Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectral neighbor representation for vector fields: Machine learning potentials including spin

We introduce a translational and rotational invariant local representation for vector fields, which can be employed in the construction of machine-learning energy models of solids and molecules. This allows us to describe, on the same footing, the energy fluctuations due to the atomic motion, the longitudinal and transverse excitations of the vector field, and their mutual interplay. The formalism can then be applied to physical systems where the total energy is determined by a vector density, as in the case of magnetism. Our representation is constructed over the power spectrum of the combined angular momentum describing the local atomic positions and the vector field, and can be used in conjunction with different machine-learning schemes and data taken from accurate ab initio electronic structure theories. We demonstrate the descriptive power of our representation for a range of classical spin Hamiltonian and machine-learning algorithms. In particular, we construct energy models based on both linear Ridge regression, as in conventional spectral neighbour analysis potentials, and gaussian approximation. These are both built to represent a Heisenberg-type Hamiltonian including a longitudinal energy term and spin-lattice coupling.
Designing Trustworthy User Interfaces

Interface design can directly influence trustworthiness of a software. Thereby, it affects users’ intention to use a tool. Previous research on user trust has not comprehensively addressed user interface design, though. We lack an understanding of what makes interfaces trustworthy (1), as well as actionable measures to improve trustworthiness (2). We contribute to this by addressing both gaps. Based on a systematic literature review, we give a thorough overview over the theory on user trust and provide a taxonomy of factors influencing user interface trustworthiness. Then, we derive concrete measures to address these factors in interface design. We use the results to create a proof of concept interface. In a preliminary evaluation, we compare a variant designed to elicit trust with one designed to reduce it. Our results show that the measures we apply can be effective in fostering trust in users.
TEScalib: Targetless Extrinsic Self-Calibration of LiDAR and Stereo Camera for Automated Driving Vehicles with Uncertainty Analysis

In this paper, we present TEScalib, a novel extrinsic self-calibration approach of LiDAR and stereo camera using the geometric and photometric information of surrounding environments without any calibration targets for automated driving vehicles. Since LiDAR and stereo camera are widely used for sensor data fusion on automated driving vehicles, their extrinsic calibration is highly important. However, most of the LiDAR and stereo camera calibration approaches are mainly target-based and therefore time consuming. Even the newly developed targetless approaches in last years are either inaccurate or unsuitable for driving platforms. To address those problems, we introduce TEScalib. By applying a 3D mesh reconstruction-based point cloud registration, the geometric information is used to estimate the LiDAR to stereo camera extrinsic parameters accurately and robustly. To calibrate the stereo camera, a photometric error function is builded and the LiDAR depth is involved to transform key points from one camera to another. During driving, these two parts are processed iteratively. Besides that, we also propose an uncertainty analysis for reflecting the reliability of the estimated extrinsic parameters. Our TEScalib approach evaluated on the KITTI dataset achieves very promising results.
Coordinated Transportation by Two Nonholonomic Mobile Robots based on Decentralized Control

In this paper, we propose a decentralized control alogorithm for transporting a single object by two nonholonomic mobile robots. We extend the leader-follower type control algorithm, which we proposed for the holonomic robots(10), to the nonholonomic mobile robots by introducing the dual caster action. The proposed control algorithm is experimentally applied to two nonholonomic mobile robots, and the experimental results illustrate the validity of the extended control algorithm.
A Simple Estimator for Estimating Treatment Effects Using Observational Data and Experimental Data

When estimating treatment effects, the golden standard is to conduct a randomized experiment and then contrast outcomes associated with the treatment group and the control group. However, in many cases, randomized experiments are either conducted with a much smaller scale compared to the size of the target population or accompanied with certain ethical issues and thus hard to implement. Therefore, researchers usually rely on observational data to study causal connections. The downside is that the unconfoundedness assumption, the key to validate the use of observational data is hard to verify and almost always violated. Hence, any conclusion drawn from observational data should be further analyzed with great care. Given the richness of observational data and usefulness of experimental data, researchers hope to develop credible method to combine the strength of the two. In this paper, we consider a setting where the observational data contain the outcome of interest as well as a surrogate outcome while the experimental data contain only the surrogate outcome. We propose a simple estimator to estimate the average treatment effect of interest using both the observational data and the experimental data. The remainder of the paper is organized as follows. Section 2 introduces the basic setup. In Section 3 we develop our method to estimate the treatment effect of primary outcome by using information from the experimental study. In Section 4, we discuss several widely-studied extensions to the basic setup and give concrete solution to each extension. Section 5 compare several different methods through simulations.
Alternative ideas in cosmology

Some remarkable examples of alternative cosmological theories are reviewed here, ranging from a compilation of variations on the Standard Model through the more distant quasi-steady-state cosmology, plasma cosmology, or universe models as a hypersphere, to the most exotic cases including static models. The present-day Standard Model of cosmology, [Formula: see text]CDM, gives us a representation of a cosmos whose dynamics is dominated by gravity (Friedmann equations derived from general relativity) with a finite lifetime, large scale homogeneity, expansion and a hot initial state, together with other elements necessary to avoid certain inconsistencies with observations (inflation, nonbaryonic dark matter, dark energy, etc.). There are however some models with characteristics that are close to those of the Standard Model but differing in some minor aspects; we call these “variations on the Standard Model”. Many of these models are indeed investigated by some mainstream cosmologists: different considerations on CP violation, inflation, number of neutrino species, quark-hadron phase transition, baryonic or nonbaryonic dark-matter, dark energy, nucleosynthesis scenarios, large-scale structure formation scenarios; or major variations like a inhomogeneous universe, Cold Big Bang, varying physical constants or gravity law, zero-active mass (also called “[Formula: see text]”), Milne, and cyclical models. At the most extreme distance from the Standard Model, the static models, a noncosmological redshift includes “tired-light” hypotheses, which assume that the photon loses energy owing to an intrinsic property or an interaction with matter or light as it travels some distance, or other nonstandard ideas. Our impression is that none of the alternative models has acquired the same level of development as [Formula: see text]CDM in offering explanations of available cosmological observations. One should not, however, judge any theory in terms of the number of observations that it can successfully explain (ad hoc in many cases) given the much lower level of development of the alternative ones, but by the plausibility of its principles and its potential to fit data with future improvements of the theories. A pluralist approach to cosmology is a reasonable option when the preferred theory is still under discussion.
Search for heavy resonances decaying to WW, WZ, or WH boson pairs in a final state consisting of a lepton and a large-radius jet in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for new heavy resonances decaying to pairs of bosons (WW, WZ, or WH) is presented. The analysis uses data from proton-proton collisions collected with the CMS detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb−1. One of the bosons is required to be a W boson decaying to an electron or muon and a neutrino, while the other boson is required to be reconstructed as a single jet with mass and substructure compatible with a quark pair from a W, Z, or Higgs boson decay. The search is performed in the resonance mass range between 1.0 and 4.5 TeV and includes a specific search for resonances produced via vector boson fusion. The signal is extracted using a two-dimensional maximum likelihood fit to the jet mass and the diboson invariant mass distributions. No significant excess is observed above the estimated background. Model-independent upper limits on the production cross sections of spin-0, spin-1, and spin-2 heavy resonances are derived as functions of the resonance mass and are interpreted in the context of bulk radion, heavy vector triplet, and bulk graviton models. The reported bounds are the most stringent to date. Published in Physical Review D as doi:10.1103/PhysRevD.105. 032008. © 2022 CERN for the benefit of the CMS Collaboration. CC-BY-4.0 license *See Appendix A for the list of collaboration members ar X iv :2 10 9. 06 05 5v 2 [ he pex ] 2 7 Fe b 20 22
Robust and Accurate Authorship Attribution via Program Normalization

Source code attribution approaches have achieved remarkable accuracy thanks to the rapid advances in deep learning. However, recent studies shed light on their vulnerability to adversarial attacks. In particular, they can be easily deceived by adversaries who attempt to either create a forgery of another author or to mask the original author. To address these emerging issues, we formulate this security challenge into a general threat model, the $\textit{relational adversary}$, that allows an arbitrary number of the semantics-preserving transformations to be applied to an input in any problem space. Our theoretical investigation shows the conditions for robustness and the trade-off between robustness and accuracy in depth. Motivated by these insights, we present a novel learning framework, $\textit{normalize-and-predict}$ ($\textit{N&P}$), that in theory guarantees the robustness of any authorship-attribution approach. We conduct an extensive evaluation of $\textit{N&P}$ in defending two of the latest authorship-attribution approaches against state-of-the-art attack methods. Our evaluation demonstrates that $\textit{N&P}$ improves the accuracy on adversarial inputs by as much as 70% over the vanilla models. More importantly, $\textit{N&P}$ also increases robust accuracy to 45% higher than adversarial training while running over 40 times faster.
Load-Altering Attacks Against Power Grids Under COVID-19 Low-Inertia Conditions

The COVID-19 pandemic has impacted our society by forcing shutdowns and shifting the way people interacted worldwide. In relation to the impacts on the electric grid, it created a significant decrease in energy demands across the globe. Recent studies have shown that the low demand conditions caused by COVID-19 lockdowns combined with large renewable generation have resulted in extremely low-inertia grid conditions. In this work, we examine how an attacker could exploit these scenarios to cause unsafe grid operating conditions by executing load-altering attacks (LAAs) targeted at compromising hundreds of thousands of IoT-connected high-wattage loads in low-inertia power systems. Our study focuses on analyzing the impact of the COVID-19 mitigation measures on U.S. regional transmission operators (RTOs), formulating a plausible and realistic least-effort LAA targeted at transmission systems with low-inertia conditions, and evaluating the probability of these large-scale LAAs. Theoretical and simulation results are presented based on the WSCC 9-bus and IEEE 118-bus test systems. Results demonstrate how adversaries could provoke major frequency disturbances by targeting vulnerable load buses in low-inertia systems and offer insights into how the temporal fluctuations of renewable energy sources, considering generation scheduling, impact the grid’s vulnerability to LAAs.
The convergence rates for the superdiffusion in the Boltzmann-Grad limit of the periodic Lorentz gas

In this article, we obtain the rates of convergence for superdiffusion in the Boltzmann-Grad limit of the periodic Lorentz gas, which is one of the fundamental models to study diffusions in deterministic systems. In their seminal work, Marklof and Strömbergsson proved the Boltzmann-Grad limit of the periodic Lorentz gas [18], and then Marklof and Tóth established a superdiffusive central limit theorem in large time for the Boltzmann-Grad limit [21]. Based on their work, we apply Stein’s method to derive the convergence rates for the superdiffusion in the BoltzmannGrad limit of the periodic Lorentz gas. For the discrete time displacement the rate of convergence in Wasserstein distance is obtained, while in the context of the continuous time displacement the result is presented for the Berry-Essen type bound.
Biosensor-Coupled In Vivo Mutagenesis and Omics Analysis Reveals Reduced Lysine and Arginine Synthesis To Improve Malonyl-Coenzyme A Flux in Saccharomyces cerevisiae

Malonyl-CoA is a key precursor for the production a variety of value-added chemicals. Although rational engineering has been performed to improve the synthesis of malonyl-CoA in S. cerevisiae, due to the complexity of the metabolism there is a need for evolving strains and analyzing new mechanism to improve malonyl-CoA flux. ABSTRACT Malonyl-coenzyme A (malonyl-CoA) is an important precursor for producing various chemicals, but its low availability limits the synthesis of downstream products in Saccharomyces cerevisiae. Owing to the complexity of metabolism, evolutionary engineering is required for developing strains with improved malonyl-CoA synthesis. Here, using the biosensor we constructed previously, a growth-based screening system that links the availability of malonyl-CoA with cell growth is developed. Coupling this system with in vivo continuous mutagenesis enabled rapid generation of genome-scale mutation library and screening strains with improved malonyl-CoA availability. The mutant strains are analyzed by whole-genome sequencing and transcriptome analysis. The omics analysis revealed that the carbon flux rearrangement to storage carbohydrate and amino acids synthesis affected malonyl-CoA metabolism. Through reverse engineering, new processes especially reduced lysine and arginine synthesis were found to improve malonyl-CoA synthesis. Our study provides a valuable complementary tool to other high-throughput screening method for mutant strains with improved metabolite synthesis and improves our understanding of the metabolic regulation of malonyl-CoA synthesis. IMPORTANCE Malonyl-CoA is a key precursor for the production a variety of value-added chemicals. Although rational engineering has been performed to improve the synthesis of malonyl-CoA in S. cerevisiae, due to the complexity of the metabolism there is a need for evolving strains and analyzing new mechanism to improve malonyl-CoA flux. Here, we developed a growth-based screening system that linked the availability of malonyl-CoA with cell growth and manipulated DNA replication for rapid in vivo mutagenesis. The combination of growth-based screening with in vivo mutagenesis enabled quick evolution of strains with improved malonyl-CoA availability. The whole-genome sequencing, transcriptome analysis of the mutated strains, together with reverse engineering, demonstrated weakening carbon flux to lysine and arginine synthesis and storage carbohydrate can contribute to malonyl-CoA synthesis. Our work provides a guideline in simultaneous strain screening and continuous evolution for improved metabolic intermediates and identified new targets for improving malonyl-CoA downstream product synthesis.
Characterization of the First Cultured Representative of “Candidatus Thermofonsia” Clade 2 within Chloroflexi Reveals Its Phototrophic Lifestyle

The deep ocean microbiota represents the unexplored majority of global ocean waters. The phylum Chloroflexi is abundant and broadly distributed in various deep-sea ecosystems. ABSTRACT “Candidatus Thermofonsia” represents a novel class within the phylum Chloroflexi. Metagenomic analysis reveals “Ca. Thermofonsia” harbors phototrophs outside the classically phototrophic Chloroflexia class. Unfortunately, the paucity of pure cultures limits further insights into their potential phototrophy. Here, we report the successful isolation of a “Ca. Thermofonsia” representative (Phototrophicus methaneseepsis ZRK33) from a deep-sea cold seep. Using combined physiological, genomic, and transcriptomic methods, we further show the long-wavelength light (e.g., red and infrared light) could promote the growth of strain ZRK33 and upregulate the expression of genes associated with phototrophy. In particular, strain ZRK33 has a typical phototrophic lifestyle under both laboratory and deep-sea conditions. Strain ZRK33 also possesses the ability to fix inorganic carbon through the 3-hydroxypropionate bicycle in both laboratory and deep-sea in situ environments, and the combined autotrophic, phototrophic, and heterotrophic capabilities endow strain ZRK33 with a photomixotrophic lifestyle. Notably, the predicted genes associated with phototrophy broadly exist in the metagenomes of 27 deep-sea Chloroflexi members, strongly suggesting diverse phototrophic Chloroflexi members are distributed in various unexplored deep biospheres. IMPORTANCE The deep ocean microbiota represents the unexplored majority of global ocean waters. The phylum Chloroflexi is abundant and broadly distributed in various deep-sea ecosystems. It was reported that some members of “Candidatus Thermofonsia” clade 2 might possess phototrophs; however, the absence of cultured representatives is a significant bottleneck toward understanding their phototrophic characteristics. In the present study, we successfully isolated a representative of the novel class “Ca. Thermofonsia” from a deep-sea cold seep by using an enrichment medium constantly supplemented with rifampicin, allowing researchers to isolate more Chloroflexi members in the future. Importantly, outside the classically phototrophic Chloroflexia class, we discover a novel phototrophic clade within the phylum Chloroflexi and demonstrate the existence of phototrophic lifestyles in the deep sea. Thus, this study expands the range of phototrophic Chloroflexi and provides a good model to study the mechanism of phototrophy performed in the deep biosphere.
Enhanced depth imaging optical coherence tomography of the optic nerve head improves correct diagnosis in glaucoma suspects without glaucomatous optic disc morphology

An 83-year-old woman with a long history of glaucoma and optic disc drusen (ODD) was referred for neuro-ophthalmological second opinion. The patient had been treated for decades with bilateral intraocular pressure (IOP)-lowering eye drops, laser trabeculoplasty and trabeculectomy and had severe, bilateral loss of visual fields and retinal nerve fibre layer (RNFL) thinning on optical coherence tomography (OCT) despite IOP that never exceeded 24 mm Hg. On ophthalmoscopy, only a single ODD was visible in the left eye and no optic disc cupping was apparent in either eye. Enhanced depth imaging OCT (EDI-OCT) of the optic nerve head revealed bilateral multiple, large, deep ODD, which in itself could easily explain the visual field loss and RNFL thinning of this patient. Optic nerve head examination using EDI-OCT is highly recommended for patients with a history of glaucoma but without optic nerve head cupping to avoid a potential misdiagnosis with consequent unnecessary treatment.
Extending Delivery of Seasonal Malaria Chemoprevention to Children Aged 5–10 Years in Chad: A Mixed-Methods Study

We sought to understand perceptions of the feasibility and acceptability of extending seasonal malaria chemoprevention (SMC) to children aged 5–10 years and explore reasons why SMC is administered to children aged 5–10 years in the current program. Key Findings Extending the age eligibility for seasonal malaria chemoprevention to children aged 5–10 years is generally regarded as acceptable by key informants in Massaguet district, Chad. Decision makers at the policy level consider it more urgent to achieve full coverage, demonstrate impact, and ensure the sustainability of SMC administration in children aged 3–59 months in the current program. Key Implications Leakage in the current program, resulting in children aged older than 59 months receiving SMC, is commonly acknowledged at all levels of the health system. To address this, program managers should consider more stringent selection criteria for community distributors, as well as more frequent training and more extensive sensitization at the community level. ABSTRACT Background: To prevent malaria among children aged 3–59 months in areas with high seasonal transmission, seasonal malaria chemoprevention (SMC) is recommended. In Chad, there is evidence of SMC administration to children aged older than 5 years (referred to as “leakage”). This study aimed to understand the reasons for leakage and explore the feasibility and acceptability of extending the delivery of SMC to children aged 5–10 years in Chad. Methods: We conducted a mixed-methods study in Massaguet health district with a cross-sectional survey to determine SMC coverage for children aged up to 10 years after SMC cycles 1 and 3 (n=90 and n=100 caregivers surveyed, respectively) and at the end of cycle 4 (n=101 caregivers surveyed). We conducted 14 key informant interviews at the national and district level and 8 focus group discussions with community distributors and caregivers. Results: In the compounds surveyed, there were no children aged 5–10 years in cycle 1. In cycles 3 (n=1 children) and 4 (n=16 children), there was 100% (95% confidence interval [CI]=2.5, 100.0) and 62.5% (95% CI=35.4, 84.8) coverage of SMC in children aged 5–10 years, respectively. Extension of SMC to older children was considered acceptable, but there were concerns about feasibility and ensuring the sustainability of the current program in children aged 3–59 months. Key informants acknowledged the need to secure additional funding to pilot SMC in older age groups and were uncertain about the impact of the current SMC program at scale. Conclusion: Key informants considered extending SMC to children aged 5–10 years acceptable but did not deem it a current priority. They expressed an urgent need to address leakage and reinforce both the sustainability and quality of the current SMC program.