Miracle-dz/UniFAR-FTUs huggingface dataset:
Solving Last-Mile Delivery Challenges is Critical to Increase COVID-19 Vaccine Uptake: A Cluster Randomized Controlled Trial (preprint)

In the first six months of COVID-19 vaccine distribution, over 90% of all doses were given to residents of high and upper middle income nations. Less than 30% of Africans were vaccinated with at least one shot even 18 months after vaccine development. This has led to an explosion of scholarly and policy interest on vaccine hesitancy and ways to overcome it. We argue instead that the limiting factor for many rural Africans is lack of access, and implemented an intervention designed to overcome the logistical challenges of last-mile delivery. The cluster randomized controlled trial in 150 remote rural communities shows that simply bringing vaccines to villages using mobile vaccination teams increases the community vaccination rate by 20 percentage points within just 48-72 hours. Moreover, auxiliary populations showed up at our temporary clinic to get vaccinated, which lowers the cost of this intervention to US$ 32 per person vaccinated. This is more cost-effective than most vaccination strategies investigated via trials.
Topology-aware method to segment 3D plant tissues images.

The study of genetic and molecular mechanisms underlying tissue morphogenesis has received a lot of attention in biology. Especially, accurate segmentation of tissues into individual cells plays an important role for quantitative analyzing the development of the growing organs. However, instance cell segmentation is still a challenging task due to the quality of the image and the ﬁne-scale structure. Any small leakage in the boundary prediction can merge different cells together, thereby damaging the global structure of the image. In this paper, we propose an end-to-end topology-aware 3D segmentation method for plant tissues. The strength of the method is that it takes care of the 3D topology of segmented structures. The keystone is a training phase and a new topology-aware loss - the CavityLoss - that are able to help the network to focus on the topological errors to ﬁx them during the learning phase. The evaluation of our method on both ﬁxed and live plant organ datasets shows that our method outperforms state-of-the-art methods (and contrary to state-of-the-art methods, does not require any post-processing stage). The code of CavityLoss is freely available at https://github.com/onvungocminh/CavityLoss.
Analytical Methods and Field Theory for Disordered Systems

This thesis presents several aspects of the physics of disordered elastic systems and of the analytical methods used for their study.On one hand we will be interested in universal properties of avalanche processes in the statics and dynamics (at the depinning transition) of elastic interfaces of arbitrary dimension in disordered media at zero temperature. To study these questions we will use the functional renormalization group. After a review of these aspects we will more particularly present the results obtained during the thesis on (i) the spatial structure of avalanches and (ii) the correlations between avalanches.On the other hand we will be interested in static properties of directed polymers in 1+1 dimension, and in particular in observables related to the KPZ universality class. In this context the study of exactly solvable models has recently led to important progress. After a review of these aspects we will be more particularly interested in exactly solvable models of directed polymer on the square lattice and present the results obtained during the thesis in this direction: (i) classification ofBethe ansatz exactly solvable models of directed polymer at finite temperature on the square lattice; (ii) KPZ universality for the Log-Gamma and Inverse-Beta models; (iii) KPZ universality and non-universality for the Beta model; (iv) stationary measures of the Inverse- Beta model and of related zero temperature models.
Discovering Link Prediction Methods' Performances by Network Topology Relation

One of the prominent topics in complex network analysis is link prediction, which is a key component of network-based recommendation systems or finding missing connections. There are several different link prediction methods in the literature based on measuring the likelihood of the existence of a link between two nodes. These methods use different topological properties of the network. Although there are methods using different strategies, previous studies have focused only on method success but have not adequately examined the relationship between the performance of these methods and the topology of the network. The main motivation for this study is to reveal the role of different network topologies in link prediction. Thus, the choice of link prediction method can be customized according to the topological characteristics of the network. The two main contributions of the study are, firstly, comparing different link prediction methods with well-known performance measures in social, biological, and information networks with different topological properties in a large experimental setup; and second, examining the possible relationship between the performance of link prediction methods and the network topology. Based on the experimental results, the global methods are more successful than others, regardless of the network topology. In addition, it was concluded that the high eigenvector centralization in the network may affect the missing link prediction performance.
Environmental vulnerability characteristics in an active swarm region

BACKGROUND AND OBJECTIVES: For the first time, an earthquake swarm occurred from April to August 2021 in Lake Toba (Indonesia), the world’s largest caldera lake. Although the earthquakes were located in a volcanic environment, the swarm activities could also be related to tectonic activities on the Sumatran fault. The swarm activities occurred at shallow depths and may influence the ground surface condition in which soil or rock below the subsurface can amplify the shaking. The research objective was to investigate the characteristics of the earthquake swarm in the Toba Caldera from the spectrum of the earthquake waveforms, site frequency, and horizontal-to-vertical ratio of sites. METHODS: The spectra of very closely located swarm and nonswarm earthquakes were analyzed to investigate the differences between both types of seismic events. The seismic spectral ratio of horizontal- over-vertical components was applied to calculate the spectrum in the active swarm region from all newly installed seismic sensors. The root mean square was applied to average the amplitude of the horizontal components. Then, the values of the horizontal-to-vertical ratios were obtained by comparing the average values of the horizontal and vertical components. FINDINGS: The microtremor study showed a more complete spectrum waveform from the low-to-high frequency of a non swarm earthquake, while the swarm earthquakes generated high-frequency seismograms. From the combination values of natural site frequencies and the horizontal-to-vertical ratios, the Toba environment can be classified into five clusters: I) Samosir–Hasinggaan, II) Samosir–Parapat, III) Silimapuluh, IV) Balige–Paropo, and V) Panjaitan. Samosir Island located in the middle of the Toba Caldera has the highest frequency and amplification, which are divided into two clusters. CONCLUSION: Cluster I, with high amplification corresponding to the earthquake intensity, was felt by people in northern Samosir. Cluster II is located in the southern part of Samosir Island. Cluster III features moderate values of amplification and seismic vulnerability and therefore needs attention before future infrastructure development. Cluster IV, located in the southern and northern regions with high amplification and vulnerability, is associated with the Quaternary eruption. Cluster V, situated in northeastern Toba, has the lowest amplification and vulnerability compared to other clusters. The microtremor results provide good correlation with the geology in the volcanic environment of the Toba region.
Opportunities in Flavour Physics at the HL-LHC and HE-LHC

Motivated by the success of the flavour physics programme carried out over the last decade at the Large Hadron Collider (LHC), we characterize in detail the physics potential of its High-Luminosity and High-Energy upgrades in this domain of physics. We document the extraordinary breadth of the HL/HE-LHC programme enabled by a putative Upgrade II of the dedicated flavour physics experiment LHCb and the evolution of the established flavour physics role of the ATLAS and CMS general purpose experiments. We connect the dedicated flavour physics programme to studies of the top quark, Higgs boson, and direct high-$p_T$ searches for new particles and force carriers. We discuss the complementarity of their discovery potential for physics beyond the Standard Model, affirming the necessity to fully exploit the LHC's flavour physics potential throughout its upgrade eras.
Thermal Expansion and Magnetostriction Studies of a Kondo Lattice Compound: Ceagsb2

We have investigated a single crystal of CeAgSb2 using low field ac-susceptibility, thermal expansion and magnetostriction measurements in the temperature range 1.5K to 90K. The ac-susceptibility exhibits a sharp peak at 9.7K for both B//c and B perp c due to the magnetic ordering of the Ce moment. The thermal expansion coefficient alpha, exhibits highly anisotropic behaviour between 3K and 80K : alpha is positive for dL/L perp c, but negative for dL/L // c. Furthermore, alpha (for dL/L) perp c (i.e. in ab-plane) exhibits a sharp peak at TN followed by a broad maximum at 20K, while a sharp negative peak at TN followed by a minimum at 20K has been observed for (dL/L //) the c direction. The observed maximum and minimum in alpha(T) at 20K have been attributed to the crystalline field effect on the J=5/2 state of the Ce3+ ion. The magnetostriction also exhibits anisotropic behaviour with a large magnetostriction along the c-axis. The ab-plane magnetostriction exhibits a peak at B=3.3T at 3K, which is consistent with the observed peak in the magnetoresistance measurements.
CTA 102 in exceptionally high state during 2016–2017

Blazars in outburst provide a unique opportunity to study their spectral behavior, correlated variations at different frequencies, and jet structure. An unprecedented flaring activity in FSRQ CTA 102, occuring from 2016 November to 2017 January, is used here for a detailed study to understand flaring mechanisms at short and long timescales, spectral behavior in different energy regimes, and to estimate sizes and location of the high-energy emitting region in the jet. Multiwavelength (MW) data for CTA 102 during its outburst period, were obtained from Fermi-LAT, Swift-XRT/UVOT, Steward Observatory, Mt Abu Infrared Observatory, and OVRO. These were analyzed to construct MW light curves, extract the spectral information, and to perform the correlated variability studies. Our study shows that CTA 102 attained the highest ever flux levels across the electromagnetic spectrum (EMS) while flaring and otherwise, with rapid and prolonged activities at all the frequencies. A number of short-term (three to eight days) and long-term (more than a month) variability events are noticed across the EMS. We infer a redder when brighter trend in faint state and a bluer when brighter trend during a few optical flares. Based on the flux doubling timescale, the size of γ-ray emitting region is estimated as ≈8.76 × 1015 cm, located at a distance of about 5.58 × 1016 cm from the central engine. CTA 102 was in extremely bright phase during 2016–2017, possibly due to, successive high energy particle injections into the jet, creating shocks traveling down the jet which lead to the overall flux enhancement across the EMS. Alternatively, a decreasing viewing angle could also lead to such flux enhancement. The study reveals correlated variations in all the energy bands, with lags within time bins, indicating co-spatial origin of the emissions. During the flaring event, a bluer-when-brighter color in the optical and harder when brighter trend in the X-ray and γ-ray spectra are noticed. During some flares softer γ-ray spectra are observed.
Cosmic microwave background constraints in light of priors over reionization histories

Non-parametric reconstruction or marginalization over the history of reionization using cosmic microwave background data necessarily assumes a prior over possible histories. We show that different but reasonable choices of priors can shift current and future constraints on the reionization optical depth, τ, or correlated parameters such as the neutrino mass sum, Σmν, at the level of 0.3–0.4 σ, meaning that this analysis is somewhat prior dependent. We point out some prior-related problems with the commonly used principal component reconstruction, concluding that the significance of some recent hints of early reionization in Planck 2015 data has been overestimated. We also present the first non-parametric reconstruction applied to newer Planck intermediate (2016) data and find that the hints of early reionization disappear entirely in this more precise dataset. These results limit possible explanations of the EDGES 21cm signal which would have also significantly reionized the universe at z > 15. Our findings about the dependence on priors motivate the pursuit of improved data or searches for physical reionization models which can reduce the prior volume. The discussion here of priors is of general applicability to other non-parametric reconstructions, for example of the primordial power spectrum, of the recombination history, or of the expansion rate.
Optomechanically amplified wavelength conversion in diamond microcavities

Efficient, low noise conversion between different colors of light is a necessary tool for interfacing quantum optical technologies that have different operating wavelengths. Optomechanically mediated wavelength conversion and amplification is a potential method for realizing this technology, and is demonstrated here in microdisks fabricated from single crystal diamond -- a material that can host a wide range of quantum emitters. Frequency up-- conversion is demonstrated with internal conversion efficiency of $\sim$ 45\% using both narrow and broadband probe fields, and optomechanical frequency conversion with amplification is demonstrated in the optical regime for the first time.
Discontinuous shear-thinning in adhesive dispersions

We present simulations for the steady-shear rheology of a model adhesive dispersion. We vary the range of the attractive forces $u$ as well as the strength of the dissipation $b$. For large dissipative forces, the rheology is governed by the Weisenberg number $ \text{Wi}\sim b\dot\gamma/u$ and displays Herschel-Bulkley form $\sigma = \sigma_y+c\text{Wi}^\nu$ with exponent $\nu=0.45$. Decreasing the strength of dissipation, the scaling with $\text{Wi}$ breaks down and inertial effects show up. The stress decreases via the Johnson-Samwer law $\Delta\sigma\sim T_s^{2/3}$, where temperature $T_s$ is exclusively due to shear-induced vibrations. During flow particles prefer to rotate around each other such that the dominant velocities are directed tangentially to the particle surfaces. This tangential channel of energy dissipation and its suppression leads to a discontinuity in the flow curve, and an associated discontinuous shear thinning transition. We set up an analogy with frictional systems, where the phenomenon of discontinuous shear thickening occurs. In both cases tangential forces, frictional or viscous, mediate a transition from one branch of the flowcurve with low tangential dissipation to one with large tangential dissipation.
D2SLAM: Decentralized and Distributed Collaborative Visual-inertial SLAM System for Aerial Swarm

A crucial technology in fully autonomous aerial swarms is collaborative SLAM (CSLAM), which enables the estimation of relative pose and global consistent trajectories of aerial robots. However, existing CSLAM systems do not prioritize relative localization accuracy, critical for close collaboration among UAVs. This paper presents $D^2$SLAM, a novel decentralized and distributed ($D^2$) CSLAM system that covers two scenarios: near-field estimation for high accuracy state estimation in close range and far-field estimation for consistent global trajectory estimation. $D^2$SLAM has a versatile and powerful front-end that can use stereo cameras or omnidirectional cameras as input, the former being easy to obtain and the latter being an excellent solution to the Field of View problem in relative localization. Our experiments verify $D^2$SLAM achieves high accuracy in ego-motion estimation, relative localization, and global consistency. Moreover, distributed optimization algorithms are adopted to achieve the $D^2$ objective to allow the scale-up of the swarm and ensure robustness against network delays. We argue $D^2$SLAM can be applied in a wide range of real-world applications.
The Origin of Buckling Instability in Galactic Bars: Searching for the Scapegoat

We analyze the origin of the buckling instability in stellar bars using high-resolution N-body simulations. Previous studies have promoted the nonresonant firehose instability to be responsible for the vertical buckling. We have analyzed the buckling process following the resonant excitation of stellar orbits in the bar. We find that (1) the buckling is associated with an abrupt increase in the central mass concentration and triggers velocities within the bar. The velocity field forms circulation cells, increasing vorticity, which is absent in classical firehose instability; (2) The bending amplitude is nonlinear when measured by isodensity contours or curvature of the Laplace plane, which has a substantial effect on the stellar motions; (3) The planar and vertical 2:1 resonances appear only with the buckling and quickly reach the overlapping phase, thus supporting the energy transfer from horizontal to vertical motions; (4) Using nonlinear orbit analysis, we analyze the stellar oscillations and find that stars cross the vertical 2:1 resonance simultaneously with the buckling. The overlapping planar and vertical 2:1 resonances trapping more than 25% of the bar particles provide the ‘smoking gun’ pointing to a close relationship between the bending of stellar orbits and the resonant action — these particles are assuring the cohesive response in the growing vertical asymmetry. We conclude that resonant excitation is important in triggering the buckling instability, and the contribution from the nonresonant firehose instability should be reevaluated. Finally, we discuss some observational implications of buckling on the kinematics in face-on and inclined galactic disks.
The Small Separation A-star Companion Population: First Results with CHARA/MIRC-X

We present preliminary results from our long-baseline interferometry (LBI) survey to constrain the multiplicity properties of intermediate-mass A-type stars within 80 pc. Previous multiplicity studies of nearby stars exhibit orbital separation distributions well fitted with a lognormal with peaks >15 au, increasing with primary mass. The A-star multiplicity survey of De Rosa et al., sensitive beyond 30 au but incomplete below 100 au, found a lognormal peak around 390 au. Radial velocity surveys of slowly rotating, chemically peculiar Am stars identified a significant number of very close companions with periods ≤5 days, ∼0.1 au, a result similar to surveys of O- and B-type primaries. With the improved performance of LBI techniques, we can probe these close separations for normal A-type stars where other surveys are incomplete. Our initial sample consists of 27 A-type primaries with estimated masses between 1.44 and 2.49 M ⊙ and ages 10–790 Myr, which we observed with the MIRC-X instrument at the CHARA Array. We use the open-source software CANDID to detect five companions, three of which are new, and derive a companion frequency of 0.19−0.06+0.11 over mass ratios of 0.25–1.0 and projected separations of 0.288–5.481 au. We find a probability of 10−6 that our results are consistent with extrapolations based on previous models of the A-star companion population over the mass ratios and separations sampled. Our results show the need to explore these very close separations to inform our understanding of stellar formation and evolution processes.
Strange-metal behavior in a Fermi liquid with strange scatterers

A variety of low-temperature, normal-state properties of optimally and overdoped cuprate superconductors, including the DC and optical transport responses, are suﬃciently anomalous that they might seem to be inconsistent with any quasiparticle description. However, we show by ex-plicit construction that the most salient phenomena can be accounted for in a system with localized “strange scatterers” embedded into a Fermi liquid with a conventional quasiparticle description. Such scatterers could originate from “two-level systems” associated with an electronic glassy state with short-range charge-order correlations.
Single SMPC Invocation DPHelmet: Differentially Private Distributed Learning on a Large Scale

Distributing machine learning predictors enables the collection of large-scale datasets while leaving sensitive raw data at trustworthy sites. We show that locally training support vector machines (SVMs) and computing their averages leads to a learning technique that is scalable to a large number of users, satisfies differential privacy, and is applicable to non-trivial tasks, such as CIFAR-10. For a large number of participants, communication cost is one of the main challenges. We achieve a low communication cost by requiring only a single invocation of an efficient secure multiparty summation protocol. By relying on state-of-the-art feature extractors (SimCLR), we are able to utilize differentially private convex learners for non-trivial tasks such as CIFAR-10. Our experimental results illustrate that for $1{,}000$ users with $50$ data points each, our scheme outperforms state-of-the-art scalable distributed learning methods (differentially private federated learning, short DP-FL) while requiring around $500$ times fewer communication costs: For CIFAR-10, we achieve a classification accuracy of $79.7\,\%$ for an $\varepsilon = 0.59$ while DP-FL achieves $57.6\,\%$. More generally, we prove learnability properties for the average of such locally trained models: convergence and uniform stability. By only requiring strongly convex, smooth, and Lipschitz-continuous objective functions, locally trained via stochastic gradient descent (SGD), we achieve a strong utility-privacy tradeoff.
Adaptive Sparse Grid Discontinuous Galerkin Method: Review and Software Implementation

This paper reviews the adaptive sparse grid discontinuous Galerkin (aSG-DG) method for computing high dimensional partial differential equations (PDEs) and its software implementation. The C ++ software package called AdaM-DG, implementing the aSG-DG method, is available on GitHub at https://github.com/JuntaoHuang/adaptive-multiresolution-DG . The package is capable of treating a large class of high dimensional linear and nonlinear PDEs. We review the essential components of the algorithm and the functionality of the software, including the multiwavelets used, assembling of bilinear operators, fast matrix-vector product for data with hierarchical structures. We further demonstrate the performance of the package by reporting the numerical error and the CPU cost for several benchmark tests, including linear transport equations, wave equations, and Hamilton-Jacobi (HJ) equations.