Cost analysis of nondeterministic probabilistic programs

We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. Previous approaches for this problem could only handle nonnegative bounded costs. However, in many scenarios, such as queuing networks or analysis of cryptocurrency protocols, both positive and negative costs are necessary and the costs are unbounded as well. In this work, we present a sound and efficient approach to obtain polynomial bounds on the expected accumulated cost of nondeterministic probabilistic programs. Our approach can handle (a) general positive and negative costs with bounded updates in variables; and (b) nonnegative costs with general updates to variables. We show that several natural examples which could not be handled by previous approaches are captured in our framework. Moreover, our approach leads to an efficient polynomial-time algorithm, while no previous approach for cost analysis of probabilistic programs could guarantee polynomial runtime. Finally, we show the effectiveness of our approach using experimental results on a variety of programs for which we efficiently synthesize tight resource-usage bounds

Cost Analysis of Nondeterministic Probabilistic Programs

We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. Previous approaches for this problem could only handle nonnegative bounded costs. However, in many scenarios, such as queuing networks or analysis of cryptocurrency protocols, both positive and negative costs are necessary and the costs are unbounded as well. In this work, we present a sound and efficient approach to obtain polynomial bounds on the expected accumulated cost of nondeterministic probabilistic programs. Our approach can handle (a) general positive and negative costs with bounded updates in variables; and (b) nonnegative costs with general updates to variables. We show that several natural examples which could not be handled by previous approaches are captured in our framework. Moreover, our approach leads to an efficient polynomial-time algorithm, while no previous approach for cost analysis of probabilistic programs could guarantee polynomial runtime. Finally, we show the effectiveness of our approach by presenting experimental results on a variety of programs, motivated by real-world applications, for which we efficiently synthesize tight resource-usage bounds.Comment: A conference version will appear in the 40th ACM Conference on Programming Language Design and Implementation (PLDI 2019

Accurate detection of complex structural variations using single-molecule sequencing

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr ) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles ) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings

Higher-order syntax and saturation algorithms for hybrid logic

We present modal logic on the basis of the simply typed lambda calculus with a system of equational deduction. Combining first-order quantification and higher-order syntax, we can maintain modal reasoning in terms of classical logic by remarkably simple means. Such an approach has been broadly uninvestigated, even though it has notable advantages, especially in the case of Hybrid Logic. We develop a tableau-like semi-decision procedure and subsequently a decision procedure for an alternative characterization o

Postoperative Delirium in Patients with Oral Cancer: Is Intraoperative Fluid Administration a Neglected Risk Factor?

Squamous cell carcinoma (SCC) is a malignant tumor derived from squamous cells and can be found in different localizations. In the oral cavity especially, it represents the most common type of malignant tumor. First-line therapy for oral squamous cell carcinoma (OSCC) is surgery, including tumor resection, neck dissection, and maybe reconstruction. Although perioperative mortality is low, complications such as delirium are very common, and may have long-lasting consequences on the patient’s quality of life. This study examines if excessive fluid administration, among other parameters, is an aggravating factor for the development of postoperative delirium. A total of 198 patients were divided into groups concerning the reconstruction technique used: group A for primary wound closure or reconstruction with a local flap, and group B for microsurgical reconstruction. The patients with and without delirium in both groups were compared regarding intraoperative fluid administration, fluid balance, and other parameters, such as blood loss, duration of surgery and overall ventilation, alcohol consumption, and creatinine, albumin, natrium, and hematocrit levels. The logistic regression for group A shows that fluid intake (p = 0.02, OR = 5.27, 95% CI 1.27–21.8) and albumin levels (p = 0.036, OR = 0.22, CI 0.054–0.908) are independent predictors for the development of delirium. For group B, gender (p = 0.026, OR = 0.34, CI 0.133–0.879) with a protective effect for females, fluid intake (p = 0.003, OR = 3.975, CI 1.606–9.839), and duration of ventilation (p = 0.025, OR = 1.178, CI 1.021–1.359) are also independent predictors for delirium. An intake of more than 3000 mL for group A, and 4150 mL for group B, increases the risk of delirium by approximately five and four times, respectively. Fluid management should be considered carefully in patients with OSCC, in order to reduce the occurrence of postoperative delirium. Different factors may become significant for the development of delirium regarding different surgical procedures

Additional file 2: of Teaser: Individualized benchmarking and optimization of read mapping results for NGS data

Configuration file used to benchmark Bowtie2 and demonstrates the simplicity of benchmarking 34 parameters using Teaser. (TXT 442 bytes