Phase-coherent repetition rate multiplication of a mode-locked laser from 40 MHz to 1 GHz by injection locking

We have used injection locking to multiply the repetition rate of a passively mode-locked femtosecond fiber laser from 40 MHz to 1 GHz while preserving optical phase coherence between the master laser and the slave output. The system is implemented almost completely in fiber and incorporates gain and passive saturable absorption. The slave repetition rate is set to a rational harmonic of the master repetition rate, inducing pulse formation at the least common multiple of the master and slave repetition rates

Methods for Handling Unobserved Covariates in a Bayesian Update of a Cost-effectiveness Model

Health economic decision models often involve a wide-ranging and complicated synthesis of evidence from a number of sources, making design and implementation of such models resource-heavy. When new data become available and reassessment of treatment recommendations is warranted, it may be more efficient to perform a Bayesian update of an existing model than to construct a new model. If the existing model depends on many, possibly correlated, covariates, then an update may produce biased estimates of model parameters if some of these covariates are completely absent from the new data. Motivated by the need to update a cost-effectiveness analysis comparing diagnostic strategies for coronary heart disease, this study develops methods to overcome this obstacle by either introducing additional data or using results from previous studies. We outline a framework to handle unobserved covariates, and use our motivating example to illustrate both the flexibility of the proposed methods and some potential difficulties in applying them

Robustness of Image-Based Malware Classification Models Trained with Generative Adversarial Networks

As malware continues to evolve, deep learning models are increasingly used for malware detection and classification, including image based classification. However, adversarial attacks can be used to perturb images so as to evade detection by these models. This study investigates the effectiveness of training deep learning models with Generative Adversarial Network-generated data to improve their robustness against such attacks. Two image conversion methods, byte plot and space-filling curves, were used to represent the malware samples, and a ResNet-50 architecture was used to train models on the image datasets. The models were then tested against a projected gradient descent attack. It was found that without GAN generated data, the models’ prediction performance drastically decreased from 93-95% to 4.5% accuracy. However, the addition of adversarial images to the training data almost doubled the accuracy of the models. This study highlights the potential benefits of incorporating GAN-generated data in the training of deep learning models to improve their robustness against adversarial attacks

Rigidity and intermediate phases in glasses driven by speciation

The rigid to floppy transitions and the associated intermediate phase in glasses are studied in the case where the local structure is not fully determined from the macroscopic concentration. The approach uses size increasing cluster approximations and constraint counting algorithms. It is shown that the location and the width of the intermediate phase and the corresponding structural, mechanical and energetical properties of the network depend crucially on the way local structures are selected at a given concentration. The broadening of the intermediate phase is obtained for networks combining a large amount of flexible local structural units and a high rate of medium range order.Comment: 4 pages, 4 figure

Microplastics in the Antarctic marine system: An emerging area of research

It was thought that the Southern Ocean was relatively free of microplastic contamination; however, recent studies and citizen science projects in the Southern Ocean have reported microplastics in deep-sea sediments and surface waters. Here we reviewed available information on microplastics (including macroplastics as a source of microplastics) in the Southern Ocean. We estimated primary microplastic concentrations from personal care products and laundry, and identified potential sources and routes of transmission into the region. Estimates showed the levels of microplastic pollution released into the region from ships and scientific research stations were likely to be negligible at the scale of the Southern Ocean, but may be significant on a local scale. This was demonstrated by the detection of the first microplastics in shallow benthic sediments close to a number of research stations on King George Island. Furthermore, our predictions of primary microplastic concentrations from local sources were five orders of magnitude lower than levels reported in published sampling surveys (assuming an even dispersal at the ocean surface). Sea surface transfer from lower latitudes may contribute, at an as yet unknown level, to Southern Ocean plastic concentrations. Acknowledging the lack of data describing microplastic origins, concentrations, distribution and impacts in the Southern Ocean, we highlight the urgent need for research, and call for routine, standardised monitoring in the Antarctic marine system

Development of smallholder dairying in Eastern Africa with particular reference to Kenya

Large increases in demand for milk and dairy products projected for the next 25 years represent exciting market opportunities for smallholders in eastern Africa. With the exception of Kenya, traditional cattle production systems based on indigenous breeds dominate milk production in the region, yet they contribute relatively little to marketed production, mainly because of poor access to major urban markets. Kenya, which has over 85% of the dairy cattle population, dominates dairy production and marketing in the region. Its per capita milk availability is four to seven times higher than the other countries in the region. The widespread adoption of dairy cattle in Kenya was stimulated by several interacting factors: the conducive policy and institutional environments provided by successive Governments; the presence of significant dairy populations (owned by settler farmers); a sub-tropical geography suitable for dairy cattle; and, smallholder communities who kept cattle and who had milk as an important part of their diet. Today most of Kenya’s 3 million dairy cattle are kept by smallholders in crop-livestock systems in areas of high and medium cropping potential. Generally 1-2 dairy cows (mostly Holstein Friesian or Ayrshire) comprise 50% of the herd, the other half consisting of female calves and heifers. In the high potential areas feeding is mainly cut-and-carry with planted Napier grass (Pennisetum purpureum) and crop residues, especially from maize and bananas, supplemented by forage gathered from common properties around the farm. On average total daily milk output is 10 kg per farm, of which a quarter is for home consumption and the rest sold. In the late 1980s, sales were mainly through local dairy co-operative societies, with some to neighbours. However, following market liberalisation in 1992, marketing channels have diversified. It is estimated that approximately 80% of marketed milk is not processed or packaged, but instead is bought by the consumer in raw form. The factors driving the continued importance of the informal market are traditional preferences for fresh raw milk, which is boiled before consumption, and unwillingness to pay the costs of processing and packaging. Raw milk markets offer both higher prices to producers and lower prices to consumers. In Kenya, therefore, as elsewhere in the tropics, market-oriented smallholder dairy farms are concentrated close to urban consumption centres because the effects of the market over-ride many production factors. Less proximate production occurs only in those regions where there is an efficient market infrastructure. As infrastructure develops, markets become more efficient and urban consumers develop stronger preferences for pasteurised milk, the advantages of proximity will be reduced and production may well move away from intensive peri-urban systems and shift to more extensive systems (as the New Zealand dairy industry illustrates on a global scale). Until these infra-structural improvements occur, and because of the ready availability of cheap human capital (labour) and the relative expense of financial capital, smallholder dairy production and informal raw milk marketing are likely to predominate for the foreseeable future. Consequently it is anticipated that the industrialised model of dairy production, processing and marketing will remain a minor contributor in Kenya and elsewhere in the region