Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic performance model construction for the fast software exploration of new hardware designs

Developing an optimizing compiler for a newly proposed architecture is extremely difficult when there is only a simulator of the machine available. Designing such a compiler requires running many experiments in order to understand how different optimizations interact. Given that simulators are orders of magnitude slower than real processors, such experiments are highly restricted. This paper develops a technique to automatically build a performance model for predicting the impact of program transformations on any architecture, based on a limited number of automatically selected runs. As a result, the time for evaluating the impact of any compiler optimization in early design stages can be drastically reduced such that all selected potential compiler optimizations can be evaluated. This is achieved by first evaluating a small set of sample compiler optimizations on a prior set of benchmarks in order to train a model, followed by a very small number of evaluations, or probes, of the target program.We show that by training on less than 0. 7% of all possible transformations (640 samples collected from 10 benchmarks out of 880000 possible samples, 88000 per training benchmark) and probing the new program on only 4 transformations, we can predict the performance of all program transformations with an error of just 7. 3% on average. As each prediction takes almost no time to generate, this scheme provides an accurate method of evaluating compiler performance, which is several orders of magnitude faster than current approaches.
Optical Trapping Force on a Plasmonic Substrate

Optical trapping is currently widely applied in the field of biotechnology, in which one critical issue is to manipulate cells in the micron-size scale without hurting or damaging them. The plasmonics-assisted optical trapping method is considered to be very promising for achieving more precise trapping of small particles compared to the conventional optical trapping method.In this project, the optical force exerted by an optical beam on a dielectric bead trapped on a substrate proliferated with nanometric gold-pillar pairs is numerically simulated in COMSOL Multiphysics environment. The numerical results show a clearly enhanced trapping capability, which is quantitatively manifested by a ten times higher trapping stiffness as compared to the scenario without the plasmonic-pillar pairs. The simulation results therefore prove that, given the same incident light condition, an appropriately designed nanometric plasmonic substrate can achieve a significantly higher trapping precision albeit Brownian motion; hence less heating damage will be induced in the trapping process, which can be vital for manipulating living cells in biotechnology.
Performance evaluation of TCP and its extensions over lossy links in a small satellite environment

Space communication protocol standards-transport protocol (SCPS-TP) is a set of extensions to transmission control protocol (TCP) aimed at improving TCP performance in space communications. It is expected to have an experimental evaluation of the throughput performance of SCPS-TP over lossy communication links in a small satellite environment, especially by comparing it with standard TCP. This paper describes a performance evaluation of TCP and SCPS-TP over lossy links in a simulated small satellite environment using a test-bed. The results show that SCPS-TP is more tolerant of heavy noise and asymmetric channel and shows a much better performance, which make it more favorable over standard TCP in similar communication environments.
The perceived roughness of resistive virtual textures: I. rendering by a force-feedback mouse

In previous work, we demonstrated that people reliably perceive variations in surface roughness when textured surfaces are explored with a rigid link between the surface and the skin [e.g., Klatzky and Lederman 1999; Klatzky et al. 2003]. Parallel experiments here investigated the potential of a force-feedback mouse to render surfaces varying in roughness. The stimuli were surfaces with alternating regions of high and low resistance to movement in the x (frontal) dimension (called ridges and grooves, respectively). Experiment 1 showed that magnitude ratings of roughness varied systematically with the spatial period of the resistance variation. Experiments 2 and 3 used a factorial design to disentangle the contributions of ridge and groove width. The stimuli constituted eight values of groove width at each of five levels of ridge width (Experiment 2) or the reverse (Experiment 3). Roughness magnitude increased with ridge width while remaining essentially invariant over groove width. Kinematic variations in exploration were observed across the surfaces. The data point to the promise of using inexpensive devices to create virtual textural variations under conditions of unconstrained exploration.
GWCNN: A Metric Alignment Layer for Deep Shape Analysis

Deep neural networks provide a promising tool for incorporating semantic information in geometry processing applications. Unlike image and video processing, however, geometry processing requires handling unstructured geometric data, and thus data representation becomes an important challenge in this framework. Existing approaches tackle this challenge by converting point clouds, meshes, or polygon soups into regular representations using, e.g., multi‐view images, volumetric grids or planar parameterizations. In each of these cases, geometric data representation is treated as a fixed pre‐process that is largely disconnected from the machine learning tool. In contrast, we propose to optimize for the geometric representation during the network learning process using a novel metric alignment layer. Our approach maps unstructured geometric data to a regular domain by minimizing the metric distortion of the map using the regularized Gromov–Wasserstein objective. This objective is parameterized by the metric of the target domain and is differentiable; thus, it can be easily incorporated into a deep network framework. Furthermore, the objective aims to align the metrics of the input and output domains, promoting consistent output for similar shapes. We show the effectiveness of our layer within a deep network trained for shape classification, demonstrating state‐of‐the‐art performance for nonrigid shapes.
Dental caries and its relationship to bacterial infection, hypoplasia, diet, and oral hygiene in 6- to 36-month-old children.

UNLABELLED Caufield et al. (1) have suggested that the acquisition of mutans streptococci in young children most likely takes place during a "window of infectivity" from 19 to 31 months of age. OBJECTIVES AND METHODS This study determined the prevalence of dental caries and bacterial infection in a randomly selected sample of 199 children 6 to 36 months old from the island of Saipan in the Common-wealth of the Northern Mariana Islands, USA. The relationships between caries and Streptococcus mutans infection, hypoplasia, diet and oral hygiene behavior were investigated. RESULTS AND CONCLUSIONS The overall estimated prevalence of caries was high: 46.8% of the children had white spot lesions and 39.1% had enamel cavitation. Colonization was seen in very young children; S. mutans was detected in 25% of the predentate children. The results of multi-variable modeling support the hypothesis that bacterial infection, diet, and hypoplasia are important in the etiology of dental caries in this population. Adjusted for age and ethnicity, children with a high level of S. mutans detected were 5 times more likely to have dental caries than children with a lower level of S. mutans detected. Hypoplasia and a high cariogenicity score (diet) were also significant independent predictors. The odds of having any white spot lesions or enamel cavitation were 9.6 times greater for children with any hypoplasia, and 7.8 times greater for children with high cariogenicity scores relative to those with lower scores after adjusting for level of S. mutans, age and ethnicity. Sleeping with a bottle, maternal sharing of utensils, and high snacking frequency were not significant predictors of caries in this population.
A High-Performance Inter-Domain Data Transferring System for Virtual Machines

Normal 0 7.8 磅 0 2 false false false EN-US ZH-CN X-NONE MicrosoftInternetExplorer4 Virtual machine technology can enhance server utilization and consolidation on an individual physical machine. In a growing number of contexts, many of which require high-performance networking inside of the system. Unfortunately, the development of virtualization technology is inclined to application isolation as yet, leads high communication overheads between virtual machines which are resident on the same physical machine , and also limits the achievable network performance. S ome efforts have been paid to bridge the network I/O performance gap between the virtualization and native environment, but the amelioration is not satisfactory. In this paper, we propose a system called IDTS ( Inter-Domain Transferring System ) which uses the shared memory between different domains (also called hosted or guest OSes) to expand the communication bandwidth and shorten the latency for network applications running in the co-resident VMs. Evaluations are also presented to prove IDTS’s availability and highly efficiency. We believe that IDTS is an effective solution for the inter-domain communication on Xen virtualization platform.
On Multiple Keyword Sponsored Search Auctions with Budgets

We study multiple keyword sponsored search auctions with budgets. Each keyword has multiple ad slots with a click-through rate. The bidders have additive valuations, which are linear in the click-through rates, and budgets, which are restricting their overall payments. Additionally, the number of slots per keyword assigned to a bidder is bounded. We show the following results: (1) We give the first mechanism for multiple keywords, where click-through rates differ among slots. Our mechanism is incentive compatible in expectation, individually rational in expectation, and Pareto optimal. (2) We study the combinatorial setting, where each bidder is only interested in a subset of the keywords. We give an incentive compatible, individually rational, Pareto-optimal, and deterministic mechanism for identical click-through rates. (3) We give an impossibility result for incentive compatible, individually rational, Pareto-optimal, and deterministic mechanisms for bidders with diminishing marginal valuations.
A formation mechanism of transverse cracks on CC slab surface.

Transverse surface cracks were metallographically investigated and the local segregation was found to be the origin of transverse surface cracks on continuously cast slabs. The positive segregation spreaded over an oscillation mark and showed high phosphorous content. At the same time, the sharp negative segregation was also seen adjacent to the positive segregation along the mark. This positive segregation penetrated deeply into austenite grain boundaries, through which transverse cracks propagated. The fractured surface was smooth and the precipitates of MnS was found.Based on the observation, a mechanism of the formation of cracks was proposed. At the meniscus, when the tip of partially solidified shell is bent down periodically during mould oscillation, interdendritic "dirty" liquid is squeezed out and accumulated at the valley of an oscillation mark. In other case, bulk liquid overflows on the tip of the shell and again interdendritic "dirty" liquid spreads out and accumulates there. In any case, the local segregation forms at the valley of an oscillation mark. The cracks lead to initiate at this weak part of the shell under any external stresses. Thus so called internal cracks forms below the oscillation mark and propagates along austenite grain boundaries. Finally a large transverse crack forms on the above-mentioned defect. Some industrial measure were summarized to prevent both the segregation and the cracks to form.
Energy-Efficient Smart Packet Access in WCDMA Networks: Performance with TCP/IP based Applications

This paper presents a performance analysis of adaptive packet access (PA) in WCDMA networks with TCP/IP based applications. The focus is on optimal tradeoffs between energy efficiency and TCP throughput over burst-error correlated fading channels. The channel model is adopted for low mobility PA applications. Both high-speed PA (HSPA) and low-speed PA (LSPA) with radio-link retransmission-and-error-control protocols are studied. By theoretical analysis and simulation, we show that in HSPA adapting the radio-packet retransmission period to the channel conditions significantly reduces the number of retransmissions while maintaining adequate TCP performance. This method is referred to as smart packet dispatching (SPD). In LSPA, adapting the length of radio packets to the channel conditions significantly increases the effective TCP throughput. This method is referred to as smart packet length (SPL). The SPD and SPL, commonly called smart packet access (SPA), are capable of avoiding burst-error states of correlated fading channels and therefore enhance the robustness of radio transmissions and allow the system to operate with much lower fade margin or transmit-power. Furthermore, the SPA schemes improve energy efficiency and system performance without need of excessive signal processing.
An effective data transformation approach for privacy preserving similarity measurement

Data similarity measurement is an important direction for data mining research. This paper is concentrated on the issue of protecting the underlying attribute values when sharing data for the similarity of objects measurement and proposes a simple data transformation method: Isometric-Based Transformation (IBT). IBT selects the attribute pairs and then distorts them with Isometric Transformation. In the process of transformation, the goal is to find the proper angle ranges to satisfy the least privacy preserving requirement and then randomly choose one angle in this interval. The experiment demonstrates that the method can distort attribute values, preserve privacy information and guarantee valid similarity measurement.
Differential Sensitivity of Brainstem versus Cortical Astrocytes to Changes in pH Reveals Functional Regional Specialization of Astroglia

Astrocytes might function as brain interoceptors capable of detecting different (chemo)sensory modalities and transmitting sensory information to the relevant neural networks controlling vital functions. For example, astrocytes that reside near the ventral surface of the brainstem (central respiratory chemosensitive area) respond to physiological decreases in pH with vigorous elevations in intracellular Ca2+ and release of ATP. ATP transmits astroglial excitation to the brainstem respiratory network and contributes to adaptive changes in lung ventilation. Here we show that in terms of pH-sensitivity, ventral brainstem astrocytes are clearly distinct from astrocytes residing in the cerebral cortex. We monitored vesicular fusion in cultured rat brainstem astrocytes using total internal reflection fluorescence microscopy and found that ∼35% of them respond to acidification with an increased rate of exocytosis of ATP-containing vesicular compartments. These fusion events require intracellular Ca2+ signaling and are independent of autocrine ATP actions. In contrast, the rate of vesicular fusion in cultured cortical astrocytes is not affected by changes in pH. Compared to cortical astrocytes, ventral brainstem astrocytes display higher levels of expression of genes encoding proteins associated with ATP vesicular transport and fusion, including vesicle-associated membrane protein-3 and vesicular nucleotide transporter. These results suggest that astrocytes residing in different parts of the rat brain are functionally specialized. In contrast to cortical astrocytes, astrocytes of the brainstem chemosensitive area(s) possess signaling properties that are functionally relevant—they are able to sense changes in pH and respond to acidification with enhanced vesicular release of ATP.
From Glacier Facies to SAR Backscatter Zones via GPR

We present a comparison between data acquired with frequency-modulated ground-penetrating radar (GPR) and satellite synthetic aperture radar (SAR). Both radars are polarimetric and operate at a center frequency of 5.3 GHz. The field site is the polythermal glacier Kongsvegen, Svalbard. Along glacier GPR profiles cover the ablation area and the accumulation area, where the latter consists of superimposed ice (SI) and firn. The glacier facies are clearly identifiable on the GPR profiles, although we show that the copolarized response is better for distinguishing different ice zones, whereas the SI-firn boundary is most obvious in the cross-polarized response. A calibrated backscatter coefficient is calculated for the GPR data and compared with the SAR backscatter coefficient. The SAR zones are in very good agreement with the GPR-derived glacier facies. We show that, in the ablation area, the SAR response is dominated by backscatter from the previous summer surface. In the SI and firn areas, it is dominated by sources below the previous summer surface.
Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products

Background Social media platforms such as Twitter are rapidly becoming key resources for public health surveillance applications, yet little is known about Twitter users’ levels of informedness and sentiment toward tobacco, especially with regard to the emerging tobacco control challenges posed by hookah and electronic cigarettes. Objective To develop a content and sentiment analysis of tobacco-related Twitter posts and build machine learning classifiers to detect tobacco-relevant posts and sentiment towards tobacco, with a particular focus on new and emerging products like hookah and electronic cigarettes. Methods We collected 7362 tobacco-related Twitter posts at 15-day intervals from December 2011 to July 2012. Each tweet was manually classified using a triaxial scheme, capturing genre, theme, and sentiment. Using the collected data, machine-learning classifiers were trained to detect tobacco-related vs irrelevant tweets as well as positive vs negative sentiment, using Naïve Bayes, k-nearest neighbors, and Support Vector Machine (SVM) algorithms. Finally, phi contingency coefficients were computed between each of the categories to discover emergent patterns. Results The most prevalent genres were first- and second-hand experience and opinion, and the most frequent themes were hookah, cessation, and pleasure. Sentiment toward tobacco was overall more positive (1939/4215, 46% of tweets) than negative (1349/4215, 32%) or neutral among tweets mentioning it, even excluding the 9% of tweets categorized as marketing. Three separate metrics converged to support an emergent distinction between, on one hand, hookah and electronic cigarettes corresponding to positive sentiment, and on the other hand, traditional tobacco products and more general references corresponding to negative sentiment. These metrics included correlations between categories in the annotation scheme (phihookah-positive=0.39; phie-cigs-positive=0.19); correlations between search keywords and sentiment (χ2 4=414.50, P<.001, Cramer’s V=0.36), and the most discriminating unigram features for positive and negative sentiment ranked by log odds ratio in the machine learning component of the study. In the automated classification tasks, SVMs using a relatively small number of unigram features (500) achieved best performance in discriminating tobacco-related from unrelated tweets (F score=0.85). Conclusions Novel insights available through Twitter for tobacco surveillance are attested through the high prevalence of positive sentiment. This positive sentiment is correlated in complex ways with social image, personal experience, and recently popular products such as hookah and electronic cigarettes. Several apparent perceptual disconnects between these products and their health effects suggest opportunities for tobacco control education. Finally, machine classification of tobacco-related posts shows a promising edge over strictly keyword-based approaches, yielding an improved signal-to-noise ratio in Twitter data and paving the way for automated tobacco surveillance applications.
Extension of the ICP Algorithm to Nonrigid Intensity-Based Registration of 3D Volumes

We present in this paper a new registration and gain correction algorithm for 3D medical images. It is intensity based. The basic idea is to represent images by 4D points (xj,yj,zj,ij) and to define a global energy function based on this representation. For minimization, we propose a technique which does not require computing the derivatives of this criterion with respect to the parameters. It can be understood as an extension of the Iterative Closest Point algorithm or as an application of the formalism proposed by L. Cohen (Proceedings of the Fifth International Conference on Computer Vision (ICCV '95), Boston, June 1995). Two parameters enable us to develop a coarse-to-fine strategy both for resolution and for deformation. Our technique presents the advantage of minimizing a well-defined global criterion, to deal with various classes of transformations (for example, rigid, affine, volume spline, and radial basis functions), to be simple to implement, and to be efficient in practice. Results on real brain and heart 3D images are presented to demonstrate the validity of our approach. We also explain how one can compute basic statistics on the deformation parameters to constrain the set of possible deformations by learning and to discriminate between different groups.
Substrate Requirements for Transglutaminases

Thirteen recombinant αA-crystallin mutants were constructed that differed in the type of amino acid residue directly preceding the sole amine donor lysine for transglutaminases in this protein. The capacity of these mutants to be cross-linked to amine acceptor substrates by tissue transglutaminase and factor XIII was assessed. Two different biotinylated glutamine-containing oligopeptides were used as amine acceptor probes. It appears that the type of residue preceding the amine donor lysine has a considerable influence on the substrate potential of αA-crystallin for transglutaminases. This influence shows qualitatively similar trends for tissue transglutaminase and factor XIII and is irrespective of the amine acceptor probe. In general, glycine or aspartic acid before the amine donor lysine has the strongest adverse effects on substrate reactivity, and proline, histidine, and tryptophan are less favorable. Valine, arginine, and phenylalanine, and to a more variable or somewhat lesser extent also serine, alanine, leucine, tyrosine, and asparagine, have an enhancing effect. This pattern of preference is largely in agreement with that observed for the limited number of characterized amine donor lysines in protein substrates for transglutaminases. It can be concluded that tissue transglutaminase and factor XIII have a rather broad yet clearly differentiated tolerance with respect to the residue preceding the amine donor lysine substrate in native proteins.