Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship of Average Outcomes Scores and Change in Status Requires Further Interpretation Between 1 and 2 Years Following Hip Arthroscopy

Background: Previous studies have demonstrated a clinically impactful change in patients between 1 and 2 years after hip arthroscopy. Assessment of differences in patient-specific factors between patients who remain the same and those who change (ie, either improve or decline) could provide valuable outcome information for orthopaedic surgeons treating those patients. Purpose: To identify patients who experienced change in functional status between 1 and 2 years after hip arthroscopy for femoroacetabular impingement syndrome and assess differences in patient-specific factors between those who improved, remained the same, or declined in functional status. Study Design: Cohort study; Level of evidence, 3. Methods: Prospectively collected data for patients who underwent hip arthroscopy at 1 of 7 centers were analyzed retrospectively at 1 year and 2 years postoperatively. Patients were categorized as “improved,”“remained the same,” or “declined” between 1- and 2-year follow-up based on the 12-item International Hip Outcome Tool (iHOT-12) minimal clinically important difference (MCID) value. A 1-way analysis of variance was used to assess differences in iHOT-12 scores, age, body mass index (BMI), alpha angle, and center-edge angle (CEA) between groups. Chi-square analyses were used to assess differences in the proportions of male and female patients in the outcome groups. Results: The study included 753 patients (515 women and 238 men), whose mean ± SD age was 34.7 ± 12 years. Average 1-year (±1 month) and 2-year (±2 months) iHOT-12 scores for all patients were 73.7 and 74.9, respectively. Based on the calculated MCID of ±11.5 points, 162 (21.5%) patients improved, 451 (59.9%) remained the same, and 140 (18.6%) declined in status between 1- and 2-year follow-up. Those who improved between 1 and 2 years had lower 1-year iHOT-12 scores (P < .0005). We found no difference in age, BMI, alpha angle, CEA, or sex between groups (P > .05). Conclusion: Between 1- and 2-year follow-up assessments, 21.5% of patients improved and 18.6% declined in self-reported functional status. Those with iHOT-12 scores indicating abnormal function at 1 year improved beyond the MCID at 2 years follow-up. Thus, any decisions about the failure or success of arthroscopic hip procedures should not be made until at least the 2-year follow-up. Failing to thrive at 1-year follow-up may not accurately predict outcomes at year 2 or beyond. This could potentially decrease the perceived need for revision surgery in patients who do not thrive before 2-year follow-up.
Atypical Presentation of Infective Endocarditis With Native Aortic Valve Involvement Secondary to Staphylococcus aureus Bacteremia in the Setting of Non-Hodgkin Lymphoma

Infective endocarditis (IE) is a condition that can involve endocardial tissue and possibly lead to valvular disease. Not only is it important to recognize the clinical presentation difference between acute and subacute IE, but physicians should understand that underlying risk factors, such as immunosuppression secondary to non-Hodgkin lymphoma (NHL), can alter an acute presentation into that of a subacute one. We report an NHL patient, who presented with subacute clinical symptoms of IE, but had a clinical test workup that showed evidence of acute IE rather than subacute.
Accelerated Model Predictive Control Based on a Greedy Algorithm With Round-Robin Priority for N-Level Single-Phase Flying Capacitor Converter in Solid-State Transformer

This article presents a control method for reducing the execution time based on model predictive control (MPC) in a grid-connected single-phase N-level flying capacitor converter (FCC). The proposed method controls the grid current and flying capacitor voltage through two layers with a hierarchical structure finite control set MPC. In particular, unlike conventional MPC, using the greedy algorithm, the number of switching combinations is reduced by segmenting power devices into groups and sequentially determining switching states. The execution time is shortened because the reduction in the number of switching combinations is diminished. Moreover, because the maximum number of switching states to be compared increases in linear proportion to the voltage level, the execution time does not increase significantly as the voltage level is increased. As a result, the switching frequency can be increased by increasing the sampling frequency, and the total harmonic distortion of the grid current can be reduced. Evaluation of the validity of the proposed method via an experiment on a scaled-down prototype of a single-phase 2 kW seven-level FCC is also detailed herein.
Worker Assignment for Multiple Masters to Speed Up Coded Distributed Computing in Heterogeneous Clusters

In distributed computing systems, coding has played an important role to robustify the system against the effect of noise, e.g., stragglers, system failures and communication bottlenecks. Most of the existing work has focused on a simple master-worker model with one master and homogeneous workers. However, real-world systems are typically configured with heterogeneous workers distributed to computing nodes and serve multiple tasks in parallel. In this study, we consider the scenario in which multiple masters perform matrix multiplications using the workers having group heterogeneity. The group heterogeneity models that homogeneous workers are located in the same location and regarded as a group; the workers deployed in the different locations are potentially heterogeneous. We propose an asymptotically optimal worker assignment to multiple masters for coded distributed computing in the presence of heterogeneous groups of workers. Specifically, we present a lower bound for the expected latency in terms of the numbers of workers assigned to the masters and the amount of tasks allocated to workers. Adding the concentration constraints on the number of workers allocated to masters, we can obtain the minimum of the lower bound by taking the optimal worker assignment. We find the optimal worker assignment by converting the problem at hand into a linear programming problem. From both numerical simulations and experiments on Amazon EC2 clusters, we confirm that the effect of the proposed worker assignment is significant in various scenarios.
Galectokines: The Promiscuous Relationship between Galectins and Cytokines

Galectins, a family of glycan-binding proteins, are well-known for their role in shaping the immune microenvironment. They can directly affect the activity and survival of different immune cell subtypes. Recent evidence suggests that galectins also indirectly affect the immune response by binding to members of another immunoregulatory protein family, i.e., cytokines. Such galectin-cytokine heterodimers, here referred to as galectokines, add a new layer of complexity to the regulation of immune homeostasis. Here, we summarize the current knowledge with regard to galectokine formation and function. We describe the known and potential mechanisms by which galectokines can help to shape the immune microenvironment. Finally, the outstanding questions and challenges for future research regarding the role of galectokines in immunomodulation are discussed.
Nonparametric Estimation of Multivariate Distributions with Given Marginals

Nonparametric estimation of the copula function using Bernstein polynomials is studied. Convergence in the uniform topology is established. From the nonparametric Bernstein copula, the nonparametric Bernstein copula density is derived. It is shown that the nonparametric Bernstein copula density is closely related to the histogram estimator, but has the smoothing properties of kernel estimators. The optimal order of polynomial under the L2 norm is shown to be closely related to the inverse of the optimal smoothing factor for common nonparametric estimator. In order of magnitude, this estimator has variance equal to the square root of other common nonparametric estimators, e.g. kernel smoothers, but it is biased as a histogram estimator.
Spectral solution of the incompressible Navier-Stokes equations on the Connection Machine 2

The authors address the issue of solving the time-dependent incompressible Navier-Stokes equations on the Connection Machine 2, for the problem of transition to turbulence on the steady flow in a channel. The spectral algorithm used serially requires O(N/sup 4/) operations; using the massive parallelism of the CM it becomes an O(N/sup 2/) problem, then solving the equations on an N*N*N grid. Preliminary timings of the code, written in Lisp, are included and compared with a corresponding code optimized for the Cray-2 for a 128*128*101 grid. <<ETX>>
Probabilistic models of word order and syntactic discontinuity

This thesis takes up the problem of syntactic comprehension, or parsing—how an agent (human or machine) with knowledge of a specific language goes about inferring the hierarchical structural relationships underlying a surface string in the language. I take the position that probabilistic models of combining evidential information are cognitively plausible and practically useful for syntactic comprehension. In particular, the thesis applies probabilistic methods in investigating the relationship between word order and psycholinguistic models of comprehension; and in the practical problems of accuracy and efficiency in parsing sentences with syntactic discontinuity. On the psychological side, the thesis proposes a theory of expectation-based processing difficulty as a consequence of probabilistic syntactic disambiguation: the ease of processing a word during comprehension is determined primarily by the degree to which that word is expected. I identify a class of syntactic phenomena, associated primarily with verb-final clause order, where the predictions of expectation-based processing diverge most sharply from more established locality-based theories of processing difficulty. Using existing probabilistic parsing algorithms and syntactically annotated data sources, I show that the expectation-based theory matches a range of established experimental psycholinguistic results better than locality-based theories. The comparison of probabilistic- and locality-driven processing theories is a crucial area of psycholinguistic research due to its implications for the relationship between linguistic production and comprehension, and more generally for theories of modularity in cognitive science. The thesis also takes up the problem of probabilistic models for discontinuous constituency, when phrases do not consist of continuous substrings of a sentence. Discontinuity poses a computational challenge in parsing, because it expands the set of possible substructures in a sentence beyond the bound, quadratic in sentence length, on the set of possible continuous constituents. For discontinuous constituency, I investigate the problem of accuracy employing discriminative classifiers organized on principles of syntactic theory and used to introduce discontinuous relationships into otherwise strictly context-free phrase structure trees; and the problem of efficiency in joint inference over both continuous and discontinuous structures, using probabilistic instantiations of mildly context-sensitive grammatical formalisms and factorizing grammatical generalizations into probabilistic components of dominance and linear order.
Leveraging Social Interaction Among Customers: Referral Reward Versus Collective Buying

Over the past decade, the developed and emerging markets have witnessed an exponential growth in online selling strategies that leverage social interaction among customers and enable sellers to offer discounts or rewards on the basis of the size of the buyer pool. This article classifies these diverse strategies into two categories—referral reward (e.g., Uber) and collective buying (e.g., GroupGets)—with associated subtypes. The authors employ an analytical model in which the seller faces customers with heterogeneity in their knowledge and/or intrinsic valuation of a product. Informed customers may inform and increase their less-informed peers’ valuation of the product. The study's richer behavioral model and consideration of a broader strategy space, relative to the existing analytical models, provide new insights into when and how specific strategies are optimal. Referral reward and collective buying encourage information sharing with less-informed potential customers and are typically superior to the individual selling strategy (under which the seller does not incentivize information sharing among customers), except when information sharing is significantly difficult. The authors conduct model refinements and robustness checks and identify clear qualitative managerial implications that can aid strategic decisions under different product-market characteristics. The authors conclude by suggesting future research opportunities to build on this article and add new theoretical insights and managerial guidance.
Adaptive sparse polynomial chaos expansions for uncertainty propagation and sensitivity analysis

Cette these s'insere dans le contexte generale de la propagation d'incertitudes et de l'analyse de sensibilite de modeles de simulation numerique, en vue d'applications industrielles. Son objectif est d'effectuer de telles etudes en minimisant le nombre d'evaluations du modele, potentiellement couteuses. Le present travail repose sur une approximation de la reponse du modele sur la base du chaos polynomial (CP), qui permet de realiser des post-traitements a un cout de calcul negligeable. Toutefois, l'ajustement du CP peut necessiter un nombre consequent d'appels au modele si ce dernier depend d'un nombre eleve de parametres (e. G. Superieur a 10). Pour contourner ce probleme, on propose deux algorithmes pour ne selectionner qu'un faible nombre de termes importants dans la representation par CP, a savoir une procedure de regression pas-a-pas et une procedure basee sur la methode de Least Angle Regression (LAR). Le faible nombre de coefficients associes aux CP creux obtenus peuvent ainsi etre determines a partir d'un nombre reduit d'evaluations du modele. Les methodes sont validees sur des cas-tests academiques de mecanique, puis appliquees sur le cas industriel de l'analyse d'integrite d'une cuve de reacteur a eau pressurisee. Les resultats obtenus confirment l'efficacite des methodes proposees pour traiter les problemes de propagation d'incertitudes et d'analyse de sensibilite en grande dimension
A framework of data-driven wind pressure predictions on bluff bodies using a hybrid deep learning approach

The static synchronous multi-pressure sensing system (SMPSS) test technique is one of the most conventional techniques used in a wind tunnel. In SMPSS tests, wind pressure sensors are prone to take off leading to missing segment data. This study has predicted single, short-term, and long-term wind pressures by a one-dimensional convolutional neural network based on empirical mode decomposition (EMD-1DCNN). The effectiveness of the EMD-1DCNN model in predicting single, short-term, and long-term wind pressures on bluff bodies has been discussed. It was found that the EMD-1DCNN model had a better performance in predicting single wind pressures compared with the DNN and LSTM models. It was also found that both the DNN and LSTM models failed to predict short-term wind pressures, while the EMD-1DCNN model was effective in addressing this problem. The EMD-1DCNN model extracted the spatial feature between wind pressure sensors and its surrounding sensors to predict long-term wind pressures with high accuracy. The effects of data length used for training the EMD-1DCNN model on the accuracy of prediction were also discussed. It was concluded that 1% datasets (500 samples) were enough for predicting long-term wind pressures with high efficiency. This study has not only presented a way to predict missing data of wind pressures using the EMD-1DCNN model but provided recommendations for the EMD-1DCNN model used for different conditions.
26aWG-6 Theory of the waterfall phenomenon in cuprate superconductors

Based on exact diagonalization and variational cluster approximation calculations we study the relationship between charge transfer models and the corresponding single band Hubbard models. We present an explanation for the waterfall phenomenon observed in angle resolved photoemission spectroscopy on cuprate superconductors. The phenomenon is due to the destructive interference between the phases of the O2$p$ orbitals belonging to a given Zhang-Rice singlet and the Bloch phases of the photohole which occurs in certain regions of $\mathbf{k}$ space. It therefore may be viewed as a direct experimental visualization of the Zhang-Rice construction of an effective single band model for the CuO${}_{2}$ plane.
GIS-T ENTERPRISE DATA MODEL WITH SUGGESTED IMPLEMENTATION CHOICES

Sharing of digital road map databases within and among organizations is dependent on translating user requirements to a data model that supports linear and non-linear location referencing systems. This paper examines issues of creating such a data model with the intent of sharing digital road map databases, and suggests implementation choices that can accommodate a range of applications. The proposal is best characterized as a geographic information system for transportation (GIS-T) enterprise data model suitable for organizations responsible for any and all modes of transportation; e.g. aviation, highways, public transit and railways. The proposed data model may be sufficiently robust to support intelligent transportation systems (ITS) map database interoperability by maintaining independence among the geographic datum, the events that occur on the transportation system, the geometry to represent the system cartographically, and the paths through the system. Sample physical database designs are provided to show how the model might be implemented.
Patient journey for those with chronic low back pain in Brazil: a semi-systematic review on the best approach

Background. Managing patients with chronic low back pain (CLBP) in many countries, including Brazil, is a major challenge at the primary and specialty care level. Moreover, the information about epidemiology and patient management with CLBP is sparse. The primary objective of this semi-systematic review was to build local evidence about the prevalence and management pattern of CLBP. Methods. This semi-systematic review used Medline, Embase, and Biosis via Ovid the platform and additional resources (Google, Google Scholar, Incidence and Prevalence Database, World Health Organization, Brazilian Ministry of Health, and anecdotal information from local experts) to identify relevant literature between 2002–2020 to map the patient journey. Original full-text articles from Brazil in English containing data on pre-defined patient journey touchpoints (awareness, screening, diagnosis, treatment, adherence, and control) were screened. Data were synthesized using a simple or weighted mean, as applicable for patient journey components. Results. Of 297 records including those provided by local experts, eight studies were included for analysis. Awareness of CLBP and CLBP-NeP was 30.4% and 12%, respectively. According to published studies, adherence and symptoms control of patients was estimated with a similar percentage of 38% and 18%, respectively for CLBP and CLBP-NeP. CLBP-NeP prevalence (3.6%) was lower than that of CLBP (20.6%). Except for a comparable percentage of the treated population, for CLBP (39.1%) and CLBP-NeP (38%), the percentage of remaining touchpoints are higher in the case of CLBP than in CLBP-NeP, implying an improved patient journey for CLBP. Conclusion. The study highlights the usefulness to improve patient outcomes at the national level by measuring these mapping patient journey touchpoints. The outcome of this evidence-based study was fruitful to bridges the know-do gap in CLBP patients. Therefore, it is recommended to ensure continuing medical education, patient awareness, and health system preparedness while embracing the emerging insights on pain management.
Morphological description and mitochondrial DNA-based phylogenetic placement of a new species of Callistoctopus Taki, 1964 (Cephalopoda, Octopodidae) from the southeast waters of China

﻿Abstract In this study, we described a new species of octopus and named it Callistoctopusxiaohongxusp. nov. based on nine specimens captured in the waters of southeast China. Callistoctopusxiaohongxusp. nov. is a small to moderate-sized octopus. The most characteristic and defining morphological features are the reddish-orange to reddish-brown skin, gills with 8 or 9 lamellae per demibranch, \∧/-shaped funnel organ, and small suckers. Fragments obtained from the mitochondrial cytochrome c oxidase subunit I (COI) gene of nine specimens were 593 bp in length, and the genetic distance among the specimens of C.xiaohongxusp. nov. and the other 16 octopods ranged from 11.13 to 21.09%. Topologies resulting from ML and BI analyses of the COI gene showed a highly supported monophyletic clade (bootstrap value [BS] = 94%, posterior probability [PP] = 100%) containing all the specimens identified as C.xiaohongxusp. nov.
The Pisot conjecture for $\unicode[STIX]{x1D6FD}$ -substitutions

We prove the Pisot conjecture for $\unicode[STIX]{x1D6FD}$ -substitutions: if $\unicode[STIX]{x1D6FD}$ is a Pisot number, then the tiling dynamical system $(\unicode[STIX]{x1D6FA}_{\unicode[STIX]{x1D713}_{\unicode[STIX]{x1D6FD}}},\mathbb{R})$ associated with the $\unicode[STIX]{x1D6FD}$ -substitution has pure discrete spectrum. As corollaries: (1) arithmetical coding of the hyperbolic solenoidal automorphism associated with the companion matrix of the minimal polynomial of any Pisot number is almost everywhere one-to-one; and (2) all Pisot numbers are weakly finitary.
The Ability of a Novel Trypsin-like Peptidase Activity Assay Kit to Detect Red-Complex Species

The trypsin-like peptidase activity assay kit measures the trypsin-like protease produced by three red-complex species, Porphyromonas gingivalis, Tannerella forsythia, and Treponema denticola, causing periodontitis, and detects the presence of these bacteria in samples. The purpose of this study was to investigate the relationship between the detection of TLPs by a novel TLP-AA, ADCHECK and the detection of red-complex pathogens by real-time PCR using tongue swabs from patients with periodontitis. The detection limit of trypsin-like protease activity by ADCHECK was validated using the culture supernatants of two different Porphyromonas gingivalis bacterial strains. Real-time PCR was performed to determine the number of red-complex species in the tongue coatings of patients with periodontal disease. Trypsin-like protease activity in tongue-swab samples was scored using ADCHECK. ADCHECK successfully detected trypsin-like protease activity in 103 Porphyromonas gingivalis bacterial strains. The specificity, positive predictive value, negative predictive value, and accuracy of ADCHECK for the presence of red-complex pathogens determined by real-time PCR were 90%, 97%, 98%, and 92%, respectively. ADCHECK is an effective tool for the detection of red-complex pathogens.
Bifurcation Synthesis by means of Harmonic Balance and Conversion Matrix

In this paper a new bifurcation synthesis procedure is described. Its foundations are built on an extension of the Conversion Matrix concept, applied to the nonlinear sub network of the circuit simulated through Harmonic Balance. The Cross-frequency Stability Curves (CSC) are defined, which are the nonlinear equivalent of the Stability Circles valid for linear networks. The CSC gives us regions of reflection coefficient values for the loads that yield potential eriod doubling in the circuit. The proposed synthesis method can be used within any simulation program based on the Harmonic Balance algorithm, allowing the designer the possibility to check the nonlinear stability of any simulated circuit, or to design intentionally unstable circuits. Results of the CSC method are given for a GaAs FET circuit synthesized to operate as a divider-by-two.