Air Pollution Emissions 2008-2018 from Australian Coal Mining: Implications for Public and Occupational Health.

Occupational exposure limits for respirable coal dust are based on exposure during working hours, but coal miners may experience additional community-based exposures during nonworking hours. We analyzed Australia National Pollutant Inventory (NPI) data for the years 2008-2018 to estimate air pollutants (metals, nitrogen oxides, particulate matter ≤ 10 micrometers (PM10) and ≤2.5 micrometers (PM2.5)) originating from coal mines. PM10 levels from community-based air monitors in Queensland and New South Wales were also compared between mining and nonmining communities. Results indicated that tons of coal mined increased over the study period, and that levels of particulate matter, metals, and nitrogen oxides increased significantly over time as well. Coal mines accounted for 42.1% of national PM10 air emissions from NPI sites. PM2.5 from coal mines accounted for 19.5% of the national total, metals for 12.1%, and nitrogen oxides for 10.1%. Coal mining occurred in 57 different post codes; the 20 coal-mining post codes with the highest PM10 emissions were home to 160,037 people. Emissions of all studied pollutants were significantly higher from coal mining sites than from other types of NPI sites. Results from community-based air monitoring stations indicated significantly higher population PM10 exposure in coal mining communities than in nonmining communities. The health of the public at large is impacted by coal mining, but to the extent that miners also live near coal mining operations, their total exposure is underestimated by consideration of exposure only during working hours

Depth profiling of Si nanocrystals in Si-implanted SiO2 films by spectroscopic ellipsometry

An approach to determine depth profiles of silicon nanocrystals in silica films was developed. In the spectral fittings, the dielectric function of silicon nanocrystal was calculated based on two different models for the band-gap expansion due to the nanocrystal size reduction. The fitting yielded the nanocrystal depth profile and the nanocrystal size.published_or_final_versio

Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement.

Three-phase induction motors (TIMs) are widely used for machines in industrial operations. As an accurate and robust controller, fuzzy logic controller (FLC) is crucial in designing TIMs control systems. The performance of FLC highly depends on the membership function (MF) variables, which are evaluated by heuristic approaches, leading to a high processing time. To address these issues, optimisation algorithms for TIMs have received increasing interest among researchers and industrialists. Here, we present an advanced and efficient quantum-inspired lightning search algorithm (QLSA) to avoid exhaustive conventional heuristic procedures when obtaining MFs. The accuracy of the QLSA based FLC (QLSAF) speed control is superior to other controllers in terms of transient response, damping capability and minimisation of statistical errors under diverse speeds and loads. The performance of the proposed QLSAF speed controller is validated through experiments. Test results under different conditions show consistent speed responses and stator currents with the simulation results

Aerosol Particle Transport and Deposition in Upper and Lower Airways of Infant, Child and Adult Human Lungs

Understanding transportation and deposition (TD) of aerosol particles in the human respiratory system can help clinical treatment of lung diseases using medicines. The lung airway diameters and the breathing capacity of human lungs normally increase with age until the age of 30. Many studies have analyzed the particle TD in the human lung airways. However, the knowledge of the nanoparticle TD in airways of infants and children with varying inhalation flow rates is still limited in the literature. This study investigates nanoparticle (5 nm ≤ dp ≤ 500 nm) TD in the lungs of infants, children, and adults. The inhalation air flow rates corresponding to three ages are considered as Qin=3.22 L/min (infant), 8.09 L/min (Child), and Qin=14 L/min (adult). It is found that less particles are deposited in upper lung airways (G0–G3) than in lower airways (G12–G15) in the lungs of all the three age groups. The results suggest that the particle deposition efficiency in lung airways increases with the decrease of particle size due to the Brownian diffusion mechanism. About 3% of 500 nm particles are deposited in airways G12–G15 for the three age groups. As the particle size is decreased to 5 nm, the deposition rate in G12–G15 is increased to over 95%. The present findings can help medical therapy by individually simulating the distribution of drug-aerosol for the patient-specific lung.</jats:p

Dissociation Between the Growing Opioid Demands and Drug Policy Directions Among the U.S. Older Adults with Degenerative Joint Diseases

We aim to examine temporal trends of orthopedic operations and opioid-related hospital stays among seniors in the nation and states of Oregon and Washington where marijuana legalization was accepted earlier than any others. As aging society advances in the United States (U.S.), orthopedic operations and opioid-related hospital stays among seniors increase in the nation. A serial cross-sectional cohort study using the healthcare cost and utilization project fast stats from 2006 through 2015 measured annual rate per 100,000 populations of orthopedic operations by age groups (45–64 vs 65 and older) as well as annual rate per 100,000 populations of opioid-related hospital stays among 65 and older in the nation, Oregon and Washington states from 2008 through 2017. Orthopedic operations (knee arthroplasty, total or partial hip replacement, spinal fusion or laminectomy) and opioid-related hospital stays were measured. The compound annual growth rate (CAGR) was used to quantify temporal trends of orthopedic operations by age groups as well as opioid-related hospital stays and was tested by Rao–Scott correction of χ2 for categorical variables. The CAGR (4.06%) of orthopedic operations among age 65 and older increased (P...) (See full abstract in article

Cytotoxicity Effects of Different Surfactant Molecules Conjugated to Carbon Nanotubes on Human Astrocytoma Cells

Phase contrast and epifluorescence microscopy were utilized to monitor morphological changes in human astrocytoma cells during a time-course exposure to single-walled carbon nanotube (SWCNT) conjugates with different surfactants and to investigate sub-cellular distribution of the nanotube conjugates, respectively. Experimental results demonstrate that cytotoxicity of the nanotube/surfactant conjugates is related to the toxicity of surfactant molecules attached on the nanotube surfaces. Both sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS) are toxic to cells. Exposure to CNT/SDS conjugates (0.5 mg/mL) for less than 5 min caused changes in cell morphology resulting in a distinctly spherical shape compared to untreated cells. In contrast, sodium cholate (SC) and CNT/SC did not affect cell morphology, proliferation, or growth. These data indicate that SC is an environmentally friendly surfactant for the purification and dispersion of SWCNTs. Epifluorescence microscopy analysis of CNT/DNA conjugates revealed distribution in the cytoplasm of cells and did not show adverse effects on cell morphology, proliferation, or viability during a 72-h incubation. These observations suggest that the SWCNTs could be used as non-viral vectors for diagnostic and therapeutic molecules across the blood–brain barrier to the brain and the central nervous system

Human surfactant protein D alters oxidative stress and HMGA1 expression to induce p53 apoptotic pathway in eosinophil leukemic cell line

This article is made available through the Brunel Open Access Publishing Fund. Copyright: © 2013 Mahajan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Surfactant protein D (SP-D), an innate immune molecule, has an indispensable role in host defense and regulation of inflammation. Immune related functions regulated by SP-D include agglutination of pathogens, phagocytosis, oxidative burst, antigen presentation, T lymphocyte proliferation, cytokine secretion, induction of apoptosis and clearance of apoptotic cells. The present study unravels a novel ability of SP-D to reduce the viability of leukemic cells (eosinophilic leukemic cell line, AML14.3D10; acute myeloid leukemia cell line, THP-1; acute lymphoid leukemia cell lines, Jurkat, Raji; and human breast epithelial cell line, MCF-7), and explains the underlying mechanisms. SP-D and a recombinant fragment of human SP-D (rhSP-D) induced G2/M phase cell cycle arrest, and dose and timedependent apoptosis in the AML14.3D10 eosinophilic leukemia cell line. Levels of various apoptotic markers viz. activated p53, cleaved caspase-9 and PARP, along with G2/M checkpoints (p21 and Tyr15 phosphorylation of cdc2) showed significant increase in these cells. We further attempted to elucidate the underlying mechanisms of rhSP-D induced apoptosis using proteomic analysis. This approach identified large scale molecular changes initiated by SPD in a human cell for the first time. Among others, the proteomics analysis highlighted a decreased expression of survival related proteins such as HMGA1, overexpression of proteins to protect the cells from oxidative burst, while a drastic decrease in mitochondrial antioxidant defense system. rhSP-D mediated enhanced oxidative burst in AML14.3D10 cells was confirmed, while antioxidant, N-acetyl-L-cysteine, abrogated the rhSP-D induced apoptosis. The rhSP-D mediated reduced viability was specific to the cancer cell lines and viability of human PBMCs from healthy controls was not affected. The study suggests involvement of SP-D in host’s immunosurveillance and therapeutic potential of rhSP-D in the eosinophilic leukemia and cancers of other origins.Department of Biotechnology, Indi

Split-based computation of majority-rule supertrees

<p>Abstract</p> <p>Background</p> <p>Supertree methods combine overlapping input trees into a larger supertree. Here, I consider split-based supertree methods that first extract the split information of the input trees and subsequently combine this split information into a phylogeny. Well known split-based supertree methods are matrix representation with parsimony and matrix representation with compatibility. Combining input trees on the same taxon set, as in the consensus setting, is a well-studied task and it is thus desirable to generalize consensus methods to supertree methods.</p> <p>Results</p> <p>Here, three variants of majority-rule (MR) supertrees that generalize majority-rule consensus trees are investigated. I provide simple formulas for computing the respective score for bifurcating input- and supertrees. These score computations, together with a heuristic tree search minmizing the scores, were implemented in the python program PluMiST (Plus- and Minus SuperTrees) available from <url>http://www.cibiv.at/software/plumist</url>. The different MR methods were tested by simulation and on real data sets. The search heuristic was successful in combining compatible input trees. When combining incompatible input trees, especially one variant, MR(-) supertrees, performed well.</p> <p>Conclusions</p> <p>The presented framework allows for an efficient score computation of three majority-rule supertree variants and input trees. I combined the score computation with a heuristic search over the supertree space. The implementation was tested by simulation and on real data sets and showed promising results. Especially the MR(-) variant seems to be a reasonable score for supertree reconstruction. Generalizing these computations to multifurcating trees is an open problem, which may be tackled using this framework.</p

Resource-efficient high-dimensional subspace teleportation with a quantum autoencoder.

Quantum autoencoders serve as efficient means for quantum data compression. Here, we propose and demonstrate their use to reduce resource costs for quantum teleportation of subspaces in high-dimensional systems. We use a quantum autoencoder in a compress-teleport-decompress manner and report the first demonstration with qutrits using an integrated photonic platform for future scalability. The key strategy is to compress the dimensionality of input states by erasing redundant information and recover the initial states after chip-to-chip teleportation. Unsupervised machine learning is applied to train the on-chip autoencoder, enabling the compression and teleportation of any state from a high-dimensional subspace. Unknown states are decompressed at a high fidelity (~0.971), obtaining a total teleportation fidelity of ~0.894. Subspace encodings hold great potential as they support enhanced noise robustness and increased coherence. Laying the groundwork for machine learning techniques in quantum systems, our scheme opens previously unidentified paths toward high-dimensional quantum computing and networking