Miracle-dz/UniFAR-FTUs huggingface dataset:
Power macromodeling for a high quality RT-level power estimation

Several approaches that address early power estimation in digital design have been published in the last few years. Most of them are based on a fast (coarse) logic synthesis step, in order to analyze power on the mapped gate-level netlist. In this paper we present a summary of RTPow, a proprietary tool dealing with the RT-level power estimation, relying on a top-down estimation engine that does not perform any type of on-the-fly logic synthesis when analyzing the HDL description. In addition, a set of power macromodeling capabilities have been developed as well, to enable an effective power budgeting and automatic bottom-up power characterization methodology.
Entrapped Posteromedial Structures in Pilon Fractures

Objectives: To analyze a patient cohort who sustained a tibial pilon fracture and report the incidence of interposed posteromedial soft tissue structures. Design: Retrospective cohort review. Setting: Regional Level 1 Trauma Center. Patients/Participants: About 394 patients with 420 pilon fractures treated between January 2005 and November 2011. Intervention: Each patient's preoperative radiographs and computed tomography (CT) images were reviewed. The axial and reconstructed images were used in bone and soft tissue windows to identify any posteromedial soft tissue structures incarcerated within the fracture. Main Outcome Measurements: Medical charts reviewed for the presence of preoperative neurologic deficit, separate posteromedial incision, and whether attending radiology CT interpretation noted the interposed structure. Results: 40 patients with 40 fractures (9.5%) had an entrapped posteromedial structure. The tibialis posterior tendon was interposed in 38/40 fractures (95%) and the posterior tibial neurovascular bundle in 4/40 fractures (10%). Preoperative neurologic deficit occurred in 5/40 patients (12%). A posteromedial incision was used in 11/40 fractures (27%). The attending radiology CT interpretation noted the interposed structure in 8/40 fractures (20%). Conclusions: In addition to the osseous injuries, CT imaging can demonstrate the posteromedial soft tissue structures. In our series, the tibialis posterior tendon was commonly incarcerated. In some cases, removal of the entrapped structure(s) may not be possible through the more commonly used anterolateral and anteromedial surgical approaches, and a separate posteromedial exposure may be required. Failure to recognize the presence of an interposed structure could lead to malreduction, impaired tendon function, neurovascular insult, and the need for further surgery. Level of Evidence: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
The effects of GUI on users' creative performance in computerized drawing

This paper presents the results of an empirical comparative study investigating how the outcomes of a computerized figural creativity test are affected when the participants use two different versions of the Graphical User Interface (GUI) on a mouse-operated desktop PC. The results show that participants get insignificantly lower creativity scores with the elaborated GUI, contrary to the GUI that has no visual artifacts available and offers more similar user experience to pen and paper, even though they spend significantly more time on drawing with the elaborated one. That phenomenon is expected to contribute to the cumulative effect of GUI and input method noticed by previous research. That implies that creative drawing and testing should be carefully introduced into computer-based environments.
Quantitative MR Markers and Psychiatric Symptoms in a Patient with Fahr Disease

Patient: Female, 43 Final Diagnosis: Fahr disease Symptoms: Movement disorder • chorea and tremors • cognitive deficit • behavioral aggressiveness and restlessness • visual hallucination Medication: Haloperidolo • levomepromazine • sodium valproate Clinical Procedure: Neurology examination • neuropsychological examination • MRI Specialty: Neurology Objective: Rare disease Background: Fahr’s disease (FD), or primitive idiopathic calcification of the basal ganglia, is a rare neurodegenerative syndrome characterized by the presence of idiopathic bilateral and symmetrical cerebral calcifications. Case Report: We describe the case of 43-year-old woman presenting with psychiatric symptoms, disorganized behavior, and migraine. Magnetic resonance imaging (MRI) examination showed basal ganglia calcifications. In addition, we analyzed the cortical brain volume and noted cortical atrophy. Extensive etiological clinico-biological assessment allowed us to exclude known causes of brain calcifications and to diagnose Fahr disease (FD). Neurological symptoms associated with psychiatric manifestations are not uncommon in FD. Conclusions: Purely psychiatric presentations are possible, as demonstrated by the present case, although there have been very few cases reported. To date, no studies related to the brain atrophy in FD have been reported.
Leveraging cross-link modification events in CLIP-seq for motif discovery

High-throughput protein–RNA interaction data generated by CLIP-seq has provided an unprecedented depth of access to the activities of RNA-binding proteins (RBPs), the key players in co- and post-transcriptional regulation of gene expression. Motif discovery forms part of the necessary follow-up data analysis for CLIP-seq, both to refine the exact locations of RBP binding sites, and to characterize them. The specific properties of RBP binding sites, and the CLIP-seq methods, provide additional information not usually present in the classic motif discovery problem: the binding site structure, and cross-linking induced events in reads. We show that CLIP-seq data contains clear secondary structure signals, as well as technology- and RBP-specific cross-link signals. We introduce Zagros, a motif discovery algorithm specifically designed to leverage this information and explore its impact on the quality of recovered motifs. Our results indicate that using both secondary structure and cross-link modifications can greatly improve motif discovery on CLIP-seq data. Further, the motifs we recover provide insight into the balance between sequence- and structure-specificity struck by RBP binding.
Documents are programs

Theavailability ofWYSIWYG word-pmcessingsp terns has enabled relatively unskilled individuals to produce documents with very impressive visual effects. The rapid feedback associated with WYSIWYGdito&tashelped peopletolearnquickly the effect of various features and exploxe the many features available. Unfortunately, many have come to believe that this is all that is required to produce large complex documents.
Damped and delayed sinusoidal model for transient signals

In this work, we present the Damped and Delayed Sinusoidal (DDS) model: a generalization of the sinusoidal model. This model takes into account an angular frequency, a damping factor, a phase, an amplitude, and a time-delay parameter for each component. Two algorithms are introduced for the DDS parameter estimation using a subband processing approach. Finally, we derive the Crame/spl acute/r-Rao Bound (CRB) expression for the DDS model and a simulation-based performance analysis in the context of a noisy fast time-varying synthetic signal and in the audio transient signal modeling context.
Towards Using Discrete Multiagent Pathfinding to Address Continuous Problems

Motivated by efﬁcient algorithms for solving combina- torial and discrete instances of the multi-agent pathﬁnding problem, this report investigates ways to utilize such solutions to solve similar problems in the continuous domain. While a simple discretization of the space which allows the direct application of combinatorial algorithms seems like a straightforward solution, there are additional constraints that such a discretization needs to satisfy in order to be able to provide some form of completeness guarantees in general conﬁguration spaces. This report reviews ideas on how to uti- lize combinatorial algorithms to solve continuous multi-agent pathﬁnding problems. It aims to collect feedback from the community regarding the importance and the complexity of this challenge, as well as the appropriate- ness of the solutions considered here.
Low Complexity Decoding of BICM STBC

It was shown earlier that the combination of bit interleaved coded modulation (BICM) with space time block codes (STBC) for OFDM systems leads to the maximum diversity order in space and frequency. In this paper we present low complexity decoding of BICM-STBC systems. First, the maximum likelihood (ML) bit metric calculations are simplified from a distance on the complex plane to a distance on the real line. Furthermore, we present log-likelihood-ratio (LLR) approximations to maximum likelihood (ML) decoding metrics to achieve easier to implement soft decision bit metrics with the same high performance. The LLR bit metrics are specifically calculated for M-ary QAM signal constellations used in IEEE 802.1la/g networks. Simulation results also show that while achieving a substantial improvement in decoder complexity, the proposed bit metrics achieve the same high performance.
HIV-1 Gag Blocks Selenite-Induced Stress Granule Assembly by Altering the mRNA Cap-Binding Complex

ABSTRACT Stress granules (SGs) are dynamic accumulations of stalled preinitiation complexes and translational machinery that assemble under stressful conditions. Sodium selenite (Se) induces the assembly of noncanonical type II SGs that differ in morphology, composition, and mechanism of assembly from canonical SGs. Se inhibits translation initiation by altering the cap-binding activity of eukaryotic translation initiation factor 4E (eIF4E)-binding protein 1 (4EBP1). In this work, we show that human immunodeficiency virus type 1 (HIV-1) Gag is able to block the assembly of type II noncanonical SGs to facilitate continued Gag protein synthesis. We demonstrate that expression of Gag reduces the amount of hypophosphorylated 4EBP1 associated with the 5′ cap potentially through an interaction with its target, eIF4E. These results suggest that the assembly of SGs is an important host antiviral defense that HIV-1 has evolved for inhibition through several distinct mechanisms. IMPORTANCE The antiviral stress response is an important host defense that many viruses, including HIV-1, have evolved to evade. Selenite induces a block in translation and leads to stress granule assembly through the sequestration of eIF4E by binding hypophosphorylated 4EBP1. In this work, we demonstrate that in the face of selenite-induced stress, HIV-1 is able to maintain Gag mRNA translation and to elicit a blockade to selenite-induced stress granule assembly by altering the amount of hypophosphorylated 4EBP1 on the 5′ cap. The antiviral stress response is an important host defense that many viruses, including HIV-1, have evolved to evade. Selenite induces a block in translation and leads to stress granule assembly through the sequestration of eIF4E by binding hypophosphorylated 4EBP1. In this work, we demonstrate that in the face of selenite-induced stress, HIV-1 is able to maintain Gag mRNA translation and to elicit a blockade to selenite-induced stress granule assembly by altering the amount of hypophosphorylated 4EBP1 on the 5′ cap.
Multiple Description of Coded Video for Path Diversity Streaming Adaptation

This paper extends the current concept of multiple description coding (MDC) to the compressed domain, by proposing efficient splitting of standard single description coded (SDC) video into a multi-stream representation. A novel multiple description video splitting (MDVS) scheme is proposed to operate at network edges, for increased robustness in path diversity video streaming across heterogeneous communications chains. It is shown that poor performance of existing methods is mainly due to distortion accumulation, i.e., drift, when decoding is carried out with missing descriptions. The proposed scheme is able to effectively control drift distortion in both intra and inter predictive coding, even when only one description reaches the decoder. This is achieved by generating a controlled amount of relevant side information to compensate for drift accumulation, whenever any description is lost in its path. The simulation results show that any individual description can be decoded on its own without producing drift, achieving significant quality improvement at reduced redundancy cost. The overall performance evaluation, carried out by simulating video streaming over lossy networks with path diversity, also demonstrates that MDVS enables higher quality video in such heterogeneous networking environments, for a wide range of packet loss rates.
Algorithm 342: generator of random numbers satisfying the Poisson distribution

Purpose. This subrout ine finds all the eigenvalues and eigenvectors of a real general matr ix . The eigenvalues are computed by the Qt~ double-step method and the eigenvectors by inverse i tera t ion. Method. Fi rs t ly the following pre l iminary modifications are carr ied out to improve the accuracy of the computed results. (i) The mat r ix is scaled by a sequence of s imi lar i ty t rans format ions so t h a t the absolute sums of corresponding rows and columns are roughly equal. (ii) The scaled mat r ix is normalized so t h a t the value of the Eucl idean norm is equal to one. The ma in pa r t of the process commences wi th the reduct ion of the mat r ix to an upper-Hessenberg form by means of s imilar i ty t rans format ions (Householder 's method) . Then the QR doubles tep i t e ra t ive process is performed on the Hessenberg ma t r ix unt i l all e lements of the subdiagonal t h a t converge to zero are in modulus less t h a n 2 -t H HIIE , where t is the number of significant digits in the man t i s sa of a b ina ry f loat ing-point number . The eigenvalues are t hen ext rac ted f rom this reduced form. Inverse i t e ra t ion is performed on the upper-Hessenberg ma t r ix unt i l the absolute value of the largest component of the r igh t hand side vector is greater t han the bound 2t/(100 N), where N is the order of the matr ix . Normal ly af ter this bound is achieved, one step more is performed to ob ta in the computed eigenvector , bu t a t each s tep the residuals are computed, and if the residuals of one par t icular s tep are greater in absolute value t han the residuals of the previous step, then the vector of the previous s tep is accepted as the computed eigenvector. Program. The subrout ine E I G E N P is completely self-conta ined (composed of five subrout ines E I G E N P , SCALE, HESQR, REALVE, and COMPVE) and communica t ion to i t is solely th rough the a rgument list. The en t rance to the subrout ine is achieved by CALL E I G E N P (N, NM, A, T, EVR, EVI, VECR, VECI, I N D I C ) The meaning of the pa ramete r s is described in the comments at the beginning of the subrout ine E I G E N P .
Smoking Status and the Five-Factor Model of Personality: Results of a Cross-Sectional Study Conducted in Poland

Tobacco smoking is the single most important modifiable factor in increased morbidity and premature mortality. Numerous factors—including genetics, personality, and environment—affect the development and persistence of tobacco addiction, and knowledge regarding these factors could improve smoking cessation rates. This study compared personality traits between never, former, and current smokers, using the Five-Factor Model of Personality in a country with a turbulent smoking reduction process. : In this cross-sectional study, 909 Polish adults completed the Revised Neuroticism-Extraversion-Openness Personality Inventory. Our results showed that current smokers’ scores for extraversion, one of the five global dimensions of personality, were higher relative to never smokers. Neuroticism, openness to experience, agreeableness, and conscientiousness did not differ significantly according to smoking status. Facet analysis, which described each dimension in detail, showed that current smokers’ activity and excitement seeking (facets of extraversion) scores were higher relative to those of never and former smokers. In turn, current smokers’ dutifulness and deliberation (facets of conscientiousness) scores were lower than those found in former and never smokers. Never smokers scored the highest in self-consciousness (a facet of neuroticism) and compliance (a component of agreeableness). The study conducted among Polish individuals showed variation in personality traits according to their smoking status; however, this variation differed from that reported in countries in which efforts to reduce smoking had begun earlier relative to Poland. Knowledge regarding personality traits could be useful in designing smoking prevention and cessation programs tailored to individuals’ needs.
Query Heartbeat: A Strange Property of Keyword Queries on the Web

This paper illustrates a strange property that was encountered when analysing keyword query data. The objective of this work was to observe the temporal properties of keyword queries. However, we found that generic keyword queries that have large enough volumes tend to follow the same “attractor” distribution. This phenomenon was discovered in a 3-month dataset. However, a visually similar phenomenon was also apparent when the keywords were searched on Google.
Discriminative Feature Grouping

Feature grouping has been demonstrated to be promising in learning with high-dimensional data. It helps reduce the variances in the estimation and improves the stability of feature selection. One major limitation of existing feature grouping approaches is that some similar but different feature groups are often mis-fused, leading to impaired performance. In this paper, we propose a Discriminative Feature Grouping (DFG) method to discover the feature groups with enhanced discrimination. Different from existing methods, DFG adopts a novel regularizer for the feature coefficients to trade-off between fusing and discriminating feature groups. The proposed regularizer consists of a ell_1 norm to enforce feature sparsity and a pairwise ell_infty norm to encourage the absolute differences among any three feature coefficients to be similar. To achieve better asymptotic property, we generalize the proposed regularizer to an adaptive one where the feature coefficients are weighted based on the solution of some estimator with root-n consistency. For optimization, we employ the alternating direction method of multipliers to solve the proposed methods efficiently. Experimental results on synthetic and real-world datasets demonstrate that the proposed methods have good performance compared with the state-of-the-art feature grouping methods.
A comparative study of two network-based anomaly detection methods

Modern networks are complex and hence, network operators often rely on automation to assist in assuring the security, availability, and performance of these networks. At the core of many of these systems are general-purpose anomaly-detection algorithms that seek to identify normal behavior and detect deviations. While the number and variations of these algorithms are large, two broad categories have emerged as leading approaches to this problem: those based on spatial correlation and those based on temporal analysis. In this paper, we compare one promising approach from each of these categories, namely entropy-based PCA and HHH-based wavelets.
Healthcare provider intervention on smoking and quit attempts among HIV-positive versus HIV-negative MSM smokers in Chengdu, China

Given the implications for smoking among HIV-positive individuals and high smoking and HIV rates among men who have sex with men (MSM) in China, we examined sociodemographic, smoking-related, psychosocial, and substance use factors in relation to HIV status; receiving some sort of healthcare provider intervention regarding smoking; and having made a quit attempt in the past year in a sample of MSM smokers in Chengdu. We conducted a cross-sectional survey of 381 MSM smokers recruited by a nongovernmental organization in Chengdu in 2012–2013. Of these, 350 disclosed their HIV status and 344 (188 HIV-positive and 156 HIV-negative) provided completed data. Half (50.0%) reported at least one quit attempt in their lifetime; 30.5% reported a quit attempt in the past year. The majority (59.4%) reported that a healthcare provider had intervened in some way (assessed smoking, advised quitting, provided assistance), most commonly by assessing smoking status (50.0%). HIV-positive individuals were more likely to report a healthcare provider intervening on their smoking (p < .001). Those who received provider intervention were more likely to have attempted to quit ever (p = .009) and in the past year (p < .001). Those HIV-positive were more likely to have attempted to quit since diagnosis if a provider had intervened (p = .001). Multivariate regression documented that being HIV-positive (p < .001), greater cigarette consumption (p = .02), less frequent drinking (p = .03), and greater depressive symptoms (p = .003) were significant correlates of healthcare provider intervention. Multivariate regression also found that healthcare provider intervention (p = .003), older age (p = .01), and higher autonomous motivation (p = .007) were significant correlates of attempting to quit in the past year. Given the impact of healthcare provider intervention regarding smoking on quit attempts among MSM, greater training and support is needed to promote consistent intervention on smoking in the clinical setting among HIV-positive and HIV-negative MSM smokers.
Awarding Points, Using Levels to Help Children Improve Behavior

3 How can teachers encourage students with learning disabilities or emotional disturbance to stay on task? To speak nicely? To follow directions? To com­ plete assignments? To achieve personal educational goals? Not necessarily to become the Perfect Student, but to improve their behavior, effort, and achievement enough to benefit from increased amounts of time spent in gen­ eral education classrooms, away from their self-contained special education classrooms. The Individuals with Disabilities Education Act (IDEA) encourages the
Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes

The inaugural workshop “Deep Sequencing in Infectious Diseases: Immune and Pathogen Repertoires for the Improvement of Patient Outcomes” was held in Singapore on 13–14 October 2016. The aim of the workshop was to discuss the latest trends in using high-throughput sequencing, bioinformatics, and allied technologies to analyze immune and pathogen repertoires and their interplay within the host, bringing together key international players in the field and Singapore-based researchers and clinician-scientists. The focus was in particular on the application of these technologies for the improvement of patient diagnosis, prognosis and treatment, and for other broad public health outcomes. The presentations by scientists and clinicians showed the potential of deep sequencing technology to capture the coevolution of adaptive immunity and pathogens. For clinical applications, some key challenges remain, such as the long turnaround time and relatively high cost of deep sequencing for pathogen identification and characterization and the lack of international standardization in immune repertoire analysis.