Miracle-dz/UniFAR-FTUs huggingface dataset:
Percolation in Fock space as a proxy for many-body localization

We study classical percolation models in Fock space as proxies for the quantum many-body localisation (MBL) transition. Percolation rules are defined for two models of disordered quantum spin-chains using their microscopic quantum Hamiltonians and the topologies of the associated Fock-space graphs. The percolation transition is revealed by the statistics of Fock-space cluster sizes, obtained by exact enumeration for finite-sized systems. As a function of disorder strength, the typical cluster size shows a transition from a volume law in Fock space to sub-volume law, directly analogous to the behaviour of eigenstate participation entropies across the MBL transition. Finite-size scaling analyses for several diagnostics of cluster size statistics yield mutually consistent critical properties. We show further that local observables averaged over Fock-space clusters also carry signatures of the transition, with their behaviour across it in direct analogy to that of corresponding eigenstate expectation values across the MBL transition. The Fock-space clusters can be explored under a mapping to kinetically constrained models. Dynamics within this framework likewise show the ergodicity-breaking transition via Monte Carlo averaged local observables, and yield critical properties consistent with those obtained from both exact cluster enumeration and analytic results derived in our recent work [arXiv:1812.05115]. This mapping allows access to system sizes two orders of magnitude larger than those accessible in exact enumerations. Simple physical pictures based on freezing of local real-space segments of spins are also presented, and shown to give values for the critical disorder strength and correlation length exponent $\nu$ consistent with numerical studies.
Ivacaftor drug desensitization

Historically, the treatment of cystic fibrosis (CF) has focused on mitigation of complications arising from defects in the cystic fibrosis transmembrane conductance regulator (CFTR). Drugs that directly target the defects in CFTR provide a novel therapeutic strategy for management of CF. CFTR modulators directly complement defective CFTR and, at least partially, restore CFTR function. Drugs from two classes are currently approved, potentiators (ivacaftor) and correctors (lumacaftor and tezacaftor). Potentiators augment chloride transport by increasing channel opening. Correctors improve the folding and trafficking of CFTR to the cell surface. Therapy of tezacaftor or lumacaftor with ivacaftor has been shown to improve lung function and decrease the rate of pulmonary exacerbations. Incidence of adverse reactions were similar between placebo and lumacaftor/ivacaftor or tezacaftor/ivacaftor in trials. Rash was documented as an adverse reaction to ivacaftor monotherapy, lumacaftor/ivacaftor, and tezacaftor/ivacaftor in 5% or less of all patients in phase 3 clinical trials. No rash was reported to be severe or life‐threatening. Herein, we present a case of rash associated with ivacaftor and our approach to management.
Restricting Control Flow During Speculative Execution with Venkman

Side-channel attacks such as Spectre that utilize speculative execution to steal application secrets pose a significant threat to modern computing systems. While program transformations can mitigate some Spectre attacks, more advanced attacks can divert control flow speculatively to bypass these protective instructions, rendering existing defenses useless. In this paper, we present Venkman: a system that employs program transformation to completely thwart Spectre attacks that poison entries in the Branch Target Buffer (BTB) and the Return Stack Buffer (RSB). Venkman transforms code so that all valid targets of a control-flow transfer have an identical alignment in the virtual address space; it further transforms all branches to ensure that all entries added to the BTB and RSB are properly aligned. By transforming all code this way, Venkman ensures that, in any program wanting Spectre defenses, all control-flow transfers, including speculative ones, do not skip over protective instructions Venkman adds to the code segment to mitigate Spectre attacks. Unlike existing defenses, Venkman does not reduce sharing of the BTB and RSB and does not flush these structures, allowing safe sharing and reuse among programs while maintaining strong protection against Spectre attacks. We built a prototype of Venkman on an IBM POWER8 machine. Our evaluation on the SPEC benchmarks and selected applications shows that Venkman increases execution time to 3.47$\times$ on average and increases code size to 1.94$\times$ on average when it is used to ensure that fences are executed to mitigate Spectre attacks. Our evaluation also shows that Spectre-resistant Software Fault Isolation (SFI) built using Venkman incurs a geometric mean of 2.42$\times$ space overhead and 1.68$\times$ performance overhead.
Quantum communication by means of collapse of the wave function

We show that quantum communication by means of collapse of the wave function is possible. In this study, quantum communication does not mean quantum teleportation or quantum cryptography, but transmission of information itself. Because of consistency with special relativity, the possibility of the quantum communication leads to another conclusion that the collapse of the wave function must propagate at the speed of light or slower. We show this requirement is consistent with nonlocality in quantum mechanics. We also demonstrate that the Einstein-Podolsky-Rosen experiment does not disprove our conclusion.
Personal Privacy Filtering via Face Pixelation in Live Video Streaming

Face pixelation in TV shows or videos is manually realized and not well studied to date. As the prevailing of online video streaming, we develop a new tool called face pixelation in live-streaming (FPLV) to generate automatic personal privacy filtering during unconstrained streaming. FPLV is organized in a frame-to-video structure for fast and accurate face pixelation of irrelevant people. Leveraging image-based face detection and recognition networks on individual frames, we propose a positioned incremental affinity propagation (PIAP) clustering algorithm to associate faces across frames. Through deep feature and position aggregated affinities, PIAP handles the cluster number generation, new cluster discovering, and faces' raw trajectories forming simultaneously. Affected by various factors, raw trajectories might be intermittent and unreliable. Hence, we introduce a proposal net for loosed face detection with an empirical likelihood test to compensate the deep network insufficiency and refine the raw trajectories. A Gaussian filter is laid on refined trajectories for final pixelation. FPLV obtains satisfying accuracy and real-time performances under streaming video data we collected.
The interplay between TGF‐β‐stimulated TSC22 domain family proteins regulates cell‐cycle dynamics in medulloblastoma cells

Proteins belonging to the TGFβ‐stimulated clone 22 domain (TSC22D) family display a repertoire of activities, regulating cell proliferation and differentiation. The tumor suppressor activity of the first identified member of the family, TSC22D1 (formerly named TSC‐22), has been extensively studied, but afterward a longer isoform encoded by the same gene turned out to play an opposite role.
Sputum Autoantibodies Are More Relevant in Autoimmune Responses in Asthma than Are Serum Autoantibodies

Purpose The data on the differences between sputum autoantibodies (Sp-Abs) and serum autoantibodies (Se-Abs) in reflection of autoimmune responses to lungs is still lacking. Methods Ten types of Abs were investigated in matched Se and Sp samples collected from recruited subjects. Correlations between Ab levels and airway inflammatory parameters and measures of pulmonary function were assessed. The network-based and inter-correlated analysis was performed to explore the patterns of Sp- and Se-Ab profiles. Results Fifty stable asthmatic patients and 24 healthy volunteers were recruited for our study, 15 with mild asthma, 18 with moderate asthma and 17 with severe asthma. The concentrations of Sp-Ab against U1 small nuclear ribonucleoprotein (Sp-anti-U1-SnRNP), Sp-Ab against Smith antigen and Se-Ab against thyroid peroxidase (anti-TPO) in severe asthmatics and Sp-anti-U1-SnRNP in moderate asthmatics were significantly higher compared to healthy controls and mild asthmatic subjects (P < 0.05). Sp-anti-U1-SnRNP levels were positively correlated with the dose of inhaled corticosteroids, Sp eosinophil counts and fractional exhaled nitric oxide (r = 0.326, P = 0.022; r = 0.356, P = 0.012; r = 0.241, P = 0.025, respectively) and negatively correlated with Sp neutrophil counts (r = −0.308, P = 0.031) with adjustment for age. Spearman's correlation matrix showed multiple inter-correlations among Sp-Abs and Se-Abs (P < 0.05) while only the levels of Ab against DNA topoisomerase and anti-TPO in Se were correlated with those Sp-Ab counterparts (P < 0.05). The network-based analysis defined 2 clusters: clusters 1 and 2 contained 10 Sp-Abs and 10 Se-Abs, respectively. Conclusions This study observes that Sp-Abs are more associated with clinical parameters and the severity of disease in asthma compared to Se-Abs. Targeting on Sp-Abs which are the hallmark of the localized autoimmune event might help us better understand the role of autoimmunity in the pathological mechanism of asthma.
Statistical methodological review for time-series data

Abstract Numerous literatures on statistical methods for Time-Series (TS) data have been published. In this paper, a literature of the TS data analysis methods is reviewed. We organize the review based on the basic three-family category of TS models: The Exponential Smoothing Model (ESM) family, the Auto-Regressive Integrated Moving Average (ARIMA) model family, and the Unobserved Component Model (UCM) family. A roadmap is provided in a diagram format to these TS methods which are translatable into nowadays computing statements. Further, the execution of these methods in SAS commands (as one of the most popular nowadays statistical software packages) is also presented. This paper will be very beneficial for practitioners, forecasters, and researchers in diverse fields of study (such as business, management, finance, economics, etc.) to determine which TS data analysis method (along with the corresponding SAS command) are ready to use.
Development of Iron Speciation Reference Materials for Palaeoredox Analysis

The development and application of geochemical techniques to identify redox conditions in modern and ancient aquatic environments has intensified over recent years. Iron (Fe) speciation has emerged as one of the most widely used procedures to distinguish different redox regimes in both the water column and sediments, and is the main technique used to identify oxic, ferruginous (anoxic, Fe(II) containing) and euxinic (anoxic, sulfidic) water column conditions. However, an international sediment reference material has never been developed. This has led to concern over the consistency of results published by the many laboratories that now utilise the technique. Here, we report an interlaboratory comparison of four Fe speciation reference materials for palaeoredox analysis, which span a range of compositions and reflect deposition under different redox conditions. We provide an update of extraction techniques used in Fe speciation and assess the effects of both test portion mass, and the use of different analytical procedures, on the quantification of different Fe fractions in sedimentary rocks. While atomic absorption spectroscopy and inductively coupled plasma‐optical emission spectrometry produced comparable Fe measurements for all extraction stages, the use of ferrozine consistently underestimated Fe in the extraction step targeting mixed ferrous–ferric minerals such as magnetite. We therefore suggest that the use of ferrozine is discontinued for this Fe pool. Finally, we report the combined data of four independent Fe speciation laboratories to characterise the Fe speciation composition of the reference materials. These reference materials are available to the community to provide an essential validation of in‐house Fe speciation measurements.
Investigation of the WR 11 field at decimeter wavelengths

The massive binary system WR 11 (γ2-Velorum) has recently been proposed as the counterpart of a Fermi source. If this association is correct, this system would be the second colliding wind binary detected in GeV γ-rays. However, the reported flux measurements from 1.4 to 8.64 GHz fail to establish the presence of nonthermal (synchrotron) emission from this source. Moreover, WR 11 is not the only radio source within the Fermi detection box. Other possible counterparts have been identified in archival data, some of which present strong nonthermal radio emission. We conducted arcsec-resolution observations toward WR 11 at very low frequencies (150–1400 MHz) where the nonthermal emission – if existent and not absorbed – is expected to dominate. We present a catalog of more than 400 radio emitters, among which a significant portion are detected at more than one frequency, including limited spectral index information. Twenty-one of these radio emitters are located within the Fermi significant emission. A search for counterparts for this last group pointed at MOST 0808–471; this source is 2′ away from WR 11 and is a promising candidate for high-energy emission, having a resolved structure along 325–1390 MHz. For this source, we reprocessed archive interferometric data up to 22.3 GHz and obtained a nonthermal radio spectral index of − 0.97 ± 0.09. However, multiwavelength observations of this source are required to establish its nature and to assess whether it can produce (part of) the observed γ-rays. WR 11 spectrum follows a spectral index of 0.74 ± 0.03 from 150 to 230 GHz, consistent with thermal emission. We interpret that any putative synchrotron radiation from the colliding-wind region of this relatively short-period system is absorbed in the photospheres of the individual components. Notwithstanding, the new radio data allowed us to derive a mass-loss rate of 2.5 × 10−5 M⊙ yr−1, which, according to the latest models for γ-ray emission in WR 11, would suffice to provide the required kinetic power to feed nonthermal radiation processes.
Automatic Detection of Interplanetary Coronal Mass Ejections from In Situ Data: A Deep Learning Approach

Decades of studies have suggested several criteria to detect interplanetary coronal mass ejections (ICME) in time series from in situ spacecraft measurements. Among them, the most common are an enhanced and smoothly rotating magnetic field, a low proton temperature, and a low plasma beta. However, these features are not all observed for each ICME due to their strong variability. Visual detection is time-consuming and biased by the observer interpretation, leading to non-exhaustive, subjective, and thus hardly reproducible catalogs. Using convolutional neural networks on sliding windows and peak detection, we provide a fast, automatic, and multi-scale detection of ICMEs. The method has been tested on the in situ data from WIND between 1997 and 2015, and on the 657 ICMEs that were recorded during this period. The method offers an unambiguous visual proxy of ICMEs that gives an interpretation of the data similar to what an expert observer would give. We found at a maximum 197 of the 232 ICMEs of the 2010–2015 period (recall 84% ± 4.5%), including 90% of the ICMEs present in the lists of Nieves-Chinchilla et al. and Chi et al. The minimal number of False Positives was 25 out of 158 predicted ICMEs (precision 84% ± 2.6%). Although less accurate, the method also works with one or several missing input parameters. The method has the advantage of improving its performance by just increasing the amount of input data. The generality of the method paves the way for automatic detection of many different event signatures in spacecraft in situ measurements.
Simulated Sensor Based Strategies for Obstacle Avoidance Using Velocity Profiling for Autonomous Vehicle FURBOT

Freight Urban Robotic Vehicle (FURBOT) is an autonomous vehicle designed to transport last mile freight to designated urban stations. It is a slow vehicle designed to tackle urban environment with complete autonomy. A slow vehicle may have slightly different strategies for avoiding obstacles. Unlike on a highway, it has to deal with pedestrians, traffic lights and slower vehicles while maintaining smoothness in its drive. To tackle obstacle avoidance for this vehicle, sensor feedback based strategies have been formulated for smooth drive and obstacle avoidance. A full mathematical model for the vehicle is formulated and simulated in MATLAB environment. The mathematical model uses velocity control for obstacle avoidance without steering control. The obstacle avoidance is attained through velocity control and strategies are formulated with velocity profiling. Innovative techniques are formulated in creating the simulated sensory feed-backs of the environment. Using these feed-backs, correct velocity profiling is autonomously created for giving velocity profile input to the velocity controller. Proximity measurements are assumed to be available for the vehicle in its given range of drive. Novelty is attained by manipulating velocity profile without prior knowledge of the environment. Four different type of obstacles are modeled for simulated environment of the vehicle. These obstacles are randomly placed in the path of the vehicle and autonomous velocity profiling is verified in simulated environment. The simulated results obtained show satisfactory velocity profiling for controller input. The current technique helps to tune the existing controller and in designing of a better velocity controller for the autonomous vehicle and bridges the gap between sensor feed-back and controller input. Moreover, accurate input profiling creates less strain on the system and brings smoothness in drive for an overall safer environment.
Protocols for Packet Quantum Network Intercommunication

A quantum network, which involves multiple parties pinging each other with quantum messages, could revolutionize communication, computing, and basic sciences. The future internet will be a global system of various packet switching quantum and classical networks, and we call it quantum internet. To build a quantum Internet, unified protocols that support the distribution of quantum messages within it are necessary. Intuitively, one would extend classical internet protocols to handle quantum messages. However, classical network mechanisms, especially those related to error control and reliable connection, implicitly assume that information can be duplicated, which is not true in the quantum world due to the no-cloning theorem and monogamy of entanglement. In this article, we investigate and propose protocols for packet quantum network intercommunication. To handle the packet loss problem in transport, we propose a quantum retransmission protocol based on the recursive use of a quantum secret sharing scheme. Other Internet protocols are also discussed. In particular, the creation of logical process-to-process connections is accomplished by a quantum version of the three-way handshake protocol.
Loopy Cuts: Surface-Field Aware Block Decomposition for Hex-Meshing

We present a new fully automatic block-decomposition hexahedral meshing algorithm capable of producing high quality meshes that strictly preserve feature curve networks on the input surface and align with an input surface cross-field. We produce all-hex meshes on the vast majority of inputs, and introduce localized non-hex elements only when the surface feature network necessitates those. The input to our framework is a closed surface with a collection of geometric or user-demarcated feature curves and a feature-aligned surface cross-field. Its output is a compact set of blocks whose edges interpolate these features and are loosely aligned with this cross-field. We obtain this block decomposition by cutting the input model using a collection of simple cutting surfaces bounded by closed surface loops. The set of cutting loops spans the input feature curves, ensuring feature preservation, and is obtained using a field-space sampling process. The computed loops are uniformly distributed across the surface, cross orthogonally, and are loosely aligned with the cross-field directions, inducing the desired block decomposition. We validate our method by applying it to a large range of complex inputs and comparing our results to those produced by state-of-the-art alternatives. Contrary to prior approaches, our framework consistently produces high-quality field aligned meshes while strictly preserving geometric or user-specified surface features.
Constructing networks by filtering correlation matrices: a null model approach

Network analysis has been applied to various correlation matrix data. Thresholding on the value of the pairwise correlation is probably the most straightforward and common method to create a network from a correlation matrix. However, there have been criticisms on this thresholding approach such as an inability to filter out spurious correlations, which have led to proposals of alternative methods to overcome some of the problems. We propose a method to create networks from correlation matrices based on optimization with regularization, where we lay an edge between each pair of nodes if and only if the edge is unexpected from a null model. The proposed algorithm is advantageous in that it can be combined with different types of null models. Moreover, the algorithm can select the most plausible null model from a set of candidate null models using a model selection criterion. For three economic datasets, we find that the configuration model for correlation matrices is often preferred to standard null models. For country-level product export data, the present method better predicts main products exported from countries than sample correlation matrices do.
Relationship Between PNPLA3 rs738409 Polymorphism and Decreased Kidney Function in Children With NAFLD

Emerging evidence suggests that patatin‐like phospholipase domain–containing protein‐3 (PNPLA3) rs738409 genotype (the major genetic variant associated with susceptibility to nonalcoholic fatty liver disease [NAFLD]) is associated with decreased kidney function in adults. Currently, it is uncertain whether this association also occurs in children/adolescents and whether any association is independent of liver disease severity. We enrolled a sample of 142 Caucasian children and adolescents with biopsy‐proven NAFLD, presenting to the Liver Unit of the “Bambino Gesù” Children's Hospital. The glomerular filtration rate (e‐GFR) was estimated using the Bedside Schwartz equation, whereas 24‐hour proteinuria was measured using a radioimmunoassay method. Genotyping for the PNPLA3 rs738409 genotype was undertaken using the single‐nucleotide polymorphism genotyping allelic discrimination method. Overall, 45 children had G/G, 56 had G/C, and 41 had C/C PNPLA3 rs738409 genotype, respectively. Children with G/G genotype had significantly lower e‐GFR (107.5 ± 20 versus 112.8 ± 18 versus 125.3 ± 23 mL/min/1.73 m2, P = 0.002) and higher 24‐hour proteinuria (58.5 ± 21 versus 53.9 ± 22 versus 42.9 ± 20 mg/day, P = 0.012) compared with those with either G/C or C/C genotypes. After adjustment for age, sex, systolic blood pressure, measures of adiposity, homeostasis model assessment–estimated insulin resistance and biopsy‐confirmed nonalcoholic steatohepatitis and stage of liver fibrosis, the presence of rs738409 G/G genotype was independently associated with both lower e‐GFR (β coefficient: −23.6; 95% confidence interval [CI]: −36.3 to −10.8; P < 0.001) and higher 24‐hour proteinuria (β coefficient: 15.3; 95% CI: 1.12 to 30.5; P = 0.046). Conclusion: Regardless of established renal risk factors and the histological severity of NAFLD, the PNPLA3 G/G genotype was strongly associated with decreasing kidney function and increasing 24‐hour proteinuria in children/adolescents with histologically confirmed NAFLD.