Shallow Cumulus Cloud Fields Are Optically Thicker When They Are More Clustered

Shallow trade cumuli over subtropical oceans are a persistent source of uncertainty in climate projections. Mesoscale organization of trade cumulus clouds has been shown to influence their cloud radiative effect (CRE) through cloud cover. We investigate whether organization can explain CRE variability independently of cloud cover variability. By analyzing satellite observations and high-resolution simulations, we show that increased clustering leads to geometrically thicker clouds with larger domain-averaged liquid water paths, smaller cloud droplets, and consequently, larger cloud optical depths. The relationships between these variables are shaped by the mixture of deep cloud cores and shallower interstitial clouds or anvils that characterize cloud organization. Eliminating cloud cover effects, more clustered clouds reflect up to 20 W/m$^2$ more instantaneous shortwave radiation back to space

Comparison between the Statistical cues in BSS techniques and Binaural cues in CASA approaches for reverberant speech separation

Reverberant speech source separation has been of great interest for over a decade, leading to two major approaches. One of them is based on statistical properties of the signals and mixing process known as blind source separation (BSS). The other approach named as computational auditory scene analysis (CASA) is inspired by human auditory system and exploits monaural and binaural cues. In this paper these two approaches are studied and compared in more depth

Evaluations of some physical properties for oil palm as alternative biomass resources

The objective of this study was to investigate the moisture content (MC), density, and amount of extractives along the height of a 32-year-old oil palm stem. The extractives were removed following TAPPI standards T-207 and T-280 for water solubility and acetone extractives. The results showed that the MC of the palm stem increased from the outer towards the inner section, while the density decreased. Along the tree height, the MC was found to increase from the bottom to the middle part, but slightly decreased towards the top. An inverse trend was obtained for the density distribution along the tree height. The results of the extractive separation showed that the middle and center sections of the oil palm stem contained the highest amount of extractives irrespective of the types of solvent. The highest amount of extractives was obtained from hot water extraction, followed by cold water and acetone extractions. The lowest amount of extractives was located at the bottom outer section of the oil palm stem which ranging from 2.0 to 9.2%, whereas the middle and center sections contained a greater amount of extractives ranged from 4.6 to 32.8% regardless of the type of solvent used

Study on the longitudinal permeability of oil palm wood

In this research, variations in longitudinal permeability of oil palm (Elaeis guineensis Jacq) wood were investigated. Panels were prepared from bark to pith with the study carried out on 3 parts of the transverse surface: outer, middle, and inner. Microscopic observations were done to determine the anatomical properties to establish its theoretical permeability using Poiseuille’s equation. Results showed that the middle part of the transverse surface of oil palm wood had the highest theoretical, water, and gas permeability values in the longitudinal direction followed by the inner and outer parts. A decrease in the length of samples resulted in an increase in the permeability of the samples. For all parts, theoretical permeability values were the highest followed by water and gas permeability Lower gas permeability values in comparison to water permeability indicates that oil palm wood is prone to drying defects and is more difficult to treat with chemicals after drying

Effects of COVID-19 prevention procedures on other common infections: a systematic review

Introduction: Since the outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) began, necessary measures to prevent virus transmission and reduce mortality have been implemented, including mandatory public use of masks, regular hand-sanitizing and hand-washing, social distancing, avoidance of crowds, remote work, and cancellation of public events. During and after the introduction of COVID-19 lockout, we performed a systematic review of available published literature to investigate the incidence of seasonal influenza and other respiratory viral infections. Methods: PubMed, Embase, Web of Science, Scopus, Science Direct, Google Scholar, Research Gate, and the World Health Organization databases and websites were systematically searched for original studies concerning the impact of COVID-19 prevention means and measures on other common respiratory infectious diseases during the pandemic published by March 2021. Results: The findings showed that the adherence to health protocols to prevent COVID-19 could help to reduce the incidence of other infectious diseases such as influenza, pneumonia, and Mycobacterium tuberculosis. Conclusion: The implemented prevention measures and protocols might have reduced the incidence of influenza and some other common respiratory infections. However, controversies exist on this matter and future large population-based studies might provide further information to address these controversies. © 2021, The Author(s)

Spatial and coherence cues based time-frequency masking for binaural reverberant speech separation

Most of the binaural source separation algorithms only consider the dissimilarities between the recorded mixtures such as interaural phase and level differences (IPD, ILD) to classify and assign the time-frequency (T-F) regions of the mixture spectrograms to each source. However, in this paper we show that the coherence between the left and right recordings can provide extra information to label the T-F units from the sources. This also reduces the effect of reverberation which contains random reflections from different directions showing low correlation between the sensors. Our algorithm assigns the T-F regions into original sources based on weighted combination of IPD, ILD, the observation vectors models and the estimated interaural coherence (IC) between the left and right recordings. The binaural room impulse responses measured in four rooms with various acoustic conditions have been used to evaluate the performance of the proposed method which shows an improvement of more than 1:4 dB in signal-to-distortion ratio (SDR) in room D with T60 = 0:89 s over the state-of-the-art algorithms

Separation of underdetermined reverberant speech mixtures by monaural, binaural and statistical cue combination

Underdetermined reverberant speech separation is a challenging problem in source sep- aration that has received considerable attention in both computational auditory scene analysis (CASA) and blind source separation (BSS). Recent studies suggest that, in general, the performance of frequency domain BSS methods suffer from the permuta- tion problem across frequencies which degrades in high reverberation, meanwhile, CASA methods perform less effectively for closely spaced sources. This paper presents a method to address these limitations, based on the combination of monaural, binaural and BSS cues for the automatic classification of time-frequency (T-F) units of the speech mixture spectrogram. By modeling the interaural phase difference, the interaural level difference and frequency-bin mixing vectors, we integrate the coherence information for each source within a probabilistic framework. The Expectation-Maximization (EM) algorithm is then used iteratively to refine the soft assignment of TF regions to sources and re-estimate their model parameters. It is observed that the reliability of the cues affects the accu- racy of the estimates and varies with respect to cue type and frequency. As such, the contribution of each cue to the assignment decision is adjusted by weighting the log- likelihoods of the cues empirically, which significantly improves the performance. Results are reported for binaural speech mixtures in five rooms covering a range of reverberation times and direct-to-reverberant ratios. The proposed method compares favorably with state-of-the-art baseline algorithms by Mandel et al. and Sawada et al., in terms of signal- to-distortion ratio (SDR) of the separated source signals. The paper also investigates the effect of introducing spectral cues for integration within the same framework. Analysis of the experimental outcomes will include a comparison of the contribution of individual cues under varying conditions and discussion of the implications for system optimization