Miracle-dz/UniFAR-FTUs huggingface dataset:
New data poison attacks on machine learning classifiers for mobile exfiltration

Most recent studies have shown several vulnerabilities to attacks with the potential to jeopardize the integrity of the model, opening in a few recent years a new window of opportunity in terms of cyber-security. The main interest of this paper is directed towards data poisoning attacks involving label-flipping, this kind of attacks occur during the training phase, being the aim of the attacker to compromise the integrity of the targeted machine learning model by drastically reducing the overall accuracy of the model and/or achieving the missclassification of determined samples. This paper is conducted with intention of proposing two new kinds of data poisoning attacks based on label-flipping, the targeted of the attack is represented by a variety of machine learning classifiers dedicated for malware detection using mobile exfiltration data. With that, the proposed attacks are proven to be model-agnostic, having successfully corrupted a wide variety of machine learning models; Logistic Regression, Decision Tree, Random Forest and KNN are some examples. The first attack is performs label-flipping actions randomly while the second attacks performs label flipping only one of the 2 classes in particular. The effects of each attack are analyzed in further detail with special emphasis on the accuracy drop and the misclassification rate. Finally, this paper pursuits further research direction by suggesting the development of a defense technique that could promise a feasible detection and/or mitigation mechanisms; such technique should be capable of conferring a certain level of robustness to a target model against potential attackers.
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning

Stackelberg equilibria arise naturally in a range of popular learning problems, such as in security games or indirect mechanism design, and have received increasing attention in the reinforcement learning literature. We present a general framework for implementing Stackelberg equilibria search as a multi-agent RL problem, allowing a wide range of algorithmic design choices. We discuss how previous approaches can be seen as specific instantiations of this framework. As a key insight, we note that the design space allows for approaches not previously seen in the literature, for instance by leveraging multitask and meta-RL techniques for follower convergence. We propose one such approach using contextual policies, and evaluate it experimentally on both standard and novel benchmark domains, showing greatly improved sample efficiency compared to previous approaches. Finally, we explore the effect of adopting algorithm designs outside the borders of our framework.
Evolution of Neural Tangent Kernels under Benign and Adversarial Training

Two key challenges facing modern deep learning are mitigating deep networks' vulnerability to adversarial attacks and understanding deep learning's generalization capabilities. Towards the first issue, many defense strategies have been developed, with the most common being Adversarial Training (AT). Towards the second challenge, one of the dominant theories that has emerged is the Neural Tangent Kernel (NTK) -- a characterization of neural network behavior in the infinite-width limit. In this limit, the kernel is frozen, and the underlying feature map is fixed. In finite widths, however, there is evidence that feature learning happens at the earlier stages of the training (kernel learning) before a second phase where the kernel remains fixed (lazy training). While prior work has aimed at studying adversarial vulnerability through the lens of the frozen infinite-width NTK, there is no work that studies the adversarial robustness of the empirical/finite NTK during training. In this work, we perform an empirical study of the evolution of the empirical NTK under standard and adversarial training, aiming to disambiguate the effect of adversarial training on kernel learning and lazy training. We find under adversarial training, the empirical NTK rapidly converges to a different kernel (and feature map) than standard training. This new kernel provides adversarial robustness, even when non-robust training is performed on top of it. Furthermore, we find that adversarial training on top of a fixed kernel can yield a classifier with $76.1\%$ robust accuracy under PGD attacks with $\varepsilon = 4/255$ on CIFAR-10.
Homogenization and Dimension Reduction of the Stokes Problem with Navier-Slip Condition in Thin Perforated Layers

We study a Stokes system posed in a thin perforated layer with a Navier-slip condition on the internal oscillating boundary from two viewpoints: 1) dimensional reduction of the layer and 2) homogenization of the perforated structure. Assuming the perforations are periodic, both aspects can be described through a small parameter $\epsilon>0,$ which is related to the thickness of the layer as well as the size of the periodic structure. By letting $\epsilon$ tend to zero, we prove that the sequence of solutions converges to a limit which satisfies a well-defined macroscopic problem. More precisely, the limit velocity and limit pressure satisfy a two pressure Stokes model, from which a Darcy law for thin layers can be derived. Due to non-standard boundary conditions, some additional terms appear in Darcy's law.
A Study of Magnetic Field Characteristics of the Flaring Active Region Based on Nonlinear Force-free Field Extrapolation

Coronal magnetic fields are responsible for the onset of solar flares and solar eruptions. However, the type of magnetic field parameters that can be used to measure the critical condition for a solar eruption is still unclear. As an effort to understand the possible condition for a solar flare, we have examined the nondimensional parameter κ introduced by Ishiguro & Kusano, which contains information about magnetic twist distribution and magnetic flux in an active region (AR). We introduce a new parameter κ*, as a proxy for κ, and we have analyzed the evolution of κ* during the flaring period of an AR using the nonlinear force-free field extrapolated from the photospheric vector magnetic field data. Using data from the Solar Dynamics Observatory/Helioseismic and Magnetic Imager, we have calculated κ* for the AR NOAA 11158 during its three-day flaring period. We found that κ* increased to a certain level before two large flares and decreased significantly after their onset. The results suggest that κ* may be used as an indicator of the necessary condition for the onset of a solar eruption in the AR. Based on this result, we propose a new method to assess the possibility of a large solar eruption from an AR by combining the parameter κ* and information about the magnetic energy of the AR.
Spectral Tomography for the Line-of-sight Structures of the Taurus Molecular Cloud 1

We clarify the line-of-sight structure of the Taurus Molecular Cloud 1 (TMC-1) on the basis of the CCS (JN = 43−32) and HC3N (J = 5−4) spectral data observed at a very high velocity resolution and sensitivity of ΔV ≃ 0.0004 km s−1 (=61 Hz) and ΔTmb ≃ 40 mK. The data were obtained toward the cyanopolyyne peak with ∼30 hr integration using the Z45 receiver and the PolariS spectrometer installed in the Nobeyama 45 m telescope. Analyses of the optically thin F = 4−4 and 5−5 hyperfine lines of the HC3N emission show that the spectra consist of four distinct velocity components with a small line width (≲0.1 km s−1) at VLSR = 5.727, 5.901, 6.064, and 6.160 km s−1, which we call A, B, C, and D, respectively, in the order of increasing LSR velocities. Utilizing the velocity information of the four velocity components, we further analyzed the optically thicker CCS spectrum and the other hyperfine lines of the HC3N emission by solving the radiative transfer to investigate how the four velocity components overlap along the line of sight. Results indicate that they are located in the order of A, B, C, and D from far side to near side to the observer, indicating that TMC-1 is shrinking, moving inward as a whole.
EXTREMELY BROAD RADIO RECOMBINATION MASER LINES TOWARD THE HIGH-VELOCITY IONIZED JET IN CEPHEUS A HW2

We present the first detection of the H40α, H34α, and H31α radio recombination lines (RRLs) at millimeter wavelengths toward the high-velocity ionized jet in the Cepheus A HW2 star-forming region. From our single-dish and interferometric observations, we find that the measured RRLs show extremely broad asymmetric line profiles with zero-intensity line widths of ∼1100 km s−1. From the line widths, we estimate a terminal velocity for the ionized gas in the jet of ⩾500 km s−1, consistent with that obtained from the proper motions of the HW2 radio jet. The total integrated line-to-continuum flux ratios of the H40α, H34α, and H31α lines are 43, 229, and 280 km s−1, clearly deviating from LTE predictions. These ratios are very similar to those observed for the RRL masers toward MWC349A, suggesting that the intensities of the RRLs toward HW2 are affected by maser emission. Our radiative transfer modeling of the RRLs shows that their asymmetric profiles could be explained by maser emission arising from a bi-conical radio jet with a semi-opening angle of 18°, electron density distribution varying as r−2.11, and turbulent and expanding wind velocities of 60 and 500 km s−1.
Quantum spin-liquid behavior in the spin-1/2 random-bond Heisenberg antiferromagnet on the kagome lattice

The effect of the quenched bond-randomness on the ordering of the $S=1/2$ antiferromagnetic Heisenberg model on the kagome lattice is investigated by means of an exact-diagonalization method. When the randomness exceeds a critical value, the ground state of the model exhibits a transition within the non-magnetic state into the randomness-relevant gapless spin-liquid state. Implications to the S=1/2 kagome-lattice antiferromagnet herbertsmithite is discussed.
The dust content of the most metal-poor star-forming galaxies

Although dust content is usually assumed to depend uniquely on metallicity, recent observations of two extremely metal-poor dwarf galaxies have suggested that this may not always be true. At a similar oxygen abundance of ~ 3% Zsun, the dust-to-gas and dust-to-stellar mass ratios in SBS 0335-052 and IZw 18 differ by a factor 40-70 according to including molecular gas or excluding it. Here we investigate a possible reason for this dramatic difference through models based on a semi-analytical formulation of chemical evolution including dust. Results suggest that the greater dust mass in SBS 0335-052 is due to the more efficient grain growth allowed by the high density in the cold interstellar medium (ISM), observationally inferred to be almost 20 times higher than in IZw 18. Our models are able to explain the difference in dust masses, suggesting that efficient dust formation and dust content in galaxies, including those with the highest measured redshifts, depend sensitively on the ISM density, rather than only on metallicity.
How planet–planet scattering can create high-inclination as well as long-period orbits

Abstract Recent observations have revealed two new classes of planetary orbits. Rossiter-Mclaughlin (RM) measurements have revealed hot Jupiters in high-obliquity orbits. In addition, direct-imaging has discovered giant planets at large (~ 100 AU) separations via direct-imaging technique. Simple-minded disk-migration scenarios are inconsistent with the high-inclination (and even retrograde) orbits as seen in recent RM measurements. Furthermore, forming giant planets at large semi-major axis (a) may be challenging in the core-accretion paradigm. We perform many N-body simulations to explore the two above-mentioned orbital architectures. Planet–planet scattering in a multi-planet system can naturally excite orbital inclinations. Planets can also get scattered to large distances. Large-a planetary orbits created from planet–planet scattering are expected to have high eccentricities (e). Theoretical models predict that the observed long-period planets, such as Fomalhaut-b have moderate e ≈ 0.3. Interestingly, these are also in systems with disks. We find that if a massive-enough outer disk is present, a scattered planet may be circularized at large a via dynamical friction from the disk and repeated scattering of the disk particles.
The Drudgery of a Doctor’s Disciple: Exploring the effects of Negative Role Modelling on medical students’ professional development

Abstract Introduction Role modelling is considered an essential component of teaching in various educational settings and impact students’ professional development. Most studies found in the literature have explored the influence of positive role models and limited data is available about the negative role modelling. This study explores the effects of negative role modelling of teachers on the professional development of future doctors. Methods A qualitative exploratory study was done in three medical colleges of Lahore, Pakistan. Fifteen, telephonic, semi-structured interviews were done with fifth-year MBBS students. A thematic analysis was done through manual coding of transcribed interviews. Results A total of 374 codes were generated in the first cycle of coding, that was merged to 42 in the second cycle. These codes led to 4 subthemes that finally emerged as two themes. The first theme was “Students & patients: In the same boat” highlighting the damaging effects of negative role modelling. The second theme was “Taking the bad with the good” focusing on the ambivalent response of students towards the unprofessional behaviours of their role models. Conclusion Negative role modelling exponentially affects the attitude and behaviour of medical students especially in informal settings and have detrimental effects on patient care. Students lose some degree of humanism while unconsciously observing the unethical behaviours, to become a part of hospital culture whereas some students show determination to channelize their resentment to reforms.
The Relationship between Plant-Based Diet Index and Semen Parameters of Men with Infertility: A Cross-Sectional Study

Background Infertility is a major clinical problem that affects people psychologically and medically. For the past 40 years, studies have linked nearly 50% of childlessness to male infertility. It is worth noting that unlike other factors contributing to infertility, diet is a tunable factor and can be applied in counseling infertile men. The goal of this study was to determine the relationship between plant diet index (PDI) and semen parameters in Iranian infertile men. Materials and Methods In this cross-sectional study, dietary intake was determined by a valid 168-item question- naire (FFQ). In this study, four dependent semen parameters, including total sperm motility (TSM), sperm concentra- tion (SC), normal sperm morphology (NSM), and semen volume (SV) were measured. Results Results of this study stated that greater adherence to the healthful plant-based diet index (hPDI), can signifi- cantly increase sperm density and motility in men, as well as greater adherence to the PDI dietary pattern is related to a lower risk of sperm volume deficiency, and ultimately more adherence to the unhealthful plant-based diet index (uPDI), can reduce the risk of sperm motility. Conclusion In this study, for the first time, the relationship between PDI, hPDI, uPDI and male infertility was evaluated. Altogether, this study demonstrated that nutrition has an impact on semen quality and fertility of men.
Non-local Thermodynamic Equilibrium Stellar Spectroscopy with 1D and 〈3D〉 Models. II. Chemical Properties of the Galactic Metal-poor Disk and the Halo

From exploratory studies and theoretical expectations it is known that simplifying approximations in spectroscopic analysis (local thermodynamic equilibrium (LTE), 1D) lead to systematic biases of stellar parameters and abundances. These biases depend strongly on surface gravity, temperature and, in particular, for LTE versus non-LTE (NLTE), on metallicity of the stars. Here we analyze the [Mg/Fe] and [Fe/H] plane of a sample of 326 stars, comparing LTE and NLTE results obtained using 1D hydrostatic models and averaged models. We show that compared to the NLTE benchmark, the other three methods display increasing biases toward lower metallicities, resulting in false trends of [Mg/Fe] against [Fe/H], which have profound implications for interpretations by chemical evolution models. In our best NLTE model, the halo and disk stars show a clearer behavior in the [Mg/Fe]–[Fe/H] plane, from the knee in abundance space down to the lowest metallicities. Our sample has a large fraction of thick disk stars and this population extends down to at least [Fe/H] ∼ −1.6 dex, further than previously proven. The thick disk stars display a constant [Mg/Fe] ≈ 0.3 dex, with a small intrinsic dispersion in [Mg/Fe] that suggests that a fast SN Ia channel is not relevant for the disk formation. The halo stars reach higher [Mg/Fe] ratios and display a net trend of [Mg/Fe] at low metallicities, paired with a large dispersion in [Mg/Fe]. These indicate the diverse origin of halo stars from accreted low-mass systems to stochastic/inhomogeneous chemical evolution in the Galactic halo.
Impact of maximal strength training on countermovement jump phase characteristics in athletes with cerebral palsy

ABSTRACT Analysis of the countermovement jump (CMJ) force–time curve phases provides insight into athlete neuromuscular function and methods by which jump height improves in response to training. A CMJ phase analysis and the dynamic strength index (DSI) have yet to be explored in athletes with cerebral palsy (CP). This study aimed to address this knowledge gap. Eleven state- to international-level athletes with CP completed a pre-post maximal strength training intervention with waitlist control. CMJ was assessed via force plate pre/post baseline and after the 12-week intervention. Following the intervention, CMJ height, takeoff velocity, and concentric phase peak and mean force, impulse and mean acceleration improved significantly (p = 0.006–0.001). No changes were observed in any eccentric braking phase variable (p = 0.79–0.13), while DSI lowered (p = 0.03). In athletes with CP, strength training increased CMJ concentric phase peak and mean force and impulse, increasing velocity and acceleration and therefore jump height. DSI lowered due to moderate and small increases in isometric mid-thigh pull and CMJ peak force, respectively. Unlike in non-disabled athletes, strength training did not alter any eccentric phase variable; therefore, other modalities may be required to further optimize jumping performance in athletes with CP.
The luminous late-time emission of the type-Ic supernova iPTF15dtg – evidence for powering from a magnetar?

Context. The transient iPTF15dtg is a type-Ic supernova (SN) showing a broad light curve around maximum light, consistent with massive ejecta if we assume a radioactive-powering scenario. Aims. We aim to study the late-time light curve of iPTF15dtg, which turned out to be extraordinarily luminous for a stripped-envelope (SE) SN, and investigate possible powering mechanisms. Methods. We compare the observed light curves to those of other SE SNe and also to models for the 56Co decay. We analyze and compare the spectra to nebular spectra of other SE SNe. We build a bolometric light curve and fit it with different models, including powering by radioactivity, magnetar powering, and a combination of the two. Results. Between 150 and 750 d post-explosion, the luminosity of iPTF15dtg declined by merely two magnitudes instead of the six magnitudes expected from 56Co decay. This is the first spectroscopically regular SE SN found to show this behavior. The model with both radioactivity and magnetar powering provides the best fit to the light curve and appears to be the most realistic powering mechanism. An alternative mechanism might be circumstellar-medium (CSM) interaction. However, the spectra of iPTF15dtg are very similar to those of other SE SNe, and do not show signs of strong CSM interaction. Conclusions. The object iPTF15dtg is the first spectroscopically regular SE SN whose light curve displays such clear signs of a magnetar contributing to its late-time powering. Given this result, the mass of the ejecta needs to be revised to a lower value, and therefore the progenitor mass could be significantly lower than the previously estimated > 35 M⊙.
Status and prospects for drought forecasting: opportunities in artificial intelligence and hybrid physical–statistical forecasting

Despite major improvements in weather and climate modelling and substantial increases in remotely sensed observations, drought prediction remains a major challenge. After a review of the existing methods, we discuss major research gaps and opportunities to improve drought prediction. We argue that current approaches are top-down, assuming that the process(es) and/or driver(s) are known—i.e. starting with a model and then imposing it on the observed events (reality). With the help of an experiment, we show that there are opportunities to develop bottom-up drought prediction models—i.e. starting from the reality (here, observed events) and searching for model(s) and driver(s) that work. Recent advances in artificial intelligence and machine learning provide significant opportunities for developing bottom-up drought forecasting models. Regardless of the type of drought forecasting model (e.g. machine learning, dynamical simulations, analogue based), we need to shift our attention to robustness of theories and outputs rather than event-based verification. A shift in our focus towards quantifying the stability of uncertainty in drought prediction models, rather than the goodness of fit or reproducing the past, could be the first step towards this goal. Finally, we highlight the advantages of hybrid dynamical and statistical models for improving current drought prediction models. This article is part of the Royal Society Science+ meeting issue ‘Drought risk in the Anthropocene’.
Homogenization via sprinkling

We show that a superposition of an $\varepsilon$-Bernoulli bond percolation and any everywhere percolating subgraph of $\mathbb Z^d$, $d\ge 2$, results in a connected subgraph, which after a renormalization dominates supercritical Bernoulli percolation. This result, which confirms a conjecture of the first author together with H\"aggstr\"om and Schramm (2000), is mainly motivated by obtaining finite volume characterizations of uniqueness for general percolation processes.