Borderline Aggregation Kinetics in ``Dry'' and ``Wet'' Environments

We investigate the kinetics of constant-kernel aggregation which is augmented by either: (a) evaporation of monomers from finite-mass clusters, or (b) continuous cluster growth -- \ie, condensation. The rate equations for these two processes are analyzed using both exact and asymptotic methods. In aggregation-evaporation, if the evaporation is mass conserving, \ie, the monomers which evaporate remain in the system and continue to be reactive, the competition between evaporation and aggregation leads to several asymptotic outcomes. For weak evaporation, the kinetics is similar to that of aggregation with no evaporation, while equilibrium is quickly reached in the opposite case. At a critical evaporation rate, the cluster mass distribution decays as $k^{-5/2}$, where $k$ is the mass, while the typical cluster mass grows with time as $t^{2/3}$. In aggregation-condensation, we consider the process with a growth rate for clusters of mass $k$, $L_k$, which is: (i) independent of $k$, (ii) proportional to $k$, and (iii) proportional to $k^\mu$, with $0<\mu<1$. In the first case, the mass distribution attains a conventional scaling form, but with the typical cluster mass growing as $t\ln t$. When $L_k\propto k$, the typical mass grows exponentially in time, while the mass distribution again scales. In the intermediate case of $L_k\propto k^\mu$, scaling generally applies, with the typical mass growing as $t^{1/(1-\mu)}$. We also give an exact solution for the linear growth model, $L_k\propto k$, in one dimension.Comment: plain TeX, 17 pages, no figures, macro file prepende

Optimization in a Self-Stabilizing Service Discovery Framework for Large Scale Systems

Ability to find and get services is a key requirement in the development of large-scale distributed sys- tems. We consider dynamic and unstable environments, namely Peer-to-Peer (P2P) systems. In previous work, we designed a service discovery solution called Distributed Lexicographic Placement Table (DLPT), based on a hierar- chical overlay structure. A self-stabilizing version was given using the Propagation of Information with Feedback (PIF) paradigm. In this paper, we introduce the self-stabilizing COPIF (for Collaborative PIF) scheme. An algo- rithm is provided with its correctness proof. We use this approach to improve a distributed P2P framework designed for the services discovery. Significantly efficient experimental results are presented

Developmental Exposure to a Commercial PBDE Mixture: Effects on Protein Networks in the Cerebellum and Hippocampus of Rats

Background: Polybrominated diphenyl ethers (PBDEs) are structurally similar to polychlorinated biphenyls (PCBs) and have both central (learning and memory deficits) and peripheral (motor dysfunction) neurotoxic effects at concentrations/doses similar to those of PCBs. The cellular and molecular mechanisms for these neurotoxic effects are not fully understood; however, several studies have shown that PBDEs affect thyroid hormones, cause oxidative stress, and disrupt Ca2+-mediated signal transduction. Changes in these signal transduction pathways can lead to differential gene regulation with subsequent changes in protein expression, which can affect the development and function of the nervous system

Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages. This is achieved by pre-training the encoder of the model on a large unlabeled multilingual dataset of 12 million (M) hours spanning over 300 languages, and fine-tuning on a smaller labeled dataset. We use multilingual pre-training with random-projection quantization and speech-text modality matching to achieve state-of-the-art performance on downstream multilingual ASR and speech-to-text translation tasks. We also demonstrate that despite using a labeled training set 1/7-th the size of that used for the Whisper model, our model exhibits comparable or better performance on both in-domain and out-of-domain speech recognition tasks across many languages.Comment: 20 pages, 7 figures, 8 table

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a million hours of audio. We find that the combination of pre-training, self-training and scaling up model size greatly increases data efficiency, even for extremely large tasks with tens of thousands of hours of labeled data. In particular, on an ASR task with 34k hours of labeled data, by fine-tuning an 8 billion parameter pre-trained Conformer model we can match state-of-the-art (SoTA) performance with only 3% of the training data and significantly improve SoTA with the full training set. We also report on the universal benefits gained from using big pre-trained and self-trained models for a large set of downstream tasks that cover a wide range of speech domains and span multiple orders of magnitudes of dataset sizes, including obtaining SoTA performance on many public benchmarks. In addition, we utilize the learned representation of pre-trained networks to achieve SoTA results on non-ASR tasks.Comment: 14 pages, 7 figures, 13 tables; v2: minor corrections, reference baselines and bibliography updated; v3: corrections based on reviewer feedback, bibliography update

Stability and Control characteristics of MIG-21 aircraft

This document provides the stability and control derivatives data for the MIG-21BIS aircraft in the form readily usable for control system synthesis. Analytical prediction of the aircraft modes, typical time responses as well as Bode plots in the frequency domain are presented. Longitudinal dynamics data presented in this document supersedes the one provided in NAL PD SE 8501

Computation of the aerodynamic characteristics of wings in linearised supersonic flow

For the solution of tbe linearised supersonic flow equation, an explicit numerical scheme is discussed. Using this formulation,the aerodynamic characteristics of finite finite wings are coaputed based on lifting surface theory. Some results of the study of wing-fusalage configurations using this metbod are also given

A Computer programme for DATCOM methods of estimation of lateral stability and control derivatives

A computer code has been developed to estimate the lateral stability and control derivatives of aircraft configuration. The code, in general, is based on USAF DATCOM methods; in the case of a few derivatives, some approximate relations are used. The code estimates nine important lateral derivatives and five control derivatives. A brief review of the methods along with the limitations of DATCOM is presented. A comparison between the results of the code with those of the worked examples of DATCOM are given for some cases. Application of the code for typical configurations is discussed