Miracle-dz/UniFAR-FTUs huggingface dataset:
Rethink the Evaluation for Attack Strength of Backdoor Attacks in Natural Language Processing

It has been shown that natural language processing (NLP) models are vulnerable to a kind of security threat called the Backdoor Attack, which utilizes a `backdoor trigger' paradigm to mislead the models. The most threatening backdoor attack is the stealthy backdoor, which defines the triggers as text style or syntactic. Although they have achieved an incredible high attack success rate (ASR), we find that the principal factor contributing to their ASR is not the `backdoor trigger' paradigm. Thus the capacity of these stealthy backdoor attacks is overestimated when categorized as backdoor attacks. Therefore, to evaluate the real attack power of backdoor attacks, we propose a new metric called attack successful rate difference (ASRD), which measures the ASR difference between clean state and poison state models. Besides, since the defenses against stealthy backdoor attacks are absent, we propose Trigger Breaker, consisting of two too simple tricks that can defend against stealthy backdoor attacks effectively. Experiments show that our method achieves significantly better performance than state-of-the-art defense methods against stealthy backdoor attacks.
A gradient sampling method with complexity guarantees for Lipschitz functions in high and low dimensions

Zhang et al. introduced a novel modification of Goldstein's classical subgradient method, with an efficiency guarantee of $O(\varepsilon^{-4})$ for minimizing Lipschitz functions. Their work, however, makes use of a nonstandard subgradient oracle model and requires the function to be directionally differentiable. In this paper, we show that both of these assumptions can be dropped by simply adding a small random perturbation in each step of their algorithm. The resulting method works on any Lipschitz function whose value and gradient can be evaluated at points of differentiability. We additionally present a new cutting plane algorithm that achieves better efficiency in low dimensions: $O(d\varepsilon^{-3})$ for Lipschitz functions and $O(d\varepsilon^{-2})$ for those that are weakly convex.
Breaking the Fourth Wall: Reaching Beyond Observer/Performer Binaries in Studies of Teacher and Researcher Learning

Abstract Researcher-practitioner collaborations often stop short of engaging researchers and teachers in collectively negotiating the moment-to-moment improvizational decision-making of instructional practice when students are present. We consider the potential for learning at one boundary that often exists between researchers and practitioners as they collaborate on instructional practice: the boundary between performing-teaching and observing-teaching. We draw on performance studies to conceptualize this boundary as a fourth wall. Our analysis examines researcher-practitioner collaboration across four sites in which participants were learning together about the complex work of facilitating student discussion. We analyze how one boundary crossing routine provided opportunities for researchers and practitioners to interact at the boundary of the fourth wall during enactment of discussion-based instruction with students. To analyze episodes of this routine, we draw on conceptualizations of potential learning mechanisms of boundary crossing in research-practice partnerships. Our findings identify and describe the mechanisms for researcher/practitioner learning that arose when our participants crossed the boundary of the fourth wall: perspective taking, boundary spanning, and recognition of shared problem spaces. We argue that these learning mechanisms create potential for researchers and practitioners to wrestle with and learn about the challenges and opportunities within facilitation of student discussions.
Prodiplosis hirsuta Kolesik sp. nov., a new species of gall midge (Diptera: Cecidomyiidae) feeding on shoot tips of Jatropha (Euphorbiaceae) in South America

A gall midge, Prodiplosis hirsuta Kolesik sp. nov., is described whose larvae feed on shoot tips of Jatropha gossypiifolia and Jatropha clavuligera in Paraguay and Bolivia. Morphology and the mitochondrial COI gene sequence of the new species are given. Field survey and preliminary no‐choice host specificity tests showed that the host plant range of P. hirsuta is confined to J. gossypiifolia and J. clavuligera. The apparent host specificity and the damage potential make P. hirsuta a prospective candidate for biological control of J. gossypiifolia in Australia.
collateral ligament reconstruction by the docking technique

Background: Ulnar collateral ligament (UCL) injurieshave been successfully treated by the dockingreconstruction. Although ﬁxation of the graft has been suggested at 30 of elbow ﬂexion, no quantitativebiomechanical data exist to provide guidelines for the optimal elbow ﬂexion angle for graft ﬁxation. Methods: Testingwasconductedon10matchedpairsofcadaverelbowswithuseofaloadingsystemandopto-electrictrackingdevice.AfterbiomechanicaldataonthenativeUCLwereobtained,reconstructionbythedock-ing technique was performed with use of palmaris longus autograft with one elbow ﬁxated at 30 and thecontralateral elbow at 90 of elbow ﬂexion. Biomechanical testing was undertaken on these specimens.Results: The load to failure of the native UCL (mean, 20.1 N-m) was signiﬁcantly higher (P ¼.004) thanthat of the reconstructed UCL (mean, 4.6 N-m). There was no statistically signiﬁcant difference in load tofailure of the UCL reconstructions ﬁxated at 30 of elbow ﬂexion (average, 4.86 N-m) compared withthose at 90 (average, 4.35 N-m). Elbows reconstructed at 30 and 90 of elbow ﬂexion produced similarkinematic coupling and valgus laxity characteristics compared with each other and with the intact UCL.Although not statistically signiﬁcant, the reconstructions ﬁxated at 30 more closely resembled the biome-chanical characteristics of the intact elbow than did reconstructions ﬁxated at 90 . Conclusion: No statistically signiﬁcant difference was found in comparing the docking technique of UCLreconstruction with graft ﬁxation at 30 vs. 90 of elbow ﬂexion. Level of evidence: Basic Science, Biomechanics. 2015 Journal of Shoulder and Elbow Surgery Board of Trustees.Keywords: UCL reconstruction; ulnar collateral ligament; elbow; docking; biomechanics of ligament;cadaver study
XCC: Theft-Resilient and Collateral-Optimized Cryptocurrency-Backed Assets

—The need for cross-blockchain interoperability is higher than ever. Today, there exists a plethora of blockchain-based cryptocurrencies, with varying levels of adoption and diverse niche use cases, and yet communication across blockchains is still in its infancy. Despite the vast potential for novel applications in an interoperable ecosystem, cross-chain tools and protocols are few and often limited. Cross-chain communication requires a trusted third party, as the Fair Exchange problem is reducible to it. However, the decentralised consensus of blockchains can be used as a source of trust, and ﬁnancial incentives can achieve security. X CLAIM uses these principles to enable collateralised cryptocurrency-backed assets to be created and used. However, full collateralization is inefﬁcient, and to protect against exchange rate ﬂuctuations overcollateralization is necessary. This is a signiﬁcant barrier to scaling, and as a result, in practice, most systems still employ a centralised architecture. In this work, we introduce XCC, an extension to the X CLAIM framework which allows for a signiﬁcant reduction in collateral required. By making use of periodic, timelocked commitments on the backing blockchain, XCC decouples locked collateral from issued C B A S , allowing fractional collateralization without loss of security. We instantiate XCC between Bitcoin and Ethereum to showcase practical feasibility. XCC is compatible with the majority of existing blockchains without modiﬁcation.
Secure Lossy Function Computation with Multiple Private Remote Source Observations

—We consider that multiple noisy observations of a remote source are used by different nodes in the same network to compute a function of the noisy observations under joint secrecy, joint privacy, and individual storage constraints, as well as a distortion constraint on the function computed. Suppose that an eavesdropper has access to one of the noisy observations in addition to the public messages exchanged between legitimate nodes. This model extends previous models by 1) considering a remote source as the source of dependency between the correlated random variables observed at different nodes; 2) allowing the function computed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 3) introducing a privacy metric that measures the information leakage about the remote source to the fusion center in addition to the classic privacy metric that measures the leakage to an eavesdropper; 4) considering two transmitting nodes to compute a function rather than one node. Single-letter inner and outer bounds are provided for the considered lossy function computation problem, and exact lossy rate regions are characterized for two special cases in which either the computed function is partially invertible or the function is invertible and the measurement channel of the eavesdropper is physically degraded with respect to the measurement channel of the fusion center.
Argumentation Meets Process Mining: an Architecture for Log Interpretation

We consider the scenario where there is an abstraction gap between the “low-level" events composing the traces in a business process log and the “high-level" activities in terms of which the analysts typically reason on the process behavior. We address the online interpretation problem of translating the event that has just been generated within a business process into the step of the activity instance it corresponds to. We present the architecture of a novel tool that models this interpretation problem as a dispute, encoded into an Abstract Argumentation Framework (AAF) [1], and that translates the computation of the valid interpretations, as well of the explanations on why the other interpretations are not valid, into instances of the AAF acceptance problem.
Lattice-Based Linkable Ring Signature in the Standard Model

Ring signatures enable a user to sign messages on behalf of an arbitrary set of users, called the ring. The anonymity of the scheme guarantees that the signature does not reveal which member of the ring signed the message. The notion of linkable ring signatures (LRS) is an extension of the concept of ring signatures such that there is a public way of determining whether two signatures have been produced by the same signer. Lattice-based LRS is an important and active research line, since lattice-based cryptography has attracted more attention due to its distinctive features especially the quantum resistant. However, all the existing lattice-based LRS relied on random oracle heuristics , i.e., no lattice-based LRS in the standard model has been introduced so far. In this paper, we present a lattice-based LRS scheme based on the well- studied standard lattice assumptions (SIS and LWE) in the standard model. Toward our goal, we present new lattice basis extending algo- rithms which are the key ingredients in our construction, that may be of independent interest.
Study on the maximum calculation height and the maximum propagation angle of the troposcatter wide-angle parabolic equation method

In this study, a method to choose the maximum calculation height and the maximum propagation angle of the split-step troposcatter wide-angle parabolic equation (TWAPE) method is presented. The method is implemented with the height and the scatter angle of the troposcatter common volume. The performance of this method is then demonstrated with a few examples which rely heavily on the choosing of the maximum calculation height and the maximum propagation angle. These examples include the comparison of calculated results of TWAPE for choosing different maximum calculated height and maximum propagation angle at frequencies of 3 and 1 GHz, path lengths of 300 and 500 km, respectively. Finally, the seasonal variation mechanism of the troposcatter propagation loss is discussed based on the seasonal variation of the refractive-index structure parameter.
Multiband 4-Port DGS MIMO Antenna with DR Isolating Element for Wireless Applications

A multiband 4 port multiple input multiple output (MIMO) antenna design functioning in 2.4/5GHz and 5G applications is analyzed. The size of proposed MIMO antenna is 45x45 mm2, where the dielectric resonator (DR) material having a height of 6 mm has been deployed as an isolating element to reduce the mutual coupling among the antenna elements. The 4-port DGS MIMO antenna functions in the 2.4 (2.4-2.6) GHz, 5G New Radio $\mathrm{n}77/78/79(3.3-5.0)$ GHz and 5 (5.15-5.75) GHz with enhanced isolation of above 20dB among the antenna elements. Furthermore, from the design analysis and results explicitly explained in the manuscript, it is confirmed that the proposed 4 port DGS MIMO antenna is considerable for wireless applications.
Stress Detection using CNN Fusion

Early stress detection has a significant impact on recognizing health issues. The aim of this paper is to discuss a Convolutional Neural Network (CNN) based multimodal fusion using a Multimodal Transfer Module (MMTM) to identify stress in a subject-independent way. Electrodermal Activity (EDA) and Electrocardiogram (ECG) physiological modalities are used for fusion. The performance of the proposed model is evaluated in comparison with and without transfer learning on the two benchmark datasets - CLAS and ASCERTAIN. Results show that multimodal fusion with transfer learning performance is higher than without transfer learning experiments. Furthermore, fusing modalities at a higher level of the network helped to enhance the model's efficiency.
Application of synthetic weather time series based on four-dimensional copula for modeling of maritime operations

This paper presents an approach to generate synthetic wind speed and wave height series for maritime environments with a four-dimensional copula using the Copulas Python library. The intended use of the approach is to generate weather data for maritime infrastructure operations modeling. For example, the ability to built and maintain offshore wind farms depends on the weather. The paper shows that this approach corrects a wave series discontinuity issue that was observed in an approach that was developed for a similar purpose. Overall, the results show that the proposed approach can produce credible weather time series. The series can be used for modeling so-called weather windows, which determine the times when maritime infrastructure can be accessed.
CIM Module of Power System and the Design of its Database

At the point,application system for power switching gradually becomes integrated,which calls for a standard open power system module,thus the CIM module was turned up.The article,by using CIM module in IEC 61970,establishing and describing the parts of the system and designs data in the database,it can effectively improve the efficiency of database.
Coordinating Multiple Autonomies to Improve Mission Performance

Research in marine autonomy has traditionally involved development around a single autonomy architecture. Even when an architecture is open and modular, modules are typically all integrated into a single architecture. In this paper, an approach is considered that couples two distinct and mature architectures into a single combined autonomy system that leverages the strengths of both singular architectures to produce a more complete and capable system. In this work, the two autonomy architectures, SeeByte’s Neptune, and MIT’s MOOSIvP, are combined via a shared interface to leverage SeeByte’s mission path-planning and exclusion zone capabilities along with the reactive path execution with obstacle and collision avoidance behaviors of MOOS-IvP. Results are reported from simulation and on-water tests held on the Charles River in Cambridge MA during July 2021. The Neptune/IvP combined system was deployed on MIT’s autonomous Boston Whaler and used to perform a safe crossing in a busy and dynamic environment.
StickyLocalization: Robust End-To-End Relocalization on Point Clouds using Graph Neural Networks

Relocalization inside pre-built maps provides a big benefit in the course of today’s autonomous driving tasks where the map can be considered as an additional sensor for refining the estimated current pose of the vehicle. Due to potentially large drifts in the initial pose guess as well as maps containing unfiltered dynamic and temporal static objects (e.g. parking cars), traditional methods like ICP tend to fail and show high computation times. We propose a novel and fast relocalization method for accurate pose estimation inside a pre-built map based on 3D point clouds. The method is robust against inaccurate initialization caused by low performance GPS systems and tolerates the presence of unfiltered objects by specifically learning to extract significant features from current scans and adjacent map sections. More specifically, we introduce a novel distance-based matching loss enabling us to simultaneously extract important information from raw point clouds and aggregating inner- and inter-cloud context by utilizing self- and cross-attention inside a Graph Neural Network. We evaluate StickyLocalization’s (SL) performance through an extensive series of experiments using two benchmark datasets in terms of Relocalization on NuScenes and Loop Closing using KITTI’s Odometry dataset. We found that SL outperforms state-of-the art point cloud registration and relocalization methods in terms of transformation errors and runtime.
Multiphysics Simulation of EM Side-Channels from Silicon Backside with ML-based Auto-POI Identification

The silicon substrate backside of modern ICs is increasingly recognized as a critical hardware vulnerability, which opens a backdoor for laser/optical probing, fault injection and side-channel attacks. In this work, a novel multiphysics simulation framework is proposed to assess near-field electromagnetic (EM) side-channel leakage. By modeling cell-level power, chip logic functionality and layout geometry, this framework efficiently generates time-domain EM traces at any virtual probe above the surface of silicon substrate. Moreover, an ML-based automatic POI (point-of-interest) identification algorithm is proposed to predict the most vulnerable leakage location, which can be 10-100x faster than a conventional correlation-based side-channel simulation approach. The simulation accuracy is further validated by silicon measurements of an AES crypto testchip in 130nm technology, with a matching leakage location pattern quantified by the required number of EM side-channel traces to disclose the secret keys. Our simulation result uncovers several unexpected data leakage issues from the silicon substrate, which is confirmed by measurements, thus demonstrating an approach that can effectively help prioritize pre-silicon design fixes or security ECOs (Engineering Change Orders).
A Miniaturized Microstrip Branch-Line Hybrid Coupler Using Two Sections and Coupled-Lines

In this paper, a miniaturized microstrip 3dB quadrature branch-line hybrid coupler (QBLHC) is presented for size reduction. The proposed QBLHC is composed of single coupled-lines, parallel coupled-lines, and cascaded two sections in structure, which gives the wider operation band, good impedance matching, and the excellent isolation. By comparing with conventional microstrip 3dB quadrature hybrid coupler, the proposed hybrid coupler has 77% size reduction at the frequency band of 0.65~1.05GHz with almost equivalent electrical performance.
Towards Durability Estimation of Bioprosthetic Heart Valves Via Motion Symmetry Analysis

This paper addresses bioprosthetic heart valve (BHV) durability estimation via computer vision (CV)-based analyses of the visual symmetry of valve leaflet motion. BHVs are routinely implanted in patients suffering from valvular heart diseases. Valve designs are rigorously tested using cardiovascular equipment, but once implanted, more than 50% of BHVs encounter a structural failure within 15 years. We investigate the correlation between the visual dynamic symmetry of BHV leaflets and the functional symmetry of the valves. We hypothesize that an asymmetry in the valve leaflet motion will generate an asymmetry in the flow patterns, resulting in added local stress and forces on some of the leaflets, which can accelerate the failure of the valve. We propose two different pair-wise leaflet symmetry scores based on the diagonals of orthogonal projection matrices (DOPM) and on dynamic time warping (DTW), computed from videos recorded during pulsatile flow tests. We compare the symmetry score profiles with those of fluid dynamic parameters (velocity and vorticity values) at the leaflet borders, obtained from valve-specific numerical simulations. Experiments on four cases that include three different tricuspid BHVs yielded promising results, with the DTW scores showing a good coherence with respect to the simulations. With a link between visual and functional symmetries established, this approach paves the way towards BHV durability estimation using CV techniques.
VCSeg: Virtual Camera Adaptation for Road Segmentation

Domain shift limits generalization in many problem domains. For road segmentation, one of the principal causes of domain shift is variation in the geometric camera parameters, which results in misregistration of scene structure between images. To address this issue, we decompose the shift into two components: Between-camera shift and within-camera shift. To handle between-camera shift, we assume that average camera parameters are known or can be estimated and use this knowledge to rectify both source and target domain images to a standard virtual camera model. To handle within-camera shift, we use estimates of road vanishing points to correct for shifts in camera pan and tilt. While this approach improves alignment, it produces gaps in the virtual image that complicates network training. To solve this problem, we introduce a novel projective image completion method that fills these gaps in a plausible way. Using five diverse and challenging road segmentation datasets, we demonstrate that our virtual camera method dramatically improves road segmentation performance when generalizing across cameras, and propose that this be integrated as a standard component of road segmentation systems to improve generalization.
An automatic method for detecting sliding railway wheels and hot bearings using thermal imagery

One of the most important safety-related tasks in the rail industry is an early detection of defective rolling stock components. Railway wheels and wheel bearings are the two components prone to damages due to their interactions with brakes and railway track, which makes them a high priority when the rail industry investigates improvements in the current detection processes. One of the specific wheel defects is a flat wheel, which is often caused by a sliding wheel during a heavy braking application. The main contribution of this paper is the development of a computer vision method for automatically detecting the sliding wheels from images taken by wayside thermal cameras. As a byproduct, the process will also include a method for detecting hot bearings from the same images. We first discuss our automatic detection and segmentation method, which identifies the wheel and bearing portion of the image. Then, we develop a method, using histogram of oriented gradients to extract the features of these regions. These feature descriptors are later employed by support vector machine to build a fast classifier with a good detection rate, which can detect abnormalities in the wheel. At the end, we train our algorithm using simulated images of sliding wheels and test it on several thermal images collected in a revenue service by the Union Pacific Railroad in North America.