Search Results (48)

High-wind structures were identified in the Cross-Calibrated Multi-Platform (CCMP) ocean wind vector reanalysis for comparison with winds measured by satellite radiometers, scatterometers, and synthetic aperture radar (SAR) instruments from February to October 2023. The comparison aims to evaluate bias, uncertainty, and spatial correlations with the goal of enhancing the accuracy of ocean wind datasets during tropical cyclones (TCs). In 10° longitude × 10° latitude blocks, each containing a TC, Soil Moisture Active Passive (SMAP) and Advanced Microwave Scanning Radiometer 2 (AMSR2) winds are 6.5 and 4.8% higher than CCMP, while Advanced Scatterometer (ASCATB) is 0.8% lower. For extratropical cyclones, AMSR2 and SMAP also show stronger winds with a 5% difference, and ASCATB is about 0.3% weaker compared to CCMP. The comparison between SAR and CCMP for TC winds, sampled at the locations and time frames of SAR tiles, indicates that SAR winds around TCs are about 9% higher than CCMP winds. Using empirically defined TC structural indices, we find that the TCs observed by CCMP are shifted in locations and lack a compact core region. A Random Forest (RF) regressor was applied to TCs in CCMP with corresponding SAR observations, nearly correcting the full magnitude of low bias in CCMP statistically, with a 15 m/s correction in the core region. The hierarchy of importance among the predictors is as follows: CCMP wind speed (62%), distance of SAR pixels to the eye region (21%) and eye center (7%), and distance of CCMP pixels to the eye region (5%) and eye center (5%). Full article

Climate changes may include variations in salinity concentrations at sea by changing ocean dynamics. These variations may be especially challenging for marine photosynthetic organisms, affecting their growth and distribution. Chlamydomonas spp. are ubiquitous and are often found in extreme salinity conditions. For this reason, they are considered good model species to study salinity adaptation strategies. In the current study, we used an integrated approach to study the Chlamydomonas sp. CCMP225 response to salinities of 20‰ and 70‰, by combining physiological, morphological, and transcriptomic analyses, and comparing differentially expressed genes in the exponential and stationary growth phases under the two salinity conditions. The results showed that the strain is able to grow under all tested salinity conditions and maintains a surprisingly high photosynthetic efficiency even under high salinities. However, at the highest salinity condition, the cells lose their flagella. The transcriptomic analysis highlighted the up- or down-regulation of specific gene categories, helping to identify key genes responding to salinity stress. Overall, the findings may be of interest to the marine biology, ecology, and biotechnology communities, to better understand species adaptation mechanisms under possible global change scenarios and the potential activation of enzymes involved in the synthesis of bioactive molecules. Full article

Amid global energy demands and environmental concerns, the exploration of renewable energy sources has become critically important. This study presents a comprehensive analysis of wind energy dynamics over a 35-year period (1988–2022) using CCMP and ERA5 datasets. It focuses on the spatial and temporal characteristics of wind energy within the region, particularly its distribution. The wind field in Sri Lanka has significant seasonal and regional characteristics. Despite seasonal variations, the overall wind activity remains moderate, with speeds generally above 5.4 m/s and annual average wind power densities exceeding 150 W/m², reaching up to 200 W/m² in certain areas. The two primary wind directions in the waters near Sri Lanka are WSW and NE. The study identifies periods of high stability, particularly from June to August, where effective wind speed occurrence (EWSO) exceeds 80%. A ‘W’-shaped pattern in monthly variations corresponds with changes in wind power density (WPD), highlighting optimal periods for wind energy extraction. Additionally, estimated reserves and technically exploitable wind energy resources (WERs) suggest that wind energy development off Sri Lanka is feasible, with potential capacities of approximately 2.00 GW and 1.60 GW, respectively. The overall coefficient of variation (CV) is small, indicating stable wind energy conditions. This analysis not only provides a scientific basis for evaluating WERs near Sri Lanka but also offers valuable insights for strategic planning and development in the renewable energy sector. Full article

Coccoid Ulvophyceae are often overlooked despite their wide distribution. They occur as epiphytes on marine seaweeds or grow on stones or on shells of mussels and corals. Most of the species are not easy to identify based solely on morphology. However, they form two groups based on the flagellated cells during asexual reproduction. The biflagellated coccoids are monophyletic and represent the genus Sykidion (Sykidiales). In contrast, the quadriflagellated taxa are polyphyletic and belong to different genera and orders. The newly investigated strains NIES-1838 and NIES-1839, originally identified as Halochlorococcum, belong to the genus Chlorocystis (C. john-westii) among the order Chlorocystidales. The unidentified strain CCMP 1293 had almost an identical SSU and ITS-2 sequence to Symbiochlorum hainanense (Ignatiales) but showed morphological differences (single chloroplast, quadriflagellated zoospores) compared with the original description of this species (multiple chloroplasts, aplanospores). Surprisingly, the strain SAG 2662 (= ULVO-129), together with the published sequence of MBIC 10461, formed a new monophyletic lineage among the Ulvophyceae, which is highly supported in all of the bootstrap and Bayesian analyses and approximately unbiased tests of user-defined trees. This strain is characterized by a spherical morphology and also form quadriflagellated zoospores, have a unique ITS-2 barcode, and can tolerate a high variation of salinities. Considering our results, we emend the diagnosis of Symbiochlorum and propose the new genus Solotvynia among the new order Solotvyniales. Full article

The purpose of dark image enhancement is to restore dark images to visual images under normal lighting conditions. Due to the ill-posedness of the enhancement process, previous enhancement algorithms often have overexposure, underexposure, noise increases and artifacts when dealing with complex and changeable images, and the robustness is poor. This article proposes a new enhancement approach consisting in constructing a dim light enhancement network with more robustness and rich detail features through the collaborative constraint of multiple self-coding priors (CCMP). Specifically, our model consists of two prior modules and an enhancement module. The former learns the feature distribution of the dark light image under normal exposure as an a priori term of the enhancement process through multiple specific autoencoders, implicitly measures the enhancement quality and drives the network to approach the truth value. The latter fits the curve mapping of the enhancement process as a fidelity term to restore global illumination and local details. Through experiments, we concluded that the new method proposed in this article can achieve more excellent quantitative and qualitative results, improve detail contrast, reduce artifacts and noise, and is suitable for dark light enhancement in multiple scenes. Full article

A 12-week feeding trial examined the dietary impact of replacing fishmeal (FM) with algal biomass (AB) derived from Pavlova sp. strain CCMP459 (Pav459) in Atlantic salmon diets. Three distinct diets were formulated: a control diet featuring 20% FM and 7% fish oil (FO), an experimental diet incorporating a 50:50 blend of FM and AB Pav459 and reduced FO (10% FM; 4.5% FO; 10% AB), and a second experimental diet with full replacement of FM with AB Pav459 and further reduction in FO (1.75% FO; 20% AB). Replacing FM with AB Pav459 showed no significant effects on the growth performance of Atlantic salmon. Fish across all diets exhibited growth exceeding 200% from their initial weight. Analysis of total lipid content after the 12-week trial revealed no significant differences among the diets. However, individual proportions of omega-3 (ω3) and omega-6 (ω6) fatty acids varied. Fatty acid profiling in muscle and liver tissues showed distinct compositions reflective of dietary treatments. Linoleic acid (LA) and α-linolenic acid (ALA) exhibited higher proportions in total fatty acids than in membrane lipids. Docosahexaenoic acid (DHA) emerged as the predominant fatty acid in the membranes of both liver and muscle tissues. Furthermore, an analysis of sterol composition in Pavlova and salmon muscle tissue showed the presence of important sterols, including conventionally animal-associated cholesterol. This emphasizes the suitability of microorganisms, such as Pav459, for synthesizing diverse nutrients. Stable isotope analysis demonstrated direct incorporation of eicosapentaenoic acid (EPA) and DHA from diets into salmon tissues. Notably, minimal biosynthesis from the precursor ALA was observed, reaffirming the utility of Pav459-derived fatty acids. The EPA+DHA proportions in the fillet consistently met daily human consumption requirements across all dietary conditions, supporting the use of Pav459 algal biomass as an alternative to FM. Full article

The Cross-Calibrated Multi-Platform (CCMP) wind analysis is a satellite-based blended wind product produced using a two-dimensional variational method. The current version available publicly is Version 2 (CCMP2.0), which includes buoy winds in addition to satellite winds. Version 3 of the product (CCMP3.0) is being produced with several improvements in analysis algorithms, without including buoy winds. Here, we compare CCMP3.0 with a special version of CCMP2.0 that did not include buoy winds, so both versions are independent of buoy measurements. We evaluate them using wind data from buoys around the coasts of the United States and discuss the implications for the wind power industry and offshore wind farms. CCMP2.0 uses ERA-Interim 10 m winds as the background to fill observational gaps. CCMP3.0 uses ERA5 10 m neutral winds as the background. Because ERA5 winds are biased towards lower values at higher wind conditions, CCMP3.0 corrected this bias by matching ERA5 wind speeds with satellite scatterometer wind speeds using a histogram matching method. Our evaluation indicates that CCMP3.0 has better agreement with the independent buoy winds, primarily for higher winds (>10 m/s). This is reflected by the higher correlation and lower root-mean-squared differences of CCMP3.0 versus buoy winds, especially for higher wind conditions. For the U.S. coastal region (within 200 km), the mean wind speed of CCMP3.0 is enhanced by 1–2%, and the wind speed standard deviation is enhanced by around 3–5%. These changes in wind speed and its standard deviation from CCMP2.0 to CCMP3.0 cause an 8–12% increase in wind power density. The wind power density along the U.S. coastal region is also correlated with various climate indices depending on locations, providing a useful approach for predicting wind power on subseasonal to interannual timescales. Full article

Based on the third-generation wave model WAVEWATCH-III (WW3), this paper analyzes the changing trend of wave power density (WPD) in the South China Sea, which can provide necessary references for the development and utilization of wave energy resources in the future. In this study, multi-platform cross-calibrated (CCMP) wind data was used to drive WW3 to calculate the WPD of the South China Sea. The Mann-Kendall (MK) algorithm can be used to determine the mutation of WPD, and the accuracy of the CCMP wind was verified. Next, the time distribution of WPD is analyzed for the whole sea area and dominant sea area of the South China Sea, and on this basis, the dominant sea area for the development of wave energy resources in the South China Sea was studied. The results are as follows: (1) Extreme weather has a significant impact on the change of WPD in the South China Sea, and this change is likely due to the effect of extreme weather on sea temperature. (2) Dongsha Islands has the highest annual WPD value and has the greatest impact on the overall trend change of the South China Sea. (3) Integrated wave energy exploitability and safety and technology perspectives, the waters around Taiwan Strait are more suitable as the primary site for energy conversion. Full article

Alzheimer’s disease (AD) is the most common form of dementia and may contribute to 60–70% of cases. Worldwide, around 50 million people suffer from dementia and the prediction is that the number will more than triple by 2050, as the population ages. Extracellular protein aggregation and plaque deposition as well as accumulation of intracellular neurofibrillary tangles, all leading to neurodegeneration, are the hallmarks of brains with Alzheimer’s disease. Therapeutic strategies including active and passive immunizations have been widely explored in the last two decades. Several compounds have shown promising results in many AD animal models. To date, only symptomatic treatments are available and because of the alarming epidemiological data, novel therapeutic strategies to prevent, mitigate, or delay the onset of AD are required. In this mini-review, we focus on our understanding of AD pathobiology and discuss current active and passive immunomodulating therapies targeting amyloid-β protein. Full article

We combined observations of ocean surface winds from Indian SCATterometer SATellite-1 (SCATSAT-1) with a background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium-Range Weather Forecast (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. We are following the concept from the modern particle filter technique, which does not represent the model probability density function (PDF) as Gaussian. We generated the 6-hourly hybrid winds for 2018 and validated them using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform (CCMP) dataset and global buoy data from National Data Buoy Centre (NDBC). The results suggest the potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and bias along the swath. The study shows that the generated hybrid winds are of prime quality compared with the already existing daily products available from Indian Space Research Organization (ISRO). Full article

Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) is a new remote sensing technology that uses GNSS signals reflected from the Earth’s surface to estimate geophysical parameters. Because of its unique advantages such as high temporal and spatial resolutions, low observation cost, wide coverage and all-weather operation, it has been widely used in land and ocean remote sensing fields. Ocean wind monitoring is the main objective of the recently launched Cyclone GNSS (CYGNSS). In previous studies, wind speed was usually retrieved using features extracted from delay-Doppler maps (DDMs) and empirical geophysical model functions (GMFs). However, it is a challenge to employ the GMF method if using multiple sea state parameters as model input. Therefore, in this article, we propose an improved deep learning network framework to retrieve global sea surface wind speed using spaceborne GNSS-R data, named GloWS-Net. GloWS-Net considers the fusion of auxiliary information including ocean swell significant wave height (SWH), sea surface rainfall and wave direction to build an end-to-end wind speed retrieval model. In order to verify the improvement of the proposed model, ERA5 and Cross-Calibrated Multi-Platform (CCMP) wind data were used as reference for extensive testing to evaluate the wind speed retrieval performance of the GloWS-Net model and previous models (i.e., GMF, fully connected network (FCN) and convolutional neural network (CNN)). The results show that, when using ERA5 winds as ground truth, the root mean square error (RMSE) of the proposed GloWS-Net model is 23.98% better than that of the MVE method. Although the GloWS-Net model and the FCN model have similar RMSE (1.92 m/s), the mean absolute percentage error (MAPE) of the former is improved by 16.56%; when using CCMP winds as ground truth, the RMSE of the proposed GloWS-Net model is 2.16 m/s, which is 20.27% better than the MVE method. Compared with the FCN model, the MAPE is improved by 17.75%. Meanwhile, the GloWS-Net outperforms the FCN, traditional CNN, modified CNN (MCNN) and CyGNSSnet models in global wind speed retrieval especially at high wind speeds. Full article

Some strains of the dinoflagellate species Prorocentrum hoffmannianum show contrasting ability to produce diarrhetic shellfish poisoning (DSP) toxins. We previously compared the okadaic acid (OA) production level between a highly toxic strain (CCMP2804) and a non-toxic strain (CCMP683) of P. hoffmannianum and revealed that the cellular concentration of OA in CCMP2804 would increase significantly under the depletion of phosphate. To understand the molecular mechanisms, here, we compared and analyzed the proteome changes of both strains growing under normal condition and at phosphate depletion using two-dimensional gel electrophoresis (2-DE). There were 41 and 33 differential protein spots observed under normal condition and phosphate depletion, respectively, of which most were upregulated in CCMP2804 and 22 were common to both conditions. Due to the lack of matched peptide mass fingerprints in the database, de novo peptide sequencing was applied to identify the differentially expressed proteins. Of those upregulated spots in CCMP2804, nearly 60% were identified as peridinin-chlorophyll a-binding protein (PCP), an important light-harvesting protein for photosynthesis in dinoflagellates. We postulated that the high expression of PCP encourages the production of DSP toxins by enhancing the yields of raw materials such as acetate, glycolate and glycine. Other possible mechanisms of toxicity related to PCP might be through triggering the transcription of non-ribosomal peptide synthetase/polyketide synthase genes and the transportation of dinophysistoxin-4 from chloroplast to vacuoles. Full article

In vehicular ad hoc networks (VANETs), content pre-caching is a significant technology that improves network performance and lowers network response delay. VANET faces network congestion when multiple requests for the same content are generated. Location-based dependency requirements make the system more congested. Content pre-caching is an existing challenge in VANET; pre-caching involves the content’s early delivery to the requested vehicles to avoid network delays and control network congestion. Early content prediction saves vehicles from accidents and road disasters in urban environments. Periodic data dissemination without considering the state of the road and surrounding vehicles are considered in this research. The content available at a specified time poses considerable challenges in VANET for content delivery. To address these challenges, we propose a machine learning-based, zonal/context-aware-equipped content pre-caching strategy in this research. The proposed model improves content placement and content management in the pre-caching mode for VANET. Content caching is achieved through machine learning, which significantly improves content prediction by pre-caching the content early to the desired vehicles that are part of the zone. In this paper, three algorithms are presented, the first is zone selection using the customized algorithm, the second is the content dissemination algorithm, and the third is the content pre-caching decision algorithm using supervised machine learning that improves the early content prediction accuracy by 99.6%. The cache hit ratio for the proposed technique improves by 13% from the previous techniques. The prediction accuracy of the proposed technique is compared with CCMP, MLCP, and PCZS+PCNS on the number of vehicles from 10 to 150, with an improved average of 16%. Finally, the average delay reduces over time compared with the state-of-the-art techniques of RPSS, MLCP, CCMP, and PCZS+PCNS. Finally, the average delay shows that the proposed method effectively reduces the delay when the number of nodes increases. The proposed solution improves the content delivery request while comparing it with existing techniques. The results show improved pre-caching in VANET to avoid network congestion. Full article

The Cross-Calibrated Multi-Platform (CCMP) Ocean vector wind analysis is a level-4 product that uses a variational method to combine satellite retrievals of ocean winds with a background wind field from a numerical weather prediction (NWP) model. The result is a spatially complete estimate of global ocean vector winds on six-hour intervals that are closely tied to satellite measurements. The current versions of CCMP are fairly accurate at low to moderate wind speeds (<15 m/s) but are systematically too low at high winds at locations/times where a collocated satellite measurement is not available. This is mainly because the NWP winds tend to be lower than satellite winds, especially at high wind speed. The current long-term CCMP version, version 2.0, also shows spurious variations on interannual to decadal time scales caused by the interaction of satellite/model bias with the varying amount of satellite measurements available as satellite missions begin and end. To alleviate these issues, here we explore methods to adjust the source datasets to more closely match each other before they are combined. The resultant new CCMP wind analysis agrees better with long-term trend estimates from satellite observations and reanalysis than previous versions. Full article

A 9-week growth trial was carried out to assess the influence of replacing poultry by-product meal protein with conventional cottonseed meal protein (CCMP) or low gossypol cottonseed meal protein (LGCMP) on growth, feed utilization, gut micromorphology, and immunity of hybrid grouper (Epinephelus fuscoguttatus♀× Epinephelus lanceolatus♂) juveniles fed low-fish meal (18.53%, dry matter) diets. Eleven experimental diets were prepared. The control diet (PBMP) contained 46.15% poultry by-product meal protein. Both conventional cottonseed meal protein (CCMP) and low-gossypol cottonseed meal protein (LGCMP) were used in replacement ratios of 20, 40, 60, 80, and 100% of poultry by-product meal protein (PBMP) from the control diet, forming ten experimental diets (CCMP20, CCMP40, CCMP60, CCMP80, CCMP100, LGCMP20, LGCMP40, LGCMP60, LGCMP80, and LGCMP100). Results demonstrated that weight-gain percentage (WG%) was not different between different sources of cottonseed meal (CCMP and LGCMP). However, values of WG% significantly differed among different replacement levels, with CCMP80 and LGCMP40 having significantly higher values compared to other treatments. Fish fed CCMP80 and LGCMP40 exhibited higher protein efficiency ratios (PERs) than fish fed other experimental diets. The regression analysis from a second-order or third-order polynomial model based on WG% showed that the optimal PBMP replacement levels by CCMP and LGCMP are 74% and 33%, respectively. The whole-body lipid contents remarkably decreased as dietary CCMP or LGCMP inclusion levels increased. The relative mRNA expression of insulin-like growth factor-1(IGF-1) in liver was higher in fish fed CCMP80 and LGCMP40 diets compared to fish fed other diets. Generally, in low-FM diets of hybrid grouper, CCMP and LGCMP could replace 74% and 33% of PBMP, respectively. Full article