Numerical Feasibility Study for Treated Wastewater Recharge as a Tool to Impede Saltwater Intrusion in the Coastal Aquifer of Gaza – Palestine

The ongoing depletion of the coastal aquifer in the Gaza strip due to groundwater overexploitation has led to the process of seawater intrusion, which is continually becoming a serious problem in Gaza, as the seawater has further invaded into many sections along the coastal shoreline. As a first step to get a hold on the problem, the artificial neural network (ANN)-model has been applied as a new approach and an attractive tool to study and predict groundwater levels without applying physically based hydrologic parameters, and also for the purpose to improve the understanding of complex groundwater systems and which is able to show the effects of hydrologic, meteorological and anthropogenic impacts on the groundwater conditions. Prediction of the future behaviour of the seawater intrusion process in the Gaza aquifer is thus of crucial importance to safeguard the already scarce groundwater resources in the region. In this study the coupled three-dimensional groundwater flow and density-dependent solute transport model SEAWAT, as implemented in Visual MODFLOW, is applied to the Gaza coastal aquifer system to simulate the location and the dynamics of the saltwater–freshwater interface in the aquifer in the time period 2000-2010. A very good agreement between simulated and observed TDS salinities with a correlation coefficient of 0.902 and 0.883 for both steady-state and transient calibration is obtained. After successful calibration of the solute transport model, simulation of future management scenarios for the Gaza aquifer have been carried out, in order to get a more comprehensive view of the effects of the artificial recharge planned in the Gaza strip for some time on forestall, or even to remedy, the presently existing adverse aquifer conditions, namely, low groundwater heads and high salinity by the end of the target simulation period, year 2040. To that avail, numerous management scenarios schemes are examined to maintain the ground water system and to control the salinity distributions within the target period 2011-2040. In the first, pessimistic scenario, it is assumed that pumping from the aquifer continues to increase in the near future to meet the rising water demand, and that there is not further recharge to the aquifer than what is provided by natural precipitation. The second, optimistic scenario assumes that treated surficial wastewater can be used as a source of additional artificial recharge to the aquifer which, in principle, should not only lead to an increased sustainable yield of the latter, but could, in the best of all cases, revert even some of the adverse present-day conditions in the aquifer, i.e., seawater intrusion. This scenario has been done with three different cases which differ by the locations and the extensions of the injection-fields for the treated wastewater. The results obtained with the first (do-nothing) scenario indicate that there will be ongoing negative impacts on the aquifer, such as a higher propensity for strong seawater intrusion into the Gaza aquifer. This scenario illustrates that, compared with 2010 situation of the baseline model, at the end of simulation period, year 2040, the amount of saltwater intrusion into the coastal aquifer will be increased by about 35 %, whereas the salinity will be increased by 34 %. In contrast, all three cases of the second (artificial recharge) scenario group can partly revert the present seawater intrusion. From the water budget point of view, compared with the first (do nothing) scenario, for year 2040, the water added to the aquifer by artificial recharge will reduces the amount of water entering the aquifer by seawater intrusion by 81, 77and 72 %, for the three recharge cases, respectively. Meanwhile, the salinity in the Gaza aquifer will be decreased by 15, 32 and 26% for the three cases, respectively.

Unveiling the components of the signaling pathway between endosomes and the phagocytic uptake machinery in Dictyostelium discoideum

The soil amoebae Dictyostelium discoideum take up particles from their environment in order to obtain nutrition. The particle transits through the cell within a phagosome that fuses with organelles of different molecular compositions, undergoing a gradual degradation by different sets of hydrolytic enzymes. Griffiths’ concept of “phagosome individuality” predicts signaling from phagosomes into the cytoplasm, which might regulate many aspects of cell physiology. The finding that Dictyostelium cells depleted of the lysozyme AlyA or over-expressing the esterase Gp70 exhibit increased uptake of food particles, led to the postulation of a signaling cascade between endocytic compartments and the cytoskeletal uptake machinery at the plasma membrane. Assuming that Gp70 acts downstream of AlyA, gene-expression profiling of both mutants revealed different and overlapping sets of misregulated genes that might participate in this signaling cascade. Based on these results, we analyzed the effects of the artificial misregulation of six candidate genes by over-expression or negative genetic interference, in order to reconstruct at least part of the signaling pathway. SSB420 and SSL793 were chosen as candidates for the first signaling step, as they were up-regulated in AlyA-null cells and remained unaltered in the Gp70 over-expressing cells. The over-expression of SSB420 enhanced phagocytosis and raised the expression levels of Gp70, supporting its involvement in the signaling pathway between AlyA and Gp70 as a positive regulator of phagocytosis. However, this was not the case of cells over-expressing SSL793, as this mutation had no effects on phagocytosis. For the signaling downstream of Gp70, we studied four commonly misregulated genes in AlyA-depleted and Gp70 over-expressing cells. The expression levels of SLB350, SSB389 and TipD were lower in both mutants and therefore these were assumed as possible candidates for the negative regulation of phagocytosis. Cells depleted of SLB350 exhibited an increased phagocytic activity and no effect on Gp70 expression, proving its participation in the signaling pathway downstream of Gp70. Unlike SLB350, the disruption of the genes coding for SSB389 and TipD had no effects on particle uptake, excluding them from the pathway. The fourth candidate was Yipf1, the only gene that was commonly up-regulated in both mutants. Yet, the artificial over-expression of this protein had no effects on phagocytosis, so this candidate is also not included in the signaling pathway. Furthermore, localizing the products of the candidate genes within the cell helped unveiling several cellular organelles that receive signals from the phagosome and transduce them towards the uptake machinery.

Development of thermo-analytical prediction and classification models for food in thermal devices using a multi sensor system and artificial neural networks

Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.