Miracle-dz/UniFAR-FTUs huggingface dataset:
Augmenting Convolutional networks with attention-based aggregation

We show how to augment any convolutional network with an attention-based global map to achieve non-local reasoning. We replace the final average pooling by an attention-based aggregation layer akin to a single transformer block, that weights how the patches are involved in the classification decision. We plug this learned aggregation layer with a simplistic patch-based convolutional network parametrized by 2 parameters (width and depth). In contrast with a pyramidal design, this architecture family maintains the input patch resolution across all the layers. It yields surprisingly competitive trade-offs between accuracy and complexity, in particular in terms of memory consumption, as shown by our experiments on various computer vision tasks: object classification, image segmentation and detection.
Estimation based on nearest neighbor matching: from density ratio to average treatment effect

Nearest neighbor (NN) matching as a tool to align data sampled from different groups is both conceptually natural and practically well-used. In a landmark paper, Abadie and Imbens (2006) provided the first large-sample analysis of NN matching under, however, a crucial assumption that the number of NNs, $M$, is fixed. This manuscript reveals something new out of their study and shows that, once allowing $M$ to diverge with the sample size, an intrinsic statistic in their analysis actually constitutes a consistent estimator of the density ratio. Furthermore, through selecting a suitable $M$, this statistic can attain the minimax lower bound of estimation over a Lipschitz density function class. Consequently, with a diverging $M$, the NN matching provably yields a doubly robust estimator of the average treatment effect and is semiparametrically efficient if the density functions are sufficiently smooth and the outcome model is appropriately specified. It can thus be viewed as a precursor of double machine learning estimators.
Leptoquark and vectorlike quark extended models as the explanation of the muon 
g−2
 anomaly

In minimal leptoquark (LQ) models, the $R_2$ and $S_1$ can be the solution to the $(g-2)_{\mu}$ anomaly because of the chiral enhancements. Here, we study the LQ and vectorlike quark (VLQ) extended models. In the one LQ and one VLQ extended models, the $(g-2)_{\mu}$ can receive the contributions from top and top partner $T$ because of the $t-T$ mixing. Besides the traditional $R_2$ and $S_1$ representations, we find that the $S_3$ LQ can also explain the anomaly when including the $(X,T,B)_{L,R}$ triplet at the same time. Moreover, we find that the LQ has the new decay channel $T\mu$ in these models.
Two-point functions from chiral kinetic theory in magnetized plasma

We study the two-point functions from chiral kinetic theory which characterize the response to perturbative vector and axial gauge fields in magnetized chiral plasma. In the lowest Landau level approximation, the solution of chiral kinetic equations gives density waves of electric and axial charges, which contain chiral magnetic wave implied by the axial anomaly and magnetic field. We then obtain the constitutive relations for covariant currents and stress tensor that involving the density waves. By considering the difference between consistent and covariant anomalies explicitly, the correlators of consistent currents and stress tensor satisfy derivative symmetry, and therefore allow an effective action for the perturbative gauge fields as the generating functional of the correlators. We also verify the derivative symmetry of the correlators agrees with the Onsager relations.
SECOND MAIN THEOREMS FOR HOLOMORPHIC MAPS WITH FINITE GROWTH INDEX ON COMPLEX DISCS INTERSECTING FAMILIES OF HYPERSURFACES

In this paper, we establish second main theorems for holomorphic maps with finite growth index on complex discs intersecting families of hypersurfaces (moving and fixed) in projective varieties, where the small term is detailed estimate for various cases. Our results are generalizations and extensions of many previous second main theorems for holomorphic maps from C intersecting with hypersurfaces (moving and fixed) or moving hyperplanes.
Family Floer superpotential's critical values are eigenvalues of quantum product by c_1

In the setting of the non-archimedean SYZ mirror construction (arXiv: 2003.06106), we prove the folklore conjecture that the critical values of the mirror superpotential are the eigenvalues of the quantum multiplication by the first Chern class. Our result relies on a weak unobstructed assumption, but it is usually ensured in practice by Solomon's results on anti-symmetric Lagrangians. Finally, we also present some explicit examples based on the very recent progress (arXiv:2206.04652)
Cover Crop Rollers: A New Component of Conservation Tillage Systems

Rollers may provide a valuable alternative to chemicals for terminating a cover crop. Several producers are now using versions that they have made or have purchased. Most of these producers, however, complain about excessive vibration that is caused by the roller passing over the cover crop. To avoid this excessive vibration, they must limit their operational speed. Experiments were performed to determine if two alternative designs for the blades of the rollers would decrease vibration while maintaining the ability to kill a cover crop. Results showed that a curved blade system or a short-staggered straight blade system significantly reduced vibration as compared to the standard long-straight blade system typically found on rollers. These two alternative blade systems were also found to kill the cover crop as effectively as the long-straight blade system.
Semantic Characterizations of General Belief Base Revision

The AGM postulates by Alchourrón, Gärdenfors, and Makinson continue to represent a cornerstone in research related to belief change. Katsuno and Mendelzon (K&M) adopted the AGM postulates for changing belief bases and characterized AGM belief base revision in propositional logic over finite signatures. We generalize K&M’s approach to the setting of (multiple) base revision in arbitrary Tarskian logics, covering all logics with a classical modeltheoretic semantics and hence a wide variety of logics used in knowledge representation and beyond. Our generic formulation applies to various notions of “base” (such as belief sets, arbitrary or finite sets of sentences, or single sentences). The core result is a representation theorem showing a two-way correspondence between AGM base revision operators and certain “assignments”: functions mapping belief bases to total — yet not transitive — “preference” relations between interpretations. Alongside, we present a companion result for the case when the AGM postulate of syntax-independence is abandoned. We also provide a characterization of all logics for which our result can be strengthened to assignments producing transitive preference relations (as in K&M’s original work), giving rise to two more representation theorems for such logics, according to syntax dependence vs. independence.
Learning Cross-Scale Prediction for Efficient Neural Video Compression

In this paper, we present the ﬁrst neural video codec that can compete with the latest coding standard H.266/VVC in terms of sRGB PSNR on UVG dataset for the low-latency mode. Existing neural hybrid video coding approaches rely on optical ﬂow or Gaussian-scale ﬂow for prediction, which cannot support ﬁne-grained adaptation to diverse motion content. Towards more content-adaptive prediction, we propose a novel cross-scale prediction module that achieves more effective motion compensation. Speciﬁcally, on the one hand, we produce a reference feature pyramid as prediction sources, then transmit cross-scale ﬂows that leverage the feature scale to control the precision of prediction. On the other hand, we introduce the mechanism of weighted prediction into the scenario of prediction with a single reference frame, where cross-scale weight maps are transmitted to synthesize a ﬁne prediction result. In addition to the cross-scale prediction module, we further propose a multi-stage quantization strategy, which improves the rate-distortion performance with no extra computational penalty during inference. We show the encouraging performance of our efﬁcient neural video codec (ENVC) on several common benchmark datasets and analyze in detail the effectiveness of every important component.
A direct imaging method for the exterior and interior inverse scattering problems

This paper is concerned with the inverse acoustic scattering problems by an obstacle or a cavity with a sound-soft or a sound-hard boundary. A direct imaging method relying on the boundary conditions is proposed for reconstructing the shape of the obstacle or cavity. First, the scattered fields are approximated by the Fourier-Bessel functions with the measurements on a closed curve. Then, the indicator functions are established by the superposition of the total fields or their derivatives to the incident point sources. We prove that the indicator functions vanish only on the boundary of the obstacle or cavity. Numerical examples are also included to demonstrate the effectiveness of the method.
Multiple Randomization Designs

In this study we introduce a new class of experimental designs. In a classical randomized controlled trial (RCT), or A/B test, a randomly selected subset of a population of units (e.g., individuals, plots of land, or experiences) is assigned to a treatment (treatment A), and the remainder of the population is assigned to the control treatment (treatment B). The difference in average outcome by treatment group is an estimate of the average effect of the treatment. However, motivating our study, the setting for modern experiments is often different, with the outcomes and treatment assignments indexed by multiple populations. For example, outcomes may be indexed by buyers and sellers, by content creators and subscribers, by drivers and riders, or by travelers and airlines and travel agents, with treatments potentially varying across these indices. Spillovers or interference can arise from interactions between units across populations. For example, sellers' behavior may depend on buyers' treatment assignment, or vice versa. This can invalidate the simple comparison of means as an estimator for the average effect of the treatment in classical RCTs. We propose new experiment designs for settings in which multiple populations interact. We show how these designs allow us to study questions about interference that cannot be answered by classical randomized experiments. Finally, we develop new statistical methods for analyzing these Multiple Randomization Designs.
Benchmarking Pedestrian Odometry: The Brown Pedestrian Odometry Dataset (BPOD)

This paper presents the Brown Pedestrian Odometry Dataset (BPOD) for benchmarking visual odometry algorithms on data from head-mounted sensors. This dataset was captured with stereo and RGB streams from RealSense cameras with rolling and global shutters in 12 diverse indoor and outdoor locations on Brown University's campus. Its associated ground-truth trajectories were generatedfrom third-person videos that documented the recorded pedestrians' positions relative to stick-on markers placed along their paths. We evaluate the performance of canonical approaches representative of direct, feature-based, and learning-based visual odometry methods on BPOD. Our finding is that current methods which are successful on other benchmarks fail on BPOD. The failure modes correspond in part to rapid pedestrian rotation, erratic body movements, etc. We hope this dataset will play a significant role in the identification of these failure modes and in the design, development, and evaluation of pedestrian odometry algorithms.
A solar collector design procedure for crop drying

A design procedure was proposed for sizing solar-assisted crop-drying systems and assessing the combination of solar collector area and auxiliary energy needs that meets the requirements of the load. Two empirical correlations were compared for use with high thermal inertia solar collectors that are cheap and appropriate for rural areas. A case study as performed in the city of Campinas in southeastern Brazil. Grain drying with partial air heating by solar energy can provide an annual savings of 30% in fuel consumption for 1.80m2 collector area during the drying of 1.2t of corn at 50oC at a daily air rate of 1526.8 m3/day.
Edge Robotics: Edge-Computing-Accelerated Multirobot Simultaneous Localization and Mapping

With the wide penetration of smart robots in multifarious fields, the simultaneous localization and mapping (SLAM) technique in robotics has attracted growing attention in the community. Yet collaborating SLAM over multiple robots still remains challenging due to performance contradiction between the intensive graphics computation of SLAM and the limited computing capability of robots. While traditional solutions resort to the powerful cloud servers acting as an external computation provider, we show by real-world measurements that the significant communication overhead in data offloading prevents its practicability to real deployment. To tackle these challenges, this article promotes the emerging edge-computing paradigm into multirobot SLAM and proposes RecSLAM, a multirobot laser SLAM system that focuses on accelerating the map construction process under the robot–edge–cloud architecture. In contrast to the conventional multirobot SLAM that generates graphic maps on robots and completely merges them on the cloud, RecSLAM develops a hierarchical map fusion technique that directs robots’ raw data to edge servers for real-time fusion and then sends to the cloud for global merging. To optimize the overall pipeline, an efficient multirobot SLAM collaborative processing framework is introduced to adaptively optimize robot-to-edge offloading tailored to heterogeneous edge resource conditions, meanwhile ensuring the workload balancing among the edge servers. Extensive evaluations show RecSLAM can achieve up to 39.31% processing latency reduction over the state of the art. Besides, a proof-of-concept prototype is developed and deployed in real scenes to demonstrate its effectiveness.
The effective radius of self repelling elastic manifolds

We study elastic manifolds with self-repelling terms and estimate their effective radius. This class of manifolds is modelled by a self-repelling vector-valued Gaussian free field with Neumann boundary conditions over the domain $[-N,N]^d\cap \mathbb{Z}^d$, that takes values in $\mathbb{R}^d$. Our main result states that in two dimensions ($d=2$), the effective radius $R_N$ of the manifold is approximately $N$. This verifies the conjecture of Kantor, Kardar and Nelson [8] up to a logarithmic correction. Our results in $d\geq 3$ give a similar lower bound on $R_N$ and an upper of order $N^{d/2}$. This result implies that self-repelling elastic manifolds undergo a substantial stretching at any dimension.
Towards a Physics-Based Battery Aging Prediction

Accurately predicting aging of lithium-ion batteries would help to prolong their lifespan, but remains a challenge owing to the complexity and interrelation of different aging mechanisms. As a result, aging prediction often relies on empirical or data-driven approaches, which obtain their performance from analyzing large datasets. However, these datasets are expensive to generate and the models are agnostic of the underlying physics and thus difficult to extrapolate to new conditions. In this article, a physical model is used to predict capacity fade caused by solid-electrolyte interphase (SEI) growth in 62 automotive cells, aged with 28 different protocols. Three protocols parametrize the time, current and temperature dependence of the model, the state of charge dependence results from the anode’s open circuit voltage curve. The model validation with the remaining 25 protocols shows a high predictivity with a root-mean squared error of 1.28%. A case study with the so-validated model shows that the operating window, i.e. maximum and minimum state of charge, has the largest impact on SEI growth, while the influence of the applied current is almost negligible. Thereby the presented model is a promising approach to better understand, quantify and predict aging of lithium-ion batteries.
A Multi-channel Training Method Boost the Performance

Deep convolutional neural network has made huge revolution and shown its superior performance on computer vision tasks such as classification and segmentation. Recent years, researches devote much effort to scaling down size of network while maintaining its ability, to adapt to the limited memory on embedded systems like mobile phone. In this paper, we propose a multi-channel training procedure which can highly facilitate the performance and robust of the target network. The proposed procedure contains two sets of networks and two information pipelines which can work independently hinge on the computation ability of the embedded platform, while in the mean time, the classification accuracy is also admirably enhanced.
Seismic behaviour of shallow foundations: Shaking table experiments vs numerical modelling

The capability of a simplified approach to model the behaviour of shallow foundations during earthquakes is explored by numerical simulation of a series of shaking table tests performed at the Public Works Research Institute, Tsukuba, Japan. After a summary of the experimental work, the numerical model is introduced, where the whole soil–foundation system is represented by a multi‐degrees‐of‐freedom elasto‐plastic macro‐element, supporting a single degree‐of‐freedom superstructure. In spite of its simplicity and of the large intensity of the excitation involving a high degree of nonlinearity in the foundation response, the proposed approach is found to provide very satisfactory results in predicting the rocking behaviour of the system and the seismic actions transmitted to the superstructure. The agreement is further improved by introducing a simple degradation rule of the foundation stiffness parameters, suitable to capture even some minor details of the observed rocking response. On the other hand, the performance of the model is not fully satisfactory in predicting vertical settlements. Copyright © 2007 John Wiley & Sons, Ltd.
Non-symmetric L\'evy-type operators

We present a general approach to the parametrix construction. We apply it to prove uniqueness and existence of a weak fundamental solution for the equation $\partial_t =\mathcal{L}$ with non-symmetric non-local operators $$ \mathcal{L}f(x):= b(x)\cdot \nabla f(x)+ \int_{\mathbb{R}^d}( f(x+z)-f(x)- 1_{|z|<1} \left)\kappa(x,z)J(z)\, dz\,, $$ under certain assumptions on $b$, $\kappa$ and $J$. The result allows more general coefficients even for $J(z)=|z|^{-d-1}$.
Analytical modeling of nonlinear behavior of composite bridges

Various aspects of a general finite‐element program for the nonlinear analysis of steel‐and‐concrete structures is described. The program accounts for the nonlinear behavior of concrete, steel, and shear connectors. Concrete is treated as an orthotropic nonlinear material. The concept of equivalent strain is used to establish independent stress‐strain relationships in the directions of orthotropy. Steel is modeled as an elastoplastic strain‐hardening material, and classical theory of plasticity together with the von Mises failure criterion is applied. For shear connectors, an empirical nonlinear shear force—slip relationship is used. The accuracy and reliability of the program are demonstrated by the analysis of two composite beams and a multigirder bridge over the entire loading range up to failure. The analytical results are compared with the corresponding experimental and/or field data with good agreement between the two. The reported results demonstrate the feasibility and reliability of the nonlinear.
The behavior of essential dimension under specialization

Let $A$ be a discrete valuation ring with generic point $\eta$ and closed point $s$. We show that in a family of torsors over $\operatorname{Spec}(A)$, the essential dimension of the torsor above $s$ is less than or equal to the essential dimension of the torsor above $\eta$. We give two applications of this result, one in mixed characteristic, the other in equal characteristic.
Simulation of structural steel erection to assess innovations

This paper presents a new application of process simulation to construction activities to assess the operational and economic impacts of technological innovations. The first construction model developed is structural steel erection, and this model is used to identify the potential benefits and costs of eight specific erection innovations, and any changes that may be required in material, equipment, or process to use them. The model includes the process flow diagram of detailed tasks which is matched to specific design elements, production rates, operating conditions and resources to calculate activity durations, taking into account the capacity of the resources, worker safety, structural stability and other constraints. The results from the simulation model incorporating the erection innovations indicate that structural steel erection could be significantly improved by the use of some technical innovations. In addition, the use of simulation for the evaluation of construction methods offers great promise.
Reference values for nerve function assessments among a study population in northern India - III: Sensory and motor nerve conduction

Objective: To identify reference values for normal sensory and motor nerve conduction in upper and lower limb peripheral nerves in a study population in India. The work was carried out in advance of the INFIR Cohort Study, a prospective study of individuals with newly diagnosed multibacillary MB leprosy, the objective being to identify early changes in nerve function predictive of new onset impairment and reactions. Methods: We assessed sensory nerve conduction in bilateral ulnar, median, radial cutaneous and sural nerves and motor nerve conduction in distal and proximal sites in bilateral ulnar, median and peroneal nerves among 315 healthy subjects. After adjustment for skin temperature and removal of outliers reference values were computed using regression analysis of log-transformed data. The analysis and resulting reference values were stratifi ed by age and sex and based on the appropriate 5th or 95th percentiles. Results: Presented here are reference values for sensory nerve conduction velocity (SNCV), sensory nerve action potential (SNAP) amplitude and latency. Also for motor nerve conduction velocity (MNCV) and compound motor action potential (CMAP) amplitude at proximal sites and for amplitude and latency at distal sites. In each case percentiles are given by sex within four 10 year age bands. For males aged 55 years old, the reference value for ulnar SNCV was 43.6 m/sec and SNAP amplitude was 7.43 ? V. Ulnar MNCV at the proximal site in the elbow was 50.8 m/sec and CMAP amplitude 7.25 mV and at distal sites in the wrist the amplitude was 7.14 mV and latency 3.1 msec. In the leprosy-affected cohort, the most common and therefore potentially the earliest impairment, is found in sensory nerve conduction amplitude of the sural nerve.
Parabolic Tamari Lattices in Linear Type B

We study parabolic aligned elements associated with the type-$B$ Coxeter group and the so-called linear Coxeter element. These elements were introduced algebraically in (Mühle and Williams, 2019) for parabolic quotients of finite Coxeter groups and were characterized by a certain forcing condition on inversions. We focus on the type-$B$ case and give a combinatorial model for these elements in terms of pattern avoidance. Moreover, we describe an equivalence relation on parabolic quotients of the type-$B$ Coxeter group whose equivalence classes are indexed by the aligned elements. We prove that this equivalence relation extends to a congruence relation for the weak order. The resulting quotient lattice is the type-$B$ analogue of the parabolic Tamari lattice introduced for type $A$ in (Mühle and Williams, 2019).