Influence of surface passivation on ultrafast carrier dynamics and terahertz radiation generation in GaAs

The carrier dynamics of photoexcited electrons in the vicinity of the surface of (NH4)2S-passivated GaAs were studied via terahertz (THz) emission spectroscopy and optical-pump THz-probe spectroscopy. THz emission spectroscopy measurements, coupled with Monte Carlo simulations of THz emission, revealed that the surface electric field of GaAs reverses after passivation. The conductivity of photoexcited electrons was determined via optical-pump THz-probe spectroscopy, and was found to double after passivation. These experiments demonstrate that passivation significantly reduces the surface state density and surface recombination velocity of GaAs. Finally, we have demonstrated that passivation leads to an enhancement in the power radiated by photoconductive switch THz emitters, thereby showing the important influence of surface chemistry on the performance of ultrafast THz photonic devices.Comment: 4 pages, 3 figures, to appear in Applied Physics Letter

Applying metrological techniques to satellite fundamental climate data records

Quantifying long-term environmental variability, including climatic trends, requires decadal-scale time series of observations. The reliability of such trend analysis depends on the long-term stability of the data record, and understanding the sources of uncertainty in historic, current and future sensors. We give a brief overview on how metrological techniques can be applied to historical satellite data sets. In particular we discuss the implications of error correlation at different spatial and temporal scales and the forms of such correlation and consider how uncertainty is propagated with partial correlation. We give a form of the Law of Propagation of Uncertainties that considers the propagation of uncertainties associated with common errors to give the covariance associated with Earth observations in different spectral channels

Evolving toward a human-cell based and multiscale approach to drug discovery for CNS disorders

A disruptive approach to therapeutic discovery and development is required in order to significantly improve the success rate of drug discovery for central nervous system (CNS) disorders. In this review, we first assess the key factors contributing to the frequent clinical failures for novel drugs. Second, we discuss cancer translational research paradigms that addressed key issues in drug discovery and development and have resulted in delivering drugs with significantly improved outcomes for patients. Finally, we discuss two emerging technologies that could improve the success rate of CNS therapies: human induced pluripotent stem cell (hiPSC)-based studies and multiscale biology models. Coincident with advances in cellular technologies that enable the generation of hiPSCs directly from patient blood or skin cells, together with methods to differentiate these hiPSC lines into specific neural cell types relevant to neurological disease, it is also now possible to combine data from large-scale forward genetics and post-mortem global epigenetic and expression studies in order to generate novel predictive models. The application of systems biology approaches to account for the multiscale nature of different data types, from genetic to molecular and cellular to clinical, can lead to new insights into human diseases that are emergent properties of biological networks, not the result of changes to single genes. Such studies have demonstrated the heterogeneity in etiological pathways and the need for studies on model systems that are patient-derived and thereby recapitulate neurological disease pathways with higher fidelity. In the context of two common and presumably representative neurological diseases, the neurodegenerative disease Alzheimer’s Disease (AD), and the psychiatric disorder schizophrenia (SZ), we propose the need for, and exemplify the impact of, a multiscale biology approach that can integrate panomic, clinical, imaging, and literature data in order to c

The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences

The iPlant Collaborative provides life science research communities access to comprehensive, scalable, and cohesive computational infrastructure for data management; identity management; collaboration tools; and cloud, high-performance, high-throughput computing. iPlant provides training, learning material, and best practice resources to help all researchers make the best use of their data, expand their computational skill set, and effectively manage their data and computation when working as distributed teams. iPlant's platform permits researchers to easily deposit and share their data and deploy new computational tools and analysis workflows, allowing the broader community to easily use and reuse those data and computational analyses

Selection of a network of large lakes and reservoirs suitable for global environmental change analysis using Earth Observation

The Globo Lakes project, a global observatory of lake responses to environmental change, aims to exploit current satellite missions and long remote-sensing archives to synoptically study multiple lake ecosystems, assess their current condition, reconstruct past trends to system trajectories, and assess lake sensitivity to multiple drivers of change. Here we describe the selection protocol for including lakes in the global observatory based upon remote-sensing techniques and an initial pool of the largest 3721 lakes and reservoirs in the world, as listed in the Global Lakes and Wetlands Database. An 18-year-long archive of satellite data was used to create spatial and temporal filters for the identification of water bodies that are appropriate for remote-sensing methods.Further criteria were applied and tested to ensure the candidate sites span a wide range of ecological settings and characteristics; a total 960 lakes, lagoons, and reservoirs were selected. The methodology proposed here is applicable to new generation satellites,such as the European Space Agency Sentinel-series

The Texas Two-Step Method: Do-It-Yourself Fire Ant Control for Homes and Neighborhoods

8 pp., 3 illustrations, 3 photos, 1 tableThe two-step method is a simple approach to controlling fire ants. The first step is to broadcast a bait insecticide over the entire yard. The second step is to treat individual mounds. The tips in this publication will help you control pesky fire ants in your yard. You can even join with your neighbors in a fire ant block party

Sources of nonlinearities, chatter generation and suppression in metal cutting

The mechanics of chip formation has been revisited in order to understand functional relationships between the process and the technological parameters. This has led to the necessity of considering the chip-formation process as highly nonlinear, with complex interrelations between its dynamics and thermodynamics. In this paper a critical review of the state of the art of modelling and the experimental investigations is outlined with a view to how the nonlinear dynamics perception can help to capture the major phenomena causing instabilities (chatter) in machining operations. The paper is concluded with a case study, where stability of a milling process is investigated in detail, using an analytical model which results in an explicit relation for the stability limit. The model is very practical for the generation of the stability lobe diagrams, which is time consuming when using numerical methods. The extension of the model to the stability analysis of variable pitch cutting tools is also given. The application and verification of the method are demonstrated by several examples

Lake surface temperature [in “State of the Climate in 2017”]

Observed lake surface water temperature anomalies in 2017 are placed in the context of the recent warming observed in global surface air temperature by collating long-term in situ lake surface temperature observations from some of the world’s best-studied lakes and a satellite-derived global lake surface water temperature dataset. The period 1996–2015, 20 years for which satellite-derived lake temperatures are available, is used as the base period for all lake temperature anomaly calculations