Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward de Sitter space from ten dimensions

Using a 10D lift of non-perturbative volume stabilization in type IIB string theory we study the limitations for obtaining de Sitter vacua. Based on this we find that the simplest KKLT vacua with a single Kahler modulus stabilized by a gaugino condensate cannot be uplifted to de Sitter. Rather, the uplift flattens out due to stronger backreaction on the volume modulus than has previously been anticipated, resulting in vacua which are meta-stable and SUSY breaking, but that are always AdS. However, we also show that setups such as racetrack stabilization can avoid this issue. In these models it is possible to obtain supersymmetric AdS vacua with a cosmological constant that can be tuned to zero while retaining finite moduli stabilization. In this regime, it seems that de Sitter uplifts are possible with negligible backreaction on the internal volume. We exhibit this behavior also from the 10D perspective.
Ticagrelor inverse agonist activity at the P2Y12 receptor is non‐reversible versus its endogenous agonist adenosine 5´‐diphosphate

Ticagrelor is labelled as a reversible, direct‐acting platelet P2Y12 receptor (P2Y12R) antagonist that is indicated clinically for the prevention of thrombotic events in patients with acute coronary syndrome (ACS). As with many antiplatelet drugs, ticagrelor therapy increases bleeding risk in patients, which may require platelet transfusion in emergency situations. The aim of this study was to further examine the reversibility of ticagrelor at the P2Y12R.
Spatially Varying Prior Learning for Blind Hyperspectral Image Fusion

In recent years, researchers have become more interested in hyperspectral image fusion (HIF) as a potential alternative to expensive high-resolution hyperspectral imaging systems, which aims to recover a high-resolution hyperspectral image (HR-HSI) from two images obtained from low-resolution hyperspectral (LR-HSI) and high-spatial-resolution multispectral (HR-MSI). It is generally assumed that degeneration in both the spatial and spectral domains is known in traditional model-based methods or that there existed paired HR-LR training data in deep learning-based methods. However, such an assumption is often invalid in practice. Furthermore, most existing works, either introducing hand-crafted priors or treating HIF as a black-box problem, cannot take full advantage of the physical model. To address those issues, we propose a deep blind HIF method by unfolding model-based maximum a posterior (MAP) estimation into a network implementation in this paper. Our method works with a Laplace distribution (LD) prior that does not need paired training data. Moreover, we have developed an observation module to directly learn degeneration in the spatial domain from LR-HSI data, addressing the challenge of spatially-varying degradation. We also propose to learn the uncertainty (mean and variance) of LD models using a novel Swin-Transformer-based denoiser and to estimate the variance of degraded images from residual errors (rather than treating them as global scalars). All parameters of the MAP estimation algorithm and the observation module can be jointly optimized through end-to-end training. Extensive experiments on both synthetic and real datasets show that the proposed method outperforms existing competing methods in terms of both objective evaluation indexes and visual qualities.
Asymptotic stability of stationary solutions to the compressible bipolar Navier–Stokes–Poisson equations

In this paper, we consider the compressible bipolar Navier–Stokes–Poisson equations with a non‐flat doping profile in three‐dimensional space. The existence and uniqueness of the non‐constant stationary solutions are established when the doping profile is a small perturbation of a positive constant state. Then under the smallness assumption of the initial perturbation, we show the global existence of smooth solutions to the Cauchy problem near the stationary state. Finally, the convergence rates are obtained by combining the energy estimates for the nonlinear system and the L2‐decay estimates for the linearized equations. Copyright © 2017 John Wiley & Sons, Ltd.
Opioid receptor antagonism and neural response to monetary rewards: Pilot studies in light and heavy alcohol users

Alcohol use disorder (AUD) is a prevalent condition associated with high degree of comorbidity and mortality. Among the few approved pharmacotherapies for AUD, two involve opioid receptor antagonism. Naltrexone and nalmefene are thought to act via opioid receptor blockage to reduce neural response to alcohol and drug-associated cues and consumption, but there have been limited efforts to characterize these effects in humans. In these studies, we sought to test the magnitude of opioid antagonism effects on neural response to monetary rewards in two groups: light drinkers (for the naltrexone study) and heavy drinkers (for the nalmefene study). We conducted double-blind, randomized, crossover pilot studies of reward activation in the brain following acute administration of opioid antagonist and placebo in 11 light and 9 heavy alcohol users. We used a monetary incentive delay task during functional MRI. We found a main effect of cue type on BOLD activation in the nucleus accumbens, demonstrating a neural reward response. The effect of opioid antagonism, relative to placebo, was small and nonsignificant for reward activation in the accumbens for both light and heavy alcohol users. Based on the results of two pilot studies, opioid antagonist medications do not appear to decrease neural activation to monetary rewards in the nucleus accumbens relative to placebo.
Long-term influenza antibodies profiles in previously vaccinated and non-vaccinated adults

ABSTRACT The aim of this work is to describe the dynamics of influenza antibodies after vaccination in adults. We conducted a case-cohort serological study in the automobile manufacturing plants of the Renault España S.A. group in Valladolid and Palencia (Spain), including 550 workers (66.9%) previously vaccinated against influenza (group V), and 272 (33.1%) never vaccinated (group NV). A pre-vaccination serum sample was collected, another after 30–40 days and another after 6 months. The dynamics of antibodies were analyzed. A lower seroprotection of NV before vaccination was observed, but an antibody response between 2 and 4 times higher than in V was assessed. After 6 months, antibodies declined in both groups until equalize. Antibodies titers decrease with age, and no differences were found among underlying pathologies. Adults never vaccinated against influenza had lower seroprotection than those previously vaccinated, but influenza vaccination produces a more intense serological response in them, acquiring significantly higher antibody titers than those previously vaccinated. The antibodies, although in lower titers, persist and equalize among both groups at least 6 months after vaccination, which allows the individual to be protected during the entire circulation of the influenza virus in the same season.
Clinical history and incidental abnormality detection in endodontic cone beam computed tomography

Abstract. Purpose To assess the effect of clinical history on incidental abnormality detection, false positive (FP) marks, and diagnostic confidence in endodontic cone beam computed tomography (CBCT) imaging. Approach A reader performance study using a free-response, factorial study design was undertaken, which accounted for changes in the independent variables: native case type, native case severity, reader type, and reading modality. Twenty-three readers interpreted 26 cases (18 diseased and 8 non-diseased) twice, once with and once without access to clinical history. Each case had at least one incidental abnormality that was not a native endodontic finding. Lesion localization (LL), non-localizations (FPs), and diagnostic confidence (rating 2, 3, or 4: lowest, middle, and highest, respectively) of incidental abnormalities were analyzed. Results Clinical history increased the detection of incidental abnormalities in non-diseased subtle cases (76 versus 59, p = 0.04). Reader experience and monthly CBCT reading volume did not affect incidental abnormality detection. FPs were neither affected by clinical history nor reader characteristics. The highest confidence rating was most often used in each case type when clinical history was available. For this rating, history had significantly greater LLs in subtle diseased (53 versus 41, p = 0.03) and non-diseased images (53 versus 33, p = 0.02). Conclusions Clinical history improved the detection of incidental endodontic abnormalities in non-diseased subtle CBCT images and did not affect the number of FP marks. Reader confidence in correctly identified abnormalities was higher with clinical history when disease and non-disease were subtle but was not associated with an improvement in diagnostic performance.
Nutrition Education Improves Intakes of Protein, Polyunsaturated Fatty Acids, and Vitamins C and E in Community-Dwelling Older Adults

Abstract This study investigated the effect of nutrition education program on protein and nutrient intake, physical performance, and health-related quality of life (HRQoL) in community-dwelling older adults (≥65 years). The participants were randomized in clusters to intervention (IG, n = 51) and control (CG, n = 45) groups. Those in IG took part in the Eating for Strong Aging education program consisting of nutrition education in peer groups, written materials, and personal advice. Nutrient intake was assessed with 3-day food diaries, physical performance with Short Physical Performance Battery (SPPB) and HRQoL with 15-D-QoL instrument. Total of 89 participants completed the study. The mean age was 76 years (IG) and 74 years (CG). At three months, the mean change in protein intake was 0.10 g/adjusted bodyweight (ABW) kg/d in the IG, and −0.07 g/ABW kg/d in the CG (p = 0.024). Intakes of polyunsaturated fatty acids and vitamins C and E increased in the IG compared to the CG (p < 0.05). Changes in SPPB or total HRQoL scores between the IG and the CG did not differ. HRQoL dimension mobility improved in the IG compared to the CG (p = 0.035). In conclusion, the Eating for Strong Aging educational program improved nutrition and may be beneficial for mobility-related QoL.
Mutual dimension, data processing inequalities, and randomness

This dissertation makes progress in the area of constructive dimension, an effectivization of classical Hausdorff dimension. Using constructive dimension, one may assign a non-zero number to the dimension of individual sequences and individual points in Euclidean space. The primary objective of this dissertation is to develop a framework for mutual dimension, i.e., the density of algorithmic mutual information between two infinite objects, that has similar properties as those of classical Shannon mutual information. Chapter 1 presents a brief history of the development of constructive dimension along with its relationships to algorithmic information theory, algorithmic randomness, and classical Hausdorff dimension. Some applications of this field are discussed and an overview of each subsequent chapter is provided. Chapter 2 defines and analyzes the mutual algorithmic information between two points x ∈ R and y ∈ R at a given precision r ∈ N. In fact, we describe two plausible definitions for this quantity, Ir(x : y) and Jr(x : y), and show that they are closely related. In order to do this, we prove and make use of a generalization of Levin’s coding theorem. Chapter 3 defines the lower and upper mutual dimensions between two points in Euclidean space and presents results on its basic properties. A large portion of this chapter is dedicated to studying data processing inequalities for points in Euclidean space. Generally speaking, a data processing inequality says that the amount of information between two objects cannot be significantly increased when one of the objects is processed by a particular type of transformation. We show that it is possible to derive several kinds of
Sample properties of random fields III : Differentiability

This is the third in a series of three papers on sample properties of random fields (cf. also [6, 7]), and in the present paper the question of the existence of a sample differentiable modification of a given random field indexed by an open connected subset of R, m ∈ N, is discussed. In contrast to the question under which conditions a given stochastic process has a continuous modification, the problem of sample differentiable modifications has not received much attention in the standard literature. In view of the path properties of Brownian motion and the stochastic processes derived thereof this seems also very natural. On the other hand, for instance for random fields which are defined as solutions of space-time stochastic partial differential equations this question seems more meaningful, because such random fields often have samples which behave in the time direction similarly as the paths of a Brownian motion, but in the space direction the samples may be smooth if their space correlation is appropriate. For stochastic processes differentiability of the sample paths has been discussed in [5] and in [1], by two quite different methods. (In [4] Loève has announced without proof a result concerning the sample differentiability of random fields. In his book [5], which appeared later, Loève unfortunately only treats the case of a one-dimensional parameter domain, i.e., of stochastic processes.) The construction of sample differentiable modification of a stochastic processes in [1] uses polygonal approximation of the paths and a regularization argument. It is rather difficult to generalize this method to the higher dimensional case. The method of Loève in [5] is quite ingenious: Loève develops first a differential and integral calculus of stochastic processes in quadratic mean (QM) sense, including a version of the
Multivariable continuous fixed-time second-order sliding mode control: design and convergence time estimation

The contribution of this study is threefold. First, a vector (multivariable) super-twisting algorithm is designed to provide a direct extension of the conventional scalar super-twisting control, without any additional terms. An upper estimate of its convergence (settling) time is calculated. Second, a fixed-time convergent continuous vector super-twisting-like algorithm is presented and its fixed convergence time is estimated. Third, an estimate of the finite convergence time of the scalar super-twisting algorithm is obtained as a particular case of the vector super-twisting one, which occurs to be less conservative than the one derived specially for the scalar case. The proposed theoretical concepts are illustrated in a number of scalar and multivariable examples.
As Frequent as Polyglutamine Spinocerebellar Ataxias: SCA27B in a Large German Autosomal Dominant Ataxia Cohort

Intronic GAA repeat expansions in the ﬁ broblast growth factor 14 gene ( FGF14 ) have recently been shown to be a common cause of adult-onset degenerative ataxia (spi-nocerebellar ataxia 27B [SCA27B], MIM: 620174), 1,2 but frequencies in strictly consecutive SCA cohorts are unknown. Here we studied the relative frequencies of SCA27B in a cohort of genetically undetermined autosomal dominant cerebellar ataxia (ADCAs) and relative to other forms of genetically con ﬁ rmed SCAs.
Sociocultural and Economic Disparities in Physical Therapy Utilization Among Insured Older Adults With Rheumatoid Arthritis

Objective To examine influences of sociocultural and economic determinants on physical therapy (PT) utilization for older adults with rheumatoid arthritis (RA). Methods In these annual cross-sectional analyses between 2012 and 2016, we accessed Medicare enrollment data and fee-for-service claims. The cohort included Medicare beneficiaries with RA based on 3 diagnosis codes or 2 codes plus a disease-modifying antirheumatic drug medication claim. We defined race and ethnicity and dual Medicare/Medicaid coverage (proxy for income) using enrollment data. Adults with a Current Procedural Terminology code for PT evaluation were classified as utilizing PT services. Associations between race and ethnicity and dual coverage and PT utilization were estimated with logistic regression analyses. Potential interactions between race and ethnicity status and dual coverage were tested using interaction terms. Results Of 106,470 adults with RA (75.1% female; aged 75.8 [SD 7.3] years; 83.9% identified as non-Hispanic White, 8.8% as non-Hispanic Black, 7.2% as Hispanic), 9.6-12.5% used PT in a given year. Non-Hispanic Black (adjusted odds ratio [aOR] 0.77, 95% CI 0.73-0.82) and Hispanic (aOR 0.92, 95% CI 0.87-0.98) individuals had lower odds of PT utilization than non-Hispanic White individuals. Adults with dual coverage (lower income) had lower odds of utilization than adults with Medicare only (aOR 0.44, 95% CI 0.43-0.46). There were no significant interactions between race and ethnicity status and dual coverage on utilization. Conclusion We found sociocultural and economic disparities in PT utilization in older adults with RA. We must identify and address the underlying factors that influence these disparities in order to mitigate them.
Lightweight Pixel Difference Networks for Efficient Visual Representation Learning

Recently, there have been tremendous efforts in developing lightweight Deep Neural Networks (DNNs) with satisfactory accuracy, which can enable the ubiquitous deployment of DNNs in edge devices. The core challenge of developing compact and efficient DNNs lies in how to balance the competing goals of achieving high accuracy and high efficiency. In this paper we propose two novel types of convolutions, dubbed <italic>Pixel Difference Convolution (PDC) and Binary PDC (Bi-PDC)</italic> which enjoy the following benefits: capturing higher-order local differential information, computationally efficient, and able to be integrated with existing DNNs. With PDC and Bi-PDC, we further present two lightweight deep networks named <italic>Pixel Difference Networks (PiDiNet)</italic> and <italic>Binary PiDiNet (Bi-PiDiNet)</italic> respectively to learn highly efficient yet more accurate representations for visual tasks including edge detection and object recognition. Extensive experiments on popular datasets (BSDS500, ImageNet, LFW, YTF, etc.) show that PiDiNet and Bi-PiDiNet achieve the best accuracy-efficiency trade-off. For edge detection, PiDiNet is the first network that can be trained without ImageNet, and can achieve the human-level performance on BSDS500 at 100 FPS and with <inline-formula><tex-math notation="LaTeX">$< $</tex-math><alternatives><mml:math><mml:mo><</mml:mo></mml:math><inline-graphic xlink:href="liu-ieq1-3300513.gif"/></alternatives></inline-formula>1 M parameters. For object recognition, among existing Binary DNNs, Bi-PiDiNet achieves the best accuracy and a nearly <inline-formula><tex-math notation="LaTeX">$2\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>2</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="liu-ieq2-3300513.gif"/></alternatives></inline-formula> reduction of computational cost on ResNet18.
Application of Ion Mobility Spectrometry–Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples

Exposure characterization of crude oils, especially in time‐sensitive circumstances such as spills and disasters, is a well‐known analytical chemistry challenge. Gas chromatography–mass spectrometry is commonly used for “fingerprinting” and origin tracing in oil spills; however, this method is both time‐consuming and lacks the resolving power to separate co‐eluting compounds. Recent advances in methodologies to analyze petroleum substances using high‐resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry–mass spectrometry (IMS–MS), is especially promising because it is both rapid and high‐throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS–MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS–MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non‐US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS–MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS–MS was used for unsupervised hierarchical clustering, as well as machine learning–based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS–MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336–2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
A technological approach to “Reaching the Unreached” – Leveraging teleophthalmology services in Rural Gujarat

Purpose: Early detection of sight-threatening disorders by technological applications like teleophthalmology and prompt treatment can help decrease visual impairment. This study evaluated the role of teleophthalmology in underserved rural areas along with cost-saving estimates for the end user. Methods: A prospective, observational, cross-sectional hospital-based study was conducted over 3 months. First 1000 teleconsultations were included. None of the patients denied providing informed consent. The patients were consulted at the eight vision centers and three satellite centers of the hospital in the nearby rural and tribal regions closer to their residential places. These vision and satellite centers were connected to the base hospital like a hub and spoke model with a teleophthalmology network. Results: Cataract (n = 301, 30.1%) and refractive error (n = 290, 29%) were the most common diagnosis. 42.1% of patients were referred to base hospital for further evaluation. Thus, a total of 57.9% of patients were not required to visit the base hospital for initial consultation, saving time and money. Furthermore, 15.1% of patients were provided medical treatment at the vision center and satellite center, which helped in making teleophthalmology cost-saving for the patients. An average of Rs. 621/- were saved per patient for the community in our study. Conclusion: Networked teleophthalmology model can be an affordable and feasible tool for providing eye care delivery services in rural and tribal regions of Gujarat and the whole country, especially for the end user. Thus, it may be a workable model in ophthalmology practice with substantial cost saving to the community.