Miracle-dz/UniFAR-FTUs huggingface dataset:
Rotating black holes in the FI-gauged $N=2$, $D=4$ $\overline{\mathbb{C}\text{P}}^n$ model

We construct supersymmetric black holes with rotation or NUT charge for the $\overline{\mathbb{C}\text{P}}^n$- and the $\text{t}^3$ model of $N=2$, $D=4$ $\text{U}(1)$ FI-gauged supergravity. The solutions preserve 2 real supercharges, which are doubled for their near-horizon geometry. For the $\overline{\mathbb{C}\text{P}}^n$ model we also present a generalization to the nonextremal case, which turns out to be characterized by a Carter-Plebanski-type metric, and has $n+3$ independent parameters, corresponding to mass, angular momentum as well as $n+1$ magnetic charges. We discuss the thermodynamics of these solutions, obtain a Christodoulou-Ruffini mass formula, and shew that they obey a first law of thermodynamics and that the product of horizon areas depends on the angular momentum and the magnetic charges only. At least some of the BPS black holes that we obtain may become instrumental for future microscopic entropy computations involving a supersymmetric index.
Hölder-stable recovery of time-dependent electromagnetic potentials appearing in a dynamical anisotropic Schrödinger equation

We consider the inverse problem of Holdder-stably determining the time-and space-dependent coefficients of the Schrodinger equation on a simple Riemannian manifold with boundary of dimension n ≥ 2 from knowledge of the Dirichlet-to-Neumann map. Assuming the divergence of the magnetic potential is known, we show that the electric and magnetic potentials can be Holder-stably recovered from these data. Here we also remove the smallness assumption for the solenoidal part of the magnetic potential present in previous results.
CEPC Conceptual Design Report: Volume 2 - Physics & Detector

The Circular Electron Positron Collider (CEPC) is a large international scientific facility proposed by the Chinese particle physics community to explore the Higgs boson and provide critical tests of the underlying fundamental physics principles of the Standard Model that might reveal new physics. The CEPC, to be hosted in China in a circular underground tunnel of approximately 100 km in circumference, is designed to operate as a Higgs factory producing electron-positron collisions with a center-of-mass energy of 240 GeV. The collider will also operate at around 91.2 GeV, as a Z factory, and at the WW production threshold (around 160 GeV). The CEPC will produce close to one trillion Z bosons, 100 million W bosons and over one million Higgs bosons. The vast amount of bottom quarks, charm quarks and tau-leptons produced in the decays of the Z bosons also makes the CEPC an effective B-factory and tau-charm factory. The CEPC will have two interaction points where two large detectors will be located. This document is the second volume of the CEPC Conceptual Design Report (CDR). It presents the physics case for the CEPC, describes conceptual designs of possible detectors and their technological options, highlights the expected detector and physics performance, and discusses future plans for detector R&D and physics investigations. The final CEPC detectors will be proposed and built by international collaborations but they are likely to be composed of the detector technologies included in the conceptual designs described in this document. A separate volume, Volume I, recently released, describes the design of the CEPC accelerator complex, its associated civil engineering, and strategic alternative scenarios.
A Novel Projection: Towards a Deeper Understanding of Mathematical Structures in the Composite Fermion Formalism

Composite fermion (CF) wave functions are used to describe both a two dimensional electron gas in a strong magnetic field (the quantum Hall effect system) and rotating two dimensional atomic gases that can be either bosons or fermions. In this thesis a new method for projecting fermionic CF wave functions (here called method 3) to the lowest Landau level is investigated. The new projection is based on attaching a Jastrow factor to a bosonic CF wave function projected in the standard way. This will be compared to two other projection methods: method 1 or Girvin-Jach projection and method 2 or Jain-Kamilla projection. I compare the minimal cyclotron energy compact CF ground state candidates for the ∇2δ interaction both to each other and to the exact ground state found by numerical diagonalization for up to 8 particles. The conclusion is that the CF candidates typically are good approximations of the exact ground state, and that method 3 is almost as good as the other two at this. An important motivation for method 3 is that it preserves linear dependencies from the bosonic states. The puzzle of linear dependencies is a part of CF theory that is not properly understood. Certain important results for low angular momentum states have been found for the bosonic case. Since method 3 works quite well in the cases tested here some of these results can be imported to the fermionic case. I have compared the linear dependencies among minimal cyclotron energy compact states for all three projection methods. If approximate linear dependencies are considered as proper linear dependencies then for all tested cases the same linear dependencies hold for all three projection methods, up to slightly different coefficients.
Ultrawideband Anisotropic Glide-Symmetric Metasurfaces

This letter presents a method to realize anisotropic two-dimensional designs with wideband operation. Glide symmetry has been proven to increase the bandwidth and equivalent refractive index of periodic structures. Here, two anisotropic glide-symmetric unit cells are proposed and characterized. Our simulated results prove that these unit cells follow the general behavior of periodic structures possessing glide symmetry. Moreover, we demonstrate that higher level of anisotropy can also be achieved by glide symmetry. Combining our proposed anisotropic glide-symmetric unit cell and transformation optics, a $\text{30}\%$ compressed Luneburg lens is designed. The lens operates from 1 to 13 GHz.
Projected shrinkage algorithm for box-constrained L1-minimization

Box-constrained L1-minimization can perform remarkably better than classical L1-minimization when correction box constraints are available. And also many practical L1-minimization models indeed involve box constraints because they take certain values from some interval. In this paper, we propose an efficient iteration scheme, namely projected shrinkage (ProShrink) algorithm, to solve a class of box-constrained L1-minimization problems. A key contribution in our technique is that a complicated proximal point operator appeared in the deduction can be equivalently simplified into a projected shrinkage operator. Theoretically, we prove that ProShrink enjoys a convergence of both the primal and dual point sequences. On the numerical level, we demonstrate the benefit of adding box constraints via sparse recovery experiments.
Frequency Domain Estimation of Continuous Time Cointegrated Models with Mixed Frequency and Mixed Sample Data

Recent work by the author on mixed frequency data analysis has focused on the estimation of cointegrated systems in continuous time based on a fully specified dynamic system of equations, while the estimation of cointegrating vectors in a discrete time system has been approached using a semiparametric frequency domain estimator. We extend the latter approach to cover the continuous time case, establishing the asymptotic properties of the frequency domain estimator and explore, in a simulation study, the effects of misspecifying the continuous time dynamic model in discrete time compared to treating the dynamics non‐parametrically. An empirical illustration is also provided.
Towards the design of low-noise aircraft landing gears using the lattice Boltzmann method

In this project, numerical simulation tools were used to investigate the feasibility of using computational fluid dynamics for the design of low-noise airplane landing gears. Fluid flow simulations were performed using a commercially available code based on the lattice Boltzmann method. Far field sound predictions were obtained using an acoustic analogy based on the Ffowcs-Williams Hawkings equation. Aerodynamic and acoustic results were verified through comparisons with experimental results from wind tunnel testing.The benchmark case of flow past tandem cylinders was first studied to verify the numerical tools for a canonical problem with basic noise generation mechanisms similar to those of landing gear. A boundary layer trip used in the experimental wind tunnel tests resulted in high Reynolds number effects including delayed flow separation and an increased vortex shedding frequency. Several techniques were investigated to simulate the effects of the boundary layer trip. It was found that reducing the viscosity of the simulated fluid yielded the best agreement between numerical and experimental results.A second benchmark case consisting of flow past a rudimentary four-wheel landing gear was studied. Surface pressure fluctuation levels near flow separation locations tended to be under-predicted, particularly at higher frequencies. However, in locations with fully separated flow where surface pressure fluctuations were highest, ￼there was good agreement with experiment. The far field noise predictions were in good agreement with experimental noise measurements.The noise emissions from flow past a fully dressed two-wheel main landing gear were then investigated. A good correlation between simulation and experimental results helped to establish the numerical tools’ ability to handle complex realistic geometries. Microphone array sound measurements from experiment and spectral analysis of predicted surface pressure fluctuations were used to identify noise sources on the fully dressed landing gear. They were located primarily along the main strut and piston, downstream of the light and torque arms. A simulation was performed using the fully dressed landing gear with the light removed. The absolute changes in acoustic signature were not consistently well-predicted. However, there was good agreement between simulation and experiment on the change in overall sound pressure levels. %%%%Ce travail presente une etude de faisabilite sur l’application de l’aeroacoustique numerique pour les trains d’atterrissage. Un code de calcul base sur la methode de Boltzmann sur reseau disponible commercialement a ete utilise. Le bruit en champ lointain a ete predit en utilisant une analogie acoustique basee sur l’equation de Ffowcs-Williams et Hawkings. Les resultats aerodynamiques et acoustiques numeriques ont ete compares a des resultats experimentaux obtenus en soufflerie.En premier lieu, le bruit provenant de l’ecoulement autour de deux cylindres paralleles a ete etudie pour valider les outils numeriques sur une geometrie simple dont…
A statistical framework for modeling asthma and COPD biological heterogeneity, and a novel variable selection method for model-based clustering

This thesis has two main parts. The first part is an application that focuses on the identification of a statistical framework to model the biological heterogeneity of asthma and COPD using sputum cytokines. Clustering subjects using the actual cytokines measurements may not be straightforward as these mediators have strong correlations, which are currently ignored by standard clustering techniques. Artificial data, which have similar patterns as the cytokines, but with known class membership, are simulated. Several approaches, such as data reduction using factor analysis, were performed on the simulated data to identify suitable representative of the variables and to use as input into clustering algorithm. In the simulation study, using ”factor-scores” (derived from factor analysis) as input variables into clustering outperformed the alternative approaches. Thus, this approach was applied to model the biological heterogeneity of asthma and COPD, and identified three stable and three exacerbation clusters, with different proportions of overlap between the diseases. The second part is a statistical methodology in which a new method for variable selection in model-based clustering was proposed. This method generalizes the approach of Raftery and Dean (2006, JASA 101, 168-178). It relaxes the global prior assumptions of linear-relationships between clustering relevant and irrelevant variables by searching for latent structures among the variables, and accounts for nonlinear relationships between these variables by splitting the data into sub-samples. A Gaussian mixture model (unconstrained variance-covariance matrices fitted using the EM-algorithm) is applied to identify the optimal clusters. The new method performed considerably better than the Raftery and Dean technique when applied to simulated and real datasets, and demonstrates that variable selection within clustering can substantially improve the identification of optimal clusters. However, at the moment it perhaps does not perform adequately in uncovering the optimal clusters in the dataset which have strong correlations such as sputum mediators.
Real-world effectiveness and persistence of reference etanercept versus biosimilar etanercept GP2015 among rheumatoid arthritis patients: A cohort study

Although several randomized clinical trials have confirmed that there is no difference in efficacy between etanercept and its biosimilar versions in the treatment of rheumatoid arthritis (RA), limited real-world evidence is available. We conducted a cohort study to compare the effectiveness and treatment persistence between the reference etanercept (ETN) and the biosimilar GP2015 in RA patients in a real-life setting. Adults with a diagnosis of RA who initiated treatment with ETN or GP2015, between January 2007 and December 2019, were included. The follow-up period was 52 weeks. The primary outcome was the mean of change in the DAS28-CRP values and the adjusted mean difference from baseline to 52 weeks between ETN and GP2015. Other effectiveness endpoints assessed were the rate of patients who achieved remission or low disease activity (LDA) at week 52, who showed a reduction of DAS28-CRP value greater than or equal to 1.2 from baseline to week 52 and rate of good responder patients (those meeting both effectiveness measures) at week 52. Treatment effectiveness over time (baseline, 26 and 52 weeks) was compared between the ETN and GP2015 groups using mixed effects models. Treatment persistence (probability of maintaining the same treatment over time) was also evaluated and shown using Kaplan–Meier survival curves. A total of 115 RA patients were included (ETN, n = 90; GP2015, n = 25). No differences were observed in the primary outcome: DAS28-CRP score decreased from baseline to week 52 [5.1 to 2.7 (mean of change -2.37) in ETN group and 5.0 to 2.2 (mean of change -2.84) in GP2015 group, p-value = 0.372] and the adjusted mean difference was −0.37 (−1.03 to 0.29). No differences were also observed in the other effectiveness endpoints assessed among patients treated with ETN or GP2015: rate of patients who achieved remission (54.1% vs. 66.7%, p-value = 0.303) and LDA (71.6% vs. 80.9%, p-value = 0.391) at week 52, reduction of DAS28-CRP value greater than or equal to 1.2 from baseline to week 52 (75.6% vs. 80.9%, p-value = 0.613) and rate of good responder patients (58.1% vs. 76.1%, p-value = 0.202). Drug survival was 82% and 80% for ETN and GP2015, respectively (log-rank p-value = 0.804). Etanercept and its biosimilar GP2015 show similar effectiveness and treatment persistence in RA patients in a real-life setting.
Pomalidomide Treatment in Relapsed/Refractory Multiple Myeloma Patients—Real-World Data From Hungary

Pomalidomide is a third generation immunomodulatory drug in the treatment of refractory and relapsed multiple myeloma patients. Our aim was to investigate the efficacy and safety of pomalidomide therapy in a real world setting. Eighty-six Hungarian patients were included, 45 of whom received pomalidomide ± an alkylating agent, while in 38 of them pomalidomide was combined with a proteasome inhibitor. 56 patients (65%) showed any response to the treatment with 18 complete or very good partial remissions and 38 partial remissions. At a median duration of follow-up of 18.6 months, the median progression-free survival (PFS) was 9.03 months, while the median overall survival (OS) was 16.53 months in the whole cohort. Patients with early stage disease (R-ISS 1 and 2) had better survival results than those with stage 3 myeloma (p = 0.002). Neither the number of prior treatment lines, nor lenalidomide refractoriness had a significant impact on PFS. PFS was found similar between the cohort of patients with impaired renal function and the cohort without kidney involvement. During the study, eight mortal infections and two fatal bleeding complications occurred, however, mild hematologic and gastrointestinal toxicities were identified as the most frequent adverse events. The results of our investigations confirm that pomalidomide is an effective treatment option for relapsed/refractory MM, besides, the safety profile is satisfactory in subjects with both normal and impaired renal function.
Mathematics of Statistical Sequential Decision Making

In this document, we give an overview of recent contributions to the mathematics of statistical sequential learning. Unlike research articles that start from a motivating example and provide little room to the mathematical tools in the main body of the article, we here give primary focus to these tools, in order to stress their potential as well as their role in the development of improved algorithms and proof techniques in the field. We revisit in particular properties of the log Laplace transform of a random variable, the handling of random stopping time in concentration of measure of empirical distributions, and we highlight the fundamental role of the “change of measure” argument both in the construction of performance lower-bounds as well as near-optimal strategies. We then give focus to obtaining finite-time error guarantees on the parameter estimation in parametric models before highlighting the strength of Legendre-Fenchel duality in the design of risk-averse and robust strategies. Finally, we turn the setting of Markov decision processes where we present some key insights for the development of the next generation of decision strategies. We end this manuscript by providing a more focused presentation of three key contributions in bandit theory, stochastic automata, and aggregation of experts
Influence of pitch rate on freely translating perching airfoils

We numerically investigated the unsteady dynamics of a two-dimensional airfoil undergoing a continuous, prescribed pitch-up motion and freely translating as a response to aerodynamic forces and the gravity field. The pitch-up motion was applied about an axis located $1/6$ chord away from the leading edge and was parameterized using the shape change number, with a Reynolds number set to 2000. It was shown that the minimum kinetic energy reached by the airfoil depends stochastically and asymptotically on shape change numbers for values below and above 1, respectively. Very low kinetic energy levels (close to zero) can be reached in both stochastic and asymptotic regions but high shape change numbers are accompanied by significant gain in altitude which may be undesirable from a practical perspective. Rather, shape change numbers in the range [0.1–0.3] allow us to reach relatively low levels of kinetic energy for close perching locations. We showed that highly nonlinear fluid–structure interactions induced by massive flow separations and strong vortices are conducive to low kinetic energy, but responsible for the stochastic dependence of kinetic energy to shape change number, which can make perching manoeuvres hardly controllable for flying vehicles.
Comparative study on the microbiota of colostrum and nipple skin from lactating mothers separated from their newborn at birth in China

Increasing studies have found breast milk (BM) contains its own microbiota. However, the route through which microbes enter the BM is still unclear. In order to verify the entero-mammary pathway of BM, we designed a rigorous study that prevented oral bacteria from contaminating the breast and nipple skin (NS) during baby nursing. Thirty-one healthy, postpartum mothers living in southern China who were immediately separated from their newborn after delivery were enrolled in this study. Using an aseptic protocol for sampling, sterile water was used to wash the NS and was then collected. Then the first drop of BM was discarded and colostrum was collected manually. Amplicon sequencing was performed targeting the V3–V4 region of the bacterial 16S rRNA gene, and the differences between the microbiota of the colostrum and NS were analyzed. Additionally, the effects of environmental factors, such as the delivery mode and intrapartum antibiotic exposure, on the diversity of the colostrum microbiota were also analyzed. We found significant differences in the α diversity and richness between the BM and NS as evidenced by richness, Chao1, and Simpson indices. There were 170 operational taxonomic units (OTUs) shared by colostrum and NS, while 111 and 87 OTUs were unique, respectively, as well as a clear distinction in OTUs was observed by unifrac binary analysis between them. Linear discriminant analysis effect size analysis found that anaerobes, such as Bifidobacterium and Pantoea at the genus level and enterobacteria including Enterobacteriaceae at the family level, were predominant in the colostrum, while the predominant bacteria on the NS were Bacteroides, Staphylococcus, and Parabacteroides at the genus level. BM is colonized by bacteria prior to baby suckling, and the diversity of the colostrum microbiota differs from that of the NS. The predominant microbiota taxa in BM indicated that they were likely to be transferred to the breast through the intestinal tract. Our study provides direct evidence for the revolutionary active migration hypothesis. Additionally, factors like intrapartum antibiotic exposure did not significantly affect the diversity of the microbiota in the BM. Therefore, it is suggested that mothers continue to provide BM for their newborns during separation.
Semantically Guided Evolution of $\mathcal{SHI}$ ABoxes

This paper presents a method for the evolution of SHI ABoxes which is based on a compilation technique of the knowledge base. For this the ABox is regarded as an interpretation of the TBox which is close to a model. It is shown, that the ABox can be used for a semantically guided transformation resulting in an equisatisfiable knowledge base. We use the result of this transformation to efficiently delete assertions from the ABox. Furthermore, insertion of assertions as well as repair of inconsistent ABoxes is addressed. For the computation of the necessary actions for deletion, insertion and repair, the E-KRHyper theorem prover is used.
A significant wave height prediction method based on deep learning combining the correlation between wind and wind waves

Accurate wave height prediction is significant in ports, energy, fisheries, and other offshore operations. In this study, a regional significant wave height prediction model with a high spatial and temporal resolution is proposed based on the ConvLSTM algorithm. The model learns the intrinsic correlations of the data generated by the numerical model, making it possible to combine the correlations between wind and wind waves to improve the predictions. In addition, this study also optimizes the long-term prediction ability of the model through the proposed Mask method and Replace mechanism. The experimental results show that the introduction of the wind field can significantly improve the significant wave height prediction results. The research on the prediction effect of the entire study area and two separate stations shows that the prediction performance of the proposed model is better than the existing methods. The model makes full use of the physical correlation between wind and wind waves, and the validity is up to 24 hours. The 24-hour forecast R² reached 0.69.