Oceans and the Sustainable Development Goals: Co-Benefits, Climate Change & Social Equity

Achieving ocean sustainability is paramount for coastal communities and marine industries, yet is also inextricably linked to much broader global sustainable development—including increased resilience to climate change and improved social equity—as envisioned by the UN 2030 Agenda for Sustainable Development. This report highlights the co-benefits from achieving each SDG 14 target: progress towards each of the other 161 SDG targets when ocean targets are met, given ten-year lag times between ocean targets and other SDG targets. The identification of co-benefits is based on input from more than 30 scientific experts in the Nereus Program. Below we highlight notable co-benefits of achieving each target within SDG 14

A simplified method for determining heat of combustion of natural gas

A simplified technique for determination of the heat of combustion of natural gas has been developed. It is a variation of the previously developed technique wherein the carrier air, in which the test sample was burnt, was oxygen enriched to adjust the mole fraction of oxygen in the combustion product gases up to that in the carrier air. The new technique eliminates the need for oxygen enrichment of the experimental mixtures and natural gas samples and has been found to predict their heats of combustion to an uncertainty of the order of 1 percent

Analysis of positron lifetime spectra in polymers

A new procedure for analyzing multicomponent positron lifetime spectra in polymers was developed. It requires initial estimates of the lifetimes and the intensities of various components, which are readily obtainable by a standard spectrum stripping process. These initial estimates, after convolution with the timing system resolution function, are then used as the inputs for a nonlinear least squares analysis to compute the estimates that conform to a global error minimization criterion. The convolution integral uses the full experimental resolution function, in contrast to the previous studies where analytical approximations of it were utilized. These concepts were incorporated into a generalized Computer Program for Analyzing Positron Lifetime Spectra (PAPLS) in polymers. Its validity was tested using several artificially generated data sets. These data sets were also analyzed using the widely used POSITRONFIT program. In almost all cases, the PAPLS program gives closer fit to the input values. The new procedure was applied to the analysis of several lifetime spectra measured in metal ion containing Epon-828 samples. The results are described

Informal rural healthcare providers in North and South India.

Rural households in India rely extensively on informal biomedical providers, who lack valid medical qualifications. Their numbers far exceed those of formal providers. Our study reports on the education, knowledge, practices and relationships of informal providers (IPs) in two very different districts: Tehri Garhwal in Uttarakhand (north) and Guntur in Andhra Pradesh (south). We mapped and interviewed IPs in all nine blocks of Tehri and in nine out of 57 blocks in Guntur, and then interviewed a smaller sample in depth (90 IPs in Tehri, 100 in Guntur) about market practices, relationships with the formal sector, and their knowledge of protocol-based management of fever, diarrhoea and respiratory conditions. We evaluated IPs' performance by observing their interactions with three patients per condition; nine patients per provider. IPs in the two districts had very different educational backgrounds-more years of schooling followed by various informal diplomas in Tehri and more apprenticeships in Guntur, yet their knowledge of management of the three conditions was similar and reasonably high (71% Tehri and 73% Guntur). IPs in Tehri were mostly clinic-based and dispensed a blend of allopathic and indigenous drugs. IPs in Guntur mostly provided door-to-door services and prescribed and dispensed mainly allopathic drugs. In Guntur, formal private doctors were important referral providers (with commissions) and source of new knowledge for IPs. At both sites, IPs prescribed inappropriate drugs, but the use of injections and antibiotics was higher in Guntur. Guntur IPs were well organized in state and block level associations that had successfully lobbied for a state government registration and training for themselves. We find that IPs are firmly established in rural India but their role has grown and evolved differently in different market settings. Interventions need to be tailored differently keeping in view these unique features

Examining the Role of Social Network Size and the Structural Holes

This study examines the importance of social network size and structural holes within the network to the entrepreneurial opportunity recognition process

Optical response of electrons in a random potential

Using our recently developed Chebyshev expansion technique for finite-temperature dynamical correlation functions we numerically study the AC conductivity $\sigma(\omega)$ of the Anderson model on large cubic clusters of up to $100^3$ sites. Extending previous results we focus on the role of the boundary conditions and check the consistency of the DC limit, $\omega\to 0$, by comparing with direct conductance calculations based on a Greens function approach in a Landauer B\"uttiker type setup.Comment: 2 pages, 3 figs, submitted to SCES'0

Shop Talk: Annual Drosophila Research Conference, 2010

This year, the Genetics Society of America (GSA) received a record-breaking number of registrants to the conference. Despite low attendance at other scientific meetings, according to GSA Meetings Manager, Suzy Brown, this year’s conference had the ‘‘largest number of registrants than any other previous years.’’ There were 170 talks, more than 850 posters and 13 workshops; so there was a range of information that people could pick according to their interests

Project Exodus

A design for a manned Mars mission, PROJECT EXODUS is presented. PROJECT EXODUS incorporates the design of a hypersonic waverider, cargo ship and NIMF (nuclear rocket using indigenous Martian fuel) shuttle lander to safely carry out a three to five month mission on the surface of Mars. The cargo ship transports return fuel, return engine, surface life support, NIMF shuttle, and the Mars base to low Mars orbit (LMO). The cargo ship is powered by a nuclear electric propulsion (NEP) system which allows the cargo ship to execute a spiral trajectory to Mars. The waverider transports ten astronauts to Mars and back. It is launched from the Space Station with propulsion provided by a chemical engine and a delta velocity of 9 km/sec. The waverider performs an aero-gravity assist maneuver through the atmosphere of Venus to obtain a deflection angle and increase in delta velocity. Once the waverider and cargo ship have docked the astronauts will detach the landing cargo capsules and nuclear electric power plant and remotely pilot them to the surface. They will then descend to the surface aboard the NIMF shuttle. A dome base will be quickly constructed on the surface and the astronauts will conduct an exploratory mission for three to five months. They will return to Earth and dock with the Space Station using the waverider

Shaping and enforcing coordination spheres: probing the ability of tripodal ligands to favour trigonal prismatic geometry

The coordination chemistry of mono(2,2′-bipyrid-6-yl)bis(2-pyridyl)methanol (L1) and bis(2,2′-bipyrid-6-yl)mono(2-pyridyl)methanol (L2) are contrasted to tris(2,2′-bipyrid-6-yl)methanol (L3).L1andL2can produce octahedral complexes compared to the trigonal prismatic preference ofL3.</p

SkullGAN: Synthetic Skull CT Generation with Generative Adversarial Networks

Deep learning offers potential for various healthcare applications involving the human skull but requires extensive datasets of curated medical images. To overcome this challenge, we propose SkullGAN, a generative adversarial network (GAN), to create large datasets of synthetic skull CT slices, reducing reliance on real images and accelerating the integration of machine learning into healthcare. In our method, CT slices of 38 subjects were fed to SkullGAN, a neural network comprising over 200 million parameters. The synthetic skull images generated were evaluated based on three quantitative radiological features: skull density ratio (SDR), mean thickness, and mean intensity. They were further analyzed using t-distributed stochastic neighbor embedding (t-SNE) and by applying the SkullGAN discriminator as a classifier. The results showed that SkullGAN-generated images demonstrated similar key quantitative radiological features to real skulls. Further definitive analysis was undertaken by applying the discriminator of SkullGAN, where the SkullGAN discriminator classified 56.5% of a test set of real skull images and 55.9% of the SkullGAN-generated images as reals (the theoretical optimum being 50%), demonstrating that the SkullGAN-generated skull set is indistinguishable from the real skull set - within the limits of our nonlinear classifier. Therefore, SkullGAN makes it possible to generate large numbers of synthetic skull CT segments, necessary for training neural networks for medical applications involving the human skull. This mitigates challenges associated with preparing large, high-quality training datasets, such as access, capital, time, and the need for domain expertise.Comment: The first two authors contributed equall