nils-herrmann/clean_scirepeval huggingface dataset:
Effect of creatine supplementation on jumping performance in elite volleyball players.

Jump height is a critical aspect of volleyball players' blocking and attacking performance. Although previous studies demonstrated that creatine monohydrate supplementation (CrMS) improves jumping performance, none have yet evaluated its effect among volleyball players with proficient jumping skills. We examined the effect of 4 wk of CrMS on 1 RM spike jump (SJ) and repeated block jump (BJ) performance among 12 elite males of the Sherbrooke University volleyball team. Using a parallel, randomized, double-blind protocol, participants were supplemented with a placebo or creatine solution for 28 d, at a dose of 20 g/d in days 1-4, 10 g/d on days 5-6, and 5 g/d on days 7-28. Pre- and postsupplementation, subjects performed the 1 RM SJ test, followed by the repeated BJ test (10 series of 10 BJs; 3 s interval between jumps; 2 min recovery between series). Due to injuries (N = 2) and outlier data (N = 2), results are reported for eight subjects. Following supplementation, both groups improved SJ and repeated BJ performance. The change in performance during the 1 RM SJ test and over the first two repeated BJ series was unclear between groups. For series 3-6 and 7-10, respectively, CrMS further improved repeated BJ performance by 2.8% (likely beneficial change) and 1.9% (possibly beneficial change), compared with the placebo. Percent repeated BJ decline in performance across the 10 series did not differ between groups pre- and postsupplementation. In conclusion, CrMS likely improved repeated BJ height capability without influencing the magnitude of muscular fatigue in these elite, university-level volleyball players.
A 46 µW 13 b 6.4 MS/s SAR ADC With Background Mismatch and Offset Calibration

A 6.4MS/s 13b ADC with a low-power background calibration for DAC mismatch and comparator offset errors is presented. Redundancy deals with DAC settling and facilitates calibration. A two-mode comparator and 0.3fF capacitors reduce power and area. The background calibration can directly detect the sign of the dynamic comparator offset error and the DAC mismatch errors and correct both of them simultaneously in a stepwise feedback loop. The calibration achieves 20dB spur reduction with little area and power overhead. The chip is implemented in 40nm CMOS and consumes 46μW from a 1V supply, and achieves 64.1dB SNDR and a FoM of 5.5 fJ/conversion-step at Nyquist.
Passive leg raising

To assess whether the passive leg raising test can help in predicting fluid responsiveness. Nonsystematic review of the literature. Passive leg raising has been used as an endogenous fluid challenge and tested for predicting the hemodynamic response to fluid in patients with acute circulatory failure. This is now easy to perform at the bedside using methods that allow a real time measurement of systolic blood flow. A passive leg raising induced increase in descending aortic blood flow of at least 10% or in echocardiographic subaortic flow of at least 12% has been shown to predict fluid responsiveness. Importantly, this prediction remains very valuable in patients with cardiac arrhythmias or spontaneous breathing activity. Passive leg raising allows reliable prediction of fluid responsiveness even in patients with spontaneous breathing activity or arrhythmias. This test may come to be used increasingly at the bedside since it is easy to perform and effective, provided that its effects are assessed by a real-time measurement of cardiac output.
Ventricular assist devices today and tomorrow.

f ( HE NUMBER OF people worldwide with heart failure (HF) is increasing at an alarming pace. In the United States lone, there are approximately 5.3 million people who have HF, ith a prevalence estimated at 10 per 1,000 in people over the age f 65.1 It is now estimated that there are 660,000 new cases of HF iagnosed every year for people over 45 years of age. In 2008, here were more than 1 million hospital admissions for HF at a ost of $34.8 billion. Currently, preventative measures, optimal edical therapy, and heart transplantation are not effectively reucing the overall morbidity and mortality of this syndrome. The American College of Cardiology/American Heart Assocition (ACC/AHA) have classified HF in 4 stages based on the rogression of the disease (Table 1).2,3 Early in the course of the isease (stages A and B), symptoms are absent or mild, but the atients are at high risk of developing symptomatic or refractory isease. As the disease progresses through stage C, ventricular unction is maintained by adrenergic stimulation, activation of enin-angiotensin-aldosterone, and other neurohumoral and cytoine systems.4,5 These compensatory mechanisms become less ffective over time, and cardiac function deteriorates to the point here patients have marked symptoms at rest (stage D). The CC/AHA-recommended therapeutic options for patients with tage D symptoms are continuous inotropic support, heart translantation, mechanical circulatory support, or hospice care. Standard HF medical therapies such as angiotensin-convertng enzyme inhibitors, -blockers, diuretics, inotropic agents, nd antiarrhythmics may relieve symptoms, but the mortality ate remains unaffected. Optimal medical therapy does not halt he progression toward stage D HF symptoms, and when this ccurs, there is a greater than 75% 2-year mortality risk, with urgical intervention being the only effective treatment. Cariac transplantation is an effective therapy for terminal HF and s associated with excellent 1-year survival (93%), 5-year surival (88%), and functional capacity.6 However, there are aproximately 2,200 donors available for as many as 100,000 atients with advanced-stage HF.7 Moreover, donor hearts are
Effects of Lactobacillus johnsonii and Lactobacillus reuteri on gut barrier function and heat shock proteins in intestinal porcine epithelial cells

Heat shock proteins (HSPs) are a set of highly conserved proteins that can serve as intestinal gate keepers in gut homeostasis. Here, effects of a probiotic, Lactobacillus rhamnosus GG (LGG), and two novel porcine isolates, Lactobacillus johnsonii strain P47-HY and Lactobacillus reuteri strain P43-HUV, on cytoprotective HSP expression and gut barrier function, were investigated in a porcine IPEC-J2 intestinal epithelial cell line model. The IPEC-J2 cells polarized on a permeable filter exhibited villus-like cell phenotype with development of apical microvilli. Western blot analysis detected HSP expression in IPEC-J2 and revealed that L. johnsonii and L. reuteri strains were able to significantly induce HSP27, despite high basal expression in IPEC-J2, whereas LGG did not. For HSP72, only the supernatant of L. reuteri induced the expression, which was comparable to the heat shock treatment, which indicated that HSP72 expression was more stimulus specific. The protective effect of lactobacilli was further studied in IPEC-J2 under an enterotoxigenic Escherichia coli (ETEC) challenge. ETEC caused intestinal barrier destruction, as reflected by loss of cell-cell contact, reduced IPEC-J2 cell viability and transepithelial electrical resistance, and disruption of tight junction protein zonula occludens-1. In contrast, the L. reuteri treatment substantially counteracted these detrimental effects and preserved the barrier function. L. johnsonii and LGG also achieved barrier protection, partly by directly inhibiting ETEC attachment. Together, the results indicate that specific strains of Lactobacillus can enhance gut barrier function through cytoprotective HSP induction and fortify the cell protection against ETEC challenge through tight junction protein modulation and direct interaction with pathogens.
Visually Grounded and Textual Semantic Models Differentially Decode Brain Activity Associated with Concrete and Abstract Nouns

Important advances have recently been made using computational semantic models to decode brain activity patterns associated with concepts; however, this work has almost exclusively focused on concrete nouns. How well these models extend to decoding abstract nouns is largely unknown. We address this question by applying state-of-the-art computational models to decode functional Magnetic Resonance Imaging (fMRI) activity patterns, elicited by participants reading and imagining a diverse set of both concrete and abstract nouns. One of the models we use is linguistic, exploiting the recent word2vec skipgram approach trained on Wikipedia. The second is visually grounded, using deep convolutional neural networks trained on Google Images. Dual coding theory considers concrete concepts to be encoded in the brain both linguistically and visually, and abstract concepts only linguistically. Splitting the fMRI data according to human concreteness ratings, we indeed observe that both models significantly decode the most concrete nouns; however, accuracy is significantly greater using the text-based models for the most abstract nouns. More generally this confirms that current computational models are sufficiently advanced to assist in investigating the representational structure of abstract concepts in the brain.
Improved Pre-Ejection Period Estimation From Ballistocardiogram and Electrocardiogram Signals by Fusing Multiple Timing Interval Features

Sympathetic nervous system (SNS) activity plays a significant role in cardiovascular control. Preejection period (PEP) is a noninvasive biomarker that reflects SNS activity. In this paper, unobtrusive estimation of PEP of the heart using ballistocardiogram (BCG) and electrocardiogram (ECG) signals is investigated. Although previous work has shown that the time intervals from ECG R-peak to BCG I and J peaks are correlated with PEP, relying on a single BCG beat can be prone to errors. An approach is proposed based on multiple regression and use of initial training data sets with a reference standard, impedance cardiography (ICG). For evaluation, healthy subjects were asked to stand on a force plate to record BCG and ECG signals. Regression coefficients were obtained using leave-one-out cross-validation and the true PEP values were obtained using ECG and ICG. Regression coefficients were averaged over two different recordings from the same subjects. The estimation performance was evaluated based on the data, via leave-one-out cross-validation. Multiple regression is shown to reduce the mean absolute error and the root mean square error, and has a reduced confidence interval compared with the models based on only a single feature. This paper shows that the fusion of multiple timing intervals can be useful for improved PEP estimation.
L-tartaric acid synthesis from vitamin C in higher plants.

The biosynthetic pathway of L-tartaric acid, the form most commonly encountered in nature, and its catabolic ties to vitamin C, remain a challenge to plant scientists. Vitamin C and L-tartaric acid are plant-derived metabolites with intrinsic human value. In contrast to most fruits during development, grapes accumulate L-tartaric acid, which remains within the berry throughout ripening. Berry taste and the organoleptic properties and aging potential of wines are intimately linked to levels of L-tartaric acid present in the fruit, and those added during vinification. Elucidation of the reactions relating L-tartaric acid to vitamin C catabolism in the Vitaceae showed that they proceed via the oxidation of L-idonic acid, the proposed rate-limiting step in the pathway. Here we report the use of transcript and metabolite profiling to identify candidate cDNAs from genes expressed at developmental times and in tissues appropriate for L-tartaric acid biosynthesis in grape berries. Enzymological analyses of one candidate confirmed its activity in the proposed rate-limiting step of the direct pathway from vitamin C to tartaric acid in higher plants. Surveying organic acid content in Vitis and related genera, we have identified a non-tartrate-forming species in which this gene is deleted. This species accumulates in excess of three times the levels of vitamin C than comparably ripe berries of tartrate-accumulating species, suggesting that modulation of tartaric acid biosynthesis may provide a rational basis for the production of grapes rich in vitamin C.
Is coding a relevant metaphor for the brain

“Neural coding” is a popular metaphor in neuroscience, where objective properties of the world are communicated to the brain in the form of spikes. Here I argue that this metaphor is often inappropriate and misleading. First, when neurons are said to encode experimental parameters, the implied communication channel consists of both the experimental and biological system. Thus, the terms “neural code” are used inappropriately when “neuroexperimental code” would be more accurate, although less insightful. Second, the brain cannot be presumed to decode neural messages into objective properties of the world, since it never gets to observe those properties. To avoid dualism, codes must relate not to external properties but to internal sensorimotor models. Because this requires structured representations, neural assemblies cannot be the basis of such codes. Third, a message is informative to the extent that the reader understands its language. But the neural code is private to the encoder since only the message is communicated: each neuron speaks its own language. It follows that in the neural coding metaphor, the brain is a Tower of Babel. Finally, the relation between input signals and actions is circular; that inputs do not preexist to outputs makes the coding paradigm problematic. I conclude that the view that spikes are messages is generally not tenable. An alternative proposition is that action potentials are actions on other neurons and the environment, and neurons interact with each other rather than exchange messages. . CC-BY 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this  (which was . http://dx.doi.org/10.1101/168237  first posted online Jul. 27, 2017;
Neural Versus Symbolic Rap Battle Bots

We contrast two opposing approaches to building bots that autonomously learn to rap battle: a symbolic probabilistic approach based on induction of stochastic transduction grammars, versus a neural network approach based on backpropagation through unconventional transduction recursive autoassociative memory (TRAAM) models. Rap battling is modeled as a quasi-translation problem, in which an appropriate output response must be improvised given any input challenge line of lyrics. Both approaches attempt to tackle the difficult problem of compositionality: for any challenge line, constructing a good response requires making salient associations while satisfying contextual preferences at many different, overlapping levels of granularity between the challenge and response lines. The contextual preferences include fluency, partial metrical or syntactic parallelism, and rhyming at various points across the lines. During both the learning and improvisation stages, the symbolic approach attempts to explicitly enumerate as many hypotheses as possible, whereas the neural approach attempts to evolve vector representations that better implicitly generalize over soft regions or neighborhoods of hypotheses. The brute force symbolic approach is more precise, but quickly generates combinatorial numbers of hypotheses when searching for generalizations. The distributed vector based neural approach can more easily confuse hypotheses, but maintains a constant level of complexity while retaining its implicit generalization bias. We contrast both the theoretical formulation and experimental outputs of the two approaches.
Smoothly clipped absolute deviation (SCAD) regularization for compressed sensing MRI using an augmented Lagrangian scheme

Compressed sensing (CS) in magnetic resonance imaging (MRI) enables the reconstruction of MR images from highly undersampled k-spaces, and thus substantial reduction of data acquisition time. In this context, edge-preserving and sparsity-promoting regularizers are used to exploit the prior knowledge that MR images are sparse or compressible in a given transform domain and thus to regulate the solution space. In this study, we introduce a new regularization scheme by iterative linearization of the non-convex clipped absolute deviation (SCAD) function in an augmented Lagrangian framework. The performance of the proposed regularization, which turned out to be an iteratively weighted total variation (TV) regularization, was evaluated using 2D phantom simulations and 3D retrospective undersampling of clinical MRI data by different sampling trajectories. It was demonstrated that the proposed regularization technique substantially outperforms conventional TV regularization, especially at reduced sampling rates.
Next-Generation Sequence Assembly: Four Stages of Data Processing and Computational Challenges

Decoding DNA symbols using next-generation sequencers was a major breakthrough in genomic research. Despite the many advantages of next-generation sequencers, e.g., the high-throughput sequencing rate and relatively low cost of sequencing, the assembly of the reads produced by these sequencers still remains a major challenge. In this review, we address the basic framework of next-generation genome sequence assemblers, which comprises four basic stages: preprocessing filtering, a graph construction process, a graph simplification process, and postprocessing filtering. Here we discuss them as a framework of four stages for data analysis and processing and survey variety of techniques, algorithms, and software tools used during each stage. We also discuss the challenges that face current assemblers in the next-generation environment to determine the current state-of-the-art. We recommend a layered architecture approach for constructing a general assembler that can handle the sequences generated by different sequencing platforms.
Mobile Robot Simultaneous Localization and Mapping in Dynamic Environments

We propose an on-line algorithm for simultaneous localization and mapping of dynamic environments. Our algorithm is capable of differentiating static and dynamic parts of the environment and representing them appropriately on the map. Our approach is based on maintaining two occupancy grids. One grid models the static parts of the environment, and the other models the dynamic parts of the environment. The union of the two grid maps provides a complete description of the environment over time. We also maintain a third map containing information about static landmarks detected in the environment. These landmarks provide the robot with localization. Results in simulation and real robots experiments show the efficiency of our approach and also show how the differentiation of dynamic and static entities in the environment and SLAM can be mutually beneficial.
Civic engagement and the transition to adulthood.

Constance Flanagan and Peter Levine survey research on civic engagement among U.S. adolescents and young adults. Civic engagement, they say, is important both for the functioning of democracies and for the growth and maturation it encourages in young adults, but opportunities for civic engagement are not evenly distributed by social class or race and ethnicity. Today's young adults, note the authors, are less likely than those in earlier generations to exhibit many important characteristics of citizenship, raising the question of whether these differences represent a decline or simply a delay in traditional adult patterns of civic engagement. Flanagan and Levine also briefly discuss the civic and political lives of immigrant youth in the United States, noting that because these youth make up a significant share of the current generation of young adults, their civic engagement is an important barometer of the future of democracy. The authors next survey differences in civic participation for youth from different social, racial, and ethnic backgrounds. They explore two sets of factors that contribute to a lower rate of civic engagement among low-income and minority young adults. The first is cumulative disadvantage-unequal opportunities and influences before adulthood, especially parental education. The second is different institutional opportunities for civic engagement among college and non-college youth during the young-adult years. Flanagan and Levine survey various settings where young adults spend time-schools and colleges, community organizations, faith-based institutions, community organizing and activism projects, and military and other voluntary service programs-and examine the opportunities for civic engagement that each affords. As the transition to adulthood has lengthened, say the authors, colleges have become perhaps the central institution for civic incorporation of younger generations. But no comparable institution exists for young adults who do not attend college. Opportunities for sustained civic engagement by year-long programs such as City Year could provide an alternative opportunity for civic engagement for young adults from disadvantaged families, allowing them to stay connected to mainstream opportunities and to adults who could mentor and guide their way.
Mechanomyography signals in spastic muscle and the correlation with the modified Ashworth scale

The modified Ashworth scale (MAS) is the most widely used measurement technique to assess levels of spasticity. In MAS, the evaluator graduates spasticity considering his/her subjective analysis of the muscular endurance during passive stretching. Therefore, it is a subjective scale. Mechanomyography (MMG) allows registering the vibrations generated by muscle contraction and stretching events that propagate through the tissue until the surface of the skin. With this in mind, this study aimed to investigate possible correlations between MMG signal and muscle spasticity levels determined by MAS. We evaluated 34 limbs considered spastic by MAS, including upper and lower limbs of 22 individuals of both sexes. Simultaneously, the MMG signals of the spastic muscle group (agonists) were acquired. The features investigated involved, in the time domain, the median energy (MMGME) of the MMG Z-axis (perpendicular to the muscle fibers) and, in the frequency domain, the median frequency (MMGmf). The Kruskal-Wallis test (p<;0.001) determined that there were significant differences between intergroup MAS spasticity levels for MMGme. There was a high linear correlation between the MMGme and MAS (R2=0.9557) and also a high correlation as indicated by Spearman test (ρ=0.9856; p<;0.001). In spectral analysis, the Kruskal-Wallis test (p = 0.0059) showed that MMGmf did not present significant differences between MAS spasticity levels. There was moderate linear correlation between MAS and MMGmf (R2=0.4883 and Spearman test [ρ = 0.4590; p <; 0.001]). Between the two investigated features, we conclude that the median energy is the most viable feature to evaluate spasticity due to strong correlations with the MAS.