Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconfigurable hybrid beamforming for dual-polarized mmWave MIMO channels

A reconfigurable hybrid beamforming (HBF) system is proposed to flexibly exploit the channel diversities and antenna array directivity in millimeter wave channels. Sub-arrays of antennas can be reconfigured in the proposed HBF system to adjust the spatial and polarization diversities and the array gains according to the channel environments and the relative locations between the transmitter and the receiver. Based on the reconfigurable HBF system, a training procedure is also proposed for the transmitter and the receiver to learn the best operating mode according to channel quality and characteristics. Compared to a fixed HBF system, the reconfigurable HBF system has 3 to 10 dB power gains in channel capacity in various simulated channel conditions.
Parental Volunteering

The No Child Left Behind legislation stipulates that schools offer volunteer opportunities to parents. This study examines the growth patterns of parent volunteerism after implementation of this legislation by national region, metropolitan status, gender, ethnicity, and immigrant status. Using the Bureau of Labor Statistics survey data on volunteers between 2002 and 2008 in a 2-year increment, we find the rate of parental volunteering for education actually decreased since 2002. Even after controlling for parents’ social-demographic characteristics, the likelihood of parents’ engaging in educational volunteering is still lower in 2008 than in prior years. Those who live in the Midwest region and nonmetropolitan areas are more likely to volunteer for education. Mothers, non-Hispanic Whites and citizens also have a higher chance of being involved in educational volunteering. In addition, Hispanic parents in the West are more likely to volunteer for education than their counterparts in the Northeast and South region.
The Influence of Climate, Soil and Pasture Type on Productivity and Greenhouse Gas Emissions Intensity of Modeled Beef Cow-Calf Grazing Systems in Southern Australia

Simple Summary Livestock production systems and the agricultural industries in general face challenges to meet the global demand for food, whilst also minimizing their environmental impact through the production of greenhouse gas (GHG) emissions. Livestock grazing systems in southern Australia are low input and reliant on pasture as a low-cost source of feed. The balance between productivity and GHG emission intensity of beef cow-calf grazing systems was studied at sites chosen to represent a range of climatic zones, soil and pasture types. While the climatic and edaphic characteristics of a location may impact on the emissions from a grazing system, management to efficiently use pasture can reduce emissions per unit product. Abstract A biophysical whole farm system model was used to simulate the interaction between the historical climate, soil and pasture type at sites in southern Australia and assess the balance between productivity and greenhouse gas emissions (expressed in carbon dioxide equivalents, CO2-eq.) intensity of beef cow-calf grazing systems. Four sites were chosen to represent a range of climatic zones, soil and pasture types. Poorer feed quality and supply limited the annual carrying capacity of the kikuyu pasture compared to phalaris pastures, with an average long-term carrying capacity across sites estimated to be 0.6 to 0.9 cows/ha. A relative reduction in level of feed intake to productivity of calf live weight/ha at weaning by feeding supplementary feed reduced the average CO2-eq. emissions/kg calf live weight at weaning of cows on the kikuyu pasture (18.4 and 18.9 kg/kg with and without supplementation, respectively), whereas at the other sites studied an increase in intake level to productivity and emission intensity was seen (between 10.4 to 12.5 kg/kg without and with supplementary feed, respectively). Enteric fermentationand nitrous oxide emissions from denitrification were the main sources of annual variability in emissions intensity, particularly at the lower rainfall sites. Emissions per unit product of low input systems can be minimized by efficient utilization of pasture to maximize the annual turnoff of weaned calves and diluting resource input per unit product.
Reconstruction Error Bounds for Compressed Sensing under Poisson Noise using the Square Root of the Jensen-Shannon Divergence

Reconstruction error bounds in compressed sensing under Gaussian or uniform bounded noise do not translate easily to the case of Poisson noise. Reasons for this include the signal dependent nature of Poisson noise, and also the fact that the negative log likelihood in case of a Poisson distribution (which is directly related to the generalized Kullback-Leibler divergence) is not a metric and does not obey the triangle inequality. There exist prior theoretical results in the form of provable error bounds for computationally tractable estimators for compressed sensing problems under Poisson noise. However, these results do not apply to \emph{realistic} compressive systems, which must obey some crucial constraints such as non-negativity and flux preservation. On the other hand, there exist provable error bounds for such realistic systems in the published literature, but they are for estimators that are computationally intractable. In this paper, we develop error bounds for a computationally tractable estimator which also applies to realistic compressive systems obeying the required constraints. The focus of our technique is on the replacement of the generalized Kullback-Leibler divergence with an information theoretic metric - namely the square root of the Jensen-Shannon divergence, which is related to a symmetrized version of the Poisson log likelihood function. This replacement allows for very simple proofs of the error bounds. Numerical experiments are performed showing the practical use of the technique in signal and image reconstruction from compressed measurements under Poisson noise. Our technique is applicable to signals that are sparse or compressible in any orthornormal basis, and works with high probability for any randomly generated sensing matrix that obeys the non-negativity and flux preservation constraints.
Building a Regular Decision Boundary with Deep Networks

In this work, we build a generic architecture of Convolutional Neural Networks to discover empirical properties of neural networks. Our first contribution is to introduce a state-of-the-art framework that depends upon few hyper parameters and to study the network when we vary them. It has no max pooling, no biases, only 13 layers, is purely convolutional and yields up to 95.4% and 79.6% accuracy respectively on CIFAR10 and CIFAR100. We show that the nonlinearity of a deep network does not need to be continuous, non expansive or point-wise, to achieve good performance. We show that increasing the width of our network permits being competitive with very deep networks. Our second contribution is an analysis of the contraction and separation properties of this network. Indeed, a 1-nearest neighbor classifier applied on deep features progressively improves with depth, which indicates that the representation is progressively more regular. Besides, we defined and analyzed local support vectors that separate classes locally. All our experiments are reproducible and code will be available online, based on TensorFlow.
[Effect of the contour line on cup surface using the Heidelberg Retina Tomograph].

BACKGROUND Significance of topometric follow-up examinations of the optic nerve head in glaucomatous eyes depends on the reproducibility of the calculated parameters. Since the definition of the standard reference plane in software version 1.11 of the Heidelberg Retina Tomograph has been changed, intrapapillary parameters depend directly on the position of the contourline in the sector between -10 degrees to -4 degrees, and therefore on the observer variability to determine the disc border. We evaluated intra- and interobserver variability and present a simple approach to increase reproducibility. METHOD The disc border of 4 glaucomatous eyes, 3 ocular hypertensive eyes and 3 eyes of healthy subjects were traced by two observers, 5 times using the free draw mode and 5 times by the addition of contourline circles. RESULTS We found a median variability of the mean disc radius in sector -10 degrees to -4 degrees of 51 microns, which defines the position of the standard reference plane, resulting in a median variability of the position of the standard reference plane of 33 microns which caused a variability of 81 microns2 of the cup area. Addition of contourline circles smoothing the final contourline along the border of the optic disc resulted in a decrease of the coefficient of variation of the standard reference plane of 3.76% (6.76% vs. 3.0%), of the cup area of 2.34% (3.87% vs. 1.53%) and of the rim volume of 3.41% (9.75% vs. 6.34%). CONCLUSION The calculation of the cup area using software version 1.11 of the Heidelberg Retina Tomograph depends on observer variability. The addition of contourline circles to define the final contourline along the disc border increases reproducibility. However, in follow-up of topometric examinations of the optic nerve head the software supported transfer mode should be used. Comparing topometric data of an individual optic disc in follow-up suppose the same definition of the contourline. Therefore, topometric data evaluated using software version 1.10 or earlier needs to be recalculated.
Frequency and predictors for postpartum fecal incontinence.

OBJECTIVE The goal of this study was to describe the frequency of postpartum fecal incontinence and to examine associated delivery events in a group of women participating in a validation study of a postpartum fecal incontinence survey. STUDY DESIGN A self-administered survey of fecal incontinence symptoms and delivery events was administered to 50 women seen for their 6-week postpartum appointments. An analysis of association between postpartum fecal incontinence and individual delivery characteristics was performed. RESULTS The frequency of at least one fecal incontinence symptom post partum was 38%. Specifically, 24% of women reported incontinence to flatus and 10% incontinence to stool. Vaginal delivery and perineal laceration were associated with an increased risk of reporting at least one symptom. Neither infant birth weight nor parity was associated with an increased risk of postpartum fecal incontinence. Cesarean delivery was associated with a lower frequency of overall fecal incontinence symptoms. CONCLUSION The frequency of postpartum fecal incontinence was higher than previously reported. Similar to other studies, perineal laceration, especially extension into the anal sphincter, was an important risk factor for postpartum fecal incontinence.
A Framework for Regularized Non-Negative Matrix Factorization, with Application to the Analysis of Gene Expression Data

Non-negative matrix factorization (NMF) condenses high-dimensional data into lower-dimensional models subject to the requirement that data can only be added, never subtracted. However, the NMF problem does not have a unique solution, creating a need for additional constraints (regularization constraints) to promote informative solutions. Regularized NMF problems are more complicated than conventional NMF problems, creating a need for computational methods that incorporate the extra constraints in a reliable way. We developed novel methods for regularized NMF based on block-coordinate descent with proximal point modification and a fast optimization procedure over the alpha simplex. Our framework has important advantages in that it (a) accommodates for a wide range of regularization terms, including sparsity-inducing terms like the penalty, (b) guarantees that the solutions satisfy necessary conditions for optimality, ensuring that the results have well-defined numerical meaning, (c) allows the scale of the solution to be controlled exactly, and (d) is computationally efficient. We illustrate the use of our approach on in the context of gene expression microarray data analysis. The improvements described remedy key limitations of previous proposals, strengthen the theoretical basis of regularized NMF, and facilitate the use of regularized NMF in applications.
Making the grade? A review of donor commitment and action on inclusive education for disabled children

At least one‐third of the 72 million children currently missing out on primary education are estimated to be disabled. With just five years remaining to achieve the Millennium Development and Education for All (EFA) goals, global efforts to ensure all children complete a full cycle of primary education by 2015 will fail if bilateral and multilateral donor support for education does not prioritise the inclusion of disabled children. This paper reviews the commitments and practices of key EFA Fast Track Initiative (FTI) donors in relation to early childhood and primary education for disabled children between 2005 and 2008/9. The review highlights that, while a number of FTI donor partners are beginning to pay greater attention to the inclusion of disabled children in education through their international development cooperation and policy commitments, this has not been accompanied by sustained and systematic action. Weak political will and continued marginalisation of the issue of education for disabled children from the mainstream EFA agenda threatens to impede current efforts towards ‘education for all’.
Subliminal influence on preferences? A test of evaluative conditioning for brief visual conditioned stimuli using auditory unconditioned stimuli

In the field of evaluative conditioning (EC), two opposing theories—propositional single-process theory versus dual-process theory—are currently being discussed in the literature. The present set of experiments test a crucial prediction to adjudicate between these two theories: Dual-process theory postulates that evaluative conditioning can occur without awareness of the contingency between conditioned stimulus (CS) and unconditioned stimulus (US); in contrast, single-process propositional theory postulates that EC requires CS-US contingency awareness. In a set of three studies, we experimentally manipulate contingency awareness by presenting the CSs very briefly, thereby rendering it unlikely to be processed consciously. We address potential issues with previous studies on EC with subliminal or near-threshold CSs that limited their interpretation. Across two experiments, we consistently found an EC effect for CSs presented for 1000 ms and consistently failed to find an EC effect for briefly presented CSs. In a third pre-registered experiment, we again found evidence for an EC effect with CSs presented for 1000 ms, and we found some indication for an EC effect for CSs presented for 20 ms.
Demineralization Depth Using QLF and a Novel Image Processing Software

Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model was Y = 0.32X + 0.17, where X was the percent loss of fluorescence and Y was the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating the P-value = . 0014. The F test for the entire model was 62.86, which shows the P-value = . 0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization.
Design and Implementation of Low Power Multiternary Digit Adder

This paper presents an efficient multiternary digit (trit) adder design using decoder. Ternary logic is three valued logic represented by 0,1,2. The adder is based on an efficient single-trit full-adder design with low-complexity encoder and reduced complexity carry generation unit. The number of encoder and decoder blocks required while putting together several single-trit full-adder units to realize a multitrit adder. The ripple carry adder is designed using the ternary fulladder. Extensive simulation results shows the proposed multitrit adder design using decoder has low power and less area compared to the multi trit adder using multiplexer.
Non-Gaussian background modeling for anomaly detection in hyperspectral images

In this paper, we address the problem of unsupervised detection of anomalies in hyperspectral images. Our proposed method is based on a novel statistical background modeling approach that combines local and global approaches and does not assume Gaussianity. The local-global background model has the ability to adapt to all nuances of the background process, like local models, but avoids overfitting that may result due a too high number of degrees of freedom, producing a high false alarm rate. This is achieved by globally combining the local background models into a “dictionary”, which serves to remove false alarms. Experimental results strongly prove the effectiveness of the proposed algorithm. These results show that the proposed local-global algorithm performs better than several other local or global anomaly detection techniques, such as the well known RX or its Gaussian Mixture version (GMM-RX).
Overview of the NTCIR-11 IMine Task

In this paper, we provide an overview of the NTCIR IMine task, which is a core task of NTCIR-11 and also a succeeding work of INTENT@NTCIR-9 and INTENT2@NTCIR-10 tasks. IMine is composed of a subtopic mining (SM) task, a document ranking (DR) task and a TaskMine (TM) pilot task. 21 groups from Canada, China, Germany, France, Japan, Korea, Spain, UK and United States registered to the task, which makes it one of the largest tasks in NTCIR-11. Finally, we receive 45 runs from 10 teams to the SM task, 25 runs from 6 groups to the DR task and 3 runs from 2 groups to the TM task. We describe the task details, annotation of results, evaluation strategies and then the official evaluation results for each subtask.
The bitmap-based feature selection method

CBR(Case-Based Reasoning) is a problem solving technique that reuses past cases and experiences to find a solution to current problems. A critical issue in case-based reasoning is to select the correct and enough features to represent a case. However, this task is difficult to carry out since such knowledge is often exhaustively captured and cannot be represented successfully. In this paper, the new, efficient feature selection method originated from bitmap indexing and rough set techniques will be proposed. The bitmap-based feature selection method is proposed for discovering the optimal feature sets for decision-making problems. And the corresponding indexing and selecting algorithms for such feature selection method are also proposed. Finally, some experiments and comparisons are given and the result shows the efficiency and accuracy of our proposed method.
Using Expert-based Bayesian Networks as Decision Support Systems to Improve Project Management of Healthcare Software Projects

One of the pillars for sound Software Project Management is reliable effort estimation. Therefore it is important to fully identify what are the fundamental factors that affect an effort estimate for a new project and how these factors are inter-related. This paper describes a case study where a Bayesian Network model to estimate effort for healthcare software projects was built. This model was solely elicited from expert knowledge, with the participation of seven project managers, and was validated using data from 22 past finished projects. The model led to numerous changes in process and also in business. The company adapted their existing effort estimation process to be in line with the model that was created, and the use of a mathematically-based model also led to an increase in the number of projects being delegated to this company by other company branches worldwide.
Influence of different types of sessile epibionts on the community structure of mobile invertebrates in an eelgrass bed

Eelgrass (Zostera marina) beds are known to have high ecological and economical values within coastal ecosystems of the temperate northern hemisphere although their biodiversity and functions varied greatly from sites to sites. The variation in the biomass, abundance and diversity of mobile invertebrates in eelgrass beds has been examined in relation to various abiotic and biotic factors, such as water temperature, salinity, eelgrass biomass and epiphytic microalgae presence. However, the importance of sessile epibionts, such as macroalgae and calcific spirorbid polychaetes attached to eelgrass blades, has not been the focus of previous studies. In the present study, we examined the effects of three different sessile epibionts, namely, branched red algae, filamentous green algae, and calcific spirorbid polychaetes, on the biomass and diversity of mobile invertebrates in the eelgrass beds of Akkeshi in northeastern Japan. The relationships between seven abiotic and biotic variables including three types of epibionts, and biomass of 11 dominant mobile invertebrate species as well as three community-level variables (the total biomass of mobile invertebrates, species richness and the Shannon-Wiener species diversity index) were analyzed using a linear mixed model. Our results show that branched red algae are correlated with Pontogeneia rostrata, Lacuna spp. , Nereis sp. , Syllis sp. and the total biomass of mobile invertebrates, filamentous green algae with P. rostrata, Ansola angustata and the species diversity of mobile invertebrates, and spirorbid polychaetes with A. angustata, Lacuna spp. , Siphonacmea oblongata, Syllis sp. , the species richness and diversity of mobile invertebrates. The effect size of the epibionts was similar or even higher than that of abiotic and eelgrass factors on the total biomass of mobile invertebrates, species richness, species diversity and most of dominant invertebrate populations across the taxonomic groups. Consequently, epibiotic macroalgae and spirorbid polychaetes can be good predictors of the variation in the total biomass, species richness and species diversity of mobile invertebrates and the biomass of major dominant species, especially for species that have a relatively high dependency on eelgrass blades. These results suggest that the different functional groups of sessile epibionts have significant roles in determining the biomass and diversity of mobile invertebrates in eelgrass beds.