Miracle-dz/UniFAR-FTUs huggingface dataset:
A Default Hierarchy for Pronouncing English

The authors study the principles governing the power and efficiency of the default hierarchy, a system of knowledge acquisition and representation. The default hierarchy trains automatically, yet yields a set of rules which can be easily assessed and analyzed. Rules are organized in a hierarchical structure containing general (default) and specific rules. In training the hierarchy, general rules are learned before specific rules. In using the hierarchy, specific rules are accessed first, with default rules used when no specific rules apply. The main results concern the properties of the default hierarchy architecture, as revealed by its application to English pronunciation. Evaluating the hierarchy as a pronouncer of English, the authors find that its rules capture several key features of English spelling. The default hierarchy pronounces English better than the neural network NETtalk, and almost as well as expert-devised systems. >
Imprisoned by Empathy

The stress process model predicts that current incarceration of a family member should damage the health status of the inmate’s relatives. We address this prediction with data from the National Survey of American Life, focusing exclusively on African American men (n = 1,168). In survey-adjusted generalized linear models, we find that familial incarceration increases psychological distress, but its effect attenuates ostensibly after controlling for other chronic strains. Familial incarceration remains statistically insignificant with the introduction of mastery and family emotional support and their respective interactions with familial incarceration. However, a statistical interaction between familial incarceration and former incarceration reveals that levels of psychological distress are significantly higher among never-incarcerated respondents whose family members are incarcerated but significantly lower among formerly incarcerated respondents whose family members are incarcerated. We conclude that familial incarceration’s influence on black men’s mental health status may be more complex than extant theory predicts.
Socioeconomic and Racial-ethnic Disparities in Prosocial Health Attitudes

Research on prosocial attitudes, social networks, social capital, and social stratification suggest that lower–socioeconomic status (SES), Hispanic, and nonwhite individuals will be more likely than their higher-SES and non-Hispanic white counterparts to engage in health behaviors that serve a social good. Analyzing data from the University of North Carolina Human Papillomavirus (HPV) Immunization in Sons Study, we test whether SES and race-ethnicity are associated with willingness to vaccinate via prosocial attitudes toward HPV vaccination among adolescent males (n = 401) and parents (n = 518). Analyses revealed that (a) parents with lower education and (b) black and Hispanic parents and adolescent males reported higher prosocial vaccination attitudes, but only some attitudes were associated with higher willingness to vaccinate. We discuss these findings in terms of how prosocial attitudes may motivate certain health behaviors and serve as countervailing mechanisms in the (re)production of health disparities and promising targets of future public health interventions.
How far are the left-behind left behind? A preliminary study in rural China

While the linkage between migration and development has attracted much academic and policy attention, a key aspect of the linkage, namely those left behind in the community of origin, remains under-researched. As one of the first academic attempts to provide a systematic overview of this group in China, this paper describes the basic problems faced by it, discusses the institutional causes of the problems, and explores long-term and short-term solutions. The paper first establishes the fact that, while it seems that individuals decide who migrates and who stays back, there are fundamental institutional constraints on such decisions. The paper then shows that the three main left-behind groups, namely wives, the elderly and children, encounter various problems, but in general their situation is not much worse than that of those living with all family members. Their problems cannot just be attributed to being left-behind individuals; instead, the fundamental cause is that many rural communities as a whole have been left behind economically and socially. Although migration exacerbates the hardship, preventing migration is certainly not a solution. The paper instead calls for measures to redress the urban–rural divide and to improve the provision of public goods in rural communities. Copyright © 2006 John Wiley & Sons, Ltd.
Integrated segmentation of cellular structures

Automatic segmentation of cellular structures is an essential step in image cytology and histology. Despite substantial progress, better automation and improvements in accuracy and adaptability to novel applications are needed. In applications utilizing multi-channel immuno-fluorescence images, challenges include misclassification of epithelial and stromal nuclei, irregular nuclei and cytoplasm boundaries, and over and under-segmentation of clustered nuclei. Variations in image acquisition conditions and artifacts from nuclei and cytoplasm images often confound existing algorithms in practice. In this paper, we present a robust and accurate algorithm for jointly segmenting cell nuclei and cytoplasm using a combination of ideas to reduce the aforementioned problems. First, an adaptive process that includes top-hat filtering, Eigenvalues-of-Hessian blob detection and distance transforms is used to estimate the inverse illumination field and correct for intensity non-uniformity in the nuclei channel. Next, a minimum-error-thresholding based binarization process and seed-detection combining Laplacian-of-Gaussian filtering constrained by a distance-map-based scale selection is used to identify candidate seeds for nuclei segmentation. The initial segmentation using a local maximum clustering algorithm is refined using a minimum-error-thresholding technique. Final refinements include an artifact removal process specifically targeted at lumens and other problematic structures and a systemic decision process to reclassify nuclei objects near the cytoplasm boundary as epithelial or stromal. Segmentation results were evaluated using 48 realistic phantom images with known ground-truth. The overall segmentation accuracy exceeds 94%. The algorithm was further tested on 981 images of actual prostate cancer tissue. The artifact removal process worked in 90% of cases. The algorithm has now been deployed in a high-volume histology analysis application.
Die Ni‐Cu‐Diffusion in elektrolytisch hergestellten dünnen Nickelschichten

Institut fLir Magnetische Werkstoffe, Jena, der Deutschen Akademie der Wissenschaften zu Berlin Die Ni-Cu-Ditfusion in elektrolytisch hergesteliten dimen Nickels chic hc en Von Werner RUSK8 Friihere Messungen an auf Cu-Unterlagen niedergeschlagenen Ni-Schichten (1) haben gezeigt, da13 die bei einer Wiirmebehandlung der Schichten auftretende Abnahme der Sattigungsmasnetisierung auf eine Diffusion der Niund Cu-Atome im System Ni-Cu zuruckgefiihrt werden kann. Die damals n u fib? zwei Temperaturen (200' und 63OoC), aber bei verschiedenen Schichtdicken durchgefiikrten Messwen wurden nun auf aas daswischenliegende Temperaturintervall erweitert.
Phantom validation for ultrasound to statistical shape model registration of human pelvis

Total Hip Replacement (THR) has become a common surgical procedure in recent years, as a result of increasing aging population with osteoarthritis of the hip joint. Localization of the pelvic anatomical coordinate system (PaCS) is a critical step in accurate placement of the femur prosthesis in the acetabulum in THR. Intra-operative ultrasound (US) imaging can provide a radiation-free navigation system for localization of the PaCS. However, US images are noisy and cannot provide any anatomical information beneath the bone surface due to the total reflection of US beam at the bone-soft tissue interface. A solution to this problem is to fuse intra-operative US with pre-operative imaging or a statistical shape model (SSM) of the pelvis. Here, we propose a multi-slice to volume intensity-based registration of the pelvic SSM to a sparse set of 2D US images in order to localize the PaCS in the US. In this registration technique, a set of 2D slices are extracted from a pelvic SSM using the approximate location and orientation of their corresponding 2D US images. During the registration, the comparison between the SSM slices and the US images is made using an ultrasound simulation technique and a correlation-based similarity metric. We demonstrate the feasibility of our proposed approach in localizing the PaCS on five patient-based phantoms. These results indicate the necessity of including pubic symphysis landmarks in the 2D US slices in order to have a precise estimation of the PaCS.
Poor Performance on Serial Visual Tasks in Persons With Reading Disabilities

The present study investigates the performance of persons with reading disabilities (PRD) on a variety of sequential visual-comparison tasks that have different working-memory requirements. In addition, mediating relationships between the sequential comparison process and attention and memory skills were looked for. Our findings suggest that PRD perform worse than normally achieving readers (NAR) when the task requires more than a minimal amount of working memory, unrelated to presentation rate. We also demonstrate high correlations between performance on the task with the most working-memory demands and reading-related skills, suggesting that poor working-memory abilities may be one of the underlying mechanisms of dyslexia. The mediating model analysis indicates that order judgment tasks are mediating to verbal working memory, suggesting that visual sequence memory precedes auditory sequence memory. We further suggest that visual tasks involving sequential comparisons could probe for poor working memory in PRD.
Participatory Action Research: A Protective Research Design

This commentary briefly reviews the ethical considerations for protection of workers participating in research. We argue that many IRBs may not fully understand the nature of collaborative and participatory research methods; consequently, this may delay IRB approval or worse, reduce the effectiveness of IRB oversight. A U.S. workplace participatory action research (PAR) project with which we are involved illustrates how researcher-worker-employer teams can navigate human subject oversight procedures (IRB approval). By design, successful and effective PAR projects incorporate, and often exceed the ethical principles espoused by current IRB principles.
Seismic event detection using three-component data

Presents an approach for the detection of seismic events using three-component data obtained from three orthogonally placed seismometers. In the first stage of processing, a detection parameter is computed as a function of the autocorrelation coefficients of the three data channels. This parameter is then input to a detector which uses the concept of comparing a short time average of the parameter against a delayed, long-term average of the parameter to produce a detector output. This algorithm is capable of detecting extremely weak signals of signal-to-noise ratios (SNRs) as low as -6 dB while keeping false alarms down to a minimum. Results obtained by using the algorithm on synthesized data as well as on field-acquired data are presented. >
Investigation of the robustness of two models for assessing synergy in pre‐clinical drug combination studies

Pre‐clinical studies may be used to screen for synergistic combinations of drugs. The types of in vitro assays used for this purpose will depend upon the disease area of interest. In oncology, one frequently used study measures cell line viability: cells placed into wells on a plate are treated with doses of two compounds, and cell viability is assessed from an optical density measurement corrected for blank well values. These measurements are often transformed and analysed as cell survival relative to untreated wells. The monotherapies are assumed to follow the Hill equation with lower and upper asymptotes at 0 and 1, respectively. Additionally, a common variance about the dose–response curve may be assumed. In this paper, we consider two models for incorporating synergy parameters. We investigate the effect of different models of biological variation on the assessment of synergy from both of these models. We show that estimates of the synergy parameters appear to be robust, even when estimates of the other model parameters are biased. Using untransformed measurements provides better coverage of the 95% confidence intervals for the synergy parameters than using transformed measurements, and the requirement to fit the upper asymptote does not cause difficulties. Assuming homoscedastic variances appears to be robust. The added complexity of determining and fitting an appropriate heteroscedastic model does not seem to be justified. Copyright © 2013 John Wiley & Sons, Ltd.
Development of geophysical retrieval algorithms for the MIMR

The feasibility of using spaceborne microwave radiometry to retrieve geophysical parameters is described. The study concentrates on the development of inversion techniques for multichannel spaceborne radiometers, especially the statistical inversion approach. The applications of the planned MIMR (Multi-Frequency Imaging Microwave Radiometer) instrument are discussed. The inversion algorithms used are conventional algorithms for different applications and the statistical inversion approach. Comparisons between results from different inversion algorithms are presented. The statistical inversion approach has been found to give promising parameter retrieval accuracies and has the potential to improve the operational use of passive spaceborne remote sensing. An analysis of the sensitivity of the radiometer apparent temperature to different geophysical parameters and the statistical behavior of the atmospheric transmissivity are presented. >
Early Oral Language Markers of Poor Reading Performance in Hong Kong Chinese Children

This study investigated the extent to which language skills at ages 2 to 4 years could discriminate Hong Kong Chinese poor from adequate readers at age 7. Selected were 41 poor readers (age M = 87.6 months) and 41 adequate readers (age M = 88.3 months). The two groups were matched on age, parents’ education levels, and nonverbal intelligence. The following language tasks were tested at different ages: vocabulary checklist and Cantonese articulation test at age 2; nonword repetition, Cantonese articulation, and receptive grammar at age 3; and nonword repetition, receptive grammar, sentence imitation, and story comprehension at age 4. Significant differences between the poor and adequate readers were found in the age 2 vocabulary knowledge, age 3 Cantonese articulation, and age 4 receptive grammar skill, sentence imitation, and story comprehension. Among these measures, sentence imitation showed the greatest power in discriminating poor and adequate readers.
An efficient analysis of covariance model for crossover thorough QT studies with period‐specific pre‐dose baselines

Baseline adjustment is an important consideration in thorough QT studies for non‐antiarrhythmic drugs. For crossover studies with period‐specific pre‐dose baselines, we propose a by‐time‐point analysis of covariance model with change from pre‐dose baseline as response, treatment as a fixed effect, pre‐dose baseline for current treatment and pre‐dose baseline averaged across treatments as covariates, and subject as a random effect. Additional factors such as period and sex should be included in the model as appropriate. Multiple pre‐dose measurements can be averaged to obtain a pre‐dose‐averaged baseline and used in the model. We provide conditions under which the proposed model is more efficient than other models. We demonstrate the efficiency and robustness of the proposed model both analytically and through simulation studies. The advantage of the proposed model is also illustrated using the data from a real clinical trial. Copyright © 2014 John Wiley & Sons, Ltd.
Measurements in a FDDI workstation cluster

We study the throughput characteristics of a FDDI workstation cluster installed at the University of Paderborn. We compare theoretical results to the performance really available to the user at the service access point to TCP and UDP. Furthermore, we compare the performance for two difficult operating systems: we consider the SUN-OS based on BSD and the new Solaris 2.3 developed for multiprocessor environments. The measurement results showed a maximum throughput of less than 60 Mbps which is still considerably less than the bandwidth promised by FDDI vendors. Moreover, it becomes clear that high throughput absolutely requires the transmission of large frames. We also briefly address the current discussion on higher speed LANs within IEEE 802. <<ETX>>
Effects of concurrent tasks on diagnostic decision making: An experimental investigation

Physicians’ decision-making performance is one of the most important factors in healthcare system engineering. Multitasking and interruptions while making diagnostic decisions have been frequently observed in the healthcare work environment. However, little evidence from controlled experiments is available to determine whether physician multitasking affects the quality and timely performance of diagnostic decisions. In the current study, we designed a diagnostic task to examine the effects of concurrent tasks on diagnostic decision making using a controlled laboratory experiment, in which potential confounding factors were controlled to allow the quantification of diagnostic performance and strategies. The results showed that diagnostic performance was negatively affected by a complex concurrent memorization task that required participants to listen to verbal updates and remember information about other patients while performing the diagnostic task. In contrast, a simple concurrent sound monitoring task did not affect diagnostic performance. Both types of concurrent tasks significantly increased mental workload. Diagnostic decision strategies were not significantly different between the single- and dual-task conditions. These findings provide new insights into the cognitive mechanisms underlying diagnostic decision and physician multitasking. Implications for the control and improvement of healthcare quality are discussed.
LARGE-SCALE SIMULATION OF BEAM DYNAMICS IN HIGH INTENSITY ION LINACS USING PARALLEL SUPERCOMPUTERS

In this paper we present results of using parallel supercomputers to simulate beam dynamics in next-generation high intensity ion linacs. Our approach uses a three-dimensional space charge calculation with six types of boundary conditions. The simulations use a hybrid approach involving transfer maps to treat externally applied fields (including rf cavities) and parallel particle-in-cell techniques to treat the space-charge fields. The large-scale simulation results presented here represent a three order of magnitude improvement in simulation capability, in terms of problem size and speed of execution, compared with typical two-dimensional serial simulations. Specific examples will be presented, including simulation of the spallation neutron source (SNS) linac and the Low Energy Demonstrator Accelerator (LEDA) beam halo experiment.
Precipitation retrieval from spaceborne microwave radiometers based on maximum a a posteriori probability estimation

A retrieval technique for estimating rainfall rate and precipitating cloud parameters from spaceborne multifrequency microwave radiometers is described. The algorithm is based on the maximum a posteriori probability criterion (MAP) applied to a simulated data base of cloud structures and related upward brightness temperatures. The cloud data base is randomly generated by imposing the mean values, the variances, and the correlations among the hydrometeor contents at each layer of the cloud vertical structure, derived from the outputs of a time-dependent microphysical cloud model. The simulated upward brightness temperatures are computed by applying a plane-parallel radiative transfer scheme. Given a multifrequency brightness temperature measurement, the MAP criterion is used to select the most probable cloud structure within the cloud-radiation data base. The algorithm is computationally efficient and has been numerically tested and compared against other methods. Its potential to retrieve rainfall over land has been explored by means of Special Sensor Microwave/Imager measurements for a rainfall event over Central Italy. The comparison of estimated rain rates with available raingauge measurements is also shown.
Time-varying ice crystal orientation in thunderstorms observed with multiparameter radar

Repeated changes associated with lightning have been observed with multiparameter radar in the echoes from the tops of Florida thunderstorms. These lightning-related radar signatures are interpreted as changes in the orientation of ice crystals being preferentially aligned parallel to the in-cloud electric field. The changes occur at intervals on the order of 10 s and are easily observed in the signatures of the differential propagation phase shift and the linear depolarization ratio which are sensitive to propagation effects caused by the oriented ice crystals. The orientation of ice crystals aloft has been previously observed using circularly polarized radar while the simultaneous differential phase shift and linear depolarization measurements reported were obtained with a dual-linear polarized radar. The observations indicate crystal orientation angles greater than 450 and occasionally near vertical. In one case, the crystals were found to be oriented in a layer near radar cloud top spanning a 20-km range and 3 km in depth.
Using Machine Learning Techniques to Identify Botnet Traffic

To date, techniques to counter cyber-attacks have predominantly been reactive; they focus on monitoring network traffic, detecting anomalies and cyber-attack traffic patterns, and, a posteriori, combating the cyber-attacks and mitigating their effects. Contrary to such approaches, we advocate proactively detecting and identifying botnets prior to their being used as part of a cyber-attack [12]. In this paper, we present our work on using machine learning-based classification techniques to identify the command and control (C2) traffic of IRC-based botnets — compromised hosts that are collectively commanded using Internet Relay Chat (IRC). We split this task into two stages: (I) distinguishing between IRC and non-IRC traffic, and (II) distinguishing between botnet and real IRC traffic. For Stage I, we compare the performance of J48, naive Bayes, and Bayesian network classifiers, identify the features that achieve good overall classification accuracy, and determine the classification sensitivity to the training set size. While sensitive to the training data and the attributes used to characterize communication flows, machine learning-based classifiers show promise in identifying IRC traffic. Using classification in Stage II is trickier, since accurately labeling IRC traffic as botnet and non-botnet is challenging. We are currently exploring labeling flows as suspicious and non-suspicious based on telltales of hosts being compromised.
A new denoising method in high-dimensional PCA-space

Kernel-design based method such as Bilateral filter (BIL), non-local means (NLM) filter is known as one of the most attractive approaches for denoising. We propose in this paper a new noise filtering method inspired by BIL, NLM filters and principal component analysis (PCA). The main idea here is to perform the BIL in a multidimensional PCA-space using an anisotropic kernel. The filtered multidimensional signal is then transformed back onto the image spatial domain to yield the desired enhanced image. In this work, it is demonstrated that the proposed method is a generalization of kernel-design based methods. The obtained results are highly promising.