Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Data Collection Technique for Preserving Privacy

A major obstacle that hinders medical and social research is the lack of reliable data due to people's reluctance to reveal private information to strangers. Fortunately, statistical inference always targets a well-defined population rather than a particular individual subject and, in many current applications, data can be collected using a web-based system or other mobile devices. These two characteristics enable us to develop a data collection method, called triple matrix-masking (TM 2 ), which offers strong privacy protection with an immediate matrix transformation so that even the researchers cannot see the data, and then further uses matrix transformations to guarantee that the data will still be analyzable by standard statistical methods. The entities involved in the proposed process are a masking service provider who receives the initially masked data and then applies another mask, and the data collectors who partially decrypt the now doubly masked data and then apply a third mask before releasing the data to the public. A critical feature of the method is that the keys to generate the matrices are held separately. This ensures that nobody sees the actual data, but because of the specially designed transformations, statistical inference on parameters of interest can be conducted with the same results as if the original data were used. Hence the TM2 method hides sensitive data with no efficiency loss for statistical inference of binary and normal data, which improves over Warner's randomized response technique. In addition, we add several features to the proposed procedure: an error checking mechanism is built into the data collection process in order to make sure that the masked data used for analysis are an appropriate transformation of the original data; and a partial masking technique is introduced to grant data users access to non-sensitive personal information while sensitive information remains hidden.
Iterative algorithms based on multistage criteria for multichannel blind deconvolution

Blind deconvolution and blind equalization have been important interesting topics in diverse fields including data communication, image processing, and geophysical data processing. Recently, Inouye and Habe introduced a multistage criterion for attaining blind deconvolution of multiple-input multiple-output (MIMO) linear time-invariant (LTI) systems. In this correspondence, based on their criterion, we present iterative algorithms for solving the blind deconvolution problem of MIMO LTI systems. However, their criterion should be subjected to several constraints of equations. Therefore, they proposed a new constraint-free multistage criterion for accomplishing the blind deconvolution of MIMO LTI systems. Based on their unconstrained criterion, we show iterative algorithms for solving the blind deconvolution of multichannel LTI systems.
Managing the Vitamin A Program Portfolio: A Case Study of Zambia, 2013–2042

Background Micronutrient deficiencies continue to constitute a major burden of disease, particularly in Africa and South Asia. Programs to address micronutrient deficiencies have been increasing in number, type, and scale in recent years, creating an ever-growing need to understand their combined coverage levels, costs, and impacts so as to more effectively combat deficiencies, avoid putting individuals at risk for excess intakes, and ensure the efficient use of public health resources. Objective To analyze combinations of the two current programs—sugar fortification and Child Health Week (CHW)—together with four prospective programs—vegetable oil fortification, wheat flour fortification, maize meal fortification, and biofortified vitamin A maize—to identify Zambia's optimal vitamin A portfolio. Methods Combining program cost estimates and 30-year Zambian food demand projections, together with the Zambian 2005 Living Conditions Monitoring Survey, the annual costs, coverage, impact, and cost-effectiveness of 62 Zambian portfolios were modeled for the period from 2013 to 2042. Results Optimal portfolios are identified for each of five alternative criteria: average cost-effectiveness, incremental cost-effectiveness, coverage maximization, health impact maximization, and affordability. The most likely scenario is identified to be one that starts with the current portfolio and takes into account all five criteria. Starting with CHW and sugar fortification, it phases in vitamin A maize, oil, wheat flour, and maize meal (in that order) to eventually include all six individual interventions. Conclusions Combining cost and Household Consumption and Expenditure Survey (HCES) data provides a powerful evidence-generating tool with which to understand how individual micronutrient programs interact and to quantify the tradeoffs involved in selecting alternative program portfolios.
Modeling Heterogeneous Survival Data Using Mixture of Extended Exponential-Geometric Distributions

In this article, we propose a mixture of extended exponential-geometric distributions to model heterogeneous survival data. Various properties of the proposed mixture of extended exponential-geometric distributions are discussed. Maximum likelihood estimations of the parameters are obtained by using the EM algorithm. Illustrative examples based on real data are also given.
Increasing throughput of a RISC architecture using arithmetic data value speculation

Arithmetic data value speculation (ADVS) is a scheme to increase the throughput of a processor pipeline similar to conventional branch prediction. An approximate arithmetic unit, with an associated probability of correctness, provides an approximate result earlier than an exact unit, allowing the speculative issue of dependent operations. This paper investigates the performance gain in terms of retired instructions per clock (IPC) by employing ADVS in a RISC processor. Simulated results show the effect of probability of correctness and latency of approximate arithmetic units on IPC. In particular, minimum requirements for approximate arithmetic units are characterized, and maximum increase in IPC is shown for typical benchmark applications.
Smart cameras: 2D affine models for robust person recognition in consumer images

In this paper we consider how next generation smart cameras will move beyond face detection and tracking to develop more useful analysis tools for determining the expression and emotions of the subjects in images. An initial proof-of-concept using an Active Appearance Model (AAM) to perform face recognition which is robust to pose and illumination variations is presented. Our initial results are very encouraging and suggest that the incorporation of a specialized AAM within next generation digital cameras will enable more accurate management and sorting of personal image collections based on the actual persons in the images.
Classification with Implicit Inter-document Semantic Relationships

This paper addresses the question of how document classifiers can exploit implicit information about document similarity to improve document classifier accuracy. We infer document similarity using simple n-gram overlap, and demonstrate that this improves overall document classification performance over two datasets. As part of this, we find that collective classification based on simple iterative classifiers outperforms the more complex and computationally-intensive dual classifier approach.
Linear-quadratic optimal control problem of second order with infinite time horizon

An optimal control problem described by the system of the second order linear ordinary differential equations with infinite time horizon and integral cost functional is considered. Basis of a variational method, sufficient conditions for a stability of considered system are given. In the final part of the paper, an existence result related to the strongly optimal processes is obtained.
Variations in histological patterns of interstitial pneumonia between connective tissue disorders and their relationship to prognosis

Aims and methods: Pulmonary parenchymal disease is common in patients with connective tissue disorders (CTDs). However, most reports precede recognition of non‐specific interstitial pneumonia (NSIP). We have therefore reviewed 54 lung biopsies from 37 patients with polymyositis/dermatomyositis (PM/DM) (n = 13), Sjögren's syndrome (n = 5), rheumatoid arthritis (n = 17) and systemic lupus erythematosus (SLE) (n = 2) to assess the overall and relative frequencies of patterns of interstitial pneumonia and their impact on prognosis.
GPI‐defective monocytes from paroxysmal nocturnal hemoglobinuria patients show impaired in vitro dendritic cell differentiation

Paroxysmal nocturnal hemoglobinuria (PNH) is a clonal, acquired hematopoietic disorder characterized by a phosphatidylinositol (PI) glycan‐A gene mutation, which impairs the synthesis of the glycosyl‐PI (GPI) anchor, thus causing the absence of all GPI‐linked proteins on the membrane of the clonal‐defective cells. The presence of a consistent GPI‐defective monocyte compartment is a common feature in PNH patients. To investigate the functional behavior of this population, we analyzed its in vitro differentiation ability toward functional dendritic cells (DCs). Our data indicate that GPI‐defective monocytes from PNH patients are unable to undergo full DC differentiation in vitro after granulocyte macrophage‐colony stimulating factor and recombinant interleukin (IL)‐4 treatment. In this context, the GPI‐defective DC population shows mannose receptor expression, high levels of the CD86 molecule, and impaired CD1a up‐regulation. The analysis of lipopolysaccharide and CD40‐dependent, functional pathways in these DCs revealed a strong decrease in tumor necrosis factor α and IL‐12 production. Finally, GPI‐defective DCs showed a severe impairment in delivering accessory signals for T cell receptor‐dependent T cell proliferation.
Improvements in Information Extraction in Legal Text by Active Learning

Managing licensing information and data rights is becoming a crucial issue in the Linked (Open) Data scenario. An open problem in this scenario is how to associate machine-readable licenses specifications to the data, so that automated approaches to treat such information can be fruitfully exploited to avoid data misuse. This means that we need a way to automatically extract from a natural language document specifying a certain license a machine-readable description of the terms of use and reuse identified in such license. Ontology-based Information Extraction is crucial to translate natural language documents into Linked Data. This connection supports consumers in navigating documents and semantically related data. However , the performances of automated information extraction systems are far from being perfect, and rely heavily on human intervention, either to create heuristics, to annotate examples for inferring models, or to interpret or validate patterns emerging from data. In this paper, we apply different Active Learning strategies to Information Extraction (IE) from licenses in English, with highly repetitive text, few annotated or unannotated examples available, and very fine precision needed. We show that the most popular approach to active learning, i.e., uncertainty sampling for instance selection, does not provide a good performance in this setting. We show that we can obtain a similar effect to that of density-based methods using uncertainty sampling , by just reversing the ranking criterion, and choosing the most certain instead of the most uncertain instances.
Comprehensive geriatric functional analysis of elderly populations in four categories of the long‐term care insurance system in a rural, depopulated and aging town in Japan

Aim: The aim of this study was to show which dimensions of functions differ among community‐dwelling elderly participants in four different certification levels of the current long‐term care insurance system (LTCI) in a rural, depopulated and aging town in Japan, with special consideration for strengths and weaknesses of the LTCI.
Capturing aerosol droplet nucleation and condensation bursts using PISO and TVD schemes

A mathematical model for single-species aerosol production and transport is formulated, and solved using an adapted PISO algorithm. The model is applied to a laminar flow diffusion chamber, using a finite volume method on a collocated grid. In tran- sient simulations, a sharp scalar front (e.g., vapor mass fraction), is shown to introduce unphysical oscillation in the solution, when applying a second order linear interpolation in the convective terms. At increased grid resolution, these oscillations are strongly at- tenuated. When applying a TVD scheme (here the MUSCL scheme), a time-accurate monotonicity-preserving solution is obtained. The numerical dissipation introduced by the MUSCL scheme implies increased spatial resolution to restore high accuracy levels. We develop a one-dimensional grid refinement algorithm, which relates the grid density in one direction to the magnitude of the scalar gradient. In combination with the MUSCL scheme, this gives accurate results, with a significant reduction in computational effort, in comparison with a uniform fine grid.
Influence of Well Pad Activity on Winter Habitat Selection Patterns of Mule Deer

Abstract Conversion of native winter range into producing gas fields can affect the habitat selection and distribution patterns of mule deer (Odocoileus hemionus). Understanding how levels of human activity influence mule deer is necessary to evaluate mitigation measures and reduce indirect habitat loss to mule deer on winter ranges with natural gas development. We examined how 3 types of well pads with varying levels of vehicle traffic influenced mule deer habitat selection in western Wyoming during the winters of 2005–2006 and 2006–2007. Well pad types included producing wells without a liquids gathering system (LGS), producing wells with a LGS, and well pads with active directional drilling. We used 36,699 Global Positioning System locations collected from a sample (n = 31) of adult (>1.5-yr-old) female mule deer to model probability of use as a function of traffic level and other habitat covariates. We treated each deer as the experimental unit and developed a population-level resource selection function for each winter by averaging coefficients among models for individual deer. Model coefficients and predictive maps for both winters suggested that mule deer avoided all types of well pads and selected areas further from well pads with high levels of traffic. Accordingly, impacts to mule deer could probably be reduced through technology and planning that minimizes the number of well pads and amount of human activity associated with them. Our results suggested that indirect habitat loss may be reduced by approximately 38–63% when condensate and produced water are collected in LGS pipelines rather than stored at well pads and removed via tanker trucks. The LGS seemed to reduce long-term (i.e., production phase) indirect habitat loss to wintering mule deer, whereas drilling in crucial winter range created a short-term (i.e., drilling phase) increase in deer disturbance and indirect habitat loss. Recognizing how mule deer respond to different types of well pads and traffic regimes may improve the ability of agencies and industry to estimate cumulative effects and quantify indirect habitat losses associated with different development scenarios.
The seismic signature of lithospheric deformation beneath eastern North America due to Grenville and Appalachian orogenesis

The eastern margin of North America has been affected by two complete Wilson cycles of supercontinental assembly and breakup over the past ~1.3 b.y. Evidence of these processes is apparent in the surface geology; however, the geometry, strength, and extent of lithospheric deformation associated with these events are poorly known. Observations of seismic anisotropy in the continental lithosphere can shed light on past deformation processes, but information about the depth distribution of anisotropy is needed. Here we investigate the azimuthal dependence of transverse component receiver functions at broadband seismic stations in eastern North America to constrain sharp con­ trasts in seismic anisotropy with depth. We examined data from six permanent seismic stations, including three that are just to the east of the Grenville Front and three that are within the Appalachian Mountains. A harmonic stacking modeling method was used to constrain the presence of anisotropic interfaces within the crust and mantle lithosphere. A comparison among stations located to the east and to the west of the Grenville Front reveals evidence for different lithospheric anisotropy across the front, which in turn argues for significant lithospheric deformation associated with the Grenville orogeny. Stations located in the Appalachians exhibit a striking signature of strong and multi­ layered anisotropy in the lower crust, consistent with observations in modern orogens, as well as the lithospheric mantle. Our observations constrain the existence and approximate depths of contrasts in anisotropy within the lithosphere and may be used for future testing of spe­ cific hypotheses regarding lithospheric deformation associated with orogenesis. LITHOSPHERE GSA Data Repository Item 2017351 https://doi.org/10.1130/L660.1
A modelling strategy for the analysis of clinical trials with partly missing longitudinal data

Standard statistical analyses of randomized controlled trials with partially missing outcome data often exclude valuable information from individuals with incomplete follow‐up. This may lead to biased estimates of the intervention effect and loss of precision. We consider a randomized trial with a repeatedly measured outcome, in which the value of the outcome on the final occasion is of primary interest. We propose a modelling strategy in which the model is successively extended to include baseline values of the outcome, then intermediate values of the outcome, and finally values of other outcome variables. Likelihood‐based estimation of random effects models is used, allowing the incorporation of data from individuals with some missing outcomes. Each estimated intervention effect is free of non‐response bias under a different missing‐at‐random assumption. These assumptions become more plausible as the more complex models are fitted, so we propose using the trend in estimated intervention effects to assess the nature of any non‐response bias. The methods are applied to data from a trial comparing intensive case management with standard case management for severely psychotic patients. All models give similar estimates of the intervention effect and we conclude that non‐response bias is likely to be small. Copyright © 2003 Whurr Publishers Ltd.
A nonlinear iterative inverse scattering procedure in Lp Banach spaces for microwave biomedical imaging

This paper presents a tomographic inverse scattering algorithm based on an iterative regularization approach developed in Lp Banach spaces. The proposed technique has been applied to the microwave biomedical imaging of the human head, in order to detect and locate hemorrhagic brain strokes. Preliminary numerical results are provided in order to show the capabilities of the inversion method.
Approximate clustering in very large relational data

Different extensions of fuzzy c‐means (FCM) clustering have been developed to approximate FCM clustering in very large (unloadable) image (eFFCM) and object vector (geFFCM) data. Both extensions share three phases: (1) progressive sampling of the VL data, terminated when a sample passes a statistical goodness of fit test; (2) clustering with (literal or exact) FCM; and (3) noniterative extension of the literal clusters to the remainder of the data set. This article presents a comparable method for the remaining case of interest, namely, clustering in VL relational data. We will propose and discuss each of the four phases of eNERF and our algorithm for this last case: (1) finding distinguished features that monitor progressive sampling, (2) progressively sampling a square N × N relation matrix RN until an n × n sample relation Rn passes a statistical test, (3) clustering Rn with literal non‐Euclidean relational fuzzy c‐means, and (4) extending the clusters in Rn to the remainder of the relational data. The extension phase in this third case is not as straightforward as it was in the image and object data cases, but our numerical examples suggest that eNERF has the same approximation qualities that eFFCM and geFFCM do. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 817–841, 2006.
One-center trapping of the holes in alkali halide crystals.

The geometric and electronic structures and electron excitation energies for the one-center hole polaron state and several possible intermediate states corresponding to the hole relaxation in KI are calculated using the static embedded molecular cluster method. The calculated optical transition energies are close to the maxima of the transient optical-absorption spectra in KI which were observed experimentally using femto-second spectroscopy. The mechanism of the self-trapping of the holes in KI is discussed. It is demonstrated that the experimental spectra can be reasonably understood if we consider that the hole first localizes in the one-center state which then transforms into the two-center state, and finally into the {ital V}{sub {ital K}} center. {copyright} {ital 1996 The American Physical Society. }
Protective role of Bacopa monniera on morphine induced hepatotoxicity in rats

The protective effect of Bacopa monniera on morphine induced liver antioxidant levels was studied in rats. Oral administration of alcohol extracts of Bacopa monniera induced a significant hepatoprotective effect. In the morphine treated group, a significant increase of lipid peroxidation and a significant decrease in liver antioxidant enzyme levels were observed. Simultaneous administration of morphine and Bacopa extract prevented these alterations. The results of this study showed that Bacopa monniera alcohol extract exerted a hepatoprotective effect against morphine induced liver toxicity. Copyright © 2001 John Wiley & Sons, Ltd.