CT-guided fine-needle localization of ground-glass nodules in re-aerated lung specimens: localization of solitary small nodules or multiple nodules within the same lobe

PURPOSEWe aimed to explore the value of localizing small ground-glass nodules (GGNs; <10 mm) or multiple GGNs within the same lobe in re-aerated lung specimens using CT-guided fine-needle localization.METHODSThirty-five lung specimens containing single small GGNs (<10 mm) and eight specimens containing two or more GGNs in the same lobe were re-aerated with an inflatable aerator. All lesions were localized via CT-guided fine-needle localization following re-aeration. The specimens were then sent for pathologic sampling and qualitative diagnosis.RESULTSAll 69 nodules from 43 cases were successfully localized using CT-guided fine-needle localization following re-aeration.CONCLUSIONSCT-guided fine-needle localization of lesions in surgical specimens under constant, moderate mechanical aeration allows for the rapid and accurate localization of lesions and helps avoid damage from preoperative localization

Comparative analysis of physiological variations and genetic architecture for cold stress response in soybean germplasm

Soybean (Glycine max L.) is susceptible to low temperatures. Increasing lines of evidence indicate that abiotic stress-responsive genes are involved in plant low-temperature stress response. However, the involvement of photosynthesis, antioxidants and metabolites genes in low temperature response is largely unexplored in Soybean. In the current study, a genetic panel of diverse soybean varieties was analyzed for photosynthesis, chlorophyll fluorescence and leaf injury parameters under cold stress and control conditions. This helps us to identify cold tolerant (V100) and cold sensitive (V45) varieties. The V100 variety outperformed for antioxidant enzymes activities and relative expression of photosynthesis (Glyma.08G204800.1, Glyma.12G232000.1), GmSOD (GmSOD01, GmSOD08), GmPOD (GmPOD29, GmPOD47), trehalose (GmTPS01, GmTPS13) and cold marker genes (DREB1E, DREB1D, SCOF1) than V45 under cold stress. Upon cold stress, the V100 variety showed reduced accumulation of H2O2 and MDA levels and subsequently showed lower leaf injury compared to V45. Together, our results uncovered new avenues for identifying cold tolerant soybean varieties from a large panel. Additionally, we identified the role of antioxidants, osmo-protectants and their posttranscriptional regulators miRNAs such as miR319, miR394, miR397, and miR398 in Soybean cold stress tolerance

Modulation of host cell processes by T3SS effectors

Two of the enteric Escherichia coli pathotypes-enteropathogenic E. coli (EPEC) and enterohaemorrhagic E. coli (EHEC)-have a conserved type 3 secretion system which is essential for virulence. The T3SS is used to translocate between 25 and 50 bacterial proteins directly into the host cytosol where they manipulate a variety of host cell processes to establish a successful infection. In this chapter, we discuss effectors from EPEC/EHEC in the context of the host proteins and processes that they target-the actin cytoskeleton, small guanosine triphosphatases and innate immune signalling pathways that regulate inflammation and cell death. Many of these translocated proteins have been extensively characterised, which has helped obtain insights into the mechanisms of pathogenesis of these bacteria and also understand the host pathways they target in more detail. With increasing knowledge of the positive and negative regulation of host signalling pathways by different effectors, a future challenge is to investigate how the specific effector repertoire of each strain cooperates over the course of an infection

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Emission of particulate matter during the combustion of bio-oil and its fractions under air and oxyfuel conditions

© 2016.The study reports the emission of inorganic particulate matter (PM) with aerodynamic diameters &lt;10µm (PM10) during the complete combustion of bio-oil in a drop-tube-furnace (DTF) system at 1400°C under air and two oxyfuel conditions (i.e., 21%O2/79%CO2 and 30%O2/70%CO2, by volume). Three bio-oil samples were studied, i.e., a raw bio-oil, a filtrated bio-oil (prepared from the raw bio-oil after fine char particles were removed via filtration), and the water-insoluble fraction of the filtrated bio-oil (blended with ethanol). The total inorganic species of the raw bio-oil are distributed dominantly (74.7%) in the water-soluble fraction but minorly in the water-insoluble fraction (10.4%) and suspended fine char particles (14.9%). The results from the combustion experiments show that the PSDs of PM10 from the complete combustion of the raw and filtrated bio-oils have a bimodal distribution, with a fine mode at ~0.03µm and a coarse mode at ~2.0µm. The water-insoluble fraction and the fine char particles suspended in the raw bio-oil have insignificant contributions to PM10 emission during the combustion of the raw bio-oil. It is the water-soluble fraction that plays a key role in the emission of PM10 during the combustion of the raw bio-oil. The data also show that PM10 emission during the complete combustion of bio-oil is insensitive to combustion atmosphere (air or oxyfuel) because complete bio-oil combustion is dominated by gaseous-phase reactions and the contribution of solid combustion is minimal. However, the excessive CO2 under oxyfuel conditions leads to more Fe being partitioned into PM0.1-1

Unconventional locomotion of liquid metal droplets driven by magnetic fields

The locomotion of liquid metal droplets enables enormous potential for realizing various applications in microelectromechanical systems (MEMSs), biomimetics, and microfluidics. However, current techniques for actuating liquid metal droplets are either associated with intense electrochemical reactions or require modification of their physical properties by coating/mixing them with other materials. These methods either generate gas bubbles or compromise the stability and liquidity of the liquid metal. Here, we introduce an innovative method for controlling the locomotion of liquid metal droplets using Lorentz force induced by magnetic fields. Remarkably, utilizing a magnetic field to induce actuation avoids the generation of gas bubbles in comparison to the method of forming a surface tension gradient on the liquid metal using electrochemistry. In addition, the use of Lorentz force avoids the need of mixing liquid metals with ferromagnetic materials, which may compromise the liquidity of liquid metals. Most importantly, we discover that the existence of a slip layer for liquid metal droplets distinguishes their actuation behaviors from solid metallic spheres. We investigate the parameters affecting the actuation behavior of liquid metal droplets and explore the science behind its operation. We further conducted a series of proof-of-concept experiments to verify the controllability of our method for actuating liquid metal droplets. As such, we believe that the presented technique represents a significant advance in comparison to reported actuation methods for liquid metals, and possesses the potential to be readily adapted by other systems to advance the fields of MEMS actuation and soft robotics

DDSM: Design-Oriented Dual-Scale Shape-Material Model for Lattice Material Components

This paper proposes a new CAD model for the design of lattice material components. The CAD model better captures the user&rsquo;s design intent and provides a dual-scale framework to represent the geometry and material distribution. Conventional CAD model formats based on B-Rep generate millions of data files, which also makes design intent and material information missing. In the present work, a new shape-material model for lattice material components is proposed. At the macroscopic scale, a compact face-based non-manifold topological data structure is proposed to express the lattice shape-material information without ambiguity. At the microscopic scale, implicit function is adopted for the representation of lattice material components. Numerical experiments verify that the proposed CAD model provides a powerful support for design intent with minor space costs. Meanwhile, the representation method supports solid modeling queries of geometric and material information on each scale

Communication Bandwidth Prediction Technology for Smart Power Distribution Business in Smart Parks

Accurate prediction of power business communication bandwidth is the premise for the effectiveness of power communication planning and the fundamental guarantee for regular operation of power businesses. To solve the problem of scientifically and reasonably allocating bandwidth resources in smart parks, communication bandwidth prediction technology of intelligent power distribution service for smart parks is proposed in this paper. First, the characteristics of mixed service data arrival rate of power distribution and communication mixed services in smart parks were analyzed. Poisson process and interrupted Poisson process were used to simulate periodic and sudden business of smart parks to realize accurate simulation of the business arrival process. Then, a service arrival rate model based on the Markov modulation Poisson process was constructed. An active buffer management mechanism was used to dynamically discard data packets according to the set threshold and achieve accurate simulation of the packet loss rate during the arrival of smart park business. At the same time, considering the communication service quality index and bandwidth resource utilization, a business communication bandwidth prediction model of smart parks was established to improve the accuracy of business bandwidth prediction. Finally, a smart power distribution room in a smart park was used as an application scenario to quantitatively analyze the relationship between the communication service quality and bandwidth configuration. According to the predicted bandwidth, the reliability and effectiveness of the proposed method were verified by comparison with the elastic coefficient method

Communication Bandwidth Prediction Technology for Smart Power Distribution Business in Smart Parks

Accurate prediction of power business communication bandwidth is the premise for the effectiveness of power communication planning and the fundamental guarantee for regular operation of power businesses. To solve the problem of scientifically and reasonably allocating bandwidth resources in smart parks, communication bandwidth prediction technology of intelligent power distribution service for smart parks is proposed in this paper. First, the characteristics of mixed service data arrival rate of power distribution and communication mixed services in smart parks were analyzed. Poisson process and interrupted Poisson process were used to simulate periodic and sudden business of smart parks to realize accurate simulation of the business arrival process. Then, a service arrival rate model based on the Markov modulation Poisson process was constructed. An active buffer management mechanism was used to dynamically discard data packets according to the set threshold and achieve accurate simulation of the packet loss rate during the arrival of smart park business. At the same time, considering the communication service quality index and bandwidth resource utilization, a business communication bandwidth prediction model of smart parks was established to improve the accuracy of business bandwidth prediction. Finally, a smart power distribution room in a smart park was used as an application scenario to quantitatively analyze the relationship between the communication service quality and bandwidth configuration. According to the predicted bandwidth, the reliability and effectiveness of the proposed method were verified by comparison with the elastic coefficient method

Endmember extraction from hyperspectral imagery based on QR factorisation using givens rotations

Hyperspectral images are mixtures of spectra of materials in a scene. Accurate analysis of hyperspectral image requires spectral unmixing. The result of spectral unmixing is the material spectral signatures and their corresponding fractions. The materials are called endmembers. Endmember extraction equals to acquire spectral signatures of the materials. In this study, the authors propose a new hyperspectral endmember extraction algorithm for hyperspectral image based on QR factorisation using Givens rotations (EEGR). Evaluation of the algorithm is demonstrated by comparing its performance with two popular endmember extraction methods, which are vertex component analysis (VCA) and maximum volume by householder transformation (MVHT). Both simulated mixtures and real hyperspectral image are applied to the three algorithms, and the quantitative analysis of them is presented. EEGR exhibits better performance than VCA and MVHT. Moreover, EEGR algorithm is convenient to implement parallel computing for real-time applications based on the hardware features of Givens rotations