Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Cyclic Space-Frequency Filtering for BICM-OFDM with Outdated CSIT

In this paper, we introduce robust cyclic space-frequency (CSF) filtering for systems combining bit-interleaved coded modulation (BICM) and orthogonal frequency division multiplexing (OFDM). The proposed robust CSF filtering scheme exploits outdated channel state information at the transmitter (CSIT) and takes into account the reliability of the CSIT via a Bayesian model. Based on an upper bound on the worst-case pairwise error probability we formulate the optimization problem for the robust CSF filters which can be solved exactly for certain special cases. For the general case, we obtain an approximate solution by solving a related problem with additional constraints. This approximate solution can be further improved with a gradient algorithm for the original problem. Simulation results confirm the excellent performance of BICM-OFDM with robust CSF filtering.
Poisson Regression Analysis of Illness and Injury Surveillance Data

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences due to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used inmore » the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra-Poisson variation. The R open source software environment for statistical computing and graphics is used for analysis. Additional details about R and the data that were used in this report are provided in an Appendix. Information on how to obtain R and utility functions that can be used to duplicate results in this report are provided. « less
The Level of Reaction Time Determines the ERP Correlates of Auditory Negative Priming

Responding to a stimulus that had to be ignored previously is usually slowed-down (negative priming effect). This study investigates the reaction time and ERP effects of the negative priming phenomenon in the auditory domain. Thirty participants had to categorize sounds as musical instruments or animal voices. Reaction times were slowed-down in the negative priming condition relative to two control conditions. This effect was stronger for slow reactions (above intraindividual median) than for fast reactions (below intraindividual median). ERP analysis revealed a parietally located negativity of the negative priming condition compared to the control conditions between 550-730 ms poststimulus. This replicates the findings of Mayr, Niedeggen, Buchner, and Pietrowsky (2003). The ERP correlate was more pronounced for slow trials (above intraindividual median) than for fast trials (below intraindividual median). The dependency of the negative priming effect size on the reaction time level found in the reaction time analysis as well as in the ERP analysis is consistent with both the inhibition as well as the episodic retrieval account of negative priming. A methodological artifact explanation of this effect-size dependency is discussed and discarded.
AN EMPIRICAL APPLICATION OF LINEAR REGRESSION METHOD AND FIR NETWORK FOR FAULT DIAGNOSIS IN NONLINEAR TIME SERIES

A fault diagnosis scheme for nonlinear time series recorded in normal and abnormal conditions is described. The fault is first detected from regression lines of the raw time series. Model for the normal condition time series is estimated using a Finite Impulse Response (FIR) neural network. The trained network is then used for filtering of abnormal condition time series. The fault is further confirmed/ analyzed using the regression lines of the predicted normal and inverse-filtered abnormal conditions time series. The described scheme is applied to two fault diagnosis problems using acoustic and vibration data obtained from rotating parts of an automobile and a boring tool, respectively.
Spatial Capacity Optimization for Indoor MIMO Los Channels Applying Methods of High-Rank Transfer Matrix Construction

The indoor MIMO line-of-sight (LOS) channel in theory strongly depends on the geometrical arrangement and spacing of the antennas at both, the transmitter as well as the receiver. Recently, theoretical directives have been presented [1] which enable the user to achieve high-rank LOS channels for linear antenna arrays which are oriented broadside to each other. The authors focus on proper phase angle relations within the entries of the channel transfer matrix, while neglecting the channel path loss in a first approach, and they consider the antenna spacings as the major degree of freedom for optimization. Contrarily, in practical indoor scenarios we consider the antenna array spacings to be fixed at the base station as well as the mobile unit and therefore they can be optimized for one particular transmitter-receiver distance at most. Furthermore, the free space path loss has to be taken into account as it causes huge SNR variations across an indoor environment. Thus, in this paper we try to apply the results in [1] to an exemplary real-world scenario observing the spatial capacity distribution as well as their variation. This way, we endorse the results in [1] by further design hints for practical MIMO systems using linear antenna arrays of arbitrary positioning.
Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo

Computational systems biology is concerned with the development of detailed mechanistic models of biological processes. Such models are often stochastic and analytically intractable, containing uncertain parameters that must be estimated from time course data. In this article, we consider the task of inferring the parameters of a stochastic kinetic model defined as a Markov (jump) process. Inference for the parameters of complex nonlinear multivariate stochastic process models is a challenging problem, but we find here that algorithms based on particle Markov chain Monte Carlo turn out to be a very effective computationally intensive approach to the problem. Approximations to the inferential model based on stochastic differential equations (SDEs) are considered, as well as improvements to the inference scheme that exploit the SDE structure. We apply the methodology to a Lotka–Volterra system and a prokaryotic auto-regulatory network.
C*-tree: A Multi-Dimensional Index Structure for Resource Space Model

Resource Space Model (RSM) is a semantic data model for specifying, organizing, and retrieving resources based on classification of resources. An efficient index mechanism is critical for its implementation. However, traditional index mechanisms are not well suitable to resource spaces because the spaces are discrete and hierarchical. This paper proposes a new multidimensional index structure C*-tree. It employs boxes to represent resources so that the containment of boxes can reflect the hierarchical structure of resources. The metric function defined in the C*-tree is able to gather close resources in the index structure. To avoid overlap between bounding boxes, a new restricted bounding box is further introduced. Moreover, the insertion algorithms based on the data partition approach can fully utilize characteristics of RSM. The C*-tree is scalable and efficient on both the number of dimension and the amount of data for different distributions.
Carbon isotope discrimination in C3 land plants is independent of natural variations in pCO2

doi: 10.7185/geochemlet.1604 The d13C of terrestrial C3 plant tissues and soil organic matter is important for understanding the carbon cycle, inferring past climatic and ecological conditions, and predicting responses of vegetation to future climate change. Plant d13C depends on the d13C of atmospheric CO2 and mean annual precipitation (MAP), but an unresolved decades-long debate centres on whether terrestrial C3 plant d13C responds to pCO2. In this study, the pCO2-dependence of C3 land plant d13C was tested using isotopic records from lowand high-pCO2 times spanning historical through Eocene data. Historical data do not resolve a clear pCO2-effect (-1.2 ± 1.0 to 0.6 ± 1.0 ‰/100 ppmv). Organic carbon records across the Pleistocene-Holocene transition are too affected by changes in MAP, carbon sources, and potential differential degradation to quantify pCO2-effects directly, but limits of ≤1.0 ‰/100 ppmv or ~0 ‰/100 ppmv are permissible. Fossil collagen and tooth enamel data constrain pCO2-effects most tightly to -0.03 ± 0.13 and -0.03 ± 0.24 ‰/100 ppmv between 200 and 700 ppmv. Combining all constraints yields a preferred value of 0.0 ± 0.3 ‰/100 ppmv (2 s.e.). Recent models of pCO2-dependence imply unrealistic MAP for Cenozoic records. Received 7 July 2015 | Accepted 3 December 2015 | Published 11 January 2016
Retinex processing for automatic image enhancement

In the last published concept (1986) for a Retinex computation, Edwin Land introduced a center/surround spatial form, which was inspired by the receptive field structures of neurophysiology. With this as our starting point we have over the years developed this concept into a full scale automatic image enhancement algorithm - the Multi-Scale Retinex with Color Restoration (MSRCR) which combines color constancy with local contrast/lightness enhancement to transform digital images into renditions that approach the realism of direct scene observation. The MSRCR algorithm has proven to be quite general purpose, and very resilient to common forms of image pre-processing such as reasonable ranges of gamma and contrast stretch transformations. More recently we have been exploring the fundamental scientific implications of this form of image processing, namely: (i) the visual inadequacy of the linear representation of digital images, (ii) the existence of a canonical or statistical ideal visual image, and (iii) new measures of visual quality based upon these insights derived from our extensive experience with MSRCR enhanced images. The lattermost serves as the basis for future schemes for automating visual assessment - a primitive first step in bringing visual intelligence to computers.
Optimal methods for coordinated enroute web caching for tree networks

Web caching is an important technology for improving the scalability of Web services. One of the key problems in coordinated enroute Web caching is to compute the locations for storing copies of an object among the enroute caches so that some specified objectives are achieved. In this article, we address this problem for tree networks, and formulate it as a maximization problem. We consider this problem for both unconstrained and constrained cases. The constrained case includes constraints on the cost gain per node and on the number of object copies to be placed. We present dynamic programming-based solutions to this problem for different cases and theoretically show that the solutions are either optimal or convergent to optimal solutions. We derive efficient algorithms that produce these solutions. Based on our mathematical model, we also present a solution to coordinated enroute Web caching for autonomous systems as a natural extension of the solution for tree networks. We implement our algorithms and evaluate our model on different performance metrics through extensive simulation experiments. The implementation results show that our methods outperform the existing algorithms of either coordinated enroute Web caching for linear topology or object placement (replacement) at individual nodes only.
Age and stress as determinants of the severity of hyperthyroidism caused by Graves' disease in newly diagnosed patients.

OBJECTIVE The evidence that stress may provoke Graves' hyperthyroidism in genetically susceptible subjects is substantial. Whether exposure to stress is related to the severity of thyrotoxicosis has not been studied. Advancing age is associated with not only less severe Graves' hyperthyroidism but also self-reported stress. We tested the hypothesis whether advancing age is associated with less exposure to stress, resulting in a lower immunological response, and less severe Graves' hyperthyroidism. DESIGN Cross-sectional multicenter study. PATIENTS Two hundred and sixty-three consecutive untreated patients with a first episode of Graves' hyperthyroidism were included. The severity of Graves' hyperthyroidism was evaluated biochemically (freeT(4)-index and freeT(3)-index, thyrotropin-binding inhibitory immunoglobulin (TBII)) and clinically by the hyperthyroid symptom scale score (HSS score). Stress exposure was quantitated by three questionnaires. RESULTS Advancing age was associated with less severe Graves' hyperthyroidism, both biochemically by lower serum freeT(3)-index and freeT(4)-index (P<0.01), lower serum TBII (P=0.05), and clinically by lower HSS scores (P=0.04) and smaller goiter size (P<0.01). FreeT(3)-index and freeT(4)-index were directly associated with HSS scores (P<0.01). Stress scores were associated with HSS scores (P<0.01) but not with biochemical severity of Graves' hyperthyroidism. Advancing age was associated with lower scores for stress exposure. Multivariate regression analysis showed that HSS score was independently related to the tendency to report negative feelings (P<0.01) but not to other stress scores and also not to age. CONCLUSION Advancing age is associated with less exposure to stress, lower serum TBII and less severe clinical and biochemical Graves' hyperthyroidism. Because no direct relationship exists between stress exposure and TBII or freeT(3)-index and freeT(4)-index, we reject our hypothesis that less stress is causally related to biochemically less severe Graves' hyperthyroidism in old age. HSS score is primarily determined by negative feelings and not by age.
"Scrum Code Camps"

A classic way to choose a supplier is through a bidding process where tenders from competing companies are evaluated in relation to the customer's requirements. If the customer wants to hire an agile software developing team instead of buying a software product, a new approach for comparing tenders is required. In this paper we present the design of such a new approach, the Scrum Code Camp, which can be used to assess agile team capability in a transparent and consistent way. A design science research approach is used to analyze properties of two instances of the Scrum Code Camp where seven agile teams were evaluated.
Comparison of Two Nonlinear Predictive Control Algorithms for Dissolved Oxygen Tracking Problem at WWTP

The linear MPC algorithm was proposed in [12] and its application to benchmark simulation WWTP. In [5] the hybrid nonlinear predictive controller was applied. The binary control signals were reformulated to nonlinear programming task at every sampling time . Interesting control results were obtained. In [7] the MPC system of DO control based on self-organizing radial basis function neural Abstract: The wastewater treatment plant is classified as a com-plex system due to its nonlinear dynamics, large uncer-tainty in the disturbance inputs, multiple time scales in the internal process dynamics and multivariable structure. Aeration is an important and expensive activity that is carried out during wastewater treatment plant operation. A precise aeration control in biological processes for all the operating conditions is necessary in order to guar-antee adequate biological conditions for microorganisms. Therefore, the most important is to operate the biological processes so that a minimal energy was consumed and minimal DO concentration demand was applied. The paper proposes a two advanced control systems to track the dissolved oxygen reference trajectory. A decentralized and multivariable nonlinear predictive control algorithms are designed and compared. Simulation tests for the case study wastewater treatment plant are presented.
Recurrent Regression for Face Recognition

To address the sequential changes of images including poses, in this paper we propose a recurrent regression neural network(RRNN) framework to unify two classic tasks of cross-pose face recognition on still images and video-based face recognition. To imitate the changes of images, we explicitly construct the potential dependencies of sequential images so as to regularize the final learning model. By performing progressive transforms for sequentially adjacent images, RRNN can adaptively memorize and forget the information that benefits for the final classification. For face recognition of still images, given any one image with any one pose, we recurrently predict the images with its sequential poses to expect to capture some useful information of others poses. For video-based face recognition, the recurrent regression takes one entire sequence rather than one image as its input. We verify RRNN in static face dataset MultiPIE and face video dataset YouTube Celebrities(YTC). The comprehensive experimental results demonstrate the effectiveness of the proposed RRNN method.
Grape Seed Oil Compounds: Biological and Chemical Actions for Health

Grape seed oil is rich in phenolic compounds, fatty acids, and vitamins, with economic importance to pharmaceutical, cosmetic, and food industry. Its use as an edible oil has also been suggested, especially due to its pleasant sensory characteristics. Grape seed oil has beneficial properties for health that are mainly detected by in vitro studies, such as anti-inflammatory, cardioprotective, antimicrobial, and anticancer properties, and may interact with cellular and molecular pathways. These effects have been related to grape seed oil constituents, mainly tocopherol, linolenic acid, resveratrol, quercetin, procyanidins, carotenoids, and phytosterols. The aim of this article was to briefly review the composition and nutritional aspects of grape seed oil, the interactions of its compounds with molecular and cellular pathways, and its possible beneficial effects on health.
Geostatistics: Unde venis et quo vadis?

Los datos espaciales o espacio-temporales no son nuevos. Han estado siempre ahí. Sin embargo, hasta hace pocos años no se ha desarrollado la teoría y la tecnología para que la comunidad científica pueda trabajar con ellos y sacar provecho de las dependencias espaciales o espacio-temporales que presentan un buen número de fenómenos de la realidad a la hora de llevar a cabo tareas de estimación, predicción, mapeo, diseño experimental, etc. Este artículo pone de manifiesto, primeramente, las perversas consecuencias que se derivan de ignorar tales dependencias. A continuación, recorre el camino seguido por la geostadística desde sus inicios hasta el presente, proporcionando al lector los rudimentos básicos del kriging, la técnica que usa la geoestadística para llevar a cabo labores inferenciales. Sin embargo, este artículo no es sólo una visión panorámica de la evolución de la geoestadística hasta nuestros días. También plantea un buen número de críticas, alternativas, cuestiones que todavía permanecen abiertas y futuras líneas de investigación en cada uno de los estadios de la disciplina: espacial, espacio-temporal y funcional. Nacida en el ámbito de las ciencias de la Tierra y aplicada en muchas de las ciencias de la naturaleza, en la actualidad la geoestadística ha encaminado sus pasos hacia las ciencias sociales, y en particular hacia la economía aplicada.
Human fetal globin gene expression is regulated by LYAR

Human globin gene expression during development is modulated by transcription factors in a stage-dependent manner. However, the mechanisms controlling the process are still largely unknown. In this study, we found that a nuclear protein, LYAR (human homologue of mouse Ly-1 antibody reactive clone) directly interacted with the methyltransferase PRMT5 which triggers the histone H4 Arg3 symmetric dimethylation (H4R3me2s) mark. We found that PRMT5 binding on the proximal γ-promoter was LYAR-dependent. The LYAR DNA-binding motif (GGTTAT) was identified by performing CASTing (cyclic amplification and selection of targets) experiments. Results of EMSA and ChIP assays confirmed that LYAR bound to a DNA region corresponding to the 5′-untranslated region of the γ-globin gene. We also found that LYAR repressed human fetal globin gene expression in both K562 cells and primary human adult erythroid progenitor cells. Thus, these data indicate that LYAR acts as a novel transcription factor that binds the γ-globin gene, and is essential for silencing the γ-globin gene.
Three Amino Acid Mutations (F51L, T59A, and S390L) in the Capsid Protein of the Hepatitis E Virus Collectively Contribute to Virus Attenuation

ABSTRACT Hepatitis E virus (HEV) is an important but extremely understudied human pathogen, and the mechanisms of HEV replication and pathogenesis are largely unknown. We previously identified an attenuated genotype 3 HEV mutant (pSHEV-1) containing three unique amino acid mutations (F51L, T59A, and S390L) in the capsid protein. To determine the role of each of these mutations, we constructed three HEV single mutants (rF51L, rT59A, and rS390L) which were all found to be replication competent in Huh7 liver cells. To determine the pathogenicities of the mutants, we utilized the specific-pathogen-free (SPF) pig model for HEV and a unique inoculation procedure that bypasses the need for propagating infectious HEV in vitro. A total of 60 pigs were intrahepatically inoculated, via an ultrasound-guided technique, with in vitro-transcribed full-length capped RNA transcripts from the infectious clones of each single mutant, the pSHEV-1 triple mutant, wild-type pSHEV-3, or phosphate-buffered saline (PBS) buffer (n = 10). The results showed that the F51L mutation partially contributed to virus attenuation, whereas the T59A and S390L mutations resulted in more drastic attenuation of HEV in pigs, as evidenced by a significantly lower incidence of viremia, a delayed appearance and shorter duration of fecal virus shedding and viremia, and lower viral loads in liver, bile, and intestinal content collected at three different necropsy times. The results indicate that the three mutations in the capsid protein collectively contribute to HEV attenuation. This study has important implications for developing a modified live-attenuated vaccine against HEV.