Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating Stateful Defenses Against Black-Box Adversarial Examples

Defending machine-learning (ML) models against white-box adversarial attacks has proven to be extremely difﬁcult. Instead, recent work has proposed stateful defenses in an attempt to defend against a more restricted black-box attacker. These defenses operate by tracking a history of incoming model queries, and rejecting those that are suspiciously similar. The current state-of-the-art stateful defense Blacklight was proposed at USENIX Security ’22 and claims to prevent nearly 100% of attacks on both the CIFAR10 and ImageNet datasets. In this paper, we observe that an attacker can signiﬁcantly reduce the accuracy of a Blacklight-protected classiﬁer (e.g., from 82.2% to 6.4% on CIFAR10) by simply adjusting the parameters of an existing black-box attack. Motivated by this surprising observation, since existing attacks were evaluated by the Blacklight authors, we provide a systematization of stateful defenses to understand why existing stateful defense models fail. Finally, we propose a stronger evaluation strategy for stateful defenses comprised of adaptive score and hard-label based black-box attacks. We use these attacks to successfully reduce even reconﬁgured versions of Blacklight to as low as 0% robust accuracy.
Influence of a tropical cyclone on Chlorophyll‐a Concentration in the Arabian Sea

The effect of a tropical cyclone on the variation of phytoplankton biomass in terms of surface chlorophyll‐a is brought out based on satellite observations and mixed layer model simulations in the Arabian Sea during 21 May–3 June 2001. Along the cyclone's passage, chlorophyll‐a was high with extreme values (5–8 mg m−3) in the blooms of phytoplankton. The model simulations indicate deepening of mixed layer on the southeastern edge of the cyclone. This forced mixed layer deepening, due to intense wind stirring and cyclone‐induced divergent geostrophic currents, has lead to the injection of nutrients into the surface layer, resulting in higher chlorophyll‐a. This study suggests that the short‐lived tropical cyclones would alter the generally prevailing oligotrophic (nutrient depleted) conditions into a productive surface layer in the Arabian Sea during spring intermonsoon.
Few-shot Quality-Diversity Optimisation

—In the past few years, a considerable amount of research has been dedicated to the exploitation of previous learning experiences and the design of Few-shot and Meta Learning approaches, in problem domains ranging from Computer Vision to Reinforcement Learning based control. A notable exception, where to the best of our knowledge, little to no effort has been made in this direction is Quality-Diversity (QD) optimisation. QD methods have been shown to be effective tools in dealing with deceptive minima and sparse rewards in Reinforcement Learning. However, they remain costly due to their reliance on inherently sample inefﬁcient evolutionary processes. We show that, given examples from a task distribution, information about the paths taken by optimisation in parameter space can be leveraged to build a prior population, which when used to initialise QD methods in unseen environments, allows for few-shot adaptation. Our proposed method does not require backpropagation. It is simple to implement and scale, and furthermore, it is agnostic to the underlying models that are being trained. Experiments carried in both sparse and dense reward settings using robotic manipulation and navigation benchmarks show that it considerably reduces the number of generations that are required for QD optimisation in these environments.
Produção de silagem e reciclagem de nutrientes em milho. 1-produção de matéria seca e composição bromatológica

In an Ultisol, of Instituto de Zootecnia, SP, was developed an experiment split plot design, with three replications to measure the DM production and nutrients removed by three varieties and four corn cultivars, harvested in two cutting heights (15 and 50 cm above the soil surface). The cut height of 50 cm decreased DM production, increased the DM% and grain percentage and didn't alter CP% of NDF%. The silage quality can be altered by the cultivar, because these were different in grain percentage, DM%, CP% and NDF%.
Introducing Multi-Convexity in Path Constrained Trajectory Optimization for Mobile Manipulators

Mobile manipulators have a highly non-linear and non-convex mapping between the end-effector path and the manipulator’s joints and position and orientation of the mobile base. As a result, trajectory optimization with end-effector path constraints takes the form of a difficult non-linear optimization problem. In this paper, we present the first multi-convex approximation to this difficult optimization problem that eventually reduces to solving a sequence of globally valid convex quadratic programs (QPs). The proposed optimizer rests on two novel building blocks. First, we introduce a set of auxiliary variables in which the non-linear constraints that arise out of manipulator kinematics and its coupling with the mobile base have a multi-affine form. Projecting the auxiliary variables to the space of actual configuration variables of the mobile manipulator involves a non-convex optimization. Thus, the second building block involves computing a convex surrogate for this non-convex projection. We show how large parts of the proposed optimizer can be solved in parallel providing the possibility of exploiting multi-core CPUs. We validate our trajectory optimization on different benchmark examples. Specifically, we highlight how it solves the cyclicity problem and provides a holistic approach where a diverse set of trajectories can be obtained by trading-off different aspects of manipulator and mobile base motion.
Controls and Development of Late Quaternary Periplatform Carbonate Stratigraphy in Walton Basin (Northeastern Nicaragua Rise, Caribbean Sea)

The late Quaternary sedimentary record in periplatform oozes and muds deposited on the northern Nicaragua Rise results from the interplay of four main controls: (1) input of pelagic carbonates and bank-derived fine aragonite and magnesian calcite; (2) input of siliciclastic sediments; (3) dispersal and removal of sediments by the Caribbean Current; and (4) partial seafloor dissolution of metastable carbonates. High accumulation rates of the calcite coarse sediment fraction throughout the study area demonstrate that planktonic foraminiferal productivity peaked during interglacial stages. Neritic carbonate productivity also peaked during interglacial stages, when bank and shelf tops along the Nicaragua Rise were submerged within the photic zone. Because the bank and shelf tops remained mostly exposed during glacial stages, the surface area available for the neritic carbonate productivity was drastically reduced to a narrow band along the margins of Pedro Bank and the southern shelf of Jamaica. A large volume of siliciclastic sediments, transported from the coastal area of South America and the eastern and western regions of Jamaica, were deposited during glacial stages within the eastern and western deep extensions of Walton Basin. This finding contrasts with the input pattern of siliciclastic sediments in Walton Basin itself, where the largest input of siliciclastic sediments occurred at each of the interglacial climatic optima, corresponding to intervals of maximum sea level transgression. Finally, cores in water depths exceeding 1100 m display during interglacial stages aragonite accumulation rates systematically lower than rates in cores from water depths shallower than 1100 m. This indicates that some bank-derived aragonite and magnesian calcite has been partially removed by seafloor dissolution in areas from water depths exceeding 1100 m. Results from this study on the northeastern Nicaragua Rise indicate that not only do offbank transport and water column saturation state influence the late Quaternary record but also that the variable strength of the Caribbean Current and the proximity of sources for siliciclastic sediments have played a major role in the development of the late Quaternary periplatform high resolution stratigraphy.
Traversal Using Relays around NAT (TURN): Relay Extensions to Session Traversal Utilities for NAT (STUN)

If a host is located behind a NAT, then in certain situations it can be impossible for that host to communicate directly with other hosts (peers). In these situations, it is necessary for the host to use the services of an intermediate node that acts as a communication relay. This specification defines a protocol, called TURN (Traversal Using Relays around NAT), that allows the host to control the operation of the relay and to exchange packets with its peers using the relay. TURN differs from some other relay control protocols in that it allows a client to communicate with multiple peers using a single relay address. [STANDARDS-TRACK]
Seismological estimates of means of isostatic support of the Sierra Nevada

The modern topography of the Sierra Nevada (California, USA) has been attributed to rapid uplift following foundering of negatively buoyant lithosphere into the asthenosphere since ca. 10 Ma. Uplift now manifests as ∼2 km mean topographic relief between the crest of the southern Sierra Nevada and the western foothills and 1–2 km between the Sierran crest and adjacent Basin and Range. In this study, we use seismic P-wave velocity structures derived from teleseismic tomography to estimate the lithospheric density structure in the region and thus infer the current sources of topographic support. We exploit the different derivatives of crustal density with temperature and wave speed to attempt to identify a single solution for crustal density and temperature that satisfies flexural isostasy and the P-wave tomography. This solution yields both temperature variations compatible with observed heat flow and Bouguer gravity anomalies concordant with observations. We find that the topographic gradient between the crest and the eastern Great Valley is due to both crustal and mantle sources. Despite a greater thickness, the foothills crust is less buoyant than that beneath the range crest, accounting for ∼1 km of the topographic difference. High densities are due principally to composition. High-velocity upper mantle (∼50–100 km depth) is also observed beneath the foothills but not the range crest, and this contrast explains an additional 1 km of topographic difference. Miocene or more recent removal of such upper mantle material from the Sierran crest, as inferred from xenoliths, would have triggered rapid uplift of ∼1 km. Our findings are consistent with the removal of negatively buoyant material from beneath the Sierra Nevada since the Miocene.
Coastal Upwelling and Kelvin Waves with Small Longshore Topography

Abstract A simple, uniformly stratified, linear model is developed to examine the effects on upwelling and internal Kelvin wave propagation of small, slow, longshore varying topography and coastline. The condition of no normal flow at the bottom yields correction terms with responses that propagate as Kelvin waves. For the first problem considered, a uniform wind stress is turned on abruptly. The response is fully three-dimensional with a zone of upwelling (downwelling) to the south of a ridge (canyon) near the shore. As time passes, the zone moves poleward and becomes centered over the topography. A complicated cyclonic and anticyclonic circulation is associated with a shoreward (seaward) flow over the ridge (canyon). If the basic state (i.e., the flow in the absence of topography) had no poleward undercurrent, the sign of the response is altered. The second problem considered the modification of an internal Kelvin wave by isolated topography. Energy is scattered into all vertical modes (i.e., the natura.
Interpretable collective intelligence of non-rational human agents

We outline how to create a mechanism that provides an optimal way to elicit, from an arbitrary group of experts, the probability of the truth of an arbitrary logical proposition together with collective information that has an explicit form and interprets this probability. Such a system could, in partic- ular, incentivize experts from all over the world to collectively solve scientiﬁc or medical problems in a very eﬃcient manner. In our main considerations about real experts, they are not assumed to be Bayesian and their behavior is described by utilities that satisfy the von Neumann–Morgenstern axioms only locally. market, self-resolving prediction market, continuous double auction, non-Bayesian learning, ontological information, lottery dependent utility, security and potential, economic equilibrium, Nash equilibrium, optimism bias, status quo bias, ambiguity aversion, comparative ignorance, Kharkevich information value, double relativity principle.
A 2mW 800MS/s 7th-order discrete-time IIR filter with 400kHz-to-30MHz BW and 100dB stop-band rejection in 65nm CMOS

Filters are key building blocks in wireless communication and analog signal processing. Typically, Gm-C and active-RC topologies are being used for this purpose. However, reduced supply voltage and lower transistor output impedance make it difficult to implement high-gain wide-bandwidth opamps in a power-efficient manner. Moreover, portable wireless communication devices demand nowadays ever decreasing power consumption, and more tunability/reprogrammability. A discrete-time (DT) analog signal processing approach appears to answer these requirements.
Efficient Identification of Bad Signatures in RSA-Type Batch Signature

As the use of electronic voting systems and e-commerce systems increases, the efficient batch verification of digital signatures becomes more and more important. In this paper, we first propose a new method to identify bad signatures in batches efficiently for the case when the batch contains one bad signature. The method can find out the bad signature using smaller number of modular multiplications than the existing method. We also propose an extension to the proposed method to find out two or more bad signatures in a batch instance. Experimental results show that our method yields better performance than the existing method in terms of the number of modular multiplications.
PERSPECTIVE - Absorbing the Concept of Absorptive Capacity: How to Realize Its Potential in the Organization Field

The purpose of this perspective paper is to advance understanding of absorptive capacity, its underlying dimensions, its multilevel antecedents, its impact on firm performance, and the contextual factors that affect absorptive capacity. Twenty years after the Cohen and Levinthal 1990 paper, the field is characterized by a wide array of theoretical perspectives and a wealth of empirical evidence. In this paper, we first review these underlying theories and empirical studies of absorptive capacity. Given the size and diversity of the absorptive capacity literature, we subsequently map the existing terrain of research through a bibliometric analysis. The resulting bibliometric cartography shows the major discrepancies in the organization field, namely that (1) most attention so far has been focused on the tangible outcomes of absorptive capacity; (2) organizational design and individual level antecedents have been relatively neglected in the absorptive capacity literature; and (3) the emergence of absorptive capacity from the actions and interactions of individual, organizational, and interorganizational antecedents remains unclear. Building on the bibliometric analysis, we develop an integrative model that identifies the multilevel antecedents, process dimensions, and outcomes of absorptive capacity as well as the contextual factors that affect absorptive capacity. We argue that realizing the potential of the absorptive capacity concept requires more research that shows how “micro-antecedents” and “macro-antecedents” influence future outcomes such as competitive advantage, innovation, and firm performance. In particular, we identify conceptual gaps that may guide future research to fully exploit the absorptive capacity concept in the organization field and to explore future fruitful extensions of the concept.
Geostatistical interpolation and classification of remote sensing data from ice surfaces

Geostatistical methods for interpolation and extrapolation of irregularly spaced data are kriging methods, a family of methods based on the least-squares optimization principle and usually introduced in a probabilistic framework ('geostatistical estimation'). The difference between kriging and numerical interpolation methods lies in the exploitation of a spatial structure function, the variogram, in the optimization. Usefulness of geostatistical interpolation for glaciological data analysis has been demonstrated a number of times. Application of ordinary kriging to satellite radar altimeter data from Antarctic ice streams yields maps of 3-km resolution that facilitate glaciodynamic investigations. The technique is exemplified here for 1995 ERS-1 data, and the resultant new map of the entire Lambert Glacier/Amery Ice Shelf area including upper Lambert Glacier and other tributaries of (lower) Lambert Glacier (59degrees-79degreesE/68degrees-75degreesS) is presented. While interpolation utilizes the primary i.
Sonified Distance in Sensory Substitution Does Not Always Improve Localization: Comparison With a 2-D and 3-D Handheld Device

Early visual to auditory substitution devices encode 2-D monocular images into sounds while more recent devices use distance information from 3-D sensors. This study assesses whether the addition of sound-encoded distance in recent systems helps to convey the “where” information. This is important to the design of new sensory substitution devices. We conducted experiments for object localization and navigation tasks with a handheld visual to audio substitution system. It comprises 2-D and 3-D modes. Both encode in real-time the position of objects in images captured by a camera. The 3-D mode encodes in addition the distance between the system and the object. Experiments have been conducted with 16 blindfolded sighted participants. For the localization, participants were quicker to understand the scene with the 3-D mode that encodes distances. On the other hand, with the 2-D only mode, they were able to compensate for the lack of distance encoding after a small training. For the navigation, participants were as good with the 2-D only mode than with the 3-D mode encoding distance.
A Large-scale Empirical Study of Online Automated Privacy Policy Generators for Mobile Apps

Mobile phones and apps have become a ubiquitous part of digital life. There is a large variety and volume of personal data sent to and used by mobile apps, leading to various privacy issues. Privacy regulations protect and promote the privacy of individuals by requiring mobile apps to provide a privacy policy that explains what personal information is gathered and how these apps process and safely keep this information. However, developers often do not have sufficient legal knowledge to create such privacy policies. Online Automated Privacy Policy Generators (APPGs) can create privacy policies, but their quality and other characteristics can vary. In this paper, we conduct the first large-scale, comprehensive empirical study of APPGs for mobile apps. Specifically, we collected and analyzed 46,472 Android app privacy policies from the Google Play Store and systematically evaluated 10 APPGs on multiple dimensions. We reported analyses on how widely APPGs are used and whether policies are consistent with app permissions. We found that nearly 20.1% of privacy policies could be generated by APPGs and summarized the potential and limitations of APPGs.
Deep-Learning-Based Optimization of the Under-Sampling Pattern in MRI

In compressed sensing MRI (CS-MRI), k-space measurements are under-sampled to achieve accelerated scan times. CS-MRI presents two fundamental problems: (1) where to sample and (2) how to reconstruct an under-sampled scan. In this article, we tackle both problems simultaneously for the specific case of 2D Cartesian sampling, using a novel end-to-end learning framework that we call LOUPE (Learning-based Optimization of the Under-sampling PattErn). Our method trains a neural network model on a set of full-resolution MRI scans, which are retrospectively under-sampled on a 2D Cartesian grid and forwarded to an anti-aliasing (a.k.a. reconstruction) model that computes a reconstruction, which is in turn compared with the input. This formulation enables a data-driven optimized under-sampling pattern at a given sparsity level. In our experiments, we demonstrate that LOUPE-optimized under-sampling masks are data-dependent, varying significantly with the imaged anatomy, and perform well with different reconstruction methods. We present empirical results obtained with a large-scale, publicly available knee MRI dataset, where LOUPE offered superior reconstruction quality across different conditions. Even with an aggressive 8-fold acceleration rate, LOUPE's reconstructions contained much of the anatomical detail that was missed by alternative masks and reconstruction methods. Our experiments also show how LOUPE yielded optimal under-sampling patterns that were significantly different for brain vs knee MRI scans. Our code is made freely available at https://github.com/cagladbahadir/LOUPE/.
North Pacific Cloud Feedbacks Inferred from Synoptic-Scale Dynamic and Thermodynamic Relationships

Daily satellite cloud observations and reanalysis dynamical parameters are analyzed to determine how midtropospheric vertical velocity and advection over the sea surface temperature gradient control midlatitude North Pacific cloud properties. Optically thick clouds with high tops are generated by synoptic ascent, but two different cloud regimes occur under synoptic descent. When vertical motion is downward during summer, extensive stratocumulus cloudiness is associated with near-surface northerly wind, while frequent cloudless pixels occur with southerly wind. Examination of ship-reported cloud types indicates that midlatitude stratocumulus breaks up as the boundary layer decouples when it is advected equatorward over warmer water. Cumulus is prevalent under conditions of synoptic descent and cold advection during winter. Poleward advection of subtropical air over colder water causes stratification of the near-surface layer that inhibits upward mixing of moisture and suppresses cloudiness until a fog eventually forms. Averaging of cloud and radiation data into intervals of 500-hPa vertical velocity and advection over the SST gradient enables the cloud response to changes in temperature and the stratification of the lower troposphere to be investigated independent of the dynamics. Vertically uniform warming results in decreased cloud amount and optical thickness over a large range of dynamical conditions. Further calculations indicate that a decrease in the variance of vertical velocity would lead to a small decrease in mean cloud optical thickness and cloud-top height. These results suggest that reflection of solar radiation back to space by midlatitude oceanic clouds will decrease as a direct response to global warming, thus producing an overall positive feedback on the climate system. An additional decrease in solar reflection would occur were the storm track also to weaken, whereas an intensification of the storm track would partially cancel the cloud response to warming.