Stable isotopic indicators of population structure and natal habitats of Asian carps threatening to invade the Great Lakes

Understanding early-life habitats is crucial for managing non-indigenous large river fishes such as silver carp that are threatening to invade the Great Lakes and may significantly impact economically valuable Great Lakes fisheries. Silver carp inhabiting the upper Illinois River directly below the electrical deterrent barrier (installed on a canal in the Chicago area that connects the Illinois River with Lake Michigan) possess the greatest potential to invade the Great Lakes. However, adult silver carp inhabiting this reach of the Illinois River may have originated from many points throughout the Mississippi River basin (e.g., Illinois River or Middle Mississippi River), and the relative importance of these potential origination locations is unknown. As such, this study was used to identify natal habitats of adult silver carp in the upper portion of the Illinois River. Based on the stable oxygen and stable carbon isotopes of otoliths (earstones) from individual fish, we have determined that silver carp inhabiting the area below the electric barrier originated from within the Illinois River itself, the Middle Mississippi River, and floodplain lakes along the lower Illinois River valley. Because of the geographically widespread points of origin for individual fish, management efforts for eradication or control of silver carp in the upper Illinois River should be directed at a similarly broad geographic scale. While potentially challenging to implement, large-scale removal of silver carp and the closely related bighead carp in the Illinois and Mississippi Rivers could greatly reduce the probability of these species breaching the electrical barriers and entering the Great Lakes

Transcriptome Analyses of Tumor-Adjacent Somatic Tissues Reveal Genes Co-Expressed with Transposable Elements

Background: Despite the long-held assumption that transposons are normally only expressed in the germ-line, recent evidence shows that transcripts of transposable element (TE) sequences are frequently found in the somatic cells. However, the extent of variation in TE transcript levels across different tissues and different individuals are unknown, and the co-expression between TEs and host gene mRNAs have not been examined. Results: Here we report the variation in TE derived transcript levels across tissues and between individuals observed in the non-tumorous tissues collected for The Cancer Genome Atlas. We found core TE co-expression modules consisting mainly of transposons, showing correlated expression across broad classes of TEs. Despite this co-expression within tissues, there are individual TE loci that exhibit tissue-specific expression patterns, when compared across tissues. The core TE modules were negatively correlated with other gene modules that consisted of immune response genes in interferon signaling. KRAB Zinc Finger Proteins (KZFPs) were over-represented gene members of the TE modules, showing positive correlation across multiple tissues. But we did not find overlap between TE-KZFP pairs that are co-expressed and TE-KZFP pairs that are bound in published ChIP-seq studies. Conclusions: We find unexpected variation in TE derived transcripts, within and across non-tumorous tissues. We describe a broad view of the RNA state for non-tumorous tissues exhibiting higher level of TE transcripts. Tissues with higher level of TE transcripts have a broad range of TEs co-expressed, with high expression of a large number of KZFPs, and lower RNA levels of immune genes

Team 4 VCU: Ram Resources: Helping Faculty Help Students

The Ram Resources Project seeks to provide students with an environment that encourages their well-being by connecting them with resources needed to succeed in their academic career at VCU. Ram Resources will help reduce the detrimental impact of the number-one problem affecting students’ academic performance: stress. Faculty are uniquely situated both to recognize changes in students’ behavior and to assist students with improving their well-being. Beginning with New Faculty Orientation, Ram Resources will educate faculty about resources for well-being available to students. By creating a brochure, a website, and establishing a program of faculty ambassadors to familiarize faculty with the resources available to identify the warning signs of stress, the team proposes to help faculty help students

CONTINUOUSLY PRESTRESSED CONCRETE PILE SPLICE

A pile splice section for a spliced prestressed concrete pile includes a prestressed concrete element including a first end and a second end and a plurality of tendons that extend from the first end to the second end. A first end assembly at the first end of the prestressed concrete element includes a first plate coupled to the plurality of tendons. The first end assembly further includes a plurality of internally threaded fasteners embedded in the first end of the prestressed concrete element that are engagable via apertures extending through the first plate. A second end assembly at the second end of the prestressed concrete element includes a second metal plate coupled to the plurality of tendons. The second end assembly further includes a plurality of apertures extending through the second plate and accessible via pockets proximate the second end of the prestressed concrete element

CONTINUOUSLY PRESTRESSED CONCRETE PILE SPLICE

A pile splice section for a spliced prestressed concrete pile includes a prestressed concrete element including a first end and a second end and a plurality of tendons that extend from the first end to the second end. A first end assembly at the first end of the prestressed concrete element includes a first plate coupled to the plurality of tendons. The first end assembly further includes a plurality of internally threaded fasteners embedded in the first end of the prestressed concrete element that are engagable via apertures extending through the first plate. A second end assembly at the second end of the prestressed concrete element includes a second metal plate coupled to the plurality of tendons. The second end assembly further includes a plurality of apertures extending through the second plate and accessible via pockets proximate the second end of the prestressed concrete element

MusCaps: generating captions for music audio

Content-based music information retrieval has seen rapid progress with the adoption of deep learning. Current approaches to high-level music description typically make use of classification models, such as in auto tagging or genre and mood classification. In this work, we propose to address music description via audio captioning, defined as the task of generating a natural language description of music audio content in a human-like manner. To this end, we present the first music audio captioning model, MusCaps, consisting of an encoder-decoder with temporal attention. Our method combines convolutional and recurrent neural network architectures to jointly process audio-text inputs through a multimodal encoder and leverages pre-training on audio data to obtain representations that effectively capture and summarise musical features in the input. Evaluation of the generated captions through automatic metrics shows that our method outperforms a baseline designed for non-music audio captioning. Through an ablation study, we unveil that this performance boost can be mainly attributed to pre-training of the audio encoder, while other design choices – modality fusion, decoding strategy and the use of attention -- contribute only marginally. Our model represents a shift away from classification-based music description and combines tasks requiring both auditory and linguistic understanding to bridge the semantic gap in music information retrieval

Two-dimensional magnetoexcitons in the presence of spin-orbit coupling

We study theoretically the effect of spin-orbit coupling on quantum well excitons in a strong magnetic field. We show that, in the presence of an in-plane field component, the excitonic absorption spectrum develops a double-peak structure due to hybridization of bright and dark magnetoexcitons. If the Rashba and Dresselhaus spin-orbit constants are comparable, the magnitude of splitting can be tuned in a wide interval by varying the azimuthal angle of the in-plane field. We also show that the interplay between spin-orbit and Coulomb interactions leads to an anisotropy of exciton energy dispersion in the momentum plane. The results suggest a way for direct optical measurements of spin-orbit parameters.Comment: 9 pages, 6 figure

Contrastive audio-language learning for music

As one of the most intuitive interfaces known to humans, natural language has the potential to mediate many tasks that involve human-computer interaction, especially in application-focused fields like Music Information Retrieval. In this work, we explore cross-modal learning in an attempt to bridge audio and language in the music domain. To this end, we propose MusCALL, a framework for Music Contrastive Audio-Language Learning. Our approach consists of a dual-encoder architecture that learns the alignment between pairs of music audio and descriptive sentences, producing multimodal embeddings that can be used for text-to-audio and audio-to-text retrieval out-of-the-box. Thanks to this property, MusCALL can be transferred to virtually any task that can be cast as text-based retrieval. Our experiments show that our method performs significantly better than the baselines at retrieving audio that matches a textual description and, conversely, text that matches an audio query. We also demonstrate that the multimodal alignment capability of our model can be successfully extended to the zero-shot transfer scenario for genre classification and auto-tagging on two public datasets

Learning music audio representations via weak language supervision

Audio representations for music information retrieval are typically learned via supervised learning in a task-specific fashion. Although effective at producing state-of-the-art results, this scheme lacks flexibility with respect to the range of applications a model can have and requires extensively annotated datasets. In this work, we pose the question of whether it may be possible to exploit weakly aligned text as the only supervisory signal to learn general-purpose music audio representations. To address this question, we design a multimodal architecture for music and language pre-training (MuLaP) optimised via a set of proxy tasks. Weak supervision is provided in the form of noisy natural language descriptions conveying the overall musical content of the track. After pre-training, we transfer the audio backbone of the model to a set of music audio classification and regression tasks. We demonstrate the usefulness of our approach by comparing the performance of audio representations produced by the same audio backbone with different training strategies and show that our pre-training method consistently achieves comparable or higher scores on all tasks and datasets considered. Our experiments also confirm that MuLaP effectively leverages audio-caption pairs to learn representations that are competitive with audio-only and cross-modal self-supervised methods in the literature