A Late Miocene Accipitrid (Aves: Accipitriformes) from Nebraska and Its Implications for the Divergence of Old World Vultures

Background: Old World vultures are likely polyphyletic, representing two subfamilies, the Aegypiinae and Gypaetinae, and some genera of the latter may be of independent origin. Evidence concerning the origin, as well as the timing of the divergence of each subfamily and even genera of the Gypaetinae has been elusive. Methodology/Principal Findings: Compared with the Old World, the New World has an unexpectedly diverse and rich fossil component of Old World vultures. Here we describe a new accipitriform bird, Anchigyps voorhiesi gen. et sp. nov., from the Ash Hollow Formation (Upper Clarendonian, Late Miocene) of Nebraska. It represents a form close in morphology to the Old World vultures. Characteristics of its wing bones suggest it was less specialized for soaring than modern vultures. It was likely an opportunistic predator or scavenger having a grasping foot and a mandible morphologically similar to modern carrion-feeding birds. Conclusions/Significance: The new fossil reported here is intermediate in morphology between the bulk of accipitrids and the Old World gypaetine vultures, representing a basal lineage of Accipitridae trending towards the vulturine habit, and of its Late Miocene age suggests the divergence of true gypaetine vultures, may have occurred during or slightly before the Miocene

Spatial Parameter Identification for MIMO Systems in the Presence of Non-Gaussian Interference

Reliable identification of spatial parameters for multiple-input multiple-output (MIMO) systems, such as the number of transmit antennas (NTA) and the direction of arrival (DOA), is a prerequisite for MIMO signal separation and detection. Most existing parameter estimation methods for MIMO systems only consider a single parameter in Gaussian noise. This paper develops a reliable identification scheme based on generalized multi-antenna time-frequency distribution (GMTFD) for MIMO systems with non-Gaussian interference and Gaussian noise. First, a new generalized correlation matrix is introduced to construct a generalized MTFD matrix. Then, the covariance matrix based on time-frequency distribution (CM-TF) is characterized by using the diagonal entries from the auto-source signal components and the non-diagonal entries from the cross-source signal components in the generalized MTFD matrix. Finally, by making use of the CM-TF, the Gerschgorin disk criterion is modified to estimate NTA, and the multiple signal classification (MUSIC) is exploited to estimate DOA for MIMO system. Simulation results indicate that the proposed scheme based on GMTFD has good robustness to non-Gaussian interference without prior information and that it can achieve high estimation accuracy and resolution at low and medium signal-to-noise ratios (SNRs)

SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching

This paper presents a study of automatic design of neural network architectures for skeleton-based action recognition. Specifically, we encode a skeleton-based action instance into a tensor and carefully define a set of operations to build two types of network cells: normal cells and reduction cells. The recently developed DARTS (Differentiable Architecture Search) is adopted to search for an effective network architecture that is built upon the two types of cells. All operations are 2D based in order to reduce the overall computation and search space. Experiments on the challenging NTU RGB+D and Kinectics datasets have verified that most of the networks developed to date for skeleton-based action recognition are likely not compact and efficient. The proposed method provides an approach to search for such a compact network that is able to achieve comparative or even better performance than the state-of-the-art methods

LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors

Prompt-tuning has emerged as an attractive paradigm for deploying large-scale language models due to its strong downstream task performance and efficient multitask serving ability. Despite its wide adoption, we empirically show that prompt-tuning is vulnerable to downstream task-agnostic backdoors, which reside in the pretrained models and can affect arbitrary downstream tasks. The state-of-the-art backdoor detection approaches cannot defend against task-agnostic backdoors since they hardly converge in reversing the backdoor triggers. To address this issue, we propose LMSanitator, a novel approach for detecting and removing task-agnostic backdoors on Transformer models. Instead of directly inverting the triggers, LMSanitator aims to invert the predefined attack vectors (pretrained models' output when the input is embedded with triggers) of the task-agnostic backdoors, which achieves much better convergence performance and backdoor detection accuracy. LMSanitator further leverages prompt-tuning's property of freezing the pretrained model to perform accurate and fast output monitoring and input purging during the inference phase. Extensive experiments on multiple language models and NLP tasks illustrate the effectiveness of LMSanitator. For instance, LMSanitator achieves 92.8% backdoor detection accuracy on 960 models and decreases the attack success rate to less than 1% in most scenarios.Comment: To Appear in the Network and Distributed System Security (NDSS) Symposium 2024, 26 February - 1 March 2024, San Diego, CA, USA; typos correcte

Evaluation of GaN-HEMT power amplifiers using BST-based components for load modulation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.In this paper, the concept of load-modulated power amplifiers (PAs) is studied. Two GaN-HEMT power amplifiers (PAs), targeted for high efficiency at maximum and output back-off (OBO) power levels, are designed, implemented, and tested across 1.8–2.2 GHz. The load modulation in the first design is realized by tuning the shunt capacitors in the output matching network. A novel method is employed in the second design, where barium–stronrium–titante is used for the realization of load modulation. The large-signal measurement results across the desired band show 59–70% drain efficiency at 44–44.5 dBm output power for both designs. Using the available tunable technique, the drain efficiency of the PAs is enhanced by 4–20% at 6 dB OBO across the bandwidth

Method and system for detecting common attributes of network upgrades

A system and method identify a set of rules for determining a commonality of attributes across different behavior changes for a network. The system performs the method by receiving a set of data correlating network triggers to performance changes of one or more network devices. The set of data further includes an indication of a sign of the performance change for each of the network devices based on the triggers. The method further includes extracting a set of rules relating to a set of relationships between the triggers and the performance changes. The rules identify a commonality of the performance changes for multiple network devices based on the triggers.Board of Regents, University of Texas Syste