Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution Of Potential Field Data In Delineating The Structural-Tectonic Set-Up Of The Eastern Qattara Depression Area , Western Desert , Egypt

In this work, a reconnaissance study is presented to delineate the subsurface structures and tectonics of the Eastern Qattara Depression area using the available geophysical data; that include Bouguer gravity and aeromagnetic data. To achieve this goal, several transformation techniques and filtering processes were accomplished on the Bouguer gravity anomaly map and the total intensity aeromagnetic map, through both qualitative and quantitative analyses. At first, the total intensity aeromagnetic map was processed through the application of reduction to the magnetic pole technique. In addition, the fast Fourier transform was carried out on the gravity and RTP magnetic data for establishing the energy spectrum curve and defining the residual (shallow) and regional (deep) sources. By the way, the frequency band pass filtering was used to enhance the anomaly wave lengths associated with the shallow and deep sources. For optional separation of the signals, the band pass filter was designed for each survey using the matched filtering. The equivalent depths of the isolated short wavelength anomalies are 0.759 & 0.340 km below the flight surface, and the depths of the intermediate wavelength anomalies are 1.28 & 2.00 km, as well as the depths of the long wavelength anomalies are 6.3 & 6.5 km for the gravity and magnetic data, respectively. Finally, the qualitative and quantitative interpretations of the available Bouguer gravity and R.T. P. magnetic maps of the Eastern Qattara area, northern Western Desert, reflect the occurrence of the various types of structures (folds and faults) and their components (anticlines and synclines, as well as their dip-slip and strike-slip faults). Added, the main tectonic deformations of the study area have NNW-SSE, NNE-SSW, NE-SW, NW-SE and E-W trends.
Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the Loop

Model-based human pose estimation is currently approached through two different paradigms. Optimization-based methods fit a parametric body model to 2D observations in an iterative manner, leading to accurate image-model alignments, but are often slow and sensitive to the initialization. In contrast, regression-based methods, that use a deep network to directly estimate the model parameters from pixels, tend to provide reasonable, but not pixel accurate, results while requiring huge amounts of supervision. In this work, instead of investigating which approach is better, our key insight is that the two paradigms can form a strong collaboration. A reasonable, directly regressed estimate from the network can initialize the iterative optimization making the fitting faster and more accurate. Similarly, a pixel accurate fit from iterative optimization can act as strong supervision for the network. This is the core of our proposed approach SPIN (SMPL oPtimization IN the loop). The deep network initializes an iterative optimization routine that fits the body model to 2D joints within the training loop, and the fitted estimate is subsequently used to supervise the network. Our approach is self-improving by nature, since better network estimates can lead the optimization to better solutions, while more accurate optimization fits provide better supervision for the network. We demonstrate the effectiveness of our approach in different settings, where 3D ground truth is scarce, or not available, and we consistently outperform the state-of-the-art model-based pose estimation approaches by significant margins. The project website with videos, results, and code can be found at https://seas.upenn. edu/~nkolot/projects/spin.
Do bulges stop stars forming?

In this paper, we use the Herschel Reference Survey to make a direct test of the hypothesis that the growth of a stellar bulge leads to a reduction in the star formation efficiency of a galaxy (or conversely a growth in the gas-depletion time-scale) as a result of the stabilization of the gaseous disc by the gravitational field of the bulge. We find a strong correlation between star formation efficiency and specific star formation rate in galaxies without prominent bulges and in galaxies of the same morphological type, showing that there must be some other process besides the growth of a bulge that reduces the star formation efficiency in galaxies. However, we also find that galaxies with more prominent bulges (Hubble types E to Sab) do have significantly lower star formation efficiencies than galaxies with later morphological types, which is at least consistent with the hypothesis that the growth of a bulge leads to the reduction in the star formation efficiency. The answer to the question in the title is therefore yes and no: bulges may reduce the star formation efficiency in galaxies but there must also be some other process at work. We also find that there is a significant but small difference in the star formation efficiencies of galaxies with and without bars, in the sense that galaxies with bars have slightly higher star formation efficiencies.
Collectivised Pension Investment

We study the optimal management of a collectivised pension fund, where all investors agree that the assets of deceased members are shared among the survivors. We find that for realistic parameters based on the UK pensions market, a collectivised fund achieves an approximately 20% better return than either an annuity or a personal investment fund. We introduce models of investor preferences over a stream of pension payments in the presence of mortality, incorporating a new concept of adequacy. We find that for risk-averse individuals, pension adequacy plays an important role in determining the optimal fund management strategy. A key issue in the design of collective funds is how to ensure the fund treats all investors fairly. This is a trivial problem in the case that all investors have identical preferences, wealth and mortality, but becomes challenging for heterogeneous funds. We give a strategy for the management of heterogeneous funds in complete markets and prove that it is asymptotically optimal in the absence of systematic longevity risk.
Manifold learning for spatial audio rendering

The objective of binaurally rendered spatial audio is to simulate a sound source in arbitrary spatial locations through the Head-Related Transfer Functions (HRTFs). HRTFs model the direction-dependent influence of ears, head, and torso on the incident sound field. When an audio source is filtered through a pair of HRTFs (one for each ear), a listener is capable of perceiving a sound as though it were reproduced at a specific location in space. Inspired by our successful results building a practical face recognition application aimed at visually impaired people that uses a spatial audio user interface, in this work we have deepened our research to address several scientific aspects of spatial audio. In this context, this thesis explores the incorporation of spatial audio prior knowledge using a novel nonlinear HRTF representation based on manifold learning, which tackles three major challenges of broad interest among the spatial audio community: HRTF personalization, HRTF interpolation, and human sound localization improvement. Exploring manifold learning for spatial audio is based on the assumption that the data (i.e. the HRTFs) lies on a low-dimensional manifold. This assumption has also been of interest among researchers in computational neuroscience, who argue that manifolds are crucial for understanding the underlying nonlinear relationships of perception in the brain. For all of our contributions using manifold learning, the construction of a single manifold across subjects through an Inter-subject Graph (ISG) has proven to lead to a powerful HRTF representation capable of incorporating prior knowledge of HRTFs and capturing the underlying factors of spatial hearing. Moreover, the use of our ISG to construct a single manifold offers the advantage of employing information from other individuals to improve the overall performance of the techniques herein proposed. The results show that our ISG-based techniques outperform other linear and nonlinear methods in tackling the spatial audio challenges addressed by this thesis. Key-words: spatial audio; manifold learning; Head-Related Transfer Functions; binaural technique.
Cyanoacrylate Coating Against Candida Albicans Biofilm Formation

reline resin by an ethyl-cyanoacrylate adhesive, ECA (Super Bonder®, Loctite, Itapevi, SP, Brazil) would be able to inhibit or reduce Candida albicans biofilm formation on its surface, comparing to a commercial surface sealant (BisCover®, Bisco, Schaumburg, USA). Reline resin specimens were fabricated and randomly divided into 6 groups (n=8): CG (control group), no surface treatment; ECA1, ECA coating on the surface before sterilization; ECA2, ECA coating after sterilization; ECA3, ECA incorporated in the resin bulk; DPE1, BisCover® coating before sterilization; DPE2, BisCover® coating after sterilization. Specimens were inoculated with C. albicans SC5314 (1x107 cells/mL) and incubated for 24 h. Then, the biofilm were stained with LIVE/DEAD® BaclightTM L7007 Kit and analyzed by Confocal Laser Scanning Microscopy. The images were evaluated by bioImageL® v.2. 0 software and total biovolume (μm3), viable cells (%), and covered area (%) were calculated. Data were statistically analyzed by Kruskal-Wallis and Dunn tests (p<0.05). Results showed that ECA-coated groups presented better results, reducing C. albicans biofilm formation. Acquired images revealed that these groups (ECA1 and ECA2) presented a reduced number of cells, mostly in yeast form (less pathogenic), while the other groups presented higher number of cells, mostly in hyphae form (more pathogenic). Based on these findings, a beneficial effect of Super Bonder® coating reline resins surface could be demonstrated, suggesting a promising way to prevent fungal biofilm formation on dentures. Bene f i c i a l E f f e c t s o f E thy l Cyanoacrylate Coating Against Candida Albicans Biofilm Formation
Online Data Poisoning Attacks

We study data poisoning attacks in the online learning setting, where training data arrive sequentially, and the attacker is eavesdropping the data stream and has the ability to contaminate the current data point to affect the online learning process. We formulate the optimal online attack problem as a stochastic optimal control problem, and provide a systematic solution using tools from model predictive control and deep reinforcement learning. We further provide theoretical analysis on the regret suffered by the attacker for not knowing the true data sequence. Experiments validate our control approach in generating near-optimal attacks on both supervised and unsupervised learning tasks. performance. We provided a regret analysis on the cost achieved by a realistic attacker and showed that despite the restricted knowledge, the optimality gap is upper-bounded by order of O ( n (cid:0) 1 = 2 ) , given the resource of n data samples.
Role of a Dentist in the Diagnosis of Child Abuse and Neglect: A Literature and Narrative Review

Child Abuse (CA) is defined as any physical or psychological harm inflicted upon children. The most commonly affected anatomical region in these cases is the orofacial complex, thereby placing dentists in a dominant position for detecting CA. The statistical figures referred to CA are high, and many cases go unreported. To determine the level of knowledge, the aptitudes and capacity of dentists in reporting cases of CA; the barriers facing the reporting of cases; and the key clinical characteristics for the detection of CA. A search was made of the PubMed (MEDLINE), ScienceDirect, LILACS and SciELO databases for articles published up until March 2019, involving analytical observational and descriptive studies relevant to the objectives of our study. All articles were independently reviewed by two authors. Injuries caused by CA are largely located in the orofacial region – the most prevalent being caries, burns and fractures. The most frequently identified risk factor is behavioral alterations on the part of the parents or caregivers. The reviewed studies reflect a discrepancy between suspected and reported cases of CA. Although dentists are able to detect injuries, there is a great lack of knowledge about how to report cases of CA to the authorities. It is interesting to establish guidelines for the detection and reporting of suspicious cases. Improved training in forensic and legal dentistry is needed, together with the establishment of detection and reporting protocols. The clinical signs detected in the case of CA and neglect include untreated caries, poor oral hygiene, traumatisms, burns, lacerations and biting. The recognition of such signs and correct case history compilation are essential for the detection of CA.
Optimizing Simulation Parameters for Weak Lensing Analyses Involving Non-Gaussian Observables

We performed a series of numerical experiments to quantify the sensitivity of the predictions for weak lensing statistics obtained in ray-tracing dark matter (DM)-only simulations, to two hyper-parameters that influence the accuracy as well as the computational cost of the predictions: the thickness of the lens planes used to build past light cones and the mass resolution of the underlying DM simulation. The statistics considered are the power spectrum (PS) and a series of non-Gaussian observables, including the one-point probability density function, lensing peaks, and Minkowski functionals. Counterintuitively, we find that using thin lens planes (< 60 h−1 Mpc on a 240 h−1 Mpc simulation box) suppresses the PS over a broad range of scales beyond what would be acceptable for a survey comparable to the Large Synoptic Survey Telescope (LSST). A mass resolution of 7.2 × 1011 h−1 M⊙ per DM particle (or 2563 particles in a (240 h−1 Mpc)3 box) is sufficient to extract information using the PS and non-Gaussian statistics from weak lensing data at angular scales down to 1′ with LSST-like levels of shape noise.
Packet-oblivious stable routing in multi-hop wireless networks

In this work, we study the fundamental problem of scheduling communication in multi-hop wireless networks. We focus on packet-oblivious routing protocols; that is, algorithms that do not take into account any historical information about packets or carried out by packets. Such protocols are well motivated in practice, as real forwarding protocols and corresponding data-link layer architectures are typically packet-oblivious. We provide a local-knowledge protocol, i.e., which is working without using any topological information, except for some upper bounds on the number of links and the network's degree, that is stable for a wide spectrum of packet injection rates. It is based on novel transmission schedules, called universally strong selectors, which, combined with some known queuing policies (LIS, SIS, NFS, FTG), makes it the best known local-knowledge packet-oblivious routing protocol regarding the injection rate for which stability is guaranteed. We also propose a global-knowledge protocol, which is stable if the packet injection rate per link is smaller than the inverse of the chromatic number of the collision graph associated with the network. Although the protocol does not take into account any historical information, it has to be seeded by some information about the network topology.
Many Average Partial Effects: with An Application to Text Regression

We study estimation, pointwise and simultaneous inference, and confidence intervals for many average partial effects of lasso Logit. Focusing on high-dimensional, cluster-sampling environments, we propose a new average partial effect estimator and explore its asymptotic properties. Practical penalty choices compatible with our asymptotic theory are also provided. The proposed estimator allow for valid inference without requiring oracle property. We provide easy-to-implement algorithms for cluster-robust high-dimensional hypothesis testing and construction of simultaneously valid confidence intervals using a multiplier cluster bootstrap. We apply the proposed algorithms to the text regression model of Wu (2018) to examine the presence of gendered language on the internet.
Lyα Observations of High Radial Velocity Low-mass Stars Ross 1044 and Ross 825

The discovery of habitable zone (HZ) planets around low-mass stars has highlighted the need for a comprehensive understanding of the radiation environments in which such planets reside. Of particular importance is knowledge of the far-ultraviolet (FUV) radiation, as low-mass stars are typically much more active than solar-type stars and the proximity of their HZs can be one-tenth the distance. The vast majority of the flux emitted by low-mass stars at FUV wavelengths occurs in the Lyα line at 1216 Å. However, measuring a low-mass star’s Lyα emission directly is almost always impossible because of the contaminating effects of interstellar hydrogen and geocoronal airglow. We observed Ross 825 (K3) and Ross 1044 (M0), two stars with exceptional radial velocities, with the Space Telescope Imaging Spectrograph on board the Hubble Space Telescope. Their radial velocities resulted in significant line shifts, allowing for a more complete view of their Lyα line profiles. We provide an updated relation between effective temperature and Lyα flux using Gaia DR2 astrometry as well as updated, model-independent relationships between Lyα flux and UV flux measurements from the Galaxy Evolution Explorer (GALEX) for low-mass stars. These new relations, in combination with GALEX's considerable spatial coverage, provide substantial predictive power for the Lyα environments for thousands of nearby, low-mass stars.
Topology of generalized spinors and chiral anomaly

Weyl fermions with nonlinear dispersion have appeared in real-world systems, such as in the Weyl semimetals and topological insulators. We consider the most general form of Dirac operators and study its topological properties embedded in the chiral anomaly, in the index theorem, and in the odd-dimensional partition function, by employing the heat kernel. We find that all of these topological quantities are enhanced by a winding number defined by the Dirac operator in the momentum space, regardless of the spacetime dimensions. The chiral anomaly in d=3+1, in particular, is also confirmed via the conventional Feynman diagram. These interconnected results allow us to clarify the relationship between the chiral anomaly and the Chern number of the Berry connection, under dispute in some recent literature, and also lead to a compact proof of the Nielsen-Ninomiya theorem.
New Attacks and Defenses for Randomized Caches

The last level cache is vulnerable to timing based side channel attacks because it is shared by the attacker and the victim processes even if they are located on different cores. These timing attacks evict the victim cache lines using small conflict groups(SCG), and monitor the cache to observe when the victim uses these cache lines again. A conflict group is a collection of cache lines which will evict the target cache line. Randomization is often used by defenses to prevent creation of SCGs. We introduce new attacks to demonstrate that the current randomization schemes require an extremely high refresh rate to be secure, on average a 15\% performance overhead, and upto 50\% in the worst case. Next, we propose a new randomization strategy using an indirection table, which mitigates this issue. Addresses of cache lines are encrypted and used to lookup the indirection table entry. Each indirection table entry stores a mapping to a randomly chosen cache set. The cache line is placed into this randomly chosen set. The encryption key changes upto 50x faster than CEASER's default rate, by using evictions to trigger the re-randomization. Instead of moving cache lines, this mechanism re-randomizes one iTable entry at a time, whenever the cache lines corresponding to the iTable entry are naturally evicted. Thus, the miss rate is not much worse than the baseline. We quantitatively show that our scheme does almost as well as a fully associative cache to defend against these attacks. We also demonstrate new attacks that target the iTable by oversubscribing its entries, and quantitatively show that our scheme is resilient against new attacks for trillions of years. We estimate low area ( < 7\%) and power overhead compared to a baseline inclusive last-level cache. Lastly, we evaluate a low performance overhead (<4%) using the SPECrate 2017 and PARSEC 3.0 benchmarks.
The Infall Motion in the Low-mass Protostellar Binary NGC 1333 IRAS 4A1/4A2

We report ALMA observations of NGC 1333 IRAS 4A, a young low-mass protostellar binary, whose components are referred to as 4A1 and 4A2. With multiple H2CO transitions and HNC (4−3) observed at a resolution of 0. ″25 (∼70 au), we investigate the gas kinematics of 4A1 and 4A2. Our results show that on the large angular scale (∼10″), 4A1 and 4A2 each display a well-collimated outflow along the N–S direction, and an S-shaped morphology is discerned in the outflow powered by 4A2. On the small scale (∼0.″3), 4A1 and 4A2 exhibit distinct spectral features toward the continuum centroid, with 4A1 showing simple symmetric profiles predominantly in absorption and 4A2 demonstrating rather complicated profiles in emission as well as in absorption. Based on radiative transfer modeling exercises, we find that the physical parameters inferred from earlier low-resolution observations cannot be directly extrapolated down to the inner region of 4A1. Possible reasons for the discrepancies between the observed and modeled profiles are discussed. We constrain the mass infall rate in 4A1 to be at most around 3 × 10−5 M⊙ yr−1 at the layer of 75 au. For the kinematics of the inner envelope of 4A2, the absorbing dips in the H2CO spectra are skewed toward the redshifted side and likely signatures of inward motion. These absorbing dips are relatively narrow. This is, like the case for 4A1, significantly slower than the anticipated inflow speed. We estimate a mass infall rate of (3.1–6.2) × 10−5 M☉ yr−1 at the layer of 100 au in 4A2.
Binary Stars in Upper Scorpius

To address the statistics of binary stars in the 8 Myr old Upper Scorpius (USco) star formation region, we conducted a speckle interferometric survey of 614 association members more massive than 0.4 (spectral types earlier than M3V) based on the list of Luhman et al. (2018). We resolved 187 pairs, 55 of which are new discoveries. Also using the published data and the Gaia DR2, a catalog of 250 physical binaries was produced. We carefully estimated detection limits for each target and studied binary statistics in the separation range from 0. ″06 to 20″ (9–2800 au), as well as clustering at larger separations. The frequency of companions with mass ratios q > 0.3 in this separation range is 0.33 ± 0.04 and 0.35 ± 0.04 for early M- and solar-type stars, respectively, larger by 1.62 ± 0.22 and 1.39 ± 0.18 times compared to field stars of similar masses. The excess is produced mostly by pairs closer than 100 au. At separations from 100 to 104 au, the separation distribution and companion fraction resemble those of solar-type stars in the field. However, unlike in the field, we see a relative deficit of equal-mass binaries at separations of ∼500 au, compared to smaller and larger separations. The distribution of q depends on the separation, with a preference of larger q and a larger fraction of twins with q > 0.95 at smaller separations. The binary population of USco differs from binaries in the field in several ways and suggests that binary statistics is not universal.