Miracle-dz/UniFAR-FTUs huggingface dataset:
Correct Approximation of Stationary Distributions

A classical problem for Markov chains is determining their stationary (or steady-state) distribution. This problem has an equally classical solution based on eigenvectors and linear equation systems. However, this approach does not scale to large instances, and iterative solutions are desirable. It turns out that a naive approach, as used by current model checkers, may yield completely wrong results. We present a new approach, which utilizes recent advances in partial exploration and mean payoff computation to obtain a correct, converging approximation.
New Metrics to Encourage Innovation and Diversity in Information Retrieval Approaches

In evaluation campaigns, participants often explore variations of popular, state-of-the-art baselines as a low-risk strategy to achieve competitive results. While effective, this can lead to local"hill climbing"rather than more radical and innovative departure from standard methods. Moreover, if many participants build on similar baselines, the overall diversity of approaches considered may be limited. In this work, we propose a new class of IR evaluation metrics intended to promote greater diversity of approaches in evaluation campaigns. Whereas traditional IR metrics focus on user experience, our two"innovation"metrics instead reward exploration of more divergent, higher-risk strategies finding relevant documents missed by other systems. Experiments on four TREC collections show that our metrics do change system rankings by rewarding systems that find such rare, relevant documents. This result is further supported by a controlled, synthetic data experiment, and a qualitative analysis. In addition, we show that our metrics achieve higher evaluation stability and discriminative power than the standard metrics we modify. To support reproducibility, we share our source code.
N2H+ in the Orion ambient ridge : cloud clumping versus rotation

The IRAM 30-m telescope is used to obtain spectra of the J = 1 yields 0 transition of N2H(+) over a 2 x 2 arcsec area toward the Orion-KL/IRc2 star-forming region with 26-arcsec angular resolution. The N2H(+) emission, which exclusively traces the ridge gas, exhibits multiple radial velocities which appear to arise from the presence of at least four clouds of quiescent material. It is argued that the velocity structure of N2H(+) does not uniformly change across OMC-1 and, consequently, is inconsistent with the presence of large-scale differential rotation of the extended ridge along the SW-NE axis about IRc2. The coincidence of the two larger clouds with star-forming activity in Orion-KL suggests that either the quiescent gas is being pushed apart or that the star formation may have been triggered by a cloud-cloud interaction.
A Nonstochastic Control Approach to Optimization

Selecting the best hyperparameters for a particular optimization instance, such as the learning rate and momentum, is an important but nonconvex problem. As a result, iterative optimization methods such as hypergradient descent lack global optimality guarantees in general. We propose an online nonstochastic control methodology for mathematical optimization. First, we formalize the setting of meta-optimization, an online learning formulation of learning the best optimization algorithm from a class of methods. The meta-optimization problem over gradient-based methods can be framed as a feedback control problem over the choice of hyperparameters, including the learning rate, momentum, and the preconditioner. Although the original optimal control problem is nonconvex, we show how recent methods from online nonstochastic control using convex relaxations can be used to overcome the challenge of nonconvexity, and obtain regret guarantees against the best offline solution. This guarantees that in meta-optimization, given a sequence of optimization problems, we can learn a method that attains convergence comparable to that of the best optimization method in hindsight from a class of methods.
Position Regression for Unsupervised Anomaly Detection

In recent years, anomaly detection has become an essential field in medical image analysis. Most current anomaly detection methods for medical images are based on image reconstruction. In this work, we propose a novel anomaly detection approach based on coordinate regression. Our method estimates the position of patches within a volume, and is trained only on data of healthy subjects. During inference, we can detect and localize anomalies by considering the error of the position estimate of a given patch. We apply our method to 3D CT volumes and evaluate it on patients with intracranial haemorrhages and cranial fractures. The results show that our method performs well in detecting these anomalies. Furthermore, we show that our method requires less memory than comparable approaches that involve image reconstruction. This is highly relevant for processing large 3D volumes, for instance, CT or MRI scans.
SpotHitPy: A Study For ML-Based Song Hit Prediction Using Spotify

In this study, we approached the Hit Song Prediction problem, which aims to predict which songs will become Billboard hits. We gathered a dataset of nearly 18500 hit and non-hit songs and extracted their audio features using the Spotify Web API. We test four machine-learning models on our dataset. We were able to predict the Billboard success of a song with approximately 86\% accuracy. The most succesful algorithms were Random Forest and Support Vector Machine.
The Inner 2 pc of Sagittarius A*: Simulations of the Circumnuclear Disk and Multiphase Gas Accretion in the Galactic Center

The inner few parsecs of the Milky Way’s Galactic center contain the central accreting supermassive black hole, over a million stars, and multiple large gaseous structures. In the past, the structures at these length scales have generally been modeled independently of each other. It is consequently not well understood how these complex features interact with each other, nor how gas flows between the outer few parsecs and the inner subarcsecond region (1″ ≈ 0.04 pc). In this work, we present hydrodynamic simulations of the inner few parsecs of the Galactic center that, for the first time, combine a realistic treatment of stellar winds and the circumnuclear disk (CND) as they interact with the gravitational potential of the nuclear star cluster and Sagittarius A*. We observe interactions of the stellar winds with the inner edge of the CND, which leads to the growth of instabilities, induced accretion of cool gas from the inner edge of the disk, and the eventual formation of a small accretion disk of ∼104–105 K within r ∼ 0.1 pc. The formation of an inner disk qualitatively agrees with observations. This disk grows in radial extent and mass with time on ≳10 kyr timescales, with a growth rate of M∝tkyr3.5 . We discuss additional physical mechanisms not yet included in this work that can improve our model.
Core-envelope Decoupling Drives Radial Shear Dynamos in Cool Stars

Differential rotation is thought to be responsible for the dynamo process in stars like our Sun, driving magnetic activity and starspots. We report that starspot measurements in the Praesepe open cluster are strongly enhanced only for stars that depart from standard models of rotational evolution. A decoupling of the spin-down history between the core and envelope explains both the activity and rotation anomalies: surface rotational evolution is stalled by interior angular momentum redistribution, and the resultant radial shears enhance starspot activity. These anomalies provide evidence for an evolving front of shear-enhanced activity affecting the magnetic and rotational evolution of cool stars and the high-energy environments of their planetary companions for hundreds of millions to billions of years on the main sequence.
Temporal Motifs for Financial Networks: A Study on Mercari, JPMC, and Venmo Platforms

Understanding the dynamics of financial transactions among people is critically important for various applications such as fraud detection. One important aspect of financial transaction networks is temporality. The order and repetition of transactions can offer new insights when considered within the graph structure. Temporal motifs, defined as a set of nodes that interact with each other in a short time period, are a promising tool in this context. In this work, we study three unique temporal financial networks: transactions in Mercari, an online marketplace, payments in a synthetic network generated by J.P. Morgan Chase, and payments and friendships among Venmo users. We consider the fraud detection problem on the Mercari and J.P. Morgan Chase networks, for which the ground truth is available. We show that temporal motifs offer superior performance than a previous method that considers simple graph features. For the Venmo network, we investigate the interplay between financial and social relations on three tasks: friendship prediction, vendor identification, and analysis of temporal cycles. For friendship prediction, temporal motifs yield better results than general heuristics, such as Jaccard and Adamic-Adar measures. We are also able to identify vendors with high accuracy and observe interesting patterns in rare motifs, like temporal cycles. We believe that the analysis, datasets, and lessons from this work will be beneficial for future research on financial transaction networks.
Au-coated tilted fiber Bragg grating twist sensor based on surface plasmon resonance

A fiber twist sensor based on the surface plasmon resonance (SPR) effect of an Au-coated tilted fiber Bragg grating (TFBG) is proposed. The SPR response to the twist effect on an Au-coated TFBG (immersing in distilled water) is studied theoretically and experimentally. The results show that the transmission power around the wavelength of SPR changes with the twist angle. For the twist ranging from 0° to 180° in clockwise or anti-clockwise directions, the proposed sensor shows sensitivities of 0.037 dBm/° (S-polarized) and 0.039 dBm/° (P-polarized), which are almost 7.5 times higher than that of the current similar existing twist sensor.
VLBI and X-ray observations of compact nuclei in pairs of galaxies

Five pairs of isolated pairs of galaxies with radio sources from the sample of Stocke et al. (1978) were observed with a three-element VLBI array operating at 4996 MHz. Parsec-scale components were detected in NGC 3894, Arp 102, and NGC 6500. Arp 102B was found to be a strong X-ray source with a luminosity in the 0.5-4.5 keV band of about 10 to the 43rd ergs/sec. Arp 102B was also found to be an elliptical galaxy for which no emission lines have been reported, and was the only source in the sample which appeared unresolved on the milli-arcsec scale, indicating that it may be related to BL Lac type objects.
On invariant means and pre-syndetic subgroups

Beyond the locally compact case, equivalent notions of amenability diverge, and some properties no longer hold, for instance amenability is not inherited by topological subgroups. This investigation is guided by some amenability-type properties of groups of paths and loops. It is shown that a version of amenability called skew-amenability is inherited by pre-syndetic subgroups in the sense of Basso and Zucker (in particular, by co-compact subgroups). It follows that co-compact subgroups of amenable topological groups whose left and right uniformities coincide are amenable. We discuss a version of amenability belonging to P. Malliavin and M. -P. Malliavin: the existence of a mean on bounded Borel functions that is invariant under the left action of a dense subgroup. We observe that this property is in general strictly stronger than amenability, and establish for it Reiter- and F{\o}lner-type criteria. Finally, there is a review of open problems.
Heterogeneous biological membranes regulate protein partitioning via fluctuating diffusivity

Abstract Cell membranes phase separate into ordered Lo and disordered Ld domains depending on their compositions. This membrane compartmentalization is heterogeneous and regulates the localization of specific proteins related to cell signaling and trafficking. However, it is unclear how the heterogeneity of the membranes affects the diffusion and localization of proteins in Lo and Ld domains. Here, using Langevin dynamics simulations coupled with the phase-field (LDPF) method, we investigate several tens of milliseconds-scale diffusion and localization of proteins in heterogeneous biological membrane models showing phase separation into Lo and Ld domains. The diffusivity of proteins exhibits temporal fluctuations depending on the field composition. Increases in molecular concentrations and domain preference of the molecule induce subdiffusive behavior due to molecular collisions by crowding and confinement effects, respectively. Moreover, we quantitatively demonstrate that the protein partitioning into the Lo domain is determined by the difference in molecular diffusivity between domains, molecular preference of domain, and molecular concentration. These results pave the way for understanding how biological reactions caused by molecular partitioning may be controlled in heterogeneous media. Moreover, the methodology proposed here is applicable not only to biological membrane systems but also to the study of diffusion and localization phenomena of molecules in various heterogeneous systems.
Booster: A Benchmark for Depth From Images of Specular and Transparent Surfaces

Estimating depth from images nowadays yields outstanding results, both in terms of in-domain accuracy and generalization. However, we identify two main challenges that remain open in this field: dealing with non-Lambertian materials and effectively processing high-resolution images. Purposely, we propose a novel dataset that includes accurate and dense ground-truth labels at high resolution, featuring scenes containing several specular and transparent surfaces. Our acquisition pipeline leverages a novel deep space-time stereo framework, enabling easy and accurate labeling with sub-pixel precision. The dataset is composed of 606 samples collected in 85 different scenes, each sample includes both a high-resolution pair (12 Mpx) as well as an unbalanced stereo pair (Left: 12 Mpx, Right: 1.1 Mpx), typical of modern mobile devices that mount sensors with different resolutions. Additionally, we provide manually annotated material segmentation masks and 15 K unlabeled samples. The dataset is composed of a train set and two test sets, the latter devoted to the evaluation of stereo and monocular depth estimation networks. Our experiments highlight the open challenges and future research directions in this field.
InGaN/GaN quantum dots as optical probes for the electric field at the GaN/electrolyte interface

We investigated the electric-field dependence of the photoluminescence-emission properties of InGaN/GaN quantum dot multilayers in contact with an electrolyte. Controlled variations of the surface potential were achieved by the application of external electric fields using the electrolytic Schottky contact and by variation of the solution's pH value. Prior to characterization, a selective electrochemical passivation process was required to suppress leakage currents. The quantum dot luminescence is strongly affected by surface potential variations, i.e., it increases exponentially with cathodic bias and acidic pH values. The results cannot be explained by a modification of intra-dot polarization induced electric fields via the quantum confined Stark effect but are attributed to the suppression/enhancement of non-radiative recombination processes, i.e., mainly hole transfer into the electrolyte. The results establish a link between the photoluminescence intensity and the magnitude of electric fields at the .
Fixed-point iterative algorithm for SVI model

The stochastic volatility inspired (SVI) model is widely used to ﬁt the implied variance smile. Presently, most optimizer algorithms for the SVI model have a strong dependence on the input starting point. In this study, we develop an e ﬃ cient iterative algorithm for the SVI model based on a ﬁxed-point and least-square optimizer. Furthermore, we present the convergence results in certain situations for this novel iterative algorithm. Compared with the quasi-explicit SVI method, we demonstrate the advantages of the ﬁxed-point iterative algorithm using simulation and market data.
Mass renormalizations and superconductivity in heavy-fermion UPt3.

The Eliashberg equations for magnetic fluctuations are solved for the case of UPt/sub 3/. As input, the neutron data of Aeppli et al. are used for the spectral function, and the results of band-structure calculations are used to model the Fermi surface. The results indicate a mass renormalization factor of about 16, a value confirmed by comparisons of band calculations to de Haas--van Alphen data. Moreover, a superconducting transition temperature of the order of 0.1--0.2 K is calculated (due to the momentum dependence of the susceptibility) with polar gaps in parts of the zone.
Evidence of near‐ultraviolet emission during electrical‐tree initiation in polyethylene

The spectra of light emitted during electrical‐tree initiation in low‐density polyethylene used in high‐voltage cables were investigated. Light in the visible and in the near‐ultraviolet range was detected. Low‐density polyethylene subjected to highly divergent fields at voltages below the light‐inception level did not develop an electrical tree, and it is suggested that the light‐inception voltage is the threshold for insulation degradation. The ultraviolet light emitted at voltages above the light‐inception level could cause degradation of the polymer. A model is proposed to explain the mechanism of electroluminescence. Ultraviolet stabilizers added to the polymer prolonged the time to electrical‐tree initiation by preventing photodegradation of the polymer.
Relative populations for levels in the 3d2 ground configuration of Fe VII

R-matrix calculations of electron impact excitation rates in Fe VII are used to derive relative populations for all levels in the 3d 2 ground configuration. Results are presented for a wide range of electron temperatures (800 ≤ T e ≤ 120000 K) and densities (10 4 ≤ N e ≤ 10 10 cm -3 ) applicable to astrophysical plasmas. The calculations are used in conjunction with observed emission-line ratios for the planetary nebula NGC 7027 to derive the electron temperature of the Fe VII-emitting region, which is found to be in good agreement with the values of T e deduced from other ionized species in the planetary.
Decision-making processes for essential packages of health services: experience from six countries

Many countries around the world strive for universal health coverage, and an essential packages of health services (EPHS) is a central policy instrument for countries to achieve this. It defines the coverage of services that are made available, as well as the proportion of the costs that are covered from different financial schemes and who can receive these services. This paper reports on the development of an analytical framework on the decision-making process of EPHS revision, and the review of practices of six countries (Afghanistan, Ethiopia, Pakistan, Somalia, Sudan and Zanzibar-Tanzania). The analytical framework distinguishes the practical organisation, fairness and institutionalisation of decision-making processes. The review shows that countries: (1) largely follow a similar practical stepwise process but differ in their implementation of some steps, such as the choice of decision criteria; (2) promote fairness in their EPHS process by involving a range of stakeholders, which in the case of Zanzibar included patients and community members; (3) are transparent in terms of at least some of the steps of their decision-making process and (4) in terms of institutionalisation, express a high degree of political will for ongoing EPHS revision with almost all countries having a designated governing institute for EPHS revision. We advise countries to organise meaningful stakeholder involvement and foster the transparency of the decision-making process, as these are key to fairness in decision-making. We also recommend countries to take steps towards the institutionalisation of their EPHS revision process.
Ionospheric constraints on VHF/UHF communications links during solar maximum and minimum periods

An extensive VHF/UHF scintillation data base covering the frequency range of VHF to a few gigahertz was utilized to determine the magnitudes of phase and intensity scintillations and their temporal/spatial structures during the sunspot maximum and minimum periods. The equatorial portion of the study was based on geostationary satellite observations at Huancayo, a station on the magnetic equator, and at Ascension Island, which is an equatorial anomaly station having an extremely disturbed irregularity environment. The high-latitude part of the study is based on quasi-stationary satellite measurements at a polar cap location (Thule) and two auroral locations (Goose Bay and Tromso). The Tromso observations are augmented with the Defense Nuclear Agency HiLatsatellite beacon measurements during the solar-minimum period. The data indicate a strong solar cycle control of scintillation activity at all locations, resulting in a drastic reduction of the magnitudes and occurrence of scintillations during the current solar-minimum period. This pattern is consistent with both a reduction of F region ionization density and a reduction of irregularity generation in the solar-minimum period. At the magnetic equator the magnitude of scintillations at 1.5 GHz seldom exceeds 3 dB with the percentage occurrence > 2 dB varying from 70% during high sunspot conditionsmore » to 30% during low sunspot conditions. At the crest of the equatorial anomaly, on the other hand, during the solar maximum in 1979, fades of 20 dB at 1.5 GHz are observed 30% of the time. « less
Metabolomics analysis unveils important changes involved in the salt tolerance of Salicornia europaea

Salicornia europaea is one of the world’s salt-tolerant plant species and is recognized as a model plant for studying the metabolism and molecular mechanisms of halophytes under salinity. To investigate the metabolic responses to salinity stress in S. europaea, this study performed a widely targeted metabolomic analysis after analyzing the physiological characteristics of plants exposed to various NaCl treatments. S. europaea exhibited excellent salt tolerance and could withstand extremely high NaCl concentrations, while lower NaCl conditions (50 and 100 mM) significantly promoted growth by increasing tissue succulence and maintaining a relatively stable K+ concentration. A total of 552 metabolites were detected, 500 of which were differently accumulated, mainly consisting of lipids, organic acids, saccharides, alcohols, amino acids, flavonoids, phenolic acids, and alkaloids. Sucrose, glucose, p-proline, quercetin and its derivatives, and kaempferol derivatives represented core metabolites that are responsive to salinity stress. Glycolysis, flavone and flavonol biosynthesis, and phenylpropanoid biosynthesis were considered as the most important pathways responsible for salt stress response by increasing the osmotic tolerance and antioxidant activities. The high accumulation of some saccharides, flavonoids, and phenolic acids under 50 mM NaCl compared with 300 mM NaCl might contribute to the improved salt tolerance under the 50 mM NaCl treatment. Furthermore, quercetin, quercetin derivatives, and kaempferol derivatives showed varied change patterns in the roots and shoots, while coumaric, caffeic, and ferulic acids increased significantly in the roots, implying that the coping strategies in the shoots and roots varied under salinity stress. These findings lay the foundation for further analysis of the mechanism underlying the response of S. europaea to salinity.