Property Testing and Probability Distributions: New Techniques, New Models, and New Goals

In order to study the real world, scientists (and computer scientists) develop simplified models that attempt to capture the essential features of the observed system. Understanding the power and limitations of these models, when they apply or fail to fully capture the situation at hand, is therefore of uttermost importance. In this thesis, we investigate the role of some of these models in property testing of probability distributions (distribution testing), as well as in related areas. We introduce natural extensions of the standard model (which only allows access to independent draws from the underlying distribution), in order to circumvent some of its limitations or draw new insights about the problems they aim at capturing. Our results are organized in three main directions: (i) We provide systematic approaches to tackle distribution testing questions. Specifically, we provide two general algorithmic frameworks that apply to a wide range of properties, and yield efficient and near-optimal results for many of them. We complement these by introducing two methodologies to prove information-theoretic lower bounds in distribution testing, which enable us to derive hardness results in a clean and unified way. (ii) We introduce and investigate two new models of access to the unknown distributions, which both generalize the standard sampling model in different ways and allow testing algorithms to achieve significantly better efficiency. Our study of the power and limitations of algorithms in these models shows how these could lead to faster algorithms in practical situations, and yields a better understanding of the underlying bottlenecks in the standard sampling setting. (iii) We then leave the field of distribution testing to explore areas adjacent to property testing. We define a new algorithmic primitive of sampling correction, which in some sense lies in between distribution learning and testing and aims to capture settings where data originates from imperfect or noisy sources. Our work sets out to model these situations in a rigorous and abstracted way, in order to enable the development of systematic methods to address these issues

Statistical modeling of HIV, tuberculosis, and Hepatitis B transmission in Ghana

Most mortality studies usually attribute death to single disease, while various other diseases could also act in the same individual or a population at large. Few works have been done by considering HIV, Tuberculosis (TB), and Hepatitis B (HB) as jointly acting in a population in spite of their high rate of infections in Ghana. This study applied competing risk methods on these three diseases by assuming they were the major risks in the study population. Among all opportunistic infections that could also act within HIV-infected individuals, TB has been asserted to be the most predominant. Other studies have also shown cases of HIV and Hepatitis B coinfections. The validity of these comorbidity assertions was statistically determined by exploring the conditional dependencies existing among HIV, TB, and HB through Bayesian networks or directed graphical model. Through Classification tree, sex and age group of individuals were found as significant demographic predictors that influence the prevalence of HIV and TB. Females were more likely to contract HIV, whereas males were prone to contracting TB

Malaria Infection Increases Attractiveness of Humans to Mosquitoes

Do malaria parasites enhance the attractiveness of humans to the parasite's vector? As such manipulation would have important implications for the epidemiology of the disease, the question has been debated for many years. To investigate the issue in a semi-natural situation, we assayed the attractiveness of 12 groups of three western Kenyan children to the main African malaria vector, the mosquito Anopheles gambiae. In each group, one child was uninfected, one was naturally infected with the asexual (non-infective) stage of Plasmodium falciparum, and one harboured the parasite's gametocytes (the stage transmissible to mosquitoes). The children harbouring gametocytes attracted about twice as many mosquitoes as the two other classes of children. In a second assay of the same children, when the parasites had been cleared with anti-malarial treatment, the attractiveness was similar between the three classes of children. In particular, the children who had previously harboured gametocytes, but had now cleared the parasite, were not more attractive than other children. This ruled out the possibility of a bias due to differential intrinsic attractiveness of the children to mosquitoes and strongly suggests that gametocytes increase the attractiveness of the children

Mesalamine-Induced Myocarditis

Nowadays mesalamine is a common treatment for Crohn's disease and hypersensitive reactions to this product have been reported. Yet there is limited information concerning mesalamine-induced myocarditis and its mechanism is not known. We described a case of mesalamine-induced myocarditis in Crohn's disease of the colon

Markov chain modeling of HIV, tuberculosis, and Hepatitis B transmission in Ghana

Several mathematical and standard epidemiological models have been proposed in studying infectious disease dynamics. These models help to understand the spread of disease infections. However, most of these models are not able to estimate other relevant disease metrics such as probability of first infection and recovery as well as the expected time to infection and recovery for both susceptible and infected individuals. That is, most of the standard epidemiological models used in estimating transition probabilities (TPs) are not able to generalize the transition estimates of disease outcomes at discrete time steps for future predictions. This paper seeks to address the aforementioned problems through a discrete-time Markov chain model. Secondary datasets from cohort studies were collected on HIV, tuberculosis (TB), and hepatitis B (HB) cases from a regional hospital in Ghana. The Markov chain model revealed that hepatitis B was more infectious over time than tuberculosis and HIV even though the probability of first infection of these diseases was relatively low within the study population. However, individuals infected with HIV had comparatively lower life expectancies than those infected with tuberculosis and hepatitis B. Discrete-time Markov chain technique is recommended as viable for modeling disease dynamics in Ghana

Climate Action In Megacities 3.0

"Climate Action in Megacities 3.0" (CAM 3.0) presents major new insights into the current status, latest trends and future potential for climate action at the city level. Documenting the volume of action being taken by cities, CAM 3.0 marks a new chapter in the C40-Arup research partnership, supported by the City Leadership Initiative at University College London. It provides compelling evidence about cities' commitment to tackling climate change and their critical role in the fight to achieve global emissions reductions

Developing a Prototype for a Microcontroller-Based Coin-Counting Machine

Coins have become a significant part of today\u27s economy and are continuously being distributed, along with banknotes, for daily transactions in the most conventional methods. The modernized circulating currency method relies heavily on coin sorting and counting machines to prevent inconsistencies when handling and calculating coins. While the innovation reduces the need for human resources and revolutionizes the way establishments work with large sums of coins, accuracy in differentiating coins becomes an issue in some existing designs. The prototype uses light occlusion and measures the energy of the coin impact to identify the denomination. The prototype shows promise in being able to identify four Philippine coin denominations

Plasmodium falciparum Produce Lower Infection Intensities in Local versus Foreign Anopheles gambiae Populations

Both Plasmodium falciparum and Anopheles gambiae show great diversity in Africa, in their own genetic makeup and population dynamics. The genetics of the individual mosquito and parasite are known to play a role in determining the outcome of infection in the vector, but whether differences in infection phenotype vary between populations remains to be investigated. Here we established two A. gambiae s.s. M molecular form colonies from Cameroon and Burkina Faso, representing a local and a foreign population for each of the geographical sites. Experimental infections of both colonies were conducted in Cameroon and Burkina Faso using local wild P. falciparum, giving a sympatric and allopatric vector-parasite combination in each site. Infection phenotype was determined in terms of oocyst prevalence and intensity for at least nine infections for each vector-parasite combination. Sympatric infections were found to produce 25% fewer oocysts per midgut than allopatric infections, while prevalence was not affected by local/foreign interactions. The reduction in oocyst numbers in sympatric couples may be the result of evolutionary processes where the mosquito populations have locally adapted to their parasite populations. Future research on vector-parasite interactions must take into account the geographic scale of adaptation revealed here by conducting experiments in natural sympatric populations to give epidemiologically meaningful results