Miracle-dz/UniFAR-FTUs huggingface dataset:
Fermi polarons at finite temperature: Spectral function and rf spectroscopy

We present a systematic study of a mobile impurity immersed in a three-dimensional Fermi sea of fermions at finite temperature, by using the standard non-self-consistent many-body $T$-matrix theory that is equivalent to a finite-temperature variational approach with the inclusion of one-particle-hole excitation. The impurity spectral function is determined in the real-frequency domain, avoiding any potential errors due to the numerical analytic continuation in previous $T$-matrix calculations and the small spectral broadening parameter used in variational calculations. In the weak-coupling limit, we find that the quasiparticle decay rate of both attractive and repulsive polarons does not increase significantly with increasing temperature, and therefore Fermi polarons may remain well-defined far above Fermi degeneracy. In contrast, near the unitary limit with strong coupling, the decay rate of Fermi polarons rapidly increase and the quasiparticle picture breaks down close to the Fermi temperature. We analyze in detail the recent ejection and injection radio-frequency (rf) spectroscopy measurements, performed at Massachusetts Institute of Technology (MIT) and at European Laboratory for Non-Linear Spectroscopy (LENS), respectively. We show that the momentum average of the spectral function, which is necessary to account for the observed rf-spectroscopy, has a sizable contribution to the width of the quasiparticle peak in spectroscopy. As a result, the measured decay rate of Fermi polarons could be significantly larger than the calculated quasiparticle decay rate at zero momentum. By take this crucial contribution into account, we find that there is a reasonable agreement between theory and experiment for the lifetime of Fermi polarons in the strong-coupling regime, as long as they remain well-defined.
Unsupervised Personalization of an Emotion Recognition System: The Unique Properties of the Externalization of Valence in Speech

The prediction of valence from speech is an important, but challenging problem. The expression of valence in speech has speaker-dependent cues, which contribute to performances that are often significantly lower than the prediction of other emotional attributes such as arousal and dominance. A practical approach to improve valence prediction from speech is to adapt the models to the target speakers in the test set. Adapting a speech emotion recognition (SER) system to a particular speaker is a hard problem, especially with deep neural networks (DNNs), since it requires optimizing millions of parameters. This study proposes an unsupervised approach to address this problem by searching for speakers in the train set with similar acoustic patterns as the speaker in the test set. Speech samples from the selected speakers are used to create the adaptation set. This approach leverages transfer learning using pre-trained models, which are adapted with these speech samples. We propose three alternative adaptation strategies: unique speaker, oversampling and weighting approaches. These methods differ on the use of the adaptation set in the personalization of the valence models. The results demonstrate that a valence prediction model can be efficiently personalized with these unsupervised approaches, leading to relative improvements as high as 13.52%.
Higher symmetries of 5D orbifold SCFTs

We determine the higher symmetries of 5d SCFTs engineered from M-theory on a $\mathbb{C}^3 / \Gamma$ background for $\Gamma$ a finite subgroup of $SU(3)$. This resolves a longstanding question as to how to extract this data when the resulting singularity is non-toric (when $\Gamma$ is non-abelian) and/or not isolated (when the action of $\Gamma$ has fixed loci). The BPS states of the theory are encoded in a 1d quiver quantum mechanics gauge theory which determines the possible 1-form and 2-form symmetries. We also show that this same data can also be extracted by a direct computation of the corresponding defect group associated with the orbifold singularity. Both methods agree, and these computations do not rely on the existence of a resolution of the singularity. We also observe that when the geometry faithfully captures the global 0-form symmetry, the abelianization of $\Gamma$ detects a 2-group structure (when present). As such, this establishes that all of this data is indeed intrinsic to the superconformal fixed point rather than being an emergent property of an IR gauge theory phase.
On the Uniqueness of Kantorovich Potentials

Kantorovich potentials denote the dual solutions of the renowned optimal transportation problem. Uniqueness of these solutions is relevant from both a theoretical and an algorithmic point of view, and has recently emerged as a necessary condition for asymptotic results in the context of statistical and entropic optimal transport. In this work, we challenge the common perception that uniqueness in continuous se ings is reliant on the connectedness of the support of at least one of the involved measures, and we provide mild su cient conditions for uniqueness even when both measures have disconnected support. Since our main nding builds upon the uniqueness of Kantorovich potentials on connected components, we revisit the corresponding arguments and provide generalizations of well-known results. Several auxiliary ndings regarding the continuity of Kantorovich potentials, for example in geodesic spaces, are established along the way.
Molecular phylogeny of Asian Ardisia (Myrsinoideae, Primulaceae) and their leaf-nodulated endosymbionts, Burkholderia s.l. (Burkholderiaceae)

The genus Ardisia (Myrsinoideae, Primulaceae) has 16 subgenera and over 700 accepted names, mainly distributed in tropical Asia and America. The circumscription of Ardisia is not well-defined and sometimes confounded with the separation of some small genera. A taxonomic revision focusing on Ardisia and allies is necessary. In the Ardisia subgenus Crispardisia, symbiotic association with leaf-nodule bacteria is a unique character within the genus. The endosymbionts are vertically transmitted, highly specific and highly dependent on the hosts, suggesting strict cospeciation may have occurred in the evolutionary history. In the present study, we aimed to establish a phylogenetic framework for further taxonomic revision. We also aimed to test the cospeciation hypothesis of the leaf-nodulate Ardisia and their endosymbiotic bacteria. Nuclear ITS and two chloroplast intergenic spaces were used to reconstruct the phylogeny of Asian Ardisia and relatives in Myrsinoideae, Primulaceae. The 16S-23S rRNA were used to reconstruct the bacterial symbionts’ phylogeny. To understand the evolutionary association of the Ardisia and symbionts, topology tests and cophylogenetic analyses were conducted. The molecular phylogeny suggested Ardisia is not monophyletic, unless Sardiria, Hymenandra, Badula and Oncostemum are included. The results suggest the generic limit within Myrsinoideae (Primulaceae) needs to be further revised. The subgenera Crispardisia, Pimelandra, and Stylardisia were supported as monophyly, while the subgenus Bladhia was separated into two distant clades. We proposed to divide the subgenus Bladhia into subgenus Bladhia s.str. and subgenus Odontophylla. Both of the cophylogenetic analyses and topology tests rejected strict cospeciation hypothesis between Ardisia hosts and symbiotic Burkholderia. Cophylogenetic analyses showed general phylogenetic concordance of Ardisia and Burkholderia, and cospeciation events, host-switching events and loss events were all inferred.
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI

The rising popularity of explainable artificial intelligence (XAI) to understand high-performing black boxes raised the question of how to evaluate explanations of machine learning (ML) models. While interpretability and explainability are often presented as a subjectively validated binary property, we consider it a multi-faceted concept. We identify 12 conceptual properties, such as Compactness and Correctness, that should be evaluated for comprehensively assessing the quality of an explanation. Our so-called Co-12 properties serve as categorization scheme for systematically reviewing the evaluation practices of more than 300 papers published in the past 7 years at major AI and ML conferences that introduce an XAI method. We find that one in three papers evaluate exclusively with anecdotal evidence, and one in five papers evaluate with users. This survey also contributes to the call for objective, quantifiable evaluation methods by presenting an extensive overview of quantitative XAI evaluation methods. Our systematic collection of evaluation methods provides researchers and practitioners with concrete tools to thoroughly validate, benchmark, and compare new and existing XAI methods. The Co-12 categorization scheme and our identified evaluation methods open up opportunities to include quantitative metrics as optimization criteria during model training to optimize for accuracy and interpretability simultaneously.
An Information Theory Approach to Network Evolution Models

A novel Markovian network evolution model is introduced and analysed by means of information theory. It will be proved that the model, called network evolution chain, is a stationary and ergodic stochastic process. Therefore, the asymptotic equipartition property can be applied to it. The model’s entropy rate and typical sequences are also explored. Extracting particular information from the network and methods to simulate network evolution in the continuous time domain are discussed. Additionally, the Erdős–Rényi network evolution chain is introduced as a subset of our model with the additional property of its stationary distribution matching the Erdős–Rényi random graph model. The stationary distributions of nodes and graphs are calculated for this subset alongside its entropy rate. The simulation results at the end of the article back up the proved theorems and calculated values.
Planar Cu and O NMR and the Pseudogap of Cuprate Superconductors

Recently, an analysis of all available planar oxygen shift and relaxation data for the cuprate high-temperature superconductors showed that the data can be understood with a simple spin susceptibility from a metallic density of states common to all cuprates. It carries a doping dependent but temperature independent pseudogap at the Fermi surface, which causes the deviations from normal metallic behavior, also in the specific heat. Here, a more coherent, unbiased assessment of all data, including planar Cu, is presented and consequences are discussed, since the planar Cu data were collected and analyzed prior to the O data. The main finding is that the planar Cu shifts for one direction of the external magnetic field largely follow from the same states and pseudogap. This explains the shift suppression stated more recently, which leads to the failure of the Korringa relation in contrast to an enhancement of the relaxation due to antiferromagnetic spin fluctuations originally proposed. However, there is still the need for a second spin component that appears to be associated with the Cu 3d(x2−y2) hole to explain the complex Cu shift anisotropy and family dependence. Furthermore, it is argued that the planar Cu relaxation which was reported recently to be rather ubiquitous for the cuprates, must be related to this universal density of states and the second spin component, while not being affected by the simple pseudogap. Thus, while this universal metallic density of states with a pseudogap is also found in the planar Cu data, there is still need for a more elaborate scenario that eludes planar O.
Physical Constraints on the Extended Interstellar Medium of the z = 6.42 Quasar J1148+5251: [C ii]158 μm, [N ii]205 μm, and [O i]146 μm Observations

We report new Northern Extended Millimeter Array observations of the [C ii]158 μm, [N ii]205 μm, and [O i]146 μm atomic fine structure lines (FSLs) and dust continuum emission of J1148+5251, a z = 6.42 quasar, which probe the physical properties of its interstellar medium (ISM). The radially averaged [C ii]158 μm and dust continuum emission have similar extensions (up to θ=2.51−0.25+0.46arcsec , corresponding to r=9.8−2.1+3.3kpc , accounting for beam convolution), confirming that J1148+5251 is the quasar with the largest [C ii]158 μm-emitting reservoir known at these epochs. Moreover, if the [C ii]158 μm emission is examined only along its NE–SW axis, a significant excess (>5.8σ) of [C ii]158 μm emission (with respect to the dust) is detected. The new wide-bandwidth observations enable us to accurately constrain the continuum emission, and do not statistically require the presence of broad [C ii]158 μm line wings that were reported in previous studies. We also report the first detection of the [O i]146 μm and (tentatively) [N ii]205 μm emission lines in J1148+5251. Using FSL ratios of the [C ii]158 μm, [N ii]205 μm, [O i]146 μm, and previously measured [C i]369 μm emission lines, we show that J1148+5251 has similar ISM conditions compared to lower-redshift (ultra)luminous infrared galaxies. CLOUDY modeling of the FSL ratios excludes X-ray-dominated regions and favors photodissociation regions as the origin of the FSL emission. We find that a high radiation field (103.5–4.5 G 0), a high gas density (n ≃ 103.5–4.5 cm−3), and an H i column density of 1023 cm−2 reproduce the observed FSL ratios well.
Estimation of Conditional Random Coefficient Models using Machine Learning Techniques

Nonparametric random coefficient (RC)-density estimation has mostly been considered in the marginal density case under strict independence of RCs and covariates. This paper deals with the estimation of RCdensities conditional on a (large-dimensional) set of control variables using machine learning techniques. The conditional RC-density allows to disentangle observable from unobservable heterogeneity in partial effects of continuous treatments adding to a growing literature on heterogeneous effect estimation using machine learning. This paper proposes a two-stage sieve estimation procedure. First a closed-form sieve approximation of the conditional RC density is derived where each sieve coefficient can be expressed as conditional expectation function varying with controls. Second, sieve coefficients are estimated with generic machine learning procedures and under appropriate sample splitting rules. The L2-convergence rate of the conditional RC-density estimator is derived. The rate is slower by a factor then typical rates of mean regression machine learning estimators which is due to the ill-posedness of the RC density estimation problem. The performance and applicability of the estimator is illustrated using random forest algorithms over a range of Monte Carlo simulations and with real data from the SOEP-IS. Here behavioral heterogeneity in an economic experiment on portfolio choice is studied. The method reveals two types of behavior in the population, one type complying with economic theory and one not. The assignment to types appears largely based on unobservables not available in the data.
Parallel and distributed Bayesian modelling for analysing high-dimensional spatio-temporal count data

This paper proposes a general procedure to analyse high-dimensional spatio-temporal count data, with special emphasis on relative risks estimation in cancer epidemiology. Model fitting is carried out using integrated nested Laplace approximations over a partition of the spatio-temporal domain. This is a simple idea that works very well in this context as the models are defined to borrow strength locally in space and time, providing reliable risk estimates. Parallel and distributed strategies are proposed to speed up computations in a setting where Bayesian model fitting is generally prohibitively time-consuming and even unfeasible. We evaluate the whole procedure in a simulation study with a twofold objective: to estimate risks accurately and to detect extreme risk areas while avoiding false positives/negatives. We show that our method outperforms classical global models. A real data analysis comparing the global models and the new procedure is also presented.
Boosted Tau Lepton as a Microscope and Macroscope

Anomalies from the LHCb lepton flavour universality and Fermilab muon anomalous magnetic moment show tantalizing hints of possible new physics from the lepton sectors. Due to its large mass and shorter lifetime than muon, the tau lepton is believed to couple more to possible new physics beyond the Standard Model. Traditionally, tau leptons are probed through their decay products due to tau’s short lifetime. On the other hand, at a high energy scale, a large fraction of tau leptons could be boosted to a much longer lifetime and fly a visible distance from several centimetres up to kilometer length scale yet very informative to new physics beyond the standard model or high energy cosmic rays. In this article, we investigate rare, yet promising, tau-physics phenomena, where long-lived taus are exploited either as a microscope (for the measurement of tau’s anomalous magnetic moment to an unprecedented level of accuracy) or as a macroscope (for the detection of 1 TeV to 1 PeV cosmic neutrinos).
GP96 and SMP30 Protein Priming of Dendritic Cell Vaccination Induces a More Potent CTL Response against Hepatoma

Heat-shock protein (HSP) GP96 is a well-known adjuvant in immunotherapy. It belongs to the HSP90 family. Our previous study demonstrated that DC pulsed with recombinant senescence marker protein 30 (SMP30) could induce cytotoxic T lymphocytes (CTLs) against liver cancer cells in vitro. In this study, SMP30 and GP96 were subcloned into lentiviruses and transfected into DCs from healthy donors. We included six groups: the GP96-SMP30 group, GP96 group, SMP30 group, DC group, empty vector control group, and hepatoma extracted protein group. We used ELISA to detect cytokines and flow cytometry to assess CD80 and CD86 on DCs and the effect of CTLs. Our vector design was considered successful and further studied. In the SMP30 group, DC expresses more CCR7 and CD86 than the control group; in the SMP30+GP96 group, DC express more CCR7, CD86, and CD80 than the control group. Transfected DCs secreted more TNF-α and interferon-β and induced more CTLs than control DCs. SMP30 + GP96 effectively stimulated the proliferation of T cells compared with control treatment (P < 0.01). We detected the cytokines TNF-α, TNF-β, IL-12, and IFN (α, β, and γ) via ELISA (Figure 5) and verified the killing effect via FCM. Four E : T ratios (0 : 1, 10 : 1, 20 : 1, and 40 : 1) were tested. The higher the ratio was, the better the effects were. We successfully constructed a liver cancer model and tested the CTL effect in each group. The GP96 + SMP30 group showed a better effect than the other groups. GP96 and SMP30 can stimulate DCs together and produce more potent antitumor effects. Our research may provide a new efficient way to improve the therapeutic effect of DC vaccines in liver cancer.
Is There a Role for Biomarkers in Surveillance of Pancreatic Neuroendocrine Neoplasms in Von Hippel-Lindau Disease?

Abstract Von Hippel-Lindau (VHL) disease is an autosomal dominant disorder characterized by the development of multi-organ neoplasms. Among the manifestations of VHL are pancreatic neuroendocrine neoplasms (panNENs). In order to detect these lesions in a timely manner, patients are enrolled in a surveillance program, in accordance with the several existing VHL guidelines. However, these guidelines remain unclear about the role of biomarkers in diagnosing panNENs, despite the benefits a biomarker may offer regarding early detection of new lesions, thereby possibly limiting radiation exposure, and improving quality of life. The aim is to determine which biomarkers might be available in VHL patients and to assess their clinical relevance in diagnosing panNENs in VHL patients. We searched the databases of PubMed/Medline, Embase, and Web of Science to identify relevant articles. Seven studies assessing the diagnostic or prognostic value of biomarkers were included. The results from these studies were conflicting. Since no evident association between VHL-related panNENs and biomarkers was established in studies with larger study populations, currently biomarkers do not play a significant role in early detection or follow-up for panNENs in VHL patients. The absence of evidence underscores the need for specific research to address this unmet need.
Postabortion Contraceptive Acceptance Rate and Its Determinants among Women Receiving Abortion Service before Discharge from the Health Facilities in Harar, Eastern Ethiopia

Background Annually, around 121 million unintended pregnancies occur in the world and more than 73 million encountered abortion. Ethiopia is also losing 19.6% of mothers due to unsafe abortion. Despite that postabortion contraceptive service is a climactic entry point for the prevention of unwanted pregnancy and associated deaths, the service magnitude and determinants immediately before discharge are not characterized well in Ethiopia. Hence, this study aimed to assess the magnitude of postabortion contraceptive utilization and associated factors among women receiving abortion care service before being discharged from health facilities in Harar, Eastern Ethiopia. Methods A facility-based cross-sectional study was conducted among 390 women receiving abortion care services. At discharge, data about contraceptive acceptance and related maternal characteristics were collected. A binary logistic regression model was used to assess the association between independent and dependent variables (postabortion contraceptive utilization). Analysis was done with SPSS 22. Statistical significance was considered at P < 0.05. Result The overall prevalence of postabortion contraceptive utilization was 81.5% (95% CI: 77.9, 85.4). Being unmarried (AOR, 0.05; 95% CI (0.02, 0.16)), having no history of previous abortion (AOR, 0.11; 95% CI (0.04, 0.34)), being multigravida (AOR 8.1; 95% CI (2.20, 13.40), lacking desire to have an additional child (AOR, 6.3; 95% CI (2.65, 15.34), and history of family planning use (AOR, 17.20; 95% CI (6.5, 38.60)) were determinants of postabortion contraceptive utilization before being discharged from the health facilities. Conclusion Postabortion contraceptive utilization in Harar health facilities still needs improvement as per the WHO and national recommendations. Therefore, the family planning provision strategies should be convincing and friendly, especially for unmarried mothers, and those who had no history of abortion should be counseled in friendly and systematically convincing schemes for enabling them to take the service before discharge from the health facility.