Miracle-dz/UniFAR-FTUs huggingface dataset:
Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!

Natural language processing (NLP) tasks, ranging from text classification to text generation, have been revolutionised by the pretrained language models, such as BERT. This allows corporations to easily build powerful APIs by encapsulating fine-tuned BERT models for downstream tasks. However, when a fine-tuned BERT model is deployed as a service, it may suffer from different attacks launched by the malicious users. In this work, we first present how an adversary can steal a BERT-based API service (the victim/target model) on multiple benchmark datasets with limited prior knowledge and queries. We further show that the extracted model can lead to highly transferable adversarial attacks against the victim model. Our studies indicate that the potential vulnerabilities of BERT-based API services still hold, even when there is an architectural mismatch between the victim model and the attack model. Finally, we investigate two defence strategies to protect the victim model, and find that unless the performance of the victim model is sacrificed, both model extraction and adversarial transferability can effectively compromise the target models.
The Old Moving Groups in the Field of Taurus

In this work, we present a systematic search for stellar groups in the Taurus field by applying the DBSCAN algorithm to the data from Gaia DR2. We find 22 groups, consisting of 8 young groups (Groups 1–8) at ages of 2–4 Myr and distances of ∼130–170 pc, and 14 old groups (Groups 9–22) at ages of 8–49 Myr and distances of ∼110–210 pc. We characterize the disk properties of group members and find 19 new disk-bearing stars, 8 of which are in the young groups with 11 others belonging to the comparatively old groups at the ages of 8–11 Myr. We characterize the accretion properties of the group members with Hα emission lines in their Large Sky Area Multi-Object Fibre Spectroscopic Telescope spectra, and discover one source in Group 10 at an age of 10 Myr which still shows accretion activity. We investigate the kinematic relations among the old groups, find that Group 9 is kinematically related to the known Taurus members, and exclude any kinematic relations between Groups 10–22 and the known Taurus members.
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks

Numerous task-specific variants of conditional generative adversarial networks have been developed for image completion. Yet, a serious limitation remains that all existing algorithms tend to fail when handling large-scale missing regions. To overcome this challenge, we propose a generic new approach that bridges the gap between image-conditional and recent modulated unconditional generative architectures via co-modulation of both conditional and stochastic style representations. Also, due to the lack of good quantitative metrics for image completion, we propose the new Paired/Unpaired Inception Discriminative Score (P-IDS/U-IDS), which robustly measures the perceptual fidelity of inpainted images compared to real images via linear separability in a feature space. Experiments demonstrate superior performance in terms of both quality and diversity over state-of-the-art methods in free-form image completion and easy generalization to image-to-image translation. Code is available at https://github.com/zsyzzsoft/co-mod-gan.
Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences

Language model pre-training (LMPT) has achieved remarkable results in natural language understanding. However, LMPT is much less successful in non-natural language domains like protein sequences, revealing a crucial discrepancy between the various sequential domains. Here, we posit that while LMPT can effectively model per-token relations, it fails at modeling per-sequence relations in non-natural language domains. To this end, we develop a framework that couples LMPT with deep structure-preserving metric learning to produce richer embeddings than can be obtained from LMPT alone. We examine new and existing pre-training models in this framework and theoretically analyze the framework overall. We also de-sign experiments on a variety of synthetic datasets and new graph-augmented datasets of proteins and scientiﬁc abstracts. Our approach offers notable performance improvements on downstream tasks, including prediction of protein remote homology and classiﬁcation of citation intent.
SparsePoint: Fully End-to-End Sparse 3D Object Detector

Object detectors based on sparse object proposals have recently been proven to be successful in the 2D domain, which makes it possible to establish a fully end-to-end detector without time-consuming post-processing. This development is also attractive for 3D object detectors. However, considering the remarkably larger search space in the 3D domain, whether it is feasible to adopt the sparse method in the 3D object detection setting is still an open question. In this paper, we propose SparsePoint, the ﬁrst sparse method for 3D object detection. Our SparsePoint adopts a number of learnable proposals to encode most likely potential positions of 3D objects and a foreground embedding to encode shared semantic features of all objects. Besides, with the attention module to provide object-level interaction for redundant proposal removal and Hungarian algorithm to supply one-one label assignment, our method can produce sparse and accurate predictions. SparsePoint sets a new state-of-the-art on four public datasets, including ScanNetV2, SUN RGB-D, S3DIS, and Matterport3D. Our code will be publicly available soon.
Real-Time Visual Object Tracking via Few-Shot Learning

Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL). While the concept of FSL is not new in tracking and has been previously applied by prior works, most of them are tailored to fit specific types of FSL algorithms and may sacrifice running speed. In this work, we propose a generalized two-stage framework that is capable of employing a large variety of FSL algorithms while presenting faster adaptation speed. The first stage uses a Siamese Regional Proposal Network to efficiently propose the potential candidates and the second stage reformulates the task of classifying these candidates to a few-shot classification problem. Following such a coarse-to-fine pipeline, the first stage proposes informative sparse samples for the second stage, where a large variety of FSL algorithms can be conducted more conveniently and efficiently. As substantiation of the second stage, we systematically investigate several forms of optimization-based few-shot learners from previous works with different objective functions, optimization methods, or solution space. Beyond that, our framework also entails a direct application of the majority of other FSL algorithms to visual tracking, enabling mutual communication between researchers on these two topics. Extensive experiments on the major benchmarks, VOT2018, OTB2015, NFS, UAV123, TrackingNet, and GOT-10k are conducted, demonstrating a desirable performance gain and a real-time speed.
Efficient Algorithms for Rotation Averaging Problems

The rotation averaging problem is a fundamental task in computer vision applications. It is generally very difficult to solve due to the nonconvex rotation constraints. While a sufficient optimality condition is available in the literature, there is a lack of a fast convergent algorithm to achieve stationary points. In this paper, by exploring the problem structure, we first propose a block coordinate descent (BCD)-based rotation averaging algorithm with guaranteed convergence to stationary points. Afterwards, we further propose an alternative rotation averaging algorithm by applying successive upper-bound minimization (SUM) method. The SUM-based rotation averaging algorithm can be implemented in parallel and thus is more suitable for addressing large-scale rotation averaging problems. Numerical examples verify that the proposed rotation averaging algorithms have superior convergence performance as compared to the state-of-the-art algorithm. Moreover, by checking the sufficient optimality condition, we find from extensive numerical experiments that the proposed two algorithms can achieve globally optimal solutions.
Compact enumeration for scheduling one machine

A Variable Parameter (VP) analysis aims to give precise time complexity expressions of algorithms with exponents appearing solely in terms of variable parameters. A variable parameter is the number of objects with specific properties. Here we describe two VP-algorithms, an implicit enumeration and a polynomial-time approximation scheme for a strongly $NP$-hard problem of scheduling $n$ independent jobs with release and due times on one machine to minimize the maximum job completion time $C_{\max}$. Thus variable parameters are numbers of some specially defined types of jobs. A partial solution without these jobs is constructed in a low degree polynomial time, and an exponential time (in the number of variable parameters) procedure is carried out to augment this solution to a complete optimal solution. Unexpectedly, we arrive at alternative pseudo-polynomial time expressions for the running time of our exponential-time procedures. Applying further the fixed parameter analysis, we get a polynomial-time dependence on the length of the input. Both, intuitive probabilistic estimations and our extensive experimental study support our conjecture that the total number of the variable parameters is far less than $n$ and asymptotically it converges to 0.
On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials Is Best

We analyse the impact of the selective pressure for the global optimisation capabilities of steady-state evolutionary algorithms (EAs). For the standard bimodal benchmark function TwoMax, we rigorously prove that using uniform parent selection leads to exponential runtimes with high probability to locate both optima for the standard ( +1) EA and ( +1) RLS with any polynomial population sizes. However, we prove that selecting the worst individual as parent leads to efficient global optimisation with overwhelming probability for reasonable population sizes. Since always selecting the worst individual may have detrimental effects for escaping from local optima, we consider the performance of stochastic parent selection operators with low selective pressure for a function class called TruncatedTwoMax, where one slope is shorter than the other. An experimental analysis shows that the EAs equipped with inverse tournament selection, where the loser is selected for reproduction and small tournament sizes, globally optimise TwoMax efficiently and effectively escape from local optima of TruncatedTwoMax with high probability. Thus, they identify both optima efficiently while uniform (or stronger) selection fails in theory and in practice. We then show the power of inverse selection on function classes from the literature where populations are essential by providing rigorous proofs or experimental evidence that it outperforms uniform selection equipped with or without a restart strategy. We conclude the article by confirming our theoretical insights with an empirical analysis of the different selective pressures on standard benchmarks of the classical MaxSat and multidimensional knapsack problems.
High Frequency Pressure Wave Interaction with Premixed Flames

Abstract The interaction of high frequency acoustic waves with premixed flames is discussed and the results presented for a simple one-dimensional theory involving the solution of the acoustic equation in the presence of a strong temperature gradient. The wavelength of the disturbance is very small on an acoustic scale, being on a level with a typical diffusion length. Thus one is considering effectively the interaction of “ultra sound” with flames (frequencies of the order of mHz). The effect of the flame is to introduce a small but significant jump in the velocity perturbation as the pressure disturbance passes through the flame. Plots showing the effect on the waveform of transmitted and reflected waves are displayed and discussed. In particular one can observe the small but significant effect of the reaction zone on the amplitude and phase of the waves emitted from the flame. It is thus possible that ultra sound could be used as a diagnostic tool to analyse flame structure. The theory can also be exte.
An infinite interval version of the $\alpha$-Kakutani equidistribution problem

In this article we extend results of Kakutani, Adler–Flatto, Smilansky and others on the classical α-Kakutani equidistribution result for sequences arising from finite partitions of the interval. In particular, we describe a generalization of the equidistribution result to infinite partitions. In addition, we give discrepancy estimates, extending results of Drmota–Infusino [8].
A Physics-based and Data-driven Linear Three-Phase Power Flow Model for Distribution Power Systems

Distribution power systems (DPSs) are mostly unbalanced, and their loads may have notable static voltage characteristics (ZIP loads). Hence, despite abundant papers on linear single-phase power flow models, it is still necessary to study linear three-phase distribution power flow models. To this end, this paper proposes a physics-based and data-driven linear three-phase power flow model for DPSs. We first formulate how to amalgamate data-driven techniques into a physics-based power flow model to obtain our linear model. This amalgamation makes our linear model independent of the assumptions commonly used in the literature (e.g., nodal voltages are nearly 1.0 p.u.) and thus have a relatively high accuracy generally even when those assumptions become invalid. We then reveal how to apply our model to the DPSs with ZIP loads. We also show that with the Huber penalty function employed, the adverse impact of bad data on our model’s accuracy is significantly reduced, rendering our model robust against poor data quality. Case studies have demonstrated that our model generally has 2 to over 10-fold smaller average errors than other linear power flow models, enjoys a satisfying accuracy against bad data, and facilitates a faster solution to DPS analysis and optimization problems.
Synthesis and Structures of Extended Cyclic Siloxanes

The facile synthesis of all-cis-tetrasiloxycyclotetrasiloxanes (extended cyclic siloxanes) [i-BuSi(OSiHMe2)O]4 1, [PhSi(OSiHMe2)O]4 2, and [CH2 = CHSi(OSiHMe2)O]4 3 was accomplished via sodium or potassium silanolates from respective trialkoxysilanes. The treatment of 1 or 2 with m-chloroperoxybenzoic acid afforded respective extended cyclic silanols [i-BuSi(OSiMe2OH)O]4 4 and [PhSi(OSiMe2OH)O]4 5. The structures of 4 and 5 were unequivocally established by X-ray crystallography. Among these new compounds, compound 3 possesses both vinyl and hydrosilyl groups in the molecule, thus this could serve as a potential monomer of well-defined cage silsesquioxanes. Extended cyclic silanols 4 and 5 contain four silanol moieties in the same direction, and application of host molecules or building units of cage silsesquioxanes is expected.
Prevention

Primary prevention is aimed at reducing the risk of stroke in asymptomatic people. Recommendations concerning patients with transient ischaemic attacks (TIA) are considered here as secondary prevention. Although there is no evidence, we have assumed that patients with silent brain infarction should be treated as though they have had a symptomatic event. Modification of risk factors is known to decrease the incidence of stroke in asymptomatic people [Bronner et al., 1995]. Definitions of levels of evidence are reported in table 1.
Acid Neutralization by Marine Cylinder Lubricants Inside a Heating Capillary: Strong/Weak-Stick Collision Mechanisms

Base nanoparticles are present in marine cylinder lubricants (MCLs) for controlling cylinder corrosive wear by neutralizing combustion-generated acids. A portion of the surfactants stabilizing these nanoparticles may have dynamic properties, upon which strong/weak-stick collisions are proposed to drive the interaction between base particles and acid drops in oil media. Neutralization of sulfuric acid droplets (150−200 μm in diameter) by MCL samples (with a base number of BN = 70 mg KOH/g oil) was performed inside a heating-capillary microreactor at 23−27, 110−140, and 140−170 °C. The progress of reactions was recorded in real time through a video-microscopy system and quantified by image analysis. Among four directly observed reaction phenomena, three had never been seen in previous research. These reaction behaviors support the theory of strong/weak-stick collisions and supplement our knowledge to help us better understand the acid neutralization in oil and to propound new strategies for improving the ac.
EFFECT OF BOVINE LACTOFERRIN ON UTILIZATION OF ORALLY ADMINISTERED IRON IN SUCKLING PIGLETS

Piglets, on days 3 and 10 of age, were given orally 100 mg of Fe 2+ as iron fumarate and 34.5 mg of Fe 3+ from iron-saturated lactoferrin (group L) or 134.5 mg of Fe 2+ as iron fumarate (group F). Positive control group received 200 mg of Fe 3+ dextran i.m. on day 3 and negative control group was treated with Fe 3+ dextran on day 21. Haemoglobin concentration, packed cell volume, mean corpuscular volume, mean corpuscular haemoglobin and iron concentration in blood plasma were significantly lower in group L compared to group F. The replacement of the part of the iron dose by iron from iron-saturated lactoferrin had negative effect on iron status of piglets.
Migration of Plasticizer between Bonded Propellant Interfaces

Plasticizer migration across bonded propellant interfaces during cure has been shown to have a measurable effect on propellant properties compared to each propellant by itself. This shows that the curing period is significant to the migration phenomenon. The plasticizer migration has been shown to have a direct influence on tensile strength for short aging periods up to the point the plasticizer reaches equilibrium. The tensile data for short aging periods have been shown to follow an empirical equation connecting the physical characteristics of plasticizer migration with increasing propellant tensile strength. The diffusion coefficient has been evaluated on the basis of this relation from a plot of σ versus t1/2 and was in good agreement with the diffusion coefficient from the plasticizer content data.
Crawling and spiraling of cholesteric fingers in electric field

We show that two types of fingers exist in homeotropic samples of cholesteric liquid crystals of positive dielectric anisotropy : fingers of a first species in which the director field is continuous, and fingers of a second species which are topologically singular and of the same nature as spherulites (also called cholesteric bubbles). When the former are subjected to a low frequency AC electric field, they crawl slowly along their axes whereas the latter drift perpendicularly to their axes and form spirals when one of their ends is pinned on a defect. This work supplements spirals recently observed in Nice by Kamaye and Gilli [8] and by Mitov and Sixou [9] in similar systems.
Non-Newtonian Fluids in Spout-Fluid Beds: Mass Transfer Coefficient at Low Reynolds Numbers

Following on from the work of Anabtawi et al. (2003), this study examined how the volumetric liquid-phase mass transfer coefficient, k L a, of oxygen in air in three-phase spout-fluid beds was affected by varying the system parameters of bed height, bed diameter, gas velocity, and liquid velocity. The liquid used was 0.1% CMC solution, displaying a pseudo-plastic rheology, with 1.75 mm glass spheres as packing. The values of the Sherwood number were lower than in previous studies (Anabtawi et al., 2003), in the range 9,000–186,000. Gas velocity had a similar effect on k L a as in a bubble column, with results also giving good agreement with previous work on two-phase and three-phase spouted bed systems. The correlation obtained for the effect of liquid velocity on k L a compared well with that of Schumpe et al. (1989). An increase in the height of packing increased k L a to the power of 0.319, with an increase in column diameter also causing an increase in k L a, which is in agreement with the results of Akita and Yoshida (1973).
Sources of climate change information used by newspaper journalists in Tanzania

This article assesses the information sources used by Tanzanian newspaper journalists to collect climate change information. The main sources of climate change information consulted by newspaper journalists in Tanzania are climate change experts and daily events, such as community meetings and other relevant social gatherings. These sources are interactive – enabling journalists to obtain climate change information – and easily accessible, and use and provide instant responses. It was also found that deficient use of other potential sources of information, such as libraries, printed materials and Internet websites, coupled with overarching challenges that limit newspaper journalists from seeking, covering and reporting information on climate change, may affect the quality and quantity of climate change information published in Tanzanian newspapers. All the stakeholders involved in the fight against climate change and journalism colleges should collaborate and devise strategies aimed at building the capacity of newspaper journalists, editors and reporters in their daily activities.
Fatal Motor Vehicle-Pedestrian Collision Injury Patterns—A Systematic Literature Review

Introduction: Injury patterns in pedestrians struck by motor vehicles were described in medical literature first published almost a half century ago. “Classical” triads of injury distribution were described for adults (skull-pelvis-extremity) and subsequently applied to children (head-hip or pelvis-distal femur/knee joint). Notably, these classical triads were derived from two publications reporting clinical observations of only 11 patients, all of whom were adults. Methods: A systematic literature review was conducted using Medline, CINAHL, EMBASE, and Cochrane to determine the evidence-base for motor vehicle collision (MVC)-pedestrian injury “triads” and other trauma patterns described for pedestrians in the adult and pediatric age groups. Results: Of the 1540 full-text articles identified in the review, 56 articles published in English met the inclusion criteria, that is, motor vehicle-pedestrian collision resulting in specific, fatal injuries determined by postmortem examinations. There were variations in injury patterns that differed from the “classical” triads. These differences likely stem from advances in vehicle design and safety features which have affected the nature and distribution of injuries. Discussion: Further research on the correlation of specific injuries sustained by pedestrians of different ages with various types of vehicles and impacts are needed to assess the validity of previously observed injury patterns in relation to the current motor vehicle fleet. Delineation of injury patterns can assist health care teams in trauma management. Vehicle manufacturers and government regulators can better assess whether the introduction of advanced driver assistance features designed to protect pedestrians when struck will be effective in reducing severe injuries. In forensic pathology practice, knowledge of pedestrian injury patterns based on data representative of impacts involving modern vehicles can provide MVC death investigators the means to determine MVC dynamics and pedestrian kinematics.