Miracle-dz/UniFAR-FTUs huggingface dataset:
Robotic Assembly Control Reconfiguration Based on Transfer Reinforcement Learning for Objects with Different Geometric Features

Robotic force-based compliance control is a preferred approach to achieve high-precision assembly tasks. When the geometric features of assembly objects are asymmetric or irregular, reinforcement learning (RL) agents are gradually incorporated into the compliance controller to adapt to complex force-pose mapping which is hard to model analytically. Since force-pose mapping is strongly dependent on geometric features, a compliance controller is only optimal for current geometric features. To reduce the learning cost of assembly objects with different geometric features, this paper is devoted to answering how to reconfigure existing controllers for new assembly objects with different geometric features. In this paper, model-based parameters are first reconfigured based on the proposed Equivalent Theory of Compliance Law (ETCL). Then the RL agent is transferred based on the proposed Weighted Dimensional Policy Distillation (WDPD) method. The experiment results demonstrate that the control reconfiguration method costs less time and achieves better control performance, which confirms the validity of proposed methods.
Collaborative Multiobjective Evolutionary Algorithms in search of better Pareto Fronts. An application to trading systems

Technical indicators use graphic representations of datasets by applying various mathematical formulas to financial time series of prices. These formulas comprise a set of rules and parameters whose values are not necessarily known and depend on many factors, such as the market in which they operate, the size of the time window, and so on. This paper focuses on the real-time optimization of the parameters applied for analyzing time series of data. In particular, we optimize the parameters of some technical financial indicators. We propose the combination of several Multiobjective Evolutionary Algorithms. Unlike other approaches, this paper applies a set of different Multiobjective Evolutionary Algorithms, collaborating to construct a global Pareto Set of solutions. Solutions for financial problems seek high returns with minimal risk. The optimization process is continuous and occurs at the same frequency as the investment time interval. This technique permits the application of the non-dominated solutions obtained with different MOEAs at the same time. Experimental results show that Collaborative Multiobjective Evolutionary Algorithms obtain up to 22% of profit and increase the returns of the commonly used Buy and Hold strategy and other multi-objective strategies, even for daily operations.
The Goodwillie tower and the EHP sequence

We study the interaction between the EHP sequence and the Goodwillie tower of the identity evaluated at spheres at the prime 2. Both give rise to spectral sequences (the EHP spectral sequence and the Goodwillie spectral sequence, respectively) which compute the unstable homotopy groups of spheres. We relate the Goodwillie filtration to the P map, and the Goodwillie differentials to the H map. Furthermore, we study an iterated Atiyah-Hirzebruch spectral sequence approach to the homotopy of the layers of the Goodwillie tower of the identity on spheres. We show that differentials in these spectral sequences give rise to differentials in the EHP spectral sequence. We use our theory to re-compute the 2-primary unstable stems through the Toda range (up to the 19-stem). We also study the homological behavior of the interaction between the EHP sequence and the Goodwillie tower of the identity. This homological analysis involves the introduction of Dyer-Lashof-like operations associated to M. Ching's operad structure on the derivatives of the identity. These operations act on the mod 2 stable homology of the Goodwillie layers of any functor from spaces to spaces.
Volume Conjecture: Refined and Categorified

The generalized volume conjecture relates asymptotic behavior of the colored Jones polynomials to objects naturally defined on an algebraic curve, the zero locus of the A-polynomial $A(x,y)$. Another "family version" of the volume conjecture depends on a quantization parameter, usually denoted $q$ or $\hbar$; this quantum volume conjecture (also known as the AJ-conjecture) can be stated in a form of a q-difference equation that annihilates the colored Jones polynomials and $SL(2,\C)$ Chern-Simons partition functions. We propose refinements / categorifications of both conjectures that include an extra deformation parameter $t$ and describe similar properties of homological knot invariants and refined BPS invariants. Much like their unrefined / decategorified predecessors, that correspond to $t=-1$, the new volume conjectures involve objects naturally defined on an algebraic curve $A^{ref} (x,y; t)$ obtained by a particular deformation of the A-polynomial, and its quantization $\hat A^{ref} (\hat x, \hat y; q, t)$. We compute both classical and quantum t-deformed curves in a number of examples coming from colored knot homologies and refined BPS invariants.
Simultaneous measurement of forward-backward asymmetry and top polarization in dilepton final states from $t\bar t$ production at the Tevatron

We present a simultaneous measurement of the forward-backward asymmetry and the top-quark polarization in $t\bar t$ production in dilepton final states using 9.7 fb$^{-1}$ of proton-antiproton collisions at $\sqrt{s}=1.96$ TeV with the D0 detector. To reconstruct the distributions of kinematic observables we employ a matrix element technique that calculates the likelihood of the possible $t\bar t$ kinematic configurations. After accounting for the presence of background events and for calibration effects, we obtain a forward-backward asymmetry of $A^{t\bar t} = (15.0 \pm 6.4 \text{ (stat)} \pm 4.9 \text{ (syst)})\%$ and a top-quark polarization times spin analyzing power in the beam basis of $\kappa P = (7.2 \pm 10.5 \text{ (stat)} \pm 4.2 \text{ (syst)})\%$, with a correlation of $-56\%$ between the measurements. If we constrain the forward-backward asymmetry to its expected standard model value, we obtain a measurement of the top polarization of $\kappa P = (11.3 \pm 9.1 \text{ (stat)} \pm 1.9 \text{ (syst)})\%. $ If we constrain the top polarization to its expected standard model value, we measure a forward-backward asymmetry of $A^{t\bar t} = (17.5 \pm 5.6 \text{ (stat)} \pm 3.1 \text{ (syst)})\%. $ A combination with the D0 $A^{t\bar t}$ measurement in the lepton+jets final state yields an asymmetry of $ A^{t\bar t} = (11.8 \pm 2.5 \text{ (stat)} \pm 1.3 \text{ (syst)})\% . $ Within their respective uncertainties, all these results are consistent with the standard model expectations.
Membrane-Binding Biomolecules Influence the Rate of Vesicle Exchange between Bacteria

The exchange of bacterial extracellular vesicles is one route of gene transfer between bacteria, although it was unclear if bacteria developed strategies to modulate the rate of gene transfer within vesicles. In eukaryotes, there are many examples of specialized molecules that have evolved to facilitate the production, loading, and uptake of vesicles. ABSTRACT The exchange of bacterial extracellular vesicles facilitates molecular exchange between cells, including the horizontal transfer of genetic material. Given the implications of such transfer events on cell physiology and adaptation, some bacterial cells have likely evolved mechanisms to regulate vesicle exchange. Past work has identified mechanisms that influence the formation of extracellular vesicles, including the production of small molecules that modulate membrane structure; however, whether these mechanisms also modulate vesicle uptake and have an overall impact on the rate of vesicle exchange is unknown. Here, we show that membrane-binding molecules produced by microbes influence both the formation and uptake of extracellular vesicles and have the overall impact of increasing the vesicle exchange rate within a bacterial coculture. In effect, production of compounds that increase vesicle exchange rates encourage gene exchange between neighboring cells. The ability of several membrane-binding compounds to increase vesicle exchange was demonstrated. Three of these compounds, nisin, colistin, and polymyxin B, are antimicrobial peptides added at sub-inhibitory concentrations. These results suggest that a potential function of exogenous compounds that bind to membranes may be the regulation of vesicle exchange between cells. IMPORTANCE The exchange of bacterial extracellular vesicles is one route of gene transfer between bacteria, although it was unclear if bacteria developed strategies to modulate the rate of gene transfer within vesicles. In eukaryotes, there are many examples of specialized molecules that have evolved to facilitate the production, loading, and uptake of vesicles. Recent work with bacteria has shown that some small molecules influence membrane curvature and induce vesicle formation. Here, we show that similar compounds facilitate vesicle uptake, thereby increasing the overall rate of vesicle exchange within bacterial populations. The addition of membrane-binding compounds, several of them antibiotics at subinhibitory concentrations, to a bacterial coculture increased the rate of horizontal gene transfer via vesicle exchange.
Permutation operators, entanglement entropy, and the XXZ spin chain in the limit

In this paper we develop a new approach to the investigation of the bi-partite entanglement entropy in integrable quantum spin chains. Our method employs the well-known replica trick, thus taking a replica version of the spin chain model as starting point. At each site i of this new model we construct an operator which acts as a cyclic permutation among the n replicas of the model. Infinite products of give rise to local operators, precursors of branch-point twist fields of quantum field theory. The entanglement entropy is then expressed in terms of correlation functions of such operators. Employing this approach we investigate the von Neumann and Rényi entropies of a particularly interesting quantum state occurring as a limit (in a compact convergence topology) of the antiferromagnetic XXZ quantum spin chain. We find that, for large sizes, the entropy scales logarithmically, but not conformally.
Completely bounded representations of convolution algebras of locally compact quantum groups

Given a locally compact quantum group G, we study the structure of completely bounded homomorphisms � : L 1 (G) → B(H), and the question of when they are similar to ∗-homomorphisms. By analogy with the cocommutative case (representations of the Fourier algebra A(G)), we are led to consider the associated (a priori unbounded) map � � : L 1 (G) → B(H) given by � � (! ) = �(! ♯ ) � . We show that the corepresentation Vπ of L 1 (G) associated tois invertible if and only if bothand � � are completely bounded. To prove the "if" part of this claim we show that coefficient operators of such representations give rise to completely bounded multipliers of the dual convolution algebra L 1 (ˆ G). An application of these results is that any (co)isometric corepresentation is automatically unitary. An averaging argument then shows that when G is amenable, � is similar to a ∗-homomorphism if and only if � � is completely bounded. For compact Kac algebras, and for certain cases of A(G), we show that any completely bounded homomorphismis similar to a ∗-homomorphism, without further assumption on ��. Using free product techniques, we construct new examples of compact quantum groups G such that L 1 (G) admits bounded, but not completely bounded, representations.
Coral larvae suppress the heat stress response during the onset of symbiosis thereby decreasing their odds of survival

The endosymbiosis between most corals and their photosynthetic dinoflagellate partners begins early in the host life history, when corals are larvae or juvenile polyps. The capacity of coral larvae to buffer climate-induced stress while in the process of symbiont acquisition could come with physiological trade-offs that alter larval behavior, development, settlement and survivorship. Here we examined the joint effects of thermal stress and symbiosis onset on colonization dynamics, survival, metamorphosis and host gene expression of Acropora digitifera larvae. We found that thermal stress decreased symbiont colonization of hosts by 50% and symbiont density by 98.5% over two weeks. Temperature and colonization also influenced larval survival and metamorphosis in an additive manner, where colonized larvae fared worse or prematurely metamorphosed more often than non-colonized larvae under thermal stress. Transcriptomic responses to colonization and thermal stress treatments were largely independent, while the interaction of these treatments revealed contrasting expression profiles of genes that function in the stress response, immunity, inflammation and cell cycle regulation. The combined treatment either canceled or lowered the magnitude of expression of heat-stress responsive genes in the presence of symbionts, revealing a physiological cost to acquiring symbionts at the larval stage with elevated temperatures. In addition, host immune suppression, a hallmark of symbiosis onset under ambient temperature, turned to immune activation under heat stress. Thus, by integrating the physical environment and biotic pressures that mediate pre-settlement event in corals, our results suggest that colonization may hinder larval survival and recruitment creating isolated, genetically similar populations under projected climate scenarios.
StrongBox: A GPU TEE on Arm Endpoints

A wide range of Arm endpoints leverage integrated and discrete GPUs to accelerate computation such as image processing and numerical processing applications. However, in spite of these important use cases, Arm GPU security has yet to be scrutinized by the community. By exploiting vulnerabilities in the kernel, attackers can directly access sensitive data used during GPU computing, such as personally-identifiable image data in computer vision tasks. Existing work has used Trusted Execution Environments (TEEs) to address GPU security concerns on Intel-based platforms, while there are numerous architectural differences that lead to novel technical challenges in deploying TEEs for Arm GPUs. In addition, extant Arm-based GPU defenses are intended for secure machine learning, and lack generality. There is a need for generalizable and efficient Arm-based GPU security mechanisms. To address these problems, we present StrongBox, the first GPU TEE for secured general computation on Arm endpoints. During confidential computation on Arm GPUs, StrongBox provides an isolated execution environment by ensuring exclusive access to the GPU. Our approach is based in part on a dynamic, fine-grained memory protection policy as Arm-based GPUs typically share a unified memory with the CPU, a stark contrast with Intel-based platforms. Furthermore, by characterizing GPU buffers as secure and non-secure, StrongBox reduces redundant security introspection operations to control access to sensitive data used by the GPU, ultimately reducing runtime overhead. Our design leverages the widely-deployed Arm TrustZone and generic Arm features, without hardware modification or architectural changes. We prototype StrongBox using an off-the-shelf Arm Mali GPU and perform an extensive evaluation. Our results show that StrongBox successfully ensures the GPU computing security with a low (4.70% - 15.26%) overhead across several indicative benchmarks.
Poirot: Probabilistically Recommending Protections for the Android Framework

Inconsistent security policy enforcement within the Android framework can allow malicious actors to improperly access sensitive resources. A number of prominent inconsistency detection approaches have been proposed in and across various layers of the Android operating system. However, the existing approaches suffer from high false positive rates as they rely solely on simplistic convergence analysis and reachability based relations to reason about the validity of access control enforcement. We observe that resource-to-access control associations are highly uncertain in the context of Android. Thus, we introduce Poirot, a next-generation inconsistency detection tool that leverages probabilistic inference to generate a comprehensive set of protection recommendations for Android framework APIs. We evaluate Poirot on four Android images and detect 26 total inconsistencies.
HIGH VELOCITY PRECESSING JETS FROM THE WATER FOUNTAIN IRAS 18286−0959 REVEALED BY VERY LONG BASELINE ARRAY OBSERVATIONS

We report the results of multi-epoch Very Long Baseline Array observations of the 22.2 GHz H2O maser emission associated with the “water fountain” IRAS 18286−0959. We suggest that this object is the second example of a highly collimated bipolar precessing outflow traced by H2O maser emission, the other is W 43A. The detected H2O emission peaks are distributed over a velocity range from −50 km s−1 to 150 km s−1. The spatial distribution of over 70% of the identified maser features is found to be highly collimated along a spiral jet (jet 1) extended southeast to northwest; the remaining features appear to trace another spiral jet (jet 2) with a different orientation. The two jets form a “double-helix” pattern which lies across ∼200 mas. The maser distribution is reasonably fit by a model consisting of two bipolar precessing jets. The three-dimensional velocities of jet 1 and jet 2 are derived to be 138 km s−1 and 99 km s−1, respectively. The precession period of jet 1 is about 56 years. For jet 2, three possible models are tested and they give different values for the kinematic parameters. We propose that the appearance of two jets is the result of a single driving source with significant proper motion.
When Evil Calls: Targeted Adversarial Voice over IP Network

As the COVID-19 pandemic fundamentally reshaped the remote life and working styles, Voice over IP (VoIP) telephony and video conferencing have become a primary method of connecting communities together. However, little has been done to understand the feasibility and limitations of delivering adversarial voice samples via such communication channels. In this paper, we propose TAINT - Targeted Adversarial Voice over IP Network, the first targeted, query-efficient, hard label black-box, adversarial attack on commercial speech recognition platforms over VoIP. The unique channel characteristics of VoIP pose significant new challenges, such as signal degradation, random channel noise, frequency selectivity, etc. To address these challenges, we systematically analyze the structure and channel characteristics of VoIP through reverse engineering. A noise-resilient efficient gradient estimation method is then developed to ensure a steady and fast convergence of the adversarial sample generation process. We demonstrate our attack in both over-the-air and over-the-line settings on four commercial automatic speech recognition (ASR) systems over the five most popular VoIP Conferencing Software (VCS). We show that TAINT can achieve performance that is comparable to the existing methods even with the addition of VoIP channel. Even in the most challenging scenario where there is an active speaker in Zoom, TAINT can still succeed within 10 attempts while staying out of the speaker focus of the video conference.
CRYSTALLINE SILICATES AND DUST PROCESSING IN THE PROTOPLANETARY DISKS OF THE TAURUS YOUNG CLUSTER

We characterize the crystalline-silicate content and spatial distribution of small dust grains in a large sample of protoplanetary disks in the Taurus-Auriga young cluster, using the Spitzer Space Telescope mid-IR spectra. In turn we use the results to analyze the evolution of structure and composition of these 1–2 Myr old disks around Solar- and later-type young stars, and test the standard models of dust processing which result in the conversion of originally amorphous dust into minerals. We find strong evidence of evolution of the dust-crystalline mass fraction in parallel with that of the structure of the disks, in the sense that increasing crystalline mass fraction is strongly linked to dust settling to the disk midplane. We also confirm that the crystalline silicates are confined to small radii, r ≲ 10 AU. However, we see no significant correlation of crystalline mass fraction with stellar mass or luminosity, stellar-accretion rate, disk mass, or disk/star mass ratio, as would be expected in the standard models of dust processing based upon photoevaporation and condensation close to the central star, accretion-heating-driven annealing at r ≲ 1 AU, or spiral-shock heating at r ≲ 10 AU, with or without effective large-scale radial mixing mechanisms. Either another grain-crystallizing mechanism dominates over these, or another process must be at work within the disks to erase the correlations they produce. We propose one of each sort that seems to be worth further investigation, namely X-ray heating and annealing of dust grains, and modulation of disk structure by giant-planetary formation and migration.
The Multi-User Security of Triple Encryption, Revisited: Exact Security, Strengthening, and Application to TDES

We study the security of triple encryption in the multi-user setting with its application to Triple DES (TDES) in mind. Although depreciation of TDES is a global trend, the migration will take the next decade, considering the billions of TDES hardware the industry has invested so far. The multi-user security captures the reality of practical systems with multiple users, substantially impacts security, and is already considered in practical protocols such as TLS 1.3. The best multi-user lower bound of TDES is 43-(3/2) \cdot łog_2 u bits with u users, which is tractable with a standard PC and is unacceptably low. We devise a new proof to improve the multi-user security and show its tightness by giving a concrete attack. The new bound with the TDES parameters is 79-(1/2) \cdot łog_2 u bits. We also propose TEFX that strengthens triple encryption with the FX construction while preserving the compatibility with legacy hardware. TDES with TEFX achieves the multi-user security of 114-(1/2) \cdot łog_2 q bits with q TEFX calls: it achieves 84.5 bits with 2^40 users and 2^21 TEFX calls for each user, which is comparable to that of AES (128-40=88 bits).
PalanTír: Optimizing Attack Provenance with Hardware-enhanced System Observability

System auditing is the foundation of attack provenance to investigate root causes and ramifications of cyber-attacks. However, provenance tracking on coarse-grained audit logs suffers from false causalities caused by dependency explosion. Recent approaches address this problem by increasing provenance granularity using execution partitioning or record-and-replay techniques. Unfortunately, they require program instrumentation and/or impose an unaffordable overhead, which is not practical in deployment. In this paper, we present PalanTír, a provenance-based system that enhances system observability to enable precise and scalable attack investigation. Leveraging hardware-assisted processor tracing (PT), PalanTír optimizes attack provenance in system-call-level audit logs by recovering instruction-level causalities via taint analysis based on PT traces. To reduce the scope of taint analysis and simplify the complexity of taint propagation, PalanTír statically profiles program binaries to identify instructions causally relevant to audit logs and pre-summarize their taint propagation logic at the coarse granularity of basic blocks. Our evaluation against real-life cyber-attacks shows PalanTír's efficiency and effectiveness in attack scenario reconstruction. We also demonstrate that PalanTír can scale to large applications (e.g., Nginx and Sendmail) compiled from upwards of 463,510 lines of C/C++ code.