Miracle-dz/UniFAR-FTUs huggingface dataset:
Pathway-Based Analysis of the Liver Response to Intravenous Methylprednisolone Administration in Rats: Acute Versus Chronic Dosing

Pharmacological time-series data, from comparative dosing studies, are critical to characterizing drug effects. Reconciling the data from multiple studies is inevitably difficult; multiple in vivo high-throughput -omics studies are necessary to capture the global and temporal effects of the drug, but these experiments, though analogous, differ in (microarray or other) platforms, time-scales, and dosing regimens and thus cannot be directly combined or compared. This investigation addresses this reconciliation issue with a meta-analysis technique aimed at assessing the intrinsic activity at the pathway level. The purpose of this is to characterize the dosing effects of methylprednisolone (MPL), a widely used anti-inflammatory and immunosuppressive corticosteroid (CS), within the liver. A multivariate decomposition approach is applied to analyze acute and chronic MPL dosing in male adrenalectomized rats and characterize the dosing-dependent differences in the dynamic response of MPL-responsive signaling and metabolic pathways. We demonstrate how to deconstruct signaling and metabolic pathways into their constituent pathway activities, activities which are scored for intrinsic pathway activity. Dosing-induced changes in the dynamics of pathway activities are compared using a model-based assessment of pathway dynamics, extending the principles of pharmacokinetics/pharmacodynamics (PKPD) to describe pathway activities. The model-based approach enabled us to hypothesize on the likely emergence (or disappearance) of indirect dosing-dependent regulatory interactions, pointing to likely mechanistic implications of dosing of MPL transcriptional regulation. Both acute and chronic MPL administration induced a strong core of activity within pathway families including the following: lipid metabolism, amino acid metabolism, carbohydrate metabolism, metabolism of cofactors and vitamins, regulation of essential organelles, and xenobiotic metabolism pathway families. Pathway activities alter between acute and chronic dosing, indicating that MPL response is dosing dependent. Furthermore, because multiple pathway activities are dominant within a single pathway, we observe that pathways cannot be defined by a single response. Instead, pathways are defined by multiple, complex, and temporally related activities corresponding to different subgroups of genes within each pathway.
Metabolomic profiling to identify effects of dietary calcium reveal the influence of the individual and postprandial dynamics on the canine plasma metabolome

Abstract Short-term feeding studies have highlighted a phenomenon in Ca regulation that raises concerns around Ca absorption in dogs that may make an impact on commercial diets near to the maximum recommended level. A recent study to determine responses in dogs fed one of two diets differing in dietary Ca over 40 weeks found no evidence to suggest a concern across a range of biological parameters hypothesised to be affected by Ca. Unforeseen consequences of dietary Ca could have occurred and metabolic profiling was deemed a suitable data-driven approach to identify effects of dietary Ca. The objectives were to compare the fasted plasma metabolome (sampled at 8-week intervals over 40 weeks) of dogs fed one of two diets, near to the minimum and maximum recommended levels of dietary Ca. Comparisons with the control diet were also investigated across the postprandial time course (1–4 h) following acute (1 d) and long-term (24 weeks) feeding of the test diet. Comparing fasted plasma samples at each time point, no significant effect (adjusted P < 0·05) of diet on metabolites was observed. In the postprandial state, only phosphate was consistently different between diets and was explained by additional dietary P to maintain Ca:P. Metabolic profiling analysis supports the view that the dietary Ca upper limit is safe. Additionally, the canine plasma metabolome was characterised, providing insights into the stability of individual profiles across 40 weeks, the response to consumption of a nutritionally complete meal over a 4 h postprandial time course and different kinetic categories of postprandial absorption.
Peripheral Refraction and Eye Lengths in Myopic Children in the Bifocal Lenses In Nearsighted Kids (BLINK) Study

Purpose Provide a detailed assessment of peripheral refractive error and peripheral eye length in myopic children. Methods Subjects were 294 children aged 7 to 11 years with −0.75 to −5.00 diopter (D) of myopia by cycloplegic autorefraction. Peripheral refraction and eye length were measured at ±20° and ±30° horizontally and vertically, with peripheral refraction also measured at ±40° horizontally. Results Relative peripheral refraction became more hyperopic in the horizontal meridian and more myopic in the vertical meridian with increasing field angle. Peripheral eye length became shorter in both meridians with increasing field angle, more so horizontally than vertically with correlations between refraction and eye length ranging from −0.40 to −0.57 (all P < 0.001). Greater foveal myopia was related to more peripheral hyperopia (or less peripheral myopia), shorter peripheral eye lengths, and a consistent average asymmetry between meridians. Conclusions Peripheral refractive errors in children do not appear to exert strong local control of peripheral eye length given that their correlation is consistently negative and the degree of meridional asymmetry is similar across the range of refractive errors. The BLINK study will provide longitudinal data to determine whether peripheral myopia and additional peripheral myopic defocus from multifocal contact lenses affect the progression of myopia in children. Translational Relevance Local retinal control of ocular growth has been demonstrated numerous times in animal experimental myopia models but has not been explored in detail in human myopia development. These BLINK baseline results suggest that children's native peripheral optical signals may not be a strong stimulus for local growth responses.
Evaluation of RE and B1 Genes as Targets for Detection of Toxoplasma gondii by Nested PCR in Blood Samples of Patients with Ocular Toxoplasmosis

To evaluate B1 and RE genes as targets to detect Toxoplasma gondii, nested PCR is used in blood samples of patients with ocular toxoplasmosis. Following the measurement of IgG and IgM antibodies using indirect ELISA, IgG avidity and assessment of blood samples by nested PCR, the agreement between various test results was studied. From 117 patients, 77 (65.81%) were found to be positive for IgG anti-Toxoplasma antibody, 12 cases were positive for both IgG and IgM, and 1 patient was positive for IgM only. The detection limit for the RE-nested PCR assay was one T. gondii tachyzoite, whereas the limit for B1-nested PCR was five tachyzoites. Nested PCR results showed higher agreement with IgM test results than IgG test results. The results of this study showed that nested PCR of peripheral blood is a useful and non-invasive method for detection of T. gondii in patients with OT, especially in case of recently acquired infections, and RE targeted assay is more sensitive than B1 targeted assay for this purpose.
Cell phone use predicts being an “active couch potato”: results from a cross-sectional survey of sufficiently active college students

Objective “Active couch potato” describes an individual who is sufficiently physically active yet highly sedentary. Cell phones promote activities understood as sedentary behaviors (e.g. watching videos). Research demonstrates that cell phone use is positively associated with sedentary behavior. Although sedentary behavior typically displaces physical activity, no relationship between cell phone use and physical activity has been found. Thus, it is possible that some sufficiently active individuals are also high-frequency cell phone users and therefore highly sedentary. In other words, cell phone use may predict being an “active couch potato” among active people. Testing this hypothesis was the purpose of this study. “Active couch potatoes” are of concern as the negative effects of excessive sedentary behavior are independent of the benefits of physical activity. Methods College students (228) completed validated surveys assessing physical activity, sedentary behavior, and cell phone use. Using a previously validated method, participants were rated as sufficiently active or not based upon their physical activity survey score. Participants who were not sufficiently active were excluded from further analysis resulting in a final sample of 171. These sufficiently active individuals were categorized as “active couch potatoes” if they were also highly sedentary (i.e. sitting for eight or more hours/day). Logistic regression determined if cell phone use predicted being categorized as an “active couch potato. ” Results Cell phone use was a significant, positive predictor of being an “active couch potato. ” With each additional hour of daily cell phone use, the odds of becoming an “active couch potato” increased by 11.4% (Wald = 5.934, P = 0.015, Exp(B) = 1.114). On average, active couch potatoes used their cell phone 1.7 hours more each day than their sufficiently active but not overly sedentary peers. Conclusion Increased cell phone use was a significant predictor of being an “active couch potato. ” Explanations and implications are discussed.
A Case of Acute Heart Failure due to Immune Checkpoint Blocker Nivolumab

Immune checkpoint inhibitors can be potentially cardiotoxic. It has not been frequently reported in the literature. Cardiomyopathy with these agents can have early onset and may start with non-specific symptoms like fatigue, weakness before presenting with obvious features of acute heart failure. Rapid progression and fulminant course of this disease necessitate high index of clinical suspicion and early diagnosis. High-dose steroids should be instituted early to blunt the immune response against myocardium. Further bigger studies are needed to fully understand the pathogenesis of this condition.
On the Contributions of Visual and Textual Supervision in Low-resource Semantic Speech Retrieval

Recent work has shown that speech paired with images can be used to learn semantically meaningful speech representations even without any textual supervision. In real-world low-resource settings, however, we often have access to some transcribed speech. We study whether and how visual grounding is useful in the presence of varying amounts of textual supervision. In particular, we consider the task of semantic speech retrieval in a low-resource setting. We use a previously studied data set and task, where models are trained on images with spoken captions and evaluated on human judgments of semantic relevance. We propose a multitask learning approach to leverage both visual and textual modalities, with visual supervision in the form of keyword probabilities from an external tagger. We find that visual grounding is helpful even in the presence of textual supervision, and we analyze this effect over a range of sizes of transcribed data sets. With ~5 hours of transcribed speech, we obtain 23% higher average precision when also using visual supervision.
Detailed Human Shape Estimation From a Single Image by Hierarchical Mesh Deformation

This paper presents a novel framework to recover detailed human body shapes from a single image. It is a challenging task due to factors such as variations in human shapes, body poses, and viewpoints. Prior methods typically attempt to recover the human body shape using a parametric based template that lacks the surface details. As such the resulting body shape appears to be without clothing. In this paper, we propose a novel learning-based framework that combines the robustness of parametric model with the flexibility of free-form 3D deformation. We use the deep neural networks to refine the 3D shape in a Hierarchical Mesh Deformation (HMD) framework, utilizing the constraints from body joints, silhouettes, and per-pixel shading information. We are able to restore detailed human body shapes beyond skinned models. Experiments demonstrate that our method has outperformed previous state-of-the-art approaches, achieving better accuracy in terms of both 2D IoU number and 3D metric distance. The code is available in https://github.com/zhuhao-nju/hmd.git.
Clinical Significance of Low Blood Testosterone Concentration in Men as a Cardiovascular Risk Factor From the Perspective of Blood Rheology

Background Recent clinical studies have indicated the importance of low blood testosterone concentration or whole blood passage time (WBPT) which reflects blood rheology as a cardiovascular risk factor. On the contrary, there are no reports regarding the association of blood testosterone concentrations and WBPT. This cross-sectional study aimed to elucidate the clinical significance of low blood testosterone concentration in men as a cardiovascular risk factor from the perspective of blood rheology using WBPT. Methods In total, 382 male patients with traditional cardiovascular risk factor and no history of cardiovascular disease (age (mean ± standard deviation (SD)), 64 ± 10 years) were enrolled. Serum total testosterone concentration (T-T) was measured as a marker of testosterone level in vivo, and WBPT was also measured using microchannel array flow analyzer as a commercial device. The relationship between T-T and WBPT was evaluated. Results There was a significantly negative correlation between T-T and WBPT (r = -0.45; P < 0.001). Furthermore, multiple regression analysis revealed that T-T (β = -0.25; P < 0.001) could be selected as an independent variable when WBPT was used as a subordinate factor. According to receiver operating characteristic curve analysis and the result of the previous report that determined WBPT of > 72.4 s as a risk for incidence of primary cardiovascular disease, T-T of < 551.4 ng/dL is the optimal cut-off point for discriminating high WBPT. Conclusions The study results showed that T-T is independently and inversely associated with WBPT in male patients with traditional cardiovascular risk factor and no history of cardiovascular disease. In addition, this study suggests that the incidence of primary cardiovascular events can be prevented by maintaining T-T at approximately ≥ 550 ng/dL from the perspective of blood rheology.
Modelling serial clustering and inter‐annual variability of European winter windstorms based on large‐scale drivers

Winter windstorms are known to be among the most dangerous and loss intensive natural hazards in Europe. In order to gain a better understanding of their variability and driving mechanisms, this study analyses the temporal variability which is often referred to as serial or seasonal clustering. This is realized by developing a statistical model relating the winter storm counts to known teleconnection patterns affecting European weather and climate conditions (e.g., North Atlantic Oscillation [NAO], Scandinavian pattern [SCA], etc.). The statistical model is developed via a stepwise Poisson regression approach that is applied to windstorm counts and large‐scale indices retrieved from the ERA‐20C reanalysis. Significant large‐scale drivers accountable for the inter‐annual variability of storms for several European regions are identified and compared. In addition to the SCA and the NAO which are found to be the essential drivers for most areas within the European domain, other teleconnections (e.g., East Atlantic pattern) are found to be more significant for the inter‐annual variability in certain regions.
BYU micro-SAR: A very small, low-power LFM-CW Synthetic Aperture Radar

BYU MICRO-SAR: A VERY SMALL, LOW-POWER LFM-CW SYNTHETIC APERTURE RADAR Michael I. Duersch Department of Electrical and Computer Engineering Master of Science Brigham Young University has developed a low-cost, light-weight, and low power consumption SAR for flight on a small unmanned aerial vehicle (UAV) at low altitudes. This micro-SAR, or μSAR, consumes only 18 watts of power, ideal for application on a small UAV. To meet these constraints, a linear frequency modulationcontinuous wave (LFM-CW) transmit signal is utilized. Use of an LFM-CW signal introduces some differences from the typical strip map SAR processing model that must be addressed in signal processing algorithms. This thesis presents a derivation of the LFM-CW signal model and the associated image processing algorithms used for the μSAR developed at BYU. A data simulator for the BYU LFM-CW SAR is detailed and results are provided for the case when the simulated data are processed using the μSAR algorithms. Data processing schemes are discussed, including compression, receive signal phase detection, interference filtering and auto-focusing. Finally, data collected from the instrument itself are processed and presented.
Native Banach spaces for splines and variational inverse problems

We propose a systematic construction of native Banach spaces for general spline-admissible operators ${\rm L}$. In short, the native space for ${\rm L}$ and the (dual) norm $\|\cdot\|_{\mathcal{X}'}$ is the largest space of functions $f: \mathbb{R}^d \to \mathbb{R}$ such that $\|{\rm L} f\|_{\mathcal{X}'}<\infty$, subject to the constraint that the growth-restricted null space of ${\rm L}$be finite-dimensional. This space, denoted by $\mathcal{X}'_{\rm L}$, is specified as the dual of the pre-native space $\mathcal{X}_{\rm L}$, which is itself obtained through a suitable completion process. The main difference with prior constructions (e.g., reproducing kernel Hilbert spaces) is that our approach involves test functions rather than sums of atoms (e.g, kernels), which makes it applicable to a much broader class of norms, including total variation. Under specific admissibility and compatibility hypotheses, we lay out the direct-sum topology of $\mathcal{X}_{\rm L}$ and $\mathcal{X}'_{\rm L}$, and identify the whole family of equivalent norms. Our construction ensures that the native space and its pre-dual are endowed with a fundamental Schwartz-Banach property. In practical terms, this means that $\mathcal{X}'_{\rm L}$ is rich enough to reproduce any function with an arbitrary degree of precision.
Complexity and Contract

It is well known that contract incompleteness can arise from the impossibility of planning for all future contingencies in a relationship (e.g. Williamson (1975)). In this paper it is shown that whether or not such incompleteness constrains the efficiency of the contract is very sensitive to assumptions concerning the timing of the resolution of uncertainty. It is shown that when agents must respond to an unforeseen contingency before being able to renegotiate the contract, then contract complexity is a binding constraint, a case that is called ex post holdup. Secondly, it is suggested that the amount of multi-tasking can provide a measure of contract complexity. When complexity is low, contingent contracting is efficient, while subjective performance evaluation is more efficient when complexity is high. In this case the optimal contract for ex post holdup is based upon the ability of humans to make subjective judgements that are in some cases more informative than explicit performance measures. Moreover, the efficiency of the contract is not sensitive to human error per se, but is an increasing function of the correlation in judgements between the contracting parties.
Generating Token-Level Explanations for Natural Language Inference

The task of Natural Language Inference (NLI) is widely modeled as supervised sentence pair classification. While there has been a lot of work recently on generating explanations of the predictions of classifiers on a single piece of text, there have been no attempts to generate explanations of classifiers operating on pairs of sentences. In this paper, we show that it is possible to generate token-level explanations for NLI without the need for training data explicitly annotated for this purpose. We use a simple LSTM architecture and evaluate both LIME and Anchor explanations for this task. We compare these to a Multiple Instance Learning (MIL) method that uses thresholded attention make token-level predictions. The approach we present in this paper is a novel extension of zero-shot single-sentence tagging to sentence pairs for NLI. We conduct our experiments on the well-studied SNLI dataset that was recently augmented with manually annotation of the tokens that explain the entailment relation. We find that our white-box MIL-based method, while orders of magnitude faster, does not reach the same accuracy as the black-box methods.
Adaptive numerical homogenization of non-linear diffusion problems

We propose an efficient numerical strategy for simulating fluid flow through porous media with highly oscillatory characteristics. Specifically, we consider non-linear diffusion models. This scheme is based on the classical homogenization theory and uses a locally mass-conservative formulation. In addition, we discuss some properties of the standard non-linear solvers and use an error estimator to perform a local mesh refinement. The main idea is to compute the effective parameters in such a way that the computational complexity is reduced without affecting the accuracy. We perform some numerical examples to illustrate the behaviour of the adaptive scheme and of the non-linear solvers. Finally, we discuss the advantages of the implementation of the numerical homogenization in a periodic media and the applicability of the same scheme in non-periodic test cases such as SPE10th project.
Identification and optimization of sharing patterns for scalable shared-memory multiprocessors

Distributed shared-memory architectures typically employ a directory-based protocol to maintain cache coherence. Identifying sharing patterns in parallel programs and applying specialized optimizations can increase cache-coherence protocol efficiency and yield performance improvements. In this thesis, I propose and study both optimizations to sharing patterns and techniques to identify sharing patterns. The main thrust of the thesis is sc GLOW, a comprehensive optimization for wide sharing--a sharing pattern that is a serious obstacle to scalability to large numbers of processors. I present sc GLOW in the form of extensions to the sc SCI ANSI/ sc IEEE standard. sc GLOW is implemented in special network switches and incorporates characteristics that are not found together in previous proposals: scalable writes and scalable reads, network locality (by exploiting the abundance of widely-shared data to satisfy requests locally), simplicity, transparency to the base protocol, and network topology independence. With simulation, I show that for programs with wide sharing, sc GLOW can be more than twice as fast as sc SCI in large systems. Furthermore, I examine techniques to identify sharing patterns. I propose a novel approach based on maintaining the history of load and store instructions in relation to coherence events (e.g., cache-misses) and predicting their future behavior. This instruction-based approach, differs from previously proposed adaptive protocols (address-based techniques) which maintain data-access history and predict future accesses. Instruction-based prediction can offer accurate detection of sharing patterns using few resources in the form of small predictors per node. I examine instruction-based prediction for three sharing patterns: wide sharing, migratory sharing, and producer-consumer sharing. For wide sharing, instruction-based prediction compares favorably to static identification and to two novel dynamic address-based identification schemes. For migratory sharing, instruction-based prediction matches or exceeds the performance of previously proposed adaptive protocols (for seven benchmark programs). For producer-consumer sharing, instruction-based prediction is coupled with speculative pre-send--a novel optimization based on speculative execution. The low mis-speculation rates of this scheme show promise for performance improvements.