Plastic pollution Whenever will we recognize ample

The results demonstrate feasibility of GWAS to identify novel candidate genes controlling industrially-relevant tracheid traits in Norway spruce.Conventional transarterial chemoembolization (cTACE) is a guideline-approved image-guided therapy option for liver cancer using the radiopaque drug-carrier and micro-embolic agent Lipiodol, which has been previously established as an imaging biomarker for tumor response. To establish automated quantitative and pattern-based image analysis techniques of Lipiodol deposition on 24 h post-cTACE CT as biomarker for treatment response. The density of Lipiodol deposits in 65 liver lesions was automatically quantified using Hounsfield Unit thresholds. Lipiodol deposition within the tumor was automatically assessed for patterns including homogeneity, sparsity, rim, and peripheral deposition. A2ti-2 solubility dmso Lipiodol deposition was correlated with enhancing tumor volume (ETV) on baseline and follow-up MRI. ETV on baseline MRI strongly correlated with Lipiodol deposition on 24 h CT (p  less then  0.0001), with 8.22% ± 14.59 more Lipiodol in viable than necrotic tumor areas. On follow-up, tumor regions with Lipiodol showed higher rates of ETV reduction than areas without Lipiodol (p = 0.0475) and increasing densities of Lipiodol enhanced this effect. Also, homogeneous (p = 0.0006), non-sparse (p  less then  0.0001), rim deposition within sparse tumors (p = 0.045), and peripheral deposition (p  less then  0.0001) of Lipiodol showed improved response. This technical innovation study showed that an automated threshold-based volumetric feature characterization of Lipiodol deposits is feasible and enables practical use of Lipiodol as imaging biomarker for therapeutic efficacy after cTACE.Satellite and ground-based remote sensing are combined to characterize lightning occurrence during the 3 June 2018 Volcán de Fuego eruption in Guatemala. The combination of the space-based Geostationary Lightning Mapper (GLM) and ground-based Earth Networks Total Lightning Network observed two distinct periods of lightning during this eruption totaling 75 unique lightning flash occurrences over five hours (57 in cloud, 18 cloud-to-ground). The first period of lightning coincided with the rapid growth of the ash cloud, while the second maxima occurred near the time of a deadly pyroclastic density current (PDC) and thunderstorm. Ninety-one percent of the lightning during the event was observed by only one of the lightning sensors, thus showing the importance of combining lightning datasets across multiple frequencies to characterize electrical activity in volcanic eruptions. GLM flashes during the event had a median total optical energy and flash length of 16 fJ, and 12 km, respectively. These median GLM flash energies and lengths observed in the volcanic plume are on the lower end of the flash spectrum because flashes observed in surrounding thunderstorms on 3 June had larger median total optical energy values (130 fJ) and longer median flash lengths (20 km). All 18 cloud-to-ground flashes were negative polarity, supportive of net negative charge within the plume. Mechanisms for the generation of the secondary lightning maxima are discussed based on the presence and potential interaction between ash plume, thunderstorm, and PDC transport during this secondary period of observed lightning.In the multi-effect evaporation salt making process, the smooth operation of the salt making process is crucial. As the salt production process continues, many unstable factors will cause the salt production process not to proceed smoothly. These factors can be discovered in advance by predicting the salt production data, thus, it is of great significance to predict the multi-effect evaporation salt production data. In the process of multi-effect evaporation and salt production, the multiple salt-making devices make the influence between the parameters closer, and the influence of a single parameter on itself is sometimes ductile. Therefore, the data of multi-effect evaporation and salt production have the characteristics of high dimensions, high complexity and temporal information. If the historical salt production data is used for data prediction directly, the prediction model will take a long time and the prediction effect is not good. Thus, how to predict the multi-effect evaporation salt production data is the main research problem of this paper. In view of the above problems, according to the characteristics of multi-effect evaporation salt production data, this paper analyzes and improves the self encoder for feature extraction of multi effect-evaporation salt production data, so as to solve the problem of high dimensions and high complexity of salt production data. On this basis, combined with the time-series information contained in the salt production data, a multi-effect evaporation salt production data prediction model is proposed based on long-term and short-term memory cycle neural network to solve the prediction problem of time-series salt production data. Experiments show that the prediction model can predict and prevent the problems in salt production line in advance. It has a certain theoretical research value and application value in the intelligent production process and production line optimization of salt chemical industry.Periodontitis is an inflammatory disease that can lead to the periodontal pocket formation and tooth loss. This study was aimed to develop antimicrobials loaded hydrogels composed of cellulose nanofibers (CNF) and κ-carrageenan oligosaccharides (CO) nanoparticles for the treatment of periodontitis. Two antimicrobial agents such as surfactin and Herbmedotcin were selected as the therapeutic agents and the hydrogels were formulated based on the increasing concentration of surfactin. The proposed material has high thermal stability, controlled release, and water absorption capacity. This study was proceeded by investigating the in vitro antibacterial and anti-inflammatory properties of the hydrogels. This material has strong antibacterial activity against periodontal pathogens such as Streptococcus mutans, Porphyromonas gingivalis, Fusobacterium nucleatum, and Pseudomonas aeruginosa. Moreover, a significant increase in malondialdehyde (MDA) production and a decrease in biofilm formation and metabolic activity of the bacteria was observed in the presence of hydrogel.