Modeling short-range ballistic missile defense and Israel's Iron Dome system

This paper develops a model of short-range ballistic missile defense and uses it to study the performance of Israel’s Iron Dome system. The deterministic base model allows for inaccurate missiles, unsuccessful interceptions, and civil defense. Model enhancements consider the trade-offs in attacking the interception system, the difficulties faced by militants in assembling large salvos, and the effects of imperfect missile classification by the defender. A stochastic model is also developed. Analysis shows that system performance can be highly sensitive to the missile salvo size, and that systems with higher interception rates are more “fragile” when overloaded. The model is calibrated using publically available data about Iron Dome’s use during Operation Pillar of Defense in November 2012. If the systems performed as claimed, they saved Israel an estimated 1778 casualties and $80 million in property damage, and thereby made preemptive strikes on Gaza about 8 times less valuable to Israel. Gaza militants could have inflicted far more damage by grouping their rockets into large salvos, but this may have been difficult given Israel’s suppression efforts. Counter-battery fire by the militants is unlikely to be worthwhile unless they can obtain much more accurate missiles.

A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970-2010

Mathematical models of mosquito-borne pathogen transmission originated in the early twentieth century to provide insights into how to most effectively combat malaria. The foundations of the Ross–Macdonald theory were established by 1970. Since then, there has been a growing interest in reducing the public health burden of mosquito-borne pathogens and an expanding use of models to guide their control. To assess how theory has changed to confront evolving public health challenges, we compiled a bibliography of 325 publications from 1970 through 2010 that included at least one mathematical model of mosquito-borne pathogen transmission and then used a 79-part questionnaire to classify each of 388 associated models according to its biological assumptions. As a composite measure to interpret the multidimensional results of our survey, we assigned a numerical value to each model that measured its similarity to 15 core assumptions of the Ross–Macdonald model. Although the analysis illustrated a growing acknowledgement of geographical, ecological and epidemiological complexities in modelling transmission, most models during the past 40 years closely resemble the Ross–Macdonald model. Modern theory would benefit from an expansion around the concepts of heterogeneous mosquito biting, poorly mixed mosquito-host encounters, spatial heterogeneity and temporal variation in the transmission process.

Problems with geoengineering schemes to combat climate change

The accelerated rate of increase in atmospheric CO2 concentration in recent years has revived the idea of stabilizing the global climate through geoengineering schemes. Majority of the proposed geoengineering schemes will attempt to reduce the amount of solar radiation absorbed by our planet. Climate modelling studies of these so called 'sunshade geoengineering schemes' show that global warming from increasing concentrations of CO2 can be mitigated by intentionally manipulating the amount of sunlight absorbed by the climate system. These studies also suggest that the residual changes could be large on regional scales, so that climate change may not be mitigated on a local basis. More recent modelling studies have shown that these schemes could lead to a slow-down in the global hydrological cycle. Other problems such as changes in the terrestrial carbon cycle and ocean acidification remain unsolved by sunshade geoengineering schemes. In this article, I review the proposed geoengineering schemes, results from climate models and discuss why geoengineering is not the best option to deal with climate change.

Stress and Resilience in Combat-Related PTSD: Integration of Psychological Theory and Biological Mechanisms

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder that has a major impact on the ability to function effectively in daily life. PTSD may develop as a response to exposure to an event or events perceived as potentially harmful or life-threatening. It has high prevalence rates in the community, especially among vulnerable groups such as military personnel or those in emergency services. Despite extensive research in this field, the underlying mechanisms of the disorder remain largely unknown. The identification of risk factors for PTSD has posed a particular challenge as there can be delays in onset of the disorder, and most people who are exposed to traumatic events will not meet diagnostic criteria for PTSD. With the advent of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM V), the classification for PTSD has changed from an anxiety disorder into the category of stress- and trauma-related disorders. This has the potential to refocus PTSD research on the nature of stress and the stress response relationship. This review focuses on some of the important findings from psychological and biological research based on early models of stress and resilience. Improving our understanding of PTSD by investigating both genetic and psychological risk and coping factors that influence stress response, as well as their interaction, may provide a basis for more effective and earlier intervention.

Generalized Partial Response Equalization and Data-Dependent Noise Predictive Signal Detection Over Media Models for TDMR

Two-dimensional magnetic recording (2-D TDMR) is an emerging technology that aims to achieve areal densities as high as 10 Tb/in(2) using sophisticated 2-D signal-processing algorithms. High areal densities are achieved by reducing the size of a bit to the order of the size of magnetic grains, resulting in severe 2-D intersymbol interference (ISI). Jitter noise due to irregular grain positions on the magnetic medium is more pronounced at these areal densities. Therefore, a viable read-channel architecture for TDMR requires 2-D signal-detection algorithms that can mitigate 2-D ISI and combat noise comprising jitter and electronic components. Partial response maximum likelihood (PRML) detection scheme allows controlled ISI as seen by the detector. With the controlled and reduced span of 2-D ISI, the PRML scheme overcomes practical difficulties such as Nyquist rate signaling required for full response 2-D equalization. As in the case of 1-D magnetic recording, jitter noise can be handled using a data-dependent noise-prediction (DDNP) filter bank within a 2-D signal-detection engine. The contributions of this paper are threefold: 1) we empirically study the jitter noise characteristics in TDMR as a function of grain density using a Voronoi-based granular media model; 2) we develop a 2-D DDNP algorithm to handle the media noise seen in TDMR; and 3) we also develop techniques to design 2-D separable and nonseparable targets for generalized partial response equalization for TDMR. This can be used along with a 2-D signal-detection algorithm. The DDNP algorithm is observed to give a 2.5 dB gain in SNR over uncoded data compared with the noise predictive maximum likelihood detection for the same choice of channel model parameters to achieve a channel bit density of 1.3 Tb/in(2) with media grain center-to-center distance of 10 nm. The DDNP algorithm is observed to give similar to 10% gain in areal density near 5 grains/bit. The proposed signal-processing framework can broadly scale to various TDMR realizations and areal density points.

The salvo combat model with area fire

This paper analyzes versions of the salvo model of missile combat where area fire is used by one or both sides in a battle. While these models share some properties with the area fire Lanchester model and the aimed fire salvo model, they also display some interesting differences, especially over the course of several salvos. Whereas the relative size of each force is important with aimed fire, with area fire it is the absolute size that matters. Similarly, while aimed fire exhibits square law behavior, area fire shows approximately linear behavior. When one side uses area and the other uses aimed fire, the model displays a mix of square and linear law behavior.

MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

New prophylactic and therapeutic treatments to combat pathogenic Enterohaemorrhagic Escherichia coli

Bacterial diarrhoeal diseases have significant influence on global human health, and are a leading cause of preventable death in the developing world. Enterohaemorrhagic Escherichia coli (EHEC), pathogenic strains of E. coli that carry potent toxins, have been associated with a high number of large-scale outbreaks caused by contaminated food and water sources. This pathotype produces diarrhoea and haemorrhagic colitis in infected humans, and in some patients leads to the development of haemolytic uremic syndrome (HUS), which can result in mortality and chronic kidney disease. A major obstacle to the treatment of EHEC infections is the increased risk of HUS development that is associated with antibiotic treatment, and rehydration and renal support are often the only options available. New treatments designed to prevent or clear E. coli infections and reduce symptoms of illness would therefore have large public health and economic impacts. The three main aims of this thesis were: to explore mouse models for pre-clinical evaluation in vivo of small compounds that inhibit a major EHEC colonisation factor, to assess the production and role of two proteins considered promising candidates for a broad-spectrum vaccine against pathogenic E. coli, and to investigate a novel compound that has recently been identified as a potential inhibitor of EHEC toxin production. As EHEC cannot be safely tested in humans due to the risk of HUS development, appropriate small animal models are required for in vivo testing of new drugs. A number of different mouse models have been developed to replicate different features of EHEC pathogenesis, several of which we investigated with a focus on colonisation mediated by the Type III Secretion System (T3SS), a needle-like structure that translocates bacterial proteins into host cells, resulting in a tight, intimate attachment between pathogen and host, aiding colonisation of the gastrointestinal tract. As E. coli models were found not to depend significantly on the T3SS for colonisation, the Citrobacter rodentium model, a natural mouse pathogen closely related to E. coli, was deemed the most suitable mouse model currently available for in vivo testing of T3SS-targeting compounds. Two bacterial proteins, EaeH (an outer membrane adhesin) and YghJ (a putative secreted lipoprotein), highly conserved surface-associated proteins recently identified as III protective antigens against E. coli infection of mice, were explored in order to determine their suitability as candidates for a human vaccine against pathogenic E. coli. We focused on the expression and function of these proteins in the EHEC O157:H7 EDL933 strain and the adherent-invasive E. coli (AIEC) LF82 strain. Although expression of EaeH by other E. coli pathotypes has recently been shown to be upregulated upon contact with host intestinal cells, no evidence of this upregulation could be demonstrated in our strains. Additionally, while YghJ was produced by the AIEC strain, it was not secreted by bacteria under conditions that other YghJ-expressing E. coli pathotypes do, despite the AIEC strain carrying all the genes required to encode the secretion system it is associated with. While our findings indicate that a vaccine that raises antibodies against EaeH and YghJ may have limited effect on the EHEC and AIEC strains we used, recent studies into these proteins in different E. coli pathogens have suggested they are still excellent candidates for a broadly effective vaccine against E. coli. Finally, we characterised a small lead compound, identified by high-throughput screening as a possible inhibitor of Shiga toxin expression. Shiga toxin production causes both the symptoms of illness and development of HUS, and thus reduction of toxin production, release, or binding to host receptors could therefore be an effective way to treat infections and decrease the risk of HUS. Inhibition of Shiga toxin production by this compound was confirmed, and was shown to be caused by an inhibitory effect on activation of the bacterial SOS response rather than on the Shiga toxin genes themselves. The bacterial target of this compound was identified as RecA, a major regulator of the SOS response, and we hypothesise that the compound binds covalently to its target, preventing oligomerisation of RecA into an activated filament. Altogether, the results presented here provide an improved understanding of these different approaches to combating EHEC infection, which will aid the development of safe and effective vaccines and anti-virulence treatments against EHEC.