Optimal operations and resilient investments in steam networks

Steam is a key energy vector for industrial sites, most commonly used for process heating and cooling, cogeneration of heat and mechanical power as a motive fluid or for stripping. Steam networks are used to carry steam from producers to consumers and between pressure levels through letdowns and steam turbines. The steam producers (boilers, heat and power cogeneration units, heat exchangers, chemical reactors) should be sized to supply the consumers at nominal operating conditions as well as peak demand. First, this paper proposes an Mixed Integer Linear Programing formulation to optimize the operations of steam networks in normal operating conditions and exceptional demand (when operating reserves fall to zero), through the introduction of load shedding. Optimization of investments based on operational and investment costs are included in the formulation. Though rare, boiler failures can have a heavy impact on steam network operations and costs, leading to undercapacity and unit shutdowns. A method is therefore proposed to simulate steam network operations when facing boiler failures. Key performance indicators are introduced to quantify the network’s resilience. The proposed methods are applied and demonstrated in an industrial case study using industrial data. The results indicate the importance of oversizing key steam producing equipments and the value of industrial symbiosis to increase industrial site resilience

Resilient decision making in steam network investments

Steam is a key energy vector for industrial sites, used for process heating, direct injection and stripping, tracing and cogeneration of mechanical power. Steam networks transport steam from producers to consumers and across different pressure levels. The steam production equipments (boilers, cogeneration units and heat exchangers) should be dimensioned to always supply key consumers as well as to deal with extreme demand caused by exceptional events such as unit startups or extreme weather. An important issue to be dealt with is that of unexpected boiler shutdowns, which can take significant amounts of time to bring back online. In cases where demand surpasses the available production of steam, load shedding is necessary in order to keep the network operable. A penalty cost can be associated to load shedding. A well dimensioned steam network is one which is resilient to such events, being able to overcome extreme demand and unexpected boiler shutdowns at minimum cost. This paper proposes a methodology for evaluating the operability of a steam network when facing unexpected boiler shutdowns. A Monte-Carlo simulation is carried out on a multi-period steam network problem, randomly shutting down boilers according to their failure properties (probability of failure and duration of failure). The aim of this method is to evaluate how resilient a steam network is to boiler shutdowns. The Monte-Carlo simulation is applied to a steam network model built using a Mixed Integer Linear Programming (MILP) formulation, whose objective function is to minimise the operational costs of the steam network and therefore also to minimise the penalty costs associated to load shedding. A case study based on anonymised industrial data is used to demonstrate the method. Two investment propositions are evaluated and compared using the proposed method

Paraneoplastic pemphigus associated with post-transplant lymphoproliferative disorder after small bowel transplantation

Background PNP is a malignancy-associated autoimmune mucocutaneous syndrome due to autoantibodies against plakins, desmogleins, and other components of the epidermis and basement membrane of epithelial tissues. PNP-causing malignancies comprise mainly lymphoproliferative and hematologic neoplasms. PNP is extremely rare, especially in children. Methods Here, we present the first case of a child who developed PNP on a PTLD after small bowel transplantation because of a severe genetic protein-losing enteropathy. Results The patient in this case report had a severe stomatitis, striate palmoplantar keratoderma, and lichenoid skin lesions. In addition, she had marked esophageal involvement. She had lung pathology due to recurrent pulmonary infections and ventilator injury. Although we found no evidence of BO, she died from severe pneumonia and respiratory failure at the age of 12 years. Conclusion It is exceptional that, despite effective treatment of the PTLD, the girl survived 5 years after her diagnosis of PNP. We hypothesize that the girl survived relatively long after the PNP diagnosis due to strong T-cell suppressive treatments for her small bowel transplantation

Self-reported data: a major tool to assess compliance with anti-malarial combination therapy among children in Senegal

Background: Although there are many methods available for measuring compliance, there is no formal gold standard. Different techniques used to measure compliance were compared among children treated by the anti-malarial amodiaquine/sulphadoxine-pyrimethamine (AQ/SP) combination therapy, in use in Senegal between 2004 and 2006. Methods: The study was carried out in 2004, in five health centres located in the Thies region (Senegal). Children who had AQ/SP prescribed for three and one day respectively at the health centre were recruited. The day following the theoretical last intake of AQ, venous blood, and urine samples were collected for anti-malarial drugs dosage. Caregivers and children above five years were interviewed concerning children's drug intake. Results: Among the children, 64.7% adhered to 80% of the prescribed dose and only 37.7% were strict full adherent to the prescription. There was 72.7% agreement between self-reported data and blood drug dosage for amodiaquine treatment. Concerning SP, results found that blood dosages were 91.4% concordant with urine tests and 90% with self-reported data based on questionnaires. Conclusion: Self-reported data could provide useful quantitative information on drug intake and administration. Under strict methodological conditions this method, easy to implement, can be used to describe patients' behaviors and their use of new anti-malarial treatment. Self-reported data is a major tool for assessing compliance in resource poor countries. Blood and urine drug dosages provide qualitative results that confirm any drug intake. Urine assays for SP could be useful to obtain public health data, for example on chemoprophylaxis among pregnant women

The prevalence of antibodies against the HLA-DRB3 protein in kidney transplantation and the correlation with HLA expression

Human leukocyte antigen (HLA)-DRB3 is a functional HLA class II gene, which has a limited allele diversity in the human population. Furthermore, the HLA-DRB3 gene is only present in a subset of individuals. Therefore, in organ transplantation, this HLA molecule is frequently mismatched between patient and graft donor and thus antibodies against this mismatched HLA molecule can develop. In this study, we aimed to evaluate the prevalence and reactivity of these antibodies and aimed to identify factors that underlie antibody formation against HLA-DRB3. We showed in our patient cohort that HLA-DRB3 antibodies are identified in about 7% of all patients that were screened with solid phase assays. In these assays, we observed multiple antibody reactivity patterns indicating that HLA-DRB3 harbours multiple epitopes. In those cases, where we succeeded at tracing back the induction of these antibodies to the molecular HLA typing of the immunogenic event, we noticed a different frequency of HLA-DRB1 allele groups in the donors as compared to a control group. To a certain extent this distribution (e.g. HLA-DRB1* 11 individuals) could be linked to an altered expression level. However, it also appears that different HLA-DRB3 alleles (e.g. HLA-DRB3* 01 group) vary in their immunogenicity without having an expression difference. In conclusion, our study provides information on the immunogenicity and reactivity patterns of antibodies against HLA-DRB3 in kidney transplantation, and it points towards the possibility of HLA expression as a factor underlying antibody formation

Energy Flow in the Hadronic Final State of Diffractive and Non-Diffractive Deep-Inelastic Scattering at HERA

An investigation of the hadronic final state in diffractive and non--diffractive deep--inelastic electron--proton scattering at HERA is presented, where diffractive data are selected experimentally by demanding a large gap in pseudo --rapidity around the proton remnant direction. The transverse energy flow in the hadronic final state is evaluated using a set of estimators which quantify topological properties. Using available Monte Carlo QCD calculations, it is demonstrated that the final state in diffractive DIS exhibits the features expected if the interaction is interpreted as the scattering of an electron off a current quark with associated effects of perturbative QCD. A model in which deep--inelastic diffraction is taken to be the exchange of a pomeron with partonic structure is found to reproduce the measurements well. Models for deep--inelastic $ep$ scattering, in which a sizeable diffractive contribution is present because of non--perturbative effects in the production of the hadronic final state, reproduce the general tendencies of the data but in all give a worse description.Comment: 22 pages, latex, 6 Figures appended as uuencoded fil