Tracking Global Population Trends: Population Time-Series Data and a Living Planet Index for Reptiles

Effective conservation action relies on access to the best-available species data. Reptiles have often been overlooked in conservation prioritization, especially because of a paucity of population data. Using data for 549 reptile populations representing 194 species from the Living Planet database, we provide the first detailed analysis of this database for a specific taxonomic group. We estimated an average global decline in reptile populations of 54–55% between 1970 and 2012. Disaggregated indices at taxonomic, system, and biogeographical levels showed trends of decline, often with wide confidence intervals because of a prevalence of short time series. We assessed gaps in our reptile time-series data and examined what types of publication they primarily originated from to provide an overview of the range of data sources captured in the Living Planet database. Data were biased toward crocodilians and chelonians, with only 1% and 2% of known lizard and snake species represented, respectively. Population time-series data stemmed primarily from published ecological research (squamates) and data collected for conservation management (chelonians and crocodilians). We recommend exploration of novel survey and analytical techniques to increase monitoring of reptiles, especially squamates, over time. Open access publication and sharing of data sets are vital to improve knowledge of reptile status and trends, aided by the provision of properly curated databases and data-sharing agreements. Such collaborative efforts are vital to effectively address global reptile declines

An Evolutionary Approach to Active Robust Multiobjective Optimisation

An Active Robust Optimisation Problem (AROP) aims at finding robust adaptable solutions, i.e. solutions that actively gain robustness to environmental changes through adaptation. Existing AROP studies have considered only a single performance objective. This study extends the Active Robust Optimisation methodology to deal with problems with more than one objective. Once multiple objectives are considered, the optimal performance for every uncertain parameter setting is a set of configurations, offering different trade-offs between the objectives. To evaluate and compare solutions to this type of problems, we suggest a robustness indicator that uses a scalarising function combining the main aims of multi-objective optimisation: proximity, diversity and pertinence. The Active Robust Multi-objective Optimisation Problem is formulated in this study, and an evolutionary algorithm that uses the hypervolume measure as a scalarasing function is suggested in order to solve it. Proof-of-concept results are demonstrated using a simplified gearbox optimisation problem for an uncertain load demand

Sal-type ABC-F proteins: intrinsic and common mediators of pleuromutilin resistance by target protection in staphylococci

The first member of the pleuromutilin (PLM) class suitable for systemic antibacterial chemotherapy in humans recently entered clinical use, underscoring the need to better understand mechanisms of PLM resistance in disease-causing bacterial genera. Of the proteins reported to mediate PLM resistance in staphylococci, the least-well studied to date is Sal(A), a putative ABC-F NTPase that—by analogy to other proteins of this type—may act to protect the ribosome from PLMs. Here, we establish the importance of Sal proteins as a common source of PLM resistance across multiple species of staphylococci. Sal(A) is revealed as but one member of a larger group of Sal-type ABC-F proteins that vary considerably in their ability to mediate resistance to PLMs and other antibiotics. We find that specific sal genes are intrinsic to particular staphylococcal species, and show that this gene family is likely ancestral to the genus Staphylococcus. Finally, we solve the cryo-EM structure of a representative Sal-type protein (Sal(B)) in complex with the staphylococcal 70S ribosome, revealing that Sal-type proteins bind into the E site to mediate target protection, likely by displacing PLMs and other antibiotics via an allosteric mechanism

Thermoplastic Composites reinforced with Multi-layer Woven Jute Fabric: A Comparative Analysis

Three commonly available thermoplastic matrices - High-density polyethylene (HDPE), polypropylene (PP) and nylon 6 – are reinforced with hessian jute fabric in multi-layer sequence to prepare composite laminates by compression moulding technique. The composite had a nominal fibre content of 18% in terms of weight and a nominal thickness of 6.5 mm. The mechanical and fracture behaviours of the resultant laminates are tested and compared. It was found that the Nylon-Jute composite exhibited the highest values of tensile strength, Young’s modulus, flexural strength, flexural modulus and hardness. On the other hand, HDPE-Jute composite showed relatively poor performance. Interestingly, the HDPE-Jute composite exhibited the highest impact strength and the Nylon-Jute composite was the poorest in this regard. The amount of water absorption by the composites from highest to the lowest was found in the following order: Nylon-Jute > HDPE-Jute > PP-Jute

Collision energy dependence of state-to-state differential cross sections for rotationally inelastic scattering of H2O by He

The inelastic scattering of H2O by He as a function of collision energy in the range 381 cm−1 to 763 cm−1 at an energy interval of approximately 100 cm−1 has been investigated in a crossed beam experiment using velocity map imaging. Change in collision energy was achieved by varying the collision angle between the H2O and He beam. We measured the state-to-state differential cross section (DCS) of scattered H2O products for the final rotational states JKaKc = 110, 111, 221 and 414. Rotational excitation of H2O is probed by (2 + 1) resonance enhanced multiphoton ionization (REMPI) spectroscopy. DCS measurements over a wide range of collision energies allowed us to probe the H2O–He potential energy surface (PES) with greater detail than in previous work. We found that a classical approximation of rotational rainbows can predict the collision energy dependence of the DCS. Close-coupling quantum mechanical calculations were used to produce DCS and partial cross sections. The forward–backward ratio (FBR), is introduced here to compare the experimental and theoretical DCS. Both theory and experiments suggest that an increase in the collision energy is accompanied with more forward scattering

Relationship between galactomannan structure and physicochemical properties of films produced thereof

In this work five sources of galactomannans, Adenanthera pavonina, Cyamopsis tetragonolobus, Caesalpinia pulcherrima, Ceratonia siliqua and Sophora japonica, presenting mannose/galactose ratios of 1.3, 1.7, 2.9, 3.4 and 5.6, respectively, were used to produce galactomannan-based films. These films were characterized in terms of: water vapour, oxygen and carbon dioxide permeabilities (WVP, O 2 P and CO 2 P); moisture content, water solubility, contact angle, elongation-at-break (EB), tensile strength (TS) and glass transition temperature (T g ). Results showed that films properties vary according to the galactomannan source (different galactose distribution) and their mannose/galactose ratio. Water affinity of mannan and galactose chains and the intermolecular interactions of mannose backbone should also be considered being factors that affect films properties. This work has shown that knowing mannose/galactose ratio of galactomannans is possible to foresee galactomannan-based edible films properties.The authors thank the fellowship (SFRH/BPD/ 72753/2010) from the Fundação para a Ciência e Tecnologia (FCT, Portugal). The authors also thank the FCT Strategic Project of UID/BIO/ 04469/2013 unit, the project RECI/BBB-EBI/0179/2012 (FCOMP-010124-FEDER-027462) and the project BBioInd - Biotechnology and Bioengineering for improved Industrial and Agro-Food processes, REF. NORTE-07-0124-FEDER-000028 Co-funded by the Programa OperacionalRegionaldoNorte(ON.2–ONovoNorte),QREN,FEDER. Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico – FUNCAP, CE Brazil (CI1-0080-00055.01.00/13)

BRCA1 Regulates Follistatin Function in Ovarian Cancer and Human Ovarian Surface Epithelial Cells

Follistatin (FST), a folliculogenesis regulating protein, is found in relatively high concentrations in female ovarian tissues. FST acts as an antagonist to Activin, which is often elevated in human ovarian carcinoma, and thus may serve as a potential target for therapeutic intervention against ovarian cancer. The breast cancer susceptibility gene 1 (BRCA1) is a known tumor suppressor gene in human breast cancer; however its role in ovarian cancer is not well understood. We performed microarray analysis on human ovarian carcinoma cell line SKOV3 that stably overexpress wild-type BRCA1 and compared with the corresponding empty vector-transfected clones. We found that stable expression of BRCA1 not only stimulates FST secretion but also simultaneously inhibits Activin expression. To determine the physiological importance of this phenomenon, we further investigated the effect of cellular BRCA1 on the FST secretion in immortalized ovarian surface epithelial (IOSE) cells derived from either normal human ovaries or ovaries of an ovarian cancer patient carrying a mutation in BRCA1 gene. Knock-down of BRCA1 in normal IOSE cells demonstrates down-regulation of FST secretion along with the simultaneous up-regulation of Activin expression. Furthermore, knock-down of FST in IOSE cell lines as well as SKOV3 cell line showed significantly reduced cell proliferation and decreased cell migration when compared with the respective controls. Thus, these findings suggest a novel function for BRCA1 as a regulator of FST expression and function in human ovarian cells

An empirical model for probabilistic decadal prediction: global attribution and regional hindcasts

Empirical models, designed to predict surface variables over seasons to decades ahead, provide useful benchmarks for comparison against the performance of dynamical forecast systems; they may also be employable as predictive tools for use by climate services in their own right. A new global empirical decadal prediction system is presented, based on a multiple linear regression approach designed to produce probabilistic output for comparison against dynamical models. A global attribution is performed initially to identify the important forcing and predictor components of the model . Ensemble hindcasts of surface air temperature anomaly fields are then generated, based on the forcings and predictors identified as important, under a series of different prediction ‘modes’ and their performance is evaluated. The modes include a real-time setting, a scenario in which future volcanic forcings are prescribed during the hindcasts, and an approach which exploits knowledge of the forced trend. A two-tier prediction system, which uses knowledge of future sea surface temperatures in the Pacific and Atlantic Oceans, is also tested, but within a perfect knowledge framework. Each mode is designed to identify sources of predictability and uncertainty, as well as investigate different approaches to the design of decadal prediction systems for operational use. It is found that the empirical model shows skill above that of persistence hindcasts for annual means at lead times of up to 10 years ahead in all of the prediction modes investigated. It is suggested that hindcasts which exploit full knowledge of the forced trend due to increasing greenhouse gases throughout the hindcast period can provide more robust estimates of model bias for the calibration of the empirical model in an operational setting. The two-tier system shows potential for improved real-time prediction, given the assumption that skilful predictions of large-scale modes of variability are available. The empirical model framework has been designed with enough flexibility to facilitate further developments, including the prediction of other surface variables and the ability to incorporate additional predictors within the model that are shown to contribute significantly to variability at the local scale. It is also semi-operational in the sense that forecasts have been produced for the coming decade and can be updated when additional data becomes available