Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary determinants of healthy/unhealthy metabolic phenotype in individuals with normal weight or overweight/obesity: a systematic review

Abstract Objectives: Nutritional factors are amongst the major determinants in the onset and development of obesity and metabolic complications. Nevertheless, the dietary determinants of metabolic health are not completely elucidated. The aim of this systematic review is to investigate nutritional and dietary factors that may contribute to metabolic heterogeneity in individuals with obesity or normal weight. Methods: A literature search was performed in PubMed, Scopus, EMBASE, and google scholar databases until August 2021, to locate studies that examined metabolic health and its association with intakes of specific foods or food groups, nutrient intakes or status, as well as adherence to certain dietary patterns. Two researchers had independently screened titles and abstracts, examined full-text studies, conducted data extraction, and evaluated their quality using the Newcastle–Ottawa Scale. Results: Twenty-seven studies, with a total of 39518 subjects, were included. Of these studies, 11 articles evaluated the association between different dietary patterns and metabolic phenotypes, while 15 had investigated the association of single food/nutrients intakes or nutrient status with metabolic phenotype, and one paper evaluated the association of dietary inflammatory index with metabolic health. The findings of these studies propose that healthy dietary patterns such as the Mediterranean pattern, Dietary Approaches to Stop Hypertension, and population-derived patterns (such as the “Healthy” and “Fruit and vegetable” patterns) were associated with higher odds of the metabolically healthy phenotype. Higher intakes of fruits, vegetables, dairy products, coffee/tea, vitamin D, magnesium, and flavonoids, were suggested to lower the risk of developing metabolically unhealthy phenotype, while, higher consumption of saturated fat, carbohydrate and sugar-sweetened beverages, fast foods, organ meats, and a pro-inflammatory diet increased the risk. Conclusion: Results from published studies, which were mostly cross-sectional, suggest that higher adherence to unhealthier dietary patterns, characterized by the consumption of refined and processed foods, was associated with a lower likelihood of having a healthy metabolic phenotype, while the opposite was observed for healthier dietary patterns. Findings may be used in developing nutritional strategies aimed at improving metabolic health in the population.
The First Near-infrared Transmission Spectrum of HIP 41378 f, A Low-mass Temperate Jovian World in a Multiplanet System

We present a near-infrared transmission spectrum of the long-period (P = 542 days), temperate (T eq = 294 K) giant planet HIP 41378 f obtained with the Wide-Field Camera 3 instrument aboard the Hubble Space Telescope (HST). With a measured mass of 12 ± 3 M ⊕ and a radius of 9.2 ± 0.1 R ⊕, HIP 41378 f has an extremely low bulk density (0.09 ± 0.02 g cm−3). We measure the transit depth with a median precision of 84 ppm in 30 spectrophotometric channels with uniformly sized widths of 0.018 μm. Within this level of precision, the spectrum shows no evidence of absorption from gaseous molecular features between 1.1 and 1.7 μm. Comparing the observed transmission spectrum to a suite of 1D radiative-convective-thermochemical-equilibrium forward models, we rule out clear, low-metallicity atmospheres and find that the data prefer high-metallicity atmospheres or models with an additional opacity source, such as high-altitude hazes and/or circumplanetary rings. We explore the ringed scenario for HIP 41378 f further by jointly fitting the K2 and HST light curves to constrain the properties of putative rings. We also assess the possibility of distinguishing between hazy, ringed, and high-metallicity scenarios at longer wavelengths with the James Webb Space Telescope. HIP 41378 f provides a rare opportunity to probe the atmospheric composition of a cool giant planet spanning the gap in temperature, orbital separation, and stellar irradiation between the solar system giants, directly imaged planets, and the highly irradiated hot Jupiters traditionally studied via transit spectroscopy.
Dynamical Mean Field Studies of Infinite Layer Nickelates: Physics Results and Methodological Implications

This article summarizes recent work on the many-body (beyond density functional theory) electronic structure of layered rare-earth nickelates, both in the context of the materials themselves and in comparison to the high-temperature superconducting (high-T c ) layered copper-oxide compounds. It aims to outline the current state of our understanding of layered nickelates and to show how the analysis of these fascinating materials can shed light on fundamental questions in modern electronic structure theory. A prime focus is determining how the interacting physics defined over a wide energy range can be estimated and “downfolded” into a low energy theory that would describe the relevant degrees of freedom on the ∼ 0.5 eV scale and that could be solved to determine superconducting and spin and charge density wave phase boundaries, temperature dependent resistivities, and dynamical susceptibilities.
Use of a purified reconstituted bilayer matrix in the management of chronic diabetic foot ulcers improves patient outcomes vs standard of care: Results of a prospective randomised controlled multi‐centre clinical trial

Diabetic foot infections continue to be a major challenge for health care delivery systems. Following encouraging results from a pilot study using a novel purified reconstituted bilayer matrix (PRBM) to treat chronic diabetic foot ulcers (DFUs), we designed a prospective, multi‐centre randomised trial comparing outcomes of PRBM at 12 weeks compared with a standard of care (SOC) using a collagen alginate dressing. The primary endpoint was percentage of wounds closed after 12 weeks. Secondary outcomes included assessments of complications, healing time, quality of life, and cost to closure. Forty patients were included in an intent‐to‐treat (ITT) and per‐protocol (PP) analysis, with 39 completing the study protocol (n = 19 PRBM, n = 20 SOC). Wounds treated with PRBM were significantly more likely to close than wounds treated with SOC (ITT: 85% vs 30%, P = .0004, PP: 94% vs 30% P = .00008), healed significantly faster (mean 37 days vs 67 days for SOC, P = .002), and achieved a mean wound area reduction within 12 weeks of 96% vs 8.9% for SOC. No adverse events (AEs) directly related to PRBM treatment were reported. Mean PRBM cost of healing was $1731. Use of PRBM was safe and effective for treatment of chronic DFUs.
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics

Recent years have seen advances in generalization bounds for noisy stochastic algorithms, especially stochastic gradient Langevin dynamics (SGLD) based on stability (Mou et al., 2018; Li et al., 2020) and information theoretic approaches (Xu and Raginsky, 2017; Negrea et al., 2019; Steinke and Zakynthinou, 2020). In this paper, we unify and substantially generalize stability based generalization bounds and make three technical contributions. First, we bound the generalization error in terms of expected (not uniform) stability which arguably leads to quantitatively sharper bounds. Second, as our main contribution, we introduce Exponential Family Langevin Dynamics (EFLD), a substantial generalization of SGLD, which includes noisy versions of Sign-SGD and quantized SGD as special cases. We establish data-dependent expected stability based generalization bounds for any EFLD algorithm with a O(1/n) sample dependence and dependence on gradient discrepancy rather than the norm of gradients, yielding significantly sharper bounds. Third, we establish optimization guarantees for special cases of EFLD. Further, empirical results on benchmarks illustrate that our bounds are non-vacuous, quantitatively sharper than existing bounds, and behave correctly under noisy labels.
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

Cross-Modal Retrieval (CMR) is an important research topic across multimodal computing and information retrieval, which takes one type of data as the query to retrieve relevant data of another type. It has been widely used in many real-world applications. Recently, the vision-language pre-trained models represented by CLIP demon-strate its superiority in learning the visual and textual representations and gain impressive performance on various vision and language related tasks. Although CLIP as well as the previous pre-trained models have shown great performance improvement in the unsupervised CMR ( i.e. , cross-modal matching), the performance and impact of these pre-trained models on the supervised CMR were rarely explored due to the lack of common representation for the multimodal class-level associations. In this paper, we take CLIP as the current representative vision-language pre-trained model to conduct a comprehensive empirical study. We evaluate its performance and impact on the supervised CMR, and attempt to answer several key research questions. To this end, we first propose a novel model CLIP4CMR (CLIP enhanced network for Cross-Modal Retrieval) that employs the pre-trained CLIP as backbone network to perform the supervised CMR. Then by means of the CLIP4CMR framework, we revisit the design of different learning objectives in current CMR methods to provide new insights on model design. Moreover, we investigate the most concerned aspects in applying CMR, including the robustness to modality imbalance and sensitivity to hyper-parameters, to provide new per-spectives for practical applications. Through extensive experiments, we show that CLIP4CMR achieves the SOTA results with prominent improvements on the benchmark datasets Wikipedia, NUS-WIDE, Pascal-Sentence and XmediaNet, and can be used as a fundamental framework to empirically study the key research issues of the supervised CMR, with significant implications for model design and practical considerations 1
Efficient forecasting and uncertainty quantification for large scale account level Monte Carlo models of debt recovery

We consider the problem of forecasting debt recovery from large portfolios of non-performing unsecured consumer loans under management. The state of the art in industry is to use stochastic processes to approximately model payment behaviour of individual customers based on several covariates, including credit scores and payment history. Monte Carlo simulation of these stochastic processes can enable forecasting of the possible returns from portfolios of defaulted debt, and the quantification of uncertainty. Despite the fact that the individual-level models are relatively simple, it is challenging to carry out simulations at the portfolio level because of the very large number of accounts. The accounts are also heterogeneous, with a broad range of values for the collection variances. We aim to solve two main problems: efficient allocation of computational resources in the simulations to estimate the likely collections as precisely as possible, and quantification of the uncertainty in the forecasts. We show that under certain conditions, robust estimators of population-level variance can be constructed by summing over coarse unbiased estimators of the variance of individual accounts. The proposed methods are demonstrated through application to a model which shares key features with those that are used in practice.
Rapid Weakening of Tropical Cyclones in Monsoon Gyres Over the Western North Pacific: A Revisit

The low-level monsoon trough over the western North Pacific (WNP) can evolve into a large cyclonic circulation, which is often termed a monsoon gyre (MG). Previous studies have revealed that tropical cyclones (TCs) embedded in MGs can experience rapid weakening (RW) and such RW might be attributed to the convective activity in the southeastern quadrant of the MG, which could induce asymmetries in a TC’s inner core structure, while the environmental factors, including the sea surface temperature (SST) and vertical wind shear (VWS), were not primary contributors to RW events. In this study, the possible role of large-scale environmental factors in association with the RW of TCs in MGs over the WNP is revisited based on the best-track TC and global reanalysis data during 2000–2018. Results indicate that TCs tend to weaken rapidly when they are embedded in the eastern semicircle of a MG, with the extreme RW events often occurring in the southeastern quadrant of a MG. However, different from previous studies, results from this study demonstrated that lower SST and strong large-scale VWS in the eastern semicircle of a MG are two major environmental factors contributing to the RW of TCs in MGs over the WNP. The different findings in this study from those in previous studies could be partly due to the different methods used to obtain the MG circulations and partly due to the environmental factors being analyzed in different quadrants of MG in this study.
Riemannian Surfaces with Simple Singularities

In this note we discuss the geometry of Riemannian surfaces having a discrete set of singular points. We assume the conformal structure extends through the singularities and the curvature is integrable. Such points are called simple singularities. We first describe them locally and then globally using the notion of (real) divisor. We formulate a Gauss-Bonnet formula and relate it to some asymptotic isoperimetric ratio. We prove a classifications theorem for flat metrics with simple singularities on a compact surface and discuss the Berger–Nirenberg Problem on surfaces with a divisor. We finally discuss the relation with spherical polyhedra. This article is a translation of the paper [15], to be included in the forthcoming book Reshetnyak’s Theory of Subharmonic Metrics edited by François Fillastre and Dmitriy Slytskiy and to be published by Springer and the Centre de recherches mathématiques (CRM) in Montréal. AMS Mathematics Subject Classification: 53.c20, 52.a55
Interdevice agreement in the measurement of physiognomy parameters and frame angles to prescribe progressive addition lenses

ABSTRACT Clinical relevance Ophthalmic lens adaptation requires accurate measurements of physiognomy parameters and frame angles, with a great impact on subject vision, especially when personalised progressive addition lenses are prescribed. Background The aim of this study is to describe interdevice agreement between different methods and traditional methods (frame ruler). Methods The agreement of the interpupillary distance, nasopupillary distance and fitting point height measured with four devices (PD-5, OptiCenter, Visioffice and a frame ruler) and of pantoscopic and frame wrap angles measured with three devices (OptiCenter, Visioffice and Essilor standard ruler) was assessed in 21 healthy volunteers, by a Bland-Altman analysis; mean difference and limits of agreement (LoA) were calculated. Results Frame ruler nasopupillary distance measurements showed limited agreement with PD-5 [−0.38 ± 1.03 (LoA −2.40 to 1.64) and 0.44 ± 1.02 (LoA −1.72 to 2.61)] and Visioffice [0.62 ± 1.24 (LoA −1.81 to 3.05) and −0.16 ± 1.72 (LoA −3.54 to 3.22)] measurements for the right and left eyes, respectively. Poor agreement was found for interpupillary distances (PD-5 [0.21 ± 1.47 (LoA −2.67 to 3.09)], OptiCenter [−0.05 ± 1.16 (LoA −2.32 to 2.22)] and Visioffice [0.46 ± 1.95 (LoA −3.36 to 4.28)]), fitting point height (OptiCenter [−1.27 ± 2.56 (LoA −6.27 to 3.75) and −0.92 ± 2.77 (LoA −6.35 to 4.51)] and Visioffice [−5.88 ± 6.21 (LoA −18.05 to 6.29) and −5.98 ± 6.12 (LoA −17.98 to 6.02)] for the right and left eyes, respectively) and pantoscopic and frame wrap angles (OptiCenter [−4.13 ± 3.75 (LoA −11.48 to 3.22) and −1.09 ± 0.60 (LoA −2.27 to 0.09)] and Visioffice [−6.18 ± 3.53 (LoA −13.10 to 0.74) and −1.93 ± 3.49 (LoA −8.77 to 4.91)], respectively). Conclusions These results suggest that measurements of physiognomy and frame angles are not interchangeable between assessed devices and that these differences could induce lens centration errors with a large impact on progressive addition lens prescriptions.
Universality of cutoff for exclusion with reservoirs

We consider the reversible exclusion process with reservoirs on arbitrary networks. We characterize the spectral gap, mixing time, and mixing window of the process, in terms of certain simple statistics of the underlying network. Among other consequences, we establish a non-conservative analogue of Aldous's spectral gap conjecture, and we show that cutoff occurs if and only if the product condition is satisfied. We illustrate this by providing explicit cutoffs on discrete lattices of arbitrary dimensions and boundary conditions, which substantially generalize recent one-dimensional results. We also obtain cutoff phenomena in relative entropy, Hilbert norm, separation distance and supremum norm. Our proof exploits negative dependence in a novel, simple way to reduce the understanding of the whole process to that of single-site marginals. We believe that this approach will find other applications.
ImageSubject: A Large-scale Dataset for Subject Detection

Main subjects usually exist in the images or videos, as they are the objects that the photographer wants to highlight. Human viewers can easily identify them but algorithms often confuse them with other objects. Detecting the main subjects is an important technique to help machines understand the content of images and videos. We present a new dataset with the goal of training models to understand the layout of the objects and the context of the image then to find the main subjects among them. This is achieved in three aspects. By gathering images from movie shots created by directors with professional shooting skills, we collect the dataset with strong diversity, specifically, it contains 107\,700 images from 21\,540 movie shots. We labeled them with the bounding box labels for two classes: subject and non-subject foreground object. We present a detailed analysis of the dataset and compare the task with saliency detection and object detection. ImageSubject is the first dataset that tries to localize the subject in an image that the photographer wants to highlight. Moreover, we find the transformer-based detection model offers the best result among other popular model architectures. Finally, we discuss the potential applications and conclude with the importance of the dataset.
Canonical parametrizations of metric surfaces of higher topology

We give an alternate proof to the following generalization of the uniformization theorem by Bonk and Kleiner. Any linearly locally connected and Ahlfors 2-regular closed metric surface is quasisymmetrically equivalent to a model surface of the same topology. Moreover, we show that this is also true for surfaces as above with non-empty boundary and that the corresponding map can be chosen in a canonical way. Our proof is based on a local argument involving the existence of quasisymmetric parametrizations for metric discs as shown in in a paper of Lytchak and Wenger.
A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Dynamic parallelism on GPUs allows GPU threads to dynamically launch other GPU threads. It is useful in applications with nested parallelism, particularly where the amount of nested parallelism is irregular and cannot be predicted beforehand. However, prior works have shown that dynamic parallelism may impose a high performance penalty when a large number of small grids are launched. The large number of launches results in high launch latency due to congestion, and the small grid sizes result in hardware underutilization.To address this issue, we propose a compiler framework for optimizing the use of dynamic parallelism in applications with nested parallelism. The framework features three key optimizations: thresholding, coarsening, and aggregation. Thresholding involves launching a grid dynamically only if the number of child threads exceeds some threshold, and serializing the child threads in the parent thread otherwise. Coarsening involves executing the work of multiple thread blocks by a single coarsened block to amortize the common work across them. Aggregation involves combining multiple child grids into a single aggregated grid.Thresholding is sometimes applied manually by programmers in the context of dynamic parallelism. We automate it in the compiler and discuss the challenges associated with doing so. Coarsening is sometimes applied as an optimization in other contexts. We propose to apply coarsening in the context of dynamic parallelism and automate it in the compiler as well. Aggregation has been automated in the compiler by prior work. We enhance aggregation by proposing a new aggregation technique that uses multi-block granularity. We also integrate these three optimizations into an open-source compiler framework to simplify the process of optimizing dynamic parallelism code.Our evaluation shows that our compiler framework improves the performance of applications with nested parallelism by a geometric mean of 43.0× over applications that use dynamic parallelism, 8.7× over applications that do not use dynamic parallelism, and 3.6× over applications that use dynamic parallelism with aggregation alone as proposed in prior work.
Generators for Decompositions of Tensor Products of Indecomposable Modules

Let F be a field of non-zero characteristic p, let G be a cyclic group of order q = pa for some positive integer a, and let U and W be indecomposable FG-modules. We identify a generator for each of the indecomposable components of U ⊗ W in terms of a particular F -basis of U ⊗ W , extending previous work in which each component occurred with multiplicity one. An anonymous reviewer helped us realize that our results are really just a translation of previous results of Iiwa and Iwamatsu to our situation.
Knots and their effect on the tensile strength of lumber: A case study

Abstract When assessing the strength of sawn lumber for use in engineering applications, the sizes and locations of knots are an important consideration. Knots are the most common visual characteristics of lumber, that result from the growth of tree branches. Large individual knots, as well as clusters of distinct knots, are known to have strength-reducing effects. However, industry grading rules that govern knots are informed by subjective judgment to some extent, particularly the spatial interaction of knots and their relationship with lumber strength. This case study reports the results of an experiment that investigated and modeled the strength-reducing effects of knots on a sample of Douglas Fir lumber. Experimental data were obtained by taking scans of lumber surfaces and applying tensile strength testing. The modeling approach presented incorporates all relevant knot information in a Bayesian framework, thereby contributing a more refined way of managing the quality of manufactured lumber.
Perturbation approach in Heisenberg equations for lasers

Nonlinear Heisenberg-Langevin equations are solved analytically by operator Fourier-expansion for the laser in the LED regime. Fluctuations of populations of lasing levels are taken into account as perturbations. Spectra of operator products are calculated as convolutions, preserving Bose commutations for the lasing field operators. It is found that fluctuations of population significantly affect spontaneous and stimulated emissions into the lasing mode, increase the radiation rate, the number of lasing photons and broad the spectrum of a bad cavity thresholdless and the superradiant lasers. The method can be applied to various resonant systems in quantum optics.