Book Review: Radiology in Global Health

This book review examines Mollura and Lungren’s (eds.) Radiology in Global Health: Strategies, Implementation, and Applications (2014). The contributors have attempted to investigate root causes for radiological service-related disparity that exists between prosperous economies and low- and middle-income countries. The book is clearly geared towards manufacturing consent among stakeholders through research-based evidence to amplify the role of radiology in global healthcare through initiation, implementation, amelioration, and developing sustainable solutions for rollout of essential diagnostic/therapeutic radiology services at population levels. This includes reducing access gaps for radiology/imaging services within industrialized countries as well

Recent advances in carbon dioxide geological storage, experimental procedures, influencing parameters, and future outlook

The oxidation of fossil fuels produces billions of tons of anthropogenic carbon dioxide (CO2) emissions from stationary and nonstationary sources per annum, contributing to global warming. The natural carbon cycle consumes a portion of CO2 emissions from the atmosphere. In contrast, substantial CO2 emissions accumulate, making it the largest contributor to greenhouse gas emissions and causing a rise in the planet\u27s temperature. The Earth\u27s temperature was estimated to be 1 °C higher in 2017 compared to the mid-twentieth century. A solution to this problem is CO2 storage in underground formations, abundant throughout the world. Millions of tons of CO2 are stored underground into geological formations annually, including deep saline aquifers. However, these geological formations have minute concentrations of organic material, significantly influencing the CO2 containment security, fluid dynamics, and storage potential. Examining the wetting characteristics and influencing parameters of geological formations is pertinent to understanding the supercritical CO2 behavior in rock/brine systems. Wettability is an important parameter governing the ability of injected CO2 to displace formation water and determine the containment security and storage capacity. Previously, many studies have provided comprehensive overviews of CO2-wettability depending on various factors, such as pressure, temperature, salinity, formation type, surfactants, and chemicals. However, mineral surfaces in these wettability studies are chemically cleaned, and natural geological storage conditions are anoxic (containing organic molecules) where reductive conditions ensue. A severe gap exists in the literature to comprehend the effects of organic material for determining the CO2 storage capacities and how this effect can be reversed using nanomaterial for increased CO2 storage potential. Therefore, we conducted a thorough literature review to comprehend the recent advances in rock/CO2/brine and rock/oil/brine systems containing organic material in different geo-storage formations. We also present recent advances in anoxic rock/CO2/brine and rock/oil/brine systems that have employed nanomaterial for wettability reversal to be more water-wet. This comprehensive review is divided into four parts: 1) reviewing CO2 emissions and geological systems, 2) recent advances in direct quantitative experimental procedures in anoxic rock/CO2/brine systems and effects of organic contaminations on experimental methodology and their controls, 3) effects of organics and nanomaterial in rock/CO2/brine and rock/oil/brine systems, and 4) the future outlook of this study

G-QoSM: Grid Service Discovery Using QoS Properties

We extend the service abstraction in the Open Grid Services Architecture citeogsa for Quality of Service (QoS) properties. The realization of QoS often requires mechanisms such as advance or on-demand reservation of resources, varying in type and implementation, and independently controlled and monitored. Foster et al. propose the GARA citeFostKessl99 architecture. The GARA library provides a restricted representation scheme for encoding resource properties and the associated monitoring of Service Level Agreements (SLAs). Our focus is on the application layer, whereby a given service may indicate the QoS properties it can offer, or where a service may search for other services based on particular QoS properties

Meta-learning with implicit gradients in a few-shot setting for medical image segmentation

Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Therefore, a more general application of any trained model is quite limited for medical imaging for clinical practice. Using separately trained models for each unique lesion category or a unique patient population will require sufficiently large curated datasets, which is not practical to use in a real-world clinical set-up. Few-shot learning approaches can not only minimize the need for an enormous number of reliable ground truth labels that are labour-intensive and expensive, but can also be used to model on a dataset coming from a new population. To this end, we propose to exploit an optimization-based implicit model agnostic meta-learning (iMAML) algorithm under few-shot settings for medical image segmentation. Our approach can leverage the learned weights from diverse but small training samples to perform analysis on unseen datasets with high accuracy. We show that, unlike classical few-shot learning approaches, our method improves generalization capability. To our knowledge, this is the first work that exploits iMAML for medical image segmentation and explores the strength of the model on scenarios such as meta-training on unique and mixed instances of lesion datasets. Our quantitative results on publicly available skin and polyp datasets show that the proposed method outperforms the naive supervised baseline model and two recent few-shot segmentation approaches by large margins. In addition, our iMAML approach shows an improvement of 2%–4% in dice score compared to its counterpart MAML for most experiments