Miracle-dz/UniFAR-FTUs huggingface dataset:
A Central Slip Injury in a Professional Basketball Player

Hand injuries are extremely prevalent in sports such as ball sports. Delayed diagnosis or improperly managed injuries have the potential to prolong the athlete’s return to the competition and permanently damage their abilities. We report the case of a 35-year-old male professional basketball player who presented to a chiropractor with pain and swelling of the right fifth finger two days after a basketball game. The injury occurred when a player passed the basketball and the ball hit his fifth finger "head-on". Examination revealed enlargement of the middle joint of the right fifth finger and a boutonniere deformity. He was diagnosed with a central slip injury using magnetic resonance imaging (MRI). Since there are no standard treatment guidelines for central slip injuries, multi-model chiropractic therapy was applied to the injury and adjacent sites. The patient returned to the game by the end of the third week and fully recovered within six weeks. Chiropractors must understand how to best guide athletes’ clinical management of these injuries, given the inherent need for immediate and complete recovery.
Multimodal representation learning for predicting molecule–disease relations

Abstract Motivation Predicting molecule–disease indications and side effects is important for drug development and pharmacovigilance. Comprehensively mining molecule–molecule, molecule–disease and disease–disease semantic dependencies can potentially improve prediction performance. Methods We introduce a Multi-Modal REpresentation Mapping Approach to Predicting molecular-disease relations (M2REMAP) by incorporating clinical semantics learned from electronic health records (EHR) of 12.6 million patients. Specifically, M2REMAP first learns a multimodal molecule representation that synthesizes chemical property and clinical semantic information by mapping molecule chemicals via a deep neural network onto the clinical semantic embedding space shared by drugs, diseases and other common clinical concepts. To infer molecule–disease relations, M2REMAP combines multimodal molecule representation and disease semantic embedding to jointly infer indications and side effects. Results We extensively evaluate M2REMAP on molecule indications, side effects and interactions. Results show that incorporating EHR embeddings improves performance significantly, for example, attaining an improvement over the baseline models by 23.6% in PRC-AUC on indications and 23.9% on side effects. Further, M2REMAP overcomes the limitation of existing methods and effectively predicts drugs for novel diseases and emerging pathogens. Availability and implementation The code is available at https://github.com/celehs/M2REMAP, and prediction results are provided at https://shiny.parse-health.org/drugs-diseases-dev/. Supplementary information Supplementary data are available at Bioinformatics online.
Experimental modeling and compensation of pivot nonlinearity in hard disk drives

This paper considers a new model-based friction compensator for servo control of hard disk drives (HDDs). Using measured and simulated responses in both time and frequency domains as a guide, an HDD designer can iteratively improve the friction model of the HDD system and verify the correctness of the HDD measurement through this new model. By feeding back the model-based estimated friction forces into the voice coil motor (VCM), the frequency response between the read/write head position and the VCM current can be linearized. This allows the cancellation scheme to be developed and implemented through model-based compensation. Experiments have confirmed that the cancellation scheme is indeed effective in the frequency range of 0-300 Hz. Furthermore, by using a sequence of square waves as references for track-to-track seeking, the overshooting in the time responses can be compared between servo controls with and without compensators for friction.
Extremum seeking loops with assumed functions: estimation and control

Extremum seeking (also peak-seeking) controllers are designed to operate at an a priori unknown set-point that extremizes the value of a performance function. Traditional approaches to the problem assume a time-scale separation between the gradient computation and function minimization and the system dynamics. The work here, in contrast, assumes that the performance function can be approximated by an assumed function with a finite number of parameters. These parameters axe estimated on-line and the extremum seeking controller operates based on these estimated values. To analyze our current scheme, quadratic functions or exponentials of quadratic functions are assumed as approximations to the performance function. A significant advantage of these functions is that they allow the peak-seeking control loop to be reduced to a linear system. For such a loop, the wealth of linear system analysis and synthesis tools can be employed. First, the control loop is analyzed assuming that the parameters in the function are known (full information case) and then when the parameters are estimated on line (the partial information case).
Decay measures on locally compact abelian topological groups

We show that the Banach space M of regular σ-additive finite Borel complex-valued measures on a non-discrete locally compact Hausdorff topological Abelian group is the direct sum of two linear closed subspaces MD and MND, where MD is the set of measures μ ∈ M whose Fourier transform vanishes at infinity and MND is the set of measures μ ∈ M such that ν ∉ MD for any ν ∈ M {0} absolutely continuous with respect to the variation |μ|. For any corresponding decomposition μ = μD + μND (μD ∈ MD and μND ∈ MND) there exist a Borel set A = A(μ) such that μD is the restriction of μ to A, therefore the measures μD and μND are singular with respect to each other. The measures μD and μND are real if μ is real and positive if μ is positive. In the case of singular continuous measures we have a refinement of Jordan's decomposition theorem. We provide series of examples of different behaviour of convolutions of measures from MD and MND.
Aspects of Wrapped Branes in String and M-Theory

This thesis consists of an introductory text together with five appended research papers. The Ariadne's thread through the whole thesis is various effects coming from high-dimensional p-branes in various subsectors of string and M-theory. The low energy effective actions in string and M-theory consists of a classical supergravity together with quantum corrections. In particular the non-perturbative correction terms arise from instanton effects, which are interpreted as p-branes wrapping supersymmetric cycles. The general structure of the full effective action is the result of a complicated interplay between supersymmetry and U-duality. Requiring the action to be invariant under U-duality leads to mathematical functions called automorphic forms. Both perturbative and non-perturbative corrections seem to be captured by these functions. The U-duality groups can be found by analyzing the algebraic structures of the moduli space after toroidal compactification. Using this line of thinking, some simple examples of higher order derivative corrections in pure gravity are investigated. Compactification on manifolds with special holonomy is also discussed in this thesis, with focus on the resulting moduli spaces. Certain quantum corrections to type IIA string theory compactified on a rigid Calabi-Yau threefold are analyzed. Manifolds with special holonomy constitute target spaces of the topological subsectors in string and M-theory. The low energy effective action of these theories consists of a classical contribution from a form theory of gravity, which receives quantum corrections from branes wrapping supersymmetric cycles in the target space. In particular the dynamics of the M2- and M5-branes are discussed in the context of a topological version of M-theory.
Tyrosine kinase receptor B attenuates liver fibrosis by inhibiting TGF-β/SMAD signaling

Background and Aims: Liver fibrosis is a leading indicator for increased mortality and long-term comorbidity in NASH. Activation of HSCs and excessive extracellular matrix production are the hallmarks of liver fibrogenesis. Tyrosine kinase receptor (TrkB) is a multifunctional receptor that participates in neurodegenerative disorders. However, paucity of literature is available about TrkB function in liver fibrosis. Herein, the regulatory network and therapeutic potential of TrkB were explored in the progression of hepatic fibrosis. Methods and Results: The protein level of TrkB was decreased in mouse models of CDAHFD feeding or carbon tetrachloride-induced hepatic fibrosis. TrkB suppressed TGF-β-stimulated proliferation and activation of HSCs in 3-dimensional liver spheroids and significantly repressed TGF-β/SMAD signaling pathway either in HSCs or in hepatocytes. The cytokine, TGF-β, boosted Nedd4 family interacting protein-1 (Ndfip1) expression, promoting the ubiquitination and degradation of TrkB through E3 ligase Nedd4-2. Moreover, carbon tetrachloride intoxication-induced hepatic fibrosis in mouse models was reduced by adeno-associated virus vector serotype 6 (AAV6)–mediated TrkB overexpression in HSCs. In addition, in murine models of CDAHFD feeding and Gubra-Amylin NASH (GAN), fibrogenesis was reduced by adeno-associated virus vector serotype 8 (AAV8)–mediated TrkB overexpression in hepatocytes. Conclusion: TGF-β stimulated TrkB degradation through E3 ligase Nedd4-2 in HSCs. TrkB overexpression inhibited the activation of TGF-β/SMAD signaling and alleviated the hepatic fibrosis both in vitro and in vivo. These findings demonstrate that TrkB could be a significant suppressor of hepatic fibrosis and confer a potential therapeutic target in hepatic fibrosis.
Microactuators with Piezoelectric Polylactic Acid Fibers—Toward the Realization of Tweezers for Biological Cells

The poly-L-lactic acid (PLLA) shows a high shear piezoelectric constant. We fabricated PLLA fiber samples with large degree of crystallinity and high orientation of crystallites using high-speed spinning. If the electric field is applied to the PLLA fiber in the direction perpendicular to the PLLA fiber axis, the PLLA fiber must be driven by the piezoelectric effect. Therefore, we devised an effective method of applying the electric field to the PLLA fiber. We also developed equipment for measuring the piezoelectric motion of the PLLA fiber, which uses a CCD camera and divided photodiodes. As a result, we could drive the PLLA fiber by the shear piezoelectric effect under the application of ac voltage, and observed the bending motion of the entire PLLA fiber. Finally, we attempted to release and grasp the bead sample using a pair of PLLA fibers like tweezers, and succeeded.
Stability conditions for heteroscedastic factor models with conditionally autoregressive betas

We characterize the stability properties of a heteroscedastic multi‐factor model of financial asset returns, with conditionally known factors and beta coefficients driven by general conditionally autoregressive processes. These processes generalize existing structures and address a number of empirical issues of current concern. Our analysis derives closed‐form sufficient conditions for the existence of strict stationary solutions for the composite asset conditional variances and covariances, not known previously in the literature. It is shown that stability is guaranteed when individual‐process and cross‐process restrictions hold simultaneously. Our results are also applicable to the study of the co‐movement between volatility and beta coefficients as well as between beta coefficients themselves.
Electronic structure of CrO2 studied by magnetic circular dichroism in resonant photoemission

C. F. Chang,1 D. J. Huang,1,* A. Tanaka,2 G. Y. Guo,3,1 S. C. Chung,1 S. -T. Kao,4,5 S. G. Shyu,4,5 and C. T. Chen1 1National Synchrotron Radiation Research Center, Hsinchu 30076, Taiwan 2Department of Quantum Matters, ADSM, Hiroshima University, Higashi-Hiroshima 739-8530, Japan 3Department of Physics, National Taiwan University, Taipei 106, Taiwan 4Institute of Chemistry, Academia Sinica, Nankang, Taipei 115, Taiwan 5Department of Chemistry, National Central University, Tao-Yuan 320, Taiwan sReceived 17 September 2004; published 23 February 2005d
Interval Type-2 Fuzzy Neural Networks for Multi-Label Classification

Prediction of multi-dimensional labels plays an important role in machine learning problems. We found that the classical binary labels could not reflect the contents and their relationships in an instance. Hence, we propose a multi-label classification model based on interval type-2 fuzzy logic. In the proposed model, we use a deep neural network to predict the type-1 fuzzy membership of an instance and another one to predict the fuzzifiers of the membership to generate interval type-2 fuzzy memberships. We also propose a loss function to measure the similarities between binary labels in datasets and interval type-2 fuzzy memberships generated by our model. The experiments validate that our approach outperforms baselines on multi-label classification benchmarks.
Analyzing Multimodal Objectives Through the Lens of Generative Diffusion Guidance

Recent years have witnessed astonishing advances in the field of multimodal representation learning, with contrastive learning being the cornerstone for major breakthroughs. Latest works delivered further improvements by incorporating different objectives such as masked modeling and captioning into the frameworks, but our understanding on how these objectives facilitate learning remains vastly incomplete. In this paper, we leverage the fact that classifier-guided diffusion models generate images that reflect the semantic signals provided by the classifier to study the characteristics of multimodal learning objectives. Specifically, we compare contrastive, matching and captioning loss in terms of their semantic signals, and introduce a simple baseline that not only supports our analyses but also improves the quality of generative guidance in a straightforward manner.
Abstract initial boundary value problems

We consider abstract initial boundary value problems in a spirit similar to that of the classical theory of linear semigroups. We assume that the solution u at time t is given by u(t) = S(t) ξ + V(t)g, where ξ and g are respectively the initial and boundary data and S(t) and V(t) are linear operators. We take as a departing point the functional equations satisfied by the propagators S and V. We discuss conditions under which a pair (S, V) describes the solution of an abstract differential initial boundary value problem. Several examples are provided of parabolic and hyperbolic problems that can be accommodated within the abstract theory. We study the backward Euler's method for the time integration of the problems considered.
The cosmological constant, dark matter, supersymmetry, and other unsolved problems from a fresh perspective

Quantum theory, general relativity, the standard model of particle physics, and the $\Lambda$CDM model of cosmology have all been spectacularly successful within their respective regimes of applicability, but each of these descriptions also has clear limitations. Here we propose a fundamental theory which (like string theory) is based on higher dimensions (with an internal space), a form of supersymmetry, important topological structures, and the implication of a multiverse. Our universe is the product of two vortex-like (or instanton-like) field configurations -- one in 4-dimensional external spacetime, with the big bang at its origin, and the other in a 10-dimensional internal space, which automatically yields an $SO(10)$ grand-unified gauge theory. Lorentz invariance requires a breaking of the initial primitive supersymmetry, as the initial (unphysical) bosonic fields are modified and combined to from physical fields. There is then a new interpretation of all scalar boson sectors -- including but extending the Higgs and sfermion sectors. This last feature predicts a novel dark matter WIMP with no (nongravitational) interactions except second-order gauge couplings to $W$ and $Z$ bosons. Calculations and estimates of the relevant cross-sections for this particle demonstrate that (1)~it may be detectable within the next few years in Xe-based direct-detection experiments, (2)~it may be observable within about 15 years at the high-luminosity LHC, and (3)~it may already have been detected in the gamma rays observed by Fermi-LAT and antiprotons observed by AMS-02. The reinterpretation of scalar boson fields also implies a new phenomenology for sfermions, with reduced cross-sections. There is then a unified picture which may explain why dark matter WIMPs and electroweak-scale sparticles have not yet been detected.
Effect of Confinement and Coulomb Interactions on the Electronic Structure of the (111) LaAlO3/SrTiO3 Interface

A tight binding supercell approach is used for the calculation of the electronic structure of the (111) LaAlO3/SrTiO3 interface. The confinement potential at the interface is evaluated solving a discrete Poisson equation by means of an iterative method. In addition to the effect of the confinement, local Hubbard electron–electron terms are included at the mean-field level within a fully self-consistent procedure. The calculation carefully describes how the two-dimensional electron gas arises from the quantum confinement of electrons near the interface due to the band bending potential. The resulting electronic sub-bands and Fermi surfaces show full agreement with the electronic structure determined by angle-resolved photoelectron spectroscopy experiments. In particular, we analyse how the effect of local Hubbard interactions change the density distribution over the layers from the interface to the bulk. Interestingly, the two-dimensional electron gas at the interface is not depleted by local Hubbard interactions which indeed induce an enhancement of the electron density between the first layers and the bulk.
Effects of perimeter recombination on GaAs-based solar cells

Perimeter recombination currents have been experimentally characterized on GaAs p/n heteroface diodes and solar cells with areas ranging from 2.5*10/sup -5/ to 0.25 cm/sup 2/. Under 1-sun operation at the maximum power point, measurements show that the n approximately=2 perimeter recombination current component degrades the cell's fill factors but does not greatly affect the open-circuit voltage. The n approximately=2 perimeter recombination currents are examined theoretically on small-area cells using a two-dimensional drift-diffusion device simulator, PUPHS2D. This model verifies the importance and origin of perimeter recombination in heteroface GaAs-based solar cells. Two methods of reducing the n approximately=2 perimeter recombination are explored. <<ETX>>
1 2 M ay 2 01 0 The number of 3SAT functions ∗

With Gk(n) the number of functions of n boolean variables definable by k-SAT formulae, we prove that G3(n) is asymptotic to 2 n+(n3). This is a strong form of the case k = 3 of a conjecture of Bollobás, Brightwell and Leader stating that for fixed k, log2Gk(n) ∼ (
Probabilistic WCET Estimation for Weakly Hard Real-Time Systems

Weakly hard real-time systems can, to some degree, tolerate deadline misses, but their schedulability still needs to be analyzed to ensure their quality of service. Such analysis usually occurs at early design stages to provide implementation guidelines to engineers so that they can make better design decisions. Estimating worst-case execution times (WCET) is a key input to schedulability analysis. However, early on during system design, estimating WCET values is challenging and engineers usually determine them as plausible ranges based on their domain knowledge. Our approach aims at finding restricted, safe WCET sub-ranges given a set of ranges initially estimated by experts in the context of weakly hard real-time systems. To this end, we leverage (1) multi-objective search aiming at maximizing the violation of weakly hard constraints in order to find worst-case scheduling scenarios and (2) polynomial logistic regression to infer safe WCET ranges with a probabilistic guarantee. We evaluated our approach by applying it to an industrial system in the satellite domain and several realistic synthetic systems. The results indicate that our approach significantly outperforms a baseline relying on random search without learning, and estimates safe WCET ranges with a high degree of confidence in practical time (< 23h).
Automotive Radar Sub-Sampling via Object Detection Networks: Leveraging Prior Signal Information

In recent years, automotive radar has attracted considerable attention due to the growing interest in autonomous driving technologies. Acquiring situational awareness using multimodal data collected at high sampling rates by various sensing devices including cameras, LiDAR, and radar requires considerable power, memory and compute resources which are often limited at an edge device. In this paper, we present a novel adaptive radar sub-sampling algorithm designed to identify regions that require more detailed/accurate reconstruction based on the information about prior environmental conditions, enabling near-optimal performance at considerably lower effective sampling rates. Designed to robustly perform under variable weather conditions, the algorithm was shown on the Oxford radar dataset to achieve accurate scene reconstruction utilizing only 10% of the collected samples in good weather. In the case of the RADIATE dataset acquired during extreme weather conditions (snow, fog), only 20% of the samples were sufficient to enable robust scene reconstruction. A further modification of the algorithm incorporates object motion to enable reliable identification of regions that require attention. This includes monitoring possible future occlusions caused by the objects detected in the present frame. Finally, we train a YOLO network on the RADIATE dataset to perform object detection, obtaining 6.6% AP50 improvement over the baseline Faster R-CNN network.
Relativistic Plasma Emission and Pulsar Radio Emission: A Critique

Relativistic plasma emission due to a beam instability in the polar cap regions is examined critically as a pulsar radio emission mechanism. Wave dispersion in the pulsar plasma is discussed, based on the use of a relativistic plasma dispersion function. The growth rate for the beam instability is estimated in the rest frame of the plasma for parallel Langmuir waves, L-O mode waves, and oblique Alfvén waves. The first two of these imply frequencies that are much higher than the observed frequencies for plausible parameters, suggesting that they are not viable as pulsar radio emission mechanisms. Growth of Alfvén waves requires that the beam speed equal the phase speed of the Alfvén waves, and this condition cannot be satisfied within the light cylinder, except for an extremely high energy beam. It is suggested that either the plasma parameters in the source region are quite different from what is currently considered plausible or the emission mechanism does not involve a beam instability. Alternative pulsar radio emission mechanisms should be explored further.
An offset bifocal reflector antenna design for wide-angle beam scanning

A synthesis procedure and performance results for an offset dual reflector with perfect focusing at \pm 8\deg of beam scan are presented. This bifocal antenna extends the theory of the previously reported symmetric system to an offset design. Approximations, such as the smearing of focal points into a "focal ring," are eliminated, as is blockage. The offset design affords greater design flexibility, although the synthesis is more complex. Computed and experimental results demonstrate the improved beam-scanning performance of this antenna.