Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Recursion as a Query Language

We propose a programming paradigm that tries to get close to both the semantic simplicity of relational algebra, and the expressive power of unrestricted programming languages. Its main computational engine is structural recursion on sets. All programming is done within a “nicely” typed lambda calculus, as in Machiavelli [OBB89]. A guiding principle is that how queries are implemented is as important as whether they can be implemented. As in relational algebra, the meaning of any relation transformer is guaranteed to be a total map taking finite relations to finite relations. A naturally restricted class of programs written with structural recursion has precisely the expressive power of the relational algebra. The same programming paradigm scales up, yielding query languages for the complex-object model [AB89]. Beyond that, there are, for example, efficient programs for transitive closure and we are also able to write programs that move out of sets, and then perhaps back to sets, as long as we stay within a (quite flexible) type system. The uniform paradigm of the language suggests positive expectations for the optimization problem. In fact, structural recursion yields finer grain programming therefore we expect that lower-level, and therefore better optimization will be feasible.
Complications of CO2 insufflation during endoscopic vein harvesting

Over the past few decades, the use of endoscopic harvest of the saphenous vein has gained popularity due to a significant reduction in rates of wound infection and improved cosmesis. The widespread adoption of this technique has introduced a set of complications associated with the use CO2 insufflation which facilitates exposure during the vein harvest. We describe a case of pneumoperitoneum with systemic acidosis and subcutaneous air following endoscopic vein harvest for coronary artery bypass grafting and review the complications that may arise from CO2 insufflation during endoscopic vein harvesting.
Fast Max-Margin Matrix Factorization with Data Augmentation

Existing max-margin matrix factorization (M3F) methods either are computationally inefficient or need a model selection procedure to determine the number of latent factors. In this paper we present a probabilistic M3F model that admits a highly efficient Gibbs sampling algorithm through data augmentation. We further extend our approach to incorporate Bayesian nonparametrics and build accordingly a truncation-free nonparametric M3F model where the number of latent factors is literally unbounded and inferred from data. Empirical studies on two large real-world data sets verify the efficacy of our proposed methods.
Synthetic aperture sequential beamforming using spatial matched filtering

Synthetic Aperture Sequential Beamforming (SASB) has shown to achieve a good resolution and high penetration depth. The low complexity at the transducer level of the beam-former makes it ideal for use with a handheld device. SASB with a low F# (≤ 0.5) can achieve even better resolution at the cost of high grating lobes, which causes loss of contrast in the final image. In this paper, Spatial Matched Filtering (SMF) was used instead the second stage of beamformer, in an attempt to suppress the grating lobes. The advantage of SMF over SASB was investigated by pushing the limits of F#, from 1.5 to 0.5. The effect of the number of emissions used in first stage was also investigated. A 3.3 MHz BK Ultrasound 9040 convex array was simulated in Field II on a point scatter phantom and a cyst phantom. The resolution was quantified with the full-width-half-max (FWHM), and the contrast was measured with the 20 dB cystic resolution. The contrast-to-noise ratio (CNR) was calculated for the cyst mimicking phantom. The results showed that SMF achieved similar resolution as SASB and improved grating lobe suppression leading to an increase in contrast. The grating lobes caused by an F# of 0.5 are dominant in the SASB images, but not as much in SMF images. The CNR for a cyst mimicking phantom was improved 7 dB and 6 dB for SMF over SASB at depth 20 mm and 30 mm, with an F# of 0.5 and 256 emissions. The FWHM for SMF was slightly higher than SASB across all depth and parameter settings, with a maximum difference of 0.3 mm. It was demonstrated that SMF can achieve similar resolution to SASB and for certain parameter settings improve the contrast by suppressing the grating lobe artifacts.
Self-Handicapping in Structured and Unstructured Exercise: Toward a Measurable Construct

This article presents three studies representing the development stages of a theoretically driven measure employed to assess the frequency of use of the self-presentational strategy of self-handicapping in exercise contexts (Self-Handicapping Exercise Questionnaire: SHEQ). First a pilot study was conducted to examine the nature of the phenomenology of self-handicaps reported in exercise settings. Study 2 involved item creation, item trimming, and model confirmation. Study 3 concerned factorial validation, cross-validating the self-handicapping measure created in the second study. The outcome was a 20-item measure assessing self-handicapping claims in exercise. The results of both model-testing studies indicated three unique and stable factors addressing self-handicapping claims about making exercise a routine, training in an exercise facility, and healthy physical functioning. Self-handicapping responses were not moderated by gender, age, or exercise setting. Further use and development of the SHEQ is dis.
Influence of Hemianopic Visual Field Loss on Visual Motor Control

Background Homonymous hemianopia (HH) is an anisotropic visual impairment characterized by the binocular inability to see one side of the visual field. Patients with HH often misperceive visual space. Here we investigated how HH affects visual motor control. Methods and Findings Seven patients with complete HH and no neglect or cognitive decline and seven gender- and age-matched controls viewed displays in which a target moved randomly along the horizontal or the vertical axis. They used a joystick to control the target movement to keep it at the center of the screen. We found that the mean deviation of the target position from the center of the screen along the horizontal axis was biased toward the blind side for five out of seven HH patients. More importantly, while the normal vision controls showed more precise control and larger response amplitudes when the target moved along the horizontal rather than the vertical axis, the control performance of the HH patients was not different between these two target motion experimental conditions. Conclusions Compared with normal vision controls, HH affected patients' control performance when the target moved horizontally (i.e., along the axis of their visual impairment) rather than vertically. We conclude that hemianopia affects the use of visual information for online control of a moving target specific to the axis of visual impairment. The implications of the findings for driving in hemianopic patients are discussed.
The Extended On / O Model for High-Speed Data

Understanding and modeling the nature of network traac is critical in designing buuer control to guarantee the required quality of service. It has been known that the network traac exhibits self-similar characteristics, and contains bursts over a wide range of time scales. The Alternating Fractal Renewal Process (AFRP), or On/OO model, has been proposed to model such network traac. According to this model, each user transmits (state 1), or stays idle (state 0), and the duration of each state follows a heavy-tail distribution. Although the AFRP model provided theoretical justiication for the self-similar nature of network traac, its aggregated results are grounded on the fractional Brownian motion, whose marginal distribution is normal. Thus, it can not account for the impulsive nature of real network traac. In this paper we propose the extended AFRP model for the bandwidth requirement of each user versus time. Each user transmits or stays idle, with durations that are heavy-tail distributed, but, unlike the AFRP model, the bandwidth requirement during the transmission state follows a heavy-tail law. We provide proofs for long-range dependence and heavy-tail properties of the propose model, and present comparisons between real and synthesized traac data.
NAOSITE : Nagasaki University ' s Academic Output SITE Title Accelerating collapsed variational bayesian inference for latentdirichlet allocation with nvidia CUDA compatible devices

In this paper, we propose an acceleration of collapsed variational Bayesian (CVB) inference for latent Dirichlet allocation (LDA) by using Nvidia CUDA compatible devices. While LDA is an efficient Bayesian multi-topic document model, it requires complicated computations for parameter estimation in comparison with other simpler document models, e.g. probabilistic latent semantic indexing, etc. Therefore, we accelerate CVB inference, an efficient deterministic inference method for LDA, with Nvidia CUDA. In the evaluation experiments, we used a set of 50,000 documents and a set of 10,000 images. We could obtain inference results comparable to sequential CVB inference.
Racial Discrimination during Adolescence Predicts Mental Health Deterioration in Adulthood: Gender Differences among Blacks

Background Despite the existing knowledge regarding the negative mental health consequences of perceived racial discrimination, very few researchers have used a longitudinal design with long-term follow-up periods to explore gender differences in this association over time. Objective The current longitudinal study aimed to investigate gender differences in predictive role of an increase in perceived racial discrimination during adolescence for mental health deterioration a decade later when they are transitioning to young adulthood. Methods Current study followed 681 Black youths for 18 years from 1994 (mean age 15) to 2012 (mean age 32). All participants spent their adolescence and transition to young adulthood in an economically disadvantaged urban area in the Midwest of the United States. Independent variable was perceived racial discrimination measured in 1999 and 2002. Outcomes were psychological symptoms (anxiety and depression) measured in 1999 and at end of follow-up (2012). Covariates included sociodemographics (age, family structure, and parental employment) measured in 1994. Gender was used to define groups in a multigroup structural equation model to test moderating effects. Results Multigroup structural equation modeling showed that among male Black youth, an increase in perceived racial discrimination from age 20 to 23 was predictive for an increase in symptoms of anxiety and depression from age 20 to 32. Among female Black youth, change in perceived racial discrimination did not predict future change in depressive or anxiety symptoms. Conclusion While racial discrimination is associated with negative mental health consequences for both genders, male and female Black youth differ in regard to long-term effects of an increase in perceived discrimination on deterioration of psychological symptoms. Black males seem to be more susceptible than Black females to the psychological effects of an increase in racial discrimination over time.
Qualification of soft-magnetic shielding materials used in inductive wireless power transmission systems

In inductive wireless power transmission systems often soft-magnetic shielding is used to avoid lossy eddy currents being induced in electrically conducting components like batteries or ground layers of electronic circuits. Datasheet information on such shielding materials are often limited to magnetic permeability and sometimes exemplary loss information. For designing inductive wireless power systems e.g. at variable frequency or different flux excitation, detailed loss information are of interest. Therefore, it is proposed to measure the impact of these materials on the power transmission in a standardized setup, which is closely related to the real application. Here, a configuration as described in the Qi standard for wireless charging of mobile devices published by the Wireless Power Consortium is used as reference. A Figure of Merit (FoM) is presented to qualify materials concerning both a) shielding against conducting components on the backside of the receiving coil and b) establishing a high mutual inductance of the transformer coils, resulting in higher system efficiencies. Furthermore, this paper derives that material saturation is not given in properly designed 5W applications using single material sheets of 20μm thickness.
Robust Unmixing Algorithms for Hyperspectral Imagery

The linear mixture model (LMM) assumes a hyperspectral pixel spectrum to be a linear combination of endmember spectra corrupted by additive noise. This model is widely used for spectral unmixing mainly because of its simplicity. However, the LMM can be inappropriate in presence of nonlinear effects, endmember variability or outliers. This paper presents a comparison between recent robust hyperspectral unmixing algorithms. The mixture models are first introduced followed by the description of their associated unmixing algorithms. The algorithms are then analyzed when considering a real image acquired over the region of Porton Down in England. The results discuss the behavior of each algorithm to unmix these data and compare their ability to detect the natural or man-made outliers in the scene. The obtained results highlight the potential of the studied mixture models to overcome the current limitations of the LMM.
A "divide and conquer" strategy based on situations to achieve reactive collision avoidance in troublesome scenarios

This paper addresses reactive collision avoidance for robots that move in arduous environments (i.e., very dense, complex and cluttered). To achieve this goal, the technique simplifies the difficulty of the navigation by a divide and conquer strategy, which is based on identifying navigational situations and applying the corresponding motion laws. The state of the art in reactive navigation still presents classic limitations such as trap situations due to U-shape obstacles, difficulty to achieve motion among very close obstacles, to obtain oscillation-free and stable motion, to move over directions far from the goal direction or towards the obstacles, or to tune the heuristic or internal parameters. This paper presents a method that overcomes all these limitations. As a result, navigation with this method is successfully achieved in scenarios where existing techniques present a high degree of difficulty to navigate. Outstanding navigation results are reported using a wheelchair vehicle. A discussion and comparison with existing techniques is provided.
Code and Tell: An Exploration of Peer Interviews and Computational Thinking With ScratchJr in the Early Childhood Classroom

The ScratchJr programming language and iPad app were created in a collaboration by Tufts University’s Developmental Technologies Research Group, MIT Media Lab’s Lifelong Kindergarten Group and the Playful Invention Company in order to provide young children with a developmentally appropriate way to learn foundational computer programming while creating animated stories and games. In this thesis, I present a novel activity called “Code and Tell,” designed specifically to supplement early childhood classrooms learning to code and create projects with ScratchJr. Students in three second grade classes learned foundational computational thinking concepts using ScratchJr and applied what they learned to the creation of animated collages, stories, and games. They participated in the Code and Tell activity three times, which involved conducting artifact-based video interviews with each other in pairs using their iPad cameras. Through an exploration of the Code and Tell activity, this thesis seeks to begin to understand the computational thinking learning opportunities that ScratchJr provides to the early childhood classroom when combined with a peer interviewing activity. CODE AND TELL iii
Data parallel acceleration of decision support queries using Cell/BE and GPUs

Decision Support System (DSS) workloads are known to be one of the most time-consuming database workloads that processes large data sets. Traditionally, DSS queries have been accelerated using large-scale multiprocessor. The topic addressed in this work is to analyze the benefits of using high-performance/low-cost processors such as the GPUs and the Cell/BE to accelerate DSS query execution. In order to overcome the programming effort of developing code for different architectures, in this work we explore the use of a platform, Rapidmind, which offers the possibility of executing the same program on both Cell/BE and GPUs. To achieve this goal we propose data-parallel versions of the original database scan and join algorithms. In our experimental results we compare the execution of three queries from the standard DSS benchmark TPC-H on two systems with two different GPU models, a system with the Cell/BE processor, and a system with dual quad-core Xeon processors. The results show that parallelism can be well exploited by the GPUs. The speedup values observed were up to 21x compared to a single processor system.
Novel cyanine-AMP conjugates for efficient 5′ RNA fluorescent labeling by one-step transcription and replacement of [γ-32P]ATP in RNA structural investigation

Two novel fluorescent cyanine-AMP conjugates, F550/570 and F650/670, have been synthesized to serve as transcription initiators under the T7 φ2. 5 promoter. Efficient fluorophore labeling of 5′ RNA is achieved in a single transcription step by including F550/570 and F650/670 in the transcription solution. The current work makes fluorescently labeled RNA readily available for broad applications in biochemistry, molecular biology, structural biology and biomedicine. In particular, site-specifically fluorophore-labeled large RNAs prepared by the current method may be used to investigate RNA structure, folding and mechanism by various fluorescence techniques. In addition, F550/570 and F650/670 may replace [γ-32P]ATP to prepare 5′ labeled RNA for RNA structural and functional investigation, thereby eliminating the need for the unstable and radio-hazardous [γ-32P]ATP.
Design planning for high-performance ASICs

Design planning is emerging as a solution to some of the most difficult challenges of the deep-submicron VLSI design era. Reducing design turnaround time for extremely large designs with ever-increasing clock speeds, while ensuring first-pass implementation success, is exhausting the capabilities of traditional design tools. To solve this problem, we have designed and implemented a hierarchical design planning system that consists of a tightly integrated set of design and analysis tools. The integrated run-time environment, with its rich set of hierarchical, timing-driven design planning and implementation functions, provides an advanced platform for realizing a variety of ASIC and custom methodologies. One of the system's particular strengths is its tight integration with an incremental, static timing engine that assists in achieving timing closure in high-performance designs. The design planner is in production use at IBM internal and at external ASIC design centers.
Assessment of software testing time using soft computing techniques

Application of a soft computing approach in place of traditional statistical techniques has shown a remarkable improvement in reliability prediction. This paper examines and compares Linear Regression (LR) and five machine learning methods: (Artificial Neural Network, Support Vector Machine, Decision Tree, Fuzzy Inference System and Adaptive Neuro-Fuzzy Inference System). These methods are explored empirically to find the effect of severity of errors for the assessment of software testing time. We use two publicly available failure datasets to analyse and compare the regression and machine learning methods for assessing the software testing time. The performance of the proposed model is compared by computing mean absolute error (MAE) and root mean square error (RMSE). Based on the results from rigours experiments, it is observed that model accuracy using FIS and ANFIS method is better and outperformed the model predicted using linear regression and other machine learning methods. Finally, we conclude that Adaptive Neuro-fuzzy Inference System is useful in constructing software quality models having better capability of generalization and less dependent on sample size.
Non-Sparse Regularization and Efficient Training with Multiple Kernels

Learning linear combinations of multiple kernels is an appealing strategy when the right choice of features is unknown. Previous approaches to multiple kernel learning (MKL) promote sparse kernel combinations to support interpretability and scalability. Unfortunately, this `1-norm MKL is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures, we generalize MKL to arbitrary norms. We devise new insights on the connection between several existing MKL formulations and develop two efficient interleaved optimization strategies for arbitrary norms, like `p-norms with p > 1. Empirically, we demonstrate that the interleaved optimization strategies are much faster compared to the commonly used wrapper approaches. An experiment on controlled artificial data experiment sheds light on the appropriateness of sparse, non-sparse and `∞ MKL in various scenarios. Application of `p-norm MKL to three hard real-world problems from computational biology show that non-sparse MKL achieves accuracies that go beyond the state-of-the-art. We conclude that our improvements finally made MKL fit for deployment to practical applications: MKL now has a good chance of improving the accuracy (over a plain sum kernel) at an affordable computational cost.
Cytokine-Induced Injury of the Lacrimal and Salivary Glands

Damages to the lacrimal and salivary glands that accompany various autoimmune diseases are categorized as secondary Sjögren syndrome. Cytokines and free radicals are thought to be responsible for the pathologic changes, but the precise mechanisms are not clear. We evaluated whether cytokines alone can cause the damages in these exocrine tissues, and whether gaseous molecules such as nitric oxide (NO) play a role in these injuries. Various knockout (KO) mice as well as wild-type mice were injected intraperitoneally (i.p.) with the proinflammatory cytokines, IL-12 and IL-18, singly or in combination. Concurrent administration of IL-12 and IL-18 to mice caused serious atrophy in the lacrimal and salivary glands, which was spared when each cytokine was singly administered. Microscopically, there were apparently no infiltrating cells; nonetheless, numerous apoptotic cells were observed in the epithelium, which was confirmed by DNA ladder formation on gel electrophoresis. Serum levels of IFN-&ggr; and NO2/NO3 were markedly elevated. Combined injections of IL-12 and IL-18 caused the same changes in Fas-deficient and Fas-ligand deficient mice, as well as in perforin-KO mice, but the same changes were not detected in inducible NO synthase-KO mice or IFN-&ggr; KO mice. Thus, the synergistic effect of IL-12 and IL-18 was dependent on production of IFN-&ggr; and NO, but independent of Fas/Fas ligand system and perforin-dependent cytotoxic T cells. IL-18 together with IL-12 caused destructive changes in the glandular tissues without apparent lymphocyte infiltration. It is suggested that these cytokines can mediate apoptosis in glandular epithelial cells and that the elevated NO production is responsible for the change.