TRBLLmaker -- Transformer Reads Between Lyrics Lines maker

Even for us, it can be challenging to comprehend the meaning of songs. As part of this project, we explore the process of generating the meaning of songs. Despite the widespread use of text-to-text models, few attempts have been made to achieve a similar objective. Songs are primarily studied in the context of sentiment analysis. This involves identifying opinions and emotions in texts, evaluating them as positive or negative, and utilizing these evaluations to make music recommendations. In this paper, we present a generative model that offers implicit meanings for several lines of a song. Our model uses a decoder Transformer architecture GPT-2, where the input is the lyrics of a song. Furthermore, we compared the performance of this architecture with that of the encoder-decoder Transformer architecture of the T5 model. We also examined the effect of different prompt types with the option of appending additional information, such as the name of the artist and the title of the song. Moreover, we tested different decoding methods with different training parameters and evaluated our results using ROUGE. In order to build our dataset, we utilized the 'Genious' API, which allowed us to acquire the lyrics of songs and their explanations, as well as their rich metadata

Bedside differentiation of vestibular neuritis from central "vestibular pseudoneuritis".

Acute unilateral peripheral and central vestibular lesions can cause similar signs and symptoms, but they require different diagnostics and management. We therefore correlated clinical signs to differentiate vestibular neuritis (40 patients) from central ‘‘vestibular pseudoneuritis’’ (43 patients) in the acute situation with the final diagnosis assessed by neuroimaging. Skew deviation was the only specific but non-sensitive (40%) sign for pseudoneuritis. None of the other isolated signs (head thrust test, saccadic pursuit, gaze evoked nystagmus, subjective visual vertical) were reliable; however, multivariate logistic regression increased their sensitivity and specificity to 92%

Continuing Change in a Virtual World: Training and Recruiting Instructors

The process of teacher identification, selection, initial training, and on-going professional development that has developed at the Illinois Virtual High School (IVHS) over the past seven years is described and discussed in this article. Validation was based upon existing practices and research. To provide background the creation and initial development of the IVHS is described. Some of the issues within the hiring process and professional development that the IVHS continues to struggle are examined including teacher certification and the changing nature of technology. The paper concludes with a recommendation that teacher education programs assist in addressing these challenges to support IVHS and other virtual schools

Career Planning with Careerforward: Exploring Student Perceptions and Experiences in an Online Career Preparation Course

In April 2006, the Michigan State Board of Education and Michigan Legislatures adopted a rigorous package of high school graduation requirements, one of which made Michigan the first state that incorporated an online learning graduation requirement into the K‐12 curriculum. All Michigan\u27s students entering high school during 2008‐2009 school year were required to complete online learning during their course of high school studies in order to graduate. Michigan Virtual School helped the schools in Michigan to fulfill this requirement by developing a 20‐hour online learning course called “Career Forward”. In December 2008, the Michigan Virtual University provided the National Repository of Online Courses access to the CareerForward course content, allowing students from anywhere in the United States, the ability to access CareerForward free of charge. This evaluation study was conducted to provide Michigan Virtual School with information to improve the design and delivery of the Career Forward course, in order to improve the learning experiences of the future student and to improve the overall efficiency of the course. Analysis of data from this research indicated that, CareerForward in its current format had very little impact on student attitude towards career planning. Recommendations for changes in design and delivery options of the course for future offerings are suggested in order to make the course more effective and to meet its objectives

Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines

Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process. However, the process by which the encoder produces the text representation is unknown. We propose the Diffusion Lens, a method for analyzing the text encoder of T2I models by generating images from its intermediate representations. Using the Diffusion Lens, we perform an extensive analysis of two recent T2I models. Exploring compound prompts, we find that complex scenes describing multiple objects are composed progressively and more slowly compared to simple scenes; Exploring knowledge retrieval, we find that representation of uncommon concepts requires further computation compared to common concepts, and that knowledge retrieval is gradual across layers. Overall, our findings provide valuable insights into the text encoder component in T2I pipelines.Comment: Project webpage: tokeron.github.io/DiffusionLensWe

A Dataset for Metaphor Detection in Early Medieval Hebrew Poetry

There is a large volume of late antique and medieval Hebrew texts. They represent a crucial linguistic and cultural bridge between Biblical and modern Hebrew. Poetry is prominent in these texts and one of its main haracteristics is the frequent use of metaphor. Distinguishing figurative and literal language use is a major task for scholars of the Humanities, especially in the fields of literature, linguistics, and hermeneutics. This paper presents a new, challenging dataset of late antique and medieval Hebrew poetry with expert annotations of metaphor, as well as some baseline results, which we hope will facilitate further research in this area.Comment: EACL 2024. Project webpage: https://tokeron.github.io/metaphor

Laser Powder Bed Fusion of NiTiHf High-Temperature Shape Memory Alloy: Effect of Process Parameters on the Thermomechanical Behavior

Laser powder bed fusion has been widely investigated for shape memory alloys, primarily NiTi alloys, with the goal of tailoring microstructures and producing complex geometries. However, processing high temperature shape memory alloys (HTSMAs) remains unknown. In our previous study, we showed that it is possible to manufacture NiTiHf HTSMA, as one of the most viable alloys in the aerospace industry, using SLM and investigated the effect of parameters on defect formation. The current study elucidates the effect of process parameters (PPs) on the functionality of this alloy. Shape memory properties and the microstructure of additively manufactured Ni-rich NiTiHf alloys were characterized across a wide range of PPs (laser power, scanning speed, and hatch spacing) and correlated with energy density. The optimum laser parameters for defect-free and functional samples were found to be in the range of approximately 60–100 J/mm3. Below an energy density of 60 J/mm3, porosity formation due to lack-of-fusion is the limiting factor. Samples fabricated with energy densities of 60–100 J/mm3 showed comparable thermomechanical behavior in comparison with the starting as-cast material, and samples fabricated with higher energy densities (\u3e 100 J/mm3) showed very high transformation temperatures but poor thermomechanical behavior. Poor properties for samples with higher energies were mainly attributed to the excessive Ni loss and resultant change in the chemical composition of the matrix, as well as the formation of cracks and porosities. Although energy density was found to be an important factor, the outcome of this study suggests that each of the PPs should be selected carefully. A maximum actuation strain of 1.67% at 400 MPa was obtained for the sample with power, scan speed, and hatch space of 100 W, 400 mm/s, and 140 µm, respectively, while 1.5% actuation strain was obtained for the starting as-cast ingot. These results can serve as a guideline for future studies on optimizing PPs for fabricating functional HTSMAs

Mechanisms underlying disorders of consciousness: Bridging gaps to move toward an integrated translational science

AIM: In order to successfully detect, classify, prognosticate, and develop targeted therapies for patients with disorders of consciousness (DOC), it is crucial to improve our mechanistic understanding of how severe brain injuries result in these disorders. METHODS: To address this need, the Curing Coma Campaign convened a Mechanisms Sub-Group of the Coma Science Work Group (CSWG), aiming to identify the most pressing knowledge gaps and the most promising approaches to bridge them. RESULTS: We identified a key conceptual gap in the need to differentiate the neural mechanisms of consciousness per se, from those underpinning connectedness to the environment and behavioral responsiveness. Further, we characterised three fundamental gaps in DOC research: (1) a lack of mechanistic integration between structural brain damage and abnormal brain function in DOC; (2) a lack of translational bridges between micro- and macro-scale neural phenomena; and (3) an incomplete exploration of possible synergies between data-driven and theory-driven approaches. CONCLUSION: In this white paper, we discuss research priorities that would enable us to begin to close these knowledge gaps. We propose that a fundamental step towards this goal will be to combine translational, multi-scale, and multimodal data, with new biomarkers, theory-driven approaches, and computational models, to produce an integrated account of neural mechanisms in DOC. Importantly, we envision that reciprocal interaction between domains will establish a virtuous cycle, leading towards a critical vantage point of integrated knowledge that will enable the advancement of the scientific understanding of DOC and consequently, an improvement of clinical practice

Spatial patterns and intraspecific diversity of the glacial relict legume species Vavilovia formosa (Stev.) Fed. in Eurasia

Vavilovia formosa is one of five genera in tribe Fabeae, (Fabaceae, Leguminosae) with close phylogenetic relationships to Pisum. It grows in subalpine and alpine levels in Armenia, Azerbaijan, Georgia, Iran, Iraq, Lebanon, Russia and Turkey and is recognized as an endangered and protected plant. This study was conducted to reveal its intraspecific variability, as well as to predict the past, extant and future species distribution range. We analysed 51 accessions with common phylogenetic markers (trnF-trnL, trnS-trnG, matK, rbcL, psbA-trnH and ITS). These represent in total up to 2551 bp of chloroplast and 664 bp of nuclear sequences per sample. Two populations from Turkey and Armenia were analysed for genetic diversity by AFLP

Beyond species counts for assessing, valuing, and conserving biodiversity:response to Wallach et al. 2019

Article impact statement: Combining native and non‐native species to evaluate biodiversity is overly simplistic and may undermine the conservation of ecosystems