Extensive categories, commutative semirings and Galois theory

We describe the Galois theory of commutative semirings as a Boolean Galois theory in the sense of Carboni and Janelidze. Such a Galois structure then naturally suggests an extension to commutative semirings of the classical theory of quadratic equations over commutative rings. We show, however, that our proposed generalization is impossible for connected commutative semirings which are not rings, leading to the conclusion that for the theory of quadratic equations, “minus is needed”. Finally, by considering semirings B which have no non-trivial additive inverses and no non-trivial zero divisors, we present an example of a normal extension of commutative semirings which has an underlying B-semimodule structure isomorphic to B×B

Stochastic volatility models: calibration, pricing and hedging

Stochastic volatility models have long provided a popular alternative to the Black- Scholes-Merton framework. They provide, in a self-consistent way, an explanation for the presence of implied volatility smiles/skews seen in practice. Incorporating jumps into the stochastic volatility framework gives further freedom to nancial mathematicians to t both the short and long end of the implied volatility surface. We present three stochastic volatility models here - the Heston model, the Bates model and the SVJJ model. The latter two models incorporate jumps in the stock price process and, in the case of the SVJJ model, jumps in the volatility process. We analyse the e ects that the di erent model parameters have on the implied volatility surface as well as the returns distribution. We also present pricing techniques for determining vanilla European option prices under the dynamics of the three models. These include the fast Fourier transform (FFT) framework of Carr and Madan as well as two Monte Carlo pricing methods. Making use of the FFT pricing framework, we present calibration techniques for tting the models to option data. Speci cally, we examine the use of the genetic algorithm, adaptive simulated annealing and a MATLAB optimisation routine for tting the models to option data via a leastsquares calibration routine. We favour the genetic algorithm and make use of it in tting the three models to ALSI and S&P 500 option data. The last section of the dissertation provides hedging techniques for the models via the calculation of option price sensitivities. We nd that a delta, vega and gamma hedging scheme provides the best results for the Heston model. The inclusion of jumps in the stock price and volatility processes, however, worsens the performance of this scheme. MATLAB code for some of the routines implemented is provided in the appendix

The molecular basis of childhood nephrotic syndrome.

Childhood nephrotic syndrome results from massive leakage of protein into the urine, a low plasma albumin and oedema. Disease may be kidney-specific, occur as part of a malformation syndrome, or may complicate systemic diseases such as diabetes mellitus. Despite the apparent heterogeneity, the underlying defect is loss of the normal permselective characteristics of the glomerular filtration barrier (GFB). Clues for a molecular basis came from observation of occasional autosomal dominant or recessive inheritance, and the detection of WT1 mutations in Denys Drash syndrome (DDS), a triad of intersex, nephrotic syndrome and Wilms' tumour (Pelletier et al, 1991). The role of three glomerular genes WTl, NPHS1 and NPHS2 in the pathogenesis of glomerular protein leak was investigated. WTl mutations were not detected in non- syndromic diffuse mesangial sclerosis (DMS) and focal segmental glomerulosclerosis (FSGS), despite their association with DDS. However, subsequent analysis established that WTl mutations cause Frasier syndrome, a triad of FSGS, intersex and gonadoblastoma, by reversing the normal +(KTS)/-(KTS) WTl isoform ratio. Unfortunately, yeast 2-hybrid screens failed to ascertain any WTl protein binding partners with clear roles in glomerular function, and through which the effects of mutations might be mediated. A wide range of NPHS1 mutations was detected in Finnish type congenital nephrotic syndrome (CNF) in non-Finns, and a novel mild CNF phenotype described. NPHS2 mutations affected some CNF cases, and an overlap in the NPHS1/NPHS2 mutation spectrum was confirmed by the discovery of a unique di-genic inheritance of mutations. This modified the phenotype from CNF to congenital FSGS, providing the first evidence for a functional inter-relationship between these genes. Finally, disrupted protein-DNA binding to an area of the NPHS1 promoter containing a G->C base substitution was identified, suggesting the location of a transcription factor binding site and underscoring the importance of appropriate transcriptional control of NPHS1 for correct gene function

Investigating urban form, and walkability measures in the new developments: the case study of Garnizon in Gdansk

Sustainable transport choices are gaining much attention as they may support the global shift towards reducing the carbon footprint and developing more energy-efficient cities. The relation between urban form and sus- tainable transport has been discussed by academics and practitioners and there is a consensus that specific pa- rameters of urban form can encourage walking and discourage car use. Following global recommendations on sustainable development, countries take steps towards strengthening pedestrian accessibility by implementing spatial characteristics of walkable neighbourhoods, but also by mobility and urban design strategies. This issue, however, is not properly recognised in countries with short experience in sustainable urban development, such as former socialist countries. In Poland no studies on walkability-related parameters of urban form have been carried out, hence the knowledge in this field is limited. This paper aims to address this gap by providing evi- dence of a newly built urban district located in Gdansk, Poland. We present the Polish case with three examples of new urban districts from Western Europe, that are designed as sustainable and walkable environments. The methodology is based on the descriptive case study. It includes characteristics of design parameters namely the components of the “walkability index” as well as mobility solutions and urban design guidelines. The results show the current position of Garnizon development in relation to the Western European cases with regard to the existing post-communist legacy and allow for indicating differences and possible shortcomings. Additionally, the study results can be discussed in the context of improving the quality of the housing environment in Poland through pedestrian-oriented development strategiesPeer ReviewedPostprint (published version

Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market

Reliable estimates of volatility and correlation are fundamental in economics and finance for understanding the impact of macroeconomics events on the market and guiding future investments and policies. Dependence across financial returns is likely to be subject to sudden structural changes, especially in correspondence with major global events, such as the COVID-19 pandemic. In this work, we are interested in capturing abrupt changes over time in the dependence across US industry stock portfolios, over a time horizon that covers the COVID-19 pandemic. The selected stocks give a comprehensive picture of the US stock market. To this end, we develop a Bayesian multivariate stochastic volatility model based on a time-varying sequence of graphs capturing the evolution of the dependence structure. The model builds on the Gaussian graphical models and the random change points literature. In particular, we treat the number, the position of change points, and the graphs as object of posterior inference, allowing for sparsity in graph recovery and change point detection. The high dimension of the parameter space poses complex computational challenges. However, the model admits a hidden Markov model formulation. This leads to the development of an efficient computational strategy, based on a combination of sequential Monte-Carlo and Markov chain Monte-Carlo techniques. Model and computational development are widely applicable, beyond the scope of the application of interest in this work

Response to First Course of Intensified Immunosuppression in Genetically-Stratified Steroid Resistant Nephrotic Syndrome

BACKGROUND AND OBJECTIVES: Intensified immunosuppression in steroid-resistant nephrotic syndrome is broadly applied, with disparate outcomes. This review of patients from the United Kingdom National Study of Nephrotic Syndrome cohort aimed to improve disease stratification by determining, in comprehensively genetically screened patients with steroid-resistant nephrotic syndrome, if there is an association between response to initial intensified immunosuppression and disease progression and/or post-transplant recurrence. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Pediatric patients with steroid-resistant nephrotic syndrome were recruited via the UK National Registry of Rare Kidney Diseases. All patients were whole-genome sequenced, whole-exome sequenced, or steroid-resistant nephrotic syndrome gene-panel sequenced. Complete response or partial response within 6 months of starting intensified immunosuppression was ascertained using laboratory data. Response to intensified immunosuppression and outcomes were analyzed according to genetic testing results, pattern of steroid resistance, and first biopsy findings. RESULTS: Of 271 patients, 178 (92 males, median onset age 4.7 years) received intensified immunosuppression with response available. A total of 4% of patients with monogenic disease showed complete response, compared with 25% of genetic-testing-negative patients (P=0.02). None of the former recurred post-transplantation. In genetic-testing-negative patients, 97% with complete response to first intensified immunosuppression did not progress, whereas 44% of nonresponders developed kidney failure with 73% recurrence post-transplant. Secondary steroid resistance had a higher complete response rate than primary/presumed resistance (43% versus 23%; P=0.001). The highest complete response rate in secondary steroid resistance was to rituximab (64%). Biopsy results showed no correlation with intensified immunosuppression response or outcome. CONCLUSIONS: Patients with monogenic steroid-resistant nephrotic syndrome had a poor therapeutic response and no post-transplant recurrence. In genetic-testing-negative patients, there was an association between response to first intensified immunosuppression and long-term outcome. Patients with complete response rarely progressed to kidney failure, whereas nonresponders had poor kidney survival and a high post-transplant recurrence rate. Patients with secondary steroid resistance were more likely to respond, particularly to rituximab

<i>TBC1D8B </i>Loss-of-Function Mutations Lead to X-Linked Nephrotic Syndrome via Defective Trafficking Pathways

International audienceSteroid-resistant nephrotic syndrome (SRNS) is characterized by high-range proteinuria and most often focal and segmental glomerulosclerosis (FSGS). Identification of mutations in genes causing SRNS has improved our understanding of disease mechanisms and highlighted defects in the podocyte, a highly specialized glomerular epithelial cell, as major factors in disease pathogenesis. By exome sequencing, we identified missense mutations in TBC1D8B in two families with an X-linked early-onset SRNS with FSGS. TBC1D8B is an uncharacterized Rab-GTPase-activating protein likely involved in endocytic and recycling pathways. Immunofluorescence studies revealed TBC1D8B presence in human glomeruli, and affected individual podocytes displayed architectural changes associated with migration defects commonly found in FSGS. In zebrafish we demonstrated that both knockdown and knockout of the unique TBC1D8B ortholog-induced proteinuria and that this phenotype was rescued by human TBC1D8B mRNA injection, but not by either of the two mutated mRNAs. We also showed an interaction between TBC1D8B and Rab11b, a key protein in vesicular recycling in cells. Interestingly, both internalization and recycling processes were dramatically decreased in affected individuals' podocytes and fibroblasts, confirming the crucial role of TBC1D8B in the cellular recycling processes, probably as a Rab11b GTPase-activating protein. Altogether, these results confirmed that pathogenic variations in TBC1D8B are involved in X-linked podocytopathy and points to alterations in recycling processes as a mechanism of SRNS

A Knowledge Brokering Framework for Integrated Landscape Management

Sustainable land management is at the heart of some of the most intractable challenges facing humanity in the 21st century. It is critical for tackling biodiversity loss, land degradation, climate change and the decline of ecosystem services. It underpins food production, livelihoods, dietary health, social equity, climate change adaptation, and many other outcomes. However, interdependencies, trade-offs, time lags, and non-linear responses make it difficult to predict the combined effects of land management decisions. Policy decisions also have to be made in the context of conflicting interests, values and power dynamics of those living on the land and those affected by the consequences of land use decisions. This makes designing and coordinating effective land management policies and programmes highly challenging. The difficulty is exacerbated by the scarcity of reliable data on the impacts of land management on the environment and livelihoods. This poses a challenge for policymakers and practitioners in governments, development banks, non-governmental organisations, and other institutions. It also sets demands for researchers, who are under ever increasing pressure from funders to demonstrate uptake and impact of their work. Relatively few research methods exist that can address such questions in a holistic way. Decision makers and researchers need to work together to help untangle, contextualise and interpret fragmented evidence through systems approaches to make decisions in spite of uncertainty. Individuals and institutions acting as knowledge brokers can support these interactions by facilitating the co-creation and use of scientific and other knowledge. Given the patchy nature of data and evidence, particularly in developing countries, it is important to draw on the full range of available models, tools and evidence. In this paper we review the use of evidence to inform multiple-objective integrated landscape management policies and programmes, focusing on how to simultaneously achieve different sustainable development objectives in diverse landscapes. We set out key success factors for evidence-based decision-making, which are summarised into 10 key principles for integrated landscape management knowledge brokering in integrated landscape management and 12 key skills for knowledge brokers. We finally propose a decision-support framework to organise evidence that can be used to tackle different types of land management policy decision