Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncertainty of Liver Cirrhosis Diagnosis and Use of Elastography

A case of severe jaundice in a patient with a long history of alcohol abuse led to a questionable diagnosis of liver cirrhosis. To determine its diagnostic utility in the setting of liver disease, elastography was utilized on our patient to confirm the clinically suspected diagnosis of cirrhosis. A 59-year-old male presented to our emergency department (ED) with two days of progressive jaundice and right upper quadrant (RUQ) pain. The patient admitted to drinking > 500 mL of vodka daily for the last seven years, with his last drink on the morning of admission. Physical exam revealed a man in mild acute distress with severe jaundice and an abdomen diffusely tender to palpation. Two spider angiomas were present on the torso along with caput medusae and mild asterixis. Labs revealed aspartate aminotransferase (AST) 408, alanine aminotransferase (ALT) 69, prothrombin time (PT) 16.3, partial thromboplastin time (PTT) 36, total bilirubin 22.6, and direct bilirubin 19.9 mg/dL. While admitted, total bilirubin rose as high as 31.5 mg/dL. Examination showed a Model for End-Stage Liver Disease (MELD) score of 22 and a Maddrey score of 37. Ultrasound revealed moderate hepatosplenomegaly with no signs of pancreatitis. Based on the patient’s history of alcohol abuse paired with physical exam findings and elevated laboratory markers, we were able to diagnose with a high level of suspicion that this patient was suffering from chronic alcoholic liver disease, exacerbated by an acute episode of alcoholic hepatitis, which led to hepatic encephalopathy. Based on these findings, a diagnosis of liver cirrhosis was suspected; however, this diagnosis required further confirmation. We utilized ultrasound elastography to measure the velocity of shear wave transmission in the liver of our patient. A literature review was conducted on the use of elastography for the diagnosis of liver disease, and a significant correlation between the velocity of shear wave transmission and hepatic histological findings was identified. Elastography revealed a mean velocity of shear wave transmission of 1.77 m/s in our patient. This finding is consistent with a Meta-analysis of Histological Data in Viral Hepatitis (METAVIR) score of F = 4, indicating significant fibrosis and confirming the suspected diagnosis of alcohol-induced liver cirrhosis. As a non-invasive and inexpensive diagnostic tool, elastography demonstrates significant potential for clinical utility in patients with liver disease. Clinicians may benefit from the use of elastography in diagnosis, while patients may receive both therapeutic and prognostic benefits secondary to its use. In similar cases with clinical uncertainty, elastography can reliably identify the presence of fibrous tissue in the liver without tissue biopsy, thus aiding in clinical diagnoses and enabling the use of optimal therapeutic regimens for future patients.
Modulated and Rotating Turbulent Plane Couette Flow: Direct numerical simulations

Direct numerical simulations of turbulent Rotating Plane Couette Flow (RPCF) with a periodically modulated plate velocity are conducted to study the effect of modulated forcing on turbulent shear flows. The time averaged shear Reynolds number is fixed to ReS = 3 · 10, which results in a frictional Reynolds number of approximately Reτ ≈ 400. The modulating frequency is varied in the range Wo ∈ (20, 200), while the modulating amplitude is kept fixed at 10% of the shear velocity except to demonstrate that varying this parameter changes little. The resulting shear at the plates are found to be independent of the forcing frequency, and equal to the non-modulated baseline. For the non-rotating simulations, two clear flow regions can be seen: a near wall region that follows Stokes’ theoretical solution, and a bulk region that behaves similar to Stokes’ solutions but with an increased effective viscosity. For high driving frequencies, the amplitude response follows the scaling laws for modulated turbulence of von der Heydt et al. (Physical Review E 67, 046308 (2003)). Cyclonic rotation is not found to modify the system’s behaviour in a substantial way, but anti-cyclonic rotation significantly changes the system’s response to periodic forcing. We find that the persistent axial inhomogeneities introduced by mild anti-cyclonic rotation make it impossible to measure the propagation of the modulation adequately, while stronger anti-cyclonic rotation creates regions where the modulation travels instantaneously.
Numerical evidence of exponential mixing by alternating shear flows

We performed a numerical study of the efficiency of mixing by alternating horizontal and vertical shear ``wedge'' flows on the two-dimensional torus. Our results suggest that except in cases where each individual flow is applied for only a short time, these flows produce exponentially fast mixing. The observed mixing rates are higher when the individual flow times are shorter (but not too short), and randomizing either the flow times or phase shifts of the flows does not appear to enhance mixing (again when the flow times are not too short). In fact, the latter surprisingly seems to inhibit it slightly.
Exponent in Smoothing the Max-Relative Entropy and Its Application to Quantum Privacy Amplification

The max-relative entropy together with its smoothed version is a basic tool in quantum information theory. In this paper, we derive the exact exponent for the decay of the small modiﬁcation of the quantum state in smoothing the max-relative entropy. We then apply this result to the problem of privacy ampliﬁcation against quantum side information, and we obtain an upper bound for the exponent of the decreasing of the insecurity, measured us-ing either puriﬁed distance or relative entropy. Our upper bound complements the earlier lower bound established by Hayashi, and the two bounds match when the rate of randomness extraction is above a critical value. Thus, for the case of high rate, we have determined the exact security exponent. Following this, we give examples and show that in the low-rate case, neither the upper bound nor the lower bound is tight in general. This exhibits a picture similar to that of the error exponent in channel coding.
Asymptotics of transverse momentum broadening in dense QCD media

We study the asymptotic behaviour of the transverse momentum broadening distribution of an energetic quark or gluon propagating through dense QCD matter, in the large system size LL limit, taking into account radiative corrections in the double logarithmic approximation. Thanks to a connection between the evolution of the jet quenching parameter \hat{q}q̂ and the formation of traveling wave fronts in nonlinear physics, we obtain a formula for the LL dependence of the characteristic transverse momentum scale Q_sQs of the distribution valid up to terms of order 1/\ln(L)1/ln(L). We briefly discuss the physical implications of this formula for jet quenching and small-xx phenomenology.
Selective recovery of critical materials in supercritical water desalination

Supercritical water desalination (SCWD) is an alternative zero-liquid discharge desalination technique that can overcome many technical and environmental challenges in common desalination processes. Our recent technoeconomic analyses on the process integration and intensification of an SCWD process suggest that SCWD can be an economically competitive zero-liquid discharge desalination technique for highly concentrated brines. In addition to these attractive features, this work explores the possibility of utilizing the SCWD process for the selective recovery of industrially essential materials as co-products. Model brines containing sodium chloride, neodymium chloride, and other sodium-containing salts, are examined as model feeds from 25 to 450 ◦C at 25 MPa. The sodium contents in the effluent were not sensitive to the presence other salts, but that of neodymium was. When sodium acetate was added, water-insoluble precipitates were obtained. The characterization of these deposits using gas pycnometer, FT-IR, SEM/EDS, and XRD indicates that the precipitates mainly contain neodymium hydroxide and some
ReSkin: versatile, replaceable, lasting tactile skins

Soft sensors have continued growing interest in robotics, due to their ability to enable both passive conformal contact from the material properties and active contact data from the sensor properties. However, the same properties of conformal contact result in faster deterioration of soft sensors and larger variations in their response characteristics over time and across samples, inhibiting their ability to be long-lasting and replaceable. ReSkin is a tactile soft sensor that leverages machine learning and magnetic sensing to offer a low-cost, diverse and compact solution for long-term use. Magnetic sensing separates the electronic circuitry from the passive interface, making it easier to replace interfaces as they wear out while allowing for a wide variety of form factors. Machine learning allows us to learn sensor response models that are robust to variations across fabrication and time, and our self-supervised learning algorithm enables finer performance enhancement with small, inexpensive data collection procedures. We believe that ReSkin opens the door to more versatile, scalable and inexpensive tactile sensation modules than existing alternatives.
Inferring the Thermal History of the Intergalactic Medium from the Properties of the Hydrogen and Helium Lyα Forest

The filamentary network of intergalactic medium (IGM) gas that gives origin to the Lyα forest in the spectra of distant quasars encodes information on the physics of structure formation and the early thermodynamics of diffuse baryonic material. Here we use a massive suite of more than 400 high-resolution cosmological hydrodynamical simulations run with the Graphics Processing Unit–accelerated code Cholla to study the IGM at high spatial resolution maintained over the entire computational volume. The simulations capture a wide range of possible IGM thermal histories by varying the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei. A statistical comparison of synthetic spectra with the observed 1D flux power spectra of hydrogen at redshifts 2.2 ≤ z ≤ 5.0 and with the helium Lyα opacity at redshifts 2.4 < z < 2.9 tightly constrains the photoionization and photoheating history of the IGM. By leveraging the constraining power of the available Lyα forest data to break model degeneracies, we find that the IGM experienced two main reheating events over 1.2 Gyr of cosmic time. For our best-fit model, hydrogen reionization completes by z R ≈ 6.0 with a first IGM temperature peak of T 0 ≃ 1.3 × 104 K and is followed by the reionization of He ii that completes by z R ≈ 3.0 and yields a second temperature peak of T 0 ≃ 1.4 × 104 K. We discuss how our results can be used to obtain information on the timing and the sources of hydrogen and helium reionization.
Multi-differential studies to explore strangeness enhancement in pp with ALICE at the LHC

The study of energy and multiplicity dependence of strange hadron production in proton-proton collisions provides a powerful tool to understand similarities and differences between small and large collision systems. In order to better understand the origin of strangeness enhancement in pp new multi-differential analyses have been performed. The first separates the contribution of soft and hard processes, such as jets, to strange hadron production through two-particle correlation techniques. The second exploits the concept of the effective energy available for particle production in the event, which is estimated by an anti-correlation with the energy deposited in ALICE's Zero Degree Calorimeters. The results indicate that strangeness production emerges from the growth of the underlying event and confirm it is related to the final state multiplicity.
The spatial structure of electrostatically forced Faraday waves

Abstract The instability of the interface between a dielectric and a conducting liquid, excited by a spatially homogeneous interface-normal time-periodic electric field, is studied based on experiments and theory. Special attention is paid to the spatial structure of the excited Faraday waves. The dominant modes of the instability are extracted using high-speed imaging in combination with an algorithm evaluating light refraction at the liquid–liquid interface. The influence of the liquid viscosities on the critical voltage corresponding to the onset of instability and on the dominant wavelength is studied. Overall, good agreement with theoretical predictions that are based on viscous fluids in an infinite domain is demonstrated. Depending on the relative influence of the domain boundary, the patterns exhibit either discrete modes corresponding to surface harmonics or boundary-independent patterns. The agreement between experiments and theory confirms that the electrostatically forced Faraday instability is sufficiently well understood, which may pave the way to control electrostatically driven instabilities. Last but not least, the analogies to classical Faraday instabilities may enable new approaches to study effects that have so far only been observed for mechanical forcing.
The role of the underlying event in the Λc
 + enhancement in high-energy pp collisions

We study the enhanced production of charmed baryons relative to charmed mesons in proton–proton collisions at LHC energies. Utilizing PYTHIA 8 simulations with enhanced color-reconnection we propose methods based on the comparative use of several event-activity classiﬁers to identify the source of the charmed-baryon enhancement. We conclude that in this enhanced color-reconnection scenario the excess Λc + production is primarily linked to the underlying event activity and not to the production of high-momentum jets.
Simultaneous angiotensin receptor blockade and glucagon‐like peptide‐1 receptor activation ameliorate albuminuria in obese insulin‐resistant rats

Insulin resistance increases renal oxidant production by upregulating NADPH oxidase 4 (Nox4) expression contributing to oxidative damage and ultimately albuminuria. Inhibition of the renin‐angiotensin system (RAS) and activation of glucagon‐like peptide‐1 (GLP‐1) receptor signalling may reverse this effect. However, whether angiotensin receptor type 1 (AT1) blockade and GLP‐1 receptor activation improve oxidative damage and albuminuria through different mechanisms is not known. Using insulin‐resistant Otsuka Long‐Evans Tokushima Fatty (OLETF) rats, we tested the hypothesis that simultaneous blockade of AT1 and activation of GLP‐1r additively decrease oxidative damage and urinary albumin excretion (UalbV) in the following groups: (a) untreated, lean LETO (n = 7), (b) untreated, obese OLETF (n = 9), (c) OLETF + angiotensin receptor blocker (ARB; 10 mg olmesartan/kg/d; n = 9), (d) OLETF + GLP‐1 mimetic (EXE; 10 µg exenatide/kg/d; n = 7) and (e) OLETF + ARB +exenatide (Combo; n = 6). Mean kidney Nox4 protein expression and nitrotyrosine (NT) levels were 30% and 46% greater, respectively, in OLETF compared with LETO. Conversely, Nox4 protein expression and NT were reduced to LETO levels in ARB and EXE, and Combo reduced Nox4, NT and 4‐hydroxy‐2‐nonenal levels by 21%, 27% and 27%, respectively. At baseline, UalbV was nearly double in OLETF compared with LETO and increased to nearly 10‐fold greater levels by the end of the study. Whereas ARB (45%) and EXE (55%) individually reduced UalbV, the combination completely ameliorated the albuminuria. Collectively, these data suggest that AT1 blockade and GLP‐1 receptor activation reduce renal oxidative damage similarly during insulin resistance, whereas targeting both signalling pathways provides added benefit in restoring and/or further ameliorating albuminuria in a model of diet‐induced obesity.
Ages and Masses of Star Clusters in M33: a Multiwavelength Study

We combine archival images for the nearby galaxy M33 (Triangulum Galaxy) from the ultraviolet (UV) to the infrared to derive ages, masses, and extinctions for the young star cluster population, and compare our physical parameters with published ones. Our goal is to test the robustness of clusters ages and masses, and possibly improve on existing ones both by expanding the wavelength range of the spectral-energy distribution (SED) fits and by using more recent population synthesis models. The rationale for this experiment is to verify the sensitivity of the clusters physical parameters to observational setups and model choices that span those commonly found in the literature. We derive the physical parameters of 137 clusters, using SEDs measured in eight UV-to-I bands, including Hα, from GALEX and ground-based images. We also add the 24 μm image from the Spitzer Space Telescope to help break some age degeneracies. We find that our derived cluster ages show significant differences with earlier determinations, while the masses remain relatively insensitive to the fitting approach adopted. We also highlight an already known difficulty in recovering old, low-extinction clusters, as SED-fitting codes tend to prefer younger, higher extinction solutions when the extinction is a free parameter. We publish updated ages, masses, and extinctions, with uncertainties for all sample star clusters, together with their photometry. Given the proximity of M33, this represents an important population to secure for the study of star formation and cluster evolution in spirals.
AdvCodeMix: Adversarial Attack on Code-Mixed Data

Research on adversarial attacks are becoming widely popular in the recent years. One of the unexplored areas where prior research is lacking is the effect of adversarial attacks on code-mixed data. Therefore, in the present work, we have explained the first generalized framework on text perturbation to attack code-mixed classification models in a black-box setting. We rely on various perturbation techniques that preserve the semantic structures of the sentences and also obscure the attacks from the perception of a human user. The present methodology leverages the importance of a token to decide where to attack by employing various perturbation strategies. We test our strategies on various sentiment classification models trained on Bengali-English and Hindi-English code-mixed datasets, and reduce their F1-scores by nearly 51% and 53% respectively, which can be further reduced if a larger number of tokens are perturbed in a given sentence.
STORM+: Fully Adaptive SGD with Momentum for Nonconvex Optimization

In this work we investigate stochastic non-convex optimization problems where the objective is an expectation over smooth loss functions, and the goal is to find an approximate stationary point. The most popular approach to handling such problems is variance reduction techniques, which are also known to obtain tight convergence rates, matching the lower bounds in this case. Nevertheless, these techniques require a careful maintenance of anchor points in conjunction with appropriately selected"mega-batchsizes". This leads to a challenging hyperparameter tuning problem, that weakens their practicality. Recently, [Cutkosky and Orabona, 2019] have shown that one can employ recursive momentum in order to avoid the use of anchor points and large batchsizes, and still obtain the optimal rate for this setting. Yet, their method called STORM crucially relies on the knowledge of the smoothness, as well a bound on the gradient norms. In this work we propose STORM+, a new method that is completely parameter-free, does not require large batch-sizes, and obtains the optimal $O(1/T^{1/3})$ rate for finding an approximate stationary point. Our work builds on the STORM algorithm, in conjunction with a novel approach to adaptively set the learning rate and momentum parameters.
Gács-Kučera's Theorem Revisited by Levin

Leonid Levin [12] published a new (and very nice) proof of G´acs–Kuˇcera’s theorem that occupies only a few lines when presented in his style. We try to explain more details and discuss the connection of this proof with image randomness theorems, making explicit some result (see Proposition 4) that is implicit in [12]
Speech Denoising Using Only Single Noisy Audio Samples

In this paper, we propose a novel Single Noisy Audio De-noising Framework (SNA-DF) for speech denoising using only single noisy audio samples, which overcomes the limitation of constructing either noisy-clean training pairs or multiple independent noisy audio samples. The proposed SNA-DF contains two modules: training audio pairs generated module and audio denoising module. The first module adopts a random audio sub-sampler on single noisy audio samples for the generation of training audio pairs. The sub-sampled training audio pairs are then fed into the audio denoising module, which employs a deep complex U-Net incorporating a complex two-stage transformer (cTSTM) to extract both magnitude and phase information for taking full advantage of the complex features of single noisy audios. Experimental re-sults show that the proposed SNA-DF not only eliminates the high dependence on clean targets of traditional audio de-noising methods, but also outperforms the methods using multiple noisy audio samples.
Productivity Convergence in Manufacturing: A Hierarchical Panel Data Approach

Despite its paramount importance in the empirical growth literature, productivity convergence analysis has three problems that have yet to be resolved: (1) little attempt has been made to explore the hierarchical structure of industry-level datasets; (2) industry-level technology heterogeneity has largely been ignored; and (3) cross-sectional dependence has rarely been allowed for. This paper aims to address these three problems within a hierarchical panel data framework. We propose an estimation procedure and then derive the corresponding asymptotic theory. Finally, we apply the framework to a dataset of 23 manufacturing industries from a wide range of countries over the period 1963-2018. Our results show that both the manufacturing industry as a whole and individual manufacturing industries at the ISIC two-digit level exhibit strong conditional convergence in labour productivity, but not unconditional convergence. In addition, our results show that both global and industry-specific shocks are important in explaining the convergence behaviours of the manufacturing industries.
Bounds for the chi-square approximation of Friedman’s statistic by Stein’s method

Friedman's chi-square test is a non-parametric statistical test for $r\geq2$ treatments across $n\ge1$ trials to assess the null hypothesis that there is no treatment effect. We use Stein's method with an exchangeable pair coupling to derive an explicit bound on the distance between the distribution of Friedman's statistic and its limiting chi-square distribution, measured using smooth test functions. Our bound is of the optimal order $n^{-1}$, and also has an optimal dependence on the parameter $r$, in that the bound tends to zero if and only if $r/n\rightarrow0$. From this bound, we deduce a Kolmogorov distance bound that decays to zero under the weaker condition $r^{1/2}/n\rightarrow0$.