Miracle-dz/UniFAR-FTUs huggingface dataset:
Multilevel adaptive sparse Leja approximations for Bayesian inverse problems

Deterministic interpolation and quadrature methods are often unsuitable to address Bayesian inverse problems depending on computationally expensive forward mathematical models. While interpolation may give precise posterior approximations, deterministic quadrature is usually unable to efficiently investigate an informative and thus concentrated likelihood. This leads to a large number of required expensive evaluations of the mathematical model. To overcome these challenges, we formulate and test a multilevel adaptive sparse Leja algorithm. At each level, adaptive sparse grid interpolation and quadrature are used to approximate the posterior and perform all quadrature operations, respectively. Specifically, our algorithm uses coarse discretizations of the underlying mathematical model to investigate the parameter space and to identify areas of high posterior probability. Adaptive sparse grid algorithms are then used to place points in these areas, and ignore other areas of small posterior probability. The points are weighted Leja points. As the model discretization is coarse, the construction of the sparse grid is computationally efficient. On this sparse grid, the posterior measure can be approximated accurately with few expensive, fine model discretizations. The efficiency of the algorithm can be enhanced further by exploiting more than two discretization levels. We apply the proposed multilevel adaptive sparse Leja algorithm in numerical experiments involving elliptic inverse problems in 2D and 3D space, in which we compare it with Markov chain Monte Carlo sampling and a standard multilevel approximation.
Association of troponin T detected with a highly sensitive assay and cardiac structure and mortality risk in the general population.

CONTEXT Detectable levels of cardiac troponin T (cTnT) are strongly associated with structural heart disease and increased risk of death and adverse cardiovascular events; however, cTnT is rarely detectable in the general population using standard assays. OBJECTIVES To determine the prevalence and determinants of detectable cTnT in the population using a new highly sensitive assay and to assess whether cTnT levels measured with the new assay associate with pathological cardiac phenotypes and subsequent mortality. DESIGN, SETTING, AND PARTICIPANTS Cardiac troponin T levels were measured using both the standard and the highly sensitive assays in 3546 individuals aged 30 to 65 years enrolled between 2000 and 2002 in the Dallas Heart Study, a multiethnic, population-based cohort study. Mortality follow-up was complete through 2007. Participants were placed into 5 categories based on cTnT levels. MAIN OUTCOME MEASURES Magnetic resonance imaging measurements of cardiac structure and function and mortality through a median of 6.4 (interquartile range, 6.0-6.8) years of follow-up. RESULTS In Dallas County, the prevalence of detectable cTnT (≥0.003 ng/mL) was 25.0% (95% confidence interval [CI], 22.7%-27.4%) with the highly sensitive assay vs 0.7% (95% CI, 0.3%-1.1%) with the standard assay. Prevalence was 37.1% (95% CI, 33.3%-41.0%) in men vs 12.9% (95% CI, 10.6%-15.2%) in women and 14.0% (95% CI, 11.2%-16.9%) in participants younger than 40 years vs 57.6% (95% CI, 47.0%-68.2%) in those 60 years and older. Prevalence of left ventricular hypertrophy increased from 7.5% (95% CI, 6.4%-8.8%) in the lowest cTnT category (<0.003 ng/mL) to 48.1% (95% CI, 36.7%-59.6%) in the highest (≥0.014 ng/mL) (P < .001); prevalence of left ventricular systolic dysfunction and chronic kidney disease also increased across categories (P < .001 for each). During a median follow-up of 6.4 years, there were 151 total deaths, including 62 cardiovascular disease deaths. All-cause mortality increased from 1.9% (95% CI, 1.5%-2.6%) to 28.4% (95% CI, 21.0%-37.8%) across higher cTnT categories (P < .001). After adjustment for traditional risk factors, C-reactive protein level, chronic kidney disease, and N-terminal pro-brain-type natriuretic peptide level, cTnT category remained independently associated with all-cause mortality (adjusted hazard ratio, 2.8 [95% CI, 1.4-5.2] in the highest category). Adding cTnT categories to the fully adjusted mortality model modestly improved model fit (P = .02) and the integrated discrimination index (0.010 [95% CI, 0.002-0.018]; P = .01). CONCLUSION In this population-based cohort, cTnT detected with a highly sensitive assay was associated with structural heart disease and subsequent risk for all-cause mortality.
Effect of Rhizobium Symbiosis on Low-Temperature Tolerance and Antioxidant Response in Alfalfa (Medicago sativa L.)

Low temperature-induced stress is a major environmental factor limiting the growth and development of plants. Alfalfa (Medicago sativa L.) is a legume well known for its tolerance of extreme environments. In this study, we sought to experimentally investigate the role of rhizobium symbiosis in alfalfa’s performance under a low-temperature stress condition. To do this, alfalfa “Ladak+” plants carrying active nodules (AN), inactive nodules (IN), or no nodules (NN) were exposed to an imposed low temperature stress and their survivorship calculated. The antioxidant defense responses, the accumulation of osmotic regulation substances, the cell membrane damage, and the expression of low temperature stress-related genes were determined in both the roots and the shoots of alfalfa plants. We found that more plants with AN survived than those with IN or NN under the same low temperature-stress condition. Greater activity of oxidation protective enzymes was observed in the AN and IN groups, conferring higher tolerance to low temperature in these plants. In addition, rhizobia nodulation also enhanced alfalfa’s ability to tolerate low temperature by altering the expression of regulatory and metabolism-associated genes, which resulted in the accumulation of soluble proteins and sugars in the nodulated plants. Taken together, the findings of this study indicate that rhizobium inoculation offers a practical way to promote the persistence and growth potential of alfalfa “Ladak+” in cold areas.
OAZ-t/OAZ3 Is Essential for Rigid Connection of Sperm Tails to Heads in Mouse

Polyamines are known to play important roles in the proliferation and differentiation of many types of cells. Although considerable amounts of polyamines are synthesized and stored in the testes, their roles remain unknown. Ornithine decarboxylase antizymes (OAZs) control the intracellular concentration of polyamines in a feedback manner. OAZ1 and OAZ2 are expressed ubiquitously, whereas OAZ-t/OAZ3 is expressed specifically in germline cells during spermiogenesis. OAZ-t reportedly binds to ornithine decarboxylase (ODC) and inactivates ODC activity. In a prior study, polyamines were capable of inducing a frameshift at the frameshift sequence of OAZ-t mRNA, resulting in the translation of OAZ-t. To investigate the physiological role of OAZ-t, we generated OAZ-t–disrupted mutant mice. Homozygous OAZ-t mutant males were infertile, although the polyamine concentrations of epididymides and testes were normal in these mice, and females were fertile. Sperm were successfully recovered from the epididymides of the mutant mice, but the heads and tails of the sperm cells were easily separated in culture medium during incubation. Results indicated that OAZ-t is essential for the formation of a rigid junction between the head and tail during spermatogenesis. The detached tails and heads were alive, and most of the headless tails showed straight forward movement. Although the tailless sperm failed to acrosome-react, the heads were capable of fertilizing eggs via intracytoplasmic sperm injection. OAZ-t likely plays a key role in haploid germ cell differentiation via the local concentration of polyamines.
Pauli Fusion: a Computational Model to Realise Quantum Transformations from ZX Terms

We present an abstract model of quantum computation, the Pauli Fusion model, whose primitive operations correspond closely to generators of the ZX calculus (a formal graphical language for quantum computing). The fundamental operations of Pauli Fusion are also straightforward abstractions of basic processes in some leading proposed quantum technologies. These operations have non-deterministic heralded effects, similarly to measurement-based quantum computation. We describe sufficient conditions for Pauli Fusion procedures to be deterministically realisable, so that it performs a given transformation independently of its non-deterministic outcomes. This provides an operational model to realise ZX terms beyond the circuit model.
Optimal Scheduling of Multiple Sensors Over Lossy and Bandwidth Limited Channels

This article considers the sensor scheduling for multiple dynamic processes. We consider $n$ linear dynamic processes. The state of each process is measured by a sensor, which transmits its local state estimate over one wireless channel to a remote estimator with certain communication costs. At each time step, only a portion of the sensors are allowed to transmit data to the remote estimator and the packet might be lost due to unreliability of the wireless channels. Our goal is to find a scheduling policy that coordinates the sensors in a centralized manner to minimize the total expected estimation error of the remote estimator and the communication costs. We formulate the problem as a Markov decision process. We develop an algorithm to check whether there exists a deterministic stationary optimal policy. We show the optimality of monotone policies, which saves the computational effort of finding an optimal policy and facilitates practical implementation. Nevertheless, obtaining an exact optimal policy still suffers from the curse of dimensionality when the number of processes is large. We further provide an index-based heuristic to avoid brute-force computation. We derive analytic expressions of the indices and show that this heuristic is asymptotically optimal. Numerical examples are presented to illustrate the theoretical results.
A Statistical Method for the Analysis of Speech Intelligibility Tests

Speech intelligibility tests are conducted on hearing-impaired people for the purpose of evaluating the performance of a hearing device under varying listening conditions and device settings or algorithms. The speech reception threshold (SRT) is typically defined as the signal-to-noise ratio (SNR) at which a subject scores 50% correct on a speech intelligibility test. An SRT is conventionally measured with an adaptive procedure, in which the SNR of successive sentences is adjusted based on the subject's scores on previous sentences. The SRT can be estimated as the mean of a subset of the SNR levels, or by fitting a psychometric function. A set of SRT results is typically analyzed with a repeated measures analysis of variance. We propose an alternative approach for analysis, a zero-and-one inflated beta regression model, in which an observation is a single sentence score rather than an SRT. A parametrization of the model is defined that allows efficient maximum likelihood estimation of the parameters. Fitted values from this model, when plotted against SNR, are analogous to a mean psychometric function in the traditional approach. Confidence intervals for the fitted value curves are obtained by parametric bootstrap. The proposed approach was applied retrospectively to data from two studies that assessed the speech perception of cochlear implant recipients using different sound processing algorithms under different listening conditions. The proposed approach yielded mean SRTs for each condition that were consistent with the traditional approach, but were more informative. It provided the mean psychometric curve of each condition, revealing differences in slope, i.e. differential performance at different parts of the SNR spectrum. Another advantage of the new method of analysis is that results are stated in terms of differences in percent correct scores, which is more interpretable than results from the traditional analysis.
Automatic extrinsic calibration between a camera and a 3D Lidar using 3D point and plane correspondences

This paper proposes an automated method to obtain the extrinsic calibration parameters between a camera and a 3D lidar with as low as 16 beams. We use a checkerboard as a reference to obtain features of interest in both sensor frames. The calibration board centre point and normal vector are automatically extracted from the lidar point cloud by exploiting the geometry of the board. The corresponding features in the camera image are obtained from the camera’s extrinsic matrix. We explain the reasons behind selecting these features, and why they are more robust compared to other approaches. To obtain the optimal extrinsic parameters, we choose a genetic algorithm to address the highly non-linear state space. The process is automated after defining the bounds of the 3D experimental region relative to the lidar, and the true board dimensions. In addition, the camera is assumed to be intrinsically calibrated. Our method requires a minimum of 3 checkerboard poses, and the calibration accuracy is demonstrated by evaluating our algorithm using real world and simulated features.
Predictors of Mortality and Symptomatic Outcome of Patients With Low‐Flow Severe Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement

Background Impaired left ventricular (LV) ejection fraction is a common finding in patients with aortic stenosis and serves as a predictor of morbidity and mortality after transcatheter aortic valve replacement. However, conflicting data on the most accurate measure for LV function exist. We wanted to examine the impact of LV ejection fraction, mean pressure gradient, and stroke volume index on the outcome of patients treated by transcatheter aortic valve replacement. Methods and Results Patients treated by transcatheter aortic valve replacement were primarily separated into normal flow (NF; stroke volume index >35 mL/m2) and low flow (LF; stroke volume index ≤35 mL/m2). Afterwards, patients were divided into 5 groups: “NF–high gradient,” “NF–low gradient” (NF‐LG), “LF–high gradient,” “paradoxical LF‐LG,” and “classic LF‐LG. ” The 3‐year mortality was the primary end point. Of 1600 patients, 789 (49.3%) were diagnosed as having LF, which was characterized by a higher 30‐day (P=0.041) and 3‐year (P<0.001) mortality. LF was an independent predictor of all‐cause (hazard ratio, 1.29; 95% confidence interval, 1.03–1.62; P=0.03) and cardiovascular (hazard ratio, 1.37; 95% confidence interval, 1.06–1.77; P=0.016) mortality. Neither mean pressure gradient nor LV ejection fraction was an independent predictor of mortality. Patients with paradoxical LF‐LG (35.0%), classic LF‐LG (35.1%) and LF–high gradient (38.1%) had higher all‐cause mortality at 3 years compared with NF–high gradient (24.8%) and NF‐LG (27.9%) (P=0.001). However, surviving patients showed a similar improvement in symptoms regardless of aortic stenosis entity. Conclusions LF is a common finding within the aortic stenosis population and, in contrast to LV ejection fraction or mean pressure gradient, an independent predictor of all‐cause and cardiovascular mortality. Despite increased long‐term mortality, high procedural success and excellent functional improvement support transcatheter aortic valve replacement in patients with LF severe aortic stenosis.
C1 inhibitor, a multi-functional serine protease inhibitor

Summary C1 inhibitor (C1INH) is a serpin that regulates both complement and contact (kallikrein-kinin) system activation. It consists of a serpin domain that is highly homologous to other serpins and an amino terminal non-serpin mucin-like domain. Deficiency of C1INH results in hereditary angioedema, a disease characterised by episodes of angioedema of the skin or the mucosa of the gastrointestinal tract or the oropharynx. Although early data suggested that angioedema was mediated via complement system activation, the preponderance of the data indicate that bradykinin is the mediator. In the past few years, it has become apparent that C1INH has additional anti-inflammatory functions independent of protease inhibition. These include interactions with leukocytes that may result in enhanced phagocytosis, with endothelial cells via Eand P-selectins that interfere with leukocyte rolling and in turn results in suppression of transmigration of leukocytes across the endothelium, and interactions with extracellular matrix components that may serve to concentrate C1INH at sites of inflammation. In addition, C1INH suppresses gram negative sepsis and endotoxin shock, partly via direct interaction with endotoxin that interferes with its interaction with macrophages, thereby suppressing tumour necrosis factor-α and other inflammatory mediators. C1INH treatment improves outcome in a number of disease models, including sepsis and other bacterial infections, possibly malaria, ischaemia-reperfusion injury (intestinal, hepatic, muscle, cardiac, brain), hyper-acute transplant rejection, and other inflammatory disease models. Recent data suggest that this effectiveness is the result of mechanisms that do not require protease inhibition, in addition to both complement and contact system activation.
Trait evolution, resource specialization and vulnerability to plant extinctions among Antillean hummingbirds

Species traits are thought to predict feeding specialization and the vulnerability of a species to extinctions of interaction partners, but the context in which a species evolved and currently inhabits may also matter. Notably, the predictive power of traits may require that traits evolved to fit interaction partners. Furthermore, local abiotic and biotic conditions may be important. On islands, for instance, specialized and vulnerable species are predicted to be found mainly in mountains, whereas species in lowlands should be generalized and less vulnerable. We evaluated these predictions for hummingbirds and their nectar-food plants on Antillean islands. Our results suggest that the rates of hummingbird trait divergence were higher among ancestral mainland forms before the colonization of the Antilles. In correspondence with the limited trait evolution that occurred within the Antilles, local abiotic and biotic conditions—not species traits—correlate with hummingbird resource specialization and the vulnerability of hummingbirds to extinctions of their floral resources. Specifically, hummingbirds were more specialized and vulnerable in conditions with high topographical complexity, high rainfall, low temperatures and high floral resource richness, which characterize the Antillean Mountains. These findings show that resource specialization and species vulnerability to extinctions of interaction partners are highly context-dependent.
Assessing the ability of numerical ice sheet models to simulate grounding line migration

Grounding line migration is a key process affecting the stability of marine ice sheets such as the West Antarctic ice sheet (WAIS). Grounding line motion is often included in numerical models simulating the past and future evolution of the WAIS; however, little attention has been paid to the numerical consistency of these models. The aim of this paper is to assess the ability of simple versions of existing marine ice sheet models to simulate grounding line migration. In particular, we investigate the response of the grounding line to external forcing and the sensitivity of the models' predictions to their numerics and the mechanical coupling between ice sheet and shelf. From the model comparison, there is no consensus on how the grounding line should react to changes in boundary conditions. A crucial finding is the strong dependency of models using a fixed grid on numerical details such as the horizontal grid size. This implies that we should be very wary about grounding line predictions from such models. Including mechanical coupling at the grounding line does not seem to change the qualitative behavior of the models. This suggests that the way the grounding line is treated in marine ice sheet models dominantly determines the grounding line dynamics. We find that models that employ a moving grid to explicitly track the grounding line do not share many of the deficiencies of the fixed grid models. We conclude that at present, no reliable model of the grounding line is available, and further model development is urgently needed.
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems

This paper proposes a distributed privacypreserving sparse PCA (DPS-PCA) algorithm that generates a minimax-optimal sparse PCA estimator under differential privacy constraints. In a distributed optimization framework, data providers can use this algorithm to collaboratively analyze the union of their data sets while limiting the disclosure of their private information. DPS-PCA can recover the leading eigenspace of the population covariance at a geometric convergence rate, and simultaneously achieves the optimal minimax statistical error for high-dimensional data. Our algorithm provides fine-tuned control over the tradeoff between estimation accuracy and privacy preservation. Numerical simulations demonstrate that DPS-PCA significantly outperforms other privacy-preserving PCA methods in terms of estimation accuracy and computational efficiency.
Naloxone injections into CA3 disrupt pattern completion associated with relapse from cocaine seeking

The goal of the present research was to assess the degree to which a pattern completion process operates in cue‐induced relapse to cocaine‐seeking behavior. Using a novel cue‐preference version of the place preference task, rats were administered cocaine or saline, which resulted in a preference for the cocaine‐paired cues. After 21 days of abstinence and prior to the preference test, for one group, PBS or naloxone was injected into the CA3 subregion of the hippocampus and for a second group, saline or naloxone was injected systemically. The results indicated that infusions of naloxone into CA3 or systemic injections produced a marked disruption for one and two cues, but had minimal disruptive effect for three or four cues, suggesting that naloxone injections disrupt CA3 function and trigger a deficit in a pattern completion process. Thus, it appears that cue‐based activation of the dorsal CA3 might be a critical trigger via a pattern completion process. Based on additional analyses it appears that there is a disruption primarily for object touches for one cue naloxone injections into the CA3 or systemic injections, but no effect on time (spatial context). © 2016 Wiley Periodicals, Inc.
The Importance of ‘Likes’: The Interplay of Message Framing, Source, and Social Endorsement on Credibility Perceptions of Health Information on Facebook

Online sources not only permeate the information-seeking environment of the younger generation, but also have profound influence in shaping their beliefs and behaviors. In this landscape, examining the factors responsible for credibility perceptions of online information is fundamental, particularly for health-related information. Using a 2 (frames: gain vs. loss) × 2 (source: expert vs. non-expert) × 2 (social endorsement: high vs. low) randomized between-subjects experimental design, this study examines the effect of health message framing and the moderating effects of social endorsement and source type on credibility perceptions of Facebook posts. Testing across two issues––physical activity and alcohol consumption––findings indicate that the gain-framed message was perceived as most credible. Additionally, significant three-way interactions suggest that social endorsement and source type affect the relationship between message framing and credibility perceptions. Specifically, the findings demonstrate that a gain-framed message from an expert source with high number of ‘likes’ is considered the most credible message. These findings have significant implications for information gathering from social media sources, such as the influence of ‘likes’ on health information.