Liquid-gas phase transition in nuclear multifragmentation

The equation of state of nuclear matter suggests that at suitable beam energies the disassembling hot system formed in heavy ion collisions will pass through a liquid-gas coexistence region. Searching for the signatures of the phase transition has been a very important focal point of experimental endeavours in heavy ion collisions, in the last fifteen years. Simultaneously theoretical models have been developed to provide information about the equation of state and reaction mechanisms consistent with the experimental observables. This article is a review of this endeavour.Comment: 63 pages, 27 figures, submitted to Adv. Nucl. Phys. Some typos corrected, minor text change

Issues in the management of simple and complex meconium ileus

Various surgical methods are used to treat meconium ileus (MI), including resection with enterostomy (RES), primary anastomosis (RPA), and purse-string enterotomy with intra-operative lavage (PSI). The aim of this study is to discuss the surgical treatment of MI, based on our experience. Of the 41 MI patients treated at our institution between 1984 and 2007, 18 had simple MI and 23 had complex MI. These groups were analyzed according to treatment modality, concentrating on length of hospital stay, complications [peritonitis, septicemia, adhesive small bowel obstruction (ASBO), and malabsorption/diarrhea], need for additional surgical procedures, mortality. Of the 18 patients with simple MI, 7 (39%) were successfully treated with diluted Gastrografin® enema. The remaining 11 patients were treated surgically: two underwent RPA, of whom one died; five had RES, of whom one developed ASBO; four underwent PSI, of whom two developed peritonitis. In the complex MI group, 14 patients underwent RPA, with peritonitis occurring in three (one died); nine underwent RES, of whom two developed ASBO. In patients with simple MI, conservative treatment with diluted Gastrografin® enema is an effective initial treatment in our hands. In case of failure, RES is advisable. Patients with complex MI are candidates for RES. RPA and PSI seem to have higher complication rate

Privacy-Enhanced Machine Learning with Functional Encryption

Functional encryption is a generalization of public-key encryption in which possessing a secret functional key allows one to learn a function of what the ciphertext is encrypting. This paper introduces the first fully-fledged open source cryptographic libraries for functional encryption. It also presents how functional encryption can be used to build efficient privacy-enhanced machine learning models and it provides an implementation of three prediction services that can be applied on the encrypted data. Finally, the paper discusses the advantages and disadvantages of the alternative approach for building privacy-enhanced machine learning models by using homomorphic encryption

A genetic programming approach to development of clinical prediction models: A case study in symptomatic cardiovascular disease

BACKGROUND:Genetic programming (GP) is an evolutionary computing methodology capable of identifying complex, non-linear patterns in large data sets. Despite the potential advantages of GP over more typical, frequentist statistical approach methods, its applications to survival analyses are rare, at best. The aim of this study was to determine the utility of GP for the automatic development of clinical prediction models. METHODS:We compared GP against the commonly used Cox regression technique in terms of the development and performance of a cardiovascular risk score using data from the SMART study, a prospective cohort study of patients with symptomatic cardiovascular disease. The composite endpoint was cardiovascular death, non-fatal stroke, and myocardial infarction. A total of 3,873 patients aged 19-82 years were enrolled in the study 1996-2006. The cohort was split 70:30 into derivation and validation sets. The derivation set was used for development of both GP and Cox regression models. These models were then used to predict the discrete hazards at t = 1, 3, and 5 years. The predictive ability of both models was evaluated in terms of their risk discrimination and calibration using the validation set. RESULTS:The discrimination of both models was comparable. At time points t = 1, 3, and 5 years the C-index was 0.59, 0.69, 0.64 and 0.66, 0.70, 0.70 for the GP and Cox regression models respectively. At the same time points, the calibration of both models, which was assessed using calibration plots and the generalization of the Hosmer-Lemeshow test statistic, was also comparable, but with the Cox model being better calibrated to the validation data. CONCLUSION:Using empirical data, we demonstrated that a prediction model developed automatically by GP has predictive ability comparable to that of manually tuned Cox regression. The GP model was more complex, but it was developed in a fully automated way and comprised fewer covariates. Furthermore, it did not require the expertise normally needed for its derivation, thereby alleviating the knowledge elicitation bottleneck. Overall, GP demonstrated considerable potential as a method for the automated development of clinical prediction models for diagnostic and prognostic purposes