Miracle-dz/UniFAR-FTUs huggingface dataset:
Value-sensitive automatic code specialization for embedded software

The objective of this work is to create a framework for the optimization of embedded software. We present algorithms and a tool flow to reduce the computational effort of programs, using value profiling and partial evaluation. Such a reduction translates into both energy savings and average-case performance improvement, while preserving a tolerable increase of worst case performance and code size. Our tool reduces the computational effort by specializing frequently executed procedures for the most common values of their parameters. The most effective specializations are automatically searched and identified, and the code is transformed through partial evaluation. Experimental results show that their technique improves both energy consumption and performance of the source code up to more than a factor of two, in average about 35% over the original program. Also, their automatic search engine greatly reduces code optimization time with respect to exhaustive search.
Urban, Suburban, and Rural: Adolescents' Use and Preferences for Fitness Promotion Technologies across Communities

Introduction. An understanding of adolescents' use of technology across ages and communities could allow for future targeted obesity intervention strategies. Methods. Focus groups of adolescents from rural, suburban, and urban cities in three states were conducted. Focus groups were led by a trained facilitator to explore how participants used technologies and whether they applied them for fitness purposes. All focus groups were audio recorded and manually transcribed. Analysis was conducted by three investigators using an iterative process. Results. Five focus groups included adolescents between the ages of 12 and 18 years (20 females and 8 males.) Three themes were derived from our data. First, we found age differences regarding technology applied to fitness. Younger participants described technology as a complement to fitness; older participants viewed technology as a motivator for fitness. Second, differences in fitness approaches existed between rural and urban adolescents. Adolescents in rural communities reported focusing on the outdoors for fitness, while urban adolescents relied on fitness-oriented video games. Both rural and urban teens related having a lack of fitness-focused resources in their communities. Conclusions. Our findings indicate differences in adolescents' application of technology for fitness. Despite adolescents' differing uses of technology across communities, a common need exists to expand their resources.
Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits.

Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere. We evaluate a 'supply-demand' theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying. The theory was implemented in a trait-based soil-plant-atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (Pcanopy ) from soil water potential (Psoil ) and vapor pressure deficit (D). Modeled responses to D and Psoil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients. Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and Pcanopy across nine data sets from seasonally dry tropical forest and piñon-juniper woodland with < 26% mean error. Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root-stem-leaf continuum will simplify parameterization.
On an Abstract Characterization of Bisimulation 1 Am-bisimulation

AM89] and JNW94] present abstract concepts of bisimulation in terms of category theory. This paper deals with the question how to relate these approaches. Futheron it shows how diierent types of bisimulations on event structures can be modelled in terms of the abstract concepts. Bisimulation was introduced by Mil80] and Par81] in order to identify processes that cannot be distinguished by an external agent. Since then various notions of \bisimulation" have been studied, e.g. on labelled transition systems by DNMV90], MS92], on event structures by GG89], GKP92], on petri nets by GV87], ABS91]. Recently attempts have been made to develop an abstract characterization of the various notions of bisimulation, see for example DDNM93] and Mal95]. We focus here on the work of AM89] and JNW94]. AM89] characterize bisimulation (AM-bisimulation) as a coalgebra relative to a functor on the category Class. JNW94] work with a general category M of models with a distinguished subcategory P of path objects. Two objects X 1 and X 2 are called P-bisimular ii there exists an object X in M together with so-called P-open morphisms f i : X ! X i ; i = 1; 2: We study here how AM-bisimulation and P-bisimulation are related. To connect these concepts we use the formalism of path-P-bisimulation of JNW94]. Starting in a setting where one may speak about path-P-bisimulation we prove the equivalence of (strong) path-P-bisimulation and (strong) AM-bisimulation. As every P-bisimulation induces a strong path-P-bisimulation we get the result: If one can introduce the concept of P-bisimulation in a category of models M this bisimulation induces a strong AM-bisimulation. For the reverse direction { i.e. to characterize a given AM-bisimulation on a category M of models in terms of P-bisimulation { numerous assumptions have to be made. In a rst step we switch from AM-bisimulation to path-P-bisimulation. Therefore we have to construct a suitable category P of path objects. Using a theorem of JNW94] which characterizes the situations where strong path-P-bisimulation coincides with P-bisimulation one may conclude that AM-bisimulation is a more general concept than P-bisimulation. As an application we study AM-bisimulation and P-bisimulation on labelled event structures where we consider the concepts of interleaving, step, pomset, history-preserving and strong-history-preserving bisimulation. This paper is a short version of Rog97], which provides the proofs of all theorems. A coalgebra for an endofunctor F on a category C is a pair (A;) where A is an object …
Tumor Demarcation by using Local Thresholding on Selected Parameters obtained from Co-occurrence Matrix of Ultrasound Image of Breast

imaging (US) is the most widely used and important imaging modality in medical domain. Due to certain artifact such as speckle, segmentation of US image has not remained a trivial task. Two stages segmentation process has been used in this paper to detect the solid mass (cancer) in breast US image. GLCM based texture feature image generation followed by local adaptive thresholding. In first, Correlation, Variance, Sum variance and Sum average texture features for all angular relationships has been implemented on original image to obtain the feature images. In Second, adaptive local thresholdinig algorithm is applied recursively by dividing the feature image into nine sub-images and compared with the result of Otsu's global thresholding technique. Results of our algorithm are better.
Vision-Based Object Registration for Real-Time Image Overlay

This paper presents a computer vision based technique for object registration, real-time tracking and image overlay. The capability can be used to superimpose registered medical images such as those from CT or MRI onto a video image of a patient body. Real-time object registration enables an image to be overlaid consistently onto objects even while the objects and cameras viewing it are moving in three dimension. Reliable real-time object registration is carried out by a sequential process of feature detection in the image, correspondence of those features in the model, and object pose calculation. Image overlay is the projection of models, models to be superimposed, onto image planes with object pose. Feature detection is executed by computing normalized correlation to reference images at every point in the small search area. The search area is updated every cycle and its repetition in sequential frames realizes feature tracking. The change of appearance of feature points due to view change is compensated by skewing reference images using the object pose information computed in every cycle during tracking. In feature correspondence, successfully tracked feature points are chosen not only by normalized correlation values , but also by computing variations of geometric invariants from initial values. In the case where feature points do not have simple textures, geometric relationship and constraints between feature points are effective for check of tracking results. " Five Coplanar Points " , which are one of major projective invariants, is used in this paper. After the feature correspondence, object position and orientation is computed from those feature positions in the image. In the case where we have object-centered coordinates of objects, the object pose can be calculated from a monocular image and the problem is formulated as an inverse problem to solve non-linear relationship between object pose and feature positions in the image. This problem can be solved by recursive methods such as Newton's method. Two experimental results to superimpose registered model data are shown. The first example is the tracking of a PC and image overly of the image of an I/O board. The second one is the tracking of a phantom leg with some marks on it and the overlay of a bone model on the view of the leg. These problems are implemented on multiple digital signal processors system with low latency vision hardware. Real-time tracking and image overlay is carried out at frame rate (30 Hz) …
Central Line Bundle Implementation in US Intensive Care Units and Impact on Bloodstream Infections

Background Central line-associated bloodstream infections (CLABSI) represent a serious patient safety issue. To prevent these infections, bundled interventions are increasingly recommended. We examine the extent of adoption of Central Line (CL) Bundle elements throughout US intensive care units (ICU) and determine their effectiveness in preventing CLABSIs. Methodology/Principal Findings In this cross-sectional study, National Healthcare Safety Network (NHSN) hospitals provided the following: ICU-specific NHSN-reported rates of CLABSI/1,000 central line days; policies and compliance rates regarding bundle components; and other setting characteristics. In 250 hospitals the mean CLABSI rate was 2.1 per 1000 central line days and 49% reported having a written CL Bundle policy. However, of those that monitored compliance, only 38% reported very high compliance with the CL Bundle. Only when an ICU had a policy, monitored compliance, and had ≥95% compliance did CLABSI rates decrease. Complying with any one of three CL Bundle elements resulted in decreased CLABSI rates (β = -1.029, p = 0.015). If an ICU without good bundle compliance achieved high compliance with any one bundle element, we estimated that its CLABSI rate would decrease by 38%. Conclusions/Significance In NHSN hospitals across the US, the CL Bundle is associated with lower infection rates only when compliance is high. Hospitals must target improving bundle implementation and compliance as opposed to simply instituting policies.
A naturally occurring variant of Hsp90 that is associated with decanalization

The heat shock protein Hsp90 has been the focus of many studies since it was suggested that it acts to mediate the buffering of phenotypic variation. Hsp90-mediated buffering may result in the accumulation of cryptic genetic variation that, when released either as a consequence of environmental or genetic stress, increases the evolvability of a population. Recent studies using laboratory-induced mutations of Hsp90 and/or chemical inhibition to disrupt Hsp90 function confirm that Hsp90 can buffer cryptic genetic variation. We have previously identified a naturally occurring variant in the charged linker region of the Hsp90 gene, and now examine whether this variant is associated with altered levels of trait variability. The variant is associated with the release of cryptic genetic variation for canalized morphological (bristle) traits, but not for uncanalized morphological (wing and bristle) traits, and the effect on canalized traits depends on culture temperature. This suggests that natural genetic variation in Hsp90 may mediate the evolution of canalized morphological traits even if it does not influence the expression of variation for uncanalized traits.
Self-organizing algorithm for logic circuit based on local rules

This study discusses a learning algorithm for autonomous robots that has five characteristics including autonomous exploration of effective output, low calculation costs, capability for multi-tasking, reusing past knowledge, and handling time series. We propose the use of self-organizing network elements (SONE) as a method for creating learning systems that provide these characteristics. Using this method, we created and evaluated a self-organizing logic circuit. The results of our experiments showed that this learning system met the requirements by being capable of creating a basic logic circuit, learning additional knowledge, controlling a simple robot in a simulation, and solving a maze problem
Persistent pods of the tree Acacia caven: a natural refuge for diverse insects including Bruchid beetles and the parasitoids Trichogrammatidae, Pteromalidae and Eulophidae

Abstract The persistent pods of the tree, Acacia caven that do not fall from the tree provide opportunities for the appearance of a diverse group of insects the following season. Such pods collected during the spring of 1999 in Chile were indehiscent with highly sclerified pod walls. In contrast, persistent pods collected in Uruguay after a wet winter and spring (2002) were partially dehiscent, inducing the deterioration of the woody pods, and consequently exposing the seeds. These persistent pods are a natural refuge for insect species, namely two bruchid beetles (Pseudopachymeria spinipes, Stator furcatus), one scolytidae (Dendroctonus sp), lepidopterous larvae, ant colonies (Camponotus sp), one species of oophagous parasitoid (Uscana espinae group senex), the gregarious larval-pupae parasitoid Monoksa dorsiplana (Pteromalidae) and two species of Horismenus spp. (Eulophidae). The patriline of M. dorsiplana is frequently formed by 1 son + 7 daughters.
Controlled aliasing in parallel imaging

Recently a new parallel imaging strategy, Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA), was introduced, which modifies the appearance of the aliasing artifacts during the acquisition in order to improve the following parallel imaging reconstruction procedure. This concept was successfully applied to simultaneous multi-slice imaging (MS-CAIPIRINHA) [1] and 3D imaging (2D-CAIPIRINHA) [2].
Performance analysis of the Edge Pixel Orientations Histogram

A study on the performance of the Edge Pixel Orientations Histogram is presented in this paper. Edges are detected with the Canny algorithm without and with hysteresis thresholding. The resulting edges are described in No different orientations using the gradient orientation. The two edge images are divided into N × N sub-images. Counting the number of edge pixels with each orientation for each sub-image results in a histogram with 2NoN2 bins. The image descriptor is tested with a subset of the TRECVID 2008 development database k-frames. The resulting Edge Pixel Orientation Histograms will be classified with the K Nearest Neighbour Algorithm and a high level description based on the image semantics is extracted. In particular the concept “images with at least one building” is tested. This descriptor is also used for the JPSearch Alinari image database annotation. Alinari database is composed by a set of 971 high resolution images (3888×2592) shot by professional photographers.
Nonlinear System Modeling With Random Matrices: Echo State Networks Revisited

Echo state networks (ESNs) are a novel form of recurrent neural networks (RNNs) that provide an efficient and powerful computational model approximating nonlinear dynamical systems. A unique feature of an ESN is that a large number of neurons (the “reservoir”) are used, whose synaptic connections are generated randomly, with only the connections from the reservoir to the output modified by learning. Why a large randomly generated fixed RNN gives such excellent performance in approximating nonlinear systems is still not well understood. In this brief, we apply random matrix theory to examine the properties of random reservoirs in ESNs under different topologies (sparse or fully connected) and connection weights (Bernoulli or Gaussian). We quantify the asymptotic gap between the scaling factor bounds for the necessary and sufficient conditions previously proposed for the echo state property. We then show that the state transition mapping is contractive with high probability when only the necessary condition is satisfied, which corroborates and thus analytically explains the observation that in practice one obtains echo states when the spectral radius of the reservoir weight matrix is smaller than 1.
3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Utran Iu Interface Layer 1 (release 1999)

The present document has been developed within the 3 rd Generation Partnership Project (3GPP TM) and may be further elaborated for the purposes of 3GPP. The present document has not been subject to any approval process by the 3GPP Organisational Partners and shall not be implemented. This Specification is provided for future development work within 3GPP only. The Organisational Partners accept no liability for any use of this Specification. Specifications and reports for implementation of the 3GPP TM system should be obtained via the 3GPP Organisational Partners' Publications Offices. No part may be reproduced except as authorized by written permission. The copyright and the foregoing restriction extend to reproduction in all media.
Sample Evaluation for Action Selection in Monte Carlo Tree Search

Building sophisticated computer players for games has been of interest since the advent of artificial intelligence research. Monte Carlo tree search (MCTS) techniques have led to recent advances in the performance of computer players in a variety of games. Without any refinements, the commonly-used upper confidence bounds applied to trees (UCT) selection policy for MCTS performs poorly on games with high branching factors, because an inordinate amount of time is spent performing simulations from each sibling of a node before that node can be further investigated. Move-ordering heuristics are usually proposed to address this issue, but when the branching factor is large, it can be costly to order candidate actions. We propose a technique combining sampling from the action space with a naïve evaluation function for identifying nodes to add to the tree when using MCTS in cases where the branching factor is large. The approach is evaluated on a restricted version of the board game Risk with promising results.
The learning curve associated with the introduction of the subcutaneous implantable defibrillator

Abstract Aims The subcutaneous implantable cardioverter defibrillator (S-ICD) was introduced to overcome complications related to transvenous leads. Adoption of the S-ICD requires implanters to learn a new implantation technique. The aim of this study was to assess the learning curve for S-ICD implanters with respect to implant-related complications, procedure time, and inappropriate shocks (IASs). Methods and results In a pooled cohort from two clinical S-ICD databases, the IDE Trial and the EFFORTLESS Registry, complications, IASs at 180 days follow-up and implant procedure duration were assessed. Patients were grouped in quartiles based on experience of the implanter and Kaplan–Meier estimates of complication and IAS rates were calculated. A total of 882 patients implanted in 61 centres by 107 implanters with a median of 4 implants (IQR 1,8) were analysed. There were a total of 59 patients with complications and 48 patients with IAS. The complication rate decreased significantly from 9.8% in Quartile 1 (least experience) to 5.4% in Quartile 4 (most experience) (P = 0.02) and non-significantly for IAS from 7.9 to 4.8% (P = 0.10). Multivariable analysis demonstrated a hazard ratio of 0.78 (P = 0.045) for complications and 1.01 (P = 0.958) for IAS. Dual-zone programming increased with experience of the individual implanter (P < 0.001), which reduced IAS significantly in the multivariable model (HR 0.44, P = 0.01). Procedure time decreased from 75 to 65 min (P < 0.001). The complication rate and procedure time stabilized after Quartile 2 (>13 implants). Conclusion There is a short and significant learning curve associated with physicians adopting the S-ICD. Performance stabilizes after 13 implants.
Re-Examining the Stop-Signal Task to Test Competing Theories of AD/HD

The current study tested two competing models of Attention-Deficit/Hyperactivity Disorder (AD/HD), the inhibition and state regulation theories, by conducting finegrained analyses of the Stop-Signal Task and another putative measure of behavioral inhibition, the Gordon Continuous Performance Test (G-CPT), in a large sample of children and adolescents. The inhibition theory posits that performance on these tasks reflects increased difficulties for AD/HD participants to inhibit prepotent responses. The model predicts that putative stop-signal reaction time (SSRT) group differences on the Stop-Signal Task will be primarily related to AD/HD participants requiring more warning than control participants to inhibit to the stop-signal and emphasizes the relative importance of commission errors, particularly “impulsive” type commissions, over other error types on the G-CPT. The state regulation theory, on the other hand, proposes response variability due to difficulties maintaining an optimal state of arousal as the primary deficit in AD/HD. This model predicts that SSRT differences will be more attributable to slower and/or more variable reaction time (RT) in the AD/HD group, as opposed to reflecting inhibitory deficits. State regulation assumptions also emphasize the relative importance of omission errors and “slow processing” type commissions over other error types on the G-CPT.