Wind-generated ocean waves drive important coastal processes that determine flooding and erosion. Ocean warming has been one factor affecting waves globally. Most studies have focused on studying ...parameters such as wave heights, but a systematic, global and long-term signal of climate change in global wave behavior remains undetermined. Here we show that the global wave power, which is the transport of the energy transferred from the wind into sea-surface motion, has increased globally (0.4% per year) and by ocean basins since 1948. We also find long-term correlations and statistical dependency with sea surface temperatures, globally and by ocean sub-basins, particularly between the tropical Atlantic temperatures and the wave power in high south latitudes, the most energetic region globally. Results indicate the upper-ocean warming, a consequence of anthropogenic global warming, is changing the global wave climate, making waves stronger. This identifies wave power as a potentially valuable climate change indicator.
This paper analyses 143 cases about the implementation of various and often interlinked, integrative, Resource Efficiency Measures (REMs). These REMs have been brought in a framework distinguishing ...on the one hand a cluster of supply side measures, demand side measures and life cycle measures with a synergistic mode of operation. They further have been related to clear classes or Business Model Changes (BMCs) that can support their implementation, notably changes in the supply chain (SC), internal processes (IP), customer interface (CI), financial model (FM) and the value proposition (VP). The BMCs were further characterised in terms of typical Implementation Barriers (IBs) that were reported in the cases, i.e. institutional, market, organisational, behavioural and technological barriers. Our study could not confirm some common theoretical wisdom, such as that firms mainly focus on ‘simple’ REMs like cleaner production and green products. Indeed, we could not confirm that REMs with a high scope and degree of change, often perceived as complex to implement, faced more Implementation Barriers than others. In general most Implementation Barriers play a role in all types of REMs and BMCs, although also some weak patterns were found. Internal processes BMCs were mainly hampered by institutional and technological factors. Value proposition and Financial model BMCs faced mainly behavioural and market barriers. Customer interface BMCs encountered additionally organisational barriers, while supply chain BMCs face a mix of all classes of barriers distinguished in this study. This is one of the first studies on business models and resource-efficiency looking at a large set of cases which is a step forward from the single case studies that dominate current literature. Yet, follow-up research should overcome weaknesses in our approach, such as a possible bias towards success cases and be more quantitative in analysing the effort it takes to overcome IBs.
Mitochondria have been proposed as the major source of reactive oxygen species in somatic cells and human spermatozoa. However, no data regarding the role of mitochondrial ROS production in stallion ...spermatozoa are available. To shed light on the role of the mitochondrial electron transport chain in the origin of oxidative stress in stallion spermatozoa, specific inhibitors of complex I (rotenone) and III (antimycin-A) were used. Ejaculates from seven Andalusian stallions were collected and incubated in BWW media at 37 °C in the presence of rotenone, antimycin-A or control vehicle. Incubation in the presence of these inhibitors reduced sperm motility and velocity (CASA analysis) (p<0.01), but the effect was more evident in the presence of rotenone (a complex I inhibitor). These inhibitors also decreased ATP content. The inhibition of complexes I and III decreased the production of reactive oxygen species (p<0.01) as assessed by flow cytometry after staining with CellRox deep red. This observation suggests that the CellRox probe mainly identifies superoxide and that superoxide production may reflect intense mitochondrial activity rather than oxidative stress. The inhibition of complex I resulted in increased hydrogen peroxide production (p<0.01). The inhibition of glycolysis resulted in reduced sperm velocities (p<0.01) without an effect on the percentage of total motile sperm. Weak and moderate (but statistically significant) positive correlations were observed between sperm motility, velocity and membrane integrity and the production of reactive oxygen species. These results indicate that stallion sperm rely heavily on oxidative phosphorylation (OXPHOS) for the production of ATP for motility but also require glycolysis to maintain high velocities. These data also indicate that increased hydrogen peroxide originating in the mitochondria is a mechanism involved in stallion sperm senescence.
Indoor positioning with smartphone-compatible technologies has fostered much research attention in recent years. In this context, Bluetooth Low Energy (BLE) reveals a good performance for this type ...of task. It offers more flexibility and better achievements when compared with similar systems based on IEEE 802.11 Wireless LAN (Wi-Fi) technology, especially for fingerprinting-based positioning systems. The literature on these systems is rich and growing; however, not all its possible algorithms have been tested and compared under similar conditions for this emergence technology.
This work presents a thorough analysis of the state of the art on Wi-Fi and Bluetooth Low Energy (BLE) algorithms used for fingerprinting systems. Based on this study, a novel scheme for fingerprinting methods classification is proposed. Then, a performance comparison between the Bluetooth Low Energy (BLE) databases is carried out, assessing training time, parameter optimization, computational time, and positioning accuracy. For the sake of completeness, a new database is provided and compared with the others to analyze how the environment can affect the accuracy of each method. The results show that those techniques based on the Weighted k-Nearest Neighbours (Wk-NN) algorithm perform better on average for large scale deployments; besides, they do not require any previous training and consume less time to optimize their parameters. On the other hand, Support Vector Machines (SVM) provides the best accuracy with less computational and training time in small environments.
•Wk-NN algorithm shows the best overall performance.•SVM require less training time for optimal accuracy.•Low performance of probabilistic-based algorithms.•Wk-NN is the preferable option for large mixed environments.•SVM is the preferable option for small indoor areas.
•A taxonomy that classifies ensemble models in the literature is presented.•Surface and deep features integration is explored to improve classification.•Several ensembles of classifiers and features ...are proposed and evaluated.•Performance of the proposed models is evaluated on several sentiment datasets.
Deep learning techniques for Sentiment Analysis have become very popular. They provide automatic feature extraction and both richer representation capabilities and better performance than traditional feature based techniques (i.e., surface methods). Traditional surface approaches are based on complex manually extracted features, and this extraction process is a fundamental question in feature driven methods. These long-established approaches can yield strong baselines, and their predictive capabilities can be used in conjunction with the arising deep learning methods. In this paper we seek to improve the performance of deep learning techniques integrating them with traditional surface approaches based on manually extracted features. The contributions of this paper are sixfold. First, we develop a deep learning based sentiment classifier using a word embeddings model and a linear machine learning algorithm. This classifier serves as a baseline to compare to subsequent results. Second, we propose two ensemble techniques which aggregate our baseline classifier with other surface classifiers widely used in Sentiment Analysis. Third, we also propose two models for combining both surface and deep features to merge information from several sources. Fourth, we introduce a taxonomy for classifying the different models found in the literature, as well as the ones we propose. Fifth, we conduct several experiments to compare the performance of these models with the deep learning baseline. For this, we use seven public datasets that were extracted from the microblogging and movie reviews domain. Finally, as a result, a statistical study confirms that the performance of these proposed models surpasses that of our original baseline on F1-Score.
Summary Culture-independent microbiological techniques have shown a previously unappreciated complexity to the bacterial microbiome of the respiratory tract that forces reconsideration of the ...interactions between host, bacteria, and the pathogenesis of exacerbations of chronic lung disease. The composition of the lung microbiome is determined by microbial immigration, elimination, and relative growth rates of its members. All these factors change dramatically in chronic lung disease and further during exacerbations. Exacerbations lack the features of bacterial infections, including increased bacterial burden and decreased diversity of microbial communities. We propose that exacerbations are occasions of respiratory tract dysbiosis—a disorder of the respiratory tract microbial ecosystem with negative effects on host biology. Respiratory tract dysbiosis provokes a dysregulated host immune response, which in turn alters growth conditions for microbes in airways, promoting further dysbiosis and perpetuating a cycle of inflammation and disordered microbiota. Differences in the composition of baseline respiratory tract microbiota might help to explain the so-called frequent-exacerbator phenotype observed in several disease states, and might provide novel targets for therapeutic intervention.
Severe Covid-19 Berlin, David A; Gulick, Roy M; Martinez, Fernando J
The New England journal of medicine,
12/2020, Letnik:
383, Številka:
25
Journal Article
Testicular function is particularly susceptible to vascular insult, resulting in a negative impact on sperm production and quality of the ejaculate. A prompt diagnosis of testicular dysfunction ...enables implementation of appropriate treatment, hence improving fertility forecasts for stallions. The present research aims to: (1) assess if Doppler ultrasonography is a good tool to diagnose stallions with testicular dysfunction; (2) to study the relationship between Doppler parameters of the testicular artery and those of sperm quality assessed by flow cytometry and (3) to establish cut off values to differentiate fertile stallions from those with pathologies causing testicular dysfunction. A total of 10 stallions (n: 7 healthy stallions and n: 3 sub-fertile stallions) were used in this study. Two ejaculates per stallion were collected and preserved at 5°C in a commercial extender. The semen was evaluated at T0, T24 and T48h by flow cytometry. Integrity and viability of sperm (YoPro®-1/EthD-1), mitochondrial activity (MitoTracker® Deep Red FM) and the DNA fragmentation index (Sperm Chromatin Structure Assay) were assessed. Doppler parameters were measured at three different locations on the testicular artery (Supratesticular artery (SA); Capsular artery (CA) and Intratesticular artery (IA)). The Doppler parameters calculated were: Resistive Index (RI), Pulsatility Index (PI), Peak Systolic Velocity (PSV), End Diastolic Velocity (EDV), Time Average Maximum Velocity (TAMV), Total Arterial Blood Flow (TABF) and TABF rate. The capsular artery was the most reliable location to carry out spectral Doppler assessment, since blood flow parameters of this artery were most closely correlated with sperm quality parameters. Significant differences in all the Doppler parameters studied were observed between fertile and subfertile stallions (p ≤ 0.05). The principal components analysis assay determined that fertile stallions are characterized by high EDV, TAMV, TABF and TABF rate values (high vascular perfusion). In contrast, subfertile stallions tend to present high values of PI and RI (high vascular resistance). The ROC curves revealed that the best Doppler parameters to predict sperm quality in stallions were: Doppler velocities (PSV, EDV and TAMV), the diameter of the capsular artery and TABF parameters (tissue perfusion parameters). Cut off values were established using a Youden´s Index to identify fertile stallions from stallions with testicular dysfunction. Spectral Doppler ultrasound is a good predictive tool for sperm quality since correlations were determined among Doppler parameters and markers of sperm quality. Doppler ultrasonography could be a valuable diagnostic tool for use by clinical practitioners for the diagnosis of stallions with testicular dysfunction and could be a viable alternative to invasive procedures traditionally used for diagnosis of sub-fertility disorders.
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