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I Hate the News Jan 14
No full textThe weekly news analysis from I Hate Politics: Montgomery County Councilmember Will Jawando makes a big political play on housing policy. State could cut 5 percent from the University System of Maryland budget. The Town of Cheverly in Prince George’s County files lawsuits against the neighboring Bladensburg for trying to annex land on which a big development project is planned. Newly in public domain music from the 1920s: The Benson Orchestra of Chicago, the Paul Whiteman band, Carl Fenton, and Jan Garber.https://open.spotify.com/episode/03Iws2IGPoGxJBTWvGIrR
Variability of Eastern North Atlantic Summertime Marine Boundary Layer Clouds and Aerosols Across Different Synoptic Regimes Identified with Multiple Conditions
No full textThis study estimates the meteorological covariations of aerosol and marine boundary layer (MBL) cloud properties in the eastern North Atlantic (ENA) region, characterized by diverse synoptic conditions. Using a deep-learning-based clustering model with mid-level and surface daily meteorological data, we identify seven distinct synoptic regimes during the summer from 2016 to 2021. Our analysis, incorporating reanalysis data and satellite retrievals, shows that surface aerosols and MBL clouds exhibit clear regime-dependent characteristics, whereas lower tropospheric aerosols do not. This discrepancy likely arises from synoptic regimes determined by daily large-scale conditions, which may overlook air mass histories that predominantly dictate lower tropospheric aerosol conditions. Focusing on three regimes dominated by northerly winds, we analyze the Atmospheric Radiation Measurement Program (ARM) ENA observations on Graciosa Island in the Azores. In the subtropical anticyclone regime, fewer cumulus clouds and more single-layer stratocumulus clouds with light drizzle are observed, along with the highest cloud droplet number concentration (Nd), surface cloud condensation nuclei (CCN) and surface aerosol levels. The post-trough regime features more broken or multi-layer stratocumulus clouds with slightly higher surface rain rate, and lower Nd and surface CCN levels. The weak trough regime is characterized by the deepest MBL clouds, primarily cumulus and broken stratocumulus clouds, with the strongest surface rain rate and the lowest Nd, surface CCN and surface aerosol levels, indicating strong wet scavenging. These findings highlight the importance of considering the covariation of cloud and aerosol properties driven by large-scale regimes when assessing aerosol indirect effects using observations.We thank the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) data facility for providing observation data and ECMWF for providing ERA5 and CAMS reanalysis data products. This study is mainly conducted using computing resources from the National Energy Research Scientific Computing Center (NERSC), which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work is funded by the DOE Office of Science Early Career Research Program and the ASR Program. This work is also partially supported by the DOE’s ARM program. The work at Pacific Northwest National Laboratory was supported by the DOE’s ARM program (grant no. DE-AC05-76RL01830). The work at Argonne National Laboratory was supported by the U.S. DOE Office of Science under contract DE-AC02-06CH11357. The work at Lawrence Livermore National Laboratory was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNL-JRNL-865275.https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024JD04224
Automated flakiness detection in quantum software bug reports
No full text4th International Workshop on Quantum Software Engineering and Technology (co-located with QCE24), 15-20 September 2024, Montreal, QC, CanadaA flaky test yields inconsistent results upon repetition, posing a significant challenge to software developers. An extensive study of their presence and characteristics has been done in classical computer software but not quantum computer software. In this paper, we outline challenges and potential solutions for the automated detection of flaky tests in bug reports of quantum software. We aim to raise awareness of flakiness in quantum software and encourage the software engineering community to work collaboratively to solve this emerging challenge.https://ieeexplore.ieee.org/document/1082113
Single Image Super Resolution Using AI Generated Images
No full textImage super-resolution has become increasingly important in various applications because of their demand for producing high output images from the low input images. Earlier for the image enhancements techniques like deblurring were performed to get the quality image. With the advancements in the Generative Adversarial Networks (GAN), the generating of high-quality image from the low-quality image has been outstanding. The models like SRGAN, ESRGAN [12]are the competitive models which make the Image-Resolution look good because of their performance on the images. But the architecture of the SRGAN which is a state-of-art model is complex and ESRGAN is built on the SRGAN, but by observing the results of the SRGAN the image quality looks good. We try to build a Super-Image Resolution by having the less complex architecture which is faster than SRGAN and the results aren’t compromising even after reducing the architecture complexity. We have built our base model based on the SRGAN by reducing the complexity in the architecture. In our final model we added another discriminator layer which enhances the sub parts of the images to improve the image quality. Our aim is to build an efficient model where the architecture of our model is less complex than SRGAN [14]and give as competitive results as SRGAN. Our results for the final model compared to our base model shows that there were significant improvements in the image quality. The code link for our project is here:https://github.com/faisalkhansk3283/ Computer_Vision_Extended_SRGA
Auto Detecting Cognitive Events Using Machine Learning on Pupillary Data
No full textThe pupillary response is a valuable indicator of cognitive workload, capturing fluctuations in attention and arousal governed by the autonomic nervous system. Cognitive events, defined as the initiation of mental processes, are closely linked to cognitive workload as they trigger cognitive responses. In this study, we detect cognitive events for the task-evoked pupillary response across four domains (vigilance, emotion processing, numerical reasoning, and short-term memory). The problem is framed as a binary classification. We train one generalized model and four task-specific models on 1-s pupil diameter and gaze position segments. Five models achieve MCC between 0.43 and 0.75. We report three key findings: (1) the generalized model reduces the specificity to enhance the sensitivity, illustrating the trade-off from specialization to generalization; (2) the permutation feature importance analyses show that both pupil dilation and gaze position contribute to model predictions, with task-specific models focusing on task-specific structure patterns to predict while the generalized model is using human cognitive responses; and (3) in an online simulation environment, models performance decreases by approximately 0.05 on MCC. The findings highlight the potential of machine learning applied to pupillary signals for rapid, individualized detection of cognitive events.We would like to express our gratitude to Phil Beach, Mario Mendoza, Hannah Erro, and Zoe Rathbun for their contributions to data generation and study coordination. We appreciate Steven Thurman for his helpful comments. We also acknowledge the Army Research Laboratory for sponsoring this dataset. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the US DEVCOM Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes not withstanding any copyright notation herein.https://www.nature.com/articles/s41598-025-16165-
Lightweight and Robust Key Agreement for Securing IIoT-Driven Flexible Manufacturing Systems
No full textThe ever-evolving Internet of Things (IoT) has ushered in a new era of intelligent manufacturing across multiple industries. However, the security and privacy of real-time data transmitted over the public channel of the industrial IoT (IIoT) remain formidable challenges. Existing lightweight protocols often omit one or more critical security features, such as anonymity and untraceability, and are susceptible to threats like desynchronization attacks. Additionally, they struggle to achieve an optimal balance between robust security and performance efficiency. To bridge these gaps, we introduce a new lightweight key agreement security scheme that guarantees secure access to the IIoT-enabled flexible manufacturing system (FMS). The strength of our scheme lies in its utilization of the authenticated encryption with associative data (AEAD) primitive, AEGIS, along with hash functions and physical unclonable functions, which secure the IIoT ecosystem. Additionally, our scheme offers flexibility in the form of the addition of new machines, password updates, and revocation in cases of theft or loss. A comprehensive security analysis demonstrates the efficacy of the proposed scheme in thwarting various attacks. The formal analysis, based on the Real-Or-Random (RoR) model, ensures session key indistinguishability, while the informal analysis highlights its resilience against known attacks. The comparative assessment demonstrate that the proposed scheme consistently outperforms the benchmark schemes across multiple dimensions, including security and functionality features, computational and communication overheads, and runtime efficiency. Specifically, the proposed scheme achieves peak performance enhancements of 77.55%, 44.73%, and 69.6% in computational overhead, runtime overhead, and communication overhead, respectively, underscoring its substantial performance advantages.https://ieeexplore.ieee.org/abstract/document/10856708
Open-Source Large Language Models in Radiology: A Review and Tutorial for Practical Research and Clinical Deployment
No full textIntegrating large language models (LLMs) into health care holds substantial potential to enhance clinical workflows and care delivery. However, LLMs also pose serious risks if integration is not thoughtfully executed, with complex challenges spanning accuracy, accessibility, privacy, and regulation. Proprietary commercial LLMs (eg, GPT-4 [OpenAI], Claude 3 Sonnet and Claude 3 Opus [Anthropic], Gemini [Google]) have received much attention from researchers in the medical domain, including radiology. Interestingly, open-source LLMs (eg, Llama 3 and LLaVA-Med) have received comparatively little attention. Yet, open-source LLMs hold several key advantages over proprietary LLMs for medical institutions, hospitals, and individual researchers. The wider adoption of open-source LLMs has been slower, perhaps in part due to the lack of familiarity, accessible computational infrastructure, and community-built tools to streamline their local implementation and customize them for specific use cases. Thus, this article provides a tutorial for the implementation of open-source LLMs in radiology, including examples of commonly used tools for text generation and techniques for troubleshooting issues with prompt engineering, retrieval-augmented generation, and fine-tuning. Implementation-ready code for each tool is provided at https://github.com/UM2ii/Open-Source-LLM-Tools-for-Radiology. In addition, this article compares the benefits and drawbacks of open-source and proprietary LLMs, discusses the differentiating characteristics of popular open-source LLMs, and highlights recent advancements that may affect their adoption.F.X.D. is supported in part by an Association of Academic Radiology Clinical Effectiveness in Radiology Research Academic Fellowship Award and a grant from the Johns Hopkins Mid-Atlantic Center for Cardiometabolic Health Equity, which is supported by the National Institute on Minority Health and Health Disparities (P50MD017348). The content is solely theresponsibility of the authors and does not necessarily represent the official views of the Mid-Atlantic Center for Cardiometabolic Health Equity or the National Institutes of Health. C.P.L.is supported in part by the Medical Imaging and Data Resource Center, which is funded by the National Institute of Biomedical Imaging and Bioengineering (75N92020D00021). H.H.is partially supported by the National Institute on Aging (U01 AG068057), National Institute of Biomedical Imaging and Bioengineering (R01 EB034116), National Institute of GeneralMedical Sciences (R01 GM148743, R01 GM141076), and National Science Foundation (IIS 2347592, 2347604, 2348159, 2348169, DBI 2405416, CCF 2348306, CNS 2347617).H.H. and F.X.D. are supported in part by the Montgomery County, Maryland, and University of Maryland Strategic Partnership (MPowering the State), a formal collaboration between theUniversity of Maryland, College Park, and the University of Maryland, Baltimorehttps://pubs.rsna.org/doi/full/10.1148/radiol.24107
Ethical Challenges in Intercultural Citizenship Education with 'Difficult Topics' in the World Language Classroom and Beyond
No full textThe purpose of this article is to examine the ethical challenges that arise in the world language classroom and beyond from using intercultural citizenship pedagogy. Intercultural citizenship is, in general, seen as a recent and positive development in intercultural language education for helping students engage with topics of social significance in the classroom. However, there are ethical challenges involved, for instance, related to the political or sensitive nature of such topics. We define and illustrate some of these ethical concerns and their implications for education by drawing on an intercultural citizenship project about COVID-19 carried out in two higher education contexts in 2020. The analysis of this example shows that these ethical concerns are unavoidable but can be minimised with an action research perspective and a combination of pedagogies of intercultural citizenship, discomfort, and the arts. We conclude with a discussion of the transferability of the example and its consequences for any language and intercultural communication teaching which deals with controversial and sensitive matters.https://www.mdpi.com/2076-0760/14/3/13
Recent Advances in Wearable Sweat Sensor Development
No full textWearable sweat sensors for detecting biochemical markers have emerged as a transformative research area, with the potential to revolutionize disease diagnosis and human health monitoring. Since 2016, a substantial body of pioneering and translational work on sweat biochemical sensors has been reported. This review aims to provide a comprehensive summary of the current state-of-the-art in the field, offering insights and perspectives on future developments. The focus is on wearable microfluidic platforms for sweat collection and delivery and the analytical chemistry applicable to wearable devices. Various microfluidic technologies, including those based on synthetic polymers, paper, textiles, and hydrogels, are discussed alongside diverse detection methods such as electrochemistry and colorimetry. Both the advantages and current limitations of these technologies are critically examined. The review concludes with our perspectives on the future of wearable sweat sensors, with the goal of inspiring new ideas, innovations, and technical advancements to further the development and practical application of these devices in promoting human health.This work was supported by the startup funds from University of Maryland Baltimore County and a Technology Catalyst Fund from the Alex Brown Center for Entrepreneurship, Maryland (Grant 5833710).https://onlinelibrary.wiley.com/doi/abs/10.1002/wnan.7000
Characterization of Papillomavirus in African Lions (Panthera leo): A Look at Botswana
No full textHuman papillomavirus (HPV), a group of viruses that can manifest as physical lesions and are capable of causing cancer, is a widely researched topic that has resulted in the identification of hundreds of lineages and sublineages that further the study of human genetics and carries medical
applications. Other papillomaviruses (PVs), including feline papillomavirus (FPV), are not the focus of PV studies. FPV, however, can be relevant to felids as a whole, specific species, and can increase general understanding of papillomaviruses. This study examines the characteristics of FPV in African lions (Panthera leo) by extracting and amplifying tissue and swab samples from Botswana, constructing a phylogenetic tree, and calculating distance values from the resulting sequences. An additional group of FPV samples from Tanzania were also sequenced and a phylogenetic tree was built using data from both locations using the Asiatic lion (Panthera leo persica) PlpPV-1 FPV sequence available in PaVE as a marker. With this
analysis, three additional types of papillomavirus in lions were identified and further compared with the FPV sequences of other felids. The results indicate that FPV in lions does deviate into distinct types despite geographic boundaries, suggesting that analysis of a greater sample pool would
provide more detailed information and patterns concerning types of FPV in lion populations.
Research performed in conjunction with the Departmental Honors projects of Katherine Stang and Riana Caldwell