Miracle-dz/UniFAR-FTUs huggingface dataset:
ZombieLoad: Cross-Privilege-Boundary Data Sampling

In early 2018, Meltdown first showed how to read arbitrary kernel memory from user space by exploiting side-effects from transient instructions. While this attack has been mitigated through stronger isolation boundaries between user and kernel space, Meltdown inspired an entirely new class of fault-driven transient-execution attacks. Particularly, over the past year, Meltdown-type attacks have been extended to not only leak data from the L1 cache but also from various other microarchitectural structures, including the FPU register file and store buffer. In this paper, we present the ZombieLoad attack which uncovers a novel Meltdown-type effect in the processor's fill-buffer logic. Our analysis shows that faulting load instructions (i.e., loads that have to be re-issued) may transiently dereference unauthorized destinations previously brought into the fill buffer by the current or a sibling logical CPU. In contrast to concurrent attacks on the fill buffer, we are the first to report data leakage of recently loaded and stored stale values across logical cores even on Meltdown- and MDS-resistant processors. Hence, despite Intel's claims, we show that the hardware fixes in new CPUs are not sufficient. We demonstrate ZombieLoad's effectiveness in a multitude of practical attack scenarios across CPU privilege rings, OS processes, virtual machines, and SGX enclaves. We discuss both short and long-term mitigation approaches and arrive at the conclusion that disabling hyperthreading is the only possible workaround to prevent at least the most-powerful cross-hyperthread attack scenarios on current processors, as Intel's software fixes are incomplete.
Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection

We introduce a novel unsupervised domain adaptation approach for object detection. We aim to alleviate the imperfect translation problem of pixel-level adaptations, and the source-biased discriminativity problem of feature-level adaptations simultaneously. Our approach is composed of two stages, i.e., Domain Diversification (DD) and Multi-domain-invariant Representation Learning (MRL). At the DD stage, we diversify the distribution of the labeled data by generating various distinctive shifted domains from the source domain. At the MRL stage, we apply adversarial learning with a multi-domain discriminator to encourage feature to be indistinguishable among the domains. DD addresses the source-biased discriminativity, while MRL mitigates the imperfect image translation. We construct a structured domain adaptation framework for our learning paradigm and introduce a practical way of DD for implementation. Our method outperforms the state-of-the-art methods by a large margin of 3%~11% in terms of mean average precision (mAP) on various datasets.
Spectral and Timing Analysis of the Accretion-powered Pulsar 4U 1626–67 Observed with Suzaku and NuSTAR

We present an analysis of the spectral shape and pulse profile of the accretion-powered pulsar 4U 1626−67 observed with Suzaku and Nuclear Spectroscopic Telescope Array (NuSTAR) during a spin-up state. The pulsar, which experienced a torque reversal to spin-up in 2008, has a spin period of ∼7.7 s. Comparing the phase-averaged spectra obtained with Suzaku in 2010 and with NuSTAR in 2015, we find that the spectral shape changed between the two observations: the 3–10 keV flux increased by ∼5%, while the 30–60 keV flux decreased significantly by ∼35%. Phase-averaged and phase-resolved spectral analysis shows that the continuum spectrum observed by NuSTAR is well described by an empirical negative and positive power law times exponential continuum with an added broad Gaussian emission component around the spectral peak at ∼20 keV. Taken together with the observed value obtained from the Fermi/gamma-ray burst monitor data, we conclude that the spectral change between the Suzaku and NuSTAR observations was likely caused by an increase in the accretion rate. We also report the possible detection of asymmetry in the profile of the fundamental cyclotron line. Furthermore, we present a study of the energy-resolved pulse profiles using a new relativistic ray tracing code, where we perform a simultaneous fit to the pulse profiles assuming a two-column geometry with a mixed pencil- and fan-beam emission pattern. The resulting pulse profile decompositions enable us to obtain geometrical parameters of accretion columns (inclination, azimuthal and polar angles) and a fiducial set of beam patterns. This information is important to validate the theoretical predictions from radiation transfer in a strong magnetic field.
Intraoperative detection of aberrant biliary anatomy via intraoperative cholangiography during laparoscopic cholecystectomy

Laparoscopic cholecystectomy (LC) is the standard of treatment for symptomatic cholelithiasis. Although intraoperative cholangiography (IOC) is widely used as an adjunct to LC, there is still no worldwide consensus on the value of its routine use. Anatomical studies have shown that variations of the biliary tree are present in approximately 35% of patients with variations in right hepatic second‐order ducts being especially common (15–20%). Approximately, 70–80% of all iatrogenic bile duct injuries are a consequence of misidentification of biliary anatomy. The purpose of this study was to assess the adequacy of and the reporting of IOCs during LC.
Stochastic Gradient Coding for Straggler Mitigation in Distributed Learning

We consider distributed gradient descent in the presence of stragglers. Recent work on <italic>gradient coding</italic> and <italic>approximate gradient coding</italic> have shown how to add redundancy in distributed gradient descent to guarantee convergence even if some workers are <italic>stragglers</italic>—that is, slow or non-responsive. In this work we propose an approximate gradient coding scheme called <italic>Stochastic Gradient Coding</italic> (SGC), which works when the stragglers are random. SGC distributes data points redundantly to workers according to a pair-wise balanced design, and then simply ignores the stragglers. We prove that the convergence rate of SGC mirrors that of batched Stochastic Gradient Descent (SGD) for the <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula> loss function, and show how the convergence rate can improve with the redundancy. We also provide bounds for more general convex loss functions. We show empirically that SGC requires a small amount of redundancy to handle a large number of stragglers and that it can outperform existing approximate gradient codes when the number of stragglers is large.
Learning for Matching Game in Cooperative D2D Communication With Incomplete Information

This paper considers a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the opportunities to use licensed spectrum. Based on the interaction of each D2D pair and each CU, we formulate the pairing problem between multiple CUs and multiple D2D pairs as a one-to-one matching game. Unlike most existing works, we consider a realistic scenario with incomplete channel information. Thus, each CU lacks enough information to establish its preference over D2D pairs. Therefore, traditional matching algorithms are not suitable for our scenario. To this end, we convert the matching game to an equivalent non-cooperative game, and then propose a novel learning algorithm, which converges to a stable matching.
Uniformizing surfaces via discrete harmonic maps

We show that for any closed surface of genus greater than one and for any finite weighted graph filling the surface, there exists a hyperbolic metric which realizes the least Dirichlet energy harmonic embedding of the graph among a fixed homotopy class and all hyperbolic metrics on the surface. We give explicit examples of such hyperbolic surfaces as a refinement of the Nielsen realization problem for the mapping class groups.
L O ] 1 4 M ay 2 01 9 Weighted parametric systems : Modelling and architecture specification

Modern systems’ design usually lies in multiple components which are connected via their interfaces. Synchronous applications, like IoT, require parametric systems, i.e., systems that aim to operate independently of the number of their components. A key feature in modelling of parametric systems is the architecture specification that defines the underlying topology and provides coordination rules. On the other hand, to achieve optimized requirements and performance there is need for describing parametric architectures and parametric behavior in a quantitative setting. In this paper we study the quantitative modelling and architecture specification of component-based parametric systems. We introduce a weighted extended first-order interaction logic as a specification language for weighted parametric architectures. We also introduce weighted parametric models defined by composed transition systems whose interactions are expressed by formulas of our weighted logic. Equivalence of weighted extended first-order interaction logic formulas is decidable in the class of computable fields. We show that our weighted logic can efficiently describe several software architectures with quantitative characteristics.
Cusp cobordism group of Morse functions

By a Morse function on a compact manifold with boundary we mean a real-valued function without critical points near the boundary such that its critical points as well as the critical points of its restriction to the boundary are all nondegenerate. For such Morse functions, Saeki and Yamamoto have previously defined a certain notion of cusp cobordism, and computed the unoriented cusp cobordism group of Morse functions on surfaces. In this paper, we compute unoriented and oriented cusp cobordism groups of Morse functions on manifolds of any dimension by employing Levine’s cusp elimination technique as well as the complementary process of creating pairs of cusps along fold lines. We show that both groups are cyclic of order two in even dimensions, and cyclic of infinite order in odd dimensions. For Morse functions on surfaces our result yields an explicit description of Saeki–Yamamoto’s cobordism invariant which they constructed by means of the cohomology of the universal complex of singular fibers.
Mechanism of Growth Promoting Activity of Epiregulin in Primary Cultures of Rat Hepatocytes

In spite of lower receptor affinity, epiregulin exhibits a stronger stimulation of DNA synthesis than epidermal growth factor (EGF) in rat hepatocytes. To determine the mechanism of stimulation, we examined the activities of epiregulin on growth stimulation, signal transduction, and mRNA induction of hepatotrophic factors in primary cultures of rat hepatocytes. Epiregulin stimulated hepatocyte proliferation as efficiently as hepatotrophic factors, including heparin-binding EGF-like growth factor (HB-EGF) and transforming growth factor- f (TGF- f ). Epiregulin induced a more prolonged activation of EGF receptor (EGFR) and p42/44 mitogen-activated protein kinase (MAPK) than EGF. Furthermore, epiregulin up-regulated the mRNAs of TGF- f and HB-EGF, and in turn, these growth factors enhanced the expression of epiregulin mRNA. In vivo, increased production of epiregulin was noted in extracts of the remnant liver obtained 24 h after partial hepatectomy, and EGFR phosphorylation by these extracts was partially inhibited by anti-epiregulin antibody. Our results showed a more potent hepatocyte proliferative activity for epiregulin compared with EGF in vitro, which depends on prolonged activation of EGFR and p42/44 MAPK. Our findings suggest that epiregulin may play significant roles in liver regeneration following partial hepatectomy in cooperation with other growth factors.
TauRieL: Targeting Traveling Salesman Problem with a deep reinforcement learning inspired architecture

In this paper, we propose TauRieL and target Traveling Salesman Problem (TSP) since it has broad applicability in theoretical and applied sciences. TauRieL utilizes an actor-critic inspired architecture that adopts ordinary feedforward nets to obtain a policy update vector $v$. Then, we use $v$ to improve the state transition matrix from which we generate the policy. Also, the state transition matrix allows the solver to initialize from precomputed solutions such as nearest neighbors. In an online learning setting, TauRieL unifies the training and the search where it can generate near-optimal results in seconds. The input to the neural nets in the actor-critic architecture are raw 2-D inputs, and the design idea behind this decision is to keep neural nets relatively smaller than the architectures with wide embeddings with the tradeoff of omitting any distributed representations of the embeddings. Consequently, TauRieL generates TSP solutions two orders of magnitude faster per TSP instance as compared to state-of-the-art offline techniques with a performance impact of 6.1\% in the worst case.
Strategic processing in long-term repetition priming in the lexical decision task

In a lexical decision task, faster reaction times (RTs) for old than new items is taken as evidence for an implicit memory involvement in this task. In contrast, the present study shows the involvement of both implicit and explicit memory in repetition priming. We propose a dual route model, in which lexical decisions can be made using one of two parallel processing routes: a lexical route, in which the lexical properties of the stimulus are used to determine whether it is a word or not, and a strategic route that builds on the inherent correlation between “wordness” and “oldness” in the experiment. Eliminating the strategic route by removing this correlation diminishes the priming effect at the slow end of the RT distribution, but not at the fast end. This dissociation is interpreted as evidence for the involvement of both implicit and explicit memory in repetition priming.
Nurse-led implementation of a safe and effective intravenous insulin protocol in a medical intensive care unit.

BACKGROUND Recent evidence has linked tight glucose control to worsened clinical outcomes among adults in intensive care units. OBJECTIVE To evaluate the effectiveness and safety of a nurse-led intravenous insulin protocol designed to achieve conservative blood glucose control in patients in a medical intensive care unit. METHODS A nurse-led intravenous insulin protocol was developed, targeting blood glucose levels at 110 to 149 mg/dL. Hypoglycemia was defined as a blood glucose level less than 70 mg/dL. Patients admitted to the medical intensive care unit who required an insulin infusion were enrolled in the study. Blood glucose levels in those patients were compared with levels in 153 historical control patients admitted to the unit in the 12 months before the protocol was implemented who required an insulin infusion. RESULTS Ninety-six patients were enrolled and treated with the protocol. The protocol and control groups had similar characteristics at baseline. More measurements in the protocol group than in the control group (46.3% vs 36.1%, P<.001) were within the target glucose range (110-149 mg/dL). Hyperglycemia (blood glucose ≥200 mg/dL) occurred less often in the protocol group than in the control group (14.8% vs 20.1%, P=.003). Hypoglycemic events (blood glucose <70 mg/dL) also occurred less often in the protocol group (0.07% vs 0.83%, P<.001). CONCLUSIONS Implementation of a nurse-led, conservative intravenous insulin protocol in the medical intensive care unit is effective and safe and markedly reduces the rate of hypoglycemia.
Transtemporal edges and crosslayer edges in incompressible high-order networks

This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph represen tation. We study some of their network topological properties and how these may be related to real world complex networks. We show that these networks have very short diameter, high k-connectivity, degrees of the order of half of the network size within a strong-asymptotically dominated standard deviation, and rigidity with respect to automorphisms. In addition, we demonstrate that incompressible dynamic (or dynamic multilayered) networks have transtemporal (or crosslayer) edges and, thus, a snapshot-like representation of dynamic networks is inaccurate for capturing the presence of such edges that compose underlying structures of some real-world networks.
Positivity determines the quantum cohomology of Grassmannians

We prove that if X is a Grassmannian of type A, then the Schubert basis of the (small) quantum cohomology ring QH(X) is the only homogeneous deformation of the Schubert basis of the ordinary cohomology ring of X that multiplies with non-negative structure constants. This implies that the (three point, genus zero) Gromov-Witten invariants of X are uniquely determined by Witten's presentation of QH(X) and the fact that they are non-negative. We conjecture that the same is true for any flag variety X = G/P of simply laced Lie type. For the variety GL(n)/B of complete flags, this conjecture is equivalent to Fomin, Gelfand, and Postnikov's conjecture that the quantum Schubert polynomials of type A are uniquely determined by positivity properties. Our proof for Grassmannians answers a question of Fulton.
Mitigation of reversible self-association and viscosity in a human IgG1 monoclonal antibody by rational, structure-guided Fv engineering

ABSTRACT Undesired solution behaviors such as reversible self-association (RSA), high viscosity, and liquid-liquid phase separation can introduce substantial challenges during development of monoclonal antibody formulations. Although a global mechanistic understanding of RSA (i.e., native and reversible protein-protein interactions) is sufficient to develop robust formulation controls, its mitigation via protein engineering requires knowledge of the sites of protein-protein interactions. In the study reported here, we coupled our previous hydrogen-deuterium exchange mass spectrometry findings with structural modeling and in vitro screening to identify the residues responsible for RSA of a model IgG1 monoclonal antibody (mAb-C), and rationally engineered variants with improved solution properties (i.e., reduced RSA and viscosity). Our data show that mutation of either solvent-exposed aromatic residues within the heavy and light chain variable regions or buried residues within the heavy chain/light chain interface can significantly mitigate RSA and viscosity by reducing the IgG's surface hydrophobicity. The engineering strategy described here highlights the utility of integrating complementary experimental and in silico methods to identify mutations that can improve developability, in particular, high concentration solution properties, of candidate therapeutic antibodies.
Gonadotropin-Releasing Hormone and Its Receptors in Rat Brain

Since the chemical identification of gonadotropin-releasing hormone (GnRH) in 1971, significant progress has been made in understanding the mechanisms by which GnRH action is mediated in the anterior pituitary. In contrast, relatively little information is available which identifies the intracerebral sites and mechanisms of action of GnRH in the brain. Early immunohistochemical studies of GnRH distribution in the central nervous system, together with behavioral and electrophysiological experiments, suggested that GnRH functioned as a neurotransmitter and was, possibly, involved in the expression of reproductive behaviors. The subsequent identification and characterization of GnRH receptors in the brain further strengthened the view that GnRH caused specific effects in select regions of the brain known to be involved in the neuroendocrine regulation of the anterior pituitary and in the generation of reproductive behaviors. After the mouse pituitary GnRH receptor was cloned it became possible to identify brain neurons which contained the GnRH receptor mRNA. Comparison of the locations of the GnRH peptide, the GnRH receptor protein, and the neurons which contain the GnRH receptor mRNA suggests that the GnRH neuronal system itself can potentially provide a direct link between the neuroendocrine regulation of anterior pituitary function and the intracerebral regulation of reproductive behaviors; furthermore, it is possible that the GnRH neuronal system takes an active part in intracerebral feedback loop systems between the mediobasal hypothalamus and the septum-diagonal band which regulate GnRH release from the median eminence.
Tubulin Acetylation Mediates Bisphenol A Effects on the Microtubule Arrays of Allium cepa and Triticum turgidum

The effects of bisphenol A (BPA), a prevalent endocrine disruptor, on both interphase and mitotic microtubule array organization was examined by immunofluorescence microscopy in meristematic root cells of Triticum turgidum (durum wheat) and Allium cepa (onion). In interphase cells of A. cepa, BPA treatment resulted in substitution of cortical microtubules by annular/spiral tubulin structures, while in T. turgidum BPA induced cortical microtubule fragmentation. Immunolocalization of acetylated α-tubulin revealed that cortical microtubules of T. turgidum were highly acetylated, unlike those of A. cepa. In addition, elevation of tubulin acetylation by trichostatin A in A. cepa resulted in microtubule disruption similar to that observed in T. turgidum. BPA also disrupted all mitotic microtubule arrays in both species. It is also worth noting that mitotic microtubule arrays were acetylated in both plants. As assessed by BPA removal, its effects are reversible. Furthermore, taxol-stabilized microtubules were resistant to BPA, while recovery from oryzalin treatment in BPA solution resulted in the formation of ring-like tubulin conformations. Overall, these findings indicate the following: (1) BPA affects plant mitosis/cytokinesis by disrupting microtubule organization. (2) Microtubule disassembly probably results from impairment of free tubulin subunit polymerization. (3) The differences in cortical microtubule responses to BPA among the species studied are correlated to the degree of tubulin acetylation.
Validation of a temperate fourth planet in the K2-133 multiplanet system

We present follow-up observations of the K2-133 multiplanet system. Previously, we announced that K2-133 contained three super-Earths orbiting an M1.5V host star – with tentative evidence of a fourth outer-planet orbiting at the edge of the temperate zone. Here, we report on the validation of the presence of the fourth planet, determining a radius of $1. 73_{-0.13}^{+0.14}$ R⊕. The four planets span the radius gap of the exoplanet population, meaning further follow-up would be worthwhile to obtain masses and test theories of the origin of the gap. In particular, the trend of increasing planetary radius with decreasing incident flux in the K2-133 system supports the claim that the gap is caused by photo-evaporation of exoplanet atmospheres. Finally, we note that K2-133 e orbits on the edge of the star's temperate zone, and that our radius measurement allows for the possibility that this is a rocky world. Additional mass measurements are required to confirm or refute this scenario.