Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simple, Assumption-Free, and Clinically Interpretable Approach for Analysis of Modified Rankin Outcomes

Background and Purpose— There is debate regarding the approach for analysis of modified Rankin scale scores, the most common functional outcome scale used in acute stroke trials. Methods— We propose to use tests to assess treatment differences addressing the metric, “if a patient is chosen at random from each treatment group and if they have different outcomes, what is the chance the patient who received the investigational treatment will have a better outcome than will the patient receiving the standard treatment? ” This approach has an associated statement of treatment efficacy easily understood by patients and clinicians, and leads to statistical testing of treatment differences by tests closely related to the Mann-Whitney U test (Wilcoxon Rank-Sum test), which can be tested precisely by permutation tests (randomization tests). Results— We show that a permutation test is as powerful as are other approaches assessing ordinal outcomes of the modified Rankin scores, and we provide data from several examples contrasting alternative approaches. Discussion— Whereas many approaches to analysis of modified Rankin scores outcomes have generally similar statistical performance, this proposed approach: captures information from the ordinal scale, provides a powerful clinical interpretation understood by both patients and clinicians, has power at least equivalent to other ordinal approaches, avoids assumptions in the parameterization, and provides an interpretable parameter based on the same foundation as the calculation of the probability value.
Managing Fuel Efficiency in the Aviation Sector: Challenges, Accomplishments and Opportunities

Abstract Aviation is one of the fastest mode of transportation in the world, and demand for air transportation is growing continuously. The past oil crises, volatile fuel prices, depleting fuel stocks, and increasing environmental concerns have drawn the significant attention of aviation industry towards the need for judicious use of aviation fuel. Thus, economic and environmental sustainability concerns have led to dramatic progress in aviation fuel efficiency improvements in the past decades. However, significant efforts to improve the fuel efficiency through more advanced designs, techniques, and strategies will remain a priority. This article provides an overview of the challenging issues, accomplishments, and opportunities in relation to the aviation industry, focusing on aviation fuel consumption. This article offers insights for the aviation industry, that is, aircraft manufacturers and airlines to move toward more fuel-efficient options in future.
Pose tracking by efficiently exploiting global features

Typical pose tracking algorithms first obtain a set of plausible pose hypotheses in all image frames of a video and subsequently stitch compatible detections across time to form a pose-track. This approach to tracking is commonly termed tracking-by-detections, and has been very successful in other areas such as multiple object tracking, video segmentation using object proposals. Often models in this category can only incorporate local spatio-temporal evidence due to exponentially increased cost when using global information. Local spatio-temporal evidence can be ambiguous, thus leading to an inferior objective modeling. To deal with ambiguities in local information it is necessary to incorporate global information over multiple frames into a model. Based on the recent advances in generating multiple solutions from a probabilistic model, we first generate multiple plausible pose-track hypotheses, and subsequently employ a mixture of local and global features to express the quality of these solutions with high fidelity. We perform extensive experiments and competitive results across varied datasets demonstrate the robustness of our approach.
Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals

The brain is a complex structure made up of interconnected neurons, and its electrical activities can be evaluated using electroencephalogram (EEG) signals. The characteristics of the brain area affected by partial epilepsy can be studied using focal and non-focal EEG signals. In this work, a method for the classification of focal and non-focal EEG signals is presented using entropy measures. These entropy measures can be useful in assessing the nonlinear interrelation and complexity of focal and non-focal EEG signals. These EEG signals are first decomposed using the empirical mode decomposition (EMD) method to extract intrinsic mode functions (IMFs). The entropy features, namely, average Shannon entropy (ShEnAvg), average Renyi’s entropy (RenEnAvg ), average approximate entropy (ApEnAvg), average sample entropy (SpEnAvg) and average phase entropies (S1Avg and S2Avg), are computed from different IMFs of focal and non-focal EEG signals. These entropies are used as the input feature set for the least squares support vector machine (LS-SVM) classifier to classify into focal and non-focal EEG signals. Experimental results show that our proposed method is able to differentiate the focal and non-focal EEG signals with an average classification accuracy of 87% correct.
Imperative functional programming

Our intuitive idea of a function is that it describes the dependence of one quantity upon another. There is no condition on what kind of quantities are involved. They could be integers, Turing machines, binary search trees, window hierarchies, digital circuits or whatever. The possibilities are endless. The idea of functional programming is that functions are described applicatively, by plugging together other functions. This recursive dependence of functions on other functions bottoms out with the primitive operators. If the primitive operators are “effective,” i.e., they can be used to calculate, compute, construct or build one quantity from another, then all functions expressed applicatively are similarly effective. Imperative functional programming is the application of these ideas to imperative computations. Quantities here are imperative computations and functions denote dependences between imperative computations. Effectiveness of a function means that a computation produced from it can be effectively carried out whenever the input computations can be effectively carried out. It is often felt that imperative computations and functional programming are in conflict. Adding imperative computations to a functional programming language is found to destroy its “referential transparency. ” See, for example, [Abelson et al., 1985, Sec. 3.1] for a discussion of the issue. However, in languages where such issues arise, imperative computations are thrown together by extending or modifying functional computation. The idea that functions denote dependences is lost in the process. In contrast, imperative functional programming does not involve altering functional computation in any way. It merely applies it to a new context, that of imperative compu-
Identification of teosinte, maize, and Tripsacum in Mesoamerica by using pollen, starch grains, and phytoliths

We examined pollen grains and starch granules from a large number of modern populations of teosinte (wild Zea spp.), maize (Zea mays L.), and closely related grasses in the genus Tripsacum to assess their strengths and weaknesses in studying the origins and early dispersals of maize in its Mesoamerican cradle of origin. We report new diagnostic criteria and question the accuracy of others used previously by investigators to identify ancient maize where its wild ancestor, teosinte, is native. Pollen grains from teosinte overlap in size with those of maize to a much greater degree than previously reported, making the differentiation of wild and domesticated maize in palynological studies difficult. There is presently no valid method for separating maize and teosinte pollen on a morphological basis. Starch grain analysis, a recently developed tool of archaeobotany, appears to be of significant utility in distinguishing the seeds of teosinte from maize. We propose that the differences in starch grain morphology and size between wild and domesticated maize defined in this study may be associated with domestication genes in Zea that have been documented in the starch biosynthesis pathway. As previously reported, phytoliths effectively discriminate the female reproductive structures of Tripsacum, teosinte, and maize. Multiproxy microfossil studies of archaeological and paleoecological contexts appear to be effective tools for investigating the earliest stages of maize domestication and dispersals.
Pathogenic Acinetobacter: from the Cell Surface to Infinity and Beyond

ABSTRACT The genus Acinetobacter encompasses multiple nosocomial opportunistic pathogens that are of increasing worldwide relevance because of their ability to survive exposure to various antimicrobial and sterilization agents. Among these, Acinetobacter baumannii, Acinetobacter nosocomialis, and Acinetobacter pittii are the most frequently isolated in hospitals around the world. Despite the growing incidence of multidrug-resistant Acinetobacter spp. , little is known about the factors that contribute to pathogenesis. New strategies for treating and managing infections caused by multidrug-resistant Acinetobacter strains are urgently needed, and this requires a detailed understanding of the pathobiology of these organisms. In recent years, some virulence factors important for Acinetobacter colonization have started to emerge. In this review, we focus on several recently described virulence factors that act at the bacterial surface level, such as the capsule, O-linked protein glycosylation, and adhesins. Furthermore, we describe the current knowledge regarding the type II and type VI secretion systems present in these strains.
Growth of Dust as the Initial Step Toward Planet Formation

We discuss the results of laboratory measurements and theoretical models concerning the aggregation of dust in protoplanetary disks as the initial step toward planet formation. Small particles easily stick when they collide and form aggregates with an open, often fractal structure, depending on the growth process. Larger particles are still expected to grow at collision velocities of about 1 m/s. Experiments also show that, after an intermezzo of destructive velocities, high collision velocities above 10 m/s on porous materials again lead to net growth of the target. Considerations of dust-gas interactions show that collision velocities for particles not too different in surface-to-mass ratio remain limited up to sizes of about 1 m, and growth seems to be guaranteed to reach these sizes quickly and easily. For meter sizes, coupling to nebula turbulence makes destructive processes more likely. Global aggregation models show that in a turbulent nebula, small particles are swept up too fast to be consistent with observations of disks. An extended phase may therefore exist in the nebula during which the small particle component is kept alive through collisions driven by turbulence, which frustrates growth to planetesimals until conditions are more favorable for one or more reasons.
Advances in Cardiovascular Imaging Nonechocardiographic Imaging in Evaluation for Cardiac Resynchronization Therapy

In patients with heart failure and prolonged QRS duration, randomized clinical trials have shown that cardiac resynchronization therapy (CRT) is associated with improvement in quality of life, left ventricular (LV) remodeling, and survival. 1–3 The improvements are believed to be mediated by more effective synchronized contraction in the presence of a wide QRS, but mechanical and electrical dyssynchrony are not equivalent. 4,5 Although the concept of CRT response remains problematic, 6 20% to 40% of patients who receive CRT based on electrical dyssynchrony criteria (ie, QRS duration) do not derive symptom improvement or demonstrate reverse remodeling. 7–10 Scar burden 11–13 and failure to place the LV pacing lead at the site of latest onset of contraction 14–17 have been linked to a poor response. Thus, optimal clinical decision-making for CRT must include a comprehensive evaluation of all these factors to identify patients with heart failure who will benefit. The standard echocardiographic parameters of LV mechanical dyssynchrony have been extensively reviewed, 18 with 600 published articles. Most of this work has been done using tissue Doppler imaging, with more recent work using speckle tracking, 19,20 3D echocardiography, 21 echocardiographic contrast imaging, 22 and intracardiac echocardiography. 23 Despite the important benefits of high temporal resolution, success in individual centers, and ability to assess the impact of scar burden and concordance of LV lead with latest activation site, 14 fundamental limitations of tissue Doppler imaging include the inability to measure over a sufficient number of cardiac cycles to overcome beat-to-beat variation, poor image quality, and measurement error. 24 In the only randomized trial of CRT in patients with wide QRS, 25 the failure of 12 different echocardiographic dyssynchrony parameters to improve outcome was most likely related to the large interobserver and intraobserver variability (4% to 24% and 7% to 72%, respectively). These limitations of echocardiography have led to a search for nonechocardiographic imaging techniques to optimize decision-making before CRT (Table 1).
Sparsity-promoting method to estimate the dispersion curve of surface-wave group velocity

Group velocity is an important characteristic of surface wave that is defined as the velocity of an envelope of frequencies. Although many studies have shown the promises of analyzing the group velocity to obtain subsurface S-wave velocity, the estimation of the group velocity is not straightforward due to the uncertainties of selecting an optimum envelope of frequencies. Conventional transformations or filtering algorithms used to define an optimum envelope usually give reasonable results just for a narrow frequency or velocity range. We introduced a new approach for the estimation of the group velocity using the sparse S transform (SST) and sparse linear Radon transform (SLRT). In SST, the width of the Gaussian window is optimally calculated by energy concentration to eliminate energy smearing in the time-frequency (TF) domain, and then the sparsity is applied to enhance the TF resolution. Compared with conventional methods for the estimation of the group velocity based on the generalized S transforms, SST does not require any adjustment to the Gaussian window and yields accurate estimates of the group velocity. We apply SST to each seismic trace of a seismic shot record to obtain a 3D cube of frequency, time, and offset. For any frequency, we obtain a common frequency gather of time and offset to which we apply SLRT to obtain the group velocity of the surface wave. Our approach is robust at calculating high-resolution distinguishable dispersion curves of the group velocity in particular when data are extremely sparse.
A LOADING-DEPENDENT MODEL OF PROBABILISTIC CASCADING FAILURE

We propose an analytically tractable model of loading-dependent cascading failure that captures some of the salient features of large blackouts of electric power transmission systems. This leads to a new application and derivation of the quasibinomial distribution and its generalization to a saturating form with an extended parameter range. The saturating quasibinomial distribution of the number of failed components has a power-law region at a critical loading and a significant probability of total failure at higher loadings.
Novel copy number variation of the TGFβ3 gene is associated with TGFβ3 gene expression and duration of fertility traits in hens

Improvements in the duration of fertility (DF) could increase the interval between successive artificial inseminations, thereby decreasing the cost associated with production of hatching eggs. The molecular mechanisms involved in DF in hens remains under-explored. In this study, expression levels of the transforming growth factor-β genes (TGFβs: TGFβ1, TGFβ2, TGFβ3) were investigated in utero-vaginal junctions (UVJs) of hens with long DF (Group L, n = 10) and short DF (Group S, n = 10). TGFβ1 and 2 tended to exhibit higher expression levels in UVJs from Group L hens. The expression levels of TGFβ3 mRNA and protein were significantly increased in UVJs of hens from Group L compared to hens in Group S. Consistently, six TGFβs downstream genes (DAXX, MEKK1, T-BET, GATA-3, TAK1, and FOXP3) associated with the immune response were found to be significantly differentially expressed in UVJs of Group L than Group S hens. In addition, four SNPs were identified in intron 1 of TGFβ3, and these SNPs were significantly associated with DF traits (P < 0.05). Furthermore, we identified multi-copy and copy number variants (CNVs) in chicken TGFβ3 and later determined significant associations between TGFβ3 CNVs and DF traits in hens. Specifically, TGFβ3 copy number exhibited a significant positive correlation with its expression (P < 0.05). Collectively, our results suggest that chicken DF traits may be regulated by the expression of TGFβ3 in UVJ. Meanwhile, the copy number variation in the TGFβ3 gene identified in this study seems to be one marker for DF traits.
Turning Information into Actions: From Data to Business Processes Through Web Services

Keywords: Business Model - IS - Factual Dependency - Web Services - Business Process - B2B Integration. Abstract: Sharing Web services across the enterprise and to support B2B integration becomes more intensive and critical for businesses. This paper proposes a process to generate Web services from the attributes describing the business objects and the coordination artefacts as described in the highest abstraction level of a business model i.e. the universe of discourse where the elements are unique. The process is based on a new concept we introduce and call factual dependency. Factual dependency is a mechanism used to aggregate attributes that are concerned by the same DB CRUD operations with respect to the time and the space. Factual dependencies are then validated with regard to the possible business events to keep only the relevant ones. Each distinct and valid factual dependency is specified in terms of input/output parameters to generate a lowest level of granularity Web services. These Web services are then registered to be discovered and (re)used at request by business processes in their reengineering or composition.
Attenuation of 3,4-methylenedioxymethamphetamine (MDMA, Ecstasy)-induced rhabdomyolysis with alpha1- plus beta3-adrenoreceptor antagonists.

1. Studies were designed to examine the effects of alpha(1) (alpha(1)AR)- plus beta(3)-adrenoreceptor (beta(3)AR) antagonists on 3,4-methylenedioxymethamphetamine (MDMA, Ecstasy)-induced hyperthermia and measures of rhabdomyolysis (creatine kinase (CK)) and renal function (blood urea nitrogen (BUN) and serum creatinine (sCr)) in male Sprague-Dawley rats. 2. MDMA (40 mg x kg(-1), s.c. ) induced a rapid and robust increase in rectal temperature, which was significantly attenuated by pretreatment with the alpha(1)AR antagonist prazosin (100 microg x kg(-1), i.p.) plus the beta(3)AR antagonist SR59230A (5 mg x kg(-1), i.p.). 3. CK levels significantly increased (peaking at 4 h) after MDMA treatment and were blocked by the combination of prazosin plus SR59230A. 4. At 4 h after MDMA treatment, BUN and sCr levels were also significantly increased and could be prevented by this combination of alpha(1)AR- plus beta(3)AR-antagonists. 5. The results from this study suggest that alpha(1)AR and beta(3)AR play a critical role in the etiology of MDMA-mediated hyperthermia and subsequent rhabdomyolysis.
Socioeconomic Impacts on Survival Differ by Race/Ethnicity among Adolescents and Young Adults with Non-Hodgkin's Lymphoma

Shorter survival has been associated with low socioeconomic status (SES) among elderly non-Hodgkin's lymphoma (NHL) patients; however it remains unknown whether the same relationship holds for younger patients. We explored the California Cancer Registry (CCR), to investigate this relationship in adolescent and young adult (AYA) NHL patients diagnosed from 1996 to 2005. A case-only survival analysis was conducted to examine demographic and clinical variables hypothesized to be related to survival. Included in the final analysis were 3,489 incident NHL cases. In the multivariate analyses, all-cause mortality (ACM) was higher in individuals who had later stage at diagnosis (P < .05) or did not receive first-course chemotherapy (P < .05). There was also a significant gradient decrease in survival, with higher ACM at each decreasing quintile of SES (P < .001). Overall results were similar for lymphoma-specific mortality. In the race/ethnicity stratified analyses, only non-Hispanic Whites (NHWs) had a significant SES-ACM trend (P < .001). Reduced overall and lymphoma-specific survival was associated with lower SES in AYAs with NHL, although a significant trend was only observed for NHWs.
Surrogate Bicycle Design for Millimeter-Wave Automotive Radar Pre-Collision Testing

This paper discusses the development of a surrogate bicycle target for evaluating the effectiveness of vehicular autonomous emergency braking (AEB)/ pre-collision systems (PCSs) that uses 77-GHz radar systems in detecting bicyclists on the road. The design objective of the surrogate bicycle is to produce similar optical appearance and radar response in a 76–78 GHz band as a real bicycle selected based on its popularity (in 2014) in the United States. In addition, the surrogate bicyclist needs to be able to withstand the impact of the test vehicle traveling at 30 mph (or 48 kph) should it fail to detect the surrogate target. Our design approach differs from the only other surrogate bicyclist developed by a European research group in that our surrogate bicyclist produces similar radar response as a real bicyclist over the entire 360° of azimuth angles. Our design approach began with experimental characterizing the radar cross section (RCS) patterns of real bikes of different types as well as identifying RCS contributions of different parts on a bike via accurate simulations, which were also used for design optimizations. The RCS performance of the fabricated surrogate bicycle was verified via 360° azimuth pattern measurement comparison with a real bicycle. Its physical performance was tested via actual field testing on a test track with two commercial vehicles equipped with AEB and PCS systems.
A compact UWB antenna with sharp band-notched characteristics and controllable notched bandwidth

A compact Ultra-Wide Band (UWB) antenna with sharp band-notched characteristic and controllable notched bandwidth is presented. The band-rejected structure is realized by inserting two half wavelength C-shaped slots with the same resonant frequency in the radiator. The two C-shaped slots couple together to form a sharp band rejection. A good impedance matching is obtained in 3.1–10.6 GHz frequency range(|S11|&#60;−10 dB), except the lower WLAN band of 5.15–5.35 GHz (|S11| >−5 dB). Moreover, the band-notched bandwidth can be controlled by adjusting the dimensions of the two C-shaped slots.