Ratio of Intensities of Blue and Red Light at Cultivation Influences Photosynthetic Light Reactions, Respiration, Growth, and Reflectance Indices in Lettuce

LED illumination can have a narrow spectral band; its intensity and time regime are regulated within a wide range. These characteristics are the potential basis for the use of a combination of LEDs for plant cultivation because light is the energy source that is used by plants as well as the regulator of photosynthesis, and the regulator of other physiological processes (e.g., plant development), and can cause plant damage under certain stress conditions. As a result, analyzing the influence of light spectra on physiological and growth characteristics during cultivation of different plant species is an important problem. In the present work, we investigated the influence of two variants of LED illumination (red light at an increased intensity, the “red” variant, and blue light at an increased intensity, the “blue” variant) on the parameters of photosynthetic dark and light reactions, respiration rate, leaf reflectance indices, and biomass, among other factors in lettuce (Lactuca sativa L.). The same light intensity (about 180 µmol m−2s−1) was used in both variants. It was shown that the blue illumination variant increased the dark respiration rate (35–130%) and cyclic electron flow around photosystem I (18–26% at the maximal intensity of the actinic light) in comparison to the red variant; the effects were dependent on the duration of cultivation. In contrast, the blue variant decreased the rate of the photosynthetic linear electron flow (13–26%) and various plant growth parameters, such as final biomass (about 40%). Some reflectance indices (e.g., the Zarco-Tejada and Miller Index, an index that is related to the core sizes and light-harvesting complex of photosystem I), were also strongly dependent on the illumination variant. Thus, our results show that the red illumination variant contributes a great deal to lettuce growth; in contrast, the blue variant contributes to stress changes, including the activation of cyclic electron flow around photosystem I.

Quality Assessment on the Oxidative Stability of Almond Kernels during Extensive Storage Time

The objective of our study is to monitor the oxidative stability of different cultivars of almonds (Australian, American and Iranian) kernels/oil during the 12th month of storage at room temperature. Several physicochemical parameters free fatty acids (FFA), peroxide value (PV), panisidine value (p-AV), total oxidation value (TOTOX), Fourier transforms infrared spectrophotometer (FT-IR) and Gas chromatography Mass spectrometry (GC-MS) were used to check the oxidative stability of almond kernel. According to the results, effects of room temperature in the early stages of oxidation, primary oxidation products remained stable, whereas secondary oxidation product levels continued to rise in the later stages. In general, FFA increased with increasing storage time, the range was observed (0.21-0.97 %), PV (1.31-16.23 meqO2/kg), p-AV (2.21-19.35), TOTOX (4.83-15.81), respectively. During storage at room temperature for up to 12th months, there was no significant shifting of the spectral band in the FT-IR study. The most bounteous fatty acid in the almond oil range was observed oleic acid C18:0 (71.01-79.56 %) followed by linoleic acid C18:2 (13.13–20.65 %), palmitic acid C16:0 (4.86-5.67 %), stearic acid C18:0 (1.20-3.81 %), and palmitoleic acid C16:1(0.21-0.47 %) in all three samples during storage. These results suggest that almond oil during the 12th month of storage keeps its good chemical properties.

The Effect of Climate Changes on The Fluctuation of The Water Level of Al- Razzaza Lake, Iraq

One of the serious environmental challenges that Iraq faces is climate changes and impacts of changing weather patterns and extreme global weather events. This paper addresses changes in the temporal and spatial characteristics of water levels of Razzaza Lake and response to climatic changes using archived series of Multispectral satellite images Landsat. TM, ETM+ and OLI images acquired on 1990, 2000 and of 2016. In order to extract, mapping the water surface area of the Razzaza Lake, Multispectral spectral band rationing the Normalized Difference Water Index (NDWI) technique was adopted, and the climatic elements data for the period (1990-2016) were analyzed which provide significant information of surface water. The results show that Razzaza Lake has a particularly sharp change rate in the water level and there are significant fluctuations on lake level and water surface area over the time.

A Randomized, Double-Blind, Placebo-Controlled Study of the Effects of Two Sequential Doses of NV-5138 SPN-820 on Quantitative Electroencephalography in Healthy Adult Males

NV-5138 (or SPN-820) is a novel small molecule activator of the mechanistic target of rapamycin complex 1 (mTORC1) currently under development for use in treatment- resistant depression. This phase I study evaluated the safety, tolerability, and pharmacodynamics (as measured by quantitative electroencephalography, qEEG) of two sequential oral doses of NV-5138 in healthy adult males. Twenty-five participants were randomly assigned to double-blind treatment with a single dose of placebo or 2400 mg NV-5138 on Day 1, and a second dose of the same treatment on Day 3. The two doses of NV-5138 were safe and well tolerated, with no deaths, serious adverse events, or discontinuations due to adverse events. Spectral band amplitudes, derived frequency measures, and magnitude squared coherences were computed from qEEG recordings during resting state eyes-open and eyes-closed conditions at multiple timepoints. In the NV-5138 group only, significant changes in qEEG measures occurred at 1 hour post-dose on both days (near NV-5138 T max ), including decreases in low-frequency band amplitudes (theta) and increases in high-frequency EEG band amplitudes (high beta and gamma). These effects were mirrored by a decrease in the theta/beta ratio, a measure negatively associated with arousal and cognitive processing capability. Significantly increased high beta and gamma band coherences were also detected at several specific electrode pairs in both eyes-open and eye-closed conditions. NV-5138 actively modulated functional brain parameters consistent with positive effects on mood, cognition, and arousal. These results indicate that qEEG measures may be useful biomarkers of NV-5138 target engagement and related changes in neural activity.

Adaptive Data Screening for Multi-Angle Polarimetric Aerosol and Ocean Color Remote Sensing Accelerated by Deep Learning

Remote sensing measurements from multi-angle polarimeters (MAPs) contain rich aerosol microphysical property information, and these sensors have been used to perform retrievals in optically complex atmosphere and ocean systems. Previous studies have concluded that, generally, five moderately separated viewing angles in each spectral band provide sufficient accuracy for aerosol property retrievals, with performance gradually saturating as angles are added above that threshold. The Hyper-Angular Rainbow Polarimeter (HARP) instruments provide high angular sampling with a total of 90–120 unique angles across four bands, a capability developed mainly for liquid cloud retrievals. In practice, not all view angles are optimal for aerosol retrievals due to impacts of clouds, sunglint, and other impediments. The many viewing angles of HARP can provide resilience to these effects, if the impacted views are screened from the dataset, as the remaining views may be sufficient for successful analysis. In this study, we discuss how the number of available viewing angles impacts aerosol and ocean color retrieval uncertainties, as applied to two versions of the HARP instrument. AirHARP is an airborne prototype that was deployed in the ACEPOL field campaign, while HARP2 is an instrument in development for the upcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Based on synthetic data, we find that a total of 20–30 angles across all bands (i.e., five to eight viewing angles per band) are sufficient to achieve good retrieval performance. Following from this result, we develop an adaptive multi-angle polarimetric data screening (MAPDS) approach to evaluate data quality by comparing measurements with their best-fitted forward model. The FastMAPOL retrieval algorithm is used to retrieve scene geophysical values, by matching an efficient, deep learning-based, radiative transfer emulator to observations. The data screening method effectively identifies and removes viewing angles affected by thin cirrus clouds and other anomalies, improving retrieval performance. This was tested with AirHARP data, and we found agreement with the High Spectral Resolution Lidar-2 (HSRL-2) aerosol data. The data screening approach can be applied to modern satellite remote sensing missions, such as PACE, where a large amount of multi-angle, hyperspectral, polarimetric measurements will be collected.

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals

Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors, Multiscale Permutation Entropy (MPE) is a suitable tool for capturing useful information from the ordinal patterns of sEMG time series. In a previous work, a theoretical comparison in terms of bias and variance of two MPE variants—namely, the refined composite MPE (rcMPE) and the refined composite downsampling (rcDPE), was addressed. In the current paper, we assess the superiority of rcDPE over MPE and rcMPE, when applied to real sEMG signals. Moreover, we demonstrate the capacity of rcDPE in quantifying fatigue levels by using sEMG data recorded during a fatiguing exercise. The processing of four consecutive temporal segments, during biceps brachii exercise maintained at 70% of maximal voluntary contraction until exhaustion, shows that the 10th-scale of rcDPE was capable of better differentiation of the fatigue segments. This scale actually brings the raw sEMG data, initially sampled at 10 kHz, to the specific 0–500 Hz sEMG spectral band of interest, which finally reveals the inner complexity of the data. This study promotes good practices in the use of MPE complexity measures on real data.

Estimating Actual Abundance of European Sousliks: Using UAV Imagery, Pixel Based Image Analysis and Random Forest Classification to Count Souslik Burrows

Burrowing mammals are widespread and contribute significantly to soil ecosystem services. However, how to conduct a non-invasive estimation of their actual population size has remained a challenge. Results support that the number of burrow entrances is positively correlated with population abundance and burrows’ location indicates their area of occupancy consequently it provides a benchmark for estimating population size. European souslik is an endangered burrowing species in decline across its range. We present an imagery-based method to identify and count animals’ burrows semi-automatically by combining remotely recorded RGB images, pixel-based imagery (PBI) and Random Forest (RF) classification. Field images recorded in four colonies were collected, combined and then processed by histogram matching and spectral band normalisation to improve the spectral distinction between the categories BURROW, SOIL, TREE, GRASS. Raw or processed images were analysed by RF classification to compare the change in accuracy metrics as a result of processing. From accuracy metrics kappa of precision (κBURROWP) and sensitivity (κBURROWS) for BURROW were 95 and 90% respectively. A 10-time bootstrapping of the final model resulted in coefficients of variation (CV%) of κBURROWS and κBURROWP lower than 5%, moreover CV% values were not significantly different between precision and sensitivity scores. The consistency of classification results and balanced precision and sensitivity confirmed the applicability of this approach. Our method provides an accurate and user-friendly tool to count the number of burrow openings and delineate the areas of occupancy as compared to traditional, more invasive approaches or other computer capacity and end-user expertise demanding methods.

Can the Dynamic Colouration and Patterning of Bluelined Goatfish (Mullidae; Upeneichthys lineatus) Be Perceived by Conspecifics?

Bluelined goatfish (<i>Upeneichthys lineatus</i>) exhibit dynamic body colour changes and transform rapidly from a pale, buff/white, horizontally banded pattern to a conspicuous, vertically striped, red pattern when foraging. This red pattern is potentially an important foraging signal for communication with conspecifics, provided that <i>U. lineatus</i> can detect and discriminate the pattern. Using both physiological and behavioural experiments, we first examined whether <i>U. lineatus</i> possess visual pigments with sensitivity to long (“red”) wavelengths of light, and whether they can discriminate the colour red. Microspectrophotometric measurements of retinal photoreceptors showed that while <i>U. lineatus</i>lack visual pigments dedicated to the red part of the spectrum, their pigments likely confer some sensitivity in this spectral band. Behavioural colour discrimination experiments suggested that <i>U. lineatus</i>can distinguish a red reward stimulus from a grey distractor stimulus of variable brightness. Furthermore, when presented with red stimuli of varying brightness they could mostly discriminate the darker and lighter reds from the grey distractor. We also obtained anatomical estimates of visual acuity, which suggest that <i>U. lineatus</i> can resolve the contrasting bands of conspecifics approximately 7 m away in clear waters. Finally, we measured the spectral reflectance of the red and white colouration on the goatfish body. Visual models suggest that <i>U. lineatus</i> can discriminate both chromatic and achromatic differences in body colouration where longer wavelength light is available. This study demonstrates that <i>U. lineatus</i> have the capacity for colour vision and can likely discriminate colours in the long-wavelength region of the spectrum where the red body pattern reflects light strongly. The ability to see red may therefore provide an advantage in recognising visual signals from conspecifics. This research furthers our understanding of how visual signals have co-evolved with visual abilities, and the role of visual communication in the marine environment.

Unmanned Aerial System-Based Multispectral Water Quality Monitoring in the Iberian Pyrite Belt (SW Spain)

Few studies have assessed mining-associated water pollution using spectral characteristics. We used high-resolution multispectral data acquired by unmanned aerial drones combined with in situ chemical data to assess water quality parameters in 12 relatively small water bodies located in the Tharsis complex, an abandoned mining area in the Iberian pyrite belt (SW Spain). The spectral bands of Micasense RedEdge-MX Dual and spectral band combinations were used jointly with physicochemical data to estimate water quality parameters and develop reliable empirical models using regression analysis. Physicochemical parameters including pH, ORP, EC, Al, Cu, Fe, Mn, S, Si, and Zn were estimated with high accuracy levels (0.81 < R2 < 0.99, 4 < RMSE% < 75, 0.01 < MAPE < 0.97). In contrast, the observed and modelled values for Ba, Ca, and Mg did not agree well (0.42 < R2 < 0.70). The best-fitted models were used to generate spatial distribution maps, providing information on water quality patterns. This study demonstrated that using empirical models to generate spatial distribution maps can be an effective and easy way to monitor acid mine drainage.

Aerosol models from the AERONET data base. Application to surface reflectance validation

Aerosols play a critical role in radiative transfer within the atmosphere, and they have a significant impact on climate change. As part of the validation of atmospheric correction of remote sensing data affected by the atmosphere, it is critical to utilize appropriate aerosol models as aerosols are a main source of error. In this paper, we propose and demonstrate a framework for building and identifying an aerosol model. For this purpose, we define the aerosol model by recalculating the aerosol microphysical properties (Cvf, Cvc, %Cvf, %Cvc, rvf, rvc, σr, σc, nr440, nr650, nr850, nr1020, ni440, ni650, ni850, ni1020, %Sph) based on the optical thickness at 440 nm τ440 and the Ångström coefficient α440–870 obtained from numerous AERosol RObotic NETwork (AERONET) sites. Using aerosol microphysical properties provided by the AERONET dataset, we were able to evaluate our own retrieved microphysical properties. The associated uncertainties are up to 23 %, except for the challenging, imaginary part of the refractive index ni (about 38 %). Uncertainties of the retrieved aerosol microphysical properties were incorporated in the framework for validating surface reflectance derived from space-borne Earth observation sensors. Results indicate that the impact of aerosol microphysical properties varies 3.5 × 10−5 to 10−3 in reflectance units. Finally, the uncertainties of the microphysical properties yielded an overall uncertainty of approximately of 1 to 3 % of the retrieved surface reflectance in the MODIS red spectral band (620–670 nm), which corresponds to the specification used for atmospheric correction.