26419 research outputs found
Sort by
Line List for the A²Π−X²Σ⁺ and the B²Σ⁺−X²Σ⁺ Band Systems of CaF
No full textThe spectral analysis of molecule-rich asymptotic giant branch (AGB) stars is challenging. Although other calcium and fluorine bearing molecules are observed in the microwave and in the visible spectrum of AGB stars, CaF has never been detected, despite favorable chemical equilibrium predictions. Yet, measuring the CaF abundance could give more insight into the fluorine budget of AGB stars and allow better simulation of stellar spectra. In this work, we present an analysis of the visible spectrum of CaF obtained with a Fourier transform spectrometer. CaF A²Π−X²Σ⁺ and B²Σ⁺−X²Σ⁺ band systems were excited with a hollow cathode discharge. Using previous fluorescence spectroscopy measurements, highly accurate ground state constants, and reasonable extrapolation schemes, the strongest features of CaF in the visible spectrum can be accurately modeled for both band systems. Spectroscopic constants are determined for A² Π with v ≤ 16 and for B²Σ⁺ with v ≤ 20. Ab initio transition dipole moment curves of both transitions were calculated and scaled, and we provide a line list with Einstein A coefficients and oscillator strengths. This line list can be used to simulate spectra of CaF at temperatures and pressures relevant to astrophysical environments
Women and Global Documentary: Practices and Perspectives in the 21st Century
No full textIn what innovative ways are women documentary filmmakers seeking to prioritize and promote political awareness, alternative modes of allyship, and advocacy for those most marginalized by patriarchy and global capitalism? Women and Global Documentary answers the urgent need to re-evaluate the significance of women\u27s documentary practices, their contributions to feminist world-building, and to the state of documentary studies as a whole. Bringing together a range of diverse practitioners and authors, the volume analyzes alternative and emergent networks of documentary production and collaboration within a global context. The chapters investigate filmmaking practices from regions such as East Africa, Latin America, South Asia, East Asia, the Middle East, and North Africa. They also examine decolonial practices in the Global North based on Indigenous filmmaking and feminist documentary institutions such as Women Make Movies. In doing so, they assess the global, institutional, political, and artistic factors that have shaped women\u27s documentary practices in the 21st century, and their implications for scholarly debates regarding women\u27s authorship, political subjectivity, and documentary representation. [Amazon.com]https://digitalcommons.odu.edu/communication_books/1032/thumbnail.jp
Factors Affecting the Quality of Life of Residents in the United States: Lessons from Virginia
Get PDFEvaluating community members\u27 views about their quality of life is important for improving quality of well-being in society, as most societies are interested in the collective well-being of the people. Moreover, quality-of-life research helps public officials to understand how well they are meeting the needs of the electorate. Using the theoretical framework of Maslow\u27s Developmental Perspective, which argues that the higher the need satisfaction of the majority in a given society the greater the quality of life of that society, I explore the effects of multiple variables on quality of life in the Hampton Roads region of Southeast Virginia (this region has approximately 1.5 million people). Using data from a random sample of 639 respondents who reside in the Hampton Roads region, I found that, compared to Whites, Black respondents had a lower quality of life. Moreover, the more highly educated, those with higher incomes, and those who were married indicated that they had a higher quality of life. Finally, economic conditions, personal finances, personal health, quality of medical and health care and the quality of the public school system all predicted community members\u27 quality of life. Of the substantive predictors, economic conditions had the strongest predictive effect on quality of life in the Hampton Roads region. The implications of the findings for scholars, elected officials, community relations, public policy and future research are discussed
A Review of Infrared Thermography Applications for Civil Infrastructure
Get PDFCivil infrastructure is continuously subject to aging and deterioration due to multiple factors, which lead to a decline in performance and impact structural health. Accumulated damage on structures increases operational costs and poses significant risks to public safety. Effective maintenance, repair, and rehabilitation strategies are needed to ensure civil infrastructure’s overall safety and reliability. Non-Destructive Evaluation (NDE) methods are utilized to assess latent damage and provide decision-makers with real-time information for mitigating hazards. Within the last decade, there has been a significant increase in the research and development of innovative NDE techniques to improve data processing and promote efficient and accurate infrastructure assessment. This paper aims to review one of those methods, namely, Infrared Thermography (IRT), and its applications in civil infrastructure. A comprehensive review is presented by investigating numerous journal articles, research papers, and technical reports describing numerous IRT applications for bridges, buildings, and general civil structures made from different materials. The capability of IRT to identify and pinpoint anomalies, typically in the early stages of degradation, has excellent potential to improve the safety and shore up the dependability of civil infrastructures while reducing expenses tied to maintenance and rehabilitation. Furthermore, the non-invasive nature of IRT is beneficial in mitigating disturbances and downtime that may occur during various inspection procedures. It is highlighted that IRT is a highly versatile and effective tool for infrastructure condition assessment. With further advancement and fine-tuning of the available techniques, it is likely that IRT will continue to gain significant popularity in maintaining and monitoring civil infrastructure
Formulation Development of Dual-Compartment Topical Inserts Combining Tenofovir Alafenamide and Elvitegravir for Flexible On-Demand HIV Prevention
Get PDFPre-exposure prophylaxis (PrEP) has emerged as a prominent approach for the prevention of HIV infections. While the latest advances have resulted in effective oral and injectable product options, there are still gaps in on-demand, event-driven, topical products for HIV prevention that are safe and effective. Here we describe the formulation development of a dual-compartment topical insert containing tenofovir alafenamide fumarate (TAF) and elvitegravir (EVG) that may be administered when needed, vaginally or rectally, pre- or post-coitus, for flexible HIV prophylaxis. Specifically, we describe the lab-scale formulation development, preclinical mucosal safety and pharmacokinetics (PK) testing in rabbits, long-term stability, and scale-up clinical manufacturing of the lead TAF/EVG (20 mg/16 mg) inserts, which are currently in clinical stages of development. As designed, the inserts are small, discreet and portable, offering a number of promising attributes, such as simple and robust direct-compression manufacturing, fast initial disintegration/dissolution, and suitable mechanical strengths showing low hardness (\u3c8 kg), friability (\u3c1 %), and moisture content (\u3c1 %). The inserts initiated disintegration quickly (~ ≤ 15 min) providing full in vitro release (\u3e90 %) of TAF and EVG within 60 min of dissolution. The lead insert was selected from formulation prototypes that met the evaluation criteria for manufacturability and characterization, together with a dose-ranging PK study in non-human primates. Successful technology transfer for clinical development of the lead TAF/EVG (20 mg/16 mg) insert was confirmed under cGMP conditions. Based on the 12 months (lab-scale) and 24 months (clinical batch) stability data, the TAF/EVG inserts are projected to have a long shelf life of over 2 years, if stored at or below 30 °C/65 % RH. Overall, these newly designed topical inserts have formulation properties that enable stable storage and fast release of the antiretroviral payload from a small, portable and discreet dosage form. They are safe and effective when applied vaginally or rectally, before or after coitus, providing the basis for a new method of flexible on-demand HIV prevention for cisgender and transgender women and men. The TAF/EVG inserts are currently the most clinically advanced on-demand topical product, as attested by their completed and ongoing clinical trials
Collision-Induced Absorption Spectra of N₂ and CH₄
Get PDFCollision-induced spectra are essential for radiative transfer modeling of Titan\u27s atmosphere. We present experimental spectra of nitrogen–methane mixtures with an accompanying fit of N₂-CH₄ collision-induced absorption in the 30–400 cm⁻¹ region at about 130 K. We found a peak absorption of 2.30 × 10⁻⁵ cm⁻¹ amagat⁻² at 75 cm⁻¹ and a secondary peak of 1.35 × 10⁻⁵ c⁻¹ amagat⁻² at 206.5 cm⁻¹, which agrees with previous studies. Our work does not support the suggestion that N₂-CH₄ CIA in the far-infrared should be increased by about 50%, as suggested by spectroscopic modeling of Titan using data from A. Borysow & C. Tang
Foundation Models in Bioinformatics
Get PDFWith the adoption of foundation models (FMs), artificial intelligence (AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges, such as pre-training frameworks, model evaluation and interpretability. FMs demonstrate notable proficiency in managing large-scale, unlabeled datasets, because experimental procedures are costly and labor intensive. In various downstream tasks, FMs have consistently achieved noteworthy results, demonstrating high levels of accuracy in representing biological entities. A new era in computational biology has been ushered in by the application of FMs, focusing on both general and specific biological issues. In this review, we introduce recent advancements in bioinformatics FMs employed in a variety of downstream tasks, including genomics, transcriptomics, proteomics, drug discovery and single-cell analysis. Our aim is to assist scientists in selecting appropriate FMs in bioinformatics, according to four model types: language FMs, vision FMs, graph FMs and multimodal FMs. In addition to understanding molecular landscapes, AI technology can establish the theoretical and practical foundation for continued innovation in molecular biology
A Comparison of Microcrystal Electron Diffraction and X-Ray Powder Diffraction for the Structural Analysis of Metal-Organic Frameworks
Get PDFThis study successfully implemented microcrystal electron diffraction (microED) and X-ray powder diffraction (XRPD) for the crystal structure determination of a new phase, TAF-CNU-1, Ni(C₈H₄O₄)·3H₂O, solved by microED from single microcrystals in the powder and refined at the kinematic and dynamic electron diffraction theory levels. This nickel metal–organic framework (MOF), together with its cobalt and manganese analogues with formula M (C₈H₄O₄)·2H₂O with M = Mn II or CoII, were synthesized in aqueous media as one-pot preparations from the corresponding hydrated metal chlorides and sodium terephthalate, as a promising `green\u27 synthetic route to moisture-stable MOFs. The crystal structures of the two latter materials have been previously determined ab initio from X-ray powder diffraction. The advantages and disadvantages of both structural characterization techniques are briefly summarized. Additional solid-state property characterization was carried out using thermogravimetric analysis, scanning electron microscopy and Fourier transform infrared spectroscopy
Laser-Induced Graphene for Early Disease Detection: A Review
Get PDFElectrochemical biosensors have been instrumental in early disease detection, facilitating effective monitoring and treatment. The emergence of graphene has significantly advanced sensor technology in various fields, including biomedicine, electronics, and energy. In this landscape, laser‐induced graphene (LIG) has emerged as a superior alternative to conventional graphene synthesis methods. Its straightforward fabrication process and compatibility with wearable devices boost its practicality and potential for real‐world applications. This review highlights the transformative potential of LIG in biosensing, showcasing its contributions to the development of next‐generation diagnostic tools for early disease detection. An overview of the LIG synthesis process and its applications in detecting a wide array of biomarkers, from small molecules to large macromolecules, is provided. The integration of LIG biosensors into wearable devices are explored, highlighting their flexibility and potential for continuous, non‐invasive monitoring of biomarkers. Additionally, this review addresses the current challenges in this field and discusses the future directions for the advancement of LIG‐based biosensors in biomedical applications
Guiding Evolutionary Algorithms With Large Language Models to Learn Fuzzy Cognitive Maps
Get PDFFuzzy Cognitive Maps (FCMs) are interpretable simulation models that represent causal relationships between concepts as a weighted digraph with labeled nodes. They serve to examine a system’s structure (e.g., what concepts are critical to spreading an intervention’s effects?) and long-term behavior (e.g., if we increase fruit availability, how will its consumption change?). When modelers build FCMs by leveraging participants’ knowledge, the resulting participant-built FCMs can be analyzed and interpreted since participants report perceived causality. However, engaging enough knowledgeable participants to construct an FCM can be challenging. Alternatively, machine learning algorithms derive FCMs from data by selecting relationships to maximize a metric such as accuracy, which can produce overly dense FCMs where relationships may not represent valid causal mechanisms—this hinders the critically important interpretability of FCMs. In this paper, we address the need for expert knowledge and the validity of causal mechanisms in FCMs. Specifically, we propose using Large Language Models (LLMs) to guide algorithms in building FCMs where valid pairs of concepts are connected in the right causal direction and with the correct causal type (increase/decrease). Our approach combines LLMs with CMA-ES, a ubiquitous, state-of-the-art evolutionary algorithm. Using three real-world case studies and several LLMs, we show our method successfully (i) learns sparse FCMs that fit the data well and (ii) represents valid causal relationships. Moreover, the learned FCMs are sparser than the corresponding participant-built ones, demonstrating our method may help simplify existing FCMs and selectively includes causal relationships, which is essential to build trustworthy and interpretable FCMs