Water discharge and sediment flux changes in the Lower Mekong River

International audienceThe Lower Mekong River has witnessed extremely low water levels over the past few years. There is speculation that the changes are a consequence of the construction and operation of the Chinese cascade dams in the upper part of the Mekong main stream, the Lancang River. Dam construction on upper streams can produce a series of induced effects downstream, particularly in terms of water, sediment, channel and ecological changes. The infilling of the Manwan reservoir in 1992 caused water levels to fall to record lows in various parts of the Mekong River, and sediment concentration values decreased similarly. Analyses of discharge and sediment flux at various gauging stations on the Lower Mekong River have indicated a disruption in water discharge, water fluctuations and sediment transport downstream of the Manwan Dam, after its reservoir was infilled in 1992. Dry season flows showed a declining trend, and water level fluctuations in the dry season increased considerably in the post-dam (1993?2000) period. Monthly suspended sediment concentration (SSC) has also decreased significantly in several gauging stations in the post-dam period. The estimation of sediment flux is challenging since the measurements of SSC were sporadic. Our estimation based on the available data indicated that the areas along the upper-middle and lowermost reaches of the Mekong River have experienced a decline in sediment flux, possibly due to sedimentation in the Manwan Dam. However, the decrease is only statistically significant at Chiang Saen. Areas located in the mid-length of the river show less sensitivity to the operation of the Manwan Dam, as sediment fluxes have remained stable or even increased in the post-dam period

Syngas Production from Glycerol-dry(CO2) Reforming Over La-promoted Ni/Al2O3 Catalyst

A 3 wt% La-promoted Ni/Al2O3 catalyst was prepared via wet co-impregnation technique and physicochemically-characterized. Lanthanum was responsible for better metal dispersion; hence higher BET specific surface area (96.0 m2 g−1) as compared to the unpromoted Ni/Al2O3 catalyst (85.0 m2 g−1). In addition, the La-promoted catalyst possessed finer crystallite size (9.1 nm) whilst the unpromoted catalyst measured 12.8 nm. Subsequently, glycerol dry reforming was performed at atmospheric pressure and temperatures ranging from 923 to 1123 K employing CO2-to-glycerol ratio from zero to five. Significantly, the reaction results have yielded syngas as main gaseous products with H2:CO ratios always below than 2.0 with concomitant maximum 96% glycerol conversion obtained at the CO2-to-glycerol ratio of 1.67. In addition, the glycerol consumption rate can be adequately captured using power law modelling with the order of reactions equal 0.72 and 0.14 with respect to glycerol and CO2 whilst the activation energy was 35.0 kJ mol−1. A 72 h longevity run moreover revealed that the catalyst gave a stable catalytic performance

Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

©2008 Pandit and Skolnick; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is available from: http://www.biomedcentral.com/1471-2105/9/531doi:10.1186/1471-2105-9-531Background: Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true. Results: To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TMalign, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr- TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align. Conclusion: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr- TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/

Minimal SUSY SO(10) model and predictions for neutrino mixings and leptonic CP violation

We discuss a minimal Supersymmetric SO(10) model where B-L symmetry is broken by a {\bf 126} dimensional Higgs multiplet which also contributes to fermion masses in conjunction with a {\bf 10} dimensional superfield. This minimal Higgs choice provides a partial unification of neutrino flavor structure with that of quarks and has been shown to predict all three neutrino mixing angles and the solar mass splitting in agreement with observations, provided one uses the type II seesaw formula for neutrino masses. In this paper we generalize this analysis to include arbitrary CP phases in couplings and vevs. We find that (i) the predictions for neutrino mixings are similar with $U_{e3}\simeq 0.18$ as before and other parameters in a somewhat bigger range and (ii) that to first order in the quark mixing parameter $\lambda$ (the Cabibbo angle), the leptonic mixing matrix is CP conserving. We also find that in the absence of any higher dimensional contributions to fermion masses, the CKM phase is different from that of the standard model implying that there must be new contributions to quark CP violation from the supersymmetry breaking sector. Inclusion of higher dimensional terms however allows the standard model CKM phase to be maintained.Comment: 22 pages, 6 figure

Using network science in the language sciences and clinic

A number of variables—word frequency, word length—have long been known to influence language processing. We briefly review the effects in speech perception and production of two more recently examined variables: phonotactic probability and neighborhood density. We then describe a new approach to study language, network science, which is an interdisciplinary field drawing from mathematics, computer science, physics, and other disciplines. In this approach, nodes represent individual entities in a system (i.e., phonological word-forms in the lexicon), links between nodes represent relationships between nodes (i.e., phonological neighbors), and various measures enable researchers to assess the micro-level (i.e., the individual word), the macro-level (i.e., characteristics about the whole system), and the meso-level (i.e., how an individual fits into smaller sub-groups in the larger system). Although research on individual lexical characteristics such as word-frequency has increased our understanding of language processing, these measures only assess the “micro-level.” Using network science, researchers can examine words at various levels in the system, and how each word relates to the many other words stored in the lexicon. Several new findings using the network science approach are summarized to illustrate how this approach can be used to advance basic research as well as clinical practice

Total anomalous pulmonary venous connection: Outcome of postoperative pulmonary venous obstruction

ObjectivePulmonary venous obstruction (PVO) is an important cause of late mortality in total anomalous pulmonary venous connection (TAPVC). We aimed to describe current practices for the management of postoperative PVO and the efficacy of the different interventional procedures.MethodsWe conducted a retrospective international collaborative population-based study involving 19 pediatric cardiac centers in the United Kingdom, Ireland, and Sweden. Patients with TAPVC born between January 1, 1998, and December 31, 2004, were identified. Patients with functionally univentricular circulation or atrial isomerism were excluded. All available data and images were reviewed.ResultsOf 406 patients undergoing repair of TAPVC, 71 (17.5%) had postoperative PVO. The diagnosis was made within 6 months of surgery in 59 (83%) of the 71 patients. In 12, serial imaging documented change in appearance of the pulmonary veins. Good-sized pulmonary veins can progress to diffusely small veins and rarely atresia. Patients presenting after 6 months had less severe disease; all are alive at most recent follow-up. Fifty-six (13.8%) of 406 patients underwent intervention for postoperative PVO: 44 had surgical treatment and 12 had an initial catheter intervention. One half underwent 1 or more reinterventions. Three-year survival for patients with postoperative PVO was 58.7% (95% confidence intervals, 46.2%-69.2%) with a trend that those having a surgical strategy did better (P = .083). Risk factors for death included earlier presentation after TAPVC repair, diffusely small pulmonary veins at presentation of postoperative PVO, and an increased number of lung segments affected by obstruction.ConclusionsPostoperative PVO tends to appear in the first 6 months after TAPVC repair and can be progressive. Early intervention for PVO may be indicated before irreversible secondary changes occur

Detection of distant evolutionary relationships between protein families using theory of sequence profile-profile comparison

<p>Abstract</p> <p>Background</p> <p>Detection of common evolutionary origin (homology) is a primary means of inferring protein structure and function. At present, comparison of protein families represented as sequence profiles is arguably the most effective homology detection strategy. However, finding the best way to represent evolutionary information of a protein sequence family in the profile, to compare profiles and to estimate the biological significance of such comparisons, remains an active area of research.</p> <p>Results</p> <p>Here, we present a new homology detection method based on sequence profile-profile comparison. The method has a number of new features including position-dependent gap penalties and a global score system. Position-dependent gap penalties provide a more biologically relevant way to represent and align protein families as sequence profiles. The global score system enables an analytical solution of the statistical parameters needed to estimate the statistical significance of profile-profile similarities. The new method, together with other state-of-the-art profile-based methods (HHsearch, COMPASS and PSI-BLAST), is benchmarked in all-against-all comparison of a challenging set of SCOP domains that share at most 20% sequence identity. For benchmarking, we use a reference ("gold standard") free model-based evaluation framework. Evaluation results show that at the level of protein domains our method compares favorably to all other tested methods. We also provide examples of the new method outperforming structure-based similarity detection and alignment. The implementation of the new method both as a standalone software package and as a web server is available at <url>http://www.ibt.lt/bioinformatics/coma</url>.</p> <p>Conclusion</p> <p>Due to a number of developments, the new profile-profile comparison method shows an improved ability to match distantly related protein domains. Therefore, the method should be useful for annotation and homology modeling of uncharacterized proteins.</p

New Perspectives on the Aging Lexicon

The field of cognitive aging has seen considerable advances in describing the linguistic and semantic changes that happen during the adult life span to uncover the structure of the mental lexicon (i.e., the mental repository of lexical and conceptual representations). Nevertheless, there is still debate concerning the sources of these changes, including the role of environmental exposure and several cognitive mechanisms associated with learning, representation, and retrieval of information. We review the current status of research in this field and outline a framework that promises to assess the contribution of both ecological and psychological aspects to the aging lexicon

Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction

Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represented as a machine learning problem, where neural networks are used to learn the native-like features of protein structures using a set of positive and negative training examples. A set of native protein structures provides the positive training examples, while negative training examples are simulated decoy structures obtained by reversing the sequences of native structures. Various features are extracted from the training dataset of positive and negative examples and used as inputs to the neural networks.Results: Results have shown that the best performing neural network is the one that uses input information comprising of PSI-BLAST [1] profiles of residue pairs, pairwise distance and the relative solvent accessibilities of the residues. This neural network is the best among all methods tested in discriminating the native structure from a set of decoys for all decoy datasets tested. Conclusion: This method is demonstrated to be viable, and furthermore evolutionary information is successfully used in the neural networks to improve decoy discrimination