Miracle-dz/UniFAR-FTUs huggingface dataset:
Etiology of Severe Febrile Illness in Low- and Middle-Income Countries: A Systematic Review

Background With apparent declines in malaria worldwide during the last decade and more widespread use of malaria rapid diagnostic tests, healthcare workers in low-resource areas face a growing proportion of febrile patients without malaria. We sought to describe current knowledge and identify information gaps of the etiology severe febrile illness in low-and middle-income countries. Methods and Findings We conducted a systematic review of studies conducted in low-and-middle income countries 1980–2013 that prospectively assessed consecutive febrile patients admitted to hospital using rigorous laboratory-based case definitions. We found 45 eligible studies describing 54,578 patients; 9,771 (17.9%) had a positive result for ≥1 pathogen meeting diagnostic criteria. There were no eligible studies identified from Southern and Middle Africa, Eastern Asia, Oceania, Latin American and Caribbean regions, and the European region. The median (range) number of diagnostic tests meeting our confirmed laboratory case definitions was 2 (1 to 11) per study. Of diagnostic tests, 5,052 (10.3%) of 49,143 had confirmed bacterial or fungal bloodstream infection; 709 (3.8%) of 18,142 had bacterial zoonosis; 3,488 (28.5%) of 12,245 had malaria; and 1,804 (17.4%) of 10,389 had a viral infection. Conclusions We demonstrate a wide range of pathogens associated with severe febrile illness and highlight the substantial information gaps regarding the geographic distribution and role of common pathogens. High quality severe febrile illness etiology research that is comprehensive with respect to pathogens and geographically representative is needed.
Eliminating Racial Profiling in School Discipline: Cultures in Conflict

1 Discipline: The New Equity Issue 2 Merely a Symptom 3 The Impact of Culture 4 Cross-Cultural Communication Conflicts in the Classroom 5 Stereotyping in the Classroom 6 Cultural Conflicts, Cultural Conditioning, and Disciplinary Practices 7 Changing the School Climate: The Administrator's Role 8 Changing Individual Attitudes 9 The Village Approach: Forming Partnerships with Parents and Community 10 Evaluating the Process: School Climate and Individual Assessment
Design and Implementation of a Virtual Machine Based Information Flow Control System

The ability to enforce usage policies attached to data in a fin e grained manner requires that the system be able to trace and control the flow of information within it. This paper presents the design and implementation of such an information flow control system as a Java Virtual Machine, called Trishul. In particular we describe a novel way to address the hard prob lem of tracing implicit information flow, which had not been resolved by previous systems. We argue tha t the security benefits offered by Trishul are substantial enough to counter-weigh the performance ov erhead of the system as shown by our experiments.
MIMO Channel Modelling: The Kronecker Model and Maximum Entropy

A method for determining the maximum entropy (ME) estimate of the full joint transmit/receive MIMO channel covariance matrix is presented, where only knowledge of the separate transmit and receive covariances is assumed. The resulting ME covariance is similar to, but distinct from, the Kronecker modelling strategy, warranting a direct comparison of the two techniques. Application of the method to wideband indoor multiple-input multiple-output (MIMO) measurements taken at 2.4 GHz indicates a slight improvement in the modelling accuracy of the dominant covariance eigenvalues compared to the Kronecker model. On the other hand, the double-directional joint transmit/receive Bartlett spectra are nearly identical, indicating that the ME technique does not significantly improve modelling of the channel multipath structure. This fact suggests that accurate multipath modelling for MIMO systems may not be possible without detailed joint transmit/receive channel knowledge.
Entrepreneurship for Inmates: A Conceptual Model

According to the Census Bureau (Census.gov, 2007), forty-one percent of the prison population is black. Approximately half of all black men that have less than a college education serve prison time (Pettit & Western, 2004). The Prison Entrepreneurship Program (PEP) is a program in Texas that recognizes the entrepreneurial potential of inmates. The program has had some intriguing success. This paper proposes a conceptual model of entrepreneurship for inmates.
Advanced antenna diagnostics and pattern processing form measured data

Introduction We discuss recent advances in antenna diagnostics from measured field data. The method proposed is based on field representation using equivalent magnetic and electric sources on arbitrary shaped geometries enclosing the antenna under test. Traditional antenna diagnostic tools are often based on a plane wave expansion similar to what is available from the corresponding planar near field measurement [1]. A more flexible approach is based Equivalent Sources (e.g. [2]), in which equivalent sources are computed on an arbitrarily shaped surface enclosing the antenna by solving the inverse problem directly from the measured field data (typically near field). Since the reconstruction surface is known, the associated inverse problem is linear; however, it is well known to be intrinsically ill-posed due to the characteristics of the operators involved. Therefore, special treatment is necessary in view of the noise present in any antenna measurements as well as to compensate for other forms of “error” in the available data (e.g. truncation). The most common such form of stabilization is the so-called regularization (e.g. [3]); it invariably results in a spatial low-pass filtering that reduces the spatial resolution, and requires the choice of a “filtering parameter” that can seldom be done a priori and in a “blind” way. To overcome these difficulties, we employ a novel and robust formulation; we will show with examples the applicability to general antenna diagnostics, leakage detection, location of antenna malfunctioning causes and identification and removal of unwanted interactions from measurements.
Contemporaneous verification of language: evidence from management earnings forecasts

Research documents that linguistic tone is incrementally informative about stock returns. What remains a puzzle is the mechanism by which investors can assess its credibility. We examine whether contemporaneous information in management earnings forecasts serves as a timely alternative to ex post verification. We document that ex post verifiable quantitative news in unbundled forecasts, and characteristics of the linguistic tone itself, affect investors’ pricing of tone. Consistent with higher quality signals enhancing the credibility of contemporaneous lower quality signals, we find that quantitative news verifies the associated linguistic tone; when the two signals have the same sign, the price effect of tone is stronger. Furthermore, the pricing attenuation of tone is increasing in the imprecision of the quantitative forecast, suggesting that lower forecast quality compromises the quantitative signal’s credibility enhancement. Managerial incentives to inflate tone lead to the verification effect being greater for optimistic language, while management’s use of hyperbole results in attenuation of the tone’s pricing.
Realistic Assumptions for Attacks on Elections

We must properly model attacks and the preferences of the electorate for the computational study of attacks on elections to give us insight into the hardness of attacks in practice. Theoretical and empirical analysis are equally important methods to understand election attacks. I discuss my recent work on domain restrictions on partial preferences and on new election attacks. I propose further study into modeling realistic election attacks and the advancement of the current state of empirical analysis of their hardness by using more advanced statistical techniques.
A Comparison of Neural Network, Statistical Methods, and Variable Choice for Life Insurers' Financial Distress Prediction

This study examines the effect of the statistical/mathematical model selected and the variable set considered on the ability to identify financially troubled life insurers. Models considered are two artificial neural network methods (back-propagation and learning vector quantization (LVQ)) and two more standard statistical methods (multiple discriminant analysis and logistic regression analysis). The variable sets considered are the insurance regulatory information system (IRIS) variables, the financial analysis solvency tracking (FAST) variables, and Texas early warning information system (EWIS) variables, and a data set consisting of twenty-two variables selected by us in conjunction with the research staff at TDI and a review of the insolvency prediction literature. The results show that the back-propagation (BP) and LVQ outperform the traditional statistical approaches for all four variable sets with a consistent superiority across the two different evaluation criteria (total misclassification cost and resubstitution risk criteria), and that the twenty-two variables and the Texas EWIS variable sets are more efficient than the IRIS and the FAST variable sets for identification of financially troubled life insurers in most comparisons.
The Effect of Learning on the Evolution of Asexual Populations

We study a model for the effect of learning on a popula­ tion of asexually reproducing individuals . While current models are usually based on simulations of the actual hypothetical organisms, we adopt a classic population genetic approach, which deals directly with gene frequencies. This allows us to investigate the model in great detail, obtaining results which are difficult to obtain using other tech­ niques . In particular, we demonstrate that learning has a drastic effect on evolution, as has already been noted by Hinton and Nowlan (3) us­ ing computer simulations. A detailed quantitative description of the temporal behavior of the model is also presented. In particular, an interesting interplay between mutation and learning is demonstrated.
Resolving Controversy in the European Union: References

How does the EU resolve controversy when making laws that affect citizens? How has the EU been affected by the recent enlargements that brought its membership to a diverse group of twenty-seven countries? This 2011 book answers these questions with analyses of the EU's legislative system that include the roles played by the European Commission, European Parliament and member states' national governments in the Council of Ministers. Robert Thomson examines more than 300 controversial issues in the EU from the past decade and describes many cases of controversial decision-making as well as rigorous comparative analyses. The analyses test competing expectations regarding key aspects of the political system, including the policy demands made by different institutions and member states, the distributions of power among the institutions and member states, and the contents of decision outcomes. These analyses are also highly relevant to the EU's democratic deficit and various reform proposals.
E-Governance for Improved Public Service Delivery in Fiji

Using ICT in the form of e-governance could yield great benefits in the reform and modernization of the public sector. The experience of e-governance in a number of developed and developing countries has shown that ICT can be a tool for greater service delivery with the goal of improving service quality. E-governance can also promote ‘good govern-ance’, that is, greater civic engagement can increase opportunities for direct representation and voice, and support for increased democracy. This paper discusses and presents the survey findings that seek to test the role of e-governance in improving service delivery by altering the principal-agent relationship. It further seeks to elucidate the quality aspects of public service. Policy recommendations to achieve the benefits of e-governance in Fiji are presented. Strong leadership is required to implement e-governance to capture and internalize the benefits of quality services and satisfied customers.
Precessing jets from a moving source and bright X-ray filaments in galaxy clusters

We present hydrodynamical calculations carried out with the 3D YGUAZU-A code for a precessing jet model that is interacting with a plane parallel wind. This scenario describes an extragalactic jet in which the jet source is in,motion with respect to the surrounding intra-cluster medium. From the numerical results, synthetic emission maps and spectra in X-ray band were obtained. We compare these predictions with observations of the radio jets emanating from the radio-galaxy 4C 26.42 (in the Abell 1795 galaxy cluster). We find that the general morphology of the radio jets can be described by a point-symmetric precessing jet system interacting with a plane parallel wind (i.e., the intra-cluster medium flowing past the galaxy). We also find that our synthetic X-ray emission maps reproduce the observed large scale structures (with sizes on the order of tens of kpc).
ISPC effect is not observed when the word comes too late: a time course analysis

The item-specific proportion congruency (ISPC) effect is demonstrated by a smaller Stroop effect observed for mostly incongruent items compared to mostly congruent items. Currently, there is a continuing debate on whether conflict driven item-specific control processes or stimulus-response contingency learning account for the ISPC effect. In the present study, we conducted two experiments to investigate the time course of the ISPC effect with a stimulus onset asynchrony (SOA) manipulation. Both negative and positive SOAs were used in order to manipulate the contingency learning between the word and the color dimensions. We also combined this SOA manipulation with a set size manipulation (Bugg and Hutchison, 2013) to moderate the contribution of contingency learning and item-specific processes to the observed ISPC effect. We expected that the change in the magnitude of the ISPC effect as a result of SOA would follow different patterns for the 2-item and 4-item set conditions. Results showed that the SOA manipulation influenced the ISPC effect. Specifically, when the word followed the color with a 200 ms delay, the observed ISPC effect was smaller, if at all present, than the ISPC effects in other negative and positive SOA conditions, regardless of set size. In conclusion, our results showed that the ISPC effect was not observed if the word arrived too late. We also conducted additional awareness and RT distribution analyses (delta plots) to further investigate the ISPC effect. These analyses showed that a higher percentage of participants were aware of the ISPC manipulation in the 2-item set condition compared to the 4-item set condition. Delta plots revealed that the ISPC effect was smaller for fastest responses and increased as the responses got slower.
Jet Study in Ultra-Relativistic Heavy-Ion Collisions with the ALICE Detectors at the LHC

First results of jet reconstruction in simulated Pb+Pb collisions with the ALICE detector at LHC at , using a combination of tracking and calorimetric information, are presented. It is demonstrated that changes in jet fragmentation functions, caused by jet energy loss in a dense medium, and modelled in simulations, are measurable.
Practical , Robust , and Scalable Black-Box Optimization with BOA and hBOA

To design practical black-box optimizers, one of the primary goals is to minimize the amount of work that must be done by the user while ensuring that a high-quality solution will be found quickly and reliably. This paper shows that probabilistic model-building genetic algorithms (PMBGAs) provide a great framework for designing practical and powerful black-box optimizers. The paper focuses on two algorithms that are among the most powerful PMBGAs: The Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA).
Public education, technological change and economic prosperity

We introduce publicly funded education in R&D-based economic growth theory. The framework allows us to i) incorporate a realistic process of human capital accumulation for industrialized countries, ii) reconcile R&D-based growth theory with the empirical evidence on the relationship between economic prosperity and population growth, iii) revise the policy invariance result of semi-endogenous growth frameworks, and iv) show that the transitional effects of an education reform tend to be qualitatively different from its long-run impact.
Influence based Link Prediction using Supervised Learning

In recent years, there has been a lot of interest in understanding how nodes get influenced in networks, and how does their influence propagate to their neighbors. In online social networks, users receive feeds about their friend’s online activities and when a user sees their social contacts performing an action such as joining an online community, that user may be influenced to perform the action themselves. In this project, we want to study how a node influences other nodes, and how a nodes' influence can be used to predict future links in the network. We propose an influence based supervised learning task and use it to predict new friend relationship links in a network.
Hot subdwarfs from the ESO Supernova Ia Progenitor Survey: II. Atmospheric parameters of subdwarf O stars

We address the origin and evolutionary status of hot subdwarf stars by studying the optical spectral properties of 58 subdwarf O (sdO) stars. Combining them with the results of our previously studied subdwarf B (sdB) stars, we aim at investigating possible evolutionary links. We analyze high-resolution ESO VLT UVES spectra from the ESO Supernova Ia Progenitor Survey (SPY). Effective temperatures, gravities, and helium abundances are determined simultaneously by fitting the profiles of H and He lines using dedicated synthetic spectra in NLTE. Evidence for cool companions to 8 sdOs as well as a binary consisting of two sdO stars is found. A correlation between He abundances and the presence of carbon and/or nitrogen lines emerges: below solar He abundance, no sdO shows C or N lines. In contrast, C and/or N lines are present in ALL sdOs with super- solar He abundance. We thus use the solar He abundance to divide our sample into He-deficient and He-enriched sdOs. While He-deficient sdOs are scattered in a wide range of the Teff-log(g)-diagram, most of the He-enriched sdOs cluster in a narrow region at Teff = 40,000 . 50,000K and log(g)=5.5 . 6.0. An evolu- tionary link between sdBs and sdOs appears plausible only for the He-deficient sdOs indicating that they are the likely successors to sdBs. The properties of He-enriched sdOs cannot be explained with canonical single star evolutionary models. Alternative scenarios (late hot flasher) as well as for binary evolution (white dwarf merger; post-RGB evolution) are tested. While we regard the post-RGB scenario as inappropriate, the white dwarf merger and the late hot flasher scenarios remain viable to explain the origin of He-enriched sdOs.
Hyperglycemia Induces Skin Barrier Dysfunctions with Impairment of Epidermal Integrity in Non-Wounded Skin of Type 1 Diabetic Mice

Diabetes causes skin complications, including xerosis and foot ulcers. Ulcers complicated by infections exacerbate skin conditions, and in severe cases, limb/toe amputations are required to prevent the development of sepsis. Here, we hypothesize that hyperglycemia induces skin barrier dysfunction with alterations of epidermal integrity. The effects of hyperglycemia on the epidermis were examined in streptozotocin-induced diabetic mice with/without insulin therapy. The results showed that dye leakages were prominent, and transepidermal water loss after tape stripping was exacerbated in diabetic mice. These data indicate that hyperglycemia impaired skin barrier functions. Additionally, the distribution of the protein associated with the tight junction structure, tight junction protein-1 (ZO-1), was characterized by diffuse and significantly wider expression in the diabetic mice compared to that in the control mice. In turn, epidermal cell number was significantly reduced and basal cells were irregularly aligned with ultrastructural alterations in diabetic mice. In contrast, the number of corneocytes, namely, denucleated and terminally differentiated keratinocytes significantly increased, while their sensitivity to mechanical stress was enhanced in the diabetic mice. We found that cell proliferation was significantly decreased, while apoptotic cells were comparable in the skin of diabetic mice, compared to those in the control mice. In the epidermis, Keratin 5 and keratin 14 expressions were reduced, while keratin 10 and loricrin were ectopically induced in diabetic mice. These data suggest that hyperglycemia altered keratinocyte proliferation/differentiation. Finally, these phenotypes observed in diabetic mice were mitigated by insulin treatment. Reduction in basal cell number and perturbation of the proliferation/differentiation process could be the underlying mechanisms for impaired skin barrier functions in diabetic mice.
Low-Rank Matrix Completion by Riemannian Optimization

The matrix completion problem consists of finding or approximating a low-rank matrix based on a few samples of this matrix. We propose a new algorithm for matrix completion that minimizes the least-square distance on the sampling set over the Riemannian manifold of fixed-rank matrices. The algorithm is an adaptation of classical non-linear conjugate gradients, developed within the framework of retraction-based optimization on manifolds. We describe all the necessary objects from differential geometry necessary to perform optimization over this low-rank matrix manifold, seen as a submanifold embedded in the space of matrices. In particular, we describe how metric projection can be used as retraction and how vector transport lets us obtain the conjugate search directions. Finally, we prove convergence of a regularized version of our algorithm under the assumption that the restricted isometry property holds for incoherent matrices throughout the iterations. The numerical experiments indicate that our approach scales very well for large-scale problems and compares favorably with the state-of-the-art, while outperforming most existing solvers.
Interstate Bank Mergers and Their Impact on Shareholder Returns: Evidence From the 1990s

During the 1990s merger activity in the commercial banking industry has expanded at a rapid pace primarily due to the loosening of interstate restrictions and the much-improved health of the banking industry. Our study examines interstate merger activity in the banking industry during the 19911995 time period, measures its impact on stockholder returns, and compares these results to a similar study that uses data from the 1980s. Our findings indicate that during the 1990s returns to targets have been significantly positive while returns to bidders have been significantly negative. These findings differ from the findings of Cometi and De (1991) who report significant positive returns to bidders and targets in interstate mergers during the time period 1982-1986. In addition, our study finds evidence that indicates that there is a significantly negative revaluation of the combined bidder and target values at the merger announcement.