Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulation of the Occurrence of Heatwaves over the Euro-Mediterranean Region by the Intensity of the Atlantic Multidecadal Variability

The influence of the Atlantic multidecadal variability (AMV) and its amplitude on the Euro-Mediterranean summer climate is studied in two climate models, namely CNRM-CM5 and EC-Earth3P. Large ensembles of idealized experiments have been conducted in which North Atlantic sea surface temperatures are relaxed toward different amplitudes of the observed AMV anomalies. In agreement with observations, during a positive phase of the AMV both models simulate an increase (decrease) in temperature of 0.2°–0.8°C and a decrease (increase) in precipitation over the Mediterranean basin of 0.1–0.2 mm day−1 (northern half of Europe) compared to a negative phase. Heatwave durations over the Mediterranean land regions are 40% (up to 85% over the eastern regions) longer for a moderate amplitude of the AMV. Lower and higher amplitudes lead to longer durations of ~30% and ~100%, respectively. A comparison with observed heatwaves indicates that the AMV can considerably modulate the current anthropogenically forced response on heatwaves durations depending on the area and on the AMV amplitude. The related anticyclonic anomalies over the Mediterranean basin are associated with drier soils and a reduction of cloud cover, which concomitantly induce a decrease (increase) of the latent (sensible) heat flux, and an enhancement of the downward radiative fluxes over lands. It is found that both tropical and extratropical forcings from the AMV are needed to trigger mechanisms, which modulate the atmospheric circulation over the Euro-Atlantic region. The amplitude of the local climate response over the Mediterranean basin evolves linearly with the amplitude of the AMV. However, the strength of this relationship differs between the models, and depends on their intrinsic biases.
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes

Autonomous systems are often required to operate in partially observable environments. They must reliably execute a specified objective even with incomplete information about the state of the environment. We propose a methodology to synthesize policies that satisfy a linear temporal logic formula in a partially observable Markov decision process (POMDP). By formulating a planning problem, we show how to use point-based value iteration methods to efficiently approximate the maximum probability of satisfying a desired logical formula and compute the associated belief state policy. We demonstrate that our method scales to large POMDP domains and provides strong bounds on the performance of the resulting policy.
Concurrently Extrapolating and Interpolating Networks for Continuous Model Generation

Most deep image smoothing operators are always trained repetitively when different explicit structure-texture pairs are employed as label images for each algorithm configured with different parameters. This kind of training strategy often takes a long time and spends equipment resources in a costly manner. To address this challenging issue, we generalize continuous network interpolation as a more powerful model generation tool, and then propose a simple yet effective model generation strategy to form a sequence of models that only requires a set of specific-effect label images. To precisely learn image smoothing operators, we present a double-state aggregation (DSA) module, which can be easily inserted into most of current network architecture. Based on this module, we design a double-state aggregation neural network structure with a local feature aggregation block and a nonlocal feature aggregation block to obtain operators with large expression capacity. Through the evaluation of many objective and visual experimental results, we show that the proposed method is capable of producing a series of continuous models and achieves better performance than that of several state-of-the-art methods for image smoothing.
Fast is better than free: Revisiting adversarial training

Adversarial training, a method for learning robust deep networks, is typically assumed to be more expensive than traditional training due to the necessity of constructing adversarial examples via a first-order method like projected gradient decent (PGD). In this paper, we make the surprising discovery that it is possible to train empirically robust models using a much weaker and cheaper adversary, an approach that was previously believed to be ineffective, rendering the method no more costly than standard training in practice. Specifically, we show that adversarial training with the fast gradient sign method (FGSM), when combined with random initialization, is as effective as PGD-based training but has significantly lower cost. Furthermore we show that FGSM adversarial training can be further accelerated by using standard techniques for efficient training of deep networks, allowing us to learn a robust CIFAR10 classifier with 45% robust accuracy to PGD attacks with $\epsilon=8/255$ in 6 minutes, and a robust ImageNet classifier with 43% robust accuracy at $\epsilon=2/255$ in 12 hours, in comparison to past work based on "free" adversarial training which took 10 and 50 hours to reach the same respective thresholds. Finally, we identify a failure mode referred to as "catastrophic overfitting" which may have caused previous attempts to use FGSM adversarial training to fail. All code for reproducing the experiments in this paper as well as pretrained model weights are at this https URL.
Error analysis for time-fractional semilinear parabolic equations using upper and lower solutions

A semilinear initial-boundary value problem with a Caputo time derivative of fractional order $\alpha\in(0,1)$ is considered, solutions of which typically exhibit a singular behaviour at an initial time. For L1-type discretizations of this problem, we employ the method of upper and lower solutions to obtain sharp pointwise-in-time error bounds on quasi-graded temporal meshes with arbitrary degree of grading. In particular, those results imply that milder (compared to the optimal) grading yields the optimal convergence rate $2-\alpha$ in positive time, while quasi-uniform temporal meshes yield first-order convergence in positive time. Furthermore, under appropriate conditions on the nonlinearity, the method of upper and lower solutions immediately implies that, similarly to the exact solutions, the computed solutions lie within a certain range. Semi-discretizations in time and full discretizations using finite differences and finite elements in space are addressed. The theoretical findings are illustrated by numerical experiments.
Large and Robust Charge-to-Spin Conversion in Sputtered Weyl Semimetal WTex with Structural Disorder

Topological insulators have recently shown great promise for ultralow-power spin-orbit torque (SOT) devices thanks to their large charge-to-spin conversion efficiency originating from the spin-momentum-locked surface states. Weyl semimetals, on the other hand, may be more desirable due to their spin-polarized surface as well as bulk states, robustness against magnetic and structural disorder, and higher electrical conductivity for integration in metallic magnetic tunnel junctions. Here, we report that sputtered WTex thin films exhibit local atomic and chemical structures of Weyl semimetal WTe2 and host massless Weyl fermions in the presence of structural disorder at low temperatures. Remarkably, we find superior spin Hall conductivity and charge-to-spin conversion efficiency in these sputtered WTex films compared with crystalline WTe2 flakes. Besides, the strength of unidirectional spin Hall magnetoresistance in annealed WTex/Mo/CoFeB heterostructure is up to 20 times larger than typical SOT/ferromagnet bilayers reported at room temperature. We further demonstrate room temperature field-free magnetization switching at a current density as low as 0.97 MA/cm2. These large charge-to-spin conversion properties that are robust in the presence of structural disorder and thermal annealing pave the way for industrial production of Weyl semimetals. Our results open up a new class of sputtered Weyl semimetals for memory and computing based on magnetic tunnel junctions as well as broader planar heterostructures containing SOT/ferromagnet interfaces.
Outer scale of the wide-range Prandtl/Schmidt number spectrum on beam wander for oceanic optical turbulence

Light propagation in ocean is influenced by the refractive-index which is related to temperature, salinity, outer-scale, etc. Based on Hill's model 1 (H1), two kinds of oceanic refractive-index spectrum (ORIS) have been proposed to describe the second order characteristic of refractive-index. Most recently, several ORIS models were proposed based on Hill's model 4 (H4), which gave a better precision in high wave-numbers (viscous-diffusive range). However, the outer scale, as a key parameter related to practical environment, has not been introduced into any oceanic H4-based spectra. In this paper, we take the outer-scale parameter into an H4-based spectrum which is adapted to the wide-range Prandtl/Schmidt number [Opt. Express. 20, 11111(2019)]. The proposed outer-scaled spectrum could be used in analyzing wave propagation in limited outer-scaled environment with different values of average temperature and salinity. We further derived the beam wander formula of collimated laser beam. Numerical calculations show that the beam wander influenced by outer-scale length $L_{0}$ is more obvious than that influenced by average temperature $\langle T\rangle$, when $L_{0}$ varies from $10 \rm m$ to $100 \rm m$, and $\langle T\rangle$ ranges from $0^{\circ} \rm C$ to $30^{\circ} \rm C$. When salinity fluctuations prevails ($\omega \rightarrow 0$), the influence of outer scale becomes weaker. In contribution proportion of beam wander, the temperature-salt coupling term is the much larger than that of temperature or salinity term.
On the maintenance of an attached leading-edge vortex via model bird alula

Researchers have hypothesized that the post-stall lift benefit of bird’s alular feathers, or alula, stems from the maintenance of an attached leading-edge vortex (LEV) over their thin-profiled, outer hand wing. Here, we investigate the connection between the alula and LEV attachment via flow measurements in a wind tunnel. We show that a model alula, whose wetted area is 1 % that of the wing, stabilizes a recirculatory aft-tilted LEV on a steadily translating unswept wing at post-stall angles of attack. The attached vortex is the result of the alula’s ability to smoothly merge otherwise separate leading- and side-edge vortical flows. We identify two key processes that facilitate this merging: (i) the steering of spanwise vorticity generated at the wing’s leading edge back to the wing plane and (ii) an aft-located wall jet of high-magnitude root-to-tip spanwise flow (${>}80\,\%$ that of the free-stream velocity). The former feature induces LEV roll-up while the latter tilts LEV vorticity aft and evacuates this flow toward the wing tip via an outboard vorticity flux. We identify the alula’s streamwise position (relative to the leading edge of the thin wing) as important for vortex steering and the alula’s cant angle as important for high-magnitude spanwise flow generation. These findings advance our understanding of the likely ways birds leverage LEVs to augment slow flight.
Grossberg-Karshon Twisted Cubes and Hesitant Jumping Walk Avoidance

Let $G$ be a complex simply-laced semisimple algebraic group of rank $r$ and $B$ a Borel subgroup. Let $\mathbf i \in [r]^n$ be a word and let $\boldsymbol{\ell} = (\ell_1,\dots,\ell_n)$ be a sequence of non-negative integers. Grossberg and Karshon introduced a virtual lattice polytope associated to $\mathbf i$ and $\boldsymbol{\ell}$ called a twisted cube, whose lattice points encode the character of a $B$-representation. More precisely, lattice points in the twisted cube, counted with sign according to a certain density function, yields the character of the generalized Demazure module determined by $\mathbf i$ and $\boldsymbol{\ell}$. In recent work, the author and Harada described precisely when the Grossberg–Karshon twisted cube is untwisted, i.e., the twisted cube is a closed convex polytope, in the situation when the integer sequence $\boldsymbol{\ell}$ comes from a weight $\lambda$ of $G$. However, not every integer sequence $\boldsymbol{\ell}$ comes from a weight of $G$. In the present paper, we interpret the untwistedness of Grossberg–Karshon twisted cubes associated with any word $\mathbf i$ and any integer sequence $\boldsymbol{\ell}$ using the combinatorics of $\mathbf i$ and $\boldsymbol{\ell}$. Indeed, we prove that the Grossberg–Karshon twisted cube is untwisted precisely when $\mathbf i$ is hesitant-jumping-$\boldsymbol{\ell}$-walk-avoiding.
Attention Flow: End-to-End Joint Attention Estimation

This paper addresses the problem of understanding joint attention in third-person social scene videos. Joint attention is the shared gaze behaviour of two or more individuals on an object or an area of interest and has a wide range of applications such as human-computer interaction, educational assessment, treatment of patients with attention disorders, and many more. Our method, Attention Flow, learns joint attention in an end-to-end fashion by using saliency-augmented attention maps and two novel convolutional attention mechanisms that determine to select relevant features and improve joint attention localization. We compare the effect of saliency maps and attention mechanisms and report quantitative and qualitative results on the detection and localization of joint attention in the VideoCoAtt dataset, which contains complex social scenes.
IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters

In this work, we study robust deep learning against abnormal training data from the perspective of example weighting built in empirical loss functions, i.e., gradient magnitude with respect to logits, an angle that is not thoroughly studied so far. Consequently, we have two key findings: (1) Mean Absolute Error (MAE) Does Not Treat Examples Equally. We present new observations and insightful analysis about MAE, which is theoretically proved to be noise-robust. First, we reveal its underfitting problem in practice. Second, we analyse that MAE's noise-robustness is from emphasising on uncertain examples instead of treating training samples equally, as claimed in prior work. (2) The Variance of Gradient Magnitude Matters. We propose an effective and simple solution to enhance MAE's fitting ability while preserving its noise-robustness. Without changing MAE's overall weighting scheme, i.e., what examples get higher weights, we simply change its weighting variance non-linearly so that the impact ratio between two examples are adjusted. Our solution is termed Improved MAE (IMAE). We prove IMAE's effectiveness using extensive experiments: image classification under clean labels, synthetic label noise, and real-world unknown noise. We conclude IMAE is superior to CCE, the most popular loss for training DNNs.
Traveling skyrmions in chiral antiferromagnets

Skyrmions in antiferromagnetic (AFM) materials with the Dzyaloshinskii-Moriya (DM) interaction are expected to exist for essentially the same reasons as in DM ferromagnets (FM). It is shown that skyrmions in antiferromagnets with the DM interaction can be traveling as solitary waves with velocities up to a maximum value that depends on the DM parameter. Their configuration is found numerically. The energy and the linear momentum of an AFM skyrmion lead to a proper definition of its mass. We give the details of the energy-momentum dispersion of traveling skyrmions and explore their particle-like character based on exact relations. The skyrmion number, known to be linked to the dynamics of topological solitons in FM, is, here, unrelated to the dynamical behavior. As a result, the solitonic behavior of skyrmions in AFM is in stark contrast to the dynamical behavior of their FM counterparts
Designing a sequential testing procedure for verifying global CO2 emissions

Following the Paris Agreement, most countries have agreed to reduce their CO2 emissions according to individually set Nationally Determined Contributions (NDCs). However, national CO2 emissions are reported by individual countries, and cannot be directly measured or verified by third parties. This engenders a potential misreporting problem, where nations that are not living up to their Paris commitments could, by under-reporting emissions, nevertheless appear to be fulfilling their NDC targets. This paper uses the theory of sequential testing to design a statistical CO2 monitoring procedure, that can detect systematic misreportings of CO2 emissions. The data series that we monitor is the so-called carbon budget imbalance, which is a time series derived from reported CO2 emissions and independently measured Earth system data. We show that, when emissions are truthfully reported, the budget imbalance constitutes a stationary process, while, if emissions become systematically misreported, a structural break occurs. Our proposed procedure monitors the budget imbalance data and sequentially tests the null that the budget imbalance is stationary; rejection of the null provides evidence for systematic misreportings of CO2 emissions. By constructing the procedure appropriately, detection time can be made sufficiently fast to help inform the 5 yearly global "stocktake" of the Paris Agreement.
Transcatheter closure of atrial septal defect in symptomatic children weighing ≤10 kg: Addressing unanswered issues from a decade of experience

Background and Objectives: Device closure of secundum atrial septal defect is shown to be feasible and effective in children weighing ≤10 kg. Issues such as how large is too large, how to choose device size, does the length of the interatrial septum (IAS) matter, and need for technical modifications for successful device delivery have not been systematically addressed. Materials and Methods: This is a retrospective study, comprising 45 patients weighing ≤10 kg, who were chosen for device closure between January 2010 and June 2018. Patient selection was done on basis of transthoracic echocardiography. Device closure was done using Amplatzer septal occluder. The device size was selected primarily based on transesophageal echocardiography (TEE)-measured defect diameter. Although IAS length was taken into consideration, adequate rim size was the key factor in deciding device closure of the defect. Results: Forty-three out of 45 patients had successful device closure. The mean age and weight were 25.71 ± 8.62 months and 8.99 ± 1.24 kg, respectively. The defect measuring as large as 27 mm (14.89 ± 3.89) on TEE was closed and device as big as 28 mm was successfully deployed (16.7 ± 4.31). Regular technique of device deployment was successful in only 15 cases. In the remaining 28, one of the modified techniques was used. There was no mortality, failure of the procedure, device embolization, thromboembolism, or pericardial effusion. One patient developed moderate mitral regurgitation and two patients had transient atrioventricular block. At follow-up, all patients showed significant improvement in symptoms and growth without any complications. Conclusions: Defect size as large as three times the weight in kg can be closed in small children. Devices as large as 28 mm can be deployed in these hearts provided the surrounding rims are adequate. In majority of cases, one of the modified techniques is essential for successful deployment. IAS length is not a limiting factor for deciding the size of the device used.
Cone-beam computed tomography analysis of canal transportation and centering ratio of fifth-generation nickel-titanium rotary file systems in curved root canals

Aim: The aim of this study is to compare canal transportation and centering ratio using of Protaper Next (PTN) (Dentsply Maillefer, Ballaigues, Switzerland) and Revo-S (RS) (MicroMega, Besancon Cedex, France) compared to Protaper Universal (PTU) (Dentsply Maillefer, Ballaigues, Switzerland) nickel-titanium rotary file systems in curved root canals using cone-beam computed tomography. Materials and Methods: Ninety maxillary mesiobuccal first molar uncalcified canals with mature apex, curvature of 20°–45° (the Estrela method) and minimum 20-mm length were selected. The samples were randomly divided into three groups of 30 teeth each, respectively, Group I PTU, Group II PTN, and Group III RS Rotary systems and Instrumented according to the manufacturers' instructions. Pre- and post-instrumentation cone-beam tomographic scan was performed in same position to calculate canal transportation and centering ability at 2 mm, 5 mm, and 8 mm from the root apex. Statistical analysis was performed with ANOVA and Post-hoc Tukey test. Results: PTU had maximum mean canal transportation and minimum mean centering ratio at all levels, whereas PTN showed minimum mean canal transportation and maximum mean centering ratio. The results were statistically significant. Conclusions: In terms of canal transportation and centering ratio in the middle and coronal third of the root, PTN and RS performed better than PTU. However, in apical third, PTN performed best among all other groups.
Sociodemographic and clinical profile of children with autism spectrum disorders – An observational study from a tertiary care hospital

BACKGROUND: In spite of advances in assessment and management of patients with autism spectrum disorders (ASDs) in the west, developing countries including India are lagging far behind in child psychiatry, let alone ASDs. The aims of our study were to find the sociodemographic and clinical profile of children with ASDs in a child psychiatry clinic of a tertiary care hospital. MATERIALS AND METHODS: A semi-structured questionnaire was used to record the sociodemographic status. The diagnosis of ASDs was made on the basis of both 4th Edition, Text Revision and 5th Edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR and DSM-V), after a thorough clinical assessment. Intelligence quotient was assessed by a clinical psychologist. Descriptive statistical analysis was done and presented as frequencies and percentages. RESULTS: A total of 55 patients were diagnosed with ASDs. Most of the patients were <9 years with 52.73% in 4–7 years' age group and 21.82% in 7–9 years' age group. Males (78.18%) outnumbered females. About 52.73% belonged to nuclear family, and 63.63% were from rural background. Nearly 70.91% were staying at home. About 87.27% with ASDs as per DSM-IV-TR met the DSM-V symptom criteria for ASDs, whereas 12.73% met DSM-V symptom criteria for social communication disorder. CONCLUSION: Almost 10.4% of children and adolescents with psychiatric disorders were having ASDs. Only 3% of our cases were receiving inclusive education, and about 70% of cases were staying at home. Nearly 87.27% of DSM-IV-diagnosed ASDs retained the DSM-V diagnosis of ASDs. Comorbid intellectual disability was frequently seen in children with ASDs.