Miracle-dz/UniFAR-FTUs huggingface dataset:
Surgical versus nonsurgical treatment in first traumatic anterior dislocation of the shoulder in athletes

Correspondence: Gustavo Gonçalves Arliani Centro de Traumatologia do esporte (CeTe), Departamento de Ortopedia e Traumatologia da Universidade Federal de São Paulo, São Paulo, Brazil Tel +55 11 5571 6621 Fax +55 11 5579 4642 email ggarliani@hotmail.com Abstract: Anterior traumatic dislocation is a common problem faced by orthopedic surgeons. After the first episode of shoulder dislocation, a combination of lesions can lead to chronic instability. The management in treatment of young athletes after the first acute anterior shoulder dislocation is controversial. The available literature supports early surgical treatment for young male athletes engaged in highly demanding physical activities after the first episode of traumatic dislocation of the shoulder. This is because of the best functional results and lower recurrence rates obtained with this treatment in this population. However, further clinical trials of good quality comparing surgical versus nonsurgical treatment for well-defined lesions are needed, especially for categories of patients who have a lower risk of recurrence.
SMU Data

This paper presents a novel method for fast classiﬁcation of surface electromyography(sEMG) signals, using a simple model of attention. The brain transmits electrical signals throughout the body to contract and relax muscles. sEMG measures these signals by recording muscle activity from the surface above the muscle on the skin. By classifying these signals with low latency, they can be used to control a prosthetic limb using an amputee’s brain power. On a diﬃcult, industry benchmark sEMG dataset, the proposed attentional architecture yields excellent results, classifying 36 more gestures (53 in total) with about 20% higher accuracy (87% overall) than the current standards in the ﬁeld. These results have direct and immediate application in the ﬁelds of robotics, myoelectric control, and prosthetics.
In vivo evaluation of a conjugated poly(lactide-ethylene glycol) nanoparticle depot formulation for prolonged insulin delivery in the diabetic rabbit model

Poly(ethylene glycol) (PEG) and polylactic acid (PLA)-based copolymeric nanoparticles were synthesized and investigated as a carrier for prolonged delivery of insulin via the parenteral route. Insulin loading was simultaneously achieved with particle synthesis using a double emulsion solvent evaporation technique, and the effect of varied PEG chain lengths on particle size and insulin loading efficiency was determined. The synthesized copolymer and nanoparticles were analyzed by standard polymer characterization techniques of gel permeation chromatography, dynamic light scattering, nuclear magnetic resonance, and transmission electron microscopy. In vitro insulin release studies performed under simulated conditions provided a near zero-order release pattern up to 10 days. In vivo animal studies were undertaken with varied insulin loads of nanoparticles administered subcutaneously to fed diabetic rabbits and, of all doses administered, nanoparticles containing 50 IU of insulin load per kg body weight controlled the blood glucose level within the physiologically normal range of 90–140 mg/dL, and had a prolonged effect for more than 7 days. Histopathological evaluation of tissue samples from the site of injection showed no signs of inflammation or aggregation, and established the nontoxic nature of the prepared copolymeric nanoparticles. Further, the reaction profiles for PLA-COOH and NH2-PEGDA-NH2 were elucidated using molecular mechanics energy relationships in vacuum and in a solvated system by exploring the spatial disposition of various concentrations of polymers with respect to each other. Incorporation of insulin within the polymeric matrix was modeled using Connolly molecular surfaces. The computational results corroborated the experimental and analytical data. The ability to control blood glucose levels effectively coupled with the nontoxic behavior of the nanoparticles indicates that these nanoparticles are a potential candidate for insulin delivery.
Probabilistic modeling and inference are becoming central computational tools across a broad range of fields

We introduce inference metaprogramming for probabilistic programming languages, including new language constructs, a formalism, and the first demonstration of effectiveness in practice. Instead of relying on rigid black-box inference algorithms hard-coded into the language implementation as in previous probabilistic programming languages, inference metaprogramming enables developers to 1) dynamically decompose inference problems into subproblems, 2) apply inference tactics to subproblems, 3) alternate between incorporating new data and performing inference over existing data, and 4) explore multiple execution traces of the probabilistic program at once. Implemented tactics include gradientbased optimization, Markov chain Monte Carlo, variational inference, and sequental Monte Carlo techniques. Inference metaprogramming enables the concise expression of probabilistic models and inference algorithms across diverse fields, such as computer vision, data science, and robotics, within a single probabilistic programming language. CCS Concepts • Mathematics of computing → Probabilistic inference problems; • Software and its engineering→ Formal language definitions;
AdarGCN: Adaptive Aggregation GCN for Few-Shot Learning – Supplementary Material –

In this document, we provide more supporting results to show the effectiveness of our AdarGCN under both the new SSFSL and conventional FSL settings. Firstly, we illustrate the cleaned examples and the removed examples (i.e. noise) obtained by our AdarGCN-based label denoising (LDN) method under the new SSFSL setting. Secondly, we present the weight distributions of outlying examples obtained by our AdarGCN-based FSL method under the conventional FSL setting. These qualitative results (shown in Sections 1 and 2) suggest that our AdarGCN can effectively deal with both noisy and outlying images, explaining its superior performance under both FSL settings. Thirdly, we report some quantitative 5-way 1-shot results under the conventional FSL setting, together with the 5-way 5-shot results in the main paper,to validate the effectiveness of our AdarGCN with different 5-way settings.
Decomposing ontology in Description Logics by graph partitioning

In this paper, we investigate the problem of decomposing an ontology in Description Logics (DLs) based on graph partitioning algorithms. Also, we focus on syntax features of axioms in a given ontology. Our approach aims at decomposing the ontology into many sub ontologies that are as distinct as possible. We analyze the algorithms and exploit parameters of partitioning that influence the efficiency of computation and reasoning. These parameters are the number of concepts and roles shared by a pair of sub-ontologies, the size (the number of axioms) of each sub-ontology, and the topology of decomposition. We provide two concrete approaches for automatically decomposing the ontology, one is called minimal separator based partitioning, and the other is eigenvectors and eigenvalues based segmenting. We also tested on some parts of used TBoxes in the systems FaCT, Vedaall, tambis, . and propose estimated results
Joint source-protocol-channel decoding: Improving 802.11N receivers

This paper combines joint protocol-channel (JPC) and joint source-channel (JSC) decoding techniques within a receiver in the context of wireless data transmission. It assumes that demodulation and channel decoding at physical (PHY) layer can provide soft information about the transmitted bits. At each layer of the protocol stack, JPC decoding allows headers of corrupted packets to be reliably decoded and soft information on the corresponding payload to be forwarded to the correct upper layer. When reaching the application (APL) layer, packets may still contain errors and are JSC decoded, exploiting residual redundancy present in the compressed bitstream, to remove part of the residual errors. The main contribution of this paper is to show that these tools may be efficiently combined to obtain i) reliable protocol layers permeable to transmission errors and ii) improved source decoders. Performance is evaluated using an OMNET++ simulation for the transmission of compressed HTML files (HTTP 1.1) over a standard RTP/UDP-Lite/Ipv6/MACLite/ 802:11n-PHY protocol stack, only the receiver is modified. For a given packet error rate, the proposed scheme provides gains up to 2 dB in SNR compared to a standard receiver.
Simultaneous few-cycle pulse generation of the depleted pump and signal from an optical parametric amplifier

We generate few-cycle laser pulses from both the depleted pump and the signal of an optical parametric amplifier using self-phase modulation in a single hollow-core fiber. Despite the depleted pump’s poor spatial quality entering the fiber, it produces a field with less than 2.5 cycles. Moreover, we can simultaneously (same fiber) generate 4 cycle pulses from the signal. The coherent combination of both pulses allows for bandwidth spanning from 500 to 1500 nm. The geometry allows for minimal path differences of the two fields, paving a route for generating multi-octave, synthesized light transients centered in the near-infrared.
A stochastic comparison study for the smallest and largest ordered statistic from Weibull-G and Gompertz Makeham distribution

In this paper, we have discussed the stochastic comparison of the smallest and largest ordered statistic from independent heterogeneous Weibull-G random variables and Gompertz Makeham random variables. We compare systems arising from taking different model parameters and obtain stochastic ordering results under the condition of multivariate chain majorization. Using the notion of vector majorization, we compare different systems and obtain stochastic ordering results.
Instantaneous imaging of ozone in a gliding arc discharge using photofragmentation laser-induced fluorescence

Ozone vapor, O3, is here visualized in a gliding arc discharge using photofragmentation laser-induced fluorescence. Ozone is imaged by first photodissociating the O3 molecule into an O radical and a vibrationally hot O2 fragment by a pump photon. Thereafter, the vibrationally excited O2 molecule absorbs a second (probe) photon that further transits the O2-molecule to an excited electronic state, and hence, fluorescence from the deexcitation process in the molecule can be detected. Both the photodissociation and excitation processes are achieved within one 248 nm KrF excimer laser pulse that is formed into a laser sheet and the fluorescence is imaged using an intensified CCD camera. The laser-induced signal in the vicinity of the plasma column formed by the gliding arc is confirmed to stem from O3 rather than plasma produced vibrationally hot O2. While both these products can be produced in plasmas a second laser pulse at 266 nm was utilized to separate the pump- from the probe-processes. Such arrangement allowed lifetime studies of vibrationally hot O2, which under these conditions were several orders of magnitude shorter than the lifetime of plasma-produced ozone.
Why tropical forest lizards are vulnerable to climate warming

Biological impacts of climate warming are predicted to increase with latitude, paralleling increases in warming. However, the magnitude of impacts depends not only on the degree of warming but also on the number of species at risk, their physiological sensitivity to warming and their options for behavioural and physiological compensation. Lizards are useful for evaluating risks of warming because their thermal biology is well studied. We conducted macrophysiological analyses of diurnal lizards from diverse latitudes plus focal species analyses of Puerto Rican Anolis and Sphaerodactyus. Although tropical lowland lizards live in environments that are warm all year, macrophysiological analyses indicate that some tropical lineages (thermoconformers that live in forests) are active at low body temperature and are intolerant of warm temperatures. Focal species analyses show that some tropical forest lizards were already experiencing stressful body temperatures in summer when studied several decades ago. Simulations suggest that warming will not only further depress their physiological performance in summer, but will also enable warm-adapted, open-habitat competitors and predators to invade forests. Forest lizards are key components of tropical ecosystems, but appear vulnerable to the cascading physiological and ecological effects of climate warming, even though rates of tropical warming may be relatively low.
Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability

Increasingly complex applications involve large datasets in combination with nonlinear and high-dimensional mathematical models. In this context, statistical inference is a challenging issue that calls for pragmatic approaches that take advantage of both Bayesian and frequentist methods. The elegance of Bayesian methodology is founded in the propagation of information content provided by experimental data and prior assumptions to the posterior probability distribution of model predictions. However, for complex applications, experimental data and prior assumptions potentially constrain the posterior probability distribution insufficiently. In these situations, Bayesian Markov chain Monte Carlo sampling can be infeasible. From a frequentist point of view, insufficient experimental data and prior assumptions can be interpreted as non-identifiability. The profile-likelihood approach offers to detect and to resolve non-identifiability by experimental design iteratively. Therefore, it allows one to better constrain the posterior probability distribution until Markov chain Monte Carlo sampling can be used securely. Using an application from cell biology, we compare both methods and show that a successive application of the two methods facilitates a realistic assessment of uncertainty in model predictions.
From genes to ecosystems: a synthesis of the effects of plant genetic factors across levels of organization

Using two genetic approaches and seven different plant systems, we present findings from a meta-analysis examining the strength of the effects of plant genetic introgression and genotypic diversity across individual, community and ecosystem levels with the goal of synthesizing the patterns to date. We found that (i) the strength of plant genetic effects can be quite high; however, the overall strength of genetic effects on most response variables declined as the levels of organization increased. (ii) Plant genetic effects varied such that introgression had a greater impact on individual phenotypes than extended effects on arthropods or microbes/fungi. By contrast, the greatest effects of genotypic diversity were on arthropods. (iii) Plant genetic effects were greater on above-ground versus below-ground processes, but there was no difference between terrestrial and aquatic environments. (iv) The strength of the effects of intraspecific genotypic diversity tended to be weaker than interspecific genetic introgression. (v) Although genetic effects generally decline across levels of organization, in some cases they do not, suggesting that specific organisms and/or processes may respond more than others to underlying genetic variation. Because patterns in the overall impacts of introgression and genotypic diversity were generally consistent across diverse study systems and consistent with theoretical expectations, these results provide generality for understanding the extended consequences of plant genetic variation across levels of organization, with evolutionary implications.
An acceleration technique for the radioelectric coverage prediction in small and microcell configurations

The purpose of this work is to optimise the necessary computation time for the coverage zone prediction. Several approaches exist to reduce the calculation time; they consist in simplifying the complexity of the used propagation model. Here, our method is different but complementary of the previous approaches. Indeed, it is independent of the propagation model and tries to reduce the number of application points of the considered model for the coverage prediction. Thus, the performances of our optimised method in term of accuracy and computation time is presented in this article
EXPERIMENTAL STUDY OF HALO FORMATION IN SPACE CHARGE DOMINATED BEAM

Beam halos are a group of particles with low density that are far away from the well-defined central beam core and have large transverse velocities. Beam losses from halos can require a larger aperture and impose restrictions on the beam current. Several theoretical techniques have been applied to analyze and understand halo formation, including the particle-core model, the free energy model as well as particle in cell (PIC) simulations. However, few experiments on beam halos have been carried out. Here, we describe an experimental study at the University of Maryland to understand and characterize space-charge induced halo formation. The experiments are conducted on the University of Maryland Electron Beam (UMER) and the results are compared with PIC simulations using WARP. INTRODUCTION Halo is generally understood as a population of particles that do, or will reach large transverse radii relative to a more intense, centralized beam core. It is associated with emittance growth, degradation of beam quality and particle loss [1]. Several analytic models such as the particle-core model [2] and the free energy model [3] are derived either to depict the process of halo formation or to describe the associated emittance growth. Many theoretical and simulation studies developed these ideas and discussed various mechanisms for halo formation. However, fewer experimental studies have been performed as it is hard to obtain a halo free beam, a crucial component to identify different mechanisms or sources for halo formation. The LEDA experiment [4] is an example for demonstrating agreement with the particle-core model. But its propagation length is limited and it is no longer operational. In this paper, we discuss a method to get a halo-free beam though envelope match and skewness correction. Based on the matched beam, we perform a mismatch experiment as well as a skewness test to verify the sources of halo formation in UMER. Then, we generate a pure breathing mode mismatch, and compare experiments with simulations to confirm this mode.
On the relationship between the mesospheric sodium layer and the meteoric input function

10 11 This study examines the relationship between the concentration of atmospheric sodium and its 12 Meteoric Input Function (MIF). We use the measurements from the Colorado State University (CSU) 13 Lidar and the Andes Lidar Observatory (ALO) with a new numerical model that includes sodium 14 chemistry in the mesosphere and lower thermosphere (MLT) region. The model is based on the 15 continuity equation to treat all sodium-bearing species and runs at a high temporal resolution. The 16 model simulation employs data assimilation to compare the MIF inferred from the meteor radiant and 17 the MIF derived from the new sodium chemistry model. The simulation captures the seasonal variability 18 of sodium number density compared with lidar observations over the CSU site. However, there were 19 discrepancies for the ALO site, which is close to the South Atlantic Anomaly (SAA) region, indicating it is 20 challenging for the model to capture the observed sodium over ALO. The CSU site had significantly more 21 lidar observations (27,930 hours) than the ALO sites (1872 hours). The simulation revealed that the 22 uptake of the sodium species on meteoric smoke particles was a critical factor in determining the 23 sodium concentration in MLT, with the sodium removal rate by uptake found to be approximately three 24 times that of the NaHCO 3 dimerization. Overall, the study's findings provide valuable information on the 25 correlation between MIF and sodium concentration in the MLT region, contributing to a better 26 understanding of the complex dynamics in this region. This knowledge can inform future research and
LSOS: Line-search Second-Order Stochastic optimization methods

We develop a line-search second-order algorithmic framework for optimization problems in noisy environments, i.e., assuming that only noisy values are available for the objective function and its gradient and Hessian. In the general noisy case, almost sure convergence of the methods fitting into the framework is proved when line searches and suitably decaying step lengths are combined. When the objective function is a finite sum, such as in machine learning applications, our framework is specialized as a stochastic L-BFGS method with line search only, with almost sure convergence to the solution. In this case, linear convergence rate of the expected function error is also proved, along with a worst-case $\mathcal{O} (\log(\varepsilon^{-1}))$ complexity bound. Numerical experiments, including comparisons with state-of-the art first- and second-order stochastic optimization methods, show the efficiency of our approach.
Manifold Alignment for Semantically Aligned Style Transfer

1. Details of the transformation of the objective function As the transformation of the objective function J(P ) in Eq. (2) of the main paper into matrix form in Eq. (4) is omitted in the main paper due to limited space, details of the transformation are thus given here as follows. All the notations are the same as the main paper. Firstly, as Fcs = PFc, we can replace φi(Fcs) with Pφi(Fc), which leads to:
Liquid crystal true 3D displays for augmented reality applications

Augmented reality (AR) technology, which integrates virtual computer-generated information into the real world scene, is believed to be the next-generation human-machine interface. However, most AR products adopt stereoscopic 3D display technique, which causes the accommodation-vergence conflict. To solve this problem, we have proposed two approaches. The first is a multi-planar volumetric display using fast switching polymer-stabilized liquid crystal (PSLC) films. By rapidly switching the films between scattering and transparent states while synchronizing with a high-speed projector, the 2D slices of a 3D volume could be displayed in time sequence. We delved into the research on developing high-performance PSLC films in both normal mode and reverse mode; moreover, we also realized the demonstration of four-depth AR images with correct accommodation cues. For the second approach, we realized a holographic AR display using digital blazed gratings and a 4f system to eliminate zero-order and higher-order noise. With a 4k liquid crystal on silicon device, we achieved a field of view (FOV) of 32 deg. Moreover, we designed a compact waveguidebased holographic 3D display. In the design, there are two holographic optical elements (HOEs), each of which functions as a diffractive grating and a Fresnel lens. Because of the grating effect, holographic 3D image light is coupled into and decoupled out of the waveguide by modifying incident angles. Because of the lens effect, the collimated zero order light is focused at a point, and got filtered out. The optical power of the second HOE also helps enlarge FOV.