Validating Dose Uncertainty Estimates Produced by AUTODIRECT: An Automated Program to Evaluate Deformable Image Registration Accuracy.

Deformable image registration is a powerful tool for mapping information, such as radiation therapy dose calculations, from one computed tomography image to another. However, deformable image registration is susceptible to mapping errors. Recently, an automated deformable image registration evaluation of confidence tool was proposed to predict voxel-specific deformable image registration dose mapping errors on a patient-by-patient basis. The purpose of this work is to conduct an extensive analysis of automated deformable image registration evaluation of confidence tool to show its effectiveness in estimating dose mapping errors. The proposed format of automated deformable image registration evaluation of confidence tool utilizes 4 simulated patient deformations (3 B-spline-based deformations and 1 rigid transformation) to predict the uncertainty in a deformable image registration algorithm's performance. This workflow is validated for 2 DIR algorithms (B-spline multipass from Velocity and Plastimatch) with 1 physical and 11 virtual phantoms, which have known ground-truth deformations, and with 3 pairs of real patient lung images, which have several hundred identified landmarks. The true dose mapping error distributions closely followed the Student t distributions predicted by automated deformable image registration evaluation of confidence tool for the validation tests: on average, the automated deformable image registration evaluation of confidence tool-produced confidence levels of 50%, 68%, and 95% contained 48.8%, 66.3%, and 93.8% and 50.1%, 67.6%, and 93.8% of the actual errors from Velocity and Plastimatch, respectively. Despite the sparsity of landmark points, the observed error distribution from the 3 lung patient data sets also followed the expected error distribution. The dose error distributions from automated deformable image registration evaluation of confidence tool also demonstrate good resemblance to the true dose error distributions. Automated deformable image registration evaluation of confidence tool was also found to produce accurate confidence intervals for the dose-volume histograms of the deformed dose

Seeing coffee tourism through the lens of coffee consumption: A critical review

One of the world’s most popular beverages, coffee is used to satisfy a wide range of consumptions, including tourism. In this article, we examined the existing concepts of coffee consumption and identified additional consumption domains that may contribute to the growing body of knowledge regarding coffee tourism. The paper used a scoping review approach and Critical Media Discourse Analysis (CMDA). The scoping review examined 152 articles on coffee consumption and coffee tourism published up to 2020. Subsequently, CMDA enabled a more in-depth textual and contextual analysis of the literature. In addition, Leximancer was used to illuminate the prominent scopes of the literature. Three prominent scopes of the literature are identified in the textual analysis: consumer behaviour, place consumption,and ethical consumption. In addition, the contextual findings indicate that coffee tourism studies have increased in recent decades. Furthermore, the social context highlights the dynamic nature of the coffee market landscape in the global North and the global South. Future research directions were suggested, and the managerial implications of these findings were discussed

Understanding of Molecular Interactions and Reversibility in Silylamines

Modern Li-ion batteries employ flammable electrolytes that pose safety concerns. Battery safety has become important as several incidents involving Li-ion battery fires have been observed. This issue could be addressed through a switchable battery electrolyte. Reversible ionic liquids (RevILs) could be used in such an electrolyte that would cease operation in the event of rapid temperature elevation because they can switch between states of drastically different properties upon the application of an external stimulus, such as temperature or CO2 addition. Silylamines, in particular, are a class of thermally responsive RevILs that are conducting in its ionic liquid (RevIL) state and non-conducting in its molecular liquid (ML) state. Thus, silylamines could serve as model compounds for the thermally switchable battery electrolyte concept. However, the temperature dynamics and ion-ion interactions within the silylamine system need to be understood before implementation. This thesis explores the viability of the (3-aminopropyl)tripropylsilylamine (TPSA) system based on its thermal responses and salt interactions. Because neat TPSA (RevIL) is viscous and non-conductive, TPSA was also studied as a solvent mixture with DMSO. Variable temperature (VT) FT-IR studies showed that the RevIL to ML switch was maintained in the TPSA/DMSO system. VT conductivity studies showed a conductivity maximum at 90°C. The thermal dependence of conductivity makes TPSA a potential candidate for the thermal switch. HOESY and PGSE NMR experiments were also performed to understand the issue of salt solubility, which correlate the ion-ion interactions within the electrolyte mixture. These experiments revealed that the alkyl groups may participate in interactions upon addition of lithium hexafluorophosphate salt, which results in inhibited diffusion. This signals a possible route for tuning the TPSA structure to improving the conductivity and salt solubility for eventual use as an electrolyte solvent

Moderating Social Media Discourse for a Healthy Democracy

The prevalence of hate speech and misinformation on the internet, heightened by the COVID-19 pandemic, directly harms minority groups that are the target of vitriol, as well as our society at large (Müller & Scwarz, 2020). In addition, the intersection between the two only exacerbates their harmful effects leading to an increase in intolerance and polarization (Kim & Kesari 2021). Current platform moderation techniques, as well as Section 230 under the Communications Decency Act, have been insufficient in addressing this problem, resulting in a lack of transparency from internet service providers, clear boundaries on user-platforms relations, and sufficient tools to handle a rapidly expanding internet. To address this problem space, we advocate for the following solutions: 1. Algorithmic governance & transparency: Internet Service Providers should be more transparent with users about content moderation policies and algorithms, and clarify users’ basic rights on the platform. 2. Flagging recommendations: We advocate a more effective, efficient and comprehensive flagging system through a combined strategy of content- and user-based approaches. 3. Multiplatform collaboration: Fighting harmful online content requires a collaborative effort among policy makers, civil society groups, researchers, and different platforms. 4. Long-term considerations: Building a regular and prolonged tracking system is essential to make anti-misinformation efforts more efficient and effective, especially in complex scenarios.Journalism and Medi

Inhibiting tryptophan metabolism enhances interferon therapy in kidney cancer.

Renal cell carcinoma (RCC) is increasing in incidence, and a complete cure remains elusive. While immune-checkpoint antibodies are promising, interferon-based immunotherapy has been disappointing. Tryptophan metabolism, which produces immunosuppressive metabolites, is enhanced in RCC. Here we show indolamine-2,3-dioxygenase-1 (IDO1) expression, a kynurenine pathway enzyme, is increased not only in tumor cells but also in the microenvironment of human RCC compared to normal kidney tissues. Neither kynurenine metabolites nor IDO inhibitors affected the survival or proliferation of human RCC or murine renal cell adenocarcinoma (RENCA) cells in vitro. However, interferon-gamma (IFNγ) induced high levels of IDO1 in both RCC and RENCA cells, concomitant with enhanced kynurenine levels in conditioned media. Induction of IDO1 by IFNα was weaker than by IFNγ. Neither the IDO1 inhibitor methyl-thiohydantoin-DL-tryptophan (MTH-trp) nor IFNα alone inhibited RENCA tumor growth, however the combination of MTH-trp and IFNα reduced tumor growth compared to IFNα. Thus, the failure of IFNα therapy for human RCC is likely due to its inability to overcome the immunosuppressive environment created by increased IDO1. Based on our data, and given that IDO inhibitors are already in clinical trials for other malignancies, IFNα therapy with an IDO inhibitor should be revisited for RCC

Audio-as-Data Tools: Replicating Computational Data Processing

The rise of audio-as-data in social science research accentuates a fundamental challenge: establishing reproducible and reliable methodologies to guide this emerging area of study. In this study, we focus on the reproducibility of audio-as-data preparation methods in computational communication research and evaluate the accuracy of popular audio-as-data tools. We analyze automated transcription and computational phonology tools applied to 200 episodes of conservative talk shows hosted by Rush Limbaugh and Alex Jones. Our findings reveal that the tools we tested are highly accurate. However, despite different transcription and audio signal processing tools yield similar results, subtle yet significant variations could impact the findings’ reproducibility. Specifically, we find that discrepancies in automated transcriptions and auditory features such as pitch and intensity underscore the need for meticulous reproduction of data preparation procedures. These insights into the variability introduced by different tools stress the importance of detailed methodological reporting and consistent processing techniques to ensure the replicability of research outcomes. Our study contributes to the broader discourse on replicability and reproducibility by highlighting the nuances of audio data preparation and advocating for more transparent and standardized practices in this area

The State of Digital Media Data Research, 2024

The purpose of this report is to reflect on the state of digital media data research in 2024. This is the second in a series of reports on the state of digital media research, which we originally published in 2023. We reflect on changes to digital media research since our report in 2023. Specifically, we highlight the following trends: 1. From 2023 to 2024, access to digital media data changed drastically. Researchers were largely priced out of the Twitter API, and Pushshift–a commonly used archive for Reddit data–went private to comply with Reddit’s API policies. Meta also announced the imminent sunsetting of CrowdTangle, a transparency tool popular amongst researchers and journalists alike. At the same time, however, many platforms announced academic programs for data access, including the YouTube researcher program, TikTok’s Research API, and the Meta Content Library. 2. Federated social media platforms became more popular. Following Elon Musk’s purchase of Twitter, Twitter users flocked to Mastodon, Threads, BlueSky, and other federated (or soon to be federated) platforms. This presents unique challenges for researchers studying digital media data. As new platforms are created, researchers must build new tools to analyze them or wait for third parties or the platforms themselves to make data available. 3. Generative AI’s explosion may change how we study digital media. First, researchers using computational methods to measure social media content have turned to OpenAI’s ChatGPT and other Large Language Models (LLMs) to classify content. Second, researchers and civil society groups are increasingly concerned about the possibility for Generative AI to flood the information environment with fake content. 4. In February 2024, the EU Digital Services Act (DSA) went into effect, mandating that large platforms give researchers near real-time access to public data. We don’t yet know how these policies will impact data access in the United States, and it remains unclear what this data access will look like in practice. In the United States, legislative efforts to mandate researcher access stalled. While the last year brought many welcome and unwelcome changes to digital media data research, the findings in this report renew our encouragement that digital media data research should be guided by collaboration, transparency, preparation, and consistency.Journalism and Medi