could open the way to a new description of global organization and information influence of brain function. With this approach is thus feasible to study the architecture of directed networks at the voxel level and individuating hubs by investigation of degree, betweenness and clustering coefficient.
ABOVEGROUND FOREST BIOMASS TRENDS FOR THE CONTERMINOUS U.S. INFERRED FROM LANDSAT TIME-SERIES AND FIELD INVENTORY DATA

We used a sample of Landsat time-series stacks (LTSS) across the conterminous U.S., calibrated with Forest Inventory and Analysis (FIA) plot-level biomass data to estimate 20+ year trends in live, aboveground biomass. To help overcome some of the limitations associated with optical remote sensing of biomass stocks, we employed a pixel-level curve-fitting algorithm to leverage the information contained within the Landsat time-series itself. The sampling framework developed here enabled estimation of live, aboveground biomass flux across 20+ years for eastern and western U.S. forest strata.
Occupational values, work climate and demographic characteristics as determinants of job satisfaction in policing

ABSTRACT The purpose of the paper is to examine the relationship between perceived importance of occupational values, assessed work climate and selected demographic characteristics of Slovenian police employees, and their job satisfaction. A total of 1,848 police service employees completed a comprehensive online questionnaire. In order to formulate the factors of perceived importance of occupational values and work climate, factor analysis was applied. A multiple linear regression analysis was performed to identify the predictors of job satisfaction. The results indicate the impact of all studied factors on job satisfaction, the strongest one for work climate, followed by demographic characteristics and the perceived importance of occupational values. The awareness of the impact of those factors on job satisfaction might be very useful when deciding about the managerial approaches that result in higher job satisfaction and, indirectly, in better performance of police service.
Influence of Social Skills and Stressors on Academic Achievement in the Sixth-Grade

Abstract Transition to middle school (MS) expressions changes in interpersonal relations and academic demands that can influence the academic achievement of students. This study aimed to evaluate the influence of social skills and perception of school stressors of students as predictors of academic achievement in the transition to the 6th grade of the MS. 214 students (aged 11 to 17 years) participated, of both genders of the 6th grade, of the state of Amazonas. Students answered the Social Skills Inventory for Adolescent and the Inventory of School Stressors. The predictive model indicated that the social skills of assertiveness, empathy and emotional approach and school stressors related to stress related to the student’s role predicted 18% of the academic achievement. The survey data can be used in future interventions with students, their families and teachers.
Mathematical transcription of the ‘time‐based resource sharing’ theory of working memory

The time-based resource sharing (TBRS) model is a prominent model of working memory that is both predictive and simple. TBRS is a mainstream decay-based model and the most susceptible to competition with interference-based models. A connectionist implementation of TBRS, TBRS*, has recently been developed. However, TBRS* is an enriched version of TBRS, making it difficult to test general characteristics resulting from TBRS assumptions. Here, we describe a novel model, TBRS2, built to be more transparent and simple than TBRS*. TBRS2 is minimalist and allows only a few parameters. It is a straightforward mathematical transcription of TBRS that focuses exclusively on the activation level of memory items as a function of time. Its simplicity makes it possible to derive several theorems from the original TBRS and allows several variants of the refresh process to be tested without relying on particular architectures.
Major histocompatibility complex-restricted H-Y-specific antibodies and cytotoxic T lymphocytes may recognize different self determinants

Previous studies have shown that influenza virus-immune cytotoxic T lymphocytes can recognize virus in conjunction with self HLA-A2 antigens. Nevertheless, the virus-infected target cells from one HLA-A2- positive male donor (designated M7) could not be lysed by the virus- immune cytotoxic lymphocytes from any HLA-A2-matched unrelated donors. Although extensive serological analyses showed no difference between the HLA-A2 antigens of donor M7 and other HLA-A2-positive donors, isoelectric focusing of the HLA-A2 molecule from donor M7 revealed a clear difference in the heavy polypeptide chains when compared with the HLA-A2 molecules of other donors. The present study demonstrates that the HLA-A2-restricted anti-H-Y cytotoxic T lymphocytes obtained from a female aplastic anaemia patient fail to lyse the male M7 target cells, whereas the HLA-A2-restricted anti-H-Y antibodies from the same patient react with the cells of donor M7. These results suggest that: (a) HLA- A2-restricted anti-H-Y antibodies can recognize self determinants on the HLA-A2 molecule that are distinct from those that are recognized by HLA-A2-restricted anti-H-Y cytotoxic T cells; and (b) HLA-restricted T and B cells may use different receptor repertoires for the recognition of foreign antigens such as H-Y.
I [ 3 H ]-Ouabain Binding Sites in Rat Brain : Distribution and Properties Assessed by Quantitative Autoradiography '

The anatomic distribution of highand low-affinity cardiac glycoside binding sites in the nervous system is largely unknown. In the present study the regional distribution and properties of these sites were determined in rat brain by quantitative autoradiography (QAR). Two populations of cardiac glycoside binding sites were demonstrated with [3H]-ouabain, a spec& inhibitor of Na,K-ATPases: (a) high-affinity binding sites with & d u e s of 22-69 nM, which were blocked by erythrosin B, and (b) low-affinity binding sites with & d u e s of 727-1482 nM. Sites with very low affiity for ouabain were not found by QAR. Highand low-affinity [3H]-ouabain binding sites were both found in all brain regions studied, including somatosensory cortex, thalamic and hypothalamic areas, medial forebrain bundle, amygdaloid nucleus, and caudate-putamen, although the distri-
Bayesian Clustering with Variable and Transformation Selections

SUMMARY The clustering problem has attracted much attention from both statisticians and computer scientists in the past fifty years. Methods such as hierarchical clustering and the K-means method are convenient and competitive first choices off the shelf for the scientist. Gaussian mixture modeling is another popular but computationally expensive clustering strategy, especially when the data is of high-dimensional. We propose to first conduct a principal component analysis (PCA) or correspondence analysis (CA) for dimension reduction, and then fit Gaussian mixtures to the data projected to the several major PCA or CA directions. Two technical difficulties of this approach are: (a) the selection of a subset of the PCA factors that are informative for clustering, and (b) the selection of a proper transformation for each factor. We propose a Bayesian formulation and Markov chain Monte Carlo strategies that overcome the two difficulties and examine the performances of the new method by both simulation studies and real applications in molecular imaging analysis and DNA microarray analysis.
Vasoconstriction to endogenous endothelin-1 is increased in the peripheral circulation of patients with essential hypertension.

BACKGROUND In humans, endothelin (ET)-1 could be implicated in the pathophysiology of several cardiovascular diseases, including essential hypertension. We therefore evaluated the role of ET-1 in control of vascular tone in essential hypertension. METHODS AND RESULTS We used strain-gauge venous plethysmography to test changes in forearm blood flow induced by intrabrachial infusion of TAK-044 (10, 30, and 100 microgram. 100 mL(-1). min(-1)), an ET(A)/ET(B) receptor antagonist, or sodium nitroprusside (1 and 2 microgram. 100 mL(-1). min(-1)), a vasodilator that acts on smooth muscle cells, in hypertensive patients and healthy controls (n=10 in each group). The NO pathway was also evaluated by infusion of N(G)-monomethyl-L-arginine, (L-NMMA; 10, 30, and 100 microgram. 100 mL(-1). min(-1)), an NO synthase inhibitor, and norepinephrine (3, 9, and 30 ng. 100 mL(-1). min(-1)) as control. Immunoreactive plasma ET-1 was measured by radioimmunoassay. In hypertensive patients, TAK-044 caused a vasodilation that was significantly (P<0.01) increased compared with normotensive subjects. Moreover, vasoconstriction to L-NMMA was significantly (P<0.01) decreased in hypertensive patients compared with controls. In contrast, the vascular responses to sodium nitroprusside and norepinephrine, as well as levels of immunoreactive plasma ET-1, were similar in hypertensive patients and controls. In the study population, vasodilation to TAK-044 and vasoconstriction to L-NMMA showed an inverse correlation (r=-0.56, P<0.05). CONCLUSIONS These results indicate that TAK-044 caused a greater degree of vasodilation in the forearm vessels of essential hypertensive patients compared with normotensive subjects, an alteration associated with decreased tonic NO release.
Robust Model-Free Multiclass Probability Estimation

Classical statistical approaches for multiclass probability estimation are typically based on regression techniques such as multiple logistic regression, or density estimation approaches such as linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). These methods often make certain assumptions on the form of probability functions or on the underlying distributions of subclasses. In this article, we develop a model-free procedure to estimate multiclass probabilities based on large-margin classifiers. In particular, the new estimation scheme is employed by solving a series of weighted large-margin classifiers and then systematically extracting the probability information from these multiple classification rules. A main advantage of the proposed probability estimation technique is that it does not impose any strong parametric assumption on the underlying distribution and can be applied for a wide range of large-margin classification methods. A general computational algorithm is developed for class probability estimation. Furthermore, we establish asymptotic consistency of the probability estimates. Both simulated and real data examples are presented to illustrate competitive performance of the new approach and compare it with several other existing methods.
Assessing elicitation task bias in time preference using experiments with artificial subjects

Experimental results in research on time preference are often controversial. We propose a systematic investigation of choice task in multiple price list format (MPL) that is frequently implemented in experiments on time preference, through a computer simulation analysis. We conduct experiments with artificial subjects to demonstrate that elicited discount rates are highly dependent on the structure of elicitation task. We verify that implementation of choice task in MPL with nominal structure results in observation of hyperbolic discounting. Choice task in MPL with interest rates structure leads to elicitation of discount rates compatible with exponential discounting. Moreover, we show that the magnitude and intensity of corresponding pattern in data depends on the internal structure of elicitation task. Comparison between discount rates elicited with articial and human subjects suggests that behavior of human subjects in experiments with MPL can be described by two simple rules: positive discounting and anchoring.
Personal thermal comfort models based on physiological parameters measured by wearable sensors

Author(s): Liu, Shichao | Abstract: Existing HVAC systems involve little feedback from indoor occupants, resulting in unnecessary cooling/heating waste and high percentage of discomfort. In addition, large thermal preference variance amongst people requires the development of personal thermal comfort models, rather than group-based methodologies such as predicted mean vote (PMV). This study focuses on assessing wearable solutions with the aim to predict personal thermal preference. We collected physiological signals (e.g., skin temperature, heart rate) of 14 subjects (6 female and 8 male adults) and environmental parameters (e.g., air temperature, wind speed, solar radiation, precipitation) for two weeks (at least 20 hr/d) to infer personal real-time thermal preference. The subjects reported their real-time thermal sensation and preference using cell-phones approximately every hour. We trained a Random Forest algorithm using data collected from individuals to develop a personal comfort model with the objective to predict thermal preference. The results show that subjects expressed needs for "warmer" or "cooler" conditions at about 30% (from 21% to 88%) of their daily time on average, implying the strong demand for a personalized indoor thermal comfort. In addition, the personal comfort model using Random Forest can infer individual thermal preference with a mean accuracy of 75% (53-93%) using physiological and environmental parameters, demonstrating the strengths of the proposed data-driven method.
Application of Forgery Localization in Overlay Text Detection

Detection of text embedded in images and videos is very useful in applications like indexing and retrieval of multimedia content. There exist very few techniques which can differentiate between overlay text which is embedded artificially and scene text which occurs naturally in images. This paper proposes an efficient method for detection and localization of overlay text from still images. By using colour filter array(CFA)-based forgery localization method, the proposed technique successfully removes any scene text present in the image. Experimental results on a database of 315 images demonstrate the efficiency of the proposed method.
Size of the giant component in a random geometric graph

In this paper, we study the size of the giant component CG in the random geometric graph G = G(n, rn, f) of n nodes independently distributed each according to a certain density f(.) in [0, 1]2 satisfying infx∈[0,1]2 f(x) > 0. If c1 n ≤ r 2 n ≤ c2 logn n for some positive constants c1, c2 and nr 2 n −→ ∞, we show that the giant component of G contains at least n − o(n) nodes with probability at least 1 − o(1) as n → ∞. We also obtain estimates on the diameter and number of the non-giant components of G.
Governance of professional nursing practice in a hospital setting: a mixed methods study1

Objective: to elaborate an interpretative model for the governance of professional nursing practice in a hospital setting. Method: a mixed methods study with concurrent triangulation strategy, using data from a cross-sectional study with 106 nurses and a Grounded Theory study with 63 participants. The quantitative data were collected through the Brazilian Nursing Work Index - Revised and underwent descriptive statistical analysis. Qualitative data were obtained from interviews and analyzed through initial, selective and focused coding. Results: based on the results obtained with the Brazilian Nursing Work Index - Revised, it is possible to state that nurses perceived that they had autonomy, control over the environment, good relationships with physicians and organizational support for nursing governance. The governance of the professional nursing practice is based on the management of nursing care and services carried out by the nurses. To perform these tasks, nurses aim to get around the constraints of the organizational support and develop management knowledge and skills. Conclusion: it is important to reorganize the structures and processes of nursing governance, especially the support provided by the organization for the management practices of nurses.