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A comparison of the analysis of respirable crystalline silica direct-on-filter methods using X-ray diffraction (XRD) and Fourier transform infrared (FT-IR) spectroscopy was undertaken using 253 real workplace air samples from road construction and tunnelling, coal mining, and kitchen benchtop manufacturing in Australia. Using pure α-quartz standards, XRD and FT-IR direct-on-filter analyses produced identical test results, however, the real workplace samples showed a clear discrepancy between FT-IR and XRD results with on average a 9% positive bias of the FT-IR results. The cause of the positive bias was due to matrix interferences which was confirmed by using synthetic mixture air samples. Approximately a third of the data by direct-on-filter method using FT-IR was assessed to be invalid based on the peak height ratio criterion due to excessive interferences and weight overload limitations. The XRD method showed better results due to less interference from the common matrices. XRD could handle up to twice the sample loading and at higher loadings up to 7 mg when a correction was applied. It was also able to achieve a lower limit of detection of 2 µg filter−1 when a slower scan condition was utilized. [ABSTRACT FROM AUTHOR]

Objectives: There are obvious seasonal variations in the GPS height time series, which affect the improvement of precision and can be corrected by both mathematical modelling and geophysical mechanisms. Compared to least square fitting, singular spectrum analysis (SSA) can extract random seasonal signals effectively through signal reconstruction, which is unaffected by the assumed sinusoidal waves. According to the elastic loading theory, the gravity recovery and climate experiment (GRACE) can be used to calculate the vertical surface displacement caused by changes in terrestrial water storage. Methods: This paper mainly studies the feasibility of correcting the seasonal variations in GPS heights using SSA and GRACE inversion results. The height time series of 27 GPS stations in Australia with a time span of from 5 to 10 years were chosen and combined with GRACE simultaneous inversions. Results: Because the spatial resolutions of GRACE are coarse and the loading displacement is much more sensitive to near‑field mass changes than far‑field ones, the amplitudes of GRACE ‑inferred hydrological loading deformations are significantly smaller than GPS. The weighted root mean square (WRMS) are reduced at 22 stations after GRACE ‑inferred displacement corrections, and the correlation coefficients between deformations estimated by GPS and GRACE range from 0.12 to 0.78 with a mean value of 0.43, indicating that GPS and GRACE results have good consistency and correlation. SSA is used to extract the annual signals of vertical displacements derived from GPS and GRACE, and contribution rates of singular spectral variance of annual signals are 21.60% and 34.48%, respectively, expressing that annual signals are the main components of GRACE inferred results. Geographical climatic conditions have a significant impact on the consistency of annual signals derived from GPS and GRACE. Compared with the arid areas in central and western Australia, the amplitude and phase of annual signals derived from GPS and GRACE are more consistent in the northern region with seasonal rainfall. Furthermore, cross wavelet transform (XWT) finds that the vertical displacement series derived from GPS and GRACE of each station have a significant resonance period of one year. The circular average phase angles of GPS/GRACE at the period closet to 1 cycle per year (cpy) outside the cone of influence range from − 74.03° to 67.23° . The mean XWT ‑ based semblances range from 0.28 to 0.99 with an average value of 0.79, showing that there is a significant positive correlation between the annual variations derived from GPS and GRACE. Conclusions: Overall, GRACE‑inferred deformations can explain the annual variations of GPS‑derived displacements, particularly in areas with high hydrological loading. It is possible to correct the annual signals of GPS heights by GRACE inversions, but the effect is not as good as the SSA‑filtered annual signals. [ABSTRACT FROM AUTHOR]

Thirty two-year observations (1990–2022) of water level from a total of 14 high-quality acoustic tide stations around the coast of Australia deployed for the Australian Baseline Sea Level Monitoring Project were analyzed. The following three approaches were used: Fourier Transform (FT), Empirical Mode Decomposition (EMD), and Singular Spectrum Analysis (SSA). The water level anomaly was observed to have predominant annual variations with a period of about 12 months based on the Fourier transform. The intrinsic components of stations were extracted in the EMD analysis and the mean period of each of the components was calculated using the zero down crossing method. A regular association was observed between the order of modes and the mean period such that the periods increase by a factor of two on successive modes. The third method used for anomaly analysis was SSA. The number of the obtained components in this method was less than in the EMD. Moreover, the order observed for the components' period in the EMD was not seen in this method. Spectral analysis of Autocorrelation function (ACF) has demonstrated that peak frequencies are almost the same with anomaly spectra so the dominant modes in anomalies are also present in the ACF. • More than 30-year sea level data around the Australian coast have been analyzed. • Fourier Transform, Empirical Mode Decomposition, and Singular Spectrum Analysis have been used. • A predominant annual variation with a period of about 12 months was observed based on the Fourier transform. ACF analysis showed that: ✓ The periodic and regular signals have larger ACF with low rate decreasing amplitude. ✓ Irregular signal has a smaller ACF and its amplitude decreases more sever. ✓ In general, the more regular the time series, the more symmetrical its ACF. ✓ Spectral analysis of anomalies and ACF has demonstrated that peak frequencies are almost the same in both spectra. [ABSTRACT FROM AUTHOR]

Phytochemical investigation of the leaves of the Australian rainforest tree Cryptocarya mackinnoniana led to the discovery of three new oxygenated phenyl alkyl acids, cryptocaryoic acids A – C and two known compounds, cryptocaryone and 2′,6′-dihydroxy-4′-methoxychalcone. The structures of all the compounds were determined by detailed spectroscopic analysis. Mosher's analysis was used for absolute stereochemistry determination at C-11, while the remaining stereochemistry determination of the one remaining stereocenter C-13 was based on NOESY correlations. All compounds isolated were also evaluated for their anti-inflammatory properties by assessing their inhibitory effects on LPS and interferon-γ induced nitric oxide (NO) production and TNF- α release in RAW 264.7 macrophages. The new cryptocaryoic acids exhibited weak to moderate anti-inflammatory activity (NO inhibition) ranging from (18.4–56 μM). [Display omitted] • Three new phenyl alkyl acids, cryptocaryoic acids A – C, were isolated from the leaves of Cryptocarya mackinnoniana • Cryptocaryoic acids exhibited weak to moderate anti-inflammatory activity • Cryptocaryoic acids are the first in the series of molecules bearing the phenyl oxy-alkyl acid from C.mackinnoniana [ABSTRACT FROM AUTHOR]