Prospecting hydrogen production of Escherichia coli by metabolic network modeling

Genome-scale model was applied to analyze the anaerobic metabolism of Escherichia coli. Three different methods were used to find deletions affecting fermentative hydrogen production: flux balance analysis (FBA), algorithm for blocking competing pathways (ABCP), and manual selection. Based on these methods, 81 E. coli mutants possessing one gene deletion were selected and cultivated in batch experiments. Experimental results of H₂ and biomass production were compared against the results of FBA. Several gene deletions enhancing H₂ production were found. Correctness of gene essentiality predictions of FBA for the selected genes was 78% and 77% in glucose and galactose media, respectively. 33% of the mutations that were predicted by FBA to increase H₂ production had a positive effect in experiments. Batch cultivation is a simple and straightforward experimental way to screen improvements in H₂ production. However, the ability of FBA to predict the H₂ production rate cannot be evaluated by batch experiments. Metabolic network models provide a method for gaining broader understanding of the complicated metabolic system of a cell and can aid in prospecting suitable gene deletions for enhancing H₂ production.     

Fermentative hydrogen production by Clostridium butyricum and Escherichia coli in pure and cocultures

The effect of coculture of Clostridium butyricum and Escherichia coli on hydrogen production was investigated. C. butyricum and E. coli were grown separately and together as batch cultures. Gas production, growth, volatile fatty acid production and glucose degradation were monitored. Whilst C. butyricum alone produced 2.09 mol-H₂/mol-glucose the coculture produced 1.65 mol-H₂/mol-glucose. However, the coculture utilized glucose more efficiently in the batch culture, i.e., it was able to produce more H₂ (5.85 mmol H₂) in the same cultivation setting than C. butyricum (4.62 mmol H₂), before the growth limiting pH was reached.     

Early physics results

For the past year, experiments at the Large Hadron Collider (LHC) have started exploring physics at the high-energy frontier. Thanks to the superb turn-on of the LHC, a rich harvest of initial physics results have already been obtained by the two general-purpose experiments A Toroidal LHC Apparatus (ATLAS) and the Compact Muon Solenoid (CMS), which are the subject of this report. The initial data have allowed a test, at the highest collision energies ever reached in a laboratory, of the Standard Model (SM) of elementary particles, and to make early searches Beyond the Standard Model (BSM). Significant results have already been obtained in the search for the Higgs boson, which would establish the postulated electro-weak symmetry breaking mechanism in the SM, as well as for BSM physics such as Supersymmetry (SUSY), heavy new particles, quark compositeness and others. The important, and successful, SM physics measurements are giving confidence that the experiments are in good shape for their journey into the uncharted territory of new physics anticipated at the LHC.     

Temperature dependence and interferences of NO and N₂O microelectrodes used in wastewater treatment

Electrodes for nitric and nitrous oxide have been on the market for some time, but have not yet been tested for an application in wastewater treatment processes. Both sensors were therefore assessed with respect to their (non)linear response, temperature dependence and potential cross sensitivity to dissolved compounds, which are present and highly dynamic in nitrogen conversion processes (nitric oxide, nitrous oxide, nitrogen dioxide, ammonia, hydrazine, hydroxylamine, nitrous acid, oxygen, and carbon dioxide). Off-gas measurements were employed to differentiate between cross sensitivity to interfering components and chemical nitric oxide or nitrous oxide production. Significant cross sensitivities were detected for both sensors: by the nitrous oxide sensor to nitric oxide and by the nitric oxide sensor to ammonia, hydrazine, hydroxylamine and nitrous acid. These interferences could, however, be removed by correction functions. Temperature fluctuations in the range of ±1 °C lead to artifacts of ±3.5% for the nitric oxide and ±3.9% for the nitrous oxide sensor and can be corrected with exponential equations. The results from this study help to significantly shorten and optimize the determination of the correction functions and are therefore relevant for all users of nitric and nitrous oxide electrodes.     

Spatial Velocity Distributions in the Ascending Aorta of Healthy Humans and Cardiac Patients

Blood velocity profiles in the human ascending aorta were assessed with the aid of ultrasonic Doppler echocardiography. To this end, the transducer was placed in the suprasternal notch, and the spatial velocity profiles along an axis passing through the center of the aortic cross section were recorded by a multigate Doppler instrument. The profiles are analyzed with respect to characteristics independent of the angle of incidence and the cross sectional area. Data from 10 healthy individuals, 10 patients with hypertrophic obstructive cardiomyopathy (HOCM), and 10 patients with severe aortic insufficiency (AI) are compared. Five instantaneous profiles recorded at different times during systole and the temporal average of all profiles recorded during the entire cardiac cycle at 16 ms intervals are examined. Considerable differences between the three groups of subjects are observed visually as well as quantitatively in terms of specific parameters. The representation of the velocity maps in the form of contour graphs is particularly incisive. The results demonstrate that the temporal velocity patterns measured depend, in general, on both the disease and the location of the sampling volume within the aortic lumen. Reliable aortic volume flow rate measurements may have to be based on a method which takes into account the velocity at every point of the entire vascular cross section of patients with HOCM or AI.     

Semantic Based Greedy Levy Gradient Boosting Algorithm for Phishing Detection

The detection of phishing and legitimate websites is considered a great challenge for web service providers because the users of such websites are indistinguishable. Phishing websites also create traffic in the entire network. Another phishing issue is the broadening malware of the entire network, thus highlighting the demand for their detection while massive datasets (i.e., big data) are processed. Despite the application of boosting mechanisms in phishing detection, these methods are prone to significant errors in their output, specifically due to the combination of all website features in the training state. The upcoming big data system requires MapReduce, a popular parallel programming, to process massive datasets. To address these issues, a probabilistic latent semantic and greedy levy gradient boosting (PLS-GLGB) algorithm for website phishing detection using MapReduce is proposed. A feature selection-based model is provided using a probabilistic intersective latent semantic preprocessing model to minimize errors in website phishing detection. Here, the missing data in each URL are identified and discarded for further processing to ensure data quality. Subsequently, with the preprocessed features (URLs), feature vectors are updated by the greedy levy divergence gradient (model) that selects the optimal features in the URL and accurately detects the websites. Thus, greedy levy efficiently differentiates between phishing websites and legitimate websites. Experiments are conducted using one of the largest public corpora of a website phish tank dataset. Results show that the PLS-GLGB algorithm for website phishing detection outperforms state-of-the-art phishing detection methods. Significant amounts of phishing detection time and errors are also saved during the detection of website phishing.     

Changes in microstructures and physical properties of polymer-modified mortars during wet storage

The decrease in strength of tile adhesive mortars during wet storage was investigated. In a first approach, the water resistance of the polymer phases was tested on structures isolated from the mortar and in situ. It was observed that cellulose ether and polyvinyl alcohol structures are water-soluble. Subsequent investigations on polymer mobility within the mortar showed that the migrating pore water transports cellulose ether and polyvinyl alcohol during periods of water intrusion and drying. This leads to enrichments at the mortar-substrate interface. In contrast, latices interacting with the cement are water-resistant, and therefore, immobile in the mortar. Further experiments revealed that the mortar underwent considerable volume changes depending on the storage condition. Cracking occurred mainly close to the mortar-tile interface, cement hydrates grew within these shrinkage or expansion cracks. Test results revealed that the strength decrease of wet stored tile adhesives is caused by different mechanisms related to cement hydration, volume changes of the mortar, and reversible swelling of latex films.     

High surface area nanostructured tubes prepared by dissolution of ALD-coated electrospun fibers

Novel nanostructured and high surface area tubular materials were produced combining electrospinning and atomic layer deposition processes with the removal of polymeric template via dissolution. The dissolution process changed the structure of the tube walls, and the smooth atomic layer deposition coating was transformed into a highly complex, coral-like structure. This material, which we have called “nanocoral,” has a relatively high surface area, 323 m² g⁻¹, due to the interconnected cavities formed after the removal of the template. This kind of material has important potential applications, for example, in the fields of catalysts and filtration.