The atmospheres of mars, venus and jupiter

Planetary atmosphere composition, temperature, and pressure of Mars, Venus, and Jupite

Results of the Mariner 6 and 7 Mars occultation experiments

Final profiles of temperature, pressure, and electron density on Mars were obtained for the Mariner 6 and 7 entry and exit cases, and results are presented for both the lower atmosphere and ionosphere. The results of an analysis of the systematic and formal errors introduced at each stage of the data-reduction process are also included. At all four occulation points, the lapse rate of temperature was subdadiabatic up to altitudes in excess of 20 km. A pronounced temperature inversion was present above the surface at the Mariner 6 exit point. All four profiles exhibit a sharp, superadiabatic drop in temperature at high altitudes, with temperatures falling below the frost point of CO2. These results give a strong indication of frozen CO2 in the middle atmosphere of Mars

Emergence of hexatic and long-range herringbone order in two-dimensional smectic liquid crystals : A Monte Carlo study

Using a high resolution Monte Carlo simulation technique based on multi-histogram method and cluster-algorithm, we have investigated critical properties of a coupled XY model, consists of a six-fold symmetric hexatic and a three-fold symmetric herringbone field, in two dimensions. The simulation results demonstrate a series of novel continues transitions, in which both long-range hexatic and herringbone orderings are established simultaneously. It is found that the specific-heat anomaly exponents for some regions in coupling constants space are in excellent agreement with the experimentally measured exponents extracted from heat-capacity data near the smecticA-hexaticB transition of two-layer free standing film

Nitrogen deficiency in barley (<i>Hordeum vulgare)</i> seedlings induces molecular and metabolic adjustments that trigger aphid resistance

Agricultural N2O pollution resulting from the use of synthetic fertilisers represents a significant contribution to anthropogenic greenhouse gas emissions, providing a rationale for reduced use of nitrogen fertilisers. Nitrogen limitation results in extensive systems rebalancing that remodels metabolism and defence processes. To analyse the regulation underpinning these responses, barley (Horedeum vulgare) seedlings were grown for seven days under nitrogen-deficient conditions until net photosynthesis was 50% lower than in nitrogen-replete controls. Although shoot growth was decreased there was no evidence for the induction of oxidative stress despite lower total concentrations of nitrogen containing antioxidants. Nitrogen deficient barley leaves were rich in amino acids, sugars and tricarboxylic acid cycle intermediates. In contrast to N-replete leaves one day old nymphs of the green peach aphid (Myzus persicae) failed to reach adulthood when transferred to N-deficient barley leaves. Transcripts encoding cell, sugar and nutrient signalling, protein degradation and secondary metabolism were over-represented in nitrogen-deficient leaves while those associated with hormone metabolism were similar under both nutrient regimes with the exception of mRNAs encoding proteins involved in auxin metabolism and responses. Significant similarities were observed between the N-limited barley leaf transcriptome and that of aphid infested Arabidopsis leaves. These findings not only highlight significant similarities between biotic and abiotic stress signalling cascades but also identify potential targets for increasing aphid resistance with implications for the development of sustainable agriculture

Coevolved mutations reveal distinct architectures for two core proteins in the bacterial flagellar motor

Switching of bacterial flagellar rotation is caused by large domain movements of the FliG protein triggered by binding of the signal protein CheY to FliM. FliG and FliM form adjacent multi-subunit arrays within the basal body C-ring. The movements alter the interaction of the FliG C-terminal (FliGC) "torque" helix with the stator complexes. Atomic models based on the Salmonella entrovar C-ring electron microscopy reconstruction have implications for switching, but lack consensus on the relative locations of the FliG armadillo (ARM) domains (amino-terminal (FliGN), middle (FliGM) and FliGC) as well as changes during chemotaxis. The generality of the Salmonella model is challenged by the variation in motor morphology and response between species. We studied coevolved residue mutations to determine the unifying elements of switch architecture. Residue interactions, measured by their coevolution, were formalized as a network, guided by structural data. Our measurements reveal a common design with dedicated switch and motor modules. The FliM middle domain (FliMM) has extensive connectivity most simply explained by conserved intra and inter-subunit contacts. In contrast, FliG has patchy, complex architecture. Conserved structural motifs form interacting nodes in the coevolution network that wire FliMM to the FliGC C-terminal, four-helix motor module (C3-6). FliG C3-6 coevolution is organized around the torque helix, differently from other ARM domains. The nodes form separated, surface-proximal patches that are targeted by deleterious mutations as in other allosteric systems. The dominant node is formed by the EHPQ motif at the FliMMFliGM contact interface and adjacent helix residues at a central location within FliGM. The node interacts with nodes in the N-terminal FliGc α-helix triad (ARM-C) and FliGN. ARM-C, separated from C3-6 by the MFVF motif, has poor intra-network connectivity consistent with its variable orientation revealed by structural data. ARM-C could be the convertor element that provides mechanistic and species diversity.JK was supported by Medical Research Council grant U117581331. SK was supported by seed funds from Lahore University of Managment Sciences (LUMS) and the Molecular Biology Consortium

Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan

Urban pluvial flooding (UPF) has emerged as a serious natural hazard, especially in recent years. Previous research on UPF prediction has mainly focused on hydrological models, which required a large amount of data. However, a data-driven method can significantly reduce the computational cost by using rainfall amounts to predict pluvial flooding. Intensity-duration-frequency (IDF) curves using the Gumbel method can provide a better interpretation of the correlation between rainfall intensity, duration, and probability of occurrence of a given rainfall amount. In this study, machine learning models (ML) for rainfall amounts were used to identify flood points in a case study conducted in Karachi, Pakistan. Thirteen inundation factors were used for the ML models, including a new factor, curve number. Ten ML models were applied first on training and then on validation data, yielding the inundation points. The training and validation process of the model included 384 flood points. Several statistics were used to verify the performance and accuracy of the model. We found that the Light Gradient Boost Machine and Random Forest Classifier models were the most accurate in training and validating the model, while the Decision Tree and K-Nearest Neighbor models were the least accurate in training and validating the model. The study provides valuable information for decision makers to protect communities from flood hazards by incorporating the likely intensity and duration of rainfall events and carefully selecting influencing factors into flood event prediction models

Functional analysis of Ectodysplasin-A mutations causing selective tooth agenesis.

Mutations of the Ectodysplasin-A (EDA) gene are generally associated with the syndrome hypohidrotic ectodermal dysplasia (MIM 305100), but they can also manifest as selective, non-syndromic tooth agenesis (MIM300606). We have performed an in vitro functional analysis of six selective tooth agenesis-causing EDA mutations (one novel and five known) that are located in the C-terminal tumor necrosis factor homology domain of the protein. Our study reveals that expression, receptor binding or signaling capability of the mutant EDA1 proteins is only impaired in contrast to syndrome-causing mutations, which we have previously shown to abolish EDA1 expression, receptor binding or signaling. Our results support a model in which the development of the human dentition, especially of anterior teeth, requires the highest level of EDA-receptor signaling, whereas other ectodermal appendages, including posterior teeth, have less stringent requirements and form normally in response to EDA mutations with reduced activity

Effect of impeller type and rotational speed on flow behavior in fully baffled mixing tank

This paper reports the results of numerical study undertaken to investigate the effect of different impeller types and rotational speed on velocity field in mixing tank. The hydrodynamic of the flow in standard mixing tank generated by two impellers, Chemineer S-4 impeller (radial flow), Pitched Blade impeller (axial flow) is studied. Using ANSYS FLUENT v15.4. is used to solve the continuity and momentum equations incorporating the RNG K-ε turbulence model with the standard wall function available in Fluent. The multiple frames of reference (MFR) model is used for impeller modeling. The results show that the mixing performance of Chemineer impeller is better than the Pitched blade impeller at the same level of rotation speed

Towards the Application of Uncertainty Analysis in Architectural Design Decision-Making

To this day, proper handling of uncertainties -including unknown variables in primary stages of a design, an actual climate data, occupants` behavior, and degradation of material properties over the time- remains as a primary challenge in an architectural design decision-making process. For many years, conventional methods based on the architects' intuition have been used as a standard approach dealing with uncertainties and estimating the resulting errors. However, with buildings reaching great complexity in both their design and material selections, conventional approaches come short to account for ever-existing but unpredictable uncertainties and prove incapable of meeting the growing demand for precise and reliable predictions. This study aims to develop a probability-based framework and associated prototypes to employ uncertainty analysis and sensitivity analysis in architectural design decision-making. The current research explores an advanced physical model for thermal energy exchange characteristics of a hypothetical building and uses it as a test case to demonstrate the proposed probability-based analysis framework. The proposed framework provides a means to employ uncertainty and sensitivity analysis to improve reliability and effectiveness in a buildings design decision-making process