In 2016, the Alcohol Hangover Research Group defined the alcohol hangover as "the combination of mental and physical symptoms experienced the day after a single episode of heavy drinking, starting when blood alcohol concentration (BAC) approaches zero". In the light of new findings and evidence, we carefully reviewed the different components of that definition. Several studies demonstrated that alcohol hangovers are not limited to heavy drinking occasions. Instead, data from both student and non-student samples revealed that at a group level, alcohol hangover may occur at much lower BAC levels than previously thought. Regression analysis further revealed that for individual drinkers, the occurrence of hangovers is more likely when subjects consume more alcohol than they usually do. However, hangovers may also occur at a drinker's usual BAC, and in some cases even at lower BAC (e.g. in case of illness). Prostaglandin E2 purchase We also carefully reviewed and modified other parts of the definition. Finally, hangovers are not necessarily limited to the 'next day'. They can start at any time of day or night, whenever BAC approaches zero after a single dinking occasion. This may also be on the same day as the drinking occasion (e.g. when drinking in, or until the morning and subsequently having a hangover in the afternoon or evening). To better reflect the new insights and sharpen the description of the concept, we hereby propose to update the definition of the alcohol hangover as follows "The alcohol hangover refers to the combination of negative mental and physical symptoms which can be experienced after a single episode of alcohol consumption, starting when blood alcohol concentration (BAC) approaches zero", and recommend to use this new definition in future hangover research.In recent years, wireless-based fingerprint positioning has attracted increasing research attention owing to its position-related features and applications in the Internet of Things (IoT). In this paper, by leveraging long-term evolution (LTE) signals, a novel deep-learning-based fingerprint positioning approach is proposed to solve the problem of outdoor positioning. Considering the outstanding performance of deep learning in image classification, LTE signal measurements are converted into location grayscale images to form a fingerprint database. In order to deal with the instability of LTE signals, prevent the gradient dispersion problem, and increase the robustness of the proposed deep neural network (DNN), the following methods are adopted First, cross-entropy is used as the loss function of the DNN. Second, the learning rate of the proposed DNN is dynamically adjusted. Third, this paper adopted several data enhancement techniques. To find the best positioning fingerprint and method, three types of fingerprint and five positioning models are compared. Finally, by using a deep residual network (Resnet) and transfer learning, a hierarchical structure training method is proposed. The proposed Resnet is used to train with the united fingerprint image database to obtain a positioning model called a coarse localizer. By using the prior knowledge of the pretrained Resnet, feed-forward neural network (FFNN)-based transfer learning is used to train with the united fingerprint database to obtain a better positioning model, called a fine localizer. The experimental results convincingly show that the proposed DNN can automatically learn the location features of LTE signals and achieve satisfactory positioning accuracy in outdoor environments.Although drinking water safety has raised considerable concern, to date, the hidden health risks in newly released overnight water from a municipal pipeline have seldom received attention. In this study, bacterial community composition and the response of antibiotic-resistant bacteria (ARB) to ciprofloxacin, azithromycin, tetracycline, penicillin, and cephalosporin in overnight stagnant water were analyzed. With increases in heterotrophic bacteria plate count (HPC) during water stagnation, the numbers of ARB and the ARB/HPC ratios for the five antibiotics in resident water were observed to increase, which illustrated that the prevalence of ARB rose in the pipe network water during stagnation time (ST). Furthermore, during water stagnation for 12 h, an increase in bacteria related to fermentation was also observed. When the ST rose to 48 h, the fermentation bacteria become non-significant, and this was related to the exchange of pipe network water during daytime stagnation within the 48-h period. The antibiotic resistance index (ARI) showed that tetracycline had the highest resistance level in fresh water, and then decreased during water stagnation. When ST increased to 12 h, all ARI values of the five antibiotics were low, which was associated with changes in parameters during water retention and reduced resistance during short-term stagnation. When the ST increased to 24 and 48 h, the resistance to most antibiotics (except for tetracycline) increased, which showed that increasing antibiotic resistance is caused by the formation of biofilms in the pipeline during water stagnation.Marek's disease is a major scourge challenging poultry health worldwide. It is caused by the highly contagious Marek's disease virus (MDV), an alphaherpesvirus. Here, we showed that, similar to other members of its Herpesviridae family, MDV also presents a complex landscape of splicing events, most of which are uncharacterised and/or not annotated. Quite strikingly, and although the biological relevance of this fact is unknown, we found that a number of viral splicing isoforms are strain-specific, despite the close sequence similarity of the strains considered very virulent RB-1B and vaccine CVI-988. We validated our findings by devising an assay that discriminated infections caused by the two strains in chicken embryonic fibroblasts on the basis of the presence of some RNA species. To our knowledge, this study is the first to accomplish such a result, emphasizing how relevant a comprehensive picture of the viral transcriptome is to fully understand viral pathogenesis.In this study, we isolated from the aerial parts of Baccharis conferta Kunth (i) a new neoclerodane, denominated "bacchofertone"; (ii) four known terpenes schensianol A, bacchofertin, kingidiol and oleanolic acid; and (iii) two flavonoids cirsimaritin and hispidulin. All structures were identified by an exhaustive analysis of nuclear magnetic resonance (NMR) and mass spectroscopy (MS). Extracts from aerial parts were screened for anti-inflammatory activity in the mice ear edema model of 12-O-tetradecanoylforbol-13-acetate mice. Dichloromethane extract (BcD) exhibited 78.5 ± 0.72% inhibition of edema, followed by the BcD2 and BcD3 fractions of 71.4% and 82.9% respectively, at a dose of 1 mg/ear. Kingidiol and cirsimaritin were the most potent compounds identified, with a median effective dose of 0.12 and 0.16 mg/ear, respectively. A histological analysis showed that the topical application of TPA promoted intense cell infiltration, and this inflammatory parameter was reduced with the topical application of isolated compounds.